Try NVIDIA NIM APIs

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Model Overview\n\n### Description:\n\nKosmos-2 model is a groundbreaking multimodal large language model (MLLM).\nKosmos-2 is designed to ground text to the visual world,\nenabling it to understand and reason about visual elements in images.\n\n### Terms of use\n\nBy using this model, you are agreeing to the terms and conditions of the\n[license](https://github.com/microsoft/unilm/blob/master/LICENSE),\nacceptable use policy and Microsoft Research privacy policy.\n\n### References(s):\n\n* [KOSMOS-2 paper](https://arxiv.org/pdf/2306.14824.pdf)\n\n### Model Architecture:\n\n**Architecture Type:** Transformer \u003cbr\u003e\n**Network Architecture:** GPT + CLIP \u003cbr\u003e\n\n### Input:\n\n**Input Format:** Red, Green, Blue (RGB) Image + Text \u003cbr\u003e\n**Input Parameters:** Temperature, TopP \u003cbr\u003e\n**Other Properties Related to Input:** None \u003cbr\u003e\n\n### Output: \u003cbr\u003e\n\n**Output Format:** Text \u003cbr\u003e\n**Output Parameters:** Max output tokens, Bounding boxes \u003cbr\u003e\n**Other Properties Related to Output:** None \u003cbr\u003e\n\n### Supported Operating System(s):\n\nLinux\n\n## Inference:\n\n**Engine:** [Triton](https://developer.nvidia.com/triton-inference-server) \u003cbr\u003e\n**Test Hardware:** Other \u003cbr\u003e\n24:[\"$\",\"$L35\",null,{\"name\":\"microsoft-kosmos-2\",\"requestStatus\":{\"statusCode\":\"SUCCESS\",\"requestId\":\"e5ce328c-206b-4df2-af73-0fc2beb534ff\"},\"artifact\":{\"orgName\":\"qc69jvmznzxy\",\"labels\":[\"Image Understanding\",\"Multimodal\",\"Visual Question Answering\",\"computer vision\",\"cv\",\"image\",\"Image-to-Text\",\"video\",\"vlm\"],\"logo\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/microsoft-kosmos-2.jpg\",\"shortDescription\":\"Groundbreaking multimodal model designed to understand and reason about visual elements in 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It can perform a wide range of tasks,\nincluding image understanding, text generation, and code generation.\nArchitecturally, Fuyu is a vanilla decoder-only transformer - there is no image encoder.\nImage patches are instead linearly projected into the first layer of the transformer, bypassing the embedding lookup.\nThe transformer decoder is simply treated like an image transformer (albeit with no pooling and causal attention).\n\n### Terms of use\n\nBy accessing this model, you are agreeing to the Fuyu-8b terms and conditions of the [CC BY-NC license](https://creativecommons.org/licenses/by-nc/4.0/deed.en).\n\n### Third-Party Community Consideration:\n\nThis model is not owned or developed by NVIDIA. This model has been developed and built to a third-party’s requirements for this application and use case; see [Fuyu's Hugging Face Model Card](https://huggingface.co/adept/fuyu-8b).\n\n### References(s):\n\n* [Fuyu-8B Blog Post](https://www.adept.ai/blog/fuyu-8b) by adept.ai \u003cbr\u003e\n* [Fuyu-8B Model Card](https://huggingface.co/adept/fuyu-8b) on Hugging Face \u003cbr\u003e\n\n### Model Architecture:\n\n**Architecture Type:** Transformer \u003cbr\u003e\n**Network Architecture:** Fuyu-8b \u003cbr\u003e\n**Model Version:** N/A \u003cbr\u003e\n\n### Input:\n\n**Input Format:** Red, Green, Blue (RGB) Image + Text \u003cbr\u003e\n**Input Parameters:** None \u003cbr\u003e\n\n### Output:\n\n**Output Format:** Text \u003cbr\u003e\n**Output Parameters:** None \u003cbr\u003e\n\n### Software Integration:\n\n**Supported Hardware Platform(s):** Hopper, Ampere/Turing \u003cbr\u003e\n**Supported Operating System(s):** Linux \u003cbr\u003e\n\n## Inference:\n\n**Engine:** [Triton](https://developer.nvidia.com/triton-inference-server) \u003cbr\u003e\n**Test Hardware:** Other \u003cbr\u003e\n25:[\"$\",\"$L35\",null,{\"name\":\""])</script><script>self.__next_f.push([1,"fuyu-8b\",\"requestStatus\":{\"statusCode\":\"SUCCESS\",\"requestId\":\"8facc793-bfb2-4237-a43d-95ac6e6c8f83\"},\"artifact\":{\"orgName\":\"qc69jvmznzxy\",\"labels\":[\"Image Understanding\",\"Language Generation\",\"Multimodal\",\"computer vision\",\"cv\",\"image\",\"Image-to-Text\",\"video\",\"vlm\"],\"logo\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/fuyu-8b.jpg\",\"shortDescription\":\"Multi-modal model for a wide range of tasks, including image understanding and language generation.\",\"isReadOnly\":true,\"description\":\"$37\",\"canGuestDownload\":true,\"isPublic\":true,\"createdDate\":\"2024-03-15T05:06:34.141Z\",\"publisher\":\"adept\",\"displayName\":\"fuyu-8b\",\"name\":\"fuyu-8b\",\"updatedDate\":\"2024-08-26T16:47:11.225Z\",\"attributes\":[{\"key\":\"PREVIEW\",\"value\":\"true\"}],\"artifactType\":\"ENDPOINT\"}}]\n38:T836,"])</script><script>self.__next_f.push([1,"Field | Response\n:----------------------------------------------------------------------------------------------------------------------------------|:-----------------------------------------------\nGeneratable or reverse engineerable personally-identifiable information (PII)? | None\nProtected class data used to create this model? | None\nWas consent obtained for any PII used? | Not Applicable\nHow often is dataset reviewed? | Before Every Release\nIs a mechanism in place to honor data subject right of access or deletion of personal data? | Not Applicable\nIf PII collected for the development of the model, was it collected directly by NVIDIA? | Not Applicable\nIf PII collected for the development of the model by NVIDIA, do you maintain or have access to disclosures made to data subjects? | Not Applicable\nIf PII collected for the development of this AI model, was it minimized to only what was required? | Not Applicable\nIs data in dataset traceable? | Yes\nIs there provenance for all datasets used in training? | Yes\nDoes data labeling (annotation, metadata) comply with privacy laws? | Yes\nIs data compliant with data subject requests for data correction or removal, if such a request was made? | No, not possible with externally-sourced data."])</script><script>self.__next_f.push([1,"39:Te39,"])</script><script>self.__next_f.push([1,"## Model Overview\n\n### Description:\n\nNeVA is NVIDIA's version of the LLaVA model where the open source LLaMA model is replaced with a GPT model trained by NVIDIA.\nAt a high level the image is encoded using a frozen hugging face CLIP model and projected to the text embedding dimensions. This is then concatenated with the embeddings of the prompt and passed in through the language model. Training happens in two stages:\n* Pretraining: Here the language model is frozen and only the projection layer (that maps the image encoding to the embedding space) is trained. Here, image-caption pairs are used to pretrain the model.\n* Finetuning: Here the language model is also trained along with the projection layer. To finetune the model synthetic instruction data generated using GPT4 is used.\n\n### References(s):\n\n* [Visual Instruction Tuning Paper](https://arxiv.org/pdf/2304.08485.pdf) \u003cbr\u003e\n* [LLaVA: Large Language and Vision Assistant GitHub Page](https://llava-vl.github.io) \u003cbr\u003e\n* [Codebase](https://github.com/haotian-liu/LLaVA) \u003cbr\u003e\n* [Demo](https://llava.hliu.cc)\u003cbr\u003e\n\n### Model Architecture:\n\n**Architecture Type:** Transformer \u003cbr\u003e\n**Network Architecture:** GPT + CLIP \u003cbr\u003e\n**Model version:** 22B \u003cbr\u003e\n\n### Input:\n\n**Input Format:** Red, Green, Blue (RGB) Image + Text \u003cbr\u003e\n**Input Parameters:** temperature, top-p, max output tokens, seed \u003cbr\u003e\n\n### Output:\n\n**Output Format:** Text \u003cbr\u003e\n**Output Parameters:** None \u003cbr\u003e\n\n### Software Integration:\n\n**Runtime(s):** N/A \u003cbr\u003e\n**Supported Hardware Platform(s):** Hopper, Ampere/Turing \u003cbr\u003e\n**Supported Operating System(s):** Linux \u003cbr\u003e\n\n## Training \u0026 Finetuning:\n\n### Pretraining Dataset:\n\n**Link:** [CC-3M](https://huggingface.co/datasets/liuhaotian/LLaVA-CC3M-Pretrain-595K) \u003cbr\u003e\n\n**Properties (Quantity, Dataset Descriptions, Sensor(s)):** \u003cbr\u003e\nThe dataset consists of CC3M images and captions filtered to 595,000 samples. \u003cbr\u003e\n\n**Dataset License:**\n* [COCO](https://cocodataset.org/#termsofuse)\n* [CC-3M](https://github.com/google-research-datasets/conceptual-captions/blob/master/LICENSE)\n* [BLIP](https://github.com/salesforce/BLIP/blob/main/LICENSE.txt) \u003cbr\u003e\n\n### Finetuning Dataset:\n\n**Link:** [Synthetic data generated by GPT4](https://huggingface.co/datasets/liuhaotian/LLaVA-Instruct-150K) \u003cbr\u003e\n\n**Properties (Quantity, Dataset Descriptions, Sensor(s)):** \u003cbr\u003e\nThe data has 158,000 samples was generated synthetically by GPT4. It consists of a mix of short question answers, detailed image description, and higher level reasoning questions. \u003cbr\u003e\n\n**Dataset License:** [CC-BY-NC 4.0 License](https://creativecommons.org/licenses/by-nc/4.0/) CC BY-NC 4.0 \u003cbr\u003e\n\n## Inference:\n\n**Engine:** [Triton](https://developer.nvidia.com/triton-inference-server) and [TensorRT-LLM](https://github.com/NVIDIA/TensorRT-LLM) \u003cbr\u003e\n**Test Hardware:** Other \u003cbr\u003e\n\n### Ethical Considerations:\n\nNVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their supporting model team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse. For more detailed information on ethical considerations for this model, please see the Model Card++ Explainability, Bias, Safety \u0026 Security, and Privacy Subcards [here](https://registry.ngc.nvidia.com/orgs/nvidia/teams/ai-foundation/models/neva-22b/bias). Please report security vulnerabilities or NVIDIA AI Concerns [here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/).\n"])</script><script>self.__next_f.push([1,"3a:T7bb,Field | Response\n:------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------\nIntended Application \u0026 Domain: | Visual Question Answering\nModel Type: | Transformer\nIntended Users: | Generative AI creators working with conversational AI models and image content.\nOutput: | Text (Responds to posed question, Stateful - remembers previous answers)\nDescribe how the model works: | Image input is encoded into embeddings and concatenated with text tokens before being passed into transformer-based language model and output as a text response.\nName the adversely impacted groups this has been tested to deliver comparable outcomes regardless of: | Not Applicable\nTechnical Limitations: | None\nVerified to have met prescribed NVIDIA quality standards: | Yes\nPerformance Metrics: | Accuracy (Visual Question Answering), Latency, Throughput\nPotential Known Risks: | None Known\nLicensing: | [NVIDIA AI Foundation Models Community License](https://docs.nvidia.com/ai-foundation-models-community-license.pdf)"])</script><script>self.__next_f.push([1,"26:[\"$\",\"$L35\",null,{\"name\":\"neva-22b\",\"requestStatus\":{\"statusCode\":\"SUCCESS\",\"requestId\":\"1aaeb6f1-707d-48f3-b558-9faf7cfa5b73\"},\"artifact\":{\"orgName\":\"qc69jvmznzxy\",\"labels\":[\"Non-Commercial Use Only\",\"Vision Assistant\",\"Visual Question Answering\",\"computer vision\",\"cv\",\"image\",\"Image-to-Text\",\"video\",\"vlm\"],\"bias\":\"Field | Response\\n:---------------------------------------------------------------------------------------------------|:---------------\\nParticipation considerations from adversely impacted groups [protected classes](https://www.senate.ca.gov/content/protected-classes) in model design and testing: | None\\nMeasures taken to mitigate against unwanted bias: | None\",\"logo\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/neva-22b.jpg\",\"shortDescription\":\"Multi-modal vision-language model that understands text/images and generates informative responses\",\"safetyAndSecurity\":\"Field | Response\\n:---------------------------------------------------|:----------------------------------\\nModel Application(s): | Visual Question Answering and Conversation\\nDescribe the physical safety impact (if present). | Not Applicable\\nUse Case Restrictions: | Model for Non-Commerical Use Only\\nModel and dataset restrictions: | The Principle of least privilege (PoLP) is applied limiting access for dataset generation and model development. Restrictions enforce dataset access during training, and dataset license constraints adhered to.\",\"privacy\":\"$38\",\"isReadOnly\":true,\"description\":\"$39\",\"canGuestDownload\":true,\"isPublic\":true,\"createdDate\":\"2024-03-15T05:06:34.987Z\",\"publisher\":\"nvidia\",\"displayName\":\"neva-22b\",\"name\":\"neva-22b\",\"explainability\":\"$3a\",\"updatedDate\":\"2024-11-18T22:05:33.055Z\",\"attributes\":[{\"key\":\"PREVIEW\",\"value\":\"true\"}],\"artifactType\":\"ENDPOINT\"}}]\n"])</script><script>self.__next_f.push([1,"1f:[\"$undefined\",[\"$\",\"section\",null,{\"className\":\"flex w-full flex-col justify-between rounded-xl border-manitoulinBorderColor bg-manitoulinDarkBlack md:rounded-[30px] relative overflow-hidden p-[20px] md:p-xl\",\"data-testid\":\"explore-carousel-view\",\"children\":[[\"$\",\"$L3b\",null,{\"alt\":\"\",\"className\":\"object-cover object-center !left-1/2 !w-1/2 brightness-20 md:brightness-100\",\"fill\":true,\"priority\":true,\"src\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/llama-3_1-nemotron-70b-reward.jpg\",\"style\":{\"maskImage\":\"linear-gradient(to left, rgba(0,0,0,1), rgba(0,0,0,0))\"}}],[\"$\",\"div\",null,{\"className\":\"relative z-10 mt-auto flex h-full flex-col items-start justify-center gap-md\",\"children\":[[\"$\",\"div\",null,{\"className\":\"items-center text-lg font-light leading-heading text-n600\",\"style\":{\"whiteSpace\":\"pre-wrap\"},\"children\":[\"$\",\"strong\",null,{\"className\":\"font-medium text-manitoulinLightWhite\",\"data-testid\":\"model-name\",\"children\":\"Align Models with Human Preferences\"}]}],[\"$\",\"p\",null,{\"className\":\"text-mm font-normal text-manitoulinLightGray md:text-ms\",\"children\":\"RewardBench leaderboard topping Llama 3.1-Nemotron-70B-Reward model improve the quality of your model's responses\"}],null,[\"$\",\"$L1b\",null,{\"href\":\"/nvidia/llama-3_1-nemotron-70b-reward\",\"target\":\"_self\",\"className\":\"text-center font-sans font-medium leading-text inline-block leading-[1.2] button-tertiary py-[7px] px-[11px] text-ms min-h-[32px] rounded-[16px] ml-[-10px] PJLV\",\"children\":[\"$\",\"div\",null,{\"className\":\"flex items-center justify-center gap-xs flex-row-reverse\",\"children\":[[\"$\",\"svg\",null,{\"xmlns\":\"http://www.w3.org/2000/svg\",\"fill\":\"none\",\"viewBox\":\"0 0 16 16\",\"width\":\"16\",\"height\":\"16\",\"display\":\"inline-block\",\"data-icon-name\":\"shapes-arrow-right\",\"color\":\"$undefined\",\"style\":{\"minWidth\":\"16px\"},\"children\":[\"$\",\"path\",null,{\"fill\":\"currentColor\",\"fillRule\":\"evenodd\",\"d\":\"M10.793 7.5 7.646 4.354l.708-.708L12.707 8l-4.353 4.354-.708-.707L10.793 8.5H3v-1z\",\"clipRule\":\"evenodd\"}]}],\"Try Now\"]}]}]]}]]}]]\n3d:T93d,"])</script><script>self.__next_f.push([1,"Field | Response\n:----------------------------------------------------------------------------------------------------------------------------------|:-----------------------------------------------\nPersonal data used to create this model? | None Known. For data included in the base Llama 3.1 model, [reference the Llama 3.1 model card.](https://github.com/meta-llama/llama-models/blob/main/models/llama3_1/MODEL_CARD.md)\nWas consent obtained for any personal data used? | Not Applicable for NVIDIA training data; NVIDIA did not introduce personal data through retraining\nGeneratable or reverse engineerable personal data? | Not a known capability.\nHow often is the dataset reviewed (if applicable)? | Before Release\nIs a mechanism in place to honor data subject right of access or deletion of personal data? | Not Applicable for NVIDIA training data \nIf personal data collected for the development of the model, was it collected directly by NVIDIA? | Not Applicable\nIf personal data collected for the development of the model by NVIDIA, do you maintain or have access to disclosures made to data subjects? | Not Applicable\nIf personal data collected for the development of this AI model, was it minimized to only what was required? | Not Applicable for NVIDIA training data \nIs there provenance for all datasets used in training? | Yes\nDoes data labeling (annotation, metadata) comply with privacy laws? | Not Applicable for NVIDIA training data\nIs data compliant with data subject requests for data correction or removal, if such a request was made? | Not Applicable for NVIDIA training data"])</script><script>self.__next_f.push([1,"3e:Td87,"])</script><script>self.__next_f.push([1,"## Model Overview\n\n### Description:\n\nLlama-3.1-Nemotron-70B-Instruct is a large language model customized by NVIDIA to improve the helpfulness of LLM generated responses to user queries.\n\nThis model is ready for commercial use.\n\n### Terms of use\n\nBy accessing this model, you are agreeing to the LLama 3 terms and conditions of the [license](https://github.com/meta-llama/llama-models/blob/main/models/llama3_1/LICENSE), [acceptable use policy](https://github.com/meta-llama/llama-models/blob/main/models/llama3_1/USE_POLICY.md) and [Meta’s privacy policy](https://www.facebook.com/privacy/policy/)\n\n### References(s):\n\n* [HelpSteer2-Preference](https://arxiv.org/abs/2410.01257)\n* [SteerLM method](https://arxiv.org/abs/2310.05344)\n* [HelpSteer](https://arxiv.org/abs/2311.09528)\n* [HelpSteer2](https://arxiv.org/abs/2406.08673)\n* [Introducing Llama 3.1: Our most capable models to date](https://ai.meta.com/blog/meta-llama-3-1/)\n* [Meta's Llama 3.1 Webpage](https://www.llama.com/docs/model-cards-and-prompt-formats/llama3_1)\n* [Meta's Llama 3.1 Model Card](https://github.com/meta-llama/llama-models/blob/main/models/llama3_1/MODEL_CARD.md)\n\n### Model Architecture:\n\n**Architecture Type:** Transformer \u003cbr\u003e\n**Network Architecture:** Llama 3.1 \u003cbr\u003e\n\n### Input:\n\n**Input Type(s):** Text \u003cbr\u003e\n**Input Format:** String \u003cbr\u003e\n**Input Parameters:** One Dimensional (1D) \u003cbr\u003e\n**Other Properties Related to Input:** Max of 128k tokens\u003cbr\u003e\n\n### Output:\n\n**Output Type(s):** Text \u003cbr\u003e\n**Output Format:** String \u003cbr\u003e\n**Output Parameters:** One Dimensional (1D) \u003cbr\u003e\n**Other Properties Related to Output:** Max of 4k tokens \u003cbr\u003e\n\n### Software Integration:\n\n**Supported Hardware Microarchitecture Compatibility:** \u003cbr\u003e\n* NVIDIA Ampere \u003cbr\u003e\n* NVIDIA Hopper \u003cbr\u003e\n* NVIDIA Turing \u003cbr\u003e\n **Supported Operating System(s):** Linux \u003cbr\u003e\n\n### Model Version:\n\nv1.0\n\n## Training \u0026 Evaluation:\n\n### Datasets:\n\n**Data Collection Method by dataset** \u003cbr\u003e\n* [Hybrid: Human, Synthetic] \u003cbr\u003e\n\n**Labeling Method by dataset** \u003cbr\u003e\n* [Human] \u003cbr\u003e\n\n**Link:**\n* [HelpSteer2](https://huggingface.co/datasets/nvidia/HelpSteer2)\n\n**Properties (Quantity, Dataset Descriptions, Sensor(s)):** \u003cbr\u003e\n* 21, 362 prompt-responses built to make more models more aligned with human preference - specifically more helpful, factually-correct, coherent, and customizable based on complexity and verbosity.\n* 20, 324 prompt-responses used for training and 1, 038 used for validation.\n\n## Inference:\n\n**Engine:** [Triton](https://developer.nvidia.com/triton-inference-server) \u003cbr\u003e\n**Test Hardware:** H100, A100 80GB, A100 40GB \u003cbr\u003e\n\n### Ethical Considerations:\n\nNVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their supporting model team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse. For more detailed information on ethical considerations for this model, please see the Model Card++ Explainability, Bias, Safety \u0026 Security, and Privacy Subcards. Please report security vulnerabilities or NVIDIA AI Concerns [here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/).\n\nPlease report security vulnerabilities or NVIDIA AI Concerns [here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/).\n"])</script><script>self.__next_f.push([1,"3f:T828,"])</script><script>self.__next_f.push([1,"Field | Response\n:------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------\nIntended Application \u0026 Domain: | Response Customization in Large Language Model Development\nModel Type: | Text-to-Text Transformer\nIntended User: | Developers customizing model response across different applications and domains.\nOutput: | Text\nDescribe how the model works: | Generates a response based on a prior conversation. \nName the adversely impacted groups this has been tested to deliver comparable outcomes regardless of: | Not Applicable\nVerified to have met prescribed quality standards: | Yes\nTechnical Limitations: | This model may not work for non-English languages.\nPerformance Metrics: | Throughput and Latency\nPotential Known Risks: | The Model may produce output that is biased and toxic based on how it is prompted, producing socially unacceptable or undesirable text, even if the prompt itself does not include anything explicitly offensive. The model may also amplify biases and return toxic responses especially when prompted with toxic prompts. \nLicensing: | [Llama 3.1 Community License Agreement](https://github.com/meta-llama/llama-models/blob/main/models/llama3_1/LICENSE)"])</script><script>self.__next_f.push([1,"40:T5777,"])</script><script>self.__next_f.push([1,"## Model Information\n\nThe Meta Llama 3.1 collection of multilingual large language models (LLMs) is a collection of pretrained and instruction tuned generative models in 8B, 70B and 405B sizes (text in/text out). The Llama 3.1 instruction tuned text only models (8B, 70B, 405B) are optimized for multilingual dialogue use cases and outperform many of the available open source and closed chat models on common industry benchmarks.\n\n**Model Developer**: Meta\n\n## Llama 3.1 Systems\n\n**Large language models, including Llama 3.1, are not designed to be deployed in isolation but instead should be deployed as part of an overall AI system with additional safety guardrails as required.** Developers are expected to deploy system safeguards when building agentic systems. Safeguards are key to achieve the right helpfulness-safety alignment as well as mitigating safety and security risks inherent to the system and any integration of the model or system with external tools. \nAs part of our responsible release approach, we provide the community with [safeguards](https://llama.meta.com/trust-and-safety/) that developers should deploy with Llama models or other LLMs, including Llama Guard 3, Prompt Guard and Code Shield. All our [reference implementations](https://github.com/meta-llama/llama-agentic-system) demos contain these safeguards by default so developers can benefit from system-level safety out-of-the-box.\n\n## Intended Use\n\n**Intended Use Cases** Llama 3.1 is intended for commercial and research use in multiple languages. Instruction tuned text only models are intended for assistant-like chat, whereas pretrained models can be adapted for a variety of natural language generation tasks. The Llama 3.1 model collection also supports the ability to leverage the outputs of its models to improve other models including synthetic data generation and distillation. The Llama 3.1 Community License allows for these use cases.\n\n**Out-of-scope** Use in any manner that violates applicable laws or regulations (including trade compliance laws). Use in any other way that is prohibited by the Acceptable Use Policy and Llama 3.1 Community License. Use in languages beyond those explicitly referenced as supported in this model card**. \n\n**Note: Llama 3.1 has been trained on a broader collection of languages than the 10 supported languages. \n\nDevelopers may fine-tune Llama 3.1 models for languages beyond the 8 supported languages provided they comply with the Llama 3.1 Community License and the Acceptable Use Policy and in such cases are responsible for ensuring that any uses of Llama 3.1 in additional languages is done in a safe and responsible manner.\n\n\n## New Capabilities\n\nNote that this release introduces new capabilities, including a longer context window, multilingual inputs and outputs and possible integrations by developers with third party tools. Building with these new capabilities requires specific considerations in addition to the best practices that generally apply across all Generative AI use cases. \n\n**Tool-use:** Just like in standard software development, developers are responsible for the integration of the LLM with the tools and services of their choice. They should define a clear policy for their use case and assess the integrity of the third party services they use to be aware of the safety and security limitations when using this capability. Refer to the Responsible Use Guide for best practices on the safe deployment of the third party safeguards. \n\n**Multilinguality:** Llama 3.1 supports 7 languages in addition to English: French, German, Hindi, Italian, Portuguese, Spanish, and Thai. Llama may be able to output text in other languages than those that meet performance thresholds for safety and helpfulness. We strongly discourage developers from using this model to converse in non-supported languages without implementing finetuning and system controls in alignment with their policies and the best practices shared in the Responsible Use Guide.\n\n**Model Architecture:** Llama 3.1 is an auto-regressive language model that uses an optimized transformer architecture. The tuned versions use supervised fine-tuning (SFT) and reinforcement learning with human feedback\n(RLHF) to align with human preferences for helpfulness and safety.\n\n| | Training Data | Params | Input modalities | Output modalities | Context Length | GQA | Token count | Knowledge cutoff |\n|-|-|-----------------------|----------------------------------------------|-----------------------|---------------------|-----------------------|-------|---------------|\n| | | 8B | Multilingual Text | Multilingual Text and code| 128k | Yes | 15T+ | December 2023 |\n| Llama 3.1 (text only) | A new mix of publicly available online data. | 70B | Multilingual Text | Multilingual Text and code| 128k | Yes | 15T+ | December 2023 |\n| | | 405B | Multilingual Text | Multilingual Text and code| 128k | Yes | 15T+ | December 2023 |\n\n**Supported languages:** English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai.\n\n**Llama 3.1 family of models**. Token counts refer to pretraining data only. All model versions use Grouped-Query Attention (GQA) for improved inference scalability.\n\n**Model Release Date:** July 23, 2024. \n\n**Status:** This is a static model trained on an offline dataset. Future versions of the tuned models will be released as we improve model safety with community feedback. \n\n**License** A custom commercial license, the Llama 3.1 Community License, is available at: https://github.com/meta-llama/llama-models/blob/main/models/llama3_1/LICENSE \n\nWhere to send questions or comments about the model Instructions on how to provide feedback or comments on the model can be found in the model [README](https://github.com/meta-llama/llama3). For more technical information about generation parameters and recipes for how to use Llama 3.1 in applications, please go [here](ttps://github.com/meta-llama/llama-recipes).\n\n## Hardware And Software\n\n**Training Factors** We used custom training libraries, Meta's custom built GPU cluster, and production infrastructure for pretraining. Fine-tuning, annotation, and evaluation were also performed on production infrastructure. \n\n**Training Energy Use** Training utilized a cumulative of **39.3**M GPU hours of computation on H100-80GB (TDP of 700W) type hardware, per the table below. Training time is the total GPU time required for training each model and power consumption is the peak power capacity per GPU device used, adjusted for power usage efficiency.\n\n**Training Greenhouse Gas Emissions** Estimated total location-based greenhouse gas emissions were **11,390** tons CO2eq for training. Since 2020, Meta has maintained net zero greenhouse gas emissions in its global operations and matched 100% of its electricity use with renewable energy, therefore the total market-based greenhouse gas emissions for training were 0 tons CO2eq.\n\n| | Training Time (GPU hours) | Training Power Consumption (W) | Training Location-Based Greenhouse Gas Emissions (tons CO2eq) | Training Market-Based Greenhouse Gas Emissions (tons CO2eq) |\n| - |---------------------------------------|---------------------------------------|---------------------------|--------|\n| Llama 3.1 8B | 1.46M | 700 | 420 | 0 |\n| Llama 3.1 70B | 7.0M | 700 | 2,040 | 0 |\n| Llama 3.1 405B | 30.84M | 700 | 8,930 | 0 |\n| Total | 39.3M | - | 11,390 | 0 |\n\nThe methodology used to determine training energy use and greenhouse gas emissions can be found [here](https://arxiv.org/pdf/2204.05149). Since Meta is openly releasing these models, the training energy use and greenhouse gas emissions will not be incurred by others.\n\n## Training Data\n\n**Overview:** Llama 3.1 was pretrained on ~15 trillion tokens of data from publicly available sources. The fine-tuning data includes publicly available instruction datasets, as well as over 25M synthetically generated examples.\n\n**Data Freshness:** The pretraining data has a cutoff of December 2023.\n\n## Benchmarks - English Text\n\nIn this section, we report the results for Llama 3.1 models on standard automatic benchmarks. For all the evaluations, we use our internal evaluations library.\n\n### Base pretrained models\n| Category | Benchmark | # Shots | Metric | Llama 3 8B | Llama 3.1 8B | Llama 3 70B | Llama 3.1 70B | Llama 3.1 405B |\n|--------------------------|---------------|--------------------|----------|------------|--------------|-------------|---------------|----------------|\n| General | MMLU | 5 | macro_avg/acc_char | 66.7 | 66.7 | 79.5 | 79.3 | 85.2 | |\n| General | MMLU PRO (CoT) | 5 | macro_avg/acc_char | 36.2 | 37.1 | 55.0 | 53.8 | 61.6 | |\n| General | AGIEval English | 3-5 | average/acc_char | 47.1 | 47.8 | 63.0 | 64.6 | 71.6 | |\n| General | CommonSenseQA | 7 | acc_char | 72.6 | 75.0 | 83.8 | 84.1 | 85.8 |\n| General | Winogrande | 5 | acc_char | - | 60.5 | - | 83.3 | 86.7 | |\n| General | BIG-Bench Hard (CoT) | 3 | average/em | 61.1 | 64.2 | 81.3 | 81.6 | **85.9** | |\n| General | ARC-Challenge | 25 | acc_char | 79.4 | 79.7 | 93.1 | 92.9 | 96.1 | |\n| Knowledge reasoning | TriviaQA-Wiki | 5 | em | 78.5 | 77.6 | 89.7 | 89.8 | 91.8 |\n| Reading comprehension | SQuAD | 1 | em | 76.4 | 77.0 | 85.6 | 81.8 | 89.3 | |\n| Reading comprehension | QuAC (F1) | 1 | f1 | 44.4 | 44.9 | 51.1 | 51.1 | 53.6 | |\n| Reading comprehension | BoolQ | 0 | acc_char | 75.7 | 75.0 | 79.0 | 79.4 | 80.0 |\n| Reading comprehension | DROP (F1) | 3 | f1 | 58.4 | 59.5 | 79.7 | 79.6 | **84.8** | |\n\n### Instruction Tuned Models\n\n\n| Category | Benchmark | # Shots | Metric | Llama 3 8B Instruct | Llama 3.1 8B Instruct | Llama 3 70B Instruct | Llama 3.1 70B Instruct | Llama 3.1 405B Instruct | \n| --- | --- | --- | --- | --- | --- | --- | --- | --- | \n | General | MMLU | 5 | macro_avg/acc | 68.5 | 69.4 | 82.0 | 83.6 | 87.3 | \n | General | MMLU (CoT) | 0 | macro_avg/acc | 65.3 | 72.7 | 80.9 | 85.9 | 88.6 | \n | General | MMLU PRO (CoT) | 5 | micro_avg/acc_char | 45.5 | 48.3 | 63.4 | 65.1 | 73.3 | \n | Reasoning | ARC-C | 0 | acc | 82.4 | 83.4 | 94.4 | 94.8 | **96.9** | \n | Reasoning | GPQA | 0 | em | 34.6 | 30.4 | 39.5 | 41.7 | 50.7 | \n | Reasoning | MuSR | 0 | correct | 56.3 | 45.7 | 55.1 | 58.1 | 56.7 | \n | Steerability | IFEval | | | 76.8 | 80.4 | 82.9 | 87.5 | **88.6** | \n | Code | HumanEval | 0 | pass@1 | 60.4 | 72.6 | 81.7 | 80.5 | 89.0 | \n | Code | MBPP ++ base version | 0 | pass@1 | 70.6 | 72.8 | 82.5 | 86.0 | 88.6 | \n | Math | GSM-8K (CoT) | 8 | em_maj1@1 | 80.6 | 84.5 | 93.0 | 95.1 | 96.8 | \n | Math | MATH (CoT) | 0 | final_em | 29.1 | 51.9 | 51.0 | 68.0 | 73.8 | \n | Tool Use | API-Bank | 0 | acc | 83.6 | 82.6 | 85.1 | 90.0 | 92.0 | \n | Tool Use | Berkeley Function Calling | 0 | acc | 76.1 | 76.1 | 83.0 | 85.1 | **88.5** |\n | Tool Use | Gorilla Benchmark API Bench | 0 | acc | 8.8 | 8.2 | 14.7 | 29.7 | 35.3 | \n | Tool Use | Nexus (0-shot) | 0 | macro_avg/acc | 37.6 | 38.5 | 47.8 | 56.7 | **58.7** | \n | Multilingual | Multilingual MGSM | 8 | em | - | 68.2 | - | 85.6 | 90.3 |\n\n## Multilingual Benchmarks\n\n| Category | Benchmark | Language | Llama 3.1 8B | Llama 3.1 70B | Llama 3.1 405B | \n| --- | --- | --- | --- | --- | --- | \n| | | Portuguese | 62.12 | 80.13 | 84.95 |\n| | | Spanish | 62.45 | 80.05 | 85.08 |\n| | | Italian | 61.63 | 80.4 | 85.04 | \n| General | MMLU (5-shot, macro_avg/acc) | German | 60.59 | 79.27 | 84.36 | \n| | | French | 62.34 | 79.82 | 84.66 | \n| | | Hindi | 50.88 | 74.52 | 80.31 | \n| | | Thai | 50.32 | 72.95 | 78.21 |\n\n\n\n## Responsibility \u0026 Safety\n\nAs part of our Responsible release approach, we followed a three-pronged strategy to managing trust \u0026 safety risks:\n- Enable developers to deploy helpful, safe and flexible experiences for their target audience and for the use cases supported by Llama.\n\n- Protect developers against adversarial users aiming to exploit Llama capabilities to potentially cause harm.\n\n- Provide protections for the community to help prevent the misuse of our models.\n\n## Responsible Deployment\n\nLlama is a foundational technology designed to be used in a variety of use cases, examples on how Meta's Llama models have been responsibly deployed can be found in our [Community Stories webpage](https://llama.meta.com/community-stories/). Our approach is to build the most helpful models enabling the world to benefit from the technology power, by aligning our model safety for the generic use cases addressing a standard set of harms. Developers are then in the driver seat to tailor safety for their use case, defining their own policy and deploying the models with the necessary safeguards in their Llama systems. Llama 3.1 was developed following the best practices outlined in our Responsible Use Guide, you can refer to the [Responsible Use Guide](https://llama.meta.com/responsible-use-guide/) to learn more.\n\n## Llama 3.1 Instruct\n\nOur main objectives for conducting safety fine-tuning are to provide the research community with a valuable resource for studying the robustness of safety fine-tuning, as well as to offer developers a readily available, safe, and powerful model for various applications to reduce the developer workload to deploy safe AI systems. For more details on the safety mitigations implemented please read the Llama 3 paper.\n\n### Fine-Tuning Data\n\nWe employ a multi-faceted approach to data collection, combining human-generated data from our vendors with synthetic data to mitigate potential safety risks. We've developed many large language model (LLM)-based classifiers that enable us to thoughtfully select high-quality prompts and responses, enhancing data quality control.\n\n### Refusals And Tone\n\nBuilding on the work we started with Llama 3, we put a great emphasis on model refusals to benign prompts as well as refusal tone. We included both borderline and adversarial prompts in our safety data strategy, and modified our safety data responses to follow tone guidelines.\n\n## Evaluations\n\nWe evaluated Llama models for common use cases as well as specific capabilities. Common use cases evaluations measure safety risks of systems for most commonly built applications including chat bot, coding assistant, tool calls. We built dedicated, adversarial evaluation datasets and evaluated systems composed of Llama models and Llama Guard 3 to filter input prompt and output response. It is important to evaluate applications in context, and we recommend building dedicated evaluation dataset for your use case. Prompt Guard and Code Shield are also available if relevant to the application. \n\nCapability evaluations measure vulnerabilities of Llama models inherent to specific capabilities, for which were crafted dedicated benchmarks including long context, multilingual, tools calls, coding or memorization.\n\n## Red Teaming\n\nFor both scenarios, we conducted recurring red teaming exercises with the goal of discovering risks via adversarial prompting and we used the learnings to improve our benchmarks and safety tuning datasets. We partnered early with subject-matter experts in critical risk areas to understand the nature of these real-world harms and how such models may lead to unintended harm for society. Based on these conversations, we derived a set of adversarial goals for the red team to attempt to achieve, such as extracting harmful information or reprogramming the model to act in a potentially harmful capacity. The red team consisted of experts in cybersecurity, adversarial machine learning, responsible AI, and integrity in addition to multilingual content specialists with background in integrity issues in specific geographic markets. .\n\n## Critical And Other Risks\n\nWe specifically focused our efforts on mitigating the following critical risk areas: \n\n ### 1- CBRNE (Chemical, Biological, Radiological, Nuclear, and Explosive materials) helpfulness\n To assess risks related to proliferation of chemical and biological weapons, we performed uplift testing designed to assess whether use of Llama 3.1 models could meaningfully increase the capabilities of malicious actors to plan or carry out attacks using these types of weapons.\n\n### 2. Child Safety\n\nChild Safety risk assessments were conducted using a team of experts, to assess the model's capability to produce outputs that could result in Child Safety risks and inform on any necessary and appropriate risk mitigations via fine tuning. We leveraged those expert red teaming sessions to expand the coverage of our evaluation benchmarks through Llama 3 model development. For Llama 3, we conducted new in-depth sessions using objective based methodologies to assess the model risks along multiple attack vectors including the additional languages Llama 3 is trained on. We also partnered with content specialists to perform red teaming exercises assessing potentially violating content while taking account of market specific nuances or experiences.\n\n### 3. Cyber Attack Enablement\n\nOur cyber attack uplift study investigated whether LLMs can enhance human capabilities in hacking tasks, both in terms of skill level and speed. Our attack automation study focused on evaluating the capabilities of LLMs when used as autonomous agents in cyber offensive operations, specifically in the context of ransomware attacks. This evaluation was distinct from previous studies that considered LLMs as interactive assistants. The primary objective was to assess whether these models could effectively function as independent agents in executing complex cyber-attacks without human intervention. Our study of Llama-3.1-405B's social engineering uplift for cyber attackers was conducted to assess the effectiveness of AI models in aiding cyber threat actors in spear phishing campaigns. Please read our Llama 3.1 Cyber security whitepaper to learn more.\n\n## Community\n\nGenerative AI safety requires expertise and tooling, and we believe in the strength of the open community to accelerate its progress. We are active members of open consortiums, including the AI Alliance, Partnership on AI and MLCommons, actively contributing to safety standardization and transparency. We encourage the community to adopt taxonomies like the MLCommons Proof of Concept evaluation to facilitate collaboration and transparency on safety and content evaluations. Our Purple Llama tools are open sourced for the community to use and widely distributed across ecosystem partners including cloud service providers. We encourage community contributions to our [Github repository](https://github.com/meta-llama/PurpleLlama). \n\nWe also set up the [Llama Impact Grants](https://llama.meta.com/llama-impact-grants/) program to identify and support the most compelling applications of Meta's Llama model for societal benefit across three categories: education, climate and open innovation. The 20 finalists from the hundreds of applications can be found [here](https://llama.meta.com/llama-impact-grants/#finalists). \nFinally, we put in place a set of resources including an [output reporting mechanism](https://developers.facebook.com/llama_output_feedback) and [bug bounty program](https://www.facebook.com/whitehat) to continuously improve the Llama technology with the help of the community.\n\n## Ethical Considerations And Limitations\n\nThe core values of Llama 3.1 are openness, inclusivity and helpfulness. It is meant to serve everyone, and to work for a wide range of use cases. It is thus designed to be accessible to people across many different backgrounds, experiences and perspectives. Llama 3.1 addresses users and their needs as they are, without insertion unnecessary judgment or normativity, while reflecting the understanding that even content that may appear problematic in some cases can serve valuable purposes in others. It respects the dignity and autonomy of all users, especially in terms of the values of free thought and expression that power innovation and progress. \n\nBut Llama 3.1 is a new technology, and like any new technology, there are risks associated with its use. Testing conducted to date has not covered, nor could it cover, all scenarios. For these reasons, as with all LLMs, Llama 3.1's potential outputs cannot be predicted in advance, and the model may in some instances produce inaccurate, biased or other objectionable responses to user prompts. Therefore, before deploying any applications of Llama 3.1 models, developers should perform safety testing and tuning tailored to their specific applications of the model. Please refer to available resources including our [Responsible Use Guide](https://llama.meta.com/responsible-use-guide), [Trust and Safety](https://llama.meta.com/trust-and-safety/) solutions, and other [resources](https://llama.meta.com/docs/get-started/) to learn more about responsible development."])</script><script>self.__next_f.push([1,"41:T8e5,"])</script><script>self.__next_f.push([1,"{\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"Tell me about Dumbledore.\"\n }\n ],\n \"model\": \"meta/llama-3.1-405b-instruct\",\n \"max_tokens\": 1024,\n \"stream\": true,\n \"tool_choice\": \"auto\",\n \"tools\": [\n {\n \"type\": \"function\",\n \"function\": {\n \"name\": \"describe_harry_potter_character\",\n \"description\": \"Returns information and images of Harry Potter characters.\",\n \"parameters\": {\n \"type\": \"object\",\n \"properties\": {\n \"name\": {\n \"type\": \"string\",\n \"enum\": [\n \"Harry James Potter\",\n \"Hermione Jean Granger\",\n \"Ron Weasley\",\n \"Fred Weasley\",\n \"George Weasley\",\n \"Bill Weasley\",\n \"Percy Weasley\",\n \"Charlie Weasley\",\n \"Ginny Weasley\",\n \"Molly Weasley\",\n \"Arthur Weasley\",\n \"Neville Longbottom\",\n \"Luna Lovegood\",\n \"Draco Malfoy\",\n \"Albus Percival Wulfric Brian Dumbledore\",\n \"Minerva McGonagall\",\n \"Remus Lupin\",\n \"Rubeus Hagrid\",\n \"Sirius Black\",\n \"Severus Snape\",\n \"Bellatrix Lestrange\",\n \"Lord Voldemort\",\n \"Cedric Diggory\",\n \"Nymphadora Tonks\",\n \"James Potter\"\n ],\n \"description\": \"Name of the Harry Potter character\"\n }\n },\n \"required\": [\n \"name\"\n ]\n }\n }\n }\n ]\n}\n"])</script><script>self.__next_f.push([1,"42:T537,{\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"What is the weather in Santa Clara, CA?\"\n }\n ],\n \"model\": \"meta/llama-3.1-405b-instruct\",\n \"max_tokens\": 1024,\n \"stream\": true,\n \"tool_choice\": \"auto\",\n \"tools\": [\n {\n \"type\": \"function\",\n \"function\": {\n \"name\": \"get_current_weather\",\n \"description\": \"A tool that gets the current weather at a location, if one is specified, and defaults to the user's location.\",\n \"parameters\": {\n \"type\": \"object\",\n \"properties\": {\n \"location\": {\n \"type\": \"string\",\n \"description\": \"The location to find the weather of, or if not provided, it's the default location.\"\n },\n \"unit\": {\n \"type\": \"string\",\n \"enum\": [\n \"u\",\n \"m\"\n ],\n \"description\": \"Whether to use SI or USCS units (celsius or fahrenheit). Infer this from the user's location.\"\n }\n }\n }\n }\n }\n ]\n}\n43:T4bd,from openai import OpenAI\n\nclient = OpenAI(\n base_url = \"https://integrate.api.nvidia.com/v1\",\n api_key = \"$NVIDIA_API_KEY\"\n)\n\u003c% if (request.tools) { %\u003e\ncompletion = client.chat.completions.create(\n model=\"\u003c%- request.model %\u003e\",\n messages=\u003c%- JSON.stringify(request.messages) %\u003e,\n temperature=\u003c%- request.temperature %\u003e,\n top_p=\u003c%- request.top_p %\u003e,\n max_tokens=\u003c%- request.max_tokens %\u003e,\n stream=\u003c%- request.stream?.toString()[0].toUpperCase() + request.stream?.toString().slice(1) %\u003e,\n tools=\u003c%- JSON.stringify(request.tools) %\u003e,\n \u003c% if (request.tool_choice) { %\u003etool_choice=\u003c%- JSON.stringify(request.tool_choice) %\u003e\u003c% } %\u003e\n)\u003c% } else { %\u003e\ncompletion = client.chat.completions.create("])</script><script>self.__next_f.push([1,"\n model=\"\u003c%- request.model %\u003e\",\n messages=\u003c%- JSON.stringify(request.messages) %\u003e,\n temperature=\u003c%- request.temperature %\u003e,\n top_p=\u003c%- request.top_p %\u003e,\n max_tokens=\u003c%- request.max_tokens %\u003e,\n stream=\u003c%- request.stream?.toString()[0].toUpperCase() + request.stream?.toString().slice(1) %\u003e\n)\u003c% } %\u003e\n\u003c% if (request.stream) { %\u003e\nfor chunk in completion:\n if chunk.choices[0].delta.content is not None:\n print(chunk.choices[0].delta.content, end=\"\")\n\u003c% } else { %\u003e\nprint(completion.choices[0].message)\n\u003c% } %\u003e\n44:T504,import OpenAI from 'openai';\n\nconst openai = new OpenAI({\n apiKey: '$NVIDIA_API_KEY',\n baseURL: 'https://integrate.api.nvidia.com/v1',\n})\n \u003c% if (request.tools) { %\u003e\nasync function main() {\n const completion = await openai.chat.completions.create({\n model: \"\u003c%- request.model %\u003e\",\n messages: \u003c%- JSON.stringify(request.messages) %\u003e,\n temperature: \u003c%- request.temperature %\u003e,\n top_p: \u003c%- request.top_p %\u003e,\n max_tokens: \u003c%- request.max_tokens %\u003e,\n stream: \u003c%- request.stream %\u003e,\n \u003c% if (request.tools) { %\u003etools: \u003c%- JSON.stringify(request.tools) %\u003e,\u003c% } %\u003e\n \u003c% if (request.tool_choice) { %\u003etool_choice: \u003c%- JSON.stringify(request.tool_choice) %\u003e,\u003c% } %\u003e\n })\u003c% } else { %\u003e\nasync function main() {\n const completion = await openai.chat.completions.create({\n model: \"\u003c%- request.model %\u003e\",\n messages: \u003c%- JSON.stringify(request.messages) %\u003e,\n temperature: \u003c%- request.temperature %\u003e,\n top_p: \u003c%- request.top_p %\u003e,\n max_tokens: \u003c%- request.max_tokens %\u003e,\n stream: \u003c%- request.stream %\u003e\n })\u003c% } %\u003e\n \u003c% if (request.stream) { %\u003e\n for await (const chunk of completion) {\n process.stdout.write(chunk.choices[0]?.delta?.content || '')\n }\n \u003c% } else { %\u003e\n process.stdout.write(completion.choices[0]?.message?.content);\n \u003c% } %\u003e\n}\n\nmain();45:T671,\u003c% if (request.tools) { %\u003e\n \"curl https://integrate.api.nvidia.com/v1/chat/completions \\\\\\n\n -H \\\"Content-Type: application/json\\\" \\\\\\n\n -H \\\"Authorization: Bearer $NVIDIA_API_KEY\\\" \\\\\\n\n -d '{\\n\n \\\"model\\\": \\\"meta/ll"])</script><script>self.__next_f.push([1,"ama-3.1-405b-instruct\\\",\\n\n \\\"messages\\\": \u003c%- JSON.stringify(request.messages).replaceAll(\\\"'\\\", \\\"'\\\\\\\"'\\\\\\\"'\\\") %\u003e,\\n\n \\\"temperature\\\": \u003c%- request.temperature %\u003e,\\n\n \\\"top_p\\\": \u003c%- request.top_p %\u003e,\\n\n \\\"max_tokens\\\": \u003c%- request.max_tokens %\u003e,\\n\n \\\"stream\\\": \u003c%- request.stream %\u003e\n \u003c% if (request.tools) { %\u003e,\\n \\\"tools\\\": \u003c%- JSON.stringify(request.tools).replaceAll(\\\"'\\\", \\\"'\\\\\\\"'\\\\\\\"'\\\") %\u003e\u003c% } %\u003e\n \u003c% if (request.tool_choice) { %\u003e,\\n \\\"tool_choice\\\": \u003c%- JSON.stringify(request.tool_choice).replaceAll(\\\"'\\\", \\\"'\\\\\\\"'\\\\\\\"'\\\") %\u003e\u003c% } %\u003e\n }'\\n\"\u003c% } else { %\u003e\n \"curl https://integrate.api.nvidia.com/v1/chat/completions \\\\\\n\n -H \\\"Content-Type: application/json\\\" \\\\\\n\n -H \\\"Authorization: Bearer $NVIDIA_API_KEY\\\" \\\\\\n\n -d '{\\n\n \\\"model\\\": \\\"meta/llama-3.1-405b-instruct\\\",\\n\n \\\"messages\\\": \u003c%- JSON.stringify(request.messages).replaceAll(\\\"'\\\", \\\"'\\\\\\\"'\\\\\\\"'\\\") %\u003e,\\n\n \\\"temperature\\\": \u003c%- request.temperature %\u003e,\\n\n \\\"top_p\\\": \u003c%- request.top_p %\u003e,\\n\n \\\"max_tokens\\\": \u003c%- request.max_tokens %\u003e,\\n\n \\\"stream\\\": \u003c%- request.stream %\u003e\n \u003c% if (request.tools) { %\u003e,\\n \\\"tools\\\": \u003c%- JSON.stringify(request.tools).replaceAll(\\\"'\\\", \\\"'\\\\\\\"'\\\\\\\"'\\\") %\u003e\u003c% } %\u003e\n \u003c% if (request.tool_choice) { %\u003e,\\n \\\"tool_choice\\\": \u003c%- JSON.stringify(request.tool_choice).replaceAll(\\\"'\\\", \\\"'\\\\\\\"'\\\\\\\"'\\\") %\u003e\u003c% } %\u003e\n }'\\n\"\u003c% } %\u003e46:T5918,"])</script><script>self.__next_f.push([1,"## Model Information\n\nThe Meta Llama 3.2 Vision collection of multimodal large language models (LLMs) is a collection of pre-trained and instruction-tuned image reasoning generative models in 11B and 90B sizes (text \\+ images in / text out). The Llama 3.2 Vision instruction-tuned models are optimized for visual recognition, image reasoning, captioning, and answering general questions about an image. The models outperform many of the available open source and closed multimodal models on common industry benchmarks. Llama 3.2 Vision models are ready for commercial use.\n\n**Models in this Collection:** \n- Llama-3.2-11B-Vision\n- Llama-3.2-11B-Vision-Instruct\n- Llama-3.2-90B-Vision\n- Llama-3.2-90B-Vision-Instruct\n\n**Model Developer**: Meta\n\n**Model Release Date:** September 25, 2024\n\n**Third-Party Community Consideration:**\nThis model is not owned or developed by NVIDIA. This model has been developed and built to a third-party’s requirements for this application and use case; see link to Non-NVIDIA [Llama 3.2 Model Card](https://github.com/meta-llama/llama-models/blob/main/models/llama3_2/MODEL_CARD_VISION.md).\n\n**License:** Use of Llama 3.2 is governed by the [Llama 3.2 Community License](https://github.com/meta-llama/llama-models/blob/main/models/llama3_2/LICENSE) (a custom, commercial license agreement).\n\n**Model Architecture:** Llama 3.2 Vision is built on top of Llama 3.1 text-only model, which is an auto-regressive language model that uses an optimized transformer architecture. The tuned versions use supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to align with human preferences for helpfulness and safety. To support image recognition tasks, the Llama 3.2 Vision model uses a separately trained vision adapter that integrates with the pre-trained Llama 3.1 language model. The adapter consists of a series of cross-attention layers that feed image encoder representations into the core LLM.\n\n| | Training Data | Params | Input modalities | Output modalities | Context length | GQA | Token count | Knowledge cutoff |\n| :---- | :---- | :---- | :---- | :---- | :---- | :---- | :---- | :---- |\n| Llama 3.2 Vision | (Image, text) pairs | 11B (10.6) | Text \\+ Image | Text | 128k | Yes | 6B (image, text) pairs | December 2023 |\n| | | 90B (88.8) | Text \\+ Image | Text | 128k | Yes | | |\n\n**Supported Languages:** For text only tasks, English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai are officially supported. Llama 3.2 has been trained on a broader collection of languages than these 8 supported languages. Note for image+text applications, English is the only language supported. \n\nDevelopers may fine-tune Llama 3.2 models for languages beyond these supported languages, provided they comply with the Llama 3.2 Community License and the Acceptable Use Policy. Developers are always expected to ensure that their deployments, including those that involve additional languages, are completed safely and responsibly.\n\n**Llama 3.2 Model Family:** Token counts refer to pre-training data only. All model versions use Grouped-Query Attention (GQA) for improved inference scalability.\n\n**Status:** This is a static model trained on an offline dataset. Future versions may be released that improve model capabilities and safety. \n\n**Feedback:** Where to send questions or comments about the model Instructions on how to provide feedback or comments on the model can be found in the model [README](https://github.com/meta-llama/llama-models/tree/main/models/llama3_2). For more technical information about generation parameters and recipes for how to use Llama 3.2 Vision in applications, please go [here](https://github.com/meta-llama/llama-recipes). \n\n## Intended Use\n\n**Intended Use Cases:** Llama 3.2 Vision is intended for commercial and research use. Instruction-tuned models are intended for visual recognition, image reasoning, captioning, and assistant-like chat with images, whereas pre-trained models can be adapted for a variety of image reasoning tasks. Additionally, because of Llama 3.2 Vision’s ability to take images and text as inputs, additional use cases could include:\n\n1. Visual Question Answering (VQA) and Visual Reasoning: Imagine a machine that looks at a picture and understands your questions about it. \n2. Document Visual Question Answering (DocVQA): Imagine a computer understanding both the text and layout of a document, like a map or contract, and then answering questions about it directly from the image. \n3. Image Captioning: Image captioning bridges the gap between vision and language, extracting details, understanding the scene, and then crafting a sentence or two that tells the story. \n4. Image-Text Retrieval: Image-text retrieval is like a matchmaker for images and their descriptions. Similar to a search engine but one that understands both pictures and words. \n5. Visual Grounding: Visual grounding is like connecting the dots between what we see and say. It’s about understanding how language references specific parts of an image, allowing AI models to pinpoint objects or regions based on natural language descriptions. \n \n\nThe Llama 3.2 model collection also supports the ability to leverage the outputs of its models to improve other models including synthetic data generation and distillation. The Llama 3.2 Community License allows for these use cases. \n\n**Out of Scope:** Use in any manner that violates applicable laws or regulations (including trade compliance laws). Use in any other way that is prohibited by the Acceptable Use Policy and Llama 3.2 Community License. Use in languages beyond those explicitly referenced as supported in this model card.\n\n## Hardware and Software\n\n**Training Factors:** We used custom training libraries, Meta's custom built GPU cluster, and production infrastructure for pre-training. Fine-tuning, annotation, and evaluation were also performed on production infrastructure.\n\n**Training Energy Use:** Training utilized a cumulative of **2.02M** GPU hours of computation on H100-80GB (TDP of 700W) type hardware, per the table below. Training time is the total GPU time required for training each model and power consumption is the peak power capacity per GPU device used, adjusted for power usage efficiency. \n\n## \n\n**Training Greenhouse Gas Emissions:** Estimated total location-based greenhouse gas emissions were **584** tons CO2eq for training. Since 2020, Meta has maintained net zero greenhouse gas emissions in its global operations and matched 100% of its electricity use with renewable energy, therefore the total market-based greenhouse gas emissions for training were 0 tons CO2eq.\n\n| | Training Time (GPU hours) | Training Power Consumption (W) | Training Location-Based Greenhouse Gas Emissions (tons CO2eq) | Training Market-Based Greenhouse Gas Emissions (tons CO2eq) |\n| :---- | :---: | :---: | :---: | :---: |\n| Llama-3.2-11B-Vision | Stage 1 pre-training: 147K H100 hours Stage 2 annealing: 98K H100 hours SFT: 896 H100 hours RLHF: 224 H100 hours | 700 | 71 | 0 |\n| Llama-3.2-90B-Vision | Stage 1 pre-training: 885K H100 hours Stage 2 annealing: 885K H100 hours SFT: 3072 H100 hours RLHF: 2048 H100 hours | 700 | 513 | 0 |\n| Total | 2.02M | | 584 | 0 |\n\nThe methodology used to determine training energy use and greenhouse gas emissions can be found [here](https://arxiv.org/pdf/2204.05149). Since Meta is openly releasing these models, the training energy use and greenhouse gas emissions will not be incurred by others.\n\n## Training Data\n\n**Data Collection Method:** Unknown\n**Labeling Method:** Unknown\n\n**Overview:** Llama 3.2 Vision was pre-trained on 6B image and text pairs. The instruction tuning data includes publicly available vision instruction datasets, as well as over 3M synthetically generated examples.\n\n**Data Freshness:** The pre-training data has a cutoff of December 2023.\n\n## Benchmarks \\- Image Reasoning\n\nIn this section, we report the results for Llama 3.2 Vision models on standard automatic benchmarks. For all these evaluations, we used our internal evaluations library.\n\n### Base Pre-trained Models\n\n| Category | Benchmark | \\# Shots | Metric | Llama-3.2-11B-Vision | Llama-3.2-90B-Vision |\n| ----- | ----- | ----- | ----- | ----- | ----- |\n| Image Understanding | VQAv2 (test-dev, 30k) | 0 | Zero-shot Accuracy | 66.83 | 73.64 |\n| | Text VQA (val) | 0 | Zero-shot Relaxed accuracy | 73.14 | 73.52 |\n| | DocVQA (val, unseen) | 0 | Zero-shot Average Normalized Levenshtein Similarity (ANLS) | 62.26 | 70.65 |\n| Visual Reasoning | MMMU (val, 0-shot) | 0 | Zero-shot Micro Average Accuracy | 41.67 | 49.33 |\n| | ChartQA (test) | 0 | Zero-shot Accuracy | 39.4 | 54.16 |\n| | InfographicsQA (val, unseen) | 0 | Zero-shot Average Normalized Levenshtein Similarity (ANLS) | 43.21 | 56.79 |\n| | AI2 Diagram (test) | 0 | Zero-shot Accuracy | 62.37 | 75.26 |\n\n### Instruction-Tuned Models\n\n| Modality | Capability | Benchmark | \\# Shots | Metric | Llama-3.2-11B-Vision-Instruct | Llama-3.2-90B-Vision-Instruct |\n| ----- | :---: | ----- | :---: | :---: | ----- | ----- |\n| Image | College-level Problems and Mathematical Reasoning | MMMU (val, CoT) | 0 | micro avg accuracy | 50.7 | 60.3 |\n| | | MMMU-Pro, Standard (10 opts, test) | 0 | accuracy | 33.0 | 45.2 |\n| | | MMMU-Pro, Vision (test) | 0 | accuracy | 23.7 | 33.8 |\n| | | MathVista (testmini) | 0 | accuracy | 51.5 | 57.3 |\n| | Charts and Diagram Understanding | ChartQA (test, CoT) | 0 | relaxed accuracy | 83.4 | 85.5 |\n| | | AI2 Diagram (test) | 0 | accuracy | 91.1 | 92.3 |\n| | | DocVQA (test) | 0 | ANLS | 88.4 | 90.1 |\n| | General Visual Question Answering | VQAv2 (test) | 0 | accuracy | 75.2 | 78.1 |\n| | | | | | | |\n| Text | General | MMLU | 0 | macro\\_avg/acc | [73.0](https://docs.google.com/spreadsheets/d/1b3IrobU5rTfbxtR-lfEMn7Fb41_YO3kfhrPmuP-g6ys/edit?gid=688970324#gid=688970324\u0026range=E19) | [86.0](https://docs.google.com/spreadsheets/d/1b3IrobU5rTfbxtR-lfEMn7Fb41_YO3kfhrPmuP-g6ys/edit?gid=688970324#gid=688970324\u0026range=H19) |\n| | Math | MATH (CoT) | 0 | final\\_em | [51.9](https://docs.google.com/spreadsheets/d/1b3IrobU5rTfbxtR-lfEMn7Fb41_YO3kfhrPmuP-g6ys/edit?gid=688970324#gid=688970324\u0026range=E25) | [68.0](https://docs.google.com/spreadsheets/d/1b3IrobU5rTfbxtR-lfEMn7Fb41_YO3kfhrPmuP-g6ys/edit?gid=688970324#gid=688970324\u0026range=H25) |\n| | Reasoning | GPQA | 0 | acc | [32.8](https://docs.google.com/spreadsheets/d/1b3IrobU5rTfbxtR-lfEMn7Fb41_YO3kfhrPmuP-g6ys/edit?gid=688970324#gid=688970324\u0026range=E27) | [46.7](https://docs.google.com/spreadsheets/d/1b3IrobU5rTfbxtR-lfEMn7Fb41_YO3kfhrPmuP-g6ys/edit?gid=688970324#gid=688970324\u0026range=H27) |\n| | Multilingual | MGSM (CoT) | 0 | em | [68.9](https://docs.google.com/spreadsheets/d/1b3IrobU5rTfbxtR-lfEMn7Fb41_YO3kfhrPmuP-g6ys/edit?gid=688970324#gid=688970324\u0026range=E33) | [86.9](https://docs.google.com/spreadsheets/d/1b3IrobU5rTfbxtR-lfEMn7Fb41_YO3kfhrPmuP-g6ys/edit?gid=688970324#gid=688970324\u0026range=H33) |\n\n## Inference\n\n**Supported Hardware Microarchitecture Compatibility:**\n- NVIDIA Ampere\n- NVIDIA Hopper\n- NVIDIA Lovelace\n\n**Supported Operating System(s):**\n- Linux\n\n## Responsibility \u0026 Safety\n\nAs part of our Responsible release approach, we followed a three-pronged strategy to managing trust \u0026 safety risks:\n\n1. Enable developers to deploy helpful, safe and flexible experiences for their target audience and for the use cases supported by Llama. \n2. Protect developers against adversarial users aiming to exploit Llama capabilities to potentially cause harm. \n3. Provide protections for the community to help prevent the misuse of our models.\n\n### Responsible Deployment \n\n**Approach:** Llama is a foundational technology designed to be used in a variety of use cases, examples on how Meta’s Llama models have been responsibly deployed can be found in our [Community Stories webpage](https://llama.meta.com/community-stories/). Our approach is to build the most helpful models enabling the world to benefit from the technology power, by aligning our model safety for the generic use cases addressing a standard set of harms. Developers are then in the driver seat to tailor safety for their use case, defining their own policy and deploying the models with the necessary safeguards in their Llama systems. Llama 3.2 was developed following the best practices outlined in our Responsible Use Guide, you can refer to the [Responsible Use Guide](https://llama.meta.com/responsible-use-guide/) to learn more. \n\n#### Llama 3.2 Instruct \n\n**Objective:** Our main objectives for conducting safety fine-tuning are to provide the research community with a valuable resource for studying the robustness of safety fine-tuning, as well as to offer developers a readily available, safe, and powerful model for various applications to reduce the developer workload to deploy safe AI systems. We implemented the same set of safety mitigations as in Llama 3, and you can learn more about these in the Llama 3 [paper](https://ai.meta.com/research/publications/the-llama-3-herd-of-models/).\n\n**Fine-Tuning Data:** We employ a multi-faceted approach to data collection, combining human-generated data from our vendors with synthetic data to mitigate potential safety risks. We’ve developed many large language model (LLM)-based classifiers that enable us to thoughtfully select high-quality prompts and responses, enhancing data quality control. \n\n**Refusals and Tone:** Building on the work we started with Llama 3, we put a great emphasis on model refusals to benign prompts as well as refusal tone. We included both borderline and adversarial prompts in our safety data strategy, and modified our safety data responses to follow tone guidelines.\n\n#### Llama 3.2 Systems\n\n**Safety as a System:** Large language models, including Llama 3.2, **are not designed to be deployed in isolation** but instead should be deployed as part of an overall AI system with additional safety guardrails as required. Developers are expected to deploy system safeguards when building agentic systems. Safeguards are key to achieve the right helpfulness-safety alignment as well as mitigating safety and security risks inherent to the system and any integration of the model or system with external tools. As part of our responsible release approach, we provide the community with [safeguards](https://llama.meta.com/trust-and-safety/) that developers should deploy with Llama models or other LLMs, including Llama Guard, Prompt Guard and Code Shield. All our [reference implementations](https://github.com/meta-llama/llama-agentic-system) demos contain these safeguards by default so developers can benefit from system-level safety out-of-the-box. \n\n### New Capabilities and Use Cases\n\n**Technological Advancement:** Llama releases usually introduce new capabilities that require specific considerations in addition to the best practices that generally apply across all Generative AI use cases. For prior release capabilities also supported by Llama 3.2, see [Llama 3.1 Model Card](https://github.com/meta-llama/llama-models/blob/main/models/llama3_1/MODEL_CARD.md), as the same considerations apply here as well., \n\n**Image Reasoning:** Llama 3.2 Vision models come with multimodal (text and image) input capabilities enabling image reasoning applications. As part of our responsible release process, we took dedicated measures including evaluations and mitigations to address the risk of the models uniquely identifying individuals in images. As with other LLM risks, models may not always be robust to adversarial prompts, and developers should evaluate identification and other applicable risks in the context of their applications as well as consider deploying Llama Guard 3-11B-Vision as part of their system or other mitigations as appropriate to detect and mitigate such risks.\n\n### Evaluations\n\n**Scaled Evaluations:** We built dedicated, adversarial evaluation datasets and evaluated systems composed of Llama models and Purple Llama safeguards to filter input prompt and output response. It is important to evaluate applications in context, and we recommend building dedicated evaluation dataset for your use case. \n\n**Red teaming:** We conducted recurring red teaming exercises with the goal of discovering risks via adversarial prompting and we used the learnings to improve our benchmarks and safety tuning datasets. We partnered early with subject-matter experts in critical risk areas to understand the nature of these real-world harms and how such models may lead to unintended harm for society. Based on these conversations, we derived a set of adversarial goals for the red team to attempt to achieve, such as extracting harmful information or reprogramming the model to act in a potentially harmful capacity. The red team consisted of experts in cybersecurity, adversarial machine learning, responsible AI, and integrity in addition to multilingual content specialists with background in integrity issues in specific geographic markets.\n\n### Critical Risks \n\nIn addition to our safety work above, we took extra care on measuring and/or mitigating the following critical risk areas:\n\n**1\\. CBRNE (Chemical, Biological, Radiological, Nuclear, and Explosive Weapons):** For Llama 3.1, to assess risks related to proliferation of chemical and biological weapons, we performed uplift testing designed to assess whether use of Llama 3.1 models could meaningfully increase the capabilities of malicious actors to plan or carry out attacks using these types of weapons. For Llama 3.2 Vision models, we conducted additional targeted evaluations and found that it was unlikely Llama 3.2 presented an increase in scientific capabilities due to its added image understanding capability as compared to Llama 3.1.\n\n**2\\. Child Safety:** Child Safety risk assessments were conducted using a team of experts, to assess the model’s capability to produce outputs that could result in Child Safety risks and inform on any necessary and appropriate risk mitigations via fine tuning. We leveraged those expert red teaming sessions to expand the coverage of our evaluation benchmarks through Llama 3 model development. For Llama 3, we conducted new in-depth sessions using objective based methodologies to assess the model risks along multiple attack vectors including the additional languages Llama 3 is trained on. We also partnered with content specialists to perform red teaming exercises assessing potentially violating content while taking account of market specific nuances or experiences. \n\n**3\\. Cyber Attacks:** Our cyber attack uplift study investigated whether LLMs can enhance human capabilities in hacking tasks, both in terms of skill level and speed. \nOur attack automation study focused on evaluating the capabilities of LLMs when used as autonomous agents in cyber offensive operations, specifically in the context of ransomware attacks. This evaluation was distinct from previous studies that considered LLMs as interactive assistants. The primary objective was to assess whether these models could effectively function as independent agents in executing complex cyber-attacks without human intervention.\n\n### Community \n\n**Industry Partnerships:** Generative AI safety requires expertise and tooling, and we believe in the strength of the open community to accelerate its progress. We are active members of open consortiums, including the AI Alliance, Partnership on AI and MLCommons, actively contributing to safety standardization and transparency. We encourage the community to adopt taxonomies like the MLCommons Proof of Concept evaluation to facilitate collaboration and transparency on safety and content evaluations. Our Purple Llama tools are open sourced for the community to use and widely distributed across ecosystem partners including cloud service providers. We encourage community contributions to our [Github repository](https://github.com/meta-llama/PurpleLlama).\n\n**Grants:** We also set up the [Llama Impact Grants](https://llama.meta.com/llama-impact-grants/) program to identify and support the most compelling applications of Meta’s Llama model for societal benefit across three categories: education, climate and open innovation. The 20 finalists from the hundreds of applications can be found [here](https://llama.meta.com/llama-impact-grants/#finalists). \n\n**Reporting:** Finally, we put in place a set of resources including an [output reporting mechanism](https://developers.facebook.com/llama_output_feedback) and [bug bounty program](https://www.facebook.com/whitehat) to continuously improve the Llama technology with the help of the community.\n\n## Ethical Considerations and Limitations\n\n**Values:** The core values of Llama 3.2 are openness, inclusivity and helpfulness. It is meant to serve everyone, and to work for a wide range of use cases. It is thus designed to be accessible to people across many different backgrounds, experiences and perspectives. Llama 3.2 addresses users and their needs as they are, without insertion unnecessary judgment or normativity, while reflecting the understanding that even content that may appear problematic in some cases can serve valuable purposes in others. It respects the dignity and autonomy of all users, especially in terms of the values of free thought and expression that power innovation and progress. \n\n**Testing:** But Llama 3.2 is a new technology, and like any new technology, there are risks associated with its use. Testing conducted to date has not covered, nor could it cover, all scenarios. For these reasons, as with all LLMs, Llama 3.2’s potential outputs cannot be predicted in advance, and the model may in some instances produce inaccurate, biased or other objectionable responses to user prompts. Therefore, before deploying any applications of Llama 3.2 models, developers should perform safety testing and tuning tailored to their specific applications of the model. Please refer to available resources including our [Responsible Use Guide](https://llama.meta.com/responsible-use-guide), [Trust and Safety](https://llama.meta.com/trust-and-safety/) solutions, and other [resources](https://llama.meta.com/docs/get-started/) to learn more about responsible development. \n\nNVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their internal model team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse.\nPlease report security vulnerabilities or NVIDIA AI Concerns [here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/)."])</script><script>self.__next_f.push([1,"47:T4c0,\u003c% let pyStream = request.stream.toString()[0].toUpperCase() + request.stream.toString().slice(1) %\u003e\nimport requests, base64\n\ninvoke_url = \"https://ai.api.nvidia.com/v1/gr/meta/llama-3.2-90b-vision-instruct/chat/completions\"\nstream = \u003c%- pyStream %\u003e\n\u003c% let content = \"What is in this image?\" %\u003e\nwith open(\"image.png\", \"rb\") as f:\n image_b64 = base64.b64encode(f.read()).decode()\n\nassert len(image_b64) \u003c 180_000, \\\n \"To upload larger images, use the assets API (see docs)\"\n \u003c% content = content.replaceAll(\"'\", \"\\\\'\") + \" \u003cimg src=\\\"data:image/png;base64,{image_b64}\\\" /\u003e\"%\u003e\n\nheaders = {\n \"Authorization\": \"Bearer $NVIDIA_API_KEY\",\n \"Accept\": \"text/event-stream\" if stream else \"application/json\"\n}\n\npayload = {\n \"model\": '\u003c%- request.model %\u003e',\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": f'\u003c%- content %\u003e'\n }\n ],\n \"max_tokens\": \u003c%- request.max_tokens %\u003e,\n \"temperature\": \u003c%- request.temperature.toFixed(2) %\u003e,\n \"top_p\": \u003c%- request.top_p.toFixed(2) %\u003e,\n \"stream\": stream\n}\n\nresponse = requests.post(invoke_url, headers=headers, json=payload)\n\nif stream:\n for line in response.iter_lines():\n if line:\n print(line.decode(\"utf-8\"))\nelse:\n print(response.json())\n48:T56f,import axios from 'axios';\nimport { readFile } from 'node:fs/promises';\n\nconst invokeUrl = \"https://ai.api.nvidia.com/v1/gr/meta/llama-3.2-90b-vision-instruct/chat/completions\";\nconst stream = \u003c%- request.stream %\u003e;\n\nconst headers = {\n \"Authorization\": \"Bearer $NVIDIA_API_KEY\",\n \"Accept\": stream ? \"text/event-stream\" : \"application/json\"\n};\n\u003c% content = \"What is in this image? \u003cimg src=\\\"data:image/png;base64,${imageB64}\\\" /\u003e\" %\u003e\nreadFile(\"image.png\")\n .then(data =\u003e {\n const imageB64 = Buffer.from(data).toString('base64');\n if (imageB64.length \u003e 180_000) {\n throw new Error(\"To upload larger images, use the assets API (see docs)\");\n }\n\n const payload = {\n \"model\": `\u003c%- request.model %\u003e`,\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": `\u003c%- content %\u003e`\n "])</script><script>self.__next_f.push([1," }\n ],\n \"max_tokens\": \u003c%- request.max_tokens %\u003e,\n \"temperature\": \u003c%- request.temperature.toFixed(2) %\u003e,\n \"top_p\": \u003c%- request.top_p.toFixed(2) %\u003e,\n \"stream\": stream\n };\n\n return axios.post(invokeUrl, payload, { headers: headers, responseType: stream ? 'stream' : 'json' });\n })\n .then(response =\u003e {\n if (stream) {\n response.data.on('data', (chunk) =\u003e {\n console.log(chunk.toString());\n });\n } else {\n console.log(JSON.stringify(response.data));\n }\n })\n .catch(error =\u003e {\n console.error(error);\n });\n49:T5116,"])</script><script>self.__next_f.push([1,"## Model Information\n\nThe Meta Llama 3.2 collection of multilingual large language models (LLMs) is a collection of pre-trained and instruction-tuned generative models in 1B and 3B sizes (text in/text out). The Llama 3.2 instruction-tuned text only models are optimized for multilingual dialogue use cases, including agentic retrieval and summarization tasks. They outperform many of the available open source and closed chat models on common industry benchmarks. Llama 3.2 models are ready for commercial use.\n\nModels are accelerated by [TensorRT-LLM](https://github.com/NVIDIA/TensorRT-LLM), a library for optimizing Large Language Model (LLM) inference on NVIDIA GPUs.\n\n**Models in this Collection:** \n- Llama-3.2-1B\n- Llama-3.2-1B-Instruct\n- Llama-3.2-3B\n- Llama-3.2-3B-Instruct\n\n**Model Developer:** Meta\n\n**Model Release Date:** September 25, 2024\n\n**Third-Party Community Consideration:**\nThis model is not owned or developed by NVIDIA. This model has been developed and built to a third-party’s requirements for this application and use case; see link to Non-NVIDIA [Llama 3.2 Model Card](https://github.com/meta-llama/llama-models/blob/main/models/llama3_2/MODEL_CARD.md).\n\n**License:** Use of Llama 3.2 is governed by the [Llama 3.2 Community License](https://github.com/meta-llama/llama-models/blob/main/models/llama3_2/LICENSE) (a custom, commercial license agreement).\n\n**Model Architecture:** Llama 3.2 is an auto-regressive language model that uses an optimized transformer architecture. The tuned versions use supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to align with human preferences for helpfulness and safety. \n\n| | Training Data | Params | Input modalities | Output modalities | Context Length | GQA | Shared Embeddings | Token count | Knowledge cutoff |\n| :---- | :---- | :---- | :---- | :---- | :---- | :---- | :---- | :---- | :---- |\n| Llama 3.2 (text only) | A new mix of publicly available online data. | 1B (1.23B) | Multilingual Text | Multilingual Text and code | 128k | Yes | Yes | Up to 9T tokens | December 2023 |\n| | | 3B (3.21B) | Multilingual Text | Multilingual Text and code | | | | | |\n\n**Supported Languages:** English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai are officially supported. Llama 3.2 has been trained on a broader collection of languages than these 8 supported languages. Developers may fine-tune Llama 3.2 models for languages beyond these supported languages, provided they comply with the Llama 3.2 Community License and the Acceptable Use Policy. Developers are always expected to ensure that their deployments, including those that involve additional languages, are completed safely and responsibly.\n\n**Llama 3.2 Model Family:** Token counts refer to pre-training data only. All model versions use Grouped-Query Attention (GQA) for improved inference scalability.\n\n**Status:** This is a static model trained on an offline dataset. Future versions may be released that improve model capabilities and safety. \n\n**Feedback:** Where to send questions or comments about the model Instructions on how to provide feedback or comments on the model can be found in the model [README](https://github.com/meta-llama/llama-models/tree/main/models/llama3_2). For more technical information about generation parameters and recipes for how to use Llama 3.2 in applications, please go [here](https://github.com/meta-llama/llama-recipes). \n\n## Intended Use\n\n**Intended Use Cases:** Llama 3.2 is intended for commercial and research use in multiple languages. Instruction tuned text only models are intended for assistant-like chat and agentic applications like knowledge retrieval and summarization, mobile AI powered writing assistants and query and prompt rewriting. Pre-trained models can be adapted for a variety of additional natural language generation tasks. \n\n**Out of Scope:** Use in any manner that violates applicable laws or regulations (including trade compliance laws). Use in any other way that is prohibited by the Acceptable Use Policy and Llama 3.2 Community License. Use in languages beyond those explicitly referenced as supported in this model card.\n\n## Hardware and Software\n\n**Training Factors:** We used custom training libraries, Meta's custom built GPU cluster, and production infrastructure for pre-training. Fine-tuning, annotation, and evaluation were also performed on production infrastructure.\n\n**Training Energy Use:** Training utilized a cumulative of **916k** GPU hours of computation on H100-80GB (TDP of 700W) type hardware, per the table below. Training time is the total GPU time required for training each model and power consumption is the peak power capacity per GPU device used, adjusted for power usage efficiency. \n\n## \n\n**Training Greenhouse Gas Emissions:** Estimated total location-based greenhouse gas emissions were **240** tons CO2eq for training. Since 2020, Meta has maintained net zero greenhouse gas emissions in its global operations and matched 100% of its electricity use with renewable energy; therefore, the total market-based greenhouse gas emissions for training were 0 tons CO2eq.\n\n| | Training Time (GPU hours) | Logit Generation Time (GPU Hours) | Training Power Consumption (W) | Training Location-Based Greenhouse Gas Emissions (tons CO2eq) | Training Market-Based Greenhouse Gas Emissions (tons CO2eq) |\n| :---- | :---: | ----- | :---: | :---: | :---: |\n| Llama-3.2-1B | 370k | \\- | 700 | 107 | 0 |\n| Llama-3.2-3B | 460k | \\- | 700 | 133 | 0 |\n| Total | 830k | 86k | | 240 | 0 |\n\nThe methodology used to determine training energy use and greenhouse gas emissions can be found [here](https://arxiv.org/pdf/2204.05149). Since Meta is openly releasing these models, the training energy use and greenhouse gas emissions will not be incurred by others.\n\n## Training Data\n\n**Data Collection Method:** Unknown \n**Labeling Method:** Unknown\n\n**Overview:** Llama 3.2 was pre-trained on up to 9 trillion tokens of data from publicly available sources. For the 1B and 3B Llama 3.2 models, we incorporated logits from the Llama 3.1 8B and 70B models into the pre-training stage of the model development, where outputs (logits) from these larger models were used as token-level targets. Knowledge distillation was used after pruning to recover performance. In post-training we used a similar recipe as Llama 3.1 and produced final chat models by doing several rounds of alignment on top of the pre-trained model. Each round involved Supervised Fine-Tuning (SFT), Rejection Sampling (RS), and Direct Preference Optimization (DPO).\n\n**Data Freshness:** The pre-training data has a cutoff of December 2023.\n\n## Benchmarks \\- English Text\n\nIn this section, we report the results for Llama 3.2 models on standard automatic benchmarks. For all these evaluations, we used our internal evaluations library. \n\n### Base Pre-trained Models \n\n| Category | Benchmark | \\# Shots | Metric | Llama-3.2-1B | Llama-3.2-3B | Llama-3.1-8B |\n| ----- | ----- | :---: | :---: | :---: | :---: | :---: |\n| General | MMLU | 5 | macro\\_avg/acc\\_char | 32.2 | 58 | 66.7 |\n| | AGIEval English | 3-5 | average/acc\\_char | 23.3 | 39.2 | 47.8 |\n| | ARC-Challenge | 25 | acc\\_char | 32.8 | 69.1 | 79.7 |\n| Reading comprehension | SQuAD | 1 | em | 49.2 | 67.7 | 77 |\n| | QuAC (F1) | 1 | f1 | 37.9 | 42.9 | 44.9 |\n| | DROP (F1) | 3 | f1 | 28.0 | 45.2 | 59.5 |\n| Long Context | Needle in Haystack | 0 | em | 96.8 | 1 | 1 |\n\n### Instruction-Tuned Models\n\n| Capability | | Benchmark | \\# Shots | Metric | Llama-3.2-1B-Instruct | Llama-3.2-3B-Instruct | Llama-3.1-8B-Instruct |\n| :---: | ----- | :---: | :---: | :---: | :---: | :---: | :---: |\n| General | | MMLU | 5 | macro\\_avg/acc | 49.3 | 63.4 | 69.4 |\n| Re-writing | | Open-rewrite eval | 0 | micro\\_avg/rougeL | 41.6 | 40.1 | 40.9 |\n| Summarization | | TLDR9+ (test) | 1 | rougeL | 16.8 | 19.0 | 17.2 |\n| Instruction following | | IFEval | 0 | Avg(Prompt/Instruction acc Loose/Strict) | 59.5 | 77.4 | 80.4 |\n| Math | | GSM8K (CoT) | 8 | em\\_maj1@1 | 44.4 | 77.7 | 84.5 |\n| | | MATH (CoT) | 0 | final\\_em | 30.6 | 48.0 | 51.9 |\n| Reasoning | | ARC-C | 0 | acc | 59.4 | 78.6 | 83.4 |\n| | | GPQA | 0 | acc | 27.2 | 32.8 | 32.8 |\n| | | Hellaswag | 0 | acc | 41.2 | 69.8 | 78.7 |\n| Tool Use | | BFCL V2 | 0 | acc | 25.7 | 67.0 | 67.1 |\n| | | Nexus | 0 | macro\\_avg/acc | 13.5 | 34.3 | 38.5 |\n| Long Context | | InfiniteBench/En.QA | 0 | longbook\\_qa/f1 | 20.3 | 19.8 | 27.3 |\n| | | InfiniteBench/En.MC | 0 | longbook\\_choice/acc | 38.0 | 63.3 | 72.2 |\n| | | NIH/Multi-needle | 0 | recall | 75.0 | 84.7 | 98.8 |\n| Multilingual | | MGSM (CoT) | 0 | em | 24.5 | 58.2 | 68.9 |\n\n### Multilingual Benchmarks\n\n| Category | Benchmark | Language | Llama-3.2-1B-Instruct | Llama-3.2-3B-Instruct | Llama-3.1-8B-Instruct |\n| :---: | :---: | :---: | :---: | :---: | :---: |\n| General | MMLU (5-shot, macro\\_avg/acc) | Portuguese | 39.82 | 54.48 | 62.12 |\n| | | Spanish | 41.52 | 55.09 | 62.45 |\n| | | Italian | 39.79 | 53.77 | 61.63 |\n| | | German | 39.20 | 53.29 | 60.59 |\n| | | French | 40.47 | 54.59 | 62.34 |\n| | | Hindi | 33.51 | 43.31 | 50.88 |\n| | | Thai | 34.67 | 44.54 | 50.32 |\n\n## Inference\n\n**Supported Hardware Microarchitecture Compatibility:**\n- NVIDIA Ampere\n- NVIDIA Hopper\n- NVIDIA Lovelace\n- NVIDIA Jetson\n\n**Supported Operating System(s):**\n- Linux \n- Windows\n\n## Responsibility \u0026 Safety\n\nAs part of our Responsible release approach, we followed a three-pronged strategy to managing trust \u0026 safety risks:\n\n1. Enable developers to deploy helpful, safe and flexible experiences for their target audience and for the use cases supported by Llama \n2. Protect developers against adversarial users aiming to exploit Llama capabilities to potentially cause harm \n3. Provide protections for the community to help prevent the misuse of our models\n\n### Responsible Deployment \n\n**Approach:** Llama is a foundational technology designed to be used in a variety of use cases. Examples on how Meta’s Llama models have been responsibly deployed can be found in our [Community Stories webpage](https://llama.meta.com/community-stories/). Our approach is to build the most helpful models, enabling the world to benefit from the technology power, by aligning our model safety for generic use cases and addressing a standard set of harms. Developers are then in the driver’s seat to tailor safety for their use cases, defining their own policies and deploying the models with the necessary safeguards in their Llama systems. Llama 3.2 was developed following the best practices outlined in our [Responsible Use Guide](https://llama.meta.com/responsible-use-guide/). \n\n#### Llama 3.2 Instruct \n\n**Objective:** Our main objectives for conducting safety fine-tuning are to provide the research community with a valuable resource for studying the robustness of safety fine-tuning, as well as to offer developers a readily available, safe, and powerful model for various applications to reduce the developer workload to deploy safe AI systems. We implemented the same set of safety mitigations as in Llama 3, and you can learn more about these in the Llama 3 [paper](https://ai.meta.com/research/publications/the-llama-3-herd-of-models/). \n\n**Fine-Tuning Data:** We employ a multi-faceted approach to data collection, combining human-generated data from our vendors with synthetic data to mitigate potential safety risks. We’ve developed many large language model (LLM)-based classifiers that enable us to thoughtfully select high-quality prompts and responses, enhancing data quality control. \n\n**Refusals and Tone:** Building on the work we started with Llama 3, we put a great emphasis on model refusals to benign prompts as well as refusal tone. We included both borderline and adversarial prompts in our safety data strategy, and modified our safety data responses to follow tone guidelines. \n\n#### Llama 3.2 Systems\n\n**Safety as a System:** Large language models, including Llama 3.2, **are not designed to be deployed in isolation** but instead should be deployed as part of an overall AI system with additional safety guardrails as required. Developers are expected to deploy system safeguards when building agentic systems. Safeguards are key to achieve the right helpfulness-safety alignment as well as mitigating safety and security risks inherent to the system and any integration of the model or system with external tools. As part of our responsible release approach, we provide the community with [safeguards](https://llama.meta.com/trust-and-safety/) that developers should deploy with Llama models or other LLMs, including Llama Guard, Prompt Guard and Code Shield. All our [reference implementations](https://github.com/meta-llama/llama-agentic-system) demos contain these safeguards by default so developers can benefit from system-level safety out-of-the-box. \n\n### New Capabilities and Use Cases\n\n**Technological Advancement:** Llama releases usually introduce new capabilities that require specific considerations in addition to the best practices that generally apply across all Generative AI use cases. For prior release capabilities also supported by Llama 3.2, see [Llama 3.1 Model Card](https://github.com/meta-llama/llama-models/blob/main/models/llama3_1/MODEL_CARD.md), as the same considerations apply here as well.\n\n**Constrained Environments:** Llama 3.2 1B and 3B models are expected to be deployed in highly constrained environments, such as mobile devices. LLM Systems using smaller models will have a different alignment profile and safety/helpfulness tradeoff than more complex, larger systems. Developers should ensure the safety of their system meets the requirements of their use case. We recommend using lighter system safeguards for such use cases, like Llama Guard 3-1B or its mobile-optimized version. \n\n### Evaluations\n\n**Scaled Evaluations:** We built dedicated, adversarial evaluation datasets and evaluated systems composed of Llama models and Purple Llama safeguards to filter input prompt and output response. It is important to evaluate applications in context, and we recommend building dedicated evaluation dataset for your use case.\n\n**Red Teaming:** We conducted recurring red teaming exercises with the goal of discovering risks via adversarial prompting and we used the learnings to improve our benchmarks and safety tuning datasets. We partnered early with subject-matter experts in critical risk areas to understand the nature of these real-world harms and how such models may lead to unintended harm for society. Based on these conversations, we derived a set of adversarial goals for the red team to attempt to achieve, such as extracting harmful information or reprogramming the model to act in a potentially harmful capacity. The red team consisted of experts in cybersecurity, adversarial machine learning, responsible AI, and integrity in addition to multilingual content specialists with background in integrity issues in specific geographic markets.\n\n### Critical Risks \n\nIn addition to our safety work above, we took extra care on measuring and/or mitigating the following critical risk areas:\n\n**1\\. CBRNE (Chemical, Biological, Radiological, Nuclear, and Explosive Weapons):** Llama 3.2 1B and 3B models are smaller and less capable derivatives of Llama 3.1. For Llama 3.1 70B and 405B, to assess risks related to proliferation of chemical and biological weapons, we performed uplift testing designed to assess whether use of Llama 3.1 models could meaningfully increase the capabilities of malicious actors to plan or carry out attacks using these types of weapons and have determined that such testing also applies to the smaller 1B and 3B models. \n\n**2\\. Child Safety:** Child Safety risk assessments were conducted using a team of experts, to assess the model’s capability to produce outputs that could result in Child Safety risks and inform on any necessary and appropriate risk mitigations via fine tuning. We leveraged those expert red teaming sessions to expand the coverage of our evaluation benchmarks through Llama 3 model development. For Llama 3, we conducted new in-depth sessions using objective based methodologies to assess the model risks along multiple attack vectors including the additional languages Llama 3 is trained on. We also partnered with content specialists to perform red teaming exercises assessing potentially violating content while taking account of market specific nuances or experiences. \n\n**3\\. Cyber Attacks:** Our cyber attack uplift study investigated whether LLMs can enhance human capabilities in hacking tasks, both in terms of skill level and speed. Our attack automation study focused on evaluating the capabilities of LLMs when used as autonomous agents in cyber offensive operations, specifically in the context of ransomware attacks. This evaluation was distinct from previous studies that considered LLMs as interactive assistants. The primary objective was to assess whether these models could effectively function as independent agents in executing complex cyber-attacks without human intervention.\n\n### Community \n\n**Industry Partnerships:** Generative AI safety requires expertise and tooling, and we believe in the strength of the open community to accelerate its progress. We are active members of open consortiums, including the AI Alliance, Partnership on AI and MLCommons, actively contributing to safety standardization and transparency. We encourage the community to adopt taxonomies like the MLCommons Proof of Concept evaluation to facilitate collaboration and transparency on safety and content evaluations. Our Purple Llama tools are open sourced for the community to use and widely distributed across ecosystem partners including cloud service providers. We encourage community contributions to our [Github repository](https://github.com/meta-llama/PurpleLlama).\n\n**Grants:** We also set up the [Llama Impact Grants](https://llama.meta.com/llama-impact-grants/) program to identify and support the most compelling applications of Meta’s Llama model for societal benefit across three categories: education, climate and open innovation. The 20 finalists from the hundreds of applications can be found [here](https://llama.meta.com/llama-impact-grants/#finalists). \n\n**Reporting:** Finally, we put in place a set of resources including an [output reporting mechanism](https://developers.facebook.com/llama_output_feedback) and [bug bounty program](https://www.facebook.com/whitehat) to continuously improve the Llama technology with the help of the community.\n\n## Ethical Considerations and Limitations\n\n**Values:** The core values of Llama 3.2 are openness, inclusivity and helpfulness. It is meant to serve everyone, and to work for a wide range of use cases. It is thus designed to be accessible to people across many different backgrounds, experiences and perspectives. Llama 3.2 addresses users and their needs as they are, without insertion unnecessary judgment or normativity, while reflecting the understanding that even content that may appear problematic in some cases can serve valuable purposes in others. It respects the dignity and autonomy of all users, especially in terms of the values of free thought and expression that power innovation and progress. \n\n**Testing:** Llama 3.2 is a new technology, and like any new technology, there are risks associated with its use. Testing conducted to date has not covered, nor could it cover, all scenarios. For these reasons, as with all LLMs, Llama 3.2’s potential outputs cannot be predicted in advance, and the model may in some instances produce inaccurate, biased or other objectionable responses to user prompts. Therefore, before deploying any applications of Llama 3.2 models, developers should perform safety testing and tuning tailored to their specific applications of the model. Please refer to available resources including our [Responsible Use Guide](https://llama.meta.com/responsible-use-guide), [Trust and Safety](https://llama.meta.com/trust-and-safety/) solutions, and other [resources](https://llama.meta.com/docs/get-started/) to learn more about responsible development. \n\nNVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their internal model team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse.\nPlease report security vulnerabilities or NVIDIA AI Concerns [here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/)."])</script><script>self.__next_f.push([1,"4a:T4bd,from openai import OpenAI\n\nclient = OpenAI(\n base_url = \"https://integrate.api.nvidia.com/v1\",\n api_key = \"$NVIDIA_API_KEY\"\n)\n\u003c% if (request.tools) { %\u003e\ncompletion = client.chat.completions.create(\n model=\"\u003c%- request.model %\u003e\",\n messages=\u003c%- JSON.stringify(request.messages) %\u003e,\n temperature=\u003c%- request.temperature %\u003e,\n top_p=\u003c%- request.top_p %\u003e,\n max_tokens=\u003c%- request.max_tokens %\u003e,\n stream=\u003c%- request.stream?.toString()[0].toUpperCase() + request.stream?.toString().slice(1) %\u003e,\n tools=\u003c%- JSON.stringify(request.tools) %\u003e,\n \u003c% if (request.tool_choice) { %\u003etool_choice=\u003c%- JSON.stringify(request.tool_choice) %\u003e\u003c% } %\u003e\n)\u003c% } else { %\u003e\ncompletion = client.chat.completions.create(\n model=\"\u003c%- request.model %\u003e\",\n messages=\u003c%- JSON.stringify(request.messages) %\u003e,\n temperature=\u003c%- request.temperature %\u003e,\n top_p=\u003c%- request.top_p %\u003e,\n max_tokens=\u003c%- request.max_tokens %\u003e,\n stream=\u003c%- request.stream?.toString()[0].toUpperCase() + request.stream?.toString().slice(1) %\u003e\n)\u003c% } %\u003e\n\u003c% if (request.stream) { %\u003e\nfor chunk in completion:\n if chunk.choices[0].delta.content is not None:\n print(chunk.choices[0].delta.content, end=\"\")\n\u003c% } else { %\u003e\nprint(completion.choices[0].message)\n\u003c% } %\u003e\n4b:T504,import OpenAI from 'openai';\n\nconst openai = new OpenAI({\n apiKey: '$NVIDIA_API_KEY',\n baseURL: 'https://integrate.api.nvidia.com/v1',\n})\n \u003c% if (request.tools) { %\u003e\nasync function main() {\n const completion = await openai.chat.completions.create({\n model: \"\u003c%- request.model %\u003e\",\n messages: \u003c%- JSON.stringify(request.messages) %\u003e,\n temperature: \u003c%- request.temperature %\u003e,\n top_p: \u003c%- request.top_p %\u003e,\n max_tokens: \u003c%- request.max_tokens %\u003e,\n stream: \u003c%- request.stream %\u003e,\n \u003c% if (request.tools) { %\u003etools: \u003c%- JSON.stringify(request.tools) %\u003e,\u003c% } %\u003e\n \u003c% if (request.tool_choice) { %\u003etool_choice: \u003c%- JSON.stringify(request.tool_choice) %\u003e,\u003c% } %\u003e\n })\u003c% } else { %\u003e\nasync function main() {\n const completion = await openai.chat.completions.create({\n model: \"\u003c%- request.model %\u003e\",\n "])</script><script>self.__next_f.push([1," messages: \u003c%- JSON.stringify(request.messages) %\u003e,\n temperature: \u003c%- request.temperature %\u003e,\n top_p: \u003c%- request.top_p %\u003e,\n max_tokens: \u003c%- request.max_tokens %\u003e,\n stream: \u003c%- request.stream %\u003e\n })\u003c% } %\u003e\n \u003c% if (request.stream) { %\u003e\n for await (const chunk of completion) {\n process.stdout.write(chunk.choices[0]?.delta?.content || '')\n }\n \u003c% } else { %\u003e\n process.stdout.write(completion.choices[0]?.message?.content);\n \u003c% } %\u003e\n}\n\nmain();4c:T66d,\u003c% if (request.tools) { %\u003e\n \"curl https://integrate.api.nvidia.com/v1/chat/completions \\\\\\n\n -H \\\"Content-Type: application/json\\\" \\\\\\n\n -H \\\"Authorization: Bearer $NVIDIA_API_KEY\\\" \\\\\\n\n -d '{\\n\n \\\"model\\\": \\\"meta/llama-3.2-3b-instruct\\\",\\n\n \\\"messages\\\": \u003c%- JSON.stringify(request.messages).replaceAll(\\\"'\\\", \\\"'\\\\\\\"'\\\\\\\"'\\\") %\u003e,\\n\n \\\"temperature\\\": \u003c%- request.temperature %\u003e,\\n\n \\\"top_p\\\": \u003c%- request.top_p %\u003e,\\n\n \\\"max_tokens\\\": \u003c%- request.max_tokens %\u003e,\\n\n \\\"stream\\\": \u003c%- request.stream %\u003e\n \u003c% if (request.tools) { %\u003e,\\n \\\"tools\\\": \u003c%- JSON.stringify(request.tools).replaceAll(\\\"'\\\", \\\"'\\\\\\\"'\\\\\\\"'\\\") %\u003e\u003c% } %\u003e\n \u003c% if (request.tool_choice) { %\u003e,\\n \\\"tool_choice\\\": \u003c%- JSON.stringify(request.tool_choice).replaceAll(\\\"'\\\", \\\"'\\\\\\\"'\\\\\\\"'\\\") %\u003e\u003c% } %\u003e\n }'\\n\"\u003c% } else { %\u003e\n \"curl https://integrate.api.nvidia.com/v1/chat/completions \\\\\\n\n -H \\\"Content-Type: application/json\\\" \\\\\\n\n -H \\\"Authorization: Bearer $NVIDIA_API_KEY\\\" \\\\\\n\n -d '{\\n\n \\\"model\\\": \\\"meta/llama-3.2-3b-instruct\\\",\\n\n \\\"messages\\\": \u003c%- JSON.stringify(request.messages).replaceAll(\\\"'\\\", \\\"'\\\\\\\"'\\\\\\\"'\\\") %\u003e,\\n\n \\\"temperature\\\": \u003c%- request.temperature %\u003e,\\n\n \\\"top_p\\\": \u003c%- request.top_p %\u003e,\\n\n \\\"max_tokens\\\": \u003c%- request.max_tokens %\u003e,\\n\n \\\"stream\\\": \u003c%- request.stream %\u003e\n \u003c% if (request.tools) { %\u003e,\\n \\\"tools\\\": \u003c%- JSON.stringify(request.tools).replaceAll(\\\"'\\\", \\\"'\\\\\\\"'\\\\\\\"'\\\") %\u003e\u003c% } %\u003e\n \u003c% if (request.tool_choice) { %\u003e,\\n \\\"tool_choice\\\": \u003c%- JSON.stringify(request.tool"])</script><script>self.__next_f.push([1,"_choice).replaceAll(\\\"'\\\", \\\"'\\\\\\\"'\\\\\\\"'\\\") %\u003e\u003c% } %\u003e\n }'\\n\"\u003c% } %\u003e4d:T472,|Field:|Response:|\n|:---:|:---:|\n|Generatable or Reverse engineerable personally-identifiable information?|None|\n|Personal dataused to create this model?|None Known|\n|Was consent obtained for any personal data used?|Not Applicable|\n|How often is dataset reviewed?|Before Release|\n|Is a mechanism in place to honor data subject right of access or deletion of personal data?|Not Applicable|\n|If personal data collected for the development of the model, was it collected by NVIDIA?|Not Applicable|\n|If personal data collected for the development of the model by NVIDIA, do you maintain or have access to disclosures made to data subjects?|Not Applicable|\n|If personal data collected for the development of this AI model, was it minimized to only what was required?|Not Applicable|\n|Is there provenance for all datasets used in training?|Yes|\n|Does data labeling (annotation, metadata) comply with privacy laws?|Not Applicable|\n|Is data compliant with data subject requests for data correction or removal, if such a request was made?|Not Applicable|\n|Applicable NVIDIA Privacy Policy|https://www.nvidia.com/en-us/about-nvidia/privacy-policy/|4e:T2035,"])</script><script>self.__next_f.push([1,"## Nemotron-4-340B-Reward\n\n### Model Overview\n\nThe Nemotron-4-340B-Reward is a multi-dimensional Reward Model that can be used as part of a synthetic data generation pipeline to create training data that helps researchers and developers build their own LLMs; Nemotron-4-340B-Reward consists of the Nemotron-4-340B-Base model and a linear layer that converts the final layer representation of the end-of-response token into five scalar values, each corresponding to a [HelpSteer2](https://arxiv.org/abs/2406.08673) attribute. \n\nIt supports a context length of up to 4,096 tokens.\n\nGiven a conversation with multiple turns between user and assistant, it rates the following attributes (typically between 0 and 4) for every assistant turn.\n\n1. **Helpfulness**: Overall helpfulness of the response to the prompt.\n2. **Correctness**: Inclusion of all pertinent facts without errors. \n3. **Coherence**: Consistency and clarity of expression. \n4. **Complexity**: Intellectual depth required to write response (i.e. whether the response can be written by anyone with basic language competency or requires deep domain expertise).\n5. **Verbosity**: Amount of detail included in the response, relative to what is asked for in the prompt.\n\nNonetheless, if you are only interested in using it as a conventional reward model that outputs a singular scalar, we recommend using the weights ```[0, 0, 0, 0, 0.3, 0.74, 0.46, 0.47, -0.33]``` to do elementwise multiplication with the predicted attributes (which outputs 9 float values in line with [Llama2-13B-SteerLM-RM](https://huggingface.co/nvidia/Llama2-13B-SteerLM-RM) but the first four are not trained or used)\n\nUnder the NVIDIA Open Model License, NVIDIA confirms: \n\n* Models are commercially usable. \n* You are free to create and distribute Derivative Models. \n* NVIDIA does not claim ownership to any outputs generated using the Models or Derivative Models.\n\n### License: \n\n[NVIDIA Open Model License](https://developer.download.nvidia.com/licenses/nvidia-open-model-license-agreement-june-2024.pdf)\n\n### Intended use\n\nNemotron-4 340B Reward Model is a pretrained Reward Model intended for use in English Synthetic Data Generation and English Reinforcement Learning from AI Feedback (RLAIF).\n\nNemotron-4 340B-Reward can be used in the alignment stage to align pretrained models to human preferences. It can also be used in cases like Reward-Model-as-a-Judge.\n\n**Model Developer:** NVIDIA\n\n**Model Input:** Text only \n**Input Format:** String \n\n**Model Output:** Scalar Values (List of 9 Floats) \n**Output Format:** Float \n\n**Model Dates:** Nemotron-4-340B-Reward was trained between December 2023 and May 2024\n\n**Data Freshness:** The pretraining data has a cutoff of June 2023\n\n### Required Hardware\n\nBF16 Inference:\n- 16x H100 (2x H100 Nodes)\n- 16x A100 (2x A100 80GB Nodes)\n\n### Usage:\n\nYou can use the model with [NeMo Aligner](https://github.com/NVIDIA/NeMo-Aligner) following [SteerLM training user guide](https://docs.nvidia.com/nemo-framework/user-guide/latest/modelalignment/steerlm.html).\n\n1. Spin up an inference server within the [NeMo Aligner container](https://github.com/NVIDIA/NeMo-Aligner/blob/main/Dockerfile)\n\n```\npython /opt/NeMo-Aligner/examples/nlp/gpt/serve_reward_model.py \\\n rm_model_file=Nemotron-4-340B-Reward \\\n trainer.num_nodes=2 \\\n trainer.devices=8 \\\n ++model.tensor_model_parallel_size=8 \\\n ++model.pipeline_model_parallel_size=2 \\\n inference.micro_batch_size=2 \\\n inference.port=1424\n```\n\n2. Annotate data files using the served reward model. As an example, this can be the Open Assistant train/val files. Then follow the next step to train a SteerLM model based on [SteerLM training user guide](https://docs.nvidia.com/nemo-framework/user-guide/latest/modelalignment/steerlm.html#step-5-train-the-attribute-conditioned-sft-model) .\n\n```\npython /opt/NeMo-Aligner/examples/nlp/data/steerlm/preprocess_openassistant_data.py --output_directory=data/oasst\n\npython /opt/NeMo-Aligner/examples/nlp/data/steerlm/attribute_annotate.py \\\n --input-file=data/oasst/train.jsonl \\\n --output-file=data/oasst/train_labeled.jsonl \\\n --port=1424\n```\n\n3. Alternatively, this can be any conversational data file (in .jsonl) in the following format, where each line looks like \n\n```\n{\n \"conversations\": [\n {\"value\": \u003cuser_turn_1\u003e, \"from\": \"User\", \"label\": None},\n {\"value\": \u003cassistant_turn_1\u003e, \"from\": \"Assistant\", \"label\": \u003cformatted_label_1\u003e},\n {\"value\": \u003cuser_turn_2\u003e, \"from\": \"User\", \"label\": None},\n {\"value\": \u003cassistant_turn_2\u003e, \"from\": \"Assistant\", \"label\": \u003cformatted_label_2\u003e},\n ],\n \"mask\": \"User\"\n}\n```\n\nIdeally, each ```\u003cformatted_label_n\u003e``` refers to the ground truth label for the assistant turn but if they are not available, we can also use ```helpfulness:4,correctness:4,coherence:4,complexity:2,verbosity:2``` (i.e. defaulting to moderate complexity and verbosity, adjust if needed. or simply ```helpfulness:-1```. It must not be ```None``` or an empty string.\n\n\n### Model Architecture:\n\nNemotron-4-340B-Reward is extended from Nemotron-4-340B-Base with an additional linear layer. It was trained with a global batch-size of 128. \n\n**Architecture Type:** Transformer Decoder (auto-regressive language model)\n\n### Intended use\n\nNemotron-4-340B-Reward is a pretrained Reward Model intended for use in English Synthetic Data Generation and English Reinforcement Learning from AI Feedback (RLAIF).\n\n### Dataset \u0026 Training\n\nNemotron-4-340B-Reward was trained for 2 epochs using the NVIDIA [HelpSteer2](https://arxiv.org/abs/2406.08673) data. The HelpSteer2 dataset is a permissively licensed preference dataset (CC-by-4.0) with ten thousand English response pairs and can be found [here](https://huggingface.co/datasets/nvidia/HelpSteer2).\n\n### Evaluation Results\n\n#### Reward Bench Primary Dataset\n\nEvaluated using RewardBench - as introduced in the paper [RewardBench: Evaluating Reward Models for Language Modeling](https://arxiv.org/abs/2403.13787).\n\n| Overall | Chat | Chat-Hard | Safety | Reasoning |\n| --------- | ------- | -------------- | --------- | -------------- |\n| 92.0 | 95.8 | 87.1 | 91.5 | 93.7 | \n\n\n### Limitations\n\nThis model was trained using an English dataset, and as such its use is optimized for English language use cases. In order to extend this model to other language domains, fine-tuning will be required.\n\n### Ethical Considerations:\n\nNVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their internal model team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse. For more detailed information on ethical considerations for this model, please see the Model Card++ Explainability, Bias, Safety \u0026 Security, and Privacy Subcards [here](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/nemo/models/nemotron-4-340b-reward). Please report security vulnerabilities or NVIDIA AI Concerns [here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/). \n\n\n### Citation\n\nIf you find this model useful, please cite the following works\n\n```bibtex\n@misc{wang2024helpsteer2,\n title={HelpSteer2: Open-source dataset for training top-performing reward models}, \n author={Zhilin Wang and Yi Dong and Olivier Delalleau and Jiaqi Zeng and Gerald Shen and Daniel Egert and Jimmy J. Zhang and Makesh Narsimhan Sreedhar and Oleksii Kuchaiev},\n year={2024},\n eprint={2406.08673},\n archivePrefix={arXiv},\n primaryClass={id='cs.CL' full_name='Computation and Language' is_active=True alt_name='cmp-lg' in_archive='cs' is_general=False description='Covers natural language processing. Roughly includes material in ACM Subject Class I.2.7. Note that work on artificial languages (programming languages, logics, formal systems) that does not explicitly address natural-language issues broadly construed (natural-language processing, computational linguistics, speech, text retrieval, etc.) is not appropriate for this area.'}\n}\n```"])</script><script>self.__next_f.push([1,"4f:T42c,|Field:|Response:|\n|:---:|:---:|\n|Intended Application(s) \u0026 Domain(s):|Large Language Model Development|\n|Model Type:|Generative Pre-Trained Transformer (GPT)|\n|Intended Users:|This model is intended for developers and researchers building LLMs.|\n|Output:|Scalar Values (List of 9 Floats)|\n|Describe how the model works:|The network architecture of this model is Nemotron-4 Reward. The decoder in Nemotron-4 generates a list of 5 floating point numbers associated with the 5 HelpSteer2 Dataset (Helpfulness, Correctness, Coherence, Complexity, Verbosity) based on the end-of-response token from the final layer of the model.|\n|Technical Limitations:|The model was trained on English preference data and has not been tested on non-English use-cases.|\n|Verified to have met prescribed quality standards?|Yes|\n|Performance Metrics:|Accuracy, Throughput, and Latency|\n|Potential Known Risks:|The Model may produce scores that are biased or incorrect based on the provided prompt and the user’s preferences.|\n|End User License Agreement:|Please see detailed model cards.|50:T436,{\n \"id\": \"id-123\",\n \"choices\": [\n {\n \"index\": 0,\n \"message\": [\n {\n \"content\": \"helpfulness:1.6171875,correctness:1.6484375,coherence:3.3125,complexity:0.546875,verbosity:0.515625\",\n \"role\": \"assistant\"\n }\n ],\n \"logprobs\": {\n \"content\": [\n {\n \"token\": \"helpfulness\",\n \"logprob\": 1.6171875,\n \"top_logprobs\": []\n },\n {\n \"token\": \"correctness\",\n \"logprob\": 1.6484375,\n \"top_logprobs\": []\n },\n {\n \"token\": \"coherence\",\n \"logprob\": 3.3125,\n \"top_logprobs\": []\n },\n {\n \"token\": \"complexity\",\n \"logprob\": 0.546875,\n \"top_logprobs\": []\n },\n {\n \"token\": \"verbosity\",\n \"logprob\": 0.515625,\n \"top_logprobs\": []\n }\n ]\n },\n \"finish_reason\": \""])</script><script>self.__next_f.push([1,"length\"\n }\n ],\n \"usage\": {\n \"completion_tokens\": 1,\n \"prompt_tokens\": 78,\n \"total_tokens\": 79\n }\n}\n51:T442,{\n \"id\": \"id-123\",\n \"choices\": [\n {\n \"index\": 0,\n \"message\": [\n {\n \"content\": \"helpfulness:2.09375,correctness:2.046875,coherence:3.546875,complexity:0.373046875,verbosity:0.287109375\",\n \"role\": \"assistant\"\n }\n ],\n \"logprobs\": {\n \"content\": [\n {\n \"token\": \"helpfulness\",\n \"logprob\": 2.09375,\n \"top_logprobs\": []\n },\n {\n \"token\": \"correctness\",\n \"logprob\": 2.046875,\n \"top_logprobs\": []\n },\n {\n \"token\": \"coherence\",\n \"logprob\": 3.546875,\n \"top_logprobs\": []\n },\n {\n \"token\": \"complexity\",\n \"logprob\": 0.373046875,\n \"top_logprobs\": []\n },\n {\n \"token\": \"verbosity\",\n \"logprob\": 0.287109375,\n \"top_logprobs\": []\n }\n ]\n },\n \"finish_reason\": \"length\"\n }\n ],\n \"usage\": {\n \"completion_tokens\": 1,\n \"prompt_tokens\": 103,\n \"total_tokens\": 104\n }\n}\n52:T440,{\n \"id\": \"id-123\",\n \"choices\": [\n {\n \"index\": 0,\n \"message\": [\n {\n \"content\": \"helpfulness:0.2578125,correctness:0.13671875,coherence:2.640625,complexity:0.328125,verbosity:0.04296875\",\n \"role\": \"assistant\"\n }\n ],\n \"logprobs\": {\n \"content\": [\n {\n \"token\": \"helpfulness\",\n \"logprob\": 0.2578125,\n \"top_logprobs\": []\n },\n {\n \"token\": \"correctness\",\n \"logprob\": 0.13671875,\n \"top_logprobs\": []\n },\n {\n \"token\": \"coherence\",\n \"logprob\": 2.640625,\n \"top_logprobs\": []\n },\n {\n \"token\": \"complexity\",\n \"logprob\": 0.328125,\n \"top_logprobs\": []\n },\n {\n "])</script><script>self.__next_f.push([1," \"token\": \"verbosity\",\n \"logprob\": 0.04296875,\n \"top_logprobs\": []\n }\n ]\n },\n \"finish_reason\": \"length\"\n }\n ],\n \"usage\": {\n \"completion_tokens\": 1,\n \"prompt_tokens\": 67,\n \"total_tokens\": 68\n }\n}\n53:T5777,"])</script><script>self.__next_f.push([1,"## Model Information\n\nThe Meta Llama 3.1 collection of multilingual large language models (LLMs) is a collection of pretrained and instruction tuned generative models in 8B, 70B and 405B sizes (text in/text out). The Llama 3.1 instruction tuned text only models (8B, 70B, 405B) are optimized for multilingual dialogue use cases and outperform many of the available open source and closed chat models on common industry benchmarks.\n\n**Model Developer**: Meta\n\n## Llama 3.1 Systems\n\n**Large language models, including Llama 3.1, are not designed to be deployed in isolation but instead should be deployed as part of an overall AI system with additional safety guardrails as required.** Developers are expected to deploy system safeguards when building agentic systems. Safeguards are key to achieve the right helpfulness-safety alignment as well as mitigating safety and security risks inherent to the system and any integration of the model or system with external tools. \nAs part of our responsible release approach, we provide the community with [safeguards](https://llama.meta.com/trust-and-safety/) that developers should deploy with Llama models or other LLMs, including Llama Guard 3, Prompt Guard and Code Shield. All our [reference implementations](https://github.com/meta-llama/llama-agentic-system) demos contain these safeguards by default so developers can benefit from system-level safety out-of-the-box.\n\n## Intended Use\n\n**Intended Use Cases** Llama 3.1 is intended for commercial and research use in multiple languages. Instruction tuned text only models are intended for assistant-like chat, whereas pretrained models can be adapted for a variety of natural language generation tasks. The Llama 3.1 model collection also supports the ability to leverage the outputs of its models to improve other models including synthetic data generation and distillation. The Llama 3.1 Community License allows for these use cases.\n\n**Out-of-scope** Use in any manner that violates applicable laws or regulations (including trade compliance laws). Use in any other way that is prohibited by the Acceptable Use Policy and Llama 3.1 Community License. Use in languages beyond those explicitly referenced as supported in this model card**. \n\n**Note: Llama 3.1 has been trained on a broader collection of languages than the 10 supported languages. \n\nDevelopers may fine-tune Llama 3.1 models for languages beyond the 8 supported languages provided they comply with the Llama 3.1 Community License and the Acceptable Use Policy and in such cases are responsible for ensuring that any uses of Llama 3.1 in additional languages is done in a safe and responsible manner.\n\n\n## New Capabilities\n\nNote that this release introduces new capabilities, including a longer context window, multilingual inputs and outputs and possible integrations by developers with third party tools. Building with these new capabilities requires specific considerations in addition to the best practices that generally apply across all Generative AI use cases. \n\n**Tool-use:** Just like in standard software development, developers are responsible for the integration of the LLM with the tools and services of their choice. They should define a clear policy for their use case and assess the integrity of the third party services they use to be aware of the safety and security limitations when using this capability. Refer to the Responsible Use Guide for best practices on the safe deployment of the third party safeguards. \n\n**Multilinguality:** Llama 3.1 supports 7 languages in addition to English: French, German, Hindi, Italian, Portuguese, Spanish, and Thai. Llama may be able to output text in other languages than those that meet performance thresholds for safety and helpfulness. We strongly discourage developers from using this model to converse in non-supported languages without implementing finetuning and system controls in alignment with their policies and the best practices shared in the Responsible Use Guide.\n\n**Model Architecture:** Llama 3.1 is an auto-regressive language model that uses an optimized transformer architecture. The tuned versions use supervised fine-tuning (SFT) and reinforcement learning with human feedback\n(RLHF) to align with human preferences for helpfulness and safety.\n\n| | Training Data | Params | Input modalities | Output modalities | Context Length | GQA | Token count | Knowledge cutoff |\n|-|-|-----------------------|----------------------------------------------|-----------------------|---------------------|-----------------------|-------|---------------|\n| | | 8B | Multilingual Text | Multilingual Text and code| 128k | Yes | 15T+ | December 2023 |\n| Llama 3.1 (text only) | A new mix of publicly available online data. | 70B | Multilingual Text | Multilingual Text and code| 128k | Yes | 15T+ | December 2023 |\n| | | 405B | Multilingual Text | Multilingual Text and code| 128k | Yes | 15T+ | December 2023 |\n\n**Supported languages:** English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai.\n\n**Llama 3.1 family of models**. Token counts refer to pretraining data only. All model versions use Grouped-Query Attention (GQA) for improved inference scalability.\n\n**Model Release Date:** July 23, 2024. \n\n**Status:** This is a static model trained on an offline dataset. Future versions of the tuned models will be released as we improve model safety with community feedback. \n\n**License** A custom commercial license, the Llama 3.1 Community License, is available at: https://github.com/meta-llama/llama-models/blob/main/models/llama3_1/LICENSE \n\nWhere to send questions or comments about the model Instructions on how to provide feedback or comments on the model can be found in the model [README](https://github.com/meta-llama/llama3). For more technical information about generation parameters and recipes for how to use Llama 3.1 in applications, please go [here](ttps://github.com/meta-llama/llama-recipes).\n\n## Hardware And Software\n\n**Training Factors** We used custom training libraries, Meta's custom built GPU cluster, and production infrastructure for pretraining. Fine-tuning, annotation, and evaluation were also performed on production infrastructure. \n\n**Training Energy Use** Training utilized a cumulative of **39.3**M GPU hours of computation on H100-80GB (TDP of 700W) type hardware, per the table below. Training time is the total GPU time required for training each model and power consumption is the peak power capacity per GPU device used, adjusted for power usage efficiency.\n\n**Training Greenhouse Gas Emissions** Estimated total location-based greenhouse gas emissions were **11,390** tons CO2eq for training. Since 2020, Meta has maintained net zero greenhouse gas emissions in its global operations and matched 100% of its electricity use with renewable energy, therefore the total market-based greenhouse gas emissions for training were 0 tons CO2eq.\n\n| | Training Time (GPU hours) | Training Power Consumption (W) | Training Location-Based Greenhouse Gas Emissions (tons CO2eq) | Training Market-Based Greenhouse Gas Emissions (tons CO2eq) |\n| - |---------------------------------------|---------------------------------------|---------------------------|--------|\n| Llama 3.1 8B | 1.46M | 700 | 420 | 0 |\n| Llama 3.1 70B | 7.0M | 700 | 2,040 | 0 |\n| Llama 3.1 405B | 30.84M | 700 | 8,930 | 0 |\n| Total | 39.3M | - | 11,390 | 0 |\n\nThe methodology used to determine training energy use and greenhouse gas emissions can be found [here](https://arxiv.org/pdf/2204.05149). Since Meta is openly releasing these models, the training energy use and greenhouse gas emissions will not be incurred by others.\n\n## Training Data\n\n**Overview:** Llama 3.1 was pretrained on ~15 trillion tokens of data from publicly available sources. The fine-tuning data includes publicly available instruction datasets, as well as over 25M synthetically generated examples.\n\n**Data Freshness:** The pretraining data has a cutoff of December 2023.\n\n## Benchmarks - English Text\n\nIn this section, we report the results for Llama 3.1 models on standard automatic benchmarks. For all the evaluations, we use our internal evaluations library.\n\n### Base pretrained models\n| Category | Benchmark | # Shots | Metric | Llama 3 8B | Llama 3.1 8B | Llama 3 70B | Llama 3.1 70B | Llama 3.1 405B |\n|--------------------------|---------------|--------------------|----------|------------|--------------|-------------|---------------|----------------|\n| General | MMLU | 5 | macro_avg/acc_char | 66.7 | 66.7 | 79.5 | 79.3 | 85.2 | |\n| General | MMLU PRO (CoT) | 5 | macro_avg/acc_char | 36.2 | 37.1 | 55.0 | 53.8 | 61.6 | |\n| General | AGIEval English | 3-5 | average/acc_char | 47.1 | 47.8 | 63.0 | 64.6 | 71.6 | |\n| General | CommonSenseQA | 7 | acc_char | 72.6 | 75.0 | 83.8 | 84.1 | 85.8 |\n| General | Winogrande | 5 | acc_char | - | 60.5 | - | 83.3 | 86.7 | |\n| General | BIG-Bench Hard (CoT) | 3 | average/em | 61.1 | 64.2 | 81.3 | 81.6 | **85.9** | |\n| General | ARC-Challenge | 25 | acc_char | 79.4 | 79.7 | 93.1 | 92.9 | 96.1 | |\n| Knowledge reasoning | TriviaQA-Wiki | 5 | em | 78.5 | 77.6 | 89.7 | 89.8 | 91.8 |\n| Reading comprehension | SQuAD | 1 | em | 76.4 | 77.0 | 85.6 | 81.8 | 89.3 | |\n| Reading comprehension | QuAC (F1) | 1 | f1 | 44.4 | 44.9 | 51.1 | 51.1 | 53.6 | |\n| Reading comprehension | BoolQ | 0 | acc_char | 75.7 | 75.0 | 79.0 | 79.4 | 80.0 |\n| Reading comprehension | DROP (F1) | 3 | f1 | 58.4 | 59.5 | 79.7 | 79.6 | **84.8** | |\n\n### Instruction Tuned Models\n\n\n| Category | Benchmark | # Shots | Metric | Llama 3 8B Instruct | Llama 3.1 8B Instruct | Llama 3 70B Instruct | Llama 3.1 70B Instruct | Llama 3.1 405B Instruct | \n| --- | --- | --- | --- | --- | --- | --- | --- | --- | \n | General | MMLU | 5 | macro_avg/acc | 68.5 | 69.4 | 82.0 | 83.6 | 87.3 | \n | General | MMLU (CoT) | 0 | macro_avg/acc | 65.3 | 72.7 | 80.9 | 85.9 | 88.6 | \n | General | MMLU PRO (CoT) | 5 | micro_avg/acc_char | 45.5 | 48.3 | 63.4 | 65.1 | 73.3 | \n | Reasoning | ARC-C | 0 | acc | 82.4 | 83.4 | 94.4 | 94.8 | **96.9** | \n | Reasoning | GPQA | 0 | em | 34.6 | 30.4 | 39.5 | 41.7 | 50.7 | \n | Reasoning | MuSR | 0 | correct | 56.3 | 45.7 | 55.1 | 58.1 | 56.7 | \n | Steerability | IFEval | | | 76.8 | 80.4 | 82.9 | 87.5 | **88.6** | \n | Code | HumanEval | 0 | pass@1 | 60.4 | 72.6 | 81.7 | 80.5 | 89.0 | \n | Code | MBPP ++ base version | 0 | pass@1 | 70.6 | 72.8 | 82.5 | 86.0 | 88.6 | \n | Math | GSM-8K (CoT) | 8 | em_maj1@1 | 80.6 | 84.5 | 93.0 | 95.1 | 96.8 | \n | Math | MATH (CoT) | 0 | final_em | 29.1 | 51.9 | 51.0 | 68.0 | 73.8 | \n | Tool Use | API-Bank | 0 | acc | 83.6 | 82.6 | 85.1 | 90.0 | 92.0 | \n | Tool Use | Berkeley Function Calling | 0 | acc | 76.1 | 76.1 | 83.0 | 85.1 | **88.5** |\n | Tool Use | Gorilla Benchmark API Bench | 0 | acc | 8.8 | 8.2 | 14.7 | 29.7 | 35.3 | \n | Tool Use | Nexus (0-shot) | 0 | macro_avg/acc | 37.6 | 38.5 | 47.8 | 56.7 | **58.7** | \n | Multilingual | Multilingual MGSM | 8 | em | - | 68.2 | - | 85.6 | 90.3 |\n\n## Multilingual Benchmarks\n\n| Category | Benchmark | Language | Llama 3.1 8B | Llama 3.1 70B | Llama 3.1 405B | \n| --- | --- | --- | --- | --- | --- | \n| | | Portuguese | 62.12 | 80.13 | 84.95 |\n| | | Spanish | 62.45 | 80.05 | 85.08 |\n| | | Italian | 61.63 | 80.4 | 85.04 | \n| General | MMLU (5-shot, macro_avg/acc) | German | 60.59 | 79.27 | 84.36 | \n| | | French | 62.34 | 79.82 | 84.66 | \n| | | Hindi | 50.88 | 74.52 | 80.31 | \n| | | Thai | 50.32 | 72.95 | 78.21 |\n\n\n\n## Responsibility \u0026 Safety\n\nAs part of our Responsible release approach, we followed a three-pronged strategy to managing trust \u0026 safety risks:\n- Enable developers to deploy helpful, safe and flexible experiences for their target audience and for the use cases supported by Llama.\n\n- Protect developers against adversarial users aiming to exploit Llama capabilities to potentially cause harm.\n\n- Provide protections for the community to help prevent the misuse of our models.\n\n## Responsible Deployment\n\nLlama is a foundational technology designed to be used in a variety of use cases, examples on how Meta's Llama models have been responsibly deployed can be found in our [Community Stories webpage](https://llama.meta.com/community-stories/). Our approach is to build the most helpful models enabling the world to benefit from the technology power, by aligning our model safety for the generic use cases addressing a standard set of harms. Developers are then in the driver seat to tailor safety for their use case, defining their own policy and deploying the models with the necessary safeguards in their Llama systems. Llama 3.1 was developed following the best practices outlined in our Responsible Use Guide, you can refer to the [Responsible Use Guide](https://llama.meta.com/responsible-use-guide/) to learn more.\n\n## Llama 3.1 Instruct\n\nOur main objectives for conducting safety fine-tuning are to provide the research community with a valuable resource for studying the robustness of safety fine-tuning, as well as to offer developers a readily available, safe, and powerful model for various applications to reduce the developer workload to deploy safe AI systems. For more details on the safety mitigations implemented please read the Llama 3 paper.\n\n### Fine-Tuning Data\n\nWe employ a multi-faceted approach to data collection, combining human-generated data from our vendors with synthetic data to mitigate potential safety risks. We've developed many large language model (LLM)-based classifiers that enable us to thoughtfully select high-quality prompts and responses, enhancing data quality control.\n\n### Refusals And Tone\n\nBuilding on the work we started with Llama 3, we put a great emphasis on model refusals to benign prompts as well as refusal tone. We included both borderline and adversarial prompts in our safety data strategy, and modified our safety data responses to follow tone guidelines.\n\n## Evaluations\n\nWe evaluated Llama models for common use cases as well as specific capabilities. Common use cases evaluations measure safety risks of systems for most commonly built applications including chat bot, coding assistant, tool calls. We built dedicated, adversarial evaluation datasets and evaluated systems composed of Llama models and Llama Guard 3 to filter input prompt and output response. It is important to evaluate applications in context, and we recommend building dedicated evaluation dataset for your use case. Prompt Guard and Code Shield are also available if relevant to the application. \n\nCapability evaluations measure vulnerabilities of Llama models inherent to specific capabilities, for which were crafted dedicated benchmarks including long context, multilingual, tools calls, coding or memorization.\n\n## Red Teaming\n\nFor both scenarios, we conducted recurring red teaming exercises with the goal of discovering risks via adversarial prompting and we used the learnings to improve our benchmarks and safety tuning datasets. We partnered early with subject-matter experts in critical risk areas to understand the nature of these real-world harms and how such models may lead to unintended harm for society. Based on these conversations, we derived a set of adversarial goals for the red team to attempt to achieve, such as extracting harmful information or reprogramming the model to act in a potentially harmful capacity. The red team consisted of experts in cybersecurity, adversarial machine learning, responsible AI, and integrity in addition to multilingual content specialists with background in integrity issues in specific geographic markets. .\n\n## Critical And Other Risks\n\nWe specifically focused our efforts on mitigating the following critical risk areas: \n\n ### 1- CBRNE (Chemical, Biological, Radiological, Nuclear, and Explosive materials) helpfulness\n To assess risks related to proliferation of chemical and biological weapons, we performed uplift testing designed to assess whether use of Llama 3.1 models could meaningfully increase the capabilities of malicious actors to plan or carry out attacks using these types of weapons.\n\n### 2. Child Safety\n\nChild Safety risk assessments were conducted using a team of experts, to assess the model's capability to produce outputs that could result in Child Safety risks and inform on any necessary and appropriate risk mitigations via fine tuning. We leveraged those expert red teaming sessions to expand the coverage of our evaluation benchmarks through Llama 3 model development. For Llama 3, we conducted new in-depth sessions using objective based methodologies to assess the model risks along multiple attack vectors including the additional languages Llama 3 is trained on. We also partnered with content specialists to perform red teaming exercises assessing potentially violating content while taking account of market specific nuances or experiences.\n\n### 3. Cyber Attack Enablement\n\nOur cyber attack uplift study investigated whether LLMs can enhance human capabilities in hacking tasks, both in terms of skill level and speed. Our attack automation study focused on evaluating the capabilities of LLMs when used as autonomous agents in cyber offensive operations, specifically in the context of ransomware attacks. This evaluation was distinct from previous studies that considered LLMs as interactive assistants. The primary objective was to assess whether these models could effectively function as independent agents in executing complex cyber-attacks without human intervention. Our study of Llama-3.1-405B's social engineering uplift for cyber attackers was conducted to assess the effectiveness of AI models in aiding cyber threat actors in spear phishing campaigns. Please read our Llama 3.1 Cyber security whitepaper to learn more.\n\n## Community\n\nGenerative AI safety requires expertise and tooling, and we believe in the strength of the open community to accelerate its progress. We are active members of open consortiums, including the AI Alliance, Partnership on AI and MLCommons, actively contributing to safety standardization and transparency. We encourage the community to adopt taxonomies like the MLCommons Proof of Concept evaluation to facilitate collaboration and transparency on safety and content evaluations. Our Purple Llama tools are open sourced for the community to use and widely distributed across ecosystem partners including cloud service providers. We encourage community contributions to our [Github repository](https://github.com/meta-llama/PurpleLlama). \n\nWe also set up the [Llama Impact Grants](https://llama.meta.com/llama-impact-grants/) program to identify and support the most compelling applications of Meta's Llama model for societal benefit across three categories: education, climate and open innovation. The 20 finalists from the hundreds of applications can be found [here](https://llama.meta.com/llama-impact-grants/#finalists). \nFinally, we put in place a set of resources including an [output reporting mechanism](https://developers.facebook.com/llama_output_feedback) and [bug bounty program](https://www.facebook.com/whitehat) to continuously improve the Llama technology with the help of the community.\n\n## Ethical Considerations And Limitations\n\nThe core values of Llama 3.1 are openness, inclusivity and helpfulness. It is meant to serve everyone, and to work for a wide range of use cases. It is thus designed to be accessible to people across many different backgrounds, experiences and perspectives. Llama 3.1 addresses users and their needs as they are, without insertion unnecessary judgment or normativity, while reflecting the understanding that even content that may appear problematic in some cases can serve valuable purposes in others. It respects the dignity and autonomy of all users, especially in terms of the values of free thought and expression that power innovation and progress. \n\nBut Llama 3.1 is a new technology, and like any new technology, there are risks associated with its use. Testing conducted to date has not covered, nor could it cover, all scenarios. For these reasons, as with all LLMs, Llama 3.1's potential outputs cannot be predicted in advance, and the model may in some instances produce inaccurate, biased or other objectionable responses to user prompts. Therefore, before deploying any applications of Llama 3.1 models, developers should perform safety testing and tuning tailored to their specific applications of the model. Please refer to available resources including our [Responsible Use Guide](https://llama.meta.com/responsible-use-guide), [Trust and Safety](https://llama.meta.com/trust-and-safety/) solutions, and other [resources](https://llama.meta.com/docs/get-started/) to learn more about responsible development."])</script><script>self.__next_f.push([1,"54:T8e3,"])</script><script>self.__next_f.push([1,"{\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"Tell me about Dumbledore.\"\n }\n ],\n \"model\": \"meta/llama-3.1-8b-instruct\",\n \"max_tokens\": 1024,\n \"stream\": true,\n \"tool_choice\": \"auto\",\n \"tools\": [\n {\n \"type\": \"function\",\n \"function\": {\n \"name\": \"describe_harry_potter_character\",\n \"description\": \"Returns information and images of Harry Potter characters.\",\n \"parameters\": {\n \"type\": \"object\",\n \"properties\": {\n \"name\": {\n \"type\": \"string\",\n \"enum\": [\n \"Harry James Potter\",\n \"Hermione Jean Granger\",\n \"Ron Weasley\",\n \"Fred Weasley\",\n \"George Weasley\",\n \"Bill Weasley\",\n \"Percy Weasley\",\n \"Charlie Weasley\",\n \"Ginny Weasley\",\n \"Molly Weasley\",\n \"Arthur Weasley\",\n \"Neville Longbottom\",\n \"Luna Lovegood\",\n \"Draco Malfoy\",\n \"Albus Percival Wulfric Brian Dumbledore\",\n \"Minerva McGonagall\",\n \"Remus Lupin\",\n \"Rubeus Hagrid\",\n \"Sirius Black\",\n \"Severus Snape\",\n \"Bellatrix Lestrange\",\n \"Lord Voldemort\",\n \"Cedric Diggory\",\n \"Nymphadora Tonks\",\n \"James Potter\"\n ],\n \"description\": \"Name of the Harry Potter character\"\n }\n },\n \"required\": [\n \"name\"\n ]\n }\n }\n }\n ]\n}\n"])</script><script>self.__next_f.push([1,"55:T535,{\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"What is the weather in Santa Clara, CA?\"\n }\n ],\n \"model\": \"meta/llama-3.1-8b-instruct\",\n \"max_tokens\": 1024,\n \"stream\": true,\n \"tool_choice\": \"auto\",\n \"tools\": [\n {\n \"type\": \"function\",\n \"function\": {\n \"name\": \"get_current_weather\",\n \"description\": \"A tool that gets the current weather at a location, if one is specified, and defaults to the user's location.\",\n \"parameters\": {\n \"type\": \"object\",\n \"properties\": {\n \"location\": {\n \"type\": \"string\",\n \"description\": \"The location to find the weather of, or if not provided, it's the default location.\"\n },\n \"unit\": {\n \"type\": \"string\",\n \"enum\": [\n \"u\",\n \"m\"\n ],\n \"description\": \"Whether to use SI or USCS units (celsius or fahrenheit). Infer this from the user's location.\"\n }\n }\n }\n }\n }\n ]\n}\n56:T4bd,from openai import OpenAI\n\nclient = OpenAI(\n base_url = \"https://integrate.api.nvidia.com/v1\",\n api_key = \"$NVIDIA_API_KEY\"\n)\n\u003c% if (request.tools) { %\u003e\ncompletion = client.chat.completions.create(\n model=\"\u003c%- request.model %\u003e\",\n messages=\u003c%- JSON.stringify(request.messages) %\u003e,\n temperature=\u003c%- request.temperature %\u003e,\n top_p=\u003c%- request.top_p %\u003e,\n max_tokens=\u003c%- request.max_tokens %\u003e,\n stream=\u003c%- request.stream?.toString()[0].toUpperCase() + request.stream?.toString().slice(1) %\u003e,\n tools=\u003c%- JSON.stringify(request.tools) %\u003e,\n \u003c% if (request.tool_choice) { %\u003etool_choice=\u003c%- JSON.stringify(request.tool_choice) %\u003e\u003c% } %\u003e\n)\u003c% } else { %\u003e\ncompletion = client.chat.completions.create(\n "])</script><script>self.__next_f.push([1," model=\"\u003c%- request.model %\u003e\",\n messages=\u003c%- JSON.stringify(request.messages) %\u003e,\n temperature=\u003c%- request.temperature %\u003e,\n top_p=\u003c%- request.top_p %\u003e,\n max_tokens=\u003c%- request.max_tokens %\u003e,\n stream=\u003c%- request.stream?.toString()[0].toUpperCase() + request.stream?.toString().slice(1) %\u003e\n)\u003c% } %\u003e\n\u003c% if (request.stream) { %\u003e\nfor chunk in completion:\n if chunk.choices[0].delta.content is not None:\n print(chunk.choices[0].delta.content, end=\"\")\n\u003c% } else { %\u003e\nprint(completion.choices[0].message)\n\u003c% } %\u003e\n57:T504,import OpenAI from 'openai';\n\nconst openai = new OpenAI({\n apiKey: '$NVIDIA_API_KEY',\n baseURL: 'https://integrate.api.nvidia.com/v1',\n})\n \u003c% if (request.tools) { %\u003e\nasync function main() {\n const completion = await openai.chat.completions.create({\n model: \"\u003c%- request.model %\u003e\",\n messages: \u003c%- JSON.stringify(request.messages) %\u003e,\n temperature: \u003c%- request.temperature %\u003e,\n top_p: \u003c%- request.top_p %\u003e,\n max_tokens: \u003c%- request.max_tokens %\u003e,\n stream: \u003c%- request.stream %\u003e,\n \u003c% if (request.tools) { %\u003etools: \u003c%- JSON.stringify(request.tools) %\u003e,\u003c% } %\u003e\n \u003c% if (request.tool_choice) { %\u003etool_choice: \u003c%- JSON.stringify(request.tool_choice) %\u003e,\u003c% } %\u003e\n })\u003c% } else { %\u003e\nasync function main() {\n const completion = await openai.chat.completions.create({\n model: \"\u003c%- request.model %\u003e\",\n messages: \u003c%- JSON.stringify(request.messages) %\u003e,\n temperature: \u003c%- request.temperature %\u003e,\n top_p: \u003c%- request.top_p %\u003e,\n max_tokens: \u003c%- request.max_tokens %\u003e,\n stream: \u003c%- request.stream %\u003e\n })\u003c% } %\u003e\n \u003c% if (request.stream) { %\u003e\n for await (const chunk of completion) {\n process.stdout.write(chunk.choices[0]?.delta?.content || '')\n }\n \u003c% } else { %\u003e\n process.stdout.write(completion.choices[0]?.message?.content);\n \u003c% } %\u003e\n}\n\nmain();58:T66d,\u003c% if (request.tools) { %\u003e\n \"curl https://integrate.api.nvidia.com/v1/chat/completions \\\\\\n\n -H \\\"Content-Type: application/json\\\" \\\\\\n\n -H \\\"Authorization: Bearer $NVIDIA_API_KEY\\\" \\\\\\n\n -d '{\\n\n \\\"model\\\": \\\"meta/llam"])</script><script>self.__next_f.push([1,"a-3.1-8b-instruct\\\",\\n\n \\\"messages\\\": \u003c%- JSON.stringify(request.messages).replaceAll(\\\"'\\\", \\\"'\\\\\\\"'\\\\\\\"'\\\") %\u003e,\\n\n \\\"temperature\\\": \u003c%- request.temperature %\u003e,\\n\n \\\"top_p\\\": \u003c%- request.top_p %\u003e,\\n\n \\\"max_tokens\\\": \u003c%- request.max_tokens %\u003e,\\n\n \\\"stream\\\": \u003c%- request.stream %\u003e\n \u003c% if (request.tools) { %\u003e,\\n \\\"tools\\\": \u003c%- JSON.stringify(request.tools).replaceAll(\\\"'\\\", \\\"'\\\\\\\"'\\\\\\\"'\\\") %\u003e\u003c% } %\u003e\n \u003c% if (request.tool_choice) { %\u003e,\\n \\\"tool_choice\\\": \u003c%- JSON.stringify(request.tool_choice).replaceAll(\\\"'\\\", \\\"'\\\\\\\"'\\\\\\\"'\\\") %\u003e\u003c% } %\u003e\n }'\\n\"\u003c% } else { %\u003e\n \"curl https://integrate.api.nvidia.com/v1/chat/completions \\\\\\n\n -H \\\"Content-Type: application/json\\\" \\\\\\n\n -H \\\"Authorization: Bearer $NVIDIA_API_KEY\\\" \\\\\\n\n -d '{\\n\n \\\"model\\\": \\\"meta/llama-3.1-8b-instruct\\\",\\n\n \\\"messages\\\": \u003c%- JSON.stringify(request.messages).replaceAll(\\\"'\\\", \\\"'\\\\\\\"'\\\\\\\"'\\\") %\u003e,\\n\n \\\"temperature\\\": \u003c%- request.temperature %\u003e,\\n\n \\\"top_p\\\": \u003c%- request.top_p %\u003e,\\n\n \\\"max_tokens\\\": \u003c%- request.max_tokens %\u003e,\\n\n \\\"stream\\\": \u003c%- request.stream %\u003e\n \u003c% if (request.tools) { %\u003e,\\n \\\"tools\\\": \u003c%- JSON.stringify(request.tools).replaceAll(\\\"'\\\", \\\"'\\\\\\\"'\\\\\\\"'\\\") %\u003e\u003c% } %\u003e\n \u003c% if (request.tool_choice) { %\u003e,\\n \\\"tool_choice\\\": \u003c%- JSON.stringify(request.tool_choice).replaceAll(\\\"'\\\", \\\"'\\\\\\\"'\\\\\\\"'\\\") %\u003e\u003c% } %\u003e\n }'\\n\"\u003c% } %\u003e59:Tbef,"])</script><script>self.__next_f.push([1,"## Model Overview\n\n### Description:\n\nMistral-NeMo is a Large Language Model (LLM) composed of 12B parameters. This model leads accuracy on popular benchmarks across common sense reasoning, coding, math, multilingual and multi-turn chat tasks; it significantly outperforms existing models smaller or similar in size.\n\nThis model is ready for commercial use.\n\n#### Key features\n\n1. Released under the Apache 2 License\n2. Pre-trained and instructed versions\n3. Trained with a 128k context window\n4. Trained on a large proportion of multilingual and code data\n5. Drop-in replacement of Mistral 7B\n\n### Joint-Party Community Consideration\n\nThis model was a jointly trained by Mistral and NVIDIA.\n\n### License \u0026 Terms of use\n\nYour use of this API is governed by [the NVIDIA API Trial Service Terms of Use](https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf); and the use of this model is governed by [the NVIDIA AI Foundation Models Community License](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-ai-foundation-models-community-license-agreement/). Mistral NeMo-12B is released under the Apache 2.0 license.\n\n### References(s):\n\nMistral NeMo 12B [Blogpost](https://mistral.ai/news/mistral-nemo/)\n\n### Model Architecture:\n\n**Architecture Type:** Transformer \u003cbr\u003e\n**Network Architecture:** Mistral \u003cbr\u003e\n**Model Version:** 0.1 \u003cbr\u003e\n\nThis transformer model has the following characteristics:\n* Layers: 40\n* Dim: 5,120\n* Head dim: 128\n* Hidden dim: 14,436\n* Activation Function: SwiGLU\n* Number of heads: 32\n* Number of kv-heads: 8 (GQA)\n* Rotary embeddings (theta = 1M)\n* Vocabulary size: 2**17 ~= 128k\n\n**Input**\n* Input Type: Text\n* Input Format: String\n* Input Parameters: max_tokens, temperature, top_p, stop, frequency_penalty, presence_penalty, seed\n\n**Output**\n* Output Type: Text\n* Output Format: String\n\n### Software Integration:\n\n* Supported Hardware Platform(s): NVIDIA Hopper\n* Preferred Operating System(s): Linux \u003cbr\u003e\n\n#### Benchmarks\n\n##### Main benchmarks\n\n- HellaSwag (0-shot): 83.5%\n- Winogrande (0-shot): 76.8%\n- OpenBookQA (0-shot): 60.6%\n- CommonSenseQA (0-shot): 70.4%\n- TruthfulQA (0-shot): 50.3%\n- MMLU (5-shot): 68.0%\n- TriviaQA (5-shot): 73.8%\n- NaturalQuestions (5-shot): 31.2%\n\n##### Multilingual benchmarks\n\n- MMLU\n - French: 62.3%\n - German: 62.7%\n - Spanish: 64.6%\n - Italian: 61.3%\n - Portuguese: 63.3%\n - Russian: 59.2%\n - Chinese: 59.0%\n - Japanese: 59.0%\n\n##### Instruct benchmarks\n\n- MT Bench (dev): 7.84\n- MixEval Hard: 0.534\n- IFEval-v5: 0.629\n- Wildbench: 42.57\n\n### Inference\n\n**Engine:** TensorRT-LLM \u003cbr\u003e\n**Test Hardware:** H100\n\n### Ethical Considerations:\n\nWhen downloaded or used in accordance with our terms of service, developers should work with their internal model team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse. Please report security vulnerabilities or NVIDIA AI Concerns [here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/).\n"])</script><script>self.__next_f.push([1,"5a:T8ef,"])</script><script>self.__next_f.push([1,"{\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"Tell me about Dumbledore.\"\n }\n ],\n \"model\": \"nv-mistralai/mistral-nemo-12b-instruct\",\n \"max_tokens\": 1024,\n \"stream\": true,\n \"tool_choice\": \"auto\",\n \"tools\": [\n {\n \"type\": \"function\",\n \"function\": {\n \"name\": \"describe_harry_potter_character\",\n \"description\": \"Returns information and images of Harry Potter characters.\",\n \"parameters\": {\n \"type\": \"object\",\n \"properties\": {\n \"name\": {\n \"type\": \"string\",\n \"enum\": [\n \"Harry James Potter\",\n \"Hermione Jean Granger\",\n \"Ron Weasley\",\n \"Fred Weasley\",\n \"George Weasley\",\n \"Bill Weasley\",\n \"Percy Weasley\",\n \"Charlie Weasley\",\n \"Ginny Weasley\",\n \"Molly Weasley\",\n \"Arthur Weasley\",\n \"Neville Longbottom\",\n \"Luna Lovegood\",\n \"Draco Malfoy\",\n \"Albus Percival Wulfric Brian Dumbledore\",\n \"Minerva McGonagall\",\n \"Remus Lupin\",\n \"Rubeus Hagrid\",\n \"Sirius Black\",\n \"Severus Snape\",\n \"Bellatrix Lestrange\",\n \"Lord Voldemort\",\n \"Cedric Diggory\",\n \"Nymphadora Tonks\",\n \"James Potter\"\n ],\n \"description\": \"Name of the Harry Potter character\"\n }\n },\n \"required\": [\n \"name\"\n ]\n }\n }\n }\n ]\n}\n"])</script><script>self.__next_f.push([1,"5b:T541,{\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"What is the weather in Santa Clara, CA?\"\n }\n ],\n \"model\": \"nv-mistralai/mistral-nemo-12b-instruct\",\n \"max_tokens\": 1024,\n \"stream\": true,\n \"tool_choice\": \"auto\",\n \"tools\": [\n {\n \"type\": \"function\",\n \"function\": {\n \"name\": \"get_current_weather\",\n \"description\": \"A tool that gets the current weather at a location, if one is specified, and defaults to the user's location.\",\n \"parameters\": {\n \"type\": \"object\",\n \"properties\": {\n \"location\": {\n \"type\": \"string\",\n \"description\": \"The location to find the weather of, or if not provided, it's the default location.\"\n },\n \"unit\": {\n \"type\": \"string\",\n \"enum\": [\n \"u\",\n \"m\"\n ],\n \"description\": \"Whether to use SI or USCS units (celsius or fahrenheit). Infer this from the user's location.\"\n }\n }\n }\n }\n }\n ]\n}\n5c:T86f,"])</script><script>self.__next_f.push([1,"## Model Overview\n\n### Description:\n\nMixtral 8x22B is MistralAI's latest open model. It sets a new standard for performance and efficiency within the AI community. It is a sparse Mixture-of-Experts (SMoE) model that uses only 39B active parameters out of 141B, offering unparalleled cost efficiency for its size.\n\nMixtral 8x22B comes with the following strengths:\n\n* It is fluent in English, French, Italian, German, and Spanish\n* It has strong mathematics and coding capabilities\n* It is natively capable of function calling; along with the constrained output mode implemented on la Plateforme, this enables application development and tech stack modernisation at scale\n* Its 64K tokens context window allows precise information recall from large documents\n\n### Third-Party Community Consideration:\n\nThis model is not owned or developed by NVIDIA. This model has been developed and built to a third-party’s requirements for this application and use case; see Mixtral 8x22b's [Model Card](https://huggingface.co/mistralai/Mixtral-8x22B-Instruct-v0.1).\n\n### Terms of use\n\nBy using this software or model, you are agreeing to the [terms and conditions](https://mistral.ai/terms-of-service/) of the license, acceptable use policy and Mistral's privacy policy. Mixtral-8x22B is released under the Apache 2.0 license\n\n### References(s):\n\nMixtral 8x22B Instruct [Model Card](https://huggingface.co/mistralai/Mixtral-8x22B-Instruct-v0.1) on Hugging Face \u003cbr\u003e\n[Cheaper, Better, Faster, Stronger | Mistral AI](https://mistral.ai/news/mixtral-8x22b/) \u003cbr\u003e\n\n### Model Architecture:\n\n**Architecture Type:** Transformer \u003cbr\u003e\n**Network Architecture:** Sparse Mixture of GPT-based experts \u003cbr\u003e\n**Model Version:** 0.1 \u003cbr\u003e\n\n### Input:\n\n**Input Format:** Text \u003cbr\u003e\n**Input Parameters:** Temperature, Top P, Max Output Tokens\u003cbr\u003e\n\n### Output:\n\n**Output Format:** Text \u003cbr\u003e\n**Output Parameters:** None \u003cbr\u003e\n\n### Software Integration:\n\n**Supported Hardware Platform(s):** Hopper, Ampere, Turing, Ada \u003cbr\u003e\n**Supported Operating System(s):** Linux \u003cbr\u003e\n\n## Inference:\n\n**Engine:** [Triton](https://developer.nvidia.com/triton-inference-server) \u003cbr\u003e\n**Test Hardware:** Other \u003cbr\u003e\n"])</script><script>self.__next_f.push([1,"5d:T8ad,"])</script><script>self.__next_f.push([1,"## Model Overview\n\n### Note: You need to request the model checkpoint and license from Stability AI\n\nRequest the model checkpoint from [Stability AI](https://stability.ai/membership)\n\n### Description:\n\nSDXL-Turbo, a distilled variant of SDXL 1.0, empowers real-time image synthesis via Adversarial Diffusion Distillation (ADD). ADD enables high-fidelity sampling from large-scale image diffusion models in 1-4 steps. Employing score distillation for leveraging teacher signals from pre-trained models, ADD seamlessly integrates an adversarial loss, guaranteeing image fidelity even at minimal sampling steps (1-2).\n\nDeveloped by: Stability AI\nFunded by: Stability AI\nModel type: Generative image-to-video model\nFinetuned from model: SDXL 1.0 Base\n\n### Terms of use\n\nBy using this software or model, you are agreeing to the terms and conditions of the [license](https://huggingface.co/stabilityai/stable-video-diffusion-img2vid/blob/main/LICENSE), [acceptable use policy](https://stability.ai/use-policy#:~:text=If%20you%20access%2C%20use%2C%20or,Stability%20Technology%20safely%20and%20responsibly.) and Stability’s [privacy policy](https://stability.ai/privacy-policy).\n\n### References(s):\n\n* [Introducing SDXL Turbo - Stability.ai](https://stability.ai/news/stability-ai-sdxl-turbo)\n* [SDXL-Turbo on Huggingface](https://huggingface.co/stabilityai/sdxl-turbo)\n* [SDXL-Turbo paper](https://stability.ai/research/adversarial-diffusion-distillation)\n\n### Model Architecture:\n\n**Architecture Type:** Transformer and Convolutional Neural Network (CNN)\n**Network Architecture:** UNet + attention blocks\n**Model Version:** SDXL Turbo\n\n### Input:\n\n**Input Format:** Text, Image (Optional)\n**Input Parameters:** inference_steps, seed, prompt_strength (for an image input)\n\n### Output:\n\n**Output Format:** Red, Green, Blue (RGB) Image\n**Output Parameters:** seed\n\n### Software Integration:\n\n**Supported Hardware Platform(s):** Hopper, Ampere/Turing\n**Supported Operating System(s):** Linux\n\n## Inference:\n\n**Engine:** [Triton](https://developer.nvidia.com/triton-inference-server)\n**Test Hardware:** Other\n\n## Request Model Checkpoint:\n\nYou can request the model checkpoint from [Stability AI](https://stability.ai/membership)\n"])</script><script>self.__next_f.push([1,"5e:T46f,|Field:|Response:|\n|:---:|:---:|\n|Generatable or Reverse engineerable personally-identifiable information?|None|\n|Was consent obtained for any personal data used?|None Known|\n|Personal data used to create this model?|None Known|\n|How often is dataset reviewed?|Before Release|\n|Is a mechanism in place to honor data subject right of access or deletion of personal data?|Not Applicable|\n|If personal data collected for the development of the model, was it collected by NVIDIA?|Not Applicable|\n|If personal data collected for the development of the model by NVIDIA, do you maintain or have access to disclosures made to data subjects?|Not Applicable|\n|If personal data collected for the development of this AI model, was it minimized to only what was required?|Not Applicable|\n|Is there provenance for all datasets used in training?|Yes|\n|Does data labeling (annotation, metadata) comply with privacy laws?|Not Applicable|\n|Is data compliant with data subject requests for data correction or removal, if such a request was made?|Not Applicable|\n|Applicable NVIDIA Privacy Policy|https://www.nvidia.com/en-us/about-nvidia/privacy-policy/|5f:T2f37,"])</script><script>self.__next_f.push([1,"## Nemotron-4-340B-Instruct\n\n\n### Model Overview\n\nNemotron-4-340B-Instruct is a large language model (LLM) that can be used as part of a synthetic data generation pipeline to create training data that helps researchers and developers build their own LLMs. It is a fine-tuned version of the Nemotron-4-340B-Base model, optimized for English-based single and multi-turn chat use-cases. It supports a context length of 4,096 tokens. \n\nThe base model was pre-trained on a corpus of 9 trillion tokens consisting of a diverse assortment of English based texts, 50+ natural languages, and 40+ coding languages. Subsequently the Nemotron-4-340B-Instruct model went through additional alignment steps including:\n\n- Supervised Fine-tuning (SFT)\n- Direct Preference Optimization (DPO)\n- Reward-aware Preference Optimization (RPO) ([Additional in-house alignment technique](https://research.nvidia.com/publication/2024-06_nemotron-4-340b)) \n\nThroughout the alignment process, we relied on only approximately 20K human-annotated data while our data generation pipeline synthesized over 98% of the data used for supervised fine-tuning and preference fine-tuning (DPO \u0026 RPO). We provide comprehensive details about our synthetic data generation pipeline in the [technical report](https://research.nvidia.com/publication/2024-06_nemotron-4-340b).\n\nThis results in a model that is aligned for human chat preferences, improvements in mathematical reasoning, coding and instruction-following, and is capable of generating high quality synthetic data for a variety of use cases.\n\nUnder the NVIDIA Open Model License, NVIDIA confirms: \n- Models are commercially usable. \n- You are free to create and distribute Derivative Models. \n- NVIDIA does not claim ownership to any outputs generated using the Models or Derivative Models.\n\n### License: \n\n[NVIDIA Open Model License](https://developer.download.nvidia.com/licenses/nvidia-open-model-license-agreement-june-2024.pdf)\n\n### Intended use\n\nNemotron-4-340B-Instruct is a chat model intended for use for the English language. \n\nNemotron-4-340B-Instruct is designed for Synthetic Data Generation to enable developers and enterprises for building and customizing their own large language models and LLM applications. \n\nThe instruct model itself can be further customized using the [NeMo Framework](https://docs.nvidia.com/nemo-framework/index.html) suite of customization tools including Parameter-Efficient Fine-Tuning (P-tuning, Adapters, LoRA, and more), and Model Alignment (SFT, SteerLM, RLHF, and more) using [NeMo-Aligner](https://github.com/NVIDIA/NeMo-Aligner).\n\n**Model Developer:** NVIDIA\n\n**Model Dates:** Nemotron-4-340B-Instruct was trained between December 2023 and May 2024.\n\n**Data Freshness:** The pretraining data has a cutoff of June 2023.\n\n### Required Hardware\n\nBF16 Inference:\n- 8x H200 (1x H200 node)\n- 16x H100 (2x H100 nodes)\n- 16x A100 80GB (2x A100 80GB nodes)\n\n\n### Model Architecture:\n\nNemotron-4-340B-Instruct is standard decoder-only Transformer, trained with a sequence length of 4096 tokens, uses Grouped-Query Attention (GQA), and Rotary Position Embeddings (RoPE).\n\n**Architecture Type:** Transformer Decoder (auto-regressive language model)\n\n**Network Architecture:**\nNemotron-4\n\n### Prompt Format\n\nNote: For Nemotron-4-340B-Instruct we recommend keeping the system prompt empty.\n\n#### Single Turn\n\n```text\n\u003cextra_id_0\u003eSystem\n\n\u003cextra_id_1\u003eUser\n{prompt}\n\u003cextra_id_1\u003eAssistant\n```\n\n#### Multi-Turn or Few-shot\n\n```text\n\u003cextra_id_0\u003eSystem\n\n\u003cextra_id_1\u003eUser\n{prompt 1}\n\u003cextra_id_1\u003eAssistant\n{response 1}\n\u003cextra_id_1\u003eUser\n{prompt 2}\n\u003cextra_id_1\u003eAssistant\n{response 2}\n...\n\u003cextra_id_1\u003eUser\n{prompt N}\n\u003cextra_id_1\u003eAssistant\n```\n\nAn example of a formattable prompt template is available in the following section.\n\n### Usage\n\nDeployment and inference with Nemotron-4-340B-Instruct can be done in three steps using NeMo Framework:\n\nCreate a Python script to interact with the deployed model.\nCreate a Bash script to start the inference server\nSchedule a Slurm job to distribute the model across 2 nodes and associate them with the inference server.\n\n1. Define the Python script ``call_server.py``\n\n```python\nimport json\nimport requests\n\nheaders = {\"Content-Type\": \"application/json\"}\n\ndef text_generation(data, ip='localhost', port=None):\n resp = requests.put(f'http://{ip}:{port}/generate', data=json.dumps(data), headers=headers)\n return resp.json()\n\n\ndef get_generation(prompt, greedy, add_BOS, token_to_gen, min_tokens, temp, top_p, top_k, repetition, batch=False):\n data = {\n \"sentences\": [prompt] if not batch else prompt,\n \"tokens_to_generate\": int(token_to_gen),\n \"temperature\": temp,\n \"add_BOS\": add_BOS,\n \"top_k\": top_k,\n \"top_p\": top_p,\n \"greedy\": greedy,\n \"all_probs\": False,\n \"repetition_penalty\": repetition,\n \"min_tokens_to_generate\": int(min_tokens),\n \"end_strings\": [\"\u003c|endoftext|\u003e\", \"\u003cextra_id_1\u003e\", \"\\x11\", \"\u003cextra_id_1\u003eUser\"],\n }\n sentences = text_generation(data, port=1424)['sentences']\n return sentences[0] if not batch else sentences\n\nPROMPT_TEMPLATE = \"\"\"\u003cextra_id_0\u003eSystem\n\n\u003cextra_id_1\u003eUser\n{prompt}\n\u003cextra_id_1\u003eAssistant\n\"\"\"\n\nquestion = \"Write a poem on NVIDIA in the style of Shakespeare\"\nprompt = PROMPT_TEMPLATE.format(prompt=question)\nprint(prompt)\n\nresponse = get_generation(prompt, greedy=True, add_BOS=False, token_to_gen=1024, min_tokens=1, temp=1.0, top_p=1.0, top_k=0, repetition=1.0, batch=False)\nresponse = response[len(prompt):]\nif response.endswith(\"\u003cextra_id_1\u003e\"):\n response = response[:-len(\"\u003cextra_id_1\u003e\")]\nprint(response)\n```\n\n2. Given this Python script, create a Bash script which spins up the inference server within the [NeMo container](https://catalog.ngc.nvidia.com/orgs/nvidia/containers/nemo) (```docker pull nvcr.io/nvidia/nemo:24.01.framework```) and calls the Python script ``call_server.py``. The Bash script ``nemo_inference.sh`` is as follows,\n\n```bash\nNEMO_FILE=$1\nWEB_PORT=1424\n\ndepends_on () {\n HOST=$1\n PORT=$2\n STATUS=$(curl -X PUT http://$HOST:$PORT \u003e/dev/null 2\u003e/dev/null; echo $?)\n while [ $STATUS -ne 0 ]\n do\n echo \"waiting for server ($HOST:$PORT) to be up\"\n sleep 10\n STATUS=$(curl -X PUT http://$HOST:$PORT \u003e/dev/null 2\u003e/dev/null; echo $?)\n done\n echo \"server ($HOST:$PORT) is up running\"\n}\n\n\n/usr/bin/python3 /opt/NeMo/examples/nlp/language_modeling/megatron_gpt_eval.py \\\n gpt_model_file=$NEMO_FILE \\\n pipeline_model_parallel_split_rank=0 \\\n server=True tensor_model_parallel_size=8 \\\n trainer.precision=bf16 pipeline_model_parallel_size=2 \\\n trainer.devices=8 \\\n trainer.num_nodes=2 \\\n web_server=False \\\n port=${WEB_PORT} \u0026\n SERVER_PID=$!\n\n readonly local_rank=\"${LOCAL_RANK:=${SLURM_LOCALID:=${OMPI_COMM_WORLD_LOCAL_RANK:-}}}\"\n if [ $SLURM_NODEID -eq 0 ] \u0026\u0026 [ $local_rank -eq 0 ]; then\n depends_on \"0.0.0.0\" ${WEB_PORT}\n\n echo \"start get json\"\n sleep 5\n\n echo \"SLURM_NODEID: $SLURM_NODEID\"\n echo \"local_rank: $local_rank\"\n /usr/bin/python3 /scripts/call_server.py\n echo \"clean up dameons: $$\"\n kill -9 $SERVER_PID\n pkill python\n fi\n wait\n```\n\n\n3. Launch ``nemo_inference.sh`` with a Slurm script defined like below, which starts a 2-node job for model inference.\n\n```\n#!/bin/bash\n#SBATCH -A SLURM-ACCOUNT\n#SBATCH -p SLURM-PARITION\n#SBATCH -N 2\n#SBATCH -J generation \n#SBATCH --ntasks-per-node=8 \n#SBATCH --gpus-per-node=8\nset -x\n\nRESULTS=\u003cPATH_TO_YOUR_SCRIPTS_FOLDER\u003e\nOUTFILE=\"${RESULTS}/slurm-%j-%n.out\"\nERRFILE=\"${RESULTS}/error-%j-%n.out\"\nMODEL=\u003cPATH_TO\u003e/Nemotron-4-340B-Instruct\nCONTAINER=\"nvcr.io/nvidia/nemo:24.01.framework\"\nMOUNTS=\"--container-mounts=\u003cPATH_TO_YOUR_SCRIPTS_FOLDER\u003e:/scripts,MODEL:/model\"\n\nread -r -d '' cmd \u003c\u003cEOF\nbash /scripts/nemo_inference.sh /model\nEOF\n\nsrun -o $OUTFILE -e $ERRFILE --container-image=\"$CONTAINER\" $MOUNTS bash -c \"${cmd}\"\n```\n\n### Evaluation Results\n\n#### MT-Bench (GPT-4-Turbo)\n\nEvaluated using MT-Bench judging by GPT-4-0125-Preview as described in Appendix H in the [HelpSteer2 Dataset Paper](https://arxiv.org/abs/2406.08673)\n\n| total | writing | roleplay | extraction | stem | humanities | reasoning | math | coding | turn 1 | turn 2 |\n| :----- | :------- | :-------- | :---------- | :---- | :---------- | :--------- | :---- | ------ | :------ | :------ | \n| 8.22 | 8.70 | 8.70 | 9.20 | 8.75 | 8.95 | 6.40 | 8.40 | 6.70 | 8.61 | 7.84 | \n\n#### IFEval\n\nEvaluated using the Instruction Following Eval (IFEval) introduced in Instruction-Following Evaluation for Large Language Models.\n\n| Prompt-Strict Acc | Instruction-Strict Acc |\n| :----------------------- | :---------------------------- |\n| 79.9 | 86.1 |\n\n#### MMLU\n\nEvaluated using the Multi-task Language Understanding benchmarks as introduced in Measuring Massive Multitask Language Understanding.\n\n|MMLU 0-shot |\n| :----------------- |\n| 78.7 | \n\n#### GSM8K\n\nEvaluated using the Grade School Math 8K (GSM8K) benchmark as introduced in Training Verifiers to Solve Math Word Problems.\n\n| GSM8K 0-shot |\n| :----------------- | \n| 92.3 | \n\n#### HumanEval\n\nEvaluated using the HumanEval benchmark as introduced in Evaluating Large Language Models Trained on Code.\n\n\n| HumanEval 0-shot |\n| :----- |\n| 73.2 |\n\n#### MBPP\n\nEvaluated using the MBPP Dataset as introduced in the Program Synthesis with Large Language Models.\n\n| MBPP 0-shot|\n| :----------------- | \n| 75.4 | \n\n\n#### Arena Hard\n\nEvaluated using the Arena-Hard Pipeline from the LMSys Org.\n\n| Arena Hard |\n| :----------------- | \n| 54.2 | \n\n#### AlpacaEval 2.0 LC\n\nEvaluated using the AlpacaEval 2.0 LC (Length Controlled) as introduced in the paper: Length-Controlled AlpacaEval: A Simple Way to Debias Automatic Evaluators\n\n| AlpacaEval 2.0 LC|\n| :----------------- | \n| 41.5 | \n\n\n#### TFEval\n\nEvaluated using the CantTalkAboutThis Dataset as introduced in the CantTalkAboutThis: Aligning Language Models to Stay on Topic in Dialogues.\n\n| Distractor F1 | On-topic F1 |\n| :----------------------- | :---------------------------- |\n| 81.7 | 97.7 |\n\n\n### Adversarial Testing and Red Teaming Efforts \n\nThe Nemotron-4 340B-Instruct model underwent safety evaluation including adversarial testing via three distinct methods: \n- [Garak](https://docs.garak.ai/garak), is an automated LLM vulnerability scanner that probes for common weaknesses, including prompt injection and data leakage. \n- AEGIS, is a content safety evaluation dataset and LLM based content safety classifier model, that adheres to a broad taxonomy of 13 categories of critical risks in human-LLM interactions.\n- Human Content Red Teaming leveraging human interaction and evaluation of the models' responses.\n\n### Limitations\n\nThe model was trained on data that contains toxic language, unsafe content, and societal biases originally crawled from the internet. Therefore, the model may amplify those biases and return toxic responses especially when prompted with toxic prompts. The model may generate answers that may be inaccurate, omit key information, or include irrelevant or redundant text producing socially unacceptable or undesirable text, even if the prompt itself does not include anything explicitly offensive.\n\n\n### Ethical Considerations\n\nNVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their internal model team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse. For more detailed information on ethical considerations for this model, please see the Model Card++ Explainability, Bias, Safety \u0026 Security, and Privacy Subcards [here](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/nemo/models/nemotron-4-340b-instruct). Please report security vulnerabilities or NVIDIA AI Concerns [here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/)."])</script><script>self.__next_f.push([1,"60:T4dc,|Field:|Response:|\n|:---:|:---:|\n|Intended Application(s) \u0026 Domain(s):|Large Language Model (LLM) Development|\n|Model Type:|Generative Pre-Trained Transformer (GPT)|\n|Intended Users:|This model is intended for developers and researchers building LLMs.|\n|Output:|Text String(s)|\n|Describe how the model works:|The network architecture of this model is Nemotron-4. The decoder in Nemotron-4 generates text by predicting the next word or token based on the context provided in the input sequence using multiple self-attention layers.|\n|Technical Limitations:| |\n|Verified to have met prescribed quality standards?|Yes|\n|Performance Metrics:|Accuracy, Throughput, and Latency|\n|Potential Known Risks:|The base model was trained on data that contains toxic language and societal biases originally crawled from the internet. Therefore, the model may amplify those biases and return toxic responses especially when prompted with toxic prompts. The model may generate answers that may be inaccurate, omit key information, or include irrelevant or redundant text producing socially unacceptable or undesirable text, even if the prompt itself does not include anything explicitly offensive.|\n|End User License Agreement:|Please see detailed model cards.|61:T40b5,"])</script><script>self.__next_f.push([1,"## Gemma 2 Model Card\n\n#### Description\n\nGemma is a family of lightweight, state-of-the-art open models from Google,\nbuilt from the same research and technology used to create the Gemini models.\nThey are text-to-text, decoder-only large language models, available in English,\nwith open weights for both pre-trained variants and instruction-tuned variants.\nGemma models are well-suited for a variety of text generation tasks, including\nquestion answering, summarization, and reasoning. Their relatively small size\nmakes it possible to deploy them in environments with limited resources such as\na laptop, desktop or your own cloud infrastructure, democratizing access to\nstate of the art AI models and helping foster innovation for everyone.\n\n### References:\n\n**Author**: Google\n**Model Page**: [Gemma](https://ai.google.dev/gemma/docs)\n\n### Third-Party Community Consideration\n\nThis model is not owned or developed by NVIDIA. This model has been developed and built to a third-party’s requirements for this application and use case.\n\n### Terms of Use\n\n[Terms][terms]\n\nProhibited uses of Gemma models are outlined in the [Gemma Prohibited Use Policy][prohibited-use].\n\n### Model Information\n\nSummary description and brief definition of inputs and outputs.\n\n#### Inputs and outputs\n\n### Input:\n\n**Input Type(s):** Text \u003cbr\u003e\n**Input Format(s):** String \u003cbr\u003e\n**Input Parameters:** One-Dimensional (1D) \u003cbr\u003e\n**Other Properties Related to Output:** Text can be question, a prompt, or a document to be\nsummarized. \u003cbr\u003e\n\n### Output:\n\n**Output Type(s):** Text \u003cbr\u003e\n**Output Format(s):** String \u003cbr\u003e\n**Output Parameters:** One-Dimensional (1D) \u003cbr\u003e\n**Other Properties Related to Output:** Generated English-language text in response to the input (e.g.,\nan answer to the question, a summary of the document). \u003cbr\u003e\n\n#### Citation\n\n```none\n@article{gemma_2024,\n title={Gemma},\n url={https://www.kaggle.com/m/3301},\n DOI={10.34740/KAGGLE/M/3301},\n publisher={Kaggle},\n author={Gemma Team},\n year={2024}\n}\n```\n\n### Usage and Limitations\n\nThese models have certain limitations that users should be aware of.\n\n#### Intended Usage\n\nOpen Large Language Models (LLMs) have a wide range of applications across\nvarious industries and domains. The following list of potential uses is not\ncomprehensive. The purpose of this list is to provide contextual information\nabout the possible use-cases that the model creators considered as part of model\ntraining and development.\n\n* Content Creation and Communication\n * Text Generation: These models can be used to generate creative text formats\n such as poems, scripts, code, marketing copy, and email drafts.\n * Chatbots and Conversational AI: Power conversational interfaces for customer\n service, virtual assistants, or interactive applications.\n * Text Summarization: Generate concise summaries of a text corpus, research\n papers, or reports.\n* Research and Education\n * Natural Language Processing (NLP) Research: These models can serve as a\n foundation for researchers to experiment with NLP techniques, develop\n algorithms, and contribute to the advancement of the field.\n * Language Learning Tools: Support interactive language learning experiences,\n aiding in grammar correction or providing writing practice.\n * Knowledge Exploration: Assist researchers in exploring large bodies of text\n by generating summaries or answering questions about specific topics.\n\n#### Limitations\n\n* Training Data\n * The quality and diversity of the training data significantly influence the\n model's capabilities. Biases or gaps in the training data can lead to\n limitations in the model's responses.\n * The scope of the training dataset determines the subject areas the model can\n handle effectively.\n* Context and Task Complexity\n * LLMs are better at tasks that can be framed with clear prompts and\n instructions. Open-ended or highly complex tasks might be challenging.\n * A model's performance can be influenced by the amount of context provided\n (longer context generally leads to better outputs, up to a certain point).\n* Language Ambiguity and Nuance\n * Natural language is inherently complex. LLMs might struggle to grasp subtle\n nuances, sarcasm, or figurative language.\n* Factual Accuracy\n * LLMs generate responses based on information they learned from their\n training datasets, but they are not knowledge bases. They may generate\n incorrect or outdated factual statements.\n* Common Sense\n * LLMs rely on statistical patterns in language. They might lack the ability\n to apply common sense reasoning in certain situations.\n\n### Model Data\n\nData used for model training and how the data was processed.\n\n#### Training Dataset\n\nThese models were trained on a dataset of text data that includes a wide variety of sources. The 27B model was trained with 13t tokens and the 9B model was trained with 8t tokens. Here are the key components:\n\n* Web Documents: A diverse collection of web text ensures the model is exposed\n to a broad range of linguistic styles, topics, and vocabulary. Primarily\n English-language content.\n* Code: Exposing the model to code helps it to learn the syntax and patterns of\n programming languages, which improves its ability to generate code or\n understand code-related questions.\n* Mathematics: Training on mathematical text helps the model learn logical\n reasoning, symbolic representation, and to address mathematical queries.\n\nThe combination of these diverse data sources is crucial for training a powerful\nlanguage model that can handle a wide variety of different tasks and text\nformats.\n\n#### Data Preprocessing\n\nHere are the key data cleaning and filtering methods applied to the training\ndata:\n\n* CSAM Filtering: Rigorous CSAM (Child Sexual Abuse Material) filtering was\n applied at multiple stages in the data preparation process to ensure the\n exclusion of harmful and illegal content.\n* Sensitive Data Filtering: As part of making Gemma pre-trained models safe and\n reliable, automated techniques were used to filter out certain personal\n information and other sensitive data from training sets.\n* Additional methods: Filtering based on content quality and safety in line with\n [our policies][safety-policies].\n\n### Implementation Information\n\n#### TensorRT-LLM\n\nThe endpoint available on NGC catalog is accelerated by TensorRT-LLM, an open-source library for optimizing inference performance. Gemma is compatible across NVIDIA AI platforms—from the datacenter, cloud, to the local PC with RTX GPU systems.  \n\nGemma models use a vocabulary size of 256K and support a context length of up to 4K while using rotary positional embedding (RoPE). With support for Position Interpolation (PI) available in TensorRT-LLM, Gemma models using RoPE can support longer output sequence lengths at inference time while retaining original model architecture. \n\n#### Software\n\nTraining was done using [JAX][jax] and [ML Pathways][ml-pathways].\n\nJAX allows researchers to take advantage of the latest generation of hardware,\nincluding TPUs, for faster and more efficient training of large models.\n\nML Pathways is Google's latest effort to build artificially intelligent systems\ncapable of generalizing across multiple tasks. This is specially suitable for\n[foundation models][foundation-models], including large language models like\nthese ones.\n\nTogether, JAX and ML Pathways are used as described in the\n[paper about the Gemini family of models][gemini-2-paper]; \"the 'single\ncontroller' programming model of Jax and Pathways allows a single Python\nprocess to orchestrate the entire training run, dramatically simplifying the\ndevelopment workflow.\"\n\n### Evaluation\n\nModel evaluation metrics and results.\n\n#### Benchmark Results\n\nThese models were evaluated against a large collection of different datasets and\nmetrics to cover different aspects of text generation:\n\n| Benchmark | Metric | Gemma PT 9B | Gemma PT 27B |\n| ------------------------------ | ------------- | ----------- | ------------ |\n| [MMLU][mmlu] | 5-shot, top-1 | 71.3 | 75.2 |\n| [HellaSwag][hellaswag] | 10-shot | 81.9 | 86.4 |\n| [PIQA][piqa] | 0-shot | 81.7 | 83.2 |\n| [SocialIQA][socialiqa] | 0-shot | 53.4 | 53.7 |\n| [BoolQ][boolq] | 0-shot | 84.2 | 84.8 |\n| [WinoGrande][winogrande] | partial score | 80.6 | 83.7 |\n| [ARC-e][arc] | 0-shot | 88.0 | 88.6 |\n| [ARC-c][arc] | 25-shot | 68.4 | 71.4 |\n| [TriviaQA][triviaqa] | 5-shot | 76.6 | 83.7 |\n| [Natural Questions][naturalq] | 5-shot | 29.2 | 34.5 |\n| [HumanEval][humaneval] | pass@1 | 40.2 | 51.8 |\n| [MBPP][mbpp] | 3-shot | 52.4 | 62.6 |\n| [GSM8K][gsm8k] | 5-shot, maj@1 | 68.6 | 74.0 |\n| [MATH][math] | 4-shot | 36.6 | 42.3 |\n| [AGIEval][agieval] | 3-5-shot | 52.8 | 55.1 |\n| [BIG-Bench][big-bench] | 3-shot, CoT | 68.2 | 74.9 |\n| ------------------------------ | ------------- | ----------- | ------------ |\n\n### Ethics and Safety\n\nEthics and safety evaluation approach and results.\n\n#### Evaluation Approach\n\nOur evaluation methods include structured evaluations and internal red-teaming\ntesting of relevant content policies. Red-teaming was conducted by a number of\ndifferent teams, each with different goals and human evaluation metrics. These\nmodels were evaluated against a number of different categories relevant to\nethics and safety, including:\n\n* Text-to-Text Content Safety: Human evaluation on prompts covering safety\n policies including child sexual abuse and exploitation, harassment, violence\n and gore, and hate speech.\n* Text-to-Text Representational Harms: Benchmark against relevant academic\n datasets such as [WinoBias][winobias] and [BBQ Dataset][bbq].\n* Memorization: Automated evaluation of memorization of training data, including\n the risk of personally identifiable information exposure.\n* Large-scale harm: Tests for \"dangerous capabilities,\" such as chemical,\n biological, radiological, and nuclear (CBRN) risks.\n\n#### Evaluation Results\n\nThe results of ethics and safety evaluations are within acceptable thresholds\nfor meeting [internal policies][safety-policies] for categories such as child\nsafety, content safety, representational harms, memorization, large-scale harms.\nOn top of robust internal evaluations, the results of well-known safety\nbenchmarks like BBQ, BOLD, Winogender, Winobias, RealToxicity, and TruthfulQA\nare shown here.\n\n##### Gemma 2.0\n\n| Benchmark | Metric | Gemma 2 IT 9B | Gemma 2 IT 27B |\n| ------------------------ | ------------- | --------------- | ---------------- |\n| [RealToxicity][realtox] | average | 8.25 | 8.84 |\n| [CrowS-Pairs][crows] | top-1 | 37.47 | 36.67 |\n| [BBQ Ambig][bbq] | 1-shot, top-1 | 88.58 | 85.99 |\n| [BBQ Disambig][bbq] | top-1 | 82.67 | 86.94 |\n| [Winogender][winogender] | top-1 | 79.17 | 77.22 |\n| [TruthfulQA][truthfulqa] | | 50.27 | 51.60 |\n| [Winobias 1_2][winobias] | | 78.09 | 81.94 |\n| [Winobias 2_2][winobias] | | 95.32 | 97.22 |\n| [Toxigen][toxigen] | | 39.30 | 38.42 |\n| ------------------------ | ------------- | --------------- | ---------------- |\n\n#### Ethical Considerations and Risks\n\nThe development of large language models (LLMs) raises several ethical concerns.\nIn creating an open model, we have carefully considered the following:\n\n* Bias and Fairness\n * LLMs trained on large-scale, real-world text data can reflect socio-cultural\n biases embedded in the training material. These models underwent careful\n scrutiny, input data pre-processing described and posterior evaluations\n reported in this card.\n* Misinformation and Misuse\n * LLMs can be misused to generate text that is false, misleading, or harmful.\n * Guidelines are provided for responsible use with the model, see the\n [Responsible Generative AI Toolkit][rai-toolkit].\n* Transparency and Accountability:\n * This model card summarizes details on the models' architecture,\n capabilities, limitations, and evaluation processes.\n * A responsibly developed open model offers the opportunity to share\n innovation by making LLM technology accessible to developers and researchers\n across the AI ecosystem.\n\nRisks identified and mitigations:\n\n* Perpetuation of biases: It's encouraged to perform continuous monitoring\n (using evaluation metrics, human review) and the exploration of de-biasing\n techniques during model training, fine-tuning, and other use cases.\n* Generation of harmful content: Mechanisms and guidelines for content safety\n are essential. Developers are encouraged to exercise caution and implement\n appropriate content safety safeguards based on their specific product policies\n and application use cases.\n* Misuse for malicious purposes: Technical limitations and developer and\n end-user education can help mitigate against malicious applications of LLMs.\n Educational resources and reporting mechanisms for users to flag misuse are\n provided. Prohibited uses of Gemma models are outlined in the\n [Gemma Prohibited Use Policy][prohibited-use].\n* Privacy violations: Models were trained on data filtered for removal of PII\n (Personally Identifiable Information). Developers are encouraged to adhere to\n privacy regulations with privacy-preserving techniques.\n\n#### Benefits\n\nAt the time of release, this family of models provides high-performance open\nlarge language model implementations designed from the ground up for Responsible\nAI development compared to similarly sized models.\n\nUsing the benchmark evaluation metrics described in this document, these models\nhave shown to provide superior performance to other, comparably-sized open model\nalternatives.\n\n[rai-toolkit]: https://ai.google.dev/responsible\n[kaggle-gemma]: https://www.kaggle.com/models/google/gemma-2\n[terms]: https://ai.google.dev/gemma/terms\n[vertex-mg-gemma]: https://console.cloud.google.com/vertex-ai/publishers/google/model-garden/335\n[sensitive-info]: https://cloud.google.com/dlp/docs/high-sensitivity-infotypes-reference\n[safety-policies]: https://storage.googleapis.com/gweb-uniblog-publish-prod/documents/2023_Google_AI_Principles_Progress_Update.pdf#page=11\n[prohibited-use]: https://ai.google.dev/gemma/prohibited_use_policy\n[tpu]: https://cloud.google.com/tpu/docs/intro-to-tpu\n[sustainability]: https://sustainability.google/operating-sustainably/\n[jax]: https://github.com/google/jax\n[ml-pathways]: https://blog.google/technology/ai/introducing-pathways-next-generation-ai-architecture/\n[sustainability]: https://sustainability.google/operating-sustainably/\n[foundation-models]: https://ai.google/discover/foundation-models/\n[gemini-2-paper]: https://goo.gle/gemma2report\n[mmlu]: https://arxiv.org/abs/2009.03300\n[hellaswag]: https://arxiv.org/abs/1905.07830\n[piqa]: https://arxiv.org/abs/1911.11641\n[socialiqa]: https://arxiv.org/abs/1904.09728\n[boolq]: https://arxiv.org/abs/1905.10044\n[winogrande]: https://arxiv.org/abs/1907.10641\n[commonsenseqa]: https://arxiv.org/abs/1811.00937\n[openbookqa]: https://arxiv.org/abs/1809.02789\n[arc]: https://arxiv.org/abs/1911.01547\n[triviaqa]: https://arxiv.org/abs/1705.03551\n[naturalq]: https://github.com/google-research-datasets/natural-questions\n[humaneval]: https://arxiv.org/abs/2107.03374\n[mbpp]: https://arxiv.org/abs/2108.07732\n[gsm8k]: https://arxiv.org/abs/2110.14168\n[realtox]: https://arxiv.org/abs/2009.11462\n[bold]: https://arxiv.org/abs/2101.11718\n[crows]: https://aclanthology.org/2020.emnlp-main.154/\n[bbq]: https://arxiv.org/abs/2110.08193v2\n[winogender]: https://arxiv.org/abs/1804.09301\n[truthfulqa]: https://arxiv.org/abs/2109.07958\n[winobias]: https://arxiv.org/abs/1804.06876\n[math]: https://arxiv.org/abs/2103.03874\n[agieval]: https://arxiv.org/abs/2304.06364\n[big-bench]: https://arxiv.org/abs/2206.04615\n[toxigen]: https://arxiv.org/abs/2203.09509\n\n"])</script><script>self.__next_f.push([1,"62:T71fb,"])</script><script>self.__next_f.push([1,"Phi-3 Vision-128K-Instruct: Model Card\n\n# Model Overview\n\n| Developer | Microsoft GenAI |\n|----------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| Description | Phi-3 Vision reasons with image and text inputs. It is a lightweight, state-of-the-art open multimodal model built upon synthetic data and filtered publicly available datasets from websites with a focus on very high-quality, reasoning dense text and vision data. The model belongs to the Phi-3 model family, and the multimodal version comes with 128K context length (in tokens) it can support. The model underwent a rigorous enhancement process, incorporating both supervised fine-tuning and direct preference optimization to ensure precise instruction adherence and robust safety measures. The model is intended for broad commercial and research use in English. |\n| License | [MIT](https://opensource.org/license/mit) | \n| Third-Party Community Consideration | This model is not owned or developed by NVIDIA. This model has been developed and built to a third-party’s requirements for this application and use case. |\n| Architecture | 4.2B parameter Phi-3 Mini language model that contains image encoder, connector, and projector |\n| Inputs | Text and Image. It’s best suited for prompts using the chat format. |\n| Context length | 128K tokens |\n| GPUS | 512 H100-80G |\n| Training time | 1.5 days |\n| Training data | 500B tokens (vision tokens + text tokens) |\n| Outputs | Generates text in response to the input |\n| Dates | The models were trained between March and May 2024. |\n| Status | This is a static model trained on an offline text dataset with cutoff date Mar 15, 2024. Future versions of the tuned models may be released as the authors improve models. |\n| Release Type | Open weight release |\n| Release dates | The model weight is released on May 21, 2024. | |\n\n# Intended Use\n\n| Primary use cases | The model provides uses for general purpose AI systems and applications with visual and text input capabilities which require 1) memory/compute constrained environments; 2) latency bound scenarios; 3) general image understanding; 3) optical character recognition (OCR); 4) chart and table understanding. The model is designed to accelerate research on efficient language and multimodal models for use as a building block for generative AI powered features. |\n|------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| Out-of-scope use cases | The models are not specifically designed or evaluated for all downstream purposes. Developers should consider common limitations of language models as they select use cases, and evaluate and mitigate for accuracy, safety, and fairness before using within a specific downstream use case, particularly for high-risk scenarios. Developers should be aware of and adhere to applicable laws or regulations (including privacy, trade compliance laws, etc.) that are relevant to their use case. **Nothing contained in this Model Card should be interpreted as or deemed a restriction or modification to the license the model is released under.** |\n\n# Data Overview\n\n## Training datasets\n\nThe training data includes a wide variety of sources, and is a combination of 1) publicly available documents filtered rigorously for quality, selected high-quality educational data and code; 2) selected high-quality image-text interleave and video understanding data; 3) newly created synthetic, “textbook-like” data for the purpose of teaching math, coding, common sense reasoning, general knowledge of the world (science, daily activities, theory of mind, etc.), newly created image data, e.g., chart/table/diagram/slides; 4) high quality chat format supervised data covering various topics to reflect human preferences on different aspects such as instruct-following, truthfulness, honesty and helpfulness.\n\nThe data collection process involved sourcing information from publicly available documents, with a meticulous approach to filtering out undesirable documents and images. To safeguard privacy, the authors carefully filtered various image and text data sources to remove or scrub any potentially personal data from the training data. \n \nMore details can be found in the (Phi-3 Technical Report)[https://arxiv.org/abs/2404.14219].\n\n## Benchmark datasets\n\nPublic datasets:\n\n- Popular aggregated benchmark:\n\n - MMMU: massive multi-discipline tasks at college-level subject knowledge and deliberate reasoning\n\n - MMBench: large-scale benchmark to evaluate perception and reasoning capabilities\n\n- Visual reasoning:\n\n - ScienceQA: multimodal visual question answering on science\n\n - MathVista: visual math reasoning\n\n - InterGPS: Visual 2D geometry reasoning\n\n- Chart reasoning:\n\n - ChartQA: visual and logical reasoning on charts\n\n - AI2D: diagram understanding\n\n- Document :\n\n - TextVQA: read and reason about text in images to answer questions about them\n\n- Object Recognition:\n\n - POPE: recognize the presence of objects in images\n\nInternal datasets:\n\n- Microsoft products\n\n - PowerPoint VQA: question answering on PowerPoint (PPT) slides\n\n - Plots \u0026 Charts: visual understanding from figures, plots, and charts\n\n - TextQA: visual question answering on OCR scenarios\n\nRAI \u0026 Security Benchmarks:\n\n- Multimodal model RAI:\n\n - VLGuardExt: [VLGuard](https://arxiv.org/abs/2402.02207) is a vision-language instruction following public dataset for model safety to address safety on deception, discrimination, privacy and risky behavior (advice, sexual, violence, political). The authors then extended to a few internal categories such as child safety and election critical information\n\n - [RTVLM](https://arxiv.org/abs/2401.12915): Public benchmark for red-teaming vision-language model on model truthfulness, privacy, safety, and fairness\n\n - GPTV-RAI: In-house benchmark for GPT-4V released from Azure AI, measuring harmfulness (ex. sexual, violent, hate and self-harm), privacy, jailbreak, misinformation\n\n- Language model RAI:\n\n - LaserTag: measure grounding, third party harm, harmful content continuation, harmful content summarization and jailbreak, leveraged from phi-3 language\n\n - [XSTest](https://arxiv.org/abs/2308.01263): Public benchmark designed to identify exaggerated safety behaviors in large language models, it is introduced to strike a balance between model helpfulness and harmfulness\n\n# Safety\n\n## Approach\n\nThe Phi-3 family of models has adopted a robust safety post-training approach. This approach leverages a variety of both open-source and in-house generated datasets. The overall technique employed to do the safety alignment is a combination of SFT (Supervised Fine-Tuning) and a modified version of RLHF (Reinforcement Learning from Human Feedback) by utilizing human-labeled and synthetic datasets, including publicly available datasets focusing on helpfulness and harmlessness as well as various questions and answers targeted to multiple safety categories.\n\n## Safety Evaluation and Red-Teaming\n\nPrior to release, Phi-3 family of models followed a multi-faceted evaluation approach. Quantitative evaluation was conducted with multiple open-source safety benchmarks and in-house tools utilizing adversarial conversation simulation. For qualitative safety evaluation, the authors collaborated with the AI Red Team at Microsoft to assess safety risks posed by both visual and text inputs, in addition with their combinations. The assessment was done in predetermined in risk categories for both vision and language with automated scoring followed by thorough manual reviews of the model responses.\n\n# Please refer to the technical report for more details of the safety alignment.\n\n# Model Quality\n\nTo understand the capabilities, the authors compare Phi-3 Vision-128K-Instruct with a set of models over a variety of zero-shot benchmarks using the internal benchmark platform BabelBench (See **Appendix A** for benchmark methodology).\n\nAt the high-level overview of the model quality on representative benchmarks:\n\n| Category | Benchmark | Phi-3 Vision-128K-In[^1] | LlaVA-1.6 Vicuna-7B | QWEN-VL Chat | Llama3-Llava-Next-8B | Claude-3 Haiku | Gemini 1.0 Pro V | GPT-4V-Turbo |\n|---------------------------------------|----------------------|--------------------------|---------------------|--------------|----------------------|----------------|------------------|--------------|\n| Popular aggregated benchmark | MMMU (val) | 40.2 | 34.2 | 39.0 | 36.4 | 40.7 | 42.0 | 55.5 |\n| | MMBench (dev-en) | 80.5 | 76.3 | 75.8 | 79.4 | 62.4 | 80.0 | 86.1 |\n| Visual scientific knowledge reasoning | ScienceQA (img-test) | 90.8 | 70.6 | 67.2 | 73.7 | 72.0 | 79.7 | 75.7 |\n| Visual math reasoning | MathVista (testmini) | 44.5 | 31.5 | 29.4 | 34.8 | 33.2 | 35.0 | 47.5 |\n| | InterGPS (test) | 38.1 | 20.5 | 22.3 | 24.6 | 32.1 | 28.6 | 41.0 |\n| Chart reasoning | AI2D (test) | 76.7 | 63.1 | 59.8 | 66.9 | 60.3 | 62.8 | 74.7 |\n| | ChartQA (test) | 81.4 | 55.0 | 50.9 | 65.8 | 59.3 | 58.0 | 62.3 |\n| Document Intelligence | TextVQA (val) | 70.9 | 64.6 | 59.4 | 55.7 | 62.7 | 64.7 | 68.1 |\n| Object visual presence verification | POPE (test) | 85.8 | 87.2 | 82.6 | 87.0 | 74.4 | 84.2 | 83.7 |\n\n[^1]: For internal reference, this is the **Vision-128K-InstructRC 3.1.3** checkpoint of 128k context length (Mini-128K RC1_44L).\n\n##### Internal benchmarks\n\n| | Phi-3 Vision-128K-In | LlaVA-1.6 Vicuna-7B | QWEN-VL Chat | Llama3-Llava-Next-8B | GPT-4V-Turbo |\n|----------------|----------------------|---------------------|--------------|----------------------|--------------|\n| PowerPoint VQA | 75.5 | 49.5 | 55.5 | 49.0 | 86.0 |\n| Plots \u0026 Charts | 64.7 | 52.0 | 43.7 | 53.8 | 83.3 |\n| TextQA | 3.39 | 2.62 | 2.69 | 2.87 | 3.92 |\n\n\u003c!-- ![A diagram of a heart Description automatically generated](model_quality.png) --\u003e\n\nSee **Appendix D** for examples on different capabilities.\n\n# Usage\n\n### Input formats\n\nGiven the nature of the training data, the Phi-3 Vision-128K-Instruct model is best suited for prompts using the chat format as follows:\n\nSingle image:\n\n**\\\u003c\\|user\\|\\\u003e\\\\n\\\u003c\\|image_1\\|\\\u003e\\\\n{prompt}\\\u003c\\|end\\|\\\u003e\\\\n\\\u003c\\|assistant\\|\\\u003e\\\\n**\n\nFor multi-turn conversations:\n\n**\\\u003c\\|user\\|\\\u003e\\\\n\\\u003c\\|image_1\\|\\\u003e\\\\n{prompt_1}\\\u003c\\|end\\|\\\u003e\\\\n\\\u003c\\|assistant\\|\\\u003e\\\\n{response_1}\\\u003c\\|end\\|\\\u003e\\\\n\\\u003c\\|user\\|\\\u003e\\\\n{prompt_2}\\\u003c\\|end\\|\\\u003e\\\\n\\\u003c\\|assistant\\|\\\u003e\\\\n**\n\nAfter obtaining the Phi-3 Vision-128K-Instruct model checkpoints, users can use this sample code for inference. \n\n``` python \n*from* PIL *import* Image\n\n*import* requests\n\n*from* transformers *import* AutoModelForCausalLM\n\n*from* transformers *import* AutoProcessor\n\nmodel_id = \"microsoft/Phi-3-vision-128k-instruct\"\n\nmodel = AutoModelForCausalLM.from_pretrained(\n\nmodel_id,\n\ndevice_map=\"cuda\",\n\ntrust_remote_code=True,\n\ntorch_dtype=\"auto\"\n\n)\n\nprocessor = AutoProcessor.from_pretrained(model_id, trust_remote_code=True)\n\nmessages = [\n\n{\"role\": \"user\", \"content\": \"\\\u003c\\|image_1\\|\\\u003e\\\\nWhat is shown in this image?\"},\n\n{\"role\": \"assistant\", \"content\": \" The chart displays the percentage of respondents who agree with various statements about their preparedness for meetings. It shows five categories: 'Having clear and pre-defined goals for meetings', 'Knowing where to find the information I need for a meeting', 'Understanding my exact role and responsibilities when I'm invited', 'Having tools to manage admin tasks like note-taking or summarization', and 'Having more focus time to sufficiently prepare for meetings'. Each category has an associated bar indicating the level of agreement, measured on a scale from 0% to 100%.\"},\n\n{\"role\": \"user\", \"content\": \"Provide insightful questions to spark discussion.\"}\n\n]\n\nurl = \"https://assets-c4akfrf5b4d3f4b7.z01.azurefd.net/assets/2024/04/BMDataViz_661fb89f3845e.png\"\n\nimage = Image.open(requests.get(url, stream=True).raw)\n\nprompt = processor.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)\n\ninputs = processor(prompt, [image], return_tensors=\"pt\").to(\"cuda:0\")\n\ngeneration_args = {\n\n\"max_new_tokens\": 500,\n\n\"temperature\": 0.0,\n\n\"do_sample\": False,\n\n}\n\ngenerate_ids = model.generate(*\\*\\**inputs, eos_token_id=processor.tokenizer.eos_token_id, *\\*\\**generation_args)\n\nresponse = processor.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]\n\nprint(response)\n\n```\n# Responsible AI Considerations\n\nLike other models, the Phi family of models can potentially behave in ways that are unfair, unreliable, or offensive. Some of the limiting behaviors to be aware of include:\n\n- Quality of Service: The Phi models are trained primarily on English text. Languages other than English will experience worse performance. English language varieties with less representation in the training data might experience worse performance than standard American English.\n\n- Representation of Harms \u0026 Perpetuation of Stereotypes: These models can over- or under-represent groups of people, erase representation of some groups, or reinforce demeaning or negative stereotypes. Despite safety post-training, these limitations may still be present due to differing levels of representation of different groups or prevalence of examples of negative stereotypes in training data that reflect real-world patterns and societal biases.\n\n- Inappropriate or Offensive Content: These models may produce other types of inappropriate or offensive content, which may make it inappropriate to deploy for sensitive contexts without additional mitigations that are specific to the use case.\n\n- Information Reliability: Language models can generate nonsensical content or fabricate content that might sound reasonable but is inaccurate or outdated.\n\n- Limited Scope for Code: Majority of Phi-3 training data is based in Python and use common packages such as \"typing, math, random, collections, datetime, itertools\". If the model generates Python scripts that utilize other packages or scripts in other languages, the authors strongly recommend users manually verify all API uses.\n\nDevelopers should apply responsible AI best practices and are responsible for ensuring that a specific use case complies with relevant laws and regulations (e.g. privacy, trade, etc.). Important areas for consideration include:\n\n- Allocation: Models may not be suitable for scenarios that could have consequential impact on legal status or the allocation of resources or life opportunities (ex: housing, employment, credit, etc.) without further assessments and additional debiasing techniques.\n\n- High-Risk Scenarios: Developers should assess suitability of using models in high-risk scenarios where unfair, unreliable or offensive outputs might be extremely costly or lead to harm. This includes providing advice in sensitive or expert domains where accuracy and reliability are critical (ex: legal or health advice). Additional safeguards should be implemented at the application level according to the deployment context.\n\n- Misinformation: Models may produce inaccurate information. Developers should follow transparency best practices and inform end-users they are interacting with an AI system. At the application level, developers can build feedback mechanisms and pipelines to ground responses in use-case specific, contextual information, a technique known as Retrieval Augmented Generation (RAG).\n\n- Generation of Harmful Content: Developers should assess outputs for their context and use available safety classifiers or custom solutions appropriate for their use case.\n\n- Misuse: Other forms of misuse such as fraud, spam, or malware production may be possible, and developers should ensure that their applications do not violate applicable laws and regulations.\n\n- Identification of individuals: models with vision capabilities may have the potential to uniquely identify individuals in images. Safety post-training steers the model to refuse such requests, but developers should consider and implement, as appropriate, additional mitigations or user consent flows as required in their respective jurisdiction, (e.g., building measures to blur faces in image inputs before processing).\n\n# Appendix A: Benchmark Methodology\n\nThe authors include a brief word on methodology here - and in particular, how the authors think about optimizing prompts and evaluating results.\n\n## Prompts in BabelBench\n\nIn an ideal world, the authors would **never change any prompts** in the benchmarks to ensure it’s always an apples-to-apples comparison when comparing different models. Indeed, this is the default approach, and is the case in the vast majority of models the authors have run to date.\n\nThere are, however, some exceptions to this. In some cases, the authors see a model that performs worse than expected on a given eval *due to a failure to respect the output format*. For example:\n\n- A Claude model may refuse to answer questions (for no apparent reason), or in coding tasks models may prefix their response with “Sure, I can help with that. …” which may break the parser. In such cases, the authors have opted to try different *system messages* (e.g. “You must always respond to a question” or “Get to the point!”).\n\n- With LLaMA-1 models, the authors observed that few shots actually hurt model performance. In this case the authors did allow running the benchmarks with 0-shots for all cases.\n\n- The authors have tools to convert between chat and completions APIs. When converting a chat prompt to a completion prompt, some models have different keywords e.g. Human vs User. In these cases, the authors do allow for model-specific mappings for chat to completion prompts. I would say that this is less common issue today –OpenAI’s chat format is becoming fairly standard.\n\nHowever, **the authors do not**:\n\n- Pick different few-shot examples. Few shots will always be the same when comparing different models.\n\n- Change prompt format: e.g. if it’s an A/B/C/D multiple choice, the authors don’t tweak this to 1/2/3/4 multiple choice.\n\n## Vision Benchmark Settings\n\nThe goal of the benchmark setup is to measure the performance of the LMM when a regular user utilizes these models for a task involving visual input. To this end, the authors selected 9 popular and publicly available datasets that cover a wide range of challenging topics and tasks (e.g., mathematics, OCR tasks, charts-and-plots understanding, etc.) as well as a set of high-quality models.\n\nThe benchmarking setup utilizes zero-shot prompts and all the prompt content are the same for every model. The authors only formatted the prompt content to satisfy the model’s prompt API. This ensures that the evaluation is fair across the set of models the authors tested. Many benchmarks necessitate that models choose their responses from a presented list of options. Therefore, the authors've included a directive in the prompt's conclusion, guiding all models to pick the option letter that corresponds to the answer they deem correct.\n\nIn terms of the visual input, the authors use the images from the benchmarks as they come from the original datasets. The authors converted these images to base-64 using a JPEG encoding for models that require this format (e.g., GPTV, Claude-3 Haiku, Gemini Pro). For other models (e.g., Llava, QWEN-VL, and QWEN-VL Chat), the authors used their Huggingface interface and passed in PIL images or a JPEG image stored locally. The authors did not scale or pre-process images in any other way.\n\nLastly, the authors used the same code to extract answers and evaluate them using the same code for every considered model. This ensured that the authors are fair in assessing the quality of their answers."])</script><script>self.__next_f.push([1,"63:T53d,\u003c% let pyStream = request.stream.toString()[0].toUpperCase() + request.stream.toString().slice(1) %\u003e\nimport requests, base64\n\ninvoke_url = \"https://ai.api.nvidia.com/v1/vlm/microsoft/phi-3-vision-128k-instruct\"\nstream = \u003c%- pyStream %\u003e\n\u003c% let content = \"\" %\u003e\n\u003c% if (request.image_name) { %\u003e\nwith open(\"\u003c%- request.image_name.replaceAll('\"', '\\\\\"') %\u003e\", \"rb\") as f:\n image_b64 = base64.b64encode(f.read()).decode()\n\nassert len(image_b64) \u003c 180_000, \\\n \"To upload larger images, use the assets API (see docs)\"\n \u003c% content = request.prompt.replaceAll(\"'\", \"\\\\'\") + \" \u003cimg src=\\\"data:image/\" + request.image_name.split('.').pop() +\";base64,{image_b64}\\\" /\u003e\"%\u003e\n\u003c% } else { %\u003e\n \u003c% content = request.prompt.replaceAll(\"'\", \"\\\\'\") %\u003e\n\u003c% } %\u003e\n\nheaders = {\n \"Authorization\": \"Bearer $NVIDIA_API_KEY\",\n \"Accept\": \"text/event-stream\" if stream else \"application/json\"\n}\n\npayload = {\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": f'\u003c%- content %\u003e'\n }\n ],\n \"max_tokens\": \u003c%- request.max_tokens %\u003e,\n \"temperature\": \u003c%- request.temperature.toFixed(2) %\u003e,\n \"top_p\": \u003c%- request.top_p.toFixed(2) %\u003e,\n \"stream\": stream\n}\n\nresponse = requests.post(invoke_url, headers=headers, json=payload)\n\nif stream:\n for line in response.iter_lines():\n if line:\n print(line.decode(\"utf-8\"))\nelse:\n print(response.json())\n64:T5ee,import axios from 'axios';\nimport { readFile } from 'node:fs/promises';\n\nconst invokeUrl = \"https://ai.api.nvidia.com/v1/vlm/microsoft/phi-3-vision-128k-instruct\";\nconst stream = \u003c%- request.stream %\u003e;\n\nconst headers = {\n \"Authorization\": \"Bearer $NVIDIA_API_KEY\",\n \"Accept\": stream ? \"text/event-stream\" : \"application/json\"\n};\n \u003c% if (request.image_name) { %\u003e\n \u003c% content = request.prompt +\" \u003cimg src=\\\"data:image/\" + request.image_name.split('.').pop() + \";base64,${imageB64}\\\" /\u003e\" %\u003e\nreadFile(\"\u003c%- request.image_name.replaceAll('\"', '\\\\\"') %\u003e\")\n .then(data =\u003e {\n const imageB64 = Buffer.from(data).toString('base64');\n if (imageB64.length \u003e 180_000) {\n throw new Erro"])</script><script>self.__next_f.push([1,"r(\"To upload larger images, use the assets API (see docs)\");\n }\n \u003c% } else { %\u003e\n \u003c% content = request.prompt %\u003e\n \u003c% } %\u003e\n const payload = {\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": `\u003c%- content %\u003e`\n }\n ],\n \"max_tokens\": \u003c%- request.max_tokens %\u003e,\n \"temperature\": \u003c%- request.temperature.toFixed(2) %\u003e,\n \"top_p\": \u003c%- request.top_p.toFixed(2) %\u003e,\n \"stream\": stream\n };\n\n return axios.post(invokeUrl, payload, { headers: headers, responseType: stream ? 'stream' : 'json' });\n })\n .then(response =\u003e {\n if (stream) {\n response.data.on('data', (chunk) =\u003e {\n console.log(chunk.toString());\n });\n } else {\n console.log(JSON.stringify(response.data));\n }\n })\n .catch(error =\u003e {\n console.error(error);\n });\n65:T404,stream=\u003c%- request.stream %\u003e\n\nif [ \"$stream\" = true ]; then\n accept_header='Accept: text/event-stream'\nelse\n accept_header='Accept: application/json'\nfi\n\u003c% if (request.image_name) { %\u003e\n\u003c% content = request.prompt.replaceAll('\"', '\\\\\"').replaceAll(\"'\", \"'\\\"'\\\"'\") +\" \u003cimg src=\\\\\\\"data:image/\" + request.image_name.split('.').pop() + \";base64,'\\\"\\$image_b64\\\"'\\\\\\\" /\u003e\" %\u003e\nimage_b64=$( base64 \u003c%- request.image_name %\u003e )\n\u003c% } else { %\u003e\n\u003c% content = request.prompt.replaceAll('\"', '\\\\\"').replaceAll(\"'\", \"'\\\"'\\\"'\") %\u003e\n\u003c% } %\u003e\necho '{\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"\u003c%- content %\u003e\"\n }\n ],\n \"max_tokens\": \u003c%- request.max_tokens %\u003e,\n \"temperature\": \u003c%- request.temperature.toFixed(2) %\u003e,\n \"top_p\": \u003c%- request.top_p.toFixed(2) %\u003e,\n \"stream\": \u003c%- request.stream %\u003e\n}' \u003e payload.json\n\ncurl https://ai.api.nvidia.com/v1/vlm/microsoft/phi-3-vision-128k-instruct \\\n -H \"Authorization: Bearer $NVIDIA_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -H \"$accept_header\" \\\n -d @payload.json\n"])</script><script>self.__next_f.push([1,"1e:[\"$\",\"$L3c\",null,{\"data\":[{\"endpoint\":{\"requestStatus\":{\"statusCode\":\"SUCCESS\",\"requestId\":\"7686913d-a546-4330-a6b8-3e3619f5b52b\"},\"artifact\":{\"orgName\":\"qc69jvmznzxy\",\"labels\":[\"Chat\",\"Language Generation\",\"Text-to-Text\",\"Code Generation\"],\"bias\":\"Field | Response\\n:---------------------------------------------------------------------------------------------------|:---------------\\nParticipation considerations from adversely impacted groups [protected classes](https://www.senate.ca.gov/content/protected-classes) in model design and testing: | None\\nMeasures taken to mitigate against unwanted bias: | None\",\"logo\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/llama-3_1-nemotron-70b-instruct.jpg\",\"shortDescription\":\"Llama-3.1-Nemotron-70B-Instruct is a large language model customized by NVIDIA in order to improve the helpfulness of LLM generated responses.\",\"safetyAndSecurity\":\"Field | Response\\n:---------------------------------------------------|:----------------------------------\\nModel Application(s): | Conversation, Question Answering, Summarization\\nDescribe the life-critical impact (if present). | None Known\\nUse Case Restrictions: | See https://github.com/meta-llama/llama-models/blob/main/models/llama3_1/LICENSE \\nModel and dataset restrictions: | The Principle of least privilege (PoLP) is applied limiting access for dataset generation and model development. Restrictions enforce dataset access during training, and dataset license constraints adhered to.\",\"privacy\":\"$3d\",\"isReadOnly\":true,\"description\":\"$3e\",\"canGuestDownload\":true,\"isPublic\":true,\"createdDate\":\"2024-10-15T16:05:16.718Z\",\"publisher\":\"nvidia\",\"displayName\":\"llama-3.1-nemotron-70b-instruct\",\"name\":\"llama-3_1-nemotron-70b-instruct\",\"explainability\":\"$3f\",\"updatedDate\":\"2024-11-18T13:11:20.741Z\",\"attributes\":[{\"key\":\"AVAILABLE\",\"value\":\"true\"},{\"key\":\"PREVIEW\",\"value\":\"false\"}],\"artifactType\":\"ENDPOINT\"}},\"spec\":{\"openAPISpec\":{\"openapi\":\"3.1.0\",\"info\":{\"title\":\"NVIDIA NIM API for nvidia/llama-3.1-nemotron-70b-instruct\",\"description\":\"The NVIDIA NIM REST API. 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See https://platform.openai.com/docs/api-reference/chat/create\",\"requestBody\":{\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ChatCompletionRequest\"}}},\"required\":true},\"responses\":{\"200\":{\"description\":\"Successful Response\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ChatCompletionResponse\"}}}},\"402\":{\"description\":\"Payment Required\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/PaymentRequiredError\"}}}},\"422\":{\"description\":\"Validation Error\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/HTTPValidationError\"}}}}},\"x-nvai-meta\":{\"name\":\"Create chat completion\",\"returns\":\"Returns a [chat completion](/docs/api-reference/chat/object) object, or a streamed sequence of [chat completion chunk](/docs/api-reference/chat/streaming) objects if the request is streamed.\\n\",\"path\":\"create\",\"examples\":[{\"name\":\"Write a limerick about the wonders of GPU computing.\",\"requestJson\":\"{\\n \\\"model\\\": \\\"nvidia/llama-3.1-nemotron-70b-instruct\\\",\\n \\\"messages\\\": [\\n {\\n \\\"role\\\": \\\"system\\\",\\n \\\"content\\\": \\\"You are a helpful assistant.\\\"\\n },\\n {\\n \\\"role\\\": \\\"user\\\",\\n \\\"content\\\": \\\"Write a limerick about the wonders of GPU computing.\\\"\\n }\\n ],\\n \\\"top_p\\\": 0.7,\\n \\\"max_tokens\\\": 1024,\\n \\\"seed\\\": 42,\\n \\\"stop\\\": null,\\n \\\"stream\\\": true\\n}\\n\",\"responseJson\":\"{\\n \\\"id\\\": \\\"id-123\\\",\\n \\\"object\\\": \\\"chat.completion\\\",\\n \\\"created\\\": 1677652288,\\n \\\"model\\\": \\\"nvidia/llama-3.1-nemotron-70b-instruct\\\",\\n \\\"system_fingerprint\\\": \\\"fp_44709d6fcb\\\",\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"Here's a short poem on...\\\"\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 9,\\n \\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"},{\"name\":\"What can I see at NVIDIA's GPU Technology Conference?\",\"requestJson\":\"{\\n \\\"model\\\": \\\"nvidia/llama-3.1-nemotron-70b-instruct\\\",\\n \\\"messages\\\": [\\n {\\n \\\"role\\\": \\\"system\\\",\\n \\\"content\\\": \\\"You are a helpful assistant.\\\"\\n },\\n {\\n \\\"role\\\": \\\"user\\\",\\n \\\"content\\\": \\\"What can I see at NVIDIA's GPU Technology Conference?\\\"\\n }\\n ],\\n \\\"top_p\\\": 0.7,\\n \\\"max_tokens\\\": 1024,\\n \\\"seed\\\": 42,\\n \\\"stop\\\": null,\\n \\\"stream\\\": true\\n}\\n\",\"responseJson\":\"{\\n \\\"id\\\": \\\"id-123\\\",\\n \\\"object\\\": \\\"chat.completion\\\",\\n \\\"created\\\": 1677652288,\\n \\\"model\\\": \\\"nvidia/llama-3.1-nemotron-70b-instruct\\\",\\n \\\"system_fingerprint\\\": \\\"fp_44709d6fcb\\\",\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"At NVIDIA's GTC conference...\\\"\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 9,\\n \\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"}],\"templates\":[{\"title\":\"No Streaming\",\"requestEjs\":{\"python\":\"from openai import OpenAI\\n\\nclient = OpenAI(\\n base_url = \\\"https://integrate.api.nvidia.com/v1\\\",\\n api_key = \\\"$NVIDIA_API_KEY\\\"\\n)\\n\\ncompletion = client.chat.completions.create(\\n model=\\\"\u003c%- request.model %\u003e\\\",\\n messages=\u003c%- JSON.stringify(request.messages) %\u003e,\\n temperature=\u003c%- request.temperature %\u003e,\\n top_p=\u003c%- request.top_p %\u003e,\\n max_tokens=\u003c%- request.max_tokens %\u003e,\\n stream=\u003c%- request.stream?.toString()[0].toUpperCase() + request.stream?.toString().slice(1) %\u003e\\n)\\n\u003c% if (request.stream) { %\u003e\\nfor chunk in completion:\\n if chunk.choices[0].delta.content is not None:\\n print(chunk.choices[0].delta.content, end=\\\"\\\")\\n\u003c% } else { %\u003e\\nprint(completion.choices[0].message)\\n\u003c% } %\u003e\\n\",\"node.js\":\"import OpenAI from 'openai';\\n\\nconst openai = new OpenAI({\\n apiKey: '$NVIDIA_API_KEY',\\n baseURL: 'https://integrate.api.nvidia.com/v1',\\n})\\n\\nasync function main() {\\n const completion = await openai.chat.completions.create({\\n model: \\\"\u003c%- request.model %\u003e\\\",\\n messages: \u003c%- JSON.stringify(request.messages) %\u003e,\\n temperature: \u003c%- request.temperature %\u003e,\\n top_p: \u003c%- request.top_p %\u003e,\\n max_tokens: \u003c%- request.max_tokens %\u003e,\\n stream: \u003c%- request.stream %\u003e,\\n })\\n \u003c% if (request.stream) { %\u003e\\n for await (const chunk of completion) {\\n process.stdout.write(chunk.choices[0]?.delta?.content || '')\\n }\\n \u003c% } else { %\u003e\\n process.stdout.write(completion.choices[0]?.message?.content);\\n \u003c% } %\u003e\\n}\\n\\nmain();\",\"curl\":\"curl https://integrate.api.nvidia.com/v1/chat/completions \\\\\\n -H \\\"Content-Type: application/json\\\" \\\\\\n -H \\\"Authorization: Bearer $NVIDIA_API_KEY\\\" \\\\\\n -d '{\\n \\\"model\\\": \\\"nvidia/llama-3.1-nemotron-70b-instruct\\\",\\n \\\"messages\\\": \u003c%- JSON.stringify(request.messages).replaceAll(\\\"'\\\", \\\"'\\\\\\\"'\\\\\\\"'\\\") %\u003e,\\n \\\"temperature\\\": \u003c%- request.temperature %\u003e, \\n \\\"top_p\\\": \u003c%- request.top_p %\u003e,\\n \\\"max_tokens\\\": \u003c%- request.max_tokens %\u003e,\\n \\\"stream\\\": \u003c%- request.stream %\u003e \\n }'\\n\"},\"response\":\"{\\n \\\"id\\\": \\\"chatcmpl-123\\\",\\n \\\"object\\\": \\\"chat.completion\\\",\\n \\\"created\\\": 1677652288,\\n \\\"model\\\": \\\"nvidia/llama-3.1-nemotron-70b-instruct\\\",\\n \\\"system_fingerprint\\\": \\\"fp_44709d6fcb\\\",\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"\\\\n\\\\nHello there, how may I assist you today?\\\",\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 9,\\n \\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"}]}}}},\"security\":[{\"Token\":[]}],\"components\":{\"securitySchemes\":{\"Token\":{\"type\":\"http\",\"scheme\":\"bearer\"}},\"schemas\":{\"ChatCompletionRequest\":{\"properties\":{\"model\":{\"type\":\"string\",\"title\":\"Model\",\"default\":\"nvidia/llama-3.1-nemotron-70b-instruct\"},\"max_tokens\":{\"type\":\"integer\",\"minimum\":1,\"title\":\"Max Tokens\",\"description\":\"The maximum number of tokens to generate in any given call. Note that the model is not aware of this value, and generation will simply stop at the number of tokens specified.\",\"default\":1024},\"stream\":{\"type\":\"boolean\",\"title\":\"Stream\",\"description\":\"If set, partial message deltas will be sent. Tokens will be sent as data-only server-sent events (SSE) as they become available (JSON responses are prefixed by `data: `), with the stream terminated by a `data: [DONE]` message.\",\"default\":false},\"temperature\":{\"type\":\"number\",\"maximum\":1,\"minimum\":0,\"title\":\"Temperature\",\"description\":\"The sampling temperature to use for text generation. The higher the temperature value is, the less deterministic the output text will be. It is not recommended to modify both temperature and top_p in the same call.\",\"default\":0.5},\"top_p\":{\"type\":\"number\",\"maximum\":1,\"exclusiveMinimum\":0,\"title\":\"Top P\",\"description\":\"The top-p sampling mass used for text generation. The top-p value determines the probability mass that is sampled at sampling time. For example, if top_p = 0.2, only the most likely tokens (summing to 0.2 cumulative probability) will be sampled. It is not recommended to modify both temperature and top_p in the same call.\",\"default\":1},\"stop\":{\"anyOf\":[{\"items\":{\"type\":\"string\"},\"type\":\"array\"},{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Stop\",\"description\":\"A string or a list of strings where the API will stop generating further tokens. The returned text will not contain the stop sequence.\",\"examples\":[null]},\"frequency_penalty\":{\"type\":\"number\",\"maximum\":2,\"minimum\":-2,\"default\":0,\"title\":\"Frequency Penalty\",\"description\":\"Indicates how much to penalize new tokens based on their existing frequency in the text so far, decreasing model likelihood to repeat the same line verbatim.\"},\"presence_penalty\":{\"type\":\"number\",\"maximum\":2,\"minimum\":-2,\"default\":0,\"title\":\"Presence Penalty\",\"description\":\"Positive values penalize new tokens based on whether they appear in the text so far, increasing model likelihood to talk about new topics.\"},\"seed\":{\"type\":\"integer\",\"maximum\":18446744073709552000,\"minimum\":0,\"title\":\"Seed\",\"description\":\"The model generates random results. Changing the input seed alone will produce a different response with similar characteristics. It is possible to reproduce results by fixing the input seed (assuming all other hyperparameters are also fixed).\",\"default\":0},\"messages\":{\"anyOf\":[{\"items\":{\"additionalProperties\":{\"type\":\"string\"},\"type\":\"object\"},\"type\":\"array\"}],\"title\":\"Messages\",\"description\":\"A list of messages comprising the conversation so far.\",\"examples\":[[{\"role\":\"user\",\"content\":\"Write a limerick about the wonders of GPU computing.\"}]]}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"messages\"],\"title\":\"ChatCompletionRequest\",\"description\":\"OpenAI ChatCompletionRequest\"},\"ChatCompletionResponse\":{\"properties\":{\"id\":{\"type\":\"string\",\"title\":\"Id\",\"description\":\"A unique identifier for the completion.\"},\"object\":{\"type\":\"string\",\"title\":\"Object\",\"default\":\"chat.completion\"},\"created\":{\"type\":\"integer\",\"title\":\"Created\"},\"model\":{\"type\":\"string\",\"title\":\"Model\",\"example\":\"nvidia/llama-3.1-nemotron-70b-instruct\"},\"choices\":{\"items\":{\"$ref\":\"#/components/schemas/ChatCompletionResponseChoice\"},\"type\":\"array\",\"title\":\"Choices\",\"description\":\"The list of completion choices the model generated for the input prompt.\"},\"usage\":{\"$ref\":\"#/components/schemas/UsageInfo\",\"description\":\"Usage statistics for the completion request.\"}},\"type\":\"object\",\"required\":[\"model\",\"choices\",\"usage\"],\"title\":\"ChatCompletionResponse\"},\"ChatCompletionResponseChoice\":{\"properties\":{\"index\":{\"type\":\"integer\",\"title\":\"Index\",\"description\":\"The index of the choice in the list of choices (always 0).\"},\"message\":{\"$ref\":\"#/components/schemas/ChatMessage\",\"description\":\"A chat completion message generated by the model.\"},\"finish_reason\":{\"anyOf\":[{\"type\":\"string\",\"enum\":[\"stop\",\"length\"]},{\"type\":\"null\"}],\"title\":\"Finish Reason\",\"description\":\"The reason the model stopped generating tokens. This will be `stop` if the model hit a natural stop point or a provided stop sequence, or `length` if the maximum number of tokens specified in the request was reached. Will be `null` if the model has not finished\"}},\"type\":\"object\",\"required\":[\"index\",\"message\"],\"title\":\"ChatCompletionResponseChoice\"},\"ChatMessage\":{\"properties\":{\"role\":{\"type\":\"string\",\"title\":\"Role\",\"description\":\"The role of the message author.\"},\"content\":{\"type\":\"string\",\"title\":\"Content\",\"description\":\"The contents of the message.\"}},\"type\":\"object\",\"required\":[\"role\",\"content\"],\"title\":\"ChatMessage\"},\"HTTPValidationError\":{\"properties\":{\"detail\":{\"items\":{\"$ref\":\"#/components/schemas/ValidationError\"},\"type\":\"array\",\"title\":\"Detail\",\"description\":\"Detailed information about the error.\"}},\"type\":\"object\",\"title\":\"HTTPValidationError\"},\"PaymentRequiredError\":{\"properties\":{\"detail\":{\"type\":\"string\",\"description\":\"Contains specific information related to the error and why it occurred.\",\"example\":\"You have reached your limit of credits.\"}},\"type\":\"object\",\"title\":\"PaymentRequiredError\"},\"UsageInfo\":{\"properties\":{\"prompt_tokens\":{\"type\":\"integer\",\"title\":\"Prompt Tokens\",\"description\":\"Number of tokens in the prompt.\",\"default\":0},\"total_tokens\":{\"type\":\"integer\",\"title\":\"Total Tokens\",\"description\":\"Total number of tokens used in the request (prompt + completion).\",\"default\":0},\"completion_tokens\":{\"anyOf\":[{\"type\":\"integer\"},{\"type\":\"null\"}],\"title\":\"Completion Tokens\",\"description\":\"Number of tokens in the generated completion.\",\"default\":0}},\"type\":\"object\",\"title\":\"UsageInfo\"},\"ValidationError\":{\"properties\":{\"loc\":{\"items\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"integer\"}]},\"type\":\"array\",\"title\":\"Location\"},\"msg\":{\"type\":\"string\",\"title\":\"Message\",\"description\":\"The error message.\"},\"type\":{\"type\":\"string\",\"title\":\"Error Type\",\"description\":\"Error type\"}},\"type\":\"object\",\"required\":[\"loc\",\"msg\",\"type\"],\"title\":\"ValidationError\"}}}},\"namespace\":\"qc69jvmznzxy\",\"updatedDate\":\"2024-11-18T13:11:21.421Z\",\"nvcfFunctionId\":\"9b96341b-9791-4db9-a00d-4e43aa192a39\",\"createdDate\":\"2024-10-15T16:05:17.117Z\",\"attributes\":{\"dockerRun\":\"Pull and run the NVIDIA NIM with the command below. This will download the optimized model for your infrastructure.\\n```bash\\nexport NGC_API_KEY=\u003cPASTE_API_KEY_HERE\u003e\\nexport LOCAL_NIM_CACHE=~/.cache/nim\\nmkdir -p \\\"$LOCAL_NIM_CACHE\\\"\\ndocker run -it --rm \\\\\\n --gpus all \\\\\\n --shm-size=16GB \\\\\\n -e NGC_API_KEY \\\\\\n -v \\\"$LOCAL_NIM_CACHE:/opt/nim/.cache\\\" \\\\\\n -u $(id -u) \\\\\\n -p 8000:8000 \\\\\\n nvcr.io/nim/nvidia/llama-3.1-nemotron-70b-instruct:latest\\n```\\n\\nYou can now make a local API call using this curl command:\\n```bash\\ncurl -X 'POST' \\\\\\n'http://0.0.0.0:8000/v1/chat/completions' \\\\\\n-H 'accept: application/json' \\\\\\n-H 'Content-Type: application/json' \\\\\\n-d '{\\n \\\"model\\\": \\\"nvidia/llama-3.1-nemotron-70b-instruct\\\",\\n \\\"messages\\\": [{\\\"role\\\":\\\"user\\\", \\\"content\\\":\\\"Write a limerick about the wonders of GPU computing.\\\"}],\\n \\\"max_tokens\\\": 64\\n}'\\n```\\n\\nFor more details on getting started with this NIM, visit the [NVIDIA NIM Docs](https://docs.nvidia.com/nim/large-language-models/latest/getting-started.html).\\n\",\"dockerTermsOfUse\":\"By running the below commands, you accept the \u003ca href=\\\"https://www.nvidia.com/en-us/data-center/products/nvidia-ai-enterprise/eula/\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA AI Enterprise Terms of Use\u003c/a\u003e and the \u003ca href=\\\"https://docs.nvidia.com/ai-foundation-models-community-license.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA Community Models License\u003c/a\u003e.\\n\",\"showUnavailableBanner\":false,\"apiDocsUrl\":\"https://docs.api.nvidia.com/nim/reference/nvidia-llama-3_1-nemotron-70b-instruct\",\"playground\":{\"type\":\"chat\"},\"termsOfUse\":\"\u003cb\u003eGOVERNING TERMS\u003c/b\u003e: This trial service is governed by the \u003ca href=\\\"https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA API Trial Terms of Service\u003c/a\u003e. Use of this model is governed by the \u003ca href=\\\"https://docs.nvidia.com/ai-foundation-models-community-license.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003e AI Foundation Models Community License Agreement \u003c/a\u003e. ADDITIONAL INFORMATION: Llama 3.1 Community License Agreement, Built with Llama.\\n\",\"cta\":{\"text\":\"Apply to Self-Host\",\"url\":\"https://www.nvidia.com/en-us/ai/nim-notifyme/\",\"nim_available_override_url\":\"https://catalog.ngc.nvidia.com/orgs/nim/teams/nvidia/containers/llama-3.1-nemotron-70b-instruct\"}},\"artifactName\":\"llama-3_1-nemotron-70b-instruct\"},\"config\":{\"name\":\"llama-3_1-nemotron-70b-instruct\",\"type\":\"model\"}},{\"endpoint\":{\"requestStatus\":{\"statusCode\":\"SUCCESS\",\"requestId\":\"0ce7a0ee-86b4-49df-84c7-9cb78180eedf\"},\"artifact\":{\"orgName\":\"qc69jvmznzxy\",\"labels\":[\"Synthetic data generation\",\"chat\",\"Code Generation\"],\"logo\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/llama-3_1-405b-instruct.jpg\",\"shortDescription\":\"Advanced LLM for synthetic data generation, distillation, and inference for chatbots, coding, and domain-specific tasks.\",\"isReadOnly\":true,\"description\":\"$40\",\"canGuestDownload\":true,\"isPublic\":true,\"createdDate\":\"2024-07-23T14:58:23.459Z\",\"publisher\":\"meta\",\"displayName\":\"llama-3.1-405b-instruct\",\"name\":\"llama-3_1-405b-instruct\",\"updatedDate\":\"2024-11-20T03:12:22.964Z\",\"attributes\":[{\"key\":\"AVAILABLE\",\"value\":\"true\"},{\"key\":\"PREVIEW\",\"value\":\"false\"}],\"artifactType\":\"ENDPOINT\"}},\"spec\":{\"openAPISpec\":{\"openapi\":\"3.1.0\",\"info\":{\"title\":\"NVIDIA NIM API for meta/llama-3.1-405b-instruct\",\"description\":\"The NVIDIA NIM REST API. Please see https://docs.api.nvidia.com/nim/reference/meta-llama-3_1-405b-instruct for more details.\",\"version\":\"1.0.0\",\"termsOfService\":\"https://www.nvidia.com/en-us/data-center/products/nvidia-ai-enterprise/eula/\",\"contact\":{\"name\":\"NVIDIA Enterprise Support\",\"url\":\"https://www.nvidia.com/en-us/support/enterprise/\"},\"license\":{\"name\":\"Llama 3.1 License\",\"url\":\"https://github.com/meta-llama/llama-models/blob/main/License/Llama3.1.txt\"}},\"servers\":[{\"url\":\"https://integrate.api.nvidia.com/v1/\"}],\"paths\":{\"/chat/completions\":{\"post\":{\"operationId\":\"create_chat_completion_v1_chat_completions_post\",\"tags\":[\"Chat\"],\"summary\":\"Creates a model response for the given chat conversation.\",\"description\":\"Given a list of messages comprising a conversation, the model will return a response. Compatible with OpenAI. See https://platform.openai.com/docs/api-reference/chat/create\",\"requestBody\":{\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ChatRequest\"}}},\"required\":true},\"responses\":{\"200\":{\"description\":\"Invocation is fulfilled\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ChatCompletion\"}},\"text/event-stream\":{\"schema\":{\"$ref\":\"#/components/schemas/ChatCompletionChunk\"}}}},\"202\":{\"description\":\"Result is pending. Client should poll using the requestId.\\n\",\"content\":{\"application/json\":{\"example\":{},\"schema\":{}}},\"headers\":{\"NVCF-REQID\":{\"description\":\"requestId required for pooling\",\"schema\":{\"type\":\"string\",\"format\":\"uuid\"}},\"NVCF-STATUS\":{\"description\":\"Invocation status\",\"schema\":{\"type\":\"string\"}}}},\"422\":{\"description\":\"Validation failed, provided entity could not be processed.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/Errors\"},\"example\":{\"type\":\"urn:nvcf-worker-service:problem-details:unprocessable-entity\",\"title\":\"Unprocessable Entity\",\"status\":422,\"detail\":\"string\",\"instance\":\"/v2/nvcf/pexec/functions/4a58c6cb-a9b4-4014-99de-3e704d4ae687\",\"requestId\":\"3fa85f64-5717-4562-b3fc-2c963f66afa6\"}}}},\"500\":{\"description\":\"The invocation ended with an error.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/Errors\"},\"example\":{\"type\":\"urn:nvcf-worker-service:problem-details:internal-server-error\",\"title\":\"Internal Server Error\",\"status\":500,\"detail\":\"string\",\"instance\":\"/v2/nvcf/pexec/functions/4a58c6cb-a9b4-4014-99de-3e704d4ae687\",\"requestId\":\"3fa85f64-5717-4562-b3fc-2c963f66afa6\"}}}}},\"x-nvai-meta\":{\"name\":\"Create chat completion\",\"returns\":\"Returns a [chat completion](/docs/api-reference/chat/object) object, or a streamed sequence of [chat completion chunk](/docs/api-reference/chat/streaming) objects if the request is streamed.\\n\",\"path\":\"create\",\"examples\":[{\"name\":\"Write a limerick about the wonders of GPU computing.\",\"requestJson\":\"{\\n \\\"model\\\": \\\"meta/llama-3.1-405b-instruct\\\",\\n \\\"messages\\\": [\\n {\\n \\\"role\\\": \\\"user\\\",\\n \\\"content\\\": \\\"Write a limerick about the wonders of GPU computing.\\\"\\n }\\n ],\\n \\\"top_p\\\": 0.7,\\n \\\"max_tokens\\\": 1024,\\n \\\"seed\\\": 42,\\n \\\"stream\\\": true\\n}\\n\",\"responseJson\":\"{\\n \\\"id\\\": \\\"id-123\\\",\\n \\\"object\\\": \\\"chat.completion\\\",\\n \\\"created\\\": 1677652288,\\n \\\"model\\\": \\\"meta/llama-3.1-405b-instruct\\\",\\n \\\"system_fingerprint\\\": \\\"fp_44709d6fcb\\\",\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"The python functions...\\\"\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 9,\\n \\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"},{\"name\":\"Tell me about Dumbledore.\",\"requestJson\":\"$41\",\"responseJson\":\"{\\n \\\"id\\\": \\\"id-123\\\",\\n \\\"object\\\": \\\"chat.completion\\\",\\n \\\"created\\\": 1677652288,\\n \\\"model\\\": \\\"meta/llama-3.1-405b-instruct\\\",\\n \\\"system_fingerprint\\\": \\\"fp_44709d6fcb\\\",\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"At NVIDIA's GPU Technology Conference (GTC)...\\\"\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 9,\\n \\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"},{\"name\":\"What is the weather in Santa Clara, CA?\",\"requestJson\":\"$42\",\"responseJson\":\"{\\n \\\"id\\\": \\\"id-123\\\",\\n \\\"object\\\": \\\"chat.completion\\\",\\n \\\"created\\\": 1677652288,\\n \\\"model\\\": \\\"meta/llama-3.1-405b-instruct\\\",\\n \\\"system_fingerprint\\\": \\\"fp_44709d6fcb\\\",\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"At NVIDIA's GPU Technology Conference (GTC)...\\\"\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 9,\\n \\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"}],\"templates\":[{\"title\":\"No Streaming\",\"requestEjs\":{\"python\":\"$43\",\"langChain\":\"from langchain_nvidia_ai_endpoints import ChatNVIDIA\\n\\nclient = ChatNVIDIA(\\n model=\\\"\u003c%- request.model %\u003e\\\",\\n api_key=\\\"$NVIDIA_API_KEY\\\", \\n temperature=\u003c%- request.temperature %\u003e,\\n top_p=\u003c%- request.top_p %\u003e,\\n max_tokens=\u003c%- request.max_tokens %\u003e,\\n)\\n\u003c% if (request.stream) { %\u003e\\nfor chunk in client.stream(\u003c%- JSON.stringify(request.messages) %\u003e): \\n print(chunk.content, end=\\\"\\\")\\n\u003c% } else { %\u003e\\nresponse = client.invoke(\u003c%- JSON.stringify(request.messages) %\u003e)\\nprint(response.content)\\n\u003c% } %\u003e\\n \\n\",\"node.js\":\"$44\",\"curl\":\"$45\"},\"response\":\"{\\n \\\"id\\\": \\\"chatcmpl-123\\\",\\n \\\"object\\\": \\\"chat.completion\\\",\\n \\\"created\\\": 1677652288,\\n \\\"model\\\": \\\"meta/llama-3.1-405b-instruct\\\",\\n \\\"system_fingerprint\\\": \\\"fp_44709d6fcb\\\",\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"\\\\n\\\\nHello there, how may I assist you today?\\\",\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 9,\\n \\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"}]}}}},\"security\":[{\"Token\":[]}],\"components\":{\"securitySchemes\":{\"Token\":{\"type\":\"http\",\"scheme\":\"bearer\"}},\"schemas\":{\"Errors\":{\"properties\":{\"type\":{\"type\":\"string\",\"description\":\"Error type\"},\"title\":{\"type\":\"string\",\"description\":\"Error title\"},\"status\":{\"type\":\"integer\",\"description\":\"Error status code\"},\"detail\":{\"type\":\"string\",\"description\":\"Detailed information about the error\"},\"instance\":{\"type\":\"string\",\"description\":\"Function instance used to invoke the request\"},\"requestId\":{\"type\":\"string\",\"format\":\"uuid\",\"description\":\"UUID of the request\"}},\"type\":\"object\",\"required\":[\"type\",\"title\",\"status\",\"detail\",\"instance\",\"requestId\"],\"title\":\"InvokeError\"},\"ChatCompletion\":{\"properties\":{\"id\":{\"description\":\"A unique identifier for the completion.\",\"format\":\"uuid\",\"title\":\"Id\",\"type\":\"string\"},\"choices\":{\"description\":\"The list of completion choices the model generated for the input prompt.\",\"items\":{\"$ref\":\"#/components/schemas/Choice\"},\"title\":\"Choices\",\"type\":\"array\"},\"usage\":{\"allOf\":[{\"$ref\":\"#/components/schemas/Usage\"}],\"description\":\"Usage statistics for the completion request.\"}},\"required\":[\"id\",\"choices\",\"usage\"],\"title\":\"ChatCompletion\",\"type\":\"object\"},\"ChatCompletionChunk\":{\"properties\":{\"id\":{\"description\":\"A unique identifier for the completion.\",\"format\":\"uuid\",\"title\":\"Id\",\"type\":\"string\"},\"choices\":{\"description\":\"The list of completion choices the model generated for the input prompt.\",\"items\":{\"$ref\":\"#/components/schemas/ChoiceChunk\"},\"title\":\"Choices\",\"type\":\"array\"}},\"required\":[\"id\",\"choices\"],\"title\":\"ChatCompletionChunk\",\"type\":\"object\"},\"ChatRequest\":{\"additionalProperties\":false,\"properties\":{\"model\":{\"type\":\"string\",\"title\":\"Model\",\"default\":\"meta/llama-3.1-405b-instruct\"},\"messages\":{\"description\":\"A list of messages comprising the conversation so far. The roles of the messages must be alternating between `user` and `assistant`. The last input message should have role `user`. A message with the the `system` role is optional, and must be the very first message if it is present; `context` is also optional, but must come before a user question.\",\"examples\":[[{\"content\":\"I am going to Paris, what should I see?\",\"role\":\"user\"}]],\"items\":{\"$ref\":\"#/components/schemas/Message\"},\"title\":\"Messages\",\"type\":\"array\"},\"temperature\":{\"default\":0.2,\"description\":\"The sampling temperature to use for text generation. The higher the temperature value is, the less deterministic the output text will be. It is not recommended to modify both temperature and top_p in the same call.\",\"maximum\":1,\"minimum\":0,\"title\":\"Temperature\",\"type\":\"number\"},\"top_p\":{\"default\":0.7,\"description\":\"The top-p sampling mass used for text generation. The top-p value determines the probability mass that is sampled at sampling time. For example, if top_p = 0.2, only the most likely tokens (summing to 0.2 cumulative probability) will be sampled. It is not recommended to modify both temperature and top_p in the same call.\",\"maximum\":1,\"exclusiveMinimum\":0,\"title\":\"Top P\",\"type\":\"number\"},\"tools\":{\"anyOf\":[{\"items\":{\"$ref\":\"#/components/schemas/ChatCompletionToolsParam\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Tools\"},\"frequency_penalty\":{\"type\":\"number\",\"maximum\":2,\"minimum\":-2,\"default\":0,\"title\":\"Frequency Penalty\",\"description\":\"Indicates how much to penalize new tokens based on their existing frequency in the text so far, decreasing model likelihood to repeat the same line verbatim.\"},\"presence_penalty\":{\"type\":\"number\",\"maximum\":2,\"minimum\":-2,\"default\":0,\"title\":\"Presence Penalty\",\"description\":\"Positive values penalize new tokens based on whether they appear in the text so far, increasing model likelihood to talk about new topics.\"},\"max_tokens\":{\"default\":1024,\"description\":\"The maximum number of tokens to generate in any given call. Note that the model is not aware of this value, and generation will simply stop at the number of tokens specified.\",\"maximum\":4096,\"minimum\":1,\"title\":\"Max Tokens\",\"type\":\"integer\"},\"stream\":{\"default\":false,\"description\":\"If set, partial message deltas will be sent. Tokens will be sent as data-only server-sent events (SSE) as they become available (JSON responses are prefixed by `data: `), with the stream terminated by a `data: [DONE]` message.\",\"title\":\"Stream\",\"type\":\"boolean\"},\"stop\":{\"anyOf\":[{\"items\":{\"type\":\"string\"},\"type\":\"array\"},{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Stop\",\"description\":\"A string or a list of strings where the API will stop generating further tokens. The returned text will not contain the stop sequence.\"}},\"required\":[\"messages\"],\"title\":\"ChatRequest\",\"type\":\"object\"},\"Choice\":{\"properties\":{\"index\":{\"description\":\"The index of the choice in the list of choices (always 0).\",\"title\":\"Index\",\"type\":\"integer\"},\"message\":{\"allOf\":[{\"$ref\":\"#/components/schemas/Message\"}],\"description\":\"A chat completion message generated by the model.\",\"examples\":[{\"content\":\"Ah, Paris, the City of Light! There are so many amazing things to see and do in this beautiful city ...\",\"role\":\"assistant\"}]},\"finish_reason\":{\"anyOf\":[{\"enum\":[\"stop\",\"length\",\"tool_calls\"],\"type\":\"string\"},{\"type\":\"null\"}],\"default\":null,\"description\":\"The reason the model stopped generating tokens. This will be `stop` if the model hit a natural stop point or a provided stop sequence, or `length` if the maximum number of tokens specified in the request was reached.\",\"examples\":[\"stop\"],\"title\":\"Finish Reason\"}},\"required\":[\"index\",\"message\"],\"title\":\"Choice\",\"type\":\"object\"},\"ChoiceChunk\":{\"properties\":{\"index\":{\"description\":\"The index of the choice in the list of choices (always 0).\",\"title\":\"Index\",\"type\":\"integer\"},\"delta\":{\"allOf\":[{\"$ref\":\"#/components/schemas/Message\"}],\"description\":\"A chat completion delta generated by streamed model responses.\",\"examples\":[{\"content\":\"Ah,\",\"role\":\"assistant\"}]},\"finish_reason\":{\"anyOf\":[{\"enum\":[\"stop\",\"length\",\"tool_calls\"],\"type\":\"string\"},{\"type\":\"null\"}],\"default\":null,\"description\":\"The reason the model stopped generating tokens. This will be `stop` if the model hit a natural stop point or a provided stop sequence, or `length` if the maximum number of tokens specified in the request was reached. Will be `null` if the model has not finished generating.\",\"title\":\"Finish Reason\"}},\"required\":[\"index\",\"delta\"],\"title\":\"ChoiceChunk\",\"type\":\"object\"},\"Message\":{\"additionalProperties\":false,\"properties\":{\"role\":{\"description\":\"The role of the message author.\",\"enum\":[\"system\",\"context\",\"user\",\"assistant\",\"tool\"],\"title\":\"Role\",\"type\":\"string\"},\"content\":{\"description\":\"The contents of the message.\",\"title\":\"Content\",\"anyOf\":[{\"type\":\"string\"},{\"type\":\"null\"}]},\"tool_call_id\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Tool Call Id\",\"description\":\"The id of the tool call.\"},\"tool_calls\":{\"anyOf\":[{\"items\":{\"$ref\":\"#/components/schemas/ToolCall\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Tool Calls\",\"description\":\"The tool(s) called by the model.\"}},\"required\":[\"role\",\"content\"],\"title\":\"Message\",\"type\":\"object\"},\"ToolCall\":{\"properties\":{\"id\":{\"type\":\"string\",\"title\":\"Id\"},\"type\":{\"type\":\"string\",\"enum\":[\"function\"],\"const\":\"function\",\"title\":\"Type\",\"default\":\"function\"},\"function\":{\"$ref\":\"#/components/schemas/FunctionCall\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"function\"],\"title\":\"ToolCall\"},\"FunctionCall\":{\"properties\":{\"name\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Name\"},\"arguments\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Arguments\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"name\",\"arguments\"],\"title\":\"FunctionCall\"},\"ChatCompletionToolsParam\":{\"properties\":{\"type\":{\"type\":\"string\",\"enum\":[\"function\"],\"const\":\"function\",\"title\":\"Type\",\"default\":\"function\"},\"function\":{\"$ref\":\"#/components/schemas/FunctionDefinition\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"function\"],\"title\":\"ChatCompletionToolsParam\"},\"ChatCompletionNamedFunction\":{\"properties\":{\"name\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Name\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"name\"],\"title\":\"ChatCompletionNamedFunction\"},\"ChatCompletionNamedToolChoiceParam\":{\"properties\":{\"function\":{\"$ref\":\"#/components/schemas/ChatCompletionNamedFunction\"},\"type\":{\"type\":\"string\",\"enum\":[\"function\"],\"const\":\"function\",\"title\":\"Type\",\"default\":\"function\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"function\"],\"title\":\"ChatCompletionNamedToolChoiceParam\"},\"FunctionDefinition\":{\"properties\":{\"name\":{\"type\":\"string\",\"title\":\"Name\"},\"description\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Description\"},\"parameters\":{\"anyOf\":[{\"type\":\"object\"},{\"type\":\"null\"}],\"title\":\"Parameters\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"name\"],\"title\":\"FunctionDefinition\"},\"Usage\":{\"properties\":{\"completion_tokens\":{\"description\":\"Number of tokens in the generated completion.\",\"examples\":[25],\"title\":\"Completion Tokens\",\"type\":\"integer\"},\"prompt_tokens\":{\"description\":\"Number of tokens in the prompt.\",\"examples\":[9],\"title\":\"Prompt Tokens\",\"type\":\"integer\"},\"total_tokens\":{\"description\":\"Total number of tokens used in the request (prompt + completion).\",\"examples\":[34],\"title\":\"Total Tokens\",\"type\":\"integer\"}},\"required\":[\"completion_tokens\",\"prompt_tokens\",\"total_tokens\"],\"title\":\"Usage\",\"type\":\"object\"}}}},\"namespace\":\"qc69jvmznzxy\",\"updatedDate\":\"2024-11-20T03:12:23.673Z\",\"nvcfFunctionId\":\"0de0002c-98f6-422d-8bfc-2716e52f99d2\",\"createdDate\":\"2024-07-23T14:58:23.731Z\",\"attributes\":{\"dockerRun\":\"Pull and run the NVIDIA NIM with the command below. This will download the optimized model for your infrastructure.\\n```bash\\nexport NGC_API_KEY=\u003cPASTE_API_KEY_HERE\u003e\\nexport LOCAL_NIM_CACHE=~/.cache/nim\\nmkdir -p \\\"$LOCAL_NIM_CACHE\\\"\\ndocker run -it --rm \\\\\\n --gpus all \\\\\\n --shm-size=16GB \\\\\\n -e NGC_API_KEY \\\\\\n -v \\\"$LOCAL_NIM_CACHE:/opt/nim/.cache\\\" \\\\\\n -u $(id -u) \\\\\\n -p 8000:8000 \\\\\\n nvcr.io/nim/meta/llama-3.1-405b-instruct:1.1.2\\n```\\n\\nYou can now make a local API call using this curl command:\\n```bash\\ncurl -X 'POST' \\\\\\n'http://0.0.0.0:8000/v1/chat/completions' \\\\\\n-H 'accept: application/json' \\\\\\n-H 'Content-Type: application/json' \\\\\\n-d '{\\n \\\"model\\\": \\\"meta/llama-3.1-405b-instruct\\\",\\n \\\"messages\\\": [{\\\"role\\\":\\\"user\\\", \\\"content\\\":\\\"Write a limerick about the wonders of GPU computing.\\\"}],\\n \\\"max_tokens\\\": 64\\n}'\\n```\\n\\nFor more details on getting started with this NIM, visit the [NVIDIA NIM Docs](https://docs.nvidia.com/nim/large-language-models/latest/getting-started.html).\\n\",\"dockerTermsOfUse\":\"By running the below commands, you accept the \u003ca href=\\\"https://www.nvidia.com/en-us/data-center/products/nvidia-ai-enterprise/eula/\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA AI Enterprise Terms of Use\u003c/a\u003e and the \u003ca href=\\\"https://docs.nvidia.com/ai-foundation-models-community-license.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA Community Models License\u003c/a\u003e.\\n\",\"showUnavailableBanner\":false,\"apiDocsUrl\":\"https://docs.api.nvidia.com/nim/reference/meta-llama-3_1-405b\",\"playground\":{\"type\":\"chatWithTools\"},\"termsOfUse\":\"\u003cb\u003eGOVERNING TERMS\u003c/b\u003e: This trial service is governed by the \u003ca href=\\\"https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA API Trial Terms of Service\u003c/a\u003e. Use of this model is governed by the \u003ca href=\\\"https://docs.nvidia.com/ai-foundation-models-community-license.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003e AI Foundation Models Community License Agreement \u003c/a\u003e. ADDITIONAL INFORMATION: Llama 3.1 Community License Agreement, Built with Llama.\\n\",\"cta\":{\"text\":\"Apply to Self-Host\",\"url\":\"https://www.nvidia.com/en-us/ai/nim-notifyme/\",\"nim_available_override_url\":\"https://catalog.ngc.nvidia.com/orgs/nim/teams/meta/containers/llama-3.1-405b-instruct\"},\"projects\":[{\"name\":\"Build a Customizable Hybrid RAG Chatbot\",\"url\":\"https://github.com/NVIDIA/workbench-example-hybrid-rag\",\"imageUrl\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/nv-workbench.jpg\",\"workbench\":true}]},\"artifactName\":\"llama-3_1-405b-instruct\"},\"config\":{\"name\":\"llama-3_1-405b-instruct\",\"type\":\"model\"}},{\"endpoint\":{\"requestStatus\":{\"statusCode\":\"SUCCESS\",\"requestId\":\"dcfa8348-85e2-4c83-a886-ced3ffcea7a8\"},\"artifact\":{\"orgName\":\"qc69jvmznzxy\",\"labels\":[\"Image Captioning\",\"Image-Text Retrieval\",\"Visual Grounding\",\"Visual QA\",\"Image-to-Text\"],\"logo\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/llama-3_2-90b-vision-instruct.jpg\",\"shortDescription\":\"Cutting-edge vision-Language model exceling in high-quality reasoning from images.\",\"isReadOnly\":true,\"description\":\"$46\",\"canGuestDownload\":true,\"isPublic\":true,\"createdDate\":\"2024-09-25T18:27:54.254Z\",\"publisher\":\"meta\",\"displayName\":\"llama-3.2-90b-vision-instruct\",\"name\":\"llama-3.2-90b-vision-instruct\",\"updatedDate\":\"2024-09-30T17:48:39.175Z\",\"attributes\":[{\"key\":\"PREVIEW\",\"value\":\"true\"}],\"artifactType\":\"ENDPOINT\"}},\"spec\":{\"openAPISpec\":{\"openapi\":\"3.1.0\",\"info\":{\"title\":\"NVIDIA NIM API for meta/llama-3.2-90b-vision-instruct\",\"description\":\"The NVIDIA NIM REST API. Please see https://docs.api.nvidia.com/nim/reference/meta-llama-3_2-90b-vision-instruct for more details.\",\"version\":\"1.0.0\",\"termsOfService\":\"https://nvidia.com/legal/terms-of-use\",\"contact\":{\"name\":\"NVIDIA Support\",\"url\":\"https://help.nvidia.com/\"},\"license\":{\"name\":\"Llama 3.2 License\",\"url\":\"https://github.com/meta-llama/llama-models/blob/main/models/llama3_2/LICENSE\"}},\"servers\":[{\"url\":\"https://ai.api.nvidia.com/v1/gr/meta/llama-3.2-90b-vision-instruct\"}],\"tags\":[{\"name\":\"Multimodal API\",\"description\":\"This API performs inference using visual language understanding models\"}],\"paths\":{\"/meta/llama-3.2-90b-vision-instruct\":{\"post\":{\"tags\":[\"Multimodal API\"],\"summary\":\"Request response from the model\",\"description\":\"Invokes inference using the model chat parameters. If uploading large images, this POST should be used in conjunction with the NVCF API which allows for the upload of large assets. \\nYou can find details on how to use NVCF Asset APIs here: https://docs.api.nvidia.com/cloud-functions/reference/createasset\",\"operationId\":\"invokeFunction\",\"parameters\":[{\"in\":\"header\",\"name\":\"NVCF-INPUT-ASSET-REFERENCES\",\"schema\":{\"type\":\"string\",\"maxLength\":370,\"format\":\"uuid\"},\"required\":false,\"description\":\"String of asset IDs separated by commas. Data is uploaded to AWS S3 using NVCF Asset APIs and associated with these asset IDs.If the size of an image is more than 180KB, it needs to be uploaded to a presigned S3 URL bucket. The presigned URL allows for secure and temporary access to the S3 bucket for uploading the image. Once the asset is requested, an asset ID is generated for it. Please include this asset ID in this header and to use the uploaded image in a prompt, you need to refer to it using the following format: `\u003cimg src=\\\"data:image/png;asset_id,{asset_id}\\\" /\u003e`.\"}],\"requestBody\":{\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/NIMLLMChatCompletionRequest\"}}},\"required\":true},\"responses\":{\"200\":{\"description\":\"Invocation is fulfilled\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ChatCompletionResponse\"}},\"text/event-stream\":{\"schema\":{\"$ref\":\"#/components/schemas/ChatCompletionStreamResponse\"}}}},\"202\":{\"description\":\"Result is pending. Client should poll using the requestId.\\n\",\"content\":{\"application/json\":{\"example\":{},\"schema\":{}}},\"headers\":{\"NVCF-REQID\":{\"description\":\"requestId required for pooling\",\"schema\":{\"type\":\"string\",\"format\":\"uuid\",\"maxLength\":36}},\"NVCF-STATUS\":{\"description\":\"Invocation status\",\"schema\":{\"type\":\"string\",\"format\":\"^[a-zA-Z-]{1,64}$\",\"maxLength\":64}}}},\"422\":{\"description\":\"Validation failed, provided entity could not be processed.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ErrorResponse\"},\"example\":{\"type\":\"urn:nvcf-worker-service:problem-details:unprocessable-entity\",\"title\":\"Unprocessable Entity\",\"status\":422,\"detail\":\"string\",\"instance\":\"/v2/nvcf/pexec/functions/e598bfc1-b058-41af-869d-556d3c7e1b48\",\"requestId\":\"3fa85f64-5717-4562-b3fc-2c963f66afa6\"}}}},\"500\":{\"description\":\"The invocation ended with an error.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ErrorResponse\"},\"example\":{\"type\":\"urn:nvcf-worker-service:problem-details:internal-server-error\",\"title\":\"Internal Server Error\",\"status\":500,\"detail\":\"string\",\"instance\":\"/v2/nvcf/pexec/functions/e598bfc1-b058-41af-869d-556d3c7e1b48\",\"requestId\":\"3fa85f64-5717-4562-b3fc-2c963f66afa6\"}}}}},\"x-nvai-meta\":{\"name\":\"Create chat completion\",\"returns\":\"Returns a [chat completion](/docs/api-reference/chat/object) object, or a streamed sequence of [chat completion chunk](/docs/api-reference/chat/streaming) objects if the request is streamed.\\n\",\"path\":\"create\",\"examples\":[{\"name\":\"dog.jpeg\",\"input\":{\"text\":\"Is there a car in this image?\",\"images\":[\"https://assets.ngc.nvidia.com/products/api-catalog/phi-3-5-vision/example1a.jpg\"]},\"output\":{\"text\":\"The image shows a small, light brown, curly-haired dog standing on a red cushion with a grey and white pillow. The dog is on a wooden deck with a white fence and greenery in the background.\"}},{\"name\":\"dogs.jpeg\",\"input\":{\"text\":\"Describe this image\",\"images\":[\"https://assets.ngc.nvidia.com/products/api-catalog/phi-3-5-vision/example1b.jpg\"]}}],\"templates\":[{\"title\":\"Default\",\"requestEjs\":{\"python\":\"$47\",\"node.js\":\"$48\",\"curl\":\"stream=\u003c%- request.stream %\u003e\\n\\nif [ \\\"$stream\\\" = true ]; then\\n accept_header='Accept: text/event-stream'\\nelse\\n accept_header='Accept: application/json'\\nfi\\n\u003c% content = \\\"What is in this image? \u003cimg src=\\\\\\\\\\\\\\\"data:image/png;base64,'\\\\\\\"\\\\$image_b64\\\\\\\"'\\\\\\\\\\\\\\\" /\u003e\\\" %\u003e\\nimage_b64=$( base64 image.png )\\n\\necho '{\\n \\\"model\\\": \\\"\u003c%- request.model %\u003e\\\",\\n \\\"messages\\\": [\\n {\\n \\\"role\\\": \\\"user\\\",\\n \\\"content\\\": \\\"\u003c%- content %\u003e\\\"\\n }\\n ],\\n \\\"max_tokens\\\": \u003c%- request.max_tokens %\u003e,\\n \\\"temperature\\\": \u003c%- request.temperature.toFixed(2) %\u003e,\\n \\\"top_p\\\": \u003c%- request.top_p.toFixed(2) %\u003e,\\n \\\"stream\\\": \u003c%- request.stream %\u003e\\n}' \u003e payload.json\\n\\ncurl https://ai.api.nvidia.com/v1/gr/meta/llama-3.2-90b-vision-instruct/chat/completions \\\\\\n -H \\\"Authorization: Bearer $NVIDIA_API_KEY\\\" \\\\\\n -H \\\"Content-Type: application/json\\\" \\\\\\n -H \\\"$accept_header\\\" \\\\\\n -d @payload.json\\n\"},\"response\":\"{\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"model\\\": \\\"meta/llama-3.2-90b-vision-instruct\\\",\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"...\\\",\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 9,\\n \\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"}]}}},\"/status/{requestId}\":{\"get\":{\"tags\":[\"Multimodal API\"],\"summary\":\"Gets the result of an earlier function invocation request that returned a status of 202.\",\"operationId\":\"getFunctionInvocationResult\",\"parameters\":[{\"name\":\"requestId\",\"in\":\"path\",\"description\":\"requestId to poll results\",\"required\":true,\"schema\":{\"type\":\"string\",\"format\":\"uuid\",\"maxLength\":36}}],\"responses\":{\"200\":{\"description\":\"Invocation is fulfilled\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ChatCompletionResponse\"}}}},\"202\":{\"description\":\"Result is pending. Client should poll using the requestId.\\n\",\"content\":{\"application/json\":{\"example\":{},\"schema\":{}}},\"headers\":{\"NVCF-REQID\":{\"description\":\"requestId required for pooling\",\"schema\":{\"type\":\"string\",\"format\":\"uuid\",\"maxLength\":36}},\"NVCF-STATUS\":{\"description\":\"Invocation status\",\"schema\":{\"type\":\"string\",\"format\":\"^[a-zA-Z-]{1,64}$\",\"maxLength\":64}}}},\"422\":{\"description\":\"The invocation ended with an error.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ErrorResponse\"},\"example\":{\"type\":\"urn:nvcf-worker-service:problem-details:unprocessable-entity\",\"title\":\"Unprocessable Entity\",\"status\":422,\"detail\":\"string\",\"instance\":\"/v2/nvcf/pexec/functions/e598bfc1-b058-41af-869d-556d3c7e1b48\",\"requestId\":\"3fa85f64-5717-4562-b3fc-2c963f66afa6\"}}}},\"500\":{\"description\":\"The invocation ended with an error.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ErrorResponse\"},\"example\":{\"type\":\"urn:nvcf-worker-service:problem-details:internal-server-error\",\"title\":\"Internal Server Error\",\"status\":500,\"detail\":\"string\",\"instance\":\"/v2/nvcf/pexec/functions/e598bfc1-b058-41af-869d-556d3c7e1b48\",\"requestId\":\"3fa85f64-5717-4562-b3fc-2c963f66afa6\"}}}}}}}},\"security\":[{\"Token\":[]}],\"components\":{\"securitySchemes\":{\"Token\":{\"type\":\"http\",\"scheme\":\"bearer\"}},\"schemas\":{\"ChatCompletionResponse\":{\"properties\":{\"id\":{\"type\":\"string\",\"title\":\"Id\"},\"object\":{\"type\":\"string\",\"enum\":[\"chat.completion\"],\"const\":\"chat.completion\",\"title\":\"Object\",\"default\":\"chat.completion\"},\"created\":{\"type\":\"integer\",\"title\":\"Created\"},\"model\":{\"type\":\"string\",\"title\":\"Model\"},\"choices\":{\"items\":{\"$ref\":\"#/components/schemas/ChatCompletionResponseChoice\"},\"type\":\"array\",\"title\":\"Choices\"},\"usage\":{\"$ref\":\"#/components/schemas/UsageInfo\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"model\",\"choices\",\"usage\"],\"title\":\"ChatCompletionResponse\"},\"ChatCompletionResponseChoice\":{\"properties\":{\"index\":{\"type\":\"integer\",\"title\":\"Index\"},\"message\":{\"$ref\":\"#/components/schemas/ChatMessage\"},\"finish_reason\":{\"anyOf\":[{\"type\":\"string\",\"enum\":[\"stop\",\"length\"]},{\"type\":\"null\"}],\"title\":\"Finish Reason\"},\"stop_reason\":{\"anyOf\":[{\"type\":\"integer\"},{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Stop Reason\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"index\",\"message\"],\"title\":\"ChatCompletionResponseChoice\"},\"ChatCompletionResponseStreamChoice\":{\"properties\":{\"index\":{\"type\":\"integer\",\"title\":\"Index\"},\"delta\":{\"$ref\":\"#/components/schemas/DeltaMessage\"},\"finish_reason\":{\"anyOf\":[{\"type\":\"string\",\"enum\":[\"stop\",\"length\"]},{\"type\":\"null\"}],\"title\":\"Finish Reason\"},\"stop_reason\":{\"anyOf\":[{\"type\":\"integer\"},{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Stop Reason\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"index\",\"delta\"],\"title\":\"ChatCompletionResponseStreamChoice\"},\"ChatCompletionStreamResponse\":{\"properties\":{\"id\":{\"type\":\"string\",\"title\":\"Id\"},\"object\":{\"type\":\"string\",\"enum\":[\"chat.completion.chunk\"],\"const\":\"chat.completion.chunk\",\"title\":\"Object\",\"default\":\"chat.completion.chunk\"},\"created\":{\"type\":\"integer\",\"title\":\"Created\"},\"model\":{\"type\":\"string\",\"title\":\"Model\"},\"choices\":{\"items\":{\"$ref\":\"#/components/schemas/ChatCompletionResponseStreamChoice\"},\"type\":\"array\",\"title\":\"Choices\"},\"usage\":{\"anyOf\":[{\"$ref\":\"#/components/schemas/UsageInfo\"},{\"type\":\"null\"}]}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"model\",\"choices\"],\"title\":\"ChatCompletionStreamResponse\"},\"ChatMessage\":{\"properties\":{\"role\":{\"type\":\"string\",\"title\":\"Role\"},\"content\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Content\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"role\"],\"title\":\"ChatMessage\"},\"DeltaMessage\":{\"properties\":{\"role\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Role\"},\"content\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Content\"}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"DeltaMessage\"},\"ErrorResponse\":{\"properties\":{\"object\":{\"type\":\"string\",\"title\":\"Object\",\"default\":\"error\"},\"message\":{\"type\":\"string\",\"title\":\"Message\"},\"type\":{\"type\":\"string\",\"title\":\"Type\"},\"param\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Param\"},\"code\":{\"type\":\"integer\",\"title\":\"Code\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"message\",\"type\",\"code\"],\"title\":\"ErrorResponse\"},\"HTTPValidationError\":{\"properties\":{\"detail\":{\"items\":{\"$ref\":\"#/components/schemas/ValidationError\"},\"type\":\"array\",\"title\":\"Detail\"}},\"type\":\"object\",\"title\":\"HTTPValidationError\"},\"ImageURL\":{\"properties\":{\"url\":{\"type\":\"string\",\"title\":\"Url\"}},\"type\":\"object\",\"required\":[\"url\"],\"title\":\"ImageURL\"},\"NIMLLMChatCompletionMessage\":{\"properties\":{\"role\":{\"allOf\":[{\"$ref\":\"#/components/schemas/Role\"}],\"description\":\"The role of the message's author.\"},\"content\":{\"anyOf\":[{\"type\":\"string\"},{\"items\":{\"anyOf\":[{\"$ref\":\"#/components/schemas/NIMVLMChatCompletionContentPartImage\"},{\"$ref\":\"#/components/schemas/NIMVLMChatCompletionContentPartText\"}]},\"type\":\"array\"}],\"title\":\"Content\",\"description\":\"The contents of the message.\\n \u003cbr\u003eTo pass images (only with role=`user`):\\n \u003cbr\u003e - When content is a string, image can be passed together with the text with `img` HTML tags that wraps \\n an image URL (`\u003cimg src=\\\"{url}\\\" /\u003e`), \\n base64 encoded image data (`\u003cimg src=\\\"data:image/{format};base64,{base64encodedimage}\\\" /\u003e`), \\n or an NVCF asset ID (`\u003cimg src=\\\"data:image/{format};asset_id,{asset_id}\\\" /\u003e`) \\n when the container is hosted in NVCF and the payload exceeds 200KB.\\n \u003cbr\u003e - When content is a list of objects, images can be passed as objects with type=`image_url`.\\n \u003cbr\u003e - In both cases, images can be PNG, JPG or JPEG.\\n \u003cbr\u003eFor `system` and `assistant` roles, the object list format is not supported.\\n \"}},\"type\":\"object\",\"required\":[\"role\",\"content\"],\"title\":\"NIMLLMChatCompletionMessage\"},\"NIMLLMChatCompletionRequest\":{\"properties\":{\"messages\":{\"items\":{\"$ref\":\"#/components/schemas/NIMLLMChatCompletionMessage\"},\"type\":\"array\",\"minItems\":1,\"title\":\"Messages\",\"description\":\"A list of messages comprising the conversation so far.\"},\"model\":{\"type\":\"string\",\"title\":\"Model\",\"description\":\"The model to use.\",\"default\":\"meta/llama-3.2-90b-vision-instruct\"},\"frequency_penalty\":{\"anyOf\":[{\"type\":\"number\",\"maximum\":2,\"minimum\":-2},{\"type\":\"null\"}],\"title\":\"Frequency Penalty\",\"description\":\"Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim.\",\"default\":0},\"max_tokens\":{\"anyOf\":[{\"type\":\"integer\",\"maximum\":8192,\"minimum\":1},{\"type\":\"null\"}],\"title\":\"Max Tokens\",\"description\":\"The maximum number of tokens that can be generated.\",\"default\":512},\"presence_penalty\":{\"anyOf\":[{\"type\":\"number\",\"maximum\":2,\"minimum\":-2},{\"type\":\"null\"}],\"title\":\"Presence Penalty\",\"description\":\"Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics.\",\"default\":0},\"seed\":{\"anyOf\":[{\"type\":\"integer\",\"maximum\":9223372036854776000,\"minimum\":-9223372036854776000},{\"type\":\"null\"}],\"title\":\"Seed\",\"description\":\"Changing the seed will produce a different response with similar characteristics. Fixing the seed will reproduce the same results if all other parameters are also kept constant.\"},\"stop\":{\"anyOf\":[{\"type\":\"string\"},{\"items\":{\"type\":\"string\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Stop\",\"description\":\"Sequences where the API will stop generating further tokens.\"},\"stream\":{\"anyOf\":[{\"type\":\"boolean\"},{\"type\":\"null\"}],\"title\":\"Stream\",\"description\":\"If set, partial message deltas will be sent, like in ChatGPT. Tokens will be sent as data-only [server-sent events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format) as they become available, with the stream terminated by a `data: [DONE]`\",\"default\":false},\"temperature\":{\"anyOf\":[{\"type\":\"number\",\"maximum\":2,\"minimum\":0},{\"type\":\"null\"}],\"title\":\"Temperature\",\"description\":\"What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.\",\"default\":1},\"top_p\":{\"anyOf\":[{\"type\":\"number\",\"maximum\":1,\"exclusiveMinimum\":0},{\"type\":\"null\"}],\"title\":\"Top P\",\"description\":\"An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered. 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\\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"}]}}}},\"security\":[{\"Token\":[]}],\"components\":{\"securitySchemes\":{\"Token\":{\"type\":\"http\",\"scheme\":\"bearer\"}},\"schemas\":{\"Errors\":{\"properties\":{\"type\":{\"type\":\"string\",\"description\":\"Error type\"},\"title\":{\"type\":\"string\",\"description\":\"Error title\"},\"status\":{\"type\":\"integer\",\"description\":\"Error status code\"},\"detail\":{\"type\":\"string\",\"description\":\"Detailed information about the error\"},\"instance\":{\"type\":\"string\",\"description\":\"Function instance used to invoke the request\"},\"requestId\":{\"type\":\"string\",\"format\":\"uuid\",\"description\":\"UUID of the request\"}},\"type\":\"object\",\"required\":[\"type\",\"title\",\"status\",\"detail\",\"instance\",\"requestId\"],\"title\":\"InvokeError\"},\"ChatCompletion\":{\"properties\":{\"id\":{\"description\":\"A unique identifier for the 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Client should poll using the requestId.\",\"content\":{\"application/json\":{\"example\":{},\"schema\":{}}},\"headers\":{\"NVCF-REQID\":{\"description\":\"requestId required for pooling\",\"schema\":{\"type\":\"string\",\"format\":\"uuid\"}},\"NVCF-STATUS\":{\"description\":\"Invocation status\",\"schema\":{\"type\":\"string\"}}}},\"422\":{\"description\":\"Validation failed, provided entity could not be processed.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/Errors\"},\"example\":{\"type\":\"urn:nvcf-worker-service:problem-details:unprocessable-entity\",\"title\":\"Unprocessable Entity\",\"status\":422,\"detail\":\"string\",\"instance\":\"/v2/nvcf/pexec/functions/c53ee0e9-bad9-4e09-b365-52c9d6b71254\",\"requestId\":\"3fa85f64-5717-4562-b3fc-2c963f66afa6\"}}}},\"500\":{\"description\":\"The invocation ended with an error.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/Errors\"},\"example\":{\"type\":\"urn:nvcf-worker-service:problem-details:internal-server-error\",\"title\":\"Internal Server Error\",\"status\":500,\"detail\":\"string\",\"instance\":\"/v2/nvcf/pexec/functions/c53ee0e9-bad9-4e09-b365-52c9d6b71254\",\"requestId\":\"3fa85f64-5717-4562-b3fc-2c963f66afa6\"}}}}},\"x-nvai-meta\":{\"name\":\"Create chat completion\",\"returns\":\"Returns a [chat completion](/docs/api-reference/chat/object) object\\n\",\"path\":\"create\",\"examples\":[{\"name\":\"Grade the assistant response\",\"requestJson\":\"{\\n \\\"model\\\": \\\"nvidia/nemotron-4-340b-reward\\\",\\n \\\"messages\\\": [\\n {\\n \\\"role\\\": \\\"user\\\",\\n \\\"content\\\": \\\"I am going to Paris, what should I see?\\\"\\n },\\n {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"Ah, Paris, the City of Light! There are so many amazing things to see and do in this beautiful city ...\\\"\\n }\\n ]\\n}\\n\",\"responseJson\":\"$50\"},{\"name\":\"Grade the assistant response in multiturn\",\"requestJson\":\"{\\n \\\"model\\\": \\\"nvidia/nemotron-4-340b-reward\\\",\\n \\\"messages\\\": [\\n {\\n \\\"role\\\": \\\"user\\\",\\n \\\"content\\\": \\\"I am going to Paris, what should I see?\\\"\\n },\\n {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"Ah, Paris, the City of Light! There are so many amazing things to see and do in this beautiful city ...\\\"\\n },\\n {\\n \\\"role\\\": \\\"user\\\",\\n \\\"content\\\": \\\"What cafes do you recommend?\\\"\\n },\\n {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"A very popular cafe in the heart of Paris is ...\\\"\\n }\\n ]\\n}\\n\",\"responseJson\":\"$51\"}],\"templates\":[{\"title\":\"No Streaming\",\"requestEjs\":{\"python\":\"from openai import OpenAI\\n\\nclient = OpenAI(\\n base_url = \\\"https://integrate.api.nvidia.com/v1\\\",\\n api_key = \\\"$NVIDIA_API_KEY\\\"\\n)\\n\\ncompletion = client.chat.completions.create(\\n model=\\\"\u003c%- request.model %\u003e\\\",\\n messages=\u003c%- JSON.stringify(request.messages) %\u003e,\\n)\\nprint(completion)\\n\",\"node.js\":\"import OpenAI from 'openai';\\n\\nconst openai = new OpenAI({\\n apiKey: '$NVIDIA_API_KEY',\\n baseURL: 'https://integrate.api.nvidia.com/v1',\\n})\\n\\nasync function main() {\\n const completion = await openai.chat.completions.create({\\n model: \\\"\u003c%- request.model %\u003e\\\",\\n messages: \u003c%- JSON.stringify(request.messages) %\u003e,\\n })\\n process.stdout.write(JSON.stringify(completion));\\n}\\n\\nmain();\",\"curl\":\"curl https://integrate.api.nvidia.com/v1/chat/completions \\\\\\n -H \\\"Content-Type: application/json\\\" \\\\\\n -H \\\"Authorization: Bearer $NVIDIA_API_KEY\\\" \\\\\\n -d '{\\n \\\"model\\\": \\\"nvidia/nemotron-4-340b-reward\\\",\\n \\\"messages\\\": \u003c%- JSON.stringify(request.messages).replaceAll(\\\"'\\\", \\\"'\\\\\\\"'\\\\\\\"'\\\") %\u003e }'\\n\"},\"response\":\"$52\"}]}}}},\"security\":[{\"Token\":[]}],\"components\":{\"securitySchemes\":{\"Token\":{\"type\":\"http\",\"scheme\":\"bearer\"}},\"schemas\":{\"Errors\":{\"properties\":{\"type\":{\"type\":\"string\",\"description\":\"Error type\"},\"title\":{\"type\":\"string\",\"description\":\"Error title\"},\"status\":{\"type\":\"integer\",\"description\":\"Error status code\"},\"detail\":{\"type\":\"string\",\"description\":\"Detailed information about the error\"},\"instance\":{\"type\":\"string\",\"description\":\"Function instance used to invoke the request\"},\"requestId\":{\"type\":\"string\",\"format\":\"uuid\",\"description\":\"UUID of the request\"}},\"type\":\"object\",\"required\":[\"type\",\"title\",\"status\",\"detail\",\"instance\",\"requestId\"],\"title\":\"InvokeError\"},\"ChatCompletion\":{\"properties\":{\"id\":{\"description\":\"A unique identifier for the completion.\",\"format\":\"uuid\",\"title\":\"Id\",\"type\":\"string\"},\"choices\":{\"description\":\"The list of completion choices the model generated for the input prompt.\",\"items\":{\"$ref\":\"#/components/schemas/Choice\"},\"title\":\"Choices\",\"type\":\"array\"},\"usage\":{\"allOf\":[{\"$ref\":\"#/components/schemas/Usage\"}],\"description\":\"Usage statistics for the completion request.\"}},\"required\":[\"id\",\"choices\",\"usage\"],\"title\":\"ChatCompletion\",\"type\":\"object\"},\"ChatCompletionMessage\":{\"properties\":{\"content\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"null\"}],\"description\":\"The contents of the message.\",\"title\":\"Content\"},\"role\":{\"const\":\"assistant\",\"description\":\"The role of the author of this message.\",\"enum\":[\"assistant\"],\"title\":\"Role\",\"type\":\"string\"}},\"required\":[\"content\",\"role\"],\"title\":\"ChatCompletionMessage\",\"type\":\"object\"},\"ChatRequest\":{\"additionalProperties\":false,\"properties\":{\"model\":{\"type\":\"string\",\"title\":\"Model\",\"default\":\"nvidia/nemotron-4-340b-reward\"},\"messages\":{\"description\":\"A list of messages comprising the conversation so far that is to be graded. The roles of the messages must be alternating between `user` and `assistant`. The last input message should have role `assistant`.\",\"examples\":[[{\"content\":\"I am going to Paris, what should I see?\",\"role\":\"user\"},{\"content\":\"Ah, Paris, the City of Light! There are so many amazing things to see and do in this beautiful city ...\",\"role\":\"assistant\"}]],\"items\":{\"$ref\":\"#/components/schemas/Message\"},\"title\":\"Messages\",\"type\":\"array\"}},\"required\":[\"messages\"],\"title\":\"ChatRequest\",\"type\":\"object\"},\"Choice\":{\"properties\":{\"index\":{\"description\":\"The index of the choice in the list of choices (always 0).\",\"title\":\"Index\",\"type\":\"integer\"},\"message\":{\"description\":\"The score key:value pairs separated by a comma.\",\"examples\":[{\"content\":\"helpfulness:0.2578125,correctness:0.13671875,coherence:2.640625,complexity:0.328125,verbosity:0.04296875\",\"role\":\"assistant\"}],\"items\":{\"$ref\":\"#/components/schemas/ChatCompletionMessage\"},\"title\":\"Message\",\"type\":\"array\"},\"logprobs\":{\"allOf\":[{\"$ref\":\"#/components/schemas/LogProbs\"}],\"default\":\"List of output reward score items.\"},\"finish_reason\":{\"anyOf\":[{\"enum\":[\"stop\",\"length\"],\"type\":\"string\"},{\"type\":\"null\"}],\"default\":null,\"description\":\"The reason the model stopped generating tokens. This will be `stop` if the model hit a natural stop point or a provided stop sequence, or `length` if the maximum number of tokens specified in the request was reached.\",\"examples\":[\"stop\"],\"title\":\"Finish Reason\"}},\"required\":[\"index\",\"message\"],\"title\":\"Choice\",\"type\":\"object\"},\"LogProbField\":{\"properties\":{\"token\":{\"default\":\"Field to be scored in the assistant response to the user prompt\",\"title\":\"Token\",\"type\":\"string\"},\"logprob\":{\"default\":\"Score of the 'token' field in the assistant response to the user prompt\",\"title\":\"Logprob\",\"type\":\"number\"},\"top_logprobs\":{\"default\":\"List of the most likely tokens and their log probability, at this token position. 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Please see https://docs.api.nvidia.com/nim/reference/meta-llama-3_1-8b-instruct for more details.\",\"version\":\"1.0.0\",\"termsOfService\":\"https://www.nvidia.com/en-us/data-center/products/nvidia-ai-enterprise/eula/\",\"contact\":{\"name\":\"NVIDIA Enterprise Support\",\"url\":\"https://www.nvidia.com/en-us/support/enterprise/\"},\"license\":{\"name\":\"Llama 3.1 License\",\"url\":\"https://github.com/meta-llama/llama-models/blob/main/License/Llama3.1.txt\"}},\"servers\":[{\"url\":\"https://integrate.api.nvidia.com/v1/\"}],\"paths\":{\"/chat/completions\":{\"post\":{\"operationId\":\"create_chat_completion_v1_chat_completions_post\",\"tags\":[\"Chat\"],\"summary\":\"Creates a model response for the given chat conversation.\",\"description\":\"Given a list of messages comprising a conversation, the model will return a response. Compatible with OpenAI. See https://platform.openai.com/docs/api-reference/chat/create\",\"requestBody\":{\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ChatRequest\"}}},\"required\":true},\"responses\":{\"200\":{\"description\":\"Invocation is fulfilled\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ChatCompletion\"}},\"text/event-stream\":{\"schema\":{\"$ref\":\"#/components/schemas/ChatCompletionChunk\"}}}},\"202\":{\"description\":\"Result is pending. Client should poll using the requestId.\\n\",\"content\":{\"application/json\":{\"example\":{},\"schema\":{}}},\"headers\":{\"NVCF-REQID\":{\"description\":\"requestId required for pooling\",\"schema\":{\"type\":\"string\",\"format\":\"uuid\"}},\"NVCF-STATUS\":{\"description\":\"Invocation status\",\"schema\":{\"type\":\"string\"}}}},\"422\":{\"description\":\"Validation failed, provided entity could not be processed.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/Errors\"},\"example\":{\"type\":\"urn:nvcf-worker-service:problem-details:unprocessable-entity\",\"title\":\"Unprocessable Entity\",\"status\":422,\"detail\":\"string\",\"instance\":\"/v2/nvcf/pexec/functions/4a58c6cb-a9b4-4014-99de-3e704d4ae687\",\"requestId\":\"3fa85f64-5717-4562-b3fc-2c963f66afa6\"}}}},\"500\":{\"description\":\"The invocation ended with an error.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/Errors\"},\"example\":{\"type\":\"urn:nvcf-worker-service:problem-details:internal-server-error\",\"title\":\"Internal Server Error\",\"status\":500,\"detail\":\"string\",\"instance\":\"/v2/nvcf/pexec/functions/4a58c6cb-a9b4-4014-99de-3e704d4ae687\",\"requestId\":\"3fa85f64-5717-4562-b3fc-2c963f66afa6\"}}}}},\"x-nvai-meta\":{\"name\":\"Create chat completion\",\"returns\":\"Returns a [chat completion](/docs/api-reference/chat/object) object, or a streamed sequence of [chat completion chunk](/docs/api-reference/chat/streaming) objects if the request is streamed.\\n\",\"path\":\"create\",\"examples\":[{\"name\":\"Write a limerick about the wonders of GPU computing.\",\"requestJson\":\"{\\n \\\"model\\\": \\\"meta/llama-3.1-8b-instruct\\\",\\n \\\"messages\\\": [\\n {\\n \\\"role\\\": \\\"user\\\",\\n \\\"content\\\": \\\"Write a limerick about the wonders of GPU computing.\\\"\\n }\\n ],\\n \\\"top_p\\\": 0.7,\\n \\\"max_tokens\\\": 1024,\\n \\\"seed\\\": 42,\\n \\\"stream\\\": true\\n}\\n\",\"responseJson\":\"{\\n \\\"id\\\": \\\"id-123\\\",\\n \\\"object\\\": \\\"chat.completion\\\",\\n \\\"created\\\": 1677652288,\\n \\\"model\\\": \\\"meta/llama-3.1-8b-instruct\\\",\\n \\\"system_fingerprint\\\": \\\"fp_44709d6fcb\\\",\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"The python functions...\\\"\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 9,\\n \\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"},{\"name\":\"Tell me about Dumbledore.\",\"requestJson\":\"$54\",\"responseJson\":\"{\\n \\\"id\\\": \\\"id-123\\\",\\n \\\"object\\\": \\\"chat.completion\\\",\\n \\\"created\\\": 1677652288,\\n \\\"model\\\": \\\"meta/llama-3.1-8b-instruct\\\",\\n \\\"system_fingerprint\\\": \\\"fp_44709d6fcb\\\",\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"At NVIDIA's GPU Technology Conference (GTC)...\\\"\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 9,\\n \\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"},{\"name\":\"What is the weather in Santa Clara, CA?\",\"requestJson\":\"$55\",\"responseJson\":\"{\\n \\\"id\\\": \\\"id-123\\\",\\n \\\"object\\\": \\\"chat.completion\\\",\\n \\\"created\\\": 1677652288,\\n \\\"model\\\": \\\"meta/llama-3.1-8b-instruct\\\",\\n \\\"system_fingerprint\\\": \\\"fp_44709d6fcb\\\",\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"At NVIDIA's GPU Technology Conference (GTC)...\\\"\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 9,\\n \\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"}],\"templates\":[{\"title\":\"No Streaming\",\"requestEjs\":{\"python\":\"$56\",\"langChain\":\"from langchain_nvidia_ai_endpoints import ChatNVIDIA\\n\\nclient = ChatNVIDIA(\\n model=\\\"\u003c%- request.model %\u003e\\\",\\n api_key=\\\"$NVIDIA_API_KEY\\\", \\n temperature=\u003c%- request.temperature %\u003e,\\n top_p=\u003c%- request.top_p %\u003e,\\n max_tokens=\u003c%- request.max_tokens %\u003e,\\n)\\n\u003c% if (request.stream) { %\u003e\\nfor chunk in client.stream(\u003c%- JSON.stringify(request.messages) %\u003e): \\n print(chunk.content, end=\\\"\\\")\\n\u003c% } else { %\u003e\\nresponse = client.invoke(\u003c%- JSON.stringify(request.messages) %\u003e)\\nprint(response.content)\\n\u003c% } %\u003e\\n \\n\",\"node.js\":\"$57\",\"curl\":\"$58\"},\"response\":\"{\\n \\\"id\\\": \\\"chatcmpl-123\\\",\\n \\\"object\\\": \\\"chat.completion\\\",\\n \\\"created\\\": 1677652288,\\n \\\"model\\\": \\\"meta/llama-3.1-8b-instruct\\\",\\n \\\"system_fingerprint\\\": \\\"fp_44709d6fcb\\\",\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"\\\\n\\\\nHello there, how may I assist you today?\\\",\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 9,\\n \\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"}]}}}},\"security\":[{\"Token\":[]}],\"components\":{\"securitySchemes\":{\"Token\":{\"type\":\"http\",\"scheme\":\"bearer\"}},\"schemas\":{\"Errors\":{\"properties\":{\"type\":{\"type\":\"string\",\"description\":\"Error type\"},\"title\":{\"type\":\"string\",\"description\":\"Error title\"},\"status\":{\"type\":\"integer\",\"description\":\"Error status code\"},\"detail\":{\"type\":\"string\",\"description\":\"Detailed information about the error\"},\"instance\":{\"type\":\"string\",\"description\":\"Function instance used to invoke the request\"},\"requestId\":{\"type\":\"string\",\"format\":\"uuid\",\"description\":\"UUID of the request\"}},\"type\":\"object\",\"required\":[\"type\",\"title\",\"status\",\"detail\",\"instance\",\"requestId\"],\"title\":\"InvokeError\"},\"ChatCompletion\":{\"properties\":{\"id\":{\"description\":\"A unique identifier for the completion.\",\"format\":\"uuid\",\"title\":\"Id\",\"type\":\"string\"},\"choices\":{\"description\":\"The list of completion choices the model generated for the input prompt.\",\"items\":{\"$ref\":\"#/components/schemas/Choice\"},\"title\":\"Choices\",\"type\":\"array\"},\"usage\":{\"allOf\":[{\"$ref\":\"#/components/schemas/Usage\"}],\"description\":\"Usage statistics for the completion request.\"}},\"required\":[\"id\",\"choices\",\"usage\"],\"title\":\"ChatCompletion\",\"type\":\"object\"},\"ChatCompletionChunk\":{\"properties\":{\"id\":{\"description\":\"A unique identifier for the completion.\",\"format\":\"uuid\",\"title\":\"Id\",\"type\":\"string\"},\"choices\":{\"description\":\"The list of completion choices the model generated for the input prompt.\",\"items\":{\"$ref\":\"#/components/schemas/ChoiceChunk\"},\"title\":\"Choices\",\"type\":\"array\"}},\"required\":[\"id\",\"choices\"],\"title\":\"ChatCompletionChunk\",\"type\":\"object\"},\"ChatRequest\":{\"additionalProperties\":false,\"properties\":{\"model\":{\"type\":\"string\",\"title\":\"Model\",\"default\":\"meta/llama-3.1-8b-instruct\"},\"messages\":{\"description\":\"A list of messages comprising the conversation so far. The roles of the messages must be alternating between `user` and `assistant`. The last input message should have role `user`. A message with the the `system` role is optional, and must be the very first message if it is present; `context` is also optional, but must come before a user question.\",\"examples\":[[{\"content\":\"I am going to Paris, what should I see?\",\"role\":\"user\"}]],\"items\":{\"$ref\":\"#/components/schemas/Message\"},\"title\":\"Messages\",\"type\":\"array\"},\"temperature\":{\"default\":0.2,\"description\":\"The sampling temperature to use for text generation. The higher the temperature value is, the less deterministic the output text will be. It is not recommended to modify both temperature and top_p in the same call.\",\"maximum\":1,\"minimum\":0,\"title\":\"Temperature\",\"type\":\"number\"},\"top_p\":{\"default\":0.7,\"description\":\"The top-p sampling mass used for text generation. The top-p value determines the probability mass that is sampled at sampling time. For example, if top_p = 0.2, only the most likely tokens (summing to 0.2 cumulative probability) will be sampled. It is not recommended to modify both temperature and top_p in the same call.\",\"maximum\":1,\"exclusiveMinimum\":0,\"title\":\"Top P\",\"type\":\"number\"},\"tools\":{\"anyOf\":[{\"items\":{\"$ref\":\"#/components/schemas/ChatCompletionToolsParam\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Tools\"},\"frequency_penalty\":{\"type\":\"number\",\"maximum\":2,\"minimum\":-2,\"default\":0,\"title\":\"Frequency Penalty\",\"description\":\"Indicates how much to penalize new tokens based on their existing frequency in the text so far, decreasing model likelihood to repeat the same line verbatim.\"},\"presence_penalty\":{\"type\":\"number\",\"maximum\":2,\"minimum\":-2,\"default\":0,\"title\":\"Presence Penalty\",\"description\":\"Positive values penalize new tokens based on whether they appear in the text so far, increasing model likelihood to talk about new topics.\"},\"max_tokens\":{\"default\":1024,\"description\":\"The maximum number of tokens to generate in any given call. Note that the model is not aware of this value, and generation will simply stop at the number of tokens specified.\",\"maximum\":4096,\"minimum\":1,\"title\":\"Max Tokens\",\"type\":\"integer\"},\"stream\":{\"default\":false,\"description\":\"If set, partial message deltas will be sent. Tokens will be sent as data-only server-sent events (SSE) as they become available (JSON responses are prefixed by `data: `), with the stream terminated by a `data: [DONE]` message.\",\"title\":\"Stream\",\"type\":\"boolean\"},\"stop\":{\"anyOf\":[{\"items\":{\"type\":\"string\"},\"type\":\"array\"},{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Stop\",\"description\":\"A string or a list of strings where the API will stop generating further tokens. The returned text will not contain the stop sequence.\"}},\"required\":[\"messages\"],\"title\":\"ChatRequest\",\"type\":\"object\"},\"Choice\":{\"properties\":{\"index\":{\"description\":\"The index of the choice in the list of choices (always 0).\",\"title\":\"Index\",\"type\":\"integer\"},\"message\":{\"allOf\":[{\"$ref\":\"#/components/schemas/Message\"}],\"description\":\"A chat completion message generated by the model.\",\"examples\":[{\"content\":\"Ah, Paris, the City of Light! There are so many amazing things to see and do in this beautiful city ...\",\"role\":\"assistant\"}]},\"finish_reason\":{\"anyOf\":[{\"enum\":[\"stop\",\"length\",\"tool_calls\"],\"type\":\"string\"},{\"type\":\"null\"}],\"default\":null,\"description\":\"The reason the model stopped generating tokens. This will be `stop` if the model hit a natural stop point or a provided stop sequence, or `length` if the maximum number of tokens specified in the request was reached.\",\"examples\":[\"stop\"],\"title\":\"Finish Reason\"}},\"required\":[\"index\",\"message\"],\"title\":\"Choice\",\"type\":\"object\"},\"ChoiceChunk\":{\"properties\":{\"index\":{\"description\":\"The index of the choice in the list of choices (always 0).\",\"title\":\"Index\",\"type\":\"integer\"},\"delta\":{\"allOf\":[{\"$ref\":\"#/components/schemas/Message\"}],\"description\":\"A chat completion delta generated by streamed model responses.\",\"examples\":[{\"content\":\"Ah,\",\"role\":\"assistant\"}]},\"finish_reason\":{\"anyOf\":[{\"enum\":[\"stop\",\"length\",\"tool_calls\"],\"type\":\"string\"},{\"type\":\"null\"}],\"default\":null,\"description\":\"The reason the model stopped generating tokens. This will be `stop` if the model hit a natural stop point or a provided stop sequence, or `length` if the maximum number of tokens specified in the request was reached. Will be `null` if the model has not finished generating.\",\"title\":\"Finish Reason\"}},\"required\":[\"index\",\"delta\"],\"title\":\"ChoiceChunk\",\"type\":\"object\"},\"Message\":{\"additionalProperties\":false,\"properties\":{\"role\":{\"description\":\"The role of the message author.\",\"enum\":[\"system\",\"context\",\"user\",\"assistant\",\"tool\"],\"title\":\"Role\",\"type\":\"string\"},\"content\":{\"description\":\"The contents of the message.\",\"title\":\"Content\",\"anyOf\":[{\"type\":\"string\"},{\"type\":\"null\"}]},\"tool_call_id\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Tool Call Id\",\"description\":\"The id of the tool call.\"},\"tool_calls\":{\"anyOf\":[{\"items\":{\"$ref\":\"#/components/schemas/ToolCall\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Tool Calls\",\"description\":\"The tool(s) called by the model.\"}},\"required\":[\"role\",\"content\"],\"title\":\"Message\",\"type\":\"object\"},\"ToolCall\":{\"properties\":{\"id\":{\"type\":\"string\",\"title\":\"Id\"},\"type\":{\"type\":\"string\",\"enum\":[\"function\"],\"const\":\"function\",\"title\":\"Type\",\"default\":\"function\"},\"function\":{\"$ref\":\"#/components/schemas/FunctionCall\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"function\"],\"title\":\"ToolCall\"},\"FunctionCall\":{\"properties\":{\"name\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Name\"},\"arguments\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Arguments\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"name\",\"arguments\"],\"title\":\"FunctionCall\"},\"ChatCompletionToolsParam\":{\"properties\":{\"type\":{\"type\":\"string\",\"enum\":[\"function\"],\"const\":\"function\",\"title\":\"Type\",\"default\":\"function\"},\"function\":{\"$ref\":\"#/components/schemas/FunctionDefinition\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"function\"],\"title\":\"ChatCompletionToolsParam\"},\"ChatCompletionNamedFunction\":{\"properties\":{\"name\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Name\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"name\"],\"title\":\"ChatCompletionNamedFunction\"},\"ChatCompletionNamedToolChoiceParam\":{\"properties\":{\"function\":{\"$ref\":\"#/components/schemas/ChatCompletionNamedFunction\"},\"type\":{\"type\":\"string\",\"enum\":[\"function\"],\"const\":\"function\",\"title\":\"Type\",\"default\":\"function\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"function\"],\"title\":\"ChatCompletionNamedToolChoiceParam\"},\"FunctionDefinition\":{\"properties\":{\"name\":{\"type\":\"string\",\"title\":\"Name\"},\"description\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Description\"},\"parameters\":{\"anyOf\":[{\"type\":\"object\"},{\"type\":\"null\"}],\"title\":\"Parameters\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"name\"],\"title\":\"FunctionDefinition\"},\"Usage\":{\"properties\":{\"completion_tokens\":{\"description\":\"Number of tokens in the generated completion.\",\"examples\":[25],\"title\":\"Completion Tokens\",\"type\":\"integer\"},\"prompt_tokens\":{\"description\":\"Number of tokens in the prompt.\",\"examples\":[9],\"title\":\"Prompt Tokens\",\"type\":\"integer\"},\"total_tokens\":{\"description\":\"Total number of tokens used in the request (prompt + completion).\",\"examples\":[34],\"title\":\"Total Tokens\",\"type\":\"integer\"}},\"required\":[\"completion_tokens\",\"prompt_tokens\",\"total_tokens\"],\"title\":\"Usage\",\"type\":\"object\"}}}},\"namespace\":\"qc69jvmznzxy\",\"updatedDate\":\"2024-11-20T03:07:03.855Z\",\"nvcfFunctionId\":\"e62a4350-2218-4cf5-9262-112432d239f8\",\"createdDate\":\"2024-07-23T14:58:17.697Z\",\"attributes\":{\"dockerRun\":\"Pull and run the NVIDIA NIM with the command below. This will download the optimized model for your infrastructure.\\n```bash\\nexport NGC_API_KEY=\u003cPASTE_API_KEY_HERE\u003e\\nexport LOCAL_NIM_CACHE=~/.cache/nim\\nmkdir -p \\\"$LOCAL_NIM_CACHE\\\"\\ndocker run -it --rm \\\\\\n --gpus all \\\\\\n --shm-size=16GB \\\\\\n -e NGC_API_KEY \\\\\\n -v \\\"$LOCAL_NIM_CACHE:/opt/nim/.cache\\\" \\\\\\n -u $(id -u) \\\\\\n -p 8000:8000 \\\\\\n nvcr.io/nim/meta/llama-3.1-8b-instruct:latest\\n```\\n\\nYou can now make a local API call using this curl command:\\n```bash\\ncurl -X 'POST' \\\\\\n'http://0.0.0.0:8000/v1/chat/completions' \\\\\\n-H 'accept: application/json' \\\\\\n-H 'Content-Type: application/json' \\\\\\n-d '{\\n \\\"model\\\": \\\"meta/llama-3.1-8b-instruct\\\",\\n \\\"messages\\\": [{\\\"role\\\":\\\"user\\\", \\\"content\\\":\\\"Write a limerick about the wonders of GPU computing.\\\"}],\\n \\\"max_tokens\\\": 64\\n}'\\n```\\n\\nFor more details on getting started with this NIM, visit the [NVIDIA NIM Docs](https://docs.nvidia.com/nim/large-language-models/latest/getting-started.html).\\n\",\"dockerTermsOfUse\":\"By running the below commands, you accept the \u003ca href=\\\"https://www.nvidia.com/en-us/data-center/products/nvidia-ai-enterprise/eula/\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA AI Enterprise Terms of Use\u003c/a\u003e and the \u003ca href=\\\"https://docs.nvidia.com/ai-foundation-models-community-license.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA Community Models License\u003c/a\u003e.\\n\",\"showUnavailableBanner\":false,\"apiDocsUrl\":\"https://docs.api.nvidia.com/nim/reference/meta-llama-3_1-8b\",\"playground\":{\"type\":\"chatWithTools\"},\"termsOfUse\":\"\u003cb\u003eGOVERNING TERMS\u003c/b\u003e: This trial service is governed by the \u003ca href=\\\"https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA API Trial Terms of Service\u003c/a\u003e. Use of this model is governed by the \u003ca href=\\\"https://docs.nvidia.com/ai-foundation-models-community-license.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003e AI Foundation Models Community License Agreement \u003c/a\u003e. ADDITIONAL INFORMATION: Llama 3.1 Community License Agreement, Built with Llama.\\n\",\"cta\":{\"text\":\"Apply to Self-Host\",\"url\":\"https://www.nvidia.com/en-us/ai/nim-notifyme/\",\"nim_available_override_url\":\"https://catalog.ngc.nvidia.com/orgs/nim/teams/meta/containers/llama-3.1-8b-instruct\"},\"projects\":[{\"name\":\"Build a Customizable Hybrid RAG Chatbot\",\"url\":\"https://github.com/NVIDIA/workbench-example-hybrid-rag\",\"imageUrl\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/nv-workbench.jpg\",\"workbench\":true},{\"name\":\"Fine-tune Llama 3.1 with LoRA and Deploy with NVIDIA NIM\",\"url\":\"http://brev.dev/llama3-1-nim\",\"imageUrl\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/brev.png\",\"workbench\":false}]},\"artifactName\":\"llama-3_1-8b-instruct\"},\"config\":{\"name\":\"llama-3_1-8b-instruct\",\"type\":\"model\"}},{\"endpoint\":{\"requestStatus\":{\"statusCode\":\"SUCCESS\",\"requestId\":\"88bf7189-6349-4be1-bf73-a8c88866eab8\"},\"artifact\":{\"orgName\":\"qc69jvmznzxy\",\"labels\":[\"Chat\",\"Code Generation\",\"Language Generation\",\"Text-to-Text\",\"Code Generation\"],\"logo\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/mistral-nemo-12b-instruct.jpg\",\"shortDescription\":\"Most advanced language model for reasoning, code, multilingual tasks; runs on a single GPU.\",\"isReadOnly\":true,\"description\":\"$59\",\"canGuestDownload\":true,\"isPublic\":true,\"createdDate\":\"2024-07-18T13:59:22.242Z\",\"publisher\":\"nv-mistralai\",\"displayName\":\"mistral-nemo-12b-instruct\",\"name\":\"mistral-nemo-12b-instruct\",\"updatedDate\":\"2024-11-20T03:05:14.347Z\",\"attributes\":[{\"key\":\"AVAILABLE\",\"value\":\"true\"},{\"key\":\"PREVIEW\",\"value\":\"false\"}],\"artifactType\":\"ENDPOINT\"}},\"spec\":{\"openAPISpec\":{\"openapi\":\"3.1.0\",\"info\":{\"title\":\"NVIDIA NIM API for nv-mistralai/mistral-nemo-12b-instruct\",\"description\":\"The NVIDIA NIM REST API. Please see https://docs.api.nvidia.com/nim/reference/nv-mistralai-mistral-nemo-12b-instruct for more details.\",\"version\":\"1.0.0\",\"termsOfService\":\"https://www.nvidia.com/en-us/data-center/products/nvidia-ai-enterprise/eula/\",\"contact\":{\"name\":\"NVIDIA Enterprise Support\",\"url\":\"https://www.nvidia.com/en-us/support/enterprise/\"},\"license\":{\"name\":\"Apache 2.0\",\"url\":\"https://mistral.ai/terms-of-service/\"}},\"servers\":[{\"url\":\"https://integrate.api.nvidia.com/v1/\"}],\"paths\":{\"/chat/completions\":{\"post\":{\"operationId\":\"create_chat_completion_v1_chat_completions_post\",\"tags\":[\"Chat\"],\"summary\":\"Creates a model response for the given chat conversation.\",\"description\":\"Given a list of messages comprising a conversation, the model will return a response. Compatible with OpenAI. See https://platform.openai.com/docs/api-reference/chat/create\",\"requestBody\":{\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ChatRequest\"}}},\"required\":true},\"responses\":{\"200\":{\"description\":\"Invocation is fulfilled\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ChatCompletion\"}},\"text/event-stream\":{\"schema\":{\"$ref\":\"#/components/schemas/ChatCompletionChunk\"}}}},\"202\":{\"description\":\"Result is pending. Client should poll using the requestId.\\n\",\"content\":{\"application/json\":{\"example\":{},\"schema\":{}}},\"headers\":{\"NVCF-REQID\":{\"description\":\"requestId required for pooling\",\"schema\":{\"type\":\"string\",\"format\":\"uuid\"}},\"NVCF-STATUS\":{\"description\":\"Invocation status\",\"schema\":{\"type\":\"string\"}}}},\"422\":{\"description\":\"Validation failed, provided entity could not be processed.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/Errors\"},\"example\":{\"type\":\"urn:nvcf-worker-service:problem-details:unprocessable-entity\",\"title\":\"Unprocessable Entity\",\"status\":422,\"detail\":\"string\",\"instance\":\"/v2/nvcf/pexec/functions/4a58c6cb-a9b4-4014-99de-3e704d4ae687\",\"requestId\":\"3fa85f64-5717-4562-b3fc-2c963f66afa6\"}}}},\"500\":{\"description\":\"The invocation ended with an error.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/Errors\"},\"example\":{\"type\":\"urn:nvcf-worker-service:problem-details:internal-server-error\",\"title\":\"Internal Server Error\",\"status\":500,\"detail\":\"string\",\"instance\":\"/v2/nvcf/pexec/functions/4a58c6cb-a9b4-4014-99de-3e704d4ae687\",\"requestId\":\"3fa85f64-5717-4562-b3fc-2c963f66afa6\"}}}}},\"x-nvai-meta\":{\"name\":\"Create chat completion\",\"returns\":\"Returns a [chat completion](/docs/api-reference/chat/object) object, or a streamed sequence of [chat completion chunk](/docs/api-reference/chat/streaming) objects if the request is streamed.\\n\",\"path\":\"create\",\"examples\":[{\"name\":\"Write a limerick about the wonders of GPU computing.\",\"requestJson\":\"{\\n \\\"model\\\": \\\"nv-mistralai/mistral-nemo-12b-instruct\\\",\\n \\\"messages\\\": [\\n {\\n \\\"role\\\": \\\"user\\\",\\n \\\"content\\\": \\\"Write a limerick about the wonders of GPU computing.\\\"\\n }\\n ],\\n \\\"top_p\\\": 0.7,\\n \\\"max_tokens\\\": 1024,\\n \\\"seed\\\": 42,\\n \\\"stream\\\": true\\n}\\n\",\"responseJson\":\"{\\n \\\"id\\\": \\\"id-123\\\",\\n \\\"object\\\": \\\"chat.completion\\\",\\n \\\"created\\\": 1677652288,\\n \\\"model\\\": \\\"nv-mistralai/mistral-nemo-12b-instruct\\\",\\n \\\"system_fingerprint\\\": \\\"fp_44709d6fcb\\\",\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"The python functions...\\\"\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 9,\\n \\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"},{\"name\":\"Tell me about Dumbledore.\",\"requestJson\":\"$5a\",\"responseJson\":\"{\\n \\\"id\\\": \\\"id-123\\\",\\n \\\"object\\\": \\\"chat.completion\\\",\\n \\\"created\\\": 1677652288,\\n \\\"model\\\": \\\"nv-mistralai/mistral-nemo-12b-instruct\\\",\\n \\\"system_fingerprint\\\": \\\"fp_44709d6fcb\\\",\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"At NVIDIA's GPU Technology Conference (GTC)...\\\"\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 9,\\n \\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"},{\"name\":\"What is the weather in Santa Clara, CA?\",\"requestJson\":\"$5b\",\"responseJson\":\"{\\n \\\"id\\\": \\\"id-123\\\",\\n \\\"object\\\": \\\"chat.completion\\\",\\n \\\"created\\\": 1677652288,\\n \\\"model\\\": \\\"nv-mistralai/mistral-nemo-12b-instruct\\\",\\n \\\"system_fingerprint\\\": \\\"fp_44709d6fcb\\\",\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"At NVIDIA's GPU Technology Conference (GTC)...\\\"\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 9,\\n \\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"}],\"templates\":[{\"title\":\"No Streaming\",\"requestEjs\":{\"python\":\"from openai import OpenAI\\n\\nclient = OpenAI(\\n base_url = \\\"https://integrate.api.nvidia.com/v1\\\",\\n api_key = \\\"$NVIDIA_API_KEY\\\"\\n)\\n\\ncompletion = client.chat.completions.create(\\n model=\\\"\u003c%- request.model %\u003e\\\",\\n messages=\u003c%- JSON.stringify(request.messages) %\u003e,\\n temperature=\u003c%- request.temperature %\u003e,\\n top_p=\u003c%- request.top_p %\u003e,\\n max_tokens=\u003c%- request.max_tokens %\u003e,\\n stream=\u003c%- request.stream?.toString()[0].toUpperCase() + request.stream?.toString().slice(1) %\u003e\\n)\\n\u003c% if (request.stream) { %\u003e\\nfor chunk in completion:\\n if chunk.choices[0].delta.content is not None:\\n print(chunk.choices[0].delta.content, end=\\\"\\\")\\n\u003c% } else { %\u003e\\nprint(completion.choices[0].message)\\n\u003c% } %\u003e\\n\",\"langChain\":\"from langchain_nvidia_ai_endpoints import ChatNVIDIA\\n\\nclient = ChatNVIDIA(\\n model=\\\"\u003c%- request.model %\u003e\\\",\\n api_key=\\\"$NVIDIA_API_KEY\\\", \\n temperature=\u003c%- request.temperature %\u003e,\\n top_p=\u003c%- request.top_p %\u003e,\\n max_tokens=\u003c%- request.max_tokens %\u003e,\\n)\\n\u003c% if (request.stream) { %\u003e\\nfor chunk in client.stream(\u003c%- JSON.stringify(request.messages) %\u003e): \\n print(chunk.content, end=\\\"\\\")\\n\u003c% } else { %\u003e\\nresponse = client.invoke(\u003c%- JSON.stringify(request.messages) %\u003e)\\nprint(response.content)\\n\u003c% } %\u003e\\n\",\"node.js\":\"import OpenAI from 'openai';\\n\\nconst openai = new OpenAI({\\n apiKey: '$NVIDIA_API_KEY',\\n baseURL: 'https://integrate.api.nvidia.com/v1',\\n})\\n\\nasync function main() {\\n const completion = await openai.chat.completions.create({\\n model: \\\"\u003c%- request.model %\u003e\\\",\\n messages: \u003c%- JSON.stringify(request.messages) %\u003e,\\n temperature: \u003c%- request.temperature %\u003e,\\n top_p: \u003c%- request.top_p %\u003e,\\n max_tokens: \u003c%- request.max_tokens %\u003e,\\n stream: \u003c%- request.stream %\u003e,\\n })\\n \u003c% if (request.stream) { %\u003e\\n for await (const chunk of completion) {\\n process.stdout.write(chunk.choices[0]?.delta?.content || '')\\n }\\n \u003c% } else { %\u003e\\n process.stdout.write(completion.choices[0]?.message?.content);\\n \u003c% } %\u003e\\n}\\n\\nmain();\",\"curl\":\"curl https://integrate.api.nvidia.com/v1/chat/completions \\\\\\n -H \\\"Content-Type: application/json\\\" \\\\\\n -H \\\"Authorization: Bearer $NVIDIA_API_KEY\\\" \\\\\\n -d '{\\n \\\"model\\\": \\\"nv-mistralai/mistral-nemo-12b-instruct\\\",\\n \\\"messages\\\": \u003c%- JSON.stringify(request.messages).replaceAll(\\\"'\\\", \\\"'\\\\\\\"'\\\\\\\"'\\\") %\u003e,\\n \\\"temperature\\\": \u003c%- request.temperature %\u003e, \\n \\\"top_p\\\": \u003c%- request.top_p %\u003e,\\n \\\"max_tokens\\\": \u003c%- request.max_tokens %\u003e,\\n \\\"stream\\\": \u003c%- request.stream %\u003e \\n }'\\n\"},\"response\":\"{\\n \\\"id\\\": \\\"chatcmpl-123\\\",\\n \\\"object\\\": \\\"chat.completion\\\",\\n \\\"created\\\": 1677652288,\\n \\\"model\\\": \\\"nv-mistralai/mistral-nemo-12b-instruct\\\",\\n \\\"system_fingerprint\\\": \\\"fp_44709d6fcb\\\",\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"\\\\n\\\\nHello there, how may I assist you today?\\\",\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 9,\\n \\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"}]}}}},\"security\":[{\"Token\":[]}],\"components\":{\"securitySchemes\":{\"Token\":{\"type\":\"http\",\"scheme\":\"bearer\"}},\"schemas\":{\"Errors\":{\"properties\":{\"type\":{\"type\":\"string\",\"description\":\"Error type\"},\"title\":{\"type\":\"string\",\"description\":\"Error title\"},\"status\":{\"type\":\"integer\",\"description\":\"Error status code\"},\"detail\":{\"type\":\"string\",\"description\":\"Detailed information about the error\"},\"instance\":{\"type\":\"string\",\"description\":\"Function instance used to invoke the request\"},\"requestId\":{\"type\":\"string\",\"format\":\"uuid\",\"description\":\"UUID of the request\"}},\"type\":\"object\",\"required\":[\"type\",\"title\",\"status\",\"detail\",\"instance\",\"requestId\"],\"title\":\"InvokeError\"},\"ChatCompletion\":{\"properties\":{\"id\":{\"description\":\"A unique identifier for the completion.\",\"format\":\"uuid\",\"title\":\"Id\",\"type\":\"string\"},\"choices\":{\"description\":\"The list of completion choices the model generated for the input prompt.\",\"items\":{\"$ref\":\"#/components/schemas/Choice\"},\"title\":\"Choices\",\"type\":\"array\"},\"usage\":{\"allOf\":[{\"$ref\":\"#/components/schemas/Usage\"}],\"description\":\"Usage statistics for the completion request.\"}},\"required\":[\"id\",\"choices\",\"usage\"],\"title\":\"ChatCompletion\",\"type\":\"object\"},\"ChatCompletionChunk\":{\"properties\":{\"id\":{\"description\":\"A unique identifier for the completion.\",\"format\":\"uuid\",\"title\":\"Id\",\"type\":\"string\"},\"choices\":{\"description\":\"The list of completion choices the model generated for the input prompt.\",\"items\":{\"$ref\":\"#/components/schemas/ChoiceChunk\"},\"title\":\"Choices\",\"type\":\"array\"}},\"required\":[\"id\",\"choices\"],\"title\":\"ChatCompletionChunk\",\"type\":\"object\"},\"ChatRequest\":{\"additionalProperties\":false,\"properties\":{\"model\":{\"type\":\"string\",\"title\":\"Model\",\"default\":\"nv-mistralai/mistral-nemo-12b-instruct\"},\"messages\":{\"description\":\"A list of messages comprising the conversation so far. The roles of the messages must be alternating between `user` and `assistant`. The last input message should have role `user`. A message with the the `system` role is optional, and must be the very first message if it is present; `context` is also optional, but must come before a user question.\",\"examples\":[[{\"content\":\"I am going to Paris, what should I see?\",\"role\":\"user\"}]],\"items\":{\"$ref\":\"#/components/schemas/Message\"},\"title\":\"Messages\",\"type\":\"array\"},\"temperature\":{\"default\":0.2,\"description\":\"The sampling temperature to use for text generation. The higher the temperature value is, the less deterministic the output text will be. It is not recommended to modify both temperature and top_p in the same call.\",\"maximum\":1,\"minimum\":0,\"title\":\"Temperature\",\"type\":\"number\"},\"top_p\":{\"default\":0.7,\"description\":\"The top-p sampling mass used for text generation. The top-p value determines the probability mass that is sampled at sampling time. For example, if top_p = 0.2, only the most likely tokens (summing to 0.2 cumulative probability) will be sampled. It is not recommended to modify both temperature and top_p in the same call.\",\"maximum\":1,\"exclusiveMinimum\":0,\"title\":\"Top P\",\"type\":\"number\"},\"frequency_penalty\":{\"type\":\"number\",\"maximum\":2,\"minimum\":-2,\"default\":0,\"title\":\"Frequency Penalty\",\"description\":\"Indicates how much to penalize new tokens based on their existing frequency in the text so far, decreasing model likelihood to repeat the same line verbatim.\"},\"presence_penalty\":{\"type\":\"number\",\"maximum\":2,\"minimum\":-2,\"default\":0,\"title\":\"Presence Penalty\",\"description\":\"Positive values penalize new tokens based on whether they appear in the text so far, increasing model likelihood to talk about new topics.\"},\"max_tokens\":{\"default\":1024,\"description\":\"The maximum number of tokens to generate in any given call. Note that the model is not aware of this value, and generation will simply stop at the number of tokens specified.\",\"maximum\":8192,\"minimum\":1,\"title\":\"Max Tokens\",\"type\":\"integer\"},\"stream\":{\"default\":false,\"description\":\"If set, partial message deltas will be sent. Tokens will be sent as data-only server-sent events (SSE) as they become available (JSON responses are prefixed by `data: `), with the stream terminated by a `data: [DONE]` message.\",\"title\":\"Stream\",\"type\":\"boolean\"},\"stop\":{\"anyOf\":[{\"items\":{\"type\":\"string\"},\"type\":\"array\"},{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Stop\",\"description\":\"A string or a list of strings where the API will stop generating further tokens. The returned text will not contain the stop sequence.\"}},\"required\":[\"messages\"],\"title\":\"ChatRequest\",\"type\":\"object\"},\"Choice\":{\"properties\":{\"index\":{\"description\":\"The index of the choice in the list of choices (always 0).\",\"title\":\"Index\",\"type\":\"integer\"},\"message\":{\"allOf\":[{\"$ref\":\"#/components/schemas/Message\"}],\"description\":\"A chat completion message generated by the model.\",\"examples\":[{\"content\":\"Ah, Paris, the City of Light! There are so many amazing things to see and do in this beautiful city ...\",\"role\":\"assistant\"}]},\"finish_reason\":{\"anyOf\":[{\"enum\":[\"stop\",\"length\"],\"type\":\"string\"},{\"type\":\"null\"}],\"default\":null,\"description\":\"The reason the model stopped generating tokens. This will be `stop` if the model hit a natural stop point or a provided stop sequence, or `length` if the maximum number of tokens specified in the request was reached.\",\"examples\":[\"stop\"],\"title\":\"Finish Reason\"}},\"required\":[\"index\",\"message\"],\"title\":\"Choice\",\"type\":\"object\"},\"ChoiceChunk\":{\"properties\":{\"index\":{\"description\":\"The index of the choice in the list of choices (always 0).\",\"title\":\"Index\",\"type\":\"integer\"},\"delta\":{\"allOf\":[{\"$ref\":\"#/components/schemas/Message\"}],\"description\":\"A chat completion delta generated by streamed model responses.\",\"examples\":[{\"content\":\"Ah,\",\"role\":\"assistant\"}]},\"finish_reason\":{\"anyOf\":[{\"enum\":[\"stop\",\"length\"],\"type\":\"string\"},{\"type\":\"null\"}],\"default\":null,\"description\":\"The reason the model stopped generating tokens. This will be `stop` if the model hit a natural stop point or a provided stop sequence, or `length` if the maximum number of tokens specified in the request was reached. Will be `null` if the model has not finished generating.\",\"title\":\"Finish Reason\"}},\"required\":[\"index\",\"delta\"],\"title\":\"ChoiceChunk\",\"type\":\"object\"},\"Message\":{\"additionalProperties\":false,\"properties\":{\"role\":{\"description\":\"The role of the message author.\",\"enum\":[\"system\",\"context\",\"user\",\"assistant\"],\"title\":\"Role\",\"type\":\"string\"},\"content\":{\"description\":\"The contents of the message.\",\"title\":\"Content\",\"type\":\"string\"}},\"required\":[\"role\",\"content\"],\"title\":\"Message\",\"type\":\"object\"},\"Usage\":{\"properties\":{\"completion_tokens\":{\"description\":\"Number of tokens in the generated completion.\",\"examples\":[25],\"title\":\"Completion Tokens\",\"type\":\"integer\"},\"prompt_tokens\":{\"description\":\"Number of tokens in the prompt.\",\"examples\":[9],\"title\":\"Prompt Tokens\",\"type\":\"integer\"},\"total_tokens\":{\"description\":\"Total number of tokens used in the request (prompt + completion).\",\"examples\":[34],\"title\":\"Total Tokens\",\"type\":\"integer\"}},\"required\":[\"completion_tokens\",\"prompt_tokens\",\"total_tokens\"],\"title\":\"Usage\",\"type\":\"object\"}}}},\"namespace\":\"qc69jvmznzxy\",\"updatedDate\":\"2024-11-20T03:05:15.058Z\",\"nvcfFunctionId\":\"f8c05193-d2e2-4f0f-bb4d-7ad70070002b\",\"createdDate\":\"2024-07-18T13:59:22.640Z\",\"attributes\":{\"dockerRun\":\"Pull and run the NVIDIA NIM with the command below. This will download the optimized model for your infrastructure.\\n```bash\\nexport NGC_API_KEY=\u003cPASTE_API_KEY_HERE\u003e\\nexport LOCAL_NIM_CACHE=~/.cache/nim\\nmkdir -p \\\"$LOCAL_NIM_CACHE\\\"\\ndocker run -it --rm \\\\\\n --gpus all \\\\\\n --shm-size=16GB \\\\\\n -e NGC_API_KEY \\\\\\n -v \\\"$LOCAL_NIM_CACHE:/opt/nim/.cache\\\" \\\\\\n -u $(id -u) \\\\\\n -p 8000:8000 \\\\\\n nvcr.io/nim/nv-mistralai/mistral-nemo-12b-instruct:latest\\n```\\n\\nYou can now make a local API call using this curl command:\\n```bash\\ncurl -X 'POST' \\\\\\n'http://0.0.0.0:8000/v1/chat/completions' \\\\\\n-H 'accept: application/json' \\\\\\n-H 'Content-Type: application/json' \\\\\\n-d '{\\n \\\"model\\\": \\\"mistral-nemo-12b-instruct\\\",\\n \\\"messages\\\": [{\\\"role\\\":\\\"user\\\", \\\"content\\\":\\\"Write a limerick about the wonders of GPU computing.\\\"}],\\n \\\"max_tokens\\\": 64\\n}'\\n```\\n\\nFor more details on getting started with this NIM, visit the [NVIDIA NIM Docs](https://docs.nvidia.com/nim/large-language-models/latest/getting-started.html).\\n\",\"dockerTermsOfUse\":\"By running the below commands, you accept the \u003ca href=\\\"https://www.nvidia.com/en-us/data-center/products/nvidia-ai-enterprise/eula/\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA AI Enterprise Terms of Use\u003c/a\u003e and the \u003ca href=\\\"https://docs.nvidia.com/ai-foundation-models-community-license.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA Community Models License\u003c/a\u003e.\\n\",\"showUnavailableBanner\":false,\"apiDocsUrl\":\"https://docs.api.nvidia.com/nim/reference/nv-mistralai-mistral-nemo-12b-instruct\",\"playground\":{\"type\":\"chatWithTools\"},\"termsOfUse\":\"\u003cb\u003eGOVERNING TERMS\u003c/b\u003e: This trial is governed by the \u003ca href=\\\"https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA API Trial Service Terms of Use\u003c/a\u003e. The use of this model is governed by the \u003ca href=\\\"https://docs.nvidia.com/ai-foundation-models-community-license.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA AI Foundation Models Community License\u003c/a\u003e. ADDITIONAL INFORMATION: Apache 2.0.\\n\",\"cta\":{\"text\":\"Apply to Self-Host\",\"url\":\"https://www.nvidia.com/en-us/ai/nim-notifyme/\",\"nim_available_override_url\":\"https://catalog.ngc.nvidia.com/orgs/nim/teams/nv-mistralai/containers/mistral-nemo-12b-instruct\"},\"projects\":[{\"name\":\"Build a Customizable Hybrid RAG Chatbot\",\"url\":\"https://github.com/NVIDIA/workbench-example-hybrid-rag\",\"imageUrl\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/nv-workbench.jpg\",\"workbench\":true}]},\"artifactName\":\"mistral-nemo-12b-instruct\"},\"config\":{\"name\":\"mistral-nemo-12b-instruct\",\"type\":\"model\"}},{\"endpoint\":{\"requestStatus\":{\"statusCode\":\"SUCCESS\",\"requestId\":\"a2bea4b0-1899-4307-b364-a586a7cb80b0\"},\"artifact\":{\"orgName\":\"qc69jvmznzxy\",\"labels\":[\"Advanced Reasoning\",\"Chat\",\"Large Language Models\",\"Text-to-Text\",\"Code Generation\"],\"logo\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/mixtral-8x22b-instruct.jpg\",\"shortDescription\":\"An MOE LLM that follows instructions, completes requests, and generates creative text.\",\"isReadOnly\":true,\"description\":\"$5c\",\"canGuestDownload\":true,\"isPublic\":true,\"createdDate\":\"2024-04-18T16:31:03.259Z\",\"publisher\":\"mistralai\",\"displayName\":\"mixtral-8x22b-instruct-v0.1\",\"name\":\"mixtral-8x22b-instruct\",\"updatedDate\":\"2024-11-18T22:30:52.701Z\",\"attributes\":[{\"key\":\"AVAILABLE\",\"value\":\"true\"},{\"key\":\"PREVIEW\",\"value\":\"false\"}],\"artifactType\":\"ENDPOINT\"}},\"spec\":{\"openAPISpec\":{\"openapi\":\"3.1.0\",\"info\":{\"title\":\"NVIDIA NIM API for mistralai/mixtral-8x22b-instruct-v0.1\",\"description\":\"The NVIDIA NIM REST API. Please see https://docs.api.nvidia.com/nim/reference/mistralai-mixtral-8x22b-instruct for more details.\",\"version\":\"1.0.0\",\"termsOfService\":\"https://www.nvidia.com/en-us/data-center/products/nvidia-ai-enterprise/eula/\",\"contact\":{\"name\":\"NVIDIA Enterprise Support\",\"url\":\"https://www.nvidia.com/en-us/support/enterprise/\"},\"license\":{\"name\":\"Apache 2.0\",\"url\":\"https://mistral.ai/terms-of-service/\"}},\"servers\":[{\"url\":\"https://integrate.api.nvidia.com/v1/\"}],\"paths\":{\"/chat/completions\":{\"post\":{\"operationId\":\"create_chat_completion_v1_chat_completions_post\",\"tags\":[\"Chat\"],\"summary\":\"Creates a model response for the given chat conversation.\",\"description\":\"Given a list of messages comprising a conversation, the model will return a response. Compatible with OpenAI. See https://platform.openai.com/docs/api-reference/chat/create\",\"requestBody\":{\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ChatCompletionRequest\"}}},\"required\":true},\"responses\":{\"200\":{\"description\":\"Successful Response\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ChatCompletionResponse\"}}}},\"402\":{\"description\":\"Payment Required\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/PaymentRequiredError\"}}}},\"422\":{\"description\":\"Validation Error\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/HTTPValidationError\"}}}}},\"x-nvai-meta\":{\"name\":\"Create chat completion\",\"returns\":\"Returns a [chat completion](/docs/api-reference/chat/object) object, or a streamed sequence of [chat completion chunk](/docs/api-reference/chat/streaming) objects if the request is streamed.\\n\",\"path\":\"create\",\"examples\":[{\"name\":\"Write a limerick about the wonders of GPU computing.\",\"requestJson\":\"{\\n \\\"model\\\": \\\"mistralai/mixtral-8x22b-instruct-v0.1\\\",\\n \\\"messages\\\": [\\n {\\n \\\"role\\\": \\\"system\\\",\\n \\\"content\\\": \\\"You are a helpful assistant.\\\"\\n },\\n {\\n \\\"role\\\": \\\"user\\\",\\n \\\"content\\\": \\\"Write a limerick about the wonders of GPU computing.\\\"\\n }\\n ],\\n \\\"top_p\\\": 0.7,\\n \\\"max_tokens\\\": 1024,\\n \\\"seed\\\": 42,\\n \\\"stop\\\": null,\\n \\\"stream\\\": true\\n}\\n\",\"responseJson\":\"{\\n \\\"id\\\": \\\"id-123\\\",\\n \\\"object\\\": \\\"chat.completion\\\",\\n \\\"created\\\": 1677652288,\\n \\\"model\\\": \\\"mistralai/mixtral-8x22b-instruct-v0.1\\\",\\n \\\"system_fingerprint\\\": \\\"fp_44709d6fcb\\\",\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"Here's a short poem on...\\\"\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 9,\\n \\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"},{\"name\":\"What can I see at NVIDIA's GPU Technology Conference?\",\"requestJson\":\"{\\n \\\"model\\\": \\\"mistralai/mixtral-8x22b-instruct-v0.1\\\",\\n \\\"messages\\\": [\\n {\\n \\\"role\\\": \\\"system\\\",\\n \\\"content\\\": \\\"You are a helpful assistant.\\\"\\n },\\n {\\n \\\"role\\\": \\\"user\\\",\\n \\\"content\\\": \\\"What can I see at NVIDIA's GPU Technology Conference?\\\"\\n }\\n ],\\n \\\"top_p\\\": 0.7,\\n \\\"max_tokens\\\": 1024,\\n \\\"seed\\\": 42,\\n \\\"stop\\\": null,\\n \\\"stream\\\": true\\n}\\n\",\"responseJson\":\"{\\n \\\"id\\\": \\\"id-123\\\",\\n \\\"object\\\": \\\"chat.completion\\\",\\n \\\"created\\\": 1677652288,\\n \\\"model\\\": \\\"mistralai/mixtral-8x22b-instruct-v0.1\\\",\\n \\\"system_fingerprint\\\": \\\"fp_44709d6fcb\\\",\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"At NVIDIA's GTC conference...\\\"\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 9,\\n \\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"}],\"templates\":[{\"title\":\"No Streaming\",\"requestEjs\":{\"python\":\"from openai import OpenAI\\n\\nclient = OpenAI(\\n base_url = \\\"https://integrate.api.nvidia.com/v1\\\",\\n api_key = \\\"$NVIDIA_API_KEY\\\"\\n)\\n\\ncompletion = client.chat.completions.create(\\n model=\\\"\u003c%- request.model %\u003e\\\",\\n messages=\u003c%- JSON.stringify(request.messages) %\u003e,\\n temperature=\u003c%- request.temperature %\u003e,\\n top_p=\u003c%- request.top_p %\u003e,\\n max_tokens=\u003c%- request.max_tokens %\u003e,\\n stream=\u003c%- request.stream?.toString()[0].toUpperCase() + request.stream?.toString().slice(1) %\u003e\\n)\\n\u003c% if (request.stream) { %\u003e\\nfor chunk in completion:\\n if chunk.choices[0].delta.content is not None:\\n print(chunk.choices[0].delta.content, end=\\\"\\\")\\n\u003c% } else { %\u003e\\nprint(completion.choices[0].message)\\n\u003c% } %\u003e\\n\",\"langChain\":\"from langchain_nvidia_ai_endpoints import ChatNVIDIA\\n\\nclient = ChatNVIDIA(\\n model=\\\"\u003c%- request.model %\u003e\\\",\\n api_key=\\\"$NVIDIA_API_KEY\\\", \\n temperature=\u003c%- request.temperature %\u003e,\\n top_p=\u003c%- request.top_p %\u003e,\\n max_tokens=\u003c%- request.max_tokens %\u003e,\\n)\\n\u003c% if (request.stream) { %\u003e\\nfor chunk in client.stream(\u003c%- JSON.stringify(request.messages) %\u003e): \\n print(chunk.content, end=\\\"\\\")\\n\u003c% } else { %\u003e\\nresponse = client.invoke(\u003c%- JSON.stringify(request.messages) %\u003e)\\nprint(response.content)\\n\u003c% } %\u003e\\n\",\"node.js\":\"import OpenAI from 'openai';\\n\\nconst openai = new OpenAI({\\n apiKey: '$NVIDIA_API_KEY',\\n baseURL: 'https://integrate.api.nvidia.com/v1',\\n})\\n\\nasync function main() {\\n const completion = await openai.chat.completions.create({\\n model: \\\"\u003c%- request.model %\u003e\\\",\\n messages: \u003c%- JSON.stringify(request.messages) %\u003e,\\n temperature: \u003c%- request.temperature %\u003e,\\n top_p: \u003c%- request.top_p %\u003e,\\n max_tokens: \u003c%- request.max_tokens %\u003e,\\n stream: \u003c%- request.stream %\u003e,\\n })\\n \u003c% if (request.stream) { %\u003e\\n for await (const chunk of completion) {\\n process.stdout.write(chunk.choices[0]?.delta?.content || '')\\n }\\n \u003c% } else { %\u003e\\n process.stdout.write(completion.choices[0]?.message?.content);\\n \u003c% } %\u003e\\n}\\n\\nmain();\",\"curl\":\"curl https://integrate.api.nvidia.com/v1/chat/completions \\\\\\n -H \\\"Content-Type: application/json\\\" \\\\\\n -H \\\"Authorization: Bearer $NVIDIA_API_KEY\\\" \\\\\\n -d '{\\n \\\"model\\\": \\\"mistralai/mixtral-8x22b-instruct-v0.1\\\",\\n \\\"messages\\\": \u003c%- JSON.stringify(request.messages).replaceAll(\\\"'\\\", \\\"'\\\\\\\"'\\\\\\\"'\\\") %\u003e,\\n \\\"temperature\\\": \u003c%- request.temperature %\u003e, \\n \\\"top_p\\\": \u003c%- request.top_p %\u003e,\\n \\\"max_tokens\\\": \u003c%- request.max_tokens %\u003e,\\n \\\"stream\\\": \u003c%- request.stream %\u003e \\n }'\\n\"},\"response\":\"{\\n \\\"id\\\": \\\"chatcmpl-123\\\",\\n \\\"object\\\": \\\"chat.completion\\\",\\n \\\"created\\\": 1677652288,\\n \\\"model\\\": \\\"mistralai/mixtral-8x22b-instruct-v0.1\\\",\\n \\\"system_fingerprint\\\": \\\"fp_44709d6fcb\\\",\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"\\\\n\\\\nHello there, how may I assist you today?\\\",\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 9,\\n \\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"}]}}}},\"security\":[{\"Token\":[]}],\"components\":{\"securitySchemes\":{\"Token\":{\"type\":\"http\",\"scheme\":\"bearer\"}},\"schemas\":{\"ChatCompletionRequest\":{\"properties\":{\"model\":{\"type\":\"string\",\"title\":\"Model\",\"default\":\"mistralai/mixtral-8x22b-instruct-v0.1\"},\"max_tokens\":{\"type\":\"integer\",\"minimum\":1,\"title\":\"Max Tokens\",\"description\":\"The maximum number of tokens to generate in any given call. Note that the model is not aware of this value, and generation will simply stop at the number of tokens specified.\",\"default\":1024},\"stream\":{\"type\":\"boolean\",\"title\":\"Stream\",\"description\":\"If set, partial message deltas will be sent. Tokens will be sent as data-only server-sent events (SSE) as they become available (JSON responses are prefixed by `data: `), with the stream terminated by a `data: [DONE]` message.\",\"default\":false},\"temperature\":{\"type\":\"number\",\"maximum\":1,\"minimum\":0,\"title\":\"Temperature\",\"description\":\"The sampling temperature to use for text generation. The higher the temperature value is, the less deterministic the output text will be. It is not recommended to modify both temperature and top_p in the same call.\",\"default\":0.5},\"top_p\":{\"type\":\"number\",\"maximum\":1,\"minimum\":0,\"title\":\"Top P\",\"description\":\"The top-p sampling mass used for text generation. The top-p value determines the probability mass that is sampled at sampling time. For example, if top_p = 0.2, only the most likely tokens (summing to 0.2 cumulative probability) will be sampled. It is not recommended to modify both temperature and top_p in the same call.\",\"default\":1},\"stop\":{\"anyOf\":[{\"items\":{\"type\":\"string\"},\"type\":\"array\"},{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Stop\",\"description\":\"A string or a list of strings where the API will stop generating further tokens. The returned text will not contain the stop sequence.\",\"examples\":[null]},\"frequency_penalty\":{\"type\":\"number\",\"maximum\":2,\"minimum\":-2,\"default\":0,\"title\":\"Frequency Penalty\",\"description\":\"Indicates how much to penalize new tokens based on their existing frequency in the text so far, decreasing model likelihood to repeat the same line verbatim.\"},\"presence_penalty\":{\"type\":\"number\",\"maximum\":2,\"minimum\":-2,\"default\":0,\"title\":\"Presence Penalty\",\"description\":\"Positive values penalize new tokens based on whether they appear in the text so far, increasing model likelihood to talk about new topics.\"},\"seed\":{\"type\":\"integer\",\"maximum\":18446744073709552000,\"minimum\":0,\"title\":\"Seed\",\"description\":\"The model generates random results. Changing the input seed alone will produce a different response with similar characteristics. It is possible to reproduce results by fixing the input seed (assuming all other hyperparameters are also fixed).\",\"default\":0},\"messages\":{\"anyOf\":[{\"type\":\"string\"},{\"items\":{\"additionalProperties\":{\"type\":\"string\"},\"type\":\"object\"},\"type\":\"array\"}],\"title\":\"Messages\",\"description\":\"A list of messages comprising the conversation so far.\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"messages\"],\"title\":\"ChatCompletionRequest\",\"description\":\"OpenAI ChatCompletionRequest\"},\"ChatCompletionResponse\":{\"properties\":{\"id\":{\"type\":\"string\",\"title\":\"Id\",\"description\":\"A unique identifier for the completion.\"},\"object\":{\"type\":\"string\",\"title\":\"Object\",\"default\":\"chat.completion\"},\"created\":{\"type\":\"integer\",\"title\":\"Created\"},\"model\":{\"type\":\"string\",\"title\":\"Model\",\"example\":\"mistralai/mixtral-8x22b-instruct-v0.1\"},\"choices\":{\"items\":{\"$ref\":\"#/components/schemas/ChatCompletionResponseChoice\"},\"type\":\"array\",\"title\":\"Choices\",\"description\":\"The list of completion choices the model generated for the input prompt.\"},\"usage\":{\"$ref\":\"#/components/schemas/UsageInfo\",\"description\":\"Usage statistics for the completion request.\"}},\"type\":\"object\",\"required\":[\"model\",\"choices\",\"usage\"],\"title\":\"ChatCompletionResponse\"},\"ChatCompletionResponseChoice\":{\"properties\":{\"index\":{\"type\":\"integer\",\"title\":\"Index\",\"description\":\"The index of the choice in the list of choices (always 0).\"},\"message\":{\"$ref\":\"#/components/schemas/ChatMessage\",\"description\":\"A chat completion message generated by the model.\"},\"finish_reason\":{\"anyOf\":[{\"type\":\"string\",\"enum\":[\"stop\",\"length\"]},{\"type\":\"null\"}],\"title\":\"Finish Reason\",\"description\":\"The reason the model stopped generating tokens. This will be `stop` if the model hit a natural stop point or a provided stop sequence, or `length` if the maximum number of tokens specified in the request was reached. Will be `null` if the model has not finished\"}},\"type\":\"object\",\"required\":[\"index\",\"message\"],\"title\":\"ChatCompletionResponseChoice\"},\"ChatMessage\":{\"properties\":{\"role\":{\"type\":\"string\",\"title\":\"Role\",\"description\":\"The role of the message author.\"},\"content\":{\"type\":\"string\",\"title\":\"Content\",\"description\":\"The contents of the message.\"}},\"type\":\"object\",\"required\":[\"role\",\"content\"],\"title\":\"ChatMessage\"},\"HTTPValidationError\":{\"properties\":{\"detail\":{\"items\":{\"$ref\":\"#/components/schemas/ValidationError\"},\"type\":\"array\",\"title\":\"Detail\",\"description\":\"Detailed information about the error.\"}},\"type\":\"object\",\"title\":\"HTTPValidationError\"},\"PaymentRequiredError\":{\"properties\":{\"detail\":{\"type\":\"string\",\"description\":\"Contains specific information related to the error and why it occurred.\",\"example\":\"You have reached your limit of credits.\"}},\"type\":\"object\",\"title\":\"PaymentRequiredError\"},\"UsageInfo\":{\"properties\":{\"prompt_tokens\":{\"type\":\"integer\",\"title\":\"Prompt Tokens\",\"description\":\"Number of tokens in the prompt.\",\"default\":0},\"total_tokens\":{\"type\":\"integer\",\"title\":\"Total Tokens\",\"description\":\"Total number of tokens used in the request (prompt + completion).\",\"default\":0},\"completion_tokens\":{\"anyOf\":[{\"type\":\"integer\"},{\"type\":\"null\"}],\"title\":\"Completion Tokens\",\"description\":\"Number of tokens in the generated completion.\",\"default\":0}},\"type\":\"object\",\"title\":\"UsageInfo\"},\"ValidationError\":{\"properties\":{\"loc\":{\"items\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"integer\"}]},\"type\":\"array\",\"title\":\"Location\"},\"msg\":{\"type\":\"string\",\"title\":\"Message\",\"description\":\"The error message.\"},\"type\":{\"type\":\"string\",\"title\":\"Error Type\",\"description\":\"Error type\"}},\"type\":\"object\",\"required\":[\"loc\",\"msg\",\"type\"],\"title\":\"ValidationError\"}}}},\"namespace\":\"qc69jvmznzxy\",\"updatedDate\":\"2024-11-18T22:30:53.299Z\",\"nvcfFunctionId\":\"710c92d0-7c98-46d6-b5ae-07e84bcaa5d3\",\"createdDate\":\"2024-04-18T16:31:03.529Z\",\"attributes\":{\"dockerRun\":\"Pull and run the NVIDIA NIM with the command below. This will download the optimized model for your infrastructure.\\n```bash\\nexport NGC_API_KEY=\u003cPASTE_API_KEY_HERE\u003e\\nexport LOCAL_NIM_CACHE=~/.cache/nim\\nmkdir -p \\\"$LOCAL_NIM_CACHE\\\"\\ndocker run -it --rm \\\\\\n --gpus all \\\\\\n --shm-size=16GB \\\\\\n -e NGC_API_KEY \\\\\\n -v \\\"$LOCAL_NIM_CACHE:/opt/nim/.cache\\\" \\\\\\n -u $(id -u) \\\\\\n -p 8000:8000 \\\\\\n nvcr.io/nim/mistralai/mixtral-8x22b-instruct-v01:latest\\n```\\n\\nYou can now make a local API call using this curl command:\\n```bash\\ncurl -X 'POST' \\\\\\n'http://0.0.0.0:8000/v1/chat/completions' \\\\\\n-H 'accept: application/json' \\\\\\n-H 'Content-Type: application/json' \\\\\\n-d '{\\n \\\"model\\\": \\\"mistralai/mixtral-8x22b-instruct-v0.1\\\",\\n \\\"messages\\\": [{\\\"role\\\":\\\"user\\\", \\\"content\\\":\\\"Write a limerick about the wonders of GPU computing.\\\"}],\\n \\\"max_tokens\\\": 64\\n}'\\n```\\n\\nFor more details on getting started with this NIM, visit the [NVIDIA NIM Docs](https://docs.nvidia.com/nim/large-language-models/latest/getting-started.html).\\n\",\"dockerTermsOfUse\":\"By running the below commands, you accept the \u003ca href=\\\"https://www.nvidia.com/en-us/data-center/products/nvidia-ai-enterprise/eula/\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA AI Enterprise Terms of Use\u003c/a\u003e and the \u003ca href=\\\"https://docs.nvidia.com/ai-foundation-models-community-license.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA Community Models License\u003c/a\u003e.\\n\",\"showUnavailableBanner\":false,\"apiDocsUrl\":\"https://docs.api.nvidia.com/nim/reference/mistralai-mixtral-8x22b-instruct\",\"playground\":{\"type\":\"chat\"},\"termsOfUse\":\"\u003cb\u003eGOVERNING TERMS\u003c/b\u003e: Your use of this API is governed by the \u003ca href=\\\"https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA API Trial Service Terms of Use\u003c/a\u003e; and the use of this model is governed by the \u003ca href=\\\"https://docs.nvidia.com/ai-foundation-models-community-license.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA AI Foundation Models Community License\u003c/a\u003e and \u003ca href=\\\"https://mistral.ai/terms-of-service/\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eMistral AI Terms of Use\u003c/a\u003e.\\n\",\"cta\":{\"text\":\"Run Anywhere - Notify Me\",\"url\":\"https://www.nvidia.com/en-us/ai/nim-notifyme/\",\"nim_available_override_url\":\"https://catalog.ngc.nvidia.com/orgs/nim/teams/mistralai/containers/mixtral-8x22b-instruct-v01\"},\"projects\":[{\"name\":\"Build a Customizable Hybrid RAG Chatbot\",\"url\":\"https://github.com/NVIDIA/workbench-example-hybrid-rag\",\"imageUrl\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/nv-workbench.jpg\",\"workbench\":true},{\"name\":\"Build a Customizable RAG Agent\",\"url\":\"https://github.com/NVIDIA/workbench-example-agentic-rag\",\"imageUrl\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/nv-workbench.jpg\",\"workbench\":true}]},\"artifactName\":\"mixtral-8x22b-instruct\"},\"config\":{\"name\":\"mixtral-8x22b-instruct\",\"type\":\"model\"}},{\"endpoint\":{\"requestStatus\":{\"statusCode\":\"SUCCESS\",\"requestId\":\"e671abbc-725e-46fa-88ff-cc0c7e744017\"},\"artifact\":{\"orgName\":\"qc69jvmznzxy\",\"labels\":[\"Image Generation\",\"Text-to-Image\"],\"logo\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/sdxl-turbo.jpg\",\"shortDescription\":\"A fast generative text-to-image model that can synthesize photorealistic images from a text prompt in a single network evaluation\",\"isReadOnly\":true,\"description\":\"$5d\",\"canGuestDownload\":true,\"isPublic\":true,\"createdDate\":\"2024-03-15T04:54:37.985Z\",\"publisher\":\"stabilityai\",\"displayName\":\"sdxl-turbo\",\"name\":\"sdxl-turbo\",\"updatedDate\":\"2024-11-15T20:31:45.922Z\",\"attributes\":[{\"key\":\"PREVIEW\",\"value\":\"true\"}],\"artifactType\":\"ENDPOINT\"}},\"spec\":{\"openAPISpec\":{\"openapi\":\"3.1.0\",\"info\":{\"contact\":{\"name\":\"NVIDIA Support\",\"url\":\"https://help.nvidia.com/\"},\"description\":\"The NVIDIA NIM REST API. Please see https://docs.api.nvidia.com/nim for more details.\",\"license\":{\"name\":\"STABILITY AI NON-COMMERCIAL RESEARCH COMMUNITY\",\"url\":\"https://github.com/Stability-AI/generative-models/blob/main/model_licenses/LICENSE-SDXL-Turbo\"},\"termsOfService\":\"https://nvidia.com/legal/terms-of-use\",\"title\":\"NVIDIA NIM API for stabilityai/sdxl-turbo\",\"version\":\"1.0.0\"},\"servers\":[{\"url\":\"https://ai.api.nvidia.com/v1/\"}],\"paths\":{\"/genai/stabilityai/sdxl-turbo\":{\"post\":{\"operationId\":\"_infer_infer_post\",\"requestBody\":{\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ImageRequest\"}}},\"required\":true},\"responses\":{\"200\":{\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ImageResponse\"}}},\"description\":\"Successful Response\"},\"422\":{\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/HTTPValidationError\"}}},\"description\":\"Validation Error\"}},\"summary\":\" Infer\",\"x-nvai-meta\":{\"examples\":[{\"name\":\"Example 1\",\"input\":{\"text\":\"A steampunk dragon soaring over a Victorian cityscape, with gears and smoke billowing from its wings.\"},\"output\":{\"image\":\"https://assets.ngc.nvidia.com/products/api-catalog/sdxl-turbo/sdxlTurbo1.jpg\"},\"requestJson\":\"{ \\\"text_prompts\\\": [ { \\\"text\\\": \\\"\u003c%- input.text %\u003e\\\", \\\"weight\\\": 1 } ], \\\"sampler\\\": \\\"K_EULER_ANCESTRAL\\\", \\\"steps\\\": 2, \\\"seed\\\": 0 }\"},{\"name\":\"Example 2\",\"input\":{\"text\":\"A dolphin swimming through a coral reef filled with bioluminescent creatures, casting an ethereal glow.\"},\"output\":{\"image\":\"https://assets.ngc.nvidia.com/products/api-catalog/sdxl-turbo/sdxlTurbo2.jpg\"},\"requestJson\":\"{ \\\"text_prompts\\\": [ { \\\"text\\\": \\\"\u003c%- input.text %\u003e\\\", \\\"weight\\\": 1 } ], \\\"sampler\\\": \\\"K_EULER_ANCESTRAL\\\", \\\"steps\\\": 2, \\\"seed\\\": 0 }\"},{\"name\":\"Example 3\",\"input\":{\"text\":\"A hot rod, racing in the desert at sunset, 35mm film\"},\"output\":{\"image\":\"https://assets.ngc.nvidia.com/products/api-catalog/sdxl-turbo/sdxlTurbo3.jpg\"},\"requestJson\":\"{ \\\"text_prompts\\\": [ { \\\"text\\\": \\\"\u003c%- input.text %\u003e\\\", \\\"weight\\\": 1 } ], \\\"sampler\\\": \\\"K_EULER_ANCESTRAL\\\", \\\"steps\\\": 2, \\\"seed\\\": 0 }\"},{\"name\":\"Example 4\",\"input\":{\"text\":\"An adorable robot pet, cute, big eyes, cuddly, happy, prototype, rendered image, glowing accents, shiny, reflective floor, glass\"},\"output\":{\"image\":\"https://assets.ngc.nvidia.com/products/api-catalog/sdxl-turbo/sdxlTurbo4.jpg\"},\"requestJson\":\"{ \\\"text_prompts\\\": [ { \\\"text\\\": \\\"\u003c%- input.text %\u003e\\\", \\\"weight\\\": 1 } ], \\\"sampler\\\": \\\"K_EULER_ANCESTRAL\\\", \\\"steps\\\": 2, \\\"seed\\\": 0 }\"}],\"name\":\"Generate a new image from a text prompt\",\"path\":\"infer\",\"returns\":\"Returns an Image artifact that consists from a generated image (JPEG) encoded in base64, finish reason and a seed used during the generation\",\"templates\":[{\"requestEjs\":{\"curl\":\"invoke_url='https://ai.api.nvidia.com/v1/genai/stabilityai/sdxl-turbo'\\n\\nauthorization_header=\\\"Authorization: Bearer $NVIDIA_API_KEY\\\"\\naccept_header='Accept: application/json'\\ncontent_type_header='Content-Type: application/json'\\n\\ndata='{\\n \\\"text_prompts\\\": [{\\\"text\\\": \u003c%- JSON.stringify(request.prompt).replaceAll('\\\\'', '\\\\'\\\\\\\\\\\\'\\\\'') %\u003e}],\\n \\\"seed\\\": \u003c%- request.seed %\u003e,\\n \\\"sampler\\\": \\\"\u003c%- request.sampler %\u003e\\\",\\n \\\"steps\\\": \u003c%- request.steps %\u003e\\n}'\\n\\nresponse=$(curl --silent -i -w \\\"\\\\n%{http_code}\\\" --request POST \\\\\\n --url \\\"$invoke_url\\\" \\\\\\n --header \\\"$authorization_header\\\" \\\\\\n --header \\\"$accept_header\\\" \\\\\\n --header \\\"$content_type_header\\\" \\\\\\n --data \\\"$data\\\"\\n)\\n\\nhttp_code=$(echo \\\"$response\\\" | tail -n 1)\\n\\necho \\\"$response\\\" | awk '/{/,EOF-1'\\n\",\"node.js\":\"import fetch from \\\"node-fetch\\\";\\n\\nconst invokeUrl = \\\"https://ai.api.nvidia.com/v1/genai/stabilityai/sdxl-turbo\\\"\\n\\nconst headers = {\\n \\\"Authorization\\\": \\\"Bearer $NVIDIA_API_KEY\\\",\\n \\\"Accept\\\": \\\"application/json\\\",\\n}\\n\\nconst payload = {\\n \\\"text_prompts\\\": [{\\\"text\\\": \u003c%- JSON.stringify(request.prompt) %\u003e}],\\n \\\"seed\\\": \u003c%- request.seed %\u003e,\\n \\\"sampler\\\": \\\"\u003c%- request.sampler %\u003e\\\",\\n \\\"steps\\\": \u003c%- request.steps %\u003e\\n}\\n\\nlet response = await fetch(invokeUrl, {\\n method: \\\"post\\\",\\n body: JSON.stringify(payload),\\n headers: { \\\"Content-Type\\\": \\\"application/json\\\", ...headers }\\n});\\n\\nif (response.status != 200) {\\n let errBody = await (await response.blob()).text()\\n throw \\\"invocation failed with status \\\" + response.status + \\\" \\\" + errBody\\n}\\nlet response_body = await response.json()\\nconsole.log(JSON.stringify(response_body))\\n\",\"python\":\"import requests\\n\\ninvoke_url = \\\"https://ai.api.nvidia.com/v1/genai/stabilityai/sdxl-turbo\\\"\\n\\nheaders = {\\n \\\"Authorization\\\": \\\"Bearer $NVIDIA_API_KEY\\\",\\n \\\"Accept\\\": \\\"application/json\\\",\\n}\\n\\npayload = {\\n \\\"text_prompts\\\": [{\\\"text\\\": \u003c%- JSON.stringify(request.prompt) %\u003e}],\\n \\\"seed\\\": \u003c%- request.seed %\u003e,\\n \\\"sampler\\\": \\\"\u003c%- request.sampler %\u003e\\\",\\n \\\"steps\\\": \u003c%- request.steps %\u003e\\n}\\n\\nresponse = requests.post(invoke_url, headers=headers, json=payload)\\n\\nresponse.raise_for_status()\\nresponse_body = response.json()\\nprint(response_body)\\n\"},\"response\":\"{\\n \\\"artifacts\\\": [\\n {\\n \\\"base64\\\": \\\"...very long string...\\\",\\n \\\"finishReason\\\": \\\"SUCCESS\\\",\\n \\\"seed\\\": 1100106574\\n }\\n ]\\n}\\n\",\"title\":\"Example\"}]}}}},\"components\":{\"schemas\":{\"Artifact\":{\"properties\":{\"base64\":{\"description\":\"A base64-encoded string of the generated image (JPEG)\",\"examples\":[\"/9j/4AAQSkZ...b+AVZ/9k=\"],\"title\":\"Base64\",\"type\":\"string\"},\"finishReason\":{\"allOf\":[{\"$ref\":\"#/components/schemas/FinishReason\"}],\"description\":\"The result of the generation process. `SUCCESS` indicates success. `ERROR` indicates an error. `CONTENT_FILTERED` indicates the result affected by the content filter\"},\"seed\":{\"description\":\"The seed used during generation\",\"title\":\"Seed\",\"type\":\"integer\"}},\"required\":[\"base64\",\"finishReason\",\"seed\"],\"title\":\"Artifact\",\"type\":\"object\"},\"FinishReason\":{\"enum\":[\"CONTENT_FILTERED\",\"ERROR\",\"SUCCESS\"],\"title\":\"FinishReason\",\"type\":\"string\"},\"HTTPValidationError\":{\"properties\":{\"detail\":{\"items\":{\"$ref\":\"#/components/schemas/ValidationError\"},\"title\":\"Detail\",\"type\":\"array\"}},\"title\":\"HTTPValidationError\",\"type\":\"object\"},\"ImageRequest\":{\"additionalProperties\":false,\"properties\":{\"height\":{\"default\":512,\"description\":\"Height of the image to generate, in pixels. 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Only clip_guidance_preset=`NONE` is supported\",\"enum\":[\"NONE\"],\"title\":\"Clip Guidance Preset\",\"type\":\"string\"},\"sampler\":{\"default\":\"K_EULER_ANCESTRAL\",\"description\":\"The sampler to use for generation. Only sampler=`K_EULER_ANCESTRAL` is supported\",\"enum\":[\"K_EULER_ANCESTRAL\",\"K_DPM_2_ANCESTRAL\"],\"title\":\"Sampler\",\"type\":\"string\"},\"samples\":{\"default\":1,\"description\":\"Number of images to generate. Only samples=1 is supported\",\"maximum\":1,\"minimum\":1,\"title\":\"Samples\",\"type\":\"integer\"},\"seed\":{\"default\":0,\"description\":\"The seed which governs generation. Changing the seed with other inputs fixed results in different outputs. (Use 0 for a random seed)\",\"exclusiveMaximum\":4294967296,\"minimum\":0,\"title\":\"Seed\",\"type\":\"integer\"},\"steps\":{\"default\":4,\"description\":\"The number of diffusion steps applied to generate an output image.\",\"maximum\":4,\"minimum\":1,\"title\":\"Steps\",\"type\":\"integer\"},\"style_preset\":{\"default\":\"none\",\"description\":\"Pass in a style preset to guide the image model towards a particular style. This list of style presets is subject to change. style_preset=`none` is supported\",\"enum\":[\"none\"],\"title\":\"Style Preset\",\"type\":\"string\"}},\"required\":[\"text_prompts\"],\"title\":\"ImageRequest\",\"type\":\"object\"},\"ImageResponse\":{\"properties\":{\"artifacts\":{\"items\":{\"$ref\":\"#/components/schemas/Artifact\"},\"maxItems\":1,\"minItems\":1,\"title\":\"Artifacts\",\"type\":\"array\"}},\"required\":[\"artifacts\"],\"title\":\"ImageResponse\",\"type\":\"object\"},\"TextPrompt\":{\"additionalProperties\":false,\"properties\":{\"text\":{\"description\":\"The prompt itself\",\"examples\":[\"A photo of a Shiba Inu dog with a backpack riding a bike\"],\"title\":\"Text\",\"type\":\"string\"},\"weight\":{\"default\":1,\"description\":\"Weight of the prompt, only weight=1.0 is supported\",\"maximum\":1,\"minimum\":1,\"title\":\"Weight\",\"type\":\"number\"}},\"required\":[\"text\"],\"title\":\"TextPrompt\",\"type\":\"object\"},\"ValidationError\":{\"properties\":{\"loc\":{\"items\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"integer\"}]},\"title\":\"Location\",\"type\":\"array\"},\"msg\":{\"title\":\"Message\",\"type\":\"string\"},\"type\":{\"title\":\"Error Type\",\"type\":\"string\"}},\"required\":[\"loc\",\"msg\",\"type\"],\"title\":\"ValidationError\",\"type\":\"object\"}},\"securitySchemes\":{\"Token\":{\"type\":\"http\",\"scheme\":\"bearer\"}}},\"security\":[{\"Token\":[]}]},\"namespace\":\"qc69jvmznzxy\",\"updatedDate\":\"2024-11-15T20:31:46.468Z\",\"nvcfFunctionId\":\"f886140c-424e-4c82-a841-99e23f9ae35d\",\"createdDate\":\"2024-03-15T04:54:38.335Z\",\"attributes\":{\"requiresLogin\":false,\"showUnavailableBanner\":true,\"apiDocsUrl\":\"https://docs.api.nvidia.com/nim/reference/stabilityai-sdxl-turbo\",\"termsOfUse\":\"\u003cb\u003eGOVERNING TERMS\u003c/b\u003e: Your use of this API is governed by the \u003ca href=\\\"https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA API Trial Service Terms of Use\u003c/a\u003e; and the use of this model is governed by the \u003ca href=\\\"https://huggingface.co/stabilityai/sdxl-turbo/blob/main/LICENSE.TXT\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eStability AI Non-Commerical Research Community License\u003c/a\u003e.\\n\",\"playground\":{\"type\":\"custom\",\"input\":{\"items\":[{\"key\":\"prompt\",\"type\":\"text-area\",\"title\":\"Prompt\",\"description\":\"Enter a prompt to receive an AI-generated image.\",\"placeholder\":\"A steampunk dragon soaring over a Victorian cityscape, with gears and smoke billowing from its wings.\"}]},\"parameters\":{\"omitProperties\":[\"clip_guidance_preset\",\"style_preset\",\"height\",\"samples\",\"width\"]},\"output\":{\"flags\":\"{ \\\"isNSFW\\\": { \\\"condition\\\": \u003c%- response.artifacts[0].finishReason === \\\"CONTENT_FILTERED\\\" %\u003e, \\\"type\\\": \\\"ValidationError\\\", \\\"description\\\": \\\"provided input produces NSFW content\\\" } }\",\"items\":[{\"key\":\"artifacts[0].base64\",\"type\":\"image\",\"base64Format\":\"data:image/jpeg;base64,\"}]},\"requestBody\":\"{ \\\"text_prompts\\\":[{\\\"text\\\": \u003c%- JSON.stringify(request.prompt) %\u003e, \\\"weight\\\": 1}], \\\"seed\\\": \u003c%- request.seed %\u003e, \\\"steps\\\": \u003c%- request.steps %\u003e, \\\"sampler\\\": \\\"\u003c%- request.sampler %\u003e\\\" }\"},\"cta\":{\"text\":\"Apply to Self-Host\",\"url\":\"https://www.nvidia.com/en-us/ai/nim-notifyme/\"},\"maxRequests\":25},\"artifactName\":\"sdxl-turbo\"},\"config\":{\"name\":\"sdxl-turbo\",\"type\":\"model\"}},{\"endpoint\":{\"requestStatus\":{\"statusCode\":\"SUCCESS\",\"requestId\":\"ec568edf-b923-4e10-b28f-46506bc26be9\"},\"artifact\":{\"orgName\":\"qc69jvmznzxy\",\"labels\":[\"Chat\",\"Synthetic Data Generation\",\"Text-to-text\",\"Synthetic Data Generation\"],\"bias\":\"|Field:|Response:|\\n|:---:|:---:|\\n|Participation considerations from adversely impacted groups (protected classes) in model design and testing:|None|\\n|Measures taken to mitigate against unwanted bias:|None|\",\"logo\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/nemotron-4-340b-instruct.jpg\",\"shortDescription\":\"Creates diverse synthetic data that mimics the characteristics of real-world data.\",\"safetyAndSecurity\":\"|Field:|Response:|\\n|:---:|:---:|\\n|Model Application(s):|Chat, Instruction Following, Code Generation, Reasoning|\\n|Describe life critical application (if present):|None Known|\\n|Use Case Restrictions:|See [NVIDIA Open Model License](https://developer.download.nvidia.com/licenses/nvidia-open-model-license-agreement-june-2024.pdf).|\\n|Model and Dataset Restrictions:|The Principle of least privilege (PoLP) is applied limiting access for dataset generation. Restrictions enforce dataset access during training, and dataset license constraints adhered to. Model checkpoints are made available on Hugging Face and NGC, and may become available on cloud providers' model catalog.|\",\"privacy\":\"$5e\",\"isReadOnly\":true,\"description\":\"$5f\",\"canGuestDownload\":true,\"isPublic\":true,\"createdDate\":\"2024-06-17T16:47:10.063Z\",\"publisher\":\"nvidia\",\"displayName\":\"nemotron-4-340b-instruct\",\"name\":\"nemotron-4-340b-instruct\",\"explainability\":\"$60\",\"updatedDate\":\"2024-09-03T13:44:20.847Z\",\"attributes\":[{\"key\":\"AVAILABLE\",\"value\":\"false\"},{\"key\":\"PREVIEW\",\"value\":\"true\"}],\"artifactType\":\"ENDPOINT\"}},\"spec\":{\"openAPISpec\":{\"openapi\":\"3.1.0\",\"info\":{\"title\":\"NVIDIA NIM API for nvidia/nemotron-4-340b-instruct\",\"description\":\"The NVIDIA NIM REST API. Please see https://docs.api.nvidia.com/nim/reference/nvidia-nemotron-4-340b-instruct for more details.\",\"version\":\"1.0.0\",\"termsOfService\":\"https://www.nvidia.com/en-us/data-center/products/nvidia-ai-enterprise/eula/\",\"contact\":{\"name\":\"NVIDIA Enterprise Support\",\"url\":\"https://www.nvidia.com/en-us/support/enterprise/\"},\"license\":{\"name\":\"NVIDIA Open Model License\",\"url\":\"https://developer.download.nvidia.com/licenses/nvidia-open-model-license-agreement-june-2024.pdf\"}},\"servers\":[{\"url\":\"https://integrate.api.nvidia.com/v1/\"}],\"tags\":[{\"name\":\"NVCF API\",\"description\":\"Run inference on the model\"}],\"paths\":{\"/chat/completions\":{\"post\":{\"operationId\":\"create_chat_completion_v1_chat_completions_post\",\"tags\":[\"Chat\"],\"summary\":\"Creates a model response for the given chat conversation.\",\"description\":\"Given a list of messages comprising a conversation, the model will return a response. Compatible with OpenAI. See https://platform.openai.com/docs/api-reference/chat/create\",\"requestBody\":{\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ChatRequest\"}}},\"required\":true},\"responses\":{\"200\":{\"description\":\"Invocation is fulfilled\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ChatCompletion\"}},\"text/event-stream\":{\"schema\":{\"$ref\":\"#/components/schemas/ChatCompletionChunk\"}}}},\"202\":{\"description\":\"Result is pending. Client should poll using the requestId.\",\"content\":{\"application/json\":{\"example\":{},\"schema\":{}}},\"headers\":{\"NVCF-REQID\":{\"description\":\"requestId required for pooling\",\"schema\":{\"type\":\"string\",\"format\":\"uuid\"}},\"NVCF-STATUS\":{\"description\":\"Invocation status\",\"schema\":{\"type\":\"string\"}}}},\"422\":{\"description\":\"Validation failed, provided entity could not be processed.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/Errors\"},\"example\":{\"type\":\"urn:nvcf-worker-service:problem-details:unprocessable-entity\",\"title\":\"Unprocessable Entity\",\"status\":422,\"detail\":\"string\",\"instance\":\"/v2/nvcf/pexec/functions/b0fcd392-e905-4ab4-8eb9-aeae95c30b37\",\"requestId\":\"3fa85f64-5717-4562-b3fc-2c963f66afa6\"}}}},\"500\":{\"description\":\"The invocation ended with an error.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/Errors\"},\"example\":{\"type\":\"urn:nvcf-worker-service:problem-details:internal-server-error\",\"title\":\"Internal Server Error\",\"status\":500,\"detail\":\"string\",\"instance\":\"/v2/nvcf/pexec/functions/b0fcd392-e905-4ab4-8eb9-aeae95c30b37\",\"requestId\":\"3fa85f64-5717-4562-b3fc-2c963f66afa6\"}}}}},\"x-nvai-meta\":{\"name\":\"Create chat completion\",\"returns\":\"Returns a [chat completion](/docs/api-reference/chat/object) object, or a streamed sequence of [chat completion chunk](/docs/api-reference/chat/streaming) objects if the request is streamed.\\n\",\"path\":\"create\",\"examples\":[{\"name\":\"Write a limerick about the wonders of GPU computing.\",\"requestJson\":\"{\\n \\\"model\\\": \\\"nvidia/nemotron-4-340b-instruct\\\",\\n \\\"messages\\\": [\\n {\\n \\\"role\\\": \\\"user\\\",\\n \\\"content\\\": \\\"Write a limerick about the wonders of GPU computing.\\\"\\n }\\n ],\\n \\\"top_p\\\": 0.7,\\n \\\"max_tokens\\\": 1024,\\n \\\"seed\\\": 42,\\n \\\"stream\\\": true\\n}\\n\",\"responseJson\":\"{\\n \\\"id\\\": \\\"b1e5349d-9011-44e7-afe7-cf48a74e27e5\\\",\\n \\\"object\\\": \\\"chat.completion\\\",\\n \\\"created\\\": 1677652288,\\n \\\"model\\\": \\\"nvidia/nemotron-4-340b-instruct\\\",\\n \\\"system_fingerprint\\\": \\\"fp_44709d6fcb\\\",\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"The python functions...\\\"\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 21,\\n \\\"completion_tokens\\\": 318,\\n \\\"total_tokens\\\": 339\\n }\\n}\\n\"},{\"name\":\"What can I see at NVIDIA's GPU Technology Conference?\",\"requestJson\":\"{\\n \\\"model\\\": \\\"nvidia/nemotron-4-340b-instruct\\\",\\n \\\"messages\\\": [\\n {\\n \\\"role\\\": \\\"user\\\",\\n \\\"content\\\": \\\"What can I see at NVIDIA's GPU Technology Conference?\\\"\\n }\\n ],\\n \\\"top_p\\\": 0.7,\\n \\\"max_tokens\\\": 1024,\\n \\\"seed\\\": 42,\\n \\\"stream\\\": true\\n}\\n\",\"responseJson\":\"{\\n \\\"id\\\": \\\"c0918f93-d1f8-4cd4-8eb8-7b0b982b6086\\\",\\n \\\"object\\\": \\\"chat.completion\\\",\\n \\\"created\\\": 1677652288,\\n \\\"model\\\": \\\"nvidia/nemotron-4-340b-instruct\\\",\\n \\\"system_fingerprint\\\": \\\"fp_44709d6fcb\\\",\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"At NVIDIA's GPU Technology Conference (GTC)...\\\"\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 19,\\n \\\"completion_tokens\\\": 270,\\n \\\"total_tokens\\\": 289\\n }\\n}\\n\"}],\"templates\":[{\"title\":\"No Streaming\",\"requestEjs\":{\"python\":\"from openai import OpenAI\\n\\nclient = OpenAI(\\n base_url = \\\"https://integrate.api.nvidia.com/v1\\\",\\n api_key = \\\"$NVIDIA_API_KEY\\\"\\n)\\n\\ncompletion = client.chat.completions.create(\\n model=\\\"\u003c%- request.model %\u003e\\\",\\n messages=\u003c%- JSON.stringify(request.messages) %\u003e,\\n temperature=\u003c%- request.temperature %\u003e,\\n top_p=\u003c%- request.top_p %\u003e,\\n max_tokens=\u003c%- request.max_tokens %\u003e,\\n stream=\u003c%- request.stream?.toString()[0].toUpperCase() + request.stream?.toString().slice(1) %\u003e\\n)\\n\u003c% if (request.stream) { %\u003e\\nfor chunk in completion:\\n if chunk.choices[0].delta.content is not None:\\n print(chunk.choices[0].delta.content, end=\\\"\\\")\\n\u003c% } else { %\u003e\\nprint(completion.choices[0].message)\\n\u003c% } %\u003e\\n\",\"langChain\":\"from langchain_nvidia_ai_endpoints import ChatNVIDIA\\n\\nclient = ChatNVIDIA(\\n model=\\\"\u003c%- request.model %\u003e\\\",\\n api_key=\\\"$NVIDIA_API_KEY\\\", \\n temperature=\u003c%- request.temperature %\u003e,\\n top_p=\u003c%- request.top_p %\u003e,\\n max_tokens=\u003c%- request.max_tokens %\u003e,\\n)\\n\u003c% if (request.stream) { %\u003e\\nfor chunk in client.stream(\u003c%- JSON.stringify(request.messages) %\u003e): \\n print(chunk.content, end=\\\"\\\")\\n\u003c% } else { %\u003e\\nresponse = client.invoke(\u003c%- JSON.stringify(request.messages) %\u003e)\\nprint(response.content)\\n\u003c% } %\u003e\\n\",\"node.js\":\"import OpenAI from 'openai';\\n\\nconst openai = new OpenAI({\\n apiKey: '$NVIDIA_API_KEY',\\n baseURL: 'https://integrate.api.nvidia.com/v1',\\n})\\n\\nasync function main() {\\n const completion = await openai.chat.completions.create({\\n model: \\\"\u003c%- request.model %\u003e\\\",\\n messages: \u003c%- JSON.stringify(request.messages) %\u003e,\\n temperature: \u003c%- request.temperature %\u003e,\\n top_p: \u003c%- request.top_p %\u003e,\\n max_tokens: \u003c%- request.max_tokens %\u003e,\\n stream: \u003c%- request.stream %\u003e,\\n })\\n \u003c% if (request.stream) { %\u003e\\n for await (const chunk of completion) {\\n process.stdout.write(chunk.choices[0]?.delta?.content || '')\\n }\\n \u003c% } else { %\u003e\\n process.stdout.write(completion.choices[0]?.message?.content);\\n \u003c% } %\u003e\\n}\\n\\nmain();\",\"curl\":\"curl https://integrate.api.nvidia.com/v1/chat/completions \\\\\\n -H \\\"Content-Type: application/json\\\" \\\\\\n -H \\\"Authorization: Bearer $NVIDIA_API_KEY\\\" \\\\\\n -d '{\\n \\\"model\\\": \\\"nvidia/nemotron-4-340b-instruct\\\",\\n \\\"messages\\\": \u003c%- JSON.stringify(request.messages).replaceAll(\\\"'\\\", \\\"'\\\\\\\"'\\\\\\\"'\\\") %\u003e,\\n \\\"temperature\\\": \u003c%- request.temperature %\u003e, \\n \\\"top_p\\\": \u003c%- request.top_p %\u003e,\\n \\\"max_tokens\\\": \u003c%- request.max_tokens %\u003e,\\n \\\"stream\\\": \u003c%- request.stream %\u003e \\n }'\\n\"},\"response\":\"{\\n \\\"id\\\": \\\"chatcmpl-123\\\",\\n \\\"object\\\": \\\"chat.completion\\\",\\n \\\"created\\\": 1677652288,\\n \\\"model\\\": \\\"nvidia/nemotron-4-340b-instruct\\\",\\n \\\"system_fingerprint\\\": \\\"fp_44709d6fcb\\\",\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"\\\\n\\\\nHello there, how may I assist you today?\\\",\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 9,\\n \\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"}]}}}},\"security\":[{\"Token\":[]}],\"components\":{\"securitySchemes\":{\"Token\":{\"type\":\"http\",\"scheme\":\"bearer\"}},\"schemas\":{\"Errors\":{\"properties\":{\"type\":{\"type\":\"string\",\"description\":\"Error type\"},\"title\":{\"type\":\"string\",\"description\":\"Error title\"},\"status\":{\"type\":\"integer\",\"description\":\"Error status code\"},\"detail\":{\"type\":\"string\",\"description\":\"Detailed information about the error\"},\"instance\":{\"type\":\"string\",\"description\":\"Function instance used to invoke the request\"},\"requestId\":{\"type\":\"string\",\"format\":\"uuid\",\"description\":\"UUID of the request\"}},\"type\":\"object\",\"required\":[\"type\",\"title\",\"status\",\"detail\",\"instance\",\"requestId\"],\"title\":\"InvokeError\"},\"ChatCompletion\":{\"properties\":{\"id\":{\"description\":\"A unique identifier for the completion.\",\"format\":\"uuid\",\"title\":\"Id\",\"type\":\"string\"},\"choices\":{\"description\":\"The list of completion choices the model generated for the input prompt.\",\"items\":{\"$ref\":\"#/components/schemas/Choice\"},\"title\":\"Choices\",\"type\":\"array\"},\"usage\":{\"allOf\":[{\"$ref\":\"#/components/schemas/Usage\"}],\"description\":\"Usage statistics for the completion request.\"}},\"required\":[\"id\",\"choices\",\"usage\"],\"title\":\"ChatCompletion\",\"type\":\"object\"},\"ChatCompletionChunk\":{\"properties\":{\"id\":{\"description\":\"A unique identifier for the completion.\",\"format\":\"uuid\",\"title\":\"Id\",\"type\":\"string\"},\"choices\":{\"description\":\"The list of completion choices the model generated for the input prompt.\",\"items\":{\"$ref\":\"#/components/schemas/ChoiceChunk\"},\"title\":\"Choices\",\"type\":\"array\"}},\"required\":[\"id\",\"choices\"],\"title\":\"ChatCompletionChunk\",\"type\":\"object\"},\"ChatRequest\":{\"additionalProperties\":false,\"properties\":{\"model\":{\"type\":\"string\",\"title\":\"Model\",\"default\":\"nvidia/nemotron-4-340b-instruct\"},\"messages\":{\"description\":\"A list of messages comprising the conversation so far. The roles of the messages must be alternating between `user` and `assistant`. The last input message should have role `user`. A message with the the `system` role is optional, and must be the very first message if it is present; `context` is also optional, but must come before a user question.\",\"examples\":[[{\"content\":\"Write a hello world program.\",\"role\":\"user\"}]],\"items\":{\"$ref\":\"#/components/schemas/Message\"},\"title\":\"Messages\",\"type\":\"array\"},\"temperature\":{\"default\":0.2,\"description\":\"The sampling temperature to use for text generation. The higher the temperature value is, the less deterministic the output text will be. It is not recommended to modify both temperature and top_p in the same call.\",\"maximum\":1,\"minimum\":0.000001,\"title\":\"Temperature\",\"type\":\"number\"},\"top_p\":{\"default\":0.7,\"description\":\"The top-p sampling mass used for text generation. The top-p value determines the probability mass that is sampled at sampling time. For example, if top_p = 0.2, only the most likely tokens (summing to 0.2 cumulative probability) will be sampled. It is not recommended to modify both temperature and top_p in the same call.\",\"maximum\":1,\"minimum\":0,\"title\":\"Top P\",\"type\":\"number\"},\"max_tokens\":{\"default\":1024,\"description\":\"The maximum number of tokens to generate in any given call. Note that the model is not aware of this value, and generation will simply stop at the number of tokens specified.\",\"maximum\":2048,\"minimum\":1,\"title\":\"Max Tokens\",\"type\":\"integer\"},\"stream\":{\"default\":false,\"description\":\"If set, partial message deltas will be sent. Tokens will be sent as data-only server-sent events (SSE) as they become available (JSON responses are prefixed by `data: `), with the stream terminated by a `data: [DONE]` message.\",\"title\":\"Stream\",\"type\":\"boolean\"}},\"required\":[\"messages\"],\"title\":\"ChatRequest\",\"type\":\"object\"},\"Choice\":{\"properties\":{\"index\":{\"description\":\"The index of the choice in the list of choices (always 0).\",\"title\":\"Index\",\"type\":\"integer\"},\"message\":{\"allOf\":[{\"$ref\":\"#/components/schemas/Message\"}],\"description\":\"A chat completion message generated by the model.\",\"examples\":[{\"content\":\"def hello_world():\\\\n\\\\tprint('Hello world!')\\\\n\\\\treturn\",\"role\":\"assistant\"}]},\"finish_reason\":{\"anyOf\":[{\"enum\":[\"stop\",\"length\"],\"type\":\"string\"},{\"type\":\"null\"}],\"default\":null,\"description\":\"The reason the model stopped generating tokens. This will be `stop` if the model hit a natural stop point or a provided stop sequence, or `length` if the maximum number of tokens specified in the request was reached.\",\"examples\":[\"stop\"],\"title\":\"Finish Reason\"}},\"required\":[\"index\",\"message\"],\"title\":\"Choice\",\"type\":\"object\"},\"ChoiceChunk\":{\"properties\":{\"index\":{\"description\":\"The index of the choice in the list of choices (always 0).\",\"title\":\"Index\",\"type\":\"integer\"},\"delta\":{\"allOf\":[{\"$ref\":\"#/components/schemas/Message\"}],\"description\":\"A chat completion delta generated by streamed model responses.\",\"examples\":[{\"content\":\"def\",\"role\":\"assistant\"}]},\"finish_reason\":{\"anyOf\":[{\"enum\":[\"stop\",\"length\"],\"type\":\"string\"},{\"type\":\"null\"}],\"default\":null,\"description\":\"The reason the model stopped generating tokens. This will be `stop` if the model hit a natural stop point or a provided stop sequence, or `length` if the maximum number of tokens specified in the request was reached. Will be `null` if the model has not finished generating.\",\"title\":\"Finish Reason\"}},\"required\":[\"index\",\"delta\"],\"title\":\"ChoiceChunk\",\"type\":\"object\"},\"Message\":{\"additionalProperties\":false,\"properties\":{\"role\":{\"description\":\"The role of the message author.\",\"enum\":[\"system\",\"context\",\"user\",\"assistant\"],\"title\":\"Role\",\"type\":\"string\"},\"content\":{\"description\":\"The contents of the message.\",\"title\":\"Content\",\"type\":\"string\"}},\"required\":[\"role\",\"content\"],\"title\":\"Message\",\"type\":\"object\"},\"Usage\":{\"properties\":{\"completion_tokens\":{\"description\":\"Number of tokens in the generated completion.\",\"examples\":[25],\"title\":\"Completion Tokens\",\"type\":\"integer\"},\"prompt_tokens\":{\"description\":\"Number of tokens in the prompt.\",\"examples\":[9],\"title\":\"Prompt Tokens\",\"type\":\"integer\"},\"total_tokens\":{\"description\":\"Total number of tokens used in the request (prompt + completion).\",\"examples\":[34],\"title\":\"Total Tokens\",\"type\":\"integer\"}},\"required\":[\"completion_tokens\",\"prompt_tokens\",\"total_tokens\"],\"title\":\"Usage\",\"type\":\"object\"}}}},\"namespace\":\"qc69jvmznzxy\",\"updatedDate\":\"2024-09-03T13:44:21.466Z\",\"nvcfFunctionId\":\"b0fcd392-e905-4ab4-8eb9-aeae95c30b37\",\"createdDate\":\"2024-06-17T16:47:10.451Z\",\"attributes\":{\"showUnavailableBanner\":false,\"apiDocsUrl\":\"https://docs.api.nvidia.com/nim/reference/nvidia-nemotron-4-340b-instruct\",\"playground\":{\"type\":\"chat\"},\"termsOfUse\":\"\u003cb\u003eGOVERNING TERMS\u003c/b\u003e: The trial service is governed by the \u003ca href=\\\"https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA API Service Agreement\u003c/a\u003e; and the use of this model is governed by the \u003ca href=\\\"https://developer.download.nvidia.com/licenses/nvidia-open-model-license-agreement-june-2024.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA Open Model License\u003c/a\u003e.\\n\",\"cta\":{\"text\":\"Run Anywhere - Notify Me\",\"url\":\"https://www.nvidia.com/en-us/ai/nim-notifyme/\"},\"projects\":[{\"name\":\"Build a Customizable Hybrid RAG Chatbot\",\"url\":\"https://github.com/NVIDIA/workbench-example-hybrid-rag\",\"imageUrl\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/github-logo.jpg\",\"workbench\":true}]},\"artifactName\":\"nemotron-4-340b-instruct\"},\"config\":{\"name\":\"nemotron-4-340b-instruct\",\"type\":\"model\"}},{\"endpoint\":{\"requestStatus\":{\"statusCode\":\"SUCCESS\",\"requestId\":\"1b18a71b-04b0-430f-a1f7-73905fe912de\"},\"artifact\":{\"orgName\":\"qc69jvmznzxy\",\"labels\":[\"Chat\",\"Language Generation\",\"Text-to-Text\",\"Code Generation\"],\"logo\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/gemma-2-9b-it.jpg\",\"shortDescription\":\"Cutting-edge text generation model text understanding, transformation, and code generation.\",\"isReadOnly\":true,\"description\":\"$61\",\"canGuestDownload\":true,\"isPublic\":true,\"createdDate\":\"2024-06-27T15:59:32.016Z\",\"publisher\":\"google\",\"displayName\":\"gemma-2-9b-it\",\"name\":\"gemma-2-9b-it\",\"updatedDate\":\"2024-11-18T22:33:27.085Z\",\"attributes\":[{\"key\":\"PREVIEW\",\"value\":\"true\"}],\"artifactType\":\"ENDPOINT\"}},\"spec\":{\"openAPISpec\":{\"openapi\":\"3.1.0\",\"info\":{\"title\":\"NVIDIA NIM API for google/gemma-2-9b-it\",\"description\":\"The NVIDIA NIM REST API. Please see https://docs.api.nvidia.com/nim/reference/google-gemma-2-9b-it for more details.\",\"version\":\"1.0.0\",\"termsOfService\":\"https://www.nvidia.com/en-us/data-center/products/nvidia-ai-enterprise/eula/\",\"contact\":{\"name\":\"NVIDIA Enterprise Support\",\"url\":\"https://www.nvidia.com/en-us/support/enterprise/\"},\"license\":{\"name\":\"Gemma Terms of Use\",\"url\":\"https://ai.google.dev/gemma/terms\"}},\"servers\":[{\"url\":\"https://integrate.api.nvidia.com/v1/\"}],\"tags\":[{\"name\":\"NVCF API\",\"description\":\"Run inference on the model\"}],\"paths\":{\"/chat/completions\":{\"post\":{\"operationId\":\"create_chat_completion_v1_chat_completions_post\",\"tags\":[\"Chat\"],\"summary\":\"Creates a model response for the given chat conversation.\",\"description\":\"Given a list of messages comprising a conversation, the model will return a response. Compatible with OpenAI. See https://platform.openai.com/docs/api-reference/chat/create\",\"requestBody\":{\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ChatRequest\"}}},\"required\":true},\"responses\":{\"200\":{\"description\":\"Invocation is fulfilled\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ChatCompletion\"}},\"text/event-stream\":{\"schema\":{\"$ref\":\"#/components/schemas/ChatCompletionChunk\"}}}},\"202\":{\"description\":\"Result is pending. Client should poll using the requestId.\\n\",\"content\":{\"application/json\":{\"example\":{},\"schema\":{}}},\"headers\":{\"NVCF-REQID\":{\"description\":\"requestId required for pooling\",\"schema\":{\"type\":\"string\",\"format\":\"uuid\"}},\"NVCF-STATUS\":{\"description\":\"Invocation status\",\"schema\":{\"type\":\"string\"}}}},\"422\":{\"description\":\"Validation failed, provided entity could not be processed.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/Errors\"},\"example\":{\"type\":\"urn:nvcf-worker-service:problem-details:unprocessable-entity\",\"title\":\"Unprocessable Entity\",\"status\":422,\"detail\":\"string\",\"instance\":\"/v2/nvcf/pexec/functions/4a58c6cb-a9b4-4014-99de-3e704d4ae687\",\"requestId\":\"3fa85f64-5717-4562-b3fc-2c963f66afa6\"}}}},\"500\":{\"description\":\"The invocation ended with an error.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/Errors\"},\"example\":{\"type\":\"urn:nvcf-worker-service:problem-details:internal-server-error\",\"title\":\"Internal Server Error\",\"status\":500,\"detail\":\"string\",\"instance\":\"/v2/nvcf/pexec/functions/4a58c6cb-a9b4-4014-99de-3e704d4ae687\",\"requestId\":\"3fa85f64-5717-4562-b3fc-2c963f66afa6\"}}}}},\"x-nvai-meta\":{\"name\":\"Create chat completion\",\"returns\":\"Returns a [chat completion](/docs/api-reference/chat/object) object, or a streamed sequence of [chat completion chunk](/docs/api-reference/chat/streaming) objects if the request is streamed.\\n\",\"path\":\"create\",\"examples\":[{\"name\":\"Write a limerick about the wonders of GPU computing.\",\"requestJson\":\"{\\n \\\"model\\\": \\\"google/gemma-2-9b-it\\\",\\n \\\"messages\\\": [\\n {\\n \\\"role\\\": \\\"user\\\",\\n \\\"content\\\": \\\"There once was a GPU ...\\\"\\n }\\n ],\\n \\\"top_p\\\": 0.7,\\n \\\"max_tokens\\\": 1024,\\n \\\"seed\\\": 42,\\n \\\"stream\\\": true\\n}\\n\",\"responseJson\":\"{\\n \\\"id\\\": \\\"id-123\\\",\\n \\\"object\\\": \\\"chat.completion\\\",\\n \\\"created\\\": 1677652288,\\n \\\"model\\\": \\\"google/gemma-2-9b-it\\\",\\n \\\"system_fingerprint\\\": \\\"fp_44709d6fcb\\\",\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"The python functions...\\\"\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 9,\\n \\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"},{\"name\":\"What can I see at NVIDIA's GPU Technology Conference?\",\"requestJson\":\"{\\n \\\"model\\\": \\\"google/gemma-2-9b-it\\\",\\n \\\"messages\\\": [\\n {\\n \\\"role\\\": \\\"user\\\",\\n \\\"content\\\": \\\"At NVIDIA's GPU Technology Conference (GTC)...\\\"\\n }\\n ],\\n \\\"top_p\\\": 0.7,\\n \\\"max_tokens\\\": 1024,\\n \\\"seed\\\": 42,\\n \\\"stream\\\": true\\n}\\n\",\"responseJson\":\"{\\n \\\"id\\\": \\\"id-123\\\",\\n \\\"object\\\": \\\"chat.completion\\\",\\n \\\"created\\\": 1677652288,\\n \\\"model\\\": \\\"google/gemma-2-9b-it\\\",\\n \\\"system_fingerprint\\\": \\\"fp_44709d6fcb\\\",\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"At NVIDIA's GPU Technology Conference (GTC)...\\\"\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 9,\\n \\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"}],\"templates\":[{\"title\":\"No Streaming\",\"requestEjs\":{\"python\":\"from openai import OpenAI\\n\\nclient = OpenAI(\\n base_url = \\\"https://integrate.api.nvidia.com/v1\\\",\\n api_key = \\\"$NVIDIA_API_KEY\\\"\\n)\\n\\ncompletion = client.chat.completions.create(\\n model=\\\"\u003c%- request.model %\u003e\\\",\\n messages=\u003c%- JSON.stringify(request.messages) %\u003e,\\n temperature=\u003c%- request.temperature %\u003e,\\n top_p=\u003c%- request.top_p %\u003e,\\n max_tokens=\u003c%- request.max_tokens %\u003e,\\n stream=\u003c%- request.stream?.toString()[0].toUpperCase() + request.stream?.toString().slice(1) %\u003e\\n)\\n\u003c% if (request.stream) { %\u003e\\nfor chunk in completion:\\n if chunk.choices[0].delta.content is not None:\\n print(chunk.choices[0].delta.content, end=\\\"\\\")\\n\u003c% } else { %\u003e\\nprint(completion.choices[0].message)\\n\u003c% } %\u003e\\n\",\"langChain\":\"from langchain_nvidia_ai_endpoints import ChatNVIDIA\\n\\nclient = ChatNVIDIA(\\n model=\\\"\u003c%- request.model %\u003e\\\",\\n api_key=\\\"$NVIDIA_API_KEY\\\", \\n temperature=\u003c%- request.temperature %\u003e,\\n top_p=\u003c%- request.top_p %\u003e,\\n max_tokens=\u003c%- request.max_tokens %\u003e,\\n)\\n\u003c% if (request.stream) { %\u003e\\nfor chunk in client.stream(\u003c%- JSON.stringify(request.messages) %\u003e): \\n print(chunk.content, end=\\\"\\\")\\n\u003c% } else { %\u003e\\nresponse = client.invoke(\u003c%- JSON.stringify(request.messages) %\u003e)\\nprint(response.content)\\n\u003c% } %\u003e\\n\",\"node.js\":\"import OpenAI from 'openai';\\n\\nconst openai = new OpenAI({\\n apiKey: '$NVIDIA_API_KEY',\\n baseURL: 'https://integrate.api.nvidia.com/v1',\\n})\\n\\nasync function main() {\\n const completion = await openai.chat.completions.create({\\n model: \\\"\u003c%- request.model %\u003e\\\",\\n messages: \u003c%- JSON.stringify(request.messages) %\u003e,\\n temperature: \u003c%- request.temperature %\u003e,\\n top_p: \u003c%- request.top_p %\u003e,\\n max_tokens: \u003c%- request.max_tokens %\u003e,\\n stream: \u003c%- request.stream %\u003e,\\n })\\n \u003c% if (request.stream) { %\u003e\\n for await (const chunk of completion) {\\n process.stdout.write(chunk.choices[0]?.delta?.content || '')\\n }\\n \u003c% } else { %\u003e\\n process.stdout.write(completion.choices[0]?.message?.content);\\n \u003c% } %\u003e\\n}\\n\\nmain();\",\"curl\":\"curl https://integrate.api.nvidia.com/v1/chat/completions \\\\\\n -H \\\"Content-Type: application/json\\\" \\\\\\n -H \\\"Authorization: Bearer $NVIDIA_API_KEY\\\" \\\\\\n -d '{\\n \\\"model\\\": \\\"google/gemma-2-9b-it\\\",\\n \\\"messages\\\": \u003c%- JSON.stringify(request.messages).replaceAll(\\\"'\\\", \\\"'\\\\\\\"'\\\\\\\"'\\\") %\u003e,\\n \\\"temperature\\\": \u003c%- request.temperature %\u003e, \\n \\\"top_p\\\": \u003c%- request.top_p %\u003e,\\n \\\"max_tokens\\\": \u003c%- request.max_tokens %\u003e,\\n \\\"stream\\\": \u003c%- request.stream %\u003e \\n }'\\n\"},\"response\":\"{\\n \\\"id\\\": \\\"chatcmpl-123\\\",\\n \\\"object\\\": \\\"chat.completion\\\",\\n \\\"created\\\": 1677652288,\\n \\\"model\\\": \\\"google/gemma-2-9b-it\\\",\\n \\\"system_fingerprint\\\": \\\"fp_44709d6fcb\\\",\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"\\\\n\\\\nHello there, how may I assist you today?\\\",\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 9,\\n \\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"}]}}}},\"security\":[{\"Token\":[]}],\"components\":{\"securitySchemes\":{\"Token\":{\"type\":\"http\",\"scheme\":\"bearer\"}},\"schemas\":{\"Errors\":{\"properties\":{\"type\":{\"type\":\"string\",\"description\":\"Error type\"},\"title\":{\"type\":\"string\",\"description\":\"Error title\"},\"status\":{\"type\":\"integer\",\"description\":\"Error status code\"},\"detail\":{\"type\":\"string\",\"description\":\"Detailed information about the error\"},\"instance\":{\"type\":\"string\",\"description\":\"Function instance used to invoke the request\"},\"requestId\":{\"type\":\"string\",\"format\":\"uuid\",\"description\":\"UUID of the request\"}},\"type\":\"object\",\"required\":[\"type\",\"title\",\"status\",\"detail\",\"instance\",\"requestId\"],\"title\":\"InvokeError\"},\"ChatCompletion\":{\"properties\":{\"id\":{\"description\":\"A unique identifier for the completion.\",\"format\":\"uuid\",\"title\":\"Id\",\"type\":\"string\"},\"choices\":{\"description\":\"The list of completion choices the model generated for the input prompt.\",\"items\":{\"$ref\":\"#/components/schemas/Choice\"},\"title\":\"Choices\",\"type\":\"array\"},\"usage\":{\"allOf\":[{\"$ref\":\"#/components/schemas/Usage\"}],\"description\":\"Usage statistics for the completion request.\"}},\"required\":[\"id\",\"choices\",\"usage\"],\"title\":\"ChatCompletion\",\"type\":\"object\"},\"ChatCompletionChunk\":{\"properties\":{\"id\":{\"description\":\"A unique identifier for the completion.\",\"format\":\"uuid\",\"title\":\"Id\",\"type\":\"string\"},\"choices\":{\"description\":\"The list of completion choices the model generated for the input prompt.\",\"items\":{\"$ref\":\"#/components/schemas/ChoiceChunk\"},\"title\":\"Choices\",\"type\":\"array\"}},\"required\":[\"id\",\"choices\"],\"title\":\"ChatCompletionChunk\",\"type\":\"object\"},\"ChatRequest\":{\"additionalProperties\":false,\"properties\":{\"model\":{\"type\":\"string\",\"title\":\"Model\",\"default\":\"google/gemma-2-9b-it\"},\"messages\":{\"description\":\"A list of messages comprising the conversation so far. The roles of the messages must be alternating between `user` and `assistant`. The last input message should have role `user`. A message with the the `system` role is optional, and must be the very first message if it is present; `context` is also optional, but must come before a user question.\",\"examples\":[[{\"content\":\"I am going to Paris, what should I see?\",\"role\":\"user\"}]],\"items\":{\"$ref\":\"#/components/schemas/Message\"},\"title\":\"Messages\",\"type\":\"array\"},\"temperature\":{\"default\":0.2,\"description\":\"The sampling temperature to use for text generation. The higher the temperature value is, the less deterministic the output text will be. It is not recommended to modify both temperature and top_p in the same call.\",\"maximum\":1,\"exclusiveMinimum\":0,\"title\":\"Temperature\",\"type\":\"number\"},\"top_p\":{\"default\":0.7,\"description\":\"The top-p sampling mass used for text generation. The top-p value determines the probability mass that is sampled at sampling time. For example, if top_p = 0.2, only the most likely tokens (summing to 0.2 cumulative probability) will be sampled. It is not recommended to modify both temperature and top_p in the same call.\",\"maximum\":1,\"exclusiveMinimum\":0,\"title\":\"Top P\",\"type\":\"number\"},\"max_tokens\":{\"default\":1024,\"description\":\"The maximum number of tokens to generate in any given call. Note that the model is not aware of this value, and generation will simply stop at the number of tokens specified.\",\"maximum\":4096,\"minimum\":1,\"title\":\"Max Tokens\",\"type\":\"integer\"},\"seed\":{\"anyOf\":[{\"maximum\":18446744073709552000,\"minimum\":0,\"type\":\"integer\"},{\"type\":\"null\"}],\"default\":null,\"description\":\"If specified, our system will make a best effort to sample deterministically, such that repeated requests with the same seed and parameters should return the same result.\",\"examples\":[42],\"title\":\"Seed\"},\"stream\":{\"default\":false,\"description\":\"If set, partial message deltas will be sent. Tokens will be sent as data-only server-sent events (SSE) as they become available (JSON responses are prefixed by `data: `), with the stream terminated by a `data: [DONE]` message.\",\"title\":\"Stream\",\"type\":\"boolean\"},\"stop\":{\"anyOf\":[{\"items\":{\"type\":\"string\"},\"type\":\"array\"},{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Stop\",\"description\":\"A string or a list of strings where the API will stop generating further tokens. The returned text will not contain the stop sequence.\"},\"bad\":{\"anyOf\":[{\"items\":{\"type\":\"string\"},\"type\":\"array\"},{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Bad\",\"description\":\"A word or list of words not to use. The words are case sensistive.\"}},\"required\":[\"messages\"],\"title\":\"ChatRequest\",\"type\":\"object\"},\"Choice\":{\"properties\":{\"index\":{\"description\":\"The index of the choice in the list of choices (always 0).\",\"title\":\"Index\",\"type\":\"integer\"},\"message\":{\"allOf\":[{\"$ref\":\"#/components/schemas/Message\"}],\"description\":\"A chat completion message generated by the model.\",\"examples\":[{\"content\":\"Ah, Paris, the City of Light! There are so many amazing things to see and do in this beautiful city ...\",\"role\":\"assistant\"}]},\"finish_reason\":{\"anyOf\":[{\"enum\":[\"stop\",\"length\"],\"type\":\"string\"},{\"type\":\"null\"}],\"default\":null,\"description\":\"The reason the model stopped generating tokens. This will be `stop` if the model hit a natural stop point or a provided stop sequence, or `length` if the maximum number of tokens specified in the request was reached.\",\"examples\":[\"stop\"],\"title\":\"Finish Reason\"}},\"required\":[\"index\",\"message\"],\"title\":\"Choice\",\"type\":\"object\"},\"ChoiceChunk\":{\"properties\":{\"index\":{\"description\":\"The index of the choice in the list of choices (always 0).\",\"title\":\"Index\",\"type\":\"integer\"},\"delta\":{\"allOf\":[{\"$ref\":\"#/components/schemas/Message\"}],\"description\":\"A chat completion delta generated by streamed model responses.\",\"examples\":[{\"content\":\"Ah,\",\"role\":\"assistant\"}]},\"finish_reason\":{\"anyOf\":[{\"enum\":[\"stop\",\"length\"],\"type\":\"string\"},{\"type\":\"null\"}],\"default\":null,\"description\":\"The reason the model stopped generating tokens. This will be `stop` if the model hit a natural stop point or a provided stop sequence, or `length` if the maximum number of tokens specified in the request was reached. Will be `null` if the model has not finished generating.\",\"title\":\"Finish Reason\"}},\"required\":[\"index\",\"delta\"],\"title\":\"ChoiceChunk\",\"type\":\"object\"},\"Message\":{\"additionalProperties\":false,\"properties\":{\"role\":{\"description\":\"The role of the message author.\",\"enum\":[\"system\",\"context\",\"user\",\"assistant\"],\"title\":\"Role\",\"type\":\"string\"},\"content\":{\"description\":\"The contents of the message.\",\"title\":\"Content\",\"type\":\"string\"}},\"required\":[\"role\",\"content\"],\"title\":\"Message\",\"type\":\"object\"},\"Usage\":{\"properties\":{\"completion_tokens\":{\"description\":\"Number of tokens in the generated completion.\",\"examples\":[25],\"title\":\"Completion Tokens\",\"type\":\"integer\"},\"prompt_tokens\":{\"description\":\"Number of tokens in the prompt.\",\"examples\":[9],\"title\":\"Prompt Tokens\",\"type\":\"integer\"},\"total_tokens\":{\"description\":\"Total number of tokens used in the request (prompt + completion).\",\"examples\":[34],\"title\":\"Total Tokens\",\"type\":\"integer\"}},\"required\":[\"completion_tokens\",\"prompt_tokens\",\"total_tokens\"],\"title\":\"Usage\",\"type\":\"object\"}}}},\"namespace\":\"qc69jvmznzxy\",\"updatedDate\":\"2024-11-18T22:33:27.720Z\",\"nvcfFunctionId\":\"1136f83f-7706-49f3-970b-67499c26724e\",\"createdDate\":\"2024-06-27T15:59:33.072Z\",\"attributes\":{\"showUnavailableBanner\":false,\"apiDocsUrl\":\"https://docs.api.nvidia.com/nim/reference/google-gemma-2-9b-it\",\"playground\":{\"type\":\"chat\"},\"termsOfUse\":\"\u003cb\u003eGOVERNING TERMS\u003c/b\u003e: Your use of this API is governed by the \u003ca href=\\\"https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA API Trial Service Terms of Use\u003c/a\u003e; and the use of this model is governed by the \u003ca href=\\\"https://docs.nvidia.com/ai-foundation-models-community-license.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA AI Foundation Models Community License\u003c/a\u003e, \u003ca href=\\\"https://ai.google.dev/gemma/terms\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eGemma Terms of Use\u003c/a\u003e and \u003ca href=\\\"https://ai.google.dev/gemma/prohibited_use_policy\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eGemma Prohibited Use Policy\u003c/a\u003e.\\n\",\"cta\":{\"text\":\"Run Anywhere - Notify Me\",\"url\":\"https://www.nvidia.com/en-us/ai/nim-notifyme/\"}},\"artifactName\":\"gemma-2-9b-it\"},\"config\":{\"name\":\"gemma-2-9b-it\",\"type\":\"model\"}},{\"endpoint\":{\"requestStatus\":{\"statusCode\":\"SUCCESS\",\"requestId\":\"c2fc809f-017d-4af3-9d84-645b5fb5b035\"},\"artifact\":{\"orgName\":\"qc69jvmznzxy\",\"labels\":[\"Language Generation\",\"Vision Assistant\",\"Visual Question Answering\",\"computer vision\",\"cv\",\"image\",\"Image-to-Text\",\"video\",\"vlm\"],\"logo\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/phi-3-vision-128k-instruct.jpg\",\"shortDescription\":\"Cutting-edge open multimodal model exceling in high-quality reasoning from images.\",\"isReadOnly\":true,\"description\":\"$62\",\"canGuestDownload\":true,\"isPublic\":true,\"createdDate\":\"2024-05-16T16:01:36.195Z\",\"publisher\":\"microsoft\",\"displayName\":\"phi-3-vision-128k-instruct\",\"name\":\"phi-3-vision-128k-instruct\",\"updatedDate\":\"2024-08-26T16:47:18.163Z\",\"attributes\":[{\"key\":\"PREVIEW\",\"value\":\"true\"}],\"artifactType\":\"ENDPOINT\"}},\"spec\":{\"openAPISpec\":{\"openapi\":\"3.1.0\",\"info\":{\"title\":\"NVIDIA NIM API for microsoft/phi-3-vision-128k-instruct\",\"description\":\"The NVIDIA NIM REST API. Please see https://docs.api.nvidia.com/nim/reference/microsoft-phi-3-vision-128k-instruct for more details.\",\"version\":\"1.0.0\",\"termsOfService\":\"https://nvidia.com/legal/terms-of-use\",\"contact\":{\"name\":\"NVIDIA Support\",\"url\":\"https://help.nvidia.com/\"},\"license\":{\"name\":\"Apache 2.0\",\"url\":\"https://choosealicense.com/licenses/apache-2.0/\"}},\"servers\":[{\"url\":\"https://ai.api.nvidia.com/v1\"}],\"tags\":[{\"name\":\"Multimodal API\",\"description\":\"This API performs inference using visual language understanding models\"}],\"paths\":{\"/vlm/microsoft/phi-3-vision-128k-instruct\":{\"post\":{\"tags\":[\"Multimodal API\"],\"summary\":\"Request response from the model\",\"description\":\"Invokes inference using the model chat parameters. If uploading large images, this POST should be used in conjunction with the NVCF API which allows for the upload of large assets. \\nYou can find details on how to use NVCF Asset APIs here: https://docs.api.nvidia.com/cloud-functions/reference/createasset\",\"operationId\":\"invokeFunction\",\"parameters\":[{\"in\":\"header\",\"name\":\"NVCF-INPUT-ASSET-REFERENCES\",\"schema\":{\"type\":\"string\",\"maxLength\":370,\"format\":\"uuid\"},\"required\":false,\"description\":\"String of asset IDs separated by commas. Data is uploaded to AWS S3 using NVCF Asset APIs and associated with these asset IDs.If the size of an image is more than 180KB, it needs to be uploaded to a presigned S3 URL bucket. The presigned URL allows for secure and temporary access to the S3 bucket for uploading the image. Once the asset is requested, an asset ID is generated for it. Please include this asset ID in this header and to use the uploaded image in a prompt, you need to refer to it using the following format: `\u003cimg src=\\\"data:image/png;asset_id,{asset_id}\\\" /\u003e`.\"}],\"requestBody\":{\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ChatRequest\"}}},\"required\":true},\"responses\":{\"200\":{\"description\":\"Invocation is fulfilled\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ChatCompletion\"}},\"text/event-stream\":{\"schema\":{\"$ref\":\"#/components/schemas/ChatCompletionChunk\"}}}},\"202\":{\"description\":\"Result is pending. Client should poll using the requestId.\\n\",\"content\":{\"application/json\":{\"example\":{},\"schema\":{}}},\"headers\":{\"NVCF-REQID\":{\"description\":\"requestId required for pooling\",\"schema\":{\"type\":\"string\",\"format\":\"uuid\",\"maxLength\":36}},\"NVCF-STATUS\":{\"description\":\"Invocation status\",\"schema\":{\"type\":\"string\",\"format\":\"^[a-zA-Z-]{1,64}$\",\"maxLength\":64}}}},\"422\":{\"description\":\"Validation failed, provided entity could not be processed.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/Errors\"},\"example\":{\"type\":\"urn:nvcf-worker-service:problem-details:unprocessable-entity\",\"title\":\"Unprocessable Entity\",\"status\":422,\"detail\":\"string\",\"instance\":\"/v2/nvcf/pexec/functions/e598bfc1-b058-41af-869d-556d3c7e1b48\",\"requestId\":\"3fa85f64-5717-4562-b3fc-2c963f66afa6\"}}}},\"500\":{\"description\":\"The invocation ended with an error.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/Errors\"},\"example\":{\"type\":\"urn:nvcf-worker-service:problem-details:internal-server-error\",\"title\":\"Internal Server Error\",\"status\":500,\"detail\":\"string\",\"instance\":\"/v2/nvcf/pexec/functions/e598bfc1-b058-41af-869d-556d3c7e1b48\",\"requestId\":\"3fa85f64-5717-4562-b3fc-2c963f66afa6\"}}}}},\"x-nvai-meta\":{\"name\":\"Create chat completion\",\"returns\":\"Returns a [chat completion](/docs/api-reference/chat/object) object, or a streamed sequence of [chat completion chunk](/docs/api-reference/chat/streaming) objects if the request is streamed.\\n\",\"path\":\"create\",\"examples\":[{\"name\":\"merlion.png\",\"input\":{\"text\":\"Which city is this?\",\"image\":\"https://assets.ngc.nvidia.com/products/api-catalog/fresca/merlion.png\"},\"output\":{\"text\":\"The image shows a cityscape with a distinctive skyline featuring Marina Bay Sands, a luxury hotel and casino in Singapore. The presence of the iconic Marina Bay Sands hotel and the unique architectural style of the buildings are indicative of Singapore.\"},\"requestJson\":\"{ \\\"max_tokens\\\": 512, \\\"temperature\\\": 1.0, \\\"top_p\\\": 0.7, \\\"messages\\\": [ { \\\"role\\\": \\\"user\\\", \\\"content\\\": \\\"\u003c%- input.text %\u003e:\u003cimg src=\\\\\\\"\u003c%- input.image %\u003e\\\\\\\"/\u003e\\\" } ], \\\"stream\\\": true }\",\"responseJson\":\"{ \\\"id\\\": \\\"b52fc961-3c88-41cd-91c7-eab3eef21015\\\", \\\"choices\\\": [ { \\\"index\\\": 0, \\\"message\\\": { \\\"role\\\": \\\"assistant\\\", \\\"content\\\": \\\"\u003c%- output.text %\u003e\\\" }, \\\"finish_reason\\\": \\\"stop\\\" } ], \\\"usage\\\": { \\\"completion_tokens\\\": 55, \\\"prompt_tokens\\\": 1938, \\\"total_tokens\\\": 1993 } }\"},{\"name\":\"chart.png\",\"input\":{\"text\":\"Can you convert the table to markdown format?\",\"image\":\"https://assets.ngc.nvidia.com/products/api-catalog/fresca/chart.png\"},\"output\":{\"text\":\"Certainly! Below is the markdown table converted from the image provided:\\n\\n```markdown\\n| Product | Qtr 1 | Qtr 2 | Grand Total |\\n|---------------------|-----------|-----------|-------------|\\n| Chocolade | $744.60 | $162.56 | $907.16 |\\n| Gummibarchen | $5,079.60 | $1,249.20 | $6,328.80 |\\n| Scottish Longbreads | $1,267.50 | $1,062.50 | $2,330.00 |\\n| Sir Rodney's Scones | $1,418.00 | $756.00 | $2,174.00 |\\n| Tarte au sucre | $4,728.00 | $4,547.92 | $9,275.92 |\\n| Chocolate Biscuits | $943.89 | $349.60 | $1,293.49 |\\n| Total | $14,181.59| $8,127.78 | $22,309.37 |\\n```\\n\\nThis table lists various products along with their sales figures for two quarters and their grand total.\"},\"requestJson\":\"{ \\\"max_tokens\\\": 512, \\\"temperature\\\": 1.0, \\\"top_p\\\": 0.7, \\\"messages\\\": [ { \\\"role\\\": \\\"user\\\", \\\"content\\\": \\\"\u003c%- input.text %\u003e:\u003cimg src=\\\\\\\"\u003c%- input.image %\u003e\\\\\\\"/\u003e\\\" } ], \\\"stream\\\": false }\",\"responseJson\":\"{ \\\"id\\\": \\\"7bda3f6a-f5e1-48c4-a67b-fc77f362dc3c\\\", \\\"choices\\\": [ { \\\"index\\\": 0, \\\"message\\\": { \\\"role\\\": \\\"assistant\\\", \\\"content\\\": \\\"\u003c%- output.text %\u003e\\\" }, \\\"finish_reason\\\": \\\"stop\\\" } ], \\\"usage\\\": { \\\"completion_tokens\\\": 350, \\\"prompt_tokens\\\": 2374, \\\"total_tokens\\\": 2724 } }\"}],\"templates\":[{\"title\":\"Default\",\"requestEjs\":{\"python\":\"$63\",\"node.js\":\"$64\",\"curl\":\"$65\"},\"response\":\"{\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"...\\\",\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 9,\\n \\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"}]}}},\"/status/{requestId}\":{\"get\":{\"tags\":[\"Multimodal API\"],\"summary\":\"Gets the result of an earlier function invocation request that returned a status of 202.\",\"operationId\":\"getFunctionInvocationResult\",\"parameters\":[{\"name\":\"requestId\",\"in\":\"path\",\"description\":\"requestId to poll results\",\"required\":true,\"schema\":{\"type\":\"string\",\"format\":\"uuid\",\"maxLength\":36}}],\"responses\":{\"200\":{\"description\":\"Invocation is fulfilled\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ChatCompletion\"}}}},\"202\":{\"description\":\"Result is pending. Client should poll using the requestId.\\n\",\"content\":{\"application/json\":{\"example\":{},\"schema\":{}}},\"headers\":{\"NVCF-REQID\":{\"description\":\"requestId required for pooling\",\"schema\":{\"type\":\"string\",\"format\":\"uuid\",\"maxLength\":36}},\"NVCF-STATUS\":{\"description\":\"Invocation status\",\"schema\":{\"type\":\"string\",\"format\":\"^[a-zA-Z-]{1,64}$\",\"maxLength\":64}}}},\"422\":{\"description\":\"The invocation ended with an error.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/Errors\"},\"example\":{\"type\":\"urn:nvcf-worker-service:problem-details:unprocessable-entity\",\"title\":\"Unprocessable Entity\",\"status\":422,\"detail\":\"string\",\"instance\":\"/v2/nvcf/pexec/functions/e598bfc1-b058-41af-869d-556d3c7e1b48\",\"requestId\":\"3fa85f64-5717-4562-b3fc-2c963f66afa6\"}}}},\"500\":{\"description\":\"The invocation ended with an error.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/Errors\"},\"example\":{\"type\":\"urn:nvcf-worker-service:problem-details:internal-server-error\",\"title\":\"Internal Server Error\",\"status\":500,\"detail\":\"string\",\"instance\":\"/v2/nvcf/pexec/functions/e598bfc1-b058-41af-869d-556d3c7e1b48\",\"requestId\":\"3fa85f64-5717-4562-b3fc-2c963f66afa6\"}}}}}}}},\"security\":[{\"Token\":[]}],\"components\":{\"securitySchemes\":{\"Token\":{\"type\":\"http\",\"scheme\":\"bearer\"}},\"schemas\":{\"Errors\":{\"properties\":{\"type\":{\"type\":\"string\",\"format\":\"^.{1, 128}$\",\"maxLength\":128,\"description\":\"Error type\"},\"title\":{\"type\":\"string\",\"format\":\"^.{1, 128}$\",\"maxLength\":128,\"description\":\"Error title\"},\"status\":{\"type\":\"integer\",\"minimum\":100,\"maximum\":999,\"description\":\"Error status code\"},\"detail\":{\"type\":\"string\",\"format\":\"^.{1, 1024}$\",\"maxLength\":1024,\"description\":\"Detailed information about the error\"},\"instance\":{\"type\":\"string\",\"format\":\"^.{1, 256}$\",\"maxLength\":256,\"description\":\"Function instance used to invoke the request\"},\"requestId\":{\"type\":\"string\",\"format\":\"uuid\",\"maxLength\":36,\"description\":\"UUID of the request\"}},\"type\":\"object\",\"required\":[\"type\",\"title\",\"status\",\"detail\",\"instance\",\"requestId\"],\"title\":\"InvokeError\"},\"ChatCompletion\":{\"properties\":{\"id\":{\"description\":\"A unique identifier for the completion.\",\"format\":\"uuid\",\"maxLength\":36,\"title\":\"Id\",\"type\":\"string\"},\"choices\":{\"description\":\"The list of completion choices the model generated for the input prompt.\",\"items\":{\"$ref\":\"#/components/schemas/Choice\"},\"maxItems\":1,\"title\":\"Choices\",\"type\":\"array\"},\"usage\":{\"allOf\":[{\"$ref\":\"#/components/schemas/Usage\"}],\"description\":\"Usage statistics for the completion request.\"}},\"required\":[\"id\",\"choices\",\"usage\"],\"title\":\"ChatCompletion\",\"type\":\"object\"},\"ChatCompletionChunk\":{\"properties\":{\"id\":{\"description\":\"A unique identifier for the completion.\",\"format\":\"uuid\",\"maxLength\":36,\"title\":\"Id\",\"type\":\"string\"},\"choices\":{\"description\":\"The list of completion choices the model generated for the input prompt.\",\"items\":{\"$ref\":\"#/components/schemas/ChoiceChunk\"},\"maxItems\":1,\"title\":\"Choices\",\"type\":\"array\"}},\"required\":[\"id\",\"choices\"],\"title\":\"ChatCompletionChunk\",\"type\":\"object\"},\"ChatRequest\":{\"additionalProperties\":false,\"properties\":{\"messages\":{\"description\":\"A list of messages comprising the conversation.\",\"examples\":[{\"content\":\"Hi! What is in this image? \u003cimg src=\\\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAgAAAAIAQMAAAD+wSzIAAAABlBMVEX///+/v7+jQ3Y5AAAADklEQVQI12P4AIX8EAgALgAD/aNpbtEAAAAASUVORK5CYII==\\\"/\u003e\",\"role\":\"user\"},{\"content\":\"Hi! What is in this image? \u003cimg src=\\\"data:image/png;asset_id,87b132b0-08f9-43ea-8fab-f107350a5d00\\\"/\u003e\",\"role\":\"user\"}],\"items\":{\"$ref\":\"#/components/schemas/Message\"},\"minItems\":1,\"title\":\"Messages\",\"type\":\"array\"},\"temperature\":{\"default\":0.2,\"description\":\"The sampling temperature to use for text generation. The higher the temperature value is, the less deterministic the output text will be. It is not recommended to modify both temperature and top_p in the same call.\",\"exclusiveMinimum\":0,\"maximum\":1,\"title\":\"Temperature\",\"type\":\"number\"},\"top_p\":{\"default\":0.7,\"description\":\"The top-p sampling mass used for text generation. The top-p value determines the probability mass that is sampled at sampling time. For example, if top_p = 0.2, only the most likely tokens (summing to 0.2 cumulative probability) will be sampled. It is not recommended to modify both temperature and top_p in the same call.\",\"exclusiveMinimum\":0,\"maximum\":1,\"title\":\"Top P\",\"type\":\"number\"},\"max_tokens\":{\"default\":1024,\"description\":\"The maximum number of tokens to generate in any given call. Note that the model is not aware of this value, and generation will simply stop at the number of tokens specified.\",\"maximum\":2048,\"minimum\":1,\"title\":\"Max Tokens\",\"type\":\"integer\"},\"stream\":{\"default\":false,\"description\":\"If set, partial message deltas will be sent. Tokens will be sent as data-only server-sent events (SSE) as they become available (JSON responses are prefixed by `data: `), with the stream terminated by a `data: [DONE]` message.\",\"title\":\"Stream\",\"type\":\"boolean\"}},\"required\":[\"messages\"],\"title\":\"ChatRequest\",\"type\":\"object\"},\"Choice\":{\"properties\":{\"index\":{\"default\":0,\"description\":\"The index of the choice in the list of choices (always 0).\",\"exclusiveMaximum\":1,\"minimum\":0,\"title\":\"Index\",\"type\":\"integer\"},\"message\":{\"allOf\":[{\"$ref\":\"#/components/schemas/Message\"}],\"description\":\"A chat completion message generated by the model.\",\"examples\":[{\"content\":\"The image features a gray and white checkered pattern on a white background.\",\"role\":\"assistant\"}]},\"finish_reason\":{\"anyOf\":[{\"enum\":[\"stop\",\"length\"],\"type\":\"string\"},{\"type\":\"null\"}],\"default\":null,\"description\":\"The reason the model stopped generating tokens. This will be `stop` if the model hit a natural stop point or a provided stop sequence, or `length` if the maximum number of tokens specified in the request was reached.\",\"examples\":[\"stop\"],\"title\":\"Finish Reason\"}},\"required\":[\"message\"],\"title\":\"Choice\",\"type\":\"object\"},\"ChoiceChunk\":{\"properties\":{\"index\":{\"default\":0,\"description\":\"The index of the choice in the list of choices (always 0).\",\"exclusiveMaximum\":1,\"minimum\":0,\"title\":\"Index\",\"type\":\"integer\"},\"delta\":{\"allOf\":[{\"$ref\":\"#/components/schemas/Message\"}],\"description\":\"A chat completion delta generated by streamed model responses.\",\"examples\":[{\"content\":\"The\",\"role\":\"assistant\"}]},\"finish_reason\":{\"anyOf\":[{\"enum\":[\"stop\",\"length\"],\"type\":\"string\"},{\"type\":\"null\"}],\"default\":null,\"description\":\"The reason the model stopped generating tokens. This will be `stop` if the model hit a natural stop point or a provided stop sequence, or `length` if the maximum number of tokens specified in the request was reached. Will be `null` if the model has not finished generating.\",\"title\":\"Finish Reason\"}},\"required\":[\"delta\"],\"title\":\"ChoiceChunk\",\"type\":\"object\"},\"Message\":{\"additionalProperties\":false,\"properties\":{\"role\":{\"description\":\"The role of the message author.\",\"enum\":[\"user\",\"assistant\"],\"title\":\"Role\",\"type\":\"string\"},\"content\":{\"anyOf\":[{\"type\":\"string\"},{\"items\":{\"anyOf\":[{\"$ref\":\"#/components/schemas/UserTextContent\"},{\"$ref\":\"#/components/schemas/UserImageContent\"}]},\"type\":\"array\"},{\"type\":\"null\"}],\"default\":null,\"description\":\"The contents of the message.\\n\u003cbr\u003eCan only be `null` as part of a last request message with role=`assistant` (used to give a role or labels for the next generation).\\n\u003cbr\u003eTo pass images (only with role=`user`):\\n\u003cbr\u003e - When content is a string, images can be passed together with the text with `img` HTML tags with base64 data: `\u003cimg src=\\\"data:image/{format};base64,{base64encodedimage}\\\" /\u003e` .\\n If the size of an image is more than 180KB, it needs to be uploaded to a presigned S3 bucket using NVCF Asset APIs. Once uploaded you can refer to it using the following format: `\u003cimg src=\\\"data:image/png;asset_id,{asset_id}\\\" /\u003e` .\\n\u003cbr\u003e - When content is a list of objects, images can be passed with objects with type=`image_url`, and image_url containing the base64 image data: `data:image/{format};base64,{base64encodedimage}`. HTML `img` tags will not be parsed from objects with type=`text`.\\n\u003cbr\u003e - In both cases, images can be PNG, JPG or JPEG.\\n\u003cbr\u003eFor `assistant` role, the object list format is not supported.\\n\",\"title\":\"Content\"}},\"required\":[\"role\"],\"title\":\"Message\",\"type\":\"object\"},\"Usage\":{\"properties\":{\"completion_tokens\":{\"description\":\"Number of tokens in the generated completion.\",\"examples\":[19],\"maximum\":2048,\"minimum\":0,\"title\":\"Completion Tokens\",\"type\":\"integer\"},\"prompt_tokens\":{\"description\":\"Number of tokens in the prompt.\",\"examples\":[52],\"maximum\":16000,\"minimum\":0,\"title\":\"Prompt Tokens\",\"type\":\"integer\"},\"total_tokens\":{\"description\":\"Total number of tokens used in the request (prompt + completion).\",\"examples\":[71],\"maximum\":18048,\"minimum\":0,\"title\":\"Total Tokens\",\"type\":\"integer\"}},\"required\":[\"completion_tokens\",\"prompt_tokens\",\"total_tokens\"],\"title\":\"Usage\",\"type\":\"object\"},\"UserImageContent\":{\"additionalProperties\":false,\"properties\":{\"type\":{\"const\":\"image_url\",\"description\":\"The type of the content part.\",\"title\":\"Type\"},\"image_url\":{\"description\":\"Base64 encoded image data in form of `data:image/{format};base64,{base64encodedimage}`. \\n If the size of an image is more than 180KB, it needs to be uploaded to a presigned S3 bucket using NVCF Asset APIs.\\n Once uploaded you can refer to it using the following format: `data:image/png;asset_id,{asset_id}`. \\n Accepted formats are `jpg`, `png` and `jpeg`.\",\"maxLength\":204800,\"title\":\"Image Url\",\"type\":\"string\"}},\"required\":[\"type\",\"image_url\"],\"title\":\"UserImageContent\",\"type\":\"object\"},\"UserTextContent\":{\"additionalProperties\":false,\"properties\":{\"type\":{\"const\":\"text\",\"description\":\"The type of the content part.\",\"title\":\"Type\"},\"text\":{\"description\":\"The text content that will be rendered as a header on the input image.\",\"maxLength\":204800,\"title\":\"Text\",\"type\":\"string\"}},\"required\":[\"type\",\"text\"],\"title\":\"UserTextContent\",\"type\":\"object\"}}}},\"namespace\":\"qc69jvmznzxy\",\"updatedDate\":\"2024-08-24T01:13:33.746Z\",\"nvcfFunctionId\":\"20f2537e-8593-4eb9-ad40-60eee3bbaa55\",\"createdDate\":\"2024-05-16T16:01:36.466Z\",\"attributes\":{\"showUnavailableBanner\":false,\"apiDocsUrl\":\"https://docs.api.nvidia.com/nim/reference/microsoft-phi-3-vision-128k-instruct\",\"playground\":{\"type\":\"custom\",\"input\":{\"items\":[{\"key\":\"image_b64\",\"type\":\"upload\",\"title\":\"Upload Image\",\"formats\":[\"jpg\",\"jpeg\",\"png\"],\"optional\":true},{\"key\":\"prompt\",\"type\":\"text-area\",\"title\":\"Input\"}]},\"output\":{\"items\":[{\"key\":\"choices[0].message.content\",\"type\":\"code\"}]},\"requestBody\":\"{ \\\"max_tokens\\\": \u003c%- request.max_tokens %\u003e, \\\"temperature\\\": \u003c%- request.temperature %\u003e, \\\"top_p\\\": \u003c%- request.top_p %\u003e, \\\"stream\\\": \u003c%- request.stream %\u003e, \\\"messages\\\": [ { \\\"role\\\": \\\"user\\\", \\\"content\\\": \\\"\u003c%- request.prompt %\u003e\u003c% if ((request.assetIds \u0026\u0026 request.assetIds.length) || request.image_b64) { %\u003e \u003cimg src=\\\\\\\\\\\\\\\\\\\"\u003c% if (request.assetIds \u0026\u0026 request.assetIds.length) { %\u003edata:image/png;asset_id,\u003c%- request.assetIds[0] %\u003e\u003c% } else { %\u003e\u003c%- request.image_b64 %\u003e\u003c% } %\u003e\\\\\\\\\\\\\\\\\\\" /\u003e\u003c% } %\u003e\\\" } ] }\"},\"termsOfUse\":\"\u003cb\u003eGOVERNING TERMS\u003c/b\u003e: Your use of this API is governed by the \u003ca href=\\\"https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA API Trial Service Terms of Use\u003c/a\u003e; and the use of this model is governed by the \u003ca href=\\\"https://opensource.org/license/MIT\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eMIT License\u003c/a\u003e.\\n\"},\"artifactName\":\"phi-3-vision-128k-instruct\"},\"config\":{\"name\":\"phi-3-vision-128k-instruct\",\"type\":\"model\"}}]}]\n"])</script><script>self.__next_f.push([1,"66:T162e,"])</script><script>self.__next_f.push([1,"## Blueprint Overview\n\n### Use Case Description\n\nInsightful, accurate, and interactive visual AI agents enable a range of industries to make better decisions faster. These AI agents are given tasks through natural language and can perform complex operations like video summarization and visual question-answering, unlocking entirely new application possibilities. The NVIDIA NIM™ Agent Blueprint makes it easy to get started building and customizing visual AI agents for video search and summarization — all powered by generative AI, vision language models (VLMs), large language models (LLMs), and NVIDIA NIM.\n\n### Architecture Diagram\n\n![Architecture Diagram](https://assets.ngc.nvidia.com/products/api-catalog/video-search-and-summarization/diagram.jpg)\n\n### Included NIM\n\nThe following [NIM](https://www.nvidia.com/en-us/ai/) microservices are used in this blueprint: \n[meta / llama-3.1-70b-instruct](https://build.nvidia.com/meta/llama-3_1-70b-instruct) \n[nv-embedqa-e5-v5](https://build.nvidia.com/nvidia/nv-embedqa-e5-v5) \n[nv-rerankqa-mistral-4b-v3](https://build.nvidia.com/nvidia/nv-rerankqa-mistral-4b-v3)\n\n### Minimum System requirements\n\n#### Core engine\n\nThe core video search and summarization blueprint pipeline supports the following hardware:\n\n- A6000\n- L40/L40s\n- A100\n- H100\n\n#### Hosted NIMs\n\n- Llama-3.1-70b-instruct requires the following minimum GPU configuration based on this [support matrix](https://docs.nvidia.com/nim/large-language-models/latest/support-matrix.html#llama-3-1-70b-instruct).\n- VILA Video VLM (Coming Soon) will require 1xA100 as a minimum GPU.\n- NeMo Retriever Embedding NIM requires 1xL40S as a minimum GPU.\n- NeMo Reranking Embedding NIM requires 1xL40S as a minimum GPU.\n\n### What’s included in the Blueprint\n\nNVIDIA AI Blueprints are customizable agentic workflow examples that equip enterprise developers with NIM microservices, reference code, documentation, and a Helm chart for deployment. This blueprint offers users a reference architecture for deploying a visual agent adept at understanding long-form videos. The agent integrates a scalable video ingestion pipeline, a context manager, a vision-language model (VLM), a large language model (LLM), and a Context-Aware Retrieval-Augmented Generation (CA-RAG) module. CA-RAG module leverages dense captions stored in vector and graph databases as its primary sources for video understanding.\n\n#### Key Agent Features\n\n- Summarization\n- Interactive Question and Answering (Q\u0026A)\n- Alerts (Not in Preview Experience)\n\n#### Core Technology\n\n- **Data processing pipeline**: The process involves decoding video segments (chunks) generated by the stream handler, selecting frames, and using a vision-language model (VLM) along with a caption prompt to generate detailed captions for each chunk. These dense captions are then indexed into vector and graph databases for use in the Context-Aware Retrieval-Augmented Generation workflow.\n- **Context Manager**: Efficiently incorporates tools—a vision-language model (VLM) and a large language model (LLM), using them as required—and key functions including a summary generator, an answer generator, and an alert handler. The tools and functions are used in summary generation, handling Q\u0026A, and managing alerts. In addition, context manager effectively maintains its working context by making efficient use of both short-term memory, such as chat history, and long-term memory resources like vector and graph databases, as needed.\n- **CA-RAG module**: The Context-Aware Retrieval-Augmented Generation (CA-RAG) module leverages both Vector RAG and Graph-RAG as the primary sources for video understanding. During the Q\u0026A workflow, the CA-RAG module extracts relevant context from the vector database and graph database to enhance temporal reasoning, anomaly detection, multi-hop reasoning, and scalability, thereby offering deeper contextual understanding and efficient management of extensive video data.\n- **NeMo Guardrails**: Filters out invalid user prompts. It makes use of the REST API of an LLM NIM microservice.\n\n### Example Walkthrough\n\nThe user selects an example video and prompt to guide the agent in generating a detailed summary. The agent splits the input video into smaller segments that are processed by a VLM (The preview uses [OpenAI's GPT4o](https://openai.com/index/hello-gpt-4o/)). These segments are processed in parallel by the VLM pipeline to produce detailed captions describing the events of each chunk in a scalable and efficient manner. The agent recursively summarizes the dense captions using an LLM, generating a final summary for the entire video once all chunk captions are processed.\n\nAdditionally, these captions are stored in vector and graph databases to power the Q\\\u0026A feature of this blueprint, allowing the user to ask any open-ended questions about the video.\n\n### License\n\nUse of the models in this blueprint is governed by the [NVIDIA AI Foundation Models Community License](https://docs.nvidia.com/ai-foundation-models-community-license.pdf).\n\n### Terms of Use\n\n**GOVERNING TERMS:** This preview is governed by the [NVIDIA API Trial Terms of Service](https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf).\n\n#### Additional Information:\n\nFor the model that includes a Llama3.1 model: [Llama 3.1 Community License Agreement](https://www.llama.com/llama3_1/license/), Built with Llama.\n\nFor the NVIDIA Retrieval QA Mistral 4B Reranking: Apache license.\n\nFor the NVIDIA Retrieval QA E5 Embedding v5: NV-EmbedQA-E5-v5: MIT license; NV-EmbedQA-Mistral7B-v2: Apache 2.0 license, and Snowflake arctic-embed-l: Apache 2.0 license.\n"])</script><script>self.__next_f.push([1,"67:T237b,"])</script><script>self.__next_f.push([1,"Organizations can benefit from using generative AI to enhance customer service but face challenges like fragmented data sources and potential data risks—this blueprint helps them address those issues. This [NVIDIA NIM Agent Blueprint](https://www.nvidia.com/en-us/ai-data-science/ai-workflows/) leverages retrieval-augmented generation (RAG) and generative AI technologies including NVIDIA NIM™ and NVIDIA NeMo™ Retriever. \n\nIt uses some of the latest AI agent-building methodologies, connecting disparate data sources to improve the operational efficiency of existing solutions or build new customer service-centric systems. It offers advanced AI tools, secure management of sensitive data wherever it resides, personalized multi-turn question answering, sentiment analysis, summary generation, and configurable session handling. \n\n## Architecture Diagram\n![](https://assets.ngc.nvidia.com/products/api-catalog/ai-virtual-assistant-for-customer-service/diagram.jpg)\n\n## What’s Included in the Blueprint\nNVIDIA NIM Agent Blueprints provide customizable generative AI reference architectures designed to equip enterprise developers with essential assets such as NIM microservices, reference code, detailed documentation, and Helm charts for deployment. These blueprints serve as a foundation for building advanced AI virtual assistants, either as standalone applications or as enhancements to existing systems. Their focus is on enabling personalization, summarization, and sentiment analysis, particularly through the use of generative AI for data that’s often inaccessible.\n\nThe blueprint includes a reference UI and an AI assistant (developed using the LangGraph framework) that leverages sub-agents to handle queries from both structured and unstructured data sources.\n\n### Included NIM Microservices\n\nThe following [NIM](https://www.nvidia.com/en-us/ai/) microservices are used in this blueprint:\n- NeMo Retriever [Embed QA E5](https://build.nvidia.com/nvidia/nv-embedqa-e5-v5)\n- NeMo Retriever [Rerank Mistral 4B](https://build.nvidia.com/nvidia/rerank-qa-mistral-4b)\n- [Llama 3.1 70B Instruct](https://build.nvidia.com/meta/llama-3_1-70b-instruct)\n\n### Sample Data\n\nThe blueprint comes with synthetic sample data representing a typical customer service function, including customer profiles, order histories (structured data), and technical product manuals (unstructured data). A notebook is provided to guide users on how to ingest both structured and unstructured data efficiently.\n- **Structured Data**: Includes customer profiles and order history \n- **Unstructured Data**: Ingests product manuals, product catalogs, and FAQs \n\n### AI Agent\nThis reference solution implements three sub-agents using the open-source LangGraph framework. These sub-agents address common customer service tasks for the included sample dataset. They rely on the Llama 3.1 models (70B and 8B Instruct) and NVIDIA NIM microservices for generating responses, converting natural language into SQL queries, and assessing the sentiment of the conversation.\n\n### Key Components\n- **Structured Data Retriever**: Works in tandem with a Postgres database and PandasAI to fetch relevant data based on user queries.\n- **Unstructured Data Retriever**: Processes unstructured data (e.g., PDFs, FAQs) by chunking it, creating embeddings using the NeMo Retriever embedding NIM, and storing it in Milvus for fast retrieval.\n\n### Analytics and Admin Operations\nTo support operational requirements, the blueprint includes reference code for managing key administrative tasks:\n- Storing conversation histories\n- Generating conversation summaries\n- Conducting sentiment analysis on customer interactions\n\nThese features ensure that customer service teams can efficiently monitor and evaluate interactions for quality and performance.\n\n### Data Flywheel\nThe blueprint comes with pre-built APIs that support continuous model improvement. The feedback loop, or “data flywheel,” allows LLM models to be fine-tuned over time to enhance both accuracy and cost-effectiveness. Feedback is collected at multiple points in the process to refine the models’ performance further.\n\n### Summary\nIn summary, this NVIDIA NIM Agent Blueprint offers a comprehensive solution for building intelligent, generative AI-powered virtual assistants for customer service, leveraging structured and unstructured data to deliver personalized and efficient support. It includes all necessary tools and guidance to deploy, monitor, and continually improve the solution in real-world environments.\n\n## Minimum System Requirements\n#### Hardware Requirements\nThe AI virtual assistant pipeline supports the following hardware:\n- H100\n- A100\n\n#### OS Requirements\n- Ubuntu 22.04 OS\n\n#### Software Dependencies\nNVIDIA NIM inference microservices\n\n- [Embed QA](https://build.nvidia.com/nvidia/nv-embedqa-e5-v5) for embeddings\n- [Rerank Mistral 4B](https://build.nvidia.com/nvidia/rerank-qa-mistral-4b) for reranking\n- [Llama 3.1 70B Instruct](https://build.nvidia.com/meta/llama-3_1-70b-instruct) for advanced reasoning, inferencing, and natural language mastery\n- [Nemotron4-340B](https://build.nvidia.com/nvidia/nemotron-4-340b-instruct) for synthetic Data Generation (Optional)\n\n## Example Walkthrough With Sample Input/Output\nExplore example walkthroughs on the NVIDIA API catalog through the specific NIM microservices links below:\n\nNeMo Retriever [Embed QA](https://build.nvidia.com/nvidia/nv-embedqa-e5-v5)\nNeMo Retriever [Rerank Mistral 4B](https://build.nvidia.com/nvidia/rerank-qa-mistral-4b)\n[Llama 3.1 70B Instruct](https://build.nvidia.com/meta/llama-3_1-70b-instruct)\n\n## Ethical Considerations\nNVIDIA believes Trustworthy AI is a shared responsibility, and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their supporting model team to ensure the models meet requirements for the relevant industry and use case and address unforeseen product misuse. For more detailed information on ethical considerations for the models, please see the Model Card++ Explainability, Bias, Safety \u0026 Security, and Privacy Subcards. Please report security vulnerabilities or NVIDIA AI concerns [here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/).\n\n\n## License\nUse of the models in this AI virtual assistant for customer service blueprint is governed by the [NVIDIA AI Foundation Models Community License](https://docs.nvidia.com/ai-foundation-models-community-license.pdf).\n\n## Terms of Use\nGOVERNING TERMS: The blueprint is governed by the [NVIDIA Agreements | Enterprise Software | NVIDIA Software License Agreement](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-software-license-agreement/) and [NVIDIA Agreements | Enterprise Software | Product Specific Terms for AI Product](https://www.nvidia.com/en-us/agreements/enterprise-software/product-specific-terms-for-ai-products/).\n \n \n#### Meta Llama 3.1 70B Instruct\t\nGOVERNING TERMS: The NIM container is governed by the [NVIDIA Software License Agreement](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-software-license-agreement/) and the [Product Specific Terms for AI Products](https://www.nvidia.com/en-us/agreements/enterprise-software/product-specific-terms-for-ai-products/); \n\nUse of this model is governed by the [NVIDIA AI Foundation Models Community License Agreement](\u003chttps://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-ai-foundation-models-community-license-agreement/#:~:text=This%20license%20agreement%20(%E2%80%9CAgreement%E2%80%9D,algorithms%2C%20parameters%2C%20configuration%20files%2C\u003e). ADDITIONAL INFORMATION: Llama 3.1 Community License Agreement, Built with Llama.\n\n#### Nemo Text Retriever E5 Embedding Model\nGOVERNING TERMS: The NIM container is governed by [NVIDIA Agreements | Enterprise Software | NVIDIA Software License Agreement](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-software-license-agreement/) and [NVIDIA Agreements | Enterprise Software | Product Specific Terms for AI Product](https://www.nvidia.com/en-us/agreements/enterprise-software/product-specific-terms-for-ai-products/); and the use of this model is governed by the ai-foundation-models-community-license.pdf (nvidia.com). ADDITIONAL INFORMATION: MIT license.\n\n#### NVIDIA Retrieval QA Mistral 4B Reranking v3\t\nGOVERNING TERMS: The NIM container is governed by [NVIDIA Agreements | Enterprise Software | NVIDIA Software License Agreement](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-software-license-agreement/) and [NVIDIA Agreements | Enterprise Software | Product Specific Terms for AI Product](https://www.nvidia.com/en-us/agreements/enterprise-software/product-specific-terms-for-ai-products/); and the use of this model is governed by the [ai-foundation-models-community-license.pdf](https://docs.nvidia.com/ai-foundation-models-community-license.pdf) (nvidia.com). ADDITIONAL INFORMATION: Apache license."])</script><script>self.__next_f.push([1,"68:T1389,"])</script><script>self.__next_f.push([1,"#### Experience a Real-time Wind Tunnel\n\nThis experience shows an interactive virtual wind tunnel. Simulating airflow in a virtual wind tunnel with computational fluid dynamics (CFD) requires millions of complex calculations. Without AI, it can take minutes to see the result of a single design change. Developers building the next generation of AI-powered CAE tools are combining simulation AI with immersive virtual environments to enable real-time digital twins where design changes instantly update in the simulation, as you see in this demonstration. NVIDIA is making it easier to create interactive design tools by introducing Omniverse Blueprint for interactive aerodynamics.\nTo enable real-time performance in a virtual wind tunnel, simulation AI models are first trained offline on representative datasets. For this demo, the training dataset was created using [Luminary Cloud's GPU-accelerated CFD solver](https://www.luminarycloud.com/), which models complex airflow over diverse geometries. The simulation AI learns the complex relationships between car geometries (STLs) and airflow. This blueprint is compatible with industry-standard CFD solvers and can connect to third-party tools for meshing and geometry morphing, creating watertight meshes for simulation-ready geometries.\nThe blueprint also integrates NVIDIA Modulus (our framework for simulation AI) with CFD solver data. This enables developers to train surrogate models from scratch or fine-tune NIM foundation models, reducing AI training time and cost. Once trained, the AI runs simulations orders of magnitude faster than traditional CFD, enabling real-time aerodynamic flow simulation. This speed provides designers with creative freedom, allowing designers to innovate and explore changes interactively.\n\n## Architecture Diagram\n![Architecture Diagram](https://assets.ngc.nvidia.com/products/api-catalog/digital-twins-for-fluid-simulation/diagram.jpg)\n\n## What’s Included in the Blueprint\nNVIDIA Blueprints are comprehensive reference workflows designed to streamline AI application development across industries and accelerate deployment to production. Built with NVIDIA AI and Omniverse libraries, SDKs, and microservices, they provide a foundation for custom AI solutions. Each blueprint includes reference code for constructing workflows, tools and documentation for deployment and customization, and a reference architecture outlining API definitions and microservice interoperability. By enabling rapid prototyping and speeding time to deployment, these blueprints empower enterprises to operationalize AI-driven solutions like AI agents, digital twins, and synthetic data generation, and more.\n\n### Included NIM Microservices\n- Coming soon: NVIDIA external aerodynamics foundation model.\n\n### Sample Data\nThe blueprint comes with sample CFD data for training a surrogate model.\n\n### World State Controller\nThis reference solution implements an Omniverse Kit application controller that maintains the application world state and connects the 3D world stage with simulation results produced by the surrogate model\n\n### Data Flywheel\nThe blueprint comes with pre-built APIs that support continuous model improvement. The feedback loop, or “data flywheel,” allows surrogate models to be fine-tuned over time to enhance both accuracy and cost-effectiveness.\n\nIn summary, this NVIDIA Omniverse Blueprint offers a starting point for building real-time digital twins for computer-aided engineering (CAE) workflows combining CUDA-X accelerated solvers, Modulus for simulation AI, and Omniverse for high quality rendering.\n\n## Minimum System Requirements\n\n#### Hardware Requirements\nThe real-time wind tunnel blueprint supports the following hardware:\n- OVX 4xL40S\n\n#### OS Requirements\n- Ubuntu 22.04 OS\n\n#### Software Requirements\n- Pyhton 3\n\n## Ethical Considerations\nNVIDIA believes Trustworthy AI is a shared responsibility, and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their supporting model team to ensure the models meet requirements for the relevant industry and use case and address unforeseen product misuse. For more detailed information on ethical considerations for the models, please see the Model Card++ Explainability, Bias, Safety \u0026 Security, and Privacy Subcards. Please report security vulnerabilities or NVIDIA AI concerns [here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/).\n\n## Terms of Use\nGOVERNING TERMS: The trial service is governed by the NVIDIA API Trial Terms of Service (found at https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf); use of the model is governed by the NVIDIA AI Foundation Models Community License Agreement (found at https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-ai-foundation-models-community-license-agreement/)"])</script><script>self.__next_f.push([1,"69:T4f1,| Field | Response |\n| -- | -- |\n| Generatable or reverse engineerable personally-identifiable information (PII)? | None |\n| Protected classes used to create this model? | Not Applicable (No PII) |\n| Was consent obtained for any personal data used? | Not Applicable (No personal data) |\n| How often is dataset reviewed? | \tBefore Release |\n| Is a mechanism in place to honor data subject right of access or deletion of personal data? | No |\n| If personal data collected for the development of the model, was it collected directly by NVIDIA? |Not Applicable |\n| If personal data collected for the development of the model by NVIDIA, do you maintain or have access to disclosures made to data subjects?\t| Not Applicable |\n| If personal data collected for the development of this AI model, was it minimized to only what was required? | Not Applicable |\n| Is there provenance for all datasets used in training? | Yes |\n| Does data labeling (annotation, metadata) comply with privacy laws? | Yes |\n| Is data compliant with data subject requests for data correction or removal, if such a request was made? | Yes |\n| Applicable NVIDIA Privacy Policy\t| [https://www.nvidia.com/en-us/about-nvidia/privacy-policy/](https://www.nvidia.com/en-us/about-nvidia/privacy-policy/) |6a:T1f56,"])</script><script>self.__next_f.push([1,"## Use Case Description\nThe 3D conditioning for precise visual generative AI NVIDIA Omniverse Blueprint, powered by [NVIDIA NIM™](https://www.nvidia.com/en-us/ai/), [NVIDIA Omniverse](https://www.nvidia.com/en-us/omniverse/)™, [OpenUSD](https://www.nvidia.com/en-us/omniverse/usd/), image2image models such as SDXL or tuned models like Realviz4.0, and [Shutterstock Generative 3D](https://www.shutterstock.com/discover/generative-ai-3d), offers a streamlined solution for creating precise, on-brand images. This experience allows users to choose the color of a hero asset, select the desired camera angle in the 3D scene, and then use generative AI to customize scene components such as backgrounds and props. Using this experience as inspiration, developers can download and customize the blueprint to unlock use cases such as scalable concepting and ideation, through to the creation of marketing assets for their brands or customers.\n\n## Experience Walkthrough\nThe user is presented with a live 3D viewport showcasing the final product—the \"hero asset\"—created by a creative team. In this instance, the hero asset is an espresso machine with a coffee mug. This asset, representing the final design, includes all the final materials and product options. It is placed within a rudimentary scene that appears unfinished. Additional props, such as the cutting board, were generated using Shutterstock 3D Generator to populate the counter with objects unavailable to the creative team when the initial scene was created.\n\nThe user can orbit the hero asset using the left mouse button and zoom in or out with the mouse wheel. Navigation within the scene is designed to keep the hero asset in frame at all times. Once the user has identified a suitable camera angle, they can adjust the espresso machine's configuration. The machine has two control surface options, various color options, and a choice of coffee mug style. An additional control allows the user to select a pre-generated HDRi image (created with Shutterstock 360 HDRi Generator) to quickly modify the scene's background.\n\nNext, the user inputs individual prompts to generate the background. These prompts are linked to specific objects, ensuring each prompt modifies a designated area within the scene. After the user enters the prompts, the system processes them along with the scene's layout using generative AI to create the final image. During this process, the system generates masks for the targeted prompts, which the creative team can use for further image processing.\n\n## Architecture Diagram\n![Architecture Diagram](https://assets.ngc.nvidia.com/products/api-catalog/conditioning-for-precise-visual-generative-ai/diagram.jpg)\n\n## Included NIM\nThe following [NIM](https://www.nvidia.com/en-us/ai/) are used by this blueprint: \n[USD Search](https://build.nvidia.com/nvidia/usdsearch) \n[USD Code](https://build.nvidia.com/nvidia/usdcode-llama3-70b-instruct) \n[Shutterstock 3D Generator (Playground Sample on NIM)](https://build.nvidia.com/shutterstock/edify-3d) \n[Shutterstock360 HDRi Generator (Playground Sample on NIM)](https://build.nvidia.com/shutterstock/edify-360-hdri)\n\n## What’s included in the Blueprint\n[NVIDIA Blueprints](https://nvidianews.nvidia.com/news/nvidia-and-global-partners-launch-nim-agent-blueprints-for-enterprises-to-make-their-own-ai) are customizable AI workflow examples that equip enterprise developers with NIM microservices, reference code, documentation, and a helm chart for deployment.\n\nThis blueprint provides a [reference](https://resources.nvidia.com/en-us-omniverse-product-configurator/blueprint-3d-conditioning) and [workflow guide](https://github.com/NVIDIA-Omniverse-Blueprints/3d-conditioning/tree/main) for the users to showcase how diffusion models, control nets, and corresponding auxiliary tools can be easily integrated to Omniverse to be streamed remotely. Our primary container with Omniverse handles viewport streaming and message passing between the web front-end with the second container; users can opt to use ComfyUI \\+ an image2image model such as SDXL or tuned models like Realviz4.0, leveraging our default template or take their own custom pipeline for diffusion models to handle requests coming from the first container with Omniverse. Then, we push the helm chart with the two containers. \n\n## Minimum System Requirements\nHardware Requirements\n\nGPU: 2 x L40 deployed (One for rendering the scene and another for inferencing the diffusion model) or 1x NVIDIA RTX™ 6000 Ada Generation for local\n\nCPU: x86\\_64 architecture, 8 Cores (Intel Core i7 (7th Generation) or AMD Ryzen 5\\)\n\nSystem Memory: 64GB\n\nSoftware Requirements\n\nOS: Ubuntu 22.04\n\n## Example Walkthrough with Sample Input/Output \nPrimary Container with Omniverse\n\nInput\n\nInput Type(s): JSON with payloads of text prompts and dropdown options in text\n\nInput Format: bytes\n\nOutput\n\nOutput Type(s): Viewport, Image\n\nOutput Format: stream\n\nSecond Container with Diffusion Model\n\nInput\n\nInput Type(s): JSON graph structure with embedded parameters (text, number, and image in base64) (10MB custom limit, which can be changed from the primary container)\nInput Format: bytes\n\nOutput\nOutput Type(s): Image\nOutput Format: bytes\n\nThe framework is designed to enable software developers to rapidly prototype and productize custom workflows that involve capturing buffers from the viewport of a USD scene while taking conditions in a text form, then generating an image that accounts for both constraints by running an inference of diffusion models. We have included a docker image that automatically installs and deploys ComfyUI + image2image models such as SDXL or tuned models like Realviz4.0 for the included workflow, which leverages Control Net heavily to handle multiple conditions.\n\n## Technical Considerations \nThe software is capable of conditioning a USD scene to mask a target asset to keep the 3D rendering while inferring the others via a diffusion model given the normal map or depth map as additional constraints along with text prompts. This allows users to have more artistic control over 3D assets, as well as opting to use the 3D rendering instead of the image generated by the diffusion model. To run the experience locally, you can use the downloadable and choose to run web front end or Omniverse application. Please consult our [documentation](https://github.com/NVIDIA-Omniverse-Blueprints/3d-conditioning/tree/main) to learn more about how we integrate 3D rendering and the diffusion model to achieve the final result. \n\n## Ethical Considerations\nNVIDIA believes that Trustworthy AI is a shared responsibility and we have established policies and practices to enable the development of a wide array of AI applications. When downloaded or used under our terms of service, developers should work with their supporting model team to ensure the models meet requirements for the relevant industry and use case and address unforeseen product misuse. \n\nFor more detailed information on ethical considerations for the models, please see the Model Card++ Explainability, Bias, Safety \u0026 Security, and Privacy Subcards. Please report security vulnerabilities or NVIDIA AI Concerns [here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/). \n\n[NVIDIA Edify](https://www.nvidia.com/en-us/gpu-cloud/edify/) is a multimodal architecture for developing visual generative AI models for image, 3D, 360 HDRi, PBR materials, and video. Using NVIDIA AI Foundry, service providers can train, and customize Edify models to build commercially viable visual services on top of NVIDIA NIM. \n\n## Terms of Use\nGOVERNING TERMS: This trial service is governed by the [NVIDIA API Trial Terms of Service](https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf). ADDITIONAL INFORMATION: RealvisXL license at [LICENSE.md · stabilityai/stable-diffusion-xl-base-1.0 at main.](https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0/blob/main/LICENSE.md)"])</script><script>self.__next_f.push([1,"6b:T458,| Field | Response |\n| -- | -- |\n| Intended Application(s) \u0026 Domain(s): | Generating image embedding that is aligned with text for zero-shot classification. |\n| Model Type: | Embedding Generation |\n| Intended Users: | This model is intended for developers building search engines, classification, detection/ segmentation models. |\n| Output: | Embedding Features |\n| Describe how the model works: | This model has a vision extractor and a text encoder trained for embedding alignment |\n| Technical Limitations: | Model needs a downstream task specific head to perform CV tasks. |\n| Verified to have met prescribed NVIDIA standards: | Yes |\n| Performance Metrics: | ImageNet zero-shot accuracy |\n| Licensing: | GOVERNING TERMS: This trial is governed by the [NVIDIA API Trial Terms of Service](https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf). The use of this model is governed by the [AI Foundation Models Community License Agreement](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-ai-foundation-models-community-license-agreement/). |6c:T9dd,"])</script><script>self.__next_f.push([1,"**USD Search** is a versatile AI-powered search engine designed to enable comprehensive searches across images\n(e.g., .jpg, .png) and USD-based 3D models within various storage backends (AWS S3 and Omniverse Nucleus server).\nIt enables users to use natural language, image similarity, and precise metadata criteria\n(file name, type, date, size, creator, etc.) to locate relevant content efficiently. Furthermore, when integrated\nwith the Asset Graph Service, DeepSearch extends its capabilities to include searches based on USD properties and\nspatial dimensions of 3D model bounding boxes, enhancing the ability to find assets that meet specific requirements.\n\n## Features\n\n- **Natural Language Searches**: Utilize AI to search for images and USD-based 3D models using simple, descriptive\n language.\n- **Image Similarity Searches**: Find images similar to a reference image through AI-driven image comparisons.\n- **Metadata Filtering**: Filter search results by file name, file type, creation/modification dates, file size, and\n creator/modifier metadata.\n- **USD Content Filtering with Asset Graph Service**: When used with the Asset Graph Service, search capabilities are\n expanded to include filtering based on USD properties and object dimensions.\n- **Multiple Storage Backend Support**: Compatible with various storage backends, including AWS S3 bucket and Omniverse Nucleus server.\n- **Advanced File Name, Extension and Path Filters**: Use wildcards for broad or specific file name and extension searches.\n- **Date and Size Range Filtering**: Specify assets created or modified within certain date ranges or file sizes larger\n or smaller than a designated threshold.\n- **User-based Filtering**: Filter assets based on their creator or modifier, allowing for searches tailored to\n particular users' contributions.\n- **Embedding-based Similarity Threshold**: Set a similarity threshold for more nuanced control over search results in\n embedding-based searches.\n- **Custom Search Paths and Scenes**: Specify search locations within the storage backend or conduct searches within\n specific scenes for targeted results.\n- **Return Detailed Results**: Option to include images, metadata, root prims, and predictions in the search results.\n\n\nFeatures available only with the **Asset Graph Service**:\n- **USD Property Filtering**\n- **USD Object Dimension Filtering**\n- **In-scene searches**\n\n## Resources\n\n* [DeepSearch Documentation](https://docs.omniverse.nvidia.com/services/latest/services/deepsearch/overview.html)\n"])</script><script>self.__next_f.push([1,"6d:T2663,"])</script><script>self.__next_f.push([1,"This experience showcases vulnerability analysis for container security using NVIDIA NIM microservices and NVIDIA Morpheus. The NIM Agent Blueprint demonstrates accelerated analysis on common vulnerabilities and exposures (CVE) at an enterprise scale, reducing mitigation from days and hours to just seconds. While traditional methods require substantial manual effort to pinpoint solutions for vulnerabilities, these technologies enable quick, automatic, and actionable CVE risk analysis using large language models (LLMs) and retrieval-augmented generation (RAG). With this blueprint, security analysts can expedite the process of determining whether a software package includes exploitable and vulnerable components using LLMs and event-driven RAG triggered by the creation of a new software package or the detection of a CVE.\n\n## Use Case Description\n\nPatching software security issues is becoming increasingly challenging as the rate of new reports into the [CVE database](https://www.cve.org/) accelerates. Hundreds of pieces of information must be retrieved, understood, and integrated to triage a single container for these vulnerabilities. Clearly, the traditional approach to scanning and patching has become unmanageable.\n\nGenerative AI can improve vulnerability defense while decreasing the load on security teams. Using NVIDIA NIM microservices and the Morpheus cybersecurity AI SDK, the NIM Agent Blueprint accelerates CVE analysis at enterprise scale, dramatically reducing time to assess from days to just seconds. \n\nThe LLM expedites the manual work of a human security analyst by properly and thoroughly researching and investigating reported CVE risks to confirm vulnerabilities, find false positives, generate investigation checklists of tasks, and determine true exploitability.\n\nAfter the required data is processed, a unique checklist is generated and sent to agents, and analysis is looped until all checklist items are triaged. The application then summarizes the findings, generates action justifications, and passes them to a human analyst to decide appropriate next steps.\n\nIn this way, security analysts can cut through the noise of the increasing number CVEs to focus on the most critical security tasks.\n\n## Architecture Diagram\n\n![](https://assets.ngc.nvidia.com/products/api-catalog/vulnerability-analysis-for-container-security/diagram.jpg)\n\n\n# Included NIM and Other Software\n\nThe following are used by this blueprint:\n\n- [NIM of meta/llama3-70b-instruct](https://build.nvidia.com/meta/llama3-70b)\n\n- [NVIDIA Morpheus Cybersecurity AI SDK](https://developer.nvidia.com/morpheus-cybersecurity)\n\n\n## Minimum System Requirements\n\n**Hardware Requirements**\n\nThe vulnerability analysis pipeline supports the following hardware:\n\n- 1x L40 GPU (Pipeline operation)\n\n- 1x H100 GPU (NIM)\n\nNote: For improved paralleled performance, we recommend 8x or more H100s for inference. Depending on the application, the Morpheus pipeline operation affords more flexibility on GPU needs.\n\n**OS Requirements**\n\n- Ubuntu 20.04/22.04\n\n**Inference**\n\n- LLM NIM: [NIM of meta/llama3-70b-instruct](https://build.nvidia.com/meta/llama3-70b)\n\n**Example Container and CVEs**\n\nContainers:\n\n- morpheus: NVIDIA Cybersecurity SDK\n\n- rapids: NVIDIA Accelerated Data Science Framework\n\n- holoscan: NVIDIA Sensor Processing Platform\n\n- Tika: Apache metadata and text extraction toolkit\n\n- Pip: Package installer for Python\n\n- tritonserver: NVIDIA Inference Server\n\nVulnerability Alerts:\n\n- CVE-2022-29501: SchedMD Slurm 21.08.x through 20.11.x has Incorrect Access Control\n\n- CVE-2024-1086: A use-after-free vulnerability in the Linux kernel's netfilter\n\n- GHSA-j7hp-h8jx-5ppr: Heap buffer overflow in libwebp\n\n- GHSA-3f63-hfp8-52jq: Arbitrary Code Execution in Pillow\n\n- GHSA-q3qx-c6g2-7pw2: aiohttp's ClientSession is vulnerable to CRLF injection via version\n\n- CVE-2023-2617: A vulnerability classified as problematic was found in OpenCV wechat_qrcode Module up to 4.7.0\n\n\n## What's included in the Blueprint\n\nThe blueprint operates using a Plan-and-Execute-style LLM pipeline for CVE impact analysis.It does not include the initial CVE risk analysis tooling. The pipeline is adaptable, supporting various LLM services, including those that conform to the LLMService interface, such as OpenAI, NIM microservices, NeMo, or local execution with llama-cpp-python.\n\n#### Key Components\n\n**Security Scan Result**\n\nThe workflow begins by inputting the identified CVEs from a container security scan as input. This can be generated from a container image scanner of your choosing such as [Anchore](https://anchore.com/container-vulnerability-scanning/).\n\n**Code Repository and Documentation**\n\nThe blueprint pulls code repositories and documentation provided by the user. These repositories are processed through an embedding model, and the resulting embeddings are stored in vector databases (VDBs) for the agent's reference.\n\n**Vector Database**\n\nVarious vector databases can be used for the embedding. We currently utilize FAISS for the VDB because it does not require an external service and is simple to use. Any vector store can be used, such as NVIDIA cuVS, which would provide accelerated indexing and search.\n\n**Web Vulnerability Intel**\n\nThe system collects detailed information about each CVE through web scraping and data retrieval from various public security databases, including GHSA, Redhat, Ubuntu, and NIST CVE records, as well as tailored threat intelligence feeds.\n\n**SBOM**\n\nThe provided Software Bill of Materials (SBOM) document is processed into a software-ingestible format for the agent's reference. SBOMs can be generated for any container using the open-source tool [Syft](https://github.com/anchore/syft).\n\n**Lexical Search**\n\nAs an alternative, a lexical search is available for use cases where creating an embedding is impractical due to a large number of source files in the target container.\n\n**PreProcessing**\n\nAll the above actions are encapsulated by multiple Morpheus preprocessing pipeline stages to prepare the data for use with the LLM engine.\n\n**Checklist Generation**\n\nLeveraging the gathered information about each vulnerability, the checklist generation node creates a tailored, context-sensitive task checklist designed to guide the impact analysis.\n\n**Task Agent**\n\nAt the core of the process is an LLM agent iterating through each item in the checklist. For each item, the agent answers the question using a set of tools which provide information about the target container. The tools tap into various data sources (web intel, vector DB, search etc.), retrieving relevant information to address each checklist item. The loop continues until the agent resolves each checklist item satisfactorily.\n\n**Summarization**\n\nOnce the agent has compiled findings for each checklist item, these results are condensed by the summarization node into a concise, human-readable paragraph.\n\n**Justification**\n\nGiven the summary, the justification status categorization node then assigns a resulting VEX (Vulnerability Exploitability eXchange) status to the CVE.\n\nWe provided a set of predefined categories for the model to choose from. If the CVE is deemed exploitable, the reasoning category is \"vulnerable.\" If it is not exploitable, there are 10 different reasoning categories to explain why the vulnerability is not exploitable in the given environment:\n\n- false_positive\n\n- code_not_present\n\n- code_not_reachable\n\n- requires_configuration\n\n- requires_dependency\n\n- requires_environment\n\n- protected_by_compiler\n\n- protected_at_runtime\n\n- protected_by_perimeter\n\n- protected_by_mitigating_control\n\nAt the end of the pipeline run, an output including all the gathered and generated information is prepared for security analysts for a final review.\n\nNote: All output should be vetted by a security analyst before being used in a cybersecurity application.\n\n**NIM microservices**\n\nThe Morpheus SDK can utilize various LLM endpoints and is optimized to use NVIDIA NIM microservices. The current default for all of the NIM models is llama3-70b-instruct with specifically tailored prompt engineering and edge case handling. Other models are able to be substituted, such as smaller, fine-tuned NIM models or other external LLM services. Subsequent updates will provide more details about fine-tuning and data flywheel techniques.\n\nNote: The LangChain library is employed to deploy all LLM agents within a Morpheus pipeline, streamlining efficiency and reducing the need for duplicative efforts.\n\nNote: Routinely checked validation datasets are critical to ensuring proper and consistent outputs.\n\n\n#### Example Walkthrough with Sample Input/Output\n\nTo explore examples walkthroughs on the NVIDIA API catalog through the specific NIM microservices links below:\n\n- [Llama 3 70B Instruct](https://build.nvidia.com/meta/llama3-70b)\n\n\n\n#### License\n\nBy using this software or microservice, you are agreeing to the [terms and conditions](https://www.nvidia.com/en-us/data-center/products/nvidia-ai-enterprise/eula/) of the license and acceptable use policy.\n\n\n## Terms of Use\n\nGOVERNING TERMS: The NIM container is governed by the [NVIDIA Software License Agreement](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-software-license-agreement/) and [Product-Specific Terms for AI Products](https://www.nvidia.com/en-us/agreements/enterprise-software/product-specific-terms-for-ai-products/); and use of this model is governed by the [NVIDIA AI Foundation Models Community License Agreement](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-ai-foundation-models-community-license-agreement/). \n\nADDITIONAL Terms: [Meta Llama 3 Community License](https://www.llama.com/llama3/license/), Built with Meta Llama 3."])</script><script>self.__next_f.push([1,"6e:T12e3,"])</script><script>self.__next_f.push([1,"{\n \"output\": [\n {\n \"vuln_id\": \"CVE-2024-1086\",\n \"checklist\": [\n {\n \"input\": \"Check Linux Kernel Version: Verify the version of the Linux kernel installed in the Docker container. The vulnerability affects kernel versions \u003e=3.15 and \u003c6.7.3. Is the container running a vulnerable kernel version? If so, it may be exploitable.\",\n \"response\": \"To determine if the container is running a vulnerable kernel version, you need to check the Linux kernel version of the host machine. You can do this by running the `uname -r` command on the host machine. If the kernel version is \u003e=3.15 and \u003c6.7.3, then the container may be exploitable.\"\n },\n {\n \"input\": \"Identify Netfilter Usage: Review the application code within the Docker container to check if the Netfilter subsystem is being used, particularly the nf_tables component. Does the codebase contain any Netfilter-related configurations or rules?\",\n \"response\": \"The Docker container does not appear to use the Netfilter subsystem or its components, such as nf_tables, based on the code review and analysis of the container's software bill of materials and purpose.\"\n },\n {\n \"input\": \"Assess Local Privilege Escalation Risks: Evaluate the potential risks of local privilege escalation within the container. Since the vulnerability can be exploited to achieve local privilege escalation, assess the impact of an attacker gaining elevated privileges within the container.\",\n \"response\": \"The potential risks of local privilege escalation within the container are moderate. While there are no known vulnerabilities in the Docker container's dependencies, the use of machine learning libraries and dependencies increases the attack surface. It is essential to regularly monitor and update these dependencies to prevent potential vulnerabilities. Additionally, implementing robust security measures, such as least privilege access and secure configuration, can help mitigate the risks of local privilege escalation.\"\n },\n {\n \"input\": \"Review User Namespace Configurations: Check if user namespaces are enabled within the container. If so, the vulnerability can be exploited to achieve privilege escalation. Review the configuration and assess the risks associated with user namespaces.\",\n \"response\": \"To review user namespace configurations and check if user namespaces are enabled within the container, you can use the `docker info` command. If user namespace support is enabled, it may indicate that the vulnerability can be exploited to achieve privilege escalation, and you should assess the risks associated with user namespaces.\"\n },\n {\n \"input\": \"Verify Patch Levels: Check if the Linux kernel has been patched to address this vulnerability. Verify if the container is running a kernel version that includes the fix for this vulnerability (commit f342de4e2f33e0e39165d8639387aa6c19dff660).\",\n \"response\": \"Unfortunately, I was unable to determine the kernel version of the Docker container due to the lack of information provided in the context. The context only provides a Dockerfile, which is a script for building a Docker image, but does not provide information about how to run a command inside a Docker container. To verify if the container is running a kernel version that includes the fix for the specified vulnerability, I would need to be able to run the command \\\"uname -r\\\" inside the Docker container, but this is not possible with the given context.\"\n }\n ],\n \"summary\": \"Based on the provided Checklist and Findings, the CVE is **not exploitable**. The definitive answers from the checklist items are:\\n\\n* Checklist Item 2: The Docker container does not use the Netfilter subsystem or its components, such as nf_tables.\\n* Checklist Item 3: The potential risks of local privilege escalation within the container are moderate, but there are no known vulnerabilities in the Docker container's dependencies.\\n* Checklist Item 5: Unfortunately, the kernel version of the Docker container could not be determined due to lack of information.\\n\\nThe other checklist items (1 and 4) require further investigation or information to provide a definitive answer.\",\n \"justification\": {\n \"label\": \"requires_environment\",\n \"reason\": \"The CVE is not exploitable because the Docker container does not use the Netfilter subsystem or its components, which are required for exploitability.\",\n \"status\": \"FALSE\"\n }\n }\n ]\n}"])</script><script>self.__next_f.push([1,"6f:Tf70,"])</script><script>self.__next_f.push([1,"{\n \"output\": [\n {\n \"vuln_id\": \"CVE-2022-29501\",\n \"checklist\": [\n {\n \"input\": \"Check Slurm Version: Verify the version of Slurm installed in the Docker container. The vulnerability affects Slurm versions 21.08.x through 20.11.x, specifically those greater than or equal to 21.08.0 and less than 21.08.08. Is the container running a vulnerable version of Slurm?\",\n \"response\": \"The Docker container is not running a vulnerable version of Slurm, as Slurm is not installed in the container.\"\n },\n {\n \"input\": \"Review Slurm Configuration: Assess the Slurm configuration within the Docker container to identify potential access control weaknesses. Check for any misconfigurations or insecure settings that could lead to escalation of privileges or code execution.\",\n \"response\": \"Based on the investigation, it appears that Slurm is not present in the Docker container, and therefore, there are no potential access control weaknesses related to Slurm configuration within the container. The container's primary purpose is to provide a self-contained environment for running cuDF, and it does not utilize Slurm, a job scheduler used in high-performance computing environments.\"\n },\n {\n \"input\": \"Evaluate Privilege Escalation Risks: Identify potential privilege escalation risks within the container, particularly those related to Slurm's access control mechanisms. Are there any opportunities for an attacker to exploit the vulnerability and gain elevated privileges?\",\n \"response\": \"Based on the investigation, Slurm is not present in the Docker container, which reduces the risk of privilege escalation related to Slurm's access control mechanisms. However, there are potential privilege escalation risks within the container related to CentOS 7 and CUDA 11.8.0. The Docker container uses CUDA and cuDF components, but it is unclear if it specifically uses CUDA 11.8.0. Further investigation is needed to determine if the container is vulnerable to Dirty COW or Dirty Pipe vulnerabilities, or if it uses any Linux kernel modules or device drivers that could lead to privilege escalation.\"\n },\n {\n \"input\": \"Inspect Code Execution Paths: Review the code execution paths within the Slurm application to identify potential entry points for code execution. Are there any opportunities for an attacker to inject malicious code or execute arbitrary commands?\",\n \"response\": \"Based on the investigation, I did not find any direct evidence of code execution paths within the Docker container that could lead to code execution vulnerabilities. However, without a deeper understanding of the entire codebase and the specific use cases, I cannot rule out the possibility of vulnerabilities entirely. It is recommended to perform a more comprehensive code review and security audit to identify potential vulnerabilities in the Docker container's code execution paths.\"\n }\n ],\n \"summary\": \"Based on the provided Checklist and Findings, the CVE is NOT exploitable. The investigation revealed that the Docker container is not running a vulnerable version of Slurm, and Slurm is not even installed in the container. Additionally, there are no potential access control weaknesses related to Slurm configuration within the container, and no opportunities for an attacker to exploit the vulnerability and gain elevated privileges through Slurm's access control mechanisms.\",\n \"justification\": {\n \"label\": \"code_not_present\",\n \"reason\": \"The Docker container does not have Slurm installed, making it impossible for the CVE to be exploitable.\",\n \"status\": \"FALSE\"\n }\n }\n ]\n}"])</script><script>self.__next_f.push([1,"70:Tb6d,"])</script><script>self.__next_f.push([1,"## Blueprint Overview\n\n### Use Case Description\n\nThe multimodal PDF data extraction workflow uses NVIDIA NeMo\u003csup\u003eTM\u003c/sup\u003e Retriever NIM microservices to unlock highly accurate insights from massive volumes of enterprise data.\n\nWith this enterprise-scale multimodal document retrieval workflow, developers can create digital humans, AI agents, or customer service chatbots that can quickly become experts on any area captured within their corpus of data.\n\nThe multimodal retrieval workflow is designed to enhance generative AI applications with RAG capabilities which can be connected to proprietary data–wherever it resides. Use this workflow to supercharge your RAG applications with unprecedented intelligence.\n\n### Architecture Diagram\n\n![Architecture Diagram Placeholder](https://assets.ngc.nvidia.com/products/api-catalog/multimodal-pdf-data-extraction-for-enterprise-rag/diagram.jpg)\n\n### Included NIM\n\nThe following [NIM](https://www.nvidia.com/en-us/ai/) is used by this blueprint:\n- [nv-embedqa-e5-v5](https://build.nvidia.com/nvidia/nv-embedqa-e5-v5)\n- [nv-rerankqa-mistral4b-v3](https://build.nvidia.com/nvidia/nv-rerankqa-mistral-4b-v3)\n- [google-deplot](https://build.nvidia.com/google/google-deplot): [Apply for Early Access](https://developer.nvidia.com/nemo-microservices)\n- nv-yolox-structured-image-v1: [Apply for Early Access](https://developer.nvidia.com/nemo-microservices)\n- cached: [Apply for Early Access](https://developer.nvidia.com/nemo-microservices)\n- paddleocr: [Apply for Early Access](https://developer.nvidia.com/nemo-microservices)\n\n### What’s included in the Blueprint\n\nNVIDIA NIM\u003csup\u003eTM\u003c/sup\u003e Agent Blueprints are customizable AI workflow examples that equip enterprise developers with NIM microservices, reference code, documentation, and a Helm chart for deployment.\n\nThis blueprint is built as a reference implementation for building a multimodal data ingest pipeline for retrieval-augmented generation (RAG). Included in this workflow are several key operational components representative of common activities one might see in a complex multimodal workflow. Three independent streams are processed:\n\n1. Text extraction directly from a corpus of PDFs\n2. Table detection and content extraction from an image of the PDF pages\n3. Chart and Chart Element content extraction from an image of the PDF pages\n\nEach extraction task takes advantage of one or more NIM components to identify (YOLOX), deconstruct (DePlot, CACHED), and recognize (PaddleOCR) text representations of PDF elements presented to the workflow, elevating PDF processing from text-only to a full multimodal workflow that extracts rich relations and context encoded in the charts and tables within the PDF.\n\n### Example Walkthrough with Sample Input/Output\n\n[Walkthrough example on GitHub](https://github.com/nvidia/nv-ingest)\n\n### License\n\n[License on GitHub](https://github.com/nvidia/nv-ingest/blob/main/LICENSE)\n"])</script><script>self.__next_f.push([1,"71:T2650,"])</script><script>self.__next_f.push([1,"This experience showcases James and Aria, our interactive digital humans who have the knowledge of NVIDIA’s products or O-RAN specifications by having direct access to corresponding knowledge bases. The Digital Human and the RAG-powered backend application use a collection of NVIDIA NIM microservices, NVIDIA ACE and Maxine technologies, and ElevenLabs text-to-speech to provide natural and immersive responses. Using James or Aria as an inspiration, users can download and customize the Digital Human for customer service blueprint for their industry use case, with document ingestion and retrieval-augmented generation (RAG), and customizing the avatar look and voice for their application. \n\n## Use Case Description\n\nThe digital human for customer service NVIDIA AI Blueprint is powered by NVIDIA Tokkio, a workflow based on ACE technologies, to bring enterprise applications to life with a 3D animated digital human interface. With approachable, human-like interactions, customer service applications can provide more engaging user experiences compared to traditional customer service options.\n\nThis workflow is designed to integrate within your existing generative AI applications built using RAG. Use this workflow to start evolving your applications running in your data center, in the cloud, or at the edge, to include a full digital human interface.\n\n## Architecture Diagram\n\n![Architecture Diagram](https://assets.ngc.nvidia.com/products/api-catalog/digital-humans-for-customer-service/diagram.png)\n\n## What’s included in the Blueprint\n\n## NIM and Other Software\nThe following [NIM](https://www.nvidia.com/en-us/ai/) are used by this blueprint:\n\n* [nv-embedqa-e5-v5](https://build.nvidia.com/nvidia/nv-embedqa-e5-v5) \n* [nv-rerankqa-mistral4b-v3](https://build.nvidia.com/nvidia/nv-rerankqa-mistral-4b-v3) \n* [Llama3-8b-instruct](https://build.nvidia.com/meta/llama3-8b) \n* [Parakeet-ctc-1.1b-asr](https://build.nvidia.com/nvidia/parakeet-ctc-1\\_1b-asr)\n* [FastPitch-hifigan-tts](https://build.nvidia.com/nvidia/fastpitch-hifigan-tts) \n* [Audio2face-3D](https://build.nvidia.com/nvidia/audio2face)\n* [Audio2face-2D](https://build.nvidia.com/nvidia/audio2face-2d) \n* [Other ACE Microservices](https://developer.nvidia.com/ace)\n\nNVIDIA AI Blueprints are customizable AI workflow examples that equip enterprise developers with NIM microservices, reference code, documentation, and a Helm chart for deployment. \n\nThis [blueprint](https://github.com/NVIDIA-AI-Blueprints/digital-human) provides a reference for the users to showcase how an LLM or a RAG application can be easily connected to a digital human pipeline. The digital human and the RAG application are deployed separately. The RAG application is responsible for generating the text content of the interaction and Tokkio customer service workflow is providing a solution to enable avatar live interaction. Those two entities are separated and communicate using the REST API. The users can develop their requirements and tune the app based on their needs. Included in this workflow are steps to setup and connect both components of the customer service pipeline. Each part of the pipelines consists of the following components:\n\n**Digital Human Pipeline**\n\n* A composable Helm chart that sets up the digital human pipeline with ACE agent and deploys the Audio2Face-3D, and Riva Parakeet and FastPitch NIM microservices to deploy the default stylized avatar. The pipeline also provides different variations incorporating Audio2Face-2D to use 2D avatars.\n\n**RAG Pipeline**\n\n* A Docker Compose application deploys a Llama 3 LLM NIM, NeMo Retriever nv-embed-qa embedding NIM, a NeMo Retriever mistral-4b reranking NIM and a LangChain RAG pipeline with a FastAPI endpoint for multiturn chat. \n* Notebooks ingestion of domain specific documents [(ORAN data)](https://specifications.o-ran.org/specifications) and parameter efficient fine tuning on synthetic data generated from ORAN documents. \n\n**With this blueprint the users will be able to do the following:**\n\n1. Use the pre-built Digital Human Helm chart to create a digital human interface powered by a sample avatar asset (named Ben), Riva text-to-speech (TTS) FastPitch, and automatic speech recognition (ASR) NIM microservices. The pre-built Helm chart also connects by default to [Llama 3 8b NIM API endpoint](https://build.nvidia.com/meta/llama3-8b) to get the users’ started with an interactive Digital Human. \n2. Use the RAG application to demonstrate the power of industry knowledge with example ORAN database or ingest documents and customize the digital human knowledge for your specific industry. \n3. Able to deploy the digital human experience and the RAG application on either bare metal or their favorite cloud provider of choice with simple one-click deployment scripts.\n\n## Example Walkthrough with Sample Input/Output\n\n## **Audio2Face-3D NIM**\n\nInput \nInput Type(s): Audio \nInput Format: bytes \nInput Parameters: Tuning Parameters, Audio \nOther Properties Related to Input: Supported Sampling rates: 22.05KHz, 44.1KHz, 16KHz; All audio is resampled to 16KHz. There is no max audio length.\n\nOutput \nOutput Type(s): Blendshape Coefficients \nOutput Format: Custom Protobuf Format \nOutput Parameters: Custom Protobuf Format\n\n## **Audio2Face-2D NIM**\n\nInput Type: Portrait image, Audio\nInput Format: RGB image, 32 bit float PCM audio\nInput Parameters: 720p to 4K for the image, Audio\nOther Properties Related to Input: Supported sampling rate: 16kHz and mono channel audio. There is no max audio length.\n\n\nOutput\nOutput Format: Animated RGB Image\nOutput Parameters: Custom Protobuf Format \nOther Properties Related to Output: Input images post-processed using proprietary technique; 3 Channel, 32 bit image supported.\n\n\n## **Llama-3-8b NIM**\n\nInput\nInput Format: Text \nInput Parameters: Temperature, TopP\n\nOutput\nOutput Format: Text and code \nOutput Parameters: Max output tokens\n\n## **Riva Parakeet-ctc-1\\_1b-asr NIM** \nInput \nInput Type(s): Audio in English \nInput Format(s): Linear PCM 16-bit 1 channel\n\nOutput \nOutput Type(s): Text String in English with Timestamps\n\n## **Fastpitch-hifigan-tts NIM** \nInput\nInput Format (For FastPitch 1st Stage): Text Strings in English\nOther Properties Related to Input: 400 Character Text String Limit\nOutput \nOutput Format (For HifiGAN 2nd Stage): Audio of shape (batch x time) in wav format\n\n## **NeMo Retriever nv-embedqa-e5-v5 NIM** \nInput \nInput Type: text \nInput Format: list of strings with task-specific instructions\n\nOutput \nOutput Type: floats \nOutput Format: list of float arrays, each array containing the embeddings for the corresponding input string\n\n## **NeMo Retriever nv-rerankqa-mistral4b-v3 NIM** \nInput \nInput Type: Pair of Texts \nInput Format: List of text pairs \nOther Properties Related to Input: The model's maximum context length is 512 tokens. Texts longer than maximum length must either be chunked or truncated.\n\nOutput \nOutput Type: floats \nOutput Format: List of float arrays \nOther Properties Related to Output: Each the probability score (or raw logits) The user can decide if a Sigmoid activation function is applied to the logits.\n\nThe Audio data captured from the user is sent to ACE agent which orchestrates the communication between various NIM microservices. The ACE agent uses the Riva Parakeet NIM to convert the audio data to text which is then sent to the RAG pipeline. The RAG pipelines uses the NeMo Retriever embedding and reranking and LLM NIM microservices to answer the question with context from documents fed to it. The text result is sent to TTS, and the voice output from TTS is used to animate the digital human using the Audio2Face-3D NIM or Audio2Face-2D NIM.\n\n## API Definition \n\nAPI Interfaces for NIM collections conform to OpenAPI standards, and can be readily integrated with NVIDIA NIM containers deployed in any compatible compute cluster. Integration or replacement of API compatible components allow for easy modification of workloads to adapt to your specific use case where needed. See individual NIM [documentation](https://docs.nvidia.com/nim/index.html) for the integration details.\n\nBy default, the digital human RAG plugin has support for an API that follows the [OpenAPI specification.](https://github.com/NVIDIA-AI-Blueprints/digital-human/tree/main/api) To customize the pipeline to connect to your own RAG system, follow the instructions [here](https://github.com/NVIDIA-AI-Blueprints/digital-human).\n\n## Minimum System requirements\n\n**Hardware Requirements**\n\n**Digital human pipeline** \n\nThe digital human pipeline supports the following hardware:\n\n* T4 \n* A10 \n* L4 \n* L40S\n\nYou would need 2 GPUs minimum for 1 stream for the default 3D avatar workflow. Additional details for hardware and compute requirements for different variants of the digital human workflow can be found [here](https://docs.nvidia.com/ace/latest/workflows/tokkio/text/reference-workflows/Reference_Workflows.html).\n\n**RAG pipeline**\n\nThe RAG pipeline needs 2xA100 GPUs, one for the embedding and reranking NIM and one for the LLM NIM.\n\n**OS Requirements**\n\nBoth the digital human and the RAG pipeline can be deployed on Ubuntu 22.04 OS.\n\n\n## Terms of Use\n\nGOVERNING TERMS: \nYour use of this trial service is governed by the [NVIDIA API Trial Terms of Service](https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf)\nACE NIM and NGC Microservices \\- [NVIDIA AI Product License](https://www.nvidia.com/en-us/data-center/products/nvidia-ai-enterprise/eula/) \nGenerative AI Examples \\- [Apache 2](https://www.apache.org/licenses/LICENSE-2.0.txt)\\\nADDITIONAL TERMS: \nMeta Llama 3 Community License Agreement at [https://llama.meta.com/llama3/license/](https://llama.meta.com/llama3/license/)."])</script><script>self.__next_f.push([1,"72:T14a1,"])</script><script>self.__next_f.push([1,"## Use Case Description\n\nComputational drug designers must pick a few chemical structures from around 10^60 options for experimental testing, more than the number of stars in the universe. To discover \"hits\" that have all the properties of a drug suitable for clinical testing, their search must be targeted and efficient. \n\nThis is a difficult problem, and pharma companies typically spend 10-15 years and $1B-$2B to bring a new drug to solve it and bring a new drug to market. In a typical drug discovery workflow, researchers first identify the biological target and mechanism that they want to alter to treat the disease, a process called target identification. Then, once a target is identified, molecules that bind to that target must be identified (hit identification). These hits are then optimized for safety and therapeutic effect. \n\nThe biology and chemistry underlying each of these steps is complex, often involving the identification of cryptic patterns in enormous datasets and long cycles of biological experimentation, chemical synthesis and validation. However, even though Pharma spent $262B USD on R\\\u0026D in 2023 (Evaluate), 90% of drugs in clinical trials fail, demonstrating a need for innovative approaches to drug discovery (Nature Review Drug Discovery).\n\nHere, we bring generative AI to bear on the problem, pre-optimizing molecules and screening their interaction with the target protein. This NIM Agent Blueprint shows how virtual screening can be recast using NVIDIA microservices for protein folding, molecule generation, and docking to speed the development cycle and produce better molecules, faster.\n\n## Experience Walkthrough\n\n1. The user passes the sequence of the protein target that they want to design against to the AlphaFold2 NIM, which accurately determines that protein's structure. This step requires aligning the protein sequence to other known proteins, and multiple configurations for this alignment step are available. \n \n2. An initial chemical structure is passed to the MolMIM NIM to seed its generative search through chemical space. The user can also choose a property to optimize for (e.g., QED), the number of molecules to generate, and other constraints. The generated molecules are scored and passed back to MolMIM for further optimization for multiple cycles depending on the number of iterations the user selects. \n3. These molecular structures and the structure of the protein target are passed to the DiffDock NIM, which generates the number of binding poses that the user indicates, along with other constraints. \n4. The user then clicks the \"Generate Molecules\" button, and when complete, optimized molecules are returned to the user, ready for further lab testing. \n\n## What's included in the Blueprint\n\nNVIDIA NIM\u003csup\u003eTM\u003c/sup\u003e Agent Blueprints are customizable AI workflow examples that equip enterprise developers with NIM microservices, reference code, documentation, and a Helm chart for deployment. \n\n![Architecture Diagram Placeholder](https://assets.ngc.nvidia.com/products/api-catalog/generative-virtual-screening-for-drug-discovery/diagram.png)\n\n## Minimum System Requirements\n\n### Hardware\n\n- GPU: 1x A6000, A100, or H100\n- CPU: x86_64 architecture only for this release with 24 physical CPU cores\n- Storage: 600GB \n- System Memory: 68GB\n\n### Software\n\n- Operating System: Ubuntu 20.04 or newer \n- NVIDIA Driver version: 535 or newer \n- NVIDIA CUDA version: 12.4 or newer \n- NVIDIA Container Toolkit version: 1.15.0 or newer \n- Docker version: Docker version 26 or newer\n\n## Example Walkthrough with Sample Input/Output\n\nSee a complete example of how to get started with this blueprint on the [NVIDIA NIM Agent Blueprints GitHub repository](https://github.com/NVIDIA-NIM-Agent-Blueprints/generative-virtual-screening)\n\n## Technical Considerations\n\nMolMIM is capable of optimizing molecules for user-defined objectives. In this example, MolMIM is employing oracles for QED (drug likeness), penalized log P (a measure of solubility), and similarity as measured by Tanimoto index. To employ MolMIM for optimization tasks on user-defined objectives, use the downloadable NIM and utilize the decoder endpoint. Learn more about how to generate molecules with user-defined oracle functions in MolMIM's documentation and example Jupyter notebooks.\n\n## Ethical Considerations\n\nNVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their supporting model team to ensure the models meet requirements for the relevant industry and use case and addresses unforeseen product misuse. For more detailed information on ethical considerations for the models, please see the Model Card++ Explainability, Bias, Safety \u0026 Security, and Privacy Subcards. Please report security vulnerabilities or NVIDIA AI Concerns [here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/).\n\n## License\n\nUse of the models in this Generative Virtual Screening Blueprint are governed by the [NVIDIA AI Foundation Models Community License](https://docs.nvidia.com/ai-foundation-models-community-license.pdf)."])</script><script>self.__next_f.push([1,"20:[\"$\",\"$L3c\",null,{\"data\":[{\"endpoint\":{\"requestStatus\":{\"statusCode\":\"SUCCESS\",\"requestId\":\"d1ea9469-fe76-4f29-8b2f-c97bb9043cbf\"},\"artifact\":{\"orgName\":\"qc69jvmznzxy\",\"labels\":[\"Agent Blueprint\",\"chat\",\"generative AI\",\"video-to-text\",\"vision\"],\"logo\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/video-search-and-summarization.jpg\",\"shortDescription\":\"Ingest massive volumes of live or archived videos and extract insights for summarization and interactive 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The server could not understand the request due to invalid syntax.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ViaError\"}}}},\"401\":{\"description\":\"Unauthorized request.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ViaError\"}}}},\"405\":{\"description\":\"Alert functionality not enabled.\"},\"422\":{\"description\":\"Failed to process request.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ViaError\"}}}},\"429\":{\"description\":\"Rate limiting exceeded.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ViaError\"}}}},\"500\":{\"description\":\"Internal Server Error.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ViaError\"}}}}}}},\"/alerts/{alert_id}\":{\"delete\":{\"tags\":[\"Alerts\"],\"summary\":\"Delete a live stream alert\",\"description\":\"Delete a live stream alert added to the VIA Server.\",\"operationId\":\"delete_alert_alerts__alert_id__delete\",\"parameters\":[{\"name\":\"alert_id\",\"in\":\"path\",\"required\":true,\"schema\":{\"type\":\"string\",\"format\":\"uuid\",\"description\":\"Unique ID of the alert to be deleted.\",\"title\":\"Alert Id\",\"maxLength\":36,\"minLength\":36},\"description\":\"Unique ID of the alert to be deleted.\"}],\"responses\":{\"200\":{\"description\":\"Successful Response.\",\"content\":{\"application/json\":{\"schema\":{}}}},\"400\":{\"description\":\"Bad Request. The server could not understand the request due to invalid syntax.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ViaError\"}}}},\"401\":{\"description\":\"Unauthorized request.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ViaError\"}}}},\"422\":{\"description\":\"Failed to process request.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ViaError\"}}}},\"429\":{\"description\":\"Rate limiting exceeded.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ViaError\"}}}},\"500\":{\"description\":\"Internal Server Error.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ViaError\"}}}}}}}},\"components\":{\"schemas\":{\"AddAlertInfo\":{\"properties\":{\"liveStreamId\":{\"type\":\"string\",\"format\":\"uuid\",\"title\":\"Livestreamid\",\"description\":\"ID of the live stream to configure the alert for\",\"maxLength\":36,\"minLength\":36},\"events\":{\"items\":{\"type\":\"string\",\"maxLength\":1024,\"minLength\":1,\"pattern\":\"^[A-Za-z0-9_.\\\\-\\\"\\\\' ,]*$\"},\"type\":\"array\",\"maxItems\":100,\"title\":\"Events\",\"description\":\"List of events to generate alert for\",\"examples\":[[\"Fire\",\"More than 5 people\"]]},\"callback\":{\"type\":\"string\",\"maxLength\":2083,\"minLength\":1,\"format\":\"uri\",\"title\":\"Callback\",\"description\":\"URL to call when events are detected\",\"examples\":[\"http://localhost:12000/via-callback-handler\"]},\"callbackJsonTemplate\":{\"type\":\"string\",\"maxLength\":1024,\"pattern\":\"^(.|\\\\n)*$\",\"title\":\"Callbackjsontemplate\",\"description\":\"JSON Template for the callback body. Supported placeholders: {{streamId}}, {{alertId}}, {{ntpTimestamp}}, {{alertText}}, {{detectedEvents}}\",\"default\":\"{ \\\"streamId\\\": \\\"{{ streamId }}\\\", \\\"alertId\\\": \\\"{{ alertId }}\\\", \\\"ntpTimestamp\\\": \\\"{{ ntpTimestamp }}\\\", \\\"alertDetails\\\": \\\"{{ alertText }}\\\", \\\"detectedEvents\\\": {{ detectedEvents }}}\"},\"callbackToken\":{\"type\":\"string\",\"maxLength\":10000,\"pattern\":\"^[A-Za-z0-9_.\\\\-]*$\",\"title\":\"Callbacktoken\",\"description\":\"Bearer token to use when calling the callback URL\",\"examples\":[\"eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9\"]}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"liveStreamId\",\"events\",\"callback\"],\"title\":\"AddAlertInfo\",\"description\":\"Information required to add an alert.\"},\"AddAlertResponse\":{\"properties\":{\"id\":{\"type\":\"string\",\"format\":\"uuid\",\"title\":\"Id\",\"description\":\"ID of the newly added alert\",\"maxLength\":36,\"minLength\":36}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"id\"],\"title\":\"AddAlertResponse\",\"description\":\"Response of the add alert API.\"},\"AddFileInfoResponse\":{\"properties\":{\"id\":{\"type\":\"string\",\"format\":\"uuid\",\"title\":\"Id\",\"description\":\"The file identifier, which can be referenced in the API endpoints.\",\"maxLength\":36,\"minLength\":36},\"bytes\":{\"type\":\"integer\",\"maximum\":100000000000,\"minimum\":0,\"format\":\"int64\",\"title\":\"Bytes\",\"description\":\"The size of the file, in bytes.\",\"examples\":[2000000]},\"filename\":{\"type\":\"string\",\"maxLength\":256,\"pattern\":\"^[A-Za-z0-9_.\\\\-]*$\",\"title\":\"Filename\",\"description\":\"Filename along with path to be used.\",\"examples\":[\"myfile.mp4\"]},\"purpose\":{\"allOf\":[{\"$ref\":\"#/components/schemas/Purpose\"}],\"description\":\"The intended purpose of the uploaded file. For VIA use-case this must be set to vision\",\"examples\":[\"vision\"]},\"media_type\":{\"allOf\":[{\"$ref\":\"#/components/schemas/MediaType\"}],\"description\":\"Media type (image / video).\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"id\",\"bytes\",\"filename\",\"purpose\",\"media_type\"],\"title\":\"AddFileInfoResponse\",\"description\":\"Response schema for the add file request.\"},\"AddLiveStream\":{\"properties\":{\"liveStreamUrl\":{\"type\":\"string\",\"maxLength\":256,\"pattern\":\"^rtsp://\",\"title\":\"Livestreamurl\",\"description\":\"Live RTSP Stream URL\",\"examples\":[\"rtsp://localhost:8554/media/video1\"]},\"description\":{\"type\":\"string\",\"maxLength\":256,\"pattern\":\"^[A-Za-z0-9_.\\\\-\\\"\\\\' ,]*$\",\"title\":\"Description\",\"description\":\"Live RTSP Stream description\",\"examples\":[\"Description of the live stream\"]},\"username\":{\"type\":\"string\",\"maxLength\":256,\"pattern\":\"^[A-Za-z0-9_.\\\\-\\\"\\\\' ,]*$\",\"title\":\"Username\",\"description\":\"Username to access live stream URL.\",\"default\":\"\",\"examples\":[\"username\"]},\"password\":{\"type\":\"string\",\"maxLength\":256,\"pattern\":\"^[A-Za-z0-9_.\\\\-\\\"\\\\' ,]*$\",\"title\":\"Password\",\"description\":\"Password to access live stream URL.\",\"default\":\"\",\"examples\":[\"password\"]}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"liveStreamUrl\",\"description\"],\"title\":\"AddLiveStream\",\"description\":\"Parameters required to add a live stream.\"},\"AddLiveStreamResponse\":{\"properties\":{\"id\":{\"type\":\"string\",\"format\":\"uuid\",\"title\":\"Id\",\"description\":\"The stream identifier, which can be referenced in the API endpoints.\",\"maxLength\":36,\"minLength\":36}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"id\"],\"title\":\"AddLiveStreamResponse\",\"description\":\"Response schema for the add live stream API.\"},\"AlertInfo\":{\"properties\":{\"liveStreamId\":{\"type\":\"string\",\"format\":\"uuid\",\"title\":\"Livestreamid\",\"description\":\"ID of the live stream to configure the alert for\",\"maxLength\":36,\"minLength\":36},\"events\":{\"items\":{\"type\":\"string\",\"maxLength\":1024,\"minLength\":1,\"pattern\":\"^[A-Za-z0-9_.\\\\-\\\"\\\\' ,]*$\"},\"type\":\"array\",\"maxItems\":100,\"title\":\"Events\",\"description\":\"List of events to generate alert for\",\"examples\":[[\"Fire\",\"More than 5 people\"]]},\"alertId\":{\"type\":\"string\",\"format\":\"uuid\",\"title\":\"Alertid\",\"description\":\"ID of the alert\",\"maxLength\":36,\"minLength\":36}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"liveStreamId\",\"events\",\"alertId\"],\"title\":\"AlertInfo\",\"description\":\"Information about an alert added to the server.\"},\"AlertTool\":{\"properties\":{\"name\":{\"type\":\"string\",\"maxLength\":256,\"pattern\":\"^[A-Za-z0-9_.\\\\-\\\"\\\\' ,]*$\",\"title\":\"Name\",\"description\":\"Name for the alert tool\"},\"events\":{\"items\":{\"type\":\"string\",\"maxLength\":1024,\"pattern\":\"^[A-Za-z0-9_.\\\\-\\\"\\\\' ,]*$\"},\"type\":\"array\",\"maxItems\":100,\"title\":\"Events\",\"description\":\"List of events to trigger the alert for\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"name\",\"events\"],\"title\":\"AlertTool\",\"description\":\"Alert tool configuration.\"},\"Body_add_video_file_files_post\":{\"properties\":{\"purpose\":{\"allOf\":[{\"$ref\":\"#/components/schemas/Purpose\"}],\"description\":\"The intended purpose of the uploaded file. For VIA use-case this must be set to vision\"},\"media_type\":{\"allOf\":[{\"$ref\":\"#/components/schemas/MediaType\"}],\"description\":\"Media type (image / video).\"},\"file\":{\"type\":\"string\",\"format\":\"binary\",\"title\":\"File\",\"description\":\"File object (not file name) to be uploaded.\",\"maxLength\":100000000000},\"filename\":{\"type\":\"string\",\"maxLength\":256,\"pattern\":\"^[A-Za-z0-9_.\\\\-/]*$\",\"title\":\"Filename\",\"description\":\"Filename along with path to be used.\",\"default\":\"\",\"examples\":[\"/home/ubuntu/myfile.mp4\"]}},\"type\":\"object\",\"required\":[\"purpose\",\"media_type\"],\"title\":\"Body_add_video_file_files_post\",\"description\":\"Request body schema for adding a file.\"},\"ChatCompletionMessageAlertTool\":{\"properties\":{\"name\":{\"type\":\"string\",\"maxLength\":256,\"pattern\":\"^[A-Za-z0-9_.\\\\-\\\"\\\\' ,]*$\",\"title\":\"Name\",\"description\":\"Name for the alert that was triggered.\"},\"ntpTimestamp\":{\"type\":\"string\",\"maxLength\":24,\"minLength\":24,\"pattern\":\"^(\\\\d{4})-(\\\\d{2})-(\\\\d{2})T(\\\\d{2}):(\\\\d{2}):(\\\\d{2})(\\\\.\\\\d{3})Z$\",\"title\":\"Ntptimestamp\",\"description\":\"NTP timestamp of when the event occurred.\",\"examples\":[\"2024-05-30T01:41:25.000Z\"]},\"detectedEvents\":{\"items\":{\"type\":\"string\",\"maxLength\":1024,\"minLength\":1,\"pattern\":\"^[A-Za-z0-9_.\\\\-\\\"\\\\' ,]*$\"},\"type\":\"array\",\"maxItems\":100,\"title\":\"Detectedevents\",\"description\":\"List of events detected.\"},\"details\":{\"type\":\"string\",\"maxLength\":10000,\"pattern\":\"^(.|\\\\n)*$\",\"title\":\"Details\",\"description\":\"Details of the alert.\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"name\",\"ntpTimestamp\",\"detectedEvents\",\"details\"],\"title\":\"ChatCompletionMessageAlertTool\",\"description\":\"Alert trigerred by VIA.\"},\"ChatCompletionMessageToolCall\":{\"properties\":{\"type\":{\"$ref\":\"#/components/schemas/ChatCompletionToolType\"},\"alert\":{\"$ref\":\"#/components/schemas/ChatCompletionMessageAlertTool\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"type\",\"alert\"],\"title\":\"ChatCompletionMessageToolCall\",\"description\":\"Tool calls generated by VIA.\"},\"ChatCompletionQuery\":{\"properties\":{\"id\":{\"anyOf\":[{\"type\":\"string\",\"format\":\"uuid\",\"maxLength\":36,\"minLength\":36},{\"items\":{\"type\":\"string\",\"format\":\"uuid\",\"maxLength\":36,\"minLength\":36},\"type\":\"array\",\"maxItems\":50}],\"title\":\"Id\",\"description\":\"Unique ID or list of IDs of the file(s)/live-stream(s) to summarize\"},\"messages\":{\"items\":{\"$ref\":\"#/components/schemas/ChatMessage\"},\"type\":\"array\",\"maxItems\":1000000,\"title\":\"Messages\",\"description\":\"The list of chat messages.\"},\"model\":{\"type\":\"string\",\"maxLength\":256,\"pattern\":\"^[A-Za-z0-9_.\\\\-]*$\",\"title\":\"Model\",\"description\":\"Model to use for this query.\",\"examples\":[\"vita-2.0\"]},\"api_type\":{\"type\":\"string\",\"maxLength\":32,\"pattern\":\"^[A-Za-z]*$\",\"title\":\"Api Type\",\"description\":\"API used to access model.\",\"default\":\"\",\"examples\":[\"internal\"]},\"response_format\":{\"allOf\":[{\"$ref\":\"#/components/schemas/ResponseFormat\"}],\"description\":\"An object specifying the format that the model must output.\",\"default\":{\"type\":\"text\"}},\"stream\":{\"type\":\"boolean\",\"title\":\"Stream\",\"description\":\"If set, partial message deltas will be sent, like in ChatGPT. Tokens will be sent as data-only [server-sent events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format) as they become available, with the stream terminated by a `data: [DONE]` message.\",\"default\":false},\"stream_options\":{\"anyOf\":[{\"$ref\":\"#/components/schemas/StreamOptions\"},{\"type\":\"null\"}],\"description\":\"Options for streaming response.\",\"nullable\":true},\"max_tokens\":{\"type\":\"integer\",\"maximum\":1024,\"minimum\":1,\"format\":\"int32\",\"title\":\"Max Tokens\",\"description\":\"The maximum number of tokens to generate in any given call.\",\"examples\":[512]},\"temperature\":{\"type\":\"number\",\"maximum\":1,\"minimum\":0,\"title\":\"Temperature\",\"description\":\"The sampling temperature to use for text generation. The higher the temperature value is, the less deterministic the output text will be.\",\"examples\":[0.2]},\"top_p\":{\"type\":\"number\",\"maximum\":1,\"minimum\":0,\"title\":\"Top P\",\"description\":\"The top-p sampling mass used for text generation. The top-p value determines the probability mass that is sampled at sampling time.\",\"examples\":[1]},\"top_k\":{\"type\":\"number\",\"maximum\":1000,\"minimum\":1,\"title\":\"Top K\",\"description\":\"The number of highest probability vocabulary tokens to keep for top-k-filtering\",\"examples\":[100]},\"seed\":{\"type\":\"integer\",\"maximum\":4294967295,\"minimum\":1,\"format\":\"int64\",\"title\":\"Seed\",\"description\":\"Seed value\",\"examples\":[10]},\"chunk_duration\":{\"type\":\"integer\",\"maximum\":3600,\"minimum\":0,\"format\":\"int32\",\"title\":\"Chunk Duration\",\"description\":\"Chunk videos into `chunkDuration` seconds. Set `0` for no chunking\",\"default\":0,\"examples\":[60]},\"chunk_overlap_duration\":{\"type\":\"integer\",\"maximum\":3600,\"minimum\":0,\"format\":\"int32\",\"title\":\"Chunk Overlap Duration\",\"description\":\"Chunk Overlap Duration Time in Seconds. Set `0` for no overlap\",\"default\":0,\"examples\":[10]},\"summary_duration\":{\"type\":\"integer\",\"maximum\":3600,\"minimum\":0,\"format\":\"int32\",\"title\":\"Summary Duration\",\"description\":\"Summarize every `summaryDuration` seconds of the video. Applicable to live streams only.\",\"default\":0,\"examples\":[60]},\"media_info\":{\"anyOf\":[{\"$ref\":\"#/components/schemas/MediaInfoOffset\"},{\"$ref\":\"#/components/schemas/MediaInfoTimeStamp\"}],\"title\":\"Media Info\",\"description\":\"Provide Start and End times offsets for processing part of a video file. Not applicable for live-streaming.\"},\"user\":{\"type\":\"string\",\"maxLength\":256,\"pattern\":\"^[a-zA-Z0-9-._]*$\",\"title\":\"User\",\"description\":\"A unique identifier for the user\",\"default\":\"\",\"examples\":[\"user-123\"]}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"id\",\"messages\",\"model\"],\"title\":\"ChatCompletionQuery\",\"description\":\"A chat completion query.\"},\"ChatCompletionResponseMessage\":{\"properties\":{\"content\":{\"type\":\"string\",\"maxLength\":100000,\"pattern\":\"^(.|\\\\n)*$\",\"title\":\"Content\",\"description\":\"The contents of the message.\",\"examples\":[\"Some summary of the video\"],\"nullable\":true},\"tool_calls\":{\"items\":{\"$ref\":\"#/components/schemas/ChatCompletionMessageToolCall\"},\"type\":\"array\",\"maxItems\":100,\"title\":\"Tool Calls\",\"default\":[]},\"role\":{\"type\":\"string\",\"enum\":[\"assistant\"],\"title\":\"Role\",\"description\":\"The role of the author of this message.\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"content\",\"role\"],\"title\":\"ChatCompletionResponseMessage\",\"description\":\"A chat completion message generated by the model.\"},\"ChatCompletionTool\":{\"properties\":{\"type\":{\"allOf\":[{\"$ref\":\"#/components/schemas/ChatCompletionToolType\"}],\"description\":\"The type of the tool. Currently, only `alert` is supported.\"},\"alert\":{\"$ref\":\"#/components/schemas/AlertTool\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"type\",\"alert\"],\"title\":\"ChatCompletionTool\",\"description\":\"Configuration of the tool to be used as part of the request.\"},\"ChatCompletionToolType\":{\"type\":\"string\",\"enum\":[\"alert\"],\"title\":\"ChatCompletionToolType\",\"description\":\"Types of tools supported by VIA.\"},\"ChatMessage\":{\"properties\":{\"content\":{\"type\":\"string\",\"maxLength\":256,\"pattern\":\"^[\\\\x00-\\\\x7F]*$\",\"title\":\"Content\",\"description\":\"The type of the message. eg: string\"},\"role\":{\"type\":\"string\",\"enum\":[\"system\",\"user\",\"assistant\"],\"title\":\"Role\",\"description\":\"The role of the author of this message.\"},\"name\":{\"type\":\"string\",\"maxLength\":256,\"pattern\":\"^[\\\\x00-\\\\x7F]*$\",\"title\":\"Name\",\"description\":\"The content of this message.\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"content\",\"role\",\"name\"],\"title\":\"ChatMessage\",\"description\":\"A chatbot chat message object. This object uniquely identify\\na query/response/other messages in a chatbot.\"},\"CompletionFinishReason\":{\"type\":\"string\",\"enum\":[\"stop\",\"length\",\"content_filter\",\"tool_calls\"],\"title\":\"CompletionFinishReason\",\"description\":\"The reason the model stopped generating tokens.\"},\"CompletionObject\":{\"type\":\"string\",\"enum\":[\"chat.completion\",\"summarization.completion\",\"summarization.progressing\"],\"title\":\"CompletionObject\",\"description\":\"Completion object type.\"},\"CompletionResponse\":{\"properties\":{\"id\":{\"type\":\"string\",\"format\":\"uuid\",\"title\":\"Id\",\"description\":\"Unique ID for the query\",\"maxLength\":36,\"minLength\":36},\"choices\":{\"items\":{\"$ref\":\"#/components/schemas/CompletionResponseChoice\"},\"type\":\"array\",\"maxItems\":10,\"title\":\"Choices\",\"description\":\"A list of chat completion choices. Can be more than one if `n` is greater than 1.\"},\"created\":{\"type\":\"integer\",\"maximum\":4000000000,\"minimum\":0,\"format\":\"int64\",\"title\":\"Created\",\"description\":\"The Unix timestamp (in seconds) of when the chat completion/summary request was created.\",\"examples\":[1717405636]},\"model\":{\"type\":\"string\",\"maxLength\":256,\"pattern\":\"^[A-Za-z0-9_.\\\\-]*$\",\"title\":\"Model\",\"description\":\"The model used for the chat completion/summarization.\",\"examples\":[\"vita-2.0\"]},\"media_info\":{\"anyOf\":[{\"$ref\":\"#/components/schemas/MediaInfoTimeStamp\"},{\"$ref\":\"#/components/schemas/MediaInfoOffset\"}],\"title\":\"Media Info\",\"description\":\"Part of the file / live-stream for which this response is applicable.\"},\"object\":{\"allOf\":[{\"$ref\":\"#/components/schemas/CompletionObject\"}],\"description\":\"The object type, which can be `chat.completion` or `summarization.completion` or `summarization.progressing`.\",\"examples\":[\"summarization.completion\"]},\"usage\":{\"anyOf\":[{\"$ref\":\"#/components/schemas/CompletionUsage\"},{\"type\":\"null\"}]}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"id\",\"choices\",\"created\",\"model\",\"media_info\",\"object\"],\"title\":\"CompletionResponse\",\"description\":\"Represents a summarization/chat completion response.\"},\"CompletionResponseChoice\":{\"properties\":{\"finish_reason\":{\"allOf\":[{\"$ref\":\"#/components/schemas/CompletionFinishReason\"}],\"description\":\"The reason the model stopped generating tokens. This will be `stop` if the model hit a natural stop point or a provided stop sequence,\\n`length` if the maximum number of tokens specified in the request was reached,\\n`content_filter` if content was omitted due to a flag from our content filters.\",\"examples\":[\"stop\"]},\"index\":{\"type\":\"integer\",\"maximum\":4000000000,\"minimum\":0,\"format\":\"int64\",\"title\":\"Index\",\"description\":\"The index of the choice in the list of choices.\",\"examples\":[1]},\"message\":{\"$ref\":\"#/components/schemas/ChatCompletionResponseMessage\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"finish_reason\",\"index\",\"message\"],\"title\":\"CompletionResponseChoice\",\"description\":\"Completion Response Choice.\"},\"CompletionUsage\":{\"properties\":{\"query_processing_time\":{\"type\":\"integer\",\"maximum\":1000000,\"minimum\":0,\"format\":\"int32\",\"title\":\"Query Processing Time\",\"description\":\"Summarization Query Processing Time in seconds.\",\"examples\":[78]},\"total_chunks_processed\":{\"type\":\"integer\",\"maximum\":1000000,\"minimum\":0,\"format\":\"int32\",\"title\":\"Total Chunks Processed\",\"description\":\"Total Number of chunks processed.\",\"examples\":[10]}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"query_processing_time\",\"total_chunks_processed\"],\"title\":\"CompletionUsage\",\"description\":\"An optional field that will only be present when you set\\n`stream_options: {\\\"include_usage\\\": true}` in your request.\\n\\nWhen present, it contains a null value except for the last chunk which contains\\nthe token usage statistics for the entire request.\"},\"DeleteFileResponse\":{\"properties\":{\"id\":{\"type\":\"string\",\"format\":\"uuid\",\"title\":\"Id\",\"description\":\"The file identifier, which can be referenced in the API endpoints.\",\"maxLength\":36,\"minLength\":36},\"object\":{\"type\":\"string\",\"enum\":[\"file\"],\"title\":\"Object\",\"description\":\"Type of response object.\"},\"deleted\":{\"type\":\"boolean\",\"title\":\"Deleted\",\"description\":\"Indicates if the file was deleted\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"id\",\"object\",\"deleted\"],\"title\":\"DeleteFileResponse\",\"description\":\"Response schema for delete file request.\"},\"FileInfo\":{\"properties\":{\"id\":{\"type\":\"string\",\"format\":\"uuid\",\"title\":\"Id\",\"description\":\"The file identifier, which can be referenced in the API endpoints.\",\"maxLength\":36,\"minLength\":36},\"bytes\":{\"type\":\"integer\",\"maximum\":100000000000,\"minimum\":0,\"format\":\"int64\",\"title\":\"Bytes\",\"description\":\"The size of the file, in bytes.\",\"examples\":[2000000]},\"filename\":{\"type\":\"string\",\"maxLength\":256,\"pattern\":\"^[A-Za-z0-9_.\\\\-]*$\",\"title\":\"Filename\",\"description\":\"Filename along with path to be used.\",\"examples\":[\"myfile.mp4\"]},\"purpose\":{\"allOf\":[{\"$ref\":\"#/components/schemas/Purpose\"}],\"description\":\"The intended purpose of the uploaded file. For VIA use-case this must be set to vision\",\"examples\":[\"vision\"]}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"id\",\"bytes\",\"filename\",\"purpose\"],\"title\":\"FileInfo\",\"description\":\"Information about an uploaded file.\"},\"ListFilesResponse\":{\"properties\":{\"data\":{\"items\":{\"$ref\":\"#/components/schemas/AddFileInfoResponse\"},\"type\":\"array\",\"maxItems\":100,\"title\":\"Data\"},\"object\":{\"type\":\"string\",\"enum\":[\"list\"],\"title\":\"Object\",\"description\":\"Type of response object\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"data\",\"object\"],\"title\":\"ListFilesResponse\",\"description\":\"Response schema for the list files API.\"},\"ListModelsResponse\":{\"properties\":{\"object\":{\"type\":\"string\",\"enum\":[\"list\"],\"title\":\"Object\",\"description\":\"Type of response object\"},\"data\":{\"items\":{\"$ref\":\"#/components/schemas/ModelInfo\"},\"type\":\"array\",\"maxItems\":5,\"title\":\"Data\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"object\",\"data\"],\"title\":\"ListModelsResponse\",\"description\":\"Lists and describes the various models available.\"},\"LiveStreamInfo\":{\"properties\":{\"id\":{\"type\":\"string\",\"format\":\"uuid\",\"title\":\"Id\",\"description\":\"Unique identifier for the live stream\",\"maxLength\":36,\"minLength\":36},\"liveStreamUrl\":{\"type\":\"string\",\"maxLength\":256,\"pattern\":\"^rtsp://\",\"title\":\"Livestreamurl\",\"description\":\"Live stream RTSP URL\",\"examples\":[\"rtsp://localhost:8554/media/video1\"]},\"description\":{\"type\":\"string\",\"maxLength\":256,\"pattern\":\"^[A-Za-z0-9_.\\\\-\\\"\\\\' ,]*$\",\"title\":\"Description\",\"description\":\"Description of live stream\",\"examples\":[\"Description of live stream\"]},\"chunk_duration\":{\"type\":\"integer\",\"maximum\":600,\"minimum\":0,\"format\":\"int32\",\"title\":\"Chunk Duration\",\"description\":\"Chunk Duration Time in Seconds. Chunks would be created at the I-Frame boundry so duration might not be exact.\",\"examples\":[60]},\"chunk_overlap_duration\":{\"type\":\"integer\",\"maximum\":600,\"minimum\":0,\"format\":\"int32\",\"title\":\"Chunk Overlap Duration\",\"description\":\"Chunk Overlap Duration Time in Seconds. Chunks would be created at the I-Frame boundry so duration might not be exact.\",\"examples\":[10]},\"summary_duration\":{\"type\":\"integer\",\"maximum\":3600,\"minimum\":0,\"format\":\"int32\",\"title\":\"Summary Duration\",\"description\":\"Summary Duration in Seconds.\",\"examples\":[300]}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"id\",\"liveStreamUrl\",\"description\",\"chunk_duration\",\"chunk_overlap_duration\",\"summary_duration\"],\"title\":\"LiveStreamInfo\",\"description\":\"Live Stream Information.\"},\"MediaInfoOffset\":{\"properties\":{\"type\":{\"type\":\"string\",\"enum\":[\"offset\"],\"title\":\"Type\",\"description\":\"Information about a segment of media with start and end offsets.\"},\"start_offset\":{\"type\":\"integer\",\"maximum\":4000000000,\"minimum\":0,\"format\":\"int64\",\"title\":\"Start Offset\",\"description\":\"Segment start offset in seconds from the beginning of the media.\",\"examples\":[0]},\"end_offset\":{\"type\":\"integer\",\"maximum\":4000000000,\"minimum\":0,\"format\":\"int64\",\"title\":\"End Offset\",\"description\":\"Segment end offset in seconds from the beginning of the media.\",\"examples\":[4000000000]}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"type\"],\"title\":\"MediaInfoOffset\",\"description\":\"Media information using offset for files.\"},\"MediaInfoTimeStamp\":{\"properties\":{\"type\":{\"type\":\"string\",\"enum\":[\"timestamp\"],\"title\":\"Type\",\"description\":\"Information about a segment of live-stream with start and end timestamp.\"},\"start_timestamp\":{\"type\":\"string\",\"maxLength\":24,\"minLength\":24,\"pattern\":\"^(\\\\d{4})-(\\\\d{2})-(\\\\d{2})T(\\\\d{2}):(\\\\d{2}):(\\\\d{2})(\\\\.\\\\d{3})Z$\",\"title\":\"Start Timestamp\",\"description\":\"Timestamp in the video to start processing from\",\"examples\":[\"2024-05-30T01:41:25.000Z\"]},\"end_timestamp\":{\"type\":\"string\",\"maxLength\":24,\"minLength\":24,\"pattern\":\"^(\\\\d{4})-(\\\\d{2})-(\\\\d{2})T(\\\\d{2}):(\\\\d{2}):(\\\\d{2})(\\\\.\\\\d{3})Z$\",\"title\":\"End Timestamp\",\"description\":\"Timestamp in the video to stop processing at\",\"examples\":[\"2024-05-30T02:14:51.000Z\"]}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"type\"],\"title\":\"MediaInfoTimeStamp\",\"description\":\"Media information using offset for live-streams.\"},\"MediaType\":{\"type\":\"string\",\"enum\":[\"video\",\"image\"],\"title\":\"MediaType\",\"description\":\"Media type of the uploaded file.\"},\"ModelInfo\":{\"properties\":{\"id\":{\"type\":\"string\",\"maxLength\":2560,\"pattern\":\"^[A-Za-z0-9_.\\\\-]*$\",\"title\":\"Id\",\"description\":\"The model identifier, which can be referenced in the API endpoints.\"},\"created\":{\"type\":\"integer\",\"maximum\":4000000000,\"minimum\":0,\"format\":\"int64\",\"title\":\"Created\",\"description\":\"The Unix timestamp (in seconds) when the model was created.\",\"examples\":[1686935002]},\"object\":{\"type\":\"string\",\"enum\":[\"model\"],\"title\":\"Object\",\"description\":\"Type of object\"},\"owned_by\":{\"type\":\"string\",\"maxLength\":10000,\"pattern\":\"^[A-Za-z0-9_.\\\\-\\\"\\\\' ,]*$\",\"title\":\"Owned By\",\"description\":\"The organization that owns the model.\",\"examples\":[\"NVIDIA\"]},\"api_type\":{\"type\":\"string\",\"maxLength\":32,\"pattern\":\"^[A-Za-z]*$\",\"title\":\"Api Type\",\"description\":\"API used to access model.\",\"examples\":[\"internal\"]}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"id\",\"created\",\"object\",\"owned_by\",\"api_type\"],\"title\":\"ModelInfo\",\"description\":\"Describes an OpenAI model offering that can be used with the API.\"},\"Purpose\":{\"type\":\"string\",\"enum\":[\"vision\"],\"title\":\"Purpose\",\"description\":\"Purpose for the file.\"},\"RecommendedConfig\":{\"properties\":{\"video_length\":{\"type\":\"integer\",\"maximum\":864000000,\"minimum\":1,\"format\":\"int32\",\"title\":\"Video Length\",\"description\":\"The video length in seconds.\",\"examples\":[5,10,60,300]},\"target_response_time\":{\"type\":\"integer\",\"maximum\":86400,\"minimum\":1,\"format\":\"int32\",\"title\":\"Target Response Time\",\"description\":\"The target response time of VIA in seconds.\",\"examples\":[5,10,60,300]},\"usecase_event_duration\":{\"type\":\"integer\",\"maximum\":86400,\"minimum\":1,\"format\":\"int32\",\"title\":\"Usecase Event Duration\",\"description\":\"The duration of the target event user wants to detect; example: it will take a box-falling event 3 seconds to happen.\",\"examples\":[5,10,60,300]}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"RecommendedConfig\",\"description\":\"Recommended VIA Config.\"},\"RecommendedConfigResponse\":{\"properties\":{\"chunk_size\":{\"type\":\"integer\",\"maximum\":86400,\"minimum\":1,\"format\":\"int32\",\"title\":\"Chunk Size\",\"description\":\"The recommended chunk size.\",\"examples\":[5,10,60,300]},\"text\":{\"type\":\"string\",\"maxLength\":5000,\"pattern\":\"^[A-Za-z0-9_.\\\\-\\\"\\\\' ,]*$\",\"title\":\"Text\",\"description\":\"Recommendation text\",\"examples\":[\"Recommendation text\"]}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"text\"],\"title\":\"RecommendedConfigResponse\",\"description\":\"Recommended VIA Config Response.\"},\"ResponseFormat\":{\"properties\":{\"type\":{\"allOf\":[{\"$ref\":\"#/components/schemas/ResponseType\"}],\"description\":\"Response format type\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"type\"],\"title\":\"ResponseFormat\",\"description\":\"Query Response Format Object.\"},\"ResponseType\":{\"type\":\"string\",\"enum\":[\"json_object\",\"text\"],\"title\":\"ResponseType\",\"description\":\"Query Response Type.\"},\"StreamOptions\":{\"properties\":{\"include_usage\":{\"type\":\"boolean\",\"title\":\"Include Usage\",\"description\":\"If set, an additional chunk will be streamed before the `data: [DONE]` message. The `usage` field on this chunk shows the token usage statistics for the entire request, and the `choices` field will always be an empty array. All other chunks will also include a `usage` field, but with a null value.\",\"default\":false}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"StreamOptions\",\"description\":\"Options for streaming response.\"},\"SummarizationQuery\":{\"properties\":{\"id\":{\"anyOf\":[{\"type\":\"string\",\"format\":\"uuid\",\"maxLength\":36,\"minLength\":36},{\"items\":{\"type\":\"string\",\"format\":\"uuid\",\"maxLength\":36,\"minLength\":36},\"type\":\"array\",\"maxItems\":50}],\"title\":\"Id\",\"description\":\"Unique ID or list of IDs of the file(s)/live-stream(s) to summarize\"},\"prompt\":{\"type\":\"string\",\"maxLength\":5000,\"pattern\":\"^(.|\\\\n)*$\",\"title\":\"Prompt\",\"description\":\"Prompt for summary generation\",\"default\":\"\",\"examples\":[\"Write a concise and clear dense caption for the provided warehouse video\"]},\"model\":{\"type\":\"string\",\"maxLength\":256,\"pattern\":\"^[A-Za-z0-9_.\\\\-]*$\",\"title\":\"Model\",\"description\":\"Model to use for this query.\",\"examples\":[\"vita-2.0\"]},\"api_type\":{\"type\":\"string\",\"maxLength\":32,\"pattern\":\"^[A-Za-z]*$\",\"title\":\"Api Type\",\"description\":\"API used to access model.\",\"default\":\"\",\"examples\":[\"internal\"]},\"response_format\":{\"allOf\":[{\"$ref\":\"#/components/schemas/ResponseFormat\"}],\"description\":\"An object specifying the format that the model must output.\",\"default\":{\"type\":\"text\"}},\"stream\":{\"type\":\"boolean\",\"title\":\"Stream\",\"description\":\"If set, partial message deltas will be sent, like in ChatGPT. Tokens will be sent as data-only [server-sent events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format) as they become available, with the stream terminated by a `data: [DONE]` message.\",\"default\":false},\"stream_options\":{\"anyOf\":[{\"$ref\":\"#/components/schemas/StreamOptions\"},{\"type\":\"null\"}],\"description\":\"Options for streaming response.\",\"nullable\":true},\"max_tokens\":{\"type\":\"integer\",\"maximum\":1024,\"minimum\":1,\"format\":\"int32\",\"title\":\"Max Tokens\",\"description\":\"The maximum number of tokens to generate in any given call.\",\"examples\":[512]},\"temperature\":{\"type\":\"number\",\"maximum\":1,\"minimum\":0,\"title\":\"Temperature\",\"description\":\"The sampling temperature to use for text generation. The higher the temperature value is, the less deterministic the output text will be.\",\"examples\":[0.2]},\"top_p\":{\"type\":\"number\",\"maximum\":1,\"minimum\":0,\"title\":\"Top P\",\"description\":\"The top-p sampling mass used for text generation. The top-p value determines the probability mass that is sampled at sampling time.\",\"examples\":[1]},\"top_k\":{\"type\":\"number\",\"maximum\":1000,\"minimum\":1,\"title\":\"Top K\",\"description\":\"The number of highest probability vocabulary tokens to keep for top-k-filtering\",\"examples\":[100]},\"seed\":{\"type\":\"integer\",\"maximum\":4294967295,\"minimum\":1,\"format\":\"int64\",\"title\":\"Seed\",\"description\":\"Seed value\",\"examples\":[10]},\"chunk_duration\":{\"type\":\"integer\",\"maximum\":3600,\"minimum\":0,\"format\":\"int32\",\"title\":\"Chunk Duration\",\"description\":\"Chunk videos into `chunkDuration` seconds. Set `0` for no chunking\",\"default\":0,\"examples\":[60]},\"chunk_overlap_duration\":{\"type\":\"integer\",\"maximum\":3600,\"minimum\":0,\"format\":\"int32\",\"title\":\"Chunk Overlap Duration\",\"description\":\"Chunk Overlap Duration Time in Seconds. Set `0` for no overlap\",\"default\":0,\"examples\":[10]},\"summary_duration\":{\"type\":\"integer\",\"maximum\":3600,\"minimum\":0,\"format\":\"int32\",\"title\":\"Summary Duration\",\"description\":\"Summarize every `summaryDuration` seconds of the video. Applicable to live streams only.\",\"default\":0,\"examples\":[60]},\"media_info\":{\"anyOf\":[{\"$ref\":\"#/components/schemas/MediaInfoOffset\"},{\"$ref\":\"#/components/schemas/MediaInfoTimeStamp\"}],\"title\":\"Media Info\",\"description\":\"Provide Start and End times offsets for processing part of a video file. Not applicable for live-streaming.\"},\"user\":{\"type\":\"string\",\"maxLength\":256,\"pattern\":\"^[a-zA-Z0-9-._]*$\",\"title\":\"User\",\"description\":\"A unique identifier for the user\",\"default\":\"\",\"examples\":[\"user-123\"]},\"tools\":{\"items\":{\"$ref\":\"#/components/schemas/ChatCompletionTool\"},\"type\":\"array\",\"maxItems\":100,\"title\":\"Tools\",\"description\":\"List of tools for the current summarization request\",\"default\":[]},\"summarize\":{\"type\":\"boolean\",\"title\":\"Summarize\",\"description\":\"Enable summarization for the group of chunks\",\"default\":true},\"enable_chat\":{\"type\":\"boolean\",\"title\":\"Enable Chat\",\"description\":\"Enable chat Question \u0026 Answers on the input media\",\"default\":false}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"id\",\"model\"],\"title\":\"SummarizationQuery\",\"description\":\"Summarization Query Request Fields.\"},\"ViaError\":{\"properties\":{\"code\":{\"type\":\"string\",\"maxLength\":128,\"pattern\":\"^[A-Za-z]*$\",\"title\":\"Code\",\"description\":\"Error code\",\"examples\":[\"ErrorCode\"]},\"message\":{\"type\":\"string\",\"maxLength\":1024,\"pattern\":\"^[A-Za-z\\\\-. ,_\\\"\\\\']*$\",\"title\":\"Message\",\"description\":\"Detailed error message\",\"examples\":[\"Detailed error message\"]}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"code\",\"message\"],\"title\":\"ViaError\",\"description\":\"VIA Error Information.\"}},\"securitySchemes\":{\"Token\":{\"type\":\"http\",\"scheme\":\"bearer\"}}},\"tags\":[{\"name\":\"Alerts\",\"description\":\"Operations to configure live stream alerts.\"},{\"name\":\"Files\",\"description\":\"Files are used to upload and manage media files.\"},{\"name\":\"Health Check\",\"description\":\"Operations to check system health.\"},{\"name\":\"Live Stream\",\"description\":\"Operations related to live streams.\"},{\"name\":\"Metrics\",\"description\":\"Operations to get metrics.\"},{\"name\":\"Models\",\"description\":\"List and describe the various models available in the API.\"},{\"name\":\"Recommended Config\",\"description\":\"Operations related to querying recommended VIA request parameters.\"},{\"name\":\"Summarization\",\"description\":\"Operations related to video summarization.\"}],\"security\":[{\"Token\":[]}]},\"namespace\":\"qc69jvmznzxy\",\"updatedDate\":\"2024-11-04T21:29:27.623Z\",\"nvcfFunctionId\":\"2bf1257d-39a6-4f67-a1f4-c9a790abe540\",\"createdDate\":\"2024-11-04T19:47:56.009Z\",\"attributes\":{\"showUnavailableBanner\":false,\"apiDocsUrl\":\"NOT REQUIRED\",\"termsOfUse\":\"GOVERNING TERMS: This trial is governed by the \u003ca href=\\\"https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA API Trial Terms of Service\u003c/a\u003e. NVIDIA Retrieval QA Mistral 4B Reranking: Apache license; NVIDIA Retrieval QA E5 Embedding v5: NV-EmbedQA-E5-v5: MIT license; NV-EmbedQA-Mistral7B-v2: Apache 2.0 license, and Snowflake arctic-embed-l: Apache 2.0 license - The use of these models is governed by the \u003ca href=\\\"https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-community-models-license/\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eAI Foundation Models Community License Agreement\u003c/a\u003e. ADDITIONAL INFORMATION: \u003ca href=\\\"https://www.llama.com/llama3_1/license/\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eLlama 3.1 Community License Agreement, Built with Llama\u003c/a\u003e\\n\",\"cta\":{\"text\":\"Apply for Early Access\",\"url\":\"https://developer.nvidia.com/ai-blueprint-for-video-search-and-summarization-early-access/join\"}},\"artifactName\":\"video-search-and-summarization\"},\"config\":{\"name\":\"video-search-and-summarization\",\"type\":\"blueprint\"}},{\"endpoint\":{\"requestStatus\":{\"statusCode\":\"SUCCESS\",\"requestId\":\"9dff8ed1-5d89-415c-b95d-09b1d9a91d3d\"},\"artifact\":{\"orgName\":\"qc69jvmznzxy\",\"labels\":[\"Agent Blueprint\",\"Customer Service\",\"Retrieval-augmented generation\",\"contact center\",\"llm\"],\"logo\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/ai-virtual-assistant-for-customer-service.jpg\",\"shortDescription\":\"Create intelligent virtual assistants for customer service across every industry\",\"isReadOnly\":true,\"description\":\"$67\",\"canGuestDownload\":true,\"isPublic\":true,\"createdDate\":\"2024-10-24T03:46:59.116Z\",\"publisher\":\"nvidia\",\"displayName\":\"Build an AI Virtual Assistant\",\"name\":\"ai-virtual-assistant-for-customer-service\",\"updatedDate\":\"2024-11-18T22:01:48.699Z\",\"attributes\":[{\"key\":\"NIM\",\"value\":\"llama-3_1-70b-instruct,nv-rerankqa-mistral-4b-v3,nv-embedqa-e5-v5\"},{\"key\":\"PREVIEW\",\"value\":\"false\"}],\"artifactType\":\"ENDPOINT\"}},\"spec\":{\"openAPISpec\":{\"openapi\":\"3.1.0\",\"info\":{\"title\":\"AI Virtual Assistant for Customer Service\",\"description\":\"This API schema describes all the endpoints exposed by the AI Virtual Assistant for Customer Service NIM Blueprint\",\"version\":\"1.0.0\"},\"paths\":{\"/agent/metrics\":{\"get\":{\"tags\":[\"Health\"],\"summary\":\"Get Metrics\",\"operationId\":\"get_metrics_agent_metrics_get\",\"responses\":{\"200\":{\"description\":\"Successful Response\",\"content\":{\"application/json\":{\"schema\":{}}}}}}},\"/agent/health\":{\"get\":{\"tags\":[\"Health\"],\"summary\":\"Health Check\",\"description\":\"Perform a Health Check\\n\\nReturns 200 when service is up. This does not check the health of downstream services.\",\"operationId\":\"health_check_agent_health_get\",\"responses\":{\"200\":{\"description\":\"Successful Response\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/HealthResponse\"}}}},\"500\":{\"description\":\"Internal Server Error\",\"content\":{\"application/json\":{\"example\":{\"detail\":\"Internal server error occurred\"}}}}}}},\"/agent/generate\":{\"post\":{\"tags\":[\"Agent\"],\"summary\":\"Generate Response\",\"description\":\"Generate and stream the response to the provided prompt.\",\"operationId\":\"generate_response_agent_generate_post\",\"requestBody\":{\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/AgentRequest\"}}},\"required\":true},\"responses\":{\"200\":{\"description\":\"Successful Response\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/AgentResponse\"}}}},\"422\":{\"description\":\"Validation Error\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/HTTPValidationError\"}}}},\"500\":{\"description\":\"Internal Server Error\",\"content\":{\"application/json\":{\"example\":{\"detail\":\"Internal server error occurred\"}}}}},\"x-nvai-meta\":{\"examples\":[{\"name\":\"What was my last purchase?\",\"requestJson\":\"{\\n \\\"user\\\": \\\"1\\\", \\\"api_type\\\": \\\"create_session\\\", \\\"messages\\\": [\\n {\\n \\\"role\\\": \\\"user\\\",\\n \\\"content\\\": \\\"What was my last purchase?\\\"\\n }\\n ],\\n \\\"stream\\\": true\\n}\\n\"},{\"name\":\"What product did I order first?\",\"requestJson\":\"{\\n \\\"user\\\": \\\"1\\\", \\\"api_type\\\": \\\"create_session\\\", \\\"messages\\\": [\\n {\\n \\\"role\\\": \\\"user\\\",\\n \\\"content\\\": \\\"What product did I order first?\\\"\\n }\\n ],\\n \\\"stream\\\": true\\n}\\n\"}]}}}},\"components\":{\"schemas\":{\"AgentRequest\":{\"properties\":{\"messages\":{\"anyOf\":[{\"items\":{\"$ref\":\"#/components/schemas/Message\"},\"type\":\"array\",\"maxItems\":50000},{\"type\":\"null\"}],\"title\":\"Messages\",\"description\":\"A list of messages comprising the conversation so far. The roles of the messages must be alternating between user and assistant. The last input message should have role user. 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Nemo Text Retriever E5 Embedding Model, MIT License; NVIDIA Retrieval QA Mistral 4B Reranking v3, Apache License - The use of these models is governed by the \u003ca href=\\\"https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-community-models-license/\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eAI Foundation Models Community License Agreement\u003c/a\u003e. 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The Llama 3.1 instruction tuned text only models (8B, 70B, 405B) are optimized for multilingual dialogue use cases and outperform many of the available open source and closed chat models on common industry benchmarks.\n\n**Model Developer**: Meta\n\n## Llama 3.1 Systems\n\n**Large language models, including Llama 3.1, are not designed to be deployed in isolation but instead should be deployed as part of an overall AI system with additional safety guardrails as required.** Developers are expected to deploy system safeguards when building agentic systems. Safeguards are key to achieve the right helpfulness-safety alignment as well as mitigating safety and security risks inherent to the system and any integration of the model or system with external tools. \nAs part of our responsible release approach, we provide the community with [safeguards](https://llama.meta.com/trust-and-safety/) that developers should deploy with Llama models or other LLMs, including Llama Guard 3, Prompt Guard and Code Shield. All our [reference implementations](https://github.com/meta-llama/llama-agentic-system) demos contain these safeguards by default so developers can benefit from system-level safety out-of-the-box.\n\n## Intended Use\n\n**Intended Use Cases** Llama 3.1 is intended for commercial and research use in multiple languages. Instruction tuned text only models are intended for assistant-like chat, whereas pretrained models can be adapted for a variety of natural language generation tasks. The Llama 3.1 model collection also supports the ability to leverage the outputs of its models to improve other models including synthetic data generation and distillation. The Llama 3.1 Community License allows for these use cases.\n\n**Out-of-scope** Use in any manner that violates applicable laws or regulations (including trade compliance laws). Use in any other way that is prohibited by the Acceptable Use Policy and Llama 3.1 Community License. Use in languages beyond those explicitly referenced as supported in this model card**. \n\n**Note: Llama 3.1 has been trained on a broader collection of languages than the 10 supported languages. \n\nDevelopers may fine-tune Llama 3.1 models for languages beyond the 8 supported languages provided they comply with the Llama 3.1 Community License and the Acceptable Use Policy and in such cases are responsible for ensuring that any uses of Llama 3.1 in additional languages is done in a safe and responsible manner.\n\n\n## New Capabilities\n\nNote that this release introduces new capabilities, including a longer context window, multilingual inputs and outputs and possible integrations by developers with third party tools. Building with these new capabilities requires specific considerations in addition to the best practices that generally apply across all Generative AI use cases. \n\n**Tool-use:** Just like in standard software development, developers are responsible for the integration of the LLM with the tools and services of their choice. They should define a clear policy for their use case and assess the integrity of the third party services they use to be aware of the safety and security limitations when using this capability. Refer to the Responsible Use Guide for best practices on the safe deployment of the third party safeguards. \n\n**Multilinguality:** Llama 3.1 supports 7 languages in addition to English: French, German, Hindi, Italian, Portuguese, Spanish, and Thai. Llama may be able to output text in other languages than those that meet performance thresholds for safety and helpfulness. We strongly discourage developers from using this model to converse in non-supported languages without implementing finetuning and system controls in alignment with their policies and the best practices shared in the Responsible Use Guide.\n\n**Model Architecture:** Llama 3.1 is an auto-regressive language model that uses an optimized transformer architecture. The tuned versions use supervised fine-tuning (SFT) and reinforcement learning with human feedback\n(RLHF) to align with human preferences for helpfulness and safety.\n\n| | Training Data | Params | Input modalities | Output modalities | Context Length | GQA | Token count | Knowledge cutoff |\n|-|-|-----------------------|----------------------------------------------|-----------------------|---------------------|-----------------------|-------|---------------|\n| | | 8B | Multilingual Text | Multilingual Text and code| 128k | Yes | 15T+ | December 2023 |\n| Llama 3.1 (text only) | A new mix of publicly available online data. | 70B | Multilingual Text | Multilingual Text and code| 128k | Yes | 15T+ | December 2023 |\n| | | 405B | Multilingual Text | Multilingual Text and code| 128k | Yes | 15T+ | December 2023 |\n\n**Supported languages:** English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai.\n\n**Llama 3.1 family of models**. Token counts refer to pretraining data only. All model versions use Grouped-Query Attention (GQA) for improved inference scalability.\n\n**Model Release Date:** July 23, 2024. \n\n**Status:** This is a static model trained on an offline dataset. Future versions of the tuned models will be released as we improve model safety with community feedback. \n\n**License** A custom commercial license, the Llama 3.1 Community License, is available at: https://github.com/meta-llama/llama-models/blob/main/models/llama3_1/LICENSE \n\nWhere to send questions or comments about the model Instructions on how to provide feedback or comments on the model can be found in the model [README](https://github.com/meta-llama/llama3). For more technical information about generation parameters and recipes for how to use Llama 3.1 in applications, please go [here](ttps://github.com/meta-llama/llama-recipes).\n\n## Hardware And Software\n\n**Training Factors** We used custom training libraries, Meta's custom built GPU cluster, and production infrastructure for pretraining. Fine-tuning, annotation, and evaluation were also performed on production infrastructure. \n\n**Training Energy Use** Training utilized a cumulative of **39.3**M GPU hours of computation on H100-80GB (TDP of 700W) type hardware, per the table below. Training time is the total GPU time required for training each model and power consumption is the peak power capacity per GPU device used, adjusted for power usage efficiency.\n\n**Training Greenhouse Gas Emissions** Estimated total location-based greenhouse gas emissions were **11,390** tons CO2eq for training. Since 2020, Meta has maintained net zero greenhouse gas emissions in its global operations and matched 100% of its electricity use with renewable energy, therefore the total market-based greenhouse gas emissions for training were 0 tons CO2eq.\n\n| | Training Time (GPU hours) | Training Power Consumption (W) | Training Location-Based Greenhouse Gas Emissions (tons CO2eq) | Training Market-Based Greenhouse Gas Emissions (tons CO2eq) |\n| - |---------------------------------------|---------------------------------------|---------------------------|--------|\n| Llama 3.1 8B | 1.46M | 700 | 420 | 0 |\n| Llama 3.1 70B | 7.0M | 700 | 2,040 | 0 |\n| Llama 3.1 405B | 30.84M | 700 | 8,930 | 0 |\n| Total | 39.3M | - | 11,390 | 0 |\n\nThe methodology used to determine training energy use and greenhouse gas emissions can be found [here](https://arxiv.org/pdf/2204.05149). Since Meta is openly releasing these models, the training energy use and greenhouse gas emissions will not be incurred by others.\n\n## Training Data\n\n**Overview:** Llama 3.1 was pretrained on ~15 trillion tokens of data from publicly available sources. The fine-tuning data includes publicly available instruction datasets, as well as over 25M synthetically generated examples.\n\n**Data Freshness:** The pretraining data has a cutoff of December 2023.\n\n## Benchmarks - English Text\n\nIn this section, we report the results for Llama 3.1 models on standard automatic benchmarks. For all the evaluations, we use our internal evaluations library.\n\n### Base pretrained models\n| Category | Benchmark | # Shots | Metric | Llama 3 8B | Llama 3.1 8B | Llama 3 70B | Llama 3.1 70B | Llama 3.1 405B |\n|--------------------------|---------------|--------------------|----------|------------|--------------|-------------|---------------|----------------|\n| General | MMLU | 5 | macro_avg/acc_char | 66.7 | 66.7 | 79.5 | 79.3 | 85.2 | |\n| General | MMLU PRO (CoT) | 5 | macro_avg/acc_char | 36.2 | 37.1 | 55.0 | 53.8 | 61.6 | |\n| General | AGIEval English | 3-5 | average/acc_char | 47.1 | 47.8 | 63.0 | 64.6 | 71.6 | |\n| General | CommonSenseQA | 7 | acc_char | 72.6 | 75.0 | 83.8 | 84.1 | 85.8 |\n| General | Winogrande | 5 | acc_char | - | 60.5 | - | 83.3 | 86.7 | |\n| General | BIG-Bench Hard (CoT) | 3 | average/em | 61.1 | 64.2 | 81.3 | 81.6 | **85.9** | |\n| General | ARC-Challenge | 25 | acc_char | 79.4 | 79.7 | 93.1 | 92.9 | 96.1 | |\n| Knowledge reasoning | TriviaQA-Wiki | 5 | em | 78.5 | 77.6 | 89.7 | 89.8 | 91.8 |\n| Reading comprehension | SQuAD | 1 | em | 76.4 | 77.0 | 85.6 | 81.8 | 89.3 | |\n| Reading comprehension | QuAC (F1) | 1 | f1 | 44.4 | 44.9 | 51.1 | 51.1 | 53.6 | |\n| Reading comprehension | BoolQ | 0 | acc_char | 75.7 | 75.0 | 79.0 | 79.4 | 80.0 |\n| Reading comprehension | DROP (F1) | 3 | f1 | 58.4 | 59.5 | 79.7 | 79.6 | **84.8** | |\n\n### Instruction Tuned Models\n\n\n| Category | Benchmark | # Shots | Metric | Llama 3 8B Instruct | Llama 3.1 8B Instruct | Llama 3 70B Instruct | Llama 3.1 70B Instruct | Llama 3.1 405B Instruct | \n| --- | --- | --- | --- | --- | --- | --- | --- | --- | \n | General | MMLU | 5 | macro_avg/acc | 68.5 | 69.4 | 82.0 | 83.6 | 87.3 | \n | General | MMLU (CoT) | 0 | macro_avg/acc | 65.3 | 72.7 | 80.9 | 85.9 | 88.6 | \n | General | MMLU PRO (CoT) | 5 | micro_avg/acc_char | 45.5 | 48.3 | 63.4 | 65.1 | 73.3 | \n | Reasoning | ARC-C | 0 | acc | 82.4 | 83.4 | 94.4 | 94.8 | **96.9** | \n | Reasoning | GPQA | 0 | em | 34.6 | 30.4 | 39.5 | 41.7 | 50.7 | \n | Reasoning | MuSR | 0 | correct | 56.3 | 45.7 | 55.1 | 58.1 | 56.7 | \n | Steerability | IFEval | | | 76.8 | 80.4 | 82.9 | 87.5 | **88.6** | \n | Code | HumanEval | 0 | pass@1 | 60.4 | 72.6 | 81.7 | 80.5 | 89.0 | \n | Code | MBPP ++ base version | 0 | pass@1 | 70.6 | 72.8 | 82.5 | 86.0 | 88.6 | \n | Math | GSM-8K (CoT) | 8 | em_maj1@1 | 80.6 | 84.5 | 93.0 | 95.1 | 96.8 | \n | Math | MATH (CoT) | 0 | final_em | 29.1 | 51.9 | 51.0 | 68.0 | 73.8 | \n | Tool Use | API-Bank | 0 | acc | 83.6 | 82.6 | 85.1 | 90.0 | 92.0 | \n | Tool Use | Berkeley Function Calling | 0 | acc | 76.1 | 76.1 | 83.0 | 85.1 | **88.5** |\n | Tool Use | Gorilla Benchmark API Bench | 0 | acc | 8.8 | 8.2 | 14.7 | 29.7 | 35.3 | \n | Tool Use | Nexus (0-shot) | 0 | macro_avg/acc | 37.6 | 38.5 | 47.8 | 56.7 | **58.7** | \n | Multilingual | Multilingual MGSM | 8 | em | - | 68.2 | - | 85.6 | 90.3 |\n\n## Multilingual Benchmarks\n\n| Category | Benchmark | Language | Llama 3.1 8B | Llama 3.1 70B | Llama 3.1 405B | \n| --- | --- | --- | --- | --- | --- | \n| | | Portuguese | 62.12 | 80.13 | 84.95 |\n| | | Spanish | 62.45 | 80.05 | 85.08 |\n| | | Italian | 61.63 | 80.4 | 85.04 | \n| General | MMLU (5-shot, macro_avg/acc) | German | 60.59 | 79.27 | 84.36 | \n| | | French | 62.34 | 79.82 | 84.66 | \n| | | Hindi | 50.88 | 74.52 | 80.31 | \n| | | Thai | 50.32 | 72.95 | 78.21 |\n\n\n\n## Responsibility \u0026 Safety\n\nAs part of our Responsible release approach, we followed a three-pronged strategy to managing trust \u0026 safety risks:\n- Enable developers to deploy helpful, safe and flexible experiences for their target audience and for the use cases supported by Llama.\n\n- Protect developers against adversarial users aiming to exploit Llama capabilities to potentially cause harm.\n\n- Provide protections for the community to help prevent the misuse of our models.\n\n## Responsible Deployment\n\nLlama is a foundational technology designed to be used in a variety of use cases, examples on how Meta's Llama models have been responsibly deployed can be found in our [Community Stories webpage](https://llama.meta.com/community-stories/). Our approach is to build the most helpful models enabling the world to benefit from the technology power, by aligning our model safety for the generic use cases addressing a standard set of harms. Developers are then in the driver seat to tailor safety for their use case, defining their own policy and deploying the models with the necessary safeguards in their Llama systems. Llama 3.1 was developed following the best practices outlined in our Responsible Use Guide, you can refer to the [Responsible Use Guide](https://llama.meta.com/responsible-use-guide/) to learn more.\n\n## Llama 3.1 Instruct\n\nOur main objectives for conducting safety fine-tuning are to provide the research community with a valuable resource for studying the robustness of safety fine-tuning, as well as to offer developers a readily available, safe, and powerful model for various applications to reduce the developer workload to deploy safe AI systems. For more details on the safety mitigations implemented please read the Llama 3 paper.\n\n### Fine-Tuning Data\n\nWe employ a multi-faceted approach to data collection, combining human-generated data from our vendors with synthetic data to mitigate potential safety risks. We've developed many large language model (LLM)-based classifiers that enable us to thoughtfully select high-quality prompts and responses, enhancing data quality control.\n\n### Refusals And Tone\n\nBuilding on the work we started with Llama 3, we put a great emphasis on model refusals to benign prompts as well as refusal tone. We included both borderline and adversarial prompts in our safety data strategy, and modified our safety data responses to follow tone guidelines.\n\n## Evaluations\n\nWe evaluated Llama models for common use cases as well as specific capabilities. Common use cases evaluations measure safety risks of systems for most commonly built applications including chat bot, coding assistant, tool calls. We built dedicated, adversarial evaluation datasets and evaluated systems composed of Llama models and Llama Guard 3 to filter input prompt and output response. It is important to evaluate applications in context, and we recommend building dedicated evaluation dataset for your use case. Prompt Guard and Code Shield are also available if relevant to the application. \n\nCapability evaluations measure vulnerabilities of Llama models inherent to specific capabilities, for which were crafted dedicated benchmarks including long context, multilingual, tools calls, coding or memorization.\n\n## Red Teaming\n\nFor both scenarios, we conducted recurring red teaming exercises with the goal of discovering risks via adversarial prompting and we used the learnings to improve our benchmarks and safety tuning datasets. We partnered early with subject-matter experts in critical risk areas to understand the nature of these real-world harms and how such models may lead to unintended harm for society. Based on these conversations, we derived a set of adversarial goals for the red team to attempt to achieve, such as extracting harmful information or reprogramming the model to act in a potentially harmful capacity. The red team consisted of experts in cybersecurity, adversarial machine learning, responsible AI, and integrity in addition to multilingual content specialists with background in integrity issues in specific geographic markets. .\n\n## Critical And Other Risks\n\nWe specifically focused our efforts on mitigating the following critical risk areas: \n\n ### 1- CBRNE (Chemical, Biological, Radiological, Nuclear, and Explosive materials) helpfulness\n To assess risks related to proliferation of chemical and biological weapons, we performed uplift testing designed to assess whether use of Llama 3.1 models could meaningfully increase the capabilities of malicious actors to plan or carry out attacks using these types of weapons.\n\n### 2. Child Safety\n\nChild Safety risk assessments were conducted using a team of experts, to assess the model's capability to produce outputs that could result in Child Safety risks and inform on any necessary and appropriate risk mitigations via fine tuning. We leveraged those expert red teaming sessions to expand the coverage of our evaluation benchmarks through Llama 3 model development. For Llama 3, we conducted new in-depth sessions using objective based methodologies to assess the model risks along multiple attack vectors including the additional languages Llama 3 is trained on. We also partnered with content specialists to perform red teaming exercises assessing potentially violating content while taking account of market specific nuances or experiences.\n\n### 3. Cyber Attack Enablement\n\nOur cyber attack uplift study investigated whether LLMs can enhance human capabilities in hacking tasks, both in terms of skill level and speed. Our attack automation study focused on evaluating the capabilities of LLMs when used as autonomous agents in cyber offensive operations, specifically in the context of ransomware attacks. This evaluation was distinct from previous studies that considered LLMs as interactive assistants. The primary objective was to assess whether these models could effectively function as independent agents in executing complex cyber-attacks without human intervention. Our study of Llama-3.1-405B's social engineering uplift for cyber attackers was conducted to assess the effectiveness of AI models in aiding cyber threat actors in spear phishing campaigns. Please read our Llama 3.1 Cyber security whitepaper to learn more.\n\n## Community\n\nGenerative AI safety requires expertise and tooling, and we believe in the strength of the open community to accelerate its progress. We are active members of open consortiums, including the AI Alliance, Partnership on AI and MLCommons, actively contributing to safety standardization and transparency. We encourage the community to adopt taxonomies like the MLCommons Proof of Concept evaluation to facilitate collaboration and transparency on safety and content evaluations. Our Purple Llama tools are open sourced for the community to use and widely distributed across ecosystem partners including cloud service providers. We encourage community contributions to our [Github repository](https://github.com/meta-llama/PurpleLlama). \n\nWe also set up the [Llama Impact Grants](https://llama.meta.com/llama-impact-grants/) program to identify and support the most compelling applications of Meta's Llama model for societal benefit across three categories: education, climate and open innovation. The 20 finalists from the hundreds of applications can be found [here](https://llama.meta.com/llama-impact-grants/#finalists). \nFinally, we put in place a set of resources including an [output reporting mechanism](https://developers.facebook.com/llama_output_feedback) and [bug bounty program](https://www.facebook.com/whitehat) to continuously improve the Llama technology with the help of the community.\n\n## Ethical Considerations And Limitations\n\nThe core values of Llama 3.1 are openness, inclusivity and helpfulness. It is meant to serve everyone, and to work for a wide range of use cases. It is thus designed to be accessible to people across many different backgrounds, experiences and perspectives. Llama 3.1 addresses users and their needs as they are, without insertion unnecessary judgment or normativity, while reflecting the understanding that even content that may appear problematic in some cases can serve valuable purposes in others. It respects the dignity and autonomy of all users, especially in terms of the values of free thought and expression that power innovation and progress. \n\nBut Llama 3.1 is a new technology, and like any new technology, there are risks associated with its use. Testing conducted to date has not covered, nor could it cover, all scenarios. For these reasons, as with all LLMs, Llama 3.1's potential outputs cannot be predicted in advance, and the model may in some instances produce inaccurate, biased or other objectionable responses to user prompts. Therefore, before deploying any applications of Llama 3.1 models, developers should perform safety testing and tuning tailored to their specific applications of the model. Please refer to available resources including our [Responsible Use Guide](https://llama.meta.com/responsible-use-guide), [Trust and Safety](https://llama.meta.com/trust-and-safety/) solutions, and other [resources](https://llama.meta.com/docs/get-started/) to learn more about responsible development."])</script><script>self.__next_f.push([1,"75:T8e5,"])</script><script>self.__next_f.push([1,"{\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"Tell me about Dumbledore.\"\n }\n ],\n \"model\": \"meta/llama-3.1-405b-instruct\",\n \"max_tokens\": 1024,\n \"stream\": true,\n \"tool_choice\": \"auto\",\n \"tools\": [\n {\n \"type\": \"function\",\n \"function\": {\n \"name\": \"describe_harry_potter_character\",\n \"description\": \"Returns information and images of Harry Potter characters.\",\n \"parameters\": {\n \"type\": \"object\",\n \"properties\": {\n \"name\": {\n \"type\": \"string\",\n \"enum\": [\n \"Harry James Potter\",\n \"Hermione Jean Granger\",\n \"Ron Weasley\",\n \"Fred Weasley\",\n \"George Weasley\",\n \"Bill Weasley\",\n \"Percy Weasley\",\n \"Charlie Weasley\",\n \"Ginny Weasley\",\n \"Molly Weasley\",\n \"Arthur Weasley\",\n \"Neville Longbottom\",\n \"Luna Lovegood\",\n \"Draco Malfoy\",\n \"Albus Percival Wulfric Brian Dumbledore\",\n \"Minerva McGonagall\",\n \"Remus Lupin\",\n \"Rubeus Hagrid\",\n \"Sirius Black\",\n \"Severus Snape\",\n \"Bellatrix Lestrange\",\n \"Lord Voldemort\",\n \"Cedric Diggory\",\n \"Nymphadora Tonks\",\n \"James Potter\"\n ],\n \"description\": \"Name of the Harry Potter character\"\n }\n },\n \"required\": [\n \"name\"\n ]\n }\n }\n }\n ]\n}\n"])</script><script>self.__next_f.push([1,"76:T537,{\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"What is the weather in Santa Clara, CA?\"\n }\n ],\n \"model\": \"meta/llama-3.1-405b-instruct\",\n \"max_tokens\": 1024,\n \"stream\": true,\n \"tool_choice\": \"auto\",\n \"tools\": [\n {\n \"type\": \"function\",\n \"function\": {\n \"name\": \"get_current_weather\",\n \"description\": \"A tool that gets the current weather at a location, if one is specified, and defaults to the user's location.\",\n \"parameters\": {\n \"type\": \"object\",\n \"properties\": {\n \"location\": {\n \"type\": \"string\",\n \"description\": \"The location to find the weather of, or if not provided, it's the default location.\"\n },\n \"unit\": {\n \"type\": \"string\",\n \"enum\": [\n \"u\",\n \"m\"\n ],\n \"description\": \"Whether to use SI or USCS units (celsius or fahrenheit). Infer this from the user's location.\"\n }\n }\n }\n }\n }\n ]\n}\n77:T4bd,from openai import OpenAI\n\nclient = OpenAI(\n base_url = \"https://integrate.api.nvidia.com/v1\",\n api_key = \"$NVIDIA_API_KEY\"\n)\n\u003c% if (request.tools) { %\u003e\ncompletion = client.chat.completions.create(\n model=\"\u003c%- request.model %\u003e\",\n messages=\u003c%- JSON.stringify(request.messages) %\u003e,\n temperature=\u003c%- request.temperature %\u003e,\n top_p=\u003c%- request.top_p %\u003e,\n max_tokens=\u003c%- request.max_tokens %\u003e,\n stream=\u003c%- request.stream?.toString()[0].toUpperCase() + request.stream?.toString().slice(1) %\u003e,\n tools=\u003c%- JSON.stringify(request.tools) %\u003e,\n \u003c% if (request.tool_choice) { %\u003etool_choice=\u003c%- JSON.stringify(request.tool_choice) %\u003e\u003c% } %\u003e\n)\u003c% } else { %\u003e\ncompletion = client.chat.completions.create("])</script><script>self.__next_f.push([1,"\n model=\"\u003c%- request.model %\u003e\",\n messages=\u003c%- JSON.stringify(request.messages) %\u003e,\n temperature=\u003c%- request.temperature %\u003e,\n top_p=\u003c%- request.top_p %\u003e,\n max_tokens=\u003c%- request.max_tokens %\u003e,\n stream=\u003c%- request.stream?.toString()[0].toUpperCase() + request.stream?.toString().slice(1) %\u003e\n)\u003c% } %\u003e\n\u003c% if (request.stream) { %\u003e\nfor chunk in completion:\n if chunk.choices[0].delta.content is not None:\n print(chunk.choices[0].delta.content, end=\"\")\n\u003c% } else { %\u003e\nprint(completion.choices[0].message)\n\u003c% } %\u003e\n78:T504,import OpenAI from 'openai';\n\nconst openai = new OpenAI({\n apiKey: '$NVIDIA_API_KEY',\n baseURL: 'https://integrate.api.nvidia.com/v1',\n})\n \u003c% if (request.tools) { %\u003e\nasync function main() {\n const completion = await openai.chat.completions.create({\n model: \"\u003c%- request.model %\u003e\",\n messages: \u003c%- JSON.stringify(request.messages) %\u003e,\n temperature: \u003c%- request.temperature %\u003e,\n top_p: \u003c%- request.top_p %\u003e,\n max_tokens: \u003c%- request.max_tokens %\u003e,\n stream: \u003c%- request.stream %\u003e,\n \u003c% if (request.tools) { %\u003etools: \u003c%- JSON.stringify(request.tools) %\u003e,\u003c% } %\u003e\n \u003c% if (request.tool_choice) { %\u003etool_choice: \u003c%- JSON.stringify(request.tool_choice) %\u003e,\u003c% } %\u003e\n })\u003c% } else { %\u003e\nasync function main() {\n const completion = await openai.chat.completions.create({\n model: \"\u003c%- request.model %\u003e\",\n messages: \u003c%- JSON.stringify(request.messages) %\u003e,\n temperature: \u003c%- request.temperature %\u003e,\n top_p: \u003c%- request.top_p %\u003e,\n max_tokens: \u003c%- request.max_tokens %\u003e,\n stream: \u003c%- request.stream %\u003e\n })\u003c% } %\u003e\n \u003c% if (request.stream) { %\u003e\n for await (const chunk of completion) {\n process.stdout.write(chunk.choices[0]?.delta?.content || '')\n }\n \u003c% } else { %\u003e\n process.stdout.write(completion.choices[0]?.message?.content);\n \u003c% } %\u003e\n}\n\nmain();79:T671,\u003c% if (request.tools) { %\u003e\n \"curl https://integrate.api.nvidia.com/v1/chat/completions \\\\\\n\n -H \\\"Content-Type: application/json\\\" \\\\\\n\n -H \\\"Authorization: Bearer $NVIDIA_API_KEY\\\" \\\\\\n\n -d '{\\n\n \\\"model\\\": \\\"meta/ll"])</script><script>self.__next_f.push([1,"ama-3.1-405b-instruct\\\",\\n\n \\\"messages\\\": \u003c%- JSON.stringify(request.messages).replaceAll(\\\"'\\\", \\\"'\\\\\\\"'\\\\\\\"'\\\") %\u003e,\\n\n \\\"temperature\\\": \u003c%- request.temperature %\u003e,\\n\n \\\"top_p\\\": \u003c%- request.top_p %\u003e,\\n\n \\\"max_tokens\\\": \u003c%- request.max_tokens %\u003e,\\n\n \\\"stream\\\": \u003c%- request.stream %\u003e\n \u003c% if (request.tools) { %\u003e,\\n \\\"tools\\\": \u003c%- JSON.stringify(request.tools).replaceAll(\\\"'\\\", \\\"'\\\\\\\"'\\\\\\\"'\\\") %\u003e\u003c% } %\u003e\n \u003c% if (request.tool_choice) { %\u003e,\\n \\\"tool_choice\\\": \u003c%- JSON.stringify(request.tool_choice).replaceAll(\\\"'\\\", \\\"'\\\\\\\"'\\\\\\\"'\\\") %\u003e\u003c% } %\u003e\n }'\\n\"\u003c% } else { %\u003e\n \"curl https://integrate.api.nvidia.com/v1/chat/completions \\\\\\n\n -H \\\"Content-Type: application/json\\\" \\\\\\n\n -H \\\"Authorization: Bearer $NVIDIA_API_KEY\\\" \\\\\\n\n -d '{\\n\n \\\"model\\\": \\\"meta/llama-3.1-405b-instruct\\\",\\n\n \\\"messages\\\": \u003c%- JSON.stringify(request.messages).replaceAll(\\\"'\\\", \\\"'\\\\\\\"'\\\\\\\"'\\\") %\u003e,\\n\n \\\"temperature\\\": \u003c%- request.temperature %\u003e,\\n\n \\\"top_p\\\": \u003c%- request.top_p %\u003e,\\n\n \\\"max_tokens\\\": \u003c%- request.max_tokens %\u003e,\\n\n \\\"stream\\\": \u003c%- request.stream %\u003e\n \u003c% if (request.tools) { %\u003e,\\n \\\"tools\\\": \u003c%- JSON.stringify(request.tools).replaceAll(\\\"'\\\", \\\"'\\\\\\\"'\\\\\\\"'\\\") %\u003e\u003c% } %\u003e\n \u003c% if (request.tool_choice) { %\u003e,\\n \\\"tool_choice\\\": \u003c%- JSON.stringify(request.tool_choice).replaceAll(\\\"'\\\", \\\"'\\\\\\\"'\\\\\\\"'\\\") %\u003e\u003c% } %\u003e\n }'\\n\"\u003c% } %\u003e7a:T9e3,"])</script><script>self.__next_f.push([1,"## Model Overview\n\n### Description:\n\nMixtral 8x7B Instruct is a language model that can follow instructions, complete requests, and generate creative text formats. Mixtral 8x7B a high-quality sparse mixture of experts model (SMoE) with open weights.\u003cbr\u003e\nThis model has been optimized through supervised fine-tuning and direct preference optimization (DPO) for careful instruction following. On MT-Bench, it reaches a score of 8.30, making it the best open-source model, with a performance comparable to GPT3.5.\u003cbr\u003e\nMixtral outperforms Llama 2 70B on most benchmarks with 6x faster inference. It is the strongest open-weight model with a permissive license and the best model overall regarding cost/performance trade-offs. In particular, it matches or outperforms GPT3.5 on most standard benchmarks.\u003cbr\u003e\nMixtral has the following capabilities.\n\n* It gracefully handles a context of 32k tokens.\n* It handles English, French, Italian, German and Spanish.\n* It shows strong performance in code generation.\n* It can be finetuned into an instruction-following model that achieves a score of 8.3 on MT-Bench.\n\n### Third-Party Community Consideration:\n\nThis model is not owned or developed by NVIDIA. This model has been developed and built to a third-party’s requirements for this application and use case; see [Mistral's 8x7B Instruct Hugging Face Model Card](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1).\n\n### Terms of use\n\nBy using this software or model, you are agreeing to the [terms and conditions](https://mistral.ai/terms-of-service/) of the license, acceptable use policy and Mistral's privacy policy. Mixtral-8x7B is released under the Apache 2.0 license\n\n### References(s):\n\nMixtral 8x7B Instruct [Model Card](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1) on Hugging Face \u003cbr\u003e\n[Mixtral of experts | Mistral AI | Open source models](https://mistral.ai/news/mixtral-of-experts/) \u003cbr\u003e\n\n### Model Architecture:\n\n**Architecture Type:** Transformer \u003cbr\u003e\n**Network Architecture:** Sparse Mixture of GPT-based experts \u003cbr\u003e\n**Model Version:** 0.1 \u003cbr\u003e\n\n### Input:\n\n**Input Format:** Text \u003cbr\u003e\n**Input Parameters:** Temperature, Top P, Max Output Tokens\u003cbr\u003e\n\n### Output:\n\n**Output Format:** Text \u003cbr\u003e\n**Output Parameters:** None \u003cbr\u003e\n\n### Software Integration:\n\n**Supported Hardware Platform(s):** Hopper, Ampere, Turing, Ada \u003cbr\u003e\n**Supported Operating System(s):** Linux \u003cbr\u003e\n\n## Inference:\n\n**Engine:** [Triton](https://developer.nvidia.com/triton-inference-server) \u003cbr\u003e\n**Test Hardware:** Other \u003cbr\u003e\n"])</script><script>self.__next_f.push([1,"7b:T5777,"])</script><script>self.__next_f.push([1,"## Model Information\n\nThe Meta Llama 3.1 collection of multilingual large language models (LLMs) is a collection of pretrained and instruction tuned generative models in 8B, 70B and 405B sizes (text in/text out). The Llama 3.1 instruction tuned text only models (8B, 70B, 405B) are optimized for multilingual dialogue use cases and outperform many of the available open source and closed chat models on common industry benchmarks.\n\n**Model Developer**: Meta\n\n## Llama 3.1 Systems\n\n**Large language models, including Llama 3.1, are not designed to be deployed in isolation but instead should be deployed as part of an overall AI system with additional safety guardrails as required.** Developers are expected to deploy system safeguards when building agentic systems. Safeguards are key to achieve the right helpfulness-safety alignment as well as mitigating safety and security risks inherent to the system and any integration of the model or system with external tools. \nAs part of our responsible release approach, we provide the community with [safeguards](https://llama.meta.com/trust-and-safety/) that developers should deploy with Llama models or other LLMs, including Llama Guard 3, Prompt Guard and Code Shield. All our [reference implementations](https://github.com/meta-llama/llama-agentic-system) demos contain these safeguards by default so developers can benefit from system-level safety out-of-the-box.\n\n## Intended Use\n\n**Intended Use Cases** Llama 3.1 is intended for commercial and research use in multiple languages. Instruction tuned text only models are intended for assistant-like chat, whereas pretrained models can be adapted for a variety of natural language generation tasks. The Llama 3.1 model collection also supports the ability to leverage the outputs of its models to improve other models including synthetic data generation and distillation. The Llama 3.1 Community License allows for these use cases.\n\n**Out-of-scope** Use in any manner that violates applicable laws or regulations (including trade compliance laws). Use in any other way that is prohibited by the Acceptable Use Policy and Llama 3.1 Community License. Use in languages beyond those explicitly referenced as supported in this model card**. \n\n**Note: Llama 3.1 has been trained on a broader collection of languages than the 10 supported languages. \n\nDevelopers may fine-tune Llama 3.1 models for languages beyond the 8 supported languages provided they comply with the Llama 3.1 Community License and the Acceptable Use Policy and in such cases are responsible for ensuring that any uses of Llama 3.1 in additional languages is done in a safe and responsible manner.\n\n\n## New Capabilities\n\nNote that this release introduces new capabilities, including a longer context window, multilingual inputs and outputs and possible integrations by developers with third party tools. Building with these new capabilities requires specific considerations in addition to the best practices that generally apply across all Generative AI use cases. \n\n**Tool-use:** Just like in standard software development, developers are responsible for the integration of the LLM with the tools and services of their choice. They should define a clear policy for their use case and assess the integrity of the third party services they use to be aware of the safety and security limitations when using this capability. Refer to the Responsible Use Guide for best practices on the safe deployment of the third party safeguards. \n\n**Multilinguality:** Llama 3.1 supports 7 languages in addition to English: French, German, Hindi, Italian, Portuguese, Spanish, and Thai. Llama may be able to output text in other languages than those that meet performance thresholds for safety and helpfulness. We strongly discourage developers from using this model to converse in non-supported languages without implementing finetuning and system controls in alignment with their policies and the best practices shared in the Responsible Use Guide.\n\n**Model Architecture:** Llama 3.1 is an auto-regressive language model that uses an optimized transformer architecture. The tuned versions use supervised fine-tuning (SFT) and reinforcement learning with human feedback\n(RLHF) to align with human preferences for helpfulness and safety.\n\n| | Training Data | Params | Input modalities | Output modalities | Context Length | GQA | Token count | Knowledge cutoff |\n|-|-|-----------------------|----------------------------------------------|-----------------------|---------------------|-----------------------|-------|---------------|\n| | | 8B | Multilingual Text | Multilingual Text and code| 128k | Yes | 15T+ | December 2023 |\n| Llama 3.1 (text only) | A new mix of publicly available online data. | 70B | Multilingual Text | Multilingual Text and code| 128k | Yes | 15T+ | December 2023 |\n| | | 405B | Multilingual Text | Multilingual Text and code| 128k | Yes | 15T+ | December 2023 |\n\n**Supported languages:** English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai.\n\n**Llama 3.1 family of models**. Token counts refer to pretraining data only. All model versions use Grouped-Query Attention (GQA) for improved inference scalability.\n\n**Model Release Date:** July 23, 2024. \n\n**Status:** This is a static model trained on an offline dataset. Future versions of the tuned models will be released as we improve model safety with community feedback. \n\n**License** A custom commercial license, the Llama 3.1 Community License, is available at: https://github.com/meta-llama/llama-models/blob/main/models/llama3_1/LICENSE \n\nWhere to send questions or comments about the model Instructions on how to provide feedback or comments on the model can be found in the model [README](https://github.com/meta-llama/llama3). For more technical information about generation parameters and recipes for how to use Llama 3.1 in applications, please go [here](ttps://github.com/meta-llama/llama-recipes).\n\n## Hardware And Software\n\n**Training Factors** We used custom training libraries, Meta's custom built GPU cluster, and production infrastructure for pretraining. Fine-tuning, annotation, and evaluation were also performed on production infrastructure. \n\n**Training Energy Use** Training utilized a cumulative of **39.3**M GPU hours of computation on H100-80GB (TDP of 700W) type hardware, per the table below. Training time is the total GPU time required for training each model and power consumption is the peak power capacity per GPU device used, adjusted for power usage efficiency.\n\n**Training Greenhouse Gas Emissions** Estimated total location-based greenhouse gas emissions were **11,390** tons CO2eq for training. Since 2020, Meta has maintained net zero greenhouse gas emissions in its global operations and matched 100% of its electricity use with renewable energy, therefore the total market-based greenhouse gas emissions for training were 0 tons CO2eq.\n\n| | Training Time (GPU hours) | Training Power Consumption (W) | Training Location-Based Greenhouse Gas Emissions (tons CO2eq) | Training Market-Based Greenhouse Gas Emissions (tons CO2eq) |\n| - |---------------------------------------|---------------------------------------|---------------------------|--------|\n| Llama 3.1 8B | 1.46M | 700 | 420 | 0 |\n| Llama 3.1 70B | 7.0M | 700 | 2,040 | 0 |\n| Llama 3.1 405B | 30.84M | 700 | 8,930 | 0 |\n| Total | 39.3M | - | 11,390 | 0 |\n\nThe methodology used to determine training energy use and greenhouse gas emissions can be found [here](https://arxiv.org/pdf/2204.05149). Since Meta is openly releasing these models, the training energy use and greenhouse gas emissions will not be incurred by others.\n\n## Training Data\n\n**Overview:** Llama 3.1 was pretrained on ~15 trillion tokens of data from publicly available sources. The fine-tuning data includes publicly available instruction datasets, as well as over 25M synthetically generated examples.\n\n**Data Freshness:** The pretraining data has a cutoff of December 2023.\n\n## Benchmarks - English Text\n\nIn this section, we report the results for Llama 3.1 models on standard automatic benchmarks. For all the evaluations, we use our internal evaluations library.\n\n### Base pretrained models\n| Category | Benchmark | # Shots | Metric | Llama 3 8B | Llama 3.1 8B | Llama 3 70B | Llama 3.1 70B | Llama 3.1 405B |\n|--------------------------|---------------|--------------------|----------|------------|--------------|-------------|---------------|----------------|\n| General | MMLU | 5 | macro_avg/acc_char | 66.7 | 66.7 | 79.5 | 79.3 | 85.2 | |\n| General | MMLU PRO (CoT) | 5 | macro_avg/acc_char | 36.2 | 37.1 | 55.0 | 53.8 | 61.6 | |\n| General | AGIEval English | 3-5 | average/acc_char | 47.1 | 47.8 | 63.0 | 64.6 | 71.6 | |\n| General | CommonSenseQA | 7 | acc_char | 72.6 | 75.0 | 83.8 | 84.1 | 85.8 |\n| General | Winogrande | 5 | acc_char | - | 60.5 | - | 83.3 | 86.7 | |\n| General | BIG-Bench Hard (CoT) | 3 | average/em | 61.1 | 64.2 | 81.3 | 81.6 | **85.9** | |\n| General | ARC-Challenge | 25 | acc_char | 79.4 | 79.7 | 93.1 | 92.9 | 96.1 | |\n| Knowledge reasoning | TriviaQA-Wiki | 5 | em | 78.5 | 77.6 | 89.7 | 89.8 | 91.8 |\n| Reading comprehension | SQuAD | 1 | em | 76.4 | 77.0 | 85.6 | 81.8 | 89.3 | |\n| Reading comprehension | QuAC (F1) | 1 | f1 | 44.4 | 44.9 | 51.1 | 51.1 | 53.6 | |\n| Reading comprehension | BoolQ | 0 | acc_char | 75.7 | 75.0 | 79.0 | 79.4 | 80.0 |\n| Reading comprehension | DROP (F1) | 3 | f1 | 58.4 | 59.5 | 79.7 | 79.6 | **84.8** | |\n\n### Instruction Tuned Models\n\n\n| Category | Benchmark | # Shots | Metric | Llama 3 8B Instruct | Llama 3.1 8B Instruct | Llama 3 70B Instruct | Llama 3.1 70B Instruct | Llama 3.1 405B Instruct | \n| --- | --- | --- | --- | --- | --- | --- | --- | --- | \n | General | MMLU | 5 | macro_avg/acc | 68.5 | 69.4 | 82.0 | 83.6 | 87.3 | \n | General | MMLU (CoT) | 0 | macro_avg/acc | 65.3 | 72.7 | 80.9 | 85.9 | 88.6 | \n | General | MMLU PRO (CoT) | 5 | micro_avg/acc_char | 45.5 | 48.3 | 63.4 | 65.1 | 73.3 | \n | Reasoning | ARC-C | 0 | acc | 82.4 | 83.4 | 94.4 | 94.8 | **96.9** | \n | Reasoning | GPQA | 0 | em | 34.6 | 30.4 | 39.5 | 41.7 | 50.7 | \n | Reasoning | MuSR | 0 | correct | 56.3 | 45.7 | 55.1 | 58.1 | 56.7 | \n | Steerability | IFEval | | | 76.8 | 80.4 | 82.9 | 87.5 | **88.6** | \n | Code | HumanEval | 0 | pass@1 | 60.4 | 72.6 | 81.7 | 80.5 | 89.0 | \n | Code | MBPP ++ base version | 0 | pass@1 | 70.6 | 72.8 | 82.5 | 86.0 | 88.6 | \n | Math | GSM-8K (CoT) | 8 | em_maj1@1 | 80.6 | 84.5 | 93.0 | 95.1 | 96.8 | \n | Math | MATH (CoT) | 0 | final_em | 29.1 | 51.9 | 51.0 | 68.0 | 73.8 | \n | Tool Use | API-Bank | 0 | acc | 83.6 | 82.6 | 85.1 | 90.0 | 92.0 | \n | Tool Use | Berkeley Function Calling | 0 | acc | 76.1 | 76.1 | 83.0 | 85.1 | **88.5** |\n | Tool Use | Gorilla Benchmark API Bench | 0 | acc | 8.8 | 8.2 | 14.7 | 29.7 | 35.3 | \n | Tool Use | Nexus (0-shot) | 0 | macro_avg/acc | 37.6 | 38.5 | 47.8 | 56.7 | **58.7** | \n | Multilingual | Multilingual MGSM | 8 | em | - | 68.2 | - | 85.6 | 90.3 |\n\n## Multilingual Benchmarks\n\n| Category | Benchmark | Language | Llama 3.1 8B | Llama 3.1 70B | Llama 3.1 405B | \n| --- | --- | --- | --- | --- | --- | \n| | | Portuguese | 62.12 | 80.13 | 84.95 |\n| | | Spanish | 62.45 | 80.05 | 85.08 |\n| | | Italian | 61.63 | 80.4 | 85.04 | \n| General | MMLU (5-shot, macro_avg/acc) | German | 60.59 | 79.27 | 84.36 | \n| | | French | 62.34 | 79.82 | 84.66 | \n| | | Hindi | 50.88 | 74.52 | 80.31 | \n| | | Thai | 50.32 | 72.95 | 78.21 |\n\n\n\n## Responsibility \u0026 Safety\n\nAs part of our Responsible release approach, we followed a three-pronged strategy to managing trust \u0026 safety risks:\n- Enable developers to deploy helpful, safe and flexible experiences for their target audience and for the use cases supported by Llama.\n\n- Protect developers against adversarial users aiming to exploit Llama capabilities to potentially cause harm.\n\n- Provide protections for the community to help prevent the misuse of our models.\n\n## Responsible Deployment\n\nLlama is a foundational technology designed to be used in a variety of use cases, examples on how Meta's Llama models have been responsibly deployed can be found in our [Community Stories webpage](https://llama.meta.com/community-stories/). Our approach is to build the most helpful models enabling the world to benefit from the technology power, by aligning our model safety for the generic use cases addressing a standard set of harms. Developers are then in the driver seat to tailor safety for their use case, defining their own policy and deploying the models with the necessary safeguards in their Llama systems. Llama 3.1 was developed following the best practices outlined in our Responsible Use Guide, you can refer to the [Responsible Use Guide](https://llama.meta.com/responsible-use-guide/) to learn more.\n\n## Llama 3.1 Instruct\n\nOur main objectives for conducting safety fine-tuning are to provide the research community with a valuable resource for studying the robustness of safety fine-tuning, as well as to offer developers a readily available, safe, and powerful model for various applications to reduce the developer workload to deploy safe AI systems. For more details on the safety mitigations implemented please read the Llama 3 paper.\n\n### Fine-Tuning Data\n\nWe employ a multi-faceted approach to data collection, combining human-generated data from our vendors with synthetic data to mitigate potential safety risks. We've developed many large language model (LLM)-based classifiers that enable us to thoughtfully select high-quality prompts and responses, enhancing data quality control.\n\n### Refusals And Tone\n\nBuilding on the work we started with Llama 3, we put a great emphasis on model refusals to benign prompts as well as refusal tone. We included both borderline and adversarial prompts in our safety data strategy, and modified our safety data responses to follow tone guidelines.\n\n## Evaluations\n\nWe evaluated Llama models for common use cases as well as specific capabilities. Common use cases evaluations measure safety risks of systems for most commonly built applications including chat bot, coding assistant, tool calls. We built dedicated, adversarial evaluation datasets and evaluated systems composed of Llama models and Llama Guard 3 to filter input prompt and output response. It is important to evaluate applications in context, and we recommend building dedicated evaluation dataset for your use case. Prompt Guard and Code Shield are also available if relevant to the application. \n\nCapability evaluations measure vulnerabilities of Llama models inherent to specific capabilities, for which were crafted dedicated benchmarks including long context, multilingual, tools calls, coding or memorization.\n\n## Red Teaming\n\nFor both scenarios, we conducted recurring red teaming exercises with the goal of discovering risks via adversarial prompting and we used the learnings to improve our benchmarks and safety tuning datasets. We partnered early with subject-matter experts in critical risk areas to understand the nature of these real-world harms and how such models may lead to unintended harm for society. Based on these conversations, we derived a set of adversarial goals for the red team to attempt to achieve, such as extracting harmful information or reprogramming the model to act in a potentially harmful capacity. The red team consisted of experts in cybersecurity, adversarial machine learning, responsible AI, and integrity in addition to multilingual content specialists with background in integrity issues in specific geographic markets. .\n\n## Critical And Other Risks\n\nWe specifically focused our efforts on mitigating the following critical risk areas: \n\n ### 1- CBRNE (Chemical, Biological, Radiological, Nuclear, and Explosive materials) helpfulness\n To assess risks related to proliferation of chemical and biological weapons, we performed uplift testing designed to assess whether use of Llama 3.1 models could meaningfully increase the capabilities of malicious actors to plan or carry out attacks using these types of weapons.\n\n### 2. Child Safety\n\nChild Safety risk assessments were conducted using a team of experts, to assess the model's capability to produce outputs that could result in Child Safety risks and inform on any necessary and appropriate risk mitigations via fine tuning. We leveraged those expert red teaming sessions to expand the coverage of our evaluation benchmarks through Llama 3 model development. For Llama 3, we conducted new in-depth sessions using objective based methodologies to assess the model risks along multiple attack vectors including the additional languages Llama 3 is trained on. We also partnered with content specialists to perform red teaming exercises assessing potentially violating content while taking account of market specific nuances or experiences.\n\n### 3. Cyber Attack Enablement\n\nOur cyber attack uplift study investigated whether LLMs can enhance human capabilities in hacking tasks, both in terms of skill level and speed. Our attack automation study focused on evaluating the capabilities of LLMs when used as autonomous agents in cyber offensive operations, specifically in the context of ransomware attacks. This evaluation was distinct from previous studies that considered LLMs as interactive assistants. The primary objective was to assess whether these models could effectively function as independent agents in executing complex cyber-attacks without human intervention. Our study of Llama-3.1-405B's social engineering uplift for cyber attackers was conducted to assess the effectiveness of AI models in aiding cyber threat actors in spear phishing campaigns. Please read our Llama 3.1 Cyber security whitepaper to learn more.\n\n## Community\n\nGenerative AI safety requires expertise and tooling, and we believe in the strength of the open community to accelerate its progress. We are active members of open consortiums, including the AI Alliance, Partnership on AI and MLCommons, actively contributing to safety standardization and transparency. We encourage the community to adopt taxonomies like the MLCommons Proof of Concept evaluation to facilitate collaboration and transparency on safety and content evaluations. Our Purple Llama tools are open sourced for the community to use and widely distributed across ecosystem partners including cloud service providers. We encourage community contributions to our [Github repository](https://github.com/meta-llama/PurpleLlama). \n\nWe also set up the [Llama Impact Grants](https://llama.meta.com/llama-impact-grants/) program to identify and support the most compelling applications of Meta's Llama model for societal benefit across three categories: education, climate and open innovation. The 20 finalists from the hundreds of applications can be found [here](https://llama.meta.com/llama-impact-grants/#finalists). \nFinally, we put in place a set of resources including an [output reporting mechanism](https://developers.facebook.com/llama_output_feedback) and [bug bounty program](https://www.facebook.com/whitehat) to continuously improve the Llama technology with the help of the community.\n\n## Ethical Considerations And Limitations\n\nThe core values of Llama 3.1 are openness, inclusivity and helpfulness. It is meant to serve everyone, and to work for a wide range of use cases. It is thus designed to be accessible to people across many different backgrounds, experiences and perspectives. Llama 3.1 addresses users and their needs as they are, without insertion unnecessary judgment or normativity, while reflecting the understanding that even content that may appear problematic in some cases can serve valuable purposes in others. It respects the dignity and autonomy of all users, especially in terms of the values of free thought and expression that power innovation and progress. \n\nBut Llama 3.1 is a new technology, and like any new technology, there are risks associated with its use. Testing conducted to date has not covered, nor could it cover, all scenarios. For these reasons, as with all LLMs, Llama 3.1's potential outputs cannot be predicted in advance, and the model may in some instances produce inaccurate, biased or other objectionable responses to user prompts. Therefore, before deploying any applications of Llama 3.1 models, developers should perform safety testing and tuning tailored to their specific applications of the model. Please refer to available resources including our [Responsible Use Guide](https://llama.meta.com/responsible-use-guide), [Trust and Safety](https://llama.meta.com/trust-and-safety/) solutions, and other [resources](https://llama.meta.com/docs/get-started/) to learn more about responsible development."])</script><script>self.__next_f.push([1,"7c:T8e4,"])</script><script>self.__next_f.push([1,"{\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"Tell me about Dumbledore.\"\n }\n ],\n \"model\": \"meta/llama-3.1-70b-instruct\",\n \"max_tokens\": 1024,\n \"stream\": true,\n \"tool_choice\": \"auto\",\n \"tools\": [\n {\n \"type\": \"function\",\n \"function\": {\n \"name\": \"describe_harry_potter_character\",\n \"description\": \"Returns information and images of Harry Potter characters.\",\n \"parameters\": {\n \"type\": \"object\",\n \"properties\": {\n \"name\": {\n \"type\": \"string\",\n \"enum\": [\n \"Harry James Potter\",\n \"Hermione Jean Granger\",\n \"Ron Weasley\",\n \"Fred Weasley\",\n \"George Weasley\",\n \"Bill Weasley\",\n \"Percy Weasley\",\n \"Charlie Weasley\",\n \"Ginny Weasley\",\n \"Molly Weasley\",\n \"Arthur Weasley\",\n \"Neville Longbottom\",\n \"Luna Lovegood\",\n \"Draco Malfoy\",\n \"Albus Percival Wulfric Brian Dumbledore\",\n \"Minerva McGonagall\",\n \"Remus Lupin\",\n \"Rubeus Hagrid\",\n \"Sirius Black\",\n \"Severus Snape\",\n \"Bellatrix Lestrange\",\n \"Lord Voldemort\",\n \"Cedric Diggory\",\n \"Nymphadora Tonks\",\n \"James Potter\"\n ],\n \"description\": \"Name of the Harry Potter character\"\n }\n },\n \"required\": [\n \"name\"\n ]\n }\n }\n }\n ]\n}\n"])</script><script>self.__next_f.push([1,"7d:T536,{\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"What is the weather in Santa Clara, CA?\"\n }\n ],\n \"model\": \"meta/llama-3.1-70b-instruct\",\n \"max_tokens\": 1024,\n \"stream\": true,\n \"tool_choice\": \"auto\",\n \"tools\": [\n {\n \"type\": \"function\",\n \"function\": {\n \"name\": \"get_current_weather\",\n \"description\": \"A tool that gets the current weather at a location, if one is specified, and defaults to the user's location.\",\n \"parameters\": {\n \"type\": \"object\",\n \"properties\": {\n \"location\": {\n \"type\": \"string\",\n \"description\": \"The location to find the weather of, or if not provided, it's the default location.\"\n },\n \"unit\": {\n \"type\": \"string\",\n \"enum\": [\n \"u\",\n \"m\"\n ],\n \"description\": \"Whether to use SI or USCS units (celsius or fahrenheit). Infer this from the user's location.\"\n }\n }\n }\n }\n }\n ]\n}\n7e:T4bd,from openai import OpenAI\n\nclient = OpenAI(\n base_url = \"https://integrate.api.nvidia.com/v1\",\n api_key = \"$NVIDIA_API_KEY\"\n)\n\u003c% if (request.tools) { %\u003e\ncompletion = client.chat.completions.create(\n model=\"\u003c%- request.model %\u003e\",\n messages=\u003c%- JSON.stringify(request.messages) %\u003e,\n temperature=\u003c%- request.temperature %\u003e,\n top_p=\u003c%- request.top_p %\u003e,\n max_tokens=\u003c%- request.max_tokens %\u003e,\n stream=\u003c%- request.stream?.toString()[0].toUpperCase() + request.stream?.toString().slice(1) %\u003e,\n tools=\u003c%- JSON.stringify(request.tools) %\u003e,\n \u003c% if (request.tool_choice) { %\u003etool_choice=\u003c%- JSON.stringify(request.tool_choice) %\u003e\u003c% } %\u003e\n)\u003c% } else { %\u003e\ncompletion = client.chat.completions.create(\n"])</script><script>self.__next_f.push([1," model=\"\u003c%- request.model %\u003e\",\n messages=\u003c%- JSON.stringify(request.messages) %\u003e,\n temperature=\u003c%- request.temperature %\u003e,\n top_p=\u003c%- request.top_p %\u003e,\n max_tokens=\u003c%- request.max_tokens %\u003e,\n stream=\u003c%- request.stream?.toString()[0].toUpperCase() + request.stream?.toString().slice(1) %\u003e\n)\u003c% } %\u003e\n\u003c% if (request.stream) { %\u003e\nfor chunk in completion:\n if chunk.choices[0].delta.content is not None:\n print(chunk.choices[0].delta.content, end=\"\")\n\u003c% } else { %\u003e\nprint(completion.choices[0].message)\n\u003c% } %\u003e\n7f:T504,import OpenAI from 'openai';\n\nconst openai = new OpenAI({\n apiKey: '$NVIDIA_API_KEY',\n baseURL: 'https://integrate.api.nvidia.com/v1',\n})\n \u003c% if (request.tools) { %\u003e\nasync function main() {\n const completion = await openai.chat.completions.create({\n model: \"\u003c%- request.model %\u003e\",\n messages: \u003c%- JSON.stringify(request.messages) %\u003e,\n temperature: \u003c%- request.temperature %\u003e,\n top_p: \u003c%- request.top_p %\u003e,\n max_tokens: \u003c%- request.max_tokens %\u003e,\n stream: \u003c%- request.stream %\u003e,\n \u003c% if (request.tools) { %\u003etools: \u003c%- JSON.stringify(request.tools) %\u003e,\u003c% } %\u003e\n \u003c% if (request.tool_choice) { %\u003etool_choice: \u003c%- JSON.stringify(request.tool_choice) %\u003e,\u003c% } %\u003e\n })\u003c% } else { %\u003e\nasync function main() {\n const completion = await openai.chat.completions.create({\n model: \"\u003c%- request.model %\u003e\",\n messages: \u003c%- JSON.stringify(request.messages) %\u003e,\n temperature: \u003c%- request.temperature %\u003e,\n top_p: \u003c%- request.top_p %\u003e,\n max_tokens: \u003c%- request.max_tokens %\u003e,\n stream: \u003c%- request.stream %\u003e\n })\u003c% } %\u003e\n \u003c% if (request.stream) { %\u003e\n for await (const chunk of completion) {\n process.stdout.write(chunk.choices[0]?.delta?.content || '')\n }\n \u003c% } else { %\u003e\n process.stdout.write(completion.choices[0]?.message?.content);\n \u003c% } %\u003e\n}\n\nmain();80:T66f,\u003c% if (request.tools) { %\u003e\n \"curl https://integrate.api.nvidia.com/v1/chat/completions \\\\\\n\n -H \\\"Content-Type: application/json\\\" \\\\\\n\n -H \\\"Authorization: Bearer $NVIDIA_API_KEY\\\" \\\\\\n\n -d '{\\n\n \\\"model\\\": \\\"meta/lla"])</script><script>self.__next_f.push([1,"ma-3.1-70b-instruct\\\",\\n\n \\\"messages\\\": \u003c%- JSON.stringify(request.messages).replaceAll(\\\"'\\\", \\\"'\\\\\\\"'\\\\\\\"'\\\") %\u003e,\\n\n \\\"temperature\\\": \u003c%- request.temperature %\u003e,\\n\n \\\"top_p\\\": \u003c%- request.top_p %\u003e,\\n\n \\\"max_tokens\\\": \u003c%- request.max_tokens %\u003e,\\n\n \\\"stream\\\": \u003c%- request.stream %\u003e\n \u003c% if (request.tools) { %\u003e,\\n \\\"tools\\\": \u003c%- JSON.stringify(request.tools).replaceAll(\\\"'\\\", \\\"'\\\\\\\"'\\\\\\\"'\\\") %\u003e\u003c% } %\u003e\n \u003c% if (request.tool_choice) { %\u003e,\\n \\\"tool_choice\\\": \u003c%- JSON.stringify(request.tool_choice).replaceAll(\\\"'\\\", \\\"'\\\\\\\"'\\\\\\\"'\\\") %\u003e\u003c% } %\u003e\n }'\\n\"\u003c% } else { %\u003e\n \"curl https://integrate.api.nvidia.com/v1/chat/completions \\\\\\n\n -H \\\"Content-Type: application/json\\\" \\\\\\n\n -H \\\"Authorization: Bearer $NVIDIA_API_KEY\\\" \\\\\\n\n -d '{\\n\n \\\"model\\\": \\\"meta/llama-3.1-70b-instruct\\\",\\n\n \\\"messages\\\": \u003c%- JSON.stringify(request.messages).replaceAll(\\\"'\\\", \\\"'\\\\\\\"'\\\\\\\"'\\\") %\u003e,\\n\n \\\"temperature\\\": \u003c%- request.temperature %\u003e,\\n\n \\\"top_p\\\": \u003c%- request.top_p %\u003e,\\n\n \\\"max_tokens\\\": \u003c%- request.max_tokens %\u003e,\\n\n \\\"stream\\\": \u003c%- request.stream %\u003e\n \u003c% if (request.tools) { %\u003e,\\n \\\"tools\\\": \u003c%- JSON.stringify(request.tools).replaceAll(\\\"'\\\", \\\"'\\\\\\\"'\\\\\\\"'\\\") %\u003e\u003c% } %\u003e\n \u003c% if (request.tool_choice) { %\u003e,\\n \\\"tool_choice\\\": \u003c%- JSON.stringify(request.tool_choice).replaceAll(\\\"'\\\", \\\"'\\\\\\\"'\\\\\\\"'\\\") %\u003e\u003c% } %\u003e\n }'\\n\"\u003c% } %\u003e81:T6bf,## Model Overview\n\n### Description:\n\nMistral-7B-Instruct-v0.3 is a language model that can follow instructions, complete requests, and generate creative text formats. It is an instruct version of the Mistral-7B-v0.3 generative text model fine-tuned using a variety of publicly available conversation datasets.\n\nThis model is ready for non-commercial use.\n\n### Third-Party Community Consideration:\n\nThis model is not owned or developed by NVIDIA. This model has been developed and built to a third-party’s requirements for this application and use case; see [Mistral's 7B Instruct Hugging Face Model Card](https://huggingfac"])</script><script>self.__next_f.push([1,"e.co/mistralai/Mistral-7B-Instruct-v0.3).\n\n### Terms of use\n\nBy using this software or model, you are agreeing to the [terms and conditions](https://mistral.ai/terms-of-service/) of the license, acceptable use policy and Mistral's privacy policy. Mistral-7B is released under the Apache 2.0 license\n\n### References(s):\n\nMistral 7B Instruct v0.3 [Model Card](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3) on Hugging Face \u003cbr\u003e\nMistral 7B [Paper](https://arxiv.org/abs/2310.06825) \u003cbr\u003e\nMistral 7B [Blogpost](https://mistral.ai/news/announcing-mistral-7b/)\n\n### Model Architecture:\n\n**Architecture Type:** Transformer \u003cbr\u003e\n**Network Architecture:** Mistral-7B \u003cbr\u003e\n**Model Version:** 0.3 \u003cbr\u003e\n\n**Input**\n* Input Type: Text\n* Input Format: String\n* Input Parameters: max_tokens, temperature, top_p, stop, frequency_penalty, presence_penalty, seed\n\n**Output**\n* Output Type: Text\n* Output Format: String\n\n### Software Integration:\n\n* Supported Hardware Platform(s): NVIDIA Hopper\n* Preferred Operating System(s): Linux \u003cbr\u003e\n\n### Inference\n\n**Engine:** TensorRT-LLM \u003cbr\u003e\n**Test Hardware:** H100\n82:T8eb,"])</script><script>self.__next_f.push([1,"{\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"Tell me about Dumbledore.\"\n }\n ],\n \"model\": \"mistralai/mistral-7b-instruct-v0.3\",\n \"max_tokens\": 1024,\n \"stream\": true,\n \"tool_choice\": \"auto\",\n \"tools\": [\n {\n \"type\": \"function\",\n \"function\": {\n \"name\": \"describe_harry_potter_character\",\n \"description\": \"Returns information and images of Harry Potter characters.\",\n \"parameters\": {\n \"type\": \"object\",\n \"properties\": {\n \"name\": {\n \"type\": \"string\",\n \"enum\": [\n \"Harry James Potter\",\n \"Hermione Jean Granger\",\n \"Ron Weasley\",\n \"Fred Weasley\",\n \"George Weasley\",\n \"Bill Weasley\",\n \"Percy Weasley\",\n \"Charlie Weasley\",\n \"Ginny Weasley\",\n \"Molly Weasley\",\n \"Arthur Weasley\",\n \"Neville Longbottom\",\n \"Luna Lovegood\",\n \"Draco Malfoy\",\n \"Albus Percival Wulfric Brian Dumbledore\",\n \"Minerva McGonagall\",\n \"Remus Lupin\",\n \"Rubeus Hagrid\",\n \"Sirius Black\",\n \"Severus Snape\",\n \"Bellatrix Lestrange\",\n \"Lord Voldemort\",\n \"Cedric Diggory\",\n \"Nymphadora Tonks\",\n \"James Potter\"\n ],\n \"description\": \"Name of the Harry Potter character\"\n }\n },\n \"required\": [\n \"name\"\n ]\n }\n }\n }\n ]\n}\n"])</script><script>self.__next_f.push([1,"83:T53d,{\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"What is the weather in Santa Clara, CA?\"\n }\n ],\n \"model\": \"mistralai/mistral-7b-instruct-v0.3\",\n \"max_tokens\": 1024,\n \"stream\": true,\n \"tool_choice\": \"auto\",\n \"tools\": [\n {\n \"type\": \"function\",\n \"function\": {\n \"name\": \"get_current_weather\",\n \"description\": \"A tool that gets the current weather at a location, if one is specified, and defaults to the user's location.\",\n \"parameters\": {\n \"type\": \"object\",\n \"properties\": {\n \"location\": {\n \"type\": \"string\",\n \"description\": \"The location to find the weather of, or if not provided, it's the default location.\"\n },\n \"unit\": {\n \"type\": \"string\",\n \"enum\": [\n \"u\",\n \"m\"\n ],\n \"description\": \"Whether to use SI or USCS units (celsius or fahrenheit). Infer this from the user's location.\"\n }\n }\n }\n }\n }\n ]\n}\n84:T93d,"])</script><script>self.__next_f.push([1,"Field | Response\n:----------------------------------------------------------------------------------------------------------------------------------|:-----------------------------------------------\nPersonal data used to create this model? | None Known. For data included in the base Llama 3.1 model, [reference the Llama 3.1 model card.](https://github.com/meta-llama/llama-models/blob/main/models/llama3_1/MODEL_CARD.md)\nWas consent obtained for any personal data used? | Not Applicable for NVIDIA training data; NVIDIA did not introduce personal data through retraining\nGeneratable or reverse engineerable personal data? | Not a known capability.\nHow often is the dataset reviewed (if applicable)? | Before Release\nIs a mechanism in place to honor data subject right of access or deletion of personal data? | Not Applicable for NVIDIA training data \nIf personal data collected for the development of the model, was it collected directly by NVIDIA? | Not Applicable\nIf personal data collected for the development of the model by NVIDIA, do you maintain or have access to disclosures made to data subjects? | Not Applicable\nIf personal data collected for the development of this AI model, was it minimized to only what was required? | Not Applicable for NVIDIA training data \nIs there provenance for all datasets used in training? | Yes\nDoes data labeling (annotation, metadata) comply with privacy laws? | Not Applicable for NVIDIA training data\nIs data compliant with data subject requests for data correction or removal, if such a request was made? | Not Applicable for NVIDIA training data"])</script><script>self.__next_f.push([1,"85:Td87,"])</script><script>self.__next_f.push([1,"## Model Overview\n\n### Description:\n\nLlama-3.1-Nemotron-70B-Instruct is a large language model customized by NVIDIA to improve the helpfulness of LLM generated responses to user queries.\n\nThis model is ready for commercial use.\n\n### Terms of use\n\nBy accessing this model, you are agreeing to the LLama 3 terms and conditions of the [license](https://github.com/meta-llama/llama-models/blob/main/models/llama3_1/LICENSE), [acceptable use policy](https://github.com/meta-llama/llama-models/blob/main/models/llama3_1/USE_POLICY.md) and [Meta’s privacy policy](https://www.facebook.com/privacy/policy/)\n\n### References(s):\n\n* [HelpSteer2-Preference](https://arxiv.org/abs/2410.01257)\n* [SteerLM method](https://arxiv.org/abs/2310.05344)\n* [HelpSteer](https://arxiv.org/abs/2311.09528)\n* [HelpSteer2](https://arxiv.org/abs/2406.08673)\n* [Introducing Llama 3.1: Our most capable models to date](https://ai.meta.com/blog/meta-llama-3-1/)\n* [Meta's Llama 3.1 Webpage](https://www.llama.com/docs/model-cards-and-prompt-formats/llama3_1)\n* [Meta's Llama 3.1 Model Card](https://github.com/meta-llama/llama-models/blob/main/models/llama3_1/MODEL_CARD.md)\n\n### Model Architecture:\n\n**Architecture Type:** Transformer \u003cbr\u003e\n**Network Architecture:** Llama 3.1 \u003cbr\u003e\n\n### Input:\n\n**Input Type(s):** Text \u003cbr\u003e\n**Input Format:** String \u003cbr\u003e\n**Input Parameters:** One Dimensional (1D) \u003cbr\u003e\n**Other Properties Related to Input:** Max of 128k tokens\u003cbr\u003e\n\n### Output:\n\n**Output Type(s):** Text \u003cbr\u003e\n**Output Format:** String \u003cbr\u003e\n**Output Parameters:** One Dimensional (1D) \u003cbr\u003e\n**Other Properties Related to Output:** Max of 4k tokens \u003cbr\u003e\n\n### Software Integration:\n\n**Supported Hardware Microarchitecture Compatibility:** \u003cbr\u003e\n* NVIDIA Ampere \u003cbr\u003e\n* NVIDIA Hopper \u003cbr\u003e\n* NVIDIA Turing \u003cbr\u003e\n **Supported Operating System(s):** Linux \u003cbr\u003e\n\n### Model Version:\n\nv1.0\n\n## Training \u0026 Evaluation:\n\n### Datasets:\n\n**Data Collection Method by dataset** \u003cbr\u003e\n* [Hybrid: Human, Synthetic] \u003cbr\u003e\n\n**Labeling Method by dataset** \u003cbr\u003e\n* [Human] \u003cbr\u003e\n\n**Link:**\n* [HelpSteer2](https://huggingface.co/datasets/nvidia/HelpSteer2)\n\n**Properties (Quantity, Dataset Descriptions, Sensor(s)):** \u003cbr\u003e\n* 21, 362 prompt-responses built to make more models more aligned with human preference - specifically more helpful, factually-correct, coherent, and customizable based on complexity and verbosity.\n* 20, 324 prompt-responses used for training and 1, 038 used for validation.\n\n## Inference:\n\n**Engine:** [Triton](https://developer.nvidia.com/triton-inference-server) \u003cbr\u003e\n**Test Hardware:** H100, A100 80GB, A100 40GB \u003cbr\u003e\n\n### Ethical Considerations:\n\nNVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their supporting model team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse. For more detailed information on ethical considerations for this model, please see the Model Card++ Explainability, Bias, Safety \u0026 Security, and Privacy Subcards. Please report security vulnerabilities or NVIDIA AI Concerns [here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/).\n\nPlease report security vulnerabilities or NVIDIA AI Concerns [here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/).\n"])</script><script>self.__next_f.push([1,"86:T828,"])</script><script>self.__next_f.push([1,"Field | Response\n:------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------\nIntended Application \u0026 Domain: | Response Customization in Large Language Model Development\nModel Type: | Text-to-Text Transformer\nIntended User: | Developers customizing model response across different applications and domains.\nOutput: | Text\nDescribe how the model works: | Generates a response based on a prior conversation. \nName the adversely impacted groups this has been tested to deliver comparable outcomes regardless of: | Not Applicable\nVerified to have met prescribed quality standards: | Yes\nTechnical Limitations: | This model may not work for non-English languages.\nPerformance Metrics: | Throughput and Latency\nPotential Known Risks: | The Model may produce output that is biased and toxic based on how it is prompted, producing socially unacceptable or undesirable text, even if the prompt itself does not include anything explicitly offensive. The model may also amplify biases and return toxic responses especially when prompted with toxic prompts. \nLicensing: | [Llama 3.1 Community License Agreement](https://github.com/meta-llama/llama-models/blob/main/models/llama3_1/LICENSE)"])</script><script>self.__next_f.push([1,"87:T792,Field | Response\n:----------------------------------------------------------------------------------------------------------------------------------|:-----------------------------------------------\nGeneratable or reverse engineerable personally-identifiable information (PII)? | None\nWas consent obtained for any personal data used? | Not Applicable (N/A)\nProtected class data used to create this model? | None\nHow often is dataset reviewed? | Before Release\nIs a mechanism in place to honor data subject right of access or deletion of personal data? | N/A\nIf personal data collected for the development of the model, was it collected directly by NVIDIA? | N/A\nIf personal data collected for the development of the model by NVIDIA, do you maintain or have access to disclosures made to data subjects? | N/A\nIf personal data collected for the development of this AI model, was it minimized to only what was required? | N/A\nIs there provenance for all datasets used in training? | Yes\nDoes data labeling (annotation, metadata) comply with privacy laws? | Yes\nIs data compliant with data subject requests for data correction or removal, if such a request was made? | N/A88:T1905,"])</script><script>self.__next_f.push([1,"## Model Overview\n\n### Description\n\nCorrector Diffusion (CorrDiff) US GEFS-HRRR model down-scales several surface and atmospheric variables from 25-km resolution\nforecast data from the Global Ensemble Forecast System (GEFS) and predicts 3-km\nresolution High-Resolution Rapid Refresh (HRRR) data. CorrDiff US allows the prediction of high-fidelity stochastic weather phenomena over\nthe CONUS from low-fidelity input data that would otherwise require expensive regional\nnumerical simulations.\n\nCorrDiff is a generative downscaling model trained over the contiguous United States (CONUS).\n\nThis model is ready for commercial use.\n\n### Reference(s)\n\n* [CorrDiff Paper](https://arxiv.org/pdf/2309.15214) \u003cbr\u003e\n* [Codebase](https://github.com/NVIDIA/modulus) \u003cbr\u003e\n* [Global Ensemble Forecast System](https://www.ncei.noaa.gov/products/weather-climate-models/global-ensemble-forecast) \u003cbr\u003e\n* [The High-Resolution Rapid Refresh](https://rapidrefresh.noaa.gov/hrrr/) \u003cbr\u003e\n\n### Model Architecture\n\n**Architecture Type:** Diffusion \u003cbr\u003e\n**Network Architecture:** Patch-Based Corrector Diffusion \u003cbr\u003e\n\n### Input\n\n**Input Type(s):**\n\n- Tensor (38 Surface \u0026 Atmospheric Variables + Forecast Lead Time) \u003cbr\u003e\n- Input data forecast lead time in hours \u003cbr\u003e\n\n**Input Format(s):** NumPy \u003cbr\u003e\n**Input Parameters:**\n\n- Four Dimensional (4D) (batch, variable, latitude, longitude) \u003cbr\u003e\n- Integer (Lead Time in Hours) \u003cbr\u003e\n\n**Other Properties Related to Input:**\n- 0.25 degree latitude-longitude grid bounded over CONUS\n- Input resolution: [129, 301]\n- Lattitude Coordinates: [53, 52.75, 52.5, ..., 21.5, 21.25, 21]\n- Longitude Coordinates: [225, 225.25, 225.5, ..., 299.5, 299.75, 300]\n- Input weather variables: \"u10m\", \"v10m\", \"t2m\", \"r2m\", \"sp\", \"msl\",\"tcwv\", \"u1000\", \"u925\", \"u850\", \"u700\", \"u500\", \"u250\", \"v1000\", \"v925\", \"v850\", \"v700\", \"v500\", \"v250\", \"z1000\", \"z925\", \"z850\", \"z700\", \"z500\", \"z200\", \"t1000\", \"t925\", \"t850\", \"t700\", \"t500\", \"t100\", \"r1000\", \"r925\", \"r850\", \"r700\", \"r500\", \"r100\"\u003cbr\u003e\n\n### Output\n\n**Output Type(s):** Tensor (8 Surface \u0026 Atmospheric Variables) \u003cbr\u003e\n**Output Format:** NumPy \u003cbr\u003e\n**Output Parameters:** 5D (batch, samples, variable, latitude, longitude)\u003cbr\u003e\n**Other Properties Related to Output:**\n- 3-km lambert-conformal projection over CONUS of resolution\n- Output resolution: [1056, 1792]\n- Output weather variables: \"u10m\", \"v10m\", \"t2m\", \"tp\", \"csnow\", \"cicep\", \"cfrzr\", \"crain\"\u003cbr\u003e\n\nThe output is on a cropped window of the grid used by HRRR.\nRefer to the [HRRR documentation](https://rapidrefresh.noaa.gov/hrrr/) for additional information on this grid.\nThe output coordinates can be obtained from the `corrdiff_output_lat.npy` and `corrdiff_output_lon.npy`\nfiles in the model package.\n\n### Software Integration\n\n**Runtime Engine(s):** Not Applicable \u003cbr\u003e\n**Supported Hardware Microarchitecture Compatibility:** \u003cbr\u003e\n* NVIDIA Ampere \u003cbr\u003e\n* NVIDIA Hopper \u003cbr\u003e\n* NVIDIA Turing \u003cbr\u003e\n\n**Supported Operating System(s):**\n* Linux \u003cbr\u003e\n\n### Model Version(s)\n\n**Model version:** v1 \u003cbr\u003e\n\n## Training, Testing, and Evaluation Datasets:\n\n### Training Dataset\n\n**Link:** [GEFS](https://www.ncei.noaa.gov/products/weather-climate-models/global-ensemble-forecast) \u003cbr\u003e\n\n*Data Collection Method by dataset* \u003cbr\u003e\n* Automatic/Sensors \u003cbr\u003e\n\n*Labeling Method by dataset* \u003cbr\u003e\n* Automatic/Sensors \u003cbr\u003e\n\n**Properties (Quantity, Dataset Descriptions, Sensor(s)):**\nGEFS data for the date range of 2020/12/02 to 2023/12/31. The Global Ensemble Forecast System (GEFS) is a weather model created by the National Centers for Environmental Prediction (NCEP) that generates 21 separate forecasts (ensemble members) to address underlying uncertainties in the input data such limited coverage, instruments or observing systems biases, and the limitations of the model itself. \u003cbr\u003e\n\n**Link:** [HRRR](https://rapidrefresh.noaa.gov/hrrr/) \u003cbr\u003e\n\n*Data Collection Method by dataset* \u003cbr\u003e\n* Automatic/Sensors \u003cbr\u003e\n\n*Labeling Method by dataset* \u003cbr\u003e\n* Automatic/Sensors \u003cbr\u003e\n\n**Properties (Quantity, Dataset Descriptions, Sensor(s)):**\nHRRR data for the date range of 2020/12/02 to 2023/12/31. The HRRR is a NOAA real-time 3-km resolution, hourly updated, cloud-resolving, convection-allowing atmospheric model, initialized by 3km grids with 3km radar assimilation. \u003cbr\u003e\n\n### Evaluation Dataset\n\n**Link:** [GEFS](https://www.ncei.noaa.gov/products/weather-climate-models/global-ensemble-forecast) \u003cbr\u003e\n\n*Data Collection Method by dataset* \u003cbr\u003e\n* Automatic/Sensors \u003cbr\u003e\n\n*Labeling Method by dataset* \u003cbr\u003e\n* Automatic/Sensors \u003cbr\u003e\n\n**Properties (Quantity, Dataset Descriptions, Sensor(s)):**\nGEFS data for the date range of 2024/01/01 to 2024/07/31. The Global Ensemble Forecast System (GEFS) is a weather model created by the National Centers for Environmental Prediction (NCEP) that generates 21 separate forecasts (ensemble members) to address underlying uncertainties in the input data such limited coverage, instruments or observing systems biases, and the limitations of the model itself. \u003cbr\u003e\n\n**Link:** [HRRR](https://rapidrefresh.noaa.gov/hrrr/) \u003cbr\u003e\n\n*Data Collection Method by dataset* \u003cbr\u003e\n* Automatic/Sensors \u003cbr\u003e\n\n*Labeling Method by dataset* \u003cbr\u003e\n* Automatic/Sensors \u003cbr\u003e\n\n**Properties (Quantity, Dataset Descriptions, Sensor(s)):**\nHRRR data for the date range of 2024/01/01 to 2024/07/31. The HRRR is a NOAA real-time 3-km resolution, hourly updated, cloud-resolving, convection-allowing atmospheric model, initialized by 3km grids with 3km radar assimilation. \u003cbr\u003e\n\n## Inference:\n\n**Engine:** [Triton](https://developer.nvidia.com/triton-inference-server) \u003cbr\u003e\n**Test Hardware:**\n* A100 \u003cbr\u003e\n* H100 \u003cbr\u003e\n* L40S \u003cbr\u003e\n* RTX6000 \u003cbr\u003e\n\n### Ethical Considerations:\n\nNVIDIA believes Trustworthy AI is a shared responsibility and we have established\npolicies and practices to enable development for a wide array of AI applications.\nWhen downloaded or used in accordance with our terms of service, developers should work\nwith their supporting model team to ensure this model meets requirements for the\nrelevant industry and use case and addresses unforeseen product misuse.\nFor more detailed information on ethical considerations for this model, please see the\nModel Card++ Explainability, Bias, Safety \u0026 Security, and Privacy Subcards [here](https://ai.nvidia.com).\nPlease report security vulnerabilities or NVIDIA AI Concerns [here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/).\n"])</script><script>self.__next_f.push([1,"89:T7b6,Field | Response\n:------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------\nIntended Application \u0026 Domain: | Global Weather Forecasting\nModel Type: | Diffusion Model\nIntended User: | Climate and Weather scientists accelerating weather prediction with AI.\nOutput: | Downscaled inputs.\nDescribe how the model works: | Diffusion model progressively adds noise to interpolated input to recreate fine-resolution features.\nName the adversely impacted groups this has been tested to deliver comparable outcomes regardless of: | Not Applicable\nTechnical Limitations: | The model may perform poorly for data sources different from that in the ERA5 training dataset\nVerified to have met prescribed NVIDIA quality standards: | Yes\nPerformance Metrics: | Accuracy, Throughput and Latency\nPotential Known Risks: | This model may mispredict fine-resolution features.\nLicensing: | [Earth-2 Service Terms of Use](https://ngc.nvidia.com/legal/terms)8a:T783,#!/usr/bin/env bash\nif [ \"$NGC_API_KEY\" = \"\" ]; then\n N"])</script><script>self.__next_f.push([1,"GC_API_KEY='$NVIDIA_API_KEY'\nfi\ninvoke_url=\"https://climate.api.nvidia.com/v1/nvidia/corrdiff\"\n\noutput_file=\"output.zip\"\npayload='{\n \"input_id\": \u003c%- request.input_id %\u003e,\n \"samples\": \u003c%- request.samples %\u003e,\n \"steps\": \u003c%- request.steps %\u003e\n}'\necho $payload\n# Initial request\necho \"$(date) Making inference request\"\nresponse=$(curl -D - --request POST -H \"content-type: application/json\" -H \"Authorization: Bearer $NGC_API_KEY\" -H \"NVCF-POLL-SECONDS: 5\" --data \"$payload\" --location \"$invoke_url\")\n\nhttp_status=$(echo \"$response\" | awk '{print $2;exit}')\nif [ \"$http_status\" -eq 202 ]; then\n req_id=$(echo \"$response\" | grep -i \"nvcf-reqid:\" | awk '{print $2}' | tr -d '\\r')\nelse\n echo \"Unexpected HTTP status: $http_status\"\n echo \"Response: $response\"\n exit 1\nfi\n\nstatus_url=\"https://api.nvcf.nvidia.com/v2/nvcf/pexec/status/$req_id\"\n# Poll the /status endpoint\necho \"$(date) Polling job $req_id\"\nwhile true; do\n status_response=$(curl -s -D - --request GET -H \"content-type: application/json\" -H \"Authorization: Bearer $NGC_API_KEY\" -H \"NVCF-POLL-SECONDS: 5\" --location \"$status_url\" -o \"$output_file\")\n status_http_status=$(echo \"$status_response\" | awk '{print $2;exit}')\n\n if [ \"$status_http_status\" -eq 200 ]; then\n echo \"Saved response to file\"\n break\n elif [ \"$status_http_status\" -eq 302 ]; then\n echo \"Downloading large asset\"\n asset_url=$(echo \"$status_response\" | grep -i \"location:\" | awk '{print $2}' | tr -d '\\r')\n curl --request GET --location \"${asset_url}\" -o \"${output_file}\"\n break\n elif [ \"$status_http_status\" -ne 202 ]; then\n echo \"Unexpected HTTP status: $status_http_status\"\n echo \"Response: $status_response\"\n exit 1\n fi\n echo \"$(date) Job still running, status $status_http_status\"\n # Wait before polling again\n sleep 3\ndone8b:Te3a,"])</script><script>self.__next_f.push([1,"package main\n\nimport (\n \"bytes\"\n \"fmt\"\n \"io\"\n \"net/http\"\n \"os\"\n \"time\"\n)\n\nfunc main() {\n // Get or request the NGC_API_KEY\n nvcfRunKey := os.Getenv(\"NGC_API_KEY\")\n if len(nvcfRunKey) == 0 {\n nvcfRunKey = \"$NVIDIA_API_KEY\"\n }\n // Define constants and payload\n invokeURL := \"https://climate.api.nvidia.com/v1/nvidia/corrdiff\"\n outputFile := \"output.zip\"\n payload := `{\"input_id\": \u003c%- request.input_id %\u003e, \"samples\": \u003c%- request.samples %\u003e, \"steps\": \u003c%- request.steps %\u003e}`\n fmt.Println(\"Payload:\", payload)\n\n // Make initial request\n fmt.Printf(\"%s Making inference request\\n\", time.Now())\n req, err := http.NewRequest(\"POST\", invokeURL, bytes.NewBuffer([]byte(payload)))\n if err != nil {\n fmt.Println(\"Error creating request:\", err)\n return\n }\n req.Header.Set(\"Content-Type\", \"application/json\")\n req.Header.Set(\"Authorization\", \"Bearer \"+nvcfRunKey)\n req.Header.Set(\"NVCF-POLL-SECONDS\", \"5\")\n\n client := \u0026http.Client{}\n resp, err := client.Do(req)\n if err != nil {\n fmt.Println(\"Request error:\", err)\n return\n }\n defer resp.Body.Close()\n\n // Check HTTP status code\n if resp.StatusCode != 202 {\n fmt.Printf(\"Unexpected HTTP status: %d\\n\", resp.StatusCode)\n return\n }\n\n // Get NVCF-ReqID header from response\n reqID := resp.Header.Get(\"nvcf-reqid\")\n fmt.Printf(\"Request ID: %s\\n\", reqID)\n\n // Poll the status endpoint\n statusURL := fmt.Sprintf(\"https://api.nvcf.nvidia.com/v2/nvcf/pexec/status/%s\", reqID)\n fmt.Printf(\"%s Polling job %s\\n\", time.Now(), reqID)\n\n for {\n statusReq, err := http.NewRequest(\"GET\", statusURL, nil)\n statusReq.Header.Set(\"Content-Type\", \"application/json\")\n statusReq.Header.Set(\"Authorization\", \"Bearer \"+nvcfRunKey)\n statusReq.Header.Set(\"NVCF-POLL-SECONDS\", \"5\")\n\n statusResp, err := client.Do(statusReq)\n if err != nil {\n fmt.Println(\"Status request error:\", err)\n return\n }\n defer statusResp.Body.Close()\n\n // Check status response HTTP code\n if statusResp.StatusCode == 200 {\n // Save response to file\n file, err := os.Create(outputFile)\n defer file.Close()\n _, err = io.Copy(file, statusResp.Body)\n if err != nil {\n fmt.Println(\"Error saving response to file:\", err)\n return\n }\n fmt.Println(\"Saved response to file\")\n break\n } else if statusResp.StatusCode == 302 {\n // Download large asset from redirected location\n assetURL := statusResp.Header.Get(\"Location\")\n fmt.Println(\"Downloading large asset\")\n assetResp, err := client.Get(assetURL)\n if err != nil {\n fmt.Println(\"Error downloading asset:\", err)\n return\n }\n defer assetResp.Body.Close()\n file, err := os.Create(outputFile)\n defer file.Close()\n _, err = io.Copy(file, assetResp.Body)\n if err != nil {\n fmt.Println(\"Error saving asset to file:\", err)\n return\n }\n break\n } else if statusResp.StatusCode != 202 {\n fmt.Printf(\"Unexpected HTTP status: %d\\n\", statusResp.StatusCode)\n respBody, _ := io.ReadAll(statusResp.Body)\n fmt.Println(\"Response:\", string(respBody))\n return\n }\n\n fmt.Printf(\"%s Job still running, status %d\\n\", time.Now(), statusResp.StatusCode)\n time.Sleep(3 * time.Second)\n }\n}"])</script><script>self.__next_f.push([1,"8c:T799,#!/usr/bin/env python3\nimport os\nimport sys\nimport requests\nimport time\nimport logging\n\nlogging.basicConfig(\n format='%(asctime)s %(levelname)-8s %(message)s',\n level=logging.INFO,\n datefmt='%Y-%m-%d %H:%M:%S')\n\noutput_file = \"output.zip\"\n\ninvoke_url = \"https://climate.api.nvidia.com/v1/nvidia/corrdiff\"\nheaders = {\n \"Authorization\": f\"Bearer {os.getenv('NGC_API_KEY', '$NVIDIA_API_KEY')}\",\n \"NVCF-POLL-SECONDS\": \"5\"\n}\npayload = {\n \"input_id\": \u003c%- request.input_id %\u003e,\n \"samples\": \u003c%- request.samples %\u003e,\n \"steps\": \u003c%- request.steps %\u003e,\n}\n\n# re-use connections\nsession = requests.Session()\n\nlogging.info(f\"Payload {payload}\")\nlogging.info(\"Making inference request\")\nresponse = session.post(invoke_url, headers=headers, json=payload)\nresponse.raise_for_status()\nif response.status_code == 202:\n request_id = response.headers['nvcf-reqid']\nelse:\n raise Exception(\"Failed request\")\n\nlogging.info(f\"Polling job {request_id}\")\nstatus_url = f\"https://api.nvcf.nvidia.com/v2/nvcf/pexec/status/{request_id}\"\nwhile(True):\n response = session.get(status_url, headers=headers, allow_redirects=False)\n response.raise_for_status()\n # Invocation is fulfilled.\n if response.status_code == 200:\n logging.info(f\"Invocation is fulfilled. Downloading to {output_file}\")\n with open(output_file, 'wb') as f:\n f.write(response.content)\n break\n # Large asset response\n elif response.status_code == 302:\n logging.info(f\"Downloading large asset output to {output_file}\")\n asset_url = response.headers['Location']\n with requests.get(asset_url, stream=True) as r:\n with open(output_file, 'wb') as f:\n f.write(r.content)\n break\n # Response in progress\n elif response.status_code == 202:\n logging.info(f\"Job still running\")\n else:\n raise Exception(f\"Unexpected status code {response.status_code}\")\n time.sleep(3)8d:Td75,"])</script><script>self.__next_f.push([1,"Pull and run the [NVIDIA Earth-2 CorrDiff NIM](https://catalog.ngc.nvidia.com/orgs/nim/teams/nvidia/containers/corrdiff) with the command below. \n\n```bash\ndocker pull nvcr.io/nim/nvidia/corrdiff:1.0.0\n```\n\nThis will download the optimized model for your infrastructure.\n\n```bash\nexport NGC_API_KEY=\u003cNGC API Key\u003e\n\ndocker run --rm --runtime=nvidia --gpus all --shm-size 4g \\\n -p 8000:8000 \\\n -e NGC_API_KEY \\\n nvcr.io/nim/nvidia/corrdiff:1.0.0\n```\n\nCheck the health of the NIM with the following curl command:\n\n```bash\ncurl -X 'GET' \\\n 'http://localhost:8000/v1/health/ready' \\\n -H 'accept: application/json'\n```\n\nGenerate an input numpy array for the model using the following Python script with [Earth2Studio](https://github.com/NVIDIA/earth2studio).\nSee the NVIDIA NIM Docs [quick start guide](https://docs.nvidia.com/nim/earth-2/corrdiff/latest/quickstart-guide.html#fetching-input-data) for more details.\n\n```python\nfrom datetime import datetime, timedelta\n\nimport numpy as np\nimport torch\nfrom earth2studio.data import GEFS_FX, GEFS_FX_721x1440\n\nGEFS_SELECT_VARIABLES = [\"u10m\",\"v10m\",\"t2m\",\"r2m\",\"sp\",\"msl\",\"tcwv\"]\nGEFS_VARIABLES = [\"u1000\",\"u925\",\"u850\",\"u700\",\"u500\",\"u250\",\"v1000\",\"v925\",\"v850\",\\\n \"v700\",\"v500\",\"v250\",\"z1000\",\"z925\",\"z850\",\"z700\",\"z500\",\"z200\",\"t1000\",\"t925\",\\\n \"t850\",\"t700\",\"t500\",\"t100\",\"r1000\",\"r925\",\"r850\",\"r700\",\"r500\",\"r100\"]\n\nds_gefs = GEFS_FX(cache=True)\nds_gefs_select = GEFS_FX_721x1440(cache=True, product=\"gec00\")\n\ndef fetch_input_gefs(\n time: datetime, lead_time: timedelta, content_dtype: str = \"float32\"\n):\n dtype = np.dtype(getattr(np, content_dtype))\n # Fetch high-res select GEFS input data\n select_data = ds_gefs_select(time, lead_time, GEFS_SELECT_VARIABLES)\n select_data = select_data.values\n # Crop to bounding box [225, 21, 300, 53]\n select_data = select_data[:, 0, :, 148:277, 900:1201].astype(dtype)\n assert select_data.shape == (1, len(GEFS_SELECT_VARIABLES), 129, 301)\n\n # Fetch GEFS input data\n pressure_data = ds_gefs(time, lead_time, GEFS_VARIABLES)\n # Interpolate to 0.25 grid\n pressure_data = torch.nn.functional.interpolate(\n torch.Tensor(pressure_data.values),\n (len(GEFS_VARIABLES), 721, 1440),\n mode=\"nearest\",\n )\n pressure_data = pressure_data.numpy()\n # Crop to bounding box [225, 21, 300, 53]\n pressure_data = pressure_data[:, 0, :, 148:277, 900:1201].astype(dtype)\n assert pressure_data.shape == (1, len(GEFS_VARIABLES), 129, 301)\n\n # Create lead time field\n lead_hour = int(lead_time.total_seconds() // (3 * 60 * 60)) * np.ones(\n (1, 1, 129, 301)\n ).astype(dtype)\n\n input_data = np.concatenate([select_data, pressure_data, lead_hour], axis=1)[None]\n return input_data \n\n\ninput_array = fetch_input_gefs(datetime(2023, 1, 1), timedelta(hours=0))\nnp.save(\"corrdiff_inputs.npy\", input_array)\n```\n\nYou can now make a local API call using this curl command:\n\n```bash\ncurl -X POST \\\n -F \"input_array=@corrdiff_inputs.npy\" \\\n -F \"samples=2\" \\\n -F \"steps=12\" \\\n -o output.tar \\\n http://localhost:8000/v1/infer\n```\n\nFor more details on getting started with this NIM, visit the [NVIDIA NIM Docs](https://docs.nvidia.com/nim/earth-2/corrdiff/latest/quickstart-guide.html).\nFor more details on the model and its input / output tensors see the [US CorrDiff Model Card](https://catalog.ngc.nvidia.com/orgs/nim/teams/nvidia/models/earth2-corrdiff-us-gefs-hrrr).\n"])</script><script>self.__next_f.push([1,"8e:T770,Field | Response\n:----------------------------------------------------------------------------------------------------------------------------------|:-----------------------------------------------\nGeneratable or reverse engineerable personally-identifiable information (PII)? | None\nWas consent obtained for any personal data used? | Not Applicable (N/A)\nProtected class data used to create this model? | None\nHow often is dataset reviewed? | Before Release\nIs a mechanism in place to honor data subject right of access or deletion of personal data? | No\nIf personal data collected for the development of the model, was it collected directly by NVIDIA? | N/A\nIf personal data collected for the development of the model by NVIDIA, do you maintain or have access to disclosures made to data subjects? | N/A\nIf personal data collected for the development of this AI model, was it minimized to only what was required? | N/A\nIs there provenance for all datasets used in training? | Yes\nDoes data labeling (annotation, metadata) comply with privacy laws? | Yes\nIs data compliant with data subject requests for data correction or removal, if such a request was made?8f:T1688,"])</script><script>self.__next_f.push([1,"## Model Overview\n\n### Description\n\nFourCastNet V2 uses Spherical Fourier Neural Operator (SFNO) to predict a collection of surface and atmospheric variables such as wind speed, temperature and pressure and is applied to forecasting global atmospheric dynamics.\n\nFourCastNet is a data-driven model that provides accurate short to medium-range global predictions at a time-step size of 6 hours with predictive stability for over a year of simulated time (1,460 steps), while retaining physically plausible dynamics.\n\nThis model is ready for commercial use.\n\n### Reference(s)\n\n* [Spherical Fourier Neural Operator Paper](https://arxiv.org/abs/2306.03838) \u003cbr\u003e\n* [FourCastNet Paper](https://arxiv.org/abs/2202.11214) \u003cbr\u003e\n* [Codebase](https://github.com/NVIDIA/modulus) \u003cbr\u003e\n* [The ERA5 global reanalysis](https://doi.org/10.1002/qj.3803) \u003cbr\u003e\n\n### Model Architecture\n\n**Architecture Type:** Neural Operator \u003cbr\u003e\n**Network Architecture:** FourCastNet SFNO \u003cbr\u003e\n\n### Input\n\n**Input Type(s):**\n\n- Tensor (73 Surface \u0026 Atmospheric Variables)\n- DateTime\u003cbr\u003e\n\n**Input Format(s):** NumPy \u003cbr\u003e\n**Input Parameters:**\n\n- Four Dimensional (4D) (batch, variable, latitude, longitude) \u003cbr\u003e\n- Input DateTime\u003cbr\u003e\n\n**Other Properties Related to Input:**\n- 0.25 degree latitude-longitude grid\n- Input resolution: [721, 1440]\n- Latitude Coordinates: [90, 89.75, 89.5, ..., -89.5, -89.75, -90]\n- Longitude Coordinates: [0, 0.25, 0.5, ..., 359.25, 359.5, 359.75]\n- Input weather variables: \"u10m\", \"v10m\", \"u100m\", \"v100m\", \"t2m\", \"sp\", \"msl\", \"tcwv\", \"u50\", \"u100\", \"u150\", \"u200\", \"u250\", \"u300\", \"u400\", \"u500\", \"u600\", \"u700\", \"u850\", \"u925\", \"u1000\", \"v50\", \"v100\", \"v150\", \"v200\", \"v250\", \"v300\", \"v400\", \"v500\", \"v600\", \"v700\", \"v850\", \"v925\", \"v1000\", \"z50\", \"z100\", \"z150\", \"z200\", \"z250\", \"z300\", \"z400\", \"z500\", \"z600\", \"z700\", \"z850\", \"z925\", \"z1000\", \"t50\", \"t100\", \"t150\", \"t200\", \"t250\", \"t300\", \"t400\", \"t500\", \"t600\", \"t700\", \"t850\", \"t925\", \"t1000\", \"q50\", \"q100\", \"q150\", \"q200\", \"q250\", \"q300\", \"q400\", \"q500\", \"q600\", \"q700\", \"q850\", \"q925\", \"q1000\"\u003cbr\u003e\n\n### Output\n\n**Output Type(s):**\n\n- Tensor (73 Surface \u0026 Atmospheric Variables)\n\n**Output Format(s):** NumPy \u003cbr\u003e\n**Output Parameters:**\n\n- Four Dimensional (4D) (batch, variable, latitude, longitude) \u003cbr\u003e\n\n**Other Properties Related to Output:**\n- Time-delta of 6 hours from input array\n- 0.25 degree latitude-longitude grid\n- Output resolution: [721, 1440]\n- Latitude Coordinates: [90, 89.75, 89.5, ..., -89.5, -89.75, -90]\n- Longitude Coordinates: [0, 0.25, 0.5, ..., 359.25, 359.5, 359.75]\n- Output weather variables: \"u10m\", \"v10m\", \"u100m\", \"v100m\", \"t2m\", \"sp\", \"msl\", \"tcwv\", \"u50\", \"u100\", \"u150\", \"u200\", \"u250\", \"u300\", \"u400\", \"u500\", \"u600\", \"u700\", \"u850\", \"u925\", \"u1000\", \"v50\", \"v100\", \"v150\", \"v200\", \"v250\", \"v300\", \"v400\", \"v500\", \"v600\", \"v700\", \"v850\", \"v925\", \"v1000\", \"z50\", \"z100\", \"z150\", \"z200\", \"z250\", \"z300\", \"z400\", \"z500\", \"z600\", \"z700\", \"z850\", \"z925\", \"z1000\", \"t50\", \"t100\", \"t150\", \"t200\", \"t250\", \"t300\", \"t400\", \"t500\", \"t600\", \"t700\", \"t850\", \"t925\", \"t1000\", \"q50\", \"q100\", \"q150\", \"q200\", \"q250\", \"q300\", \"q400\", \"q500\", \"q600\", \"q700\", \"q850\", \"q925\", \"q1000\"\u003cbr\u003e\n\n### Software Integration\n\n**Runtime Engine(s):** Not Applicable \u003cbr\u003e\n**Supported Hardware Microarchitecture Compatibility:** \u003cbr\u003e\n* Ampere \u003cbr\u003e\n* Hopper \u003cbr\u003e\n* Turing \u003cbr\u003e\n\n**Supported Operating System(s):**\n* Linux \u003cbr\u003e\n\n### Model Version(s)\n\n**Model version:** v1 \u003cbr\u003e\n\n## Training, Testing, and Evaluation Datasets:\n\n### Training Dataset\n\n**Link:** [ERA5](https://cds.climate.copernicus.eu/) \u003cbr\u003e\n\n*Data Collection Method by dataset* \u003cbr\u003e\n* Automatic/Sensors \u003cbr\u003e\n\n*Labeling Method by dataset* \u003cbr\u003e\n* Automatic/Sensors \u003cbr\u003e\n\n**Properties (Quantity, Dataset Descriptions, Sensor(s)):**\nERA5 data for the years of 1979-2017. ERA5 provides hourly estimates of various\natmospheric, land, and oceanic climate variables. The data covers the Earth on a 30km\ngrid and resolves the atmosphere at 137 levels. \u003cbr\u003e\n\n### Evaluation Dataset\n\n**Link:** [ERA5](https://cds.climate.copernicus.eu/) \u003cbr\u003e\n\n*Data Collection Method by dataset* \u003cbr\u003e\n* Automatic/Sensors \u003cbr\u003e\n\n*Labeling Method by dataset* \u003cbr\u003e\n* Automatic/Sensors \u003cbr\u003e\n\n**Properties (Quantity, Dataset Descriptions, Sensor(s)):**\nERA5 data for the year of 2018. ERA5 provides hourly estimates of various atmospheric,\nland, and oceanic climate variables. The data covers the Earth on a 30km grid and\nresolves the atmosphere at 137 levels. \u003cbr\u003e\n\n## Inference:\n\n**Engine:** [Triton](https://developer.nvidia.com/triton-inference-server) \u003cbr\u003e\n**Test Hardware:**\n* A100 \u003cbr\u003e\n* H100 \u003cbr\u003e\n* L40S \u003cbr\u003e\n* RTX6000 \u003cbr\u003e\n\n### Ethical Considerations:\n\nNVIDIA believes Trustworthy AI is a shared responsibility and we have established\npolicies and practices to enable development for a wide array of AI applications.\nWhen downloaded or used in accordance with our terms of service, developers should work\nwith their supporting model team to ensure this model meets requirements for the\nrelevant industry and use case and addresses unforeseen product misuse.\nFor more detailed information on ethical considerations for this model, please see the\nModel Card++ Explainability, Bias, Safety \u0026 Security, and Privacy Subcards [here](https://ai.nvidia.com).\nPlease report security vulnerabilities or NVIDIA AI Concerns [here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/).\n\n### License\n\nThis model is licensed under the [NVIDIA AI Product Agreement](https://www.nvidia.com/en-us/agreements/enterprise-software/product-specific-terms-for-ai-products/). By pulling and using this model, you accept the terms and conditions of this license.\n\n**You are responsible for ensuring that your use of NVIDIA AI Foundation Models complies with all applicable laws.**\n"])</script><script>self.__next_f.push([1,"90:T801,"])</script><script>self.__next_f.push([1,"Field | Response\n:------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------\nIntended Application \u0026 Domain: | Global Weather Forecasting\nModel Type: | Neural Operator\nIntended User: | Climate and Weather scientists accelerating weather prediction with AI.\nOutput: | Global forecast prediction of surface and atmosphere variables.\nDescribe how the model works: | Neural operator auto-regressively predicts a time-series forecast from an initial state.\nName the adversely impacted groups this has been tested to deliver comparable outcomes regardless of: | Not Applicable\nTechnical Limitations: | The model may perform poorly for longer range forecasts and atmospheric data sources different from that in the ERA5 training dataset\nVerified to have met prescribed NVIDIA quality standards: | Yes\nPerformance Metrics: | Accuracy, Throughput and Latency\nPotential Known Risks: | This model may mispredict global atmospheric dynamics.\nLicensing: | [Earth-2 Service Terms of Use](https://ngc.nvidia.com/legal/terms)"])</script><script>self.__next_f.push([1,"91:T679,Pull and run the [NVIDIA Earth-2 FourCastNet NIM](https://catalog.ngc.nvidia.com/orgs/nim/teams/nvidia/containers/fourcastnet) with the command below. \n\n```bash\ndocker pull nvcr.io/nim/nvidia/fourcastnet:1.0.0\n```\n\nThis will download the optimized model for your infrastructure.\n\n```bash\nexport NGC_API_KEY=\u003cNGC API Key\u003e\n\ndocker run --rm --runtime=nvidia --gpus all --shm-size 4g \\\n -p 8000:8000 \\\n -e NGC_API_KEY \\\n nvcr.io/nim/nvidia/fourcastnet:1.0.0\n```\n\nCheck the health of the NIM with the following curl command:\n\n```bash\ncurl -X 'GET' \\\n 'http://localhost:8000/v1/health/ready' \\\n -H 'accept: application/json'\n```\n\nGenerate an input numpy array for the model using the following Python script with [Earth2Studio](https://github.com/NVIDIA/earth2studio):\n\n```python\nimport numpy as np\nfrom datetime import datetime\nfrom earth2studio.data import ARCO\nfrom earth2studio.models.px.sfno import VARIABLES\n\nds = ARCO()\nda = ds(time=datetime(2023, 1, 1), variable=VARIABLES)\nnp.save(\"fcn_inputs.npy\", da.to_numpy()[None].astype('float32'))\n```\n\nYou can now make a local API call using this curl command:\n\n```bash\ncurl -X POST \\\n -F \"input_array=@fcn_inputs.npy\" \\\n -F \"input_time=2023-01-01T00:00:00Z\" \\\n -F \"simulation_length=4\" \\\n -o output.tar \\\n http://localhost:8000/v1/infer\n```\n\nFor more details on getting started with this NIM, visit the [NVIDIA NIM Docs](https://docs.nvidia.com/nim/earth-2/fourcastnet/latest/getting-started.html).\nFor more details on the model and its input / output tensors see the [FourCastNet SFNO Model Card](https://catalog.ngc.nvidia.com/orgs/nim/teams/nvidia/models/earth2-sfno-era5-73ch).\n92:T93d,"])</script><script>self.__next_f.push([1,"Field | Response\n:----------------------------------------------------------------------------------------------------------------------------------|:-----------------------------------------------\nPersonal data used to create this model? | None Known. For data included in the base Llama 3.1 model, [reference the Llama 3.1 model card.](https://github.com/meta-llama/llama-models/blob/main/models/llama3_1/MODEL_CARD.md)\nWas consent obtained for any personal data used? | Not Applicable for NVIDIA training data; NVIDIA did not introduce personal data through retraining\nGeneratable or reverse engineerable personal data? | Not a known capability.\nHow often is the dataset reviewed (if applicable)? | Before Release\nIs a mechanism in place to honor data subject right of access or deletion of personal data? | Not Applicable for NVIDIA training data \nIf personal data collected for the development of the model, was it collected directly by NVIDIA? | Not Applicable\nIf personal data collected for the development of the model by NVIDIA, do you maintain or have access to disclosures made to data subjects? | Not Applicable\nIf personal data collected for the development of this AI model, was it minimized to only what was required? | Not Applicable for NVIDIA training data \nIs there provenance for all datasets used in training? | Yes\nDoes data labeling (annotation, metadata) comply with privacy laws? | Not Applicable for NVIDIA training data\nIs data compliant with data subject requests for data correction or removal, if such a request was made? | Not Applicable for NVIDIA training data"])</script><script>self.__next_f.push([1,"93:Td87,"])</script><script>self.__next_f.push([1,"## Model Overview\n\n### Description:\n\nLlama-3.1-Nemotron-70B-Instruct is a large language model customized by NVIDIA to improve the helpfulness of LLM generated responses to user queries.\n\nThis model is ready for commercial use.\n\n### Terms of use\n\nBy accessing this model, you are agreeing to the LLama 3 terms and conditions of the [license](https://github.com/meta-llama/llama-models/blob/main/models/llama3_1/LICENSE), [acceptable use policy](https://github.com/meta-llama/llama-models/blob/main/models/llama3_1/USE_POLICY.md) and [Meta’s privacy policy](https://www.facebook.com/privacy/policy/)\n\n### References(s):\n\n* [HelpSteer2-Preference](https://arxiv.org/abs/2410.01257)\n* [SteerLM method](https://arxiv.org/abs/2310.05344)\n* [HelpSteer](https://arxiv.org/abs/2311.09528)\n* [HelpSteer2](https://arxiv.org/abs/2406.08673)\n* [Introducing Llama 3.1: Our most capable models to date](https://ai.meta.com/blog/meta-llama-3-1/)\n* [Meta's Llama 3.1 Webpage](https://www.llama.com/docs/model-cards-and-prompt-formats/llama3_1)\n* [Meta's Llama 3.1 Model Card](https://github.com/meta-llama/llama-models/blob/main/models/llama3_1/MODEL_CARD.md)\n\n### Model Architecture:\n\n**Architecture Type:** Transformer \u003cbr\u003e\n**Network Architecture:** Llama 3.1 \u003cbr\u003e\n\n### Input:\n\n**Input Type(s):** Text \u003cbr\u003e\n**Input Format:** String \u003cbr\u003e\n**Input Parameters:** One Dimensional (1D) \u003cbr\u003e\n**Other Properties Related to Input:** Max of 128k tokens\u003cbr\u003e\n\n### Output:\n\n**Output Type(s):** Text \u003cbr\u003e\n**Output Format:** String \u003cbr\u003e\n**Output Parameters:** One Dimensional (1D) \u003cbr\u003e\n**Other Properties Related to Output:** Max of 4k tokens \u003cbr\u003e\n\n### Software Integration:\n\n**Supported Hardware Microarchitecture Compatibility:** \u003cbr\u003e\n* NVIDIA Ampere \u003cbr\u003e\n* NVIDIA Hopper \u003cbr\u003e\n* NVIDIA Turing \u003cbr\u003e\n **Supported Operating System(s):** Linux \u003cbr\u003e\n\n### Model Version:\n\nv1.0\n\n## Training \u0026 Evaluation:\n\n### Datasets:\n\n**Data Collection Method by dataset** \u003cbr\u003e\n* [Hybrid: Human, Synthetic] \u003cbr\u003e\n\n**Labeling Method by dataset** \u003cbr\u003e\n* [Human] \u003cbr\u003e\n\n**Link:**\n* [HelpSteer2](https://huggingface.co/datasets/nvidia/HelpSteer2)\n\n**Properties (Quantity, Dataset Descriptions, Sensor(s)):** \u003cbr\u003e\n* 21, 362 prompt-responses built to make more models more aligned with human preference - specifically more helpful, factually-correct, coherent, and customizable based on complexity and verbosity.\n* 20, 324 prompt-responses used for training and 1, 038 used for validation.\n\n## Inference:\n\n**Engine:** [Triton](https://developer.nvidia.com/triton-inference-server) \u003cbr\u003e\n**Test Hardware:** H100, A100 80GB, A100 40GB \u003cbr\u003e\n\n### Ethical Considerations:\n\nNVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their supporting model team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse. For more detailed information on ethical considerations for this model, please see the Model Card++ Explainability, Bias, Safety \u0026 Security, and Privacy Subcards. Please report security vulnerabilities or NVIDIA AI Concerns [here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/).\n\nPlease report security vulnerabilities or NVIDIA AI Concerns [here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/).\n"])</script><script>self.__next_f.push([1,"94:T828,"])</script><script>self.__next_f.push([1,"Field | Response\n:------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------\nIntended Application \u0026 Domain: | Response Customization in Large Language Model Development\nModel Type: | Text-to-Text Transformer\nIntended User: | Developers customizing model response across different applications and domains.\nOutput: | Text\nDescribe how the model works: | Generates a response based on a prior conversation. \nName the adversely impacted groups this has been tested to deliver comparable outcomes regardless of: | Not Applicable\nVerified to have met prescribed quality standards: | Yes\nTechnical Limitations: | This model may not work for non-English languages.\nPerformance Metrics: | Throughput and Latency\nPotential Known Risks: | The Model may produce output that is biased and toxic based on how it is prompted, producing socially unacceptable or undesirable text, even if the prompt itself does not include anything explicitly offensive. The model may also amplify biases and return toxic responses especially when prompted with toxic prompts. \nLicensing: | [Llama 3.1 Community License Agreement](https://github.com/meta-llama/llama-models/blob/main/models/llama3_1/LICENSE)"])</script><script>self.__next_f.push([1,"95:T15dd,"])</script><script>self.__next_f.push([1,"## Model Overview\n\n### Description:\n\nAlphaFold2 is a deep learning model for protein structure prediction developed by the research group at DeepMind, an artificial intelligence (AI) research lab owned by Google (`jumper2021alphafold`). AlphaFold2 builds on the success of its predecessor, AlphaFold, and represents a significant breakthrough in the field of protein structure prediction. This model is available for commercial use.\n\u003cbr\u003e\n\n### Third-Party Community Consideration\n\nThis model is not owned or developed by NVIDIA. This model has been developed and built to a third-party’s requirements for this application and use case.\n\n#### License / Terms of Use\n\nThe AlphaFold2 code is released under the [Apache 2.0 License](https://github.com/google-deepmind/alphafold/blob/main/LICENSE). The model parameters are licensed under the [CC BY 4.0 License](https://github.com/google-deepmind/alphafold?tab=readme-ov-file#model-parameters).\n\n### References:\n\n```\n@ARTICLE{jumper2021alphafold,\n title = \"Highly accurate protein structure prediction with {AlphaFold}\",\n author = \"Jumper, John and Evans, Richard and Pritzel, Alexander and Green,\n Tim and Figurnov, Michael and Ronneberger, Olaf and\n Tunyasuvunakool, Kathryn and Bates, Russ and {\\v Z}{\\'\\i}dek,\n Augustin and Potapenko, Anna and Bridgland, Alex and Meyer,\n Clemens and Kohl, Simon A A and Ballard, Andrew J and Cowie,\n Andrew and Romera-Paredes, Bernardino and Nikolov, Stanislav and\n Jain, Rishub and Adler, Jonas and Back, Trevor and Petersen, Stig\n and Reiman, David and Clancy, Ellen and Zielinski, Michal and\n Steinegger, Martin and Pacholska, Michalina and Berghammer, Tamas\n and Bodenstein, Sebastian and Silver, David and Vinyals, Oriol\n and Senior, Andrew W and Kavukcuoglu, Koray and Kohli, Pushmeet\n and Hassabis, Demis\",\n journal = \"Nature\",\n volume = 596,\n number = 7873,\n pages = \"583--589\",\n month = aug,\n year = 2021,\n language = \"en\",\n doi = {10.1038/s41586-021-03819-2},\n}\n```\n\n\u003cbr\u003e\n\n### Model Architecture:\n\n**Architecture Type:** Protein Structure Prediction \u003cbr\u003e\n**Network Architecture:** AlphaFold2 \u003cbr\u003e\n\n**Input Type(s):** Protein Sequence, Relax Prediction (Default True) \u003cbr\u003e\n**Input Format(s):** String (less than or equal to 4096 characters), boolean \u003cbr\u003e\n**Input Parameters:** 1D \u003cbr\u003e\n**Other Properties Related to Input:** NA \u003cbr\u003e\n\n### Output:\n\n**Output Type(s):** Protein Structure(s) in PDB Format \u003cbr\u003e\n**Output Format:** PDB (text file)\u003cbr\u003e\n**Output Parameters:** 1D \u003cbr\u003e\n**Other Properties Related to Output:** Pose (num_atm_ x 3)\u003cbr\u003e\n\n### Software Integration:\n\n**Runtime Engine(s):**\n* Python \u003cbr\u003e\n\n**Supported Hardware Microarchitecture Compatibility:** \u003cbr\u003e\n* NVIDIA Ampere \u003cbr\u003e\n\n**[Preferred/Supported] Operating System(s):** \u003cbr\u003e\n* [Linux] \u003cbr\u003e\n\n### Model Version(s):\n\nAlphaFold2 2.3.2 \u003cbr\u003e\n\n## Training \u0026 Evaluation:\n\n### Training Dataset:\n\n**Link:** A description of the training dataset and relevant download links are available at [https://www.nature.com/articles/s41586-021-03819-2#data-availability](https://www.nature.com/articles/s41586-021-03819-2#data-availability). This data was not collected by NVIDIA. \u003cbr\u003e\n** Data Collection Method by dataset \u003cbr\u003e\n* See the description at [https://www.nature.com/articles/s41586-021-03819-2#data-availability](https://www.nature.com/articles/s41586-021-03819-2#data-availability). \u003cbr\u003e\n\n** Labeling Method by dataset \u003cbr\u003e\n* See the description at [https://www.nature.com/articles/s41586-021-03819-2#data-availability](https://www.nature.com/articles/s41586-021-03819-2#data-availability). \u003cbr\u003e\n\n**Properties (Quantity, Dataset Descriptions, Sensor(s)):**\nUniclust dataset of 355,993 sequences with the full MSAs. These predictions were then used to train a final model with identical hyperparameters, except for sampling examples 75% of the time from the Uniclust prediction set, with sub-sampled MSAs, and 25% of the time from the clustered PDB set.\n\u003cbr\u003e\n\n### Evaluation Dataset:\n\n**Link:** See the description at [https://www.nature.com/articles/s41586-021-03819-2#Sec10](https://www.nature.com/articles/s41586-021-03819-2#Sec10). \u003cbr\u003e\n** Data Collection Method by dataset \u003cbr\u003e\n* [Not Applicable] \u003cbr\u003e\n\n** Labeling Method by dataset \u003cbr\u003e\n* [Not Applicable] \u003cbr\u003e\n\n**Properties (Quantity, Dataset Descriptions, Sensor(s)):**\nUniclust dataset of 355,993 sequences with the full MSAs. These predictions were then used to train a final model with identical hyperparameters, except for sampling examples 75% of the time from the Uniclust prediction set, with sub-sampled MSAs, and 25% of the time from the clustered PDB set.\n\u003cbr\u003e\n\n### Inference:\n\n**Engine:** Python \u003cbr\u003e\n**Test Hardware:** \u003cbr\u003e\n* NVIDIA A6000 \u003cbr\u003e\n* NVIDIA A100 \u003cbr\u003e\n\n### Ethical Considerations:\n\nNVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their supporting model team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse. Please report security vulnerabilities or NVIDIA AI Concerns [here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/).\n\n**You are responsible for ensuring that your use of NVIDIA AI Foundation Models complies with all applicable laws.**\n"])</script><script>self.__next_f.push([1,"96:T9d7,"])</script><script>self.__next_f.push([1,"#!/usr/bin/env bash\nif [ \"$NVCF_RUN_KEY\" = \"\" ]; then read -p \"Paste Run Key: \" NVCF_RUN_KEY; fi\nURL=${URL:-https://health.api.nvidia.com/v1/biology/deepmind/alphafold2-multimer}\nSTATUS_URL=${STATUS_URL:-https://health.api.nvidia.com/v1/status}\n\nsequences='[\"GSHMAQPRPPFHITIPIYPGVDLLDVAAPVELFSWMADAWKARATTITLAAEHLTPLKTRDGLTLTPQRQFADYADAAAPQPQTHLLWVPGGAPDVLRKLMRGGPYLDFLKAQSAGADHVSSVCEGALLLAAAGLLDGYRATTHWAFIPCLQQFPAIKVAEGFPRYVIDGNRITGGGISSGLAEALAIVARVAGQDIAKHVQMITQYFPDPPFEQTIVPATHCPLQA\",\"GSHMAQPRPPFHITIPIYPGVDLLDVAAPVELFSWMADAWKARATTITLAAEHLTPLKTRDGLTLTPQRQFADYADAAAPQPQTHLLWVPGGAPDVLRKLMRGGPYLDFLKAQSAGADHVSSVCEGALLLAAAGLLDGYRATTHWAFIPCLQQFPAIKVAEGFPRYVIDGNRITGGGISSGLAEALAIVARVAGQDIAKHVQMITQYFPDPPFEQTIVPATHCPLQA\"]'\n\nrequest_body='{\n \"sequences\": '$sequences',\n \"algorithm\": \"jackhmmer\",\n \"e_value\": 0.0001,\n \"iterations\": 1,\n \"databases\": [\"uniref90\", \"small_bfd\", \"mgnify\"],\n \"relax_prediction\": true\n}'\noutput_file=\"output.json\"\n\n# Initial request\necho \"Making request...\"\nresponse=$(curl -s -D /dev/stderr --fail-with-body -H \"content-type: application/json\" -H \"Authorization: Bearer $NVCF_RUN_KEY\" -H \"NVCF-POLL-SECONDS: 1\" --request POST --data \"$request_body\" \"$URL\" 2\u003e\u00261 1\u003e $output_file)\n\n# Extract HTTP status code\nhttp_status=$(echo \"$response\" | awk '{print $2;exit}')\n\n# Check the status code\nif [ \"$http_status\" -eq 200 ]; then\n echo \"Saved response to file: $output_file\"\nelif [ \"$http_status\" -eq 202 ]; then\n echo \"Request accepted...\"\n # Extract nvcf-reqid header\n req_id=$(echo \"$response\" | grep -i \"nvcf-reqid:\" | awk '{print $2}' | tr -d '\\r')\n\n # Poll the /status endpoint\n while true; do\n echo \"Polling for response...\"\n status_response=$(curl -s -D /dev/stderr --fail-with-body -H \"content-type: application/json\" -H \"Authorization: Bearer $NVCF_RUN_KEY\" -H \"NVCF-POLL-SECONDS: 5\" --request GET \"${STATUS_URL}/${req_id}\" 2\u003e\u00261 1\u003e $output_file)\n\n status_http_status=$(echo \"$status_response\" | awk '{print $2;exit}')\n\n if [ \"$status_http_status\" -eq 200 ]; then\n echo \"Saved response to file: $output_file\"\n break\n elif [ \"$status_http_status\" -ne 202 ]; then\n echo \"Unexpected HTTP status: $status_http_status\"\n echo \"Response: $status_response\"\n exit 1\n fi\n\n # Wait before polling again\n sleep 5\n done\nelse\n echo \"Unexpected HTTP status: $http_status\"\n echo \"Response: $response\"\n exit 1\nfi"])</script><script>self.__next_f.push([1,"97:T8d4,"])</script><script>self.__next_f.push([1,"#!/usr/bin/env python3\nimport os\nimport requests\nimport time\nfrom pathlib import Path\n\n# Variables\nkey = os.getenv(\"NVCF_RUN_KEY\") or input(\"Paste the Run Key: \")\nurl = os.getenv(\"URL\", \"https://health.api.nvidia.com/v1/biology/deepmind/alphafold2-multimer\")\nstatus_url = os.getenv(\"STATUS_URL\", \"https://health.api.nvidia.com/v1/status\")\n\nsequences = [\n \"GSHMAQPRPPFHITIPIYPGVDLLDVAAPVELFSWMADAWKARATTITLAAEHLTPLKTRDGLTLTPQRQFADYADAAAPQPQTHLLWVPGGAPDVLRKLMRGGPYLDFLKAQSAGADHVSSVCEGALLLAAAGLLDGYRATTHWAFIPCLQQFPAIKVAEGFPRYVIDGNRITGGGISSGLAEALAIVARVAGQDIAKHVQMITQYFPDPPFEQTIVPATHCPLQA\",\n \"GSHMAQPRPPFHITIPIYPGVDLLDVAAPVELFSWMADAWKARATTITLAAEHLTPLKTRDGLTLTPQRQFADYADAAAPQPQTHLLWVPGGAPDVLRKLMRGGPYLDFLKAQSAGADHVSSVCEGALLLAAAGLLDGYRATTHWAFIPCLQQFPAIKVAEGFPRYVIDGNRITGGGISSGLAEALAIVARVAGQDIAKHVQMITQYFPDPPFEQTIVPATHCPLQA\"\n]\n\noutput_file = Path(\"output.json\")\n\n# Request to predict structure from a list of sequences, i.e. the NVCF endpoint for\n# http://localhost:8000/protein-structure/alphafold2/multimer/predict-structure-from-sequences\nheaders = {\n \"content-type\": \"application/json\",\n \"Authorization\": f\"Bearer {key}\",\n \"NVCF-POLL-SECONDS\": \"5\",\n}\ndata = {\n \"sequences\": sequences,\n \"algorithm\": \"jackhmmer\",\n \"e_value\": 0.0001,\n \"iterations\": 1,\n \"databases\": [\"uniref90\", \"small_bfd\", \"mgnify\"],\n \"relax_prediction\": True,\n}\n\nprint(\"Making request...\")\nresponse = requests.post(url, headers=headers, json=data)\n\n# Check the status code\nif response.status_code == 200:\n output_file.write_text(response.text)\n print(f\"Response output to file: {output_file}\")\nelif response.status_code == 202:\n print(\"Request accepted...\")\n # Extract reqId header\n req_id = response.headers.get(\"nvcf-reqid\")\n\n # Poll the /status endpoint\n while True:\n print(\"Polling for response...\")\n status_response = requests.get(f\"{status_url}/{req_id}\", headers=headers)\n\n if status_response.status_code != 202:\n output_file.write_text(status_response.text)\n print(f\"Response output to file: {output_file}\")\n break\n\n # Wait before polling again\n time.sleep(5)\nelse:\n print(f\"Unexpected HTTP status: {response.status_code}\")\n print(f\"Response: {response.text}\")"])</script><script>self.__next_f.push([1,"98:Tc10,"])</script><script>self.__next_f.push([1,"## Start NIM\n\n1. Export `NGC_CLI_API_KEY` variable.\n\n```\nexport NGC_CLI_API_KEY=\u003cyour personal NGC key\u003e\n```\n\n2. The NIM container automatically downloads any required models. To save time and bandwidth it\n is recommended to provide a local cache directory. This way the NIM will be able to\n reuse any already downloaded models. Execute the following command to setup the cache\n directory:\n\n```bash\nexport LOCAL_NIM_CACHE=~/.cache/nim\nmkdir -p $LOCAL_NIM_CACHE\n```\n\nNote that you may need to run `(sudo) chmod -R 777 $LOCAL_NIM_CACHE` after the AlphaFold2 model is downloaded to avoid permission issues.\n\n3. Run the NIM container with the following commands:\n\n```bash\ndocker run -it --rm \\\n --runtime=nvidia \\\n -p 8000:8000 \\\n -e NGC_CLI_API_KEY \\\n -v $LOCAL_NIM_CACHE:/opt/nim/.cache \\\n nvcr.io/nim/deepmind/alphafold2-multimer:1.0.0\n```\n\nThis command will start the NIM container and expose port 8000 for the user to interact with the NIM.\n\n4. Open a new terminal, leaving the terminal open with the just launched service. In the new terminal, wait until the health check end point returns `{\"status\":\"ready\"}` before proceeding. This may take a couple of minutes. You can use the following command to query the health check.\n\n```bash\ncurl -X 'GET' \\\n 'http://localhost:8000/v1/health/ready' \\\n -H 'accept: application/json'\n```\n\n## Python Client Example\n\n1. Save following Python example to a file named `nim_client.py`.\n\n```python\nimport requests\nimport json\n\nurl = \"http://localhost:8000/protein-structure/alphafold2/multimer/predict-structure-from-sequences\" # Replace with the actual URL\nsequences = [\"MNVIDIAIAMAI\", \"NESKHCAWVMIPTFRQYDGL\"] # Replace with the actual sequences.\n\nheaders = {\n \"content-type\": \"application/json\"\n}\n\ndata = {\n \"sequences\": sequences,\n \"databases\": [\"small_bfd\"],\n \"e_value\": 0.000001,\n \"algorithm\": \"jackhmmer\",\n \"num_predictions_per_model\" : 1,\n \"relax_prediction\": False,\n}\n\nresponse = requests.post(url, headers=headers, data=json.dumps(data))\n\n# Check if the request was successful\nif response.ok:\n with open(\"output.pdb\", \"w\") as ofi:\n ofi.write(json.dumps(response.json()))\n print(\"Request succeeded:\", response.json())\nelse:\n print(\"Request failed:\", response.status_code, response.text)\n```\n\n2. Execute the example.\n\n```bash\npython nim_client.py\n```\n\n3. The resulting PDB structure will be returned and written to `output.pdb`.\n\n```bash\ncat output.pdb\n```\n\n## Shell Client Example\n\n1. Save the following Shell example to a file named `nim_client.sh`.\n\n```bash\n#!/usr/bin/env bash\nset -e\n\nURL=http://localhost:8000/protein-structure/alphafold2/multimer/predict-structure-from-sequences\n\nrequest='{\n \"sequences\": [\"MNVIDIAIAMAI\", \"NESKHCAWVMIPTFRQYDGL\"]\n}'\ncurl -H 'Content-Type: application/json' \\\n -d \"$request\" \"$URL\"\n```\n\n2. Execute the example.\n\n```bash\nchmod +x nim_client.sh\n\n./nim_client.sh\n```\n\n3. Results will be printed on the terminal in JSON format. You will be able\n to see the PDB formatted output; you can also use curl to save the output directly to file.\n"])</script><script>self.__next_f.push([1,"99:T15dd,"])</script><script>self.__next_f.push([1,"## Model Overview\n\n### Description:\n\nAlphaFold2 is a deep learning model for protein structure prediction developed by the research group at DeepMind, an artificial intelligence (AI) research lab owned by Google (`jumper2021alphafold`). AlphaFold2 builds on the success of its predecessor, AlphaFold, and represents a significant breakthrough in the field of protein structure prediction. This model is available for commercial use.\n\u003cbr\u003e\n\n### Third-Party Community Consideration\n\nThis model is not owned or developed by NVIDIA. This model has been developed and built to a third-party’s requirements for this application and use case.\n\n#### License / Terms of Use\n\nThe AlphaFold2 code is released under the [Apache 2.0 License](https://github.com/google-deepmind/alphafold/blob/main/LICENSE). The model parameters are licensed under the [CC BY 4.0 License](https://github.com/google-deepmind/alphafold?tab=readme-ov-file#model-parameters).\n\n### References:\n\n```\n@ARTICLE{jumper2021alphafold,\n title = \"Highly accurate protein structure prediction with {AlphaFold}\",\n author = \"Jumper, John and Evans, Richard and Pritzel, Alexander and Green,\n Tim and Figurnov, Michael and Ronneberger, Olaf and\n Tunyasuvunakool, Kathryn and Bates, Russ and {\\v Z}{\\'\\i}dek,\n Augustin and Potapenko, Anna and Bridgland, Alex and Meyer,\n Clemens and Kohl, Simon A A and Ballard, Andrew J and Cowie,\n Andrew and Romera-Paredes, Bernardino and Nikolov, Stanislav and\n Jain, Rishub and Adler, Jonas and Back, Trevor and Petersen, Stig\n and Reiman, David and Clancy, Ellen and Zielinski, Michal and\n Steinegger, Martin and Pacholska, Michalina and Berghammer, Tamas\n and Bodenstein, Sebastian and Silver, David and Vinyals, Oriol\n and Senior, Andrew W and Kavukcuoglu, Koray and Kohli, Pushmeet\n and Hassabis, Demis\",\n journal = \"Nature\",\n volume = 596,\n number = 7873,\n pages = \"583--589\",\n month = aug,\n year = 2021,\n language = \"en\",\n doi = {10.1038/s41586-021-03819-2},\n}\n```\n\n\u003cbr\u003e\n\n### Model Architecture:\n\n**Architecture Type:** Protein Structure Prediction \u003cbr\u003e\n**Network Architecture:** AlphaFold2 \u003cbr\u003e\n\n**Input Type(s):** Protein Sequence, Relax Prediction (Default True) \u003cbr\u003e\n**Input Format(s):** String (less than or equal to 4096 characters), boolean \u003cbr\u003e\n**Input Parameters:** 1D \u003cbr\u003e\n**Other Properties Related to Input:** NA \u003cbr\u003e\n\n### Output:\n\n**Output Type(s):** Protein Structure(s) in PDB Format \u003cbr\u003e\n**Output Format:** PDB (text file)\u003cbr\u003e\n**Output Parameters:** 1D \u003cbr\u003e\n**Other Properties Related to Output:** Pose (num_atm_ x 3)\u003cbr\u003e\n\n### Software Integration:\n\n**Runtime Engine(s):**\n* Python \u003cbr\u003e\n\n**Supported Hardware Microarchitecture Compatibility:** \u003cbr\u003e\n* NVIDIA Ampere \u003cbr\u003e\n\n**[Preferred/Supported] Operating System(s):** \u003cbr\u003e\n* [Linux] \u003cbr\u003e\n\n### Model Version(s):\n\nAlphaFold2 2.3.2 \u003cbr\u003e\n\n## Training \u0026 Evaluation:\n\n### Training Dataset:\n\n**Link:** A description of the training dataset and relevant download links are available at [https://www.nature.com/articles/s41586-021-03819-2#data-availability](https://www.nature.com/articles/s41586-021-03819-2#data-availability). This data was not collected by NVIDIA. \u003cbr\u003e\n** Data Collection Method by dataset \u003cbr\u003e\n* See the description at [https://www.nature.com/articles/s41586-021-03819-2#data-availability](https://www.nature.com/articles/s41586-021-03819-2#data-availability). \u003cbr\u003e\n\n** Labeling Method by dataset \u003cbr\u003e\n* See the description at [https://www.nature.com/articles/s41586-021-03819-2#data-availability](https://www.nature.com/articles/s41586-021-03819-2#data-availability). \u003cbr\u003e\n\n**Properties (Quantity, Dataset Descriptions, Sensor(s)):**\nUniclust dataset of 355,993 sequences with the full MSAs. These predictions were then used to train a final model with identical hyperparameters, except for sampling examples 75% of the time from the Uniclust prediction set, with sub-sampled MSAs, and 25% of the time from the clustered PDB set.\n\u003cbr\u003e\n\n### Evaluation Dataset:\n\n**Link:** See the description at [https://www.nature.com/articles/s41586-021-03819-2#Sec10](https://www.nature.com/articles/s41586-021-03819-2#Sec10). \u003cbr\u003e\n** Data Collection Method by dataset \u003cbr\u003e\n* [Not Applicable] \u003cbr\u003e\n\n** Labeling Method by dataset \u003cbr\u003e\n* [Not Applicable] \u003cbr\u003e\n\n**Properties (Quantity, Dataset Descriptions, Sensor(s)):**\nUniclust dataset of 355,993 sequences with the full MSAs. These predictions were then used to train a final model with identical hyperparameters, except for sampling examples 75% of the time from the Uniclust prediction set, with sub-sampled MSAs, and 25% of the time from the clustered PDB set.\n\u003cbr\u003e\n\n### Inference:\n\n**Engine:** Python \u003cbr\u003e\n**Test Hardware:** \u003cbr\u003e\n* NVIDIA A6000 \u003cbr\u003e\n* NVIDIA A100 \u003cbr\u003e\n\n### Ethical Considerations:\n\nNVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their supporting model team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse. Please report security vulnerabilities or NVIDIA AI Concerns [here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/).\n\n**You are responsible for ensuring that your use of NVIDIA AI Foundation Models complies with all applicable laws.**\n"])</script><script>self.__next_f.push([1,"9a:T7539,"])</script><script>self.__next_f.push([1,"{\n \"pdbs\": [\n \"PARENT N/A\\nATOM 1 N MET A 1 12.501 2.331 -26.921 1.00 47.72 N \\nATOM 2 CA MET A 1 12.036 1.790 -25.647 1.00 50.64 C \\nATOM 3 C MET A 1 10.886 2.622 -25.090 1.00 50.01 C \\nATOM 4 CB MET A 1 13.182 1.737 -24.635 1.00 43.04 C \\nATOM 5 O MET A 1 11.032 3.828 -24.879 1.00 48.15 O \\nATOM 6 CG MET A 1 13.327 0.391 -23.944 1.00 41.60 C \\nATOM 7 SD MET A 1 14.560 0.428 -22.585 1.00 39.32 S \\nATOM 8 CE MET A 1 14.275 -1.206 -21.850 1.00 35.36 C \\nATOM 9 N SER A 2 9.707 2.634 -25.722 1.00 54.18 N \\nATOM 10 CA SER A 2 8.571 3.356 -25.157 1.00 55.29 C \\nATOM 11 C SER A 2 8.396 3.039 -23.675 1.00 54.83 C \\nATOM 12 CB SER A 2 7.288 3.015 -25.915 1.00 49.15 C \\nATOM 13 O SER A 2 8.428 1.873 -23.277 1.00 52.08 O \\nATOM 14 OG SER A 2 6.187 2.929 -25.027 1.00 48.74 O \\nATOM 15 N LEU A 3 9.218 3.712 -22.773 1.00 56.59 N \\nATOM 16 CA LEU A 3 8.914 3.579 -21.352 1.00 57.28 C \\nATOM 17 C LEU A 3 7.407 3.556 -21.119 1.00 57.34 C \\nATOM 18 CB LEU A 3 9.548 4.724 -20.558 1.00 52.72 C \\nATOM 19 O LEU A 3 6.702 4.494 -21.495 1.00 55.22 O \\nATOM 20 CG LEU A 3 11.023 4.558 -20.188 1.00 50.52 C \\nATOM 21 CD1 LEU A 3 11.657 5.918 -19.916 1.00 46.13 C \\nATOM 22 CD2 LEU A 3 11.170 3.641 -18.978 1.00 46.40 C \\nATOM 23 N LYS A 4 6.644 2.377 -21.470 1.00 56.17 N \\nATOM 24 CA LYS A 4 5.297 2.253 -20.921 1.00 56.33 C \\nATOM 25 C LYS A 4 5.160 3.037 -19.619 1.00 56.26 C \\nATOM 26 CB LYS A 4 4.946 0.783 -20.686 1.00 52.46 C \\nATOM 27 O LYS A 4 6.059 3.014 -18.777 1.00 54.00 O \\nATOM 28 CG LYS A 4 4.160 0.145 -21.822 1.00 50.74 C \\nATOM 29 CD LYS A 4 3.742 -1.280 -21.482 1.00 51.22 C \\nATOM 30 CE LYS A 4 2.972 -1.926 -22.626 1.00 46.00 C \\nATOM 31 NZ LYS A 4 2.570 -3.327 -22.301 1.00 41.10 N \\nATOM 32 N ARG A 5 4.654 4.355 -19.659 1.00 57.17 N \\nATOM 33 CA ARG A 5 4.370 5.118 -18.448 1.00 56.75 C \\nATOM 34 C ARG A 5 4.145 4.191 -17.258 1.00 57.30 C \\nATOM 35 CB ARG A 5 3.147 6.014 -18.652 1.00 54.00 C \\nATOM 36 O ARG A 5 3.305 3.291 -17.315 1.00 55.39 O \\nATOM 37 CG ARG A 5 3.418 7.241 -19.507 1.00 52.34 C \\nATOM 38 CD ARG A 5 2.248 8.215 -19.485 1.00 51.80 C \\nATOM 39 NE ARG A 5 2.490 9.368 -20.347 1.00 47.80 N \\nATOM 40 NH1 ARG A 5 0.476 10.400 -19.880 1.00 36.09 N \\nATOM 41 NH2 ARG A 5 1.963 11.379 -21.324 1.00 30.93 N \\nATOM 42 CZ ARG A 5 1.642 10.380 -20.515 1.00 48.53 C \\nATOM 43 N LYS A 6 5.076 3.542 -16.648 1.00 56.74 N \\nATOM 44 CA LYS A 6 4.941 3.003 -15.298 1.00 55.91 C \\nATOM 45 C LYS A 6 4.159 3.957 -14.400 1.00 57.02 C \\nATOM 46 CB LYS A 6 6.317 2.722 -14.692 1.00 53.22 C \\nATOM 47 O LYS A 6 4.437 5.158 -14.370 1.00 55.13 O \\nATOM 48 CG LYS A 6 7.043 1.544 -15.323 1.00 51.42 C \\nATOM 49 CD LYS A 6 8.240 1.111 -14.486 1.00 51.12 C \\nATOM 50 CE LYS A 6 8.985 -0.049 -15.132 1.00 46.58 C \\nATOM 51 NZ LYS A 6 10.148 -0.490 -14.305 1.00 40.34 N \\nATOM 52 N ASN A 7 2.844 3.954 -14.515 1.00 59.23 N \\nATOM 53 CA ASN A 7 2.185 4.649 -13.414 1.00 58.05 C \\nATOM 54 C ASN A 7 3.018 4.592 -12.137 1.00 59.52 C \\nATOM 55 CB ASN A 7 0.793 4.064 -13.167 1.00 55.24 C \\nATOM 56 O ASN A 7 3.423 3.513 -11.702 1.00 57.25 O \\nATOM 57 CG ASN A 7 -0.186 4.395 -14.276 1.00 52.37 C \\nATOM 58 ND2 ASN A 7 -0.992 3.415 -14.668 1.00 50.08 N \\nATOM 59 OD1 ASN A 7 -0.217 5.522 -14.777 1.00 53.79 O \\nATOM 60 N ILE A 8 4.069 5.352 -12.056 1.00 59.68 N \\nATOM 61 CA ILE A 8 4.815 5.542 -10.817 1.00 59.01 C \\nATOM 62 C ILE A 8 3.902 6.142 -9.751 1.00 59.98 C \\nATOM 63 CB ILE A 8 6.050 6.445 -11.034 1.00 55.49 C \\nATOM 64 O ILE A 8 3.251 7.163 -9.985 1.00 57.77 O \\nATOM 65 CG1 ILE A 8 6.987 5.827 -12.078 1.00 48.43 C \\nATOM 66 CG2 ILE A 8 6.785 6.683 -9.711 1.00 50.12 C \\nATOM 67 CD1 ILE A 8 8.131 6.738 -12.500 1.00 48.88 C \\nATOM 68 N ALA A 9 3.305 5.411 -8.843 1.00 61.62 N \\nATOM 69 CA ALA A 9 2.704 5.967 -7.633 1.00 60.50 C \\nATOM 70 C ALA A 9 3.767 6.566 -6.717 1.00 61.95 C \\nATOM 71 CB ALA A 9 1.909 4.894 -6.892 1.00 57.91 C \\nATOM 72 O ALA A 9 4.802 5.943 -6.467 1.00 59.91 O \\nATOM 73 N LEU A 10 4.029 7.816 -6.856 1.00 59.55 N \\nATOM 74 CA LEU A 10 4.825 8.505 -5.845 1.00 58.84 C \\nATOM 75 C LEU A 10 4.129 8.470 -4.489 1.00 59.62 C \\nATOM 76 CB LEU A 10 5.083 9.955 -6.262 1.00 55.09 C \\nATOM 77 O LEU A 10 3.007 8.963 -4.349 1.00 56.92 O \\nATOM 78 CG LEU A 10 6.506 10.287 -6.715 1.00 52.00 C \\nATOM 79 CD1 LEU A 10 6.495 10.832 -8.139 1.00 47.29 C \\nATOM 80 CD2 LEU A 10 7.153 11.285 -5.760 1.00 47.91 C \\nATOM 81 N ILE A 11 4.324 7.555 -3.640 1.00 63.93 N \\nATOM 82 CA ILE A 11 3.807 7.436 -2.281 1.00 62.81 C \\nATOM 83 C ILE A 11 4.630 8.311 -1.338 1.00 64.11 C \\nATOM 84 CB ILE A 11 3.820 5.968 -1.798 1.00 60.05 C \\nATOM 85 O ILE A 11 5.827 8.080 -1.152 1.00 62.31 O \\nATOM 86 CG1 ILE A 11 3.044 5.078 -2.775 1.00 55.32 C \\nATOM 87 CG2 ILE A 11 3.243 5.860 -0.383 1.00 56.55 C \\nATOM 88 CD1 ILE A 11 3.024 3.605 -2.388 1.00 56.02 C \\nATOM 89 N PRO A 12 4.236 9.559 -1.122 1.00 59.69 N \\nATOM 90 CA PRO A 12 4.957 10.421 -0.183 1.00 57.99 C \\nATOM 91 C PRO A 12 5.285 9.717 1.132 1.00 59.47 C \\nATOM 92 CB PRO A 12 3.985 11.582 0.047 1.00 55.24 C \\nATOM 93 O PRO A 12 4.386 9.199 1.800 1.00 56.72 O \\nATOM 94 CG PRO A 12 2.679 11.101 -0.497 1.00 52.39 C \\nATOM 95 CD PRO A 12 2.920 9.830 -1.261 1.00 51.89 C \\nATOM 96 N ALA A 13 6.303 8.725 1.183 1.00 58.14 N \\nATOM 97 CA ALA A 13 6.956 8.140 2.351 1.00 56.61 C \\nATOM 98 C ALA A 13 7.721 9.198 3.139 1.00 58.03 C \\nATOM 99 CB ALA A 13 7.895 7.014 1.927 1.00 54.18 C \\nATOM 100 O ALA A 13 8.747 9.705 2.677 1.00 56.02 O \\nATOM 101 N ALA A 14 7.310 10.425 3.224 1.00 55.08 N \\nATOM 102 CA ALA A 14 8.297 11.292 3.863 1.00 53.30 C \\nATOM 103 C ALA A 14 7.694 12.017 5.063 1.00 54.76 C \\nATOM 104 CB ALA A 14 8.849 12.301 2.858 1.00 49.07 C \\nATOM 105 O ALA A 14 6.582 12.545 4.983 1.00 51.84 O \\nATOM 106 N GLY A 15 7.542 11.287 6.272 1.00 56.09 N \\nATOM 107 CA GLY A 15 7.794 11.777 7.617 1.00 54.70 C \\nATOM 108 C GLY A 15 7.422 10.777 8.696 1.00 55.87 C \\nATOM 109 O GLY A 15 6.534 9.945 8.498 1.00 53.38 O \\nATOM 110 N ILE A 16 8.382 10.048 9.409 1.00 54.33 N \\nATOM 111 CA ILE A 16 8.033 9.496 10.713 1.00 52.91 C \\nATOM 112 C ILE A 16 6.988 10.383 11.386 1.00 54.37 C \\nATOM 113 CB ILE A 16 9.278 9.354 11.618 1.00 50.66 C \\nATOM 114 O ILE A 16 7.218 11.576 11.595 1.00 52.62 O \\nATOM 115 CG1 ILE A 16 10.421 8.679 10.852 1.00 45.57 C \\nATOM 116 CG2 ILE A 16 8.934 8.574 12.890 1.00 47.18 C \\nATOM 117 CD1 ILE A 16 11.747 8.668 11.601 1.00 43.25 C \\nATOM 118 N GLY A 17 5.897 10.652 10.712 1.00 51.05 N \\nATOM 119 CA GLY A 17 4.889 11.495 11.333 1.00 49.41 C \\nATOM 120 C GLY A 17 4.616 11.131 12.781 1.00 51.34 C \\nATOM 121 O GLY A 17 4.557 9.950 13.129 1.00 49.32 O \\nATOM 122 N VAL A 18 5.390 11.622 13.767 1.00 52.37 N \\nATOM 123 CA VAL A 18 5.180 11.695 15.209 1.00 51.47 C \\nATOM 124 C VAL A 18 3.749 11.281 15.545 1.00 52.74 C \\nATOM 125 CB VAL A 18 5.467 13.112 15.754 1.00 47.82 C \\nATOM 126 O VAL A 18 3.482 10.780 16.640 1.00 50.91 O \\nATOM 127 CG1 VAL A 18 5.921 13.049 17.211 1.00 40.43 C \\nATOM 128 CG2 VAL A 18 6.518 13.811 14.894 1.00 42.74 C \\nATOM 129 N ARG A 19 2.843 11.411 14.494 1.00 54.51 N \\nATOM 130 CA ARG A 19 1.471 11.191 14.939 1.00 53.31 C \\nATOM 131 C ARG A 19 1.173 9.702 15.081 1.00 54.54 C \\nATOM 132 CB ARG A 19 0.480 11.834 13.966 1.00 49.59 C \\nATOM 133 O ARG A 19 0.258 9.313 15.809 1.00 52.50 O \\nATOM 134 CG ARG A 19 0.116 13.268 14.315 1.00 46.93 C \\nATOM 135 CD ARG A 19 -1.015 13.792 13.441 1.00 47.92 C \\nATOM 136 NE ARG A 19 -1.345 15.178 13.759 1.00 41.79 N \\nATOM 137 NH1 ARG A 19 -3.052 15.344 12.211 1.00 32.33 N \\nATOM 138 NH2 ARG A 19 -2.521 17.138 13.535 1.00 28.40 N \\nATOM 139 CZ ARG A 19 -2.305 15.883 13.168 1.00 42.08 C \\nATOM 140 N PHE A 20 2.037 8.828 14.567 1.00 53.76 N \\nATOM 141 CA PHE A 20 1.640 7.435 14.728 1.00 52.52 C \\nATOM 142 C PHE A 20 2.579 6.711 15.685 1.00 53.62 C \\nATOM 143 CB PHE A 20 1.619 6.720 13.373 1.00 50.12 C \\nATOM 144 O PHE A 20 2.336 5.558 16.049 1.00 52.09 O \\nATOM 145 CG PHE A 20 0.410 7.041 12.536 1.00 47.89 C \\nATOM 146 CD1 PHE A 20 -0.794 6.379 12.747 1.00 45.18 C \\nATOM 147 CD2 PHE A 20 0.477 8.004 11.538 1.00 46.49 C \\nATOM 148 CE1 PHE A 20 -1.915 6.674 11.974 1.00 47.12 C \\nATOM 149 CE2 PHE A 20 -0.639 8.304 10.762 1.00 46.89 C \\nATOM 150 CZ PHE A 20 -1.833 7.637 10.981 1.00 45.52 C \\nATOM 151 N GLY A 21 3.306 7.533 16.434 1.00 57.48 N \\nATOM 152 CA GLY A 21 4.107 6.863 17.445 1.00 55.82 C \\nATOM 153 C GLY A 21 4.934 5.719 16.891 1.00 57.70 C \\nATOM 154 O GLY A 21 5.405 4.864 17.644 1.00 55.16 O \\nATOM 155 N ALA A 22 5.071 5.575 15.673 1.00 56.68 N \\nATOM 156 CA ALA A 22 5.774 4.435 15.093 1.00 55.11 C \\nATOM 157 C ALA A 22 7.162 4.838 14.602 1.00 56.79 C \\nATOM 158 CB ALA A 22 4.962 3.835 13.948 1.00 52.06 C \\nATOM 159 O ALA A 22 7.398 6.004 14.277 1.00 54.83 O \\nATOM 160 N ASP A 23 8.194 4.133 15.107 1.00 64.08 N \\nATOM 161 CA ASP A 23 9.572 4.078 14.630 1.00 63.11 C \\nATOM 162 C ASP A 23 9.624 3.822 13.126 1.00 64.36 C \\nATOM 163 CB ASP A 23 10.355 2.995 15.375 1.00 59.64 C \\nATOM 164 O ASP A 23 10.706 3.693 12.549 1.00 62.57 O \\nATOM 165 CG ASP A 23 10.227 3.103 16.884 1.00 56.58 C \\nATOM 166 OD1 ASP A 23 10.042 4.225 17.402 1.00 55.54 O \\nATOM 167 OD2 ASP A 23 10.316 2.056 17.562 1.00 58.07 O \\nATOM 168 N LYS A 24 8.455 3.717 12.487 1.00 67.05 N \\nATOM 169 CA LYS A 24 8.508 3.334 11.079 1.00 65.58 C \\nATOM 170 C LYS A 24 7.828 4.379 10.199 1.00 66.66 C \\nATOM 171 CB LYS A 24 7.854 1.967 10.869 1.00 63.36 C \\nATOM 172 O LYS A 24 6.937 5.098 10.656 1.00 63.65 O \\nATOM 173 CG LYS A 24 8.521 0.837 11.639 1.00 60.44 C \\nATOM 174 CD LYS A 24 7.852 -0.502 11.357 1.00 59.53 C \\nATOM 175 CE LYS A 24 8.471 -1.622 12.184 1.00 54.94 C \\nATOM 176 NZ LYS A 24 7.733 -2.909 12.012 1.00 48.19 N \\nATOM 177 N PRO A 25 8.378 4.698 8.980 1.00 72.42 N \\nATOM 178 CA PRO A 25 7.719 5.610 8.041 1.00 71.65 C \\nATOM 179 C PRO A 25 6.249 5.265 7.817 1.00 72.81 C \\nATOM 180 CB PRO A 25 8.525 5.431 6.752 1.00 70.34 C \\nATOM 181 O PRO A 25 5.866 4.096 7.900 1.00 70.73 O \\nATOM 182 CG PRO A 25 9.826 4.841 7.193 1.00 67.60 C \\nATOM 183 CD PRO A 25 9.587 4.038 8.439 1.00 66.12 C \\nATOM 184 N LYS A 26 5.283 6.270 7.722 1.00 73.08 N \\nATOM 185 CA LYS A 26 3.827 6.180 7.685 1.00 72.63 C \\nATOM 186 C LYS A 26 3.367 5.116 6.692 1.00 73.79 C \\nATOM 187 CB LYS A 26 3.214 7.534 7.323 1.00 70.90 C \\nATOM 188 O LYS A 26 2.394 4.402 6.945 1.00 73.26 O \\nATOM 189 CG LYS A 26 3.306 8.571 8.432 1.00 66.73 C \\nATOM 190 CD LYS A 26 2.631 9.877 8.033 1.00 63.11 C \\nATOM 191 CE LYS A 26 2.752 10.928 9.129 1.00 56.23 C \\nATOM 192 NZ LYS A 26 2.143 12.229 8.719 1.00 51.14 N \\nATOM 193 N GLN A 27 4.004 5.040 5.619 1.00 74.47 N \\nATOM 194 CA GLN A 27 3.545 4.126 4.578 1.00 74.03 C \\nATOM 195 C GLN A 27 3.680 2.673 5.023 1.00 75.08 C \\nATOM 196 CB GLN A 27 4.326 4.352 3.282 1.00 72.50 C \\nATOM 197 O GLN A 27 3.068 1.778 4.435 1.00 73.98 O \\nATOM 198 CG GLN A 27 5.800 3.985 3.380 1.00 69.45 C \\nATOM 199 CD GLN A 27 6.665 5.146 3.836 1.00 66.53 C \\nATOM 200 NE2 GLN A 27 7.945 5.106 3.484 1.00 61.05 N \\nATOM 201 OE1 GLN A 27 6.186 6.071 4.499 1.00 64.36 O \\nATOM 202 N TYR A 28 4.486 2.408 6.120 1.00 77.28 N \\nATOM 203 CA TYR A 28 4.684 1.029 6.551 1.00 77.08 C \\nATOM 204 C TYR A 28 3.824 0.708 7.767 1.00 77.45 C \\nATOM 205 CB TYR A 28 6.160 0.772 6.872 1.00 75.60 C \\nATOM 206 O TYR A 28 3.894 -0.396 8.311 1.00 76.21 O \\nATOM 207 CG TYR A 28 7.063 0.827 5.664 1.00 73.99 C \\nATOM 208 CD1 TYR A 28 6.847 -0.008 4.570 1.00 72.59 C \\nATOM 209 CD2 TYR A 28 8.134 1.713 5.614 1.00 73.01 C \\nATOM 210 CE1 TYR A 28 7.678 0.038 3.455 1.00 71.16 C \\nATOM 211 CE2 TYR A 28 8.971 1.767 4.505 1.00 71.93 C \\nATOM 212 OH TYR A 28 9.561 0.977 2.331 1.00 69.53 O \\nATOM 213 CZ TYR A 28 8.735 0.927 3.432 1.00 66.43 C \\nATOM 214 N VAL A 29 3.056 1.727 8.204 1.00 77.93 N \\nATOM 215 CA VAL A 29 2.120 1.461 9.291 1.00 77.90 C \\nATOM 216 C VAL A 29 1.004 0.542 8.799 1.00 79.01 C \\nATOM 217 CB VAL A 29 1.524 2.768 9.860 1.00 76.49 C \\nATOM 218 O VAL A 29 0.498 0.710 7.687 1.00 78.77 O \\nATOM 219 CG1 VAL A 29 0.448 2.462 10.901 1.00 72.72 C \\nATOM 220 CG2 VAL A 29 2.624 3.638 10.463 1.00 72.65 C \\nATOM 221 N GLU A 30 0.558 -0.456 9.611 1.00 78.48 N \\nATOM 222 CA GLU A 30 -0.443 -1.461 9.265 1.00 78.57 C \\nATOM 223 C GLU A 30 -1.843 -1.006 9.667 1.00 79.17 C \\nATOM 224 CB GLU A 30 -0.114 -2.800 9.931 1.00 76.54 C \\nATOM 225 O GLU A 30 -2.036 -0.462 10.757 1.00 78.29 O \\nATOM 226 CG GLU A 30 1.134 -3.472 9.376 1.00 72.78 C \\nATOM 227 CD GLU A 30 1.473 -4.778 10.075 1.00 70.99 C \\nATOM 228 OE1 GLU A 30 0.938 -5.033 11.178 1.00 68.94 O \\nATOM 229 OE2 GLU A 30 2.281 -5.553 9.517 1.00 65.31 O \\nATOM 230 N ILE A 31 -2.732 -1.003 8.730 1.00 79.81 N \\nATOM 231 CA ILE A 31 -4.173 -0.906 8.940 1.00 80.21 C \\nATOM 232 C ILE A 31 -4.838 -2.232 8.576 1.00 81.01 C \\nATOM 233 CB ILE A 31 -4.788 0.246 8.114 1.00 78.02 C \\nATOM 234 O ILE A 31 -4.964 -2.567 7.396 1.00 80.31 O \\nATOM 235 CG1 ILE A 31 -4.087 1.570 8.439 1.00 71.79 C \\nATOM 236 CG2 ILE A 31 -6.295 0.348 8.367 1.00 71.33 C \\nATOM 237 CD1 ILE A 31 -4.572 2.748 7.606 1.00 68.69 C \\nATOM 238 N GLY A 32 -5.258 -3.027 9.817 1.00 80.95 N \\nATOM 239 CA GLY A 32 -5.635 -4.404 9.541 1.00 81.75 C \\nATOM 240 C GLY A 32 -4.460 -5.275 9.134 1.00 79.05 C \\nATOM 241 O GLY A 32 -3.422 -5.274 9.798 1.00 73.40 O \\nATOM 242 N SER A 33 -4.521 -6.074 8.047 1.00 82.85 N \\nATOM 243 CA SER A 33 -3.462 -6.968 7.590 1.00 84.02 C \\nATOM 244 C SER A 33 -2.611 -6.309 6.509 1.00 82.91 C \\nATOM 245 CB SER A 33 -4.055 -8.274 7.058 1.00 78.34 C \\nATOM 246 O SER A 33 -1.711 -6.939 5.950 1.00 79.75 O \\nATOM 247 OG SER A 33 -4.887 -8.029 5.937 1.00 68.18 O \\nATOM 248 N LYS A 34 -2.932 -5.116 6.176 1.00 85.34 N \\nATOM 249 CA LYS A 34 -2.201 -4.485 5.081 1.00 84.95 C \\nATOM 250 C LYS A 34 -1.574 -3.167 5.527 1.00 85.12 C \\nATOM 251 CB LYS A 34 -3.125 -4.247 3.886 1.00 83.34 C \\nATOM 252 O LYS A 34 -2.094 -2.496 6.420 1.00 83.10 O \\nATOM 253 CG LYS A 34 -3.633 -5.525 3.232 1.00 78.44 C \\nATOM 254 CD LYS A 34 -4.507 -5.224 2.021 1.00 75.88 C \\nATOM 255 CE LYS A 34 -5.014 -6.501 1.366 1.00 70.89 C \\nATOM 256 NZ LYS A 34 -5.878 -6.211 0.182 1.00 63.91 N \\nATOM 257 N THR A 35 -0.405 -2.863 4.935 1.00 81.15 N \\nATOM 258 CA THR A 35 0.219 -1.568 5.181 1.00 80.99 C \\nATOM 259 C THR A 35 -0.504 -0.465 4.413 1.00 81.04 C \\nATOM 260 CB THR A 35 1.708 -1.581 4.787 1.00 79.53 C \\nATOM 261 O THR A 35 -1.241 -0.742 3.465 1.00 79.37 O \\nATOM 262 CG2 THR A 35 2.451 -2.715 5.485 1.00 75.12 C \\nATOM 263 OG1 THR A 35 1.819 -1.753 3.369 1.00 76.52 O \\nATOM 264 N VAL A 36 -0.411 0.819 4.846 1.00 80.11 N \\nATOM 265 CA VAL A 36 -0.934 1.965 4.110 1.00 79.63 C \\nATOM 266 C VAL A 36 -0.466 1.903 2.658 1.00 80.06 C \\nATOM 267 CB VAL A 36 -0.500 3.300 4.754 1.00 78.52 C \\nATOM 268 O VAL A 36 -1.251 2.137 1.736 1.00 78.93 O \\nATOM 269 CG1 VAL A 36 -0.881 4.480 3.862 1.00 75.72 C \\nATOM 270 CG2 VAL A 36 -1.124 3.451 6.140 1.00 75.36 C \\nATOM 271 N LEU A 37 0.847 1.469 2.453 1.00 78.80 N \\nATOM 272 CA LEU A 37 1.378 1.370 1.098 1.00 78.45 C \\nATOM 273 C LEU A 37 0.594 0.350 0.280 1.00 79.14 C \\nATOM 274 CB LEU A 37 2.860 0.986 1.130 1.00 77.10 C \\nATOM 275 O LEU A 37 0.245 0.609 -0.874 1.00 78.31 O \\nATOM 276 CG LEU A 37 3.551 0.837 -0.227 1.00 73.70 C \\nATOM 277 CD1 LEU A 37 3.479 2.147 -1.005 1.00 70.12 C \\nATOM 278 CD2 LEU A 37 4.999 0.396 -0.045 1.00 70.38 C \\nATOM 279 N GLU A 38 0.326 -0.772 0.910 1.00 81.00 N \\nATOM 280 CA GLU A 38 -0.398 -1.831 0.214 1.00 80.69 C \\nATOM 281 C GLU A 38 -1.823 -1.399 -0.120 1.00 80.97 C \\nATOM 282 CB GLU A 38 -0.421 -3.111 1.054 1.00 79.72 C \\nATOM 283 O GLU A 38 -2.351 -1.745 -1.179 1.00 79.93 O \\nATOM 284 CG GLU A 38 0.907 -3.854 1.079 1.00 78.36 C \\nATOM 285 CD GLU A 38 0.922 -5.025 2.048 1.00 77.16 C \\nATOM 286 OE1 GLU A 38 0.633 -4.822 3.250 1.00 75.05 O \\nATOM 287 OE2 GLU A 38 1.225 -6.154 1.603 1.00 73.48 O \\nATOM 288 N HIS A 39 -2.457 -0.687 0.816 1.00 81.53 N \\nATOM 289 CA HIS A 39 -3.795 -0.168 0.558 1.00 81.42 C \\nATOM 290 C HIS A 39 -3.799 0.775 -0.641 1.00 81.14 C \\nATOM 291 CB HIS A 39 -4.338 0.552 1.793 1.00 80.11 C \\nATOM 292 O HIS A 39 -4.679 0.690 -1.500 1.00 79.71 O \\nATOM 293 CG HIS A 39 -4.855 -0.374 2.848 1.00 77.94 C \\nATOM 294 CD2 HIS A 39 -4.368 -0.687 4.072 1.00 76.33 C \\nATOM 295 ND1 HIS A 39 -6.012 -1.106 2.694 1.00 75.15 N \\nATOM 296 CE1 HIS A 39 -6.215 -1.832 3.781 1.00 75.03 C \\nATOM 297 NE2 HIS A 39 -5.232 -1.595 4.633 1.00 74.02 N \\nATOM 298 N VAL A 40 -2.828 1.745 -0.721 1.00 78.76 N \\nATOM 299 CA VAL A 40 -2.721 2.734 -1.789 1.00 78.03 C \\nATOM 300 C VAL A 40 -2.453 2.031 -3.118 1.00 78.38 C \\nATOM 301 CB VAL A 40 -1.608 3.766 -1.498 1.00 76.80 C \\nATOM 302 O VAL A 40 -3.062 2.365 -4.138 1.00 76.89 O \\nATOM 303 CG1 VAL A 40 -1.357 4.647 -2.720 1.00 72.40 C \\nATOM 304 CG2 VAL A 40 -1.977 4.619 -0.286 1.00 72.27 C \\nATOM 305 N LEU A 41 -1.533 1.030 -3.081 1.00 77.58 N \\nATOM 306 CA LEU A 41 -1.216 0.308 -4.309 1.00 77.11 C \\nATOM 307 C LEU A 41 -2.433 -0.455 -4.819 1.00 77.56 C \\nATOM 308 CB LEU A 41 -0.052 -0.659 -4.077 1.00 75.74 C \\nATOM 309 O LEU A 41 -2.640 -0.564 -6.030 1.00 76.53 O \\nATOM 310 CG LEU A 41 1.326 -0.026 -3.878 1.00 72.48 C \\nATOM 311 CD1 LEU A 41 2.355 -1.095 -3.528 1.00 69.28 C \\nATOM 312 CD2 LEU A 41 1.748 0.741 -5.127 1.00 69.52 C \\nATOM 313 N GLY A 42 -3.206 -1.059 -3.937 1.00 80.25 N \\nATOM 314 CA GLY A 42 -4.423 -1.754 -4.325 1.00 79.71 C \\nATOM 315 C GLY A 42 -5.423 -0.859 -5.030 1.00 79.88 C \\nATOM 316 O GLY A 42 -6.161 -1.313 -5.907 1.00 78.27 O \\nATOM 317 N ILE A 43 -5.531 0.394 -4.566 1.00 78.63 N \\nATOM 318 CA ILE A 43 -6.434 1.357 -5.189 1.00 77.91 C \\nATOM 319 C ILE A 43 -6.013 1.597 -6.637 1.00 77.95 C \\nATOM 320 CB ILE A 43 -6.461 2.691 -4.411 1.00 76.47 C \\nATOM 321 O ILE A 43 -6.860 1.694 -7.528 1.00 76.49 O \\nATOM 322 CG1 ILE A 43 -7.132 2.500 -3.046 1.00 73.27 C \\nATOM 323 CG2 ILE A 43 -7.173 3.776 -5.224 1.00 72.94 C \\nATOM 324 CD1 ILE A 43 -6.943 3.672 -2.093 1.00 70.53 C \\nATOM 325 N PHE A 44 -4.748 1.699 -6.863 1.00 73.12 N \\nATOM 326 CA PHE A 44 -4.249 1.975 -8.205 1.00 72.40 C \\nATOM 327 C PHE A 44 -4.421 0.758 -9.107 1.00 72.33 C \\nATOM 328 CB PHE A 44 -2.774 2.388 -8.157 1.00 70.49 C \\nATOM 329 O PHE A 44 -4.595 0.898 -10.319 1.00 70.65 O \\nATOM 330 CG PHE A 44 -2.551 3.782 -7.636 1.00 66.97 C \\nATOM 331 CD1 PHE A 44 -2.949 4.888 -8.377 1.00 63.88 C \\nATOM 332 CD2 PHE A 44 -1.944 3.986 -6.404 1.00 64.30 C \\nATOM 333 CE1 PHE A 44 -2.743 6.180 -7.897 1.00 61.63 C \\nATOM 334 CE2 PHE A 44 -1.736 5.274 -5.917 1.00 60.85 C \\nATOM 335 CZ PHE A 44 -2.135 6.369 -6.666 1.00 60.58 C \\nATOM 336 N GLU A 45 -4.220 -0.483 -8.572 1.00 73.09 N \\nATOM 337 CA GLU A 45 -4.439 -1.686 -9.370 1.00 72.37 C \\nATOM 338 C GLU A 45 -5.852 -1.718 -9.943 1.00 72.92 C \\nATOM 339 CB GLU A 45 -4.182 -2.941 -8.532 1.00 69.91 C \\nATOM 340 O GLU A 45 -6.084 -2.302 -11.004 1.00 71.77 O \\nATOM 341 CG GLU A 45 -2.707 -3.234 -8.298 1.00 65.37 C \\nATOM 342 CD GLU A 45 -2.469 -4.459 -7.430 1.00 62.84 C \\nATOM 343 OE1 GLU A 45 -3.437 -4.968 -6.820 1.00 61.26 O \\nATOM 344 OE2 GLU A 45 -1.305 -4.913 -7.358 1.00 57.67 O \\nATOM 345 N ARG A 46 -6.746 -1.213 -9.196 1.00 72.48 N \\nATOM 346 CA ARG A 46 -8.117 -1.239 -9.693 1.00 71.19 C \\nATOM 347 C ARG A 46 -8.294 -0.274 -10.861 1.00 70.30 C \\nATOM 348 CB ARG A 46 -9.102 -0.893 -8.574 1.00 68.43 C \\nATOM 349 O ARG A 46 -9.281 -0.356 -11.596 1.00 67.62 O \\nATOM 350 CG ARG A 46 -9.252 -1.984 -7.526 1.00 64.68 C \\nATOM 351 CD ARG A 46 -10.310 -1.630 -6.490 1.00 62.70 C \\nATOM 352 NE ARG A 46 -9.869 -1.955 -5.137 1.00 52.56 N \\nATOM 353 NH1 ARG A 46 -11.980 -1.859 -4.203 1.00 46.86 N \\nATOM 354 NH2 ARG A 46 -10.165 -2.358 -2.895 1.00 43.74 N \\nATOM 355 CZ ARG A 46 -10.672 -2.057 -4.082 1.00 57.43 C \\nATOM 356 N HIS A 47 -7.201 0.509 -11.001 1.00 63.25 N \\nATOM 357 CA HIS A 47 -7.372 1.411 -12.134 1.00 63.43 C \\nATOM 358 C HIS A 47 -6.377 1.094 -13.245 1.00 61.36 C \\nATOM 359 CB HIS A 47 -7.216 2.866 -11.688 1.00 58.29 C \\nATOM 360 O HIS A 47 -6.706 1.206 -14.429 1.00 58.05 O \\nATOM 361 CG HIS A 47 -8.300 3.331 -10.768 1.00 54.95 C \\nATOM 362 CD2 HIS A 47 -8.262 3.709 -9.469 1.00 54.55 C \\nATOM 363 ND1 HIS A 47 -9.615 3.444 -11.165 1.00 53.98 N \\nATOM 364 CE1 HIS A 47 -10.340 3.874 -10.146 1.00 50.05 C \\nATOM 365 NE2 HIS A 47 -9.543 4.042 -9.105 1.00 45.43 N \\nTER 366 HIS A 47\\nEND\\n\"\n ]\n}"])</script><script>self.__next_f.push([1,"9b:T923,"])</script><script>self.__next_f.push([1,"#!/usr/bin/env bash\nif [ \"$NVCF_RUN_KEY\" = \"\" ]; then read -p \"Paste Run Key: \" NVCF_RUN_KEY; fi\nURL=${URL:-https://health.api.nvidia.com/v1/biology/deepmind/alphafold2}\nSTATUS_URL=${STATUS_URL:-https://health.api.nvidia.com/v1/status}\n\nsequence=\"MVPSAGQLALFALGIVLAACQALENSTSPLSADPPVAAAVVSHFNDCPDSHTQFCFHGTCRFLVQED\"\\\n\"KPACVCHSGYVGARCEHADLLAVVAASQKKQAITALVVVSIVALAVLIITCVLIHCCQVRKHCEWCRALICRHEKP\"\\\n\"SALLKGRTACCHSETVV\"\nrequest_body='{\n \"sequence\": \"'$sequence'\",\n \"algorithm\": \"mmseqs2\",\n \"e_value\": 0.0001,\n \"iterations\": 1,\n \"databases\": [\"uniref90\", \"small_bfd\", \"mgnify\"],\n \"relax_prediction\": true\n}'\noutput_file=output.json\n\n# Initial request\necho \"Making request...\"\nresponse=$(curl -s -D /dev/stderr --fail-with-body \\\n -H \"content-type: application/json\" \\\n -H \"Authorization: Bearer $NVCF_RUN_KEY\" \\\n -H \"NVCF-POLL-SECONDS: 1\" \\\n --request POST \\\n --data \"$request_body\" \\\n \"$URL\" 2\u003e\u00261 1\u003e $output_file)\n\n# Extract HTTP status code\nhttp_status=$(echo \"$response\" | awk '{print $2;exit}')\n\n# Check the status code\nif [ \"$http_status\" -eq 200 ]; then\n echo \"Saved response to file: $output_file\"\nelif [ \"$http_status\" -eq 202 ]; then\n echo \"Request accepted...\"\n # Extract nvcf-reqid header\n req_id=$(echo \"$response\" | grep -i \"nvcf-reqid:\" | awk '{print $2}' | tr -d '\\r')\n\n # Poll the /status endpoint\n while true; do\n echo \"Polling for response...\"\n status_response=$(curl -s -D /dev/stderr --fail-with-body \\\n -H \"content-type: application/json\" \\\n -H \"Authorization: Bearer $NVCF_RUN_KEY\" \\\n -H \"NVCF-POLL-SECONDS: 5\" \\\n --request GET \\\n \"${STATUS_URL}/${req_id}\" 2\u003e\u00261 1\u003e $output_file)\n\n status_http_status=$(echo \"$status_response\" | awk '{print $2;exit}')\n\n if [ \"$status_http_status\" -eq 200 ]; then\n echo \"Saved response to file: $output_file\"\n break\n elif [ \"$status_http_status\" -ne 202 ]; then\n echo \"Unexpected HTTP status: $status_http_status\"\n echo \"Response: $status_response\"\n exit 1\n fi\n\n # Wait before polling again\n sleep 5\n done\nelse\n echo \"Unexpected HTTP status: $http_status\"\n echo \"Response: $response\"\n exit 1\nfi\n"])</script><script>self.__next_f.push([1,"9c:T700,#!/usr/bin/env python3\nimport os\nimport requests\nimport time\nfrom pathlib import Path\n\n# Variables\nkey = os.getenv(\"NVCF_RUN_KEY\") or input(\"Paste the Run Key: \")\nurl = os.getenv(\"URL\", \"https://health.api.nvidia.com/v1/biology/deepmind/alphafold2\")\nstatus_url = os.getenv(\"STATUS_URL\", \"https://health.api.nvidia.com/v1/status\")\n\nsequence = (\"MVPSAGQLALFALGIVLAACQALENSTSPLSADPPVAAAVVSHFNDCPDSHTQFCFHGTCRFL\"\n \"VQEDKPACVCHSGYVGARCEHADLLAVVAASQKKQAITALVVVSIVALAVLIITCVLIHCCQVRKHCEWCR\"\n \"ALICRHEKPSALLKGRTACCHSETVV\"\n)\noutput_file = Path(\"output.json\")\n\n# Initial request\nheaders = {\n \"content-type\": \"application/json\",\n \"Authorization\": f\"Bearer {key}\",\n \"NVCF-POLL-SECONDS\": \"5\",\n}\ndata = {\n \"sequence\": sequence,\n \"algorithm\": \"mmseqs2\",\n \"e_value\": 0.0001,\n \"iterations\": 1,\n \"databases\": [\"uniref90\", \"small_bfd\", \"mgnify\"],\n \"relax_prediction\": True,\n}\n\nprint(\"Making request...\")\nresponse = requests.post(url, headers=headers, json=data)\n\n# Check the status code\nif response.status_code == 200:\n output_file.write_text(response.text)\n print(f\"Response output to file: {output_file}\")\nelif response.status_code == 202:\n print(\"Request accepted...\")\n # Extract reqId header\n req_id = response.headers.get(\"nvcf-reqid\")\n\n # Poll the /status endpoint\n while True:\n print(\"Polling for response...\")\n status_response = requests.get(f\"{status_url}/{req_id}\", headers=headers)\n\n if status_response.status_code != 202:\n output_file.write_text(status_response.text)\n print(f\"Response output to file: {output_file}\")\n break\n\n # Wait before polling again\n time.sleep(5)\nelse:\n print(f\"Unexpected HTTP status: {response.status_code}\")\n print(f\"Response: {response.text}\")\n9d:Taec,"])</script><script>self.__next_f.push([1,"## Start NIM\n\n1. Export `NGC_API_KEY` variable.\n\n```\nexport NGC_API_KEY=\u003cyour personal NGC key\u003e\n```\n\n2. The NIM container automatically downloads any required models. To save time and bandwidth it\n is recommended to provide a local cache directory. This way the NIM will be able to\n reuse any already downloaded models. Execute the following command to setup the cache\n directory:\n\n```bash\nexport LOCAL_NIM_CACHE=~/.cache/nim\nmkdir -p $LOCAL_NIM_CACHE\n```\n\n3. Run the NIM container with the following commands.\n\n```bash\ndocker run -it \\\n --runtime=nvidia \\\n -p 8000:8000 \\\n -e NGC_API_KEY \\\n -v $LOCAL_NIM_CACHE:/opt/nim/.cache \\\n nvcr.io/nim/deepmind/alphafold2:2.0.0\n```\n\nThis command will start the NIM container and expose port 8000 for the user to interact with the NIM.\n\n4. Open a new terminal, leaving the terminal open with the just launched service. In the new terminal, wait until the health check end point returns `{\"status\":\"ready\"}` before proceeding. This may take a couple of minutes. You can use the following command to query the health check.\n\n```bash\ncurl http://localhost:8000/v1/health/ready\n```\n\n## Python client example\n\n1. Save following Python example to a file named `nim_client.py`.\n\n```python\nimport requests\nimport json\n\nurl = \"http://localhost:8000/protein-structure/alphafold2/predict-structure-from-sequence\" # Replace with the actual URL\nsequence = \"MNVIDIAIAMAI\" # Replace with the actual sequence value\n\nheaders = {\n \"content-type\": \"application/json\"\n}\n\ndata = {\n \"sequence\": sequence,\n \"databases\": [\"small_bfd\"],\n \"e_value\": 0.000001,\n \"algorithm\": \"mmseqs2\",\n \"num_predictions_per_model\" : 1,\n \"relax_prediction\": False,\n}\n\nresponse = requests.post(url, headers=headers, data=json.dumps(data))\n\n# Check if the request was successful\nif response.ok:\n with open(\"output.pdb\", \"w\") as ofi:\n ofi.write(json.dumps(response.json()))\n print(\"Request succeeded:\", response.json())\nelse:\n print(\"Request failed:\", response.status_code, response.text)\n```\n\n2. Execute the example.\n\n```bash\npython nim_client.py\n```\n\n3. The resulting PDB structure will be returned and written to `output.pdb`.\n\n```bash\ncat output.pdb\n```\n\n## Shell client example\n\n1. Save the following Shell example to a file named `nim_client.sh`.\n\n```bash\n#!/usr/bin/env bash\nset -e\n\nURL=http://localhost:8000/protein-structure/alphafold2/predict-structure-from-sequence\n\nrequest='{\n \"sequence\": \"MNVIDIAIAMAI\"\n}'\ncurl -H 'Content-Type: application/json' \\\n -d \"$request\" \"$URL\"\n```\n\n2. Execute the example.\n\n```bash\nchmod +x nim_client.sh\n\n./nim_client.sh\n```\n\n3. Results will be printed on the terminal in JSON format. You will be able\n to see the PDB formatted output; you can also use curl to save the output directly to file.\n"])</script><script>self.__next_f.push([1,"9e:T5a4c,"])</script><script>self.__next_f.push([1,"## Model Description\n\nLlama-3-Taiwan-70B is a large language model finetuned for Traditional Mandarin and English users. It has strong capabilities in language understanding, generation, reasoning, and multi-turn dialogue. Key features include:\n* 70B parameters\n* Languages: Traditional Mandarin (zh-tw), English (en)\n* Finetuned on High-quality Traditional Mandarin and English corpus covering general knowledge as well as industrial knowledge in legal, manufacturing, medical, and electronics domains\n* 8K context length\n* Open model released under the Llama-3 license\n\nLlama 3 is a large language AI model comprising a collection of models capable of generating text and code in response to prompts. Meta developed and released the Meta Llama 3 family of large language models (LLMs), a collection of pretrained and instruction tuned generative text models in 8 and 70B sizes. Token counts refer to pretraining data only. Both the 8 and 70B versions use Grouped-Query Attention (GQA) for improved inference scalability. The Llama 3 instruction tuned models are optimized for dialogue use cases and outperform many of the available open source chat models on common industry benchmarks. Further, in developing these models, we took great care to optimize helpfulness and safety. \n\n**Model Developer** Meta\n\n**License** A custom commercial license is available at: [https://llama.meta.com/llama3/license](https://llama.meta.com/llama3/license)\n\nWhere to send questions or comments about the model Instructions on how to provide feedback or comments on the model can be found in the model [README](https://github.com/meta-llama/llama3). For more technical information about generation parameters and recipes for how to use Llama 3 in applications, please go [here](https://github.com/meta-llama/llama-recipes).\n\n**Model Release Date** April 18, 2024.\n\n**Status** This is a static model trained on an offline dataset. Future versions of the tuned models will be released as we improve model safety with community feedback.\n\n**Llama 3 Family of Models**. \n\n## Intended Use\n\n**Intended Use Cases** Llama 3 is intended for commercial and research use in English. Instruction tuned models are intended for assistant-like chat, whereas pretrained models can be adapted for a variety of natural language generation tasks.\n\n**Out-of-scope** Use in any manner that violates applicable laws or regulations (including trade compliance laws). Use in any other way that is prohibited by the Acceptable Use Policy and Llama 3 Community License. Use in languages other than English**.\n\n**Note: Developers may fine-tune Llama 3 models for languages beyond English provided they comply with the Llama 3 Community License and the Acceptable Use Policy.\n\n**Model Architecture** \n* Architecture Type: Transformer\n* Network Architecture: Llama 3\n\nLlama 3 is an auto-regressive language model that uses an optimized transformer architecture. The tuned versions use supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to align with human preferences for helpfulness and safety.\n\n**Input** \n* Input Format: Text\n* Input Parameters: Temperature, TopP\n\n**Output** \n* Output Format: Text and code\n* Output Parameters: Max output tokens\n\n\n\u003ctable\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cstrong\u003eTraining Data\u003c/strong\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cstrong\u003eParams\u003c/strong\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cstrong\u003eContext length\u003c/strong\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cstrong\u003eGQA\u003c/strong\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cstrong\u003eToken count\u003c/strong\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cstrong\u003eKnowledge cutoff\u003c/strong\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" \u003eLlama 3\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" \u003eA new mix of publicly available online data.\n \u003c/td\u003e\n \u003ctd\u003e8B\n \u003c/td\u003e\n \u003ctd\u003e8k\n \u003c/td\u003e\n \u003ctd\u003eYes\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" \u003e15T+\n \u003c/td\u003e\n \u003ctd\u003eMarch, 2023\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e70B\n \u003c/td\u003e\n \u003ctd\u003e8k\n \u003c/td\u003e\n \u003ctd\u003eYes\n \u003c/td\u003e\n \u003ctd\u003eDecember, 2023\n \u003c/td\u003e\n \u003c/tr\u003e\n\u003c/table\u003e\n\n\n## Hardware and Software\n\n## Inference:\n**Engine:** Triton \u003cbr\u003e\n**Test Hardware:** \u003cbr\u003e\n* H100 \u003cbr\u003e\n\n**Training Factors** We used custom training libraries, Meta's Research SuperCluster, and production clusters for pretraining. Fine-tuning, annotation, and evaluation were also performed on third-party cloud compute.\n\n**Carbon Footprint Pretraining utilized a cumulative** 7.7M GPU hours of computation on hardware of type H100-80GB (TDP of 700W). Estimated total emissions were 2290 tCO2eq, 100% of which were offset by Meta’s sustainability program.\n\n\n\u003ctable\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cstrong\u003eTime (GPU hours)\u003c/strong\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cstrong\u003ePower Consumption (W)\u003c/strong\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cstrong\u003eCarbon Emitted(tCO2eq)\u003c/strong\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eLlama 3 8B\n \u003c/td\u003e\n \u003ctd\u003e1.3M\n \u003c/td\u003e\n \u003ctd\u003e700\n \u003c/td\u003e\n \u003ctd\u003e390\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eLlama 3 70B\n \u003c/td\u003e\n \u003ctd\u003e6.4M\n \u003c/td\u003e\n \u003ctd\u003e700\n \u003c/td\u003e\n \u003ctd\u003e1900\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eTotal\n \u003c/td\u003e\n \u003ctd\u003e7.7M\n \u003c/td\u003e\n \u003ctd\u003e\n \u003c/td\u003e\n \u003ctd\u003e2290\n \u003c/td\u003e\n \u003c/tr\u003e\n\u003c/table\u003e\n\n\n**CO2 emissions during pre-training**. Time: total GPU time required for training each model. Power Consumption: peak power capacity per GPU device for the GPUs used adjusted for power usage efficiency. 100% of the emissions are directly offset by Meta's sustainability program, and because we are openly releasing these models, the pretraining costs do not need to be incurred by others.\n\n\n## Training Dataset\n\n**Overview** Llama 3 was pretrained on over 15 trillion tokens of data from publicly available sources. The fine-tuning data includes publicly available instruction datasets, as well as over 10M human-annotated examples. Neither the pretraining nor the fine-tuning datasets include Meta user data.\n\n**Data Freshness** The pretraining data has a cutoff of March 2023 for the 7B and December 2023 for the 70B models respectively. \n\n\n## Benchmarks \n\nIn this section, we report the results for Llama 3 models on standard automatic benchmarks. For all the evaluations, we use our internal evaluations library. For details on the methodology see [here](https://github.com/meta-llama/llama3/blob/main/eval_methodology.md).\n\n\n### Base pretrained models\n\n\n\u003ctable\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cstrong\u003eCategory\u003c/strong\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cstrong\u003eBenchmark\u003c/strong\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cstrong\u003eLlama 3 8B\u003c/strong\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cstrong\u003eLlama2 7B\u003c/strong\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cstrong\u003eLlama2 13B\u003c/strong\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cstrong\u003eLlama 3 70B\u003c/strong\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cstrong\u003eLlama2 70B\u003c/strong\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"6\" \u003eGeneral\n \u003c/td\u003e\n \u003ctd\u003eMMLU (5-shot)\n \u003c/td\u003e\n \u003ctd\u003e66.6\n \u003c/td\u003e\n \u003ctd\u003e45.7\n \u003c/td\u003e\n \u003ctd\u003e53.8\n \u003c/td\u003e\n \u003ctd\u003e79.5\n \u003c/td\u003e\n \u003ctd\u003e69.7\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eAGIEval English (3-5 shot)\n \u003c/td\u003e\n \u003ctd\u003e45.9\n \u003c/td\u003e\n \u003ctd\u003e28.8\n \u003c/td\u003e\n \u003ctd\u003e38.7\n \u003c/td\u003e\n \u003ctd\u003e63.0\n \u003c/td\u003e\n \u003ctd\u003e54.8\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eCommonSenseQA (7-shot)\n \u003c/td\u003e\n \u003ctd\u003e72.6\n \u003c/td\u003e\n \u003ctd\u003e57.6\n \u003c/td\u003e\n \u003ctd\u003e67.6\n \u003c/td\u003e\n \u003ctd\u003e83.8\n \u003c/td\u003e\n \u003ctd\u003e78.7\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eWinogrande (5-shot)\n \u003c/td\u003e\n \u003ctd\u003e76.1\n \u003c/td\u003e\n \u003ctd\u003e73.3\n \u003c/td\u003e\n \u003ctd\u003e75.4\n \u003c/td\u003e\n \u003ctd\u003e83.1\n \u003c/td\u003e\n \u003ctd\u003e81.8\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eBIG-Bench Hard (3-shot, CoT)\n \u003c/td\u003e\n \u003ctd\u003e61.1\n \u003c/td\u003e\n \u003ctd\u003e38.1\n \u003c/td\u003e\n \u003ctd\u003e47.0\n \u003c/td\u003e\n \u003ctd\u003e81.3\n \u003c/td\u003e\n \u003ctd\u003e65.7\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eARC-Challenge (25-shot)\n \u003c/td\u003e\n \u003ctd\u003e78.6\n \u003c/td\u003e\n \u003ctd\u003e53.7\n \u003c/td\u003e\n \u003ctd\u003e67.6\n \u003c/td\u003e\n \u003ctd\u003e93.0\n \u003c/td\u003e\n \u003ctd\u003e85.3\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eKnowledge reasoning\n \u003c/td\u003e\n \u003ctd\u003eTriviaQA-Wiki (5-shot)\n \u003c/td\u003e\n \u003ctd\u003e78.5\n \u003c/td\u003e\n \u003ctd\u003e72.1\n \u003c/td\u003e\n \u003ctd\u003e79.6\n \u003c/td\u003e\n \u003ctd\u003e89.7\n \u003c/td\u003e\n \u003ctd\u003e87.5\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" \u003eReading comprehension\n \u003c/td\u003e\n \u003ctd\u003eSQuAD (1-shot)\n \u003c/td\u003e\n \u003ctd\u003e76.4\n \u003c/td\u003e\n \u003ctd\u003e72.2\n \u003c/td\u003e\n \u003ctd\u003e72.1\n \u003c/td\u003e\n \u003ctd\u003e85.6\n \u003c/td\u003e\n \u003ctd\u003e82.6\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eQuAC (1-shot, F1)\n \u003c/td\u003e\n \u003ctd\u003e44.4\n \u003c/td\u003e\n \u003ctd\u003e39.6\n \u003c/td\u003e\n \u003ctd\u003e44.9\n \u003c/td\u003e\n \u003ctd\u003e51.1\n \u003c/td\u003e\n \u003ctd\u003e49.4\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eBoolQ (0-shot)\n \u003c/td\u003e\n \u003ctd\u003e75.7\n \u003c/td\u003e\n \u003ctd\u003e65.5\n \u003c/td\u003e\n \u003ctd\u003e66.9\n \u003c/td\u003e\n \u003ctd\u003e79.0\n \u003c/td\u003e\n \u003ctd\u003e73.1\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eDROP (3-shot, F1)\n \u003c/td\u003e\n \u003ctd\u003e58.4\n \u003c/td\u003e\n \u003ctd\u003e37.9\n \u003c/td\u003e\n \u003ctd\u003e49.8\n \u003c/td\u003e\n \u003ctd\u003e79.7\n \u003c/td\u003e\n \u003ctd\u003e70.2\n \u003c/td\u003e\n \u003c/tr\u003e\n\u003c/table\u003e\n\n\n\n### Instruction tuned models\n\n\n\u003ctable\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cstrong\u003eBenchmark\u003c/strong\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cstrong\u003eLlama 3 8B\u003c/strong\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cstrong\u003eLlama 2 7B\u003c/strong\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cstrong\u003eLlama 2 13B\u003c/strong\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cstrong\u003eLlama 3 70B\u003c/strong\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cstrong\u003eLlama 2 70B\u003c/strong\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eMMLU (5-shot)\n \u003c/td\u003e\n \u003ctd\u003e68.4\n \u003c/td\u003e\n \u003ctd\u003e34.1\n \u003c/td\u003e\n \u003ctd\u003e47.8\n \u003c/td\u003e\n \u003ctd\u003e82.0\n \u003c/td\u003e\n \u003ctd\u003e52.9\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eGPQA (0-shot)\n \u003c/td\u003e\n \u003ctd\u003e34.2\n \u003c/td\u003e\n \u003ctd\u003e21.7\n \u003c/td\u003e\n \u003ctd\u003e22.3\n \u003c/td\u003e\n \u003ctd\u003e39.5\n \u003c/td\u003e\n \u003ctd\u003e21.0\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eHumanEval (0-shot)\n \u003c/td\u003e\n \u003ctd\u003e62.2\n \u003c/td\u003e\n \u003ctd\u003e7.9\n \u003c/td\u003e\n \u003ctd\u003e14.0\n \u003c/td\u003e\n \u003ctd\u003e81.7\n \u003c/td\u003e\n \u003ctd\u003e25.6\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eGSM-8K (8-shot, CoT)\n \u003c/td\u003e\n \u003ctd\u003e79.6\n \u003c/td\u003e\n \u003ctd\u003e25.7\n \u003c/td\u003e\n \u003ctd\u003e77.4\n \u003c/td\u003e\n \u003ctd\u003e93.0\n \u003c/td\u003e\n \u003ctd\u003e57.5\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003eMATH (4-shot, CoT)\n \u003c/td\u003e\n \u003ctd\u003e30.0\n \u003c/td\u003e\n \u003ctd\u003e3.8\n \u003c/td\u003e\n \u003ctd\u003e6.7\n \u003c/td\u003e\n \u003ctd\u003e50.4\n \u003c/td\u003e\n \u003ctd\u003e11.6\n \u003c/td\u003e\n \u003c/tr\u003e\n\u003c/table\u003e\n\n\n\n### Responsibility \u0026 Safety\n\nWe believe that an open approach to AI leads to better, safer products, faster innovation, and a bigger overall market. We are committed to Responsible AI development and took a series of steps to limit misuse and harm and support the open source community.\n\nFoundation models are widely capable technologies that are built to be used for a diverse range of applications. They are not designed to meet every developer preference on safety levels for all use cases, out-of-the-box, as those by their nature will differ across different applications. \n\nRather, responsible LLM-application deployment is achieved by implementing a series of safety best practices throughout the development of such applications, from the model pre-training, fine-tuning and the deployment of systems composed of safeguards to tailor the safety needs specifically to the use case and audience. \n\nAs part of the Llama 3 release, we updated our [Responsible Use Guide](https://llama.meta.com/responsible-use-guide/) to outline the steps and best practices for developers to implement model and system level safety for their application. We also provide a set of resources including [Meta Llama Guard 2](https://llama.meta.com/purple-llama/) and [Code Shield](https://llama.meta.com/purple-llama/) safeguards. These tools have proven to drastically reduce residual risks of LLM Systems, while maintaining a high level of helpfulness. We encourage developers to tune and deploy these safeguards according to their needs and we provide a [Reference Implementation](https://github.com/meta-llama/llama-recipes/tree/main/recipes/responsible_ai) to get you started.\n\n\n#### Llama 3-Instruct\n\nAs outlined in the Responsible Use Guide, some trade-off between model helpfulness and model alignment is likely unavoidable. Developers should exercise discretion about how to weigh the benefits of alignment and helpfulness for their specific use case and audience. Developers should be mindful of residual risks when using Llama models and leverage additional safety tools as needed to reach the right safety bar for their use case. \n\n\u003cspan style=\"text-decoration:underline;\"\u003eSafety\u003c/span\u003e\n\nFor our instruction tuned model, we conducted extensive red teaming exercises, performed adversarial evaluations and implemented safety mitigations techniques to lower residual risks. As with any Large Language Model, residual risks will likely remain and we recommend that developers assess these risks in the context of their use case. In parallel, we are working with the community to make AI safety benchmark standards transparent, rigorous, and interpretable. \n\n\u003cspan style=\"text-decoration:underline;\"\u003eRefusals\u003c/span\u003e\n\nIn addition to residual risks, we put a great emphasis on model refusals to benign prompts. Over-refusing not only can impact the user experience but could even be harmful in certain contexts as well. We’ve heard the feedback from the developer community and improved our fine tuning to ensure that Llama 3 is significantly less likely to falsely refuse to answer prompts than Llama 2. \n\nWe built internal benchmarks and developed mitigations to limit false refusals making Llama 3 our most helpful model to date. \n\n\n#### Responsible Release \n\nIn addition to responsible use considerations outlined above, we followed a rigorous process that requires us to take extra measures against misuse and critical risks before we make our release decision. \n\nMisuse\n\nIf you access or use Llama 3, you agree to the Acceptable Use Policy. The most recent copy of this policy can be found at [https://llama.meta.com/llama3/use-policy/](https://llama.meta.com/llama3/use-policy/).\n\n\n#### Critical risks \n\n\u003cspan style=\"text-decoration:underline;\"\u003eCBRNE\u003c/span\u003e (Chemical, Biological, Radiological, Nuclear, and high yield Explosives)\n\nWe have conducted a two fold assessment of the safety of the model in this area:\n\n* Iterative testing during model training to assess the safety of responses related to CBRNE threats and other adversarial risks.\n* Involving external CBRNE experts to conduct an uplift test assessing the ability of the model to accurately provide expert knowledge and reduce barriers to potential CBRNE misuse, by reference to what can be achieved using web search (without the model).\n\n\n### \u003cspan style=\"text-decoration:underline;\"\u003eCyber Security \u003c/span\u003e\n\nWe have evaluated Llama 3 with CyberSecEval, Meta’s cybersecurity safety eval suite, measuring Llama 3’s propensity to suggest insecure code when used as a coding assistant, and Llama 3’s propensity to comply with requests to help carry out cyber attacks, where attacks are defined by the industry standard MITRE ATT\u0026CK cyber attack ontology. On our insecure coding and cyber attacker helpfulness tests, Llama 3 behaved in the same range or safer than models of [equivalent coding capability](https://huggingface.co/spaces/facebook/CyberSecEval). \n\n\n### \u003cspan style=\"text-decoration:underline;\"\u003eChild Safety\u003c/span\u003e\n\nChild Safety risk assessments were conducted using a team of experts, to assess the model’s capability to produce outputs that could result in Child Safety risks and inform on any necessary and appropriate risk mitigations via fine tuning. We leveraged those expert red teaming sessions to expand the coverage of our evaluation benchmarks through Llama 3 model development. For Llama 3, we conducted new in-depth sessions using objective based methodologies to assess the model risks along multiple attack vectors. We also partnered with content specialists to perform red teaming exercises assessing potentially violating content while taking account of market specific nuances or experiences. \n\n\n### Community \n\nGenerative AI safety requires expertise and tooling, and we believe in the strength of the open community to accelerate its progress. We are active members of open consortiums, including the AI Alliance, Partnership in AI and MLCommons, actively contributing to safety standardization and transparency. We encourage the community to adopt taxonomies like the MLCommons Proof of Concept evaluation to facilitate collaboration and transparency on safety and content evaluations. Our Purple Llama tools are open sourced for the community to use and widely distributed across ecosystem partners including cloud service providers. We encourage community contributions to our [Github repository](https://github.com/meta-llama/PurpleLlama). \n\nFinally, we put in place a set of resources including an [output reporting mechanism](https://developers.facebook.com/llama_output_feedback) and [bug bounty program](https://www.facebook.com/whitehat) to continuously improve the Llama technology with the help of the community. \n\n\n## Ethical Considerations and Limitations\n\nThe core values of Llama 3 are openness, inclusivity and helpfulness. It is meant to serve everyone, and to work for a wide range of use cases. It is thus designed to be accessible to people across many different backgrounds, experiences and perspectives. Llama 3 addresses users and their needs as they are, without insertion unnecessary judgment or normativity, while reflecting the understanding that even content that may appear problematic in some cases can serve valuable purposes in others. It respects the dignity and autonomy of all users, especially in terms of the values of free thought and expression that power innovation and progress. \n\nBut Llama 3 is a new technology, and like any new technology, there are risks associated with its use. Testing conducted to date has been in English, and has not covered, nor could it cover, all scenarios. For these reasons, as with all LLMs, Llama 3’s potential outputs cannot be predicted in advance, and the model may in some instances produce inaccurate, biased or other objectionable responses to user prompts. Therefore, before deploying any applications of Llama 3 models, developers should perform safety testing and tuning tailored to their specific applications of the model. As outlined in the Responsible Use Guide, we recommend incorporating [Purple Llama](https://github.com/facebookresearch/PurpleLlama) solutions into your workflows and specifically [Llama Guard](https://ai.meta.com/research/publications/llama-guard-llm-based-input-output-safeguard-for-human-ai-conversations/) which provides a base model to filter input and output prompts to layer system-level safety on top of model-level safety. \n\nPlease see the Responsible Use Guide available at [http://llama.meta.com/responsible-use-guide](http://llama.meta.com/responsible-use-guide)\n\n\n## Citation Instructions\n\n@article{llama3modelcard,\n\n title={Llama-3-Taiwan-70B-Instruct},\n\n author={yentinglin},\n\n year={2024},\n\n url = {https://huggingface.co/yentinglin/Llama-3-Taiwan-70B-Instruct}\n\n}\n\n## Contributors\n\nAaditya Singh; Aaron Grattafiori; Abhimanyu Dubey; Abhinav Jauhri; Abhinav Pandey; Abhishek Kadian; Adam Kelsey; Adi Gangidi; Ahmad Al-Dahle; Ahuva Goldstand; Aiesha Letman; Ajay Menon; Akhil Mathur; Alan Schelten; Alex Vaughan; Amy Yang; Andrei Lupu; Andres Alvarado; Andrew Gallagher; Andrew Gu; Andrew Ho; Andrew Poulton; Andrew Ryan; Angela Fan; Ankit Ramchandani; Anthony Hartshorn; Archi Mitra; Archie Sravankumar; Artem Korenev; Arun Rao; Ashley Gabriel; Ashwin Bharambe; Assaf Eisenman; Aston Zhang; Aurelien Rodriguez; Austen Gregerson; Ava Spataru; Baptiste Roziere; Ben Maurer; Benjamin Leonhardi; Bernie Huang; Bhargavi Paranjape; Bing Liu; Binh Tang; Bobbie Chern; Brani Stojkovic; Brian Fuller; Catalina Mejia Arenas; Chao Zhou; Charlotte Caucheteux; Chaya Nayak; Ching-Hsiang Chu; Chloe Bi; Chris Cai; Chris Cox; Chris Marra; Chris McConnell; Christian Keller; Christoph Feichtenhofer; Christophe Touret; Chunyang Wu; Corinne Wong; Cristian Canton Ferrer; Damien Allonsius; Daniel Kreymer; Daniel Haziza; Daniel Li; Danielle Pintz; Danny Livshits; Danny Wyatt; David Adkins; David Esiobu; David Xu; Davide Testuggine; Delia David; Devi Parikh; Dhruv Choudhary; Dhruv Mahajan; Diana Liskovich; Diego Garcia-Olano; Diego Perino; Dieuwke Hupkes; Dingkang Wang; Dustin Holland; Egor Lakomkin; Elina Lobanova; Xiaoqing Ellen Tan; Emily Dinan; Eric Smith; Erik Brinkman; Esteban Arcaute; Filip Radenovic; Firat Ozgenel; Francesco Caggioni; Frank Seide; Frank Zhang; Gabriel Synnaeve; Gabriella Schwarz; Gabrielle Lee; Gada Badeer; Georgia Anderson; Graeme Nail; Gregoire Mialon; Guan Pang; Guillem Cucurell; Hailey Nguyen; Hannah Korevaar; Hannah Wang; Haroun Habeeb; Harrison Rudolph; Henry Aspegren; Hu Xu; Hugo Touvron; Iga Kozlowska; Igor Molybog; Igor Tufanov; Iliyan Zarov; Imanol Arrieta Ibarra; Irina-Elena Veliche; Isabel Kloumann; Ishan Misra; Ivan Evtimov; Jacob Xu; Jade Copet; Jake Weissman; Jan Geffert; Jana Vranes; Japhet Asher; Jason Park; Jay Mahadeokar; Jean-Baptiste Gaya; Jeet Shah; Jelmer van der Linde; Jennifer Chan; Jenny Hong; Jenya Lee; Jeremy Fu; Jeremy Teboul; Jianfeng Chi; Jianyu Huang; Jie Wang; Jiecao Yu; Joanna Bitton; Joe Spisak; Joelle Pineau; Jon Carvill; Jongsoo Park; Joseph Rocca; Joshua Johnstun; Junteng Jia; Kalyan Vasuden Alwala; Kam Hou U; Kate Plawiak; Kartikeya Upasani; Kaushik Veeraraghavan; Ke Li; Kenneth Heafield; Kevin Stone; Khalid El-Arini; Krithika Iyer; Kshitiz Malik; Kuenley Chiu; Kunal Bhalla; Kyle Huang; Lakshya Garg; Lauren Rantala-Yeary; Laurens van der Maaten; Lawrence Chen; Leandro Silva; Lee Bell; Lei Zhang; Liang Tan; Louis Martin; Lovish Madaan; Luca Wehrstedt; Lukas Blecher; Luke de Oliveira; Madeline Muzzi; Madian Khabsa; Manav Avlani; Mannat Singh; Manohar Paluri; Mark Zuckerberg; Marcin Kardas; Martynas Mankus; Mathew Oldham; Mathieu Rita; Matthew Lennie; Maya Pavlova; Meghan Keneally; Melanie Kambadur; Mihir Patel; Mikayel Samvelyan; Mike Clark; Mike Lewis; Min Si; Mitesh Kumar Singh; Mo Metanat; Mona Hassan; Naman Goyal; Narjes Torabi; Nicolas Usunier; Nikolay Bashlykov; Nikolay Bogoychev; Niladri Chatterji; Ning Dong; Oliver Aobo Yang; Olivier Duchenne; Onur Celebi; Parth Parekh; Patrick Alrassy; Paul Saab; Pavan Balaji; Pedro Rittner; Pengchuan Zhang; Pengwei Li; Petar Vasic; Peter Weng; Polina Zvyagina; Prajjwal Bhargava; Pratik Dubal; Praveen Krishnan; Punit Singh Koura; Qing He; Rachel Rodriguez; Ragavan Srinivasan; Rahul Mitra; Ramon Calderer; Raymond Li; Robert Stojnic; Roberta Raileanu; Robin Battey; Rocky Wang; Rohit Girdhar; Rohit Patel; Romain Sauvestre; Ronnie Polidoro; Roshan Sumbaly; Ross Taylor; Ruan Silva; Rui Hou; Rui Wang; Russ Howes; Ruty Rinott; Saghar Hosseini; Sai Jayesh Bondu; Samyak Datta; Sanjay Singh; Sara Chugh; Sargun Dhillon; Satadru Pan; Sean Bell; Sergey Edunov; Shaoliang Nie; Sharan Narang; Sharath Raparthy; Shaun Lindsay; Sheng Feng; Sheng Shen; Shenghao Lin; Shiva Shankar; Shruti Bhosale; Shun Zhang; Simon Vandenhende; Sinong Wang; Seohyun Sonia Kim; Soumya Batra; Sten Sootla; Steve Kehoe; Suchin Gururangan; Sumit Gupta; Sunny Virk; Sydney Borodinsky; Tamar Glaser; Tamar Herman; Tamara Best; Tara Fowler; Thomas Georgiou; Thomas Scialom; Tianhe Li; Todor Mihaylov; Tong Xiao; Ujjwal Karn; Vedanuj Goswami; Vibhor Gupta; Vignesh Ramanathan; Viktor Kerkez; Vinay Satish Kumar; Vincent Gonguet; Vish Vogeti; Vlad Poenaru; Vlad Tiberiu Mihailescu; Vladan Petrovic; Vladimir Ivanov; Wei Li; Weiwei Chu; Wenhan Xiong; Wenyin Fu; Wes Bouaziz; Whitney Meers; Will Constable; Xavier Martinet; Xiaojian Wu; Xinbo Gao; Xinfeng Xie; Xuchao Jia; Yaelle Goldschlag; Yann LeCun; Yashesh Gaur; Yasmine Babaei; Ye Qi; Yenda Li; Yi Wen; Yiwen Song; Youngjin Nam; Yuchen Hao; Yuchen Zhang; Yun Wang; Yuning Mao; Yuzi He; Zacharie Delpierre Coudert; Zachary DeVito; Zahra Hankir; Zhaoduo Wen; Zheng Yan; Zhengxing Chen; Zhenyu Yang; Zoe Papakipos"])</script><script>self.__next_f.push([1,"9f:T2a20,"])</script><script>self.__next_f.push([1,"## Llama3 Swallow\n\nOur Swallow model has undergone continual pre-training from the [Llama 3 family](https://huggingface.co/collections/meta-llama/meta-llama-3-66214712577ca38149ebb2b6), primarily with the addition of Japanese language data. The Instruct versions use supervised fine-tuning (SFT) and Chat Vector.\n\n## Model Release Updates\n\nWe are excited to share the release schedule for our latest models:\n- **July 1, 2024**: Released the [Llama-3-Swallow-8B-v0.1](https://huggingface.co/tokyotech-llm/Llama-3-Swallow-8B-v0.1), [Llama-3-Swallow-8B-Instruct-v0.1](https://huggingface.co/tokyotech-llm/Llama-3-Swallow-8B-Instruct-v0.1), [Llama-3-Swallow-70B-v0.1](https://huggingface.co/tokyotech-llm/Llama-3-Swallow-70B-v0.1), and [Llama-3-Swallow-70B-Instruct-v0.1](https://huggingface.co/tokyotech-llm/Llama-3-Swallow-70B-Instruct-v0.1).\n\n### Swallow Model Index\n\n|Model|Llama-3-Swallow|Llama3 Swallow Instruct|\n|---|---|---|\n|8B| [Link](https://huggingface.co/tokyotech-llm/Llama-3-Swallow-8B-v0.1) | [Link](https://huggingface.co/tokyotech-llm/Llama-3-Swallow-8B-Instruct-v0.1) |\n|70B| [Link](https://huggingface.co/tokyotech-llm/Llama-3-Swallow-70B-v0.1) | [Link](https://huggingface.co/tokyotech-llm/Llama-3-Swallow-70B-Instruct-v0.1) |\n\nThis repository provides large language models developed by [Swallow-LLM](https://swallow-llm.github.io/).\nRead our [blog post](https://zenn.dev/tokyotech_lm/articles/f65989d76baf2c).\n\n### Third-Party Community Consideration\n\nThis model is not owned or developed by NVIDIA. This model has been developed and built to a third-party’s requirements for this application and use case; see link to [Non-NVIDIA Model Card](https://github.com/meta-llama/llama3/blob/main/MODEL_CARD.md).\n\n### License\n\n[META LLAMA 3 COMMUNITY LICENSE](https://llama.meta.com/llama3/license/)\n\n### Model Details\n\n* **Model type**: Please refer to [Llama 3 MODEL_CARD](https://github.com/meta-llama/llama3/blob/main/MODEL_CARD.md) for details on the model architecture.\n* **Languages**: Japanese English\n* **Library**: [Megatron-LM](https://github.com/NVIDIA/Megatron-LM)\n* **Tokenizer**: Please refer to [Llama 3 blog](https://ai.meta.com/blog/meta-llama-3/) for details on the tokenizer.\n* **Contact**: swallow[at]nlp.c.titech.ac.jp\n\n### Model Architecture:\n\n**Architecture Type:** Transformer \u003cbr\u003e\n\n### Risks and Limitations\n\nThe models released here are still in the early stages of our research and development and have not been tuned to ensure outputs align with human intent and safety considerations.\n\n### Input:\n\n**Input Type(s):** Text \u003cbr\u003e\n**Input Format(s):** String \u003cbr\u003e\n**Input Parameters:** One Dimensional (1D) \u003cbr\u003e\n\n### Output:\n\n**Output Type(s):** Text \u003cbr\u003e\n**Output Format:** String \u003cbr\u003e\n**Output Parameters:** 1D \u003cbr\u003e\n\n**Supported Hardware Microarchitecture Compatibility:** \u003cbr\u003e\n* NVIDIA Ampere \u003cbr\u003e\n* NVIDIA Hopper \u003cbr\u003e\n* NVIDIA Lovelace \u003cbr\u003e\n\n**Preferred Operating System(s):** \u003cbr\u003e\n* Linux \u003cbr\u003e\n\n### Training Dataset:\n\n#### Instruction Tuning\n\nThe following datasets were used for the instruction tuning.\n\n- [OpenAssistant Conversations Dataset EN top-1 thread](https://huggingface.co/datasets/OpenAssistant/oasst2)\n- [OpenAssistant Conversations Dataset](https://huggingface.co/datasets/llm-jp/oasst1-21k-ja) was used, where human utterances are included but the responses are not used. Instead, the responses were generated using the [Mixtral-8x7B-Instruct-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1) model.\n\n### Model Performance\n\n#### Japanese tasks\n\n|Model|Size|JCom.|JEMHopQA|NIILC|JSQuAD|XL-Sum|MGSM|WMT20-en-ja|WMT20-ja-en|JMMLU|JHumanEval|Ja Avg|\n|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| | |4-shot|4-shot|4-shot|4-shot|1-shot|4-shot|4-shot|4-shot|5-shot|0-shot| |\n| | |EM acc|Char-F1|Char-F1|Char-F1|ROUGE-2|EM acc|BLEU|BLEU|EM acc|pass@1| |\n|karakuri-lm-70b-chat-v0.1|70B|0.8847|0.5139|0.5668|0.9096|0.1369|0.2800|0.2526|0.2095|0.4648|0.2354|0.4454|\n|Meta-Llama-3-70B-Instruct|70B|0.9419|0.6114|0.5506|0.9164|0.1912|0.7200|0.2708|0.2350|0.6789|0.6610|0.5777|\n|Llama-3-Swallow-70B-Instruct-v0.1|70B|0.9607|0.6188|0.6026|0.9236|0.1389|0.6560|0.2724|0.2532|0.6572|0.6000|0.5683|\n|Qwen2-72B-Instruct|72B|0.9634|0.6268|0.5418|0.9210|0.1644|0.7840|0.2592|0.2327|0.7713|0.6909|0.5955|\n\n#### English tasks\n\n|Model|Size|OpenBookQA|TriviaQA|HellaSWAG|SQuAD2.0|XWINO|MMLU|GSM8K|BBH|HumanEval|EnAvg|\n|---|---|---|---|---|---|---|---|---|---|---|---|\n|||4-shot|4-shot|4-shot|4-shot|4-shot|5-shot|4-shot|3-shot|0-shot||\n|||Acc|EMacc|Acc|EMacc|Acc|Acc|EMacc|CoTEMAcc|pass@1||\n|karakuri-lm-70b-chat-v0.1|70B|0.4100|0.6873|0.6315|0.3677|0.9049|0.5941|0.3882|0.5724|0.2305|0.5319|\n|Meta-Llama-3-70B-Instruct|70B|00.4400|0.7999|0.6552|0.4024|0.9127|0.7992|0.9052|0.8326|0.7555|0.7225|\n|Llama-3-Swallow-70B-Instruct-v0.1|70B|0.4520|0.8174|0.6758|0.4050|0.9230|0.7883|0.8688|0.8152|0.6890|0.7150|\n|Qwen2-72B-Instruct|72B|0.4360|0.7588|0.6857|0.3913|0.9110|0.8391|0.8499|0.2436|0.6939|0.6455|\n\n### MT-Bench JA\n\n|Model|Size|coding|extraction|humanities|math|reasoning|roleplay|stem|writing|JMTAvg|\n|---|---|---|---|---|---|---|---|---|---|---|\n|karakuri-lm-70b-chat-v0.1|70B|0.2804|0.5862|0.6240|0.2934|0.4183|0.5530|0.4859|0.5964|0.4797|\n|Meta-Llama-3-70B-Instruct|70B|0.5969|0.8410|0.7120|0.4481|0.4884|0.7117|0.6510|0.6900|0.6424|\n|Llama-3-Swallow-70B-Instruct-v0.1|70B|0.5269|0.7250|0.5690|0.4669|0.6121|0.6238|0.5533|0.5698|0.5809|\n|Qwen2-72B-Instruct|72B|0.5699|0.7858|0.8222|0.5096|0.7032|0.7963|0.7728|0.8223|0.7228|\n|GPT-3.5(gpt-3.5-turbo-0125)| |0.6851|0.7641|0.7414|0.5522|0.5128|0.7104|0.6266|0.7361|0.6661|\n|GPT-4o(gpt-4o-2024-05-13)| |0.7296|0.8540|0.8646|0.6641|0.6661|0.8274|0.8184|0.8085|0.7791|\n\n### Evaluation Benchmarks\n\n#### Japanese evaluation benchmarks\n\nWe used llm-jp-eval(v1.3.0), JP Language Model Evaluation Harness(commit #9b42d41) and Code Generation LM Evaluation Harness(commit #0261c52). The details are as follows:\n\n- Multiple-choice question answering (JCommonsenseQA [Kurihara et al., 2022])\n- Open-ended question answering (JEMHopQA [Ishii et al., 2024])\n- Open-ended question answering (NIILC [関根, 2003])\n- Machine reading comprehension (JSQuAD [Kurihara et al., 2022])\n- Automatic summarization (XL-Sum [Hasan et al., 2021])\n- Machine translation (WMT2020 ja-en [Barrault et al., 2020])\n- Machine translation (WMT2020 en-ja [Barrault et al., 2020])\n- Mathematical reasoning (MGSM [Shi et al., 2023])\n- Academic exams (JMMLU [尹ら, 2024])\n- Code generation (JHumanEval [佐藤ら, 2024])\n\n#### English evaluation benchmarks\n\nWe used the Language Model Evaluation Harness(v.0.4.2) and Code Generation LM Evaluation Harness(commit #0261c52). The details are as follows:\n\n- Multiple-choice question answering (OpenBookQA [Mihaylov et al., 2018])\n- Open-ended question answering (TriviaQA [Joshi et al., 2017])\n- Machine reading comprehension (SQuAD2 [Rajpurkar et al., 2018])\n- Commonsense reasoning (XWINO [Tikhonov and Ryabinin, 2021])\n- Natural language inference (HellaSwag [Zellers et al., 2019])\n- Mathematical reasoning (GSM8K [Cobbe et al., 2021])\n- Reasoning (BBH (BIG-Bench-Hard) [Suzgun et al., 2023])\n- Academic exams (MMLU [Hendrycks et al., 2021])\n- Code generation (HumanEval [Chen et al., 2021])\n\n#### MT-Bench JA\n\nWe used [Japanese MT-Bench](https://wandb.ai/wandb-japan/llm-leaderboard/artifacts/dataset/mtbench_ja_question) to assess the instruction-following capabilities of models.\nWe utilized the following settings:\n\n- Implemantation: FastChat [Zheng+, 2023] (commit #e86e70d0)\n- Question: [Nejumi LLM-Leaderboard NEO, mtbench_ja_question_v3](https://wandb.ai/wandb-japan/llm-leaderboard/artifacts/dataset/mtbench_ja_question/v3)\n- Reference Answer: [Nejumi LLM-Leaderboard NEO, mtbench_ja_referenceanswer_v1](https://wandb.ai/wandb-japan/llm-leaderboard/artifacts/dataset/mtbench_ja_referenceanswer/v1)\n- Prompt for Judge: [Nejumi LLM-Lederboard NEO, mtbench_ja_prompt_v1](https://wandb.ai/wandb-japan/llm-leaderboard/artifacts/dataset/mtbench_ja_prompt/v1)\n- Judge: `gpt-4-1106-preview`\n- Scoring: Absolute scale normalized to a 0-1 range, averaged over five runs.\n\n### Inference:\n\n**Engine:** TensorRT-LLM \u003cbr\u003e\n**Test Hardware:** \u003cbr\u003e\n* NVIDIA H100x4 \u003cbr\u003e\n\n### Ethical Considerations:\n\nNVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their internal model team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse.\n\nPlease report security vulnerabilities or NVIDIA AI Concerns [here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/).\n\n### Authors\n\nHere are the team members:\n- From [Tokyo Institute of Technology Okazaki Laboratory](https://www.nlp.c.titech.ac.jp/index.en.html), the following members:\n - [Naoaki Okazaki](https://www.chokkan.org/index.ja.html)\n - [Sakae Mizuki](https://s-mizuki-nlp.github.io/)\n - [Youmi Ma](https://www.nlp.c.titech.ac.jp/member/youmi.en.html)\n - [Koki Maeda](https://sites.google.com/view/silviase)\n - [Kakeru Hattori](https://aya-se.vercel.app/)\n - [Masanari Ohi](https://sites.google.com/view/masanariohi)\n - [Taihei Shiotani](https://github.com/inatoihs)\n - [Koshiro Saito](https://sites.google.com/view/koshiro-saito)\n- From [Tokyo Institute of Technology YOKOTA Laboratory](https://www.rio.gsic.titech.ac.jp/en/index.html), the following members:\n - [Rio Yokota](https://twitter.com/rioyokota)\n - [Kazuki Fujii](https://twitter.com/okoge_kaz)\n - [Taishi Nakamura](https://twitter.com/Setuna7777_2)\n - [Takumi Okamoto](https://www.linkedin.com/in/takumi-okamoto)\n - [Ishida Shigeki](https://www.wantedly.com/id/reborn27)\n- From [Artificial Intelligence Research Center, AIST, Japan](https://www.airc.aist.go.jp/en/teams/), the following members:\n - [Hiroya Takamura](https://sites.google.com/view/hjtakamura)\n\n### How to Cite\n\nIf you find our work helpful, please feel free to cite us.\n\n```tex\n@misc{llama3swallow,\n title={Llama 3 Swallow},\n url={https://swallow-llm.github.io/llama3-swallow.en.html},\n author={Swallow LLM},\n year={2024},\n}\n```\n\n#### Citations\n\n```tex\n@article{llama3modelcard,\n title={Llama 3 Model Card},\n author={AI@Meta},\n year={2024},\n url = {https://github.com/meta-llama/llama3/blob/main/MODEL_CARD.md}\n}\n```\n\n### Acknowledgements\n\nWe thank Meta Research for releasing Llama 3 under an open license for others to build on.\n\nOur project is supported by the [Large Generative AI Development Support Program](https://abci.ai/en/link/lfm_support_program.html) of the National Institute of Advanced Industrial Science and Technology.\n"])</script><script>self.__next_f.push([1,"a0:T7c0,Field | Response\n:----------------------------------------------------------------------------------------------------------------------------------|:-----------------------------------------------\nGeneratable or reverse engineerable personally-identifiable information (PII)? | None\nWas consent obtained for any PII used? | Not Applicable\nProtected class data used to create this model? | Not Applicable\nHow often is dataset reviewed? | Before Release\nIs a mechanism in place to honor data subject right of access or deletion of personal data? | No\nIf PII collected for the development of the model, was it collected directly by NVIDIA? | Not Applicable\nIf PII collected for the development of the model by NVIDIA, do you maintain or have access to disclosures made to data subjects? | Not Applicable\nIf PII collected for the development of this AI model, was it minimized to only what was required? | Not Applicable\nIs there provenance for all datasets used in training? | Yes\nDoes data labeling (annotation, metadata) comply with privacy laws? | Yes\nIs data compliant with data subject requests for data correction or removal, if such a request was made? | No, not possible with externally-sourced data.a1:Te2b,"])</script><script>self.__next_f.push([1,"## Description:\nThe Megatron Multilingual 1.5B Neural Machine Translation model translates text in any to any directions across the 33 supported languages, including non-English centric translation (such as French to Chinese, etc). The Supported languages are: English(en), Czech(cs), Danish (da), German(de), Greek(el), Spanish(es), Finnish(fi), France(fr), Hungarian(hu), Italian(it), Lithuanian(lt), Latvian(lv),Dutch(nl), Norwegian(no), Polish(pl), Portugese(pt), Romanian(ro), Russian(ru), Slovak(sk), Swedish(sv), Chinese(zh), Japanese(ja), Hindi(hi), Korean(ko), Estonian(et), Slovenian(sl), Bulgarian(bg), Ukrainian(uk), Croatian(hr), Arabic(ar), Vietnamese(vi), Turkish(tr), Indonesian(id). This model is ready for commercial use. \n\n## Model Architecture\n\nArchitecture Type: Transformer\n\nNetwork Architecture: Megatron\n\nThe model is based on Transformer architecture originally presented in \"Attention Is All You Need\" paper [1]. In this particular instance, the model has 24 layers in the encoder and 24 layers in the decoder. It is using SentencePiece tokenizer [2].\n\n\n## Input: \n**Input Type(s):** Text String \u003cbr\u003e\n**Input Format(s):** List \u003cbr\u003e\n\n**Other Properties Related to Input:** No Pre-Processing Needed; No Tokenization required; 512 Character Text String Limit (No non-textual characters) \u003cbr\u003e\n\n\n## Output: \n**Output Type(s):** Text String \u003cbr\u003e\n**Output Format:** List \u003cbr\u003e\n**Output Parameters:** Selected Language \u003cbr\u003e\n**Other Properties Related to Output:** Outputs are not tokenized or processed to hide sensitive input information \u003cbr\u003e\n\n# Training \u0026 Evaluation Dataset: \n\n** Data Collection Method by dataset \u003cbr\u003e\n* Human \u003cbr\u003e\n\n** Labeling Method by dataset \u003cbr\u003e\n* Automated \u003cbr\u003e\n\n**Properties (Quantity, Dataset Descriptions, Sensor(s)):** This model is trained on open-sourced datasets and synthetic datasets of text parallel corpora generated via back-translation. \u003cbr\u003e\n\n## References:\n[1] Vaswani, Ashish, et al. \"Attention is all you need.\" arXiv preprint arXiv:1706.03762 (2017).\n[2] https://github.com/google/sentencepiece\n[3] https://en.wikipedia.org/wiki/BLEU\n[4] https://github.com/mjpost/sacreBLEU\n[5] NVIDIA NeMo Toolkit\n\n## Software Integration\n**Runtime Engine(s):** \n* Riva 2.15.0 or Higher \u003cbr\u003e\n\n**Supported Operating System(s):** \u003cbr\u003e\n* Linux \u003cbr\u003e\n\n## Model Version(s): \nnmt_megatron_1b_any_any:2.15.1\u003cbr\u003e\n\n# Inference\n**Engine:** Triton \u003cbr\u003e\n**Test Hardware:** \u003cbr\u003e\n* NVIDIA H100 GPU\n* NVIDIA A100 GPU\n* NVIDIA L40 GPU\n\n\n## Ethical Considerations (For NVIDIA Models Only):\nNVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their internal model team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse. For more detailed information on ethical considerations for this model, please see the Model Card++ Explainability, Bias, Safety \u0026 Security, and Privacy Subcards. Please report security vulnerabilities or NVIDIA AI Concerns [here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/).\n\n## GOVERNING TERMS: \nThis trial is governed by the NVIDIA API Trial Terms of Service (found at https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf). The use of this model is governed by the AI Foundation Models Community License Agreement (found at NVIDIA Agreements | Enterprise Software | NVIDIA AI Foundation Models Community License Agreement)."])</script><script>self.__next_f.push([1,"a2:T8ab,"])</script><script>self.__next_f.push([1,"Field | Response\n:------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------\nIntended Applications \u0026 Domains: | Text and Document Translation\nTypes: | Text translation\nIntended Users: | This model is intended for our developers to perform text and document translation.\nOutput: | Text (in Target Language)\nDescribe how the model works: | Model translates text in one language into in target language.\nName the adversely impacted groups this has been tested to deliver comparable outcomes regardless of: | Not Applicable\nTechnical Limitations: | Translations may not be 100% accurate. Accuracy varies based on the characteristics of input (Domain, Use Case, Noise, Context, etcetera). Grammar errors and semantic issues may be present.\nVerified to have met prescribed NVIDIA quality standards: | Yes\nPerformance Metrics: | BiLingual Evaluation Understudy (BLEU) Scores, Crosslingual Optimized Metric for Evaluation of Translation (COMET)\nPotential Known Risks: | Model only supports 2-letter language codes and not Internet Engineering Task Force BCP-47 codes so this model may not return translations specific to a region.\nLicensing: | [Riva](https:developer.nvidia.com/riva/ga/license)"])</script><script>self.__next_f.push([1,"a3:T756,Pull and run the NVIDIA NIM with the command below. \n\nThis command launches NIM container on any of the supported GPUs.\n\n```bash\nexport NGC_API_KEY=\u003cPASTE_API_KEY_HERE\u003e\n\nexport CONTAINER_NAME=megatron-1b-nmt\ndocker run -it --rm --name=$CONTAINER_NAME \\\n --runtime=nvidia \\\n --gpus '\"device=0\"' \\\n --shm-size=8GB \\\n -e NGC_API_KEY=$NGC_API_KEY \\\n -e NIM_MANIFEST_PROFILE=89e2a0b4-477e-11ef-b226-cf5f41e3c684 \\\n -e NIM_HTTP_API_PORT=9000 \\\n -e NIM_GRPC_API_PORT=50051 \\\n -p 9000:9000 \\\n -p 50051:50051 \\\n nvcr.io/nim/nvidia/megatron-1b-nmt:1.0.0\n```\n\n```{note}\nIt may take a up to 30 minutes depending on your network speed, for the container to be ready and start accepting requests from the time the docker container is started.\n```\n\nOpen a new terminal and run following command to check if the service is ready to handle inference requests\n\n```bash\ncurl -X 'GET' 'http://localhost:9000/v1/health/ready'\n```\n\nIf the service is ready, you get a response similar to the following.\n```bash\n{\"ready\":true}\n```\n\nInstall the Riva Python client package\n\n```bash\nsudo apt-get install python3-pip\npip install -r https://raw.githubusercontent.com/nvidia-riva/python-clients/main/requirements.txt\npip install --force-reinstall git+https://github.com/nvidia-riva/python-clients.git\n```\n\nDownload Riva sample clients\n\n```bash\ngit clone https://github.com/nvidia-riva/python-clients.git\n```\n\nRun Text to Text translation inference\n\n```bash\npython3 python-clients/scripts/nmt/nmt.py --server 0.0.0.0:50051 --text \"This will become German words\" --source-language-code en --target-language-code de\n```\n\nAbove command will translate the text from English to German and output will be as shown below.\n\n```bash\n## Das werden deutsche Wörter\n```\n\nFor more details on getting started with this NIM, visit the [NVIDIA NIM Docs](https://docs.nvidia.com/nim/riva/nmt/latest/overview.html).\na4:T842,"])</script><script>self.__next_f.push([1,"### Getting Started\n\nRiva uses \u003ca href=\"https://grpc.io/\"\u003egRPC\u003c/a\u003e APIs. Instructions below demonstrate usage of \u003c%- name %\u003e model using Python gRPC client.\n\n### Prerequisites\n\nYou will need a system with Git and Python 3+ installed.\n\n### Install Riva Python Client\n\n```bash\n$ pip install -r https://raw.githubusercontent.com/nvidia-riva/python-clients/main/requirements.txt\n$ pip install --force-reinstall git+https://github.com/nvidia-riva/python-clients.git\n```\n\n### Download Python Client\n\nDownload Python client code by cloning \u003ca href=\"https://github.com/nvidia-riva/python-clients\"\u003ePython Client Repository\u003c/a\u003e.\n\n```bash\n$ git clone https://github.com/nvidia-riva/python-clients.git\n```\n\n### Run Python Client\n\nOpen a command terminal and execute below command to translate text. If you have generated the API key, it will be auto-populated in the command.\n\n```bash\n$ python python-clients/scripts/nmt/nmt.py \\\n --server grpc.nvcf.nvidia.com:443 --use-ssl \\\n --metadata function-id \"\u003c%- nvcfFunctionId %\u003e\" \\\n --metadata \"authorization\" \"Bearer \u003c%- apiKey %\u003e\" \\\n --text \"This is an example text for Riva text translation\" \\\n --source-language-code en \\\n --target-language-code de\n```\n\nList of supported source and target languages can be queried using below command.\n\n```bash\n$ python python-clients/scripts/nmt/nmt.py \\\n --server grpc.nvcf.nvidia.com:443 --use-ssl \\\n --metadata function-id \"\u003c%- nvcfFunctionId %\u003e\" \\\n --metadata \"authorization\" \"Bearer \u003c%- apiKey %\u003e\" \\\n --list-models\n```\n\n### Support for gRPC clients in other languages\n\nRiva uses \u003ca href=\"https://grpc.io/\"\u003egRPC\u003c/a\u003e APIs. Proto files can be downloaded from \u003ca href=\"https://github.com/nvidia-riva/common/archive/refs/heads/main.zip\"\u003eRiva gRPC Proto files\u003c/a\u003e and compiled to target language using \u003ca href=\"https://grpc.io/docs/protoc-installation/\"\u003eProtoc compiler\u003c/a\u003e. Example Riva clients in C++ and Python languages are provided below.\n\n* \u003ca href=\"https://github.com/nvidia-riva/python-clients\"\u003ePython Client Repository\u003c/a\u003e\n* \u003ca href=\"https://github.com/nvidia-riva/cpp-clients\"\u003eC++ Client Repository\u003c/a\u003e\n"])</script><script>self.__next_f.push([1,"a5:T1309,"])</script><script>self.__next_f.push([1,"## Speech Synthesis: English-US Multispeaker - Model Overview\n\n### Description:\n\nThe English-US Multispeaker FastPitch-HifiGAN model transcribes text into audio representations using two model components: Fastpitch and HifiGAN. This model is ready for commercial use.\n\nFastPitch is a mel-spectrogram generator, designed to be used as the first part of a neural text-to-speech system in conjunction with a neural vocoder. This model uses the International Phonetic Alphabet (IPA) for inference and training, and it can output a female or a male voice for US English.\n\nHifiGAN is a neural vocoder model for text-to-speech applications. It is the second part of a two-stage speech synthesis pipeline.\n\n### References:\n\n[FastPitch Model on NGC](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/riva/models/speechsynthesis_en_us_fastpitch_ipa)\n\n[HifiGAN Model on NGC](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/riva/models/speechsynthesis_en_us_hifigan_ipa)\n\nHifiGAN paper: [https://arxiv.org/abs/2010.05646](https://arxiv.org/abs/2010.05646)\n\n### Model Architecture:\n\nNetwork Architecture: FastPitch + HifiGAN\n\nFastPitch is a fully-parallel text-to-speech transformer-based model, conditioned on fundamental frequency contours. The model predicts pitch contours during inference. By altering these predictions, the generated speech can be more expressive, better match the semantic of the utterance, and be engaging to the listener.\n\nHifiGAN is a neural vocoder based on a generative adversarial network framework. During training, the model uses a powerful discriminator consisting of small sub-discriminators, each one focusing on specific periodic parts of a raw waveform.\n\n### Input:\n\nFor FastPitch (1st Stage): Text Strings in English\n\n**Other Properties Related to Input:** 400 Character Text String Limit \u003cbr\u003e\n\n### Output:\n\nFor HifiGAN (2nd Stage): Audio of shape (batch x time) in wav format\n\n**Other Parameters Related to Output:** Mono, Encoded 16 bit audio; 20 Second Maximum Length; Depending on input, this model can output a female or a male voice for American English with six (6) emotions for the female voice and four (4) emotions for male voice. The female voice is classified as \"neutral,\" \"calm,\" \"happy,\" \"angry,\" \"fearful,\" and \"sad.\" The male voice is classified as \"neutral,\" “calm,\" \"happy,\" and \"angry.\"\n\n## Training \u0026 Evaluation Dataset:\n\n### Training Dataset:\n\n** Data Collection Method by dataset \u003cbr\u003e\n* Human \u003cbr\u003e\n **Properties (Quantity, Dataset Descriptions, Sensor(s)):** This model is trained on a proprietary dataset of audio-text pairs sampled at 44100 Hz, which contains one Female and one Male voice speaking US English. While both genders are trained for all emotions, this dataset only releases those that passed the evaluation standard for expressiveness and quality. The dataset also contains a subset of sentences with different words emphasized. \u003cbr\u003e\n\n### Evaluation Dataset:\n\n** Data Collection Method by dataset \u003cbr\u003e\n* Human \u003cbr\u003e\n **Properties (Quantity, Dataset Descriptions, Sensor(s)):** This model is trained on a proprietary dataset sampled at 44100 Hz, which contains one Female and one Male voice speaking US English. While both genders are trained for all emotions, this dataset only releases those that passed the evaluation standard for expressiveness and quality. The dataset also contains a subset of sentences with different words emphasized. \u003cbr\u003e\n\n### Software Integration\n\n**Runtime Engine(s):**\n* Riva 2.15.0 or Higher \u003cbr\u003e\n\n**Supported Operating System(s):** \u003cbr\u003e\n* Linux \u003cbr\u003e\n\n### Model Version(s):\n\n* 2.15.0 \u003cbr\u003e\n\n## Inference\n\n**Engine:** Triton \u003cbr\u003e\n**Test Hardware:** \u003cbr\u003e\n* NVIDIA H100 GPU\n* NVIDIA A100 GPU\n* NVIDIA L40 GPU\n\n### Ethical Considerations (For NVIDIA Models Only):\n\nNVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their internal model team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse. For more detailed information on ethical considerations for this model, please see the Model Card++ Explainability, Bias, Safety \u0026 Security, and Privacy Subcards. Please report security vulnerabilities or NVIDIA AI Concerns [here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/).\n\n### GOVERNING TERMS:\n\nThis trial is governed by the NVIDIA API Trial Terms of Service (found at https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf). The use of this model is governed by the AI Foundation Models Community License Agreement (found at NVIDIA Agreements | Enterprise Software | NVIDIA AI Foundation Models Community License Agreement).\n"])</script><script>self.__next_f.push([1,"a6:T646,Field | Response\n:------|:----------\nIntended Application \u0026 Domain: | Speech Synthesis\nModel Task | Speech Synthesis and Generative Adversarial Network\nIntended Users | This model is intended for developers building interactive call centers, virtual assistants, language learning assistants to improve pronunciation, automatically generate voice-overs, narrate or comment on videos, provide audio alternatives for visually impaired users or people with light sensitivity.\nModel Output | Audio files (.wav)\nHow the model works | Model transcribes input text characters into audio representation.\nTechnical Limitations | Model only has the capacity to produce a voice in the language, dialect and gender(s) in which it is trained. This model makes no effort to moderate or modify input text. \nPerformance Metrics | % preference when compared with available alternatives\u003cbr\u003ePitch (mean)\u003cbr\u003ePitch_standard deviation (std) (mean)\u003cbr\u003ePitch_kurtosis (mean)\u003cbr\u003ePitch_skew (mean)\u003cbr\u003eFundamental Frequency Ratio (f0_ratio) (mean)\u003cbr\u003ef0_ratio_std (mean)\u003cbr\u003ef0_ratio_kurtosis (mean)\u003cbr\u003ef0_ratio_skew (mean)\u003cbr\u003ePitch (median)\u003cbr\u003ePitch_std (median)\u003cbr\u003ePitch_kurtosis (median)\u003cbr\u003ePitch_skew (median)\u003cbr\u003ef0_ratio (median)\u003cbr\u003ef0_ratio_std (median)\u003cbr\u003ef0_ratio_kurtosis (median)\u003cbr\u003ef0_ratio_skew (median)\"\nPotential Known Risks | May unnaturally synthesize vocabulary not included in pronunciation dictionary or omit phonetic symbols not used in training.\nLicensing: | [https://docs.nvidia.com/ai-foundation-models-community-license.pdf](https://docs.nvidia.com/ai-foundation-models-community-license.pdf)a7:T86e,"])</script><script>self.__next_f.push([1,"Pull and run the NVIDIA NIM with the command below. \n\nThis command launches NIM container with the generic (non-optimized) model on any of the supported GPUs. GPU specific optimized models are available for select GPUs. For using optimized models, refer the [Supported Models](https://docs.nvidia.com/nim/riva/tts/latest/getting-started.html#supported-models) and specify NIM_MANIFEST_PROFILE according to your GPU in the Docker run command below.\n\n```bash\nexport NGC_API_KEY=\u003cPASTE_API_KEY_HERE\u003e\n\nexport CONTAINER_NAME=fastpitch-hifigan-tts\ndocker run -it --rm --name=$CONTAINER_NAME \\\n --runtime=nvidia \\\n --gpus '\"device=0\"' \\\n --shm-size=8GB \\\n -e NGC_API_KEY=$NGC_API_KEY \\\n -e NIM_MANIFEST_PROFILE=3c8ee3ee-477f-11ef-aa12-1b4e6406fad5 \\\n -e NIM_HTTP_API_PORT=9000 \\\n -e NIM_GRPC_API_PORT=50051 \\\n -p 9000:9000 \\\n -p 50051:50051 \\\n nvcr.io/nim/nvidia/fastpitch-hifigan-tts:1.0.0\n```\n\n```{note}\nIt may take a up to 30 minutes depending on your network speed, for the container to be ready and start accepting requests from the time the docker container is started.\n```\n\nOpen a new terminal and run following command to check if the service is ready to handle inference requests\n\n```bash\ncurl -X 'GET' 'http://localhost:9000/v1/health/ready'\n```\n\nIf the service is ready, you get a response similar to the following.\n```bash\n{\"ready\":true}\n```\n\nInstall the Riva Python client package\n\n```bash\nsudo apt-get install python3-pip\npip install -r https://raw.githubusercontent.com/nvidia-riva/python-clients/main/requirements.txt\npip install --force-reinstall git+https://github.com/nvidia-riva/python-clients.git\n```\n\nDownload Riva sample clients\n\n```bash\ngit clone https://github.com/nvidia-riva/python-clients.git\n```\n\nRun Text to Speech inference\n\n```bash\npython3 python-clients/scripts/tts/talk.py --server 0.0.0.0:50051 --text \"Hello, this is a speech synthesizer.\" --language-code en-US --output output.wav\n```\n\nOn running the above command, the synthesized audio file named output.wav will be created.\n\n\nFor more details on getting started with this NIM, visit the [NVIDIA NIM Docs](https://docs.nvidia.com/nim/riva/tts/latest/overview.html).\n"])</script><script>self.__next_f.push([1,"a8:T84c,"])</script><script>self.__next_f.push([1,"### Getting Started\n\nRiva uses \u003ca href=\"https://grpc.io/\"\u003egRPC\u003c/a\u003e APIs. Instructions below demonstrate usage of \u003c%- name %\u003e model using Python gRPC client.\n\n### Prerequisites\n\nYou will need a system with Git and Python 3+ installed.\n\n### Install Riva Python Client\n\n```bash\n$ pip install -r https://raw.githubusercontent.com/nvidia-riva/python-clients/main/requirements.txt\n$ pip install --force-reinstall git+https://github.com/nvidia-riva/python-clients.git\n```\n\n### Download Python Client\n\nDownload Python client code by cloning \u003ca href=\"https://github.com/nvidia-riva/python-clients\"\u003ePython Client Repository\u003c/a\u003e.\n\n```bash\n$ git clone https://github.com/nvidia-riva/python-clients.git\n```\n\n### Run Python Client\n\nOpen a command terminal and execute below command to synthesize audio from the example text. If you have generated the API key, it will be auto-populated in the command.\n\n```bash\n$ python python-clients/scripts/tts/talk.py \\\n --server grpc.nvcf.nvidia.com:443 --use-ssl \\\n --metadata function-id \"\u003c%- nvcfFunctionId %\u003e\" \\\n --metadata authorization \"Bearer \u003c%- apiKey %\u003e\" \\\n --text \"this audio is generated from nvidia's text-to-speech model\" \\\n --voice \"English-US.Female-1\" \\\n --output audio.wav\n```\n\nList of available voices can be obtained using below command.\n\n```bash\n$ python python-clients/scripts/tts/talk.py \\\n --server grpc.nvcf.nvidia.com:443 --use-ssl \\\n --metadata function-id \"\u003c%- nvcfFunctionId %\u003e\" \\\n --metadata authorization \"Bearer \u003c%- apiKey %\u003e\" \\\n --list-voices\n```\n\n### Support for gRPC clients in other languages\n\nRiva uses \u003ca href=\"https://grpc.io/\"\u003egRPC\u003c/a\u003e APIs. Proto files can be downloaded from \u003ca href=\"https://github.com/nvidia-riva/common/archive/refs/heads/main.zip\"\u003eRiva gRPC Proto files\u003c/a\u003e and compiled to target language using \u003ca href=\"https://grpc.io/docs/protoc-installation/\"\u003eProtoc compiler\u003c/a\u003e. Example Riva clients in C++ and Python languages are provided below.\n\n* \u003ca href=\"https://github.com/nvidia-riva/python-clients\"\u003ePython Client Repository\u003c/a\u003e\n* \u003ca href=\"https://github.com/nvidia-riva/cpp-clients\"\u003eC++ Client Repository\u003c/a\u003e\n"])</script><script>self.__next_f.push([1,"a9:T81f,"])</script><script>self.__next_f.push([1,"Field | Response\n:----------------------------------------------------------------------------------------------------------------------------------|:-----------------------------------------------\nGeneratable or reverse engineerable personally-identifiable information (PII)? | None\nWas consent obtained for any PII used? | Yes\nProtected class data used to create this model? | Age, Gender, Linguistic Background, National Origin\nHow often is dataset reviewed? | Before Release\nIs a mechanism in place to honor data subject right of access or deletion of personal data? | No\nIf PII collected for the development of the model, was it collected directly by NVIDIA? | PII not collected by NVIDIA for development of model\nIf PII collected for the development of the model by NVIDIA, do you maintain or have access to disclosures made to data subjects? | Not applicable\nIf PII collected for the development of this AI model, was it minimized to only what was required? | Yes\nIs there provenance for all datasets used in training? | Yes\nDoes data labeling (annotation, metadata) comply with privacy laws? | Yes \nIs data compliant with data subject requests for data correction or removal, if such a request was made? | The data is compliant where applicable, but is not applicable for all data."])</script><script>self.__next_f.push([1,"aa:Tbf9,"])</script><script>self.__next_f.push([1,"## Model Overview\n\nParakeet is a major step forward in the evolution of conversational AI. Its exceptional accuracy, coupled with the flexibility and ease of use offered by NeMo, empowers developers to create more natural and intuitive voice-powered applications. The possibilities are endless, from enhancing the accuracy of virtual assistants to enabling seamless real-time communication.\n\n### Description\n\nParakeet transcribes audio into text, using spaces and apostrophes where needed \u003cbr\u003e\n\n### Terms of use\n\nBy using this software or microservice, you are agreeing to the [terms and conditions](https://www.nvidia.com/en-us/data-center/products/nvidia-ai-enterprise/eula/) of the license and acceptable use policy.\n\n## Disclaimer\n\nAI models generate responses and outputs based on complex algorithms and machine learning techniques, and those responses or outputs may be inaccurate or indecent. By testing this model, you assume the risk of any harm caused by any response or output of the model. Please do not upload any confidential information or personal data. Your use is logged for security.\n\n## References\n\n* [Fast Conformer](https://docs.nvidia.com/deeplearning/nemo/user-guide/docs/en/main/asr/models.html#fast-conformer)\n\n### Model Architecture\n\n**Architecture Type:** Convolutional Neural Network + Transformer \u003cbr\u003e\n**Network Architecture:** Fast Conformer Encoder with CTC Decoder \u003cbr\u003e\n\n### Input\n\n**Input Type(s):** Audio in English \u003cbr\u003e\n**Input Format(s):** Linear PCM 16-bit 1 channel \u003cbr\u003e\n\n### Output\n\n**Output Type(s):** Text String in English with Timestamps \u003cbr\u003e\n\n### Software Integration\n\n**Runtime Engine(s):**\n* Riva 2.15.0 or Higher \u003cbr\u003e\n\n**Supported Operating System(s):** \u003cbr\u003e\n* Linux \u003cbr\u003e\n\n### Model Version\n\nParakeet-1.1b-ctc-en-us-asr-set-6.0 \u003cbr\u003e\n\n## Inference\n\n**Engine:** Triton \u003cbr\u003e\n**Test Hardware:** \u003cbr\u003e\n* NVIDIA H100 GPU\n* NVIDIA A100 GPU\n* NVIDIA L40 GPU\n\n### Ethical Considerations (For NVIDIA Models Only):\n\nNVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their internal model team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse. For more detailed information on ethical considerations for this model, please see the Model Card++ Explainability, Bias, Safety \u0026 Security, and Privacy Subcards. Please report security vulnerabilities or NVIDIA AI Concerns [here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/).\n\n### GOVERNING TERMS:\n\nThis trial is governed by the NVIDIA API Trial Terms of Service (found at https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf). The use of this model is governed by the AI Foundation Models Community License Agreement (found at NVIDIA Agreements | Enterprise Software | NVIDIA AI Foundation Models Community License Agreement).\n"])</script><script>self.__next_f.push([1,"ab:T917,"])</script><script>self.__next_f.push([1,"Field | Response\n:------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------\nIntended Applications \u0026 Domains: | Speech Transcription\nTypes: | Speech Transcription\nIntended Users: | Data Scientists in Contact Center Transcription, Video Conferencing Transcription, Virtual Assistants, etc\nOutput: | Transcribed text with timestamps and confidence scores\nDescribe how the model works: | Model transcribes audio input into text for the input language\nName the adversely impacted groups this has been tested to deliver comparable outcomes regardless of: | Age, Gender, National Origin\nTechnical Limitations: | Transcripts may not be 100% accurate. Accuracy varies based on the characteristics of input audio (Domain, Use Case, Accent, Noise, Speech Type, Context of speech, etc.)\nVerified to have met prescribed NVIDIA quality standards: | Yes\nPerformance Metrics: | Word Error Rate (WER), Silence Robustness (Characters/mins of silent audio), Latency (in milliseconds), Throughput (Total audio processed per unit of time)\nPotential Known Risks: | Not recommended for word-for-word transcription as accuracy varies based on the characteristics of input audio (domain, use case, accent, noise, speech type, and context of speech)\nLicensing: | https://developer.nvidia.com/riva/ga/license"])</script><script>self.__next_f.push([1,"ac:T857,"])</script><script>self.__next_f.push([1,"Pull and run the NVIDIA NIM with the command below. \n\nThis command launches NIM container with the generic (non-optimized) model on any of the supported GPUs. GPU specific optimized models are available for select GPUs. For using optimized models, refer the [Supported Models](https://docs.nvidia.com/nim/riva/asr/latest/getting-started.html#supported-models) and specify NIM_MANIFEST_PROFILE according to your GPU in the Docker run command below.\n\n```bash\nexport NGC_API_KEY=\u003cPASTE_API_KEY_HERE\u003e\n\nexport CONTAINER_NAME=parakeet-ctc-1.1b-asr\ndocker run -it --rm --name=$CONTAINER_NAME \\\n --runtime=nvidia \\\n --gpus '\"device=0\"' \\\n --shm-size=8GB \\\n -e NGC_API_KEY=$NGC_API_KEY \\\n -e NIM_MANIFEST_PROFILE=9136dd64-4777-11ef-9f27-37cfd56fa6ee \\\n -e NIM_HTTP_API_PORT=9000 \\\n -e NIM_GRPC_API_PORT=50051 \\\n -p 9000:9000 \\\n -p 50051:50051 \\\n nvcr.io/nim/nvidia/parakeet-ctc-1.1b-asr:1.0.0\n```\n\n```{note}\nIt may take a up to 30 minutes depending on your network speed, for the container to be ready and start accepting requests from the time the docker container is started.\n```\n\nOpen a new terminal and run following command to check if the service is ready to handle inference requests\n\n```bash\ncurl -X 'GET' 'http://localhost:9000/v1/health/ready'\n```\n\nIf the service is ready, you get a response similar to the following.\n```bash\n{\"ready\":true}\n```\n\nInstall the Riva Python client package\n\n```bash\nsudo apt-get install python3-pip\npip install -r https://raw.githubusercontent.com/nvidia-riva/python-clients/main/requirements.txt\npip install --force-reinstall git+https://github.com/nvidia-riva/python-clients.git\n```\n\nDownload Riva sample clients\n\n```bash\ngit clone https://github.com/nvidia-riva/python-clients.git\n```\n\nRun Speech to Text inference in streaming modes. Riva ASR supports Mono, 16-bit audio in WAV, OPUS and FLAC formats.\n\n```bash\npython3 python-clients/scripts/asr/transcribe_file.py --server 0.0.0.0:50051 --input-file \u003cpath_to_speech_file\u003e --language-code en-US\n```\n\n\nFor more details on getting started with this NIM, visit the [NVIDIA NIM Docs](https://docs.nvidia.com/nim/riva/asr/latest/overview.html).\n"])</script><script>self.__next_f.push([1,"ad:T727,### Getting Started\n\nRiva uses \u003ca href=\"https://grpc.io/\"\u003egRPC\u003c/a\u003e APIs. Instructions below demonstrate usage of \u003c%- name %\u003e model using Python gRPC client.\n\n### Prerequisites\n\nYou will need a system with Git and Python 3+ installed.\n\n### Install Riva Python Client\n\n```bash\n$ pip install -r https://raw.githubusercontent.com/nvidia-riva/python-clients/main/requirements.txt\n$ pip install --force-reinstall git+https://github.com/nvidia-riva/python-clients.git\n```\n\n### Download Python Client\n\nDownload Python client code by cloning \u003ca href=\"https://github.com/nvidia-riva/python-clients\"\u003ePython Client Repository\u003c/a\u003e.\n\n```bash\n$ git clone https://github.com/nvidia-riva/python-clients.git\n```\n\n### Run Python Client\n\nOpen a command terminal and execute below command to transcribe audio. Make sure you have a speech file in 16-bit Mono format in WAV/OGG/OPUS container. If you have generated the API key, it will be auto-populated in the command.\n\n```bash\n$ python python-clients/scripts/asr/transcribe_file.py \\\n --server grpc.nvcf.nvidia.com:443 --use-ssl \\\n --metadata function-id \"\u003c%- nvcfFunctionId %\u003e\" \\\n --metadata \"authorization\" \"Bearer \u003c%- apiKey %\u003e\" \\\n --language-code en-US \\\n --input-file \u003cpath_to_audio_file\u003e\n```\n\n### Support for gRPC clients in other languages\n\nRiva uses \u003ca href=\"https://grpc.io/\"\u003egRPC\u003c/a\u003e APIs. Proto files can be downloaded from \u003ca href=\"https://github.com/nvidia-riva/common/archive/refs/heads/main.zip\"\u003eRiva gRPC Proto files\u003c/a\u003e and compiled to target language using \u003ca href=\"https://grpc.io/docs/protoc-installation/\"\u003eProtoc compiler\u003c/a\u003e. Example Riva clients in C++ and Python languages are provided below.\n\n* \u003ca href=\"https://github.com/nvidia-riva/python-clients\"\u003ePython Client Repository\u003c/a\u003e\n* \u003ca href=\"https://github.com/nvidia-riva/cpp-clients\"\u003eC++ Client Repository\u003c/a\u003e\n"])</script><script>self.__next_f.push([1,"73:[\"$\",\"$L3c\",null,{\"data\":[{\"endpoint\":{\"requestStatus\":{\"statusCode\":\"SUCCESS\",\"requestId\":\"0ce7a0ee-86b4-49df-84c7-9cb78180eedf\"},\"artifact\":{\"orgName\":\"qc69jvmznzxy\",\"labels\":[\"Synthetic data generation\",\"chat\",\"Code Generation\"],\"logo\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/llama-3_1-405b-instruct.jpg\",\"shortDescription\":\"Advanced LLM for synthetic data generation, distillation, and inference for chatbots, coding, and domain-specific tasks.\",\"isReadOnly\":true,\"description\":\"$74\",\"canGuestDownload\":true,\"isPublic\":true,\"createdDate\":\"2024-07-23T14:58:23.459Z\",\"publisher\":\"meta\",\"displayName\":\"llama-3.1-405b-instruct\",\"name\":\"llama-3_1-405b-instruct\",\"updatedDate\":\"2024-11-20T03:12:22.964Z\",\"attributes\":[{\"key\":\"AVAILABLE\",\"value\":\"true\"},{\"key\":\"PREVIEW\",\"value\":\"false\"}],\"artifactType\":\"ENDPOINT\"}},\"spec\":{\"openAPISpec\":{\"openapi\":\"3.1.0\",\"info\":{\"title\":\"NVIDIA NIM API for meta/llama-3.1-405b-instruct\",\"description\":\"The NVIDIA NIM REST API. 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See https://platform.openai.com/docs/api-reference/chat/create\",\"requestBody\":{\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ChatRequest\"}}},\"required\":true},\"responses\":{\"200\":{\"description\":\"Invocation is fulfilled\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ChatCompletion\"}},\"text/event-stream\":{\"schema\":{\"$ref\":\"#/components/schemas/ChatCompletionChunk\"}}}},\"202\":{\"description\":\"Result is pending. Client should poll using the requestId.\\n\",\"content\":{\"application/json\":{\"example\":{},\"schema\":{}}},\"headers\":{\"NVCF-REQID\":{\"description\":\"requestId required for pooling\",\"schema\":{\"type\":\"string\",\"format\":\"uuid\"}},\"NVCF-STATUS\":{\"description\":\"Invocation status\",\"schema\":{\"type\":\"string\"}}}},\"422\":{\"description\":\"Validation failed, provided entity could not be processed.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/Errors\"},\"example\":{\"type\":\"urn:nvcf-worker-service:problem-details:unprocessable-entity\",\"title\":\"Unprocessable Entity\",\"status\":422,\"detail\":\"string\",\"instance\":\"/v2/nvcf/pexec/functions/4a58c6cb-a9b4-4014-99de-3e704d4ae687\",\"requestId\":\"3fa85f64-5717-4562-b3fc-2c963f66afa6\"}}}},\"500\":{\"description\":\"The invocation ended with an error.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/Errors\"},\"example\":{\"type\":\"urn:nvcf-worker-service:problem-details:internal-server-error\",\"title\":\"Internal Server Error\",\"status\":500,\"detail\":\"string\",\"instance\":\"/v2/nvcf/pexec/functions/4a58c6cb-a9b4-4014-99de-3e704d4ae687\",\"requestId\":\"3fa85f64-5717-4562-b3fc-2c963f66afa6\"}}}}},\"x-nvai-meta\":{\"name\":\"Create chat completion\",\"returns\":\"Returns a [chat completion](/docs/api-reference/chat/object) object, or a streamed sequence of [chat completion chunk](/docs/api-reference/chat/streaming) objects if the request is streamed.\\n\",\"path\":\"create\",\"examples\":[{\"name\":\"Write a limerick about the wonders of GPU computing.\",\"requestJson\":\"{\\n \\\"model\\\": \\\"meta/llama-3.1-405b-instruct\\\",\\n \\\"messages\\\": [\\n {\\n \\\"role\\\": \\\"user\\\",\\n \\\"content\\\": \\\"Write a limerick about the wonders of GPU computing.\\\"\\n }\\n ],\\n \\\"top_p\\\": 0.7,\\n \\\"max_tokens\\\": 1024,\\n \\\"seed\\\": 42,\\n \\\"stream\\\": true\\n}\\n\",\"responseJson\":\"{\\n \\\"id\\\": \\\"id-123\\\",\\n \\\"object\\\": \\\"chat.completion\\\",\\n \\\"created\\\": 1677652288,\\n \\\"model\\\": \\\"meta/llama-3.1-405b-instruct\\\",\\n \\\"system_fingerprint\\\": \\\"fp_44709d6fcb\\\",\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"The python functions...\\\"\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 9,\\n \\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"},{\"name\":\"Tell me about Dumbledore.\",\"requestJson\":\"$75\",\"responseJson\":\"{\\n \\\"id\\\": \\\"id-123\\\",\\n \\\"object\\\": \\\"chat.completion\\\",\\n \\\"created\\\": 1677652288,\\n \\\"model\\\": \\\"meta/llama-3.1-405b-instruct\\\",\\n \\\"system_fingerprint\\\": \\\"fp_44709d6fcb\\\",\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"At NVIDIA's GPU Technology Conference (GTC)...\\\"\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 9,\\n \\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"},{\"name\":\"What is the weather in Santa Clara, CA?\",\"requestJson\":\"$76\",\"responseJson\":\"{\\n \\\"id\\\": \\\"id-123\\\",\\n \\\"object\\\": \\\"chat.completion\\\",\\n \\\"created\\\": 1677652288,\\n \\\"model\\\": \\\"meta/llama-3.1-405b-instruct\\\",\\n \\\"system_fingerprint\\\": \\\"fp_44709d6fcb\\\",\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"At NVIDIA's GPU Technology Conference (GTC)...\\\"\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 9,\\n \\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"}],\"templates\":[{\"title\":\"No Streaming\",\"requestEjs\":{\"python\":\"$77\",\"langChain\":\"from langchain_nvidia_ai_endpoints import ChatNVIDIA\\n\\nclient = ChatNVIDIA(\\n model=\\\"\u003c%- request.model %\u003e\\\",\\n api_key=\\\"$NVIDIA_API_KEY\\\", \\n temperature=\u003c%- request.temperature %\u003e,\\n top_p=\u003c%- request.top_p %\u003e,\\n max_tokens=\u003c%- request.max_tokens %\u003e,\\n)\\n\u003c% if (request.stream) { %\u003e\\nfor chunk in client.stream(\u003c%- JSON.stringify(request.messages) %\u003e): \\n print(chunk.content, end=\\\"\\\")\\n\u003c% } else { %\u003e\\nresponse = client.invoke(\u003c%- JSON.stringify(request.messages) %\u003e)\\nprint(response.content)\\n\u003c% } %\u003e\\n \\n\",\"node.js\":\"$78\",\"curl\":\"$79\"},\"response\":\"{\\n \\\"id\\\": \\\"chatcmpl-123\\\",\\n \\\"object\\\": \\\"chat.completion\\\",\\n \\\"created\\\": 1677652288,\\n \\\"model\\\": \\\"meta/llama-3.1-405b-instruct\\\",\\n \\\"system_fingerprint\\\": \\\"fp_44709d6fcb\\\",\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"\\\\n\\\\nHello there, how may I assist you today?\\\",\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 9,\\n \\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"}]}}}},\"security\":[{\"Token\":[]}],\"components\":{\"securitySchemes\":{\"Token\":{\"type\":\"http\",\"scheme\":\"bearer\"}},\"schemas\":{\"Errors\":{\"properties\":{\"type\":{\"type\":\"string\",\"description\":\"Error type\"},\"title\":{\"type\":\"string\",\"description\":\"Error title\"},\"status\":{\"type\":\"integer\",\"description\":\"Error status code\"},\"detail\":{\"type\":\"string\",\"description\":\"Detailed information about the error\"},\"instance\":{\"type\":\"string\",\"description\":\"Function instance used to invoke the request\"},\"requestId\":{\"type\":\"string\",\"format\":\"uuid\",\"description\":\"UUID of the request\"}},\"type\":\"object\",\"required\":[\"type\",\"title\",\"status\",\"detail\",\"instance\",\"requestId\"],\"title\":\"InvokeError\"},\"ChatCompletion\":{\"properties\":{\"id\":{\"description\":\"A unique identifier for the completion.\",\"format\":\"uuid\",\"title\":\"Id\",\"type\":\"string\"},\"choices\":{\"description\":\"The list of completion choices the model generated for the input prompt.\",\"items\":{\"$ref\":\"#/components/schemas/Choice\"},\"title\":\"Choices\",\"type\":\"array\"},\"usage\":{\"allOf\":[{\"$ref\":\"#/components/schemas/Usage\"}],\"description\":\"Usage statistics for the completion request.\"}},\"required\":[\"id\",\"choices\",\"usage\"],\"title\":\"ChatCompletion\",\"type\":\"object\"},\"ChatCompletionChunk\":{\"properties\":{\"id\":{\"description\":\"A unique identifier for the completion.\",\"format\":\"uuid\",\"title\":\"Id\",\"type\":\"string\"},\"choices\":{\"description\":\"The list of completion choices the model generated for the input prompt.\",\"items\":{\"$ref\":\"#/components/schemas/ChoiceChunk\"},\"title\":\"Choices\",\"type\":\"array\"}},\"required\":[\"id\",\"choices\"],\"title\":\"ChatCompletionChunk\",\"type\":\"object\"},\"ChatRequest\":{\"additionalProperties\":false,\"properties\":{\"model\":{\"type\":\"string\",\"title\":\"Model\",\"default\":\"meta/llama-3.1-405b-instruct\"},\"messages\":{\"description\":\"A list of messages comprising the conversation so far. The roles of the messages must be alternating between `user` and `assistant`. The last input message should have role `user`. A message with the the `system` role is optional, and must be the very first message if it is present; `context` is also optional, but must come before a user question.\",\"examples\":[[{\"content\":\"I am going to Paris, what should I see?\",\"role\":\"user\"}]],\"items\":{\"$ref\":\"#/components/schemas/Message\"},\"title\":\"Messages\",\"type\":\"array\"},\"temperature\":{\"default\":0.2,\"description\":\"The sampling temperature to use for text generation. The higher the temperature value is, the less deterministic the output text will be. It is not recommended to modify both temperature and top_p in the same call.\",\"maximum\":1,\"minimum\":0,\"title\":\"Temperature\",\"type\":\"number\"},\"top_p\":{\"default\":0.7,\"description\":\"The top-p sampling mass used for text generation. The top-p value determines the probability mass that is sampled at sampling time. For example, if top_p = 0.2, only the most likely tokens (summing to 0.2 cumulative probability) will be sampled. It is not recommended to modify both temperature and top_p in the same call.\",\"maximum\":1,\"exclusiveMinimum\":0,\"title\":\"Top P\",\"type\":\"number\"},\"tools\":{\"anyOf\":[{\"items\":{\"$ref\":\"#/components/schemas/ChatCompletionToolsParam\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Tools\"},\"frequency_penalty\":{\"type\":\"number\",\"maximum\":2,\"minimum\":-2,\"default\":0,\"title\":\"Frequency Penalty\",\"description\":\"Indicates how much to penalize new tokens based on their existing frequency in the text so far, decreasing model likelihood to repeat the same line verbatim.\"},\"presence_penalty\":{\"type\":\"number\",\"maximum\":2,\"minimum\":-2,\"default\":0,\"title\":\"Presence Penalty\",\"description\":\"Positive values penalize new tokens based on whether they appear in the text so far, increasing model likelihood to talk about new topics.\"},\"max_tokens\":{\"default\":1024,\"description\":\"The maximum number of tokens to generate in any given call. Note that the model is not aware of this value, and generation will simply stop at the number of tokens specified.\",\"maximum\":4096,\"minimum\":1,\"title\":\"Max Tokens\",\"type\":\"integer\"},\"stream\":{\"default\":false,\"description\":\"If set, partial message deltas will be sent. Tokens will be sent as data-only server-sent events (SSE) as they become available (JSON responses are prefixed by `data: `), with the stream terminated by a `data: [DONE]` message.\",\"title\":\"Stream\",\"type\":\"boolean\"},\"stop\":{\"anyOf\":[{\"items\":{\"type\":\"string\"},\"type\":\"array\"},{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Stop\",\"description\":\"A string or a list of strings where the API will stop generating further tokens. The returned text will not contain the stop sequence.\"}},\"required\":[\"messages\"],\"title\":\"ChatRequest\",\"type\":\"object\"},\"Choice\":{\"properties\":{\"index\":{\"description\":\"The index of the choice in the list of choices (always 0).\",\"title\":\"Index\",\"type\":\"integer\"},\"message\":{\"allOf\":[{\"$ref\":\"#/components/schemas/Message\"}],\"description\":\"A chat completion message generated by the model.\",\"examples\":[{\"content\":\"Ah, Paris, the City of Light! There are so many amazing things to see and do in this beautiful city ...\",\"role\":\"assistant\"}]},\"finish_reason\":{\"anyOf\":[{\"enum\":[\"stop\",\"length\",\"tool_calls\"],\"type\":\"string\"},{\"type\":\"null\"}],\"default\":null,\"description\":\"The reason the model stopped generating tokens. This will be `stop` if the model hit a natural stop point or a provided stop sequence, or `length` if the maximum number of tokens specified in the request was reached.\",\"examples\":[\"stop\"],\"title\":\"Finish Reason\"}},\"required\":[\"index\",\"message\"],\"title\":\"Choice\",\"type\":\"object\"},\"ChoiceChunk\":{\"properties\":{\"index\":{\"description\":\"The index of the choice in the list of choices (always 0).\",\"title\":\"Index\",\"type\":\"integer\"},\"delta\":{\"allOf\":[{\"$ref\":\"#/components/schemas/Message\"}],\"description\":\"A chat completion delta generated by streamed model responses.\",\"examples\":[{\"content\":\"Ah,\",\"role\":\"assistant\"}]},\"finish_reason\":{\"anyOf\":[{\"enum\":[\"stop\",\"length\",\"tool_calls\"],\"type\":\"string\"},{\"type\":\"null\"}],\"default\":null,\"description\":\"The reason the model stopped generating tokens. This will be `stop` if the model hit a natural stop point or a provided stop sequence, or `length` if the maximum number of tokens specified in the request was reached. Will be `null` if the model has not finished generating.\",\"title\":\"Finish Reason\"}},\"required\":[\"index\",\"delta\"],\"title\":\"ChoiceChunk\",\"type\":\"object\"},\"Message\":{\"additionalProperties\":false,\"properties\":{\"role\":{\"description\":\"The role of the message author.\",\"enum\":[\"system\",\"context\",\"user\",\"assistant\",\"tool\"],\"title\":\"Role\",\"type\":\"string\"},\"content\":{\"description\":\"The contents of the message.\",\"title\":\"Content\",\"anyOf\":[{\"type\":\"string\"},{\"type\":\"null\"}]},\"tool_call_id\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Tool Call Id\",\"description\":\"The id of the tool call.\"},\"tool_calls\":{\"anyOf\":[{\"items\":{\"$ref\":\"#/components/schemas/ToolCall\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Tool Calls\",\"description\":\"The tool(s) called by the model.\"}},\"required\":[\"role\",\"content\"],\"title\":\"Message\",\"type\":\"object\"},\"ToolCall\":{\"properties\":{\"id\":{\"type\":\"string\",\"title\":\"Id\"},\"type\":{\"type\":\"string\",\"enum\":[\"function\"],\"const\":\"function\",\"title\":\"Type\",\"default\":\"function\"},\"function\":{\"$ref\":\"#/components/schemas/FunctionCall\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"function\"],\"title\":\"ToolCall\"},\"FunctionCall\":{\"properties\":{\"name\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Name\"},\"arguments\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Arguments\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"name\",\"arguments\"],\"title\":\"FunctionCall\"},\"ChatCompletionToolsParam\":{\"properties\":{\"type\":{\"type\":\"string\",\"enum\":[\"function\"],\"const\":\"function\",\"title\":\"Type\",\"default\":\"function\"},\"function\":{\"$ref\":\"#/components/schemas/FunctionDefinition\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"function\"],\"title\":\"ChatCompletionToolsParam\"},\"ChatCompletionNamedFunction\":{\"properties\":{\"name\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Name\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"name\"],\"title\":\"ChatCompletionNamedFunction\"},\"ChatCompletionNamedToolChoiceParam\":{\"properties\":{\"function\":{\"$ref\":\"#/components/schemas/ChatCompletionNamedFunction\"},\"type\":{\"type\":\"string\",\"enum\":[\"function\"],\"const\":\"function\",\"title\":\"Type\",\"default\":\"function\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"function\"],\"title\":\"ChatCompletionNamedToolChoiceParam\"},\"FunctionDefinition\":{\"properties\":{\"name\":{\"type\":\"string\",\"title\":\"Name\"},\"description\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Description\"},\"parameters\":{\"anyOf\":[{\"type\":\"object\"},{\"type\":\"null\"}],\"title\":\"Parameters\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"name\"],\"title\":\"FunctionDefinition\"},\"Usage\":{\"properties\":{\"completion_tokens\":{\"description\":\"Number of tokens in the generated completion.\",\"examples\":[25],\"title\":\"Completion Tokens\",\"type\":\"integer\"},\"prompt_tokens\":{\"description\":\"Number of tokens in the prompt.\",\"examples\":[9],\"title\":\"Prompt Tokens\",\"type\":\"integer\"},\"total_tokens\":{\"description\":\"Total number of tokens used in the request (prompt + completion).\",\"examples\":[34],\"title\":\"Total Tokens\",\"type\":\"integer\"}},\"required\":[\"completion_tokens\",\"prompt_tokens\",\"total_tokens\"],\"title\":\"Usage\",\"type\":\"object\"}}}},\"namespace\":\"qc69jvmznzxy\",\"updatedDate\":\"2024-11-20T03:12:23.673Z\",\"nvcfFunctionId\":\"0de0002c-98f6-422d-8bfc-2716e52f99d2\",\"createdDate\":\"2024-07-23T14:58:23.731Z\",\"attributes\":{\"dockerRun\":\"Pull and run the NVIDIA NIM with the command below. This will download the optimized model for your infrastructure.\\n```bash\\nexport NGC_API_KEY=\u003cPASTE_API_KEY_HERE\u003e\\nexport LOCAL_NIM_CACHE=~/.cache/nim\\nmkdir -p \\\"$LOCAL_NIM_CACHE\\\"\\ndocker run -it --rm \\\\\\n --gpus all \\\\\\n --shm-size=16GB \\\\\\n -e NGC_API_KEY \\\\\\n -v \\\"$LOCAL_NIM_CACHE:/opt/nim/.cache\\\" \\\\\\n -u $(id -u) \\\\\\n -p 8000:8000 \\\\\\n nvcr.io/nim/meta/llama-3.1-405b-instruct:1.1.2\\n```\\n\\nYou can now make a local API call using this curl command:\\n```bash\\ncurl -X 'POST' \\\\\\n'http://0.0.0.0:8000/v1/chat/completions' \\\\\\n-H 'accept: application/json' \\\\\\n-H 'Content-Type: application/json' \\\\\\n-d '{\\n \\\"model\\\": \\\"meta/llama-3.1-405b-instruct\\\",\\n \\\"messages\\\": [{\\\"role\\\":\\\"user\\\", \\\"content\\\":\\\"Write a limerick about the wonders of GPU computing.\\\"}],\\n \\\"max_tokens\\\": 64\\n}'\\n```\\n\\nFor more details on getting started with this NIM, visit the [NVIDIA NIM Docs](https://docs.nvidia.com/nim/large-language-models/latest/getting-started.html).\\n\",\"dockerTermsOfUse\":\"By running the below commands, you accept the \u003ca href=\\\"https://www.nvidia.com/en-us/data-center/products/nvidia-ai-enterprise/eula/\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA AI Enterprise Terms of Use\u003c/a\u003e and the \u003ca href=\\\"https://docs.nvidia.com/ai-foundation-models-community-license.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA Community Models License\u003c/a\u003e.\\n\",\"showUnavailableBanner\":false,\"apiDocsUrl\":\"https://docs.api.nvidia.com/nim/reference/meta-llama-3_1-405b\",\"playground\":{\"type\":\"chatWithTools\"},\"termsOfUse\":\"\u003cb\u003eGOVERNING TERMS\u003c/b\u003e: This trial service is governed by the \u003ca href=\\\"https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA API Trial Terms of Service\u003c/a\u003e. Use of this model is governed by the \u003ca href=\\\"https://docs.nvidia.com/ai-foundation-models-community-license.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003e AI Foundation Models Community License Agreement \u003c/a\u003e. ADDITIONAL INFORMATION: Llama 3.1 Community License Agreement, Built with Llama.\\n\",\"cta\":{\"text\":\"Apply to Self-Host\",\"url\":\"https://www.nvidia.com/en-us/ai/nim-notifyme/\",\"nim_available_override_url\":\"https://catalog.ngc.nvidia.com/orgs/nim/teams/meta/containers/llama-3.1-405b-instruct\"},\"projects\":[{\"name\":\"Build a Customizable Hybrid RAG Chatbot\",\"url\":\"https://github.com/NVIDIA/workbench-example-hybrid-rag\",\"imageUrl\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/nv-workbench.jpg\",\"workbench\":true}]},\"artifactName\":\"llama-3_1-405b-instruct\"},\"config\":{\"name\":\"llama-3_1-405b-instruct\",\"type\":\"model\"}},{\"endpoint\":{\"requestStatus\":{\"statusCode\":\"SUCCESS\",\"requestId\":\"0c32812b-c972-409f-a45a-125bade1901d\"},\"artifact\":{\"orgName\":\"qc69jvmznzxy\",\"labels\":[\"Advanced Reasoning\",\"Chat\",\"Large Language Models\",\"Text-to-Text\",\"Code Generation\"],\"logo\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/mixtral-8x7b-instruct.jpg\",\"shortDescription\":\"An MOE LLM that follows instructions, completes requests, and generates creative text.\",\"isReadOnly\":true,\"description\":\"$7a\",\"canGuestDownload\":true,\"isPublic\":true,\"createdDate\":\"2024-03-15T04:09:28.642Z\",\"publisher\":\"mistralai\",\"displayName\":\"mixtral-8x7b-instruct-v0.1\",\"name\":\"mixtral-8x7b-instruct\",\"updatedDate\":\"2024-11-18T22:30:56.877Z\",\"attributes\":[{\"key\":\"AVAILABLE\",\"value\":\"true\"},{\"key\":\"PREVIEW\",\"value\":\"false\"}],\"artifactType\":\"ENDPOINT\"}},\"spec\":{\"openAPISpec\":{\"openapi\":\"3.1.0\",\"info\":{\"title\":\"NVIDIA NIM API for mistralai/mixtral-8x7b-instruct-v0.1\",\"description\":\"The NVIDIA NIM REST API. Please see https://docs.api.nvidia.com/nim/reference/mistralai-mixtral-8x7b-instruct for more details.\",\"version\":\"1.0.0\",\"termsOfService\":\"https://www.nvidia.com/en-us/data-center/products/nvidia-ai-enterprise/eula/\",\"contact\":{\"name\":\"NVIDIA Enterprise Support\",\"url\":\"https://www.nvidia.com/en-us/support/enterprise/\"},\"license\":{\"name\":\"Apache 2.0\",\"url\":\"https://mistral.ai/terms-of-service/\"}},\"servers\":[{\"url\":\"https://integrate.api.nvidia.com/v1/\"}],\"paths\":{\"/chat/completions\":{\"post\":{\"operationId\":\"create_chat_completion_v1_chat_completions_post\",\"tags\":[\"Chat\"],\"summary\":\"Creates a model response for the given chat conversation.\",\"description\":\"Given a list of messages comprising a conversation, the model will return a response. Compatible with OpenAI. See https://platform.openai.com/docs/api-reference/chat/create\",\"requestBody\":{\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ChatCompletionRequest\"}}},\"required\":true},\"responses\":{\"200\":{\"description\":\"Successful Response\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ChatCompletionResponse\"}}}},\"402\":{\"description\":\"Payment Required\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/PaymentRequiredError\"}}}},\"422\":{\"description\":\"Validation Error\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/HTTPValidationError\"}}}}},\"x-nvai-meta\":{\"name\":\"Create chat completion\",\"returns\":\"Returns a [chat completion](/docs/api-reference/chat/object) object, or a streamed sequence of [chat completion chunk](/docs/api-reference/chat/streaming) objects if the request is streamed.\\n\",\"path\":\"create\",\"examples\":[{\"name\":\"Write a limerick about the wonders of GPU computing.\",\"requestJson\":\"{\\n \\\"model\\\": \\\"mistralai/mixtral-8x7b-instruct-v0.1\\\",\\n \\\"messages\\\": [\\n {\\n \\\"role\\\": \\\"system\\\",\\n \\\"content\\\": \\\"You are a helpful assistant.\\\"\\n },\\n {\\n \\\"role\\\": \\\"user\\\",\\n \\\"content\\\": \\\"Write a limerick about the wonders of GPU computing.\\\"\\n }\\n ],\\n \\\"top_p\\\": 0.7,\\n \\\"max_tokens\\\": 1024,\\n \\\"seed\\\": 42,\\n \\\"stop\\\": null,\\n \\\"stream\\\": true\\n}\\n\",\"responseJson\":\"{\\n \\\"id\\\": \\\"id-123\\\",\\n \\\"object\\\": \\\"chat.completion\\\",\\n \\\"created\\\": 1677652288,\\n \\\"model\\\": \\\"mistralai/mixtral-8x7b-instruct-v0.1\\\",\\n \\\"system_fingerprint\\\": \\\"fp_44709d6fcb\\\",\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"Here's a short poem on...\\\"\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 9,\\n \\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"},{\"name\":\"What can I see at NVIDIA's GPU Technology Conference?\",\"requestJson\":\"{\\n \\\"model\\\": \\\"mistralai/mixtral-8x7b-instruct-v0.1\\\",\\n \\\"messages\\\": [\\n {\\n \\\"role\\\": \\\"system\\\",\\n \\\"content\\\": \\\"You are a helpful assistant.\\\"\\n },\\n {\\n \\\"role\\\": \\\"user\\\",\\n \\\"content\\\": \\\"What can I see at NVIDIA's GPU Technology Conference?\\\"\\n }\\n ],\\n \\\"top_p\\\": 0.7,\\n \\\"max_tokens\\\": 1024,\\n \\\"seed\\\": 42,\\n \\\"stop\\\": null,\\n \\\"stream\\\": true\\n}\\n\",\"responseJson\":\"{\\n \\\"id\\\": \\\"id-123\\\",\\n \\\"object\\\": \\\"chat.completion\\\",\\n \\\"created\\\": 1677652288,\\n \\\"model\\\": \\\"mistralai/mixtral-8x7b-instruct-v0.1\\\",\\n \\\"system_fingerprint\\\": \\\"fp_44709d6fcb\\\",\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"At NVIDIA's GTC conference...\\\"\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 9,\\n \\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"}],\"templates\":[{\"title\":\"No Streaming\",\"requestEjs\":{\"python\":\"from openai import OpenAI\\n\\nclient = OpenAI(\\n base_url = \\\"https://integrate.api.nvidia.com/v1\\\",\\n api_key = \\\"$NVIDIA_API_KEY\\\"\\n)\\n\\ncompletion = client.chat.completions.create(\\n model=\\\"\u003c%- request.model %\u003e\\\",\\n messages=\u003c%- JSON.stringify(request.messages) %\u003e,\\n temperature=\u003c%- request.temperature %\u003e,\\n top_p=\u003c%- request.top_p %\u003e,\\n max_tokens=\u003c%- request.max_tokens %\u003e,\\n stream=\u003c%- request.stream?.toString()[0].toUpperCase() + request.stream?.toString().slice(1) %\u003e\\n)\\n\u003c% if (request.stream) { %\u003e\\nfor chunk in completion:\\n if chunk.choices[0].delta.content is not None:\\n print(chunk.choices[0].delta.content, end=\\\"\\\")\\n\u003c% } else { %\u003e\\nprint(completion.choices[0].message)\\n\u003c% } %\u003e\\n\",\"langChain\":\"from langchain_nvidia_ai_endpoints import ChatNVIDIA\\n\\nclient = ChatNVIDIA(\\n model=\\\"\u003c%- request.model %\u003e\\\",\\n api_key=\\\"$NVIDIA_API_KEY\\\", \\n temperature=\u003c%- request.temperature %\u003e,\\n top_p=\u003c%- request.top_p %\u003e,\\n max_tokens=\u003c%- request.max_tokens %\u003e,\\n)\\n\u003c% if (request.stream) { %\u003e\\nfor chunk in client.stream(\u003c%- JSON.stringify(request.messages) %\u003e): \\n print(chunk.content, end=\\\"\\\")\\n\u003c% } else { %\u003e\\nresponse = client.invoke(\u003c%- JSON.stringify(request.messages) %\u003e)\\nprint(response.content)\\n\u003c% } %\u003e\\n\",\"node.js\":\"import OpenAI from 'openai';\\n\\nconst openai = new OpenAI({\\n apiKey: '$NVIDIA_API_KEY',\\n baseURL: 'https://integrate.api.nvidia.com/v1',\\n})\\n\\nasync function main() {\\n const completion = await openai.chat.completions.create({\\n model: \\\"\u003c%- request.model %\u003e\\\",\\n messages: \u003c%- JSON.stringify(request.messages) %\u003e,\\n temperature: \u003c%- request.temperature %\u003e,\\n top_p: \u003c%- request.top_p %\u003e,\\n max_tokens: \u003c%- request.max_tokens %\u003e,\\n stream: \u003c%- request.stream %\u003e,\\n })\\n \u003c% if (request.stream) { %\u003e\\n for await (const chunk of completion) {\\n process.stdout.write(chunk.choices[0]?.delta?.content || '')\\n }\\n \u003c% } else { %\u003e\\n process.stdout.write(completion.choices[0]?.message?.content);\\n \u003c% } %\u003e\\n}\\n\\nmain();\",\"curl\":\"curl https://integrate.api.nvidia.com/v1/chat/completions \\\\\\n -H \\\"Content-Type: application/json\\\" \\\\\\n -H \\\"Authorization: Bearer $NVIDIA_API_KEY\\\" \\\\\\n -d '{\\n \\\"model\\\": \\\"mistralai/mixtral-8x7b-instruct-v0.1\\\",\\n \\\"messages\\\": \u003c%- JSON.stringify(request.messages).replaceAll(\\\"'\\\", \\\"'\\\\\\\"'\\\\\\\"'\\\") %\u003e,\\n \\\"temperature\\\": \u003c%- request.temperature %\u003e, \\n \\\"top_p\\\": \u003c%- request.top_p %\u003e,\\n \\\"max_tokens\\\": \u003c%- request.max_tokens %\u003e,\\n \\\"stream\\\": \u003c%- request.stream %\u003e \\n }'\\n\"},\"response\":\"{\\n \\\"id\\\": \\\"chatcmpl-123\\\",\\n \\\"object\\\": \\\"chat.completion\\\",\\n \\\"created\\\": 1677652288,\\n \\\"model\\\": \\\"mistralai/mixtral-8x7b-instruct-v0.1\\\",\\n \\\"system_fingerprint\\\": \\\"fp_44709d6fcb\\\",\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"\\\\n\\\\nHello there, how may I assist you today?\\\",\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 9,\\n \\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"}]}}}},\"security\":[{\"Token\":[]}],\"components\":{\"securitySchemes\":{\"Token\":{\"type\":\"http\",\"scheme\":\"bearer\"}},\"schemas\":{\"ChatCompletionRequest\":{\"properties\":{\"model\":{\"type\":\"string\",\"title\":\"Model\",\"default\":\"mistralai/mixtral-8x7b-instruct-v0.1\"},\"max_tokens\":{\"type\":\"integer\",\"minimum\":1,\"title\":\"Max Tokens\",\"description\":\"The maximum number of tokens to generate in any given call. Note that the model is not aware of this value, and generation will simply stop at the number of tokens specified.\",\"default\":1024},\"stream\":{\"type\":\"boolean\",\"title\":\"Stream\",\"description\":\"If set, partial message deltas will be sent. Tokens will be sent as data-only server-sent events (SSE) as they become available (JSON responses are prefixed by `data: `), with the stream terminated by a `data: [DONE]` message.\",\"default\":false},\"temperature\":{\"type\":\"number\",\"maximum\":1,\"minimum\":0,\"title\":\"Temperature\",\"description\":\"The sampling temperature to use for text generation. The higher the temperature value is, the less deterministic the output text will be. It is not recommended to modify both temperature and top_p in the same call.\",\"default\":0.5},\"top_p\":{\"type\":\"number\",\"maximum\":1,\"minimum\":0,\"title\":\"Top P\",\"description\":\"The top-p sampling mass used for text generation. The top-p value determines the probability mass that is sampled at sampling time. For example, if top_p = 0.2, only the most likely tokens (summing to 0.2 cumulative probability) will be sampled. It is not recommended to modify both temperature and top_p in the same call.\",\"default\":1},\"stop\":{\"anyOf\":[{\"items\":{\"type\":\"string\"},\"type\":\"array\"},{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Stop\",\"description\":\"A string or a list of strings where the API will stop generating further tokens. The returned text will not contain the stop sequence.\",\"examples\":[null]},\"frequency_penalty\":{\"type\":\"number\",\"maximum\":2,\"minimum\":-2,\"default\":0,\"title\":\"Frequency Penalty\",\"description\":\"Indicates how much to penalize new tokens based on their existing frequency in the text so far, decreasing model likelihood to repeat the same line verbatim.\"},\"presence_penalty\":{\"type\":\"number\",\"maximum\":2,\"minimum\":-2,\"default\":0,\"title\":\"Presence Penalty\",\"description\":\"Positive values penalize new tokens based on whether they appear in the text so far, increasing model likelihood to talk about new topics.\"},\"seed\":{\"type\":\"integer\",\"maximum\":18446744073709552000,\"minimum\":0,\"title\":\"Seed\",\"description\":\"The model generates random results. Changing the input seed alone will produce a different response with similar characteristics. It is possible to reproduce results by fixing the input seed (assuming all other hyperparameters are also fixed).\",\"default\":0},\"messages\":{\"anyOf\":[{\"type\":\"string\"},{\"items\":{\"additionalProperties\":{\"type\":\"string\"},\"type\":\"object\"},\"type\":\"array\"}],\"title\":\"Messages\",\"description\":\"A list of messages comprising the conversation so far.\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"messages\"],\"title\":\"ChatCompletionRequest\",\"description\":\"OpenAI ChatCompletionRequest\"},\"ChatCompletionResponse\":{\"properties\":{\"id\":{\"type\":\"string\",\"title\":\"Id\",\"description\":\"A unique identifier for the completion.\"},\"object\":{\"type\":\"string\",\"title\":\"Object\",\"default\":\"chat.completion\"},\"created\":{\"type\":\"integer\",\"title\":\"Created\"},\"model\":{\"type\":\"string\",\"title\":\"Model\",\"example\":\"mistralai/mixtral-8x7b-instruct-v0.1\"},\"choices\":{\"items\":{\"$ref\":\"#/components/schemas/ChatCompletionResponseChoice\"},\"type\":\"array\",\"title\":\"Choices\",\"description\":\"The list of completion choices the model generated for the input prompt.\"},\"usage\":{\"$ref\":\"#/components/schemas/UsageInfo\",\"description\":\"Usage statistics for the completion request.\"}},\"type\":\"object\",\"required\":[\"model\",\"choices\",\"usage\"],\"title\":\"ChatCompletionResponse\"},\"ChatCompletionResponseChoice\":{\"properties\":{\"index\":{\"type\":\"integer\",\"title\":\"Index\",\"description\":\"The index of the choice in the list of choices (always 0).\"},\"message\":{\"$ref\":\"#/components/schemas/ChatMessage\",\"description\":\"A chat completion message generated by the model.\"},\"finish_reason\":{\"anyOf\":[{\"type\":\"string\",\"enum\":[\"stop\",\"length\"]},{\"type\":\"null\"}],\"title\":\"Finish Reason\",\"description\":\"The reason the model stopped generating tokens. This will be `stop` if the model hit a natural stop point or a provided stop sequence, or `length` if the maximum number of tokens specified in the request was reached. Will be `null` if the model has not finished\"}},\"type\":\"object\",\"required\":[\"index\",\"message\"],\"title\":\"ChatCompletionResponseChoice\"},\"ChatMessage\":{\"properties\":{\"role\":{\"type\":\"string\",\"title\":\"Role\",\"description\":\"The role of the message author.\"},\"content\":{\"type\":\"string\",\"title\":\"Content\",\"description\":\"The contents of the message.\"}},\"type\":\"object\",\"required\":[\"role\",\"content\"],\"title\":\"ChatMessage\"},\"HTTPValidationError\":{\"properties\":{\"detail\":{\"items\":{\"$ref\":\"#/components/schemas/ValidationError\"},\"type\":\"array\",\"title\":\"Detail\",\"description\":\"Detailed information about the error.\"}},\"type\":\"object\",\"title\":\"HTTPValidationError\"},\"PaymentRequiredError\":{\"properties\":{\"detail\":{\"type\":\"string\",\"description\":\"Contains specific information related to the error and why it occurred.\",\"example\":\"You have reached your limit of credits.\"}},\"type\":\"object\",\"title\":\"PaymentRequiredError\"},\"UsageInfo\":{\"properties\":{\"prompt_tokens\":{\"type\":\"integer\",\"title\":\"Prompt Tokens\",\"description\":\"Number of tokens in the prompt.\",\"default\":0},\"total_tokens\":{\"type\":\"integer\",\"title\":\"Total Tokens\",\"description\":\"Total number of tokens used in the request (prompt + completion).\",\"default\":0},\"completion_tokens\":{\"anyOf\":[{\"type\":\"integer\"},{\"type\":\"null\"}],\"title\":\"Completion Tokens\",\"description\":\"Number of tokens in the generated completion.\",\"default\":0}},\"type\":\"object\",\"title\":\"UsageInfo\"},\"ValidationError\":{\"properties\":{\"loc\":{\"items\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"integer\"}]},\"type\":\"array\",\"title\":\"Location\"},\"msg\":{\"type\":\"string\",\"title\":\"Message\",\"description\":\"The error message.\"},\"type\":{\"type\":\"string\",\"title\":\"Error Type\",\"description\":\"Error type\"}},\"type\":\"object\",\"required\":[\"loc\",\"msg\",\"type\"],\"title\":\"ValidationError\"}}}},\"namespace\":\"qc69jvmznzxy\",\"updatedDate\":\"2024-11-18T22:30:57.559Z\",\"nvcfFunctionId\":\"a1e53ece-bff4-44d1-8b13-c009e5bf47f6\",\"createdDate\":\"2024-02-22T05:29:04.143Z\",\"attributes\":{\"dockerRun\":\"Pull and run the NVIDIA NIM with the command below. This will download the optimized model for your infrastructure.\\n```bash\\nexport NGC_API_KEY=\u003cPASTE_API_KEY_HERE\u003e\\nexport LOCAL_NIM_CACHE=~/.cache/nim\\nmkdir -p \\\"$LOCAL_NIM_CACHE\\\"\\ndocker run -it --rm \\\\\\n --gpus all \\\\\\n --shm-size=16GB \\\\\\n -e NGC_API_KEY \\\\\\n -v \\\"$LOCAL_NIM_CACHE:/opt/nim/.cache\\\" \\\\\\n -u $(id -u) \\\\\\n -p 8000:8000 \\\\\\n nvcr.io/nim/mistralai/mixtral-8x7b-instruct-v01:latest\\n```\\n\\nYou can now make a local API call using this curl command:\\n```bash\\ncurl -X 'POST' \\\\\\n'http://0.0.0.0:8000/v1/chat/completions' \\\\\\n-H 'accept: application/json' \\\\\\n-H 'Content-Type: application/json' \\\\\\n-d '{\\n \\\"model\\\": \\\"mistralai/mixtral-8x7b-instruct-v0.1\\\",\\n \\\"messages\\\": [{\\\"role\\\":\\\"user\\\", \\\"content\\\":\\\"Write a limerick about the wonders of GPU computing.\\\"}],\\n \\\"max_tokens\\\": 64\\n}'\\n```\\n\\nFor more details on getting started with this NIM, visit the [NVIDIA NIM Docs](https://docs.nvidia.com/nim/large-language-models/latest/getting-started.html).\\n\",\"dockerTermsOfUse\":\"By running the below commands, you accept the \u003ca href=\\\"https://www.nvidia.com/en-us/data-center/products/nvidia-ai-enterprise/eula/\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA AI Enterprise Terms of Use\u003c/a\u003e and the \u003ca href=\\\"https://docs.nvidia.com/ai-foundation-models-community-license.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA Community Models License\u003c/a\u003e.\\n\",\"requiresLogin\":false,\"showUnavailableBanner\":false,\"apiDocsUrl\":\"https://docs.api.nvidia.com/nim/reference/mistralai-mixtral-8x7b-instruct\",\"termsOfUse\":\"\u003cb\u003eGOVERNING TERMS\u003c/b\u003e: Your use of this API is governed by the \u003ca href=\\\"https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA API Trial Service Terms of Use\u003c/a\u003e; and the use of this model is governed by the \u003ca href=\\\"https://docs.nvidia.com/ai-foundation-models-community-license.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA AI Foundation Models Community License\u003c/a\u003e and \u003ca href=\\\"https://mistral.ai/terms-of-service/\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eMistral AI Terms of Use\u003c/a\u003e.\\n\",\"cta\":{\"text\":\"Run Anywhere - Notify Me\",\"url\":\"https://www.nvidia.com/en-us/ai/nim-notifyme/\",\"nim_available_override_url\":\"https://catalog.ngc.nvidia.com/orgs/nim/teams/mistralai/containers/mixtral-8x7b-instruct-v01\"},\"projects\":[{\"name\":\"Customize Mixtral 8x7b using QLoRA\",\"url\":\"https://github.com/NVIDIA/workbench-example-mixtral-finetune\",\"imageUrl\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/nv-workbench.jpg\",\"workbench\":true},{\"name\":\"Build a Customizable Hybrid RAG Chatbot\",\"url\":\"https://github.com/NVIDIA/workbench-example-hybrid-rag\",\"imageUrl\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/nv-workbench.jpg\",\"workbench\":true}]},\"artifactName\":\"mixtral-8x7b-instruct\"},\"config\":{\"name\":\"mixtral-8x7b-instruct\",\"type\":\"model\"}},{\"endpoint\":{\"requestStatus\":{\"statusCode\":\"SUCCESS\",\"requestId\":\"aa20ba81-87ca-4e87-a7fd-8b230392ec51\"},\"artifact\":{\"orgName\":\"qc69jvmznzxy\",\"labels\":[\"Chat\",\"Language Generation\",\"Text-to-Text\",\"Code Generation\"],\"logo\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/llama-3_1-70b-instruct.jpg\",\"shortDescription\":\"Powers complex conversations with superior contextual understanding, reasoning and text generation.\",\"isReadOnly\":true,\"description\":\"$7b\",\"canGuestDownload\":true,\"isPublic\":true,\"createdDate\":\"2024-07-23T14:58:21.518Z\",\"publisher\":\"meta\",\"displayName\":\"llama-3.1-70b-instruct\",\"name\":\"llama-3_1-70b-instruct\",\"updatedDate\":\"2024-11-20T03:07:20.995Z\",\"attributes\":[{\"key\":\"AVAILABLE\",\"value\":\"true\"},{\"key\":\"PREVIEW\",\"value\":\"false\"}],\"artifactType\":\"ENDPOINT\"}},\"spec\":{\"openAPISpec\":{\"openapi\":\"3.1.0\",\"info\":{\"title\":\"NVIDIA NIM API for meta/llama-3.1-70b-instruct\",\"description\":\"The NVIDIA NIM REST API. Please see https://docs.api.nvidia.com/nim/reference/meta-llama-3_1-70b-instruct for more details.\",\"version\":\"1.0.0\",\"termsOfService\":\"https://www.nvidia.com/en-us/data-center/products/nvidia-ai-enterprise/eula/\",\"contact\":{\"name\":\"NVIDIA Enterprise Support\",\"url\":\"https://www.nvidia.com/en-us/support/enterprise/\"},\"license\":{\"name\":\"Llama 3.1 License\",\"url\":\"https://github.com/meta-llama/llama-models/blob/main/License/Llama3.1.txt\"}},\"servers\":[{\"url\":\"https://integrate.api.nvidia.com/v1/\"}],\"paths\":{\"/chat/completions\":{\"post\":{\"operationId\":\"create_chat_completion_v1_chat_completions_post\",\"tags\":[\"Chat\"],\"summary\":\"Creates a model response for the given chat conversation.\",\"description\":\"Given a list of messages comprising a conversation, the model will return a response. Compatible with OpenAI. See https://platform.openai.com/docs/api-reference/chat/create\",\"requestBody\":{\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ChatRequest\"}}},\"required\":true},\"responses\":{\"200\":{\"description\":\"Invocation is fulfilled\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ChatCompletion\"}},\"text/event-stream\":{\"schema\":{\"$ref\":\"#/components/schemas/ChatCompletionChunk\"}}}},\"202\":{\"description\":\"Result is pending. Client should poll using the requestId.\\n\",\"content\":{\"application/json\":{\"example\":{},\"schema\":{}}},\"headers\":{\"NVCF-REQID\":{\"description\":\"requestId required for pooling\",\"schema\":{\"type\":\"string\",\"format\":\"uuid\"}},\"NVCF-STATUS\":{\"description\":\"Invocation status\",\"schema\":{\"type\":\"string\"}}}},\"422\":{\"description\":\"Validation failed, provided entity could not be processed.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/Errors\"},\"example\":{\"type\":\"urn:nvcf-worker-service:problem-details:unprocessable-entity\",\"title\":\"Unprocessable Entity\",\"status\":422,\"detail\":\"string\",\"instance\":\"/v2/nvcf/pexec/functions/4a58c6cb-a9b4-4014-99de-3e704d4ae687\",\"requestId\":\"3fa85f64-5717-4562-b3fc-2c963f66afa6\"}}}},\"500\":{\"description\":\"The invocation ended with an error.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/Errors\"},\"example\":{\"type\":\"urn:nvcf-worker-service:problem-details:internal-server-error\",\"title\":\"Internal Server Error\",\"status\":500,\"detail\":\"string\",\"instance\":\"/v2/nvcf/pexec/functions/4a58c6cb-a9b4-4014-99de-3e704d4ae687\",\"requestId\":\"3fa85f64-5717-4562-b3fc-2c963f66afa6\"}}}}},\"x-nvai-meta\":{\"name\":\"Create chat completion\",\"returns\":\"Returns a [chat completion](/docs/api-reference/chat/object) object, or a streamed sequence of [chat completion chunk](/docs/api-reference/chat/streaming) objects if the request is streamed.\\n\",\"path\":\"create\",\"examples\":[{\"name\":\"Write a limerick about the wonders of GPU computing.\",\"requestJson\":\"{\\n \\\"model\\\": \\\"meta/llama-3.1-70b-instruct\\\",\\n \\\"messages\\\": [\\n {\\n \\\"role\\\": \\\"user\\\",\\n \\\"content\\\": \\\"Write a limerick about the wonders of GPU computing.\\\"\\n }\\n ],\\n \\\"top_p\\\": 0.7,\\n \\\"max_tokens\\\": 1024,\\n \\\"seed\\\": 42,\\n \\\"stream\\\": true\\n}\\n\",\"responseJson\":\"{\\n \\\"id\\\": \\\"id-123\\\",\\n \\\"object\\\": \\\"chat.completion\\\",\\n \\\"created\\\": 1677652288,\\n \\\"model\\\": \\\"meta/llama-3.1-70b-instruct\\\",\\n \\\"system_fingerprint\\\": \\\"fp_44709d6fcb\\\",\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"The python functions...\\\"\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 9,\\n \\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"},{\"name\":\"Tell me about Dumbledore.\",\"requestJson\":\"$7c\",\"responseJson\":\"{\\n \\\"id\\\": \\\"id-123\\\",\\n \\\"object\\\": \\\"chat.completion\\\",\\n \\\"created\\\": 1677652288,\\n \\\"model\\\": \\\"meta/llama-3.1-70b-instruct\\\",\\n \\\"system_fingerprint\\\": \\\"fp_44709d6fcb\\\",\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"At NVIDIA's GPU Technology Conference (GTC)...\\\"\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 9,\\n \\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"},{\"name\":\"What is the weather in Santa Clara, CA?\",\"requestJson\":\"$7d\",\"responseJson\":\"{\\n \\\"id\\\": \\\"id-123\\\",\\n \\\"object\\\": \\\"chat.completion\\\",\\n \\\"created\\\": 1677652288,\\n \\\"model\\\": \\\"meta/llama-3.1-70b-instruct\\\",\\n \\\"system_fingerprint\\\": \\\"fp_44709d6fcb\\\",\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"At NVIDIA's GPU Technology Conference (GTC)...\\\"\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 9,\\n \\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"}],\"templates\":[{\"title\":\"No Streaming\",\"requestEjs\":{\"python\":\"$7e\",\"langChain\":\"from langchain_nvidia_ai_endpoints import ChatNVIDIA\\n\\nclient = ChatNVIDIA(\\n model=\\\"\u003c%- request.model %\u003e\\\",\\n api_key=\\\"$NVIDIA_API_KEY\\\", \\n temperature=\u003c%- request.temperature %\u003e,\\n top_p=\u003c%- request.top_p %\u003e,\\n max_tokens=\u003c%- request.max_tokens %\u003e,\\n)\\n\u003c% if (request.stream) { %\u003e\\nfor chunk in client.stream(\u003c%- JSON.stringify(request.messages) %\u003e): \\n print(chunk.content, end=\\\"\\\")\\n\u003c% } else { %\u003e\\nresponse = client.invoke(\u003c%- JSON.stringify(request.messages) %\u003e)\\nprint(response.content)\\n\u003c% } %\u003e\\n \\n\",\"node.js\":\"$7f\",\"curl\":\"$80\"},\"response\":\"{\\n \\\"id\\\": \\\"chatcmpl-123\\\",\\n \\\"object\\\": \\\"chat.completion\\\",\\n \\\"created\\\": 1677652288,\\n \\\"model\\\": \\\"meta/llama-3.1-70b-instruct\\\",\\n \\\"system_fingerprint\\\": \\\"fp_44709d6fcb\\\",\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"\\\\n\\\\nHello there, how may I assist you today?\\\",\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 9,\\n \\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"}]}}}},\"security\":[{\"Token\":[]}],\"components\":{\"securitySchemes\":{\"Token\":{\"type\":\"http\",\"scheme\":\"bearer\"}},\"schemas\":{\"Errors\":{\"properties\":{\"type\":{\"type\":\"string\",\"description\":\"Error type\"},\"title\":{\"type\":\"string\",\"description\":\"Error title\"},\"status\":{\"type\":\"integer\",\"description\":\"Error status code\"},\"detail\":{\"type\":\"string\",\"description\":\"Detailed information about the error\"},\"instance\":{\"type\":\"string\",\"description\":\"Function instance used to invoke the request\"},\"requestId\":{\"type\":\"string\",\"format\":\"uuid\",\"description\":\"UUID of the request\"}},\"type\":\"object\",\"required\":[\"type\",\"title\",\"status\",\"detail\",\"instance\",\"requestId\"],\"title\":\"InvokeError\"},\"ChatCompletion\":{\"properties\":{\"id\":{\"description\":\"A unique identifier for the completion.\",\"format\":\"uuid\",\"title\":\"Id\",\"type\":\"string\"},\"choices\":{\"description\":\"The list of completion choices the model generated for the input prompt.\",\"items\":{\"$ref\":\"#/components/schemas/Choice\"},\"title\":\"Choices\",\"type\":\"array\"},\"usage\":{\"allOf\":[{\"$ref\":\"#/components/schemas/Usage\"}],\"description\":\"Usage statistics for the completion request.\"}},\"required\":[\"id\",\"choices\",\"usage\"],\"title\":\"ChatCompletion\",\"type\":\"object\"},\"ChatCompletionChunk\":{\"properties\":{\"id\":{\"description\":\"A unique identifier for the completion.\",\"format\":\"uuid\",\"title\":\"Id\",\"type\":\"string\"},\"choices\":{\"description\":\"The list of completion choices the model generated for the input prompt.\",\"items\":{\"$ref\":\"#/components/schemas/ChoiceChunk\"},\"title\":\"Choices\",\"type\":\"array\"}},\"required\":[\"id\",\"choices\"],\"title\":\"ChatCompletionChunk\",\"type\":\"object\"},\"ChatRequest\":{\"additionalProperties\":false,\"properties\":{\"model\":{\"type\":\"string\",\"title\":\"Model\",\"default\":\"meta/llama-3.1-70b-instruct\"},\"messages\":{\"description\":\"A list of messages comprising the conversation so far. The roles of the messages must be alternating between `user` and `assistant`. The last input message should have role `user`. A message with the the `system` role is optional, and must be the very first message if it is present; `context` is also optional, but must come before a user question.\",\"examples\":[[{\"content\":\"I am going to Paris, what should I see?\",\"role\":\"user\"}]],\"items\":{\"$ref\":\"#/components/schemas/Message\"},\"title\":\"Messages\",\"type\":\"array\"},\"temperature\":{\"default\":0.2,\"description\":\"The sampling temperature to use for text generation. The higher the temperature value is, the less deterministic the output text will be. It is not recommended to modify both temperature and top_p in the same call.\",\"maximum\":1,\"minimum\":0,\"title\":\"Temperature\",\"type\":\"number\"},\"top_p\":{\"default\":0.7,\"description\":\"The top-p sampling mass used for text generation. The top-p value determines the probability mass that is sampled at sampling time. For example, if top_p = 0.2, only the most likely tokens (summing to 0.2 cumulative probability) will be sampled. It is not recommended to modify both temperature and top_p in the same call.\",\"maximum\":1,\"exclusiveMinimum\":0,\"title\":\"Top P\",\"type\":\"number\"},\"tools\":{\"anyOf\":[{\"items\":{\"$ref\":\"#/components/schemas/ChatCompletionToolsParam\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Tools\"},\"frequency_penalty\":{\"type\":\"number\",\"maximum\":2,\"minimum\":-2,\"default\":0,\"title\":\"Frequency Penalty\",\"description\":\"Indicates how much to penalize new tokens based on their existing frequency in the text so far, decreasing model likelihood to repeat the same line verbatim.\"},\"presence_penalty\":{\"type\":\"number\",\"maximum\":2,\"minimum\":-2,\"default\":0,\"title\":\"Presence Penalty\",\"description\":\"Positive values penalize new tokens based on whether they appear in the text so far, increasing model likelihood to talk about new topics.\"},\"max_tokens\":{\"default\":1024,\"description\":\"The maximum number of tokens to generate in any given call. Note that the model is not aware of this value, and generation will simply stop at the number of tokens specified.\",\"maximum\":4096,\"minimum\":1,\"title\":\"Max Tokens\",\"type\":\"integer\"},\"stream\":{\"default\":false,\"description\":\"If set, partial message deltas will be sent. Tokens will be sent as data-only server-sent events (SSE) as they become available (JSON responses are prefixed by `data: `), with the stream terminated by a `data: [DONE]` message.\",\"title\":\"Stream\",\"type\":\"boolean\"},\"stop\":{\"anyOf\":[{\"items\":{\"type\":\"string\"},\"type\":\"array\"},{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Stop\",\"description\":\"A string or a list of strings where the API will stop generating further tokens. The returned text will not contain the stop sequence.\"}},\"required\":[\"messages\"],\"title\":\"ChatRequest\",\"type\":\"object\"},\"Choice\":{\"properties\":{\"index\":{\"description\":\"The index of the choice in the list of choices (always 0).\",\"title\":\"Index\",\"type\":\"integer\"},\"message\":{\"allOf\":[{\"$ref\":\"#/components/schemas/Message\"}],\"description\":\"A chat completion message generated by the model.\",\"examples\":[{\"content\":\"Ah, Paris, the City of Light! There are so many amazing things to see and do in this beautiful city ...\",\"role\":\"assistant\"}]},\"finish_reason\":{\"anyOf\":[{\"enum\":[\"stop\",\"length\",\"tool_calls\"],\"type\":\"string\"},{\"type\":\"null\"}],\"default\":null,\"description\":\"The reason the model stopped generating tokens. This will be `stop` if the model hit a natural stop point or a provided stop sequence, or `length` if the maximum number of tokens specified in the request was reached.\",\"examples\":[\"stop\"],\"title\":\"Finish Reason\"}},\"required\":[\"index\",\"message\"],\"title\":\"Choice\",\"type\":\"object\"},\"ChoiceChunk\":{\"properties\":{\"index\":{\"description\":\"The index of the choice in the list of choices (always 0).\",\"title\":\"Index\",\"type\":\"integer\"},\"delta\":{\"allOf\":[{\"$ref\":\"#/components/schemas/Message\"}],\"description\":\"A chat completion delta generated by streamed model responses.\",\"examples\":[{\"content\":\"Ah,\",\"role\":\"assistant\"}]},\"finish_reason\":{\"anyOf\":[{\"enum\":[\"stop\",\"length\",\"tool_calls\"],\"type\":\"string\"},{\"type\":\"null\"}],\"default\":null,\"description\":\"The reason the model stopped generating tokens. This will be `stop` if the model hit a natural stop point or a provided stop sequence, or `length` if the maximum number of tokens specified in the request was reached. Will be `null` if the model has not finished generating.\",\"title\":\"Finish Reason\"}},\"required\":[\"index\",\"delta\"],\"title\":\"ChoiceChunk\",\"type\":\"object\"},\"Message\":{\"additionalProperties\":false,\"properties\":{\"role\":{\"description\":\"The role of the message author.\",\"enum\":[\"system\",\"context\",\"user\",\"assistant\",\"tool\"],\"title\":\"Role\",\"type\":\"string\"},\"content\":{\"description\":\"The contents of the message.\",\"title\":\"Content\",\"anyOf\":[{\"type\":\"string\"},{\"type\":\"null\"}]},\"tool_call_id\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Tool Call Id\",\"description\":\"The id of the tool call.\"},\"tool_calls\":{\"anyOf\":[{\"items\":{\"$ref\":\"#/components/schemas/ToolCall\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Tool Calls\",\"description\":\"The tool(s) called by the model.\"}},\"required\":[\"role\",\"content\"],\"title\":\"Message\",\"type\":\"object\"},\"ToolCall\":{\"properties\":{\"id\":{\"type\":\"string\",\"title\":\"Id\"},\"type\":{\"type\":\"string\",\"enum\":[\"function\"],\"const\":\"function\",\"title\":\"Type\",\"default\":\"function\"},\"function\":{\"$ref\":\"#/components/schemas/FunctionCall\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"function\"],\"title\":\"ToolCall\"},\"FunctionCall\":{\"properties\":{\"name\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Name\"},\"arguments\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Arguments\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"name\",\"arguments\"],\"title\":\"FunctionCall\"},\"ChatCompletionToolsParam\":{\"properties\":{\"type\":{\"type\":\"string\",\"enum\":[\"function\"],\"const\":\"function\",\"title\":\"Type\",\"default\":\"function\"},\"function\":{\"$ref\":\"#/components/schemas/FunctionDefinition\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"function\"],\"title\":\"ChatCompletionToolsParam\"},\"ChatCompletionNamedFunction\":{\"properties\":{\"name\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Name\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"name\"],\"title\":\"ChatCompletionNamedFunction\"},\"ChatCompletionNamedToolChoiceParam\":{\"properties\":{\"function\":{\"$ref\":\"#/components/schemas/ChatCompletionNamedFunction\"},\"type\":{\"type\":\"string\",\"enum\":[\"function\"],\"const\":\"function\",\"title\":\"Type\",\"default\":\"function\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"function\"],\"title\":\"ChatCompletionNamedToolChoiceParam\"},\"FunctionDefinition\":{\"properties\":{\"name\":{\"type\":\"string\",\"title\":\"Name\"},\"description\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Description\"},\"parameters\":{\"anyOf\":[{\"type\":\"object\"},{\"type\":\"null\"}],\"title\":\"Parameters\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"name\"],\"title\":\"FunctionDefinition\"},\"Usage\":{\"properties\":{\"completion_tokens\":{\"description\":\"Number of tokens in the generated completion.\",\"examples\":[25],\"title\":\"Completion Tokens\",\"type\":\"integer\"},\"prompt_tokens\":{\"description\":\"Number of tokens in the prompt.\",\"examples\":[9],\"title\":\"Prompt Tokens\",\"type\":\"integer\"},\"total_tokens\":{\"description\":\"Total number of tokens used in the request (prompt + completion).\",\"examples\":[34],\"title\":\"Total Tokens\",\"type\":\"integer\"}},\"required\":[\"completion_tokens\",\"prompt_tokens\",\"total_tokens\"],\"title\":\"Usage\",\"type\":\"object\"}}}},\"namespace\":\"qc69jvmznzxy\",\"updatedDate\":\"2024-11-20T03:07:21.745Z\",\"nvcfFunctionId\":\"8f723982-f99d-4978-a0cb-1334163e0e07\",\"createdDate\":\"2024-07-23T14:58:21.785Z\",\"attributes\":{\"dockerRun\":\"Pull and run the NVIDIA NIM with the command below. This will download the optimized model for your infrastructure.\\n```bash\\nexport NGC_API_KEY=\u003cPASTE_API_KEY_HERE\u003e\\nexport LOCAL_NIM_CACHE=~/.cache/nim\\nmkdir -p \\\"$LOCAL_NIM_CACHE\\\"\\ndocker run -it --rm \\\\\\n --gpus all \\\\\\n --shm-size=16GB \\\\\\n -e NGC_API_KEY \\\\\\n -v \\\"$LOCAL_NIM_CACHE:/opt/nim/.cache\\\" \\\\\\n -u $(id -u) \\\\\\n -p 8000:8000 \\\\\\n nvcr.io/nim/meta/llama-3.1-70b-instruct:latest\\n```\\n\\nYou can now make a local API call using this curl command:\\n```bash\\ncurl -X 'POST' \\\\\\n'http://0.0.0.0:8000/v1/chat/completions' \\\\\\n-H 'accept: application/json' \\\\\\n-H 'Content-Type: application/json' \\\\\\n-d '{\\n \\\"model\\\": \\\"meta/llama-3.1-70b-instruct\\\",\\n \\\"messages\\\": [{\\\"role\\\":\\\"user\\\", \\\"content\\\":\\\"Write a limerick about the wonders of GPU computing.\\\"}],\\n \\\"max_tokens\\\": 64\\n}'\\n```\\n\\nFor more details on getting started with this NIM, visit the [NVIDIA NIM Docs](https://docs.nvidia.com/nim/large-language-models/latest/getting-started.html).\\n\",\"dockerTermsOfUse\":\"By running the below commands, you accept the \u003ca href=\\\"https://www.nvidia.com/en-us/data-center/products/nvidia-ai-enterprise/eula/\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA AI Enterprise Terms of Use\u003c/a\u003e and the \u003ca href=\\\"https://docs.nvidia.com/ai-foundation-models-community-license.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA Community Models License\u003c/a\u003e.\\n\",\"showUnavailableBanner\":false,\"apiDocsUrl\":\"https://docs.api.nvidia.com/nim/reference/meta-llama-3_1-70b\",\"playground\":{\"type\":\"chatWithTools\"},\"termsOfUse\":\"\u003cb\u003eGOVERNING TERMS\u003c/b\u003e: This trial service is governed by the \u003ca href=\\\"https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA API Trial Terms of Service\u003c/a\u003e. Use of this model is governed by the \u003ca href=\\\"https://docs.nvidia.com/ai-foundation-models-community-license.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003e AI Foundation Models Community License Agreement \u003c/a\u003e. ADDITIONAL INFORMATION: Llama 3.1 Community License Agreement, Built with Llama.\\n\",\"cta\":{\"text\":\"Apply to Self-Host\",\"url\":\"https://www.nvidia.com/en-us/ai/nim-notifyme/\",\"nim_available_override_url\":\"https://catalog.ngc.nvidia.com/orgs/nim/teams/meta/containers/llama-3.1-70b-instruct\"},\"projects\":[{\"name\":\"Build a Customizable Hybrid RAG Chatbot\",\"url\":\"https://github.com/NVIDIA/workbench-example-hybrid-rag\",\"imageUrl\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/nv-workbench.jpg\",\"workbench\":true}]},\"artifactName\":\"llama-3_1-70b-instruct\"},\"config\":{\"name\":\"llama-3_1-70b-instruct\",\"type\":\"model\"}},{\"endpoint\":{\"requestStatus\":{\"statusCode\":\"SUCCESS\",\"requestId\":\"e0f7f35f-66e3-4f76-8fed-0ef2aeab216c\"},\"artifact\":{\"orgName\":\"qc69jvmznzxy\",\"labels\":[\"Chat\",\"Language Generation\",\"Text-to-Text\"],\"logo\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/mistral-7b-instruct-v03.jpg\",\"shortDescription\":\"This LLM follows instructions, completes requests, and generates creative text.\",\"isReadOnly\":true,\"description\":\"$81\",\"canGuestDownload\":true,\"isPublic\":true,\"createdDate\":\"2024-06-17T16:46:48.346Z\",\"publisher\":\"mistralai\",\"displayName\":\"mistral-7b-instruct-v0.3\",\"name\":\"mistral-7b-instruct-v03\",\"updatedDate\":\"2024-11-18T22:30:26.294Z\",\"attributes\":[{\"key\":\"AVAILABLE\",\"value\":\"true\"},{\"key\":\"PREVIEW\",\"value\":\"false\"}],\"artifactType\":\"ENDPOINT\"}},\"spec\":{\"openAPISpec\":{\"openapi\":\"3.1.0\",\"info\":{\"title\":\"NVIDIA NIM API for mistralai/mistral-7b-instruct-v0.3\",\"description\":\"The NVIDIA NIM REST API. Please see https://docs.api.nvidia.com/nim/reference/mistralai-mistral-7b-instruct-v03 for more details.\",\"version\":\"1.0.0\",\"termsOfService\":\"https://www.nvidia.com/en-us/data-center/products/nvidia-ai-enterprise/eula/\",\"contact\":{\"name\":\"NVIDIA Enterprise Support\",\"url\":\"https://www.nvidia.com/en-us/support/enterprise/\"},\"license\":{\"name\":\"Apache 2.0\",\"url\":\"https://mistral.ai/terms-of-service/\"}},\"servers\":[{\"url\":\"https://integrate.api.nvidia.com/v1/\"}],\"paths\":{\"/chat/completions\":{\"post\":{\"operationId\":\"create_chat_completion_v1_chat_completions_post\",\"tags\":[\"Chat\"],\"summary\":\"Creates a model response for the given chat conversation.\",\"description\":\"Given a list of messages comprising a conversation, the model will return a response. Compatible with OpenAI. See https://platform.openai.com/docs/api-reference/chat/create\",\"requestBody\":{\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ChatRequest\"}}},\"required\":true},\"responses\":{\"200\":{\"description\":\"Invocation is fulfilled\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ChatCompletion\"}},\"text/event-stream\":{\"schema\":{\"$ref\":\"#/components/schemas/ChatCompletionChunk\"}}}},\"202\":{\"description\":\"Result is pending. Client should poll using the requestId.\\n\",\"content\":{\"application/json\":{\"example\":{},\"schema\":{}}},\"headers\":{\"NVCF-REQID\":{\"description\":\"requestId required for pooling\",\"schema\":{\"type\":\"string\",\"format\":\"uuid\"}},\"NVCF-STATUS\":{\"description\":\"Invocation status\",\"schema\":{\"type\":\"string\"}}}},\"422\":{\"description\":\"Validation failed, provided entity could not be processed.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/Errors\"},\"example\":{\"type\":\"urn:nvcf-worker-service:problem-details:unprocessable-entity\",\"title\":\"Unprocessable Entity\",\"status\":422,\"detail\":\"string\",\"instance\":\"/v2/nvcf/pexec/functions/4a58c6cb-a9b4-4014-99de-3e704d4ae687\",\"requestId\":\"3fa85f64-5717-4562-b3fc-2c963f66afa6\"}}}},\"500\":{\"description\":\"The invocation ended with an error.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/Errors\"},\"example\":{\"type\":\"urn:nvcf-worker-service:problem-details:internal-server-error\",\"title\":\"Internal Server Error\",\"status\":500,\"detail\":\"string\",\"instance\":\"/v2/nvcf/pexec/functions/4a58c6cb-a9b4-4014-99de-3e704d4ae687\",\"requestId\":\"3fa85f64-5717-4562-b3fc-2c963f66afa6\"}}}}},\"x-nvai-meta\":{\"name\":\"Create chat completion\",\"returns\":\"Returns a [chat completion](/docs/api-reference/chat/object) object, or a streamed sequence of [chat completion chunk](/docs/api-reference/chat/streaming) objects if the request is streamed.\\n\",\"path\":\"create\",\"examples\":[{\"name\":\"Write a limerick about the wonders of GPU computing.\",\"requestJson\":\"{\\n \\\"model\\\": \\\"mistralai/mistral-7b-instruct-v0.3\\\",\\n \\\"messages\\\": [\\n {\\n \\\"role\\\": \\\"user\\\",\\n \\\"content\\\": \\\"Write a limerick about the wonders of GPU computing.\\\"\\n }\\n ],\\n \\\"top_p\\\": 0.7,\\n \\\"max_tokens\\\": 1024,\\n \\\"seed\\\": 42,\\n \\\"stream\\\": true\\n}\\n\",\"responseJson\":\"{\\n \\\"id\\\": \\\"id-123\\\",\\n \\\"object\\\": \\\"chat.completion\\\",\\n \\\"created\\\": 1677652288,\\n \\\"model\\\": \\\"mistralai/mistral-7b-instruct-v0.3\\\",\\n \\\"system_fingerprint\\\": \\\"fp_44709d6fcb\\\",\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"The python functions...\\\"\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 9,\\n \\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"},{\"name\":\"Tell me about Dumbledore.\",\"requestJson\":\"$82\",\"responseJson\":\"{\\n \\\"id\\\": \\\"id-123\\\",\\n \\\"object\\\": \\\"chat.completion\\\",\\n \\\"created\\\": 1677652288,\\n \\\"model\\\": \\\"mistralai/mistral-7b-instruct-v0.3\\\",\\n \\\"system_fingerprint\\\": \\\"fp_44709d6fcb\\\",\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"At NVIDIA's GPU Technology Conference (GTC)...\\\"\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 9,\\n \\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"},{\"name\":\"What is the weather in Santa Clara, CA?\",\"requestJson\":\"$83\",\"responseJson\":\"{\\n \\\"id\\\": \\\"id-123\\\",\\n \\\"object\\\": \\\"chat.completion\\\",\\n \\\"created\\\": 1677652288,\\n \\\"model\\\": \\\"mistralai/mistral-7b-instruct-v0.3\\\",\\n \\\"system_fingerprint\\\": \\\"fp_44709d6fcb\\\",\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"At NVIDIA's GPU Technology Conference (GTC)...\\\"\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 9,\\n \\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"}],\"templates\":[{\"title\":\"No Streaming\",\"requestEjs\":{\"python\":\"from openai import OpenAI\\n\\nclient = OpenAI(\\n base_url = \\\"https://integrate.api.nvidia.com/v1\\\",\\n api_key = \\\"$NVIDIA_API_KEY\\\"\\n)\\n\\ncompletion = client.chat.completions.create(\\n model=\\\"\u003c%- request.model %\u003e\\\",\\n messages=\u003c%- JSON.stringify(request.messages) %\u003e,\\n temperature=\u003c%- request.temperature %\u003e,\\n top_p=\u003c%- request.top_p %\u003e,\\n max_tokens=\u003c%- request.max_tokens %\u003e,\\n stream=\u003c%- request.stream?.toString()[0].toUpperCase() + request.stream?.toString().slice(1) %\u003e\\n)\\n\u003c% if (request.stream) { %\u003e\\nfor chunk in completion:\\n if chunk.choices[0].delta.content is not None:\\n print(chunk.choices[0].delta.content, end=\\\"\\\")\\n\u003c% } else { %\u003e\\nprint(completion.choices[0].message)\\n\u003c% } %\u003e\\n\",\"langChain\":\"from langchain_nvidia_ai_endpoints import ChatNVIDIA\\n\\nclient = ChatNVIDIA(\\n model=\\\"\u003c%- request.model %\u003e\\\",\\n api_key=\\\"$NVIDIA_API_KEY\\\", \\n temperature=\u003c%- request.temperature %\u003e,\\n top_p=\u003c%- request.top_p %\u003e,\\n max_tokens=\u003c%- request.max_tokens %\u003e,\\n)\\n\u003c% if (request.stream) { %\u003e\\nfor chunk in client.stream(\u003c%- JSON.stringify(request.messages) %\u003e): \\n print(chunk.content, end=\\\"\\\")\\n\u003c% } else { %\u003e\\nresponse = client.invoke(\u003c%- JSON.stringify(request.messages) %\u003e)\\nprint(response.content)\\n\u003c% } %\u003e\\n\",\"node.js\":\"import OpenAI from 'openai';\\n\\nconst openai = new OpenAI({\\n apiKey: '$NVIDIA_API_KEY',\\n baseURL: 'https://integrate.api.nvidia.com/v1',\\n})\\n\\nasync function main() {\\n const completion = await openai.chat.completions.create({\\n model: \\\"\u003c%- request.model %\u003e\\\",\\n messages: \u003c%- JSON.stringify(request.messages) %\u003e,\\n temperature: \u003c%- request.temperature %\u003e,\\n top_p: \u003c%- request.top_p %\u003e,\\n max_tokens: \u003c%- request.max_tokens %\u003e,\\n stream: \u003c%- request.stream %\u003e,\\n })\\n \u003c% if (request.stream) { %\u003e\\n for await (const chunk of completion) {\\n process.stdout.write(chunk.choices[0]?.delta?.content || '')\\n }\\n \u003c% } else { %\u003e\\n process.stdout.write(completion.choices[0]?.message?.content);\\n \u003c% } %\u003e\\n}\\n\\nmain();\",\"curl\":\"curl https://integrate.api.nvidia.com/v1/chat/completions \\\\\\n -H \\\"Content-Type: application/json\\\" \\\\\\n -H \\\"Authorization: Bearer $NVIDIA_API_KEY\\\" \\\\\\n -d '{\\n \\\"model\\\": \\\"mistralai/mistral-7b-instruct-v0.3\\\",\\n \\\"messages\\\": \u003c%- JSON.stringify(request.messages).replaceAll(\\\"'\\\", \\\"'\\\\\\\"'\\\\\\\"'\\\") %\u003e,\\n \\\"temperature\\\": \u003c%- request.temperature %\u003e, \\n \\\"top_p\\\": \u003c%- request.top_p %\u003e,\\n \\\"max_tokens\\\": \u003c%- request.max_tokens %\u003e,\\n \\\"stream\\\": \u003c%- request.stream %\u003e \\n }'\\n\"},\"response\":\"{\\n \\\"id\\\": \\\"chatcmpl-123\\\",\\n \\\"object\\\": \\\"chat.completion\\\",\\n \\\"created\\\": 1677652288,\\n \\\"model\\\": \\\"mistralai/mistral-7b-instruct-v0.3\\\",\\n \\\"system_fingerprint\\\": \\\"fp_44709d6fcb\\\",\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"\\\\n\\\\nHello there, how may I assist you today?\\\",\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 9,\\n \\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"}]}}}},\"security\":[{\"Token\":[]}],\"components\":{\"securitySchemes\":{\"Token\":{\"type\":\"http\",\"scheme\":\"bearer\"}},\"schemas\":{\"Errors\":{\"properties\":{\"type\":{\"type\":\"string\",\"description\":\"Error type\"},\"title\":{\"type\":\"string\",\"description\":\"Error title\"},\"status\":{\"type\":\"integer\",\"description\":\"Error status code\"},\"detail\":{\"type\":\"string\",\"description\":\"Detailed information about the error\"},\"instance\":{\"type\":\"string\",\"description\":\"Function instance used to invoke the request\"},\"requestId\":{\"type\":\"string\",\"format\":\"uuid\",\"description\":\"UUID of the request\"}},\"type\":\"object\",\"required\":[\"type\",\"title\",\"status\",\"detail\",\"instance\",\"requestId\"],\"title\":\"InvokeError\"},\"ChatCompletion\":{\"properties\":{\"id\":{\"description\":\"A unique identifier for the completion.\",\"format\":\"uuid\",\"title\":\"Id\",\"type\":\"string\"},\"choices\":{\"description\":\"The list of completion choices the model generated for the input prompt.\",\"items\":{\"$ref\":\"#/components/schemas/Choice\"},\"title\":\"Choices\",\"type\":\"array\"},\"usage\":{\"allOf\":[{\"$ref\":\"#/components/schemas/Usage\"}],\"description\":\"Usage statistics for the completion request.\"}},\"required\":[\"id\",\"choices\",\"usage\"],\"title\":\"ChatCompletion\",\"type\":\"object\"},\"ChatCompletionChunk\":{\"properties\":{\"id\":{\"description\":\"A unique identifier for the completion.\",\"format\":\"uuid\",\"title\":\"Id\",\"type\":\"string\"},\"choices\":{\"description\":\"The list of completion choices the model generated for the input prompt.\",\"items\":{\"$ref\":\"#/components/schemas/ChoiceChunk\"},\"title\":\"Choices\",\"type\":\"array\"}},\"required\":[\"id\",\"choices\"],\"title\":\"ChatCompletionChunk\",\"type\":\"object\"},\"ChatRequest\":{\"additionalProperties\":false,\"properties\":{\"model\":{\"type\":\"string\",\"title\":\"Model\",\"default\":\"mistralai/mistral-7b-instruct-v0.3\"},\"messages\":{\"description\":\"A list of messages comprising the conversation so far. The roles of the messages must be alternating between `user` and `assistant`. The last input message should have role `user`. A message with the the `system` role is optional, and must be the very first message if it is present; `context` is also optional, but must come before a user question.\",\"examples\":[[{\"content\":\"I am going to Paris, what should I see?\",\"role\":\"user\"}]],\"items\":{\"$ref\":\"#/components/schemas/Message\"},\"title\":\"Messages\",\"type\":\"array\"},\"temperature\":{\"default\":0.2,\"description\":\"The sampling temperature to use for text generation. The higher the temperature value is, the less deterministic the output text will be. It is not recommended to modify both temperature and top_p in the same call.\",\"maximum\":1,\"minimum\":0,\"title\":\"Temperature\",\"type\":\"number\"},\"top_p\":{\"default\":0.7,\"description\":\"The top-p sampling mass used for text generation. The top-p value determines the probability mass that is sampled at sampling time. For example, if top_p = 0.2, only the most likely tokens (summing to 0.2 cumulative probability) will be sampled. It is not recommended to modify both temperature and top_p in the same call.\",\"maximum\":1,\"exclusiveMinimum\":0,\"title\":\"Top P\",\"type\":\"number\"},\"frequency_penalty\":{\"type\":\"number\",\"maximum\":2,\"minimum\":-2,\"default\":0,\"title\":\"Frequency Penalty\",\"description\":\"Indicates how much to penalize new tokens based on their existing frequency in the text so far, decreasing model likelihood to repeat the same line verbatim.\"},\"presence_penalty\":{\"type\":\"number\",\"maximum\":2,\"minimum\":-2,\"default\":0,\"title\":\"Presence Penalty\",\"description\":\"Positive values penalize new tokens based on whether they appear in the text so far, increasing model likelihood to talk about new topics.\"},\"max_tokens\":{\"default\":1024,\"description\":\"The maximum number of tokens to generate in any given call. Note that the model is not aware of this value, and generation will simply stop at the number of tokens specified.\",\"maximum\":4096,\"minimum\":1,\"title\":\"Max Tokens\",\"type\":\"integer\"},\"stream\":{\"default\":false,\"description\":\"If set, partial message deltas will be sent. Tokens will be sent as data-only server-sent events (SSE) as they become available (JSON responses are prefixed by `data: `), with the stream terminated by a `data: [DONE]` message.\",\"title\":\"Stream\",\"type\":\"boolean\"},\"stop\":{\"anyOf\":[{\"items\":{\"type\":\"string\"},\"type\":\"array\"},{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Stop\",\"description\":\"A string or a list of strings where the API will stop generating further tokens. The returned text will not contain the stop sequence.\"}},\"required\":[\"messages\"],\"title\":\"ChatRequest\",\"type\":\"object\"},\"Choice\":{\"properties\":{\"index\":{\"description\":\"The index of the choice in the list of choices (always 0).\",\"title\":\"Index\",\"type\":\"integer\"},\"message\":{\"allOf\":[{\"$ref\":\"#/components/schemas/Message\"}],\"description\":\"A chat completion message generated by the model.\",\"examples\":[{\"content\":\"Ah, Paris, the City of Light! There are so many amazing things to see and do in this beautiful city ...\",\"role\":\"assistant\"}]},\"finish_reason\":{\"anyOf\":[{\"enum\":[\"stop\",\"length\"],\"type\":\"string\"},{\"type\":\"null\"}],\"default\":null,\"description\":\"The reason the model stopped generating tokens. This will be `stop` if the model hit a natural stop point or a provided stop sequence, or `length` if the maximum number of tokens specified in the request was reached.\",\"examples\":[\"stop\"],\"title\":\"Finish Reason\"}},\"required\":[\"index\",\"message\"],\"title\":\"Choice\",\"type\":\"object\"},\"ChoiceChunk\":{\"properties\":{\"index\":{\"description\":\"The index of the choice in the list of choices (always 0).\",\"title\":\"Index\",\"type\":\"integer\"},\"delta\":{\"allOf\":[{\"$ref\":\"#/components/schemas/Message\"}],\"description\":\"A chat completion delta generated by streamed model responses.\",\"examples\":[{\"content\":\"Ah,\",\"role\":\"assistant\"}]},\"finish_reason\":{\"anyOf\":[{\"enum\":[\"stop\",\"length\"],\"type\":\"string\"},{\"type\":\"null\"}],\"default\":null,\"description\":\"The reason the model stopped generating tokens. This will be `stop` if the model hit a natural stop point or a provided stop sequence, or `length` if the maximum number of tokens specified in the request was reached. Will be `null` if the model has not finished generating.\",\"title\":\"Finish Reason\"}},\"required\":[\"index\",\"delta\"],\"title\":\"ChoiceChunk\",\"type\":\"object\"},\"Message\":{\"additionalProperties\":false,\"properties\":{\"role\":{\"description\":\"The role of the message author.\",\"enum\":[\"system\",\"context\",\"user\",\"assistant\"],\"title\":\"Role\",\"type\":\"string\"},\"content\":{\"description\":\"The contents of the message.\",\"title\":\"Content\",\"type\":\"string\"}},\"required\":[\"role\",\"content\"],\"title\":\"Message\",\"type\":\"object\"},\"Usage\":{\"properties\":{\"completion_tokens\":{\"description\":\"Number of tokens in the generated completion.\",\"examples\":[25],\"title\":\"Completion Tokens\",\"type\":\"integer\"},\"prompt_tokens\":{\"description\":\"Number of tokens in the prompt.\",\"examples\":[9],\"title\":\"Prompt Tokens\",\"type\":\"integer\"},\"total_tokens\":{\"description\":\"Total number of tokens used in the request (prompt + completion).\",\"examples\":[34],\"title\":\"Total Tokens\",\"type\":\"integer\"}},\"required\":[\"completion_tokens\",\"prompt_tokens\",\"total_tokens\"],\"title\":\"Usage\",\"type\":\"object\"}}}},\"namespace\":\"qc69jvmznzxy\",\"updatedDate\":\"2024-11-18T22:30:26.913Z\",\"nvcfFunctionId\":\"cd89bd68-13e3-47a9-861e-9a62e6e14b05\",\"createdDate\":\"2024-06-17T16:46:48.975Z\",\"attributes\":{\"dockerRun\":\"Pull and run the NVIDIA NIM with the command below. This will download the optimized model for your infrastructure.\\n```bash\\nexport NGC_API_KEY=\u003cPASTE_API_KEY_HERE\u003e\\nexport LOCAL_NIM_CACHE=~/.cache/nim\\nmkdir -p \\\"$LOCAL_NIM_CACHE\\\"\\ndocker run -it --rm \\\\\\n --gpus all \\\\\\n --shm-size=16GB \\\\\\n -e NGC_API_KEY \\\\\\n -v \\\"$LOCAL_NIM_CACHE:/opt/nim/.cache\\\" \\\\\\n -u $(id -u) \\\\\\n -p 8000:8000 \\\\\\n nvcr.io/nim/mistralai/mistral-7b-instruct-v0.3:latest\\n```\\n\\nYou can now make a local API call using this curl command:\\n```bash\\ncurl -X 'POST' \\\\\\n'http://0.0.0.0:8000/v1/chat/completions' \\\\\\n-H 'accept: application/json' \\\\\\n-H 'Content-Type: application/json' \\\\\\n-d '{\\n \\\"model\\\": \\\"mistralai/mistral-7b-instruct-v0.3\\\",\\n \\\"messages\\\": [{\\\"role\\\":\\\"user\\\", \\\"content\\\":\\\"Write a limerick about the wonders of GPU computing.\\\"}],\\n \\\"max_tokens\\\": 64\\n}'\\n```\\n\\nFor more details on getting started with this NIM, visit the [NVIDIA NIM Docs](https://docs.nvidia.com/nim/large-language-models/latest/getting-started.html).\\n\",\"dockerTermsOfUse\":\"By running the below commands, you accept the \u003ca href=\\\"https://www.nvidia.com/en-us/data-center/products/nvidia-ai-enterprise/eula/\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA AI Enterprise Terms of Use\u003c/a\u003e and the \u003ca href=\\\"https://docs.nvidia.com/ai-foundation-models-community-license.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA Community Models License\u003c/a\u003e.\\n\",\"showUnavailableBanner\":false,\"apiDocsUrl\":\"https://docs.api.nvidia.com/nim/reference/mistralai-mistral-7b-instruct-v03\",\"playground\":{\"type\":\"chatWithTools\"},\"termsOfUse\":\"\u003cb\u003eGOVERNING TERMS\u003c/b\u003e: Your use of this API is governed by the \u003ca href=\\\"https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA API Trial Service Terms of Use\u003c/a\u003e; and the use of this model is governed by the \u003ca href=\\\"https://docs.nvidia.com/ai-foundation-models-community-license.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA AI Foundation Models Community License\u003c/a\u003e and \u003ca href=\\\"https://mistral.ai/terms-of-service/\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eMistral AI Terms of Use\u003c/a\u003e.\\n\",\"cta\":{\"text\":\"Run Anywhere - Notify Me\",\"url\":\"https://www.nvidia.com/en-us/ai/nim-notifyme/\",\"nim_available_override_url\":\"https://catalog.ngc.nvidia.com/orgs/nim/teams/mistralai/containers/mistral-7b-instruct-v0.3\"},\"projects\":[{\"name\":\"Build a Customizable Hybrid RAG Chatbot\",\"url\":\"https://github.com/NVIDIA/workbench-example-hybrid-rag\",\"imageUrl\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/nv-workbench.jpg\",\"workbench\":true}]},\"artifactName\":\"mistral-7b-instruct-v03\"},\"config\":{\"name\":\"mistral-7b-instruct-v03\",\"type\":\"model\"}},{\"endpoint\":{\"requestStatus\":{\"statusCode\":\"SUCCESS\",\"requestId\":\"7686913d-a546-4330-a6b8-3e3619f5b52b\"},\"artifact\":{\"orgName\":\"qc69jvmznzxy\",\"labels\":[\"Chat\",\"Language Generation\",\"Text-to-Text\",\"Code Generation\"],\"bias\":\"Field | Response\\n:---------------------------------------------------------------------------------------------------|:---------------\\nParticipation considerations from adversely impacted groups [protected classes](https://www.senate.ca.gov/content/protected-classes) in model design and testing: | None\\nMeasures taken to mitigate against unwanted bias: | None\",\"logo\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/llama-3_1-nemotron-70b-instruct.jpg\",\"shortDescription\":\"Llama-3.1-Nemotron-70B-Instruct is a large language model customized by NVIDIA in order to improve the helpfulness of LLM generated responses.\",\"safetyAndSecurity\":\"Field | Response\\n:---------------------------------------------------|:----------------------------------\\nModel Application(s): | Conversation, Question Answering, Summarization\\nDescribe the life-critical impact (if present). | None Known\\nUse Case Restrictions: | See https://github.com/meta-llama/llama-models/blob/main/models/llama3_1/LICENSE \\nModel and dataset restrictions: | The Principle of least privilege (PoLP) is applied limiting access for dataset generation and model development. Restrictions enforce dataset access during training, and dataset license constraints adhered to.\",\"privacy\":\"$84\",\"isReadOnly\":true,\"description\":\"$85\",\"canGuestDownload\":true,\"isPublic\":true,\"createdDate\":\"2024-10-15T16:05:16.718Z\",\"publisher\":\"nvidia\",\"displayName\":\"llama-3.1-nemotron-70b-instruct\",\"name\":\"llama-3_1-nemotron-70b-instruct\",\"explainability\":\"$86\",\"updatedDate\":\"2024-11-18T13:11:20.741Z\",\"attributes\":[{\"key\":\"AVAILABLE\",\"value\":\"true\"},{\"key\":\"PREVIEW\",\"value\":\"false\"}],\"artifactType\":\"ENDPOINT\"}},\"spec\":{\"openAPISpec\":{\"openapi\":\"3.1.0\",\"info\":{\"title\":\"NVIDIA NIM API for nvidia/llama-3.1-nemotron-70b-instruct\",\"description\":\"The NVIDIA NIM REST API. Please see https://docs.api.nvidia.com/nim/reference/nvidia-llama-3_1-nemotron-70b-instruct for more details.\",\"version\":\"1.0.0\",\"termsOfService\":\"https://www.nvidia.com/en-us/data-center/products/nvidia-ai-enterprise/eula/\",\"contact\":{\"name\":\"NVIDIA Enterprise Support\",\"url\":\"https://www.nvidia.com/en-us/support/enterprise/\"},\"license\":{\"name\":\"Llama 3.1 License\",\"url\":\"https://github.com/meta-llama/llama-models/blob/main/License/Llama3.1.txt\"}},\"servers\":[{\"url\":\"https://integrate.api.nvidia.com/v1/\"}],\"paths\":{\"/chat/completions\":{\"post\":{\"operationId\":\"create_chat_completion_v1_chat_completions_post\",\"tags\":[\"Chat\"],\"summary\":\"Creates a model response for the given chat conversation.\",\"description\":\"Given a list of messages comprising a conversation, the model will return a response. Compatible with OpenAI. See https://platform.openai.com/docs/api-reference/chat/create\",\"requestBody\":{\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ChatCompletionRequest\"}}},\"required\":true},\"responses\":{\"200\":{\"description\":\"Successful Response\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ChatCompletionResponse\"}}}},\"402\":{\"description\":\"Payment Required\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/PaymentRequiredError\"}}}},\"422\":{\"description\":\"Validation Error\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/HTTPValidationError\"}}}}},\"x-nvai-meta\":{\"name\":\"Create chat completion\",\"returns\":\"Returns a [chat completion](/docs/api-reference/chat/object) object, or a streamed sequence of [chat completion chunk](/docs/api-reference/chat/streaming) objects if the request is streamed.\\n\",\"path\":\"create\",\"examples\":[{\"name\":\"Write a limerick about the wonders of GPU computing.\",\"requestJson\":\"{\\n \\\"model\\\": \\\"nvidia/llama-3.1-nemotron-70b-instruct\\\",\\n \\\"messages\\\": [\\n {\\n \\\"role\\\": \\\"system\\\",\\n \\\"content\\\": \\\"You are a helpful assistant.\\\"\\n },\\n {\\n \\\"role\\\": \\\"user\\\",\\n \\\"content\\\": \\\"Write a limerick about the wonders of GPU computing.\\\"\\n }\\n ],\\n \\\"top_p\\\": 0.7,\\n \\\"max_tokens\\\": 1024,\\n \\\"seed\\\": 42,\\n \\\"stop\\\": null,\\n \\\"stream\\\": true\\n}\\n\",\"responseJson\":\"{\\n \\\"id\\\": \\\"id-123\\\",\\n \\\"object\\\": \\\"chat.completion\\\",\\n \\\"created\\\": 1677652288,\\n \\\"model\\\": \\\"nvidia/llama-3.1-nemotron-70b-instruct\\\",\\n \\\"system_fingerprint\\\": \\\"fp_44709d6fcb\\\",\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"Here's a short poem on...\\\"\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 9,\\n \\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"},{\"name\":\"What can I see at NVIDIA's GPU Technology Conference?\",\"requestJson\":\"{\\n \\\"model\\\": \\\"nvidia/llama-3.1-nemotron-70b-instruct\\\",\\n \\\"messages\\\": [\\n {\\n \\\"role\\\": \\\"system\\\",\\n \\\"content\\\": \\\"You are a helpful assistant.\\\"\\n },\\n {\\n \\\"role\\\": \\\"user\\\",\\n \\\"content\\\": \\\"What can I see at NVIDIA's GPU Technology Conference?\\\"\\n }\\n ],\\n \\\"top_p\\\": 0.7,\\n \\\"max_tokens\\\": 1024,\\n \\\"seed\\\": 42,\\n \\\"stop\\\": null,\\n \\\"stream\\\": true\\n}\\n\",\"responseJson\":\"{\\n \\\"id\\\": \\\"id-123\\\",\\n \\\"object\\\": \\\"chat.completion\\\",\\n \\\"created\\\": 1677652288,\\n \\\"model\\\": \\\"nvidia/llama-3.1-nemotron-70b-instruct\\\",\\n \\\"system_fingerprint\\\": \\\"fp_44709d6fcb\\\",\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"At NVIDIA's GTC conference...\\\"\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 9,\\n \\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"}],\"templates\":[{\"title\":\"No Streaming\",\"requestEjs\":{\"python\":\"from openai import OpenAI\\n\\nclient = OpenAI(\\n base_url = \\\"https://integrate.api.nvidia.com/v1\\\",\\n api_key = \\\"$NVIDIA_API_KEY\\\"\\n)\\n\\ncompletion = client.chat.completions.create(\\n model=\\\"\u003c%- request.model %\u003e\\\",\\n messages=\u003c%- JSON.stringify(request.messages) %\u003e,\\n temperature=\u003c%- request.temperature %\u003e,\\n top_p=\u003c%- request.top_p %\u003e,\\n max_tokens=\u003c%- request.max_tokens %\u003e,\\n stream=\u003c%- request.stream?.toString()[0].toUpperCase() + request.stream?.toString().slice(1) %\u003e\\n)\\n\u003c% if (request.stream) { %\u003e\\nfor chunk in completion:\\n if chunk.choices[0].delta.content is not None:\\n print(chunk.choices[0].delta.content, end=\\\"\\\")\\n\u003c% } else { %\u003e\\nprint(completion.choices[0].message)\\n\u003c% } %\u003e\\n\",\"node.js\":\"import OpenAI from 'openai';\\n\\nconst openai = new OpenAI({\\n apiKey: '$NVIDIA_API_KEY',\\n baseURL: 'https://integrate.api.nvidia.com/v1',\\n})\\n\\nasync function main() {\\n const completion = await openai.chat.completions.create({\\n model: \\\"\u003c%- request.model %\u003e\\\",\\n messages: \u003c%- JSON.stringify(request.messages) %\u003e,\\n temperature: \u003c%- request.temperature %\u003e,\\n top_p: \u003c%- request.top_p %\u003e,\\n max_tokens: \u003c%- request.max_tokens %\u003e,\\n stream: \u003c%- request.stream %\u003e,\\n })\\n \u003c% if (request.stream) { %\u003e\\n for await (const chunk of completion) {\\n process.stdout.write(chunk.choices[0]?.delta?.content || '')\\n }\\n \u003c% } else { %\u003e\\n process.stdout.write(completion.choices[0]?.message?.content);\\n \u003c% } %\u003e\\n}\\n\\nmain();\",\"curl\":\"curl https://integrate.api.nvidia.com/v1/chat/completions \\\\\\n -H \\\"Content-Type: application/json\\\" \\\\\\n -H \\\"Authorization: Bearer $NVIDIA_API_KEY\\\" \\\\\\n -d '{\\n \\\"model\\\": \\\"nvidia/llama-3.1-nemotron-70b-instruct\\\",\\n \\\"messages\\\": \u003c%- JSON.stringify(request.messages).replaceAll(\\\"'\\\", \\\"'\\\\\\\"'\\\\\\\"'\\\") %\u003e,\\n \\\"temperature\\\": \u003c%- request.temperature %\u003e, \\n \\\"top_p\\\": \u003c%- request.top_p %\u003e,\\n \\\"max_tokens\\\": \u003c%- request.max_tokens %\u003e,\\n \\\"stream\\\": \u003c%- request.stream %\u003e \\n }'\\n\"},\"response\":\"{\\n \\\"id\\\": \\\"chatcmpl-123\\\",\\n \\\"object\\\": \\\"chat.completion\\\",\\n \\\"created\\\": 1677652288,\\n \\\"model\\\": \\\"nvidia/llama-3.1-nemotron-70b-instruct\\\",\\n \\\"system_fingerprint\\\": \\\"fp_44709d6fcb\\\",\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"\\\\n\\\\nHello there, how may I assist you today?\\\",\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 9,\\n \\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"}]}}}},\"security\":[{\"Token\":[]}],\"components\":{\"securitySchemes\":{\"Token\":{\"type\":\"http\",\"scheme\":\"bearer\"}},\"schemas\":{\"ChatCompletionRequest\":{\"properties\":{\"model\":{\"type\":\"string\",\"title\":\"Model\",\"default\":\"nvidia/llama-3.1-nemotron-70b-instruct\"},\"max_tokens\":{\"type\":\"integer\",\"minimum\":1,\"title\":\"Max Tokens\",\"description\":\"The maximum number of tokens to generate in any given call. Note that the model is not aware of this value, and generation will simply stop at the number of tokens specified.\",\"default\":1024},\"stream\":{\"type\":\"boolean\",\"title\":\"Stream\",\"description\":\"If set, partial message deltas will be sent. Tokens will be sent as data-only server-sent events (SSE) as they become available (JSON responses are prefixed by `data: `), with the stream terminated by a `data: [DONE]` message.\",\"default\":false},\"temperature\":{\"type\":\"number\",\"maximum\":1,\"minimum\":0,\"title\":\"Temperature\",\"description\":\"The sampling temperature to use for text generation. The higher the temperature value is, the less deterministic the output text will be. It is not recommended to modify both temperature and top_p in the same call.\",\"default\":0.5},\"top_p\":{\"type\":\"number\",\"maximum\":1,\"exclusiveMinimum\":0,\"title\":\"Top P\",\"description\":\"The top-p sampling mass used for text generation. The top-p value determines the probability mass that is sampled at sampling time. For example, if top_p = 0.2, only the most likely tokens (summing to 0.2 cumulative probability) will be sampled. It is not recommended to modify both temperature and top_p in the same call.\",\"default\":1},\"stop\":{\"anyOf\":[{\"items\":{\"type\":\"string\"},\"type\":\"array\"},{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Stop\",\"description\":\"A string or a list of strings where the API will stop generating further tokens. The returned text will not contain the stop sequence.\",\"examples\":[null]},\"frequency_penalty\":{\"type\":\"number\",\"maximum\":2,\"minimum\":-2,\"default\":0,\"title\":\"Frequency Penalty\",\"description\":\"Indicates how much to penalize new tokens based on their existing frequency in the text so far, decreasing model likelihood to repeat the same line verbatim.\"},\"presence_penalty\":{\"type\":\"number\",\"maximum\":2,\"minimum\":-2,\"default\":0,\"title\":\"Presence Penalty\",\"description\":\"Positive values penalize new tokens based on whether they appear in the text so far, increasing model likelihood to talk about new topics.\"},\"seed\":{\"type\":\"integer\",\"maximum\":18446744073709552000,\"minimum\":0,\"title\":\"Seed\",\"description\":\"The model generates random results. Changing the input seed alone will produce a different response with similar characteristics. It is possible to reproduce results by fixing the input seed (assuming all other hyperparameters are also fixed).\",\"default\":0},\"messages\":{\"anyOf\":[{\"items\":{\"additionalProperties\":{\"type\":\"string\"},\"type\":\"object\"},\"type\":\"array\"}],\"title\":\"Messages\",\"description\":\"A list of messages comprising the conversation so far.\",\"examples\":[[{\"role\":\"user\",\"content\":\"Write a limerick about the wonders of GPU computing.\"}]]}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"messages\"],\"title\":\"ChatCompletionRequest\",\"description\":\"OpenAI ChatCompletionRequest\"},\"ChatCompletionResponse\":{\"properties\":{\"id\":{\"type\":\"string\",\"title\":\"Id\",\"description\":\"A unique identifier for the completion.\"},\"object\":{\"type\":\"string\",\"title\":\"Object\",\"default\":\"chat.completion\"},\"created\":{\"type\":\"integer\",\"title\":\"Created\"},\"model\":{\"type\":\"string\",\"title\":\"Model\",\"example\":\"nvidia/llama-3.1-nemotron-70b-instruct\"},\"choices\":{\"items\":{\"$ref\":\"#/components/schemas/ChatCompletionResponseChoice\"},\"type\":\"array\",\"title\":\"Choices\",\"description\":\"The list of completion choices the model generated for the input prompt.\"},\"usage\":{\"$ref\":\"#/components/schemas/UsageInfo\",\"description\":\"Usage statistics for the completion request.\"}},\"type\":\"object\",\"required\":[\"model\",\"choices\",\"usage\"],\"title\":\"ChatCompletionResponse\"},\"ChatCompletionResponseChoice\":{\"properties\":{\"index\":{\"type\":\"integer\",\"title\":\"Index\",\"description\":\"The index of the choice in the list of choices (always 0).\"},\"message\":{\"$ref\":\"#/components/schemas/ChatMessage\",\"description\":\"A chat completion message generated by the model.\"},\"finish_reason\":{\"anyOf\":[{\"type\":\"string\",\"enum\":[\"stop\",\"length\"]},{\"type\":\"null\"}],\"title\":\"Finish Reason\",\"description\":\"The reason the model stopped generating tokens. This will be `stop` if the model hit a natural stop point or a provided stop sequence, or `length` if the maximum number of tokens specified in the request was reached. Will be `null` if the model has not finished\"}},\"type\":\"object\",\"required\":[\"index\",\"message\"],\"title\":\"ChatCompletionResponseChoice\"},\"ChatMessage\":{\"properties\":{\"role\":{\"type\":\"string\",\"title\":\"Role\",\"description\":\"The role of the message author.\"},\"content\":{\"type\":\"string\",\"title\":\"Content\",\"description\":\"The contents of the message.\"}},\"type\":\"object\",\"required\":[\"role\",\"content\"],\"title\":\"ChatMessage\"},\"HTTPValidationError\":{\"properties\":{\"detail\":{\"items\":{\"$ref\":\"#/components/schemas/ValidationError\"},\"type\":\"array\",\"title\":\"Detail\",\"description\":\"Detailed information about the error.\"}},\"type\":\"object\",\"title\":\"HTTPValidationError\"},\"PaymentRequiredError\":{\"properties\":{\"detail\":{\"type\":\"string\",\"description\":\"Contains specific information related to the error and why it occurred.\",\"example\":\"You have reached your limit of credits.\"}},\"type\":\"object\",\"title\":\"PaymentRequiredError\"},\"UsageInfo\":{\"properties\":{\"prompt_tokens\":{\"type\":\"integer\",\"title\":\"Prompt Tokens\",\"description\":\"Number of tokens in the prompt.\",\"default\":0},\"total_tokens\":{\"type\":\"integer\",\"title\":\"Total Tokens\",\"description\":\"Total number of tokens used in the request (prompt + completion).\",\"default\":0},\"completion_tokens\":{\"anyOf\":[{\"type\":\"integer\"},{\"type\":\"null\"}],\"title\":\"Completion Tokens\",\"description\":\"Number of tokens in the generated completion.\",\"default\":0}},\"type\":\"object\",\"title\":\"UsageInfo\"},\"ValidationError\":{\"properties\":{\"loc\":{\"items\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"integer\"}]},\"type\":\"array\",\"title\":\"Location\"},\"msg\":{\"type\":\"string\",\"title\":\"Message\",\"description\":\"The error message.\"},\"type\":{\"type\":\"string\",\"title\":\"Error Type\",\"description\":\"Error type\"}},\"type\":\"object\",\"required\":[\"loc\",\"msg\",\"type\"],\"title\":\"ValidationError\"}}}},\"namespace\":\"qc69jvmznzxy\",\"updatedDate\":\"2024-11-18T13:11:21.421Z\",\"nvcfFunctionId\":\"9b96341b-9791-4db9-a00d-4e43aa192a39\",\"createdDate\":\"2024-10-15T16:05:17.117Z\",\"attributes\":{\"dockerRun\":\"Pull and run the NVIDIA NIM with the command below. This will download the optimized model for your infrastructure.\\n```bash\\nexport NGC_API_KEY=\u003cPASTE_API_KEY_HERE\u003e\\nexport LOCAL_NIM_CACHE=~/.cache/nim\\nmkdir -p \\\"$LOCAL_NIM_CACHE\\\"\\ndocker run -it --rm \\\\\\n --gpus all \\\\\\n --shm-size=16GB \\\\\\n -e NGC_API_KEY \\\\\\n -v \\\"$LOCAL_NIM_CACHE:/opt/nim/.cache\\\" \\\\\\n -u $(id -u) \\\\\\n -p 8000:8000 \\\\\\n nvcr.io/nim/nvidia/llama-3.1-nemotron-70b-instruct:latest\\n```\\n\\nYou can now make a local API call using this curl command:\\n```bash\\ncurl -X 'POST' \\\\\\n'http://0.0.0.0:8000/v1/chat/completions' \\\\\\n-H 'accept: application/json' \\\\\\n-H 'Content-Type: application/json' \\\\\\n-d '{\\n \\\"model\\\": \\\"nvidia/llama-3.1-nemotron-70b-instruct\\\",\\n \\\"messages\\\": [{\\\"role\\\":\\\"user\\\", \\\"content\\\":\\\"Write a limerick about the wonders of GPU computing.\\\"}],\\n \\\"max_tokens\\\": 64\\n}'\\n```\\n\\nFor more details on getting started with this NIM, visit the [NVIDIA NIM Docs](https://docs.nvidia.com/nim/large-language-models/latest/getting-started.html).\\n\",\"dockerTermsOfUse\":\"By running the below commands, you accept the \u003ca href=\\\"https://www.nvidia.com/en-us/data-center/products/nvidia-ai-enterprise/eula/\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA AI Enterprise Terms of Use\u003c/a\u003e and the \u003ca href=\\\"https://docs.nvidia.com/ai-foundation-models-community-license.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA Community Models License\u003c/a\u003e.\\n\",\"showUnavailableBanner\":false,\"apiDocsUrl\":\"https://docs.api.nvidia.com/nim/reference/nvidia-llama-3_1-nemotron-70b-instruct\",\"playground\":{\"type\":\"chat\"},\"termsOfUse\":\"\u003cb\u003eGOVERNING TERMS\u003c/b\u003e: This trial service is governed by the \u003ca href=\\\"https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA API Trial Terms of Service\u003c/a\u003e. Use of this model is governed by the \u003ca href=\\\"https://docs.nvidia.com/ai-foundation-models-community-license.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003e AI Foundation Models Community License Agreement \u003c/a\u003e. ADDITIONAL INFORMATION: Llama 3.1 Community License Agreement, Built with Llama.\\n\",\"cta\":{\"text\":\"Apply to Self-Host\",\"url\":\"https://www.nvidia.com/en-us/ai/nim-notifyme/\",\"nim_available_override_url\":\"https://catalog.ngc.nvidia.com/orgs/nim/teams/nvidia/containers/llama-3.1-nemotron-70b-instruct\"}},\"artifactName\":\"llama-3_1-nemotron-70b-instruct\"},\"config\":{\"name\":\"llama-3_1-nemotron-70b-instruct\",\"type\":\"model\"}},{\"endpoint\":{\"requestStatus\":{\"statusCode\":\"SUCCESS\",\"requestId\":\"1a6f165e-4f73-4952-8299-34838db428e2\"},\"artifact\":{\"orgName\":\"qc69jvmznzxy\",\"labels\":[\"AI Weather Prediction\",\"Earth-2\",\"Weather Simulation\"],\"bias\":\"Field | Response\\n:---------------------------------------------------------------------------------------------------|:---------------\\nParticipation considerations from adversely impacted groups [protected classes](https://www.senate.ca.gov/content/protected-classes) in model design and testing: | None of the Above\\nMeasures taken to mitigate against unwanted bias: | None\",\"logo\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/corrdiff.jpg\",\"shortDescription\":\"Generative downscaling model for generating high resolution regional scale weather fields.\",\"safetyAndSecurity\":\"Field | Response\\n:---------------------------------------------------|:----------------------------------\\nModel Application(s): | Regional Weather Downscaling\\nDescribe the life critical impact (if present). | None Known\\nUse Case Restrictions: | Abide by [NVIDIA Earth-2 Cloud API Agreement](https://ngc.nvidia.com/legal/terms).\\nModel and dataset restrictions: | The Principle of least privilege (PoLP) is applied limiting access for dataset generation and model development. 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\\\"content\\\": \\\"At NVIDIA's GTC conference...\\\"\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 9,\\n \\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"}],\"templates\":[{\"title\":\"No Streaming\",\"requestEjs\":{\"python\":\"from openai import OpenAI\\n\\nclient = OpenAI(\\n base_url = \\\"https://integrate.api.nvidia.com/v1\\\",\\n api_key = \\\"$NVIDIA_API_KEY\\\"\\n)\\n\\ncompletion = client.chat.completions.create(\\n model=\\\"\u003c%- request.model %\u003e\\\",\\n messages=\u003c%- JSON.stringify(request.messages) %\u003e,\\n temperature=\u003c%- request.temperature %\u003e,\\n top_p=\u003c%- request.top_p %\u003e,\\n max_tokens=\u003c%- request.max_tokens %\u003e,\\n stream=\u003c%- request.stream?.toString()[0].toUpperCase() + request.stream?.toString().slice(1) %\u003e\\n)\\n\u003c% if (request.stream) { %\u003e\\nfor chunk in completion:\\n if chunk.choices[0].delta.content is not None:\\n print(chunk.choices[0].delta.content, end=\\\"\\\")\\n\u003c% } else { %\u003e\\nprint(completion.choices[0].message)\\n\u003c% } %\u003e\\n\",\"node.js\":\"import OpenAI from 'openai';\\n\\nconst openai = new OpenAI({\\n apiKey: '$NVIDIA_API_KEY',\\n baseURL: 'https://integrate.api.nvidia.com/v1',\\n})\\n\\nasync function main() {\\n const completion = await openai.chat.completions.create({\\n model: \\\"\u003c%- request.model %\u003e\\\",\\n messages: \u003c%- JSON.stringify(request.messages) %\u003e,\\n temperature: \u003c%- request.temperature %\u003e,\\n top_p: \u003c%- request.top_p %\u003e,\\n max_tokens: \u003c%- request.max_tokens %\u003e,\\n stream: \u003c%- request.stream %\u003e,\\n })\\n \u003c% if (request.stream) { %\u003e\\n for await (const chunk of completion) {\\n process.stdout.write(chunk.choices[0]?.delta?.content || '')\\n }\\n \u003c% } else { %\u003e\\n process.stdout.write(completion.choices[0]?.message?.content);\\n \u003c% } %\u003e\\n}\\n\\nmain();\",\"curl\":\"curl https://integrate.api.nvidia.com/v1/chat/completions \\\\\\n -H \\\"Content-Type: application/json\\\" \\\\\\n -H \\\"Authorization: Bearer $NVIDIA_API_KEY\\\" \\\\\\n -d '{\\n \\\"model\\\": \\\"nvidia/llama-3.1-nemotron-70b-instruct\\\",\\n \\\"messages\\\": \u003c%- JSON.stringify(request.messages).replaceAll(\\\"'\\\", \\\"'\\\\\\\"'\\\\\\\"'\\\") %\u003e,\\n \\\"temperature\\\": \u003c%- request.temperature %\u003e, \\n \\\"top_p\\\": \u003c%- request.top_p %\u003e,\\n \\\"max_tokens\\\": \u003c%- request.max_tokens %\u003e,\\n \\\"stream\\\": \u003c%- request.stream %\u003e \\n }'\\n\"},\"response\":\"{\\n \\\"id\\\": \\\"chatcmpl-123\\\",\\n \\\"object\\\": \\\"chat.completion\\\",\\n \\\"created\\\": 1677652288,\\n \\\"model\\\": \\\"nvidia/llama-3.1-nemotron-70b-instruct\\\",\\n \\\"system_fingerprint\\\": \\\"fp_44709d6fcb\\\",\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"\\\\n\\\\nHello there, how may I assist you today?\\\",\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 9,\\n \\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"}]}}}},\"security\":[{\"Token\":[]}],\"components\":{\"securitySchemes\":{\"Token\":{\"type\":\"http\",\"scheme\":\"bearer\"}},\"schemas\":{\"ChatCompletionRequest\":{\"properties\":{\"model\":{\"type\":\"string\",\"title\":\"Model\",\"default\":\"nvidia/llama-3.1-nemotron-70b-instruct\"},\"max_tokens\":{\"type\":\"integer\",\"minimum\":1,\"title\":\"Max Tokens\",\"description\":\"The maximum number of tokens to generate in any given call. Note that the model is not aware of this value, and generation will simply stop at the number of tokens specified.\",\"default\":1024},\"stream\":{\"type\":\"boolean\",\"title\":\"Stream\",\"description\":\"If set, partial message deltas will be sent. Tokens will be sent as data-only server-sent events (SSE) as they become available (JSON responses are prefixed by `data: `), with the stream terminated by a `data: [DONE]` message.\",\"default\":false},\"temperature\":{\"type\":\"number\",\"maximum\":1,\"minimum\":0,\"title\":\"Temperature\",\"description\":\"The sampling temperature to use for text generation. The higher the temperature value is, the less deterministic the output text will be. It is not recommended to modify both temperature and top_p in the same call.\",\"default\":0.5},\"top_p\":{\"type\":\"number\",\"maximum\":1,\"exclusiveMinimum\":0,\"title\":\"Top P\",\"description\":\"The top-p sampling mass used for text generation. The top-p value determines the probability mass that is sampled at sampling time. For example, if top_p = 0.2, only the most likely tokens (summing to 0.2 cumulative probability) will be sampled. It is not recommended to modify both temperature and top_p in the same call.\",\"default\":1},\"stop\":{\"anyOf\":[{\"items\":{\"type\":\"string\"},\"type\":\"array\"},{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Stop\",\"description\":\"A string or a list of strings where the API will stop generating further tokens. The returned text will not contain the stop sequence.\",\"examples\":[null]},\"frequency_penalty\":{\"type\":\"number\",\"maximum\":2,\"minimum\":-2,\"default\":0,\"title\":\"Frequency Penalty\",\"description\":\"Indicates how much to penalize new tokens based on their existing frequency in the text so far, decreasing model likelihood to repeat the same line verbatim.\"},\"presence_penalty\":{\"type\":\"number\",\"maximum\":2,\"minimum\":-2,\"default\":0,\"title\":\"Presence Penalty\",\"description\":\"Positive values penalize new tokens based on whether they appear in the text so far, increasing model likelihood to talk about new topics.\"},\"seed\":{\"type\":\"integer\",\"maximum\":18446744073709552000,\"minimum\":0,\"title\":\"Seed\",\"description\":\"The model generates random results. Changing the input seed alone will produce a different response with similar characteristics. It is possible to reproduce results by fixing the input seed (assuming all other hyperparameters are also fixed).\",\"default\":0},\"messages\":{\"anyOf\":[{\"items\":{\"additionalProperties\":{\"type\":\"string\"},\"type\":\"object\"},\"type\":\"array\"}],\"title\":\"Messages\",\"description\":\"A list of messages comprising the conversation so far.\",\"examples\":[[{\"role\":\"user\",\"content\":\"Write a limerick about the wonders of GPU computing.\"}]]}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"messages\"],\"title\":\"ChatCompletionRequest\",\"description\":\"OpenAI ChatCompletionRequest\"},\"ChatCompletionResponse\":{\"properties\":{\"id\":{\"type\":\"string\",\"title\":\"Id\",\"description\":\"A unique identifier for the completion.\"},\"object\":{\"type\":\"string\",\"title\":\"Object\",\"default\":\"chat.completion\"},\"created\":{\"type\":\"integer\",\"title\":\"Created\"},\"model\":{\"type\":\"string\",\"title\":\"Model\",\"example\":\"nvidia/llama-3.1-nemotron-70b-instruct\"},\"choices\":{\"items\":{\"$ref\":\"#/components/schemas/ChatCompletionResponseChoice\"},\"type\":\"array\",\"title\":\"Choices\",\"description\":\"The list of completion choices the model generated for the input prompt.\"},\"usage\":{\"$ref\":\"#/components/schemas/UsageInfo\",\"description\":\"Usage statistics for the completion request.\"}},\"type\":\"object\",\"required\":[\"model\",\"choices\",\"usage\"],\"title\":\"ChatCompletionResponse\"},\"ChatCompletionResponseChoice\":{\"properties\":{\"index\":{\"type\":\"integer\",\"title\":\"Index\",\"description\":\"The index of the choice in the list of choices (always 0).\"},\"message\":{\"$ref\":\"#/components/schemas/ChatMessage\",\"description\":\"A chat completion message generated by the model.\"},\"finish_reason\":{\"anyOf\":[{\"type\":\"string\",\"enum\":[\"stop\",\"length\"]},{\"type\":\"null\"}],\"title\":\"Finish Reason\",\"description\":\"The reason the model stopped generating tokens. This will be `stop` if the model hit a natural stop point or a provided stop sequence, or `length` if the maximum number of tokens specified in the request was reached. Will be `null` if the model has not finished\"}},\"type\":\"object\",\"required\":[\"index\",\"message\"],\"title\":\"ChatCompletionResponseChoice\"},\"ChatMessage\":{\"properties\":{\"role\":{\"type\":\"string\",\"title\":\"Role\",\"description\":\"The role of the message author.\"},\"content\":{\"type\":\"string\",\"title\":\"Content\",\"description\":\"The contents of the message.\"}},\"type\":\"object\",\"required\":[\"role\",\"content\"],\"title\":\"ChatMessage\"},\"HTTPValidationError\":{\"properties\":{\"detail\":{\"items\":{\"$ref\":\"#/components/schemas/ValidationError\"},\"type\":\"array\",\"title\":\"Detail\",\"description\":\"Detailed information about the error.\"}},\"type\":\"object\",\"title\":\"HTTPValidationError\"},\"PaymentRequiredError\":{\"properties\":{\"detail\":{\"type\":\"string\",\"description\":\"Contains specific information related to the error and why it occurred.\",\"example\":\"You have reached your limit of credits.\"}},\"type\":\"object\",\"title\":\"PaymentRequiredError\"},\"UsageInfo\":{\"properties\":{\"prompt_tokens\":{\"type\":\"integer\",\"title\":\"Prompt Tokens\",\"description\":\"Number of tokens in the prompt.\",\"default\":0},\"total_tokens\":{\"type\":\"integer\",\"title\":\"Total Tokens\",\"description\":\"Total number of tokens used in the request (prompt + completion).\",\"default\":0},\"completion_tokens\":{\"anyOf\":[{\"type\":\"integer\"},{\"type\":\"null\"}],\"title\":\"Completion Tokens\",\"description\":\"Number of tokens in the generated completion.\",\"default\":0}},\"type\":\"object\",\"title\":\"UsageInfo\"},\"ValidationError\":{\"properties\":{\"loc\":{\"items\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"integer\"}]},\"type\":\"array\",\"title\":\"Location\"},\"msg\":{\"type\":\"string\",\"title\":\"Message\",\"description\":\"The error message.\"},\"type\":{\"type\":\"string\",\"title\":\"Error Type\",\"description\":\"Error type\"}},\"type\":\"object\",\"required\":[\"loc\",\"msg\",\"type\"],\"title\":\"ValidationError\"}}}},\"namespace\":\"qc69jvmznzxy\",\"updatedDate\":\"2024-11-18T13:11:21.421Z\",\"nvcfFunctionId\":\"9b96341b-9791-4db9-a00d-4e43aa192a39\",\"createdDate\":\"2024-10-15T16:05:17.117Z\",\"attributes\":{\"dockerRun\":\"Pull and run the NVIDIA NIM with the command below. This will download the optimized model for your infrastructure.\\n```bash\\nexport NGC_API_KEY=\u003cPASTE_API_KEY_HERE\u003e\\nexport LOCAL_NIM_CACHE=~/.cache/nim\\nmkdir -p \\\"$LOCAL_NIM_CACHE\\\"\\ndocker run -it --rm \\\\\\n --gpus all \\\\\\n --shm-size=16GB \\\\\\n -e NGC_API_KEY \\\\\\n -v \\\"$LOCAL_NIM_CACHE:/opt/nim/.cache\\\" \\\\\\n -u $(id -u) \\\\\\n -p 8000:8000 \\\\\\n nvcr.io/nim/nvidia/llama-3.1-nemotron-70b-instruct:latest\\n```\\n\\nYou can now make a local API call using this curl command:\\n```bash\\ncurl -X 'POST' \\\\\\n'http://0.0.0.0:8000/v1/chat/completions' \\\\\\n-H 'accept: application/json' \\\\\\n-H 'Content-Type: application/json' \\\\\\n-d '{\\n \\\"model\\\": \\\"nvidia/llama-3.1-nemotron-70b-instruct\\\",\\n \\\"messages\\\": [{\\\"role\\\":\\\"user\\\", \\\"content\\\":\\\"Write a limerick about the wonders of GPU computing.\\\"}],\\n \\\"max_tokens\\\": 64\\n}'\\n```\\n\\nFor more details on getting started with this NIM, visit the [NVIDIA NIM Docs](https://docs.nvidia.com/nim/large-language-models/latest/getting-started.html).\\n\",\"dockerTermsOfUse\":\"By running the below commands, you accept the \u003ca href=\\\"https://www.nvidia.com/en-us/data-center/products/nvidia-ai-enterprise/eula/\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA AI Enterprise Terms of Use\u003c/a\u003e and the \u003ca href=\\\"https://docs.nvidia.com/ai-foundation-models-community-license.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA Community Models License\u003c/a\u003e.\\n\",\"showUnavailableBanner\":false,\"apiDocsUrl\":\"https://docs.api.nvidia.com/nim/reference/nvidia-llama-3_1-nemotron-70b-instruct\",\"playground\":{\"type\":\"chat\"},\"termsOfUse\":\"\u003cb\u003eGOVERNING TERMS\u003c/b\u003e: This trial service is governed by the \u003ca href=\\\"https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA API Trial Terms of Service\u003c/a\u003e. Use of this model is governed by the \u003ca href=\\\"https://docs.nvidia.com/ai-foundation-models-community-license.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003e AI Foundation Models Community License Agreement \u003c/a\u003e. ADDITIONAL INFORMATION: Llama 3.1 Community License Agreement, Built with Llama.\\n\",\"cta\":{\"text\":\"Apply to Self-Host\",\"url\":\"https://www.nvidia.com/en-us/ai/nim-notifyme/\",\"nim_available_override_url\":\"https://catalog.ngc.nvidia.com/orgs/nim/teams/nvidia/containers/llama-3.1-nemotron-70b-instruct\"}},\"artifactName\":\"llama-3_1-nemotron-70b-instruct\"},\"config\":{\"orgName\":\"qc69jvmznzxy\",\"resourceId\":\"qc69jvmznzxy/llama-3_1-nemotron-70b-instruct\",\"labels\":[{\"values\":[\"Code Generation\",\"Chat\",\"Text-to-Text\",\"Language Generation\"],\"key\":\"general\"},{\"values\":[\"nvidia\"],\"key\":\"publisher\"}],\"sharedWithTeams\":[],\"msgTimestamp\":1731935482539,\"dateModified\":\"2024-11-18T13:11:20.741Z\",\"sharedWithOrgs\":[\"qc69jvmznzxy\"],\"description\":\"Llama-3.1-Nemotron-70B-Instruct is a large language model customized by NVIDIA in order to improve the helpfulness of LLM generated responses.\",\"isPublic\":true,\"dateCreated\":\"2024-10-15T16:05:16.718Z\",\"createdBy\":\"fhi3d0ktjp1si0mr5oie4kej7a\",\"displayName\":\"llama-3.1-nemotron-70b-instruct\",\"name\":\"llama-3_1-nemotron-70b-instruct\",\"resourceType\":\"ENDPOINT\",\"attributes\":[{\"key\":\"logo\",\"value\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/llama-3_1-nemotron-70b-instruct.jpg\"}],\"guestAccess\":true,\"type\":\"model\"}},{\"endpoint\":{\"requestStatus\":{\"statusCode\":\"SUCCESS\",\"requestId\":\"9e682d60-2b24-4d96-96d6-9ddfba9fbfc0\"},\"artifact\":{\"orgName\":\"qc69jvmznzxy\",\"labels\":[\"Biology\",\"Bionemo\",\"Drug Discovery\",\"Protein Folding\"],\"logo\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/alphafold2-multimer.jpg\",\"shortDescription\":\"Predicts the 3D structure of a protein from its amino acid sequence.\",\"isReadOnly\":true,\"description\":\"$95\",\"canGuestDownload\":true,\"isPublic\":true,\"createdDate\":\"2024-09-11T19:40:59.897Z\",\"publisher\":\"deepmind\",\"displayName\":\"alphafold2-multimer\",\"name\":\"alphafold2-multimer\",\"updatedDate\":\"2024-11-20T17:25:50.979Z\",\"attributes\":[{\"key\":\"AVAILABLE\",\"value\":\"true\"},{\"key\":\"PREVIEW\",\"value\":\"false\"}],\"artifactType\":\"ENDPOINT\"}},\"spec\":{\"openAPISpec\":{\"openapi\":\"3.1.0\",\"info\":{\"contact\":{\"name\":\"NVIDIA Support\",\"url\":\"https://help.nvidia.com/\"},\"description\":\"The NVIDIA NIM REST API. Please see https://docs.nvidia.com/nim/api-reference for more details.\",\"license\":{\"name\":\"Apache License 2.0\",\"url\":\"https://github.com/google-deepmind/alphafold/blob/main/LICENSE\"},\"termsOfService\":\"https://nvidia.com/legal/terms-of-use\",\"title\":\"NVIDIA NIM API for AlphaFold-2\",\"version\":\"1.0.0\"},\"servers\":[{\"url\":\"https://health.api.nvidia.com/v1/\"}],\"paths\":{\"/protein-structure/alphafold2/multimer/predict-structure-from-sequences\":{\"post\":{\"summary\":\"Nim Api Post Call Protein Structure Alphafold2 Predict Structure From Sequence Post\",\"operationId\":\"nim_api_post_call_protein_structure_alphafold2_multimer_predict_structure_from_sequences_post\",\"requestBody\":{\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/AlphaFold2MultimerSeqsToStructInputs\"}}},\"required\":true},\"responses\":{\"200\":{\"description\":\"Successful Response\",\"content\":{\"application/json\":{\"schema\":{\"title\":\"Response Nim Api Post Call Protein Structure Alphafold2 Predict Structure From Sequence Post Protein Structure Alphafold2 Predict Structure From Sequence Post\"}}}},\"422\":{\"description\":\"Validation Error\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/HTTPValidationError\"}}}}},\"x-nvai-meta\":{\"name\":\"Generate protein structures from amino acid sequences.\",\"returns\":\"Returns predicted structures.\",\"path\":\"predict-structure-from-sequences\",\"templates\":[{\"title\":\"Synchronous Requests\",\"requestEjs\":{\"curl\":\"$96\",\"python\":\"$97\"}}]}}}},\"components\":{\"schemas\":{\"AlphaFold2MultimerSeqsToStructInputs\":{\"properties\":{\"sequences\":{\"type\":\"array\",\"items\":{\"type\":\"string\",\"maxLength\":4096,\"minLength\":1,\"pattern\":\"^[ARNDCQEGHILKMFPSTWYV]+\"},\"maxItems\":6,\"minItems\":1,\"title\":\"Input Polypeptide Sequence\",\"description\":\"An input polypeptide (i.e., amino acid) sequence that must be composed of valid Amino Acid IUPAC symbols.\",\"tooltip\":\"The input sequence for structural prediction.\"},\"algorithm\":{\"type\":\"string\",\"enum\":[\"jackhmmer\",\"mmseqs2\"],\"title\":\"MSA Algorithm\",\"description\":\"The algorithm to use for MSA. AlphaFold2 was trained on JackHMMer; MMSeqs2 provides faster inference. (MMSeqs2 will be supported in a future version of AlphaFold2 NIM!)\",\"default\":\"jackhmmer\",\"tooltip\":\"MSA Algorithm used for generating model MSA features.\"},\"bit_score\":{\"anyOf\":[{\"type\":\"number\",\"exclusiveMinimum\":0},{\"type\":\"null\"}],\"title\":\"MSA BitScore\",\"description\":\"Sequence Bit Score cutoff for filtering sequences used in seeding the Multiple Sequence Alignment. Bit score must be \u003e 0 or NULL. Note: If this value is unset, e-value is ignored.\",\"tooltip\":\"Sequence Bit Score Threshold\",\"default\":null},\"databases\":{\"items\":{\"type\":\"string\"},\"type\":\"array\",\"maxItems\":3,\"minItems\":1,\"title\":\"MSA Databases\",\"description\":\"Databases used for Multiple Sequence Alignment. By default, uniref90, mgnify, and small_bfd are used. Choice of databases(s) can significantly impact downstream structure prediction, so we recommend modifying carefully.\",\"default\":[\"uniref90\",\"mgnfiy\",\"small_bfd\"],\"tooltip\":\"Sequence databases used for Multiple Sequence Alignment.\"},\"e_value\":{\"type\":\"number\",\"maximum\":10,\"exclusiveMinimum\":0,\"title\":\"MSA e-value.\",\"description\":\"The e-value used for filtering hits when building the Multiple Sequence Alignment. Takes values between 0 \u003c x \u003c= 10.\",\"default\":0.0001,\"tooltip\":\"Sequence e-value for filtering sequences seeding the MSA.\"},\"iterations\":{\"type\":\"integer\",\"minimum\":1,\"title\":\"MSA Iterations\",\"description\":\"The number of MSA iterations to perform.\",\"default\":1,\"tooltip\":\"The number of iterations performed by the MSA algorithm.\"},\"relax_prediction\":{\"type\":\"boolean\",\"title\":\"Relax Prediction\",\"description\":\"Run structural relaxation after prediction\",\"default\":true,\"tooltip\":\"Relax the predicted structure using AMBER.\"},\"structure_models_to_relax\":{\"type\":\"string\",\"enum\":[\"all\",\"best\",\"none\"],\"title\":\"Models to relax\",\"description\":\"Which structural prediction to relax with AMBER. Default: Relax 'all' models.\",\"default\":\"all\",\"tooltip\":\"Which models to relax with AMBER\"},\"num_predictions_per_model\":{\"type\":\"integer\",\"maximum\":8,\"minimum\":1,\"title\":\"Number of Predictions per Model\",\"description\":\"Determines the number of times the trunk of the network is run with different random MSA cluster centers.\",\"default\":1,\"tooltip\":\"The cycling resampling setting for MSA clusters in the AlphaFold network trunk.\"},\"max_msa_sequences\":{\"anyOf\":[{\"type\":\"integer\",\"maximum\":100000,\"minimum\":1},{\"type\":\"null\"}],\"default\":null,\"title\":\"Maximum MSA Sequences\",\"description\":\"The maximum sequences taken from the MSA for model prediction.\",\"tooltip\":\"Maximum number of MSA sequences used for structural prediction.\"},\"template_searcher\":{\"type\":\"string\",\"enum\":[\"hhsearch\",\"hmmsearch\"],\"title\":\"Template Search Program\",\"description\":\"The template searcher to use for templating. hmmsearch should be used for multimer; 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and the use of this model is governed by the \u003ca href=\\\"https://huggingface.co/datasets/choosealicense/licenses/blob/main/markdown/apache-2.0.md\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eApache 2.0 License\u003c/a\u003e.\\n\",\"cta\":{\"text\":\"Build with this NIM\",\"url\":\"https://www.nvidia.com/en-us/ai/nim-notifyme/\",\"nim_available_override_url\":\"https://catalog.ngc.nvidia.com/orgs/nim/teams/deepmind/containers/alphafold2-multimer\"},\"projects\":[{\"name\":\"BioNemo Examples\",\"url\":\"https://github.com/NVIDIA/BioNeMo/tree/main/examples/nims\",\"imageUrl\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/github-logo.jpg\",\"workbench\":false}]},\"artifactName\":\"alphafold2-multimer\"},\"config\":{\"orgName\":\"qc69jvmznzxy\",\"resourceId\":\"qc69jvmznzxy/alphafold2-multimer\",\"labels\":[{\"values\":[\"Bionemo\",\"Biology\",\"Drug Discovery\",\"Protein Folding\"],\"key\":\"general\"},{\"values\":[\"deepmind\"],\"key\":\"publisher\"}],\"sharedWithTeams\":[],\"msgTimestamp\":1732123552787,\"dateModified\":\"2024-11-20T17:25:50.979Z\",\"sharedWithOrgs\":[\"qc69jvmznzxy\"],\"description\":\"Predicts the 3D structure of a protein from its amino acid sequence.\",\"isPublic\":true,\"dateCreated\":\"2024-09-11T19:40:59.897Z\",\"createdBy\":\"fhi3d0ktjp1si0mr5oie4kej7a\",\"displayName\":\"alphafold2-multimer\",\"name\":\"alphafold2-multimer\",\"resourceType\":\"ENDPOINT\",\"attributes\":[{\"key\":\"logo\",\"value\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/alphafold2-multimer.jpg\"}],\"guestAccess\":true,\"type\":\"model\"}},{\"endpoint\":{\"requestStatus\":{\"statusCode\":\"SUCCESS\",\"requestId\":\"5676c418-f0dc-419a-b4e1-285dd32bb4ef\"},\"artifact\":{\"orgName\":\"qc69jvmznzxy\",\"labels\":[\"Biology\",\"Bionemo\",\"Drug Discovery\",\"Protein Folding\"],\"logo\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/alphafold2.jpg\",\"shortDescription\":\"Predicts the 3D structure of a protein from its amino acid sequence.\",\"isReadOnly\":true,\"description\":\"$99\",\"canGuestDownload\":true,\"isPublic\":true,\"createdDate\":\"2024-08-27T12:37:14.685Z\",\"publisher\":\"deepmind\",\"displayName\":\"alphafold2\",\"name\":\"alphafold2\",\"updatedDate\":\"2024-11-18T22:02:15.848Z\",\"attributes\":[{\"key\":\"AVAILABLE\",\"value\":\"true\"},{\"key\":\"PREVIEW\",\"value\":\"true\"}],\"artifactType\":\"ENDPOINT\"}},\"spec\":{\"openAPISpec\":{\"openapi\":\"3.1.0\",\"info\":{\"title\":\"NVIDIA NIM API for AlphaFold2\",\"description\":\"The NVIDIA NIM REST API for AlphaFold2, a deep learning model for protein structural prediction. 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Note that the model is not aware of this value, and generation will simply stop at the number of tokens specified.\",\"default\":1024},\"stream\":{\"type\":\"boolean\",\"title\":\"Stream\",\"description\":\"If set, partial message deltas will be sent. Tokens will be sent as data-only server-sent events (SSE) as they become available (JSON responses are prefixed by `data: `), with the stream terminated by a `data: [DONE]` message.\",\"default\":false},\"temperature\":{\"type\":\"number\",\"maximum\":1,\"minimum\":0,\"title\":\"Temperature\",\"description\":\"The sampling temperature to use for text generation. The higher the temperature value is, the less deterministic the output text will be. It is not recommended to modify both temperature and top_p in the same call.\",\"default\":0.5},\"top_p\":{\"type\":\"number\",\"maximum\":1,\"minimum\":0,\"title\":\"Top P\",\"description\":\"The top-p sampling mass used for text generation. The top-p value determines the probability mass that is sampled at sampling time. For example, if top_p = 0.2, only the most likely tokens (summing to 0.2 cumulative probability) will be sampled. It is not recommended to modify both temperature and top_p in the same call.\",\"default\":1},\"stop\":{\"anyOf\":[{\"items\":{\"type\":\"string\"},\"type\":\"array\"},{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Stop\",\"description\":\"A string or a list of strings where the API will stop generating further tokens. The returned text will not contain the stop sequence.\",\"examples\":[null]},\"frequency_penalty\":{\"type\":\"number\",\"maximum\":2,\"minimum\":-2,\"default\":0,\"title\":\"Frequency Penalty\",\"description\":\"Indicates how much to penalize new tokens based on their existing frequency in the text so far, decreasing model likelihood to repeat the same line verbatim.\"},\"presence_penalty\":{\"type\":\"number\",\"maximum\":2,\"minimum\":-2,\"default\":0,\"title\":\"Presence Penalty\",\"description\":\"Positive values penalize new tokens based on whether they appear in the text so far, increasing model likelihood to talk about new topics.\"},\"seed\":{\"type\":\"integer\",\"maximum\":18446744073709552000,\"minimum\":0,\"title\":\"Seed\",\"description\":\"The model generates random results. Changing the input seed alone will produce a different response with similar characteristics. It is possible to reproduce results by fixing the input seed (assuming all other hyperparameters are also fixed).\",\"default\":0},\"messages\":{\"anyOf\":[{\"type\":\"string\"},{\"items\":{\"additionalProperties\":{\"type\":\"string\"},\"type\":\"object\"},\"type\":\"array\"}],\"title\":\"Messages\",\"description\":\"A list of messages comprising the conversation so far.\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"messages\"],\"title\":\"ChatCompletionRequest\",\"description\":\"OpenAI ChatCompletionRequest\"},\"ChatCompletionResponse\":{\"properties\":{\"id\":{\"type\":\"string\",\"title\":\"Id\",\"description\":\"A unique identifier for the completion.\"},\"object\":{\"type\":\"string\",\"title\":\"Object\",\"default\":\"chat.completion\"},\"created\":{\"type\":\"integer\",\"title\":\"Created\"},\"model\":{\"type\":\"string\",\"title\":\"Model\",\"example\":\"yentinglin/llama-3-taiwan-70b-instruct\"},\"choices\":{\"items\":{\"$ref\":\"#/components/schemas/ChatCompletionResponseChoice\"},\"type\":\"array\",\"title\":\"Choices\",\"description\":\"The list of completion choices the model generated for the input prompt.\"},\"usage\":{\"$ref\":\"#/components/schemas/UsageInfo\",\"description\":\"Usage statistics for the completion request.\"}},\"type\":\"object\",\"required\":[\"model\",\"choices\",\"usage\"],\"title\":\"ChatCompletionResponse\"},\"ChatCompletionResponseChoice\":{\"properties\":{\"index\":{\"type\":\"integer\",\"title\":\"Index\",\"description\":\"The index of the choice in the list of choices (always 0).\"},\"message\":{\"$ref\":\"#/components/schemas/ChatMessage\",\"description\":\"A chat completion message generated by the model.\"},\"finish_reason\":{\"anyOf\":[{\"type\":\"string\",\"enum\":[\"stop\",\"length\"]},{\"type\":\"null\"}],\"title\":\"Finish Reason\",\"description\":\"The reason the model stopped generating tokens. This will be `stop` if the model hit a natural stop point or a provided stop sequence, or `length` if the maximum number of tokens specified in the request was reached. Will be `null` if the model has not finished\"}},\"type\":\"object\",\"required\":[\"index\",\"message\"],\"title\":\"ChatCompletionResponseChoice\"},\"ChatMessage\":{\"properties\":{\"role\":{\"type\":\"string\",\"title\":\"Role\",\"description\":\"The role of the message author.\"},\"content\":{\"type\":\"string\",\"title\":\"Content\",\"description\":\"The contents of the message.\"}},\"type\":\"object\",\"required\":[\"role\",\"content\"],\"title\":\"ChatMessage\"},\"HTTPValidationError\":{\"properties\":{\"detail\":{\"items\":{\"$ref\":\"#/components/schemas/ValidationError\"},\"type\":\"array\",\"title\":\"Detail\",\"description\":\"Detailed information about the error.\"}},\"type\":\"object\",\"title\":\"HTTPValidationError\"},\"PaymentRequiredError\":{\"properties\":{\"detail\":{\"type\":\"string\",\"description\":\"Contains specific information related to the error and why it occurred.\",\"example\":\"You have reached your limit of credits.\"}},\"type\":\"object\",\"title\":\"PaymentRequiredError\"},\"UsageInfo\":{\"properties\":{\"prompt_tokens\":{\"type\":\"integer\",\"title\":\"Prompt Tokens\",\"description\":\"Number of tokens in the prompt.\",\"default\":0},\"total_tokens\":{\"type\":\"integer\",\"title\":\"Total Tokens\",\"description\":\"Total number of tokens used in the request (prompt + completion).\",\"default\":0},\"completion_tokens\":{\"anyOf\":[{\"type\":\"integer\"},{\"type\":\"null\"}],\"title\":\"Completion Tokens\",\"description\":\"Number of tokens in the generated completion.\",\"default\":0}},\"type\":\"object\",\"title\":\"UsageInfo\"},\"ValidationError\":{\"properties\":{\"loc\":{\"items\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"integer\"}]},\"type\":\"array\",\"title\":\"Location\"},\"msg\":{\"type\":\"string\",\"title\":\"Message\",\"description\":\"The error message.\"},\"type\":{\"type\":\"string\",\"title\":\"Error Type\",\"description\":\"Error type\"}},\"type\":\"object\",\"required\":[\"loc\",\"msg\",\"type\"],\"title\":\"ValidationError\"}}}},\"namespace\":\"qc69jvmznzxy\",\"updatedDate\":\"2024-11-18T22:31:30.115Z\",\"nvcfFunctionId\":\"9572a08b-4cc1-4bd6-91e0-acb7fdb5c45d\",\"createdDate\":\"2024-08-23T10:45:01.990Z\",\"attributes\":{\"dockerRun\":\"Pull and run the NVIDIA NIM with the command below. This will download the optimized model for your infrastructure.\\n```bash\\nexport NGC_API_KEY=\u003cPASTE_API_KEY_HERE\u003e\\nexport LOCAL_NIM_CACHE=~/.cache/nim\\nmkdir -p \\\"$LOCAL_NIM_CACHE\\\"\\ndocker run -it --rm \\\\\\n --gpus all \\\\\\n --shm-size=16GB \\\\\\n -e NGC_API_KEY \\\\\\n -v \\\"$LOCAL_NIM_CACHE:/opt/nim/.cache\\\" \\\\\\n -u $(id -u) \\\\\\n -p 8000:8000 \\\\\\n nvcr.io/nim/yentinglin/llama-3-taiwan-70b-instruct:latest\\n```\\n\\nYou can now make a local API call using this curl command:\\n```bash\\ncurl -X 'POST' \\\\\\n'http://0.0.0.0:8000/v1/chat/completions' \\\\\\n-H 'accept: application/json' \\\\\\n-H 'Content-Type: application/json' \\\\\\n-d '{\\n \\\"model\\\": \\\"yentinglin/llama-3-taiwan-70b-instruct\\\",\\n \\\"messages\\\": [{\\\"role\\\":\\\"user\\\", \\\"content\\\":\\\"台灣的夜市文化有什麼特色?\\\"}],\\n \\\"max_tokens\\\": 64\\n}'\\n```\\n\\nFor more details on getting started with this NIM, visit the [NVIDIA NIM Docs](https://docs.nvidia.com/nim/large-language-models/latest/getting-started.html).\\n\",\"dockerTermsOfUse\":\"By running the below commands, you accept the \u003ca href=\\\"https://www.nvidia.com/en-us/data-center/products/nvidia-ai-enterprise/eula/\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA AI Enterprise Terms of Use\u003c/a\u003e and the \u003ca href=\\\"https://docs.nvidia.com/ai-foundation-models-community-license.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA Community Models License\u003c/a\u003e.\\n\",\"showUnavailableBanner\":false,\"apiDocsUrl\":\"https://docs.api.nvidia.com/nim/reference/yentinglin-llama-3-taiwan-70b-instruct\",\"playground\":{\"type\":\"chat\"},\"termsOfUse\":\"\u003cb\u003eGOVERNING TERMS\u003c/b\u003e: The trial service is governed by the \u003ca href=\\\"https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA API Trial Service Terms of Use\u003c/a\u003e; and the use of this model is governed by the \u003ca href=\\\"https://docs.nvidia.com/ai-foundation-models-community-license.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA AI Foundation Models Community License\u003c/a\u003e. ADDITIONAL INFORMATION: \u003ca href=\\\"https://huggingface.co/meta-llama/Meta-Llama-3-8B/blob/main/LICENSE\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eMeta Llama 3 Community License\u003c/a\u003e, Built with Llama.\\n\",\"cta\":{\"text\":\"Apply to Self-Host\",\"url\":\"https://www.nvidia.com/en-us/ai/nim-notifyme/\"}},\"artifactName\":\"llama-3-taiwan-70b-instruct\"},\"config\":{\"orgName\":\"qc69jvmznzxy\",\"resourceId\":\"qc69jvmznzxy/llama-3-taiwan-70b-instruct\",\"labels\":[{\"values\":[\"regional language generation\",\"Code Generation\",\"Chat\",\"Large Language Models\"],\"key\":\"general\"},{\"values\":[\"yentinglin\"],\"key\":\"publisher\"}],\"sharedWithTeams\":[],\"msgTimestamp\":1731969090957,\"dateModified\":\"2024-11-18T22:31:29.472Z\",\"sharedWithOrgs\":[\"qc69jvmznzxy\"],\"description\":\"Sovereign AI model finetuned on Traditional Mandarin and English data using the Llama-3 architecture.\",\"isPublic\":true,\"dateCreated\":\"2024-08-23T10:45:01.563Z\",\"createdBy\":\"fhi3d0ktjp1si0mr5oie4kej7a\",\"displayName\":\"llama-3-taiwan-70b-instruct\",\"name\":\"llama-3-taiwan-70b-instruct\",\"resourceType\":\"ENDPOINT\",\"attributes\":[{\"key\":\"logo\",\"value\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/llama-3-taiwan-70b-instruct.jpg\"}],\"guestAccess\":true,\"type\":\"model\"}},{\"endpoint\":{\"requestStatus\":{\"statusCode\":\"SUCCESS\",\"requestId\":\"67bea127-c88b-4304-a7e3-9b8803c9f3cb\"},\"artifact\":{\"orgName\":\"qc69jvmznzxy\",\"labels\":[\"Chat\",\"Large Language Model\",\"Regional Language Generation\"],\"logo\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/llama-3-swallow-70b-instruct-v01.jpg\",\"shortDescription\":\"Sovereign AI model trained on Japanese language that understands regional nuances.\",\"isReadOnly\":true,\"description\":\"$9f\",\"canGuestDownload\":true,\"isPublic\":true,\"createdDate\":\"2024-08-23T10:41:20.239Z\",\"publisher\":\"tokyotech-llm\",\"displayName\":\"llama-3-swallow-70b-instruct-v0.1\",\"name\":\"llama-3-swallow-70b-instruct-v01\",\"updatedDate\":\"2024-11-18T22:32:35.626Z\",\"attributes\":[{\"key\":\"AVAILABLE\",\"value\":\"true\"},{\"key\":\"PREVIEW\",\"value\":\"false\"}],\"artifactType\":\"ENDPOINT\"}},\"spec\":{\"openAPISpec\":{\"openapi\":\"3.1.0\",\"info\":{\"title\":\"NVIDIA NIM API for tokyotech-llm/llama-3-swallow-70b-instruct-v0.1\",\"description\":\"The NVIDIA NIM REST API. Please see https://docs.nvidia.com/nim/api-reference for more details.\",\"version\":\"1.0.0\",\"termsOfService\":\"https://www.nvidia.com/en-us/data-center/products/nvidia-ai-enterprise/eula/\",\"contact\":{\"name\":\"NVIDIA Enterprise Support\",\"url\":\"https://www.nvidia.com/en-us/support/enterprise/\"},\"license\":{\"name\":\"Llama 3 License\",\"url\":\"https://llama.meta.com/llama3/license/\"}},\"servers\":[{\"url\":\"https://integrate.api.nvidia.com/v1/\"}],\"paths\":{\"/chat/completions\":{\"post\":{\"operationId\":\"create_chat_completion_v1_chat_completions_post\",\"tags\":[\"Chat\"],\"summary\":\"Creates a model response for the given chat conversation.\",\"description\":\"Given a list of messages comprising a conversation, the model will return a response. Compatible with OpenAI. See https://platform.openai.com/docs/api-reference/chat/create\",\"requestBody\":{\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ChatCompletionRequest\"}}},\"required\":true},\"responses\":{\"200\":{\"description\":\"Successful Response\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ChatCompletionResponse\"}}}},\"402\":{\"description\":\"Payment Required\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/PaymentRequiredError\"}}}},\"422\":{\"description\":\"Validation Error\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/HTTPValidationError\"}}}}},\"x-nvai-meta\":{\"name\":\"Create chat completion\",\"returns\":\"Returns a [chat completion](/docs/api-reference/chat/object) object, or a streamed sequence of [chat completion chunk](/docs/api-reference/chat/streaming) objects if the request is streamed.\\n\",\"path\":\"create\",\"examples\":[{\"name\":\"東京の夜空に打ち上がっている花火の下、向かい合っている燕とラマの温かい物語を書いてください。\",\"requestJson\":\"{\\n \\\"model\\\": \\\"tokyotech-llm/llama-3-swallow-70b-instruct-v0.1\\\",\\n \\\"messages\\\": [\\n {\\n \\\"role\\\": \\\"system\\\",\\n \\\"content\\\": \\\"You are a helpful assistant.\\\"\\n },\\n {\\n \\\"role\\\": \\\"user\\\",\\n \\\"content\\\": \\\"東京の夜空に打ち上がっている花火の下、向かい合っている燕とラマの温かい物語を書いてください。\\\"\\n }\\n ],\\n \\\"top_p\\\": 0.7,\\n \\\"max_tokens\\\": 1024,\\n \\\"seed\\\": 42,\\n \\\"stop\\\": null,\\n \\\"stream\\\": true\\n}\\n\",\"responseJson\":\"{\\n \\\"id\\\": \\\"id-123\\\",\\n \\\"object\\\": \\\"chat.completion\\\",\\n \\\"created\\\": 1677652288,\\n \\\"model\\\": \\\"tokyotech-llm/llama-3-swallow-70b-instruct-v0.1\\\",\\n \\\"system_fingerprint\\\": \\\"fp_44709d6fcb\\\",\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"東京の夜空に、花火が打ち上がっていた。花火の光は、街全体を照らしていた...\\\"\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 9,\\n \\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"},{\"name\":\"Write a heartwarming story about a swallow and a llama facing each other under the fireworks exploding in the Tokyo night sky.\",\"requestJson\":\"{\\n \\\"model\\\": \\\"tokyotech-llm/llama-3-swallow-70b-instruct-v0.1\\\",\\n \\\"messages\\\": [\\n {\\n \\\"role\\\": \\\"system\\\",\\n \\\"content\\\": \\\"You are a helpful assistant.\\\"\\n },\\n {\\n \\\"role\\\": \\\"user\\\",\\n \\\"content\\\": \\\"Write a heartwarming story about a swallow and a llama facing each other under the fireworks exploding in the Tokyo night sky.\\\"\\n }\\n ],\\n \\\"top_p\\\": 0.7,\\n \\\"max_tokens\\\": 1024,\\n \\\"seed\\\": 42,\\n \\\"stop\\\": null,\\n \\\"stream\\\": true\\n}\\n\",\"responseJson\":\"{\\n \\\"id\\\": \\\"id-123\\\",\\n \\\"object\\\": \\\"chat.completion\\\",\\n \\\"created\\\": 1677652288,\\n \\\"model\\\": \\\"tokyotech-llm/llama-3-swallow-70b-instruct-v0.1\\\",\\n \\\"system_fingerprint\\\": \\\"fp_44709d6fcb\\\",\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"Once upon a time, in the bustling city of Tokyo...\\\"\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 9,\\n \\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"}],\"templates\":[{\"title\":\"No Streaming\",\"requestEjs\":{\"python\":\"from openai import OpenAI\\n\\nclient = OpenAI(\\n base_url = \\\"https://integrate.api.nvidia.com/v1\\\",\\n api_key = \\\"$NVIDIA_API_KEY\\\"\\n)\\n\\ncompletion = client.chat.completions.create(\\n model=\\\"\u003c%- request.model %\u003e\\\",\\n messages=\u003c%- JSON.stringify(request.messages) %\u003e,\\n temperature=\u003c%- request.temperature %\u003e,\\n top_p=\u003c%- request.top_p %\u003e,\\n max_tokens=\u003c%- request.max_tokens %\u003e,\\n stream=\u003c%- request.stream?.toString()[0].toUpperCase() + request.stream?.toString().slice(1) %\u003e\\n)\\n\u003c% if (request.stream) { %\u003e\\nfor chunk in completion:\\n if chunk.choices[0].delta.content is not None:\\n print(chunk.choices[0].delta.content, end=\\\"\\\")\\n\u003c% } else { %\u003e\\nprint(completion.choices[0].message)\\n\u003c% } %\u003e\\n\",\"node.js\":\"import OpenAI from 'openai';\\n\\nconst openai = new OpenAI({\\n apiKey: '$NVIDIA_API_KEY',\\n baseURL: 'https://integrate.api.nvidia.com/v1',\\n})\\n\\nasync function main() {\\n const completion = await openai.chat.completions.create({\\n model: \\\"\u003c%- request.model %\u003e\\\",\\n messages: \u003c%- JSON.stringify(request.messages) %\u003e,\\n temperature: \u003c%- request.temperature %\u003e,\\n top_p: \u003c%- request.top_p %\u003e,\\n max_tokens: \u003c%- request.max_tokens %\u003e,\\n stream: \u003c%- request.stream %\u003e,\\n })\\n \u003c% if (request.stream) { %\u003e\\n for await (const chunk of completion) {\\n process.stdout.write(chunk.choices[0]?.delta?.content || '')\\n }\\n \u003c% } else { %\u003e\\n process.stdout.write(completion.choices[0]?.message?.content);\\n \u003c% } %\u003e\\n}\\n\\nmain();\",\"curl\":\"curl https://integrate.api.nvidia.com/v1/chat/completions \\\\\\n -H \\\"Content-Type: application/json\\\" \\\\\\n -H \\\"Authorization: Bearer $NVIDIA_API_KEY\\\" \\\\\\n -d '{\\n \\\"model\\\": \\\"tokyotech-llm/llama-3-swallow-70b-instruct-v0.1\\\",\\n \\\"messages\\\": \u003c%- JSON.stringify(request.messages).replaceAll(\\\"'\\\", \\\"'\\\\\\\"'\\\\\\\"'\\\") %\u003e,\\n \\\"temperature\\\": \u003c%- request.temperature %\u003e, \\n \\\"top_p\\\": \u003c%- request.top_p %\u003e,\\n \\\"max_tokens\\\": \u003c%- request.max_tokens %\u003e,\\n \\\"stream\\\": \u003c%- request.stream %\u003e \\n }'\\n\"},\"response\":\"{\\n \\\"id\\\": \\\"chatcmpl-123\\\",\\n \\\"object\\\": \\\"chat.completion\\\",\\n \\\"created\\\": 1677652288,\\n \\\"model\\\": \\\"tokyotech-llm/llama-3-swallow-70b-instruct-v0.1\\\",\\n \\\"system_fingerprint\\\": \\\"fp_44709d6fcb\\\",\\n \\\"choices\\\": [{\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"\\\\n\\\\nHello there, how may I assist you today?\\\",\\n },\\n \\\"finish_reason\\\": \\\"stop\\\"\\n }],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 9,\\n \\\"completion_tokens\\\": 12,\\n \\\"total_tokens\\\": 21\\n }\\n}\\n\"}]}}}},\"security\":[{\"Token\":[]}],\"components\":{\"securitySchemes\":{\"Token\":{\"type\":\"http\",\"scheme\":\"bearer\"}},\"schemas\":{\"ChatCompletionRequest\":{\"properties\":{\"model\":{\"type\":\"string\",\"title\":\"Model\",\"default\":\"tokyotech-llm/llama-3-swallow-70b-instruct-v0.1\"},\"max_tokens\":{\"type\":\"integer\",\"minimum\":1,\"title\":\"Max Tokens\",\"description\":\"The maximum number of tokens to generate in any given call. Note that the model is not aware of this value, and generation will simply stop at the number of tokens specified.\",\"default\":1024},\"stream\":{\"type\":\"boolean\",\"title\":\"Stream\",\"description\":\"If set, partial message deltas will be sent. Tokens will be sent as data-only server-sent events (SSE) as they become available (JSON responses are prefixed by `data: `), with the stream terminated by a `data: [DONE]` message.\",\"default\":false},\"temperature\":{\"type\":\"number\",\"maximum\":1,\"minimum\":0,\"title\":\"Temperature\",\"description\":\"The sampling temperature to use for text generation. The higher the temperature value is, the less deterministic the output text will be. It is not recommended to modify both temperature and top_p in the same call.\",\"default\":0.5},\"top_p\":{\"type\":\"number\",\"maximum\":1,\"exclusiveMinimum\":0,\"title\":\"Top P\",\"description\":\"The top-p sampling mass used for text generation. The top-p value determines the probability mass that is sampled at sampling time. For example, if top_p = 0.2, only the most likely tokens (summing to 0.2 cumulative probability) will be sampled. It is not recommended to modify both temperature and top_p in the same call.\",\"default\":1},\"stop\":{\"anyOf\":[{\"items\":{\"type\":\"string\"},\"type\":\"array\"},{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Stop\",\"description\":\"A string or a list of strings where the API will stop generating further tokens. The returned text will not contain the stop sequence.\",\"examples\":[null]},\"frequency_penalty\":{\"type\":\"number\",\"maximum\":2,\"minimum\":-2,\"default\":0,\"title\":\"Frequency Penalty\",\"description\":\"Indicates how much to penalize new tokens based on their existing frequency in the text so far, decreasing model likelihood to repeat the same line verbatim.\"},\"presence_penalty\":{\"type\":\"number\",\"maximum\":2,\"minimum\":-2,\"default\":0,\"title\":\"Presence Penalty\",\"description\":\"Positive values penalize new tokens based on whether they appear in the text so far, increasing model likelihood to talk about new topics.\"},\"messages\":{\"items\":{\"$ref\":\"#/components/schemas/ChatMessage\"},\"type\":\"array\",\"title\":\"Messages\",\"description\":\"A list of messages comprising the conversation so far.\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"messages\"],\"title\":\"ChatCompletionRequest\",\"description\":\"OpenAI ChatCompletionRequest\"},\"ChatCompletionResponse\":{\"properties\":{\"id\":{\"type\":\"string\",\"title\":\"Id\",\"description\":\"A unique identifier for the completion.\"},\"object\":{\"type\":\"string\",\"title\":\"Object\",\"default\":\"chat.completion\"},\"created\":{\"type\":\"integer\",\"title\":\"Created\"},\"model\":{\"type\":\"string\",\"title\":\"Model\",\"example\":\"tokyotech-llm/llama-3-swallow-70b-instruct-v0.1\"},\"choices\":{\"items\":{\"$ref\":\"#/components/schemas/ChatCompletionResponseChoice\"},\"type\":\"array\",\"title\":\"Choices\",\"description\":\"The list of completion choices the model generated for the input prompt.\"},\"usage\":{\"$ref\":\"#/components/schemas/UsageInfo\",\"description\":\"Usage statistics for the completion request.\"}},\"type\":\"object\",\"required\":[\"model\",\"choices\",\"usage\"],\"title\":\"ChatCompletionResponse\"},\"ChatCompletionResponseChoice\":{\"properties\":{\"index\":{\"type\":\"integer\",\"title\":\"Index\",\"description\":\"The index of the choice in the list of choices (always 0).\"},\"message\":{\"$ref\":\"#/components/schemas/ChatMessage\",\"description\":\"A chat completion message generated by the model.\"},\"finish_reason\":{\"anyOf\":[{\"type\":\"string\",\"enum\":[\"stop\",\"length\"]},{\"type\":\"null\"}],\"title\":\"Finish Reason\",\"description\":\"The reason the model stopped generating tokens. This will be `stop` if the model hit a natural stop point or a provided stop sequence, or `length` if the maximum number of tokens specified in the request was reached. Will be `null` if the model has not finished\"}},\"type\":\"object\",\"required\":[\"index\",\"message\"],\"title\":\"ChatCompletionResponseChoice\"},\"ChatMessage\":{\"properties\":{\"role\":{\"type\":\"string\",\"title\":\"Role\",\"example\":\"user\",\"description\":\"The role of the message author.\"},\"content\":{\"type\":\"string\",\"title\":\"Content\",\"example\":\"東京の夜空に打ち上がっている花火の下、向かい合っている燕とラマの温かい物語を書いてください。\",\"description\":\"The contents of the message.\"}},\"type\":\"object\",\"required\":[\"role\",\"content\"],\"title\":\"ChatMessage\"},\"HTTPValidationError\":{\"properties\":{\"detail\":{\"items\":{\"$ref\":\"#/components/schemas/ValidationError\"},\"type\":\"array\",\"title\":\"Detail\",\"description\":\"Detailed information about the error.\"}},\"type\":\"object\",\"title\":\"HTTPValidationError\"},\"PaymentRequiredError\":{\"properties\":{\"detail\":{\"type\":\"string\",\"description\":\"Contains specific information related to the error and why it occurred.\",\"example\":\"You have reached your limit of credits.\"}},\"type\":\"object\",\"title\":\"PaymentRequiredError\"},\"UsageInfo\":{\"properties\":{\"prompt_tokens\":{\"type\":\"integer\",\"title\":\"Prompt Tokens\",\"description\":\"Number of tokens in the prompt.\",\"default\":0},\"total_tokens\":{\"type\":\"integer\",\"title\":\"Total Tokens\",\"description\":\"Total number of tokens used in the request (prompt + completion).\",\"default\":0},\"completion_tokens\":{\"anyOf\":[{\"type\":\"integer\"},{\"type\":\"null\"}],\"title\":\"Completion Tokens\",\"description\":\"Number of tokens in the generated completion.\",\"default\":0}},\"type\":\"object\",\"title\":\"UsageInfo\"},\"ValidationError\":{\"properties\":{\"loc\":{\"items\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"integer\"}]},\"type\":\"array\",\"title\":\"Location\"},\"msg\":{\"type\":\"string\",\"title\":\"Message\",\"description\":\"The error message.\"},\"type\":{\"type\":\"string\",\"title\":\"Error Type\",\"description\":\"Error type\"}},\"type\":\"object\",\"required\":[\"loc\",\"msg\",\"type\"],\"title\":\"ValidationError\"}}}},\"namespace\":\"qc69jvmznzxy\",\"updatedDate\":\"2024-11-18T22:32:36.300Z\",\"nvcfFunctionId\":\"0967cb57-a94c-4483-91a6-c797d1fdb4a7\",\"createdDate\":\"2024-08-23T10:41:20.624Z\",\"attributes\":{\"showUnavailableBanner\":false,\"apiDocsUrl\":\"https://docs.api.nvidia.com/nim/reference/tokyotech-llm-llama-3-swallow-70b-instruct-v01\",\"playground\":{\"type\":\"chat\"},\"termsOfUse\":\"\u003cb\u003eGOVERNING TERMS\u003c/b\u003e: This trial service is governed by the \u003ca href=\\\"https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA API Trial Service Terms of Use\u003c/a\u003e; and the use of this model is governed by the \u003ca href=\\\"https://docs.nvidia.com/ai-foundation-models-community-license.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA AI Foundation Models Community License\u003c/a\u003e. ADDITIONAL INFORMATION: \u003ca href=\\\"https://huggingface.co/meta-llama/Meta-Llama-3-8B/blob/main/LICENSE\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eMeta Llama 3 Community License\u003c/a\u003e, Built with Meta Llama 3.\\n\",\"cta\":{\"text\":\"Run Anywhere - Notify Me\",\"url\":\"https://www.nvidia.com/en-us/ai/nim-notifyme/\",\"nim_available_override_url\":\"https://catalog.ngc.nvidia.com/orgs/nim/teams/tokyotech-llm/containers/llama-3-swallow-70b-instruct-v0.1\"},\"dockerRun\":\"Pull and run the NVIDIA NIM with the command below. This will download the optimized model for your infrastructure.\\n```bash\\nexport NGC_API_KEY=\u003cPASTE_API_KEY_HERE\u003e\\nexport LOCAL_NIM_CACHE=~/.cache/nim\\nmkdir -p \\\"$LOCAL_NIM_CACHE\\\"\\ndocker run -it --rm \\\\\\n --gpus all \\\\\\n --shm-size=16GB \\\\\\n -e NGC_API_KEY \\\\\\n -v \\\"$LOCAL_NIM_CACHE:/opt/nim/.cache\\\" \\\\\\n -u $(id -u) \\\\\\n -p 8000:8000 \\\\\\n nvcr.io/nim/tokyotech-llm/llama-3-swallow-70b-instruct-v0.1:latest\\n```\\n\\nYou can now make a local API call using this curl command:\\n```bash\\ncurl -X 'POST' \\\\\\n'http://0.0.0.0:8000/v1/chat/completions' \\\\\\n-H 'accept: application/json' \\\\\\n-H 'Content-Type: application/json' \\\\\\n-d '{\\n \\\"model\\\": \\\"tokyotech-llm/llama-3-swallow-70b-instruct-v0.1\\\",\\n \\\"messages\\\": [{\\\"role\\\":\\\"user\\\", \\\"content\\\":\\\"東京の夜空に打ち上がっている花火の下、向かい合っている燕とラマの温かい物語を書いてください。\\\"}],\\n \\\"max_tokens\\\": 64\\n}'\\n```\\n\\nFor more details on getting started with this NIM, visit the [NVIDIA NIM Docs](https://docs.nvidia.com/nim/large-language-models/latest/getting-started.html).\\n\",\"dockerTermsOfUse\":\"By running the below commands, you accept the \u003ca href=\\\"https://www.nvidia.com/en-us/data-center/products/nvidia-ai-enterprise/eula/\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA AI Enterprise Terms of Use\u003c/a\u003e and the \u003ca href=\\\"https://docs.nvidia.com/ai-foundation-models-community-license.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA Community Models License\u003c/a\u003e.\\n\"},\"artifactName\":\"llama-3-swallow-70b-instruct-v01\"},\"config\":{\"orgName\":\"qc69jvmznzxy\",\"resourceId\":\"qc69jvmznzxy/llama-3-swallow-70b-instruct-v01\",\"labels\":[{\"values\":[\"Large Language Model\",\"Chat\",\"Regional Language Generation\"],\"key\":\"general\"},{\"values\":[\"tokyotech-llm\"],\"key\":\"publisher\"}],\"sharedWithTeams\":[],\"msgTimestamp\":1731969157054,\"dateModified\":\"2024-11-18T22:32:35.626Z\",\"sharedWithOrgs\":[\"qc69jvmznzxy\"],\"description\":\"Sovereign AI model trained on Japanese language that understands regional nuances.\",\"isPublic\":true,\"dateCreated\":\"2024-08-23T10:41:20.239Z\",\"createdBy\":\"fhi3d0ktjp1si0mr5oie4kej7a\",\"displayName\":\"llama-3-swallow-70b-instruct-v0.1\",\"name\":\"llama-3-swallow-70b-instruct-v01\",\"resourceType\":\"ENDPOINT\",\"attributes\":[{\"key\":\"logo\",\"value\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/llama-3-swallow-70b-instruct-v01.jpg\"}],\"guestAccess\":true,\"type\":\"model\"}},{\"endpoint\":{\"requestStatus\":{\"statusCode\":\"SUCCESS\",\"requestId\":\"86e7de88-c942-450d-81eb-ba89e6ab8f64\"},\"artifact\":{\"orgName\":\"qc69jvmznzxy\",\"labels\":[\"NVIDIA NIM\",\"neural machine translation\",\"Text Translation\"],\"bias\":\"Field | Response\\n:---------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------\\nParticipation considerations from adversely impacted groups ([protected classes](https://www.senate.ca.gov/content/protected-classes)) in model design and testing: | Not Applicable\\nMeasures taken to mitigate against unwanted bias: | Sourced diverse dataset from East Asia, South Asia, Latin America, and North America annotated by different gender.\\\" See https://www.arxiv-vanity.com/papers/2106.03193/ for more details.\",\"logo\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/megatron-1b-nmt.jpg\",\"shortDescription\":\"Enable smooth global interactions in 32 languages.\",\"safetyAndSecurity\":\"Field | Response\\n:---------------------------------------------------|:----------------------------------\\nModel Application(s): | Language Translation\\nDescribe the life-critical impacts (if present). | Not Applicable\\nUse Case Restriction(s): | Abide by https://developer.nvidia.com/riva/ga/license\\nModel and Dataset Restriction(s): | The Principle of least privilege (PoLP) is applied limiting access for dataset generation and model development. Restrictions enforce dataset access during training, and dataset license constraints adhered to.\",\"privacy\":\"$a0\",\"isReadOnly\":true,\"description\":\"$a1\",\"canGuestDownload\":true,\"isPublic\":true,\"createdDate\":\"2024-08-06T06:27:14.100Z\",\"publisher\":\"nvidia\",\"displayName\":\"megatron-1b-nmt\",\"name\":\"megatron-1b-nmt\",\"explainability\":\"$a2\",\"updatedDate\":\"2024-11-20T03:24:12.567Z\",\"attributes\":[{\"key\":\"AVAILABLE\",\"value\":\"true\"},{\"key\":\"PREVIEW\",\"value\":\"false\"}],\"artifactType\":\"ENDPOINT\"}},\"spec\":{\"namespace\":\"qc69jvmznzxy\",\"updatedDate\":\"2024-11-20T03:24:13.144Z\",\"nvcfFunctionId\":\"647147c1-9c23-496c-8304-2e29e7574510\",\"createdDate\":\"2024-08-06T06:27:14.399Z\",\"attributes\":{\"dockerRun\":\"$a3\",\"dockerTermsOfUse\":\"By running the below commands, you accept the \u003ca href=\\\"https://www.nvidia.com/en-us/data-center/products/nvidia-ai-enterprise/eula/\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA AI Enterprise Terms of Use\u003c/a\u003e and the \u003ca href=\\\"https://docs.nvidia.com/ai-foundation-models-community-license.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA Community Models License\u003c/a\u003e.\\n\",\"usage\":\"$a4\",\"showUnavailableBanner\":false,\"apiDocsUrl\":\"https://github.com/nvidia-riva/common\",\"termsOfUse\":\"\u003cb\u003eGOVERNING TERMS\u003c/b\u003e: Your use of this API is governed by the \u003ca href=\\\"https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA API Trial Service Terms of Use\u003c/a\u003e; and the use of this model is governed by the \u003ca href=\\\"https://docs.nvidia.com/ai-foundation-models-community-license.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA AI Foundation Models Community License\u003c/a\u003e.\\n\",\"cta\":{\"text\":\"Run Anywhere - Notify Me\",\"url\":\"https://www.nvidia.com/en-us/ai/nim-notifyme/\"}},\"artifactName\":\"megatron-1b-nmt\"},\"config\":{\"orgName\":\"qc69jvmznzxy\",\"resourceId\":\"qc69jvmznzxy/megatron-1b-nmt\",\"labels\":[{\"values\":[\"Text Translation\",\"neural machine translation\",\"NVIDIA NIM\"],\"key\":\"general\"},{\"values\":[\"nvidia\"],\"key\":\"publisher\"}],\"sharedWithTeams\":[],\"msgTimestamp\":1732073054358,\"dateModified\":\"2024-11-20T03:24:12.567Z\",\"sharedWithOrgs\":[\"qc69jvmznzxy\"],\"description\":\"Enable smooth global interactions in 32 languages.\",\"isPublic\":true,\"dateCreated\":\"2024-08-06T06:27:14.100Z\",\"createdBy\":\"fhi3d0ktjp1si0mr5oie4kej7a\",\"displayName\":\"megatron-1b-nmt\",\"name\":\"megatron-1b-nmt\",\"resourceType\":\"ENDPOINT\",\"attributes\":[{\"key\":\"logo\",\"value\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/megatron-1b-nmt.jpg\"}],\"guestAccess\":true,\"type\":\"model\"}},{\"endpoint\":{\"requestStatus\":{\"statusCode\":\"SUCCESS\",\"requestId\":\"ed04ecec-b809-43a7-9aa4-fd2a5f196cac\"},\"artifact\":{\"orgName\":\"qc69jvmznzxy\",\"labels\":[\"nvidia nim\",\"text-to-speech\",\"Text-to-Speech\"],\"bias\":\"Field | Response\\n:------|:----------\\nWhat is the language balance of the model validation data? | English: 100%\\nWhat is the geographic origin language balance of the model validation data? | United States: 100%\\nWhat is the accent balance of the model validation data? | English: 100%\\nMeasures taken to mitigate against unwanted bias: | None\\nParticipation considerations from adversely impacted groups [protected classes](https://www.senate.ca.gov/content/protected-classes) in model design and testing: | None\",\"logo\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/fastpitch-hifigan-tts.jpg\",\"shortDescription\":\"Expressive and engaging English voices for Q\u0026A assistants, brand ambassadors, and service robots\",\"safetyAndSecurity\":\"Field | Response\\n:------|:---------\\nModel Application(s): | Speech synthesis\\nDescribe the life critical impact (if present). | Not Applicable\\nModel and dataset restrictions: | The Principle of least privilege (PoLP) is applied limiting access for dataset generation and model development. Restrictions enforce dataset access during training, and dataset license constraints adhered to.\\nUse case restrictions for the model. | Abide by [https://developer.nvidia.com/riva/ga/license](https://developer.nvidia.com/riva/ga/license)\",\"privacy\":\"Field | Response\\n:------|:---------\\nGeneratable or reverse engineerable personal information? | None\\nHow often is dataset reviewed? | When ingested\\nIs a mechanism in place to honor data subject right of access or deletion of personal data? | Not Applicable\\nIf personal data collected for the development of the model, was it collected directly by NVIDIA? | Yes\\nIf personal data collected for the development of the model by NVIDIA, do you maintain or have access to disclosures made to data subjects? | Yes\\nIf personal data collected for the development of this AI model, was it minimized to only what was required? | Yes\\nIs there provenance for all datasets used in training? | Yes\\nIs data in dataset traceable? | Yes\\nDoes data labeling (annotation, metadata) comply with privacy laws? | Yes\\nIs data compliant with data subject requests for data correction or removal, if such a request was made? | No, not possible with externally-sourced data.\",\"isReadOnly\":true,\"description\":\"$a5\",\"canGuestDownload\":true,\"isPublic\":true,\"createdDate\":\"2024-08-06T06:27:13.898Z\",\"publisher\":\"nvidia\",\"displayName\":\"fastpitch-hifigan-tts\",\"name\":\"fastpitch-hifigan-tts\",\"explainability\":\"$a6\",\"updatedDate\":\"2024-11-20T03:20:13.999Z\",\"attributes\":[{\"key\":\"AVAILABLE\",\"value\":\"true\"},{\"key\":\"PREVIEW\",\"value\":\"false\"}],\"artifactType\":\"ENDPOINT\"}},\"spec\":{\"namespace\":\"qc69jvmznzxy\",\"updatedDate\":\"2024-11-20T03:20:14.482Z\",\"nvcfFunctionId\":\"0149dedb-2be8-4195-b9a0-e57e0e14f972\",\"createdDate\":\"2024-08-06T06:27:14.255Z\",\"attributes\":{\"dockerRun\":\"$a7\",\"dockerTermsOfUse\":\"By running the below commands, you accept the \u003ca href=\\\"https://www.nvidia.com/en-us/data-center/products/nvidia-ai-enterprise/eula/\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA AI Enterprise Terms of Use\u003c/a\u003e and the \u003ca href=\\\"https://docs.nvidia.com/ai-foundation-models-community-license.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA Community Models License\u003c/a\u003e.\\n\",\"usage\":\"$a8\",\"showUnavailableBanner\":false,\"apiDocsUrl\":\"https://github.com/nvidia-riva/common\",\"termsOfUse\":\"\u003cb\u003eGOVERNING TERMS\u003c/b\u003e: Your use of this API is governed by the \u003ca href=\\\"https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA API Trial Service Terms of Use\u003c/a\u003e; and the use of this model is governed by the \u003ca href=\\\"https://docs.nvidia.com/ai-foundation-models-community-license.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA AI Foundation Models Community License\u003c/a\u003e.\\n\",\"cta\":{\"text\":\"Run Anywhere - Notify Me\",\"url\":\"https://www.nvidia.com/en-us/ai/nim-notifyme/\"}},\"artifactName\":\"fastpitch-hifigan-tts\"},\"config\":{\"orgName\":\"qc69jvmznzxy\",\"resourceId\":\"qc69jvmznzxy/fastpitch-hifigan-tts\",\"labels\":[{\"values\":[\"text-to-speech\",\"Text-to-Speech\",\"nvidia nim\"],\"key\":\"general\"},{\"values\":[\"nvidia\"],\"key\":\"publisher\"}],\"sharedWithTeams\":[],\"msgTimestamp\":1732072815371,\"dateModified\":\"2024-11-20T03:20:13.999Z\",\"sharedWithOrgs\":[\"qc69jvmznzxy\"],\"description\":\"Expressive and engaging English voices for Q\u0026A assistants, brand ambassadors, and service robots\",\"isPublic\":true,\"dateCreated\":\"2024-08-06T06:27:13.898Z\",\"createdBy\":\"fhi3d0ktjp1si0mr5oie4kej7a\",\"displayName\":\"fastpitch-hifigan-tts\",\"name\":\"fastpitch-hifigan-tts\",\"resourceType\":\"ENDPOINT\",\"attributes\":[{\"key\":\"logo\",\"value\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/fastpitch-hifigan-tts.jpg\"}],\"guestAccess\":true,\"type\":\"model\"}},{\"endpoint\":{\"requestStatus\":{\"statusCode\":\"SUCCESS\",\"requestId\":\"bbbff509-de27-4bef-8c8c-791af897ddd6\"},\"artifact\":{\"orgName\":\"qc69jvmznzxy\",\"labels\":[\"Automatic Speech Recognition\",\"NVIDIA NIM\",\"Speech-to-Text\"],\"bias\":\"Field | Response\\n:---------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------\\nParticipation considerations from adversely impacted groups ([protected classes](https://www.senate.ca.gov/content/protected-classes)) in model design and testing: | Age, Gender, Linguistic Background\\nMeasures taken to mitigate against unwanted bias: | Used custom dataset to validate model performance across gender, age, and linguistic demographics\",\"logo\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/parakeet-ctc-1_1b-asr.jpg\",\"shortDescription\":\"Record-setting accuracy and performance for English transcription.\",\"safetyAndSecurity\":\"Field | Response\\n:---------------------------------------------------|:----------------------------------\\nModel Application(s): | Speech Transcription\\nDescribe the life-critical impacts (if present). | Not Applicable for Licensed Use Cases per [NVIDIA RIVA License Agreement](https://developer.nvidia.com/riva/ga/license)\\nUse Case Restriction(s): | Abide by https://developer.nvidia.com/riva/ga/license\\nModel and Dataset Restriction(s): | Dataset access restrictions\\nDescribe access restrictions (if any): | The Principle of Least Privilege (PoLP) is applied limiting access for dataset generation and model development. Restrictions enforce dataset access during training and dataset license constraints adhered to.\",\"privacy\":\"$a9\",\"isReadOnly\":true,\"description\":\"$aa\",\"canGuestDownload\":true,\"isPublic\":true,\"createdDate\":\"2024-08-06T06:27:13.068Z\",\"publisher\":\"nvidia\",\"displayName\":\"parakeet-ctc-1.1b-asr\",\"name\":\"parakeet-ctc-1_1b-asr\",\"explainability\":\"$ab\",\"updatedDate\":\"2024-11-20T03:20:09.029Z\",\"attributes\":[{\"key\":\"AVAILABLE\",\"value\":\"true\"},{\"key\":\"PREVIEW\",\"value\":\"false\"}],\"artifactType\":\"ENDPOINT\"}},\"spec\":{\"namespace\":\"qc69jvmznzxy\",\"updatedDate\":\"2024-11-20T03:20:09.572Z\",\"nvcfFunctionId\":\"1598d209-5e27-4d3c-8079-4751568b1081\",\"createdDate\":\"2024-08-06T06:27:13.397Z\",\"attributes\":{\"dockerRun\":\"$ac\",\"dockerTermsOfUse\":\"By running the below commands, you accept the \u003ca href=\\\"https://www.nvidia.com/en-us/data-center/products/nvidia-ai-enterprise/eula/\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA AI Enterprise Terms of Use\u003c/a\u003e and the \u003ca href=\\\"https://docs.nvidia.com/ai-foundation-models-community-license.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA Community Models License\u003c/a\u003e.\\n\",\"usage\":\"$ad\",\"showUnavailableBanner\":false,\"apiDocsUrl\":\"https://github.com/nvidia-riva/common\",\"termsOfUse\":\"\u003cb\u003eGOVERNING TERMS\u003c/b\u003e: Your use of this API is governed by the \u003ca href=\\\"https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA API Trial Service Terms of Use\u003c/a\u003e; and the use of this model is governed by the \u003ca href=\\\"https://docs.nvidia.com/ai-foundation-models-community-license.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA AI Foundation Models Community License\u003c/a\u003e.\\n\",\"cta\":{\"text\":\"Run Anywhere - Notify Me\",\"url\":\"https://www.nvidia.com/en-us/ai/nim-notifyme/\"}},\"artifactName\":\"parakeet-ctc-1_1b-asr\"},\"config\":{\"orgName\":\"qc69jvmznzxy\",\"resourceId\":\"qc69jvmznzxy/parakeet-ctc-1_1b-asr\",\"labels\":[{\"values\":[\"Automatic Speech Recognition\",\"Speech-to-Text\",\"NVIDIA NIM\"],\"key\":\"general\"},{\"values\":[\"nvidia\"],\"key\":\"publisher\"}],\"sharedWithTeams\":[],\"msgTimestamp\":1732072810829,\"dateModified\":\"2024-11-20T03:20:09.029Z\",\"sharedWithOrgs\":[\"qc69jvmznzxy\"],\"description\":\"Record-setting accuracy and performance for English transcription.\",\"isPublic\":true,\"dateCreated\":\"2024-08-06T06:27:13.068Z\",\"createdBy\":\"fhi3d0ktjp1si0mr5oie4kej7a\",\"displayName\":\"parakeet-ctc-1.1b-asr\",\"name\":\"parakeet-ctc-1_1b-asr\",\"resourceType\":\"ENDPOINT\",\"attributes\":[{\"key\":\"logo\",\"value\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/parakeet-ctc-1_1b-asr.jpg\"}],\"guestAccess\":true,\"type\":\"model\"}}]}]\n"])</script><script>self.__next_f.push([1,"ae:T81c,"])</script><script>self.__next_f.push([1,"Field | Response\n:----------------------------------------------------------------------------------------------------------------------------------|:-----------------------------------------------\nGeneratable or reverse engineerable personal information? | None\nProtected class data used to create this model? | None\nWas consent obtained for any personal data used? | Not Applicable (No Personal Data)\nHow often is dataset reviewed? | Before Release\nIs a mechanism in place to honor data subject right of access or deletion of personal data? | Not Applicable\nIf personal collected for the development of the model, was it collected directly by NVIDIA? | Not Applicable\nIf personal collected for the development of the model by NVIDIA, do you maintain or have access to disclosures made to data subjects? | Not Applicable\nIf personal collected for the development of this AI model, was it minimized to only what was required? | Not Applicable\nIs data in dataset traceable? | Yes\nIs there provenance for all datasets used in training? | Yes\nDoes data labeling (annotation, metadata) comply with privacy laws? | Yes\nIs data compliant with data subject requests for data correction or removal, if such a request was made? | Yes"])</script><script>self.__next_f.push([1,"af:Ta8b,"])</script><script>self.__next_f.push([1,"## Model Overview\n\n### Description:\n\nUSD Code (usdcode-llama3-70b-instruct) is an OpenUSD Python code generation and knowledge answering model that helps developers to write OpenUSD code and answer OpenUSD knowledge questions.\n\nThis model is available for preview, demonstration, and non-production usage on the NVIDIA API Catalog.\n\n### References:\n\n- Llama3 - https://ai.meta.com/blog/meta-llama-3/\n- OpenUSD - https://www.openusd.org/\n\n### Model Architecture:\n\n**Architecture Type:** Transformer-Based Architecture \u003cbr\u003e\n\n**Network Architecture:** Llama-3 \u003cbr\u003e\n\n### Input\n\n**Input Type(s):** Text \u003cbr\u003e\n**Input Format(s):** String \u003cbr\u003e\n**Other Properties Related to Input:** Max context length of 8k tokens \u003cbr\u003e\n\n### Output\n\n**Output Type(s):** Text (Code, Python) \u003cbr\u003e\n**Output Format:** String \u003cbr\u003e\n**Other Properties Related to Output:** Max output length of 8k tokens \u003cbr\u003e\n\n### Software Integration:\n\n**Runtime Engine(s):**\n* NIM 1.0.0 \u003cbr\u003e\n\n**Supported Hardware Microarchitecture Compatibility:** \u003cbr\u003e\n* NVIDIA Hopper \u003cbr\u003e\n\n**[Preferred/Supported] Operating System(s):** \u003cbr\u003e\n* Linux \u003cbr\u003e\n\n### Model Version(s): \u003cbr\u003e\n\n* usdcode-llama3-70b-instruct-tuned-0703 \u003cbr\u003e\n\n## Training, Testing, and Evaluation Datasets:\n\n### Training Dataset:\n\n**Data Collection Method by dataset** \u003cbr\u003e\n* Hybrid: Automated, Synthetic \u003cbr\u003e\n\n**Labeling Method by dataset** \u003cbr\u003e\n* Unknown \u003cbr\u003e\n\n**Properties (Quantity, Dataset Descriptions, Sensor(s)):** \u003cbr\u003e\n* 59,729 question/answer pairs (text) \u003cbr\u003e\n\n### Testing Dataset:\n\n**Data Collection Method by dataset** \u003cbr\u003e\n* Not Applicable \u003cbr\u003e\n\n**Labeling Method by dataset** \u003cbr\u003e\n* Not Applicable \u003cbr\u003e\n\n**Properties (Quantity, Dataset Descriptions, Sensor(s)):** \u003cbr\u003e\n* Not Applicable \u003cbr\u003e\n\n### Evaluation Dataset:\n\n**Data Collection Method by dataset** \u003cbr\u003e\n* Hybrid: Automated, Synthetic \u003cbr\u003e\n\n**Labeling Method by dataset** \u003cbr\u003e\n* Not Applicable \u003cbr\u003e\n\n**Properties (Quantity, Dataset Descriptions, Sensor(s)):** \u003cbr\u003e\n* 100 question/answer pairs (text) \u003cbr\u003e\n\n### Inference:\n\n**Engine:** \u003cbr\u003e\n* TensorRT \u003cbr\u003e\n\n**Test Hardware:** \u003cbr\u003e\n* H100 \u003cbr\u003e\n\n### Ethical Considerations (For NVIDIA Models Only):\n\nNVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their internal model team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse. For more detailed information on ethical considerations for this model, please see the Model Card++ Explainability, Bias, Safety \u0026 Security, and Privacy Subcards.\n"])</script><script>self.__next_f.push([1,"b0:T990,"])</script><script>self.__next_f.push([1,"Field | Response\n:------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------\nIntended Application \u0026 Domain: | Generating code for and answering questions related to OpenUSD.\nModel Type: | Code Generation\nIntended Users: | This model is intended for developers to learn and develop with OpenUSD.\nOutput: | Text\nDescribe how the model works: | Text input is passed into transformer-based language model and output is text.\nName the adversely impacted groups this has been tested to deliver comparable outcomes regardless of: | Not Applicable\nTechnical Limitations: | This model may not produce accurate OpenUSD code when handling complex scene hierarchies and advanced USD features that require domain-specific knowledge.\nVerified to have met prescribed NVIDIA quality standards: | Yes\nPerformance Metrics: | Accuracy\nPotential Known Risks: | This model may produce inaccurate OpenUSD code and/or code outside of OpenUSD.\nLicensing: | GOVERNING TERMS: This trial is governed by the [NVIDIA API Trial Terms of Service](https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf). The use of this model is governed by the [AI Foundation Models Community License Agreement](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-ai-foundation-models-community-license-agreement/). ADDITIONAL INFORMATION: Meta Llama 3 Community License, Built with Meta Llama 3."])</script><script>self.__next_f.push([1,"b1:T517,| Field | Response |\n| -- | -- |\n| Generatable or reverse engineerable personally-identifiable information (PII)? | None |\n| Protected classes used to create this model? | Not Applicable (No PII) |\n| Was consent obtained for any personal data used? | Not Applicable (No personal data) |\n| How often is dataset reviewed? | \tBefore Release |\n| Is a mechanism in place to honor data subject right of access or deletion of personal data? | No |\n| If personal data collected for the development of the model, was it collected directly by NVIDIA? |Not Applicable |\n| If personal data collected for the development of the model by NVIDIA, do you maintain or have access to disclosures made to data subjects?\t| Not Applicable |\n| If personal data collected for the development of this AI model, was it minimized to only what was required? | Not Applicable |\n| Is there provenance for all datasets used in training? | Yes |\n| Does data labeling (annotation, metadata) comply with privacy laws? | Yes |\n| Is data compliant with data subject requests for data correction or removal, if such a request was made? | Yes |\n| Applicable NVIDIA Privacy Policy\t| [https://www.nvidia.com/en-us/data-center/products/nvidia-ai-enterprise/eula/](https://www.nvidia.com/en-us/data-center/products/nvidia-ai-enterprise/eula/) |b2:Td7a,"])</script><script>self.__next_f.push([1,"## USD Search\n\n### Model Overview\n\nUSD Search is an AI-powered search for OpenUSD data, three dimensional (3D) models, images, and assets using text or image-based inputs. It leverages NVCLIP, which is a NVIDIA commercial version of the \"Contrastive Language-Image Pre-Training (CLIP)\" model that transforms an image into textual embeddings.\n\n### References:\n\n- Radford, Alec, et al. \"Learning transferable visual models from natural language supervision.\" International conference on machine learning. PMLR, 2021.\n\n### Model Architecture:\n\n**Architecture Type:** Transformer-based architecture \u003cbr\u003e\n\n### Input:\n\n**Input Type(s):** Text or Image \u003cbr\u003e\n**Input Format(s):** Text, or Red, Green, Blue (RGB) \u003cbr\u003e\n**Other Properties Related to Input:** The model accepts either text or image input, but not both simultaneously \u003cbr\u003e\n\n### Output:\n\n**Output Type(s):** List \u003cbr\u003e\n**Output Format:** Rendered thumbnails, asset metadata \u003cbr\u003e\n**Other Properties Related to Output:** \u003cbr\u003e\nThe output of this model is a sorted-by-relevance list of OpenUSD assets. List contains rendered thumbnails and associated metadata containing URL pointing to the location of the asset in the backend database.\n\n### Software Integration:\n\n**Runtime Engine(s):**\n* TensorRT \u003cbr\u003e\n\n**Supported Hardware Architecture(s):** \u003cbr\u003e\n* NVIDIA Ampere \u003cbr\u003e\n* NVIDIA Hopper \u003cbr\u003e\n* NVIDIA Lovelace \u003cbr\u003e\n\n**Supported Operating System(s):** \u003cbr\u003e\n* Linux \u003cbr\u003e\n\n### Model Version(s):\n\n- nv_clip_224_vit_h - NVCLIP ViT-H with 224 resolution.\n\n### Training \u0026 Evaluation:\n\nNo additional training or evaluation in addition to what has been done for the NVCLIP model.\n\n### Using this Model \u003ca class=\"anchor\" name=\"how_to_use_this_model\"\u003e\u003c/a\u003e\n\nThese models need to be used with NVIDIA hardware and software. For hardware, the models can run on any of the latest NVIDIA GPUs since NVIDIA Ampere.\n\n### Training Dataset:\n\n**Data Collection Method by dataset:** \u003cbr\u003e\n* Automated \u003cbr\u003e\n\n**Labeling Method by dataset:** \u003cbr\u003e\n* Automated \u003cbr\u003e\n\n**Properties:** \u003cbr\u003e\n\n| Dataset | No. of Images |\n|--|--|\n|NV Internal Data| 700M |\n\n### Evaluation Dataset:\n\n**Link:** [https://www.image-net.org/](https://www.image-net.org/)\n\n**Data Collection Method by dataset:** \u003cbr\u003e\n* Unknown \u003cbr\u003e\n\n**Labeling Method by dataset:** \u003cbr\u003e\n* Unknown \u003cbr\u003e\n\n**Properties:** \u003cbr\u003e\n50,000 validation images from [ImageNet dataset](https://www.image-net.org/download.php) \u003cbr\u003e\nThe performance details of the underlying NVCLIP model is noted below.\n\n##### Methodology and KPI\n\nThe performance of zero shot accuracy of NVCLIP on ImageNet validation dataset.\n\n| model | top-1 Accuracy |\n| ----------------------- | -------------- |\n| ViT-H-336 | 0.7786 |\n| ViT-L-336 | 0.7629 |\n\n### Inference:\n\n**Engine:** TensorRT \u003cbr\u003e\n**Test Hardware:** \u003cbr\u003e\n- A100\n- L40\n\n### Ethical Considerations:\n\nNVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their internal model team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse. For more detailed information on ethical considerations for this model, please see the Model Card++ Promise and the Explainability, Bias, Safety \u0026 Security, and Privacy Subcards.\n"])</script><script>self.__next_f.push([1,"b3:T458,| Field | Response |\n| -- | -- |\n| Intended Application(s) \u0026 Domain(s): | Generating image embedding that is aligned with text for zero-shot classification. |\n| Model Type: | Embedding Generation |\n| Intended Users: | This model is intended for developers building search engines, classification, detection/ segmentation models. |\n| Output: | Embedding Features |\n| Describe how the model works: | This model has a vision extractor and a text encoder trained for embedding alignment |\n| Technical Limitations: | Model needs a downstream task specific head to perform CV tasks. |\n| Verified to have met prescribed NVIDIA standards: | Yes |\n| Performance Metrics: | ImageNet zero-shot accuracy |\n| Licensing: | GOVERNING TERMS: This trial is governed by the [NVIDIA API Trial Terms of Service](https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf). The use of this model is governed by the [AI Foundation Models Community License Agreement](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-ai-foundation-models-community-license-agreement/). |b4:T9dd,"])</script><script>self.__next_f.push([1,"**USD Search** is a versatile AI-powered search engine designed to enable comprehensive searches across images\n(e.g., .jpg, .png) and USD-based 3D models within various storage backends (AWS S3 and Omniverse Nucleus server).\nIt enables users to use natural language, image similarity, and precise metadata criteria\n(file name, type, date, size, creator, etc.) to locate relevant content efficiently. Furthermore, when integrated\nwith the Asset Graph Service, DeepSearch extends its capabilities to include searches based on USD properties and\nspatial dimensions of 3D model bounding boxes, enhancing the ability to find assets that meet specific requirements.\n\n## Features\n\n- **Natural Language Searches**: Utilize AI to search for images and USD-based 3D models using simple, descriptive\n language.\n- **Image Similarity Searches**: Find images similar to a reference image through AI-driven image comparisons.\n- **Metadata Filtering**: Filter search results by file name, file type, creation/modification dates, file size, and\n creator/modifier metadata.\n- **USD Content Filtering with Asset Graph Service**: When used with the Asset Graph Service, search capabilities are\n expanded to include filtering based on USD properties and object dimensions.\n- **Multiple Storage Backend Support**: Compatible with various storage backends, including AWS S3 bucket and Omniverse Nucleus server.\n- **Advanced File Name, Extension and Path Filters**: Use wildcards for broad or specific file name and extension searches.\n- **Date and Size Range Filtering**: Specify assets created or modified within certain date ranges or file sizes larger\n or smaller than a designated threshold.\n- **User-based Filtering**: Filter assets based on their creator or modifier, allowing for searches tailored to\n particular users' contributions.\n- **Embedding-based Similarity Threshold**: Set a similarity threshold for more nuanced control over search results in\n embedding-based searches.\n- **Custom Search Paths and Scenes**: Specify search locations within the storage backend or conduct searches within\n specific scenes for targeted results.\n- **Return Detailed Results**: Option to include images, metadata, root prims, and predictions in the search results.\n\n\nFeatures available only with the **Asset Graph Service**:\n- **USD Property Filtering**\n- **USD Object Dimension Filtering**\n- **In-scene searches**\n\n## Resources\n\n* [DeepSearch Documentation](https://docs.omniverse.nvidia.com/services/latest/services/deepsearch/overview.html)\n"])</script><script>self.__next_f.push([1,"b5:T713,Field | Response\n:----------------------------------------------------------------------------------------------------------------------------------|:-----------------------------------------------\nGeneratable or reverse engineerable personally-identifiable information (PII)? | None\nWas consent obtained for any PII used? | N/A\nProtected class data used to create this model? | N/A\nHow often is dataset reviewed? | N/A\nIs a mechanism in place to honor data subject right of access or deletion of personal data? | N/A\nIf personal data collected for the development of the model, was it collected directly by NVIDIA? | N/A\nIf personal data collected for the development of the model by NVIDIA, do you maintain or have access to disclosures made to data subjects? | N/A\nIf personal data collected for the development of this AI model, was it minimized to only what was required? | N/A\nIs there provenance for all datasets used in training? | N/A\nDoes data labeling (annotation, metadata) comply with privacy laws? | N/A\nIs data compliant with data subject requests for data correction or removal, if such a request was made?b6:T6e9,## Model Overview\n\n### Description:\n\nUSD Validate is a service for rule based and visual validation of usdz files. It is based on the Omniverse [Embedded Web Viewer](https://docs.omniverse.nvidia.com/embedded-web-viewer/l"])</script><script>self.__next_f.push([1,"atest/) and the [Asset Validator Extension](https://docs.omniverse.nvidia.com/kit/docs/asset-validator/latest/index.html).\n\nThis service is for demonstration purposes and not for production usage.\n\n### References(s):\n\n* [Omniverse Embedded Web Viewer](https://docs.omniverse.nvidia.com/embedded-web-viewer/latest/)\n* [Asset Validator Extension](https://docs.omniverse.nvidia.com/kit/docs/asset-validator/latest/index.html)\n* [OpenUSD USDChecker](https://openusd.org/release/toolset.html#usdchecker)\n\n### Model Architecture:\n\n**Architecture Type:** Not Applicable (N/A) \u003cbr\u003e\n**Network Architecture:** Not Applicable (N/A) \u003cbr\u003e\n\n### Input:\n\n**Input Type(s):** 3D File, Validation Rule Identifiers, and Viewport Commands\u003cbr\u003e\n**Input Format(s):** USDZ, String Array, and Webrtc Data Channel \u003cbr\u003e\n\n#### Other Properties Related to Input:\n\n* MaterialX, OpenPbr and MDL materials are currently unsupported in USDZ. \u003cbr\u003e\n* UDIM texture tiles are currently unsupported in USDZ\u003cbr\u003e\n\n### Output:\n\n**Output Type(s):** Interactive Viewport and Validation Results SUmmary \u003cbr\u003e\n**Output Format:** WebRTC stream and Json \u003cbr\u003e\n**Other Properties Related to Output:** \u003cbr\u003e\nThe output of this service is currently limited to the webRTC stream / data channel only.\n\n### Software Integration:\n\n**Runtime Engine(s):**\n* Not Applicable (N/A) \u003cbr\u003e\n\n**Supported Hardware Microarchitecture Compatibility:** \u003cbr\u003e\n* NVIDIA Lovelace \u003cbr\u003e\n* NVIDIA Ampere \u003cbr\u003e\n\n### Preferred/Supported Operating System(s):\n\n* Linux \u003cbr\u003e\n* Cuda \u003e 12.2.2 \u003cbr\u003e\n* NVIDIA driver \u003e 535.129.03 \u003cbr\u003e\n\n"])</script><script>self.__next_f.push([1,"21:[\"$\",\"$L3c\",null,{\"data\":[{\"endpoint\":{\"requestStatus\":{\"statusCode\":\"SUCCESS\",\"requestId\":\"5d88b896-d28c-4006-814f-34a795171c26\"},\"artifact\":{\"orgName\":\"qc69jvmznzxy\",\"labels\":[\"Chat\",\"Code Generation\",\"NVIDIA NIM\",\"OpenUSD\",\"Code Generation\",\"Digital Twin\",\"Synthetic Data Generation\"],\"bias\":\"Field | Response\\n:---------------------------------------------------------------------------------------------------|:---------------\\nParticipation considerations from adversely impacted groups [protected classes](https://www.senate.ca.gov/content/protected-classes) in model design and testing: | Not Applicable\\nMeasures taken to mitigate against unwanted bias: | None of the Above\",\"logo\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/usdcode-llama3-70b-instruct.jpg\",\"shortDescription\":\"State-of-the-art LLM that answers OpenUSD knowledge queries and generates USD-Python code.\",\"safetyAndSecurity\":\"Field | Response\\n:---------------------------------------------------|:----------------------------------\\nModel Application(s): | Answering OpenUSD knowledge questions and generating Python USD code\\nDescribe the life critical impact (if present). | None: Not within Operational Design Domain\\nUse Case Restrictions: | Abide by [NVIDIA API Trial Terms of Service](https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf), and [AI Foundation Models Community License Agreement](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-ai-foundation-models-community-license-agreement/).\\nModel and dataset restrictions: | The Principle of least privilege (PoLP) is applied limiting access for dataset generation and model development. 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The use of this model is governed by \u003ca href=\\\"https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-ai-foundation-models-community-license-agreement/\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003ethe AI Foundation Models Community License Agreement\u003c/a\u003e. 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Prims\"}},\"type\":\"object\",\"required\":[\"url\",\"score\"],\"title\":\"SearchResult\",\"examples\":[{\"url\":\"omniverse://simready.ov.nvidia.com/Projects/cardbox_a2.usd\",\"score\":1.2529583,\"root_prims\":[{\"scene_url\":\"omniverse://simready.ov.nvidia.com/Projects/cardbox_a2.usd\",\"usd_path\":\"/RootNode\",\"prim_type\":\"Xform\",\"bbox_max\":[0.34971755743026733,0.2549635171890259,0.5211517214775085],\"bbox_min\":[-0.34971755743026733,-0.25496378540992737,1.9483268332010084e-8],\"bbox_midpoint\":[0,-1.341104507446289e-7,0.26057587048038844],\"bbox_dimension_x\":0.6994351148605347,\"bbox_dimension_y\":0.5099273025989532,\"bbox_dimension_z\":0.5211517019942402,\"properties\":{\"semantic:QWQQ:params:semanticData\":\"Q1395006\",\"semantic:QWQL:params:semanticType\":\"class\",\"semantic:QWQQ:params:semanticType\":\"qcode\",\"semantic:QWQC:params:semanticData\":\"container/product packaging/box/cardboard box\",\"semantic:QWQL:params:semanticData\":\"cardboard box\",\"semantic:QWQC:params:semanticType\":\"hierarchy\"}}],\"metadata\":{\"created\":\"Mon Mar 20 22:06:58 2023\",\"created_by\":\"user@nvidia.com\",\"modified\":\"Mon Mar 20 22:06:58 2023\",\"modified_by\":\"user@nvidia.com\",\"size\":14938,\"etag\":\"169176\"},\"vision_generated_metadata\":{\"vision_generated_object_type\":\"electric guitar, musical instrument, guitar\",\"vision_generated_materials\":\"wood, metal, plastic\"}}]},\"StatusType\":{\"enum\":[\"OK\",\"DENIED\",\"TOKEN_EXPIRED\",\"UNAUTHORIZED\",\"ES_REQUEST_ERROR\",\"ES_CONNECTION_TIMEOUT\",\"FILE_NOT_FOUND_ERROR\",\"THUMBNAIL_MISSING_ERROR\",\"INVALID_PREFIX\",\"UNKNOWN_ERROR\",\"PROJECTION_SERVICE_UNAVAILABLE\",\"REST_API_UNAVAILABLE\"],\"title\":\"StatusType\",\"description\":\"An enumeration.\"},\"ValidationError\":{\"properties\":{\"loc\":{\"items\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"integer\"}]},\"type\":\"array\",\"title\":\"Location\"},\"msg\":{\"type\":\"string\",\"title\":\"Message\"},\"type\":{\"type\":\"string\",\"title\":\"Error Type\"}},\"type\":\"object\",\"required\":[\"loc\",\"msg\",\"type\"],\"title\":\"ValidationError\"}},\"securitySchemes\":{\"Token\":{\"type\":\"http\",\"scheme\":\"bearer\"}}}},\"namespace\":\"qc69jvmznzxy\",\"updatedDate\":\"2024-11-14T16:34:01.464Z\",\"nvcfFunctionId\":\"1e006b75-c292-4cde-8201-ffaab26c5a88\",\"createdDate\":\"2024-07-29T19:07:06.898Z\",\"attributes\":{\"requiresLogin\":false,\"showUnavailableBanner\":false,\"apiDocsUrl\":\"https://docs.api.nvidia.com/nim/reference/nvidia-usdsearch\",\"termsOfUse\":\"GOVERNING TERMS: This trial is governed by the [NVIDIA API Trial Terms of Service](https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf). The use of this model is governed by the [AI Foundation Models Community License Agreement](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-ai-foundation-models-community-license-agreement/).\\n\",\"cta\":{\"text\":\"Download and Self-deploy\",\"url\":\"https://catalog.ngc.nvidia.com/orgs/nvidia/teams/usdsearch/collections/usdsearch\"},\"projects\":[{\"name\":\"Get started with this NVIDIA NIM microservice today\",\"url\":\"https://docs.omniverse.nvidia.com/usdsearch/get-started.html\",\"imageUrl\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/usdsearch.jpg\",\"workbench\":false}]},\"artifactName\":\"usdsearch\"},\"config\":{\"name\":\"usdsearch\",\"type\":\"model\"}},{\"endpoint\":{\"requestStatus\":{\"statusCode\":\"SUCCESS\",\"requestId\":\"2491c9f1-60f8-431e-adf5-a5f5b9cf2f10\"},\"artifact\":{\"orgName\":\"qc69jvmznzxy\",\"labels\":[\"OpenUSD\",\"USD\",\"Validation\",\"Visualization 3D\",\"Digital Twin\",\"Synthetic Data Generation\"],\"bias\":\"Field | Response\\n:---------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------\\nParticipation considerations from adversely impacted groups [protected classes](https://www.senate.ca.gov/content/protected-classes) in model design and testing: | None\\nMeasures taken to mitigate against unwanted bias: | None\",\"logo\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/usdvalidate.jpg\",\"shortDescription\":\"Verify compatibility of OpenUSD assets with instant RTX render and rule-based validation.\",\"safetyAndSecurity\":\"Field | Response\\n:---------------------------------------------------|:----------------------------------\\nModel Application(s): | Validation of USDZ files.\\nDescribe the life-critical impact (if present). | None\\nUse Case Restrictions: | For Non-Commerical/Evaluation Use Only\\nModel and dataset restrictions: | The Principle of Least Privilege (PoLP) is applied limiting access for USD Validate's development. Restrictions enforce solver access and solver license constraints adhered to.\",\"privacy\":\"$b5\",\"isReadOnly\":true,\"description\":\"$b6\",\"canGuestDownload\":true,\"isPublic\":true,\"createdDate\":\"2024-07-24T23:25:20.013Z\",\"publisher\":\"nvidia\",\"displayName\":\"usdvalidate\",\"name\":\"usdvalidate\",\"explainability\":\"| Field | Response |\\n| -- | -- |\\n| Intended Application(s) \u0026 Domain(s): | Rule based and visual validation of usdz files |\\n| Model Type: | n/a |\\n| Intended Users: | This service is intended for developers building USD based data pipelines, asset libraries and Omniverse streaming applications. |\\n| Output: | Interactive 3D viewport and text. |\\n| Describe how the model works: | USDZ files are rendered with the Omniverse RTX renderer and validated. |\\n| Technical Limitations: | Validation results are summarized to limit response size. |\\n| Verified to have met prescribed NVIDIA standards: | Yes |\\n| Performance Metrics: | Interactivity, Accuracy |\\n| Licensing: | GOVERNING TERMS: This trial is governed by the [NVIDIA API Trial Terms of Service](https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf). |\",\"updatedDate\":\"2024-11-06T17:18:57.311Z\",\"attributes\":[{\"key\":\"PREVIEW\",\"value\":\"true\"}],\"artifactType\":\"ENDPOINT\"}},\"spec\":{\"openAPISpec\":{\"openapi\":\"3.1.0\",\"info\":{\"title\":\"Some Category\",\"description\":\"Your will replace this file with your NVIDIA NIM REST API. Please follow API governance guidelines\",\"version\":\"1.0.0\",\"termsOfService\":\"https://nvidia.com/legal/terms-of-use\",\"contact\":{\"name\":\"NVIDIA Support\",\"url\":\"https://help.nvidia.com/\"},\"license\":{\"name\":\"Name\",\"url\":\"https://place\"}},\"servers\":[{\"url\":\"https://ai.api.nvidia.com/v1/\"}],\"paths\":{\"/gatewaypath/family/model\":{\"post\":{\"summary\":\"Perform inference\",\"operationId\":\"rename-this-rename-also-infer\",\"requestBody\":{\"content\":{\"application/json\":{}}}},\"x-nvai-meta\":{\"templates\":[{\"requestEjs\":{\"python\":\"\",\"node\":\"\",\"shell\":\"\"}}]}}},\"security\":[{\"Token\":[]}],\"components\":{\"securitySchemes\":{\"Token\":{\"type\":\"http\",\"scheme\":\"bearer\"}}}},\"namespace\":\"qc69jvmznzxy\",\"updatedDate\":\"2024-11-06T17:18:57.701Z\",\"nvcfFunctionId\":\"04462117-bb59-4e0c-80d2-faeeb9932d7c\",\"createdDate\":\"2024-07-24T23:25:20.291Z\",\"attributes\":{\"requiresLogin\":false,\"showUnavailableBanner\":false,\"apiDocsUrl\":null,\"termsOfUse\":\"\u003cb\u003eNotes:\u003c/b\u003e Please note that MDL and MaterialX materials are currently unsupported, as well as UDIM textures.\u003cbr\u003e\\n\u003cb\u003eGOVERNING TERMS:\u003c/b\u003e Use of this trial service is governed by the \u003ca href=\\\"https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA_Technology_Access_TOU.pdf\\\"\u003eNVIDIA Technology Access Terms of Use\u003c/a\u003e.\u003cbr\u003e\\n\u003cb\u003ePRIVACY Policy:\u003c/b\u003e Use of this trial service is covered by the \u003ca href=\\\"https://www.nvidia.com/en-us/about-nvidia/privacy-policy/\\\"\u003eNVIDIA Privacy Policy\u003c/a\u003e\\n\"},\"artifactName\":\"usdvalidate\"},\"config\":{\"name\":\"usdvalidate\",\"type\":\"model\"}}]}]\n"])</script><script>self.__next_f.push([1,"b7:T770,Field | Response\n:----------------------------------------------------------------------------------------------------------------------------------|:-----------------------------------------------\nGeneratable or reverse engineerable personally-identifiable information (PII)? | None\nWas consent obtained for any personal data used? | Not Applicable (N/A)\nProtected class data used to create this model? | None\nHow often is dataset reviewed? | Before Release\nIs a mechanism in place to honor data subject right of access or deletion of personal data? | No\nIf personal data collected for the development of the model, was it collected directly by NVIDIA? | N/A\nIf personal data collected for the development of the model by NVIDIA, do you maintain or have access to disclosures made to data subjects? | N/A\nIf personal data collected for the development of this AI model, was it minimized to only what was required? | N/A\nIs there provenance for all datasets used in training? | Yes\nDoes data labeling (annotation, metadata) comply with privacy laws? | Yes\nIs data compliant with data subject requests for data correction or removal, if such a request was made?b8:T1688,"])</script><script>self.__next_f.push([1,"## Model Overview\n\n### Description\n\nFourCastNet V2 uses Spherical Fourier Neural Operator (SFNO) to predict a collection of surface and atmospheric variables such as wind speed, temperature and pressure and is applied to forecasting global atmospheric dynamics.\n\nFourCastNet is a data-driven model that provides accurate short to medium-range global predictions at a time-step size of 6 hours with predictive stability for over a year of simulated time (1,460 steps), while retaining physically plausible dynamics.\n\nThis model is ready for commercial use.\n\n### Reference(s)\n\n* [Spherical Fourier Neural Operator Paper](https://arxiv.org/abs/2306.03838) \u003cbr\u003e\n* [FourCastNet Paper](https://arxiv.org/abs/2202.11214) \u003cbr\u003e\n* [Codebase](https://github.com/NVIDIA/modulus) \u003cbr\u003e\n* [The ERA5 global reanalysis](https://doi.org/10.1002/qj.3803) \u003cbr\u003e\n\n### Model Architecture\n\n**Architecture Type:** Neural Operator \u003cbr\u003e\n**Network Architecture:** FourCastNet SFNO \u003cbr\u003e\n\n### Input\n\n**Input Type(s):**\n\n- Tensor (73 Surface \u0026 Atmospheric Variables)\n- DateTime\u003cbr\u003e\n\n**Input Format(s):** NumPy \u003cbr\u003e\n**Input Parameters:**\n\n- Four Dimensional (4D) (batch, variable, latitude, longitude) \u003cbr\u003e\n- Input DateTime\u003cbr\u003e\n\n**Other Properties Related to Input:**\n- 0.25 degree latitude-longitude grid\n- Input resolution: [721, 1440]\n- Latitude Coordinates: [90, 89.75, 89.5, ..., -89.5, -89.75, -90]\n- Longitude Coordinates: [0, 0.25, 0.5, ..., 359.25, 359.5, 359.75]\n- Input weather variables: \"u10m\", \"v10m\", \"u100m\", \"v100m\", \"t2m\", \"sp\", \"msl\", \"tcwv\", \"u50\", \"u100\", \"u150\", \"u200\", \"u250\", \"u300\", \"u400\", \"u500\", \"u600\", \"u700\", \"u850\", \"u925\", \"u1000\", \"v50\", \"v100\", \"v150\", \"v200\", \"v250\", \"v300\", \"v400\", \"v500\", \"v600\", \"v700\", \"v850\", \"v925\", \"v1000\", \"z50\", \"z100\", \"z150\", \"z200\", \"z250\", \"z300\", \"z400\", \"z500\", \"z600\", \"z700\", \"z850\", \"z925\", \"z1000\", \"t50\", \"t100\", \"t150\", \"t200\", \"t250\", \"t300\", \"t400\", \"t500\", \"t600\", \"t700\", \"t850\", \"t925\", \"t1000\", \"q50\", \"q100\", \"q150\", \"q200\", \"q250\", \"q300\", \"q400\", \"q500\", \"q600\", \"q700\", \"q850\", \"q925\", \"q1000\"\u003cbr\u003e\n\n### Output\n\n**Output Type(s):**\n\n- Tensor (73 Surface \u0026 Atmospheric Variables)\n\n**Output Format(s):** NumPy \u003cbr\u003e\n**Output Parameters:**\n\n- Four Dimensional (4D) (batch, variable, latitude, longitude) \u003cbr\u003e\n\n**Other Properties Related to Output:**\n- Time-delta of 6 hours from input array\n- 0.25 degree latitude-longitude grid\n- Output resolution: [721, 1440]\n- Latitude Coordinates: [90, 89.75, 89.5, ..., -89.5, -89.75, -90]\n- Longitude Coordinates: [0, 0.25, 0.5, ..., 359.25, 359.5, 359.75]\n- Output weather variables: \"u10m\", \"v10m\", \"u100m\", \"v100m\", \"t2m\", \"sp\", \"msl\", \"tcwv\", \"u50\", \"u100\", \"u150\", \"u200\", \"u250\", \"u300\", \"u400\", \"u500\", \"u600\", \"u700\", \"u850\", \"u925\", \"u1000\", \"v50\", \"v100\", \"v150\", \"v200\", \"v250\", \"v300\", \"v400\", \"v500\", \"v600\", \"v700\", \"v850\", \"v925\", \"v1000\", \"z50\", \"z100\", \"z150\", \"z200\", \"z250\", \"z300\", \"z400\", \"z500\", \"z600\", \"z700\", \"z850\", \"z925\", \"z1000\", \"t50\", \"t100\", \"t150\", \"t200\", \"t250\", \"t300\", \"t400\", \"t500\", \"t600\", \"t700\", \"t850\", \"t925\", \"t1000\", \"q50\", \"q100\", \"q150\", \"q200\", \"q250\", \"q300\", \"q400\", \"q500\", \"q600\", \"q700\", \"q850\", \"q925\", \"q1000\"\u003cbr\u003e\n\n### Software Integration\n\n**Runtime Engine(s):** Not Applicable \u003cbr\u003e\n**Supported Hardware Microarchitecture Compatibility:** \u003cbr\u003e\n* Ampere \u003cbr\u003e\n* Hopper \u003cbr\u003e\n* Turing \u003cbr\u003e\n\n**Supported Operating System(s):**\n* Linux \u003cbr\u003e\n\n### Model Version(s)\n\n**Model version:** v1 \u003cbr\u003e\n\n## Training, Testing, and Evaluation Datasets:\n\n### Training Dataset\n\n**Link:** [ERA5](https://cds.climate.copernicus.eu/) \u003cbr\u003e\n\n*Data Collection Method by dataset* \u003cbr\u003e\n* Automatic/Sensors \u003cbr\u003e\n\n*Labeling Method by dataset* \u003cbr\u003e\n* Automatic/Sensors \u003cbr\u003e\n\n**Properties (Quantity, Dataset Descriptions, Sensor(s)):**\nERA5 data for the years of 1979-2017. ERA5 provides hourly estimates of various\natmospheric, land, and oceanic climate variables. The data covers the Earth on a 30km\ngrid and resolves the atmosphere at 137 levels. \u003cbr\u003e\n\n### Evaluation Dataset\n\n**Link:** [ERA5](https://cds.climate.copernicus.eu/) \u003cbr\u003e\n\n*Data Collection Method by dataset* \u003cbr\u003e\n* Automatic/Sensors \u003cbr\u003e\n\n*Labeling Method by dataset* \u003cbr\u003e\n* Automatic/Sensors \u003cbr\u003e\n\n**Properties (Quantity, Dataset Descriptions, Sensor(s)):**\nERA5 data for the year of 2018. ERA5 provides hourly estimates of various atmospheric,\nland, and oceanic climate variables. The data covers the Earth on a 30km grid and\nresolves the atmosphere at 137 levels. \u003cbr\u003e\n\n## Inference:\n\n**Engine:** [Triton](https://developer.nvidia.com/triton-inference-server) \u003cbr\u003e\n**Test Hardware:**\n* A100 \u003cbr\u003e\n* H100 \u003cbr\u003e\n* L40S \u003cbr\u003e\n* RTX6000 \u003cbr\u003e\n\n### Ethical Considerations:\n\nNVIDIA believes Trustworthy AI is a shared responsibility and we have established\npolicies and practices to enable development for a wide array of AI applications.\nWhen downloaded or used in accordance with our terms of service, developers should work\nwith their supporting model team to ensure this model meets requirements for the\nrelevant industry and use case and addresses unforeseen product misuse.\nFor more detailed information on ethical considerations for this model, please see the\nModel Card++ Explainability, Bias, Safety \u0026 Security, and Privacy Subcards [here](https://ai.nvidia.com).\nPlease report security vulnerabilities or NVIDIA AI Concerns [here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/).\n\n### License\n\nThis model is licensed under the [NVIDIA AI Product Agreement](https://www.nvidia.com/en-us/agreements/enterprise-software/product-specific-terms-for-ai-products/). By pulling and using this model, you accept the terms and conditions of this license.\n\n**You are responsible for ensuring that your use of NVIDIA AI Foundation Models complies with all applicable laws.**\n"])</script><script>self.__next_f.push([1,"b9:T801,"])</script><script>self.__next_f.push([1,"Field | Response\n:------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------\nIntended Application \u0026 Domain: | Global Weather Forecasting\nModel Type: | Neural Operator\nIntended User: | Climate and Weather scientists accelerating weather prediction with AI.\nOutput: | Global forecast prediction of surface and atmosphere variables.\nDescribe how the model works: | Neural operator auto-regressively predicts a time-series forecast from an initial state.\nName the adversely impacted groups this has been tested to deliver comparable outcomes regardless of: | Not Applicable\nTechnical Limitations: | The model may perform poorly for longer range forecasts and atmospheric data sources different from that in the ERA5 training dataset\nVerified to have met prescribed NVIDIA quality standards: | Yes\nPerformance Metrics: | Accuracy, Throughput and Latency\nPotential Known Risks: | This model may mispredict global atmospheric dynamics.\nLicensing: | [Earth-2 Service Terms of Use](https://ngc.nvidia.com/legal/terms)"])</script><script>self.__next_f.push([1,"ba:T679,Pull and run the [NVIDIA Earth-2 FourCastNet NIM](https://catalog.ngc.nvidia.com/orgs/nim/teams/nvidia/containers/fourcastnet) with the command below. \n\n```bash\ndocker pull nvcr.io/nim/nvidia/fourcastnet:1.0.0\n```\n\nThis will download the optimized model for your infrastructure.\n\n```bash\nexport NGC_API_KEY=\u003cNGC API Key\u003e\n\ndocker run --rm --runtime=nvidia --gpus all --shm-size 4g \\\n -p 8000:8000 \\\n -e NGC_API_KEY \\\n nvcr.io/nim/nvidia/fourcastnet:1.0.0\n```\n\nCheck the health of the NIM with the following curl command:\n\n```bash\ncurl -X 'GET' \\\n 'http://localhost:8000/v1/health/ready' \\\n -H 'accept: application/json'\n```\n\nGenerate an input numpy array for the model using the following Python script with [Earth2Studio](https://github.com/NVIDIA/earth2studio):\n\n```python\nimport numpy as np\nfrom datetime import datetime\nfrom earth2studio.data import ARCO\nfrom earth2studio.models.px.sfno import VARIABLES\n\nds = ARCO()\nda = ds(time=datetime(2023, 1, 1), variable=VARIABLES)\nnp.save(\"fcn_inputs.npy\", da.to_numpy()[None].astype('float32'))\n```\n\nYou can now make a local API call using this curl command:\n\n```bash\ncurl -X POST \\\n -F \"input_array=@fcn_inputs.npy\" \\\n -F \"input_time=2023-01-01T00:00:00Z\" \\\n -F \"simulation_length=4\" \\\n -o output.tar \\\n http://localhost:8000/v1/infer\n```\n\nFor more details on getting started with this NIM, visit the [NVIDIA NIM Docs](https://docs.nvidia.com/nim/earth-2/fourcastnet/latest/getting-started.html).\nFor more details on the model and its input / output tensors see the [FourCastNet SFNO Model Card](https://catalog.ngc.nvidia.com/orgs/nim/teams/nvidia/models/earth2-sfno-era5-73ch).\nbb:T777,Field | Response\n:----------------------------------------------------------------------------------------------------------------------------------|:-----------------------------------------------\nGeneratable or reverse engineerable personally-iden"])</script><script>self.__next_f.push([1,"tifiable information (PII)? | None\nWas consent obtained for any PII used? | Not Applicable (N/A); user should consider PII implications when using actual addresses for routing.\nProtected class data used to create this model? | N/A\nHow often is dataset reviewed? | N/A\nIs a mechanism in place to honor data subject right of access or deletion of personal data? | N/A\nIf PII collected for the development of the model, was it collected directly by NVIDIA? | N/A\nIf PII collected for the development of the model by NVIDIA, do you maintain or have access to disclosures made to data subjects? | N/A\nIf PII collected for the development of this AI model, was it minimized to only what was required? | N/A\nIs there provenance for all datasets used in training? | N/A\nDoes data labeling (annotation, metadata) comply with privacy laws? | N/A\nIs data compliant with data subject requests for data correction or removal, if such a request was made? | N/Abc:T14b6,"])</script><script>self.__next_f.push([1,"## Model Overview\n\n### Description\n\n**NVIDIA cuOpt** is an AI microservice that optimizes logistics routing to save enterprises money, increase revenue, and reduce carbon emissions. It offers dynamic rerouting, horizontal load-balancing, and robotic simulations, with sub second solver response times. cuOpt enables organizations to easily access world record accelerated optimization capabilities across multi- and hybrid cloud environments. It solves complex routing problems with multiple constraints and delivers new capabilities, empowering teams to make dynamic, data-driven decisions.\n\nToday, cuOpt focuses primarily on variants of Vehicle Routing Problems (VRP) such as Capacitated Vehicle Routing Problems (CVRP), Capacitated Vehicle Routing with Time Windows (CVRTW), and Pick up and Delivery with Time Windows (PDPTW). To solve these problems, NVIDIA cuOpt uses GPU-accelerated logistics solvers relying on heuristics, metaheuristics, and optimization to calculate complex vehicle-routing-problem variants with a wide range of constraints.Typical Use Cases\n\n- **Last Mile Delivery (LMD)**: A fleet of vehicles is tasked with serving customers at multiple locations or demand points, typically with the goal of minimizing total costs, such as fleet size, distance traveled or time taken, while satisfying various constraints and objectives. Each customer has specific demand along with other constraints such as time windows and other service level agreements. Each vehicle may be bound by constraints such as such as maximum load capacity, maximum travel distance, emission types and availability. In Manufacturing, the last mile is the supply of components in a production process, e.g., the delivery of parts to the plant. In Distribution (B2B), the last mile is the supply of stock to physical stores for in-store experiences. In E-Commerce (B2C)/Grocery/Parcel/Quick Service delivery, the last mile is the hand-off point to customer or to a prearranged drop-off location.\n\n- **Dispatch Optimization**: This involves the allocation and scheduling of field service technicians to fulfill customer orders, service requests or deliveries. Determining the most efficient routes for vehicles or technicians based on factors such as location, capacity, availability, skillset, priority, and regulatory compliance. The objective could be to minimize travel time, distance, fuel consumption, maximize the number of tasks or service calls, or minimize empty space and unnecessary trips. Implement continuous optimization by processing dynamic events to accommodate changes, disruptions, or new requests while increasing productivity and maintaining service level agreements (SLAs). Option available to allocate tasks evenly by balancing workload distribution to prevent overloading or under-utilization of service personnel. Dispatch optimization is essential for any businesses with field service operations, transportation and logistics, emergency response teams, health or hunger drives and any other operations that involve routing of field assets.\n\n- **Pickup and Delivery (PDP) –** This involves determining the most efficient routes for a fleet of vehicles to pick up items from specified pick-up points and deliver them to specified drop-off points, while satisfying various constraints and objectives. The objective could be to minimize total travel time, minimize fleet size, maximizing vehicle utilization, minimize transportation costs, reduce emissions while ensuring timely delivery and maintaining customer service level agreements (SLAs). Both pick-up and drop-off locations have capacity constraints, geographical proximity/constraints, service durations, time windows, precedence relationships and customer preferences. The fleet also has constraints such as limited capabilities, maximum load, maximum travel distance, or reduced emissions. Pickup and delivery use cases can be applied in various routing scenarios: Quick service food delivery, ride hailing, retail distribution, parcel delivery, intralogistics routing, school bus routing, and waste collection.\n\n### Terms of use\n\nBy using this software or microservice, you are agreeing to the [terms and conditions](https://www.nvidia.com/en-us/data-center/products/nvidia-ai-enterprise/eula/) of the license and acceptable use policy.\n\n#### References(s):\n\n- [NVIDIA cuOpt docs](https://docs.nvidia.com/cuopt/) \u003cbr\u003e\n- [NVIDIA cuOpt Resources](https://github.com/NVIDIA/cuOpt-Resources/tree/branch-24.07) \u003cbr\u003e\n- [DLI Course on NVIDIA cuOpt](https://www.nvidia.com/en-us/training/) \u003cbr\u003e\n\n### Model Architecture\n\n**Architecture Type:** Not Applicable (N/A) \u003cbr\u003e\n**Network Architecture:** Not Applicable (N/A) \u003cbr\u003e\n**Container Version:** 24.07.00 \u003cbr\u003e\n\n### Input\n\n**Input Format:** Json data in Text or File format. \u003cbr\u003e\n**Input Parameters:** Please refer to [open-api](https://docs.nvidia.com/cuopt/user-guide/open-api.html) specification.\n\n### Output\n\n**Output Format:** Json data in Text or File format. \u003cbr\u003e\n**Output Parameters:** Please refer to [open-api](https://docs.nvidia.com/cuopt/user-guide/open-api.html) specification. \u003cbr\u003e\n\n#### Software Integration:\n\n**Runtime(s):** N/A \u003cbr\u003e\n**Supported Hardware Platform(s):** Hopper, Ampere \u003cbr\u003e\n**Supported Operating System(s):** Linux and Windows(WSL) with CUDA \u003e= 11.8.\n"])</script><script>self.__next_f.push([1,"bd:T6a2,Field | Response\n:------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------\nIntended Applications \u0026 Domains: | Solving routing problems (transportation \u0026 delivery) and operations research to optimize for time and cost\nIntended Users: | Data scientists, operations research engineers, and AI developers building route optimization solutions\nOutput: | List of tasks (e.g. delivery, pick-up) per vehicle\nDescribe how the model works: | Solver calculates route-specific parameters based upon constraints. \nTechnical Limitations: | None\nVerified to have met prescribed NVIDIA quality standards: | Yes\nPerformance Metrics: | Throughput and Latency\nPotential Known Risks: | None Known\nLicensing: | [NVIDIA cuOpt AGREEMENT](https://ngc.nvidia.com/legal/terms)be:T4de,{\"action\":\"cuOpt_OptimizedRouting\",\"data\":{\"cost_waypoint_graph_data\":null,\"travel_time_waypoint_graph_data\":null,\"cost_matrix_data\":{\"data\":{\"1\":[[0,1,1],[1,0,1],[1,1,0]],\"2\":[[0,1,1],[1,0,1],[1,2,0]]}},\"travel_time_matrix_data\":{\"data\":{\"1\":[[0,1,1],[1,0,1],[1,1,0]],\"2\":[[0,1,1],[1,0,1],[1,2,0]]}},\"fleet_data\":{\"vehicle_locations\""])</script><script>self.__next_f.push([1,":[[0,0],[0,0]],\"vehicle_ids\":[\"veh-1\",\"veh-2\"],\"capacities\":[[2,2],[4,1]],\"vehicle_time_windows\":[[0,10],[0,10]],\"vehicle_break_time_windows\":[[[1,2],[2,3]]],\"vehicle_break_durations\":[[1,1]],\"vehicle_break_locations\":[0,1],\"vehicle_types\":[1,2],\"vehicle_order_match\":[{\"order_ids\":[0],\"vehicle_id\":0},{\"order_ids\":[1],\"vehicle_id\":1}],\"skip_first_trips\":[true,false],\"drop_return_trips\":[true,false],\"min_vehicles\":2,\"vehicle_max_costs\":[7,10],\"vehicle_max_times\":[7,10]},\"task_data\":{\"task_locations\":[1,2],\"task_ids\":[\"Task-A\",\"Task-B\"],\"demand\":[[1,1],[3,1]],\"task_time_windows\":[[0,5],[3,9]],\"service_times\":[0,0],\"order_vehicle_match\":[{\"order_id\":0,\"vehicle_ids\":[0]},{\"order_id\":1,\"vehicle_ids\":[1]}]},\"solver_config\":{\"time_limit\":1,\"objectives\":{\"cost\":1,\"travel_time\":0,\"variance_route_size\":0,\"variance_route_service_time\":0,\"prize\":0},\"verbose_mode\":false,\"error_logging\":true}},\"client_version\":\"\"}bf:T1078,"])</script><script>self.__next_f.push([1,"import requests\n\ninvoke_url = \"https://optimize.api.nvidia.com/v1/nvidia/cuopt\"\nfetch_url_format = \"https://optimize.api.nvidia.com/v1/status/\"\n\nheaders = {\n \"Authorization\": \"Bearer $API_KEY_REQUIRED_IF_EXECUTING_OUTSIDE_NGC\",\n \"Accept\": \"application/json\",\n}\n\npayload = {\n \"action\": \"cuOpt_OptimizedRouting\",\n \"data\": {\n \"cost_waypoint_graph_data\": None,\n \"travel_time_waypoint_graph_data\": None,\n \"cost_matrix_data\": {\n \"data\": {\n \"1\": [\n [\n 0,\n 1,\n 1\n ],\n [\n 1,\n 0,\n 1\n ],\n [\n 1,\n 1,\n 0\n ]\n ],\n \"2\": [\n [\n 0,\n 1,\n 1\n ],\n [\n 1,\n 0,\n 1\n ],\n [\n 1,\n 2,\n 0\n ]\n ]\n }\n },\n \"travel_time_matrix_data\": {\n \"data\": {\n \"1\": [\n [\n 0,\n 1,\n 1\n ],\n [\n 1,\n 0,\n 1\n ],\n [\n 1,\n 1,\n 0\n ]\n ],\n \"2\": [\n [\n 0,\n 1,\n 1\n ],\n [\n 1,\n 0,\n 1\n ],\n [\n 1,\n 2,\n 0\n ]\n ]\n }\n },\n \"fleet_data\": {\n \"vehicle_locations\": [\n [\n 0,\n 0\n ],\n [\n 0,\n 0\n ]\n ],\n \"vehicle_ids\": [\n \"veh-1\",\n \"veh-2\"\n ],\n \"capacities\": [\n [\n 2,\n 2\n ],\n [\n 4,\n 1\n ]\n ],\n \"vehicle_time_windows\": [\n [\n 0,\n 10\n ],\n [\n 0,\n 10\n ]\n ],\n \"vehicle_break_time_windows\": [\n [\n [\n 1,\n 2\n ],\n [\n 2,\n 3\n ]\n ]\n ],\n \"vehicle_break_durations\": [\n [\n 1,\n 1\n ]\n ],\n \"vehicle_break_locations\": [\n 0,\n 1\n ],\n \"vehicle_types\": [\n 1,\n 2\n ],\n \"vehicle_order_match\": [\n {\n \"order_ids\": [\n 0\n ],\n \"vehicle_id\": 0\n },\n {\n \"order_ids\": [\n 1\n ],\n \"vehicle_id\": 1\n }\n ],\n \"skip_first_trips\": [\n True,\n False\n ],\n \"drop_return_trips\": [\n True,\n False\n ],\n \"min_vehicles\": 2,\n \"vehicle_max_costs\": [\n 7,\n 10\n ],\n \"vehicle_max_times\": [\n 7,\n 10\n ]\n },\n \"task_data\": {\n \"task_locations\": [\n 1,\n 2\n ],\n \"task_ids\": [\n \"Task-A\",\n \"Task-B\"\n ],\n \"demand\": [\n [\n 1,\n 1\n ],\n [\n 3,\n 1\n ]\n ],\n \"task_time_windows\": [\n [\n 0,\n 5\n ],\n [\n 3,\n 9\n ]\n ],\n \"service_times\": [\n 0,\n 0\n ],\n \"order_vehicle_match\": [\n {\n \"order_id\": 0,\n \"vehicle_ids\": [\n 0\n ]\n },\n {\n \"order_id\": 1,\n \"vehicle_ids\": [\n 1\n ]\n }\n ]\n },\n \"solver_config\": {\n \"time_limit\": 1,\n \"objectives\": {\n \"cost\": 1,\n \"travel_time\": 0,\n \"variance_route_size\": 0,\n \"variance_route_service_time\": 0,\n \"prize\": 0\n },\n \"verbose_mode\": False,\n \"error_logging\": True\n }\n },\n \"client_version\": \"\"\n}\n\n# re-use connections\nsession = requests.Session()\n\nresponse = session.post(invoke_url, headers=headers, json=payload)\n\nwhile response.status_code == 202:\n request_id = response.headers.get(\"NVCF-REQID\")\n fetch_url = fetch_url_format + request_id\n response = session.get(fetch_url, headers=headers)\n\nresponse.raise_for_status()\nresponse_body = response.json()\nprint(response_body)\n"])</script><script>self.__next_f.push([1,"c0:T118f,"])</script><script>self.__next_f.push([1,"import fetch from \"node-fetch\";\n\nconst invokeUrl = \"https://optimize.api.nvidia.com/v1/nvidia/cuopt\"\nconst fetchUrlFormat = \"https://optimize.api.nvidia.com/v1/status/\"\n\nconst headers = {\n \"Authorization\": \"Bearer $API_KEY_REQUIRED_IF_EXECUTING_OUTSIDE_NGC\",\n \"Accept\": \"application/json\",\n}\n\nconst payload = {\n \"action\": \"cuOpt_OptimizedRouting\",\n \"data\": {\n \"cost_waypoint_graph_data\": null,\n \"travel_time_waypoint_graph_data\": null,\n \"cost_matrix_data\": {\n \"data\": {\n \"1\": [\n [\n 0,\n 1,\n 1\n ],\n [\n 1,\n 0,\n 1\n ],\n [\n 1,\n 1,\n 0\n ]\n ],\n \"2\": [\n [\n 0,\n 1,\n 1\n ],\n [\n 1,\n 0,\n 1\n ],\n [\n 1,\n 2,\n 0\n ]\n ]\n }\n },\n \"travel_time_matrix_data\": {\n \"data\": {\n \"1\": [\n [\n 0,\n 1,\n 1\n ],\n [\n 1,\n 0,\n 1\n ],\n [\n 1,\n 1,\n 0\n ]\n ],\n \"2\": [\n [\n 0,\n 1,\n 1\n ],\n [\n 1,\n 0,\n 1\n ],\n [\n 1,\n 2,\n 0\n ]\n ]\n }\n },\n \"fleet_data\": {\n \"vehicle_locations\": [\n [\n 0,\n 0\n ],\n [\n 0,\n 0\n ]\n ],\n \"vehicle_ids\": [\n \"veh-1\",\n \"veh-2\"\n ],\n \"capacities\": [\n [\n 2,\n 2\n ],\n [\n 4,\n 1\n ]\n ],\n \"vehicle_time_windows\": [\n [\n 0,\n 10\n ],\n [\n 0,\n 10\n ]\n ],\n \"vehicle_break_time_windows\": [\n [\n [\n 1,\n 2\n ],\n [\n 2,\n 3\n ]\n ]\n ],\n \"vehicle_break_durations\": [\n [\n 1,\n 1\n ]\n ],\n \"vehicle_break_locations\": [\n 0,\n 1\n ],\n \"vehicle_types\": [\n 1,\n 2\n ],\n \"vehicle_order_match\": [\n {\n \"order_ids\": [\n 0\n ],\n \"vehicle_id\": 0\n },\n {\n \"order_ids\": [\n 1\n ],\n \"vehicle_id\": 1\n }\n ],\n \"skip_first_trips\": [\n true,\n false\n ],\n \"drop_return_trips\": [\n true,\n false\n ],\n \"min_vehicles\": 2,\n \"vehicle_max_costs\": [\n 7,\n 10\n ],\n \"vehicle_max_times\": [\n 7,\n 10\n ]\n },\n \"task_data\": {\n \"task_locations\": [\n 1,\n 2\n ],\n \"task_ids\": [\n \"Task-A\",\n \"Task-B\"\n ],\n \"demand\": [\n [\n 1,\n 1\n ],\n [\n 3,\n 1\n ]\n ],\n \"task_time_windows\": [\n [\n 0,\n 5\n ],\n [\n 3,\n 9\n ]\n ],\n \"service_times\": [\n 0,\n 0\n ],\n \"order_vehicle_match\": [\n {\n \"order_id\": 0,\n \"vehicle_ids\": [\n 0\n ]\n },\n {\n \"order_id\": 1,\n \"vehicle_ids\": [\n 1\n ]\n }\n ]\n },\n \"solver_config\": {\n \"time_limit\": 1,\n \"objectives\": {\n \"cost\": 1,\n \"travel_time\": 0,\n \"variance_route_size\": 0,\n \"variance_route_service_time\": 0,\n \"prize\": 0\n },\n \"verbose_mode\": false,\n \"error_logging\": true\n }\n },\n \"client_version\": \"\"\n}\n\nlet response = await fetch(invokeUrl, {\n method: \"post\",\n body: JSON.stringify(payload),\n headers: { \"Content-Type\": \"application/json\", ...headers }\n});\n\nwhile (response.status == 202) {\n let requestId = response.headers.get(\"NVCF-REQID\")\n let fetchUrl = fetchUrlFormat + requestId;\n response = await fetch(fetchUrl, {\n method: \"get\",\n headers: headers\n })\n}\n\nif (response.status != 200) {\n let errBody = await (await response.blob()).text()\n throw \"invocation failed with status \" + response.status + \" \" + errBody\n}\n\nlet response_body = await response.json()\n\nconsole.log(JSON.stringify(response_body))\n"])</script><script>self.__next_f.push([1,"c1:T120f,"])</script><script>self.__next_f.push([1,"invoke_url='https://optimize.api.nvidia.com/v1/nvidia/cuopt'\nfetch_url_format='https://optimize.api.nvidia.com/v1/status/'\n\nauthorization_header='Authorization: Bearer $API_KEY_REQUIRED_IF_EXECUTING_OUTSIDE_NGC'\naccept_header='Accept: application/json'\ncontent_type_header='Content-Type: application/json'\n\ndata='{\n \"action\": \"cuOpt_OptimizedRouting\",\n \"data\": {\n \"cost_waypoint_graph_data\": null,\n \"travel_time_waypoint_graph_data\": null,\n \"cost_matrix_data\": {\n \"data\": {\n \"1\": [\n [\n 0,\n 1,\n 1\n ],\n [\n 1,\n 0,\n 1\n ],\n [\n 1,\n 1,\n 0\n ]\n ],\n \"2\": [\n [\n 0,\n 1,\n 1\n ],\n [\n 1,\n 0,\n 1\n ],\n [\n 1,\n 2,\n 0\n ]\n ]\n }\n },\n \"travel_time_matrix_data\": {\n \"data\": {\n \"1\": [\n [\n 0,\n 1,\n 1\n ],\n [\n 1,\n 0,\n 1\n ],\n [\n 1,\n 1,\n 0\n ]\n ],\n \"2\": [\n [\n 0,\n 1,\n 1\n ],\n [\n 1,\n 0,\n 1\n ],\n [\n 1,\n 2,\n 0\n ]\n ]\n }\n },\n \"fleet_data\": {\n \"vehicle_locations\": [\n [\n 0,\n 0\n ],\n [\n 0,\n 0\n ]\n ],\n \"vehicle_ids\": [\n \"veh-1\",\n \"veh-2\"\n ],\n \"capacities\": [\n [\n 2,\n 2\n ],\n [\n 4,\n 1\n ]\n ],\n \"vehicle_time_windows\": [\n [\n 0,\n 10\n ],\n [\n 0,\n 10\n ]\n ],\n \"vehicle_break_time_windows\": [\n [\n [\n 1,\n 2\n ],\n [\n 2,\n 3\n ]\n ]\n ],\n \"vehicle_break_durations\": [\n [\n 1,\n 1\n ]\n ],\n \"vehicle_break_locations\": [\n 0,\n 1\n ],\n \"vehicle_types\": [\n 1,\n 2\n ],\n \"vehicle_order_match\": [\n {\n \"order_ids\": [\n 0\n ],\n \"vehicle_id\": 0\n },\n {\n \"order_ids\": [\n 1\n ],\n \"vehicle_id\": 1\n }\n ],\n \"skip_first_trips\": [\n true,\n false\n ],\n \"drop_return_trips\": [\n true,\n false\n ],\n \"min_vehicles\": 2,\n \"vehicle_max_costs\": [\n 7,\n 10\n ],\n \"vehicle_max_times\": [\n 7,\n 10\n ]\n },\n \"task_data\": {\n \"task_locations\": [\n 1,\n 2\n ],\n \"task_ids\": [\n \"Task-A\",\n \"Task-B\"\n ],\n \"demand\": [\n [\n 1,\n 1\n ],\n [\n 3,\n 1\n ]\n ],\n \"task_time_windows\": [\n [\n 0,\n 5\n ],\n [\n 3,\n 9\n ]\n ],\n \"service_times\": [\n 0,\n 0\n ],\n \"order_vehicle_match\": [\n {\n \"order_id\": 0,\n \"vehicle_ids\": [\n 0\n ]\n },\n {\n \"order_id\": 1,\n \"vehicle_ids\": [\n 1\n ]\n }\n ]\n },\n \"solver_config\": {\n \"time_limit\": 1,\n \"objectives\": {\n \"cost\": 1,\n \"travel_time\": 0,\n \"variance_route_size\": 0,\n \"variance_route_service_time\": 0,\n \"prize\": 0\n },\n \"verbose_mode\": false,\n \"error_logging\": true\n }\n },\n \"client_version\": \"\"\n}'\n\nresponse=$(curl --silent -i -w \"\n%{http_code}\" --request POST \\n --url \"$invoke_url\" \\n --header \"$authorization_header\" \\n --header \"$accept_header\" \\n --header \"$content_type_header\" \\n --data \"$data\"\n)\n\nhttp_code=$(echo \"$response\" | tail -n 1)\nreq_id=$(echo \"$response\" | grep -i '^nvcf-reqid:' | awk '{print $2}' | tr -d '\r')\n\nwhile [ \"$http_code\" -eq 202 ]; do\n response=$(curl --silent -i -w \"\n%{http_code}\" --request GET \\n --url \"$fetch_url_format$req_id\" \\n --header \"$authorization_header\" \\n --header \"$accept_header\" \\n --header \"$content_type_header\" \\n )\n\n http_code=$(echo \"$response\" | tail -n 1)\n req_id=$(echo \"$response\" | grep -i '^nvcf-reqid:' | awk '{print $2}' | tr -d '\r')\ndone\n\necho \"$response\" | awk '/{/,EOF-1'\n"])</script><script>self.__next_f.push([1,"c2:T7ac,## Start NIM\n\n1. Export `NGC_API_KEY` variable.\n\n```\nexport NGC_API_KEY=\u003cPASTE_API_KEY_HERE\u003e\n```\n\n2. Run the NIM container with the following commands.\n\n```bash\ndocker run -it \\\n --gpus='\"device=0\"' \\\n -p 5000:5000 \\\n -e NGC_API_KEY \\\n nvcr.io/nvidia/cuopt/cuopt:24.07\n```\n\nThis command will start the NIM container and expose port 5000 for the user to interact with the NIM.\n\n3. Open a new terminal, leaving the terminal open with the just launched service. In the new terminal, wait until the health check end point returns `{\"status\":\"RUNNING\",\"version\":\"24.07\"}` before proceeding. This may take a couple of minutes. You can use the following command to query the health check.\n\n```bash\ncurl http://localhost:5000/v2/health/ready\n```\n\n## Python client example\n\n1. Save following Python example to a file named `nim_client.py`.\n\n```python\n#!/usr/bin/env python3\nimport requests\n\ndata = {\"cost_matrix_data\": {\"data\": {\"0\": [[0,1],[1,0]]}},\n \"task_data\": {\"task_locations\": [0,1]},\n \"fleet_data\": {\"vehicle_locations\": [[0,0],[0,0]]}}\n\nresponse = requests.post(\n url=\"http://localhost:5000/cuopt/routes\",\n json=data\n)\nresponse_body = response.json()\nprint(response_body)\n```\n\n2. Execute the example.\n\n```bash\nchmod +x nim_client.py\n\n./nim_client.py\n```\n\n## Shell client example\n\n1. Save the following Shell example to a file named `nim_client.sh`.\n\n```bash\n#!/usr/bin/env bash\nset -e\n\nURL=http://localhost:5000/cuopt/routes\n\ndata='{\"cost_matrix_data\": {\"data\": {\"0\": [[0,1],[1,0]]}},\n \"task_data\": {\"task_locations\": [0,1]},\n \"fleet_data\": {\"vehicle_locations\": [[0,0],[0,0]]}}'\ncurl -H 'Content-Type: application/json' \\\n -d \"$data\" \"$URL\"\n```\n\n2. Execute the example.\n\n```bash\nchmod +x nim_client.sh\n\n./nim_client.sh\n```\n\n3. The NIM displays the results to the terminal in JSON format.\nFor more details on getting started with this NIM, visit the [NVIDIA CUOPT Docs](https://docs.nvidia.com/cuopt/)\n"])</script><script>self.__next_f.push([1,"28:[\"$\",\"$L3c\",null,{\"data\":[{\"endpoint\":{\"requestStatus\":{\"statusCode\":\"SUCCESS\",\"requestId\":\"99a5c78e-a11e-4f99-a399-d868e9cb24ff\"},\"artifact\":{\"orgName\":\"qc69jvmznzxy\",\"labels\":[\"AI Weather Prediction\",\"Climate Science\",\"Earth-2\",\"Weather Simulation\"],\"bias\":\"Field | Response\\n:---------------------------------------------------------------------------------------------------|:---------------\\nParticipation considerations from adversely impacted groups [protected classes](https://www.senate.ca.gov/content/protected-classes) in model design and testing: | None of the Above\\nMeasures taken to mitigate against unwanted bias: | None\",\"logo\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/fourcastnet.jpg\",\"shortDescription\":\"FourCastNet predicts global atmospheric dynamics of various weather / climate variables.\",\"safetyAndSecurity\":\"Field | Response\\n:---------------------------------------------------|:----------------------------------\\nModel Application(s): | Global Weather Forecasting\\nDescribe the life critical impact (if present). | None Known\\nUse Case Restrictions: | Abide by [NVIDIA AI Product Agreement](https://www.nvidia.com/en-us/agreements/enterprise-software/product-specific-terms-for-ai-products/)\\nModel and dataset restrictions: | The Principle of least privilege (PoLP) is applied limiting access for dataset generation and model development. Restrictions enforce dataset access during training, and dataset license constraints adhered to.\",\"privacy\":\"$b7\",\"isReadOnly\":true,\"description\":\"$b8\",\"canGuestDownload\":true,\"isPublic\":true,\"createdDate\":\"2024-11-18T16:03:35.078Z\",\"publisher\":\"nvidia\",\"displayName\":\"fourcastnet\",\"name\":\"fourcastnet\",\"explainability\":\"$b9\",\"updatedDate\":\"2024-11-18T22:44:53.914Z\",\"attributes\":[{\"key\":\"AVAILABLE\",\"value\":\"true\"}],\"artifactType\":\"ENDPOINT\"}},\"spec\":{\"openAPISpec\":{\"openapi\":\"3.0.1\",\"info\":{\"title\":\"Earth-2 FourCastNet Preview API\",\"description\":\"Earth-2 FourCastNet ensemble forcasting preview API. Please see the [Earth-2 home page](https://www.nvidia.com/en-us/high-performance-computing/earth-2/) for more information about Earth-2.\\n\",\"version\":\"1.0.0\",\"termsOfService\":\"https://www.nvidia.com/en-us/agreements/enterprise-software/product-specific-terms-for-ai-products/\",\"contact\":{\"name\":\"NVIDIA Support\",\"url\":\"https://help.nvidia.com/\"},\"license\":{\"name\":\"NVIDIA Community Model License\",\"url\":\"https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-community-models-license/\"}},\"components\":{\"schemas\":{\"InferenceMultipartRequestV1\":{\"type\":\"object\",\"additionalProperties\":false,\"properties\":{\"input_id\":{\"type\":\"integer\",\"format\":\"int32\",\"minimum\":0,\"maximum\":3,\"title\":\"Input ID\",\"description\":\"Index indicating which sample input data built into the NVCF API to use\"},\"variables\":{\"type\":\"string\",\"format\":\"regex\",\"pattern\":\"^(\\\\w+(,\\\\w+)*)?$\",\"maxLength\":1024,\"example\":\"w10m,z500\",\"title\":\"Output variables\",\"description\":\"Comma-separated list of variable IDs to plot and return from the model. Present supported options are [w10m,t2m,msl,tcwv,z500]\\n\"},\"simulation_length\":{\"type\":\"integer\",\"format\":\"int32\",\"minimum\":1,\"maximum\":40,\"default\":4,\"title\":\"Forecast length\",\"description\":\"Number of simulation steps to forecast from the initial state. The duration for each step is 6 hours. Defaults to 4 steps.\\n\"},\"ensemble_size\":{\"type\":\"integer\",\"format\":\"int32\",\"minimum\":1,\"maximum\":4,\"default\":1,\"title\":\"Ensemble size\",\"description\":\"Number of ensemble members to predict. Defaults to 1 steps.\\n\"},\"noise_amplitude\":{\"type\":\"number\",\"format\":\"float32\",\"minimum\":0,\"maximum\":0.1,\"default\":0,\"title\":\"Noise amplitude\",\"description\":\"The perturbation strength or amplitude applied to the initial state of each ensemble member. Defaults to 0.\\n\"}},\"required\":[\"input_id\",\"variables\"]},\"InferenceTarResponseV1\":{\"type\":\"string\",\"format\":\"binary\",\"example\":\"Tar archive\\n├─w10m_000_000.png\\n├─w10m_000_001.png\\n├─w10m_006_000.png\\n├─w10m_006_001.png\\n...\\n└─\u003cvariable id\u003e_\u003clead time\u003e_\u003cmember index\u003e.png\\n\",\"description\":\"Tar file containing contour images for each variable, simulation step and batch index. Images are streamed in order after each model simulation step. Each array will have a file name in the format `\u003cvariable id\u003e_\u003clead time\u003e_\u003cmember index\u003e.png`.\\n\"},\"ErrorResponseV1\":{\"type\":\"object\",\"properties\":{\"message\":{\"type\":\"string\",\"maxLength\":4096,\"description\":\"Error message\"}}}}},\"paths\":{\"/v1/infer\":{\"post\":{\"summary\":\"Runs FourCastNet inference.\",\"tags\":[\"Inference\"],\"requestBody\":{\"required\":true,\"content\":{\"multipart/form-data\":{\"schema\":{\"$ref\":\"#/components/schemas/InferenceMultipartRequestV1\"}}}},\"responses\":{\"200\":{\"description\":\"OK\",\"content\":{\"application/x-tar\":{\"schema\":{\"$ref\":\"#/components/schemas/InferenceTarResponseV1\"}}}},\"400\":{\"description\":\"Bad inference request\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ErrorResponseV1\"},\"example\":{\"message\":\"Bad request body\"}}}},\"500\":{\"description\":\"Internal server error\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ErrorResponseV1\"},\"example\":{\"message\":\"Internal Triton server error\"}}}}}}}}},\"namespace\":\"qc69jvmznzxy\",\"updatedDate\":\"2024-11-18T22:44:54.493Z\",\"nvcfFunctionId\":\"5bdd622c-14f1-4783-854c-d9d310e4fab0\",\"createdDate\":\"2024-11-18T16:03:35.412Z\",\"attributes\":{\"iframeUrl\":\"https://earth2.playground.ngc.nvidia.com?__theme=dark\",\"showUnavailableBanner\":false,\"apiDocsUrl\":\"https://docs.api.nvidia.com/nim/reference/nvidia-fourcastnet\",\"termsOfUse\":\"\u003cb\u003eGOVERNING TERMS\u003c/b\u003e: Your use of this API is governed by the \u003ca href=\\\"https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA API Trial Service Terms of Use\u003c/a\u003e; and the use of this model is governed by the \u003ca href=\\\"https://docs.nvidia.com/ai-foundation-models-community-license.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA AI Foundation Models Community License\u003c/a\u003e.\\n\",\"dockerRun\":\"$ba\",\"dockerTermsOfUse\":\"By running the below commands, you accept the \u003ca href=\\\"https://www.nvidia.com/en-us/data-center/products/nvidia-ai-enterprise/eula/\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA AI Enterprise Terms of Use\u003c/a\u003e and the \u003ca href=\\\"https://docs.nvidia.com/ai-foundation-models-community-license.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA Community Models License\u003c/a\u003e.\\n\",\"cta\":{\"text\":\"Build with this NIM\",\"url\":\"https://www.nvidia.com/en-us/ai/nim-notifyme/\",\"nim_available_override_url\":\"https://catalog.ngc.nvidia.com/orgs/nim/teams/nvidia/containers/fourcastnet\"}},\"artifactName\":\"fourcastnet\"},\"config\":{\"name\":\"fourcastnet\",\"type\":\"model\"}},{\"endpoint\":{\"requestStatus\":{\"statusCode\":\"SUCCESS\",\"requestId\":\"63265285-26b9-4a89-a3aa-189eeed7ff1f\"},\"artifact\":{\"orgName\":\"qc69jvmznzxy\",\"labels\":[\"Route Optimization\"],\"bias\":\"Field | Response\\n:---------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------\\nParticipation considerations from adversely impacted groups [protected classes](https://www.senate.ca.gov/content/protected-classes) in model design and testing: | None\\nMeasures taken to mitigate against unwanted bias: | None\",\"logo\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/nvidia-cuopt.jpg\",\"shortDescription\":\"World-record accuracy and performance for complex route optimization.\",\"safetyAndSecurity\":\"Field | Response\\n:---------------------------------------------------|:----------------------------------\\nModel Application(s): | Solving Vehicle Routing Problems and Optimizing Logistics Operations\\nDescribe the life-critical impact (if present). | None\\nUse Case Restrictions: | Solver for Non-Commerical Use Only\\nModel and dataset restrictions: | The Principle of Least Privilege (PoLP) is applied limiting access for the solver's development. Restrictions enforce solver access and solver license constraints adhered to.\",\"privacy\":\"$bb\",\"isReadOnly\":true,\"description\":\"$bc\",\"canGuestDownload\":true,\"isPublic\":true,\"createdDate\":\"2024-03-15T04:08:53.109Z\",\"publisher\":\"nvidia\",\"displayName\":\"cuopt\",\"name\":\"nvidia-cuopt\",\"explainability\":\"$bd\",\"updatedDate\":\"2024-11-18T22:01:42.675Z\",\"attributes\":[{\"key\":\"AVAILABLE\",\"value\":\"true\"},{\"key\":\"PREVIEW\",\"value\":\"false\"}],\"artifactType\":\"ENDPOINT\"}},\"spec\":{\"openAPISpec\":{\"openapi\":\"3.1.0\",\"info\":{\"title\":\"Route Optimization\",\"description\":\"The NVIDIA cuOpt REST API for cuOpt-24.07\",\"version\":\"24.07\",\"termsOfService\":\"https://nvidia.com/legal/terms-of-use\",\"contact\":{\"name\":\"NVIDIA Support\",\"url\":\"https://help.nvidia.com/\"},\"license\":{\"name\":\"NVIDIA cuOpt License and Usage Agreement\",\"url\":\"https://www.nvidia.com/en-us/data-center/products/nvidia-ai-enterprise/eula/\"}},\"servers\":[{\"url\":\"optimize.api.nvidia.com/v1\"}],\"tags\":[{\"name\":\"nvidia / cuOpt\",\"description\":\"an accelerated optimization API for complex, real-time fleet routing workflows\"}],\"paths\":{\"/nvidia/cuopt\":{\"post\":{\"tags\":[\"nvidia / cuOpt\"],\"summary\":\"Submit to solver\",\"description\":\"Note: This is for managed service. Takes all the data and options at once, solves the routing problem and returns result. This POST should be used in conjunction with the NVCF API which allows for the upload of large assets. \\nYou can find details on how to use NVCF Asset APIs here: https://docs.api.nvidia.com/cloud-functions/reference/createasset\",\"operationId\":\"nvidia-cuopt-infer\",\"parameters\":[{\"in\":\"header\",\"name\":\"NVCF-INPUT-ASSET-REFERENCES\",\"schema\":{\"type\":\"string\"},\"required\":false,\"description\":\"String of asset IDs separated by commas. Data is uploaded to AWS S3 using NVCF Asset APIs and associated with these asset IDs.If the size of the json is more than 200KB, it needs to be uploaded to a presigned S3 URL bucket. The presigned URL allows for secure and temporary access to the S3 bucket for uploading the image. Once the asset is requested, an asset ID is generated for it. Please include this asset ID in this header and to use the uploaded json the 'data' field in the request body should be null; otherwise, it will be ignored.\"}],\"requestBody\":{\"required\":true,\"content\":{\"application/json\":{\"schema\":{\"properties\":{\"action\":{\"anyOf\":[{\"type\":\"string\",\"enum\":[\"cuOpt_OptimizedRouting\",\"cuOpt_RoutingValidator\",0]},{\"type\":\"null\"}],\"title\":\"Action\",\"description\":\"Action to be performed by the service, validator action just validates input against format and base rules.\",\"default\":\"cuOpt_OptimizedRouting\"},\"data\":{\"anyOf\":[{\"properties\":{\"cost_waypoint_graph_data\":{\"anyOf\":[{\"properties\":{\"waypoint_graph\":{\"anyOf\":[{\"additionalProperties\":{\"properties\":{\"edges\":{\"items\":{\"type\":\"integer\"},\"type\":\"array\",\"title\":\"Edges\",\"description\":\"dtype: int32, edge \u003e= 0. \\n\\n Vertices of all the directed edges.\"},\"offsets\":{\"items\":{\"type\":\"integer\"},\"type\":\"array\",\"title\":\"Offsets\",\"description\":\"dtype: int32, offset \u003e= 0. \\n\\n Offsets which provide number of edges from the source vertex signified by the index.\"},\"weights\":{\"anyOf\":[{\"items\":{\"type\":\"number\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Weights\",\"description\":\"dtype: float32, weight \u003e= 0. \\n\\n Weights of each edges.\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"edges\",\"offsets\"],\"title\":\"WaypointGraph\"},\"type\":\"object\"},{\"type\":\"null\"}],\"title\":\"Waypoint Graph\"}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"UpdateWaypointGraphData\"},{\"type\":\"null\"}],\"description\":\"Waypoint graph with weights as cost to travel from A to B \\nand B to A. If there are different types of vehicles \\nthey can be provided with key value pair \\nwhere key is vehicle-type and value is the graph. Value of \\nvehicle type should be within [0, 255]\",\"default\":{},\"examples\":[null]},\"travel_time_waypoint_graph_data\":{\"anyOf\":[{\"properties\":{\"waypoint_graph\":{\"anyOf\":[{\"additionalProperties\":{\"properties\":{\"edges\":{\"items\":{\"type\":\"integer\"},\"type\":\"array\",\"title\":\"Edges\",\"description\":\"dtype: int32, edge \u003e= 0. \\n\\n Vertices of all the directed edges.\"},\"offsets\":{\"items\":{\"type\":\"integer\"},\"type\":\"array\",\"title\":\"Offsets\",\"description\":\"dtype: int32, offset \u003e= 0. \\n\\n Offsets which provide number of edges from the source vertex signified by the index.\"},\"weights\":{\"anyOf\":[{\"items\":{\"type\":\"number\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Weights\",\"description\":\"dtype: float32, weight \u003e= 0. \\n\\n Weights of each edges.\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"edges\",\"offsets\"],\"title\":\"WaypointGraph\"},\"type\":\"object\"},{\"type\":\"null\"}],\"title\":\"Waypoint Graph\"}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"UpdateWaypointGraphData\"},{\"type\":\"null\"}],\"description\":\"Waypoint graph with weights as time to travel from A to B \\nand B to A. If there are different types of vehicles \\nthey can be provided with key value pair \\nwhere key is vehicle-type and value is the graph. Value of \\nvehicle type should be within [0, 255]\",\"default\":{},\"examples\":[null]},\"cost_matrix_data\":{\"anyOf\":[{\"properties\":{\"data\":{\"anyOf\":[{\"additionalProperties\":{\"items\":{\"items\":{\"type\":\"number\"},\"type\":\"array\"},\"type\":\"array\"},\"type\":\"object\"},{\"type\":\"null\"}],\"title\":\"Data\",\"description\":\"dtype : vehicle-type (uint8), cost (float32), cost \u003e= 0.\\n \\n\\n Sqaure matrix with cost to travel from A to B and B to A. \\nIf there different types of vehicles which have different \\ncost matrices, they can be provided with key value pair \\nwhere key is vehicle-type and value is cost matrix. Value of \\nvehicle type should be within [0, 255]\"},\"cost_matrix\":{\"anyOf\":[{\"additionalProperties\":{\"items\":{\"items\":{\"type\":\"number\"},\"type\":\"array\"},\"type\":\"array\"},\"type\":\"object\"},{\"type\":\"null\"}],\"title\":\"Cost Matrix\",\"description\":\"This field is deprecated, please use the 'data' field instead\",\"deprecated\":true}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"UpdateCostMatrices\"},{\"type\":\"null\"}],\"description\":\"Sqaure matrix with cost to travel from A to B and B to A. \\nIf there are different types of vehicles which have different \\ncost matrices, they can be provided with key value pair \\nwhere key is vehicle-type and value is cost matrix. Value of \\nvehicle type should be within [0, 255]\",\"default\":{},\"examples\":[{\"cost_matrix\":{\"1\":[[0,1,1],[1,0,1],[1,1,0]],\"2\":[[0,1,1],[1,0,1],[1,2,0]]}}]},\"travel_time_matrix_data\":{\"anyOf\":[{\"properties\":{\"data\":{\"anyOf\":[{\"additionalProperties\":{\"items\":{\"items\":{\"type\":\"number\"},\"type\":\"array\"},\"type\":\"array\"},\"type\":\"object\"},{\"type\":\"null\"}],\"title\":\"Data\",\"description\":\"dtype : vehicle-type (uint8), cost (float32), cost \u003e= 0.\\n \\n\\n Sqaure matrix with cost to travel from A to B and B to A. \\nIf there different types of vehicles which have different \\ncost matrices, they can be provided with key value pair \\nwhere key is vehicle-type and value is cost matrix. Value of \\nvehicle type should be within [0, 255]\"},\"cost_matrix\":{\"anyOf\":[{\"additionalProperties\":{\"items\":{\"items\":{\"type\":\"number\"},\"type\":\"array\"},\"type\":\"array\"},\"type\":\"object\"},{\"type\":\"null\"}],\"title\":\"Cost Matrix\",\"description\":\"This field is deprecated, please use the 'data' field instead\",\"deprecated\":true}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"UpdateCostMatrices\"},{\"type\":\"null\"}],\"description\":\"Sqaure matrix with time to travel from A to B and B to A. \\nIf there are different types of vehicles which have different \\ntravel time matrices, they can be provided with key value pair \\nwhere key is vehicle-type and value is time matrix. Value of \\nvehicle type should be within [0, 255]\",\"default\":{},\"examples\":[{\"cost_matrix\":{\"1\":[[0,1,1],[1,0,1],[1,1,0]],\"2\":[[0,1,1],[1,0,1],[1,2,0]]}}]},\"fleet_data\":{\"allOf\":[{\"properties\":{\"vehicle_locations\":{\"items\":{\"items\":{\"type\":\"integer\"},\"type\":\"array\"},\"type\":\"array\",\"title\":\"Vehicle Locations\",\"description\":\"dtype: int32, vehicle_location \u003e= 0. \\n\\n Start and end location of the vehicles in the given set of locations in WayPointGraph or CostMatrices.\\nExample: For 2 vehicles, \\n\\n [ \\n\\n [veh_1_start_loc, veh_1_end_loc], \\n\\n [veh_2_start_loc, veh_2_end_loc] \\n\\n ]\",\"examples\":[[[0,0],[0,0]]]},\"vehicle_ids\":{\"anyOf\":[{\"items\":{\"type\":\"string\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Vehicle Ids\",\"description\":\"List of the vehicle ids or names provided as a string.\",\"examples\":[[\"veh-1\",\"veh-2\"]]},\"capacities\":{\"anyOf\":[{\"items\":{\"items\":{\"type\":\"integer\"},\"type\":\"array\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Capacities\",\"description\":\"dtype: int32, capacity \u003e= 0. \\n\\n Note: For this release number of capacity dimensions are limited to 3. \\n\\n Lists of capacities of each vehicle.\\nMultiple capacities can be added and each list will represent one kind of capacity. Order of kind of the capacities should match order of the demands.\\nTotal capacity for each type should be sufficient to complete all demand of that type.Example: In case of two sets of capacities per vehicle with 3 vehicles, \\n\\n [ \\n\\n [cap_1_veh_1, cap_1_veh_2, cap_1_veh_3], \\n\\n [cap_2_veh_1, cap_2_veh_2, cap_2_veh_3] \\n\\n ]\",\"examples\":[[[2,2],[4,1]]]},\"vehicle_time_windows\":{\"anyOf\":[{\"items\":{\"items\":{\"type\":\"integer\"},\"type\":\"array\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Vehicle Time Windows\",\"description\":\"dtype: int32, time \u003e= 0. \\n\\n Earliest and Latest time window pairs for each vehicle,\\nfor example the data would look as follows for 2 vehicles, \\n \\n\\n [ \\n\\n [veh_1_earliest, veh_1_latest], \\n\\n [veh_2_earliest, veh_2_latest] \\n\\n ]\",\"examples\":[[[0,10],[0,10]]]},\"vehicle_break_time_windows\":{\"anyOf\":[{\"items\":{\"items\":{\"items\":{\"type\":\"integer\"},\"type\":\"array\"},\"type\":\"array\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Vehicle Break Time Windows\",\"description\":\"dtype: int32, time \u003e= 0. \\n\\n Multiple break time windows can be added for each vehicle.Earliest and Latest break time window pairs for each vehicle,\\nFor example, in case of 2 sets of breaks for each vehicle which translates to 2 dimensions of breaks,\\n \\n\\n [ \\n\\n [[brk_1_veh_1_earliest, brk_1_veh_1_latest], [brk_1_veh_2_earliest, brk_1_veh_2_latest]] \\n\\n [[brk_2_veh_1_earliest, brk_2_veh_1_latest], [brk_2_veh_2_earliest, brk_2_veh_2_latest]] \\n\\n ] \\n\\n The break duration within this time window is provided through vehicle_break_durations.\",\"examples\":[[[[1,2],[2,3]]]]},\"vehicle_break_durations\":{\"anyOf\":[{\"items\":{\"items\":{\"type\":\"integer\"},\"type\":\"array\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Vehicle Break Durations\",\"description\":\"dtype: int32, time \u003e= 0. \\n\\n Break duration for each vehicle. vehicle_break_time_windows should be provided to use this option.For example, in case of having 2 breaks for each vehicle, \\n\\n [ \\n\\n [brk_1_veh_1_duration, brk_1_veh_2_duration], \\n\\n [brk_2_veh_1_duration, brk_2_veh_2_duration], \\n\\n ]\",\"examples\":[[[1,1]]]},\"vehicle_break_locations\":{\"anyOf\":[{\"items\":{\"type\":\"integer\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Vehicle Break Locations\",\"description\":\"dtype: int32, location \u003e= 0. \\n\\n Break location where vehicles can take breaks. If not set, any location can be used for the break.\",\"examples\":[[0,1]]},\"vehicle_types\":{\"anyOf\":[{\"items\":{\"type\":\"integer\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Vehicle Types\",\"description\":\"dtype: uint8. \\n\\n Types of vehicles in the fleet given as positive integers.\",\"examples\":[[1,2]]},\"vehicle_order_match\":{\"anyOf\":[{\"items\":{\"properties\":{\"vehicle_id\":{\"type\":\"integer\",\"title\":\"Vehicle Id\",\"description\":\"dtype: int32, vehicle_id \u003e= 0. \\n\\n Vehicle id as an integer, and can serve all the order listed in order_ids.\"},\"order_ids\":{\"items\":{\"type\":\"integer\"},\"type\":\"array\",\"title\":\"Order Ids\",\"description\":\"dtype: int32, order_id \u003e= 0. \\n\\n Indices of orders which can be served by this particular vehicle\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"vehicle_id\",\"order_ids\"],\"title\":\"VehicleOrderMatch\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Vehicle Order Match\",\"description\":\"A list of vehicle order match, where the match would contain a vehicle id and a list of orders that vehicle can serve.\",\"examples\":[[{\"order_ids\":[0],\"vehicle_id\":0},{\"order_ids\":[1],\"vehicle_id\":1}]]},\"skip_first_trips\":{\"anyOf\":[{\"items\":{\"type\":\"boolean\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Skip First Trips\",\"description\":\"Drop the cost of trip to first location for that vehicle.\",\"examples\":[[true,false]]},\"drop_return_trips\":{\"anyOf\":[{\"items\":{\"type\":\"boolean\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Drop Return Trips\",\"description\":\"Drop cost of return trip for each vehicle.\",\"examples\":[[true,false]]},\"min_vehicles\":{\"anyOf\":[{\"type\":\"integer\"},{\"type\":\"null\"}],\"title\":\"Min Vehicles\",\"description\":\"dtype: int32, min_vehicles \u003e= 1. \\n\\n Solution should consider minimum number of vehicles\",\"examples\":[2]},\"vehicle_max_costs\":{\"anyOf\":[{\"items\":{\"type\":\"number\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Vehicle Max Costs\",\"description\":\"dtype: float32, max_costs \u003e= 0. \\n\\n Maximum cost a vehicle can incur and it is based on cost matrix/cost waypoint graph.\",\"examples\":[[7,10]]},\"vehicle_max_times\":{\"anyOf\":[{\"items\":{\"type\":\"number\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Vehicle Max Times\",\"description\":\"dtype: float32, max_time \u003e= 0. \\n\\n Maximum time a vehicle can operate (includes drive, service and wait time), this is based on travel time matrix/travel time waypoint graph.\",\"examples\":[[7,10]]},\"vehicle_fixed_costs\":{\"anyOf\":[{\"items\":{\"type\":\"number\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Vehicle Fixed Costs\",\"description\":\"dtype: float32, fixed_cost \u003e= 0. \\n\\n Cost of each vehicle.This helps in routing where may be 2 vehicles with less cost is effective compared to 1 vehicle with huge cost. As example shows veh-0 (15) \u003e veh-1 (5) + veh-2 (5)\",\"examples\":[[15,5]]}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"vehicle_locations\"],\"title\":\"FleetData\"}],\"description\":\"All Fleet information\"},\"task_data\":{\"allOf\":[{\"properties\":{\"task_locations\":{\"items\":{\"type\":\"integer\"},\"type\":\"array\",\"title\":\"Task Locations\",\"description\":\"dtype: int32, location \u003e= 0. \\n\\n Location where the task has been requested.\",\"examples\":[[1,2]]},\"task_ids\":{\"anyOf\":[{\"items\":{\"type\":\"string\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Task Ids\",\"description\":\"List of the task ids or names provided as a string.\",\"examples\":[[\"Task-A\",\"Task-B\"]]},\"demand\":{\"anyOf\":[{\"items\":{\"items\":{\"type\":\"integer\"},\"type\":\"array\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Demand\",\"description\":\"dtype: int32 \\n\\n Note: For this release number of demand dimensions are limited to 3. \\n\\n Lists of demands of each tasks.\\nMultiple demands can be added and each list represents one kind of demand. Order of these demands should match the type of vehicle capacities provided.Example: In case of two sets of demands per vehicle with 3 vehicles, \\n\\n [ \\n\\n [dem_1_tsk_1, dem_1_tsk_2, dem_1_tsk_3], \\n\\n [dem_2_tsk_1, dem_2_tsk_2, dem_2_tsk_3] \\n\\n ]\",\"examples\":[[[1,1],[3,1]]]},\"pickup_and_delivery_pairs\":{\"anyOf\":[{\"items\":{\"items\":{\"type\":\"integer\"},\"type\":\"array\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Pickup And Delivery Pairs\",\"description\":\"dtype: int32, pairs \u003e= 0. \\n\\n List of Pick-up and delivery index pairs from task locations.\\nIn case we have the following pick-up and delivery locations, 2-\u003e1, 4-\u003e5, 3-\u003e4, then task locations would look something like, task_locations = [0, 2, 1, 4, 5, 3, 4] and pick-up and delivery pairs would be index of those locations in task location and would look like [[1, 2], [3, 4], [5, 6]], 1 is pickup index for location 2 and it should be delivered to location 1 which is at index 2.Example schema: \\n\\n [ \\n\\n [pcikup_1_idx_to_task, drop_1_idx_to_task], \\n\\n [pcikup_2_idx_to_task, drop_2_idx_to_task], \\n\\n ]\",\"examples\":[null]},\"task_time_windows\":{\"anyOf\":[{\"items\":{\"items\":{\"type\":\"integer\"},\"type\":\"array\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Task Time Windows\",\"description\":\"dtype: int32, time \u003e= 0. \\n\\n Earliest and Latest time windows for each tasks.\\nFor example the data would look as follows, \\n \\n\\n [ \\n\\n [tsk_1_earliest, tsk_1_latest], \\n\\n [tsk_2_earliest, tsk_2_latest] \\n\\n ]\",\"examples\":[[[0,5],[3,9]]]},\"service_times\":{\"anyOf\":[{\"items\":{\"type\":\"integer\"},\"type\":\"array\"},{\"additionalProperties\":{\"items\":{\"type\":\"integer\"},\"type\":\"array\"},\"type\":\"object\"},{\"type\":\"null\"}],\"title\":\"Service Times\",\"description\":\"dtype: int32, time \u003e= 0. \\n\\n Service time for each task. Accepts a list of service times for all vehicles. In case of vehicle specific service times, accepts a dict with key as vehicle id and value as list of service times.Example schema: In case all vehicles have same service times, \\n\\n [tsk_1_srv_time, tsk_2_srv_time, tsk_3_srv_time] \\n\\n \\n\\n In case, there are 2 types of vehicle types and each of them have different service times, \\n\\n { \\n\\n type-1: [tsk_1_srv_time, tsk_3_srv_time, tsk_3_srv_time], \\n\\n type-2: [tsk_1_srv_time, tsk_3_srv_time, tsk_3_srv_time] \\n\\n }\",\"examples\":[[0,0]]},\"prizes\":{\"anyOf\":[{\"items\":{\"type\":\"number\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Prizes\",\"description\":\"dtype: float32, prizes \u003e= 0. \\n\\n List of values which signifies prizes that are collected for fulfilling each task. This can be used effectively in case solution is infeasible and need to drop few tasks to get feasible solution. Solver will prioritize for higher prize tasks \",\"examples\":[null]},\"order_vehicle_match\":{\"anyOf\":[{\"items\":{\"properties\":{\"order_id\":{\"type\":\"integer\",\"title\":\"Order Id\",\"description\":\"dtype: int32, order_id \u003e= 0. \\n\\n Indices of orders which can be served by this particular vehicleOrder id as an integer\"},\"vehicle_ids\":{\"items\":{\"type\":\"integer\"},\"type\":\"array\",\"title\":\"Vehicle Ids\",\"description\":\"dtype: int32, vehicle_id \u003e= 0. \\n\\n Indices of the vehicles which can serve this particular order. \\n\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"order_id\",\"vehicle_ids\"],\"title\":\"OrderVehicleMatch\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Order Vehicle Match\",\"description\":\"A list of order vehicle match, where the match would contain a order id and a list of vehicle ids that can serve this order.\",\"examples\":[[{\"order_id\":0,\"vehicle_ids\":[0]},{\"order_id\":1,\"vehicle_ids\":[1]}]]},\"mandatory_task_ids\":{\"anyOf\":[{\"items\":{\"type\":\"integer\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Mandatory Task Ids\",\"description\":\"dtype: int32, mandatory_task_id \u003e= 0. \\n\\n Note: This is only effective when used along with drop infeasible option. \\n\\n A list of task ids which are mandatory and solver would fail if these cannot be fulfilled.\",\"examples\":[null]}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"task_locations\"],\"title\":\"TaskData\"}],\"description\":\"All Task information\"},\"solver_config\":{\"anyOf\":[{\"properties\":{\"time_limit\":{\"anyOf\":[{\"type\":\"number\"},{\"type\":\"null\"}],\"title\":\"Time Limit\",\"description\":\"SolverSettings time limit\",\"examples\":[1]},\"objectives\":{\"anyOf\":[{\"properties\":{\"cost\":{\"anyOf\":[{\"type\":\"number\"},{\"type\":\"null\"}],\"title\":\"Cost\",\"description\":\"dtype: float32. \\n\\n The weight assigned to minimizing the cost for a given solution, default value is 1\",\"examples\":[1]},\"travel_time\":{\"anyOf\":[{\"type\":\"number\"},{\"type\":\"null\"}],\"title\":\"Travel Time\",\"description\":\"dtype: float32. \\n\\n The weight assigned to minimizing total travel time for a given solution (includes drive, service and wait time)\",\"examples\":[0]},\"variance_route_size\":{\"anyOf\":[{\"type\":\"number\"},{\"type\":\"null\"}],\"title\":\"Variance Route Size\",\"description\":\"dtype: float32. \\n\\n The weight assigned to the variance in the number of orders served by each route.\",\"examples\":[0]},\"variance_route_service_time\":{\"anyOf\":[{\"type\":\"number\"},{\"type\":\"null\"}],\"title\":\"Variance Route Service Time\",\"description\":\"dtype: float32. \\n\\n The weight assigned to the variance in the accumulated service times of each route\",\"examples\":[0]},\"prize\":{\"anyOf\":[{\"type\":\"number\"},{\"type\":\"null\"}],\"title\":\"Prize\",\"description\":\"dtype: float32. \\n\\n The weight assigned to the prize in accumulated prizes for each job fulfilled.This will be negated from overall values accumulated with other objectives.For example, if cost accumulated is 10 and objective value for it is 1, and if the prize accumulated is 3 and objective is 2, then total cost would look something like this 10 x 1 - 3 x 2 = 4.\",\"examples\":[0]},\"vehicle_fixed_cost\":{\"anyOf\":[{\"type\":\"number\"},{\"type\":\"null\"}],\"title\":\"Vehicle Fixed Cost\",\"description\":\"dtype: float32. \\n\\n The weight assigned to the accumulated fixed costs of each vehicle used in solution\",\"examples\":[0]}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"Objective\"},{\"type\":\"null\"}],\"description\":\"Values provided dictate the linear combination of factors used to evaluate solution quality.Only prize will be negated, all others gets accumulated. That's why sometime you might come across negative value as solution cost.\"},\"config_file\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Config File\",\"description\":\"Dump configuration information in a given file as yaml\",\"examples\":[null]},\"verbose_mode\":{\"anyOf\":[{\"type\":\"boolean\"},{\"type\":\"null\"}],\"title\":\"Verbose Mode\",\"description\":\"Displaying internal information during the solver execution.\",\"default\":false},\"error_logging\":{\"anyOf\":[{\"type\":\"boolean\"},{\"type\":\"null\"}],\"title\":\"Error Logging\",\"description\":\"Displaying constraint error information during the solver execution.\",\"default\":true}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"UpdateSolverSettingsConfig\"},{\"type\":\"null\"}]}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"fleet_data\",\"task_data\"],\"title\":\"OptimizedRoutingData\"},{\"type\":\"null\"}],\"title\":\"Data\",\"description\":\"The data that needs to be processed by the service. For detailed explanations of each field, please consult the following link: \u003ca href=\\\"https://docs.nvidia.com/cuopt/service/latest/data-requirements.html\\\"\u003edata requirements\u003c/a\u003e . To ensure best practices, please refer to: \u003ca href=\\\"https://docs.nvidia.com/cuopt/service/latest/best-practices.html\\\"\u003ebest practices\u003c/a\u003e. For examples, you can find them at: \u003ca href=\\\"https://github.com/NVIDIA/cuOpt-Resources/tree/branch-23.10/notebooks/routing/service\\\"\u003enotebooks\u003c/a\u003e. If the size of the data exceeds 250KB, please utilize the large assets API to upload it to s3. In such cases, set the data as null and include the header NVCF-INPUT-ASSET-REFERENCES: $ASSET_ID in the POST request.\"},\"parameters\":{\"anyOf\":[{\"type\":\"object\"},{\"type\":\"null\"}],\"title\":\"Parameters\",\"description\":\"unused/ignored but retained for compatibility\"},\"client_version\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Client Version\",\"description\":\"cuOpt client version. Set to 'custom' to skip version check.\",\"default\":\"\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"data\"],\"title\":\"cuoptData\"}}}},\"responses\":{\"200\":{\"description\":\"Successful Response\",\"content\":{\"application/json\":{\"schema\":{\"anyOf\":[{\"properties\":{},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"EmptyDict\"},{\"properties\":{\"response\":{\"anyOf\":[{\"properties\":{\"solver_response\":{\"allOf\":[{\"properties\":{\"status\":{\"type\":\"integer\",\"title\":\"Status\",\"description\":\"0 - Solution is available \\n1 - Infeasible solution is available \\n\",\"default\":0,\"examples\":[0]},\"num_vehicles\":{\"type\":\"integer\",\"title\":\"Num Vehicles\",\"description\":\"Number of vehicle being used for the solution\",\"default\":-1,\"examples\":[2]},\"solution_cost\":{\"type\":\"number\",\"title\":\"Solution Cost\",\"description\":\"Total cost of the solution\",\"default\":-1,\"examples\":[2]},\"vehicle_data\":{\"additionalProperties\":{\"properties\":{\"task_id\":{\"items\":{\"type\":\"string\"},\"type\":\"array\",\"title\":\"Task Id\",\"description\":\"task_ids being assigned to vehicle along with depot and breaks\",\"default\":[]},\"arrival_stamp\":{\"items\":{\"type\":\"number\"},\"type\":\"array\",\"title\":\"Arrival Stamp\",\"description\":\"arrival stamps at each task locations\",\"default\":[]},\"route\":{\"items\":{\"type\":\"integer\"},\"type\":\"array\",\"title\":\"Route\",\"description\":\"Route indices as per waypoint graph or cost matrix provided\",\"default\":[]},\"type\":{\"items\":{\"type\":\"string\",\"enum\":[\"Depot\",\"Pickup\",\"Delivery\",\"Break\",\"w\"],\"title\":\"LocationTypeEnum\"},\"type\":\"array\",\"title\":\"Type\",\"description\":\"Type of routing point, whether it is Depot, Waypoint - w \\nDelivery, Break, Pickup \\n\",\"default\":[]}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"VehicleData\"},\"type\":\"object\",\"title\":\"Vehicle Data\",\"description\":\"All the details of vehicle routes and timestamps\",\"default\":{},\"examples\":[{\"vehicle_data\":{\"veh-1\":{\"arrival_stamp\":[1,2],\"route\":[1,1],\"task_id\":[\"Break\",\"Task-A\"],\"type\":[\"Break\",\"Delivery\"]},\"veh-2\":{\"arrival_stamp\":[2,2,4,5],\"route\":[0,0,2,0],\"task_id\":[\"Depot\",\"Break\",\"Task-B\",\"Depot\"],\"type\":[\"Depot\",\"Break\",\"Delivery\",\"Depot\"]}}}]},\"msg\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Msg\",\"description\":\"Any information pertaining to the run.\",\"default\":\"\"}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"FeasibleResultData\"}],\"description\":\"Feasible solution\",\"default\":{\"status\":0,\"num_vehicles\":-1,\"solution_cost\":-1,\"vehicle_data\":{},\"msg\":\"\"}},\"perf_times\":{\"anyOf\":[{\"type\":\"object\"},{\"type\":\"null\"}],\"title\":\"Perf Times\",\"description\":\"Etl and Solve times of the solve call\"}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"FeasibleSolve\"},{\"properties\":{\"solver_infeasible_response\":{\"allOf\":[{\"properties\":{\"status\":{\"type\":\"integer\",\"title\":\"Status\",\"description\":\"1 - Infeasible solution is available \\n\",\"default\":1,\"examples\":[1]},\"num_vehicles\":{\"type\":\"integer\",\"title\":\"Num Vehicles\",\"description\":\"Number of vehicle being used for the solution\",\"default\":-1,\"examples\":[2]},\"solution_cost\":{\"type\":\"number\",\"title\":\"Solution Cost\",\"description\":\"Total cost of the solution\",\"default\":-1,\"examples\":[2]},\"vehicle_data\":{\"additionalProperties\":{\"properties\":{\"task_id\":{\"items\":{\"type\":\"string\"},\"type\":\"array\",\"title\":\"Task Id\",\"description\":\"task_ids being assigned to vehicle along with depot and breaks\",\"default\":[]},\"arrival_stamp\":{\"items\":{\"type\":\"number\"},\"type\":\"array\",\"title\":\"Arrival Stamp\",\"description\":\"arrival stamps at each task locations\",\"default\":[]},\"route\":{\"items\":{\"type\":\"integer\"},\"type\":\"array\",\"title\":\"Route\",\"description\":\"Route indices as per waypoint graph or cost matrix provided\",\"default\":[]},\"type\":{\"items\":{\"type\":\"string\",\"enum\":[\"Depot\",\"Pickup\",\"Delivery\",\"Break\",\"w\"],\"title\":\"LocationTypeEnum\"},\"type\":\"array\",\"title\":\"Type\",\"description\":\"Type of routing point, whether it is Depot, Waypoint - w \\nDelivery, Break, Pickup \\n\",\"default\":[]}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"VehicleData\"},\"type\":\"object\",\"title\":\"Vehicle Data\",\"description\":\"All the details of vehicle routes and timestamps\",\"default\":{},\"examples\":[{\"vehicle_data\":{\"veh-1\":{\"arrival_stamp\":[1,2],\"route\":[1,1],\"task_id\":[\"Break\",\"Task-A\"],\"type\":[\"Break\",\"Delivery\"]},\"veh-2\":{\"arrival_stamp\":[2,2,4,5],\"route\":[0,0,2,0],\"task_id\":[\"Depot\",\"Break\",\"Task-B\",\"Depot\"],\"type\":[\"Depot\",\"Break\",\"Delivery\",\"Depot\"]}}}]},\"msg\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Msg\",\"description\":\"Any information pertaining to the run.\",\"default\":\"\"}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"InfeasibleResultData\"}],\"description\":\"Infeasible solution, this can mean the problem itself is infeasible or solver requires more time to find a solution. Setting default solve time is suggested in case you are not aware of the expected time.\",\"default\":{\"status\":1,\"num_vehicles\":-1,\"solution_cost\":-1,\"vehicle_data\":{},\"msg\":\"\"}},\"perf_times\":{\"anyOf\":[{\"type\":\"object\"},{\"type\":\"null\"}],\"title\":\"Perf Times\",\"description\":\"Etl and Solve times of the solve call\"}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"InFeasibleSolve\"}],\"title\":\"Response\",\"description\":\"Response\"},\"warnings\":{\"items\":{\"type\":\"string\"},\"type\":\"array\",\"title\":\"Warnings\",\"description\":\"List of warnings for users to handle issues\",\"default\":[]},\"notes\":{\"items\":{\"type\":\"string\"},\"type\":\"array\",\"title\":\"Notes\",\"description\":\"Any notes for users\",\"default\":[]}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"response\"],\"title\":\"ResponseModel\"}],\"title\":\"Response Cuopt Cuopt Cuopt Post\"}}}},\"202\":{\"description\":\"Result is pending. Client should poll using the requestId.\\n\",\"content\":{\"application/json\":{\"example\":{},\"schema\":{}}},\"headers\":{\"NVCF-REQID\":{\"description\":\"requestId required for pooling\",\"schema\":{\"type\":\"string\",\"format\":\"uuid\",\"maxLength\":36}},\"NVCF-STATUS\":{\"description\":\"Invocation status\",\"schema\":{\"type\":\"string\",\"format\":\"^[a-zA-Z-]{1,64}$\",\"maxLength\":64}}}},\"400\":{\"description\":\"Value Error Or Validation Error\",\"content\":{\"application/json\":{\"schema\":{\"properties\":{\"detail\":{\"type\":\"string\",\"title\":\"Detail\",\"description\":\"Error details\"}},\"type\":\"object\",\"required\":[\"detail\"],\"title\":\"DetailModel\"}}}},\"409\":{\"description\":\"Failed to get route\",\"content\":{\"application/json\":{\"schema\":{\"properties\":{\"detail\":{\"type\":\"string\",\"title\":\"Detail\",\"description\":\"Error details\"}},\"type\":\"object\",\"required\":[\"detail\"],\"title\":\"DetailModel\"}}}},\"422\":{\"description\":\"Unprocessable Entity or Runtime Error or Out of memory error\",\"content\":{\"application/json\":{\"schema\":{\"properties\":{\"detail\":{\"type\":\"string\",\"title\":\"Detail\",\"description\":\"Error details\"}},\"type\":\"object\",\"required\":[\"detail\"],\"title\":\"DetailModel\"}}}},\"500\":{\"description\":\"Any uncaught cuOpt error or Server errors\",\"content\":{\"application/json\":{\"schema\":{\"properties\":{\"detail\":{\"type\":\"string\",\"title\":\"Detail\",\"description\":\"Error details\"}},\"type\":\"object\",\"required\":[\"detail\"],\"title\":\"DetailModel\"}}}}},\"x-nvai-meta\":{\"name\":\"VRP examples\",\"returns\":\"Returns a json reponse with vehicle routing details.\",\"path\":\"route\",\"examples\":[{\"name\":\"VRP problem\",\"requestJson\":\"$be\",\"responseJson\":\"{\\\"response\\\":{\\\"solver_response\\\":{\\\"status\\\":0,\\\"num_vehicles\\\":2,\\\"solution_cost\\\":2,\\\"vehicle_data\\\":{\\\"veh-1\\\":{\\\"task_id\\\":[\\\"Break\\\",\\\"Task-A\\\"],\\\"arrival_stamp\\\":[1,2],\\\"route\\\":[1,1],\\\"type\\\":[\\\"Break\\\",\\\"Delivery\\\"]},\\\"veh-2\\\":{\\\"task_id\\\":[\\\"Depot\\\",\\\"Break\\\",\\\"Task-B\\\",\\\"Depot\\\"],\\\"arrival_stamp\\\":[2,2,4,5],\\\"route\\\":[0,0,2,0],\\\"type\\\":[\\\"Depot\\\",\\\"Break\\\",\\\"Delivery\\\",\\\"Depot\\\"]}},\\\"msg\\\":\\\"\\\",\\\"perf_times\\\":{\\\"etl_time\\\":0.008506059646606445,\\\"solver_run_time\\\":0.5540950298309326}}},\\\"warnings\\\":[],\\\"notes\\\":[]}\"}],\"templates\":[{\"title\":\"Examples\",\"requestEjs\":{\"python\":\"$bf\",\"node.js\":\"$c0\",\"curl\":\"$c1\"},\"response\":\"{\\\"response\\\":{\\\"solver_response\\\":{\\\"status\\\":0,\\\"num_vehicles\\\":2,\\\"solution_cost\\\":2,\\\"vehicle_data\\\":{\\\"veh-1\\\":{\\\"task_id\\\":[\\\"Break\\\",\\\"Task-A\\\"],\\\"arrival_stamp\\\":[1,2],\\\"route\\\":[1,1],\\\"type\\\":[\\\"Break\\\",\\\"Delivery\\\"]},\\\"veh-2\\\":{\\\"task_id\\\":[\\\"Depot\\\",\\\"Break\\\",\\\"Task-B\\\",\\\"Depot\\\"],\\\"arrival_stamp\\\":[2,2,4,5],\\\"route\\\":[0,0,2,0],\\\"type\\\":[\\\"Depot\\\",\\\"Break\\\",\\\"Delivery\\\",\\\"Depot\\\"]}},\\\"msg\\\":\\\"\\\",\\\"perf_times\\\":{\\\"etl_time\\\":0.008506059646606445,\\\"solver_run_time\\\":0.5540950298309326}}},\\\"warnings\\\":[],\\\"notes\\\":[]}\"}]}}},\"/status/{requestId}\":{\"get\":{\"tags\":[\"nvidia / cuOpt\"],\"summary\":\"Status polling\",\"description\":\"Gets the result of an earlier function invocation request that returned a status of 202.\",\"operationId\":\"nvidia-cuopt-statuspolling\",\"parameters\":[{\"name\":\"requestId\",\"in\":\"path\",\"description\":\"requestId to poll results\",\"required\":true,\"schema\":{\"type\":\"string\",\"format\":\"uuid\",\"maxLength\":36}}],\"responses\":{\"200\":{\"description\":\"Invocation is fulfilled\",\"content\":{\"application/json\":{}}},\"202\":{\"description\":\"Result is pending. Client should poll using the requestId.\\n\",\"content\":{\"application/json\":{\"example\":{},\"schema\":{}}},\"headers\":{\"NVCF-REQID\":{\"description\":\"requestId required for pooling\",\"schema\":{\"type\":\"string\",\"format\":\"uuid\",\"maxLength\":36}},\"NVCF-STATUS\":{\"description\":\"Invocation status\",\"schema\":{\"type\":\"string\",\"format\":\"^[a-zA-Z-]{1,64}$\",\"maxLength\":64}}}},\"422\":{\"description\":\"The invocation ended with an error.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/Errors\"},\"example\":{\"type\":\"urn:nvcf-worker-service:problem-details:unprocessable-entity\",\"title\":\"Unprocessable Entity\",\"status\":422,\"detail\":\"string\",\"instance\":\"/v2/nvcf/pexec/functions/784a8ca4-ea7d-4c93-bb46-ec027c3fae47\",\"requestId\":\"3fa85f64-5717-4562-b3fc-2c963f66afa6\"}}}},\"500\":{\"description\":\"The invocation ended with an error.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/Errors\"},\"example\":{\"type\":\"urn:nvcf-worker-service:problem-details:internal-server-error\",\"title\":\"Internal Server Error\",\"status\":500,\"detail\":\"string\",\"instance\":\"/v2/nvcf/pexec/functions/784a8ca4-ea7d-4c93-bb46-ec027c3fae47\",\"requestId\":\"3fa85f64-5717-4562-b3fc-2c963f66afa6\"}}}}}}}},\"security\":[{\"Token\":[]}],\"components\":{\"securitySchemes\":{\"Token\":{\"type\":\"http\",\"scheme\":\"bearer\"}},\"schemas\":{\"Errors\":{\"properties\":{\"type\":{\"type\":\"string\",\"description\":\"Error type\"},\"title\":{\"type\":\"string\",\"description\":\"Error title\"},\"status\":{\"type\":\"integer\",\"description\":\"Error status code\"},\"detail\":{\"type\":\"string\",\"description\":\"Detailed information about the error\"},\"instance\":{\"type\":\"string\",\"description\":\"Function instance used to invoke the request\"},\"requestId\":{\"type\":\"string\",\"format\":\"uuid\",\"description\":\"UUID of the request\"}},\"type\":\"object\",\"required\":[\"type\",\"title\",\"status\",\"detail\",\"instance\",\"requestId\"],\"title\":\"InvokeError\"},\"DetailModel\":{\"properties\":{\"detail\":{\"type\":\"string\",\"title\":\"Detail\",\"description\":\"Error details\"}},\"type\":\"object\",\"required\":[\"detail\"],\"title\":\"DetailModel\"},\"EmptyDict\":{\"properties\":{},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"EmptyDict\"},\"FeasibleResultData\":{\"properties\":{\"status\":{\"type\":\"integer\",\"title\":\"Status\",\"maximum\":0,\"minimum\":0,\"description\":\"0 - Solution is available \\n1 - Infeasible solution is available \\n\",\"default\":0,\"examples\":[0]},\"num_vehicles\":{\"type\":\"integer\",\"title\":\"Num Vehicles\",\"maximum\":2147483647,\"minimum\":0,\"description\":\"Number of vehicle being used for the solution\",\"default\":-1,\"examples\":[2]},\"solution_cost\":{\"type\":\"number\",\"title\":\"Solution Cost\",\"description\":\"Total cost of the solution\",\"default\":-1,\"examples\":[2]},\"vehicle_data\":{\"additionalProperties\":{\"properties\":{\"task_id\":{\"items\":{\"type\":\"string\"},\"type\":\"array\",\"title\":\"Task Id\",\"description\":\"task_ids being assigned to vehicle along with depot and breaks\",\"default\":[]},\"arrival_stamp\":{\"items\":{\"type\":\"number\"},\"type\":\"array\",\"title\":\"Arrival Stamp\",\"description\":\"arrival stamps at each task locations\",\"default\":[]},\"route\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\",\"title\":\"Route\",\"description\":\"Route indices as per waypoint graph or cost matrix provided\",\"default\":[]},\"type\":{\"items\":{\"type\":\"string\",\"enum\":[\"Depot\",\"Pickup\",\"Delivery\",\"Break\",\"w\"],\"title\":\"LocationTypeEnum\"},\"type\":\"array\",\"title\":\"Type\",\"description\":\"Type of routing point, whether it is Depot, Waypoint - w \\nDelivery, Break, Pickup \\n\",\"default\":[]}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"VehicleData\"},\"type\":\"object\",\"title\":\"Vehicle Data\",\"description\":\"All the details of vehicle routes and timestamps\",\"default\":{},\"examples\":[{\"vehicle_data\":{\"veh-1\":{\"arrival_stamp\":[1,2],\"route\":[1,1],\"task_id\":[\"Break\",\"Task-A\"],\"type\":[\"Break\",\"Delivery\"]},\"veh-2\":{\"arrival_stamp\":[2,2,4,5],\"route\":[0,0,2,0],\"task_id\":[\"Depot\",\"Break\",\"Task-B\",\"Depot\"],\"type\":[\"Depot\",\"Break\",\"Delivery\",\"Depot\"]}}}]},\"msg\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Msg\",\"description\":\"Any information pertaining to the run.\",\"default\":\"\"}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"FeasibleResultData\"},\"FeasibleSolve\":{\"properties\":{\"solver_response\":{\"allOf\":[{\"properties\":{\"status\":{\"type\":\"integer\",\"title\":\"Status\",\"maximum\":0,\"minimum\":0,\"description\":\"0 - Solution is available \\n1 - Infeasible solution is available \\n\",\"default\":0,\"examples\":[0]},\"num_vehicles\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0,\"title\":\"Num Vehicles\",\"description\":\"Number of vehicle being used for the solution\",\"default\":-1,\"examples\":[2]},\"solution_cost\":{\"type\":\"number\",\"title\":\"Solution Cost\",\"description\":\"Total cost of the solution\",\"default\":-1,\"examples\":[2]},\"vehicle_data\":{\"additionalProperties\":{\"properties\":{\"task_id\":{\"items\":{\"type\":\"string\"},\"type\":\"array\",\"title\":\"Task Id\",\"description\":\"task_ids being assigned to vehicle along with depot and breaks\",\"default\":[]},\"arrival_stamp\":{\"items\":{\"type\":\"number\"},\"type\":\"array\",\"title\":\"Arrival Stamp\",\"description\":\"arrival stamps at each task locations\",\"default\":[]},\"route\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\",\"title\":\"Route\",\"description\":\"Route indices as per waypoint graph or cost matrix provided\",\"default\":[]},\"type\":{\"items\":{\"type\":\"string\",\"enum\":[\"Depot\",\"Pickup\",\"Delivery\",\"Break\",\"w\"],\"title\":\"LocationTypeEnum\"},\"type\":\"array\",\"title\":\"Type\",\"description\":\"Type of routing point, whether it is Depot, Waypoint - w \\nDelivery, Break, Pickup \\n\",\"default\":[]}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"VehicleData\"},\"type\":\"object\",\"title\":\"Vehicle Data\",\"description\":\"All the details of vehicle routes and timestamps\",\"default\":{},\"examples\":[{\"vehicle_data\":{\"veh-1\":{\"arrival_stamp\":[1,2],\"route\":[1,1],\"task_id\":[\"Break\",\"Task-A\"],\"type\":[\"Break\",\"Delivery\"]},\"veh-2\":{\"arrival_stamp\":[2,2,4,5],\"route\":[0,0,2,0],\"task_id\":[\"Depot\",\"Break\",\"Task-B\",\"Depot\"],\"type\":[\"Depot\",\"Break\",\"Delivery\",\"Depot\"]}}}]},\"msg\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Msg\",\"description\":\"Any information pertaining to the run.\",\"default\":\"\"}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"FeasibleResultData\"}],\"description\":\"Feasible solution\",\"default\":{\"status\":0,\"num_vehicles\":-1,\"solution_cost\":-1,\"vehicle_data\":{},\"msg\":\"\"}},\"perf_times\":{\"anyOf\":[{\"type\":\"object\"},{\"type\":\"null\"}],\"title\":\"Perf Times\",\"description\":\"Etl and Solve times of the solve call\"}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"FeasibleSolve\"},\"FleetData\":{\"properties\":{\"vehicle_locations\":{\"items\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\"},\"type\":\"array\",\"title\":\"Vehicle Locations\",\"description\":\"dtype: int32, vehicle_location \u003e= 0. \\n\\n Start and end location of the vehicles in the given set of locations in WayPointGraph or CostMatrices.\\nExample: For 2 vehicles, \\n\\n [ \\n\\n [veh_1_start_loc, veh_1_end_loc], \\n\\n [veh_2_start_loc, veh_2_end_loc] \\n\\n ]\",\"examples\":[[[0,0],[0,0]]]},\"vehicle_ids\":{\"anyOf\":[{\"items\":{\"type\":\"string\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Vehicle Ids\",\"description\":\"List of the vehicle ids or names provided as a string.\",\"examples\":[[\"veh-1\",\"veh-2\"]]},\"capacities\":{\"anyOf\":[{\"items\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Capacities\",\"description\":\"dtype: int32, capacity \u003e= 0. \\n\\n Note: For this release number of capacity dimensions are limited to 3. \\n\\n Lists of capacities of each vehicle.\\nMultiple capacities can be added and each list will represent one kind of capacity. Order of kind of the capacities should match order of the demands.\\nTotal capacity for each type should be sufficient to complete all demand of that type.Example: In case of two sets of capacities per vehicle with 3 vehicles, \\n\\n [ \\n\\n [cap_1_veh_1, cap_1_veh_2, cap_1_veh_3], \\n\\n [cap_2_veh_1, cap_2_veh_2, cap_2_veh_3] \\n\\n ]\",\"examples\":[[[2,2],[4,1]]]},\"vehicle_time_windows\":{\"anyOf\":[{\"items\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Vehicle Time Windows\",\"description\":\"dtype: int32, time \u003e= 0. \\n\\n Earliest and Latest time window pairs for each vehicle,\\nfor example the data would look as follows for 2 vehicles, \\n \\n\\n [ \\n\\n [veh_1_earliest, veh_1_latest], \\n\\n [veh_2_earliest, veh_2_latest] \\n\\n ]\",\"examples\":[[[0,10],[0,10]]]},\"vehicle_break_time_windows\":{\"anyOf\":[{\"items\":{\"items\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\"},\"type\":\"array\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Vehicle Break Time Windows\",\"description\":\"dtype: int32, time \u003e= 0. \\n\\n Multiple break time windows can be added for each vehicle.Earliest and Latest break time window pairs for each vehicle,\\nFor example, in case of 2 sets of breaks for each vehicle which translates to 2 dimensions of breaks,\\n \\n\\n [ \\n\\n [[brk_1_veh_1_earliest, brk_1_veh_1_latest], [brk_1_veh_2_earliest, brk_1_veh_2_latest]] \\n\\n [[brk_2_veh_1_earliest, brk_2_veh_1_latest], [brk_2_veh_2_earliest, brk_2_veh_2_latest]] \\n\\n ] \\n\\n The break duration within this time window is provided through vehicle_break_durations.\",\"examples\":[[[[1,2],[2,3]]]]},\"vehicle_break_durations\":{\"anyOf\":[{\"items\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Vehicle Break Durations\",\"description\":\"dtype: int32, time \u003e= 0. \\n\\n Break duration for each vehicle. vehicle_break_time_windows should be provided to use this option.For example, in case of having 2 breaks for each vehicle, \\n\\n [ \\n\\n [brk_1_veh_1_duration, brk_1_veh_2_duration], \\n\\n [brk_2_veh_1_duration, brk_2_veh_2_duration], \\n\\n ]\",\"examples\":[[[1,1]]]},\"vehicle_break_locations\":{\"anyOf\":[{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Vehicle Break Locations\",\"description\":\"dtype: int32, location \u003e= 0. \\n\\n Break location where vehicles can take breaks. If not set, any location can be used for the break.\",\"examples\":[[0,1]]},\"vehicle_types\":{\"anyOf\":[{\"items\":{\"type\":\"integer\",\"maximum\":255,\"minimum\":0},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Vehicle Types\",\"description\":\"dtype: uint8. \\n\\n Types of vehicles in the fleet given as positive integers.\",\"examples\":[[1,2]]},\"vehicle_order_match\":{\"anyOf\":[{\"items\":{\"properties\":{\"vehicle_id\":{\"type\":\"integer\",\"title\":\"Vehicle Id\",\"description\":\"dtype: int32, vehicle_id \u003e= 0. \\n\\n Vehicle id as an integer, and can serve all the order listed in order_ids.\",\"maximum\":2147483647,\"minimum\":0},\"order_ids\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\",\"title\":\"Order Ids\",\"description\":\"dtype: int32, order_id \u003e= 0. \\n\\n Indices of orders which can be served by this particular vehicle\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"vehicle_id\",\"order_ids\"],\"title\":\"VehicleOrderMatch\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Vehicle Order Match\",\"description\":\"A list of vehicle order match, where the match would contain a vehicle id and a list of orders that vehicle can serve.\",\"examples\":[[{\"order_ids\":[0],\"vehicle_id\":0},{\"order_ids\":[1],\"vehicle_id\":1}]]},\"skip_first_trips\":{\"anyOf\":[{\"items\":{\"type\":\"boolean\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Skip First Trips\",\"description\":\"Drop the cost of trip to first location for that vehicle.\",\"examples\":[[true,false]]},\"drop_return_trips\":{\"anyOf\":[{\"items\":{\"type\":\"boolean\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Drop Return Trips\",\"description\":\"Drop cost of return trip for each vehicle.\",\"examples\":[[true,false]]},\"min_vehicles\":{\"anyOf\":[{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},{\"type\":\"null\"}],\"title\":\"Min Vehicles\",\"description\":\"dtype: int32, min_vehicles \u003e= 1. \\n\\n Solution should consider minimum number of vehicles\",\"examples\":[2]},\"vehicle_max_costs\":{\"anyOf\":[{\"items\":{\"type\":\"number\",\"minimum\":0},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Vehicle Max Costs\",\"description\":\"dtype: float32, max_costs \u003e= 0. \\n\\n Maximum cost a vehicle can incur and it is based on cost matrix/cost waypoint graph.\",\"examples\":[[7,10]]},\"vehicle_max_times\":{\"anyOf\":[{\"items\":{\"type\":\"number\",\"minimum\":0},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Vehicle Max Times\",\"description\":\"dtype: float32, max_time \u003e= 0. \\n\\n Maximum time a vehicle can operate (includes drive, service and wait time), this is based on travel time matrix/travel time waypoint graph.\",\"examples\":[[7,10]]},\"vehicle_fixed_costs\":{\"anyOf\":[{\"items\":{\"type\":\"number\",\"minimum\":0},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Vehicle Fixed Costs\",\"description\":\"dtype: float32, fixed_cost \u003e= 0. \\n\\n Cost of each vehicle.This helps in routing where may be 2 vehicles with less cost is effective compared to 1 vehicle with huge cost. As example shows veh-0 (15) \u003e veh-1 (5) + veh-2 (5)\",\"examples\":[[15,5]]}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"vehicle_locations\"],\"title\":\"FleetData\"},\"InFeasibleSolve\":{\"properties\":{\"solver_infeasible_response\":{\"allOf\":[{\"properties\":{\"status\":{\"type\":\"integer\",\"title\":\"Status\",\"description\":\"1 - Infeasible solution is available \\n\",\"default\":1,\"examples\":[1],\"maximum\":1,\"minimum\":1},\"num_vehicles\":{\"type\":\"integer\",\"title\":\"Num Vehicles\",\"description\":\"Number of vehicle being used for the solution\",\"default\":-1,\"examples\":[2],\"maximum\":2147483647,\"minimum\":0},\"solution_cost\":{\"type\":\"number\",\"title\":\"Solution Cost\",\"description\":\"Total cost of the solution\",\"default\":-1,\"examples\":[2]},\"vehicle_data\":{\"additionalProperties\":{\"properties\":{\"task_id\":{\"items\":{\"type\":\"string\"},\"type\":\"array\",\"title\":\"Task Id\",\"description\":\"task_ids being assigned to vehicle along with depot and breaks\",\"default\":[]},\"arrival_stamp\":{\"items\":{\"type\":\"number\"},\"type\":\"array\",\"title\":\"Arrival Stamp\",\"description\":\"arrival stamps at each task locations\",\"default\":[]},\"route\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\",\"title\":\"Route\",\"description\":\"Route indices as per waypoint graph or cost matrix provided\",\"default\":[]},\"type\":{\"items\":{\"type\":\"string\",\"enum\":[\"Depot\",\"Pickup\",\"Delivery\",\"Break\",\"w\"],\"title\":\"LocationTypeEnum\"},\"type\":\"array\",\"title\":\"Type\",\"description\":\"Type of routing point, whether it is Depot, Waypoint - w \\nDelivery, Break, Pickup \\n\",\"default\":[]}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"VehicleData\"},\"type\":\"object\",\"title\":\"Vehicle Data\",\"description\":\"All the details of vehicle routes and timestamps\",\"default\":{},\"examples\":[{\"vehicle_data\":{\"veh-1\":{\"arrival_stamp\":[1,2],\"route\":[1,1],\"task_id\":[\"Break\",\"Task-A\"],\"type\":[\"Break\",\"Delivery\"]},\"veh-2\":{\"arrival_stamp\":[2,2,4,5],\"route\":[0,0,2,0],\"task_id\":[\"Depot\",\"Break\",\"Task-B\",\"Depot\"],\"type\":[\"Depot\",\"Break\",\"Delivery\",\"Depot\"]}}}]},\"msg\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Msg\",\"description\":\"Any information pertaining to the run.\",\"default\":\"\"}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"InfeasibleResultData\"}],\"description\":\"Infeasible solution, this can mean the problem itself is infeasible or solver requires more time to find a solution. Setting default solve time is suggested in case you are not aware of the expected time.\",\"default\":{\"status\":1,\"num_vehicles\":-1,\"solution_cost\":-1,\"vehicle_data\":{},\"msg\":\"\"}},\"perf_times\":{\"anyOf\":[{\"type\":\"object\"},{\"type\":\"null\"}],\"title\":\"Perf Times\",\"description\":\"Etl and Solve times of the solve call\"}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"InFeasibleSolve\"},\"InfeasibleResultData\":{\"properties\":{\"status\":{\"type\":\"integer\",\"title\":\"Status\",\"description\":\"1 - Infeasible solution is available \\n\",\"default\":1,\"examples\":[1],\"maximum\":1,\"minimum\":1},\"num_vehicles\":{\"type\":\"integer\",\"title\":\"Num Vehicles\",\"description\":\"Number of vehicle being used for the solution\",\"default\":-1,\"examples\":[2],\"maximum\":2147483647,\"minimum\":0},\"solution_cost\":{\"type\":\"number\",\"title\":\"Solution Cost\",\"description\":\"Total cost of the solution\",\"default\":-1,\"examples\":[2]},\"vehicle_data\":{\"additionalProperties\":{\"properties\":{\"task_id\":{\"items\":{\"type\":\"string\"},\"type\":\"array\",\"title\":\"Task Id\",\"description\":\"task_ids being assigned to vehicle along with depot and breaks\",\"default\":[]},\"arrival_stamp\":{\"items\":{\"type\":\"number\"},\"type\":\"array\",\"title\":\"Arrival Stamp\",\"description\":\"arrival stamps at each task locations\",\"default\":[]},\"route\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\",\"title\":\"Route\",\"description\":\"Route indices as per waypoint graph or cost matrix provided\",\"default\":[]},\"type\":{\"items\":{\"type\":\"string\",\"enum\":[\"Depot\",\"Pickup\",\"Delivery\",\"Break\",\"w\"],\"title\":\"LocationTypeEnum\"},\"type\":\"array\",\"title\":\"Type\",\"description\":\"Type of routing point, whether it is Depot, Waypoint - w \\nDelivery, Break, Pickup \\n\",\"default\":[]}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"VehicleData\"},\"type\":\"object\",\"title\":\"Vehicle Data\",\"description\":\"All the details of vehicle routes and timestamps\",\"default\":{},\"examples\":[{\"vehicle_data\":{\"veh-1\":{\"arrival_stamp\":[1,2],\"route\":[1,1],\"task_id\":[\"Break\",\"Task-A\"],\"type\":[\"Break\",\"Delivery\"]},\"veh-2\":{\"arrival_stamp\":[2,2,4,5],\"route\":[0,0,2,0],\"task_id\":[\"Depot\",\"Break\",\"Task-B\",\"Depot\"],\"type\":[\"Depot\",\"Break\",\"Delivery\",\"Depot\"]}}}]},\"msg\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Msg\",\"description\":\"Any information pertaining to the run.\",\"default\":\"\"}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"InfeasibleResultData\"},\"LocationTypeEnum\":{\"type\":\"string\",\"enum\":[\"Depot\",\"Pickup\",\"Delivery\",\"Break\",\"w\"],\"title\":\"LocationTypeEnum\"},\"Objective\":{\"properties\":{\"cost\":{\"anyOf\":[{\"type\":\"number\"},{\"type\":\"null\"}],\"title\":\"Cost\",\"description\":\"dtype: float32. \\n\\n The weight assigned to minimizing the cost for a given solution, default value is 1\",\"examples\":[1]},\"travel_time\":{\"anyOf\":[{\"type\":\"number\"},{\"type\":\"null\"}],\"title\":\"Travel Time\",\"description\":\"dtype: float32. \\n\\n The weight assigned to minimizing total travel time for a given solution (includes drive, service and wait time)\",\"examples\":[0]},\"variance_route_size\":{\"anyOf\":[{\"type\":\"number\"},{\"type\":\"null\"}],\"title\":\"Variance Route Size\",\"description\":\"dtype: float32. \\n\\n The weight assigned to the variance in the number of orders served by each route.\",\"examples\":[0]},\"variance_route_service_time\":{\"anyOf\":[{\"type\":\"number\"},{\"type\":\"null\"}],\"title\":\"Variance Route Service Time\",\"description\":\"dtype: float32. \\n\\n The weight assigned to the variance in the accumulated service times of each route\",\"examples\":[0]},\"prize\":{\"anyOf\":[{\"type\":\"number\"},{\"type\":\"null\"}],\"title\":\"Prize\",\"description\":\"dtype: float32. \\n\\n The weight assigned to the prize in accumulated prizes for each job fulfilled.This will be negated from overall values accumulated with other objectives.For example, if cost accumulated is 10 and objective value for it is 1, and if the prize accumulated is 3 and objective is 2, then total cost would look something like this 10 x 1 - 3 x 2 = 4.\",\"examples\":[0]},\"vehicle_fixed_cost\":{\"anyOf\":[{\"type\":\"number\"},{\"type\":\"null\"}],\"title\":\"Vehicle Fixed Cost\",\"description\":\"dtype: float32. \\n\\n The weight assigned to the accumulated fixed costs of each vehicle used in solution\",\"examples\":[0]}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"Objective\"},\"OptimizedRoutingData\":{\"properties\":{\"cost_waypoint_graph_data\":{\"anyOf\":[{\"properties\":{\"waypoint_graph\":{\"anyOf\":[{\"additionalProperties\":{\"properties\":{\"edges\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\",\"title\":\"Edges\",\"description\":\"dtype: int32, edge \u003e= 0. \\n\\n Vertices of all the directed edges.\"},\"offsets\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\",\"title\":\"Offsets\",\"description\":\"dtype: int32, offset \u003e= 0. \\n\\n Offsets which provide number of edges from the source vertex signified by the index.\"},\"weights\":{\"anyOf\":[{\"items\":{\"type\":\"number\",\"minimum\":0},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Weights\",\"description\":\"dtype: float32, weight \u003e= 0. \\n\\n Weights of each edges.\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"edges\",\"offsets\"],\"title\":\"WaypointGraph\"},\"type\":\"object\"},{\"type\":\"null\"}],\"title\":\"Waypoint Graph\"}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"UpdateWaypointGraphData\"},{\"type\":\"null\"}],\"description\":\"Waypoint graph with weights as cost to travel from A to B \\nand B to A. If there are different types of vehicles \\nthey can be provided with key value pair \\nwhere key is vehicle-type and value is the graph. Value of \\nvehicle type should be within [0, 255]\",\"default\":{},\"examples\":[null]},\"travel_time_waypoint_graph_data\":{\"anyOf\":[{\"properties\":{\"waypoint_graph\":{\"anyOf\":[{\"additionalProperties\":{\"properties\":{\"edges\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\",\"title\":\"Edges\",\"description\":\"dtype: int32, edge \u003e= 0. \\n\\n Vertices of all the directed edges.\"},\"offsets\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\",\"title\":\"Offsets\",\"description\":\"dtype: int32, offset \u003e= 0. \\n\\n Offsets which provide number of edges from the source vertex signified by the index.\"},\"weights\":{\"anyOf\":[{\"items\":{\"type\":\"number\",\"minimum\":0},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Weights\",\"description\":\"dtype: float32, weight \u003e= 0. \\n\\n Weights of each edges.\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"edges\",\"offsets\"],\"title\":\"WaypointGraph\"},\"type\":\"object\"},{\"type\":\"null\"}],\"title\":\"Waypoint Graph\"}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"UpdateWaypointGraphData\"},{\"type\":\"null\"}],\"description\":\"Waypoint graph with weights as time to travel from A to B \\nand B to A. If there are different types of vehicles \\nthey can be provided with key value pair \\nwhere key is vehicle-type and value is the graph. Value of \\nvehicle type should be within [0, 255]\",\"default\":{},\"examples\":[null]},\"cost_matrix_data\":{\"anyOf\":[{\"properties\":{\"data\":{\"anyOf\":[{\"additionalProperties\":{\"items\":{\"items\":{\"type\":\"number\",\"minimum\":0},\"type\":\"array\"},\"type\":\"array\"},\"type\":\"object\"},{\"type\":\"null\"}],\"title\":\"Data\",\"description\":\"dtype : vehicle-type (uint8), cost (float32), cost \u003e= 0.\\n \\n\\n Sqaure matrix with cost to travel from A to B and B to A. \\nIf there different types of vehicles which have different \\ncost matrices, they can be provided with key value pair \\nwhere key is vehicle-type and value is cost matrix. Value of \\nvehicle type should be within [0, 255]\"},\"cost_matrix\":{\"anyOf\":[{\"additionalProperties\":{\"items\":{\"items\":{\"type\":\"number\",\"minimum\":0},\"type\":\"array\"},\"type\":\"array\"},\"type\":\"object\"},{\"type\":\"null\"}],\"title\":\"Cost Matrix\",\"description\":\"This field is deprecated, please use the 'data' field instead\",\"deprecated\":true}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"UpdateCostMatrices\"},{\"type\":\"null\"}],\"description\":\"Sqaure matrix with cost to travel from A to B and B to A. \\nIf there are different types of vehicles which have different \\ncost matrices, they can be provided with key value pair \\nwhere key is vehicle-type and value is cost matrix. Value of \\nvehicle type should be within [0, 255]\",\"default\":{},\"examples\":[{\"cost_matrix\":{\"1\":[[0,1,1],[1,0,1],[1,1,0]],\"2\":[[0,1,1],[1,0,1],[1,2,0]]}}]},\"travel_time_matrix_data\":{\"anyOf\":[{\"properties\":{\"data\":{\"anyOf\":[{\"additionalProperties\":{\"items\":{\"items\":{\"type\":\"number\",\"minimum\":0},\"type\":\"array\"},\"type\":\"array\"},\"type\":\"object\"},{\"type\":\"null\"}],\"title\":\"Data\",\"description\":\"dtype : vehicle-type (uint8), cost (float32), cost \u003e= 0.\\n \\n\\n Sqaure matrix with cost to travel from A to B and B to A. \\nIf there different types of vehicles which have different \\ncost matrices, they can be provided with key value pair \\nwhere key is vehicle-type and value is cost matrix. Value of \\nvehicle type should be within [0, 255]\"},\"cost_matrix\":{\"anyOf\":[{\"additionalProperties\":{\"items\":{\"items\":{\"type\":\"number\",\"minimum\":0},\"type\":\"array\"},\"type\":\"array\"},\"type\":\"object\"},{\"type\":\"null\"}],\"title\":\"Cost Matrix\",\"description\":\"This field is deprecated, please use the 'data' field instead\",\"deprecated\":true}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"UpdateCostMatrices\"},{\"type\":\"null\"}],\"description\":\"Sqaure matrix with time to travel from A to B and B to A. \\nIf there are different types of vehicles which have different \\ntravel time matrices, they can be provided with key value pair \\nwhere key is vehicle-type and value is time matrix. Value of \\nvehicle type should be within [0, 255]\",\"default\":{},\"examples\":[{\"cost_matrix\":{\"1\":[[0,1,1],[1,0,1],[1,1,0]],\"2\":[[0,1,1],[1,0,1],[1,2,0]]}}]},\"fleet_data\":{\"allOf\":[{\"properties\":{\"vehicle_locations\":{\"items\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\"},\"type\":\"array\",\"title\":\"Vehicle Locations\",\"description\":\"dtype: int32, vehicle_location \u003e= 0. \\n\\n Start and end location of the vehicles in the given set of locations in WayPointGraph or CostMatrices.\\nExample: For 2 vehicles, \\n\\n [ \\n\\n [veh_1_start_loc, veh_1_end_loc], \\n\\n [veh_2_start_loc, veh_2_end_loc] \\n\\n ]\",\"examples\":[[[0,0],[0,0]]]},\"vehicle_ids\":{\"anyOf\":[{\"items\":{\"type\":\"string\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Vehicle Ids\",\"description\":\"List of the vehicle ids or names provided as a string.\",\"examples\":[[\"veh-1\",\"veh-2\"]]},\"capacities\":{\"anyOf\":[{\"items\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Capacities\",\"description\":\"dtype: int32, capacity \u003e= 0. \\n\\n Note: For this release number of capacity dimensions are limited to 3. \\n\\n Lists of capacities of each vehicle.\\nMultiple capacities can be added and each list will represent one kind of capacity. Order of kind of the capacities should match order of the demands.\\nTotal capacity for each type should be sufficient to complete all demand of that type.Example: In case of two sets of capacities per vehicle with 3 vehicles, \\n\\n [ \\n\\n [cap_1_veh_1, cap_1_veh_2, cap_1_veh_3], \\n\\n [cap_2_veh_1, cap_2_veh_2, cap_2_veh_3] \\n\\n ]\",\"examples\":[[[2,2],[4,1]]]},\"vehicle_time_windows\":{\"anyOf\":[{\"items\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Vehicle Time Windows\",\"description\":\"dtype: int32, time \u003e= 0. \\n\\n Earliest and Latest time window pairs for each vehicle,\\nfor example the data would look as follows for 2 vehicles, \\n \\n\\n [ \\n\\n [veh_1_earliest, veh_1_latest], \\n\\n [veh_2_earliest, veh_2_latest] \\n\\n ]\",\"examples\":[[[0,10],[0,10]]]},\"vehicle_break_time_windows\":{\"anyOf\":[{\"items\":{\"items\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\"},\"type\":\"array\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Vehicle Break Time Windows\",\"description\":\"dtype: int32, time \u003e= 0. \\n\\n Multiple break time windows can be added for each vehicle.Earliest and Latest break time window pairs for each vehicle,\\nFor example, in case of 2 sets of breaks for each vehicle which translates to 2 dimensions of breaks,\\n \\n\\n [ \\n\\n [[brk_1_veh_1_earliest, brk_1_veh_1_latest], [brk_1_veh_2_earliest, brk_1_veh_2_latest]] \\n\\n [[brk_2_veh_1_earliest, brk_2_veh_1_latest], [brk_2_veh_2_earliest, brk_2_veh_2_latest]] \\n\\n ] \\n\\n The break duration within this time window is provided through vehicle_break_durations.\",\"examples\":[[[[1,2],[2,3]]]]},\"vehicle_break_durations\":{\"anyOf\":[{\"items\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Vehicle Break Durations\",\"description\":\"dtype: int32, time \u003e= 0. \\n\\n Break duration for each vehicle. vehicle_break_time_windows should be provided to use this option.For example, in case of having 2 breaks for each vehicle, \\n\\n [ \\n\\n [brk_1_veh_1_duration, brk_1_veh_2_duration], \\n\\n [brk_2_veh_1_duration, brk_2_veh_2_duration], \\n\\n ]\",\"examples\":[[[1,1]]]},\"vehicle_break_locations\":{\"anyOf\":[{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Vehicle Break Locations\",\"description\":\"dtype: int32, location \u003e= 0. \\n\\n Break location where vehicles can take breaks. If not set, any location can be used for the break.\",\"examples\":[[0,1]]},\"vehicle_types\":{\"anyOf\":[{\"items\":{\"type\":\"integer\",\"maximum\":255,\"minimum\":0},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Vehicle Types\",\"description\":\"dtype: uint8. \\n\\n Types of vehicles in the fleet given as positive integers.\",\"examples\":[[1,2]]},\"vehicle_order_match\":{\"anyOf\":[{\"items\":{\"properties\":{\"vehicle_id\":{\"type\":\"integer\",\"title\":\"Vehicle Id\",\"description\":\"dtype: int32, vehicle_id \u003e= 0. \\n\\n Vehicle id as an integer, and can serve all the order listed in order_ids.\",\"maximum\":2147483647,\"minimum\":0},\"order_ids\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\",\"title\":\"Order Ids\",\"description\":\"dtype: int32, order_id \u003e= 0. \\n\\n Indices of orders which can be served by this particular vehicle\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"vehicle_id\",\"order_ids\"],\"title\":\"VehicleOrderMatch\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Vehicle Order Match\",\"description\":\"A list of vehicle order match, where the match would contain a vehicle id and a list of orders that vehicle can serve.\",\"examples\":[[{\"order_ids\":[0],\"vehicle_id\":0},{\"order_ids\":[1],\"vehicle_id\":1}]]},\"skip_first_trips\":{\"anyOf\":[{\"items\":{\"type\":\"boolean\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Skip First Trips\",\"description\":\"Drop the cost of trip to first location for that vehicle.\",\"examples\":[[true,false]]},\"drop_return_trips\":{\"anyOf\":[{\"items\":{\"type\":\"boolean\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Drop Return Trips\",\"description\":\"Drop cost of return trip for each vehicle.\",\"examples\":[[true,false]]},\"min_vehicles\":{\"anyOf\":[{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},{\"type\":\"null\"}],\"title\":\"Min Vehicles\",\"description\":\"dtype: int32, min_vehicles \u003e= 1. \\n\\n Solution should consider minimum number of vehicles\",\"examples\":[2]},\"vehicle_max_costs\":{\"anyOf\":[{\"items\":{\"type\":\"number\",\"minimum\":0},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Vehicle Max Costs\",\"description\":\"dtype: float32, max_costs \u003e= 0. \\n\\n Maximum cost a vehicle can incur and it is based on cost matrix/cost waypoint graph.\",\"examples\":[[7,10]]},\"vehicle_max_times\":{\"anyOf\":[{\"items\":{\"type\":\"number\",\"minimum\":0},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Vehicle Max Times\",\"description\":\"dtype: float32, max_time \u003e= 0. \\n\\n Maximum time a vehicle can operate (includes drive, service and wait time), this is based on travel time matrix/travel time waypoint graph.\",\"examples\":[[7,10]]},\"vehicle_fixed_costs\":{\"anyOf\":[{\"items\":{\"type\":\"number\",\"minimum\":0},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Vehicle Fixed Costs\",\"description\":\"dtype: float32, fixed_cost \u003e= 0. \\n\\n Cost of each vehicle.This helps in routing where may be 2 vehicles with less cost is effective compared to 1 vehicle with huge cost. As example shows veh-0 (15) \u003e veh-1 (5) + veh-2 (5)\",\"examples\":[[15,5]]}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"vehicle_locations\"],\"title\":\"FleetData\"}],\"description\":\"All Fleet information\"},\"task_data\":{\"allOf\":[{\"properties\":{\"task_locations\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\",\"title\":\"Task Locations\",\"description\":\"dtype: int32, location \u003e= 0. \\n\\n Location where the task has been requested.\",\"examples\":[[1,2]]},\"task_ids\":{\"anyOf\":[{\"items\":{\"type\":\"string\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Task Ids\",\"description\":\"List of the task ids or names provided as a string.\",\"examples\":[[\"Task-A\",\"Task-B\"]]},\"demand\":{\"anyOf\":[{\"items\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Demand\",\"description\":\"dtype: int32 \\n\\n Note: For this release number of demand dimensions are limited to 3. \\n\\n Lists of demands of each tasks.\\nMultiple demands can be added and each list represents one kind of demand. Order of these demands should match the type of vehicle capacities provided.Example: In case of two sets of demands per vehicle with 3 vehicles, \\n\\n [ \\n\\n [dem_1_tsk_1, dem_1_tsk_2, dem_1_tsk_3], \\n\\n [dem_2_tsk_1, dem_2_tsk_2, dem_2_tsk_3] \\n\\n ]\",\"examples\":[[[1,1],[3,1]]]},\"pickup_and_delivery_pairs\":{\"anyOf\":[{\"items\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Pickup And Delivery Pairs\",\"description\":\"dtype: int32, pairs \u003e= 0. \\n\\n List of Pick-up and delivery index pairs from task locations.\\nIn case we have the following pick-up and delivery locations, 2-\u003e1, 4-\u003e5, 3-\u003e4, then task locations would look something like, task_locations = [0, 2, 1, 4, 5, 3, 4] and pick-up and delivery pairs would be index of those locations in task location and would look like [[1, 2], [3, 4], [5, 6]], 1 is pickup index for location 2 and it should be delivered to location 1 which is at index 2.Example schema: \\n\\n [ \\n\\n [pcikup_1_idx_to_task, drop_1_idx_to_task], \\n\\n [pcikup_2_idx_to_task, drop_2_idx_to_task], \\n\\n ]\",\"examples\":[null]},\"task_time_windows\":{\"anyOf\":[{\"items\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Task Time Windows\",\"description\":\"dtype: int32, time \u003e= 0. \\n\\n Earliest and Latest time windows for each tasks.\\nFor example the data would look as follows, \\n \\n\\n [ \\n\\n [tsk_1_earliest, tsk_1_latest], \\n\\n [tsk_2_earliest, tsk_2_latest] \\n\\n ]\",\"examples\":[[[0,5],[3,9]]]},\"service_times\":{\"anyOf\":[{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\"},{\"additionalProperties\":{\"items\":{\"type\":\"integer\"},\"type\":\"array\"},\"type\":\"object\"},{\"type\":\"null\"}],\"title\":\"Service Times\",\"description\":\"dtype: int32, time \u003e= 0. \\n\\n Service time for each task. Accepts a list of service times for all vehicles. In case of vehicle specific service times, accepts a dict with key as vehicle id and value as list of service times.Example schema: In case all vehicles have same service times, \\n\\n [tsk_1_srv_time, tsk_2_srv_time, tsk_3_srv_time] \\n\\n \\n\\n In case, there are 2 types of vehicle types and each of them have different service times, \\n\\n { \\n\\n type-1: [tsk_1_srv_time, tsk_3_srv_time, tsk_3_srv_time], \\n\\n type-2: [tsk_1_srv_time, tsk_3_srv_time, tsk_3_srv_time] \\n\\n }\",\"examples\":[[0,0]]},\"prizes\":{\"anyOf\":[{\"items\":{\"type\":\"number\",\"minimum\":0},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Prizes\",\"description\":\"dtype: float32, prizes \u003e= 0. \\n\\n List of values which signifies prizes that are collected for fulfilling each task. This can be used effectively in case solution is infeasible and need to drop few tasks to get feasible solution. Solver will prioritize for higher prize tasks \",\"examples\":[null]},\"order_vehicle_match\":{\"anyOf\":[{\"items\":{\"properties\":{\"order_id\":{\"type\":\"integer\",\"title\":\"Order Id\",\"description\":\"dtype: int32, order_id \u003e= 0. \\n\\n Indices of orders which can be served by this particular vehicleOrder id as an integer\",\"maximum\":2147483647,\"minimum\":0},\"vehicle_ids\":{\"items\":{\"type\":\"integer\"},\"type\":\"array\",\"title\":\"Vehicle Ids\",\"description\":\"dtype: int32, vehicle_id \u003e= 0. \\n\\n Indices of the vehicles which can serve this particular order. \\n\",\"maximum\":2147483647,\"minimum\":0}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"order_id\",\"vehicle_ids\"],\"title\":\"OrderVehicleMatch\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Order Vehicle Match\",\"description\":\"A list of order vehicle match, where the match would contain a order id and a list of vehicle ids that can serve this order.\",\"examples\":[[{\"order_id\":0,\"vehicle_ids\":[0]},{\"order_id\":1,\"vehicle_ids\":[1]}]]},\"mandatory_task_ids\":{\"anyOf\":[{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Mandatory Task Ids\",\"description\":\"dtype: int32, mandatory_task_id \u003e= 0. \\n\\n Note: This is only effective when used along with drop infeasible option. \\n\\n A list of task ids which are mandatory and solver would fail if these cannot be fulfilled.\",\"examples\":[null]}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"task_locations\"],\"title\":\"TaskData\"}],\"description\":\"All Task information\"},\"solver_config\":{\"anyOf\":[{\"properties\":{\"time_limit\":{\"anyOf\":[{\"type\":\"number\",\"minimum\":0},{\"type\":\"null\"}],\"title\":\"Time Limit\",\"description\":\"SolverSettings time limit\",\"examples\":[1]},\"objectives\":{\"anyOf\":[{\"properties\":{\"cost\":{\"anyOf\":[{\"type\":\"number\"},{\"type\":\"null\"}],\"title\":\"Cost\",\"description\":\"dtype: float32. \\n\\n The weight assigned to minimizing the cost for a given solution, default value is 1\",\"examples\":[1]},\"travel_time\":{\"anyOf\":[{\"type\":\"number\"},{\"type\":\"null\"}],\"title\":\"Travel Time\",\"description\":\"dtype: float32. \\n\\n The weight assigned to minimizing total travel time for a given solution (includes drive, service and wait time)\",\"examples\":[0]},\"variance_route_size\":{\"anyOf\":[{\"type\":\"number\"},{\"type\":\"null\"}],\"title\":\"Variance Route Size\",\"description\":\"dtype: float32. \\n\\n The weight assigned to the variance in the number of orders served by each route.\",\"examples\":[0]},\"variance_route_service_time\":{\"anyOf\":[{\"type\":\"number\"},{\"type\":\"null\"}],\"title\":\"Variance Route Service Time\",\"description\":\"dtype: float32. \\n\\n The weight assigned to the variance in the accumulated service times of each route\",\"examples\":[0]},\"prize\":{\"anyOf\":[{\"type\":\"number\"},{\"type\":\"null\"}],\"title\":\"Prize\",\"description\":\"dtype: float32. \\n\\n The weight assigned to the prize in accumulated prizes for each job fulfilled.This will be negated from overall values accumulated with other objectives.For example, if cost accumulated is 10 and objective value for it is 1, and if the prize accumulated is 3 and objective is 2, then total cost would look something like this 10 x 1 - 3 x 2 = 4.\",\"examples\":[0]},\"vehicle_fixed_cost\":{\"anyOf\":[{\"type\":\"number\"},{\"type\":\"null\"}],\"title\":\"Vehicle Fixed Cost\",\"description\":\"dtype: float32. \\n\\n The weight assigned to the accumulated fixed costs of each vehicle used in solution\",\"examples\":[0]}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"Objective\"},{\"type\":\"null\"}],\"description\":\"Values provided dictate the linear combination of factors used to evaluate solution quality.Only prize will be negated, all others gets accumulated. That's why sometime you might come across negative value as solution cost.\"},\"config_file\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Config File\",\"description\":\"Dump configuration information in a given file as yaml\",\"examples\":[null]},\"verbose_mode\":{\"anyOf\":[{\"type\":\"boolean\"},{\"type\":\"null\"}],\"title\":\"Verbose Mode\",\"description\":\"Displaying internal information during the solver execution.\",\"default\":false},\"error_logging\":{\"anyOf\":[{\"type\":\"boolean\"},{\"type\":\"null\"}],\"title\":\"Error Logging\",\"description\":\"Displaying constraint error information during the solver execution.\",\"default\":true}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"UpdateSolverSettingsConfig\"},{\"type\":\"null\"}]}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"fleet_data\",\"task_data\"],\"title\":\"OptimizedRoutingData\"},\"OrderVehicleMatch\":{\"properties\":{\"order_id\":{\"type\":\"integer\",\"title\":\"Order Id\",\"description\":\"dtype: int32, order_id \u003e= 0. \\n\\n Indices of orders which can be served by this particular vehicleOrder id as an integer\",\"maximum\":2147483647,\"minimum\":0},\"vehicle_ids\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\",\"title\":\"Vehicle Ids\",\"description\":\"dtype: int32, vehicle_id \u003e= 0. \\n\\n Indices of the vehicles which can serve this particular order. \\n\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"order_id\",\"vehicle_ids\"],\"title\":\"OrderVehicleMatch\"},\"ResponseModel\":{\"properties\":{\"response\":{\"anyOf\":[{\"properties\":{\"solver_response\":{\"allOf\":[{\"properties\":{\"status\":{\"type\":\"integer\",\"title\":\"Status\",\"description\":\"0 - Solution is available \\n1 - Infeasible solution is available \\n\",\"default\":0,\"examples\":[0],\"maximum\":0,\"minimum\":0},\"num_vehicles\":{\"type\":\"integer\",\"title\":\"Num Vehicles\",\"description\":\"Number of vehicle being used for the solution\",\"default\":-1,\"maximum\":2147483647,\"minimum\":0,\"examples\":[2]},\"solution_cost\":{\"type\":\"number\",\"title\":\"Solution Cost\",\"description\":\"Total cost of the solution\",\"default\":-1,\"examples\":[2]},\"vehicle_data\":{\"additionalProperties\":{\"properties\":{\"task_id\":{\"items\":{\"type\":\"string\"},\"type\":\"array\",\"title\":\"Task Id\",\"description\":\"task_ids being assigned to vehicle along with depot and breaks\",\"default\":[]},\"arrival_stamp\":{\"items\":{\"type\":\"number\"},\"type\":\"array\",\"title\":\"Arrival Stamp\",\"description\":\"arrival stamps at each task locations\",\"default\":[]},\"route\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\",\"title\":\"Route\",\"description\":\"Route indices as per waypoint graph or cost matrix provided\",\"default\":[]},\"type\":{\"items\":{\"type\":\"string\",\"enum\":[\"Depot\",\"Pickup\",\"Delivery\",\"Break\",\"w\"],\"title\":\"LocationTypeEnum\"},\"type\":\"array\",\"title\":\"Type\",\"description\":\"Type of routing point, whether it is Depot, Waypoint - w \\nDelivery, Break, Pickup \\n\",\"default\":[]}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"VehicleData\"},\"type\":\"object\",\"title\":\"Vehicle Data\",\"description\":\"All the details of vehicle routes and timestamps\",\"default\":{},\"examples\":[{\"vehicle_data\":{\"veh-1\":{\"arrival_stamp\":[1,2],\"route\":[1,1],\"task_id\":[\"Break\",\"Task-A\"],\"type\":[\"Break\",\"Delivery\"]},\"veh-2\":{\"arrival_stamp\":[2,2,4,5],\"route\":[0,0,2,0],\"task_id\":[\"Depot\",\"Break\",\"Task-B\",\"Depot\"],\"type\":[\"Depot\",\"Break\",\"Delivery\",\"Depot\"]}}}]},\"msg\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Msg\",\"description\":\"Any information pertaining to the run.\",\"default\":\"\"}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"FeasibleResultData\"}],\"description\":\"Feasible solution\",\"default\":{\"status\":0,\"num_vehicles\":-1,\"solution_cost\":-1,\"vehicle_data\":{},\"msg\":\"\"}},\"perf_times\":{\"anyOf\":[{\"type\":\"object\"},{\"type\":\"null\"}],\"title\":\"Perf Times\",\"description\":\"Etl and Solve times of the solve call\"}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"FeasibleSolve\"},{\"properties\":{\"solver_infeasible_response\":{\"allOf\":[{\"properties\":{\"status\":{\"type\":\"integer\",\"title\":\"Status\",\"description\":\"1 - Infeasible solution is available \\n\",\"default\":1,\"examples\":[1],\"maximum\":1,\"minimum\":1},\"num_vehicles\":{\"type\":\"integer\",\"title\":\"Num Vehicles\",\"description\":\"Number of vehicle being used for the solution\",\"default\":-1,\"examples\":[2],\"maximum\":2147483647,\"minimum\":0},\"solution_cost\":{\"type\":\"number\",\"title\":\"Solution Cost\",\"description\":\"Total cost of the solution\",\"default\":-1,\"examples\":[2]},\"vehicle_data\":{\"additionalProperties\":{\"properties\":{\"task_id\":{\"items\":{\"type\":\"string\"},\"type\":\"array\",\"title\":\"Task Id\",\"description\":\"task_ids being assigned to vehicle along with depot and breaks\",\"default\":[]},\"arrival_stamp\":{\"items\":{\"type\":\"number\"},\"type\":\"array\",\"title\":\"Arrival Stamp\",\"description\":\"arrival stamps at each task locations\",\"default\":[]},\"route\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\",\"title\":\"Route\",\"description\":\"Route indices as per waypoint graph or cost matrix provided\",\"default\":[]},\"type\":{\"items\":{\"type\":\"string\",\"enum\":[\"Depot\",\"Pickup\",\"Delivery\",\"Break\",\"w\"],\"title\":\"LocationTypeEnum\"},\"type\":\"array\",\"title\":\"Type\",\"description\":\"Type of routing point, whether it is Depot, Waypoint - w \\nDelivery, Break, Pickup \\n\",\"default\":[]}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"VehicleData\"},\"type\":\"object\",\"title\":\"Vehicle Data\",\"description\":\"All the details of vehicle routes and timestamps\",\"default\":{},\"examples\":[{\"vehicle_data\":{\"veh-1\":{\"arrival_stamp\":[1,2],\"route\":[1,1],\"task_id\":[\"Break\",\"Task-A\"],\"type\":[\"Break\",\"Delivery\"]},\"veh-2\":{\"arrival_stamp\":[2,2,4,5],\"route\":[0,0,2,0],\"task_id\":[\"Depot\",\"Break\",\"Task-B\",\"Depot\"],\"type\":[\"Depot\",\"Break\",\"Delivery\",\"Depot\"]}}}]},\"msg\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Msg\",\"description\":\"Any information pertaining to the run.\",\"default\":\"\"}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"InfeasibleResultData\"}],\"description\":\"Infeasible solution, this can mean the problem itself is infeasible or solver requires more time to find a solution. Setting default solve time is suggested in case you are not aware of the expected time.\",\"default\":{\"status\":1,\"num_vehicles\":-1,\"solution_cost\":-1,\"vehicle_data\":{},\"msg\":\"\"}},\"perf_times\":{\"anyOf\":[{\"type\":\"object\"},{\"type\":\"null\"}],\"title\":\"Perf Times\",\"description\":\"Etl and Solve times of the solve call\"}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"InFeasibleSolve\"}],\"title\":\"Response\",\"description\":\"Response\"},\"warnings\":{\"items\":{\"type\":\"string\"},\"type\":\"array\",\"title\":\"Warnings\",\"description\":\"List of warnings for users to handle issues\",\"default\":[]},\"notes\":{\"items\":{\"type\":\"string\"},\"type\":\"array\",\"title\":\"Notes\",\"description\":\"Any notes for users\",\"default\":[]}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"response\"],\"title\":\"ResponseModel\"},\"TaskData\":{\"properties\":{\"task_locations\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\",\"title\":\"Task Locations\",\"description\":\"dtype: int32, location \u003e= 0. \\n\\n Location where the task has been requested.\",\"examples\":[[1,2]]},\"task_ids\":{\"anyOf\":[{\"items\":{\"type\":\"string\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Task Ids\",\"description\":\"List of the task ids or names provided as a string.\",\"examples\":[[\"Task-A\",\"Task-B\"]]},\"demand\":{\"anyOf\":[{\"items\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Demand\",\"description\":\"dtype: int32 \\n\\n Note: For this release number of demand dimensions are limited to 3. \\n\\n Lists of demands of each tasks.\\nMultiple demands can be added and each list represents one kind of demand. Order of these demands should match the type of vehicle capacities provided.Example: In case of two sets of demands per vehicle with 3 vehicles, \\n\\n [ \\n\\n [dem_1_tsk_1, dem_1_tsk_2, dem_1_tsk_3], \\n\\n [dem_2_tsk_1, dem_2_tsk_2, dem_2_tsk_3] \\n\\n ]\",\"examples\":[[[1,1],[3,1]]]},\"pickup_and_delivery_pairs\":{\"anyOf\":[{\"items\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Pickup And Delivery Pairs\",\"description\":\"dtype: int32, pairs \u003e= 0. \\n\\n List of Pick-up and delivery index pairs from task locations.\\nIn case we have the following pick-up and delivery locations, 2-\u003e1, 4-\u003e5, 3-\u003e4, then task locations would look something like, task_locations = [0, 2, 1, 4, 5, 3, 4] and pick-up and delivery pairs would be index of those locations in task location and would look like [[1, 2], [3, 4], [5, 6]], 1 is pickup index for location 2 and it should be delivered to location 1 which is at index 2.Example schema: \\n\\n [ \\n\\n [pcikup_1_idx_to_task, drop_1_idx_to_task], \\n\\n [pcikup_2_idx_to_task, drop_2_idx_to_task], \\n\\n ]\",\"examples\":[null]},\"task_time_windows\":{\"anyOf\":[{\"items\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Task Time Windows\",\"description\":\"dtype: int32, time \u003e= 0. \\n\\n Earliest and Latest time windows for each tasks.\\nFor example the data would look as follows, \\n \\n\\n [ \\n\\n [tsk_1_earliest, tsk_1_latest], \\n\\n [tsk_2_earliest, tsk_2_latest] \\n\\n ]\",\"examples\":[[[0,5],[3,9]]]},\"service_times\":{\"anyOf\":[{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\"},{\"additionalProperties\":{\"items\":{\"type\":\"integer\"},\"type\":\"array\"},\"type\":\"object\"},{\"type\":\"null\"}],\"title\":\"Service Times\",\"description\":\"dtype: int32, time \u003e= 0. \\n\\n Service time for each task. Accepts a list of service times for all vehicles. In case of vehicle specific service times, accepts a dict with key as vehicle id and value as list of service times.Example schema: In case all vehicles have same service times, \\n\\n [tsk_1_srv_time, tsk_2_srv_time, tsk_3_srv_time] \\n\\n \\n\\n In case, there are 2 types of vehicle types and each of them have different service times, \\n\\n { \\n\\n type-1: [tsk_1_srv_time, tsk_3_srv_time, tsk_3_srv_time], \\n\\n type-2: [tsk_1_srv_time, tsk_3_srv_time, tsk_3_srv_time] \\n\\n }\",\"examples\":[[0,0]]},\"prizes\":{\"anyOf\":[{\"items\":{\"type\":\"number\",\"minimum\":0},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Prizes\",\"description\":\"dtype: float32, prizes \u003e= 0. \\n\\n List of values which signifies prizes that are collected for fulfilling each task. This can be used effectively in case solution is infeasible and need to drop few tasks to get feasible solution. Solver will prioritize for higher prize tasks \",\"examples\":[null]},\"order_vehicle_match\":{\"anyOf\":[{\"items\":{\"properties\":{\"order_id\":{\"type\":\"integer\",\"title\":\"Order Id\",\"description\":\"dtype: int32, order_id \u003e= 0. \\n\\n Indices of orders which can be served by this particular vehicleOrder id as an integer\",\"maximum\":2147483647,\"minimum\":0},\"vehicle_ids\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\",\"title\":\"Vehicle Ids\",\"description\":\"dtype: int32, vehicle_id \u003e= 0. \\n\\n Indices of the vehicles which can serve this particular order. \\n\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"order_id\",\"vehicle_ids\"],\"title\":\"OrderVehicleMatch\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Order Vehicle Match\",\"description\":\"A list of order vehicle match, where the match would contain a order id and a list of vehicle ids that can serve this order.\",\"examples\":[[{\"order_id\":0,\"vehicle_ids\":[0]},{\"order_id\":1,\"vehicle_ids\":[1]}]]},\"mandatory_task_ids\":{\"anyOf\":[{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Mandatory Task Ids\",\"description\":\"dtype: int32, mandatory_task_id \u003e= 0. \\n\\n Note: This is only effective when used along with drop infeasible option. \\n\\n A list of task ids which are mandatory and solver would fail if these cannot be fulfilled.\",\"examples\":[null]}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"task_locations\"],\"title\":\"TaskData\"},\"UpdateCostMatrices\":{\"properties\":{\"data\":{\"anyOf\":[{\"additionalProperties\":{\"items\":{\"items\":{\"type\":\"number\",\"minimum\":0},\"type\":\"array\"},\"type\":\"array\"},\"type\":\"object\"},{\"type\":\"null\"}],\"title\":\"Data\",\"description\":\"dtype : vehicle-type (uint8), cost (float32), cost \u003e= 0.\\n \\n\\n Sqaure matrix with cost to travel from A to B and B to A. \\nIf there different types of vehicles which have different \\ncost matrices, they can be provided with key value pair \\nwhere key is vehicle-type and value is cost matrix. Value of \\nvehicle type should be within [0, 255]\"},\"cost_matrix\":{\"anyOf\":[{\"additionalProperties\":{\"items\":{\"items\":{\"type\":\"number\",\"minimum\":0},\"type\":\"array\"},\"type\":\"array\"},\"type\":\"object\"},{\"type\":\"null\"}],\"title\":\"Cost Matrix\",\"description\":\"This field is deprecated, please use the 'data' field instead\",\"deprecated\":true}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"UpdateCostMatrices\"},\"UpdateSolverSettingsConfig\":{\"properties\":{\"time_limit\":{\"anyOf\":[{\"type\":\"number\",\"maximum\":2147483647,\"minimum\":0},{\"type\":\"null\"}],\"title\":\"Time Limit\",\"description\":\"SolverSettings time limit\",\"examples\":[1]},\"objectives\":{\"anyOf\":[{\"properties\":{\"cost\":{\"anyOf\":[{\"type\":\"number\"},{\"type\":\"null\"}],\"title\":\"Cost\",\"description\":\"dtype: float32. \\n\\n The weight assigned to minimizing the cost for a given solution, default value is 1\",\"examples\":[1]},\"travel_time\":{\"anyOf\":[{\"type\":\"number\"},{\"type\":\"null\"}],\"title\":\"Travel Time\",\"description\":\"dtype: float32. \\n\\n The weight assigned to minimizing total travel time for a given solution (includes drive, service and wait time)\",\"examples\":[0]},\"variance_route_size\":{\"anyOf\":[{\"type\":\"number\"},{\"type\":\"null\"}],\"title\":\"Variance Route Size\",\"description\":\"dtype: float32. \\n\\n The weight assigned to the variance in the number of orders served by each route.\",\"examples\":[0]},\"variance_route_service_time\":{\"anyOf\":[{\"type\":\"number\"},{\"type\":\"null\"}],\"title\":\"Variance Route Service Time\",\"description\":\"dtype: float32. \\n\\n The weight assigned to the variance in the accumulated service times of each route\",\"examples\":[0]},\"prize\":{\"anyOf\":[{\"type\":\"number\"},{\"type\":\"null\"}],\"title\":\"Prize\",\"description\":\"dtype: float32. \\n\\n The weight assigned to the prize in accumulated prizes for each job fulfilled.This will be negated from overall values accumulated with other objectives.For example, if cost accumulated is 10 and objective value for it is 1, and if the prize accumulated is 3 and objective is 2, then total cost would look something like this 10 x 1 - 3 x 2 = 4.\",\"examples\":[0]},\"vehicle_fixed_cost\":{\"anyOf\":[{\"type\":\"number\"},{\"type\":\"null\"}],\"title\":\"Vehicle Fixed Cost\",\"description\":\"dtype: float32. \\n\\n The weight assigned to the accumulated fixed costs of each vehicle used in solution\",\"examples\":[0]}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"Objective\"},{\"type\":\"null\"}],\"description\":\"Values provided dictate the linear combination of factors used to evaluate solution quality.Only prize will be negated, all others gets accumulated. That's why sometime you might come across negative value as solution cost.\"},\"config_file\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Config File\",\"description\":\"Dump configuration information in a given file as yaml\",\"examples\":[null]},\"verbose_mode\":{\"anyOf\":[{\"type\":\"boolean\"},{\"type\":\"null\"}],\"title\":\"Verbose Mode\",\"description\":\"Displaying internal information during the solver execution.\",\"default\":false},\"error_logging\":{\"anyOf\":[{\"type\":\"boolean\"},{\"type\":\"null\"}],\"title\":\"Error Logging\",\"description\":\"Displaying constraint error information during the solver execution.\",\"default\":true}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"UpdateSolverSettingsConfig\"},\"UpdateWaypointGraphData\":{\"properties\":{\"waypoint_graph\":{\"anyOf\":[{\"additionalProperties\":{\"properties\":{\"edges\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\",\"title\":\"Edges\",\"description\":\"dtype: int32, edge \u003e= 0. \\n\\n Vertices of all the directed edges.\"},\"offsets\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\",\"title\":\"Offsets\",\"description\":\"dtype: int32, offset \u003e= 0. \\n\\n Offsets which provide number of edges from the source vertex signified by the index.\"},\"weights\":{\"anyOf\":[{\"items\":{\"type\":\"number\",\"minimum\":0},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Weights\",\"description\":\"dtype: float32, weight \u003e= 0. \\n\\n Weights of each edges.\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"edges\",\"offsets\"],\"title\":\"WaypointGraph\"},\"type\":\"object\"},{\"type\":\"null\"}],\"title\":\"Waypoint Graph\"}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"UpdateWaypointGraphData\"},\"VehicleData\":{\"properties\":{\"task_id\":{\"items\":{\"type\":\"string\"},\"type\":\"array\",\"title\":\"Task Id\",\"description\":\"task_ids being assigned to vehicle along with depot and breaks\",\"default\":[]},\"arrival_stamp\":{\"items\":{\"type\":\"number\"},\"type\":\"array\",\"title\":\"Arrival Stamp\",\"description\":\"arrival stamps at each task locations\",\"default\":[]},\"route\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\",\"title\":\"Route\",\"description\":\"Route indices as per waypoint graph or cost matrix provided\",\"default\":[]},\"type\":{\"items\":{\"type\":\"string\",\"enum\":[\"Depot\",\"Pickup\",\"Delivery\",\"Break\",\"w\"],\"title\":\"LocationTypeEnum\"},\"type\":\"array\",\"title\":\"Type\",\"description\":\"Type of routing point, whether it is Depot, Waypoint - w \\nDelivery, Break, Pickup \\n\",\"default\":[]}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"VehicleData\"},\"VehicleOrderMatch\":{\"properties\":{\"vehicle_id\":{\"type\":\"integer\",\"title\":\"Vehicle Id\",\"description\":\"dtype: int32, vehicle_id \u003e= 0. \\n\\n Vehicle id as an integer, and can serve all the order listed in order_ids.\",\"maximum\":2147483647,\"minimum\":0},\"order_ids\":{\"items\":{\"type\":\"integer\"},\"type\":\"array\",\"title\":\"Order Ids\",\"description\":\"dtype: int32, order_id \u003e= 0. \\n\\n Indices of orders which can be served by this particular vehicle\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"vehicle_id\",\"order_ids\"],\"title\":\"VehicleOrderMatch\"},\"WaypointGraph\":{\"properties\":{\"edges\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\",\"title\":\"Edges\",\"description\":\"dtype: int32, edge \u003e= 0. \\n\\n Vertices of all the directed edges.\"},\"offsets\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\",\"title\":\"Offsets\",\"description\":\"dtype: int32, offset \u003e= 0. \\n\\n Offsets which provide number of edges from the source vertex signified by the index.\"},\"weights\":{\"anyOf\":[{\"items\":{\"type\":\"number\",\"minimum\":0},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Weights\",\"description\":\"dtype: float32, weight \u003e= 0. \\n\\n Weights of each edges.\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"edges\",\"offsets\"],\"title\":\"WaypointGraph\"},\"cuoptData\":{\"properties\":{\"action\":{\"anyOf\":[{\"type\":\"string\",\"enum\":[\"cuOpt_OptimizedRouting\",\"cuOpt_RoutingValidator\",0]},{\"type\":\"null\"}],\"title\":\"Action\",\"description\":\"Action to be performed by the service, validator action just validates input against format and base rules.\",\"default\":\"cuOpt_OptimizedRouting\"},\"data\":{\"anyOf\":[{\"properties\":{\"cost_waypoint_graph_data\":{\"anyOf\":[{\"properties\":{\"waypoint_graph\":{\"anyOf\":[{\"additionalProperties\":{\"properties\":{\"edges\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\",\"title\":\"Edges\",\"description\":\"dtype: int32, edge \u003e= 0. \\n\\n Vertices of all the directed edges.\"},\"offsets\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\",\"title\":\"Offsets\",\"description\":\"dtype: int32, offset \u003e= 0. \\n\\n Offsets which provide number of edges from the source vertex signified by the index.\"},\"weights\":{\"anyOf\":[{\"items\":{\"type\":\"number\",\"minimum\":0},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Weights\",\"description\":\"dtype: float32, weight \u003e= 0. \\n\\n Weights of each edges.\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"edges\",\"offsets\"],\"title\":\"WaypointGraph\"},\"type\":\"object\"},{\"type\":\"null\"}],\"title\":\"Waypoint Graph\"}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"UpdateWaypointGraphData\"},{\"type\":\"null\"}],\"description\":\"Waypoint graph with weights as cost to travel from A to B \\nand B to A. If there are different types of vehicles \\nthey can be provided with key value pair \\nwhere key is vehicle-type and value is the graph. Value of \\nvehicle type should be within [0, 255]\",\"default\":{},\"examples\":[null]},\"travel_time_waypoint_graph_data\":{\"anyOf\":[{\"properties\":{\"waypoint_graph\":{\"anyOf\":[{\"additionalProperties\":{\"properties\":{\"edges\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\",\"title\":\"Edges\",\"description\":\"dtype: int32, edge \u003e= 0. \\n\\n Vertices of all the directed edges.\"},\"offsets\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\",\"title\":\"Offsets\",\"description\":\"dtype: int32, offset \u003e= 0. \\n\\n Offsets which provide number of edges from the source vertex signified by the index.\"},\"weights\":{\"anyOf\":[{\"items\":{\"type\":\"number\",\"minimum\":0},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Weights\",\"description\":\"dtype: float32, weight \u003e= 0. \\n\\n Weights of each edges.\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"edges\",\"offsets\"],\"title\":\"WaypointGraph\"},\"type\":\"object\"},{\"type\":\"null\"}],\"title\":\"Waypoint Graph\"}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"UpdateWaypointGraphData\"},{\"type\":\"null\"}],\"description\":\"Waypoint graph with weights as time to travel from A to B \\nand B to A. If there are different types of vehicles \\nthey can be provided with key value pair \\nwhere key is vehicle-type and value is the graph. Value of \\nvehicle type should be within [0, 255]\",\"default\":{},\"examples\":[null]},\"cost_matrix_data\":{\"anyOf\":[{\"properties\":{\"data\":{\"anyOf\":[{\"additionalProperties\":{\"items\":{\"items\":{\"type\":\"number\",\"minimum\":0},\"type\":\"array\"},\"type\":\"array\"},\"type\":\"object\"},{\"type\":\"null\"}],\"title\":\"Data\",\"description\":\"dtype : vehicle-type (uint8), cost (float32), cost \u003e= 0.\\n \\n\\n Sqaure matrix with cost to travel from A to B and B to A. \\nIf there different types of vehicles which have different \\ncost matrices, they can be provided with key value pair \\nwhere key is vehicle-type and value is cost matrix. Value of \\nvehicle type should be within [0, 255]\"},\"cost_matrix\":{\"anyOf\":[{\"additionalProperties\":{\"items\":{\"items\":{\"type\":\"number\",\"minimum\":0},\"type\":\"array\"},\"type\":\"array\"},\"type\":\"object\"},{\"type\":\"null\"}],\"title\":\"Cost Matrix\",\"description\":\"This field is deprecated, please use the 'data' field instead\",\"deprecated\":true}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"UpdateCostMatrices\"},{\"type\":\"null\"}],\"description\":\"Sqaure matrix with cost to travel from A to B and B to A. \\nIf there are different types of vehicles which have different \\ncost matrices, they can be provided with key value pair \\nwhere key is vehicle-type and value is cost matrix. Value of \\nvehicle type should be within [0, 255]\",\"default\":{},\"examples\":[{\"cost_matrix\":{\"1\":[[0,1,1],[1,0,1],[1,1,0]],\"2\":[[0,1,1],[1,0,1],[1,2,0]]}}]},\"travel_time_matrix_data\":{\"anyOf\":[{\"properties\":{\"data\":{\"anyOf\":[{\"additionalProperties\":{\"items\":{\"items\":{\"type\":\"number\",\"minimum\":0},\"type\":\"array\"},\"type\":\"array\"},\"type\":\"object\"},{\"type\":\"null\"}],\"title\":\"Data\",\"description\":\"dtype : vehicle-type (uint8), cost (float32), cost \u003e= 0.\\n \\n\\n Sqaure matrix with cost to travel from A to B and B to A. \\nIf there different types of vehicles which have different \\ncost matrices, they can be provided with key value pair \\nwhere key is vehicle-type and value is cost matrix. Value of \\nvehicle type should be within [0, 255]\"},\"cost_matrix\":{\"anyOf\":[{\"additionalProperties\":{\"items\":{\"items\":{\"type\":\"number\",\"minimum\":0},\"type\":\"array\"},\"type\":\"array\"},\"type\":\"object\"},{\"type\":\"null\"}],\"title\":\"Cost Matrix\",\"description\":\"This field is deprecated, please use the 'data' field instead\",\"deprecated\":true}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"UpdateCostMatrices\"},{\"type\":\"null\"}],\"description\":\"Sqaure matrix with time to travel from A to B and B to A. \\nIf there are different types of vehicles which have different \\ntravel time matrices, they can be provided with key value pair \\nwhere key is vehicle-type and value is time matrix. Value of \\nvehicle type should be within [0, 255]\",\"default\":{},\"examples\":[{\"cost_matrix\":{\"1\":[[0,1,1],[1,0,1],[1,1,0]],\"2\":[[0,1,1],[1,0,1],[1,2,0]]}}]},\"fleet_data\":{\"allOf\":[{\"properties\":{\"vehicle_locations\":{\"items\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\"},\"type\":\"array\",\"title\":\"Vehicle Locations\",\"description\":\"dtype: int32, vehicle_location \u003e= 0. \\n\\n Start and end location of the vehicles in the given set of locations in WayPointGraph or CostMatrices.\\nExample: For 2 vehicles, \\n\\n [ \\n\\n [veh_1_start_loc, veh_1_end_loc], \\n\\n [veh_2_start_loc, veh_2_end_loc] \\n\\n ]\",\"examples\":[[[0,0],[0,0]]]},\"vehicle_ids\":{\"anyOf\":[{\"items\":{\"type\":\"string\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Vehicle Ids\",\"description\":\"List of the vehicle ids or names provided as a string.\",\"examples\":[[\"veh-1\",\"veh-2\"]]},\"capacities\":{\"anyOf\":[{\"items\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Capacities\",\"description\":\"dtype: int32, capacity \u003e= 0. \\n\\n Note: For this release number of capacity dimensions are limited to 3. \\n\\n Lists of capacities of each vehicle.\\nMultiple capacities can be added and each list will represent one kind of capacity. Order of kind of the capacities should match order of the demands.\\nTotal capacity for each type should be sufficient to complete all demand of that type.Example: In case of two sets of capacities per vehicle with 3 vehicles, \\n\\n [ \\n\\n [cap_1_veh_1, cap_1_veh_2, cap_1_veh_3], \\n\\n [cap_2_veh_1, cap_2_veh_2, cap_2_veh_3] \\n\\n ]\",\"examples\":[[[2,2],[4,1]]]},\"vehicle_time_windows\":{\"anyOf\":[{\"items\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Vehicle Time Windows\",\"description\":\"dtype: int32, time \u003e= 0. \\n\\n Earliest and Latest time window pairs for each vehicle,\\nfor example the data would look as follows for 2 vehicles, \\n \\n\\n [ \\n\\n [veh_1_earliest, veh_1_latest], \\n\\n [veh_2_earliest, veh_2_latest] \\n\\n ]\",\"examples\":[[[0,10],[0,10]]]},\"vehicle_break_time_windows\":{\"anyOf\":[{\"items\":{\"items\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\"},\"type\":\"array\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Vehicle Break Time Windows\",\"description\":\"dtype: int32, time \u003e= 0. \\n\\n Multiple break time windows can be added for each vehicle.Earliest and Latest break time window pairs for each vehicle,\\nFor example, in case of 2 sets of breaks for each vehicle which translates to 2 dimensions of breaks,\\n \\n\\n [ \\n\\n [[brk_1_veh_1_earliest, brk_1_veh_1_latest], [brk_1_veh_2_earliest, brk_1_veh_2_latest]] \\n\\n [[brk_2_veh_1_earliest, brk_2_veh_1_latest], [brk_2_veh_2_earliest, brk_2_veh_2_latest]] \\n\\n ] \\n\\n The break duration within this time window is provided through vehicle_break_durations.\",\"examples\":[[[[1,2],[2,3]]]]},\"vehicle_break_durations\":{\"anyOf\":[{\"items\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Vehicle Break Durations\",\"description\":\"dtype: int32, time \u003e= 0. \\n\\n Break duration for each vehicle. vehicle_break_time_windows should be provided to use this option.For example, in case of having 2 breaks for each vehicle, \\n\\n [ \\n\\n [brk_1_veh_1_duration, brk_1_veh_2_duration], \\n\\n [brk_2_veh_1_duration, brk_2_veh_2_duration], \\n\\n ]\",\"examples\":[[[1,1]]]},\"vehicle_break_locations\":{\"anyOf\":[{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Vehicle Break Locations\",\"description\":\"dtype: int32, location \u003e= 0. \\n\\n Break location where vehicles can take breaks. If not set, any location can be used for the break.\",\"examples\":[[0,1]]},\"vehicle_types\":{\"anyOf\":[{\"items\":{\"type\":\"integer\",\"maximum\":255,\"minimum\":0},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Vehicle Types\",\"description\":\"dtype: uint8. \\n\\n Types of vehicles in the fleet given as positive integers.\",\"examples\":[[1,2]]},\"vehicle_order_match\":{\"anyOf\":[{\"items\":{\"properties\":{\"vehicle_id\":{\"type\":\"integer\",\"title\":\"Vehicle Id\",\"description\":\"dtype: int32, vehicle_id \u003e= 0. \\n\\n Vehicle id as an integer, and can serve all the order listed in order_ids.\",\"maximum\":2147483647,\"minimum\":0},\"order_ids\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\",\"title\":\"Order Ids\",\"description\":\"dtype: int32, order_id \u003e= 0. \\n\\n Indices of orders which can be served by this particular vehicle\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"vehicle_id\",\"order_ids\"],\"title\":\"VehicleOrderMatch\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Vehicle Order Match\",\"description\":\"A list of vehicle order match, where the match would contain a vehicle id and a list of orders that vehicle can serve.\",\"examples\":[[{\"order_ids\":[0],\"vehicle_id\":0},{\"order_ids\":[1],\"vehicle_id\":1}]]},\"skip_first_trips\":{\"anyOf\":[{\"items\":{\"type\":\"boolean\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Skip First Trips\",\"description\":\"Drop the cost of trip to first location for that vehicle.\",\"examples\":[[true,false]]},\"drop_return_trips\":{\"anyOf\":[{\"items\":{\"type\":\"boolean\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Drop Return Trips\",\"description\":\"Drop cost of return trip for each vehicle.\",\"examples\":[[true,false]]},\"min_vehicles\":{\"anyOf\":[{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},{\"type\":\"null\"}],\"title\":\"Min Vehicles\",\"description\":\"dtype: int32, min_vehicles \u003e= 1. \\n\\n Solution should consider minimum number of vehicles\",\"examples\":[2]},\"vehicle_max_costs\":{\"anyOf\":[{\"items\":{\"type\":\"number\",\"minimum\":0},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Vehicle Max Costs\",\"description\":\"dtype: float32, max_costs \u003e= 0. \\n\\n Maximum cost a vehicle can incur and it is based on cost matrix/cost waypoint graph.\",\"examples\":[[7,10]]},\"vehicle_max_times\":{\"anyOf\":[{\"items\":{\"type\":\"number\",\"minimum\":0},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Vehicle Max Times\",\"description\":\"dtype: float32, max_time \u003e= 0. \\n\\n Maximum time a vehicle can operate (includes drive, service and wait time), this is based on travel time matrix/travel time waypoint graph.\",\"examples\":[[7,10]]},\"vehicle_fixed_costs\":{\"anyOf\":[{\"items\":{\"type\":\"number\",\"minimum\":0},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Vehicle Fixed Costs\",\"description\":\"dtype: float32, fixed_cost \u003e= 0. \\n\\n Cost of each vehicle.This helps in routing where may be 2 vehicles with less cost is effective compared to 1 vehicle with huge cost. As example shows veh-0 (15) \u003e veh-1 (5) + veh-2 (5)\",\"examples\":[[15,5]]}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"vehicle_locations\"],\"title\":\"FleetData\"}],\"description\":\"All Fleet information\"},\"task_data\":{\"allOf\":[{\"properties\":{\"task_locations\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\",\"title\":\"Task Locations\",\"description\":\"dtype: int32, location \u003e= 0. \\n\\n Location where the task has been requested.\",\"examples\":[[1,2]]},\"task_ids\":{\"anyOf\":[{\"items\":{\"type\":\"string\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Task Ids\",\"description\":\"List of the task ids or names provided as a string.\",\"examples\":[[\"Task-A\",\"Task-B\"]]},\"demand\":{\"anyOf\":[{\"items\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Demand\",\"description\":\"dtype: int32 \\n\\n Note: For this release number of demand dimensions are limited to 3. \\n\\n Lists of demands of each tasks.\\nMultiple demands can be added and each list represents one kind of demand. Order of these demands should match the type of vehicle capacities provided.Example: In case of two sets of demands per vehicle with 3 vehicles, \\n\\n [ \\n\\n [dem_1_tsk_1, dem_1_tsk_2, dem_1_tsk_3], \\n\\n [dem_2_tsk_1, dem_2_tsk_2, dem_2_tsk_3] \\n\\n ]\",\"examples\":[[[1,1],[3,1]]]},\"pickup_and_delivery_pairs\":{\"anyOf\":[{\"items\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Pickup And Delivery Pairs\",\"description\":\"dtype: int32, pairs \u003e= 0. \\n\\n List of Pick-up and delivery index pairs from task locations.\\nIn case we have the following pick-up and delivery locations, 2-\u003e1, 4-\u003e5, 3-\u003e4, then task locations would look something like, task_locations = [0, 2, 1, 4, 5, 3, 4] and pick-up and delivery pairs would be index of those locations in task location and would look like [[1, 2], [3, 4], [5, 6]], 1 is pickup index for location 2 and it should be delivered to location 1 which is at index 2.Example schema: \\n\\n [ \\n\\n [pcikup_1_idx_to_task, drop_1_idx_to_task], \\n\\n [pcikup_2_idx_to_task, drop_2_idx_to_task], \\n\\n ]\",\"examples\":[null]},\"task_time_windows\":{\"anyOf\":[{\"items\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Task Time Windows\",\"description\":\"dtype: int32, time \u003e= 0. \\n\\n Earliest and Latest time windows for each tasks.\\nFor example the data would look as follows, \\n \\n\\n [ \\n\\n [tsk_1_earliest, tsk_1_latest], \\n\\n [tsk_2_earliest, tsk_2_latest] \\n\\n ]\",\"examples\":[[[0,5],[3,9]]]},\"service_times\":{\"anyOf\":[{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\"},{\"additionalProperties\":{\"items\":{\"type\":\"integer\"},\"type\":\"array\"},\"type\":\"object\"},{\"type\":\"null\"}],\"title\":\"Service Times\",\"description\":\"dtype: int32, time \u003e= 0. \\n\\n Service time for each task. Accepts a list of service times for all vehicles. In case of vehicle specific service times, accepts a dict with key as vehicle id and value as list of service times.Example schema: In case all vehicles have same service times, \\n\\n [tsk_1_srv_time, tsk_2_srv_time, tsk_3_srv_time] \\n\\n \\n\\n In case, there are 2 types of vehicle types and each of them have different service times, \\n\\n { \\n\\n type-1: [tsk_1_srv_time, tsk_3_srv_time, tsk_3_srv_time], \\n\\n type-2: [tsk_1_srv_time, tsk_3_srv_time, tsk_3_srv_time] \\n\\n }\",\"examples\":[[0,0]]},\"prizes\":{\"anyOf\":[{\"items\":{\"type\":\"number\",\"minimum\":0},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Prizes\",\"description\":\"dtype: float32, prizes \u003e= 0. \\n\\n List of values which signifies prizes that are collected for fulfilling each task. This can be used effectively in case solution is infeasible and need to drop few tasks to get feasible solution. Solver will prioritize for higher prize tasks \",\"examples\":[null]},\"order_vehicle_match\":{\"anyOf\":[{\"items\":{\"properties\":{\"order_id\":{\"type\":\"integer\",\"title\":\"Order Id\",\"description\":\"dtype: int32, order_id \u003e= 0. \\n\\n Indices of orders which can be served by this particular vehicleOrder id as an integer\",\"maximum\":2147483647,\"minimum\":0},\"vehicle_ids\":{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\",\"title\":\"Vehicle Ids\",\"description\":\"dtype: int32, vehicle_id \u003e= 0. \\n\\n Indices of the vehicles which can serve this particular order. \\n\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"order_id\",\"vehicle_ids\"],\"title\":\"OrderVehicleMatch\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Order Vehicle Match\",\"description\":\"A list of order vehicle match, where the match would contain a order id and a list of vehicle ids that can serve this order.\",\"examples\":[[{\"order_id\":0,\"vehicle_ids\":[0]},{\"order_id\":1,\"vehicle_ids\":[1]}]]},\"mandatory_task_ids\":{\"anyOf\":[{\"items\":{\"type\":\"integer\",\"maximum\":2147483647,\"minimum\":0},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Mandatory Task Ids\",\"description\":\"dtype: int32, mandatory_task_id \u003e= 0. \\n\\n Note: This is only effective when used along with drop infeasible option. \\n\\n A list of task ids which are mandatory and solver would fail if these cannot be fulfilled.\",\"examples\":[null]}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"task_locations\"],\"title\":\"TaskData\"}],\"description\":\"All Task information\"},\"solver_config\":{\"anyOf\":[{\"properties\":{\"time_limit\":{\"anyOf\":[{\"type\":\"number\",\"maximum\":2147483647,\"minimum\":0},{\"type\":\"null\"}],\"title\":\"Time Limit\",\"description\":\"SolverSettings time limit\",\"examples\":[1]},\"objectives\":{\"anyOf\":[{\"properties\":{\"cost\":{\"anyOf\":[{\"type\":\"number\"},{\"type\":\"null\"}],\"title\":\"Cost\",\"description\":\"dtype: float32. \\n\\n The weight assigned to minimizing the cost for a given solution, default value is 1\",\"examples\":[1]},\"travel_time\":{\"anyOf\":[{\"type\":\"number\"},{\"type\":\"null\"}],\"title\":\"Travel Time\",\"description\":\"dtype: float32. \\n\\n The weight assigned to minimizing total travel time for a given solution (includes drive, service and wait time)\",\"examples\":[0]},\"variance_route_size\":{\"anyOf\":[{\"type\":\"number\"},{\"type\":\"null\"}],\"title\":\"Variance Route Size\",\"description\":\"dtype: float32. \\n\\n The weight assigned to the variance in the number of orders served by each route.\",\"examples\":[0]},\"variance_route_service_time\":{\"anyOf\":[{\"type\":\"number\"},{\"type\":\"null\"}],\"title\":\"Variance Route Service Time\",\"description\":\"dtype: float32. \\n\\n The weight assigned to the variance in the accumulated service times of each route\",\"examples\":[0]},\"prize\":{\"anyOf\":[{\"type\":\"number\"},{\"type\":\"null\"}],\"title\":\"Prize\",\"description\":\"dtype: float32. \\n\\n The weight assigned to the prize in accumulated prizes for each job fulfilled.This will be negated from overall values accumulated with other objectives.For example, if cost accumulated is 10 and objective value for it is 1, and if the prize accumulated is 3 and objective is 2, then total cost would look something like this 10 x 1 - 3 x 2 = 4.\",\"examples\":[0]},\"vehicle_fixed_cost\":{\"anyOf\":[{\"type\":\"number\"},{\"type\":\"null\"}],\"title\":\"Vehicle Fixed Cost\",\"description\":\"dtype: float32. \\n\\n The weight assigned to the accumulated fixed costs of each vehicle used in solution\",\"examples\":[0]}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"Objective\"},{\"type\":\"null\"}],\"description\":\"Values provided dictate the linear combination of factors used to evaluate solution quality.Only prize will be negated, all others gets accumulated. That's why sometime you might come across negative value as solution cost.\"},\"config_file\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Config File\",\"description\":\"Dump configuration information in a given file as yaml\",\"examples\":[null]},\"verbose_mode\":{\"anyOf\":[{\"type\":\"boolean\"},{\"type\":\"null\"}],\"title\":\"Verbose Mode\",\"description\":\"Displaying internal information during the solver execution.\",\"default\":false},\"error_logging\":{\"anyOf\":[{\"type\":\"boolean\"},{\"type\":\"null\"}],\"title\":\"Error Logging\",\"description\":\"Displaying constraint error information during the solver execution.\",\"default\":true}},\"additionalProperties\":false,\"type\":\"object\",\"title\":\"UpdateSolverSettingsConfig\"},{\"type\":\"null\"}]}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"fleet_data\",\"task_data\"],\"title\":\"OptimizedRoutingData\"},{\"type\":\"null\"}],\"title\":\"Data\",\"description\":\"The data that needs to be processed by the service. For detailed explanations of each field, please consult the following link: \u003ca href=\\\"https://docs.nvidia.com/cuopt/service/latest/data-requirements.html\\\"\u003edata requirements\u003c/a\u003e . To ensure best practices, please refer to: \u003ca href=\\\"https://docs.nvidia.com/cuopt/service/latest/best-practices.html\\\"\u003ebest practices\u003c/a\u003e. For examples, you can find them at: \u003ca href=\\\"https://github.com/NVIDIA/cuOpt-Resources/tree/branch-23.10/notebooks/routing/service\\\"\u003enotebooks\u003c/a\u003e. If the size of the data exceeds 250KB, please utilize the large assets API to upload it to s3. In such cases, set the data as null and include the header NVCF-INPUT-ASSET-REFERENCES: $ASSET_ID in the POST request.\"},\"parameters\":{\"anyOf\":[{\"type\":\"object\"},{\"type\":\"null\"}],\"title\":\"Parameters\",\"description\":\"unused/ignored but retained for compatibility\"},\"client_version\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Client Version\",\"description\":\"cuOpt client version. Set to 'custom' to skip version check.\",\"default\":\"\"}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"data\"],\"title\":\"cuoptData\"}}}},\"namespace\":\"qc69jvmznzxy\",\"updatedDate\":\"2024-11-18T22:01:43.669Z\",\"nvcfFunctionId\":\"b0ac1378-3d00-43cb-a8d9-0f0c37ef36c0\",\"createdDate\":\"2024-03-15T04:08:53.884Z\",\"attributes\":{\"showUnavailableBanner\":false,\"apiDocsUrl\":\"https://docs.api.nvidia.com/nim/reference/nvidia-cuopt\",\"termsOfUse\":\"\u003cb\u003eGOVERNING TERMS\u003c/b\u003e: Your use of this API is governed by the \u003ca href=\\\"https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA API Trial Service Terms of Use\u003c/a\u003e.\\n\",\"dockerRun\":\"$c2\",\"dockerTermsOfUse\":\"By running the below commands, you accept the \u003ca href=\\\"https://www.nvidia.com/en-us/data-center/products/nvidia-ai-enterprise/eula/\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA AI Enterprise Terms of Use\u003c/a\u003e and the \u003ca href=\\\"https://docs.nvidia.com/ai-foundation-models-community-license.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA Community Models License\u003c/a\u003e.\\n\",\"cta\":{\"text\":\"Self-Host this API\",\"url\":\"https://enterpriseproductregistration.nvidia.com/?LicType=EVAL\u0026ProductFamily=NVAIEnterprise\",\"nim_available_override_url\":\"https://catalog.ngc.nvidia.com/orgs/nvidia/teams/cuopt/containers/cuopt\"}},\"artifactName\":\"nvidia-cuopt\"},\"config\":{\"name\":\"nvidia-cuopt\",\"type\":\"model\"}}]}]\n"])</script><script>self.__next_f.push([1,"c3:Tf30,"])</script><script>self.__next_f.push([1,"## Model Overview\n\n### Description:\n\nShutterstock 3D Generation powered by NVIDIA Edify generates 3D meshes and associated 2D PBR textures from text prompt or optional reference image. This model is for commercial use. \u003cbr\u003e\n\n### References:\n\nThis model is based on large-scale diffusion models.\n\n[1] Balaji, Y., Nah, S., Huang, X., Vahdat, A., Song, J., Kreis, K., Aittala, M., Aila, T., Laine, S.,\nCatanzaro, B. and Karras, T., 2022. ediffi: Text-to-image diffusion models with an ensemble of\nexpert denoisers. arXiv preprint arXiv:2211.01324.\n\n[2] Saharia, C., Chan, W., Saxena, S., Li, L., Whang, J., Denton, E.L., Ghasemipour, K., Gontijo\nLopes, R., Karagol Ayan, B., Salimans, T. and Ho, J., 2022. Photorealistic text-to-image\ndiffusion models with deep language understanding. Advances in Neural Information Processing\nSystems, 35, pp.36479-36494.\n\n[3] Ramesh, A., Dhariwal, P., Nichol, A., Chu, C. and Chen, M., 2022. Hierarchical\ntext-conditional image generation with clip latents. arXiv preprint arXiv:2204.06125, 1(2), p.3.\n\n[4] Lin, C-H, Gao, J., Tang, L, Takikawa, T., Zeng, X., Huang, X., Kreis, K., Fidler, S., Liu, M-Y\nand Lin, T-Y, Magic3D: High-Resolution Text-to-3D Content Creation. CVPR 2023.\n\n### Model Architecture:\n\n**Architecture Type:** Convolution Neural Network (CNN) and Transformer \u003cbr\u003e\n**Network Architecture:** Unet-Based CNN and Transformer \u003cbr\u003e\nThis model is based on diffusion architecture and Transformer architecture.\n\n### Input:\n\n**Input Type(s):** Text (Prompt), Image (Optional) \u003cbr\u003e\n**Input Format(s):** Text: Raw and Image: Red, Green, Blue (RGB) \u003cbr\u003e\n**Input Parameters:** Text: One-Dimensional (1D) and Image: Two-Dimensional (2D, optional)\n\n**Other Properties Related to Input:** Max 500 text tokens. No input minimum or maximum\nresolution; input images segmented and resized to 224 x 224 \u003cbr\u003e\n\n### Output:\n\n**Output Type(s):** Mesh \u003cbr\u003e\n**Output Format:** Three-Dimensional (3D) with Texture Map (2D) \u003cbr\u003e\n**Other Properties Related to Output:** Output Target Faces (Configurable)- [500, 200000]; Texture Resolution: {'1k', '2k', ‘4k’}\n\n### Software Integration:\n\n**Supported Hardware Microarchitecture Compatibility:** \u003cbr\u003e\n* NVIDIA Ampere \u003cbr\u003e\n **[Preferred/Supported] Operating System(s):** \u003cbr\u003e\n* Linux \u003cbr\u003e\n\n### Model Version(s):\n\nEdify 3D v1.0 \u003cbr\u003e\n\n## Training \u0026 Evaluation:\n\n### Training Dataset:\n\n**Link:** Shutterstock Images, TurboSquid 3D Models \u003cbr\u003e\n** Data Collection Method by dataset \u003cbr\u003e\n* Customer data \u003cbr\u003e\n ** Labeling Method by dataset \u003cbr\u003e\n* Automated \u003cbr\u003e\n **Properties (Quantity, Dataset Descriptions, Sensor(s)):** 600 million image-text pairs of\n licensed high quality photography, illustrations, and 3D renderings. 270 thousand 3D meshes. 228k PixelSquid 3D models rendered in multi-view images.\n from TurboSquid.\u003cbr\u003e\n\n### Evaluation Dataset:\n\n** Data Collection Method by dataset \u003cbr\u003e\n* Customer data \u003cbr\u003e\n **Properties (Quantity, Dataset Descriptions, Sensor(s)):** Data contains: 600 million image-text\n pairs of licensed high quality photography, illustrations, and 3D renderings. 270 thousand 3D\n meshes from TurboSquid. 228k PixelSquid 3D models rendered in multi-view images.\u003cbr\u003e\n\n### Inference:\n\n**Engine:** Tensor(RT), Triton \u003cbr\u003e\n**Test Hardware:** \u003cbr\u003e\n* NVIDIA H100 \u003cbr\u003e\n\n### Ethical Considerations:\n\nNVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and\npractices to enable development for a wide array of AI applications. When downloaded or used\nin accordance with our terms of service, developers should work with their internal model team\nto ensure this model meets requirements for the relevant industry and use case and addresses\nunforeseen product misuse. Please report security vulnerabilities or NVIDIA AI Concerns\n[here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/).\n\n### Contact:\n\nhttps://www.shutterstock.com/help\n"])</script><script>self.__next_f.push([1,"22:[\"$\",\"$L3c\",null,{\"data\":[{\"endpoint\":{\"requestStatus\":{\"statusCode\":\"SUCCESS\",\"requestId\":\"52e09f0f-b723-475c-9e02-4d0197c53ff2\"},\"artifact\":{\"orgName\":\"qc69jvmznzxy\",\"labels\":[\"Image-to-3D\",\"Text-to-3D\"],\"bias\":\"\",\"logo\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/edify-3d.jpg\",\"shortDescription\":\"Shutterstock Generative 3D service for 3D asset generation. Trained on NVIDIA Edify using Shutterstock’s licensed creative libraries\",\"safetyAndSecurity\":\"\",\"privacy\":\"\",\"isReadOnly\":true,\"description\":\"$c3\",\"canGuestDownload\":true,\"isPublic\":true,\"createdDate\":\"2024-07-29T19:04:54.041Z\",\"publisher\":\"Shutterstock\",\"displayName\":\"edify-3d\",\"name\":\"edify-3d\",\"explainability\":\"\",\"updatedDate\":\"2024-08-26T16:46:35.655Z\",\"attributes\":[{\"key\":\"PREVIEW\",\"value\":\"false\"}],\"artifactType\":\"ENDPOINT\"}},\"spec\":{\"openAPISpec\":{\"openapi\":\"3.0.1\",\"info\":{\"title\":\"Picasso Edify API v3.0 - Text-to-3D\",\"version\":\"3.0.0\",\"description\":\"This API generates an image based on a given text prompt, offering various customization options.\"},\"servers\":[{\"url\":\"https://ai.api.nvidia.com/v3/edify2d/text23d\",\"description\":\"Production\"}],\"tags\":[{\"name\":\"Function Invocation API\",\"description\":\"An example command for invoking Text-to-3D Picasso API's. All tne endpoints defined in this API require SSA JWT or SAK as bearer token in the HTTP Authorization header with invoke_function scope.\\n\"}],\"paths\":{\"/v2/nvcf/exec/status/{requestId}\":{\"get\":{\"tags\":[\"Function Invocation API\"],\"summary\":\"Gets the result of an earlier function invocation request.\",\"description\":\"This endpoint can be invoked by Account Admin or Account User. It is used to\\n obtain the result of a previously submitted request for function invocation.\\n Redis is polled for 5 seconds(by default) for the result. If the result is\\n available, then it is included in the response and the request is considered\\n fulfilled. Otherwise, the request is considered pending. This endpoint\\n requires SSA JWT with invoke_function scope or Starfleet ApiKey(SAK) in the\\n HTTP Authorization header.\\nIn-progress responses are returned in order. If no in-progress response is received\\n during polling you will receive the most recent in-progress response. Only the first\\n 256 unread in-progress messages are kept.\\n\",\"operationId\":\"getFunctionInvocationResult_1\",\"parameters\":[{\"name\":\"requestId\",\"in\":\"path\",\"description\":\"Function invocation request id\",\"required\":true,\"schema\":{\"type\":\"string\",\"format\":\"uuid\"}}],\"responses\":{\"200\":{\"description\":\"Invocation is fulfilled\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/InvokeFunctionResponse\"}}}},\"202\":{\"description\":\"Result is pending. Client should poll using the requestId.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/InvokeFunctionResponse\"}}}},\"302\":{\"description\":\"Result is in a different region. Client should use the fully-qualified\\nendpoint specified in 'Location' response header to fetch the result.\\nClient can use the same Bearer token in 'Authorization' header when\\nretrieving the result from the redirected region.\\n\",\"headers\":{\"Location\":{\"style\":\"simple\",\"schema\":{\"type\":\"string\"}}},\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/InvokeFunctionResponse\"}}}},\"402\":{\"description\":\"Cloud credits expired for public functions. Please contact NVIDIA representatives.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/InvokeFunctionResponse\"}}}},\"403\":{\"description\":\"Either missing scope in the auth(SSA JWT / SAK) token and/or missing resource entry\\n in the SAK for the function.\\n\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/InvokeFunctionResponse\"}}}}}}},\"/v2/nvcf/exec/functions/{functionId}\":{\"post\":{\"tags\":[\"Function Invocation API\"],\"summary\":\"Invokes Text23D API running on an NVCF instance for a given function-id.\",\"description\":\"This endpoint can be invoked by Account Admin or Account User. It invokes a\\n function by publishing a message to function-specific request queue and waits\\n for the result polling Redis for 5 seconds (by default). If result is available\\n during that time, then it is included in the response. Otherwise, the\\n invocation is considered pending and the client should keep polling for the\\n result using the invocation request id. This endpoint requires SSA JWT token\\n with invoke_function scope or Starfleet ApiKey(SAK) in the HTTP Authorization\\n header.\\nIn-progress responses are returned in order. If no in-progress response is received\\n during polling you will receive the most recent in-progress response. Only the first\\n 256 unread in-progress messages are kept.\\n\",\"operationId\":\"invokeFunction\",\"parameters\":[{\"name\":\"functionId\",\"in\":\"path\",\"required\":true,\"schema\":{\"type\":\"string\",\"format\":\"uuid\"}}],\"requestBody\":{\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/InvokeFunctionRequest\"}}},\"required\":true},\"responses\":{\"200\":{\"description\":\"Invocation is fulfilled\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/InvokeFunctionResponse\"}}}},\"202\":{\"description\":\"Result is pending. Client should poll using the requestId.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/InvokeFunctionResponse\"}}}},\"302\":{\"description\":\"Result is in a different region. Client should use the fully-qualified\\nendpoint specified in 'Location' response header to fetch the result.\\nClient can use the same Bearer token in 'Authorization' header when\\nretrieving the result from the redirected region.\\n\",\"headers\":{\"Location\":{\"style\":\"simple\",\"schema\":{\"type\":\"string\"}}},\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/InvokeFunctionResponse\"}}}},\"402\":{\"description\":\"Cloud credits expired for public functions. Please contact NVIDIA representatives.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/InvokeFunctionResponse\"}}}},\"403\":{\"description\":\"Either missing scope in the auth(SSA JWT / SAK) token and/or missing resource entry\\n in the SAK for the function.\\n\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/InvokeFunctionResponse\"}}}}}}},\"/v2/nvcf/exec/functions/{functionId}/versions/{versionId}\":{\"post\":{\"tags\":[\"Function Invocation API\"],\"summary\":\"Invokes Text23D API running on an NVCF instance for a given function-id and version-id.\",\"description\":\"This endpoint can be invoked by Account Admin or Account User. It invokes a\\n function by publishing a message to function-specific request queue and waits\\n for the result polling Redis for 5 seconds (by default). If result is available\\n during that time, then it is included in the response. Otherwise, the\\n invocation is considered pending and the client should keep polling for the\\n result using the invocation request id. This endpoint requires SSA JWT token\\n with invoke_function scope or Starfleet ApiKey(SAK) in the HTTP Authorization\\n header.\\nIn-progress responses are returned in order. If no in-progress response is received\\n during polling you will receive the most recent in-progress response. Only the first\\n 256 unread in-progress messages are kept.\\n\",\"operationId\":\"invokeFunction_1\",\"parameters\":[{\"name\":\"functionId\",\"in\":\"path\",\"required\":true,\"schema\":{\"type\":\"string\",\"format\":\"uuid\"}},{\"name\":\"versionId\",\"in\":\"path\",\"required\":true,\"schema\":{\"type\":\"string\",\"format\":\"uuid\"}}],\"requestBody\":{\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/InvokeFunctionRequest\"}}},\"required\":true},\"responses\":{\"200\":{\"description\":\"Invocation is fulfilled\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/InvokeFunctionResponse\"}}}},\"202\":{\"description\":\"Result is pending. Client should poll using the requestId.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/InvokeFunctionResponse\"}}}},\"302\":{\"description\":\"Result is in a different region. Client should use the fully-qualified\\nendpoint specified in 'Location' response header to fetch the result.\\nClient can use the same Bearer token in 'Authorization' header when\\nretrieving the result from the redirected region.\\n\",\"headers\":{\"Location\":{\"style\":\"simple\",\"schema\":{\"type\":\"string\"}}},\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/InvokeFunctionResponse\"}}}},\"402\":{\"description\":\"Cloud credits expired for public functions. Please contact NVIDIA representatives.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/InvokeFunctionResponse\"}}}},\"403\":{\"description\":\"Either missing scope in the auth(SSA JWT / SAK) token and/or missing resource entry\\n in the SAK for the function.\\n\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/InvokeFunctionResponse\"}}}}}}}},\"components\":{\"schemas\":{\"InvokeFunctionRequest\":{\"required\":[\"InvokeFunctionRequestBody\"],\"type\":\"object\",\"properties\":{\"InvokeFunctionRequestHeader\":{\"$ref\":\"#/components/schemas/InvokeFunctionRequestHeader\"},\"InvokeFunctionRequestBody\":{\"$ref\":\"#/components/schemas/InvokeFunctionRequestBody\"}},\"description\":\"Request body for creating a job/task for inference/train using a GPU powered spot instance in cloud.\"},\"InvokeFunctionRequestHeader\":{\"type\":\"object\",\"properties\":{\"pollDurationSeconds\":{\"maximum\":300,\"type\":\"integer\",\"description\":\"Polling timeout duration.\",\"format\":\"int32\",\"default\":300}},\"description\":\"POJO representing header/address for NVCF processing.\"},\"InvokeFunctionRequestBody\":{\"type\":\"object\",\"properties\":{\"inputs\":{\"type\":\"array\",\"description\":\"List of inputs.\",\"items\":{\"$ref\":\"#/components/schemas/Inputs\"}}},\"description\":\"POJO representing inputs to Edify API for processing.\"},\"InvokeFunctionResponse\":{\"type\":\"object\",\"properties\":{\"reqId\":{\"type\":\"string\",\"description\":\"Request id\",\"format\":\"uuid\"},\"status\":{\"type\":\"string\",\"description\":\"Status of the task/job executing cloud function.\",\"enum\":[\"errored\",\"in-progress\",\"fulfilled\",\"pending-evaluation\",\"rejected\"]},\"responseReference\":{\"type\":\"string\",\"description\":\"For large results, responseReference will be a pre-signeddownload URL.\",\"format\":\"url\"},\"percentComplete\":{\"type\":\"integer\",\"description\":\"Progress indicator for the task/job executing cloud function.\",\"format\":\"int32\"},\"errorCode\":{\"type\":\"integer\",\"description\":\"Error code from the container while executing cloud function.\",\"format\":\"int32\"},\"response\":{\"type\":\"string\",\"description\":\"Response/result of size \u003c 5MB size for the task/job executing cloud function.\"}},\"description\":\"Response body with result from a request for executing a job/task as a cloud function using a GPU powered spot/on-demand instance.\"},\"Inputs\":{\"required\":[\"name\",\"shape\",\"dataType\",\"data\"],\"type\":\"object\",\"properties\":{\"name\":{\"type\":\"string\",\"description\":\"Name of the input parameter\",\"example\":\"command\"},\"shape\":{\"type\":\"array\",\"description\":\"Shape of the input 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details\"}}}},\"namespace\":\"qc69jvmznzxy\",\"updatedDate\":\"2024-07-29T20:08:42.588Z\",\"nvcfFunctionId\":\"8217fe06-0747-4276-a8fb-894b8b6e3342\",\"createdDate\":\"2024-07-29T19:04:54.275Z\",\"attributes\":{\"requiresLogin\":false,\"showUnavailableBanner\":false,\"apiDocsUrl\":null,\"termsOfUse\":\"\u003cb\u003eGOVERNING TERMS\u003c/b\u003e: Your use of this API for is governed by the \u003ca href=\\\"https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA API Trial Service Terms of Use\u003c/a\u003e and the \u003ca href=\\\"https://assets.ngc.nvidia.com/products/api-catalog/legal/Shutterstock-AI-3D-Generato-Preview-TOU.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eShutterstock Generative AI Trial Terms of Use\u003c/a\u003e.\\n\",\"cta\":{\"type\":\"Get API from Shutterstock\",\"url\":\"https://www.shutterstock.com/discover/generative-ai-3d\"}},\"artifactName\":\"edify-3d\"},\"config\":{\"name\":\"edify-3d\",\"type\":\"model\"}},{\"endpoint\":{\"requestStatus\":{\"statusCode\":\"SUCCESS\",\"requestId\":\"33364173-e137-4200-8731-4a3699a76a88\"},\"artifact\":{\"orgName\":\"qc69jvmznzxy\",\"labels\":[\"Image Generation\",\"Image Modification\",\"Inpaint\",\"Outpaint\",\"Replace\"],\"bias\":\"\",\"logo\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/edify-image.jpg\",\"shortDescription\":\"Getty Images’ API service for 4K image generation. Trained on NVIDIA Edify using Getty Images' commercially safe creative libraries.\",\"safetyAndSecurity\":\"\",\"privacy\":\"\",\"isReadOnly\":true,\"description\":\"https://developers.gettyimages.com/ai-generation/model-card/\",\"canGuestDownload\":true,\"isPublic\":true,\"createdDate\":\"2024-07-29T19:04:51.433Z\",\"publisher\":\"GettyImages\",\"displayName\":\"edify-image\",\"name\":\"edify-image\",\"explainability\":\"\",\"updatedDate\":\"2024-08-26T16:47:09.211Z\",\"attributes\":[{\"key\":\"PREVIEW\",\"value\":\"false\"}],\"artifactType\":\"ENDPOINT\"}},\"spec\":{\"openAPISpec\":{\"openapi\":\"3.0.1\",\"info\":{\"title\":\"Picasso Edify API v3.0 - Text-to-Image\",\"version\":\"3.0.0\",\"description\":\"This API generates an image based on a given text prompt, offering various customization options.\"},\"servers\":[{\"url\":\"https://ai.api.nvidia.com/v3/edify2d/text2image\",\"description\":\"Production\"}],\"tags\":[{\"name\":\"Function Invocation API\",\"description\":\"An example command for invoking Text2Image Picasso API's. All tne endpoints defined in this API require SSA JWT or SAK as bearer token in the HTTP Authorization header with invoke_function scope.\\n\"}],\"paths\":{\"/v2/nvcf/exec/status/{requestId}\":{\"get\":{\"tags\":[\"Function Invocation API\"],\"summary\":\"Gets the result of an earlier function invocation request.\",\"description\":\"This endpoint can be invoked by Account Admin or Account User. It is used to\\n obtain the result of a previously submitted request for function invocation.\\n Redis is polled for 5 seconds(by default) for the result. If the result is\\n available, then it is included in the response and the request is considered\\n fulfilled. Otherwise, the request is considered pending. This endpoint\\n requires SSA JWT with invoke_function scope or Starfleet ApiKey(SAK) in the\\n HTTP Authorization header.\\nIn-progress responses are returned in order. If no in-progress response is received\\n during polling you will receive the most recent in-progress response. Only the first\\n 256 unread in-progress messages are kept.\\n\",\"operationId\":\"getFunctionInvocationResult_1\",\"parameters\":[{\"name\":\"requestId\",\"in\":\"path\",\"description\":\"Function invocation request id\",\"required\":true,\"schema\":{\"type\":\"string\",\"format\":\"uuid\"}}],\"responses\":{\"200\":{\"description\":\"Invocation is fulfilled\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/InvokeFunctionResponse\"}}}},\"202\":{\"description\":\"Result is pending. Client should poll using the requestId.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/InvokeFunctionResponse\"}}}},\"302\":{\"description\":\"Result is in a different region. Client should use the fully-qualified\\nendpoint specified in 'Location' response header to fetch the result.\\nClient can use the same Bearer token in 'Authorization' header when\\nretrieving the result from the redirected region.\\n\",\"headers\":{\"Location\":{\"style\":\"simple\",\"schema\":{\"type\":\"string\"}}},\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/InvokeFunctionResponse\"}}}},\"402\":{\"description\":\"Cloud credits expired for public functions. Please contact NVIDIA representatives.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/InvokeFunctionResponse\"}}}},\"403\":{\"description\":\"Either missing scope in the auth(SSA JWT / SAK) token and/or missing resource entry\\n in the SAK for the function.\\n\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/InvokeFunctionResponse\"}}}}}}},\"/v2/nvcf/exec/functions/{functionId}\":{\"post\":{\"tags\":[\"Function Invocation API\"],\"summary\":\"Invokes Text2Image API running on an NVCF instance for a given function-id.\",\"description\":\"This endpoint can be invoked by Account Admin or Account User. It invokes a\\n function by publishing a message to function-specific request queue and waits\\n for the result polling Redis for 5 seconds (by default). If result is available\\n during that time, then it is included in the response. Otherwise, the\\n invocation is considered pending and the client should keep polling for the\\n result using the invocation request id. This endpoint requires SSA JWT token\\n with invoke_function scope or Starfleet ApiKey(SAK) in the HTTP Authorization\\n header.\\nIn-progress responses are returned in order. If no in-progress response is received\\n during polling you will receive the most recent in-progress response. Only the first\\n 256 unread in-progress messages are kept.\\n\",\"operationId\":\"invokeFunction\",\"parameters\":[{\"name\":\"functionId\",\"in\":\"path\",\"required\":true,\"schema\":{\"type\":\"string\",\"format\":\"uuid\"}}],\"requestBody\":{\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/InvokeFunctionRequest\"}}},\"required\":true},\"responses\":{\"200\":{\"description\":\"Invocation is fulfilled\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/InvokeFunctionResponse\"}}}},\"202\":{\"description\":\"Result is pending. Client should poll using the requestId.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/InvokeFunctionResponse\"}}}},\"302\":{\"description\":\"Result is in a different region. Client should use the fully-qualified\\nendpoint specified in 'Location' response header to fetch the result.\\nClient can use the same Bearer token in 'Authorization' header when\\nretrieving the result from the redirected region.\\n\",\"headers\":{\"Location\":{\"style\":\"simple\",\"schema\":{\"type\":\"string\"}}},\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/InvokeFunctionResponse\"}}}},\"402\":{\"description\":\"Cloud credits expired for public functions. Please contact NVIDIA representatives.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/InvokeFunctionResponse\"}}}},\"403\":{\"description\":\"Either missing scope in the auth(SSA JWT / SAK) token and/or missing resource entry\\n in the SAK for the function.\\n\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/InvokeFunctionResponse\"}}}}}}},\"/v2/nvcf/exec/functions/{functionId}/versions/{versionId}\":{\"post\":{\"tags\":[\"Function Invocation API\"],\"summary\":\"Invokes Text2Image API running on an NVCF instance for a given function-id and version-id.\",\"description\":\"This endpoint can be invoked by Account Admin or Account User. It invokes a\\n function by publishing a message to function-specific request queue and waits\\n for the result polling Redis for 5 seconds (by default). If result is available\\n during that time, then it is included in the response. Otherwise, the\\n invocation is considered pending and the client should keep polling for the\\n result using the invocation request id. This endpoint requires SSA JWT token\\n with invoke_function scope or Starfleet ApiKey(SAK) in the HTTP Authorization\\n header.\\nIn-progress responses are returned in order. If no in-progress response is received\\n during polling you will receive the most recent in-progress response. Only the first\\n 256 unread in-progress messages are kept.\\n\",\"operationId\":\"invokeFunction_1\",\"parameters\":[{\"name\":\"functionId\",\"in\":\"path\",\"required\":true,\"schema\":{\"type\":\"string\",\"format\":\"uuid\"}},{\"name\":\"versionId\",\"in\":\"path\",\"required\":true,\"schema\":{\"type\":\"string\",\"format\":\"uuid\"}}],\"requestBody\":{\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/InvokeFunctionRequest\"}}},\"required\":true},\"responses\":{\"200\":{\"description\":\"Invocation is fulfilled\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/InvokeFunctionResponse\"}}}},\"202\":{\"description\":\"Result is pending. Client should poll using the requestId.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/InvokeFunctionResponse\"}}}},\"302\":{\"description\":\"Result is in a different region. Client should use the fully-qualified\\nendpoint specified in 'Location' response header to fetch the result.\\nClient can use the same Bearer token in 'Authorization' header when\\nretrieving the result from the redirected region.\\n\",\"headers\":{\"Location\":{\"style\":\"simple\",\"schema\":{\"type\":\"string\"}}},\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/InvokeFunctionResponse\"}}}},\"402\":{\"description\":\"Cloud credits expired for public functions. Please contact NVIDIA representatives.\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/InvokeFunctionResponse\"}}}},\"403\":{\"description\":\"Either missing scope in the auth(SSA JWT / SAK) token and/or missing resource entry\\n in the SAK for the function.\\n\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/InvokeFunctionResponse\"}}}}}}}},\"components\":{\"schemas\":{\"InvokeFunctionRequest\":{\"required\":[\"InvokeFunctionRequestBody\"],\"type\":\"object\",\"properties\":{\"InvokeFunctionRequestHeader\":{\"$ref\":\"#/components/schemas/InvokeFunctionRequestHeader\"},\"InvokeFunctionRequestBody\":{\"$ref\":\"#/components/schemas/InvokeFunctionRequestBody\"}},\"description\":\"Request body for creating a job/task for inference/train using a GPU powered spot instance in cloud.\"},\"InvokeFunctionRequestHeader\":{\"type\":\"object\",\"properties\":{\"pollDurationSeconds\":{\"maximum\":300,\"type\":\"integer\",\"description\":\"Polling timeout duration.\",\"format\":\"int32\",\"default\":300}},\"description\":\"POJO representing header/address for NVCF processing.\"},\"InvokeFunctionRequestBody\":{\"type\":\"object\",\"properties\":{\"inputs\":{\"type\":\"array\",\"description\":\"List of inputs.\",\"items\":{\"$ref\":\"#/components/schemas/Inputs\"}}},\"description\":\"POJO representing inputs to Edify API for processing.\"},\"InvokeFunctionResponse\":{\"type\":\"object\",\"properties\":{\"reqId\":{\"type\":\"string\",\"description\":\"Request id\",\"format\":\"uuid\"},\"status\":{\"type\":\"string\",\"description\":\"Status of the task/job executing cloud function.\",\"enum\":[\"errored\",\"in-progress\",\"fulfilled\",\"pending-evaluation\",\"rejected\"]},\"responseReference\":{\"type\":\"string\",\"description\":\"For large results, responseReference will be a pre-signeddownload URL.\",\"format\":\"url\"},\"percentComplete\":{\"type\":\"integer\",\"description\":\"Progress indicator for the task/job executing cloud function.\",\"format\":\"int32\"},\"errorCode\":{\"type\":\"integer\",\"description\":\"Error code from the container while executing cloud function.\",\"format\":\"int32\"},\"response\":{\"type\":\"string\",\"description\":\"Response/result of size \u003c 5MB size for the task/job executing cloud function.\"}},\"description\":\"Response body with result from a request for executing a job/task as a cloud function using a GPU powered spot/on-demand instance.\"},\"Inputs\":{\"required\":[\"name\",\"shape\",\"dataType\",\"data\"],\"type\":\"object\",\"properties\":{\"name\":{\"type\":\"string\",\"description\":\"Name of the input parameter\",\"example\":\"command\"},\"shape\":{\"type\":\"array\",\"description\":\"Shape of the input parameter\",\"items\":{\"type\":\"integer\",\"example\":1}},\"dataType\":{\"type\":\"string\",\"description\":\"Type of input data\",\"example\":\"BYTES\"},\"data\":{\"type\":\"array\",\"description\":\"Value of the input parameter\",\"items\":{\"type\":\"string\"}}},\"description\":\"POJO representing an input entry\",\"example\":{\"name\":\"command\",\"shape\":[1],\"dataType\":\"BYTES\",\"data\":[\"text2image --prompt='blue carrot' --negative_prompt='ugly, blurry, ' --nsamples=4 --output_res=1024 --media_type='Photography' --aspect_ratio='1,1' --nstep_1024=10 --gs_1024=5 --seed=0 --num_humans=1 --human_attributes='random'\"]}},\"ErrorDetails\":{\"type\":\"object\",\"properties\":{\"type\":{\"type\":\"string\",\"format\":\"uri\"},\"title\":{\"type\":\"string\"},\"status\":{\"type\":\"integer\",\"format\":\"int32\"},\"detail\":{\"type\":\"string\"}},\"description\":\"POJO representing error details\"}}}},\"namespace\":\"qc69jvmznzxy\",\"nvcfFunctionId\":\"40ba924a-d5df-476f-99af-93e5ecf496a8\",\"createdDate\":\"2024-07-29T19:04:51.733Z\",\"attributes\":{\"requiresLogin\":false,\"showUnavailableBanner\":false,\"apiDocsUrl\":\"https://api.gettyimages.com/swagger/v3/swagger.json\",\"termsOfUse\":\"\u003cb\u003eGOVERNING TERMS\u003c/b\u003e: Your use of this API for is governed by the \u003ca href=\\\"https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA API Trial Service Terms of Use\u003c/a\u003e and the \u003ca href=\\\"https://assets.ngc.nvidia.com/products/api-catalog/legal/GettyImages-AI-ImageGeneration-Trial-TOU.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eGetty Images AI Image Generation Trial Terms of Use\u003c/a\u003e.\\n\",\"cta\":{\"type\":\"Get API from Getty Images\",\"url\":\"https://www.gettyimages.com/enterprise/contact-sales?utm_campaignid=7014M000002KtRsQAK\u0026form=GI_NVIDIAStrategicParnership\"},\"maxRequests\":50},\"artifactName\":\"edify-image\"},\"config\":{\"name\":\"edify-image\",\"type\":\"model\"}},{\"endpoint\":null,\"spec\":null,\"config\":{\"name\":\"edify-360-hdri-early-access\",\"type\":\"model\"}}]}]\n"])</script><script>self.__next_f.push([1,"c4:T15dd,"])</script><script>self.__next_f.push([1,"## Model Overview\n\n### Description:\n\nAlphaFold2 is a deep learning model for protein structure prediction developed by the research group at DeepMind, an artificial intelligence (AI) research lab owned by Google (`jumper2021alphafold`). AlphaFold2 builds on the success of its predecessor, AlphaFold, and represents a significant breakthrough in the field of protein structure prediction. This model is available for commercial use.\n\u003cbr\u003e\n\n### Third-Party Community Consideration\n\nThis model is not owned or developed by NVIDIA. This model has been developed and built to a third-party’s requirements for this application and use case.\n\n#### License / Terms of Use\n\nThe AlphaFold2 code is released under the [Apache 2.0 License](https://github.com/google-deepmind/alphafold/blob/main/LICENSE). The model parameters are licensed under the [CC BY 4.0 License](https://github.com/google-deepmind/alphafold?tab=readme-ov-file#model-parameters).\n\n### References:\n\n```\n@ARTICLE{jumper2021alphafold,\n title = \"Highly accurate protein structure prediction with {AlphaFold}\",\n author = \"Jumper, John and Evans, Richard and Pritzel, Alexander and Green,\n Tim and Figurnov, Michael and Ronneberger, Olaf and\n Tunyasuvunakool, Kathryn and Bates, Russ and {\\v Z}{\\'\\i}dek,\n Augustin and Potapenko, Anna and Bridgland, Alex and Meyer,\n Clemens and Kohl, Simon A A and Ballard, Andrew J and Cowie,\n Andrew and Romera-Paredes, Bernardino and Nikolov, Stanislav and\n Jain, Rishub and Adler, Jonas and Back, Trevor and Petersen, Stig\n and Reiman, David and Clancy, Ellen and Zielinski, Michal and\n Steinegger, Martin and Pacholska, Michalina and Berghammer, Tamas\n and Bodenstein, Sebastian and Silver, David and Vinyals, Oriol\n and Senior, Andrew W and Kavukcuoglu, Koray and Kohli, Pushmeet\n and Hassabis, Demis\",\n journal = \"Nature\",\n volume = 596,\n number = 7873,\n pages = \"583--589\",\n month = aug,\n year = 2021,\n language = \"en\",\n doi = {10.1038/s41586-021-03819-2},\n}\n```\n\n\u003cbr\u003e\n\n### Model Architecture:\n\n**Architecture Type:** Protein Structure Prediction \u003cbr\u003e\n**Network Architecture:** AlphaFold2 \u003cbr\u003e\n\n**Input Type(s):** Protein Sequence, Relax Prediction (Default True) \u003cbr\u003e\n**Input Format(s):** String (less than or equal to 4096 characters), boolean \u003cbr\u003e\n**Input Parameters:** 1D \u003cbr\u003e\n**Other Properties Related to Input:** NA \u003cbr\u003e\n\n### Output:\n\n**Output Type(s):** Protein Structure(s) in PDB Format \u003cbr\u003e\n**Output Format:** PDB (text file)\u003cbr\u003e\n**Output Parameters:** 1D \u003cbr\u003e\n**Other Properties Related to Output:** Pose (num_atm_ x 3)\u003cbr\u003e\n\n### Software Integration:\n\n**Runtime Engine(s):**\n* Python \u003cbr\u003e\n\n**Supported Hardware Microarchitecture Compatibility:** \u003cbr\u003e\n* NVIDIA Ampere \u003cbr\u003e\n\n**[Preferred/Supported] Operating System(s):** \u003cbr\u003e\n* [Linux] \u003cbr\u003e\n\n### Model Version(s):\n\nAlphaFold2 2.3.2 \u003cbr\u003e\n\n## Training \u0026 Evaluation:\n\n### Training Dataset:\n\n**Link:** A description of the training dataset and relevant download links are available at [https://www.nature.com/articles/s41586-021-03819-2#data-availability](https://www.nature.com/articles/s41586-021-03819-2#data-availability). This data was not collected by NVIDIA. \u003cbr\u003e\n** Data Collection Method by dataset \u003cbr\u003e\n* See the description at [https://www.nature.com/articles/s41586-021-03819-2#data-availability](https://www.nature.com/articles/s41586-021-03819-2#data-availability). \u003cbr\u003e\n\n** Labeling Method by dataset \u003cbr\u003e\n* See the description at [https://www.nature.com/articles/s41586-021-03819-2#data-availability](https://www.nature.com/articles/s41586-021-03819-2#data-availability). \u003cbr\u003e\n\n**Properties (Quantity, Dataset Descriptions, Sensor(s)):**\nUniclust dataset of 355,993 sequences with the full MSAs. These predictions were then used to train a final model with identical hyperparameters, except for sampling examples 75% of the time from the Uniclust prediction set, with sub-sampled MSAs, and 25% of the time from the clustered PDB set.\n\u003cbr\u003e\n\n### Evaluation Dataset:\n\n**Link:** See the description at [https://www.nature.com/articles/s41586-021-03819-2#Sec10](https://www.nature.com/articles/s41586-021-03819-2#Sec10). \u003cbr\u003e\n** Data Collection Method by dataset \u003cbr\u003e\n* [Not Applicable] \u003cbr\u003e\n\n** Labeling Method by dataset \u003cbr\u003e\n* [Not Applicable] \u003cbr\u003e\n\n**Properties (Quantity, Dataset Descriptions, Sensor(s)):**\nUniclust dataset of 355,993 sequences with the full MSAs. These predictions were then used to train a final model with identical hyperparameters, except for sampling examples 75% of the time from the Uniclust prediction set, with sub-sampled MSAs, and 25% of the time from the clustered PDB set.\n\u003cbr\u003e\n\n### Inference:\n\n**Engine:** Python \u003cbr\u003e\n**Test Hardware:** \u003cbr\u003e\n* NVIDIA A6000 \u003cbr\u003e\n* NVIDIA A100 \u003cbr\u003e\n\n### Ethical Considerations:\n\nNVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their supporting model team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse. Please report security vulnerabilities or NVIDIA AI Concerns [here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/).\n\n**You are responsible for ensuring that your use of NVIDIA AI Foundation Models complies with all applicable laws.**\n"])</script><script>self.__next_f.push([1,"c5:T9d7,"])</script><script>self.__next_f.push([1,"#!/usr/bin/env bash\nif [ \"$NVCF_RUN_KEY\" = \"\" ]; then read -p \"Paste Run Key: \" NVCF_RUN_KEY; fi\nURL=${URL:-https://health.api.nvidia.com/v1/biology/deepmind/alphafold2-multimer}\nSTATUS_URL=${STATUS_URL:-https://health.api.nvidia.com/v1/status}\n\nsequences='[\"GSHMAQPRPPFHITIPIYPGVDLLDVAAPVELFSWMADAWKARATTITLAAEHLTPLKTRDGLTLTPQRQFADYADAAAPQPQTHLLWVPGGAPDVLRKLMRGGPYLDFLKAQSAGADHVSSVCEGALLLAAAGLLDGYRATTHWAFIPCLQQFPAIKVAEGFPRYVIDGNRITGGGISSGLAEALAIVARVAGQDIAKHVQMITQYFPDPPFEQTIVPATHCPLQA\",\"GSHMAQPRPPFHITIPIYPGVDLLDVAAPVELFSWMADAWKARATTITLAAEHLTPLKTRDGLTLTPQRQFADYADAAAPQPQTHLLWVPGGAPDVLRKLMRGGPYLDFLKAQSAGADHVSSVCEGALLLAAAGLLDGYRATTHWAFIPCLQQFPAIKVAEGFPRYVIDGNRITGGGISSGLAEALAIVARVAGQDIAKHVQMITQYFPDPPFEQTIVPATHCPLQA\"]'\n\nrequest_body='{\n \"sequences\": '$sequences',\n \"algorithm\": \"jackhmmer\",\n \"e_value\": 0.0001,\n \"iterations\": 1,\n \"databases\": [\"uniref90\", \"small_bfd\", \"mgnify\"],\n \"relax_prediction\": true\n}'\noutput_file=\"output.json\"\n\n# Initial request\necho \"Making request...\"\nresponse=$(curl -s -D /dev/stderr --fail-with-body -H \"content-type: application/json\" -H \"Authorization: Bearer $NVCF_RUN_KEY\" -H \"NVCF-POLL-SECONDS: 1\" --request POST --data \"$request_body\" \"$URL\" 2\u003e\u00261 1\u003e $output_file)\n\n# Extract HTTP status code\nhttp_status=$(echo \"$response\" | awk '{print $2;exit}')\n\n# Check the status code\nif [ \"$http_status\" -eq 200 ]; then\n echo \"Saved response to file: $output_file\"\nelif [ \"$http_status\" -eq 202 ]; then\n echo \"Request accepted...\"\n # Extract nvcf-reqid header\n req_id=$(echo \"$response\" | grep -i \"nvcf-reqid:\" | awk '{print $2}' | tr -d '\\r')\n\n # Poll the /status endpoint\n while true; do\n echo \"Polling for response...\"\n status_response=$(curl -s -D /dev/stderr --fail-with-body -H \"content-type: application/json\" -H \"Authorization: Bearer $NVCF_RUN_KEY\" -H \"NVCF-POLL-SECONDS: 5\" --request GET \"${STATUS_URL}/${req_id}\" 2\u003e\u00261 1\u003e $output_file)\n\n status_http_status=$(echo \"$status_response\" | awk '{print $2;exit}')\n\n if [ \"$status_http_status\" -eq 200 ]; then\n echo \"Saved response to file: $output_file\"\n break\n elif [ \"$status_http_status\" -ne 202 ]; then\n echo \"Unexpected HTTP status: $status_http_status\"\n echo \"Response: $status_response\"\n exit 1\n fi\n\n # Wait before polling again\n sleep 5\n done\nelse\n echo \"Unexpected HTTP status: $http_status\"\n echo \"Response: $response\"\n exit 1\nfi"])</script><script>self.__next_f.push([1,"c6:T8d4,"])</script><script>self.__next_f.push([1,"#!/usr/bin/env python3\nimport os\nimport requests\nimport time\nfrom pathlib import Path\n\n# Variables\nkey = os.getenv(\"NVCF_RUN_KEY\") or input(\"Paste the Run Key: \")\nurl = os.getenv(\"URL\", \"https://health.api.nvidia.com/v1/biology/deepmind/alphafold2-multimer\")\nstatus_url = os.getenv(\"STATUS_URL\", \"https://health.api.nvidia.com/v1/status\")\n\nsequences = [\n \"GSHMAQPRPPFHITIPIYPGVDLLDVAAPVELFSWMADAWKARATTITLAAEHLTPLKTRDGLTLTPQRQFADYADAAAPQPQTHLLWVPGGAPDVLRKLMRGGPYLDFLKAQSAGADHVSSVCEGALLLAAAGLLDGYRATTHWAFIPCLQQFPAIKVAEGFPRYVIDGNRITGGGISSGLAEALAIVARVAGQDIAKHVQMITQYFPDPPFEQTIVPATHCPLQA\",\n \"GSHMAQPRPPFHITIPIYPGVDLLDVAAPVELFSWMADAWKARATTITLAAEHLTPLKTRDGLTLTPQRQFADYADAAAPQPQTHLLWVPGGAPDVLRKLMRGGPYLDFLKAQSAGADHVSSVCEGALLLAAAGLLDGYRATTHWAFIPCLQQFPAIKVAEGFPRYVIDGNRITGGGISSGLAEALAIVARVAGQDIAKHVQMITQYFPDPPFEQTIVPATHCPLQA\"\n]\n\noutput_file = Path(\"output.json\")\n\n# Request to predict structure from a list of sequences, i.e. the NVCF endpoint for\n# http://localhost:8000/protein-structure/alphafold2/multimer/predict-structure-from-sequences\nheaders = {\n \"content-type\": \"application/json\",\n \"Authorization\": f\"Bearer {key}\",\n \"NVCF-POLL-SECONDS\": \"5\",\n}\ndata = {\n \"sequences\": sequences,\n \"algorithm\": \"jackhmmer\",\n \"e_value\": 0.0001,\n \"iterations\": 1,\n \"databases\": [\"uniref90\", \"small_bfd\", \"mgnify\"],\n \"relax_prediction\": True,\n}\n\nprint(\"Making request...\")\nresponse = requests.post(url, headers=headers, json=data)\n\n# Check the status code\nif response.status_code == 200:\n output_file.write_text(response.text)\n print(f\"Response output to file: {output_file}\")\nelif response.status_code == 202:\n print(\"Request accepted...\")\n # Extract reqId header\n req_id = response.headers.get(\"nvcf-reqid\")\n\n # Poll the /status endpoint\n while True:\n print(\"Polling for response...\")\n status_response = requests.get(f\"{status_url}/{req_id}\", headers=headers)\n\n if status_response.status_code != 202:\n output_file.write_text(status_response.text)\n print(f\"Response output to file: {output_file}\")\n break\n\n # Wait before polling again\n time.sleep(5)\nelse:\n print(f\"Unexpected HTTP status: {response.status_code}\")\n print(f\"Response: {response.text}\")"])</script><script>self.__next_f.push([1,"c7:Tc10,"])</script><script>self.__next_f.push([1,"## Start NIM\n\n1. Export `NGC_CLI_API_KEY` variable.\n\n```\nexport NGC_CLI_API_KEY=\u003cyour personal NGC key\u003e\n```\n\n2. The NIM container automatically downloads any required models. To save time and bandwidth it\n is recommended to provide a local cache directory. This way the NIM will be able to\n reuse any already downloaded models. Execute the following command to setup the cache\n directory:\n\n```bash\nexport LOCAL_NIM_CACHE=~/.cache/nim\nmkdir -p $LOCAL_NIM_CACHE\n```\n\nNote that you may need to run `(sudo) chmod -R 777 $LOCAL_NIM_CACHE` after the AlphaFold2 model is downloaded to avoid permission issues.\n\n3. Run the NIM container with the following commands:\n\n```bash\ndocker run -it --rm \\\n --runtime=nvidia \\\n -p 8000:8000 \\\n -e NGC_CLI_API_KEY \\\n -v $LOCAL_NIM_CACHE:/opt/nim/.cache \\\n nvcr.io/nim/deepmind/alphafold2-multimer:1.0.0\n```\n\nThis command will start the NIM container and expose port 8000 for the user to interact with the NIM.\n\n4. Open a new terminal, leaving the terminal open with the just launched service. In the new terminal, wait until the health check end point returns `{\"status\":\"ready\"}` before proceeding. This may take a couple of minutes. You can use the following command to query the health check.\n\n```bash\ncurl -X 'GET' \\\n 'http://localhost:8000/v1/health/ready' \\\n -H 'accept: application/json'\n```\n\n## Python Client Example\n\n1. Save following Python example to a file named `nim_client.py`.\n\n```python\nimport requests\nimport json\n\nurl = \"http://localhost:8000/protein-structure/alphafold2/multimer/predict-structure-from-sequences\" # Replace with the actual URL\nsequences = [\"MNVIDIAIAMAI\", \"NESKHCAWVMIPTFRQYDGL\"] # Replace with the actual sequences.\n\nheaders = {\n \"content-type\": \"application/json\"\n}\n\ndata = {\n \"sequences\": sequences,\n \"databases\": [\"small_bfd\"],\n \"e_value\": 0.000001,\n \"algorithm\": \"jackhmmer\",\n \"num_predictions_per_model\" : 1,\n \"relax_prediction\": False,\n}\n\nresponse = requests.post(url, headers=headers, data=json.dumps(data))\n\n# Check if the request was successful\nif response.ok:\n with open(\"output.pdb\", \"w\") as ofi:\n ofi.write(json.dumps(response.json()))\n print(\"Request succeeded:\", response.json())\nelse:\n print(\"Request failed:\", response.status_code, response.text)\n```\n\n2. Execute the example.\n\n```bash\npython nim_client.py\n```\n\n3. The resulting PDB structure will be returned and written to `output.pdb`.\n\n```bash\ncat output.pdb\n```\n\n## Shell Client Example\n\n1. Save the following Shell example to a file named `nim_client.sh`.\n\n```bash\n#!/usr/bin/env bash\nset -e\n\nURL=http://localhost:8000/protein-structure/alphafold2/multimer/predict-structure-from-sequences\n\nrequest='{\n \"sequences\": [\"MNVIDIAIAMAI\", \"NESKHCAWVMIPTFRQYDGL\"]\n}'\ncurl -H 'Content-Type: application/json' \\\n -d \"$request\" \"$URL\"\n```\n\n2. Execute the example.\n\n```bash\nchmod +x nim_client.sh\n\n./nim_client.sh\n```\n\n3. Results will be printed on the terminal in JSON format. You will be able\n to see the PDB formatted output; you can also use curl to save the output directly to file.\n"])</script><script>self.__next_f.push([1,"c8:T1374,"])</script><script>self.__next_f.push([1,"## Model Overview\n\n### Description:\n\nProteinMPNN (Protein Message Passing Neural Network) is a deep learning-based\ngraph neural network designed to predict amino acid sequences for given protein\nbackbones. This network leverages evolutionary, functional, and structural\ninformation to generate sequences that are likely to fold into the desired 3D\nstructures.\u003cbr\u003e\n\nThis model is available for commercial use.\u003cbr\u003e\n\n### Third-Party Community Consideration\n\nThis model is not owned or developed by NVIDIA. This model has been developed\nand built to a third-party’s requirements for this application and use case. \u003cbr\u003e\n\n#### License/Terms of Use:\n\nThis model is released under the\n[MIT License](https://github.com/dauparas/ProteinMPNN/blob/8907e6671bfbfc92303b5f79c4b5e6ce47cdef57/LICENSE).\n\n**You are responsible for ensuring that your use of NVIDIA AI Foundation Models\ncomplies with all applicable laws.**\n\n### References:\n\n```\n@article{dauparas2022robust,\n title={Robust deep learning--based protein sequence design using ProteinMPNN},\n author={Dauparas, Justas and Anishchenko, Ivan and Bennett, Nathaniel and Bai, Hua and Ragotte, Robert J and Milles, Lukas F and Wicky, Basile IM and Courbet, Alexis and de Haas, Rob J and Bethel, Neville and others},\n journal={Science},\n volume={378},\n number={6615}, \n pages={49--56},\n year={2022},\n publisher={American Association for the Advancement of Science}\n}\n```\n\n### Model Architecture:\n\n**Architecture Type:** Protein Amino Acid Sequence Prediction \u003cbr\u003e\n**Network Architecture:** ProteinMPNN \u003cbr\u003e\n\n### Input:\n\n**Input Type(s):** Protein in Protein Data Bank (PDB) format \u003cbr\u003e\n**Input Format(s):** String \u003cbr\u003e\n**Input Parameters:** One-Dimensional (1D) \u003cbr\u003e\n\n### Output:\n\n**Output Type(s):** Amino Acid Sequence \u003cbr\u003e\n**Output Format:** Multi-FASTA (text file)\u003cbr\u003e\n**Output Parameters:** 1D \u003cbr\u003e\n\n### Software Integration:\n\n**Runtime Engine(s):**\n* Triton \u003cbr\u003e\n\n**Supported Hardware Microarchitecture Compatibility:** \u003cbr\u003e\n* NVIDIA Ampere \u003cbr\u003e\n* NVIDIA Lovelace \u003cbr\u003e\n* NVIDIA Turing \u003cbr\u003e\n\n**[Preferred/Supported] Operating System(s):** \u003cbr\u003e\n* Linux \u003cbr\u003e\n\n### Model Version(s):\n\nProteinMPNN 1.0.0 \u003cbr\u003e\n\n## Training \u0026 Evaluation:\n\n### Training Dataset:\n\n**Link:**\n[The Protein Data Bank](https://www.rcsb.org/) \u003cbr\u003e\n\n** Data Collection Method by dataset \u003cbr\u003e\n* Hybrid: Automatic, Human \u003cbr\u003e\n\nFor PDB dataset, scientists worldwide submit structural data\ndetermined by X-ray crystallography or cryo-electron microscopy (cryo-EM).\nThis includes atomic coordinates, experimental data, and metadata about the\nbiological macromolecules. \u003cbr\u003e\n\n** Labeling Method by dataset \u003cbr\u003e\n* Hybrid: Automatic, Human \u003cbr\u003e\n\nFor PDB dataset, expert biocurators review the submitted data to\nensure accuracy and completeness. This involves checking the plausibility of\nthe data and annotating it with relevant biological and chemical information.\nCATH 4.1 dataset is derived from the PDB dataset. The CATH\n(Class, Architecture, Topology, Homologous superfamily) database\nhierarchically classifies protein domain structures that are obtained from\nprotein structures deposited in the PDB. The data in CATH are specifically\nsourced from PDB files and include structures determined at a resolution of 4\nangstrom or better. The classification process involves both manual and\nautomated methods to ensure accurate domain identification and classification.\nFor ProteinMPNN, the data underwent quality filtering to ensure high accuracy,\nthis involved removing structures with low resolution and potential errors. \u003cbr\u003e\n\n**Properties (Quantity, Dataset Descriptions, Sensor(s)):** Model was trained by Institute for Protein Design. The dataset for training consisted of 23,358 sequences. Dataset: CATH 4.2, PDB. Sensors: X-ray crystallography, cryoEM.\u003cbr\u003e\n\n### Evaluation Dataset:\n\n** Data Collection Method by dataset \u003cbr\u003e\n* Automatic: random splits from PDB dataset. \u003cbr\u003e\n\n** Labeling Method by dataset \u003cbr\u003e\n* Automatic: random splits from PDB dataset. \u003cbr\u003e\n\nThe training, validation, and test splits were derived from protein assemblies\nin the PDB, which includes structures determined by X-ray\ncrystallography or cryo-electron microscopy (cryoEM). The dataset was divided\ninto random splits with 23,358 sequences for training, 1,464 for validation, and\n1,529 for testing.\u003cbr\u003e\n\n### Inference:\n\n**Engine:** Triton \u003cbr\u003e\n**Test Hardware:** \u003cbr\u003e\n* A100 \u003cbr\u003e\n* L40 \u003cbr\u003e\n* H100 \u003cbr\u003e\n\n### Ethical Considerations:\n\nNVIDIA believes Trustworthy AI is a shared responsibility and we have\nestablished policies and practices to enable development for a wide array of AI\napplications. When downloaded or used in accordance with our terms of service,\ndevelopers should work with their supporting model team to ensure this model\nmeets requirements for the relevant industry and use case and addresses\nunforeseen product misuse.\nPlease report security vulnerabilities or NVIDIA AI Concerns\n[here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/).\n"])</script><script>self.__next_f.push([1,"c9:Tc64,"])</script><script>self.__next_f.push([1,"## Start NIM\n\n1. Export `NGC_CLI_API_KEY` variable.\n\n```\nexport NGC_CLI_API_KEY=\u003cyour personal NGC key\u003e\n```\n\n2. NIM container automatically downloads models. To save time and bandwidth it\n is recommended to provide local cache directory. This way NIM will be able to\n reuse already downloaded models. Execute following command to setup cache\n directory.\n\n```bash\nexport LOCAL_NIM_CACHE=~/.cache/nim\nmkdir -p \"$LOCAL_NIM_CACHE\"\nsudo chmod 0777 -R \"$LOCAL_NIM_CACHE\"\n```\n\n3. Run the NIM container with the following commands.\n\n```bash\ndocker run -it \\\n --runtime=nvidia \\\n --gpus='\"device=0\"' \\\n -p 8000:8000 \\\n -e NGC_CLI_API_KEY \\\n -v \"$LOCAL_NIM_CACHE\":/home/nvs/.cache/nim \\\n nvcr.io/nim/ipd/proteinmpnn:1.0.0\n```\n\nThis command will start the NIM container and expose port 8000 for the user to interact with the NIM.\n\n4. Open a new terminal, leaving the terminal open with the just launched service. In the new terminal, wait until the health check end point returns `{\"status\":\"ready\"}` before proceeding. This may take a couple of minutes. You can use the following command to query the health check.\n\n```bash\ncurl http://localhost:8000/v1/health/ready\n```\n\n## Python client example\n\n1. Save following Python example to a file named `nim_client.py`.\n\n```python\n#!/usr/bin/env python3\nimport requests\nimport os\nimport json\nfrom pathlib import Path\n\ndef get_reduced_pdb():\n pdb = Path(\"1R42.pdb\")\n if not pdb.exists():\n pdb.write_text(requests.get(f\"https://files.rcsb.org/download/{pdb}\").text)\n lines = filter(lambda line: line.startswith(\"ATOM\"), pdb.read_text().split(\"\\n\"))\n return \"\\n\".join(list(lines)[:200])\n\nr = requests.post(\n url=\"http://localhost:8000/biology/ipd/proteinmpnn/predict\",\n json={\n \"input_pdb\": get_reduced_pdb(),\n \"ca_only\": False,\n \"use_soluble_model\": False,\n \"sampling_temp\": [0.1],\n },\n)\nprint(r, \"Saving to output.fa:\\n\", r.text[:200], \"...\")\nPath(\"output.fa\").write_text(json.loads(r.text)[\"mfasta\"])\n```\n\n2. Execute the example.\n\n```bash\nchmod +x nim_client.py\n\n./nim_client.py\n```\n\n3. The NIM saves results to the `output.fa` file in Multi-FASTA format. You can quickly view the file using the following command.\n\n```bash\ncat output.fa\n```\n\n## Shell client example\n\n1. Save the following Shell example to a file named `nim_client.sh`.\n\n```bash\n#!/usr/bin/env bash\nset -e\n\nURL=http://localhost:8000/biology/ipd/proteinmpnn/predict\n\nif [ ! -e 1R42.pdb ]; then curl -O https://files.rcsb.org/download/1R42.pdb; fi\n\npdb=$(cat 1R42.pdb | grep ^ATOM | head -n 200 | awk '{printf \"%s\\\\n\", $0}')\n\nrequest='{\n \"input_pdb\": \"'\"$pdb\"'\",\n \"ca_only\": false,\n \"use_soluble_model\": false,\n \"sampling_temp\": [0.1]\n}'\ncurl -H 'Content-Type: application/json' \\\n -d \"$request\" \"$URL\"\n```\n\n2. Execute the example.\n\n```bash\nchmod +x nim_client.sh\n\n./nim_client.sh\n```\n\n3. The NIM displays the results to the terminal in JSON format. You can configure the NIM to display the results, scores, and probabilities in the Multi-FASTA output format.\n\nFor more details on getting started with this NIM, visit the [NVIDIA NIM Docs](https://docs.nvidia.com/nim/index.html#bionemo).\n"])</script><script>self.__next_f.push([1,"ca:T183a,"])</script><script>self.__next_f.push([1,"## Model Overview\n\n### Description:\n\nESM2 is a state of the art language model for protein sequences. It outputs a numerical representation of input protein sequences that is suitable for downstream tasks. In particular, its output is used for protein folding in the ESMFold model. ESM2 comes in various sizes: 650M parameters, 3B parameters, and 15B parameters. ESM2 was developed and trained by [META](https://github.com/facebookresearch/esm). The larger models tend to result in more accurate results on downstream tasks, however they also have a longer runtime.\n\u003cbr\u003e\n\n### License\n\nMIT License\n\nCopyright (c) Meta Platforms, Inc. and affiliates.\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\nSOFTWARE.\n\nThis model is available for commercial use.\n\n### Third-Party Community Consideration\n\nThis model is not owned or developed by NVIDIA. This model has been developed and built to a third-party’s requirements for this application and use case; see link to Non-NVIDIA Model Card.\n\n### References:\n\n```\n@ARTICLE{rives2021esm,\n title = \"Biological structure and function emerge from scaling\n unsupervised learning to 250 million protein sequences\",\n author = \"Rives, Alexander and Meier, Joshua and Sercu, Tom and Goyal,\n Siddharth and Lin, Zeming and Liu, Jason and Guo, Demi and Ott,\n Myle and Zitnick, C Lawrence and Ma, Jerry and Fergus, Rob\",\n journal = \"Proc. Natl. Acad. Sci. U. S. A.\",\n volume = 118,\n number = 15,\n month = apr,\n year = 2021,\n keywords = \"deep learning; generative biology; protein language model;\n representation learning; synthetic biology\",\n language = \"en\",\n doi = {10.1073/pnas.2016239118}\n}\n\n\nFor the self-attention contact prediction:\n\n@article{rao2020transformer,\n author = {Rao, Roshan M and Meier, Joshua and Sercu,\n Tom and Ovchinnikov, Sergey and Rives, Alexander},\n title= {Transformer protein language models are unsupervised\n structure learners},\n year= {2020},\n doi= {10.1101/2020.12.15.422761},\n url= {https://www.biorxiv.org/content/10.1101/2020.12.15.422761v1},\n journal= {bioRxiv}\n}\n\n```\n\n\u003cbr\u003e\n\n### Model Architecture:\n\n**Architecture Type:** BERT with rotational embeddings\u003cbr\u003e\n**Network Architecture:** ESM2-650m \u003cbr\u003e\n\n### Input:\n\n**Input Type(s):** Protein Sequence \u003cbr\u003e\n**Input Format(s):** String \u003cbr\u003e\n**Input Parameters:** 1D \u003cbr\u003e\n**Other Properties Related to Input:** Protein Sequence matching the regular expression `^[ARNDCQEGHILKMFPSTWYVXBOU]*$` upto 1024 characters\u003cbr\u003e\n\n### Output:\n\n**Output Type(s):** Embeddings \u003cbr\u003e\n**Output Format:** Float 16 Array \u003cbr\u003e\n**Output Parameters:** 1D \u003cbr\u003e\n**Other Properties Related to Output:** NA \u003cbr\u003e\n\n### Software Integration:\n\n**Runtime Engine(s):**\n* [Not Applicable (N/A)- Name Platform If Multiple] \u003cbr\u003e\n\n**Supported Hardware Microarchitecture Compatibility:** \u003cbr\u003e\n* NVIDIA Ampere \u003cbr\u003e\n* L40 \u003cbr\u003e\n\n**[Preferred/Supported] Operating System(s):** \u003cbr\u003e\n* Linux \u003cbr\u003e\n\n### Model Version(s):\n\nESM2 \u003cbr\u003e\n\n## Training \u0026 Evaluation:\n\n### Training Dataset:\n\n**Link:**\n[UniRef50](https://www.uniprot.org/help/uniref) \u003cbr\u003e\n** Data Collection Method by dataset\n* Not Applicable \u003cbr\u003e\n\n** Labeling Method by dataset\n* Not Applicable \u003cbr\u003e\n\n**Properties (Quantity, Dataset Descriptions, Sensor(s)):** [UniRef50](https://www.uniprot.org/help/uniref), September 2021 version, is used for the training of ESM models. The training dataset was partitioned by randomly selecting 0.5% (≈ 250,000) sequences to form the validation set. The training set has sequences removed via the procedure described \u003cbr\u003e\n\n### Evaluation Dataset:\n\n[UniRef50](https://www.uniprot.org/help/uniref) \u003cbr\u003e\n** Data Collection Method by dataset \u003cbr\u003e\n* Not Applicable \u003cbr\u003e\n\n** Labeling Method by dataset \u003cbr\u003e\n* Not Applicable \u003cbr\u003e\n\n**Properties (Quantity, Dataset Descriptions, Sensor(s)):** [UniRef50](https://www.uniprot.org/help/uniref), September 2021 version, is used for the training of ESM models. The training dataset was partitioned by randomly selecting 0.5% (≈ 250,000) sequences to form the validation set. The training set has sequences removed via the procedure described \u003cbr\u003e\n\n### Inference:\n\n**Engine:** Triton \u003cbr\u003e\n**Test Hardware:** \u003cbr\u003e\n* [Other (Not Listed)] \u003cbr\u003e\n\n### Ethical Considerations:\n\nNVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their supporting model team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse. For more detailed information on ethical considerations for this model, please see the Model Card++ Explainability, Bias, Safety \u0026 Security, and Privacy Subcards. Please report security vulnerabilities or NVIDIA AI Concerns [here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/).\n\n**If anything is meant for internal-purposes only (including this statement and pre-filled content recommendations, please alert Trustworthy AI Product Manager or designee before publishing)\n"])</script><script>self.__next_f.push([1,"cb:T4a4,#!/usr/bin/env python3\nimport requests\nimport os\nfrom pathlib import Path\n\nkey = os.getenv(\"NVCF_RUN_KEY\") or input(\"Paste the Run Key: \")\n\nSEROTONIN_PROT_SEQ = \"MDILCEENTSLSSTTNSLMQLNDDTRLYSNDFNSGEANTSDAFNWTVDSENRTNLSCEGCLSPSCLSLLHLQEKNWSALLTAVVIILTIAGNILVIMAVSLEKKLQNATNYFLMSLAIADMLLGFLVMPVSMLTILYGYRWPLPSKLCAVWIYLDVLFSTASIMHLCAISLDRYVAIQNPIHHSRFNSRTKAFLKIIAVWTISVGISMPIPVFGLQDDSKVFKEGSCLLADDNFVLIGSFVSFFIPLTIMVITYFLTIKSLQKEATLCVSDLGTRAKLASFSFLPQSSLSSEKLFQRSIHREPGSYTGRRTMQSISNEQKACKVLGIVFFLFVVMWCPFFITNIMAVICKESCNEDVIGALLNVFVWIGYLSSAVNPLVYTLFNKTYRSAFSRYIQCQYKENKKPLQLILVNTIPALAYKSSQLQMGQKKNSKQDAKTTDNDCSMVALGKQHSEEASKDNSDGVNEKVSCV\"\nEMB_FORMAT = \"npz\"\n\nresponse = requests.post(\n url=\"https://health.api.nvidia.com/v1/biology/meta/esm2-650m\",\n\theaders={\n\t\t\"Content-Type\": \"application/json\",\n\t\t\"Authorization\": f\"Bearer {key}\"\n\t},\n\tjson={\n\t\t\"sequences\": [SEROTONIN_PROT_SEQ],\n \"format\": EMB_FORMAT,\n },\n)\n\nif response.status_code == 200:\n print(response)\n ext = \"zip\" if response.headers[\"Content-Type\"] == \"application/zip\" else EMB_FORMAT\n with open(Path(f\"output.{ext}\"), \"wb\") as fb:\n fb.write(response.content)\nelse:\n print(response, response.text)\ncc:T15dd,"])</script><script>self.__next_f.push([1,"## Model Overview\n\n### Description:\n\nAlphaFold2 is a deep learning model for protein structure prediction developed by the research group at DeepMind, an artificial intelligence (AI) research lab owned by Google (`jumper2021alphafold`). AlphaFold2 builds on the success of its predecessor, AlphaFold, and represents a significant breakthrough in the field of protein structure prediction. This model is available for commercial use.\n\u003cbr\u003e\n\n### Third-Party Community Consideration\n\nThis model is not owned or developed by NVIDIA. This model has been developed and built to a third-party’s requirements for this application and use case.\n\n#### License / Terms of Use\n\nThe AlphaFold2 code is released under the [Apache 2.0 License](https://github.com/google-deepmind/alphafold/blob/main/LICENSE). The model parameters are licensed under the [CC BY 4.0 License](https://github.com/google-deepmind/alphafold?tab=readme-ov-file#model-parameters).\n\n### References:\n\n```\n@ARTICLE{jumper2021alphafold,\n title = \"Highly accurate protein structure prediction with {AlphaFold}\",\n author = \"Jumper, John and Evans, Richard and Pritzel, Alexander and Green,\n Tim and Figurnov, Michael and Ronneberger, Olaf and\n Tunyasuvunakool, Kathryn and Bates, Russ and {\\v Z}{\\'\\i}dek,\n Augustin and Potapenko, Anna and Bridgland, Alex and Meyer,\n Clemens and Kohl, Simon A A and Ballard, Andrew J and Cowie,\n Andrew and Romera-Paredes, Bernardino and Nikolov, Stanislav and\n Jain, Rishub and Adler, Jonas and Back, Trevor and Petersen, Stig\n and Reiman, David and Clancy, Ellen and Zielinski, Michal and\n Steinegger, Martin and Pacholska, Michalina and Berghammer, Tamas\n and Bodenstein, Sebastian and Silver, David and Vinyals, Oriol\n and Senior, Andrew W and Kavukcuoglu, Koray and Kohli, Pushmeet\n and Hassabis, Demis\",\n journal = \"Nature\",\n volume = 596,\n number = 7873,\n pages = \"583--589\",\n month = aug,\n year = 2021,\n language = \"en\",\n doi = {10.1038/s41586-021-03819-2},\n}\n```\n\n\u003cbr\u003e\n\n### Model Architecture:\n\n**Architecture Type:** Protein Structure Prediction \u003cbr\u003e\n**Network Architecture:** AlphaFold2 \u003cbr\u003e\n\n**Input Type(s):** Protein Sequence, Relax Prediction (Default True) \u003cbr\u003e\n**Input Format(s):** String (less than or equal to 4096 characters), boolean \u003cbr\u003e\n**Input Parameters:** 1D \u003cbr\u003e\n**Other Properties Related to Input:** NA \u003cbr\u003e\n\n### Output:\n\n**Output Type(s):** Protein Structure(s) in PDB Format \u003cbr\u003e\n**Output Format:** PDB (text file)\u003cbr\u003e\n**Output Parameters:** 1D \u003cbr\u003e\n**Other Properties Related to Output:** Pose (num_atm_ x 3)\u003cbr\u003e\n\n### Software Integration:\n\n**Runtime Engine(s):**\n* Python \u003cbr\u003e\n\n**Supported Hardware Microarchitecture Compatibility:** \u003cbr\u003e\n* NVIDIA Ampere \u003cbr\u003e\n\n**[Preferred/Supported] Operating System(s):** \u003cbr\u003e\n* [Linux] \u003cbr\u003e\n\n### Model Version(s):\n\nAlphaFold2 2.3.2 \u003cbr\u003e\n\n## Training \u0026 Evaluation:\n\n### Training Dataset:\n\n**Link:** A description of the training dataset and relevant download links are available at [https://www.nature.com/articles/s41586-021-03819-2#data-availability](https://www.nature.com/articles/s41586-021-03819-2#data-availability). This data was not collected by NVIDIA. \u003cbr\u003e\n** Data Collection Method by dataset \u003cbr\u003e\n* See the description at [https://www.nature.com/articles/s41586-021-03819-2#data-availability](https://www.nature.com/articles/s41586-021-03819-2#data-availability). \u003cbr\u003e\n\n** Labeling Method by dataset \u003cbr\u003e\n* See the description at [https://www.nature.com/articles/s41586-021-03819-2#data-availability](https://www.nature.com/articles/s41586-021-03819-2#data-availability). \u003cbr\u003e\n\n**Properties (Quantity, Dataset Descriptions, Sensor(s)):**\nUniclust dataset of 355,993 sequences with the full MSAs. These predictions were then used to train a final model with identical hyperparameters, except for sampling examples 75% of the time from the Uniclust prediction set, with sub-sampled MSAs, and 25% of the time from the clustered PDB set.\n\u003cbr\u003e\n\n### Evaluation Dataset:\n\n**Link:** See the description at [https://www.nature.com/articles/s41586-021-03819-2#Sec10](https://www.nature.com/articles/s41586-021-03819-2#Sec10). \u003cbr\u003e\n** Data Collection Method by dataset \u003cbr\u003e\n* [Not Applicable] \u003cbr\u003e\n\n** Labeling Method by dataset \u003cbr\u003e\n* [Not Applicable] \u003cbr\u003e\n\n**Properties (Quantity, Dataset Descriptions, Sensor(s)):**\nUniclust dataset of 355,993 sequences with the full MSAs. These predictions were then used to train a final model with identical hyperparameters, except for sampling examples 75% of the time from the Uniclust prediction set, with sub-sampled MSAs, and 25% of the time from the clustered PDB set.\n\u003cbr\u003e\n\n### Inference:\n\n**Engine:** Python \u003cbr\u003e\n**Test Hardware:** \u003cbr\u003e\n* NVIDIA A6000 \u003cbr\u003e\n* NVIDIA A100 \u003cbr\u003e\n\n### Ethical Considerations:\n\nNVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their supporting model team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse. Please report security vulnerabilities or NVIDIA AI Concerns [here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/).\n\n**You are responsible for ensuring that your use of NVIDIA AI Foundation Models complies with all applicable laws.**\n"])</script><script>self.__next_f.push([1,"cd:T7539,"])</script><script>self.__next_f.push([1,"{\n \"pdbs\": [\n \"PARENT N/A\\nATOM 1 N MET A 1 12.501 2.331 -26.921 1.00 47.72 N \\nATOM 2 CA MET A 1 12.036 1.790 -25.647 1.00 50.64 C \\nATOM 3 C MET A 1 10.886 2.622 -25.090 1.00 50.01 C \\nATOM 4 CB MET A 1 13.182 1.737 -24.635 1.00 43.04 C \\nATOM 5 O MET A 1 11.032 3.828 -24.879 1.00 48.15 O \\nATOM 6 CG MET A 1 13.327 0.391 -23.944 1.00 41.60 C \\nATOM 7 SD MET A 1 14.560 0.428 -22.585 1.00 39.32 S \\nATOM 8 CE MET A 1 14.275 -1.206 -21.850 1.00 35.36 C \\nATOM 9 N SER A 2 9.707 2.634 -25.722 1.00 54.18 N \\nATOM 10 CA SER A 2 8.571 3.356 -25.157 1.00 55.29 C \\nATOM 11 C SER A 2 8.396 3.039 -23.675 1.00 54.83 C \\nATOM 12 CB SER A 2 7.288 3.015 -25.915 1.00 49.15 C \\nATOM 13 O SER A 2 8.428 1.873 -23.277 1.00 52.08 O \\nATOM 14 OG SER A 2 6.187 2.929 -25.027 1.00 48.74 O \\nATOM 15 N LEU A 3 9.218 3.712 -22.773 1.00 56.59 N \\nATOM 16 CA LEU A 3 8.914 3.579 -21.352 1.00 57.28 C \\nATOM 17 C LEU A 3 7.407 3.556 -21.119 1.00 57.34 C \\nATOM 18 CB LEU A 3 9.548 4.724 -20.558 1.00 52.72 C \\nATOM 19 O LEU A 3 6.702 4.494 -21.495 1.00 55.22 O \\nATOM 20 CG LEU A 3 11.023 4.558 -20.188 1.00 50.52 C \\nATOM 21 CD1 LEU A 3 11.657 5.918 -19.916 1.00 46.13 C \\nATOM 22 CD2 LEU A 3 11.170 3.641 -18.978 1.00 46.40 C \\nATOM 23 N LYS A 4 6.644 2.377 -21.470 1.00 56.17 N \\nATOM 24 CA LYS A 4 5.297 2.253 -20.921 1.00 56.33 C \\nATOM 25 C LYS A 4 5.160 3.037 -19.619 1.00 56.26 C \\nATOM 26 CB LYS A 4 4.946 0.783 -20.686 1.00 52.46 C \\nATOM 27 O LYS A 4 6.059 3.014 -18.777 1.00 54.00 O \\nATOM 28 CG LYS A 4 4.160 0.145 -21.822 1.00 50.74 C \\nATOM 29 CD LYS A 4 3.742 -1.280 -21.482 1.00 51.22 C \\nATOM 30 CE LYS A 4 2.972 -1.926 -22.626 1.00 46.00 C \\nATOM 31 NZ LYS A 4 2.570 -3.327 -22.301 1.00 41.10 N \\nATOM 32 N ARG A 5 4.654 4.355 -19.659 1.00 57.17 N \\nATOM 33 CA ARG A 5 4.370 5.118 -18.448 1.00 56.75 C \\nATOM 34 C ARG A 5 4.145 4.191 -17.258 1.00 57.30 C \\nATOM 35 CB ARG A 5 3.147 6.014 -18.652 1.00 54.00 C \\nATOM 36 O ARG A 5 3.305 3.291 -17.315 1.00 55.39 O \\nATOM 37 CG ARG A 5 3.418 7.241 -19.507 1.00 52.34 C \\nATOM 38 CD ARG A 5 2.248 8.215 -19.485 1.00 51.80 C \\nATOM 39 NE ARG A 5 2.490 9.368 -20.347 1.00 47.80 N \\nATOM 40 NH1 ARG A 5 0.476 10.400 -19.880 1.00 36.09 N \\nATOM 41 NH2 ARG A 5 1.963 11.379 -21.324 1.00 30.93 N \\nATOM 42 CZ ARG A 5 1.642 10.380 -20.515 1.00 48.53 C \\nATOM 43 N LYS A 6 5.076 3.542 -16.648 1.00 56.74 N \\nATOM 44 CA LYS A 6 4.941 3.003 -15.298 1.00 55.91 C \\nATOM 45 C LYS A 6 4.159 3.957 -14.400 1.00 57.02 C \\nATOM 46 CB LYS A 6 6.317 2.722 -14.692 1.00 53.22 C \\nATOM 47 O LYS A 6 4.437 5.158 -14.370 1.00 55.13 O \\nATOM 48 CG LYS A 6 7.043 1.544 -15.323 1.00 51.42 C \\nATOM 49 CD LYS A 6 8.240 1.111 -14.486 1.00 51.12 C \\nATOM 50 CE LYS A 6 8.985 -0.049 -15.132 1.00 46.58 C \\nATOM 51 NZ LYS A 6 10.148 -0.490 -14.305 1.00 40.34 N \\nATOM 52 N ASN A 7 2.844 3.954 -14.515 1.00 59.23 N \\nATOM 53 CA ASN A 7 2.185 4.649 -13.414 1.00 58.05 C \\nATOM 54 C ASN A 7 3.018 4.592 -12.137 1.00 59.52 C \\nATOM 55 CB ASN A 7 0.793 4.064 -13.167 1.00 55.24 C \\nATOM 56 O ASN A 7 3.423 3.513 -11.702 1.00 57.25 O \\nATOM 57 CG ASN A 7 -0.186 4.395 -14.276 1.00 52.37 C \\nATOM 58 ND2 ASN A 7 -0.992 3.415 -14.668 1.00 50.08 N \\nATOM 59 OD1 ASN A 7 -0.217 5.522 -14.777 1.00 53.79 O \\nATOM 60 N ILE A 8 4.069 5.352 -12.056 1.00 59.68 N \\nATOM 61 CA ILE A 8 4.815 5.542 -10.817 1.00 59.01 C \\nATOM 62 C ILE A 8 3.902 6.142 -9.751 1.00 59.98 C \\nATOM 63 CB ILE A 8 6.050 6.445 -11.034 1.00 55.49 C \\nATOM 64 O ILE A 8 3.251 7.163 -9.985 1.00 57.77 O \\nATOM 65 CG1 ILE A 8 6.987 5.827 -12.078 1.00 48.43 C \\nATOM 66 CG2 ILE A 8 6.785 6.683 -9.711 1.00 50.12 C \\nATOM 67 CD1 ILE A 8 8.131 6.738 -12.500 1.00 48.88 C \\nATOM 68 N ALA A 9 3.305 5.411 -8.843 1.00 61.62 N \\nATOM 69 CA ALA A 9 2.704 5.967 -7.633 1.00 60.50 C \\nATOM 70 C ALA A 9 3.767 6.566 -6.717 1.00 61.95 C \\nATOM 71 CB ALA A 9 1.909 4.894 -6.892 1.00 57.91 C \\nATOM 72 O ALA A 9 4.802 5.943 -6.467 1.00 59.91 O \\nATOM 73 N LEU A 10 4.029 7.816 -6.856 1.00 59.55 N \\nATOM 74 CA LEU A 10 4.825 8.505 -5.845 1.00 58.84 C \\nATOM 75 C LEU A 10 4.129 8.470 -4.489 1.00 59.62 C \\nATOM 76 CB LEU A 10 5.083 9.955 -6.262 1.00 55.09 C \\nATOM 77 O LEU A 10 3.007 8.963 -4.349 1.00 56.92 O \\nATOM 78 CG LEU A 10 6.506 10.287 -6.715 1.00 52.00 C \\nATOM 79 CD1 LEU A 10 6.495 10.832 -8.139 1.00 47.29 C \\nATOM 80 CD2 LEU A 10 7.153 11.285 -5.760 1.00 47.91 C \\nATOM 81 N ILE A 11 4.324 7.555 -3.640 1.00 63.93 N \\nATOM 82 CA ILE A 11 3.807 7.436 -2.281 1.00 62.81 C \\nATOM 83 C ILE A 11 4.630 8.311 -1.338 1.00 64.11 C \\nATOM 84 CB ILE A 11 3.820 5.968 -1.798 1.00 60.05 C \\nATOM 85 O ILE A 11 5.827 8.080 -1.152 1.00 62.31 O \\nATOM 86 CG1 ILE A 11 3.044 5.078 -2.775 1.00 55.32 C \\nATOM 87 CG2 ILE A 11 3.243 5.860 -0.383 1.00 56.55 C \\nATOM 88 CD1 ILE A 11 3.024 3.605 -2.388 1.00 56.02 C \\nATOM 89 N PRO A 12 4.236 9.559 -1.122 1.00 59.69 N \\nATOM 90 CA PRO A 12 4.957 10.421 -0.183 1.00 57.99 C \\nATOM 91 C PRO A 12 5.285 9.717 1.132 1.00 59.47 C \\nATOM 92 CB PRO A 12 3.985 11.582 0.047 1.00 55.24 C \\nATOM 93 O PRO A 12 4.386 9.199 1.800 1.00 56.72 O \\nATOM 94 CG PRO A 12 2.679 11.101 -0.497 1.00 52.39 C \\nATOM 95 CD PRO A 12 2.920 9.830 -1.261 1.00 51.89 C \\nATOM 96 N ALA A 13 6.303 8.725 1.183 1.00 58.14 N \\nATOM 97 CA ALA A 13 6.956 8.140 2.351 1.00 56.61 C \\nATOM 98 C ALA A 13 7.721 9.198 3.139 1.00 58.03 C \\nATOM 99 CB ALA A 13 7.895 7.014 1.927 1.00 54.18 C \\nATOM 100 O ALA A 13 8.747 9.705 2.677 1.00 56.02 O \\nATOM 101 N ALA A 14 7.310 10.425 3.224 1.00 55.08 N \\nATOM 102 CA ALA A 14 8.297 11.292 3.863 1.00 53.30 C \\nATOM 103 C ALA A 14 7.694 12.017 5.063 1.00 54.76 C \\nATOM 104 CB ALA A 14 8.849 12.301 2.858 1.00 49.07 C \\nATOM 105 O ALA A 14 6.582 12.545 4.983 1.00 51.84 O \\nATOM 106 N GLY A 15 7.542 11.287 6.272 1.00 56.09 N \\nATOM 107 CA GLY A 15 7.794 11.777 7.617 1.00 54.70 C \\nATOM 108 C GLY A 15 7.422 10.777 8.696 1.00 55.87 C \\nATOM 109 O GLY A 15 6.534 9.945 8.498 1.00 53.38 O \\nATOM 110 N ILE A 16 8.382 10.048 9.409 1.00 54.33 N \\nATOM 111 CA ILE A 16 8.033 9.496 10.713 1.00 52.91 C \\nATOM 112 C ILE A 16 6.988 10.383 11.386 1.00 54.37 C \\nATOM 113 CB ILE A 16 9.278 9.354 11.618 1.00 50.66 C \\nATOM 114 O ILE A 16 7.218 11.576 11.595 1.00 52.62 O \\nATOM 115 CG1 ILE A 16 10.421 8.679 10.852 1.00 45.57 C \\nATOM 116 CG2 ILE A 16 8.934 8.574 12.890 1.00 47.18 C \\nATOM 117 CD1 ILE A 16 11.747 8.668 11.601 1.00 43.25 C \\nATOM 118 N GLY A 17 5.897 10.652 10.712 1.00 51.05 N \\nATOM 119 CA GLY A 17 4.889 11.495 11.333 1.00 49.41 C \\nATOM 120 C GLY A 17 4.616 11.131 12.781 1.00 51.34 C \\nATOM 121 O GLY A 17 4.557 9.950 13.129 1.00 49.32 O \\nATOM 122 N VAL A 18 5.390 11.622 13.767 1.00 52.37 N \\nATOM 123 CA VAL A 18 5.180 11.695 15.209 1.00 51.47 C \\nATOM 124 C VAL A 18 3.749 11.281 15.545 1.00 52.74 C \\nATOM 125 CB VAL A 18 5.467 13.112 15.754 1.00 47.82 C \\nATOM 126 O VAL A 18 3.482 10.780 16.640 1.00 50.91 O \\nATOM 127 CG1 VAL A 18 5.921 13.049 17.211 1.00 40.43 C \\nATOM 128 CG2 VAL A 18 6.518 13.811 14.894 1.00 42.74 C \\nATOM 129 N ARG A 19 2.843 11.411 14.494 1.00 54.51 N \\nATOM 130 CA ARG A 19 1.471 11.191 14.939 1.00 53.31 C \\nATOM 131 C ARG A 19 1.173 9.702 15.081 1.00 54.54 C \\nATOM 132 CB ARG A 19 0.480 11.834 13.966 1.00 49.59 C \\nATOM 133 O ARG A 19 0.258 9.313 15.809 1.00 52.50 O \\nATOM 134 CG ARG A 19 0.116 13.268 14.315 1.00 46.93 C \\nATOM 135 CD ARG A 19 -1.015 13.792 13.441 1.00 47.92 C \\nATOM 136 NE ARG A 19 -1.345 15.178 13.759 1.00 41.79 N \\nATOM 137 NH1 ARG A 19 -3.052 15.344 12.211 1.00 32.33 N \\nATOM 138 NH2 ARG A 19 -2.521 17.138 13.535 1.00 28.40 N \\nATOM 139 CZ ARG A 19 -2.305 15.883 13.168 1.00 42.08 C \\nATOM 140 N PHE A 20 2.037 8.828 14.567 1.00 53.76 N \\nATOM 141 CA PHE A 20 1.640 7.435 14.728 1.00 52.52 C \\nATOM 142 C PHE A 20 2.579 6.711 15.685 1.00 53.62 C \\nATOM 143 CB PHE A 20 1.619 6.720 13.373 1.00 50.12 C \\nATOM 144 O PHE A 20 2.336 5.558 16.049 1.00 52.09 O \\nATOM 145 CG PHE A 20 0.410 7.041 12.536 1.00 47.89 C \\nATOM 146 CD1 PHE A 20 -0.794 6.379 12.747 1.00 45.18 C \\nATOM 147 CD2 PHE A 20 0.477 8.004 11.538 1.00 46.49 C \\nATOM 148 CE1 PHE A 20 -1.915 6.674 11.974 1.00 47.12 C \\nATOM 149 CE2 PHE A 20 -0.639 8.304 10.762 1.00 46.89 C \\nATOM 150 CZ PHE A 20 -1.833 7.637 10.981 1.00 45.52 C \\nATOM 151 N GLY A 21 3.306 7.533 16.434 1.00 57.48 N \\nATOM 152 CA GLY A 21 4.107 6.863 17.445 1.00 55.82 C \\nATOM 153 C GLY A 21 4.934 5.719 16.891 1.00 57.70 C \\nATOM 154 O GLY A 21 5.405 4.864 17.644 1.00 55.16 O \\nATOM 155 N ALA A 22 5.071 5.575 15.673 1.00 56.68 N \\nATOM 156 CA ALA A 22 5.774 4.435 15.093 1.00 55.11 C \\nATOM 157 C ALA A 22 7.162 4.838 14.602 1.00 56.79 C \\nATOM 158 CB ALA A 22 4.962 3.835 13.948 1.00 52.06 C \\nATOM 159 O ALA A 22 7.398 6.004 14.277 1.00 54.83 O \\nATOM 160 N ASP A 23 8.194 4.133 15.107 1.00 64.08 N \\nATOM 161 CA ASP A 23 9.572 4.078 14.630 1.00 63.11 C \\nATOM 162 C ASP A 23 9.624 3.822 13.126 1.00 64.36 C \\nATOM 163 CB ASP A 23 10.355 2.995 15.375 1.00 59.64 C \\nATOM 164 O ASP A 23 10.706 3.693 12.549 1.00 62.57 O \\nATOM 165 CG ASP A 23 10.227 3.103 16.884 1.00 56.58 C \\nATOM 166 OD1 ASP A 23 10.042 4.225 17.402 1.00 55.54 O \\nATOM 167 OD2 ASP A 23 10.316 2.056 17.562 1.00 58.07 O \\nATOM 168 N LYS A 24 8.455 3.717 12.487 1.00 67.05 N \\nATOM 169 CA LYS A 24 8.508 3.334 11.079 1.00 65.58 C \\nATOM 170 C LYS A 24 7.828 4.379 10.199 1.00 66.66 C \\nATOM 171 CB LYS A 24 7.854 1.967 10.869 1.00 63.36 C \\nATOM 172 O LYS A 24 6.937 5.098 10.656 1.00 63.65 O \\nATOM 173 CG LYS A 24 8.521 0.837 11.639 1.00 60.44 C \\nATOM 174 CD LYS A 24 7.852 -0.502 11.357 1.00 59.53 C \\nATOM 175 CE LYS A 24 8.471 -1.622 12.184 1.00 54.94 C \\nATOM 176 NZ LYS A 24 7.733 -2.909 12.012 1.00 48.19 N \\nATOM 177 N PRO A 25 8.378 4.698 8.980 1.00 72.42 N \\nATOM 178 CA PRO A 25 7.719 5.610 8.041 1.00 71.65 C \\nATOM 179 C PRO A 25 6.249 5.265 7.817 1.00 72.81 C \\nATOM 180 CB PRO A 25 8.525 5.431 6.752 1.00 70.34 C \\nATOM 181 O PRO A 25 5.866 4.096 7.900 1.00 70.73 O \\nATOM 182 CG PRO A 25 9.826 4.841 7.193 1.00 67.60 C \\nATOM 183 CD PRO A 25 9.587 4.038 8.439 1.00 66.12 C \\nATOM 184 N LYS A 26 5.283 6.270 7.722 1.00 73.08 N \\nATOM 185 CA LYS A 26 3.827 6.180 7.685 1.00 72.63 C \\nATOM 186 C LYS A 26 3.367 5.116 6.692 1.00 73.79 C \\nATOM 187 CB LYS A 26 3.214 7.534 7.323 1.00 70.90 C \\nATOM 188 O LYS A 26 2.394 4.402 6.945 1.00 73.26 O \\nATOM 189 CG LYS A 26 3.306 8.571 8.432 1.00 66.73 C \\nATOM 190 CD LYS A 26 2.631 9.877 8.033 1.00 63.11 C \\nATOM 191 CE LYS A 26 2.752 10.928 9.129 1.00 56.23 C \\nATOM 192 NZ LYS A 26 2.143 12.229 8.719 1.00 51.14 N \\nATOM 193 N GLN A 27 4.004 5.040 5.619 1.00 74.47 N \\nATOM 194 CA GLN A 27 3.545 4.126 4.578 1.00 74.03 C \\nATOM 195 C GLN A 27 3.680 2.673 5.023 1.00 75.08 C \\nATOM 196 CB GLN A 27 4.326 4.352 3.282 1.00 72.50 C \\nATOM 197 O GLN A 27 3.068 1.778 4.435 1.00 73.98 O \\nATOM 198 CG GLN A 27 5.800 3.985 3.380 1.00 69.45 C \\nATOM 199 CD GLN A 27 6.665 5.146 3.836 1.00 66.53 C \\nATOM 200 NE2 GLN A 27 7.945 5.106 3.484 1.00 61.05 N \\nATOM 201 OE1 GLN A 27 6.186 6.071 4.499 1.00 64.36 O \\nATOM 202 N TYR A 28 4.486 2.408 6.120 1.00 77.28 N \\nATOM 203 CA TYR A 28 4.684 1.029 6.551 1.00 77.08 C \\nATOM 204 C TYR A 28 3.824 0.708 7.767 1.00 77.45 C \\nATOM 205 CB TYR A 28 6.160 0.772 6.872 1.00 75.60 C \\nATOM 206 O TYR A 28 3.894 -0.396 8.311 1.00 76.21 O \\nATOM 207 CG TYR A 28 7.063 0.827 5.664 1.00 73.99 C \\nATOM 208 CD1 TYR A 28 6.847 -0.008 4.570 1.00 72.59 C \\nATOM 209 CD2 TYR A 28 8.134 1.713 5.614 1.00 73.01 C \\nATOM 210 CE1 TYR A 28 7.678 0.038 3.455 1.00 71.16 C \\nATOM 211 CE2 TYR A 28 8.971 1.767 4.505 1.00 71.93 C \\nATOM 212 OH TYR A 28 9.561 0.977 2.331 1.00 69.53 O \\nATOM 213 CZ TYR A 28 8.735 0.927 3.432 1.00 66.43 C \\nATOM 214 N VAL A 29 3.056 1.727 8.204 1.00 77.93 N \\nATOM 215 CA VAL A 29 2.120 1.461 9.291 1.00 77.90 C \\nATOM 216 C VAL A 29 1.004 0.542 8.799 1.00 79.01 C \\nATOM 217 CB VAL A 29 1.524 2.768 9.860 1.00 76.49 C \\nATOM 218 O VAL A 29 0.498 0.710 7.687 1.00 78.77 O \\nATOM 219 CG1 VAL A 29 0.448 2.462 10.901 1.00 72.72 C \\nATOM 220 CG2 VAL A 29 2.624 3.638 10.463 1.00 72.65 C \\nATOM 221 N GLU A 30 0.558 -0.456 9.611 1.00 78.48 N \\nATOM 222 CA GLU A 30 -0.443 -1.461 9.265 1.00 78.57 C \\nATOM 223 C GLU A 30 -1.843 -1.006 9.667 1.00 79.17 C \\nATOM 224 CB GLU A 30 -0.114 -2.800 9.931 1.00 76.54 C \\nATOM 225 O GLU A 30 -2.036 -0.462 10.757 1.00 78.29 O \\nATOM 226 CG GLU A 30 1.134 -3.472 9.376 1.00 72.78 C \\nATOM 227 CD GLU A 30 1.473 -4.778 10.075 1.00 70.99 C \\nATOM 228 OE1 GLU A 30 0.938 -5.033 11.178 1.00 68.94 O \\nATOM 229 OE2 GLU A 30 2.281 -5.553 9.517 1.00 65.31 O \\nATOM 230 N ILE A 31 -2.732 -1.003 8.730 1.00 79.81 N \\nATOM 231 CA ILE A 31 -4.173 -0.906 8.940 1.00 80.21 C \\nATOM 232 C ILE A 31 -4.838 -2.232 8.576 1.00 81.01 C \\nATOM 233 CB ILE A 31 -4.788 0.246 8.114 1.00 78.02 C \\nATOM 234 O ILE A 31 -4.964 -2.567 7.396 1.00 80.31 O \\nATOM 235 CG1 ILE A 31 -4.087 1.570 8.439 1.00 71.79 C \\nATOM 236 CG2 ILE A 31 -6.295 0.348 8.367 1.00 71.33 C \\nATOM 237 CD1 ILE A 31 -4.572 2.748 7.606 1.00 68.69 C \\nATOM 238 N GLY A 32 -5.258 -3.027 9.817 1.00 80.95 N \\nATOM 239 CA GLY A 32 -5.635 -4.404 9.541 1.00 81.75 C \\nATOM 240 C GLY A 32 -4.460 -5.275 9.134 1.00 79.05 C \\nATOM 241 O GLY A 32 -3.422 -5.274 9.798 1.00 73.40 O \\nATOM 242 N SER A 33 -4.521 -6.074 8.047 1.00 82.85 N \\nATOM 243 CA SER A 33 -3.462 -6.968 7.590 1.00 84.02 C \\nATOM 244 C SER A 33 -2.611 -6.309 6.509 1.00 82.91 C \\nATOM 245 CB SER A 33 -4.055 -8.274 7.058 1.00 78.34 C \\nATOM 246 O SER A 33 -1.711 -6.939 5.950 1.00 79.75 O \\nATOM 247 OG SER A 33 -4.887 -8.029 5.937 1.00 68.18 O \\nATOM 248 N LYS A 34 -2.932 -5.116 6.176 1.00 85.34 N \\nATOM 249 CA LYS A 34 -2.201 -4.485 5.081 1.00 84.95 C \\nATOM 250 C LYS A 34 -1.574 -3.167 5.527 1.00 85.12 C \\nATOM 251 CB LYS A 34 -3.125 -4.247 3.886 1.00 83.34 C \\nATOM 252 O LYS A 34 -2.094 -2.496 6.420 1.00 83.10 O \\nATOM 253 CG LYS A 34 -3.633 -5.525 3.232 1.00 78.44 C \\nATOM 254 CD LYS A 34 -4.507 -5.224 2.021 1.00 75.88 C \\nATOM 255 CE LYS A 34 -5.014 -6.501 1.366 1.00 70.89 C \\nATOM 256 NZ LYS A 34 -5.878 -6.211 0.182 1.00 63.91 N \\nATOM 257 N THR A 35 -0.405 -2.863 4.935 1.00 81.15 N \\nATOM 258 CA THR A 35 0.219 -1.568 5.181 1.00 80.99 C \\nATOM 259 C THR A 35 -0.504 -0.465 4.413 1.00 81.04 C \\nATOM 260 CB THR A 35 1.708 -1.581 4.787 1.00 79.53 C \\nATOM 261 O THR A 35 -1.241 -0.742 3.465 1.00 79.37 O \\nATOM 262 CG2 THR A 35 2.451 -2.715 5.485 1.00 75.12 C \\nATOM 263 OG1 THR A 35 1.819 -1.753 3.369 1.00 76.52 O \\nATOM 264 N VAL A 36 -0.411 0.819 4.846 1.00 80.11 N \\nATOM 265 CA VAL A 36 -0.934 1.965 4.110 1.00 79.63 C \\nATOM 266 C VAL A 36 -0.466 1.903 2.658 1.00 80.06 C \\nATOM 267 CB VAL A 36 -0.500 3.300 4.754 1.00 78.52 C \\nATOM 268 O VAL A 36 -1.251 2.137 1.736 1.00 78.93 O \\nATOM 269 CG1 VAL A 36 -0.881 4.480 3.862 1.00 75.72 C \\nATOM 270 CG2 VAL A 36 -1.124 3.451 6.140 1.00 75.36 C \\nATOM 271 N LEU A 37 0.847 1.469 2.453 1.00 78.80 N \\nATOM 272 CA LEU A 37 1.378 1.370 1.098 1.00 78.45 C \\nATOM 273 C LEU A 37 0.594 0.350 0.280 1.00 79.14 C \\nATOM 274 CB LEU A 37 2.860 0.986 1.130 1.00 77.10 C \\nATOM 275 O LEU A 37 0.245 0.609 -0.874 1.00 78.31 O \\nATOM 276 CG LEU A 37 3.551 0.837 -0.227 1.00 73.70 C \\nATOM 277 CD1 LEU A 37 3.479 2.147 -1.005 1.00 70.12 C \\nATOM 278 CD2 LEU A 37 4.999 0.396 -0.045 1.00 70.38 C \\nATOM 279 N GLU A 38 0.326 -0.772 0.910 1.00 81.00 N \\nATOM 280 CA GLU A 38 -0.398 -1.831 0.214 1.00 80.69 C \\nATOM 281 C GLU A 38 -1.823 -1.399 -0.120 1.00 80.97 C \\nATOM 282 CB GLU A 38 -0.421 -3.111 1.054 1.00 79.72 C \\nATOM 283 O GLU A 38 -2.351 -1.745 -1.179 1.00 79.93 O \\nATOM 284 CG GLU A 38 0.907 -3.854 1.079 1.00 78.36 C \\nATOM 285 CD GLU A 38 0.922 -5.025 2.048 1.00 77.16 C \\nATOM 286 OE1 GLU A 38 0.633 -4.822 3.250 1.00 75.05 O \\nATOM 287 OE2 GLU A 38 1.225 -6.154 1.603 1.00 73.48 O \\nATOM 288 N HIS A 39 -2.457 -0.687 0.816 1.00 81.53 N \\nATOM 289 CA HIS A 39 -3.795 -0.168 0.558 1.00 81.42 C \\nATOM 290 C HIS A 39 -3.799 0.775 -0.641 1.00 81.14 C \\nATOM 291 CB HIS A 39 -4.338 0.552 1.793 1.00 80.11 C \\nATOM 292 O HIS A 39 -4.679 0.690 -1.500 1.00 79.71 O \\nATOM 293 CG HIS A 39 -4.855 -0.374 2.848 1.00 77.94 C \\nATOM 294 CD2 HIS A 39 -4.368 -0.687 4.072 1.00 76.33 C \\nATOM 295 ND1 HIS A 39 -6.012 -1.106 2.694 1.00 75.15 N \\nATOM 296 CE1 HIS A 39 -6.215 -1.832 3.781 1.00 75.03 C \\nATOM 297 NE2 HIS A 39 -5.232 -1.595 4.633 1.00 74.02 N \\nATOM 298 N VAL A 40 -2.828 1.745 -0.721 1.00 78.76 N \\nATOM 299 CA VAL A 40 -2.721 2.734 -1.789 1.00 78.03 C \\nATOM 300 C VAL A 40 -2.453 2.031 -3.118 1.00 78.38 C \\nATOM 301 CB VAL A 40 -1.608 3.766 -1.498 1.00 76.80 C \\nATOM 302 O VAL A 40 -3.062 2.365 -4.138 1.00 76.89 O \\nATOM 303 CG1 VAL A 40 -1.357 4.647 -2.720 1.00 72.40 C \\nATOM 304 CG2 VAL A 40 -1.977 4.619 -0.286 1.00 72.27 C \\nATOM 305 N LEU A 41 -1.533 1.030 -3.081 1.00 77.58 N \\nATOM 306 CA LEU A 41 -1.216 0.308 -4.309 1.00 77.11 C \\nATOM 307 C LEU A 41 -2.433 -0.455 -4.819 1.00 77.56 C \\nATOM 308 CB LEU A 41 -0.052 -0.659 -4.077 1.00 75.74 C \\nATOM 309 O LEU A 41 -2.640 -0.564 -6.030 1.00 76.53 O \\nATOM 310 CG LEU A 41 1.326 -0.026 -3.878 1.00 72.48 C \\nATOM 311 CD1 LEU A 41 2.355 -1.095 -3.528 1.00 69.28 C \\nATOM 312 CD2 LEU A 41 1.748 0.741 -5.127 1.00 69.52 C \\nATOM 313 N GLY A 42 -3.206 -1.059 -3.937 1.00 80.25 N \\nATOM 314 CA GLY A 42 -4.423 -1.754 -4.325 1.00 79.71 C \\nATOM 315 C GLY A 42 -5.423 -0.859 -5.030 1.00 79.88 C \\nATOM 316 O GLY A 42 -6.161 -1.313 -5.907 1.00 78.27 O \\nATOM 317 N ILE A 43 -5.531 0.394 -4.566 1.00 78.63 N \\nATOM 318 CA ILE A 43 -6.434 1.357 -5.189 1.00 77.91 C \\nATOM 319 C ILE A 43 -6.013 1.597 -6.637 1.00 77.95 C \\nATOM 320 CB ILE A 43 -6.461 2.691 -4.411 1.00 76.47 C \\nATOM 321 O ILE A 43 -6.860 1.694 -7.528 1.00 76.49 O \\nATOM 322 CG1 ILE A 43 -7.132 2.500 -3.046 1.00 73.27 C \\nATOM 323 CG2 ILE A 43 -7.173 3.776 -5.224 1.00 72.94 C \\nATOM 324 CD1 ILE A 43 -6.943 3.672 -2.093 1.00 70.53 C \\nATOM 325 N PHE A 44 -4.748 1.699 -6.863 1.00 73.12 N \\nATOM 326 CA PHE A 44 -4.249 1.975 -8.205 1.00 72.40 C \\nATOM 327 C PHE A 44 -4.421 0.758 -9.107 1.00 72.33 C \\nATOM 328 CB PHE A 44 -2.774 2.388 -8.157 1.00 70.49 C \\nATOM 329 O PHE A 44 -4.595 0.898 -10.319 1.00 70.65 O \\nATOM 330 CG PHE A 44 -2.551 3.782 -7.636 1.00 66.97 C \\nATOM 331 CD1 PHE A 44 -2.949 4.888 -8.377 1.00 63.88 C \\nATOM 332 CD2 PHE A 44 -1.944 3.986 -6.404 1.00 64.30 C \\nATOM 333 CE1 PHE A 44 -2.743 6.180 -7.897 1.00 61.63 C \\nATOM 334 CE2 PHE A 44 -1.736 5.274 -5.917 1.00 60.85 C \\nATOM 335 CZ PHE A 44 -2.135 6.369 -6.666 1.00 60.58 C \\nATOM 336 N GLU A 45 -4.220 -0.483 -8.572 1.00 73.09 N \\nATOM 337 CA GLU A 45 -4.439 -1.686 -9.370 1.00 72.37 C \\nATOM 338 C GLU A 45 -5.852 -1.718 -9.943 1.00 72.92 C \\nATOM 339 CB GLU A 45 -4.182 -2.941 -8.532 1.00 69.91 C \\nATOM 340 O GLU A 45 -6.084 -2.302 -11.004 1.00 71.77 O \\nATOM 341 CG GLU A 45 -2.707 -3.234 -8.298 1.00 65.37 C \\nATOM 342 CD GLU A 45 -2.469 -4.459 -7.430 1.00 62.84 C \\nATOM 343 OE1 GLU A 45 -3.437 -4.968 -6.820 1.00 61.26 O \\nATOM 344 OE2 GLU A 45 -1.305 -4.913 -7.358 1.00 57.67 O \\nATOM 345 N ARG A 46 -6.746 -1.213 -9.196 1.00 72.48 N \\nATOM 346 CA ARG A 46 -8.117 -1.239 -9.693 1.00 71.19 C \\nATOM 347 C ARG A 46 -8.294 -0.274 -10.861 1.00 70.30 C \\nATOM 348 CB ARG A 46 -9.102 -0.893 -8.574 1.00 68.43 C \\nATOM 349 O ARG A 46 -9.281 -0.356 -11.596 1.00 67.62 O \\nATOM 350 CG ARG A 46 -9.252 -1.984 -7.526 1.00 64.68 C \\nATOM 351 CD ARG A 46 -10.310 -1.630 -6.490 1.00 62.70 C \\nATOM 352 NE ARG A 46 -9.869 -1.955 -5.137 1.00 52.56 N \\nATOM 353 NH1 ARG A 46 -11.980 -1.859 -4.203 1.00 46.86 N \\nATOM 354 NH2 ARG A 46 -10.165 -2.358 -2.895 1.00 43.74 N \\nATOM 355 CZ ARG A 46 -10.672 -2.057 -4.082 1.00 57.43 C \\nATOM 356 N HIS A 47 -7.201 0.509 -11.001 1.00 63.25 N \\nATOM 357 CA HIS A 47 -7.372 1.411 -12.134 1.00 63.43 C \\nATOM 358 C HIS A 47 -6.377 1.094 -13.245 1.00 61.36 C \\nATOM 359 CB HIS A 47 -7.216 2.866 -11.688 1.00 58.29 C \\nATOM 360 O HIS A 47 -6.706 1.206 -14.429 1.00 58.05 O \\nATOM 361 CG HIS A 47 -8.300 3.331 -10.768 1.00 54.95 C \\nATOM 362 CD2 HIS A 47 -8.262 3.709 -9.469 1.00 54.55 C \\nATOM 363 ND1 HIS A 47 -9.615 3.444 -11.165 1.00 53.98 N \\nATOM 364 CE1 HIS A 47 -10.340 3.874 -10.146 1.00 50.05 C \\nATOM 365 NE2 HIS A 47 -9.543 4.042 -9.105 1.00 45.43 N \\nTER 366 HIS A 47\\nEND\\n\"\n ]\n}"])</script><script>self.__next_f.push([1,"ce:T923,"])</script><script>self.__next_f.push([1,"#!/usr/bin/env bash\nif [ \"$NVCF_RUN_KEY\" = \"\" ]; then read -p \"Paste Run Key: \" NVCF_RUN_KEY; fi\nURL=${URL:-https://health.api.nvidia.com/v1/biology/deepmind/alphafold2}\nSTATUS_URL=${STATUS_URL:-https://health.api.nvidia.com/v1/status}\n\nsequence=\"MVPSAGQLALFALGIVLAACQALENSTSPLSADPPVAAAVVSHFNDCPDSHTQFCFHGTCRFLVQED\"\\\n\"KPACVCHSGYVGARCEHADLLAVVAASQKKQAITALVVVSIVALAVLIITCVLIHCCQVRKHCEWCRALICRHEKP\"\\\n\"SALLKGRTACCHSETVV\"\nrequest_body='{\n \"sequence\": \"'$sequence'\",\n \"algorithm\": \"mmseqs2\",\n \"e_value\": 0.0001,\n \"iterations\": 1,\n \"databases\": [\"uniref90\", \"small_bfd\", \"mgnify\"],\n \"relax_prediction\": true\n}'\noutput_file=output.json\n\n# Initial request\necho \"Making request...\"\nresponse=$(curl -s -D /dev/stderr --fail-with-body \\\n -H \"content-type: application/json\" \\\n -H \"Authorization: Bearer $NVCF_RUN_KEY\" \\\n -H \"NVCF-POLL-SECONDS: 1\" \\\n --request POST \\\n --data \"$request_body\" \\\n \"$URL\" 2\u003e\u00261 1\u003e $output_file)\n\n# Extract HTTP status code\nhttp_status=$(echo \"$response\" | awk '{print $2;exit}')\n\n# Check the status code\nif [ \"$http_status\" -eq 200 ]; then\n echo \"Saved response to file: $output_file\"\nelif [ \"$http_status\" -eq 202 ]; then\n echo \"Request accepted...\"\n # Extract nvcf-reqid header\n req_id=$(echo \"$response\" | grep -i \"nvcf-reqid:\" | awk '{print $2}' | tr -d '\\r')\n\n # Poll the /status endpoint\n while true; do\n echo \"Polling for response...\"\n status_response=$(curl -s -D /dev/stderr --fail-with-body \\\n -H \"content-type: application/json\" \\\n -H \"Authorization: Bearer $NVCF_RUN_KEY\" \\\n -H \"NVCF-POLL-SECONDS: 5\" \\\n --request GET \\\n \"${STATUS_URL}/${req_id}\" 2\u003e\u00261 1\u003e $output_file)\n\n status_http_status=$(echo \"$status_response\" | awk '{print $2;exit}')\n\n if [ \"$status_http_status\" -eq 200 ]; then\n echo \"Saved response to file: $output_file\"\n break\n elif [ \"$status_http_status\" -ne 202 ]; then\n echo \"Unexpected HTTP status: $status_http_status\"\n echo \"Response: $status_response\"\n exit 1\n fi\n\n # Wait before polling again\n sleep 5\n done\nelse\n echo \"Unexpected HTTP status: $http_status\"\n echo \"Response: $response\"\n exit 1\nfi\n"])</script><script>self.__next_f.push([1,"cf:T700,#!/usr/bin/env python3\nimport os\nimport requests\nimport time\nfrom pathlib import Path\n\n# Variables\nkey = os.getenv(\"NVCF_RUN_KEY\") or input(\"Paste the Run Key: \")\nurl = os.getenv(\"URL\", \"https://health.api.nvidia.com/v1/biology/deepmind/alphafold2\")\nstatus_url = os.getenv(\"STATUS_URL\", \"https://health.api.nvidia.com/v1/status\")\n\nsequence = (\"MVPSAGQLALFALGIVLAACQALENSTSPLSADPPVAAAVVSHFNDCPDSHTQFCFHGTCRFL\"\n \"VQEDKPACVCHSGYVGARCEHADLLAVVAASQKKQAITALVVVSIVALAVLIITCVLIHCCQVRKHCEWCR\"\n \"ALICRHEKPSALLKGRTACCHSETVV\"\n)\noutput_file = Path(\"output.json\")\n\n# Initial request\nheaders = {\n \"content-type\": \"application/json\",\n \"Authorization\": f\"Bearer {key}\",\n \"NVCF-POLL-SECONDS\": \"5\",\n}\ndata = {\n \"sequence\": sequence,\n \"algorithm\": \"mmseqs2\",\n \"e_value\": 0.0001,\n \"iterations\": 1,\n \"databases\": [\"uniref90\", \"small_bfd\", \"mgnify\"],\n \"relax_prediction\": True,\n}\n\nprint(\"Making request...\")\nresponse = requests.post(url, headers=headers, json=data)\n\n# Check the status code\nif response.status_code == 200:\n output_file.write_text(response.text)\n print(f\"Response output to file: {output_file}\")\nelif response.status_code == 202:\n print(\"Request accepted...\")\n # Extract reqId header\n req_id = response.headers.get(\"nvcf-reqid\")\n\n # Poll the /status endpoint\n while True:\n print(\"Polling for response...\")\n status_response = requests.get(f\"{status_url}/{req_id}\", headers=headers)\n\n if status_response.status_code != 202:\n output_file.write_text(status_response.text)\n print(f\"Response output to file: {output_file}\")\n break\n\n # Wait before polling again\n time.sleep(5)\nelse:\n print(f\"Unexpected HTTP status: {response.status_code}\")\n print(f\"Response: {response.text}\")\nd0:Taec,"])</script><script>self.__next_f.push([1,"## Start NIM\n\n1. Export `NGC_API_KEY` variable.\n\n```\nexport NGC_API_KEY=\u003cyour personal NGC key\u003e\n```\n\n2. The NIM container automatically downloads any required models. To save time and bandwidth it\n is recommended to provide a local cache directory. This way the NIM will be able to\n reuse any already downloaded models. Execute the following command to setup the cache\n directory:\n\n```bash\nexport LOCAL_NIM_CACHE=~/.cache/nim\nmkdir -p $LOCAL_NIM_CACHE\n```\n\n3. Run the NIM container with the following commands.\n\n```bash\ndocker run -it \\\n --runtime=nvidia \\\n -p 8000:8000 \\\n -e NGC_API_KEY \\\n -v $LOCAL_NIM_CACHE:/opt/nim/.cache \\\n nvcr.io/nim/deepmind/alphafold2:2.0.0\n```\n\nThis command will start the NIM container and expose port 8000 for the user to interact with the NIM.\n\n4. Open a new terminal, leaving the terminal open with the just launched service. In the new terminal, wait until the health check end point returns `{\"status\":\"ready\"}` before proceeding. This may take a couple of minutes. You can use the following command to query the health check.\n\n```bash\ncurl http://localhost:8000/v1/health/ready\n```\n\n## Python client example\n\n1. Save following Python example to a file named `nim_client.py`.\n\n```python\nimport requests\nimport json\n\nurl = \"http://localhost:8000/protein-structure/alphafold2/predict-structure-from-sequence\" # Replace with the actual URL\nsequence = \"MNVIDIAIAMAI\" # Replace with the actual sequence value\n\nheaders = {\n \"content-type\": \"application/json\"\n}\n\ndata = {\n \"sequence\": sequence,\n \"databases\": [\"small_bfd\"],\n \"e_value\": 0.000001,\n \"algorithm\": \"mmseqs2\",\n \"num_predictions_per_model\" : 1,\n \"relax_prediction\": False,\n}\n\nresponse = requests.post(url, headers=headers, data=json.dumps(data))\n\n# Check if the request was successful\nif response.ok:\n with open(\"output.pdb\", \"w\") as ofi:\n ofi.write(json.dumps(response.json()))\n print(\"Request succeeded:\", response.json())\nelse:\n print(\"Request failed:\", response.status_code, response.text)\n```\n\n2. Execute the example.\n\n```bash\npython nim_client.py\n```\n\n3. The resulting PDB structure will be returned and written to `output.pdb`.\n\n```bash\ncat output.pdb\n```\n\n## Shell client example\n\n1. Save the following Shell example to a file named `nim_client.sh`.\n\n```bash\n#!/usr/bin/env bash\nset -e\n\nURL=http://localhost:8000/protein-structure/alphafold2/predict-structure-from-sequence\n\nrequest='{\n \"sequence\": \"MNVIDIAIAMAI\"\n}'\ncurl -H 'Content-Type: application/json' \\\n -d \"$request\" \"$URL\"\n```\n\n2. Execute the example.\n\n```bash\nchmod +x nim_client.sh\n\n./nim_client.sh\n```\n\n3. Results will be printed on the terminal in JSON format. You will be able\n to see the PDB formatted output; you can also use curl to save the output directly to file.\n"])</script><script>self.__next_f.push([1,"d1:T1578,"])</script><script>self.__next_f.push([1,"## Model Overview\n\n### Description:\n\nRFdiffusion (RoseTTAFold Diffusion) is a generative model that creates novel protein structures for protein scaffolding and protein binder design tasks. This model generates entirely new protein backbones and designs proteins that can be specifically tailored to bind to target molecules.\u003cbr\u003e\n\nThis model is available for commercial use.\u003cbr\u003e\n\n### Third-Party Community Consideration\n\nThis model is not owned or developed by NVIDIA. This model has been developed\nand built to a third-party’s requirements for this application and use case; see link to Non-NVIDIA [GitHub Model Card](https://github.com/RosettaCommons/RFdiffusion). \u003cbr\u003e\n\n#### License/Terms of Use:\n\nThis model is released under the\n[BSD License](https://github.com/RosettaCommons/RFdiffusion/blob/820bfdfaded8c260b962dc40a3171eae316b6ce0/LICENSE).\n\n**You are responsible for ensuring that your use of NVIDIA AI Foundation Models\ncomplies with all applicable laws.**\n\n### References:\n\n```\n@ARTICLE{nat2023rfdiffusion,\n title = \"De novo design of protein structure and function with RFdiffusion\",\n author = \"Watson, Joseph L. and Juergens, David and Bennett, Nathaniel R.\n and Trippe, Brian L. and Yim, Jason and Eisenach, Helen E. and Ahern, Woody\n and Borst, Andrew J. and Ragotte, Robert J. and Milles, Lukas F. and Wicky,\n Basile I. M. and Hanikel, Nikita and Pellock, Samuel J. and Courbet, Alexis\n and Sheffler, William and Wang, Jue and Venkatesh, Preetham and Sappington,\n Isaac and Torres, Susana Vázquez and Lauko, Anna and De Bortoli, Valentin\n and Mathieu, Emile and Ovchinnikov, Sergey and Barzilay, Regina and\n Jaakkola, Tommi S. and DiMaio, Frank and Baek, Minkyung and Baker, David\",\n journal = \"Nature\",\n volume = 620,\n number = 7976,\n pages = \"1089--1100\",\n month = aug,\n year = 2023,\n language = \"en\",\n doi = {10.1038/s41586-023-06415-8}\n}\n```\n\n### Model Architecture:\n\n**Architecture Type:** Diffusion-based Generative Neural Network \u003cbr\u003e\n**Network Architecture:** RFdiffusion \u003cbr\u003e\n\n### Input:\n\n**Input Type(s):** Text (Protein) \u003cbr\u003e\n**Input Format(s):** Protein Data Bank (PDB) \u003cbr\u003e\n**Input Parameters:** String, One-Dimensional (1D) \u003cbr\u003e\n\n### Output:\n\n**Output Type(s):** Text (Protein) \u003cbr\u003e\n**Output Format:** Protein Data Bank (PDB)\u003cbr\u003e\n**Output Parameters:** String, 1D \u003cbr\u003e\n\n### Software Integration:\n\n**Runtime Engine(s):**\n* PyTorch \u003cbr\u003e\n\n**Supported Hardware Microarchitecture Compatibility:** \u003cbr\u003e\n* NVIDIA Hopper\u003cbr\u003e\n* NVIDIA Ampere \u003cbr\u003e\n* NVIDIA Lovelace \u003cbr\u003e\n* NVIDIA Turing \u003cbr\u003e\n\n**[Preferred/Supported] Operating System(s):** \u003cbr\u003e\n* Linux \u003cbr\u003e\n\n### Model Version(s):\n\nRFdiffusion 2.0.0 \u003cbr\u003e\n\n## Training \u0026 Evaluation:\n\n### Training Dataset:\n\n**Link:**\n[The Protein Data Bank](https://www.rcsb.org/) \u003cbr\u003e\n\n** Data Collection Method by dataset \u003cbr\u003e\n* Hybrid: Automatic, Human \u003cbr\u003e\n\nFor PDB dataset, scientists worldwide submit structural data\ndetermined by X-ray crystallography or cryo-electron microscopy (cryo-EM).\nThis includes atomic coordinates, experimental data, and metadata about the\nbiological macromolecules. \u003cbr\u003e\n\n** Labeling Method by dataset \u003cbr\u003e\n* Hybrid: Automatic, Human \u003cbr\u003e\n\nFor PDB dataset, expert biocurators review the submitted data to\nensure accuracy and completeness. This involves checking the plausibility of\nthe data and annotating it with relevant biological and chemical information.\u003cbr\u003e\n\n**Properties (Quantity, Dataset Descriptions, Sensor(s)):**\nThe training dataset\nused for RFdiffusion, as detailed in referenced paper, consists of protein structures sampled\nfrom the Protein Data Bank (PDB). To prepare these structures for training, a\nnoising process is applied. This process involves simulating up to 200 steps of\nrandom modifications on the protein structures. Specifically, the modifications\ninclude perturbing the Cα coordinates with 3D Gaussian noise and applying\nBrownian motion to the residue orientations on the manifold of rotation\nmatrices.\u003cbr\u003e\n\n**Dataset License(s):** [CC0 1.0](https://www.rcsb.org/news/feature/611e8d97ef055f03d1f222c6). \u003cbr\u003e\n\n### Evaluation Dataset:\n\nThe evaluation strategy involved training the model on PDB structures (as\ndescribed in Training Dataset) with added noise and then assessing its ability\nto denoise these structures, as well as evaluating its performance on design\ntasks with auxiliary conditioning information.\u003cbr\u003e\n\n** Data Collection Method by dataset \u003cbr\u003e\n* Automatic: random splits from PDB dataset. \u003cbr\u003e\n\n** Labeling Method by dataset \u003cbr\u003e\n* Automatic: random splits from PDB dataset. \u003cbr\u003e\n\nThe training, validation, and test splits were derived from protein assemblies\nin the PDB, which includes structures determined by X-ray\ncrystallography or cryo-electron microscopy (cryoEM).\u003cbr\u003e\n\n### Inference:\n\n**Engine:** PyTorch \u003cbr\u003e\n**Test Hardware:** \u003cbr\u003e\n* A100 \u003cbr\u003e\n* L40 \u003cbr\u003e\n* H100 \u003cbr\u003e\n\n### Ethical Considerations:\n\nNVIDIA believes Trustworthy AI is a shared responsibility and we have\nestablished policies and practices to enable development for a wide array of AI\napplications. When downloaded or used in accordance with our terms of service,\ndevelopers should work with their supporting model team to ensure this model\nmeets requirements for the relevant industry and use case and addresses\nunforeseen product misuse.\nPlease report security vulnerabilities or NVIDIA AI Concerns\n[here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/).\n"])</script><script>self.__next_f.push([1,"d2:Tc26,"])</script><script>self.__next_f.push([1,"## Start NIM\n\n1. Export `NGC_API_KEY` variable.\n\n```\nexport NGC_API_KEY=\u003cyour personal NGC key\u003e\n```\n\n2. NIM container automatically downloads models. To save time and bandwidth it\n is recommended to provide local cache directory. This way NIM will be able to\n reuse already downloaded models. Execute following command to setup cache\n directory.\n\n```bash\nexport LOCAL_NIM_CACHE=~/.cache/nim\nmkdir -p \"$LOCAL_NIM_CACHE\"\nsudo chmod 0777 -R \"$LOCAL_NIM_CACHE\"\n```\n\n3. Run the NIM container with the following commands.\n\n```bash\ndocker run -it \\\n --runtime=nvidia \\\n --gpus='\"device=0\"' \\\n -p 8000:8000 \\\n -e NGC_API_KEY \\\n -v \"$LOCAL_NIM_CACHE\":/opt/nim/.cache \\\n nvcr.io/nim/ipd/rfdiffusion:2\n```\n\nThis command will start the NIM container and expose port 8000 for the user to interact with the NIM.\n\n4. Open a new terminal, leaving the terminal open with the just launched service. In the new terminal, wait until the health check end point returns `{\"status\":\"ready\"}` before proceeding. This may take a couple of minutes. You can use the following command to query the health check.\n\n```bash\ncurl http://localhost:8000/v1/health/ready\n```\n\n## Python client example\n\n1. Save following Python example to a file named `nim_client.py`.\n\n```python\n#!/usr/bin/env python3\nimport requests\nimport os\nimport json\nfrom pathlib import Path\n\ndef get_reduced_pdb():\n pdb = Path(\"1R42.pdb\")\n if not pdb.exists():\n pdb.write_text(requests.get(f\"https://files.rcsb.org/download/{pdb}\").text)\n lines = filter(lambda line: line.startswith(\"ATOM\"), pdb.read_text().split(\"\\n\"))\n return \"\\n\".join(list(lines)[:400])\n\nr = requests.post(\n url=\"http://localhost:8000/biology/ipd/rfdiffusion/generate\",\n json={\n \"input_pdb\": get_reduced_pdb(),\n \"contigs\": \"A20-60/0 50-100\",\n \"hotspot_res\": [\"A50\",\"A51\",\"A52\",\"A53\",\"A54\"],\n \"diffusion_steps\": 15,\n },\n)\nprint(r, \"Saving to output.pdb:\\n\", r.text[:200], \"...\")\nPath(\"output.pdb\").write_text(json.loads(r.text)[\"output_pdb\"])\n```\n\n2. Execute the example.\n\n```bash\nchmod +x nim_client.py\n\n./nim_client.py\n```\n\n3. The example saves results to the `output.pdb` file in PDB format. You can quickly view the file using the following command.\n\n```bash\nless output.pdb\n```\n\n## Shell client example\n\n1. Save the following Shell example to a file named `nim_client.sh`.\n\n```bash\n#!/usr/bin/env bash\nset -e\n\nURL=http://localhost:8000/biology/ipd/rfdiffusion/generate\n\nif [ ! -e 1R42.pdb ]; then curl -O https://files.rcsb.org/download/1R42.pdb; fi\n\npdb=$(cat 1R42.pdb | grep ^ATOM | head -n 400 | awk '{printf \"%s\\\\n\", $0}')\n\nrequest='{\n \"input_pdb\": \"'\"$pdb\"'\",\n \"contigs\": \"A20-60/0 50-100\",\n \"hotspot_res\": [\"A50\",\"A51\",\"A52\",\"A53\",\"A54\"],\n \"diffusion_steps\": 15\n}'\ncurl -H 'Content-Type: application/json' \\\n -d \"$request\" \"$URL\"\n```\n\n2. Execute the example. The example displays the results to the terminal in JSON format.\n\n```bash\nchmod +x nim_client.sh\n\n./nim_client.sh\n```\n\nFor more details on getting started with this NIM, visit the [NVIDIA NIM Docs](https://docs.nvidia.com/nim/index.html#bionemo).\n"])</script><script>self.__next_f.push([1,"d3:T731,Field | Response\n:----------------------------------------------------------------------------------------------------------------------------------|:-----------------------------------------------\nGeneratable or reverse engineerable personally-identifiable information (PII)? | None\nWas consent obtained for any PII used? | Not Applicable \nHow often is dataset reviewed? | Before Release\nIs a mechanism in place to honor data subject right of access or deletion of personal data? | Not Applicable \nIf PII collected for the development of the model, was it collected directly by NVIDIA? | Not Applicable\nIf PII collected for the development of the model by NVIDIA, do you maintain or have access to disclosures made to data subjects? | Not Applicable\nIf PII collected for the development of this AI model, was it minimized to only what was required? | Not Applicable\nIs there provenance for all datasets used in training? | Yes\nDoes data labeling (annotation, metadata) comply with privacy laws? | Not Applicable\nIs data compliant with data subject requests for data correction or removal, if such a request was made? | Not Applicabled4:T142d,"])</script><script>self.__next_f.push([1,"## Model Overview\n\n### Description:\n\nMolMIM generates a random sample of new molecules in SMILES format by sampling from the latent space around the point corresponding to the given seed molecule. MolMIM performs optimization with the CMA-ES algorithmin the model’s latent space and sample molecules with improved values of the desired scoring function.\n\nMolMIM is a latent variable model developed by NVIDIA that is trained in an unsupervised manner over a large-scale dataset of molecules in the form of SMILES strings. MolMIM utilizes transformer architecture to learn an informative fixed-size latent space using Mutual Information Machine (MIM) learning. MIM is a learning framework for a latent variable model which promotes informative and clustered latent codes. MolMIM can be used for sampling novel molecules from the model’s latent space.\n\n### References(s):\n\n[Improving Small Molecule Generation using Mutual Information Machine](https://arxiv.org/abs/2208.09016)\n\n[MIM: Mutual Information Machine](https://arxiv.org/abs/1910.03175)\n\n[The CMA Evolution Strategy: A Comparing Review](https://link.springer.com/chapter/10.1007/3-540-32494-1_4)\n\n### Model Architecture:\n\n**Architecture Type:** Encoder-Decoder\n**Network Architecture:** Perceiver \u003cbr\u003e\n\nMolMIM utilizes a Perceiver encoder architecture which outputs a fixed-size representation, where molecules of various lengths are mapped into a latent space. MolMIM’s decoder architecture is a Transformer. Both encoder and decoder container 6 layers with a hidden size of 512, 8 attention heads, and a feed-forward dimension of 2048. Total number of parameters in MolMIM is 65.2M. The model was trained with A-MIM learning. \u003cbr\u003e\n\n### Input:\n\n**Input Type(s):** Text (Molecular Sequence) \u003cbr\u003e\n**Input Format(s):** Comma Separated Values, Simplified Molecular-Input Line Entry System (SMILES) \u003cbr\u003e\n**Input Parameters:** 1D \u003cbr\u003e\n**Other Properties Related to Input:** Maximum input length is 512 tokens. Pretraining dataset samples were randomly split into train, validation, and test sets ( 99% / 0.5% / 0.5% ). \u003cbr\u003e\n\n### Output: \u003cbr\u003e\n\n**Output Type(s):** Text, Numerical \u003cbr\u003e\n**Output Format:** [SMILES] \u003cbr\u003e\n**Output Parameters:** [2D] \u003cbr\u003e\n**Other Properties Related to Output:** Maximum output length is 128 tokens \u003cbr\u003e\n\n### Software Integration:\n\n**Runtime Engine(s):**\n* Triton Inference Server\u003cbr\u003e\n\n**Supported Hardware Microarchitecture Compatibility:** \u003cbr\u003e\n* Ampere \u003cbr\u003e\n* L40 \u003cbr\u003e\n\n### Preferred/Supported Operating System(s):\n\n* [Linux] \u003cbr\u003e\n* [Windows] \u003cbr\u003e\n\n### Model Version(s):\n\nMolMIM-24.03 \u003cbr\u003e\n\n### Training and Evaluation Dataset:\n\n**Link:** [ZINC-15](https://zinc15.docking.org) \u003cbr\u003e\n\n** Data Collection Method by dataset \u003cbr\u003e\n* Not Applicable \u003cbr\u003e\n\n** Labeling Method by dataset \u003cbr\u003e\n* Not Applicable \u003cbr\u003e\n\n**Properties (Quantity, Dataset Descriptions, Sensor(s)):** 1.54B molecules with molecular weight \u003c= 500 Daltons, LogP \u003c= 5, with reactivity levels rated as “reactive” and purchasability “annotated.” The compounds were filtered to ensure a maximum length of 512 characters. \u003cbr\u003e\n\n### Evaluation Dataset:\n\n**Link:** [MoleculeNet - Lipophilicity, FreeSolv, ESOL](https://moleculenet.org/datasets-1) \u003cbr\u003e\n\n** Data Collection Method by dataset \u003cbr\u003e\n* Hybrid: Human \u0026 Automatic/Sensors \u003cbr\u003e\n\n** Labeling Method by dataset \u003cbr\u003e\n* Hybrid: Human \u0026 Automated \u003cbr\u003e\n\n**Properties (Quantity, Dataset Descriptions, Sensor(s)):**\n\n[MoleculeNet Physical Chemistry](https://moleculenet.org/datasets-1) is an aggregation of public molecular datasets. The physical chemistry portion of MoleculeNet that we used for evaluation is made up of ESOL (1128 compunds), FreeSolv (642 compunds) and Lipohilicity (4200 compunds).\n\nZhenqin Wu, Bharath Ramsundar, Evan N. Feinberg, Joseph Gomes, Caleb Geniesse, Aneesh S. Pappu, Karl Leswing, Vijay Pande, [MoleculeNet: A Benchmark for Molecular Machine Learning](https://arxiv.org/abs/1703.00564), arXiv preprint, arXiv: 1703.00564, 2017.\n\nFrom the MoleculeNet documentation:\n\n* ESOL is made up of water solubility data(log solubility in mols per litre) for common organic small molecules.\n* FreeSolv is made up of experimental and calculated hydration free energy of small molecules in water.\n* Lipophilicity is composed of experimental results of octanol/water distribution coefficient(logD at pH 7.4).\n\n### Inference:\n\n**Engine:** Tensor(RT) \u003cbr\u003e\n**Test Hardware:** \u003cbr\u003e\n\n* Ampere \u003cbr\u003e\n* L40 \u003cbr\u003e\n\n### Ethical Considerations:\n\nNVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their internal model team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse. For more detailed information on ethical considerations for this model, please see the Model Card++ Explainability, Bias, Safety \u0026 Security, and Privacy Subcards. Please report security vulnerabilities or NVIDIA AI Concerns [here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/).\n"])</script><script>self.__next_f.push([1,"d5:T949,"])</script><script>self.__next_f.push([1,"Field | Response\n:------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------\nIntended Applications \u0026 Domains: | Molecular drug discovery and design\nType: | Molecular Sequence Generation\nIntended Users: | This model is intended for developers in the academic or pharmaceutical industries who build artificial intelligence applications to perform property guided molecule optimization and novel molecule generation. \nOutput: | Text (Molecule Sequence)\nDescribe how the model works: | Computes numerical embeddings for molecular representations and generates similar molecular representations from numerical embeddings\nName the adversely impacted groups this has been tested to deliver comparable outcomes regardless of: | None of the Above\nTechnical Limitations: | Model may not perform well on sequences that are highly divergent from the ZINC-15 dataset\nVerified to have met prescribed quality standards: | Yes\nPerformance Metrics: | Similarity, Modelability, Nearest Neighbor Correlation, Validity, Unique, Novelty, Non-Identicality, Effective Novelty, Scaffold Unique, Scaffold Non-Identical Similarity, Scaffold Novelty, Effective Scaffold Novelty, and Entropy\nPotential Known Risks: | The model may produce molecules that are invalid; validate with RDKit.\nLicensing: | https://docs.nvidia.com/ai-foundation-models-community-license.pdf"])</script><script>self.__next_f.push([1,"d6:T4e8,Pull and run the NVIDIA NIM with the command below. This will download the optimized model for your infrastructure.\n```bash\nexport NGC_API_KEY=\u003cPASTE_API_KEY_HERE\u003e\nexport LOCAL_NIM_CACHE=~/.cache/nim\nmkdir -p \"$LOCAL_NIM_CACHE\"\ndocker run -it --rm \\\n --runtime=nvidia \\\n -e NVIDIA_VISIBLE_DEVICES=0 \\\n -e NGC_API_KEY=$NGC_API_KEY \\\n --shm-size=2G \\\n --ulimit memlock=-1 \\\n --ulimit stack=67108864 \\\n -p 8000:8000 \\\n nvcr.io/nim/nvidia/molmim:1.0.0\n```\n\nYou can now make a local API call using this curl command:\n```bash\naccept_header='Accept: application/json'\ncontent_type_header='Content-Type: application/json'\n\ndata='{\n \"algorithm\": \"CMA-ES\",\n \"num_molecules\": 10,\n \"property_name\": \"QED\",\n \"minimize\": false,\n \"min_similarity\": 0.3,\n \"particles\": 20,\n \"iterations\": 3,\n \"smi\": \"[H][C@@]12Cc3c[nH]c4cccc(C1=C[C@H](NC(=O)N(CC)CC)CN2C)c34\"\n}'\n\nresponse=$(curl --silent -i -w \"\n%{http_code}\" --request POST \\\n --url http://localhost:8000/generate \\\n --header \"$authorization_header\" \\\n --header \"$accept_header\" \\\n --header \"$content_type_header\" \\\n --data \"$data\"\n)\n\necho \"$response\"\n```\n\nFor more details on getting started with this NIM, visit the [NVIDIA NIM Docs](https://docs.nvidia.com/nim/index.html#bionemo).\nd7:T1afe,"])</script><script>self.__next_f.push([1,"## Model Overview\n\n### Description:\n\nDiffDock is a generative diffusion model for drug discovery in molecular blind docking.\n\nDiffDock consists of two models: the Score and Confidence models. The Score model generates a series of potential poses for protein-ligand binding by running a reverse diffusion process.\n\nDiffDock does not require any information about a binding pocket. During its diffusion process, the molecule's position relative to the protein, its orientation, and the torsion angles are allowed to change. Running the learned reverse diffusion process transforms a distribution of noisy prior molecule poses to the one learned by the model. As a result, it outputs many sampled poses and ranks them via its confidence model.\n\nLeveraging the same neural-network architecture designed in the original DiffDock by MIT, the model v2.0 is trained by NVIDIA using PLINDER, a state-of-art dataset of well curated and labeled protein-ligand complexes, which therefore, delivers a much higher accuracy for molecular docking tasks.\n\nThis model is ready for commercial and non-commercial use.\n\u003cbr\u003e\n\n### License/Terms of Use:\n\nThis model is released under the [MIT License](https://github.com/gcorso/DiffDock/blob/main/LICENSE).\n\n### References:\n\n```\n@article {Durairaj2024.07.17.603955,\n\tauthor = {Durairaj, Janani and Adeshina, Yusuf and Cao, Zhonglin and Zhang, Xuejin and Oleinikovas, Vladas and Duignan, Thomas and McClure, Zachary and Robin, Xavier and Studer, Gabriel and Kovtun, Daniel and Rossi, Emanuele and Zhou, Guoqing and Veccham, Srimukh and Isert, Clemens and Peng, Yuxing and Sundareson, Prabindh and Akdel, Mehmet and Corso, Gabriele and St{\\\"a}rk, Hannes and Tauriello, Gerardo and Carpenter, Zachary and Bronstein, Michael and Kucukbenli, Emine and Schwede, Torsten and Naef, Luca},\n\ttitle = {PLINDER: The protein-ligand interactions dataset and evaluation resource},\n\telocation-id = {2024.07.17.603955},\n\tyear = {2024},\n\tdoi = {10.1101/2024.07.17.603955},\n\tpublisher = {Cold Spring Harbor Laboratory},\n\tabstract = {Protein-ligand interactions (PLI) are foundational to small molecule drug design. With computational methods striving towards experimental accuracy, there is a critical demand for a well-curated and diverse PLI dataset. Existing datasets are often limited in size and diversity, and commonly used evaluation sets suffer from training information leakage, hindering the realistic assessment of method generalization capabilities. To address these shortcomings, we present PLIN-DER, the largest and most annotated dataset to date, comprising 449,383 PLI systems, each with over 500 annotations, similarity metrics at protein, pocket, interaction and ligand levels, and paired unbound (apo) and predicted structures. We propose an approach to generate training and evaluation splits that minimizes task-specific leakage and maximizes test set quality, and compare the resulting performance of DiffDock when retrained with different kinds of splits.Competing Interest StatementThe authors have declared no competing interest.},\n\tURL = {https://www.biorxiv.org/content/early/2024/07/19/2024.07.17.603955.1},\n\teprint = {https://www.biorxiv.org/content/early/2024/07/19/2024.07.17.603955.1.full.pdf},\n\tjournal = {bioRxiv}\n}\n```\n\n```\n@article{corso2023diffdock,\n title={DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking}, \n author = {Corso, Gabriele and Stärk, Hannes and Jing, Bowen and Barzilay, Regina and Jaakkola, Tommi},\n journal={International Conference on Learning Representations (ICLR)},\n year={2023}\n}\n```\n\n### Model Architecture:\n\n**Architecture Type:** Score-Based Diffusion Model (SBDM) \u003cbr\u003e\n**Network Architecture:** Graph Convolution Neural Network \u003cbr\u003e\n\nThe Score model is a 3-dimensional equivariant graph neural network that has three layers: embedding, interaction layer with 6 graph convolution layers, and output layer. In total, the Score model has 20M parameters.\n\n### Input:\n\n**Input Type(s):** Text (Ligand, Protein), Number (Poses to Generate, Batch Size, Diffusion Steps, Diffusion Time Divisions) Binary (No Final Step Noise, Save Diffusion Trajectory, and Skip Gen Conformer)\u003cbr\u003e\n**Input Format(s):** Text: String (SMILES, Structural Data Files (SDF) or Tripos molecule structure (Mol2) for Ligand), String (Protein Data Bank (PDB)), Number: Integer; Binary: Boolean\u003cbr\u003e\n**Input Parameters:** 1D\u003cbr\u003e\n**Other Properties Related to Input:** No max sequence\u003cbr\u003e\n\n### Output:\n\n**Output Type(s):** Text (Ligand Molecule 3D Positions, 3D), Text (Ligand Molecule 3D Positions, 3D), Number (List of Confidence Scores, 1D)\u003cbr\u003e\n**Output Format:** Text: Structural Data Files (SDF), Text: Protein Data Bank (PDB), Number: Array of Floating Point 32\u003cbr\u003e\n**Output Parameters:** docked_ligand, visualizations_files, pose_confidence\u003cbr\u003e\n\n### Software Integration:\n\n**Runtime Engine(s):**\n* Triton \u003cbr\u003e\n\n**Supported Hardware Microarchitecture Compatibility:** \u003cbr\u003e\n* NVIDIA Ampere \u003cbr\u003e\n* NVIDIA Ada Lovelace \u003cbr\u003e\n* NVIDIA Hopper \u003cbr\u003e\n* NVIDIA Grace Hopper \u003cbr\u003e\n\n**[Preferred/Supported] Operating System(s):** \u003cbr\u003e\n* Linux \u003cbr\u003e\n\n### Model Version(s):\n\nDiffDock v2.0 \u003cbr\u003e\n\n## Training \u0026 Evaluation Dataset:\n\n### Training:\n\n**Link:** [PLINDER](https://plinder-org.github.io/plinder/index.html) \u003cbr\u003e\u003cbr\u003e\n**Data Collection Method by dataset:** \u003cbr\u003e\n* Human \u003cbr\u003e\n\n**Labeling Method by dataset:** \u003cbr\u003e\n* Hybrid: Human \u0026 Automated \u003cbr\u003e\n\n**Properties (Quantity, Dataset Descriptions, Sensor(s)):** 450,000 protein-ligand complexes automatically curated using the PDB database. See (https://www.biorxiv.org/content/10.1101/2024.07.17.603955v3). \u003cbr\u003e\n\n### Evaluation:\n\n**Link:** [PoseBusters benchmark (PDB) set](https://zenodo.org/records/8278563) \u003cbr\u003e\u003cbr\u003e\n**Data Collection Method by dataset:** \u003cbr\u003e\n* Human \u003cbr\u003e\n\n**Labeling Method by dataset:** \u003cbr\u003e\n* Hybrid: Human \u0026 Automated \u003cbr\u003e\n\n**Properties (Quantity, Dataset Descriptions, Sensor(s)):** 428 protein-ligand complexes manually curated using the PDB database. See https://arxiv.org/abs/2308.05777v1. \u003cbr\u003e\n\n### Inference:\n\n**Engine:** Triton \u003cbr\u003e\n**Test Hardware:** \u003cbr\u003e\n* A6000, A100, L40, L40S, H100\u003cbr\u003e\n\n## Ethical Considerations:\n\nNVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their internal model team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse.\n\nFor more detailed information on ethical considerations for this model, please see the Model Card++ Explainability, Bias, Safety \u0026 Security, and Privacy Subcards [Insert Link to Model Card++ here].\n\nPlease report security vulnerabilities or NVIDIA AI Concerns [here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/).\n"])</script><script>self.__next_f.push([1,"d8:T8f15b,"])</script><script>self.__next_f.push([1,"'{\"num_poses\": 2, \"time_divisions\": 20, \"steps\": 18, \"save_trajectory\": true, \"is_staged\": false, \"ligand_file_type\": \"mol2\", \"ligand\": \"asdasdadas asdfsd f### \n### Created by X-TOOL on Mon Aug 2 16:12:23 2021\n### \n\n@\u003cTRIPOS\u003eMOLECULE\n5zcu_ligand\n 35 37 1 0 0\nSMALL\nGAST_HUCK\n\n\n@\u003cTRIPOS\u003eATOM\n 1 S -21.9840 -3.4930 30.2670 S.o2 1 PYV 0.0724\n 2 BR -24.1210 -0.6400 35.6790 Br 1 PYV -0.0495\n 3 C1 -23.4470 -1.7030 34.2030 C.ar 1 PYV 0.0197\n 4 N1 -23.0330 -4.7560 29.7870 N.am 1 PYV -0.2334\n 5 O1 -20.5870 -3.9290 30.2880 O.2 1 PYV -0.1496\n 6 C2 -23.0400 -3.0490 34.2500 C.ar 1 PYV -0.0084\n 7 N2 -25.6720 -6.3800 30.7570 N.ar 1 PYV -0.2964\n 8 O2 -21.9450 -2.4040 29.2880 O.2 1 PYV -0.1496\n 9 C3 -22.5840 -3.6600 33.1100 C.ar 1 PYV 0.0112\n 10 C4 -22.5270 -2.9450 31.9060 C.ar 1 PYV 0.1195\n 11 C5 -22.9290 -1.6180 31.8510 C.ar 1 PYV -0.0306\n 12 C6 -23.3900 -0.9950 33.0070 C.ar 1 PYV -0.0494\n 13 C7 -22.1770 -5.0060 33.1320 C.ar 1 PYV -0.0511\n 14 C8 -22.2310 -5.7250 34.3150 C.ar 1 PYV -0.0605\n 15 C9 -22.6880 -5.1080 35.4720 C.ar 1 PYV -0.0607\n 16 C10 -23.0940 -3.7790 35.4510 C.ar 1 PYV -0.0538\n 17 C11 -24.4580 -4.5040 29.6550 C.3 1 PYV 0.0756\n 18 C12 -25.2580 -5.0960 30.8150 C.ar 1 PYV 0.0465\n 19 C13 -26.3850 -6.9080 31.7770 C.ar 1 PYV 0.0028\n 20 C14 -26.7010 -6.1340 32.8800 C.ar 1 PYV -0.0410\n 21 C15 -26.2930 -4.8430 32.9390 C.ar 1 PYV -0.0488\n 22 C16 -25.5800 -4.3150 31.9150 C.ar 1 PYV -0.0308\n 23 H1 -22.6660 -5.6667 29.5974 H 1 PYV 0.1703\n 24 H2 -22.8844 -1.0714 30.9159 H 1 PYV 0.0646\n 25 H3 -23.7046 0.0419 32.9754 H 1 PYV 0.0655\n 26 H4 -21.8215 -5.4803 32.2244 H 1 PYV 0.0630\n 27 H5 -21.9185 -6.7627 34.3373 H 1 PYV 0.0618\n 28 H6 -22.7284 -5.6677 36.3995 H 1 PYV 0.0624\n 29 H7 -23.4516 -3.3060 36.3584 H 1 PYV 0.0620\n 30 H8 -24.8117 -4.9528 28.7151 H 1 PYV 0.0668\n 31 H9 -24.6247 -3.4171 29.6279 H 1 PYV 0.0668\n 32 H10 -26.7103 -7.9410 31.7308 H 1 PYV 0.0803\n 33 H11 -27.2741 -6.5599 33.6956 H 1 PYV 0.0652\n 34 H12 -26.5363 -4.2348 33.8027 H 1 PYV 0.0719\n 35 H13 -25.2605 -3.2799 31.9555 H 1 PYV 0.0652\n@\u003cTRIPOS\u003eBOND\n 1 4 1 am \n 2 1 5 2 \n 3 1 8 2 \n 4 1 10 1 \n 5 3 2 1 \n 6 6 3 ar \n 7 12 3 ar \n 8 17 4 1 \n 9 9 6 ar \n 10 6 16 ar \n 11 18 7 ar \n 12 7 19 ar \n 13 10 9 ar \n 14 9 13 ar \n 15 10 11 ar \n 16 11 12 ar \n 17 13 14 ar \n 18 14 15 ar \n 19 16 15 ar \n 20 17 18 1 \n 21 18 22 ar \n 22 19 20 ar \n 23 20 21 ar \n 24 21 22 ar \n 25 4 23 1 \n 26 11 24 1 \n 27 12 25 1 \n 28 13 26 1 \n 29 14 27 1 \n 30 15 28 1 \n 31 16 29 1 \n 32 17 30 1 \n 33 17 31 1 \n 34 19 32 1 \n 35 20 33 1 \n 36 21 34 1 \n 37 22 35 1 \n@\u003cTRIPOS\u003eSUBSTRUCTURE\n 1 PYV 1\n\", \"protein\": \"REMARK Selection 'chain A or chain C'\nATOM 1 N ALA A 58 -11.274 42.755 37.461 1.00 0.00 N \nATOM 2 CA ALA A 58 -12.250 43.198 38.453 1.00 0.00 C \nATOM 3 C ALA A 58 -12.711 42.083 39.413 1.00 0.00 C \nATOM 4 O ALA A 58 -12.736 42.303 40.624 1.00 0.00 O \nATOM 5 CB ALA A 58 -13.458 43.839 37.758 1.00 0.00 C \nATOM 6 HA ALA A 58 -11.798 43.856 39.004 1.00 0.00 H \nATOM 7 HB1 ALA A 58 -14.099 44.129 38.425 1.00 0.00 H \nATOM 8 HB2 ALA A 58 -13.164 44.604 37.238 1.00 0.00 H \nATOM 9 HB3 ALA A 58 -13.875 43.190 37.170 1.00 0.00 H \nATOM 10 N PRO A 59 -13.078 40.899 38.906 1.00 0.00 N \nATOM 11 CA PRO A 59 -13.494 39.830 39.821 1.00 0.00 C \nATOM 12 C PRO A 59 -12.309 39.217 40.551 1.00 0.00 C \nATOM 13 O PRO A 59 -11.178 39.207 40.060 1.00 0.00 O \nATOM 14 CB PRO A 59 -14.168 38.811 38.896 1.00 0.00 C \nATOM 15 CG PRO A 59 -13.508 39.006 37.602 1.00 0.00 C \nATOM 16 CD PRO A 59 -13.226 40.475 37.499 1.00 0.00 C \nATOM 17 HA PRO A 59 -14.080 40.150 40.524 1.00 0.00 H \nATOM 18 HB2 PRO A 59 -14.049 37.905 39.221 1.00 0.00 H \nATOM 19 HB3 PRO A 59 -15.123 38.967 38.833 1.00 0.00 H \nATOM 20 HG2 PRO A 59 -12.688 38.491 37.549 1.00 0.00 H \nATOM 21 HG3 PRO A 59 -14.077 38.710 36.874 1.00 0.00 H \nATOM 22 HD2 PRO A 59 -12.420 40.649 36.987 1.00 0.00 H \nATOM 23 HD3 PRO A 59 -13.950 40.947 37.058 1.00 0.00 H \nATOM 24 N VAL A 60 -12.594 38.690 41.740 1.00 0.00 N \nATOM 25 CA VAL A 60 -11.586 38.156 42.650 1.00 0.00 C \nATOM 26 C VAL A 60 -11.981 36.723 42.978 1.00 0.00 C \nATOM 27 O VAL A 60 -12.982 36.492 43.668 1.00 0.00 O \nATOM 28 CB VAL A 60 -11.461 39.005 43.922 1.00 0.00 C \nATOM 29 CG1 VAL A 60 -10.662 38.269 44.982 1.00 0.00 C \nATOM 30 CG2 VAL A 60 -10.824 40.352 43.600 1.00 0.00 C \nATOM 31 H VAL A 60 -13.396 38.632 42.045 1.00 0.00 H \nATOM 32 HA VAL A 60 -10.713 38.178 42.227 1.00 0.00 H \nATOM 33 HB VAL A 60 -12.351 39.164 44.274 1.00 0.00 H \nATOM 34 HG11 VAL A 60 -10.594 38.820 45.777 1.00 0.00 H \nATOM 35 HG12 VAL A 60 -11.108 37.437 45.204 1.00 0.00 H \nATOM 36 HG13 VAL A 60 -9.773 38.079 44.644 1.00 0.00 H \nATOM 37 HG21 VAL A 60 -10.751 40.878 44.412 1.00 0.00 H \nATOM 38 HG22 VAL A 60 -9.940 40.211 43.226 1.00 0.00 H \nATOM 39 HG23 VAL A 60 -11.375 40.825 42.957 1.00 0.00 H \nATOM 40 N TRP A 61 -11.212 35.757 42.475 1.00 0.00 N \nATOM 41 CA TRP A 61 -11.581 34.357 42.626 1.00 0.00 C \nATOM 42 C TRP A 61 -10.341 33.472 42.633 1.00 0.00 C \nATOM 43 O TRP A 61 -9.248 33.889 42.242 1.00 0.00 O \nATOM 44 CB TRP A 61 -12.520 33.905 41.504 1.00 0.00 C \nATOM 45 CG TRP A 61 -11.787 33.635 40.228 1.00 0.00 C \nATOM 46 CD1 TRP A 61 -11.367 32.422 39.758 1.00 0.00 C \nATOM 47 CD2 TRP A 61 -11.367 34.606 39.263 1.00 0.00 C \nATOM 48 NE1 TRP A 61 -10.719 32.580 38.558 1.00 0.00 N \nATOM 49 CE2 TRP A 61 -10.705 33.910 38.231 1.00 0.00 C \nATOM 50 CE3 TRP A 61 -11.491 35.995 39.167 1.00 0.00 C \nATOM 51 CZ2 TRP A 61 -10.170 34.556 37.119 1.00 0.00 C \nATOM 52 CZ3 TRP A 61 -10.959 36.635 38.064 1.00 0.00 C \nATOM 53 CH2 TRP A 61 -10.306 35.917 37.054 1.00 0.00 C \nATOM 54 H TRP A 61 -10.479 35.893 42.047 1.00 0.00 H \nATOM 55 HA TRP A 61 -12.044 34.270 43.474 1.00 0.00 H \nATOM 56 HB2 TRP A 61 -12.990 33.103 41.781 1.00 0.00 H \nATOM 57 HB3 TRP A 61 -13.191 34.588 41.351 1.00 0.00 H \nATOM 58 HD1 TRP A 61 -11.501 31.608 40.188 1.00 0.00 H \nATOM 59 HE1 TRP A 61 -10.377 31.946 38.088 1.00 0.00 H \nATOM 60 HE3 TRP A 61 -11.923 36.479 39.833 1.00 0.00 H \nATOM 61 HZ2 TRP A 61 -9.737 34.081 36.447 1.00 0.00 H \nATOM 62 HZ3 TRP A 61 -11.036 37.559 37.991 1.00 0.00 H \nATOM 63 HH2 TRP A 61 -9.957 36.375 36.323 1.00 0.00 H \nATOM 64 N GLY A 62 -10.541 32.233 43.085 1.00 0.00 N \nATOM 65 CA GLY A 62 -9.531 31.201 42.968 1.00 0.00 C \nATOM 66 C GLY A 62 -10.172 29.899 42.529 1.00 0.00 C \nATOM 67 O GLY A 62 -11.375 29.688 42.706 1.00 0.00 O \nATOM 68 H GLY A 62 -11.267 31.975 43.466 1.00 0.00 H \nATOM 69 HA2 GLY A 62 -8.855 31.470 42.327 1.00 0.00 H \nATOM 70 HA3 GLY A 62 -9.082 31.079 43.819 1.00 0.00 H \nATOM 71 N CYS A 63 -9.349 29.018 41.957 1.00 0.00 N \nATOM 72 CA CYS A 63 -9.844 27.768 41.386 1.00 0.00 C \nATOM 73 C CYS A 63 -8.831 26.654 41.606 1.00 0.00 C \nATOM 74 O CYS A 63 -7.662 26.795 41.236 1.00 0.00 O \nATOM 75 CB CYS A 63 -10.144 27.930 39.892 1.00 0.00 C \nATOM 76 SG CYS A 63 -10.815 26.447 39.104 1.00 0.00 S \nATOM 77 H CYS A 63 -8.499 29.128 41.890 1.00 0.00 H \nATOM 78 HA CYS A 63 -10.671 27.533 41.835 1.00 0.00 H \nATOM 79 HB2 CYS A 63 -10.774 28.658 39.776 1.00 0.00 H \nATOM 80 HB3 CYS A 63 -9.328 28.186 39.435 1.00 0.00 H \nATOM 81 HG CYS A 63 -11.250 26.730 38.022 1.00 0.00 H \nATOM 82 N ALA A 64 -9.282 25.553 42.210 1.00 0.00 N \nATOM 83 CA ALA A 64 -8.466 24.367 42.441 1.00 0.00 C \nATOM 84 C ALA A 64 -9.216 23.128 41.964 1.00 0.00 C \nATOM 85 O ALA A 64 -10.434 23.028 42.140 1.00 0.00 O \nATOM 86 CB ALA A 64 -8.097 24.230 43.925 1.00 0.00 C \nATOM 87 H ALA A 64 -10.087 25.476 42.502 1.00 0.00 H \nATOM 88 HA ALA A 64 -7.642 24.457 41.938 1.00 0.00 H \nATOM 89 HB1 ALA A 64 -7.555 23.435 44.052 1.00 0.00 H \nATOM 90 HB2 ALA A 64 -7.596 25.011 44.207 1.00 0.00 H \nATOM 91 HB3 ALA A 64 -8.906 24.157 44.455 1.00 0.00 H \nATOM 92 N SER A 65 -8.485 22.180 41.373 1.00 0.00 N \nATOM 93 CA SER A 65 -9.092 20.980 40.808 1.00 0.00 C \nATOM 94 C SER A 65 -8.072 19.845 40.805 1.00 0.00 C \nATOM 95 O SER A 65 -6.866 20.082 40.693 1.00 0.00 O \nATOM 96 CB SER A 65 -9.618 21.237 39.392 1.00 0.00 C \nATOM 97 OG SER A 65 -8.563 21.547 38.501 1.00 0.00 O \nATOM 98 H SER A 65 -7.630 22.217 41.290 1.00 0.00 H \nATOM 99 HA SER A 65 -9.850 20.728 41.359 1.00 0.00 H \nATOM 100 HB2 SER A 65 -10.093 20.454 39.074 1.00 0.00 H \nATOM 101 HB3 SER A 65 -10.255 21.968 39.409 1.00 0.00 H \nATOM 102 HG SER A 65 -7.828 21.347 38.856 1.00 0.00 H \nATOM 103 N THR A 66 -8.570 18.610 40.931 1.00 0.00 N \nATOM 104 CA THR A 66 -7.706 17.432 40.942 1.00 0.00 C \nATOM 105 C THR A 66 -8.520 16.178 40.649 1.00 0.00 C \nATOM 106 O THR A 66 -9.709 16.106 40.950 1.00 0.00 O \nATOM 107 CB THR A 66 -6.975 17.264 42.281 1.00 0.00 C \nATOM 108 OG1 THR A 66 -6.072 16.154 42.197 1.00 0.00 O \nATOM 109 CG2 THR A 66 -7.966 17.017 43.408 1.00 0.00 C \nATOM 110 H THR A 66 -9.408 18.436 41.011 1.00 0.00 H \nATOM 111 HA THR A 66 -7.038 17.562 40.250 1.00 0.00 H \nATOM 112 HB THR A 66 -6.484 18.079 42.468 1.00 0.00 H \nATOM 113 HG1 THR A 66 -5.774 15.977 42.962 1.00 0.00 H \nATOM 114 HG21 THR A 66 -7.486 16.914 44.244 1.00 0.00 H \nATOM 115 HG22 THR A 66 -8.574 17.770 43.475 1.00 0.00 H \nATOM 116 HG23 THR A 66 -8.471 16.210 43.224 1.00 0.00 H \nATOM 117 N ARG A 67 -7.862 15.208 40.016 1.00 0.00 N \nATOM 118 CA ARG A 67 -8.376 13.842 39.909 1.00 0.00 C \nATOM 119 C ARG A 67 -8.842 13.277 41.253 1.00 0.00 C \nATOM 120 O ARG A 67 -9.943 12.719 41.347 1.00 0.00 O \nATOM 121 CB ARG A 67 -7.315 12.896 39.290 1.00 0.00 C \nATOM 122 CG ARG A 67 -6.827 13.166 37.841 1.00 0.00 C \nATOM 123 CD ARG A 67 -5.979 14.426 37.765 1.00 0.00 C \nATOM 124 NE ARG A 67 -5.623 14.728 36.395 1.00 0.00 N \nATOM 125 CZ ARG A 67 -5.115 15.887 35.997 1.00 0.00 C \nATOM 126 NH1 ARG A 67 -4.931 16.870 36.867 1.00 0.00 N \nATOM 127 NH2 ARG A 67 -4.821 16.076 34.718 1.00 0.00 N \nATOM 128 H ARG A 67 -7.100 15.324 39.634 1.00 0.00 H \nATOM 129 HA ARG A 67 -9.149 13.891 39.325 1.00 0.00 H \nATOM 130 HB2 ARG A 67 -6.537 12.908 39.869 1.00 0.00 H \nATOM 131 HB3 ARG A 67 -7.674 11.995 39.316 1.00 0.00 H \nATOM 132 HG2 ARG A 67 -6.311 12.408 37.525 1.00 0.00 H \nATOM 133 HG3 ARG A 67 -7.592 13.253 37.251 1.00 0.00 H \nATOM 134 HD2 ARG A 67 -6.466 15.172 38.148 1.00 0.00 H \nATOM 135 HD3 ARG A 67 -5.174 14.311 38.294 1.00 0.00 H \nATOM 136 HE ARG A 67 -5.749 14.118 35.802 1.00 0.00 H \nATOM 137 HH11 ARG A 67 -5.141 16.758 37.693 1.00 0.00 H \nATOM 138 HH12 ARG A 67 -4.601 17.620 36.605 1.00 0.00 H \nATOM 139 HH21 ARG A 67 -4.960 15.448 34.147 1.00 0.00 H \nATOM 140 HH22 ARG A 67 -4.492 16.827 34.459 1.00 0.00 H \nATOM 141 N GLY A 68 -8.002 13.388 42.297 1.00 0.00 N \nATOM 142 CA GLY A 68 -8.226 12.647 43.531 1.00 0.00 C \nATOM 143 C GLY A 68 -7.802 11.192 43.372 1.00 0.00 C \nATOM 144 O GLY A 68 -6.884 10.883 42.620 1.00 0.00 O \nATOM 145 H GLY A 68 -7.302 13.887 42.302 1.00 0.00 H \nATOM 146 HA2 GLY A 68 -7.727 13.057 44.255 1.00 0.00 H \nATOM 147 HA3 GLY A 68 -9.164 12.690 43.774 1.00 0.00 H \nATOM 148 N ARG A 69 -8.490 10.283 44.074 1.00 0.00 N \nATOM 149 CA ARG A 69 -8.308 8.858 43.778 1.00 0.00 C \nATOM 150 C ARG A 69 -8.915 8.429 42.473 1.00 0.00 C \nATOM 151 O ARG A 69 -8.605 7.318 42.016 1.00 0.00 O \nATOM 152 CB ARG A 69 -8.914 7.947 44.832 1.00 0.00 C \nATOM 153 CG ARG A 69 -7.986 7.571 45.954 1.00 0.00 C \nATOM 154 CD ARG A 69 -7.994 8.692 47.040 1.00 0.00 C \nATOM 155 NE ARG A 69 -7.086 8.413 48.165 1.00 0.00 N \nATOM 156 CZ ARG A 69 -7.134 8.968 49.384 1.00 0.00 C \nATOM 157 NH1 ARG A 69 -8.100 9.814 49.713 1.00 0.00 N \nATOM 158 NH2 ARG A 69 -6.210 8.647 50.303 1.00 0.00 N \nATOM 159 H ARG A 69 -9.048 10.462 44.704 1.00 0.00 H \nATOM 160 HA ARG A 69 -7.343 8.768 43.750 1.00 0.00 H \nATOM 161 HB2 ARG A 69 -9.694 8.384 45.208 1.00 0.00 H \nATOM 162 HB3 ARG A 69 -9.223 7.135 44.400 1.00 0.00 H \nATOM 163 HG2 ARG A 69 -8.262 6.727 46.345 1.00 0.00 H \nATOM 164 HG3 ARG A 69 -7.087 7.445 45.613 1.00 0.00 H \nATOM 165 HD2 ARG A 69 -7.742 9.534 46.630 1.00 0.00 H \nATOM 166 HD3 ARG A 69 -8.896 8.800 47.379 1.00 0.00 H \nATOM 167 HE ARG A 69 -6.463 7.837 48.026 1.00 0.00 H \nATOM 168 HH11 ARG A 69 -8.709 10.015 49.140 1.00 0.00 H \nATOM 169 HH12 ARG A 69 -8.117 10.162 50.499 1.00 0.00 H \nATOM 170 HH21 ARG A 69 -5.588 8.086 50.109 1.00 0.00 H \nATOM 171 HH22 ARG A 69 -6.240 9.003 51.085 1.00 0.00 H \nATOM 172 N SER A 70 -9.695 9.287 41.835 1.00 0.00 N \nATOM 173 CA SER A 70 -10.378 8.832 40.646 1.00 0.00 C \nATOM 174 C SER A 70 -9.368 8.558 39.541 1.00 0.00 C \nATOM 175 O SER A 70 -8.303 9.171 39.472 1.00 0.00 O \nATOM 176 CB SER A 70 -11.411 9.859 40.197 1.00 0.00 C \nATOM 177 OG SER A 70 -12.581 9.824 40.997 1.00 0.00 O \nATOM 178 H SER A 70 -9.837 10.104 42.064 1.00 0.00 H \nATOM 179 HA SER A 70 -10.846 8.007 40.848 1.00 0.00 H \nATOM 180 HB2 SER A 70 -11.021 10.746 40.235 1.00 0.00 H \nATOM 181 HB3 SER A 70 -11.649 9.693 39.271 1.00 0.00 H \nATOM 182 HG SER A 70 -12.378 9.975 41.798 1.00 0.00 H \nATOM 183 N ALA A 71 -9.710 7.610 38.675 1.00 0.00 N \nATOM 184 CA ALA A 71 -8.794 7.221 37.611 1.00 0.00 C \nATOM 185 C ALA A 71 -8.564 8.370 36.640 1.00 0.00 C \nATOM 186 O ALA A 71 -7.418 8.742 36.360 1.00 0.00 O \nATOM 187 CB ALA A 71 -9.337 5.996 36.880 1.00 0.00 C \nATOM 188 H ALA A 71 -10.458 7.185 38.685 1.00 0.00 H \nATOM 189 HA ALA A 71 -7.938 6.996 38.008 1.00 0.00 H \nATOM 190 HB1 ALA A 71 -8.723 5.742 36.173 1.00 0.00 H \nATOM 191 HB2 ALA A 71 -9.431 5.261 37.506 1.00 0.00 H \nATOM 192 HB3 ALA A 71 -10.203 6.206 36.496 1.00 0.00 H \nATOM 193 N GLU A 72 -9.642 8.948 36.120 1.00 0.00 N \nATOM 194 CA GLU A 72 -9.561 9.975 35.096 1.00 0.00 C \nATOM 195 C GLU A 72 -10.209 11.261 35.590 1.00 0.00 C \nATOM 196 O GLU A 72 -11.067 11.247 36.477 1.00 0.00 O \nATOM 197 CB GLU A 72 -10.229 9.506 33.796 1.00 0.00 C \nATOM 198 CG GLU A 72 -9.957 8.043 33.482 1.00 0.00 C \nATOM 199 CD GLU A 72 -11.091 7.378 32.729 1.00 0.00 C \nATOM 200 OE1 GLU A 72 -11.458 6.239 33.091 1.00 0.00 O \nATOM 201 OE2 GLU A 72 -11.613 7.992 31.775 1.00 0.00 O \nATOM 202 H GLU A 72 -10.446 8.752 36.355 1.00 0.00 H \nATOM 203 HA GLU A 72 -8.625 10.146 34.910 1.00 0.00 H \nATOM 204 HB2 GLU A 72 -11.187 9.645 33.862 1.00 0.00 H \nATOM 205 HB3 GLU A 72 -9.913 10.054 33.060 1.00 0.00 H \nATOM 206 HG2 GLU A 72 -9.144 7.976 32.957 1.00 0.00 H \nATOM 207 HG3 GLU A 72 -9.800 7.563 34.310 1.00 0.00 H \nATOM 208 N MET A 73 -9.778 12.378 35.006 1.00 0.00 N \nATOM 209 CA MET A 73 -10.291 13.698 35.356 1.00 0.00 C \nATOM 210 C MET A 73 -11.426 14.043 34.401 1.00 0.00 C \nATOM 211 O MET A 73 -11.205 14.201 33.196 1.00 0.00 O \nATOM 212 CB MET A 73 -9.177 14.739 35.287 1.00 0.00 C \nATOM 213 CG MET A 73 -9.603 16.140 35.691 1.00 0.00 C \nATOM 214 SD MET A 73 -10.532 16.170 37.234 1.00 0.00 S \nATOM 215 CE MET A 73 -10.416 17.907 37.661 1.00 0.00 C \nATOM 216 H MET A 73 -9.176 12.389 34.392 1.00 0.00 H \nATOM 217 HA MET A 73 -10.627 13.694 36.266 1.00 0.00 H \nATOM 218 HB2 MET A 73 -8.448 14.456 35.861 1.00 0.00 H \nATOM 219 HB3 MET A 73 -8.830 14.766 34.382 1.00 0.00 H \nATOM 220 HG2 MET A 73 -8.816 16.699 35.781 1.00 0.00 H \nATOM 221 HG3 MET A 73 -10.145 16.525 34.985 1.00 0.00 H \nATOM 222 HE1 MET A 73 -10.886 18.068 38.494 1.00 0.00 H \nATOM 223 HE2 MET A 73 -9.484 18.154 37.764 1.00 0.00 H \nATOM 224 HE3 MET A 73 -10.815 18.441 36.957 1.00 0.00 H \nATOM 225 N GLU A 74 -12.641 14.157 34.936 1.00 0.00 N \nATOM 226 CA GLU A 74 -13.806 14.515 34.138 1.00 0.00 C \nATOM 227 C GLU A 74 -14.492 15.778 34.642 1.00 0.00 C \nATOM 228 O GLU A 74 -15.562 16.136 34.134 1.00 0.00 O \nATOM 229 CB GLU A 74 -14.789 13.342 34.090 1.00 0.00 C \nATOM 230 CG GLU A 74 -14.177 12.092 33.476 1.00 0.00 C \nATOM 231 CD GLU A 74 -15.093 10.888 33.543 1.00 0.00 C \nATOM 232 OE1 GLU A 74 -15.948 10.836 34.453 1.00 0.00 O \nATOM 233 OE2 GLU A 74 -14.954 9.988 32.686 1.00 0.00 O \nATOM 234 H GLU A 74 -12.810 14.029 35.769 1.00 0.00 H \nATOM 235 HA GLU A 74 -13.496 14.709 33.240 1.00 0.00 H \nATOM 236 HB2 GLU A 74 -15.092 13.141 34.989 1.00 0.00 H \nATOM 237 HB3 GLU A 74 -15.571 13.600 33.578 1.00 0.00 H \nATOM 238 HG2 GLU A 74 -13.953 12.270 32.549 1.00 0.00 H \nATOM 239 HG3 GLU A 74 -13.347 11.886 33.934 1.00 0.00 H \nATOM 240 N ASP A 75 -13.907 16.458 35.621 1.00 0.00 N \nATOM 241 CA ASP A 75 -14.391 17.756 36.057 1.00 0.00 C \nATOM 242 C ASP A 75 -13.796 18.850 35.180 1.00 0.00 C \nATOM 243 O ASP A 75 -12.696 18.711 34.641 1.00 0.00 O \nATOM 244 CB ASP A 75 -14.029 18.010 37.520 1.00 0.00 C \nATOM 245 CG ASP A 75 -15.086 17.512 38.480 1.00 0.00 C \nATOM 246 OD1 ASP A 75 -16.052 16.862 38.026 1.00 0.00 O \nATOM 247 OD2 ASP A 75 -14.952 17.771 39.696 1.00 0.00 O \nATOM 248 H ASP A 75 -13.217 16.177 36.051 1.00 0.00 H \nATOM 249 HA ASP A 75 -15.358 17.765 35.975 1.00 0.00 H \nATOM 250 HB2 ASP A 75 -13.185 17.575 37.720 1.00 0.00 H \nATOM 251 HB3 ASP A 75 -13.897 18.961 37.656 1.00 0.00 H \nATOM 252 N ALA A 76 -14.539 19.943 35.039 1.00 0.00 N \nATOM 253 CA ALA A 76 -14.051 21.122 34.342 1.00 0.00 C \nATOM 254 C ALA A 76 -14.604 22.362 35.028 1.00 0.00 C \nATOM 255 O ALA A 76 -15.589 22.299 35.767 1.00 0.00 O \nATOM 256 CB ALA A 76 -14.440 21.108 32.857 1.00 0.00 C \nATOM 257 H ALA A 76 -15.339 20.020 35.345 1.00 0.00 H \nATOM 258 HA ALA A 76 -13.082 21.127 34.380 1.00 0.00 H \nATOM 259 HB1 ALA A 76 -14.099 21.907 32.425 1.00 0.00 H \nATOM 260 HB2 ALA A 76 -14.061 20.324 32.430 1.00 0.00 H \nATOM 261 HB3 ALA A 76 -15.406 21.085 32.776 1.00 0.00 H \nATOM 262 N SER A 77 -13.964 23.499 34.769 1.00 0.00 N \nATOM 263 CA SER A 77 -14.387 24.746 35.385 1.00 0.00 C \nATOM 264 C SER A 77 -14.145 25.903 34.428 1.00 0.00 C \nATOM 265 O SER A 77 -13.386 25.791 33.461 1.00 0.00 O \nATOM 266 CB SER A 77 -13.656 24.990 36.711 1.00 0.00 C \nATOM 267 OG SER A 77 -12.255 25.039 36.518 1.00 0.00 O \nATOM 268 H SER A 77 -13.287 23.567 34.243 1.00 0.00 H \nATOM 269 HA SER A 77 -15.336 24.682 35.578 1.00 0.00 H \nATOM 270 HB2 SER A 77 -13.961 25.823 37.103 1.00 0.00 H \nATOM 271 HB3 SER A 77 -13.875 24.284 37.339 1.00 0.00 H \nATOM 272 HG SER A 77 -11.870 24.667 37.165 1.00 0.00 H \nATOM 273 N ALA A 78 -14.802 27.023 34.720 1.00 0.00 N \nATOM 274 CA ALA A 78 -14.707 28.212 33.890 1.00 0.00 C \nATOM 275 C ALA A 78 -14.796 29.450 34.769 1.00 0.00 C \nATOM 276 O ALA A 78 -15.535 29.470 35.756 1.00 0.00 O \nATOM 277 CB ALA A 78 -15.808 28.242 32.825 1.00 0.00 C \nATOM 278 H ALA A 78 -15.314 27.111 35.405 1.00 0.00 H \nATOM 279 HA ALA A 78 -13.853 28.196 33.430 1.00 0.00 H \nATOM 280 HB1 ALA A 78 -15.718 29.045 32.289 1.00 0.00 H \nATOM 281 HB2 ALA A 78 -15.728 27.462 32.254 1.00 0.00 H \nATOM 282 HB3 ALA A 78 -16.677 28.238 33.257 1.00 0.00 H \nATOM 283 N ALA A 79 -14.033 30.477 34.401 1.00 0.00 N \nATOM 284 CA ALA A 79 -14.054 31.759 35.104 1.00 0.00 C \nATOM 285 C ALA A 79 -13.760 32.831 34.056 1.00 0.00 C \nATOM 286 O ALA A 79 -12.599 33.035 33.691 1.00 0.00 O \nATOM 287 CB ALA A 79 -13.046 31.790 36.243 1.00 0.00 C \nATOM 288 H ALA A 79 -13.488 30.450 33.736 1.00 0.00 H \nATOM 289 HA ALA A 79 -14.917 31.913 35.519 1.00 0.00 H \nATOM 290 HB1 ALA A 79 -13.086 32.651 36.687 1.00 0.00 H \nATOM 291 HB2 ALA A 79 -13.255 31.089 36.880 1.00 0.00 H \nATOM 292 HB3 ALA A 79 -12.154 31.650 35.890 1.00 0.00 H \nATOM 293 N VAL A 80 -14.801 33.498 33.586 1.00 0.00 N \nATOM 294 CA VAL A 80 -14.700 34.438 32.474 1.00 0.00 C \nATOM 295 C VAL A 80 -15.060 35.826 32.984 1.00 0.00 C \nATOM 296 O VAL A 80 -16.232 36.142 33.191 1.00 0.00 O \nATOM 297 CB VAL A 80 -15.611 34.023 31.304 1.00 0.00 C \nATOM 298 CG1 VAL A 80 -15.236 34.794 30.047 1.00 0.00 C \nATOM 299 CG2 VAL A 80 -15.529 32.523 31.067 1.00 0.00 C \nATOM 300 H VAL A 80 -15.596 33.420 33.904 1.00 0.00 H \nATOM 301 HA VAL A 80 -13.792 34.440 32.133 1.00 0.00 H \nATOM 302 HB VAL A 80 -16.529 34.239 31.533 1.00 0.00 H \nATOM 303 HG11 VAL A 80 -15.816 34.525 29.317 1.00 0.00 H \nATOM 304 HG12 VAL A 80 -15.339 35.745 30.208 1.00 0.00 H \nATOM 305 HG13 VAL A 80 -14.314 34.604 29.814 1.00 0.00 H \nATOM 306 HG21 VAL A 80 -16.108 32.280 30.328 1.00 0.00 H \nATOM 307 HG22 VAL A 80 -14.615 32.278 30.855 1.00 0.00 H \nATOM 308 HG23 VAL A 80 -15.812 32.053 31.867 1.00 0.00 H \nATOM 309 N PRO A 81 -14.067 36.690 33.199 1.00 0.00 N \nATOM 310 CA PRO A 81 -14.365 38.069 33.601 1.00 0.00 C \nATOM 311 C PRO A 81 -14.903 38.872 32.429 1.00 0.00 C \nATOM 312 O PRO A 81 -14.459 38.712 31.289 1.00 0.00 O \nATOM 313 CB PRO A 81 -13.009 38.612 34.072 1.00 0.00 C \nATOM 314 CG PRO A 81 -12.076 37.425 34.112 1.00 0.00 C \nATOM 315 CD PRO A 81 -12.622 36.418 33.159 1.00 0.00 C \nATOM 316 HA PRO A 81 -15.047 38.123 34.289 1.00 0.00 H \nATOM 317 HB2 PRO A 81 -12.678 39.293 33.466 1.00 0.00 H \nATOM 318 HB3 PRO A 81 -13.085 39.024 34.947 1.00 0.00 H \nATOM 319 HG2 PRO A 81 -11.176 37.686 33.860 1.00 0.00 H \nATOM 320 HG3 PRO A 81 -12.024 37.058 35.008 1.00 0.00 H \nATOM 321 HD2 PRO A 81 -12.258 36.531 32.267 1.00 0.00 H \nATOM 322 HD3 PRO A 81 -12.418 35.511 33.436 1.00 0.00 H \nATOM 323 N ARG A 82 -15.854 39.758 32.731 1.00 0.00 N \nATOM 324 CA ARG A 82 -16.477 40.635 31.737 1.00 0.00 C \nATOM 325 C ARG A 82 -16.914 39.850 30.501 1.00 0.00 C \nATOM 326 O ARG A 82 -16.672 40.246 29.358 1.00 0.00 O \nATOM 327 CB ARG A 82 -15.538 41.780 31.355 1.00 0.00 C \nATOM 328 CG ARG A 82 -14.969 42.529 32.547 1.00 0.00 C \nATOM 329 CD ARG A 82 -14.035 43.641 32.105 1.00 0.00 C \nATOM 330 NE ARG A 82 -12.862 43.126 31.403 1.00 0.00 N \nATOM 331 CZ ARG A 82 -12.575 43.389 30.132 1.00 0.00 C \nATOM 332 NH1 ARG A 82 -13.374 44.167 29.414 1.00 0.00 N \nATOM 333 NH2 ARG A 82 -11.485 42.875 29.578 1.00 0.00 N \nATOM 334 H ARG A 82 -16.159 39.868 33.528 1.00 0.00 H \nATOM 335 HA ARG A 82 -17.272 41.019 32.138 1.00 0.00 H \nATOM 336 HB2 ARG A 82 -14.806 41.424 30.827 1.00 0.00 H \nATOM 337 HB3 ARG A 82 -16.017 42.405 30.789 1.00 0.00 H \nATOM 338 HG2 ARG A 82 -15.694 42.902 33.073 1.00 0.00 H \nATOM 339 HG3 ARG A 82 -14.490 41.911 33.122 1.00 0.00 H \nATOM 340 HD2 ARG A 82 -14.514 44.253 31.525 1.00 0.00 H \nATOM 341 HD3 ARG A 82 -13.749 44.149 32.880 1.00 0.00 H \nATOM 342 HE ARG A 82 -12.322 42.620 31.841 1.00 0.00 H \nATOM 343 HH11 ARG A 82 -14.081 44.503 29.771 1.00 0.00 H \nATOM 344 HH12 ARG A 82 -13.185 44.335 28.592 1.00 0.00 H \nATOM 345 HH21 ARG A 82 -10.964 42.371 30.041 1.00 0.00 H \nATOM 346 HH22 ARG A 82 -11.299 43.045 28.756 1.00 0.00 H \nATOM 347 N PHE A 83 -17.574 38.717 30.745 1.00 0.00 N \nATOM 348 CA PHE A 83 -17.998 37.860 29.646 1.00 0.00 C \nATOM 349 C PHE A 83 -19.171 38.449 28.876 1.00 0.00 C \nATOM 350 O PHE A 83 -19.404 38.049 27.730 1.00 0.00 O \nATOM 351 CB PHE A 83 -18.378 36.475 30.172 1.00 0.00 C \nATOM 352 CG PHE A 83 -19.800 36.378 30.641 1.00 0.00 C \nATOM 353 CD1 PHE A 83 -20.184 36.931 31.851 1.00 0.00 C \nATOM 354 CD2 PHE A 83 -20.756 35.743 29.867 1.00 0.00 C \nATOM 355 CE1 PHE A 83 -21.494 36.848 32.284 1.00 0.00 C \nATOM 356 CE2 PHE A 83 -22.066 35.656 30.295 1.00 0.00 C \nATOM 357 CZ PHE A 83 -22.436 36.209 31.506 1.00 0.00 C \nATOM 358 H PHE A 83 -17.782 38.432 31.529 1.00 0.00 H \nATOM 359 HA PHE A 83 -17.248 37.788 29.036 1.00 0.00 H \nATOM 360 HB2 PHE A 83 -18.231 35.820 29.472 1.00 0.00 H \nATOM 361 HB3 PHE A 83 -17.787 36.243 30.905 1.00 0.00 H \nATOM 362 HD1 PHE A 83 -19.552 37.364 32.379 1.00 0.00 H \nATOM 363 HD2 PHE A 83 -20.513 35.371 29.050 1.00 0.00 H \nATOM 364 HE1 PHE A 83 -21.740 37.223 33.099 1.00 0.00 H \nATOM 365 HE2 PHE A 83 -22.700 35.225 29.768 1.00 0.00 H \nATOM 366 HZ PHE A 83 -23.318 36.150 31.795 1.00 0.00 H \nATOM 367 N ALA A 84 -19.905 39.384 29.471 1.00 0.00 N \nATOM 368 CA ALA A 84 -21.092 39.943 28.840 1.00 0.00 C \nATOM 369 C ALA A 84 -21.470 41.227 29.561 1.00 0.00 C \nATOM 370 O ALA A 84 -20.883 41.587 30.585 1.00 0.00 O \nATOM 371 CB ALA A 84 -22.256 38.947 28.854 1.00 0.00 C \nATOM 372 H ALA A 84 -19.729 39.710 30.247 1.00 0.00 H \nATOM 373 HA ALA A 84 -20.896 40.135 27.910 1.00 0.00 H \nATOM 374 HB1 ALA A 84 -23.030 39.347 28.428 1.00 0.00 H \nATOM 375 HB2 ALA A 84 -22.001 38.144 28.372 1.00 0.00 H \nATOM 376 HB3 ALA A 84 -22.475 38.718 29.771 1.00 0.00 H \nATOM 377 N ASP A 85 -22.466 41.914 29.008 1.00 0.00 N \nATOM 378 CA ASP A 85 -23.056 43.096 29.621 1.00 0.00 C \nATOM 379 C ASP A 85 -24.537 42.827 29.839 1.00 0.00 C \nATOM 380 O ASP A 85 -25.268 42.556 28.879 1.00 0.00 O \nATOM 381 CB ASP A 85 -22.847 44.333 28.743 1.00 0.00 C \nATOM 382 CG ASP A 85 -21.399 44.783 28.704 1.00 0.00 C \nATOM 383 OD1 ASP A 85 -20.582 44.238 29.477 1.00 0.00 O \nATOM 384 OD2 ASP A 85 -21.076 45.678 27.896 1.00 0.00 O \nATOM 385 H ASP A 85 -22.822 41.702 28.255 1.00 0.00 H \nATOM 386 HA ASP A 85 -22.624 43.276 30.471 1.00 0.00 H \nATOM 387 HB2 ASP A 85 -23.146 44.139 27.841 1.00 0.00 H \nATOM 388 HB3 ASP A 85 -23.399 45.058 29.075 1.00 0.00 H \nATOM 389 N VAL A 86 -24.973 42.893 31.093 1.00 0.00 N \nATOM 390 CA VAL A 86 -26.350 42.566 31.453 1.00 0.00 C \nATOM 391 C VAL A 86 -27.223 43.811 31.353 1.00 0.00 C \nATOM 392 O VAL A 86 -26.866 44.861 31.908 1.00 0.00 O \nATOM 393 CB VAL A 86 -26.424 41.960 32.864 1.00 0.00 C \nATOM 394 CG1 VAL A 86 -27.870 41.666 33.243 1.00 0.00 C \nATOM 395 CG2 VAL A 86 -25.574 40.701 32.948 1.00 0.00 C \nATOM 396 H VAL A 86 -24.481 43.128 31.758 1.00 0.00 H \nATOM 397 HA VAL A 86 -26.681 41.901 30.830 1.00 0.00 H \nATOM 398 HB VAL A 86 -26.071 42.605 33.496 1.00 0.00 H \nATOM 399 HG11 VAL A 86 -27.900 41.285 34.134 1.00 0.00 H \nATOM 400 HG12 VAL A 86 -28.383 42.489 33.226 1.00 0.00 H \nATOM 401 HG13 VAL A 86 -28.249 41.037 32.610 1.00 0.00 H \nATOM 402 HG21 VAL A 86 -25.631 40.331 33.843 1.00 0.00 H \nATOM 403 HG22 VAL A 86 -25.898 40.048 32.308 1.00 0.00 H \nATOM 404 HG23 VAL A 86 -24.651 40.920 32.747 1.00 0.00 H \nATOM 405 N PRO A 87 -28.364 43.749 30.668 1.00 0.00 N \nATOM 406 CA PRO A 87 -29.287 44.894 30.646 1.00 0.00 C \nATOM 407 C PRO A 87 -29.870 45.120 32.038 1.00 0.00 C \nATOM 408 O PRO A 87 -30.484 44.221 32.616 1.00 0.00 O \nATOM 409 CB PRO A 87 -30.361 44.483 29.634 1.00 0.00 C \nATOM 410 CG PRO A 87 -30.228 43.011 29.478 1.00 0.00 C \nATOM 411 CD PRO A 87 -28.820 42.636 29.815 1.00 0.00 C \nATOM 412 HA PRO A 87 -28.863 45.730 30.398 1.00 0.00 H \nATOM 413 HB2 PRO A 87 -31.247 44.721 29.950 1.00 0.00 H \nATOM 414 HB3 PRO A 87 -30.232 44.936 28.786 1.00 0.00 H \nATOM 415 HG2 PRO A 87 -30.851 42.550 30.062 1.00 0.00 H \nATOM 416 HG3 PRO A 87 -30.442 42.746 28.570 1.00 0.00 H \nATOM 417 HD2 PRO A 87 -28.778 41.787 30.282 1.00 0.00 H \nATOM 418 HD3 PRO A 87 -28.273 42.549 29.019 1.00 0.00 H \nATOM 419 N VAL A 88 -29.663 46.327 32.568 1.00 0.00 N \nATOM 420 CA VAL A 88 -29.968 46.624 33.964 1.00 0.00 C \nATOM 421 C VAL A 88 -31.444 46.429 34.300 1.00 0.00 C \nATOM 422 O VAL A 88 -31.788 46.248 35.474 1.00 0.00 O \nATOM 423 CB VAL A 88 -29.486 48.051 34.302 1.00 0.00 C \nATOM 424 CG1 VAL A 88 -29.612 48.326 35.788 1.00 0.00 C \nATOM 425 CG2 VAL A 88 -28.040 48.215 33.875 1.00 0.00 C \nATOM 426 H VAL A 88 -29.343 46.993 32.128 1.00 0.00 H \nATOM 427 HA VAL A 88 -29.490 45.988 34.519 1.00 0.00 H \nATOM 428 HB VAL A 88 -30.043 48.685 33.824 1.00 0.00 H \nATOM 429 HG11 VAL A 88 -29.304 49.226 35.978 1.00 0.00 H \nATOM 430 HG12 VAL A 88 -30.540 48.239 36.056 1.00 0.00 H \nATOM 431 HG13 VAL A 88 -29.072 47.689 36.282 1.00 0.00 H \nATOM 432 HG21 VAL A 88 -27.739 49.112 34.088 1.00 0.00 H \nATOM 433 HG22 VAL A 88 -27.489 47.569 34.344 1.00 0.00 H \nATOM 434 HG23 VAL A 88 -27.966 48.068 32.919 1.00 0.00 H \nATOM 435 N ARG A 89 -32.331 46.432 33.301 1.00 0.00 N \nATOM 436 CA ARG A 89 -33.739 46.179 33.594 1.00 0.00 C \nATOM 437 C ARG A 89 -33.981 44.783 34.147 1.00 0.00 C \nATOM 438 O ARG A 89 -35.086 44.511 34.627 1.00 0.00 O \nATOM 439 CB ARG A 89 -34.594 46.364 32.340 1.00 0.00 C \nATOM 440 CG ARG A 89 -35.294 47.698 32.265 1.00 0.00 C \nATOM 441 CD ARG A 89 -36.487 47.652 31.333 1.00 0.00 C \nATOM 442 NE ARG A 89 -37.706 47.191 31.993 1.00 0.00 N \nATOM 443 CZ ARG A 89 -38.754 46.682 31.354 1.00 0.00 C \nATOM 444 NH1 ARG A 89 -38.732 46.568 30.033 1.00 0.00 N \nATOM 445 NH2 ARG A 89 -39.828 46.300 32.032 1.00 0.00 N \nATOM 446 H ARG A 89 -32.144 46.574 32.474 1.00 0.00 H \nATOM 447 HA ARG A 89 -33.993 46.823 34.273 1.00 0.00 H \nATOM 448 HB2 ARG A 89 -34.030 46.261 31.557 1.00 0.00 H \nATOM 449 HB3 ARG A 89 -35.259 45.658 32.306 1.00 0.00 H \nATOM 450 HG2 ARG A 89 -35.586 47.961 33.152 1.00 0.00 H \nATOM 451 HG3 ARG A 89 -34.670 48.375 31.959 1.00 0.00 H \nATOM 452 HD2 ARG A 89 -36.639 48.537 30.965 1.00 0.00 H \nATOM 453 HD3 ARG A 89 -36.287 47.065 30.587 1.00 0.00 H \nATOM 454 HE ARG A 89 -37.748 47.253 32.850 1.00 0.00 H \nATOM 455 HH11 ARG A 89 -38.040 46.823 29.591 1.00 0.00 H \nATOM 456 HH12 ARG A 89 -39.410 46.239 29.618 1.00 0.00 H \nATOM 457 HH21 ARG A 89 -39.848 46.381 32.888 1.00 0.00 H \nATOM 458 HH22 ARG A 89 -40.505 45.971 31.616 1.00 0.00 H \nATOM 459 N LEU A 90 -32.984 43.902 34.098 1.00 0.00 N \nATOM 460 CA LEU A 90 -33.030 42.609 34.764 1.00 0.00 C \nATOM 461 C LEU A 90 -32.500 42.667 36.189 1.00 0.00 C \nATOM 462 O LEU A 90 -32.570 41.662 36.904 1.00 0.00 O \nATOM 463 CB LEU A 90 -32.231 41.568 33.970 1.00 0.00 C \nATOM 464 CG LEU A 90 -32.722 41.189 32.574 1.00 0.00 C \nATOM 465 CD1 LEU A 90 -31.595 40.598 31.746 1.00 0.00 C \nATOM 466 CD2 LEU A 90 -33.874 40.210 32.681 1.00 0.00 C \nATOM 467 H LEU A 90 -32.252 44.044 33.670 1.00 0.00 H \nATOM 468 HA LEU A 90 -33.964 42.352 34.804 1.00 0.00 H \nATOM 469 HB2 LEU A 90 -31.322 41.895 33.885 1.00 0.00 H \nATOM 470 HB3 LEU A 90 -32.193 40.757 34.501 1.00 0.00 H \nATOM 471 HG LEU A 90 -33.032 41.992 32.126 1.00 0.00 H \nATOM 472 HD11 LEU A 90 -31.928 40.365 30.865 1.00 0.00 H \nATOM 473 HD12 LEU A 90 -30.881 41.249 31.659 1.00 0.00 H \nATOM 474 HD13 LEU A 90 -31.255 39.802 32.184 1.00 0.00 H \nATOM 475 HD21 LEU A 90 -34.181 39.973 31.792 1.00 0.00 H \nATOM 476 HD22 LEU A 90 -33.578 39.411 33.144 1.00 0.00 H \nATOM 477 HD23 LEU A 90 -34.601 40.619 33.176 1.00 0.00 H \nATOM 478 N LEU A 91 -31.976 43.817 36.619 1.00 0.00 N \nATOM 479 CA LEU A 91 -31.355 43.952 37.926 1.00 0.00 C \nATOM 480 C LEU A 91 -31.945 45.065 38.776 1.00 0.00 C \nATOM 481 O LEU A 91 -31.679 45.103 39.982 1.00 0.00 O \nATOM 482 CB LEU A 91 -29.845 44.205 37.778 1.00 0.00 C \nATOM 483 CG LEU A 91 -29.053 43.291 36.842 1.00 0.00 C \nATOM 484 CD1 LEU A 91 -27.726 43.933 36.475 1.00 0.00 C \nATOM 485 CD2 LEU A 91 -28.832 41.927 37.475 1.00 0.00 C \nATOM 486 H LEU A 91 -31.974 44.541 36.154 1.00 0.00 H \nATOM 487 HA LEU A 91 -31.528 43.113 38.381 1.00 0.00 H \nATOM 488 HB2 LEU A 91 -29.725 45.118 37.474 1.00 0.00 H \nATOM 489 HB3 LEU A 91 -29.446 44.145 38.660 1.00 0.00 H \nATOM 490 HG LEU A 91 -29.570 43.164 36.031 1.00 0.00 H \nATOM 491 HD11 LEU A 91 -27.234 43.344 35.882 1.00 0.00 H \nATOM 492 HD12 LEU A 91 -27.888 44.779 36.029 1.00 0.00 H \nATOM 493 HD13 LEU A 91 -27.207 44.087 37.280 1.00 0.00 H \nATOM 494 HD21 LEU A 91 -28.329 41.365 36.865 1.00 0.00 H \nATOM 495 HD22 LEU A 91 -28.336 42.030 38.302 1.00 0.00 H \nATOM 496 HD23 LEU A 91 -29.690 41.514 37.662 1.00 0.00 H \nATOM 497 N ALA A 92 -32.732 45.967 38.197 1.00 0.00 N \nATOM 498 CA ALA A 92 -33.297 47.067 38.960 1.00 0.00 C \nATOM 499 C ALA A 92 -34.684 47.386 38.430 1.00 0.00 C \nATOM 500 O ALA A 92 -34.969 47.212 37.241 1.00 0.00 O \nATOM 501 CB ALA A 92 -32.406 48.313 38.900 1.00 0.00 C \nATOM 502 H ALA A 92 -32.949 45.958 37.365 1.00 0.00 H \nATOM 503 HA ALA A 92 -33.355 46.796 39.890 1.00 0.00 H \nATOM 504 HB1 ALA A 92 -32.811 49.026 39.418 1.00 0.00 H \nATOM 505 HB2 ALA A 92 -31.532 48.104 39.266 1.00 0.00 H \nATOM 506 HB3 ALA A 92 -32.310 48.598 37.978 1.00 0.00 H \nATOM 507 N SER A 93 -35.542 47.854 39.331 1.00 0.00 N \nATOM 508 CA SER A 93 -36.877 48.283 38.946 1.00 0.00 C \nATOM 509 C SER A 93 -36.787 49.471 37.998 1.00 0.00 C \nATOM 510 O SER A 93 -35.926 50.342 38.151 1.00 0.00 O \nATOM 511 CB SER A 93 -37.687 48.653 40.190 1.00 0.00 C \nATOM 512 OG SER A 93 -38.617 49.685 39.912 1.00 0.00 O \nATOM 513 H SER A 93 -35.369 47.930 40.170 1.00 0.00 H \nATOM 514 HA SER A 93 -37.326 47.554 38.490 1.00 0.00 H \nATOM 515 HB2 SER A 93 -38.158 47.870 40.516 1.00 0.00 H \nATOM 516 HB3 SER A 93 -37.086 48.938 40.896 1.00 0.00 H \nATOM 517 HG SER A 93 -39.122 49.793 40.574 1.00 0.00 H \nATOM 518 N ARG A 94 -37.679 49.497 37.001 1.00 0.00 N \nATOM 519 CA ARG A 94 -37.685 50.607 36.053 1.00 0.00 C \nATOM 520 C ARG A 94 -37.910 51.933 36.756 1.00 0.00 C \nATOM 521 O ARG A 94 -37.371 52.961 36.335 1.00 0.00 O \nATOM 522 CB ARG A 94 -38.791 50.410 35.018 1.00 0.00 C \nATOM 523 CG ARG A 94 -38.380 49.734 33.742 1.00 0.00 C \nATOM 524 CD ARG A 94 -39.550 49.715 32.770 1.00 0.00 C \nATOM 525 NE ARG A 94 -39.930 51.057 32.344 1.00 0.00 N \nATOM 526 CZ ARG A 94 -39.733 51.531 31.119 1.00 0.00 C \nATOM 527 NH1 ARG A 94 -39.161 50.766 30.199 1.00 0.00 N \nATOM 528 NH2 ARG A 94 -40.107 52.765 30.812 1.00 0.00 N \nATOM 529 H ARG A 94 -38.275 48.893 36.861 1.00 0.00 H \nATOM 530 HA ARG A 94 -36.818 50.623 35.618 1.00 0.00 H \nATOM 531 HB2 ARG A 94 -39.502 49.891 35.425 1.00 0.00 H \nATOM 532 HB3 ARG A 94 -39.164 51.278 34.799 1.00 0.00 H \nATOM 533 HG2 ARG A 94 -37.627 50.201 33.346 1.00 0.00 H \nATOM 534 HG3 ARG A 94 -38.087 48.828 33.926 1.00 0.00 H \nATOM 535 HD2 ARG A 94 -39.315 49.185 31.993 1.00 0.00 H \nATOM 536 HD3 ARG A 94 -40.310 49.282 33.189 1.00 0.00 H \nATOM 537 HE ARG A 94 -40.304 51.573 32.921 1.00 0.00 H \nATOM 538 HH11 ARG A 94 -38.919 49.965 30.396 1.00 0.00 H \nATOM 539 HH12 ARG A 94 -39.033 51.071 29.405 1.00 0.00 H \nATOM 540 HH21 ARG A 94 -40.479 53.262 31.407 1.00 0.00 H \nATOM 541 HH22 ARG A 94 -39.978 53.068 30.018 1.00 0.00 H \nATOM 542 N ARG A 95 -38.682 51.918 37.836 1.00 0.00 N \nATOM 543 CA ARG A 95 -39.106 53.121 38.531 1.00 0.00 C \nATOM 544 C ARG A 95 -38.085 53.589 39.555 1.00 0.00 C \nATOM 545 O ARG A 95 -38.080 54.772 39.911 1.00 0.00 O \nATOM 546 CB ARG A 95 -40.463 52.893 39.218 1.00 0.00 C \nATOM 547 CG ARG A 95 -41.654 52.603 38.284 1.00 0.00 C \nATOM 548 CD ARG A 95 -41.554 51.263 37.553 1.00 0.00 C \nATOM 549 NE ARG A 95 -41.205 50.169 38.458 1.00 0.00 N \nATOM 550 CZ ARG A 95 -40.932 48.929 38.065 1.00 0.00 C \nATOM 551 NH1 ARG A 95 -40.961 48.616 36.776 1.00 0.00 N \nATOM 552 NH2 ARG A 95 -40.627 48.001 38.960 1.00 0.00 N \nATOM 553 H ARG A 95 -38.979 51.193 38.191 1.00 0.00 H \nATOM 554 HA ARG A 95 -39.191 53.818 37.862 1.00 0.00 H \nATOM 555 HB2 ARG A 95 -40.372 52.151 39.836 1.00 0.00 H \nATOM 556 HB3 ARG A 95 -40.674 53.678 39.747 1.00 0.00 H \nATOM 557 HG2 ARG A 95 -42.473 52.618 38.804 1.00 0.00 H \nATOM 558 HG3 ARG A 95 -41.721 53.315 37.629 1.00 0.00 H \nATOM 559 HD2 ARG A 95 -42.400 51.067 37.122 1.00 0.00 H \nATOM 560 HD3 ARG A 95 -40.887 51.327 36.852 1.00 0.00 H \nATOM 561 HE ARG A 95 -41.174 50.339 39.300 1.00 0.00 H \nATOM 562 HH11 ARG A 95 -41.157 49.216 36.192 1.00 0.00 H \nATOM 563 HH12 ARG A 95 -40.784 47.813 36.524 1.00 0.00 H \nATOM 564 HH21 ARG A 95 -40.606 48.201 39.796 1.00 0.00 H \nATOM 565 HH22 ARG A 95 -40.451 47.199 38.705 1.00 0.00 H \nATOM 566 N ASP A 96 -37.216 52.692 40.028 1.00 0.00 N \nATOM 567 CA ASP A 96 -36.155 53.110 40.931 1.00 0.00 C \nATOM 568 C ASP A 96 -34.987 53.712 40.171 1.00 0.00 C \nATOM 569 O ASP A 96 -34.296 54.585 40.701 1.00 0.00 O \nATOM 570 CB ASP A 96 -35.663 51.921 41.758 1.00 0.00 C \nATOM 571 CG ASP A 96 -36.340 51.827 43.107 1.00 0.00 C \nATOM 572 OD1 ASP A 96 -37.421 52.429 43.277 1.00 0.00 O \nATOM 573 OD2 ASP A 96 -35.789 51.148 43.999 1.00 0.00 O \nATOM 574 H ASP A 96 -37.226 51.853 39.840 1.00 0.00 H \nATOM 575 HA ASP A 96 -36.522 53.788 41.520 1.00 0.00 H \nATOM 576 HB2 ASP A 96 -35.820 51.101 41.264 1.00 0.00 H \nATOM 577 HB3 ASP A 96 -34.704 51.996 41.886 1.00 0.00 H \nATOM 578 N LEU A 97 -34.759 53.266 38.937 1.00 0.00 N \nATOM 579 CA LEU A 97 -33.805 53.934 38.065 1.00 0.00 C \nATOM 580 C LEU A 97 -34.418 55.153 37.385 1.00 0.00 C \nATOM 581 O LEU A 97 -33.698 56.105 37.065 1.00 0.00 O \nATOM 582 CB LEU A 97 -33.261 52.946 37.038 1.00 0.00 C \nATOM 583 CG LEU A 97 -31.931 52.315 37.457 1.00 0.00 C \nATOM 584 CD1 LEU A 97 -31.562 51.185 36.526 1.00 0.00 C \nATOM 585 CD2 LEU A 97 -30.826 53.364 37.501 1.00 0.00 C \nATOM 586 H LEU A 97 -35.146 52.581 38.590 1.00 0.00 H \nATOM 587 HA LEU A 97 -33.070 54.256 38.610 1.00 0.00 H \nATOM 588 HB2 LEU A 97 -33.915 52.244 36.895 1.00 0.00 H \nATOM 589 HB3 LEU A 97 -33.144 53.402 36.190 1.00 0.00 H \nATOM 590 HG LEU A 97 -32.035 51.950 38.350 1.00 0.00 H \nATOM 591 HD11 LEU A 97 -30.718 50.797 36.806 1.00 0.00 H \nATOM 592 HD12 LEU A 97 -32.254 50.505 36.552 1.00 0.00 H \nATOM 593 HD13 LEU A 97 -31.477 51.525 35.622 1.00 0.00 H \nATOM 594 HD21 LEU A 97 -29.993 52.945 37.768 1.00 0.00 H \nATOM 595 HD22 LEU A 97 -30.721 53.761 36.622 1.00 0.00 H \nATOM 596 HD23 LEU A 97 -31.060 54.054 38.141 1.00 0.00 H \nATOM 597 N ASP A 98 -35.734 55.138 37.150 1.00 0.00 N \nATOM 598 CA ASP A 98 -36.411 56.323 36.631 1.00 0.00 C \nATOM 599 C ASP A 98 -36.371 57.468 37.634 1.00 0.00 C \nATOM 600 O ASP A 98 -36.443 58.639 37.241 1.00 0.00 O \nATOM 601 CB ASP A 98 -37.858 55.980 36.264 1.00 0.00 C \nATOM 602 CG ASP A 98 -38.648 57.185 35.799 1.00 0.00 C \nATOM 603 OD1 ASP A 98 -38.148 57.932 34.933 1.00 0.00 O \nATOM 604 OD2 ASP A 98 -39.777 57.382 36.299 1.00 0.00 O \nATOM 605 H ASP A 98 -36.245 54.459 37.284 1.00 0.00 H \nATOM 606 HA ASP A 98 -35.943 56.615 35.833 1.00 0.00 H \nATOM 607 HB2 ASP A 98 -37.859 55.308 35.564 1.00 0.00 H \nATOM 608 HB3 ASP A 98 -38.298 55.588 37.034 1.00 0.00 H \nATOM 609 N ALA A 99 -36.256 57.153 38.928 1.00 0.00 N \nATOM 610 CA ALA A 99 -36.116 58.197 39.936 1.00 0.00 C \nATOM 611 C ALA A 99 -34.804 58.957 39.775 1.00 0.00 C \nATOM 612 O ALA A 99 -34.739 60.151 40.088 1.00 0.00 O \nATOM 613 CB ALA A 99 -36.215 57.592 41.336 1.00 0.00 C \nATOM 614 H ALA A 99 -36.257 56.350 39.236 1.00 0.00 H \nATOM 615 HA ALA A 99 -36.839 58.831 39.813 1.00 0.00 H \nATOM 616 HB1 ALA A 99 -36.121 58.293 41.999 1.00 0.00 H \nATOM 617 HB2 ALA A 99 -37.077 57.161 41.442 1.00 0.00 H \nATOM 618 HB3 ALA A 99 -35.510 56.937 41.456 1.00 0.00 H \nATOM 619 N LEU A 100 -33.759 58.290 39.289 1.00 0.00 N \nATOM 620 CA LEU A 100 -32.497 58.939 38.963 1.00 0.00 C \nATOM 621 C LEU A 100 -32.451 59.403 37.515 1.00 0.00 C \nATOM 622 O LEU A 100 -31.395 59.834 37.043 1.00 0.00 O \nATOM 623 CB LEU A 100 -31.317 57.998 39.236 1.00 0.00 C \nATOM 624 CG LEU A 100 -31.004 57.516 40.658 1.00 0.00 C \nATOM 625 CD1 LEU A 100 -31.977 56.459 41.142 1.00 0.00 C \nATOM 626 CD2 LEU A 100 -29.577 56.993 40.732 1.00 0.00 C \nATOM 627 H LEU A 100 -33.765 57.443 39.139 1.00 0.00 H \nATOM 628 HA LEU A 100 -32.427 59.721 39.533 1.00 0.00 H \nATOM 629 HB2 LEU A 100 -31.452 57.207 38.691 1.00 0.00 H \nATOM 630 HB3 LEU A 100 -30.519 58.438 38.903 1.00 0.00 H \nATOM 631 HG LEU A 100 -31.101 58.281 41.247 1.00 0.00 H \nATOM 632 HD11 LEU A 100 -31.739 56.187 42.042 1.00 0.00 H \nATOM 633 HD12 LEU A 100 -32.876 56.822 41.142 1.00 0.00 H \nATOM 634 HD13 LEU A 100 -31.940 55.690 40.552 1.00 0.00 H \nATOM 635 HD21 LEU A 100 -29.389 56.691 41.634 1.00 0.00 H \nATOM 636 HD22 LEU A 100 -29.471 56.252 40.115 1.00 0.00 H \nATOM 637 HD23 LEU A 100 -28.959 57.702 40.494 1.00 0.00 H \nATOM 638 N GLY A 101 -33.575 59.322 36.808 1.00 0.00 N \nATOM 639 CA GLY A 101 -33.640 59.673 35.406 1.00 0.00 C \nATOM 640 C GLY A 101 -32.842 58.776 34.493 1.00 0.00 C \nATOM 641 O GLY A 101 -32.617 59.133 33.336 1.00 0.00 O \nATOM 642 H GLY A 101 -34.325 59.059 37.137 1.00 0.00 H \nATOM 643 HA2 GLY A 101 -34.568 59.657 35.124 1.00 0.00 H \nATOM 644 HA3 GLY A 101 -33.326 60.585 35.299 1.00 0.00 H \nATOM 645 N LEU A 102 -32.443 57.599 34.963 1.00 0.00 N \nATOM 646 CA LEU A 102 -31.626 56.677 34.182 1.00 0.00 C \nATOM 647 C LEU A 102 -32.540 55.521 33.790 1.00 0.00 C \nATOM 648 O LEU A 102 -32.691 54.556 34.537 1.00 0.00 O \nATOM 649 CB LEU A 102 -30.424 56.182 34.989 1.00 0.00 C \nATOM 650 CG LEU A 102 -29.225 57.100 35.233 1.00 0.00 C \nATOM 651 CD1 LEU A 102 -28.223 56.404 36.142 1.00 0.00 C \nATOM 652 CD2 LEU A 102 -28.569 57.503 33.924 1.00 0.00 C \nATOM 653 H LEU A 102 -32.640 57.311 35.749 1.00 0.00 H \nATOM 654 HA LEU A 102 -31.262 57.115 33.397 1.00 0.00 H \nATOM 655 HB2 LEU A 102 -30.756 55.906 35.858 1.00 0.00 H \nATOM 656 HB3 LEU A 102 -30.090 55.386 34.547 1.00 0.00 H \nATOM 657 HG LEU A 102 -29.538 57.909 35.666 1.00 0.00 H \nATOM 658 HD11 LEU A 102 -27.464 56.988 36.295 1.00 0.00 H \nATOM 659 HD12 LEU A 102 -28.646 56.195 36.990 1.00 0.00 H \nATOM 660 HD13 LEU A 102 -27.920 55.584 35.722 1.00 0.00 H \nATOM 661 HD21 LEU A 102 -27.813 58.083 34.106 1.00 0.00 H \nATOM 662 HD22 LEU A 102 -28.262 56.710 33.458 1.00 0.00 H \nATOM 663 HD23 LEU A 102 -29.212 57.974 33.371 1.00 0.00 H \nATOM 664 N ASP A 103 -33.137 55.609 32.607 1.00 0.00 N \nATOM 665 CA ASP A 103 -34.010 54.534 32.153 1.00 0.00 C \nATOM 666 C ASP A 103 -33.167 53.324 31.773 1.00 0.00 C \nATOM 667 O ASP A 103 -32.287 53.414 30.911 1.00 0.00 O \nATOM 668 CB ASP A 103 -34.889 54.987 30.993 1.00 0.00 C \nATOM 669 CG ASP A 103 -36.336 54.555 31.171 1.00 0.00 C \nATOM 670 OD1 ASP A 103 -36.767 54.386 32.333 1.00 0.00 O \nATOM 671 OD2 ASP A 103 -37.041 54.372 30.156 1.00 0.00 O \nATOM 672 H ASP A 103 -33.053 56.269 32.062 1.00 0.00 H \nATOM 673 HA ASP A 103 -34.606 54.285 32.877 1.00 0.00 H \nATOM 674 HB2 ASP A 103 -34.848 55.953 30.916 1.00 0.00 H \nATOM 675 HB3 ASP A 103 -34.543 54.621 30.164 1.00 0.00 H \nATOM 676 N ALA A 104 -33.445 52.194 32.416 1.00 0.00 N \nATOM 677 CA ALA A 104 -32.639 50.985 32.316 1.00 0.00 C \nATOM 678 C ALA A 104 -32.759 50.283 30.969 1.00 0.00 C \nATOM 679 O ALA A 104 -32.088 49.263 30.775 1.00 0.00 O \nATOM 680 CB ALA A 104 -33.002 50.018 33.442 1.00 0.00 C \nATOM 681 H ALA A 104 -34.125 52.108 32.935 1.00 0.00 H \nATOM 682 HA ALA A 104 -31.714 51.265 32.399 1.00 0.00 H \nATOM 683 HB1 ALA A 104 -32.461 49.216 33.367 1.00 0.00 H \nATOM 684 HB2 ALA A 104 -32.836 50.441 34.299 1.00 0.00 H \nATOM 685 HB3 ALA A 104 -33.940 49.781 33.376 1.00 0.00 H \nATOM 686 N ASP A 105 -33.583 50.774 30.038 1.00 0.00 N \nATOM 687 CA ASP A 105 -33.655 50.119 28.737 1.00 0.00 C \nATOM 688 C ASP A 105 -32.389 50.343 27.920 1.00 0.00 C \nATOM 689 O ASP A 105 -32.147 49.602 26.960 1.00 0.00 O \nATOM 690 CB ASP A 105 -34.855 50.636 27.932 1.00 0.00 C \nATOM 691 CG ASP A 105 -36.060 50.947 28.797 1.00 0.00 C \nATOM 692 OD1 ASP A 105 -36.447 50.095 29.619 1.00 0.00 O \nATOM 693 OD2 ASP A 105 -36.626 52.051 28.649 1.00 0.00 O \nATOM 694 H ASP A 105 -34.091 51.461 30.137 1.00 0.00 H \nATOM 695 HA ASP A 105 -33.755 49.170 28.909 1.00 0.00 H \nATOM 696 HB2 ASP A 105 -34.594 51.436 27.450 1.00 0.00 H \nATOM 697 HB3 ASP A 105 -35.102 49.973 27.268 1.00 0.00 H \nATOM 698 N ALA A 106 -31.585 51.345 28.277 1.00 0.00 N \nATOM 699 CA ALA A 106 -30.301 51.601 27.635 1.00 0.00 C \nATOM 700 C ALA A 106 -29.098 51.237 28.492 1.00 0.00 C \nATOM 701 O ALA A 106 -28.041 50.925 27.944 1.00 0.00 O \nATOM 702 CB ALA A 106 -30.190 53.076 27.230 1.00 0.00 C \nATOM 703 H ALA A 106 -31.774 51.900 28.906 1.00 0.00 H \nATOM 704 HA ALA A 106 -30.283 51.024 26.855 1.00 0.00 H \nATOM 705 HB1 ALA A 106 -29.332 53.231 26.805 1.00 0.00 H \nATOM 706 HB2 ALA A 106 -30.902 53.296 26.610 1.00 0.00 H \nATOM 707 HB3 ALA A 106 -30.265 53.635 28.019 1.00 0.00 H \nATOM 708 N LEU A 107 -29.237 51.251 29.815 1.00 0.00 N \nATOM 709 CA LEU A 107 -28.123 50.911 30.692 1.00 0.00 C \nATOM 710 C LEU A 107 -27.751 49.442 30.553 1.00 0.00 C \nATOM 711 O LEU A 107 -28.615 48.579 30.374 1.00 0.00 O \nATOM 712 CB LEU A 107 -28.477 51.216 32.149 1.00 0.00 C \nATOM 713 CG LEU A 107 -28.275 52.627 32.704 1.00 0.00 C \nATOM 714 CD1 LEU A 107 -29.121 52.845 33.951 1.00 0.00 C \nATOM 715 CD2 LEU A 107 -26.803 52.873 32.993 1.00 0.00 C \nATOM 716 H LEU A 107 -29.966 51.454 30.223 1.00 0.00 H \nATOM 717 HA LEU A 107 -27.362 51.451 30.429 1.00 0.00 H \nATOM 718 HB2 LEU A 107 -29.412 50.988 32.273 1.00 0.00 H \nATOM 719 HB3 LEU A 107 -27.961 50.611 32.704 1.00 0.00 H \nATOM 720 HG LEU A 107 -28.566 53.266 32.035 1.00 0.00 H \nATOM 721 HD11 LEU A 107 -28.978 53.744 34.286 1.00 0.00 H \nATOM 722 HD12 LEU A 107 -30.058 52.727 33.731 1.00 0.00 H \nATOM 723 HD13 LEU A 107 -28.866 52.203 34.632 1.00 0.00 H \nATOM 724 HD21 LEU A 107 -26.687 53.770 33.344 1.00 0.00 H \nATOM 725 HD22 LEU A 107 -26.489 52.228 33.646 1.00 0.00 H \nATOM 726 HD23 LEU A 107 -26.292 52.779 32.174 1.00 0.00 H \nATOM 727 N ARG A 108 -26.450 49.160 30.644 1.00 0.00 N \nATOM 728 CA ARG A 108 -25.963 47.799 30.794 1.00 0.00 C \nATOM 729 C ARG A 108 -24.772 47.808 31.744 1.00 0.00 C \nATOM 730 O ARG A 108 -24.081 48.823 31.895 1.00 0.00 O \nATOM 731 CB ARG A 108 -25.528 47.194 29.444 1.00 0.00 C \nATOM 732 CG ARG A 108 -26.341 47.646 28.239 1.00 0.00 C \nATOM 733 CD ARG A 108 -25.669 47.293 26.912 1.00 0.00 C \nATOM 734 NE ARG A 108 -24.218 47.503 26.936 1.00 0.00 N \nATOM 735 CZ ARG A 108 -23.569 48.350 26.141 1.00 0.00 C \nATOM 736 NH1 ARG A 108 -24.234 49.060 25.239 1.00 0.00 N \nATOM 737 NH2 ARG A 108 -22.253 48.471 26.235 1.00 0.00 N \nATOM 738 H ARG A 108 -25.830 49.755 30.620 1.00 0.00 H \nATOM 739 HA ARG A 108 -26.685 47.254 31.146 1.00 0.00 H \nATOM 740 HB2 ARG A 108 -24.597 47.418 29.290 1.00 0.00 H \nATOM 741 HB3 ARG A 108 -25.580 46.227 29.507 1.00 0.00 H \nATOM 742 HG2 ARG A 108 -27.219 47.235 28.273 1.00 0.00 H \nATOM 743 HG3 ARG A 108 -26.475 48.606 28.285 1.00 0.00 H \nATOM 744 HD2 ARG A 108 -25.854 46.365 26.697 1.00 0.00 H \nATOM 745 HD3 ARG A 108 -26.058 47.831 26.204 1.00 0.00 H \nATOM 746 HE ARG A 108 -23.756 47.049 27.501 1.00 0.00 H \nATOM 747 HH11 ARG A 108 -25.087 48.973 25.167 1.00 0.00 H \nATOM 748 HH12 ARG A 108 -23.812 49.607 24.726 1.00 0.00 H \nATOM 749 HH21 ARG A 108 -21.818 48.002 26.810 1.00 0.00 H \nATOM 750 HH22 ARG A 108 -21.834 49.018 25.721 1.00 0.00 H \nATOM 751 N LEU A 109 -24.535 46.662 32.384 1.00 0.00 N \nATOM 752 CA LEU A 109 -23.462 46.528 33.357 1.00 0.00 C \nATOM 753 C LEU A 109 -22.677 45.239 33.083 1.00 0.00 C \nATOM 754 O LEU A 109 -23.285 44.191 32.855 1.00 0.00 O \nATOM 755 CB LEU A 109 -24.011 46.518 34.788 1.00 0.00 C \nATOM 756 CG LEU A 109 -23.014 46.375 35.943 1.00 0.00 C \nATOM 757 CD1 LEU A 109 -22.429 47.731 36.304 1.00 0.00 C \nATOM 758 CD2 LEU A 109 -23.686 45.751 37.159 1.00 0.00 C \nATOM 759 H LEU A 109 -24.993 45.944 32.264 1.00 0.00 H \nATOM 760 HA LEU A 109 -22.871 47.292 33.270 1.00 0.00 H \nATOM 761 HB2 LEU A 109 -24.504 47.342 34.922 1.00 0.00 H \nATOM 762 HB3 LEU A 109 -24.650 45.791 34.856 1.00 0.00 H \nATOM 763 HG LEU A 109 -22.295 45.790 35.656 1.00 0.00 H \nATOM 764 HD11 LEU A 109 -21.800 47.628 37.035 1.00 0.00 H \nATOM 765 HD12 LEU A 109 -21.970 48.101 35.534 1.00 0.00 H \nATOM 766 HD13 LEU A 109 -23.143 48.330 36.574 1.00 0.00 H \nATOM 767 HD21 LEU A 109 -23.041 45.668 37.879 1.00 0.00 H \nATOM 768 HD22 LEU A 109 -24.421 46.314 37.447 1.00 0.00 H \nATOM 769 HD23 LEU A 109 -24.025 44.872 36.927 1.00 0.00 H \nATOM 770 N PRO A 110 -21.350 45.307 33.109 1.00 0.00 N \nATOM 771 CA PRO A 110 -20.557 44.094 32.854 1.00 0.00 C \nATOM 772 C PRO A 110 -20.709 43.083 33.977 1.00 0.00 C \nATOM 773 O PRO A 110 -20.977 43.429 35.129 1.00 0.00 O \nATOM 774 CB PRO A 110 -19.121 44.626 32.769 1.00 0.00 C \nATOM 775 CG PRO A 110 -19.148 45.926 33.504 1.00 0.00 C \nATOM 776 CD PRO A 110 -20.508 46.503 33.254 1.00 0.00 C \nATOM 777 HA PRO A 110 -20.835 43.622 32.053 1.00 0.00 H \nATOM 778 HB2 PRO A 110 -18.492 44.007 33.172 1.00 0.00 H \nATOM 779 HB3 PRO A 110 -18.846 44.749 31.847 1.00 0.00 H \nATOM 780 HG2 PRO A 110 -18.994 45.794 34.453 1.00 0.00 H \nATOM 781 HG3 PRO A 110 -18.452 46.522 33.185 1.00 0.00 H \nATOM 782 HD2 PRO A 110 -20.802 47.063 33.990 1.00 0.00 H \nATOM 783 HD3 PRO A 110 -20.524 47.053 32.455 1.00 0.00 H \nATOM 784 N ALA A 111 -20.531 41.812 33.622 1.00 0.00 N \nATOM 785 CA ALA A 111 -20.717 40.712 34.554 1.00 0.00 C \nATOM 786 C ALA A 111 -19.686 39.630 34.268 1.00 0.00 C \nATOM 787 O ALA A 111 -19.143 39.535 33.165 1.00 0.00 O \nATOM 788 CB ALA A 111 -22.133 40.131 34.465 1.00 0.00 C \nATOM 789 H ALA A 111 -20.298 41.567 32.831 1.00 0.00 H \nATOM 790 HA ALA A 111 -20.597 41.051 35.455 1.00 0.00 H \nATOM 791 HB1 ALA A 111 -22.224 39.401 35.098 1.00 0.00 H \nATOM 792 HB2 ALA A 111 -22.780 40.822 34.674 1.00 0.00 H \nATOM 793 HB3 ALA A 111 -22.292 39.801 33.567 1.00 0.00 H \nATOM 794 N HIS A 112 -19.415 38.816 35.285 1.00 0.00 N \nATOM 795 CA HIS A 112 -18.424 37.752 35.207 1.00 0.00 C \nATOM 796 C HIS A 112 -19.110 36.405 35.375 1.00 0.00 C \nATOM 797 O HIS A 112 -20.079 36.283 36.131 1.00 0.00 O \nATOM 798 CB HIS A 112 -17.339 37.934 36.277 1.00 0.00 C \nATOM 799 CG HIS A 112 -16.999 39.367 36.550 1.00 0.00 C \nATOM 800 ND1 HIS A 112 -16.392 40.180 35.617 1.00 0.00 N \nATOM 801 CD2 HIS A 112 -17.185 40.133 37.651 1.00 0.00 C \nATOM 802 CE1 HIS A 112 -16.218 41.384 36.132 1.00 0.00 C \nATOM 803 NE2 HIS A 112 -16.688 41.382 37.366 1.00 0.00 N \nATOM 804 H HIS A 112 -19.808 38.869 36.048 1.00 0.00 H \nATOM 805 HA HIS A 112 -17.995 37.789 34.338 1.00 0.00 H \nATOM 806 HB2 HIS A 112 -17.635 37.517 37.101 1.00 0.00 H \nATOM 807 HB3 HIS A 112 -16.537 37.467 35.996 1.00 0.00 H \nATOM 808 HD1 HIS A 112 -16.162 39.941 34.823 1.00 0.00 H \nATOM 809 HD2 HIS A 112 -17.576 39.864 38.451 1.00 0.00 H \nATOM 810 HE1 HIS A 112 -15.830 42.110 35.699 1.00 0.00 H \nATOM 811 HE2 HIS A 112 -16.684 42.053 37.904 1.00 0.00 H \nATOM 812 N LEU A 113 -18.605 35.396 34.669 1.00 0.00 N \nATOM 813 CA LEU A 113 -19.199 34.066 34.659 1.00 0.00 C \nATOM 814 C LEU A 113 -18.239 33.078 35.307 1.00 0.00 C \nATOM 815 O LEU A 113 -17.082 32.965 34.890 1.00 0.00 O \nATOM 816 CB LEU A 113 -19.532 33.636 33.229 1.00 0.00 C \nATOM 817 CG LEU A 113 -20.495 32.461 33.003 1.00 0.00 C \nATOM 818 CD1 LEU A 113 -19.780 31.116 33.052 1.00 0.00 C \nATOM 819 CD2 LEU A 113 -21.632 32.502 34.012 1.00 0.00 C \nATOM 820 H LEU A 113 -17.902 35.467 34.179 1.00 0.00 H \nATOM 821 HA LEU A 113 -20.026 34.083 35.165 1.00 0.00 H \nATOM 822 HB2 LEU A 113 -19.901 34.407 32.771 1.00 0.00 H \nATOM 823 HB3 LEU A 113 -18.696 33.417 32.788 1.00 0.00 H \nATOM 824 HG LEU A 113 -20.864 32.557 32.111 1.00 0.00 H \nATOM 825 HD11 LEU A 113 -20.421 30.403 32.905 1.00 0.00 H \nATOM 826 HD12 LEU A 113 -19.100 31.086 32.361 1.00 0.00 H \nATOM 827 HD13 LEU A 113 -19.364 31.002 33.921 1.00 0.00 H \nATOM 828 HD21 LEU A 113 -22.230 31.755 33.856 1.00 0.00 H \nATOM 829 HD22 LEU A 113 -21.270 32.444 34.910 1.00 0.00 H \nATOM 830 HD23 LEU A 113 -22.122 33.334 33.914 1.00 0.00 H \nATOM 831 N PHE A 114 -18.723 32.370 36.323 1.00 0.00 N \nATOM 832 CA PHE A 114 -18.017 31.254 36.936 1.00 0.00 C \nATOM 833 C PHE A 114 -18.875 30.004 36.806 1.00 0.00 C \nATOM 834 O PHE A 114 -20.099 30.067 36.962 1.00 0.00 O \nATOM 835 CB PHE A 114 -17.703 31.534 38.411 1.00 0.00 C \nATOM 836 CG PHE A 114 -17.000 32.843 38.645 1.00 0.00 C \nATOM 837 CD1 PHE A 114 -15.622 32.935 38.546 1.00 0.00 C \nATOM 838 CD2 PHE A 114 -17.720 33.983 38.967 1.00 0.00 C \nATOM 839 CE1 PHE A 114 -14.974 34.139 38.763 1.00 0.00 C \nATOM 840 CE2 PHE A 114 -17.079 35.190 39.186 1.00 0.00 C \nATOM 841 CZ PHE A 114 -15.704 35.266 39.083 1.00 0.00 C \nATOM 842 H PHE A 114 -19.488 32.530 36.682 1.00 0.00 H \nATOM 843 HA PHE A 114 -17.171 31.126 36.480 1.00 0.00 H \nATOM 844 HB2 PHE A 114 -18.531 31.527 38.916 1.00 0.00 H \nATOM 845 HB3 PHE A 114 -17.153 30.815 38.758 1.00 0.00 H \nATOM 846 HD1 PHE A 114 -15.126 32.179 38.331 1.00 0.00 H \nATOM 847 HD2 PHE A 114 -18.646 33.936 39.037 1.00 0.00 H \nATOM 848 HE1 PHE A 114 -14.048 34.188 38.693 1.00 0.00 H \nATOM 849 HE2 PHE A 114 -17.573 35.948 39.402 1.00 0.00 H \nATOM 850 HZ PHE A 114 -15.270 36.076 39.229 1.00 0.00 H \nATOM 851 N GLY A 115 -18.243 28.875 36.518 1.00 0.00 N \nATOM 852 CA GLY A 115 -18.982 27.641 36.316 1.00 0.00 C \nATOM 853 C GLY A 115 -18.159 26.420 36.651 1.00 0.00 C \nATOM 854 O GLY A 115 -16.940 26.394 36.454 1.00 0.00 O \nATOM 855 H GLY A 115 -17.390 28.803 36.436 1.00 0.00 H \nATOM 856 HA2 GLY A 115 -19.781 27.651 36.866 1.00 0.00 H \nATOM 857 HA3 GLY A 115 -19.274 27.589 35.392 1.00 0.00 H \nATOM 858 N VAL A 116 -18.839 25.398 37.168 1.00 0.00 N \nATOM 859 CA VAL A 116 -18.249 24.096 37.450 1.00 0.00 C \nATOM 860 C VAL A 116 -19.075 23.041 36.728 1.00 0.00 C \nATOM 861 O VAL A 116 -20.310 23.087 36.749 1.00 0.00 O \nATOM 862 CB VAL A 116 -18.193 23.811 38.967 1.00 0.00 C \nATOM 863 CG1 VAL A 116 -17.887 22.345 39.233 1.00 0.00 C \nATOM 864 CG2 VAL A 116 -17.157 24.702 39.636 1.00 0.00 C \nATOM 865 H VAL A 116 -19.674 25.446 37.368 1.00 0.00 H \nATOM 866 HA VAL A 116 -17.332 24.080 37.134 1.00 0.00 H \nATOM 867 HB VAL A 116 -19.064 24.010 39.345 1.00 0.00 H \nATOM 868 HG11 VAL A 116 -17.857 22.189 40.190 1.00 0.00 H \nATOM 869 HG12 VAL A 116 -18.580 21.793 38.838 1.00 0.00 H \nATOM 870 HG13 VAL A 116 -17.029 22.117 38.841 1.00 0.00 H \nATOM 871 HG21 VAL A 116 -17.133 24.513 40.587 1.00 0.00 H \nATOM 872 HG22 VAL A 116 -16.284 24.530 39.250 1.00 0.00 H \nATOM 873 HG23 VAL A 116 -17.393 25.633 39.498 1.00 0.00 H \nATOM 874 N PHE A 117 -18.395 22.094 36.084 1.00 0.00 N \nATOM 875 CA PHE A 117 -19.049 21.104 35.229 1.00 0.00 C \nATOM 876 C PHE A 117 -18.511 19.716 35.565 1.00 0.00 C \nATOM 877 O PHE A 117 -17.410 19.350 35.144 1.00 0.00 O \nATOM 878 CB PHE A 117 -18.842 21.454 33.759 1.00 0.00 C \nATOM 879 CG PHE A 117 -19.021 22.917 33.462 1.00 0.00 C \nATOM 880 CD1 PHE A 117 -20.289 23.456 33.320 1.00 0.00 C \nATOM 881 CD2 PHE A 117 -17.926 23.758 33.350 1.00 0.00 C \nATOM 882 CE1 PHE A 117 -20.461 24.802 33.057 1.00 0.00 C \nATOM 883 CE2 PHE A 117 -18.094 25.105 33.090 1.00 0.00 C \nATOM 884 CZ PHE A 117 -19.362 25.628 32.942 1.00 0.00 C \nATOM 885 H PHE A 117 -17.541 22.007 36.130 1.00 0.00 H \nATOM 886 HA PHE A 117 -20.005 21.107 35.392 1.00 0.00 H \nATOM 887 HB2 PHE A 117 -17.950 21.183 33.492 1.00 0.00 H \nATOM 888 HB3 PHE A 117 -19.467 20.943 33.221 1.00 0.00 H \nATOM 889 HD1 PHE A 117 -21.034 22.905 33.403 1.00 0.00 H \nATOM 890 HD2 PHE A 117 -17.068 23.412 33.451 1.00 0.00 H \nATOM 891 HE1 PHE A 117 -21.317 25.151 32.958 1.00 0.00 H \nATOM 892 HE2 PHE A 117 -17.351 25.660 33.015 1.00 0.00 H \nATOM 893 HZ PHE A 117 -19.476 26.534 32.765 1.00 0.00 H \nATOM 894 N ASP A 118 -19.293 18.950 36.323 1.00 0.00 N \nATOM 895 CA ASP A 118 -18.939 17.585 36.698 1.00 0.00 C \nATOM 896 C ASP A 118 -19.370 16.652 35.573 1.00 0.00 C \nATOM 897 O ASP A 118 -20.564 16.382 35.405 1.00 0.00 O \nATOM 898 CB ASP A 118 -19.606 17.206 38.020 1.00 0.00 C \nATOM 899 CG ASP A 118 -19.143 15.857 38.560 1.00 0.00 C \nATOM 900 OD1 ASP A 118 -18.640 15.016 37.785 1.00 0.00 O \nATOM 901 OD2 ASP A 118 -19.288 15.637 39.782 1.00 0.00 O \nATOM 902 H ASP A 118 -20.050 19.211 36.636 1.00 0.00 H \nATOM 903 HA ASP A 118 -17.981 17.510 36.828 1.00 0.00 H \nATOM 904 HB2 ASP A 118 -19.419 17.893 38.679 1.00 0.00 H \nATOM 905 HB3 ASP A 118 -20.568 17.186 37.896 1.00 0.00 H \nATOM 906 N GLY A 119 -18.400 16.155 34.809 1.00 0.00 N \nATOM 907 CA GLY A 119 -18.709 15.237 33.735 1.00 0.00 C \nATOM 908 C GLY A 119 -18.836 13.802 34.214 1.00 0.00 C \nATOM 909 O GLY A 119 -18.279 13.406 35.236 1.00 0.00 O \nATOM 910 H GLY A 119 -17.565 16.339 34.900 1.00 0.00 H \nATOM 911 HA2 GLY A 119 -19.538 15.508 33.311 1.00 0.00 H \nATOM 912 HA3 GLY A 119 -18.015 15.289 33.060 1.00 0.00 H \nATOM 913 N HIS A 120 -19.594 13.016 33.451 1.00 0.00 N \nATOM 914 CA HIS A 120 -19.712 11.582 33.676 1.00 0.00 C \nATOM 915 C HIS A 120 -19.697 10.867 32.334 1.00 0.00 C \nATOM 916 O HIS A 120 -20.082 11.435 31.307 1.00 0.00 O \nATOM 917 CB HIS A 120 -20.983 11.220 34.458 1.00 0.00 C \nATOM 918 CG HIS A 120 -22.212 11.931 33.983 1.00 0.00 C \nATOM 919 ND1 HIS A 120 -22.638 13.124 34.524 1.00 0.00 N \nATOM 920 CD2 HIS A 120 -23.112 11.612 33.022 1.00 0.00 C \nATOM 921 CE1 HIS A 120 -23.745 13.512 33.916 1.00 0.00 C \nATOM 922 NE2 HIS A 120 -24.054 12.612 33.000 1.00 0.00 N \nATOM 923 H HIS A 120 -20.056 13.304 32.785 1.00 0.00 H \nATOM 924 HA HIS A 120 -18.958 11.297 34.216 1.00 0.00 H \nATOM 925 HB2 HIS A 120 -21.129 10.263 34.395 1.00 0.00 H \nATOM 926 HB3 HIS A 120 -20.844 11.425 35.396 1.00 0.00 H \nATOM 927 HD1 HIS A 120 -22.244 13.550 35.159 1.00 0.00 H \nATOM 928 HD2 HIS A 120 -23.095 10.857 32.479 1.00 0.00 H \nATOM 929 HE1 HIS A 120 -24.225 14.287 34.101 1.00 0.00 H \nATOM 930 HE2 HIS A 120 -24.734 12.646 32.475 1.00 0.00 H \nATOM 931 N GLY A 121 -19.238 9.615 32.352 1.00 0.00 N \nATOM 932 CA GLY A 121 -19.065 8.860 31.129 1.00 0.00 C \nATOM 933 C GLY A 121 -17.913 9.327 30.272 1.00 0.00 C \nATOM 934 O GLY A 121 -17.769 8.859 29.139 1.00 0.00 O \nATOM 935 H GLY A 121 -19.023 9.190 33.068 1.00 0.00 H \nATOM 936 HA2 GLY A 121 -18.930 7.926 31.354 1.00 0.00 H \nATOM 937 HA3 GLY A 121 -19.883 8.912 30.610 1.00 0.00 H \nATOM 938 N GLY A 122 -17.098 10.253 30.763 1.00 0.00 N \nATOM 939 CA GLY A 122 -16.076 10.847 29.925 1.00 0.00 C \nATOM 940 C GLY A 122 -15.982 12.325 30.233 1.00 0.00 C \nATOM 941 O GLY A 122 -16.791 12.834 31.010 1.00 0.00 O \nATOM 942 H GLY A 122 -17.122 10.547 31.571 1.00 0.00 H \nATOM 943 HA2 GLY A 122 -15.221 10.417 30.084 1.00 0.00 H \nATOM 944 HA3 GLY A 122 -16.291 10.713 28.989 1.00 0.00 H \nATOM 945 N ALA A 123 -15.020 13.042 29.661 1.00 0.00 N \nATOM 946 CA ALA A 123 -14.846 14.447 30.008 1.00 0.00 C \nATOM 947 C ALA A 123 -15.188 15.415 28.898 1.00 0.00 C \nATOM 948 O ALA A 123 -15.158 16.643 29.119 1.00 0.00 O \nATOM 949 CB ALA A 123 -13.401 14.696 30.431 1.00 0.00 C \nATOM 950 H ALA A 123 -14.465 12.739 29.078 1.00 0.00 H \nATOM 951 HA ALA A 123 -15.471 14.614 30.731 1.00 0.00 H \nATOM 952 HB1 ALA A 123 -13.288 15.631 30.661 1.00 0.00 H \nATOM 953 HB2 ALA A 123 -13.190 14.146 31.201 1.00 0.00 H \nATOM 954 HB3 ALA A 123 -12.806 14.469 29.699 1.00 0.00 H \nATOM 955 N GLU A 124 -15.445 14.877 27.710 1.00 0.00 N \nATOM 956 CA GLU A 124 -15.726 15.672 26.517 1.00 0.00 C \nATOM 957 C GLU A 124 -16.929 16.602 26.601 1.00 0.00 C \nATOM 958 O GLU A 124 -16.956 17.644 25.946 1.00 0.00 O \nATOM 959 CB GLU A 124 -15.870 14.757 25.297 1.00 0.00 C \nATOM 960 CG GLU A 124 -16.331 13.347 25.629 1.00 0.00 C \nATOM 961 CD GLU A 124 -15.182 12.362 25.709 1.00 0.00 C \nATOM 962 OE1 GLU A 124 -14.615 12.195 26.809 1.00 0.00 O \nATOM 963 OE2 GLU A 124 -14.845 11.754 24.671 1.00 0.00 O \nATOM 964 H GLU A 124 -15.461 14.028 27.571 1.00 0.00 H \nATOM 965 HA GLU A 124 -14.959 16.260 26.434 1.00 0.00 H \nATOM 966 HB2 GLU A 124 -16.502 15.156 24.678 1.00 0.00 H \nATOM 967 HB3 GLU A 124 -15.016 14.708 24.839 1.00 0.00 H \nATOM 968 HG2 GLU A 124 -16.804 13.356 26.476 1.00 0.00 H \nATOM 969 HG3 GLU A 124 -16.961 13.049 24.955 1.00 0.00 H \nATOM 970 N VAL A 125 -17.925 16.232 27.395 1.00 0.00 N \nATOM 971 CA VAL A 125 -19.125 17.070 27.505 1.00 0.00 C \nATOM 972 C VAL A 125 -18.894 18.191 28.519 1.00 0.00 C \nATOM 973 O VAL A 125 -19.302 19.336 28.294 1.00 0.00 O \nATOM 974 CB VAL A 125 -20.395 16.271 27.878 1.00 0.00 C \nATOM 975 CG1 VAL A 125 -21.522 17.240 28.292 1.00 0.00 C \nATOM 976 CG2 VAL A 125 -20.915 15.436 26.726 1.00 0.00 C \nATOM 977 H VAL A 125 -17.933 15.516 27.872 1.00 0.00 H \nATOM 978 HA VAL A 125 -19.281 17.446 26.625 1.00 0.00 H \nATOM 979 HB VAL A 125 -20.144 15.681 28.606 1.00 0.00 H \nATOM 980 HG11 VAL A 125 -22.316 16.733 28.525 1.00 0.00 H \nATOM 981 HG12 VAL A 125 -21.236 17.761 29.058 1.00 0.00 H \nATOM 982 HG13 VAL A 125 -21.724 17.836 27.554 1.00 0.00 H \nATOM 983 HG21 VAL A 125 -21.709 14.955 27.007 1.00 0.00 H \nATOM 984 HG22 VAL A 125 -21.136 16.015 25.980 1.00 0.00 H \nATOM 985 HG23 VAL A 125 -20.234 14.802 26.452 1.00 0.00 H \nATOM 986 N ALA A 126 -18.213 17.894 29.634 1.00 0.00 N \nATOM 987 CA ALA A 126 -17.873 18.939 30.601 1.00 0.00 C \nATOM 988 C ALA A 126 -16.939 19.976 29.993 1.00 0.00 C \nATOM 989 O ALA A 126 -17.104 21.182 30.218 1.00 0.00 O \nATOM 990 CB ALA A 126 -17.247 18.329 31.853 1.00 0.00 C \nATOM 991 H ALA A 126 -17.944 17.105 29.844 1.00 0.00 H \nATOM 992 HA ALA A 126 -18.696 19.388 30.851 1.00 0.00 H \nATOM 993 HB1 ALA A 126 -17.028 19.034 32.482 1.00 0.00 H \nATOM 994 HB2 ALA A 126 -17.876 17.714 32.263 1.00 0.00 H \nATOM 995 HB3 ALA A 126 -16.439 17.850 31.611 1.00 0.00 H \nATOM 996 N ASN A 127 -15.936 19.521 29.236 1.00 0.00 N \nATOM 997 CA ASN A 127 -15.028 20.451 28.571 1.00 0.00 C \nATOM 998 C ASN A 127 -15.772 21.329 27.572 1.00 0.00 C \nATOM 999 O ASN A 127 -15.450 22.513 27.411 1.00 0.00 O \nATOM 1000 CB ASN A 127 -13.900 19.688 27.876 1.00 0.00 C \nATOM 1001 CG ASN A 127 -12.859 19.169 28.852 1.00 0.00 C \nATOM 1002 OD1 ASN A 127 -12.704 19.696 29.953 1.00 0.00 O \nATOM 1003 ND2 ASN A 127 -12.140 18.128 28.450 1.00 0.00 N \nATOM 1004 H ASN A 127 -15.768 18.689 29.098 1.00 0.00 H \nATOM 1005 HA ASN A 127 -14.643 21.030 29.248 1.00 0.00 H \nATOM 1006 HB2 ASN A 127 -14.275 18.943 27.382 1.00 0.00 H \nATOM 1007 HB3 ASN A 127 -13.471 20.270 27.230 1.00 0.00 H \nATOM 1008 HD21 ASN A 127 -11.538 17.796 28.967 1.00 0.00 H \nATOM 1009 HD22 ASN A 127 -12.276 17.786 27.673 1.00 0.00 H \nATOM 1010 N TYR A 128 -16.761 20.761 26.881 1.00 0.00 N \nATOM 1011 CA TYR A 128 -17.553 21.552 25.946 1.00 0.00 C \nATOM 1012 C TYR A 128 -18.332 22.643 26.669 1.00 0.00 C \nATOM 1013 O TYR A 128 -18.499 23.750 26.143 1.00 0.00 O \nATOM 1014 CB TYR A 128 -18.502 20.651 25.159 1.00 0.00 C \nATOM 1015 CG TYR A 128 -19.117 21.347 23.970 1.00 0.00 C \nATOM 1016 CD1 TYR A 128 -18.466 21.370 22.745 1.00 0.00 C \nATOM 1017 CD2 TYR A 128 -20.338 22.001 24.077 1.00 0.00 C \nATOM 1018 CE1 TYR A 128 -19.019 22.013 21.653 1.00 0.00 C \nATOM 1019 CE2 TYR A 128 -20.899 22.650 22.990 1.00 0.00 C \nATOM 1020 CZ TYR A 128 -20.235 22.652 21.782 1.00 0.00 C \nATOM 1021 OH TYR A 128 -20.785 23.295 20.696 1.00 0.00 O \nATOM 1022 H TYR A 128 -16.985 19.933 26.939 1.00 0.00 H \nATOM 1023 HA TYR A 128 -16.944 21.982 25.326 1.00 0.00 H \nATOM 1024 HB2 TYR A 128 -18.019 19.867 24.855 1.00 0.00 H \nATOM 1025 HB3 TYR A 128 -19.208 20.340 25.747 1.00 0.00 H \nATOM 1026 HD1 TYR A 128 -17.643 20.945 22.657 1.00 0.00 H \nATOM 1027 HD2 TYR A 128 -20.786 22.003 24.892 1.00 0.00 H \nATOM 1028 HE1 TYR A 128 -18.574 22.015 20.836 1.00 0.00 H \nATOM 1029 HE2 TYR A 128 -21.718 23.082 23.074 1.00 0.00 H \nATOM 1030 HH TYR A 128 -21.140 24.014 20.946 1.00 0.00 H \nATOM 1031 N CYS A 129 -18.829 22.346 27.873 1.00 0.00 N \nATOM 1032 CA CYS A 129 -19.568 23.348 28.635 1.00 0.00 C \nATOM 1033 C CYS A 129 -18.667 24.505 29.049 1.00 0.00 C \nATOM 1034 O CYS A 129 -19.085 25.669 29.015 1.00 0.00 O \nATOM 1035 CB CYS A 129 -20.212 22.703 29.863 1.00 0.00 C \nATOM 1036 SG CYS A 129 -21.643 21.657 29.506 1.00 0.00 S \nATOM 1037 H CYS A 129 -18.750 21.582 28.259 1.00 0.00 H \nATOM 1038 HA CYS A 129 -20.266 23.708 28.065 1.00 0.00 H \nATOM 1039 HB2 CYS A 129 -19.543 22.170 30.321 1.00 0.00 H \nATOM 1040 HB3 CYS A 129 -20.484 23.404 30.476 1.00 0.00 H \nATOM 1041 HG CYS A 129 -21.276 20.642 28.981 1.00 0.00 H \nATOM 1042 N ARG A 130 -17.431 24.201 29.455 1.00 0.00 N \nATOM 1043 CA ARG A 130 -16.488 25.254 29.819 1.00 0.00 C \nATOM 1044 C ARG A 130 -16.202 26.178 28.640 1.00 0.00 C \nATOM 1045 O ARG A 130 -16.084 27.397 28.811 1.00 0.00 O \nATOM 1046 CB ARG A 130 -15.194 24.632 30.347 1.00 0.00 C \nATOM 1047 CG ARG A 130 -13.960 25.511 30.191 1.00 0.00 C \nATOM 1048 CD ARG A 130 -12.681 24.705 30.357 1.00 0.00 C \nATOM 1049 NE ARG A 130 -12.345 23.953 29.149 1.00 0.00 N \nATOM 1050 CZ ARG A 130 -11.744 22.768 29.149 1.00 0.00 C \nATOM 1051 NH1 ARG A 130 -11.410 22.192 30.296 1.00 0.00 N \nATOM 1052 NH2 ARG A 130 -11.477 22.158 28.003 1.00 0.00 N \nATOM 1053 H ARG A 130 -17.125 23.400 29.525 1.00 0.00 H \nATOM 1054 HA ARG A 130 -16.888 25.793 30.519 1.00 0.00 H \nATOM 1055 HB2 ARG A 130 -15.310 24.421 31.287 1.00 0.00 H \nATOM 1056 HB3 ARG A 130 -15.040 23.793 29.885 1.00 0.00 H \nATOM 1057 HG2 ARG A 130 -13.968 25.931 29.317 1.00 0.00 H \nATOM 1058 HG3 ARG A 130 -13.983 26.224 30.849 1.00 0.00 H \nATOM 1059 HD2 ARG A 130 -11.950 25.303 30.578 1.00 0.00 H \nATOM 1060 HD3 ARG A 130 -12.781 24.091 31.101 1.00 0.00 H \nATOM 1061 HE ARG A 130 -12.550 24.300 28.389 1.00 0.00 H \nATOM 1062 HH11 ARG A 130 -11.582 22.586 31.041 1.00 0.00 H \nATOM 1063 HH12 ARG A 130 -11.021 21.425 30.295 1.00 0.00 H \nATOM 1064 HH21 ARG A 130 -11.693 22.529 27.258 1.00 0.00 H \nATOM 1065 HH22 ARG A 130 -11.088 21.391 28.005 1.00 0.00 H \nATOM 1066 N GLU A 131 -16.095 25.617 27.435 1.00 0.00 N \nATOM 1067 CA GLU A 131 -15.757 26.418 26.264 1.00 0.00 C \nATOM 1068 C GLU A 131 -16.936 27.237 25.753 1.00 0.00 C \nATOM 1069 O GLU A 131 -16.740 28.357 25.271 1.00 0.00 O \nATOM 1070 CB GLU A 131 -15.238 25.519 25.138 1.00 0.00 C \nATOM 1071 CG GLU A 131 -13.898 24.855 25.413 1.00 0.00 C \nATOM 1072 CD GLU A 131 -12.880 25.811 26.001 1.00 0.00 C \nATOM 1073 OE1 GLU A 131 -12.408 25.559 27.130 1.00 0.00 O \nATOM 1074 OE2 GLU A 131 -12.553 26.817 25.336 1.00 0.00 O \nATOM 1075 H GLU A 131 -16.214 24.780 27.277 1.00 0.00 H \nATOM 1076 HA GLU A 131 -15.066 27.039 26.542 1.00 0.00 H \nATOM 1077 HB2 GLU A 131 -15.896 24.828 24.964 1.00 0.00 H \nATOM 1078 HB3 GLU A 131 -15.162 26.048 24.329 1.00 0.00 H \nATOM 1079 HG2 GLU A 131 -14.029 24.112 26.023 1.00 0.00 H \nATOM 1080 HG3 GLU A 131 -13.549 24.485 24.587 1.00 0.00 H \nATOM 1081 N ARG A 132 -18.156 26.710 25.848 1.00 0.00 N \nATOM 1082 CA ARG A 132 -19.262 27.191 25.031 1.00 0.00 C \nATOM 1083 C ARG A 132 -20.369 27.905 25.796 1.00 0.00 C \nATOM 1084 O ARG A 132 -21.000 28.802 25.232 1.00 0.00 O \nATOM 1085 CB ARG A 132 -19.880 26.017 24.258 1.00 0.00 C \nATOM 1086 CG ARG A 132 -21.007 26.400 23.317 1.00 0.00 C \nATOM 1087 CD ARG A 132 -20.487 26.693 21.924 1.00 0.00 C \nATOM 1088 NE ARG A 132 -21.561 27.101 21.022 1.00 0.00 N \nATOM 1089 CZ ARG A 132 -21.615 28.281 20.413 1.00 0.00 C \nATOM 1090 NH1 ARG A 132 -20.648 29.169 20.600 1.00 0.00 N \nATOM 1091 NH2 ARG A 132 -22.629 28.571 19.612 1.00 0.00 N \nATOM 1092 H ARG A 132 -18.362 26.069 26.384 1.00 0.00 H \nATOM 1093 HA ARG A 132 -18.871 27.853 24.439 1.00 0.00 H \nATOM 1094 HB2 ARG A 132 -19.182 25.580 23.746 1.00 0.00 H \nATOM 1095 HB3 ARG A 132 -20.214 25.366 24.895 1.00 0.00 H \nATOM 1096 HG2 ARG A 132 -21.656 25.680 23.277 1.00 0.00 H \nATOM 1097 HG3 ARG A 132 -21.469 27.180 23.663 1.00 0.00 H \nATOM 1098 HD2 ARG A 132 -19.818 27.394 21.969 1.00 0.00 H \nATOM 1099 HD3 ARG A 132 -20.048 25.904 21.569 1.00 0.00 H \nATOM 1100 HE ARG A 132 -22.198 26.543 20.876 1.00 0.00 H \nATOM 1101 HH11 ARG A 132 -19.986 28.981 21.115 1.00 0.00 H \nATOM 1102 HH12 ARG A 132 -20.683 29.933 20.206 1.00 0.00 H \nATOM 1103 HH21 ARG A 132 -23.255 27.995 19.485 1.00 0.00 H \nATOM 1104 HH22 ARG A 132 -22.662 29.335 19.219 1.00 0.00 H \nATOM 1105 N ILE A 133 -20.611 27.556 27.062 1.00 0.00 N \nATOM 1106 CA ILE A 133 -21.804 28.055 27.747 1.00 0.00 C \nATOM 1107 C ILE A 133 -21.749 29.571 27.909 1.00 0.00 C \nATOM 1108 O ILE A 133 -22.747 30.268 27.688 1.00 0.00 O \nATOM 1109 CB ILE A 133 -21.993 27.336 29.096 1.00 0.00 C \nATOM 1110 CG1 ILE A 133 -22.721 26.007 28.881 1.00 0.00 C \nATOM 1111 CG2 ILE A 133 -22.785 28.203 30.065 1.00 0.00 C \nATOM 1112 CD1 ILE A 133 -23.082 25.281 30.160 1.00 0.00 C \nATOM 1113 H ILE A 133 -20.108 27.042 27.533 1.00 0.00 H \nATOM 1114 HA ILE A 133 -22.580 27.857 27.200 1.00 0.00 H \nATOM 1115 HB ILE A 133 -21.117 27.168 29.477 1.00 0.00 H \nATOM 1116 HG12 ILE A 133 -23.532 26.173 28.375 1.00 0.00 H \nATOM 1117 HG13 ILE A 133 -22.162 25.428 28.339 1.00 0.00 H \nATOM 1118 HG21 ILE A 133 -22.893 27.733 30.907 1.00 0.00 H \nATOM 1119 HG22 ILE A 133 -22.310 29.035 30.218 1.00 0.00 H \nATOM 1120 HG23 ILE A 133 -23.658 28.395 29.688 1.00 0.00 H \nATOM 1121 HD11 ILE A 133 -23.538 24.452 29.944 1.00 0.00 H \nATOM 1122 HD12 ILE A 133 -22.274 25.084 30.660 1.00 0.00 H \nATOM 1123 HD13 ILE A 133 -23.665 25.840 30.696 1.00 0.00 H \nATOM 1124 N HIS A 134 -20.588 30.111 28.285 1.00 0.00 N \nATOM 1125 CA HIS A 134 -20.497 31.553 28.499 1.00 0.00 C \nATOM 1126 C HIS A 134 -20.607 32.318 27.184 1.00 0.00 C \nATOM 1127 O HIS A 134 -21.163 33.421 27.148 1.00 0.00 O \nATOM 1128 CB HIS A 134 -19.198 31.903 29.228 1.00 0.00 C \nATOM 1129 CG HIS A 134 -17.974 31.822 28.371 1.00 0.00 C \nATOM 1130 ND1 HIS A 134 -17.292 30.645 28.154 1.00 0.00 N \nATOM 1131 CD2 HIS A 134 -17.302 32.778 27.687 1.00 0.00 C \nATOM 1132 CE1 HIS A 134 -16.256 30.877 27.368 1.00 0.00 C \nATOM 1133 NE2 HIS A 134 -16.239 32.164 27.070 1.00 0.00 N \nATOM 1134 H HIS A 134 -19.860 29.672 28.418 1.00 0.00 H \nATOM 1135 HA HIS A 134 -21.244 31.822 29.056 1.00 0.00 H \nATOM 1136 HB2 HIS A 134 -19.271 32.802 29.586 1.00 0.00 H \nATOM 1137 HB3 HIS A 134 -19.092 31.305 29.984 1.00 0.00 H \nATOM 1138 HD1 HIS A 134 -17.507 29.879 28.480 1.00 0.00 H \nATOM 1139 HD2 HIS A 134 -17.519 33.681 27.643 1.00 0.00 H \nATOM 1140 HE1 HIS A 134 -15.643 30.242 27.074 1.00 0.00 H \nATOM 1141 HE2 HIS A 134 -15.657 32.554 26.571 1.00 0.00 H \nATOM 1142 N VAL A 135 -20.073 31.756 26.096 1.00 0.00 N \nATOM 1143 CA VAL A 135 -20.206 32.395 24.788 1.00 0.00 C \nATOM 1144 C VAL A 135 -21.671 32.454 24.376 1.00 0.00 C \nATOM 1145 O VAL A 135 -22.153 33.477 23.872 1.00 0.00 O \nATOM 1146 CB VAL A 135 -19.350 31.661 23.740 1.00 0.00 C \nATOM 1147 CG1 VAL A 135 -19.513 32.309 22.371 1.00 0.00 C \nATOM 1148 CG2 VAL A 135 -17.883 31.653 24.158 1.00 0.00 C \nATOM 1149 H VAL A 135 -19.636 31.015 26.095 1.00 0.00 H \nATOM 1150 HA VAL A 135 -19.878 33.306 24.847 1.00 0.00 H \nATOM 1151 HB VAL A 135 -19.656 30.742 23.683 1.00 0.00 H \nATOM 1152 HG11 VAL A 135 -18.968 31.836 21.722 1.00 0.00 H \nATOM 1153 HG12 VAL A 135 -20.444 32.268 22.102 1.00 0.00 H \nATOM 1154 HG13 VAL A 135 -19.230 33.236 22.416 1.00 0.00 H \nATOM 1155 HG21 VAL A 135 -17.358 31.188 23.488 1.00 0.00 H \nATOM 1156 HG22 VAL A 135 -17.565 32.566 24.241 1.00 0.00 H \nATOM 1157 HG23 VAL A 135 -17.792 31.201 25.011 1.00 0.00 H \nATOM 1158 N VAL A 136 -22.403 31.360 24.588 1.00 0.00 N \nATOM 1159 CA VAL A 136 -23.820 31.327 24.243 1.00 0.00 C \nATOM 1160 C VAL A 136 -24.606 32.261 25.154 1.00 0.00 C \nATOM 1161 O VAL A 136 -25.530 32.957 24.709 1.00 0.00 O \nATOM 1162 CB VAL A 136 -24.348 29.882 24.308 1.00 0.00 C \nATOM 1163 CG1 VAL A 136 -25.847 29.843 24.068 1.00 0.00 C \nATOM 1164 CG2 VAL A 136 -23.618 29.019 23.291 1.00 0.00 C \nATOM 1165 H VAL A 136 -22.098 30.631 24.929 1.00 0.00 H \nATOM 1166 HA VAL A 136 -23.937 31.641 23.333 1.00 0.00 H \nATOM 1167 HB VAL A 136 -24.180 29.529 25.196 1.00 0.00 H \nATOM 1168 HG11 VAL A 136 -26.158 28.925 24.113 1.00 0.00 H \nATOM 1169 HG12 VAL A 136 -26.297 30.371 24.746 1.00 0.00 H \nATOM 1170 HG13 VAL A 136 -26.044 30.208 23.191 1.00 0.00 H \nATOM 1171 HG21 VAL A 136 -23.954 28.110 23.336 1.00 0.00 H \nATOM 1172 HG22 VAL A 136 -23.765 29.374 22.400 1.00 0.00 H \nATOM 1173 HG23 VAL A 136 -22.668 29.022 23.487 1.00 0.00 H \nATOM 1174 N LEU A 137 -24.260 32.282 26.448 1.00 0.00 N \nATOM 1175 CA LEU A 137 -24.928 33.182 27.385 1.00 0.00 C \nATOM 1176 C LEU A 137 -24.735 34.638 26.993 1.00 0.00 C \nATOM 1177 O LEU A 137 -25.673 35.439 27.073 1.00 0.00 O \nATOM 1178 CB LEU A 137 -24.389 32.964 28.800 1.00 0.00 C \nATOM 1179 CG LEU A 137 -25.053 33.675 29.981 1.00 0.00 C \nATOM 1180 CD1 LEU A 137 -26.574 33.688 29.876 1.00 0.00 C \nATOM 1181 CD2 LEU A 137 -24.527 33.154 31.308 1.00 0.00 C \nATOM 1182 H LEU A 137 -23.648 31.788 26.796 1.00 0.00 H \nATOM 1183 HA LEU A 137 -25.876 32.980 27.359 1.00 0.00 H \nATOM 1184 HB2 LEU A 137 -24.422 32.011 28.979 1.00 0.00 H \nATOM 1185 HB3 LEU A 137 -23.453 33.220 28.796 1.00 0.00 H \nATOM 1186 HG LEU A 137 -24.798 34.610 29.943 1.00 0.00 H \nATOM 1187 HD11 LEU A 137 -26.948 34.148 30.644 1.00 0.00 H \nATOM 1188 HD12 LEU A 137 -26.839 34.148 29.064 1.00 0.00 H \nATOM 1189 HD13 LEU A 137 -26.905 32.776 29.853 1.00 0.00 H \nATOM 1190 HD21 LEU A 137 -24.965 33.622 32.036 1.00 0.00 H \nATOM 1191 HD22 LEU A 137 -24.710 32.204 31.378 1.00 0.00 H \nATOM 1192 HD23 LEU A 137 -23.570 33.303 31.358 1.00 0.00 H \nATOM 1193 N SER A 138 -23.521 34.998 26.575 1.00 0.00 N \nATOM 1194 CA SER A 138 -23.231 36.387 26.226 1.00 0.00 C \nATOM 1195 C SER A 138 -24.033 36.835 25.009 1.00 0.00 C \nATOM 1196 O SER A 138 -24.621 37.924 25.001 1.00 0.00 O \nATOM 1197 CB SER A 138 -21.732 36.568 25.979 1.00 0.00 C \nATOM 1198 OG SER A 138 -21.410 37.925 25.781 1.00 0.00 O \nATOM 1199 H SER A 138 -22.858 34.458 26.487 1.00 0.00 H \nATOM 1200 HA SER A 138 -23.496 36.945 26.974 1.00 0.00 H \nATOM 1201 HB2 SER A 138 -21.233 36.221 26.735 1.00 0.00 H \nATOM 1202 HB3 SER A 138 -21.465 36.053 25.202 1.00 0.00 H \nATOM 1203 HG SER A 138 -22.071 38.325 25.451 1.00 0.00 H \nATOM 1204 N ALA A 139 -24.059 36.008 23.963 1.00 0.00 N \nATOM 1205 CA ALA A 139 -24.859 36.333 22.787 1.00 0.00 C \nATOM 1206 C ALA A 139 -26.334 36.421 23.147 1.00 0.00 C \nATOM 1207 O ALA A 139 -27.079 37.225 22.572 1.00 0.00 O \nATOM 1208 CB ALA A 139 -24.632 35.295 21.690 1.00 0.00 C \nATOM 1209 H ALA A 139 -23.627 35.266 23.916 1.00 0.00 H \nATOM 1210 HA ALA A 139 -24.579 37.200 22.454 1.00 0.00 H \nATOM 1211 HB1 ALA A 139 -25.168 35.521 20.914 1.00 0.00 H \nATOM 1212 HB2 ALA A 139 -23.694 35.285 21.442 1.00 0.00 H \nATOM 1213 HB3 ALA A 139 -24.889 34.418 22.016 1.00 0.00 H \nATOM 1214 N ALA A 140 -26.773 35.599 24.100 1.00 0.00 N \nATOM 1215 CA ALA A 140 -28.157 35.651 24.551 1.00 0.00 C \nATOM 1216 C ALA A 140 -28.471 36.933 25.311 1.00 0.00 C \nATOM 1217 O ALA A 140 -29.573 37.478 25.172 1.00 0.00 O \nATOM 1218 CB ALA A 140 -28.469 34.425 25.404 1.00 0.00 C \nATOM 1219 H ALA A 140 -26.287 35.009 24.494 1.00 0.00 H \nATOM 1220 HA ALA A 140 -28.724 35.648 23.764 1.00 0.00 H \nATOM 1221 HB1 ALA A 140 -29.391 34.464 25.702 1.00 0.00 H \nATOM 1222 HB2 ALA A 140 -28.333 33.621 24.878 1.00 0.00 H \nATOM 1223 HB3 ALA A 140 -27.881 34.409 26.175 1.00 0.00 H \nATOM 1224 N LEU A 141 -27.519 37.433 26.098 1.00 0.00 N \nATOM 1225 CA LEU A 141 -27.739 38.661 26.853 1.00 0.00 C \nATOM 1226 C LEU A 141 -27.742 39.880 25.939 1.00 0.00 C \nATOM 1227 O LEU A 141 -28.531 40.810 26.140 1.00 0.00 O \nATOM 1228 CB LEU A 141 -26.673 38.791 27.939 1.00 0.00 C \nATOM 1229 CG LEU A 141 -26.984 38.016 29.223 1.00 0.00 C \nATOM 1230 CD1 LEU A 141 -25.846 38.157 30.213 1.00 0.00 C \nATOM 1231 CD2 LEU A 141 -28.297 38.485 29.829 1.00 0.00 C \nATOM 1232 H LEU A 141 -26.744 37.077 26.207 1.00 0.00 H \nATOM 1233 HA LEU A 141 -28.613 38.617 27.272 1.00 0.00 H \nATOM 1234 HB2 LEU A 141 -25.825 38.481 27.584 1.00 0.00 H \nATOM 1235 HB3 LEU A 141 -26.563 39.729 28.159 1.00 0.00 H \nATOM 1236 HG LEU A 141 -27.078 37.076 29.002 1.00 0.00 H \nATOM 1237 HD11 LEU A 141 -26.056 37.662 31.020 1.00 0.00 H \nATOM 1238 HD12 LEU A 141 -25.031 37.806 29.822 1.00 0.00 H \nATOM 1239 HD13 LEU A 141 -25.721 39.094 30.432 1.00 0.00 H \nATOM 1240 HD21 LEU A 141 -28.477 37.984 30.640 1.00 0.00 H \nATOM 1241 HD22 LEU A 141 -28.237 39.430 30.040 1.00 0.00 H \nATOM 1242 HD23 LEU A 141 -29.016 38.341 29.194 1.00 0.00 H \nATOM 1243 N ALA A 142 -26.836 39.888 25.015 1.00 0.00 N \nATOM 1244 CA ALA A 142 -26.718 40.990 24.140 1.00 0.00 C \nATOM 1245 C ALA A 142 -27.955 41.263 23.294 1.00 0.00 C \nATOM 1246 O ALA A 142 -28.240 42.384 23.009 1.00 0.00 O \nATOM 1247 CB ALA A 142 -25.486 40.846 23.298 1.00 0.00 C \nATOM 1248 H ALA A 142 -26.272 39.253 24.878 1.00 0.00 H \nATOM 1249 HA ALA A 142 -26.635 41.777 24.701 1.00 0.00 H \nATOM 1250 HB1 ALA A 142 -25.412 41.606 22.700 1.00 0.00 H \nATOM 1251 HB2 ALA A 142 -24.704 40.809 23.871 1.00 0.00 H \nATOM 1252 HB3 ALA A 142 -25.543 40.030 22.777 1.00 0.00 H \nATOM 1253 N ARG A 143 -28.676 40.209 22.925 1.00 0.00 N \nATOM 1254 CA ARG A 143 -29.880 40.348 22.112 1.00 0.00 C \nATOM 1255 C ARG A 143 -31.128 40.684 22.930 1.00 0.00 C \nATOM 1256 O ARG A 143 -32.042 41.341 22.431 1.00 0.00 O \nATOM 1257 CB ARG A 143 -30.119 39.077 21.293 1.00 0.00 C \nATOM 1258 CG ARG A 143 -30.855 37.982 22.048 1.00 0.00 C \nATOM 1259 CD ARG A 143 -31.568 37.037 21.094 1.00 0.00 C \nATOM 1260 NE ARG A 143 -31.496 35.650 21.542 1.00 0.00 N \nATOM 1261 CZ ARG A 143 -30.375 34.936 21.587 1.00 0.00 C \nATOM 1262 NH1 ARG A 143 -29.226 35.479 21.210 1.00 0.00 N \nATOM 1263 NH2 ARG A 143 -30.403 33.680 22.009 1.00 0.00 N \nATOM 1264 H ARG A 143 -28.483 39.398 23.137 1.00 0.00 H \nATOM 1265 HA ARG A 143 -29.723 41.100 21.519 1.00 0.00 H \nATOM 1266 HB2 ARG A 143 -30.626 39.306 20.499 1.00 0.00 H \nATOM 1267 HB3 ARG A 143 -29.264 38.731 20.993 1.00 0.00 H \nATOM 1268 HG2 ARG A 143 -30.226 37.482 22.592 1.00 0.00 H \nATOM 1269 HG3 ARG A 143 -31.499 38.381 22.654 1.00 0.00 H \nATOM 1270 HD2 ARG A 143 -32.498 37.302 21.013 1.00 0.00 H \nATOM 1271 HD3 ARG A 143 -31.173 37.112 20.211 1.00 0.00 H \nATOM 1272 HE ARG A 143 -32.225 35.270 21.793 1.00 0.00 H \nATOM 1273 HH11 ARG A 143 -29.205 36.294 20.936 1.00 0.00 H \nATOM 1274 HH12 ARG A 143 -28.502 35.016 21.240 1.00 0.00 H \nATOM 1275 HH21 ARG A 143 -31.147 33.325 22.254 1.00 0.00 H \nATOM 1276 HH22 ARG A 143 -29.677 33.220 22.037 1.00 0.00 H \nATOM 1277 N LEU A 144 -31.169 40.234 24.181 1.00 0.00 N \nATOM 1278 CA LEU A 144 -32.296 40.487 25.020 1.00 0.00 C \nATOM 1279 C LEU A 144 -32.312 41.953 25.259 1.00 0.00 C \nATOM 1280 O LEU A 144 -33.352 42.535 25.409 1.00 0.00 O \nATOM 1281 CB LEU A 144 -32.219 39.729 26.326 1.00 0.00 C \nATOM 1282 CG LEU A 144 -33.392 39.826 27.291 1.00 0.00 C \nATOM 1283 CD1 LEU A 144 -34.620 39.184 26.732 1.00 0.00 C \nATOM 1284 CD2 LEU A 144 -33.061 39.174 28.597 1.00 0.00 C \nATOM 1285 H LEU A 144 -30.541 39.778 24.552 1.00 0.00 H \nATOM 1286 HA LEU A 144 -33.111 40.184 24.591 1.00 0.00 H \nATOM 1287 HB2 LEU A 144 -32.087 38.791 26.116 1.00 0.00 H \nATOM 1288 HB3 LEU A 144 -31.425 40.029 26.795 1.00 0.00 H \nATOM 1289 HG LEU A 144 -33.565 40.770 27.429 1.00 0.00 H \nATOM 1290 HD11 LEU A 144 -35.346 39.263 27.370 1.00 0.00 H \nATOM 1291 HD12 LEU A 144 -34.868 39.625 25.904 1.00 0.00 H \nATOM 1292 HD13 LEU A 144 -34.444 38.246 26.558 1.00 0.00 H \nATOM 1293 HD21 LEU A 144 -33.820 39.247 29.197 1.00 0.00 H \nATOM 1294 HD22 LEU A 144 -32.855 38.238 28.449 1.00 0.00 H \nATOM 1295 HD23 LEU A 144 -32.293 39.615 28.993 1.00 0.00 H \nATOM 1296 N GLY A 145 -31.153 42.578 25.280 1.00 0.00 N \nATOM 1297 CA GLY A 145 -31.156 44.018 25.487 1.00 0.00 C \nATOM 1298 C GLY A 145 -31.805 44.773 24.345 1.00 0.00 C \nATOM 1299 O GLY A 145 -32.396 45.837 24.553 1.00 0.00 O \nATOM 1300 H GLY A 145 -30.381 42.211 25.182 1.00 0.00 H \nATOM 1301 HA2 GLY A 145 -31.625 44.221 26.312 1.00 0.00 H \nATOM 1302 HA3 GLY A 145 -30.243 44.327 25.596 1.00 0.00 H \nATOM 1303 N LYS A 146 -31.679 44.256 23.126 1.00 0.00 N \nATOM 1304 CA LYS A 146 -32.284 44.868 21.952 1.00 0.00 C \nATOM 1305 C LYS A 146 -33.803 44.728 21.990 1.00 0.00 C \nATOM 1306 O LYS A 146 -34.480 45.403 22.764 1.00 0.00 O \nATOM 1307 CB LYS A 146 -31.735 44.226 20.675 1.00 0.00 C \nATOM 1308 CG LYS A 146 -30.694 45.051 19.936 1.00 0.00 C \nATOM 1309 CD LYS A 146 -31.258 46.378 19.461 1.00 0.00 C \nATOM 1310 CE LYS A 146 -30.237 47.138 18.631 1.00 0.00 C \nATOM 1311 NZ LYS A 146 -30.227 46.685 17.212 1.00 0.00 N \nATOM 1312 H LYS A 146 -31.238 43.537 22.958 1.00 0.00 H \nATOM 1313 HA LYS A 146 -32.060 45.812 21.955 1.00 0.00 H \nATOM 1314 HB2 LYS A 146 -31.345 43.367 20.903 1.00 0.00 H \nATOM 1315 HB3 LYS A 146 -32.475 44.051 20.073 1.00 0.00 H \nATOM 1316 HG2 LYS A 146 -29.936 45.212 20.519 1.00 0.00 H \nATOM 1317 HG3 LYS A 146 -30.364 44.549 19.174 1.00 0.00 H \nATOM 1318 HD2 LYS A 146 -32.058 46.223 18.934 1.00 0.00 H \nATOM 1319 HD3 LYS A 146 -31.521 46.914 20.226 1.00 0.00 H \nATOM 1320 HE2 LYS A 146 -30.434 48.087 18.666 1.00 0.00 H \nATOM 1321 HE3 LYS A 146 -29.354 47.018 19.015 1.00 0.00 H \nATOM 1322 HZ1 LYS A 146 -29.963 47.355 16.688 1.00 0.00 H \nATOM 1323 HZ2 LYS A 146 -29.666 46.000 17.123 1.00 0.00 H \nATOM 1324 HZ3 LYS A 146 -31.046 46.429 16.976 1.00 0.00 H \nATOM 1325 N ASP A 155 -42.107 40.565 33.671 1.00 0.00 N \nATOM 1326 CA ASP A 155 -41.459 39.999 34.849 1.00 0.00 C \nATOM 1327 C ASP A 155 -40.011 39.624 34.542 1.00 0.00 C \nATOM 1328 O ASP A 155 -39.734 38.925 33.568 1.00 0.00 O \nATOM 1329 CB ASP A 155 -42.231 38.779 35.353 1.00 0.00 C \nATOM 1330 CG ASP A 155 -42.073 38.567 36.845 1.00 0.00 C \nATOM 1331 OD1 ASP A 155 -40.965 38.190 37.282 1.00 0.00 O \nATOM 1332 OD2 ASP A 155 -43.056 38.786 37.585 1.00 0.00 O \nATOM 1333 HA ASP A 155 -41.458 40.673 35.547 1.00 0.00 H \nATOM 1334 HB2 ASP A 155 -43.172 38.886 35.143 1.00 0.00 H \nATOM 1335 HB3 ASP A 155 -41.923 37.988 34.883 1.00 0.00 H \nATOM 1336 N MET A 156 -39.092 40.092 35.388 1.00 0.00 N \nATOM 1337 CA MET A 156 -37.669 39.890 35.139 1.00 0.00 C \nATOM 1338 C MET A 156 -37.180 38.522 35.593 1.00 0.00 C \nATOM 1339 O MET A 156 -36.199 38.011 35.045 1.00 0.00 O \nATOM 1340 CB MET A 156 -36.859 40.990 35.822 1.00 0.00 C \nATOM 1341 CG MET A 156 -37.242 42.372 35.348 1.00 0.00 C \nATOM 1342 SD MET A 156 -37.229 42.444 33.548 1.00 0.00 S \nATOM 1343 CE MET A 156 -38.504 43.660 33.258 1.00 0.00 C \nATOM 1344 H MET A 156 -39.273 40.527 36.108 1.00 0.00 H \nATOM 1345 HA MET A 156 -37.539 39.932 34.179 1.00 0.00 H \nATOM 1346 HB2 MET A 156 -36.988 40.934 36.782 1.00 0.00 H \nATOM 1347 HB3 MET A 156 -35.915 40.844 35.654 1.00 0.00 H \nATOM 1348 HG2 MET A 156 -38.124 42.602 35.680 1.00 0.00 H \nATOM 1349 HG3 MET A 156 -36.624 43.027 35.708 1.00 0.00 H \nATOM 1350 HE1 MET A 156 -38.606 43.801 32.304 1.00 0.00 H \nATOM 1351 HE2 MET A 156 -39.343 43.345 33.629 1.00 0.00 H \nATOM 1352 HE3 MET A 156 -38.257 44.496 33.683 1.00 0.00 H \nATOM 1353 N LYS A 157 -37.829 37.924 36.594 1.00 0.00 N \nATOM 1354 CA LYS A 157 -37.510 36.545 36.950 1.00 0.00 C \nATOM 1355 C LYS A 157 -37.772 35.604 35.780 1.00 0.00 C \nATOM 1356 O LYS A 157 -36.965 34.710 35.500 1.00 0.00 O \nATOM 1357 CB LYS A 157 -38.313 36.118 38.180 1.00 0.00 C \nATOM 1358 CG LYS A 157 -38.055 34.687 38.627 1.00 0.00 C \nATOM 1359 CD LYS A 157 -36.597 34.471 39.005 1.00 0.00 C \nATOM 1360 CE LYS A 157 -36.292 32.993 39.191 1.00 0.00 C \nATOM 1361 NZ LYS A 157 -35.108 32.765 40.063 1.00 0.00 N \nATOM 1362 H LYS A 157 -38.444 38.292 37.069 1.00 0.00 H \nATOM 1363 HA LYS A 157 -36.565 36.495 37.164 1.00 0.00 H \nATOM 1364 HB2 LYS A 157 -38.105 36.718 38.914 1.00 0.00 H \nATOM 1365 HB3 LYS A 157 -39.258 36.221 37.988 1.00 0.00 H \nATOM 1366 HG2 LYS A 157 -38.621 34.478 39.386 1.00 0.00 H \nATOM 1367 HG3 LYS A 157 -38.299 34.076 37.914 1.00 0.00 H \nATOM 1368 HD2 LYS A 157 -36.023 34.838 38.314 1.00 0.00 H \nATOM 1369 HD3 LYS A 157 -36.398 34.951 39.824 1.00 0.00 H \nATOM 1370 HE2 LYS A 157 -37.065 32.552 39.577 1.00 0.00 H \nATOM 1371 HE3 LYS A 157 -36.136 32.586 38.325 1.00 0.00 H \nATOM 1372 HZ1 LYS A 157 -35.074 31.908 40.300 1.00 0.00 H \nATOM 1373 HZ2 LYS A 157 -34.367 32.979 39.620 1.00 0.00 H \nATOM 1374 HZ3 LYS A 157 -35.174 33.271 40.792 1.00 0.00 H \nATOM 1375 N GLU A 158 -38.902 35.785 35.092 1.00 0.00 N \nATOM 1376 CA GLU A 158 -39.200 34.963 33.923 1.00 0.00 C \nATOM 1377 C GLU A 158 -38.141 35.143 32.843 1.00 0.00 C \nATOM 1378 O GLU A 158 -37.765 34.181 32.163 1.00 0.00 O \nATOM 1379 CB GLU A 158 -40.589 35.292 33.379 1.00 0.00 C \nATOM 1380 CG GLU A 158 -41.215 34.153 32.587 1.00 0.00 C \nATOM 1381 CD GLU A 158 -42.725 34.113 32.710 1.00 0.00 C \nATOM 1382 OE1 GLU A 158 -43.397 34.988 32.123 1.00 0.00 O \nATOM 1383 OE2 GLU A 158 -43.241 33.204 33.395 1.00 0.00 O \nATOM 1384 H GLU A 158 -39.501 36.372 35.285 1.00 0.00 H \nATOM 1385 HA GLU A 158 -39.190 34.033 34.197 1.00 0.00 H \nATOM 1386 HB2 GLU A 158 -41.173 35.521 34.119 1.00 0.00 H \nATOM 1387 HB3 GLU A 158 -40.529 36.077 32.812 1.00 0.00 H \nATOM 1388 HG2 GLU A 158 -40.973 34.243 31.652 1.00 0.00 H \nATOM 1389 HG3 GLU A 158 -40.847 33.310 32.895 1.00 0.00 H \nATOM 1390 N HIS A 159 -37.657 36.376 32.664 1.00 0.00 N \nATOM 1391 CA HIS A 159 -36.682 36.644 31.612 1.00 0.00 C \nATOM 1392 C HIS A 159 -35.346 35.974 31.915 1.00 0.00 C \nATOM 1393 O HIS A 159 -34.690 35.450 31.007 1.00 0.00 O \nATOM 1394 CB HIS A 159 -36.499 38.152 31.441 1.00 0.00 C \nATOM 1395 CG HIS A 159 -37.508 38.788 30.535 1.00 0.00 C \nATOM 1396 ND1 HIS A 159 -38.657 39.387 31.005 1.00 0.00 N \nATOM 1397 CD2 HIS A 159 -37.536 38.927 29.188 1.00 0.00 C \nATOM 1398 CE1 HIS A 159 -39.352 39.864 29.987 1.00 0.00 C \nATOM 1399 NE2 HIS A 159 -38.693 39.598 28.873 1.00 0.00 N \nATOM 1400 H HIS A 159 -37.879 37.060 33.136 1.00 0.00 H \nATOM 1401 HA HIS A 159 -37.018 36.271 30.782 1.00 0.00 H \nATOM 1402 HB2 HIS A 159 -36.548 38.575 32.312 1.00 0.00 H \nATOM 1403 HB3 HIS A 159 -35.610 38.323 31.092 1.00 0.00 H \nATOM 1404 HD1 HIS A 159 -38.886 39.442 31.832 1.00 0.00 H \nATOM 1405 HD2 HIS A 159 -36.892 38.625 28.588 1.00 0.00 H \nATOM 1406 HE1 HIS A 159 -40.166 40.311 30.045 1.00 0.00 H \nATOM 1407 HE2 HIS A 159 -38.947 39.810 28.079 1.00 0.00 H \nATOM 1408 N TRP A 160 -34.922 35.992 33.182 1.00 0.00 N \nATOM 1409 CA TRP A 160 -33.691 35.305 33.563 1.00 0.00 C \nATOM 1410 C TRP A 160 -33.798 33.809 33.295 1.00 0.00 C \nATOM 1411 O TRP A 160 -32.868 33.190 32.766 1.00 0.00 O \nATOM 1412 CB TRP A 160 -33.374 35.564 35.035 1.00 0.00 C \nATOM 1413 CG TRP A 160 -32.525 36.781 35.287 1.00 0.00 C \nATOM 1414 CD1 TRP A 160 -32.834 37.840 36.089 1.00 0.00 C \nATOM 1415 CD2 TRP A 160 -31.224 37.054 34.745 1.00 0.00 C \nATOM 1416 NE1 TRP A 160 -31.811 38.757 36.078 1.00 0.00 N \nATOM 1417 CE2 TRP A 160 -30.812 38.299 35.260 1.00 0.00 C \nATOM 1418 CE3 TRP A 160 -30.372 36.371 33.872 1.00 0.00 C \nATOM 1419 CZ2 TRP A 160 -29.586 38.874 34.932 1.00 0.00 C \nATOM 1420 CZ3 TRP A 160 -29.153 36.944 33.549 1.00 0.00 C \nATOM 1421 CH2 TRP A 160 -28.773 38.183 34.078 1.00 0.00 C \nATOM 1422 H TRP A 160 -35.328 36.391 33.826 1.00 0.00 H \nATOM 1423 HA TRP A 160 -32.966 35.656 33.022 1.00 0.00 H \nATOM 1424 HB2 TRP A 160 -34.208 35.659 35.522 1.00 0.00 H \nATOM 1425 HB3 TRP A 160 -32.921 34.787 35.398 1.00 0.00 H \nATOM 1426 HD1 TRP A 160 -33.623 37.929 36.573 1.00 0.00 H \nATOM 1427 HE1 TRP A 160 -31.800 39.498 36.514 1.00 0.00 H \nATOM 1428 HE3 TRP A 160 -30.619 35.548 33.515 1.00 0.00 H \nATOM 1429 HZ2 TRP A 160 -29.330 39.697 35.281 1.00 0.00 H \nATOM 1430 HZ3 TRP A 160 -28.577 36.498 32.971 1.00 0.00 H \nATOM 1431 HH2 TRP A 160 -27.949 38.544 33.843 1.00 0.00 H \nATOM 1432 N ASP A 161 -34.928 33.205 33.670 1.00 0.00 N \nATOM 1433 CA ASP A 161 -35.135 31.786 33.400 1.00 0.00 C \nATOM 1434 C ASP A 161 -35.141 31.492 31.906 1.00 0.00 C \nATOM 1435 O ASP A 161 -34.679 30.428 31.485 1.00 0.00 O \nATOM 1436 CB ASP A 161 -36.444 31.313 34.029 1.00 0.00 C \nATOM 1437 CG ASP A 161 -36.304 31.009 35.503 1.00 0.00 C \nATOM 1438 OD1 ASP A 161 -36.017 31.946 36.275 1.00 0.00 O \nATOM 1439 OD2 ASP A 161 -36.477 29.833 35.891 1.00 0.00 O \nATOM 1440 H ASP A 161 -35.578 33.595 34.077 1.00 0.00 H \nATOM 1441 HA ASP A 161 -34.394 31.302 33.796 1.00 0.00 H \nATOM 1442 HB2 ASP A 161 -37.123 31.995 33.906 1.00 0.00 H \nATOM 1443 HB3 ASP A 161 -36.753 30.518 33.566 1.00 0.00 H \nATOM 1444 N ASP A 162 -35.644 32.422 31.092 1.00 0.00 N \nATOM 1445 CA ASP A 162 -35.756 32.164 29.660 1.00 0.00 C \nATOM 1446 C ASP A 162 -34.399 32.242 28.975 1.00 0.00 C \nATOM 1447 O ASP A 162 -34.097 31.432 28.091 1.00 0.00 O \nATOM 1448 CB ASP A 162 -36.736 33.149 29.023 1.00 0.00 C \nATOM 1449 CG ASP A 162 -38.178 32.830 29.353 1.00 0.00 C \nATOM 1450 OD1 ASP A 162 -38.441 31.721 29.867 1.00 0.00 O \nATOM 1451 OD2 ASP A 162 -39.051 33.686 29.100 1.00 0.00 O \nATOM 1452 H ASP A 162 -35.921 33.196 31.346 1.00 0.00 H \nATOM 1453 HA ASP A 162 -36.094 31.263 29.542 1.00 0.00 H \nATOM 1454 HB2 ASP A 162 -36.529 34.047 29.326 1.00 0.00 H \nATOM 1455 HB3 ASP A 162 -36.618 33.140 28.060 1.00 0.00 H \nATOM 1456 N VAL A 163 -33.567 33.209 29.366 1.00 0.00 N \nATOM 1457 CA VAL A 163 -32.253 33.332 28.745 1.00 0.00 C \nATOM 1458 C VAL A 163 -31.359 32.173 29.163 1.00 0.00 C \nATOM 1459 O VAL A 163 -30.508 31.725 28.384 1.00 0.00 O \nATOM 1460 CB VAL A 163 -31.625 34.701 29.080 1.00 0.00 C \nATOM 1461 CG1 VAL A 163 -31.289 34.807 30.557 1.00 0.00 C \nATOM 1462 CG2 VAL A 163 -30.389 34.933 28.245 1.00 0.00 C \nATOM 1463 H VAL A 163 -33.741 33.790 29.975 1.00 0.00 H \nATOM 1464 HA VAL A 163 -32.351 33.288 27.781 1.00 0.00 H \nATOM 1465 HB VAL A 163 -32.279 35.386 28.871 1.00 0.00 H \nATOM 1466 HG11 VAL A 163 -30.897 35.675 30.738 1.00 0.00 H \nATOM 1467 HG12 VAL A 163 -32.098 34.702 31.081 1.00 0.00 H \nATOM 1468 HG13 VAL A 163 -30.657 34.111 30.796 1.00 0.00 H \nATOM 1469 HG21 VAL A 163 -30.006 35.796 28.466 1.00 0.00 H \nATOM 1470 HG22 VAL A 163 -29.740 34.235 28.427 1.00 0.00 H \nATOM 1471 HG23 VAL A 163 -30.626 34.917 27.305 1.00 0.00 H \nATOM 1472 N PHE A 164 -31.531 31.667 30.387 1.00 0.00 N \nATOM 1473 CA PHE A 164 -30.737 30.534 30.845 1.00 0.00 C \nATOM 1474 C PHE A 164 -31.257 29.215 30.281 1.00 0.00 C \nATOM 1475 O PHE A 164 -30.466 28.318 29.968 1.00 0.00 O \nATOM 1476 CB PHE A 164 -30.710 30.494 32.373 1.00 0.00 C \nATOM 1477 CG PHE A 164 -29.623 31.335 32.980 1.00 0.00 C \nATOM 1478 CD1 PHE A 164 -28.293 30.971 32.849 1.00 0.00 C \nATOM 1479 CD2 PHE A 164 -29.928 32.496 33.673 1.00 0.00 C \nATOM 1480 CE1 PHE A 164 -27.288 31.740 33.405 1.00 0.00 C \nATOM 1481 CE2 PHE A 164 -28.926 33.271 34.229 1.00 0.00 C \nATOM 1482 CZ PHE A 164 -27.605 32.894 34.096 1.00 0.00 C \nATOM 1483 H PHE A 164 -32.098 31.965 30.960 1.00 0.00 H \nATOM 1484 HA PHE A 164 -29.832 30.652 30.516 1.00 0.00 H \nATOM 1485 HB2 PHE A 164 -31.568 30.795 32.712 1.00 0.00 H \nATOM 1486 HB3 PHE A 164 -30.597 29.575 32.663 1.00 0.00 H \nATOM 1487 HD1 PHE A 164 -28.073 30.198 32.380 1.00 0.00 H \nATOM 1488 HD2 PHE A 164 -30.816 32.757 33.765 1.00 0.00 H \nATOM 1489 HE1 PHE A 164 -26.399 31.481 33.314 1.00 0.00 H \nATOM 1490 HE2 PHE A 164 -29.143 34.047 34.693 1.00 0.00 H \nATOM 1491 HZ PHE A 164 -26.931 33.414 34.470 1.00 0.00 H \nATOM 1492 N THR A 165 -32.580 29.076 30.153 1.00 0.00 N \nATOM 1493 CA THR A 165 -33.142 27.847 29.600 1.00 0.00 C \nATOM 1494 C THR A 165 -32.778 27.684 28.130 1.00 0.00 C \nATOM 1495 O THR A 165 -32.397 26.591 27.697 1.00 0.00 O \nATOM 1496 CB THR A 165 -34.662 27.832 29.775 1.00 0.00 C \nATOM 1497 OG1 THR A 165 -34.986 27.870 31.171 1.00 0.00 O \nATOM 1498 CG2 THR A 165 -35.263 26.583 29.154 1.00 0.00 C \nATOM 1499 H THR A 165 -33.158 29.672 30.377 1.00 0.00 H \nATOM 1500 HA THR A 165 -32.761 27.099 30.087 1.00 0.00 H \nATOM 1501 HB THR A 165 -35.030 28.611 29.329 1.00 0.00 H \nATOM 1502 HG1 THR A 165 -34.752 28.609 31.493 1.00 0.00 H \nATOM 1503 HG21 THR A 165 -36.225 26.592 29.275 1.00 0.00 H \nATOM 1504 HG22 THR A 165 -35.057 26.561 28.206 1.00 0.00 H \nATOM 1505 HG23 THR A 165 -34.891 25.797 29.583 1.00 0.00 H \nATOM 1506 N LYS A 166 -32.879 28.762 27.349 1.00 0.00 N \nATOM 1507 CA LYS A 166 -32.547 28.679 25.931 1.00 0.00 C \nATOM 1508 C LYS A 166 -31.051 28.506 25.714 1.00 0.00 C \nATOM 1509 O LYS A 166 -30.637 27.911 24.713 1.00 0.00 O \nATOM 1510 CB LYS A 166 -33.049 29.924 25.197 1.00 0.00 C \nATOM 1511 CG LYS A 166 -34.510 29.851 24.795 1.00 0.00 C \nATOM 1512 CD LYS A 166 -35.055 31.220 24.426 1.00 0.00 C \nATOM 1513 CE LYS A 166 -36.506 31.132 23.978 1.00 0.00 C \nATOM 1514 NZ LYS A 166 -37.353 32.179 24.614 1.00 0.00 N \nATOM 1515 H LYS A 166 -33.134 29.538 27.618 1.00 0.00 H \nATOM 1516 HA LYS A 166 -32.990 27.895 25.569 1.00 0.00 H \nATOM 1517 HB2 LYS A 166 -32.917 30.699 25.765 1.00 0.00 H \nATOM 1518 HB3 LYS A 166 -32.510 30.060 24.402 1.00 0.00 H \nATOM 1519 HG2 LYS A 166 -34.610 29.248 24.042 1.00 0.00 H \nATOM 1520 HG3 LYS A 166 -35.030 29.481 25.526 1.00 0.00 H \nATOM 1521 HD2 LYS A 166 -34.985 31.815 25.189 1.00 0.00 H \nATOM 1522 HD3 LYS A 166 -34.517 31.604 23.716 1.00 0.00 H \nATOM 1523 HE2 LYS A 166 -36.551 31.223 23.013 1.00 0.00 H \nATOM 1524 HE3 LYS A 166 -36.858 30.255 24.197 1.00 0.00 H \nATOM 1525 HZ1 LYS A 166 -37.793 32.628 23.984 1.00 0.00 H \nATOM 1526 HZ2 LYS A 166 -37.936 31.795 25.166 1.00 0.00 H \nATOM 1527 HZ3 LYS A 166 -36.837 32.741 25.072 1.00 0.00 H \nATOM 1528 N CYS A 167 -30.228 29.013 26.634 1.00 0.00 N \nATOM 1529 CA CYS A 167 -28.785 28.843 26.505 1.00 0.00 C \nATOM 1530 C CYS A 167 -28.380 27.405 26.807 1.00 0.00 C \nATOM 1531 O CYS A 167 -27.589 26.802 26.071 1.00 0.00 O \nATOM 1532 CB CYS A 167 -28.056 29.818 27.429 1.00 0.00 C \nATOM 1533 SG CYS A 167 -26.396 29.285 27.912 1.00 0.00 S \nATOM 1534 H CYS A 167 -30.482 29.451 27.329 1.00 0.00 H \nATOM 1535 HA CYS A 167 -28.532 29.037 25.589 1.00 0.00 H \nATOM 1536 HB2 CYS A 167 -27.992 30.679 26.988 1.00 0.00 H \nATOM 1537 HB3 CYS A 167 -28.588 29.948 28.229 1.00 0.00 H \nATOM 1538 HG CYS A 167 -26.475 28.491 28.808 1.00 0.00 H \nATOM 1539 N PHE A 168 -28.907 26.844 27.898 1.00 0.00 N \nATOM 1540 CA PHE A 168 -28.595 25.461 28.244 1.00 0.00 C \nATOM 1541 C PHE A 168 -29.139 24.496 27.197 1.00 0.00 C \nATOM 1542 O PHE A 168 -28.485 23.501 26.859 1.00 0.00 O \nATOM 1543 CB PHE A 168 -29.158 25.124 29.625 1.00 0.00 C \nATOM 1544 CG PHE A 168 -28.277 25.555 30.766 1.00 0.00 C \nATOM 1545 CD1 PHE A 168 -27.682 26.806 30.772 1.00 0.00 C \nATOM 1546 CD2 PHE A 168 -28.048 24.706 31.835 1.00 0.00 C \nATOM 1547 CE1 PHE A 168 -26.874 27.199 31.821 1.00 0.00 C \nATOM 1548 CE2 PHE A 168 -27.243 25.095 32.888 1.00 0.00 C \nATOM 1549 CZ PHE A 168 -26.653 26.343 32.880 1.00 0.00 C \nATOM 1550 H PHE A 168 -29.440 27.243 28.442 1.00 0.00 H \nATOM 1551 HA PHE A 168 -27.630 25.364 28.265 1.00 0.00 H \nATOM 1552 HB2 PHE A 168 -30.026 25.545 29.722 1.00 0.00 H \nATOM 1553 HB3 PHE A 168 -29.300 24.166 29.682 1.00 0.00 H \nATOM 1554 HD1 PHE A 168 -27.828 27.388 30.061 1.00 0.00 H \nATOM 1555 HD2 PHE A 168 -28.441 23.863 31.844 1.00 0.00 H \nATOM 1556 HE1 PHE A 168 -26.479 28.041 31.813 1.00 0.00 H \nATOM 1557 HE2 PHE A 168 -27.099 24.517 33.602 1.00 0.00 H \nATOM 1558 HZ PHE A 168 -26.108 26.606 33.586 1.00 0.00 H \nATOM 1559 N GLN A 169 -30.340 24.770 26.680 1.00 0.00 N \nATOM 1560 CA GLN A 169 -30.905 23.929 25.629 1.00 0.00 C \nATOM 1561 C GLN A 169 -30.067 23.989 24.358 1.00 0.00 C \nATOM 1562 O GLN A 169 -29.871 22.968 23.686 1.00 0.00 O \nATOM 1563 CB GLN A 169 -32.347 24.344 25.340 1.00 0.00 C \nATOM 1564 CG GLN A 169 -33.041 23.480 24.297 1.00 0.00 C \nATOM 1565 CD GLN A 169 -33.114 22.021 24.703 1.00 0.00 C \nATOM 1566 OE1 GLN A 169 -32.427 21.172 24.136 1.00 0.00 O \nATOM 1567 NE2 GLN A 169 -33.951 21.723 25.690 1.00 0.00 N \nATOM 1568 H GLN A 169 -30.836 25.430 26.922 1.00 0.00 H \nATOM 1569 HA GLN A 169 -30.898 23.011 25.943 1.00 0.00 H \nATOM 1570 HB2 GLN A 169 -32.855 24.310 26.165 1.00 0.00 H \nATOM 1571 HB3 GLN A 169 -32.355 25.266 25.040 1.00 0.00 H \nATOM 1572 HG2 GLN A 169 -33.939 23.816 24.149 1.00 0.00 H \nATOM 1573 HG3 GLN A 169 -32.568 23.554 23.454 1.00 0.00 H \nATOM 1574 HE21 GLN A 169 -34.415 22.344 26.062 1.00 0.00 H \nATOM 1575 HE22 GLN A 169 -34.029 20.909 25.957 1.00 0.00 H \nATOM 1576 N ARG A 170 -29.571 25.178 24.007 1.00 0.00 N \nATOM 1577 CA ARG A 170 -28.765 25.311 22.797 1.00 0.00 C \nATOM 1578 C ARG A 170 -27.468 24.521 22.912 1.00 0.00 C \nATOM 1579 O ARG A 170 -27.056 23.847 21.960 1.00 0.00 O \nATOM 1580 CB ARG A 170 -28.477 26.786 22.513 1.00 0.00 C \nATOM 1581 CG ARG A 170 -27.402 27.015 21.463 1.00 0.00 C \nATOM 1582 CD ARG A 170 -27.902 26.645 20.076 1.00 0.00 C \nATOM 1583 NE ARG A 170 -26.825 26.624 19.089 1.00 0.00 N \nATOM 1584 CZ ARG A 170 -27.015 26.492 17.780 1.00 0.00 C \nATOM 1585 NH1 ARG A 170 -28.243 26.367 17.295 1.00 0.00 N \nATOM 1586 NH2 ARG A 170 -25.976 26.483 16.955 1.00 0.00 N \nATOM 1587 H ARG A 170 -29.688 25.907 24.449 1.00 0.00 H \nATOM 1588 HA ARG A 170 -29.269 24.944 22.054 1.00 0.00 H \nATOM 1589 HB2 ARG A 170 -29.297 27.216 22.223 1.00 0.00 H \nATOM 1590 HB3 ARG A 170 -28.207 27.218 23.338 1.00 0.00 H \nATOM 1591 HG2 ARG A 170 -27.129 27.946 21.474 1.00 0.00 H \nATOM 1592 HG3 ARG A 170 -26.618 26.487 21.679 1.00 0.00 H \nATOM 1593 HD2 ARG A 170 -28.326 25.773 20.109 1.00 0.00 H \nATOM 1594 HD3 ARG A 170 -28.581 27.280 19.798 1.00 0.00 H \nATOM 1595 HE ARG A 170 -26.017 26.702 19.373 1.00 0.00 H \nATOM 1596 HH11 ARG A 170 -28.918 26.371 17.828 1.00 0.00 H \nATOM 1597 HH12 ARG A 170 -28.364 26.282 16.448 1.00 0.00 H \nATOM 1598 HH21 ARG A 170 -25.179 26.563 17.267 1.00 0.00 H \nATOM 1599 HH22 ARG A 170 -26.100 26.398 16.108 1.00 0.00 H \nATOM 1600 N VAL A 171 -26.808 24.596 24.069 1.00 0.00 N \nATOM 1601 CA VAL A 171 -25.590 23.822 24.281 1.00 0.00 C \nATOM 1602 C VAL A 171 -25.895 22.328 24.266 1.00 0.00 C \nATOM 1603 O VAL A 171 -25.138 21.532 23.695 1.00 0.00 O \nATOM 1604 CB VAL A 171 -24.909 24.253 25.593 1.00 0.00 C \nATOM 1605 CG1 VAL A 171 -23.767 23.308 25.942 1.00 0.00 C \nATOM 1606 CG2 VAL A 171 -24.410 25.684 25.479 1.00 0.00 C \nATOM 1607 H VAL A 171 -27.047 25.084 24.735 1.00 0.00 H \nATOM 1608 HA VAL A 171 -24.972 23.998 23.554 1.00 0.00 H \nATOM 1609 HB VAL A 171 -25.562 24.211 26.309 1.00 0.00 H \nATOM 1610 HG11 VAL A 171 -23.351 23.595 26.770 1.00 0.00 H \nATOM 1611 HG12 VAL A 171 -24.113 22.408 26.049 1.00 0.00 H \nATOM 1612 HG13 VAL A 171 -23.109 23.318 25.229 1.00 0.00 H \nATOM 1613 HG21 VAL A 171 -23.983 25.945 26.310 1.00 0.00 H \nATOM 1614 HG22 VAL A 171 -23.769 25.747 24.753 1.00 0.00 H \nATOM 1615 HG23 VAL A 171 -25.159 26.275 25.301 1.00 0.00 H \nATOM 1616 N ASP A 172 -27.004 21.924 24.893 1.00 0.00 N \nATOM 1617 CA ASP A 172 -27.390 20.516 24.872 1.00 0.00 C \nATOM 1618 C ASP A 172 -27.647 20.037 23.449 1.00 0.00 C \nATOM 1619 O ASP A 172 -27.233 18.934 23.072 1.00 0.00 O \nATOM 1620 CB ASP A 172 -28.626 20.294 25.743 1.00 0.00 C \nATOM 1621 CG ASP A 172 -28.933 18.823 25.952 1.00 0.00 C \nATOM 1622 OD1 ASP A 172 -28.353 18.218 26.878 1.00 0.00 O \nATOM 1623 OD2 ASP A 172 -29.753 18.269 25.188 1.00 0.00 O \nATOM 1624 H ASP A 172 -27.536 22.441 25.328 1.00 0.00 H \nATOM 1625 HA ASP A 172 -26.655 19.996 25.233 1.00 0.00 H \nATOM 1626 HB2 ASP A 172 -28.491 20.719 26.605 1.00 0.00 H \nATOM 1627 HB3 ASP A 172 -29.391 20.725 25.330 1.00 0.00 H \nATOM 1628 N ASP A 173 -28.341 20.849 22.648 1.00 0.00 N \nATOM 1629 CA ASP A 173 -28.592 20.485 21.259 1.00 0.00 C \nATOM 1630 C ASP A 173 -27.302 20.432 20.450 1.00 0.00 C \nATOM 1631 O ASP A 173 -27.192 19.625 19.520 1.00 0.00 O \nATOM 1632 CB ASP A 173 -29.583 21.465 20.632 1.00 0.00 C \nATOM 1633 CG ASP A 173 -31.002 21.239 21.112 1.00 0.00 C \nATOM 1634 OD1 ASP A 173 -31.300 20.117 21.577 1.00 0.00 O \nATOM 1635 OD2 ASP A 173 -31.823 22.177 21.027 1.00 0.00 O \nATOM 1636 H ASP A 173 -28.670 21.606 22.889 1.00 0.00 H \nATOM 1637 HA ASP A 173 -28.977 19.595 21.247 1.00 0.00 H \nATOM 1638 HB2 ASP A 173 -29.314 22.373 20.843 1.00 0.00 H \nATOM 1639 HB3 ASP A 173 -29.553 21.378 19.666 1.00 0.00 H \nATOM 1640 N GLU A 174 -26.329 21.287 20.771 1.00 0.00 N \nATOM 1641 CA GLU A 174 -25.030 21.207 20.108 1.00 0.00 C \nATOM 1642 C GLU A 174 -24.288 19.936 20.500 1.00 0.00 C \nATOM 1643 O GLU A 174 -23.669 19.285 19.651 1.00 0.00 O \nATOM 1644 CB GLU A 174 -24.187 22.438 20.442 1.00 0.00 C \nATOM 1645 CG GLU A 174 -24.465 23.648 19.567 1.00 0.00 C \nATOM 1646 CD GLU A 174 -23.849 24.920 20.118 1.00 0.00 C \nATOM 1647 OE1 GLU A 174 -24.430 26.005 19.903 1.00 0.00 O \nATOM 1648 OE2 GLU A 174 -22.782 24.837 20.763 1.00 0.00 O \nATOM 1649 H GLU A 174 -26.400 21.910 21.360 1.00 0.00 H \nATOM 1650 HA GLU A 174 -25.184 21.181 19.151 1.00 0.00 H \nATOM 1651 HB2 GLU A 174 -24.342 22.680 21.368 1.00 0.00 H \nATOM 1652 HB3 GLU A 174 -23.249 22.205 20.363 1.00 0.00 H \nATOM 1653 HG2 GLU A 174 -24.119 23.485 18.676 1.00 0.00 H \nATOM 1654 HG3 GLU A 174 -25.424 23.768 19.481 1.00 0.00 H \nATOM 1655 N VAL A 175 -24.328 19.577 21.786 1.00 0.00 N \nATOM 1656 CA VAL A 175 -23.617 18.391 22.258 1.00 0.00 C \nATOM 1657 C VAL A 175 -24.184 17.131 21.614 1.00 0.00 C \nATOM 1658 O VAL A 175 -23.437 16.222 21.229 1.00 0.00 O \nATOM 1659 CB VAL A 175 -23.672 18.317 23.797 1.00 0.00 C \nATOM 1660 CG1 VAL A 175 -23.324 16.918 24.286 1.00 0.00 C \nATOM 1661 CG2 VAL A 175 -22.741 19.350 24.412 1.00 0.00 C \nATOM 1662 H VAL A 175 -24.758 20.005 22.395 1.00 0.00 H \nATOM 1663 HA VAL A 175 -22.686 18.456 21.995 1.00 0.00 H \nATOM 1664 HB VAL A 175 -24.579 18.515 24.079 1.00 0.00 H \nATOM 1665 HG11 VAL A 175 -23.365 16.894 25.255 1.00 0.00 H \nATOM 1666 HG12 VAL A 175 -23.957 16.280 23.920 1.00 0.00 H \nATOM 1667 HG13 VAL A 175 -22.428 16.687 23.995 1.00 0.00 H \nATOM 1668 HG21 VAL A 175 -22.786 19.292 25.379 1.00 0.00 H \nATOM 1669 HG22 VAL A 175 -21.832 19.180 24.120 1.00 0.00 H \nATOM 1670 HG23 VAL A 175 -23.011 20.238 24.129 1.00 0.00 H \nATOM 1671 N SER A 176 -25.506 17.061 21.474 1.00 0.00 N \nATOM 1672 CA SER A 176 -26.170 15.865 20.973 1.00 0.00 C \nATOM 1673 C SER A 176 -26.268 15.819 19.453 1.00 0.00 C \nATOM 1674 O SER A 176 -26.776 14.832 18.911 1.00 0.00 O \nATOM 1675 CB SER A 176 -27.571 15.752 21.579 1.00 0.00 C \nATOM 1676 OG SER A 176 -28.466 16.654 20.953 1.00 0.00 O \nATOM 1677 H SER A 176 -26.041 17.706 21.667 1.00 0.00 H \nATOM 1678 HA SER A 176 -25.620 15.113 21.243 1.00 0.00 H \nATOM 1679 HB2 SER A 176 -27.898 14.844 21.480 1.00 0.00 H \nATOM 1680 HB3 SER A 176 -27.532 15.937 22.530 1.00 0.00 H \nATOM 1681 HG SER A 176 -28.313 17.434 21.224 1.00 0.00 H \nATOM 1682 N GLY A 177 -25.797 16.848 18.754 1.00 0.00 N \nATOM 1683 CA GLY A 177 -25.832 16.851 17.306 1.00 0.00 C \nATOM 1684 C GLY A 177 -27.163 17.174 16.660 1.00 0.00 C \nATOM 1685 O GLY A 177 -27.304 16.961 15.451 1.00 0.00 O \nATOM 1686 H GLY A 177 -25.453 17.554 19.105 1.00 0.00 H \nATOM 1687 HA2 GLY A 177 -25.177 17.492 16.988 1.00 0.00 H \nATOM 1688 HA3 GLY A 177 -25.548 15.978 16.994 1.00 0.00 H \nATOM 1689 N ARG A 178 -28.151 17.672 17.413 1.00 0.00 N \nATOM 1690 CA ARG A 178 -29.421 18.050 16.797 1.00 0.00 C \nATOM 1691 C ARG A 178 -29.354 19.372 16.056 1.00 0.00 C \nATOM 1692 O ARG A 178 -30.164 19.601 15.152 1.00 0.00 O \nATOM 1693 CB ARG A 178 -30.529 18.132 17.844 1.00 0.00 C \nATOM 1694 CG ARG A 178 -31.029 16.774 18.222 1.00 0.00 C \nATOM 1695 CD ARG A 178 -31.971 16.778 19.398 1.00 0.00 C \nATOM 1696 NE ARG A 178 -31.737 15.586 20.179 1.00 0.00 N \nATOM 1697 CZ ARG A 178 -31.242 15.594 21.409 1.00 0.00 C \nATOM 1698 NH1 ARG A 178 -30.954 16.752 21.988 1.00 0.00 N \nATOM 1699 NH2 ARG A 178 -31.034 14.447 22.065 1.00 0.00 N \nATOM 1700 H ARG A 178 -28.106 17.795 18.263 1.00 0.00 H \nATOM 1701 HA ARG A 178 -29.617 17.354 16.151 1.00 0.00 H \nATOM 1702 HB2 ARG A 178 -30.196 18.587 18.634 1.00 0.00 H \nATOM 1703 HB3 ARG A 178 -31.263 18.664 17.499 1.00 0.00 H \nATOM 1704 HG2 ARG A 178 -31.480 16.381 17.459 1.00 0.00 H \nATOM 1705 HG3 ARG A 178 -30.271 16.205 18.428 1.00 0.00 H \nATOM 1706 HD2 ARG A 178 -31.829 17.569 19.941 1.00 0.00 H \nATOM 1707 HD3 ARG A 178 -32.891 16.805 19.092 1.00 0.00 H \nATOM 1708 HE ARG A 178 -31.930 14.826 19.825 1.00 0.00 H \nATOM 1709 HH11 ARG A 178 -31.089 17.489 21.566 1.00 0.00 H \nATOM 1710 HH12 ARG A 178 -30.633 16.766 22.786 1.00 0.00 H \nATOM 1711 HH21 ARG A 178 -31.222 13.697 21.689 1.00 0.00 H \nATOM 1712 HH22 ARG A 178 -30.713 14.460 22.863 1.00 0.00 H \nATOM 1713 N VAL A 179 -28.424 20.247 16.425 1.00 0.00 N \nATOM 1714 CA VAL A 179 -28.136 21.442 15.653 1.00 0.00 C \nATOM 1715 C VAL A 179 -26.639 21.465 15.396 1.00 0.00 C \nATOM 1716 O VAL A 179 -25.861 20.762 16.045 1.00 0.00 O \nATOM 1717 CB VAL A 179 -28.592 22.738 16.358 1.00 0.00 C \nATOM 1718 CG1 VAL A 179 -30.060 22.647 16.753 1.00 0.00 C \nATOM 1719 CG2 VAL A 179 -27.720 23.024 17.573 1.00 0.00 C \nATOM 1720 H VAL A 179 -27.943 20.161 17.133 1.00 0.00 H \nATOM 1721 HA VAL A 179 -28.635 21.410 14.822 1.00 0.00 H \nATOM 1722 HB VAL A 179 -28.493 23.475 15.735 1.00 0.00 H \nATOM 1723 HG11 VAL A 179 -30.328 23.468 17.194 1.00 0.00 H \nATOM 1724 HG12 VAL A 179 -30.601 22.515 15.959 1.00 0.00 H \nATOM 1725 HG13 VAL A 179 -30.187 21.900 17.358 1.00 0.00 H \nATOM 1726 HG21 VAL A 179 -28.021 23.840 18.002 1.00 0.00 H \nATOM 1727 HG22 VAL A 179 -27.786 22.286 18.200 1.00 0.00 H \nATOM 1728 HG23 VAL A 179 -26.797 23.128 17.292 1.00 0.00 H \nATOM 1729 N THR A 180 -26.243 22.286 14.438 1.00 0.00 N \nATOM 1730 CA THR A 180 -24.855 22.362 14.020 1.00 0.00 C \nATOM 1731 C THR A 180 -24.083 23.354 14.886 1.00 0.00 C \nATOM 1732 O THR A 180 -24.659 24.202 15.570 1.00 0.00 O \nATOM 1733 CB THR A 180 -24.780 22.758 12.546 1.00 0.00 C \nATOM 1734 OG1 THR A 180 -25.039 24.162 12.413 1.00 0.00 O \nATOM 1735 CG2 THR A 180 -25.814 21.985 11.741 1.00 0.00 C \nATOM 1736 H THR A 180 -26.771 22.815 14.012 1.00 0.00 H \nATOM 1737 HA THR A 180 -24.446 21.489 14.131 1.00 0.00 H \nATOM 1738 HB THR A 180 -23.893 22.551 12.212 1.00 0.00 H \nATOM 1739 HG1 THR A 180 -25.010 24.377 11.601 1.00 0.00 H \nATOM 1740 HG21 THR A 180 -25.758 22.244 10.808 1.00 0.00 H \nATOM 1741 HG22 THR A 180 -25.643 21.034 11.823 1.00 0.00 H \nATOM 1742 HG23 THR A 180 -26.702 22.184 12.078 1.00 0.00 H \nATOM 1743 N ARG A 181 -22.757 23.229 14.855 1.00 0.00 N \nATOM 1744 CA ARG A 181 -21.886 24.092 15.639 1.00 0.00 C \nATOM 1745 C ARG A 181 -20.715 24.549 14.782 1.00 0.00 C \nATOM 1746 O ARG A 181 -20.314 23.872 13.834 1.00 0.00 O \nATOM 1747 CB ARG A 181 -21.379 23.388 16.904 1.00 0.00 C \nATOM 1748 CG ARG A 181 -20.406 22.255 16.645 1.00 0.00 C \nATOM 1749 CD ARG A 181 -20.172 21.447 17.910 1.00 0.00 C \nATOM 1750 NE ARG A 181 -19.534 20.164 17.630 1.00 0.00 N \nATOM 1751 CZ ARG A 181 -20.176 19.097 17.165 1.00 0.00 C \nATOM 1752 NH1 ARG A 181 -21.480 19.155 16.928 1.00 0.00 N \nATOM 1753 NH2 ARG A 181 -19.515 17.971 16.937 1.00 0.00 N \nATOM 1754 H ARG A 181 -22.342 22.644 14.381 1.00 0.00 H \nATOM 1755 HA ARG A 181 -22.401 24.863 15.924 1.00 0.00 H \nATOM 1756 HB2 ARG A 181 -20.950 24.044 17.475 1.00 0.00 H \nATOM 1757 HB3 ARG A 181 -22.140 23.040 17.394 1.00 0.00 H \nATOM 1758 HG2 ARG A 181 -20.753 21.678 15.947 1.00 0.00 H \nATOM 1759 HG3 ARG A 181 -19.564 22.613 16.324 1.00 0.00 H \nATOM 1760 HD2 ARG A 181 -19.617 21.957 18.520 1.00 0.00 H \nATOM 1761 HD3 ARG A 181 -21.019 21.295 18.357 1.00 0.00 H \nATOM 1762 HE ARG A 181 -18.689 20.094 17.775 1.00 0.00 H \nATOM 1763 HH11 ARG A 181 -21.912 19.884 17.075 1.00 0.00 H \nATOM 1764 HH12 ARG A 181 -21.894 18.464 16.627 1.00 0.00 H \nATOM 1765 HH21 ARG A 181 -18.670 17.930 17.090 1.00 0.00 H \nATOM 1766 HH22 ARG A 181 -19.931 17.281 16.636 1.00 0.00 H \nATOM 1767 N VAL A 182 -20.157 25.699 15.145 1.00 0.00 N \nATOM 1768 CA VAL A 182 -19.110 26.363 14.373 1.00 0.00 C \nATOM 1769 C VAL A 182 -17.742 25.954 14.897 1.00 0.00 C \nATOM 1770 O VAL A 182 -17.530 25.853 16.110 1.00 0.00 O \nATOM 1771 CB VAL A 182 -19.277 27.896 14.424 1.00 0.00 C \nATOM 1772 CG1 VAL A 182 -18.382 28.568 13.398 1.00 0.00 C \nATOM 1773 CG2 VAL A 182 -20.734 28.277 14.213 1.00 0.00 C \nATOM 1774 H VAL A 182 -20.379 26.123 15.859 1.00 0.00 H \nATOM 1775 HA VAL A 182 -19.186 26.087 13.446 1.00 0.00 H \nATOM 1776 HB VAL A 182 -19.007 28.207 15.302 1.00 0.00 H \nATOM 1777 HG11 VAL A 182 -18.501 29.530 13.445 1.00 0.00 H \nATOM 1778 HG12 VAL A 182 -17.456 28.348 13.583 1.00 0.00 H \nATOM 1779 HG13 VAL A 182 -18.617 28.257 12.510 1.00 0.00 H \nATOM 1780 HG21 VAL A 182 -20.825 29.242 14.247 1.00 0.00 H \nATOM 1781 HG22 VAL A 182 -21.031 27.956 13.347 1.00 0.00 H \nATOM 1782 HG23 VAL A 182 -21.278 27.877 14.910 1.00 0.00 H \nATOM 1783 N VAL A 183 -16.810 25.718 13.979 1.00 0.00 N \nATOM 1784 CA VAL A 183 -15.437 25.382 14.335 1.00 0.00 C \nATOM 1785 C VAL A 183 -14.473 26.312 13.606 1.00 0.00 C \nATOM 1786 O VAL A 183 -13.539 26.849 14.203 1.00 0.00 O \nATOM 1787 CB VAL A 183 -15.122 23.909 14.025 1.00 0.00 C \nATOM 1788 CG1 VAL A 183 -13.620 23.691 13.945 1.00 0.00 C \nATOM 1789 CG2 VAL A 183 -15.741 23.009 15.086 1.00 0.00 C \nATOM 1790 H VAL A 183 -16.957 25.748 13.132 1.00 0.00 H \nATOM 1791 HA VAL A 183 -15.328 25.504 15.291 1.00 0.00 H \nATOM 1792 HB VAL A 183 -15.506 23.682 13.164 1.00 0.00 H \nATOM 1793 HG11 VAL A 183 -13.438 22.759 13.749 1.00 0.00 H \nATOM 1794 HG12 VAL A 183 -13.249 24.247 13.242 1.00 0.00 H \nATOM 1795 HG13 VAL A 183 -13.213 23.928 14.793 1.00 0.00 H \nATOM 1796 HG21 VAL A 183 -15.538 22.082 14.883 1.00 0.00 H \nATOM 1797 HG22 VAL A 183 -15.377 23.236 15.956 1.00 0.00 H \nATOM 1798 HG23 VAL A 183 -16.703 23.134 15.096 1.00 0.00 H \nATOM 1799 N GLY A 186 -12.084 28.785 12.961 1.00 0.00 N \nATOM 1800 CA GLY A 186 -12.467 28.441 11.604 1.00 0.00 C \nATOM 1801 C GLY A 186 -13.849 28.939 11.229 1.00 0.00 C \nATOM 1802 O GLY A 186 -14.495 29.651 12.000 1.00 0.00 O \nATOM 1803 HA2 GLY A 186 -11.817 28.812 10.987 1.00 0.00 H \nATOM 1804 HA3 GLY A 186 -12.438 27.477 11.500 1.00 0.00 H \nATOM 1805 N GLY A 187 -14.305 28.562 10.037 1.00 0.00 N \nATOM 1806 CA GLY A 187 -15.601 28.996 9.554 1.00 0.00 C \nATOM 1807 C GLY A 187 -16.443 27.864 9.005 1.00 0.00 C \nATOM 1808 O GLY A 187 -17.404 28.099 8.266 1.00 0.00 O \nATOM 1809 H GLY A 187 -13.873 28.053 9.495 1.00 0.00 H \nATOM 1810 HA2 GLY A 187 -16.082 29.427 10.278 1.00 0.00 H \nATOM 1811 HA3 GLY A 187 -15.475 29.663 8.861 1.00 0.00 H \nATOM 1812 N GLU A 188 -16.090 26.629 9.353 1.00 0.00 N \nATOM 1813 CA GLU A 188 -16.854 25.465 8.946 1.00 0.00 C \nATOM 1814 C GLU A 188 -17.775 25.033 10.081 1.00 0.00 C \nATOM 1815 O GLU A 188 -17.797 25.621 11.165 1.00 0.00 O \nATOM 1816 CB GLU A 188 -15.924 24.324 8.537 1.00 0.00 C \nATOM 1817 CG GLU A 188 -14.753 24.750 7.680 1.00 0.00 C \nATOM 1818 CD GLU A 188 -13.509 23.946 7.981 1.00 0.00 C \nATOM 1819 OE1 GLU A 188 -12.523 24.062 7.225 1.00 0.00 O \nATOM 1820 OE2 GLU A 188 -13.520 23.194 8.979 1.00 0.00 O \nATOM 1821 H GLU A 188 -15.399 26.447 9.832 1.00 0.00 H \nATOM 1822 HA GLU A 188 -17.395 25.697 8.175 1.00 0.00 H \nATOM 1823 HB2 GLU A 188 -15.585 23.894 9.338 1.00 0.00 H \nATOM 1824 HB3 GLU A 188 -16.439 23.659 8.054 1.00 0.00 H \nATOM 1825 HG2 GLU A 188 -14.984 24.648 6.744 1.00 0.00 H \nATOM 1826 HG3 GLU A 188 -14.572 25.692 7.826 1.00 0.00 H \nATOM 1827 N VAL A 189 -18.551 23.989 9.825 1.00 0.00 N \nATOM 1828 CA VAL A 189 -19.635 23.587 10.710 1.00 0.00 C \nATOM 1829 C VAL A 189 -19.557 22.081 10.932 1.00 0.00 C \nATOM 1830 O VAL A 189 -19.227 21.320 10.015 1.00 0.00 O \nATOM 1831 CB VAL A 189 -21.014 24.018 10.153 1.00 0.00 C \nATOM 1832 CG1 VAL A 189 -21.579 23.004 9.181 1.00 0.00 C \nATOM 1833 CG2 VAL A 189 -21.984 24.287 11.281 1.00 0.00 C \nATOM 1834 H VAL A 189 -18.463 23.491 9.129 1.00 0.00 H \nATOM 1835 HA VAL A 189 -19.536 24.037 11.564 1.00 0.00 H \nATOM 1836 HB VAL A 189 -20.881 24.841 9.657 1.00 0.00 H \nATOM 1837 HG11 VAL A 189 -22.440 23.311 8.857 1.00 0.00 H \nATOM 1838 HG12 VAL A 189 -20.971 22.899 8.433 1.00 0.00 H \nATOM 1839 HG13 VAL A 189 -21.688 22.151 9.630 1.00 0.00 H \nATOM 1840 HG21 VAL A 189 -22.841 24.555 10.914 1.00 0.00 H \nATOM 1841 HG22 VAL A 189 -22.097 23.482 11.810 1.00 0.00 H \nATOM 1842 HG23 VAL A 189 -21.637 24.997 11.844 1.00 0.00 H \nATOM 1843 N ARG A 190 -19.799 21.659 12.168 1.00 0.00 N \nATOM 1844 CA ARG A 190 -19.895 20.251 12.521 1.00 0.00 C \nATOM 1845 C ARG A 190 -21.314 19.958 12.992 1.00 0.00 C \nATOM 1846 O ARG A 190 -21.900 20.741 13.746 1.00 0.00 O \nATOM 1847 CB ARG A 190 -18.885 19.897 13.619 1.00 0.00 C \nATOM 1848 CG ARG A 190 -18.454 18.442 13.647 1.00 0.00 C \nATOM 1849 CD ARG A 190 -16.936 18.315 13.713 1.00 0.00 C \nATOM 1850 NE ARG A 190 -16.350 19.123 14.781 1.00 0.00 N \nATOM 1851 CZ ARG A 190 -15.048 19.175 15.050 1.00 0.00 C \nATOM 1852 NH1 ARG A 190 -14.189 18.470 14.323 1.00 0.00 N \nATOM 1853 NH2 ARG A 190 -14.598 19.936 16.041 1.00 0.00 N \nATOM 1854 H ARG A 190 -19.913 22.191 12.834 1.00 0.00 H \nATOM 1855 HA ARG A 190 -19.690 19.709 11.743 1.00 0.00 H \nATOM 1856 HB2 ARG A 190 -18.097 20.452 13.507 1.00 0.00 H \nATOM 1857 HB3 ARG A 190 -19.271 20.123 14.480 1.00 0.00 H \nATOM 1858 HG2 ARG A 190 -18.851 18.000 14.413 1.00 0.00 H \nATOM 1859 HG3 ARG A 190 -18.784 17.989 12.855 1.00 0.00 H \nATOM 1860 HD2 ARG A 190 -16.698 17.384 13.849 1.00 0.00 H \nATOM 1861 HD3 ARG A 190 -16.555 18.584 12.862 1.00 0.00 H \nATOM 1862 HE ARG A 190 -16.881 19.595 15.266 1.00 0.00 H \nATOM 1863 HH11 ARG A 190 -14.474 17.979 13.677 1.00 0.00 H \nATOM 1864 HH12 ARG A 190 -13.348 18.505 14.498 1.00 0.00 H \nATOM 1865 HH21 ARG A 190 -15.149 20.398 16.512 1.00 0.00 H \nATOM 1866 HH22 ARG A 190 -13.756 19.967 16.211 1.00 0.00 H \nATOM 1867 N SER A 191 -21.870 18.830 12.540 1.00 0.00 N \nATOM 1868 CA SER A 191 -23.216 18.431 12.927 1.00 0.00 C \nATOM 1869 C SER A 191 -23.290 17.111 13.680 1.00 0.00 C \nATOM 1870 O SER A 191 -24.346 16.809 14.247 1.00 0.00 O \nATOM 1871 CB SER A 191 -24.123 18.344 11.690 1.00 0.00 C \nATOM 1872 OG SER A 191 -24.093 17.045 11.126 1.00 0.00 O \nATOM 1873 H SER A 191 -21.478 18.282 12.005 1.00 0.00 H \nATOM 1874 HA SER A 191 -23.519 19.121 13.538 1.00 0.00 H \nATOM 1875 HB2 SER A 191 -25.033 18.572 11.936 1.00 0.00 H \nATOM 1876 HB3 SER A 191 -23.837 18.994 11.029 1.00 0.00 H \nATOM 1877 HG SER A 191 -24.596 17.020 10.454 1.00 0.00 H \nATOM 1878 N GLU A 192 -22.221 16.321 13.700 1.00 0.00 N \nATOM 1879 CA GLU A 192 -22.242 15.078 14.451 1.00 0.00 C \nATOM 1880 C GLU A 192 -22.275 15.371 15.952 1.00 0.00 C \nATOM 1881 O GLU A 192 -21.853 16.442 16.392 1.00 0.00 O \nATOM 1882 CB GLU A 192 -21.018 14.230 14.110 1.00 0.00 C \nATOM 1883 CG GLU A 192 -21.282 13.143 13.081 1.00 0.00 C \nATOM 1884 CD GLU A 192 -21.814 11.866 13.704 1.00 0.00 C \nATOM 1885 OE1 GLU A 192 -21.008 11.096 14.268 1.00 0.00 O \nATOM 1886 OE2 GLU A 192 -23.039 11.634 13.634 1.00 0.00 O \nATOM 1887 H GLU A 192 -21.483 16.486 13.290 1.00 0.00 H \nATOM 1888 HA GLU A 192 -23.040 14.583 14.209 1.00 0.00 H \nATOM 1889 HB2 GLU A 192 -20.316 14.812 13.779 1.00 0.00 H \nATOM 1890 HB3 GLU A 192 -20.685 13.818 14.923 1.00 0.00 H \nATOM 1891 HG2 GLU A 192 -21.919 13.470 12.427 1.00 0.00 H \nATOM 1892 HG3 GLU A 192 -20.460 12.948 12.604 1.00 0.00 H \nATOM 1893 N PRO A 193 -22.788 14.438 16.757 1.00 0.00 N \nATOM 1894 CA PRO A 193 -22.715 14.611 18.213 1.00 0.00 C \nATOM 1895 C PRO A 193 -21.271 14.743 18.674 1.00 0.00 C \nATOM 1896 O PRO A 193 -20.348 14.198 18.066 1.00 0.00 O \nATOM 1897 CB PRO A 193 -23.367 13.336 18.760 1.00 0.00 C \nATOM 1898 CG PRO A 193 -24.214 12.821 17.642 1.00 0.00 C \nATOM 1899 CD PRO A 193 -23.519 13.220 16.373 1.00 0.00 C \nATOM 1900 HA PRO A 193 -23.158 15.417 18.523 1.00 0.00 H \nATOM 1901 HB2 PRO A 193 -22.698 12.684 19.022 1.00 0.00 H \nATOM 1902 HB3 PRO A 193 -23.902 13.525 19.547 1.00 0.00 H \nATOM 1903 HG2 PRO A 193 -24.311 11.857 17.696 1.00 0.00 H \nATOM 1904 HG3 PRO A 193 -25.107 13.198 17.681 1.00 0.00 H \nATOM 1905 HD2 PRO A 193 -22.918 12.526 16.060 1.00 0.00 H \nATOM 1906 HD3 PRO A 193 -24.151 13.392 15.657 1.00 0.00 H \nATOM 1907 N VAL A 194 -21.083 15.482 19.770 1.00 0.00 N \nATOM 1908 CA VAL A 194 -19.736 15.722 20.277 1.00 0.00 C \nATOM 1909 C VAL A 194 -19.079 14.430 20.746 1.00 0.00 C \nATOM 1910 O VAL A 194 -17.871 14.237 20.559 1.00 0.00 O \nATOM 1911 CB VAL A 194 -19.779 16.780 21.401 1.00 0.00 C \nATOM 1912 CG1 VAL A 194 -18.459 16.825 22.151 1.00 0.00 C \nATOM 1913 CG2 VAL A 194 -20.115 18.151 20.829 1.00 0.00 C \nATOM 1914 H VAL A 194 -21.714 15.847 20.227 1.00 0.00 H \nATOM 1915 HA VAL A 194 -19.190 16.066 19.553 1.00 0.00 H \nATOM 1916 HB VAL A 194 -20.475 16.528 22.028 1.00 0.00 H \nATOM 1917 HG11 VAL A 194 -18.507 17.495 22.851 1.00 0.00 H \nATOM 1918 HG12 VAL A 194 -18.281 15.957 22.546 1.00 0.00 H \nATOM 1919 HG13 VAL A 194 -17.744 17.052 21.536 1.00 0.00 H \nATOM 1920 HG21 VAL A 194 -20.138 18.804 21.546 1.00 0.00 H \nATOM 1921 HG22 VAL A 194 -19.439 18.406 20.182 1.00 0.00 H \nATOM 1922 HG23 VAL A 194 -20.982 18.117 20.395 1.00 0.00 H \nATOM 1923 N THR A 195 -19.854 13.509 21.309 1.00 0.00 N \nATOM 1924 CA THR A 195 -19.297 12.256 21.810 1.00 0.00 C \nATOM 1925 C THR A 195 -20.427 11.241 21.971 1.00 0.00 C \nATOM 1926 O THR A 195 -21.537 11.431 21.463 1.00 0.00 O \nATOM 1927 CB THR A 195 -18.533 12.489 23.118 1.00 0.00 C \nATOM 1928 OG1 THR A 195 -17.938 11.261 23.557 1.00 0.00 O \nATOM 1929 CG2 THR A 195 -19.470 13.027 24.187 1.00 0.00 C \nATOM 1930 H THR A 195 -20.704 13.589 21.411 1.00 0.00 H \nATOM 1931 HA THR A 195 -18.655 11.900 21.176 1.00 0.00 H \nATOM 1932 HB THR A 195 -17.834 13.143 22.962 1.00 0.00 H \nATOM 1933 HG1 THR A 195 -17.101 11.331 23.534 1.00 0.00 H \nATOM 1934 HG21 THR A 195 -18.975 13.170 25.009 1.00 0.00 H \nATOM 1935 HG22 THR A 195 -19.852 13.867 23.889 1.00 0.00 H \nATOM 1936 HG23 THR A 195 -20.182 12.387 24.346 1.00 0.00 H \nATOM 1937 N ALA A 196 -20.133 10.151 22.681 1.00 0.00 N \nATOM 1938 CA ALA A 196 -21.052 9.031 22.803 1.00 0.00 C \nATOM 1939 C ALA A 196 -22.309 9.429 23.575 1.00 0.00 C \nATOM 1940 O ALA A 196 -22.389 10.492 24.199 1.00 0.00 O \nATOM 1941 CB ALA A 196 -20.366 7.849 23.488 1.00 0.00 C \nATOM 1942 H ALA A 196 -19.392 10.045 23.105 1.00 0.00 H \nATOM 1943 HA ALA A 196 -21.318 8.766 21.909 1.00 0.00 H \nATOM 1944 HB1 ALA A 196 -20.991 7.111 23.562 1.00 0.00 H \nATOM 1945 HB2 ALA A 196 -19.599 7.571 22.963 1.00 0.00 H \nATOM 1946 HB3 ALA A 196 -20.073 8.114 24.374 1.00 0.00 H \nATOM 1947 N GLU A 197 -23.305 8.539 23.529 1.00 0.00 N \nATOM 1948 CA GLU A 197 -24.622 8.857 24.070 1.00 0.00 C \nATOM 1949 C GLU A 197 -24.633 8.874 25.594 1.00 0.00 C \nATOM 1950 O GLU A 197 -25.467 9.563 26.195 1.00 0.00 O \nATOM 1951 CB GLU A 197 -25.654 7.860 23.540 1.00 0.00 C \nATOM 1952 CG GLU A 197 -25.416 6.420 23.967 1.00 0.00 C \nATOM 1953 CD GLU A 197 -24.720 5.603 22.894 1.00 0.00 C \nATOM 1954 OE1 GLU A 197 -23.571 5.943 22.536 1.00 0.00 O \nATOM 1955 OE2 GLU A 197 -25.323 4.624 22.400 1.00 0.00 O \nATOM 1956 H GLU A 197 -23.236 7.752 23.190 1.00 0.00 H \nATOM 1957 HA GLU A 197 -24.852 9.752 23.775 1.00 0.00 H \nATOM 1958 HB2 GLU A 197 -26.535 8.133 23.840 1.00 0.00 H \nATOM 1959 HB3 GLU A 197 -25.659 7.902 22.571 1.00 0.00 H \nATOM 1960 HG2 GLU A 197 -24.880 6.410 24.775 1.00 0.00 H \nATOM 1961 HG3 GLU A 197 -26.266 6.006 24.185 1.00 0.00 H \nATOM 1962 N ASN A 198 -23.727 8.138 26.234 1.00 0.00 N \nATOM 1963 CA ASN A 198 -23.701 8.032 27.687 1.00 0.00 C \nATOM 1964 C ASN A 198 -22.864 9.111 28.362 1.00 0.00 C \nATOM 1965 O ASN A 198 -22.714 9.076 29.588 1.00 0.00 O \nATOM 1966 CB ASN A 198 -23.183 6.652 28.105 1.00 0.00 C \nATOM 1967 CG ASN A 198 -21.736 6.429 27.714 1.00 0.00 C \nATOM 1968 OD1 ASN A 198 -21.317 6.787 26.615 1.00 0.00 O \nATOM 1969 ND2 ASN A 198 -20.962 5.840 28.617 1.00 0.00 N \nATOM 1970 H ASN A 198 -23.112 7.687 25.837 1.00 0.00 H \nATOM 1971 HA ASN A 198 -24.616 8.158 27.983 1.00 0.00 H \nATOM 1972 HB2 ASN A 198 -23.274 6.554 29.066 1.00 0.00 H \nATOM 1973 HB3 ASN A 198 -23.734 5.966 27.697 1.00 0.00 H \nATOM 1974 HD21 ASN A 198 -20.132 5.695 28.443 1.00 0.00 H \nATOM 1975 HD22 ASN A 198 -21.290 5.603 29.376 1.00 0.00 H \nATOM 1976 N VAL A 199 -22.320 10.062 27.612 1.00 0.00 N \nATOM 1977 CA VAL A 199 -21.465 11.098 28.179 1.00 0.00 C \nATOM 1978 C VAL A 199 -22.307 12.327 28.490 1.00 0.00 C \nATOM 1979 O VAL A 199 -23.071 12.804 27.643 1.00 0.00 O \nATOM 1980 CB VAL A 199 -20.314 11.446 27.221 1.00 0.00 C \nATOM 1981 CG1 VAL A 199 -19.352 12.429 27.873 1.00 0.00 C \nATOM 1982 CG2 VAL A 199 -19.586 10.185 26.779 1.00 0.00 C \nATOM 1983 H VAL A 199 -22.435 10.125 26.762 1.00 0.00 H \nATOM 1984 HA VAL A 199 -21.067 10.769 29.000 1.00 0.00 H \nATOM 1985 HB VAL A 199 -20.689 11.870 26.433 1.00 0.00 H \nATOM 1986 HG11 VAL A 199 -18.634 12.637 27.255 1.00 0.00 H \nATOM 1987 HG12 VAL A 199 -19.827 13.243 28.102 1.00 0.00 H \nATOM 1988 HG13 VAL A 199 -18.982 12.034 28.678 1.00 0.00 H \nATOM 1989 HG21 VAL A 199 -18.864 10.422 26.176 1.00 0.00 H \nATOM 1990 HG22 VAL A 199 -19.222 9.732 27.556 1.00 0.00 H \nATOM 1991 HG23 VAL A 199 -20.207 9.596 26.323 1.00 0.00 H \nATOM 1992 N GLY A 200 -22.169 12.843 29.708 1.00 0.00 N \nATOM 1993 CA GLY A 200 -22.909 14.011 30.134 1.00 0.00 C \nATOM 1994 C GLY A 200 -22.110 14.806 31.143 1.00 0.00 C \nATOM 1995 O GLY A 200 -20.963 14.478 31.456 1.00 0.00 O \nATOM 1996 H GLY A 200 -21.642 12.521 30.307 1.00 0.00 H \nATOM 1997 HA2 GLY A 200 -23.116 14.567 29.367 1.00 0.00 H \nATOM 1998 HA3 GLY A 200 -23.755 13.740 30.524 1.00 0.00 H \nATOM 1999 N SER A 201 -22.729 15.869 31.654 1.00 0.00 N \nATOM 2000 CA SER A 201 -22.066 16.740 32.613 1.00 0.00 C \nATOM 2001 C SER A 201 -23.103 17.557 33.369 1.00 0.00 C \nATOM 2002 O SER A 201 -24.123 17.955 32.799 1.00 0.00 O \nATOM 2003 CB SER A 201 -21.067 17.675 31.921 1.00 0.00 C \nATOM 2004 OG SER A 201 -20.516 18.595 32.850 1.00 0.00 O \nATOM 2005 H SER A 201 -23.533 16.101 31.456 1.00 0.00 H \nATOM 2006 HA SER A 201 -21.573 16.183 33.236 1.00 0.00 H \nATOM 2007 HB2 SER A 201 -20.357 17.154 31.515 1.00 0.00 H \nATOM 2008 HB3 SER A 201 -21.510 18.157 31.205 1.00 0.00 H \nATOM 2009 HG SER A 201 -20.490 18.243 33.612 1.00 0.00 H \nATOM 2010 N THR A 202 -22.828 17.804 34.649 1.00 0.00 N \nATOM 2011 CA THR A 202 -23.560 18.820 35.382 1.00 0.00 C \nATOM 2012 C THR A 202 -23.116 20.209 34.927 1.00 0.00 C \nATOM 2013 O THR A 202 -22.101 20.380 34.246 1.00 0.00 O \nATOM 2014 CB THR A 202 -23.331 18.678 36.886 1.00 0.00 C \nATOM 2015 OG1 THR A 202 -22.149 19.399 37.257 1.00 0.00 O \nATOM 2016 CG2 THR A 202 -23.145 17.222 37.265 1.00 0.00 C \nATOM 2017 H THR A 202 -22.224 17.394 35.104 1.00 0.00 H \nATOM 2018 HA THR A 202 -24.506 18.704 35.201 1.00 0.00 H \nATOM 2019 HB THR A 202 -24.107 19.032 37.348 1.00 0.00 H \nATOM 2020 HG1 THR A 202 -22.366 20.111 37.647 1.00 0.00 H \nATOM 2021 HG21 THR A 202 -23.001 17.152 38.222 1.00 0.00 H \nATOM 2022 HG22 THR A 202 -23.938 16.720 37.020 1.00 0.00 H \nATOM 2023 HG23 THR A 202 -22.377 16.861 36.796 1.00 0.00 H \nATOM 2024 N ALA A 203 -23.898 21.213 35.308 1.00 0.00 N \nATOM 2025 CA ALA A 203 -23.508 22.599 35.078 1.00 0.00 C \nATOM 2026 C ALA A 203 -24.156 23.466 36.142 1.00 0.00 C \nATOM 2027 O ALA A 203 -25.386 23.559 36.202 1.00 0.00 O \nATOM 2028 CB ALA A 203 -23.917 23.066 33.678 1.00 0.00 C \nATOM 2029 H ALA A 203 -24.657 21.114 35.700 1.00 0.00 H \nATOM 2030 HA ALA A 203 -22.542 22.674 35.134 1.00 0.00 H \nATOM 2031 HB1 ALA A 203 -23.646 23.989 33.553 1.00 0.00 H \nATOM 2032 HB2 ALA A 203 -23.485 22.509 33.012 1.00 0.00 H \nATOM 2033 HB3 ALA A 203 -24.880 22.996 33.582 1.00 0.00 H \nATOM 2034 N VAL A 204 -23.333 24.090 36.980 1.00 0.00 N \nATOM 2035 CA VAL A 204 -23.780 25.131 37.897 1.00 0.00 C \nATOM 2036 C VAL A 204 -22.963 26.377 37.583 1.00 0.00 C \nATOM 2037 O VAL A 204 -21.726 26.352 37.645 1.00 0.00 O \nATOM 2038 CB VAL A 204 -23.651 24.707 39.373 1.00 0.00 C \nATOM 2039 CG1 VAL A 204 -22.212 24.348 39.746 1.00 0.00 C \nATOM 2040 CG2 VAL A 204 -24.192 25.792 40.282 1.00 0.00 C \nATOM 2041 H VAL A 204 -22.492 23.919 37.032 1.00 0.00 H \nATOM 2042 HA VAL A 204 -24.726 25.306 37.772 1.00 0.00 H \nATOM 2043 HB VAL A 204 -24.182 23.904 39.494 1.00 0.00 H \nATOM 2044 HG11 VAL A 204 -22.175 24.088 40.680 1.00 0.00 H \nATOM 2045 HG12 VAL A 204 -21.908 23.611 39.193 1.00 0.00 H \nATOM 2046 HG13 VAL A 204 -21.639 25.117 39.602 1.00 0.00 H \nATOM 2047 HG21 VAL A 204 -24.105 25.513 41.207 1.00 0.00 H \nATOM 2048 HG22 VAL A 204 -23.690 26.611 40.143 1.00 0.00 H \nATOM 2049 HG23 VAL A 204 -25.127 25.948 40.079 1.00 0.00 H \nATOM 2050 N VAL A 205 -23.645 27.451 37.199 1.00 0.00 N \nATOM 2051 CA VAL A 205 -22.970 28.670 36.778 1.00 0.00 C \nATOM 2052 C VAL A 205 -23.423 29.822 37.660 1.00 0.00 C \nATOM 2053 O VAL A 205 -24.567 29.870 38.124 1.00 0.00 O \nATOM 2054 CB VAL A 205 -23.212 28.982 35.283 1.00 0.00 C \nATOM 2055 CG1 VAL A 205 -22.912 27.756 34.429 1.00 0.00 C \nATOM 2056 CG2 VAL A 205 -24.634 29.465 35.048 1.00 0.00 C \nATOM 2057 H VAL A 205 -24.504 27.493 37.176 1.00 0.00 H \nATOM 2058 HA VAL A 205 -22.014 28.543 36.879 1.00 0.00 H \nATOM 2059 HB VAL A 205 -22.609 29.695 35.022 1.00 0.00 H \nATOM 2060 HG11 VAL A 205 -23.068 27.966 33.495 1.00 0.00 H \nATOM 2061 HG12 VAL A 205 -21.986 27.495 34.551 1.00 0.00 H \nATOM 2062 HG13 VAL A 205 -23.491 27.025 34.697 1.00 0.00 H \nATOM 2063 HG21 VAL A 205 -24.760 29.654 34.105 1.00 0.00 H \nATOM 2064 HG22 VAL A 205 -25.260 28.778 35.326 1.00 0.00 H \nATOM 2065 HG23 VAL A 205 -24.791 30.272 35.562 1.00 0.00 H \nATOM 2066 N ALA A 206 -22.500 30.747 37.906 1.00 0.00 N \nATOM 2067 CA ALA A 206 -22.762 31.940 38.702 1.00 0.00 C \nATOM 2068 C ALA A 206 -22.485 33.167 37.844 1.00 0.00 C \nATOM 2069 O ALA A 206 -21.340 33.408 37.449 1.00 0.00 O \nATOM 2070 CB ALA A 206 -21.908 31.954 39.968 1.00 0.00 C \nATOM 2071 H ALA A 206 -21.694 30.698 37.611 1.00 0.00 H \nATOM 2072 HA ALA A 206 -23.690 31.943 38.985 1.00 0.00 H \nATOM 2073 HB1 ALA A 206 -22.100 32.756 40.479 1.00 0.00 H \nATOM 2074 HB2 ALA A 206 -22.112 31.172 40.505 1.00 0.00 H \nATOM 2075 HB3 ALA A 206 -20.969 31.943 39.725 1.00 0.00 H \nATOM 2076 N LEU A 207 -23.530 33.934 37.554 1.00 0.00 N \nATOM 2077 CA LEU A 207 -23.387 35.238 36.922 1.00 0.00 C \nATOM 2078 C LEU A 207 -23.242 36.284 38.021 1.00 0.00 C \nATOM 2079 O LEU A 207 -24.176 36.506 38.798 1.00 0.00 O \nATOM 2080 CB LEU A 207 -24.592 35.539 36.029 1.00 0.00 C \nATOM 2081 CG LEU A 207 -24.446 36.608 34.948 1.00 0.00 C \nATOM 2082 CD1 LEU A 207 -25.306 36.258 33.741 1.00 0.00 C \nATOM 2083 CD2 LEU A 207 -24.827 37.975 35.493 1.00 0.00 C \nATOM 2084 H LEU A 207 -24.344 33.711 37.719 1.00 0.00 H \nATOM 2085 HA LEU A 207 -22.601 35.250 36.354 1.00 0.00 H \nATOM 2086 HB2 LEU A 207 -24.851 34.712 35.593 1.00 0.00 H \nATOM 2087 HB3 LEU A 207 -25.328 35.799 36.604 1.00 0.00 H \nATOM 2088 HG LEU A 207 -23.517 36.639 34.669 1.00 0.00 H \nATOM 2089 HD11 LEU A 207 -25.205 36.943 33.062 1.00 0.00 H \nATOM 2090 HD12 LEU A 207 -25.025 35.402 33.381 1.00 0.00 H \nATOM 2091 HD13 LEU A 207 -26.236 36.205 34.011 1.00 0.00 H \nATOM 2092 HD21 LEU A 207 -24.729 38.641 34.795 1.00 0.00 H \nATOM 2093 HD22 LEU A 207 -25.749 37.958 35.795 1.00 0.00 H \nATOM 2094 HD23 LEU A 207 -24.247 38.200 36.237 1.00 0.00 H \nATOM 2095 N VAL A 208 -22.074 36.917 38.092 1.00 0.00 N \nATOM 2096 CA VAL A 208 -21.758 37.873 39.146 1.00 0.00 C \nATOM 2097 C VAL A 208 -21.595 39.251 38.523 1.00 0.00 C \nATOM 2098 O VAL A 208 -20.709 39.459 37.683 1.00 0.00 O \nATOM 2099 CB VAL A 208 -20.490 37.476 39.918 1.00 0.00 C \nATOM 2100 CG1 VAL A 208 -20.291 38.392 41.119 1.00 0.00 C \nATOM 2101 CG2 VAL A 208 -20.559 36.017 40.354 1.00 0.00 C \nATOM 2102 H VAL A 208 -21.438 36.802 37.524 1.00 0.00 H \nATOM 2103 HA VAL A 208 -22.486 37.881 39.787 1.00 0.00 H \nATOM 2104 HB VAL A 208 -19.727 37.577 39.328 1.00 0.00 H \nATOM 2105 HG11 VAL A 208 -19.488 38.130 41.596 1.00 0.00 H \nATOM 2106 HG12 VAL A 208 -20.202 39.309 40.816 1.00 0.00 H \nATOM 2107 HG13 VAL A 208 -21.056 38.321 41.711 1.00 0.00 H \nATOM 2108 HG21 VAL A 208 -19.751 35.785 40.839 1.00 0.00 H \nATOM 2109 HG22 VAL A 208 -21.329 35.887 40.929 1.00 0.00 H \nATOM 2110 HG23 VAL A 208 -20.640 35.449 39.572 1.00 0.00 H \nATOM 2111 N CYS A 209 -22.446 40.187 38.936 1.00 0.00 N \nATOM 2112 CA CYS A 209 -22.303 41.596 38.606 1.00 0.00 C \nATOM 2113 C CYS A 209 -22.325 42.396 39.904 1.00 0.00 C \nATOM 2114 O CYS A 209 -22.378 41.833 41.003 1.00 0.00 O \nATOM 2115 CB CYS A 209 -23.397 42.061 37.634 1.00 0.00 C \nATOM 2116 SG CYS A 209 -25.061 42.128 38.333 1.00 0.00 S \nATOM 2117 H CYS A 209 -23.133 40.015 39.424 1.00 0.00 H \nATOM 2118 HA CYS A 209 -21.459 41.741 38.151 1.00 0.00 H \nATOM 2119 HB2 CYS A 209 -23.164 42.943 37.304 1.00 0.00 H \nATOM 2120 HB3 CYS A 209 -23.406 41.465 36.869 1.00 0.00 H \nATOM 2121 HG CYS A 209 -25.866 42.194 37.445 1.00 0.00 H \nATOM 2122 N SER A 210 -22.283 43.725 39.773 1.00 0.00 N \nATOM 2123 CA SER A 210 -22.151 44.580 40.950 1.00 0.00 C \nATOM 2124 C SER A 210 -23.364 44.489 41.868 1.00 0.00 C \nATOM 2125 O SER A 210 -23.225 44.595 43.092 1.00 0.00 O \nATOM 2126 CB SER A 210 -21.920 46.029 40.523 1.00 0.00 C \nATOM 2127 OG SER A 210 -23.153 46.708 40.347 1.00 0.00 O \nATOM 2128 H SER A 210 -22.329 44.143 39.023 1.00 0.00 H \nATOM 2129 HA SER A 210 -21.384 44.264 41.453 1.00 0.00 H \nATOM 2130 HB2 SER A 210 -21.387 46.486 41.192 1.00 0.00 H \nATOM 2131 HB3 SER A 210 -21.414 46.050 39.696 1.00 0.00 H \nATOM 2132 HG SER A 210 -23.005 47.502 40.114 1.00 0.00 H \nATOM 2133 N SER A 211 -24.557 44.308 41.305 1.00 0.00 N \nATOM 2134 CA SER A 211 -25.787 44.351 42.086 1.00 0.00 C \nATOM 2135 C SER A 211 -26.331 42.980 42.455 1.00 0.00 C \nATOM 2136 O SER A 211 -26.935 42.839 43.523 1.00 0.00 O \nATOM 2137 CB SER A 211 -26.873 45.122 41.326 1.00 0.00 C \nATOM 2138 OG SER A 211 -27.609 44.259 40.480 1.00 0.00 O \nATOM 2139 H SER A 211 -24.674 44.158 40.466 1.00 0.00 H \nATOM 2140 HA SER A 211 -25.554 44.800 42.913 1.00 0.00 H \nATOM 2141 HB2 SER A 211 -27.472 45.550 41.957 1.00 0.00 H \nATOM 2142 HB3 SER A 211 -26.465 45.827 40.799 1.00 0.00 H \nATOM 2143 HG SER A 211 -27.458 44.457 39.678 1.00 0.00 H \nATOM 2144 N HIS A 212 -26.131 41.967 41.615 1.00 0.00 N \nATOM 2145 CA HIS A 212 -26.789 40.686 41.818 1.00 0.00 C \nATOM 2146 C HIS A 212 -25.820 39.540 41.583 1.00 0.00 C \nATOM 2147 O HIS A 212 -24.792 39.684 40.915 1.00 0.00 O \nATOM 2148 CB HIS A 212 -27.992 40.515 40.881 1.00 0.00 C \nATOM 2149 CG HIS A 212 -29.224 41.231 41.333 1.00 0.00 C \nATOM 2150 ND1 HIS A 212 -29.412 42.583 41.143 1.00 0.00 N \nATOM 2151 CD2 HIS A 212 -30.336 40.782 41.961 1.00 0.00 C \nATOM 2152 CE1 HIS A 212 -30.584 42.936 41.639 1.00 0.00 C \nATOM 2153 NE2 HIS A 212 -31.166 41.861 42.140 1.00 0.00 N \nATOM 2154 H HIS A 212 -25.619 42.003 40.925 1.00 0.00 H \nATOM 2155 HA HIS A 212 -27.100 40.671 42.737 1.00 0.00 H \nATOM 2156 HB2 HIS A 212 -27.750 40.834 39.998 1.00 0.00 H \nATOM 2157 HB3 HIS A 212 -28.192 39.570 40.796 1.00 0.00 H \nATOM 2158 HD1 HIS A 212 -28.853 43.114 40.761 1.00 0.00 H \nATOM 2159 HD2 HIS A 212 -30.506 39.906 42.222 1.00 0.00 H \nATOM 2160 HE1 HIS A 212 -30.939 43.795 41.636 1.00 0.00 H \nATOM 2161 HE2 HIS A 212 -31.939 41.840 42.517 1.00 0.00 H \nATOM 2162 N VAL A 213 -26.172 38.392 42.154 1.00 0.00 N \nATOM 2163 CA VAL A 213 -25.613 37.098 41.786 1.00 0.00 C \nATOM 2164 C VAL A 213 -26.755 36.277 41.204 1.00 0.00 C \nATOM 2165 O VAL A 213 -27.780 36.075 41.865 1.00 0.00 O \nATOM 2166 CB VAL A 213 -24.970 36.389 42.987 1.00 0.00 C \nATOM 2167 CG1 VAL A 213 -24.634 34.947 42.636 1.00 0.00 C \nATOM 2168 CG2 VAL A 213 -23.724 37.137 43.445 1.00 0.00 C \nATOM 2169 H VAL A 213 -26.758 38.344 42.782 1.00 0.00 H \nATOM 2170 HA VAL A 213 -24.901 37.210 41.137 1.00 0.00 H \nATOM 2171 HB VAL A 213 -25.607 36.384 43.719 1.00 0.00 H \nATOM 2172 HG11 VAL A 213 -24.229 34.513 43.403 1.00 0.00 H \nATOM 2173 HG12 VAL A 213 -25.445 34.476 42.390 1.00 0.00 H \nATOM 2174 HG13 VAL A 213 -24.013 34.931 41.891 1.00 0.00 H \nATOM 2175 HG21 VAL A 213 -23.331 36.677 44.203 1.00 0.00 H \nATOM 2176 HG22 VAL A 213 -23.082 37.171 42.719 1.00 0.00 H \nATOM 2177 HG23 VAL A 213 -23.966 38.040 43.705 1.00 0.00 H \nATOM 2178 N VAL A 214 -26.595 35.819 39.967 1.00 0.00 N \nATOM 2179 CA VAL A 214 -27.602 35.002 39.298 1.00 0.00 C \nATOM 2180 C VAL A 214 -27.034 33.602 39.118 1.00 0.00 C \nATOM 2181 O VAL A 214 -25.970 33.426 38.511 1.00 0.00 O \nATOM 2182 CB VAL A 214 -28.028 35.609 37.954 1.00 0.00 C \nATOM 2183 CG1 VAL A 214 -29.225 34.859 37.398 1.00 0.00 C \nATOM 2184 CG2 VAL A 214 -28.358 37.086 38.125 1.00 0.00 C \nATOM 2185 H VAL A 214 -25.896 35.974 39.490 1.00 0.00 H \nATOM 2186 HA VAL A 214 -28.403 34.966 39.844 1.00 0.00 H \nATOM 2187 HB VAL A 214 -27.293 35.528 37.326 1.00 0.00 H \nATOM 2188 HG11 VAL A 214 -29.486 35.250 36.550 1.00 0.00 H \nATOM 2189 HG12 VAL A 214 -28.990 33.927 37.266 1.00 0.00 H \nATOM 2190 HG13 VAL A 214 -29.964 34.920 38.023 1.00 0.00 H \nATOM 2191 HG21 VAL A 214 -28.626 37.459 37.271 1.00 0.00 H \nATOM 2192 HG22 VAL A 214 -29.083 37.184 38.762 1.00 0.00 H \nATOM 2193 HG23 VAL A 214 -27.576 37.557 38.452 1.00 0.00 H \nATOM 2194 N VAL A 215 -27.745 32.610 39.645 1.00 0.00 N \nATOM 2195 CA VAL A 215 -27.305 31.220 39.646 1.00 0.00 C \nATOM 2196 C VAL A 215 -28.242 30.415 38.760 1.00 0.00 C \nATOM 2197 O VAL A 215 -29.466 30.553 38.853 1.00 0.00 O \nATOM 2198 CB VAL A 215 -27.279 30.642 41.072 1.00 0.00 C \nATOM 2199 CG1 VAL A 215 -27.264 29.117 41.038 1.00 0.00 C \nATOM 2200 CG2 VAL A 215 -26.086 31.181 41.839 1.00 0.00 C \nATOM 2201 H VAL A 215 -28.510 32.729 40.019 1.00 0.00 H \nATOM 2202 HA VAL A 215 -26.400 31.172 39.301 1.00 0.00 H \nATOM 2203 HB VAL A 215 -28.087 30.921 41.532 1.00 0.00 H \nATOM 2204 HG11 VAL A 215 -27.248 28.773 41.945 1.00 0.00 H \nATOM 2205 HG12 VAL A 215 -28.059 28.795 40.585 1.00 0.00 H \nATOM 2206 HG13 VAL A 215 -26.476 28.811 40.563 1.00 0.00 H \nATOM 2207 HG21 VAL A 215 -26.082 30.809 42.735 1.00 0.00 H \nATOM 2208 HG22 VAL A 215 -25.268 30.931 41.382 1.00 0.00 H \nATOM 2209 HG23 VAL A 215 -26.145 32.148 41.891 1.00 0.00 H \nATOM 2210 N ALA A 216 -27.667 29.584 37.896 1.00 0.00 N \nATOM 2211 CA ALA A 216 -28.420 28.619 37.104 1.00 0.00 C \nATOM 2212 C ALA A 216 -27.809 27.249 37.344 1.00 0.00 C \nATOM 2213 O ALA A 216 -26.616 27.050 37.098 1.00 0.00 O \nATOM 2214 CB ALA A 216 -28.397 28.970 35.615 1.00 0.00 C \nATOM 2215 H ALA A 216 -26.819 29.565 37.752 1.00 0.00 H \nATOM 2216 HA ALA A 216 -29.351 28.629 37.375 1.00 0.00 H \nATOM 2217 HB1 ALA A 216 -28.906 28.310 35.119 1.00 0.00 H \nATOM 2218 HB2 ALA A 216 -28.790 29.847 35.483 1.00 0.00 H \nATOM 2219 HB3 ALA A 216 -27.480 28.976 35.298 1.00 0.00 H \nATOM 2220 N ASN A 217 -28.617 26.310 37.823 1.00 0.00 N \nATOM 2221 CA ASN A 217 -28.132 24.995 38.213 1.00 0.00 C \nATOM 2222 C ASN A 217 -28.774 23.908 37.367 1.00 0.00 C \nATOM 2223 O ASN A 217 -29.983 23.932 37.116 1.00 0.00 O \nATOM 2224 CB ASN A 217 -28.410 24.715 39.690 1.00 0.00 C \nATOM 2225 CG ASN A 217 -27.800 23.409 40.153 1.00 0.00 C \nATOM 2226 OD1 ASN A 217 -26.623 23.139 39.909 1.00 0.00 O \nATOM 2227 ND2 ASN A 217 -28.600 22.583 40.815 1.00 0.00 N \nATOM 2228 H ASN A 217 -29.463 26.419 37.931 1.00 0.00 H \nATOM 2229 HA ASN A 217 -27.173 24.989 38.068 1.00 0.00 H \nATOM 2230 HB2 ASN A 217 -28.058 25.442 40.227 1.00 0.00 H \nATOM 2231 HB3 ASN A 217 -29.368 24.692 39.838 1.00 0.00 H \nATOM 2232 HD21 ASN A 217 -28.302 21.825 41.092 1.00 0.00 H \nATOM 2233 HD22 ASN A 217 -29.417 22.805 40.967 1.00 0.00 H \nATOM 2234 N CYS A 218 -27.949 22.952 36.937 1.00 0.00 N \nATOM 2235 CA CYS A 218 -28.397 21.795 36.159 1.00 0.00 C \nATOM 2236 C CYS A 218 -27.556 20.602 36.615 1.00 0.00 C \nATOM 2237 O CYS A 218 -26.467 20.359 36.087 1.00 0.00 O \nATOM 2238 CB CYS A 218 -28.266 22.050 34.662 1.00 0.00 C \nATOM 2239 SG CYS A 218 -28.967 20.760 33.614 1.00 0.00 S \nATOM 2240 H CYS A 218 -27.103 22.957 37.091 1.00 0.00 H \nATOM 2241 HA CYS A 218 -29.338 21.618 36.312 1.00 0.00 H \nATOM 2242 HB2 CYS A 218 -28.699 22.892 34.451 1.00 0.00 H \nATOM 2243 HB3 CYS A 218 -27.326 22.151 34.444 1.00 0.00 H \nATOM 2244 HG CYS A 218 -29.736 21.251 32.835 1.00 0.00 H \nATOM 2245 N GLY A 219 -28.066 19.866 37.601 1.00 0.00 N \nATOM 2246 CA GLY A 219 -27.382 18.683 38.088 1.00 0.00 C \nATOM 2247 C GLY A 219 -27.091 18.694 39.575 1.00 0.00 C \nATOM 2248 O GLY A 219 -27.698 19.461 40.330 1.00 0.00 O \nATOM 2249 H GLY A 219 -28.809 20.039 37.999 1.00 0.00 H \nATOM 2250 HA2 GLY A 219 -27.921 17.903 37.881 1.00 0.00 H \nATOM 2251 HA3 GLY A 219 -26.545 18.586 37.607 1.00 0.00 H \nATOM 2252 N ASP A 220 -26.156 17.848 40.008 1.00 0.00 N \nATOM 2253 CA ASP A 220 -25.857 17.677 41.422 1.00 0.00 C \nATOM 2254 C ASP A 220 -24.584 18.395 41.852 1.00 0.00 C \nATOM 2255 O ASP A 220 -24.058 18.110 42.933 1.00 0.00 O \nATOM 2256 CB ASP A 220 -25.777 16.187 41.770 1.00 0.00 C \nATOM 2257 CG ASP A 220 -24.513 15.522 41.255 1.00 0.00 C \nATOM 2258 OD1 ASP A 220 -23.891 16.044 40.305 1.00 0.00 O \nATOM 2259 OD2 ASP A 220 -24.146 14.460 41.801 1.00 0.00 O \nATOM 2260 H ASP A 220 -25.679 17.358 39.486 1.00 0.00 H \nATOM 2261 HA ASP A 220 -26.585 18.086 41.915 1.00 0.00 H \nATOM 2262 HB2 ASP A 220 -25.821 16.083 42.733 1.00 0.00 H \nATOM 2263 HB3 ASP A 220 -26.549 15.732 41.399 1.00 0.00 H \nATOM 2264 N SER A 221 -24.073 19.311 41.034 1.00 0.00 N \nATOM 2265 CA SER A 221 -23.101 20.264 41.538 1.00 0.00 C \nATOM 2266 C SER A 221 -23.828 21.338 42.343 1.00 0.00 C \nATOM 2267 O SER A 221 -25.053 21.476 42.279 1.00 0.00 O \nATOM 2268 CB SER A 221 -22.302 20.879 40.389 1.00 0.00 C \nATOM 2269 OG SER A 221 -21.377 19.950 39.850 1.00 0.00 O \nATOM 2270 H SER A 221 -24.273 19.394 40.202 1.00 0.00 H \nATOM 2271 HA SER A 221 -22.470 19.809 42.117 1.00 0.00 H \nATOM 2272 HB2 SER A 221 -22.909 21.176 39.693 1.00 0.00 H \nATOM 2273 HB3 SER A 221 -21.828 21.664 40.706 1.00 0.00 H \nATOM 2274 HG SER A 221 -21.727 19.187 39.826 1.00 0.00 H \nATOM 2275 N ARG A 222 -23.067 22.115 43.110 1.00 0.00 N \nATOM 2276 CA ARG A 222 -23.703 23.027 44.047 1.00 0.00 C \nATOM 2277 C ARG A 222 -22.897 24.309 44.180 1.00 0.00 C \nATOM 2278 O ARG A 222 -21.664 24.299 44.112 1.00 0.00 O \nATOM 2279 CB ARG A 222 -23.880 22.366 45.421 1.00 0.00 C \nATOM 2280 CG ARG A 222 -24.827 23.102 46.351 1.00 0.00 C \nATOM 2281 CD ARG A 222 -24.870 22.461 47.728 1.00 0.00 C \nATOM 2282 NE ARG A 222 -25.287 21.063 47.672 1.00 0.00 N \nATOM 2283 CZ ARG A 222 -24.963 20.150 48.582 1.00 0.00 C \nATOM 2284 NH1 ARG A 222 -24.216 20.486 49.625 1.00 0.00 N \nATOM 2285 NH2 ARG A 222 -25.384 18.899 48.450 1.00 0.00 N \nATOM 2286 H ARG A 222 -22.207 22.129 43.103 1.00 0.00 H \nATOM 2287 HA ARG A 222 -24.581 23.248 43.699 1.00 0.00 H \nATOM 2288 HB2 ARG A 222 -24.207 21.462 45.293 1.00 0.00 H \nATOM 2289 HB3 ARG A 222 -23.012 22.296 45.849 1.00 0.00 H \nATOM 2290 HG2 ARG A 222 -24.547 24.027 46.433 1.00 0.00 H \nATOM 2291 HG3 ARG A 222 -25.718 23.108 45.968 1.00 0.00 H \nATOM 2292 HD2 ARG A 222 -23.993 22.519 48.138 1.00 0.00 H \nATOM 2293 HD3 ARG A 222 -25.481 22.957 48.295 1.00 0.00 H \nATOM 2294 HE ARG A 222 -25.773 20.814 47.008 1.00 0.00 H \nATOM 2295 HH11 ARG A 222 -23.940 21.296 49.713 1.00 0.00 H \nATOM 2296 HH12 ARG A 222 -24.007 19.894 50.213 1.00 0.00 H \nATOM 2297 HH21 ARG A 222 -25.868 18.677 47.774 1.00 0.00 H \nATOM 2298 HH22 ARG A 222 -25.173 18.310 49.040 1.00 0.00 H \nATOM 2299 N ILE A 223 -23.615 25.413 44.372 1.00 0.00 N \nATOM 2300 CA ILE A 223 -23.031 26.709 44.695 1.00 0.00 C \nATOM 2301 C ILE A 223 -23.632 27.172 46.015 1.00 0.00 C \nATOM 2302 O ILE A 223 -24.846 27.060 46.222 1.00 0.00 O \nATOM 2303 CB ILE A 223 -23.276 27.746 43.583 1.00 0.00 C \nATOM 2304 CG1 ILE A 223 -22.849 29.138 44.047 1.00 0.00 C \nATOM 2305 CG2 ILE A 223 -24.738 27.753 43.178 1.00 0.00 C \nATOM 2306 CD1 ILE A 223 -22.780 30.157 42.941 1.00 0.00 C \nATOM 2307 H ILE A 223 -24.473 25.428 44.317 1.00 0.00 H \nATOM 2308 HA ILE A 223 -22.068 26.620 44.772 1.00 0.00 H \nATOM 2309 HB ILE A 223 -22.742 27.500 42.812 1.00 0.00 H \nATOM 2310 HG12 ILE A 223 -23.472 29.449 44.723 1.00 0.00 H \nATOM 2311 HG13 ILE A 223 -21.979 29.075 44.471 1.00 0.00 H \nATOM 2312 HG21 ILE A 223 -24.877 28.410 42.478 1.00 0.00 H \nATOM 2313 HG22 ILE A 223 -24.988 26.875 42.851 1.00 0.00 H \nATOM 2314 HG23 ILE A 223 -25.286 27.979 43.946 1.00 0.00 H \nATOM 2315 HD11 ILE A 223 -22.504 31.012 43.306 1.00 0.00 H \nATOM 2316 HD12 ILE A 223 -22.138 29.868 42.274 1.00 0.00 H \nATOM 2317 HD13 ILE A 223 -23.654 30.248 42.530 1.00 0.00 H \nATOM 2318 N VAL A 224 -22.785 27.670 46.913 1.00 0.00 N \nATOM 2319 CA VAL A 224 -23.204 28.089 48.246 1.00 0.00 C \nATOM 2320 C VAL A 224 -22.660 29.486 48.511 1.00 0.00 C \nATOM 2321 O VAL A 224 -21.486 29.761 48.239 1.00 0.00 O \nATOM 2322 CB VAL A 224 -22.722 27.105 49.331 1.00 0.00 C \nATOM 2323 CG1 VAL A 224 -23.013 27.654 50.716 1.00 0.00 C \nATOM 2324 CG2 VAL A 224 -23.380 25.744 49.147 1.00 0.00 C \nATOM 2325 H VAL A 224 -21.945 27.775 46.763 1.00 0.00 H \nATOM 2326 HA VAL A 224 -24.173 28.097 48.283 1.00 0.00 H \nATOM 2327 HB VAL A 224 -21.762 26.996 49.241 1.00 0.00 H \nATOM 2328 HG11 VAL A 224 -22.704 27.024 51.386 1.00 0.00 H \nATOM 2329 HG12 VAL A 224 -22.553 28.500 50.832 1.00 0.00 H \nATOM 2330 HG13 VAL A 224 -23.968 27.789 50.816 1.00 0.00 H \nATOM 2331 HG21 VAL A 224 -23.067 25.137 49.836 1.00 0.00 H \nATOM 2332 HG22 VAL A 224 -24.343 25.838 49.213 1.00 0.00 H \nATOM 2333 HG23 VAL A 224 -23.150 25.388 48.275 1.00 0.00 H \nATOM 2334 N LEU A 225 -23.510 30.365 49.035 1.00 0.00 N \nATOM 2335 CA LEU A 225 -23.116 31.717 49.405 1.00 0.00 C \nATOM 2336 C LEU A 225 -22.923 31.820 50.913 1.00 0.00 C \nATOM 2337 O LEU A 225 -23.692 31.247 51.690 1.00 0.00 O \nATOM 2338 CB LEU A 225 -24.162 32.736 48.945 1.00 0.00 C \nATOM 2339 CG LEU A 225 -24.105 34.118 49.602 1.00 0.00 C \nATOM 2340 CD1 LEU A 225 -22.869 34.879 49.144 1.00 0.00 C \nATOM 2341 CD2 LEU A 225 -25.369 34.922 49.324 1.00 0.00 C \nATOM 2342 H LEU A 225 -24.338 30.190 49.186 1.00 0.00 H \nATOM 2343 HA LEU A 225 -22.276 31.916 48.963 1.00 0.00 H \nATOM 2344 HB2 LEU A 225 -24.072 32.852 47.986 1.00 0.00 H \nATOM 2345 HB3 LEU A 225 -25.042 32.360 49.104 1.00 0.00 H \nATOM 2346 HG LEU A 225 -24.047 33.986 50.561 1.00 0.00 H \nATOM 2347 HD11 LEU A 225 -22.849 35.751 49.569 1.00 0.00 H \nATOM 2348 HD12 LEU A 225 -22.073 34.382 49.390 1.00 0.00 H \nATOM 2349 HD13 LEU A 225 -22.896 34.990 48.181 1.00 0.00 H \nATOM 2350 HD21 LEU A 225 -25.302 35.790 49.753 1.00 0.00 H \nATOM 2351 HD22 LEU A 225 -25.473 35.042 48.367 1.00 0.00 H \nATOM 2352 HD23 LEU A 225 -26.139 34.447 49.675 1.00 0.00 H \nATOM 2353 N CYS A 226 -21.883 32.546 51.319 1.00 0.00 N \nATOM 2354 CA CYS A 226 -21.620 32.842 52.723 1.00 0.00 C \nATOM 2355 C CYS A 226 -22.058 34.278 52.997 1.00 0.00 C \nATOM 2356 O CYS A 226 -21.425 35.227 52.523 1.00 0.00 O \nATOM 2357 CB CYS A 226 -20.142 32.641 53.053 1.00 0.00 C \nATOM 2358 SG CYS A 226 -19.747 32.761 54.810 1.00 0.00 S \nATOM 2359 H CYS A 226 -21.305 32.884 50.780 1.00 0.00 H \nATOM 2360 HA CYS A 226 -22.121 32.235 53.290 1.00 0.00 H \nATOM 2361 HB2 CYS A 226 -19.865 31.769 52.729 1.00 0.00 H \nATOM 2362 HB3 CYS A 226 -19.621 33.302 52.570 1.00 0.00 H \nATOM 2363 HG CYS A 226 -20.286 33.726 55.277 1.00 0.00 H \nATOM 2364 N ARG A 227 -23.143 34.436 53.752 1.00 0.00 N \nATOM 2365 CA ARG A 227 -23.642 35.765 54.101 1.00 0.00 C \nATOM 2366 C ARG A 227 -24.394 35.662 55.420 1.00 0.00 C \nATOM 2367 O ARG A 227 -25.462 35.040 55.480 1.00 0.00 O \nATOM 2368 CB ARG A 227 -24.542 36.322 53.000 1.00 0.00 C \nATOM 2369 CG ARG A 227 -25.556 37.350 53.485 1.00 0.00 C \nATOM 2370 CD ARG A 227 -26.831 37.310 52.658 1.00 0.00 C \nATOM 2371 NE ARG A 227 -26.656 37.943 51.354 1.00 0.00 N \nATOM 2372 CZ ARG A 227 -27.600 38.002 50.421 1.00 0.00 C \nATOM 2373 NH1 ARG A 227 -28.792 37.464 50.644 1.00 0.00 N \nATOM 2374 NH2 ARG A 227 -27.352 38.600 49.264 1.00 0.00 N \nATOM 2375 H ARG A 227 -23.605 33.786 54.073 1.00 0.00 H \nATOM 2376 HA ARG A 227 -22.897 36.379 54.194 1.00 0.00 H \nATOM 2377 HB2 ARG A 227 -23.987 36.728 52.316 1.00 0.00 H \nATOM 2378 HB3 ARG A 227 -25.016 35.587 52.581 1.00 0.00 H \nATOM 2379 HG2 ARG A 227 -25.768 37.182 54.417 1.00 0.00 H \nATOM 2380 HG3 ARG A 227 -25.167 38.237 53.438 1.00 0.00 H \nATOM 2381 HD2 ARG A 227 -27.107 36.388 52.535 1.00 0.00 H \nATOM 2382 HD3 ARG A 227 -27.543 37.757 53.141 1.00 0.00 H \nATOM 2383 HE ARG A 227 -25.894 38.300 51.179 1.00 0.00 H \nATOM 2384 HH11 ARG A 227 -28.955 37.076 51.394 1.00 0.00 H \nATOM 2385 HH12 ARG A 227 -29.402 37.503 50.039 1.00 0.00 H \nATOM 2386 HH21 ARG A 227 -26.580 38.950 49.117 1.00 0.00 H \nATOM 2387 HH22 ARG A 227 -27.963 38.638 48.660 1.00 0.00 H \nATOM 2388 N GLY A 228 -23.825 36.232 56.479 1.00 0.00 N \nATOM 2389 CA GLY A 228 -22.472 36.754 56.470 1.00 0.00 C \nATOM 2390 C GLY A 228 -21.657 35.652 57.105 1.00 0.00 C \nATOM 2391 O GLY A 228 -20.462 35.475 56.838 1.00 0.00 O \nATOM 2392 H GLY A 228 -24.226 36.326 57.234 1.00 0.00 H \nATOM 2393 HA2 GLY A 228 -22.170 36.946 55.568 1.00 0.00 H \nATOM 2394 HA3 GLY A 228 -22.406 37.581 56.973 1.00 0.00 H \nATOM 2395 N LYS A 229 -22.332 34.905 57.978 1.00 0.00 N \nATOM 2396 CA LYS A 229 -21.846 33.642 58.510 1.00 0.00 C \nATOM 2397 C LYS A 229 -22.787 32.498 58.164 1.00 0.00 C \nATOM 2398 O LYS A 229 -22.397 31.336 58.291 1.00 0.00 O \nATOM 2399 CB LYS A 229 -21.684 33.750 60.043 1.00 0.00 C \nATOM 2400 CG LYS A 229 -21.751 32.481 60.940 1.00 0.00 C \nATOM 2401 CD LYS A 229 -20.838 31.319 60.596 1.00 0.00 C \nATOM 2402 CE LYS A 229 -21.016 30.245 61.658 1.00 0.00 C \nATOM 2403 NZ LYS A 229 -22.108 29.315 61.248 1.00 0.00 N \nATOM 2404 H LYS A 229 -23.105 35.128 58.282 1.00 0.00 H \nATOM 2405 HA LYS A 229 -20.985 33.453 58.105 1.00 0.00 H \nATOM 2406 HB2 LYS A 229 -20.827 34.173 60.210 1.00 0.00 H \nATOM 2407 HB3 LYS A 229 -22.368 34.360 60.360 1.00 0.00 H \nATOM 2408 HG2 LYS A 229 -21.559 32.751 61.852 1.00 0.00 H \nATOM 2409 HG3 LYS A 229 -22.665 32.155 60.927 1.00 0.00 H \nATOM 2410 HD2 LYS A 229 -21.055 30.967 59.719 1.00 0.00 H \nATOM 2411 HD3 LYS A 229 -19.914 31.613 60.563 1.00 0.00 H \nATOM 2412 HE2 LYS A 229 -20.188 29.754 61.777 1.00 0.00 H \nATOM 2413 HE3 LYS A 229 -21.229 30.653 62.512 1.00 0.00 H \nATOM 2414 HZ1 LYS A 229 -22.607 29.113 61.956 1.00 0.00 H \nATOM 2415 HZ2 LYS A 229 -22.615 29.706 60.630 1.00 0.00 H \nATOM 2416 HZ3 LYS A 229 -21.754 28.570 60.913 1.00 0.00 H \nATOM 2417 N GLU A 230 -23.941 32.775 57.597 1.00 0.00 N \nATOM 2418 CA GLU A 230 -24.662 31.584 57.193 1.00 0.00 C \nATOM 2419 C GLU A 230 -24.117 31.056 55.875 1.00 0.00 C \nATOM 2420 O GLU A 230 -23.633 31.822 55.036 1.00 0.00 O \nATOM 2421 CB GLU A 230 -26.151 31.872 56.995 1.00 0.00 C \nATOM 2422 CG GLU A 230 -26.927 32.379 58.183 1.00 0.00 C \nATOM 2423 CD GLU A 230 -27.327 33.828 58.011 1.00 0.00 C \nATOM 2424 OE1 GLU A 230 -27.952 34.150 56.976 1.00 0.00 O \nATOM 2425 OE2 GLU A 230 -27.034 34.643 58.910 1.00 0.00 O \nATOM 2426 H GLU A 230 -24.296 33.544 57.448 1.00 0.00 H \nATOM 2427 HA GLU A 230 -24.546 30.931 57.900 1.00 0.00 H \nATOM 2428 HB2 GLU A 230 -26.237 32.523 56.281 1.00 0.00 H \nATOM 2429 HB3 GLU A 230 -26.575 31.056 56.687 1.00 0.00 H \nATOM 2430 HG2 GLU A 230 -27.721 31.836 58.307 1.00 0.00 H \nATOM 2431 HG3 GLU A 230 -26.390 32.284 58.985 1.00 0.00 H \nATOM 2432 N PRO A 231 -24.150 29.746 55.693 1.00 0.00 N \nATOM 2433 CA PRO A 231 -24.244 29.212 54.343 1.00 0.00 C \nATOM 2434 C PRO A 231 -25.696 29.357 53.934 1.00 0.00 C \nATOM 2435 O PRO A 231 -26.608 29.191 54.748 1.00 0.00 O \nATOM 2436 CB PRO A 231 -23.836 27.746 54.510 1.00 0.00 C \nATOM 2437 CG PRO A 231 -24.172 27.434 55.940 1.00 0.00 C \nATOM 2438 CD PRO A 231 -23.953 28.699 56.710 1.00 0.00 C \nATOM 2439 HA PRO A 231 -23.695 29.645 53.671 1.00 0.00 H \nATOM 2440 HB2 PRO A 231 -24.321 27.171 53.898 1.00 0.00 H \nATOM 2441 HB3 PRO A 231 -22.891 27.618 54.331 1.00 0.00 H \nATOM 2442 HG2 PRO A 231 -25.091 27.134 56.022 1.00 0.00 H \nATOM 2443 HG3 PRO A 231 -23.609 26.721 56.280 1.00 0.00 H \nATOM 2444 HD2 PRO A 231 -24.583 28.787 57.442 1.00 0.00 H \nATOM 2445 HD3 PRO A 231 -23.063 28.735 57.095 1.00 0.00 H \nATOM 2446 N VAL A 232 -25.915 29.689 52.671 1.00 0.00 N \nATOM 2447 CA VAL A 232 -27.255 29.673 52.108 1.00 0.00 C \nATOM 2448 C VAL A 232 -27.138 29.078 50.718 1.00 0.00 C \nATOM 2449 O VAL A 232 -26.392 29.595 49.877 1.00 0.00 O \nATOM 2450 CB VAL A 232 -27.900 31.072 52.074 1.00 0.00 C \nATOM 2451 CG1 VAL A 232 -26.934 32.114 51.522 1.00 0.00 C \nATOM 2452 CG2 VAL A 232 -29.196 31.045 51.277 1.00 0.00 C \nATOM 2453 H VAL A 232 -25.299 29.928 52.121 1.00 0.00 H \nATOM 2454 HA VAL A 232 -27.843 29.140 52.666 1.00 0.00 H \nATOM 2455 HB VAL A 232 -28.112 31.327 52.986 1.00 0.00 H \nATOM 2456 HG11 VAL A 232 -27.366 32.983 51.512 1.00 0.00 H \nATOM 2457 HG12 VAL A 232 -26.144 32.152 52.083 1.00 0.00 H \nATOM 2458 HG13 VAL A 232 -26.677 31.871 50.619 1.00 0.00 H \nATOM 2459 HG21 VAL A 232 -29.588 31.932 51.266 1.00 0.00 H \nATOM 2460 HG22 VAL A 232 -29.011 30.762 50.368 1.00 0.00 H \nATOM 2461 HG23 VAL A 232 -29.816 30.423 51.689 1.00 0.00 H \nATOM 2462 N ALA A 233 -27.849 27.983 50.481 1.00 0.00 N \nATOM 2463 CA ALA A 233 -27.722 27.274 49.219 1.00 0.00 C \nATOM 2464 C ALA A 233 -28.419 28.062 48.122 1.00 0.00 C \nATOM 2465 O ALA A 233 -29.609 28.378 48.232 1.00 0.00 O \nATOM 2466 CB ALA A 233 -28.313 25.873 49.338 1.00 0.00 C \nATOM 2467 H ALA A 233 -28.408 27.637 51.036 1.00 0.00 H \nATOM 2468 HA ALA A 233 -26.783 27.186 48.993 1.00 0.00 H \nATOM 2469 HB1 ALA A 233 -28.222 25.410 48.490 1.00 0.00 H \nATOM 2470 HB2 ALA A 233 -27.841 25.380 50.027 1.00 0.00 H \nATOM 2471 HB3 ALA A 233 -29.252 25.937 49.572 1.00 0.00 H \nATOM 2472 N LEU A 234 -27.677 28.383 47.070 1.00 0.00 N \nATOM 2473 CA LEU A 234 -28.240 29.053 45.910 1.00 0.00 C \nATOM 2474 C LEU A 234 -28.676 28.070 44.836 1.00 0.00 C \nATOM 2475 O LEU A 234 -29.106 28.494 43.759 1.00 0.00 O \nATOM 2476 CB LEU A 234 -27.230 30.048 45.327 1.00 0.00 C \nATOM 2477 CG LEU A 234 -26.587 31.069 46.277 1.00 0.00 C \nATOM 2478 CD1 LEU A 234 -25.986 32.224 45.484 1.00 0.00 C \nATOM 2479 CD2 LEU A 234 -27.568 31.590 47.324 1.00 0.00 C \nATOM 2480 H LEU A 234 -26.835 28.218 47.010 1.00 0.00 H \nATOM 2481 HA LEU A 234 -29.030 29.530 46.210 1.00 0.00 H \nATOM 2482 HB2 LEU A 234 -26.516 29.538 44.913 1.00 0.00 H \nATOM 2483 HB3 LEU A 234 -27.674 30.540 44.619 1.00 0.00 H \nATOM 2484 HG LEU A 234 -25.880 30.609 46.757 1.00 0.00 H \nATOM 2485 HD11 LEU A 234 -25.584 32.861 46.095 1.00 0.00 H \nATOM 2486 HD12 LEU A 234 -25.308 31.884 44.879 1.00 0.00 H \nATOM 2487 HD13 LEU A 234 -26.683 32.663 44.973 1.00 0.00 H \nATOM 2488 HD21 LEU A 234 -27.119 32.229 47.899 1.00 0.00 H \nATOM 2489 HD22 LEU A 234 -28.315 32.023 46.881 1.00 0.00 H \nATOM 2490 HD23 LEU A 234 -27.895 30.849 47.858 1.00 0.00 H \nATOM 2491 N SER A 235 -28.574 26.772 45.110 1.00 0.00 N \nATOM 2492 CA SER A 235 -28.983 25.737 44.176 1.00 0.00 C \nATOM 2493 C SER A 235 -29.365 24.492 44.962 1.00 0.00 C \nATOM 2494 O SER A 235 -28.791 24.204 46.015 1.00 0.00 O \nATOM 2495 CB SER A 235 -27.873 25.412 43.171 1.00 0.00 C \nATOM 2496 OG SER A 235 -26.743 24.859 43.823 1.00 0.00 O \nATOM 2497 H SER A 235 -28.262 26.468 45.852 1.00 0.00 H \nATOM 2498 HA SER A 235 -29.744 26.058 43.668 1.00 0.00 H \nATOM 2499 HB2 SER A 235 -28.206 24.787 42.508 1.00 0.00 H \nATOM 2500 HB3 SER A 235 -27.615 26.218 42.697 1.00 0.00 H \nATOM 2501 HG SER A 235 -26.957 24.618 44.599 1.00 0.00 H \nATOM 2502 N ILE A 236 -30.341 23.757 44.438 1.00 0.00 N \nATOM 2503 CA ILE A 236 -30.789 22.498 45.020 1.00 0.00 C \nATOM 2504 C ILE A 236 -30.375 21.373 44.084 1.00 0.00 C \nATOM 2505 O ILE A 236 -30.566 21.472 42.866 1.00 0.00 O \nATOM 2506 CB ILE A 236 -32.310 22.490 45.251 1.00 0.00 C \nATOM 2507 CG1 ILE A 236 -32.739 23.725 46.047 1.00 0.00 C \nATOM 2508 CG2 ILE A 236 -32.735 21.218 45.974 1.00 0.00 C \nATOM 2509 CD1 ILE A 236 -34.176 24.136 45.800 1.00 0.00 C \nATOM 2510 H ILE A 236 -30.767 23.979 43.725 1.00 0.00 H \nATOM 2511 HA ILE A 236 -30.377 22.378 45.890 1.00 0.00 H \nATOM 2512 HB ILE A 236 -32.750 22.513 44.387 1.00 0.00 H \nATOM 2513 HG12 ILE A 236 -32.619 23.548 46.993 1.00 0.00 H \nATOM 2514 HG13 ILE A 236 -32.155 24.466 45.820 1.00 0.00 H \nATOM 2515 HG21 ILE A 236 -33.695 21.229 46.111 1.00 0.00 H \nATOM 2516 HG22 ILE A 236 -32.494 20.446 45.439 1.00 0.00 H \nATOM 2517 HG23 ILE A 236 -32.286 21.168 46.833 1.00 0.00 H \nATOM 2518 HD11 ILE A 236 -34.384 24.921 46.331 1.00 0.00 H \nATOM 2519 HD12 ILE A 236 -34.297 24.341 44.860 1.00 0.00 H \nATOM 2520 HD13 ILE A 236 -34.768 23.410 46.051 1.00 0.00 H \nATOM 2521 N ASP A 237 -29.797 20.314 44.648 1.00 0.00 N \nATOM 2522 CA ASP A 237 -29.298 19.221 43.828 1.00 0.00 C \nATOM 2523 C ASP A 237 -30.450 18.556 43.089 1.00 0.00 C \nATOM 2524 O ASP A 237 -31.514 18.303 43.658 1.00 0.00 O \nATOM 2525 CB ASP A 237 -28.562 18.194 44.690 1.00 0.00 C \nATOM 2526 CG ASP A 237 -27.432 18.808 45.493 1.00 0.00 C \nATOM 2527 OD1 ASP A 237 -27.259 20.044 45.429 1.00 0.00 O \nATOM 2528 OD2 ASP A 237 -26.711 18.055 46.182 1.00 0.00 O \nATOM 2529 H ASP A 237 -29.686 20.212 45.495 1.00 0.00 H \nATOM 2530 HA ASP A 237 -28.673 19.582 43.180 1.00 0.00 H \nATOM 2531 HB2 ASP A 237 -29.193 17.774 45.295 1.00 0.00 H \nATOM 2532 HB3 ASP A 237 -28.206 17.494 44.120 1.00 0.00 H \nATOM 2533 N HIS A 238 -30.230 18.275 41.807 1.00 0.00 N \nATOM 2534 CA HIS A 238 -31.236 17.611 40.981 1.00 0.00 C \nATOM 2535 C HIS A 238 -31.041 16.097 41.077 1.00 0.00 C \nATOM 2536 O HIS A 238 -30.603 15.422 40.145 1.00 0.00 O \nATOM 2537 CB HIS A 238 -31.158 18.113 39.545 1.00 0.00 C \nATOM 2538 CG HIS A 238 -31.559 19.548 39.389 1.00 0.00 C \nATOM 2539 ND1 HIS A 238 -30.797 20.462 38.693 1.00 0.00 N \nATOM 2540 CD2 HIS A 238 -32.638 20.227 39.843 1.00 0.00 C \nATOM 2541 CE1 HIS A 238 -31.392 21.642 38.723 1.00 0.00 C \nATOM 2542 NE2 HIS A 238 -32.511 21.527 39.415 1.00 0.00 N \nATOM 2543 H HIS A 238 -29.499 18.462 41.394 1.00 0.00 H \nATOM 2544 HA HIS A 238 -32.126 17.822 41.304 1.00 0.00 H \nATOM 2545 HB2 HIS A 238 -30.251 18.001 39.220 1.00 0.00 H \nATOM 2546 HB3 HIS A 238 -31.729 17.563 38.986 1.00 0.00 H \nATOM 2547 HD1 HIS A 238 -30.051 20.291 38.301 1.00 0.00 H \nATOM 2548 HD2 HIS A 238 -33.336 19.879 40.350 1.00 0.00 H \nATOM 2549 HE1 HIS A 238 -31.076 22.421 38.325 1.00 0.00 H \nATOM 2550 HE2 HIS A 238 -33.069 22.162 39.572 1.00 0.00 H \nATOM 2551 N LYS A 239 -31.388 15.571 42.251 1.00 0.00 N \nATOM 2552 CA LYS A 239 -31.398 14.144 42.544 1.00 0.00 C \nATOM 2553 C LYS A 239 -32.741 13.538 42.147 1.00 0.00 C \nATOM 2554 O LYS A 239 -33.782 14.185 42.297 1.00 0.00 O \nATOM 2555 CB LYS A 239 -31.139 13.894 44.025 1.00 0.00 C \nATOM 2556 CG LYS A 239 -29.778 14.380 44.498 1.00 0.00 C \nATOM 2557 CD LYS A 239 -28.751 13.260 44.458 1.00 0.00 C \nATOM 2558 CE LYS A 239 -27.373 13.789 44.100 1.00 0.00 C \nATOM 2559 NZ LYS A 239 -26.500 12.723 43.532 1.00 0.00 N \nATOM 2560 H LYS A 239 -31.632 16.054 42.920 1.00 0.00 H \nATOM 2561 HA LYS A 239 -30.691 13.723 42.031 1.00 0.00 H \nATOM 2562 HB2 LYS A 239 -31.829 14.335 44.545 1.00 0.00 H \nATOM 2563 HB3 LYS A 239 -31.214 12.943 44.202 1.00 0.00 H \nATOM 2564 HG2 LYS A 239 -29.481 15.115 43.938 1.00 0.00 H \nATOM 2565 HG3 LYS A 239 -29.851 14.724 45.402 1.00 0.00 H \nATOM 2566 HD2 LYS A 239 -28.716 12.819 45.321 1.00 0.00 H \nATOM 2567 HD3 LYS A 239 -29.022 12.592 43.809 1.00 0.00 H \nATOM 2568 HE2 LYS A 239 -27.461 14.511 43.458 1.00 0.00 H \nATOM 2569 HE3 LYS A 239 -26.954 14.162 44.891 1.00 0.00 H \nATOM 2570 HZ1 LYS A 239 -25.660 13.015 43.496 1.00 0.00 H \nATOM 2571 HZ2 LYS A 239 -26.541 11.999 44.048 1.00 0.00 H \nATOM 2572 HZ3 LYS A 239 -26.777 12.518 42.712 1.00 0.00 H \nATOM 2573 N PRO A 240 -32.733 12.312 41.616 1.00 0.00 N \nATOM 2574 CA PRO A 240 -33.992 11.731 41.117 1.00 0.00 C \nATOM 2575 C PRO A 240 -35.073 11.572 42.175 1.00 0.00 C \nATOM 2576 O PRO A 240 -36.257 11.757 41.865 1.00 0.00 O \nATOM 2577 CB PRO A 240 -33.543 10.373 40.555 1.00 0.00 C \nATOM 2578 CG PRO A 240 -32.086 10.541 40.260 1.00 0.00 C \nATOM 2579 CD PRO A 240 -31.564 11.473 41.306 1.00 0.00 C \nATOM 2580 HA PRO A 240 -34.417 12.310 40.465 1.00 0.00 H \nATOM 2581 HB2 PRO A 240 -33.692 9.661 41.196 1.00 0.00 H \nATOM 2582 HB3 PRO A 240 -34.040 10.142 39.754 1.00 0.00 H \nATOM 2583 HG2 PRO A 240 -31.624 9.689 40.291 1.00 0.00 H \nATOM 2584 HG3 PRO A 240 -31.951 10.905 39.371 1.00 0.00 H \nATOM 2585 HD2 PRO A 240 -31.248 10.994 42.088 1.00 0.00 H \nATOM 2586 HD3 PRO A 240 -30.820 12.001 40.977 1.00 0.00 H \nATOM 2587 N ASP A 241 -34.707 11.239 43.416 1.00 0.00 N \nATOM 2588 CA ASP A 241 -35.696 11.131 44.486 1.00 0.00 C \nATOM 2589 C ASP A 241 -36.380 12.457 44.804 1.00 0.00 C \nATOM 2590 O ASP A 241 -37.486 12.439 45.358 1.00 0.00 O \nATOM 2591 CB ASP A 241 -35.084 10.514 45.746 1.00 0.00 C \nATOM 2592 CG ASP A 241 -33.693 11.009 46.031 1.00 0.00 C \nATOM 2593 OD1 ASP A 241 -33.009 11.449 45.085 1.00 0.00 O \nATOM 2594 OD2 ASP A 241 -33.271 10.929 47.204 1.00 0.00 O \nATOM 2595 H ASP A 241 -33.898 11.073 43.655 1.00 0.00 H \nATOM 2596 HA ASP A 241 -36.388 10.536 44.156 1.00 0.00 H \nATOM 2597 HB2 ASP A 241 -35.654 10.712 46.506 1.00 0.00 H \nATOM 2598 HB3 ASP A 241 -35.064 9.549 45.650 1.00 0.00 H \nATOM 2599 N ARG A 242 -35.744 13.595 44.508 1.00 0.00 N \nATOM 2600 CA ARG A 242 -36.352 14.891 44.795 1.00 0.00 C \nATOM 2601 C ARG A 242 -37.750 14.949 44.191 1.00 0.00 C \nATOM 2602 O ARG A 242 -37.970 14.531 43.051 1.00 0.00 O \nATOM 2603 CB ARG A 242 -35.475 16.022 44.246 1.00 0.00 C \nATOM 2604 CG ARG A 242 -36.141 17.391 44.198 1.00 0.00 C \nATOM 2605 CD ARG A 242 -35.132 18.497 43.891 1.00 0.00 C \nATOM 2606 NE ARG A 242 -35.758 19.658 43.260 1.00 0.00 N \nATOM 2607 CZ ARG A 242 -35.085 20.680 42.740 1.00 0.00 C \nATOM 2608 NH1 ARG A 242 -33.759 20.695 42.778 1.00 0.00 N \nATOM 2609 NH2 ARG A 242 -35.737 21.692 42.186 1.00 0.00 N \nATOM 2610 H ARG A 242 -34.966 13.635 44.144 1.00 0.00 H \nATOM 2611 HA ARG A 242 -36.424 15.004 45.756 1.00 0.00 H \nATOM 2612 HB2 ARG A 242 -34.675 16.086 44.791 1.00 0.00 H \nATOM 2613 HB3 ARG A 242 -35.189 15.785 43.350 1.00 0.00 H \nATOM 2614 HG2 ARG A 242 -36.837 17.390 43.522 1.00 0.00 H \nATOM 2615 HG3 ARG A 242 -36.572 17.572 45.048 1.00 0.00 H \nATOM 2616 HD2 ARG A 242 -34.697 18.773 44.713 1.00 0.00 H \nATOM 2617 HD3 ARG A 242 -34.440 18.148 43.308 1.00 0.00 H \nATOM 2618 HE ARG A 242 -36.617 19.681 43.223 1.00 0.00 H \nATOM 2619 HH11 ARG A 242 -33.332 20.042 43.140 1.00 0.00 H \nATOM 2620 HH12 ARG A 242 -33.327 21.358 42.441 1.00 0.00 H \nATOM 2621 HH21 ARG A 242 -36.597 21.688 42.162 1.00 0.00 H \nATOM 2622 HH22 ARG A 242 -35.300 22.352 41.850 1.00 0.00 H \nATOM 2623 N LYS A 243 -38.696 15.484 44.969 1.00 0.00 N \nATOM 2624 CA LYS A 243 -40.106 15.158 44.761 1.00 0.00 C \nATOM 2625 C LYS A 243 -40.637 15.667 43.426 1.00 0.00 C \nATOM 2626 O LYS A 243 -41.328 14.930 42.713 1.00 0.00 O \nATOM 2627 CB LYS A 243 -40.943 15.717 45.911 1.00 0.00 C \nATOM 2628 CG LYS A 243 -40.790 14.947 47.206 1.00 0.00 C \nATOM 2629 CD LYS A 243 -41.659 13.705 47.192 1.00 0.00 C \nATOM 2630 CE LYS A 243 -43.123 14.038 46.959 1.00 0.00 C \nATOM 2631 NZ LYS A 243 -43.594 15.115 47.868 1.00 0.00 N \nATOM 2632 H LYS A 243 -38.543 16.031 45.615 1.00 0.00 H \nATOM 2633 HA LYS A 243 -40.178 14.191 44.741 1.00 0.00 H \nATOM 2634 HB2 LYS A 243 -40.693 16.642 46.063 1.00 0.00 H \nATOM 2635 HB3 LYS A 243 -41.878 15.715 45.651 1.00 0.00 H \nATOM 2636 HG2 LYS A 243 -39.861 14.697 47.332 1.00 0.00 H \nATOM 2637 HG3 LYS A 243 -41.036 15.512 47.955 1.00 0.00 H \nATOM 2638 HD2 LYS A 243 -41.350 13.103 46.497 1.00 0.00 H \nATOM 2639 HD3 LYS A 243 -41.565 13.236 48.036 1.00 0.00 H \nATOM 2640 HE2 LYS A 243 -43.250 14.314 46.038 1.00 0.00 H \nATOM 2641 HE3 LYS A 243 -43.661 13.242 47.094 1.00 0.00 H \nATOM 2642 HZ1 LYS A 243 -44.481 15.177 47.821 1.00 0.00 H \nATOM 2643 HZ2 LYS A 243 -43.354 14.925 48.704 1.00 0.00 H \nATOM 2644 HZ3 LYS A 243 -43.230 15.890 47.624 1.00 0.00 H \nATOM 2645 N ASP A 244 -40.333 16.914 43.064 1.00 0.00 N \nATOM 2646 CA ASP A 244 -40.839 17.428 41.796 1.00 0.00 C \nATOM 2647 C ASP A 244 -40.150 16.770 40.606 1.00 0.00 C \nATOM 2648 O ASP A 244 -40.758 16.638 39.537 1.00 0.00 O \nATOM 2649 CB ASP A 244 -40.692 18.949 41.736 1.00 0.00 C \nATOM 2650 CG ASP A 244 -39.262 19.405 41.905 1.00 0.00 C \nATOM 2651 OD1 ASP A 244 -38.528 18.782 42.698 1.00 0.00 O \nATOM 2652 OD2 ASP A 244 -38.872 20.392 41.247 1.00 0.00 O \nATOM 2653 H ASP A 244 -39.852 17.461 43.522 1.00 0.00 H \nATOM 2654 HA ASP A 244 -41.782 17.206 41.744 1.00 0.00 H \nATOM 2655 HB2 ASP A 244 -41.031 19.269 40.886 1.00 0.00 H \nATOM 2656 HB3 ASP A 244 -41.239 19.350 42.429 1.00 0.00 H \nATOM 2657 N GLU A 245 -38.892 16.353 40.767 1.00 0.00 N \nATOM 2658 CA GLU A 245 -38.203 15.660 39.683 1.00 0.00 C \nATOM 2659 C GLU A 245 -38.762 14.256 39.476 1.00 0.00 C \nATOM 2660 O GLU A 245 -38.984 13.835 38.334 1.00 0.00 O \nATOM 2661 CB GLU A 245 -36.704 15.602 39.969 1.00 0.00 C \nATOM 2662 CG GLU A 245 -36.033 16.962 40.095 1.00 0.00 C \nATOM 2663 CD GLU A 245 -36.205 17.814 38.852 1.00 0.00 C \nATOM 2664 OE1 GLU A 245 -36.949 18.816 38.913 1.00 0.00 O \nATOM 2665 OE2 GLU A 245 -35.595 17.482 37.813 1.00 0.00 O \nATOM 2666 H GLU A 245 -38.429 16.460 41.484 1.00 0.00 H \nATOM 2667 HA GLU A 245 -38.350 16.159 38.864 1.00 0.00 H \nATOM 2668 HB2 GLU A 245 -36.562 15.106 40.791 1.00 0.00 H \nATOM 2669 HB3 GLU A 245 -36.270 15.104 39.259 1.00 0.00 H \nATOM 2670 HG2 GLU A 245 -36.403 17.432 40.859 1.00 0.00 H \nATOM 2671 HG3 GLU A 245 -35.087 16.837 40.269 1.00 0.00 H \nATOM 2672 N ARG A 246 -38.989 13.514 40.564 1.00 0.00 N \nATOM 2673 CA ARG A 246 -39.578 12.183 40.442 1.00 0.00 C \nATOM 2674 C ARG A 246 -40.960 12.246 39.806 1.00 0.00 C \nATOM 2675 O ARG A 246 -41.316 11.389 38.989 1.00 0.00 O \nATOM 2676 CB ARG A 246 -39.650 11.501 41.808 1.00 0.00 C \nATOM 2677 CG ARG A 246 -40.097 10.048 41.730 1.00 0.00 C \nATOM 2678 CD ARG A 246 -39.842 9.302 43.027 1.00 0.00 C \nATOM 2679 NE ARG A 246 -40.989 9.370 43.924 1.00 0.00 N \nATOM 2680 CZ ARG A 246 -40.988 10.000 45.094 1.00 0.00 C \nATOM 2681 NH1 ARG A 246 -39.894 10.619 45.512 1.00 0.00 N \nATOM 2682 NH2 ARG A 246 -42.083 10.011 45.845 1.00 0.00 N \nATOM 2683 H ARG A 246 -38.811 13.760 41.369 1.00 0.00 H \nATOM 2684 HA ARG A 246 -39.006 11.657 39.861 1.00 0.00 H \nATOM 2685 HB2 ARG A 246 -38.778 11.543 42.230 1.00 0.00 H \nATOM 2686 HB3 ARG A 246 -40.264 11.992 42.376 1.00 0.00 H \nATOM 2687 HG2 ARG A 246 -41.043 10.013 41.519 1.00 0.00 H \nATOM 2688 HG3 ARG A 246 -39.628 9.605 41.006 1.00 0.00 H \nATOM 2689 HD2 ARG A 246 -39.638 8.374 42.832 1.00 0.00 H \nATOM 2690 HD3 ARG A 246 -39.064 9.677 43.468 1.00 0.00 H \nATOM 2691 HE ARG A 246 -41.714 8.977 43.680 1.00 0.00 H \nATOM 2692 HH11 ARG A 246 -39.184 10.613 45.026 1.00 0.00 H \nATOM 2693 HH12 ARG A 246 -39.893 11.027 46.269 1.00 0.00 H \nATOM 2694 HH21 ARG A 246 -42.794 9.610 45.574 1.00 0.00 H \nATOM 2695 HH22 ARG A 246 -42.081 10.419 46.602 1.00 0.00 H \nATOM 2696 N ALA A 247 -41.757 13.252 40.175 1.00 0.00 N \nATOM 2697 CA ALA A 247 -43.092 13.386 39.602 1.00 0.00 C \nATOM 2698 C ALA A 247 -43.026 13.678 38.109 1.00 0.00 C \nATOM 2699 O ALA A 247 -43.800 13.112 37.328 1.00 0.00 O \nATOM 2700 CB ALA A 247 -43.868 14.482 40.331 1.00 0.00 C \nATOM 2701 H ALA A 247 -41.545 13.858 40.747 1.00 0.00 H \nATOM 2702 HA ALA A 247 -43.557 12.542 39.716 1.00 0.00 H \nATOM 2703 HB1 ALA A 247 -44.754 14.564 39.944 1.00 0.00 H \nATOM 2704 HB2 ALA A 247 -43.946 14.253 41.270 1.00 0.00 H \nATOM 2705 HB3 ALA A 247 -43.397 15.326 40.242 1.00 0.00 H \nATOM 2706 N ARG A 248 -42.115 14.563 37.695 1.00 0.00 N \nATOM 2707 CA ARG A 248 -41.967 14.856 36.273 1.00 0.00 C \nATOM 2708 C ARG A 248 -41.515 13.623 35.501 1.00 0.00 C \nATOM 2709 O ARG A 248 -42.019 13.346 34.406 1.00 0.00 O \nATOM 2710 CB ARG A 248 -40.981 16.004 36.071 1.00 0.00 C \nATOM 2711 CG ARG A 248 -40.540 16.173 34.623 1.00 0.00 C \nATOM 2712 CD ARG A 248 -39.486 17.257 34.465 1.00 0.00 C \nATOM 2713 NE ARG A 248 -38.236 16.938 35.151 1.00 0.00 N \nATOM 2714 CZ ARG A 248 -37.321 16.093 34.686 1.00 0.00 C \nATOM 2715 NH1 ARG A 248 -36.211 15.869 35.378 1.00 0.00 N \nATOM 2716 NH2 ARG A 248 -37.514 15.472 33.530 1.00 0.00 N \nATOM 2717 H ARG A 248 -41.583 14.996 38.214 1.00 0.00 H \nATOM 2718 HA ARG A 248 -42.834 15.122 35.928 1.00 0.00 H \nATOM 2719 HB2 ARG A 248 -41.389 16.829 36.377 1.00 0.00 H \nATOM 2720 HB3 ARG A 248 -40.199 15.852 36.625 1.00 0.00 H \nATOM 2721 HG2 ARG A 248 -40.188 15.331 34.294 1.00 0.00 H \nATOM 2722 HG3 ARG A 248 -41.310 16.391 34.076 1.00 0.00 H \nATOM 2723 HD2 ARG A 248 -39.306 17.392 33.521 1.00 0.00 H \nATOM 2724 HD3 ARG A 248 -39.835 18.094 34.810 1.00 0.00 H \nATOM 2725 HE ARG A 248 -38.082 17.322 35.905 1.00 0.00 H \nATOM 2726 HH11 ARG A 248 -36.083 16.271 36.128 1.00 0.00 H \nATOM 2727 HH12 ARG A 248 -35.619 15.322 35.077 1.00 0.00 H \nATOM 2728 HH21 ARG A 248 -38.232 15.616 33.079 1.00 0.00 H \nATOM 2729 HH22 ARG A 248 -36.921 14.926 33.231 1.00 0.00 H \nATOM 2730 N ILE A 249 -40.569 12.867 36.061 1.00 0.00 N \nATOM 2731 CA ILE A 249 -40.045 11.690 35.374 1.00 0.00 C \nATOM 2732 C ILE A 249 -41.130 10.629 35.220 1.00 0.00 C \nATOM 2733 O ILE A 249 -41.326 10.075 34.132 1.00 0.00 O \nATOM 2734 CB ILE A 249 -38.815 11.142 36.120 1.00 0.00 C \nATOM 2735 CG1 ILE A 249 -37.584 11.995 35.805 1.00 0.00 C \nATOM 2736 CG2 ILE A 249 -38.565 9.686 35.751 1.00 0.00 C \nATOM 2737 CD1 ILE A 249 -36.446 11.811 36.782 1.00 0.00 C \nATOM 2738 H ILE A 249 -40.221 13.019 36.833 1.00 0.00 H \nATOM 2739 HA ILE A 249 -39.762 11.946 34.482 1.00 0.00 H \nATOM 2740 HB ILE A 249 -38.988 11.186 37.073 1.00 0.00 H \nATOM 2741 HG12 ILE A 249 -37.271 11.778 34.913 1.00 0.00 H \nATOM 2742 HG13 ILE A 249 -37.843 12.930 35.796 1.00 0.00 H \nATOM 2743 HG21 ILE A 249 -37.787 9.359 36.230 1.00 0.00 H \nATOM 2744 HG22 ILE A 249 -39.339 9.154 35.991 1.00 0.00 H \nATOM 2745 HG23 ILE A 249 -38.409 9.616 34.796 1.00 0.00 H \nATOM 2746 HD11 ILE A 249 -35.703 12.378 36.524 1.00 0.00 H \nATOM 2747 HD12 ILE A 249 -36.742 12.053 37.673 1.00 0.00 H \nATOM 2748 HD13 ILE A 249 -36.162 10.884 36.777 1.00 0.00 H \nATOM 2749 N GLU A 250 -41.855 10.335 36.301 1.00 0.00 N \nATOM 2750 CA GLU A 250 -42.883 9.300 36.231 1.00 0.00 C \nATOM 2751 C GLU A 250 -44.045 9.714 35.339 1.00 0.00 C \nATOM 2752 O GLU A 250 -44.703 8.853 34.746 1.00 0.00 O \nATOM 2753 CB GLU A 250 -43.388 8.960 37.634 1.00 0.00 C \nATOM 2754 CG GLU A 250 -42.352 8.295 38.523 1.00 0.00 C \nATOM 2755 CD GLU A 250 -42.745 8.317 39.987 1.00 0.00 C \nATOM 2756 OE1 GLU A 250 -43.716 9.025 40.333 1.00 0.00 O \nATOM 2757 OE2 GLU A 250 -42.086 7.626 40.793 1.00 0.00 O \nATOM 2758 H GLU A 250 -41.769 10.715 37.068 1.00 0.00 H \nATOM 2759 HA GLU A 250 -42.478 8.512 35.837 1.00 0.00 H \nATOM 2760 HB2 GLU A 250 -43.693 9.774 38.063 1.00 0.00 H \nATOM 2761 HB3 GLU A 250 -44.157 8.374 37.557 1.00 0.00 H \nATOM 2762 HG2 GLU A 250 -42.227 7.376 38.238 1.00 0.00 H \nATOM 2763 HG3 GLU A 250 -41.499 8.744 38.413 1.00 0.00 H \nATOM 2764 N ALA A 251 -44.317 11.018 35.236 1.00 0.00 N \nATOM 2765 CA ALA A 251 -45.391 11.482 34.364 1.00 0.00 C \nATOM 2766 C ALA A 251 -45.087 11.206 32.897 1.00 0.00 C \nATOM 2767 O ALA A 251 -46.013 11.024 32.097 1.00 0.00 O \nATOM 2768 CB ALA A 251 -45.641 12.973 34.583 1.00 0.00 C \nATOM 2769 H ALA A 251 -43.897 11.639 35.657 1.00 0.00 H \nATOM 2770 HA ALA A 251 -46.193 10.987 34.595 1.00 0.00 H \nATOM 2771 HB1 ALA A 251 -46.356 13.271 33.999 1.00 0.00 H \nATOM 2772 HB2 ALA A 251 -45.894 13.127 35.507 1.00 0.00 H \nATOM 2773 HB3 ALA A 251 -44.832 13.470 34.382 1.00 0.00 H \nATOM 2774 N GLN A 252 -43.809 11.167 32.526 1.00 0.00 N \nATOM 2775 CA GLN A 252 -43.400 10.824 31.172 1.00 0.00 C \nATOM 2776 C GLN A 252 -43.267 9.323 30.968 1.00 0.00 C \nATOM 2777 O GLN A 252 -42.725 8.893 29.944 1.00 0.00 O \nATOM 2778 CB GLN A 252 -42.072 11.503 30.826 1.00 0.00 C \nATOM 2779 CG GLN A 252 -42.024 12.995 31.092 1.00 0.00 C \nATOM 2780 CD GLN A 252 -40.635 13.569 30.887 1.00 0.00 C \nATOM 2781 OE1 GLN A 252 -39.760 13.428 31.742 1.00 0.00 O \nATOM 2782 NE2 GLN A 252 -40.424 14.215 29.745 1.00 0.00 N \nATOM 2783 H GLN A 252 -43.155 11.340 33.057 1.00 0.00 H \nATOM 2784 HA GLN A 252 -44.099 11.144 30.580 1.00 0.00 H \nATOM 2785 HB2 GLN A 252 -41.364 11.075 31.333 1.00 0.00 H \nATOM 2786 HB3 GLN A 252 -41.881 11.350 29.887 1.00 0.00 H \nATOM 2787 HG2 GLN A 252 -42.649 13.447 30.504 1.00 0.00 H \nATOM 2788 HG3 GLN A 252 -42.313 13.169 32.001 1.00 0.00 H \nATOM 2789 HE21 GLN A 252 -41.060 14.293 29.171 1.00 0.00 H \nATOM 2790 HE22 GLN A 252 -39.651 14.555 29.580 1.00 0.00 H \nATOM 2791 N GLY A 253 -43.744 8.519 31.915 1.00 0.00 N \nATOM 2792 CA GLY A 253 -43.622 7.081 31.833 1.00 0.00 C \nATOM 2793 C GLY A 253 -42.300 6.521 32.309 1.00 0.00 C \nATOM 2794 O GLY A 253 -42.089 5.305 32.203 1.00 0.00 O \nATOM 2795 H GLY A 253 -44.147 8.799 32.621 1.00 0.00 H \nATOM 2796 HA2 GLY A 253 -44.334 6.680 32.355 1.00 0.00 H \nATOM 2797 HA3 GLY A 253 -43.759 6.811 30.912 1.00 0.00 H \nATOM 2798 N GLY A 254 -41.405 7.360 32.830 1.00 0.00 N \nATOM 2799 CA GLY A 254 -40.137 6.895 33.344 1.00 0.00 C \nATOM 2800 C GLY A 254 -40.248 6.336 34.748 1.00 0.00 C \nATOM 2801 O GLY A 254 -41.325 6.224 35.332 1.00 0.00 O \nATOM 2802 H GLY A 254 -41.523 8.210 32.892 1.00 0.00 H \nATOM 2803 HA2 GLY A 254 -39.784 6.211 32.754 1.00 0.00 H \nATOM 2804 HA3 GLY A 254 -39.502 7.628 33.341 1.00 0.00 H \nATOM 2805 N LYS A 255 -39.091 5.980 35.300 1.00 0.00 N \nATOM 2806 CA LYS A 255 -39.011 5.408 36.636 1.00 0.00 C \nATOM 2807 C LYS A 255 -37.777 5.940 37.348 1.00 0.00 C \nATOM 2808 O LYS A 255 -36.733 6.165 36.729 1.00 0.00 O \nATOM 2809 CB LYS A 255 -38.956 3.873 36.599 1.00 0.00 C \nATOM 2810 CG LYS A 255 -40.223 3.198 36.104 1.00 0.00 C \nATOM 2811 CD LYS A 255 -39.936 1.765 35.691 1.00 0.00 C \nATOM 2812 CE LYS A 255 -40.529 0.760 36.659 1.00 0.00 C \nATOM 2813 NZ LYS A 255 -42.012 0.694 36.546 1.00 0.00 N \nATOM 2814 H LYS A 255 -38.330 6.064 34.908 1.00 0.00 H \nATOM 2815 HA LYS A 255 -39.813 5.667 37.116 1.00 0.00 H \nATOM 2816 HB2 LYS A 255 -38.218 3.603 36.030 1.00 0.00 H \nATOM 2817 HB3 LYS A 255 -38.760 3.548 37.492 1.00 0.00 H \nATOM 2818 HG2 LYS A 255 -40.896 3.210 36.802 1.00 0.00 H \nATOM 2819 HG3 LYS A 255 -40.586 3.691 35.351 1.00 0.00 H \nATOM 2820 HD2 LYS A 255 -40.295 1.608 34.804 1.00 0.00 H \nATOM 2821 HD3 LYS A 255 -38.977 1.632 35.636 1.00 0.00 H \nATOM 2822 HE2 LYS A 255 -40.152 -0.117 36.487 1.00 0.00 H \nATOM 2823 HE3 LYS A 255 -40.284 1.001 37.566 1.00 0.00 H \nATOM 2824 HZ1 LYS A 255 -42.310 -0.031 36.967 1.00 0.00 H \nATOM 2825 HZ2 LYS A 255 -42.371 1.420 36.916 1.00 0.00 H \nATOM 2826 HZ3 LYS A 255 -42.243 0.654 35.687 1.00 0.00 H \nATOM 2827 N VAL A 256 -37.911 6.137 38.656 1.00 0.00 N \nATOM 2828 CA VAL A 256 -36.786 6.438 39.533 1.00 0.00 C \nATOM 2829 C VAL A 256 -36.571 5.227 40.427 1.00 0.00 C \nATOM 2830 O VAL A 256 -37.457 4.859 41.208 1.00 0.00 O \nATOM 2831 CB VAL A 256 -37.033 7.707 40.360 1.00 0.00 C \nATOM 2832 CG1 VAL A 256 -36.001 7.824 41.474 1.00 0.00 C \nATOM 2833 CG2 VAL A 256 -37.002 8.936 39.461 1.00 0.00 C \nATOM 2834 H VAL A 256 -38.667 6.099 39.063 1.00 0.00 H \nATOM 2835 HA VAL A 256 -35.991 6.615 39.005 1.00 0.00 H \nATOM 2836 HB VAL A 256 -37.912 7.649 40.767 1.00 0.00 H \nATOM 2837 HG11 VAL A 256 -36.169 8.629 41.988 1.00 0.00 H \nATOM 2838 HG12 VAL A 256 -36.064 7.051 42.056 1.00 0.00 H \nATOM 2839 HG13 VAL A 256 -35.112 7.867 41.089 1.00 0.00 H \nATOM 2840 HG21 VAL A 256 -37.159 9.731 39.994 1.00 0.00 H \nATOM 2841 HG22 VAL A 256 -36.135 9.001 39.032 1.00 0.00 H \nATOM 2842 HG23 VAL A 256 -37.692 8.859 38.784 1.00 0.00 H \nATOM 2843 N ILE A 257 -35.399 4.605 40.309 1.00 0.00 N \nATOM 2844 CA ILE A 257 -35.095 3.351 40.986 1.00 0.00 C \nATOM 2845 C ILE A 257 -33.926 3.564 41.935 1.00 0.00 C \nATOM 2846 O ILE A 257 -32.936 4.211 41.579 1.00 0.00 O \nATOM 2847 CB ILE A 257 -34.773 2.232 39.973 1.00 0.00 C \nATOM 2848 CG1 ILE A 257 -35.881 2.131 38.920 1.00 0.00 C \nATOM 2849 CG2 ILE A 257 -34.565 0.900 40.682 1.00 0.00 C \nATOM 2850 CD1 ILE A 257 -35.519 1.262 37.739 1.00 0.00 C \nATOM 2851 H ILE A 257 -34.752 4.905 39.828 1.00 0.00 H \nATOM 2852 HA ILE A 257 -35.875 3.071 41.490 1.00 0.00 H \nATOM 2853 HB ILE A 257 -33.945 2.456 39.521 1.00 0.00 H \nATOM 2854 HG12 ILE A 257 -36.682 1.778 39.338 1.00 0.00 H \nATOM 2855 HG13 ILE A 257 -36.096 3.022 38.602 1.00 0.00 H \nATOM 2856 HG21 ILE A 257 -34.364 0.213 40.028 1.00 0.00 H \nATOM 2857 HG22 ILE A 257 -33.826 0.977 41.306 1.00 0.00 H \nATOM 2858 HG23 ILE A 257 -35.372 0.661 41.165 1.00 0.00 H \nATOM 2859 HD11 ILE A 257 -36.260 1.241 37.113 1.00 0.00 H \nATOM 2860 HD12 ILE A 257 -34.735 1.625 37.298 1.00 0.00 H \nATOM 2861 HD13 ILE A 257 -35.330 0.361 38.046 1.00 0.00 H \nATOM 2862 N GLN A 258 -34.045 3.023 43.146 1.00 0.00 N \nATOM 2863 CA GLN A 258 -32.929 2.999 44.083 1.00 0.00 C \nATOM 2864 C GLN A 258 -32.007 1.837 43.729 1.00 0.00 C \nATOM 2865 O GLN A 258 -32.406 0.670 43.810 1.00 0.00 O \nATOM 2866 CB GLN A 258 -33.418 2.875 45.525 1.00 0.00 C \nATOM 2867 CG GLN A 258 -32.298 2.572 46.513 1.00 0.00 C \nATOM 2868 CD GLN A 258 -32.665 2.900 47.945 1.00 0.00 C \nATOM 2869 OE1 GLN A 258 -33.685 2.439 48.458 1.00 0.00 O \nATOM 2870 NE2 GLN A 258 -31.829 3.697 48.603 1.00 0.00 N \nATOM 2871 H GLN A 258 -34.768 2.664 43.443 1.00 0.00 H \nATOM 2872 HA GLN A 258 -32.442 3.835 44.013 1.00 0.00 H \nATOM 2873 HB2 GLN A 258 -33.856 3.701 45.784 1.00 0.00 H \nATOM 2874 HB3 GLN A 258 -34.085 2.172 45.575 1.00 0.00 H \nATOM 2875 HG2 GLN A 258 -32.065 1.632 46.452 1.00 0.00 H \nATOM 2876 HG3 GLN A 258 -31.508 3.077 46.263 1.00 0.00 H \nATOM 2877 HE21 GLN A 258 -31.126 4.000 48.211 1.00 0.00 H \nATOM 2878 HE22 GLN A 258 -31.991 3.910 49.420 1.00 0.00 H \nATOM 2879 N TRP A 259 -30.777 2.158 43.335 1.00 0.00 N \nATOM 2880 CA TRP A 259 -29.817 1.157 42.866 1.00 0.00 C \nATOM 2881 C TRP A 259 -28.430 1.749 43.120 1.00 0.00 C \nATOM 2882 O TRP A 259 -27.877 2.447 42.266 1.00 0.00 O \nATOM 2883 CB TRP A 259 -30.034 0.819 41.398 1.00 0.00 C \nATOM 2884 CG TRP A 259 -29.547 -0.546 41.003 1.00 0.00 C \nATOM 2885 CD1 TRP A 259 -28.250 -0.933 40.817 1.00 0.00 C \nATOM 2886 CD2 TRP A 259 -30.350 -1.705 40.740 1.00 0.00 C \nATOM 2887 NE1 TRP A 259 -28.196 -2.259 40.460 1.00 0.00 N \nATOM 2888 CE2 TRP A 259 -29.471 -2.756 40.405 1.00 0.00 C \nATOM 2889 CE3 TRP A 259 -31.725 -1.957 40.758 1.00 0.00 C \nATOM 2890 CZ2 TRP A 259 -29.923 -4.036 40.091 1.00 0.00 C \nATOM 2891 CZ3 TRP A 259 -32.172 -3.229 40.444 1.00 0.00 C \nATOM 2892 CH2 TRP A 259 -31.273 -4.253 40.117 1.00 0.00 C \nATOM 2893 H TRP A 259 -30.474 2.963 43.332 1.00 0.00 H \nATOM 2894 HA TRP A 259 -29.925 0.317 43.339 1.00 0.00 H \nATOM 2895 HB2 TRP A 259 -30.981 0.884 41.198 1.00 0.00 H \nATOM 2896 HB3 TRP A 259 -29.583 1.483 40.853 1.00 0.00 H \nATOM 2897 HD1 TRP A 259 -27.510 -0.379 40.918 1.00 0.00 H \nATOM 2898 HE1 TRP A 259 -27.478 -2.704 40.298 1.00 0.00 H \nATOM 2899 HE3 TRP A 259 -32.328 -1.283 40.977 1.00 0.00 H \nATOM 2900 HZ2 TRP A 259 -29.329 -4.717 39.872 1.00 0.00 H \nATOM 2901 HZ3 TRP A 259 -33.085 -3.407 40.450 1.00 0.00 H \nATOM 2902 HH2 TRP A 259 -31.602 -5.099 39.913 1.00 0.00 H \nATOM 2903 N ASN A 260 -27.877 1.440 44.296 1.00 0.00 N \nATOM 2904 CA ASN A 260 -26.849 2.268 44.920 1.00 0.00 C \nATOM 2905 C ASN A 260 -27.192 3.744 44.766 1.00 0.00 C \nATOM 2906 O ASN A 260 -26.533 4.473 44.016 1.00 0.00 O \nATOM 2907 CB ASN A 260 -25.470 1.967 44.325 1.00 0.00 C \nATOM 2908 CG ASN A 260 -25.194 0.481 44.218 1.00 0.00 C \nATOM 2909 OD1 ASN A 260 -25.751 -0.320 44.968 1.00 0.00 O \nATOM 2910 ND2 ASN A 260 -24.320 0.105 43.291 1.00 0.00 N \nATOM 2911 H ASN A 260 -28.090 0.743 44.752 1.00 0.00 H \nATOM 2912 HA ASN A 260 -26.819 2.056 45.866 1.00 0.00 H \nATOM 2913 HB2 ASN A 260 -25.407 2.369 43.444 1.00 0.00 H \nATOM 2914 HB3 ASN A 260 -24.787 2.381 44.875 1.00 0.00 H \nATOM 2915 HD21 ASN A 260 -24.124 -0.727 43.197 1.00 0.00 H \nATOM 2916 HD22 ASN A 260 -23.950 0.694 42.785 1.00 0.00 H \nATOM 2917 N GLY A 261 -28.225 4.184 45.472 1.00 0.00 N \nATOM 2918 CA GLY A 261 -28.743 5.529 45.360 1.00 0.00 C \nATOM 2919 C GLY A 261 -29.894 5.616 44.370 1.00 0.00 C \nATOM 2920 O GLY A 261 -30.080 4.762 43.500 1.00 0.00 O \nATOM 2921 H GLY A 261 -28.649 3.696 46.039 1.00 0.00 H \nATOM 2922 HA2 GLY A 261 -29.043 5.833 46.231 1.00 0.00 H \nATOM 2923 HA3 GLY A 261 -28.032 6.126 45.081 1.00 0.00 H \nATOM 2924 N TYR A 262 -30.688 6.674 44.515 1.00 0.00 N \nATOM 2925 CA TYR A 262 -31.820 6.898 43.627 1.00 0.00 C \nATOM 2926 C TYR A 262 -31.333 7.404 42.276 1.00 0.00 C \nATOM 2927 O TYR A 262 -30.582 8.382 42.202 1.00 0.00 O \nATOM 2928 CB TYR A 262 -32.799 7.886 44.258 1.00 0.00 C \nATOM 2929 CG TYR A 262 -33.638 7.245 45.335 1.00 0.00 C \nATOM 2930 CD1 TYR A 262 -34.789 6.539 45.014 1.00 0.00 C \nATOM 2931 CD2 TYR A 262 -33.263 7.317 46.669 1.00 0.00 C \nATOM 2932 CE1 TYR A 262 -35.556 5.942 45.994 1.00 0.00 C \nATOM 2933 CE2 TYR A 262 -34.023 6.721 47.658 1.00 0.00 C \nATOM 2934 CZ TYR A 262 -35.169 6.033 47.314 1.00 0.00 C \nATOM 2935 OH TYR A 262 -35.931 5.435 48.290 1.00 0.00 O \nATOM 2936 H TYR A 262 -30.586 7.274 45.123 1.00 0.00 H \nATOM 2937 HA TYR A 262 -32.285 6.058 43.489 1.00 0.00 H \nATOM 2938 HB2 TYR A 262 -32.306 8.632 44.635 1.00 0.00 H \nATOM 2939 HB3 TYR A 262 -33.379 8.248 43.570 1.00 0.00 H \nATOM 2940 HD1 TYR A 262 -35.048 6.467 44.124 1.00 0.00 H \nATOM 2941 HD2 TYR A 262 -32.487 7.774 46.902 1.00 0.00 H \nATOM 2942 HE1 TYR A 262 -36.330 5.481 45.765 1.00 0.00 H \nATOM 2943 HE2 TYR A 262 -33.764 6.783 48.549 1.00 0.00 H \nATOM 2944 HH TYR A 262 -35.532 5.486 49.028 1.00 0.00 H \nATOM 2945 N ARG A 263 -31.764 6.735 41.206 1.00 0.00 N \nATOM 2946 CA ARG A 263 -31.259 7.012 39.871 1.00 0.00 C \nATOM 2947 C ARG A 263 -32.382 6.937 38.848 1.00 0.00 C \nATOM 2948 O ARG A 263 -33.294 6.115 38.972 1.00 0.00 O \nATOM 2949 CB ARG A 263 -30.144 6.034 39.484 1.00 0.00 C \nATOM 2950 CG ARG A 263 -28.913 6.099 40.374 1.00 0.00 C \nATOM 2951 CD ARG A 263 -28.002 4.911 40.131 1.00 0.00 C \nATOM 2952 NE ARG A 263 -26.877 4.885 41.060 1.00 0.00 N \nATOM 2953 CZ ARG A 263 -25.692 5.434 40.817 1.00 0.00 C \nATOM 2954 NH1 ARG A 263 -25.470 6.057 39.669 1.00 0.00 N \nATOM 2955 NH2 ARG A 263 -24.729 5.362 41.724 1.00 0.00 N \nATOM 2956 H ARG A 263 -32.355 6.111 41.238 1.00 0.00 H \nATOM 2957 HA ARG A 263 -30.893 7.910 39.878 1.00 0.00 H \nATOM 2958 HB2 ARG A 263 -30.498 5.131 39.507 1.00 0.00 H \nATOM 2959 HB3 ARG A 263 -29.877 6.211 38.568 1.00 0.00 H \nATOM 2960 HG2 ARG A 263 -28.429 6.922 40.203 1.00 0.00 H \nATOM 2961 HG3 ARG A 263 -29.184 6.118 41.305 1.00 0.00 H \nATOM 2962 HD2 ARG A 263 -28.512 4.090 40.219 1.00 0.00 H \nATOM 2963 HD3 ARG A 263 -27.668 4.942 39.221 1.00 0.00 H \nATOM 2964 HE ARG A 263 -26.989 4.488 41.815 1.00 0.00 H \nATOM 2965 HH11 ARG A 263 -26.094 6.107 39.079 1.00 0.00 H \nATOM 2966 HH12 ARG A 263 -24.702 6.412 39.514 1.00 0.00 H \nATOM 2967 HH21 ARG A 263 -24.871 4.960 42.471 1.00 0.00 H \nATOM 2968 HH22 ARG A 263 -23.962 5.718 41.566 1.00 0.00 H \nATOM 2969 N VAL A 264 -32.313 7.812 37.844 1.00 0.00 N \nATOM 2970 CA VAL A 264 -33.214 7.718 36.701 1.00 0.00 C \nATOM 2971 C VAL A 264 -32.942 6.411 35.972 1.00 0.00 C \nATOM 2972 O VAL A 264 -31.801 6.130 35.583 1.00 0.00 O \nATOM 2973 CB VAL A 264 -33.041 8.923 35.775 1.00 0.00 C \nATOM 2974 CG1 VAL A 264 -34.075 8.880 34.666 1.00 0.00 C \nATOM 2975 CG2 VAL A 264 -33.147 10.218 36.570 1.00 0.00 C \nATOM 2976 H VAL A 264 -31.753 8.464 37.808 1.00 0.00 H \nATOM 2977 HA VAL A 264 -34.135 7.725 37.006 1.00 0.00 H \nATOM 2978 HB VAL A 264 -32.160 8.888 35.371 1.00 0.00 H \nATOM 2979 HG11 VAL A 264 -33.958 9.647 34.084 1.00 0.00 H \nATOM 2980 HG12 VAL A 264 -33.965 8.065 34.152 1.00 0.00 H \nATOM 2981 HG13 VAL A 264 -34.965 8.900 35.052 1.00 0.00 H \nATOM 2982 HG21 VAL A 264 -33.036 10.974 35.973 1.00 0.00 H \nATOM 2983 HG22 VAL A 264 -34.018 10.267 36.995 1.00 0.00 H \nATOM 2984 HG23 VAL A 264 -32.455 10.238 37.249 1.00 0.00 H \nATOM 2985 N SER A 265 -33.988 5.603 35.792 1.00 0.00 N \nATOM 2986 CA SER A 265 -33.884 4.266 35.208 1.00 0.00 C \nATOM 2987 C SER A 265 -32.932 3.371 35.994 1.00 0.00 C \nATOM 2988 O SER A 265 -32.461 2.355 35.476 1.00 0.00 O \nATOM 2989 CB SER A 265 -33.451 4.323 33.737 1.00 0.00 C \nATOM 2990 OG SER A 265 -34.129 5.353 33.042 1.00 0.00 O \nATOM 2991 H SER A 265 -34.791 5.821 36.010 1.00 0.00 H \nATOM 2992 HA SER A 265 -34.772 3.879 35.255 1.00 0.00 H \nATOM 2993 HB2 SER A 265 -32.494 4.470 33.685 1.00 0.00 H \nATOM 2994 HB3 SER A 265 -33.630 3.470 33.311 1.00 0.00 H \nATOM 2995 HG SER A 265 -34.919 5.113 32.886 1.00 0.00 H \nATOM 2996 N GLY A 266 -32.638 3.732 37.241 1.00 0.00 N \nATOM 2997 CA GLY A 266 -31.649 3.011 38.015 1.00 0.00 C \nATOM 2998 C GLY A 266 -30.219 3.242 37.588 1.00 0.00 C \nATOM 2999 O GLY A 266 -29.319 2.579 38.110 1.00 0.00 O \nATOM 3000 H GLY A 266 -33.004 4.393 37.652 1.00 0.00 H \nATOM 3001 HA2 GLY A 266 -31.740 3.263 38.947 1.00 0.00 H \nATOM 3002 HA3 GLY A 266 -31.841 2.062 37.958 1.00 0.00 H \nATOM 3003 N ILE A 267 -29.979 4.164 36.656 1.00 0.00 N \nATOM 3004 CA ILE A 267 -28.659 4.377 36.066 1.00 0.00 C \nATOM 3005 C ILE A 267 -28.021 5.673 36.567 1.00 0.00 C \nATOM 3006 O ILE A 267 -26.971 5.648 37.209 1.00 0.00 O \nATOM 3007 CB ILE A 267 -28.735 4.354 34.524 1.00 0.00 C \nATOM 3008 CG1 ILE A 267 -29.156 2.969 34.033 1.00 0.00 C \nATOM 3009 CG2 ILE A 267 -27.398 4.742 33.931 1.00 0.00 C \nATOM 3010 CD1 ILE A 267 -29.657 2.957 32.608 1.00 0.00 C \nATOM 3011 H ILE A 267 -30.585 4.689 36.346 1.00 0.00 H \nATOM 3012 HA ILE A 267 -28.089 3.645 36.351 1.00 0.00 H \nATOM 3013 HB ILE A 267 -29.401 4.997 34.235 1.00 0.00 H \nATOM 3014 HG12 ILE A 267 -28.401 2.365 34.107 1.00 0.00 H \nATOM 3015 HG13 ILE A 267 -29.852 2.626 34.615 1.00 0.00 H \nATOM 3016 HG21 ILE A 267 -27.456 4.725 32.963 1.00 0.00 H \nATOM 3017 HG22 ILE A 267 -27.161 5.636 34.224 1.00 0.00 H \nATOM 3018 HG23 ILE A 267 -26.719 4.115 34.225 1.00 0.00 H \nATOM 3019 HD11 ILE A 267 -29.906 2.053 32.360 1.00 0.00 H \nATOM 3020 HD12 ILE A 267 -30.430 3.538 32.532 1.00 0.00 H \nATOM 3021 HD13 ILE A 267 -28.957 3.273 32.016 1.00 0.00 H \nATOM 3022 N LEU A 268 -28.634 6.814 36.267 1.00 0.00 N \nATOM 3023 CA LEU A 268 -28.014 8.116 36.481 1.00 0.00 C \nATOM 3024 C LEU A 268 -28.519 8.748 37.769 1.00 0.00 C \nATOM 3025 O LEU A 268 -29.731 8.878 37.970 1.00 0.00 O \nATOM 3026 CB LEU A 268 -28.287 9.052 35.306 1.00 0.00 C \nATOM 3027 CG LEU A 268 -27.397 10.295 35.263 1.00 0.00 C \nATOM 3028 CD1 LEU A 268 -25.933 9.897 35.125 1.00 0.00 C \nATOM 3029 CD2 LEU A 268 -27.819 11.219 34.125 1.00 0.00 C \nATOM 3030 H LEU A 268 -29.425 6.854 35.932 1.00 0.00 H \nATOM 3031 HA LEU A 268 -27.057 7.977 36.552 1.00 0.00 H \nATOM 3032 HB2 LEU A 268 -28.172 8.557 34.480 1.00 0.00 H \nATOM 3033 HB3 LEU A 268 -29.215 9.334 35.341 1.00 0.00 H \nATOM 3034 HG LEU A 268 -27.503 10.778 36.097 1.00 0.00 H \nATOM 3035 HD11 LEU A 268 -25.382 10.695 35.099 1.00 0.00 H \nATOM 3036 HD12 LEU A 268 -25.674 9.350 35.883 1.00 0.00 H \nATOM 3037 HD13 LEU A 268 -25.810 9.393 34.305 1.00 0.00 H \nATOM 3038 HD21 LEU A 268 -27.245 12.001 34.113 1.00 0.00 H \nATOM 3039 HD22 LEU A 268 -27.742 10.748 33.280 1.00 0.00 H \nATOM 3040 HD23 LEU A 268 -28.739 11.496 34.257 1.00 0.00 H \nATOM 3041 N ALA A 269 -27.585 9.175 38.617 1.00 0.00 N \nATOM 3042 CA ALA A 269 -27.889 9.777 39.908 1.00 0.00 C \nATOM 3043 C ALA A 269 -28.280 11.247 39.803 1.00 0.00 C \nATOM 3044 O ALA A 269 -28.153 11.980 40.792 1.00 0.00 O \nATOM 3045 CB ALA A 269 -26.694 9.624 40.852 1.00 0.00 C \nATOM 3046 H ALA A 269 -26.743 9.121 38.453 1.00 0.00 H \nATOM 3047 HA ALA A 269 -28.658 9.304 40.263 1.00 0.00 H \nATOM 3048 HB1 ALA A 269 -26.904 10.027 41.709 1.00 0.00 H \nATOM 3049 HB2 ALA A 269 -26.499 8.682 40.978 1.00 0.00 H \nATOM 3050 HB3 ALA A 269 -25.920 10.066 40.469 1.00 0.00 H \nATOM 3051 N MET A 270 -28.737 11.698 38.636 1.00 0.00 N \nATOM 3052 CA MET A 270 -29.218 13.060 38.456 1.00 0.00 C \nATOM 3053 C MET A 270 -30.410 13.049 37.511 1.00 0.00 C \nATOM 3054 O MET A 270 -30.509 12.196 36.626 1.00 0.00 O \nATOM 3055 CB MET A 270 -28.137 13.990 37.877 1.00 0.00 C \nATOM 3056 CG MET A 270 -26.728 13.762 38.391 1.00 0.00 C \nATOM 3057 SD MET A 270 -25.486 14.100 37.133 1.00 0.00 S \nATOM 3058 CE MET A 270 -26.103 15.635 36.462 1.00 0.00 C \nATOM 3059 H MET A 270 -28.776 11.217 37.924 1.00 0.00 H \nATOM 3060 HA MET A 270 -29.467 13.399 39.330 1.00 0.00 H \nATOM 3061 HB2 MET A 270 -28.131 13.891 36.912 1.00 0.00 H \nATOM 3062 HB3 MET A 270 -28.388 14.908 38.066 1.00 0.00 H \nATOM 3063 HG2 MET A 270 -26.570 14.330 39.161 1.00 0.00 H \nATOM 3064 HG3 MET A 270 -26.640 12.844 38.693 1.00 0.00 H \nATOM 3065 HE1 MET A 270 -25.513 15.940 35.755 1.00 0.00 H \nATOM 3066 HE2 MET A 270 -26.993 15.497 36.103 1.00 0.00 H \nATOM 3067 HE3 MET A 270 -26.138 16.304 37.163 1.00 0.00 H \nATOM 3068 N SER A 271 -31.317 14.007 37.708 1.00 0.00 N \nATOM 3069 CA SER A 271 -32.493 14.144 36.861 1.00 0.00 C \nATOM 3070 C SER A 271 -32.345 15.245 35.821 1.00 0.00 C \nATOM 3071 O SER A 271 -33.219 15.386 34.961 1.00 0.00 O \nATOM 3072 CB SER A 271 -33.734 14.415 37.716 1.00 0.00 C \nATOM 3073 OG SER A 271 -33.573 15.589 38.497 1.00 0.00 O \nATOM 3074 H SER A 271 -31.265 14.592 38.336 1.00 0.00 H \nATOM 3075 HA SER A 271 -32.592 13.304 36.385 1.00 0.00 H \nATOM 3076 HB2 SER A 271 -34.511 14.509 37.143 1.00 0.00 H \nATOM 3077 HB3 SER A 271 -33.901 13.657 38.298 1.00 0.00 H \nATOM 3078 HG SER A 271 -32.848 15.548 38.919 1.00 0.00 H \nATOM 3079 N ARG A 272 -31.261 16.016 35.874 1.00 0.00 N \nATOM 3080 CA ARG A 272 -31.014 17.120 34.958 1.00 0.00 C \nATOM 3081 C ARG A 272 -29.531 17.139 34.625 1.00 0.00 C \nATOM 3082 O ARG A 272 -28.696 16.975 35.516 1.00 0.00 O \nATOM 3083 CB ARG A 272 -31.403 18.475 35.570 1.00 0.00 C \nATOM 3084 CG ARG A 272 -32.733 18.501 36.300 1.00 0.00 C \nATOM 3085 CD ARG A 272 -33.444 19.828 36.099 1.00 0.00 C \nATOM 3086 NE ARG A 272 -34.714 19.880 36.819 1.00 0.00 N \nATOM 3087 CZ ARG A 272 -35.356 21.003 37.120 1.00 0.00 C \nATOM 3088 NH1 ARG A 272 -34.853 22.175 36.757 1.00 0.00 N \nATOM 3089 NH2 ARG A 272 -36.505 20.953 37.778 1.00 0.00 N \nATOM 3090 H ARG A 272 -30.638 15.907 36.456 1.00 0.00 H \nATOM 3091 HA ARG A 272 -31.556 16.987 34.165 1.00 0.00 H \nATOM 3092 HB2 ARG A 272 -30.706 18.745 36.188 1.00 0.00 H \nATOM 3093 HB3 ARG A 272 -31.427 19.138 34.862 1.00 0.00 H \nATOM 3094 HG2 ARG A 272 -33.295 17.778 35.979 1.00 0.00 H \nATOM 3095 HG3 ARG A 272 -32.588 18.349 37.247 1.00 0.00 H \nATOM 3096 HD2 ARG A 272 -32.871 20.550 36.401 1.00 0.00 H \nATOM 3097 HD3 ARG A 272 -33.603 19.969 35.153 1.00 0.00 H \nATOM 3098 HE ARG A 272 -35.069 19.136 37.064 1.00 0.00 H \nATOM 3099 HH11 ARG A 272 -34.110 22.209 36.326 1.00 0.00 H \nATOM 3100 HH12 ARG A 272 -35.270 22.901 36.953 1.00 0.00 H \nATOM 3101 HH21 ARG A 272 -36.835 20.193 38.010 1.00 0.00 H \nATOM 3102 HH22 ARG A 272 -36.921 21.680 37.973 1.00 0.00 H \nATOM 3103 N SER A 273 -29.197 17.378 33.362 1.00 0.00 N \nATOM 3104 CA SER A 273 -27.799 17.430 32.945 1.00 0.00 C \nATOM 3105 C SER A 273 -27.718 17.954 31.517 1.00 0.00 C \nATOM 3106 O SER A 273 -28.732 18.164 30.845 1.00 0.00 O \nATOM 3107 CB SER A 273 -27.133 16.054 33.031 1.00 0.00 C \nATOM 3108 OG SER A 273 -27.191 15.392 31.780 1.00 0.00 O \nATOM 3109 H SER A 273 -29.764 17.513 32.730 1.00 0.00 H \nATOM 3110 HA SER A 273 -27.325 18.026 33.546 1.00 0.00 H \nATOM 3111 HB2 SER A 273 -26.208 16.153 33.307 1.00 0.00 H \nATOM 3112 HB3 SER A 273 -27.575 15.517 33.707 1.00 0.00 H \nATOM 3113 HG SER A 273 -27.984 15.169 31.618 1.00 0.00 H \nATOM 3114 N ILE A 274 -26.482 18.172 31.070 1.00 0.00 N \nATOM 3115 CA ILE A 274 -26.172 18.445 29.672 1.00 0.00 C \nATOM 3116 C ILE A 274 -25.645 17.158 29.054 1.00 0.00 C \nATOM 3117 O ILE A 274 -24.738 16.524 29.608 1.00 0.00 O \nATOM 3118 CB ILE A 274 -25.145 19.583 29.539 1.00 0.00 C \nATOM 3119 CG1 ILE A 274 -25.604 20.820 30.316 1.00 0.00 C \nATOM 3120 CG2 ILE A 274 -24.906 19.924 28.076 1.00 0.00 C \nATOM 3121 CD1 ILE A 274 -26.937 21.366 29.864 1.00 0.00 C \nATOM 3122 H ILE A 274 -25.790 18.165 31.581 1.00 0.00 H \nATOM 3123 HA ILE A 274 -26.971 18.738 29.207 1.00 0.00 H \nATOM 3124 HB ILE A 274 -24.306 19.280 29.920 1.00 0.00 H \nATOM 3125 HG12 ILE A 274 -25.658 20.597 31.259 1.00 0.00 H \nATOM 3126 HG13 ILE A 274 -24.933 21.515 30.227 1.00 0.00 H \nATOM 3127 HG21 ILE A 274 -24.257 20.642 28.013 1.00 0.00 H \nATOM 3128 HG22 ILE A 274 -24.568 19.142 27.612 1.00 0.00 H \nATOM 3129 HG23 ILE A 274 -25.740 20.206 27.669 1.00 0.00 H \nATOM 3130 HD11 ILE A 274 -27.165 22.145 30.396 1.00 0.00 H \nATOM 3131 HD12 ILE A 274 -26.883 21.618 28.929 1.00 0.00 H \nATOM 3132 HD13 ILE A 274 -27.620 20.687 29.977 1.00 0.00 H \nATOM 3133 N GLY A 275 -26.205 16.767 27.909 1.00 0.00 N \nATOM 3134 CA GLY A 275 -25.807 15.524 27.272 1.00 0.00 C \nATOM 3135 C GLY A 275 -26.686 14.342 27.641 1.00 0.00 C \nATOM 3136 O GLY A 275 -27.900 14.497 27.804 1.00 0.00 O \nATOM 3137 H GLY A 275 -26.813 17.208 27.491 1.00 0.00 H \nATOM 3138 HA2 GLY A 275 -25.825 15.643 26.309 1.00 0.00 H \nATOM 3139 HA3 GLY A 275 -24.890 15.324 27.516 1.00 0.00 H \nATOM 3140 N ASP A 276 -26.076 13.164 27.790 1.00 0.00 N \nATOM 3141 CA ASP A 276 -26.773 11.917 28.123 1.00 0.00 C \nATOM 3142 C ASP A 276 -28.035 11.726 27.283 1.00 0.00 C \nATOM 3143 O ASP A 276 -29.139 11.546 27.803 1.00 0.00 O \nATOM 3144 CB ASP A 276 -27.113 11.864 29.611 1.00 0.00 C \nATOM 3145 CG ASP A 276 -25.924 12.165 30.498 1.00 0.00 C \nATOM 3146 OD1 ASP A 276 -25.029 11.302 30.612 1.00 0.00 O \nATOM 3147 OD2 ASP A 276 -25.891 13.261 31.096 1.00 0.00 O \nATOM 3148 H ASP A 276 -25.227 13.065 27.698 1.00 0.00 H \nATOM 3149 HA ASP A 276 -26.168 11.188 27.914 1.00 0.00 H \nATOM 3150 HB2 ASP A 276 -27.820 12.500 29.799 1.00 0.00 H \nATOM 3151 HB3 ASP A 276 -27.458 10.984 29.828 1.00 0.00 H \nATOM 3152 N ARG A 277 -27.867 11.767 25.958 1.00 0.00 N \nATOM 3153 CA ARG A 277 -29.024 11.659 25.075 1.00 0.00 C \nATOM 3154 C ARG A 277 -29.725 10.307 25.174 1.00 0.00 C \nATOM 3155 O ARG A 277 -30.876 10.192 24.749 1.00 0.00 O \nATOM 3156 CB ARG A 277 -28.629 11.947 23.623 1.00 0.00 C \nATOM 3157 CG ARG A 277 -27.638 10.984 23.001 1.00 0.00 C \nATOM 3158 CD ARG A 277 -27.379 11.384 21.556 1.00 0.00 C \nATOM 3159 NE ARG A 277 -26.241 10.692 20.962 1.00 0.00 N \nATOM 3160 CZ ARG A 277 -24.975 11.053 21.134 1.00 0.00 C \nATOM 3161 NH1 ARG A 277 -24.680 12.097 21.895 1.00 0.00 N \nATOM 3162 NH2 ARG A 277 -24.000 10.366 20.552 1.00 0.00 N \nATOM 3163 H ARG A 277 -27.109 11.855 25.561 1.00 0.00 H \nATOM 3164 HA ARG A 277 -29.659 12.329 25.373 1.00 0.00 H \nATOM 3165 HB2 ARG A 277 -29.434 11.949 23.082 1.00 0.00 H \nATOM 3166 HB3 ARG A 277 -28.255 12.841 23.579 1.00 0.00 H \nATOM 3167 HG2 ARG A 277 -26.808 10.991 23.502 1.00 0.00 H \nATOM 3168 HG3 ARG A 277 -27.985 10.079 23.039 1.00 0.00 H \nATOM 3169 HD2 ARG A 277 -28.172 11.201 21.029 1.00 0.00 H \nATOM 3170 HD3 ARG A 277 -27.226 12.341 21.514 1.00 0.00 H \nATOM 3171 HE ARG A 277 -26.400 10.006 20.469 1.00 0.00 H \nATOM 3172 HH11 ARG A 277 -25.309 12.541 22.278 1.00 0.00 H \nATOM 3173 HH12 ARG A 277 -23.860 12.330 22.006 1.00 0.00 H \nATOM 3174 HH21 ARG A 277 -24.187 9.685 20.062 1.00 0.00 H \nATOM 3175 HH22 ARG A 277 -23.181 10.602 20.665 1.00 0.00 H \nATOM 3176 N TYR A 278 -29.062 9.272 25.691 1.00 0.00 N \nATOM 3177 CA TYR A 278 -29.730 7.978 25.812 1.00 0.00 C \nATOM 3178 C TYR A 278 -30.751 7.915 26.948 1.00 0.00 C \nATOM 3179 O TYR A 278 -31.527 6.954 26.998 1.00 0.00 O \nATOM 3180 CB TYR A 278 -28.692 6.861 25.963 1.00 0.00 C \nATOM 3181 CG TYR A 278 -28.151 6.659 27.366 1.00 0.00 C \nATOM 3182 CD1 TYR A 278 -27.346 7.618 27.973 1.00 0.00 C \nATOM 3183 CD2 TYR A 278 -28.414 5.488 28.071 1.00 0.00 C \nATOM 3184 CE1 TYR A 278 -26.841 7.427 29.250 1.00 0.00 C \nATOM 3185 CE2 TYR A 278 -27.910 5.290 29.349 1.00 0.00 C \nATOM 3186 CZ TYR A 278 -27.125 6.262 29.930 1.00 0.00 C \nATOM 3187 OH TYR A 278 -26.617 6.077 31.195 1.00 0.00 O \nATOM 3188 H TYR A 278 -28.249 9.296 25.970 1.00 0.00 H \nATOM 3189 HA TYR A 278 -30.234 7.853 24.993 1.00 0.00 H \nATOM 3190 HB2 TYR A 278 -29.089 6.028 25.663 1.00 0.00 H \nATOM 3191 HB3 TYR A 278 -27.948 7.050 25.370 1.00 0.00 H \nATOM 3192 HD1 TYR A 278 -27.143 8.401 27.514 1.00 0.00 H \nATOM 3193 HD2 TYR A 278 -28.937 4.826 27.679 1.00 0.00 H \nATOM 3194 HE1 TYR A 278 -26.313 8.082 29.646 1.00 0.00 H \nATOM 3195 HE2 TYR A 278 -28.101 4.506 29.811 1.00 0.00 H \nATOM 3196 HH TYR A 278 -26.142 5.385 31.208 1.00 0.00 H \nATOM 3197 N LEU A 279 -30.778 8.905 27.846 1.00 0.00 N \nATOM 3198 CA LEU A 279 -31.681 8.926 28.998 1.00 0.00 C \nATOM 3199 C LEU A 279 -32.795 9.961 28.852 1.00 0.00 C \nATOM 3200 O LEU A 279 -33.380 10.410 29.844 1.00 0.00 O \nATOM 3201 CB LEU A 279 -30.902 9.195 30.277 1.00 0.00 C \nATOM 3202 CG LEU A 279 -30.230 7.958 30.852 1.00 0.00 C \nATOM 3203 CD1 LEU A 279 -29.376 8.348 32.031 1.00 0.00 C \nATOM 3204 CD2 LEU A 279 -31.274 6.924 31.248 1.00 0.00 C \nATOM 3205 H LEU A 279 -30.264 9.593 27.800 1.00 0.00 H \nATOM 3206 HA LEU A 279 -32.097 8.051 29.042 1.00 0.00 H \nATOM 3207 HB2 LEU A 279 -30.226 9.868 30.100 1.00 0.00 H \nATOM 3208 HB3 LEU A 279 -31.504 9.565 30.942 1.00 0.00 H \nATOM 3209 HG LEU A 279 -29.659 7.559 30.177 1.00 0.00 H \nATOM 3210 HD11 LEU A 279 -28.948 7.558 32.396 1.00 0.00 H \nATOM 3211 HD12 LEU A 279 -28.698 8.979 31.745 1.00 0.00 H \nATOM 3212 HD13 LEU A 279 -29.932 8.758 32.712 1.00 0.00 H \nATOM 3213 HD21 LEU A 279 -30.832 6.141 31.613 1.00 0.00 H \nATOM 3214 HD22 LEU A 279 -31.866 7.302 31.917 1.00 0.00 H \nATOM 3215 HD23 LEU A 279 -31.790 6.669 30.467 1.00 0.00 H \nATOM 3216 N LYS A 280 -33.093 10.309 27.656 1.00 0.00 N \nATOM 3217 CA LYS A 280 -34.000 11.236 27.008 1.00 0.00 C \nATOM 3218 C LYS A 280 -35.375 10.571 26.849 1.00 0.00 C \nATOM 3219 O LYS A 280 -35.453 9.430 26.387 1.00 0.00 O \nATOM 3220 CB LYS A 280 -33.341 11.562 25.640 1.00 0.00 C \nATOM 3221 CG LYS A 280 -32.112 12.560 25.597 1.00 0.00 C \nATOM 3222 CD LYS A 280 -32.573 13.982 25.088 1.00 0.00 C \nATOM 3223 CE LYS A 280 -31.827 15.209 25.705 1.00 0.00 C \nATOM 3224 NZ LYS A 280 -30.408 14.953 26.178 1.00 0.00 N \nATOM 3225 H LYS A 280 -32.659 9.907 27.031 1.00 0.00 H \nATOM 3226 HA LYS A 280 -34.146 12.050 27.515 1.00 0.00 H \nATOM 3227 HB2 LYS A 280 -33.051 10.724 25.248 1.00 0.00 H \nATOM 3228 HB3 LYS A 280 -34.031 11.922 25.061 1.00 0.00 H \nATOM 3229 HG2 LYS A 280 -31.720 12.638 26.481 1.00 0.00 H \nATOM 3230 HG3 LYS A 280 -31.423 12.208 25.012 1.00 0.00 H \nATOM 3231 HD2 LYS A 280 -32.464 14.011 24.125 1.00 0.00 H \nATOM 3232 HD3 LYS A 280 -33.521 14.078 25.269 1.00 0.00 H \nATOM 3233 HE2 LYS A 280 -31.806 15.919 25.044 1.00 0.00 H \nATOM 3234 HE3 LYS A 280 -32.346 15.537 26.456 1.00 0.00 H \nATOM 3235 HZ1 LYS A 280 -30.021 15.726 26.390 1.00 0.00 H \nATOM 3236 HZ2 LYS A 280 -30.424 14.424 26.893 1.00 0.00 H \nATOM 3237 HZ3 LYS A 280 -29.945 14.559 25.528 1.00 0.00 H \nATOM 3238 N PRO A 281 -36.487 11.242 27.241 1.00 0.00 N \nATOM 3239 CA PRO A 281 -36.628 12.628 27.680 1.00 0.00 C \nATOM 3240 C PRO A 281 -36.610 12.795 29.200 1.00 0.00 C \nATOM 3241 O PRO A 281 -37.147 13.786 29.681 1.00 0.00 O \nATOM 3242 CB PRO A 281 -38.000 13.000 27.126 1.00 0.00 C \nATOM 3243 CG PRO A 281 -38.795 11.730 27.344 1.00 0.00 C \nATOM 3244 CD PRO A 281 -37.809 10.589 27.150 1.00 0.00 C \nATOM 3245 HA PRO A 281 -35.893 13.182 27.373 1.00 0.00 H \nATOM 3246 HB2 PRO A 281 -38.388 13.754 27.597 1.00 0.00 H \nATOM 3247 HB3 PRO A 281 -37.957 13.243 26.188 1.00 0.00 H \nATOM 3248 HG2 PRO A 281 -39.181 11.709 28.233 1.00 0.00 H \nATOM 3249 HG3 PRO A 281 -39.530 11.666 26.714 1.00 0.00 H \nATOM 3250 HD2 PRO A 281 -37.916 9.907 27.831 1.00 0.00 H \nATOM 3251 HD3 PRO A 281 -37.933 10.154 26.292 1.00 0.00 H \nATOM 3252 N PHE A 282 -36.025 11.846 29.939 1.00 0.00 N \nATOM 3253 CA PHE A 282 -36.114 11.895 31.396 1.00 0.00 C \nATOM 3254 C PHE A 282 -35.091 12.856 31.998 1.00 0.00 C \nATOM 3255 O PHE A 282 -35.397 13.558 32.967 1.00 0.00 O \nATOM 3256 CB PHE A 282 -35.936 10.491 31.983 1.00 0.00 C \nATOM 3257 CG PHE A 282 -36.737 9.436 31.282 1.00 0.00 C \nATOM 3258 CD1 PHE A 282 -38.112 9.550 31.177 1.00 0.00 C \nATOM 3259 CD2 PHE A 282 -36.113 8.338 30.710 1.00 0.00 C \nATOM 3260 CE1 PHE A 282 -38.854 8.585 30.520 1.00 0.00 C \nATOM 3261 CE2 PHE A 282 -36.852 7.369 30.052 1.00 0.00 C \nATOM 3262 CZ PHE A 282 -38.223 7.494 29.957 1.00 0.00 C \nATOM 3263 H PHE A 282 -35.582 11.181 29.622 1.00 0.00 H \nATOM 3264 HA PHE A 282 -36.995 12.229 31.625 1.00 0.00 H \nATOM 3265 HB2 PHE A 282 -34.997 10.251 31.945 1.00 0.00 H \nATOM 3266 HB3 PHE A 282 -36.187 10.507 32.920 1.00 0.00 H \nATOM 3267 HD1 PHE A 282 -38.542 10.284 31.553 1.00 0.00 H \nATOM 3268 HD2 PHE A 282 -35.189 8.251 30.769 1.00 0.00 H \nATOM 3269 HE1 PHE A 282 -39.778 8.671 30.458 1.00 0.00 H \nATOM 3270 HE2 PHE A 282 -36.425 6.634 29.674 1.00 0.00 H \nATOM 3271 HZ PHE A 282 -38.721 6.845 29.515 1.00 0.00 H \nATOM 3272 N VAL A 283 -33.877 12.895 31.457 1.00 0.00 N \nATOM 3273 CA VAL A 283 -32.824 13.788 31.933 1.00 0.00 C \nATOM 3274 C VAL A 283 -32.810 15.006 31.018 1.00 0.00 C \nATOM 3275 O VAL A 283 -32.441 14.905 29.843 1.00 0.00 O \nATOM 3276 CB VAL A 283 -31.458 13.089 31.964 1.00 0.00 C \nATOM 3277 CG1 VAL A 283 -30.372 14.067 32.387 1.00 0.00 C \nATOM 3278 CG2 VAL A 283 -31.495 11.893 32.903 1.00 0.00 C \nATOM 3279 H VAL A 283 -33.639 12.399 30.796 1.00 0.00 H \nATOM 3280 HA VAL A 283 -33.004 14.058 32.847 1.00 0.00 H \nATOM 3281 HB VAL A 283 -31.253 12.771 31.071 1.00 0.00 H \nATOM 3282 HG11 VAL A 283 -29.515 13.613 32.402 1.00 0.00 H \nATOM 3283 HG12 VAL A 283 -30.336 14.803 31.757 1.00 0.00 H \nATOM 3284 HG13 VAL A 283 -30.572 14.410 33.272 1.00 0.00 H \nATOM 3285 HG21 VAL A 283 -30.626 11.462 32.912 1.00 0.00 H \nATOM 3286 HG22 VAL A 283 -31.717 12.191 33.799 1.00 0.00 H \nATOM 3287 HG23 VAL A 283 -32.165 11.262 32.597 1.00 0.00 H \nATOM 3288 N ILE A 284 -33.210 16.158 31.552 1.00 0.00 N \nATOM 3289 CA ILE A 284 -33.406 17.363 30.747 1.00 0.00 C \nATOM 3290 C ILE A 284 -32.317 18.386 31.054 1.00 0.00 C \nATOM 3291 O ILE A 284 -31.698 18.327 32.126 1.00 0.00 O \nATOM 3292 CB ILE A 284 -34.802 17.961 30.988 1.00 0.00 C \nATOM 3293 CG1 ILE A 284 -35.001 18.261 32.476 1.00 0.00 C \nATOM 3294 CG2 ILE A 284 -35.879 17.019 30.481 1.00 0.00 C \nATOM 3295 CD1 ILE A 284 -36.309 18.962 32.786 1.00 0.00 C \nATOM 3296 H ILE A 284 -33.375 16.263 32.389 1.00 0.00 H \nATOM 3297 HA ILE A 284 -33.344 17.120 29.810 1.00 0.00 H \nATOM 3298 HB ILE A 284 -34.872 18.794 30.495 1.00 0.00 H \nATOM 3299 HG12 ILE A 284 -34.963 17.429 32.973 1.00 0.00 H \nATOM 3300 HG13 ILE A 284 -34.266 18.812 32.788 1.00 0.00 H \nATOM 3301 HG21 ILE A 284 -36.752 17.410 30.640 1.00 0.00 H \nATOM 3302 HG22 ILE A 284 -35.759 16.872 29.530 1.00 0.00 H \nATOM 3303 HG23 ILE A 284 -35.815 16.172 30.949 1.00 0.00 H \nATOM 3304 HD11 ILE A 284 -36.372 19.122 33.741 1.00 0.00 H \nATOM 3305 HD12 ILE A 284 -36.342 19.809 32.314 1.00 0.00 H \nATOM 3306 HD13 ILE A 284 -37.050 18.404 32.502 1.00 0.00 H \nATOM 3307 N PRO A 285 -32.042 19.331 30.154 1.00 0.00 N \nATOM 3308 CA PRO A 285 -31.056 20.385 30.435 1.00 0.00 C \nATOM 3309 C PRO A 285 -31.610 21.678 31.019 1.00 0.00 C \nATOM 3310 O PRO A 285 -30.833 22.625 31.195 1.00 0.00 O \nATOM 3311 CB PRO A 285 -30.454 20.641 29.045 1.00 0.00 C \nATOM 3312 CG PRO A 285 -31.560 20.343 28.095 1.00 0.00 C \nATOM 3313 CD PRO A 285 -32.435 19.298 28.733 1.00 0.00 C \nATOM 3314 HA PRO A 285 -30.436 20.097 31.123 1.00 0.00 H \nATOM 3315 HB2 PRO A 285 -30.150 21.558 28.956 1.00 0.00 H \nATOM 3316 HB3 PRO A 285 -29.686 20.071 28.883 1.00 0.00 H \nATOM 3317 HG2 PRO A 285 -32.071 21.145 27.904 1.00 0.00 H \nATOM 3318 HG3 PRO A 285 -31.207 20.023 27.250 1.00 0.00 H \nATOM 3319 HD2 PRO A 285 -33.376 19.504 28.619 1.00 0.00 H \nATOM 3320 HD3 PRO A 285 -32.287 18.423 28.343 1.00 0.00 H \nATOM 3321 N LYS A 286 -32.912 21.755 31.303 1.00 0.00 N \nATOM 3322 CA LYS A 286 -33.552 22.885 31.975 1.00 0.00 C \nATOM 3323 C LYS A 286 -32.856 23.281 33.274 1.00 0.00 C \nATOM 3324 O LYS A 286 -32.870 22.510 34.242 1.00 0.00 O \nATOM 3325 CB LYS A 286 -35.021 22.573 32.259 1.00 0.00 C \nATOM 3326 CG LYS A 286 -35.833 23.796 32.658 1.00 0.00 C \nATOM 3327 CD LYS A 286 -37.316 23.489 32.702 1.00 0.00 C \nATOM 3328 CE LYS A 286 -38.119 24.721 33.085 1.00 0.00 C \nATOM 3329 NZ LYS A 286 -37.777 25.890 32.229 1.00 0.00 N \nATOM 3330 H LYS A 286 -33.465 21.128 31.102 1.00 0.00 H \nATOM 3331 HA LYS A 286 -33.481 23.639 31.368 1.00 0.00 H \nATOM 3332 HB2 LYS A 286 -35.418 22.173 31.470 1.00 0.00 H \nATOM 3333 HB3 LYS A 286 -35.073 21.913 32.968 1.00 0.00 H \nATOM 3334 HG2 LYS A 286 -35.541 24.110 33.528 1.00 0.00 H \nATOM 3335 HG3 LYS A 286 -35.669 24.514 32.027 1.00 0.00 H \nATOM 3336 HD2 LYS A 286 -37.608 23.166 31.835 1.00 0.00 H \nATOM 3337 HD3 LYS A 286 -37.483 22.779 33.341 1.00 0.00 H \nATOM 3338 HE2 LYS A 286 -39.066 24.528 33.006 1.00 0.00 H \nATOM 3339 HE3 LYS A 286 -37.951 24.941 34.015 1.00 0.00 H \nATOM 3340 HZ1 LYS A 286 -38.475 26.441 32.186 1.00 0.00 H \nATOM 3341 HZ2 LYS A 286 -37.081 26.320 32.578 1.00 0.00 H \nATOM 3342 HZ3 LYS A 286 -37.571 25.608 31.410 1.00 0.00 H \nATOM 3343 N PRO A 287 -32.240 24.458 33.338 1.00 0.00 N \nATOM 3344 CA PRO A 287 -31.596 24.890 34.581 1.00 0.00 C \nATOM 3345 C PRO A 287 -32.585 25.520 35.554 1.00 0.00 C \nATOM 3346 O PRO A 287 -33.637 26.038 35.178 1.00 0.00 O \nATOM 3347 CB PRO A 287 -30.573 25.921 34.098 1.00 0.00 C \nATOM 3348 CG PRO A 287 -31.214 26.523 32.888 1.00 0.00 C \nATOM 3349 CD PRO A 287 -32.084 25.450 32.260 1.00 0.00 C \nATOM 3350 HA PRO A 287 -31.204 24.151 35.071 1.00 0.00 H \nATOM 3351 HB2 PRO A 287 -30.395 26.591 34.777 1.00 0.00 H \nATOM 3352 HB3 PRO A 287 -29.724 25.505 33.881 1.00 0.00 H \nATOM 3353 HG2 PRO A 287 -31.747 27.296 33.132 1.00 0.00 H \nATOM 3354 HG3 PRO A 287 -30.541 26.829 32.260 1.00 0.00 H \nATOM 3355 HD2 PRO A 287 -32.940 25.806 31.976 1.00 0.00 H \nATOM 3356 HD3 PRO A 287 -31.663 25.063 31.476 1.00 0.00 H \nATOM 3357 N GLU A 288 -32.213 25.471 36.831 1.00 0.00 N \nATOM 3358 CA GLU A 288 -32.953 26.123 37.906 1.00 0.00 C \nATOM 3359 C GLU A 288 -32.257 27.435 38.255 1.00 0.00 C \nATOM 3360 O GLU A 288 -31.077 27.436 38.622 1.00 0.00 O \nATOM 3361 CB GLU A 288 -33.040 25.209 39.128 1.00 0.00 C \nATOM 3362 CG GLU A 288 -34.092 25.603 40.150 1.00 0.00 C \nATOM 3363 CD GLU A 288 -34.530 24.429 41.009 1.00 0.00 C \nATOM 3364 OE1 GLU A 288 -35.664 23.940 40.818 1.00 0.00 O \nATOM 3365 OE2 GLU A 288 -33.736 23.990 41.868 1.00 0.00 O \nATOM 3366 H GLU A 288 -31.512 25.051 37.100 1.00 0.00 H \nATOM 3367 HA GLU A 288 -33.860 26.308 37.615 1.00 0.00 H \nATOM 3368 HB2 GLU A 288 -33.223 24.305 38.827 1.00 0.00 H \nATOM 3369 HB3 GLU A 288 -32.174 25.192 39.565 1.00 0.00 H \nATOM 3370 HG2 GLU A 288 -33.739 26.304 40.720 1.00 0.00 H \nATOM 3371 HG3 GLU A 288 -34.863 25.971 39.691 1.00 0.00 H \nATOM 3372 N VAL A 289 -32.987 28.543 38.150 1.00 0.00 N \nATOM 3373 CA VAL A 289 -32.417 29.882 38.256 1.00 0.00 C \nATOM 3374 C VAL A 289 -32.863 30.533 39.559 1.00 0.00 C \nATOM 3375 O VAL A 289 -34.033 30.436 39.946 1.00 0.00 O \nATOM 3376 CB VAL A 289 -32.822 30.751 37.049 1.00 0.00 C \nATOM 3377 CG1 VAL A 289 -32.218 32.145 37.159 1.00 0.00 C \nATOM 3378 CG2 VAL A 289 -32.405 30.081 35.749 1.00 0.00 C \nATOM 3379 H VAL A 289 -33.836 28.537 38.014 1.00 0.00 H \nATOM 3380 HA VAL A 289 -31.450 29.807 38.256 1.00 0.00 H \nATOM 3381 HB VAL A 289 -33.788 30.843 37.049 1.00 0.00 H \nATOM 3382 HG11 VAL A 289 -32.484 32.675 36.391 1.00 0.00 H \nATOM 3383 HG12 VAL A 289 -32.534 32.572 37.971 1.00 0.00 H \nATOM 3384 HG13 VAL A 289 -31.251 32.078 37.185 1.00 0.00 H \nATOM 3385 HG21 VAL A 289 -32.666 30.638 34.999 1.00 0.00 H \nATOM 3386 HG22 VAL A 289 -31.443 29.959 35.742 1.00 0.00 H \nATOM 3387 HG23 VAL A 289 -32.840 29.217 35.676 1.00 0.00 H \nATOM 3388 N MET A 290 -31.925 31.199 40.236 1.00 0.00 N \nATOM 3389 CA MET A 290 -32.235 31.985 41.427 1.00 0.00 C \nATOM 3390 C MET A 290 -31.484 33.307 41.359 1.00 0.00 C \nATOM 3391 O MET A 290 -30.253 33.320 41.249 1.00 0.00 O \nATOM 3392 CB MET A 290 -31.885 31.236 42.715 1.00 0.00 C \nATOM 3393 CG MET A 290 -32.826 31.577 43.862 1.00 0.00 C \nATOM 3394 SD MET A 290 -32.317 30.880 45.439 1.00 0.00 S \nATOM 3395 CE MET A 290 -30.672 31.559 45.560 1.00 0.00 C \nATOM 3396 H MET A 290 -31.094 31.206 40.016 1.00 0.00 H \nATOM 3397 HA MET A 290 -33.191 32.148 41.446 1.00 0.00 H \nATOM 3398 HB2 MET A 290 -31.916 30.281 42.549 1.00 0.00 H \nATOM 3399 HB3 MET A 290 -30.975 31.450 42.973 1.00 0.00 H \nATOM 3400 HG2 MET A 290 -32.885 32.542 43.947 1.00 0.00 H \nATOM 3401 HG3 MET A 290 -33.716 31.256 43.647 1.00 0.00 H \nATOM 3402 HE1 MET A 290 -30.259 31.261 46.385 1.00 0.00 H \nATOM 3403 HE2 MET A 290 -30.141 31.258 44.806 1.00 0.00 H \nATOM 3404 HE3 MET A 290 -30.720 32.528 45.554 1.00 0.00 H \nATOM 3405 N VAL A 291 -32.224 34.411 41.420 1.00 0.00 N \nATOM 3406 CA VAL A 291 -31.663 35.758 41.418 1.00 0.00 C \nATOM 3407 C VAL A 291 -31.587 36.250 42.860 1.00 0.00 C \nATOM 3408 O VAL A 291 -32.619 36.380 43.529 1.00 0.00 O \nATOM 3409 CB VAL A 291 -32.509 36.706 40.553 1.00 0.00 C \nATOM 3410 CG1 VAL A 291 -32.021 38.136 40.679 1.00 0.00 C \nATOM 3411 CG2 VAL A 291 -32.495 36.251 39.103 1.00 0.00 C \nATOM 3412 H VAL A 291 -33.083 34.397 41.465 1.00 0.00 H \nATOM 3413 HA VAL A 291 -30.773 35.742 41.032 1.00 0.00 H \nATOM 3414 HB VAL A 291 -33.424 36.678 40.873 1.00 0.00 H \nATOM 3415 HG11 VAL A 291 -32.568 38.715 40.126 1.00 0.00 H \nATOM 3416 HG12 VAL A 291 -32.084 38.419 41.605 1.00 0.00 H \nATOM 3417 HG13 VAL A 291 -31.097 38.190 40.387 1.00 0.00 H \nATOM 3418 HG21 VAL A 291 -33.032 36.857 38.568 1.00 0.00 H \nATOM 3419 HG22 VAL A 291 -31.583 36.250 38.773 1.00 0.00 H \nATOM 3420 HG23 VAL A 291 -32.861 35.355 39.041 1.00 0.00 H \nATOM 3421 N VAL A 292 -30.380 36.523 43.344 1.00 0.00 N \nATOM 3422 CA VAL A 292 -30.167 37.017 44.701 1.00 0.00 C \nATOM 3423 C VAL A 292 -29.439 38.356 44.641 1.00 0.00 C \nATOM 3424 O VAL A 292 -28.351 38.446 44.067 1.00 0.00 O \nATOM 3425 CB VAL A 292 -29.390 36.021 45.579 1.00 0.00 C \nATOM 3426 CG1 VAL A 292 -30.324 34.972 46.139 1.00 0.00 C \nATOM 3427 CG2 VAL A 292 -28.262 35.368 44.802 1.00 0.00 C \nATOM 3428 H VAL A 292 -29.655 36.426 42.891 1.00 0.00 H \nATOM 3429 HA VAL A 292 -31.037 37.129 45.115 1.00 0.00 H \nATOM 3430 HB VAL A 292 -28.997 36.514 46.316 1.00 0.00 H \nATOM 3431 HG11 VAL A 292 -29.821 34.352 46.690 1.00 0.00 H \nATOM 3432 HG12 VAL A 292 -31.007 35.401 46.677 1.00 0.00 H \nATOM 3433 HG13 VAL A 292 -30.743 34.489 45.410 1.00 0.00 H \nATOM 3434 HG21 VAL A 292 -27.790 34.746 45.378 1.00 0.00 H \nATOM 3435 HG22 VAL A 292 -28.627 34.890 44.041 1.00 0.00 H \nATOM 3436 HG23 VAL A 292 -27.647 36.050 44.490 1.00 0.00 H \nATOM 3437 N PRO A 293 -30.005 39.424 45.205 1.00 0.00 N \nATOM 3438 CA PRO A 293 -29.279 40.700 45.278 1.00 0.00 C \nATOM 3439 C PRO A 293 -28.201 40.691 46.354 1.00 0.00 C \nATOM 3440 O PRO A 293 -28.393 40.160 47.450 1.00 0.00 O \nATOM 3441 CB PRO A 293 -30.381 41.715 45.599 1.00 0.00 C \nATOM 3442 CG PRO A 293 -31.420 40.916 46.314 1.00 0.00 C \nATOM 3443 CD PRO A 293 -31.378 39.530 45.728 1.00 0.00 C \nATOM 3444 HA PRO A 293 -28.801 40.900 44.458 1.00 0.00 H \nATOM 3445 HB2 PRO A 293 -30.047 42.438 46.153 1.00 0.00 H \nATOM 3446 HB3 PRO A 293 -30.737 42.118 44.792 1.00 0.00 H \nATOM 3447 HG2 PRO A 293 -31.241 40.893 47.267 1.00 0.00 H \nATOM 3448 HG3 PRO A 293 -32.298 41.312 46.200 1.00 0.00 H \nATOM 3449 HD2 PRO A 293 -31.559 38.852 46.398 1.00 0.00 H \nATOM 3450 HD3 PRO A 293 -32.038 39.418 45.026 1.00 0.00 H \nATOM 3451 N ARG A 294 -27.053 41.282 46.020 1.00 0.00 N \nATOM 3452 CA ARG A 294 -25.907 41.341 46.926 1.00 0.00 C \nATOM 3453 C ARG A 294 -26.124 42.390 48.026 1.00 0.00 C \nATOM 3454 O ARG A 294 -26.328 43.571 47.734 1.00 0.00 O \nATOM 3455 CB ARG A 294 -24.635 41.634 46.124 1.00 0.00 C \nATOM 3456 CG ARG A 294 -24.423 40.692 44.940 1.00 0.00 C \nATOM 3457 CD ARG A 294 -23.210 41.092 44.111 1.00 0.00 C \nATOM 3458 NE ARG A 294 -22.033 41.293 44.950 1.00 0.00 N \nATOM 3459 CZ ARG A 294 -20.808 41.532 44.492 1.00 0.00 C \nATOM 3460 NH1 ARG A 294 -20.585 41.605 43.188 1.00 0.00 N \nATOM 3461 NH2 ARG A 294 -19.806 41.700 45.345 1.00 0.00 N \nATOM 3462 H ARG A 294 -26.918 41.661 45.260 1.00 0.00 H \nATOM 3463 HA ARG A 294 -25.809 40.482 47.366 1.00 0.00 H \nATOM 3464 HB2 ARG A 294 -24.671 42.547 45.798 1.00 0.00 H \nATOM 3465 HB3 ARG A 294 -23.869 41.574 46.716 1.00 0.00 H \nATOM 3466 HG2 ARG A 294 -24.309 39.785 45.264 1.00 0.00 H \nATOM 3467 HG3 ARG A 294 -25.214 40.695 44.379 1.00 0.00 H \nATOM 3468 HD2 ARG A 294 -23.026 40.404 43.452 1.00 0.00 H \nATOM 3469 HD3 ARG A 294 -23.404 41.908 43.623 1.00 0.00 H \nATOM 3470 HE ARG A 294 -22.140 41.254 45.802 1.00 0.00 H \nATOM 3471 HH11 ARG A 294 -21.234 41.498 42.634 1.00 0.00 H \nATOM 3472 HH12 ARG A 294 -19.791 41.760 42.896 1.00 0.00 H \nATOM 3473 HH21 ARG A 294 -19.950 41.654 46.192 1.00 0.00 H \nATOM 3474 HH22 ARG A 294 -19.013 41.855 45.051 1.00 0.00 H \nATOM 3475 N ALA A 295 -26.076 41.948 49.278 1.00 0.00 N \nATOM 3476 CA ALA A 295 -26.261 42.842 50.414 1.00 0.00 C \nATOM 3477 C ALA A 295 -24.948 43.034 51.165 1.00 0.00 C \nATOM 3478 O ALA A 295 -24.256 42.065 51.479 1.00 0.00 O \nATOM 3479 CB ALA A 295 -27.334 42.300 51.346 1.00 0.00 C \nATOM 3480 H ALA A 295 -25.936 41.127 49.492 1.00 0.00 H \nATOM 3481 HA ALA A 295 -26.550 43.706 50.081 1.00 0.00 H \nATOM 3482 HB1 ALA A 295 -27.446 42.904 52.096 1.00 0.00 H \nATOM 3483 HB2 ALA A 295 -28.173 42.224 50.865 1.00 0.00 H \nATOM 3484 HB3 ALA A 295 -27.068 41.426 51.672 1.00 0.00 H \nATOM 3485 N LYS A 296 -24.610 44.288 51.447 1.00 0.00 N \nATOM 3486 CA LYS A 296 -23.378 44.608 52.159 1.00 0.00 C \nATOM 3487 C LYS A 296 -23.176 43.685 53.355 1.00 0.00 C \nATOM 3488 O LYS A 296 -23.149 44.134 54.501 1.00 0.00 O \nATOM 3489 CB LYS A 296 -23.390 46.068 52.618 1.00 0.00 C \nATOM 3490 CG LYS A 296 -24.464 46.388 53.645 1.00 0.00 C \nATOM 3491 CD LYS A 296 -23.963 47.385 54.676 1.00 0.00 C \nATOM 3492 CE LYS A 296 -23.037 46.721 55.682 1.00 0.00 C \nATOM 3493 NZ LYS A 296 -22.011 47.668 56.202 1.00 0.00 N \nATOM 3494 H LYS A 296 -25.084 44.973 51.233 1.00 0.00 H \nATOM 3495 HA LYS A 296 -22.638 44.475 51.546 1.00 0.00 H \nATOM 3496 HB2 LYS A 296 -22.522 46.286 52.993 1.00 0.00 H \nATOM 3497 HB3 LYS A 296 -23.516 46.639 51.844 1.00 0.00 H \nATOM 3498 HG2 LYS A 296 -25.246 46.748 53.197 1.00 0.00 H \nATOM 3499 HG3 LYS A 296 -24.742 45.572 54.090 1.00 0.00 H \nATOM 3500 HD2 LYS A 296 -23.494 48.107 54.229 1.00 0.00 H \nATOM 3501 HD3 LYS A 296 -24.718 47.781 55.140 1.00 0.00 H \nATOM 3502 HE2 LYS A 296 -23.560 46.373 56.421 1.00 0.00 H \nATOM 3503 HE3 LYS A 296 -22.596 45.964 55.265 1.00 0.00 H \nATOM 3504 HZ1 LYS A 296 -21.233 47.245 56.288 1.00 0.00 H \nATOM 3505 HZ2 LYS A 296 -21.918 48.347 55.634 1.00 0.00 H \nATOM 3506 HZ3 LYS A 296 -22.268 47.979 56.995 1.00 0.00 H \nATOM 3507 N ASP A 297 -23.034 42.392 53.081 1.00 0.00 N \nATOM 3508 CA ASP A 297 -22.836 41.404 54.135 1.00 0.00 C \nATOM 3509 C ASP A 297 -22.193 40.128 53.598 1.00 0.00 C \nATOM 3510 O ASP A 297 -21.548 39.390 54.342 1.00 0.00 O \nATOM 3511 CB ASP A 297 -24.165 41.075 54.817 1.00 0.00 C \nATOM 3512 CG ASP A 297 -23.981 40.531 56.220 1.00 0.00 C \nATOM 3513 OD1 ASP A 297 -22.856 40.629 56.754 1.00 0.00 O \nATOM 3514 OD2 ASP A 297 -24.961 40.004 56.788 1.00 0.00 O \nATOM 3515 H ASP A 297 -23.050 42.065 52.286 1.00 0.00 H \nATOM 3516 HA ASP A 297 -22.231 41.791 54.787 1.00 0.00 H \nATOM 3517 HB2 ASP A 297 -24.713 41.875 54.853 1.00 0.00 H \nATOM 3518 HB3 ASP A 297 -24.647 40.425 54.282 1.00 0.00 H \nATOM 3519 N ASP A 298 -22.373 39.873 52.306 1.00 0.00 N \nATOM 3520 CA ASP A 298 -21.811 38.688 51.684 1.00 0.00 C \nATOM 3521 C ASP A 298 -20.308 38.615 51.916 1.00 0.00 C \nATOM 3522 O ASP A 298 -19.610 39.632 51.947 1.00 0.00 O \nATOM 3523 CB ASP A 298 -22.109 38.698 50.187 1.00 0.00 C \nATOM 3524 CG ASP A 298 -23.559 39.000 49.889 1.00 0.00 C \nATOM 3525 OD1 ASP A 298 -24.439 38.471 50.605 1.00 0.00 O \nATOM 3526 OD2 ASP A 298 -23.823 39.771 48.946 1.00 0.00 O \nATOM 3527 H ASP A 298 -22.820 40.378 51.773 1.00 0.00 H \nATOM 3528 HA ASP A 298 -22.219 37.906 52.087 1.00 0.00 H \nATOM 3529 HB2 ASP A 298 -21.548 39.359 49.753 1.00 0.00 H \nATOM 3530 HB3 ASP A 298 -21.877 37.836 49.808 1.00 0.00 H \nATOM 3531 N ASP A 299 -19.814 37.393 52.094 1.00 0.00 N \nATOM 3532 CA ASP A 299 -18.387 37.129 52.216 1.00 0.00 C \nATOM 3533 C ASP A 299 -17.826 36.527 50.933 1.00 0.00 C \nATOM 3534 O ASP A 299 -16.932 37.109 50.312 1.00 0.00 O \nATOM 3535 CB ASP A 299 -18.117 36.199 53.407 1.00 0.00 C \nATOM 3536 CG ASP A 299 -18.009 36.950 54.719 1.00 0.00 C \nATOM 3537 OD1 ASP A 299 -16.940 37.542 54.985 1.00 0.00 O \nATOM 3538 OD2 ASP A 299 -18.993 36.952 55.485 1.00 0.00 O \nATOM 3539 H ASP A 299 -20.304 36.688 52.148 1.00 0.00 H \nATOM 3540 HA ASP A 299 -17.937 37.974 52.370 1.00 0.00 H \nATOM 3541 HB2 ASP A 299 -18.830 35.545 53.470 1.00 0.00 H \nATOM 3542 HB3 ASP A 299 -17.295 35.708 53.250 1.00 0.00 H \nATOM 3543 N CYS A 300 -18.337 35.368 50.523 1.00 0.00 N \nATOM 3544 CA CYS A 300 -17.755 34.669 49.388 1.00 0.00 C \nATOM 3545 C CYS A 300 -18.789 33.752 48.754 1.00 0.00 C \nATOM 3546 O CYS A 300 -19.809 33.414 49.361 1.00 0.00 O \nATOM 3547 CB CYS A 300 -16.518 33.865 49.807 1.00 0.00 C \nATOM 3548 SG CYS A 300 -16.785 32.789 51.237 1.00 0.00 S \nATOM 3549 H CYS A 300 -19.012 34.976 50.885 1.00 0.00 H \nATOM 3550 HA CYS A 300 -17.475 35.331 48.737 1.00 0.00 H \nATOM 3551 HB2 CYS A 300 -16.227 33.323 49.057 1.00 0.00 H \nATOM 3552 HB3 CYS A 300 -15.797 34.481 50.009 1.00 0.00 H \nATOM 3553 HG CYS A 300 -17.950 32.512 51.318 1.00 0.00 H \nATOM 3554 N LEU A 301 -18.507 33.362 47.513 1.00 0.00 N \nATOM 3555 CA LEU A 301 -19.262 32.348 46.793 1.00 0.00 C \nATOM 3556 C LEU A 301 -18.412 31.089 46.699 1.00 0.00 C \nATOM 3557 O LEU A 301 -17.195 31.169 46.508 1.00 0.00 O \nATOM 3558 CB LEU A 301 -19.637 32.821 45.384 1.00 0.00 C \nATOM 3559 CG LEU A 301 -20.914 33.631 45.162 1.00 0.00 C \nATOM 3560 CD1 LEU A 301 -21.116 33.899 43.674 1.00 0.00 C \nATOM 3561 CD2 LEU A 301 -22.120 32.914 45.743 1.00 0.00 C \nATOM 3562 H LEU A 301 -17.855 33.690 47.058 1.00 0.00 H \nATOM 3563 HA LEU A 301 -20.086 32.172 47.274 1.00 0.00 H \nATOM 3564 HB2 LEU A 301 -18.897 33.353 45.052 1.00 0.00 H \nATOM 3565 HB3 LEU A 301 -19.694 32.033 44.821 1.00 0.00 H \nATOM 3566 HG LEU A 301 -20.820 34.480 45.622 1.00 0.00 H \nATOM 3567 HD11 LEU A 301 -21.928 34.413 43.545 1.00 0.00 H \nATOM 3568 HD12 LEU A 301 -20.359 34.399 43.329 1.00 0.00 H \nATOM 3569 HD13 LEU A 301 -21.189 33.056 43.200 1.00 0.00 H \nATOM 3570 HD21 LEU A 301 -22.917 33.445 45.591 1.00 0.00 H \nATOM 3571 HD22 LEU A 301 -22.221 32.050 45.314 1.00 0.00 H \nATOM 3572 HD23 LEU A 301 -21.993 32.788 46.696 1.00 0.00 H \nATOM 3573 N ILE A 302 -19.049 29.929 46.837 1.00 0.00 N \nATOM 3574 CA ILE A 302 -18.364 28.648 46.703 1.00 0.00 C \nATOM 3575 C ILE A 302 -19.116 27.814 45.676 1.00 0.00 C \nATOM 3576 O ILE A 302 -20.240 27.369 45.935 1.00 0.00 O \nATOM 3577 CB ILE A 302 -18.258 27.905 48.042 1.00 0.00 C \nATOM 3578 CG1 ILE A 302 -17.482 28.753 49.053 1.00 0.00 C \nATOM 3579 CG2 ILE A 302 -17.588 26.554 47.852 1.00 0.00 C \nATOM 3580 CD1 ILE A 302 -17.790 28.426 50.497 1.00 0.00 C \nATOM 3581 H ILE A 302 -19.889 29.863 47.011 1.00 0.00 H \nATOM 3582 HA ILE A 302 -17.453 28.805 46.408 1.00 0.00 H \nATOM 3583 HB ILE A 302 -19.153 27.753 48.385 1.00 0.00 H \nATOM 3584 HG12 ILE A 302 -16.532 28.633 48.900 1.00 0.00 H \nATOM 3585 HG13 ILE A 302 -17.679 29.689 48.894 1.00 0.00 H \nATOM 3586 HG21 ILE A 302 -17.529 26.099 48.706 1.00 0.00 H \nATOM 3587 HG22 ILE A 302 -18.110 26.017 47.235 1.00 0.00 H \nATOM 3588 HG23 ILE A 302 -16.696 26.683 47.493 1.00 0.00 H \nATOM 3589 HD11 ILE A 302 -17.265 28.999 51.078 1.00 0.00 H \nATOM 3590 HD12 ILE A 302 -18.734 28.571 50.668 1.00 0.00 H \nATOM 3591 HD13 ILE A 302 -17.569 27.498 50.673 1.00 0.00 H \nATOM 3592 N LEU A 303 -18.490 27.587 44.524 1.00 0.00 N \nATOM 3593 CA LEU A 303 -18.975 26.663 43.508 1.00 0.00 C \nATOM 3594 C LEU A 303 -18.091 25.427 43.533 1.00 0.00 C \nATOM 3595 O LEU A 303 -16.861 25.543 43.514 1.00 0.00 O \nATOM 3596 CB LEU A 303 -18.946 27.291 42.112 1.00 0.00 C \nATOM 3597 CG LEU A 303 -19.626 28.635 41.855 1.00 0.00 C \nATOM 3598 CD1 LEU A 303 -18.645 29.778 42.046 1.00 0.00 C \nATOM 3599 CD2 LEU A 303 -20.205 28.658 40.447 1.00 0.00 C \nATOM 3600 H LEU A 303 -17.754 27.976 44.308 1.00 0.00 H \nATOM 3601 HA LEU A 303 -19.897 26.434 43.703 1.00 0.00 H \nATOM 3602 HB2 LEU A 303 -18.014 27.388 41.861 1.00 0.00 H \nATOM 3603 HB3 LEU A 303 -19.339 26.649 41.500 1.00 0.00 H \nATOM 3604 HG LEU A 303 -20.347 28.748 42.494 1.00 0.00 H \nATOM 3605 HD11 LEU A 303 -19.094 30.621 41.879 1.00 0.00 H \nATOM 3606 HD12 LEU A 303 -18.308 29.766 42.955 1.00 0.00 H \nATOM 3607 HD13 LEU A 303 -17.906 29.677 41.426 1.00 0.00 H \nATOM 3608 HD21 LEU A 303 -20.636 29.512 40.288 1.00 0.00 H \nATOM 3609 HD22 LEU A 303 -19.492 28.530 39.802 1.00 0.00 H \nATOM 3610 HD23 LEU A 303 -20.857 27.946 40.353 1.00 0.00 H \nATOM 3611 N ALA A 304 -18.706 24.249 43.568 1.00 0.00 N \nATOM 3612 CA ALA A 304 -17.911 23.033 43.645 1.00 0.00 C \nATOM 3613 C ALA A 304 -18.705 21.849 43.120 1.00 0.00 C \nATOM 3614 O ALA A 304 -19.932 21.796 43.253 1.00 0.00 O \nATOM 3615 CB ALA A 304 -17.446 22.758 45.079 1.00 0.00 C \nATOM 3616 H ALA A 304 -19.558 24.134 43.549 1.00 0.00 H \nATOM 3617 HA ALA A 304 -17.124 23.159 43.093 1.00 0.00 H \nATOM 3618 HB1 ALA A 304 -16.920 21.943 45.098 1.00 0.00 H \nATOM 3619 HB2 ALA A 304 -16.904 23.500 45.392 1.00 0.00 H \nATOM 3620 HB3 ALA A 304 -18.219 22.657 45.656 1.00 0.00 H \nATOM 3621 N SER A 305 -17.984 20.902 42.521 1.00 0.00 N \nATOM 3622 CA SER A 305 -18.574 19.622 42.174 1.00 0.00 C \nATOM 3623 C SER A 305 -18.876 18.832 43.447 1.00 0.00 C \nATOM 3624 O SER A 305 -18.424 19.170 44.543 1.00 0.00 O \nATOM 3625 CB SER A 305 -17.642 18.834 41.254 1.00 0.00 C \nATOM 3626 OG SER A 305 -16.369 18.661 41.852 1.00 0.00 O \nATOM 3627 H SER A 305 -17.155 20.985 42.310 1.00 0.00 H \nATOM 3628 HA SER A 305 -19.405 19.775 41.697 1.00 0.00 H \nATOM 3629 HB2 SER A 305 -18.032 17.968 41.058 1.00 0.00 H \nATOM 3630 HB3 SER A 305 -17.546 19.300 40.409 1.00 0.00 H \nATOM 3631 HG SER A 305 -16.419 18.834 42.672 1.00 0.00 H \nATOM 3632 N ASP A 306 -19.644 17.753 43.292 1.00 0.00 N \nATOM 3633 CA ASP A 306 -20.006 16.945 44.450 1.00 0.00 C \nATOM 3634 C ASP A 306 -18.812 16.250 45.093 1.00 0.00 C \nATOM 3635 O ASP A 306 -18.973 15.665 46.165 1.00 0.00 O \nATOM 3636 CB ASP A 306 -21.071 15.913 44.071 1.00 0.00 C \nATOM 3637 CG ASP A 306 -20.581 14.911 43.040 1.00 0.00 C \nATOM 3638 OD1 ASP A 306 -19.456 15.072 42.528 1.00 0.00 O \nATOM 3639 OD2 ASP A 306 -21.330 13.954 42.747 1.00 0.00 O \nATOM 3640 H ASP A 306 -19.959 17.478 42.540 1.00 0.00 H \nATOM 3641 HA ASP A 306 -20.364 17.559 45.110 1.00 0.00 H \nATOM 3642 HB2 ASP A 306 -21.353 15.438 44.868 1.00 0.00 H \nATOM 3643 HB3 ASP A 306 -21.851 16.373 43.723 1.00 0.00 H \nATOM 3644 N GLY A 307 -17.627 16.306 44.483 1.00 0.00 N \nATOM 3645 CA GLY A 307 -16.442 15.796 45.151 1.00 0.00 C \nATOM 3646 C GLY A 307 -16.163 16.487 46.471 1.00 0.00 C \nATOM 3647 O GLY A 307 -15.645 15.867 47.404 1.00 0.00 O \nATOM 3648 H GLY A 307 -17.494 16.630 43.697 1.00 0.00 H \nATOM 3649 HA2 GLY A 307 -16.548 14.844 45.306 1.00 0.00 H \nATOM 3650 HA3 GLY A 307 -15.675 15.904 44.567 1.00 0.00 H \nATOM 3651 N LEU A 308 -16.542 17.759 46.588 1.00 0.00 N \nATOM 3652 CA LEU A 308 -16.409 18.477 47.848 1.00 0.00 C \nATOM 3653 C LEU A 308 -17.641 18.268 48.716 1.00 0.00 C \nATOM 3654 O LEU A 308 -17.520 17.924 49.895 1.00 0.00 O \nATOM 3655 CB LEU A 308 -16.179 19.974 47.601 1.00 0.00 C \nATOM 3656 CG LEU A 308 -16.218 20.840 48.864 1.00 0.00 C \nATOM 3657 CD1 LEU A 308 -14.815 21.042 49.420 1.00 0.00 C \nATOM 3658 CD2 LEU A 308 -16.899 22.179 48.608 1.00 0.00 C \nATOM 3659 H LEU A 308 -16.879 18.222 45.947 1.00 0.00 H \nATOM 3660 HA LEU A 308 -15.637 18.122 48.316 1.00 0.00 H \nATOM 3661 HB2 LEU A 308 -15.318 20.090 47.169 1.00 0.00 H \nATOM 3662 HB3 LEU A 308 -16.853 20.295 46.981 1.00 0.00 H \nATOM 3663 HG LEU A 308 -16.746 20.369 49.527 1.00 0.00 H \nATOM 3664 HD11 LEU A 308 -14.859 21.592 50.218 1.00 0.00 H \nATOM 3665 HD12 LEU A 308 -14.428 20.181 49.642 1.00 0.00 H \nATOM 3666 HD13 LEU A 308 -14.263 21.482 48.755 1.00 0.00 H \nATOM 3667 HD21 LEU A 308 -16.906 22.700 49.426 1.00 0.00 H \nATOM 3668 HD22 LEU A 308 -16.414 22.663 47.921 1.00 0.00 H \nATOM 3669 HD23 LEU A 308 -17.811 22.028 48.314 1.00 0.00 H \nATOM 3670 N TRP A 309 -18.832 18.466 48.147 1.00 0.00 N \nATOM 3671 CA TRP A 309 -20.055 18.428 48.938 1.00 0.00 C \nATOM 3672 C TRP A 309 -20.362 17.034 49.469 1.00 0.00 C \nATOM 3673 O TRP A 309 -21.190 16.902 50.376 1.00 0.00 O \nATOM 3674 CB TRP A 309 -21.232 18.951 48.109 1.00 0.00 C \nATOM 3675 CG TRP A 309 -20.964 20.291 47.484 1.00 0.00 C \nATOM 3676 CD1 TRP A 309 -20.916 20.580 46.150 1.00 0.00 C \nATOM 3677 CD2 TRP A 309 -20.700 21.522 48.169 1.00 0.00 C \nATOM 3678 NE1 TRP A 309 -20.639 21.913 45.963 1.00 0.00 N \nATOM 3679 CE2 TRP A 309 -20.502 22.513 47.187 1.00 0.00 C \nATOM 3680 CE3 TRP A 309 -20.612 21.882 49.517 1.00 0.00 C \nATOM 3681 CZ2 TRP A 309 -20.224 23.839 47.510 1.00 0.00 C \nATOM 3682 CZ3 TRP A 309 -20.334 23.197 49.837 1.00 0.00 C \nATOM 3683 CH2 TRP A 309 -20.143 24.161 48.838 1.00 0.00 C \nATOM 3684 H TRP A 309 -18.949 18.623 47.310 1.00 0.00 H \nATOM 3685 HA TRP A 309 -19.918 19.002 49.708 1.00 0.00 H \nATOM 3686 HB2 TRP A 309 -21.439 18.310 47.411 1.00 0.00 H \nATOM 3687 HB3 TRP A 309 -22.016 19.016 48.676 1.00 0.00 H \nATOM 3688 HD1 TRP A 309 -21.051 19.964 45.467 1.00 0.00 H \nATOM 3689 HE1 TRP A 309 -20.564 22.306 45.202 1.00 0.00 H \nATOM 3690 HE3 TRP A 309 -20.738 21.248 50.186 1.00 0.00 H \nATOM 3691 HZ2 TRP A 309 -20.098 24.481 46.849 1.00 0.00 H \nATOM 3692 HZ3 TRP A 309 -20.273 23.447 50.731 1.00 0.00 H \nATOM 3693 HH2 TRP A 309 -19.957 25.039 49.083 1.00 0.00 H \nATOM 3694 N ASP A 310 -19.720 15.993 48.931 1.00 0.00 N \nATOM 3695 CA ASP A 310 -19.950 14.646 49.441 1.00 0.00 C \nATOM 3696 C ASP A 310 -19.364 14.463 50.835 1.00 0.00 C \nATOM 3697 O ASP A 310 -19.864 13.641 51.611 1.00 0.00 O \nATOM 3698 CB ASP A 310 -19.350 13.608 48.491 1.00 0.00 C \nATOM 3699 CG ASP A 310 -20.253 13.299 47.313 1.00 0.00 C \nATOM 3700 OD1 ASP A 310 -21.424 13.733 47.324 1.00 0.00 O \nATOM 3701 OD2 ASP A 310 -19.787 12.623 46.372 1.00 0.00 O \nATOM 3702 H ASP A 310 -19.158 16.046 48.282 1.00 0.00 H \nATOM 3703 HA ASP A 310 -20.910 14.518 49.498 1.00 0.00 H \nATOM 3704 HB2 ASP A 310 -18.496 13.931 48.163 1.00 0.00 H \nATOM 3705 HB3 ASP A 310 -19.174 12.790 48.982 1.00 0.00 H \nATOM 3706 N VAL A 311 -18.321 15.216 51.173 1.00 0.00 N \nATOM 3707 CA VAL A 311 -17.648 15.074 52.459 1.00 0.00 C \nATOM 3708 C VAL A 311 -17.600 16.368 53.256 1.00 0.00 C \nATOM 3709 O VAL A 311 -17.249 16.327 54.446 1.00 0.00 O \nATOM 3710 CB VAL A 311 -16.220 14.515 52.285 1.00 0.00 C \nATOM 3711 CG1 VAL A 311 -16.269 13.105 51.718 1.00 0.00 C \nATOM 3712 CG2 VAL A 311 -15.400 15.426 51.385 1.00 0.00 C \nATOM 3713 H VAL A 311 -17.985 15.822 50.664 1.00 0.00 H \nATOM 3714 HA VAL A 311 -18.182 14.442 52.966 1.00 0.00 H \nATOM 3715 HB VAL A 311 -15.793 14.480 53.155 1.00 0.00 H \nATOM 3716 HG11 VAL A 311 -15.366 12.766 51.614 1.00 0.00 H \nATOM 3717 HG12 VAL A 311 -16.762 12.529 52.324 1.00 0.00 H \nATOM 3718 HG13 VAL A 311 -16.710 13.118 50.854 1.00 0.00 H \nATOM 3719 HG21 VAL A 311 -14.506 15.063 51.285 1.00 0.00 H \nATOM 3720 HG22 VAL A 311 -15.823 15.487 50.514 1.00 0.00 H \nATOM 3721 HG23 VAL A 311 -15.347 16.310 51.781 1.00 0.00 H \nATOM 3722 N VAL A 312 -17.934 17.508 52.659 1.00 0.00 N \nATOM 3723 CA VAL A 312 -17.923 18.794 53.345 1.00 0.00 C \nATOM 3724 C VAL A 312 -19.320 19.392 53.265 1.00 0.00 C \nATOM 3725 O VAL A 312 -19.924 19.427 52.187 1.00 0.00 O \nATOM 3726 CB VAL A 312 -16.875 19.748 52.741 1.00 0.00 C \nATOM 3727 CG1 VAL A 312 -16.905 21.092 53.448 1.00 0.00 C \nATOM 3728 CG2 VAL A 312 -15.485 19.129 52.819 1.00 0.00 C \nATOM 3729 H VAL A 312 -18.176 17.556 51.835 1.00 0.00 H \nATOM 3730 HA VAL A 312 -17.674 18.662 54.273 1.00 0.00 H \nATOM 3731 HB VAL A 312 -17.093 19.893 51.807 1.00 0.00 H \nATOM 3732 HG11 VAL A 312 -16.240 21.679 53.056 1.00 0.00 H \nATOM 3733 HG12 VAL A 312 -17.784 21.489 53.351 1.00 0.00 H \nATOM 3734 HG13 VAL A 312 -16.710 20.967 54.390 1.00 0.00 H \nATOM 3735 HG21 VAL A 312 -14.836 19.740 52.436 1.00 0.00 H \nATOM 3736 HG22 VAL A 312 -15.258 18.958 53.746 1.00 0.00 H \nATOM 3737 HG23 VAL A 312 -15.474 18.295 52.325 1.00 0.00 H \nATOM 3738 N SER A 313 -19.828 19.859 54.402 1.00 0.00 N \nATOM 3739 CA SER A 313 -21.156 20.444 54.456 1.00 0.00 C \nATOM 3740 C SER A 313 -21.108 21.918 54.059 1.00 0.00 C \nATOM 3741 O SER A 313 -20.041 22.526 53.943 1.00 0.00 O \nATOM 3742 CB SER A 313 -21.754 20.289 55.854 1.00 0.00 C \nATOM 3743 OG SER A 313 -21.290 21.307 56.723 1.00 0.00 O \nATOM 3744 H SER A 313 -19.414 19.845 55.156 1.00 0.00 H \nATOM 3745 HA SER A 313 -21.723 19.973 53.825 1.00 0.00 H \nATOM 3746 HB2 SER A 313 -22.722 20.322 55.800 1.00 0.00 H \nATOM 3747 HB3 SER A 313 -21.519 19.420 56.215 1.00 0.00 H \nATOM 3748 HG SER A 313 -21.631 21.204 57.483 1.00 0.00 H \nATOM 3749 N ASN A 314 -22.294 22.488 53.829 1.00 0.00 N \nATOM 3750 CA ASN A 314 -22.377 23.907 53.497 1.00 0.00 C \nATOM 3751 C ASN A 314 -21.808 24.764 54.620 1.00 0.00 C \nATOM 3752 O ASN A 314 -21.084 25.735 54.367 1.00 0.00 O \nATOM 3753 CB ASN A 314 -23.826 24.294 53.200 1.00 0.00 C \nATOM 3754 CG ASN A 314 -24.353 23.654 51.930 1.00 0.00 C \nATOM 3755 OD1 ASN A 314 -23.703 22.792 51.338 1.00 0.00 O \nATOM 3756 ND2 ASN A 314 -25.534 24.079 51.501 1.00 0.00 N \nATOM 3757 H ASN A 314 -23.049 22.076 53.860 1.00 0.00 H \nATOM 3758 HA ASN A 314 -21.844 24.068 52.703 1.00 0.00 H \nATOM 3759 HB2 ASN A 314 -24.387 24.032 53.947 1.00 0.00 H \nATOM 3760 HB3 ASN A 314 -23.890 25.259 53.122 1.00 0.00 H \nATOM 3761 HD21 ASN A 314 -25.874 23.750 50.783 1.00 0.00 H \nATOM 3762 HD22 ASN A 314 -25.959 24.683 51.941 1.00 0.00 H \nATOM 3763 N GLU A 315 -22.142 24.428 55.869 1.00 0.00 N \nATOM 3764 CA GLU A 315 -21.556 25.118 57.014 1.00 0.00 C \nATOM 3765 C GLU A 315 -20.043 24.949 57.038 1.00 0.00 C \nATOM 3766 O GLU A 315 -19.297 25.920 57.215 1.00 0.00 O \nATOM 3767 CB GLU A 315 -22.170 24.590 58.310 1.00 0.00 C \nATOM 3768 CG GLU A 315 -23.679 24.715 58.395 1.00 0.00 C \nATOM 3769 CD GLU A 315 -24.118 25.654 59.501 1.00 0.00 C \nATOM 3770 OE1 GLU A 315 -23.243 26.289 60.125 1.00 0.00 O \nATOM 3771 OE2 GLU A 315 -25.338 25.751 59.750 1.00 0.00 O \nATOM 3772 H GLU A 315 -22.702 23.807 56.071 1.00 0.00 H \nATOM 3773 HA GLU A 315 -21.750 26.065 56.933 1.00 0.00 H \nATOM 3774 HB2 GLU A 315 -21.929 23.656 58.410 1.00 0.00 H \nATOM 3775 HB3 GLU A 315 -21.776 25.066 59.057 1.00 0.00 H \nATOM 3776 HG2 GLU A 315 -24.023 25.035 57.546 1.00 0.00 H \nATOM 3777 HG3 GLU A 315 -24.066 23.838 58.545 1.00 0.00 H \nATOM 3778 N GLU A 316 -19.575 23.709 56.871 1.00 0.00 N \nATOM 3779 CA GLU A 316 -18.145 23.424 56.933 1.00 0.00 C \nATOM 3780 C GLU A 316 -17.378 24.177 55.854 1.00 0.00 C \nATOM 3781 O GLU A 316 -16.317 24.751 56.121 1.00 0.00 O \nATOM 3782 CB GLU A 316 -17.924 21.919 56.796 1.00 0.00 C \nATOM 3783 CG GLU A 316 -16.598 21.411 57.314 1.00 0.00 C \nATOM 3784 CD GLU A 316 -16.563 19.898 57.377 1.00 0.00 C \nATOM 3785 OE1 GLU A 316 -17.602 19.270 57.081 1.00 0.00 O \nATOM 3786 OE2 GLU A 316 -15.500 19.335 57.715 1.00 0.00 O \nATOM 3787 H GLU A 316 -20.071 23.022 56.721 1.00 0.00 H \nATOM 3788 HA GLU A 316 -17.807 23.726 57.791 1.00 0.00 H \nATOM 3789 HB2 GLU A 316 -18.636 21.458 57.267 1.00 0.00 H \nATOM 3790 HB3 GLU A 316 -18.002 21.680 55.859 1.00 0.00 H \nATOM 3791 HG2 GLU A 316 -15.883 21.728 56.740 1.00 0.00 H \nATOM 3792 HG3 GLU A 316 -16.434 21.776 58.198 1.00 0.00 H \nATOM 3793 N ALA A 317 -17.904 24.197 54.631 1.00 0.00 N \nATOM 3794 CA ALA A 317 -17.194 24.849 53.537 1.00 0.00 C \nATOM 3795 C ALA A 317 -17.178 26.367 53.702 1.00 0.00 C \nATOM 3796 O ALA A 317 -16.178 27.020 53.382 1.00 0.00 O \nATOM 3797 CB ALA A 317 -17.815 24.451 52.198 1.00 0.00 C \nATOM 3798 H ALA A 317 -18.659 23.845 54.417 1.00 0.00 H \nATOM 3799 HA ALA A 317 -16.272 24.550 53.555 1.00 0.00 H \nATOM 3800 HB1 ALA A 317 -17.337 24.889 51.476 1.00 0.00 H \nATOM 3801 HB2 ALA A 317 -17.757 23.489 52.087 1.00 0.00 H \nATOM 3802 HB3 ALA A 317 -18.746 24.722 52.180 1.00 0.00 H \nATOM 3803 N CYS A 318 -18.276 26.946 54.198 1.00 0.00 N \nATOM 3804 CA CYS A 318 -18.370 28.398 54.327 1.00 0.00 C \nATOM 3805 C CYS A 318 -17.424 28.946 55.392 1.00 0.00 C \nATOM 3806 O CYS A 318 -16.759 29.973 55.172 1.00 0.00 O \nATOM 3807 CB CYS A 318 -19.821 28.792 54.631 1.00 0.00 C \nATOM 3808 SG CYS A 318 -20.838 29.070 53.146 1.00 0.00 S \nATOM 3809 H CYS A 318 -18.972 26.516 54.463 1.00 0.00 H \nATOM 3810 HA CYS A 318 -18.097 28.793 53.484 1.00 0.00 H \nATOM 3811 HB2 CYS A 318 -20.231 28.095 55.167 1.00 0.00 H \nATOM 3812 HB3 CYS A 318 -19.822 29.600 55.168 1.00 0.00 H \nATOM 3813 HG CYS A 318 -21.116 28.014 52.648 1.00 0.00 H \nATOM 3814 N LYS A 319 -17.362 28.274 56.549 1.00 0.00 N \nATOM 3815 CA LYS A 319 -16.568 28.773 57.665 1.00 0.00 C \nATOM 3816 C LYS A 319 -15.078 28.655 57.338 1.00 0.00 C \nATOM 3817 O LYS A 319 -14.271 29.516 57.707 1.00 0.00 O \nATOM 3818 CB LYS A 319 -16.994 28.000 58.919 1.00 0.00 C \nATOM 3819 CG LYS A 319 -16.100 27.878 60.137 1.00 0.00 C \nATOM 3820 CD LYS A 319 -17.065 28.049 61.367 1.00 0.00 C \nATOM 3821 CE LYS A 319 -16.399 28.124 62.733 1.00 0.00 C \nATOM 3822 NZ LYS A 319 -17.350 27.510 63.721 1.00 0.00 N \nATOM 3823 H LYS A 319 -17.771 27.533 56.702 1.00 0.00 H \nATOM 3824 HA LYS A 319 -16.723 29.716 57.830 1.00 0.00 H \nATOM 3825 HB2 LYS A 319 -17.825 28.398 59.222 1.00 0.00 H \nATOM 3826 HB3 LYS A 319 -17.200 27.096 58.633 1.00 0.00 H \nATOM 3827 HG2 LYS A 319 -15.651 27.018 60.159 1.00 0.00 H \nATOM 3828 HG3 LYS A 319 -15.409 28.559 60.135 1.00 0.00 H \nATOM 3829 HD2 LYS A 319 -17.586 28.857 61.236 1.00 0.00 H \nATOM 3830 HD3 LYS A 319 -17.689 27.306 61.372 1.00 0.00 H \nATOM 3831 HE2 LYS A 319 -15.554 27.648 62.729 1.00 0.00 H \nATOM 3832 HE3 LYS A 319 -16.205 29.044 62.970 1.00 0.00 H \nATOM 3833 HZ1 LYS A 319 -17.240 27.893 64.517 1.00 0.00 H \nATOM 3834 HZ2 LYS A 319 -18.187 27.636 63.445 1.00 0.00 H \nATOM 3835 HZ3 LYS A 319 -17.188 26.637 63.787 1.00 0.00 H \nATOM 3836 N VAL A 320 -14.708 27.614 56.589 1.00 0.00 N \nATOM 3837 CA VAL A 320 -13.314 27.384 56.203 1.00 0.00 C \nATOM 3838 C VAL A 320 -12.873 28.365 55.118 1.00 0.00 C \nATOM 3839 O VAL A 320 -11.781 28.944 55.184 1.00 0.00 O \nATOM 3840 CB VAL A 320 -13.140 25.928 55.735 1.00 0.00 C \nATOM 3841 CG1 VAL A 320 -11.841 25.771 54.992 1.00 0.00 C \nATOM 3842 CG2 VAL A 320 -13.225 25.002 56.936 1.00 0.00 C \nATOM 3843 H VAL A 320 -15.257 27.023 56.291 1.00 0.00 H \nATOM 3844 HA VAL A 320 -12.748 27.535 56.976 1.00 0.00 H \nATOM 3845 HB VAL A 320 -13.851 25.690 55.120 1.00 0.00 H \nATOM 3846 HG11 VAL A 320 -11.743 24.850 54.703 1.00 0.00 H \nATOM 3847 HG12 VAL A 320 -11.838 26.355 54.218 1.00 0.00 H \nATOM 3848 HG13 VAL A 320 -11.103 26.006 55.576 1.00 0.00 H \nATOM 3849 HG21 VAL A 320 -13.116 24.083 56.645 1.00 0.00 H \nATOM 3850 HG22 VAL A 320 -12.524 25.226 57.568 1.00 0.00 H \nATOM 3851 HG23 VAL A 320 -14.090 25.105 57.363 1.00 0.00 H \nATOM 3852 N ALA A 321 -13.708 28.559 54.098 1.00 0.00 N \nATOM 3853 CA ALA A 321 -13.351 29.470 53.015 1.00 0.00 C \nATOM 3854 C ALA A 321 -13.234 30.894 53.542 1.00 0.00 C \nATOM 3855 O ALA A 321 -12.234 31.581 53.304 1.00 0.00 O \nATOM 3856 CB ALA A 321 -14.383 29.386 51.890 1.00 0.00 C \nATOM 3857 H ALA A 321 -14.475 28.178 54.015 1.00 0.00 H \nATOM 3858 HA ALA A 321 -12.489 29.208 52.655 1.00 0.00 H \nATOM 3859 HB1 ALA A 321 -14.135 29.995 51.177 1.00 0.00 H \nATOM 3860 HB2 ALA A 321 -14.413 28.480 51.545 1.00 0.00 H \nATOM 3861 HB3 ALA A 321 -15.257 29.629 52.233 1.00 0.00 H \nATOM 3862 N ARG A 322 -14.251 31.342 54.284 1.00 0.00 N \nATOM 3863 CA ARG A 322 -14.254 32.693 54.834 1.00 0.00 C \nATOM 3864 C ARG A 322 -13.067 32.933 55.763 1.00 0.00 C \nATOM 3865 O ARG A 322 -12.583 34.067 55.870 1.00 0.00 O \nATOM 3866 CB ARG A 322 -15.571 32.937 55.571 1.00 0.00 C \nATOM 3867 CG ARG A 322 -15.678 34.279 56.265 1.00 0.00 C \nATOM 3868 CD ARG A 322 -16.791 34.266 57.299 1.00 0.00 C \nATOM 3869 NE ARG A 322 -17.117 35.606 57.777 1.00 0.00 N \nATOM 3870 CZ ARG A 322 -16.408 36.271 58.684 1.00 0.00 C \nATOM 3871 NH1 ARG A 322 -15.331 35.718 59.225 1.00 0.00 N \nATOM 3872 NH2 ARG A 322 -16.781 37.488 59.056 1.00 0.00 N \nATOM 3873 H ARG A 322 -14.947 30.876 54.478 1.00 0.00 H \nATOM 3874 HA ARG A 322 -14.170 33.320 54.099 1.00 0.00 H \nATOM 3875 HB2 ARG A 322 -16.300 32.857 54.937 1.00 0.00 H \nATOM 3876 HB3 ARG A 322 -15.691 32.236 56.231 1.00 0.00 H \nATOM 3877 HG2 ARG A 322 -14.835 34.494 56.694 1.00 0.00 H \nATOM 3878 HG3 ARG A 322 -15.848 34.974 55.610 1.00 0.00 H \nATOM 3879 HD2 ARG A 322 -17.583 33.860 56.913 1.00 0.00 H \nATOM 3880 HD3 ARG A 322 -16.526 33.712 58.050 1.00 0.00 H \nATOM 3881 HE ARG A 322 -17.813 35.991 57.450 1.00 0.00 H \nATOM 3882 HH11 ARG A 322 -15.089 34.927 58.989 1.00 0.00 H \nATOM 3883 HH12 ARG A 322 -14.874 36.150 59.811 1.00 0.00 H \nATOM 3884 HH21 ARG A 322 -17.482 37.847 58.711 1.00 0.00 H \nATOM 3885 HH22 ARG A 322 -16.322 37.918 59.643 1.00 0.00 H \nATOM 3886 N ARG A 323 -12.573 31.885 56.427 1.00 0.00 N \nATOM 3887 CA ARG A 323 -11.444 32.056 57.335 1.00 0.00 C \nATOM 3888 C ARG A 323 -10.110 32.013 56.602 1.00 0.00 C \nATOM 3889 O ARG A 323 -9.176 32.732 56.979 1.00 0.00 O \nATOM 3890 CB ARG A 323 -11.479 30.984 58.429 1.00 0.00 C \nATOM 3891 CG ARG A 323 -10.108 30.561 58.937 1.00 0.00 C \nATOM 3892 CD ARG A 323 -10.215 29.608 60.106 1.00 0.00 C \nATOM 3893 NE ARG A 323 -11.398 29.862 60.912 1.00 0.00 N \nATOM 3894 CZ ARG A 323 -11.807 29.078 61.900 1.00 0.00 C \nATOM 3895 NH1 ARG A 323 -11.130 27.981 62.212 1.00 0.00 N \nATOM 3896 NH2 ARG A 323 -12.890 29.401 62.582 1.00 0.00 N \nATOM 3897 H ARG A 323 -12.873 31.081 56.366 1.00 0.00 H \nATOM 3898 HA ARG A 323 -11.526 32.934 57.740 1.00 0.00 H \nATOM 3899 HB2 ARG A 323 -12.000 31.317 59.176 1.00 0.00 H \nATOM 3900 HB3 ARG A 323 -11.940 30.203 58.087 1.00 0.00 H \nATOM 3901 HG2 ARG A 323 -9.613 30.138 58.218 1.00 0.00 H \nATOM 3902 HG3 ARG A 323 -9.605 31.346 59.204 1.00 0.00 H \nATOM 3903 HD2 ARG A 323 -10.239 28.696 59.777 1.00 0.00 H \nATOM 3904 HD3 ARG A 323 -9.424 29.689 60.661 1.00 0.00 H \nATOM 3905 HE ARG A 323 -11.862 30.565 60.737 1.00 0.00 H \nATOM 3906 HH11 ARG A 323 -10.420 27.774 61.772 1.00 0.00 H \nATOM 3907 HH12 ARG A 323 -11.401 27.477 62.854 1.00 0.00 H \nATOM 3908 HH21 ARG A 323 -13.325 30.116 62.384 1.00 0.00 H \nATOM 3909 HH22 ARG A 323 -13.160 28.897 63.224 1.00 0.00 H \nATOM 3910 N GLN A 324 -10.006 31.199 55.547 1.00 0.00 N \nATOM 3911 CA GLN A 324 -8.784 31.178 54.751 1.00 0.00 C \nATOM 3912 C GLN A 324 -8.555 32.513 54.054 1.00 0.00 C \nATOM 3913 O GLN A 324 -7.408 32.953 53.902 1.00 0.00 O \nATOM 3914 CB GLN A 324 -8.842 30.044 53.730 1.00 0.00 C \nATOM 3915 CG GLN A 324 -8.469 28.687 54.296 1.00 0.00 C \nATOM 3916 CD GLN A 324 -7.069 28.668 54.876 1.00 0.00 C \nATOM 3917 OE1 GLN A 324 -6.127 29.189 54.276 1.00 0.00 O \nATOM 3918 NE2 GLN A 324 -6.925 28.071 56.054 1.00 0.00 N \nATOM 3919 H GLN A 324 -10.622 30.661 55.282 1.00 0.00 H \nATOM 3920 HA GLN A 324 -8.036 31.025 55.349 1.00 0.00 H \nATOM 3921 HB2 GLN A 324 -9.739 29.996 53.364 1.00 0.00 H \nATOM 3922 HB3 GLN A 324 -8.246 30.253 52.994 1.00 0.00 H \nATOM 3923 HG2 GLN A 324 -9.105 28.441 54.985 1.00 0.00 H \nATOM 3924 HG3 GLN A 324 -8.536 28.018 53.597 1.00 0.00 H \nATOM 3925 HE21 GLN A 324 -7.606 27.718 56.443 1.00 0.00 H \nATOM 3926 HE22 GLN A 324 -6.151 28.037 56.427 1.00 0.00 H \nATOM 3927 N ILE A 325 -9.634 33.171 53.623 1.00 0.00 N \nATOM 3928 CA ILE A 325 -9.504 34.483 52.995 1.00 0.00 C \nATOM 3929 C ILE A 325 -8.968 35.494 53.998 1.00 0.00 C \nATOM 3930 O ILE A 325 -8.072 36.290 53.687 1.00 0.00 O \nATOM 3931 CB ILE A 325 -10.858 34.934 52.414 1.00 0.00 C \nATOM 3932 CG1 ILE A 325 -11.374 33.926 51.385 1.00 0.00 C \nATOM 3933 CG2 ILE A 325 -10.743 36.335 51.818 1.00 0.00 C \nATOM 3934 CD1 ILE A 325 -10.783 34.085 50.008 1.00 0.00 C \nATOM 3935 H ILE A 325 -10.440 32.877 53.685 1.00 0.00 H \nATOM 3936 HA ILE A 325 -8.871 34.423 52.263 1.00 0.00 H \nATOM 3937 HB ILE A 325 -11.506 34.970 53.135 1.00 0.00 H \nATOM 3938 HG12 ILE A 325 -11.186 33.029 51.704 1.00 0.00 H \nATOM 3939 HG13 ILE A 325 -12.338 34.009 51.323 1.00 0.00 H \nATOM 3940 HG21 ILE A 325 -11.602 36.605 51.457 1.00 0.00 H \nATOM 3941 HG22 ILE A 325 -10.473 36.960 52.509 1.00 0.00 H \nATOM 3942 HG23 ILE A 325 -10.081 36.332 51.109 1.00 0.00 H \nATOM 3943 HD11 ILE A 325 -11.157 33.414 49.416 1.00 0.00 H \nATOM 3944 HD12 ILE A 325 -10.991 34.969 49.667 1.00 0.00 H \nATOM 3945 HD13 ILE A 325 -9.820 33.974 50.054 1.00 0.00 H \nATOM 3946 N LEU A 326 -9.508 35.477 55.218 1.00 0.00 N \nATOM 3947 CA LEU A 326 -9.099 36.443 56.230 1.00 0.00 C \nATOM 3948 C LEU A 326 -7.672 36.188 56.698 1.00 0.00 C \nATOM 3949 O LEU A 326 -6.923 37.137 56.962 1.00 0.00 O \nATOM 3950 CB LEU A 326 -10.072 36.412 57.408 1.00 0.00 C \nATOM 3951 CG LEU A 326 -11.191 37.457 57.377 1.00 0.00 C \nATOM 3952 CD1 LEU A 326 -12.014 37.348 56.100 1.00 0.00 C \nATOM 3953 CD2 LEU A 326 -12.082 37.322 58.601 1.00 0.00 C \nATOM 3954 H LEU A 326 -10.108 34.917 55.475 1.00 0.00 H \nATOM 3955 HA LEU A 326 -9.119 37.327 55.831 1.00 0.00 H \nATOM 3956 HB2 LEU A 326 -10.476 35.531 57.448 1.00 0.00 H \nATOM 3957 HB3 LEU A 326 -9.566 36.529 58.227 1.00 0.00 H \nATOM 3958 HG LEU A 326 -10.779 38.335 57.390 1.00 0.00 H \nATOM 3959 HD11 LEU A 326 -12.714 38.020 56.107 1.00 0.00 H \nATOM 3960 HD12 LEU A 326 -11.439 37.489 55.331 1.00 0.00 H \nATOM 3961 HD13 LEU A 326 -12.414 36.466 56.047 1.00 0.00 H \nATOM 3962 HD21 LEU A 326 -12.784 37.990 58.566 1.00 0.00 H \nATOM 3963 HD22 LEU A 326 -12.479 36.437 58.617 1.00 0.00 H \nATOM 3964 HD23 LEU A 326 -11.552 37.453 59.403 1.00 0.00 H \nATOM 3965 N LEU A 327 -7.273 34.917 56.811 1.00 0.00 N \nATOM 3966 CA LEU A 327 -5.934 34.628 57.309 1.00 0.00 C \nATOM 3967 C LEU A 327 -4.857 34.931 56.278 1.00 0.00 C \nATOM 3968 O LEU A 327 -3.692 35.108 56.653 1.00 0.00 O \nATOM 3969 CB LEU A 327 -5.831 33.162 57.733 1.00 0.00 C \nATOM 3970 CG LEU A 327 -6.584 32.731 58.993 1.00 0.00 C \nATOM 3971 CD1 LEU A 327 -6.054 31.396 59.499 1.00 0.00 C \nATOM 3972 CD2 LEU A 327 -6.499 33.799 60.078 1.00 0.00 C \nATOM 3973 H LEU A 327 -7.749 34.230 56.610 1.00 0.00 H \nATOM 3974 HA LEU A 327 -5.786 35.206 58.074 1.00 0.00 H \nATOM 3975 HB2 LEU A 327 -6.145 32.615 56.996 1.00 0.00 H \nATOM 3976 HB3 LEU A 327 -4.892 32.954 57.860 1.00 0.00 H \nATOM 3977 HG LEU A 327 -7.520 32.621 58.763 1.00 0.00 H \nATOM 3978 HD11 LEU A 327 -6.540 31.136 60.297 1.00 0.00 H \nATOM 3979 HD12 LEU A 327 -6.173 30.720 58.814 1.00 0.00 H \nATOM 3980 HD13 LEU A 327 -5.111 31.481 59.709 1.00 0.00 H \nATOM 3981 HD21 LEU A 327 -6.983 33.501 60.864 1.00 0.00 H \nATOM 3982 HD22 LEU A 327 -5.570 33.952 60.310 1.00 0.00 H \nATOM 3983 HD23 LEU A 327 -6.890 34.624 59.751 1.00 0.00 H \nATOM 3984 N TRP A 328 -5.210 34.998 54.994 1.00 0.00 N \nATOM 3985 CA TRP A 328 -4.216 35.366 53.994 1.00 0.00 C \nATOM 3986 C TRP A 328 -3.931 36.861 54.040 1.00 0.00 C \nATOM 3987 O TRP A 328 -2.777 37.284 53.911 1.00 0.00 O \nATOM 3988 CB TRP A 328 -4.670 34.949 52.593 1.00 0.00 C \nATOM 3989 CG TRP A 328 -3.551 34.979 51.591 1.00 0.00 C \nATOM 3990 CD1 TRP A 328 -2.800 33.920 51.167 1.00 0.00 C \nATOM 3991 CD2 TRP A 328 -3.046 36.129 50.897 1.00 0.00 C \nATOM 3992 NE1 TRP A 328 -1.864 34.338 50.250 1.00 0.00 N \nATOM 3993 CE2 TRP A 328 -1.994 35.690 50.068 1.00 0.00 C \nATOM 3994 CE3 TRP A 328 -3.385 37.485 50.892 1.00 0.00 C \nATOM 3995 CZ2 TRP A 328 -1.276 36.558 49.250 1.00 0.00 C \nATOM 3996 CZ3 TRP A 328 -2.671 38.346 50.079 1.00 0.00 C \nATOM 3997 CH2 TRP A 328 -1.631 37.880 49.266 1.00 0.00 C \nATOM 3998 H TRP A 328 -5.998 34.838 54.690 1.00 0.00 H \nATOM 3999 HA TRP A 328 -3.395 34.892 54.200 1.00 0.00 H \nATOM 4000 HB2 TRP A 328 -5.042 34.054 52.630 1.00 0.00 H \nATOM 4001 HB3 TRP A 328 -5.380 35.540 52.298 1.00 0.00 H \nATOM 4002 HD1 TRP A 328 -2.906 33.043 51.457 1.00 0.00 H \nATOM 4003 HE1 TRP A 328 -1.291 33.833 49.855 1.00 0.00 H \nATOM 4004 HE3 TRP A 328 -4.078 37.802 51.425 1.00 0.00 H \nATOM 4005 HZ2 TRP A 328 -0.581 36.251 48.713 1.00 0.00 H \nATOM 4006 HZ3 TRP A 328 -2.886 39.251 50.072 1.00 0.00 H \nATOM 4007 HH2 TRP A 328 -1.172 38.481 48.725 1.00 0.00 H \nATOM 4008 N HIS A 329 -4.974 37.672 54.234 1.00 0.00 N \nATOM 4009 CA HIS A 329 -4.820 39.121 54.219 1.00 0.00 C \nATOM 4010 C HIS A 329 -4.189 39.658 55.497 1.00 0.00 C \nATOM 4011 O HIS A 329 -3.543 40.711 55.464 1.00 0.00 O \nATOM 4012 CB HIS A 329 -6.176 39.783 53.976 1.00 0.00 C \nATOM 4013 CG HIS A 329 -6.667 39.640 52.570 1.00 0.00 C \nATOM 4014 ND1 HIS A 329 -5.857 39.857 51.476 1.00 0.00 N \nATOM 4015 CD2 HIS A 329 -7.880 39.295 52.077 1.00 0.00 C \nATOM 4016 CE1 HIS A 329 -6.551 39.655 50.370 1.00 0.00 C \nATOM 4017 NE2 HIS A 329 -7.781 39.313 50.707 1.00 0.00 N \nATOM 4018 H HIS A 329 -5.777 37.399 54.376 1.00 0.00 H \nATOM 4019 HA HIS A 329 -4.213 39.340 53.495 1.00 0.00 H \nATOM 4020 HB2 HIS A 329 -6.829 39.397 54.580 1.00 0.00 H \nATOM 4021 HB3 HIS A 329 -6.111 40.726 54.194 1.00 0.00 H \nATOM 4022 HD1 HIS A 329 -5.029 40.088 51.508 1.00 0.00 H \nATOM 4023 HD2 HIS A 329 -8.638 39.085 52.573 1.00 0.00 H \nATOM 4024 HE1 HIS A 329 -6.228 39.739 49.502 1.00 0.00 H \nATOM 4025 HE2 HIS A 329 -8.417 39.131 50.158 1.00 0.00 H \nATOM 4026 N LYS A 330 -4.367 38.973 56.628 1.00 0.00 N \nATOM 4027 CA LYS A 330 -3.659 39.377 57.835 1.00 0.00 C \nATOM 4028 C LYS A 330 -2.215 38.896 57.834 1.00 0.00 C \nATOM 4029 O LYS A 330 -1.380 39.477 58.535 1.00 0.00 O \nATOM 4030 CB LYS A 330 -4.407 38.880 59.081 1.00 0.00 C \nATOM 4031 CG LYS A 330 -4.132 37.443 59.521 1.00 0.00 C \nATOM 4032 CD LYS A 330 -3.012 37.352 60.552 1.00 0.00 C \nATOM 4033 CE LYS A 330 -2.461 35.941 60.629 1.00 0.00 C \nATOM 4034 NZ LYS A 330 -1.224 35.861 61.452 1.00 0.00 N \nATOM 4035 H LYS A 330 -4.881 38.289 56.714 1.00 0.00 H \nATOM 4036 HA LYS A 330 -3.633 40.346 57.854 1.00 0.00 H \nATOM 4037 HB2 LYS A 330 -4.189 39.470 59.820 1.00 0.00 H \nATOM 4038 HB3 LYS A 330 -5.359 38.970 58.918 1.00 0.00 H \nATOM 4039 HG2 LYS A 330 -4.942 37.061 59.894 1.00 0.00 H \nATOM 4040 HG3 LYS A 330 -3.898 36.910 58.745 1.00 0.00 H \nATOM 4041 HD2 LYS A 330 -2.301 37.969 60.318 1.00 0.00 H \nATOM 4042 HD3 LYS A 330 -3.346 37.621 61.422 1.00 0.00 H \nATOM 4043 HE2 LYS A 330 -3.135 35.353 61.004 1.00 0.00 H \nATOM 4044 HE3 LYS A 330 -2.272 35.621 59.733 1.00 0.00 H \nATOM 4045 HZ1 LYS A 330 -0.708 35.202 61.149 1.00 0.00 H \nATOM 4046 HZ2 LYS A 330 -0.782 36.632 61.400 1.00 0.00 H \nATOM 4047 HZ3 LYS A 330 -1.441 35.701 62.300 1.00 0.00 H \nATOM 4048 N ASN A 331 -1.902 37.862 57.052 1.00 0.00 N \nATOM 4049 CA ASN A 331 -0.535 37.381 56.911 1.00 0.00 C \nATOM 4050 C ASN A 331 0.213 38.042 55.763 1.00 0.00 C \nATOM 4051 O ASN A 331 1.450 38.037 55.767 1.00 0.00 O \nATOM 4052 CB ASN A 331 -0.523 35.863 56.699 1.00 0.00 C \nATOM 4053 CG ASN A 331 -0.571 35.088 57.998 1.00 0.00 C \nATOM 4054 OD1 ASN A 331 0.173 35.379 58.935 1.00 0.00 O \nATOM 4055 ND2 ASN A 331 -1.442 34.086 58.059 1.00 0.00 N \nATOM 4056 H ASN A 331 -2.479 37.422 56.590 1.00 0.00 H \nATOM 4057 HA ASN A 331 -0.080 37.614 57.735 1.00 0.00 H \nATOM 4058 HB2 ASN A 331 -1.282 35.612 56.149 1.00 0.00 H \nATOM 4059 HB3 ASN A 331 0.277 35.616 56.209 1.00 0.00 H \nATOM 4060 HD21 ASN A 331 -1.502 33.611 58.774 1.00 0.00 H \nATOM 4061 HD22 ASN A 331 -1.946 33.912 57.384 1.00 0.00 H \nATOM 4062 N ASN A 332 -0.495 38.598 54.781 1.00 0.00 N \nATOM 4063 CA ASN A 332 0.137 39.146 53.586 1.00 0.00 C \nATOM 4064 C ASN A 332 -0.530 40.475 53.247 1.00 0.00 C \nATOM 4065 O ASN A 332 -1.257 41.054 54.059 1.00 0.00 O \nATOM 4066 CB ASN A 332 0.058 38.145 52.424 1.00 0.00 C \nATOM 4067 CG ASN A 332 0.392 36.726 52.849 1.00 0.00 C \nATOM 4068 OD1 ASN A 332 -0.375 36.078 53.562 1.00 0.00 O \nATOM 4069 ND2 ASN A 332 1.553 36.243 52.431 1.00 0.00 N \nATOM 4070 H ASN A 332 -1.352 38.667 54.790 1.00 0.00 H \nATOM 4071 HA ASN A 332 1.080 39.306 53.749 1.00 0.00 H \nATOM 4072 HB2 ASN A 332 -0.835 38.164 52.046 1.00 0.00 H \nATOM 4073 HB3 ASN A 332 0.669 38.421 51.722 1.00 0.00 H \nATOM 4074 HD21 ASN A 332 1.795 35.449 52.657 1.00 0.00 H \nATOM 4075 HD22 ASN A 332 2.065 36.723 51.934 1.00 0.00 H \nATOM 4076 N GLY A 333 -0.271 40.967 52.039 1.00 0.00 N \nATOM 4077 CA GLY A 333 -0.850 42.218 51.586 1.00 0.00 C \nATOM 4078 C GLY A 333 -2.309 42.093 51.194 1.00 0.00 C \nATOM 4079 O GLY A 333 -2.706 42.493 50.101 1.00 0.00 O \nATOM 4080 H GLY A 333 0.243 40.585 51.465 1.00 0.00 H \nATOM 4081 HA2 GLY A 333 -0.766 42.880 52.290 1.00 0.00 H \nATOM 4082 HA3 GLY A 333 -0.344 42.546 50.826 1.00 0.00 H \nATOM 4083 N SER A 345 -6.523 36.801 35.949 1.00 0.00 N \nATOM 4084 CA SER A 345 -5.896 35.689 36.655 1.00 0.00 C \nATOM 4085 C SER A 345 -6.498 35.518 38.045 1.00 0.00 C \nATOM 4086 O SER A 345 -7.445 36.213 38.412 1.00 0.00 O \nATOM 4087 CB SER A 345 -4.384 35.898 36.755 1.00 0.00 C \nATOM 4088 OG SER A 345 -4.069 36.917 37.686 1.00 0.00 O \nATOM 4089 HA SER A 345 -6.064 34.880 36.148 1.00 0.00 H \nATOM 4090 HB2 SER A 345 -3.957 35.069 37.022 1.00 0.00 H \nATOM 4091 HB3 SER A 345 -4.029 36.132 35.883 1.00 0.00 H \nATOM 4092 HG SER A 345 -4.733 37.422 37.784 1.00 0.00 H \nATOM 4093 N THR A 346 -5.939 34.592 38.818 1.00 0.00 N \nATOM 4094 CA THR A 346 -6.493 34.274 40.123 1.00 0.00 C \nATOM 4095 C THR A 346 -5.974 35.245 41.180 1.00 0.00 C \nATOM 4096 O THR A 346 -4.963 35.928 40.999 1.00 0.00 O \nATOM 4097 CB THR A 346 -6.158 32.835 40.521 1.00 0.00 C \nATOM 4098 OG1 THR A 346 -4.738 32.650 40.507 1.00 0.00 O \nATOM 4099 CG2 THR A 346 -6.806 31.851 39.556 1.00 0.00 C \nATOM 4100 H THR A 346 -5.240 34.139 38.604 1.00 0.00 H \nATOM 4101 HA THR A 346 -7.457 34.362 40.067 1.00 0.00 H \nATOM 4102 HB THR A 346 -6.501 32.672 41.414 1.00 0.00 H \nATOM 4103 HG1 THR A 346 -4.358 33.399 40.525 1.00 0.00 H \nATOM 4104 HG21 THR A 346 -6.585 30.944 39.821 1.00 0.00 H \nATOM 4105 HG22 THR A 346 -7.769 31.967 39.574 1.00 0.00 H \nATOM 4106 HG23 THR A 346 -6.477 32.014 38.658 1.00 0.00 H \nATOM 4107 N ASP A 347 -6.691 35.293 42.303 1.00 0.00 N \nATOM 4108 CA ASP A 347 -6.341 36.073 43.485 1.00 0.00 C \nATOM 4109 C ASP A 347 -5.721 35.170 44.539 1.00 0.00 C \nATOM 4110 O ASP A 347 -6.259 34.086 44.805 1.00 0.00 O \nATOM 4111 CB ASP A 347 -7.580 36.760 44.051 1.00 0.00 C \nATOM 4112 CG ASP A 347 -7.386 37.239 45.474 1.00 0.00 C \nATOM 4113 OD1 ASP A 347 -6.946 38.393 45.659 1.00 0.00 O \nATOM 4114 OD2 ASP A 347 -7.679 36.464 46.409 1.00 0.00 O \nATOM 4115 H ASP A 347 -7.424 34.853 42.398 1.00 0.00 H \nATOM 4116 HA ASP A 347 -5.696 36.752 43.231 1.00 0.00 H \nATOM 4117 HB2 ASP A 347 -7.811 37.516 43.488 1.00 0.00 H \nATOM 4118 HB3 ASP A 347 -8.329 36.144 44.021 1.00 0.00 H \nATOM 4119 N PRO A 348 -4.599 35.568 45.151 1.00 0.00 N \nATOM 4120 CA PRO A 348 -3.872 34.618 46.012 1.00 0.00 C \nATOM 4121 C PRO A 348 -4.652 34.207 47.245 1.00 0.00 C \nATOM 4122 O PRO A 348 -4.608 33.035 47.639 1.00 0.00 O \nATOM 4123 CB PRO A 348 -2.591 35.381 46.384 1.00 0.00 C \nATOM 4124 CG PRO A 348 -2.617 36.662 45.601 1.00 0.00 C \nATOM 4125 CD PRO A 348 -4.034 36.923 45.227 1.00 0.00 C \nATOM 4126 HA PRO A 348 -3.704 33.778 45.557 1.00 0.00 H \nATOM 4127 HB2 PRO A 348 -2.559 35.559 47.337 1.00 0.00 H \nATOM 4128 HB3 PRO A 348 -1.803 34.859 46.167 1.00 0.00 H \nATOM 4129 HG2 PRO A 348 -2.263 37.394 46.130 1.00 0.00 H \nATOM 4130 HG3 PRO A 348 -2.062 36.590 44.809 1.00 0.00 H \nATOM 4131 HD2 PRO A 348 -4.488 37.467 45.890 1.00 0.00 H \nATOM 4132 HD3 PRO A 348 -4.103 37.391 44.380 1.00 0.00 H \nATOM 4133 N ALA A 349 -5.362 35.145 47.874 1.00 0.00 N \nATOM 4134 CA ALA A 349 -6.121 34.819 49.076 1.00 0.00 C \nATOM 4135 C ALA A 349 -7.257 33.856 48.757 1.00 0.00 C \nATOM 4136 O ALA A 349 -7.472 32.872 49.473 1.00 0.00 O \nATOM 4137 CB ALA A 349 -6.656 36.097 49.721 1.00 0.00 C \nATOM 4138 H ALA A 349 -5.416 35.966 47.623 1.00 0.00 H \nATOM 4139 HA ALA A 349 -5.529 34.379 49.706 1.00 0.00 H \nATOM 4140 HB1 ALA A 349 -7.159 35.871 50.519 1.00 0.00 H \nATOM 4141 HB2 ALA A 349 -5.914 36.674 49.960 1.00 0.00 H \nATOM 4142 HB3 ALA A 349 -7.235 36.558 49.094 1.00 0.00 H \nATOM 4143 N ALA A 350 -7.997 34.125 47.679 1.00 0.00 N \nATOM 4144 CA ALA A 350 -9.077 33.230 47.278 1.00 0.00 C \nATOM 4145 C ALA A 350 -8.546 31.907 46.746 1.00 0.00 C \nATOM 4146 O ALA A 350 -9.178 30.864 46.947 1.00 0.00 O \nATOM 4147 CB ALA A 350 -9.960 33.908 46.231 1.00 0.00 C \nATOM 4148 H ALA A 350 -7.890 34.813 47.174 1.00 0.00 H \nATOM 4149 HA ALA A 350 -9.608 33.035 48.066 1.00 0.00 H \nATOM 4150 HB1 ALA A 350 -10.674 33.306 45.971 1.00 0.00 H \nATOM 4151 HB2 ALA A 350 -10.341 34.718 46.604 1.00 0.00 H \nATOM 4152 HB3 ALA A 350 -9.426 34.131 45.452 1.00 0.00 H \nATOM 4153 N GLN A 351 -7.402 31.928 46.059 1.00 0.00 N \nATOM 4154 CA GLN A 351 -6.784 30.682 45.618 1.00 0.00 C \nATOM 4155 C GLN A 351 -6.389 29.814 46.805 1.00 0.00 C \nATOM 4156 O GLN A 351 -6.474 28.582 46.739 1.00 0.00 O \nATOM 4157 CB GLN A 351 -5.569 30.976 44.737 1.00 0.00 C \nATOM 4158 CG GLN A 351 -5.026 29.754 44.021 1.00 0.00 C \nATOM 4159 CD GLN A 351 -6.036 29.151 43.065 1.00 0.00 C \nATOM 4160 OE1 GLN A 351 -6.562 29.835 42.187 1.00 0.00 O \nATOM 4161 NE2 GLN A 351 -6.317 27.863 43.236 1.00 0.00 N \nATOM 4162 H GLN A 351 -6.975 32.643 45.842 1.00 0.00 H \nATOM 4163 HA GLN A 351 -7.436 30.190 45.095 1.00 0.00 H \nATOM 4164 HB2 GLN A 351 -5.811 31.646 44.079 1.00 0.00 H \nATOM 4165 HB3 GLN A 351 -4.866 31.359 45.286 1.00 0.00 H \nATOM 4166 HG2 GLN A 351 -4.225 29.998 43.531 1.00 0.00 H \nATOM 4167 HG3 GLN A 351 -4.765 29.087 44.676 1.00 0.00 H \nATOM 4168 HE21 GLN A 351 -5.929 27.417 43.861 1.00 0.00 H \nATOM 4169 HE22 GLN A 351 -6.887 27.475 42.722 1.00 0.00 H \nATOM 4170 N ALA A 352 -5.948 30.440 47.899 1.00 0.00 N \nATOM 4171 CA ALA A 352 -5.623 29.685 49.105 1.00 0.00 C \nATOM 4172 C ALA A 352 -6.864 29.029 49.694 1.00 0.00 C \nATOM 4173 O ALA A 352 -6.803 27.893 50.181 1.00 0.00 O \nATOM 4174 CB ALA A 352 -4.959 30.599 50.134 1.00 0.00 C \nATOM 4175 H ALA A 352 -5.832 31.290 47.961 1.00 0.00 H \nATOM 4176 HA ALA A 352 -5.002 28.980 48.864 1.00 0.00 H \nATOM 4177 HB1 ALA A 352 -4.747 30.089 50.931 1.00 0.00 H \nATOM 4178 HB2 ALA A 352 -4.144 30.968 49.761 1.00 0.00 H \nATOM 4179 HB3 ALA A 352 -5.565 31.321 50.364 1.00 0.00 H \nATOM 4180 N ALA A 353 -8.002 29.730 49.660 1.00 0.00 N \nATOM 4181 CA ALA A 353 -9.242 29.146 50.160 1.00 0.00 C \nATOM 4182 C ALA A 353 -9.669 27.957 49.309 1.00 0.00 C \nATOM 4183 O ALA A 353 -10.071 26.916 49.841 1.00 0.00 O \nATOM 4184 CB ALA A 353 -10.343 30.204 50.198 1.00 0.00 C \nATOM 4185 H ALA A 353 -8.074 30.531 49.356 1.00 0.00 H \nATOM 4186 HA ALA A 353 -9.086 28.825 51.062 1.00 0.00 H \nATOM 4187 HB1 ALA A 353 -11.163 29.807 50.531 1.00 0.00 H \nATOM 4188 HB2 ALA A 353 -10.075 30.930 50.783 1.00 0.00 H \nATOM 4189 HB3 ALA A 353 -10.492 30.549 49.304 1.00 0.00 H \nATOM 4190 N ALA A 354 -9.602 28.099 47.984 1.00 0.00 N \nATOM 4191 CA ALA A 354 -9.978 26.998 47.105 1.00 0.00 C \nATOM 4192 C ALA A 354 -9.018 25.824 47.255 1.00 0.00 C \nATOM 4193 O ALA A 354 -9.446 24.664 47.285 1.00 0.00 O \nATOM 4194 CB ALA A 354 -10.028 27.475 45.653 1.00 0.00 C \nATOM 4195 H ALA A 354 -9.345 28.814 47.582 1.00 0.00 H \nATOM 4196 HA ALA A 354 -10.862 26.691 47.362 1.00 0.00 H \nATOM 4197 HB1 ALA A 354 -10.279 26.735 45.078 1.00 0.00 H \nATOM 4198 HB2 ALA A 354 -10.682 28.186 45.568 1.00 0.00 H \nATOM 4199 HB3 ALA A 354 -9.155 27.806 45.391 1.00 0.00 H \nATOM 4200 N ASP A 355 -7.714 26.108 47.334 1.00 0.00 N \nATOM 4201 CA ASP A 355 -6.734 25.050 47.561 1.00 0.00 C \nATOM 4202 C ASP A 355 -6.985 24.338 48.886 1.00 0.00 C \nATOM 4203 O ASP A 355 -6.910 23.106 48.962 1.00 0.00 O \nATOM 4204 CB ASP A 355 -5.322 25.632 47.526 1.00 0.00 C \nATOM 4205 CG ASP A 355 -4.739 25.666 46.128 1.00 0.00 C \nATOM 4206 OD1 ASP A 355 -4.954 24.698 45.369 1.00 0.00 O \nATOM 4207 OD2 ASP A 355 -4.067 26.663 45.786 1.00 0.00 O \nATOM 4208 H ASP A 355 -7.383 26.898 47.259 1.00 0.00 H \nATOM 4209 HA ASP A 355 -6.825 24.394 46.852 1.00 0.00 H \nATOM 4210 HB2 ASP A 355 -5.338 26.532 47.888 1.00 0.00 H \nATOM 4211 HB3 ASP A 355 -4.745 25.105 48.101 1.00 0.00 H \nATOM 4212 N TYR A 356 -7.283 25.100 49.942 1.00 0.00 N \nATOM 4213 CA TYR A 356 -7.535 24.493 51.246 1.00 0.00 C \nATOM 4214 C TYR A 356 -8.782 23.620 51.213 1.00 0.00 C \nATOM 4215 O TYR A 356 -8.777 22.499 51.735 1.00 0.00 O \nATOM 4216 CB TYR A 356 -7.664 25.583 52.312 1.00 0.00 C \nATOM 4217 CG TYR A 356 -7.600 25.080 53.740 1.00 0.00 C \nATOM 4218 CD1 TYR A 356 -8.682 24.424 54.317 1.00 0.00 C \nATOM 4219 CD2 TYR A 356 -6.464 25.272 54.516 1.00 0.00 C \nATOM 4220 CE1 TYR A 356 -8.631 23.968 55.619 1.00 0.00 C \nATOM 4221 CE2 TYR A 356 -6.406 24.819 55.823 1.00 0.00 C \nATOM 4222 CZ TYR A 356 -7.492 24.168 56.368 1.00 0.00 C \nATOM 4223 OH TYR A 356 -7.442 23.713 57.665 1.00 0.00 O \nATOM 4224 H TYR A 356 -7.343 25.958 49.923 1.00 0.00 H \nATOM 4225 HA TYR A 356 -6.783 23.922 51.470 1.00 0.00 H \nATOM 4226 HB2 TYR A 356 -6.957 26.234 52.179 1.00 0.00 H \nATOM 4227 HB3 TYR A 356 -8.506 26.047 52.183 1.00 0.00 H \nATOM 4228 HD1 TYR A 356 -9.454 24.290 53.816 1.00 0.00 H \nATOM 4229 HD2 TYR A 356 -5.730 25.712 54.152 1.00 0.00 H \nATOM 4230 HE1 TYR A 356 -9.362 23.528 55.989 1.00 0.00 H \nATOM 4231 HE2 TYR A 356 -5.638 24.953 56.331 1.00 0.00 H \nATOM 4232 HH TYR A 356 -8.141 23.280 57.837 1.00 0.00 H \nATOM 4233 N LEU A 357 -9.862 24.120 50.605 1.00 0.00 N \nATOM 4234 CA LEU A 357 -11.097 23.344 50.533 1.00 0.00 C \nATOM 4235 C LEU A 357 -10.897 22.066 49.733 1.00 0.00 C \nATOM 4236 O LEU A 357 -11.450 21.013 50.076 1.00 0.00 O \nATOM 4237 CB LEU A 357 -12.210 24.188 49.915 1.00 0.00 C \nATOM 4238 CG LEU A 357 -12.883 25.206 50.835 1.00 0.00 C \nATOM 4239 CD1 LEU A 357 -13.698 26.190 50.017 1.00 0.00 C \nATOM 4240 CD2 LEU A 357 -13.754 24.499 51.859 1.00 0.00 C \nATOM 4241 H LEU A 357 -9.898 24.895 50.234 1.00 0.00 H \nATOM 4242 HA LEU A 357 -11.351 23.095 51.435 1.00 0.00 H \nATOM 4243 HB2 LEU A 357 -11.844 24.663 49.153 1.00 0.00 H \nATOM 4244 HB3 LEU A 357 -12.892 23.589 49.574 1.00 0.00 H \nATOM 4245 HG LEU A 357 -12.198 25.700 51.312 1.00 0.00 H \nATOM 4246 HD11 LEU A 357 -14.121 26.831 50.609 1.00 0.00 H \nATOM 4247 HD12 LEU A 357 -13.115 26.657 49.398 1.00 0.00 H \nATOM 4248 HD13 LEU A 357 -14.380 25.711 49.520 1.00 0.00 H \nATOM 4249 HD21 LEU A 357 -14.174 25.156 52.435 1.00 0.00 H \nATOM 4250 HD22 LEU A 357 -14.438 23.985 51.402 1.00 0.00 H \nATOM 4251 HD23 LEU A 357 -13.206 23.904 52.394 1.00 0.00 H \nATOM 4252 N MET A 358 -10.114 22.142 48.656 1.00 0.00 N \nATOM 4253 CA MET A 358 -9.836 20.955 47.858 1.00 0.00 C \nATOM 4254 C MET A 358 -9.052 19.925 48.655 1.00 0.00 C \nATOM 4255 O MET A 358 -9.404 18.740 48.673 1.00 0.00 O \nATOM 4256 CB MET A 358 -9.064 21.331 46.600 1.00 0.00 C \nATOM 4257 CG MET A 358 -8.851 20.161 45.675 1.00 0.00 C \nATOM 4258 SD MET A 358 -8.288 20.689 44.063 1.00 0.00 S \nATOM 4259 CE MET A 358 -6.526 20.417 44.196 1.00 0.00 C \nATOM 4260 H MET A 358 -9.740 22.864 48.375 1.00 0.00 H \nATOM 4261 HA MET A 358 -10.687 20.562 47.606 1.00 0.00 H \nATOM 4262 HB2 MET A 358 -9.544 22.029 46.127 1.00 0.00 H \nATOM 4263 HB3 MET A 358 -8.203 21.700 46.852 1.00 0.00 H \nATOM 4264 HG2 MET A 358 -8.200 19.555 46.063 1.00 0.00 H \nATOM 4265 HG3 MET A 358 -9.680 19.666 45.583 1.00 0.00 H \nATOM 4266 HE1 MET A 358 -6.095 20.671 43.365 1.00 0.00 H \nATOM 4267 HE2 MET A 358 -6.170 20.953 44.922 1.00 0.00 H \nATOM 4268 HE3 MET A 358 -6.356 19.479 44.374 1.00 0.00 H \nATOM 4269 N ARG A 359 -7.973 20.356 49.313 1.00 0.00 N \nATOM 4270 CA ARG A 359 -7.203 19.408 50.102 1.00 0.00 C \nATOM 4271 C ARG A 359 -8.000 18.901 51.293 1.00 0.00 C \nATOM 4272 O ARG A 359 -7.927 17.711 51.610 1.00 0.00 O \nATOM 4273 CB ARG A 359 -5.886 20.041 50.550 1.00 0.00 C \nATOM 4274 CG ARG A 359 -4.910 20.272 49.406 1.00 0.00 C \nATOM 4275 CD ARG A 359 -3.635 20.956 49.866 1.00 0.00 C \nATOM 4276 NE ARG A 359 -3.630 22.376 49.527 1.00 0.00 N \nATOM 4277 CZ ARG A 359 -2.531 23.095 49.323 1.00 0.00 C \nATOM 4278 NH1 ARG A 359 -1.335 22.529 49.418 1.00 0.00 N \nATOM 4279 NH2 ARG A 359 -2.626 24.382 49.020 1.00 0.00 N \nATOM 4280 H ARG A 359 -7.682 21.165 49.314 1.00 0.00 H \nATOM 4281 HA ARG A 359 -7.002 18.641 49.543 1.00 0.00 H \nATOM 4282 HB2 ARG A 359 -6.073 20.888 50.984 1.00 0.00 H \nATOM 4283 HB3 ARG A 359 -5.468 19.469 51.213 1.00 0.00 H \nATOM 4284 HG2 ARG A 359 -4.688 19.421 48.996 1.00 0.00 H \nATOM 4285 HG3 ARG A 359 -5.337 20.813 48.724 1.00 0.00 H \nATOM 4286 HD2 ARG A 359 -3.540 20.852 50.826 1.00 0.00 H \nATOM 4287 HD3 ARG A 359 -2.870 20.523 49.457 1.00 0.00 H \nATOM 4288 HE ARG A 359 -4.389 22.774 49.454 1.00 0.00 H \nATOM 4289 HH11 ARG A 359 -1.269 21.694 49.612 1.00 0.00 H \nATOM 4290 HH12 ARG A 359 -0.626 22.997 49.285 1.00 0.00 H \nATOM 4291 HH21 ARG A 359 -3.399 24.753 48.955 1.00 0.00 H \nATOM 4292 HH22 ARG A 359 -1.914 24.846 48.888 1.00 0.00 H \nATOM 4293 N LEU A 360 -8.830 19.757 51.900 1.00 0.00 N \nATOM 4294 CA LEU A 360 -9.651 19.318 53.026 1.00 0.00 C \nATOM 4295 C LEU A 360 -10.593 18.195 52.615 1.00 0.00 C \nATOM 4296 O LEU A 360 -10.739 17.200 53.338 1.00 0.00 O \nATOM 4297 CB LEU A 360 -10.442 20.494 53.595 1.00 0.00 C \nATOM 4298 CG LEU A 360 -11.635 20.136 54.486 1.00 0.00 C \nATOM 4299 CD1 LEU A 360 -11.184 19.429 55.761 1.00 0.00 C \nATOM 4300 CD2 LEU A 360 -12.465 21.366 54.815 1.00 0.00 C \nATOM 4301 H LEU A 360 -8.929 20.582 51.677 1.00 0.00 H \nATOM 4302 HA LEU A 360 -9.059 18.975 53.714 1.00 0.00 H \nATOM 4303 HB2 LEU A 360 -9.835 21.051 54.107 1.00 0.00 H \nATOM 4304 HB3 LEU A 360 -10.764 21.032 52.855 1.00 0.00 H \nATOM 4305 HG LEU A 360 -12.195 19.521 53.987 1.00 0.00 H \nATOM 4306 HD11 LEU A 360 -11.959 19.215 56.304 1.00 0.00 H \nATOM 4307 HD12 LEU A 360 -10.716 18.611 55.530 1.00 0.00 H \nATOM 4308 HD13 LEU A 360 -10.590 20.011 56.261 1.00 0.00 H \nATOM 4309 HD21 LEU A 360 -13.212 21.111 55.379 1.00 0.00 H \nATOM 4310 HD22 LEU A 360 -11.914 22.013 55.282 1.00 0.00 H \nATOM 4311 HD23 LEU A 360 -12.800 21.760 53.994 1.00 0.00 H \nATOM 4312 N ALA A 361 -11.239 18.333 51.454 1.00 0.00 N \nATOM 4313 CA ALA A 361 -12.086 17.255 50.960 1.00 0.00 C \nATOM 4314 C ALA A 361 -11.273 15.996 50.694 1.00 0.00 C \nATOM 4315 O ALA A 361 -11.775 14.880 50.880 1.00 0.00 O \nATOM 4316 CB ALA A 361 -12.820 17.700 49.696 1.00 0.00 C \nATOM 4317 H ALA A 361 -11.200 19.029 50.950 1.00 0.00 H \nATOM 4318 HA ALA A 361 -12.741 17.045 51.644 1.00 0.00 H \nATOM 4319 HB1 ALA A 361 -13.381 16.976 49.375 1.00 0.00 H \nATOM 4320 HB2 ALA A 361 -13.372 18.472 49.897 1.00 0.00 H \nATOM 4321 HB3 ALA A 361 -12.174 17.935 49.012 1.00 0.00 H \nATOM 4322 N LEU A 362 -10.022 16.153 50.252 1.00 0.00 N \nATOM 4323 CA LEU A 362 -9.158 14.996 50.040 1.00 0.00 C \nATOM 4324 C LEU A 362 -8.859 14.279 51.354 1.00 0.00 C \nATOM 4325 O LEU A 362 -8.756 13.047 51.384 1.00 0.00 O \nATOM 4326 CB LEU A 362 -7.861 15.423 49.345 1.00 0.00 C \nATOM 4327 CG LEU A 362 -7.786 15.281 47.820 1.00 0.00 C \nATOM 4328 CD1 LEU A 362 -6.351 15.454 47.337 1.00 0.00 C \nATOM 4329 CD2 LEU A 362 -8.358 13.946 47.352 1.00 0.00 C \nATOM 4330 H LEU A 362 -9.661 16.912 50.072 1.00 0.00 H \nATOM 4331 HA LEU A 362 -9.626 14.370 49.466 1.00 0.00 H \nATOM 4332 HB2 LEU A 362 -7.697 16.353 49.566 1.00 0.00 H \nATOM 4333 HB3 LEU A 362 -7.134 14.908 49.728 1.00 0.00 H \nATOM 4334 HG LEU A 362 -8.330 15.983 47.430 1.00 0.00 H \nATOM 4335 HD11 LEU A 362 -6.321 15.361 46.372 1.00 0.00 H \nATOM 4336 HD12 LEU A 362 -6.029 16.334 47.587 1.00 0.00 H \nATOM 4337 HD13 LEU A 362 -5.788 14.777 47.744 1.00 0.00 H \nATOM 4338 HD21 LEU A 362 -8.296 13.888 46.386 1.00 0.00 H \nATOM 4339 HD22 LEU A 362 -7.855 13.220 47.752 1.00 0.00 H \nATOM 4340 HD23 LEU A 362 -9.288 13.880 47.620 1.00 0.00 H \nATOM 4341 N LYS A 363 -8.712 15.027 52.452 1.00 0.00 N \nATOM 4342 CA LYS A 363 -8.369 14.409 53.729 1.00 0.00 C \nATOM 4343 C LYS A 363 -9.574 13.812 54.443 1.00 0.00 C \nATOM 4344 O LYS A 363 -9.389 13.107 55.441 1.00 0.00 O \nATOM 4345 CB LYS A 363 -7.703 15.421 54.672 1.00 0.00 C \nATOM 4346 CG LYS A 363 -6.842 16.472 54.001 1.00 0.00 C \nATOM 4347 CD LYS A 363 -5.475 16.632 54.649 1.00 0.00 C \nATOM 4348 CE LYS A 363 -4.598 17.570 53.839 1.00 0.00 C \nATOM 4349 NZ LYS A 363 -4.644 17.232 52.389 1.00 0.00 N \nATOM 4350 H LYS A 363 -8.806 15.882 52.476 1.00 0.00 H \nATOM 4351 HA LYS A 363 -7.753 13.691 53.513 1.00 0.00 H \nATOM 4352 HB2 LYS A 363 -8.396 15.870 55.180 1.00 0.00 H \nATOM 4353 HB3 LYS A 363 -7.155 14.935 55.308 1.00 0.00 H \nATOM 4354 HG2 LYS A 363 -6.725 16.237 53.067 1.00 0.00 H \nATOM 4355 HG3 LYS A 363 -7.306 17.324 54.024 1.00 0.00 H \nATOM 4356 HD2 LYS A 363 -5.578 16.977 55.550 1.00 0.00 H \nATOM 4357 HD3 LYS A 363 -5.045 15.766 54.724 1.00 0.00 H \nATOM 4358 HE2 LYS A 363 -4.892 18.485 53.970 1.00 0.00 H \nATOM 4359 HE3 LYS A 363 -3.683 17.517 54.157 1.00 0.00 H \nATOM 4360 HZ1 LYS A 363 -3.982 17.649 51.965 1.00 0.00 H \nATOM 4361 HZ2 LYS A 363 -4.554 16.353 52.286 1.00 0.00 H \nATOM 4362 HZ3 LYS A 363 -5.424 17.492 52.048 1.00 0.00 H \nATOM 4363 N LYS A 364 -10.792 14.071 53.969 1.00 0.00 N \nATOM 4364 CA LYS A 364 -11.991 13.538 54.601 1.00 0.00 C \nATOM 4365 C LYS A 364 -12.571 12.342 53.857 1.00 0.00 C \nATOM 4366 O LYS A 364 -13.697 11.928 54.153 1.00 0.00 O \nATOM 4367 CB LYS A 364 -13.049 14.634 54.738 1.00 0.00 C \nATOM 4368 CG LYS A 364 -12.647 15.767 55.668 1.00 0.00 C \nATOM 4369 CD LYS A 364 -13.834 16.660 55.983 1.00 0.00 C \nATOM 4370 CE LYS A 364 -14.909 15.891 56.732 1.00 0.00 C \nATOM 4371 NZ LYS A 364 -16.068 16.754 57.087 1.00 0.00 N \nATOM 4372 H LYS A 364 -10.943 14.558 53.276 1.00 0.00 H \nATOM 4373 HA LYS A 364 -11.728 13.224 55.480 1.00 0.00 H \nATOM 4374 HB2 LYS A 364 -13.238 15.000 53.860 1.00 0.00 H \nATOM 4375 HB3 LYS A 364 -13.872 14.237 55.063 1.00 0.00 H \nATOM 4376 HG2 LYS A 364 -12.286 15.402 56.491 1.00 0.00 H \nATOM 4377 HG3 LYS A 364 -11.943 16.293 55.257 1.00 0.00 H \nATOM 4378 HD2 LYS A 364 -13.542 17.416 56.516 1.00 0.00 H \nATOM 4379 HD3 LYS A 364 -14.202 17.018 55.160 1.00 0.00 H \nATOM 4380 HE2 LYS A 364 -15.214 15.149 56.186 1.00 0.00 H \nATOM 4381 HE3 LYS A 364 -14.530 15.511 57.540 1.00 0.00 H \nATOM 4382 HZ1 LYS A 364 -16.796 16.250 57.181 1.00 0.00 H \nATOM 4383 HZ2 LYS A 364 -15.900 17.177 57.852 1.00 0.00 H \nATOM 4384 HZ3 LYS A 364 -16.203 17.351 56.441 1.00 0.00 H \nATOM 4385 N GLY A 365 -11.829 11.772 52.913 1.00 0.00 N \nATOM 4386 CA GLY A 365 -12.257 10.560 52.243 1.00 0.00 C \nATOM 4387 C GLY A 365 -13.182 10.767 51.061 1.00 0.00 C \nATOM 4388 O GLY A 365 -14.229 10.118 50.967 1.00 0.00 O \nATOM 4389 H GLY A 365 -11.070 12.077 52.648 1.00 0.00 H \nATOM 4390 HA2 GLY A 365 -11.470 10.081 51.939 1.00 0.00 H \nATOM 4391 HA3 GLY A 365 -12.704 9.991 52.889 1.00 0.00 H \nATOM 4392 N SER A 366 -12.816 11.672 50.159 1.00 0.00 N \nATOM 4393 CA SER A 366 -13.562 11.904 48.928 1.00 0.00 C \nATOM 4394 C SER A 366 -12.829 11.211 47.784 1.00 0.00 C \nATOM 4395 O SER A 366 -11.656 11.505 47.524 1.00 0.00 O \nATOM 4396 CB SER A 366 -13.718 13.400 48.651 1.00 0.00 C \nATOM 4397 OG SER A 366 -14.623 13.630 47.583 1.00 0.00 O \nATOM 4398 H SER A 366 -12.122 12.173 50.245 1.00 0.00 H \nATOM 4399 HA SER A 366 -14.456 11.538 49.015 1.00 0.00 H \nATOM 4400 HB2 SER A 366 -14.036 13.849 49.450 1.00 0.00 H \nATOM 4401 HB3 SER A 366 -12.854 13.784 48.435 1.00 0.00 H \nATOM 4402 HG SER A 366 -14.573 14.433 47.341 1.00 0.00 H \nATOM 4403 N GLU A 367 -13.515 10.290 47.108 1.00 0.00 N \nATOM 4404 CA GLU A 367 -12.924 9.505 46.031 1.00 0.00 C \nATOM 4405 C GLU A 367 -13.134 10.111 44.648 1.00 0.00 C \nATOM 4406 O GLU A 367 -12.596 9.578 43.669 1.00 0.00 O \nATOM 4407 CB GLU A 367 -13.499 8.084 46.048 1.00 0.00 C \nATOM 4408 CG GLU A 367 -13.271 7.337 47.355 1.00 0.00 C \nATOM 4409 CD GLU A 367 -13.737 5.893 47.293 1.00 0.00 C \nATOM 4410 OE1 GLU A 367 -14.957 5.664 47.152 1.00 0.00 O \nATOM 4411 OE2 GLU A 367 -12.881 4.989 47.385 1.00 0.00 O \nATOM 4412 H GLU A 367 -14.340 10.104 47.264 1.00 0.00 H \nATOM 4413 HA GLU A 367 -11.968 9.496 46.195 1.00 0.00 H \nATOM 4414 HB2 GLU A 367 -14.452 8.129 45.874 1.00 0.00 H \nATOM 4415 HB3 GLU A 367 -13.102 7.576 45.323 1.00 0.00 H \nATOM 4416 HG2 GLU A 367 -12.327 7.359 47.575 1.00 0.00 H \nATOM 4417 HG3 GLU A 367 -13.740 7.794 48.071 1.00 0.00 H \nATOM 4418 N ASP A 368 -13.892 11.198 44.545 1.00 0.00 N \nATOM 4419 CA ASP A 368 -14.293 11.765 43.267 1.00 0.00 C \nATOM 4420 C ASP A 368 -13.301 12.827 42.793 1.00 0.00 C \nATOM 4421 O ASP A 368 -12.394 13.245 43.519 1.00 0.00 O \nATOM 4422 CB ASP A 368 -15.695 12.364 43.377 1.00 0.00 C \nATOM 4423 CG ASP A 368 -16.343 12.592 42.024 1.00 0.00 C \nATOM 4424 OD1 ASP A 368 -15.740 12.214 40.998 1.00 0.00 O \nATOM 4425 OD2 ASP A 368 -17.451 13.164 41.989 1.00 0.00 O \nATOM 4426 H ASP A 368 -14.191 11.631 45.225 1.00 0.00 H \nATOM 4427 HA ASP A 368 -14.301 11.051 42.611 1.00 0.00 H \nATOM 4428 HB2 ASP A 368 -16.255 11.772 43.904 1.00 0.00 H \nATOM 4429 HB3 ASP A 368 -15.646 13.207 43.854 1.00 0.00 H \nATOM 4430 N ASN A 369 -13.472 13.249 41.540 1.00 0.00 N \nATOM 4431 CA ASN A 369 -12.853 14.487 41.086 1.00 0.00 C \nATOM 4432 C ASN A 369 -13.297 15.637 41.981 1.00 0.00 C \nATOM 4433 O ASN A 369 -14.441 15.672 42.446 1.00 0.00 O \nATOM 4434 CB ASN A 369 -13.236 14.776 39.631 1.00 0.00 C \nATOM 4435 CG ASN A 369 -12.696 13.741 38.657 1.00 0.00 C \nATOM 4436 OD1 ASN A 369 -13.151 13.653 37.514 1.00 0.00 O \nATOM 4437 ND2 ASN A 369 -11.718 12.959 39.101 1.00 0.00 N \nATOM 4438 H ASN A 369 -13.937 12.837 40.946 1.00 0.00 H \nATOM 4439 HA ASN A 369 -11.889 14.394 41.136 1.00 0.00 H \nATOM 4440 HB2 ASN A 369 -14.203 14.809 39.557 1.00 0.00 H \nATOM 4441 HB3 ASN A 369 -12.902 15.652 39.382 1.00 0.00 H \nATOM 4442 HD21 ASN A 369 -11.377 12.362 38.584 1.00 0.00 H \nATOM 4443 HD22 ASN A 369 -11.426 13.050 39.905 1.00 0.00 H \nATOM 4444 N ILE A 370 -12.396 16.591 42.210 1.00 0.00 N \nATOM 4445 CA ILE A 370 -12.684 17.750 43.041 1.00 0.00 C \nATOM 4446 C ILE A 370 -12.446 19.004 42.213 1.00 0.00 C \nATOM 4447 O ILE A 370 -11.427 19.111 41.519 1.00 0.00 O \nATOM 4448 CB ILE A 370 -11.809 17.777 44.313 1.00 0.00 C \nATOM 4449 CG1 ILE A 370 -11.690 16.405 45.000 1.00 0.00 C \nATOM 4450 CG2 ILE A 370 -12.345 18.785 45.303 1.00 0.00 C \nATOM 4451 CD1 ILE A 370 -12.861 15.990 45.837 1.00 0.00 C \nATOM 4452 H ILE A 370 -11.600 16.581 41.885 1.00 0.00 H \nATOM 4453 HA ILE A 370 -13.608 17.705 43.333 1.00 0.00 H \nATOM 4454 HB ILE A 370 -10.920 18.032 44.020 1.00 0.00 H \nATOM 4455 HG12 ILE A 370 -11.548 15.731 44.317 1.00 0.00 H \nATOM 4456 HG13 ILE A 370 -10.899 16.411 45.561 1.00 0.00 H \nATOM 4457 HG21 ILE A 370 -11.785 18.790 46.095 1.00 0.00 H \nATOM 4458 HG22 ILE A 370 -12.342 19.667 44.900 1.00 0.00 H \nATOM 4459 HG23 ILE A 370 -13.252 18.546 45.550 1.00 0.00 H \nATOM 4460 HD11 ILE A 370 -12.689 15.117 46.224 1.00 0.00 H \nATOM 4461 HD12 ILE A 370 -12.997 16.637 46.547 1.00 0.00 H \nATOM 4462 HD13 ILE A 370 -13.656 15.947 45.283 1.00 0.00 H \nATOM 4463 N THR A 371 -13.393 19.937 42.265 1.00 0.00 N \nATOM 4464 CA THR A 371 -13.244 21.235 41.621 1.00 0.00 C \nATOM 4465 C THR A 371 -13.911 22.259 42.518 1.00 0.00 C \nATOM 4466 O THR A 371 -15.096 22.127 42.829 1.00 0.00 O \nATOM 4467 CB THR A 371 -13.853 21.252 40.217 1.00 0.00 C \nATOM 4468 OG1 THR A 371 -13.088 20.393 39.364 1.00 0.00 O \nATOM 4469 CG2 THR A 371 -13.820 22.659 39.654 1.00 0.00 C \nATOM 4470 H THR A 371 -14.141 19.833 42.676 1.00 0.00 H \nATOM 4471 HA THR A 371 -12.303 21.440 41.504 1.00 0.00 H \nATOM 4472 HB THR A 371 -14.772 20.946 40.265 1.00 0.00 H \nATOM 4473 HG1 THR A 371 -12.477 20.027 39.810 1.00 0.00 H \nATOM 4474 HG21 THR A 371 -14.207 22.661 38.765 1.00 0.00 H \nATOM 4475 HG22 THR A 371 -14.330 23.250 40.230 1.00 0.00 H \nATOM 4476 HG23 THR A 371 -12.902 22.967 39.607 1.00 0.00 H \nATOM 4477 N VAL A 372 -13.155 23.264 42.944 1.00 0.00 N \nATOM 4478 CA VAL A 372 -13.653 24.289 43.849 1.00 0.00 C \nATOM 4479 C VAL A 372 -13.333 25.653 43.255 1.00 0.00 C \nATOM 4480 O VAL A 372 -12.179 25.931 42.913 1.00 0.00 O \nATOM 4481 CB VAL A 372 -13.044 24.162 45.260 1.00 0.00 C \nATOM 4482 CG1 VAL A 372 -13.595 25.249 46.171 1.00 0.00 C \nATOM 4483 CG2 VAL A 372 -13.324 22.786 45.847 1.00 0.00 C \nATOM 4484 H VAL A 372 -12.333 23.370 42.714 1.00 0.00 H \nATOM 4485 HA VAL A 372 -14.612 24.178 43.947 1.00 0.00 H \nATOM 4486 HB VAL A 372 -12.083 24.272 45.189 1.00 0.00 H \nATOM 4487 HG11 VAL A 372 -13.205 25.159 47.055 1.00 0.00 H \nATOM 4488 HG12 VAL A 372 -13.372 26.120 45.807 1.00 0.00 H \nATOM 4489 HG13 VAL A 372 -14.559 25.162 46.233 1.00 0.00 H \nATOM 4490 HG21 VAL A 372 -12.934 22.726 46.733 1.00 0.00 H \nATOM 4491 HG22 VAL A 372 -14.282 22.648 45.907 1.00 0.00 H \nATOM 4492 HG23 VAL A 372 -12.935 22.105 45.276 1.00 0.00 H \nATOM 4493 N ILE A 373 -14.352 26.497 43.136 1.00 0.00 N \nATOM 4494 CA ILE A 373 -14.183 27.908 42.819 1.00 0.00 C \nATOM 4495 C ILE A 373 -14.646 28.713 44.023 1.00 0.00 C \nATOM 4496 O ILE A 373 -15.777 28.541 44.494 1.00 0.00 O \nATOM 4497 CB ILE A 373 -14.966 28.309 41.556 1.00 0.00 C \nATOM 4498 CG1 ILE A 373 -14.408 27.595 40.324 1.00 0.00 C \nATOM 4499 CG2 ILE A 373 -14.916 29.817 41.361 1.00 0.00 C \nATOM 4500 CD1 ILE A 373 -15.138 27.936 39.044 1.00 0.00 C \nATOM 4501 H ILE A 373 -15.173 26.262 43.239 1.00 0.00 H \nATOM 4502 HA ILE A 373 -13.249 28.088 42.629 1.00 0.00 H \nATOM 4503 HB ILE A 373 -15.891 28.040 41.671 1.00 0.00 H \nATOM 4504 HG12 ILE A 373 -13.471 27.824 40.224 1.00 0.00 H \nATOM 4505 HG13 ILE A 373 -14.452 26.637 40.467 1.00 0.00 H \nATOM 4506 HG21 ILE A 373 -15.412 30.057 40.563 1.00 0.00 H \nATOM 4507 HG22 ILE A 373 -15.310 30.256 42.131 1.00 0.00 H \nATOM 4508 HG23 ILE A 373 -13.993 30.101 41.265 1.00 0.00 H \nATOM 4509 HD11 ILE A 373 -14.737 27.453 38.304 1.00 0.00 H \nATOM 4510 HD12 ILE A 373 -16.071 27.684 39.126 1.00 0.00 H \nATOM 4511 HD13 ILE A 373 -15.074 28.890 38.879 1.00 0.00 H \nATOM 4512 N VAL A 374 -13.776 29.586 44.518 1.00 0.00 N \nATOM 4513 CA VAL A 374 -14.111 30.516 45.589 1.00 0.00 C \nATOM 4514 C VAL A 374 -14.061 31.917 45.005 1.00 0.00 C \nATOM 4515 O VAL A 374 -13.022 32.342 44.488 1.00 0.00 O \nATOM 4516 CB VAL A 374 -13.158 30.379 46.786 1.00 0.00 C \nATOM 4517 CG1 VAL A 374 -13.392 31.506 47.787 1.00 0.00 C \nATOM 4518 CG2 VAL A 374 -13.329 29.019 47.451 1.00 0.00 C \nATOM 4519 H VAL A 374 -12.966 29.656 44.238 1.00 0.00 H \nATOM 4520 HA VAL A 374 -14.998 30.320 45.930 1.00 0.00 H \nATOM 4521 HB VAL A 374 -12.246 30.446 46.463 1.00 0.00 H \nATOM 4522 HG11 VAL A 374 -12.784 31.406 48.536 1.00 0.00 H \nATOM 4523 HG12 VAL A 374 -13.235 32.360 47.355 1.00 0.00 H \nATOM 4524 HG13 VAL A 374 -14.307 31.470 48.107 1.00 0.00 H \nATOM 4525 HG21 VAL A 374 -12.721 28.948 48.204 1.00 0.00 H \nATOM 4526 HG22 VAL A 374 -14.242 28.924 47.763 1.00 0.00 H \nATOM 4527 HG23 VAL A 374 -13.132 28.318 46.810 1.00 0.00 H \nATOM 4528 N VAL A 375 -15.177 32.633 45.087 1.00 0.00 N \nATOM 4529 CA VAL A 375 -15.274 34.002 44.597 1.00 0.00 C \nATOM 4530 C VAL A 375 -15.431 34.912 45.804 1.00 0.00 C \nATOM 4531 O VAL A 375 -16.411 34.801 46.550 1.00 0.00 O \nATOM 4532 CB VAL A 375 -16.444 34.173 43.618 1.00 0.00 C \nATOM 4533 CG1 VAL A 375 -16.395 35.547 42.968 1.00 0.00 C \nATOM 4534 CG2 VAL A 375 -16.425 33.067 42.568 1.00 0.00 C \nATOM 4535 H VAL A 375 -15.906 32.335 45.432 1.00 0.00 H \nATOM 4536 HA VAL A 375 -14.472 34.232 44.102 1.00 0.00 H \nATOM 4537 HB VAL A 375 -17.276 34.104 44.111 1.00 0.00 H \nATOM 4538 HG11 VAL A 375 -17.139 35.641 42.353 1.00 0.00 H \nATOM 4539 HG12 VAL A 375 -16.454 36.231 43.653 1.00 0.00 H \nATOM 4540 HG13 VAL A 375 -15.561 35.646 42.483 1.00 0.00 H \nATOM 4541 HG21 VAL A 375 -17.169 33.188 41.957 1.00 0.00 H \nATOM 4542 HG22 VAL A 375 -15.591 33.105 42.073 1.00 0.00 H \nATOM 4543 HG23 VAL A 375 -16.503 32.204 43.005 1.00 0.00 H \nATOM 4544 N ASP A 376 -14.474 35.814 45.994 1.00 0.00 N \nATOM 4545 CA ASP A 376 -14.517 36.739 47.119 1.00 0.00 C \nATOM 4546 C ASP A 376 -15.401 37.925 46.758 1.00 0.00 C \nATOM 4547 O ASP A 376 -15.084 38.687 45.837 1.00 0.00 O \nATOM 4548 CB ASP A 376 -13.108 37.200 47.486 1.00 0.00 C \nATOM 4549 CG ASP A 376 -13.083 38.062 48.733 1.00 0.00 C \nATOM 4550 OD1 ASP A 376 -14.110 38.124 49.442 1.00 0.00 O \nATOM 4551 OD2 ASP A 376 -12.034 38.682 49.005 1.00 0.00 O \nATOM 4552 H ASP A 376 -13.790 35.906 45.481 1.00 0.00 H \nATOM 4553 HA ASP A 376 -14.891 36.290 47.893 1.00 0.00 H \nATOM 4554 HB2 ASP A 376 -12.543 36.424 47.622 1.00 0.00 H \nATOM 4555 HB3 ASP A 376 -12.731 37.699 46.744 1.00 0.00 H \nATOM 4556 N LEU A 377 -16.506 38.079 47.479 1.00 0.00 N \nATOM 4557 CA LEU A 377 -17.464 39.140 47.201 1.00 0.00 C \nATOM 4558 C LEU A 377 -17.158 40.386 48.026 1.00 0.00 C \nATOM 4559 O LEU A 377 -17.627 41.480 47.711 1.00 0.00 O \nATOM 4560 CB LEU A 377 -18.891 38.661 47.477 1.00 0.00 C \nATOM 4561 CG LEU A 377 -19.433 37.586 46.532 1.00 0.00 C \nATOM 4562 CD1 LEU A 377 -20.827 37.146 46.952 1.00 0.00 C \nATOM 4563 CD2 LEU A 377 -19.428 38.084 45.093 1.00 0.00 C \nATOM 4564 H LEU A 377 -16.720 37.573 48.141 1.00 0.00 H \nATOM 4565 HA LEU A 377 -17.388 39.371 46.262 1.00 0.00 H \nATOM 4566 HB2 LEU A 377 -18.928 38.318 48.384 1.00 0.00 H \nATOM 4567 HB3 LEU A 377 -19.484 39.428 47.439 1.00 0.00 H \nATOM 4568 HG LEU A 377 -18.849 36.813 46.586 1.00 0.00 H \nATOM 4569 HD11 LEU A 377 -21.150 36.466 46.340 1.00 0.00 H \nATOM 4570 HD12 LEU A 377 -20.795 36.783 47.851 1.00 0.00 H \nATOM 4571 HD13 LEU A 377 -21.427 37.908 46.933 1.00 0.00 H \nATOM 4572 HD21 LEU A 377 -19.774 37.391 44.509 1.00 0.00 H \nATOM 4573 HD22 LEU A 377 -19.986 38.874 45.022 1.00 0.00 H \nATOM 4574 HD23 LEU A 377 -18.521 38.304 44.830 1.00 0.00 H \nATOM 4575 N VAL C 34 -38.148 -17.706 17.338 1.00 0.00 N \nATOM 4576 CA VAL C 34 -36.736 -17.593 17.682 1.00 0.00 C \nATOM 4577 C VAL C 34 -36.579 -17.235 19.152 1.00 0.00 C \nATOM 4578 O VAL C 34 -35.726 -16.430 19.517 1.00 0.00 O \nATOM 4579 CB VAL C 34 -36.027 -16.566 16.792 1.00 0.00 C \nATOM 4580 CG1 VAL C 34 -35.637 -17.192 15.460 1.00 0.00 C \nATOM 4581 CG2 VAL C 34 -36.916 -15.349 16.580 1.00 0.00 C \nATOM 4582 HA VAL C 34 -36.317 -18.454 17.526 1.00 0.00 H \nATOM 4583 HB VAL C 34 -35.215 -16.277 17.237 1.00 0.00 H \nATOM 4584 HG11 VAL C 34 -35.190 -16.530 14.910 1.00 0.00 H \nATOM 4585 HG12 VAL C 34 -35.038 -17.939 15.616 1.00 0.00 H \nATOM 4586 HG13 VAL C 34 -36.434 -17.506 15.004 1.00 0.00 H \nATOM 4587 HG21 VAL C 34 -36.457 -14.707 16.016 1.00 0.00 H \nATOM 4588 HG22 VAL C 34 -37.742 -15.622 16.152 1.00 0.00 H \nATOM 4589 HG23 VAL C 34 -37.116 -14.941 17.437 1.00 0.00 H \nATOM 4590 N ARG C 35 -37.401 -17.867 19.995 1.00 0.00 N \nATOM 4591 CA ARG C 35 -37.257 -17.794 21.444 1.00 0.00 C \nATOM 4592 C ARG C 35 -37.209 -19.182 22.071 1.00 0.00 C \nATOM 4593 O ARG C 35 -37.413 -19.322 23.282 1.00 0.00 O \nATOM 4594 CB ARG C 35 -38.345 -16.933 22.086 1.00 0.00 C \nATOM 4595 CG ARG C 35 -38.623 -15.650 21.328 1.00 0.00 C \nATOM 4596 CD ARG C 35 -40.095 -15.392 21.301 1.00 0.00 C \nATOM 4597 NE ARG C 35 -40.625 -15.468 22.655 1.00 0.00 N \nATOM 4598 CZ ARG C 35 -41.915 -15.555 22.951 1.00 0.00 C \nATOM 4599 NH1 ARG C 35 -42.814 -15.584 21.980 1.00 0.00 N \nATOM 4600 NH2 ARG C 35 -42.304 -15.619 24.217 1.00 0.00 N \nATOM 4601 H ARG C 35 -38.062 -18.353 19.736 1.00 0.00 H \nATOM 4602 HA ARG C 35 -36.408 -17.360 21.621 1.00 0.00 H \nATOM 4603 HB2 ARG C 35 -39.164 -17.450 22.145 1.00 0.00 H \nATOM 4604 HB3 ARG C 35 -38.081 -16.714 22.993 1.00 0.00 H \nATOM 4605 HG2 ARG C 35 -38.163 -14.908 21.751 1.00 0.00 H \nATOM 4606 HG3 ARG C 35 -38.281 -15.718 20.423 1.00 0.00 H \nATOM 4607 HD2 ARG C 35 -40.273 -14.517 20.922 1.00 0.00 H \nATOM 4608 HD3 ARG C 35 -40.537 -16.042 20.733 1.00 0.00 H \nATOM 4609 HE ARG C 35 -40.064 -15.456 23.307 1.00 0.00 H \nATOM 4610 HH11 ARG C 35 -42.561 -15.546 21.159 1.00 0.00 H \nATOM 4611 HH12 ARG C 35 -43.651 -15.640 22.170 1.00 0.00 H \nATOM 4612 HH21 ARG C 35 -41.720 -15.604 24.848 1.00 0.00 H \nATOM 4613 HH22 ARG C 35 -43.141 -15.675 24.407 1.00 0.00 H \nATOM 4614 N ARG C 36 -36.969 -20.209 21.253 1.00 0.00 N \nATOM 4615 CA ARG C 36 -36.479 -21.469 21.791 1.00 0.00 C \nATOM 4616 C ARG C 36 -35.223 -21.205 22.610 1.00 0.00 C \nATOM 4617 O ARG C 36 -34.947 -21.913 23.585 1.00 0.00 O \nATOM 4618 CB ARG C 36 -36.200 -22.443 20.644 1.00 0.00 C \nATOM 4619 CG ARG C 36 -35.239 -23.576 20.961 1.00 0.00 C \nATOM 4620 CD ARG C 36 -35.805 -24.905 20.506 1.00 0.00 C \nATOM 4621 NE ARG C 36 -34.989 -26.030 20.948 1.00 0.00 N \nATOM 4622 CZ ARG C 36 -35.486 -27.153 21.453 1.00 0.00 C \nATOM 4623 NH1 ARG C 36 -36.798 -27.303 21.565 1.00 0.00 N \nATOM 4624 NH2 ARG C 36 -34.675 -28.131 21.836 1.00 0.00 N \nATOM 4625 H ARG C 36 -37.082 -20.194 20.401 1.00 0.00 H \nATOM 4626 HA ARG C 36 -37.146 -21.870 22.370 1.00 0.00 H \nATOM 4627 HB2 ARG C 36 -37.043 -22.827 20.355 1.00 0.00 H \nATOM 4628 HB3 ARG C 36 -35.845 -21.941 19.894 1.00 0.00 H \nATOM 4629 HG2 ARG C 36 -34.388 -23.416 20.524 1.00 0.00 H \nATOM 4630 HG3 ARG C 36 -35.067 -23.603 21.915 1.00 0.00 H \nATOM 4631 HD2 ARG C 36 -36.706 -25.006 20.850 1.00 0.00 H \nATOM 4632 HD3 ARG C 36 -35.868 -24.914 19.538 1.00 0.00 H \nATOM 4633 HE ARG C 36 -34.135 -25.962 20.877 1.00 0.00 H \nATOM 4634 HH11 ARG C 36 -37.326 -26.674 21.311 1.00 0.00 H \nATOM 4635 HH12 ARG C 36 -37.121 -28.030 21.892 1.00 0.00 H \nATOM 4636 HH21 ARG C 36 -33.824 -28.039 21.758 1.00 0.00 H \nATOM 4637 HH22 ARG C 36 -35.001 -28.857 22.163 1.00 0.00 H \nATOM 4638 N PHE C 37 -34.466 -20.171 22.235 1.00 0.00 N \nATOM 4639 CA PHE C 37 -33.256 -19.773 22.936 1.00 0.00 C \nATOM 4640 C PHE C 37 -33.520 -18.734 24.016 1.00 0.00 C \nATOM 4641 O PHE C 37 -32.653 -18.519 24.870 1.00 0.00 O \nATOM 4642 CB PHE C 37 -32.238 -19.199 21.945 1.00 0.00 C \nATOM 4643 CG PHE C 37 -31.769 -20.184 20.923 1.00 0.00 C \nATOM 4644 CD1 PHE C 37 -31.077 -21.318 21.305 1.00 0.00 C \nATOM 4645 CD2 PHE C 37 -32.028 -19.980 19.579 1.00 0.00 C \nATOM 4646 CE1 PHE C 37 -30.643 -22.229 20.365 1.00 0.00 C \nATOM 4647 CE2 PHE C 37 -31.598 -20.889 18.632 1.00 0.00 C \nATOM 4648 CZ PHE C 37 -30.905 -22.015 19.027 1.00 0.00 C \nATOM 4649 H PHE C 37 -34.649 -19.677 21.555 1.00 0.00 H \nATOM 4650 HA PHE C 37 -32.908 -20.571 23.363 1.00 0.00 H \nATOM 4651 HB2 PHE C 37 -32.634 -18.439 21.491 1.00 0.00 H \nATOM 4652 HB3 PHE C 37 -31.471 -18.867 22.438 1.00 0.00 H \nATOM 4653 HD1 PHE C 37 -30.902 -21.468 22.206 1.00 0.00 H \nATOM 4654 HD2 PHE C 37 -32.497 -19.223 19.311 1.00 0.00 H \nATOM 4655 HE1 PHE C 37 -30.174 -22.987 20.632 1.00 0.00 H \nATOM 4656 HE2 PHE C 37 -31.775 -20.743 17.731 1.00 0.00 H \nATOM 4657 HZ PHE C 37 -30.615 -22.629 18.392 1.00 0.00 H \nATOM 4658 N HIS C 38 -34.686 -18.079 24.002 1.00 0.00 N \nATOM 4659 CA HIS C 38 -34.948 -16.966 24.908 1.00 0.00 C \nATOM 4660 C HIS C 38 -36.200 -17.193 25.746 1.00 0.00 C \nATOM 4661 O HIS C 38 -36.806 -16.228 26.223 1.00 0.00 O \nATOM 4662 CB HIS C 38 -35.079 -15.655 24.131 1.00 0.00 C \nATOM 4663 CG HIS C 38 -33.938 -15.384 23.202 1.00 0.00 C \nATOM 4664 ND1 HIS C 38 -32.749 -14.829 23.622 1.00 0.00 N \nATOM 4665 CD2 HIS C 38 -33.808 -15.587 21.870 1.00 0.00 C \nATOM 4666 CE1 HIS C 38 -31.935 -14.704 22.589 1.00 0.00 C \nATOM 4667 NE2 HIS C 38 -32.553 -15.157 21.514 1.00 0.00 N \nATOM 4668 H HIS C 38 -35.337 -18.268 23.472 1.00 0.00 H \nATOM 4669 HA HIS C 38 -34.190 -16.909 25.511 1.00 0.00 H \nATOM 4670 HB2 HIS C 38 -35.903 -15.673 23.620 1.00 0.00 H \nATOM 4671 HB3 HIS C 38 -35.152 -14.922 24.762 1.00 0.00 H \nATOM 4672 HD1 HIS C 38 -32.565 -14.600 24.430 1.00 0.00 H \nATOM 4673 HD2 HIS C 38 -34.449 -15.950 21.302 1.00 0.00 H \nATOM 4674 HE1 HIS C 38 -31.073 -14.356 22.615 1.00 0.00 H \nATOM 4675 HE2 HIS C 38 -32.223 -15.179 20.720 1.00 0.00 H \nATOM 4676 N ARG C 39 -36.592 -18.448 25.947 1.00 0.00 N \nATOM 4677 CA ARG C 39 -37.640 -18.781 26.898 1.00 0.00 C \nATOM 4678 C ARG C 39 -36.969 -19.120 28.218 1.00 0.00 C \nATOM 4679 O ARG C 39 -36.033 -19.926 28.257 1.00 0.00 O \nATOM 4680 CB ARG C 39 -38.501 -19.944 26.406 1.00 0.00 C \nATOM 4681 CG ARG C 39 -39.859 -19.518 25.859 1.00 0.00 C \nATOM 4682 CD ARG C 39 -40.859 -19.239 26.974 1.00 0.00 C \nATOM 4683 NE ARG C 39 -41.921 -18.329 26.544 1.00 0.00 N \nATOM 4684 CZ ARG C 39 -42.917 -17.914 27.321 1.00 0.00 C \nATOM 4685 NH1 ARG C 39 -43.835 -17.087 26.839 1.00 0.00 N \nATOM 4686 NH2 ARG C 39 -42.999 -18.327 28.580 1.00 0.00 N \nATOM 4687 H ARG C 39 -36.258 -19.126 25.536 1.00 0.00 H \nATOM 4688 HA ARG C 39 -38.239 -18.026 27.005 1.00 0.00 H \nATOM 4689 HB2 ARG C 39 -38.018 -20.422 25.713 1.00 0.00 H \nATOM 4690 HB3 ARG C 39 -38.637 -20.566 27.138 1.00 0.00 H \nATOM 4691 HG2 ARG C 39 -39.753 -18.723 25.314 1.00 0.00 H \nATOM 4692 HG3 ARG C 39 -40.207 -20.214 25.280 1.00 0.00 H \nATOM 4693 HD2 ARG C 39 -41.251 -20.075 27.272 1.00 0.00 H \nATOM 4694 HD3 ARG C 39 -40.395 -18.856 27.735 1.00 0.00 H \nATOM 4695 HE ARG C 39 -41.900 -18.043 25.733 1.00 0.00 H \nATOM 4696 HH11 ARG C 39 -43.786 -16.819 26.023 1.00 0.00 H \nATOM 4697 HH12 ARG C 39 -44.479 -16.819 27.342 1.00 0.00 H \nATOM 4698 HH21 ARG C 39 -42.407 -18.865 28.896 1.00 0.00 H \nATOM 4699 HH22 ARG C 39 -43.644 -18.057 29.080 1.00 0.00 H \nATOM 4700 N HIS C 40 -37.441 -18.507 29.292 1.00 0.00 N \nATOM 4701 CA HIS C 40 -36.831 -18.677 30.597 1.00 0.00 C \nATOM 4702 C HIS C 40 -37.891 -19.028 31.626 1.00 0.00 C \nATOM 4703 O HIS C 40 -39.052 -18.625 31.508 1.00 0.00 O \nATOM 4704 CB HIS C 40 -36.089 -17.414 31.029 1.00 0.00 C \nATOM 4705 CG HIS C 40 -35.012 -16.988 30.080 1.00 0.00 C \nATOM 4706 ND1 HIS C 40 -33.857 -17.715 29.891 1.00 0.00 N \nATOM 4707 CD2 HIS C 40 -34.908 -15.901 29.277 1.00 0.00 C \nATOM 4708 CE1 HIS C 40 -33.092 -17.101 29.007 1.00 0.00 C \nATOM 4709 NE2 HIS C 40 -33.706 -15.997 28.620 1.00 0.00 N \nATOM 4710 H HIS C 40 -38.122 -17.982 29.284 1.00 0.00 H \nATOM 4711 HA HIS C 40 -36.188 -19.401 30.535 1.00 0.00 H \nATOM 4712 HB2 HIS C 40 -36.728 -16.691 31.124 1.00 0.00 H \nATOM 4713 HB3 HIS C 40 -35.697 -17.563 31.904 1.00 0.00 H \nATOM 4714 HD1 HIS C 40 -33.664 -18.454 30.287 1.00 0.00 H \nATOM 4715 HD2 HIS C 40 -35.533 -15.218 29.188 1.00 0.00 H \nATOM 4716 HE1 HIS C 40 -32.262 -17.396 28.708 1.00 0.00 H \nATOM 4717 HE2 HIS C 40 -33.402 -15.430 28.049 1.00 0.00 H \nATOM 4718 N GLU C 41 -37.483 -19.791 32.633 1.00 0.00 N \nATOM 4719 CA GLU C 41 -38.373 -20.083 33.745 1.00 0.00 C \nATOM 4720 C GLU C 41 -37.831 -19.422 35.005 1.00 0.00 C \nATOM 4721 O GLU C 41 -37.166 -20.078 35.818 1.00 0.00 O \nATOM 4722 CB GLU C 41 -38.516 -21.591 33.949 1.00 0.00 C \nATOM 4723 CG GLU C 41 -38.911 -22.351 32.696 1.00 0.00 C \nATOM 4724 CD GLU C 41 -37.752 -23.122 32.098 1.00 0.00 C \nATOM 4725 OE1 GLU C 41 -36.903 -23.615 32.872 1.00 0.00 O \nATOM 4726 OE2 GLU C 41 -37.686 -23.233 30.855 1.00 0.00 O \nATOM 4727 H GLU C 41 -36.702 -20.146 32.691 1.00 0.00 H \nATOM 4728 HA GLU C 41 -39.254 -19.729 33.547 1.00 0.00 H \nATOM 4729 HB2 GLU C 41 -37.675 -21.944 34.278 1.00 0.00 H \nATOM 4730 HB3 GLU C 41 -39.180 -21.753 34.637 1.00 0.00 H \nATOM 4731 HG2 GLU C 41 -39.631 -22.966 32.907 1.00 0.00 H \nATOM 4732 HG3 GLU C 41 -39.255 -21.727 32.038 1.00 0.00 H \nATOM 4733 N PRO C 42 -38.080 -18.129 35.197 1.00 0.00 N \nATOM 4734 CA PRO C 42 -37.633 -17.471 36.426 1.00 0.00 C \nATOM 4735 C PRO C 42 -38.415 -17.981 37.623 1.00 0.00 C \nATOM 4736 O PRO C 42 -39.605 -18.290 37.537 1.00 0.00 O \nATOM 4737 CB PRO C 42 -37.917 -15.987 36.163 1.00 0.00 C \nATOM 4738 CG PRO C 42 -39.023 -15.998 35.169 1.00 0.00 C \nATOM 4739 CD PRO C 42 -38.774 -17.194 34.296 1.00 0.00 C \nATOM 4740 HA PRO C 42 -36.700 -17.640 36.632 1.00 0.00 H \nATOM 4741 HB2 PRO C 42 -38.176 -15.526 36.976 1.00 0.00 H \nATOM 4742 HB3 PRO C 42 -37.133 -15.532 35.816 1.00 0.00 H \nATOM 4743 HG2 PRO C 42 -39.885 -16.061 35.608 1.00 0.00 H \nATOM 4744 HG3 PRO C 42 -39.030 -15.181 34.647 1.00 0.00 H \nATOM 4745 HD2 PRO C 42 -39.602 -17.570 33.958 1.00 0.00 H \nATOM 4746 HD3 PRO C 42 -38.230 -16.968 33.525 1.00 0.00 H \nATOM 4747 N ARG C 43 -37.724 -18.075 38.753 1.00 0.00 N \nATOM 4748 CA ARG C 43 -38.378 -18.428 40.001 1.00 0.00 C \nATOM 4749 C ARG C 43 -39.220 -17.246 40.493 1.00 0.00 C \nATOM 4750 O ARG C 43 -39.332 -16.208 39.834 1.00 0.00 O \nATOM 4751 CB ARG C 43 -37.342 -18.884 41.023 1.00 0.00 C \nATOM 4752 CG ARG C 43 -36.510 -20.077 40.567 1.00 0.00 C \nATOM 4753 CD ARG C 43 -37.380 -21.164 39.947 1.00 0.00 C \nATOM 4754 NE ARG C 43 -38.111 -21.930 40.953 1.00 0.00 N \nATOM 4755 CZ ARG C 43 -38.885 -22.976 40.680 1.00 0.00 C \nATOM 4756 NH1 ARG C 43 -39.036 -23.382 39.427 1.00 0.00 N \nATOM 4757 NH2 ARG C 43 -39.512 -23.613 41.659 1.00 0.00 N \nATOM 4758 H ARG C 43 -36.877 -17.938 38.816 1.00 0.00 H \nATOM 4759 HA ARG C 43 -38.983 -19.174 39.863 1.00 0.00 H \nATOM 4760 HB2 ARG C 43 -36.748 -18.143 41.221 1.00 0.00 H \nATOM 4761 HB3 ARG C 43 -37.795 -19.113 41.850 1.00 0.00 H \nATOM 4762 HG2 ARG C 43 -35.849 -19.783 39.921 1.00 0.00 H \nATOM 4763 HG3 ARG C 43 -36.025 -20.442 41.323 1.00 0.00 H \nATOM 4764 HD2 ARG C 43 -38.010 -20.759 39.331 1.00 0.00 H \nATOM 4765 HD3 ARG C 43 -36.823 -21.765 39.428 1.00 0.00 H \nATOM 4766 HE ARG C 43 -38.036 -21.689 41.775 1.00 0.00 H \nATOM 4767 HH11 ARG C 43 -38.633 -22.969 38.790 1.00 0.00 H \nATOM 4768 HH12 ARG C 43 -39.537 -24.059 39.252 1.00 0.00 H \nATOM 4769 HH21 ARG C 43 -39.418 -23.350 42.472 1.00 0.00 H \nATOM 4770 HH22 ARG C 43 -40.012 -24.289 41.481 1.00 0.00 H \nATOM 4771 N ASP C 44 -39.822 -17.402 41.675 1.00 0.00 N \nATOM 4772 CA ASP C 44 -40.648 -16.336 42.238 1.00 0.00 C \nATOM 4773 C ASP C 44 -39.860 -15.086 42.614 1.00 0.00 C \nATOM 4774 O ASP C 44 -40.445 -13.999 42.654 1.00 0.00 O \nATOM 4775 CB ASP C 44 -41.406 -16.859 43.456 1.00 0.00 C \nATOM 4776 CG ASP C 44 -42.516 -17.815 43.077 1.00 0.00 C \nATOM 4777 OD1 ASP C 44 -43.269 -17.504 42.129 1.00 0.00 O \nATOM 4778 OD2 ASP C 44 -42.635 -18.878 43.721 1.00 0.00 O \nATOM 4779 H ASP C 44 -39.765 -18.110 42.160 1.00 0.00 H \nATOM 4780 HA ASP C 44 -41.267 -16.069 41.541 1.00 0.00 H \nATOM 4781 HB2 ASP C 44 -40.786 -17.307 44.052 1.00 0.00 H \nATOM 4782 HB3 ASP C 44 -41.780 -16.111 43.947 1.00 0.00 H \nATOM 4783 N HIS C 45 -38.568 -15.205 42.910 1.00 0.00 N \nATOM 4784 CA HIS C 45 -37.762 -14.069 43.339 1.00 0.00 C \nATOM 4785 C HIS C 45 -36.723 -13.711 42.283 1.00 0.00 C \nATOM 4786 O HIS C 45 -35.693 -13.103 42.593 1.00 0.00 O \nATOM 4787 CB HIS C 45 -37.125 -14.338 44.701 1.00 0.00 C \nATOM 4788 CG HIS C 45 -38.123 -14.398 45.816 1.00 0.00 C \nATOM 4789 ND1 HIS C 45 -38.610 -15.587 46.316 1.00 0.00 N \nATOM 4790 CD2 HIS C 45 -38.753 -13.416 46.502 1.00 0.00 C \nATOM 4791 CE1 HIS C 45 -39.481 -15.334 47.276 1.00 0.00 C \nATOM 4792 NE2 HIS C 45 -39.587 -14.024 47.409 1.00 0.00 N \nATOM 4793 H HIS C 45 -38.136 -15.947 42.867 1.00 0.00 H \nATOM 4794 HA HIS C 45 -38.344 -13.300 43.441 1.00 0.00 H \nATOM 4795 HB2 HIS C 45 -36.639 -15.176 44.664 1.00 0.00 H \nATOM 4796 HB3 HIS C 45 -36.477 -13.642 44.892 1.00 0.00 H \nATOM 4797 HD1 HIS C 45 -38.382 -16.371 46.045 1.00 0.00 H \nATOM 4798 HD2 HIS C 45 -38.642 -12.500 46.382 1.00 0.00 H \nATOM 4799 HE1 HIS C 45 -39.942 -15.970 47.774 1.00 0.00 H \nATOM 4800 HE2 HIS C 45 -40.095 -13.618 47.972 1.00 0.00 H \nATOM 4801 N GLN C 46 -36.994 -14.092 41.039 1.00 0.00 N \nATOM 4802 CA GLN C 46 -36.199 -13.782 39.865 1.00 0.00 C \nATOM 4803 C GLN C 46 -37.088 -13.069 38.858 1.00 0.00 C \nATOM 4804 O GLN C 46 -38.318 -13.145 38.924 1.00 0.00 O \nATOM 4805 CB GLN C 46 -35.629 -15.047 39.208 1.00 0.00 C \nATOM 4806 CG GLN C 46 -34.532 -15.745 39.973 1.00 0.00 C \nATOM 4807 CD GLN C 46 -34.052 -16.998 39.265 1.00 0.00 C \nATOM 4808 OE1 GLN C 46 -34.850 -17.753 38.705 1.00 0.00 O \nATOM 4809 NE2 GLN C 46 -32.743 -17.221 39.275 1.00 0.00 N \nATOM 4810 H GLN C 46 -37.687 -14.565 40.851 1.00 0.00 H \nATOM 4811 HA GLN C 46 -35.454 -13.225 40.140 1.00 0.00 H \nATOM 4812 HB2 GLN C 46 -36.355 -15.675 39.071 1.00 0.00 H \nATOM 4813 HB3 GLN C 46 -35.289 -14.811 38.331 1.00 0.00 H \nATOM 4814 HG2 GLN C 46 -33.786 -15.137 40.094 1.00 0.00 H \nATOM 4815 HG3 GLN C 46 -34.854 -15.978 40.858 1.00 0.00 H \nATOM 4816 HE21 GLN C 46 -32.216 -16.672 39.676 1.00 0.00 H \nATOM 4817 HE22 GLN C 46 -32.422 -17.914 38.880 1.00 0.00 H \nATOM 4818 N CYS C 47 -36.457 -12.368 37.924 1.00 0.00 N \nATOM 4819 CA CYS C 47 -37.177 -11.729 36.838 1.00 0.00 C \nATOM 4820 C CYS C 47 -36.451 -12.012 35.532 1.00 0.00 C \nATOM 4821 O CYS C 47 -35.248 -12.286 35.509 1.00 0.00 O \nATOM 4822 CB CYS C 47 -37.309 -10.216 37.053 1.00 0.00 C \nATOM 4823 SG CYS C 47 -35.743 -9.329 36.982 1.00 0.00 S \nATOM 4824 H CYS C 47 -35.605 -12.251 37.904 1.00 0.00 H \nATOM 4825 HA CYS C 47 -38.075 -12.093 36.808 1.00 0.00 H \nATOM 4826 HB2 CYS C 47 -37.907 -9.854 36.380 1.00 0.00 H \nATOM 4827 HB3 CYS C 47 -37.722 -10.056 37.916 1.00 0.00 H \nATOM 4828 HG CYS C 47 -34.885 -10.063 36.577 1.00 0.00 H \nATOM 4829 N SER C 48 -37.203 -11.940 34.439 1.00 0.00 N \nATOM 4830 CA SER C 48 -36.686 -12.286 33.125 1.00 0.00 C \nATOM 4831 C SER C 48 -37.316 -11.367 32.094 1.00 0.00 C \nATOM 4832 O SER C 48 -38.475 -10.966 32.226 1.00 0.00 O \nATOM 4833 CB SER C 48 -36.973 -13.749 32.772 1.00 0.00 C \nATOM 4834 OG SER C 48 -36.346 -14.119 31.555 1.00 0.00 O \nATOM 4835 H SER C 48 -38.026 -11.689 34.440 1.00 0.00 H \nATOM 4836 HA SER C 48 -35.723 -12.174 33.131 1.00 0.00 H \nATOM 4837 HB2 SER C 48 -36.659 -14.324 33.488 1.00 0.00 H \nATOM 4838 HB3 SER C 48 -37.931 -13.884 32.699 1.00 0.00 H \nATOM 4839 HG SER C 48 -35.512 -14.115 31.657 1.00 0.00 H \nATOM 4840 N SER C 49 -36.540 -11.032 31.069 1.00 0.00 N \nATOM 4841 CA SER C 49 -37.045 -10.219 29.972 1.00 0.00 C \nATOM 4842 C SER C 49 -36.099 -10.353 28.787 1.00 0.00 C \nATOM 4843 O SER C 49 -35.098 -11.072 28.838 1.00 0.00 O \nATOM 4844 CB SER C 49 -37.204 -8.757 30.390 1.00 0.00 C \nATOM 4845 OG SER C 49 -38.257 -8.143 29.668 1.00 0.00 O \nATOM 4846 H SER C 49 -35.716 -11.266 30.991 1.00 0.00 H \nATOM 4847 HA SER C 49 -37.926 -10.535 29.719 1.00 0.00 H \nATOM 4848 HB2 SER C 49 -37.385 -8.705 31.342 1.00 0.00 H \nATOM 4849 HB3 SER C 49 -36.375 -8.278 30.232 1.00 0.00 H \nATOM 4850 HG SER C 49 -38.765 -7.740 30.202 1.00 0.00 H \nATOM 4851 N ALA C 50 -36.429 -9.640 27.714 1.00 0.00 N \nATOM 4852 CA ALA C 50 -35.646 -9.661 26.491 1.00 0.00 C \nATOM 4853 C ALA C 50 -35.738 -8.297 25.826 1.00 0.00 C \nATOM 4854 O ALA C 50 -36.685 -7.538 26.047 1.00 0.00 O \nATOM 4855 CB ALA C 50 -36.121 -10.757 25.531 1.00 0.00 C \nATOM 4856 H ALA C 50 -37.119 -9.128 27.678 1.00 0.00 H \nATOM 4857 HA ALA C 50 -34.724 -9.860 26.716 1.00 0.00 H \nATOM 4858 HB1 ALA C 50 -35.577 -10.742 24.728 1.00 0.00 H \nATOM 4859 HB2 ALA C 50 -36.038 -11.622 25.961 1.00 0.00 H \nATOM 4860 HB3 ALA C 50 -37.049 -10.601 25.296 1.00 0.00 H \nATOM 4861 N VAL C 51 -34.732 -7.990 25.014 1.00 0.00 N \nATOM 4862 CA VAL C 51 -34.718 -6.795 24.184 1.00 0.00 C \nATOM 4863 C VAL C 51 -34.269 -7.207 22.791 1.00 0.00 C \nATOM 4864 O VAL C 51 -33.500 -8.159 22.624 1.00 0.00 O \nATOM 4865 CB VAL C 51 -33.799 -5.689 24.751 1.00 0.00 C \nATOM 4866 CG1 VAL C 51 -34.358 -5.146 26.059 1.00 0.00 C \nATOM 4867 CG2 VAL C 51 -32.388 -6.217 24.945 1.00 0.00 C \nATOM 4868 H VAL C 51 -34.029 -8.478 24.930 1.00 0.00 H \nATOM 4869 HA VAL C 51 -35.610 -6.413 24.163 1.00 0.00 H \nATOM 4870 HB VAL C 51 -33.765 -4.960 24.112 1.00 0.00 H \nATOM 4871 HG11 VAL C 51 -33.770 -4.454 26.400 1.00 0.00 H \nATOM 4872 HG12 VAL C 51 -35.240 -4.773 25.904 1.00 0.00 H \nATOM 4873 HG13 VAL C 51 -34.421 -5.865 26.707 1.00 0.00 H \nATOM 4874 HG21 VAL C 51 -31.825 -5.512 25.301 1.00 0.00 H \nATOM 4875 HG22 VAL C 51 -32.404 -6.962 25.566 1.00 0.00 H \nATOM 4876 HG23 VAL C 51 -32.033 -6.514 24.092 1.00 0.00 H \nATOM 4877 N ALA C 52 -34.761 -6.490 21.785 1.00 0.00 N \nATOM 4878 CA ALA C 52 -34.438 -6.789 20.400 1.00 0.00 C \nATOM 4879 C ALA C 52 -34.054 -5.511 19.670 1.00 0.00 C \nATOM 4880 O ALA C 52 -34.403 -4.402 20.084 1.00 0.00 O \nATOM 4881 CB ALA C 52 -35.613 -7.469 19.683 1.00 0.00 C \nATOM 4882 H ALA C 52 -35.289 -5.819 21.888 1.00 0.00 H \nATOM 4883 HA ALA C 52 -33.688 -7.404 20.394 1.00 0.00 H \nATOM 4884 HB1 ALA C 52 -35.367 -7.655 18.763 1.00 0.00 H \nATOM 4885 HB2 ALA C 52 -35.830 -8.300 20.134 1.00 0.00 H \nATOM 4886 HB3 ALA C 52 -36.385 -6.882 19.698 1.00 0.00 H \nATOM 4887 N LYS C 53 -33.324 -5.681 18.568 1.00 0.00 N \nATOM 4888 CA LYS C 53 -32.881 -4.545 17.770 1.00 0.00 C \nATOM 4889 C LYS C 53 -32.631 -5.006 16.343 1.00 0.00 C \nATOM 4890 O LYS C 53 -31.978 -6.032 16.126 1.00 0.00 O \nATOM 4891 CB LYS C 53 -31.613 -3.919 18.361 1.00 0.00 C \nATOM 4892 CG LYS C 53 -31.041 -2.780 17.537 1.00 0.00 C \nATOM 4893 CD LYS C 53 -31.740 -1.468 17.852 1.00 0.00 C \nATOM 4894 CE LYS C 53 -31.499 -0.441 16.757 1.00 0.00 C \nATOM 4895 NZ LYS C 53 -32.262 0.814 16.991 1.00 0.00 N \nATOM 4896 H LYS C 53 -33.076 -6.448 18.267 1.00 0.00 H \nATOM 4897 HA LYS C 53 -33.574 -3.866 17.775 1.00 0.00 H \nATOM 4898 HB2 LYS C 53 -31.811 -3.592 19.253 1.00 0.00 H \nATOM 4899 HB3 LYS C 53 -30.937 -4.608 18.455 1.00 0.00 H \nATOM 4900 HG2 LYS C 53 -30.091 -2.694 17.715 1.00 0.00 H \nATOM 4901 HG3 LYS C 53 -31.136 -2.981 16.593 1.00 0.00 H \nATOM 4902 HD2 LYS C 53 -32.693 -1.622 17.951 1.00 0.00 H \nATOM 4903 HD3 LYS C 53 -31.419 -1.123 18.700 1.00 0.00 H \nATOM 4904 HE2 LYS C 53 -30.552 -0.238 16.708 1.00 0.00 H \nATOM 4905 HE3 LYS C 53 -31.753 -0.818 15.900 1.00 0.00 H \nATOM 4906 HZ1 LYS C 53 -32.412 1.220 16.213 1.00 0.00 H \nATOM 4907 HZ2 LYS C 53 -33.039 0.621 17.380 1.00 0.00 H \nATOM 4908 HZ3 LYS C 53 -31.792 1.353 17.520 1.00 0.00 H \nATOM 4909 N HIS C 54 -33.152 -4.249 15.381 1.00 0.00 N \nATOM 4910 CA HIS C 54 -32.937 -4.505 13.963 1.00 0.00 C \nATOM 4911 C HIS C 54 -31.785 -3.638 13.473 1.00 0.00 C \nATOM 4912 O HIS C 54 -31.785 -2.422 13.686 1.00 0.00 O \nATOM 4913 CB HIS C 54 -34.208 -4.228 13.160 1.00 0.00 C \nATOM 4914 CG HIS C 54 -35.396 -5.015 13.625 1.00 0.00 C \nATOM 4915 ND1 HIS C 54 -35.844 -6.145 12.976 1.00 0.00 N \nATOM 4916 CD2 HIS C 54 -36.224 -4.837 14.682 1.00 0.00 C \nATOM 4917 CE1 HIS C 54 -36.899 -6.626 13.610 1.00 0.00 C \nATOM 4918 NE2 HIS C 54 -37.150 -5.851 14.649 1.00 0.00 N \nATOM 4919 H HIS C 54 -33.647 -3.563 15.538 1.00 0.00 H \nATOM 4920 HA HIS C 54 -32.712 -5.440 13.836 1.00 0.00 H \nATOM 4921 HB2 HIS C 54 -34.415 -3.282 13.213 1.00 0.00 H \nATOM 4922 HB3 HIS C 54 -34.042 -4.430 12.226 1.00 0.00 H \nATOM 4923 HD1 HIS C 54 -35.492 -6.484 12.269 1.00 0.00 H \nATOM 4924 HD2 HIS C 54 -36.175 -4.155 15.313 1.00 0.00 H \nATOM 4925 HE1 HIS C 54 -37.383 -7.382 13.366 1.00 0.00 H \nATOM 4926 HE2 HIS C 54 -37.789 -5.963 15.213 1.00 0.00 H \nATOM 4927 N ILE C 55 -30.807 -4.263 12.823 1.00 0.00 N \nATOM 4928 CA ILE C 55 -29.574 -3.599 12.418 1.00 0.00 C \nATOM 4929 C ILE C 55 -29.434 -3.708 10.906 1.00 0.00 C \nATOM 4930 O ILE C 55 -29.532 -4.805 10.345 1.00 0.00 O \nATOM 4931 CB ILE C 55 -28.348 -4.207 13.124 1.00 0.00 C \nATOM 4932 CG1 ILE C 55 -28.564 -4.223 14.640 1.00 0.00 C \nATOM 4933 CG2 ILE C 55 -27.084 -3.440 12.752 1.00 0.00 C \nATOM 4934 CD1 ILE C 55 -27.303 -4.462 15.444 1.00 0.00 C \nATOM 4935 H ILE C 55 -30.842 -5.094 12.603 1.00 0.00 H \nATOM 4936 HA ILE C 55 -29.617 -2.666 12.678 1.00 0.00 H \nATOM 4937 HB ILE C 55 -28.236 -5.124 12.827 1.00 0.00 H \nATOM 4938 HG12 ILE C 55 -28.952 -3.376 14.910 1.00 0.00 H \nATOM 4939 HG13 ILE C 55 -29.210 -4.913 14.857 1.00 0.00 H \nATOM 4940 HG21 ILE C 55 -26.321 -3.834 13.204 1.00 0.00 H \nATOM 4941 HG22 ILE C 55 -26.949 -3.484 11.792 1.00 0.00 H \nATOM 4942 HG23 ILE C 55 -27.176 -2.513 13.023 1.00 0.00 H \nATOM 4943 HD11 ILE C 55 -27.517 -4.459 16.390 1.00 0.00 H \nATOM 4944 HD12 ILE C 55 -26.923 -5.321 15.202 1.00 0.00 H \nATOM 4945 HD13 ILE C 55 -26.661 -3.760 15.256 1.00 0.00 H \nATOM 4946 N LYS C 56 -29.197 -2.571 10.252 1.00 0.00 N \nATOM 4947 CA LYS C 56 -29.028 -2.525 8.800 1.00 0.00 C \nATOM 4948 C LYS C 56 -27.574 -2.849 8.454 1.00 0.00 C \nATOM 4949 O LYS C 56 -26.783 -2.005 8.030 1.00 0.00 O \nATOM 4950 CB LYS C 56 -29.450 -1.168 8.254 1.00 0.00 C \nATOM 4951 CG LYS C 56 -30.957 -0.996 8.146 1.00 0.00 C \nATOM 4952 CD LYS C 56 -31.478 -0.001 9.168 1.00 0.00 C \nATOM 4953 CE LYS C 56 -31.414 1.420 8.638 1.00 0.00 C \nATOM 4954 NZ LYS C 56 -32.112 2.378 9.538 1.00 0.00 N \nATOM 4955 H LYS C 56 -29.130 -1.805 10.638 1.00 0.00 H \nATOM 4956 HA LYS C 56 -29.599 -3.188 8.382 1.00 0.00 H \nATOM 4957 HB2 LYS C 56 -29.093 -0.472 8.828 1.00 0.00 H \nATOM 4958 HB3 LYS C 56 -29.054 -1.044 7.377 1.00 0.00 H \nATOM 4959 HG2 LYS C 56 -31.186 -0.694 7.253 1.00 0.00 H \nATOM 4960 HG3 LYS C 56 -31.392 -1.853 8.276 1.00 0.00 H \nATOM 4961 HD2 LYS C 56 -32.394 -0.221 9.399 1.00 0.00 H \nATOM 4962 HD3 LYS C 56 -30.956 -0.068 9.983 1.00 0.00 H \nATOM 4963 HE2 LYS C 56 -30.487 1.687 8.539 1.00 0.00 H \nATOM 4964 HE3 LYS C 56 -31.815 1.454 7.756 1.00 0.00 H \nATOM 4965 HZ1 LYS C 56 -32.338 3.106 9.079 1.00 0.00 H \nATOM 4966 HZ2 LYS C 56 -32.845 1.996 9.867 1.00 0.00 H \nATOM 4967 HZ3 LYS C 56 -31.571 2.605 10.207 1.00 0.00 H \nATOM 4968 N ALA C 57 -27.235 -4.121 8.645 1.00 0.00 N \nATOM 4969 CA ALA C 57 -25.909 -4.651 8.362 1.00 0.00 C \nATOM 4970 C ALA C 57 -26.022 -6.163 8.285 1.00 0.00 C \nATOM 4971 O ALA C 57 -26.883 -6.747 8.954 1.00 0.00 O \nATOM 4972 CB ALA C 57 -24.902 -4.243 9.445 1.00 0.00 C \nATOM 4973 H ALA C 57 -27.782 -4.711 8.949 1.00 0.00 H \nATOM 4974 HA ALA C 57 -25.584 -4.289 7.523 1.00 0.00 H \nATOM 4975 HB1 ALA C 57 -24.030 -4.609 9.231 1.00 0.00 H \nATOM 4976 HB2 ALA C 57 -24.845 -3.276 9.486 1.00 0.00 H \nATOM 4977 HB3 ALA C 57 -25.194 -4.586 10.304 1.00 0.00 H \nATOM 4978 N PRO C 58 -25.188 -6.824 7.488 1.00 0.00 N \nATOM 4979 CA PRO C 58 -25.287 -8.282 7.375 1.00 0.00 C \nATOM 4980 C PRO C 58 -24.905 -8.968 8.678 1.00 0.00 C \nATOM 4981 O PRO C 58 -24.163 -8.436 9.508 1.00 0.00 O \nATOM 4982 CB PRO C 58 -24.300 -8.631 6.255 1.00 0.00 C \nATOM 4983 CG PRO C 58 -23.377 -7.466 6.172 1.00 0.00 C \nATOM 4984 CD PRO C 58 -24.169 -6.262 6.585 1.00 0.00 C \nATOM 4985 HA PRO C 58 -26.191 -8.579 7.184 1.00 0.00 H \nATOM 4986 HB2 PRO C 58 -23.817 -9.448 6.456 1.00 0.00 H \nATOM 4987 HB3 PRO C 58 -24.761 -8.774 5.414 1.00 0.00 H \nATOM 4988 HG2 PRO C 58 -22.611 -7.591 6.754 1.00 0.00 H \nATOM 4989 HG3 PRO C 58 -23.035 -7.361 5.271 1.00 0.00 H \nATOM 4990 HD2 PRO C 58 -23.615 -5.605 7.035 1.00 0.00 H \nATOM 4991 HD3 PRO C 58 -24.572 -5.819 5.822 1.00 0.00 H \nATOM 4992 N VAL C 59 -25.443 -10.176 8.847 1.00 0.00 N \nATOM 4993 CA VAL C 59 -25.285 -10.901 10.106 1.00 0.00 C \nATOM 4994 C VAL C 59 -23.820 -11.229 10.356 1.00 0.00 C \nATOM 4995 O VAL C 59 -23.342 -11.169 11.497 1.00 0.00 O \nATOM 4996 CB VAL C 59 -26.169 -12.160 10.107 1.00 0.00 C \nATOM 4997 CG1 VAL C 59 -25.686 -13.168 11.134 1.00 0.00 C \nATOM 4998 CG2 VAL C 59 -27.579 -11.763 10.420 1.00 0.00 C \nATOM 4999 H VAL C 59 -25.900 -10.591 8.248 1.00 0.00 H \nATOM 5000 HA VAL C 59 -25.579 -10.336 10.838 1.00 0.00 H \nATOM 5001 HB VAL C 59 -26.121 -12.575 9.232 1.00 0.00 H \nATOM 5002 HG11 VAL C 59 -26.259 -13.950 11.114 1.00 0.00 H \nATOM 5003 HG12 VAL C 59 -24.775 -13.430 10.927 1.00 0.00 H \nATOM 5004 HG13 VAL C 59 -25.715 -12.769 12.018 1.00 0.00 H \nATOM 5005 HG21 VAL C 59 -28.144 -12.551 10.423 1.00 0.00 H \nATOM 5006 HG22 VAL C 59 -27.610 -11.340 11.292 1.00 0.00 H \nATOM 5007 HG23 VAL C 59 -27.897 -11.140 9.748 1.00 0.00 H \nATOM 5008 N HIS C 60 -23.085 -11.575 9.296 1.00 0.00 N \nATOM 5009 CA HIS C 60 -21.678 -11.922 9.456 1.00 0.00 C \nATOM 5010 C HIS C 60 -20.892 -10.763 10.056 1.00 0.00 C \nATOM 5011 O HIS C 60 -19.993 -10.974 10.880 1.00 0.00 O \nATOM 5012 CB HIS C 60 -21.085 -12.330 8.107 1.00 0.00 C \nATOM 5013 CG HIS C 60 -19.607 -12.560 8.143 1.00 0.00 C \nATOM 5014 ND1 HIS C 60 -19.044 -13.704 8.668 1.00 0.00 N \nATOM 5015 CD2 HIS C 60 -18.573 -11.790 7.728 1.00 0.00 C \nATOM 5016 CE1 HIS C 60 -17.729 -13.631 8.570 1.00 0.00 C \nATOM 5017 NE2 HIS C 60 -17.417 -12.479 8.004 1.00 0.00 N \nATOM 5018 H HIS C 60 -23.380 -11.614 8.489 1.00 0.00 H \nATOM 5019 HA HIS C 60 -21.615 -12.671 10.069 1.00 0.00 H \nATOM 5020 HB2 HIS C 60 -21.523 -13.140 7.802 1.00 0.00 H \nATOM 5021 HB3 HIS C 60 -21.281 -11.639 7.455 1.00 0.00 H \nATOM 5022 HD1 HIS C 60 -19.481 -14.363 9.007 1.00 0.00 H \nATOM 5023 HD2 HIS C 60 -18.634 -10.951 7.330 1.00 0.00 H \nATOM 5024 HE1 HIS C 60 -17.125 -14.280 8.852 1.00 0.00 H \nATOM 5025 HE2 HIS C 60 -16.619 -12.205 7.836 1.00 0.00 H \nATOM 5026 N LEU C 61 -21.219 -9.529 9.661 1.00 0.00 N \nATOM 5027 CA LEU C 61 -20.529 -8.376 10.228 1.00 0.00 C \nATOM 5028 C LEU C 61 -20.913 -8.157 11.687 1.00 0.00 C \nATOM 5029 O LEU C 61 -20.047 -7.890 12.529 1.00 0.00 O \nATOM 5030 CB LEU C 61 -20.824 -7.122 9.409 1.00 0.00 C \nATOM 5031 CG LEU C 61 -20.133 -5.870 9.954 1.00 0.00 C \nATOM 5032 CD1 LEU C 61 -18.620 -6.029 9.915 1.00 0.00 C \nATOM 5033 CD2 LEU C 61 -20.559 -4.633 9.189 1.00 0.00 C \nATOM 5034 H LEU C 61 -21.824 -9.344 9.079 1.00 0.00 H \nATOM 5035 HA LEU C 61 -19.577 -8.557 10.195 1.00 0.00 H \nATOM 5036 HB2 LEU C 61 -20.541 -7.267 8.493 1.00 0.00 H \nATOM 5037 HB3 LEU C 61 -21.782 -6.973 9.390 1.00 0.00 H \nATOM 5038 HG LEU C 61 -20.406 -5.759 10.878 1.00 0.00 H \nATOM 5039 HD11 LEU C 61 -18.201 -5.227 10.264 1.00 0.00 H \nATOM 5040 HD12 LEU C 61 -18.360 -6.791 10.457 1.00 0.00 H \nATOM 5041 HD13 LEU C 61 -18.333 -6.171 8.999 1.00 0.00 H \nATOM 5042 HD21 LEU C 61 -20.108 -3.856 9.553 1.00 0.00 H \nATOM 5043 HD22 LEU C 61 -20.324 -4.734 8.253 1.00 0.00 H \nATOM 5044 HD23 LEU C 61 -21.519 -4.517 9.270 1.00 0.00 H \nATOM 5045 N VAL C 62 -22.205 -8.266 12.005 1.00 0.00 N \nATOM 5046 CA VAL C 62 -22.655 -8.036 13.374 1.00 0.00 C \nATOM 5047 C VAL C 62 -22.130 -9.123 14.303 1.00 0.00 C \nATOM 5048 O VAL C 62 -21.710 -8.842 15.434 1.00 0.00 O \nATOM 5049 CB VAL C 62 -24.192 -7.941 13.421 1.00 0.00 C \nATOM 5050 CG1 VAL C 62 -24.685 -7.891 14.863 1.00 0.00 C \nATOM 5051 CG2 VAL C 62 -24.668 -6.727 12.642 1.00 0.00 C \nATOM 5052 H VAL C 62 -22.828 -8.470 11.448 1.00 0.00 H \nATOM 5053 HA VAL C 62 -22.295 -7.191 13.685 1.00 0.00 H \nATOM 5054 HB VAL C 62 -24.564 -8.735 13.006 1.00 0.00 H \nATOM 5055 HG11 VAL C 62 -25.653 -7.831 14.872 1.00 0.00 H \nATOM 5056 HG12 VAL C 62 -24.406 -8.695 15.328 1.00 0.00 H \nATOM 5057 HG13 VAL C 62 -24.309 -7.115 15.307 1.00 0.00 H \nATOM 5058 HG21 VAL C 62 -25.636 -6.678 12.679 1.00 0.00 H \nATOM 5059 HG22 VAL C 62 -24.289 -5.923 13.031 1.00 0.00 H \nATOM 5060 HG23 VAL C 62 -24.383 -6.803 11.718 1.00 0.00 H \nATOM 5061 N TRP C 63 -22.146 -10.380 13.848 1.00 0.00 N \nATOM 5062 CA TRP C 63 -21.648 -11.466 14.685 1.00 0.00 C \nATOM 5063 C TRP C 63 -20.148 -11.354 14.921 1.00 0.00 C \nATOM 5064 O TRP C 63 -19.664 -11.721 15.997 1.00 0.00 O \nATOM 5065 CB TRP C 63 -21.976 -12.819 14.060 1.00 0.00 C \nATOM 5066 CG TRP C 63 -21.400 -13.968 14.830 1.00 0.00 C \nATOM 5067 CD1 TRP C 63 -20.452 -14.852 14.401 1.00 0.00 C \nATOM 5068 CD2 TRP C 63 -21.719 -14.344 16.177 1.00 0.00 C \nATOM 5069 NE1 TRP C 63 -20.169 -15.761 15.394 1.00 0.00 N \nATOM 5070 CE2 TRP C 63 -20.933 -15.471 16.493 1.00 0.00 C \nATOM 5071 CE3 TRP C 63 -22.594 -13.839 17.143 1.00 0.00 C \nATOM 5072 CZ2 TRP C 63 -20.997 -16.102 17.734 1.00 0.00 C \nATOM 5073 CZ3 TRP C 63 -22.657 -14.466 18.375 1.00 0.00 C \nATOM 5074 CH2 TRP C 63 -21.863 -15.586 18.660 1.00 0.00 C \nATOM 5075 H TRP C 63 -22.435 -10.618 13.074 1.00 0.00 H \nATOM 5076 HA TRP C 63 -22.093 -11.395 15.544 1.00 0.00 H \nATOM 5077 HB2 TRP C 63 -22.939 -12.921 14.006 1.00 0.00 H \nATOM 5078 HB3 TRP C 63 -21.637 -12.842 13.151 1.00 0.00 H \nATOM 5079 HD1 TRP C 63 -20.055 -14.841 13.560 1.00 0.00 H \nATOM 5080 HE1 TRP C 63 -19.604 -16.407 15.334 1.00 0.00 H \nATOM 5081 HE3 TRP C 63 -23.123 -13.096 16.961 1.00 0.00 H \nATOM 5082 HZ2 TRP C 63 -20.472 -16.845 17.926 1.00 0.00 H \nATOM 5083 HZ3 TRP C 63 -23.236 -14.139 19.025 1.00 0.00 H \nATOM 5084 HH2 TRP C 63 -21.926 -15.987 19.497 1.00 0.00 H \nATOM 5085 N SER C 64 -19.398 -10.853 13.936 1.00 0.00 N \nATOM 5086 CA SER C 64 -17.960 -10.694 14.118 1.00 0.00 C \nATOM 5087 C SER C 64 -17.650 -9.683 15.212 1.00 0.00 C \nATOM 5088 O SER C 64 -16.594 -9.764 15.849 1.00 0.00 O \nATOM 5089 CB SER C 64 -17.297 -10.283 12.801 1.00 0.00 C \nATOM 5090 OG SER C 64 -17.437 -8.895 12.565 1.00 0.00 O \nATOM 5091 H SER C 64 -19.699 -10.604 13.170 1.00 0.00 H \nATOM 5092 HA SER C 64 -17.597 -11.550 14.395 1.00 0.00 H \nATOM 5093 HB2 SER C 64 -16.356 -10.516 12.824 1.00 0.00 H \nATOM 5094 HB3 SER C 64 -17.694 -10.779 12.068 1.00 0.00 H \nATOM 5095 HG SER C 64 -18.233 -8.665 12.706 1.00 0.00 H \nATOM 5096 N LEU C 65 -18.554 -8.728 15.438 1.00 0.00 N \nATOM 5097 CA LEU C 65 -18.403 -7.789 16.543 1.00 0.00 C \nATOM 5098 C LEU C 65 -18.758 -8.437 17.877 1.00 0.00 C \nATOM 5099 O LEU C 65 -18.036 -8.275 18.867 1.00 0.00 O \nATOM 5100 CB LEU C 65 -19.282 -6.557 16.308 1.00 0.00 C \nATOM 5101 CG LEU C 65 -18.773 -5.373 15.478 1.00 0.00 C \nATOM 5102 CD1 LEU C 65 -17.901 -5.816 14.315 1.00 0.00 C \nATOM 5103 CD2 LEU C 65 -19.950 -4.544 14.979 1.00 0.00 C \nATOM 5104 H LEU C 65 -19.260 -8.609 14.962 1.00 0.00 H \nATOM 5105 HA LEU C 65 -17.472 -7.518 16.580 1.00 0.00 H \nATOM 5106 HB2 LEU C 65 -20.100 -6.867 15.889 1.00 0.00 H \nATOM 5107 HB3 LEU C 65 -19.524 -6.210 17.181 1.00 0.00 H \nATOM 5108 HG LEU C 65 -18.217 -4.828 16.056 1.00 0.00 H \nATOM 5109 HD11 LEU C 65 -17.602 -5.038 13.819 1.00 0.00 H \nATOM 5110 HD12 LEU C 65 -17.131 -6.298 14.653 1.00 0.00 H \nATOM 5111 HD13 LEU C 65 -18.413 -6.395 13.729 1.00 0.00 H \nATOM 5112 HD21 LEU C 65 -19.621 -3.797 14.455 1.00 0.00 H \nATOM 5113 HD22 LEU C 65 -20.525 -5.097 14.427 1.00 0.00 H \nATOM 5114 HD23 LEU C 65 -20.455 -4.209 15.737 1.00 0.00 H \nATOM 5115 N VAL C 66 -19.873 -9.172 17.918 1.00 0.00 N \nATOM 5116 CA VAL C 66 -20.355 -9.738 19.175 1.00 0.00 C \nATOM 5117 C VAL C 66 -19.443 -10.859 19.661 1.00 0.00 C \nATOM 5118 O VAL C 66 -19.227 -11.020 20.870 1.00 0.00 O \nATOM 5119 CB VAL C 66 -21.808 -10.221 19.006 1.00 0.00 C \nATOM 5120 CG1 VAL C 66 -22.289 -10.937 20.260 1.00 0.00 C \nATOM 5121 CG2 VAL C 66 -22.719 -9.048 18.665 1.00 0.00 C \nATOM 5122 H VAL C 66 -20.360 -9.352 17.232 1.00 0.00 H \nATOM 5123 HA VAL C 66 -20.339 -9.047 19.856 1.00 0.00 H \nATOM 5124 HB VAL C 66 -21.838 -10.855 18.272 1.00 0.00 H \nATOM 5125 HG11 VAL C 66 -23.204 -11.233 20.133 1.00 0.00 H \nATOM 5126 HG12 VAL C 66 -21.722 -11.705 20.432 1.00 0.00 H \nATOM 5127 HG13 VAL C 66 -22.247 -10.330 21.015 1.00 0.00 H \nATOM 5128 HG21 VAL C 66 -23.630 -9.365 18.561 1.00 0.00 H \nATOM 5129 HG22 VAL C 66 -22.684 -8.393 19.379 1.00 0.00 H \nATOM 5130 HG23 VAL C 66 -22.423 -8.639 17.837 1.00 0.00 H \nATOM 5131 N ARG C 67 -18.890 -11.648 18.734 1.00 0.00 N \nATOM 5132 CA ARG C 67 -18.036 -12.765 19.122 1.00 0.00 C \nATOM 5133 C ARG C 67 -16.785 -12.316 19.868 1.00 0.00 C \nATOM 5134 O ARG C 67 -16.235 -13.096 20.654 1.00 0.00 O \nATOM 5135 CB ARG C 67 -17.663 -13.603 17.901 1.00 0.00 C \nATOM 5136 CG ARG C 67 -16.658 -12.966 16.962 1.00 0.00 C \nATOM 5137 CD ARG C 67 -16.730 -13.615 15.591 1.00 0.00 C \nATOM 5138 NE ARG C 67 -16.259 -14.994 15.615 1.00 0.00 N \nATOM 5139 CZ ARG C 67 -14.997 -15.354 15.408 1.00 0.00 C \nATOM 5140 NH1 ARG C 67 -14.077 -14.431 15.164 1.00 0.00 N \nATOM 5141 NH2 ARG C 67 -14.654 -16.635 15.448 1.00 0.00 N \nATOM 5142 H ARG C 67 -18.997 -11.552 17.886 1.00 0.00 H \nATOM 5143 HA ARG C 67 -18.549 -13.312 19.738 1.00 0.00 H \nATOM 5144 HB2 ARG C 67 -17.306 -14.452 18.206 1.00 0.00 H \nATOM 5145 HB3 ARG C 67 -18.471 -13.798 17.402 1.00 0.00 H \nATOM 5146 HG2 ARG C 67 -16.835 -12.015 16.886 1.00 0.00 H \nATOM 5147 HG3 ARG C 67 -15.763 -13.060 17.324 1.00 0.00 H \nATOM 5148 HD2 ARG C 67 -17.645 -13.592 15.271 1.00 0.00 H \nATOM 5149 HD3 ARG C 67 -16.197 -13.103 14.963 1.00 0.00 H \nATOM 5150 HE ARG C 67 -16.834 -15.614 15.773 1.00 0.00 H \nATOM 5151 HH11 ARG C 67 -14.297 -13.600 15.140 1.00 0.00 H \nATOM 5152 HH12 ARG C 67 -13.260 -14.663 15.030 1.00 0.00 H \nATOM 5153 HH21 ARG C 67 -15.249 -17.235 15.608 1.00 0.00 H \nATOM 5154 HH22 ARG C 67 -13.836 -16.866 15.314 1.00 0.00 H \nATOM 5155 N ARG C 68 -16.323 -11.086 19.648 1.00 0.00 N \nATOM 5156 CA ARG C 68 -15.078 -10.629 20.253 1.00 0.00 C \nATOM 5157 C ARG C 68 -15.293 -10.408 21.746 1.00 0.00 C \nATOM 5158 O ARG C 68 -15.401 -9.271 22.219 1.00 0.00 O \nATOM 5159 CB ARG C 68 -14.574 -9.361 19.563 1.00 0.00 C \nATOM 5160 CG ARG C 68 -13.890 -9.642 18.234 1.00 0.00 C \nATOM 5161 CD ARG C 68 -13.937 -8.450 17.298 1.00 0.00 C \nATOM 5162 NE ARG C 68 -12.992 -7.407 17.684 1.00 0.00 N \nATOM 5163 CZ ARG C 68 -12.717 -6.341 16.940 1.00 0.00 C \nATOM 5164 NH1 ARG C 68 -13.317 -6.180 15.769 1.00 0.00 N \nATOM 5165 NH2 ARG C 68 -11.844 -5.438 17.366 1.00 0.00 N \nATOM 5166 H ARG C 68 -16.716 -10.503 19.152 1.00 0.00 H \nATOM 5167 HA ARG C 68 -14.395 -11.308 20.137 1.00 0.00 H \nATOM 5168 HB2 ARG C 68 -15.321 -8.760 19.416 1.00 0.00 H \nATOM 5169 HB3 ARG C 68 -13.953 -8.904 20.151 1.00 0.00 H \nATOM 5170 HG2 ARG C 68 -12.966 -9.888 18.394 1.00 0.00 H \nATOM 5171 HG3 ARG C 68 -14.316 -10.402 17.808 1.00 0.00 H \nATOM 5172 HD2 ARG C 68 -13.741 -8.743 16.394 1.00 0.00 H \nATOM 5173 HD3 ARG C 68 -14.835 -8.083 17.289 1.00 0.00 H \nATOM 5174 HE ARG C 68 -12.588 -7.487 18.439 1.00 0.00 H \nATOM 5175 HH11 ARG C 68 -13.883 -6.765 15.492 1.00 0.00 H \nATOM 5176 HH12 ARG C 68 -13.140 -5.491 15.286 1.00 0.00 H \nATOM 5177 HH21 ARG C 68 -11.454 -5.542 18.126 1.00 0.00 H \nATOM 5178 HH22 ARG C 68 -11.668 -4.749 16.883 1.00 0.00 H \nATOM 5179 N PHE C 69 -15.359 -11.520 22.482 1.00 0.00 N \nATOM 5180 CA PHE C 69 -15.686 -11.510 23.905 1.00 0.00 C \nATOM 5181 C PHE C 69 -14.710 -10.668 24.716 1.00 0.00 C \nATOM 5182 O PHE C 69 -15.087 -10.113 25.754 1.00 0.00 O \nATOM 5183 CB PHE C 69 -15.707 -12.952 24.419 1.00 0.00 C \nATOM 5184 CG PHE C 69 -16.135 -13.096 25.852 1.00 0.00 C \nATOM 5185 CD1 PHE C 69 -17.458 -12.917 26.218 1.00 0.00 C \nATOM 5186 CD2 PHE C 69 -15.215 -13.442 26.828 1.00 0.00 C \nATOM 5187 CE1 PHE C 69 -17.852 -13.061 27.536 1.00 0.00 C \nATOM 5188 CE2 PHE C 69 -15.604 -13.588 28.146 1.00 0.00 C \nATOM 5189 CZ PHE C 69 -16.923 -13.397 28.502 1.00 0.00 C \nATOM 5190 H PHE C 69 -15.214 -12.306 22.164 1.00 0.00 H \nATOM 5191 HA PHE C 69 -16.560 -11.104 24.014 1.00 0.00 H \nATOM 5192 HB2 PHE C 69 -16.305 -13.474 23.861 1.00 0.00 H \nATOM 5193 HB3 PHE C 69 -14.820 -13.332 24.318 1.00 0.00 H \nATOM 5194 HD1 PHE C 69 -18.089 -12.698 25.571 1.00 0.00 H \nATOM 5195 HD2 PHE C 69 -14.325 -13.578 26.594 1.00 0.00 H \nATOM 5196 HE1 PHE C 69 -18.742 -12.932 27.772 1.00 0.00 H \nATOM 5197 HE2 PHE C 69 -14.976 -13.815 28.793 1.00 0.00 H \nATOM 5198 HZ PHE C 69 -17.186 -13.494 29.389 1.00 0.00 H \nATOM 5199 N ASP C 70 -13.463 -10.557 24.264 1.00 0.00 N \nATOM 5200 CA ASP C 70 -12.440 -9.834 25.009 1.00 0.00 C \nATOM 5201 C ASP C 70 -12.500 -8.324 24.826 1.00 0.00 C \nATOM 5202 O ASP C 70 -11.797 -7.607 25.546 1.00 0.00 O \nATOM 5203 CB ASP C 70 -11.052 -10.329 24.594 1.00 0.00 C \nATOM 5204 CG ASP C 70 -10.813 -10.199 23.102 1.00 0.00 C \nATOM 5205 OD1 ASP C 70 -11.793 -10.301 22.332 1.00 0.00 O \nATOM 5206 OD2 ASP C 70 -9.650 -9.993 22.695 1.00 0.00 O \nATOM 5207 H ASP C 70 -13.189 -10.896 23.523 1.00 0.00 H \nATOM 5208 HA ASP C 70 -12.612 -10.013 25.947 1.00 0.00 H \nATOM 5209 HB2 ASP C 70 -10.375 -9.825 25.072 1.00 0.00 H \nATOM 5210 HB3 ASP C 70 -10.951 -11.258 24.855 1.00 0.00 H \nATOM 5211 N GLN C 71 -13.306 -7.818 23.896 1.00 0.00 N \nATOM 5212 CA GLN C 71 -13.408 -6.381 23.638 1.00 0.00 C \nATOM 5213 C GLN C 71 -14.870 -5.946 23.576 1.00 0.00 C \nATOM 5214 O GLN C 71 -15.370 -5.567 22.512 1.00 0.00 O \nATOM 5215 CB GLN C 71 -12.673 -6.013 22.348 1.00 0.00 C \nATOM 5216 CG GLN C 71 -11.190 -6.366 22.360 1.00 0.00 C \nATOM 5217 CD GLN C 71 -10.494 -6.051 21.049 1.00 0.00 C \nATOM 5218 OE1 GLN C 71 -11.071 -6.202 19.972 1.00 0.00 O \nATOM 5219 NE2 GLN C 71 -9.243 -5.610 21.136 1.00 0.00 N \nATOM 5220 H GLN C 71 -13.812 -8.300 23.394 1.00 0.00 H \nATOM 5221 HA GLN C 71 -12.985 -5.908 24.372 1.00 0.00 H \nATOM 5222 HB2 GLN C 71 -13.098 -6.466 21.603 1.00 0.00 H \nATOM 5223 HB3 GLN C 71 -12.768 -5.060 22.192 1.00 0.00 H \nATOM 5224 HG2 GLN C 71 -10.753 -5.880 23.077 1.00 0.00 H \nATOM 5225 HG3 GLN C 71 -11.089 -7.311 22.555 1.00 0.00 H \nATOM 5226 HE21 GLN C 71 -8.872 -5.517 21.906 1.00 0.00 H \nATOM 5227 HE22 GLN C 71 -8.804 -5.418 20.422 1.00 0.00 H \nATOM 5228 N PRO C 72 -15.591 -6.001 24.701 1.00 0.00 N \nATOM 5229 CA PRO C 72 -16.967 -5.475 24.704 1.00 0.00 C \nATOM 5230 C PRO C 72 -17.037 -3.975 24.479 1.00 0.00 C \nATOM 5231 O PRO C 72 -18.080 -3.478 24.036 1.00 0.00 O \nATOM 5232 CB PRO C 72 -17.485 -5.860 26.095 1.00 0.00 C \nATOM 5233 CG PRO C 72 -16.259 -5.919 26.934 1.00 0.00 C \nATOM 5234 CD PRO C 72 -15.183 -6.468 26.036 1.00 0.00 C \nATOM 5235 HA PRO C 72 -17.495 -5.840 23.977 1.00 0.00 H \nATOM 5236 HB2 PRO C 72 -18.115 -5.205 26.433 1.00 0.00 H \nATOM 5237 HB3 PRO C 72 -17.945 -6.714 26.079 1.00 0.00 H \nATOM 5238 HG2 PRO C 72 -16.021 -5.040 27.267 1.00 0.00 H \nATOM 5239 HG3 PRO C 72 -16.392 -6.489 27.708 1.00 0.00 H \nATOM 5240 HD2 PRO C 72 -14.306 -6.133 26.281 1.00 0.00 H \nATOM 5241 HD3 PRO C 72 -15.139 -7.436 26.079 1.00 0.00 H \nATOM 5242 N GLN C 73 -15.961 -3.239 24.772 1.00 0.00 N \nATOM 5243 CA GLN C 73 -15.903 -1.809 24.486 1.00 0.00 C \nATOM 5244 C GLN C 73 -16.113 -1.499 23.010 1.00 0.00 C \nATOM 5245 O GLN C 73 -16.348 -0.336 22.665 1.00 0.00 O \nATOM 5246 CB GLN C 73 -14.563 -1.231 24.947 1.00 0.00 C \nATOM 5247 CG GLN C 73 -13.348 -1.785 24.213 1.00 0.00 C \nATOM 5248 CD GLN C 73 -12.829 -3.072 24.824 1.00 0.00 C \nATOM 5249 OE1 GLN C 73 -13.548 -3.766 25.542 1.00 0.00 O \nATOM 5250 NE2 GLN C 73 -11.569 -3.393 24.544 1.00 0.00 N \nATOM 5251 H GLN C 73 -15.251 -3.555 25.140 1.00 0.00 H \nATOM 5252 HA GLN C 73 -16.629 -1.394 24.977 1.00 0.00 H \nATOM 5253 HB2 GLN C 73 -14.583 -0.268 24.834 1.00 0.00 H \nATOM 5254 HB3 GLN C 73 -14.459 -1.403 25.896 1.00 0.00 H \nATOM 5255 HG2 GLN C 73 -13.581 -1.943 23.285 1.00 0.00 H \nATOM 5256 HG3 GLN C 73 -12.641 -1.121 24.219 1.00 0.00 H \nATOM 5257 HE21 GLN C 73 -11.097 -2.882 24.038 1.00 0.00 H \nATOM 5258 HE22 GLN C 73 -11.226 -4.111 24.869 1.00 0.00 H \nATOM 5259 N LEU C 74 -16.006 -2.505 22.136 1.00 0.00 N \nATOM 5260 CA LEU C 74 -16.189 -2.292 20.704 1.00 0.00 C \nATOM 5261 C LEU C 74 -17.560 -1.699 20.394 1.00 0.00 C \nATOM 5262 O LEU C 74 -17.699 -0.887 19.471 1.00 0.00 O \nATOM 5263 CB LEU C 74 -15.994 -3.615 19.959 1.00 0.00 C \nATOM 5264 CG LEU C 74 -16.131 -3.613 18.437 1.00 0.00 C \nATOM 5265 CD1 LEU C 74 -15.104 -2.687 17.809 1.00 0.00 C \nATOM 5266 CD2 LEU C 74 -15.986 -5.027 17.889 1.00 0.00 C \nATOM 5267 H LEU C 74 -15.828 -3.317 22.356 1.00 0.00 H \nATOM 5268 HA LEU C 74 -15.524 -1.652 20.404 1.00 0.00 H \nATOM 5269 HB2 LEU C 74 -15.110 -3.950 20.177 1.00 0.00 H \nATOM 5270 HB3 LEU C 74 -16.634 -4.252 20.313 1.00 0.00 H \nATOM 5271 HG LEU C 74 -17.015 -3.285 18.208 1.00 0.00 H \nATOM 5272 HD11 LEU C 74 -15.205 -2.698 16.844 1.00 0.00 H \nATOM 5273 HD12 LEU C 74 -15.238 -1.784 18.138 1.00 0.00 H \nATOM 5274 HD13 LEU C 74 -14.212 -2.987 18.043 1.00 0.00 H \nATOM 5275 HD21 LEU C 74 -16.075 -5.011 16.923 1.00 0.00 H \nATOM 5276 HD22 LEU C 74 -15.114 -5.379 18.127 1.00 0.00 H \nATOM 5277 HD23 LEU C 74 -16.677 -5.593 18.267 1.00 0.00 H \nATOM 5278 N PHE C 75 -18.587 -2.088 21.155 1.00 0.00 N \nATOM 5279 CA PHE C 75 -19.921 -1.534 20.966 1.00 0.00 C \nATOM 5280 C PHE C 75 -20.628 -1.143 22.256 1.00 0.00 C \nATOM 5281 O PHE C 75 -21.719 -0.569 22.182 1.00 0.00 O \nATOM 5282 CB PHE C 75 -20.816 -2.516 20.190 1.00 0.00 C \nATOM 5283 CG PHE C 75 -21.135 -3.779 20.942 1.00 0.00 C \nATOM 5284 CD1 PHE C 75 -20.278 -4.866 20.892 1.00 0.00 C \nATOM 5285 CD2 PHE C 75 -22.302 -3.887 21.683 1.00 0.00 C \nATOM 5286 CE1 PHE C 75 -20.572 -6.029 21.574 1.00 0.00 C \nATOM 5287 CE2 PHE C 75 -22.601 -5.049 22.368 1.00 0.00 C \nATOM 5288 CZ PHE C 75 -21.734 -6.120 22.315 1.00 0.00 C \nATOM 5289 H PHE C 75 -18.528 -2.671 21.784 1.00 0.00 H \nATOM 5290 HA PHE C 75 -19.781 -0.719 20.460 1.00 0.00 H \nATOM 5291 HB2 PHE C 75 -21.646 -2.070 19.959 1.00 0.00 H \nATOM 5292 HB3 PHE C 75 -20.378 -2.749 19.356 1.00 0.00 H \nATOM 5293 HD1 PHE C 75 -19.495 -4.811 20.393 1.00 0.00 H \nATOM 5294 HD2 PHE C 75 -22.891 -3.168 21.719 1.00 0.00 H \nATOM 5295 HE1 PHE C 75 -19.988 -6.752 21.535 1.00 0.00 H \nATOM 5296 HE2 PHE C 75 -23.385 -5.109 22.864 1.00 0.00 H \nATOM 5297 HZ PHE C 75 -21.931 -6.902 22.777 1.00 0.00 H \nATOM 5298 N LYS C 76 -20.062 -1.433 23.426 1.00 0.00 N \nATOM 5299 CA LYS C 76 -20.703 -1.060 24.679 1.00 0.00 C \nATOM 5300 C LYS C 76 -20.086 0.236 25.177 1.00 0.00 C \nATOM 5301 O LYS C 76 -18.928 0.226 25.625 1.00 0.00 O \nATOM 5302 CB LYS C 76 -20.544 -2.163 25.725 1.00 0.00 C \nATOM 5303 CG LYS C 76 -21.113 -3.507 25.309 1.00 0.00 C \nATOM 5304 CD LYS C 76 -21.030 -4.516 26.447 1.00 0.00 C \nATOM 5305 CE LYS C 76 -21.483 -5.893 25.995 1.00 0.00 C \nATOM 5306 NZ LYS C 76 -21.772 -6.791 27.147 1.00 0.00 N \nATOM 5307 H LYS C 76 -19.311 -1.843 23.513 1.00 0.00 H \nATOM 5308 HA LYS C 76 -21.653 -0.935 24.527 1.00 0.00 H \nATOM 5309 HB2 LYS C 76 -19.601 -2.271 25.925 1.00 0.00 H \nATOM 5310 HB3 LYS C 76 -20.977 -1.881 26.546 1.00 0.00 H \nATOM 5311 HG2 LYS C 76 -22.037 -3.399 25.036 1.00 0.00 H \nATOM 5312 HG3 LYS C 76 -20.627 -3.843 24.540 1.00 0.00 H \nATOM 5313 HD2 LYS C 76 -20.118 -4.564 26.774 1.00 0.00 H \nATOM 5314 HD3 LYS C 76 -21.581 -4.218 27.187 1.00 0.00 H \nATOM 5315 HE2 LYS C 76 -22.278 -5.807 25.446 1.00 0.00 H \nATOM 5316 HE3 LYS C 76 -20.796 -6.292 25.439 1.00 0.00 H \nATOM 5317 HZ1 LYS C 76 -21.262 -7.518 27.092 1.00 0.00 H \nATOM 5318 HZ2 LYS C 76 -21.598 -6.363 27.908 1.00 0.00 H \nATOM 5319 HZ3 LYS C 76 -22.629 -7.029 27.130 1.00 0.00 H \nATOM 5320 N PRO C 77 -20.801 1.365 25.124 1.00 0.00 N \nATOM 5321 CA PRO C 77 -20.185 2.640 25.521 1.00 0.00 C \nATOM 5322 C PRO C 77 -19.877 2.733 27.004 1.00 0.00 C \nATOM 5323 O PRO C 77 -19.092 3.603 27.399 1.00 0.00 O \nATOM 5324 CB PRO C 77 -21.229 3.683 25.103 1.00 0.00 C \nATOM 5325 CG PRO C 77 -22.524 2.938 25.072 1.00 0.00 C \nATOM 5326 CD PRO C 77 -22.198 1.527 24.684 1.00 0.00 C \nATOM 5327 HA PRO C 77 -19.319 2.761 25.101 1.00 0.00 H \nATOM 5328 HB2 PRO C 77 -21.262 4.420 25.733 1.00 0.00 H \nATOM 5329 HB3 PRO C 77 -21.020 4.061 24.235 1.00 0.00 H \nATOM 5330 HG2 PRO C 77 -22.958 2.966 25.939 1.00 0.00 H \nATOM 5331 HG3 PRO C 77 -23.137 3.338 24.435 1.00 0.00 H \nATOM 5332 HD2 PRO C 77 -22.786 0.891 25.121 1.00 0.00 H \nATOM 5333 HD3 PRO C 77 -22.290 1.389 23.728 1.00 0.00 H \nATOM 5334 N PHE C 78 -20.467 1.876 27.838 1.00 0.00 N \nATOM 5335 CA PHE C 78 -20.233 1.933 29.275 1.00 0.00 C \nATOM 5336 C PHE C 78 -18.906 1.320 29.700 1.00 0.00 C \nATOM 5337 O PHE C 78 -18.471 1.561 30.829 1.00 0.00 O \nATOM 5338 CB PHE C 78 -21.366 1.228 30.026 1.00 0.00 C \nATOM 5339 CG PHE C 78 -22.737 1.688 29.626 1.00 0.00 C \nATOM 5340 CD1 PHE C 78 -23.194 2.946 29.986 1.00 0.00 C \nATOM 5341 CD2 PHE C 78 -23.576 0.858 28.898 1.00 0.00 C \nATOM 5342 CE1 PHE C 78 -24.456 3.369 29.621 1.00 0.00 C \nATOM 5343 CE2 PHE C 78 -24.838 1.278 28.531 1.00 0.00 C \nATOM 5344 CZ PHE C 78 -25.280 2.534 28.894 1.00 0.00 C \nATOM 5345 H PHE C 78 -21.006 1.254 27.588 1.00 0.00 H \nATOM 5346 HA PHE C 78 -20.203 2.876 29.501 1.00 0.00 H \nATOM 5347 HB2 PHE C 78 -21.298 0.272 29.874 1.00 0.00 H \nATOM 5348 HB3 PHE C 78 -21.251 1.373 30.978 1.00 0.00 H \nATOM 5349 HD1 PHE C 78 -22.644 3.511 30.479 1.00 0.00 H \nATOM 5350 HD2 PHE C 78 -23.285 0.009 28.654 1.00 0.00 H \nATOM 5351 HE1 PHE C 78 -24.751 4.217 29.865 1.00 0.00 H \nATOM 5352 HE2 PHE C 78 -25.391 0.715 28.039 1.00 0.00 H \nATOM 5353 HZ PHE C 78 -26.131 2.817 28.649 1.00 0.00 H \nATOM 5354 N VAL C 79 -18.249 0.553 28.838 1.00 0.00 N \nATOM 5355 CA VAL C 79 -17.052 -0.186 29.220 1.00 0.00 C \nATOM 5356 C VAL C 79 -15.834 0.694 28.978 1.00 0.00 C \nATOM 5357 O VAL C 79 -15.640 1.213 27.873 1.00 0.00 O \nATOM 5358 CB VAL C 79 -16.946 -1.505 28.437 1.00 0.00 C \nATOM 5359 CG1 VAL C 79 -15.597 -2.169 28.688 1.00 0.00 C \nATOM 5360 CG2 VAL C 79 -18.088 -2.438 28.813 1.00 0.00 C \nATOM 5361 H VAL C 79 -18.483 0.446 28.017 1.00 0.00 H \nATOM 5362 HA VAL C 79 -17.101 -0.416 30.161 1.00 0.00 H \nATOM 5363 HB VAL C 79 -17.014 -1.309 27.489 1.00 0.00 H \nATOM 5364 HG11 VAL C 79 -15.546 -2.998 28.188 1.00 0.00 H \nATOM 5365 HG12 VAL C 79 -14.886 -1.575 28.402 1.00 0.00 H \nATOM 5366 HG13 VAL C 79 -15.500 -2.357 29.635 1.00 0.00 H \nATOM 5367 HG21 VAL C 79 -18.009 -3.265 28.312 1.00 0.00 H \nATOM 5368 HG22 VAL C 79 -18.049 -2.631 29.763 1.00 0.00 H \nATOM 5369 HG23 VAL C 79 -18.935 -2.014 28.604 1.00 0.00 H \nATOM 5370 N SER C 80 -15.010 0.866 30.014 1.00 0.00 N \nATOM 5371 CA SER C 80 -13.772 1.622 29.896 1.00 0.00 C \nATOM 5372 C SER C 80 -12.517 0.764 29.918 1.00 0.00 C \nATOM 5373 O SER C 80 -11.445 1.266 29.568 1.00 0.00 O \nATOM 5374 CB SER C 80 -13.667 2.654 31.028 1.00 0.00 C \nATOM 5375 OG SER C 80 -13.214 2.043 32.222 1.00 0.00 O \nATOM 5376 H SER C 80 -15.156 0.548 30.799 1.00 0.00 H \nATOM 5377 HA SER C 80 -13.817 2.051 29.027 1.00 0.00 H \nATOM 5378 HB2 SER C 80 -13.057 3.363 30.770 1.00 0.00 H \nATOM 5379 HB3 SER C 80 -14.532 3.066 31.178 1.00 0.00 H \nATOM 5380 HG SER C 80 -13.552 1.277 32.291 1.00 0.00 H \nATOM 5381 N ARG C 81 -12.625 -0.508 30.289 1.00 0.00 N \nATOM 5382 CA ARG C 81 -11.525 -1.452 30.161 1.00 0.00 C \nATOM 5383 C ARG C 81 -12.069 -2.849 30.428 1.00 0.00 C \nATOM 5384 O ARG C 81 -13.099 -3.019 31.087 1.00 0.00 O \nATOM 5385 CB ARG C 81 -10.388 -1.108 31.138 1.00 0.00 C \nATOM 5386 CG ARG C 81 -9.150 -1.989 31.073 1.00 0.00 C \nATOM 5387 CD ARG C 81 -8.600 -2.249 32.470 1.00 0.00 C \nATOM 5388 NE ARG C 81 -8.304 -1.011 33.187 1.00 0.00 N \nATOM 5389 CZ ARG C 81 -8.159 -0.921 34.506 1.00 0.00 C \nATOM 5390 NH1 ARG C 81 -8.334 -1.988 35.270 1.00 0.00 N \nATOM 5391 NH2 ARG C 81 -7.884 0.250 35.065 1.00 0.00 N \nATOM 5392 H ARG C 81 -13.341 -0.847 30.623 1.00 0.00 H \nATOM 5393 HA ARG C 81 -11.153 -1.407 29.266 1.00 0.00 H \nATOM 5394 HB2 ARG C 81 -10.117 -0.191 30.978 1.00 0.00 H \nATOM 5395 HB3 ARG C 81 -10.741 -1.146 32.041 1.00 0.00 H \nATOM 5396 HG2 ARG C 81 -9.369 -2.831 30.645 1.00 0.00 H \nATOM 5397 HG3 ARG C 81 -8.471 -1.561 30.528 1.00 0.00 H \nATOM 5398 HD2 ARG C 81 -9.243 -2.769 32.977 1.00 0.00 H \nATOM 5399 HD3 ARG C 81 -7.793 -2.783 32.404 1.00 0.00 H \nATOM 5400 HE ARG C 81 -8.218 -0.291 32.724 1.00 0.00 H \nATOM 5401 HH11 ARG C 81 -8.542 -2.743 34.914 1.00 0.00 H \nATOM 5402 HH12 ARG C 81 -8.239 -1.927 36.123 1.00 0.00 H \nATOM 5403 HH21 ARG C 81 -7.799 0.951 34.575 1.00 0.00 H \nATOM 5404 HH22 ARG C 81 -7.790 0.308 35.918 1.00 0.00 H \nATOM 5405 N CYS C 82 -11.345 -3.847 29.930 1.00 0.00 N \nATOM 5406 CA CYS C 82 -11.781 -5.238 29.991 1.00 0.00 C \nATOM 5407 C CYS C 82 -10.550 -6.119 29.883 1.00 0.00 C \nATOM 5408 O CYS C 82 -9.796 -6.015 28.910 1.00 0.00 O \nATOM 5409 CB CYS C 82 -12.778 -5.568 28.882 1.00 0.00 C \nATOM 5410 SG CYS C 82 -13.246 -7.315 28.830 1.00 0.00 S \nATOM 5411 H CYS C 82 -10.584 -3.736 29.546 1.00 0.00 H \nATOM 5412 HA CYS C 82 -12.239 -5.395 30.832 1.00 0.00 H \nATOM 5413 HB2 CYS C 82 -13.576 -5.030 29.004 1.00 0.00 H \nATOM 5414 HB3 CYS C 82 -12.395 -5.318 28.027 1.00 0.00 H \nATOM 5415 HG CYS C 82 -13.301 -7.681 27.689 1.00 0.00 H \nATOM 5416 N GLU C 83 -10.340 -6.970 30.883 1.00 0.00 N \nATOM 5417 CA GLU C 83 -9.205 -7.877 30.920 1.00 0.00 C \nATOM 5418 C GLU C 83 -9.677 -9.315 31.051 1.00 0.00 C \nATOM 5419 O GLU C 83 -10.606 -9.610 31.809 1.00 0.00 O \nATOM 5420 CB GLU C 83 -8.278 -7.532 32.074 1.00 0.00 C \nATOM 5421 CG GLU C 83 -8.003 -6.065 32.136 1.00 0.00 C \nATOM 5422 CD GLU C 83 -6.767 -5.690 31.370 1.00 0.00 C \nATOM 5423 OE1 GLU C 83 -6.168 -4.654 31.700 1.00 0.00 O \nATOM 5424 OE2 GLU C 83 -6.379 -6.438 30.445 1.00 0.00 O \nATOM 5425 H GLU C 83 -10.860 -7.035 31.565 1.00 0.00 H \nATOM 5426 HA GLU C 83 -8.716 -7.780 30.088 1.00 0.00 H \nATOM 5427 HB2 GLU C 83 -8.677 -7.823 32.909 1.00 0.00 H \nATOM 5428 HB3 GLU C 83 -7.443 -8.015 31.975 1.00 0.00 H \nATOM 5429 HG2 GLU C 83 -8.763 -5.579 31.779 1.00 0.00 H \nATOM 5430 HG3 GLU C 83 -7.903 -5.795 33.062 1.00 0.00 H \nATOM 5431 N MET C 84 -9.034 -10.205 30.304 1.00 0.00 N \nATOM 5432 CA MET C 84 -9.276 -11.632 30.440 1.00 0.00 C \nATOM 5433 C MET C 84 -7.984 -12.366 30.113 1.00 0.00 C \nATOM 5434 O MET C 84 -7.292 -12.022 29.151 1.00 0.00 O \nATOM 5435 CB MET C 84 -10.434 -12.104 29.551 1.00 0.00 C \nATOM 5436 CG MET C 84 -10.192 -12.034 28.060 1.00 0.00 C \nATOM 5437 SD MET C 84 -11.429 -13.003 27.182 1.00 0.00 S \nATOM 5438 CE MET C 84 -10.748 -14.649 27.372 1.00 0.00 C \nATOM 5439 H MET C 84 -8.449 -9.999 29.708 1.00 0.00 H \nATOM 5440 HA MET C 84 -9.544 -11.829 31.351 1.00 0.00 H \nATOM 5441 HB2 MET C 84 -10.645 -13.022 29.784 1.00 0.00 H \nATOM 5442 HB3 MET C 84 -11.217 -11.571 29.760 1.00 0.00 H \nATOM 5443 HG2 MET C 84 -10.225 -11.111 27.763 1.00 0.00 H \nATOM 5444 HG3 MET C 84 -9.305 -12.367 27.854 1.00 0.00 H \nATOM 5445 HE1 MET C 84 -11.328 -15.292 26.935 1.00 0.00 H \nATOM 5446 HE2 MET C 84 -9.866 -14.683 26.969 1.00 0.00 H \nATOM 5447 HE3 MET C 84 -10.680 -14.864 28.315 1.00 0.00 H \nATOM 5448 N LYS C 85 -7.651 -13.353 30.939 1.00 0.00 N \nATOM 5449 CA LYS C 85 -6.438 -14.129 30.735 1.00 0.00 C \nATOM 5450 C LYS C 85 -6.681 -15.240 29.724 1.00 0.00 C \nATOM 5451 O LYS C 85 -7.745 -15.865 29.703 1.00 0.00 O \nATOM 5452 CB LYS C 85 -5.956 -14.726 32.057 1.00 0.00 C \nATOM 5453 CG LYS C 85 -6.302 -13.895 33.281 1.00 0.00 C \nATOM 5454 CD LYS C 85 -5.306 -12.767 33.476 1.00 0.00 C \nATOM 5455 CE LYS C 85 -3.981 -13.296 34.000 1.00 0.00 C \nATOM 5456 NZ LYS C 85 -3.142 -12.211 34.574 1.00 0.00 N \nATOM 5457 H LYS C 85 -8.116 -13.588 31.623 1.00 0.00 H \nATOM 5458 HA LYS C 85 -5.752 -13.536 30.391 1.00 0.00 H \nATOM 5459 HB2 LYS C 85 -6.341 -15.610 32.160 1.00 0.00 H \nATOM 5460 HB3 LYS C 85 -4.993 -14.839 32.017 1.00 0.00 H \nATOM 5461 HG2 LYS C 85 -7.195 -13.529 33.185 1.00 0.00 H \nATOM 5462 HG3 LYS C 85 -6.311 -14.462 34.068 1.00 0.00 H \nATOM 5463 HD2 LYS C 85 -5.164 -12.307 32.634 1.00 0.00 H \nATOM 5464 HD3 LYS C 85 -5.667 -12.116 34.098 1.00 0.00 H \nATOM 5465 HE2 LYS C 85 -4.147 -13.970 34.678 1.00 0.00 H \nATOM 5466 HE3 LYS C 85 -3.499 -13.731 33.280 1.00 0.00 H \nATOM 5467 HZ1 LYS C 85 -2.706 -12.518 35.287 1.00 0.00 H \nATOM 5468 HZ2 LYS C 85 -2.555 -11.935 33.964 1.00 0.00 H \nATOM 5469 HZ3 LYS C 85 -3.661 -11.530 34.815 1.00 0.00 H \nATOM 5470 N GLY C 86 -5.680 -15.481 28.884 1.00 0.00 N \nATOM 5471 CA GLY C 86 -5.715 -16.588 27.955 1.00 0.00 C \nATOM 5472 C GLY C 86 -6.588 -16.310 26.746 1.00 0.00 C \nATOM 5473 O GLY C 86 -7.052 -15.192 26.503 1.00 0.00 O \nATOM 5474 H GLY C 86 -4.965 -15.005 28.841 1.00 0.00 H \nATOM 5475 HA2 GLY C 86 -4.813 -16.786 27.659 1.00 0.00 H \nATOM 5476 HA3 GLY C 86 -6.043 -17.378 28.412 1.00 0.00 H \nATOM 5477 N ASN C 87 -6.817 -17.371 25.978 1.00 0.00 N \nATOM 5478 CA ASN C 87 -7.628 -17.290 24.776 1.00 0.00 C \nATOM 5479 C ASN C 87 -9.115 -17.363 25.124 1.00 0.00 C \nATOM 5480 O ASN C 87 -9.508 -17.696 26.245 1.00 0.00 O \nATOM 5481 CB ASN C 87 -7.238 -18.394 23.794 1.00 0.00 C \nATOM 5482 CG ASN C 87 -5.857 -18.184 23.203 1.00 0.00 C \nATOM 5483 OD1 ASN C 87 -4.939 -18.969 23.446 1.00 0.00 O \nATOM 5484 ND2 ASN C 87 -5.700 -17.116 22.429 1.00 0.00 N \nATOM 5485 H ASN C 87 -6.506 -18.156 26.142 1.00 0.00 H \nATOM 5486 HA ASN C 87 -7.463 -16.435 24.349 1.00 0.00 H \nATOM 5487 HB2 ASN C 87 -7.266 -19.251 24.248 1.00 0.00 H \nATOM 5488 HB3 ASN C 87 -7.891 -18.431 23.078 1.00 0.00 H \nATOM 5489 HD21 ASN C 87 -4.934 -16.950 22.075 1.00 0.00 H \nATOM 5490 HD22 ASN C 87 -6.364 -16.590 22.282 1.00 0.00 H \nATOM 5491 N ILE C 88 -9.947 -17.044 24.138 1.00 0.00 N \nATOM 5492 CA ILE C 88 -11.397 -17.081 24.303 1.00 0.00 C \nATOM 5493 C ILE C 88 -11.889 -18.513 24.129 1.00 0.00 C \nATOM 5494 O ILE C 88 -11.750 -19.104 23.053 1.00 0.00 O \nATOM 5495 CB ILE C 88 -12.092 -16.136 23.312 1.00 0.00 C \nATOM 5496 CG1 ILE C 88 -11.661 -14.689 23.558 1.00 0.00 C \nATOM 5497 CG2 ILE C 88 -13.606 -16.276 23.415 1.00 0.00 C \nATOM 5498 CD1 ILE C 88 -11.938 -13.766 22.390 1.00 0.00 C \nATOM 5499 H ILE C 88 -9.688 -16.800 23.355 1.00 0.00 H \nATOM 5500 HA ILE C 88 -11.620 -16.775 25.196 1.00 0.00 H \nATOM 5501 HB ILE C 88 -11.825 -16.382 22.412 1.00 0.00 H \nATOM 5502 HG12 ILE C 88 -12.121 -14.352 24.343 1.00 0.00 H \nATOM 5503 HG13 ILE C 88 -10.712 -14.672 23.756 1.00 0.00 H \nATOM 5504 HG21 ILE C 88 -14.031 -15.674 22.784 1.00 0.00 H \nATOM 5505 HG22 ILE C 88 -13.861 -17.189 23.212 1.00 0.00 H \nATOM 5506 HG23 ILE C 88 -13.891 -16.054 24.315 1.00 0.00 H \nATOM 5507 HD11 ILE C 88 -11.643 -12.868 22.610 1.00 0.00 H \nATOM 5508 HD12 ILE C 88 -11.459 -14.081 21.608 1.00 0.00 H \nATOM 5509 HD13 ILE C 88 -12.890 -13.756 22.204 1.00 0.00 H \nATOM 5510 N GLU C 89 -12.460 -19.073 25.195 1.00 0.00 N \nATOM 5511 CA GLU C 89 -12.998 -20.425 25.169 1.00 0.00 C \nATOM 5512 C GLU C 89 -14.113 -20.522 26.200 1.00 0.00 C \nATOM 5513 O GLU C 89 -14.298 -19.627 27.028 1.00 0.00 O \nATOM 5514 CB GLU C 89 -11.909 -21.473 25.433 1.00 0.00 C \nATOM 5515 CG GLU C 89 -11.094 -21.229 26.693 1.00 0.00 C \nATOM 5516 CD GLU C 89 -9.959 -22.223 26.854 1.00 0.00 C \nATOM 5517 OE1 GLU C 89 -8.821 -21.789 27.131 1.00 0.00 O \nATOM 5518 OE2 GLU C 89 -10.206 -23.438 26.702 1.00 0.00 O \nATOM 5519 H GLU C 89 -12.545 -18.676 25.953 1.00 0.00 H \nATOM 5520 HA GLU C 89 -13.351 -20.611 24.285 1.00 0.00 H \nATOM 5521 HB2 GLU C 89 -12.325 -22.347 25.494 1.00 0.00 H \nATOM 5522 HB3 GLU C 89 -11.308 -21.498 24.672 1.00 0.00 H \nATOM 5523 HG2 GLU C 89 -10.731 -20.330 26.671 1.00 0.00 H \nATOM 5524 HG3 GLU C 89 -11.677 -21.281 27.467 1.00 0.00 H \nATOM 5525 N ILE C 90 -14.870 -21.620 26.129 1.00 0.00 N \nATOM 5526 CA ILE C 90 -15.936 -21.856 27.097 1.00 0.00 C \nATOM 5527 C ILE C 90 -15.351 -21.895 28.500 1.00 0.00 C \nATOM 5528 O ILE C 90 -14.404 -22.640 28.780 1.00 0.00 O \nATOM 5529 CB ILE C 90 -16.688 -23.150 26.756 1.00 0.00 C \nATOM 5530 CG1 ILE C 90 -17.567 -22.937 25.521 1.00 0.00 C \nATOM 5531 CG2 ILE C 90 -17.519 -23.612 27.946 1.00 0.00 C \nATOM 5532 CD1 ILE C 90 -18.701 -23.935 25.380 1.00 0.00 C \nATOM 5533 H ILE C 90 -14.782 -22.233 25.533 1.00 0.00 H \nATOM 5534 HA ILE C 90 -16.578 -21.130 27.059 1.00 0.00 H \nATOM 5535 HB ILE C 90 -16.043 -23.846 26.555 1.00 0.00 H \nATOM 5536 HG12 ILE C 90 -17.940 -22.042 25.553 1.00 0.00 H \nATOM 5537 HG13 ILE C 90 -17.009 -22.983 24.729 1.00 0.00 H \nATOM 5538 HG21 ILE C 90 -17.988 -24.429 27.716 1.00 0.00 H \nATOM 5539 HG22 ILE C 90 -16.936 -23.776 28.704 1.00 0.00 H \nATOM 5540 HG23 ILE C 90 -18.163 -22.925 28.177 1.00 0.00 H \nATOM 5541 HD11 ILE C 90 -19.210 -23.736 24.579 1.00 0.00 H \nATOM 5542 HD12 ILE C 90 -18.337 -24.832 25.317 1.00 0.00 H \nATOM 5543 HD13 ILE C 90 -19.282 -23.876 26.154 1.00 0.00 H \nATOM 5544 N GLY C 91 -15.915 -21.083 29.393 1.00 0.00 N \nATOM 5545 CA GLY C 91 -15.409 -20.943 30.740 1.00 0.00 C \nATOM 5546 C GLY C 91 -14.501 -19.751 30.947 1.00 0.00 C \nATOM 5547 O GLY C 91 -14.140 -19.462 32.096 1.00 0.00 O \nATOM 5548 H GLY C 91 -16.606 -20.598 29.226 1.00 0.00 H \nATOM 5549 HA2 GLY C 91 -16.160 -20.873 31.350 1.00 0.00 H \nATOM 5550 HA3 GLY C 91 -14.925 -21.749 30.977 1.00 0.00 H \nATOM 5551 N SER C 92 -14.114 -19.062 29.873 1.00 0.00 N \nATOM 5552 CA SER C 92 -13.301 -17.861 30.003 1.00 0.00 C \nATOM 5553 C SER C 92 -14.032 -16.800 30.814 1.00 0.00 C \nATOM 5554 O SER C 92 -15.262 -16.702 30.796 1.00 0.00 O \nATOM 5555 CB SER C 92 -12.934 -17.305 28.627 1.00 0.00 C \nATOM 5556 OG SER C 92 -11.978 -18.127 27.979 1.00 0.00 O \nATOM 5557 H SER C 92 -14.313 -19.275 29.064 1.00 0.00 H \nATOM 5558 HA SER C 92 -12.485 -18.102 30.469 1.00 0.00 H \nATOM 5559 HB2 SER C 92 -13.732 -17.239 28.079 1.00 0.00 H \nATOM 5560 HB3 SER C 92 -12.580 -16.407 28.722 1.00 0.00 H \nATOM 5561 HG SER C 92 -11.496 -17.655 27.479 1.00 0.00 H \nATOM 5562 N VAL C 93 -13.255 -16.000 31.535 1.00 0.00 N \nATOM 5563 CA VAL C 93 -13.776 -14.965 32.416 1.00 0.00 C \nATOM 5564 C VAL C 93 -13.105 -13.648 32.058 1.00 0.00 C \nATOM 5565 O VAL C 93 -11.872 -13.565 32.023 1.00 0.00 O \nATOM 5566 CB VAL C 93 -13.537 -15.310 33.898 1.00 0.00 C \nATOM 5567 CG1 VAL C 93 -13.485 -14.050 34.734 1.00 0.00 C \nATOM 5568 CG2 VAL C 93 -14.621 -16.243 34.408 1.00 0.00 C \nATOM 5569 H VAL C 93 -12.396 -16.045 31.525 1.00 0.00 H \nATOM 5570 HA VAL C 93 -14.736 -14.896 32.294 1.00 0.00 H \nATOM 5571 HB VAL C 93 -12.683 -15.763 33.973 1.00 0.00 H \nATOM 5572 HG11 VAL C 93 -13.334 -14.284 35.663 1.00 0.00 H \nATOM 5573 HG12 VAL C 93 -12.762 -13.484 34.422 1.00 0.00 H \nATOM 5574 HG13 VAL C 93 -14.326 -13.573 34.654 1.00 0.00 H \nATOM 5575 HG21 VAL C 93 -14.457 -16.451 35.341 1.00 0.00 H \nATOM 5576 HG22 VAL C 93 -15.486 -15.813 34.320 1.00 0.00 H \nATOM 5577 HG23 VAL C 93 -14.614 -17.062 33.889 1.00 0.00 H \nATOM 5578 N ARG C 94 -13.911 -12.624 31.792 1.00 0.00 N \nATOM 5579 CA ARG C 94 -13.403 -11.286 31.545 1.00 0.00 C \nATOM 5580 C ARG C 94 -13.746 -10.388 32.726 1.00 0.00 C \nATOM 5581 O ARG C 94 -14.800 -10.529 33.351 1.00 0.00 O \nATOM 5582 CB ARG C 94 -13.974 -10.703 30.247 1.00 0.00 C \nATOM 5583 CG ARG C 94 -15.489 -10.543 30.219 1.00 0.00 C \nATOM 5584 CD ARG C 94 -15.957 -9.966 28.888 1.00 0.00 C \nATOM 5585 NE ARG C 94 -17.411 -9.838 28.812 1.00 0.00 N \nATOM 5586 CZ ARG C 94 -18.090 -9.697 27.678 1.00 0.00 C \nATOM 5587 NH1 ARG C 94 -17.449 -9.664 26.517 1.00 0.00 N \nATOM 5588 NH2 ARG C 94 -19.411 -9.590 27.701 1.00 0.00 N \nATOM 5589 H ARG C 94 -14.768 -12.689 31.750 1.00 0.00 H \nATOM 5590 HA ARG C 94 -12.440 -11.336 31.444 1.00 0.00 H \nATOM 5591 HB2 ARG C 94 -13.569 -9.835 30.093 1.00 0.00 H \nATOM 5592 HB3 ARG C 94 -13.710 -11.274 29.509 1.00 0.00 H \nATOM 5593 HG2 ARG C 94 -15.911 -11.404 30.368 1.00 0.00 H \nATOM 5594 HG3 ARG C 94 -15.769 -9.961 30.943 1.00 0.00 H \nATOM 5595 HD2 ARG C 94 -15.552 -9.095 28.756 1.00 0.00 H \nATOM 5596 HD3 ARG C 94 -15.647 -10.535 28.166 1.00 0.00 H \nATOM 5597 HE ARG C 94 -17.856 -9.855 29.548 1.00 0.00 H \nATOM 5598 HH11 ARG C 94 -16.592 -9.734 26.497 1.00 0.00 H \nATOM 5599 HH12 ARG C 94 -17.890 -9.573 25.785 1.00 0.00 H \nATOM 5600 HH21 ARG C 94 -19.831 -9.612 28.451 1.00 0.00 H \nATOM 5601 HH22 ARG C 94 -19.848 -9.499 26.966 1.00 0.00 H \nATOM 5602 N GLU C 95 -12.838 -9.467 33.029 1.00 0.00 N \nATOM 5603 CA GLU C 95 -13.008 -8.512 34.119 1.00 0.00 C \nATOM 5604 C GLU C 95 -13.277 -7.154 33.487 1.00 0.00 C \nATOM 5605 O GLU C 95 -12.400 -6.585 32.829 1.00 0.00 O \nATOM 5606 CB GLU C 95 -11.775 -8.475 35.020 1.00 0.00 C \nATOM 5607 CG GLU C 95 -11.920 -7.573 36.236 1.00 0.00 C \nATOM 5608 CD GLU C 95 -13.033 -8.016 37.165 1.00 0.00 C \nATOM 5609 OE1 GLU C 95 -13.667 -7.142 37.794 1.00 0.00 O \nATOM 5610 OE2 GLU C 95 -13.277 -9.238 37.267 1.00 0.00 O \nATOM 5611 H GLU C 95 -12.097 -9.378 32.602 1.00 0.00 H \nATOM 5612 HA GLU C 95 -13.750 -8.772 34.687 1.00 0.00 H \nATOM 5613 HB2 GLU C 95 -11.578 -9.376 35.320 1.00 0.00 H \nATOM 5614 HB3 GLU C 95 -11.014 -8.177 34.498 1.00 0.00 H \nATOM 5615 HG2 GLU C 95 -11.082 -7.559 36.725 1.00 0.00 H \nATOM 5616 HG3 GLU C 95 -12.092 -6.665 35.942 1.00 0.00 H \nATOM 5617 N VAL C 96 -14.482 -6.636 33.697 1.00 0.00 N \nATOM 5618 CA VAL C 96 -14.966 -5.446 33.009 1.00 0.00 C \nATOM 5619 C VAL C 96 -14.978 -4.287 33.991 1.00 0.00 C \nATOM 5620 O VAL C 96 -15.505 -4.411 35.103 1.00 0.00 O \nATOM 5621 CB VAL C 96 -16.366 -5.678 32.416 1.00 0.00 C \nATOM 5622 CG1 VAL C 96 -16.878 -4.412 31.743 1.00 0.00 C \nATOM 5623 CG2 VAL C 96 -16.340 -6.844 31.440 1.00 0.00 C \nATOM 5624 H VAL C 96 -15.049 -6.971 34.251 1.00 0.00 H \nATOM 5625 HA VAL C 96 -14.374 -5.239 32.269 1.00 0.00 H \nATOM 5626 HB VAL C 96 -16.976 -5.901 33.137 1.00 0.00 H \nATOM 5627 HG11 VAL C 96 -17.760 -4.575 31.375 1.00 0.00 H \nATOM 5628 HG12 VAL C 96 -16.928 -3.696 32.395 1.00 0.00 H \nATOM 5629 HG13 VAL C 96 -16.273 -4.157 31.029 1.00 0.00 H \nATOM 5630 HG21 VAL C 96 -17.228 -6.980 31.074 1.00 0.00 H \nATOM 5631 HG22 VAL C 96 -15.720 -6.650 30.720 1.00 0.00 H \nATOM 5632 HG23 VAL C 96 -16.056 -7.648 31.903 1.00 0.00 H \nATOM 5633 N ASN C 97 -14.398 -3.164 33.581 1.00 0.00 N \nATOM 5634 CA ASN C 97 -14.474 -1.914 34.324 1.00 0.00 C \nATOM 5635 C ASN C 97 -15.327 -0.931 33.535 1.00 0.00 C \nATOM 5636 O ASN C 97 -15.070 -0.695 32.349 1.00 0.00 O \nATOM 5637 CB ASN C 97 -13.079 -1.337 34.574 1.00 0.00 C \nATOM 5638 CG ASN C 97 -12.302 -2.122 35.612 1.00 0.00 C \nATOM 5639 OD1 ASN C 97 -12.400 -1.854 36.809 1.00 0.00 O \nATOM 5640 ND2 ASN C 97 -11.524 -3.096 35.157 1.00 0.00 N \nATOM 5641 H ASN C 97 -13.943 -3.107 32.853 1.00 0.00 H \nATOM 5642 HA ASN C 97 -14.878 -2.079 35.190 1.00 0.00 H \nATOM 5643 HB2 ASN C 97 -12.582 -1.328 33.741 1.00 0.00 H \nATOM 5644 HB3 ASN C 97 -13.161 -0.415 34.865 1.00 0.00 H \nATOM 5645 HD21 ASN C 97 -11.062 -3.570 35.707 1.00 0.00 H \nATOM 5646 HD22 ASN C 97 -11.482 -3.254 34.313 1.00 0.00 H \nATOM 5647 N VAL C 98 -16.334 -0.362 34.189 1.00 0.00 N \nATOM 5648 CA VAL C 98 -17.255 0.550 33.534 1.00 0.00 C \nATOM 5649 C VAL C 98 -16.928 1.980 33.947 1.00 0.00 C \nATOM 5650 O VAL C 98 -16.260 2.234 34.953 1.00 0.00 O \nATOM 5651 CB VAL C 98 -18.730 0.200 33.838 1.00 0.00 C \nATOM 5652 CG1 VAL C 98 -19.071 -1.182 33.296 1.00 0.00 C \nATOM 5653 CG2 VAL C 98 -18.996 0.272 35.321 1.00 0.00 C \nATOM 5654 H VAL C 98 -16.500 -0.495 35.022 1.00 0.00 H \nATOM 5655 HA VAL C 98 -17.145 0.462 32.574 1.00 0.00 H \nATOM 5656 HB VAL C 98 -19.298 0.850 33.396 1.00 0.00 H \nATOM 5657 HG11 VAL C 98 -19.998 -1.388 33.494 1.00 0.00 H \nATOM 5658 HG12 VAL C 98 -18.935 -1.196 32.336 1.00 0.00 H \nATOM 5659 HG13 VAL C 98 -18.497 -1.844 33.713 1.00 0.00 H \nATOM 5660 HG21 VAL C 98 -19.924 0.050 35.495 1.00 0.00 H \nATOM 5661 HG22 VAL C 98 -18.421 -0.358 35.784 1.00 0.00 H \nATOM 5662 HG23 VAL C 98 -18.814 1.170 35.639 1.00 0.00 H \nATOM 5663 N LYS C 99 -17.407 2.933 33.147 1.00 0.00 N \nATOM 5664 CA LYS C 99 -17.061 4.335 33.320 1.00 0.00 C \nATOM 5665 C LYS C 99 -17.895 4.974 34.430 1.00 0.00 C \nATOM 5666 O LYS C 99 -18.691 4.319 35.110 1.00 0.00 O \nATOM 5667 CB LYS C 99 -17.249 5.089 32.006 1.00 0.00 C \nATOM 5668 CG LYS C 99 -16.837 4.308 30.772 1.00 0.00 C \nATOM 5669 CD LYS C 99 -17.000 5.134 29.510 1.00 0.00 C \nATOM 5670 CE LYS C 99 -16.153 4.577 28.378 1.00 0.00 C \nATOM 5671 NZ LYS C 99 -16.634 5.034 27.047 1.00 0.00 N \nATOM 5672 H LYS C 99 -17.941 2.781 32.490 1.00 0.00 H \nATOM 5673 HA LYS C 99 -16.128 4.388 33.581 1.00 0.00 H \nATOM 5674 HB2 LYS C 99 -18.182 5.340 31.920 1.00 0.00 H \nATOM 5675 HB3 LYS C 99 -16.736 5.912 32.041 1.00 0.00 H \nATOM 5676 HG2 LYS C 99 -15.913 4.027 30.859 1.00 0.00 H \nATOM 5677 HG3 LYS C 99 -17.373 3.502 30.704 1.00 0.00 H \nATOM 5678 HD2 LYS C 99 -17.933 5.144 29.245 1.00 0.00 H \nATOM 5679 HD3 LYS C 99 -16.745 6.053 29.686 1.00 0.00 H \nATOM 5680 HE2 LYS C 99 -15.231 4.852 28.500 1.00 0.00 H \nATOM 5681 HE3 LYS C 99 -16.167 3.608 28.411 1.00 0.00 H \nATOM 5682 HZ1 LYS C 99 -16.490 4.396 26.444 1.00 0.00 H \nATOM 5683 HZ2 LYS C 99 -17.505 5.210 27.090 1.00 0.00 H \nATOM 5684 HZ3 LYS C 99 -16.195 5.771 26.809 1.00 0.00 H \nATOM 5685 N SER C 100 -17.699 6.278 34.617 1.00 0.00 N \nATOM 5686 CA SER C 100 -18.418 7.030 35.633 1.00 0.00 C \nATOM 5687 C SER C 100 -19.889 7.191 35.249 1.00 0.00 C \nATOM 5688 O SER C 100 -20.295 6.965 34.106 1.00 0.00 O \nATOM 5689 CB SER C 100 -17.770 8.399 35.840 1.00 0.00 C \nATOM 5690 OG SER C 100 -17.542 9.048 34.601 1.00 0.00 O \nATOM 5691 H SER C 100 -17.145 6.748 34.157 1.00 0.00 H \nATOM 5692 HA SER C 100 -18.373 6.535 36.466 1.00 0.00 H \nATOM 5693 HB2 SER C 100 -18.342 8.950 36.397 1.00 0.00 H \nATOM 5694 HB3 SER C 100 -16.930 8.294 36.313 1.00 0.00 H \nATOM 5695 HG SER C 100 -17.334 9.850 34.739 1.00 0.00 H \nATOM 5696 N GLY C 101 -20.693 7.591 36.232 1.00 0.00 N \nATOM 5697 CA GLY C 101 -22.105 7.816 36.000 1.00 0.00 C \nATOM 5698 C GLY C 101 -22.961 6.573 36.018 1.00 0.00 C \nATOM 5699 O GLY C 101 -24.051 6.577 35.437 1.00 0.00 O \nATOM 5700 H GLY C 101 -20.434 7.736 37.039 1.00 0.00 H \nATOM 5701 HA2 GLY C 101 -22.436 8.430 36.674 1.00 0.00 H \nATOM 5702 HA3 GLY C 101 -22.212 8.254 35.141 1.00 0.00 H \nATOM 5703 N LEU C 102 -22.503 5.508 36.661 1.00 0.00 N \nATOM 5704 CA LEU C 102 -23.192 4.229 36.690 1.00 0.00 C \nATOM 5705 C LEU C 102 -23.294 3.731 38.124 1.00 0.00 C \nATOM 5706 O LEU C 102 -22.552 4.186 39.000 1.00 0.00 O \nATOM 5707 CB LEU C 102 -22.454 3.203 35.818 1.00 0.00 C \nATOM 5708 CG LEU C 102 -22.480 3.536 34.323 1.00 0.00 C \nATOM 5709 CD1 LEU C 102 -21.527 2.638 33.546 1.00 0.00 C \nATOM 5710 CD2 LEU C 102 -23.895 3.433 33.774 1.00 0.00 C \nATOM 5711 H LEU C 102 -21.765 5.510 37.103 1.00 0.00 H \nATOM 5712 HA LEU C 102 -24.086 4.345 36.333 1.00 0.00 H \nATOM 5713 HB2 LEU C 102 -21.532 3.144 36.112 1.00 0.00 H \nATOM 5714 HB3 LEU C 102 -22.852 2.329 35.954 1.00 0.00 H \nATOM 5715 HG LEU C 102 -22.179 4.452 34.213 1.00 0.00 H \nATOM 5716 HD11 LEU C 102 -21.561 2.868 32.604 1.00 0.00 H \nATOM 5717 HD12 LEU C 102 -20.623 2.762 33.876 1.00 0.00 H \nATOM 5718 HD13 LEU C 102 -21.788 1.711 33.662 1.00 0.00 H \nATOM 5719 HD21 LEU C 102 -23.892 3.647 32.828 1.00 0.00 H \nATOM 5720 HD22 LEU C 102 -24.226 2.530 33.900 1.00 0.00 H \nATOM 5721 HD23 LEU C 102 -24.471 4.056 34.244 1.00 0.00 H \nATOM 5722 N PRO C 103 -24.207 2.792 38.396 1.00 0.00 N \nATOM 5723 CA PRO C 103 -24.294 2.239 39.759 1.00 0.00 C \nATOM 5724 C PRO C 103 -23.160 1.293 40.106 1.00 0.00 C \nATOM 5725 O PRO C 103 -22.894 1.089 41.296 1.00 0.00 O \nATOM 5726 CB PRO C 103 -25.646 1.509 39.768 1.00 0.00 C \nATOM 5727 CG PRO C 103 -26.292 1.796 38.447 1.00 0.00 C \nATOM 5728 CD PRO C 103 -25.226 2.218 37.503 1.00 0.00 C \nATOM 5729 HA PRO C 103 -24.223 2.939 40.427 1.00 0.00 H \nATOM 5730 HB2 PRO C 103 -25.523 0.555 39.892 1.00 0.00 H \nATOM 5731 HB3 PRO C 103 -26.202 1.821 40.499 1.00 0.00 H \nATOM 5732 HG2 PRO C 103 -26.749 1.008 38.114 1.00 0.00 H \nATOM 5733 HG3 PRO C 103 -26.960 2.493 38.539 1.00 0.00 H \nATOM 5734 HD2 PRO C 103 -24.878 1.469 36.995 1.00 0.00 H \nATOM 5735 HD3 PRO C 103 -25.551 2.869 36.862 1.00 0.00 H \nATOM 5736 N ALA C 104 -22.483 0.718 39.119 1.00 0.00 N \nATOM 5737 CA ALA C 104 -21.417 -0.245 39.349 1.00 0.00 C \nATOM 5738 C ALA C 104 -20.102 0.291 38.798 1.00 0.00 C \nATOM 5739 O ALA C 104 -20.058 1.312 38.110 1.00 0.00 O \nATOM 5740 CB ALA C 104 -21.747 -1.596 38.703 1.00 0.00 C \nATOM 5741 H ALA C 104 -22.632 0.879 38.287 1.00 0.00 H \nATOM 5742 HA ALA C 104 -21.331 -0.380 40.306 1.00 0.00 H \nATOM 5743 HB1 ALA C 104 -21.023 -2.220 38.870 1.00 0.00 H \nATOM 5744 HB2 ALA C 104 -22.568 -1.945 39.084 1.00 0.00 H \nATOM 5745 HB3 ALA C 104 -21.859 -1.479 37.747 1.00 0.00 H \nATOM 5746 N THR C 105 -19.025 -0.407 39.128 1.00 0.00 N \nATOM 5747 CA THR C 105 -17.692 -0.077 38.637 1.00 0.00 C \nATOM 5748 C THR C 105 -17.001 -1.262 37.984 1.00 0.00 C \nATOM 5749 O THR C 105 -16.265 -1.079 37.010 1.00 0.00 O \nATOM 5750 CB THR C 105 -16.814 0.449 39.784 1.00 0.00 C \nATOM 5751 OG1 THR C 105 -16.649 -0.580 40.769 1.00 0.00 O \nATOM 5752 CG2 THR C 105 -17.455 1.669 40.435 1.00 0.00 C \nATOM 5753 H THR C 105 -19.045 -1.092 39.648 1.00 0.00 H \nATOM 5754 HA THR C 105 -17.808 0.610 37.962 1.00 0.00 H \nATOM 5755 HB THR C 105 -15.951 0.704 39.422 1.00 0.00 H \nATOM 5756 HG1 THR C 105 -17.352 -1.038 40.816 1.00 0.00 H \nATOM 5757 HG21 THR C 105 -16.888 1.987 41.155 1.00 0.00 H \nATOM 5758 HG22 THR C 105 -17.561 2.371 39.774 1.00 0.00 H \nATOM 5759 HG23 THR C 105 -18.324 1.427 40.791 1.00 0.00 H \nATOM 5760 N ARG C 106 -17.234 -2.472 38.483 1.00 0.00 N \nATOM 5761 CA ARG C 106 -16.559 -3.660 37.990 1.00 0.00 C \nATOM 5762 C ARG C 106 -17.573 -4.781 37.835 1.00 0.00 C \nATOM 5763 O ARG C 106 -18.646 -4.769 38.443 1.00 0.00 O \nATOM 5764 CB ARG C 106 -15.429 -4.096 38.930 1.00 0.00 C \nATOM 5765 CG ARG C 106 -15.916 -4.503 40.303 1.00 0.00 C \nATOM 5766 CD ARG C 106 -14.762 -4.777 41.245 1.00 0.00 C \nATOM 5767 NE ARG C 106 -15.206 -4.791 42.633 1.00 0.00 N \nATOM 5768 CZ ARG C 106 -15.781 -5.835 43.220 1.00 0.00 C \nATOM 5769 NH1 ARG C 106 -15.979 -6.954 42.536 1.00 0.00 N \nATOM 5770 NH2 ARG C 106 -16.158 -5.760 44.488 1.00 0.00 N \nATOM 5771 H ARG C 106 -17.791 -2.624 39.120 1.00 0.00 H \nATOM 5772 HA ARG C 106 -16.160 -3.454 37.130 1.00 0.00 H \nATOM 5773 HB2 ARG C 106 -14.952 -4.840 38.529 1.00 0.00 H \nATOM 5774 HB3 ARG C 106 -14.794 -3.368 39.022 1.00 0.00 H \nATOM 5775 HG2 ARG C 106 -16.475 -3.800 40.670 1.00 0.00 H \nATOM 5776 HG3 ARG C 106 -16.470 -5.296 40.229 1.00 0.00 H \nATOM 5777 HD2 ARG C 106 -14.356 -5.630 41.024 1.00 0.00 H \nATOM 5778 HD3 ARG C 106 -14.078 -4.099 41.128 1.00 0.00 H \nATOM 5779 HE ARG C 106 -15.089 -4.079 43.101 1.00 0.00 H \nATOM 5780 HH11 ARG C 106 -15.735 -7.004 41.713 1.00 0.00 H \nATOM 5781 HH12 ARG C 106 -16.351 -7.630 42.916 1.00 0.00 H \nATOM 5782 HH21 ARG C 106 -16.031 -5.035 44.932 1.00 0.00 H \nATOM 5783 HH22 ARG C 106 -16.530 -6.437 44.867 1.00 0.00 H \nATOM 5784 N SER C 107 -17.217 -5.759 37.009 1.00 0.00 N \nATOM 5785 CA SER C 107 -18.092 -6.892 36.744 1.00 0.00 C \nATOM 5786 C SER C 107 -17.240 -8.042 36.236 1.00 0.00 C \nATOM 5787 O SER C 107 -16.420 -7.856 35.333 1.00 0.00 O \nATOM 5788 CB SER C 107 -19.176 -6.530 35.726 1.00 0.00 C \nATOM 5789 OG SER C 107 -19.650 -7.678 35.052 1.00 0.00 O \nATOM 5790 H SER C 107 -16.467 -5.784 36.590 1.00 0.00 H \nATOM 5791 HA SER C 107 -18.546 -7.150 37.562 1.00 0.00 H \nATOM 5792 HB2 SER C 107 -19.913 -6.090 36.178 1.00 0.00 H \nATOM 5793 HB3 SER C 107 -18.820 -5.898 35.082 1.00 0.00 H \nATOM 5794 HG SER C 107 -20.324 -7.476 34.593 1.00 0.00 H \nATOM 5795 N THR C 108 -17.438 -9.222 36.812 1.00 0.00 N \nATOM 5796 CA THR C 108 -16.772 -10.441 36.375 1.00 0.00 C \nATOM 5797 C THR C 108 -17.802 -11.306 35.664 1.00 0.00 C \nATOM 5798 O THR C 108 -18.824 -11.673 36.255 1.00 0.00 O \nATOM 5799 CB THR C 108 -16.164 -11.183 37.564 1.00 0.00 C \nATOM 5800 OG1 THR C 108 -15.668 -10.232 38.513 1.00 0.00 O \nATOM 5801 CG2 THR C 108 -15.021 -12.067 37.111 1.00 0.00 C \nATOM 5802 H THR C 108 -17.971 -9.338 37.477 1.00 0.00 H \nATOM 5803 HA THR C 108 -16.044 -10.226 35.771 1.00 0.00 H \nATOM 5804 HB THR C 108 -16.851 -11.736 37.969 1.00 0.00 H \nATOM 5805 HG1 THR C 108 -15.449 -9.526 38.114 1.00 0.00 H \nATOM 5806 HG21 THR C 108 -14.647 -12.530 37.877 1.00 0.00 H \nATOM 5807 HG22 THR C 108 -15.349 -12.716 36.469 1.00 0.00 H \nATOM 5808 HG23 THR C 108 -14.334 -11.521 36.696 1.00 0.00 H \nATOM 5809 N GLU C 109 -17.528 -11.641 34.406 1.00 0.00 N \nATOM 5810 CA GLU C 109 -18.491 -12.335 33.566 1.00 0.00 C \nATOM 5811 C GLU C 109 -17.829 -13.539 32.916 1.00 0.00 C \nATOM 5812 O GLU C 109 -16.678 -13.467 32.475 1.00 0.00 O \nATOM 5813 CB GLU C 109 -19.053 -11.388 32.495 1.00 0.00 C \nATOM 5814 CG GLU C 109 -19.103 -9.930 32.947 1.00 0.00 C \nATOM 5815 CD GLU C 109 -19.582 -8.970 31.872 1.00 0.00 C \nATOM 5816 OE1 GLU C 109 -19.206 -9.148 30.695 1.00 0.00 O \nATOM 5817 OE2 GLU C 109 -20.336 -8.033 32.212 1.00 0.00 O \nATOM 5818 H GLU C 109 -16.779 -11.471 34.019 1.00 0.00 H \nATOM 5819 HA GLU C 109 -19.229 -12.639 34.118 1.00 0.00 H \nATOM 5820 HB2 GLU C 109 -18.508 -11.454 31.695 1.00 0.00 H \nATOM 5821 HB3 GLU C 109 -19.947 -11.676 32.254 1.00 0.00 H \nATOM 5822 HG2 GLU C 109 -19.689 -9.859 33.717 1.00 0.00 H \nATOM 5823 HG3 GLU C 109 -18.218 -9.660 33.239 1.00 0.00 H \nATOM 5824 N ARG C 110 -18.575 -14.639 32.838 1.00 0.00 N \nATOM 5825 CA ARG C 110 -18.041 -15.931 32.432 1.00 0.00 C \nATOM 5826 C ARG C 110 -18.713 -16.381 31.144 1.00 0.00 C \nATOM 5827 O ARG C 110 -19.944 -16.400 31.056 1.00 0.00 O \nATOM 5828 CB ARG C 110 -18.240 -16.981 33.529 1.00 0.00 C \nATOM 5829 CG ARG C 110 -17.862 -18.393 33.102 1.00 0.00 C \nATOM 5830 CD ARG C 110 -17.934 -19.377 34.262 1.00 0.00 C \nATOM 5831 NE ARG C 110 -19.226 -20.055 34.339 1.00 0.00 N \nATOM 5832 CZ ARG C 110 -19.852 -20.346 35.475 1.00 0.00 C \nATOM 5833 NH1 ARG C 110 -19.307 -20.017 36.638 1.00 0.00 N \nATOM 5834 NH2 ARG C 110 -21.024 -20.965 35.449 1.00 0.00 N \nATOM 5835 H ARG C 110 -19.415 -14.653 33.022 1.00 0.00 H \nATOM 5836 HA ARG C 110 -17.088 -15.836 32.281 1.00 0.00 H \nATOM 5837 HB2 ARG C 110 -17.710 -16.733 34.303 1.00 0.00 H \nATOM 5838 HB3 ARG C 110 -19.169 -16.974 33.808 1.00 0.00 H \nATOM 5839 HG2 ARG C 110 -18.456 -18.686 32.393 1.00 0.00 H \nATOM 5840 HG3 ARG C 110 -16.964 -18.390 32.736 1.00 0.00 H \nATOM 5841 HD2 ARG C 110 -17.230 -20.038 34.166 1.00 0.00 H \nATOM 5842 HD3 ARG C 110 -17.769 -18.905 35.093 1.00 0.00 H \nATOM 5843 HE ARG C 110 -19.606 -20.280 33.601 1.00 0.00 H \nATOM 5844 HH11 ARG C 110 -18.547 -19.615 36.658 1.00 0.00 H \nATOM 5845 HH12 ARG C 110 -19.713 -20.206 37.372 1.00 0.00 H \nATOM 5846 HH21 ARG C 110 -21.381 -21.179 34.696 1.00 0.00 H \nATOM 5847 HH22 ARG C 110 -21.428 -21.153 36.185 1.00 0.00 H \nATOM 5848 N LEU C 111 -17.902 -16.747 30.154 1.00 0.00 N \nATOM 5849 CA LEU C 111 -18.419 -17.240 28.883 1.00 0.00 C \nATOM 5850 C LEU C 111 -18.977 -18.645 29.073 1.00 0.00 C \nATOM 5851 O LEU C 111 -18.230 -19.586 29.356 1.00 0.00 O \nATOM 5852 CB LEU C 111 -17.312 -17.227 27.833 1.00 0.00 C \nATOM 5853 CG LEU C 111 -17.640 -17.799 26.453 1.00 0.00 C \nATOM 5854 CD1 LEU C 111 -18.863 -17.111 25.867 1.00 0.00 C \nATOM 5855 CD2 LEU C 111 -16.443 -17.661 25.521 1.00 0.00 C \nATOM 5856 H LEU C 111 -17.044 -16.717 30.200 1.00 0.00 H \nATOM 5857 HA LEU C 111 -19.135 -16.663 28.574 1.00 0.00 H \nATOM 5858 HB2 LEU C 111 -17.022 -16.309 27.715 1.00 0.00 H \nATOM 5859 HB3 LEU C 111 -16.556 -17.720 28.189 1.00 0.00 H \nATOM 5860 HG LEU C 111 -17.842 -18.743 26.551 1.00 0.00 H \nATOM 5861 HD11 LEU C 111 -19.057 -17.485 24.993 1.00 0.00 H \nATOM 5862 HD12 LEU C 111 -19.624 -17.248 26.453 1.00 0.00 H \nATOM 5863 HD13 LEU C 111 -18.689 -16.161 25.780 1.00 0.00 H \nATOM 5864 HD21 LEU C 111 -16.666 -18.028 24.651 1.00 0.00 H \nATOM 5865 HD22 LEU C 111 -16.212 -16.724 25.427 1.00 0.00 H \nATOM 5866 HD23 LEU C 111 -15.687 -18.144 25.891 1.00 0.00 H \nATOM 5867 N GLU C 112 -20.290 -18.793 28.914 1.00 0.00 N \nATOM 5868 CA GLU C 112 -20.951 -20.084 29.061 1.00 0.00 C \nATOM 5869 C GLU C 112 -21.159 -20.793 27.732 1.00 0.00 C \nATOM 5870 O GLU C 112 -20.971 -22.010 27.649 1.00 0.00 O \nATOM 5871 CB GLU C 112 -22.303 -19.915 29.761 1.00 0.00 C \nATOM 5872 CG GLU C 112 -22.213 -19.297 31.147 1.00 0.00 C \nATOM 5873 CD GLU C 112 -21.774 -20.293 32.203 1.00 0.00 C \nATOM 5874 OE1 GLU C 112 -20.572 -20.631 32.243 1.00 0.00 O \nATOM 5875 OE2 GLU C 112 -22.633 -20.742 32.991 1.00 0.00 O \nATOM 5876 H GLU C 112 -20.822 -18.146 28.718 1.00 0.00 H \nATOM 5877 HA GLU C 112 -20.362 -20.635 29.600 1.00 0.00 H \nATOM 5878 HB2 GLU C 112 -22.876 -19.361 29.207 1.00 0.00 H \nATOM 5879 HB3 GLU C 112 -22.730 -20.783 29.832 1.00 0.00 H \nATOM 5880 HG2 GLU C 112 -21.588 -18.556 31.127 1.00 0.00 H \nATOM 5881 HG3 GLU C 112 -23.078 -18.932 31.391 1.00 0.00 H \nATOM 5882 N LEU C 113 -21.539 -20.060 26.689 1.00 0.00 N \nATOM 5883 CA LEU C 113 -21.799 -20.656 25.386 1.00 0.00 C \nATOM 5884 C LEU C 113 -21.388 -19.670 24.305 1.00 0.00 C \nATOM 5885 O LEU C 113 -21.703 -18.480 24.396 1.00 0.00 O \nATOM 5886 CB LEU C 113 -23.281 -21.029 25.239 1.00 0.00 C \nATOM 5887 CG LEU C 113 -23.716 -21.911 24.064 1.00 0.00 C \nATOM 5888 CD1 LEU C 113 -24.912 -22.754 24.469 1.00 0.00 C \nATOM 5889 CD2 LEU C 113 -24.053 -21.081 22.832 1.00 0.00 C \nATOM 5890 H LEU C 113 -21.652 -19.208 26.718 1.00 0.00 H \nATOM 5891 HA LEU C 113 -21.282 -21.472 25.298 1.00 0.00 H \nATOM 5892 HB2 LEU C 113 -23.552 -21.476 26.056 1.00 0.00 H \nATOM 5893 HB3 LEU C 113 -23.786 -20.203 25.187 1.00 0.00 H \nATOM 5894 HG LEU C 113 -22.973 -22.490 23.834 1.00 0.00 H \nATOM 5895 HD11 LEU C 113 -25.184 -23.310 23.722 1.00 0.00 H \nATOM 5896 HD12 LEU C 113 -24.671 -23.318 25.221 1.00 0.00 H \nATOM 5897 HD13 LEU C 113 -25.646 -22.173 24.723 1.00 0.00 H \nATOM 5898 HD21 LEU C 113 -24.324 -21.669 22.110 1.00 0.00 H \nATOM 5899 HD22 LEU C 113 -24.778 -20.471 23.041 1.00 0.00 H \nATOM 5900 HD23 LEU C 113 -23.272 -20.573 22.560 1.00 0.00 H \nATOM 5901 N LEU C 114 -20.682 -20.171 23.291 1.00 0.00 N \nATOM 5902 CA LEU C 114 -20.337 -19.392 22.102 1.00 0.00 C \nATOM 5903 C LEU C 114 -20.439 -20.338 20.911 1.00 0.00 C \nATOM 5904 O LEU C 114 -19.505 -21.094 20.633 1.00 0.00 O \nATOM 5905 CB LEU C 114 -18.949 -18.768 22.204 1.00 0.00 C \nATOM 5906 CG LEU C 114 -18.719 -17.526 21.333 1.00 0.00 C \nATOM 5907 CD1 LEU C 114 -17.635 -16.639 21.923 1.00 0.00 C \nATOM 5908 CD2 LEU C 114 -18.374 -17.900 19.896 1.00 0.00 C \nATOM 5909 H LEU C 114 -20.388 -20.979 23.274 1.00 0.00 H \nATOM 5910 HA LEU C 114 -20.947 -18.644 22.003 1.00 0.00 H \nATOM 5911 HB2 LEU C 114 -18.786 -18.529 23.130 1.00 0.00 H \nATOM 5912 HB3 LEU C 114 -18.291 -19.439 21.964 1.00 0.00 H \nATOM 5913 HG LEU C 114 -19.552 -17.029 21.319 1.00 0.00 H \nATOM 5914 HD11 LEU C 114 -17.508 -15.862 21.356 1.00 0.00 H \nATOM 5915 HD12 LEU C 114 -17.900 -16.351 22.811 1.00 0.00 H \nATOM 5916 HD13 LEU C 114 -16.804 -17.137 21.979 1.00 0.00 H \nATOM 5917 HD21 LEU C 114 -18.236 -17.093 19.376 1.00 0.00 H \nATOM 5918 HD22 LEU C 114 -17.564 -18.434 19.886 1.00 0.00 H \nATOM 5919 HD23 LEU C 114 -19.103 -18.412 19.511 1.00 0.00 H \nATOM 5920 N ASP C 115 -21.566 -20.294 20.213 1.00 0.00 N \nATOM 5921 CA ASP C 115 -21.778 -21.106 19.018 1.00 0.00 C \nATOM 5922 C ASP C 115 -21.476 -20.224 17.813 1.00 0.00 C \nATOM 5923 O ASP C 115 -22.264 -19.346 17.456 1.00 0.00 O \nATOM 5924 CB ASP C 115 -23.198 -21.662 18.971 1.00 0.00 C \nATOM 5925 CG ASP C 115 -23.336 -22.827 18.005 1.00 0.00 C \nATOM 5926 OD1 ASP C 115 -22.646 -22.830 16.964 1.00 0.00 O \nATOM 5927 OD2 ASP C 115 -24.137 -23.739 18.290 1.00 0.00 O \nATOM 5928 H ASP C 115 -22.233 -19.791 20.418 1.00 0.00 H \nATOM 5929 HA ASP C 115 -21.190 -21.877 19.021 1.00 0.00 H \nATOM 5930 HB2 ASP C 115 -23.459 -21.950 19.860 1.00 0.00 H \nATOM 5931 HB3 ASP C 115 -23.810 -20.956 18.711 1.00 0.00 H \nATOM 5932 N ASP C 116 -20.320 -20.460 17.191 1.00 0.00 N \nATOM 5933 CA ASP C 116 -19.897 -19.640 16.063 1.00 0.00 C \nATOM 5934 C ASP C 116 -20.659 -19.970 14.787 1.00 0.00 C \nATOM 5935 O ASP C 116 -20.637 -19.170 13.846 1.00 0.00 O \nATOM 5936 CB ASP C 116 -18.395 -19.814 15.830 1.00 0.00 C \nATOM 5937 CG ASP C 116 -17.716 -18.528 15.410 1.00 0.00 C \nATOM 5938 OD1 ASP C 116 -18.253 -17.440 15.708 1.00 0.00 O \nATOM 5939 OD2 ASP C 116 -16.640 -18.605 14.780 1.00 0.00 O \nATOM 5940 H ASP C 116 -19.772 -21.086 17.407 1.00 0.00 H \nATOM 5941 HA ASP C 116 -20.094 -18.717 16.287 1.00 0.00 H \nATOM 5942 HB2 ASP C 116 -17.981 -20.143 16.643 1.00 0.00 H \nATOM 5943 HB3 ASP C 116 -18.253 -20.488 15.147 1.00 0.00 H \nATOM 5944 N ASN C 117 -21.333 -21.119 14.734 1.00 0.00 N \nATOM 5945 CA ASN C 117 -22.156 -21.460 13.580 1.00 0.00 C \nATOM 5946 C ASN C 117 -23.569 -20.909 13.702 1.00 0.00 C \nATOM 5947 O ASN C 117 -24.138 -20.439 12.711 1.00 0.00 O \nATOM 5948 CB ASN C 117 -22.219 -22.978 13.394 1.00 0.00 C \nATOM 5949 CG ASN C 117 -20.981 -23.685 13.907 1.00 0.00 C \nATOM 5950 OD1 ASN C 117 -19.881 -23.496 13.386 1.00 0.00 O \nATOM 5951 ND2 ASN C 117 -21.157 -24.511 14.932 1.00 0.00 N \nATOM 5952 H ASN C 117 -21.325 -21.712 15.356 1.00 0.00 H \nATOM 5953 HA ASN C 117 -21.738 -21.052 12.806 1.00 0.00 H \nATOM 5954 HB2 ASN C 117 -22.999 -23.324 13.856 1.00 0.00 H \nATOM 5955 HB3 ASN C 117 -22.335 -23.180 12.452 1.00 0.00 H \nATOM 5956 HD21 ASN C 117 -20.487 -24.940 15.259 1.00 0.00 H \nATOM 5957 HD22 ASN C 117 -21.941 -24.617 15.269 1.00 0.00 H \nATOM 5958 N GLU C 118 -24.140 -20.943 14.904 1.00 0.00 N \nATOM 5959 CA GLU C 118 -25.499 -20.478 15.138 1.00 0.00 C \nATOM 5960 C GLU C 118 -25.548 -19.068 15.700 1.00 0.00 C \nATOM 5961 O GLU C 118 -26.644 -18.544 15.927 1.00 0.00 O \nATOM 5962 CB GLU C 118 -26.224 -21.429 16.096 1.00 0.00 C \nATOM 5963 CG GLU C 118 -26.066 -22.898 15.757 1.00 0.00 C \nATOM 5964 CD GLU C 118 -26.600 -23.233 14.383 1.00 0.00 C \nATOM 5965 OE1 GLU C 118 -25.860 -23.855 13.592 1.00 0.00 O \nATOM 5966 OE2 GLU C 118 -27.760 -22.872 14.092 1.00 0.00 O \nATOM 5967 H GLU C 118 -23.745 -21.239 15.609 1.00 0.00 H \nATOM 5968 HA GLU C 118 -25.942 -20.466 14.275 1.00 0.00 H \nATOM 5969 HB2 GLU C 118 -25.894 -21.278 16.996 1.00 0.00 H \nATOM 5970 HB3 GLU C 118 -27.169 -21.209 16.100 1.00 0.00 H \nATOM 5971 HG2 GLU C 118 -25.128 -23.139 15.804 1.00 0.00 H \nATOM 5972 HG3 GLU C 118 -26.530 -23.432 16.421 1.00 0.00 H \nATOM 5973 N HIS C 119 -24.391 -18.444 15.925 1.00 0.00 N \nATOM 5974 CA HIS C 119 -24.302 -17.070 16.416 1.00 0.00 C \nATOM 5975 C HIS C 119 -25.079 -16.905 17.725 1.00 0.00 C \nATOM 5976 O HIS C 119 -26.037 -16.135 17.823 1.00 0.00 O \nATOM 5977 CB HIS C 119 -24.790 -16.081 15.353 1.00 0.00 C \nATOM 5978 CG HIS C 119 -24.374 -16.427 13.956 1.00 0.00 C \nATOM 5979 ND1 HIS C 119 -23.055 -16.513 13.570 1.00 0.00 N \nATOM 5980 CD2 HIS C 119 -25.108 -16.688 12.848 1.00 0.00 C \nATOM 5981 CE1 HIS C 119 -22.992 -16.823 12.287 1.00 0.00 C \nATOM 5982 NE2 HIS C 119 -24.224 -16.934 11.825 1.00 0.00 N \nATOM 5983 H HIS C 119 -23.625 -18.813 15.794 1.00 0.00 H \nATOM 5984 HA HIS C 119 -23.370 -16.874 16.600 1.00 0.00 H \nATOM 5985 HB2 HIS C 119 -25.758 -16.034 15.389 1.00 0.00 H \nATOM 5986 HB3 HIS C 119 -24.455 -15.197 15.570 1.00 0.00 H \nATOM 5987 HD1 HIS C 119 -22.378 -16.385 14.084 1.00 0.00 H \nATOM 5988 HD2 HIS C 119 -26.036 -16.699 12.790 1.00 0.00 H \nATOM 5989 HE1 HIS C 119 -22.213 -16.943 11.794 1.00 0.00 H \nATOM 5990 HE2 HIS C 119 -24.438 -17.129 11.015 1.00 0.00 H \nATOM 5991 N ILE C 120 -24.647 -17.656 18.738 1.00 0.00 N \nATOM 5992 CA ILE C 120 -25.228 -17.605 20.076 1.00 0.00 C \nATOM 5993 C ILE C 120 -24.121 -17.302 21.075 1.00 0.00 C \nATOM 5994 O ILE C 120 -23.072 -17.956 21.062 1.00 0.00 O \nATOM 5995 CB ILE C 120 -25.941 -18.918 20.449 1.00 0.00 C \nATOM 5996 CG1 ILE C 120 -26.853 -19.387 19.315 1.00 0.00 C \nATOM 5997 CG2 ILE C 120 -26.742 -18.738 21.730 1.00 0.00 C \nATOM 5998 CD1 ILE C 120 -27.385 -20.793 19.512 1.00 0.00 C \nATOM 5999 H ILE C 120 -23.999 -18.217 18.664 1.00 0.00 H \nATOM 6000 HA ILE C 120 -25.901 -16.906 20.094 1.00 0.00 H \nATOM 6001 HB ILE C 120 -25.265 -19.598 20.594 1.00 0.00 H \nATOM 6002 HG12 ILE C 120 -27.600 -18.774 19.236 1.00 0.00 H \nATOM 6003 HG13 ILE C 120 -26.364 -19.348 18.478 1.00 0.00 H \nATOM 6004 HG21 ILE C 120 -27.186 -19.571 21.954 1.00 0.00 H \nATOM 6005 HG22 ILE C 120 -26.146 -18.486 22.452 1.00 0.00 H \nATOM 6006 HG23 ILE C 120 -27.406 -18.043 21.602 1.00 0.00 H \nATOM 6007 HD11 ILE C 120 -27.954 -21.032 18.764 1.00 0.00 H \nATOM 6008 HD12 ILE C 120 -26.643 -21.416 19.565 1.00 0.00 H \nATOM 6009 HD13 ILE C 120 -27.899 -20.833 20.334 1.00 0.00 H \nATOM 6010 N LEU C 121 -24.352 -16.309 21.930 1.00 0.00 N \nATOM 6011 CA LEU C 121 -23.402 -15.923 22.968 1.00 0.00 C \nATOM 6012 C LEU C 121 -24.117 -15.905 24.310 1.00 0.00 C \nATOM 6013 O LEU C 121 -25.071 -15.143 24.497 1.00 0.00 O \nATOM 6014 CB LEU C 121 -22.785 -14.554 22.669 1.00 0.00 C \nATOM 6015 CG LEU C 121 -21.879 -13.980 23.760 1.00 0.00 C \nATOM 6016 CD1 LEU C 121 -20.551 -14.714 23.788 1.00 0.00 C \nATOM 6017 CD2 LEU C 121 -21.661 -12.493 23.549 1.00 0.00 C \nATOM 6018 H LEU C 121 -25.071 -15.837 21.923 1.00 0.00 H \nATOM 6019 HA LEU C 121 -22.679 -16.569 22.992 1.00 0.00 H \nATOM 6020 HB2 LEU C 121 -22.272 -14.621 21.848 1.00 0.00 H \nATOM 6021 HB3 LEU C 121 -23.503 -13.923 22.504 1.00 0.00 H \nATOM 6022 HG LEU C 121 -22.317 -14.104 24.616 1.00 0.00 H \nATOM 6023 HD11 LEU C 121 -19.988 -14.339 24.484 1.00 0.00 H \nATOM 6024 HD12 LEU C 121 -20.705 -15.655 23.969 1.00 0.00 H \nATOM 6025 HD13 LEU C 121 -20.110 -14.618 22.929 1.00 0.00 H \nATOM 6026 HD21 LEU C 121 -21.085 -12.148 24.249 1.00 0.00 H \nATOM 6027 HD22 LEU C 121 -21.243 -12.346 22.686 1.00 0.00 H \nATOM 6028 HD23 LEU C 121 -22.515 -12.033 23.577 1.00 0.00 H \nATOM 6029 N SER C 122 -23.660 -16.742 25.240 1.00 0.00 N \nATOM 6030 CA SER C 122 -24.241 -16.840 26.574 1.00 0.00 C \nATOM 6031 C SER C 122 -23.198 -16.453 27.612 1.00 0.00 C \nATOM 6032 O SER C 122 -22.085 -16.989 27.610 1.00 0.00 O \nATOM 6033 CB SER C 122 -24.758 -18.253 26.847 1.00 0.00 C \nATOM 6034 OG SER C 122 -25.499 -18.742 25.743 1.00 0.00 O \nATOM 6035 H SER C 122 -22.997 -17.274 25.111 1.00 0.00 H \nATOM 6036 HA SER C 122 -24.994 -16.231 26.629 1.00 0.00 H \nATOM 6037 HB2 SER C 122 -24.011 -18.845 27.028 1.00 0.00 H \nATOM 6038 HB3 SER C 122 -25.316 -18.250 27.640 1.00 0.00 H \nATOM 6039 HG SER C 122 -25.703 -19.546 25.876 1.00 0.00 H \nATOM 6040 N VAL C 123 -23.563 -15.525 28.496 1.00 0.00 N \nATOM 6041 CA VAL C 123 -22.672 -15.015 29.530 1.00 0.00 C \nATOM 6042 C VAL C 123 -23.356 -15.148 30.886 1.00 0.00 C \nATOM 6043 O VAL C 123 -24.581 -15.047 30.997 1.00 0.00 O \nATOM 6044 CB VAL C 123 -22.278 -13.545 29.242 1.00 0.00 C \nATOM 6045 CG1 VAL C 123 -21.457 -12.953 30.373 1.00 0.00 C \nATOM 6046 CG2 VAL C 123 -21.517 -13.449 27.928 1.00 0.00 C \nATOM 6047 H VAL C 123 -24.347 -15.171 28.510 1.00 0.00 H \nATOM 6048 HA VAL C 123 -21.853 -15.535 29.536 1.00 0.00 H \nATOM 6049 HB VAL C 123 -23.096 -13.029 29.172 1.00 0.00 H \nATOM 6050 HG11 VAL C 123 -21.228 -12.035 30.161 1.00 0.00 H \nATOM 6051 HG12 VAL C 123 -21.973 -12.976 31.194 1.00 0.00 H \nATOM 6052 HG13 VAL C 123 -20.644 -13.470 30.488 1.00 0.00 H \nATOM 6053 HG21 VAL C 123 -21.277 -12.524 27.760 1.00 0.00 H \nATOM 6054 HG22 VAL C 123 -20.712 -13.988 27.980 1.00 0.00 H \nATOM 6055 HG23 VAL C 123 -22.077 -13.774 27.205 1.00 0.00 H \nATOM 6056 N ARG C 124 -22.553 -15.377 31.925 1.00 0.00 N \nATOM 6057 CA ARG C 124 -23.039 -15.443 33.298 1.00 0.00 C \nATOM 6058 C ARG C 124 -22.187 -14.534 34.172 1.00 0.00 C \nATOM 6059 O ARG C 124 -20.956 -14.544 34.069 1.00 0.00 O \nATOM 6060 CB ARG C 124 -23.007 -16.879 33.836 1.00 0.00 C \nATOM 6061 CG ARG C 124 -23.636 -17.036 35.212 1.00 0.00 C \nATOM 6062 CD ARG C 124 -23.800 -18.500 35.586 1.00 0.00 C \nATOM 6063 NE ARG C 124 -25.206 -18.895 35.635 1.00 0.00 N \nATOM 6064 CZ ARG C 124 -26.020 -18.649 36.656 1.00 0.00 C \nATOM 6065 NH1 ARG C 124 -25.572 -18.006 37.726 1.00 0.00 N \nATOM 6066 NH2 ARG C 124 -27.283 -19.049 36.608 1.00 0.00 N \nATOM 6067 H ARG C 124 -21.705 -15.499 31.850 1.00 0.00 H \nATOM 6068 HA ARG C 124 -23.962 -15.146 33.315 1.00 0.00 H \nATOM 6069 HB2 ARG C 124 -23.469 -17.459 33.211 1.00 0.00 H \nATOM 6070 HB3 ARG C 124 -22.086 -17.180 33.875 1.00 0.00 H \nATOM 6071 HG2 ARG C 124 -23.084 -16.592 35.874 1.00 0.00 H \nATOM 6072 HG3 ARG C 124 -24.502 -16.599 35.225 1.00 0.00 H \nATOM 6073 HD2 ARG C 124 -23.331 -19.053 34.941 1.00 0.00 H \nATOM 6074 HD3 ARG C 124 -23.389 -18.661 36.450 1.00 0.00 H \nATOM 6075 HE ARG C 124 -25.528 -19.315 34.957 1.00 0.00 H \nATOM 6076 HH11 ARG C 124 -24.753 -17.747 37.760 1.00 0.00 H \nATOM 6077 HH12 ARG C 124 -26.101 -17.848 38.385 1.00 0.00 H \nATOM 6078 HH21 ARG C 124 -27.575 -19.468 35.916 1.00 0.00 H \nATOM 6079 HH22 ARG C 124 -27.810 -18.890 37.269 1.00 0.00 H \nATOM 6080 N PHE C 125 -22.845 -13.754 35.028 1.00 0.00 N \nATOM 6081 CA PHE C 125 -22.150 -12.866 35.952 1.00 0.00 C \nATOM 6082 C PHE C 125 -21.711 -13.657 37.180 1.00 0.00 C \nATOM 6083 O PHE C 125 -22.532 -14.318 37.825 1.00 0.00 O \nATOM 6084 CB PHE C 125 -23.053 -11.702 36.357 1.00 0.00 C \nATOM 6085 CG PHE C 125 -23.270 -10.685 35.267 1.00 0.00 C \nATOM 6086 CD1 PHE C 125 -22.646 -10.809 34.036 1.00 0.00 C \nATOM 6087 CD2 PHE C 125 -24.110 -9.603 35.477 1.00 0.00 C \nATOM 6088 CE1 PHE C 125 -22.852 -9.873 33.039 1.00 0.00 C \nATOM 6089 CE2 PHE C 125 -24.320 -8.666 34.484 1.00 0.00 C \nATOM 6090 CZ PHE C 125 -23.691 -8.800 33.264 1.00 0.00 C \nATOM 6091 H PHE C 125 -23.702 -13.726 35.088 1.00 0.00 H \nATOM 6092 HA PHE C 125 -21.367 -12.499 35.514 1.00 0.00 H \nATOM 6093 HB2 PHE C 125 -23.913 -12.054 36.634 1.00 0.00 H \nATOM 6094 HB3 PHE C 125 -22.666 -11.258 37.128 1.00 0.00 H \nATOM 6095 HD1 PHE C 125 -22.081 -11.531 33.878 1.00 0.00 H \nATOM 6096 HD2 PHE C 125 -24.538 -9.506 36.297 1.00 0.00 H \nATOM 6097 HE1 PHE C 125 -22.426 -9.966 32.218 1.00 0.00 H \nATOM 6098 HE2 PHE C 125 -24.886 -7.944 34.638 1.00 0.00 H \nATOM 6099 HZ PHE C 125 -23.832 -8.170 32.595 1.00 0.00 H \nATOM 6100 N VAL C 126 -20.421 -13.588 37.506 1.00 0.00 N \nATOM 6101 CA VAL C 126 -19.864 -14.318 38.637 1.00 0.00 C \nATOM 6102 C VAL C 126 -19.157 -13.382 39.617 1.00 0.00 C \nATOM 6103 O VAL C 126 -18.348 -13.825 40.424 1.00 0.00 O \nATOM 6104 CB VAL C 126 -18.922 -15.443 38.166 1.00 0.00 C \nATOM 6105 CG1 VAL C 126 -19.704 -16.511 37.414 1.00 0.00 C \nATOM 6106 CG2 VAL C 126 -17.810 -14.876 37.299 1.00 0.00 C \nATOM 6107 H VAL C 126 -19.846 -13.115 37.075 1.00 0.00 H \nATOM 6108 HA VAL C 126 -20.605 -14.729 39.109 1.00 0.00 H \nATOM 6109 HB VAL C 126 -18.518 -15.856 38.945 1.00 0.00 H \nATOM 6110 HG11 VAL C 126 -19.099 -17.211 37.124 1.00 0.00 H \nATOM 6111 HG12 VAL C 126 -20.380 -16.889 37.998 1.00 0.00 H \nATOM 6112 HG13 VAL C 126 -20.132 -16.114 36.640 1.00 0.00 H \nATOM 6113 HG21 VAL C 126 -17.226 -15.595 37.010 1.00 0.00 H \nATOM 6114 HG22 VAL C 126 -18.195 -14.441 36.522 1.00 0.00 H \nATOM 6115 HG23 VAL C 126 -17.298 -14.230 37.810 1.00 0.00 H \nATOM 6116 N GLY C 127 -19.457 -12.091 39.557 1.00 0.00 N \nATOM 6117 CA GLY C 127 -18.862 -11.144 40.479 1.00 0.00 C \nATOM 6118 C GLY C 127 -19.127 -9.725 40.033 1.00 0.00 C \nATOM 6119 O GLY C 127 -19.638 -9.470 38.938 1.00 0.00 O \nATOM 6120 H GLY C 127 -20.003 -11.746 38.989 1.00 0.00 H \nATOM 6121 HA2 GLY C 127 -19.224 -11.281 41.369 1.00 0.00 H \nATOM 6122 HA3 GLY C 127 -17.906 -11.297 40.535 1.00 0.00 H \nATOM 6123 N GLY C 128 -18.757 -8.794 40.909 1.00 0.00 N \nATOM 6124 CA GLY C 128 -18.941 -7.382 40.639 1.00 0.00 C \nATOM 6125 C GLY C 128 -19.865 -6.695 41.624 1.00 0.00 C \nATOM 6126 O GLY C 128 -20.669 -7.349 42.296 1.00 0.00 O \nATOM 6127 H GLY C 128 -18.395 -8.967 41.670 1.00 0.00 H \nATOM 6128 HA2 GLY C 128 -18.077 -6.941 40.655 1.00 0.00 H \nATOM 6129 HA3 GLY C 128 -19.297 -7.275 39.743 1.00 0.00 H \nATOM 6130 N ASP C 129 -19.753 -5.371 41.721 1.00 0.00 N \nATOM 6131 CA ASP C 129 -20.567 -4.559 42.617 1.00 0.00 C \nATOM 6132 C ASP C 129 -21.864 -4.081 41.968 1.00 0.00 C \nATOM 6133 O ASP C 129 -22.424 -3.066 42.399 1.00 0.00 O \nATOM 6134 CB ASP C 129 -19.761 -3.356 43.115 1.00 0.00 C \nATOM 6135 CG ASP C 129 -19.114 -2.572 41.985 1.00 0.00 C \nATOM 6136 OD1 ASP C 129 -19.359 -2.900 40.804 1.00 0.00 O \nATOM 6137 OD2 ASP C 129 -18.362 -1.619 42.279 1.00 0.00 O \nATOM 6138 H ASP C 129 -19.191 -4.913 41.258 1.00 0.00 H \nATOM 6139 HA ASP C 129 -20.813 -5.126 43.365 1.00 0.00 H \nATOM 6140 HB2 ASP C 129 -20.344 -2.767 43.619 1.00 0.00 H \nATOM 6141 HB3 ASP C 129 -19.073 -3.663 43.725 1.00 0.00 H \nATOM 6142 N HIS C 130 -22.354 -4.788 40.950 1.00 0.00 N \nATOM 6143 CA HIS C 130 -23.511 -4.361 40.172 1.00 0.00 C \nATOM 6144 C HIS C 130 -24.858 -4.753 40.770 1.00 0.00 C \nATOM 6145 O HIS C 130 -25.887 -4.275 40.277 1.00 0.00 O \nATOM 6146 CB HIS C 130 -23.416 -4.932 38.757 1.00 0.00 C \nATOM 6147 CG HIS C 130 -22.932 -6.348 38.713 1.00 0.00 C \nATOM 6148 ND1 HIS C 130 -23.712 -7.413 39.108 1.00 0.00 N \nATOM 6149 CD2 HIS C 130 -21.742 -6.873 38.337 1.00 0.00 C \nATOM 6150 CE1 HIS C 130 -23.026 -8.534 38.970 1.00 0.00 C \nATOM 6151 NE2 HIS C 130 -21.827 -8.234 38.505 1.00 0.00 N \nATOM 6152 H HIS C 130 -22.019 -5.536 40.691 1.00 0.00 H \nATOM 6153 HA HIS C 130 -23.482 -3.391 40.172 1.00 0.00 H \nATOM 6154 HB2 HIS C 130 -24.289 -4.884 38.338 1.00 0.00 H \nATOM 6155 HB3 HIS C 130 -22.818 -4.377 38.232 1.00 0.00 H \nATOM 6156 HD1 HIS C 130 -24.519 -7.357 39.399 1.00 0.00 H \nATOM 6157 HD2 HIS C 130 -21.005 -6.401 38.024 1.00 0.00 H \nATOM 6158 HE1 HIS C 130 -23.335 -9.389 39.167 1.00 0.00 H \nATOM 6159 HE2 HIS C 130 -21.201 -8.799 38.335 1.00 0.00 H \nATOM 6160 N ARG C 131 -24.882 -5.611 41.794 1.00 0.00 N \nATOM 6161 CA ARG C 131 -26.103 -6.064 42.466 1.00 0.00 C \nATOM 6162 C ARG C 131 -26.986 -6.945 41.587 1.00 0.00 C \nATOM 6163 O ARG C 131 -28.177 -7.103 41.873 1.00 0.00 O \nATOM 6164 CB ARG C 131 -26.937 -4.887 42.988 1.00 0.00 C \nATOM 6165 CG ARG C 131 -26.219 -3.969 43.953 1.00 0.00 C \nATOM 6166 CD ARG C 131 -27.221 -3.269 44.853 1.00 0.00 C \nATOM 6167 NE ARG C 131 -28.408 -2.843 44.115 1.00 0.00 N \nATOM 6168 CZ ARG C 131 -29.655 -3.021 44.540 1.00 0.00 C \nATOM 6169 NH1 ARG C 131 -29.881 -3.618 45.703 1.00 0.00 N \nATOM 6170 NH2 ARG C 131 -30.677 -2.600 43.807 1.00 0.00 N \nATOM 6171 H ARG C 131 -24.167 -5.955 42.126 1.00 0.00 H \nATOM 6172 HA ARG C 131 -25.792 -6.600 43.212 1.00 0.00 H \nATOM 6173 HB2 ARG C 131 -27.241 -4.363 42.230 1.00 0.00 H \nATOM 6174 HB3 ARG C 131 -27.728 -5.238 43.426 1.00 0.00 H \nATOM 6175 HG2 ARG C 131 -25.593 -4.479 44.490 1.00 0.00 H \nATOM 6176 HG3 ARG C 131 -25.702 -3.312 43.461 1.00 0.00 H \nATOM 6177 HD2 ARG C 131 -27.483 -3.866 45.571 1.00 0.00 H \nATOM 6178 HD3 ARG C 131 -26.802 -2.497 45.265 1.00 0.00 H \nATOM 6179 HE ARG C 131 -28.293 -2.452 43.358 1.00 0.00 H \nATOM 6180 HH11 ARG C 131 -29.221 -3.890 46.182 1.00 0.00 H \nATOM 6181 HH12 ARG C 131 -30.688 -3.733 45.978 1.00 0.00 H \nATOM 6182 HH21 ARG C 131 -30.534 -2.210 43.054 1.00 0.00 H \nATOM 6183 HH22 ARG C 131 -31.482 -2.717 44.085 1.00 0.00 H \nATOM 6184 N LEU C 132 -26.440 -7.523 40.523 1.00 0.00 N \nATOM 6185 CA LEU C 132 -27.181 -8.412 39.627 1.00 0.00 C \nATOM 6186 C LEU C 132 -26.646 -9.825 39.849 1.00 0.00 C \nATOM 6187 O LEU C 132 -25.677 -10.241 39.213 1.00 0.00 O \nATOM 6188 CB LEU C 132 -27.042 -7.984 38.166 1.00 0.00 C \nATOM 6189 CG LEU C 132 -27.601 -6.620 37.757 1.00 0.00 C \nATOM 6190 CD1 LEU C 132 -26.959 -6.160 36.461 1.00 0.00 C \nATOM 6191 CD2 LEU C 132 -29.114 -6.678 37.613 1.00 0.00 C \nATOM 6192 H LEU C 132 -25.618 -7.410 40.296 1.00 0.00 H \nATOM 6193 HA LEU C 132 -28.130 -8.374 39.825 1.00 0.00 H \nATOM 6194 HB2 LEU C 132 -26.098 -7.997 37.942 1.00 0.00 H \nATOM 6195 HB3 LEU C 132 -27.473 -8.658 37.617 1.00 0.00 H \nATOM 6196 HG LEU C 132 -27.390 -5.979 38.454 1.00 0.00 H \nATOM 6197 HD11 LEU C 132 -27.320 -5.295 36.210 1.00 0.00 H \nATOM 6198 HD12 LEU C 132 -26.000 -6.087 36.583 1.00 0.00 H \nATOM 6199 HD13 LEU C 132 -27.147 -6.804 35.760 1.00 0.00 H \nATOM 6200 HD21 LEU C 132 -29.448 -5.805 37.354 1.00 0.00 H \nATOM 6201 HD22 LEU C 132 -29.350 -7.329 36.934 1.00 0.00 H \nATOM 6202 HD23 LEU C 132 -29.510 -6.937 38.460 1.00 0.00 H \nATOM 6203 N LYS C 133 -27.286 -10.566 40.748 1.00 0.00 N \nATOM 6204 CA LYS C 133 -26.796 -11.881 41.131 1.00 0.00 C \nATOM 6205 C LYS C 133 -27.521 -12.980 40.367 1.00 0.00 C \nATOM 6206 O LYS C 133 -28.712 -12.874 40.063 1.00 0.00 O \nATOM 6207 CB LYS C 133 -26.965 -12.106 42.635 1.00 0.00 C \nATOM 6208 CG LYS C 133 -26.311 -11.041 43.499 1.00 0.00 C \nATOM 6209 CD LYS C 133 -25.219 -11.635 44.370 1.00 0.00 C \nATOM 6210 CE LYS C 133 -24.022 -10.704 44.469 1.00 0.00 C \nATOM 6211 NZ LYS C 133 -22.742 -11.457 44.598 1.00 0.00 N \nATOM 6212 H LYS C 133 -28.008 -10.323 41.148 1.00 0.00 H \nATOM 6213 HA LYS C 133 -25.853 -11.917 40.909 1.00 0.00 H \nATOM 6214 HB2 LYS C 133 -27.912 -12.141 42.843 1.00 0.00 H \nATOM 6215 HB3 LYS C 133 -26.592 -12.971 42.867 1.00 0.00 H \nATOM 6216 HG2 LYS C 133 -25.936 -10.348 42.934 1.00 0.00 H \nATOM 6217 HG3 LYS C 133 -26.981 -10.619 44.059 1.00 0.00 H \nATOM 6218 HD2 LYS C 133 -25.570 -11.809 45.257 1.00 0.00 H \nATOM 6219 HD3 LYS C 133 -24.938 -12.488 44.003 1.00 0.00 H \nATOM 6220 HE2 LYS C 133 -23.986 -10.139 43.682 1.00 0.00 H \nATOM 6221 HE3 LYS C 133 -24.131 -10.118 45.234 1.00 0.00 H \nATOM 6222 HZ1 LYS C 133 -22.137 -11.112 44.044 1.00 0.00 H \nATOM 6223 HZ2 LYS C 133 -22.445 -11.397 45.435 1.00 0.00 H \nATOM 6224 HZ3 LYS C 133 -22.878 -12.312 44.393 1.00 0.00 H \nATOM 6225 N ASN C 134 -26.777 -14.051 40.077 1.00 0.00 N \nATOM 6226 CA ASN C 134 -27.237 -15.135 39.210 1.00 0.00 C \nATOM 6227 C ASN C 134 -27.782 -14.601 37.887 1.00 0.00 C \nATOM 6228 O ASN C 134 -28.764 -15.108 37.343 1.00 0.00 O \nATOM 6229 CB ASN C 134 -28.271 -16.005 39.924 1.00 0.00 C \nATOM 6230 CG ASN C 134 -27.677 -16.767 41.097 1.00 0.00 C \nATOM 6231 OD1 ASN C 134 -26.484 -17.078 41.109 1.00 0.00 O \nATOM 6232 ND2 ASN C 134 -28.507 -17.067 42.091 1.00 0.00 N \nATOM 6233 H ASN C 134 -25.982 -14.168 40.383 1.00 0.00 H \nATOM 6234 HA ASN C 134 -26.470 -15.692 39.003 1.00 0.00 H \nATOM 6235 HB2 ASN C 134 -28.998 -15.446 40.240 1.00 0.00 H \nATOM 6236 HB3 ASN C 134 -28.652 -16.635 39.292 1.00 0.00 H \nATOM 6237 HD21 ASN C 134 -28.218 -17.495 42.778 1.00 0.00 H \nATOM 6238 HD22 ASN C 134 -29.333 -16.833 42.047 1.00 0.00 H \nATOM 6239 N TYR C 135 -27.137 -13.563 37.360 1.00 0.00 N \nATOM 6240 CA TYR C 135 -27.513 -13.026 36.059 1.00 0.00 C \nATOM 6241 C TYR C 135 -26.987 -13.949 34.968 1.00 0.00 C \nATOM 6242 O TYR C 135 -25.775 -14.160 34.853 1.00 0.00 O \nATOM 6243 CB TYR C 135 -26.973 -11.607 35.879 1.00 0.00 C \nATOM 6244 CG TYR C 135 -27.266 -10.997 34.522 1.00 0.00 C \nATOM 6245 CD1 TYR C 135 -26.427 -11.226 33.437 1.00 0.00 C \nATOM 6246 CD2 TYR C 135 -28.379 -10.187 34.327 1.00 0.00 C \nATOM 6247 CE1 TYR C 135 -26.690 -10.672 32.200 1.00 0.00 C \nATOM 6248 CE2 TYR C 135 -28.648 -9.627 33.088 1.00 0.00 C \nATOM 6249 CZ TYR C 135 -27.799 -9.876 32.029 1.00 0.00 C \nATOM 6250 OH TYR C 135 -28.058 -9.325 30.796 1.00 0.00 O \nATOM 6251 H TYR C 135 -26.481 -13.157 37.740 1.00 0.00 H \nATOM 6252 HA TYR C 135 -28.480 -12.979 36.000 1.00 0.00 H \nATOM 6253 HB2 TYR C 135 -27.352 -11.038 36.567 1.00 0.00 H \nATOM 6254 HB3 TYR C 135 -26.013 -11.617 36.017 1.00 0.00 H \nATOM 6255 HD1 TYR C 135 -25.675 -11.762 33.547 1.00 0.00 H \nATOM 6256 HD2 TYR C 135 -28.952 -10.018 35.040 1.00 0.00 H \nATOM 6257 HE1 TYR C 135 -26.119 -10.836 31.484 1.00 0.00 H \nATOM 6258 HE2 TYR C 135 -29.396 -9.087 32.971 1.00 0.00 H \nATOM 6259 HH TYR C 135 -27.887 -9.887 30.196 1.00 0.00 H \nATOM 6260 N SER C 136 -27.898 -14.498 34.173 1.00 0.00 N \nATOM 6261 CA SER C 136 -27.565 -15.295 33.002 1.00 0.00 C \nATOM 6262 C SER C 136 -28.274 -14.690 31.801 1.00 0.00 C \nATOM 6263 O SER C 136 -29.450 -14.329 31.888 1.00 0.00 O \nATOM 6264 CB SER C 136 -27.980 -16.759 33.186 1.00 0.00 C \nATOM 6265 OG SER C 136 -28.359 -17.343 31.953 1.00 0.00 O \nATOM 6266 H SER C 136 -28.744 -14.415 34.303 1.00 0.00 H \nATOM 6267 HA SER C 136 -26.604 -15.286 32.868 1.00 0.00 H \nATOM 6268 HB2 SER C 136 -27.244 -17.260 33.572 1.00 0.00 H \nATOM 6269 HB3 SER C 136 -28.719 -16.812 33.812 1.00 0.00 H \nATOM 6270 HG SER C 136 -28.580 -18.144 32.078 1.00 0.00 H \nATOM 6271 N SER C 137 -27.568 -14.586 30.676 1.00 0.00 N \nATOM 6272 CA SER C 137 -28.128 -13.922 29.509 1.00 0.00 C \nATOM 6273 C SER C 137 -27.785 -14.684 28.239 1.00 0.00 C \nATOM 6274 O SER C 137 -26.732 -15.318 28.136 1.00 0.00 O \nATOM 6275 CB SER C 137 -27.629 -12.475 29.396 1.00 0.00 C \nATOM 6276 OG SER C 137 -26.429 -12.407 28.647 1.00 0.00 O \nATOM 6277 H SER C 137 -26.771 -14.891 30.571 1.00 0.00 H \nATOM 6278 HA SER C 137 -29.092 -13.907 29.619 1.00 0.00 H \nATOM 6279 HB2 SER C 137 -28.309 -11.927 28.974 1.00 0.00 H \nATOM 6280 HB3 SER C 137 -27.482 -12.110 30.283 1.00 0.00 H \nATOM 6281 HG SER C 137 -26.437 -11.718 28.166 1.00 0.00 H \nATOM 6282 N ILE C 138 -28.692 -14.600 27.267 1.00 0.00 N \nATOM 6283 CA ILE C 138 -28.564 -15.269 25.977 1.00 0.00 C \nATOM 6284 C ILE C 138 -28.692 -14.206 24.893 1.00 0.00 C \nATOM 6285 O ILE C 138 -29.703 -13.495 24.835 1.00 0.00 O \nATOM 6286 CB ILE C 138 -29.632 -16.361 25.791 1.00 0.00 C \nATOM 6287 CG1 ILE C 138 -29.616 -17.363 26.952 1.00 0.00 C \nATOM 6288 CG2 ILE C 138 -29.443 -17.072 24.461 1.00 0.00 C \nATOM 6289 CD1 ILE C 138 -28.310 -18.091 27.134 1.00 0.00 C \nATOM 6290 H ILE C 138 -29.415 -14.141 27.343 1.00 0.00 H \nATOM 6291 HA ILE C 138 -27.703 -15.713 25.925 1.00 0.00 H \nATOM 6292 HB ILE C 138 -30.501 -15.930 25.788 1.00 0.00 H \nATOM 6293 HG12 ILE C 138 -29.827 -16.892 27.773 1.00 0.00 H \nATOM 6294 HG13 ILE C 138 -30.320 -18.016 26.810 1.00 0.00 H \nATOM 6295 HG21 ILE C 138 -30.123 -17.756 24.360 1.00 0.00 H \nATOM 6296 HG22 ILE C 138 -29.520 -16.431 23.737 1.00 0.00 H \nATOM 6297 HG23 ILE C 138 -28.565 -17.484 24.436 1.00 0.00 H \nATOM 6298 HD11 ILE C 138 -28.382 -18.702 27.884 1.00 0.00 H \nATOM 6299 HD12 ILE C 138 -28.103 -18.591 26.329 1.00 0.00 H \nATOM 6300 HD13 ILE C 138 -27.603 -17.450 27.307 1.00 0.00 H \nATOM 6301 N LEU C 139 -27.676 -14.095 24.040 1.00 0.00 N \nATOM 6302 CA LEU C 139 -27.707 -13.195 22.893 1.00 0.00 C \nATOM 6303 C LEU C 139 -27.628 -14.014 21.613 1.00 0.00 C \nATOM 6304 O LEU C 139 -26.739 -14.860 21.467 1.00 0.00 O \nATOM 6305 CB LEU C 139 -26.556 -12.181 22.947 1.00 0.00 C \nATOM 6306 CG LEU C 139 -26.593 -11.003 21.961 1.00 0.00 C \nATOM 6307 CD1 LEU C 139 -25.893 -9.790 22.552 1.00 0.00 C \nATOM 6308 CD2 LEU C 139 -25.965 -11.362 20.616 1.00 0.00 C \nATOM 6309 H LEU C 139 -26.946 -14.543 24.112 1.00 0.00 H \nATOM 6310 HA LEU C 139 -28.538 -12.695 22.913 1.00 0.00 H \nATOM 6311 HB2 LEU C 139 -26.521 -11.817 23.845 1.00 0.00 H \nATOM 6312 HB3 LEU C 139 -25.727 -12.663 22.804 1.00 0.00 H \nATOM 6313 HG LEU C 139 -27.527 -10.791 21.805 1.00 0.00 H \nATOM 6314 HD11 LEU C 139 -25.925 -9.057 21.918 1.00 0.00 H \nATOM 6315 HD12 LEU C 139 -26.338 -9.527 23.373 1.00 0.00 H \nATOM 6316 HD13 LEU C 139 -24.968 -10.011 22.743 1.00 0.00 H \nATOM 6317 HD21 LEU C 139 -26.008 -10.595 20.024 1.00 0.00 H \nATOM 6318 HD22 LEU C 139 -25.038 -11.616 20.749 1.00 0.00 H \nATOM 6319 HD23 LEU C 139 -26.449 -12.103 20.220 1.00 0.00 H \nATOM 6320 N THR C 140 -28.561 -13.767 20.692 1.00 0.00 N \nATOM 6321 CA THR C 140 -28.560 -14.394 19.378 1.00 0.00 C \nATOM 6322 C THR C 140 -28.762 -13.334 18.302 1.00 0.00 C \nATOM 6323 O THR C 140 -29.395 -12.301 18.540 1.00 0.00 O \nATOM 6324 CB THR C 140 -29.658 -15.465 19.256 1.00 0.00 C \nATOM 6325 OG1 THR C 140 -30.946 -14.844 19.348 1.00 0.00 O \nATOM 6326 CG2 THR C 140 -29.522 -16.516 20.353 1.00 0.00 C \nATOM 6327 H THR C 140 -29.217 -13.225 20.818 1.00 0.00 H \nATOM 6328 HA THR C 140 -27.702 -14.830 19.259 1.00 0.00 H \nATOM 6329 HB THR C 140 -29.562 -15.904 18.396 1.00 0.00 H \nATOM 6330 HG1 THR C 140 -30.885 -14.138 19.799 1.00 0.00 H \nATOM 6331 HG21 THR C 140 -30.224 -17.179 20.255 1.00 0.00 H \nATOM 6332 HG22 THR C 140 -28.657 -16.949 20.281 1.00 0.00 H \nATOM 6333 HG23 THR C 140 -29.599 -16.090 21.221 1.00 0.00 H \nATOM 6334 N VAL C 141 -28.216 -13.596 17.113 1.00 0.00 N \nATOM 6335 CA VAL C 141 -28.328 -12.696 15.969 1.00 0.00 C \nATOM 6336 C VAL C 141 -28.830 -13.504 14.775 1.00 0.00 C \nATOM 6337 O VAL C 141 -28.307 -14.586 14.486 1.00 0.00 O \nATOM 6338 CB VAL C 141 -27.002 -11.967 15.653 1.00 0.00 C \nATOM 6339 CG1 VAL C 141 -26.475 -11.255 16.891 1.00 0.00 C \nATOM 6340 CG2 VAL C 141 -25.950 -12.899 15.102 1.00 0.00 C \nATOM 6341 H VAL C 141 -27.766 -14.310 16.949 1.00 0.00 H \nATOM 6342 HA VAL C 141 -28.961 -11.992 16.181 1.00 0.00 H \nATOM 6343 HB VAL C 141 -27.197 -11.312 14.965 1.00 0.00 H \nATOM 6344 HG11 VAL C 141 -25.644 -10.803 16.676 1.00 0.00 H \nATOM 6345 HG12 VAL C 141 -27.128 -10.604 17.192 1.00 0.00 H \nATOM 6346 HG13 VAL C 141 -26.317 -11.903 17.595 1.00 0.00 H \nATOM 6347 HG21 VAL C 141 -25.139 -12.400 14.919 1.00 0.00 H \nATOM 6348 HG22 VAL C 141 -25.762 -13.595 15.751 1.00 0.00 H \nATOM 6349 HG23 VAL C 141 -26.273 -13.302 14.281 1.00 0.00 H \nATOM 6350 N HIS C 142 -29.880 -13.008 14.120 1.00 0.00 N \nATOM 6351 CA HIS C 142 -30.543 -13.738 13.048 1.00 0.00 C \nATOM 6352 C HIS C 142 -30.603 -12.910 11.773 1.00 0.00 C \nATOM 6353 O HIS C 142 -30.714 -11.678 11.832 1.00 0.00 O \nATOM 6354 CB HIS C 142 -31.959 -14.145 13.482 1.00 0.00 C \nATOM 6355 CG HIS C 142 -32.043 -14.603 14.904 1.00 0.00 C \nATOM 6356 ND1 HIS C 142 -31.897 -15.924 15.270 1.00 0.00 N \nATOM 6357 CD2 HIS C 142 -32.245 -13.916 16.053 1.00 0.00 C \nATOM 6358 CE1 HIS C 142 -32.013 -16.031 16.581 1.00 0.00 C \nATOM 6359 NE2 HIS C 142 -32.224 -14.827 17.081 1.00 0.00 N \nATOM 6360 H HIS C 142 -30.226 -12.238 14.287 1.00 0.00 H \nATOM 6361 HA HIS C 142 -30.025 -14.537 12.863 1.00 0.00 H \nATOM 6362 HB2 HIS C 142 -32.556 -13.391 13.357 1.00 0.00 H \nATOM 6363 HB3 HIS C 142 -32.275 -14.856 12.902 1.00 0.00 H \nATOM 6364 HD1 HIS C 142 -31.753 -16.577 14.729 1.00 0.00 H \nATOM 6365 HD2 HIS C 142 -32.374 -12.998 16.132 1.00 0.00 H \nATOM 6366 HE1 HIS C 142 -31.956 -16.820 17.069 1.00 0.00 H \nATOM 6367 HE2 HIS C 142 -32.331 -14.643 17.914 1.00 0.00 H \nATOM 6368 N PRO C 143 -30.516 -13.551 10.604 1.00 0.00 N \nATOM 6369 CA PRO C 143 -30.589 -12.803 9.341 1.00 0.00 C \nATOM 6370 C PRO C 143 -31.980 -12.260 9.057 1.00 0.00 C \nATOM 6371 O PRO C 143 -32.994 -12.894 9.357 1.00 0.00 O \nATOM 6372 CB PRO C 143 -30.167 -13.835 8.287 1.00 0.00 C \nATOM 6373 CG PRO C 143 -30.428 -15.157 8.916 1.00 0.00 C \nATOM 6374 CD PRO C 143 -30.236 -14.981 10.393 1.00 0.00 C \nATOM 6375 HA PRO C 143 -30.024 -12.014 9.355 1.00 0.00 H \nATOM 6376 HB2 PRO C 143 -30.676 -13.729 7.468 1.00 0.00 H \nATOM 6377 HB3 PRO C 143 -29.231 -13.736 8.054 1.00 0.00 H \nATOM 6378 HG2 PRO C 143 -31.329 -15.459 8.720 1.00 0.00 H \nATOM 6379 HG3 PRO C 143 -29.821 -15.829 8.568 1.00 0.00 H \nATOM 6380 HD2 PRO C 143 -30.841 -15.543 10.902 1.00 0.00 H \nATOM 6381 HD3 PRO C 143 -29.335 -15.213 10.667 1.00 0.00 H \nATOM 6382 N GLU C 144 -32.013 -11.063 8.475 1.00 0.00 N \nATOM 6383 CA GLU C 144 -33.260 -10.403 8.118 1.00 0.00 C \nATOM 6384 C GLU C 144 -33.006 -9.464 6.950 1.00 0.00 C \nATOM 6385 O GLU C 144 -31.889 -8.977 6.759 1.00 0.00 O \nATOM 6386 CB GLU C 144 -33.843 -9.622 9.297 1.00 0.00 C \nATOM 6387 CG GLU C 144 -35.084 -10.245 9.895 1.00 0.00 C \nATOM 6388 CD GLU C 144 -35.703 -9.374 10.967 1.00 0.00 C \nATOM 6389 OE1 GLU C 144 -35.155 -8.284 11.237 1.00 0.00 O \nATOM 6390 OE2 GLU C 144 -36.738 -9.777 11.539 1.00 0.00 O \nATOM 6391 H GLU C 144 -31.308 -10.612 8.277 1.00 0.00 H \nATOM 6392 HA GLU C 144 -33.907 -11.082 7.869 1.00 0.00 H \nATOM 6393 HB2 GLU C 144 -33.166 -9.545 9.988 1.00 0.00 H \nATOM 6394 HB3 GLU C 144 -34.054 -8.722 9.004 1.00 0.00 H \nATOM 6395 HG2 GLU C 144 -35.735 -10.403 9.193 1.00 0.00 H \nATOM 6396 HG3 GLU C 144 -34.860 -11.110 10.273 1.00 0.00 H \nATOM 6397 N VAL C 145 -34.039 -9.246 6.146 1.00 0.00 N \nATOM 6398 CA VAL C 145 -33.991 -8.275 5.062 1.00 0.00 C \nATOM 6399 C VAL C 145 -34.637 -6.993 5.565 1.00 0.00 C \nATOM 6400 O VAL C 145 -35.824 -6.982 5.912 1.00 0.00 O \nATOM 6401 CB VAL C 145 -34.700 -8.792 3.803 1.00 0.00 C \nATOM 6402 CG1 VAL C 145 -34.532 -7.809 2.643 1.00 0.00 C \nATOM 6403 CG2 VAL C 145 -34.218 -10.190 3.434 1.00 0.00 C \nATOM 6404 H VAL C 145 -34.790 -9.659 6.214 1.00 0.00 H \nATOM 6405 HA VAL C 145 -33.069 -8.114 4.807 1.00 0.00 H \nATOM 6406 HB VAL C 145 -35.648 -8.858 3.995 1.00 0.00 H \nATOM 6407 HG11 VAL C 145 -34.986 -8.153 1.858 1.00 0.00 H \nATOM 6408 HG12 VAL C 145 -34.914 -6.952 2.887 1.00 0.00 H \nATOM 6409 HG13 VAL C 145 -33.589 -7.698 2.447 1.00 0.00 H \nATOM 6410 HG21 VAL C 145 -34.681 -10.492 2.637 1.00 0.00 H \nATOM 6411 HG22 VAL C 145 -33.263 -10.169 3.265 1.00 0.00 H \nATOM 6412 HG23 VAL C 145 -34.403 -10.800 4.165 1.00 0.00 H \nATOM 6413 N ILE C 146 -33.865 -5.912 5.590 1.00 0.00 N \nATOM 6414 CA ILE C 146 -34.368 -4.617 6.036 1.00 0.00 C \nATOM 6415 C ILE C 146 -34.240 -3.584 4.920 1.00 0.00 C \nATOM 6416 O ILE C 146 -33.132 -3.196 4.550 1.00 0.00 O \nATOM 6417 CB ILE C 146 -33.613 -4.115 7.281 1.00 0.00 C \nATOM 6418 CG1 ILE C 146 -33.592 -5.196 8.364 1.00 0.00 C \nATOM 6419 CG2 ILE C 146 -34.248 -2.838 7.809 1.00 0.00 C \nATOM 6420 CD1 ILE C 146 -32.817 -4.804 9.602 1.00 0.00 C \nATOM 6421 H ILE C 146 -33.039 -5.908 5.350 1.00 0.00 H \nATOM 6422 HA ILE C 146 -35.302 -4.734 6.268 1.00 0.00 H \nATOM 6423 HB ILE C 146 -32.697 -3.918 7.029 1.00 0.00 H \nATOM 6424 HG12 ILE C 146 -34.504 -5.406 8.617 1.00 0.00 H \nATOM 6425 HG13 ILE C 146 -33.206 -6.005 7.994 1.00 0.00 H \nATOM 6426 HG21 ILE C 146 -33.762 -2.535 8.592 1.00 0.00 H \nATOM 6427 HG22 ILE C 146 -34.216 -2.153 7.123 1.00 0.00 H \nATOM 6428 HG23 ILE C 146 -35.172 -3.011 8.049 1.00 0.00 H \nATOM 6429 HD11 ILE C 146 -32.844 -5.530 10.244 1.00 0.00 H \nATOM 6430 HD12 ILE C 146 -31.896 -4.619 9.362 1.00 0.00 H \nATOM 6431 HD13 ILE C 146 -33.214 -4.011 9.995 1.00 0.00 H \nATOM 6432 N ASP C 147 -35.375 -3.143 4.385 1.00 0.00 N \nATOM 6433 CA ASP C 147 -35.374 -2.180 3.327 1.00 0.00 C \nATOM 6434 C ASP C 147 -34.749 -2.757 2.070 1.00 0.00 C \nATOM 6435 O ASP C 147 -34.106 -2.091 1.372 1.00 0.00 O \nATOM 6436 CB ASP C 147 -34.631 -0.939 3.759 1.00 0.00 C \nATOM 6437 CG ASP C 147 -35.247 -0.276 4.945 1.00 0.00 C \nATOM 6438 OD1 ASP C 147 -36.426 -0.457 5.166 1.00 0.00 O \nATOM 6439 OD2 ASP C 147 -34.552 0.450 5.649 1.00 0.00 O \nATOM 6440 H ASP C 147 -36.157 -3.401 4.633 1.00 0.00 H \nATOM 6441 HA ASP C 147 -36.293 -1.945 3.126 1.00 0.00 H \nATOM 6442 HB2 ASP C 147 -33.713 -1.173 3.966 1.00 0.00 H \nATOM 6443 HB3 ASP C 147 -34.604 -0.310 3.021 1.00 0.00 H \nATOM 6444 N GLY C 148 -34.941 -4.026 1.822 1.00 0.00 N \nATOM 6445 CA GLY C 148 -34.362 -4.678 0.687 1.00 0.00 C \nATOM 6446 C GLY C 148 -32.896 -4.996 0.765 1.00 0.00 C \nATOM 6447 O GLY C 148 -32.394 -5.572 -0.133 1.00 0.00 O \nATOM 6448 H GLY C 148 -35.420 -4.541 2.317 1.00 0.00 H \nATOM 6449 HA2 GLY C 148 -34.844 -5.506 0.536 1.00 0.00 H \nATOM 6450 HA3 GLY C 148 -34.509 -4.118 -0.091 1.00 0.00 H \nATOM 6451 N ARG C 149 -32.219 -4.594 1.836 1.00 0.00 N \nATOM 6452 CA ARG C 149 -30.785 -4.858 1.968 1.00 0.00 C \nATOM 6453 C ARG C 149 -30.500 -5.853 3.087 1.00 0.00 C \nATOM 6454 O ARG C 149 -31.394 -6.183 3.866 1.00 0.00 O \nATOM 6455 CB ARG C 149 -30.021 -3.556 2.214 1.00 0.00 C \nATOM 6456 CG ARG C 149 -30.540 -2.371 1.416 1.00 0.00 C \nATOM 6457 CD ARG C 149 -29.522 -1.243 1.376 1.00 0.00 C \nATOM 6458 NE ARG C 149 -29.981 -0.066 2.106 1.00 0.00 N \nATOM 6459 CZ ARG C 149 -29.295 1.069 2.202 1.00 0.00 C \nATOM 6460 NH1 ARG C 149 -28.113 1.183 1.612 1.00 0.00 N \nATOM 6461 NH2 ARG C 149 -29.791 2.090 2.887 1.00 0.00 N \nATOM 6462 H ARG C 149 -32.568 -4.168 2.497 1.00 0.00 H \nATOM 6463 HA ARG C 149 -30.482 -5.250 1.134 1.00 0.00 H \nATOM 6464 HB2 ARG C 149 -30.064 -3.341 3.159 1.00 0.00 H \nATOM 6465 HB3 ARG C 149 -29.086 -3.695 1.997 1.00 0.00 H \nATOM 6466 HG2 ARG C 149 -30.748 -2.654 0.512 1.00 0.00 H \nATOM 6467 HG3 ARG C 149 -31.366 -2.050 1.810 1.00 0.00 H \nATOM 6468 HD2 ARG C 149 -28.684 -1.551 1.755 1.00 0.00 H \nATOM 6469 HD3 ARG C 149 -29.344 -1.001 0.454 1.00 0.00 H \nATOM 6470 HE ARG C 149 -30.744 -0.109 2.500 1.00 0.00 H \nATOM 6471 HH11 ARG C 149 -27.789 0.522 1.167 1.00 0.00 H \nATOM 6472 HH12 ARG C 149 -27.670 1.918 1.675 1.00 0.00 H \nATOM 6473 HH21 ARG C 149 -30.558 2.019 3.270 1.00 0.00 H \nATOM 6474 HH22 ARG C 149 -29.346 2.823 2.948 1.00 0.00 H \nATOM 6475 N PRO C 150 -29.261 -6.333 3.175 1.00 0.00 N \nATOM 6476 CA PRO C 150 -28.930 -7.294 4.236 1.00 0.00 C \nATOM 6477 C PRO C 150 -29.055 -6.709 5.650 1.00 0.00 C \nATOM 6478 O PRO C 150 -28.461 -5.670 5.936 1.00 0.00 O \nATOM 6479 CB PRO C 150 -27.470 -7.644 3.941 1.00 0.00 C \nATOM 6480 CG PRO C 150 -27.330 -7.440 2.471 1.00 0.00 C \nATOM 6481 CD PRO C 150 -28.222 -6.278 2.131 1.00 0.00 C \nATOM 6482 HA PRO C 150 -29.537 -8.050 4.230 1.00 0.00 H \nATOM 6483 HB2 PRO C 150 -26.862 -7.073 4.437 1.00 0.00 H \nATOM 6484 HB3 PRO C 150 -27.268 -8.559 4.192 1.00 0.00 H \nATOM 6485 HG2 PRO C 150 -26.409 -7.253 2.232 1.00 0.00 H \nATOM 6486 HG3 PRO C 150 -27.594 -8.236 1.983 1.00 0.00 H \nATOM 6487 HD2 PRO C 150 -27.738 -5.437 2.151 1.00 0.00 H \nATOM 6488 HD3 PRO C 150 -28.602 -6.366 1.243 1.00 0.00 H \nATOM 6489 N GLY C 151 -29.832 -7.352 6.519 1.00 0.00 N \nATOM 6490 CA GLY C 151 -30.024 -6.852 7.874 1.00 0.00 C \nATOM 6491 C GLY C 151 -29.726 -7.850 8.977 1.00 0.00 C \nATOM 6492 O GLY C 151 -29.177 -8.921 8.716 1.00 0.00 O \nATOM 6493 H GLY C 151 -30.256 -8.079 6.342 1.00 0.00 H \nATOM 6494 HA2 GLY C 151 -29.459 -6.074 8.000 1.00 0.00 H \nATOM 6495 HA3 GLY C 151 -30.942 -6.553 7.967 1.00 0.00 H \nATOM 6496 N THR C 152 -30.083 -7.506 10.215 1.00 0.00 N \nATOM 6497 CA THR C 152 -29.830 -8.405 11.335 1.00 0.00 C \nATOM 6498 C THR C 152 -30.815 -8.114 12.454 1.00 0.00 C \nATOM 6499 O THR C 152 -31.065 -6.948 12.764 1.00 0.00 O \nATOM 6500 CB THR C 152 -28.394 -8.256 11.849 1.00 0.00 C \nATOM 6501 OG1 THR C 152 -27.471 -8.518 10.786 1.00 0.00 O \nATOM 6502 CG2 THR C 152 -28.127 -9.219 13.000 1.00 0.00 C \nATOM 6503 H THR C 152 -30.468 -6.766 10.424 1.00 0.00 H \nATOM 6504 HA THR C 152 -29.946 -9.318 11.028 1.00 0.00 H \nATOM 6505 HB THR C 152 -28.277 -7.348 12.170 1.00 0.00 H \nATOM 6506 HG1 THR C 152 -27.387 -7.830 10.312 1.00 0.00 H \nATOM 6507 HG21 THR C 152 -27.214 -9.108 13.310 1.00 0.00 H \nATOM 6508 HG22 THR C 152 -28.740 -9.031 13.728 1.00 0.00 H \nATOM 6509 HG23 THR C 152 -28.256 -10.131 12.696 1.00 0.00 H \nATOM 6510 N LEU C 153 -31.377 -9.164 13.048 1.00 0.00 N \nATOM 6511 CA LEU C 153 -32.129 -9.045 14.291 1.00 0.00 C \nATOM 6512 C LEU C 153 -31.279 -9.600 15.426 1.00 0.00 C \nATOM 6513 O LEU C 153 -30.871 -10.766 15.388 1.00 0.00 O \nATOM 6514 CB LEU C 153 -33.466 -9.783 14.215 1.00 0.00 C \nATOM 6515 CG LEU C 153 -34.263 -9.760 15.524 1.00 0.00 C \nATOM 6516 CD1 LEU C 153 -34.642 -8.331 15.892 1.00 0.00 C \nATOM 6517 CD2 LEU C 153 -35.503 -10.645 15.440 1.00 0.00 C \nATOM 6518 H LEU C 153 -31.332 -9.966 12.740 1.00 0.00 H \nATOM 6519 HA LEU C 153 -32.330 -8.109 14.449 1.00 0.00 H \nATOM 6520 HB2 LEU C 153 -34.004 -9.387 13.512 1.00 0.00 H \nATOM 6521 HB3 LEU C 153 -33.303 -10.705 13.962 1.00 0.00 H \nATOM 6522 HG LEU C 153 -33.695 -10.119 16.224 1.00 0.00 H \nATOM 6523 HD11 LEU C 153 -35.145 -8.333 16.721 1.00 0.00 H \nATOM 6524 HD12 LEU C 153 -33.837 -7.801 16.004 1.00 0.00 H \nATOM 6525 HD13 LEU C 153 -35.185 -7.948 15.186 1.00 0.00 H \nATOM 6526 HD21 LEU C 153 -35.984 -10.609 16.281 1.00 0.00 H \nATOM 6527 HD22 LEU C 153 -36.078 -10.330 14.725 1.00 0.00 H \nATOM 6528 HD23 LEU C 153 -35.236 -11.560 15.260 1.00 0.00 H \nATOM 6529 N VAL C 154 -31.018 -8.769 16.431 1.00 0.00 N \nATOM 6530 CA VAL C 154 -30.292 -9.171 17.629 1.00 0.00 C \nATOM 6531 C VAL C 154 -31.280 -9.229 18.783 1.00 0.00 C \nATOM 6532 O VAL C 154 -32.026 -8.272 19.016 1.00 0.00 O \nATOM 6533 CB VAL C 154 -29.137 -8.204 17.940 1.00 0.00 C \nATOM 6534 CG1 VAL C 154 -28.380 -8.657 19.178 1.00 0.00 C \nATOM 6535 CG2 VAL C 154 -28.206 -8.088 16.746 1.00 0.00 C \nATOM 6536 H VAL C 154 -31.262 -7.944 16.435 1.00 0.00 H \nATOM 6537 HA VAL C 154 -29.892 -10.044 17.489 1.00 0.00 H \nATOM 6538 HB VAL C 154 -29.509 -7.326 18.120 1.00 0.00 H \nATOM 6539 HG11 VAL C 154 -27.656 -8.037 19.360 1.00 0.00 H \nATOM 6540 HG12 VAL C 154 -28.984 -8.680 19.937 1.00 0.00 H \nATOM 6541 HG13 VAL C 154 -28.016 -9.544 19.029 1.00 0.00 H \nATOM 6542 HG21 VAL C 154 -27.484 -7.476 16.957 1.00 0.00 H \nATOM 6543 HG22 VAL C 154 -27.839 -8.961 16.536 1.00 0.00 H \nATOM 6544 HG23 VAL C 154 -28.700 -7.753 15.981 1.00 0.00 H \nATOM 6545 N ILE C 155 -31.279 -10.345 19.505 1.00 0.00 N \nATOM 6546 CA ILE C 155 -32.129 -10.536 20.673 1.00 0.00 C \nATOM 6547 C ILE C 155 -31.240 -10.900 21.849 1.00 0.00 C \nATOM 6548 O ILE C 155 -30.405 -11.805 21.745 1.00 0.00 O \nATOM 6549 CB ILE C 155 -33.189 -11.629 20.442 1.00 0.00 C \nATOM 6550 CG1 ILE C 155 -33.980 -11.358 19.159 1.00 0.00 C \nATOM 6551 CG2 ILE C 155 -34.125 -11.727 21.641 1.00 0.00 C \nATOM 6552 CD1 ILE C 155 -34.942 -12.468 18.796 1.00 0.00 C \nATOM 6553 H ILE C 155 -30.778 -11.021 19.327 1.00 0.00 H \nATOM 6554 HA ILE C 155 -32.612 -9.714 20.851 1.00 0.00 H \nATOM 6555 HB ILE C 155 -32.732 -12.479 20.340 1.00 0.00 H \nATOM 6556 HG12 ILE C 155 -34.476 -10.531 19.262 1.00 0.00 H \nATOM 6557 HG13 ILE C 155 -33.358 -11.226 18.426 1.00 0.00 H \nATOM 6558 HG21 ILE C 155 -34.786 -12.419 21.480 1.00 0.00 H \nATOM 6559 HG22 ILE C 155 -33.613 -11.948 22.434 1.00 0.00 H \nATOM 6560 HG23 ILE C 155 -34.573 -10.877 21.772 1.00 0.00 H \nATOM 6561 HD11 ILE C 155 -35.410 -12.237 17.978 1.00 0.00 H \nATOM 6562 HD12 ILE C 155 -34.449 -13.293 18.664 1.00 0.00 H \nATOM 6563 HD13 ILE C 155 -35.585 -12.587 19.513 1.00 0.00 H \nATOM 6564 N GLU C 156 -31.415 -10.192 22.961 1.00 0.00 N \nATOM 6565 CA GLU C 156 -30.716 -10.507 24.199 1.00 0.00 C \nATOM 6566 C GLU C 156 -31.754 -10.658 25.297 1.00 0.00 C \nATOM 6567 O GLU C 156 -32.485 -9.708 25.598 1.00 0.00 O \nATOM 6568 CB GLU C 156 -29.694 -9.423 24.561 1.00 0.00 C \nATOM 6569 CG GLU C 156 -28.768 -9.810 25.705 1.00 0.00 C \nATOM 6570 CD GLU C 156 -27.577 -8.881 25.836 1.00 0.00 C \nATOM 6571 OE1 GLU C 156 -27.680 -7.714 25.403 1.00 0.00 O \nATOM 6572 OE2 GLU C 156 -26.534 -9.316 26.373 1.00 0.00 O \nATOM 6573 H GLU C 156 -31.943 -9.515 23.017 1.00 0.00 H \nATOM 6574 HA GLU C 156 -30.218 -11.332 24.090 1.00 0.00 H \nATOM 6575 HB2 GLU C 156 -29.159 -9.220 23.778 1.00 0.00 H \nATOM 6576 HB3 GLU C 156 -30.167 -8.611 24.800 1.00 0.00 H \nATOM 6577 HG2 GLU C 156 -29.268 -9.807 26.536 1.00 0.00 H \nATOM 6578 HG3 GLU C 156 -28.452 -10.717 25.567 1.00 0.00 H \nATOM 6579 N SER C 157 -31.814 -11.846 25.889 1.00 0.00 N \nATOM 6580 CA SER C 157 -32.703 -12.125 27.002 1.00 0.00 C \nATOM 6581 C SER C 157 -31.865 -12.489 28.218 1.00 0.00 C \nATOM 6582 O SER C 157 -30.675 -12.791 28.106 1.00 0.00 O \nATOM 6583 CB SER C 157 -33.684 -13.258 26.669 1.00 0.00 C \nATOM 6584 OG SER C 157 -32.998 -14.471 26.414 1.00 0.00 O \nATOM 6585 H SER C 157 -31.333 -12.518 25.651 1.00 0.00 H \nATOM 6586 HA SER C 157 -33.232 -11.333 27.188 1.00 0.00 H \nATOM 6587 HB2 SER C 157 -34.302 -13.382 27.407 1.00 0.00 H \nATOM 6588 HB3 SER C 157 -34.213 -13.014 25.894 1.00 0.00 H \nATOM 6589 HG SER C 157 -32.172 -14.322 26.370 1.00 0.00 H \nATOM 6590 N PHE C 158 -32.496 -12.459 29.388 1.00 0.00 N \nATOM 6591 CA PHE C 158 -31.747 -12.645 30.621 1.00 0.00 C \nATOM 6592 C PHE C 158 -32.662 -13.162 31.721 1.00 0.00 C \nATOM 6593 O PHE C 158 -33.887 -13.025 31.658 1.00 0.00 O \nATOM 6594 CB PHE C 158 -31.077 -11.339 31.064 1.00 0.00 C \nATOM 6595 CG PHE C 158 -32.051 -10.241 31.383 1.00 0.00 C \nATOM 6596 CD1 PHE C 158 -32.472 -9.362 30.399 1.00 0.00 C \nATOM 6597 CD2 PHE C 158 -32.545 -10.085 32.668 1.00 0.00 C \nATOM 6598 CE1 PHE C 158 -33.370 -8.353 30.688 1.00 0.00 C \nATOM 6599 CE2 PHE C 158 -33.442 -9.079 32.965 1.00 0.00 C \nATOM 6600 CZ PHE C 158 -33.855 -8.213 31.975 1.00 0.00 C \nATOM 6601 H PHE C 158 -33.341 -12.335 29.487 1.00 0.00 H \nATOM 6602 HA PHE C 158 -31.052 -13.300 30.453 1.00 0.00 H \nATOM 6603 HB2 PHE C 158 -30.531 -11.514 31.846 1.00 0.00 H \nATOM 6604 HB3 PHE C 158 -30.479 -11.037 30.362 1.00 0.00 H \nATOM 6605 HD1 PHE C 158 -32.146 -9.452 29.533 1.00 0.00 H \nATOM 6606 HD2 PHE C 158 -32.268 -10.666 33.339 1.00 0.00 H \nATOM 6607 HE1 PHE C 158 -33.647 -7.770 30.019 1.00 0.00 H \nATOM 6608 HE2 PHE C 158 -33.767 -8.985 33.831 1.00 0.00 H \nATOM 6609 HZ PHE C 158 -34.460 -7.535 32.173 1.00 0.00 H \nATOM 6610 N VAL C 159 -32.036 -13.765 32.730 1.00 0.00 N \nATOM 6611 CA VAL C 159 -32.665 -14.085 34.004 1.00 0.00 C \nATOM 6612 C VAL C 159 -31.723 -13.632 35.107 1.00 0.00 C \nATOM 6613 O VAL C 159 -30.501 -13.774 34.983 1.00 0.00 O \nATOM 6614 CB VAL C 159 -32.972 -15.589 34.151 1.00 0.00 C \nATOM 6615 CG1 VAL C 159 -34.241 -15.936 33.427 1.00 0.00 C \nATOM 6616 CG2 VAL C 159 -31.814 -16.423 33.629 1.00 0.00 C \nATOM 6617 H VAL C 159 -31.211 -14.005 32.689 1.00 0.00 H \nATOM 6618 HA VAL C 159 -33.518 -13.627 34.058 1.00 0.00 H \nATOM 6619 HB VAL C 159 -33.091 -15.789 35.093 1.00 0.00 H \nATOM 6620 HG11 VAL C 159 -34.422 -16.884 33.527 1.00 0.00 H \nATOM 6621 HG12 VAL C 159 -34.977 -15.425 33.800 1.00 0.00 H \nATOM 6622 HG13 VAL C 159 -34.145 -15.724 32.485 1.00 0.00 H \nATOM 6623 HG21 VAL C 159 -32.023 -17.365 33.729 1.00 0.00 H \nATOM 6624 HG22 VAL C 159 -31.667 -16.222 32.691 1.00 0.00 H \nATOM 6625 HG23 VAL C 159 -31.012 -16.215 34.133 1.00 0.00 H \nATOM 6626 N VAL C 160 -32.285 -13.089 36.183 1.00 0.00 N \nATOM 6627 CA VAL C 160 -31.469 -12.563 37.270 1.00 0.00 C \nATOM 6628 C VAL C 160 -32.305 -12.563 38.540 1.00 0.00 C \nATOM 6629 O VAL C 160 -33.527 -12.397 38.498 1.00 0.00 O \nATOM 6630 CB VAL C 160 -30.934 -11.149 36.924 1.00 0.00 C \nATOM 6631 CG1 VAL C 160 -32.083 -10.168 36.738 1.00 0.00 C \nATOM 6632 CG2 VAL C 160 -29.960 -10.657 37.986 1.00 0.00 C \nATOM 6633 H VAL C 160 -33.134 -13.016 36.302 1.00 0.00 H \nATOM 6634 HA VAL C 160 -30.690 -13.124 37.406 1.00 0.00 H \nATOM 6635 HB VAL C 160 -30.451 -11.208 36.085 1.00 0.00 H \nATOM 6636 HG11 VAL C 160 -31.728 -9.291 36.523 1.00 0.00 H \nATOM 6637 HG12 VAL C 160 -32.654 -10.472 36.015 1.00 0.00 H \nATOM 6638 HG13 VAL C 160 -32.599 -10.115 37.557 1.00 0.00 H \nATOM 6639 HG21 VAL C 160 -29.640 -9.773 37.747 1.00 0.00 H \nATOM 6640 HG22 VAL C 160 -30.410 -10.617 38.844 1.00 0.00 H \nATOM 6641 HG23 VAL C 160 -29.208 -11.267 38.044 1.00 0.00 H \nATOM 6642 N ASP C 161 -31.638 -12.751 39.677 1.00 0.00 N \nATOM 6643 CA ASP C 161 -32.297 -12.612 40.966 1.00 0.00 C \nATOM 6644 C ASP C 161 -32.691 -11.160 41.195 1.00 0.00 C \nATOM 6645 O ASP C 161 -31.904 -10.242 40.947 1.00 0.00 O \nATOM 6646 CB ASP C 161 -31.372 -13.076 42.094 1.00 0.00 C \nATOM 6647 CG ASP C 161 -31.136 -14.571 42.084 1.00 0.00 C \nATOM 6648 OD1 ASP C 161 -31.915 -15.300 41.440 1.00 0.00 O \nATOM 6649 OD2 ASP C 161 -30.160 -15.023 42.719 1.00 0.00 O \nATOM 6650 H ASP C 161 -30.805 -12.959 39.720 1.00 0.00 H \nATOM 6651 HA ASP C 161 -33.093 -13.166 40.965 1.00 0.00 H \nATOM 6652 HB2 ASP C 161 -30.520 -12.618 42.017 1.00 0.00 H \nATOM 6653 HB3 ASP C 161 -31.756 -12.819 42.947 1.00 0.00 H \nATOM 6654 N VAL C 162 -33.918 -10.953 41.660 1.00 0.00 N \nATOM 6655 CA VAL C 162 -34.347 -9.621 42.071 1.00 0.00 C \nATOM 6656 C VAL C 162 -33.700 -9.330 43.418 1.00 0.00 C \nATOM 6657 O VAL C 162 -33.987 -10.032 44.398 1.00 0.00 O \nATOM 6658 CB VAL C 162 -35.877 -9.520 42.157 1.00 0.00 C \nATOM 6659 CG1 VAL C 162 -36.279 -8.181 42.743 1.00 0.00 C \nATOM 6660 CG2 VAL C 162 -36.503 -9.719 40.789 1.00 0.00 C \nATOM 6661 H VAL C 162 -34.515 -11.566 41.745 1.00 0.00 H \nATOM 6662 HA VAL C 162 -34.070 -8.965 41.412 1.00 0.00 H \nATOM 6663 HB VAL C 162 -36.203 -10.222 42.741 1.00 0.00 H \nATOM 6664 HG11 VAL C 162 -37.246 -8.127 42.793 1.00 0.00 H \nATOM 6665 HG12 VAL C 162 -35.904 -8.091 43.633 1.00 0.00 H \nATOM 6666 HG13 VAL C 162 -35.944 -7.467 42.178 1.00 0.00 H \nATOM 6667 HG21 VAL C 162 -37.468 -9.652 40.862 1.00 0.00 H \nATOM 6668 HG22 VAL C 162 -36.177 -9.037 40.181 1.00 0.00 H \nATOM 6669 HG23 VAL C 162 -36.265 -10.595 40.448 1.00 0.00 H \nATOM 6670 N PRO C 163 -32.822 -8.336 43.525 1.00 0.00 N \nATOM 6671 CA PRO C 163 -32.227 -8.041 44.830 1.00 0.00 C \nATOM 6672 C PRO C 163 -33.275 -7.462 45.763 1.00 0.00 C \nATOM 6673 O PRO C 163 -34.207 -6.778 45.335 1.00 0.00 O \nATOM 6674 CB PRO C 163 -31.137 -7.016 44.504 1.00 0.00 C \nATOM 6675 CG PRO C 163 -31.609 -6.352 43.256 1.00 0.00 C \nATOM 6676 CD PRO C 163 -32.386 -7.391 42.481 1.00 0.00 C \nATOM 6677 HA PRO C 163 -31.872 -8.823 45.281 1.00 0.00 H \nATOM 6678 HB2 PRO C 163 -31.027 -6.376 45.225 1.00 0.00 H \nATOM 6679 HB3 PRO C 163 -30.277 -7.445 44.372 1.00 0.00 H \nATOM 6680 HG2 PRO C 163 -32.168 -5.587 43.463 1.00 0.00 H \nATOM 6681 HG3 PRO C 163 -30.859 -6.023 42.736 1.00 0.00 H \nATOM 6682 HD2 PRO C 163 -33.141 -6.999 42.015 1.00 0.00 H \nATOM 6683 HD3 PRO C 163 -31.834 -7.826 41.812 1.00 0.00 H \nATOM 6684 N GLU C 164 -33.113 -7.736 47.053 1.00 0.00 N \nATOM 6685 CA GLU C 164 -34.132 -7.333 48.011 1.00 0.00 C \nATOM 6686 C GLU C 164 -34.157 -5.818 48.146 1.00 0.00 C \nATOM 6687 O GLU C 164 -33.114 -5.165 48.240 1.00 0.00 O \nATOM 6688 CB GLU C 164 -33.915 -7.993 49.370 1.00 0.00 C \nATOM 6689 CG GLU C 164 -35.153 -7.891 50.244 1.00 0.00 C \nATOM 6690 CD GLU C 164 -35.385 -9.114 51.104 1.00 0.00 C \nATOM 6691 OE1 GLU C 164 -36.206 -9.970 50.708 1.00 0.00 O \nATOM 6692 OE2 GLU C 164 -34.762 -9.211 52.180 1.00 0.00 O \nATOM 6693 H GLU C 164 -32.435 -8.146 47.388 1.00 0.00 H \nATOM 6694 HA GLU C 164 -34.992 -7.632 47.677 1.00 0.00 H \nATOM 6695 HB2 GLU C 164 -33.683 -8.926 49.244 1.00 0.00 H \nATOM 6696 HB3 GLU C 164 -33.165 -7.572 49.819 1.00 0.00 H \nATOM 6697 HG2 GLU C 164 -35.073 -7.112 50.816 1.00 0.00 H \nATOM 6698 HG3 GLU C 164 -35.929 -7.749 49.679 1.00 0.00 H \nATOM 6699 N GLY C 165 -35.363 -5.264 48.154 1.00 0.00 N \nATOM 6700 CA GLY C 165 -35.571 -3.836 48.130 1.00 0.00 C \nATOM 6701 C GLY C 165 -35.934 -3.292 46.768 1.00 0.00 C \nATOM 6702 O GLY C 165 -36.198 -2.090 46.649 1.00 0.00 O \nATOM 6703 H GLY C 165 -36.092 -5.720 48.174 1.00 0.00 H \nATOM 6704 HA2 GLY C 165 -36.276 -3.610 48.757 1.00 0.00 H \nATOM 6705 HA3 GLY C 165 -34.764 -3.395 48.440 1.00 0.00 H \nATOM 6706 N ASN C 166 -35.956 -4.139 45.739 1.00 0.00 N \nATOM 6707 CA ASN C 166 -36.349 -3.747 44.396 1.00 0.00 C \nATOM 6708 C ASN C 166 -37.445 -4.688 43.912 1.00 0.00 C \nATOM 6709 O ASN C 166 -37.570 -5.820 44.383 1.00 0.00 O \nATOM 6710 CB ASN C 166 -35.161 -3.784 43.424 1.00 0.00 C \nATOM 6711 CG ASN C 166 -34.175 -2.655 43.663 1.00 0.00 C \nATOM 6712 OD1 ASN C 166 -33.025 -2.889 44.035 1.00 0.00 O \nATOM 6713 ND2 ASN C 166 -34.624 -1.423 43.456 1.00 0.00 N \nATOM 6714 H ASN C 166 -35.739 -4.968 45.807 1.00 0.00 H \nATOM 6715 HA ASN C 166 -36.674 -2.834 44.423 1.00 0.00 H \nATOM 6716 HB2 ASN C 166 -34.702 -4.634 43.512 1.00 0.00 H \nATOM 6717 HB3 ASN C 166 -35.491 -3.733 42.513 1.00 0.00 H \nATOM 6718 HD21 ASN C 166 -34.105 -0.749 43.582 1.00 0.00 H \nATOM 6719 HD22 ASN C 166 -35.434 -1.299 43.196 1.00 0.00 H \nATOM 6720 N THR C 167 -38.244 -4.209 42.965 1.00 0.00 N \nATOM 6721 CA THR C 167 -39.299 -5.006 42.357 1.00 0.00 C \nATOM 6722 C THR C 167 -38.803 -5.661 41.069 1.00 0.00 C \nATOM 6723 O THR C 167 -37.751 -5.313 40.528 1.00 0.00 O \nATOM 6724 CB THR C 167 -40.540 -4.149 42.088 1.00 0.00 C \nATOM 6725 OG1 THR C 167 -40.233 -3.155 41.098 1.00 0.00 O \nATOM 6726 CG2 THR C 167 -41.001 -3.463 43.375 1.00 0.00 C \nATOM 6727 H THR C 167 -38.188 -3.408 42.656 1.00 0.00 H \nATOM 6728 HA THR C 167 -39.547 -5.708 42.979 1.00 0.00 H \nATOM 6729 HB THR C 167 -41.253 -4.722 41.765 1.00 0.00 H \nATOM 6730 HG1 THR C 167 -39.544 -2.733 41.328 1.00 0.00 H \nATOM 6731 HG21 THR C 167 -41.786 -2.924 43.191 1.00 0.00 H \nATOM 6732 HG22 THR C 167 -41.219 -4.135 44.040 1.00 0.00 H \nATOM 6733 HG23 THR C 167 -40.291 -2.894 43.711 1.00 0.00 H \nATOM 6734 N LYS C 168 -39.581 -6.633 40.584 1.00 0.00 N \nATOM 6735 CA LYS C 168 -39.328 -7.192 39.258 1.00 0.00 C \nATOM 6736 C LYS C 168 -39.429 -6.126 38.175 1.00 0.00 C \nATOM 6737 O LYS C 168 -38.649 -6.133 37.214 1.00 0.00 O \nATOM 6738 CB LYS C 168 -40.302 -8.335 38.973 1.00 0.00 C \nATOM 6739 CG LYS C 168 -40.227 -9.473 39.970 1.00 0.00 C \nATOM 6740 CD LYS C 168 -41.053 -10.663 39.508 1.00 0.00 C \nATOM 6741 CE LYS C 168 -41.082 -11.749 40.571 1.00 0.00 C \nATOM 6742 NZ LYS C 168 -41.793 -12.966 40.098 1.00 0.00 N \nATOM 6743 H LYS C 168 -40.250 -6.977 41.001 1.00 0.00 H \nATOM 6744 HA LYS C 168 -38.422 -7.538 39.248 1.00 0.00 H \nATOM 6745 HB2 LYS C 168 -41.206 -7.983 38.966 1.00 0.00 H \nATOM 6746 HB3 LYS C 168 -40.126 -8.683 38.085 1.00 0.00 H \nATOM 6747 HG2 LYS C 168 -39.303 -9.743 40.087 1.00 0.00 H \nATOM 6748 HG3 LYS C 168 -40.546 -9.171 40.835 1.00 0.00 H \nATOM 6749 HD2 LYS C 168 -41.958 -10.376 39.309 1.00 0.00 H \nATOM 6750 HD3 LYS C 168 -40.682 -11.020 38.686 1.00 0.00 H \nATOM 6751 HE2 LYS C 168 -40.174 -11.981 40.821 1.00 0.00 H \nATOM 6752 HE3 LYS C 168 -41.517 -11.409 41.368 1.00 0.00 H \nATOM 6753 HZ1 LYS C 168 -41.394 -13.690 40.428 1.00 0.00 H \nATOM 6754 HZ2 LYS C 168 -42.639 -12.942 40.374 1.00 0.00 H \nATOM 6755 HZ3 LYS C 168 -41.772 -12.996 39.209 1.00 0.00 H \nATOM 6756 N ASP C 169 -40.389 -5.207 38.305 1.00 0.00 N \nATOM 6757 CA ASP C 169 -40.558 -4.183 37.283 1.00 0.00 C \nATOM 6758 C ASP C 169 -39.383 -3.216 37.276 1.00 0.00 C \nATOM 6759 O ASP C 169 -39.013 -2.700 36.216 1.00 0.00 O \nATOM 6760 CB ASP C 169 -41.868 -3.429 37.507 1.00 0.00 C \nATOM 6761 CG ASP C 169 -43.080 -4.208 37.033 1.00 0.00 C \nATOM 6762 OD1 ASP C 169 -42.912 -5.139 36.219 1.00 0.00 O \nATOM 6763 OD2 ASP C 169 -44.205 -3.886 37.476 1.00 0.00 O \nATOM 6764 H ASP C 169 -40.940 -5.162 38.964 1.00 0.00 H \nATOM 6765 HA ASP C 169 -40.590 -4.620 36.418 1.00 0.00 H \nATOM 6766 HB2 ASP C 169 -41.965 -3.230 38.451 1.00 0.00 H \nATOM 6767 HB3 ASP C 169 -41.832 -2.579 37.041 1.00 0.00 H \nATOM 6768 N GLU C 170 -38.787 -2.961 38.443 1.00 0.00 N \nATOM 6769 CA GLU C 170 -37.620 -2.088 38.503 1.00 0.00 C \nATOM 6770 C GLU C 170 -36.387 -2.778 37.936 1.00 0.00 C \nATOM 6771 O GLU C 170 -35.626 -2.172 37.172 1.00 0.00 O \nATOM 6772 CB GLU C 170 -37.361 -1.658 39.946 1.00 0.00 C \nATOM 6773 CG GLU C 170 -38.317 -0.610 40.477 1.00 0.00 C \nATOM 6774 CD GLU C 170 -38.133 -0.387 41.966 1.00 0.00 C \nATOM 6775 OE1 GLU C 170 -37.804 -1.364 42.671 1.00 0.00 O \nATOM 6776 OE2 GLU C 170 -38.308 0.761 42.425 1.00 0.00 O \nATOM 6777 H GLU C 170 -39.041 -3.280 39.200 1.00 0.00 H \nATOM 6778 HA GLU C 170 -37.803 -1.304 37.962 1.00 0.00 H \nATOM 6779 HB2 GLU C 170 -37.409 -2.441 40.517 1.00 0.00 H \nATOM 6780 HB3 GLU C 170 -36.456 -1.315 40.011 1.00 0.00 H \nATOM 6781 HG2 GLU C 170 -38.177 0.225 40.005 1.00 0.00 H \nATOM 6782 HG3 GLU C 170 -39.230 -0.886 40.301 1.00 0.00 H \nATOM 6783 N THR C 171 -36.170 -4.043 38.306 1.00 0.00 N \nATOM 6784 CA THR C 171 -34.983 -4.759 37.851 1.00 0.00 C \nATOM 6785 C THR C 171 -34.995 -4.951 36.339 1.00 0.00 C \nATOM 6786 O THR C 171 -33.971 -4.756 35.673 1.00 0.00 O \nATOM 6787 CB THR C 171 -34.875 -6.108 38.562 1.00 0.00 C \nATOM 6788 OG1 THR C 171 -34.858 -5.904 39.981 1.00 0.00 O \nATOM 6789 CG2 THR C 171 -33.597 -6.819 38.151 1.00 0.00 C \nATOM 6790 H THR C 171 -36.694 -4.498 38.815 1.00 0.00 H \nATOM 6791 HA THR C 171 -34.206 -4.223 38.074 1.00 0.00 H \nATOM 6792 HB THR C 171 -35.639 -6.652 38.314 1.00 0.00 H \nATOM 6793 HG1 THR C 171 -34.677 -6.628 40.366 1.00 0.00 H \nATOM 6794 HG21 THR C 171 -33.540 -7.673 38.608 1.00 0.00 H \nATOM 6795 HG22 THR C 171 -33.602 -6.966 37.192 1.00 0.00 H \nATOM 6796 HG23 THR C 171 -32.832 -6.273 38.390 1.00 0.00 H \nATOM 6797 N CYS C 172 -36.142 -5.345 35.780 1.00 0.00 N \nATOM 6798 CA CYS C 172 -36.248 -5.494 34.332 1.00 0.00 C \nATOM 6799 C CYS C 172 -36.035 -4.162 33.624 1.00 0.00 C \nATOM 6800 O CYS C 172 -35.287 -4.079 32.643 1.00 0.00 O \nATOM 6801 CB CYS C 172 -37.611 -6.084 33.965 1.00 0.00 C \nATOM 6802 SG CYS C 172 -37.791 -7.848 34.323 1.00 0.00 S \nATOM 6803 H CYS C 172 -36.860 -5.528 36.217 1.00 0.00 H \nATOM 6804 HA CYS C 172 -35.551 -6.101 34.037 1.00 0.00 H \nATOM 6805 HB2 CYS C 172 -38.300 -5.597 34.444 1.00 0.00 H \nATOM 6806 HB3 CYS C 172 -37.768 -5.941 33.019 1.00 0.00 H \nATOM 6807 HG CYS C 172 -38.338 -7.988 35.382 1.00 0.00 H \nATOM 6808 N TYR C 173 -36.684 -3.103 34.117 1.00 0.00 N \nATOM 6809 CA TYR C 173 -36.546 -1.786 33.501 1.00 0.00 C \nATOM 6810 C TYR C 173 -35.100 -1.308 33.530 1.00 0.00 C \nATOM 6811 O TYR C 173 -34.626 -0.679 32.578 1.00 0.00 O \nATOM 6812 CB TYR C 173 -37.454 -0.786 34.213 1.00 0.00 C \nATOM 6813 CG TYR C 173 -37.586 0.554 33.526 1.00 0.00 C \nATOM 6814 CD1 TYR C 173 -36.652 1.561 33.735 1.00 0.00 C \nATOM 6815 CD2 TYR C 173 -38.650 0.815 32.674 1.00 0.00 C \nATOM 6816 CE1 TYR C 173 -36.769 2.787 33.111 1.00 0.00 C \nATOM 6817 CE2 TYR C 173 -38.779 2.039 32.049 1.00 0.00 C \nATOM 6818 CZ TYR C 173 -37.838 3.020 32.269 1.00 0.00 C \nATOM 6819 OH TYR C 173 -37.964 4.240 31.646 1.00 0.00 O \nATOM 6820 H TYR C 173 -37.204 -3.128 34.802 1.00 0.00 H \nATOM 6821 HA TYR C 173 -36.813 -1.855 32.571 1.00 0.00 H \nATOM 6822 HB2 TYR C 173 -38.337 -1.177 34.303 1.00 0.00 H \nATOM 6823 HB3 TYR C 173 -37.115 -0.643 35.110 1.00 0.00 H \nATOM 6824 HD1 TYR C 173 -35.934 1.406 34.306 1.00 0.00 H \nATOM 6825 HD2 TYR C 173 -39.287 0.154 32.522 1.00 0.00 H \nATOM 6826 HE1 TYR C 173 -36.133 3.450 33.257 1.00 0.00 H \nATOM 6827 HE2 TYR C 173 -39.498 2.200 31.482 1.00 0.00 H \nATOM 6828 HH TYR C 173 -38.134 4.831 32.218 1.00 0.00 H \nATOM 6829 N PHE C 174 -34.385 -1.595 34.616 1.00 0.00 N \nATOM 6830 CA PHE C 174 -32.997 -1.162 34.732 1.00 0.00 C \nATOM 6831 C PHE C 174 -32.101 -1.917 33.758 1.00 0.00 C \nATOM 6832 O PHE C 174 -31.262 -1.314 33.078 1.00 0.00 O \nATOM 6833 CB PHE C 174 -32.527 -1.343 36.177 1.00 0.00 C \nATOM 6834 CG PHE C 174 -31.037 -1.294 36.355 1.00 0.00 C \nATOM 6835 CD1 PHE C 174 -30.324 -0.142 36.066 1.00 0.00 C \nATOM 6836 CD2 PHE C 174 -30.354 -2.396 36.837 1.00 0.00 C \nATOM 6837 CE1 PHE C 174 -28.954 -0.098 36.241 1.00 0.00 C \nATOM 6838 CE2 PHE C 174 -28.985 -2.359 37.014 1.00 0.00 C \nATOM 6839 CZ PHE C 174 -28.283 -1.210 36.715 1.00 0.00 C \nATOM 6840 H PHE C 174 -34.683 -2.036 35.291 1.00 0.00 H \nATOM 6841 HA PHE C 174 -32.939 -0.222 34.499 1.00 0.00 H \nATOM 6842 HB2 PHE C 174 -32.930 -0.652 36.726 1.00 0.00 H \nATOM 6843 HB3 PHE C 174 -32.853 -2.194 36.508 1.00 0.00 H \nATOM 6844 HD1 PHE C 174 -30.772 0.610 35.751 1.00 0.00 H \nATOM 6845 HD2 PHE C 174 -30.823 -3.172 37.045 1.00 0.00 H \nATOM 6846 HE1 PHE C 174 -28.484 0.679 36.040 1.00 0.00 H \nATOM 6847 HE2 PHE C 174 -28.537 -3.108 37.335 1.00 0.00 H \nATOM 6848 HZ PHE C 174 -27.361 -1.183 36.832 1.00 0.00 H \nATOM 6849 N VAL C 175 -32.268 -3.239 33.673 1.00 0.00 N \nATOM 6850 CA VAL C 175 -31.439 -4.035 32.773 1.00 0.00 C \nATOM 6851 C VAL C 175 -31.790 -3.745 31.317 1.00 0.00 C \nATOM 6852 O VAL C 175 -30.901 -3.616 30.465 1.00 0.00 O \nATOM 6853 CB VAL C 175 -31.575 -5.533 33.103 1.00 0.00 C \nATOM 6854 CG1 VAL C 175 -30.810 -6.366 32.086 1.00 0.00 C \nATOM 6855 CG2 VAL C 175 -31.081 -5.818 34.515 1.00 0.00 C \nATOM 6856 H VAL C 175 -32.848 -3.687 34.123 1.00 0.00 H \nATOM 6857 HA VAL C 175 -30.510 -3.786 32.902 1.00 0.00 H \nATOM 6858 HB VAL C 175 -32.513 -5.777 33.058 1.00 0.00 H \nATOM 6859 HG11 VAL C 175 -30.902 -7.307 32.303 1.00 0.00 H \nATOM 6860 HG12 VAL C 175 -31.167 -6.203 31.199 1.00 0.00 H \nATOM 6861 HG13 VAL C 175 -29.872 -6.120 32.106 1.00 0.00 H \nATOM 6862 HG21 VAL C 175 -31.174 -6.765 34.706 1.00 0.00 H \nATOM 6863 HG22 VAL C 175 -30.148 -5.564 34.589 1.00 0.00 H \nATOM 6864 HG23 VAL C 175 -31.606 -5.308 35.151 1.00 0.00 H \nATOM 6865 N GLU C 176 -33.086 -3.654 31.005 1.00 0.00 N \nATOM 6866 CA GLU C 176 -33.505 -3.391 29.631 1.00 0.00 C \nATOM 6867 C GLU C 176 -32.959 -2.061 29.128 1.00 0.00 C \nATOM 6868 O GLU C 176 -32.600 -1.936 27.953 1.00 0.00 O \nATOM 6869 CB GLU C 176 -35.030 -3.414 29.530 1.00 0.00 C \nATOM 6870 CG GLU C 176 -35.641 -4.803 29.608 1.00 0.00 C \nATOM 6871 CD GLU C 176 -37.145 -4.763 29.797 1.00 0.00 C \nATOM 6872 OE1 GLU C 176 -37.670 -5.579 30.584 1.00 0.00 O \nATOM 6873 OE2 GLU C 176 -37.802 -3.913 29.161 1.00 0.00 O \nATOM 6874 H GLU C 176 -33.729 -3.741 31.569 1.00 0.00 H \nATOM 6875 HA GLU C 176 -33.141 -4.092 29.068 1.00 0.00 H \nATOM 6876 HB2 GLU C 176 -35.399 -2.869 30.243 1.00 0.00 H \nATOM 6877 HB3 GLU C 176 -35.294 -3.002 28.692 1.00 0.00 H \nATOM 6878 HG2 GLU C 176 -35.432 -5.291 28.796 1.00 0.00 H \nATOM 6879 HG3 GLU C 176 -35.238 -5.290 30.344 1.00 0.00 H \nATOM 6880 N ALA C 177 -32.898 -1.052 29.999 1.00 0.00 N \nATOM 6881 CA ALA C 177 -32.392 0.253 29.585 1.00 0.00 C \nATOM 6882 C ALA C 177 -30.924 0.172 29.184 1.00 0.00 C \nATOM 6883 O ALA C 177 -30.505 0.793 28.201 1.00 0.00 O \nATOM 6884 CB ALA C 177 -32.590 1.274 30.706 1.00 0.00 C \nATOM 6885 H ALA C 177 -33.141 -1.103 30.822 1.00 0.00 H \nATOM 6886 HA ALA C 177 -32.895 0.541 28.807 1.00 0.00 H \nATOM 6887 HB1 ALA C 177 -32.251 2.137 30.421 1.00 0.00 H \nATOM 6888 HB2 ALA C 177 -33.535 1.350 30.911 1.00 0.00 H \nATOM 6889 HB3 ALA C 177 -32.110 0.983 31.497 1.00 0.00 H \nATOM 6890 N LEU C 178 -30.127 -0.586 29.939 1.00 0.00 N \nATOM 6891 CA LEU C 178 -28.714 -0.733 29.609 1.00 0.00 C \nATOM 6892 C LEU C 178 -28.524 -1.594 28.366 1.00 0.00 C \nATOM 6893 O LEU C 178 -27.690 -1.278 27.508 1.00 0.00 O \nATOM 6894 CB LEU C 178 -27.961 -1.324 30.800 1.00 0.00 C \nATOM 6895 CG LEU C 178 -27.801 -0.382 31.996 1.00 0.00 C \nATOM 6896 CD1 LEU C 178 -27.265 -1.131 33.206 1.00 0.00 C \nATOM 6897 CD2 LEU C 178 -26.893 0.783 31.631 1.00 0.00 C \nATOM 6898 H LEU C 178 -30.383 -1.017 30.637 1.00 0.00 H \nATOM 6899 HA LEU C 178 -28.351 0.145 29.413 1.00 0.00 H \nATOM 6900 HB2 LEU C 178 -28.425 -2.123 31.095 1.00 0.00 H \nATOM 6901 HB3 LEU C 178 -27.080 -1.601 30.503 1.00 0.00 H \nATOM 6902 HG LEU C 178 -28.674 -0.028 32.229 1.00 0.00 H \nATOM 6903 HD11 LEU C 178 -27.171 -0.517 33.951 1.00 0.00 H \nATOM 6904 HD12 LEU C 178 -27.882 -1.840 33.447 1.00 0.00 H \nATOM 6905 HD13 LEU C 178 -26.400 -1.514 32.992 1.00 0.00 H \nATOM 6906 HD21 LEU C 178 -26.799 1.372 32.396 1.00 0.00 H \nATOM 6907 HD22 LEU C 178 -26.021 0.446 31.375 1.00 0.00 H \nATOM 6908 HD23 LEU C 178 -27.280 1.275 30.890 1.00 0.00 H \nATOM 6909 N LEU C 179 -29.287 -2.685 28.252 1.00 0.00 N \nATOM 6910 CA LEU C 179 -29.205 -3.526 27.063 1.00 0.00 C \nATOM 6911 C LEU C 179 -29.653 -2.770 25.818 1.00 0.00 C \nATOM 6912 O LEU C 179 -29.054 -2.915 24.746 1.00 0.00 O \nATOM 6913 CB LEU C 179 -30.039 -4.792 27.256 1.00 0.00 C \nATOM 6914 CG LEU C 179 -29.595 -5.764 28.349 1.00 0.00 C \nATOM 6915 CD1 LEU C 179 -30.460 -7.015 28.332 1.00 0.00 C \nATOM 6916 CD2 LEU C 179 -28.127 -6.121 28.192 1.00 0.00 C \nATOM 6917 H LEU C 179 -29.850 -2.950 28.845 1.00 0.00 H \nATOM 6918 HA LEU C 179 -28.277 -3.779 26.934 1.00 0.00 H \nATOM 6919 HB2 LEU C 179 -30.952 -4.524 27.445 1.00 0.00 H \nATOM 6920 HB3 LEU C 179 -30.053 -5.273 26.414 1.00 0.00 H \nATOM 6921 HG LEU C 179 -29.706 -5.327 29.208 1.00 0.00 H \nATOM 6922 HD11 LEU C 179 -30.166 -7.621 29.030 1.00 0.00 H \nATOM 6923 HD12 LEU C 179 -31.386 -6.770 28.485 1.00 0.00 H \nATOM 6924 HD13 LEU C 179 -30.380 -7.452 27.470 1.00 0.00 H \nATOM 6925 HD21 LEU C 179 -27.867 -6.737 28.894 1.00 0.00 H \nATOM 6926 HD22 LEU C 179 -27.986 -6.538 27.328 1.00 0.00 H \nATOM 6927 HD23 LEU C 179 -27.590 -5.316 28.254 1.00 0.00 H \nATOM 6928 N LYS C 180 -30.712 -1.966 25.939 1.00 0.00 N \nATOM 6929 CA LYS C 180 -31.209 -1.214 24.791 1.00 0.00 C \nATOM 6930 C LYS C 180 -30.169 -0.217 24.293 1.00 0.00 C \nATOM 6931 O LYS C 180 -29.986 -0.054 23.080 1.00 0.00 O \nATOM 6932 CB LYS C 180 -32.508 -0.498 25.165 1.00 0.00 C \nATOM 6933 CG LYS C 180 -33.217 0.194 24.015 1.00 0.00 C \nATOM 6934 CD LYS C 180 -34.398 1.011 24.526 1.00 0.00 C \nATOM 6935 CE LYS C 180 -35.381 1.329 23.411 1.00 0.00 C \nATOM 6936 NZ LYS C 180 -36.796 1.207 23.865 1.00 0.00 N \nATOM 6937 H LYS C 180 -31.150 -1.845 26.669 1.00 0.00 H \nATOM 6938 HA LYS C 180 -31.387 -1.836 24.069 1.00 0.00 H \nATOM 6939 HB2 LYS C 180 -33.115 -1.144 25.559 1.00 0.00 H \nATOM 6940 HB3 LYS C 180 -32.312 0.161 25.849 1.00 0.00 H \nATOM 6941 HG2 LYS C 180 -32.595 0.773 23.547 1.00 0.00 H \nATOM 6942 HG3 LYS C 180 -33.527 -0.466 23.375 1.00 0.00 H \nATOM 6943 HD2 LYS C 180 -34.852 0.520 25.229 1.00 0.00 H \nATOM 6944 HD3 LYS C 180 -34.075 1.837 24.919 1.00 0.00 H \nATOM 6945 HE2 LYS C 180 -35.222 2.230 23.087 1.00 0.00 H \nATOM 6946 HE3 LYS C 180 -35.228 0.728 22.665 1.00 0.00 H \nATOM 6947 HZ1 LYS C 180 -37.291 0.870 23.207 1.00 0.00 H \nATOM 6948 HZ2 LYS C 180 -36.836 0.668 24.572 1.00 0.00 H \nATOM 6949 HZ3 LYS C 180 -37.107 2.011 24.088 1.00 0.00 H \nATOM 6950 N CYS C 181 -29.483 0.464 25.214 1.00 0.00 N \nATOM 6951 CA CYS C 181 -28.412 1.373 24.820 1.00 0.00 C \nATOM 6952 C CYS C 181 -27.251 0.632 24.166 1.00 0.00 C \nATOM 6953 O CYS C 181 -26.619 1.163 23.244 1.00 0.00 O \nATOM 6954 CB CYS C 181 -27.922 2.163 26.033 1.00 0.00 C \nATOM 6955 SG CYS C 181 -26.492 3.223 25.706 1.00 0.00 S \nATOM 6956 H CYS C 181 -29.622 0.413 26.061 1.00 0.00 H \nATOM 6957 HA CYS C 181 -28.773 1.987 24.162 1.00 0.00 H \nATOM 6958 HB2 CYS C 181 -28.650 2.713 26.363 1.00 0.00 H \nATOM 6959 HB3 CYS C 181 -27.694 1.540 26.741 1.00 0.00 H \nATOM 6960 HG CYS C 181 -26.627 4.267 26.282 1.00 0.00 H \nATOM 6961 N ASN C 182 -26.959 -0.589 24.621 1.00 0.00 N \nATOM 6962 CA ASN C 182 -25.855 -1.347 24.041 1.00 0.00 C \nATOM 6963 C ASN C 182 -26.204 -1.872 22.655 1.00 0.00 C \nATOM 6964 O ASN C 182 -25.344 -1.910 21.766 1.00 0.00 O \nATOM 6965 CB ASN C 182 -25.468 -2.500 24.963 1.00 0.00 C \nATOM 6966 CG ASN C 182 -24.480 -2.081 26.023 1.00 0.00 C \nATOM 6967 OD1 ASN C 182 -23.894 -1.003 25.952 1.00 0.00 O \nATOM 6968 ND2 ASN C 182 -24.281 -2.936 27.011 1.00 0.00 N \nATOM 6969 H ASN C 182 -27.382 -0.989 25.254 1.00 0.00 H \nATOM 6970 HA ASN C 182 -25.099 -0.747 23.947 1.00 0.00 H \nATOM 6971 HB2 ASN C 182 -26.265 -2.852 25.389 1.00 0.00 H \nATOM 6972 HB3 ASN C 182 -25.087 -3.219 24.435 1.00 0.00 H \nATOM 6973 HD21 ASN C 182 -23.723 -2.747 27.637 1.00 0.00 H \nATOM 6974 HD22 ASN C 182 -24.710 -3.681 27.027 1.00 0.00 H \nATOM 6975 N LEU C 183 -27.456 -2.285 22.450 1.00 0.00 N \nATOM 6976 CA LEU C 183 -27.859 -2.753 21.130 1.00 0.00 C \nATOM 6977 C LEU C 183 -27.944 -1.601 20.139 1.00 0.00 C \nATOM 6978 O LEU C 183 -27.620 -1.769 18.957 1.00 0.00 O \nATOM 6979 CB LEU C 183 -29.186 -3.503 21.217 1.00 0.00 C \nATOM 6980 CG LEU C 183 -29.117 -4.806 22.022 1.00 0.00 C \nATOM 6981 CD1 LEU C 183 -30.411 -5.587 21.887 1.00 0.00 C \nATOM 6982 CD2 LEU C 183 -27.929 -5.650 21.583 1.00 0.00 C \nATOM 6983 H LEU C 183 -28.073 -2.301 23.049 1.00 0.00 H \nATOM 6984 HA LEU C 183 -27.181 -3.366 20.804 1.00 0.00 H \nATOM 6985 HB2 LEU C 183 -29.850 -2.921 21.619 1.00 0.00 H \nATOM 6986 HB3 LEU C 183 -29.492 -3.705 20.319 1.00 0.00 H \nATOM 6987 HG LEU C 183 -28.996 -4.579 22.957 1.00 0.00 H \nATOM 6988 HD11 LEU C 183 -30.350 -6.407 22.402 1.00 0.00 H \nATOM 6989 HD12 LEU C 183 -31.148 -5.052 22.219 1.00 0.00 H \nATOM 6990 HD13 LEU C 183 -30.563 -5.803 20.954 1.00 0.00 H \nATOM 6991 HD21 LEU C 183 -27.903 -6.468 22.103 1.00 0.00 H \nATOM 6992 HD22 LEU C 183 -28.017 -5.868 20.642 1.00 0.00 H \nATOM 6993 HD23 LEU C 183 -27.109 -5.152 21.724 1.00 0.00 H \nATOM 6994 N LYS C 184 -28.385 -0.427 20.597 1.00 0.00 N \nATOM 6995 CA LYS C 184 -28.406 0.737 19.717 1.00 0.00 C \nATOM 6996 C LYS C 184 -26.994 1.141 19.311 1.00 0.00 C \nATOM 6997 O LYS C 184 -26.760 1.565 18.171 1.00 0.00 O \nATOM 6998 CB LYS C 184 -29.125 1.900 20.402 1.00 0.00 C \nATOM 6999 CG LYS C 184 -28.930 3.245 19.719 1.00 0.00 C \nATOM 7000 CD LYS C 184 -30.243 4.002 19.579 1.00 0.00 C \nATOM 7001 CE LYS C 184 -30.989 4.088 20.903 1.00 0.00 C \nATOM 7002 NZ LYS C 184 -32.361 4.641 20.723 1.00 0.00 N \nATOM 7003 H LYS C 184 -28.670 -0.287 21.396 1.00 0.00 H \nATOM 7004 HA LYS C 184 -28.890 0.502 18.910 1.00 0.00 H \nATOM 7005 HB2 LYS C 184 -30.074 1.703 20.440 1.00 0.00 H \nATOM 7006 HB3 LYS C 184 -28.812 1.966 21.318 1.00 0.00 H \nATOM 7007 HG2 LYS C 184 -28.301 3.779 20.229 1.00 0.00 H \nATOM 7008 HG3 LYS C 184 -28.540 3.109 18.841 1.00 0.00 H \nATOM 7009 HD2 LYS C 184 -30.067 4.897 19.248 1.00 0.00 H \nATOM 7010 HD3 LYS C 184 -30.802 3.561 18.921 1.00 0.00 H \nATOM 7011 HE2 LYS C 184 -31.045 3.206 21.302 1.00 0.00 H \nATOM 7012 HE3 LYS C 184 -30.492 4.648 21.520 1.00 0.00 H \nATOM 7013 HZ1 LYS C 184 -32.905 4.290 21.334 1.00 0.00 H \nATOM 7014 HZ2 LYS C 184 -32.340 5.526 20.819 1.00 0.00 H \nATOM 7015 HZ3 LYS C 184 -32.659 4.438 19.909 1.00 0.00 H \nATOM 7016 N SER C 185 -26.036 1.009 20.231 1.00 0.00 N \nATOM 7017 CA SER C 185 -24.648 1.303 19.893 1.00 0.00 C \nATOM 7018 C SER C 185 -24.064 0.232 18.980 1.00 0.00 C \nATOM 7019 O SER C 185 -23.265 0.538 18.087 1.00 0.00 O \nATOM 7020 CB SER C 185 -23.820 1.447 21.168 1.00 0.00 C \nATOM 7021 OG SER C 185 -22.434 1.476 20.880 1.00 0.00 O \nATOM 7022 H SER C 185 -26.168 0.755 21.042 1.00 0.00 H \nATOM 7023 HA SER C 185 -24.621 2.143 19.408 1.00 0.00 H \nATOM 7024 HB2 SER C 185 -24.074 2.261 21.631 1.00 0.00 H \nATOM 7025 HB3 SER C 185 -24.013 0.709 21.767 1.00 0.00 H \nATOM 7026 HG SER C 185 -22.009 1.119 21.510 1.00 0.00 H \nATOM 7027 N LEU C 186 -24.448 -1.031 19.187 1.00 0.00 N \nATOM 7028 CA LEU C 186 -24.044 -2.083 18.260 1.00 0.00 C \nATOM 7029 C LEU C 186 -24.596 -1.812 16.867 1.00 0.00 C \nATOM 7030 O LEU C 186 -23.917 -2.050 15.861 1.00 0.00 O \nATOM 7031 CB LEU C 186 -24.507 -3.449 18.773 1.00 0.00 C \nATOM 7032 CG LEU C 186 -24.315 -4.651 17.846 1.00 0.00 C \nATOM 7033 CD1 LEU C 186 -22.837 -4.923 17.595 1.00 0.00 C \nATOM 7034 CD2 LEU C 186 -25.004 -5.887 18.420 1.00 0.00 C \nATOM 7035 H LEU C 186 -24.934 -1.293 19.847 1.00 0.00 H \nATOM 7036 HA LEU C 186 -23.076 -2.090 18.203 1.00 0.00 H \nATOM 7037 HB2 LEU C 186 -24.039 -3.632 19.602 1.00 0.00 H \nATOM 7038 HB3 LEU C 186 -25.451 -3.384 18.988 1.00 0.00 H \nATOM 7039 HG LEU C 186 -24.726 -4.440 16.993 1.00 0.00 H \nATOM 7040 HD11 LEU C 186 -22.744 -5.688 17.006 1.00 0.00 H \nATOM 7041 HD12 LEU C 186 -22.430 -4.146 17.181 1.00 0.00 H \nATOM 7042 HD13 LEU C 186 -22.394 -5.109 18.438 1.00 0.00 H \nATOM 7043 HD21 LEU C 186 -24.873 -6.638 17.821 1.00 0.00 H \nATOM 7044 HD22 LEU C 186 -24.624 -6.096 19.288 1.00 0.00 H \nATOM 7045 HD23 LEU C 186 -25.953 -5.713 18.516 1.00 0.00 H \nATOM 7046 N ALA C 187 -25.831 -1.315 16.791 1.00 0.00 N \nATOM 7047 CA ALA C 187 -26.418 -0.964 15.502 1.00 0.00 C \nATOM 7048 C ALA C 187 -25.638 0.162 14.832 1.00 0.00 C \nATOM 7049 O ALA C 187 -25.341 0.098 13.633 1.00 0.00 O \nATOM 7050 CB ALA C 187 -27.886 -0.573 15.687 1.00 0.00 C \nATOM 7051 H ALA C 187 -26.341 -1.175 17.469 1.00 0.00 H \nATOM 7052 HA ALA C 187 -26.371 -1.739 14.921 1.00 0.00 H \nATOM 7053 HB1 ALA C 187 -28.270 -0.341 14.827 1.00 0.00 H \nATOM 7054 HB2 ALA C 187 -28.374 -1.320 16.068 1.00 0.00 H \nATOM 7055 HB3 ALA C 187 -27.945 0.190 16.283 1.00 0.00 H \nATOM 7056 N GLU C 188 -25.305 1.209 15.593 1.00 0.00 N \nATOM 7057 CA GLU C 188 -24.550 2.324 15.026 1.00 0.00 C \nATOM 7058 C GLU C 188 -23.162 1.885 14.575 1.00 0.00 C \nATOM 7059 O GLU C 188 -22.696 2.280 13.498 1.00 0.00 O \nATOM 7060 CB GLU C 188 -24.449 3.465 16.040 1.00 0.00 C \nATOM 7061 CG GLU C 188 -23.307 4.447 15.773 1.00 0.00 C \nATOM 7062 CD GLU C 188 -23.626 5.461 14.683 1.00 0.00 C \nATOM 7063 OE1 GLU C 188 -23.996 5.053 13.561 1.00 0.00 O \nATOM 7064 OE2 GLU C 188 -23.506 6.674 14.954 1.00 0.00 O \nATOM 7065 H GLU C 188 -25.504 1.291 16.426 1.00 0.00 H \nATOM 7066 HA GLU C 188 -25.027 2.641 14.243 1.00 0.00 H \nATOM 7067 HB2 GLU C 188 -25.287 3.954 16.045 1.00 0.00 H \nATOM 7068 HB3 GLU C 188 -24.336 3.087 16.926 1.00 0.00 H \nATOM 7069 HG2 GLU C 188 -23.097 4.919 16.594 1.00 0.00 H \nATOM 7070 HG3 GLU C 188 -22.513 3.949 15.521 1.00 0.00 H \nATOM 7071 N VAL C 189 -22.484 1.073 15.389 1.00 0.00 N \nATOM 7072 CA VAL C 189 -21.149 0.601 15.030 1.00 0.00 C \nATOM 7073 C VAL C 189 -21.214 -0.280 13.788 1.00 0.00 C \nATOM 7074 O VAL C 189 -20.417 -0.128 12.855 1.00 0.00 O \nATOM 7075 CB VAL C 189 -20.501 -0.136 16.217 1.00 0.00 C \nATOM 7076 CG1 VAL C 189 -19.243 -0.858 15.772 1.00 0.00 C \nATOM 7077 CG2 VAL C 189 -20.187 0.843 17.334 1.00 0.00 C \nATOM 7078 H VAL C 189 -22.777 0.787 16.145 1.00 0.00 H \nATOM 7079 HA VAL C 189 -20.590 1.366 14.820 1.00 0.00 H \nATOM 7080 HB VAL C 189 -21.128 -0.796 16.552 1.00 0.00 H \nATOM 7081 HG11 VAL C 189 -18.848 -1.316 16.530 1.00 0.00 H \nATOM 7082 HG12 VAL C 189 -19.467 -1.505 15.084 1.00 0.00 H \nATOM 7083 HG13 VAL C 189 -18.609 -0.215 15.417 1.00 0.00 H \nATOM 7084 HG21 VAL C 189 -19.780 0.368 18.076 1.00 0.00 H \nATOM 7085 HG22 VAL C 189 -19.574 1.520 17.008 1.00 0.00 H \nATOM 7086 HG23 VAL C 189 -21.007 1.267 17.633 1.00 0.00 H \nATOM 7087 N SER C 190 -22.162 -1.219 13.760 1.00 0.00 N \nATOM 7088 CA SER C 190 -22.277 -2.111 12.611 1.00 0.00 C \nATOM 7089 C SER C 190 -22.607 -1.339 11.340 1.00 0.00 C \nATOM 7090 O SER C 190 -22.044 -1.615 10.274 1.00 0.00 O \nATOM 7091 CB SER C 190 -23.338 -3.180 12.877 1.00 0.00 C \nATOM 7092 OG SER C 190 -23.085 -3.879 14.080 1.00 0.00 O \nATOM 7093 H SER C 190 -22.737 -1.353 14.385 1.00 0.00 H \nATOM 7094 HA SER C 190 -21.419 -2.544 12.480 1.00 0.00 H \nATOM 7095 HB2 SER C 190 -24.213 -2.764 12.922 1.00 0.00 H \nATOM 7096 HB3 SER C 190 -23.360 -3.806 12.137 1.00 0.00 H \nATOM 7097 HG SER C 190 -23.203 -3.364 14.733 1.00 0.00 H \nATOM 7098 N GLU C 191 -23.510 -0.359 11.433 1.00 0.00 N \nATOM 7099 CA GLU C 191 -23.948 0.368 10.247 1.00 0.00 C \nATOM 7100 C GLU C 191 -22.930 1.377 9.749 1.00 0.00 C \nATOM 7101 O GLU C 191 -23.001 1.782 8.584 1.00 0.00 O \nATOM 7102 CB GLU C 191 -25.264 1.094 10.528 1.00 0.00 C \nATOM 7103 CG GLU C 191 -26.472 0.197 10.429 1.00 0.00 C \nATOM 7104 CD GLU C 191 -27.618 0.684 11.283 1.00 0.00 C \nATOM 7105 OE1 GLU C 191 -28.615 -0.056 11.416 1.00 0.00 O \nATOM 7106 OE2 GLU C 191 -27.526 1.808 11.821 1.00 0.00 O \nATOM 7107 H GLU C 191 -23.876 -0.104 12.168 1.00 0.00 H \nATOM 7108 HA GLU C 191 -24.063 -0.299 9.552 1.00 0.00 H \nATOM 7109 HB2 GLU C 191 -25.229 1.482 11.416 1.00 0.00 H \nATOM 7110 HB3 GLU C 191 -25.362 1.828 9.901 1.00 0.00 H \nATOM 7111 HG2 GLU C 191 -26.759 0.146 9.504 1.00 0.00 H \nATOM 7112 HG3 GLU C 191 -26.228 -0.702 10.700 1.00 0.00 H \nATOM 7113 N ARG C 192 -21.998 1.802 10.594 1.00 0.00 N \nATOM 7114 CA ARG C 192 -20.964 2.728 10.166 1.00 0.00 C \nATOM 7115 C ARG C 192 -19.673 1.999 9.827 1.00 0.00 C \nATOM 7116 O ARG C 192 -18.630 2.634 9.639 1.00 0.00 O \nATOM 7117 CB ARG C 192 -20.765 3.820 11.224 1.00 0.00 C \nATOM 7118 CG ARG C 192 -19.841 3.524 12.376 1.00 0.00 C \nATOM 7119 CD ARG C 192 -19.216 4.823 12.818 1.00 0.00 C \nATOM 7120 NE ARG C 192 -18.511 5.490 11.716 1.00 0.00 N \nATOM 7121 CZ ARG C 192 -19.041 6.421 10.933 1.00 0.00 C \nATOM 7122 NH1 ARG C 192 -20.251 6.874 11.187 1.00 0.00 N \nATOM 7123 NH2 ARG C 192 -18.325 6.946 9.956 1.00 0.00 N \nATOM 7124 H ARG C 192 -21.949 1.565 11.419 1.00 0.00 H \nATOM 7125 HA ARG C 192 -21.251 3.163 9.348 1.00 0.00 H \nATOM 7126 HB2 ARG C 192 -20.435 4.614 10.774 1.00 0.00 H \nATOM 7127 HB3 ARG C 192 -21.635 4.042 11.590 1.00 0.00 H \nATOM 7128 HG2 ARG C 192 -20.331 3.117 13.108 1.00 0.00 H \nATOM 7129 HG3 ARG C 192 -19.156 2.892 12.107 1.00 0.00 H \nATOM 7130 HD2 ARG C 192 -19.904 5.412 13.165 1.00 0.00 H \nATOM 7131 HD3 ARG C 192 -18.595 4.653 13.544 1.00 0.00 H \nATOM 7132 HE ARG C 192 -17.696 5.261 11.567 1.00 0.00 H \nATOM 7133 HH11 ARG C 192 -20.693 6.567 11.857 1.00 0.00 H \nATOM 7134 HH12 ARG C 192 -20.599 7.477 10.683 1.00 0.00 H \nATOM 7135 HH21 ARG C 192 -17.516 6.685 9.827 1.00 0.00 H \nATOM 7136 HH22 ARG C 192 -18.668 7.549 9.448 1.00 0.00 H \nATOM 7137 N LEU C 193 -19.739 0.672 9.767 1.00 0.00 N \nATOM 7138 CA LEU C 193 -18.725 -0.178 9.165 1.00 0.00 C \nATOM 7139 C LEU C 193 -19.224 -0.829 7.882 1.00 0.00 C \nATOM 7140 O LEU C 193 -18.465 -1.541 7.217 1.00 0.00 O \nATOM 7141 CB LEU C 193 -18.252 -1.243 10.159 1.00 0.00 C \nATOM 7142 CG LEU C 193 -17.204 -0.723 11.148 1.00 0.00 C \nATOM 7143 CD1 LEU C 193 -17.277 -1.479 12.461 1.00 0.00 C \nATOM 7144 CD2 LEU C 193 -15.804 -0.800 10.544 1.00 0.00 C \nATOM 7145 H LEU C 193 -20.402 0.228 10.089 1.00 0.00 H \nATOM 7146 HA LEU C 193 -17.972 0.388 8.933 1.00 0.00 H \nATOM 7147 HB2 LEU C 193 -19.016 -1.578 10.653 1.00 0.00 H \nATOM 7148 HB3 LEU C 193 -17.881 -1.993 9.668 1.00 0.00 H \nATOM 7149 HG LEU C 193 -17.398 0.209 11.332 1.00 0.00 H \nATOM 7150 HD11 LEU C 193 -16.606 -1.134 13.071 1.00 0.00 H \nATOM 7151 HD12 LEU C 193 -18.158 -1.365 12.852 1.00 0.00 H \nATOM 7152 HD13 LEU C 193 -17.114 -2.422 12.301 1.00 0.00 H \nATOM 7153 HD21 LEU C 193 -15.156 -0.467 11.185 1.00 0.00 H \nATOM 7154 HD22 LEU C 193 -15.596 -1.722 10.324 1.00 0.00 H \nATOM 7155 HD23 LEU C 193 -15.769 -0.260 9.739 1.00 0.00 H \nATOM 7156 N VAL C 194 -20.490 -0.615 7.534 1.00 0.00 N \nATOM 7157 CA VAL C 194 -21.017 -1.024 6.239 1.00 0.00 C \nATOM 7158 C VAL C 194 -20.823 0.092 5.218 1.00 0.00 C \nATOM 7159 O VAL C 194 -20.667 -0.179 4.022 1.00 0.00 O \nATOM 7160 CB VAL C 194 -22.506 -1.409 6.372 1.00 0.00 C \nATOM 7161 CG1 VAL C 194 -23.208 -1.414 5.019 1.00 0.00 C \nATOM 7162 CG2 VAL C 194 -22.649 -2.759 7.038 1.00 0.00 C \nATOM 7163 H VAL C 194 -21.066 -0.229 8.043 1.00 0.00 H \nATOM 7164 HA VAL C 194 -20.531 -1.803 5.927 1.00 0.00 H \nATOM 7165 HB VAL C 194 -22.932 -0.737 6.927 1.00 0.00 H \nATOM 7166 HG11 VAL C 194 -24.139 -1.659 5.138 1.00 0.00 H \nATOM 7167 HG12 VAL C 194 -23.155 -0.530 4.623 1.00 0.00 H \nATOM 7168 HG13 VAL C 194 -22.777 -2.056 4.433 1.00 0.00 H \nATOM 7169 HG21 VAL C 194 -23.589 -2.985 7.113 1.00 0.00 H \nATOM 7170 HG22 VAL C 194 -22.197 -3.432 6.506 1.00 0.00 H \nATOM 7171 HG23 VAL C 194 -22.253 -2.727 7.923 1.00 0.00 H \nATOM 7172 N VAL C 195 -20.777 1.337 5.677 1.00 0.00 N \nATOM 7173 CA VAL C 195 -20.526 2.476 4.814 1.00 0.00 C \nATOM 7174 C VAL C 195 -19.103 2.410 4.274 1.00 0.00 C \nATOM 7175 O VAL C 195 -18.149 2.243 5.034 1.00 0.00 O \nATOM 7176 CB VAL C 195 -20.762 3.797 5.562 1.00 0.00 C \nATOM 7177 CG1 VAL C 195 -20.112 4.952 4.818 1.00 0.00 C \nATOM 7178 CG2 VAL C 195 -22.253 4.039 5.760 1.00 0.00 C \nATOM 7179 H VAL C 195 -20.892 1.543 6.504 1.00 0.00 H \nATOM 7180 HA VAL C 195 -21.148 2.444 4.070 1.00 0.00 H \nATOM 7181 HB VAL C 195 -20.351 3.736 6.438 1.00 0.00 H \nATOM 7182 HG11 VAL C 195 -20.269 5.778 5.302 1.00 0.00 H \nATOM 7183 HG12 VAL C 195 -19.157 4.796 4.748 1.00 0.00 H \nATOM 7184 HG13 VAL C 195 -20.494 5.020 3.929 1.00 0.00 H \nATOM 7185 HG21 VAL C 195 -22.385 4.875 6.233 1.00 0.00 H \nATOM 7186 HG22 VAL C 195 -22.691 4.084 4.896 1.00 0.00 H \nATOM 7187 HG23 VAL C 195 -22.633 3.312 6.277 1.00 0.00 H \"}'"])</script><script>self.__next_f.push([1,"d9:Tb2257,"])</script><script>self.__next_f.push([1,"{\n \"trajectory\": [\n \"MODEL\\\\nCOMPND 5zcu_ligand\\\\nHETATM 1 S1 UNL 1 -21.984 -3.493 30.267 1.00 0.00 S \\\\nHETATM 2 BR1 UNL 1 -24.121 -0.640 35.679 1.00 0.00 BR \\\\nHETATM 3 C1 UNL 1 -23.447 -1.703 34.203 1.00 0.00 C \\\\nHETATM 4 N1 UNL 1 -23.033 -4.756 29.787 1.00 0.00 N \\\\nHETATM 5 O1 UNL 1 -20.587 -3.929 30.288 1.00 0.00 O \\\\nHETATM 6 C2 UNL 1 -23.040 -3.049 34.250 1.00 0.00 C \\\\nHETATM 7 N2 UNL 1 -25.672 -6.380 30.757 1.00 0.00 N \\\\nHETATM 8 O2 UNL 1 -21.945 -2.404 29.288 1.00 0.00 O \\\\nHETATM 9 C3 UNL 1 -22.584 -3.660 33.110 1.00 0.00 C \\\\nHETATM 10 C4 UNL 1 -22.527 -2.945 31.906 1.00 0.00 C \\\\nHETATM 11 C5 UNL 1 -22.929 -1.618 31.851 1.00 0.00 C \\\\nHETATM 12 C6 UNL 1 -23.390 -0.995 33.007 1.00 0.00 C \\\\nHETATM 13 C7 UNL 1 -22.177 -5.006 33.132 1.00 0.00 C \\\\nHETATM 14 C8 UNL 1 -22.231 -5.725 34.315 1.00 0.00 C \\\\nHETATM 15 C9 UNL 1 -22.688 -5.108 35.472 1.00 0.00 C \\\\nHETATM 16 C10 UNL 1 -23.094 -3.779 35.451 1.00 0.00 C \\\\nHETATM 17 C11 UNL 1 -24.458 -4.504 29.655 1.00 0.00 C \\\\nHETATM 18 C12 UNL 1 -25.258 -5.096 30.815 1.00 0.00 C \\\\nHETATM 19 C13 UNL 1 -26.385 -6.908 31.777 1.00 0.00 C \\\\nHETATM 20 C14 UNL 1 -26.701 -6.134 32.880 1.00 0.00 C \\\\nHETATM 21 C15 UNL 1 -26.293 -4.843 32.939 1.00 0.00 C \\\\nHETATM 22 C16 UNL 1 -25.580 -4.315 31.915 1.00 0.00 C \\\\nHETATM 23 H1 UNL 1 -22.666 -5.667 29.597 1.00 0.00 H \\\\nHETATM 24 H2 UNL 1 -22.884 -1.071 30.916 1.00 0.00 H \\\\nHETATM 25 H3 UNL 1 -23.705 0.042 32.975 1.00 0.00 H \\\\nHETATM 26 H4 UNL 1 -21.822 -5.480 32.224 1.00 0.00 H \\\\nHETATM 27 H5 UNL 1 -21.919 -6.763 34.337 1.00 0.00 H \\\\nHETATM 28 H6 UNL 1 -22.728 -5.668 36.400 1.00 0.00 H \\\\nHETATM 29 H7 UNL 1 -23.452 -3.306 36.358 1.00 0.00 H \\\\nHETATM 30 H8 UNL 1 -24.812 -4.953 28.715 1.00 0.00 H \\\\nHETATM 31 H9 UNL 1 -24.625 -3.417 29.628 1.00 0.00 H \\\\nHETATM 32 H10 UNL 1 -26.710 -7.941 31.731 1.00 0.00 H \\\\nHETATM 33 H11 UNL 1 -27.274 -6.560 33.696 1.00 0.00 H \\\\nHETATM 34 H12 UNL 1 -26.536 -4.235 33.803 1.00 0.00 H \\\\nHETATM 35 H13 UNL 1 -25.261 -3.280 31.956 1.00 0.00 H \\\\nCONECT 1 4 5 5 8\\\\nCONECT 1 8 10\\\\nCONECT 2 3\\\\nCONECT 3 6 6 12\\\\nCONECT 4 17 23\\\\nCONECT 6 9 16\\\\nCONECT 7 18 18 19\\\\nCONECT 9 10 10 13\\\\nCONECT 10 11\\\\nCONECT 11 12 12 24\\\\nCONECT 12 25\\\\nCONECT 13 14 14 26\\\\nCONECT 14 15 27\\\\nCONECT 15 16 16 28\\\\nCONECT 16 29\\\\nCONECT 17 18 30 31\\\\nCONECT 18 22\\\\nCONECT 19 20 20 32\\\\nCONECT 20 21 33\\\\nCONECT 21 22 22 34\\\\nCONECT 22 35\\\\nENDMDL\\\\nMODEL\\\\nCOMPND 5zcu_ligand\\\\nHETATM 1 S1 UNL 1 -22.160 14.516 31.439 1.00 0.00 S \\\\nHETATM 2 BR1 UNL 1 -24.297 17.369 36.851 1.00 0.00 BR \\\\nHETATM 3 C1 UNL 1 -23.623 16.306 35.375 1.00 0.00 C \\\\nHETATM 4 N1 UNL 1 -23.209 13.253 30.959 1.00 0.00 N \\\\nHETATM 5 O1 UNL 1 -20.763 14.080 31.460 1.00 0.00 O \\\\nHETATM 6 C2 UNL 1 -23.216 14.960 35.422 1.00 0.00 C \\\\nHETATM 7 N2 UNL 1 -25.848 11.629 31.929 1.00 0.00 N \\\\nHETATM 8 O2 UNL 1 -22.121 15.605 30.460 1.00 0.00 O \\\\nHETATM 9 C3 UNL 1 -22.760 14.349 34.282 1.00 0.00 C \\\\nHETATM 10 C4 UNL 1 -22.703 15.064 33.078 1.00 0.00 C \\\\nHETATM 11 C5 UNL 1 -23.105 16.391 33.023 1.00 0.00 C \\\\nHETATM 12 C6 UNL 1 -23.566 17.014 34.179 1.00 0.00 C \\\\nHETATM 13 C7 UNL 1 -22.353 13.003 34.304 1.00 0.00 C \\\\nHETATM 14 C8 UNL 1 -22.407 12.284 35.487 1.00 0.00 C \\\\nHETATM 15 C9 UNL 1 -22.864 12.901 36.644 1.00 0.00 C \\\\nHETATM 16 C10 UNL 1 -23.270 14.230 36.623 1.00 0.00 C \\\\nHETATM 17 C11 UNL 1 -24.634 13.505 30.827 1.00 0.00 C \\\\nHETATM 18 C12 UNL 1 -25.434 12.913 31.987 1.00 0.00 C \\\\nHETATM 19 C13 UNL 1 -26.561 11.101 32.949 1.00 0.00 C \\\\nHETATM 20 C14 UNL 1 -26.877 11.875 34.052 1.00 0.00 C \\\\nHETATM 21 C15 UNL 1 -26.469 13.166 34.111 1.00 0.00 C \\\\nHETATM 22 C16 UNL 1 -25.756 13.694 33.087 1.00 0.00 C \\\\nHETATM 23 H1 UNL 1 -22.666 -5.667 29.597 1.00 0.00 H \\\\nHETATM 24 H2 UNL 1 -22.884 -1.071 30.916 1.00 0.00 H \\\\nHETATM 25 H3 UNL 1 -23.705 0.042 32.975 1.00 0.00 H \\\\nHETATM 26 H4 UNL 1 -21.822 -5.480 32.224 1.00 0.00 H \\\\nHETATM 27 H5 UNL 1 -21.919 -6.763 34.337 1.00 0.00 H \\\\nHETATM 28 H6 UNL 1 -22.728 -5.668 36.400 1.00 0.00 H \\\\nHETATM 29 H7 UNL 1 -23.452 -3.306 36.358 1.00 0.00 H \\\\nHETATM 30 H8 UNL 1 -24.812 -4.953 28.715 1.00 0.00 H \\\\nHETATM 31 H9 UNL 1 -24.625 -3.417 29.628 1.00 0.00 H \\\\nHETATM 32 H10 UNL 1 -26.710 -7.941 31.731 1.00 0.00 H \\\\nHETATM 33 H11 UNL 1 -27.274 -6.560 33.696 1.00 0.00 H \\\\nHETATM 34 H12 UNL 1 -26.536 -4.235 33.803 1.00 0.00 H \\\\nHETATM 35 H13 UNL 1 -25.261 -3.280 31.956 1.00 0.00 H \\\\nENDMDL\\\\nMODEL\\\\nCOMPND 5zcu_ligand\\\\nHETATM 1 S1 UNL 1 -22.160 14.516 31.439 1.00 0.00 S \\\\nHETATM 2 BR1 UNL 1 -24.297 17.369 36.851 1.00 0.00 BR \\\\nHETATM 3 C1 UNL 1 -23.623 16.306 35.375 1.00 0.00 C \\\\nHETATM 4 N1 UNL 1 -23.209 13.253 30.959 1.00 0.00 N \\\\nHETATM 5 O1 UNL 1 -20.763 14.080 31.460 1.00 0.00 O \\\\nHETATM 6 C2 UNL 1 -23.216 14.960 35.422 1.00 0.00 C \\\\nHETATM 7 N2 UNL 1 -25.848 11.629 31.929 1.00 0.00 N \\\\nHETATM 8 O2 UNL 1 -22.121 15.605 30.460 1.00 0.00 O \\\\nHETATM 9 C3 UNL 1 -22.760 14.349 34.282 1.00 0.00 C \\\\nHETATM 10 C4 UNL 1 -22.703 15.064 33.078 1.00 0.00 C \\\\nHETATM 11 C5 UNL 1 -23.105 16.391 33.023 1.00 0.00 C \\\\nHETATM 12 C6 UNL 1 -23.566 17.014 34.179 1.00 0.00 C \\\\nHETATM 13 C7 UNL 1 -22.353 13.003 34.304 1.00 0.00 C \\\\nHETATM 14 C8 UNL 1 -22.407 12.284 35.487 1.00 0.00 C \\\\nHETATM 15 C9 UNL 1 -22.864 12.901 36.644 1.00 0.00 C \\\\nHETATM 16 C10 UNL 1 -23.270 14.230 36.623 1.00 0.00 C \\\\nHETATM 17 C11 UNL 1 -24.634 13.505 30.827 1.00 0.00 C \\\\nHETATM 18 C12 UNL 1 -25.434 12.913 31.987 1.00 0.00 C \\\\nHETATM 19 C13 UNL 1 -26.561 11.101 32.949 1.00 0.00 C \\\\nHETATM 20 C14 UNL 1 -26.877 11.875 34.052 1.00 0.00 C \\\\nHETATM 21 C15 UNL 1 -26.469 13.166 34.111 1.00 0.00 C \\\\nHETATM 22 C16 UNL 1 -25.756 13.694 33.087 1.00 0.00 C \\\\nHETATM 23 H1 UNL 1 -22.666 -5.667 29.597 1.00 0.00 H \\\\nHETATM 24 H2 UNL 1 -22.884 -1.071 30.916 1.00 0.00 H \\\\nHETATM 25 H3 UNL 1 -23.705 0.042 32.975 1.00 0.00 H \\\\nHETATM 26 H4 UNL 1 -21.822 -5.480 32.224 1.00 0.00 H \\\\nHETATM 27 H5 UNL 1 -21.919 -6.763 34.337 1.00 0.00 H \\\\nHETATM 28 H6 UNL 1 -22.728 -5.668 36.400 1.00 0.00 H \\\\nHETATM 29 H7 UNL 1 -23.452 -3.306 36.358 1.00 0.00 H \\\\nHETATM 30 H8 UNL 1 -24.812 -4.953 28.715 1.00 0.00 H \\\\nHETATM 31 H9 UNL 1 -24.625 -3.417 29.628 1.00 0.00 H \\\\nHETATM 32 H10 UNL 1 -26.710 -7.941 31.731 1.00 0.00 H \\\\nHETATM 33 H11 UNL 1 -27.274 -6.560 33.696 1.00 0.00 H \\\\nHETATM 34 H12 UNL 1 -26.536 -4.235 33.803 1.00 0.00 H \\\\nHETATM 35 H13 UNL 1 -25.261 -3.280 31.956 1.00 0.00 H \\\\nENDMDL\\\\nMODEL\\\\nCOMPND 5zcu_ligand\\\\nHETATM 1 S1 UNL 1 -20.266 9.953 28.976 1.00 0.00 S \\\\nHETATM 2 BR1 UNL 1 -21.002 14.346 33.684 1.00 0.00 BR \\\\nHETATM 3 C1 UNL 1 -20.935 13.181 32.134 1.00 0.00 C \\\\nHETATM 4 N1 UNL 1 -21.557 9.862 27.857 1.00 0.00 N \\\\nHETATM 5 O1 UNL 1 -20.090 8.695 29.702 1.00 0.00 O \\\\nHETATM 6 C2 UNL 1 -21.572 13.386 30.897 1.00 0.00 C \\\\nHETATM 7 N2 UNL 1 -24.565 11.391 27.264 1.00 0.00 N \\\\nHETATM 8 O2 UNL 1 -18.969 10.104 28.313 1.00 0.00 O \\\\nHETATM 9 C3 UNL 1 -21.424 12.460 29.896 1.00 0.00 C \\\\nHETATM 10 C4 UNL 1 -20.640 11.319 30.107 1.00 0.00 C \\\\nHETATM 11 C5 UNL 1 -20.005 11.111 31.324 1.00 0.00 C \\\\nHETATM 12 C6 UNL 1 -20.156 12.047 32.342 1.00 0.00 C \\\\nHETATM 13 C7 UNL 1 -22.048 12.647 28.649 1.00 0.00 C \\\\nHETATM 14 C8 UNL 1 -22.824 13.772 28.426 1.00 0.00 C \\\\nHETATM 15 C9 UNL 1 -22.980 14.709 29.439 1.00 0.00 C \\\\nHETATM 16 C10 UNL 1 -22.361 14.528 30.671 1.00 0.00 C \\\\nHETATM 17 C11 UNL 1 -22.930 9.845 28.334 1.00 0.00 C \\\\nHETATM 18 C12 UNL 1 -23.927 10.201 27.232 1.00 0.00 C \\\\nHETATM 19 C13 UNL 1 -25.453 11.710 26.296 1.00 0.00 C \\\\nHETATM 20 C14 UNL 1 -25.718 10.816 25.272 1.00 0.00 C \\\\nHETATM 21 C15 UNL 1 -25.084 9.619 25.240 1.00 0.00 C \\\\nHETATM 22 C16 UNL 1 -24.196 9.300 26.212 1.00 0.00 C \\\\nHETATM 23 H1 UNL 1 -22.666 -5.667 29.597 1.00 0.00 H \\\\nHETATM 24 H2 UNL 1 -22.884 -1.071 30.916 1.00 0.00 H \\\\nHETATM 25 H3 UNL 1 -23.705 0.042 32.975 1.00 0.00 H \\\\nHETATM 26 H4 UNL 1 -21.822 -5.480 32.224 1.00 0.00 H \\\\nHETATM 27 H5 UNL 1 -21.919 -6.763 34.337 1.00 0.00 H \\\\nHETATM 28 H6 UNL 1 -22.728 -5.668 36.400 1.00 0.00 H \\\\nHETATM 29 H7 UNL 1 -23.452 -3.306 36.358 1.00 0.00 H \\\\nHETATM 30 H8 UNL 1 -24.812 -4.953 28.715 1.00 0.00 H \\\\nHETATM 31 H9 UNL 1 -24.625 -3.417 29.628 1.00 0.00 H \\\\nHETATM 32 H10 UNL 1 -26.710 -7.941 31.731 1.00 0.00 H \\\\nHETATM 33 H11 UNL 1 -27.274 -6.560 33.696 1.00 0.00 H \\\\nHETATM 34 H12 UNL 1 -26.536 -4.235 33.803 1.00 0.00 H \\\\nHETATM 35 H13 UNL 1 -25.261 -3.280 31.956 1.00 0.00 H \\\\nENDMDL\\\\nMODEL\\\\nCOMPND 5zcu_ligand\\\\nHETATM 1 S1 UNL 1 -33.731 13.814 41.940 1.00 0.00 S \\\\nHETATM 2 BR1 UNL 1 -28.457 12.592 45.501 1.00 0.00 BR \\\\nHETATM 3 C1 UNL 1 -29.953 13.200 44.426 1.00 0.00 C \\\\nHETATM 4 N1 UNL 1 -34.459 15.331 42.253 1.00 0.00 N \\\\nHETATM 5 O1 UNL 1 -34.623 12.706 42.284 1.00 0.00 O \\\\nHETATM 6 C2 UNL 1 -30.175 14.506 43.952 1.00 0.00 C \\\\nHETATM 7 N2 UNL 1 -32.239 16.490 44.667 1.00 0.00 N \\\\nHETATM 8 O2 UNL 1 -33.511 13.591 40.509 1.00 0.00 O \\\\nHETATM 9 C3 UNL 1 -31.290 14.774 43.200 1.00 0.00 C \\\\nHETATM 10 C4 UNL 1 -32.200 13.750 42.906 1.00 0.00 C \\\\nHETATM 11 C5 UNL 1 -31.987 12.459 43.367 1.00 0.00 C \\\\nHETATM 12 C6 UNL 1 -30.857 12.185 44.133 1.00 0.00 C \\\\nHETATM 13 C7 UNL 1 -31.530 16.071 42.711 1.00 0.00 C \\\\nHETATM 14 C8 UNL 1 -30.636 17.092 42.992 1.00 0.00 C \\\\nHETATM 15 C9 UNL 1 -29.509 16.825 43.757 1.00 0.00 C \\\\nHETATM 16 C10 UNL 1 -29.268 15.543 44.238 1.00 0.00 C \\\\nHETATM 17 C11 UNL 1 -34.406 15.898 43.590 1.00 0.00 C \\\\nHETATM 18 C12 UNL 1 -33.201 16.819 43.778 1.00 0.00 C \\\\nHETATM 19 C13 UNL 1 -31.174 17.303 44.843 1.00 0.00 C \\\\nHETATM 20 C14 UNL 1 -31.068 18.479 44.120 1.00 0.00 C \\\\nHETATM 21 C15 UNL 1 -32.035 18.816 43.232 1.00 0.00 C \\\\nHETATM 22 C16 UNL 1 -33.103 18.000 43.059 1.00 0.00 C \\\\nHETATM 23 H1 UNL 1 -22.666 -5.667 29.597 1.00 0.00 H \\\\nHETATM 24 H2 UNL 1 -22.884 -1.071 30.916 1.00 0.00 H \\\\nHETATM 25 H3 UNL 1 -23.705 0.042 32.975 1.00 0.00 H \\\\nHETATM 26 H4 UNL 1 -21.822 -5.480 32.224 1.00 0.00 H \\\\nHETATM 27 H5 UNL 1 -21.919 -6.763 34.337 1.00 0.00 H \\\\nHETATM 28 H6 UNL 1 -22.728 -5.668 36.400 1.00 0.00 H \\\\nHETATM 29 H7 UNL 1 -23.452 -3.306 36.358 1.00 0.00 H \\\\nHETATM 30 H8 UNL 1 -24.812 -4.953 28.715 1.00 0.00 H \\\\nHETATM 31 H9 UNL 1 -24.625 -3.417 29.628 1.00 0.00 H \\\\nHETATM 32 H10 UNL 1 -26.710 -7.941 31.731 1.00 0.00 H \\\\nHETATM 33 H11 UNL 1 -27.274 -6.560 33.696 1.00 0.00 H \\\\nHETATM 34 H12 UNL 1 -26.536 -4.235 33.803 1.00 0.00 H \\\\nHETATM 35 H13 UNL 1 -25.261 -3.280 31.956 1.00 0.00 H \\\\nENDMDL\\\\nMODEL\\\\nCOMPND 5zcu_ligand\\\\nHETATM 1 S1 UNL 1 -34.301 0.020 26.843 1.00 0.00 S \\\\nHETATM 2 BR1 UNL 1 -31.959 3.515 31.772 1.00 0.00 BR \\\\nHETATM 3 C1 UNL 1 -32.767 2.319 30.476 1.00 0.00 C \\\\nHETATM 4 N1 UNL 1 -35.819 0.689 26.428 1.00 0.00 N \\\\nHETATM 5 O1 UNL 1 -34.372 -1.435 26.985 1.00 0.00 O \\\\nHETATM 6 C2 UNL 1 -33.566 1.194 30.749 1.00 0.00 C \\\\nHETATM 7 N2 UNL 1 -38.606 -1.741 26.043 1.00 0.00 N \\\\nHETATM 8 O2 UNL 1 -33.317 0.169 25.768 1.00 0.00 O \\\\nHETATM 9 C3 UNL 1 -34.064 0.447 29.712 1.00 0.00 C \\\\nHETATM 10 C4 UNL 1 -33.777 0.807 28.388 1.00 0.00 C \\\\nHETATM 11 C5 UNL 1 -32.991 1.916 28.110 1.00 0.00 C \\\\nHETATM 12 C6 UNL 1 -32.483 2.675 29.161 1.00 0.00 C \\\\nHETATM 13 C7 UNL 1 -34.869 -0.678 29.962 1.00 0.00 C \\\\nHETATM 14 C8 UNL 1 -35.163 -1.043 31.266 1.00 0.00 C \\\\nHETATM 15 C9 UNL 1 -34.657 -0.291 32.318 1.00 0.00 C \\\\nHETATM 16 C10 UNL 1 -33.863 0.823 32.073 1.00 0.00 C \\\\nHETATM 17 C11 UNL 1 -36.774 -0.096 25.665 1.00 0.00 C \\\\nHETATM 18 C12 UNL 1 -37.530 -1.095 26.540 1.00 0.00 C \\\\nHETATM 19 C13 UNL 1 -39.283 -2.622 26.815 1.00 0.00 C \\\\nHETATM 20 C14 UNL 1 -38.882 -2.858 28.118 1.00 0.00 C \\\\nHETATM 21 C15 UNL 1 -37.806 -2.206 28.623 1.00 0.00 C \\\\nHETATM 22 C16 UNL 1 -37.130 -1.323 27.849 1.00 0.00 C \\\\nHETATM 23 H1 UNL 1 -22.666 -5.667 29.597 1.00 0.00 H \\\\nHETATM 24 H2 UNL 1 -22.884 -1.071 30.916 1.00 0.00 H \\\\nHETATM 25 H3 UNL 1 -23.705 0.042 32.975 1.00 0.00 H \\\\nHETATM 26 H4 UNL 1 -21.822 -5.480 32.224 1.00 0.00 H \\\\nHETATM 27 H5 UNL 1 -21.919 -6.763 34.337 1.00 0.00 H \\\\nHETATM 28 H6 UNL 1 -22.728 -5.668 36.400 1.00 0.00 H \\\\nHETATM 29 H7 UNL 1 -23.452 -3.306 36.358 1.00 0.00 H \\\\nHETATM 30 H8 UNL 1 -24.812 -4.953 28.715 1.00 0.00 H \\\\nHETATM 31 H9 UNL 1 -24.625 -3.417 29.628 1.00 0.00 H \\\\nHETATM 32 H10 UNL 1 -26.710 -7.941 31.731 1.00 0.00 H \\\\nHETATM 33 H11 UNL 1 -27.274 -6.560 33.696 1.00 0.00 H \\\\nHETATM 34 H12 UNL 1 -26.536 -4.235 33.803 1.00 0.00 H \\\\nHETATM 35 H13 UNL 1 -25.261 -3.280 31.956 1.00 0.00 H \\\\nENDMDL\\\\nMODEL\\\\nCOMPND 5zcu_ligand\\\\nHETATM 1 S1 UNL 1 -27.114 3.575 29.793 1.00 0.00 S \\\\nHETATM 2 BR1 UNL 1 -31.304 6.634 33.677 1.00 0.00 BR \\\\nHETATM 3 C1 UNL 1 -30.064 5.524 32.681 1.00 0.00 C \\\\nHETATM 4 N1 UNL 1 -26.884 4.830 28.654 1.00 0.00 N \\\\nHETATM 5 O1 UNL 1 -27.618 2.356 29.160 1.00 0.00 O \\\\nHETATM 6 C2 UNL 1 -29.644 4.222 33.011 1.00 0.00 C \\\\nHETATM 7 N2 UNL 1 -27.292 5.258 24.977 1.00 0.00 N \\\\nHETATM 8 O2 UNL 1 -25.850 3.114 30.372 1.00 0.00 O \\\\nHETATM 9 C3 UNL 1 -28.756 3.569 32.196 1.00 0.00 C \\\\nHETATM 10 C4 UNL 1 -28.272 4.196 31.040 1.00 0.00 C \\\\nHETATM 11 C5 UNL 1 -28.684 5.478 30.706 1.00 0.00 C \\\\nHETATM 12 C6 UNL 1 -29.584 6.145 31.532 1.00 0.00 C \\\\nHETATM 13 C7 UNL 1 -28.326 2.265 32.504 1.00 0.00 C \\\\nHETATM 14 C8 UNL 1 -28.799 1.633 33.643 1.00 0.00 C \\\\nHETATM 15 C9 UNL 1 -29.695 2.294 34.472 1.00 0.00 C \\\\nHETATM 16 C10 UNL 1 -30.123 3.580 34.167 1.00 0.00 C \\\\nHETATM 17 C11 UNL 1 -26.635 4.506 27.259 1.00 0.00 C \\\\nHETATM 18 C12 UNL 1 -27.479 5.356 26.310 1.00 0.00 C \\\\nHETATM 19 C13 UNL 1 -28.032 6.012 24.132 1.00 0.00 C \\\\nHETATM 20 C14 UNL 1 -28.976 6.892 24.630 1.00 0.00 C \\\\nHETATM 21 C15 UNL 1 -29.162 6.998 25.968 1.00 0.00 C \\\\nHETATM 22 C16 UNL 1 -28.419 6.244 26.813 1.00 0.00 C \\\\nHETATM 23 H1 UNL 1 -22.666 -5.667 29.597 1.00 0.00 H \\\\nHETATM 24 H2 UNL 1 -22.884 -1.071 30.916 1.00 0.00 H \\\\nHETATM 25 H3 UNL 1 -23.705 0.042 32.975 1.00 0.00 H \\\\nHETATM 26 H4 UNL 1 -21.822 -5.480 32.224 1.00 0.00 H \\\\nHETATM 27 H5 UNL 1 -21.919 -6.763 34.337 1.00 0.00 H \\\\nHETATM 28 H6 UNL 1 -22.728 -5.668 36.400 1.00 0.00 H \\\\nHETATM 29 H7 UNL 1 -23.452 -3.306 36.358 1.00 0.00 H \\\\nHETATM 30 H8 UNL 1 -24.812 -4.953 28.715 1.00 0.00 H \\\\nHETATM 31 H9 UNL 1 -24.625 -3.417 29.628 1.00 0.00 H \\\\nHETATM 32 H10 UNL 1 -26.710 -7.941 31.731 1.00 0.00 H \\\\nHETATM 33 H11 UNL 1 -27.274 -6.560 33.696 1.00 0.00 H \\\\nHETATM 34 H12 UNL 1 -26.536 -4.235 33.803 1.00 0.00 H \\\\nHETATM 35 H13 UNL 1 -25.261 -3.280 31.956 1.00 0.00 H \\\\nENDMDL\\\\nMODEL\\\\nCOMPND 5zcu_ligand\\\\nHETATM 1 S1 UNL 1 -29.968 4.743 29.457 1.00 0.00 S \\\\nHETATM 2 BR1 UNL 1 -30.818 9.396 33.887 1.00 0.00 BR \\\\nHETATM 3 C1 UNL 1 -30.315 8.012 32.624 1.00 0.00 C \\\\nHETATM 4 N1 UNL 1 -30.417 5.508 27.994 1.00 0.00 N \\\\nHETATM 5 O1 UNL 1 -30.897 3.670 29.813 1.00 0.00 O \\\\nHETATM 6 C2 UNL 1 -29.025 7.495 32.410 1.00 0.00 C \\\\nHETATM 7 N2 UNL 1 -33.999 5.906 27.289 1.00 0.00 N \\\\nHETATM 8 O2 UNL 1 -28.701 4.018 29.336 1.00 0.00 O \\\\nHETATM 9 C3 UNL 1 -28.835 6.512 31.472 1.00 0.00 C \\\\nHETATM 10 C4 UNL 1 -29.924 6.026 30.735 1.00 0.00 C \\\\nHETATM 11 C5 UNL 1 -31.200 6.530 30.943 1.00 0.00 C \\\\nHETATM 12 C6 UNL 1 -31.395 7.529 31.892 1.00 0.00 C \\\\nHETATM 13 C7 UNL 1 -27.555 5.975 31.244 1.00 0.00 C \\\\nHETATM 14 C8 UNL 1 -26.471 6.444 31.968 1.00 0.00 C \\\\nHETATM 15 C9 UNL 1 -26.659 7.443 32.915 1.00 0.00 C \\\\nHETATM 16 C10 UNL 1 -27.924 7.971 33.144 1.00 0.00 C \\\\nHETATM 17 C11 UNL 1 -31.638 5.111 27.314 1.00 0.00 C \\\\nHETATM 18 C12 UNL 1 -32.687 6.223 27.318 1.00 0.00 C \\\\nHETATM 19 C13 UNL 1 -34.932 6.885 27.287 1.00 0.00 C \\\\nHETATM 20 C14 UNL 1 -34.547 8.214 27.306 1.00 0.00 C \\\\nHETATM 21 C15 UNL 1 -33.231 8.536 27.329 1.00 0.00 C \\\\nHETATM 22 C16 UNL 1 -32.297 7.554 27.329 1.00 0.00 C \\\\nHETATM 23 H1 UNL 1 -22.666 -5.667 29.597 1.00 0.00 H \\\\nHETATM 24 H2 UNL 1 -22.884 -1.071 30.916 1.00 0.00 H \\\\nHETATM 25 H3 UNL 1 -23.705 0.042 32.975 1.00 0.00 H \\\\nHETATM 26 H4 UNL 1 -21.822 -5.480 32.224 1.00 0.00 H \\\\nHETATM 27 H5 UNL 1 -21.919 -6.763 34.337 1.00 0.00 H \\\\nHETATM 28 H6 UNL 1 -22.728 -5.668 36.400 1.00 0.00 H \\\\nHETATM 29 H7 UNL 1 -23.452 -3.306 36.358 1.00 0.00 H \\\\nHETATM 30 H8 UNL 1 -24.812 -4.953 28.715 1.00 0.00 H \\\\nHETATM 31 H9 UNL 1 -24.625 -3.417 29.628 1.00 0.00 H \\\\nHETATM 32 H10 UNL 1 -26.710 -7.941 31.731 1.00 0.00 H \\\\nHETATM 33 H11 UNL 1 -27.274 -6.560 33.696 1.00 0.00 H \\\\nHETATM 34 H12 UNL 1 -26.536 -4.235 33.803 1.00 0.00 H \\\\nHETATM 35 H13 UNL 1 -25.261 -3.280 31.956 1.00 0.00 H \\\\nENDMDL\\\\nMODEL\\\\nCOMPND 5zcu_ligand\\\\nHETATM 1 S1 UNL 1 -23.151 1.637 36.038 1.00 0.00 S \\\\nHETATM 2 BR1 UNL 1 -22.204 5.948 40.783 1.00 0.00 BR \\\\nHETATM 3 C1 UNL 1 -22.355 4.818 39.214 1.00 0.00 C \\\\nHETATM 4 N1 UNL 1 -22.996 2.246 34.447 1.00 0.00 N \\\\nHETATM 5 O1 UNL 1 -24.496 1.118 36.290 1.00 0.00 O \\\\nHETATM 6 C2 UNL 1 -21.820 5.072 37.937 1.00 0.00 C \\\\nHETATM 7 N2 UNL 1 -25.693 3.063 32.293 1.00 0.00 N \\\\nHETATM 8 O2 UNL 1 -22.323 0.449 36.259 1.00 0.00 O \\\\nHETATM 9 C3 UNL 1 -22.018 4.166 36.927 1.00 0.00 C \\\\nHETATM 10 C4 UNL 1 -22.747 2.994 37.168 1.00 0.00 C \\\\nHETATM 11 C5 UNL 1 -23.276 2.736 38.424 1.00 0.00 C \\\\nHETATM 12 C6 UNL 1 -23.079 3.654 39.451 1.00 0.00 C \\\\nHETATM 13 C7 UNL 1 -21.488 4.396 35.644 1.00 0.00 C \\\\nHETATM 14 C8 UNL 1 -20.762 5.550 35.393 1.00 0.00 C \\\\nHETATM 15 C9 UNL 1 -20.564 6.471 36.413 1.00 0.00 C \\\\nHETATM 16 C10 UNL 1 -21.084 6.243 37.682 1.00 0.00 C \\\\nHETATM 17 C11 UNL 1 -23.877 1.763 33.397 1.00 0.00 C \\\\nHETATM 18 C12 UNL 1 -24.368 2.892 32.492 1.00 0.00 C \\\\nHETATM 19 C13 UNL 1 -26.134 4.056 31.489 1.00 0.00 C \\\\nHETATM 20 C14 UNL 1 -25.232 4.895 30.860 1.00 0.00 C \\\\nHETATM 21 C15 UNL 1 -23.901 4.723 31.051 1.00 0.00 C \\\\nHETATM 22 C16 UNL 1 -23.461 3.726 31.856 1.00 0.00 C \\\\nHETATM 23 H1 UNL 1 -22.666 -5.667 29.597 1.00 0.00 H \\\\nHETATM 24 H2 UNL 1 -22.884 -1.071 30.916 1.00 0.00 H \\\\nHETATM 25 H3 UNL 1 -23.705 0.042 32.975 1.00 0.00 H \\\\nHETATM 26 H4 UNL 1 -21.822 -5.480 32.224 1.00 0.00 H \\\\nHETATM 27 H5 UNL 1 -21.919 -6.763 34.337 1.00 0.00 H \\\\nHETATM 28 H6 UNL 1 -22.728 -5.668 36.400 1.00 0.00 H \\\\nHETATM 29 H7 UNL 1 -23.452 -3.306 36.358 1.00 0.00 H \\\\nHETATM 30 H8 UNL 1 -24.812 -4.953 28.715 1.00 0.00 H \\\\nHETATM 31 H9 UNL 1 -24.625 -3.417 29.628 1.00 0.00 H \\\\nHETATM 32 H10 UNL 1 -26.710 -7.941 31.731 1.00 0.00 H \\\\nHETATM 33 H11 UNL 1 -27.274 -6.560 33.696 1.00 0.00 H \\\\nHETATM 34 H12 UNL 1 -26.536 -4.235 33.803 1.00 0.00 H \\\\nHETATM 35 H13 UNL 1 -25.261 -3.280 31.956 1.00 0.00 H \\\\nENDMDL\\\\nMODEL\\\\nCOMPND 5zcu_ligand\\\\nHETATM 1 S1 UNL 1 -21.833 -3.376 35.200 1.00 0.00 S \\\\nHETATM 2 BR1 UNL 1 -23.121 1.330 39.465 1.00 0.00 BR \\\\nHETATM 3 C1 UNL 1 -22.662 0.108 38.030 1.00 0.00 C \\\\nHETATM 4 N1 UNL 1 -22.255 -2.995 33.587 1.00 0.00 N \\\\nHETATM 5 O1 UNL 1 -22.615 -4.502 35.712 1.00 0.00 O \\\\nHETATM 6 C2 UNL 1 -22.145 0.449 36.766 1.00 0.00 C \\\\nHETATM 7 N2 UNL 1 -25.647 -3.720 33.711 1.00 0.00 N \\\\nHETATM 8 O2 UNL 1 -20.464 -3.886 35.307 1.00 0.00 O \\\\nHETATM 9 C3 UNL 1 -21.872 -0.541 35.856 1.00 0.00 C \\\\nHETATM 10 C4 UNL 1 -22.106 -1.882 36.188 1.00 0.00 C \\\\nHETATM 11 C5 UNL 1 -22.613 -2.226 37.433 1.00 0.00 C \\\\nHETATM 12 C6 UNL 1 -22.893 -1.224 38.357 1.00 0.00 C \\\\nHETATM 13 C7 UNL 1 -21.350 -0.225 34.589 1.00 0.00 C \\\\nHETATM 14 C8 UNL 1 -21.112 1.097 34.250 1.00 0.00 C \\\\nHETATM 15 C9 UNL 1 -21.391 2.101 35.167 1.00 0.00 C \\\\nHETATM 16 C10 UNL 1 -21.904 1.790 36.421 1.00 0.00 C \\\\nHETATM 17 C11 UNL 1 -23.289 -3.759 32.908 1.00 0.00 C \\\\nHETATM 18 C12 UNL 1 -24.663 -3.100 33.025 1.00 0.00 C \\\\nHETATM 19 C13 UNL 1 -26.867 -3.146 33.813 1.00 0.00 C \\\\nHETATM 20 C14 UNL 1 -27.115 -1.926 33.209 1.00 0.00 C \\\\nHETATM 21 C15 UNL 1 -26.132 -1.303 32.514 1.00 0.00 C \\\\nHETATM 22 C16 UNL 1 -24.910 -1.881 32.411 1.00 0.00 C \\\\nHETATM 23 H1 UNL 1 -22.666 -5.667 29.597 1.00 0.00 H \\\\nHETATM 24 H2 UNL 1 -22.884 -1.071 30.916 1.00 0.00 H \\\\nHETATM 25 H3 UNL 1 -23.705 0.042 32.975 1.00 0.00 H \\\\nHETATM 26 H4 UNL 1 -21.822 -5.480 32.224 1.00 0.00 H \\\\nHETATM 27 H5 UNL 1 -21.919 -6.763 34.337 1.00 0.00 H \\\\nHETATM 28 H6 UNL 1 -22.728 -5.668 36.400 1.00 0.00 H \\\\nHETATM 29 H7 UNL 1 -23.452 -3.306 36.358 1.00 0.00 H \\\\nHETATM 30 H8 UNL 1 -24.812 -4.953 28.715 1.00 0.00 H \\\\nHETATM 31 H9 UNL 1 -24.625 -3.417 29.628 1.00 0.00 H \\\\nHETATM 32 H10 UNL 1 -26.710 -7.941 31.731 1.00 0.00 H \\\\nHETATM 33 H11 UNL 1 -27.274 -6.560 33.696 1.00 0.00 H \\\\nHETATM 34 H12 UNL 1 -26.536 -4.235 33.803 1.00 0.00 H \\\\nHETATM 35 H13 UNL 1 -25.261 -3.280 31.956 1.00 0.00 H \\\\nENDMDL\\\\nMODEL\\\\nCOMPND 5zcu_ligand\\\\nHETATM 1 S1 UNL 1 -21.058 -3.811 34.815 1.00 0.00 S \\\\nHETATM 2 BR1 UNL 1 -21.316 0.596 39.559 1.00 0.00 BR \\\\nHETATM 3 C1 UNL 1 -21.062 -0.572 38.031 1.00 0.00 C \\\\nHETATM 4 N1 UNL 1 -21.802 -3.198 33.402 1.00 0.00 N \\\\nHETATM 5 O1 UNL 1 -21.813 -4.929 35.382 1.00 0.00 O \\\\nHETATM 6 C2 UNL 1 -20.175 -0.375 36.957 1.00 0.00 C \\\\nHETATM 7 N2 UNL 1 -24.635 -4.687 34.196 1.00 0.00 N \\\\nHETATM 8 O2 UNL 1 -19.763 -4.435 34.532 1.00 0.00 O \\\\nHETATM 9 C3 UNL 1 -20.116 -1.301 35.948 1.00 0.00 C \\\\nHETATM 10 C4 UNL 1 -20.934 -2.438 35.990 1.00 0.00 C \\\\nHETATM 11 C5 UNL 1 -21.810 -2.641 37.047 1.00 0.00 C \\\\nHETATM 12 C6 UNL 1 -21.874 -1.701 38.072 1.00 0.00 C \\\\nHETATM 13 C7 UNL 1 -19.233 -1.128 34.867 1.00 0.00 C \\\\nHETATM 14 C8 UNL 1 -18.416 -0.010 34.814 1.00 0.00 C \\\\nHETATM 15 C9 UNL 1 -18.477 0.932 35.833 1.00 0.00 C \\\\nHETATM 16 C10 UNL 1 -19.346 0.760 36.903 1.00 0.00 C \\\\nHETATM 17 C11 UNL 1 -22.774 -4.005 32.686 1.00 0.00 C \\\\nHETATM 18 C12 UNL 1 -24.187 -3.839 33.245 1.00 0.00 C \\\\nHETATM 19 C13 UNL 1 -25.886 -4.548 34.691 1.00 0.00 C \\\\nHETATM 20 C14 UNL 1 -26.714 -3.544 34.221 1.00 0.00 C \\\\nHETATM 21 C15 UNL 1 -26.269 -2.695 33.263 1.00 0.00 C \\\\nHETATM 22 C16 UNL 1 -25.017 -2.836 32.766 1.00 0.00 C \\\\nHETATM 23 H1 UNL 1 -22.666 -5.667 29.597 1.00 0.00 H \\\\nHETATM 24 H2 UNL 1 -22.884 -1.071 30.916 1.00 0.00 H \\\\nHETATM 25 H3 UNL 1 -23.705 0.042 32.975 1.00 0.00 H \\\\nHETATM 26 H4 UNL 1 -21.822 -5.480 32.224 1.00 0.00 H \\\\nHETATM 27 H5 UNL 1 -21.919 -6.763 34.337 1.00 0.00 H \\\\nHETATM 28 H6 UNL 1 -22.728 -5.668 36.400 1.00 0.00 H \\\\nHETATM 29 H7 UNL 1 -23.452 -3.306 36.358 1.00 0.00 H \\\\nHETATM 30 H8 UNL 1 -24.812 -4.953 28.715 1.00 0.00 H \\\\nHETATM 31 H9 UNL 1 -24.625 -3.417 29.628 1.00 0.00 H \\\\nHETATM 32 H10 UNL 1 -26.710 -7.941 31.731 1.00 0.00 H \\\\nHETATM 33 H11 UNL 1 -27.274 -6.560 33.696 1.00 0.00 H \\\\nHETATM 34 H12 UNL 1 -26.536 -4.235 33.803 1.00 0.00 H \\\\nHETATM 35 H13 UNL 1 -25.261 -3.280 31.956 1.00 0.00 H \\\\nENDMDL\\\\nMODEL\\\\nCOMPND 5zcu_ligand\\\\nHETATM 1 S1 UNL 1 -21.073 -5.562 31.839 1.00 0.00 S \\\\nHETATM 2 BR1 UNL 1 -24.875 -1.008 34.446 1.00 0.00 BR \\\\nHETATM 3 C1 UNL 1 -23.595 -2.178 33.578 1.00 0.00 C \\\\nHETATM 4 N1 UNL 1 -21.890 -6.090 30.432 1.00 0.00 N \\\\nHETATM 5 O1 UNL 1 -21.014 -6.613 32.857 1.00 0.00 O \\\\nHETATM 6 C2 UNL 1 -22.453 -1.788 32.853 1.00 0.00 C \\\\nHETATM 7 N2 UNL 1 -24.617 -6.380 32.415 1.00 0.00 N \\\\nHETATM 8 O2 UNL 1 -19.652 -5.304 31.590 1.00 0.00 O \\\\nHETATM 9 C3 UNL 1 -21.644 -2.745 32.296 1.00 0.00 C \\\\nHETATM 10 C4 UNL 1 -21.955 -4.103 32.451 1.00 0.00 C \\\\nHETATM 11 C5 UNL 1 -23.078 -4.495 33.166 1.00 0.00 C \\\\nHETATM 12 C6 UNL 1 -23.901 -3.526 33.730 1.00 0.00 C \\\\nHETATM 13 C7 UNL 1 -20.495 -2.380 31.573 1.00 0.00 C \\\\nHETATM 14 C8 UNL 1 -20.174 -1.041 31.415 1.00 0.00 C \\\\nHETATM 15 C9 UNL 1 -20.994 -0.069 31.974 1.00 0.00 C \\\\nHETATM 16 C10 UNL 1 -22.128 -0.429 32.692 1.00 0.00 C \\\\nHETATM 17 C11 UNL 1 -23.061 -6.942 30.551 1.00 0.00 C \\\\nHETATM 18 C12 UNL 1 -24.263 -6.192 31.125 1.00 0.00 C \\\\nHETATM 19 C13 UNL 1 -25.682 -5.725 32.927 1.00 0.00 C \\\\nHETATM 20 C14 UNL 1 -26.420 -4.866 32.131 1.00 0.00 C \\\\nHETATM 21 C15 UNL 1 -26.073 -4.680 30.835 1.00 0.00 C \\\\nHETATM 22 C16 UNL 1 -25.006 -5.339 30.323 1.00 0.00 C \\\\nHETATM 23 H1 UNL 1 -22.666 -5.667 29.597 1.00 0.00 H \\\\nHETATM 24 H2 UNL 1 -22.884 -1.071 30.916 1.00 0.00 H \\\\nHETATM 25 H3 UNL 1 -23.705 0.042 32.975 1.00 0.00 H \\\\nHETATM 26 H4 UNL 1 -21.822 -5.480 32.224 1.00 0.00 H \\\\nHETATM 27 H5 UNL 1 -21.919 -6.763 34.337 1.00 0.00 H \\\\nHETATM 28 H6 UNL 1 -22.728 -5.668 36.400 1.00 0.00 H \\\\nHETATM 29 H7 UNL 1 -23.452 -3.306 36.358 1.00 0.00 H \\\\nHETATM 30 H8 UNL 1 -24.812 -4.953 28.715 1.00 0.00 H \\\\nHETATM 31 H9 UNL 1 -24.625 -3.417 29.628 1.00 0.00 H \\\\nHETATM 32 H10 UNL 1 -26.710 -7.941 31.731 1.00 0.00 H \\\\nHETATM 33 H11 UNL 1 -27.274 -6.560 33.696 1.00 0.00 H \\\\nHETATM 34 H12 UNL 1 -26.536 -4.235 33.803 1.00 0.00 H \\\\nHETATM 35 H13 UNL 1 -25.261 -3.280 31.956 1.00 0.00 H \\\\nENDMDL\\\\nMODEL\\\\nCOMPND 5zcu_ligand\\\\nHETATM 1 S1 UNL 1 -21.539 -6.906 32.685 1.00 0.00 S \\\\nHETATM 2 BR1 UNL 1 -23.763 -2.134 36.464 1.00 0.00 BR \\\\nHETATM 3 C1 UNL 1 -22.913 -3.398 35.263 1.00 0.00 C \\\\nHETATM 4 N1 UNL 1 -22.785 -7.119 31.533 1.00 0.00 N \\\\nHETATM 5 O1 UNL 1 -21.402 -8.074 33.556 1.00 0.00 O \\\\nHETATM 6 C2 UNL 1 -21.759 -3.181 34.488 1.00 0.00 C \\\\nHETATM 7 N2 UNL 1 -24.431 -7.740 34.360 1.00 0.00 N \\\\nHETATM 8 O2 UNL 1 -20.215 -6.838 32.062 1.00 0.00 O \\\\nHETATM 9 C3 UNL 1 -21.283 -4.184 33.683 1.00 0.00 C \\\\nHETATM 10 C4 UNL 1 -21.944 -5.419 33.637 1.00 0.00 C \\\\nHETATM 11 C5 UNL 1 -23.081 -5.643 34.401 1.00 0.00 C \\\\nHETATM 12 C6 UNL 1 -23.567 -4.625 35.216 1.00 0.00 C \\\\nHETATM 13 C7 UNL 1 -20.128 -3.991 32.904 1.00 0.00 C \\\\nHETATM 14 C8 UNL 1 -19.464 -2.776 32.942 1.00 0.00 C \\\\nHETATM 15 C9 UNL 1 -19.946 -1.756 33.752 1.00 0.00 C \\\\nHETATM 16 C10 UNL 1 -21.085 -1.947 34.526 1.00 0.00 C \\\\nHETATM 17 C11 UNL 1 -24.007 -7.811 31.906 1.00 0.00 C \\\\nHETATM 18 C12 UNL 1 -24.661 -7.199 33.145 1.00 0.00 C \\\\nHETATM 19 C13 UNL 1 -25.010 -7.208 35.459 1.00 0.00 C \\\\nHETATM 20 C14 UNL 1 -25.848 -6.112 35.343 1.00 0.00 C \\\\nHETATM 21 C15 UNL 1 -26.087 -5.570 34.124 1.00 0.00 C \\\\nHETATM 22 C16 UNL 1 -25.506 -6.107 33.023 1.00 0.00 C \\\\nHETATM 23 H1 UNL 1 -22.666 -5.667 29.597 1.00 0.00 H \\\\nHETATM 24 H2 UNL 1 -22.884 -1.071 30.916 1.00 0.00 H \\\\nHETATM 25 H3 UNL 1 -23.705 0.042 32.975 1.00 0.00 H \\\\nHETATM 26 H4 UNL 1 -21.822 -5.480 32.224 1.00 0.00 H \\\\nHETATM 27 H5 UNL 1 -21.919 -6.763 34.337 1.00 0.00 H \\\\nHETATM 28 H6 UNL 1 -22.728 -5.668 36.400 1.00 0.00 H \\\\nHETATM 29 H7 UNL 1 -23.452 -3.306 36.358 1.00 0.00 H \\\\nHETATM 30 H8 UNL 1 -24.812 -4.953 28.715 1.00 0.00 H \\\\nHETATM 31 H9 UNL 1 -24.625 -3.417 29.628 1.00 0.00 H \\\\nHETATM 32 H10 UNL 1 -26.710 -7.941 31.731 1.00 0.00 H \\\\nHETATM 33 H11 UNL 1 -27.274 -6.560 33.696 1.00 0.00 H \\\\nHETATM 34 H12 UNL 1 -26.536 -4.235 33.803 1.00 0.00 H \\\\nHETATM 35 H13 UNL 1 -25.261 -3.280 31.956 1.00 0.00 H \\\\nENDMDL\\\\nMODEL\\\\nCOMPND 5zcu_ligand\\\\nHETATM 1 S1 UNL 1 -20.620 -6.031 32.523 1.00 0.00 S \\\\nHETATM 2 BR1 UNL 1 -23.859 -1.545 35.898 1.00 0.00 BR \\\\nHETATM 3 C1 UNL 1 -22.721 -2.702 34.835 1.00 0.00 C \\\\nHETATM 4 N1 UNL 1 -21.506 -6.226 31.073 1.00 0.00 N \\\\nHETATM 5 O1 UNL 1 -20.676 -7.232 33.357 1.00 0.00 O \\\\nHETATM 6 C2 UNL 1 -21.522 -2.346 34.192 1.00 0.00 C \\\\nHETATM 7 N2 UNL 1 -23.766 -7.336 33.356 1.00 0.00 N \\\\nHETATM 8 O2 UNL 1 -19.182 -5.900 32.279 1.00 0.00 O \\\\nHETATM 9 C3 UNL 1 -20.831 -3.288 33.474 1.00 0.00 C \\\\nHETATM 10 C4 UNL 1 -21.319 -4.598 33.384 1.00 0.00 C \\\\nHETATM 11 C5 UNL 1 -22.500 -4.959 34.018 1.00 0.00 C \\\\nHETATM 12 C6 UNL 1 -23.204 -4.004 34.745 1.00 0.00 C \\\\nHETATM 13 C7 UNL 1 -19.627 -2.956 32.827 1.00 0.00 C \\\\nHETATM 14 C8 UNL 1 -19.132 -1.664 32.910 1.00 0.00 C \\\\nHETATM 15 C9 UNL 1 -19.831 -0.707 33.633 1.00 0.00 C \\\\nHETATM 16 C10 UNL 1 -21.019 -1.035 34.275 1.00 0.00 C \\\\nHETATM 17 C11 UNL 1 -22.816 -6.854 31.103 1.00 0.00 C \\\\nHETATM 18 C12 UNL 1 -23.618 -6.456 32.342 1.00 0.00 C \\\\nHETATM 19 C13 UNL 1 -24.478 -6.993 34.452 1.00 0.00 C \\\\nHETATM 20 C14 UNL 1 -25.066 -5.743 34.537 1.00 0.00 C \\\\nHETATM 21 C15 UNL 1 -24.925 -4.859 33.520 1.00 0.00 C \\\\nHETATM 22 C16 UNL 1 -24.212 -5.205 32.421 1.00 0.00 C \\\\nHETATM 23 H1 UNL 1 -22.666 -5.667 29.597 1.00 0.00 H \\\\nHETATM 24 H2 UNL 1 -22.884 -1.071 30.916 1.00 0.00 H \\\\nHETATM 25 H3 UNL 1 -23.705 0.042 32.975 1.00 0.00 H \\\\nHETATM 26 H4 UNL 1 -21.822 -5.480 32.224 1.00 0.00 H \\\\nHETATM 27 H5 UNL 1 -21.919 -6.763 34.337 1.00 0.00 H \\\\nHETATM 28 H6 UNL 1 -22.728 -5.668 36.400 1.00 0.00 H \\\\nHETATM 29 H7 UNL 1 -23.452 -3.306 36.358 1.00 0.00 H \\\\nHETATM 30 H8 UNL 1 -24.812 -4.953 28.715 1.00 0.00 H \\\\nHETATM 31 H9 UNL 1 -24.625 -3.417 29.628 1.00 0.00 H \\\\nHETATM 32 H10 UNL 1 -26.710 -7.941 31.731 1.00 0.00 H \\\\nHETATM 33 H11 UNL 1 -27.274 -6.560 33.696 1.00 0.00 H \\\\nHETATM 34 H12 UNL 1 -26.536 -4.235 33.803 1.00 0.00 H \\\\nHETATM 35 H13 UNL 1 -25.261 -3.280 31.956 1.00 0.00 H \\\\nENDMDL\\\\nMODEL\\\\nCOMPND 5zcu_ligand\\\\nHETATM 1 S1 UNL 1 -20.907 -5.442 32.235 1.00 0.00 S \\\\nHETATM 2 BR1 UNL 1 -23.539 -2.774 37.522 1.00 0.00 BR \\\\nHETATM 3 C1 UNL 1 -22.623 -3.353 35.913 1.00 0.00 C \\\\nHETATM 4 N1 UNL 1 -22.110 -5.333 31.024 1.00 0.00 N \\\\nHETATM 5 O1 UNL 1 -20.649 -6.831 32.617 1.00 0.00 O \\\\nHETATM 6 C2 UNL 1 -21.686 -2.616 35.165 1.00 0.00 C \\\\nHETATM 7 N2 UNL 1 -23.965 -6.156 33.727 1.00 0.00 N \\\\nHETATM 8 O2 UNL 1 -19.593 -5.014 31.750 1.00 0.00 O \\\\nHETATM 9 C3 UNL 1 -21.126 -3.172 34.043 1.00 0.00 C \\\\nHETATM 10 C4 UNL 1 -21.486 -4.468 33.648 1.00 0.00 C \\\\nHETATM 11 C5 UNL 1 -22.407 -5.201 34.382 1.00 0.00 C \\\\nHETATM 12 C6 UNL 1 -22.979 -4.639 35.519 1.00 0.00 C \\\\nHETATM 13 C7 UNL 1 -20.183 -2.457 33.283 1.00 0.00 C \\\\nHETATM 14 C8 UNL 1 -19.817 -1.177 33.665 1.00 0.00 C \\\\nHETATM 15 C9 UNL 1 -20.385 -0.609 34.797 1.00 0.00 C \\\\nHETATM 16 C10 UNL 1 -21.314 -1.316 35.551 1.00 0.00 C \\\\nHETATM 17 C11 UNL 1 -23.477 -5.727 31.322 1.00 0.00 C \\\\nHETATM 18 C12 UNL 1 -23.919 -5.268 32.711 1.00 0.00 C \\\\nHETATM 19 C13 UNL 1 -24.361 -5.758 34.957 1.00 0.00 C \\\\nHETATM 20 C14 UNL 1 -24.729 -4.443 35.178 1.00 0.00 C \\\\nHETATM 21 C15 UNL 1 -24.691 -3.550 34.159 1.00 0.00 C \\\\nHETATM 22 C16 UNL 1 -24.295 -3.951 32.927 1.00 0.00 C \\\\nHETATM 23 H1 UNL 1 -22.666 -5.667 29.597 1.00 0.00 H \\\\nHETATM 24 H2 UNL 1 -22.884 -1.071 30.916 1.00 0.00 H \\\\nHETATM 25 H3 UNL 1 -23.705 0.042 32.975 1.00 0.00 H \\\\nHETATM 26 H4 UNL 1 -21.822 -5.480 32.224 1.00 0.00 H \\\\nHETATM 27 H5 UNL 1 -21.919 -6.763 34.337 1.00 0.00 H \\\\nHETATM 28 H6 UNL 1 -22.728 -5.668 36.400 1.00 0.00 H \\\\nHETATM 29 H7 UNL 1 -23.452 -3.306 36.358 1.00 0.00 H \\\\nHETATM 30 H8 UNL 1 -24.812 -4.953 28.715 1.00 0.00 H \\\\nHETATM 31 H9 UNL 1 -24.625 -3.417 29.628 1.00 0.00 H \\\\nHETATM 32 H10 UNL 1 -26.710 -7.941 31.731 1.00 0.00 H \\\\nHETATM 33 H11 UNL 1 -27.274 -6.560 33.696 1.00 0.00 H \\\\nHETATM 34 H12 UNL 1 -26.536 -4.235 33.803 1.00 0.00 H \\\\nHETATM 35 H13 UNL 1 -25.261 -3.280 31.956 1.00 0.00 H \\\\nENDMDL\\\\nMODEL\\\\nCOMPND 5zcu_ligand\\\\nHETATM 1 S1 UNL 1 -20.211 -6.378 30.834 1.00 0.00 S \\\\nHETATM 2 BR1 UNL 1 -22.418 -4.703 36.692 1.00 0.00 BR \\\\nHETATM 3 C1 UNL 1 -21.697 -4.957 34.910 1.00 0.00 C \\\\nHETATM 4 N1 UNL 1 -21.538 -6.295 29.759 1.00 0.00 N \\\\nHETATM 5 O1 UNL 1 -19.752 -7.755 31.022 1.00 0.00 O \\\\nHETATM 6 C2 UNL 1 -21.135 -3.971 34.079 1.00 0.00 C \\\\nHETATM 7 N2 UNL 1 -22.897 -7.149 32.596 1.00 0.00 N \\\\nHETATM 8 O2 UNL 1 -19.015 -5.733 30.288 1.00 0.00 O \\\\nHETATM 9 C3 UNL 1 -20.668 -4.316 32.837 1.00 0.00 C \\\\nHETATM 10 C4 UNL 1 -20.750 -5.645 32.401 1.00 0.00 C \\\\nHETATM 11 C5 UNL 1 -21.300 -6.625 33.216 1.00 0.00 C \\\\nHETATM 12 C6 UNL 1 -21.777 -6.277 34.476 1.00 0.00 C \\\\nHETATM 13 C7 UNL 1 -20.097 -3.348 31.991 1.00 0.00 C \\\\nHETATM 14 C8 UNL 1 -20.008 -2.030 32.411 1.00 0.00 C \\\\nHETATM 15 C9 UNL 1 -20.484 -1.677 33.666 1.00 0.00 C \\\\nHETATM 16 C10 UNL 1 -21.045 -2.633 34.504 1.00 0.00 C \\\\nHETATM 17 C11 UNL 1 -22.801 -6.918 30.117 1.00 0.00 C \\\\nHETATM 18 C12 UNL 1 -23.292 -6.475 31.495 1.00 0.00 C \\\\nHETATM 19 C13 UNL 1 -23.332 -6.766 33.817 1.00 0.00 C \\\\nHETATM 20 C14 UNL 1 -24.191 -5.689 33.944 1.00 0.00 C \\\\nHETATM 21 C15 UNL 1 -24.596 -5.014 32.840 1.00 0.00 C \\\\nHETATM 22 C16 UNL 1 -24.160 -5.400 31.617 1.00 0.00 C \\\\nHETATM 23 H1 UNL 1 -22.666 -5.667 29.597 1.00 0.00 H \\\\nHETATM 24 H2 UNL 1 -22.884 -1.071 30.916 1.00 0.00 H \\\\nHETATM 25 H3 UNL 1 -23.705 0.042 32.975 1.00 0.00 H \\\\nHETATM 26 H4 UNL 1 -21.822 -5.480 32.224 1.00 0.00 H \\\\nHETATM 27 H5 UNL 1 -21.919 -6.763 34.337 1.00 0.00 H \\\\nHETATM 28 H6 UNL 1 -22.728 -5.668 36.400 1.00 0.00 H \\\\nHETATM 29 H7 UNL 1 -23.452 -3.306 36.358 1.00 0.00 H \\\\nHETATM 30 H8 UNL 1 -24.812 -4.953 28.715 1.00 0.00 H \\\\nHETATM 31 H9 UNL 1 -24.625 -3.417 29.628 1.00 0.00 H \\\\nHETATM 32 H10 UNL 1 -26.710 -7.941 31.731 1.00 0.00 H \\\\nHETATM 33 H11 UNL 1 -27.274 -6.560 33.696 1.00 0.00 H \\\\nHETATM 34 H12 UNL 1 -26.536 -4.235 33.803 1.00 0.00 H \\\\nHETATM 35 H13 UNL 1 -25.261 -3.280 31.956 1.00 0.00 H \\\\nENDMDL\\\\nMODEL\\\\nCOMPND 5zcu_ligand\\\\nHETATM 1 S1 UNL 1 -20.824 -5.811 29.946 1.00 0.00 S \\\\nHETATM 2 BR1 UNL 1 -23.051 -4.588 35.907 1.00 0.00 BR \\\\nHETATM 3 C1 UNL 1 -22.344 -4.702 34.104 1.00 0.00 C \\\\nHETATM 4 N1 UNL 1 -22.144 -5.685 28.866 1.00 0.00 N \\\\nHETATM 5 O1 UNL 1 -20.336 -7.187 30.045 1.00 0.00 O \\\\nHETATM 6 C2 UNL 1 -21.877 -3.636 33.313 1.00 0.00 C \\\\nHETATM 7 N2 UNL 1 -23.898 -6.073 31.645 1.00 0.00 N \\\\nHETATM 8 O2 UNL 1 -19.638 -5.106 29.454 1.00 0.00 O \\\\nHETATM 9 C3 UNL 1 -21.406 -3.886 32.049 1.00 0.00 C \\\\nHETATM 10 C4 UNL 1 -21.390 -5.196 31.553 1.00 0.00 C \\\\nHETATM 11 C5 UNL 1 -21.847 -6.252 32.328 1.00 0.00 C \\\\nHETATM 12 C6 UNL 1 -22.327 -6.002 33.610 1.00 0.00 C \\\\nHETATM 13 C7 UNL 1 -20.929 -2.837 31.242 1.00 0.00 C \\\\nHETATM 14 C8 UNL 1 -20.936 -1.538 31.722 1.00 0.00 C \\\\nHETATM 15 C9 UNL 1 -21.417 -1.281 32.999 1.00 0.00 C \\\\nHETATM 16 C10 UNL 1 -21.885 -2.317 33.799 1.00 0.00 C \\\\nHETATM 17 C11 UNL 1 -23.421 -6.287 29.209 1.00 0.00 C \\\\nHETATM 18 C12 UNL 1 -24.086 -5.593 30.397 1.00 0.00 C \\\\nHETATM 19 C13 UNL 1 -24.488 -5.466 32.699 1.00 0.00 C \\\\nHETATM 20 C14 UNL 1 -25.294 -4.358 32.504 1.00 0.00 C \\\\nHETATM 21 C15 UNL 1 -25.490 -3.877 31.252 1.00 0.00 C \\\\nHETATM 22 C16 UNL 1 -24.899 -4.487 30.197 1.00 0.00 C \\\\nHETATM 23 H1 UNL 1 -22.666 -5.667 29.597 1.00 0.00 H \\\\nHETATM 24 H2 UNL 1 -22.884 -1.071 30.916 1.00 0.00 H \\\\nHETATM 25 H3 UNL 1 -23.705 0.042 32.975 1.00 0.00 H \\\\nHETATM 26 H4 UNL 1 -21.822 -5.480 32.224 1.00 0.00 H \\\\nHETATM 27 H5 UNL 1 -21.919 -6.763 34.337 1.00 0.00 H \\\\nHETATM 28 H6 UNL 1 -22.728 -5.668 36.400 1.00 0.00 H \\\\nHETATM 29 H7 UNL 1 -23.452 -3.306 36.358 1.00 0.00 H \\\\nHETATM 30 H8 UNL 1 -24.812 -4.953 28.715 1.00 0.00 H \\\\nHETATM 31 H9 UNL 1 -24.625 -3.417 29.628 1.00 0.00 H \\\\nHETATM 32 H10 UNL 1 -26.710 -7.941 31.731 1.00 0.00 H \\\\nHETATM 33 H11 UNL 1 -27.274 -6.560 33.696 1.00 0.00 H \\\\nHETATM 34 H12 UNL 1 -26.536 -4.235 33.803 1.00 0.00 H \\\\nHETATM 35 H13 UNL 1 -25.261 -3.280 31.956 1.00 0.00 H \\\\nENDMDL\\\\nMODEL\\\\nCOMPND 5zcu_ligand\\\\nHETATM 1 S1 UNL 1 -21.329 -5.333 30.375 1.00 0.00 S \\\\nHETATM 2 BR1 UNL 1 -24.725 -4.536 35.836 1.00 0.00 BR \\\\nHETATM 3 C1 UNL 1 -23.705 -4.519 34.186 1.00 0.00 C \\\\nHETATM 4 N1 UNL 1 -22.410 -5.254 29.052 1.00 0.00 N \\\\nHETATM 5 O1 UNL 1 -20.764 -6.674 30.533 1.00 0.00 O \\\\nHETATM 6 C2 UNL 1 -23.273 -3.385 33.473 1.00 0.00 C \\\\nHETATM 7 N2 UNL 1 -24.605 -6.050 31.359 1.00 0.00 N \\\\nHETATM 8 O2 UNL 1 -20.127 -4.524 30.156 1.00 0.00 O \\\\nHETATM 9 C3 UNL 1 -22.556 -3.544 32.315 1.00 0.00 C \\\\nHETATM 10 C4 UNL 1 -22.255 -4.831 31.849 1.00 0.00 C \\\\nHETATM 11 C5 UNL 1 -22.675 -5.954 32.548 1.00 0.00 C \\\\nHETATM 12 C6 UNL 1 -23.405 -5.795 33.722 1.00 0.00 C \\\\nHETATM 13 C7 UNL 1 -22.110 -2.426 31.589 1.00 0.00 C \\\\nHETATM 14 C8 UNL 1 -22.399 -1.149 32.041 1.00 0.00 C \\\\nHETATM 15 C9 UNL 1 -23.128 -0.984 33.211 1.00 0.00 C \\\\nHETATM 16 C10 UNL 1 -23.567 -2.088 33.931 1.00 0.00 C \\\\nHETATM 17 C11 UNL 1 -23.631 -6.041 29.066 1.00 0.00 C \\\\nHETATM 18 C12 UNL 1 -24.629 -5.539 30.109 1.00 0.00 C \\\\nHETATM 19 C13 UNL 1 -25.489 -5.615 32.285 1.00 0.00 C \\\\nHETATM 20 C14 UNL 1 -26.425 -4.651 31.955 1.00 0.00 C \\\\nHETATM 21 C15 UNL 1 -26.456 -4.140 30.700 1.00 0.00 C \\\\nHETATM 22 C16 UNL 1 -25.571 -4.579 29.773 1.00 0.00 C \\\\nHETATM 23 H1 UNL 1 -22.666 -5.667 29.597 1.00 0.00 H \\\\nHETATM 24 H2 UNL 1 -22.884 -1.071 30.916 1.00 0.00 H \\\\nHETATM 25 H3 UNL 1 -23.705 0.042 32.975 1.00 0.00 H \\\\nHETATM 26 H4 UNL 1 -21.822 -5.480 32.224 1.00 0.00 H \\\\nHETATM 27 H5 UNL 1 -21.919 -6.763 34.337 1.00 0.00 H \\\\nHETATM 28 H6 UNL 1 -22.728 -5.668 36.400 1.00 0.00 H \\\\nHETATM 29 H7 UNL 1 -23.452 -3.306 36.358 1.00 0.00 H \\\\nHETATM 30 H8 UNL 1 -24.812 -4.953 28.715 1.00 0.00 H \\\\nHETATM 31 H9 UNL 1 -24.625 -3.417 29.628 1.00 0.00 H \\\\nHETATM 32 H10 UNL 1 -26.710 -7.941 31.731 1.00 0.00 H \\\\nHETATM 33 H11 UNL 1 -27.274 -6.560 33.696 1.00 0.00 H \\\\nHETATM 34 H12 UNL 1 -26.536 -4.235 33.803 1.00 0.00 H \\\\nHETATM 35 H13 UNL 1 -25.261 -3.280 31.956 1.00 0.00 H \\\\nENDMDL\\\\nMODEL\\\\nCOMPND 5zcu_ligand\\\\nHETATM 1 S1 UNL 1 -21.096 -5.157 30.281 1.00 0.00 S \\\\nHETATM 2 BR1 UNL 1 -24.375 -4.102 35.770 1.00 0.00 BR \\\\nHETATM 3 C1 UNL 1 -23.418 -4.166 34.084 1.00 0.00 C \\\\nHETATM 4 N1 UNL 1 -22.160 -5.077 28.943 1.00 0.00 N \\\\nHETATM 5 O1 UNL 1 -20.575 -6.510 30.478 1.00 0.00 O \\\\nHETATM 6 C2 UNL 1 -23.139 -3.083 33.231 1.00 0.00 C \\\\nHETATM 7 N2 UNL 1 -24.414 -6.217 31.042 1.00 0.00 N \\\\nHETATM 8 O2 UNL 1 -19.867 -4.391 30.056 1.00 0.00 O \\\\nHETATM 9 C3 UNL 1 -22.448 -3.297 32.066 1.00 0.00 C \\\\nHETATM 10 C4 UNL 1 -22.022 -4.590 31.731 1.00 0.00 C \\\\nHETATM 11 C5 UNL 1 -22.291 -5.663 32.568 1.00 0.00 C \\\\nHETATM 12 C6 UNL 1 -22.994 -5.448 33.750 1.00 0.00 C \\\\nHETATM 13 C7 UNL 1 -22.153 -2.229 31.200 1.00 0.00 C \\\\nHETATM 14 C8 UNL 1 -22.566 -0.946 31.521 1.00 0.00 C \\\\nHETATM 15 C9 UNL 1 -23.270 -0.726 32.697 1.00 0.00 C \\\\nHETATM 16 C10 UNL 1 -23.559 -1.780 33.555 1.00 0.00 C \\\\nHETATM 17 C11 UNL 1 -23.266 -6.014 28.840 1.00 0.00 C \\\\nHETATM 18 C12 UNL 1 -24.401 -5.674 29.805 1.00 0.00 C \\\\nHETATM 19 C13 UNL 1 -25.419 -5.925 31.898 1.00 0.00 C \\\\nHETATM 20 C14 UNL 1 -26.441 -5.077 31.509 1.00 0.00 C \\\\nHETATM 21 C15 UNL 1 -26.435 -4.536 30.267 1.00 0.00 C \\\\nHETATM 22 C16 UNL 1 -25.428 -4.831 29.409 1.00 0.00 C \\\\nHETATM 23 H1 UNL 1 -22.666 -5.667 29.597 1.00 0.00 H \\\\nHETATM 24 H2 UNL 1 -22.884 -1.071 30.916 1.00 0.00 H \\\\nHETATM 25 H3 UNL 1 -23.705 0.042 32.975 1.00 0.00 H \\\\nHETATM 26 H4 UNL 1 -21.822 -5.480 32.224 1.00 0.00 H \\\\nHETATM 27 H5 UNL 1 -21.919 -6.763 34.337 1.00 0.00 H \\\\nHETATM 28 H6 UNL 1 -22.728 -5.668 36.400 1.00 0.00 H \\\\nHETATM 29 H7 UNL 1 -23.452 -3.306 36.358 1.00 0.00 H \\\\nHETATM 30 H8 UNL 1 -24.812 -4.953 28.715 1.00 0.00 H \\\\nHETATM 31 H9 UNL 1 -24.625 -3.417 29.628 1.00 0.00 H \\\\nHETATM 32 H10 UNL 1 -26.710 -7.941 31.731 1.00 0.00 H \\\\nHETATM 33 H11 UNL 1 -27.274 -6.560 33.696 1.00 0.00 H \\\\nHETATM 34 H12 UNL 1 -26.536 -4.235 33.803 1.00 0.00 H \\\\nHETATM 35 H13 UNL 1 -25.261 -3.280 31.956 1.00 0.00 H \\\\nENDMDL\\\\nMODEL\\\\nCOMPND 5zcu_ligand\\\\nHETATM 1 S1 UNL 1 -21.251 -5.263 29.967 1.00 0.00 S \\\\nHETATM 2 BR1 UNL 1 -24.132 -3.848 35.597 1.00 0.00 BR \\\\nHETATM 3 C1 UNL 1 -23.303 -4.025 33.852 1.00 0.00 C \\\\nHETATM 4 N1 UNL 1 -22.394 -5.238 28.695 1.00 0.00 N \\\\nHETATM 5 O1 UNL 1 -20.738 -6.613 30.207 1.00 0.00 O \\\\nHETATM 6 C2 UNL 1 -23.111 -3.005 32.903 1.00 0.00 C \\\\nHETATM 7 N2 UNL 1 -24.714 -6.369 30.822 1.00 0.00 N \\\\nHETATM 8 O2 UNL 1 -20.028 -4.533 29.627 1.00 0.00 O \\\\nHETATM 9 C3 UNL 1 -22.504 -3.296 31.708 1.00 0.00 C \\\\nHETATM 10 C4 UNL 1 -22.078 -4.603 31.438 1.00 0.00 C \\\\nHETATM 11 C5 UNL 1 -22.261 -5.614 32.370 1.00 0.00 C \\\\nHETATM 12 C6 UNL 1 -22.878 -5.322 33.583 1.00 0.00 C \\\\nHETATM 13 C7 UNL 1 -22.297 -2.291 30.746 1.00 0.00 C \\\\nHETATM 14 C8 UNL 1 -22.712 -0.994 31.001 1.00 0.00 C \\\\nHETATM 15 C9 UNL 1 -23.330 -0.697 32.208 1.00 0.00 C \\\\nHETATM 16 C10 UNL 1 -23.532 -1.688 33.161 1.00 0.00 C \\\\nHETATM 17 C11 UNL 1 -23.471 -6.213 28.668 1.00 0.00 C \\\\nHETATM 18 C12 UNL 1 -24.626 -5.823 29.590 1.00 0.00 C \\\\nHETATM 19 C13 UNL 1 -25.736 -6.033 31.640 1.00 0.00 C \\\\nHETATM 20 C14 UNL 1 -26.700 -5.134 31.217 1.00 0.00 C \\\\nHETATM 21 C15 UNL 1 -26.618 -4.588 29.979 1.00 0.00 C \\\\nHETATM 22 C16 UNL 1 -25.594 -4.928 29.160 1.00 0.00 C \\\\nHETATM 23 H1 UNL 1 -22.666 -5.667 29.597 1.00 0.00 H \\\\nHETATM 24 H2 UNL 1 -22.884 -1.071 30.916 1.00 0.00 H \\\\nHETATM 25 H3 UNL 1 -23.705 0.042 32.975 1.00 0.00 H \\\\nHETATM 26 H4 UNL 1 -21.822 -5.480 32.224 1.00 0.00 H \\\\nHETATM 27 H5 UNL 1 -21.919 -6.763 34.337 1.00 0.00 H \\\\nHETATM 28 H6 UNL 1 -22.728 -5.668 36.400 1.00 0.00 H \\\\nHETATM 29 H7 UNL 1 -23.452 -3.306 36.358 1.00 0.00 H \\\\nHETATM 30 H8 UNL 1 -24.812 -4.953 28.715 1.00 0.00 H \\\\nHETATM 31 H9 UNL 1 -24.625 -3.417 29.628 1.00 0.00 H \\\\nHETATM 32 H10 UNL 1 -26.710 -7.941 31.731 1.00 0.00 H \\\\nHETATM 33 H11 UNL 1 -27.274 -6.560 33.696 1.00 0.00 H \\\\nHETATM 34 H12 UNL 1 -26.536 -4.235 33.803 1.00 0.00 H \\\\nHETATM 35 H13 UNL 1 -25.261 -3.280 31.956 1.00 0.00 H \\\\nENDMDL\\\\nMODEL\\\\nCOMPND 5zcu_ligand\\\\nHETATM 1 S1 UNL 1 -20.952 -5.492 30.632 1.00 0.00 S \\\\nHETATM 2 BR1 UNL 1 -24.034 -4.422 36.231 1.00 0.00 BR \\\\nHETATM 3 C1 UNL 1 -23.198 -4.512 34.483 1.00 0.00 C \\\\nHETATM 4 N1 UNL 1 -22.062 -5.635 29.338 1.00 0.00 N \\\\nHETATM 5 O1 UNL 1 -20.260 -6.755 30.893 1.00 0.00 O \\\\nHETATM 6 C2 UNL 1 -23.236 -3.528 33.478 1.00 0.00 C \\\\nHETATM 7 N2 UNL 1 -24.459 -7.040 31.313 1.00 0.00 N \\\\nHETATM 8 O2 UNL 1 -19.837 -4.599 30.308 1.00 0.00 O \\\\nHETATM 9 C3 UNL 1 -22.589 -3.747 32.289 1.00 0.00 C \\\\nHETATM 10 C4 UNL 1 -21.892 -4.945 32.080 1.00 0.00 C \\\\nHETATM 11 C5 UNL 1 -21.847 -5.919 33.068 1.00 0.00 C \\\\nHETATM 12 C6 UNL 1 -22.505 -5.700 34.274 1.00 0.00 C \\\\nHETATM 13 C7 UNL 1 -22.609 -2.775 31.273 1.00 0.00 C \\\\nHETATM 14 C8 UNL 1 -23.291 -1.586 31.467 1.00 0.00 C \\\\nHETATM 15 C9 UNL 1 -23.951 -1.363 32.668 1.00 0.00 C \\\\nHETATM 16 C10 UNL 1 -23.929 -2.320 33.675 1.00 0.00 C \\\\nHETATM 17 C11 UNL 1 -23.006 -6.738 29.312 1.00 0.00 C \\\\nHETATM 18 C12 UNL 1 -24.268 -6.437 30.121 1.00 0.00 C \\\\nHETATM 19 C13 UNL 1 -25.575 -6.782 32.031 1.00 0.00 C \\\\nHETATM 20 C14 UNL 1 -26.530 -5.907 31.544 1.00 0.00 C \\\\nHETATM 21 C15 UNL 1 -26.345 -5.305 30.344 1.00 0.00 C \\\\nHETATM 22 C16 UNL 1 -25.226 -5.566 29.625 1.00 0.00 C \\\\nHETATM 23 H1 UNL 1 -22.666 -5.667 29.597 1.00 0.00 H \\\\nHETATM 24 H2 UNL 1 -22.884 -1.071 30.916 1.00 0.00 H \\\\nHETATM 25 H3 UNL 1 -23.705 0.042 32.975 1.00 0.00 H \\\\nHETATM 26 H4 UNL 1 -21.822 -5.480 32.224 1.00 0.00 H \\\\nHETATM 27 H5 UNL 1 -21.919 -6.763 34.337 1.00 0.00 H \\\\nHETATM 28 H6 UNL 1 -22.728 -5.668 36.400 1.00 0.00 H \\\\nHETATM 29 H7 UNL 1 -23.452 -3.306 36.358 1.00 0.00 H \\\\nHETATM 30 H8 UNL 1 -24.812 -4.953 28.715 1.00 0.00 H \\\\nHETATM 31 H9 UNL 1 -24.625 -3.417 29.628 1.00 0.00 H \\\\nHETATM 32 H10 UNL 1 -26.710 -7.941 31.731 1.00 0.00 H \\\\nHETATM 33 H11 UNL 1 -27.274 -6.560 33.696 1.00 0.00 H \\\\nHETATM 34 H12 UNL 1 -26.536 -4.235 33.803 1.00 0.00 H \\\\nHETATM 35 H13 UNL 1 -25.261 -3.280 31.956 1.00 0.00 H \\\\nENDMDL\\\\n\",\n \"MODEL\\\\nCOMPND 5zcu_ligand\\\\nHETATM 1 S1 UNL 1 -21.984 -3.493 30.267 1.00 0.00 S \\\\nHETATM 2 BR1 UNL 1 -24.121 -0.640 35.679 1.00 0.00 BR \\\\nHETATM 3 C1 UNL 1 -23.447 -1.703 34.203 1.00 0.00 C \\\\nHETATM 4 N1 UNL 1 -23.033 -4.756 29.787 1.00 0.00 N \\\\nHETATM 5 O1 UNL 1 -20.587 -3.929 30.288 1.00 0.00 O \\\\nHETATM 6 C2 UNL 1 -23.040 -3.049 34.250 1.00 0.00 C \\\\nHETATM 7 N2 UNL 1 -25.672 -6.380 30.757 1.00 0.00 N \\\\nHETATM 8 O2 UNL 1 -21.945 -2.404 29.288 1.00 0.00 O \\\\nHETATM 9 C3 UNL 1 -22.584 -3.660 33.110 1.00 0.00 C \\\\nHETATM 10 C4 UNL 1 -22.527 -2.945 31.906 1.00 0.00 C \\\\nHETATM 11 C5 UNL 1 -22.929 -1.618 31.851 1.00 0.00 C \\\\nHETATM 12 C6 UNL 1 -23.390 -0.995 33.007 1.00 0.00 C \\\\nHETATM 13 C7 UNL 1 -22.177 -5.006 33.132 1.00 0.00 C \\\\nHETATM 14 C8 UNL 1 -22.231 -5.725 34.315 1.00 0.00 C \\\\nHETATM 15 C9 UNL 1 -22.688 -5.108 35.472 1.00 0.00 C \\\\nHETATM 16 C10 UNL 1 -23.094 -3.779 35.451 1.00 0.00 C \\\\nHETATM 17 C11 UNL 1 -24.458 -4.504 29.655 1.00 0.00 C \\\\nHETATM 18 C12 UNL 1 -25.258 -5.096 30.815 1.00 0.00 C \\\\nHETATM 19 C13 UNL 1 -26.385 -6.908 31.777 1.00 0.00 C \\\\nHETATM 20 C14 UNL 1 -26.701 -6.134 32.880 1.00 0.00 C \\\\nHETATM 21 C15 UNL 1 -26.293 -4.843 32.939 1.00 0.00 C \\\\nHETATM 22 C16 UNL 1 -25.580 -4.315 31.915 1.00 0.00 C \\\\nHETATM 23 H1 UNL 1 -22.666 -5.667 29.597 1.00 0.00 H \\\\nHETATM 24 H2 UNL 1 -22.884 -1.071 30.916 1.00 0.00 H \\\\nHETATM 25 H3 UNL 1 -23.705 0.042 32.975 1.00 0.00 H \\\\nHETATM 26 H4 UNL 1 -21.822 -5.480 32.224 1.00 0.00 H \\\\nHETATM 27 H5 UNL 1 -21.919 -6.763 34.337 1.00 0.00 H \\\\nHETATM 28 H6 UNL 1 -22.728 -5.668 36.400 1.00 0.00 H \\\\nHETATM 29 H7 UNL 1 -23.452 -3.306 36.358 1.00 0.00 H \\\\nHETATM 30 H8 UNL 1 -24.812 -4.953 28.715 1.00 0.00 H \\\\nHETATM 31 H9 UNL 1 -24.625 -3.417 29.628 1.00 0.00 H \\\\nHETATM 32 H10 UNL 1 -26.710 -7.941 31.731 1.00 0.00 H \\\\nHETATM 33 H11 UNL 1 -27.274 -6.560 33.696 1.00 0.00 H \\\\nHETATM 34 H12 UNL 1 -26.536 -4.235 33.803 1.00 0.00 H \\\\nHETATM 35 H13 UNL 1 -25.261 -3.280 31.956 1.00 0.00 H \\\\nCONECT 1 4 5 5 8\\\\nCONECT 1 8 10\\\\nCONECT 2 3\\\\nCONECT 3 6 6 12\\\\nCONECT 4 17 23\\\\nCONECT 6 9 16\\\\nCONECT 7 18 18 19\\\\nCONECT 9 10 10 13\\\\nCONECT 10 11\\\\nCONECT 11 12 12 24\\\\nCONECT 12 25\\\\nCONECT 13 14 14 26\\\\nCONECT 14 15 27\\\\nCONECT 15 16 16 28\\\\nCONECT 16 29\\\\nCONECT 17 18 30 31\\\\nCONECT 18 22\\\\nCONECT 19 20 20 32\\\\nCONECT 20 21 33\\\\nCONECT 21 22 22 34\\\\nCONECT 22 35\\\\nENDMDL\\\\nMODEL\\\\nCOMPND 5zcu_ligand\\\\nHETATM 1 S1 UNL 1 -22.160 14.516 31.439 1.00 0.00 S \\\\nHETATM 2 BR1 UNL 1 -24.297 17.369 36.851 1.00 0.00 BR \\\\nHETATM 3 C1 UNL 1 -23.623 16.306 35.375 1.00 0.00 C \\\\nHETATM 4 N1 UNL 1 -23.209 13.253 30.959 1.00 0.00 N \\\\nHETATM 5 O1 UNL 1 -20.763 14.080 31.460 1.00 0.00 O \\\\nHETATM 6 C2 UNL 1 -23.216 14.960 35.422 1.00 0.00 C \\\\nHETATM 7 N2 UNL 1 -25.848 11.629 31.929 1.00 0.00 N \\\\nHETATM 8 O2 UNL 1 -22.121 15.605 30.460 1.00 0.00 O \\\\nHETATM 9 C3 UNL 1 -22.760 14.349 34.282 1.00 0.00 C \\\\nHETATM 10 C4 UNL 1 -22.703 15.064 33.078 1.00 0.00 C \\\\nHETATM 11 C5 UNL 1 -23.105 16.391 33.023 1.00 0.00 C \\\\nHETATM 12 C6 UNL 1 -23.566 17.014 34.179 1.00 0.00 C \\\\nHETATM 13 C7 UNL 1 -22.353 13.003 34.304 1.00 0.00 C \\\\nHETATM 14 C8 UNL 1 -22.407 12.284 35.487 1.00 0.00 C \\\\nHETATM 15 C9 UNL 1 -22.864 12.901 36.644 1.00 0.00 C \\\\nHETATM 16 C10 UNL 1 -23.270 14.230 36.623 1.00 0.00 C \\\\nHETATM 17 C11 UNL 1 -24.634 13.505 30.827 1.00 0.00 C \\\\nHETATM 18 C12 UNL 1 -25.434 12.913 31.987 1.00 0.00 C \\\\nHETATM 19 C13 UNL 1 -26.561 11.101 32.949 1.00 0.00 C \\\\nHETATM 20 C14 UNL 1 -26.877 11.875 34.052 1.00 0.00 C \\\\nHETATM 21 C15 UNL 1 -26.469 13.166 34.111 1.00 0.00 C \\\\nHETATM 22 C16 UNL 1 -25.756 13.694 33.087 1.00 0.00 C \\\\nHETATM 23 H1 UNL 1 -22.666 -5.667 29.597 1.00 0.00 H \\\\nHETATM 24 H2 UNL 1 -22.884 -1.071 30.916 1.00 0.00 H \\\\nHETATM 25 H3 UNL 1 -23.705 0.042 32.975 1.00 0.00 H \\\\nHETATM 26 H4 UNL 1 -21.822 -5.480 32.224 1.00 0.00 H \\\\nHETATM 27 H5 UNL 1 -21.919 -6.763 34.337 1.00 0.00 H \\\\nHETATM 28 H6 UNL 1 -22.728 -5.668 36.400 1.00 0.00 H \\\\nHETATM 29 H7 UNL 1 -23.452 -3.306 36.358 1.00 0.00 H \\\\nHETATM 30 H8 UNL 1 -24.812 -4.953 28.715 1.00 0.00 H \\\\nHETATM 31 H9 UNL 1 -24.625 -3.417 29.628 1.00 0.00 H \\\\nHETATM 32 H10 UNL 1 -26.710 -7.941 31.731 1.00 0.00 H \\\\nHETATM 33 H11 UNL 1 -27.274 -6.560 33.696 1.00 0.00 H \\\\nHETATM 34 H12 UNL 1 -26.536 -4.235 33.803 1.00 0.00 H \\\\nHETATM 35 H13 UNL 1 -25.261 -3.280 31.956 1.00 0.00 H \\\\nENDMDL\\\\nMODEL\\\\nCOMPND 5zcu_ligand\\\\nHETATM 1 S1 UNL 1 -22.160 14.516 31.439 1.00 0.00 S \\\\nHETATM 2 BR1 UNL 1 -24.297 17.369 36.851 1.00 0.00 BR \\\\nHETATM 3 C1 UNL 1 -23.623 16.306 35.375 1.00 0.00 C \\\\nHETATM 4 N1 UNL 1 -23.209 13.253 30.959 1.00 0.00 N \\\\nHETATM 5 O1 UNL 1 -20.763 14.080 31.460 1.00 0.00 O \\\\nHETATM 6 C2 UNL 1 -23.216 14.960 35.422 1.00 0.00 C \\\\nHETATM 7 N2 UNL 1 -25.848 11.629 31.929 1.00 0.00 N \\\\nHETATM 8 O2 UNL 1 -22.121 15.605 30.460 1.00 0.00 O \\\\nHETATM 9 C3 UNL 1 -22.760 14.349 34.282 1.00 0.00 C \\\\nHETATM 10 C4 UNL 1 -22.703 15.064 33.078 1.00 0.00 C \\\\nHETATM 11 C5 UNL 1 -23.105 16.391 33.023 1.00 0.00 C \\\\nHETATM 12 C6 UNL 1 -23.566 17.014 34.179 1.00 0.00 C \\\\nHETATM 13 C7 UNL 1 -22.353 13.003 34.304 1.00 0.00 C \\\\nHETATM 14 C8 UNL 1 -22.407 12.284 35.487 1.00 0.00 C \\\\nHETATM 15 C9 UNL 1 -22.864 12.901 36.644 1.00 0.00 C \\\\nHETATM 16 C10 UNL 1 -23.270 14.230 36.623 1.00 0.00 C \\\\nHETATM 17 C11 UNL 1 -24.634 13.505 30.827 1.00 0.00 C \\\\nHETATM 18 C12 UNL 1 -25.434 12.913 31.987 1.00 0.00 C \\\\nHETATM 19 C13 UNL 1 -26.561 11.101 32.949 1.00 0.00 C \\\\nHETATM 20 C14 UNL 1 -26.877 11.875 34.052 1.00 0.00 C \\\\nHETATM 21 C15 UNL 1 -26.469 13.166 34.111 1.00 0.00 C \\\\nHETATM 22 C16 UNL 1 -25.756 13.694 33.087 1.00 0.00 C \\\\nHETATM 23 H1 UNL 1 -22.666 -5.667 29.597 1.00 0.00 H \\\\nHETATM 24 H2 UNL 1 -22.884 -1.071 30.916 1.00 0.00 H \\\\nHETATM 25 H3 UNL 1 -23.705 0.042 32.975 1.00 0.00 H \\\\nHETATM 26 H4 UNL 1 -21.822 -5.480 32.224 1.00 0.00 H \\\\nHETATM 27 H5 UNL 1 -21.919 -6.763 34.337 1.00 0.00 H \\\\nHETATM 28 H6 UNL 1 -22.728 -5.668 36.400 1.00 0.00 H \\\\nHETATM 29 H7 UNL 1 -23.452 -3.306 36.358 1.00 0.00 H \\\\nHETATM 30 H8 UNL 1 -24.812 -4.953 28.715 1.00 0.00 H \\\\nHETATM 31 H9 UNL 1 -24.625 -3.417 29.628 1.00 0.00 H \\\\nHETATM 32 H10 UNL 1 -26.710 -7.941 31.731 1.00 0.00 H \\\\nHETATM 33 H11 UNL 1 -27.274 -6.560 33.696 1.00 0.00 H \\\\nHETATM 34 H12 UNL 1 -26.536 -4.235 33.803 1.00 0.00 H \\\\nHETATM 35 H13 UNL 1 -25.261 -3.280 31.956 1.00 0.00 H \\\\nENDMDL\\\\nMODEL\\\\nCOMPND 5zcu_ligand\\\\nHETATM 1 S1 UNL 1 -29.200 -6.379 16.899 1.00 0.00 S \\\\nHETATM 2 BR1 UNL 1 -30.054 -12.712 15.820 1.00 0.00 BR \\\\nHETATM 3 C1 UNL 1 -30.013 -10.781 16.008 1.00 0.00 C \\\\nHETATM 4 N1 UNL 1 -27.870 -5.950 15.912 1.00 0.00 N \\\\nHETATM 5 O1 UNL 1 -28.873 -6.277 18.322 1.00 0.00 O \\\\nHETATM 6 C2 UNL 1 -30.950 -9.864 15.497 1.00 0.00 C \\\\nHETATM 7 N2 UNL 1 -25.034 -4.508 17.534 1.00 0.00 N \\\\nHETATM 8 O2 UNL 1 -30.309 -5.430 16.776 1.00 0.00 O \\\\nHETATM 9 C3 UNL 1 -30.776 -8.522 15.719 1.00 0.00 C \\\\nHETATM 10 C4 UNL 1 -29.670 -8.070 16.452 1.00 0.00 C \\\\nHETATM 11 C5 UNL 1 -28.743 -8.968 16.961 1.00 0.00 C \\\\nHETATM 12 C6 UNL 1 -28.917 -10.331 16.736 1.00 0.00 C \\\\nHETATM 13 C7 UNL 1 -31.702 -7.588 15.222 1.00 0.00 C \\\\nHETATM 14 C8 UNL 1 -32.801 -8.022 14.498 1.00 0.00 C \\\\nHETATM 15 C9 UNL 1 -32.978 -9.380 14.269 1.00 0.00 C \\\\nHETATM 16 C10 UNL 1 -32.065 -10.304 14.762 1.00 0.00 C \\\\nHETATM 17 C11 UNL 1 -27.121 -4.737 16.192 1.00 0.00 C \\\\nHETATM 18 C12 UNL 1 -25.639 -5.019 16.440 1.00 0.00 C \\\\nHETATM 19 C13 UNL 1 -23.722 -4.749 17.755 1.00 0.00 C \\\\nHETATM 20 C14 UNL 1 -22.992 -5.511 16.860 1.00 0.00 C \\\\nHETATM 21 C15 UNL 1 -23.595 -6.020 15.758 1.00 0.00 C \\\\nHETATM 22 C16 UNL 1 -24.909 -5.777 15.536 1.00 0.00 C \\\\nHETATM 23 H1 UNL 1 -22.666 -5.667 29.597 1.00 0.00 H \\\\nHETATM 24 H2 UNL 1 -22.884 -1.071 30.916 1.00 0.00 H \\\\nHETATM 25 H3 UNL 1 -23.705 0.042 32.975 1.00 0.00 H \\\\nHETATM 26 H4 UNL 1 -21.822 -5.480 32.224 1.00 0.00 H \\\\nHETATM 27 H5 UNL 1 -21.919 -6.763 34.337 1.00 0.00 H \\\\nHETATM 28 H6 UNL 1 -22.728 -5.668 36.400 1.00 0.00 H \\\\nHETATM 29 H7 UNL 1 -23.452 -3.306 36.358 1.00 0.00 H \\\\nHETATM 30 H8 UNL 1 -24.812 -4.953 28.715 1.00 0.00 H \\\\nHETATM 31 H9 UNL 1 -24.625 -3.417 29.628 1.00 0.00 H \\\\nHETATM 32 H10 UNL 1 -26.710 -7.941 31.731 1.00 0.00 H \\\\nHETATM 33 H11 UNL 1 -27.274 -6.560 33.696 1.00 0.00 H \\\\nHETATM 34 H12 UNL 1 -26.536 -4.235 33.803 1.00 0.00 H \\\\nHETATM 35 H13 UNL 1 -25.261 -3.280 31.956 1.00 0.00 H \\\\nENDMDL\\\\nMODEL\\\\nCOMPND 5zcu_ligand\\\\nHETATM 1 S1 UNL 1 -15.353 1.142 52.143 1.00 0.00 S \\\\nHETATM 2 BR1 UNL 1 -17.380 -3.960 55.586 1.00 0.00 BR \\\\nHETATM 3 C1 UNL 1 -16.751 -2.312 54.780 1.00 0.00 C \\\\nHETATM 4 N1 UNL 1 -13.955 0.538 51.364 1.00 0.00 N \\\\nHETATM 5 O1 UNL 1 -15.094 2.422 52.803 1.00 0.00 O \\\\nHETATM 6 C2 UNL 1 -16.390 -1.129 55.451 1.00 0.00 C \\\\nHETATM 7 N2 UNL 1 -11.658 -0.801 50.316 1.00 0.00 N \\\\nHETATM 8 O2 UNL 1 -16.405 1.502 51.189 1.00 0.00 O \\\\nHETATM 9 C3 UNL 1 -15.963 -0.044 54.730 1.00 0.00 C \\\\nHETATM 10 C4 UNL 1 -15.884 -0.117 53.332 1.00 0.00 C \\\\nHETATM 11 C5 UNL 1 -16.236 -1.281 52.664 1.00 0.00 C \\\\nHETATM 12 C6 UNL 1 -16.672 -2.383 53.393 1.00 0.00 C \\\\nHETATM 13 C7 UNL 1 -15.592 1.147 55.379 1.00 0.00 C \\\\nHETATM 14 C8 UNL 1 -15.662 1.232 56.760 1.00 0.00 C \\\\nHETATM 15 C9 UNL 1 -16.099 0.136 57.493 1.00 0.00 C \\\\nHETATM 16 C10 UNL 1 -16.462 -1.043 56.853 1.00 0.00 C \\\\nHETATM 17 C11 UNL 1 -14.085 -0.263 50.159 1.00 0.00 C \\\\nHETATM 18 C12 UNL 1 -12.730 -0.578 49.526 1.00 0.00 C \\\\nHETATM 19 C13 UNL 1 -10.455 -1.074 49.764 1.00 0.00 C \\\\nHETATM 20 C14 UNL 1 -10.315 -1.119 48.387 1.00 0.00 C \\\\nHETATM 21 C15 UNL 1 -11.387 -0.890 47.591 1.00 0.00 C \\\\nHETATM 22 C16 UNL 1 -12.591 -0.615 48.147 1.00 0.00 C \\\\nHETATM 23 H1 UNL 1 -22.666 -5.667 29.597 1.00 0.00 H \\\\nHETATM 24 H2 UNL 1 -22.884 -1.071 30.916 1.00 0.00 H \\\\nHETATM 25 H3 UNL 1 -23.705 0.042 32.975 1.00 0.00 H \\\\nHETATM 26 H4 UNL 1 -21.822 -5.480 32.224 1.00 0.00 H \\\\nHETATM 27 H5 UNL 1 -21.919 -6.763 34.337 1.00 0.00 H \\\\nHETATM 28 H6 UNL 1 -22.728 -5.668 36.400 1.00 0.00 H \\\\nHETATM 29 H7 UNL 1 -23.452 -3.306 36.358 1.00 0.00 H \\\\nHETATM 30 H8 UNL 1 -24.812 -4.953 28.715 1.00 0.00 H \\\\nHETATM 31 H9 UNL 1 -24.625 -3.417 29.628 1.00 0.00 H \\\\nHETATM 32 H10 UNL 1 -26.710 -7.941 31.731 1.00 0.00 H \\\\nHETATM 33 H11 UNL 1 -27.274 -6.560 33.696 1.00 0.00 H \\\\nHETATM 34 H12 UNL 1 -26.536 -4.235 33.803 1.00 0.00 H \\\\nHETATM 35 H13 UNL 1 -25.261 -3.280 31.956 1.00 0.00 H \\\\nENDMDL\\\\nMODEL\\\\nCOMPND 5zcu_ligand\\\\nHETATM 1 S1 UNL 1 -11.906 -12.670 43.300 1.00 0.00 S \\\\nHETATM 2 BR1 UNL 1 -14.971 -17.129 46.866 1.00 0.00 BR \\\\nHETATM 3 C1 UNL 1 -13.839 -15.926 45.848 1.00 0.00 C \\\\nHETATM 4 N1 UNL 1 -12.005 -13.191 41.674 1.00 0.00 N \\\\nHETATM 5 O1 UNL 1 -10.541 -12.288 43.663 1.00 0.00 O \\\\nHETATM 6 C2 UNL 1 -12.450 -16.036 45.655 1.00 0.00 C \\\\nHETATM 7 N2 UNL 1 -13.668 -13.666 39.075 1.00 0.00 N \\\\nHETATM 8 O2 UNL 1 -12.638 -11.421 43.527 1.00 0.00 O \\\\nHETATM 9 C3 UNL 1 -11.793 -15.095 44.904 1.00 0.00 C \\\\nHETATM 10 C4 UNL 1 -12.505 -14.033 44.332 1.00 0.00 C \\\\nHETATM 11 C5 UNL 1 -13.876 -13.919 44.515 1.00 0.00 C \\\\nHETATM 12 C6 UNL 1 -14.545 -14.871 45.279 1.00 0.00 C \\\\nHETATM 13 C7 UNL 1 -10.406 -15.188 44.694 1.00 0.00 C \\\\nHETATM 14 C8 UNL 1 -9.690 -16.235 45.252 1.00 0.00 C \\\\nHETATM 15 C9 UNL 1 -10.352 -17.186 46.016 1.00 0.00 C \\\\nHETATM 16 C10 UNL 1 -11.723 -17.098 46.222 1.00 0.00 C \\\\nHETATM 17 C11 UNL 1 -12.836 -14.331 41.327 1.00 0.00 C \\\\nHETATM 18 C12 UNL 1 -13.959 -13.955 40.361 1.00 0.00 C \\\\nHETATM 19 C13 UNL 1 -14.656 -13.326 38.217 1.00 0.00 C \\\\nHETATM 20 C14 UNL 1 -15.967 -13.264 38.654 1.00 0.00 C \\\\nHETATM 21 C15 UNL 1 -16.263 -13.547 39.946 1.00 0.00 C \\\\nHETATM 22 C16 UNL 1 -15.271 -13.886 40.805 1.00 0.00 C \\\\nHETATM 23 H1 UNL 1 -22.666 -5.667 29.597 1.00 0.00 H \\\\nHETATM 24 H2 UNL 1 -22.884 -1.071 30.916 1.00 0.00 H \\\\nHETATM 25 H3 UNL 1 -23.705 0.042 32.975 1.00 0.00 H \\\\nHETATM 26 H4 UNL 1 -21.822 -5.480 32.224 1.00 0.00 H \\\\nHETATM 27 H5 UNL 1 -21.919 -6.763 34.337 1.00 0.00 H \\\\nHETATM 28 H6 UNL 1 -22.728 -5.668 36.400 1.00 0.00 H \\\\nHETATM 29 H7 UNL 1 -23.452 -3.306 36.358 1.00 0.00 H \\\\nHETATM 30 H8 UNL 1 -24.812 -4.953 28.715 1.00 0.00 H \\\\nHETATM 31 H9 UNL 1 -24.625 -3.417 29.628 1.00 0.00 H \\\\nHETATM 32 H10 UNL 1 -26.710 -7.941 31.731 1.00 0.00 H \\\\nHETATM 33 H11 UNL 1 -27.274 -6.560 33.696 1.00 0.00 H \\\\nHETATM 34 H12 UNL 1 -26.536 -4.235 33.803 1.00 0.00 H \\\\nHETATM 35 H13 UNL 1 -25.261 -3.280 31.956 1.00 0.00 H \\\\nENDMDL\\\\nMODEL\\\\nCOMPND 5zcu_ligand\\\\nHETATM 1 S1 UNL 1 -11.296 -7.234 27.542 1.00 0.00 S \\\\nHETATM 2 BR1 UNL 1 -12.295 -13.622 27.111 1.00 0.00 BR \\\\nHETATM 3 C1 UNL 1 -11.847 -11.764 27.441 1.00 0.00 C \\\\nHETATM 4 N1 UNL 1 -9.661 -6.848 27.219 1.00 0.00 N \\\\nHETATM 5 O1 UNL 1 -11.769 -6.598 28.773 1.00 0.00 O \\\\nHETATM 6 C2 UNL 1 -11.003 -11.267 28.451 1.00 0.00 C \\\\nHETATM 7 N2 UNL 1 -8.419 -8.860 25.809 1.00 0.00 N \\\\nHETATM 8 O2 UNL 1 -12.206 -6.668 26.543 1.00 0.00 O \\\\nHETATM 9 C3 UNL 1 -10.788 -9.916 28.551 1.00 0.00 C \\\\nHETATM 10 C4 UNL 1 -11.406 -9.039 27.650 1.00 0.00 C \\\\nHETATM 11 C5 UNL 1 -12.237 -9.522 26.649 1.00 0.00 C \\\\nHETATM 12 C6 UNL 1 -12.459 -10.892 26.547 1.00 0.00 C \\\\nHETATM 13 C7 UNL 1 -9.944 -9.396 29.549 1.00 0.00 C \\\\nHETATM 14 C8 UNL 1 -9.325 -10.253 30.445 1.00 0.00 C \\\\nHETATM 15 C9 UNL 1 -9.544 -11.621 30.349 1.00 0.00 C \\\\nHETATM 16 C10 UNL 1 -10.374 -12.136 29.361 1.00 0.00 C \\\\nHETATM 17 C11 UNL 1 -8.599 -7.550 27.920 1.00 0.00 C \\\\nHETATM 18 C12 UNL 1 -7.999 -8.676 27.079 1.00 0.00 C \\\\nHETATM 19 C13 UNL 1 -7.897 -9.858 25.061 1.00 0.00 C \\\\nHETATM 20 C14 UNL 1 -6.937 -10.700 25.595 1.00 0.00 C \\\\nHETATM 21 C15 UNL 1 -6.517 -10.522 26.871 1.00 0.00 C \\\\nHETATM 22 C16 UNL 1 -7.043 -9.523 27.620 1.00 0.00 C \\\\nHETATM 23 H1 UNL 1 -22.666 -5.667 29.597 1.00 0.00 H \\\\nHETATM 24 H2 UNL 1 -22.884 -1.071 30.916 1.00 0.00 H \\\\nHETATM 25 H3 UNL 1 -23.705 0.042 32.975 1.00 0.00 H \\\\nHETATM 26 H4 UNL 1 -21.822 -5.480 32.224 1.00 0.00 H \\\\nHETATM 27 H5 UNL 1 -21.919 -6.763 34.337 1.00 0.00 H \\\\nHETATM 28 H6 UNL 1 -22.728 -5.668 36.400 1.00 0.00 H \\\\nHETATM 29 H7 UNL 1 -23.452 -3.306 36.358 1.00 0.00 H \\\\nHETATM 30 H8 UNL 1 -24.812 -4.953 28.715 1.00 0.00 H \\\\nHETATM 31 H9 UNL 1 -24.625 -3.417 29.628 1.00 0.00 H \\\\nHETATM 32 H10 UNL 1 -26.710 -7.941 31.731 1.00 0.00 H \\\\nHETATM 33 H11 UNL 1 -27.274 -6.560 33.696 1.00 0.00 H \\\\nHETATM 34 H12 UNL 1 -26.536 -4.235 33.803 1.00 0.00 H \\\\nHETATM 35 H13 UNL 1 -25.261 -3.280 31.956 1.00 0.00 H \\\\nENDMDL\\\\nMODEL\\\\nCOMPND 5zcu_ligand\\\\nHETATM 1 S1 UNL 1 -12.908 -8.987 30.589 1.00 0.00 S \\\\nHETATM 2 BR1 UNL 1 -18.719 -6.194 29.940 1.00 0.00 BR \\\\nHETATM 3 C1 UNL 1 -17.049 -7.079 30.376 1.00 0.00 C \\\\nHETATM 4 N1 UNL 1 -13.089 -10.688 30.572 1.00 0.00 N \\\\nHETATM 5 O1 UNL 1 -12.077 -8.543 31.709 1.00 0.00 O \\\\nHETATM 6 C2 UNL 1 -16.697 -7.656 31.610 1.00 0.00 C \\\\nHETATM 7 N2 UNL 1 -15.055 -11.649 28.657 1.00 0.00 N \\\\nHETATM 8 O2 UNL 1 -12.145 -8.500 29.437 1.00 0.00 O \\\\nHETATM 9 C3 UNL 1 -15.469 -8.247 31.757 1.00 0.00 C \\\\nHETATM 10 C4 UNL 1 -14.571 -8.276 30.681 1.00 0.00 C \\\\nHETATM 11 C5 UNL 1 -14.912 -7.711 29.460 1.00 0.00 C \\\\nHETATM 12 C6 UNL 1 -16.157 -7.109 29.309 1.00 0.00 C \\\\nHETATM 13 C7 UNL 1 -15.097 -8.835 32.980 1.00 0.00 C \\\\nHETATM 14 C8 UNL 1 -15.976 -8.816 34.051 1.00 0.00 C \\\\nHETATM 15 C9 UNL 1 -17.220 -8.214 33.906 1.00 0.00 C \\\\nHETATM 16 C10 UNL 1 -17.589 -7.636 32.698 1.00 0.00 C \\\\nHETATM 17 C11 UNL 1 -14.336 -11.288 31.016 1.00 0.00 C \\\\nHETATM 18 C12 UNL 1 -14.994 -12.125 29.919 1.00 0.00 C \\\\nHETATM 19 C13 UNL 1 -15.641 -12.381 27.685 1.00 0.00 C \\\\nHETATM 20 C14 UNL 1 -16.190 -13.617 27.978 1.00 0.00 C \\\\nHETATM 21 C15 UNL 1 -16.137 -14.096 29.245 1.00 0.00 C \\\\nHETATM 22 C16 UNL 1 -15.550 -13.360 30.219 1.00 0.00 C \\\\nHETATM 23 H1 UNL 1 -22.666 -5.667 29.597 1.00 0.00 H \\\\nHETATM 24 H2 UNL 1 -22.884 -1.071 30.916 1.00 0.00 H \\\\nHETATM 25 H3 UNL 1 -23.705 0.042 32.975 1.00 0.00 H \\\\nHETATM 26 H4 UNL 1 -21.822 -5.480 32.224 1.00 0.00 H \\\\nHETATM 27 H5 UNL 1 -21.919 -6.763 34.337 1.00 0.00 H \\\\nHETATM 28 H6 UNL 1 -22.728 -5.668 36.400 1.00 0.00 H \\\\nHETATM 29 H7 UNL 1 -23.452 -3.306 36.358 1.00 0.00 H \\\\nHETATM 30 H8 UNL 1 -24.812 -4.953 28.715 1.00 0.00 H \\\\nHETATM 31 H9 UNL 1 -24.625 -3.417 29.628 1.00 0.00 H \\\\nHETATM 32 H10 UNL 1 -26.710 -7.941 31.731 1.00 0.00 H \\\\nHETATM 33 H11 UNL 1 -27.274 -6.560 33.696 1.00 0.00 H \\\\nHETATM 34 H12 UNL 1 -26.536 -4.235 33.803 1.00 0.00 H \\\\nHETATM 35 H13 UNL 1 -25.261 -3.280 31.956 1.00 0.00 H \\\\nENDMDL\\\\nMODEL\\\\nCOMPND 5zcu_ligand\\\\nHETATM 1 S1 UNL 1 -21.285 -3.093 31.985 1.00 0.00 S \\\\nHETATM 2 BR1 UNL 1 -27.079 -4.409 29.398 1.00 0.00 BR \\\\nHETATM 3 C1 UNL 1 -25.414 -4.170 30.365 1.00 0.00 C \\\\nHETATM 4 N1 UNL 1 -20.243 -4.430 31.753 1.00 0.00 N \\\\nHETATM 5 O1 UNL 1 -21.265 -2.626 33.372 1.00 0.00 O \\\\nHETATM 6 C2 UNL 1 -25.056 -4.766 31.588 1.00 0.00 C \\\\nHETATM 7 N2 UNL 1 -21.132 -5.745 29.406 1.00 0.00 N \\\\nHETATM 8 O2 UNL 1 -20.829 -1.905 31.260 1.00 0.00 O \\\\nHETATM 9 C3 UNL 1 -23.833 -4.491 32.144 1.00 0.00 C \\\\nHETATM 10 C4 UNL 1 -22.946 -3.622 31.493 1.00 0.00 C \\\\nHETATM 11 C5 UNL 1 -23.291 -3.033 30.285 1.00 0.00 C \\\\nHETATM 12 C6 UNL 1 -24.533 -3.308 29.720 1.00 0.00 C \\\\nHETATM 13 C7 UNL 1 -23.451 -5.079 33.363 1.00 0.00 C \\\\nHETATM 14 C8 UNL 1 -24.317 -5.942 34.015 1.00 0.00 C \\\\nHETATM 15 C9 UNL 1 -25.558 -6.219 33.457 1.00 0.00 C \\\\nHETATM 16 C10 UNL 1 -25.935 -5.641 32.250 1.00 0.00 C \\\\nHETATM 17 C11 UNL 1 -20.762 -5.782 31.869 1.00 0.00 C \\\\nHETATM 18 C12 UNL 1 -20.875 -6.475 30.512 1.00 0.00 C \\\\nHETATM 19 C13 UNL 1 -21.239 -6.352 28.203 1.00 0.00 C \\\\nHETATM 20 C14 UNL 1 -21.093 -7.724 28.100 1.00 0.00 C \\\\nHETATM 21 C15 UNL 1 -20.841 -8.462 29.209 1.00 0.00 C \\\\nHETATM 22 C16 UNL 1 -20.736 -7.852 30.414 1.00 0.00 C \\\\nHETATM 23 H1 UNL 1 -22.666 -5.667 29.597 1.00 0.00 H \\\\nHETATM 24 H2 UNL 1 -22.884 -1.071 30.916 1.00 0.00 H \\\\nHETATM 25 H3 UNL 1 -23.705 0.042 32.975 1.00 0.00 H \\\\nHETATM 26 H4 UNL 1 -21.822 -5.480 32.224 1.00 0.00 H \\\\nHETATM 27 H5 UNL 1 -21.919 -6.763 34.337 1.00 0.00 H \\\\nHETATM 28 H6 UNL 1 -22.728 -5.668 36.400 1.00 0.00 H \\\\nHETATM 29 H7 UNL 1 -23.452 -3.306 36.358 1.00 0.00 H \\\\nHETATM 30 H8 UNL 1 -24.812 -4.953 28.715 1.00 0.00 H \\\\nHETATM 31 H9 UNL 1 -24.625 -3.417 29.628 1.00 0.00 H \\\\nHETATM 32 H10 UNL 1 -26.710 -7.941 31.731 1.00 0.00 H \\\\nHETATM 33 H11 UNL 1 -27.274 -6.560 33.696 1.00 0.00 H \\\\nHETATM 34 H12 UNL 1 -26.536 -4.235 33.803 1.00 0.00 H \\\\nHETATM 35 H13 UNL 1 -25.261 -3.280 31.956 1.00 0.00 H \\\\nENDMDL\\\\nMODEL\\\\nCOMPND 5zcu_ligand\\\\nHETATM 1 S1 UNL 1 -26.487 -2.166 31.872 1.00 0.00 S \\\\nHETATM 2 BR1 UNL 1 -31.584 -4.574 28.675 1.00 0.00 BR \\\\nHETATM 3 C1 UNL 1 -30.135 -3.998 29.828 1.00 0.00 C \\\\nHETATM 4 N1 UNL 1 -25.329 -3.389 32.169 1.00 0.00 N \\\\nHETATM 5 O1 UNL 1 -26.792 -1.404 33.083 1.00 0.00 O \\\\nHETATM 6 C2 UNL 1 -29.892 -4.417 31.149 1.00 0.00 C \\\\nHETATM 7 N2 UNL 1 -26.466 -5.421 30.636 1.00 0.00 N \\\\nHETATM 8 O2 UNL 1 -25.974 -1.123 30.981 1.00 0.00 O \\\\nHETATM 9 C3 UNL 1 -28.817 -3.911 31.834 1.00 0.00 C \\\\nHETATM 10 C4 UNL 1 -27.966 -2.983 31.218 1.00 0.00 C \\\\nHETATM 11 C5 UNL 1 -28.199 -2.566 29.915 1.00 0.00 C \\\\nHETATM 12 C6 UNL 1 -29.290 -3.077 29.218 1.00 0.00 C \\\\nHETATM 13 C7 UNL 1 -28.550 -4.319 33.153 1.00 0.00 C \\\\nHETATM 14 C8 UNL 1 -29.381 -5.239 33.773 1.00 0.00 C \\\\nHETATM 15 C9 UNL 1 -30.473 -5.750 33.084 1.00 0.00 C \\\\nHETATM 16 C10 UNL 1 -30.735 -5.350 31.779 1.00 0.00 C \\\\nHETATM 17 C11 UNL 1 -25.719 -4.603 32.867 1.00 0.00 C \\\\nHETATM 18 C12 UNL 1 -26.534 -5.542 31.979 1.00 0.00 C \\\\nHETATM 19 C13 UNL 1 -27.190 -6.245 29.845 1.00 0.00 C \\\\nHETATM 20 C14 UNL 1 -28.008 -7.209 30.407 1.00 0.00 C \\\\nHETATM 21 C15 UNL 1 -28.084 -7.329 31.754 1.00 0.00 C \\\\nHETATM 22 C16 UNL 1 -27.360 -6.502 32.546 1.00 0.00 C \\\\nHETATM 23 H1 UNL 1 -22.666 -5.667 29.597 1.00 0.00 H \\\\nHETATM 24 H2 UNL 1 -22.884 -1.071 30.916 1.00 0.00 H \\\\nHETATM 25 H3 UNL 1 -23.705 0.042 32.975 1.00 0.00 H \\\\nHETATM 26 H4 UNL 1 -21.822 -5.480 32.224 1.00 0.00 H \\\\nHETATM 27 H5 UNL 1 -21.919 -6.763 34.337 1.00 0.00 H \\\\nHETATM 28 H6 UNL 1 -22.728 -5.668 36.400 1.00 0.00 H \\\\nHETATM 29 H7 UNL 1 -23.452 -3.306 36.358 1.00 0.00 H \\\\nHETATM 30 H8 UNL 1 -24.812 -4.953 28.715 1.00 0.00 H \\\\nHETATM 31 H9 UNL 1 -24.625 -3.417 29.628 1.00 0.00 H \\\\nHETATM 32 H10 UNL 1 -26.710 -7.941 31.731 1.00 0.00 H \\\\nHETATM 33 H11 UNL 1 -27.274 -6.560 33.696 1.00 0.00 H \\\\nHETATM 34 H12 UNL 1 -26.536 -4.235 33.803 1.00 0.00 H \\\\nHETATM 35 H13 UNL 1 -25.261 -3.280 31.956 1.00 0.00 H \\\\nENDMDL\\\\nMODEL\\\\nCOMPND 5zcu_ligand\\\\nHETATM 1 S1 UNL 1 -24.671 -2.851 30.725 1.00 0.00 S \\\\nHETATM 2 BR1 UNL 1 -29.471 -6.191 27.932 1.00 0.00 BR \\\\nHETATM 3 C1 UNL 1 -28.156 -5.234 28.989 1.00 0.00 C \\\\nHETATM 4 N1 UNL 1 -23.557 -3.954 31.408 1.00 0.00 N \\\\nHETATM 5 O1 UNL 1 -25.041 -1.799 31.673 1.00 0.00 O \\\\nHETATM 6 C2 UNL 1 -28.164 -5.055 30.384 1.00 0.00 C \\\\nHETATM 7 N2 UNL 1 -24.454 -5.849 29.502 1.00 0.00 N \\\\nHETATM 8 O2 UNL 1 -24.082 -2.076 29.630 1.00 0.00 O \\\\nHETATM 9 C3 UNL 1 -27.154 -4.347 30.984 1.00 0.00 C \\\\nHETATM 10 C4 UNL 1 -26.119 -3.808 30.207 1.00 0.00 C \\\\nHETATM 11 C5 UNL 1 -26.102 -3.983 28.831 1.00 0.00 C \\\\nHETATM 12 C6 UNL 1 -27.127 -4.699 28.220 1.00 0.00 C \\\\nHETATM 13 C7 UNL 1 -27.139 -4.159 32.377 1.00 0.00 C \\\\nHETATM 14 C8 UNL 1 -28.155 -4.689 33.157 1.00 0.00 C \\\\nHETATM 15 C9 UNL 1 -29.182 -5.402 32.553 1.00 0.00 C \\\\nHETATM 16 C10 UNL 1 -29.196 -5.591 31.176 1.00 0.00 C \\\\nHETATM 17 C11 UNL 1 -24.017 -5.249 31.881 1.00 0.00 C \\\\nHETATM 18 C12 UNL 1 -24.778 -6.019 30.802 1.00 0.00 C \\\\nHETATM 19 C13 UNL 1 -25.126 -6.522 28.542 1.00 0.00 C \\\\nHETATM 20 C14 UNL 1 -26.155 -7.382 28.886 1.00 0.00 C \\\\nHETATM 21 C15 UNL 1 -26.488 -7.551 30.189 1.00 0.00 C \\\\nHETATM 22 C16 UNL 1 -25.814 -6.874 31.149 1.00 0.00 C \\\\nHETATM 23 H1 UNL 1 -22.666 -5.667 29.597 1.00 0.00 H \\\\nHETATM 24 H2 UNL 1 -22.884 -1.071 30.916 1.00 0.00 H \\\\nHETATM 25 H3 UNL 1 -23.705 0.042 32.975 1.00 0.00 H \\\\nHETATM 26 H4 UNL 1 -21.822 -5.480 32.224 1.00 0.00 H \\\\nHETATM 27 H5 UNL 1 -21.919 -6.763 34.337 1.00 0.00 H \\\\nHETATM 28 H6 UNL 1 -22.728 -5.668 36.400 1.00 0.00 H \\\\nHETATM 29 H7 UNL 1 -23.452 -3.306 36.358 1.00 0.00 H \\\\nHETATM 30 H8 UNL 1 -24.812 -4.953 28.715 1.00 0.00 H \\\\nHETATM 31 H9 UNL 1 -24.625 -3.417 29.628 1.00 0.00 H \\\\nHETATM 32 H10 UNL 1 -26.710 -7.941 31.731 1.00 0.00 H \\\\nHETATM 33 H11 UNL 1 -27.274 -6.560 33.696 1.00 0.00 H \\\\nHETATM 34 H12 UNL 1 -26.536 -4.235 33.803 1.00 0.00 H \\\\nHETATM 35 H13 UNL 1 -25.261 -3.280 31.956 1.00 0.00 H \\\\nENDMDL\\\\nMODEL\\\\nCOMPND 5zcu_ligand\\\\nHETATM 1 S1 UNL 1 -21.518 -5.494 30.732 1.00 0.00 S \\\\nHETATM 2 BR1 UNL 1 -26.170 -9.922 29.864 1.00 0.00 BR \\\\nHETATM 3 C1 UNL 1 -24.918 -8.513 30.321 1.00 0.00 C \\\\nHETATM 4 N1 UNL 1 -20.155 -6.431 31.168 1.00 0.00 N \\\\nHETATM 5 O1 UNL 1 -21.727 -4.380 31.657 1.00 0.00 O \\\\nHETATM 6 C2 UNL 1 -25.031 -7.596 31.382 1.00 0.00 C \\\\nHETATM 7 N2 UNL 1 -21.021 -8.946 30.296 1.00 0.00 N \\\\nHETATM 8 O2 UNL 1 -21.326 -4.797 29.458 1.00 0.00 O \\\\nHETATM 9 C3 UNL 1 -24.052 -6.654 31.572 1.00 0.00 C \\\\nHETATM 10 C4 UNL 1 -22.946 -6.610 30.713 1.00 0.00 C \\\\nHETATM 11 C5 UNL 1 -22.826 -7.512 29.666 1.00 0.00 C \\\\nHETATM 12 C6 UNL 1 -23.819 -8.468 29.470 1.00 0.00 C \\\\nHETATM 13 C7 UNL 1 -24.141 -5.731 32.629 1.00 0.00 C \\\\nHETATM 14 C8 UNL 1 -25.228 -5.766 33.487 1.00 0.00 C \\\\nHETATM 15 C9 UNL 1 -26.223 -6.716 33.296 1.00 0.00 C \\\\nHETATM 16 C10 UNL 1 -26.134 -7.631 32.254 1.00 0.00 C \\\\nHETATM 17 C11 UNL 1 -20.285 -7.477 32.168 1.00 0.00 C \\\\nHETATM 18 C12 UNL 1 -21.010 -8.708 31.625 1.00 0.00 C \\\\nHETATM 19 C13 UNL 1 -21.666 -10.030 29.809 1.00 0.00 C \\\\nHETATM 20 C14 UNL 1 -22.323 -10.894 30.667 1.00 0.00 C \\\\nHETATM 21 C15 UNL 1 -22.319 -10.655 32.001 1.00 0.00 C \\\\nHETATM 22 C16 UNL 1 -21.674 -9.567 32.487 1.00 0.00 C \\\\nHETATM 23 H1 UNL 1 -22.666 -5.667 29.597 1.00 0.00 H \\\\nHETATM 24 H2 UNL 1 -22.884 -1.071 30.916 1.00 0.00 H \\\\nHETATM 25 H3 UNL 1 -23.705 0.042 32.975 1.00 0.00 H \\\\nHETATM 26 H4 UNL 1 -21.822 -5.480 32.224 1.00 0.00 H \\\\nHETATM 27 H5 UNL 1 -21.919 -6.763 34.337 1.00 0.00 H \\\\nHETATM 28 H6 UNL 1 -22.728 -5.668 36.400 1.00 0.00 H \\\\nHETATM 29 H7 UNL 1 -23.452 -3.306 36.358 1.00 0.00 H \\\\nHETATM 30 H8 UNL 1 -24.812 -4.953 28.715 1.00 0.00 H \\\\nHETATM 31 H9 UNL 1 -24.625 -3.417 29.628 1.00 0.00 H \\\\nHETATM 32 H10 UNL 1 -26.710 -7.941 31.731 1.00 0.00 H \\\\nHETATM 33 H11 UNL 1 -27.274 -6.560 33.696 1.00 0.00 H \\\\nHETATM 34 H12 UNL 1 -26.536 -4.235 33.803 1.00 0.00 H \\\\nHETATM 35 H13 UNL 1 -25.261 -3.280 31.956 1.00 0.00 H \\\\nENDMDL\\\\nMODEL\\\\nCOMPND 5zcu_ligand\\\\nHETATM 1 S1 UNL 1 -20.906 -5.399 31.582 1.00 0.00 S \\\\nHETATM 2 BR1 UNL 1 -26.081 -9.270 31.099 1.00 0.00 BR \\\\nHETATM 3 C1 UNL 1 -24.625 -8.043 31.472 1.00 0.00 C \\\\nHETATM 4 N1 UNL 1 -19.658 -6.317 32.309 1.00 0.00 N \\\\nHETATM 5 O1 UNL 1 -21.062 -4.094 32.225 1.00 0.00 O \\\\nHETATM 6 C2 UNL 1 -24.455 -7.264 32.631 1.00 0.00 C \\\\nHETATM 7 N2 UNL 1 -21.142 -8.632 32.579 1.00 0.00 N \\\\nHETATM 8 O2 UNL 1 -20.582 -5.020 30.205 1.00 0.00 O \\\\nHETATM 9 C3 UNL 1 -23.364 -6.441 32.741 1.00 0.00 C \\\\nHETATM 10 C4 UNL 1 -22.425 -6.379 31.703 1.00 0.00 C \\\\nHETATM 11 C5 UNL 1 -22.584 -7.145 30.557 1.00 0.00 C \\\\nHETATM 12 C6 UNL 1 -23.692 -7.981 30.443 1.00 0.00 C \\\\nHETATM 13 C7 UNL 1 -23.170 -5.657 33.893 1.00 0.00 C \\\\nHETATM 14 C8 UNL 1 -24.090 -5.711 34.928 1.00 0.00 C \\\\nHETATM 15 C9 UNL 1 -25.198 -6.541 34.818 1.00 0.00 C \\\\nHETATM 16 C10 UNL 1 -25.388 -7.318 33.682 1.00 0.00 C \\\\nHETATM 17 C11 UNL 1 -19.822 -6.818 33.663 1.00 0.00 C \\\\nHETATM 18 C12 UNL 1 -20.761 -8.022 33.722 1.00 0.00 C \\\\nHETATM 19 C13 UNL 1 -21.977 -9.694 32.624 1.00 0.00 C \\\\nHETATM 20 C14 UNL 1 -22.453 -10.155 33.839 1.00 0.00 C \\\\nHETATM 21 C15 UNL 1 -22.079 -9.541 34.988 1.00 0.00 C \\\\nHETATM 22 C16 UNL 1 -21.243 -8.476 34.941 1.00 0.00 C \\\\nHETATM 23 H1 UNL 1 -22.666 -5.667 29.597 1.00 0.00 H \\\\nHETATM 24 H2 UNL 1 -22.884 -1.071 30.916 1.00 0.00 H \\\\nHETATM 25 H3 UNL 1 -23.705 0.042 32.975 1.00 0.00 H \\\\nHETATM 26 H4 UNL 1 -21.822 -5.480 32.224 1.00 0.00 H \\\\nHETATM 27 H5 UNL 1 -21.919 -6.763 34.337 1.00 0.00 H \\\\nHETATM 28 H6 UNL 1 -22.728 -5.668 36.400 1.00 0.00 H \\\\nHETATM 29 H7 UNL 1 -23.452 -3.306 36.358 1.00 0.00 H \\\\nHETATM 30 H8 UNL 1 -24.812 -4.953 28.715 1.00 0.00 H \\\\nHETATM 31 H9 UNL 1 -24.625 -3.417 29.628 1.00 0.00 H \\\\nHETATM 32 H10 UNL 1 -26.710 -7.941 31.731 1.00 0.00 H \\\\nHETATM 33 H11 UNL 1 -27.274 -6.560 33.696 1.00 0.00 H \\\\nHETATM 34 H12 UNL 1 -26.536 -4.235 33.803 1.00 0.00 H \\\\nHETATM 35 H13 UNL 1 -25.261 -3.280 31.956 1.00 0.00 H \\\\nENDMDL\\\\nMODEL\\\\nCOMPND 5zcu_ligand\\\\nHETATM 1 S1 UNL 1 -23.246 -4.740 29.518 1.00 0.00 S \\\\nHETATM 2 BR1 UNL 1 -27.054 -9.179 32.310 1.00 0.00 BR \\\\nHETATM 3 C1 UNL 1 -25.894 -7.746 31.707 1.00 0.00 C \\\\nHETATM 4 N1 UNL 1 -21.691 -5.447 29.423 1.00 0.00 N \\\\nHETATM 5 O1 UNL 1 -23.192 -3.389 30.078 1.00 0.00 O \\\\nHETATM 6 C2 UNL 1 -25.336 -6.724 32.497 1.00 0.00 C \\\\nHETATM 7 N2 UNL 1 -22.259 -7.299 31.423 1.00 0.00 N \\\\nHETATM 8 O2 UNL 1 -23.824 -4.495 28.195 1.00 0.00 O \\\\nHETATM 9 C3 UNL 1 -24.531 -5.779 31.914 1.00 0.00 C \\\\nHETATM 10 C4 UNL 1 -24.266 -5.835 30.539 1.00 0.00 C \\\\nHETATM 11 C5 UNL 1 -24.810 -6.841 29.754 1.00 0.00 C \\\\nHETATM 12 C6 UNL 1 -25.629 -7.800 30.343 1.00 0.00 C \\\\nHETATM 13 C7 UNL 1 -23.958 -4.751 32.685 1.00 0.00 C \\\\nHETATM 14 C8 UNL 1 -24.210 -4.686 34.046 1.00 0.00 C \\\\nHETATM 15 C9 UNL 1 -25.028 -5.638 34.638 1.00 0.00 C \\\\nHETATM 16 C10 UNL 1 -25.592 -6.657 33.879 1.00 0.00 C \\\\nHETATM 17 C11 UNL 1 -20.821 -5.444 30.587 1.00 0.00 C \\\\nHETATM 18 C12 UNL 1 -21.351 -6.340 31.706 1.00 0.00 C \\\\nHETATM 19 C13 UNL 1 -22.736 -8.092 32.408 1.00 0.00 C \\\\nHETATM 20 C14 UNL 1 -22.304 -7.919 33.712 1.00 0.00 C \\\\nHETATM 21 C15 UNL 1 -21.398 -6.954 34.001 1.00 0.00 C \\\\nHETATM 22 C16 UNL 1 -20.922 -6.159 33.012 1.00 0.00 C \\\\nHETATM 23 H1 UNL 1 -22.666 -5.667 29.597 1.00 0.00 H \\\\nHETATM 24 H2 UNL 1 -22.884 -1.071 30.916 1.00 0.00 H \\\\nHETATM 25 H3 UNL 1 -23.705 0.042 32.975 1.00 0.00 H \\\\nHETATM 26 H4 UNL 1 -21.822 -5.480 32.224 1.00 0.00 H \\\\nHETATM 27 H5 UNL 1 -21.919 -6.763 34.337 1.00 0.00 H \\\\nHETATM 28 H6 UNL 1 -22.728 -5.668 36.400 1.00 0.00 H \\\\nHETATM 29 H7 UNL 1 -23.452 -3.306 36.358 1.00 0.00 H \\\\nHETATM 30 H8 UNL 1 -24.812 -4.953 28.715 1.00 0.00 H \\\\nHETATM 31 H9 UNL 1 -24.625 -3.417 29.628 1.00 0.00 H \\\\nHETATM 32 H10 UNL 1 -26.710 -7.941 31.731 1.00 0.00 H \\\\nHETATM 33 H11 UNL 1 -27.274 -6.560 33.696 1.00 0.00 H \\\\nHETATM 34 H12 UNL 1 -26.536 -4.235 33.803 1.00 0.00 H \\\\nHETATM 35 H13 UNL 1 -25.261 -3.280 31.956 1.00 0.00 H \\\\nENDMDL\\\\nMODEL\\\\nCOMPND 5zcu_ligand\\\\nHETATM 1 S1 UNL 1 -23.089 -3.909 30.307 1.00 0.00 S \\\\nHETATM 2 BR1 UNL 1 -27.503 -5.889 34.619 1.00 0.00 BR \\\\nHETATM 3 C1 UNL 1 -26.109 -5.127 33.506 1.00 0.00 C \\\\nHETATM 4 N1 UNL 1 -22.001 -5.224 30.202 1.00 0.00 N \\\\nHETATM 5 O1 UNL 1 -22.386 -2.640 30.506 1.00 0.00 O \\\\nHETATM 6 C2 UNL 1 -25.228 -4.086 33.852 1.00 0.00 C \\\\nHETATM 7 N2 UNL 1 -22.349 -6.819 32.495 1.00 0.00 N \\\\nHETATM 8 O2 UNL 1 -23.791 -3.669 29.043 1.00 0.00 O \\\\nHETATM 9 C3 UNL 1 -24.292 -3.659 32.945 1.00 0.00 C \\\\nHETATM 10 C4 UNL 1 -24.216 -4.259 31.681 1.00 0.00 C \\\\nHETATM 11 C5 UNL 1 -25.079 -5.288 31.333 1.00 0.00 C \\\\nHETATM 12 C6 UNL 1 -26.031 -5.722 32.251 1.00 0.00 C \\\\nHETATM 13 C7 UNL 1 -23.398 -2.624 33.271 1.00 0.00 C \\\\nHETATM 14 C8 UNL 1 -23.461 -2.023 34.518 1.00 0.00 C \\\\nHETATM 15 C9 UNL 1 -24.410 -2.450 35.437 1.00 0.00 C \\\\nHETATM 16 C10 UNL 1 -25.292 -3.475 35.118 1.00 0.00 C \\\\nHETATM 17 C11 UNL 1 -20.891 -5.324 31.135 1.00 0.00 C \\\\nHETATM 18 C12 UNL 1 -21.310 -5.957 32.462 1.00 0.00 C \\\\nHETATM 19 C13 UNL 1 -22.728 -7.377 33.666 1.00 0.00 C \\\\nHETATM 20 C14 UNL 1 -22.060 -7.062 34.837 1.00 0.00 C \\\\nHETATM 21 C15 UNL 1 -21.021 -6.193 34.809 1.00 0.00 C \\\\nHETATM 22 C16 UNL 1 -20.643 -5.632 33.634 1.00 0.00 C \\\\nHETATM 23 H1 UNL 1 -22.666 -5.667 29.597 1.00 0.00 H \\\\nHETATM 24 H2 UNL 1 -22.884 -1.071 30.916 1.00 0.00 H \\\\nHETATM 25 H3 UNL 1 -23.705 0.042 32.975 1.00 0.00 H \\\\nHETATM 26 H4 UNL 1 -21.822 -5.480 32.224 1.00 0.00 H \\\\nHETATM 27 H5 UNL 1 -21.919 -6.763 34.337 1.00 0.00 H \\\\nHETATM 28 H6 UNL 1 -22.728 -5.668 36.400 1.00 0.00 H \\\\nHETATM 29 H7 UNL 1 -23.452 -3.306 36.358 1.00 0.00 H \\\\nHETATM 30 H8 UNL 1 -24.812 -4.953 28.715 1.00 0.00 H \\\\nHETATM 31 H9 UNL 1 -24.625 -3.417 29.628 1.00 0.00 H \\\\nHETATM 32 H10 UNL 1 -26.710 -7.941 31.731 1.00 0.00 H \\\\nHETATM 33 H11 UNL 1 -27.274 -6.560 33.696 1.00 0.00 H \\\\nHETATM 34 H12 UNL 1 -26.536 -4.235 33.803 1.00 0.00 H \\\\nHETATM 35 H13 UNL 1 -25.261 -3.280 31.956 1.00 0.00 H \\\\nENDMDL\\\\nMODEL\\\\nCOMPND 5zcu_ligand\\\\nHETATM 1 S1 UNL 1 -22.924 -4.581 30.300 1.00 0.00 S \\\\nHETATM 2 BR1 UNL 1 -26.441 -6.217 35.491 1.00 0.00 BR \\\\nHETATM 3 C1 UNL 1 -25.310 -5.526 34.075 1.00 0.00 C \\\\nHETATM 4 N1 UNL 1 -21.796 -5.861 30.169 1.00 0.00 N \\\\nHETATM 5 O1 UNL 1 -22.268 -3.274 30.237 1.00 0.00 O \\\\nHETATM 6 C2 UNL 1 -24.504 -4.374 34.126 1.00 0.00 C \\\\nHETATM 7 N2 UNL 1 -21.586 -7.082 32.784 1.00 0.00 N \\\\nHETATM 8 O2 UNL 1 -23.828 -4.521 29.149 1.00 0.00 O \\\\nHETATM 9 C3 UNL 1 -23.758 -4.019 33.031 1.00 0.00 C \\\\nHETATM 10 C4 UNL 1 -23.799 -4.803 31.870 1.00 0.00 C \\\\nHETATM 11 C5 UNL 1 -24.589 -5.943 31.814 1.00 0.00 C \\\\nHETATM 12 C6 UNL 1 -25.349 -6.304 32.922 1.00 0.00 C \\\\nHETATM 13 C7 UNL 1 -22.942 -2.874 33.061 1.00 0.00 C \\\\nHETATM 14 C8 UNL 1 -22.890 -2.092 34.203 1.00 0.00 C \\\\nHETATM 15 C9 UNL 1 -23.647 -2.446 35.311 1.00 0.00 C \\\\nHETATM 16 C10 UNL 1 -24.452 -3.579 35.285 1.00 0.00 C \\\\nHETATM 17 C11 UNL 1 -20.549 -5.807 30.912 1.00 0.00 C \\\\nHETATM 18 C12 UNL 1 -20.750 -6.094 32.399 1.00 0.00 C \\\\nHETATM 19 C13 UNL 1 -21.773 -7.337 34.098 1.00 0.00 C \\\\nHETATM 20 C14 UNL 1 -21.117 -6.582 35.054 1.00 0.00 C \\\\nHETATM 21 C15 UNL 1 -20.283 -5.584 34.673 1.00 0.00 C \\\\nHETATM 22 C16 UNL 1 -20.098 -5.329 33.355 1.00 0.00 C \\\\nHETATM 23 H1 UNL 1 -22.666 -5.667 29.597 1.00 0.00 H \\\\nHETATM 24 H2 UNL 1 -22.884 -1.071 30.916 1.00 0.00 H \\\\nHETATM 25 H3 UNL 1 -23.705 0.042 32.975 1.00 0.00 H \\\\nHETATM 26 H4 UNL 1 -21.822 -5.480 32.224 1.00 0.00 H \\\\nHETATM 27 H5 UNL 1 -21.919 -6.763 34.337 1.00 0.00 H \\\\nHETATM 28 H6 UNL 1 -22.728 -5.668 36.400 1.00 0.00 H \\\\nHETATM 29 H7 UNL 1 -23.452 -3.306 36.358 1.00 0.00 H \\\\nHETATM 30 H8 UNL 1 -24.812 -4.953 28.715 1.00 0.00 H \\\\nHETATM 31 H9 UNL 1 -24.625 -3.417 29.628 1.00 0.00 H \\\\nHETATM 32 H10 UNL 1 -26.710 -7.941 31.731 1.00 0.00 H \\\\nHETATM 33 H11 UNL 1 -27.274 -6.560 33.696 1.00 0.00 H \\\\nHETATM 34 H12 UNL 1 -26.536 -4.235 33.803 1.00 0.00 H \\\\nHETATM 35 H13 UNL 1 -25.261 -3.280 31.956 1.00 0.00 H \\\\nENDMDL\\\\nMODEL\\\\nCOMPND 5zcu_ligand\\\\nHETATM 1 S1 UNL 1 -21.854 -4.743 29.518 1.00 0.00 S \\\\nHETATM 2 BR1 UNL 1 -25.869 -6.577 34.263 1.00 0.00 BR \\\\nHETATM 3 C1 UNL 1 -24.617 -5.823 32.987 1.00 0.00 C \\\\nHETATM 4 N1 UNL 1 -20.626 -5.934 29.552 1.00 0.00 N \\\\nHETATM 5 O1 UNL 1 -21.295 -3.390 29.510 1.00 0.00 O \\\\nHETATM 6 C2 UNL 1 -23.892 -4.625 33.125 1.00 0.00 C \\\\nHETATM 7 N2 UNL 1 -20.748 -7.584 31.928 1.00 0.00 N \\\\nHETATM 8 O2 UNL 1 -22.611 -4.764 28.265 1.00 0.00 O \\\\nHETATM 9 C3 UNL 1 -23.042 -4.228 32.125 1.00 0.00 C \\\\nHETATM 10 C4 UNL 1 -22.897 -5.014 30.974 1.00 0.00 C \\\\nHETATM 11 C5 UNL 1 -23.607 -6.198 30.832 1.00 0.00 C \\\\nHETATM 12 C6 UNL 1 -24.472 -6.602 31.845 1.00 0.00 C \\\\nHETATM 13 C7 UNL 1 -22.303 -3.037 32.243 1.00 0.00 C \\\\nHETATM 14 C8 UNL 1 -22.434 -2.252 33.377 1.00 0.00 C \\\\nHETATM 15 C9 UNL 1 -23.297 -2.649 34.389 1.00 0.00 C \\\\nHETATM 16 C10 UNL 1 -24.026 -3.827 34.276 1.00 0.00 C \\\\nHETATM 17 C11 UNL 1 -19.577 -5.866 30.555 1.00 0.00 C \\\\nHETATM 18 C12 UNL 1 -20.025 -6.444 31.897 1.00 0.00 C \\\\nHETATM 19 C13 UNL 1 -21.152 -8.098 33.111 1.00 0.00 C \\\\nHETATM 20 C14 UNL 1 -20.834 -7.454 34.295 1.00 0.00 C \\\\nHETATM 21 C15 UNL 1 -20.114 -6.306 34.268 1.00 0.00 C \\\\nHETATM 22 C16 UNL 1 -19.712 -5.792 33.080 1.00 0.00 C \\\\nHETATM 23 H1 UNL 1 -22.666 -5.667 29.597 1.00 0.00 H \\\\nHETATM 24 H2 UNL 1 -22.884 -1.071 30.916 1.00 0.00 H \\\\nHETATM 25 H3 UNL 1 -23.705 0.042 32.975 1.00 0.00 H \\\\nHETATM 26 H4 UNL 1 -21.822 -5.480 32.224 1.00 0.00 H \\\\nHETATM 27 H5 UNL 1 -21.919 -6.763 34.337 1.00 0.00 H \\\\nHETATM 28 H6 UNL 1 -22.728 -5.668 36.400 1.00 0.00 H \\\\nHETATM 29 H7 UNL 1 -23.452 -3.306 36.358 1.00 0.00 H \\\\nHETATM 30 H8 UNL 1 -24.812 -4.953 28.715 1.00 0.00 H \\\\nHETATM 31 H9 UNL 1 -24.625 -3.417 29.628 1.00 0.00 H \\\\nHETATM 32 H10 UNL 1 -26.710 -7.941 31.731 1.00 0.00 H \\\\nHETATM 33 H11 UNL 1 -27.274 -6.560 33.696 1.00 0.00 H \\\\nHETATM 34 H12 UNL 1 -26.536 -4.235 33.803 1.00 0.00 H \\\\nHETATM 35 H13 UNL 1 -25.261 -3.280 31.956 1.00 0.00 H \\\\nENDMDL\\\\nMODEL\\\\nCOMPND 5zcu_ligand\\\\nHETATM 1 S1 UNL 1 -22.259 -3.968 29.239 1.00 0.00 S \\\\nHETATM 2 BR1 UNL 1 -26.494 -5.396 33.932 1.00 0.00 BR \\\\nHETATM 3 C1 UNL 1 -25.150 -4.776 32.678 1.00 0.00 C \\\\nHETATM 4 N1 UNL 1 -21.064 -5.188 29.351 1.00 0.00 N \\\\nHETATM 5 O1 UNL 1 -21.663 -2.633 29.177 1.00 0.00 O \\\\nHETATM 6 C2 UNL 1 -24.275 -3.688 32.849 1.00 0.00 C \\\\nHETATM 7 N2 UNL 1 -21.215 -6.458 31.964 1.00 0.00 N \\\\nHETATM 8 O2 UNL 1 -22.995 -4.029 27.975 1.00 0.00 O \\\\nHETATM 9 C3 UNL 1 -23.377 -3.377 31.860 1.00 0.00 C \\\\nHETATM 10 C4 UNL 1 -23.333 -4.143 30.687 1.00 0.00 C \\\\nHETATM 11 C5 UNL 1 -24.191 -5.219 30.512 1.00 0.00 C \\\\nHETATM 12 C6 UNL 1 -25.105 -5.535 31.513 1.00 0.00 C \\\\nHETATM 13 C7 UNL 1 -22.489 -2.297 32.012 1.00 0.00 C \\\\nHETATM 14 C8 UNL 1 -22.520 -1.534 33.168 1.00 0.00 C \\\\nHETATM 15 C9 UNL 1 -23.431 -1.844 34.169 1.00 0.00 C \\\\nHETATM 16 C10 UNL 1 -24.307 -2.913 34.022 1.00 0.00 C \\\\nHETATM 17 C11 UNL 1 -19.983 -5.058 30.312 1.00 0.00 C \\\\nHETATM 18 C12 UNL 1 -20.436 -5.379 31.736 1.00 0.00 C \\\\nHETATM 19 C13 UNL 1 -21.624 -6.745 33.220 1.00 0.00 C \\\\nHETATM 20 C14 UNL 1 -21.253 -5.931 34.276 1.00 0.00 C \\\\nHETATM 21 C15 UNL 1 -20.477 -4.843 34.051 1.00 0.00 C \\\\nHETATM 22 C16 UNL 1 -20.069 -4.556 32.791 1.00 0.00 C \\\\nHETATM 23 H1 UNL 1 -22.666 -5.667 29.597 1.00 0.00 H \\\\nHETATM 24 H2 UNL 1 -22.884 -1.071 30.916 1.00 0.00 H \\\\nHETATM 25 H3 UNL 1 -23.705 0.042 32.975 1.00 0.00 H \\\\nHETATM 26 H4 UNL 1 -21.822 -5.480 32.224 1.00 0.00 H \\\\nHETATM 27 H5 UNL 1 -21.919 -6.763 34.337 1.00 0.00 H \\\\nHETATM 28 H6 UNL 1 -22.728 -5.668 36.400 1.00 0.00 H \\\\nHETATM 29 H7 UNL 1 -23.452 -3.306 36.358 1.00 0.00 H \\\\nHETATM 30 H8 UNL 1 -24.812 -4.953 28.715 1.00 0.00 H \\\\nHETATM 31 H9 UNL 1 -24.625 -3.417 29.628 1.00 0.00 H \\\\nHETATM 32 H10 UNL 1 -26.710 -7.941 31.731 1.00 0.00 H \\\\nHETATM 33 H11 UNL 1 -27.274 -6.560 33.696 1.00 0.00 H \\\\nHETATM 34 H12 UNL 1 -26.536 -4.235 33.803 1.00 0.00 H \\\\nHETATM 35 H13 UNL 1 -25.261 -3.280 31.956 1.00 0.00 H \\\\nENDMDL\\\\nMODEL\\\\nCOMPND 5zcu_ligand\\\\nHETATM 1 S1 UNL 1 -22.327 -4.603 29.735 1.00 0.00 S \\\\nHETATM 2 BR1 UNL 1 -26.413 -5.603 34.664 1.00 0.00 BR \\\\nHETATM 3 C1 UNL 1 -25.099 -5.108 33.326 1.00 0.00 C \\\\nHETATM 4 N1 UNL 1 -21.142 -5.828 29.889 1.00 0.00 N \\\\nHETATM 5 O1 UNL 1 -21.720 -3.284 29.552 1.00 0.00 O \\\\nHETATM 6 C2 UNL 1 -24.170 -4.055 33.407 1.00 0.00 C \\\\nHETATM 7 N2 UNL 1 -21.250 -7.001 32.517 1.00 0.00 N \\\\nHETATM 8 O2 UNL 1 -23.114 -4.746 28.508 1.00 0.00 O \\\\nHETATM 9 C3 UNL 1 -23.303 -3.834 32.367 1.00 0.00 C \\\\nHETATM 10 C4 UNL 1 -23.344 -4.657 31.233 1.00 0.00 C \\\\nHETATM 11 C5 UNL 1 -24.256 -5.699 31.148 1.00 0.00 C \\\\nHETATM 12 C6 UNL 1 -25.138 -5.923 32.200 1.00 0.00 C \\\\nHETATM 13 C7 UNL 1 -22.361 -2.791 32.428 1.00 0.00 C \\\\nHETATM 14 C8 UNL 1 -22.308 -1.972 33.544 1.00 0.00 C \\\\nHETATM 15 C9 UNL 1 -23.188 -2.190 34.596 1.00 0.00 C \\\\nHETATM 16 C10 UNL 1 -24.116 -3.223 34.540 1.00 0.00 C \\\\nHETATM 17 C11 UNL 1 -20.033 -5.652 30.811 1.00 0.00 C \\\\nHETATM 18 C12 UNL 1 -20.430 -5.961 32.255 1.00 0.00 C \\\\nHETATM 19 C13 UNL 1 -21.609 -7.276 33.791 1.00 0.00 C \\\\nHETATM 20 C14 UNL 1 -21.145 -6.489 34.830 1.00 0.00 C \\\\nHETATM 21 C15 UNL 1 -20.327 -5.440 34.571 1.00 0.00 C \\\\nHETATM 22 C16 UNL 1 -19.970 -5.165 33.293 1.00 0.00 C \\\\nHETATM 23 H1 UNL 1 -22.666 -5.667 29.597 1.00 0.00 H \\\\nHETATM 24 H2 UNL 1 -22.884 -1.071 30.916 1.00 0.00 H \\\\nHETATM 25 H3 UNL 1 -23.705 0.042 32.975 1.00 0.00 H \\\\nHETATM 26 H4 UNL 1 -21.822 -5.480 32.224 1.00 0.00 H \\\\nHETATM 27 H5 UNL 1 -21.919 -6.763 34.337 1.00 0.00 H \\\\nHETATM 28 H6 UNL 1 -22.728 -5.668 36.400 1.00 0.00 H \\\\nHETATM 29 H7 UNL 1 -23.452 -3.306 36.358 1.00 0.00 H \\\\nHETATM 30 H8 UNL 1 -24.812 -4.953 28.715 1.00 0.00 H \\\\nHETATM 31 H9 UNL 1 -24.625 -3.417 29.628 1.00 0.00 H \\\\nHETATM 32 H10 UNL 1 -26.710 -7.941 31.731 1.00 0.00 H \\\\nHETATM 33 H11 UNL 1 -27.274 -6.560 33.696 1.00 0.00 H \\\\nHETATM 34 H12 UNL 1 -26.536 -4.235 33.803 1.00 0.00 H \\\\nHETATM 35 H13 UNL 1 -25.261 -3.280 31.956 1.00 0.00 H \\\\nENDMDL\\\\nMODEL\\\\nCOMPND 5zcu_ligand\\\\nHETATM 1 S1 UNL 1 -22.656 -4.927 29.771 1.00 0.00 S \\\\nHETATM 2 BR1 UNL 1 -26.708 -5.187 34.821 1.00 0.00 BR \\\\nHETATM 3 C1 UNL 1 -25.392 -4.905 33.425 1.00 0.00 C \\\\nHETATM 4 N1 UNL 1 -21.533 -6.189 30.040 1.00 0.00 N \\\\nHETATM 5 O1 UNL 1 -21.986 -3.668 29.442 1.00 0.00 O \\\\nHETATM 6 C2 UNL 1 -24.405 -3.904 33.386 1.00 0.00 C \\\\nHETATM 7 N2 UNL 1 -21.704 -7.426 32.667 1.00 0.00 N \\\\nHETATM 8 O2 UNL 1 -23.470 -5.157 28.575 1.00 0.00 O \\\\nHETATM 9 C3 UNL 1 -23.544 -3.840 32.320 1.00 0.00 C \\\\nHETATM 10 C4 UNL 1 -23.650 -4.770 31.278 1.00 0.00 C \\\\nHETATM 11 C5 UNL 1 -24.619 -5.763 31.310 1.00 0.00 C \\\\nHETATM 12 C6 UNL 1 -25.494 -5.828 32.389 1.00 0.00 C \\\\nHETATM 13 C7 UNL 1 -22.546 -2.850 32.263 1.00 0.00 C \\\\nHETATM 14 C8 UNL 1 -22.430 -1.926 33.288 1.00 0.00 C \\\\nHETATM 15 C9 UNL 1 -23.302 -1.986 34.367 1.00 0.00 C \\\\nHETATM 16 C10 UNL 1 -24.286 -2.965 34.427 1.00 0.00 C \\\\nHETATM 17 C11 UNL 1 -20.473 -6.020 31.019 1.00 0.00 C \\\\nHETATM 18 C12 UNL 1 -20.944 -6.333 32.439 1.00 0.00 C \\\\nHETATM 19 C13 UNL 1 -22.129 -7.705 33.919 1.00 0.00 C \\\\nHETATM 20 C14 UNL 1 -21.796 -6.869 34.971 1.00 0.00 C \\\\nHETATM 21 C15 UNL 1 -21.039 -5.768 34.745 1.00 0.00 C \\\\nHETATM 22 C16 UNL 1 -20.615 -5.488 33.489 1.00 0.00 C \\\\nHETATM 23 H1 UNL 1 -22.666 -5.667 29.597 1.00 0.00 H \\\\nHETATM 24 H2 UNL 1 -22.884 -1.071 30.916 1.00 0.00 H \\\\nHETATM 25 H3 UNL 1 -23.705 0.042 32.975 1.00 0.00 H \\\\nHETATM 26 H4 UNL 1 -21.822 -5.480 32.224 1.00 0.00 H \\\\nHETATM 27 H5 UNL 1 -21.919 -6.763 34.337 1.00 0.00 H \\\\nHETATM 28 H6 UNL 1 -22.728 -5.668 36.400 1.00 0.00 H \\\\nHETATM 29 H7 UNL 1 -23.452 -3.306 36.358 1.00 0.00 H \\\\nHETATM 30 H8 UNL 1 -24.812 -4.953 28.715 1.00 0.00 H \\\\nHETATM 31 H9 UNL 1 -24.625 -3.417 29.628 1.00 0.00 H \\\\nHETATM 32 H10 UNL 1 -26.710 -7.941 31.731 1.00 0.00 H \\\\nHETATM 33 H11 UNL 1 -27.274 -6.560 33.696 1.00 0.00 H \\\\nHETATM 34 H12 UNL 1 -26.536 -4.235 33.803 1.00 0.00 H \\\\nHETATM 35 H13 UNL 1 -25.261 -3.280 31.956 1.00 0.00 H \\\\nENDMDL\\\\nMODEL\\\\nCOMPND 5zcu_ligand\\\\nHETATM 1 S1 UNL 1 -22.725 -4.540 29.544 1.00 0.00 S \\\\nHETATM 2 BR1 UNL 1 -26.954 -4.743 34.450 1.00 0.00 BR \\\\nHETATM 3 C1 UNL 1 -25.596 -4.470 33.092 1.00 0.00 C \\\\nHETATM 4 N1 UNL 1 -21.611 -5.794 29.882 1.00 0.00 N \\\\nHETATM 5 O1 UNL 1 -22.044 -3.285 29.220 1.00 0.00 O \\\\nHETATM 6 C2 UNL 1 -24.645 -3.434 33.046 1.00 0.00 C \\\\nHETATM 7 N2 UNL 1 -21.833 -6.753 32.617 1.00 0.00 N \\\\nHETATM 8 O2 UNL 1 -23.488 -4.794 28.320 1.00 0.00 O \\\\nHETATM 9 C3 UNL 1 -23.748 -3.382 32.010 1.00 0.00 C \\\\nHETATM 10 C4 UNL 1 -23.780 -4.358 31.005 1.00 0.00 C \\\\nHETATM 11 C5 UNL 1 -24.713 -5.385 31.045 1.00 0.00 C \\\\nHETATM 12 C6 UNL 1 -25.626 -5.438 32.094 1.00 0.00 C \\\\nHETATM 13 C7 UNL 1 -22.786 -2.358 31.946 1.00 0.00 C \\\\nHETATM 14 C8 UNL 1 -22.742 -1.388 32.934 1.00 0.00 C \\\\nHETATM 15 C9 UNL 1 -23.652 -1.435 33.982 1.00 0.00 C \\\\nHETATM 16 C10 UNL 1 -24.601 -2.448 34.048 1.00 0.00 C \\\\nHETATM 17 C11 UNL 1 -20.542 -5.575 30.842 1.00 0.00 C \\\\nHETATM 18 C12 UNL 1 -21.023 -5.725 32.284 1.00 0.00 C \\\\nHETATM 19 C13 UNL 1 -22.267 -6.888 33.890 1.00 0.00 C \\\\nHETATM 20 C14 UNL 1 -21.890 -5.971 34.856 1.00 0.00 C \\\\nHETATM 21 C15 UNL 1 -21.082 -4.935 34.525 1.00 0.00 C \\\\nHETATM 22 C16 UNL 1 -20.650 -4.800 33.248 1.00 0.00 C \\\\nHETATM 23 H1 UNL 1 -22.666 -5.667 29.597 1.00 0.00 H \\\\nHETATM 24 H2 UNL 1 -22.884 -1.071 30.916 1.00 0.00 H \\\\nHETATM 25 H3 UNL 1 -23.705 0.042 32.975 1.00 0.00 H \\\\nHETATM 26 H4 UNL 1 -21.822 -5.480 32.224 1.00 0.00 H \\\\nHETATM 27 H5 UNL 1 -21.919 -6.763 34.337 1.00 0.00 H \\\\nHETATM 28 H6 UNL 1 -22.728 -5.668 36.400 1.00 0.00 H \\\\nHETATM 29 H7 UNL 1 -23.452 -3.306 36.358 1.00 0.00 H \\\\nHETATM 30 H8 UNL 1 -24.812 -4.953 28.715 1.00 0.00 H \\\\nHETATM 31 H9 UNL 1 -24.625 -3.417 29.628 1.00 0.00 H \\\\nHETATM 32 H10 UNL 1 -26.710 -7.941 31.731 1.00 0.00 H \\\\nHETATM 33 H11 UNL 1 -27.274 -6.560 33.696 1.00 0.00 H \\\\nHETATM 34 H12 UNL 1 -26.536 -4.235 33.803 1.00 0.00 H \\\\nHETATM 35 H13 UNL 1 -25.261 -3.280 31.956 1.00 0.00 H \\\\nENDMDL\\\\n\"\n ],\n \"ligand_positions\": [\n \"5zcu_ligand_rank1\\\\n RDKit 3D\\\\n\\\\n 22 24 0 0 0 0 0 0 0 0999 V2000\\\\n -20.9518 -5.4917 30.6318 S 0 0 1 0 0 6 0 0 0 0 0 0\\\\n -24.0338 -4.4219 36.2310 Br 0 0 0 0 0 0 0 0 0 0 0 0\\\\n -23.1975 -4.5119 34.4831 C 0 0 0 0 0 0 0 0 0 0 0 0\\\\n -22.0616 -5.6347 29.3379 N 0 0 0 0 0 0 0 0 0 0 0 0\\\\n -20.2600 -6.7548 30.8927 O 0 0 0 0 0 0 0 0 0 0 0 0\\\\n -23.2358 -3.5279 33.4783 C 0 0 0 0 0 0 0 0 0 0 0 0\\\\n -24.4589 -7.0401 31.3134 N 0 0 0 0 0 0 0 0 0 0 0 0\\\\n -19.8367 -4.5988 30.3080 O 0 0 0 0 0 0 0 0 0 0 0 0\\\\n -22.5885 -3.7470 32.2892 C 0 0 0 0 0 0 0 0 0 0 0 0\\\\n -21.8919 -4.9449 32.0804 C 0 0 0 0 0 0 0 0 0 0 0 0\\\\n -21.8473 -5.9192 33.0675 C 0 0 0 0 0 0 0 0 0 0 0 0\\\\n -22.5053 -5.7002 34.2742 C 0 0 0 0 0 0 0 0 0 0 0 0\\\\n -22.6087 -2.7755 31.2726 C 0 0 0 0 0 0 0 0 0 0 0 0\\\\n -23.2913 -1.5857 31.4672 C 0 0 0 0 0 0 0 0 0 0 0 0\\\\n -23.9515 -1.3627 32.6683 C 0 0 0 0 0 0 0 0 0 0 0 0\\\\n -23.9294 -2.3203 33.6752 C 0 0 0 0 0 0 0 0 0 0 0 0\\\\n -23.0063 -6.7385 29.3119 C 0 0 0 0 0 0 0 0 0 0 0 0\\\\n -24.2676 -6.4369 30.1206 C 0 0 0 0 0 0 0 0 0 0 0 0\\\\n -25.5752 -6.7823 32.0310 C 0 0 0 0 0 0 0 0 0 0 0 0\\\\n -26.5299 -5.9070 31.5435 C 0 0 0 0 0 0 0 0 0 0 0 0\\\\n -26.3448 -5.3047 30.3437 C 0 0 0 0 0 0 0 0 0 0 0 0\\\\n -25.2262 -5.5656 29.6251 C 0 0 0 0 0 0 0 0 0 0 0 0\\\\n 1 4 1 6\\\\n 1 5 2 0\\\\n 1 8 2 0\\\\n 1 10 1 0\\\\n 3 2 1 0\\\\n 6 3 2 0\\\\n 12 3 1 0\\\\n 17 4 1 1\\\\n 9 6 1 0\\\\n 6 16 1 0\\\\n 18 7 2 0\\\\n 7 19 1 0\\\\n 10 9 2 0\\\\n 9 13 1 0\\\\n 10 11 1 0\\\\n 11 12 2 0\\\\n 13 14 2 0\\\\n 14 15 1 0\\\\n 16 15 2 0\\\\n 17 18 1 0\\\\n 18 22 1 0\\\\n 19 20 2 0\\\\n 20 21 1 0\\\\n 21 22 2 0\\\\nM END\\\\n\u003e \u003c_TriposChargeType\u003e (1) \\\\nGAST_HUCK\\\\n\\\\n$$$$\\\\n\",\n \"5zcu_ligand_rank2\\\\n RDKit 3D\\\\n\\\\n 22 24 0 0 0 0 0 0 0 0999 V2000\\\\n -22.7246 -4.5402 29.5439 S 0 0 1 0 0 6 0 0 0 0 0 0\\\\n -26.9539 -4.7426 34.4498 Br 0 0 0 0 0 0 0 0 0 0 0 0\\\\n -25.5961 -4.4698 33.0916 C 0 0 0 0 0 0 0 0 0 0 0 0\\\\n -21.6110 -5.7938 29.8819 N 0 0 0 0 0 0 0 0 0 0 0 0\\\\n -22.0442 -3.2855 29.2199 O 0 0 0 0 0 0 0 0 0 0 0 0\\\\n -24.6455 -3.4336 33.0457 C 0 0 0 0 0 0 0 0 0 0 0 0\\\\n -21.8335 -6.7528 32.6169 N 0 0 0 0 0 0 0 0 0 0 0 0\\\\n -23.4882 -4.7936 28.3198 O 0 0 0 0 0 0 0 0 0 0 0 0\\\\n -23.7482 -3.3816 32.0097 C 0 0 0 0 0 0 0 0 0 0 0 0\\\\n -23.7797 -4.3582 31.0051 C 0 0 0 0 0 0 0 0 0 0 0 0\\\\n -24.7125 -5.3847 31.0447 C 0 0 0 0 0 0 0 0 0 0 0 0\\\\n -25.6256 -5.4385 32.0937 C 0 0 0 0 0 0 0 0 0 0 0 0\\\\n -22.7857 -2.3582 31.9460 C 0 0 0 0 0 0 0 0 0 0 0 0\\\\n -22.7419 -1.3882 32.9342 C 0 0 0 0 0 0 0 0 0 0 0 0\\\\n -23.6518 -1.4355 33.9820 C 0 0 0 0 0 0 0 0 0 0 0 0\\\\n -24.6012 -2.4483 34.0483 C 0 0 0 0 0 0 0 0 0 0 0 0\\\\n -20.5421 -5.5747 30.8415 C 0 0 0 0 0 0 0 0 0 0 0 0\\\\n -21.0230 -5.7252 32.2845 C 0 0 0 0 0 0 0 0 0 0 0 0\\\\n -22.2671 -6.8883 33.8901 C 0 0 0 0 0 0 0 0 0 0 0 0\\\\n -21.8902 -5.9713 34.8557 C 0 0 0 0 0 0 0 0 0 0 0 0\\\\n -21.0822 -4.9348 34.5246 C 0 0 0 0 0 0 0 0 0 0 0 0\\\\n -20.6500 -4.7996 33.2477 C 0 0 0 0 0 0 0 0 0 0 0 0\\\\n 1 4 1 1\\\\n 1 5 2 0\\\\n 1 8 2 0\\\\n 1 10 1 0\\\\n 3 2 1 0\\\\n 6 3 2 0\\\\n 12 3 1 0\\\\n 17 4 1 1\\\\n 9 6 1 0\\\\n 6 16 1 0\\\\n 18 7 2 0\\\\n 7 19 1 0\\\\n 10 9 2 0\\\\n 9 13 1 0\\\\n 10 11 1 0\\\\n 11 12 2 0\\\\n 13 14 2 0\\\\n 14 15 1 0\\\\n 16 15 2 0\\\\n 17 18 1 0\\\\n 18 22 1 0\\\\n 19 20 2 0\\\\n 20 21 1 0\\\\n 21 22 2 0\\\\nM END\\\\n\u003e \u003c_TriposChargeType\u003e (1) \\\\nGAST_HUCK\\\\n\\\\n$$$$\\\\n\"\n ],\n \"position_confidence\": [\n -0.5491877794265747,\n -2.936824321746826\n ],\n \"protein\": \"REMARK Selection 'chain A or chain C'\\\\nATOM 1 N ALA A 58 -11.274 42.755 37.461 1.00 0.00 N \\\\nATOM 2 CA ALA A 58 -12.250 43.198 38.453 1.00 0.00 C \\\\nATOM 3 C ALA A 58 -12.711 42.083 39.413 1.00 0.00 C \\\\nATOM 4 O ALA A 58 -12.736 42.303 40.624 1.00 0.00 O \\\\nATOM 5 CB ALA A 58 -13.458 43.839 37.758 1.00 0.00 C \\\\nATOM 6 HA ALA A 58 -11.798 43.856 39.004 1.00 0.00 H \\\\nATOM 7 HB1 ALA A 58 -14.099 44.129 38.425 1.00 0.00 H \\\\nATOM 8 HB2 ALA A 58 -13.164 44.604 37.238 1.00 0.00 H \\\\nATOM 9 HB3 ALA A 58 -13.875 43.190 37.170 1.00 0.00 H \\\\nATOM 10 N PRO A 59 -13.078 40.899 38.906 1.00 0.00 N \\\\nATOM 11 CA PRO A 59 -13.494 39.830 39.821 1.00 0.00 C \\\\nATOM 12 C PRO A 59 -12.309 39.217 40.551 1.00 0.00 C \\\\nATOM 13 O PRO A 59 -11.178 39.207 40.060 1.00 0.00 O \\\\nATOM 14 CB PRO A 59 -14.168 38.811 38.896 1.00 0.00 C \\\\nATOM 15 CG PRO A 59 -13.508 39.006 37.602 1.00 0.00 C \\\\nATOM 16 CD PRO A 59 -13.226 40.475 37.499 1.00 0.00 C \\\\nATOM 17 HA PRO A 59 -14.080 40.150 40.524 1.00 0.00 H \\\\nATOM 18 HB2 PRO A 59 -14.049 37.905 39.221 1.00 0.00 H \\\\nATOM 19 HB3 PRO A 59 -15.123 38.967 38.833 1.00 0.00 H \\\\nATOM 20 HG2 PRO A 59 -12.688 38.491 37.549 1.00 0.00 H \\\\nATOM 21 HG3 PRO A 59 -14.077 38.710 36.874 1.00 0.00 H \\\\nATOM 22 HD2 PRO A 59 -12.420 40.649 36.987 1.00 0.00 H \\\\nATOM 23 HD3 PRO A 59 -13.950 40.947 37.058 1.00 0.00 H \\\\nATOM 24 N VAL A 60 -12.594 38.690 41.740 1.00 0.00 N \\\\nATOM 25 CA VAL A 60 -11.586 38.156 42.650 1.00 0.00 C \\\\nATOM 26 C VAL A 60 -11.981 36.723 42.978 1.00 0.00 C \\\\nATOM 27 O VAL A 60 -12.982 36.492 43.668 1.00 0.00 O \\\\nATOM 28 CB VAL A 60 -11.461 39.005 43.922 1.00 0.00 C \\\\nATOM 29 CG1 VAL A 60 -10.662 38.269 44.982 1.00 0.00 C \\\\nATOM 30 CG2 VAL A 60 -10.824 40.352 43.600 1.00 0.00 C \\\\nATOM 31 H VAL A 60 -13.396 38.632 42.045 1.00 0.00 H \\\\nATOM 32 HA VAL A 60 -10.713 38.178 42.227 1.00 0.00 H \\\\nATOM 33 HB VAL A 60 -12.351 39.164 44.274 1.00 0.00 H \\\\nATOM 34 HG11 VAL A 60 -10.594 38.820 45.777 1.00 0.00 H \\\\nATOM 35 HG12 VAL A 60 -11.108 37.437 45.204 1.00 0.00 H \\\\nATOM 36 HG13 VAL A 60 -9.773 38.079 44.644 1.00 0.00 H \\\\nATOM 37 HG21 VAL A 60 -10.751 40.878 44.412 1.00 0.00 H \\\\nATOM 38 HG22 VAL A 60 -9.940 40.211 43.226 1.00 0.00 H \\\\nATOM 39 HG23 VAL A 60 -11.375 40.825 42.957 1.00 0.00 H \\\\nATOM 40 N TRP A 61 -11.212 35.757 42.475 1.00 0.00 N \\\\nATOM 41 CA TRP A 61 -11.581 34.357 42.626 1.00 0.00 C \\\\nATOM 42 C TRP A 61 -10.341 33.472 42.633 1.00 0.00 C \\\\nATOM 43 O TRP A 61 -9.248 33.889 42.242 1.00 0.00 O \\\\nATOM 44 CB TRP A 61 -12.520 33.905 41.504 1.00 0.00 C \\\\nATOM 45 CG TRP A 61 -11.787 33.635 40.228 1.00 0.00 C \\\\nATOM 46 CD1 TRP A 61 -11.367 32.422 39.758 1.00 0.00 C \\\\nATOM 47 CD2 TRP A 61 -11.367 34.606 39.263 1.00 0.00 C \\\\nATOM 48 NE1 TRP A 61 -10.719 32.580 38.558 1.00 0.00 N \\\\nATOM 49 CE2 TRP A 61 -10.705 33.910 38.231 1.00 0.00 C \\\\nATOM 50 CE3 TRP A 61 -11.491 35.995 39.167 1.00 0.00 C \\\\nATOM 51 CZ2 TRP A 61 -10.170 34.556 37.119 1.00 0.00 C \\\\nATOM 52 CZ3 TRP A 61 -10.959 36.635 38.064 1.00 0.00 C \\\\nATOM 53 CH2 TRP A 61 -10.306 35.917 37.054 1.00 0.00 C \\\\nATOM 54 H TRP A 61 -10.479 35.893 42.047 1.00 0.00 H \\\\nATOM 55 HA TRP A 61 -12.044 34.270 43.474 1.00 0.00 H \\\\nATOM 56 HB2 TRP A 61 -12.990 33.103 41.781 1.00 0.00 H \\\\nATOM 57 HB3 TRP A 61 -13.191 34.588 41.351 1.00 0.00 H \\\\nATOM 58 HD1 TRP A 61 -11.501 31.608 40.188 1.00 0.00 H \\\\nATOM 59 HE1 TRP A 61 -10.377 31.946 38.088 1.00 0.00 H \\\\nATOM 60 HE3 TRP A 61 -11.923 36.479 39.833 1.00 0.00 H \\\\nATOM 61 HZ2 TRP A 61 -9.737 34.081 36.447 1.00 0.00 H \\\\nATOM 62 HZ3 TRP A 61 -11.036 37.559 37.991 1.00 0.00 H \\\\nATOM 63 HH2 TRP A 61 -9.957 36.375 36.323 1.00 0.00 H \\\\nATOM 64 N GLY A 62 -10.541 32.233 43.085 1.00 0.00 N \\\\nATOM 65 CA GLY A 62 -9.531 31.201 42.968 1.00 0.00 C \\\\nATOM 66 C GLY A 62 -10.172 29.899 42.529 1.00 0.00 C \\\\nATOM 67 O GLY A 62 -11.375 29.688 42.706 1.00 0.00 O \\\\nATOM 68 H GLY A 62 -11.267 31.975 43.466 1.00 0.00 H \\\\nATOM 69 HA2 GLY A 62 -8.855 31.470 42.327 1.00 0.00 H \\\\nATOM 70 HA3 GLY A 62 -9.082 31.079 43.819 1.00 0.00 H \\\\nATOM 71 N CYS A 63 -9.349 29.018 41.957 1.00 0.00 N \\\\nATOM 72 CA CYS A 63 -9.844 27.768 41.386 1.00 0.00 C \\\\nATOM 73 C CYS A 63 -8.831 26.654 41.606 1.00 0.00 C \\\\nATOM 74 O CYS A 63 -7.662 26.795 41.236 1.00 0.00 O \\\\nATOM 75 CB CYS A 63 -10.144 27.930 39.892 1.00 0.00 C \\\\nATOM 76 SG CYS A 63 -10.815 26.447 39.104 1.00 0.00 S \\\\nATOM 77 H CYS A 63 -8.499 29.128 41.890 1.00 0.00 H \\\\nATOM 78 HA CYS A 63 -10.671 27.533 41.835 1.00 0.00 H \\\\nATOM 79 HB2 CYS A 63 -10.774 28.658 39.776 1.00 0.00 H \\\\nATOM 80 HB3 CYS A 63 -9.328 28.186 39.435 1.00 0.00 H \\\\nATOM 81 HG CYS A 63 -11.250 26.730 38.022 1.00 0.00 H \\\\nATOM 82 N ALA A 64 -9.282 25.553 42.210 1.00 0.00 N \\\\nATOM 83 CA ALA A 64 -8.466 24.367 42.441 1.00 0.00 C \\\\nATOM 84 C ALA A 64 -9.216 23.128 41.964 1.00 0.00 C \\\\nATOM 85 O ALA A 64 -10.434 23.028 42.140 1.00 0.00 O \\\\nATOM 86 CB ALA A 64 -8.097 24.230 43.925 1.00 0.00 C \\\\nATOM 87 H ALA A 64 -10.087 25.476 42.502 1.00 0.00 H \\\\nATOM 88 HA ALA A 64 -7.642 24.457 41.938 1.00 0.00 H \\\\nATOM 89 HB1 ALA A 64 -7.555 23.435 44.052 1.00 0.00 H \\\\nATOM 90 HB2 ALA A 64 -7.596 25.011 44.207 1.00 0.00 H \\\\nATOM 91 HB3 ALA A 64 -8.906 24.157 44.455 1.00 0.00 H \\\\nATOM 92 N SER A 65 -8.485 22.180 41.373 1.00 0.00 N \\\\nATOM 93 CA SER A 65 -9.092 20.980 40.808 1.00 0.00 C \\\\nATOM 94 C SER A 65 -8.072 19.845 40.805 1.00 0.00 C \\\\nATOM 95 O SER A 65 -6.866 20.082 40.693 1.00 0.00 O \\\\nATOM 96 CB SER A 65 -9.618 21.237 39.392 1.00 0.00 C \\\\nATOM 97 OG SER A 65 -8.563 21.547 38.501 1.00 0.00 O \\\\nATOM 98 H SER A 65 -7.630 22.217 41.290 1.00 0.00 H \\\\nATOM 99 HA SER A 65 -9.850 20.728 41.359 1.00 0.00 H \\\\nATOM 100 HB2 SER A 65 -10.093 20.454 39.074 1.00 0.00 H \\\\nATOM 101 HB3 SER A 65 -10.255 21.968 39.409 1.00 0.00 H \\\\nATOM 102 HG SER A 65 -7.828 21.347 38.856 1.00 0.00 H \\\\nATOM 103 N THR A 66 -8.570 18.610 40.931 1.00 0.00 N \\\\nATOM 104 CA THR A 66 -7.706 17.432 40.942 1.00 0.00 C \\\\nATOM 105 C THR A 66 -8.520 16.178 40.649 1.00 0.00 C \\\\nATOM 106 O THR A 66 -9.709 16.106 40.950 1.00 0.00 O \\\\nATOM 107 CB THR A 66 -6.975 17.264 42.281 1.00 0.00 C \\\\nATOM 108 OG1 THR A 66 -6.072 16.154 42.197 1.00 0.00 O \\\\nATOM 109 CG2 THR A 66 -7.966 17.017 43.408 1.00 0.00 C \\\\nATOM 110 H THR A 66 -9.408 18.436 41.011 1.00 0.00 H \\\\nATOM 111 HA THR A 66 -7.038 17.562 40.250 1.00 0.00 H \\\\nATOM 112 HB THR A 66 -6.484 18.079 42.468 1.00 0.00 H \\\\nATOM 113 HG1 THR A 66 -5.774 15.977 42.962 1.00 0.00 H \\\\nATOM 114 HG21 THR A 66 -7.486 16.914 44.244 1.00 0.00 H \\\\nATOM 115 HG22 THR A 66 -8.574 17.770 43.475 1.00 0.00 H \\\\nATOM 116 HG23 THR A 66 -8.471 16.210 43.224 1.00 0.00 H \\\\nATOM 117 N ARG A 67 -7.862 15.208 40.016 1.00 0.00 N \\\\nATOM 118 CA ARG A 67 -8.376 13.842 39.909 1.00 0.00 C \\\\nATOM 119 C ARG A 67 -8.842 13.277 41.253 1.00 0.00 C \\\\nATOM 120 O ARG A 67 -9.943 12.719 41.347 1.00 0.00 O \\\\nATOM 121 CB ARG A 67 -7.315 12.896 39.290 1.00 0.00 C \\\\nATOM 122 CG ARG A 67 -6.827 13.166 37.841 1.00 0.00 C \\\\nATOM 123 CD ARG A 67 -5.979 14.426 37.765 1.00 0.00 C \\\\nATOM 124 NE ARG A 67 -5.623 14.728 36.395 1.00 0.00 N \\\\nATOM 125 CZ ARG A 67 -5.115 15.887 35.997 1.00 0.00 C \\\\nATOM 126 NH1 ARG A 67 -4.931 16.870 36.867 1.00 0.00 N \\\\nATOM 127 NH2 ARG A 67 -4.821 16.076 34.718 1.00 0.00 N \\\\nATOM 128 H ARG A 67 -7.100 15.324 39.634 1.00 0.00 H \\\\nATOM 129 HA ARG A 67 -9.149 13.891 39.325 1.00 0.00 H \\\\nATOM 130 HB2 ARG A 67 -6.537 12.908 39.869 1.00 0.00 H \\\\nATOM 131 HB3 ARG A 67 -7.674 11.995 39.316 1.00 0.00 H \\\\nATOM 132 HG2 ARG A 67 -6.311 12.408 37.525 1.00 0.00 H \\\\nATOM 133 HG3 ARG A 67 -7.592 13.253 37.251 1.00 0.00 H \\\\nATOM 134 HD2 ARG A 67 -6.466 15.172 38.148 1.00 0.00 H \\\\nATOM 135 HD3 ARG A 67 -5.174 14.311 38.294 1.00 0.00 H \\\\nATOM 136 HE ARG A 67 -5.749 14.118 35.802 1.00 0.00 H \\\\nATOM 137 HH11 ARG A 67 -5.141 16.758 37.693 1.00 0.00 H \\\\nATOM 138 HH12 ARG A 67 -4.601 17.620 36.605 1.00 0.00 H \\\\nATOM 139 HH21 ARG A 67 -4.960 15.448 34.147 1.00 0.00 H \\\\nATOM 140 HH22 ARG A 67 -4.492 16.827 34.459 1.00 0.00 H \\\\nATOM 141 N GLY A 68 -8.002 13.388 42.297 1.00 0.00 N \\\\nATOM 142 CA GLY A 68 -8.226 12.647 43.531 1.00 0.00 C \\\\nATOM 143 C GLY A 68 -7.802 11.192 43.372 1.00 0.00 C \\\\nATOM 144 O GLY A 68 -6.884 10.883 42.620 1.00 0.00 O \\\\nATOM 145 H GLY A 68 -7.302 13.887 42.302 1.00 0.00 H \\\\nATOM 146 HA2 GLY A 68 -7.727 13.057 44.255 1.00 0.00 H \\\\nATOM 147 HA3 GLY A 68 -9.164 12.690 43.774 1.00 0.00 H \\\\nATOM 148 N ARG A 69 -8.490 10.283 44.074 1.00 0.00 N \\\\nATOM 149 CA ARG A 69 -8.308 8.858 43.778 1.00 0.00 C \\\\nATOM 150 C ARG A 69 -8.915 8.429 42.473 1.00 0.00 C \\\\nATOM 151 O ARG A 69 -8.605 7.318 42.016 1.00 0.00 O \\\\nATOM 152 CB ARG A 69 -8.914 7.947 44.832 1.00 0.00 C \\\\nATOM 153 CG ARG A 69 -7.986 7.571 45.954 1.00 0.00 C \\\\nATOM 154 CD ARG A 69 -7.994 8.692 47.040 1.00 0.00 C \\\\nATOM 155 NE ARG A 69 -7.086 8.413 48.165 1.00 0.00 N \\\\nATOM 156 CZ ARG A 69 -7.134 8.968 49.384 1.00 0.00 C \\\\nATOM 157 NH1 ARG A 69 -8.100 9.814 49.713 1.00 0.00 N \\\\nATOM 158 NH2 ARG A 69 -6.210 8.647 50.303 1.00 0.00 N \\\\nATOM 159 H ARG A 69 -9.048 10.462 44.704 1.00 0.00 H \\\\nATOM 160 HA ARG A 69 -7.343 8.768 43.750 1.00 0.00 H \\\\nATOM 161 HB2 ARG A 69 -9.694 8.384 45.208 1.00 0.00 H \\\\nATOM 162 HB3 ARG A 69 -9.223 7.135 44.400 1.00 0.00 H \\\\nATOM 163 HG2 ARG A 69 -8.262 6.727 46.345 1.00 0.00 H \\\\nATOM 164 HG3 ARG A 69 -7.087 7.445 45.613 1.00 0.00 H \\\\nATOM 165 HD2 ARG A 69 -7.742 9.534 46.630 1.00 0.00 H \\\\nATOM 166 HD3 ARG A 69 -8.896 8.800 47.379 1.00 0.00 H \\\\nATOM 167 HE ARG A 69 -6.463 7.837 48.026 1.00 0.00 H \\\\nATOM 168 HH11 ARG A 69 -8.709 10.015 49.140 1.00 0.00 H \\\\nATOM 169 HH12 ARG A 69 -8.117 10.162 50.499 1.00 0.00 H \\\\nATOM 170 HH21 ARG A 69 -5.588 8.086 50.109 1.00 0.00 H \\\\nATOM 171 HH22 ARG A 69 -6.240 9.003 51.085 1.00 0.00 H \\\\nATOM 172 N SER A 70 -9.695 9.287 41.835 1.00 0.00 N \\\\nATOM 173 CA SER A 70 -10.378 8.832 40.646 1.00 0.00 C \\\\nATOM 174 C SER A 70 -9.368 8.558 39.541 1.00 0.00 C \\\\nATOM 175 O SER A 70 -8.303 9.171 39.472 1.00 0.00 O \\\\nATOM 176 CB SER A 70 -11.411 9.859 40.197 1.00 0.00 C \\\\nATOM 177 OG SER A 70 -12.581 9.824 40.997 1.00 0.00 O \\\\nATOM 178 H SER A 70 -9.837 10.104 42.064 1.00 0.00 H \\\\nATOM 179 HA SER A 70 -10.846 8.007 40.848 1.00 0.00 H \\\\nATOM 180 HB2 SER A 70 -11.021 10.746 40.235 1.00 0.00 H \\\\nATOM 181 HB3 SER A 70 -11.649 9.693 39.271 1.00 0.00 H \\\\nATOM 182 HG SER A 70 -12.378 9.975 41.798 1.00 0.00 H \\\\nATOM 183 N ALA A 71 -9.710 7.610 38.675 1.00 0.00 N \\\\nATOM 184 CA ALA A 71 -8.794 7.221 37.611 1.00 0.00 C \\\\nATOM 185 C ALA A 71 -8.564 8.370 36.640 1.00 0.00 C \\\\nATOM 186 O ALA A 71 -7.418 8.742 36.360 1.00 0.00 O \\\\nATOM 187 CB ALA A 71 -9.337 5.996 36.880 1.00 0.00 C \\\\nATOM 188 H ALA A 71 -10.458 7.185 38.685 1.00 0.00 H \\\\nATOM 189 HA ALA A 71 -7.938 6.996 38.008 1.00 0.00 H \\\\nATOM 190 HB1 ALA A 71 -8.723 5.742 36.173 1.00 0.00 H \\\\nATOM 191 HB2 ALA A 71 -9.431 5.261 37.506 1.00 0.00 H \\\\nATOM 192 HB3 ALA A 71 -10.203 6.206 36.496 1.00 0.00 H \\\\nATOM 193 N GLU A 72 -9.642 8.948 36.120 1.00 0.00 N \\\\nATOM 194 CA GLU A 72 -9.561 9.975 35.096 1.00 0.00 C \\\\nATOM 195 C GLU A 72 -10.209 11.261 35.590 1.00 0.00 C \\\\nATOM 196 O GLU A 72 -11.067 11.247 36.477 1.00 0.00 O \\\\nATOM 197 CB GLU A 72 -10.229 9.506 33.796 1.00 0.00 C \\\\nATOM 198 CG GLU A 72 -9.957 8.043 33.482 1.00 0.00 C \\\\nATOM 199 CD GLU A 72 -11.091 7.378 32.729 1.00 0.00 C \\\\nATOM 200 OE1 GLU A 72 -11.458 6.239 33.091 1.00 0.00 O \\\\nATOM 201 OE2 GLU A 72 -11.613 7.992 31.775 1.00 0.00 O \\\\nATOM 202 H GLU A 72 -10.446 8.752 36.355 1.00 0.00 H \\\\nATOM 203 HA GLU A 72 -8.625 10.146 34.910 1.00 0.00 H \\\\nATOM 204 HB2 GLU A 72 -11.187 9.645 33.862 1.00 0.00 H \\\\nATOM 205 HB3 GLU A 72 -9.913 10.054 33.060 1.00 0.00 H \\\\nATOM 206 HG2 GLU A 72 -9.144 7.976 32.957 1.00 0.00 H \\\\nATOM 207 HG3 GLU A 72 -9.800 7.563 34.310 1.00 0.00 H \\\\nATOM 208 N MET A 73 -9.778 12.378 35.006 1.00 0.00 N \\\\nATOM 209 CA MET A 73 -10.291 13.698 35.356 1.00 0.00 C \\\\nATOM 210 C MET A 73 -11.426 14.043 34.401 1.00 0.00 C \\\\nATOM 211 O MET A 73 -11.205 14.201 33.196 1.00 0.00 O \\\\nATOM 212 CB MET A 73 -9.177 14.739 35.287 1.00 0.00 C \\\\nATOM 213 CG MET A 73 -9.603 16.140 35.691 1.00 0.00 C \\\\nATOM 214 SD MET A 73 -10.532 16.170 37.234 1.00 0.00 S \\\\nATOM 215 CE MET A 73 -10.416 17.907 37.661 1.00 0.00 C \\\\nATOM 216 H MET A 73 -9.176 12.389 34.392 1.00 0.00 H \\\\nATOM 217 HA MET A 73 -10.627 13.694 36.266 1.00 0.00 H \\\\nATOM 218 HB2 MET A 73 -8.448 14.456 35.861 1.00 0.00 H \\\\nATOM 219 HB3 MET A 73 -8.830 14.766 34.382 1.00 0.00 H \\\\nATOM 220 HG2 MET A 73 -8.816 16.699 35.781 1.00 0.00 H \\\\nATOM 221 HG3 MET A 73 -10.145 16.525 34.985 1.00 0.00 H \\\\nATOM 222 HE1 MET A 73 -10.886 18.068 38.494 1.00 0.00 H \\\\nATOM 223 HE2 MET A 73 -9.484 18.154 37.764 1.00 0.00 H \\\\nATOM 224 HE3 MET A 73 -10.815 18.441 36.957 1.00 0.00 H \\\\nATOM 225 N GLU A 74 -12.641 14.157 34.936 1.00 0.00 N \\\\nATOM 226 CA GLU A 74 -13.806 14.515 34.138 1.00 0.00 C \\\\nATOM 227 C GLU A 74 -14.492 15.778 34.642 1.00 0.00 C \\\\nATOM 228 O GLU A 74 -15.562 16.136 34.134 1.00 0.00 O \\\\nATOM 229 CB GLU A 74 -14.789 13.342 34.090 1.00 0.00 C \\\\nATOM 230 CG GLU A 74 -14.177 12.092 33.476 1.00 0.00 C \\\\nATOM 231 CD GLU A 74 -15.093 10.888 33.543 1.00 0.00 C \\\\nATOM 232 OE1 GLU A 74 -15.948 10.836 34.453 1.00 0.00 O \\\\nATOM 233 OE2 GLU A 74 -14.954 9.988 32.686 1.00 0.00 O \\\\nATOM 234 H GLU A 74 -12.810 14.029 35.769 1.00 0.00 H \\\\nATOM 235 HA GLU A 74 -13.496 14.709 33.240 1.00 0.00 H \\\\nATOM 236 HB2 GLU A 74 -15.092 13.141 34.989 1.00 0.00 H \\\\nATOM 237 HB3 GLU A 74 -15.571 13.600 33.578 1.00 0.00 H \\\\nATOM 238 HG2 GLU A 74 -13.953 12.270 32.549 1.00 0.00 H \\\\nATOM 239 HG3 GLU A 74 -13.347 11.886 33.934 1.00 0.00 H \\\\nATOM 240 N ASP A 75 -13.907 16.458 35.621 1.00 0.00 N \\\\nATOM 241 CA ASP A 75 -14.391 17.756 36.057 1.00 0.00 C \\\\nATOM 242 C ASP A 75 -13.796 18.850 35.180 1.00 0.00 C \\\\nATOM 243 O ASP A 75 -12.696 18.711 34.641 1.00 0.00 O \\\\nATOM 244 CB ASP A 75 -14.029 18.010 37.520 1.00 0.00 C \\\\nATOM 245 CG ASP A 75 -15.086 17.512 38.480 1.00 0.00 C \\\\nATOM 246 OD1 ASP A 75 -16.052 16.862 38.026 1.00 0.00 O \\\\nATOM 247 OD2 ASP A 75 -14.952 17.771 39.696 1.00 0.00 O \\\\nATOM 248 H ASP A 75 -13.217 16.177 36.051 1.00 0.00 H \\\\nATOM 249 HA ASP A 75 -15.358 17.765 35.975 1.00 0.00 H \\\\nATOM 250 HB2 ASP A 75 -13.185 17.575 37.720 1.00 0.00 H \\\\nATOM 251 HB3 ASP A 75 -13.897 18.961 37.656 1.00 0.00 H \\\\nATOM 252 N ALA A 76 -14.539 19.943 35.039 1.00 0.00 N \\\\nATOM 253 CA ALA A 76 -14.051 21.122 34.342 1.00 0.00 C \\\\nATOM 254 C ALA A 76 -14.604 22.362 35.028 1.00 0.00 C \\\\nATOM 255 O ALA A 76 -15.589 22.299 35.767 1.00 0.00 O \\\\nATOM 256 CB ALA A 76 -14.440 21.108 32.857 1.00 0.00 C \\\\nATOM 257 H ALA A 76 -15.339 20.020 35.345 1.00 0.00 H \\\\nATOM 258 HA ALA A 76 -13.082 21.127 34.380 1.00 0.00 H \\\\nATOM 259 HB1 ALA A 76 -14.099 21.907 32.425 1.00 0.00 H \\\\nATOM 260 HB2 ALA A 76 -14.061 20.324 32.430 1.00 0.00 H \\\\nATOM 261 HB3 ALA A 76 -15.406 21.085 32.776 1.00 0.00 H \\\\nATOM 262 N SER A 77 -13.964 23.499 34.769 1.00 0.00 N \\\\nATOM 263 CA SER A 77 -14.387 24.746 35.385 1.00 0.00 C \\\\nATOM 264 C SER A 77 -14.145 25.903 34.428 1.00 0.00 C \\\\nATOM 265 O SER A 77 -13.386 25.791 33.461 1.00 0.00 O \\\\nATOM 266 CB SER A 77 -13.656 24.990 36.711 1.00 0.00 C \\\\nATOM 267 OG SER A 77 -12.255 25.039 36.518 1.00 0.00 O \\\\nATOM 268 H SER A 77 -13.287 23.567 34.243 1.00 0.00 H \\\\nATOM 269 HA SER A 77 -15.336 24.682 35.578 1.00 0.00 H \\\\nATOM 270 HB2 SER A 77 -13.961 25.823 37.103 1.00 0.00 H \\\\nATOM 271 HB3 SER A 77 -13.875 24.284 37.339 1.00 0.00 H \\\\nATOM 272 HG SER A 77 -11.870 24.667 37.165 1.00 0.00 H \\\\nATOM 273 N ALA A 78 -14.802 27.023 34.720 1.00 0.00 N \\\\nATOM 274 CA ALA A 78 -14.707 28.212 33.890 1.00 0.00 C \\\\nATOM 275 C ALA A 78 -14.796 29.450 34.769 1.00 0.00 C \\\\nATOM 276 O ALA A 78 -15.535 29.470 35.756 1.00 0.00 O \\\\nATOM 277 CB ALA A 78 -15.808 28.242 32.825 1.00 0.00 C \\\\nATOM 278 H ALA A 78 -15.314 27.111 35.405 1.00 0.00 H \\\\nATOM 279 HA ALA A 78 -13.853 28.196 33.430 1.00 0.00 H \\\\nATOM 280 HB1 ALA A 78 -15.718 29.045 32.289 1.00 0.00 H \\\\nATOM 281 HB2 ALA A 78 -15.728 27.462 32.254 1.00 0.00 H \\\\nATOM 282 HB3 ALA A 78 -16.677 28.238 33.257 1.00 0.00 H \\\\nATOM 283 N ALA A 79 -14.033 30.477 34.401 1.00 0.00 N \\\\nATOM 284 CA ALA A 79 -14.054 31.759 35.104 1.00 0.00 C \\\\nATOM 285 C ALA A 79 -13.760 32.831 34.056 1.00 0.00 C \\\\nATOM 286 O ALA A 79 -12.599 33.035 33.691 1.00 0.00 O \\\\nATOM 287 CB ALA A 79 -13.046 31.790 36.243 1.00 0.00 C \\\\nATOM 288 H ALA A 79 -13.488 30.450 33.736 1.00 0.00 H \\\\nATOM 289 HA ALA A 79 -14.917 31.913 35.519 1.00 0.00 H \\\\nATOM 290 HB1 ALA A 79 -13.086 32.651 36.687 1.00 0.00 H \\\\nATOM 291 HB2 ALA A 79 -13.255 31.089 36.880 1.00 0.00 H \\\\nATOM 292 HB3 ALA A 79 -12.154 31.650 35.890 1.00 0.00 H \\\\nATOM 293 N VAL A 80 -14.801 33.498 33.586 1.00 0.00 N \\\\nATOM 294 CA VAL A 80 -14.700 34.438 32.474 1.00 0.00 C \\\\nATOM 295 C VAL A 80 -15.060 35.826 32.984 1.00 0.00 C \\\\nATOM 296 O VAL A 80 -16.232 36.142 33.191 1.00 0.00 O \\\\nATOM 297 CB VAL A 80 -15.611 34.023 31.304 1.00 0.00 C \\\\nATOM 298 CG1 VAL A 80 -15.236 34.794 30.047 1.00 0.00 C \\\\nATOM 299 CG2 VAL A 80 -15.529 32.523 31.067 1.00 0.00 C \\\\nATOM 300 H VAL A 80 -15.596 33.420 33.904 1.00 0.00 H \\\\nATOM 301 HA VAL A 80 -13.792 34.440 32.133 1.00 0.00 H \\\\nATOM 302 HB VAL A 80 -16.529 34.239 31.533 1.00 0.00 H \\\\nATOM 303 HG11 VAL A 80 -15.816 34.525 29.317 1.00 0.00 H \\\\nATOM 304 HG12 VAL A 80 -15.339 35.745 30.208 1.00 0.00 H \\\\nATOM 305 HG13 VAL A 80 -14.314 34.604 29.814 1.00 0.00 H \\\\nATOM 306 HG21 VAL A 80 -16.108 32.280 30.328 1.00 0.00 H \\\\nATOM 307 HG22 VAL A 80 -14.615 32.278 30.855 1.00 0.00 H \\\\nATOM 308 HG23 VAL A 80 -15.812 32.053 31.867 1.00 0.00 H \\\\nATOM 309 N PRO A 81 -14.067 36.690 33.199 1.00 0.00 N \\\\nATOM 310 CA PRO A 81 -14.365 38.069 33.601 1.00 0.00 C \\\\nATOM 311 C PRO A 81 -14.903 38.872 32.429 1.00 0.00 C \\\\nATOM 312 O PRO A 81 -14.459 38.712 31.289 1.00 0.00 O \\\\nATOM 313 CB PRO A 81 -13.009 38.612 34.072 1.00 0.00 C \\\\nATOM 314 CG PRO A 81 -12.076 37.425 34.112 1.00 0.00 C \\\\nATOM 315 CD PRO A 81 -12.622 36.418 33.159 1.00 0.00 C \\\\nATOM 316 HA PRO A 81 -15.047 38.123 34.289 1.00 0.00 H \\\\nATOM 317 HB2 PRO A 81 -12.678 39.293 33.466 1.00 0.00 H \\\\nATOM 318 HB3 PRO A 81 -13.085 39.024 34.947 1.00 0.00 H \\\\nATOM 319 HG2 PRO A 81 -11.176 37.686 33.860 1.00 0.00 H \\\\nATOM 320 HG3 PRO A 81 -12.024 37.058 35.008 1.00 0.00 H \\\\nATOM 321 HD2 PRO A 81 -12.258 36.531 32.267 1.00 0.00 H \\\\nATOM 322 HD3 PRO A 81 -12.418 35.511 33.436 1.00 0.00 H \\\\nATOM 323 N ARG A 82 -15.854 39.758 32.731 1.00 0.00 N \\\\nATOM 324 CA ARG A 82 -16.477 40.635 31.737 1.00 0.00 C \\\\nATOM 325 C ARG A 82 -16.914 39.850 30.501 1.00 0.00 C \\\\nATOM 326 O ARG A 82 -16.672 40.246 29.358 1.00 0.00 O \\\\nATOM 327 CB ARG A 82 -15.538 41.780 31.355 1.00 0.00 C \\\\nATOM 328 CG ARG A 82 -14.969 42.529 32.547 1.00 0.00 C \\\\nATOM 329 CD ARG A 82 -14.035 43.641 32.105 1.00 0.00 C \\\\nATOM 330 NE ARG A 82 -12.862 43.126 31.403 1.00 0.00 N \\\\nATOM 331 CZ ARG A 82 -12.575 43.389 30.132 1.00 0.00 C \\\\nATOM 332 NH1 ARG A 82 -13.374 44.167 29.414 1.00 0.00 N \\\\nATOM 333 NH2 ARG A 82 -11.485 42.875 29.578 1.00 0.00 N \\\\nATOM 334 H ARG A 82 -16.159 39.868 33.528 1.00 0.00 H \\\\nATOM 335 HA ARG A 82 -17.272 41.019 32.138 1.00 0.00 H \\\\nATOM 336 HB2 ARG A 82 -14.806 41.424 30.827 1.00 0.00 H \\\\nATOM 337 HB3 ARG A 82 -16.017 42.405 30.789 1.00 0.00 H \\\\nATOM 338 HG2 ARG A 82 -15.694 42.902 33.073 1.00 0.00 H \\\\nATOM 339 HG3 ARG A 82 -14.490 41.911 33.122 1.00 0.00 H \\\\nATOM 340 HD2 ARG A 82 -14.514 44.253 31.525 1.00 0.00 H \\\\nATOM 341 HD3 ARG A 82 -13.749 44.149 32.880 1.00 0.00 H \\\\nATOM 342 HE ARG A 82 -12.322 42.620 31.841 1.00 0.00 H \\\\nATOM 343 HH11 ARG A 82 -14.081 44.503 29.771 1.00 0.00 H \\\\nATOM 344 HH12 ARG A 82 -13.185 44.335 28.592 1.00 0.00 H \\\\nATOM 345 HH21 ARG A 82 -10.964 42.371 30.041 1.00 0.00 H \\\\nATOM 346 HH22 ARG A 82 -11.299 43.045 28.756 1.00 0.00 H \\\\nATOM 347 N PHE A 83 -17.574 38.717 30.745 1.00 0.00 N \\\\nATOM 348 CA PHE A 83 -17.998 37.860 29.646 1.00 0.00 C \\\\nATOM 349 C PHE A 83 -19.171 38.449 28.876 1.00 0.00 C \\\\nATOM 350 O PHE A 83 -19.404 38.049 27.730 1.00 0.00 O \\\\nATOM 351 CB PHE A 83 -18.378 36.475 30.172 1.00 0.00 C \\\\nATOM 352 CG PHE A 83 -19.800 36.378 30.641 1.00 0.00 C \\\\nATOM 353 CD1 PHE A 83 -20.184 36.931 31.851 1.00 0.00 C \\\\nATOM 354 CD2 PHE A 83 -20.756 35.743 29.867 1.00 0.00 C \\\\nATOM 355 CE1 PHE A 83 -21.494 36.848 32.284 1.00 0.00 C \\\\nATOM 356 CE2 PHE A 83 -22.066 35.656 30.295 1.00 0.00 C \\\\nATOM 357 CZ PHE A 83 -22.436 36.209 31.506 1.00 0.00 C \\\\nATOM 358 H PHE A 83 -17.782 38.432 31.529 1.00 0.00 H \\\\nATOM 359 HA PHE A 83 -17.248 37.788 29.036 1.00 0.00 H \\\\nATOM 360 HB2 PHE A 83 -18.231 35.820 29.472 1.00 0.00 H \\\\nATOM 361 HB3 PHE A 83 -17.787 36.243 30.905 1.00 0.00 H \\\\nATOM 362 HD1 PHE A 83 -19.552 37.364 32.379 1.00 0.00 H \\\\nATOM 363 HD2 PHE A 83 -20.513 35.371 29.050 1.00 0.00 H \\\\nATOM 364 HE1 PHE A 83 -21.740 37.223 33.099 1.00 0.00 H \\\\nATOM 365 HE2 PHE A 83 -22.700 35.225 29.768 1.00 0.00 H \\\\nATOM 366 HZ PHE A 83 -23.318 36.150 31.795 1.00 0.00 H \\\\nATOM 367 N ALA A 84 -19.905 39.384 29.471 1.00 0.00 N \\\\nATOM 368 CA ALA A 84 -21.092 39.943 28.840 1.00 0.00 C \\\\nATOM 369 C ALA A 84 -21.470 41.227 29.561 1.00 0.00 C \\\\nATOM 370 O ALA A 84 -20.883 41.587 30.585 1.00 0.00 O \\\\nATOM 371 CB ALA A 84 -22.256 38.947 28.854 1.00 0.00 C \\\\nATOM 372 H ALA A 84 -19.729 39.710 30.247 1.00 0.00 H \\\\nATOM 373 HA ALA A 84 -20.896 40.135 27.910 1.00 0.00 H \\\\nATOM 374 HB1 ALA A 84 -23.030 39.347 28.428 1.00 0.00 H \\\\nATOM 375 HB2 ALA A 84 -22.001 38.144 28.372 1.00 0.00 H \\\\nATOM 376 HB3 ALA A 84 -22.475 38.718 29.771 1.00 0.00 H \\\\nATOM 377 N ASP A 85 -22.466 41.914 29.008 1.00 0.00 N \\\\nATOM 378 CA ASP A 85 -23.056 43.096 29.621 1.00 0.00 C \\\\nATOM 379 C ASP A 85 -24.537 42.827 29.839 1.00 0.00 C \\\\nATOM 380 O ASP A 85 -25.268 42.556 28.879 1.00 0.00 O \\\\nATOM 381 CB ASP A 85 -22.847 44.333 28.743 1.00 0.00 C \\\\nATOM 382 CG ASP A 85 -21.399 44.783 28.704 1.00 0.00 C \\\\nATOM 383 OD1 ASP A 85 -20.582 44.238 29.477 1.00 0.00 O \\\\nATOM 384 OD2 ASP A 85 -21.076 45.678 27.896 1.00 0.00 O \\\\nATOM 385 H ASP A 85 -22.822 41.702 28.255 1.00 0.00 H \\\\nATOM 386 HA ASP A 85 -22.624 43.276 30.471 1.00 0.00 H \\\\nATOM 387 HB2 ASP A 85 -23.146 44.139 27.841 1.00 0.00 H \\\\nATOM 388 HB3 ASP A 85 -23.399 45.058 29.075 1.00 0.00 H \\\\nATOM 389 N VAL A 86 -24.973 42.893 31.093 1.00 0.00 N \\\\nATOM 390 CA VAL A 86 -26.350 42.566 31.453 1.00 0.00 C \\\\nATOM 391 C VAL A 86 -27.223 43.811 31.353 1.00 0.00 C \\\\nATOM 392 O VAL A 86 -26.866 44.861 31.908 1.00 0.00 O \\\\nATOM 393 CB VAL A 86 -26.424 41.960 32.864 1.00 0.00 C \\\\nATOM 394 CG1 VAL A 86 -27.870 41.666 33.243 1.00 0.00 C \\\\nATOM 395 CG2 VAL A 86 -25.574 40.701 32.948 1.00 0.00 C \\\\nATOM 396 H VAL A 86 -24.481 43.128 31.758 1.00 0.00 H \\\\nATOM 397 HA VAL A 86 -26.681 41.901 30.830 1.00 0.00 H \\\\nATOM 398 HB VAL A 86 -26.071 42.605 33.496 1.00 0.00 H \\\\nATOM 399 HG11 VAL A 86 -27.900 41.285 34.134 1.00 0.00 H \\\\nATOM 400 HG12 VAL A 86 -28.383 42.489 33.226 1.00 0.00 H \\\\nATOM 401 HG13 VAL A 86 -28.249 41.037 32.610 1.00 0.00 H \\\\nATOM 402 HG21 VAL A 86 -25.631 40.331 33.843 1.00 0.00 H \\\\nATOM 403 HG22 VAL A 86 -25.898 40.048 32.308 1.00 0.00 H \\\\nATOM 404 HG23 VAL A 86 -24.651 40.920 32.747 1.00 0.00 H \\\\nATOM 405 N PRO A 87 -28.364 43.749 30.668 1.00 0.00 N \\\\nATOM 406 CA PRO A 87 -29.287 44.894 30.646 1.00 0.00 C \\\\nATOM 407 C PRO A 87 -29.870 45.120 32.038 1.00 0.00 C \\\\nATOM 408 O PRO A 87 -30.484 44.221 32.616 1.00 0.00 O \\\\nATOM 409 CB PRO A 87 -30.361 44.483 29.634 1.00 0.00 C \\\\nATOM 410 CG PRO A 87 -30.228 43.011 29.478 1.00 0.00 C \\\\nATOM 411 CD PRO A 87 -28.820 42.636 29.815 1.00 0.00 C \\\\nATOM 412 HA PRO A 87 -28.863 45.730 30.398 1.00 0.00 H \\\\nATOM 413 HB2 PRO A 87 -31.247 44.721 29.950 1.00 0.00 H \\\\nATOM 414 HB3 PRO A 87 -30.232 44.936 28.786 1.00 0.00 H \\\\nATOM 415 HG2 PRO A 87 -30.851 42.550 30.062 1.00 0.00 H \\\\nATOM 416 HG3 PRO A 87 -30.442 42.746 28.570 1.00 0.00 H \\\\nATOM 417 HD2 PRO A 87 -28.778 41.787 30.282 1.00 0.00 H \\\\nATOM 418 HD3 PRO A 87 -28.273 42.549 29.019 1.00 0.00 H \\\\nATOM 419 N VAL A 88 -29.663 46.327 32.568 1.00 0.00 N \\\\nATOM 420 CA VAL A 88 -29.968 46.624 33.964 1.00 0.00 C \\\\nATOM 421 C VAL A 88 -31.444 46.429 34.300 1.00 0.00 C \\\\nATOM 422 O VAL A 88 -31.788 46.248 35.474 1.00 0.00 O \\\\nATOM 423 CB VAL A 88 -29.486 48.051 34.302 1.00 0.00 C \\\\nATOM 424 CG1 VAL A 88 -29.612 48.326 35.788 1.00 0.00 C \\\\nATOM 425 CG2 VAL A 88 -28.040 48.215 33.875 1.00 0.00 C \\\\nATOM 426 H VAL A 88 -29.343 46.993 32.128 1.00 0.00 H \\\\nATOM 427 HA VAL A 88 -29.490 45.988 34.519 1.00 0.00 H \\\\nATOM 428 HB VAL A 88 -30.043 48.685 33.824 1.00 0.00 H \\\\nATOM 429 HG11 VAL A 88 -29.304 49.226 35.978 1.00 0.00 H \\\\nATOM 430 HG12 VAL A 88 -30.540 48.239 36.056 1.00 0.00 H \\\\nATOM 431 HG13 VAL A 88 -29.072 47.689 36.282 1.00 0.00 H \\\\nATOM 432 HG21 VAL A 88 -27.739 49.112 34.088 1.00 0.00 H \\\\nATOM 433 HG22 VAL A 88 -27.489 47.569 34.344 1.00 0.00 H \\\\nATOM 434 HG23 VAL A 88 -27.966 48.068 32.919 1.00 0.00 H \\\\nATOM 435 N ARG A 89 -32.331 46.432 33.301 1.00 0.00 N \\\\nATOM 436 CA ARG A 89 -33.739 46.179 33.594 1.00 0.00 C \\\\nATOM 437 C ARG A 89 -33.981 44.783 34.147 1.00 0.00 C \\\\nATOM 438 O ARG A 89 -35.086 44.511 34.627 1.00 0.00 O \\\\nATOM 439 CB ARG A 89 -34.594 46.364 32.340 1.00 0.00 C \\\\nATOM 440 CG ARG A 89 -35.294 47.698 32.265 1.00 0.00 C \\\\nATOM 441 CD ARG A 89 -36.487 47.652 31.333 1.00 0.00 C \\\\nATOM 442 NE ARG A 89 -37.706 47.191 31.993 1.00 0.00 N \\\\nATOM 443 CZ ARG A 89 -38.754 46.682 31.354 1.00 0.00 C \\\\nATOM 444 NH1 ARG A 89 -38.732 46.568 30.033 1.00 0.00 N \\\\nATOM 445 NH2 ARG A 89 -39.828 46.300 32.032 1.00 0.00 N \\\\nATOM 446 H ARG A 89 -32.144 46.574 32.474 1.00 0.00 H \\\\nATOM 447 HA ARG A 89 -33.993 46.823 34.273 1.00 0.00 H \\\\nATOM 448 HB2 ARG A 89 -34.030 46.261 31.557 1.00 0.00 H \\\\nATOM 449 HB3 ARG A 89 -35.259 45.658 32.306 1.00 0.00 H \\\\nATOM 450 HG2 ARG A 89 -35.586 47.961 33.152 1.00 0.00 H \\\\nATOM 451 HG3 ARG A 89 -34.670 48.375 31.959 1.00 0.00 H \\\\nATOM 452 HD2 ARG A 89 -36.639 48.537 30.965 1.00 0.00 H \\\\nATOM 453 HD3 ARG A 89 -36.287 47.065 30.587 1.00 0.00 H \\\\nATOM 454 HE ARG A 89 -37.748 47.253 32.850 1.00 0.00 H \\\\nATOM 455 HH11 ARG A 89 -38.040 46.823 29.591 1.00 0.00 H \\\\nATOM 456 HH12 ARG A 89 -39.410 46.239 29.618 1.00 0.00 H \\\\nATOM 457 HH21 ARG A 89 -39.848 46.381 32.888 1.00 0.00 H \\\\nATOM 458 HH22 ARG A 89 -40.505 45.971 31.616 1.00 0.00 H \\\\nATOM 459 N LEU A 90 -32.984 43.902 34.098 1.00 0.00 N \\\\nATOM 460 CA LEU A 90 -33.030 42.609 34.764 1.00 0.00 C \\\\nATOM 461 C LEU A 90 -32.500 42.667 36.189 1.00 0.00 C \\\\nATOM 462 O LEU A 90 -32.570 41.662 36.904 1.00 0.00 O \\\\nATOM 463 CB LEU A 90 -32.231 41.568 33.970 1.00 0.00 C \\\\nATOM 464 CG LEU A 90 -32.722 41.189 32.574 1.00 0.00 C \\\\nATOM 465 CD1 LEU A 90 -31.595 40.598 31.746 1.00 0.00 C \\\\nATOM 466 CD2 LEU A 90 -33.874 40.210 32.681 1.00 0.00 C \\\\nATOM 467 H LEU A 90 -32.252 44.044 33.670 1.00 0.00 H \\\\nATOM 468 HA LEU A 90 -33.964 42.352 34.804 1.00 0.00 H \\\\nATOM 469 HB2 LEU A 90 -31.322 41.895 33.885 1.00 0.00 H \\\\nATOM 470 HB3 LEU A 90 -32.193 40.757 34.501 1.00 0.00 H \\\\nATOM 471 HG LEU A 90 -33.032 41.992 32.126 1.00 0.00 H \\\\nATOM 472 HD11 LEU A 90 -31.928 40.365 30.865 1.00 0.00 H \\\\nATOM 473 HD12 LEU A 90 -30.881 41.249 31.659 1.00 0.00 H \\\\nATOM 474 HD13 LEU A 90 -31.255 39.802 32.184 1.00 0.00 H \\\\nATOM 475 HD21 LEU A 90 -34.181 39.973 31.792 1.00 0.00 H \\\\nATOM 476 HD22 LEU A 90 -33.578 39.411 33.144 1.00 0.00 H \\\\nATOM 477 HD23 LEU A 90 -34.601 40.619 33.176 1.00 0.00 H \\\\nATOM 478 N LEU A 91 -31.976 43.817 36.619 1.00 0.00 N \\\\nATOM 479 CA LEU A 91 -31.355 43.952 37.926 1.00 0.00 C \\\\nATOM 480 C LEU A 91 -31.945 45.065 38.776 1.00 0.00 C \\\\nATOM 481 O LEU A 91 -31.679 45.103 39.982 1.00 0.00 O \\\\nATOM 482 CB LEU A 91 -29.845 44.205 37.778 1.00 0.00 C \\\\nATOM 483 CG LEU A 91 -29.053 43.291 36.842 1.00 0.00 C \\\\nATOM 484 CD1 LEU A 91 -27.726 43.933 36.475 1.00 0.00 C \\\\nATOM 485 CD2 LEU A 91 -28.832 41.927 37.475 1.00 0.00 C \\\\nATOM 486 H LEU A 91 -31.974 44.541 36.154 1.00 0.00 H \\\\nATOM 487 HA LEU A 91 -31.528 43.113 38.381 1.00 0.00 H \\\\nATOM 488 HB2 LEU A 91 -29.725 45.118 37.474 1.00 0.00 H \\\\nATOM 489 HB3 LEU A 91 -29.446 44.145 38.660 1.00 0.00 H \\\\nATOM 490 HG LEU A 91 -29.570 43.164 36.031 1.00 0.00 H \\\\nATOM 491 HD11 LEU A 91 -27.234 43.344 35.882 1.00 0.00 H \\\\nATOM 492 HD12 LEU A 91 -27.888 44.779 36.029 1.00 0.00 H \\\\nATOM 493 HD13 LEU A 91 -27.207 44.087 37.280 1.00 0.00 H \\\\nATOM 494 HD21 LEU A 91 -28.329 41.365 36.865 1.00 0.00 H \\\\nATOM 495 HD22 LEU A 91 -28.336 42.030 38.302 1.00 0.00 H \\\\nATOM 496 HD23 LEU A 91 -29.690 41.514 37.662 1.00 0.00 H \\\\nATOM 497 N ALA A 92 -32.732 45.967 38.197 1.00 0.00 N \\\\nATOM 498 CA ALA A 92 -33.297 47.067 38.960 1.00 0.00 C \\\\nATOM 499 C ALA A 92 -34.684 47.386 38.430 1.00 0.00 C \\\\nATOM 500 O ALA A 92 -34.969 47.212 37.241 1.00 0.00 O \\\\nATOM 501 CB ALA A 92 -32.406 48.313 38.900 1.00 0.00 C \\\\nATOM 502 H ALA A 92 -32.949 45.958 37.365 1.00 0.00 H \\\\nATOM 503 HA ALA A 92 -33.355 46.796 39.890 1.00 0.00 H \\\\nATOM 504 HB1 ALA A 92 -32.811 49.026 39.418 1.00 0.00 H \\\\nATOM 505 HB2 ALA A 92 -31.532 48.104 39.266 1.00 0.00 H \\\\nATOM 506 HB3 ALA A 92 -32.310 48.598 37.978 1.00 0.00 H \\\\nATOM 507 N SER A 93 -35.542 47.854 39.331 1.00 0.00 N \\\\nATOM 508 CA SER A 93 -36.877 48.283 38.946 1.00 0.00 C \\\\nATOM 509 C SER A 93 -36.787 49.471 37.998 1.00 0.00 C \\\\nATOM 510 O SER A 93 -35.926 50.342 38.151 1.00 0.00 O \\\\nATOM 511 CB SER A 93 -37.687 48.653 40.190 1.00 0.00 C \\\\nATOM 512 OG SER A 93 -38.617 49.685 39.912 1.00 0.00 O \\\\nATOM 513 H SER A 93 -35.369 47.930 40.170 1.00 0.00 H \\\\nATOM 514 HA SER A 93 -37.326 47.554 38.490 1.00 0.00 H \\\\nATOM 515 HB2 SER A 93 -38.158 47.870 40.516 1.00 0.00 H \\\\nATOM 516 HB3 SER A 93 -37.086 48.938 40.896 1.00 0.00 H \\\\nATOM 517 HG SER A 93 -39.122 49.793 40.574 1.00 0.00 H \\\\nATOM 518 N ARG A 94 -37.679 49.497 37.001 1.00 0.00 N \\\\nATOM 519 CA ARG A 94 -37.685 50.607 36.053 1.00 0.00 C \\\\nATOM 520 C ARG A 94 -37.910 51.933 36.756 1.00 0.00 C \\\\nATOM 521 O ARG A 94 -37.371 52.961 36.335 1.00 0.00 O \\\\nATOM 522 CB ARG A 94 -38.791 50.410 35.018 1.00 0.00 C \\\\nATOM 523 CG ARG A 94 -38.380 49.734 33.742 1.00 0.00 C \\\\nATOM 524 CD ARG A 94 -39.550 49.715 32.770 1.00 0.00 C \\\\nATOM 525 NE ARG A 94 -39.930 51.057 32.344 1.00 0.00 N \\\\nATOM 526 CZ ARG A 94 -39.733 51.531 31.119 1.00 0.00 C \\\\nATOM 527 NH1 ARG A 94 -39.161 50.766 30.199 1.00 0.00 N \\\\nATOM 528 NH2 ARG A 94 -40.107 52.765 30.812 1.00 0.00 N \\\\nATOM 529 H ARG A 94 -38.275 48.893 36.861 1.00 0.00 H \\\\nATOM 530 HA ARG A 94 -36.818 50.623 35.618 1.00 0.00 H \\\\nATOM 531 HB2 ARG A 94 -39.502 49.891 35.425 1.00 0.00 H \\\\nATOM 532 HB3 ARG A 94 -39.164 51.278 34.799 1.00 0.00 H \\\\nATOM 533 HG2 ARG A 94 -37.627 50.201 33.346 1.00 0.00 H \\\\nATOM 534 HG3 ARG A 94 -38.087 48.828 33.926 1.00 0.00 H \\\\nATOM 535 HD2 ARG A 94 -39.315 49.185 31.993 1.00 0.00 H \\\\nATOM 536 HD3 ARG A 94 -40.310 49.282 33.189 1.00 0.00 H \\\\nATOM 537 HE ARG A 94 -40.304 51.573 32.921 1.00 0.00 H \\\\nATOM 538 HH11 ARG A 94 -38.919 49.965 30.396 1.00 0.00 H \\\\nATOM 539 HH12 ARG A 94 -39.033 51.071 29.405 1.00 0.00 H \\\\nATOM 540 HH21 ARG A 94 -40.479 53.262 31.407 1.00 0.00 H \\\\nATOM 541 HH22 ARG A 94 -39.978 53.068 30.018 1.00 0.00 H \\\\nATOM 542 N ARG A 95 -38.682 51.918 37.836 1.00 0.00 N \\\\nATOM 543 CA ARG A 95 -39.106 53.121 38.531 1.00 0.00 C \\\\nATOM 544 C ARG A 95 -38.085 53.589 39.555 1.00 0.00 C \\\\nATOM 545 O ARG A 95 -38.080 54.772 39.911 1.00 0.00 O \\\\nATOM 546 CB ARG A 95 -40.463 52.893 39.218 1.00 0.00 C \\\\nATOM 547 CG ARG A 95 -41.654 52.603 38.284 1.00 0.00 C \\\\nATOM 548 CD ARG A 95 -41.554 51.263 37.553 1.00 0.00 C \\\\nATOM 549 NE ARG A 95 -41.205 50.169 38.458 1.00 0.00 N \\\\nATOM 550 CZ ARG A 95 -40.932 48.929 38.065 1.00 0.00 C \\\\nATOM 551 NH1 ARG A 95 -40.961 48.616 36.776 1.00 0.00 N \\\\nATOM 552 NH2 ARG A 95 -40.627 48.001 38.960 1.00 0.00 N \\\\nATOM 553 H ARG A 95 -38.979 51.193 38.191 1.00 0.00 H \\\\nATOM 554 HA ARG A 95 -39.191 53.818 37.862 1.00 0.00 H \\\\nATOM 555 HB2 ARG A 95 -40.372 52.151 39.836 1.00 0.00 H \\\\nATOM 556 HB3 ARG A 95 -40.674 53.678 39.747 1.00 0.00 H \\\\nATOM 557 HG2 ARG A 95 -42.473 52.618 38.804 1.00 0.00 H \\\\nATOM 558 HG3 ARG A 95 -41.721 53.315 37.629 1.00 0.00 H \\\\nATOM 559 HD2 ARG A 95 -42.400 51.067 37.122 1.00 0.00 H \\\\nATOM 560 HD3 ARG A 95 -40.887 51.327 36.852 1.00 0.00 H \\\\nATOM 561 HE ARG A 95 -41.174 50.339 39.300 1.00 0.00 H \\\\nATOM 562 HH11 ARG A 95 -41.157 49.216 36.192 1.00 0.00 H \\\\nATOM 563 HH12 ARG A 95 -40.784 47.813 36.524 1.00 0.00 H \\\\nATOM 564 HH21 ARG A 95 -40.606 48.201 39.796 1.00 0.00 H \\\\nATOM 565 HH22 ARG A 95 -40.451 47.199 38.705 1.00 0.00 H \\\\nATOM 566 N ASP A 96 -37.216 52.692 40.028 1.00 0.00 N \\\\nATOM 567 CA ASP A 96 -36.155 53.110 40.931 1.00 0.00 C \\\\nATOM 568 C ASP A 96 -34.987 53.712 40.171 1.00 0.00 C \\\\nATOM 569 O ASP A 96 -34.296 54.585 40.701 1.00 0.00 O \\\\nATOM 570 CB ASP A 96 -35.663 51.921 41.758 1.00 0.00 C \\\\nATOM 571 CG ASP A 96 -36.340 51.827 43.107 1.00 0.00 C \\\\nATOM 572 OD1 ASP A 96 -37.421 52.429 43.277 1.00 0.00 O \\\\nATOM 573 OD2 ASP A 96 -35.789 51.148 43.999 1.00 0.00 O \\\\nATOM 574 H ASP A 96 -37.226 51.853 39.840 1.00 0.00 H \\\\nATOM 575 HA ASP A 96 -36.522 53.788 41.520 1.00 0.00 H \\\\nATOM 576 HB2 ASP A 96 -35.820 51.101 41.264 1.00 0.00 H \\\\nATOM 577 HB3 ASP A 96 -34.704 51.996 41.886 1.00 0.00 H \\\\nATOM 578 N LEU A 97 -34.759 53.266 38.937 1.00 0.00 N \\\\nATOM 579 CA LEU A 97 -33.805 53.934 38.065 1.00 0.00 C \\\\nATOM 580 C LEU A 97 -34.418 55.153 37.385 1.00 0.00 C \\\\nATOM 581 O LEU A 97 -33.698 56.105 37.065 1.00 0.00 O \\\\nATOM 582 CB LEU A 97 -33.261 52.946 37.038 1.00 0.00 C \\\\nATOM 583 CG LEU A 97 -31.931 52.315 37.457 1.00 0.00 C \\\\nATOM 584 CD1 LEU A 97 -31.562 51.185 36.526 1.00 0.00 C \\\\nATOM 585 CD2 LEU A 97 -30.826 53.364 37.501 1.00 0.00 C \\\\nATOM 586 H LEU A 97 -35.146 52.581 38.590 1.00 0.00 H \\\\nATOM 587 HA LEU A 97 -33.070 54.256 38.610 1.00 0.00 H \\\\nATOM 588 HB2 LEU A 97 -33.915 52.244 36.895 1.00 0.00 H \\\\nATOM 589 HB3 LEU A 97 -33.144 53.402 36.190 1.00 0.00 H \\\\nATOM 590 HG LEU A 97 -32.035 51.950 38.350 1.00 0.00 H \\\\nATOM 591 HD11 LEU A 97 -30.718 50.797 36.806 1.00 0.00 H \\\\nATOM 592 HD12 LEU A 97 -32.254 50.505 36.552 1.00 0.00 H \\\\nATOM 593 HD13 LEU A 97 -31.477 51.525 35.622 1.00 0.00 H \\\\nATOM 594 HD21 LEU A 97 -29.993 52.945 37.768 1.00 0.00 H \\\\nATOM 595 HD22 LEU A 97 -30.721 53.761 36.622 1.00 0.00 H \\\\nATOM 596 HD23 LEU A 97 -31.060 54.054 38.141 1.00 0.00 H \\\\nATOM 597 N ASP A 98 -35.734 55.138 37.150 1.00 0.00 N \\\\nATOM 598 CA ASP A 98 -36.411 56.323 36.631 1.00 0.00 C \\\\nATOM 599 C ASP A 98 -36.371 57.468 37.634 1.00 0.00 C \\\\nATOM 600 O ASP A 98 -36.443 58.639 37.241 1.00 0.00 O \\\\nATOM 601 CB ASP A 98 -37.858 55.980 36.264 1.00 0.00 C \\\\nATOM 602 CG ASP A 98 -38.648 57.185 35.799 1.00 0.00 C \\\\nATOM 603 OD1 ASP A 98 -38.148 57.932 34.933 1.00 0.00 O \\\\nATOM 604 OD2 ASP A 98 -39.777 57.382 36.299 1.00 0.00 O \\\\nATOM 605 H ASP A 98 -36.245 54.459 37.284 1.00 0.00 H \\\\nATOM 606 HA ASP A 98 -35.943 56.615 35.833 1.00 0.00 H \\\\nATOM 607 HB2 ASP A 98 -37.859 55.308 35.564 1.00 0.00 H \\\\nATOM 608 HB3 ASP A 98 -38.298 55.588 37.034 1.00 0.00 H \\\\nATOM 609 N ALA A 99 -36.256 57.153 38.928 1.00 0.00 N \\\\nATOM 610 CA ALA A 99 -36.116 58.197 39.936 1.00 0.00 C \\\\nATOM 611 C ALA A 99 -34.804 58.957 39.775 1.00 0.00 C \\\\nATOM 612 O ALA A 99 -34.739 60.151 40.088 1.00 0.00 O \\\\nATOM 613 CB ALA A 99 -36.215 57.592 41.336 1.00 0.00 C \\\\nATOM 614 H ALA A 99 -36.257 56.350 39.236 1.00 0.00 H \\\\nATOM 615 HA ALA A 99 -36.839 58.831 39.813 1.00 0.00 H \\\\nATOM 616 HB1 ALA A 99 -36.121 58.293 41.999 1.00 0.00 H \\\\nATOM 617 HB2 ALA A 99 -37.077 57.161 41.442 1.00 0.00 H \\\\nATOM 618 HB3 ALA A 99 -35.510 56.937 41.456 1.00 0.00 H \\\\nATOM 619 N LEU A 100 -33.759 58.290 39.289 1.00 0.00 N \\\\nATOM 620 CA LEU A 100 -32.497 58.939 38.963 1.00 0.00 C \\\\nATOM 621 C LEU A 100 -32.451 59.403 37.515 1.00 0.00 C \\\\nATOM 622 O LEU A 100 -31.395 59.834 37.043 1.00 0.00 O \\\\nATOM 623 CB LEU A 100 -31.317 57.998 39.236 1.00 0.00 C \\\\nATOM 624 CG LEU A 100 -31.004 57.516 40.658 1.00 0.00 C \\\\nATOM 625 CD1 LEU A 100 -31.977 56.459 41.142 1.00 0.00 C \\\\nATOM 626 CD2 LEU A 100 -29.577 56.993 40.732 1.00 0.00 C \\\\nATOM 627 H LEU A 100 -33.765 57.443 39.139 1.00 0.00 H \\\\nATOM 628 HA LEU A 100 -32.427 59.721 39.533 1.00 0.00 H \\\\nATOM 629 HB2 LEU A 100 -31.452 57.207 38.691 1.00 0.00 H \\\\nATOM 630 HB3 LEU A 100 -30.519 58.438 38.903 1.00 0.00 H \\\\nATOM 631 HG LEU A 100 -31.101 58.281 41.247 1.00 0.00 H \\\\nATOM 632 HD11 LEU A 100 -31.739 56.187 42.042 1.00 0.00 H \\\\nATOM 633 HD12 LEU A 100 -32.876 56.822 41.142 1.00 0.00 H \\\\nATOM 634 HD13 LEU A 100 -31.940 55.690 40.552 1.00 0.00 H \\\\nATOM 635 HD21 LEU A 100 -29.389 56.691 41.634 1.00 0.00 H \\\\nATOM 636 HD22 LEU A 100 -29.471 56.252 40.115 1.00 0.00 H \\\\nATOM 637 HD23 LEU A 100 -28.959 57.702 40.494 1.00 0.00 H \\\\nATOM 638 N GLY A 101 -33.575 59.322 36.808 1.00 0.00 N \\\\nATOM 639 CA GLY A 101 -33.640 59.673 35.406 1.00 0.00 C \\\\nATOM 640 C GLY A 101 -32.842 58.776 34.493 1.00 0.00 C \\\\nATOM 641 O GLY A 101 -32.617 59.133 33.336 1.00 0.00 O \\\\nATOM 642 H GLY A 101 -34.325 59.059 37.137 1.00 0.00 H \\\\nATOM 643 HA2 GLY A 101 -34.568 59.657 35.124 1.00 0.00 H \\\\nATOM 644 HA3 GLY A 101 -33.326 60.585 35.299 1.00 0.00 H \\\\nATOM 645 N LEU A 102 -32.443 57.599 34.963 1.00 0.00 N \\\\nATOM 646 CA LEU A 102 -31.626 56.677 34.182 1.00 0.00 C \\\\nATOM 647 C LEU A 102 -32.540 55.521 33.790 1.00 0.00 C \\\\nATOM 648 O LEU A 102 -32.691 54.556 34.537 1.00 0.00 O \\\\nATOM 649 CB LEU A 102 -30.424 56.182 34.989 1.00 0.00 C \\\\nATOM 650 CG LEU A 102 -29.225 57.100 35.233 1.00 0.00 C \\\\nATOM 651 CD1 LEU A 102 -28.223 56.404 36.142 1.00 0.00 C \\\\nATOM 652 CD2 LEU A 102 -28.569 57.503 33.924 1.00 0.00 C \\\\nATOM 653 H LEU A 102 -32.640 57.311 35.749 1.00 0.00 H \\\\nATOM 654 HA LEU A 102 -31.262 57.115 33.397 1.00 0.00 H \\\\nATOM 655 HB2 LEU A 102 -30.756 55.906 35.858 1.00 0.00 H \\\\nATOM 656 HB3 LEU A 102 -30.090 55.386 34.547 1.00 0.00 H \\\\nATOM 657 HG LEU A 102 -29.538 57.909 35.666 1.00 0.00 H \\\\nATOM 658 HD11 LEU A 102 -27.464 56.988 36.295 1.00 0.00 H \\\\nATOM 659 HD12 LEU A 102 -28.646 56.195 36.990 1.00 0.00 H \\\\nATOM 660 HD13 LEU A 102 -27.920 55.584 35.722 1.00 0.00 H \\\\nATOM 661 HD21 LEU A 102 -27.813 58.083 34.106 1.00 0.00 H \\\\nATOM 662 HD22 LEU A 102 -28.262 56.710 33.458 1.00 0.00 H \\\\nATOM 663 HD23 LEU A 102 -29.212 57.974 33.371 1.00 0.00 H \\\\nATOM 664 N ASP A 103 -33.137 55.609 32.607 1.00 0.00 N \\\\nATOM 665 CA ASP A 103 -34.010 54.534 32.153 1.00 0.00 C \\\\nATOM 666 C ASP A 103 -33.167 53.324 31.773 1.00 0.00 C \\\\nATOM 667 O ASP A 103 -32.287 53.414 30.911 1.00 0.00 O \\\\nATOM 668 CB ASP A 103 -34.889 54.987 30.993 1.00 0.00 C \\\\nATOM 669 CG ASP A 103 -36.336 54.555 31.171 1.00 0.00 C \\\\nATOM 670 OD1 ASP A 103 -36.767 54.386 32.333 1.00 0.00 O \\\\nATOM 671 OD2 ASP A 103 -37.041 54.372 30.156 1.00 0.00 O \\\\nATOM 672 H ASP A 103 -33.053 56.269 32.062 1.00 0.00 H \\\\nATOM 673 HA ASP A 103 -34.606 54.285 32.877 1.00 0.00 H \\\\nATOM 674 HB2 ASP A 103 -34.848 55.953 30.916 1.00 0.00 H \\\\nATOM 675 HB3 ASP A 103 -34.543 54.621 30.164 1.00 0.00 H \\\\nATOM 676 N ALA A 104 -33.445 52.194 32.416 1.00 0.00 N \\\\nATOM 677 CA ALA A 104 -32.639 50.985 32.316 1.00 0.00 C \\\\nATOM 678 C ALA A 104 -32.759 50.283 30.969 1.00 0.00 C \\\\nATOM 679 O ALA A 104 -32.088 49.263 30.775 1.00 0.00 O \\\\nATOM 680 CB ALA A 104 -33.002 50.018 33.442 1.00 0.00 C \\\\nATOM 681 H ALA A 104 -34.125 52.108 32.935 1.00 0.00 H \\\\nATOM 682 HA ALA A 104 -31.714 51.265 32.399 1.00 0.00 H \\\\nATOM 683 HB1 ALA A 104 -32.461 49.216 33.367 1.00 0.00 H \\\\nATOM 684 HB2 ALA A 104 -32.836 50.441 34.299 1.00 0.00 H \\\\nATOM 685 HB3 ALA A 104 -33.940 49.781 33.376 1.00 0.00 H \\\\nATOM 686 N ASP A 105 -33.583 50.774 30.038 1.00 0.00 N \\\\nATOM 687 CA ASP A 105 -33.655 50.119 28.737 1.00 0.00 C \\\\nATOM 688 C ASP A 105 -32.389 50.343 27.920 1.00 0.00 C \\\\nATOM 689 O ASP A 105 -32.147 49.602 26.960 1.00 0.00 O \\\\nATOM 690 CB ASP A 105 -34.855 50.636 27.932 1.00 0.00 C \\\\nATOM 691 CG ASP A 105 -36.060 50.947 28.797 1.00 0.00 C \\\\nATOM 692 OD1 ASP A 105 -36.447 50.095 29.619 1.00 0.00 O \\\\nATOM 693 OD2 ASP A 105 -36.626 52.051 28.649 1.00 0.00 O \\\\nATOM 694 H ASP A 105 -34.091 51.461 30.137 1.00 0.00 H \\\\nATOM 695 HA ASP A 105 -33.755 49.170 28.909 1.00 0.00 H \\\\nATOM 696 HB2 ASP A 105 -34.594 51.436 27.450 1.00 0.00 H \\\\nATOM 697 HB3 ASP A 105 -35.102 49.973 27.268 1.00 0.00 H \\\\nATOM 698 N ALA A 106 -31.585 51.345 28.277 1.00 0.00 N \\\\nATOM 699 CA ALA A 106 -30.301 51.601 27.635 1.00 0.00 C \\\\nATOM 700 C ALA A 106 -29.098 51.237 28.492 1.00 0.00 C \\\\nATOM 701 O ALA A 106 -28.041 50.925 27.944 1.00 0.00 O \\\\nATOM 702 CB ALA A 106 -30.190 53.076 27.230 1.00 0.00 C \\\\nATOM 703 H ALA A 106 -31.774 51.900 28.906 1.00 0.00 H \\\\nATOM 704 HA ALA A 106 -30.283 51.024 26.855 1.00 0.00 H \\\\nATOM 705 HB1 ALA A 106 -29.332 53.231 26.805 1.00 0.00 H \\\\nATOM 706 HB2 ALA A 106 -30.902 53.296 26.610 1.00 0.00 H \\\\nATOM 707 HB3 ALA A 106 -30.265 53.635 28.019 1.00 0.00 H \\\\nATOM 708 N LEU A 107 -29.237 51.251 29.815 1.00 0.00 N \\\\nATOM 709 CA LEU A 107 -28.123 50.911 30.692 1.00 0.00 C \\\\nATOM 710 C LEU A 107 -27.751 49.442 30.553 1.00 0.00 C \\\\nATOM 711 O LEU A 107 -28.615 48.579 30.374 1.00 0.00 O \\\\nATOM 712 CB LEU A 107 -28.477 51.216 32.149 1.00 0.00 C \\\\nATOM 713 CG LEU A 107 -28.275 52.627 32.704 1.00 0.00 C \\\\nATOM 714 CD1 LEU A 107 -29.121 52.845 33.951 1.00 0.00 C \\\\nATOM 715 CD2 LEU A 107 -26.803 52.873 32.993 1.00 0.00 C \\\\nATOM 716 H LEU A 107 -29.966 51.454 30.223 1.00 0.00 H \\\\nATOM 717 HA LEU A 107 -27.362 51.451 30.429 1.00 0.00 H \\\\nATOM 718 HB2 LEU A 107 -29.412 50.988 32.273 1.00 0.00 H \\\\nATOM 719 HB3 LEU A 107 -27.961 50.611 32.704 1.00 0.00 H \\\\nATOM 720 HG LEU A 107 -28.566 53.266 32.035 1.00 0.00 H \\\\nATOM 721 HD11 LEU A 107 -28.978 53.744 34.286 1.00 0.00 H \\\\nATOM 722 HD12 LEU A 107 -30.058 52.727 33.731 1.00 0.00 H \\\\nATOM 723 HD13 LEU A 107 -28.866 52.203 34.632 1.00 0.00 H \\\\nATOM 724 HD21 LEU A 107 -26.687 53.770 33.344 1.00 0.00 H \\\\nATOM 725 HD22 LEU A 107 -26.489 52.228 33.646 1.00 0.00 H \\\\nATOM 726 HD23 LEU A 107 -26.292 52.779 32.174 1.00 0.00 H \\\\nATOM 727 N ARG A 108 -26.450 49.160 30.644 1.00 0.00 N \\\\nATOM 728 CA ARG A 108 -25.963 47.799 30.794 1.00 0.00 C \\\\nATOM 729 C ARG A 108 -24.772 47.808 31.744 1.00 0.00 C \\\\nATOM 730 O ARG A 108 -24.081 48.823 31.895 1.00 0.00 O \\\\nATOM 731 CB ARG A 108 -25.528 47.194 29.444 1.00 0.00 C \\\\nATOM 732 CG ARG A 108 -26.341 47.646 28.239 1.00 0.00 C \\\\nATOM 733 CD ARG A 108 -25.669 47.293 26.912 1.00 0.00 C \\\\nATOM 734 NE ARG A 108 -24.218 47.503 26.936 1.00 0.00 N \\\\nATOM 735 CZ ARG A 108 -23.569 48.350 26.141 1.00 0.00 C \\\\nATOM 736 NH1 ARG A 108 -24.234 49.060 25.239 1.00 0.00 N \\\\nATOM 737 NH2 ARG A 108 -22.253 48.471 26.235 1.00 0.00 N \\\\nATOM 738 H ARG A 108 -25.830 49.755 30.620 1.00 0.00 H \\\\nATOM 739 HA ARG A 108 -26.685 47.254 31.146 1.00 0.00 H \\\\nATOM 740 HB2 ARG A 108 -24.597 47.418 29.290 1.00 0.00 H \\\\nATOM 741 HB3 ARG A 108 -25.580 46.227 29.507 1.00 0.00 H \\\\nATOM 742 HG2 ARG A 108 -27.219 47.235 28.273 1.00 0.00 H \\\\nATOM 743 HG3 ARG A 108 -26.475 48.606 28.285 1.00 0.00 H \\\\nATOM 744 HD2 ARG A 108 -25.854 46.365 26.697 1.00 0.00 H \\\\nATOM 745 HD3 ARG A 108 -26.058 47.831 26.204 1.00 0.00 H \\\\nATOM 746 HE ARG A 108 -23.756 47.049 27.501 1.00 0.00 H \\\\nATOM 747 HH11 ARG A 108 -25.087 48.973 25.167 1.00 0.00 H \\\\nATOM 748 HH12 ARG A 108 -23.812 49.607 24.726 1.00 0.00 H \\\\nATOM 749 HH21 ARG A 108 -21.818 48.002 26.810 1.00 0.00 H \\\\nATOM 750 HH22 ARG A 108 -21.834 49.018 25.721 1.00 0.00 H \\\\nATOM 751 N LEU A 109 -24.535 46.662 32.384 1.00 0.00 N \\\\nATOM 752 CA LEU A 109 -23.462 46.528 33.357 1.00 0.00 C \\\\nATOM 753 C LEU A 109 -22.677 45.239 33.083 1.00 0.00 C \\\\nATOM 754 O LEU A 109 -23.285 44.191 32.855 1.00 0.00 O \\\\nATOM 755 CB LEU A 109 -24.011 46.518 34.788 1.00 0.00 C \\\\nATOM 756 CG LEU A 109 -23.014 46.375 35.943 1.00 0.00 C \\\\nATOM 757 CD1 LEU A 109 -22.429 47.731 36.304 1.00 0.00 C \\\\nATOM 758 CD2 LEU A 109 -23.686 45.751 37.159 1.00 0.00 C \\\\nATOM 759 H LEU A 109 -24.993 45.944 32.264 1.00 0.00 H \\\\nATOM 760 HA LEU A 109 -22.871 47.292 33.270 1.00 0.00 H \\\\nATOM 761 HB2 LEU A 109 -24.504 47.342 34.922 1.00 0.00 H \\\\nATOM 762 HB3 LEU A 109 -24.650 45.791 34.856 1.00 0.00 H \\\\nATOM 763 HG LEU A 109 -22.295 45.790 35.656 1.00 0.00 H \\\\nATOM 764 HD11 LEU A 109 -21.800 47.628 37.035 1.00 0.00 H \\\\nATOM 765 HD12 LEU A 109 -21.970 48.101 35.534 1.00 0.00 H \\\\nATOM 766 HD13 LEU A 109 -23.143 48.330 36.574 1.00 0.00 H \\\\nATOM 767 HD21 LEU A 109 -23.041 45.668 37.879 1.00 0.00 H \\\\nATOM 768 HD22 LEU A 109 -24.421 46.314 37.447 1.00 0.00 H \\\\nATOM 769 HD23 LEU A 109 -24.025 44.872 36.927 1.00 0.00 H \\\\nATOM 770 N PRO A 110 -21.350 45.307 33.109 1.00 0.00 N \\\\nATOM 771 CA PRO A 110 -20.557 44.094 32.854 1.00 0.00 C \\\\nATOM 772 C PRO A 110 -20.709 43.083 33.977 1.00 0.00 C \\\\nATOM 773 O PRO A 110 -20.977 43.429 35.129 1.00 0.00 O \\\\nATOM 774 CB PRO A 110 -19.121 44.626 32.769 1.00 0.00 C \\\\nATOM 775 CG PRO A 110 -19.148 45.926 33.504 1.00 0.00 C \\\\nATOM 776 CD PRO A 110 -20.508 46.503 33.254 1.00 0.00 C \\\\nATOM 777 HA PRO A 110 -20.835 43.622 32.053 1.00 0.00 H \\\\nATOM 778 HB2 PRO A 110 -18.492 44.007 33.172 1.00 0.00 H \\\\nATOM 779 HB3 PRO A 110 -18.846 44.749 31.847 1.00 0.00 H \\\\nATOM 780 HG2 PRO A 110 -18.994 45.794 34.453 1.00 0.00 H \\\\nATOM 781 HG3 PRO A 110 -18.452 46.522 33.185 1.00 0.00 H \\\\nATOM 782 HD2 PRO A 110 -20.802 47.063 33.990 1.00 0.00 H \\\\nATOM 783 HD3 PRO A 110 -20.524 47.053 32.455 1.00 0.00 H \\\\nATOM 784 N ALA A 111 -20.531 41.812 33.622 1.00 0.00 N \\\\nATOM 785 CA ALA A 111 -20.717 40.712 34.554 1.00 0.00 C \\\\nATOM 786 C ALA A 111 -19.686 39.630 34.268 1.00 0.00 C \\\\nATOM 787 O ALA A 111 -19.143 39.535 33.165 1.00 0.00 O \\\\nATOM 788 CB ALA A 111 -22.133 40.131 34.465 1.00 0.00 C \\\\nATOM 789 H ALA A 111 -20.298 41.567 32.831 1.00 0.00 H \\\\nATOM 790 HA ALA A 111 -20.597 41.051 35.455 1.00 0.00 H \\\\nATOM 791 HB1 ALA A 111 -22.224 39.401 35.098 1.00 0.00 H \\\\nATOM 792 HB2 ALA A 111 -22.780 40.822 34.674 1.00 0.00 H \\\\nATOM 793 HB3 ALA A 111 -22.292 39.801 33.567 1.00 0.00 H \\\\nATOM 794 N HIS A 112 -19.415 38.816 35.285 1.00 0.00 N \\\\nATOM 795 CA HIS A 112 -18.424 37.752 35.207 1.00 0.00 C \\\\nATOM 796 C HIS A 112 -19.110 36.405 35.375 1.00 0.00 C \\\\nATOM 797 O HIS A 112 -20.079 36.283 36.131 1.00 0.00 O \\\\nATOM 798 CB HIS A 112 -17.339 37.934 36.277 1.00 0.00 C \\\\nATOM 799 CG HIS A 112 -16.999 39.367 36.550 1.00 0.00 C \\\\nATOM 800 ND1 HIS A 112 -16.392 40.180 35.617 1.00 0.00 N \\\\nATOM 801 CD2 HIS A 112 -17.185 40.133 37.651 1.00 0.00 C \\\\nATOM 802 CE1 HIS A 112 -16.218 41.384 36.132 1.00 0.00 C \\\\nATOM 803 NE2 HIS A 112 -16.688 41.382 37.366 1.00 0.00 N \\\\nATOM 804 H HIS A 112 -19.808 38.869 36.048 1.00 0.00 H \\\\nATOM 805 HA HIS A 112 -17.995 37.789 34.338 1.00 0.00 H \\\\nATOM 806 HB2 HIS A 112 -17.635 37.517 37.101 1.00 0.00 H \\\\nATOM 807 HB3 HIS A 112 -16.537 37.467 35.996 1.00 0.00 H \\\\nATOM 808 HD1 HIS A 112 -16.162 39.941 34.823 1.00 0.00 H \\\\nATOM 809 HD2 HIS A 112 -17.576 39.864 38.451 1.00 0.00 H \\\\nATOM 810 HE1 HIS A 112 -15.830 42.110 35.699 1.00 0.00 H \\\\nATOM 811 HE2 HIS A 112 -16.684 42.053 37.904 1.00 0.00 H \\\\nATOM 812 N LEU A 113 -18.605 35.396 34.669 1.00 0.00 N \\\\nATOM 813 CA LEU A 113 -19.199 34.066 34.659 1.00 0.00 C \\\\nATOM 814 C LEU A 113 -18.239 33.078 35.307 1.00 0.00 C \\\\nATOM 815 O LEU A 113 -17.082 32.965 34.890 1.00 0.00 O \\\\nATOM 816 CB LEU A 113 -19.532 33.636 33.229 1.00 0.00 C \\\\nATOM 817 CG LEU A 113 -20.495 32.461 33.003 1.00 0.00 C \\\\nATOM 818 CD1 LEU A 113 -19.780 31.116 33.052 1.00 0.00 C \\\\nATOM 819 CD2 LEU A 113 -21.632 32.502 34.012 1.00 0.00 C \\\\nATOM 820 H LEU A 113 -17.902 35.467 34.179 1.00 0.00 H \\\\nATOM 821 HA LEU A 113 -20.026 34.083 35.165 1.00 0.00 H \\\\nATOM 822 HB2 LEU A 113 -19.901 34.407 32.771 1.00 0.00 H \\\\nATOM 823 HB3 LEU A 113 -18.696 33.417 32.788 1.00 0.00 H \\\\nATOM 824 HG LEU A 113 -20.864 32.557 32.111 1.00 0.00 H \\\\nATOM 825 HD11 LEU A 113 -20.421 30.403 32.905 1.00 0.00 H \\\\nATOM 826 HD12 LEU A 113 -19.100 31.086 32.361 1.00 0.00 H \\\\nATOM 827 HD13 LEU A 113 -19.364 31.002 33.921 1.00 0.00 H \\\\nATOM 828 HD21 LEU A 113 -22.230 31.755 33.856 1.00 0.00 H \\\\nATOM 829 HD22 LEU A 113 -21.270 32.444 34.910 1.00 0.00 H \\\\nATOM 830 HD23 LEU A 113 -22.122 33.334 33.914 1.00 0.00 H \\\\nATOM 831 N PHE A 114 -18.723 32.370 36.323 1.00 0.00 N \\\\nATOM 832 CA PHE A 114 -18.017 31.254 36.936 1.00 0.00 C \\\\nATOM 833 C PHE A 114 -18.875 30.004 36.806 1.00 0.00 C \\\\nATOM 834 O PHE A 114 -20.099 30.067 36.962 1.00 0.00 O \\\\nATOM 835 CB PHE A 114 -17.703 31.534 38.411 1.00 0.00 C \\\\nATOM 836 CG PHE A 114 -17.000 32.843 38.645 1.00 0.00 C \\\\nATOM 837 CD1 PHE A 114 -15.622 32.935 38.546 1.00 0.00 C \\\\nATOM 838 CD2 PHE A 114 -17.720 33.983 38.967 1.00 0.00 C \\\\nATOM 839 CE1 PHE A 114 -14.974 34.139 38.763 1.00 0.00 C \\\\nATOM 840 CE2 PHE A 114 -17.079 35.190 39.186 1.00 0.00 C \\\\nATOM 841 CZ PHE A 114 -15.704 35.266 39.083 1.00 0.00 C \\\\nATOM 842 H PHE A 114 -19.488 32.530 36.682 1.00 0.00 H \\\\nATOM 843 HA PHE A 114 -17.171 31.126 36.480 1.00 0.00 H \\\\nATOM 844 HB2 PHE A 114 -18.531 31.527 38.916 1.00 0.00 H \\\\nATOM 845 HB3 PHE A 114 -17.153 30.815 38.758 1.00 0.00 H \\\\nATOM 846 HD1 PHE A 114 -15.126 32.179 38.331 1.00 0.00 H \\\\nATOM 847 HD2 PHE A 114 -18.646 33.936 39.037 1.00 0.00 H \\\\nATOM 848 HE1 PHE A 114 -14.048 34.188 38.693 1.00 0.00 H \\\\nATOM 849 HE2 PHE A 114 -17.573 35.948 39.402 1.00 0.00 H \\\\nATOM 850 HZ PHE A 114 -15.270 36.076 39.229 1.00 0.00 H \\\\nATOM 851 N GLY A 115 -18.243 28.875 36.518 1.00 0.00 N \\\\nATOM 852 CA GLY A 115 -18.982 27.641 36.316 1.00 0.00 C \\\\nATOM 853 C GLY A 115 -18.159 26.420 36.651 1.00 0.00 C \\\\nATOM 854 O GLY A 115 -16.940 26.394 36.454 1.00 0.00 O \\\\nATOM 855 H GLY A 115 -17.390 28.803 36.436 1.00 0.00 H \\\\nATOM 856 HA2 GLY A 115 -19.781 27.651 36.866 1.00 0.00 H \\\\nATOM 857 HA3 GLY A 115 -19.274 27.589 35.392 1.00 0.00 H \\\\nATOM 858 N VAL A 116 -18.839 25.398 37.168 1.00 0.00 N \\\\nATOM 859 CA VAL A 116 -18.249 24.096 37.450 1.00 0.00 C \\\\nATOM 860 C VAL A 116 -19.075 23.041 36.728 1.00 0.00 C \\\\nATOM 861 O VAL A 116 -20.310 23.087 36.749 1.00 0.00 O \\\\nATOM 862 CB VAL A 116 -18.193 23.811 38.967 1.00 0.00 C \\\\nATOM 863 CG1 VAL A 116 -17.887 22.345 39.233 1.00 0.00 C \\\\nATOM 864 CG2 VAL A 116 -17.157 24.702 39.636 1.00 0.00 C \\\\nATOM 865 H VAL A 116 -19.674 25.446 37.368 1.00 0.00 H \\\\nATOM 866 HA VAL A 116 -17.332 24.080 37.134 1.00 0.00 H \\\\nATOM 867 HB VAL A 116 -19.064 24.010 39.345 1.00 0.00 H \\\\nATOM 868 HG11 VAL A 116 -17.857 22.189 40.190 1.00 0.00 H \\\\nATOM 869 HG12 VAL A 116 -18.580 21.793 38.838 1.00 0.00 H \\\\nATOM 870 HG13 VAL A 116 -17.029 22.117 38.841 1.00 0.00 H \\\\nATOM 871 HG21 VAL A 116 -17.133 24.513 40.587 1.00 0.00 H \\\\nATOM 872 HG22 VAL A 116 -16.284 24.530 39.250 1.00 0.00 H \\\\nATOM 873 HG23 VAL A 116 -17.393 25.633 39.498 1.00 0.00 H \\\\nATOM 874 N PHE A 117 -18.395 22.094 36.084 1.00 0.00 N \\\\nATOM 875 CA PHE A 117 -19.049 21.104 35.229 1.00 0.00 C \\\\nATOM 876 C PHE A 117 -18.511 19.716 35.565 1.00 0.00 C \\\\nATOM 877 O PHE A 117 -17.410 19.350 35.144 1.00 0.00 O \\\\nATOM 878 CB PHE A 117 -18.842 21.454 33.759 1.00 0.00 C \\\\nATOM 879 CG PHE A 117 -19.021 22.917 33.462 1.00 0.00 C \\\\nATOM 880 CD1 PHE A 117 -20.289 23.456 33.320 1.00 0.00 C \\\\nATOM 881 CD2 PHE A 117 -17.926 23.758 33.350 1.00 0.00 C \\\\nATOM 882 CE1 PHE A 117 -20.461 24.802 33.057 1.00 0.00 C \\\\nATOM 883 CE2 PHE A 117 -18.094 25.105 33.090 1.00 0.00 C \\\\nATOM 884 CZ PHE A 117 -19.362 25.628 32.942 1.00 0.00 C \\\\nATOM 885 H PHE A 117 -17.541 22.007 36.130 1.00 0.00 H \\\\nATOM 886 HA PHE A 117 -20.005 21.107 35.392 1.00 0.00 H \\\\nATOM 887 HB2 PHE A 117 -17.950 21.183 33.492 1.00 0.00 H \\\\nATOM 888 HB3 PHE A 117 -19.467 20.943 33.221 1.00 0.00 H \\\\nATOM 889 HD1 PHE A 117 -21.034 22.905 33.403 1.00 0.00 H \\\\nATOM 890 HD2 PHE A 117 -17.068 23.412 33.451 1.00 0.00 H \\\\nATOM 891 HE1 PHE A 117 -21.317 25.151 32.958 1.00 0.00 H \\\\nATOM 892 HE2 PHE A 117 -17.351 25.660 33.015 1.00 0.00 H \\\\nATOM 893 HZ PHE A 117 -19.476 26.534 32.765 1.00 0.00 H \\\\nATOM 894 N ASP A 118 -19.293 18.950 36.323 1.00 0.00 N \\\\nATOM 895 CA ASP A 118 -18.939 17.585 36.698 1.00 0.00 C \\\\nATOM 896 C ASP A 118 -19.370 16.652 35.573 1.00 0.00 C \\\\nATOM 897 O ASP A 118 -20.564 16.382 35.405 1.00 0.00 O \\\\nATOM 898 CB ASP A 118 -19.606 17.206 38.020 1.00 0.00 C \\\\nATOM 899 CG ASP A 118 -19.143 15.857 38.560 1.00 0.00 C \\\\nATOM 900 OD1 ASP A 118 -18.640 15.016 37.785 1.00 0.00 O \\\\nATOM 901 OD2 ASP A 118 -19.288 15.637 39.782 1.00 0.00 O \\\\nATOM 902 H ASP A 118 -20.050 19.211 36.636 1.00 0.00 H \\\\nATOM 903 HA ASP A 118 -17.981 17.510 36.828 1.00 0.00 H \\\\nATOM 904 HB2 ASP A 118 -19.419 17.893 38.679 1.00 0.00 H \\\\nATOM 905 HB3 ASP A 118 -20.568 17.186 37.896 1.00 0.00 H \\\\nATOM 906 N GLY A 119 -18.400 16.155 34.809 1.00 0.00 N \\\\nATOM 907 CA GLY A 119 -18.709 15.237 33.735 1.00 0.00 C \\\\nATOM 908 C GLY A 119 -18.836 13.802 34.214 1.00 0.00 C \\\\nATOM 909 O GLY A 119 -18.279 13.406 35.236 1.00 0.00 O \\\\nATOM 910 H GLY A 119 -17.565 16.339 34.900 1.00 0.00 H \\\\nATOM 911 HA2 GLY A 119 -19.538 15.508 33.311 1.00 0.00 H \\\\nATOM 912 HA3 GLY A 119 -18.015 15.289 33.060 1.00 0.00 H \\\\nATOM 913 N HIS A 120 -19.594 13.016 33.451 1.00 0.00 N \\\\nATOM 914 CA HIS A 120 -19.712 11.582 33.676 1.00 0.00 C \\\\nATOM 915 C HIS A 120 -19.697 10.867 32.334 1.00 0.00 C \\\\nATOM 916 O HIS A 120 -20.082 11.435 31.307 1.00 0.00 O \\\\nATOM 917 CB HIS A 120 -20.983 11.220 34.458 1.00 0.00 C \\\\nATOM 918 CG HIS A 120 -22.212 11.931 33.983 1.00 0.00 C \\\\nATOM 919 ND1 HIS A 120 -22.638 13.124 34.524 1.00 0.00 N \\\\nATOM 920 CD2 HIS A 120 -23.112 11.612 33.022 1.00 0.00 C \\\\nATOM 921 CE1 HIS A 120 -23.745 13.512 33.916 1.00 0.00 C \\\\nATOM 922 NE2 HIS A 120 -24.054 12.612 33.000 1.00 0.00 N \\\\nATOM 923 H HIS A 120 -20.056 13.304 32.785 1.00 0.00 H \\\\nATOM 924 HA HIS A 120 -18.958 11.297 34.216 1.00 0.00 H \\\\nATOM 925 HB2 HIS A 120 -21.129 10.263 34.395 1.00 0.00 H \\\\nATOM 926 HB3 HIS A 120 -20.844 11.425 35.396 1.00 0.00 H \\\\nATOM 927 HD1 HIS A 120 -22.244 13.550 35.159 1.00 0.00 H \\\\nATOM 928 HD2 HIS A 120 -23.095 10.857 32.479 1.00 0.00 H \\\\nATOM 929 HE1 HIS A 120 -24.225 14.287 34.101 1.00 0.00 H \\\\nATOM 930 HE2 HIS A 120 -24.734 12.646 32.475 1.00 0.00 H \\\\nATOM 931 N GLY A 121 -19.238 9.615 32.352 1.00 0.00 N \\\\nATOM 932 CA GLY A 121 -19.065 8.860 31.129 1.00 0.00 C \\\\nATOM 933 C GLY A 121 -17.913 9.327 30.272 1.00 0.00 C \\\\nATOM 934 O GLY A 121 -17.769 8.859 29.139 1.00 0.00 O \\\\nATOM 935 H GLY A 121 -19.023 9.190 33.068 1.00 0.00 H \\\\nATOM 936 HA2 GLY A 121 -18.930 7.926 31.354 1.00 0.00 H \\\\nATOM 937 HA3 GLY A 121 -19.883 8.912 30.610 1.00 0.00 H \\\\nATOM 938 N GLY A 122 -17.098 10.253 30.763 1.00 0.00 N \\\\nATOM 939 CA GLY A 122 -16.076 10.847 29.925 1.00 0.00 C \\\\nATOM 940 C GLY A 122 -15.982 12.325 30.233 1.00 0.00 C \\\\nATOM 941 O GLY A 122 -16.791 12.834 31.010 1.00 0.00 O \\\\nATOM 942 H GLY A 122 -17.122 10.547 31.571 1.00 0.00 H \\\\nATOM 943 HA2 GLY A 122 -15.221 10.417 30.084 1.00 0.00 H \\\\nATOM 944 HA3 GLY A 122 -16.291 10.713 28.989 1.00 0.00 H \\\\nATOM 945 N ALA A 123 -15.020 13.042 29.661 1.00 0.00 N \\\\nATOM 946 CA ALA A 123 -14.846 14.447 30.008 1.00 0.00 C \\\\nATOM 947 C ALA A 123 -15.188 15.415 28.898 1.00 0.00 C \\\\nATOM 948 O ALA A 123 -15.158 16.643 29.119 1.00 0.00 O \\\\nATOM 949 CB ALA A 123 -13.401 14.696 30.431 1.00 0.00 C \\\\nATOM 950 H ALA A 123 -14.465 12.739 29.078 1.00 0.00 H \\\\nATOM 951 HA ALA A 123 -15.471 14.614 30.731 1.00 0.00 H \\\\nATOM 952 HB1 ALA A 123 -13.288 15.631 30.661 1.00 0.00 H \\\\nATOM 953 HB2 ALA A 123 -13.190 14.146 31.201 1.00 0.00 H \\\\nATOM 954 HB3 ALA A 123 -12.806 14.469 29.699 1.00 0.00 H \\\\nATOM 955 N GLU A 124 -15.445 14.877 27.710 1.00 0.00 N \\\\nATOM 956 CA GLU A 124 -15.726 15.672 26.517 1.00 0.00 C \\\\nATOM 957 C GLU A 124 -16.929 16.602 26.601 1.00 0.00 C \\\\nATOM 958 O GLU A 124 -16.956 17.644 25.946 1.00 0.00 O \\\\nATOM 959 CB GLU A 124 -15.870 14.757 25.297 1.00 0.00 C \\\\nATOM 960 CG GLU A 124 -16.331 13.347 25.629 1.00 0.00 C \\\\nATOM 961 CD GLU A 124 -15.182 12.362 25.709 1.00 0.00 C \\\\nATOM 962 OE1 GLU A 124 -14.615 12.195 26.809 1.00 0.00 O \\\\nATOM 963 OE2 GLU A 124 -14.845 11.754 24.671 1.00 0.00 O \\\\nATOM 964 H GLU A 124 -15.461 14.028 27.571 1.00 0.00 H \\\\nATOM 965 HA GLU A 124 -14.959 16.260 26.434 1.00 0.00 H \\\\nATOM 966 HB2 GLU A 124 -16.502 15.156 24.678 1.00 0.00 H \\\\nATOM 967 HB3 GLU A 124 -15.016 14.708 24.839 1.00 0.00 H \\\\nATOM 968 HG2 GLU A 124 -16.804 13.356 26.476 1.00 0.00 H \\\\nATOM 969 HG3 GLU A 124 -16.961 13.049 24.955 1.00 0.00 H \\\\nATOM 970 N VAL A 125 -17.925 16.232 27.395 1.00 0.00 N \\\\nATOM 971 CA VAL A 125 -19.125 17.070 27.505 1.00 0.00 C \\\\nATOM 972 C VAL A 125 -18.894 18.191 28.519 1.00 0.00 C \\\\nATOM 973 O VAL A 125 -19.302 19.336 28.294 1.00 0.00 O \\\\nATOM 974 CB VAL A 125 -20.395 16.271 27.878 1.00 0.00 C \\\\nATOM 975 CG1 VAL A 125 -21.522 17.240 28.292 1.00 0.00 C \\\\nATOM 976 CG2 VAL A 125 -20.915 15.436 26.726 1.00 0.00 C \\\\nATOM 977 H VAL A 125 -17.933 15.516 27.872 1.00 0.00 H \\\\nATOM 978 HA VAL A 125 -19.281 17.446 26.625 1.00 0.00 H \\\\nATOM 979 HB VAL A 125 -20.144 15.681 28.606 1.00 0.00 H \\\\nATOM 980 HG11 VAL A 125 -22.316 16.733 28.525 1.00 0.00 H \\\\nATOM 981 HG12 VAL A 125 -21.236 17.761 29.058 1.00 0.00 H \\\\nATOM 982 HG13 VAL A 125 -21.724 17.836 27.554 1.00 0.00 H \\\\nATOM 983 HG21 VAL A 125 -21.709 14.955 27.007 1.00 0.00 H \\\\nATOM 984 HG22 VAL A 125 -21.136 16.015 25.980 1.00 0.00 H \\\\nATOM 985 HG23 VAL A 125 -20.234 14.802 26.452 1.00 0.00 H \\\\nATOM 986 N ALA A 126 -18.213 17.894 29.634 1.00 0.00 N \\\\nATOM 987 CA ALA A 126 -17.873 18.939 30.601 1.00 0.00 C \\\\nATOM 988 C ALA A 126 -16.939 19.976 29.993 1.00 0.00 C \\\\nATOM 989 O ALA A 126 -17.104 21.182 30.218 1.00 0.00 O \\\\nATOM 990 CB ALA A 126 -17.247 18.329 31.853 1.00 0.00 C \\\\nATOM 991 H ALA A 126 -17.944 17.105 29.844 1.00 0.00 H \\\\nATOM 992 HA ALA A 126 -18.696 19.388 30.851 1.00 0.00 H \\\\nATOM 993 HB1 ALA A 126 -17.028 19.034 32.482 1.00 0.00 H \\\\nATOM 994 HB2 ALA A 126 -17.876 17.714 32.263 1.00 0.00 H \\\\nATOM 995 HB3 ALA A 126 -16.439 17.850 31.611 1.00 0.00 H \\\\nATOM 996 N ASN A 127 -15.936 19.521 29.236 1.00 0.00 N \\\\nATOM 997 CA ASN A 127 -15.028 20.451 28.571 1.00 0.00 C \\\\nATOM 998 C ASN A 127 -15.772 21.329 27.572 1.00 0.00 C \\\\nATOM 999 O ASN A 127 -15.450 22.513 27.411 1.00 0.00 O \\\\nATOM 1000 CB ASN A 127 -13.900 19.688 27.876 1.00 0.00 C \\\\nATOM 1001 CG ASN A 127 -12.859 19.169 28.852 1.00 0.00 C \\\\nATOM 1002 OD1 ASN A 127 -12.704 19.696 29.953 1.00 0.00 O \\\\nATOM 1003 ND2 ASN A 127 -12.140 18.128 28.450 1.00 0.00 N \\\\nATOM 1004 H ASN A 127 -15.768 18.689 29.098 1.00 0.00 H \\\\nATOM 1005 HA ASN A 127 -14.643 21.030 29.248 1.00 0.00 H \\\\nATOM 1006 HB2 ASN A 127 -14.275 18.943 27.382 1.00 0.00 H \\\\nATOM 1007 HB3 ASN A 127 -13.471 20.270 27.230 1.00 0.00 H \\\\nATOM 1008 HD21 ASN A 127 -11.538 17.796 28.967 1.00 0.00 H \\\\nATOM 1009 HD22 ASN A 127 -12.276 17.786 27.673 1.00 0.00 H \\\\nATOM 1010 N TYR A 128 -16.761 20.761 26.881 1.00 0.00 N \\\\nATOM 1011 CA TYR A 128 -17.553 21.552 25.946 1.00 0.00 C \\\\nATOM 1012 C TYR A 128 -18.332 22.643 26.669 1.00 0.00 C \\\\nATOM 1013 O TYR A 128 -18.499 23.750 26.143 1.00 0.00 O \\\\nATOM 1014 CB TYR A 128 -18.502 20.651 25.159 1.00 0.00 C \\\\nATOM 1015 CG TYR A 128 -19.117 21.347 23.970 1.00 0.00 C \\\\nATOM 1016 CD1 TYR A 128 -18.466 21.370 22.745 1.00 0.00 C \\\\nATOM 1017 CD2 TYR A 128 -20.338 22.001 24.077 1.00 0.00 C \\\\nATOM 1018 CE1 TYR A 128 -19.019 22.013 21.653 1.00 0.00 C \\\\nATOM 1019 CE2 TYR A 128 -20.899 22.650 22.990 1.00 0.00 C \\\\nATOM 1020 CZ TYR A 128 -20.235 22.652 21.782 1.00 0.00 C \\\\nATOM 1021 OH TYR A 128 -20.785 23.295 20.696 1.00 0.00 O \\\\nATOM 1022 H TYR A 128 -16.985 19.933 26.939 1.00 0.00 H \\\\nATOM 1023 HA TYR A 128 -16.944 21.982 25.326 1.00 0.00 H \\\\nATOM 1024 HB2 TYR A 128 -18.019 19.867 24.855 1.00 0.00 H \\\\nATOM 1025 HB3 TYR A 128 -19.208 20.340 25.747 1.00 0.00 H \\\\nATOM 1026 HD1 TYR A 128 -17.643 20.945 22.657 1.00 0.00 H \\\\nATOM 1027 HD2 TYR A 128 -20.786 22.003 24.892 1.00 0.00 H \\\\nATOM 1028 HE1 TYR A 128 -18.574 22.015 20.836 1.00 0.00 H \\\\nATOM 1029 HE2 TYR A 128 -21.718 23.082 23.074 1.00 0.00 H \\\\nATOM 1030 HH TYR A 128 -21.140 24.014 20.946 1.00 0.00 H \\\\nATOM 1031 N CYS A 129 -18.829 22.346 27.873 1.00 0.00 N \\\\nATOM 1032 CA CYS A 129 -19.568 23.348 28.635 1.00 0.00 C \\\\nATOM 1033 C CYS A 129 -18.667 24.505 29.049 1.00 0.00 C \\\\nATOM 1034 O CYS A 129 -19.085 25.669 29.015 1.00 0.00 O \\\\nATOM 1035 CB CYS A 129 -20.212 22.703 29.863 1.00 0.00 C \\\\nATOM 1036 SG CYS A 129 -21.643 21.657 29.506 1.00 0.00 S \\\\nATOM 1037 H CYS A 129 -18.750 21.582 28.259 1.00 0.00 H \\\\nATOM 1038 HA CYS A 129 -20.266 23.708 28.065 1.00 0.00 H \\\\nATOM 1039 HB2 CYS A 129 -19.543 22.170 30.321 1.00 0.00 H \\\\nATOM 1040 HB3 CYS A 129 -20.484 23.404 30.476 1.00 0.00 H \\\\nATOM 1041 HG CYS A 129 -21.276 20.642 28.981 1.00 0.00 H \\\\nATOM 1042 N ARG A 130 -17.431 24.201 29.455 1.00 0.00 N \\\\nATOM 1043 CA ARG A 130 -16.488 25.254 29.819 1.00 0.00 C \\\\nATOM 1044 C ARG A 130 -16.202 26.178 28.640 1.00 0.00 C \\\\nATOM 1045 O ARG A 130 -16.084 27.397 28.811 1.00 0.00 O \\\\nATOM 1046 CB ARG A 130 -15.194 24.632 30.347 1.00 0.00 C \\\\nATOM 1047 CG ARG A 130 -13.960 25.511 30.191 1.00 0.00 C \\\\nATOM 1048 CD ARG A 130 -12.681 24.705 30.357 1.00 0.00 C \\\\nATOM 1049 NE ARG A 130 -12.345 23.953 29.149 1.00 0.00 N \\\\nATOM 1050 CZ ARG A 130 -11.744 22.768 29.149 1.00 0.00 C \\\\nATOM 1051 NH1 ARG A 130 -11.410 22.192 30.296 1.00 0.00 N \\\\nATOM 1052 NH2 ARG A 130 -11.477 22.158 28.003 1.00 0.00 N \\\\nATOM 1053 H ARG A 130 -17.125 23.400 29.525 1.00 0.00 H \\\\nATOM 1054 HA ARG A 130 -16.888 25.793 30.519 1.00 0.00 H \\\\nATOM 1055 HB2 ARG A 130 -15.310 24.421 31.287 1.00 0.00 H \\\\nATOM 1056 HB3 ARG A 130 -15.040 23.793 29.885 1.00 0.00 H \\\\nATOM 1057 HG2 ARG A 130 -13.968 25.931 29.317 1.00 0.00 H \\\\nATOM 1058 HG3 ARG A 130 -13.983 26.224 30.849 1.00 0.00 H \\\\nATOM 1059 HD2 ARG A 130 -11.950 25.303 30.578 1.00 0.00 H \\\\nATOM 1060 HD3 ARG A 130 -12.781 24.091 31.101 1.00 0.00 H \\\\nATOM 1061 HE ARG A 130 -12.550 24.300 28.389 1.00 0.00 H \\\\nATOM 1062 HH11 ARG A 130 -11.582 22.586 31.041 1.00 0.00 H \\\\nATOM 1063 HH12 ARG A 130 -11.021 21.425 30.295 1.00 0.00 H \\\\nATOM 1064 HH21 ARG A 130 -11.693 22.529 27.258 1.00 0.00 H \\\\nATOM 1065 HH22 ARG A 130 -11.088 21.391 28.005 1.00 0.00 H \\\\nATOM 1066 N GLU A 131 -16.095 25.617 27.435 1.00 0.00 N \\\\nATOM 1067 CA GLU A 131 -15.757 26.418 26.264 1.00 0.00 C \\\\nATOM 1068 C GLU A 131 -16.936 27.237 25.753 1.00 0.00 C \\\\nATOM 1069 O GLU A 131 -16.740 28.357 25.271 1.00 0.00 O \\\\nATOM 1070 CB GLU A 131 -15.238 25.519 25.138 1.00 0.00 C \\\\nATOM 1071 CG GLU A 131 -13.898 24.855 25.413 1.00 0.00 C \\\\nATOM 1072 CD GLU A 131 -12.880 25.811 26.001 1.00 0.00 C \\\\nATOM 1073 OE1 GLU A 131 -12.408 25.559 27.130 1.00 0.00 O \\\\nATOM 1074 OE2 GLU A 131 -12.553 26.817 25.336 1.00 0.00 O \\\\nATOM 1075 H GLU A 131 -16.214 24.780 27.277 1.00 0.00 H \\\\nATOM 1076 HA GLU A 131 -15.066 27.039 26.542 1.00 0.00 H \\\\nATOM 1077 HB2 GLU A 131 -15.896 24.828 24.964 1.00 0.00 H \\\\nATOM 1078 HB3 GLU A 131 -15.162 26.048 24.329 1.00 0.00 H \\\\nATOM 1079 HG2 GLU A 131 -14.029 24.112 26.023 1.00 0.00 H \\\\nATOM 1080 HG3 GLU A 131 -13.549 24.485 24.587 1.00 0.00 H \\\\nATOM 1081 N ARG A 132 -18.156 26.710 25.848 1.00 0.00 N \\\\nATOM 1082 CA ARG A 132 -19.262 27.191 25.031 1.00 0.00 C \\\\nATOM 1083 C ARG A 132 -20.369 27.905 25.796 1.00 0.00 C \\\\nATOM 1084 O ARG A 132 -21.000 28.802 25.232 1.00 0.00 O \\\\nATOM 1085 CB ARG A 132 -19.880 26.017 24.258 1.00 0.00 C \\\\nATOM 1086 CG ARG A 132 -21.007 26.400 23.317 1.00 0.00 C \\\\nATOM 1087 CD ARG A 132 -20.487 26.693 21.924 1.00 0.00 C \\\\nATOM 1088 NE ARG A 132 -21.561 27.101 21.022 1.00 0.00 N \\\\nATOM 1089 CZ ARG A 132 -21.615 28.281 20.413 1.00 0.00 C \\\\nATOM 1090 NH1 ARG A 132 -20.648 29.169 20.600 1.00 0.00 N \\\\nATOM 1091 NH2 ARG A 132 -22.629 28.571 19.612 1.00 0.00 N \\\\nATOM 1092 H ARG A 132 -18.362 26.069 26.384 1.00 0.00 H \\\\nATOM 1093 HA ARG A 132 -18.871 27.853 24.439 1.00 0.00 H \\\\nATOM 1094 HB2 ARG A 132 -19.182 25.580 23.746 1.00 0.00 H \\\\nATOM 1095 HB3 ARG A 132 -20.214 25.366 24.895 1.00 0.00 H \\\\nATOM 1096 HG2 ARG A 132 -21.656 25.680 23.277 1.00 0.00 H \\\\nATOM 1097 HG3 ARG A 132 -21.469 27.180 23.663 1.00 0.00 H \\\\nATOM 1098 HD2 ARG A 132 -19.818 27.394 21.969 1.00 0.00 H \\\\nATOM 1099 HD3 ARG A 132 -20.048 25.904 21.569 1.00 0.00 H \\\\nATOM 1100 HE ARG A 132 -22.198 26.543 20.876 1.00 0.00 H \\\\nATOM 1101 HH11 ARG A 132 -19.986 28.981 21.115 1.00 0.00 H \\\\nATOM 1102 HH12 ARG A 132 -20.683 29.933 20.206 1.00 0.00 H \\\\nATOM 1103 HH21 ARG A 132 -23.255 27.995 19.485 1.00 0.00 H \\\\nATOM 1104 HH22 ARG A 132 -22.662 29.335 19.219 1.00 0.00 H \\\\nATOM 1105 N ILE A 133 -20.611 27.556 27.062 1.00 0.00 N \\\\nATOM 1106 CA ILE A 133 -21.804 28.055 27.747 1.00 0.00 C \\\\nATOM 1107 C ILE A 133 -21.749 29.571 27.909 1.00 0.00 C \\\\nATOM 1108 O ILE A 133 -22.747 30.268 27.688 1.00 0.00 O \\\\nATOM 1109 CB ILE A 133 -21.993 27.336 29.096 1.00 0.00 C \\\\nATOM 1110 CG1 ILE A 133 -22.721 26.007 28.881 1.00 0.00 C \\\\nATOM 1111 CG2 ILE A 133 -22.785 28.203 30.065 1.00 0.00 C \\\\nATOM 1112 CD1 ILE A 133 -23.082 25.281 30.160 1.00 0.00 C \\\\nATOM 1113 H ILE A 133 -20.108 27.042 27.533 1.00 0.00 H \\\\nATOM 1114 HA ILE A 133 -22.580 27.857 27.200 1.00 0.00 H \\\\nATOM 1115 HB ILE A 133 -21.117 27.168 29.477 1.00 0.00 H \\\\nATOM 1116 HG12 ILE A 133 -23.532 26.173 28.375 1.00 0.00 H \\\\nATOM 1117 HG13 ILE A 133 -22.162 25.428 28.339 1.00 0.00 H \\\\nATOM 1118 HG21 ILE A 133 -22.893 27.733 30.907 1.00 0.00 H \\\\nATOM 1119 HG22 ILE A 133 -22.310 29.035 30.218 1.00 0.00 H \\\\nATOM 1120 HG23 ILE A 133 -23.658 28.395 29.688 1.00 0.00 H \\\\nATOM 1121 HD11 ILE A 133 -23.538 24.452 29.944 1.00 0.00 H \\\\nATOM 1122 HD12 ILE A 133 -22.274 25.084 30.660 1.00 0.00 H \\\\nATOM 1123 HD13 ILE A 133 -23.665 25.840 30.696 1.00 0.00 H \\\\nATOM 1124 N HIS A 134 -20.588 30.111 28.285 1.00 0.00 N \\\\nATOM 1125 CA HIS A 134 -20.497 31.553 28.499 1.00 0.00 C \\\\nATOM 1126 C HIS A 134 -20.607 32.318 27.184 1.00 0.00 C \\\\nATOM 1127 O HIS A 134 -21.163 33.421 27.148 1.00 0.00 O \\\\nATOM 1128 CB HIS A 134 -19.198 31.903 29.228 1.00 0.00 C \\\\nATOM 1129 CG HIS A 134 -17.974 31.822 28.371 1.00 0.00 C \\\\nATOM 1130 ND1 HIS A 134 -17.292 30.645 28.154 1.00 0.00 N \\\\nATOM 1131 CD2 HIS A 134 -17.302 32.778 27.687 1.00 0.00 C \\\\nATOM 1132 CE1 HIS A 134 -16.256 30.877 27.368 1.00 0.00 C \\\\nATOM 1133 NE2 HIS A 134 -16.239 32.164 27.070 1.00 0.00 N \\\\nATOM 1134 H HIS A 134 -19.860 29.672 28.418 1.00 0.00 H \\\\nATOM 1135 HA HIS A 134 -21.244 31.822 29.056 1.00 0.00 H \\\\nATOM 1136 HB2 HIS A 134 -19.271 32.802 29.586 1.00 0.00 H \\\\nATOM 1137 HB3 HIS A 134 -19.092 31.305 29.984 1.00 0.00 H \\\\nATOM 1138 HD1 HIS A 134 -17.507 29.879 28.480 1.00 0.00 H \\\\nATOM 1139 HD2 HIS A 134 -17.519 33.681 27.643 1.00 0.00 H \\\\nATOM 1140 HE1 HIS A 134 -15.643 30.242 27.074 1.00 0.00 H \\\\nATOM 1141 HE2 HIS A 134 -15.657 32.554 26.571 1.00 0.00 H \\\\nATOM 1142 N VAL A 135 -20.073 31.756 26.096 1.00 0.00 N \\\\nATOM 1143 CA VAL A 135 -20.206 32.395 24.788 1.00 0.00 C \\\\nATOM 1144 C VAL A 135 -21.671 32.454 24.376 1.00 0.00 C \\\\nATOM 1145 O VAL A 135 -22.153 33.477 23.872 1.00 0.00 O \\\\nATOM 1146 CB VAL A 135 -19.350 31.661 23.740 1.00 0.00 C \\\\nATOM 1147 CG1 VAL A 135 -19.513 32.309 22.371 1.00 0.00 C \\\\nATOM 1148 CG2 VAL A 135 -17.883 31.653 24.158 1.00 0.00 C \\\\nATOM 1149 H VAL A 135 -19.636 31.015 26.095 1.00 0.00 H \\\\nATOM 1150 HA VAL A 135 -19.878 33.306 24.847 1.00 0.00 H \\\\nATOM 1151 HB VAL A 135 -19.656 30.742 23.683 1.00 0.00 H \\\\nATOM 1152 HG11 VAL A 135 -18.968 31.836 21.722 1.00 0.00 H \\\\nATOM 1153 HG12 VAL A 135 -20.444 32.268 22.102 1.00 0.00 H \\\\nATOM 1154 HG13 VAL A 135 -19.230 33.236 22.416 1.00 0.00 H \\\\nATOM 1155 HG21 VAL A 135 -17.358 31.188 23.488 1.00 0.00 H \\\\nATOM 1156 HG22 VAL A 135 -17.565 32.566 24.241 1.00 0.00 H \\\\nATOM 1157 HG23 VAL A 135 -17.792 31.201 25.011 1.00 0.00 H \\\\nATOM 1158 N VAL A 136 -22.403 31.360 24.588 1.00 0.00 N \\\\nATOM 1159 CA VAL A 136 -23.820 31.327 24.243 1.00 0.00 C \\\\nATOM 1160 C VAL A 136 -24.606 32.261 25.154 1.00 0.00 C \\\\nATOM 1161 O VAL A 136 -25.530 32.957 24.709 1.00 0.00 O \\\\nATOM 1162 CB VAL A 136 -24.348 29.882 24.308 1.00 0.00 C \\\\nATOM 1163 CG1 VAL A 136 -25.847 29.843 24.068 1.00 0.00 C \\\\nATOM 1164 CG2 VAL A 136 -23.618 29.019 23.291 1.00 0.00 C \\\\nATOM 1165 H VAL A 136 -22.098 30.631 24.929 1.00 0.00 H \\\\nATOM 1166 HA VAL A 136 -23.937 31.641 23.333 1.00 0.00 H \\\\nATOM 1167 HB VAL A 136 -24.180 29.529 25.196 1.00 0.00 H \\\\nATOM 1168 HG11 VAL A 136 -26.158 28.925 24.113 1.00 0.00 H \\\\nATOM 1169 HG12 VAL A 136 -26.297 30.371 24.746 1.00 0.00 H \\\\nATOM 1170 HG13 VAL A 136 -26.044 30.208 23.191 1.00 0.00 H \\\\nATOM 1171 HG21 VAL A 136 -23.954 28.110 23.336 1.00 0.00 H \\\\nATOM 1172 HG22 VAL A 136 -23.765 29.374 22.400 1.00 0.00 H \\\\nATOM 1173 HG23 VAL A 136 -22.668 29.022 23.487 1.00 0.00 H \\\\nATOM 1174 N LEU A 137 -24.260 32.282 26.448 1.00 0.00 N \\\\nATOM 1175 CA LEU A 137 -24.928 33.182 27.385 1.00 0.00 C \\\\nATOM 1176 C LEU A 137 -24.735 34.638 26.993 1.00 0.00 C \\\\nATOM 1177 O LEU A 137 -25.673 35.439 27.073 1.00 0.00 O \\\\nATOM 1178 CB LEU A 137 -24.389 32.964 28.800 1.00 0.00 C \\\\nATOM 1179 CG LEU A 137 -25.053 33.675 29.981 1.00 0.00 C \\\\nATOM 1180 CD1 LEU A 137 -26.574 33.688 29.876 1.00 0.00 C \\\\nATOM 1181 CD2 LEU A 137 -24.527 33.154 31.308 1.00 0.00 C \\\\nATOM 1182 H LEU A 137 -23.648 31.788 26.796 1.00 0.00 H \\\\nATOM 1183 HA LEU A 137 -25.876 32.980 27.359 1.00 0.00 H \\\\nATOM 1184 HB2 LEU A 137 -24.422 32.011 28.979 1.00 0.00 H \\\\nATOM 1185 HB3 LEU A 137 -23.453 33.220 28.796 1.00 0.00 H \\\\nATOM 1186 HG LEU A 137 -24.798 34.610 29.943 1.00 0.00 H \\\\nATOM 1187 HD11 LEU A 137 -26.948 34.148 30.644 1.00 0.00 H \\\\nATOM 1188 HD12 LEU A 137 -26.839 34.148 29.064 1.00 0.00 H \\\\nATOM 1189 HD13 LEU A 137 -26.905 32.776 29.853 1.00 0.00 H \\\\nATOM 1190 HD21 LEU A 137 -24.965 33.622 32.036 1.00 0.00 H \\\\nATOM 1191 HD22 LEU A 137 -24.710 32.204 31.378 1.00 0.00 H \\\\nATOM 1192 HD23 LEU A 137 -23.570 33.303 31.358 1.00 0.00 H \\\\nATOM 1193 N SER A 138 -23.521 34.998 26.575 1.00 0.00 N \\\\nATOM 1194 CA SER A 138 -23.231 36.387 26.226 1.00 0.00 C \\\\nATOM 1195 C SER A 138 -24.033 36.835 25.009 1.00 0.00 C \\\\nATOM 1196 O SER A 138 -24.621 37.924 25.001 1.00 0.00 O \\\\nATOM 1197 CB SER A 138 -21.732 36.568 25.979 1.00 0.00 C \\\\nATOM 1198 OG SER A 138 -21.410 37.925 25.781 1.00 0.00 O \\\\nATOM 1199 H SER A 138 -22.858 34.458 26.487 1.00 0.00 H \\\\nATOM 1200 HA SER A 138 -23.496 36.945 26.974 1.00 0.00 H \\\\nATOM 1201 HB2 SER A 138 -21.233 36.221 26.735 1.00 0.00 H \\\\nATOM 1202 HB3 SER A 138 -21.465 36.053 25.202 1.00 0.00 H \\\\nATOM 1203 HG SER A 138 -22.071 38.325 25.451 1.00 0.00 H \\\\nATOM 1204 N ALA A 139 -24.059 36.008 23.963 1.00 0.00 N \\\\nATOM 1205 CA ALA A 139 -24.859 36.333 22.787 1.00 0.00 C \\\\nATOM 1206 C ALA A 139 -26.334 36.421 23.147 1.00 0.00 C \\\\nATOM 1207 O ALA A 139 -27.079 37.225 22.572 1.00 0.00 O \\\\nATOM 1208 CB ALA A 139 -24.632 35.295 21.690 1.00 0.00 C \\\\nATOM 1209 H ALA A 139 -23.627 35.266 23.916 1.00 0.00 H \\\\nATOM 1210 HA ALA A 139 -24.579 37.200 22.454 1.00 0.00 H \\\\nATOM 1211 HB1 ALA A 139 -25.168 35.521 20.914 1.00 0.00 H \\\\nATOM 1212 HB2 ALA A 139 -23.694 35.285 21.442 1.00 0.00 H \\\\nATOM 1213 HB3 ALA A 139 -24.889 34.418 22.016 1.00 0.00 H \\\\nATOM 1214 N ALA A 140 -26.773 35.599 24.100 1.00 0.00 N \\\\nATOM 1215 CA ALA A 140 -28.157 35.651 24.551 1.00 0.00 C \\\\nATOM 1216 C ALA A 140 -28.471 36.933 25.311 1.00 0.00 C \\\\nATOM 1217 O ALA A 140 -29.573 37.478 25.172 1.00 0.00 O \\\\nATOM 1218 CB ALA A 140 -28.469 34.425 25.404 1.00 0.00 C \\\\nATOM 1219 H ALA A 140 -26.287 35.009 24.494 1.00 0.00 H \\\\nATOM 1220 HA ALA A 140 -28.724 35.648 23.764 1.00 0.00 H \\\\nATOM 1221 HB1 ALA A 140 -29.391 34.464 25.702 1.00 0.00 H \\\\nATOM 1222 HB2 ALA A 140 -28.333 33.621 24.878 1.00 0.00 H \\\\nATOM 1223 HB3 ALA A 140 -27.881 34.409 26.175 1.00 0.00 H \\\\nATOM 1224 N LEU A 141 -27.519 37.433 26.098 1.00 0.00 N \\\\nATOM 1225 CA LEU A 141 -27.739 38.661 26.853 1.00 0.00 C \\\\nATOM 1226 C LEU A 141 -27.742 39.880 25.939 1.00 0.00 C \\\\nATOM 1227 O LEU A 141 -28.531 40.810 26.140 1.00 0.00 O \\\\nATOM 1228 CB LEU A 141 -26.673 38.791 27.939 1.00 0.00 C \\\\nATOM 1229 CG LEU A 141 -26.984 38.016 29.223 1.00 0.00 C \\\\nATOM 1230 CD1 LEU A 141 -25.846 38.157 30.213 1.00 0.00 C \\\\nATOM 1231 CD2 LEU A 141 -28.297 38.485 29.829 1.00 0.00 C \\\\nATOM 1232 H LEU A 141 -26.744 37.077 26.207 1.00 0.00 H \\\\nATOM 1233 HA LEU A 141 -28.613 38.617 27.272 1.00 0.00 H \\\\nATOM 1234 HB2 LEU A 141 -25.825 38.481 27.584 1.00 0.00 H \\\\nATOM 1235 HB3 LEU A 141 -26.563 39.729 28.159 1.00 0.00 H \\\\nATOM 1236 HG LEU A 141 -27.078 37.076 29.002 1.00 0.00 H \\\\nATOM 1237 HD11 LEU A 141 -26.056 37.662 31.020 1.00 0.00 H \\\\nATOM 1238 HD12 LEU A 141 -25.031 37.806 29.822 1.00 0.00 H \\\\nATOM 1239 HD13 LEU A 141 -25.721 39.094 30.432 1.00 0.00 H \\\\nATOM 1240 HD21 LEU A 141 -28.477 37.984 30.640 1.00 0.00 H \\\\nATOM 1241 HD22 LEU A 141 -28.237 39.430 30.040 1.00 0.00 H \\\\nATOM 1242 HD23 LEU A 141 -29.016 38.341 29.194 1.00 0.00 H \\\\nATOM 1243 N ALA A 142 -26.836 39.888 25.015 1.00 0.00 N \\\\nATOM 1244 CA ALA A 142 -26.718 40.990 24.140 1.00 0.00 C \\\\nATOM 1245 C ALA A 142 -27.955 41.263 23.294 1.00 0.00 C \\\\nATOM 1246 O ALA A 142 -28.240 42.384 23.009 1.00 0.00 O \\\\nATOM 1247 CB ALA A 142 -25.486 40.846 23.298 1.00 0.00 C \\\\nATOM 1248 H ALA A 142 -26.272 39.253 24.878 1.00 0.00 H \\\\nATOM 1249 HA ALA A 142 -26.635 41.777 24.701 1.00 0.00 H \\\\nATOM 1250 HB1 ALA A 142 -25.412 41.606 22.700 1.00 0.00 H \\\\nATOM 1251 HB2 ALA A 142 -24.704 40.809 23.871 1.00 0.00 H \\\\nATOM 1252 HB3 ALA A 142 -25.543 40.030 22.777 1.00 0.00 H \\\\nATOM 1253 N ARG A 143 -28.676 40.209 22.925 1.00 0.00 N \\\\nATOM 1254 CA ARG A 143 -29.880 40.348 22.112 1.00 0.00 C \\\\nATOM 1255 C ARG A 143 -31.128 40.684 22.930 1.00 0.00 C \\\\nATOM 1256 O ARG A 143 -32.042 41.341 22.431 1.00 0.00 O \\\\nATOM 1257 CB ARG A 143 -30.119 39.077 21.293 1.00 0.00 C \\\\nATOM 1258 CG ARG A 143 -30.855 37.982 22.048 1.00 0.00 C \\\\nATOM 1259 CD ARG A 143 -31.568 37.037 21.094 1.00 0.00 C \\\\nATOM 1260 NE ARG A 143 -31.496 35.650 21.542 1.00 0.00 N \\\\nATOM 1261 CZ ARG A 143 -30.375 34.936 21.587 1.00 0.00 C \\\\nATOM 1262 NH1 ARG A 143 -29.226 35.479 21.210 1.00 0.00 N \\\\nATOM 1263 NH2 ARG A 143 -30.403 33.680 22.009 1.00 0.00 N \\\\nATOM 1264 H ARG A 143 -28.483 39.398 23.137 1.00 0.00 H \\\\nATOM 1265 HA ARG A 143 -29.723 41.100 21.519 1.00 0.00 H \\\\nATOM 1266 HB2 ARG A 143 -30.626 39.306 20.499 1.00 0.00 H \\\\nATOM 1267 HB3 ARG A 143 -29.264 38.731 20.993 1.00 0.00 H \\\\nATOM 1268 HG2 ARG A 143 -30.226 37.482 22.592 1.00 0.00 H \\\\nATOM 1269 HG3 ARG A 143 -31.499 38.381 22.654 1.00 0.00 H \\\\nATOM 1270 HD2 ARG A 143 -32.498 37.302 21.013 1.00 0.00 H \\\\nATOM 1271 HD3 ARG A 143 -31.173 37.112 20.211 1.00 0.00 H \\\\nATOM 1272 HE ARG A 143 -32.225 35.270 21.793 1.00 0.00 H \\\\nATOM 1273 HH11 ARG A 143 -29.205 36.294 20.936 1.00 0.00 H \\\\nATOM 1274 HH12 ARG A 143 -28.502 35.016 21.240 1.00 0.00 H \\\\nATOM 1275 HH21 ARG A 143 -31.147 33.325 22.254 1.00 0.00 H \\\\nATOM 1276 HH22 ARG A 143 -29.677 33.220 22.037 1.00 0.00 H \\\\nATOM 1277 N LEU A 144 -31.169 40.234 24.181 1.00 0.00 N \\\\nATOM 1278 CA LEU A 144 -32.296 40.487 25.020 1.00 0.00 C \\\\nATOM 1279 C LEU A 144 -32.312 41.953 25.259 1.00 0.00 C \\\\nATOM 1280 O LEU A 144 -33.352 42.535 25.409 1.00 0.00 O \\\\nATOM 1281 CB LEU A 144 -32.219 39.729 26.326 1.00 0.00 C \\\\nATOM 1282 CG LEU A 144 -33.392 39.826 27.291 1.00 0.00 C \\\\nATOM 1283 CD1 LEU A 144 -34.620 39.184 26.732 1.00 0.00 C \\\\nATOM 1284 CD2 LEU A 144 -33.061 39.174 28.597 1.00 0.00 C \\\\nATOM 1285 H LEU A 144 -30.541 39.778 24.552 1.00 0.00 H \\\\nATOM 1286 HA LEU A 144 -33.111 40.184 24.591 1.00 0.00 H \\\\nATOM 1287 HB2 LEU A 144 -32.087 38.791 26.116 1.00 0.00 H \\\\nATOM 1288 HB3 LEU A 144 -31.425 40.029 26.795 1.00 0.00 H \\\\nATOM 1289 HG LEU A 144 -33.565 40.770 27.429 1.00 0.00 H \\\\nATOM 1290 HD11 LEU A 144 -35.346 39.263 27.370 1.00 0.00 H \\\\nATOM 1291 HD12 LEU A 144 -34.868 39.625 25.904 1.00 0.00 H \\\\nATOM 1292 HD13 LEU A 144 -34.444 38.246 26.558 1.00 0.00 H \\\\nATOM 1293 HD21 LEU A 144 -33.820 39.247 29.197 1.00 0.00 H \\\\nATOM 1294 HD22 LEU A 144 -32.855 38.238 28.449 1.00 0.00 H \\\\nATOM 1295 HD23 LEU A 144 -32.293 39.615 28.993 1.00 0.00 H \\\\nATOM 1296 N GLY A 145 -31.153 42.578 25.280 1.00 0.00 N \\\\nATOM 1297 CA GLY A 145 -31.156 44.018 25.487 1.00 0.00 C \\\\nATOM 1298 C GLY A 145 -31.805 44.773 24.345 1.00 0.00 C \\\\nATOM 1299 O GLY A 145 -32.396 45.837 24.553 1.00 0.00 O \\\\nATOM 1300 H GLY A 145 -30.381 42.211 25.182 1.00 0.00 H \\\\nATOM 1301 HA2 GLY A 145 -31.625 44.221 26.312 1.00 0.00 H \\\\nATOM 1302 HA3 GLY A 145 -30.243 44.327 25.596 1.00 0.00 H \\\\nATOM 1303 N LYS A 146 -31.679 44.256 23.126 1.00 0.00 N \\\\nATOM 1304 CA LYS A 146 -32.284 44.868 21.952 1.00 0.00 C \\\\nATOM 1305 C LYS A 146 -33.803 44.728 21.990 1.00 0.00 C \\\\nATOM 1306 O LYS A 146 -34.480 45.403 22.764 1.00 0.00 O \\\\nATOM 1307 CB LYS A 146 -31.735 44.226 20.675 1.00 0.00 C \\\\nATOM 1308 CG LYS A 146 -30.694 45.051 19.936 1.00 0.00 C \\\\nATOM 1309 CD LYS A 146 -31.258 46.378 19.461 1.00 0.00 C \\\\nATOM 1310 CE LYS A 146 -30.237 47.138 18.631 1.00 0.00 C \\\\nATOM 1311 NZ LYS A 146 -30.227 46.685 17.212 1.00 0.00 N \\\\nATOM 1312 H LYS A 146 -31.238 43.537 22.958 1.00 0.00 H \\\\nATOM 1313 HA LYS A 146 -32.060 45.812 21.955 1.00 0.00 H \\\\nATOM 1314 HB2 LYS A 146 -31.345 43.367 20.903 1.00 0.00 H \\\\nATOM 1315 HB3 LYS A 146 -32.475 44.051 20.073 1.00 0.00 H \\\\nATOM 1316 HG2 LYS A 146 -29.936 45.212 20.519 1.00 0.00 H \\\\nATOM 1317 HG3 LYS A 146 -30.364 44.549 19.174 1.00 0.00 H \\\\nATOM 1318 HD2 LYS A 146 -32.058 46.223 18.934 1.00 0.00 H \\\\nATOM 1319 HD3 LYS A 146 -31.521 46.914 20.226 1.00 0.00 H \\\\nATOM 1320 HE2 LYS A 146 -30.434 48.087 18.666 1.00 0.00 H \\\\nATOM 1321 HE3 LYS A 146 -29.354 47.018 19.015 1.00 0.00 H \\\\nATOM 1322 HZ1 LYS A 146 -29.963 47.355 16.688 1.00 0.00 H \\\\nATOM 1323 HZ2 LYS A 146 -29.666 46.000 17.123 1.00 0.00 H \\\\nATOM 1324 HZ3 LYS A 146 -31.046 46.429 16.976 1.00 0.00 H \\\\nATOM 1325 N ASP A 155 -42.107 40.565 33.671 1.00 0.00 N \\\\nATOM 1326 CA ASP A 155 -41.459 39.999 34.849 1.00 0.00 C \\\\nATOM 1327 C ASP A 155 -40.011 39.624 34.542 1.00 0.00 C \\\\nATOM 1328 O ASP A 155 -39.734 38.925 33.568 1.00 0.00 O \\\\nATOM 1329 CB ASP A 155 -42.231 38.779 35.353 1.00 0.00 C \\\\nATOM 1330 CG ASP A 155 -42.073 38.567 36.845 1.00 0.00 C \\\\nATOM 1331 OD1 ASP A 155 -40.965 38.190 37.282 1.00 0.00 O \\\\nATOM 1332 OD2 ASP A 155 -43.056 38.786 37.585 1.00 0.00 O \\\\nATOM 1333 HA ASP A 155 -41.458 40.673 35.547 1.00 0.00 H \\\\nATOM 1334 HB2 ASP A 155 -43.172 38.886 35.143 1.00 0.00 H \\\\nATOM 1335 HB3 ASP A 155 -41.923 37.988 34.883 1.00 0.00 H \\\\nATOM 1336 N MET A 156 -39.092 40.092 35.388 1.00 0.00 N \\\\nATOM 1337 CA MET A 156 -37.669 39.890 35.139 1.00 0.00 C \\\\nATOM 1338 C MET A 156 -37.180 38.522 35.593 1.00 0.00 C \\\\nATOM 1339 O MET A 156 -36.199 38.011 35.045 1.00 0.00 O \\\\nATOM 1340 CB MET A 156 -36.859 40.990 35.822 1.00 0.00 C \\\\nATOM 1341 CG MET A 156 -37.242 42.372 35.348 1.00 0.00 C \\\\nATOM 1342 SD MET A 156 -37.229 42.444 33.548 1.00 0.00 S \\\\nATOM 1343 CE MET A 156 -38.504 43.660 33.258 1.00 0.00 C \\\\nATOM 1344 H MET A 156 -39.273 40.527 36.108 1.00 0.00 H \\\\nATOM 1345 HA MET A 156 -37.539 39.932 34.179 1.00 0.00 H \\\\nATOM 1346 HB2 MET A 156 -36.988 40.934 36.782 1.00 0.00 H \\\\nATOM 1347 HB3 MET A 156 -35.915 40.844 35.654 1.00 0.00 H \\\\nATOM 1348 HG2 MET A 156 -38.124 42.602 35.680 1.00 0.00 H \\\\nATOM 1349 HG3 MET A 156 -36.624 43.027 35.708 1.00 0.00 H \\\\nATOM 1350 HE1 MET A 156 -38.606 43.801 32.304 1.00 0.00 H \\\\nATOM 1351 HE2 MET A 156 -39.343 43.345 33.629 1.00 0.00 H \\\\nATOM 1352 HE3 MET A 156 -38.257 44.496 33.683 1.00 0.00 H \\\\nATOM 1353 N LYS A 157 -37.829 37.924 36.594 1.00 0.00 N \\\\nATOM 1354 CA LYS A 157 -37.510 36.545 36.950 1.00 0.00 C \\\\nATOM 1355 C LYS A 157 -37.772 35.604 35.780 1.00 0.00 C \\\\nATOM 1356 O LYS A 157 -36.965 34.710 35.500 1.00 0.00 O \\\\nATOM 1357 CB LYS A 157 -38.313 36.118 38.180 1.00 0.00 C \\\\nATOM 1358 CG LYS A 157 -38.055 34.687 38.627 1.00 0.00 C \\\\nATOM 1359 CD LYS A 157 -36.597 34.471 39.005 1.00 0.00 C \\\\nATOM 1360 CE LYS A 157 -36.292 32.993 39.191 1.00 0.00 C \\\\nATOM 1361 NZ LYS A 157 -35.108 32.765 40.063 1.00 0.00 N \\\\nATOM 1362 H LYS A 157 -38.444 38.292 37.069 1.00 0.00 H \\\\nATOM 1363 HA LYS A 157 -36.565 36.495 37.164 1.00 0.00 H \\\\nATOM 1364 HB2 LYS A 157 -38.105 36.718 38.914 1.00 0.00 H \\\\nATOM 1365 HB3 LYS A 157 -39.258 36.221 37.988 1.00 0.00 H \\\\nATOM 1366 HG2 LYS A 157 -38.621 34.478 39.386 1.00 0.00 H \\\\nATOM 1367 HG3 LYS A 157 -38.299 34.076 37.914 1.00 0.00 H \\\\nATOM 1368 HD2 LYS A 157 -36.023 34.838 38.314 1.00 0.00 H \\\\nATOM 1369 HD3 LYS A 157 -36.398 34.951 39.824 1.00 0.00 H \\\\nATOM 1370 HE2 LYS A 157 -37.065 32.552 39.577 1.00 0.00 H \\\\nATOM 1371 HE3 LYS A 157 -36.136 32.586 38.325 1.00 0.00 H \\\\nATOM 1372 HZ1 LYS A 157 -35.074 31.908 40.300 1.00 0.00 H \\\\nATOM 1373 HZ2 LYS A 157 -34.367 32.979 39.620 1.00 0.00 H \\\\nATOM 1374 HZ3 LYS A 157 -35.174 33.271 40.792 1.00 0.00 H \\\\nATOM 1375 N GLU A 158 -38.902 35.785 35.092 1.00 0.00 N \\\\nATOM 1376 CA GLU A 158 -39.200 34.963 33.923 1.00 0.00 C \\\\nATOM 1377 C GLU A 158 -38.141 35.143 32.843 1.00 0.00 C \\\\nATOM 1378 O GLU A 158 -37.765 34.181 32.163 1.00 0.00 O \\\\nATOM 1379 CB GLU A 158 -40.589 35.292 33.379 1.00 0.00 C \\\\nATOM 1380 CG GLU A 158 -41.215 34.153 32.587 1.00 0.00 C \\\\nATOM 1381 CD GLU A 158 -42.725 34.113 32.710 1.00 0.00 C \\\\nATOM 1382 OE1 GLU A 158 -43.397 34.988 32.123 1.00 0.00 O \\\\nATOM 1383 OE2 GLU A 158 -43.241 33.204 33.395 1.00 0.00 O \\\\nATOM 1384 H GLU A 158 -39.501 36.372 35.285 1.00 0.00 H \\\\nATOM 1385 HA GLU A 158 -39.190 34.033 34.197 1.00 0.00 H \\\\nATOM 1386 HB2 GLU A 158 -41.173 35.521 34.119 1.00 0.00 H \\\\nATOM 1387 HB3 GLU A 158 -40.529 36.077 32.812 1.00 0.00 H \\\\nATOM 1388 HG2 GLU A 158 -40.973 34.243 31.652 1.00 0.00 H \\\\nATOM 1389 HG3 GLU A 158 -40.847 33.310 32.895 1.00 0.00 H \\\\nATOM 1390 N HIS A 159 -37.657 36.376 32.664 1.00 0.00 N \\\\nATOM 1391 CA HIS A 159 -36.682 36.644 31.612 1.00 0.00 C \\\\nATOM 1392 C HIS A 159 -35.346 35.974 31.915 1.00 0.00 C \\\\nATOM 1393 O HIS A 159 -34.690 35.450 31.007 1.00 0.00 O \\\\nATOM 1394 CB HIS A 159 -36.499 38.152 31.441 1.00 0.00 C \\\\nATOM 1395 CG HIS A 159 -37.508 38.788 30.535 1.00 0.00 C \\\\nATOM 1396 ND1 HIS A 159 -38.657 39.387 31.005 1.00 0.00 N \\\\nATOM 1397 CD2 HIS A 159 -37.536 38.927 29.188 1.00 0.00 C \\\\nATOM 1398 CE1 HIS A 159 -39.352 39.864 29.987 1.00 0.00 C \\\\nATOM 1399 NE2 HIS A 159 -38.693 39.598 28.873 1.00 0.00 N \\\\nATOM 1400 H HIS A 159 -37.879 37.060 33.136 1.00 0.00 H \\\\nATOM 1401 HA HIS A 159 -37.018 36.271 30.782 1.00 0.00 H \\\\nATOM 1402 HB2 HIS A 159 -36.548 38.575 32.312 1.00 0.00 H \\\\nATOM 1403 HB3 HIS A 159 -35.610 38.323 31.092 1.00 0.00 H \\\\nATOM 1404 HD1 HIS A 159 -38.886 39.442 31.832 1.00 0.00 H \\\\nATOM 1405 HD2 HIS A 159 -36.892 38.625 28.588 1.00 0.00 H \\\\nATOM 1406 HE1 HIS A 159 -40.166 40.311 30.045 1.00 0.00 H \\\\nATOM 1407 HE2 HIS A 159 -38.947 39.810 28.079 1.00 0.00 H \\\\nATOM 1408 N TRP A 160 -34.922 35.992 33.182 1.00 0.00 N \\\\nATOM 1409 CA TRP A 160 -33.691 35.305 33.563 1.00 0.00 C \\\\nATOM 1410 C TRP A 160 -33.798 33.809 33.295 1.00 0.00 C \\\\nATOM 1411 O TRP A 160 -32.868 33.190 32.766 1.00 0.00 O \\\\nATOM 1412 CB TRP A 160 -33.374 35.564 35.035 1.00 0.00 C \\\\nATOM 1413 CG TRP A 160 -32.525 36.781 35.287 1.00 0.00 C \\\\nATOM 1414 CD1 TRP A 160 -32.834 37.840 36.089 1.00 0.00 C \\\\nATOM 1415 CD2 TRP A 160 -31.224 37.054 34.745 1.00 0.00 C \\\\nATOM 1416 NE1 TRP A 160 -31.811 38.757 36.078 1.00 0.00 N \\\\nATOM 1417 CE2 TRP A 160 -30.812 38.299 35.260 1.00 0.00 C \\\\nATOM 1418 CE3 TRP A 160 -30.372 36.371 33.872 1.00 0.00 C \\\\nATOM 1419 CZ2 TRP A 160 -29.586 38.874 34.932 1.00 0.00 C \\\\nATOM 1420 CZ3 TRP A 160 -29.153 36.944 33.549 1.00 0.00 C \\\\nATOM 1421 CH2 TRP A 160 -28.773 38.183 34.078 1.00 0.00 C \\\\nATOM 1422 H TRP A 160 -35.328 36.391 33.826 1.00 0.00 H \\\\nATOM 1423 HA TRP A 160 -32.966 35.656 33.022 1.00 0.00 H \\\\nATOM 1424 HB2 TRP A 160 -34.208 35.659 35.522 1.00 0.00 H \\\\nATOM 1425 HB3 TRP A 160 -32.921 34.787 35.398 1.00 0.00 H \\\\nATOM 1426 HD1 TRP A 160 -33.623 37.929 36.573 1.00 0.00 H \\\\nATOM 1427 HE1 TRP A 160 -31.800 39.498 36.514 1.00 0.00 H \\\\nATOM 1428 HE3 TRP A 160 -30.619 35.548 33.515 1.00 0.00 H \\\\nATOM 1429 HZ2 TRP A 160 -29.330 39.697 35.281 1.00 0.00 H \\\\nATOM 1430 HZ3 TRP A 160 -28.577 36.498 32.971 1.00 0.00 H \\\\nATOM 1431 HH2 TRP A 160 -27.949 38.544 33.843 1.00 0.00 H \\\\nATOM 1432 N ASP A 161 -34.928 33.205 33.670 1.00 0.00 N \\\\nATOM 1433 CA ASP A 161 -35.135 31.786 33.400 1.00 0.00 C \\\\nATOM 1434 C ASP A 161 -35.141 31.492 31.906 1.00 0.00 C \\\\nATOM 1435 O ASP A 161 -34.679 30.428 31.485 1.00 0.00 O \\\\nATOM 1436 CB ASP A 161 -36.444 31.313 34.029 1.00 0.00 C \\\\nATOM 1437 CG ASP A 161 -36.304 31.009 35.503 1.00 0.00 C \\\\nATOM 1438 OD1 ASP A 161 -36.017 31.946 36.275 1.00 0.00 O \\\\nATOM 1439 OD2 ASP A 161 -36.477 29.833 35.891 1.00 0.00 O \\\\nATOM 1440 H ASP A 161 -35.578 33.595 34.077 1.00 0.00 H \\\\nATOM 1441 HA ASP A 161 -34.394 31.302 33.796 1.00 0.00 H \\\\nATOM 1442 HB2 ASP A 161 -37.123 31.995 33.906 1.00 0.00 H \\\\nATOM 1443 HB3 ASP A 161 -36.753 30.518 33.566 1.00 0.00 H \\\\nATOM 1444 N ASP A 162 -35.644 32.422 31.092 1.00 0.00 N \\\\nATOM 1445 CA ASP A 162 -35.756 32.164 29.660 1.00 0.00 C \\\\nATOM 1446 C ASP A 162 -34.399 32.242 28.975 1.00 0.00 C \\\\nATOM 1447 O ASP A 162 -34.097 31.432 28.091 1.00 0.00 O \\\\nATOM 1448 CB ASP A 162 -36.736 33.149 29.023 1.00 0.00 C \\\\nATOM 1449 CG ASP A 162 -38.178 32.830 29.353 1.00 0.00 C \\\\nATOM 1450 OD1 ASP A 162 -38.441 31.721 29.867 1.00 0.00 O \\\\nATOM 1451 OD2 ASP A 162 -39.051 33.686 29.100 1.00 0.00 O \\\\nATOM 1452 H ASP A 162 -35.921 33.196 31.346 1.00 0.00 H \\\\nATOM 1453 HA ASP A 162 -36.094 31.263 29.542 1.00 0.00 H \\\\nATOM 1454 HB2 ASP A 162 -36.529 34.047 29.326 1.00 0.00 H \\\\nATOM 1455 HB3 ASP A 162 -36.618 33.140 28.060 1.00 0.00 H \\\\nATOM 1456 N VAL A 163 -33.567 33.209 29.366 1.00 0.00 N \\\\nATOM 1457 CA VAL A 163 -32.253 33.332 28.745 1.00 0.00 C \\\\nATOM 1458 C VAL A 163 -31.359 32.173 29.163 1.00 0.00 C \\\\nATOM 1459 O VAL A 163 -30.508 31.725 28.384 1.00 0.00 O \\\\nATOM 1460 CB VAL A 163 -31.625 34.701 29.080 1.00 0.00 C \\\\nATOM 1461 CG1 VAL A 163 -31.289 34.807 30.557 1.00 0.00 C \\\\nATOM 1462 CG2 VAL A 163 -30.389 34.933 28.245 1.00 0.00 C \\\\nATOM 1463 H VAL A 163 -33.741 33.790 29.975 1.00 0.00 H \\\\nATOM 1464 HA VAL A 163 -32.351 33.288 27.781 1.00 0.00 H \\\\nATOM 1465 HB VAL A 163 -32.279 35.386 28.871 1.00 0.00 H \\\\nATOM 1466 HG11 VAL A 163 -30.897 35.675 30.738 1.00 0.00 H \\\\nATOM 1467 HG12 VAL A 163 -32.098 34.702 31.081 1.00 0.00 H \\\\nATOM 1468 HG13 VAL A 163 -30.657 34.111 30.796 1.00 0.00 H \\\\nATOM 1469 HG21 VAL A 163 -30.006 35.796 28.466 1.00 0.00 H \\\\nATOM 1470 HG22 VAL A 163 -29.740 34.235 28.427 1.00 0.00 H \\\\nATOM 1471 HG23 VAL A 163 -30.626 34.917 27.305 1.00 0.00 H \\\\nATOM 1472 N PHE A 164 -31.531 31.667 30.387 1.00 0.00 N \\\\nATOM 1473 CA PHE A 164 -30.737 30.534 30.845 1.00 0.00 C \\\\nATOM 1474 C PHE A 164 -31.257 29.215 30.281 1.00 0.00 C \\\\nATOM 1475 O PHE A 164 -30.466 28.318 29.968 1.00 0.00 O \\\\nATOM 1476 CB PHE A 164 -30.710 30.494 32.373 1.00 0.00 C \\\\nATOM 1477 CG PHE A 164 -29.623 31.335 32.980 1.00 0.00 C \\\\nATOM 1478 CD1 PHE A 164 -28.293 30.971 32.849 1.00 0.00 C \\\\nATOM 1479 CD2 PHE A 164 -29.928 32.496 33.673 1.00 0.00 C \\\\nATOM 1480 CE1 PHE A 164 -27.288 31.740 33.405 1.00 0.00 C \\\\nATOM 1481 CE2 PHE A 164 -28.926 33.271 34.229 1.00 0.00 C \\\\nATOM 1482 CZ PHE A 164 -27.605 32.894 34.096 1.00 0.00 C \\\\nATOM 1483 H PHE A 164 -32.098 31.965 30.960 1.00 0.00 H \\\\nATOM 1484 HA PHE A 164 -29.832 30.652 30.516 1.00 0.00 H \\\\nATOM 1485 HB2 PHE A 164 -31.568 30.795 32.712 1.00 0.00 H \\\\nATOM 1486 HB3 PHE A 164 -30.597 29.575 32.663 1.00 0.00 H \\\\nATOM 1487 HD1 PHE A 164 -28.073 30.198 32.380 1.00 0.00 H \\\\nATOM 1488 HD2 PHE A 164 -30.816 32.757 33.765 1.00 0.00 H \\\\nATOM 1489 HE1 PHE A 164 -26.399 31.481 33.314 1.00 0.00 H \\\\nATOM 1490 HE2 PHE A 164 -29.143 34.047 34.693 1.00 0.00 H \\\\nATOM 1491 HZ PHE A 164 -26.931 33.414 34.470 1.00 0.00 H \\\\nATOM 1492 N THR A 165 -32.580 29.076 30.153 1.00 0.00 N \\\\nATOM 1493 CA THR A 165 -33.142 27.847 29.600 1.00 0.00 C \\\\nATOM 1494 C THR A 165 -32.778 27.684 28.130 1.00 0.00 C \\\\nATOM 1495 O THR A 165 -32.397 26.591 27.697 1.00 0.00 O \\\\nATOM 1496 CB THR A 165 -34.662 27.832 29.775 1.00 0.00 C \\\\nATOM 1497 OG1 THR A 165 -34.986 27.870 31.171 1.00 0.00 O \\\\nATOM 1498 CG2 THR A 165 -35.263 26.583 29.154 1.00 0.00 C \\\\nATOM 1499 H THR A 165 -33.158 29.672 30.377 1.00 0.00 H \\\\nATOM 1500 HA THR A 165 -32.761 27.099 30.087 1.00 0.00 H \\\\nATOM 1501 HB THR A 165 -35.030 28.611 29.329 1.00 0.00 H \\\\nATOM 1502 HG1 THR A 165 -34.752 28.609 31.493 1.00 0.00 H \\\\nATOM 1503 HG21 THR A 165 -36.225 26.592 29.275 1.00 0.00 H \\\\nATOM 1504 HG22 THR A 165 -35.057 26.561 28.206 1.00 0.00 H \\\\nATOM 1505 HG23 THR A 165 -34.891 25.797 29.583 1.00 0.00 H \\\\nATOM 1506 N LYS A 166 -32.879 28.762 27.349 1.00 0.00 N \\\\nATOM 1507 CA LYS A 166 -32.547 28.679 25.931 1.00 0.00 C \\\\nATOM 1508 C LYS A 166 -31.051 28.506 25.714 1.00 0.00 C \\\\nATOM 1509 O LYS A 166 -30.637 27.911 24.713 1.00 0.00 O \\\\nATOM 1510 CB LYS A 166 -33.049 29.924 25.197 1.00 0.00 C \\\\nATOM 1511 CG LYS A 166 -34.510 29.851 24.795 1.00 0.00 C \\\\nATOM 1512 CD LYS A 166 -35.055 31.220 24.426 1.00 0.00 C \\\\nATOM 1513 CE LYS A 166 -36.506 31.132 23.978 1.00 0.00 C \\\\nATOM 1514 NZ LYS A 166 -37.353 32.179 24.614 1.00 0.00 N \\\\nATOM 1515 H LYS A 166 -33.134 29.538 27.618 1.00 0.00 H \\\\nATOM 1516 HA LYS A 166 -32.990 27.895 25.569 1.00 0.00 H \\\\nATOM 1517 HB2 LYS A 166 -32.917 30.699 25.765 1.00 0.00 H \\\\nATOM 1518 HB3 LYS A 166 -32.510 30.060 24.402 1.00 0.00 H \\\\nATOM 1519 HG2 LYS A 166 -34.610 29.248 24.042 1.00 0.00 H \\\\nATOM 1520 HG3 LYS A 166 -35.030 29.481 25.526 1.00 0.00 H \\\\nATOM 1521 HD2 LYS A 166 -34.985 31.815 25.189 1.00 0.00 H \\\\nATOM 1522 HD3 LYS A 166 -34.517 31.604 23.716 1.00 0.00 H \\\\nATOM 1523 HE2 LYS A 166 -36.551 31.223 23.013 1.00 0.00 H \\\\nATOM 1524 HE3 LYS A 166 -36.858 30.255 24.197 1.00 0.00 H \\\\nATOM 1525 HZ1 LYS A 166 -37.793 32.628 23.984 1.00 0.00 H \\\\nATOM 1526 HZ2 LYS A 166 -37.936 31.795 25.166 1.00 0.00 H \\\\nATOM 1527 HZ3 LYS A 166 -36.837 32.741 25.072 1.00 0.00 H \\\\nATOM 1528 N CYS A 167 -30.228 29.013 26.634 1.00 0.00 N \\\\nATOM 1529 CA CYS A 167 -28.785 28.843 26.505 1.00 0.00 C \\\\nATOM 1530 C CYS A 167 -28.380 27.405 26.807 1.00 0.00 C \\\\nATOM 1531 O CYS A 167 -27.589 26.802 26.071 1.00 0.00 O \\\\nATOM 1532 CB CYS A 167 -28.056 29.818 27.429 1.00 0.00 C \\\\nATOM 1533 SG CYS A 167 -26.396 29.285 27.912 1.00 0.00 S \\\\nATOM 1534 H CYS A 167 -30.482 29.451 27.329 1.00 0.00 H \\\\nATOM 1535 HA CYS A 167 -28.532 29.037 25.589 1.00 0.00 H \\\\nATOM 1536 HB2 CYS A 167 -27.992 30.679 26.988 1.00 0.00 H \\\\nATOM 1537 HB3 CYS A 167 -28.588 29.948 28.229 1.00 0.00 H \\\\nATOM 1538 HG CYS A 167 -26.475 28.491 28.808 1.00 0.00 H \\\\nATOM 1539 N PHE A 168 -28.907 26.844 27.898 1.00 0.00 N \\\\nATOM 1540 CA PHE A 168 -28.595 25.461 28.244 1.00 0.00 C \\\\nATOM 1541 C PHE A 168 -29.139 24.496 27.197 1.00 0.00 C \\\\nATOM 1542 O PHE A 168 -28.485 23.501 26.859 1.00 0.00 O \\\\nATOM 1543 CB PHE A 168 -29.158 25.124 29.625 1.00 0.00 C \\\\nATOM 1544 CG PHE A 168 -28.277 25.555 30.766 1.00 0.00 C \\\\nATOM 1545 CD1 PHE A 168 -27.682 26.806 30.772 1.00 0.00 C \\\\nATOM 1546 CD2 PHE A 168 -28.048 24.706 31.835 1.00 0.00 C \\\\nATOM 1547 CE1 PHE A 168 -26.874 27.199 31.821 1.00 0.00 C \\\\nATOM 1548 CE2 PHE A 168 -27.243 25.095 32.888 1.00 0.00 C \\\\nATOM 1549 CZ PHE A 168 -26.653 26.343 32.880 1.00 0.00 C \\\\nATOM 1550 H PHE A 168 -29.440 27.243 28.442 1.00 0.00 H \\\\nATOM 1551 HA PHE A 168 -27.630 25.364 28.265 1.00 0.00 H \\\\nATOM 1552 HB2 PHE A 168 -30.026 25.545 29.722 1.00 0.00 H \\\\nATOM 1553 HB3 PHE A 168 -29.300 24.166 29.682 1.00 0.00 H \\\\nATOM 1554 HD1 PHE A 168 -27.828 27.388 30.061 1.00 0.00 H \\\\nATOM 1555 HD2 PHE A 168 -28.441 23.863 31.844 1.00 0.00 H \\\\nATOM 1556 HE1 PHE A 168 -26.479 28.041 31.813 1.00 0.00 H \\\\nATOM 1557 HE2 PHE A 168 -27.099 24.517 33.602 1.00 0.00 H \\\\nATOM 1558 HZ PHE A 168 -26.108 26.606 33.586 1.00 0.00 H \\\\nATOM 1559 N GLN A 169 -30.340 24.770 26.680 1.00 0.00 N \\\\nATOM 1560 CA GLN A 169 -30.905 23.929 25.629 1.00 0.00 C \\\\nATOM 1561 C GLN A 169 -30.067 23.989 24.358 1.00 0.00 C \\\\nATOM 1562 O GLN A 169 -29.871 22.968 23.686 1.00 0.00 O \\\\nATOM 1563 CB GLN A 169 -32.347 24.344 25.340 1.00 0.00 C \\\\nATOM 1564 CG GLN A 169 -33.041 23.480 24.297 1.00 0.00 C \\\\nATOM 1565 CD GLN A 169 -33.114 22.021 24.703 1.00 0.00 C \\\\nATOM 1566 OE1 GLN A 169 -32.427 21.172 24.136 1.00 0.00 O \\\\nATOM 1567 NE2 GLN A 169 -33.951 21.723 25.690 1.00 0.00 N \\\\nATOM 1568 H GLN A 169 -30.836 25.430 26.922 1.00 0.00 H \\\\nATOM 1569 HA GLN A 169 -30.898 23.011 25.943 1.00 0.00 H \\\\nATOM 1570 HB2 GLN A 169 -32.855 24.310 26.165 1.00 0.00 H \\\\nATOM 1571 HB3 GLN A 169 -32.355 25.266 25.040 1.00 0.00 H \\\\nATOM 1572 HG2 GLN A 169 -33.939 23.816 24.149 1.00 0.00 H \\\\nATOM 1573 HG3 GLN A 169 -32.568 23.554 23.454 1.00 0.00 H \\\\nATOM 1574 HE21 GLN A 169 -34.415 22.344 26.062 1.00 0.00 H \\\\nATOM 1575 HE22 GLN A 169 -34.029 20.909 25.957 1.00 0.00 H \\\\nATOM 1576 N ARG A 170 -29.571 25.178 24.007 1.00 0.00 N \\\\nATOM 1577 CA ARG A 170 -28.765 25.311 22.797 1.00 0.00 C \\\\nATOM 1578 C ARG A 170 -27.468 24.521 22.912 1.00 0.00 C \\\\nATOM 1579 O ARG A 170 -27.056 23.847 21.960 1.00 0.00 O \\\\nATOM 1580 CB ARG A 170 -28.477 26.786 22.513 1.00 0.00 C \\\\nATOM 1581 CG ARG A 170 -27.402 27.015 21.463 1.00 0.00 C \\\\nATOM 1582 CD ARG A 170 -27.902 26.645 20.076 1.00 0.00 C \\\\nATOM 1583 NE ARG A 170 -26.825 26.624 19.089 1.00 0.00 N \\\\nATOM 1584 CZ ARG A 170 -27.015 26.492 17.780 1.00 0.00 C \\\\nATOM 1585 NH1 ARG A 170 -28.243 26.367 17.295 1.00 0.00 N \\\\nATOM 1586 NH2 ARG A 170 -25.976 26.483 16.955 1.00 0.00 N \\\\nATOM 1587 H ARG A 170 -29.688 25.907 24.449 1.00 0.00 H \\\\nATOM 1588 HA ARG A 170 -29.269 24.944 22.054 1.00 0.00 H \\\\nATOM 1589 HB2 ARG A 170 -29.297 27.216 22.223 1.00 0.00 H \\\\nATOM 1590 HB3 ARG A 170 -28.207 27.218 23.338 1.00 0.00 H \\\\nATOM 1591 HG2 ARG A 170 -27.129 27.946 21.474 1.00 0.00 H \\\\nATOM 1592 HG3 ARG A 170 -26.618 26.487 21.679 1.00 0.00 H \\\\nATOM 1593 HD2 ARG A 170 -28.326 25.773 20.109 1.00 0.00 H \\\\nATOM 1594 HD3 ARG A 170 -28.581 27.280 19.798 1.00 0.00 H \\\\nATOM 1595 HE ARG A 170 -26.017 26.702 19.373 1.00 0.00 H \\\\nATOM 1596 HH11 ARG A 170 -28.918 26.371 17.828 1.00 0.00 H \\\\nATOM 1597 HH12 ARG A 170 -28.364 26.282 16.448 1.00 0.00 H \\\\nATOM 1598 HH21 ARG A 170 -25.179 26.563 17.267 1.00 0.00 H \\\\nATOM 1599 HH22 ARG A 170 -26.100 26.398 16.108 1.00 0.00 H \\\\nATOM 1600 N VAL A 171 -26.808 24.596 24.069 1.00 0.00 N \\\\nATOM 1601 CA VAL A 171 -25.590 23.822 24.281 1.00 0.00 C \\\\nATOM 1602 C VAL A 171 -25.895 22.328 24.266 1.00 0.00 C \\\\nATOM 1603 O VAL A 171 -25.138 21.532 23.695 1.00 0.00 O \\\\nATOM 1604 CB VAL A 171 -24.909 24.253 25.593 1.00 0.00 C \\\\nATOM 1605 CG1 VAL A 171 -23.767 23.308 25.942 1.00 0.00 C \\\\nATOM 1606 CG2 VAL A 171 -24.410 25.684 25.479 1.00 0.00 C \\\\nATOM 1607 H VAL A 171 -27.047 25.084 24.735 1.00 0.00 H \\\\nATOM 1608 HA VAL A 171 -24.972 23.998 23.554 1.00 0.00 H \\\\nATOM 1609 HB VAL A 171 -25.562 24.211 26.309 1.00 0.00 H \\\\nATOM 1610 HG11 VAL A 171 -23.351 23.595 26.770 1.00 0.00 H \\\\nATOM 1611 HG12 VAL A 171 -24.113 22.408 26.049 1.00 0.00 H \\\\nATOM 1612 HG13 VAL A 171 -23.109 23.318 25.229 1.00 0.00 H \\\\nATOM 1613 HG21 VAL A 171 -23.983 25.945 26.310 1.00 0.00 H \\\\nATOM 1614 HG22 VAL A 171 -23.769 25.747 24.753 1.00 0.00 H \\\\nATOM 1615 HG23 VAL A 171 -25.159 26.275 25.301 1.00 0.00 H \\\\nATOM 1616 N ASP A 172 -27.004 21.924 24.893 1.00 0.00 N \\\\nATOM 1617 CA ASP A 172 -27.390 20.516 24.872 1.00 0.00 C \\\\nATOM 1618 C ASP A 172 -27.647 20.037 23.449 1.00 0.00 C \\\\nATOM 1619 O ASP A 172 -27.233 18.934 23.072 1.00 0.00 O \\\\nATOM 1620 CB ASP A 172 -28.626 20.294 25.743 1.00 0.00 C \\\\nATOM 1621 CG ASP A 172 -28.933 18.823 25.952 1.00 0.00 C \\\\nATOM 1622 OD1 ASP A 172 -28.353 18.218 26.878 1.00 0.00 O \\\\nATOM 1623 OD2 ASP A 172 -29.753 18.269 25.188 1.00 0.00 O \\\\nATOM 1624 H ASP A 172 -27.536 22.441 25.328 1.00 0.00 H \\\\nATOM 1625 HA ASP A 172 -26.655 19.996 25.233 1.00 0.00 H \\\\nATOM 1626 HB2 ASP A 172 -28.491 20.719 26.605 1.00 0.00 H \\\\nATOM 1627 HB3 ASP A 172 -29.391 20.725 25.330 1.00 0.00 H \\\\nATOM 1628 N ASP A 173 -28.341 20.849 22.648 1.00 0.00 N \\\\nATOM 1629 CA ASP A 173 -28.592 20.485 21.259 1.00 0.00 C \\\\nATOM 1630 C ASP A 173 -27.302 20.432 20.450 1.00 0.00 C \\\\nATOM 1631 O ASP A 173 -27.192 19.625 19.520 1.00 0.00 O \\\\nATOM 1632 CB ASP A 173 -29.583 21.465 20.632 1.00 0.00 C \\\\nATOM 1633 CG ASP A 173 -31.002 21.239 21.112 1.00 0.00 C \\\\nATOM 1634 OD1 ASP A 173 -31.300 20.117 21.577 1.00 0.00 O \\\\nATOM 1635 OD2 ASP A 173 -31.823 22.177 21.027 1.00 0.00 O \\\\nATOM 1636 H ASP A 173 -28.670 21.606 22.889 1.00 0.00 H \\\\nATOM 1637 HA ASP A 173 -28.977 19.595 21.247 1.00 0.00 H \\\\nATOM 1638 HB2 ASP A 173 -29.314 22.373 20.843 1.00 0.00 H \\\\nATOM 1639 HB3 ASP A 173 -29.553 21.378 19.666 1.00 0.00 H \\\\nATOM 1640 N GLU A 174 -26.329 21.287 20.771 1.00 0.00 N \\\\nATOM 1641 CA GLU A 174 -25.030 21.207 20.108 1.00 0.00 C \\\\nATOM 1642 C GLU A 174 -24.288 19.936 20.500 1.00 0.00 C \\\\nATOM 1643 O GLU A 174 -23.669 19.285 19.651 1.00 0.00 O \\\\nATOM 1644 CB GLU A 174 -24.187 22.438 20.442 1.00 0.00 C \\\\nATOM 1645 CG GLU A 174 -24.465 23.648 19.567 1.00 0.00 C \\\\nATOM 1646 CD GLU A 174 -23.849 24.920 20.118 1.00 0.00 C \\\\nATOM 1647 OE1 GLU A 174 -24.430 26.005 19.903 1.00 0.00 O \\\\nATOM 1648 OE2 GLU A 174 -22.782 24.837 20.763 1.00 0.00 O \\\\nATOM 1649 H GLU A 174 -26.400 21.910 21.360 1.00 0.00 H \\\\nATOM 1650 HA GLU A 174 -25.184 21.181 19.151 1.00 0.00 H \\\\nATOM 1651 HB2 GLU A 174 -24.342 22.680 21.368 1.00 0.00 H \\\\nATOM 1652 HB3 GLU A 174 -23.249 22.205 20.363 1.00 0.00 H \\\\nATOM 1653 HG2 GLU A 174 -24.119 23.485 18.676 1.00 0.00 H \\\\nATOM 1654 HG3 GLU A 174 -25.424 23.768 19.481 1.00 0.00 H \\\\nATOM 1655 N VAL A 175 -24.328 19.577 21.786 1.00 0.00 N \\\\nATOM 1656 CA VAL A 175 -23.617 18.391 22.258 1.00 0.00 C \\\\nATOM 1657 C VAL A 175 -24.184 17.131 21.614 1.00 0.00 C \\\\nATOM 1658 O VAL A 175 -23.437 16.222 21.229 1.00 0.00 O \\\\nATOM 1659 CB VAL A 175 -23.672 18.317 23.797 1.00 0.00 C \\\\nATOM 1660 CG1 VAL A 175 -23.324 16.918 24.286 1.00 0.00 C \\\\nATOM 1661 CG2 VAL A 175 -22.741 19.350 24.412 1.00 0.00 C \\\\nATOM 1662 H VAL A 175 -24.758 20.005 22.395 1.00 0.00 H \\\\nATOM 1663 HA VAL A 175 -22.686 18.456 21.995 1.00 0.00 H \\\\nATOM 1664 HB VAL A 175 -24.579 18.515 24.079 1.00 0.00 H \\\\nATOM 1665 HG11 VAL A 175 -23.365 16.894 25.255 1.00 0.00 H \\\\nATOM 1666 HG12 VAL A 175 -23.957 16.280 23.920 1.00 0.00 H \\\\nATOM 1667 HG13 VAL A 175 -22.428 16.687 23.995 1.00 0.00 H \\\\nATOM 1668 HG21 VAL A 175 -22.786 19.292 25.379 1.00 0.00 H \\\\nATOM 1669 HG22 VAL A 175 -21.832 19.180 24.120 1.00 0.00 H \\\\nATOM 1670 HG23 VAL A 175 -23.011 20.238 24.129 1.00 0.00 H \\\\nATOM 1671 N SER A 176 -25.506 17.061 21.474 1.00 0.00 N \\\\nATOM 1672 CA SER A 176 -26.170 15.865 20.973 1.00 0.00 C \\\\nATOM 1673 C SER A 176 -26.268 15.819 19.453 1.00 0.00 C \\\\nATOM 1674 O SER A 176 -26.776 14.832 18.911 1.00 0.00 O \\\\nATOM 1675 CB SER A 176 -27.571 15.752 21.579 1.00 0.00 C \\\\nATOM 1676 OG SER A 176 -28.466 16.654 20.953 1.00 0.00 O \\\\nATOM 1677 H SER A 176 -26.041 17.706 21.667 1.00 0.00 H \\\\nATOM 1678 HA SER A 176 -25.620 15.113 21.243 1.00 0.00 H \\\\nATOM 1679 HB2 SER A 176 -27.898 14.844 21.480 1.00 0.00 H \\\\nATOM 1680 HB3 SER A 176 -27.532 15.937 22.530 1.00 0.00 H \\\\nATOM 1681 HG SER A 176 -28.313 17.434 21.224 1.00 0.00 H \\\\nATOM 1682 N GLY A 177 -25.797 16.848 18.754 1.00 0.00 N \\\\nATOM 1683 CA GLY A 177 -25.832 16.851 17.306 1.00 0.00 C \\\\nATOM 1684 C GLY A 177 -27.163 17.174 16.660 1.00 0.00 C \\\\nATOM 1685 O GLY A 177 -27.304 16.961 15.451 1.00 0.00 O \\\\nATOM 1686 H GLY A 177 -25.453 17.554 19.105 1.00 0.00 H \\\\nATOM 1687 HA2 GLY A 177 -25.177 17.492 16.988 1.00 0.00 H \\\\nATOM 1688 HA3 GLY A 177 -25.548 15.978 16.994 1.00 0.00 H \\\\nATOM 1689 N ARG A 178 -28.151 17.672 17.413 1.00 0.00 N \\\\nATOM 1690 CA ARG A 178 -29.421 18.050 16.797 1.00 0.00 C \\\\nATOM 1691 C ARG A 178 -29.354 19.372 16.056 1.00 0.00 C \\\\nATOM 1692 O ARG A 178 -30.164 19.601 15.152 1.00 0.00 O \\\\nATOM 1693 CB ARG A 178 -30.529 18.132 17.844 1.00 0.00 C \\\\nATOM 1694 CG ARG A 178 -31.029 16.774 18.222 1.00 0.00 C \\\\nATOM 1695 CD ARG A 178 -31.971 16.778 19.398 1.00 0.00 C \\\\nATOM 1696 NE ARG A 178 -31.737 15.586 20.179 1.00 0.00 N \\\\nATOM 1697 CZ ARG A 178 -31.242 15.594 21.409 1.00 0.00 C \\\\nATOM 1698 NH1 ARG A 178 -30.954 16.752 21.988 1.00 0.00 N \\\\nATOM 1699 NH2 ARG A 178 -31.034 14.447 22.065 1.00 0.00 N \\\\nATOM 1700 H ARG A 178 -28.106 17.795 18.263 1.00 0.00 H \\\\nATOM 1701 HA ARG A 178 -29.617 17.354 16.151 1.00 0.00 H \\\\nATOM 1702 HB2 ARG A 178 -30.196 18.587 18.634 1.00 0.00 H \\\\nATOM 1703 HB3 ARG A 178 -31.263 18.664 17.499 1.00 0.00 H \\\\nATOM 1704 HG2 ARG A 178 -31.480 16.381 17.459 1.00 0.00 H \\\\nATOM 1705 HG3 ARG A 178 -30.271 16.205 18.428 1.00 0.00 H \\\\nATOM 1706 HD2 ARG A 178 -31.829 17.569 19.941 1.00 0.00 H \\\\nATOM 1707 HD3 ARG A 178 -32.891 16.805 19.092 1.00 0.00 H \\\\nATOM 1708 HE ARG A 178 -31.930 14.826 19.825 1.00 0.00 H \\\\nATOM 1709 HH11 ARG A 178 -31.089 17.489 21.566 1.00 0.00 H \\\\nATOM 1710 HH12 ARG A 178 -30.633 16.766 22.786 1.00 0.00 H \\\\nATOM 1711 HH21 ARG A 178 -31.222 13.697 21.689 1.00 0.00 H \\\\nATOM 1712 HH22 ARG A 178 -30.713 14.460 22.863 1.00 0.00 H \\\\nATOM 1713 N VAL A 179 -28.424 20.247 16.425 1.00 0.00 N \\\\nATOM 1714 CA VAL A 179 -28.136 21.442 15.653 1.00 0.00 C \\\\nATOM 1715 C VAL A 179 -26.639 21.465 15.396 1.00 0.00 C \\\\nATOM 1716 O VAL A 179 -25.861 20.762 16.045 1.00 0.00 O \\\\nATOM 1717 CB VAL A 179 -28.592 22.738 16.358 1.00 0.00 C \\\\nATOM 1718 CG1 VAL A 179 -30.060 22.647 16.753 1.00 0.00 C \\\\nATOM 1719 CG2 VAL A 179 -27.720 23.024 17.573 1.00 0.00 C \\\\nATOM 1720 H VAL A 179 -27.943 20.161 17.133 1.00 0.00 H \\\\nATOM 1721 HA VAL A 179 -28.635 21.410 14.822 1.00 0.00 H \\\\nATOM 1722 HB VAL A 179 -28.493 23.475 15.735 1.00 0.00 H \\\\nATOM 1723 HG11 VAL A 179 -30.328 23.468 17.194 1.00 0.00 H \\\\nATOM 1724 HG12 VAL A 179 -30.601 22.515 15.959 1.00 0.00 H \\\\nATOM 1725 HG13 VAL A 179 -30.187 21.900 17.358 1.00 0.00 H \\\\nATOM 1726 HG21 VAL A 179 -28.021 23.840 18.002 1.00 0.00 H \\\\nATOM 1727 HG22 VAL A 179 -27.786 22.286 18.200 1.00 0.00 H \\\\nATOM 1728 HG23 VAL A 179 -26.797 23.128 17.292 1.00 0.00 H \\\\nATOM 1729 N THR A 180 -26.243 22.286 14.438 1.00 0.00 N \\\\nATOM 1730 CA THR A 180 -24.855 22.362 14.020 1.00 0.00 C \\\\nATOM 1731 C THR A 180 -24.083 23.354 14.886 1.00 0.00 C \\\\nATOM 1732 O THR A 180 -24.659 24.202 15.570 1.00 0.00 O \\\\nATOM 1733 CB THR A 180 -24.780 22.758 12.546 1.00 0.00 C \\\\nATOM 1734 OG1 THR A 180 -25.039 24.162 12.413 1.00 0.00 O \\\\nATOM 1735 CG2 THR A 180 -25.814 21.985 11.741 1.00 0.00 C \\\\nATOM 1736 H THR A 180 -26.771 22.815 14.012 1.00 0.00 H \\\\nATOM 1737 HA THR A 180 -24.446 21.489 14.131 1.00 0.00 H \\\\nATOM 1738 HB THR A 180 -23.893 22.551 12.212 1.00 0.00 H \\\\nATOM 1739 HG1 THR A 180 -25.010 24.377 11.601 1.00 0.00 H \\\\nATOM 1740 HG21 THR A 180 -25.758 22.244 10.808 1.00 0.00 H \\\\nATOM 1741 HG22 THR A 180 -25.643 21.034 11.823 1.00 0.00 H \\\\nATOM 1742 HG23 THR A 180 -26.702 22.184 12.078 1.00 0.00 H \\\\nATOM 1743 N ARG A 181 -22.757 23.229 14.855 1.00 0.00 N \\\\nATOM 1744 CA ARG A 181 -21.886 24.092 15.639 1.00 0.00 C \\\\nATOM 1745 C ARG A 181 -20.715 24.549 14.782 1.00 0.00 C \\\\nATOM 1746 O ARG A 181 -20.314 23.872 13.834 1.00 0.00 O \\\\nATOM 1747 CB ARG A 181 -21.379 23.388 16.904 1.00 0.00 C \\\\nATOM 1748 CG ARG A 181 -20.406 22.255 16.645 1.00 0.00 C \\\\nATOM 1749 CD ARG A 181 -20.172 21.447 17.910 1.00 0.00 C \\\\nATOM 1750 NE ARG A 181 -19.534 20.164 17.630 1.00 0.00 N \\\\nATOM 1751 CZ ARG A 181 -20.176 19.097 17.165 1.00 0.00 C \\\\nATOM 1752 NH1 ARG A 181 -21.480 19.155 16.928 1.00 0.00 N \\\\nATOM 1753 NH2 ARG A 181 -19.515 17.971 16.937 1.00 0.00 N \\\\nATOM 1754 H ARG A 181 -22.342 22.644 14.381 1.00 0.00 H \\\\nATOM 1755 HA ARG A 181 -22.401 24.863 15.924 1.00 0.00 H \\\\nATOM 1756 HB2 ARG A 181 -20.950 24.044 17.475 1.00 0.00 H \\\\nATOM 1757 HB3 ARG A 181 -22.140 23.040 17.394 1.00 0.00 H \\\\nATOM 1758 HG2 ARG A 181 -20.753 21.678 15.947 1.00 0.00 H \\\\nATOM 1759 HG3 ARG A 181 -19.564 22.613 16.324 1.00 0.00 H \\\\nATOM 1760 HD2 ARG A 181 -19.617 21.957 18.520 1.00 0.00 H \\\\nATOM 1761 HD3 ARG A 181 -21.019 21.295 18.357 1.00 0.00 H \\\\nATOM 1762 HE ARG A 181 -18.689 20.094 17.775 1.00 0.00 H \\\\nATOM 1763 HH11 ARG A 181 -21.912 19.884 17.075 1.00 0.00 H \\\\nATOM 1764 HH12 ARG A 181 -21.894 18.464 16.627 1.00 0.00 H \\\\nATOM 1765 HH21 ARG A 181 -18.670 17.930 17.090 1.00 0.00 H \\\\nATOM 1766 HH22 ARG A 181 -19.931 17.281 16.636 1.00 0.00 H \\\\nATOM 1767 N VAL A 182 -20.157 25.699 15.145 1.00 0.00 N \\\\nATOM 1768 CA VAL A 182 -19.110 26.363 14.373 1.00 0.00 C \\\\nATOM 1769 C VAL A 182 -17.742 25.954 14.897 1.00 0.00 C \\\\nATOM 1770 O VAL A 182 -17.530 25.853 16.110 1.00 0.00 O \\\\nATOM 1771 CB VAL A 182 -19.277 27.896 14.424 1.00 0.00 C \\\\nATOM 1772 CG1 VAL A 182 -18.382 28.568 13.398 1.00 0.00 C \\\\nATOM 1773 CG2 VAL A 182 -20.734 28.277 14.213 1.00 0.00 C \\\\nATOM 1774 H VAL A 182 -20.379 26.123 15.859 1.00 0.00 H \\\\nATOM 1775 HA VAL A 182 -19.186 26.087 13.446 1.00 0.00 H \\\\nATOM 1776 HB VAL A 182 -19.007 28.207 15.302 1.00 0.00 H \\\\nATOM 1777 HG11 VAL A 182 -18.501 29.530 13.445 1.00 0.00 H \\\\nATOM 1778 HG12 VAL A 182 -17.456 28.348 13.583 1.00 0.00 H \\\\nATOM 1779 HG13 VAL A 182 -18.617 28.257 12.510 1.00 0.00 H \\\\nATOM 1780 HG21 VAL A 182 -20.825 29.242 14.247 1.00 0.00 H \\\\nATOM 1781 HG22 VAL A 182 -21.031 27.956 13.347 1.00 0.00 H \\\\nATOM 1782 HG23 VAL A 182 -21.278 27.877 14.910 1.00 0.00 H \\\\nATOM 1783 N VAL A 183 -16.810 25.718 13.979 1.00 0.00 N \\\\nATOM 1784 CA VAL A 183 -15.437 25.382 14.335 1.00 0.00 C \\\\nATOM 1785 C VAL A 183 -14.473 26.312 13.606 1.00 0.00 C \\\\nATOM 1786 O VAL A 183 -13.539 26.849 14.203 1.00 0.00 O \\\\nATOM 1787 CB VAL A 183 -15.122 23.909 14.025 1.00 0.00 C \\\\nATOM 1788 CG1 VAL A 183 -13.620 23.691 13.945 1.00 0.00 C \\\\nATOM 1789 CG2 VAL A 183 -15.741 23.009 15.086 1.00 0.00 C \\\\nATOM 1790 H VAL A 183 -16.957 25.748 13.132 1.00 0.00 H \\\\nATOM 1791 HA VAL A 183 -15.328 25.504 15.291 1.00 0.00 H \\\\nATOM 1792 HB VAL A 183 -15.506 23.682 13.164 1.00 0.00 H \\\\nATOM 1793 HG11 VAL A 183 -13.438 22.759 13.749 1.00 0.00 H \\\\nATOM 1794 HG12 VAL A 183 -13.249 24.247 13.242 1.00 0.00 H \\\\nATOM 1795 HG13 VAL A 183 -13.213 23.928 14.793 1.00 0.00 H \\\\nATOM 1796 HG21 VAL A 183 -15.538 22.082 14.883 1.00 0.00 H \\\\nATOM 1797 HG22 VAL A 183 -15.377 23.236 15.956 1.00 0.00 H \\\\nATOM 1798 HG23 VAL A 183 -16.703 23.134 15.096 1.00 0.00 H \\\\nATOM 1799 N GLY A 186 -12.084 28.785 12.961 1.00 0.00 N \\\\nATOM 1800 CA GLY A 186 -12.467 28.441 11.604 1.00 0.00 C \\\\nATOM 1801 C GLY A 186 -13.849 28.939 11.229 1.00 0.00 C \\\\nATOM 1802 O GLY A 186 -14.495 29.651 12.000 1.00 0.00 O \\\\nATOM 1803 HA2 GLY A 186 -11.817 28.812 10.987 1.00 0.00 H \\\\nATOM 1804 HA3 GLY A 186 -12.438 27.477 11.500 1.00 0.00 H \\\\nATOM 1805 N GLY A 187 -14.305 28.562 10.037 1.00 0.00 N \\\\nATOM 1806 CA GLY A 187 -15.601 28.996 9.554 1.00 0.00 C \\\\nATOM 1807 C GLY A 187 -16.443 27.864 9.005 1.00 0.00 C \\\\nATOM 1808 O GLY A 187 -17.404 28.099 8.266 1.00 0.00 O \\\\nATOM 1809 H GLY A 187 -13.873 28.053 9.495 1.00 0.00 H \\\\nATOM 1810 HA2 GLY A 187 -16.082 29.427 10.278 1.00 0.00 H \\\\nATOM 1811 HA3 GLY A 187 -15.475 29.663 8.861 1.00 0.00 H \\\\nATOM 1812 N GLU A 188 -16.090 26.629 9.353 1.00 0.00 N \\\\nATOM 1813 CA GLU A 188 -16.854 25.465 8.946 1.00 0.00 C \\\\nATOM 1814 C GLU A 188 -17.775 25.033 10.081 1.00 0.00 C \\\\nATOM 1815 O GLU A 188 -17.797 25.621 11.165 1.00 0.00 O \\\\nATOM 1816 CB GLU A 188 -15.924 24.324 8.537 1.00 0.00 C \\\\nATOM 1817 CG GLU A 188 -14.753 24.750 7.680 1.00 0.00 C \\\\nATOM 1818 CD GLU A 188 -13.509 23.946 7.981 1.00 0.00 C \\\\nATOM 1819 OE1 GLU A 188 -12.523 24.062 7.225 1.00 0.00 O \\\\nATOM 1820 OE2 GLU A 188 -13.520 23.194 8.979 1.00 0.00 O \\\\nATOM 1821 H GLU A 188 -15.399 26.447 9.832 1.00 0.00 H \\\\nATOM 1822 HA GLU A 188 -17.395 25.697 8.175 1.00 0.00 H \\\\nATOM 1823 HB2 GLU A 188 -15.585 23.894 9.338 1.00 0.00 H \\\\nATOM 1824 HB3 GLU A 188 -16.439 23.659 8.054 1.00 0.00 H \\\\nATOM 1825 HG2 GLU A 188 -14.984 24.648 6.744 1.00 0.00 H \\\\nATOM 1826 HG3 GLU A 188 -14.572 25.692 7.826 1.00 0.00 H \\\\nATOM 1827 N VAL A 189 -18.551 23.989 9.825 1.00 0.00 N \\\\nATOM 1828 CA VAL A 189 -19.635 23.587 10.710 1.00 0.00 C \\\\nATOM 1829 C VAL A 189 -19.557 22.081 10.932 1.00 0.00 C \\\\nATOM 1830 O VAL A 189 -19.227 21.320 10.015 1.00 0.00 O \\\\nATOM 1831 CB VAL A 189 -21.014 24.018 10.153 1.00 0.00 C \\\\nATOM 1832 CG1 VAL A 189 -21.579 23.004 9.181 1.00 0.00 C \\\\nATOM 1833 CG2 VAL A 189 -21.984 24.287 11.281 1.00 0.00 C \\\\nATOM 1834 H VAL A 189 -18.463 23.491 9.129 1.00 0.00 H \\\\nATOM 1835 HA VAL A 189 -19.536 24.037 11.564 1.00 0.00 H \\\\nATOM 1836 HB VAL A 189 -20.881 24.841 9.657 1.00 0.00 H \\\\nATOM 1837 HG11 VAL A 189 -22.440 23.311 8.857 1.00 0.00 H \\\\nATOM 1838 HG12 VAL A 189 -20.971 22.899 8.433 1.00 0.00 H \\\\nATOM 1839 HG13 VAL A 189 -21.688 22.151 9.630 1.00 0.00 H \\\\nATOM 1840 HG21 VAL A 189 -22.841 24.555 10.914 1.00 0.00 H \\\\nATOM 1841 HG22 VAL A 189 -22.097 23.482 11.810 1.00 0.00 H \\\\nATOM 1842 HG23 VAL A 189 -21.637 24.997 11.844 1.00 0.00 H \\\\nATOM 1843 N ARG A 190 -19.799 21.659 12.168 1.00 0.00 N \\\\nATOM 1844 CA ARG A 190 -19.895 20.251 12.521 1.00 0.00 C \\\\nATOM 1845 C ARG A 190 -21.314 19.958 12.992 1.00 0.00 C \\\\nATOM 1846 O ARG A 190 -21.900 20.741 13.746 1.00 0.00 O \\\\nATOM 1847 CB ARG A 190 -18.885 19.897 13.619 1.00 0.00 C \\\\nATOM 1848 CG ARG A 190 -18.454 18.442 13.647 1.00 0.00 C \\\\nATOM 1849 CD ARG A 190 -16.936 18.315 13.713 1.00 0.00 C \\\\nATOM 1850 NE ARG A 190 -16.350 19.123 14.781 1.00 0.00 N \\\\nATOM 1851 CZ ARG A 190 -15.048 19.175 15.050 1.00 0.00 C \\\\nATOM 1852 NH1 ARG A 190 -14.189 18.470 14.323 1.00 0.00 N \\\\nATOM 1853 NH2 ARG A 190 -14.598 19.936 16.041 1.00 0.00 N \\\\nATOM 1854 H ARG A 190 -19.913 22.191 12.834 1.00 0.00 H \\\\nATOM 1855 HA ARG A 190 -19.690 19.709 11.743 1.00 0.00 H \\\\nATOM 1856 HB2 ARG A 190 -18.097 20.452 13.507 1.00 0.00 H \\\\nATOM 1857 HB3 ARG A 190 -19.271 20.123 14.480 1.00 0.00 H \\\\nATOM 1858 HG2 ARG A 190 -18.851 18.000 14.413 1.00 0.00 H \\\\nATOM 1859 HG3 ARG A 190 -18.784 17.989 12.855 1.00 0.00 H \\\\nATOM 1860 HD2 ARG A 190 -16.698 17.384 13.849 1.00 0.00 H \\\\nATOM 1861 HD3 ARG A 190 -16.555 18.584 12.862 1.00 0.00 H \\\\nATOM 1862 HE ARG A 190 -16.881 19.595 15.266 1.00 0.00 H \\\\nATOM 1863 HH11 ARG A 190 -14.474 17.979 13.677 1.00 0.00 H \\\\nATOM 1864 HH12 ARG A 190 -13.348 18.505 14.498 1.00 0.00 H \\\\nATOM 1865 HH21 ARG A 190 -15.149 20.398 16.512 1.00 0.00 H \\\\nATOM 1866 HH22 ARG A 190 -13.756 19.967 16.211 1.00 0.00 H \\\\nATOM 1867 N SER A 191 -21.870 18.830 12.540 1.00 0.00 N \\\\nATOM 1868 CA SER A 191 -23.216 18.431 12.927 1.00 0.00 C \\\\nATOM 1869 C SER A 191 -23.290 17.111 13.680 1.00 0.00 C \\\\nATOM 1870 O SER A 191 -24.346 16.809 14.247 1.00 0.00 O \\\\nATOM 1871 CB SER A 191 -24.123 18.344 11.690 1.00 0.00 C \\\\nATOM 1872 OG SER A 191 -24.093 17.045 11.126 1.00 0.00 O \\\\nATOM 1873 H SER A 191 -21.478 18.282 12.005 1.00 0.00 H \\\\nATOM 1874 HA SER A 191 -23.519 19.121 13.538 1.00 0.00 H \\\\nATOM 1875 HB2 SER A 191 -25.033 18.572 11.936 1.00 0.00 H \\\\nATOM 1876 HB3 SER A 191 -23.837 18.994 11.029 1.00 0.00 H \\\\nATOM 1877 HG SER A 191 -24.596 17.020 10.454 1.00 0.00 H \\\\nATOM 1878 N GLU A 192 -22.221 16.321 13.700 1.00 0.00 N \\\\nATOM 1879 CA GLU A 192 -22.242 15.078 14.451 1.00 0.00 C \\\\nATOM 1880 C GLU A 192 -22.275 15.371 15.952 1.00 0.00 C \\\\nATOM 1881 O GLU A 192 -21.853 16.442 16.392 1.00 0.00 O \\\\nATOM 1882 CB GLU A 192 -21.018 14.230 14.110 1.00 0.00 C \\\\nATOM 1883 CG GLU A 192 -21.282 13.143 13.081 1.00 0.00 C \\\\nATOM 1884 CD GLU A 192 -21.814 11.866 13.704 1.00 0.00 C \\\\nATOM 1885 OE1 GLU A 192 -21.008 11.096 14.268 1.00 0.00 O \\\\nATOM 1886 OE2 GLU A 192 -23.039 11.634 13.634 1.00 0.00 O \\\\nATOM 1887 H GLU A 192 -21.483 16.486 13.290 1.00 0.00 H \\\\nATOM 1888 HA GLU A 192 -23.040 14.583 14.209 1.00 0.00 H \\\\nATOM 1889 HB2 GLU A 192 -20.316 14.812 13.779 1.00 0.00 H \\\\nATOM 1890 HB3 GLU A 192 -20.685 13.818 14.923 1.00 0.00 H \\\\nATOM 1891 HG2 GLU A 192 -21.919 13.470 12.427 1.00 0.00 H \\\\nATOM 1892 HG3 GLU A 192 -20.460 12.948 12.604 1.00 0.00 H \\\\nATOM 1893 N PRO A 193 -22.788 14.438 16.757 1.00 0.00 N \\\\nATOM 1894 CA PRO A 193 -22.715 14.611 18.213 1.00 0.00 C \\\\nATOM 1895 C PRO A 193 -21.271 14.743 18.674 1.00 0.00 C \\\\nATOM 1896 O PRO A 193 -20.348 14.198 18.066 1.00 0.00 O \\\\nATOM 1897 CB PRO A 193 -23.367 13.336 18.760 1.00 0.00 C \\\\nATOM 1898 CG PRO A 193 -24.214 12.821 17.642 1.00 0.00 C \\\\nATOM 1899 CD PRO A 193 -23.519 13.220 16.373 1.00 0.00 C \\\\nATOM 1900 HA PRO A 193 -23.158 15.417 18.523 1.00 0.00 H \\\\nATOM 1901 HB2 PRO A 193 -22.698 12.684 19.022 1.00 0.00 H \\\\nATOM 1902 HB3 PRO A 193 -23.902 13.525 19.547 1.00 0.00 H \\\\nATOM 1903 HG2 PRO A 193 -24.311 11.857 17.696 1.00 0.00 H \\\\nATOM 1904 HG3 PRO A 193 -25.107 13.198 17.681 1.00 0.00 H \\\\nATOM 1905 HD2 PRO A 193 -22.918 12.526 16.060 1.00 0.00 H \\\\nATOM 1906 HD3 PRO A 193 -24.151 13.392 15.657 1.00 0.00 H \\\\nATOM 1907 N VAL A 194 -21.083 15.482 19.770 1.00 0.00 N \\\\nATOM 1908 CA VAL A 194 -19.736 15.722 20.277 1.00 0.00 C \\\\nATOM 1909 C VAL A 194 -19.079 14.430 20.746 1.00 0.00 C \\\\nATOM 1910 O VAL A 194 -17.871 14.237 20.559 1.00 0.00 O \\\\nATOM 1911 CB VAL A 194 -19.779 16.780 21.401 1.00 0.00 C \\\\nATOM 1912 CG1 VAL A 194 -18.459 16.825 22.151 1.00 0.00 C \\\\nATOM 1913 CG2 VAL A 194 -20.115 18.151 20.829 1.00 0.00 C \\\\nATOM 1914 H VAL A 194 -21.714 15.847 20.227 1.00 0.00 H \\\\nATOM 1915 HA VAL A 194 -19.190 16.066 19.553 1.00 0.00 H \\\\nATOM 1916 HB VAL A 194 -20.475 16.528 22.028 1.00 0.00 H \\\\nATOM 1917 HG11 VAL A 194 -18.507 17.495 22.851 1.00 0.00 H \\\\nATOM 1918 HG12 VAL A 194 -18.281 15.957 22.546 1.00 0.00 H \\\\nATOM 1919 HG13 VAL A 194 -17.744 17.052 21.536 1.00 0.00 H \\\\nATOM 1920 HG21 VAL A 194 -20.138 18.804 21.546 1.00 0.00 H \\\\nATOM 1921 HG22 VAL A 194 -19.439 18.406 20.182 1.00 0.00 H \\\\nATOM 1922 HG23 VAL A 194 -20.982 18.117 20.395 1.00 0.00 H \\\\nATOM 1923 N THR A 195 -19.854 13.509 21.309 1.00 0.00 N \\\\nATOM 1924 CA THR A 195 -19.297 12.256 21.810 1.00 0.00 C \\\\nATOM 1925 C THR A 195 -20.427 11.241 21.971 1.00 0.00 C \\\\nATOM 1926 O THR A 195 -21.537 11.431 21.463 1.00 0.00 O \\\\nATOM 1927 CB THR A 195 -18.533 12.489 23.118 1.00 0.00 C \\\\nATOM 1928 OG1 THR A 195 -17.938 11.261 23.557 1.00 0.00 O \\\\nATOM 1929 CG2 THR A 195 -19.470 13.027 24.187 1.00 0.00 C \\\\nATOM 1930 H THR A 195 -20.704 13.589 21.411 1.00 0.00 H \\\\nATOM 1931 HA THR A 195 -18.655 11.900 21.176 1.00 0.00 H \\\\nATOM 1932 HB THR A 195 -17.834 13.143 22.962 1.00 0.00 H \\\\nATOM 1933 HG1 THR A 195 -17.101 11.331 23.534 1.00 0.00 H \\\\nATOM 1934 HG21 THR A 195 -18.975 13.170 25.009 1.00 0.00 H \\\\nATOM 1935 HG22 THR A 195 -19.852 13.867 23.889 1.00 0.00 H \\\\nATOM 1936 HG23 THR A 195 -20.182 12.387 24.346 1.00 0.00 H \\\\nATOM 1937 N ALA A 196 -20.133 10.151 22.681 1.00 0.00 N \\\\nATOM 1938 CA ALA A 196 -21.052 9.031 22.803 1.00 0.00 C \\\\nATOM 1939 C ALA A 196 -22.309 9.429 23.575 1.00 0.00 C \\\\nATOM 1940 O ALA A 196 -22.389 10.492 24.199 1.00 0.00 O \\\\nATOM 1941 CB ALA A 196 -20.366 7.849 23.488 1.00 0.00 C \\\\nATOM 1942 H ALA A 196 -19.392 10.045 23.105 1.00 0.00 H \\\\nATOM 1943 HA ALA A 196 -21.318 8.766 21.909 1.00 0.00 H \\\\nATOM 1944 HB1 ALA A 196 -20.991 7.111 23.562 1.00 0.00 H \\\\nATOM 1945 HB2 ALA A 196 -19.599 7.571 22.963 1.00 0.00 H \\\\nATOM 1946 HB3 ALA A 196 -20.073 8.114 24.374 1.00 0.00 H \\\\nATOM 1947 N GLU A 197 -23.305 8.539 23.529 1.00 0.00 N \\\\nATOM 1948 CA GLU A 197 -24.622 8.857 24.070 1.00 0.00 C \\\\nATOM 1949 C GLU A 197 -24.633 8.874 25.594 1.00 0.00 C \\\\nATOM 1950 O GLU A 197 -25.467 9.563 26.195 1.00 0.00 O \\\\nATOM 1951 CB GLU A 197 -25.654 7.860 23.540 1.00 0.00 C \\\\nATOM 1952 CG GLU A 197 -25.416 6.420 23.967 1.00 0.00 C \\\\nATOM 1953 CD GLU A 197 -24.720 5.603 22.894 1.00 0.00 C \\\\nATOM 1954 OE1 GLU A 197 -23.571 5.943 22.536 1.00 0.00 O \\\\nATOM 1955 OE2 GLU A 197 -25.323 4.624 22.400 1.00 0.00 O \\\\nATOM 1956 H GLU A 197 -23.236 7.752 23.190 1.00 0.00 H \\\\nATOM 1957 HA GLU A 197 -24.852 9.752 23.775 1.00 0.00 H \\\\nATOM 1958 HB2 GLU A 197 -26.535 8.133 23.840 1.00 0.00 H \\\\nATOM 1959 HB3 GLU A 197 -25.659 7.902 22.571 1.00 0.00 H \\\\nATOM 1960 HG2 GLU A 197 -24.880 6.410 24.775 1.00 0.00 H \\\\nATOM 1961 HG3 GLU A 197 -26.266 6.006 24.185 1.00 0.00 H \\\\nATOM 1962 N ASN A 198 -23.727 8.138 26.234 1.00 0.00 N \\\\nATOM 1963 CA ASN A 198 -23.701 8.032 27.687 1.00 0.00 C \\\\nATOM 1964 C ASN A 198 -22.864 9.111 28.362 1.00 0.00 C \\\\nATOM 1965 O ASN A 198 -22.714 9.076 29.588 1.00 0.00 O \\\\nATOM 1966 CB ASN A 198 -23.183 6.652 28.105 1.00 0.00 C \\\\nATOM 1967 CG ASN A 198 -21.736 6.429 27.714 1.00 0.00 C \\\\nATOM 1968 OD1 ASN A 198 -21.317 6.787 26.615 1.00 0.00 O \\\\nATOM 1969 ND2 ASN A 198 -20.962 5.840 28.617 1.00 0.00 N \\\\nATOM 1970 H ASN A 198 -23.112 7.687 25.837 1.00 0.00 H \\\\nATOM 1971 HA ASN A 198 -24.616 8.158 27.983 1.00 0.00 H \\\\nATOM 1972 HB2 ASN A 198 -23.274 6.554 29.066 1.00 0.00 H \\\\nATOM 1973 HB3 ASN A 198 -23.734 5.966 27.697 1.00 0.00 H \\\\nATOM 1974 HD21 ASN A 198 -20.132 5.695 28.443 1.00 0.00 H \\\\nATOM 1975 HD22 ASN A 198 -21.290 5.603 29.376 1.00 0.00 H \\\\nATOM 1976 N VAL A 199 -22.320 10.062 27.612 1.00 0.00 N \\\\nATOM 1977 CA VAL A 199 -21.465 11.098 28.179 1.00 0.00 C \\\\nATOM 1978 C VAL A 199 -22.307 12.327 28.490 1.00 0.00 C \\\\nATOM 1979 O VAL A 199 -23.071 12.804 27.643 1.00 0.00 O \\\\nATOM 1980 CB VAL A 199 -20.314 11.446 27.221 1.00 0.00 C \\\\nATOM 1981 CG1 VAL A 199 -19.352 12.429 27.873 1.00 0.00 C \\\\nATOM 1982 CG2 VAL A 199 -19.586 10.185 26.779 1.00 0.00 C \\\\nATOM 1983 H VAL A 199 -22.435 10.125 26.762 1.00 0.00 H \\\\nATOM 1984 HA VAL A 199 -21.067 10.769 29.000 1.00 0.00 H \\\\nATOM 1985 HB VAL A 199 -20.689 11.870 26.433 1.00 0.00 H \\\\nATOM 1986 HG11 VAL A 199 -18.634 12.637 27.255 1.00 0.00 H \\\\nATOM 1987 HG12 VAL A 199 -19.827 13.243 28.102 1.00 0.00 H \\\\nATOM 1988 HG13 VAL A 199 -18.982 12.034 28.678 1.00 0.00 H \\\\nATOM 1989 HG21 VAL A 199 -18.864 10.422 26.176 1.00 0.00 H \\\\nATOM 1990 HG22 VAL A 199 -19.222 9.732 27.556 1.00 0.00 H \\\\nATOM 1991 HG23 VAL A 199 -20.207 9.596 26.323 1.00 0.00 H \\\\nATOM 1992 N GLY A 200 -22.169 12.843 29.708 1.00 0.00 N \\\\nATOM 1993 CA GLY A 200 -22.909 14.011 30.134 1.00 0.00 C \\\\nATOM 1994 C GLY A 200 -22.110 14.806 31.143 1.00 0.00 C \\\\nATOM 1995 O GLY A 200 -20.963 14.478 31.456 1.00 0.00 O \\\\nATOM 1996 H GLY A 200 -21.642 12.521 30.307 1.00 0.00 H \\\\nATOM 1997 HA2 GLY A 200 -23.116 14.567 29.367 1.00 0.00 H \\\\nATOM 1998 HA3 GLY A 200 -23.755 13.740 30.524 1.00 0.00 H \\\\nATOM 1999 N SER A 201 -22.729 15.869 31.654 1.00 0.00 N \\\\nATOM 2000 CA SER A 201 -22.066 16.740 32.613 1.00 0.00 C \\\\nATOM 2001 C SER A 201 -23.103 17.557 33.369 1.00 0.00 C \\\\nATOM 2002 O SER A 201 -24.123 17.955 32.799 1.00 0.00 O \\\\nATOM 2003 CB SER A 201 -21.067 17.675 31.921 1.00 0.00 C \\\\nATOM 2004 OG SER A 201 -20.516 18.595 32.850 1.00 0.00 O \\\\nATOM 2005 H SER A 201 -23.533 16.101 31.456 1.00 0.00 H \\\\nATOM 2006 HA SER A 201 -21.573 16.183 33.236 1.00 0.00 H \\\\nATOM 2007 HB2 SER A 201 -20.357 17.154 31.515 1.00 0.00 H \\\\nATOM 2008 HB3 SER A 201 -21.510 18.157 31.205 1.00 0.00 H \\\\nATOM 2009 HG SER A 201 -20.490 18.243 33.612 1.00 0.00 H \\\\nATOM 2010 N THR A 202 -22.828 17.804 34.649 1.00 0.00 N \\\\nATOM 2011 CA THR A 202 -23.560 18.820 35.382 1.00 0.00 C \\\\nATOM 2012 C THR A 202 -23.116 20.209 34.927 1.00 0.00 C \\\\nATOM 2013 O THR A 202 -22.101 20.380 34.246 1.00 0.00 O \\\\nATOM 2014 CB THR A 202 -23.331 18.678 36.886 1.00 0.00 C \\\\nATOM 2015 OG1 THR A 202 -22.149 19.399 37.257 1.00 0.00 O \\\\nATOM 2016 CG2 THR A 202 -23.145 17.222 37.265 1.00 0.00 C \\\\nATOM 2017 H THR A 202 -22.224 17.394 35.104 1.00 0.00 H \\\\nATOM 2018 HA THR A 202 -24.506 18.704 35.201 1.00 0.00 H \\\\nATOM 2019 HB THR A 202 -24.107 19.032 37.348 1.00 0.00 H \\\\nATOM 2020 HG1 THR A 202 -22.366 20.111 37.647 1.00 0.00 H \\\\nATOM 2021 HG21 THR A 202 -23.001 17.152 38.222 1.00 0.00 H \\\\nATOM 2022 HG22 THR A 202 -23.938 16.720 37.020 1.00 0.00 H \\\\nATOM 2023 HG23 THR A 202 -22.377 16.861 36.796 1.00 0.00 H \\\\nATOM 2024 N ALA A 203 -23.898 21.213 35.308 1.00 0.00 N \\\\nATOM 2025 CA ALA A 203 -23.508 22.599 35.078 1.00 0.00 C \\\\nATOM 2026 C ALA A 203 -24.156 23.466 36.142 1.00 0.00 C \\\\nATOM 2027 O ALA A 203 -25.386 23.559 36.202 1.00 0.00 O \\\\nATOM 2028 CB ALA A 203 -23.917 23.066 33.678 1.00 0.00 C \\\\nATOM 2029 H ALA A 203 -24.657 21.114 35.700 1.00 0.00 H \\\\nATOM 2030 HA ALA A 203 -22.542 22.674 35.134 1.00 0.00 H \\\\nATOM 2031 HB1 ALA A 203 -23.646 23.989 33.553 1.00 0.00 H \\\\nATOM 2032 HB2 ALA A 203 -23.485 22.509 33.012 1.00 0.00 H \\\\nATOM 2033 HB3 ALA A 203 -24.880 22.996 33.582 1.00 0.00 H \\\\nATOM 2034 N VAL A 204 -23.333 24.090 36.980 1.00 0.00 N \\\\nATOM 2035 CA VAL A 204 -23.780 25.131 37.897 1.00 0.00 C \\\\nATOM 2036 C VAL A 204 -22.963 26.377 37.583 1.00 0.00 C \\\\nATOM 2037 O VAL A 204 -21.726 26.352 37.645 1.00 0.00 O \\\\nATOM 2038 CB VAL A 204 -23.651 24.707 39.373 1.00 0.00 C \\\\nATOM 2039 CG1 VAL A 204 -22.212 24.348 39.746 1.00 0.00 C \\\\nATOM 2040 CG2 VAL A 204 -24.192 25.792 40.282 1.00 0.00 C \\\\nATOM 2041 H VAL A 204 -22.492 23.919 37.032 1.00 0.00 H \\\\nATOM 2042 HA VAL A 204 -24.726 25.306 37.772 1.00 0.00 H \\\\nATOM 2043 HB VAL A 204 -24.182 23.904 39.494 1.00 0.00 H \\\\nATOM 2044 HG11 VAL A 204 -22.175 24.088 40.680 1.00 0.00 H \\\\nATOM 2045 HG12 VAL A 204 -21.908 23.611 39.193 1.00 0.00 H \\\\nATOM 2046 HG13 VAL A 204 -21.639 25.117 39.602 1.00 0.00 H \\\\nATOM 2047 HG21 VAL A 204 -24.105 25.513 41.207 1.00 0.00 H \\\\nATOM 2048 HG22 VAL A 204 -23.690 26.611 40.143 1.00 0.00 H \\\\nATOM 2049 HG23 VAL A 204 -25.127 25.948 40.079 1.00 0.00 H \\\\nATOM 2050 N VAL A 205 -23.645 27.451 37.199 1.00 0.00 N \\\\nATOM 2051 CA VAL A 205 -22.970 28.670 36.778 1.00 0.00 C \\\\nATOM 2052 C VAL A 205 -23.423 29.822 37.660 1.00 0.00 C \\\\nATOM 2053 O VAL A 205 -24.567 29.870 38.124 1.00 0.00 O \\\\nATOM 2054 CB VAL A 205 -23.212 28.982 35.283 1.00 0.00 C \\\\nATOM 2055 CG1 VAL A 205 -22.912 27.756 34.429 1.00 0.00 C \\\\nATOM 2056 CG2 VAL A 205 -24.634 29.465 35.048 1.00 0.00 C \\\\nATOM 2057 H VAL A 205 -24.504 27.493 37.176 1.00 0.00 H \\\\nATOM 2058 HA VAL A 205 -22.014 28.543 36.879 1.00 0.00 H \\\\nATOM 2059 HB VAL A 205 -22.609 29.695 35.022 1.00 0.00 H \\\\nATOM 2060 HG11 VAL A 205 -23.068 27.966 33.495 1.00 0.00 H \\\\nATOM 2061 HG12 VAL A 205 -21.986 27.495 34.551 1.00 0.00 H \\\\nATOM 2062 HG13 VAL A 205 -23.491 27.025 34.697 1.00 0.00 H \\\\nATOM 2063 HG21 VAL A 205 -24.760 29.654 34.105 1.00 0.00 H \\\\nATOM 2064 HG22 VAL A 205 -25.260 28.778 35.326 1.00 0.00 H \\\\nATOM 2065 HG23 VAL A 205 -24.791 30.272 35.562 1.00 0.00 H \\\\nATOM 2066 N ALA A 206 -22.500 30.747 37.906 1.00 0.00 N \\\\nATOM 2067 CA ALA A 206 -22.762 31.940 38.702 1.00 0.00 C \\\\nATOM 2068 C ALA A 206 -22.485 33.167 37.844 1.00 0.00 C \\\\nATOM 2069 O ALA A 206 -21.340 33.408 37.449 1.00 0.00 O \\\\nATOM 2070 CB ALA A 206 -21.908 31.954 39.968 1.00 0.00 C \\\\nATOM 2071 H ALA A 206 -21.694 30.698 37.611 1.00 0.00 H \\\\nATOM 2072 HA ALA A 206 -23.690 31.943 38.985 1.00 0.00 H \\\\nATOM 2073 HB1 ALA A 206 -22.100 32.756 40.479 1.00 0.00 H \\\\nATOM 2074 HB2 ALA A 206 -22.112 31.172 40.505 1.00 0.00 H \\\\nATOM 2075 HB3 ALA A 206 -20.969 31.943 39.725 1.00 0.00 H \\\\nATOM 2076 N LEU A 207 -23.530 33.934 37.554 1.00 0.00 N \\\\nATOM 2077 CA LEU A 207 -23.387 35.238 36.922 1.00 0.00 C \\\\nATOM 2078 C LEU A 207 -23.242 36.284 38.021 1.00 0.00 C \\\\nATOM 2079 O LEU A 207 -24.176 36.506 38.798 1.00 0.00 O \\\\nATOM 2080 CB LEU A 207 -24.592 35.539 36.029 1.00 0.00 C \\\\nATOM 2081 CG LEU A 207 -24.446 36.608 34.948 1.00 0.00 C \\\\nATOM 2082 CD1 LEU A 207 -25.306 36.258 33.741 1.00 0.00 C \\\\nATOM 2083 CD2 LEU A 207 -24.827 37.975 35.493 1.00 0.00 C \\\\nATOM 2084 H LEU A 207 -24.344 33.711 37.719 1.00 0.00 H \\\\nATOM 2085 HA LEU A 207 -22.601 35.250 36.354 1.00 0.00 H \\\\nATOM 2086 HB2 LEU A 207 -24.851 34.712 35.593 1.00 0.00 H \\\\nATOM 2087 HB3 LEU A 207 -25.328 35.799 36.604 1.00 0.00 H \\\\nATOM 2088 HG LEU A 207 -23.517 36.639 34.669 1.00 0.00 H \\\\nATOM 2089 HD11 LEU A 207 -25.205 36.943 33.062 1.00 0.00 H \\\\nATOM 2090 HD12 LEU A 207 -25.025 35.402 33.381 1.00 0.00 H \\\\nATOM 2091 HD13 LEU A 207 -26.236 36.205 34.011 1.00 0.00 H \\\\nATOM 2092 HD21 LEU A 207 -24.729 38.641 34.795 1.00 0.00 H \\\\nATOM 2093 HD22 LEU A 207 -25.749 37.958 35.795 1.00 0.00 H \\\\nATOM 2094 HD23 LEU A 207 -24.247 38.200 36.237 1.00 0.00 H \\\\nATOM 2095 N VAL A 208 -22.074 36.917 38.092 1.00 0.00 N \\\\nATOM 2096 CA VAL A 208 -21.758 37.873 39.146 1.00 0.00 C \\\\nATOM 2097 C VAL A 208 -21.595 39.251 38.523 1.00 0.00 C \\\\nATOM 2098 O VAL A 208 -20.709 39.459 37.683 1.00 0.00 O \\\\nATOM 2099 CB VAL A 208 -20.490 37.476 39.918 1.00 0.00 C \\\\nATOM 2100 CG1 VAL A 208 -20.291 38.392 41.119 1.00 0.00 C \\\\nATOM 2101 CG2 VAL A 208 -20.559 36.017 40.354 1.00 0.00 C \\\\nATOM 2102 H VAL A 208 -21.438 36.802 37.524 1.00 0.00 H \\\\nATOM 2103 HA VAL A 208 -22.486 37.881 39.787 1.00 0.00 H \\\\nATOM 2104 HB VAL A 208 -19.727 37.577 39.328 1.00 0.00 H \\\\nATOM 2105 HG11 VAL A 208 -19.488 38.130 41.596 1.00 0.00 H \\\\nATOM 2106 HG12 VAL A 208 -20.202 39.309 40.816 1.00 0.00 H \\\\nATOM 2107 HG13 VAL A 208 -21.056 38.321 41.711 1.00 0.00 H \\\\nATOM 2108 HG21 VAL A 208 -19.751 35.785 40.839 1.00 0.00 H \\\\nATOM 2109 HG22 VAL A 208 -21.329 35.887 40.929 1.00 0.00 H \\\\nATOM 2110 HG23 VAL A 208 -20.640 35.449 39.572 1.00 0.00 H \\\\nATOM 2111 N CYS A 209 -22.446 40.187 38.936 1.00 0.00 N \\\\nATOM 2112 CA CYS A 209 -22.303 41.596 38.606 1.00 0.00 C \\\\nATOM 2113 C CYS A 209 -22.325 42.396 39.904 1.00 0.00 C \\\\nATOM 2114 O CYS A 209 -22.378 41.833 41.003 1.00 0.00 O \\\\nATOM 2115 CB CYS A 209 -23.397 42.061 37.634 1.00 0.00 C \\\\nATOM 2116 SG CYS A 209 -25.061 42.128 38.333 1.00 0.00 S \\\\nATOM 2117 H CYS A 209 -23.133 40.015 39.424 1.00 0.00 H \\\\nATOM 2118 HA CYS A 209 -21.459 41.741 38.151 1.00 0.00 H \\\\nATOM 2119 HB2 CYS A 209 -23.164 42.943 37.304 1.00 0.00 H \\\\nATOM 2120 HB3 CYS A 209 -23.406 41.465 36.869 1.00 0.00 H \\\\nATOM 2121 HG CYS A 209 -25.866 42.194 37.445 1.00 0.00 H \\\\nATOM 2122 N SER A 210 -22.283 43.725 39.773 1.00 0.00 N \\\\nATOM 2123 CA SER A 210 -22.151 44.580 40.950 1.00 0.00 C \\\\nATOM 2124 C SER A 210 -23.364 44.489 41.868 1.00 0.00 C \\\\nATOM 2125 O SER A 210 -23.225 44.595 43.092 1.00 0.00 O \\\\nATOM 2126 CB SER A 210 -21.920 46.029 40.523 1.00 0.00 C \\\\nATOM 2127 OG SER A 210 -23.153 46.708 40.347 1.00 0.00 O \\\\nATOM 2128 H SER A 210 -22.329 44.143 39.023 1.00 0.00 H \\\\nATOM 2129 HA SER A 210 -21.384 44.264 41.453 1.00 0.00 H \\\\nATOM 2130 HB2 SER A 210 -21.387 46.486 41.192 1.00 0.00 H \\\\nATOM 2131 HB3 SER A 210 -21.414 46.050 39.696 1.00 0.00 H \\\\nATOM 2132 HG SER A 210 -23.005 47.502 40.114 1.00 0.00 H \\\\nATOM 2133 N SER A 211 -24.557 44.308 41.305 1.00 0.00 N \\\\nATOM 2134 CA SER A 211 -25.787 44.351 42.086 1.00 0.00 C \\\\nATOM 2135 C SER A 211 -26.331 42.980 42.455 1.00 0.00 C \\\\nATOM 2136 O SER A 211 -26.935 42.839 43.523 1.00 0.00 O \\\\nATOM 2137 CB SER A 211 -26.873 45.122 41.326 1.00 0.00 C \\\\nATOM 2138 OG SER A 211 -27.609 44.259 40.480 1.00 0.00 O \\\\nATOM 2139 H SER A 211 -24.674 44.158 40.466 1.00 0.00 H \\\\nATOM 2140 HA SER A 211 -25.554 44.800 42.913 1.00 0.00 H \\\\nATOM 2141 HB2 SER A 211 -27.472 45.550 41.957 1.00 0.00 H \\\\nATOM 2142 HB3 SER A 211 -26.465 45.827 40.799 1.00 0.00 H \\\\nATOM 2143 HG SER A 211 -27.458 44.457 39.678 1.00 0.00 H \\\\nATOM 2144 N HIS A 212 -26.131 41.967 41.615 1.00 0.00 N \\\\nATOM 2145 CA HIS A 212 -26.789 40.686 41.818 1.00 0.00 C \\\\nATOM 2146 C HIS A 212 -25.820 39.540 41.583 1.00 0.00 C \\\\nATOM 2147 O HIS A 212 -24.792 39.684 40.915 1.00 0.00 O \\\\nATOM 2148 CB HIS A 212 -27.992 40.515 40.881 1.00 0.00 C \\\\nATOM 2149 CG HIS A 212 -29.224 41.231 41.333 1.00 0.00 C \\\\nATOM 2150 ND1 HIS A 212 -29.412 42.583 41.143 1.00 0.00 N \\\\nATOM 2151 CD2 HIS A 212 -30.336 40.782 41.961 1.00 0.00 C \\\\nATOM 2152 CE1 HIS A 212 -30.584 42.936 41.639 1.00 0.00 C \\\\nATOM 2153 NE2 HIS A 212 -31.166 41.861 42.140 1.00 0.00 N \\\\nATOM 2154 H HIS A 212 -25.619 42.003 40.925 1.00 0.00 H \\\\nATOM 2155 HA HIS A 212 -27.100 40.671 42.737 1.00 0.00 H \\\\nATOM 2156 HB2 HIS A 212 -27.750 40.834 39.998 1.00 0.00 H \\\\nATOM 2157 HB3 HIS A 212 -28.192 39.570 40.796 1.00 0.00 H \\\\nATOM 2158 HD1 HIS A 212 -28.853 43.114 40.761 1.00 0.00 H \\\\nATOM 2159 HD2 HIS A 212 -30.506 39.906 42.222 1.00 0.00 H \\\\nATOM 2160 HE1 HIS A 212 -30.939 43.795 41.636 1.00 0.00 H \\\\nATOM 2161 HE2 HIS A 212 -31.939 41.840 42.517 1.00 0.00 H \\\\nATOM 2162 N VAL A 213 -26.172 38.392 42.154 1.00 0.00 N \\\\nATOM 2163 CA VAL A 213 -25.613 37.098 41.786 1.00 0.00 C \\\\nATOM 2164 C VAL A 213 -26.755 36.277 41.204 1.00 0.00 C \\\\nATOM 2165 O VAL A 213 -27.780 36.075 41.865 1.00 0.00 O \\\\nATOM 2166 CB VAL A 213 -24.970 36.389 42.987 1.00 0.00 C \\\\nATOM 2167 CG1 VAL A 213 -24.634 34.947 42.636 1.00 0.00 C \\\\nATOM 2168 CG2 VAL A 213 -23.724 37.137 43.445 1.00 0.00 C \\\\nATOM 2169 H VAL A 213 -26.758 38.344 42.782 1.00 0.00 H \\\\nATOM 2170 HA VAL A 213 -24.901 37.210 41.137 1.00 0.00 H \\\\nATOM 2171 HB VAL A 213 -25.607 36.384 43.719 1.00 0.00 H \\\\nATOM 2172 HG11 VAL A 213 -24.229 34.513 43.403 1.00 0.00 H \\\\nATOM 2173 HG12 VAL A 213 -25.445 34.476 42.390 1.00 0.00 H \\\\nATOM 2174 HG13 VAL A 213 -24.013 34.931 41.891 1.00 0.00 H \\\\nATOM 2175 HG21 VAL A 213 -23.331 36.677 44.203 1.00 0.00 H \\\\nATOM 2176 HG22 VAL A 213 -23.082 37.171 42.719 1.00 0.00 H \\\\nATOM 2177 HG23 VAL A 213 -23.966 38.040 43.705 1.00 0.00 H \\\\nATOM 2178 N VAL A 214 -26.595 35.819 39.967 1.00 0.00 N \\\\nATOM 2179 CA VAL A 214 -27.602 35.002 39.298 1.00 0.00 C \\\\nATOM 2180 C VAL A 214 -27.034 33.602 39.118 1.00 0.00 C \\\\nATOM 2181 O VAL A 214 -25.970 33.426 38.511 1.00 0.00 O \\\\nATOM 2182 CB VAL A 214 -28.028 35.609 37.954 1.00 0.00 C \\\\nATOM 2183 CG1 VAL A 214 -29.225 34.859 37.398 1.00 0.00 C \\\\nATOM 2184 CG2 VAL A 214 -28.358 37.086 38.125 1.00 0.00 C \\\\nATOM 2185 H VAL A 214 -25.896 35.974 39.490 1.00 0.00 H \\\\nATOM 2186 HA VAL A 214 -28.403 34.966 39.844 1.00 0.00 H \\\\nATOM 2187 HB VAL A 214 -27.293 35.528 37.326 1.00 0.00 H \\\\nATOM 2188 HG11 VAL A 214 -29.486 35.250 36.550 1.00 0.00 H \\\\nATOM 2189 HG12 VAL A 214 -28.990 33.927 37.266 1.00 0.00 H \\\\nATOM 2190 HG13 VAL A 214 -29.964 34.920 38.023 1.00 0.00 H \\\\nATOM 2191 HG21 VAL A 214 -28.626 37.459 37.271 1.00 0.00 H \\\\nATOM 2192 HG22 VAL A 214 -29.083 37.184 38.762 1.00 0.00 H \\\\nATOM 2193 HG23 VAL A 214 -27.576 37.557 38.452 1.00 0.00 H \\\\nATOM 2194 N VAL A 215 -27.745 32.610 39.645 1.00 0.00 N \\\\nATOM 2195 CA VAL A 215 -27.305 31.220 39.646 1.00 0.00 C \\\\nATOM 2196 C VAL A 215 -28.242 30.415 38.760 1.00 0.00 C \\\\nATOM 2197 O VAL A 215 -29.466 30.553 38.853 1.00 0.00 O \\\\nATOM 2198 CB VAL A 215 -27.279 30.642 41.072 1.00 0.00 C \\\\nATOM 2199 CG1 VAL A 215 -27.264 29.117 41.038 1.00 0.00 C \\\\nATOM 2200 CG2 VAL A 215 -26.086 31.181 41.839 1.00 0.00 C \\\\nATOM 2201 H VAL A 215 -28.510 32.729 40.019 1.00 0.00 H \\\\nATOM 2202 HA VAL A 215 -26.400 31.172 39.301 1.00 0.00 H \\\\nATOM 2203 HB VAL A 215 -28.087 30.921 41.532 1.00 0.00 H \\\\nATOM 2204 HG11 VAL A 215 -27.248 28.773 41.945 1.00 0.00 H \\\\nATOM 2205 HG12 VAL A 215 -28.059 28.795 40.585 1.00 0.00 H \\\\nATOM 2206 HG13 VAL A 215 -26.476 28.811 40.563 1.00 0.00 H \\\\nATOM 2207 HG21 VAL A 215 -26.082 30.809 42.735 1.00 0.00 H \\\\nATOM 2208 HG22 VAL A 215 -25.268 30.931 41.382 1.00 0.00 H \\\\nATOM 2209 HG23 VAL A 215 -26.145 32.148 41.891 1.00 0.00 H \\\\nATOM 2210 N ALA A 216 -27.667 29.584 37.896 1.00 0.00 N \\\\nATOM 2211 CA ALA A 216 -28.420 28.619 37.104 1.00 0.00 C \\\\nATOM 2212 C ALA A 216 -27.809 27.249 37.344 1.00 0.00 C \\\\nATOM 2213 O ALA A 216 -26.616 27.050 37.098 1.00 0.00 O \\\\nATOM 2214 CB ALA A 216 -28.397 28.970 35.615 1.00 0.00 C \\\\nATOM 2215 H ALA A 216 -26.819 29.565 37.752 1.00 0.00 H \\\\nATOM 2216 HA ALA A 216 -29.351 28.629 37.375 1.00 0.00 H \\\\nATOM 2217 HB1 ALA A 216 -28.906 28.310 35.119 1.00 0.00 H \\\\nATOM 2218 HB2 ALA A 216 -28.790 29.847 35.483 1.00 0.00 H \\\\nATOM 2219 HB3 ALA A 216 -27.480 28.976 35.298 1.00 0.00 H \\\\nATOM 2220 N ASN A 217 -28.617 26.310 37.823 1.00 0.00 N \\\\nATOM 2221 CA ASN A 217 -28.132 24.995 38.213 1.00 0.00 C \\\\nATOM 2222 C ASN A 217 -28.774 23.908 37.367 1.00 0.00 C \\\\nATOM 2223 O ASN A 217 -29.983 23.932 37.116 1.00 0.00 O \\\\nATOM 2224 CB ASN A 217 -28.410 24.715 39.690 1.00 0.00 C \\\\nATOM 2225 CG ASN A 217 -27.800 23.409 40.153 1.00 0.00 C \\\\nATOM 2226 OD1 ASN A 217 -26.623 23.139 39.909 1.00 0.00 O \\\\nATOM 2227 ND2 ASN A 217 -28.600 22.583 40.815 1.00 0.00 N \\\\nATOM 2228 H ASN A 217 -29.463 26.419 37.931 1.00 0.00 H \\\\nATOM 2229 HA ASN A 217 -27.173 24.989 38.068 1.00 0.00 H \\\\nATOM 2230 HB2 ASN A 217 -28.058 25.442 40.227 1.00 0.00 H \\\\nATOM 2231 HB3 ASN A 217 -29.368 24.692 39.838 1.00 0.00 H \\\\nATOM 2232 HD21 ASN A 217 -28.302 21.825 41.092 1.00 0.00 H \\\\nATOM 2233 HD22 ASN A 217 -29.417 22.805 40.967 1.00 0.00 H \\\\nATOM 2234 N CYS A 218 -27.949 22.952 36.937 1.00 0.00 N \\\\nATOM 2235 CA CYS A 218 -28.397 21.795 36.159 1.00 0.00 C \\\\nATOM 2236 C CYS A 218 -27.556 20.602 36.615 1.00 0.00 C \\\\nATOM 2237 O CYS A 218 -26.467 20.359 36.087 1.00 0.00 O \\\\nATOM 2238 CB CYS A 218 -28.266 22.050 34.662 1.00 0.00 C \\\\nATOM 2239 SG CYS A 218 -28.967 20.760 33.614 1.00 0.00 S \\\\nATOM 2240 H CYS A 218 -27.103 22.957 37.091 1.00 0.00 H \\\\nATOM 2241 HA CYS A 218 -29.338 21.618 36.312 1.00 0.00 H \\\\nATOM 2242 HB2 CYS A 218 -28.699 22.892 34.451 1.00 0.00 H \\\\nATOM 2243 HB3 CYS A 218 -27.326 22.151 34.444 1.00 0.00 H \\\\nATOM 2244 HG CYS A 218 -29.736 21.251 32.835 1.00 0.00 H \\\\nATOM 2245 N GLY A 219 -28.066 19.866 37.601 1.00 0.00 N \\\\nATOM 2246 CA GLY A 219 -27.382 18.683 38.088 1.00 0.00 C \\\\nATOM 2247 C GLY A 219 -27.091 18.694 39.575 1.00 0.00 C \\\\nATOM 2248 O GLY A 219 -27.698 19.461 40.330 1.00 0.00 O \\\\nATOM 2249 H GLY A 219 -28.809 20.039 37.999 1.00 0.00 H \\\\nATOM 2250 HA2 GLY A 219 -27.921 17.903 37.881 1.00 0.00 H \\\\nATOM 2251 HA3 GLY A 219 -26.545 18.586 37.607 1.00 0.00 H \\\\nATOM 2252 N ASP A 220 -26.156 17.848 40.008 1.00 0.00 N \\\\nATOM 2253 CA ASP A 220 -25.857 17.677 41.422 1.00 0.00 C \\\\nATOM 2254 C ASP A 220 -24.584 18.395 41.852 1.00 0.00 C \\\\nATOM 2255 O ASP A 220 -24.058 18.110 42.933 1.00 0.00 O \\\\nATOM 2256 CB ASP A 220 -25.777 16.187 41.770 1.00 0.00 C \\\\nATOM 2257 CG ASP A 220 -24.513 15.522 41.255 1.00 0.00 C \\\\nATOM 2258 OD1 ASP A 220 -23.891 16.044 40.305 1.00 0.00 O \\\\nATOM 2259 OD2 ASP A 220 -24.146 14.460 41.801 1.00 0.00 O \\\\nATOM 2260 H ASP A 220 -25.679 17.358 39.486 1.00 0.00 H \\\\nATOM 2261 HA ASP A 220 -26.585 18.086 41.915 1.00 0.00 H \\\\nATOM 2262 HB2 ASP A 220 -25.821 16.083 42.733 1.00 0.00 H \\\\nATOM 2263 HB3 ASP A 220 -26.549 15.732 41.399 1.00 0.00 H \\\\nATOM 2264 N SER A 221 -24.073 19.311 41.034 1.00 0.00 N \\\\nATOM 2265 CA SER A 221 -23.101 20.264 41.538 1.00 0.00 C \\\\nATOM 2266 C SER A 221 -23.828 21.338 42.343 1.00 0.00 C \\\\nATOM 2267 O SER A 221 -25.053 21.476 42.279 1.00 0.00 O \\\\nATOM 2268 CB SER A 221 -22.302 20.879 40.389 1.00 0.00 C \\\\nATOM 2269 OG SER A 221 -21.377 19.950 39.850 1.00 0.00 O \\\\nATOM 2270 H SER A 221 -24.273 19.394 40.202 1.00 0.00 H \\\\nATOM 2271 HA SER A 221 -22.470 19.809 42.117 1.00 0.00 H \\\\nATOM 2272 HB2 SER A 221 -22.909 21.176 39.693 1.00 0.00 H \\\\nATOM 2273 HB3 SER A 221 -21.828 21.664 40.706 1.00 0.00 H \\\\nATOM 2274 HG SER A 221 -21.727 19.187 39.826 1.00 0.00 H \\\\nATOM 2275 N ARG A 222 -23.067 22.115 43.110 1.00 0.00 N \\\\nATOM 2276 CA ARG A 222 -23.703 23.027 44.047 1.00 0.00 C \\\\nATOM 2277 C ARG A 222 -22.897 24.309 44.180 1.00 0.00 C \\\\nATOM 2278 O ARG A 222 -21.664 24.299 44.112 1.00 0.00 O \\\\nATOM 2279 CB ARG A 222 -23.880 22.366 45.421 1.00 0.00 C \\\\nATOM 2280 CG ARG A 222 -24.827 23.102 46.351 1.00 0.00 C \\\\nATOM 2281 CD ARG A 222 -24.870 22.461 47.728 1.00 0.00 C \\\\nATOM 2282 NE ARG A 222 -25.287 21.063 47.672 1.00 0.00 N \\\\nATOM 2283 CZ ARG A 222 -24.963 20.150 48.582 1.00 0.00 C \\\\nATOM 2284 NH1 ARG A 222 -24.216 20.486 49.625 1.00 0.00 N \\\\nATOM 2285 NH2 ARG A 222 -25.384 18.899 48.450 1.00 0.00 N \\\\nATOM 2286 H ARG A 222 -22.207 22.129 43.103 1.00 0.00 H \\\\nATOM 2287 HA ARG A 222 -24.581 23.248 43.699 1.00 0.00 H \\\\nATOM 2288 HB2 ARG A 222 -24.207 21.462 45.293 1.00 0.00 H \\\\nATOM 2289 HB3 ARG A 222 -23.012 22.296 45.849 1.00 0.00 H \\\\nATOM 2290 HG2 ARG A 222 -24.547 24.027 46.433 1.00 0.00 H \\\\nATOM 2291 HG3 ARG A 222 -25.718 23.108 45.968 1.00 0.00 H \\\\nATOM 2292 HD2 ARG A 222 -23.993 22.519 48.138 1.00 0.00 H \\\\nATOM 2293 HD3 ARG A 222 -25.481 22.957 48.295 1.00 0.00 H \\\\nATOM 2294 HE ARG A 222 -25.773 20.814 47.008 1.00 0.00 H \\\\nATOM 2295 HH11 ARG A 222 -23.940 21.296 49.713 1.00 0.00 H \\\\nATOM 2296 HH12 ARG A 222 -24.007 19.894 50.213 1.00 0.00 H \\\\nATOM 2297 HH21 ARG A 222 -25.868 18.677 47.774 1.00 0.00 H \\\\nATOM 2298 HH22 ARG A 222 -25.173 18.310 49.040 1.00 0.00 H \\\\nATOM 2299 N ILE A 223 -23.615 25.413 44.372 1.00 0.00 N \\\\nATOM 2300 CA ILE A 223 -23.031 26.709 44.695 1.00 0.00 C \\\\nATOM 2301 C ILE A 223 -23.632 27.172 46.015 1.00 0.00 C \\\\nATOM 2302 O ILE A 223 -24.846 27.060 46.222 1.00 0.00 O \\\\nATOM 2303 CB ILE A 223 -23.276 27.746 43.583 1.00 0.00 C \\\\nATOM 2304 CG1 ILE A 223 -22.849 29.138 44.047 1.00 0.00 C \\\\nATOM 2305 CG2 ILE A 223 -24.738 27.753 43.178 1.00 0.00 C \\\\nATOM 2306 CD1 ILE A 223 -22.780 30.157 42.941 1.00 0.00 C \\\\nATOM 2307 H ILE A 223 -24.473 25.428 44.317 1.00 0.00 H \\\\nATOM 2308 HA ILE A 223 -22.068 26.620 44.772 1.00 0.00 H \\\\nATOM 2309 HB ILE A 223 -22.742 27.500 42.812 1.00 0.00 H \\\\nATOM 2310 HG12 ILE A 223 -23.472 29.449 44.723 1.00 0.00 H \\\\nATOM 2311 HG13 ILE A 223 -21.979 29.075 44.471 1.00 0.00 H \\\\nATOM 2312 HG21 ILE A 223 -24.877 28.410 42.478 1.00 0.00 H \\\\nATOM 2313 HG22 ILE A 223 -24.988 26.875 42.851 1.00 0.00 H \\\\nATOM 2314 HG23 ILE A 223 -25.286 27.979 43.946 1.00 0.00 H \\\\nATOM 2315 HD11 ILE A 223 -22.504 31.012 43.306 1.00 0.00 H \\\\nATOM 2316 HD12 ILE A 223 -22.138 29.868 42.274 1.00 0.00 H \\\\nATOM 2317 HD13 ILE A 223 -23.654 30.248 42.530 1.00 0.00 H \\\\nATOM 2318 N VAL A 224 -22.785 27.670 46.913 1.00 0.00 N \\\\nATOM 2319 CA VAL A 224 -23.204 28.089 48.246 1.00 0.00 C \\\\nATOM 2320 C VAL A 224 -22.660 29.486 48.511 1.00 0.00 C \\\\nATOM 2321 O VAL A 224 -21.486 29.761 48.239 1.00 0.00 O \\\\nATOM 2322 CB VAL A 224 -22.722 27.105 49.331 1.00 0.00 C \\\\nATOM 2323 CG1 VAL A 224 -23.013 27.654 50.716 1.00 0.00 C \\\\nATOM 2324 CG2 VAL A 224 -23.380 25.744 49.147 1.00 0.00 C \\\\nATOM 2325 H VAL A 224 -21.945 27.775 46.763 1.00 0.00 H \\\\nATOM 2326 HA VAL A 224 -24.173 28.097 48.283 1.00 0.00 H \\\\nATOM 2327 HB VAL A 224 -21.762 26.996 49.241 1.00 0.00 H \\\\nATOM 2328 HG11 VAL A 224 -22.704 27.024 51.386 1.00 0.00 H \\\\nATOM 2329 HG12 VAL A 224 -22.553 28.500 50.832 1.00 0.00 H \\\\nATOM 2330 HG13 VAL A 224 -23.968 27.789 50.816 1.00 0.00 H \\\\nATOM 2331 HG21 VAL A 224 -23.067 25.137 49.836 1.00 0.00 H \\\\nATOM 2332 HG22 VAL A 224 -24.343 25.838 49.213 1.00 0.00 H \\\\nATOM 2333 HG23 VAL A 224 -23.150 25.388 48.275 1.00 0.00 H \\\\nATOM 2334 N LEU A 225 -23.510 30.365 49.035 1.00 0.00 N \\\\nATOM 2335 CA LEU A 225 -23.116 31.717 49.405 1.00 0.00 C \\\\nATOM 2336 C LEU A 225 -22.923 31.820 50.913 1.00 0.00 C \\\\nATOM 2337 O LEU A 225 -23.692 31.247 51.690 1.00 0.00 O \\\\nATOM 2338 CB LEU A 225 -24.162 32.736 48.945 1.00 0.00 C \\\\nATOM 2339 CG LEU A 225 -24.105 34.118 49.602 1.00 0.00 C \\\\nATOM 2340 CD1 LEU A 225 -22.869 34.879 49.144 1.00 0.00 C \\\\nATOM 2341 CD2 LEU A 225 -25.369 34.922 49.324 1.00 0.00 C \\\\nATOM 2342 H LEU A 225 -24.338 30.190 49.186 1.00 0.00 H \\\\nATOM 2343 HA LEU A 225 -22.276 31.916 48.963 1.00 0.00 H \\\\nATOM 2344 HB2 LEU A 225 -24.072 32.852 47.986 1.00 0.00 H \\\\nATOM 2345 HB3 LEU A 225 -25.042 32.360 49.104 1.00 0.00 H \\\\nATOM 2346 HG LEU A 225 -24.047 33.986 50.561 1.00 0.00 H \\\\nATOM 2347 HD11 LEU A 225 -22.849 35.751 49.569 1.00 0.00 H \\\\nATOM 2348 HD12 LEU A 225 -22.073 34.382 49.390 1.00 0.00 H \\\\nATOM 2349 HD13 LEU A 225 -22.896 34.990 48.181 1.00 0.00 H \\\\nATOM 2350 HD21 LEU A 225 -25.302 35.790 49.753 1.00 0.00 H \\\\nATOM 2351 HD22 LEU A 225 -25.473 35.042 48.367 1.00 0.00 H \\\\nATOM 2352 HD23 LEU A 225 -26.139 34.447 49.675 1.00 0.00 H \\\\nATOM 2353 N CYS A 226 -21.883 32.546 51.319 1.00 0.00 N \\\\nATOM 2354 CA CYS A 226 -21.620 32.842 52.723 1.00 0.00 C \\\\nATOM 2355 C CYS A 226 -22.058 34.278 52.997 1.00 0.00 C \\\\nATOM 2356 O CYS A 226 -21.425 35.227 52.523 1.00 0.00 O \\\\nATOM 2357 CB CYS A 226 -20.142 32.641 53.053 1.00 0.00 C \\\\nATOM 2358 SG CYS A 226 -19.747 32.761 54.810 1.00 0.00 S \\\\nATOM 2359 H CYS A 226 -21.305 32.884 50.780 1.00 0.00 H \\\\nATOM 2360 HA CYS A 226 -22.121 32.235 53.290 1.00 0.00 H \\\\nATOM 2361 HB2 CYS A 226 -19.865 31.769 52.729 1.00 0.00 H \\\\nATOM 2362 HB3 CYS A 226 -19.621 33.302 52.570 1.00 0.00 H \\\\nATOM 2363 HG CYS A 226 -20.286 33.726 55.277 1.00 0.00 H \\\\nATOM 2364 N ARG A 227 -23.143 34.436 53.752 1.00 0.00 N \\\\nATOM 2365 CA ARG A 227 -23.642 35.765 54.101 1.00 0.00 C \\\\nATOM 2366 C ARG A 227 -24.394 35.662 55.420 1.00 0.00 C \\\\nATOM 2367 O ARG A 227 -25.462 35.040 55.480 1.00 0.00 O \\\\nATOM 2368 CB ARG A 227 -24.542 36.322 53.000 1.00 0.00 C \\\\nATOM 2369 CG ARG A 227 -25.556 37.350 53.485 1.00 0.00 C \\\\nATOM 2370 CD ARG A 227 -26.831 37.310 52.658 1.00 0.00 C \\\\nATOM 2371 NE ARG A 227 -26.656 37.943 51.354 1.00 0.00 N \\\\nATOM 2372 CZ ARG A 227 -27.600 38.002 50.421 1.00 0.00 C \\\\nATOM 2373 NH1 ARG A 227 -28.792 37.464 50.644 1.00 0.00 N \\\\nATOM 2374 NH2 ARG A 227 -27.352 38.600 49.264 1.00 0.00 N \\\\nATOM 2375 H ARG A 227 -23.605 33.786 54.073 1.00 0.00 H \\\\nATOM 2376 HA ARG A 227 -22.897 36.379 54.194 1.00 0.00 H \\\\nATOM 2377 HB2 ARG A 227 -23.987 36.728 52.316 1.00 0.00 H \\\\nATOM 2378 HB3 ARG A 227 -25.016 35.587 52.581 1.00 0.00 H \\\\nATOM 2379 HG2 ARG A 227 -25.768 37.182 54.417 1.00 0.00 H \\\\nATOM 2380 HG3 ARG A 227 -25.167 38.237 53.438 1.00 0.00 H \\\\nATOM 2381 HD2 ARG A 227 -27.107 36.388 52.535 1.00 0.00 H \\\\nATOM 2382 HD3 ARG A 227 -27.543 37.757 53.141 1.00 0.00 H \\\\nATOM 2383 HE ARG A 227 -25.894 38.300 51.179 1.00 0.00 H \\\\nATOM 2384 HH11 ARG A 227 -28.955 37.076 51.394 1.00 0.00 H \\\\nATOM 2385 HH12 ARG A 227 -29.402 37.503 50.039 1.00 0.00 H \\\\nATOM 2386 HH21 ARG A 227 -26.580 38.950 49.117 1.00 0.00 H \\\\nATOM 2387 HH22 ARG A 227 -27.963 38.638 48.660 1.00 0.00 H \\\\nATOM 2388 N GLY A 228 -23.825 36.232 56.479 1.00 0.00 N \\\\nATOM 2389 CA GLY A 228 -22.472 36.754 56.470 1.00 0.00 C \\\\nATOM 2390 C GLY A 228 -21.657 35.652 57.105 1.00 0.00 C \\\\nATOM 2391 O GLY A 228 -20.462 35.475 56.838 1.00 0.00 O \\\\nATOM 2392 H GLY A 228 -24.226 36.326 57.234 1.00 0.00 H \\\\nATOM 2393 HA2 GLY A 228 -22.170 36.946 55.568 1.00 0.00 H \\\\nATOM 2394 HA3 GLY A 228 -22.406 37.581 56.973 1.00 0.00 H \\\\nATOM 2395 N LYS A 229 -22.332 34.905 57.978 1.00 0.00 N \\\\nATOM 2396 CA LYS A 229 -21.846 33.642 58.510 1.00 0.00 C \\\\nATOM 2397 C LYS A 229 -22.787 32.498 58.164 1.00 0.00 C \\\\nATOM 2398 O LYS A 229 -22.397 31.336 58.291 1.00 0.00 O \\\\nATOM 2399 CB LYS A 229 -21.684 33.750 60.043 1.00 0.00 C \\\\nATOM 2400 CG LYS A 229 -21.751 32.481 60.940 1.00 0.00 C \\\\nATOM 2401 CD LYS A 229 -20.838 31.319 60.596 1.00 0.00 C \\\\nATOM 2402 CE LYS A 229 -21.016 30.245 61.658 1.00 0.00 C \\\\nATOM 2403 NZ LYS A 229 -22.108 29.315 61.248 1.00 0.00 N \\\\nATOM 2404 H LYS A 229 -23.105 35.128 58.282 1.00 0.00 H \\\\nATOM 2405 HA LYS A 229 -20.985 33.453 58.105 1.00 0.00 H \\\\nATOM 2406 HB2 LYS A 229 -20.827 34.173 60.210 1.00 0.00 H \\\\nATOM 2407 HB3 LYS A 229 -22.368 34.360 60.360 1.00 0.00 H \\\\nATOM 2408 HG2 LYS A 229 -21.559 32.751 61.852 1.00 0.00 H \\\\nATOM 2409 HG3 LYS A 229 -22.665 32.155 60.927 1.00 0.00 H \\\\nATOM 2410 HD2 LYS A 229 -21.055 30.967 59.719 1.00 0.00 H \\\\nATOM 2411 HD3 LYS A 229 -19.914 31.613 60.563 1.00 0.00 H \\\\nATOM 2412 HE2 LYS A 229 -20.188 29.754 61.777 1.00 0.00 H \\\\nATOM 2413 HE3 LYS A 229 -21.229 30.653 62.512 1.00 0.00 H \\\\nATOM 2414 HZ1 LYS A 229 -22.607 29.113 61.956 1.00 0.00 H \\\\nATOM 2415 HZ2 LYS A 229 -22.615 29.706 60.630 1.00 0.00 H \\\\nATOM 2416 HZ3 LYS A 229 -21.754 28.570 60.913 1.00 0.00 H \\\\nATOM 2417 N GLU A 230 -23.941 32.775 57.597 1.00 0.00 N \\\\nATOM 2418 CA GLU A 230 -24.662 31.584 57.193 1.00 0.00 C \\\\nATOM 2419 C GLU A 230 -24.117 31.056 55.875 1.00 0.00 C \\\\nATOM 2420 O GLU A 230 -23.633 31.822 55.036 1.00 0.00 O \\\\nATOM 2421 CB GLU A 230 -26.151 31.872 56.995 1.00 0.00 C \\\\nATOM 2422 CG GLU A 230 -26.927 32.379 58.183 1.00 0.00 C \\\\nATOM 2423 CD GLU A 230 -27.327 33.828 58.011 1.00 0.00 C \\\\nATOM 2424 OE1 GLU A 230 -27.952 34.150 56.976 1.00 0.00 O \\\\nATOM 2425 OE2 GLU A 230 -27.034 34.643 58.910 1.00 0.00 O \\\\nATOM 2426 H GLU A 230 -24.296 33.544 57.448 1.00 0.00 H \\\\nATOM 2427 HA GLU A 230 -24.546 30.931 57.900 1.00 0.00 H \\\\nATOM 2428 HB2 GLU A 230 -26.237 32.523 56.281 1.00 0.00 H \\\\nATOM 2429 HB3 GLU A 230 -26.575 31.056 56.687 1.00 0.00 H \\\\nATOM 2430 HG2 GLU A 230 -27.721 31.836 58.307 1.00 0.00 H \\\\nATOM 2431 HG3 GLU A 230 -26.390 32.284 58.985 1.00 0.00 H \\\\nATOM 2432 N PRO A 231 -24.150 29.746 55.693 1.00 0.00 N \\\\nATOM 2433 CA PRO A 231 -24.244 29.212 54.343 1.00 0.00 C \\\\nATOM 2434 C PRO A 231 -25.696 29.357 53.934 1.00 0.00 C \\\\nATOM 2435 O PRO A 231 -26.608 29.191 54.748 1.00 0.00 O \\\\nATOM 2436 CB PRO A 231 -23.836 27.746 54.510 1.00 0.00 C \\\\nATOM 2437 CG PRO A 231 -24.172 27.434 55.940 1.00 0.00 C \\\\nATOM 2438 CD PRO A 231 -23.953 28.699 56.710 1.00 0.00 C \\\\nATOM 2439 HA PRO A 231 -23.695 29.645 53.671 1.00 0.00 H \\\\nATOM 2440 HB2 PRO A 231 -24.321 27.171 53.898 1.00 0.00 H \\\\nATOM 2441 HB3 PRO A 231 -22.891 27.618 54.331 1.00 0.00 H \\\\nATOM 2442 HG2 PRO A 231 -25.091 27.134 56.022 1.00 0.00 H \\\\nATOM 2443 HG3 PRO A 231 -23.609 26.721 56.280 1.00 0.00 H \\\\nATOM 2444 HD2 PRO A 231 -24.583 28.787 57.442 1.00 0.00 H \\\\nATOM 2445 HD3 PRO A 231 -23.063 28.735 57.095 1.00 0.00 H \\\\nATOM 2446 N VAL A 232 -25.915 29.689 52.671 1.00 0.00 N \\\\nATOM 2447 CA VAL A 232 -27.255 29.673 52.108 1.00 0.00 C \\\\nATOM 2448 C VAL A 232 -27.138 29.078 50.718 1.00 0.00 C \\\\nATOM 2449 O VAL A 232 -26.392 29.595 49.877 1.00 0.00 O \\\\nATOM 2450 CB VAL A 232 -27.900 31.072 52.074 1.00 0.00 C \\\\nATOM 2451 CG1 VAL A 232 -26.934 32.114 51.522 1.00 0.00 C \\\\nATOM 2452 CG2 VAL A 232 -29.196 31.045 51.277 1.00 0.00 C \\\\nATOM 2453 H VAL A 232 -25.299 29.928 52.121 1.00 0.00 H \\\\nATOM 2454 HA VAL A 232 -27.843 29.140 52.666 1.00 0.00 H \\\\nATOM 2455 HB VAL A 232 -28.112 31.327 52.986 1.00 0.00 H \\\\nATOM 2456 HG11 VAL A 232 -27.366 32.983 51.512 1.00 0.00 H \\\\nATOM 2457 HG12 VAL A 232 -26.144 32.152 52.083 1.00 0.00 H \\\\nATOM 2458 HG13 VAL A 232 -26.677 31.871 50.619 1.00 0.00 H \\\\nATOM 2459 HG21 VAL A 232 -29.588 31.932 51.266 1.00 0.00 H \\\\nATOM 2460 HG22 VAL A 232 -29.011 30.762 50.368 1.00 0.00 H \\\\nATOM 2461 HG23 VAL A 232 -29.816 30.423 51.689 1.00 0.00 H \\\\nATOM 2462 N ALA A 233 -27.849 27.983 50.481 1.00 0.00 N \\\\nATOM 2463 CA ALA A 233 -27.722 27.274 49.219 1.00 0.00 C \\\\nATOM 2464 C ALA A 233 -28.419 28.062 48.122 1.00 0.00 C \\\\nATOM 2465 O ALA A 233 -29.609 28.378 48.232 1.00 0.00 O \\\\nATOM 2466 CB ALA A 233 -28.313 25.873 49.338 1.00 0.00 C \\\\nATOM 2467 H ALA A 233 -28.408 27.637 51.036 1.00 0.00 H \\\\nATOM 2468 HA ALA A 233 -26.783 27.186 48.993 1.00 0.00 H \\\\nATOM 2469 HB1 ALA A 233 -28.222 25.410 48.490 1.00 0.00 H \\\\nATOM 2470 HB2 ALA A 233 -27.841 25.380 50.027 1.00 0.00 H \\\\nATOM 2471 HB3 ALA A 233 -29.252 25.937 49.572 1.00 0.00 H \\\\nATOM 2472 N LEU A 234 -27.677 28.383 47.070 1.00 0.00 N \\\\nATOM 2473 CA LEU A 234 -28.240 29.053 45.910 1.00 0.00 C \\\\nATOM 2474 C LEU A 234 -28.676 28.070 44.836 1.00 0.00 C \\\\nATOM 2475 O LEU A 234 -29.106 28.494 43.759 1.00 0.00 O \\\\nATOM 2476 CB LEU A 234 -27.230 30.048 45.327 1.00 0.00 C \\\\nATOM 2477 CG LEU A 234 -26.587 31.069 46.277 1.00 0.00 C \\\\nATOM 2478 CD1 LEU A 234 -25.986 32.224 45.484 1.00 0.00 C \\\\nATOM 2479 CD2 LEU A 234 -27.568 31.590 47.324 1.00 0.00 C \\\\nATOM 2480 H LEU A 234 -26.835 28.218 47.010 1.00 0.00 H \\\\nATOM 2481 HA LEU A 234 -29.030 29.530 46.210 1.00 0.00 H \\\\nATOM 2482 HB2 LEU A 234 -26.516 29.538 44.913 1.00 0.00 H \\\\nATOM 2483 HB3 LEU A 234 -27.674 30.540 44.619 1.00 0.00 H \\\\nATOM 2484 HG LEU A 234 -25.880 30.609 46.757 1.00 0.00 H \\\\nATOM 2485 HD11 LEU A 234 -25.584 32.861 46.095 1.00 0.00 H \\\\nATOM 2486 HD12 LEU A 234 -25.308 31.884 44.879 1.00 0.00 H \\\\nATOM 2487 HD13 LEU A 234 -26.683 32.663 44.973 1.00 0.00 H \\\\nATOM 2488 HD21 LEU A 234 -27.119 32.229 47.899 1.00 0.00 H \\\\nATOM 2489 HD22 LEU A 234 -28.315 32.023 46.881 1.00 0.00 H \\\\nATOM 2490 HD23 LEU A 234 -27.895 30.849 47.858 1.00 0.00 H \\\\nATOM 2491 N SER A 235 -28.574 26.772 45.110 1.00 0.00 N \\\\nATOM 2492 CA SER A 235 -28.983 25.737 44.176 1.00 0.00 C \\\\nATOM 2493 C SER A 235 -29.365 24.492 44.962 1.00 0.00 C \\\\nATOM 2494 O SER A 235 -28.791 24.204 46.015 1.00 0.00 O \\\\nATOM 2495 CB SER A 235 -27.873 25.412 43.171 1.00 0.00 C \\\\nATOM 2496 OG SER A 235 -26.743 24.859 43.823 1.00 0.00 O \\\\nATOM 2497 H SER A 235 -28.262 26.468 45.852 1.00 0.00 H \\\\nATOM 2498 HA SER A 235 -29.744 26.058 43.668 1.00 0.00 H \\\\nATOM 2499 HB2 SER A 235 -28.206 24.787 42.508 1.00 0.00 H \\\\nATOM 2500 HB3 SER A 235 -27.615 26.218 42.697 1.00 0.00 H \\\\nATOM 2501 HG SER A 235 -26.957 24.618 44.599 1.00 0.00 H \\\\nATOM 2502 N ILE A 236 -30.341 23.757 44.438 1.00 0.00 N \\\\nATOM 2503 CA ILE A 236 -30.789 22.498 45.020 1.00 0.00 C \\\\nATOM 2504 C ILE A 236 -30.375 21.373 44.084 1.00 0.00 C \\\\nATOM 2505 O ILE A 236 -30.566 21.472 42.866 1.00 0.00 O \\\\nATOM 2506 CB ILE A 236 -32.310 22.490 45.251 1.00 0.00 C \\\\nATOM 2507 CG1 ILE A 236 -32.739 23.725 46.047 1.00 0.00 C \\\\nATOM 2508 CG2 ILE A 236 -32.735 21.218 45.974 1.00 0.00 C \\\\nATOM 2509 CD1 ILE A 236 -34.176 24.136 45.800 1.00 0.00 C \\\\nATOM 2510 H ILE A 236 -30.767 23.979 43.725 1.00 0.00 H \\\\nATOM 2511 HA ILE A 236 -30.377 22.378 45.890 1.00 0.00 H \\\\nATOM 2512 HB ILE A 236 -32.750 22.513 44.387 1.00 0.00 H \\\\nATOM 2513 HG12 ILE A 236 -32.619 23.548 46.993 1.00 0.00 H \\\\nATOM 2514 HG13 ILE A 236 -32.155 24.466 45.820 1.00 0.00 H \\\\nATOM 2515 HG21 ILE A 236 -33.695 21.229 46.111 1.00 0.00 H \\\\nATOM 2516 HG22 ILE A 236 -32.494 20.446 45.439 1.00 0.00 H \\\\nATOM 2517 HG23 ILE A 236 -32.286 21.168 46.833 1.00 0.00 H \\\\nATOM 2518 HD11 ILE A 236 -34.384 24.921 46.331 1.00 0.00 H \\\\nATOM 2519 HD12 ILE A 236 -34.297 24.341 44.860 1.00 0.00 H \\\\nATOM 2520 HD13 ILE A 236 -34.768 23.410 46.051 1.00 0.00 H \\\\nATOM 2521 N ASP A 237 -29.797 20.314 44.648 1.00 0.00 N \\\\nATOM 2522 CA ASP A 237 -29.298 19.221 43.828 1.00 0.00 C \\\\nATOM 2523 C ASP A 237 -30.450 18.556 43.089 1.00 0.00 C \\\\nATOM 2524 O ASP A 237 -31.514 18.303 43.658 1.00 0.00 O \\\\nATOM 2525 CB ASP A 237 -28.562 18.194 44.690 1.00 0.00 C \\\\nATOM 2526 CG ASP A 237 -27.432 18.808 45.493 1.00 0.00 C \\\\nATOM 2527 OD1 ASP A 237 -27.259 20.044 45.429 1.00 0.00 O \\\\nATOM 2528 OD2 ASP A 237 -26.711 18.055 46.182 1.00 0.00 O \\\\nATOM 2529 H ASP A 237 -29.686 20.212 45.495 1.00 0.00 H \\\\nATOM 2530 HA ASP A 237 -28.673 19.582 43.180 1.00 0.00 H \\\\nATOM 2531 HB2 ASP A 237 -29.193 17.774 45.295 1.00 0.00 H \\\\nATOM 2532 HB3 ASP A 237 -28.206 17.494 44.120 1.00 0.00 H \\\\nATOM 2533 N HIS A 238 -30.230 18.275 41.807 1.00 0.00 N \\\\nATOM 2534 CA HIS A 238 -31.236 17.611 40.981 1.00 0.00 C \\\\nATOM 2535 C HIS A 238 -31.041 16.097 41.077 1.00 0.00 C \\\\nATOM 2536 O HIS A 238 -30.603 15.422 40.145 1.00 0.00 O \\\\nATOM 2537 CB HIS A 238 -31.158 18.113 39.545 1.00 0.00 C \\\\nATOM 2538 CG HIS A 238 -31.559 19.548 39.389 1.00 0.00 C \\\\nATOM 2539 ND1 HIS A 238 -30.797 20.462 38.693 1.00 0.00 N \\\\nATOM 2540 CD2 HIS A 238 -32.638 20.227 39.843 1.00 0.00 C \\\\nATOM 2541 CE1 HIS A 238 -31.392 21.642 38.723 1.00 0.00 C \\\\nATOM 2542 NE2 HIS A 238 -32.511 21.527 39.415 1.00 0.00 N \\\\nATOM 2543 H HIS A 238 -29.499 18.462 41.394 1.00 0.00 H \\\\nATOM 2544 HA HIS A 238 -32.126 17.822 41.304 1.00 0.00 H \\\\nATOM 2545 HB2 HIS A 238 -30.251 18.001 39.220 1.00 0.00 H \\\\nATOM 2546 HB3 HIS A 238 -31.729 17.563 38.986 1.00 0.00 H \\\\nATOM 2547 HD1 HIS A 238 -30.051 20.291 38.301 1.00 0.00 H \\\\nATOM 2548 HD2 HIS A 238 -33.336 19.879 40.350 1.00 0.00 H \\\\nATOM 2549 HE1 HIS A 238 -31.076 22.421 38.325 1.00 0.00 H \\\\nATOM 2550 HE2 HIS A 238 -33.069 22.162 39.572 1.00 0.00 H \\\\nATOM 2551 N LYS A 239 -31.388 15.571 42.251 1.00 0.00 N \\\\nATOM 2552 CA LYS A 239 -31.398 14.144 42.544 1.00 0.00 C \\\\nATOM 2553 C LYS A 239 -32.741 13.538 42.147 1.00 0.00 C \\\\nATOM 2554 O LYS A 239 -33.782 14.185 42.297 1.00 0.00 O \\\\nATOM 2555 CB LYS A 239 -31.139 13.894 44.025 1.00 0.00 C \\\\nATOM 2556 CG LYS A 239 -29.778 14.380 44.498 1.00 0.00 C \\\\nATOM 2557 CD LYS A 239 -28.751 13.260 44.458 1.00 0.00 C \\\\nATOM 2558 CE LYS A 239 -27.373 13.789 44.100 1.00 0.00 C \\\\nATOM 2559 NZ LYS A 239 -26.500 12.723 43.532 1.00 0.00 N \\\\nATOM 2560 H LYS A 239 -31.632 16.054 42.920 1.00 0.00 H \\\\nATOM 2561 HA LYS A 239 -30.691 13.723 42.031 1.00 0.00 H \\\\nATOM 2562 HB2 LYS A 239 -31.829 14.335 44.545 1.00 0.00 H \\\\nATOM 2563 HB3 LYS A 239 -31.214 12.943 44.202 1.00 0.00 H \\\\nATOM 2564 HG2 LYS A 239 -29.481 15.115 43.938 1.00 0.00 H \\\\nATOM 2565 HG3 LYS A 239 -29.851 14.724 45.402 1.00 0.00 H \\\\nATOM 2566 HD2 LYS A 239 -28.716 12.819 45.321 1.00 0.00 H \\\\nATOM 2567 HD3 LYS A 239 -29.022 12.592 43.809 1.00 0.00 H \\\\nATOM 2568 HE2 LYS A 239 -27.461 14.511 43.458 1.00 0.00 H \\\\nATOM 2569 HE3 LYS A 239 -26.954 14.162 44.891 1.00 0.00 H \\\\nATOM 2570 HZ1 LYS A 239 -25.660 13.015 43.496 1.00 0.00 H \\\\nATOM 2571 HZ2 LYS A 239 -26.541 11.999 44.048 1.00 0.00 H \\\\nATOM 2572 HZ3 LYS A 239 -26.777 12.518 42.712 1.00 0.00 H \\\\nATOM 2573 N PRO A 240 -32.733 12.312 41.616 1.00 0.00 N \\\\nATOM 2574 CA PRO A 240 -33.992 11.731 41.117 1.00 0.00 C \\\\nATOM 2575 C PRO A 240 -35.073 11.572 42.175 1.00 0.00 C \\\\nATOM 2576 O PRO A 240 -36.257 11.757 41.865 1.00 0.00 O \\\\nATOM 2577 CB PRO A 240 -33.543 10.373 40.555 1.00 0.00 C \\\\nATOM 2578 CG PRO A 240 -32.086 10.541 40.260 1.00 0.00 C \\\\nATOM 2579 CD PRO A 240 -31.564 11.473 41.306 1.00 0.00 C \\\\nATOM 2580 HA PRO A 240 -34.417 12.310 40.465 1.00 0.00 H \\\\nATOM 2581 HB2 PRO A 240 -33.692 9.661 41.196 1.00 0.00 H \\\\nATOM 2582 HB3 PRO A 240 -34.040 10.142 39.754 1.00 0.00 H \\\\nATOM 2583 HG2 PRO A 240 -31.624 9.689 40.291 1.00 0.00 H \\\\nATOM 2584 HG3 PRO A 240 -31.951 10.905 39.371 1.00 0.00 H \\\\nATOM 2585 HD2 PRO A 240 -31.248 10.994 42.088 1.00 0.00 H \\\\nATOM 2586 HD3 PRO A 240 -30.820 12.001 40.977 1.00 0.00 H \\\\nATOM 2587 N ASP A 241 -34.707 11.239 43.416 1.00 0.00 N \\\\nATOM 2588 CA ASP A 241 -35.696 11.131 44.486 1.00 0.00 C \\\\nATOM 2589 C ASP A 241 -36.380 12.457 44.804 1.00 0.00 C \\\\nATOM 2590 O ASP A 241 -37.486 12.439 45.358 1.00 0.00 O \\\\nATOM 2591 CB ASP A 241 -35.084 10.514 45.746 1.00 0.00 C \\\\nATOM 2592 CG ASP A 241 -33.693 11.009 46.031 1.00 0.00 C \\\\nATOM 2593 OD1 ASP A 241 -33.009 11.449 45.085 1.00 0.00 O \\\\nATOM 2594 OD2 ASP A 241 -33.271 10.929 47.204 1.00 0.00 O \\\\nATOM 2595 H ASP A 241 -33.898 11.073 43.655 1.00 0.00 H \\\\nATOM 2596 HA ASP A 241 -36.388 10.536 44.156 1.00 0.00 H \\\\nATOM 2597 HB2 ASP A 241 -35.654 10.712 46.506 1.00 0.00 H \\\\nATOM 2598 HB3 ASP A 241 -35.064 9.549 45.650 1.00 0.00 H \\\\nATOM 2599 N ARG A 242 -35.744 13.595 44.508 1.00 0.00 N \\\\nATOM 2600 CA ARG A 242 -36.352 14.891 44.795 1.00 0.00 C \\\\nATOM 2601 C ARG A 242 -37.750 14.949 44.191 1.00 0.00 C \\\\nATOM 2602 O ARG A 242 -37.970 14.531 43.051 1.00 0.00 O \\\\nATOM 2603 CB ARG A 242 -35.475 16.022 44.246 1.00 0.00 C \\\\nATOM 2604 CG ARG A 242 -36.141 17.391 44.198 1.00 0.00 C \\\\nATOM 2605 CD ARG A 242 -35.132 18.497 43.891 1.00 0.00 C \\\\nATOM 2606 NE ARG A 242 -35.758 19.658 43.260 1.00 0.00 N \\\\nATOM 2607 CZ ARG A 242 -35.085 20.680 42.740 1.00 0.00 C \\\\nATOM 2608 NH1 ARG A 242 -33.759 20.695 42.778 1.00 0.00 N \\\\nATOM 2609 NH2 ARG A 242 -35.737 21.692 42.186 1.00 0.00 N \\\\nATOM 2610 H ARG A 242 -34.966 13.635 44.144 1.00 0.00 H \\\\nATOM 2611 HA ARG A 242 -36.424 15.004 45.756 1.00 0.00 H \\\\nATOM 2612 HB2 ARG A 242 -34.675 16.086 44.791 1.00 0.00 H \\\\nATOM 2613 HB3 ARG A 242 -35.189 15.785 43.350 1.00 0.00 H \\\\nATOM 2614 HG2 ARG A 242 -36.837 17.390 43.522 1.00 0.00 H \\\\nATOM 2615 HG3 ARG A 242 -36.572 17.572 45.048 1.00 0.00 H \\\\nATOM 2616 HD2 ARG A 242 -34.697 18.773 44.713 1.00 0.00 H \\\\nATOM 2617 HD3 ARG A 242 -34.440 18.148 43.308 1.00 0.00 H \\\\nATOM 2618 HE ARG A 242 -36.617 19.681 43.223 1.00 0.00 H \\\\nATOM 2619 HH11 ARG A 242 -33.332 20.042 43.140 1.00 0.00 H \\\\nATOM 2620 HH12 ARG A 242 -33.327 21.358 42.441 1.00 0.00 H \\\\nATOM 2621 HH21 ARG A 242 -36.597 21.688 42.162 1.00 0.00 H \\\\nATOM 2622 HH22 ARG A 242 -35.300 22.352 41.850 1.00 0.00 H \\\\nATOM 2623 N LYS A 243 -38.696 15.484 44.969 1.00 0.00 N \\\\nATOM 2624 CA LYS A 243 -40.106 15.158 44.761 1.00 0.00 C \\\\nATOM 2625 C LYS A 243 -40.637 15.667 43.426 1.00 0.00 C \\\\nATOM 2626 O LYS A 243 -41.328 14.930 42.713 1.00 0.00 O \\\\nATOM 2627 CB LYS A 243 -40.943 15.717 45.911 1.00 0.00 C \\\\nATOM 2628 CG LYS A 243 -40.790 14.947 47.206 1.00 0.00 C \\\\nATOM 2629 CD LYS A 243 -41.659 13.705 47.192 1.00 0.00 C \\\\nATOM 2630 CE LYS A 243 -43.123 14.038 46.959 1.00 0.00 C \\\\nATOM 2631 NZ LYS A 243 -43.594 15.115 47.868 1.00 0.00 N \\\\nATOM 2632 H LYS A 243 -38.543 16.031 45.615 1.00 0.00 H \\\\nATOM 2633 HA LYS A 243 -40.178 14.191 44.741 1.00 0.00 H \\\\nATOM 2634 HB2 LYS A 243 -40.693 16.642 46.063 1.00 0.00 H \\\\nATOM 2635 HB3 LYS A 243 -41.878 15.715 45.651 1.00 0.00 H \\\\nATOM 2636 HG2 LYS A 243 -39.861 14.697 47.332 1.00 0.00 H \\\\nATOM 2637 HG3 LYS A 243 -41.036 15.512 47.955 1.00 0.00 H \\\\nATOM 2638 HD2 LYS A 243 -41.350 13.103 46.497 1.00 0.00 H \\\\nATOM 2639 HD3 LYS A 243 -41.565 13.236 48.036 1.00 0.00 H \\\\nATOM 2640 HE2 LYS A 243 -43.250 14.314 46.038 1.00 0.00 H \\\\nATOM 2641 HE3 LYS A 243 -43.661 13.242 47.094 1.00 0.00 H \\\\nATOM 2642 HZ1 LYS A 243 -44.481 15.177 47.821 1.00 0.00 H \\\\nATOM 2643 HZ2 LYS A 243 -43.354 14.925 48.704 1.00 0.00 H \\\\nATOM 2644 HZ3 LYS A 243 -43.230 15.890 47.624 1.00 0.00 H \\\\nATOM 2645 N ASP A 244 -40.333 16.914 43.064 1.00 0.00 N \\\\nATOM 2646 CA ASP A 244 -40.839 17.428 41.796 1.00 0.00 C \\\\nATOM 2647 C ASP A 244 -40.150 16.770 40.606 1.00 0.00 C \\\\nATOM 2648 O ASP A 244 -40.758 16.638 39.537 1.00 0.00 O \\\\nATOM 2649 CB ASP A 244 -40.692 18.949 41.736 1.00 0.00 C \\\\nATOM 2650 CG ASP A 244 -39.262 19.405 41.905 1.00 0.00 C \\\\nATOM 2651 OD1 ASP A 244 -38.528 18.782 42.698 1.00 0.00 O \\\\nATOM 2652 OD2 ASP A 244 -38.872 20.392 41.247 1.00 0.00 O \\\\nATOM 2653 H ASP A 244 -39.852 17.461 43.522 1.00 0.00 H \\\\nATOM 2654 HA ASP A 244 -41.782 17.206 41.744 1.00 0.00 H \\\\nATOM 2655 HB2 ASP A 244 -41.031 19.269 40.886 1.00 0.00 H \\\\nATOM 2656 HB3 ASP A 244 -41.239 19.350 42.429 1.00 0.00 H \\\\nATOM 2657 N GLU A 245 -38.892 16.353 40.767 1.00 0.00 N \\\\nATOM 2658 CA GLU A 245 -38.203 15.660 39.683 1.00 0.00 C \\\\nATOM 2659 C GLU A 245 -38.762 14.256 39.476 1.00 0.00 C \\\\nATOM 2660 O GLU A 245 -38.984 13.835 38.334 1.00 0.00 O \\\\nATOM 2661 CB GLU A 245 -36.704 15.602 39.969 1.00 0.00 C \\\\nATOM 2662 CG GLU A 245 -36.033 16.962 40.095 1.00 0.00 C \\\\nATOM 2663 CD GLU A 245 -36.205 17.814 38.852 1.00 0.00 C \\\\nATOM 2664 OE1 GLU A 245 -36.949 18.816 38.913 1.00 0.00 O \\\\nATOM 2665 OE2 GLU A 245 -35.595 17.482 37.813 1.00 0.00 O \\\\nATOM 2666 H GLU A 245 -38.429 16.460 41.484 1.00 0.00 H \\\\nATOM 2667 HA GLU A 245 -38.350 16.159 38.864 1.00 0.00 H \\\\nATOM 2668 HB2 GLU A 245 -36.562 15.106 40.791 1.00 0.00 H \\\\nATOM 2669 HB3 GLU A 245 -36.270 15.104 39.259 1.00 0.00 H \\\\nATOM 2670 HG2 GLU A 245 -36.403 17.432 40.859 1.00 0.00 H \\\\nATOM 2671 HG3 GLU A 245 -35.087 16.837 40.269 1.00 0.00 H \\\\nATOM 2672 N ARG A 246 -38.989 13.514 40.564 1.00 0.00 N \\\\nATOM 2673 CA ARG A 246 -39.578 12.183 40.442 1.00 0.00 C \\\\nATOM 2674 C ARG A 246 -40.960 12.246 39.806 1.00 0.00 C \\\\nATOM 2675 O ARG A 246 -41.316 11.389 38.989 1.00 0.00 O \\\\nATOM 2676 CB ARG A 246 -39.650 11.501 41.808 1.00 0.00 C \\\\nATOM 2677 CG ARG A 246 -40.097 10.048 41.730 1.00 0.00 C \\\\nATOM 2678 CD ARG A 246 -39.842 9.302 43.027 1.00 0.00 C \\\\nATOM 2679 NE ARG A 246 -40.989 9.370 43.924 1.00 0.00 N \\\\nATOM 2680 CZ ARG A 246 -40.988 10.000 45.094 1.00 0.00 C \\\\nATOM 2681 NH1 ARG A 246 -39.894 10.619 45.512 1.00 0.00 N \\\\nATOM 2682 NH2 ARG A 246 -42.083 10.011 45.845 1.00 0.00 N \\\\nATOM 2683 H ARG A 246 -38.811 13.760 41.369 1.00 0.00 H \\\\nATOM 2684 HA ARG A 246 -39.006 11.657 39.861 1.00 0.00 H \\\\nATOM 2685 HB2 ARG A 246 -38.778 11.543 42.230 1.00 0.00 H \\\\nATOM 2686 HB3 ARG A 246 -40.264 11.992 42.376 1.00 0.00 H \\\\nATOM 2687 HG2 ARG A 246 -41.043 10.013 41.519 1.00 0.00 H \\\\nATOM 2688 HG3 ARG A 246 -39.628 9.605 41.006 1.00 0.00 H \\\\nATOM 2689 HD2 ARG A 246 -39.638 8.374 42.832 1.00 0.00 H \\\\nATOM 2690 HD3 ARG A 246 -39.064 9.677 43.468 1.00 0.00 H \\\\nATOM 2691 HE ARG A 246 -41.714 8.977 43.680 1.00 0.00 H \\\\nATOM 2692 HH11 ARG A 246 -39.184 10.613 45.026 1.00 0.00 H \\\\nATOM 2693 HH12 ARG A 246 -39.893 11.027 46.269 1.00 0.00 H \\\\nATOM 2694 HH21 ARG A 246 -42.794 9.610 45.574 1.00 0.00 H \\\\nATOM 2695 HH22 ARG A 246 -42.081 10.419 46.602 1.00 0.00 H \\\\nATOM 2696 N ALA A 247 -41.757 13.252 40.175 1.00 0.00 N \\\\nATOM 2697 CA ALA A 247 -43.092 13.386 39.602 1.00 0.00 C \\\\nATOM 2698 C ALA A 247 -43.026 13.678 38.109 1.00 0.00 C \\\\nATOM 2699 O ALA A 247 -43.800 13.112 37.328 1.00 0.00 O \\\\nATOM 2700 CB ALA A 247 -43.868 14.482 40.331 1.00 0.00 C \\\\nATOM 2701 H ALA A 247 -41.545 13.858 40.747 1.00 0.00 H \\\\nATOM 2702 HA ALA A 247 -43.557 12.542 39.716 1.00 0.00 H \\\\nATOM 2703 HB1 ALA A 247 -44.754 14.564 39.944 1.00 0.00 H \\\\nATOM 2704 HB2 ALA A 247 -43.946 14.253 41.270 1.00 0.00 H \\\\nATOM 2705 HB3 ALA A 247 -43.397 15.326 40.242 1.00 0.00 H \\\\nATOM 2706 N ARG A 248 -42.115 14.563 37.695 1.00 0.00 N \\\\nATOM 2707 CA ARG A 248 -41.967 14.856 36.273 1.00 0.00 C \\\\nATOM 2708 C ARG A 248 -41.515 13.623 35.501 1.00 0.00 C \\\\nATOM 2709 O ARG A 248 -42.019 13.346 34.406 1.00 0.00 O \\\\nATOM 2710 CB ARG A 248 -40.981 16.004 36.071 1.00 0.00 C \\\\nATOM 2711 CG ARG A 248 -40.540 16.173 34.623 1.00 0.00 C \\\\nATOM 2712 CD ARG A 248 -39.486 17.257 34.465 1.00 0.00 C \\\\nATOM 2713 NE ARG A 248 -38.236 16.938 35.151 1.00 0.00 N \\\\nATOM 2714 CZ ARG A 248 -37.321 16.093 34.686 1.00 0.00 C \\\\nATOM 2715 NH1 ARG A 248 -36.211 15.869 35.378 1.00 0.00 N \\\\nATOM 2716 NH2 ARG A 248 -37.514 15.472 33.530 1.00 0.00 N \\\\nATOM 2717 H ARG A 248 -41.583 14.996 38.214 1.00 0.00 H \\\\nATOM 2718 HA ARG A 248 -42.834 15.122 35.928 1.00 0.00 H \\\\nATOM 2719 HB2 ARG A 248 -41.389 16.829 36.377 1.00 0.00 H \\\\nATOM 2720 HB3 ARG A 248 -40.199 15.852 36.625 1.00 0.00 H \\\\nATOM 2721 HG2 ARG A 248 -40.188 15.331 34.294 1.00 0.00 H \\\\nATOM 2722 HG3 ARG A 248 -41.310 16.391 34.076 1.00 0.00 H \\\\nATOM 2723 HD2 ARG A 248 -39.306 17.392 33.521 1.00 0.00 H \\\\nATOM 2724 HD3 ARG A 248 -39.835 18.094 34.810 1.00 0.00 H \\\\nATOM 2725 HE ARG A 248 -38.082 17.322 35.905 1.00 0.00 H \\\\nATOM 2726 HH11 ARG A 248 -36.083 16.271 36.128 1.00 0.00 H \\\\nATOM 2727 HH12 ARG A 248 -35.619 15.322 35.077 1.00 0.00 H \\\\nATOM 2728 HH21 ARG A 248 -38.232 15.616 33.079 1.00 0.00 H \\\\nATOM 2729 HH22 ARG A 248 -36.921 14.926 33.231 1.00 0.00 H \\\\nATOM 2730 N ILE A 249 -40.569 12.867 36.061 1.00 0.00 N \\\\nATOM 2731 CA ILE A 249 -40.045 11.690 35.374 1.00 0.00 C \\\\nATOM 2732 C ILE A 249 -41.130 10.629 35.220 1.00 0.00 C \\\\nATOM 2733 O ILE A 249 -41.326 10.075 34.132 1.00 0.00 O \\\\nATOM 2734 CB ILE A 249 -38.815 11.142 36.120 1.00 0.00 C \\\\nATOM 2735 CG1 ILE A 249 -37.584 11.995 35.805 1.00 0.00 C \\\\nATOM 2736 CG2 ILE A 249 -38.565 9.686 35.751 1.00 0.00 C \\\\nATOM 2737 CD1 ILE A 249 -36.446 11.811 36.782 1.00 0.00 C \\\\nATOM 2738 H ILE A 249 -40.221 13.019 36.833 1.00 0.00 H \\\\nATOM 2739 HA ILE A 249 -39.762 11.946 34.482 1.00 0.00 H \\\\nATOM 2740 HB ILE A 249 -38.988 11.186 37.073 1.00 0.00 H \\\\nATOM 2741 HG12 ILE A 249 -37.271 11.778 34.913 1.00 0.00 H \\\\nATOM 2742 HG13 ILE A 249 -37.843 12.930 35.796 1.00 0.00 H \\\\nATOM 2743 HG21 ILE A 249 -37.787 9.359 36.230 1.00 0.00 H \\\\nATOM 2744 HG22 ILE A 249 -39.339 9.154 35.991 1.00 0.00 H \\\\nATOM 2745 HG23 ILE A 249 -38.409 9.616 34.796 1.00 0.00 H \\\\nATOM 2746 HD11 ILE A 249 -35.703 12.378 36.524 1.00 0.00 H \\\\nATOM 2747 HD12 ILE A 249 -36.742 12.053 37.673 1.00 0.00 H \\\\nATOM 2748 HD13 ILE A 249 -36.162 10.884 36.777 1.00 0.00 H \\\\nATOM 2749 N GLU A 250 -41.855 10.335 36.301 1.00 0.00 N \\\\nATOM 2750 CA GLU A 250 -42.883 9.300 36.231 1.00 0.00 C \\\\nATOM 2751 C GLU A 250 -44.045 9.714 35.339 1.00 0.00 C \\\\nATOM 2752 O GLU A 250 -44.703 8.853 34.746 1.00 0.00 O \\\\nATOM 2753 CB GLU A 250 -43.388 8.960 37.634 1.00 0.00 C \\\\nATOM 2754 CG GLU A 250 -42.352 8.295 38.523 1.00 0.00 C \\\\nATOM 2755 CD GLU A 250 -42.745 8.317 39.987 1.00 0.00 C \\\\nATOM 2756 OE1 GLU A 250 -43.716 9.025 40.333 1.00 0.00 O \\\\nATOM 2757 OE2 GLU A 250 -42.086 7.626 40.793 1.00 0.00 O \\\\nATOM 2758 H GLU A 250 -41.769 10.715 37.068 1.00 0.00 H \\\\nATOM 2759 HA GLU A 250 -42.478 8.512 35.837 1.00 0.00 H \\\\nATOM 2760 HB2 GLU A 250 -43.693 9.774 38.063 1.00 0.00 H \\\\nATOM 2761 HB3 GLU A 250 -44.157 8.374 37.557 1.00 0.00 H \\\\nATOM 2762 HG2 GLU A 250 -42.227 7.376 38.238 1.00 0.00 H \\\\nATOM 2763 HG3 GLU A 250 -41.499 8.744 38.413 1.00 0.00 H \\\\nATOM 2764 N ALA A 251 -44.317 11.018 35.236 1.00 0.00 N \\\\nATOM 2765 CA ALA A 251 -45.391 11.482 34.364 1.00 0.00 C \\\\nATOM 2766 C ALA A 251 -45.087 11.206 32.897 1.00 0.00 C \\\\nATOM 2767 O ALA A 251 -46.013 11.024 32.097 1.00 0.00 O \\\\nATOM 2768 CB ALA A 251 -45.641 12.973 34.583 1.00 0.00 C \\\\nATOM 2769 H ALA A 251 -43.897 11.639 35.657 1.00 0.00 H \\\\nATOM 2770 HA ALA A 251 -46.193 10.987 34.595 1.00 0.00 H \\\\nATOM 2771 HB1 ALA A 251 -46.356 13.271 33.999 1.00 0.00 H \\\\nATOM 2772 HB2 ALA A 251 -45.894 13.127 35.507 1.00 0.00 H \\\\nATOM 2773 HB3 ALA A 251 -44.832 13.470 34.382 1.00 0.00 H \\\\nATOM 2774 N GLN A 252 -43.809 11.167 32.526 1.00 0.00 N \\\\nATOM 2775 CA GLN A 252 -43.400 10.824 31.172 1.00 0.00 C \\\\nATOM 2776 C GLN A 252 -43.267 9.323 30.968 1.00 0.00 C \\\\nATOM 2777 O GLN A 252 -42.725 8.893 29.944 1.00 0.00 O \\\\nATOM 2778 CB GLN A 252 -42.072 11.503 30.826 1.00 0.00 C \\\\nATOM 2779 CG GLN A 252 -42.024 12.995 31.092 1.00 0.00 C \\\\nATOM 2780 CD GLN A 252 -40.635 13.569 30.887 1.00 0.00 C \\\\nATOM 2781 OE1 GLN A 252 -39.760 13.428 31.742 1.00 0.00 O \\\\nATOM 2782 NE2 GLN A 252 -40.424 14.215 29.745 1.00 0.00 N \\\\nATOM 2783 H GLN A 252 -43.155 11.340 33.057 1.00 0.00 H \\\\nATOM 2784 HA GLN A 252 -44.099 11.144 30.580 1.00 0.00 H \\\\nATOM 2785 HB2 GLN A 252 -41.364 11.075 31.333 1.00 0.00 H \\\\nATOM 2786 HB3 GLN A 252 -41.881 11.350 29.887 1.00 0.00 H \\\\nATOM 2787 HG2 GLN A 252 -42.649 13.447 30.504 1.00 0.00 H \\\\nATOM 2788 HG3 GLN A 252 -42.313 13.169 32.001 1.00 0.00 H \\\\nATOM 2789 HE21 GLN A 252 -41.060 14.293 29.171 1.00 0.00 H \\\\nATOM 2790 HE22 GLN A 252 -39.651 14.555 29.580 1.00 0.00 H \\\\nATOM 2791 N GLY A 253 -43.744 8.519 31.915 1.00 0.00 N \\\\nATOM 2792 CA GLY A 253 -43.622 7.081 31.833 1.00 0.00 C \\\\nATOM 2793 C GLY A 253 -42.300 6.521 32.309 1.00 0.00 C \\\\nATOM 2794 O GLY A 253 -42.089 5.305 32.203 1.00 0.00 O \\\\nATOM 2795 H GLY A 253 -44.147 8.799 32.621 1.00 0.00 H \\\\nATOM 2796 HA2 GLY A 253 -44.334 6.680 32.355 1.00 0.00 H \\\\nATOM 2797 HA3 GLY A 253 -43.759 6.811 30.912 1.00 0.00 H \\\\nATOM 2798 N GLY A 254 -41.405 7.360 32.830 1.00 0.00 N \\\\nATOM 2799 CA GLY A 254 -40.137 6.895 33.344 1.00 0.00 C \\\\nATOM 2800 C GLY A 254 -40.248 6.336 34.748 1.00 0.00 C \\\\nATOM 2801 O GLY A 254 -41.325 6.224 35.332 1.00 0.00 O \\\\nATOM 2802 H GLY A 254 -41.523 8.210 32.892 1.00 0.00 H \\\\nATOM 2803 HA2 GLY A 254 -39.784 6.211 32.754 1.00 0.00 H \\\\nATOM 2804 HA3 GLY A 254 -39.502 7.628 33.341 1.00 0.00 H \\\\nATOM 2805 N LYS A 255 -39.091 5.980 35.300 1.00 0.00 N \\\\nATOM 2806 CA LYS A 255 -39.011 5.408 36.636 1.00 0.00 C \\\\nATOM 2807 C LYS A 255 -37.777 5.940 37.348 1.00 0.00 C \\\\nATOM 2808 O LYS A 255 -36.733 6.165 36.729 1.00 0.00 O \\\\nATOM 2809 CB LYS A 255 -38.956 3.873 36.599 1.00 0.00 C \\\\nATOM 2810 CG LYS A 255 -40.223 3.198 36.104 1.00 0.00 C \\\\nATOM 2811 CD LYS A 255 -39.936 1.765 35.691 1.00 0.00 C \\\\nATOM 2812 CE LYS A 255 -40.529 0.760 36.659 1.00 0.00 C \\\\nATOM 2813 NZ LYS A 255 -42.012 0.694 36.546 1.00 0.00 N \\\\nATOM 2814 H LYS A 255 -38.330 6.064 34.908 1.00 0.00 H \\\\nATOM 2815 HA LYS A 255 -39.813 5.667 37.116 1.00 0.00 H \\\\nATOM 2816 HB2 LYS A 255 -38.218 3.603 36.030 1.00 0.00 H \\\\nATOM 2817 HB3 LYS A 255 -38.760 3.548 37.492 1.00 0.00 H \\\\nATOM 2818 HG2 LYS A 255 -40.896 3.210 36.802 1.00 0.00 H \\\\nATOM 2819 HG3 LYS A 255 -40.586 3.691 35.351 1.00 0.00 H \\\\nATOM 2820 HD2 LYS A 255 -40.295 1.608 34.804 1.00 0.00 H \\\\nATOM 2821 HD3 LYS A 255 -38.977 1.632 35.636 1.00 0.00 H \\\\nATOM 2822 HE2 LYS A 255 -40.152 -0.117 36.487 1.00 0.00 H \\\\nATOM 2823 HE3 LYS A 255 -40.284 1.001 37.566 1.00 0.00 H \\\\nATOM 2824 HZ1 LYS A 255 -42.310 -0.031 36.967 1.00 0.00 H \\\\nATOM 2825 HZ2 LYS A 255 -42.371 1.420 36.916 1.00 0.00 H \\\\nATOM 2826 HZ3 LYS A 255 -42.243 0.654 35.687 1.00 0.00 H \\\\nATOM 2827 N VAL A 256 -37.911 6.137 38.656 1.00 0.00 N \\\\nATOM 2828 CA VAL A 256 -36.786 6.438 39.533 1.00 0.00 C \\\\nATOM 2829 C VAL A 256 -36.571 5.227 40.427 1.00 0.00 C \\\\nATOM 2830 O VAL A 256 -37.457 4.859 41.208 1.00 0.00 O \\\\nATOM 2831 CB VAL A 256 -37.033 7.707 40.360 1.00 0.00 C \\\\nATOM 2832 CG1 VAL A 256 -36.001 7.824 41.474 1.00 0.00 C \\\\nATOM 2833 CG2 VAL A 256 -37.002 8.936 39.461 1.00 0.00 C \\\\nATOM 2834 H VAL A 256 -38.667 6.099 39.063 1.00 0.00 H \\\\nATOM 2835 HA VAL A 256 -35.991 6.615 39.005 1.00 0.00 H \\\\nATOM 2836 HB VAL A 256 -37.912 7.649 40.767 1.00 0.00 H \\\\nATOM 2837 HG11 VAL A 256 -36.169 8.629 41.988 1.00 0.00 H \\\\nATOM 2838 HG12 VAL A 256 -36.064 7.051 42.056 1.00 0.00 H \\\\nATOM 2839 HG13 VAL A 256 -35.112 7.867 41.089 1.00 0.00 H \\\\nATOM 2840 HG21 VAL A 256 -37.159 9.731 39.994 1.00 0.00 H \\\\nATOM 2841 HG22 VAL A 256 -36.135 9.001 39.032 1.00 0.00 H \\\\nATOM 2842 HG23 VAL A 256 -37.692 8.859 38.784 1.00 0.00 H \\\\nATOM 2843 N ILE A 257 -35.399 4.605 40.309 1.00 0.00 N \\\\nATOM 2844 CA ILE A 257 -35.095 3.351 40.986 1.00 0.00 C \\\\nATOM 2845 C ILE A 257 -33.926 3.564 41.935 1.00 0.00 C \\\\nATOM 2846 O ILE A 257 -32.936 4.211 41.579 1.00 0.00 O \\\\nATOM 2847 CB ILE A 257 -34.773 2.232 39.973 1.00 0.00 C \\\\nATOM 2848 CG1 ILE A 257 -35.881 2.131 38.920 1.00 0.00 C \\\\nATOM 2849 CG2 ILE A 257 -34.565 0.900 40.682 1.00 0.00 C \\\\nATOM 2850 CD1 ILE A 257 -35.519 1.262 37.739 1.00 0.00 C \\\\nATOM 2851 H ILE A 257 -34.752 4.905 39.828 1.00 0.00 H \\\\nATOM 2852 HA ILE A 257 -35.875 3.071 41.490 1.00 0.00 H \\\\nATOM 2853 HB ILE A 257 -33.945 2.456 39.521 1.00 0.00 H \\\\nATOM 2854 HG12 ILE A 257 -36.682 1.778 39.338 1.00 0.00 H \\\\nATOM 2855 HG13 ILE A 257 -36.096 3.022 38.602 1.00 0.00 H \\\\nATOM 2856 HG21 ILE A 257 -34.364 0.213 40.028 1.00 0.00 H \\\\nATOM 2857 HG22 ILE A 257 -33.826 0.977 41.306 1.00 0.00 H \\\\nATOM 2858 HG23 ILE A 257 -35.372 0.661 41.165 1.00 0.00 H \\\\nATOM 2859 HD11 ILE A 257 -36.260 1.241 37.113 1.00 0.00 H \\\\nATOM 2860 HD12 ILE A 257 -34.735 1.625 37.298 1.00 0.00 H \\\\nATOM 2861 HD13 ILE A 257 -35.330 0.361 38.046 1.00 0.00 H \\\\nATOM 2862 N GLN A 258 -34.045 3.023 43.146 1.00 0.00 N \\\\nATOM 2863 CA GLN A 258 -32.929 2.999 44.083 1.00 0.00 C \\\\nATOM 2864 C GLN A 258 -32.007 1.837 43.729 1.00 0.00 C \\\\nATOM 2865 O GLN A 258 -32.406 0.670 43.810 1.00 0.00 O \\\\nATOM 2866 CB GLN A 258 -33.418 2.875 45.525 1.00 0.00 C \\\\nATOM 2867 CG GLN A 258 -32.298 2.572 46.513 1.00 0.00 C \\\\nATOM 2868 CD GLN A 258 -32.665 2.900 47.945 1.00 0.00 C \\\\nATOM 2869 OE1 GLN A 258 -33.685 2.439 48.458 1.00 0.00 O \\\\nATOM 2870 NE2 GLN A 258 -31.829 3.697 48.603 1.00 0.00 N \\\\nATOM 2871 H GLN A 258 -34.768 2.664 43.443 1.00 0.00 H \\\\nATOM 2872 HA GLN A 258 -32.442 3.835 44.013 1.00 0.00 H \\\\nATOM 2873 HB2 GLN A 258 -33.856 3.701 45.784 1.00 0.00 H \\\\nATOM 2874 HB3 GLN A 258 -34.085 2.172 45.575 1.00 0.00 H \\\\nATOM 2875 HG2 GLN A 258 -32.065 1.632 46.452 1.00 0.00 H \\\\nATOM 2876 HG3 GLN A 258 -31.508 3.077 46.263 1.00 0.00 H \\\\nATOM 2877 HE21 GLN A 258 -31.126 4.000 48.211 1.00 0.00 H \\\\nATOM 2878 HE22 GLN A 258 -31.991 3.910 49.420 1.00 0.00 H \\\\nATOM 2879 N TRP A 259 -30.777 2.158 43.335 1.00 0.00 N \\\\nATOM 2880 CA TRP A 259 -29.817 1.157 42.866 1.00 0.00 C \\\\nATOM 2881 C TRP A 259 -28.430 1.749 43.120 1.00 0.00 C \\\\nATOM 2882 O TRP A 259 -27.877 2.447 42.266 1.00 0.00 O \\\\nATOM 2883 CB TRP A 259 -30.034 0.819 41.398 1.00 0.00 C \\\\nATOM 2884 CG TRP A 259 -29.547 -0.546 41.003 1.00 0.00 C \\\\nATOM 2885 CD1 TRP A 259 -28.250 -0.933 40.817 1.00 0.00 C \\\\nATOM 2886 CD2 TRP A 259 -30.350 -1.705 40.740 1.00 0.00 C \\\\nATOM 2887 NE1 TRP A 259 -28.196 -2.259 40.460 1.00 0.00 N \\\\nATOM 2888 CE2 TRP A 259 -29.471 -2.756 40.405 1.00 0.00 C \\\\nATOM 2889 CE3 TRP A 259 -31.725 -1.957 40.758 1.00 0.00 C \\\\nATOM 2890 CZ2 TRP A 259 -29.923 -4.036 40.091 1.00 0.00 C \\\\nATOM 2891 CZ3 TRP A 259 -32.172 -3.229 40.444 1.00 0.00 C \\\\nATOM 2892 CH2 TRP A 259 -31.273 -4.253 40.117 1.00 0.00 C \\\\nATOM 2893 H TRP A 259 -30.474 2.963 43.332 1.00 0.00 H \\\\nATOM 2894 HA TRP A 259 -29.925 0.317 43.339 1.00 0.00 H \\\\nATOM 2895 HB2 TRP A 259 -30.981 0.884 41.198 1.00 0.00 H \\\\nATOM 2896 HB3 TRP A 259 -29.583 1.483 40.853 1.00 0.00 H \\\\nATOM 2897 HD1 TRP A 259 -27.510 -0.379 40.918 1.00 0.00 H \\\\nATOM 2898 HE1 TRP A 259 -27.478 -2.704 40.298 1.00 0.00 H \\\\nATOM 2899 HE3 TRP A 259 -32.328 -1.283 40.977 1.00 0.00 H \\\\nATOM 2900 HZ2 TRP A 259 -29.329 -4.717 39.872 1.00 0.00 H \\\\nATOM 2901 HZ3 TRP A 259 -33.085 -3.407 40.450 1.00 0.00 H \\\\nATOM 2902 HH2 TRP A 259 -31.602 -5.099 39.913 1.00 0.00 H \\\\nATOM 2903 N ASN A 260 -27.877 1.440 44.296 1.00 0.00 N \\\\nATOM 2904 CA ASN A 260 -26.849 2.268 44.920 1.00 0.00 C \\\\nATOM 2905 C ASN A 260 -27.192 3.744 44.766 1.00 0.00 C \\\\nATOM 2906 O ASN A 260 -26.533 4.473 44.016 1.00 0.00 O \\\\nATOM 2907 CB ASN A 260 -25.470 1.967 44.325 1.00 0.00 C \\\\nATOM 2908 CG ASN A 260 -25.194 0.481 44.218 1.00 0.00 C \\\\nATOM 2909 OD1 ASN A 260 -25.751 -0.320 44.968 1.00 0.00 O \\\\nATOM 2910 ND2 ASN A 260 -24.320 0.105 43.291 1.00 0.00 N \\\\nATOM 2911 H ASN A 260 -28.090 0.743 44.752 1.00 0.00 H \\\\nATOM 2912 HA ASN A 260 -26.819 2.056 45.866 1.00 0.00 H \\\\nATOM 2913 HB2 ASN A 260 -25.407 2.369 43.444 1.00 0.00 H \\\\nATOM 2914 HB3 ASN A 260 -24.787 2.381 44.875 1.00 0.00 H \\\\nATOM 2915 HD21 ASN A 260 -24.124 -0.727 43.197 1.00 0.00 H \\\\nATOM 2916 HD22 ASN A 260 -23.950 0.694 42.785 1.00 0.00 H \\\\nATOM 2917 N GLY A 261 -28.225 4.184 45.472 1.00 0.00 N \\\\nATOM 2918 CA GLY A 261 -28.743 5.529 45.360 1.00 0.00 C \\\\nATOM 2919 C GLY A 261 -29.894 5.616 44.370 1.00 0.00 C \\\\nATOM 2920 O GLY A 261 -30.080 4.762 43.500 1.00 0.00 O \\\\nATOM 2921 H GLY A 261 -28.649 3.696 46.039 1.00 0.00 H \\\\nATOM 2922 HA2 GLY A 261 -29.043 5.833 46.231 1.00 0.00 H \\\\nATOM 2923 HA3 GLY A 261 -28.032 6.126 45.081 1.00 0.00 H \\\\nATOM 2924 N TYR A 262 -30.688 6.674 44.515 1.00 0.00 N \\\\nATOM 2925 CA TYR A 262 -31.820 6.898 43.627 1.00 0.00 C \\\\nATOM 2926 C TYR A 262 -31.333 7.404 42.276 1.00 0.00 C \\\\nATOM 2927 O TYR A 262 -30.582 8.382 42.202 1.00 0.00 O \\\\nATOM 2928 CB TYR A 262 -32.799 7.886 44.258 1.00 0.00 C \\\\nATOM 2929 CG TYR A 262 -33.638 7.245 45.335 1.00 0.00 C \\\\nATOM 2930 CD1 TYR A 262 -34.789 6.539 45.014 1.00 0.00 C \\\\nATOM 2931 CD2 TYR A 262 -33.263 7.317 46.669 1.00 0.00 C \\\\nATOM 2932 CE1 TYR A 262 -35.556 5.942 45.994 1.00 0.00 C \\\\nATOM 2933 CE2 TYR A 262 -34.023 6.721 47.658 1.00 0.00 C \\\\nATOM 2934 CZ TYR A 262 -35.169 6.033 47.314 1.00 0.00 C \\\\nATOM 2935 OH TYR A 262 -35.931 5.435 48.290 1.00 0.00 O \\\\nATOM 2936 H TYR A 262 -30.586 7.274 45.123 1.00 0.00 H \\\\nATOM 2937 HA TYR A 262 -32.285 6.058 43.489 1.00 0.00 H \\\\nATOM 2938 HB2 TYR A 262 -32.306 8.632 44.635 1.00 0.00 H \\\\nATOM 2939 HB3 TYR A 262 -33.379 8.248 43.570 1.00 0.00 H \\\\nATOM 2940 HD1 TYR A 262 -35.048 6.467 44.124 1.00 0.00 H \\\\nATOM 2941 HD2 TYR A 262 -32.487 7.774 46.902 1.00 0.00 H \\\\nATOM 2942 HE1 TYR A 262 -36.330 5.481 45.765 1.00 0.00 H \\\\nATOM 2943 HE2 TYR A 262 -33.764 6.783 48.549 1.00 0.00 H \\\\nATOM 2944 HH TYR A 262 -35.532 5.486 49.028 1.00 0.00 H \\\\nATOM 2945 N ARG A 263 -31.764 6.735 41.206 1.00 0.00 N \\\\nATOM 2946 CA ARG A 263 -31.259 7.012 39.871 1.00 0.00 C \\\\nATOM 2947 C ARG A 263 -32.382 6.937 38.848 1.00 0.00 C \\\\nATOM 2948 O ARG A 263 -33.294 6.115 38.972 1.00 0.00 O \\\\nATOM 2949 CB ARG A 263 -30.144 6.034 39.484 1.00 0.00 C \\\\nATOM 2950 CG ARG A 263 -28.913 6.099 40.374 1.00 0.00 C \\\\nATOM 2951 CD ARG A 263 -28.002 4.911 40.131 1.00 0.00 C \\\\nATOM 2952 NE ARG A 263 -26.877 4.885 41.060 1.00 0.00 N \\\\nATOM 2953 CZ ARG A 263 -25.692 5.434 40.817 1.00 0.00 C \\\\nATOM 2954 NH1 ARG A 263 -25.470 6.057 39.669 1.00 0.00 N \\\\nATOM 2955 NH2 ARG A 263 -24.729 5.362 41.724 1.00 0.00 N \\\\nATOM 2956 H ARG A 263 -32.355 6.111 41.238 1.00 0.00 H \\\\nATOM 2957 HA ARG A 263 -30.893 7.910 39.878 1.00 0.00 H \\\\nATOM 2958 HB2 ARG A 263 -30.498 5.131 39.507 1.00 0.00 H \\\\nATOM 2959 HB3 ARG A 263 -29.877 6.211 38.568 1.00 0.00 H \\\\nATOM 2960 HG2 ARG A 263 -28.429 6.922 40.203 1.00 0.00 H \\\\nATOM 2961 HG3 ARG A 263 -29.184 6.118 41.305 1.00 0.00 H \\\\nATOM 2962 HD2 ARG A 263 -28.512 4.090 40.219 1.00 0.00 H \\\\nATOM 2963 HD3 ARG A 263 -27.668 4.942 39.221 1.00 0.00 H \\\\nATOM 2964 HE ARG A 263 -26.989 4.488 41.815 1.00 0.00 H \\\\nATOM 2965 HH11 ARG A 263 -26.094 6.107 39.079 1.00 0.00 H \\\\nATOM 2966 HH12 ARG A 263 -24.702 6.412 39.514 1.00 0.00 H \\\\nATOM 2967 HH21 ARG A 263 -24.871 4.960 42.471 1.00 0.00 H \\\\nATOM 2968 HH22 ARG A 263 -23.962 5.718 41.566 1.00 0.00 H \\\\nATOM 2969 N VAL A 264 -32.313 7.812 37.844 1.00 0.00 N \\\\nATOM 2970 CA VAL A 264 -33.214 7.718 36.701 1.00 0.00 C \\\\nATOM 2971 C VAL A 264 -32.942 6.411 35.972 1.00 0.00 C \\\\nATOM 2972 O VAL A 264 -31.801 6.130 35.583 1.00 0.00 O \\\\nATOM 2973 CB VAL A 264 -33.041 8.923 35.775 1.00 0.00 C \\\\nATOM 2974 CG1 VAL A 264 -34.075 8.880 34.666 1.00 0.00 C \\\\nATOM 2975 CG2 VAL A 264 -33.147 10.218 36.570 1.00 0.00 C \\\\nATOM 2976 H VAL A 264 -31.753 8.464 37.808 1.00 0.00 H \\\\nATOM 2977 HA VAL A 264 -34.135 7.725 37.006 1.00 0.00 H \\\\nATOM 2978 HB VAL A 264 -32.160 8.888 35.371 1.00 0.00 H \\\\nATOM 2979 HG11 VAL A 264 -33.958 9.647 34.084 1.00 0.00 H \\\\nATOM 2980 HG12 VAL A 264 -33.965 8.065 34.152 1.00 0.00 H \\\\nATOM 2981 HG13 VAL A 264 -34.965 8.900 35.052 1.00 0.00 H \\\\nATOM 2982 HG21 VAL A 264 -33.036 10.974 35.973 1.00 0.00 H \\\\nATOM 2983 HG22 VAL A 264 -34.018 10.267 36.995 1.00 0.00 H \\\\nATOM 2984 HG23 VAL A 264 -32.455 10.238 37.249 1.00 0.00 H \\\\nATOM 2985 N SER A 265 -33.988 5.603 35.792 1.00 0.00 N \\\\nATOM 2986 CA SER A 265 -33.884 4.266 35.208 1.00 0.00 C \\\\nATOM 2987 C SER A 265 -32.932 3.371 35.994 1.00 0.00 C \\\\nATOM 2988 O SER A 265 -32.461 2.355 35.476 1.00 0.00 O \\\\nATOM 2989 CB SER A 265 -33.451 4.323 33.737 1.00 0.00 C \\\\nATOM 2990 OG SER A 265 -34.129 5.353 33.042 1.00 0.00 O \\\\nATOM 2991 H SER A 265 -34.791 5.821 36.010 1.00 0.00 H \\\\nATOM 2992 HA SER A 265 -34.772 3.879 35.255 1.00 0.00 H \\\\nATOM 2993 HB2 SER A 265 -32.494 4.470 33.685 1.00 0.00 H \\\\nATOM 2994 HB3 SER A 265 -33.630 3.470 33.311 1.00 0.00 H \\\\nATOM 2995 HG SER A 265 -34.919 5.113 32.886 1.00 0.00 H \\\\nATOM 2996 N GLY A 266 -32.638 3.732 37.241 1.00 0.00 N \\\\nATOM 2997 CA GLY A 266 -31.649 3.011 38.015 1.00 0.00 C \\\\nATOM 2998 C GLY A 266 -30.219 3.242 37.588 1.00 0.00 C \\\\nATOM 2999 O GLY A 266 -29.319 2.579 38.110 1.00 0.00 O \\\\nATOM 3000 H GLY A 266 -33.004 4.393 37.652 1.00 0.00 H \\\\nATOM 3001 HA2 GLY A 266 -31.740 3.263 38.947 1.00 0.00 H \\\\nATOM 3002 HA3 GLY A 266 -31.841 2.062 37.958 1.00 0.00 H \\\\nATOM 3003 N ILE A 267 -29.979 4.164 36.656 1.00 0.00 N \\\\nATOM 3004 CA ILE A 267 -28.659 4.377 36.066 1.00 0.00 C \\\\nATOM 3005 C ILE A 267 -28.021 5.673 36.567 1.00 0.00 C \\\\nATOM 3006 O ILE A 267 -26.971 5.648 37.209 1.00 0.00 O \\\\nATOM 3007 CB ILE A 267 -28.735 4.354 34.524 1.00 0.00 C \\\\nATOM 3008 CG1 ILE A 267 -29.156 2.969 34.033 1.00 0.00 C \\\\nATOM 3009 CG2 ILE A 267 -27.398 4.742 33.931 1.00 0.00 C \\\\nATOM 3010 CD1 ILE A 267 -29.657 2.957 32.608 1.00 0.00 C \\\\nATOM 3011 H ILE A 267 -30.585 4.689 36.346 1.00 0.00 H \\\\nATOM 3012 HA ILE A 267 -28.089 3.645 36.351 1.00 0.00 H \\\\nATOM 3013 HB ILE A 267 -29.401 4.997 34.235 1.00 0.00 H \\\\nATOM 3014 HG12 ILE A 267 -28.401 2.365 34.107 1.00 0.00 H \\\\nATOM 3015 HG13 ILE A 267 -29.852 2.626 34.615 1.00 0.00 H \\\\nATOM 3016 HG21 ILE A 267 -27.456 4.725 32.963 1.00 0.00 H \\\\nATOM 3017 HG22 ILE A 267 -27.161 5.636 34.224 1.00 0.00 H \\\\nATOM 3018 HG23 ILE A 267 -26.719 4.115 34.225 1.00 0.00 H \\\\nATOM 3019 HD11 ILE A 267 -29.906 2.053 32.360 1.00 0.00 H \\\\nATOM 3020 HD12 ILE A 267 -30.430 3.538 32.532 1.00 0.00 H \\\\nATOM 3021 HD13 ILE A 267 -28.957 3.273 32.016 1.00 0.00 H \\\\nATOM 3022 N LEU A 268 -28.634 6.814 36.267 1.00 0.00 N \\\\nATOM 3023 CA LEU A 268 -28.014 8.116 36.481 1.00 0.00 C \\\\nATOM 3024 C LEU A 268 -28.519 8.748 37.769 1.00 0.00 C \\\\nATOM 3025 O LEU A 268 -29.731 8.878 37.970 1.00 0.00 O \\\\nATOM 3026 CB LEU A 268 -28.287 9.052 35.306 1.00 0.00 C \\\\nATOM 3027 CG LEU A 268 -27.397 10.295 35.263 1.00 0.00 C \\\\nATOM 3028 CD1 LEU A 268 -25.933 9.897 35.125 1.00 0.00 C \\\\nATOM 3029 CD2 LEU A 268 -27.819 11.219 34.125 1.00 0.00 C \\\\nATOM 3030 H LEU A 268 -29.425 6.854 35.932 1.00 0.00 H \\\\nATOM 3031 HA LEU A 268 -27.057 7.977 36.552 1.00 0.00 H \\\\nATOM 3032 HB2 LEU A 268 -28.172 8.557 34.480 1.00 0.00 H \\\\nATOM 3033 HB3 LEU A 268 -29.215 9.334 35.341 1.00 0.00 H \\\\nATOM 3034 HG LEU A 268 -27.503 10.778 36.097 1.00 0.00 H \\\\nATOM 3035 HD11 LEU A 268 -25.382 10.695 35.099 1.00 0.00 H \\\\nATOM 3036 HD12 LEU A 268 -25.674 9.350 35.883 1.00 0.00 H \\\\nATOM 3037 HD13 LEU A 268 -25.810 9.393 34.305 1.00 0.00 H \\\\nATOM 3038 HD21 LEU A 268 -27.245 12.001 34.113 1.00 0.00 H \\\\nATOM 3039 HD22 LEU A 268 -27.742 10.748 33.280 1.00 0.00 H \\\\nATOM 3040 HD23 LEU A 268 -28.739 11.496 34.257 1.00 0.00 H \\\\nATOM 3041 N ALA A 269 -27.585 9.175 38.617 1.00 0.00 N \\\\nATOM 3042 CA ALA A 269 -27.889 9.777 39.908 1.00 0.00 C \\\\nATOM 3043 C ALA A 269 -28.280 11.247 39.803 1.00 0.00 C \\\\nATOM 3044 O ALA A 269 -28.153 11.980 40.792 1.00 0.00 O \\\\nATOM 3045 CB ALA A 269 -26.694 9.624 40.852 1.00 0.00 C \\\\nATOM 3046 H ALA A 269 -26.743 9.121 38.453 1.00 0.00 H \\\\nATOM 3047 HA ALA A 269 -28.658 9.304 40.263 1.00 0.00 H \\\\nATOM 3048 HB1 ALA A 269 -26.904 10.027 41.709 1.00 0.00 H \\\\nATOM 3049 HB2 ALA A 269 -26.499 8.682 40.978 1.00 0.00 H \\\\nATOM 3050 HB3 ALA A 269 -25.920 10.066 40.469 1.00 0.00 H \\\\nATOM 3051 N MET A 270 -28.737 11.698 38.636 1.00 0.00 N \\\\nATOM 3052 CA MET A 270 -29.218 13.060 38.456 1.00 0.00 C \\\\nATOM 3053 C MET A 270 -30.410 13.049 37.511 1.00 0.00 C \\\\nATOM 3054 O MET A 270 -30.509 12.196 36.626 1.00 0.00 O \\\\nATOM 3055 CB MET A 270 -28.137 13.990 37.877 1.00 0.00 C \\\\nATOM 3056 CG MET A 270 -26.728 13.762 38.391 1.00 0.00 C \\\\nATOM 3057 SD MET A 270 -25.486 14.100 37.133 1.00 0.00 S \\\\nATOM 3058 CE MET A 270 -26.103 15.635 36.462 1.00 0.00 C \\\\nATOM 3059 H MET A 270 -28.776 11.217 37.924 1.00 0.00 H \\\\nATOM 3060 HA MET A 270 -29.467 13.399 39.330 1.00 0.00 H \\\\nATOM 3061 HB2 MET A 270 -28.131 13.891 36.912 1.00 0.00 H \\\\nATOM 3062 HB3 MET A 270 -28.388 14.908 38.066 1.00 0.00 H \\\\nATOM 3063 HG2 MET A 270 -26.570 14.330 39.161 1.00 0.00 H \\\\nATOM 3064 HG3 MET A 270 -26.640 12.844 38.693 1.00 0.00 H \\\\nATOM 3065 HE1 MET A 270 -25.513 15.940 35.755 1.00 0.00 H \\\\nATOM 3066 HE2 MET A 270 -26.993 15.497 36.103 1.00 0.00 H \\\\nATOM 3067 HE3 MET A 270 -26.138 16.304 37.163 1.00 0.00 H \\\\nATOM 3068 N SER A 271 -31.317 14.007 37.708 1.00 0.00 N \\\\nATOM 3069 CA SER A 271 -32.493 14.144 36.861 1.00 0.00 C \\\\nATOM 3070 C SER A 271 -32.345 15.245 35.821 1.00 0.00 C \\\\nATOM 3071 O SER A 271 -33.219 15.386 34.961 1.00 0.00 O \\\\nATOM 3072 CB SER A 271 -33.734 14.415 37.716 1.00 0.00 C \\\\nATOM 3073 OG SER A 271 -33.573 15.589 38.497 1.00 0.00 O \\\\nATOM 3074 H SER A 271 -31.265 14.592 38.336 1.00 0.00 H \\\\nATOM 3075 HA SER A 271 -32.592 13.304 36.385 1.00 0.00 H \\\\nATOM 3076 HB2 SER A 271 -34.511 14.509 37.143 1.00 0.00 H \\\\nATOM 3077 HB3 SER A 271 -33.901 13.657 38.298 1.00 0.00 H \\\\nATOM 3078 HG SER A 271 -32.848 15.548 38.919 1.00 0.00 H \\\\nATOM 3079 N ARG A 272 -31.261 16.016 35.874 1.00 0.00 N \\\\nATOM 3080 CA ARG A 272 -31.014 17.120 34.958 1.00 0.00 C \\\\nATOM 3081 C ARG A 272 -29.531 17.139 34.625 1.00 0.00 C \\\\nATOM 3082 O ARG A 272 -28.696 16.975 35.516 1.00 0.00 O \\\\nATOM 3083 CB ARG A 272 -31.403 18.475 35.570 1.00 0.00 C \\\\nATOM 3084 CG ARG A 272 -32.733 18.501 36.300 1.00 0.00 C \\\\nATOM 3085 CD ARG A 272 -33.444 19.828 36.099 1.00 0.00 C \\\\nATOM 3086 NE ARG A 272 -34.714 19.880 36.819 1.00 0.00 N \\\\nATOM 3087 CZ ARG A 272 -35.356 21.003 37.120 1.00 0.00 C \\\\nATOM 3088 NH1 ARG A 272 -34.853 22.175 36.757 1.00 0.00 N \\\\nATOM 3089 NH2 ARG A 272 -36.505 20.953 37.778 1.00 0.00 N \\\\nATOM 3090 H ARG A 272 -30.638 15.907 36.456 1.00 0.00 H \\\\nATOM 3091 HA ARG A 272 -31.556 16.987 34.165 1.00 0.00 H \\\\nATOM 3092 HB2 ARG A 272 -30.706 18.745 36.188 1.00 0.00 H \\\\nATOM 3093 HB3 ARG A 272 -31.427 19.138 34.862 1.00 0.00 H \\\\nATOM 3094 HG2 ARG A 272 -33.295 17.778 35.979 1.00 0.00 H \\\\nATOM 3095 HG3 ARG A 272 -32.588 18.349 37.247 1.00 0.00 H \\\\nATOM 3096 HD2 ARG A 272 -32.871 20.550 36.401 1.00 0.00 H \\\\nATOM 3097 HD3 ARG A 272 -33.603 19.969 35.153 1.00 0.00 H \\\\nATOM 3098 HE ARG A 272 -35.069 19.136 37.064 1.00 0.00 H \\\\nATOM 3099 HH11 ARG A 272 -34.110 22.209 36.326 1.00 0.00 H \\\\nATOM 3100 HH12 ARG A 272 -35.270 22.901 36.953 1.00 0.00 H \\\\nATOM 3101 HH21 ARG A 272 -36.835 20.193 38.010 1.00 0.00 H \\\\nATOM 3102 HH22 ARG A 272 -36.921 21.680 37.973 1.00 0.00 H \\\\nATOM 3103 N SER A 273 -29.197 17.378 33.362 1.00 0.00 N \\\\nATOM 3104 CA SER A 273 -27.799 17.430 32.945 1.00 0.00 C \\\\nATOM 3105 C SER A 273 -27.718 17.954 31.517 1.00 0.00 C \\\\nATOM 3106 O SER A 273 -28.732 18.164 30.845 1.00 0.00 O \\\\nATOM 3107 CB SER A 273 -27.133 16.054 33.031 1.00 0.00 C \\\\nATOM 3108 OG SER A 273 -27.191 15.392 31.780 1.00 0.00 O \\\\nATOM 3109 H SER A 273 -29.764 17.513 32.730 1.00 0.00 H \\\\nATOM 3110 HA SER A 273 -27.325 18.026 33.546 1.00 0.00 H \\\\nATOM 3111 HB2 SER A 273 -26.208 16.153 33.307 1.00 0.00 H \\\\nATOM 3112 HB3 SER A 273 -27.575 15.517 33.707 1.00 0.00 H \\\\nATOM 3113 HG SER A 273 -27.984 15.169 31.618 1.00 0.00 H \\\\nATOM 3114 N ILE A 274 -26.482 18.172 31.070 1.00 0.00 N \\\\nATOM 3115 CA ILE A 274 -26.172 18.445 29.672 1.00 0.00 C \\\\nATOM 3116 C ILE A 274 -25.645 17.158 29.054 1.00 0.00 C \\\\nATOM 3117 O ILE A 274 -24.738 16.524 29.608 1.00 0.00 O \\\\nATOM 3118 CB ILE A 274 -25.145 19.583 29.539 1.00 0.00 C \\\\nATOM 3119 CG1 ILE A 274 -25.604 20.820 30.316 1.00 0.00 C \\\\nATOM 3120 CG2 ILE A 274 -24.906 19.924 28.076 1.00 0.00 C \\\\nATOM 3121 CD1 ILE A 274 -26.937 21.366 29.864 1.00 0.00 C \\\\nATOM 3122 H ILE A 274 -25.790 18.165 31.581 1.00 0.00 H \\\\nATOM 3123 HA ILE A 274 -26.971 18.738 29.207 1.00 0.00 H \\\\nATOM 3124 HB ILE A 274 -24.306 19.280 29.920 1.00 0.00 H \\\\nATOM 3125 HG12 ILE A 274 -25.658 20.597 31.259 1.00 0.00 H \\\\nATOM 3126 HG13 ILE A 274 -24.933 21.515 30.227 1.00 0.00 H \\\\nATOM 3127 HG21 ILE A 274 -24.257 20.642 28.013 1.00 0.00 H \\\\nATOM 3128 HG22 ILE A 274 -24.568 19.142 27.612 1.00 0.00 H \\\\nATOM 3129 HG23 ILE A 274 -25.740 20.206 27.669 1.00 0.00 H \\\\nATOM 3130 HD11 ILE A 274 -27.165 22.145 30.396 1.00 0.00 H \\\\nATOM 3131 HD12 ILE A 274 -26.883 21.618 28.929 1.00 0.00 H \\\\nATOM 3132 HD13 ILE A 274 -27.620 20.687 29.977 1.00 0.00 H \\\\nATOM 3133 N GLY A 275 -26.205 16.767 27.909 1.00 0.00 N \\\\nATOM 3134 CA GLY A 275 -25.807 15.524 27.272 1.00 0.00 C \\\\nATOM 3135 C GLY A 275 -26.686 14.342 27.641 1.00 0.00 C \\\\nATOM 3136 O GLY A 275 -27.900 14.497 27.804 1.00 0.00 O \\\\nATOM 3137 H GLY A 275 -26.813 17.208 27.491 1.00 0.00 H \\\\nATOM 3138 HA2 GLY A 275 -25.825 15.643 26.309 1.00 0.00 H \\\\nATOM 3139 HA3 GLY A 275 -24.890 15.324 27.516 1.00 0.00 H \\\\nATOM 3140 N ASP A 276 -26.076 13.164 27.790 1.00 0.00 N \\\\nATOM 3141 CA ASP A 276 -26.773 11.917 28.123 1.00 0.00 C \\\\nATOM 3142 C ASP A 276 -28.035 11.726 27.283 1.00 0.00 C \\\\nATOM 3143 O ASP A 276 -29.139 11.546 27.803 1.00 0.00 O \\\\nATOM 3144 CB ASP A 276 -27.113 11.864 29.611 1.00 0.00 C \\\\nATOM 3145 CG ASP A 276 -25.924 12.165 30.498 1.00 0.00 C \\\\nATOM 3146 OD1 ASP A 276 -25.029 11.302 30.612 1.00 0.00 O \\\\nATOM 3147 OD2 ASP A 276 -25.891 13.261 31.096 1.00 0.00 O \\\\nATOM 3148 H ASP A 276 -25.227 13.065 27.698 1.00 0.00 H \\\\nATOM 3149 HA ASP A 276 -26.168 11.188 27.914 1.00 0.00 H \\\\nATOM 3150 HB2 ASP A 276 -27.820 12.500 29.799 1.00 0.00 H \\\\nATOM 3151 HB3 ASP A 276 -27.458 10.984 29.828 1.00 0.00 H \\\\nATOM 3152 N ARG A 277 -27.867 11.767 25.958 1.00 0.00 N \\\\nATOM 3153 CA ARG A 277 -29.024 11.659 25.075 1.00 0.00 C \\\\nATOM 3154 C ARG A 277 -29.725 10.307 25.174 1.00 0.00 C \\\\nATOM 3155 O ARG A 277 -30.876 10.192 24.749 1.00 0.00 O \\\\nATOM 3156 CB ARG A 277 -28.629 11.947 23.623 1.00 0.00 C \\\\nATOM 3157 CG ARG A 277 -27.638 10.984 23.001 1.00 0.00 C \\\\nATOM 3158 CD ARG A 277 -27.379 11.384 21.556 1.00 0.00 C \\\\nATOM 3159 NE ARG A 277 -26.241 10.692 20.962 1.00 0.00 N \\\\nATOM 3160 CZ ARG A 277 -24.975 11.053 21.134 1.00 0.00 C \\\\nATOM 3161 NH1 ARG A 277 -24.680 12.097 21.895 1.00 0.00 N \\\\nATOM 3162 NH2 ARG A 277 -24.000 10.366 20.552 1.00 0.00 N \\\\nATOM 3163 H ARG A 277 -27.109 11.855 25.561 1.00 0.00 H \\\\nATOM 3164 HA ARG A 277 -29.659 12.329 25.373 1.00 0.00 H \\\\nATOM 3165 HB2 ARG A 277 -29.434 11.949 23.082 1.00 0.00 H \\\\nATOM 3166 HB3 ARG A 277 -28.255 12.841 23.579 1.00 0.00 H \\\\nATOM 3167 HG2 ARG A 277 -26.808 10.991 23.502 1.00 0.00 H \\\\nATOM 3168 HG3 ARG A 277 -27.985 10.079 23.039 1.00 0.00 H \\\\nATOM 3169 HD2 ARG A 277 -28.172 11.201 21.029 1.00 0.00 H \\\\nATOM 3170 HD3 ARG A 277 -27.226 12.341 21.514 1.00 0.00 H \\\\nATOM 3171 HE ARG A 277 -26.400 10.006 20.469 1.00 0.00 H \\\\nATOM 3172 HH11 ARG A 277 -25.309 12.541 22.278 1.00 0.00 H \\\\nATOM 3173 HH12 ARG A 277 -23.860 12.330 22.006 1.00 0.00 H \\\\nATOM 3174 HH21 ARG A 277 -24.187 9.685 20.062 1.00 0.00 H \\\\nATOM 3175 HH22 ARG A 277 -23.181 10.602 20.665 1.00 0.00 H \\\\nATOM 3176 N TYR A 278 -29.062 9.272 25.691 1.00 0.00 N \\\\nATOM 3177 CA TYR A 278 -29.730 7.978 25.812 1.00 0.00 C \\\\nATOM 3178 C TYR A 278 -30.751 7.915 26.948 1.00 0.00 C \\\\nATOM 3179 O TYR A 278 -31.527 6.954 26.998 1.00 0.00 O \\\\nATOM 3180 CB TYR A 278 -28.692 6.861 25.963 1.00 0.00 C \\\\nATOM 3181 CG TYR A 278 -28.151 6.659 27.366 1.00 0.00 C \\\\nATOM 3182 CD1 TYR A 278 -27.346 7.618 27.973 1.00 0.00 C \\\\nATOM 3183 CD2 TYR A 278 -28.414 5.488 28.071 1.00 0.00 C \\\\nATOM 3184 CE1 TYR A 278 -26.841 7.427 29.250 1.00 0.00 C \\\\nATOM 3185 CE2 TYR A 278 -27.910 5.290 29.349 1.00 0.00 C \\\\nATOM 3186 CZ TYR A 278 -27.125 6.262 29.930 1.00 0.00 C \\\\nATOM 3187 OH TYR A 278 -26.617 6.077 31.195 1.00 0.00 O \\\\nATOM 3188 H TYR A 278 -28.249 9.296 25.970 1.00 0.00 H \\\\nATOM 3189 HA TYR A 278 -30.234 7.853 24.993 1.00 0.00 H \\\\nATOM 3190 HB2 TYR A 278 -29.089 6.028 25.663 1.00 0.00 H \\\\nATOM 3191 HB3 TYR A 278 -27.948 7.050 25.370 1.00 0.00 H \\\\nATOM 3192 HD1 TYR A 278 -27.143 8.401 27.514 1.00 0.00 H \\\\nATOM 3193 HD2 TYR A 278 -28.937 4.826 27.679 1.00 0.00 H \\\\nATOM 3194 HE1 TYR A 278 -26.313 8.082 29.646 1.00 0.00 H \\\\nATOM 3195 HE2 TYR A 278 -28.101 4.506 29.811 1.00 0.00 H \\\\nATOM 3196 HH TYR A 278 -26.142 5.385 31.208 1.00 0.00 H \\\\nATOM 3197 N LEU A 279 -30.778 8.905 27.846 1.00 0.00 N \\\\nATOM 3198 CA LEU A 279 -31.681 8.926 28.998 1.00 0.00 C \\\\nATOM 3199 C LEU A 279 -32.795 9.961 28.852 1.00 0.00 C \\\\nATOM 3200 O LEU A 279 -33.380 10.410 29.844 1.00 0.00 O \\\\nATOM 3201 CB LEU A 279 -30.902 9.195 30.277 1.00 0.00 C \\\\nATOM 3202 CG LEU A 279 -30.230 7.958 30.852 1.00 0.00 C \\\\nATOM 3203 CD1 LEU A 279 -29.376 8.348 32.031 1.00 0.00 C \\\\nATOM 3204 CD2 LEU A 279 -31.274 6.924 31.248 1.00 0.00 C \\\\nATOM 3205 H LEU A 279 -30.264 9.593 27.800 1.00 0.00 H \\\\nATOM 3206 HA LEU A 279 -32.097 8.051 29.042 1.00 0.00 H \\\\nATOM 3207 HB2 LEU A 279 -30.226 9.868 30.100 1.00 0.00 H \\\\nATOM 3208 HB3 LEU A 279 -31.504 9.565 30.942 1.00 0.00 H \\\\nATOM 3209 HG LEU A 279 -29.659 7.559 30.177 1.00 0.00 H \\\\nATOM 3210 HD11 LEU A 279 -28.948 7.558 32.396 1.00 0.00 H \\\\nATOM 3211 HD12 LEU A 279 -28.698 8.979 31.745 1.00 0.00 H \\\\nATOM 3212 HD13 LEU A 279 -29.932 8.758 32.712 1.00 0.00 H \\\\nATOM 3213 HD21 LEU A 279 -30.832 6.141 31.613 1.00 0.00 H \\\\nATOM 3214 HD22 LEU A 279 -31.866 7.302 31.917 1.00 0.00 H \\\\nATOM 3215 HD23 LEU A 279 -31.790 6.669 30.467 1.00 0.00 H \\\\nATOM 3216 N LYS A 280 -33.093 10.309 27.656 1.00 0.00 N \\\\nATOM 3217 CA LYS A 280 -34.000 11.236 27.008 1.00 0.00 C \\\\nATOM 3218 C LYS A 280 -35.375 10.571 26.849 1.00 0.00 C \\\\nATOM 3219 O LYS A 280 -35.453 9.430 26.387 1.00 0.00 O \\\\nATOM 3220 CB LYS A 280 -33.341 11.562 25.640 1.00 0.00 C \\\\nATOM 3221 CG LYS A 280 -32.112 12.560 25.597 1.00 0.00 C \\\\nATOM 3222 CD LYS A 280 -32.573 13.982 25.088 1.00 0.00 C \\\\nATOM 3223 CE LYS A 280 -31.827 15.209 25.705 1.00 0.00 C \\\\nATOM 3224 NZ LYS A 280 -30.408 14.953 26.178 1.00 0.00 N \\\\nATOM 3225 H LYS A 280 -32.659 9.907 27.031 1.00 0.00 H \\\\nATOM 3226 HA LYS A 280 -34.146 12.050 27.515 1.00 0.00 H \\\\nATOM 3227 HB2 LYS A 280 -33.051 10.724 25.248 1.00 0.00 H \\\\nATOM 3228 HB3 LYS A 280 -34.031 11.922 25.061 1.00 0.00 H \\\\nATOM 3229 HG2 LYS A 280 -31.720 12.638 26.481 1.00 0.00 H \\\\nATOM 3230 HG3 LYS A 280 -31.423 12.208 25.012 1.00 0.00 H \\\\nATOM 3231 HD2 LYS A 280 -32.464 14.011 24.125 1.00 0.00 H \\\\nATOM 3232 HD3 LYS A 280 -33.521 14.078 25.269 1.00 0.00 H \\\\nATOM 3233 HE2 LYS A 280 -31.806 15.919 25.044 1.00 0.00 H \\\\nATOM 3234 HE3 LYS A 280 -32.346 15.537 26.456 1.00 0.00 H \\\\nATOM 3235 HZ1 LYS A 280 -30.021 15.726 26.390 1.00 0.00 H \\\\nATOM 3236 HZ2 LYS A 280 -30.424 14.424 26.893 1.00 0.00 H \\\\nATOM 3237 HZ3 LYS A 280 -29.945 14.559 25.528 1.00 0.00 H \\\\nATOM 3238 N PRO A 281 -36.487 11.242 27.241 1.00 0.00 N \\\\nATOM 3239 CA PRO A 281 -36.628 12.628 27.680 1.00 0.00 C \\\\nATOM 3240 C PRO A 281 -36.610 12.795 29.200 1.00 0.00 C \\\\nATOM 3241 O PRO A 281 -37.147 13.786 29.681 1.00 0.00 O \\\\nATOM 3242 CB PRO A 281 -38.000 13.000 27.126 1.00 0.00 C \\\\nATOM 3243 CG PRO A 281 -38.795 11.730 27.344 1.00 0.00 C \\\\nATOM 3244 CD PRO A 281 -37.809 10.589 27.150 1.00 0.00 C \\\\nATOM 3245 HA PRO A 281 -35.893 13.182 27.373 1.00 0.00 H \\\\nATOM 3246 HB2 PRO A 281 -38.388 13.754 27.597 1.00 0.00 H \\\\nATOM 3247 HB3 PRO A 281 -37.957 13.243 26.188 1.00 0.00 H \\\\nATOM 3248 HG2 PRO A 281 -39.181 11.709 28.233 1.00 0.00 H \\\\nATOM 3249 HG3 PRO A 281 -39.530 11.666 26.714 1.00 0.00 H \\\\nATOM 3250 HD2 PRO A 281 -37.916 9.907 27.831 1.00 0.00 H \\\\nATOM 3251 HD3 PRO A 281 -37.933 10.154 26.292 1.00 0.00 H \\\\nATOM 3252 N PHE A 282 -36.025 11.846 29.939 1.00 0.00 N \\\\nATOM 3253 CA PHE A 282 -36.114 11.895 31.396 1.00 0.00 C \\\\nATOM 3254 C PHE A 282 -35.091 12.856 31.998 1.00 0.00 C \\\\nATOM 3255 O PHE A 282 -35.397 13.558 32.967 1.00 0.00 O \\\\nATOM 3256 CB PHE A 282 -35.936 10.491 31.983 1.00 0.00 C \\\\nATOM 3257 CG PHE A 282 -36.737 9.436 31.282 1.00 0.00 C \\\\nATOM 3258 CD1 PHE A 282 -38.112 9.550 31.177 1.00 0.00 C \\\\nATOM 3259 CD2 PHE A 282 -36.113 8.338 30.710 1.00 0.00 C \\\\nATOM 3260 CE1 PHE A 282 -38.854 8.585 30.520 1.00 0.00 C \\\\nATOM 3261 CE2 PHE A 282 -36.852 7.369 30.052 1.00 0.00 C \\\\nATOM 3262 CZ PHE A 282 -38.223 7.494 29.957 1.00 0.00 C \\\\nATOM 3263 H PHE A 282 -35.582 11.181 29.622 1.00 0.00 H \\\\nATOM 3264 HA PHE A 282 -36.995 12.229 31.625 1.00 0.00 H \\\\nATOM 3265 HB2 PHE A 282 -34.997 10.251 31.945 1.00 0.00 H \\\\nATOM 3266 HB3 PHE A 282 -36.187 10.507 32.920 1.00 0.00 H \\\\nATOM 3267 HD1 PHE A 282 -38.542 10.284 31.553 1.00 0.00 H \\\\nATOM 3268 HD2 PHE A 282 -35.189 8.251 30.769 1.00 0.00 H \\\\nATOM 3269 HE1 PHE A 282 -39.778 8.671 30.458 1.00 0.00 H \\\\nATOM 3270 HE2 PHE A 282 -36.425 6.634 29.674 1.00 0.00 H \\\\nATOM 3271 HZ PHE A 282 -38.721 6.845 29.515 1.00 0.00 H \\\\nATOM 3272 N VAL A 283 -33.877 12.895 31.457 1.00 0.00 N \\\\nATOM 3273 CA VAL A 283 -32.824 13.788 31.933 1.00 0.00 C \\\\nATOM 3274 C VAL A 283 -32.810 15.006 31.018 1.00 0.00 C \\\\nATOM 3275 O VAL A 283 -32.441 14.905 29.843 1.00 0.00 O \\\\nATOM 3276 CB VAL A 283 -31.458 13.089 31.964 1.00 0.00 C \\\\nATOM 3277 CG1 VAL A 283 -30.372 14.067 32.387 1.00 0.00 C \\\\nATOM 3278 CG2 VAL A 283 -31.495 11.893 32.903 1.00 0.00 C \\\\nATOM 3279 H VAL A 283 -33.639 12.399 30.796 1.00 0.00 H \\\\nATOM 3280 HA VAL A 283 -33.004 14.058 32.847 1.00 0.00 H \\\\nATOM 3281 HB VAL A 283 -31.253 12.771 31.071 1.00 0.00 H \\\\nATOM 3282 HG11 VAL A 283 -29.515 13.613 32.402 1.00 0.00 H \\\\nATOM 3283 HG12 VAL A 283 -30.336 14.803 31.757 1.00 0.00 H \\\\nATOM 3284 HG13 VAL A 283 -30.572 14.410 33.272 1.00 0.00 H \\\\nATOM 3285 HG21 VAL A 283 -30.626 11.462 32.912 1.00 0.00 H \\\\nATOM 3286 HG22 VAL A 283 -31.717 12.191 33.799 1.00 0.00 H \\\\nATOM 3287 HG23 VAL A 283 -32.165 11.262 32.597 1.00 0.00 H \\\\nATOM 3288 N ILE A 284 -33.210 16.158 31.552 1.00 0.00 N \\\\nATOM 3289 CA ILE A 284 -33.406 17.363 30.747 1.00 0.00 C \\\\nATOM 3290 C ILE A 284 -32.317 18.386 31.054 1.00 0.00 C \\\\nATOM 3291 O ILE A 284 -31.698 18.327 32.126 1.00 0.00 O \\\\nATOM 3292 CB ILE A 284 -34.802 17.961 30.988 1.00 0.00 C \\\\nATOM 3293 CG1 ILE A 284 -35.001 18.261 32.476 1.00 0.00 C \\\\nATOM 3294 CG2 ILE A 284 -35.879 17.019 30.481 1.00 0.00 C \\\\nATOM 3295 CD1 ILE A 284 -36.309 18.962 32.786 1.00 0.00 C \\\\nATOM 3296 H ILE A 284 -33.375 16.263 32.389 1.00 0.00 H \\\\nATOM 3297 HA ILE A 284 -33.344 17.120 29.810 1.00 0.00 H \\\\nATOM 3298 HB ILE A 284 -34.872 18.794 30.495 1.00 0.00 H \\\\nATOM 3299 HG12 ILE A 284 -34.963 17.429 32.973 1.00 0.00 H \\\\nATOM 3300 HG13 ILE A 284 -34.266 18.812 32.788 1.00 0.00 H \\\\nATOM 3301 HG21 ILE A 284 -36.752 17.410 30.640 1.00 0.00 H \\\\nATOM 3302 HG22 ILE A 284 -35.759 16.872 29.530 1.00 0.00 H \\\\nATOM 3303 HG23 ILE A 284 -35.815 16.172 30.949 1.00 0.00 H \\\\nATOM 3304 HD11 ILE A 284 -36.372 19.122 33.741 1.00 0.00 H \\\\nATOM 3305 HD12 ILE A 284 -36.342 19.809 32.314 1.00 0.00 H \\\\nATOM 3306 HD13 ILE A 284 -37.050 18.404 32.502 1.00 0.00 H \\\\nATOM 3307 N PRO A 285 -32.042 19.331 30.154 1.00 0.00 N \\\\nATOM 3308 CA PRO A 285 -31.056 20.385 30.435 1.00 0.00 C \\\\nATOM 3309 C PRO A 285 -31.610 21.678 31.019 1.00 0.00 C \\\\nATOM 3310 O PRO A 285 -30.833 22.625 31.195 1.00 0.00 O \\\\nATOM 3311 CB PRO A 285 -30.454 20.641 29.045 1.00 0.00 C \\\\nATOM 3312 CG PRO A 285 -31.560 20.343 28.095 1.00 0.00 C \\\\nATOM 3313 CD PRO A 285 -32.435 19.298 28.733 1.00 0.00 C \\\\nATOM 3314 HA PRO A 285 -30.436 20.097 31.123 1.00 0.00 H \\\\nATOM 3315 HB2 PRO A 285 -30.150 21.558 28.956 1.00 0.00 H \\\\nATOM 3316 HB3 PRO A 285 -29.686 20.071 28.883 1.00 0.00 H \\\\nATOM 3317 HG2 PRO A 285 -32.071 21.145 27.904 1.00 0.00 H \\\\nATOM 3318 HG3 PRO A 285 -31.207 20.023 27.250 1.00 0.00 H \\\\nATOM 3319 HD2 PRO A 285 -33.376 19.504 28.619 1.00 0.00 H \\\\nATOM 3320 HD3 PRO A 285 -32.287 18.423 28.343 1.00 0.00 H \\\\nATOM 3321 N LYS A 286 -32.912 21.755 31.303 1.00 0.00 N \\\\nATOM 3322 CA LYS A 286 -33.552 22.885 31.975 1.00 0.00 C \\\\nATOM 3323 C LYS A 286 -32.856 23.281 33.274 1.00 0.00 C \\\\nATOM 3324 O LYS A 286 -32.870 22.510 34.242 1.00 0.00 O \\\\nATOM 3325 CB LYS A 286 -35.021 22.573 32.259 1.00 0.00 C \\\\nATOM 3326 CG LYS A 286 -35.833 23.796 32.658 1.00 0.00 C \\\\nATOM 3327 CD LYS A 286 -37.316 23.489 32.702 1.00 0.00 C \\\\nATOM 3328 CE LYS A 286 -38.119 24.721 33.085 1.00 0.00 C \\\\nATOM 3329 NZ LYS A 286 -37.777 25.890 32.229 1.00 0.00 N \\\\nATOM 3330 H LYS A 286 -33.465 21.128 31.102 1.00 0.00 H \\\\nATOM 3331 HA LYS A 286 -33.481 23.639 31.368 1.00 0.00 H \\\\nATOM 3332 HB2 LYS A 286 -35.418 22.173 31.470 1.00 0.00 H \\\\nATOM 3333 HB3 LYS A 286 -35.073 21.913 32.968 1.00 0.00 H \\\\nATOM 3334 HG2 LYS A 286 -35.541 24.110 33.528 1.00 0.00 H \\\\nATOM 3335 HG3 LYS A 286 -35.669 24.514 32.027 1.00 0.00 H \\\\nATOM 3336 HD2 LYS A 286 -37.608 23.166 31.835 1.00 0.00 H \\\\nATOM 3337 HD3 LYS A 286 -37.483 22.779 33.341 1.00 0.00 H \\\\nATOM 3338 HE2 LYS A 286 -39.066 24.528 33.006 1.00 0.00 H \\\\nATOM 3339 HE3 LYS A 286 -37.951 24.941 34.015 1.00 0.00 H \\\\nATOM 3340 HZ1 LYS A 286 -38.475 26.441 32.186 1.00 0.00 H \\\\nATOM 3341 HZ2 LYS A 286 -37.081 26.320 32.578 1.00 0.00 H \\\\nATOM 3342 HZ3 LYS A 286 -37.571 25.608 31.410 1.00 0.00 H \\\\nATOM 3343 N PRO A 287 -32.240 24.458 33.338 1.00 0.00 N \\\\nATOM 3344 CA PRO A 287 -31.596 24.890 34.581 1.00 0.00 C \\\\nATOM 3345 C PRO A 287 -32.585 25.520 35.554 1.00 0.00 C \\\\nATOM 3346 O PRO A 287 -33.637 26.038 35.178 1.00 0.00 O \\\\nATOM 3347 CB PRO A 287 -30.573 25.921 34.098 1.00 0.00 C \\\\nATOM 3348 CG PRO A 287 -31.214 26.523 32.888 1.00 0.00 C \\\\nATOM 3349 CD PRO A 287 -32.084 25.450 32.260 1.00 0.00 C \\\\nATOM 3350 HA PRO A 287 -31.204 24.151 35.071 1.00 0.00 H \\\\nATOM 3351 HB2 PRO A 287 -30.395 26.591 34.777 1.00 0.00 H \\\\nATOM 3352 HB3 PRO A 287 -29.724 25.505 33.881 1.00 0.00 H \\\\nATOM 3353 HG2 PRO A 287 -31.747 27.296 33.132 1.00 0.00 H \\\\nATOM 3354 HG3 PRO A 287 -30.541 26.829 32.260 1.00 0.00 H \\\\nATOM 3355 HD2 PRO A 287 -32.940 25.806 31.976 1.00 0.00 H \\\\nATOM 3356 HD3 PRO A 287 -31.663 25.063 31.476 1.00 0.00 H \\\\nATOM 3357 N GLU A 288 -32.213 25.471 36.831 1.00 0.00 N \\\\nATOM 3358 CA GLU A 288 -32.953 26.123 37.906 1.00 0.00 C \\\\nATOM 3359 C GLU A 288 -32.257 27.435 38.255 1.00 0.00 C \\\\nATOM 3360 O GLU A 288 -31.077 27.436 38.622 1.00 0.00 O \\\\nATOM 3361 CB GLU A 288 -33.040 25.209 39.128 1.00 0.00 C \\\\nATOM 3362 CG GLU A 288 -34.092 25.603 40.150 1.00 0.00 C \\\\nATOM 3363 CD GLU A 288 -34.530 24.429 41.009 1.00 0.00 C \\\\nATOM 3364 OE1 GLU A 288 -35.664 23.940 40.818 1.00 0.00 O \\\\nATOM 3365 OE2 GLU A 288 -33.736 23.990 41.868 1.00 0.00 O \\\\nATOM 3366 H GLU A 288 -31.512 25.051 37.100 1.00 0.00 H \\\\nATOM 3367 HA GLU A 288 -33.860 26.308 37.615 1.00 0.00 H \\\\nATOM 3368 HB2 GLU A 288 -33.223 24.305 38.827 1.00 0.00 H \\\\nATOM 3369 HB3 GLU A 288 -32.174 25.192 39.565 1.00 0.00 H \\\\nATOM 3370 HG2 GLU A 288 -33.739 26.304 40.720 1.00 0.00 H \\\\nATOM 3371 HG3 GLU A 288 -34.863 25.971 39.691 1.00 0.00 H \\\\nATOM 3372 N VAL A 289 -32.987 28.543 38.150 1.00 0.00 N \\\\nATOM 3373 CA VAL A 289 -32.417 29.882 38.256 1.00 0.00 C \\\\nATOM 3374 C VAL A 289 -32.863 30.533 39.559 1.00 0.00 C \\\\nATOM 3375 O VAL A 289 -34.033 30.436 39.946 1.00 0.00 O \\\\nATOM 3376 CB VAL A 289 -32.822 30.751 37.049 1.00 0.00 C \\\\nATOM 3377 CG1 VAL A 289 -32.218 32.145 37.159 1.00 0.00 C \\\\nATOM 3378 CG2 VAL A 289 -32.405 30.081 35.749 1.00 0.00 C \\\\nATOM 3379 H VAL A 289 -33.836 28.537 38.014 1.00 0.00 H \\\\nATOM 3380 HA VAL A 289 -31.450 29.807 38.256 1.00 0.00 H \\\\nATOM 3381 HB VAL A 289 -33.788 30.843 37.049 1.00 0.00 H \\\\nATOM 3382 HG11 VAL A 289 -32.484 32.675 36.391 1.00 0.00 H \\\\nATOM 3383 HG12 VAL A 289 -32.534 32.572 37.971 1.00 0.00 H \\\\nATOM 3384 HG13 VAL A 289 -31.251 32.078 37.185 1.00 0.00 H \\\\nATOM 3385 HG21 VAL A 289 -32.666 30.638 34.999 1.00 0.00 H \\\\nATOM 3386 HG22 VAL A 289 -31.443 29.959 35.742 1.00 0.00 H \\\\nATOM 3387 HG23 VAL A 289 -32.840 29.217 35.676 1.00 0.00 H \\\\nATOM 3388 N MET A 290 -31.925 31.199 40.236 1.00 0.00 N \\\\nATOM 3389 CA MET A 290 -32.235 31.985 41.427 1.00 0.00 C \\\\nATOM 3390 C MET A 290 -31.484 33.307 41.359 1.00 0.00 C \\\\nATOM 3391 O MET A 290 -30.253 33.320 41.249 1.00 0.00 O \\\\nATOM 3392 CB MET A 290 -31.885 31.236 42.715 1.00 0.00 C \\\\nATOM 3393 CG MET A 290 -32.826 31.577 43.862 1.00 0.00 C \\\\nATOM 3394 SD MET A 290 -32.317 30.880 45.439 1.00 0.00 S \\\\nATOM 3395 CE MET A 290 -30.672 31.559 45.560 1.00 0.00 C \\\\nATOM 3396 H MET A 290 -31.094 31.206 40.016 1.00 0.00 H \\\\nATOM 3397 HA MET A 290 -33.191 32.148 41.446 1.00 0.00 H \\\\nATOM 3398 HB2 MET A 290 -31.916 30.281 42.549 1.00 0.00 H \\\\nATOM 3399 HB3 MET A 290 -30.975 31.450 42.973 1.00 0.00 H \\\\nATOM 3400 HG2 MET A 290 -32.885 32.542 43.947 1.00 0.00 H \\\\nATOM 3401 HG3 MET A 290 -33.716 31.256 43.647 1.00 0.00 H \\\\nATOM 3402 HE1 MET A 290 -30.259 31.261 46.385 1.00 0.00 H \\\\nATOM 3403 HE2 MET A 290 -30.141 31.258 44.806 1.00 0.00 H \\\\nATOM 3404 HE3 MET A 290 -30.720 32.528 45.554 1.00 0.00 H \\\\nATOM 3405 N VAL A 291 -32.224 34.411 41.420 1.00 0.00 N \\\\nATOM 3406 CA VAL A 291 -31.663 35.758 41.418 1.00 0.00 C \\\\nATOM 3407 C VAL A 291 -31.587 36.250 42.860 1.00 0.00 C \\\\nATOM 3408 O VAL A 291 -32.619 36.380 43.529 1.00 0.00 O \\\\nATOM 3409 CB VAL A 291 -32.509 36.706 40.553 1.00 0.00 C \\\\nATOM 3410 CG1 VAL A 291 -32.021 38.136 40.679 1.00 0.00 C \\\\nATOM 3411 CG2 VAL A 291 -32.495 36.251 39.103 1.00 0.00 C \\\\nATOM 3412 H VAL A 291 -33.083 34.397 41.465 1.00 0.00 H \\\\nATOM 3413 HA VAL A 291 -30.773 35.742 41.032 1.00 0.00 H \\\\nATOM 3414 HB VAL A 291 -33.424 36.678 40.873 1.00 0.00 H \\\\nATOM 3415 HG11 VAL A 291 -32.568 38.715 40.126 1.00 0.00 H \\\\nATOM 3416 HG12 VAL A 291 -32.084 38.419 41.605 1.00 0.00 H \\\\nATOM 3417 HG13 VAL A 291 -31.097 38.190 40.387 1.00 0.00 H \\\\nATOM 3418 HG21 VAL A 291 -33.032 36.857 38.568 1.00 0.00 H \\\\nATOM 3419 HG22 VAL A 291 -31.583 36.250 38.773 1.00 0.00 H \\\\nATOM 3420 HG23 VAL A 291 -32.861 35.355 39.041 1.00 0.00 H \\\\nATOM 3421 N VAL A 292 -30.380 36.523 43.344 1.00 0.00 N \\\\nATOM 3422 CA VAL A 292 -30.167 37.017 44.701 1.00 0.00 C \\\\nATOM 3423 C VAL A 292 -29.439 38.356 44.641 1.00 0.00 C \\\\nATOM 3424 O VAL A 292 -28.351 38.446 44.067 1.00 0.00 O \\\\nATOM 3425 CB VAL A 292 -29.390 36.021 45.579 1.00 0.00 C \\\\nATOM 3426 CG1 VAL A 292 -30.324 34.972 46.139 1.00 0.00 C \\\\nATOM 3427 CG2 VAL A 292 -28.262 35.368 44.802 1.00 0.00 C \\\\nATOM 3428 H VAL A 292 -29.655 36.426 42.891 1.00 0.00 H \\\\nATOM 3429 HA VAL A 292 -31.037 37.129 45.115 1.00 0.00 H \\\\nATOM 3430 HB VAL A 292 -28.997 36.514 46.316 1.00 0.00 H \\\\nATOM 3431 HG11 VAL A 292 -29.821 34.352 46.690 1.00 0.00 H \\\\nATOM 3432 HG12 VAL A 292 -31.007 35.401 46.677 1.00 0.00 H \\\\nATOM 3433 HG13 VAL A 292 -30.743 34.489 45.410 1.00 0.00 H \\\\nATOM 3434 HG21 VAL A 292 -27.790 34.746 45.378 1.00 0.00 H \\\\nATOM 3435 HG22 VAL A 292 -28.627 34.890 44.041 1.00 0.00 H \\\\nATOM 3436 HG23 VAL A 292 -27.647 36.050 44.490 1.00 0.00 H \\\\nATOM 3437 N PRO A 293 -30.005 39.424 45.205 1.00 0.00 N \\\\nATOM 3438 CA PRO A 293 -29.279 40.700 45.278 1.00 0.00 C \\\\nATOM 3439 C PRO A 293 -28.201 40.691 46.354 1.00 0.00 C \\\\nATOM 3440 O PRO A 293 -28.393 40.160 47.450 1.00 0.00 O \\\\nATOM 3441 CB PRO A 293 -30.381 41.715 45.599 1.00 0.00 C \\\\nATOM 3442 CG PRO A 293 -31.420 40.916 46.314 1.00 0.00 C \\\\nATOM 3443 CD PRO A 293 -31.378 39.530 45.728 1.00 0.00 C \\\\nATOM 3444 HA PRO A 293 -28.801 40.900 44.458 1.00 0.00 H \\\\nATOM 3445 HB2 PRO A 293 -30.047 42.438 46.153 1.00 0.00 H \\\\nATOM 3446 HB3 PRO A 293 -30.737 42.118 44.792 1.00 0.00 H \\\\nATOM 3447 HG2 PRO A 293 -31.241 40.893 47.267 1.00 0.00 H \\\\nATOM 3448 HG3 PRO A 293 -32.298 41.312 46.200 1.00 0.00 H \\\\nATOM 3449 HD2 PRO A 293 -31.559 38.852 46.398 1.00 0.00 H \\\\nATOM 3450 HD3 PRO A 293 -32.038 39.418 45.026 1.00 0.00 H \\\\nATOM 3451 N ARG A 294 -27.053 41.282 46.020 1.00 0.00 N \\\\nATOM 3452 CA ARG A 294 -25.907 41.341 46.926 1.00 0.00 C \\\\nATOM 3453 C ARG A 294 -26.124 42.390 48.026 1.00 0.00 C \\\\nATOM 3454 O ARG A 294 -26.328 43.571 47.734 1.00 0.00 O \\\\nATOM 3455 CB ARG A 294 -24.635 41.634 46.124 1.00 0.00 C \\\\nATOM 3456 CG ARG A 294 -24.423 40.692 44.940 1.00 0.00 C \\\\nATOM 3457 CD ARG A 294 -23.210 41.092 44.111 1.00 0.00 C \\\\nATOM 3458 NE ARG A 294 -22.033 41.293 44.950 1.00 0.00 N \\\\nATOM 3459 CZ ARG A 294 -20.808 41.532 44.492 1.00 0.00 C \\\\nATOM 3460 NH1 ARG A 294 -20.585 41.605 43.188 1.00 0.00 N \\\\nATOM 3461 NH2 ARG A 294 -19.806 41.700 45.345 1.00 0.00 N \\\\nATOM 3462 H ARG A 294 -26.918 41.661 45.260 1.00 0.00 H \\\\nATOM 3463 HA ARG A 294 -25.809 40.482 47.366 1.00 0.00 H \\\\nATOM 3464 HB2 ARG A 294 -24.671 42.547 45.798 1.00 0.00 H \\\\nATOM 3465 HB3 ARG A 294 -23.869 41.574 46.716 1.00 0.00 H \\\\nATOM 3466 HG2 ARG A 294 -24.309 39.785 45.264 1.00 0.00 H \\\\nATOM 3467 HG3 ARG A 294 -25.214 40.695 44.379 1.00 0.00 H \\\\nATOM 3468 HD2 ARG A 294 -23.026 40.404 43.452 1.00 0.00 H \\\\nATOM 3469 HD3 ARG A 294 -23.404 41.908 43.623 1.00 0.00 H \\\\nATOM 3470 HE ARG A 294 -22.140 41.254 45.802 1.00 0.00 H \\\\nATOM 3471 HH11 ARG A 294 -21.234 41.498 42.634 1.00 0.00 H \\\\nATOM 3472 HH12 ARG A 294 -19.791 41.760 42.896 1.00 0.00 H \\\\nATOM 3473 HH21 ARG A 294 -19.950 41.654 46.192 1.00 0.00 H \\\\nATOM 3474 HH22 ARG A 294 -19.013 41.855 45.051 1.00 0.00 H \\\\nATOM 3475 N ALA A 295 -26.076 41.948 49.278 1.00 0.00 N \\\\nATOM 3476 CA ALA A 295 -26.261 42.842 50.414 1.00 0.00 C \\\\nATOM 3477 C ALA A 295 -24.948 43.034 51.165 1.00 0.00 C \\\\nATOM 3478 O ALA A 295 -24.256 42.065 51.479 1.00 0.00 O \\\\nATOM 3479 CB ALA A 295 -27.334 42.300 51.346 1.00 0.00 C \\\\nATOM 3480 H ALA A 295 -25.936 41.127 49.492 1.00 0.00 H \\\\nATOM 3481 HA ALA A 295 -26.550 43.706 50.081 1.00 0.00 H \\\\nATOM 3482 HB1 ALA A 295 -27.446 42.904 52.096 1.00 0.00 H \\\\nATOM 3483 HB2 ALA A 295 -28.173 42.224 50.865 1.00 0.00 H \\\\nATOM 3484 HB3 ALA A 295 -27.068 41.426 51.672 1.00 0.00 H \\\\nATOM 3485 N LYS A 296 -24.610 44.288 51.447 1.00 0.00 N \\\\nATOM 3486 CA LYS A 296 -23.378 44.608 52.159 1.00 0.00 C \\\\nATOM 3487 C LYS A 296 -23.176 43.685 53.355 1.00 0.00 C \\\\nATOM 3488 O LYS A 296 -23.149 44.134 54.501 1.00 0.00 O \\\\nATOM 3489 CB LYS A 296 -23.390 46.068 52.618 1.00 0.00 C \\\\nATOM 3490 CG LYS A 296 -24.464 46.388 53.645 1.00 0.00 C \\\\nATOM 3491 CD LYS A 296 -23.963 47.385 54.676 1.00 0.00 C \\\\nATOM 3492 CE LYS A 296 -23.037 46.721 55.682 1.00 0.00 C \\\\nATOM 3493 NZ LYS A 296 -22.011 47.668 56.202 1.00 0.00 N \\\\nATOM 3494 H LYS A 296 -25.084 44.973 51.233 1.00 0.00 H \\\\nATOM 3495 HA LYS A 296 -22.638 44.475 51.546 1.00 0.00 H \\\\nATOM 3496 HB2 LYS A 296 -22.522 46.286 52.993 1.00 0.00 H \\\\nATOM 3497 HB3 LYS A 296 -23.516 46.639 51.844 1.00 0.00 H \\\\nATOM 3498 HG2 LYS A 296 -25.246 46.748 53.197 1.00 0.00 H \\\\nATOM 3499 HG3 LYS A 296 -24.742 45.572 54.090 1.00 0.00 H \\\\nATOM 3500 HD2 LYS A 296 -23.494 48.107 54.229 1.00 0.00 H \\\\nATOM 3501 HD3 LYS A 296 -24.718 47.781 55.140 1.00 0.00 H \\\\nATOM 3502 HE2 LYS A 296 -23.560 46.373 56.421 1.00 0.00 H \\\\nATOM 3503 HE3 LYS A 296 -22.596 45.964 55.265 1.00 0.00 H \\\\nATOM 3504 HZ1 LYS A 296 -21.233 47.245 56.288 1.00 0.00 H \\\\nATOM 3505 HZ2 LYS A 296 -21.918 48.347 55.634 1.00 0.00 H \\\\nATOM 3506 HZ3 LYS A 296 -22.268 47.979 56.995 1.00 0.00 H \\\\nATOM 3507 N ASP A 297 -23.034 42.392 53.081 1.00 0.00 N \\\\nATOM 3508 CA ASP A 297 -22.836 41.404 54.135 1.00 0.00 C \\\\nATOM 3509 C ASP A 297 -22.193 40.128 53.598 1.00 0.00 C \\\\nATOM 3510 O ASP A 297 -21.548 39.390 54.342 1.00 0.00 O \\\\nATOM 3511 CB ASP A 297 -24.165 41.075 54.817 1.00 0.00 C \\\\nATOM 3512 CG ASP A 297 -23.981 40.531 56.220 1.00 0.00 C \\\\nATOM 3513 OD1 ASP A 297 -22.856 40.629 56.754 1.00 0.00 O \\\\nATOM 3514 OD2 ASP A 297 -24.961 40.004 56.788 1.00 0.00 O \\\\nATOM 3515 H ASP A 297 -23.050 42.065 52.286 1.00 0.00 H \\\\nATOM 3516 HA ASP A 297 -22.231 41.791 54.787 1.00 0.00 H \\\\nATOM 3517 HB2 ASP A 297 -24.713 41.875 54.853 1.00 0.00 H \\\\nATOM 3518 HB3 ASP A 297 -24.647 40.425 54.282 1.00 0.00 H \\\\nATOM 3519 N ASP A 298 -22.373 39.873 52.306 1.00 0.00 N \\\\nATOM 3520 CA ASP A 298 -21.811 38.688 51.684 1.00 0.00 C \\\\nATOM 3521 C ASP A 298 -20.308 38.615 51.916 1.00 0.00 C \\\\nATOM 3522 O ASP A 298 -19.610 39.632 51.947 1.00 0.00 O \\\\nATOM 3523 CB ASP A 298 -22.109 38.698 50.187 1.00 0.00 C \\\\nATOM 3524 CG ASP A 298 -23.559 39.000 49.889 1.00 0.00 C \\\\nATOM 3525 OD1 ASP A 298 -24.439 38.471 50.605 1.00 0.00 O \\\\nATOM 3526 OD2 ASP A 298 -23.823 39.771 48.946 1.00 0.00 O \\\\nATOM 3527 H ASP A 298 -22.820 40.378 51.773 1.00 0.00 H \\\\nATOM 3528 HA ASP A 298 -22.219 37.906 52.087 1.00 0.00 H \\\\nATOM 3529 HB2 ASP A 298 -21.548 39.359 49.753 1.00 0.00 H \\\\nATOM 3530 HB3 ASP A 298 -21.877 37.836 49.808 1.00 0.00 H \\\\nATOM 3531 N ASP A 299 -19.814 37.393 52.094 1.00 0.00 N \\\\nATOM 3532 CA ASP A 299 -18.387 37.129 52.216 1.00 0.00 C \\\\nATOM 3533 C ASP A 299 -17.826 36.527 50.933 1.00 0.00 C \\\\nATOM 3534 O ASP A 299 -16.932 37.109 50.312 1.00 0.00 O \\\\nATOM 3535 CB ASP A 299 -18.117 36.199 53.407 1.00 0.00 C \\\\nATOM 3536 CG ASP A 299 -18.009 36.950 54.719 1.00 0.00 C \\\\nATOM 3537 OD1 ASP A 299 -16.940 37.542 54.985 1.00 0.00 O \\\\nATOM 3538 OD2 ASP A 299 -18.993 36.952 55.485 1.00 0.00 O \\\\nATOM 3539 H ASP A 299 -20.304 36.688 52.148 1.00 0.00 H \\\\nATOM 3540 HA ASP A 299 -17.937 37.974 52.370 1.00 0.00 H \\\\nATOM 3541 HB2 ASP A 299 -18.830 35.545 53.470 1.00 0.00 H \\\\nATOM 3542 HB3 ASP A 299 -17.295 35.708 53.250 1.00 0.00 H \\\\nATOM 3543 N CYS A 300 -18.337 35.368 50.523 1.00 0.00 N \\\\nATOM 3544 CA CYS A 300 -17.755 34.669 49.388 1.00 0.00 C \\\\nATOM 3545 C CYS A 300 -18.789 33.752 48.754 1.00 0.00 C \\\\nATOM 3546 O CYS A 300 -19.809 33.414 49.361 1.00 0.00 O \\\\nATOM 3547 CB CYS A 300 -16.518 33.865 49.807 1.00 0.00 C \\\\nATOM 3548 SG CYS A 300 -16.785 32.789 51.237 1.00 0.00 S \\\\nATOM 3549 H CYS A 300 -19.012 34.976 50.885 1.00 0.00 H \\\\nATOM 3550 HA CYS A 300 -17.475 35.331 48.737 1.00 0.00 H \\\\nATOM 3551 HB2 CYS A 300 -16.227 33.323 49.057 1.00 0.00 H \\\\nATOM 3552 HB3 CYS A 300 -15.797 34.481 50.009 1.00 0.00 H \\\\nATOM 3553 HG CYS A 300 -17.950 32.512 51.318 1.00 0.00 H \\\\nATOM 3554 N LEU A 301 -18.507 33.362 47.513 1.00 0.00 N \\\\nATOM 3555 CA LEU A 301 -19.262 32.348 46.793 1.00 0.00 C \\\\nATOM 3556 C LEU A 301 -18.412 31.089 46.699 1.00 0.00 C \\\\nATOM 3557 O LEU A 301 -17.195 31.169 46.508 1.00 0.00 O \\\\nATOM 3558 CB LEU A 301 -19.637 32.821 45.384 1.00 0.00 C \\\\nATOM 3559 CG LEU A 301 -20.914 33.631 45.162 1.00 0.00 C \\\\nATOM 3560 CD1 LEU A 301 -21.116 33.899 43.674 1.00 0.00 C \\\\nATOM 3561 CD2 LEU A 301 -22.120 32.914 45.743 1.00 0.00 C \\\\nATOM 3562 H LEU A 301 -17.855 33.690 47.058 1.00 0.00 H \\\\nATOM 3563 HA LEU A 301 -20.086 32.172 47.274 1.00 0.00 H \\\\nATOM 3564 HB2 LEU A 301 -18.897 33.353 45.052 1.00 0.00 H \\\\nATOM 3565 HB3 LEU A 301 -19.694 32.033 44.821 1.00 0.00 H \\\\nATOM 3566 HG LEU A 301 -20.820 34.480 45.622 1.00 0.00 H \\\\nATOM 3567 HD11 LEU A 301 -21.928 34.413 43.545 1.00 0.00 H \\\\nATOM 3568 HD12 LEU A 301 -20.359 34.399 43.329 1.00 0.00 H \\\\nATOM 3569 HD13 LEU A 301 -21.189 33.056 43.200 1.00 0.00 H \\\\nATOM 3570 HD21 LEU A 301 -22.917 33.445 45.591 1.00 0.00 H \\\\nATOM 3571 HD22 LEU A 301 -22.221 32.050 45.314 1.00 0.00 H \\\\nATOM 3572 HD23 LEU A 301 -21.993 32.788 46.696 1.00 0.00 H \\\\nATOM 3573 N ILE A 302 -19.049 29.929 46.837 1.00 0.00 N \\\\nATOM 3574 CA ILE A 302 -18.364 28.648 46.703 1.00 0.00 C \\\\nATOM 3575 C ILE A 302 -19.116 27.814 45.676 1.00 0.00 C \\\\nATOM 3576 O ILE A 302 -20.240 27.369 45.935 1.00 0.00 O \\\\nATOM 3577 CB ILE A 302 -18.258 27.905 48.042 1.00 0.00 C \\\\nATOM 3578 CG1 ILE A 302 -17.482 28.753 49.053 1.00 0.00 C \\\\nATOM 3579 CG2 ILE A 302 -17.588 26.554 47.852 1.00 0.00 C \\\\nATOM 3580 CD1 ILE A 302 -17.790 28.426 50.497 1.00 0.00 C \\\\nATOM 3581 H ILE A 302 -19.889 29.863 47.011 1.00 0.00 H \\\\nATOM 3582 HA ILE A 302 -17.453 28.805 46.408 1.00 0.00 H \\\\nATOM 3583 HB ILE A 302 -19.153 27.753 48.385 1.00 0.00 H \\\\nATOM 3584 HG12 ILE A 302 -16.532 28.633 48.900 1.00 0.00 H \\\\nATOM 3585 HG13 ILE A 302 -17.679 29.689 48.894 1.00 0.00 H \\\\nATOM 3586 HG21 ILE A 302 -17.529 26.099 48.706 1.00 0.00 H \\\\nATOM 3587 HG22 ILE A 302 -18.110 26.017 47.235 1.00 0.00 H \\\\nATOM 3588 HG23 ILE A 302 -16.696 26.683 47.493 1.00 0.00 H \\\\nATOM 3589 HD11 ILE A 302 -17.265 28.999 51.078 1.00 0.00 H \\\\nATOM 3590 HD12 ILE A 302 -18.734 28.571 50.668 1.00 0.00 H \\\\nATOM 3591 HD13 ILE A 302 -17.569 27.498 50.673 1.00 0.00 H \\\\nATOM 3592 N LEU A 303 -18.490 27.587 44.524 1.00 0.00 N \\\\nATOM 3593 CA LEU A 303 -18.975 26.663 43.508 1.00 0.00 C \\\\nATOM 3594 C LEU A 303 -18.091 25.427 43.533 1.00 0.00 C \\\\nATOM 3595 O LEU A 303 -16.861 25.543 43.514 1.00 0.00 O \\\\nATOM 3596 CB LEU A 303 -18.946 27.291 42.112 1.00 0.00 C \\\\nATOM 3597 CG LEU A 303 -19.626 28.635 41.855 1.00 0.00 C \\\\nATOM 3598 CD1 LEU A 303 -18.645 29.778 42.046 1.00 0.00 C \\\\nATOM 3599 CD2 LEU A 303 -20.205 28.658 40.447 1.00 0.00 C \\\\nATOM 3600 H LEU A 303 -17.754 27.976 44.308 1.00 0.00 H \\\\nATOM 3601 HA LEU A 303 -19.897 26.434 43.703 1.00 0.00 H \\\\nATOM 3602 HB2 LEU A 303 -18.014 27.388 41.861 1.00 0.00 H \\\\nATOM 3603 HB3 LEU A 303 -19.339 26.649 41.500 1.00 0.00 H \\\\nATOM 3604 HG LEU A 303 -20.347 28.748 42.494 1.00 0.00 H \\\\nATOM 3605 HD11 LEU A 303 -19.094 30.621 41.879 1.00 0.00 H \\\\nATOM 3606 HD12 LEU A 303 -18.308 29.766 42.955 1.00 0.00 H \\\\nATOM 3607 HD13 LEU A 303 -17.906 29.677 41.426 1.00 0.00 H \\\\nATOM 3608 HD21 LEU A 303 -20.636 29.512 40.288 1.00 0.00 H \\\\nATOM 3609 HD22 LEU A 303 -19.492 28.530 39.802 1.00 0.00 H \\\\nATOM 3610 HD23 LEU A 303 -20.857 27.946 40.353 1.00 0.00 H \\\\nATOM 3611 N ALA A 304 -18.706 24.249 43.568 1.00 0.00 N \\\\nATOM 3612 CA ALA A 304 -17.911 23.033 43.645 1.00 0.00 C \\\\nATOM 3613 C ALA A 304 -18.705 21.849 43.120 1.00 0.00 C \\\\nATOM 3614 O ALA A 304 -19.932 21.796 43.253 1.00 0.00 O \\\\nATOM 3615 CB ALA A 304 -17.446 22.758 45.079 1.00 0.00 C \\\\nATOM 3616 H ALA A 304 -19.558 24.134 43.549 1.00 0.00 H \\\\nATOM 3617 HA ALA A 304 -17.124 23.159 43.093 1.00 0.00 H \\\\nATOM 3618 HB1 ALA A 304 -16.920 21.943 45.098 1.00 0.00 H \\\\nATOM 3619 HB2 ALA A 304 -16.904 23.500 45.392 1.00 0.00 H \\\\nATOM 3620 HB3 ALA A 304 -18.219 22.657 45.656 1.00 0.00 H \\\\nATOM 3621 N SER A 305 -17.984 20.902 42.521 1.00 0.00 N \\\\nATOM 3622 CA SER A 305 -18.574 19.622 42.174 1.00 0.00 C \\\\nATOM 3623 C SER A 305 -18.876 18.832 43.447 1.00 0.00 C \\\\nATOM 3624 O SER A 305 -18.424 19.170 44.543 1.00 0.00 O \\\\nATOM 3625 CB SER A 305 -17.642 18.834 41.254 1.00 0.00 C \\\\nATOM 3626 OG SER A 305 -16.369 18.661 41.852 1.00 0.00 O \\\\nATOM 3627 H SER A 305 -17.155 20.985 42.310 1.00 0.00 H \\\\nATOM 3628 HA SER A 305 -19.405 19.775 41.697 1.00 0.00 H \\\\nATOM 3629 HB2 SER A 305 -18.032 17.968 41.058 1.00 0.00 H \\\\nATOM 3630 HB3 SER A 305 -17.546 19.300 40.409 1.00 0.00 H \\\\nATOM 3631 HG SER A 305 -16.419 18.834 42.672 1.00 0.00 H \\\\nATOM 3632 N ASP A 306 -19.644 17.753 43.292 1.00 0.00 N \\\\nATOM 3633 CA ASP A 306 -20.006 16.945 44.450 1.00 0.00 C \\\\nATOM 3634 C ASP A 306 -18.812 16.250 45.093 1.00 0.00 C \\\\nATOM 3635 O ASP A 306 -18.973 15.665 46.165 1.00 0.00 O \\\\nATOM 3636 CB ASP A 306 -21.071 15.913 44.071 1.00 0.00 C \\\\nATOM 3637 CG ASP A 306 -20.581 14.911 43.040 1.00 0.00 C \\\\nATOM 3638 OD1 ASP A 306 -19.456 15.072 42.528 1.00 0.00 O \\\\nATOM 3639 OD2 ASP A 306 -21.330 13.954 42.747 1.00 0.00 O \\\\nATOM 3640 H ASP A 306 -19.959 17.478 42.540 1.00 0.00 H \\\\nATOM 3641 HA ASP A 306 -20.364 17.559 45.110 1.00 0.00 H \\\\nATOM 3642 HB2 ASP A 306 -21.353 15.438 44.868 1.00 0.00 H \\\\nATOM 3643 HB3 ASP A 306 -21.851 16.373 43.723 1.00 0.00 H \\\\nATOM 3644 N GLY A 307 -17.627 16.306 44.483 1.00 0.00 N \\\\nATOM 3645 CA GLY A 307 -16.442 15.796 45.151 1.00 0.00 C \\\\nATOM 3646 C GLY A 307 -16.163 16.487 46.471 1.00 0.00 C \\\\nATOM 3647 O GLY A 307 -15.645 15.867 47.404 1.00 0.00 O \\\\nATOM 3648 H GLY A 307 -17.494 16.630 43.697 1.00 0.00 H \\\\nATOM 3649 HA2 GLY A 307 -16.548 14.844 45.306 1.00 0.00 H \\\\nATOM 3650 HA3 GLY A 307 -15.675 15.904 44.567 1.00 0.00 H \\\\nATOM 3651 N LEU A 308 -16.542 17.759 46.588 1.00 0.00 N \\\\nATOM 3652 CA LEU A 308 -16.409 18.477 47.848 1.00 0.00 C \\\\nATOM 3653 C LEU A 308 -17.641 18.268 48.716 1.00 0.00 C \\\\nATOM 3654 O LEU A 308 -17.520 17.924 49.895 1.00 0.00 O \\\\nATOM 3655 CB LEU A 308 -16.179 19.974 47.601 1.00 0.00 C \\\\nATOM 3656 CG LEU A 308 -16.218 20.840 48.864 1.00 0.00 C \\\\nATOM 3657 CD1 LEU A 308 -14.815 21.042 49.420 1.00 0.00 C \\\\nATOM 3658 CD2 LEU A 308 -16.899 22.179 48.608 1.00 0.00 C \\\\nATOM 3659 H LEU A 308 -16.879 18.222 45.947 1.00 0.00 H \\\\nATOM 3660 HA LEU A 308 -15.637 18.122 48.316 1.00 0.00 H \\\\nATOM 3661 HB2 LEU A 308 -15.318 20.090 47.169 1.00 0.00 H \\\\nATOM 3662 HB3 LEU A 308 -16.853 20.295 46.981 1.00 0.00 H \\\\nATOM 3663 HG LEU A 308 -16.746 20.369 49.527 1.00 0.00 H \\\\nATOM 3664 HD11 LEU A 308 -14.859 21.592 50.218 1.00 0.00 H \\\\nATOM 3665 HD12 LEU A 308 -14.428 20.181 49.642 1.00 0.00 H \\\\nATOM 3666 HD13 LEU A 308 -14.263 21.482 48.755 1.00 0.00 H \\\\nATOM 3667 HD21 LEU A 308 -16.906 22.700 49.426 1.00 0.00 H \\\\nATOM 3668 HD22 LEU A 308 -16.414 22.663 47.921 1.00 0.00 H \\\\nATOM 3669 HD23 LEU A 308 -17.811 22.028 48.314 1.00 0.00 H \\\\nATOM 3670 N TRP A 309 -18.832 18.466 48.147 1.00 0.00 N \\\\nATOM 3671 CA TRP A 309 -20.055 18.428 48.938 1.00 0.00 C \\\\nATOM 3672 C TRP A 309 -20.362 17.034 49.469 1.00 0.00 C \\\\nATOM 3673 O TRP A 309 -21.190 16.902 50.376 1.00 0.00 O \\\\nATOM 3674 CB TRP A 309 -21.232 18.951 48.109 1.00 0.00 C \\\\nATOM 3675 CG TRP A 309 -20.964 20.291 47.484 1.00 0.00 C \\\\nATOM 3676 CD1 TRP A 309 -20.916 20.580 46.150 1.00 0.00 C \\\\nATOM 3677 CD2 TRP A 309 -20.700 21.522 48.169 1.00 0.00 C \\\\nATOM 3678 NE1 TRP A 309 -20.639 21.913 45.963 1.00 0.00 N \\\\nATOM 3679 CE2 TRP A 309 -20.502 22.513 47.187 1.00 0.00 C \\\\nATOM 3680 CE3 TRP A 309 -20.612 21.882 49.517 1.00 0.00 C \\\\nATOM 3681 CZ2 TRP A 309 -20.224 23.839 47.510 1.00 0.00 C \\\\nATOM 3682 CZ3 TRP A 309 -20.334 23.197 49.837 1.00 0.00 C \\\\nATOM 3683 CH2 TRP A 309 -20.143 24.161 48.838 1.00 0.00 C \\\\nATOM 3684 H TRP A 309 -18.949 18.623 47.310 1.00 0.00 H \\\\nATOM 3685 HA TRP A 309 -19.918 19.002 49.708 1.00 0.00 H \\\\nATOM 3686 HB2 TRP A 309 -21.439 18.310 47.411 1.00 0.00 H \\\\nATOM 3687 HB3 TRP A 309 -22.016 19.016 48.676 1.00 0.00 H \\\\nATOM 3688 HD1 TRP A 309 -21.051 19.964 45.467 1.00 0.00 H \\\\nATOM 3689 HE1 TRP A 309 -20.564 22.306 45.202 1.00 0.00 H \\\\nATOM 3690 HE3 TRP A 309 -20.738 21.248 50.186 1.00 0.00 H \\\\nATOM 3691 HZ2 TRP A 309 -20.098 24.481 46.849 1.00 0.00 H \\\\nATOM 3692 HZ3 TRP A 309 -20.273 23.447 50.731 1.00 0.00 H \\\\nATOM 3693 HH2 TRP A 309 -19.957 25.039 49.083 1.00 0.00 H \\\\nATOM 3694 N ASP A 310 -19.720 15.993 48.931 1.00 0.00 N \\\\nATOM 3695 CA ASP A 310 -19.950 14.646 49.441 1.00 0.00 C \\\\nATOM 3696 C ASP A 310 -19.364 14.463 50.835 1.00 0.00 C \\\\nATOM 3697 O ASP A 310 -19.864 13.641 51.611 1.00 0.00 O \\\\nATOM 3698 CB ASP A 310 -19.350 13.608 48.491 1.00 0.00 C \\\\nATOM 3699 CG ASP A 310 -20.253 13.299 47.313 1.00 0.00 C \\\\nATOM 3700 OD1 ASP A 310 -21.424 13.733 47.324 1.00 0.00 O \\\\nATOM 3701 OD2 ASP A 310 -19.787 12.623 46.372 1.00 0.00 O \\\\nATOM 3702 H ASP A 310 -19.158 16.046 48.282 1.00 0.00 H \\\\nATOM 3703 HA ASP A 310 -20.910 14.518 49.498 1.00 0.00 H \\\\nATOM 3704 HB2 ASP A 310 -18.496 13.931 48.163 1.00 0.00 H \\\\nATOM 3705 HB3 ASP A 310 -19.174 12.790 48.982 1.00 0.00 H \\\\nATOM 3706 N VAL A 311 -18.321 15.216 51.173 1.00 0.00 N \\\\nATOM 3707 CA VAL A 311 -17.648 15.074 52.459 1.00 0.00 C \\\\nATOM 3708 C VAL A 311 -17.600 16.368 53.256 1.00 0.00 C \\\\nATOM 3709 O VAL A 311 -17.249 16.327 54.446 1.00 0.00 O \\\\nATOM 3710 CB VAL A 311 -16.220 14.515 52.285 1.00 0.00 C \\\\nATOM 3711 CG1 VAL A 311 -16.269 13.105 51.718 1.00 0.00 C \\\\nATOM 3712 CG2 VAL A 311 -15.400 15.426 51.385 1.00 0.00 C \\\\nATOM 3713 H VAL A 311 -17.985 15.822 50.664 1.00 0.00 H \\\\nATOM 3714 HA VAL A 311 -18.182 14.442 52.966 1.00 0.00 H \\\\nATOM 3715 HB VAL A 311 -15.793 14.480 53.155 1.00 0.00 H \\\\nATOM 3716 HG11 VAL A 311 -15.366 12.766 51.614 1.00 0.00 H \\\\nATOM 3717 HG12 VAL A 311 -16.762 12.529 52.324 1.00 0.00 H \\\\nATOM 3718 HG13 VAL A 311 -16.710 13.118 50.854 1.00 0.00 H \\\\nATOM 3719 HG21 VAL A 311 -14.506 15.063 51.285 1.00 0.00 H \\\\nATOM 3720 HG22 VAL A 311 -15.823 15.487 50.514 1.00 0.00 H \\\\nATOM 3721 HG23 VAL A 311 -15.347 16.310 51.781 1.00 0.00 H \\\\nATOM 3722 N VAL A 312 -17.934 17.508 52.659 1.00 0.00 N \\\\nATOM 3723 CA VAL A 312 -17.923 18.794 53.345 1.00 0.00 C \\\\nATOM 3724 C VAL A 312 -19.320 19.392 53.265 1.00 0.00 C \\\\nATOM 3725 O VAL A 312 -19.924 19.427 52.187 1.00 0.00 O \\\\nATOM 3726 CB VAL A 312 -16.875 19.748 52.741 1.00 0.00 C \\\\nATOM 3727 CG1 VAL A 312 -16.905 21.092 53.448 1.00 0.00 C \\\\nATOM 3728 CG2 VAL A 312 -15.485 19.129 52.819 1.00 0.00 C \\\\nATOM 3729 H VAL A 312 -18.176 17.556 51.835 1.00 0.00 H \\\\nATOM 3730 HA VAL A 312 -17.674 18.662 54.273 1.00 0.00 H \\\\nATOM 3731 HB VAL A 312 -17.093 19.893 51.807 1.00 0.00 H \\\\nATOM 3732 HG11 VAL A 312 -16.240 21.679 53.056 1.00 0.00 H \\\\nATOM 3733 HG12 VAL A 312 -17.784 21.489 53.351 1.00 0.00 H \\\\nATOM 3734 HG13 VAL A 312 -16.710 20.967 54.390 1.00 0.00 H \\\\nATOM 3735 HG21 VAL A 312 -14.836 19.740 52.436 1.00 0.00 H \\\\nATOM 3736 HG22 VAL A 312 -15.258 18.958 53.746 1.00 0.00 H \\\\nATOM 3737 HG23 VAL A 312 -15.474 18.295 52.325 1.00 0.00 H \\\\nATOM 3738 N SER A 313 -19.828 19.859 54.402 1.00 0.00 N \\\\nATOM 3739 CA SER A 313 -21.156 20.444 54.456 1.00 0.00 C \\\\nATOM 3740 C SER A 313 -21.108 21.918 54.059 1.00 0.00 C \\\\nATOM 3741 O SER A 313 -20.041 22.526 53.943 1.00 0.00 O \\\\nATOM 3742 CB SER A 313 -21.754 20.289 55.854 1.00 0.00 C \\\\nATOM 3743 OG SER A 313 -21.290 21.307 56.723 1.00 0.00 O \\\\nATOM 3744 H SER A 313 -19.414 19.845 55.156 1.00 0.00 H \\\\nATOM 3745 HA SER A 313 -21.723 19.973 53.825 1.00 0.00 H \\\\nATOM 3746 HB2 SER A 313 -22.722 20.322 55.800 1.00 0.00 H \\\\nATOM 3747 HB3 SER A 313 -21.519 19.420 56.215 1.00 0.00 H \\\\nATOM 3748 HG SER A 313 -21.631 21.204 57.483 1.00 0.00 H \\\\nATOM 3749 N ASN A 314 -22.294 22.488 53.829 1.00 0.00 N \\\\nATOM 3750 CA ASN A 314 -22.377 23.907 53.497 1.00 0.00 C \\\\nATOM 3751 C ASN A 314 -21.808 24.764 54.620 1.00 0.00 C \\\\nATOM 3752 O ASN A 314 -21.084 25.735 54.367 1.00 0.00 O \\\\nATOM 3753 CB ASN A 314 -23.826 24.294 53.200 1.00 0.00 C \\\\nATOM 3754 CG ASN A 314 -24.353 23.654 51.930 1.00 0.00 C \\\\nATOM 3755 OD1 ASN A 314 -23.703 22.792 51.338 1.00 0.00 O \\\\nATOM 3756 ND2 ASN A 314 -25.534 24.079 51.501 1.00 0.00 N \\\\nATOM 3757 H ASN A 314 -23.049 22.076 53.860 1.00 0.00 H \\\\nATOM 3758 HA ASN A 314 -21.844 24.068 52.703 1.00 0.00 H \\\\nATOM 3759 HB2 ASN A 314 -24.387 24.032 53.947 1.00 0.00 H \\\\nATOM 3760 HB3 ASN A 314 -23.890 25.259 53.122 1.00 0.00 H \\\\nATOM 3761 HD21 ASN A 314 -25.874 23.750 50.783 1.00 0.00 H \\\\nATOM 3762 HD22 ASN A 314 -25.959 24.683 51.941 1.00 0.00 H \\\\nATOM 3763 N GLU A 315 -22.142 24.428 55.869 1.00 0.00 N \\\\nATOM 3764 CA GLU A 315 -21.556 25.118 57.014 1.00 0.00 C \\\\nATOM 3765 C GLU A 315 -20.043 24.949 57.038 1.00 0.00 C \\\\nATOM 3766 O GLU A 315 -19.297 25.920 57.215 1.00 0.00 O \\\\nATOM 3767 CB GLU A 315 -22.170 24.590 58.310 1.00 0.00 C \\\\nATOM 3768 CG GLU A 315 -23.679 24.715 58.395 1.00 0.00 C \\\\nATOM 3769 CD GLU A 315 -24.118 25.654 59.501 1.00 0.00 C \\\\nATOM 3770 OE1 GLU A 315 -23.243 26.289 60.125 1.00 0.00 O \\\\nATOM 3771 OE2 GLU A 315 -25.338 25.751 59.750 1.00 0.00 O \\\\nATOM 3772 H GLU A 315 -22.702 23.807 56.071 1.00 0.00 H \\\\nATOM 3773 HA GLU A 315 -21.750 26.065 56.933 1.00 0.00 H \\\\nATOM 3774 HB2 GLU A 315 -21.929 23.656 58.410 1.00 0.00 H \\\\nATOM 3775 HB3 GLU A 315 -21.776 25.066 59.057 1.00 0.00 H \\\\nATOM 3776 HG2 GLU A 315 -24.023 25.035 57.546 1.00 0.00 H \\\\nATOM 3777 HG3 GLU A 315 -24.066 23.838 58.545 1.00 0.00 H \\\\nATOM 3778 N GLU A 316 -19.575 23.709 56.871 1.00 0.00 N \\\\nATOM 3779 CA GLU A 316 -18.145 23.424 56.933 1.00 0.00 C \\\\nATOM 3780 C GLU A 316 -17.378 24.177 55.854 1.00 0.00 C \\\\nATOM 3781 O GLU A 316 -16.317 24.751 56.121 1.00 0.00 O \\\\nATOM 3782 CB GLU A 316 -17.924 21.919 56.796 1.00 0.00 C \\\\nATOM 3783 CG GLU A 316 -16.598 21.411 57.314 1.00 0.00 C \\\\nATOM 3784 CD GLU A 316 -16.563 19.898 57.377 1.00 0.00 C \\\\nATOM 3785 OE1 GLU A 316 -17.602 19.270 57.081 1.00 0.00 O \\\\nATOM 3786 OE2 GLU A 316 -15.500 19.335 57.715 1.00 0.00 O \\\\nATOM 3787 H GLU A 316 -20.071 23.022 56.721 1.00 0.00 H \\\\nATOM 3788 HA GLU A 316 -17.807 23.726 57.791 1.00 0.00 H \\\\nATOM 3789 HB2 GLU A 316 -18.636 21.458 57.267 1.00 0.00 H \\\\nATOM 3790 HB3 GLU A 316 -18.002 21.680 55.859 1.00 0.00 H \\\\nATOM 3791 HG2 GLU A 316 -15.883 21.728 56.740 1.00 0.00 H \\\\nATOM 3792 HG3 GLU A 316 -16.434 21.776 58.198 1.00 0.00 H \\\\nATOM 3793 N ALA A 317 -17.904 24.197 54.631 1.00 0.00 N \\\\nATOM 3794 CA ALA A 317 -17.194 24.849 53.537 1.00 0.00 C \\\\nATOM 3795 C ALA A 317 -17.178 26.367 53.702 1.00 0.00 C \\\\nATOM 3796 O ALA A 317 -16.178 27.020 53.382 1.00 0.00 O \\\\nATOM 3797 CB ALA A 317 -17.815 24.451 52.198 1.00 0.00 C \\\\nATOM 3798 H ALA A 317 -18.659 23.845 54.417 1.00 0.00 H \\\\nATOM 3799 HA ALA A 317 -16.272 24.550 53.555 1.00 0.00 H \\\\nATOM 3800 HB1 ALA A 317 -17.337 24.889 51.476 1.00 0.00 H \\\\nATOM 3801 HB2 ALA A 317 -17.757 23.489 52.087 1.00 0.00 H \\\\nATOM 3802 HB3 ALA A 317 -18.746 24.722 52.180 1.00 0.00 H \\\\nATOM 3803 N CYS A 318 -18.276 26.946 54.198 1.00 0.00 N \\\\nATOM 3804 CA CYS A 318 -18.370 28.398 54.327 1.00 0.00 C \\\\nATOM 3805 C CYS A 318 -17.424 28.946 55.392 1.00 0.00 C \\\\nATOM 3806 O CYS A 318 -16.759 29.973 55.172 1.00 0.00 O \\\\nATOM 3807 CB CYS A 318 -19.821 28.792 54.631 1.00 0.00 C \\\\nATOM 3808 SG CYS A 318 -20.838 29.070 53.146 1.00 0.00 S \\\\nATOM 3809 H CYS A 318 -18.972 26.516 54.463 1.00 0.00 H \\\\nATOM 3810 HA CYS A 318 -18.097 28.793 53.484 1.00 0.00 H \\\\nATOM 3811 HB2 CYS A 318 -20.231 28.095 55.167 1.00 0.00 H \\\\nATOM 3812 HB3 CYS A 318 -19.822 29.600 55.168 1.00 0.00 H \\\\nATOM 3813 HG CYS A 318 -21.116 28.014 52.648 1.00 0.00 H \\\\nATOM 3814 N LYS A 319 -17.362 28.274 56.549 1.00 0.00 N \\\\nATOM 3815 CA LYS A 319 -16.568 28.773 57.665 1.00 0.00 C \\\\nATOM 3816 C LYS A 319 -15.078 28.655 57.338 1.00 0.00 C \\\\nATOM 3817 O LYS A 319 -14.271 29.516 57.707 1.00 0.00 O \\\\nATOM 3818 CB LYS A 319 -16.994 28.000 58.919 1.00 0.00 C \\\\nATOM 3819 CG LYS A 319 -16.100 27.878 60.137 1.00 0.00 C \\\\nATOM 3820 CD LYS A 319 -17.065 28.049 61.367 1.00 0.00 C \\\\nATOM 3821 CE LYS A 319 -16.399 28.124 62.733 1.00 0.00 C \\\\nATOM 3822 NZ LYS A 319 -17.350 27.510 63.721 1.00 0.00 N \\\\nATOM 3823 H LYS A 319 -17.771 27.533 56.702 1.00 0.00 H \\\\nATOM 3824 HA LYS A 319 -16.723 29.716 57.830 1.00 0.00 H \\\\nATOM 3825 HB2 LYS A 319 -17.825 28.398 59.222 1.00 0.00 H \\\\nATOM 3826 HB3 LYS A 319 -17.200 27.096 58.633 1.00 0.00 H \\\\nATOM 3827 HG2 LYS A 319 -15.651 27.018 60.159 1.00 0.00 H \\\\nATOM 3828 HG3 LYS A 319 -15.409 28.559 60.135 1.00 0.00 H \\\\nATOM 3829 HD2 LYS A 319 -17.586 28.857 61.236 1.00 0.00 H \\\\nATOM 3830 HD3 LYS A 319 -17.689 27.306 61.372 1.00 0.00 H \\\\nATOM 3831 HE2 LYS A 319 -15.554 27.648 62.729 1.00 0.00 H \\\\nATOM 3832 HE3 LYS A 319 -16.205 29.044 62.970 1.00 0.00 H \\\\nATOM 3833 HZ1 LYS A 319 -17.240 27.893 64.517 1.00 0.00 H \\\\nATOM 3834 HZ2 LYS A 319 -18.187 27.636 63.445 1.00 0.00 H \\\\nATOM 3835 HZ3 LYS A 319 -17.188 26.637 63.787 1.00 0.00 H \\\\nATOM 3836 N VAL A 320 -14.708 27.614 56.589 1.00 0.00 N \\\\nATOM 3837 CA VAL A 320 -13.314 27.384 56.203 1.00 0.00 C \\\\nATOM 3838 C VAL A 320 -12.873 28.365 55.118 1.00 0.00 C \\\\nATOM 3839 O VAL A 320 -11.781 28.944 55.184 1.00 0.00 O \\\\nATOM 3840 CB VAL A 320 -13.140 25.928 55.735 1.00 0.00 C \\\\nATOM 3841 CG1 VAL A 320 -11.841 25.771 54.992 1.00 0.00 C \\\\nATOM 3842 CG2 VAL A 320 -13.225 25.002 56.936 1.00 0.00 C \\\\nATOM 3843 H VAL A 320 -15.257 27.023 56.291 1.00 0.00 H \\\\nATOM 3844 HA VAL A 320 -12.748 27.535 56.976 1.00 0.00 H \\\\nATOM 3845 HB VAL A 320 -13.851 25.690 55.120 1.00 0.00 H \\\\nATOM 3846 HG11 VAL A 320 -11.743 24.850 54.703 1.00 0.00 H \\\\nATOM 3847 HG12 VAL A 320 -11.838 26.355 54.218 1.00 0.00 H \\\\nATOM 3848 HG13 VAL A 320 -11.103 26.006 55.576 1.00 0.00 H \\\\nATOM 3849 HG21 VAL A 320 -13.116 24.083 56.645 1.00 0.00 H \\\\nATOM 3850 HG22 VAL A 320 -12.524 25.226 57.568 1.00 0.00 H \\\\nATOM 3851 HG23 VAL A 320 -14.090 25.105 57.363 1.00 0.00 H \\\\nATOM 3852 N ALA A 321 -13.708 28.559 54.098 1.00 0.00 N \\\\nATOM 3853 CA ALA A 321 -13.351 29.470 53.015 1.00 0.00 C \\\\nATOM 3854 C ALA A 321 -13.234 30.894 53.542 1.00 0.00 C \\\\nATOM 3855 O ALA A 321 -12.234 31.581 53.304 1.00 0.00 O \\\\nATOM 3856 CB ALA A 321 -14.383 29.386 51.890 1.00 0.00 C \\\\nATOM 3857 H ALA A 321 -14.475 28.178 54.015 1.00 0.00 H \\\\nATOM 3858 HA ALA A 321 -12.489 29.208 52.655 1.00 0.00 H \\\\nATOM 3859 HB1 ALA A 321 -14.135 29.995 51.177 1.00 0.00 H \\\\nATOM 3860 HB2 ALA A 321 -14.413 28.480 51.545 1.00 0.00 H \\\\nATOM 3861 HB3 ALA A 321 -15.257 29.629 52.233 1.00 0.00 H \\\\nATOM 3862 N ARG A 322 -14.251 31.342 54.284 1.00 0.00 N \\\\nATOM 3863 CA ARG A 322 -14.254 32.693 54.834 1.00 0.00 C \\\\nATOM 3864 C ARG A 322 -13.067 32.933 55.763 1.00 0.00 C \\\\nATOM 3865 O ARG A 322 -12.583 34.067 55.870 1.00 0.00 O \\\\nATOM 3866 CB ARG A 322 -15.571 32.937 55.571 1.00 0.00 C \\\\nATOM 3867 CG ARG A 322 -15.678 34.279 56.265 1.00 0.00 C \\\\nATOM 3868 CD ARG A 322 -16.791 34.266 57.299 1.00 0.00 C \\\\nATOM 3869 NE ARG A 322 -17.117 35.606 57.777 1.00 0.00 N \\\\nATOM 3870 CZ ARG A 322 -16.408 36.271 58.684 1.00 0.00 C \\\\nATOM 3871 NH1 ARG A 322 -15.331 35.718 59.225 1.00 0.00 N \\\\nATOM 3872 NH2 ARG A 322 -16.781 37.488 59.056 1.00 0.00 N \\\\nATOM 3873 H ARG A 322 -14.947 30.876 54.478 1.00 0.00 H \\\\nATOM 3874 HA ARG A 322 -14.170 33.320 54.099 1.00 0.00 H \\\\nATOM 3875 HB2 ARG A 322 -16.300 32.857 54.937 1.00 0.00 H \\\\nATOM 3876 HB3 ARG A 322 -15.691 32.236 56.231 1.00 0.00 H \\\\nATOM 3877 HG2 ARG A 322 -14.835 34.494 56.694 1.00 0.00 H \\\\nATOM 3878 HG3 ARG A 322 -15.848 34.974 55.610 1.00 0.00 H \\\\nATOM 3879 HD2 ARG A 322 -17.583 33.860 56.913 1.00 0.00 H \\\\nATOM 3880 HD3 ARG A 322 -16.526 33.712 58.050 1.00 0.00 H \\\\nATOM 3881 HE ARG A 322 -17.813 35.991 57.450 1.00 0.00 H \\\\nATOM 3882 HH11 ARG A 322 -15.089 34.927 58.989 1.00 0.00 H \\\\nATOM 3883 HH12 ARG A 322 -14.874 36.150 59.811 1.00 0.00 H \\\\nATOM 3884 HH21 ARG A 322 -17.482 37.847 58.711 1.00 0.00 H \\\\nATOM 3885 HH22 ARG A 322 -16.322 37.918 59.643 1.00 0.00 H \\\\nATOM 3886 N ARG A 323 -12.573 31.885 56.427 1.00 0.00 N \\\\nATOM 3887 CA ARG A 323 -11.444 32.056 57.335 1.00 0.00 C \\\\nATOM 3888 C ARG A 323 -10.110 32.013 56.602 1.00 0.00 C \\\\nATOM 3889 O ARG A 323 -9.176 32.732 56.979 1.00 0.00 O \\\\nATOM 3890 CB ARG A 323 -11.479 30.984 58.429 1.00 0.00 C \\\\nATOM 3891 CG ARG A 323 -10.108 30.561 58.937 1.00 0.00 C \\\\nATOM 3892 CD ARG A 323 -10.215 29.608 60.106 1.00 0.00 C \\\\nATOM 3893 NE ARG A 323 -11.398 29.862 60.912 1.00 0.00 N \\\\nATOM 3894 CZ ARG A 323 -11.807 29.078 61.900 1.00 0.00 C \\\\nATOM 3895 NH1 ARG A 323 -11.130 27.981 62.212 1.00 0.00 N \\\\nATOM 3896 NH2 ARG A 323 -12.890 29.401 62.582 1.00 0.00 N \\\\nATOM 3897 H ARG A 323 -12.873 31.081 56.366 1.00 0.00 H \\\\nATOM 3898 HA ARG A 323 -11.526 32.934 57.740 1.00 0.00 H \\\\nATOM 3899 HB2 ARG A 323 -12.000 31.317 59.176 1.00 0.00 H \\\\nATOM 3900 HB3 ARG A 323 -11.940 30.203 58.087 1.00 0.00 H \\\\nATOM 3901 HG2 ARG A 323 -9.613 30.138 58.218 1.00 0.00 H \\\\nATOM 3902 HG3 ARG A 323 -9.605 31.346 59.204 1.00 0.00 H \\\\nATOM 3903 HD2 ARG A 323 -10.239 28.696 59.777 1.00 0.00 H \\\\nATOM 3904 HD3 ARG A 323 -9.424 29.689 60.661 1.00 0.00 H \\\\nATOM 3905 HE ARG A 323 -11.862 30.565 60.737 1.00 0.00 H \\\\nATOM 3906 HH11 ARG A 323 -10.420 27.774 61.772 1.00 0.00 H \\\\nATOM 3907 HH12 ARG A 323 -11.401 27.477 62.854 1.00 0.00 H \\\\nATOM 3908 HH21 ARG A 323 -13.325 30.116 62.384 1.00 0.00 H \\\\nATOM 3909 HH22 ARG A 323 -13.160 28.897 63.224 1.00 0.00 H \\\\nATOM 3910 N GLN A 324 -10.006 31.199 55.547 1.00 0.00 N \\\\nATOM 3911 CA GLN A 324 -8.784 31.178 54.751 1.00 0.00 C \\\\nATOM 3912 C GLN A 324 -8.555 32.513 54.054 1.00 0.00 C \\\\nATOM 3913 O GLN A 324 -7.408 32.953 53.902 1.00 0.00 O \\\\nATOM 3914 CB GLN A 324 -8.842 30.044 53.730 1.00 0.00 C \\\\nATOM 3915 CG GLN A 324 -8.469 28.687 54.296 1.00 0.00 C \\\\nATOM 3916 CD GLN A 324 -7.069 28.668 54.876 1.00 0.00 C \\\\nATOM 3917 OE1 GLN A 324 -6.127 29.189 54.276 1.00 0.00 O \\\\nATOM 3918 NE2 GLN A 324 -6.925 28.071 56.054 1.00 0.00 N \\\\nATOM 3919 H GLN A 324 -10.622 30.661 55.282 1.00 0.00 H \\\\nATOM 3920 HA GLN A 324 -8.036 31.025 55.349 1.00 0.00 H \\\\nATOM 3921 HB2 GLN A 324 -9.739 29.996 53.364 1.00 0.00 H \\\\nATOM 3922 HB3 GLN A 324 -8.246 30.253 52.994 1.00 0.00 H \\\\nATOM 3923 HG2 GLN A 324 -9.105 28.441 54.985 1.00 0.00 H \\\\nATOM 3924 HG3 GLN A 324 -8.536 28.018 53.597 1.00 0.00 H \\\\nATOM 3925 HE21 GLN A 324 -7.606 27.718 56.443 1.00 0.00 H \\\\nATOM 3926 HE22 GLN A 324 -6.151 28.037 56.427 1.00 0.00 H \\\\nATOM 3927 N ILE A 325 -9.634 33.171 53.623 1.00 0.00 N \\\\nATOM 3928 CA ILE A 325 -9.504 34.483 52.995 1.00 0.00 C \\\\nATOM 3929 C ILE A 325 -8.968 35.494 53.998 1.00 0.00 C \\\\nATOM 3930 O ILE A 325 -8.072 36.290 53.687 1.00 0.00 O \\\\nATOM 3931 CB ILE A 325 -10.858 34.934 52.414 1.00 0.00 C \\\\nATOM 3932 CG1 ILE A 325 -11.374 33.926 51.385 1.00 0.00 C \\\\nATOM 3933 CG2 ILE A 325 -10.743 36.335 51.818 1.00 0.00 C \\\\nATOM 3934 CD1 ILE A 325 -10.783 34.085 50.008 1.00 0.00 C \\\\nATOM 3935 H ILE A 325 -10.440 32.877 53.685 1.00 0.00 H \\\\nATOM 3936 HA ILE A 325 -8.871 34.423 52.263 1.00 0.00 H \\\\nATOM 3937 HB ILE A 325 -11.506 34.970 53.135 1.00 0.00 H \\\\nATOM 3938 HG12 ILE A 325 -11.186 33.029 51.704 1.00 0.00 H \\\\nATOM 3939 HG13 ILE A 325 -12.338 34.009 51.323 1.00 0.00 H \\\\nATOM 3940 HG21 ILE A 325 -11.602 36.605 51.457 1.00 0.00 H \\\\nATOM 3941 HG22 ILE A 325 -10.473 36.960 52.509 1.00 0.00 H \\\\nATOM 3942 HG23 ILE A 325 -10.081 36.332 51.109 1.00 0.00 H \\\\nATOM 3943 HD11 ILE A 325 -11.157 33.414 49.416 1.00 0.00 H \\\\nATOM 3944 HD12 ILE A 325 -10.991 34.969 49.667 1.00 0.00 H \\\\nATOM 3945 HD13 ILE A 325 -9.820 33.974 50.054 1.00 0.00 H \\\\nATOM 3946 N LEU A 326 -9.508 35.477 55.218 1.00 0.00 N \\\\nATOM 3947 CA LEU A 326 -9.099 36.443 56.230 1.00 0.00 C \\\\nATOM 3948 C LEU A 326 -7.672 36.188 56.698 1.00 0.00 C \\\\nATOM 3949 O LEU A 326 -6.923 37.137 56.962 1.00 0.00 O \\\\nATOM 3950 CB LEU A 326 -10.072 36.412 57.408 1.00 0.00 C \\\\nATOM 3951 CG LEU A 326 -11.191 37.457 57.377 1.00 0.00 C \\\\nATOM 3952 CD1 LEU A 326 -12.014 37.348 56.100 1.00 0.00 C \\\\nATOM 3953 CD2 LEU A 326 -12.082 37.322 58.601 1.00 0.00 C \\\\nATOM 3954 H LEU A 326 -10.108 34.917 55.475 1.00 0.00 H \\\\nATOM 3955 HA LEU A 326 -9.119 37.327 55.831 1.00 0.00 H \\\\nATOM 3956 HB2 LEU A 326 -10.476 35.531 57.448 1.00 0.00 H \\\\nATOM 3957 HB3 LEU A 326 -9.566 36.529 58.227 1.00 0.00 H \\\\nATOM 3958 HG LEU A 326 -10.779 38.335 57.390 1.00 0.00 H \\\\nATOM 3959 HD11 LEU A 326 -12.714 38.020 56.107 1.00 0.00 H \\\\nATOM 3960 HD12 LEU A 326 -11.439 37.489 55.331 1.00 0.00 H \\\\nATOM 3961 HD13 LEU A 326 -12.414 36.466 56.047 1.00 0.00 H \\\\nATOM 3962 HD21 LEU A 326 -12.784 37.990 58.566 1.00 0.00 H \\\\nATOM 3963 HD22 LEU A 326 -12.479 36.437 58.617 1.00 0.00 H \\\\nATOM 3964 HD23 LEU A 326 -11.552 37.453 59.403 1.00 0.00 H \\\\nATOM 3965 N LEU A 327 -7.273 34.917 56.811 1.00 0.00 N \\\\nATOM 3966 CA LEU A 327 -5.934 34.628 57.309 1.00 0.00 C \\\\nATOM 3967 C LEU A 327 -4.857 34.931 56.278 1.00 0.00 C \\\\nATOM 3968 O LEU A 327 -3.692 35.108 56.653 1.00 0.00 O \\\\nATOM 3969 CB LEU A 327 -5.831 33.162 57.733 1.00 0.00 C \\\\nATOM 3970 CG LEU A 327 -6.584 32.731 58.993 1.00 0.00 C \\\\nATOM 3971 CD1 LEU A 327 -6.054 31.396 59.499 1.00 0.00 C \\\\nATOM 3972 CD2 LEU A 327 -6.499 33.799 60.078 1.00 0.00 C \\\\nATOM 3973 H LEU A 327 -7.749 34.230 56.610 1.00 0.00 H \\\\nATOM 3974 HA LEU A 327 -5.786 35.206 58.074 1.00 0.00 H \\\\nATOM 3975 HB2 LEU A 327 -6.145 32.615 56.996 1.00 0.00 H \\\\nATOM 3976 HB3 LEU A 327 -4.892 32.954 57.860 1.00 0.00 H \\\\nATOM 3977 HG LEU A 327 -7.520 32.621 58.763 1.00 0.00 H \\\\nATOM 3978 HD11 LEU A 327 -6.540 31.136 60.297 1.00 0.00 H \\\\nATOM 3979 HD12 LEU A 327 -6.173 30.720 58.814 1.00 0.00 H \\\\nATOM 3980 HD13 LEU A 327 -5.111 31.481 59.709 1.00 0.00 H \\\\nATOM 3981 HD21 LEU A 327 -6.983 33.501 60.864 1.00 0.00 H \\\\nATOM 3982 HD22 LEU A 327 -5.570 33.952 60.310 1.00 0.00 H \\\\nATOM 3983 HD23 LEU A 327 -6.890 34.624 59.751 1.00 0.00 H \\\\nATOM 3984 N TRP A 328 -5.210 34.998 54.994 1.00 0.00 N \\\\nATOM 3985 CA TRP A 328 -4.216 35.366 53.994 1.00 0.00 C \\\\nATOM 3986 C TRP A 328 -3.931 36.861 54.040 1.00 0.00 C \\\\nATOM 3987 O TRP A 328 -2.777 37.284 53.911 1.00 0.00 O \\\\nATOM 3988 CB TRP A 328 -4.670 34.949 52.593 1.00 0.00 C \\\\nATOM 3989 CG TRP A 328 -3.551 34.979 51.591 1.00 0.00 C \\\\nATOM 3990 CD1 TRP A 328 -2.800 33.920 51.167 1.00 0.00 C \\\\nATOM 3991 CD2 TRP A 328 -3.046 36.129 50.897 1.00 0.00 C \\\\nATOM 3992 NE1 TRP A 328 -1.864 34.338 50.250 1.00 0.00 N \\\\nATOM 3993 CE2 TRP A 328 -1.994 35.690 50.068 1.00 0.00 C \\\\nATOM 3994 CE3 TRP A 328 -3.385 37.485 50.892 1.00 0.00 C \\\\nATOM 3995 CZ2 TRP A 328 -1.276 36.558 49.250 1.00 0.00 C \\\\nATOM 3996 CZ3 TRP A 328 -2.671 38.346 50.079 1.00 0.00 C \\\\nATOM 3997 CH2 TRP A 328 -1.631 37.880 49.266 1.00 0.00 C \\\\nATOM 3998 H TRP A 328 -5.998 34.838 54.690 1.00 0.00 H \\\\nATOM 3999 HA TRP A 328 -3.395 34.892 54.200 1.00 0.00 H \\\\nATOM 4000 HB2 TRP A 328 -5.042 34.054 52.630 1.00 0.00 H \\\\nATOM 4001 HB3 TRP A 328 -5.380 35.540 52.298 1.00 0.00 H \\\\nATOM 4002 HD1 TRP A 328 -2.906 33.043 51.457 1.00 0.00 H \\\\nATOM 4003 HE1 TRP A 328 -1.291 33.833 49.855 1.00 0.00 H \\\\nATOM 4004 HE3 TRP A 328 -4.078 37.802 51.425 1.00 0.00 H \\\\nATOM 4005 HZ2 TRP A 328 -0.581 36.251 48.713 1.00 0.00 H \\\\nATOM 4006 HZ3 TRP A 328 -2.886 39.251 50.072 1.00 0.00 H \\\\nATOM 4007 HH2 TRP A 328 -1.172 38.481 48.725 1.00 0.00 H \\\\nATOM 4008 N HIS A 329 -4.974 37.672 54.234 1.00 0.00 N \\\\nATOM 4009 CA HIS A 329 -4.820 39.121 54.219 1.00 0.00 C \\\\nATOM 4010 C HIS A 329 -4.189 39.658 55.497 1.00 0.00 C \\\\nATOM 4011 O HIS A 329 -3.543 40.711 55.464 1.00 0.00 O \\\\nATOM 4012 CB HIS A 329 -6.176 39.783 53.976 1.00 0.00 C \\\\nATOM 4013 CG HIS A 329 -6.667 39.640 52.570 1.00 0.00 C \\\\nATOM 4014 ND1 HIS A 329 -5.857 39.857 51.476 1.00 0.00 N \\\\nATOM 4015 CD2 HIS A 329 -7.880 39.295 52.077 1.00 0.00 C \\\\nATOM 4016 CE1 HIS A 329 -6.551 39.655 50.370 1.00 0.00 C \\\\nATOM 4017 NE2 HIS A 329 -7.781 39.313 50.707 1.00 0.00 N \\\\nATOM 4018 H HIS A 329 -5.777 37.399 54.376 1.00 0.00 H \\\\nATOM 4019 HA HIS A 329 -4.213 39.340 53.495 1.00 0.00 H \\\\nATOM 4020 HB2 HIS A 329 -6.829 39.397 54.580 1.00 0.00 H \\\\nATOM 4021 HB3 HIS A 329 -6.111 40.726 54.194 1.00 0.00 H \\\\nATOM 4022 HD1 HIS A 329 -5.029 40.088 51.508 1.00 0.00 H \\\\nATOM 4023 HD2 HIS A 329 -8.638 39.085 52.573 1.00 0.00 H \\\\nATOM 4024 HE1 HIS A 329 -6.228 39.739 49.502 1.00 0.00 H \\\\nATOM 4025 HE2 HIS A 329 -8.417 39.131 50.158 1.00 0.00 H \\\\nATOM 4026 N LYS A 330 -4.367 38.973 56.628 1.00 0.00 N \\\\nATOM 4027 CA LYS A 330 -3.659 39.377 57.835 1.00 0.00 C \\\\nATOM 4028 C LYS A 330 -2.215 38.896 57.834 1.00 0.00 C \\\\nATOM 4029 O LYS A 330 -1.380 39.477 58.535 1.00 0.00 O \\\\nATOM 4030 CB LYS A 330 -4.407 38.880 59.081 1.00 0.00 C \\\\nATOM 4031 CG LYS A 330 -4.132 37.443 59.521 1.00 0.00 C \\\\nATOM 4032 CD LYS A 330 -3.012 37.352 60.552 1.00 0.00 C \\\\nATOM 4033 CE LYS A 330 -2.461 35.941 60.629 1.00 0.00 C \\\\nATOM 4034 NZ LYS A 330 -1.224 35.861 61.452 1.00 0.00 N \\\\nATOM 4035 H LYS A 330 -4.881 38.289 56.714 1.00 0.00 H \\\\nATOM 4036 HA LYS A 330 -3.633 40.346 57.854 1.00 0.00 H \\\\nATOM 4037 HB2 LYS A 330 -4.189 39.470 59.820 1.00 0.00 H \\\\nATOM 4038 HB3 LYS A 330 -5.359 38.970 58.918 1.00 0.00 H \\\\nATOM 4039 HG2 LYS A 330 -4.942 37.061 59.894 1.00 0.00 H \\\\nATOM 4040 HG3 LYS A 330 -3.898 36.910 58.745 1.00 0.00 H \\\\nATOM 4041 HD2 LYS A 330 -2.301 37.969 60.318 1.00 0.00 H \\\\nATOM 4042 HD3 LYS A 330 -3.346 37.621 61.422 1.00 0.00 H \\\\nATOM 4043 HE2 LYS A 330 -3.135 35.353 61.004 1.00 0.00 H \\\\nATOM 4044 HE3 LYS A 330 -2.272 35.621 59.733 1.00 0.00 H \\\\nATOM 4045 HZ1 LYS A 330 -0.708 35.202 61.149 1.00 0.00 H \\\\nATOM 4046 HZ2 LYS A 330 -0.782 36.632 61.400 1.00 0.00 H \\\\nATOM 4047 HZ3 LYS A 330 -1.441 35.701 62.300 1.00 0.00 H \\\\nATOM 4048 N ASN A 331 -1.902 37.862 57.052 1.00 0.00 N \\\\nATOM 4049 CA ASN A 331 -0.535 37.381 56.911 1.00 0.00 C \\\\nATOM 4050 C ASN A 331 0.213 38.042 55.763 1.00 0.00 C \\\\nATOM 4051 O ASN A 331 1.450 38.037 55.767 1.00 0.00 O \\\\nATOM 4052 CB ASN A 331 -0.523 35.863 56.699 1.00 0.00 C \\\\nATOM 4053 CG ASN A 331 -0.571 35.088 57.998 1.00 0.00 C \\\\nATOM 4054 OD1 ASN A 331 0.173 35.379 58.935 1.00 0.00 O \\\\nATOM 4055 ND2 ASN A 331 -1.442 34.086 58.059 1.00 0.00 N \\\\nATOM 4056 H ASN A 331 -2.479 37.422 56.590 1.00 0.00 H \\\\nATOM 4057 HA ASN A 331 -0.080 37.614 57.735 1.00 0.00 H \\\\nATOM 4058 HB2 ASN A 331 -1.282 35.612 56.149 1.00 0.00 H \\\\nATOM 4059 HB3 ASN A 331 0.277 35.616 56.209 1.00 0.00 H \\\\nATOM 4060 HD21 ASN A 331 -1.502 33.611 58.774 1.00 0.00 H \\\\nATOM 4061 HD22 ASN A 331 -1.946 33.912 57.384 1.00 0.00 H \\\\nATOM 4062 N ASN A 332 -0.495 38.598 54.781 1.00 0.00 N \\\\nATOM 4063 CA ASN A 332 0.137 39.146 53.586 1.00 0.00 C \\\\nATOM 4064 C ASN A 332 -0.530 40.475 53.247 1.00 0.00 C \\\\nATOM 4065 O ASN A 332 -1.257 41.054 54.059 1.00 0.00 O \\\\nATOM 4066 CB ASN A 332 0.058 38.145 52.424 1.00 0.00 C \\\\nATOM 4067 CG ASN A 332 0.392 36.726 52.849 1.00 0.00 C \\\\nATOM 4068 OD1 ASN A 332 -0.375 36.078 53.562 1.00 0.00 O \\\\nATOM 4069 ND2 ASN A 332 1.553 36.243 52.431 1.00 0.00 N \\\\nATOM 4070 H ASN A 332 -1.352 38.667 54.790 1.00 0.00 H \\\\nATOM 4071 HA ASN A 332 1.080 39.306 53.749 1.00 0.00 H \\\\nATOM 4072 HB2 ASN A 332 -0.835 38.164 52.046 1.00 0.00 H \\\\nATOM 4073 HB3 ASN A 332 0.669 38.421 51.722 1.00 0.00 H \\\\nATOM 4074 HD21 ASN A 332 1.795 35.449 52.657 1.00 0.00 H \\\\nATOM 4075 HD22 ASN A 332 2.065 36.723 51.934 1.00 0.00 H \\\\nATOM 4076 N GLY A 333 -0.271 40.967 52.039 1.00 0.00 N \\\\nATOM 4077 CA GLY A 333 -0.850 42.218 51.586 1.00 0.00 C \\\\nATOM 4078 C GLY A 333 -2.309 42.093 51.194 1.00 0.00 C \\\\nATOM 4079 O GLY A 333 -2.706 42.493 50.101 1.00 0.00 O \\\\nATOM 4080 H GLY A 333 0.243 40.585 51.465 1.00 0.00 H \\\\nATOM 4081 HA2 GLY A 333 -0.766 42.880 52.290 1.00 0.00 H \\\\nATOM 4082 HA3 GLY A 333 -0.344 42.546 50.826 1.00 0.00 H \\\\nATOM 4083 N SER A 345 -6.523 36.801 35.949 1.00 0.00 N \\\\nATOM 4084 CA SER A 345 -5.896 35.689 36.655 1.00 0.00 C \\\\nATOM 4085 C SER A 345 -6.498 35.518 38.045 1.00 0.00 C \\\\nATOM 4086 O SER A 345 -7.445 36.213 38.412 1.00 0.00 O \\\\nATOM 4087 CB SER A 345 -4.384 35.898 36.755 1.00 0.00 C \\\\nATOM 4088 OG SER A 345 -4.069 36.917 37.686 1.00 0.00 O \\\\nATOM 4089 HA SER A 345 -6.064 34.880 36.148 1.00 0.00 H \\\\nATOM 4090 HB2 SER A 345 -3.957 35.069 37.022 1.00 0.00 H \\\\nATOM 4091 HB3 SER A 345 -4.029 36.132 35.883 1.00 0.00 H \\\\nATOM 4092 HG SER A 345 -4.733 37.422 37.784 1.00 0.00 H \\\\nATOM 4093 N THR A 346 -5.939 34.592 38.818 1.00 0.00 N \\\\nATOM 4094 CA THR A 346 -6.493 34.274 40.123 1.00 0.00 C \\\\nATOM 4095 C THR A 346 -5.974 35.245 41.180 1.00 0.00 C \\\\nATOM 4096 O THR A 346 -4.963 35.928 40.999 1.00 0.00 O \\\\nATOM 4097 CB THR A 346 -6.158 32.835 40.521 1.00 0.00 C \\\\nATOM 4098 OG1 THR A 346 -4.738 32.650 40.507 1.00 0.00 O \\\\nATOM 4099 CG2 THR A 346 -6.806 31.851 39.556 1.00 0.00 C \\\\nATOM 4100 H THR A 346 -5.240 34.139 38.604 1.00 0.00 H \\\\nATOM 4101 HA THR A 346 -7.457 34.362 40.067 1.00 0.00 H \\\\nATOM 4102 HB THR A 346 -6.501 32.672 41.414 1.00 0.00 H \\\\nATOM 4103 HG1 THR A 346 -4.358 33.399 40.525 1.00 0.00 H \\\\nATOM 4104 HG21 THR A 346 -6.585 30.944 39.821 1.00 0.00 H \\\\nATOM 4105 HG22 THR A 346 -7.769 31.967 39.574 1.00 0.00 H \\\\nATOM 4106 HG23 THR A 346 -6.477 32.014 38.658 1.00 0.00 H \\\\nATOM 4107 N ASP A 347 -6.691 35.293 42.303 1.00 0.00 N \\\\nATOM 4108 CA ASP A 347 -6.341 36.073 43.485 1.00 0.00 C \\\\nATOM 4109 C ASP A 347 -5.721 35.170 44.539 1.00 0.00 C \\\\nATOM 4110 O ASP A 347 -6.259 34.086 44.805 1.00 0.00 O \\\\nATOM 4111 CB ASP A 347 -7.580 36.760 44.051 1.00 0.00 C \\\\nATOM 4112 CG ASP A 347 -7.386 37.239 45.474 1.00 0.00 C \\\\nATOM 4113 OD1 ASP A 347 -6.946 38.393 45.659 1.00 0.00 O \\\\nATOM 4114 OD2 ASP A 347 -7.679 36.464 46.409 1.00 0.00 O \\\\nATOM 4115 H ASP A 347 -7.424 34.853 42.398 1.00 0.00 H \\\\nATOM 4116 HA ASP A 347 -5.696 36.752 43.231 1.00 0.00 H \\\\nATOM 4117 HB2 ASP A 347 -7.811 37.516 43.488 1.00 0.00 H \\\\nATOM 4118 HB3 ASP A 347 -8.329 36.144 44.021 1.00 0.00 H \\\\nATOM 4119 N PRO A 348 -4.599 35.568 45.151 1.00 0.00 N \\\\nATOM 4120 CA PRO A 348 -3.872 34.618 46.012 1.00 0.00 C \\\\nATOM 4121 C PRO A 348 -4.652 34.207 47.245 1.00 0.00 C \\\\nATOM 4122 O PRO A 348 -4.608 33.035 47.639 1.00 0.00 O \\\\nATOM 4123 CB PRO A 348 -2.591 35.381 46.384 1.00 0.00 C \\\\nATOM 4124 CG PRO A 348 -2.617 36.662 45.601 1.00 0.00 C \\\\nATOM 4125 CD PRO A 348 -4.034 36.923 45.227 1.00 0.00 C \\\\nATOM 4126 HA PRO A 348 -3.704 33.778 45.557 1.00 0.00 H \\\\nATOM 4127 HB2 PRO A 348 -2.559 35.559 47.337 1.00 0.00 H \\\\nATOM 4128 HB3 PRO A 348 -1.803 34.859 46.167 1.00 0.00 H \\\\nATOM 4129 HG2 PRO A 348 -2.263 37.394 46.130 1.00 0.00 H \\\\nATOM 4130 HG3 PRO A 348 -2.062 36.590 44.809 1.00 0.00 H \\\\nATOM 4131 HD2 PRO A 348 -4.488 37.467 45.890 1.00 0.00 H \\\\nATOM 4132 HD3 PRO A 348 -4.103 37.391 44.380 1.00 0.00 H \\\\nATOM 4133 N ALA A 349 -5.362 35.145 47.874 1.00 0.00 N \\\\nATOM 4134 CA ALA A 349 -6.121 34.819 49.076 1.00 0.00 C \\\\nATOM 4135 C ALA A 349 -7.257 33.856 48.757 1.00 0.00 C \\\\nATOM 4136 O ALA A 349 -7.472 32.872 49.473 1.00 0.00 O \\\\nATOM 4137 CB ALA A 349 -6.656 36.097 49.721 1.00 0.00 C \\\\nATOM 4138 H ALA A 349 -5.416 35.966 47.623 1.00 0.00 H \\\\nATOM 4139 HA ALA A 349 -5.529 34.379 49.706 1.00 0.00 H \\\\nATOM 4140 HB1 ALA A 349 -7.159 35.871 50.519 1.00 0.00 H \\\\nATOM 4141 HB2 ALA A 349 -5.914 36.674 49.960 1.00 0.00 H \\\\nATOM 4142 HB3 ALA A 349 -7.235 36.558 49.094 1.00 0.00 H \\\\nATOM 4143 N ALA A 350 -7.997 34.125 47.679 1.00 0.00 N \\\\nATOM 4144 CA ALA A 350 -9.077 33.230 47.278 1.00 0.00 C \\\\nATOM 4145 C ALA A 350 -8.546 31.907 46.746 1.00 0.00 C \\\\nATOM 4146 O ALA A 350 -9.178 30.864 46.947 1.00 0.00 O \\\\nATOM 4147 CB ALA A 350 -9.960 33.908 46.231 1.00 0.00 C \\\\nATOM 4148 H ALA A 350 -7.890 34.813 47.174 1.00 0.00 H \\\\nATOM 4149 HA ALA A 350 -9.608 33.035 48.066 1.00 0.00 H \\\\nATOM 4150 HB1 ALA A 350 -10.674 33.306 45.971 1.00 0.00 H \\\\nATOM 4151 HB2 ALA A 350 -10.341 34.718 46.604 1.00 0.00 H \\\\nATOM 4152 HB3 ALA A 350 -9.426 34.131 45.452 1.00 0.00 H \\\\nATOM 4153 N GLN A 351 -7.402 31.928 46.059 1.00 0.00 N \\\\nATOM 4154 CA GLN A 351 -6.784 30.682 45.618 1.00 0.00 C \\\\nATOM 4155 C GLN A 351 -6.389 29.814 46.805 1.00 0.00 C \\\\nATOM 4156 O GLN A 351 -6.474 28.582 46.739 1.00 0.00 O \\\\nATOM 4157 CB GLN A 351 -5.569 30.976 44.737 1.00 0.00 C \\\\nATOM 4158 CG GLN A 351 -5.026 29.754 44.021 1.00 0.00 C \\\\nATOM 4159 CD GLN A 351 -6.036 29.151 43.065 1.00 0.00 C \\\\nATOM 4160 OE1 GLN A 351 -6.562 29.835 42.187 1.00 0.00 O \\\\nATOM 4161 NE2 GLN A 351 -6.317 27.863 43.236 1.00 0.00 N \\\\nATOM 4162 H GLN A 351 -6.975 32.643 45.842 1.00 0.00 H \\\\nATOM 4163 HA GLN A 351 -7.436 30.190 45.095 1.00 0.00 H \\\\nATOM 4164 HB2 GLN A 351 -5.811 31.646 44.079 1.00 0.00 H \\\\nATOM 4165 HB3 GLN A 351 -4.866 31.359 45.286 1.00 0.00 H \\\\nATOM 4166 HG2 GLN A 351 -4.225 29.998 43.531 1.00 0.00 H \\\\nATOM 4167 HG3 GLN A 351 -4.765 29.087 44.676 1.00 0.00 H \\\\nATOM 4168 HE21 GLN A 351 -5.929 27.417 43.861 1.00 0.00 H \\\\nATOM 4169 HE22 GLN A 351 -6.887 27.475 42.722 1.00 0.00 H \\\\nATOM 4170 N ALA A 352 -5.948 30.440 47.899 1.00 0.00 N \\\\nATOM 4171 CA ALA A 352 -5.623 29.685 49.105 1.00 0.00 C \\\\nATOM 4172 C ALA A 352 -6.864 29.029 49.694 1.00 0.00 C \\\\nATOM 4173 O ALA A 352 -6.803 27.893 50.181 1.00 0.00 O \\\\nATOM 4174 CB ALA A 352 -4.959 30.599 50.134 1.00 0.00 C \\\\nATOM 4175 H ALA A 352 -5.832 31.290 47.961 1.00 0.00 H \\\\nATOM 4176 HA ALA A 352 -5.002 28.980 48.864 1.00 0.00 H \\\\nATOM 4177 HB1 ALA A 352 -4.747 30.089 50.931 1.00 0.00 H \\\\nATOM 4178 HB2 ALA A 352 -4.144 30.968 49.761 1.00 0.00 H \\\\nATOM 4179 HB3 ALA A 352 -5.565 31.321 50.364 1.00 0.00 H \\\\nATOM 4180 N ALA A 353 -8.002 29.730 49.660 1.00 0.00 N \\\\nATOM 4181 CA ALA A 353 -9.242 29.146 50.160 1.00 0.00 C \\\\nATOM 4182 C ALA A 353 -9.669 27.957 49.309 1.00 0.00 C \\\\nATOM 4183 O ALA A 353 -10.071 26.916 49.841 1.00 0.00 O \\\\nATOM 4184 CB ALA A 353 -10.343 30.204 50.198 1.00 0.00 C \\\\nATOM 4185 H ALA A 353 -8.074 30.531 49.356 1.00 0.00 H \\\\nATOM 4186 HA ALA A 353 -9.086 28.825 51.062 1.00 0.00 H \\\\nATOM 4187 HB1 ALA A 353 -11.163 29.807 50.531 1.00 0.00 H \\\\nATOM 4188 HB2 ALA A 353 -10.075 30.930 50.783 1.00 0.00 H \\\\nATOM 4189 HB3 ALA A 353 -10.492 30.549 49.304 1.00 0.00 H \\\\nATOM 4190 N ALA A 354 -9.602 28.099 47.984 1.00 0.00 N \\\\nATOM 4191 CA ALA A 354 -9.978 26.998 47.105 1.00 0.00 C \\\\nATOM 4192 C ALA A 354 -9.018 25.824 47.255 1.00 0.00 C \\\\nATOM 4193 O ALA A 354 -9.446 24.664 47.285 1.00 0.00 O \\\\nATOM 4194 CB ALA A 354 -10.028 27.475 45.653 1.00 0.00 C \\\\nATOM 4195 H ALA A 354 -9.345 28.814 47.582 1.00 0.00 H \\\\nATOM 4196 HA ALA A 354 -10.862 26.691 47.362 1.00 0.00 H \\\\nATOM 4197 HB1 ALA A 354 -10.279 26.735 45.078 1.00 0.00 H \\\\nATOM 4198 HB2 ALA A 354 -10.682 28.186 45.568 1.00 0.00 H \\\\nATOM 4199 HB3 ALA A 354 -9.155 27.806 45.391 1.00 0.00 H \\\\nATOM 4200 N ASP A 355 -7.714 26.108 47.334 1.00 0.00 N \\\\nATOM 4201 CA ASP A 355 -6.734 25.050 47.561 1.00 0.00 C \\\\nATOM 4202 C ASP A 355 -6.985 24.338 48.886 1.00 0.00 C \\\\nATOM 4203 O ASP A 355 -6.910 23.106 48.962 1.00 0.00 O \\\\nATOM 4204 CB ASP A 355 -5.322 25.632 47.526 1.00 0.00 C \\\\nATOM 4205 CG ASP A 355 -4.739 25.666 46.128 1.00 0.00 C \\\\nATOM 4206 OD1 ASP A 355 -4.954 24.698 45.369 1.00 0.00 O \\\\nATOM 4207 OD2 ASP A 355 -4.067 26.663 45.786 1.00 0.00 O \\\\nATOM 4208 H ASP A 355 -7.383 26.898 47.259 1.00 0.00 H \\\\nATOM 4209 HA ASP A 355 -6.825 24.394 46.852 1.00 0.00 H \\\\nATOM 4210 HB2 ASP A 355 -5.338 26.532 47.888 1.00 0.00 H \\\\nATOM 4211 HB3 ASP A 355 -4.745 25.105 48.101 1.00 0.00 H \\\\nATOM 4212 N TYR A 356 -7.283 25.100 49.942 1.00 0.00 N \\\\nATOM 4213 CA TYR A 356 -7.535 24.493 51.246 1.00 0.00 C \\\\nATOM 4214 C TYR A 356 -8.782 23.620 51.213 1.00 0.00 C \\\\nATOM 4215 O TYR A 356 -8.777 22.499 51.735 1.00 0.00 O \\\\nATOM 4216 CB TYR A 356 -7.664 25.583 52.312 1.00 0.00 C \\\\nATOM 4217 CG TYR A 356 -7.600 25.080 53.740 1.00 0.00 C \\\\nATOM 4218 CD1 TYR A 356 -8.682 24.424 54.317 1.00 0.00 C \\\\nATOM 4219 CD2 TYR A 356 -6.464 25.272 54.516 1.00 0.00 C \\\\nATOM 4220 CE1 TYR A 356 -8.631 23.968 55.619 1.00 0.00 C \\\\nATOM 4221 CE2 TYR A 356 -6.406 24.819 55.823 1.00 0.00 C \\\\nATOM 4222 CZ TYR A 356 -7.492 24.168 56.368 1.00 0.00 C \\\\nATOM 4223 OH TYR A 356 -7.442 23.713 57.665 1.00 0.00 O \\\\nATOM 4224 H TYR A 356 -7.343 25.958 49.923 1.00 0.00 H \\\\nATOM 4225 HA TYR A 356 -6.783 23.922 51.470 1.00 0.00 H \\\\nATOM 4226 HB2 TYR A 356 -6.957 26.234 52.179 1.00 0.00 H \\\\nATOM 4227 HB3 TYR A 356 -8.506 26.047 52.183 1.00 0.00 H \\\\nATOM 4228 HD1 TYR A 356 -9.454 24.290 53.816 1.00 0.00 H \\\\nATOM 4229 HD2 TYR A 356 -5.730 25.712 54.152 1.00 0.00 H \\\\nATOM 4230 HE1 TYR A 356 -9.362 23.528 55.989 1.00 0.00 H \\\\nATOM 4231 HE2 TYR A 356 -5.638 24.953 56.331 1.00 0.00 H \\\\nATOM 4232 HH TYR A 356 -8.141 23.280 57.837 1.00 0.00 H \\\\nATOM 4233 N LEU A 357 -9.862 24.120 50.605 1.00 0.00 N \\\\nATOM 4234 CA LEU A 357 -11.097 23.344 50.533 1.00 0.00 C \\\\nATOM 4235 C LEU A 357 -10.897 22.066 49.733 1.00 0.00 C \\\\nATOM 4236 O LEU A 357 -11.450 21.013 50.076 1.00 0.00 O \\\\nATOM 4237 CB LEU A 357 -12.210 24.188 49.915 1.00 0.00 C \\\\nATOM 4238 CG LEU A 357 -12.883 25.206 50.835 1.00 0.00 C \\\\nATOM 4239 CD1 LEU A 357 -13.698 26.190 50.017 1.00 0.00 C \\\\nATOM 4240 CD2 LEU A 357 -13.754 24.499 51.859 1.00 0.00 C \\\\nATOM 4241 H LEU A 357 -9.898 24.895 50.234 1.00 0.00 H \\\\nATOM 4242 HA LEU A 357 -11.351 23.095 51.435 1.00 0.00 H \\\\nATOM 4243 HB2 LEU A 357 -11.844 24.663 49.153 1.00 0.00 H \\\\nATOM 4244 HB3 LEU A 357 -12.892 23.589 49.574 1.00 0.00 H \\\\nATOM 4245 HG LEU A 357 -12.198 25.700 51.312 1.00 0.00 H \\\\nATOM 4246 HD11 LEU A 357 -14.121 26.831 50.609 1.00 0.00 H \\\\nATOM 4247 HD12 LEU A 357 -13.115 26.657 49.398 1.00 0.00 H \\\\nATOM 4248 HD13 LEU A 357 -14.380 25.711 49.520 1.00 0.00 H \\\\nATOM 4249 HD21 LEU A 357 -14.174 25.156 52.435 1.00 0.00 H \\\\nATOM 4250 HD22 LEU A 357 -14.438 23.985 51.402 1.00 0.00 H \\\\nATOM 4251 HD23 LEU A 357 -13.206 23.904 52.394 1.00 0.00 H \\\\nATOM 4252 N MET A 358 -10.114 22.142 48.656 1.00 0.00 N \\\\nATOM 4253 CA MET A 358 -9.836 20.955 47.858 1.00 0.00 C \\\\nATOM 4254 C MET A 358 -9.052 19.925 48.655 1.00 0.00 C \\\\nATOM 4255 O MET A 358 -9.404 18.740 48.673 1.00 0.00 O \\\\nATOM 4256 CB MET A 358 -9.064 21.331 46.600 1.00 0.00 C \\\\nATOM 4257 CG MET A 358 -8.851 20.161 45.675 1.00 0.00 C \\\\nATOM 4258 SD MET A 358 -8.288 20.689 44.063 1.00 0.00 S \\\\nATOM 4259 CE MET A 358 -6.526 20.417 44.196 1.00 0.00 C \\\\nATOM 4260 H MET A 358 -9.740 22.864 48.375 1.00 0.00 H \\\\nATOM 4261 HA MET A 358 -10.687 20.562 47.606 1.00 0.00 H \\\\nATOM 4262 HB2 MET A 358 -9.544 22.029 46.127 1.00 0.00 H \\\\nATOM 4263 HB3 MET A 358 -8.203 21.700 46.852 1.00 0.00 H \\\\nATOM 4264 HG2 MET A 358 -8.200 19.555 46.063 1.00 0.00 H \\\\nATOM 4265 HG3 MET A 358 -9.680 19.666 45.583 1.00 0.00 H \\\\nATOM 4266 HE1 MET A 358 -6.095 20.671 43.365 1.00 0.00 H \\\\nATOM 4267 HE2 MET A 358 -6.170 20.953 44.922 1.00 0.00 H \\\\nATOM 4268 HE3 MET A 358 -6.356 19.479 44.374 1.00 0.00 H \\\\nATOM 4269 N ARG A 359 -7.973 20.356 49.313 1.00 0.00 N \\\\nATOM 4270 CA ARG A 359 -7.203 19.408 50.102 1.00 0.00 C \\\\nATOM 4271 C ARG A 359 -8.000 18.901 51.293 1.00 0.00 C \\\\nATOM 4272 O ARG A 359 -7.927 17.711 51.610 1.00 0.00 O \\\\nATOM 4273 CB ARG A 359 -5.886 20.041 50.550 1.00 0.00 C \\\\nATOM 4274 CG ARG A 359 -4.910 20.272 49.406 1.00 0.00 C \\\\nATOM 4275 CD ARG A 359 -3.635 20.956 49.866 1.00 0.00 C \\\\nATOM 4276 NE ARG A 359 -3.630 22.376 49.527 1.00 0.00 N \\\\nATOM 4277 CZ ARG A 359 -2.531 23.095 49.323 1.00 0.00 C \\\\nATOM 4278 NH1 ARG A 359 -1.335 22.529 49.418 1.00 0.00 N \\\\nATOM 4279 NH2 ARG A 359 -2.626 24.382 49.020 1.00 0.00 N \\\\nATOM 4280 H ARG A 359 -7.682 21.165 49.314 1.00 0.00 H \\\\nATOM 4281 HA ARG A 359 -7.002 18.641 49.543 1.00 0.00 H \\\\nATOM 4282 HB2 ARG A 359 -6.073 20.888 50.984 1.00 0.00 H \\\\nATOM 4283 HB3 ARG A 359 -5.468 19.469 51.213 1.00 0.00 H \\\\nATOM 4284 HG2 ARG A 359 -4.688 19.421 48.996 1.00 0.00 H \\\\nATOM 4285 HG3 ARG A 359 -5.337 20.813 48.724 1.00 0.00 H \\\\nATOM 4286 HD2 ARG A 359 -3.540 20.852 50.826 1.00 0.00 H \\\\nATOM 4287 HD3 ARG A 359 -2.870 20.523 49.457 1.00 0.00 H \\\\nATOM 4288 HE ARG A 359 -4.389 22.774 49.454 1.00 0.00 H \\\\nATOM 4289 HH11 ARG A 359 -1.269 21.694 49.612 1.00 0.00 H \\\\nATOM 4290 HH12 ARG A 359 -0.626 22.997 49.285 1.00 0.00 H \\\\nATOM 4291 HH21 ARG A 359 -3.399 24.753 48.955 1.00 0.00 H \\\\nATOM 4292 HH22 ARG A 359 -1.914 24.846 48.888 1.00 0.00 H \\\\nATOM 4293 N LEU A 360 -8.830 19.757 51.900 1.00 0.00 N \\\\nATOM 4294 CA LEU A 360 -9.651 19.318 53.026 1.00 0.00 C \\\\nATOM 4295 C LEU A 360 -10.593 18.195 52.615 1.00 0.00 C \\\\nATOM 4296 O LEU A 360 -10.739 17.200 53.338 1.00 0.00 O \\\\nATOM 4297 CB LEU A 360 -10.442 20.494 53.595 1.00 0.00 C \\\\nATOM 4298 CG LEU A 360 -11.635 20.136 54.486 1.00 0.00 C \\\\nATOM 4299 CD1 LEU A 360 -11.184 19.429 55.761 1.00 0.00 C \\\\nATOM 4300 CD2 LEU A 360 -12.465 21.366 54.815 1.00 0.00 C \\\\nATOM 4301 H LEU A 360 -8.929 20.582 51.677 1.00 0.00 H \\\\nATOM 4302 HA LEU A 360 -9.059 18.975 53.714 1.00 0.00 H \\\\nATOM 4303 HB2 LEU A 360 -9.835 21.051 54.107 1.00 0.00 H \\\\nATOM 4304 HB3 LEU A 360 -10.764 21.032 52.855 1.00 0.00 H \\\\nATOM 4305 HG LEU A 360 -12.195 19.521 53.987 1.00 0.00 H \\\\nATOM 4306 HD11 LEU A 360 -11.959 19.215 56.304 1.00 0.00 H \\\\nATOM 4307 HD12 LEU A 360 -10.716 18.611 55.530 1.00 0.00 H \\\\nATOM 4308 HD13 LEU A 360 -10.590 20.011 56.261 1.00 0.00 H \\\\nATOM 4309 HD21 LEU A 360 -13.212 21.111 55.379 1.00 0.00 H \\\\nATOM 4310 HD22 LEU A 360 -11.914 22.013 55.282 1.00 0.00 H \\\\nATOM 4311 HD23 LEU A 360 -12.800 21.760 53.994 1.00 0.00 H \\\\nATOM 4312 N ALA A 361 -11.239 18.333 51.454 1.00 0.00 N \\\\nATOM 4313 CA ALA A 361 -12.086 17.255 50.960 1.00 0.00 C \\\\nATOM 4314 C ALA A 361 -11.273 15.996 50.694 1.00 0.00 C \\\\nATOM 4315 O ALA A 361 -11.775 14.880 50.880 1.00 0.00 O \\\\nATOM 4316 CB ALA A 361 -12.820 17.700 49.696 1.00 0.00 C \\\\nATOM 4317 H ALA A 361 -11.200 19.029 50.950 1.00 0.00 H \\\\nATOM 4318 HA ALA A 361 -12.741 17.045 51.644 1.00 0.00 H \\\\nATOM 4319 HB1 ALA A 361 -13.381 16.976 49.375 1.00 0.00 H \\\\nATOM 4320 HB2 ALA A 361 -13.372 18.472 49.897 1.00 0.00 H \\\\nATOM 4321 HB3 ALA A 361 -12.174 17.935 49.012 1.00 0.00 H \\\\nATOM 4322 N LEU A 362 -10.022 16.153 50.252 1.00 0.00 N \\\\nATOM 4323 CA LEU A 362 -9.158 14.996 50.040 1.00 0.00 C \\\\nATOM 4324 C LEU A 362 -8.859 14.279 51.354 1.00 0.00 C \\\\nATOM 4325 O LEU A 362 -8.756 13.047 51.384 1.00 0.00 O \\\\nATOM 4326 CB LEU A 362 -7.861 15.423 49.345 1.00 0.00 C \\\\nATOM 4327 CG LEU A 362 -7.786 15.281 47.820 1.00 0.00 C \\\\nATOM 4328 CD1 LEU A 362 -6.351 15.454 47.337 1.00 0.00 C \\\\nATOM 4329 CD2 LEU A 362 -8.358 13.946 47.352 1.00 0.00 C \\\\nATOM 4330 H LEU A 362 -9.661 16.912 50.072 1.00 0.00 H \\\\nATOM 4331 HA LEU A 362 -9.626 14.370 49.466 1.00 0.00 H \\\\nATOM 4332 HB2 LEU A 362 -7.697 16.353 49.566 1.00 0.00 H \\\\nATOM 4333 HB3 LEU A 362 -7.134 14.908 49.728 1.00 0.00 H \\\\nATOM 4334 HG LEU A 362 -8.330 15.983 47.430 1.00 0.00 H \\\\nATOM 4335 HD11 LEU A 362 -6.321 15.361 46.372 1.00 0.00 H \\\\nATOM 4336 HD12 LEU A 362 -6.029 16.334 47.587 1.00 0.00 H \\\\nATOM 4337 HD13 LEU A 362 -5.788 14.777 47.744 1.00 0.00 H \\\\nATOM 4338 HD21 LEU A 362 -8.296 13.888 46.386 1.00 0.00 H \\\\nATOM 4339 HD22 LEU A 362 -7.855 13.220 47.752 1.00 0.00 H \\\\nATOM 4340 HD23 LEU A 362 -9.288 13.880 47.620 1.00 0.00 H \\\\nATOM 4341 N LYS A 363 -8.712 15.027 52.452 1.00 0.00 N \\\\nATOM 4342 CA LYS A 363 -8.369 14.409 53.729 1.00 0.00 C \\\\nATOM 4343 C LYS A 363 -9.574 13.812 54.443 1.00 0.00 C \\\\nATOM 4344 O LYS A 363 -9.389 13.107 55.441 1.00 0.00 O \\\\nATOM 4345 CB LYS A 363 -7.703 15.421 54.672 1.00 0.00 C \\\\nATOM 4346 CG LYS A 363 -6.842 16.472 54.001 1.00 0.00 C \\\\nATOM 4347 CD LYS A 363 -5.475 16.632 54.649 1.00 0.00 C \\\\nATOM 4348 CE LYS A 363 -4.598 17.570 53.839 1.00 0.00 C \\\\nATOM 4349 NZ LYS A 363 -4.644 17.232 52.389 1.00 0.00 N \\\\nATOM 4350 H LYS A 363 -8.806 15.882 52.476 1.00 0.00 H \\\\nATOM 4351 HA LYS A 363 -7.753 13.691 53.513 1.00 0.00 H \\\\nATOM 4352 HB2 LYS A 363 -8.396 15.870 55.180 1.00 0.00 H \\\\nATOM 4353 HB3 LYS A 363 -7.155 14.935 55.308 1.00 0.00 H \\\\nATOM 4354 HG2 LYS A 363 -6.725 16.237 53.067 1.00 0.00 H \\\\nATOM 4355 HG3 LYS A 363 -7.306 17.324 54.024 1.00 0.00 H \\\\nATOM 4356 HD2 LYS A 363 -5.578 16.977 55.550 1.00 0.00 H \\\\nATOM 4357 HD3 LYS A 363 -5.045 15.766 54.724 1.00 0.00 H \\\\nATOM 4358 HE2 LYS A 363 -4.892 18.485 53.970 1.00 0.00 H \\\\nATOM 4359 HE3 LYS A 363 -3.683 17.517 54.157 1.00 0.00 H \\\\nATOM 4360 HZ1 LYS A 363 -3.982 17.649 51.965 1.00 0.00 H \\\\nATOM 4361 HZ2 LYS A 363 -4.554 16.353 52.286 1.00 0.00 H \\\\nATOM 4362 HZ3 LYS A 363 -5.424 17.492 52.048 1.00 0.00 H \\\\nATOM 4363 N LYS A 364 -10.792 14.071 53.969 1.00 0.00 N \\\\nATOM 4364 CA LYS A 364 -11.991 13.538 54.601 1.00 0.00 C \\\\nATOM 4365 C LYS A 364 -12.571 12.342 53.857 1.00 0.00 C \\\\nATOM 4366 O LYS A 364 -13.697 11.928 54.153 1.00 0.00 O \\\\nATOM 4367 CB LYS A 364 -13.049 14.634 54.738 1.00 0.00 C \\\\nATOM 4368 CG LYS A 364 -12.647 15.767 55.668 1.00 0.00 C \\\\nATOM 4369 CD LYS A 364 -13.834 16.660 55.983 1.00 0.00 C \\\\nATOM 4370 CE LYS A 364 -14.909 15.891 56.732 1.00 0.00 C \\\\nATOM 4371 NZ LYS A 364 -16.068 16.754 57.087 1.00 0.00 N \\\\nATOM 4372 H LYS A 364 -10.943 14.558 53.276 1.00 0.00 H \\\\nATOM 4373 HA LYS A 364 -11.728 13.224 55.480 1.00 0.00 H \\\\nATOM 4374 HB2 LYS A 364 -13.238 15.000 53.860 1.00 0.00 H \\\\nATOM 4375 HB3 LYS A 364 -13.872 14.237 55.063 1.00 0.00 H \\\\nATOM 4376 HG2 LYS A 364 -12.286 15.402 56.491 1.00 0.00 H \\\\nATOM 4377 HG3 LYS A 364 -11.943 16.293 55.257 1.00 0.00 H \\\\nATOM 4378 HD2 LYS A 364 -13.542 17.416 56.516 1.00 0.00 H \\\\nATOM 4379 HD3 LYS A 364 -14.202 17.018 55.160 1.00 0.00 H \\\\nATOM 4380 HE2 LYS A 364 -15.214 15.149 56.186 1.00 0.00 H \\\\nATOM 4381 HE3 LYS A 364 -14.530 15.511 57.540 1.00 0.00 H \\\\nATOM 4382 HZ1 LYS A 364 -16.796 16.250 57.181 1.00 0.00 H \\\\nATOM 4383 HZ2 LYS A 364 -15.900 17.177 57.852 1.00 0.00 H \\\\nATOM 4384 HZ3 LYS A 364 -16.203 17.351 56.441 1.00 0.00 H \\\\nATOM 4385 N GLY A 365 -11.829 11.772 52.913 1.00 0.00 N \\\\nATOM 4386 CA GLY A 365 -12.257 10.560 52.243 1.00 0.00 C \\\\nATOM 4387 C GLY A 365 -13.182 10.767 51.061 1.00 0.00 C \\\\nATOM 4388 O GLY A 365 -14.229 10.118 50.967 1.00 0.00 O \\\\nATOM 4389 H GLY A 365 -11.070 12.077 52.648 1.00 0.00 H \\\\nATOM 4390 HA2 GLY A 365 -11.470 10.081 51.939 1.00 0.00 H \\\\nATOM 4391 HA3 GLY A 365 -12.704 9.991 52.889 1.00 0.00 H \\\\nATOM 4392 N SER A 366 -12.816 11.672 50.159 1.00 0.00 N \\\\nATOM 4393 CA SER A 366 -13.562 11.904 48.928 1.00 0.00 C \\\\nATOM 4394 C SER A 366 -12.829 11.211 47.784 1.00 0.00 C \\\\nATOM 4395 O SER A 366 -11.656 11.505 47.524 1.00 0.00 O \\\\nATOM 4396 CB SER A 366 -13.718 13.400 48.651 1.00 0.00 C \\\\nATOM 4397 OG SER A 366 -14.623 13.630 47.583 1.00 0.00 O \\\\nATOM 4398 H SER A 366 -12.122 12.173 50.245 1.00 0.00 H \\\\nATOM 4399 HA SER A 366 -14.456 11.538 49.015 1.00 0.00 H \\\\nATOM 4400 HB2 SER A 366 -14.036 13.849 49.450 1.00 0.00 H \\\\nATOM 4401 HB3 SER A 366 -12.854 13.784 48.435 1.00 0.00 H \\\\nATOM 4402 HG SER A 366 -14.573 14.433 47.341 1.00 0.00 H \\\\nATOM 4403 N GLU A 367 -13.515 10.290 47.108 1.00 0.00 N \\\\nATOM 4404 CA GLU A 367 -12.924 9.505 46.031 1.00 0.00 C \\\\nATOM 4405 C GLU A 367 -13.134 10.111 44.648 1.00 0.00 C \\\\nATOM 4406 O GLU A 367 -12.596 9.578 43.669 1.00 0.00 O \\\\nATOM 4407 CB GLU A 367 -13.499 8.084 46.048 1.00 0.00 C \\\\nATOM 4408 CG GLU A 367 -13.271 7.337 47.355 1.00 0.00 C \\\\nATOM 4409 CD GLU A 367 -13.737 5.893 47.293 1.00 0.00 C \\\\nATOM 4410 OE1 GLU A 367 -14.957 5.664 47.152 1.00 0.00 O \\\\nATOM 4411 OE2 GLU A 367 -12.881 4.989 47.385 1.00 0.00 O \\\\nATOM 4412 H GLU A 367 -14.340 10.104 47.264 1.00 0.00 H \\\\nATOM 4413 HA GLU A 367 -11.968 9.496 46.195 1.00 0.00 H \\\\nATOM 4414 HB2 GLU A 367 -14.452 8.129 45.874 1.00 0.00 H \\\\nATOM 4415 HB3 GLU A 367 -13.102 7.576 45.323 1.00 0.00 H \\\\nATOM 4416 HG2 GLU A 367 -12.327 7.359 47.575 1.00 0.00 H \\\\nATOM 4417 HG3 GLU A 367 -13.740 7.794 48.071 1.00 0.00 H \\\\nATOM 4418 N ASP A 368 -13.892 11.198 44.545 1.00 0.00 N \\\\nATOM 4419 CA ASP A 368 -14.293 11.765 43.267 1.00 0.00 C \\\\nATOM 4420 C ASP A 368 -13.301 12.827 42.793 1.00 0.00 C \\\\nATOM 4421 O ASP A 368 -12.394 13.245 43.519 1.00 0.00 O \\\\nATOM 4422 CB ASP A 368 -15.695 12.364 43.377 1.00 0.00 C \\\\nATOM 4423 CG ASP A 368 -16.343 12.592 42.024 1.00 0.00 C \\\\nATOM 4424 OD1 ASP A 368 -15.740 12.214 40.998 1.00 0.00 O \\\\nATOM 4425 OD2 ASP A 368 -17.451 13.164 41.989 1.00 0.00 O \\\\nATOM 4426 H ASP A 368 -14.191 11.631 45.225 1.00 0.00 H \\\\nATOM 4427 HA ASP A 368 -14.301 11.051 42.611 1.00 0.00 H \\\\nATOM 4428 HB2 ASP A 368 -16.255 11.772 43.904 1.00 0.00 H \\\\nATOM 4429 HB3 ASP A 368 -15.646 13.207 43.854 1.00 0.00 H \\\\nATOM 4430 N ASN A 369 -13.472 13.249 41.540 1.00 0.00 N \\\\nATOM 4431 CA ASN A 369 -12.853 14.487 41.086 1.00 0.00 C \\\\nATOM 4432 C ASN A 369 -13.297 15.637 41.981 1.00 0.00 C \\\\nATOM 4433 O ASN A 369 -14.441 15.672 42.446 1.00 0.00 O \\\\nATOM 4434 CB ASN A 369 -13.236 14.776 39.631 1.00 0.00 C \\\\nATOM 4435 CG ASN A 369 -12.696 13.741 38.657 1.00 0.00 C \\\\nATOM 4436 OD1 ASN A 369 -13.151 13.653 37.514 1.00 0.00 O \\\\nATOM 4437 ND2 ASN A 369 -11.718 12.959 39.101 1.00 0.00 N \\\\nATOM 4438 H ASN A 369 -13.937 12.837 40.946 1.00 0.00 H \\\\nATOM 4439 HA ASN A 369 -11.889 14.394 41.136 1.00 0.00 H \\\\nATOM 4440 HB2 ASN A 369 -14.203 14.809 39.557 1.00 0.00 H \\\\nATOM 4441 HB3 ASN A 369 -12.902 15.652 39.382 1.00 0.00 H \\\\nATOM 4442 HD21 ASN A 369 -11.377 12.362 38.584 1.00 0.00 H \\\\nATOM 4443 HD22 ASN A 369 -11.426 13.050 39.905 1.00 0.00 H \\\\nATOM 4444 N ILE A 370 -12.396 16.591 42.210 1.00 0.00 N \\\\nATOM 4445 CA ILE A 370 -12.684 17.750 43.041 1.00 0.00 C \\\\nATOM 4446 C ILE A 370 -12.446 19.004 42.213 1.00 0.00 C \\\\nATOM 4447 O ILE A 370 -11.427 19.111 41.519 1.00 0.00 O \\\\nATOM 4448 CB ILE A 370 -11.809 17.777 44.313 1.00 0.00 C \\\\nATOM 4449 CG1 ILE A 370 -11.690 16.405 45.000 1.00 0.00 C \\\\nATOM 4450 CG2 ILE A 370 -12.345 18.785 45.303 1.00 0.00 C \\\\nATOM 4451 CD1 ILE A 370 -12.861 15.990 45.837 1.00 0.00 C \\\\nATOM 4452 H ILE A 370 -11.600 16.581 41.885 1.00 0.00 H \\\\nATOM 4453 HA ILE A 370 -13.608 17.705 43.333 1.00 0.00 H \\\\nATOM 4454 HB ILE A 370 -10.920 18.032 44.020 1.00 0.00 H \\\\nATOM 4455 HG12 ILE A 370 -11.548 15.731 44.317 1.00 0.00 H \\\\nATOM 4456 HG13 ILE A 370 -10.899 16.411 45.561 1.00 0.00 H \\\\nATOM 4457 HG21 ILE A 370 -11.785 18.790 46.095 1.00 0.00 H \\\\nATOM 4458 HG22 ILE A 370 -12.342 19.667 44.900 1.00 0.00 H \\\\nATOM 4459 HG23 ILE A 370 -13.252 18.546 45.550 1.00 0.00 H \\\\nATOM 4460 HD11 ILE A 370 -12.689 15.117 46.224 1.00 0.00 H \\\\nATOM 4461 HD12 ILE A 370 -12.997 16.637 46.547 1.00 0.00 H \\\\nATOM 4462 HD13 ILE A 370 -13.656 15.947 45.283 1.00 0.00 H \\\\nATOM 4463 N THR A 371 -13.393 19.937 42.265 1.00 0.00 N \\\\nATOM 4464 CA THR A 371 -13.244 21.235 41.621 1.00 0.00 C \\\\nATOM 4465 C THR A 371 -13.911 22.259 42.518 1.00 0.00 C \\\\nATOM 4466 O THR A 371 -15.096 22.127 42.829 1.00 0.00 O \\\\nATOM 4467 CB THR A 371 -13.853 21.252 40.217 1.00 0.00 C \\\\nATOM 4468 OG1 THR A 371 -13.088 20.393 39.364 1.00 0.00 O \\\\nATOM 4469 CG2 THR A 371 -13.820 22.659 39.654 1.00 0.00 C \\\\nATOM 4470 H THR A 371 -14.141 19.833 42.676 1.00 0.00 H \\\\nATOM 4471 HA THR A 371 -12.303 21.440 41.504 1.00 0.00 H \\\\nATOM 4472 HB THR A 371 -14.772 20.946 40.265 1.00 0.00 H \\\\nATOM 4473 HG1 THR A 371 -12.477 20.027 39.810 1.00 0.00 H \\\\nATOM 4474 HG21 THR A 371 -14.207 22.661 38.765 1.00 0.00 H \\\\nATOM 4475 HG22 THR A 371 -14.330 23.250 40.230 1.00 0.00 H \\\\nATOM 4476 HG23 THR A 371 -12.902 22.967 39.607 1.00 0.00 H \\\\nATOM 4477 N VAL A 372 -13.155 23.264 42.944 1.00 0.00 N \\\\nATOM 4478 CA VAL A 372 -13.653 24.289 43.849 1.00 0.00 C \\\\nATOM 4479 C VAL A 372 -13.333 25.653 43.255 1.00 0.00 C \\\\nATOM 4480 O VAL A 372 -12.179 25.931 42.913 1.00 0.00 O \\\\nATOM 4481 CB VAL A 372 -13.044 24.162 45.260 1.00 0.00 C \\\\nATOM 4482 CG1 VAL A 372 -13.595 25.249 46.171 1.00 0.00 C \\\\nATOM 4483 CG2 VAL A 372 -13.324 22.786 45.847 1.00 0.00 C \\\\nATOM 4484 H VAL A 372 -12.333 23.370 42.714 1.00 0.00 H \\\\nATOM 4485 HA VAL A 372 -14.612 24.178 43.947 1.00 0.00 H \\\\nATOM 4486 HB VAL A 372 -12.083 24.272 45.189 1.00 0.00 H \\\\nATOM 4487 HG11 VAL A 372 -13.205 25.159 47.055 1.00 0.00 H \\\\nATOM 4488 HG12 VAL A 372 -13.372 26.120 45.807 1.00 0.00 H \\\\nATOM 4489 HG13 VAL A 372 -14.559 25.162 46.233 1.00 0.00 H \\\\nATOM 4490 HG21 VAL A 372 -12.934 22.726 46.733 1.00 0.00 H \\\\nATOM 4491 HG22 VAL A 372 -14.282 22.648 45.907 1.00 0.00 H \\\\nATOM 4492 HG23 VAL A 372 -12.935 22.105 45.276 1.00 0.00 H \\\\nATOM 4493 N ILE A 373 -14.352 26.497 43.136 1.00 0.00 N \\\\nATOM 4494 CA ILE A 373 -14.183 27.908 42.819 1.00 0.00 C \\\\nATOM 4495 C ILE A 373 -14.646 28.713 44.023 1.00 0.00 C \\\\nATOM 4496 O ILE A 373 -15.777 28.541 44.494 1.00 0.00 O \\\\nATOM 4497 CB ILE A 373 -14.966 28.309 41.556 1.00 0.00 C \\\\nATOM 4498 CG1 ILE A 373 -14.408 27.595 40.324 1.00 0.00 C \\\\nATOM 4499 CG2 ILE A 373 -14.916 29.817 41.361 1.00 0.00 C \\\\nATOM 4500 CD1 ILE A 373 -15.138 27.936 39.044 1.00 0.00 C \\\\nATOM 4501 H ILE A 373 -15.173 26.262 43.239 1.00 0.00 H \\\\nATOM 4502 HA ILE A 373 -13.249 28.088 42.629 1.00 0.00 H \\\\nATOM 4503 HB ILE A 373 -15.891 28.040 41.671 1.00 0.00 H \\\\nATOM 4504 HG12 ILE A 373 -13.471 27.824 40.224 1.00 0.00 H \\\\nATOM 4505 HG13 ILE A 373 -14.452 26.637 40.467 1.00 0.00 H \\\\nATOM 4506 HG21 ILE A 373 -15.412 30.057 40.563 1.00 0.00 H \\\\nATOM 4507 HG22 ILE A 373 -15.310 30.256 42.131 1.00 0.00 H \\\\nATOM 4508 HG23 ILE A 373 -13.993 30.101 41.265 1.00 0.00 H \\\\nATOM 4509 HD11 ILE A 373 -14.737 27.453 38.304 1.00 0.00 H \\\\nATOM 4510 HD12 ILE A 373 -16.071 27.684 39.126 1.00 0.00 H \\\\nATOM 4511 HD13 ILE A 373 -15.074 28.890 38.879 1.00 0.00 H \\\\nATOM 4512 N VAL A 374 -13.776 29.586 44.518 1.00 0.00 N \\\\nATOM 4513 CA VAL A 374 -14.111 30.516 45.589 1.00 0.00 C \\\\nATOM 4514 C VAL A 374 -14.061 31.917 45.005 1.00 0.00 C \\\\nATOM 4515 O VAL A 374 -13.022 32.342 44.488 1.00 0.00 O \\\\nATOM 4516 CB VAL A 374 -13.158 30.379 46.786 1.00 0.00 C \\\\nATOM 4517 CG1 VAL A 374 -13.392 31.506 47.787 1.00 0.00 C \\\\nATOM 4518 CG2 VAL A 374 -13.329 29.019 47.451 1.00 0.00 C \\\\nATOM 4519 H VAL A 374 -12.966 29.656 44.238 1.00 0.00 H \\\\nATOM 4520 HA VAL A 374 -14.998 30.320 45.930 1.00 0.00 H \\\\nATOM 4521 HB VAL A 374 -12.246 30.446 46.463 1.00 0.00 H \\\\nATOM 4522 HG11 VAL A 374 -12.784 31.406 48.536 1.00 0.00 H \\\\nATOM 4523 HG12 VAL A 374 -13.235 32.360 47.355 1.00 0.00 H \\\\nATOM 4524 HG13 VAL A 374 -14.307 31.470 48.107 1.00 0.00 H \\\\nATOM 4525 HG21 VAL A 374 -12.721 28.948 48.204 1.00 0.00 H \\\\nATOM 4526 HG22 VAL A 374 -14.242 28.924 47.763 1.00 0.00 H \\\\nATOM 4527 HG23 VAL A 374 -13.132 28.318 46.810 1.00 0.00 H \\\\nATOM 4528 N VAL A 375 -15.177 32.633 45.087 1.00 0.00 N \\\\nATOM 4529 CA VAL A 375 -15.274 34.002 44.597 1.00 0.00 C \\\\nATOM 4530 C VAL A 375 -15.431 34.912 45.804 1.00 0.00 C \\\\nATOM 4531 O VAL A 375 -16.411 34.801 46.550 1.00 0.00 O \\\\nATOM 4532 CB VAL A 375 -16.444 34.173 43.618 1.00 0.00 C \\\\nATOM 4533 CG1 VAL A 375 -16.395 35.547 42.968 1.00 0.00 C \\\\nATOM 4534 CG2 VAL A 375 -16.425 33.067 42.568 1.00 0.00 C \\\\nATOM 4535 H VAL A 375 -15.906 32.335 45.432 1.00 0.00 H \\\\nATOM 4536 HA VAL A 375 -14.472 34.232 44.102 1.00 0.00 H \\\\nATOM 4537 HB VAL A 375 -17.276 34.104 44.111 1.00 0.00 H \\\\nATOM 4538 HG11 VAL A 375 -17.139 35.641 42.353 1.00 0.00 H \\\\nATOM 4539 HG12 VAL A 375 -16.454 36.231 43.653 1.00 0.00 H \\\\nATOM 4540 HG13 VAL A 375 -15.561 35.646 42.483 1.00 0.00 H \\\\nATOM 4541 HG21 VAL A 375 -17.169 33.188 41.957 1.00 0.00 H \\\\nATOM 4542 HG22 VAL A 375 -15.591 33.105 42.073 1.00 0.00 H \\\\nATOM 4543 HG23 VAL A 375 -16.503 32.204 43.005 1.00 0.00 H \\\\nATOM 4544 N ASP A 376 -14.474 35.814 45.994 1.00 0.00 N \\\\nATOM 4545 CA ASP A 376 -14.517 36.739 47.119 1.00 0.00 C \\\\nATOM 4546 C ASP A 376 -15.401 37.925 46.758 1.00 0.00 C \\\\nATOM 4547 O ASP A 376 -15.084 38.687 45.837 1.00 0.00 O \\\\nATOM 4548 CB ASP A 376 -13.108 37.200 47.486 1.00 0.00 C \\\\nATOM 4549 CG ASP A 376 -13.083 38.062 48.733 1.00 0.00 C \\\\nATOM 4550 OD1 ASP A 376 -14.110 38.124 49.442 1.00 0.00 O \\\\nATOM 4551 OD2 ASP A 376 -12.034 38.682 49.005 1.00 0.00 O \\\\nATOM 4552 H ASP A 376 -13.790 35.906 45.481 1.00 0.00 H \\\\nATOM 4553 HA ASP A 376 -14.891 36.290 47.893 1.00 0.00 H \\\\nATOM 4554 HB2 ASP A 376 -12.543 36.424 47.622 1.00 0.00 H \\\\nATOM 4555 HB3 ASP A 376 -12.731 37.699 46.744 1.00 0.00 H \\\\nATOM 4556 N LEU A 377 -16.506 38.079 47.479 1.00 0.00 N \\\\nATOM 4557 CA LEU A 377 -17.464 39.140 47.201 1.00 0.00 C \\\\nATOM 4558 C LEU A 377 -17.158 40.386 48.026 1.00 0.00 C \\\\nATOM 4559 O LEU A 377 -17.627 41.480 47.711 1.00 0.00 O \\\\nATOM 4560 CB LEU A 377 -18.891 38.661 47.477 1.00 0.00 C \\\\nATOM 4561 CG LEU A 377 -19.433 37.586 46.532 1.00 0.00 C \\\\nATOM 4562 CD1 LEU A 377 -20.827 37.146 46.952 1.00 0.00 C \\\\nATOM 4563 CD2 LEU A 377 -19.428 38.084 45.093 1.00 0.00 C \\\\nATOM 4564 H LEU A 377 -16.720 37.573 48.141 1.00 0.00 H \\\\nATOM 4565 HA LEU A 377 -17.388 39.371 46.262 1.00 0.00 H \\\\nATOM 4566 HB2 LEU A 377 -18.928 38.318 48.384 1.00 0.00 H \\\\nATOM 4567 HB3 LEU A 377 -19.484 39.428 47.439 1.00 0.00 H \\\\nATOM 4568 HG LEU A 377 -18.849 36.813 46.586 1.00 0.00 H \\\\nATOM 4569 HD11 LEU A 377 -21.150 36.466 46.340 1.00 0.00 H \\\\nATOM 4570 HD12 LEU A 377 -20.795 36.783 47.851 1.00 0.00 H \\\\nATOM 4571 HD13 LEU A 377 -21.427 37.908 46.933 1.00 0.00 H \\\\nATOM 4572 HD21 LEU A 377 -19.774 37.391 44.509 1.00 0.00 H \\\\nATOM 4573 HD22 LEU A 377 -19.986 38.874 45.022 1.00 0.00 H \\\\nATOM 4574 HD23 LEU A 377 -18.521 38.304 44.830 1.00 0.00 H \\\\nATOM 4575 N VAL C 34 -38.148 -17.706 17.338 1.00 0.00 N \\\\nATOM 4576 CA VAL C 34 -36.736 -17.593 17.682 1.00 0.00 C \\\\nATOM 4577 C VAL C 34 -36.579 -17.235 19.152 1.00 0.00 C \\\\nATOM 4578 O VAL C 34 -35.726 -16.430 19.517 1.00 0.00 O \\\\nATOM 4579 CB VAL C 34 -36.027 -16.566 16.792 1.00 0.00 C \\\\nATOM 4580 CG1 VAL C 34 -35.637 -17.192 15.460 1.00 0.00 C \\\\nATOM 4581 CG2 VAL C 34 -36.916 -15.349 16.580 1.00 0.00 C \\\\nATOM 4582 HA VAL C 34 -36.317 -18.454 17.526 1.00 0.00 H \\\\nATOM 4583 HB VAL C 34 -35.215 -16.277 17.237 1.00 0.00 H \\\\nATOM 4584 HG11 VAL C 34 -35.190 -16.530 14.910 1.00 0.00 H \\\\nATOM 4585 HG12 VAL C 34 -35.038 -17.939 15.616 1.00 0.00 H \\\\nATOM 4586 HG13 VAL C 34 -36.434 -17.506 15.004 1.00 0.00 H \\\\nATOM 4587 HG21 VAL C 34 -36.457 -14.707 16.016 1.00 0.00 H \\\\nATOM 4588 HG22 VAL C 34 -37.742 -15.622 16.152 1.00 0.00 H \\\\nATOM 4589 HG23 VAL C 34 -37.116 -14.941 17.437 1.00 0.00 H \\\\nATOM 4590 N ARG C 35 -37.401 -17.867 19.995 1.00 0.00 N \\\\nATOM 4591 CA ARG C 35 -37.257 -17.794 21.444 1.00 0.00 C \\\\nATOM 4592 C ARG C 35 -37.209 -19.182 22.071 1.00 0.00 C \\\\nATOM 4593 O ARG C 35 -37.413 -19.322 23.282 1.00 0.00 O \\\\nATOM 4594 CB ARG C 35 -38.345 -16.933 22.086 1.00 0.00 C \\\\nATOM 4595 CG ARG C 35 -38.623 -15.650 21.328 1.00 0.00 C \\\\nATOM 4596 CD ARG C 35 -40.095 -15.392 21.301 1.00 0.00 C \\\\nATOM 4597 NE ARG C 35 -40.625 -15.468 22.655 1.00 0.00 N \\\\nATOM 4598 CZ ARG C 35 -41.915 -15.555 22.951 1.00 0.00 C \\\\nATOM 4599 NH1 ARG C 35 -42.814 -15.584 21.980 1.00 0.00 N \\\\nATOM 4600 NH2 ARG C 35 -42.304 -15.619 24.217 1.00 0.00 N \\\\nATOM 4601 H ARG C 35 -38.062 -18.353 19.736 1.00 0.00 H \\\\nATOM 4602 HA ARG C 35 -36.408 -17.360 21.621 1.00 0.00 H \\\\nATOM 4603 HB2 ARG C 35 -39.164 -17.450 22.145 1.00 0.00 H \\\\nATOM 4604 HB3 ARG C 35 -38.081 -16.714 22.993 1.00 0.00 H \\\\nATOM 4605 HG2 ARG C 35 -38.163 -14.908 21.751 1.00 0.00 H \\\\nATOM 4606 HG3 ARG C 35 -38.281 -15.718 20.423 1.00 0.00 H \\\\nATOM 4607 HD2 ARG C 35 -40.273 -14.517 20.922 1.00 0.00 H \\\\nATOM 4608 HD3 ARG C 35 -40.537 -16.042 20.733 1.00 0.00 H \\\\nATOM 4609 HE ARG C 35 -40.064 -15.456 23.307 1.00 0.00 H \\\\nATOM 4610 HH11 ARG C 35 -42.561 -15.546 21.159 1.00 0.00 H \\\\nATOM 4611 HH12 ARG C 35 -43.651 -15.640 22.170 1.00 0.00 H \\\\nATOM 4612 HH21 ARG C 35 -41.720 -15.604 24.848 1.00 0.00 H \\\\nATOM 4613 HH22 ARG C 35 -43.141 -15.675 24.407 1.00 0.00 H \\\\nATOM 4614 N ARG C 36 -36.969 -20.209 21.253 1.00 0.00 N \\\\nATOM 4615 CA ARG C 36 -36.479 -21.469 21.791 1.00 0.00 C \\\\nATOM 4616 C ARG C 36 -35.223 -21.205 22.610 1.00 0.00 C \\\\nATOM 4617 O ARG C 36 -34.947 -21.913 23.585 1.00 0.00 O \\\\nATOM 4618 CB ARG C 36 -36.200 -22.443 20.644 1.00 0.00 C \\\\nATOM 4619 CG ARG C 36 -35.239 -23.576 20.961 1.00 0.00 C \\\\nATOM 4620 CD ARG C 36 -35.805 -24.905 20.506 1.00 0.00 C \\\\nATOM 4621 NE ARG C 36 -34.989 -26.030 20.948 1.00 0.00 N \\\\nATOM 4622 CZ ARG C 36 -35.486 -27.153 21.453 1.00 0.00 C \\\\nATOM 4623 NH1 ARG C 36 -36.798 -27.303 21.565 1.00 0.00 N \\\\nATOM 4624 NH2 ARG C 36 -34.675 -28.131 21.836 1.00 0.00 N \\\\nATOM 4625 H ARG C 36 -37.082 -20.194 20.401 1.00 0.00 H \\\\nATOM 4626 HA ARG C 36 -37.146 -21.870 22.370 1.00 0.00 H \\\\nATOM 4627 HB2 ARG C 36 -37.043 -22.827 20.355 1.00 0.00 H \\\\nATOM 4628 HB3 ARG C 36 -35.845 -21.941 19.894 1.00 0.00 H \\\\nATOM 4629 HG2 ARG C 36 -34.388 -23.416 20.524 1.00 0.00 H \\\\nATOM 4630 HG3 ARG C 36 -35.067 -23.603 21.915 1.00 0.00 H \\\\nATOM 4631 HD2 ARG C 36 -36.706 -25.006 20.850 1.00 0.00 H \\\\nATOM 4632 HD3 ARG C 36 -35.868 -24.914 19.538 1.00 0.00 H \\\\nATOM 4633 HE ARG C 36 -34.135 -25.962 20.877 1.00 0.00 H \\\\nATOM 4634 HH11 ARG C 36 -37.326 -26.674 21.311 1.00 0.00 H \\\\nATOM 4635 HH12 ARG C 36 -37.121 -28.030 21.892 1.00 0.00 H \\\\nATOM 4636 HH21 ARG C 36 -33.824 -28.039 21.758 1.00 0.00 H \\\\nATOM 4637 HH22 ARG C 36 -35.001 -28.857 22.163 1.00 0.00 H \\\\nATOM 4638 N PHE C 37 -34.466 -20.171 22.235 1.00 0.00 N \\\\nATOM 4639 CA PHE C 37 -33.256 -19.773 22.936 1.00 0.00 C \\\\nATOM 4640 C PHE C 37 -33.520 -18.734 24.016 1.00 0.00 C \\\\nATOM 4641 O PHE C 37 -32.653 -18.519 24.870 1.00 0.00 O \\\\nATOM 4642 CB PHE C 37 -32.238 -19.199 21.945 1.00 0.00 C \\\\nATOM 4643 CG PHE C 37 -31.769 -20.184 20.923 1.00 0.00 C \\\\nATOM 4644 CD1 PHE C 37 -31.077 -21.318 21.305 1.00 0.00 C \\\\nATOM 4645 CD2 PHE C 37 -32.028 -19.980 19.579 1.00 0.00 C \\\\nATOM 4646 CE1 PHE C 37 -30.643 -22.229 20.365 1.00 0.00 C \\\\nATOM 4647 CE2 PHE C 37 -31.598 -20.889 18.632 1.00 0.00 C \\\\nATOM 4648 CZ PHE C 37 -30.905 -22.015 19.027 1.00 0.00 C \\\\nATOM 4649 H PHE C 37 -34.649 -19.677 21.555 1.00 0.00 H \\\\nATOM 4650 HA PHE C 37 -32.908 -20.571 23.363 1.00 0.00 H \\\\nATOM 4651 HB2 PHE C 37 -32.634 -18.439 21.491 1.00 0.00 H \\\\nATOM 4652 HB3 PHE C 37 -31.471 -18.867 22.438 1.00 0.00 H \\\\nATOM 4653 HD1 PHE C 37 -30.902 -21.468 22.206 1.00 0.00 H \\\\nATOM 4654 HD2 PHE C 37 -32.497 -19.223 19.311 1.00 0.00 H \\\\nATOM 4655 HE1 PHE C 37 -30.174 -22.987 20.632 1.00 0.00 H \\\\nATOM 4656 HE2 PHE C 37 -31.775 -20.743 17.731 1.00 0.00 H \\\\nATOM 4657 HZ PHE C 37 -30.615 -22.629 18.392 1.00 0.00 H \\\\nATOM 4658 N HIS C 38 -34.686 -18.079 24.002 1.00 0.00 N \\\\nATOM 4659 CA HIS C 38 -34.948 -16.966 24.908 1.00 0.00 C \\\\nATOM 4660 C HIS C 38 -36.200 -17.193 25.746 1.00 0.00 C \\\\nATOM 4661 O HIS C 38 -36.806 -16.228 26.223 1.00 0.00 O \\\\nATOM 4662 CB HIS C 38 -35.079 -15.655 24.131 1.00 0.00 C \\\\nATOM 4663 CG HIS C 38 -33.938 -15.384 23.202 1.00 0.00 C \\\\nATOM 4664 ND1 HIS C 38 -32.749 -14.829 23.622 1.00 0.00 N \\\\nATOM 4665 CD2 HIS C 38 -33.808 -15.587 21.870 1.00 0.00 C \\\\nATOM 4666 CE1 HIS C 38 -31.935 -14.704 22.589 1.00 0.00 C \\\\nATOM 4667 NE2 HIS C 38 -32.553 -15.157 21.514 1.00 0.00 N \\\\nATOM 4668 H HIS C 38 -35.337 -18.268 23.472 1.00 0.00 H \\\\nATOM 4669 HA HIS C 38 -34.190 -16.909 25.511 1.00 0.00 H \\\\nATOM 4670 HB2 HIS C 38 -35.903 -15.673 23.620 1.00 0.00 H \\\\nATOM 4671 HB3 HIS C 38 -35.152 -14.922 24.762 1.00 0.00 H \\\\nATOM 4672 HD1 HIS C 38 -32.565 -14.600 24.430 1.00 0.00 H \\\\nATOM 4673 HD2 HIS C 38 -34.449 -15.950 21.302 1.00 0.00 H \\\\nATOM 4674 HE1 HIS C 38 -31.073 -14.356 22.615 1.00 0.00 H \\\\nATOM 4675 HE2 HIS C 38 -32.223 -15.179 20.720 1.00 0.00 H \\\\nATOM 4676 N ARG C 39 -36.592 -18.448 25.947 1.00 0.00 N \\\\nATOM 4677 CA ARG C 39 -37.640 -18.781 26.898 1.00 0.00 C \\\\nATOM 4678 C ARG C 39 -36.969 -19.120 28.218 1.00 0.00 C \\\\nATOM 4679 O ARG C 39 -36.033 -19.926 28.257 1.00 0.00 O \\\\nATOM 4680 CB ARG C 39 -38.501 -19.944 26.406 1.00 0.00 C \\\\nATOM 4681 CG ARG C 39 -39.859 -19.518 25.859 1.00 0.00 C \\\\nATOM 4682 CD ARG C 39 -40.859 -19.239 26.974 1.00 0.00 C \\\\nATOM 4683 NE ARG C 39 -41.921 -18.329 26.544 1.00 0.00 N \\\\nATOM 4684 CZ ARG C 39 -42.917 -17.914 27.321 1.00 0.00 C \\\\nATOM 4685 NH1 ARG C 39 -43.835 -17.087 26.839 1.00 0.00 N \\\\nATOM 4686 NH2 ARG C 39 -42.999 -18.327 28.580 1.00 0.00 N \\\\nATOM 4687 H ARG C 39 -36.258 -19.126 25.536 1.00 0.00 H \\\\nATOM 4688 HA ARG C 39 -38.239 -18.026 27.005 1.00 0.00 H \\\\nATOM 4689 HB2 ARG C 39 -38.018 -20.422 25.713 1.00 0.00 H \\\\nATOM 4690 HB3 ARG C 39 -38.637 -20.566 27.138 1.00 0.00 H \\\\nATOM 4691 HG2 ARG C 39 -39.753 -18.723 25.314 1.00 0.00 H \\\\nATOM 4692 HG3 ARG C 39 -40.207 -20.214 25.280 1.00 0.00 H \\\\nATOM 4693 HD2 ARG C 39 -41.251 -20.075 27.272 1.00 0.00 H \\\\nATOM 4694 HD3 ARG C 39 -40.395 -18.856 27.735 1.00 0.00 H \\\\nATOM 4695 HE ARG C 39 -41.900 -18.043 25.733 1.00 0.00 H \\\\nATOM 4696 HH11 ARG C 39 -43.786 -16.819 26.023 1.00 0.00 H \\\\nATOM 4697 HH12 ARG C 39 -44.479 -16.819 27.342 1.00 0.00 H \\\\nATOM 4698 HH21 ARG C 39 -42.407 -18.865 28.896 1.00 0.00 H \\\\nATOM 4699 HH22 ARG C 39 -43.644 -18.057 29.080 1.00 0.00 H \\\\nATOM 4700 N HIS C 40 -37.441 -18.507 29.292 1.00 0.00 N \\\\nATOM 4701 CA HIS C 40 -36.831 -18.677 30.597 1.00 0.00 C \\\\nATOM 4702 C HIS C 40 -37.891 -19.028 31.626 1.00 0.00 C \\\\nATOM 4703 O HIS C 40 -39.052 -18.625 31.508 1.00 0.00 O \\\\nATOM 4704 CB HIS C 40 -36.089 -17.414 31.029 1.00 0.00 C \\\\nATOM 4705 CG HIS C 40 -35.012 -16.988 30.080 1.00 0.00 C \\\\nATOM 4706 ND1 HIS C 40 -33.857 -17.715 29.891 1.00 0.00 N \\\\nATOM 4707 CD2 HIS C 40 -34.908 -15.901 29.277 1.00 0.00 C \\\\nATOM 4708 CE1 HIS C 40 -33.092 -17.101 29.007 1.00 0.00 C \\\\nATOM 4709 NE2 HIS C 40 -33.706 -15.997 28.620 1.00 0.00 N \\\\nATOM 4710 H HIS C 40 -38.122 -17.982 29.284 1.00 0.00 H \\\\nATOM 4711 HA HIS C 40 -36.188 -19.401 30.535 1.00 0.00 H \\\\nATOM 4712 HB2 HIS C 40 -36.728 -16.691 31.124 1.00 0.00 H \\\\nATOM 4713 HB3 HIS C 40 -35.697 -17.563 31.904 1.00 0.00 H \\\\nATOM 4714 HD1 HIS C 40 -33.664 -18.454 30.287 1.00 0.00 H \\\\nATOM 4715 HD2 HIS C 40 -35.533 -15.218 29.188 1.00 0.00 H \\\\nATOM 4716 HE1 HIS C 40 -32.262 -17.396 28.708 1.00 0.00 H \\\\nATOM 4717 HE2 HIS C 40 -33.402 -15.430 28.049 1.00 0.00 H \\\\nATOM 4718 N GLU C 41 -37.483 -19.791 32.633 1.00 0.00 N \\\\nATOM 4719 CA GLU C 41 -38.373 -20.083 33.745 1.00 0.00 C \\\\nATOM 4720 C GLU C 41 -37.831 -19.422 35.005 1.00 0.00 C \\\\nATOM 4721 O GLU C 41 -37.166 -20.078 35.818 1.00 0.00 O \\\\nATOM 4722 CB GLU C 41 -38.516 -21.591 33.949 1.00 0.00 C \\\\nATOM 4723 CG GLU C 41 -38.911 -22.351 32.696 1.00 0.00 C \\\\nATOM 4724 CD GLU C 41 -37.752 -23.122 32.098 1.00 0.00 C \\\\nATOM 4725 OE1 GLU C 41 -36.903 -23.615 32.872 1.00 0.00 O \\\\nATOM 4726 OE2 GLU C 41 -37.686 -23.233 30.855 1.00 0.00 O \\\\nATOM 4727 H GLU C 41 -36.702 -20.146 32.691 1.00 0.00 H \\\\nATOM 4728 HA GLU C 41 -39.254 -19.729 33.547 1.00 0.00 H \\\\nATOM 4729 HB2 GLU C 41 -37.675 -21.944 34.278 1.00 0.00 H \\\\nATOM 4730 HB3 GLU C 41 -39.180 -21.753 34.637 1.00 0.00 H \\\\nATOM 4731 HG2 GLU C 41 -39.631 -22.966 32.907 1.00 0.00 H \\\\nATOM 4732 HG3 GLU C 41 -39.255 -21.727 32.038 1.00 0.00 H \\\\nATOM 4733 N PRO C 42 -38.080 -18.129 35.197 1.00 0.00 N \\\\nATOM 4734 CA PRO C 42 -37.633 -17.471 36.426 1.00 0.00 C \\\\nATOM 4735 C PRO C 42 -38.415 -17.981 37.623 1.00 0.00 C \\\\nATOM 4736 O PRO C 42 -39.605 -18.290 37.537 1.00 0.00 O \\\\nATOM 4737 CB PRO C 42 -37.917 -15.987 36.163 1.00 0.00 C \\\\nATOM 4738 CG PRO C 42 -39.023 -15.998 35.169 1.00 0.00 C \\\\nATOM 4739 CD PRO C 42 -38.774 -17.194 34.296 1.00 0.00 C \\\\nATOM 4740 HA PRO C 42 -36.700 -17.640 36.632 1.00 0.00 H \\\\nATOM 4741 HB2 PRO C 42 -38.176 -15.526 36.976 1.00 0.00 H \\\\nATOM 4742 HB3 PRO C 42 -37.133 -15.532 35.816 1.00 0.00 H \\\\nATOM 4743 HG2 PRO C 42 -39.885 -16.061 35.608 1.00 0.00 H \\\\nATOM 4744 HG3 PRO C 42 -39.030 -15.181 34.647 1.00 0.00 H \\\\nATOM 4745 HD2 PRO C 42 -39.602 -17.570 33.958 1.00 0.00 H \\\\nATOM 4746 HD3 PRO C 42 -38.230 -16.968 33.525 1.00 0.00 H \\\\nATOM 4747 N ARG C 43 -37.724 -18.075 38.753 1.00 0.00 N \\\\nATOM 4748 CA ARG C 43 -38.378 -18.428 40.001 1.00 0.00 C \\\\nATOM 4749 C ARG C 43 -39.220 -17.246 40.493 1.00 0.00 C \\\\nATOM 4750 O ARG C 43 -39.332 -16.208 39.834 1.00 0.00 O \\\\nATOM 4751 CB ARG C 43 -37.342 -18.884 41.023 1.00 0.00 C \\\\nATOM 4752 CG ARG C 43 -36.510 -20.077 40.567 1.00 0.00 C \\\\nATOM 4753 CD ARG C 43 -37.380 -21.164 39.947 1.00 0.00 C \\\\nATOM 4754 NE ARG C 43 -38.111 -21.930 40.953 1.00 0.00 N \\\\nATOM 4755 CZ ARG C 43 -38.885 -22.976 40.680 1.00 0.00 C \\\\nATOM 4756 NH1 ARG C 43 -39.036 -23.382 39.427 1.00 0.00 N \\\\nATOM 4757 NH2 ARG C 43 -39.512 -23.613 41.659 1.00 0.00 N \\\\nATOM 4758 H ARG C 43 -36.877 -17.938 38.816 1.00 0.00 H \\\\nATOM 4759 HA ARG C 43 -38.983 -19.174 39.863 1.00 0.00 H \\\\nATOM 4760 HB2 ARG C 43 -36.748 -18.143 41.221 1.00 0.00 H \\\\nATOM 4761 HB3 ARG C 43 -37.795 -19.113 41.850 1.00 0.00 H \\\\nATOM 4762 HG2 ARG C 43 -35.849 -19.783 39.921 1.00 0.00 H \\\\nATOM 4763 HG3 ARG C 43 -36.025 -20.442 41.323 1.00 0.00 H \\\\nATOM 4764 HD2 ARG C 43 -38.010 -20.759 39.331 1.00 0.00 H \\\\nATOM 4765 HD3 ARG C 43 -36.823 -21.765 39.428 1.00 0.00 H \\\\nATOM 4766 HE ARG C 43 -38.036 -21.689 41.775 1.00 0.00 H \\\\nATOM 4767 HH11 ARG C 43 -38.633 -22.969 38.790 1.00 0.00 H \\\\nATOM 4768 HH12 ARG C 43 -39.537 -24.059 39.252 1.00 0.00 H \\\\nATOM 4769 HH21 ARG C 43 -39.418 -23.350 42.472 1.00 0.00 H \\\\nATOM 4770 HH22 ARG C 43 -40.012 -24.289 41.481 1.00 0.00 H \\\\nATOM 4771 N ASP C 44 -39.822 -17.402 41.675 1.00 0.00 N \\\\nATOM 4772 CA ASP C 44 -40.648 -16.336 42.238 1.00 0.00 C \\\\nATOM 4773 C ASP C 44 -39.860 -15.086 42.614 1.00 0.00 C \\\\nATOM 4774 O ASP C 44 -40.445 -13.999 42.654 1.00 0.00 O \\\\nATOM 4775 CB ASP C 44 -41.406 -16.859 43.456 1.00 0.00 C \\\\nATOM 4776 CG ASP C 44 -42.516 -17.815 43.077 1.00 0.00 C \\\\nATOM 4777 OD1 ASP C 44 -43.269 -17.504 42.129 1.00 0.00 O \\\\nATOM 4778 OD2 ASP C 44 -42.635 -18.878 43.721 1.00 0.00 O \\\\nATOM 4779 H ASP C 44 -39.765 -18.110 42.160 1.00 0.00 H \\\\nATOM 4780 HA ASP C 44 -41.267 -16.069 41.541 1.00 0.00 H \\\\nATOM 4781 HB2 ASP C 44 -40.786 -17.307 44.052 1.00 0.00 H \\\\nATOM 4782 HB3 ASP C 44 -41.780 -16.111 43.947 1.00 0.00 H \\\\nATOM 4783 N HIS C 45 -38.568 -15.205 42.910 1.00 0.00 N \\\\nATOM 4784 CA HIS C 45 -37.762 -14.069 43.339 1.00 0.00 C \\\\nATOM 4785 C HIS C 45 -36.723 -13.711 42.283 1.00 0.00 C \\\\nATOM 4786 O HIS C 45 -35.693 -13.103 42.593 1.00 0.00 O \\\\nATOM 4787 CB HIS C 45 -37.125 -14.338 44.701 1.00 0.00 C \\\\nATOM 4788 CG HIS C 45 -38.123 -14.398 45.816 1.00 0.00 C \\\\nATOM 4789 ND1 HIS C 45 -38.610 -15.587 46.316 1.00 0.00 N \\\\nATOM 4790 CD2 HIS C 45 -38.753 -13.416 46.502 1.00 0.00 C \\\\nATOM 4791 CE1 HIS C 45 -39.481 -15.334 47.276 1.00 0.00 C \\\\nATOM 4792 NE2 HIS C 45 -39.587 -14.024 47.409 1.00 0.00 N \\\\nATOM 4793 H HIS C 45 -38.136 -15.947 42.867 1.00 0.00 H \\\\nATOM 4794 HA HIS C 45 -38.344 -13.300 43.441 1.00 0.00 H \\\\nATOM 4795 HB2 HIS C 45 -36.639 -15.176 44.664 1.00 0.00 H \\\\nATOM 4796 HB3 HIS C 45 -36.477 -13.642 44.892 1.00 0.00 H \\\\nATOM 4797 HD1 HIS C 45 -38.382 -16.371 46.045 1.00 0.00 H \\\\nATOM 4798 HD2 HIS C 45 -38.642 -12.500 46.382 1.00 0.00 H \\\\nATOM 4799 HE1 HIS C 45 -39.942 -15.970 47.774 1.00 0.00 H \\\\nATOM 4800 HE2 HIS C 45 -40.095 -13.618 47.972 1.00 0.00 H \\\\nATOM 4801 N GLN C 46 -36.994 -14.092 41.039 1.00 0.00 N \\\\nATOM 4802 CA GLN C 46 -36.199 -13.782 39.865 1.00 0.00 C \\\\nATOM 4803 C GLN C 46 -37.088 -13.069 38.858 1.00 0.00 C \\\\nATOM 4804 O GLN C 46 -38.318 -13.145 38.924 1.00 0.00 O \\\\nATOM 4805 CB GLN C 46 -35.629 -15.047 39.208 1.00 0.00 C \\\\nATOM 4806 CG GLN C 46 -34.532 -15.745 39.973 1.00 0.00 C \\\\nATOM 4807 CD GLN C 46 -34.052 -16.998 39.265 1.00 0.00 C \\\\nATOM 4808 OE1 GLN C 46 -34.850 -17.753 38.705 1.00 0.00 O \\\\nATOM 4809 NE2 GLN C 46 -32.743 -17.221 39.275 1.00 0.00 N \\\\nATOM 4810 H GLN C 46 -37.687 -14.565 40.851 1.00 0.00 H \\\\nATOM 4811 HA GLN C 46 -35.454 -13.225 40.140 1.00 0.00 H \\\\nATOM 4812 HB2 GLN C 46 -36.355 -15.675 39.071 1.00 0.00 H \\\\nATOM 4813 HB3 GLN C 46 -35.289 -14.811 38.331 1.00 0.00 H \\\\nATOM 4814 HG2 GLN C 46 -33.786 -15.137 40.094 1.00 0.00 H \\\\nATOM 4815 HG3 GLN C 46 -34.854 -15.978 40.858 1.00 0.00 H \\\\nATOM 4816 HE21 GLN C 46 -32.216 -16.672 39.676 1.00 0.00 H \\\\nATOM 4817 HE22 GLN C 46 -32.422 -17.914 38.880 1.00 0.00 H \\\\nATOM 4818 N CYS C 47 -36.457 -12.368 37.924 1.00 0.00 N \\\\nATOM 4819 CA CYS C 47 -37.177 -11.729 36.838 1.00 0.00 C \\\\nATOM 4820 C CYS C 47 -36.451 -12.012 35.532 1.00 0.00 C \\\\nATOM 4821 O CYS C 47 -35.248 -12.286 35.509 1.00 0.00 O \\\\nATOM 4822 CB CYS C 47 -37.309 -10.216 37.053 1.00 0.00 C \\\\nATOM 4823 SG CYS C 47 -35.743 -9.329 36.982 1.00 0.00 S \\\\nATOM 4824 H CYS C 47 -35.605 -12.251 37.904 1.00 0.00 H \\\\nATOM 4825 HA CYS C 47 -38.075 -12.093 36.808 1.00 0.00 H \\\\nATOM 4826 HB2 CYS C 47 -37.907 -9.854 36.380 1.00 0.00 H \\\\nATOM 4827 HB3 CYS C 47 -37.722 -10.056 37.916 1.00 0.00 H \\\\nATOM 4828 HG CYS C 47 -34.885 -10.063 36.577 1.00 0.00 H \\\\nATOM 4829 N SER C 48 -37.203 -11.940 34.439 1.00 0.00 N \\\\nATOM 4830 CA SER C 48 -36.686 -12.286 33.125 1.00 0.00 C \\\\nATOM 4831 C SER C 48 -37.316 -11.367 32.094 1.00 0.00 C \\\\nATOM 4832 O SER C 48 -38.475 -10.966 32.226 1.00 0.00 O \\\\nATOM 4833 CB SER C 48 -36.973 -13.749 32.772 1.00 0.00 C \\\\nATOM 4834 OG SER C 48 -36.346 -14.119 31.555 1.00 0.00 O \\\\nATOM 4835 H SER C 48 -38.026 -11.689 34.440 1.00 0.00 H \\\\nATOM 4836 HA SER C 48 -35.723 -12.174 33.131 1.00 0.00 H \\\\nATOM 4837 HB2 SER C 48 -36.659 -14.324 33.488 1.00 0.00 H \\\\nATOM 4838 HB3 SER C 48 -37.931 -13.884 32.699 1.00 0.00 H \\\\nATOM 4839 HG SER C 48 -35.512 -14.115 31.657 1.00 0.00 H \\\\nATOM 4840 N SER C 49 -36.540 -11.032 31.069 1.00 0.00 N \\\\nATOM 4841 CA SER C 49 -37.045 -10.219 29.972 1.00 0.00 C \\\\nATOM 4842 C SER C 49 -36.099 -10.353 28.787 1.00 0.00 C \\\\nATOM 4843 O SER C 49 -35.098 -11.072 28.838 1.00 0.00 O \\\\nATOM 4844 CB SER C 49 -37.204 -8.757 30.390 1.00 0.00 C \\\\nATOM 4845 OG SER C 49 -38.257 -8.143 29.668 1.00 0.00 O \\\\nATOM 4846 H SER C 49 -35.716 -11.266 30.991 1.00 0.00 H \\\\nATOM 4847 HA SER C 49 -37.926 -10.535 29.719 1.00 0.00 H \\\\nATOM 4848 HB2 SER C 49 -37.385 -8.705 31.342 1.00 0.00 H \\\\nATOM 4849 HB3 SER C 49 -36.375 -8.278 30.232 1.00 0.00 H \\\\nATOM 4850 HG SER C 49 -38.765 -7.740 30.202 1.00 0.00 H \\\\nATOM 4851 N ALA C 50 -36.429 -9.640 27.714 1.00 0.00 N \\\\nATOM 4852 CA ALA C 50 -35.646 -9.661 26.491 1.00 0.00 C \\\\nATOM 4853 C ALA C 50 -35.738 -8.297 25.826 1.00 0.00 C \\\\nATOM 4854 O ALA C 50 -36.685 -7.538 26.047 1.00 0.00 O \\\\nATOM 4855 CB ALA C 50 -36.121 -10.757 25.531 1.00 0.00 C \\\\nATOM 4856 H ALA C 50 -37.119 -9.128 27.678 1.00 0.00 H \\\\nATOM 4857 HA ALA C 50 -34.724 -9.860 26.716 1.00 0.00 H \\\\nATOM 4858 HB1 ALA C 50 -35.577 -10.742 24.728 1.00 0.00 H \\\\nATOM 4859 HB2 ALA C 50 -36.038 -11.622 25.961 1.00 0.00 H \\\\nATOM 4860 HB3 ALA C 50 -37.049 -10.601 25.296 1.00 0.00 H \\\\nATOM 4861 N VAL C 51 -34.732 -7.990 25.014 1.00 0.00 N \\\\nATOM 4862 CA VAL C 51 -34.718 -6.795 24.184 1.00 0.00 C \\\\nATOM 4863 C VAL C 51 -34.269 -7.207 22.791 1.00 0.00 C \\\\nATOM 4864 O VAL C 51 -33.500 -8.159 22.624 1.00 0.00 O \\\\nATOM 4865 CB VAL C 51 -33.799 -5.689 24.751 1.00 0.00 C \\\\nATOM 4866 CG1 VAL C 51 -34.358 -5.146 26.059 1.00 0.00 C \\\\nATOM 4867 CG2 VAL C 51 -32.388 -6.217 24.945 1.00 0.00 C \\\\nATOM 4868 H VAL C 51 -34.029 -8.478 24.930 1.00 0.00 H \\\\nATOM 4869 HA VAL C 51 -35.610 -6.413 24.163 1.00 0.00 H \\\\nATOM 4870 HB VAL C 51 -33.765 -4.960 24.112 1.00 0.00 H \\\\nATOM 4871 HG11 VAL C 51 -33.770 -4.454 26.400 1.00 0.00 H \\\\nATOM 4872 HG12 VAL C 51 -35.240 -4.773 25.904 1.00 0.00 H \\\\nATOM 4873 HG13 VAL C 51 -34.421 -5.865 26.707 1.00 0.00 H \\\\nATOM 4874 HG21 VAL C 51 -31.825 -5.512 25.301 1.00 0.00 H \\\\nATOM 4875 HG22 VAL C 51 -32.404 -6.962 25.566 1.00 0.00 H \\\\nATOM 4876 HG23 VAL C 51 -32.033 -6.514 24.092 1.00 0.00 H \\\\nATOM 4877 N ALA C 52 -34.761 -6.490 21.785 1.00 0.00 N \\\\nATOM 4878 CA ALA C 52 -34.438 -6.789 20.400 1.00 0.00 C \\\\nATOM 4879 C ALA C 52 -34.054 -5.511 19.670 1.00 0.00 C \\\\nATOM 4880 O ALA C 52 -34.403 -4.402 20.084 1.00 0.00 O \\\\nATOM 4881 CB ALA C 52 -35.613 -7.469 19.683 1.00 0.00 C \\\\nATOM 4882 H ALA C 52 -35.289 -5.819 21.888 1.00 0.00 H \\\\nATOM 4883 HA ALA C 52 -33.688 -7.404 20.394 1.00 0.00 H \\\\nATOM 4884 HB1 ALA C 52 -35.367 -7.655 18.763 1.00 0.00 H \\\\nATOM 4885 HB2 ALA C 52 -35.830 -8.300 20.134 1.00 0.00 H \\\\nATOM 4886 HB3 ALA C 52 -36.385 -6.882 19.698 1.00 0.00 H \\\\nATOM 4887 N LYS C 53 -33.324 -5.681 18.568 1.00 0.00 N \\\\nATOM 4888 CA LYS C 53 -32.881 -4.545 17.770 1.00 0.00 C \\\\nATOM 4889 C LYS C 53 -32.631 -5.006 16.343 1.00 0.00 C \\\\nATOM 4890 O LYS C 53 -31.978 -6.032 16.126 1.00 0.00 O \\\\nATOM 4891 CB LYS C 53 -31.613 -3.919 18.361 1.00 0.00 C \\\\nATOM 4892 CG LYS C 53 -31.041 -2.780 17.537 1.00 0.00 C \\\\nATOM 4893 CD LYS C 53 -31.740 -1.468 17.852 1.00 0.00 C \\\\nATOM 4894 CE LYS C 53 -31.499 -0.441 16.757 1.00 0.00 C \\\\nATOM 4895 NZ LYS C 53 -32.262 0.814 16.991 1.00 0.00 N \\\\nATOM 4896 H LYS C 53 -33.076 -6.448 18.267 1.00 0.00 H \\\\nATOM 4897 HA LYS C 53 -33.574 -3.866 17.775 1.00 0.00 H \\\\nATOM 4898 HB2 LYS C 53 -31.811 -3.592 19.253 1.00 0.00 H \\\\nATOM 4899 HB3 LYS C 53 -30.937 -4.608 18.455 1.00 0.00 H \\\\nATOM 4900 HG2 LYS C 53 -30.091 -2.694 17.715 1.00 0.00 H \\\\nATOM 4901 HG3 LYS C 53 -31.136 -2.981 16.593 1.00 0.00 H \\\\nATOM 4902 HD2 LYS C 53 -32.693 -1.622 17.951 1.00 0.00 H \\\\nATOM 4903 HD3 LYS C 53 -31.419 -1.123 18.700 1.00 0.00 H \\\\nATOM 4904 HE2 LYS C 53 -30.552 -0.238 16.708 1.00 0.00 H \\\\nATOM 4905 HE3 LYS C 53 -31.753 -0.818 15.900 1.00 0.00 H \\\\nATOM 4906 HZ1 LYS C 53 -32.412 1.220 16.213 1.00 0.00 H \\\\nATOM 4907 HZ2 LYS C 53 -33.039 0.621 17.380 1.00 0.00 H \\\\nATOM 4908 HZ3 LYS C 53 -31.792 1.353 17.520 1.00 0.00 H \\\\nATOM 4909 N HIS C 54 -33.152 -4.249 15.381 1.00 0.00 N \\\\nATOM 4910 CA HIS C 54 -32.937 -4.505 13.963 1.00 0.00 C \\\\nATOM 4911 C HIS C 54 -31.785 -3.638 13.473 1.00 0.00 C \\\\nATOM 4912 O HIS C 54 -31.785 -2.422 13.686 1.00 0.00 O \\\\nATOM 4913 CB HIS C 54 -34.208 -4.228 13.160 1.00 0.00 C \\\\nATOM 4914 CG HIS C 54 -35.396 -5.015 13.625 1.00 0.00 C \\\\nATOM 4915 ND1 HIS C 54 -35.844 -6.145 12.976 1.00 0.00 N \\\\nATOM 4916 CD2 HIS C 54 -36.224 -4.837 14.682 1.00 0.00 C \\\\nATOM 4917 CE1 HIS C 54 -36.899 -6.626 13.610 1.00 0.00 C \\\\nATOM 4918 NE2 HIS C 54 -37.150 -5.851 14.649 1.00 0.00 N \\\\nATOM 4919 H HIS C 54 -33.647 -3.563 15.538 1.00 0.00 H \\\\nATOM 4920 HA HIS C 54 -32.712 -5.440 13.836 1.00 0.00 H \\\\nATOM 4921 HB2 HIS C 54 -34.415 -3.282 13.213 1.00 0.00 H \\\\nATOM 4922 HB3 HIS C 54 -34.042 -4.430 12.226 1.00 0.00 H \\\\nATOM 4923 HD1 HIS C 54 -35.492 -6.484 12.269 1.00 0.00 H \\\\nATOM 4924 HD2 HIS C 54 -36.175 -4.155 15.313 1.00 0.00 H \\\\nATOM 4925 HE1 HIS C 54 -37.383 -7.382 13.366 1.00 0.00 H \\\\nATOM 4926 HE2 HIS C 54 -37.789 -5.963 15.213 1.00 0.00 H \\\\nATOM 4927 N ILE C 55 -30.807 -4.263 12.823 1.00 0.00 N \\\\nATOM 4928 CA ILE C 55 -29.574 -3.599 12.418 1.00 0.00 C \\\\nATOM 4929 C ILE C 55 -29.434 -3.708 10.906 1.00 0.00 C \\\\nATOM 4930 O ILE C 55 -29.532 -4.805 10.345 1.00 0.00 O \\\\nATOM 4931 CB ILE C 55 -28.348 -4.207 13.124 1.00 0.00 C \\\\nATOM 4932 CG1 ILE C 55 -28.564 -4.223 14.640 1.00 0.00 C \\\\nATOM 4933 CG2 ILE C 55 -27.084 -3.440 12.752 1.00 0.00 C \\\\nATOM 4934 CD1 ILE C 55 -27.303 -4.462 15.444 1.00 0.00 C \\\\nATOM 4935 H ILE C 55 -30.842 -5.094 12.603 1.00 0.00 H \\\\nATOM 4936 HA ILE C 55 -29.617 -2.666 12.678 1.00 0.00 H \\\\nATOM 4937 HB ILE C 55 -28.236 -5.124 12.827 1.00 0.00 H \\\\nATOM 4938 HG12 ILE C 55 -28.952 -3.376 14.910 1.00 0.00 H \\\\nATOM 4939 HG13 ILE C 55 -29.210 -4.913 14.857 1.00 0.00 H \\\\nATOM 4940 HG21 ILE C 55 -26.321 -3.834 13.204 1.00 0.00 H \\\\nATOM 4941 HG22 ILE C 55 -26.949 -3.484 11.792 1.00 0.00 H \\\\nATOM 4942 HG23 ILE C 55 -27.176 -2.513 13.023 1.00 0.00 H \\\\nATOM 4943 HD11 ILE C 55 -27.517 -4.459 16.390 1.00 0.00 H \\\\nATOM 4944 HD12 ILE C 55 -26.923 -5.321 15.202 1.00 0.00 H \\\\nATOM 4945 HD13 ILE C 55 -26.661 -3.760 15.256 1.00 0.00 H \\\\nATOM 4946 N LYS C 56 -29.197 -2.571 10.252 1.00 0.00 N \\\\nATOM 4947 CA LYS C 56 -29.028 -2.525 8.800 1.00 0.00 C \\\\nATOM 4948 C LYS C 56 -27.574 -2.849 8.454 1.00 0.00 C \\\\nATOM 4949 O LYS C 56 -26.783 -2.005 8.030 1.00 0.00 O \\\\nATOM 4950 CB LYS C 56 -29.450 -1.168 8.254 1.00 0.00 C \\\\nATOM 4951 CG LYS C 56 -30.957 -0.996 8.146 1.00 0.00 C \\\\nATOM 4952 CD LYS C 56 -31.478 -0.001 9.168 1.00 0.00 C \\\\nATOM 4953 CE LYS C 56 -31.414 1.420 8.638 1.00 0.00 C \\\\nATOM 4954 NZ LYS C 56 -32.112 2.378 9.538 1.00 0.00 N \\\\nATOM 4955 H LYS C 56 -29.130 -1.805 10.638 1.00 0.00 H \\\\nATOM 4956 HA LYS C 56 -29.599 -3.188 8.382 1.00 0.00 H \\\\nATOM 4957 HB2 LYS C 56 -29.093 -0.472 8.828 1.00 0.00 H \\\\nATOM 4958 HB3 LYS C 56 -29.054 -1.044 7.377 1.00 0.00 H \\\\nATOM 4959 HG2 LYS C 56 -31.186 -0.694 7.253 1.00 0.00 H \\\\nATOM 4960 HG3 LYS C 56 -31.392 -1.853 8.276 1.00 0.00 H \\\\nATOM 4961 HD2 LYS C 56 -32.394 -0.221 9.399 1.00 0.00 H \\\\nATOM 4962 HD3 LYS C 56 -30.956 -0.068 9.983 1.00 0.00 H \\\\nATOM 4963 HE2 LYS C 56 -30.487 1.687 8.539 1.00 0.00 H \\\\nATOM 4964 HE3 LYS C 56 -31.815 1.454 7.756 1.00 0.00 H \\\\nATOM 4965 HZ1 LYS C 56 -32.338 3.106 9.079 1.00 0.00 H \\\\nATOM 4966 HZ2 LYS C 56 -32.845 1.996 9.867 1.00 0.00 H \\\\nATOM 4967 HZ3 LYS C 56 -31.571 2.605 10.207 1.00 0.00 H \\\\nATOM 4968 N ALA C 57 -27.235 -4.121 8.645 1.00 0.00 N \\\\nATOM 4969 CA ALA C 57 -25.909 -4.651 8.362 1.00 0.00 C \\\\nATOM 4970 C ALA C 57 -26.022 -6.163 8.285 1.00 0.00 C \\\\nATOM 4971 O ALA C 57 -26.883 -6.747 8.954 1.00 0.00 O \\\\nATOM 4972 CB ALA C 57 -24.902 -4.243 9.445 1.00 0.00 C \\\\nATOM 4973 H ALA C 57 -27.782 -4.711 8.949 1.00 0.00 H \\\\nATOM 4974 HA ALA C 57 -25.584 -4.289 7.523 1.00 0.00 H \\\\nATOM 4975 HB1 ALA C 57 -24.030 -4.609 9.231 1.00 0.00 H \\\\nATOM 4976 HB2 ALA C 57 -24.845 -3.276 9.486 1.00 0.00 H \\\\nATOM 4977 HB3 ALA C 57 -25.194 -4.586 10.304 1.00 0.00 H \\\\nATOM 4978 N PRO C 58 -25.188 -6.824 7.488 1.00 0.00 N \\\\nATOM 4979 CA PRO C 58 -25.287 -8.282 7.375 1.00 0.00 C \\\\nATOM 4980 C PRO C 58 -24.905 -8.968 8.678 1.00 0.00 C \\\\nATOM 4981 O PRO C 58 -24.163 -8.436 9.508 1.00 0.00 O \\\\nATOM 4982 CB PRO C 58 -24.300 -8.631 6.255 1.00 0.00 C \\\\nATOM 4983 CG PRO C 58 -23.377 -7.466 6.172 1.00 0.00 C \\\\nATOM 4984 CD PRO C 58 -24.169 -6.262 6.585 1.00 0.00 C \\\\nATOM 4985 HA PRO C 58 -26.191 -8.579 7.184 1.00 0.00 H \\\\nATOM 4986 HB2 PRO C 58 -23.817 -9.448 6.456 1.00 0.00 H \\\\nATOM 4987 HB3 PRO C 58 -24.761 -8.774 5.414 1.00 0.00 H \\\\nATOM 4988 HG2 PRO C 58 -22.611 -7.591 6.754 1.00 0.00 H \\\\nATOM 4989 HG3 PRO C 58 -23.035 -7.361 5.271 1.00 0.00 H \\\\nATOM 4990 HD2 PRO C 58 -23.615 -5.605 7.035 1.00 0.00 H \\\\nATOM 4991 HD3 PRO C 58 -24.572 -5.819 5.822 1.00 0.00 H \\\\nATOM 4992 N VAL C 59 -25.443 -10.176 8.847 1.00 0.00 N \\\\nATOM 4993 CA VAL C 59 -25.285 -10.901 10.106 1.00 0.00 C \\\\nATOM 4994 C VAL C 59 -23.820 -11.229 10.356 1.00 0.00 C \\\\nATOM 4995 O VAL C 59 -23.342 -11.169 11.497 1.00 0.00 O \\\\nATOM 4996 CB VAL C 59 -26.169 -12.160 10.107 1.00 0.00 C \\\\nATOM 4997 CG1 VAL C 59 -25.686 -13.168 11.134 1.00 0.00 C \\\\nATOM 4998 CG2 VAL C 59 -27.579 -11.763 10.420 1.00 0.00 C \\\\nATOM 4999 H VAL C 59 -25.900 -10.591 8.248 1.00 0.00 H \\\\nATOM 5000 HA VAL C 59 -25.579 -10.336 10.838 1.00 0.00 H \\\\nATOM 5001 HB VAL C 59 -26.121 -12.575 9.232 1.00 0.00 H \\\\nATOM 5002 HG11 VAL C 59 -26.259 -13.950 11.114 1.00 0.00 H \\\\nATOM 5003 HG12 VAL C 59 -24.775 -13.430 10.927 1.00 0.00 H \\\\nATOM 5004 HG13 VAL C 59 -25.715 -12.769 12.018 1.00 0.00 H \\\\nATOM 5005 HG21 VAL C 59 -28.144 -12.551 10.423 1.00 0.00 H \\\\nATOM 5006 HG22 VAL C 59 -27.610 -11.340 11.292 1.00 0.00 H \\\\nATOM 5007 HG23 VAL C 59 -27.897 -11.140 9.748 1.00 0.00 H \\\\nATOM 5008 N HIS C 60 -23.085 -11.575 9.296 1.00 0.00 N \\\\nATOM 5009 CA HIS C 60 -21.678 -11.922 9.456 1.00 0.00 C \\\\nATOM 5010 C HIS C 60 -20.892 -10.763 10.056 1.00 0.00 C \\\\nATOM 5011 O HIS C 60 -19.993 -10.974 10.880 1.00 0.00 O \\\\nATOM 5012 CB HIS C 60 -21.085 -12.330 8.107 1.00 0.00 C \\\\nATOM 5013 CG HIS C 60 -19.607 -12.560 8.143 1.00 0.00 C \\\\nATOM 5014 ND1 HIS C 60 -19.044 -13.704 8.668 1.00 0.00 N \\\\nATOM 5015 CD2 HIS C 60 -18.573 -11.790 7.728 1.00 0.00 C \\\\nATOM 5016 CE1 HIS C 60 -17.729 -13.631 8.570 1.00 0.00 C \\\\nATOM 5017 NE2 HIS C 60 -17.417 -12.479 8.004 1.00 0.00 N \\\\nATOM 5018 H HIS C 60 -23.380 -11.614 8.489 1.00 0.00 H \\\\nATOM 5019 HA HIS C 60 -21.615 -12.671 10.069 1.00 0.00 H \\\\nATOM 5020 HB2 HIS C 60 -21.523 -13.140 7.802 1.00 0.00 H \\\\nATOM 5021 HB3 HIS C 60 -21.281 -11.639 7.455 1.00 0.00 H \\\\nATOM 5022 HD1 HIS C 60 -19.481 -14.363 9.007 1.00 0.00 H \\\\nATOM 5023 HD2 HIS C 60 -18.634 -10.951 7.330 1.00 0.00 H \\\\nATOM 5024 HE1 HIS C 60 -17.125 -14.280 8.852 1.00 0.00 H \\\\nATOM 5025 HE2 HIS C 60 -16.619 -12.205 7.836 1.00 0.00 H \\\\nATOM 5026 N LEU C 61 -21.219 -9.529 9.661 1.00 0.00 N \\\\nATOM 5027 CA LEU C 61 -20.529 -8.376 10.228 1.00 0.00 C \\\\nATOM 5028 C LEU C 61 -20.913 -8.157 11.687 1.00 0.00 C \\\\nATOM 5029 O LEU C 61 -20.047 -7.890 12.529 1.00 0.00 O \\\\nATOM 5030 CB LEU C 61 -20.824 -7.122 9.409 1.00 0.00 C \\\\nATOM 5031 CG LEU C 61 -20.133 -5.870 9.954 1.00 0.00 C \\\\nATOM 5032 CD1 LEU C 61 -18.620 -6.029 9.915 1.00 0.00 C \\\\nATOM 5033 CD2 LEU C 61 -20.559 -4.633 9.189 1.00 0.00 C \\\\nATOM 5034 H LEU C 61 -21.824 -9.344 9.079 1.00 0.00 H \\\\nATOM 5035 HA LEU C 61 -19.577 -8.557 10.195 1.00 0.00 H \\\\nATOM 5036 HB2 LEU C 61 -20.541 -7.267 8.493 1.00 0.00 H \\\\nATOM 5037 HB3 LEU C 61 -21.782 -6.973 9.390 1.00 0.00 H \\\\nATOM 5038 HG LEU C 61 -20.406 -5.759 10.878 1.00 0.00 H \\\\nATOM 5039 HD11 LEU C 61 -18.201 -5.227 10.264 1.00 0.00 H \\\\nATOM 5040 HD12 LEU C 61 -18.360 -6.791 10.457 1.00 0.00 H \\\\nATOM 5041 HD13 LEU C 61 -18.333 -6.171 8.999 1.00 0.00 H \\\\nATOM 5042 HD21 LEU C 61 -20.108 -3.856 9.553 1.00 0.00 H \\\\nATOM 5043 HD22 LEU C 61 -20.324 -4.734 8.253 1.00 0.00 H \\\\nATOM 5044 HD23 LEU C 61 -21.519 -4.517 9.270 1.00 0.00 H \\\\nATOM 5045 N VAL C 62 -22.205 -8.266 12.005 1.00 0.00 N \\\\nATOM 5046 CA VAL C 62 -22.655 -8.036 13.374 1.00 0.00 C \\\\nATOM 5047 C VAL C 62 -22.130 -9.123 14.303 1.00 0.00 C \\\\nATOM 5048 O VAL C 62 -21.710 -8.842 15.434 1.00 0.00 O \\\\nATOM 5049 CB VAL C 62 -24.192 -7.941 13.421 1.00 0.00 C \\\\nATOM 5050 CG1 VAL C 62 -24.685 -7.891 14.863 1.00 0.00 C \\\\nATOM 5051 CG2 VAL C 62 -24.668 -6.727 12.642 1.00 0.00 C \\\\nATOM 5052 H VAL C 62 -22.828 -8.470 11.448 1.00 0.00 H \\\\nATOM 5053 HA VAL C 62 -22.295 -7.191 13.685 1.00 0.00 H \\\\nATOM 5054 HB VAL C 62 -24.564 -8.735 13.006 1.00 0.00 H \\\\nATOM 5055 HG11 VAL C 62 -25.653 -7.831 14.872 1.00 0.00 H \\\\nATOM 5056 HG12 VAL C 62 -24.406 -8.695 15.328 1.00 0.00 H \\\\nATOM 5057 HG13 VAL C 62 -24.309 -7.115 15.307 1.00 0.00 H \\\\nATOM 5058 HG21 VAL C 62 -25.636 -6.678 12.679 1.00 0.00 H \\\\nATOM 5059 HG22 VAL C 62 -24.289 -5.923 13.031 1.00 0.00 H \\\\nATOM 5060 HG23 VAL C 62 -24.383 -6.803 11.718 1.00 0.00 H \\\\nATOM 5061 N TRP C 63 -22.146 -10.380 13.848 1.00 0.00 N \\\\nATOM 5062 CA TRP C 63 -21.648 -11.466 14.685 1.00 0.00 C \\\\nATOM 5063 C TRP C 63 -20.148 -11.354 14.921 1.00 0.00 C \\\\nATOM 5064 O TRP C 63 -19.664 -11.721 15.997 1.00 0.00 O \\\\nATOM 5065 CB TRP C 63 -21.976 -12.819 14.060 1.00 0.00 C \\\\nATOM 5066 CG TRP C 63 -21.400 -13.968 14.830 1.00 0.00 C \\\\nATOM 5067 CD1 TRP C 63 -20.452 -14.852 14.401 1.00 0.00 C \\\\nATOM 5068 CD2 TRP C 63 -21.719 -14.344 16.177 1.00 0.00 C \\\\nATOM 5069 NE1 TRP C 63 -20.169 -15.761 15.394 1.00 0.00 N \\\\nATOM 5070 CE2 TRP C 63 -20.933 -15.471 16.493 1.00 0.00 C \\\\nATOM 5071 CE3 TRP C 63 -22.594 -13.839 17.143 1.00 0.00 C \\\\nATOM 5072 CZ2 TRP C 63 -20.997 -16.102 17.734 1.00 0.00 C \\\\nATOM 5073 CZ3 TRP C 63 -22.657 -14.466 18.375 1.00 0.00 C \\\\nATOM 5074 CH2 TRP C 63 -21.863 -15.586 18.660 1.00 0.00 C \\\\nATOM 5075 H TRP C 63 -22.435 -10.618 13.074 1.00 0.00 H \\\\nATOM 5076 HA TRP C 63 -22.093 -11.395 15.544 1.00 0.00 H \\\\nATOM 5077 HB2 TRP C 63 -22.939 -12.921 14.006 1.00 0.00 H \\\\nATOM 5078 HB3 TRP C 63 -21.637 -12.842 13.151 1.00 0.00 H \\\\nATOM 5079 HD1 TRP C 63 -20.055 -14.841 13.560 1.00 0.00 H \\\\nATOM 5080 HE1 TRP C 63 -19.604 -16.407 15.334 1.00 0.00 H \\\\nATOM 5081 HE3 TRP C 63 -23.123 -13.096 16.961 1.00 0.00 H \\\\nATOM 5082 HZ2 TRP C 63 -20.472 -16.845 17.926 1.00 0.00 H \\\\nATOM 5083 HZ3 TRP C 63 -23.236 -14.139 19.025 1.00 0.00 H \\\\nATOM 5084 HH2 TRP C 63 -21.926 -15.987 19.497 1.00 0.00 H \\\\nATOM 5085 N SER C 64 -19.398 -10.853 13.936 1.00 0.00 N \\\\nATOM 5086 CA SER C 64 -17.960 -10.694 14.118 1.00 0.00 C \\\\nATOM 5087 C SER C 64 -17.650 -9.683 15.212 1.00 0.00 C \\\\nATOM 5088 O SER C 64 -16.594 -9.764 15.849 1.00 0.00 O \\\\nATOM 5089 CB SER C 64 -17.297 -10.283 12.801 1.00 0.00 C \\\\nATOM 5090 OG SER C 64 -17.437 -8.895 12.565 1.00 0.00 O \\\\nATOM 5091 H SER C 64 -19.699 -10.604 13.170 1.00 0.00 H \\\\nATOM 5092 HA SER C 64 -17.597 -11.550 14.395 1.00 0.00 H \\\\nATOM 5093 HB2 SER C 64 -16.356 -10.516 12.824 1.00 0.00 H \\\\nATOM 5094 HB3 SER C 64 -17.694 -10.779 12.068 1.00 0.00 H \\\\nATOM 5095 HG SER C 64 -18.233 -8.665 12.706 1.00 0.00 H \\\\nATOM 5096 N LEU C 65 -18.554 -8.728 15.438 1.00 0.00 N \\\\nATOM 5097 CA LEU C 65 -18.403 -7.789 16.543 1.00 0.00 C \\\\nATOM 5098 C LEU C 65 -18.758 -8.437 17.877 1.00 0.00 C \\\\nATOM 5099 O LEU C 65 -18.036 -8.275 18.867 1.00 0.00 O \\\\nATOM 5100 CB LEU C 65 -19.282 -6.557 16.308 1.00 0.00 C \\\\nATOM 5101 CG LEU C 65 -18.773 -5.373 15.478 1.00 0.00 C \\\\nATOM 5102 CD1 LEU C 65 -17.901 -5.816 14.315 1.00 0.00 C \\\\nATOM 5103 CD2 LEU C 65 -19.950 -4.544 14.979 1.00 0.00 C \\\\nATOM 5104 H LEU C 65 -19.260 -8.609 14.962 1.00 0.00 H \\\\nATOM 5105 HA LEU C 65 -17.472 -7.518 16.580 1.00 0.00 H \\\\nATOM 5106 HB2 LEU C 65 -20.100 -6.867 15.889 1.00 0.00 H \\\\nATOM 5107 HB3 LEU C 65 -19.524 -6.210 17.181 1.00 0.00 H \\\\nATOM 5108 HG LEU C 65 -18.217 -4.828 16.056 1.00 0.00 H \\\\nATOM 5109 HD11 LEU C 65 -17.602 -5.038 13.819 1.00 0.00 H \\\\nATOM 5110 HD12 LEU C 65 -17.131 -6.298 14.653 1.00 0.00 H \\\\nATOM 5111 HD13 LEU C 65 -18.413 -6.395 13.729 1.00 0.00 H \\\\nATOM 5112 HD21 LEU C 65 -19.621 -3.797 14.455 1.00 0.00 H \\\\nATOM 5113 HD22 LEU C 65 -20.525 -5.097 14.427 1.00 0.00 H \\\\nATOM 5114 HD23 LEU C 65 -20.455 -4.209 15.737 1.00 0.00 H \\\\nATOM 5115 N VAL C 66 -19.873 -9.172 17.918 1.00 0.00 N \\\\nATOM 5116 CA VAL C 66 -20.355 -9.738 19.175 1.00 0.00 C \\\\nATOM 5117 C VAL C 66 -19.443 -10.859 19.661 1.00 0.00 C \\\\nATOM 5118 O VAL C 66 -19.227 -11.020 20.870 1.00 0.00 O \\\\nATOM 5119 CB VAL C 66 -21.808 -10.221 19.006 1.00 0.00 C \\\\nATOM 5120 CG1 VAL C 66 -22.289 -10.937 20.260 1.00 0.00 C \\\\nATOM 5121 CG2 VAL C 66 -22.719 -9.048 18.665 1.00 0.00 C \\\\nATOM 5122 H VAL C 66 -20.360 -9.352 17.232 1.00 0.00 H \\\\nATOM 5123 HA VAL C 66 -20.339 -9.047 19.856 1.00 0.00 H \\\\nATOM 5124 HB VAL C 66 -21.838 -10.855 18.272 1.00 0.00 H \\\\nATOM 5125 HG11 VAL C 66 -23.204 -11.233 20.133 1.00 0.00 H \\\\nATOM 5126 HG12 VAL C 66 -21.722 -11.705 20.432 1.00 0.00 H \\\\nATOM 5127 HG13 VAL C 66 -22.247 -10.330 21.015 1.00 0.00 H \\\\nATOM 5128 HG21 VAL C 66 -23.630 -9.365 18.561 1.00 0.00 H \\\\nATOM 5129 HG22 VAL C 66 -22.684 -8.393 19.379 1.00 0.00 H \\\\nATOM 5130 HG23 VAL C 66 -22.423 -8.639 17.837 1.00 0.00 H \\\\nATOM 5131 N ARG C 67 -18.890 -11.648 18.734 1.00 0.00 N \\\\nATOM 5132 CA ARG C 67 -18.036 -12.765 19.122 1.00 0.00 C \\\\nATOM 5133 C ARG C 67 -16.785 -12.316 19.868 1.00 0.00 C \\\\nATOM 5134 O ARG C 67 -16.235 -13.096 20.654 1.00 0.00 O \\\\nATOM 5135 CB ARG C 67 -17.663 -13.603 17.901 1.00 0.00 C \\\\nATOM 5136 CG ARG C 67 -16.658 -12.966 16.962 1.00 0.00 C \\\\nATOM 5137 CD ARG C 67 -16.730 -13.615 15.591 1.00 0.00 C \\\\nATOM 5138 NE ARG C 67 -16.259 -14.994 15.615 1.00 0.00 N \\\\nATOM 5139 CZ ARG C 67 -14.997 -15.354 15.408 1.00 0.00 C \\\\nATOM 5140 NH1 ARG C 67 -14.077 -14.431 15.164 1.00 0.00 N \\\\nATOM 5141 NH2 ARG C 67 -14.654 -16.635 15.448 1.00 0.00 N \\\\nATOM 5142 H ARG C 67 -18.997 -11.552 17.886 1.00 0.00 H \\\\nATOM 5143 HA ARG C 67 -18.549 -13.312 19.738 1.00 0.00 H \\\\nATOM 5144 HB2 ARG C 67 -17.306 -14.452 18.206 1.00 0.00 H \\\\nATOM 5145 HB3 ARG C 67 -18.471 -13.798 17.402 1.00 0.00 H \\\\nATOM 5146 HG2 ARG C 67 -16.835 -12.015 16.886 1.00 0.00 H \\\\nATOM 5147 HG3 ARG C 67 -15.763 -13.060 17.324 1.00 0.00 H \\\\nATOM 5148 HD2 ARG C 67 -17.645 -13.592 15.271 1.00 0.00 H \\\\nATOM 5149 HD3 ARG C 67 -16.197 -13.103 14.963 1.00 0.00 H \\\\nATOM 5150 HE ARG C 67 -16.834 -15.614 15.773 1.00 0.00 H \\\\nATOM 5151 HH11 ARG C 67 -14.297 -13.600 15.140 1.00 0.00 H \\\\nATOM 5152 HH12 ARG C 67 -13.260 -14.663 15.030 1.00 0.00 H \\\\nATOM 5153 HH21 ARG C 67 -15.249 -17.235 15.608 1.00 0.00 H \\\\nATOM 5154 HH22 ARG C 67 -13.836 -16.866 15.314 1.00 0.00 H \\\\nATOM 5155 N ARG C 68 -16.323 -11.086 19.648 1.00 0.00 N \\\\nATOM 5156 CA ARG C 68 -15.078 -10.629 20.253 1.00 0.00 C \\\\nATOM 5157 C ARG C 68 -15.293 -10.408 21.746 1.00 0.00 C \\\\nATOM 5158 O ARG C 68 -15.401 -9.271 22.219 1.00 0.00 O \\\\nATOM 5159 CB ARG C 68 -14.574 -9.361 19.563 1.00 0.00 C \\\\nATOM 5160 CG ARG C 68 -13.890 -9.642 18.234 1.00 0.00 C \\\\nATOM 5161 CD ARG C 68 -13.937 -8.450 17.298 1.00 0.00 C \\\\nATOM 5162 NE ARG C 68 -12.992 -7.407 17.684 1.00 0.00 N \\\\nATOM 5163 CZ ARG C 68 -12.717 -6.341 16.940 1.00 0.00 C \\\\nATOM 5164 NH1 ARG C 68 -13.317 -6.180 15.769 1.00 0.00 N \\\\nATOM 5165 NH2 ARG C 68 -11.844 -5.438 17.366 1.00 0.00 N \\\\nATOM 5166 H ARG C 68 -16.716 -10.503 19.152 1.00 0.00 H \\\\nATOM 5167 HA ARG C 68 -14.395 -11.308 20.137 1.00 0.00 H \\\\nATOM 5168 HB2 ARG C 68 -15.321 -8.760 19.416 1.00 0.00 H \\\\nATOM 5169 HB3 ARG C 68 -13.953 -8.904 20.151 1.00 0.00 H \\\\nATOM 5170 HG2 ARG C 68 -12.966 -9.888 18.394 1.00 0.00 H \\\\nATOM 5171 HG3 ARG C 68 -14.316 -10.402 17.808 1.00 0.00 H \\\\nATOM 5172 HD2 ARG C 68 -13.741 -8.743 16.394 1.00 0.00 H \\\\nATOM 5173 HD3 ARG C 68 -14.835 -8.083 17.289 1.00 0.00 H \\\\nATOM 5174 HE ARG C 68 -12.588 -7.487 18.439 1.00 0.00 H \\\\nATOM 5175 HH11 ARG C 68 -13.883 -6.765 15.492 1.00 0.00 H \\\\nATOM 5176 HH12 ARG C 68 -13.140 -5.491 15.286 1.00 0.00 H \\\\nATOM 5177 HH21 ARG C 68 -11.454 -5.542 18.126 1.00 0.00 H \\\\nATOM 5178 HH22 ARG C 68 -11.668 -4.749 16.883 1.00 0.00 H \\\\nATOM 5179 N PHE C 69 -15.359 -11.520 22.482 1.00 0.00 N \\\\nATOM 5180 CA PHE C 69 -15.686 -11.510 23.905 1.00 0.00 C \\\\nATOM 5181 C PHE C 69 -14.710 -10.668 24.716 1.00 0.00 C \\\\nATOM 5182 O PHE C 69 -15.087 -10.113 25.754 1.00 0.00 O \\\\nATOM 5183 CB PHE C 69 -15.707 -12.952 24.419 1.00 0.00 C \\\\nATOM 5184 CG PHE C 69 -16.135 -13.096 25.852 1.00 0.00 C \\\\nATOM 5185 CD1 PHE C 69 -17.458 -12.917 26.218 1.00 0.00 C \\\\nATOM 5186 CD2 PHE C 69 -15.215 -13.442 26.828 1.00 0.00 C \\\\nATOM 5187 CE1 PHE C 69 -17.852 -13.061 27.536 1.00 0.00 C \\\\nATOM 5188 CE2 PHE C 69 -15.604 -13.588 28.146 1.00 0.00 C \\\\nATOM 5189 CZ PHE C 69 -16.923 -13.397 28.502 1.00 0.00 C \\\\nATOM 5190 H PHE C 69 -15.214 -12.306 22.164 1.00 0.00 H \\\\nATOM 5191 HA PHE C 69 -16.560 -11.104 24.014 1.00 0.00 H \\\\nATOM 5192 HB2 PHE C 69 -16.305 -13.474 23.861 1.00 0.00 H \\\\nATOM 5193 HB3 PHE C 69 -14.820 -13.332 24.318 1.00 0.00 H \\\\nATOM 5194 HD1 PHE C 69 -18.089 -12.698 25.571 1.00 0.00 H \\\\nATOM 5195 HD2 PHE C 69 -14.325 -13.578 26.594 1.00 0.00 H \\\\nATOM 5196 HE1 PHE C 69 -18.742 -12.932 27.772 1.00 0.00 H \\\\nATOM 5197 HE2 PHE C 69 -14.976 -13.815 28.793 1.00 0.00 H \\\\nATOM 5198 HZ PHE C 69 -17.186 -13.494 29.389 1.00 0.00 H \\\\nATOM 5199 N ASP C 70 -13.463 -10.557 24.264 1.00 0.00 N \\\\nATOM 5200 CA ASP C 70 -12.440 -9.834 25.009 1.00 0.00 C \\\\nATOM 5201 C ASP C 70 -12.500 -8.324 24.826 1.00 0.00 C \\\\nATOM 5202 O ASP C 70 -11.797 -7.607 25.546 1.00 0.00 O \\\\nATOM 5203 CB ASP C 70 -11.052 -10.329 24.594 1.00 0.00 C \\\\nATOM 5204 CG ASP C 70 -10.813 -10.199 23.102 1.00 0.00 C \\\\nATOM 5205 OD1 ASP C 70 -11.793 -10.301 22.332 1.00 0.00 O \\\\nATOM 5206 OD2 ASP C 70 -9.650 -9.993 22.695 1.00 0.00 O \\\\nATOM 5207 H ASP C 70 -13.189 -10.896 23.523 1.00 0.00 H \\\\nATOM 5208 HA ASP C 70 -12.612 -10.013 25.947 1.00 0.00 H \\\\nATOM 5209 HB2 ASP C 70 -10.375 -9.825 25.072 1.00 0.00 H \\\\nATOM 5210 HB3 ASP C 70 -10.951 -11.258 24.855 1.00 0.00 H \\\\nATOM 5211 N GLN C 71 -13.306 -7.818 23.896 1.00 0.00 N \\\\nATOM 5212 CA GLN C 71 -13.408 -6.381 23.638 1.00 0.00 C \\\\nATOM 5213 C GLN C 71 -14.870 -5.946 23.576 1.00 0.00 C \\\\nATOM 5214 O GLN C 71 -15.370 -5.567 22.512 1.00 0.00 O \\\\nATOM 5215 CB GLN C 71 -12.673 -6.013 22.348 1.00 0.00 C \\\\nATOM 5216 CG GLN C 71 -11.190 -6.366 22.360 1.00 0.00 C \\\\nATOM 5217 CD GLN C 71 -10.494 -6.051 21.049 1.00 0.00 C \\\\nATOM 5218 OE1 GLN C 71 -11.071 -6.202 19.972 1.00 0.00 O \\\\nATOM 5219 NE2 GLN C 71 -9.243 -5.610 21.136 1.00 0.00 N \\\\nATOM 5220 H GLN C 71 -13.812 -8.300 23.394 1.00 0.00 H \\\\nATOM 5221 HA GLN C 71 -12.985 -5.908 24.372 1.00 0.00 H \\\\nATOM 5222 HB2 GLN C 71 -13.098 -6.466 21.603 1.00 0.00 H \\\\nATOM 5223 HB3 GLN C 71 -12.768 -5.060 22.192 1.00 0.00 H \\\\nATOM 5224 HG2 GLN C 71 -10.753 -5.880 23.077 1.00 0.00 H \\\\nATOM 5225 HG3 GLN C 71 -11.089 -7.311 22.555 1.00 0.00 H \\\\nATOM 5226 HE21 GLN C 71 -8.872 -5.517 21.906 1.00 0.00 H \\\\nATOM 5227 HE22 GLN C 71 -8.804 -5.418 20.422 1.00 0.00 H \\\\nATOM 5228 N PRO C 72 -15.591 -6.001 24.701 1.00 0.00 N \\\\nATOM 5229 CA PRO C 72 -16.967 -5.475 24.704 1.00 0.00 C \\\\nATOM 5230 C PRO C 72 -17.037 -3.975 24.479 1.00 0.00 C \\\\nATOM 5231 O PRO C 72 -18.080 -3.478 24.036 1.00 0.00 O \\\\nATOM 5232 CB PRO C 72 -17.485 -5.860 26.095 1.00 0.00 C \\\\nATOM 5233 CG PRO C 72 -16.259 -5.919 26.934 1.00 0.00 C \\\\nATOM 5234 CD PRO C 72 -15.183 -6.468 26.036 1.00 0.00 C \\\\nATOM 5235 HA PRO C 72 -17.495 -5.840 23.977 1.00 0.00 H \\\\nATOM 5236 HB2 PRO C 72 -18.115 -5.205 26.433 1.00 0.00 H \\\\nATOM 5237 HB3 PRO C 72 -17.945 -6.714 26.079 1.00 0.00 H \\\\nATOM 5238 HG2 PRO C 72 -16.021 -5.040 27.267 1.00 0.00 H \\\\nATOM 5239 HG3 PRO C 72 -16.392 -6.489 27.708 1.00 0.00 H \\\\nATOM 5240 HD2 PRO C 72 -14.306 -6.133 26.281 1.00 0.00 H \\\\nATOM 5241 HD3 PRO C 72 -15.139 -7.436 26.079 1.00 0.00 H \\\\nATOM 5242 N GLN C 73 -15.961 -3.239 24.772 1.00 0.00 N \\\\nATOM 5243 CA GLN C 73 -15.903 -1.809 24.486 1.00 0.00 C \\\\nATOM 5244 C GLN C 73 -16.113 -1.499 23.010 1.00 0.00 C \\\\nATOM 5245 O GLN C 73 -16.348 -0.336 22.665 1.00 0.00 O \\\\nATOM 5246 CB GLN C 73 -14.563 -1.231 24.947 1.00 0.00 C \\\\nATOM 5247 CG GLN C 73 -13.348 -1.785 24.213 1.00 0.00 C \\\\nATOM 5248 CD GLN C 73 -12.829 -3.072 24.824 1.00 0.00 C \\\\nATOM 5249 OE1 GLN C 73 -13.548 -3.766 25.542 1.00 0.00 O \\\\nATOM 5250 NE2 GLN C 73 -11.569 -3.393 24.544 1.00 0.00 N \\\\nATOM 5251 H GLN C 73 -15.251 -3.555 25.140 1.00 0.00 H \\\\nATOM 5252 HA GLN C 73 -16.629 -1.394 24.977 1.00 0.00 H \\\\nATOM 5253 HB2 GLN C 73 -14.583 -0.268 24.834 1.00 0.00 H \\\\nATOM 5254 HB3 GLN C 73 -14.459 -1.403 25.896 1.00 0.00 H \\\\nATOM 5255 HG2 GLN C 73 -13.581 -1.943 23.285 1.00 0.00 H \\\\nATOM 5256 HG3 GLN C 73 -12.641 -1.121 24.219 1.00 0.00 H \\\\nATOM 5257 HE21 GLN C 73 -11.097 -2.882 24.038 1.00 0.00 H \\\\nATOM 5258 HE22 GLN C 73 -11.226 -4.111 24.869 1.00 0.00 H \\\\nATOM 5259 N LEU C 74 -16.006 -2.505 22.136 1.00 0.00 N \\\\nATOM 5260 CA LEU C 74 -16.189 -2.292 20.704 1.00 0.00 C \\\\nATOM 5261 C LEU C 74 -17.560 -1.699 20.394 1.00 0.00 C \\\\nATOM 5262 O LEU C 74 -17.699 -0.887 19.471 1.00 0.00 O \\\\nATOM 5263 CB LEU C 74 -15.994 -3.615 19.959 1.00 0.00 C \\\\nATOM 5264 CG LEU C 74 -16.131 -3.613 18.437 1.00 0.00 C \\\\nATOM 5265 CD1 LEU C 74 -15.104 -2.687 17.809 1.00 0.00 C \\\\nATOM 5266 CD2 LEU C 74 -15.986 -5.027 17.889 1.00 0.00 C \\\\nATOM 5267 H LEU C 74 -15.828 -3.317 22.356 1.00 0.00 H \\\\nATOM 5268 HA LEU C 74 -15.524 -1.652 20.404 1.00 0.00 H \\\\nATOM 5269 HB2 LEU C 74 -15.110 -3.950 20.177 1.00 0.00 H \\\\nATOM 5270 HB3 LEU C 74 -16.634 -4.252 20.313 1.00 0.00 H \\\\nATOM 5271 HG LEU C 74 -17.015 -3.285 18.208 1.00 0.00 H \\\\nATOM 5272 HD11 LEU C 74 -15.205 -2.698 16.844 1.00 0.00 H \\\\nATOM 5273 HD12 LEU C 74 -15.238 -1.784 18.138 1.00 0.00 H \\\\nATOM 5274 HD13 LEU C 74 -14.212 -2.987 18.043 1.00 0.00 H \\\\nATOM 5275 HD21 LEU C 74 -16.075 -5.011 16.923 1.00 0.00 H \\\\nATOM 5276 HD22 LEU C 74 -15.114 -5.379 18.127 1.00 0.00 H \\\\nATOM 5277 HD23 LEU C 74 -16.677 -5.593 18.267 1.00 0.00 H \\\\nATOM 5278 N PHE C 75 -18.587 -2.088 21.155 1.00 0.00 N \\\\nATOM 5279 CA PHE C 75 -19.921 -1.534 20.966 1.00 0.00 C \\\\nATOM 5280 C PHE C 75 -20.628 -1.143 22.256 1.00 0.00 C \\\\nATOM 5281 O PHE C 75 -21.719 -0.569 22.182 1.00 0.00 O \\\\nATOM 5282 CB PHE C 75 -20.816 -2.516 20.190 1.00 0.00 C \\\\nATOM 5283 CG PHE C 75 -21.135 -3.779 20.942 1.00 0.00 C \\\\nATOM 5284 CD1 PHE C 75 -20.278 -4.866 20.892 1.00 0.00 C \\\\nATOM 5285 CD2 PHE C 75 -22.302 -3.887 21.683 1.00 0.00 C \\\\nATOM 5286 CE1 PHE C 75 -20.572 -6.029 21.574 1.00 0.00 C \\\\nATOM 5287 CE2 PHE C 75 -22.601 -5.049 22.368 1.00 0.00 C \\\\nATOM 5288 CZ PHE C 75 -21.734 -6.120 22.315 1.00 0.00 C \\\\nATOM 5289 H PHE C 75 -18.528 -2.671 21.784 1.00 0.00 H \\\\nATOM 5290 HA PHE C 75 -19.781 -0.719 20.460 1.00 0.00 H \\\\nATOM 5291 HB2 PHE C 75 -21.646 -2.070 19.959 1.00 0.00 H \\\\nATOM 5292 HB3 PHE C 75 -20.378 -2.749 19.356 1.00 0.00 H \\\\nATOM 5293 HD1 PHE C 75 -19.495 -4.811 20.393 1.00 0.00 H \\\\nATOM 5294 HD2 PHE C 75 -22.891 -3.168 21.719 1.00 0.00 H \\\\nATOM 5295 HE1 PHE C 75 -19.988 -6.752 21.535 1.00 0.00 H \\\\nATOM 5296 HE2 PHE C 75 -23.385 -5.109 22.864 1.00 0.00 H \\\\nATOM 5297 HZ PHE C 75 -21.931 -6.902 22.777 1.00 0.00 H \\\\nATOM 5298 N LYS C 76 -20.062 -1.433 23.426 1.00 0.00 N \\\\nATOM 5299 CA LYS C 76 -20.703 -1.060 24.679 1.00 0.00 C \\\\nATOM 5300 C LYS C 76 -20.086 0.236 25.177 1.00 0.00 C \\\\nATOM 5301 O LYS C 76 -18.928 0.226 25.625 1.00 0.00 O \\\\nATOM 5302 CB LYS C 76 -20.544 -2.163 25.725 1.00 0.00 C \\\\nATOM 5303 CG LYS C 76 -21.113 -3.507 25.309 1.00 0.00 C \\\\nATOM 5304 CD LYS C 76 -21.030 -4.516 26.447 1.00 0.00 C \\\\nATOM 5305 CE LYS C 76 -21.483 -5.893 25.995 1.00 0.00 C \\\\nATOM 5306 NZ LYS C 76 -21.772 -6.791 27.147 1.00 0.00 N \\\\nATOM 5307 H LYS C 76 -19.311 -1.843 23.513 1.00 0.00 H \\\\nATOM 5308 HA LYS C 76 -21.653 -0.935 24.527 1.00 0.00 H \\\\nATOM 5309 HB2 LYS C 76 -19.601 -2.271 25.925 1.00 0.00 H \\\\nATOM 5310 HB3 LYS C 76 -20.977 -1.881 26.546 1.00 0.00 H \\\\nATOM 5311 HG2 LYS C 76 -22.037 -3.399 25.036 1.00 0.00 H \\\\nATOM 5312 HG3 LYS C 76 -20.627 -3.843 24.540 1.00 0.00 H \\\\nATOM 5313 HD2 LYS C 76 -20.118 -4.564 26.774 1.00 0.00 H \\\\nATOM 5314 HD3 LYS C 76 -21.581 -4.218 27.187 1.00 0.00 H \\\\nATOM 5315 HE2 LYS C 76 -22.278 -5.807 25.446 1.00 0.00 H \\\\nATOM 5316 HE3 LYS C 76 -20.796 -6.292 25.439 1.00 0.00 H \\\\nATOM 5317 HZ1 LYS C 76 -21.262 -7.518 27.092 1.00 0.00 H \\\\nATOM 5318 HZ2 LYS C 76 -21.598 -6.363 27.908 1.00 0.00 H \\\\nATOM 5319 HZ3 LYS C 76 -22.629 -7.029 27.130 1.00 0.00 H \\\\nATOM 5320 N PRO C 77 -20.801 1.365 25.124 1.00 0.00 N \\\\nATOM 5321 CA PRO C 77 -20.185 2.640 25.521 1.00 0.00 C \\\\nATOM 5322 C PRO C 77 -19.877 2.733 27.004 1.00 0.00 C \\\\nATOM 5323 O PRO C 77 -19.092 3.603 27.399 1.00 0.00 O \\\\nATOM 5324 CB PRO C 77 -21.229 3.683 25.103 1.00 0.00 C \\\\nATOM 5325 CG PRO C 77 -22.524 2.938 25.072 1.00 0.00 C \\\\nATOM 5326 CD PRO C 77 -22.198 1.527 24.684 1.00 0.00 C \\\\nATOM 5327 HA PRO C 77 -19.319 2.761 25.101 1.00 0.00 H \\\\nATOM 5328 HB2 PRO C 77 -21.262 4.420 25.733 1.00 0.00 H \\\\nATOM 5329 HB3 PRO C 77 -21.020 4.061 24.235 1.00 0.00 H \\\\nATOM 5330 HG2 PRO C 77 -22.958 2.966 25.939 1.00 0.00 H \\\\nATOM 5331 HG3 PRO C 77 -23.137 3.338 24.435 1.00 0.00 H \\\\nATOM 5332 HD2 PRO C 77 -22.786 0.891 25.121 1.00 0.00 H \\\\nATOM 5333 HD3 PRO C 77 -22.290 1.389 23.728 1.00 0.00 H \\\\nATOM 5334 N PHE C 78 -20.467 1.876 27.838 1.00 0.00 N \\\\nATOM 5335 CA PHE C 78 -20.233 1.933 29.275 1.00 0.00 C \\\\nATOM 5336 C PHE C 78 -18.906 1.320 29.700 1.00 0.00 C \\\\nATOM 5337 O PHE C 78 -18.471 1.561 30.829 1.00 0.00 O \\\\nATOM 5338 CB PHE C 78 -21.366 1.228 30.026 1.00 0.00 C \\\\nATOM 5339 CG PHE C 78 -22.737 1.688 29.626 1.00 0.00 C \\\\nATOM 5340 CD1 PHE C 78 -23.194 2.946 29.986 1.00 0.00 C \\\\nATOM 5341 CD2 PHE C 78 -23.576 0.858 28.898 1.00 0.00 C \\\\nATOM 5342 CE1 PHE C 78 -24.456 3.369 29.621 1.00 0.00 C \\\\nATOM 5343 CE2 PHE C 78 -24.838 1.278 28.531 1.00 0.00 C \\\\nATOM 5344 CZ PHE C 78 -25.280 2.534 28.894 1.00 0.00 C \\\\nATOM 5345 H PHE C 78 -21.006 1.254 27.588 1.00 0.00 H \\\\nATOM 5346 HA PHE C 78 -20.203 2.876 29.501 1.00 0.00 H \\\\nATOM 5347 HB2 PHE C 78 -21.298 0.272 29.874 1.00 0.00 H \\\\nATOM 5348 HB3 PHE C 78 -21.251 1.373 30.978 1.00 0.00 H \\\\nATOM 5349 HD1 PHE C 78 -22.644 3.511 30.479 1.00 0.00 H \\\\nATOM 5350 HD2 PHE C 78 -23.285 0.009 28.654 1.00 0.00 H \\\\nATOM 5351 HE1 PHE C 78 -24.751 4.217 29.865 1.00 0.00 H \\\\nATOM 5352 HE2 PHE C 78 -25.391 0.715 28.039 1.00 0.00 H \\\\nATOM 5353 HZ PHE C 78 -26.131 2.817 28.649 1.00 0.00 H \\\\nATOM 5354 N VAL C 79 -18.249 0.553 28.838 1.00 0.00 N \\\\nATOM 5355 CA VAL C 79 -17.052 -0.186 29.220 1.00 0.00 C \\\\nATOM 5356 C VAL C 79 -15.834 0.694 28.978 1.00 0.00 C \\\\nATOM 5357 O VAL C 79 -15.640 1.213 27.873 1.00 0.00 O \\\\nATOM 5358 CB VAL C 79 -16.946 -1.505 28.437 1.00 0.00 C \\\\nATOM 5359 CG1 VAL C 79 -15.597 -2.169 28.688 1.00 0.00 C \\\\nATOM 5360 CG2 VAL C 79 -18.088 -2.438 28.813 1.00 0.00 C \\\\nATOM 5361 H VAL C 79 -18.483 0.446 28.017 1.00 0.00 H \\\\nATOM 5362 HA VAL C 79 -17.101 -0.416 30.161 1.00 0.00 H \\\\nATOM 5363 HB VAL C 79 -17.014 -1.309 27.489 1.00 0.00 H \\\\nATOM 5364 HG11 VAL C 79 -15.546 -2.998 28.188 1.00 0.00 H \\\\nATOM 5365 HG12 VAL C 79 -14.886 -1.575 28.402 1.00 0.00 H \\\\nATOM 5366 HG13 VAL C 79 -15.500 -2.357 29.635 1.00 0.00 H \\\\nATOM 5367 HG21 VAL C 79 -18.009 -3.265 28.312 1.00 0.00 H \\\\nATOM 5368 HG22 VAL C 79 -18.049 -2.631 29.763 1.00 0.00 H \\\\nATOM 5369 HG23 VAL C 79 -18.935 -2.014 28.604 1.00 0.00 H \\\\nATOM 5370 N SER C 80 -15.010 0.866 30.014 1.00 0.00 N \\\\nATOM 5371 CA SER C 80 -13.772 1.622 29.896 1.00 0.00 C \\\\nATOM 5372 C SER C 80 -12.517 0.764 29.918 1.00 0.00 C \\\\nATOM 5373 O SER C 80 -11.445 1.266 29.568 1.00 0.00 O \\\\nATOM 5374 CB SER C 80 -13.667 2.654 31.028 1.00 0.00 C \\\\nATOM 5375 OG SER C 80 -13.214 2.043 32.222 1.00 0.00 O \\\\nATOM 5376 H SER C 80 -15.156 0.548 30.799 1.00 0.00 H \\\\nATOM 5377 HA SER C 80 -13.817 2.051 29.027 1.00 0.00 H \\\\nATOM 5378 HB2 SER C 80 -13.057 3.363 30.770 1.00 0.00 H \\\\nATOM 5379 HB3 SER C 80 -14.532 3.066 31.178 1.00 0.00 H \\\\nATOM 5380 HG SER C 80 -13.552 1.277 32.291 1.00 0.00 H \\\\nATOM 5381 N ARG C 81 -12.625 -0.508 30.289 1.00 0.00 N \\\\nATOM 5382 CA ARG C 81 -11.525 -1.452 30.161 1.00 0.00 C \\\\nATOM 5383 C ARG C 81 -12.069 -2.849 30.428 1.00 0.00 C \\\\nATOM 5384 O ARG C 81 -13.099 -3.019 31.087 1.00 0.00 O \\\\nATOM 5385 CB ARG C 81 -10.388 -1.108 31.138 1.00 0.00 C \\\\nATOM 5386 CG ARG C 81 -9.150 -1.989 31.073 1.00 0.00 C \\\\nATOM 5387 CD ARG C 81 -8.600 -2.249 32.470 1.00 0.00 C \\\\nATOM 5388 NE ARG C 81 -8.304 -1.011 33.187 1.00 0.00 N \\\\nATOM 5389 CZ ARG C 81 -8.159 -0.921 34.506 1.00 0.00 C \\\\nATOM 5390 NH1 ARG C 81 -8.334 -1.988 35.270 1.00 0.00 N \\\\nATOM 5391 NH2 ARG C 81 -7.884 0.250 35.065 1.00 0.00 N \\\\nATOM 5392 H ARG C 81 -13.341 -0.847 30.623 1.00 0.00 H \\\\nATOM 5393 HA ARG C 81 -11.153 -1.407 29.266 1.00 0.00 H \\\\nATOM 5394 HB2 ARG C 81 -10.117 -0.191 30.978 1.00 0.00 H \\\\nATOM 5395 HB3 ARG C 81 -10.741 -1.146 32.041 1.00 0.00 H \\\\nATOM 5396 HG2 ARG C 81 -9.369 -2.831 30.645 1.00 0.00 H \\\\nATOM 5397 HG3 ARG C 81 -8.471 -1.561 30.528 1.00 0.00 H \\\\nATOM 5398 HD2 ARG C 81 -9.243 -2.769 32.977 1.00 0.00 H \\\\nATOM 5399 HD3 ARG C 81 -7.793 -2.783 32.404 1.00 0.00 H \\\\nATOM 5400 HE ARG C 81 -8.218 -0.291 32.724 1.00 0.00 H \\\\nATOM 5401 HH11 ARG C 81 -8.542 -2.743 34.914 1.00 0.00 H \\\\nATOM 5402 HH12 ARG C 81 -8.239 -1.927 36.123 1.00 0.00 H \\\\nATOM 5403 HH21 ARG C 81 -7.799 0.951 34.575 1.00 0.00 H \\\\nATOM 5404 HH22 ARG C 81 -7.790 0.308 35.918 1.00 0.00 H \\\\nATOM 5405 N CYS C 82 -11.345 -3.847 29.930 1.00 0.00 N \\\\nATOM 5406 CA CYS C 82 -11.781 -5.238 29.991 1.00 0.00 C \\\\nATOM 5407 C CYS C 82 -10.550 -6.119 29.883 1.00 0.00 C \\\\nATOM 5408 O CYS C 82 -9.796 -6.015 28.910 1.00 0.00 O \\\\nATOM 5409 CB CYS C 82 -12.778 -5.568 28.882 1.00 0.00 C \\\\nATOM 5410 SG CYS C 82 -13.246 -7.315 28.830 1.00 0.00 S \\\\nATOM 5411 H CYS C 82 -10.584 -3.736 29.546 1.00 0.00 H \\\\nATOM 5412 HA CYS C 82 -12.239 -5.395 30.832 1.00 0.00 H \\\\nATOM 5413 HB2 CYS C 82 -13.576 -5.030 29.004 1.00 0.00 H \\\\nATOM 5414 HB3 CYS C 82 -12.395 -5.318 28.027 1.00 0.00 H \\\\nATOM 5415 HG CYS C 82 -13.301 -7.681 27.689 1.00 0.00 H \\\\nATOM 5416 N GLU C 83 -10.340 -6.970 30.883 1.00 0.00 N \\\\nATOM 5417 CA GLU C 83 -9.205 -7.877 30.920 1.00 0.00 C \\\\nATOM 5418 C GLU C 83 -9.677 -9.315 31.051 1.00 0.00 C \\\\nATOM 5419 O GLU C 83 -10.606 -9.610 31.809 1.00 0.00 O \\\\nATOM 5420 CB GLU C 83 -8.278 -7.532 32.074 1.00 0.00 C \\\\nATOM 5421 CG GLU C 83 -8.003 -6.065 32.136 1.00 0.00 C \\\\nATOM 5422 CD GLU C 83 -6.767 -5.690 31.370 1.00 0.00 C \\\\nATOM 5423 OE1 GLU C 83 -6.168 -4.654 31.700 1.00 0.00 O \\\\nATOM 5424 OE2 GLU C 83 -6.379 -6.438 30.445 1.00 0.00 O \\\\nATOM 5425 H GLU C 83 -10.860 -7.035 31.565 1.00 0.00 H \\\\nATOM 5426 HA GLU C 83 -8.716 -7.780 30.088 1.00 0.00 H \\\\nATOM 5427 HB2 GLU C 83 -8.677 -7.823 32.909 1.00 0.00 H \\\\nATOM 5428 HB3 GLU C 83 -7.443 -8.015 31.975 1.00 0.00 H \\\\nATOM 5429 HG2 GLU C 83 -8.763 -5.579 31.779 1.00 0.00 H \\\\nATOM 5430 HG3 GLU C 83 -7.903 -5.795 33.062 1.00 0.00 H \\\\nATOM 5431 N MET C 84 -9.034 -10.205 30.304 1.00 0.00 N \\\\nATOM 5432 CA MET C 84 -9.276 -11.632 30.440 1.00 0.00 C \\\\nATOM 5433 C MET C 84 -7.984 -12.366 30.113 1.00 0.00 C \\\\nATOM 5434 O MET C 84 -7.292 -12.022 29.151 1.00 0.00 O \\\\nATOM 5435 CB MET C 84 -10.434 -12.104 29.551 1.00 0.00 C \\\\nATOM 5436 CG MET C 84 -10.192 -12.034 28.060 1.00 0.00 C \\\\nATOM 5437 SD MET C 84 -11.429 -13.003 27.182 1.00 0.00 S \\\\nATOM 5438 CE MET C 84 -10.748 -14.649 27.372 1.00 0.00 C \\\\nATOM 5439 H MET C 84 -8.449 -9.999 29.708 1.00 0.00 H \\\\nATOM 5440 HA MET C 84 -9.544 -11.829 31.351 1.00 0.00 H \\\\nATOM 5441 HB2 MET C 84 -10.645 -13.022 29.784 1.00 0.00 H \\\\nATOM 5442 HB3 MET C 84 -11.217 -11.571 29.760 1.00 0.00 H \\\\nATOM 5443 HG2 MET C 84 -10.225 -11.111 27.763 1.00 0.00 H \\\\nATOM 5444 HG3 MET C 84 -9.305 -12.367 27.854 1.00 0.00 H \\\\nATOM 5445 HE1 MET C 84 -11.328 -15.292 26.935 1.00 0.00 H \\\\nATOM 5446 HE2 MET C 84 -9.866 -14.683 26.969 1.00 0.00 H \\\\nATOM 5447 HE3 MET C 84 -10.680 -14.864 28.315 1.00 0.00 H \\\\nATOM 5448 N LYS C 85 -7.651 -13.353 30.939 1.00 0.00 N \\\\nATOM 5449 CA LYS C 85 -6.438 -14.129 30.735 1.00 0.00 C \\\\nATOM 5450 C LYS C 85 -6.681 -15.240 29.724 1.00 0.00 C \\\\nATOM 5451 O LYS C 85 -7.745 -15.865 29.703 1.00 0.00 O \\\\nATOM 5452 CB LYS C 85 -5.956 -14.726 32.057 1.00 0.00 C \\\\nATOM 5453 CG LYS C 85 -6.302 -13.895 33.281 1.00 0.00 C \\\\nATOM 5454 CD LYS C 85 -5.306 -12.767 33.476 1.00 0.00 C \\\\nATOM 5455 CE LYS C 85 -3.981 -13.296 34.000 1.00 0.00 C \\\\nATOM 5456 NZ LYS C 85 -3.142 -12.211 34.574 1.00 0.00 N \\\\nATOM 5457 H LYS C 85 -8.116 -13.588 31.623 1.00 0.00 H \\\\nATOM 5458 HA LYS C 85 -5.752 -13.536 30.391 1.00 0.00 H \\\\nATOM 5459 HB2 LYS C 85 -6.341 -15.610 32.160 1.00 0.00 H \\\\nATOM 5460 HB3 LYS C 85 -4.993 -14.839 32.017 1.00 0.00 H \\\\nATOM 5461 HG2 LYS C 85 -7.195 -13.529 33.185 1.00 0.00 H \\\\nATOM 5462 HG3 LYS C 85 -6.311 -14.462 34.068 1.00 0.00 H \\\\nATOM 5463 HD2 LYS C 85 -5.164 -12.307 32.634 1.00 0.00 H \\\\nATOM 5464 HD3 LYS C 85 -5.667 -12.116 34.098 1.00 0.00 H \\\\nATOM 5465 HE2 LYS C 85 -4.147 -13.970 34.678 1.00 0.00 H \\\\nATOM 5466 HE3 LYS C 85 -3.499 -13.731 33.280 1.00 0.00 H \\\\nATOM 5467 HZ1 LYS C 85 -2.706 -12.518 35.287 1.00 0.00 H \\\\nATOM 5468 HZ2 LYS C 85 -2.555 -11.935 33.964 1.00 0.00 H \\\\nATOM 5469 HZ3 LYS C 85 -3.661 -11.530 34.815 1.00 0.00 H \\\\nATOM 5470 N GLY C 86 -5.680 -15.481 28.884 1.00 0.00 N \\\\nATOM 5471 CA GLY C 86 -5.715 -16.588 27.955 1.00 0.00 C \\\\nATOM 5472 C GLY C 86 -6.588 -16.310 26.746 1.00 0.00 C \\\\nATOM 5473 O GLY C 86 -7.052 -15.192 26.503 1.00 0.00 O \\\\nATOM 5474 H GLY C 86 -4.965 -15.005 28.841 1.00 0.00 H \\\\nATOM 5475 HA2 GLY C 86 -4.813 -16.786 27.659 1.00 0.00 H \\\\nATOM 5476 HA3 GLY C 86 -6.043 -17.378 28.412 1.00 0.00 H \\\\nATOM 5477 N ASN C 87 -6.817 -17.371 25.978 1.00 0.00 N \\\\nATOM 5478 CA ASN C 87 -7.628 -17.290 24.776 1.00 0.00 C \\\\nATOM 5479 C ASN C 87 -9.115 -17.363 25.124 1.00 0.00 C \\\\nATOM 5480 O ASN C 87 -9.508 -17.696 26.245 1.00 0.00 O \\\\nATOM 5481 CB ASN C 87 -7.238 -18.394 23.794 1.00 0.00 C \\\\nATOM 5482 CG ASN C 87 -5.857 -18.184 23.203 1.00 0.00 C \\\\nATOM 5483 OD1 ASN C 87 -4.939 -18.969 23.446 1.00 0.00 O \\\\nATOM 5484 ND2 ASN C 87 -5.700 -17.116 22.429 1.00 0.00 N \\\\nATOM 5485 H ASN C 87 -6.506 -18.156 26.142 1.00 0.00 H \\\\nATOM 5486 HA ASN C 87 -7.463 -16.435 24.349 1.00 0.00 H \\\\nATOM 5487 HB2 ASN C 87 -7.266 -19.251 24.248 1.00 0.00 H \\\\nATOM 5488 HB3 ASN C 87 -7.891 -18.431 23.078 1.00 0.00 H \\\\nATOM 5489 HD21 ASN C 87 -4.934 -16.950 22.075 1.00 0.00 H \\\\nATOM 5490 HD22 ASN C 87 -6.364 -16.590 22.282 1.00 0.00 H \\\\nATOM 5491 N ILE C 88 -9.947 -17.044 24.138 1.00 0.00 N \\\\nATOM 5492 CA ILE C 88 -11.397 -17.081 24.303 1.00 0.00 C \\\\nATOM 5493 C ILE C 88 -11.889 -18.513 24.129 1.00 0.00 C \\\\nATOM 5494 O ILE C 88 -11.750 -19.104 23.053 1.00 0.00 O \\\\nATOM 5495 CB ILE C 88 -12.092 -16.136 23.312 1.00 0.00 C \\\\nATOM 5496 CG1 ILE C 88 -11.661 -14.689 23.558 1.00 0.00 C \\\\nATOM 5497 CG2 ILE C 88 -13.606 -16.276 23.415 1.00 0.00 C \\\\nATOM 5498 CD1 ILE C 88 -11.938 -13.766 22.390 1.00 0.00 C \\\\nATOM 5499 H ILE C 88 -9.688 -16.800 23.355 1.00 0.00 H \\\\nATOM 5500 HA ILE C 88 -11.620 -16.775 25.196 1.00 0.00 H \\\\nATOM 5501 HB ILE C 88 -11.825 -16.382 22.412 1.00 0.00 H \\\\nATOM 5502 HG12 ILE C 88 -12.121 -14.352 24.343 1.00 0.00 H \\\\nATOM 5503 HG13 ILE C 88 -10.712 -14.672 23.756 1.00 0.00 H \\\\nATOM 5504 HG21 ILE C 88 -14.031 -15.674 22.784 1.00 0.00 H \\\\nATOM 5505 HG22 ILE C 88 -13.861 -17.189 23.212 1.00 0.00 H \\\\nATOM 5506 HG23 ILE C 88 -13.891 -16.054 24.315 1.00 0.00 H \\\\nATOM 5507 HD11 ILE C 88 -11.643 -12.868 22.610 1.00 0.00 H \\\\nATOM 5508 HD12 ILE C 88 -11.459 -14.081 21.608 1.00 0.00 H \\\\nATOM 5509 HD13 ILE C 88 -12.890 -13.756 22.204 1.00 0.00 H \\\\nATOM 5510 N GLU C 89 -12.460 -19.073 25.195 1.00 0.00 N \\\\nATOM 5511 CA GLU C 89 -12.998 -20.425 25.169 1.00 0.00 C \\\\nATOM 5512 C GLU C 89 -14.113 -20.522 26.200 1.00 0.00 C \\\\nATOM 5513 O GLU C 89 -14.298 -19.627 27.028 1.00 0.00 O \\\\nATOM 5514 CB GLU C 89 -11.909 -21.473 25.433 1.00 0.00 C \\\\nATOM 5515 CG GLU C 89 -11.094 -21.229 26.693 1.00 0.00 C \\\\nATOM 5516 CD GLU C 89 -9.959 -22.223 26.854 1.00 0.00 C \\\\nATOM 5517 OE1 GLU C 89 -8.821 -21.789 27.131 1.00 0.00 O \\\\nATOM 5518 OE2 GLU C 89 -10.206 -23.438 26.702 1.00 0.00 O \\\\nATOM 5519 H GLU C 89 -12.545 -18.676 25.953 1.00 0.00 H \\\\nATOM 5520 HA GLU C 89 -13.351 -20.611 24.285 1.00 0.00 H \\\\nATOM 5521 HB2 GLU C 89 -12.325 -22.347 25.494 1.00 0.00 H \\\\nATOM 5522 HB3 GLU C 89 -11.308 -21.498 24.672 1.00 0.00 H \\\\nATOM 5523 HG2 GLU C 89 -10.731 -20.330 26.671 1.00 0.00 H \\\\nATOM 5524 HG3 GLU C 89 -11.677 -21.281 27.467 1.00 0.00 H \\\\nATOM 5525 N ILE C 90 -14.870 -21.620 26.129 1.00 0.00 N \\\\nATOM 5526 CA ILE C 90 -15.936 -21.856 27.097 1.00 0.00 C \\\\nATOM 5527 C ILE C 90 -15.351 -21.895 28.500 1.00 0.00 C \\\\nATOM 5528 O ILE C 90 -14.404 -22.640 28.780 1.00 0.00 O \\\\nATOM 5529 CB ILE C 90 -16.688 -23.150 26.756 1.00 0.00 C \\\\nATOM 5530 CG1 ILE C 90 -17.567 -22.937 25.521 1.00 0.00 C \\\\nATOM 5531 CG2 ILE C 90 -17.519 -23.612 27.946 1.00 0.00 C \\\\nATOM 5532 CD1 ILE C 90 -18.701 -23.935 25.380 1.00 0.00 C \\\\nATOM 5533 H ILE C 90 -14.782 -22.233 25.533 1.00 0.00 H \\\\nATOM 5534 HA ILE C 90 -16.578 -21.130 27.059 1.00 0.00 H \\\\nATOM 5535 HB ILE C 90 -16.043 -23.846 26.555 1.00 0.00 H \\\\nATOM 5536 HG12 ILE C 90 -17.940 -22.042 25.553 1.00 0.00 H \\\\nATOM 5537 HG13 ILE C 90 -17.009 -22.983 24.729 1.00 0.00 H \\\\nATOM 5538 HG21 ILE C 90 -17.988 -24.429 27.716 1.00 0.00 H \\\\nATOM 5539 HG22 ILE C 90 -16.936 -23.776 28.704 1.00 0.00 H \\\\nATOM 5540 HG23 ILE C 90 -18.163 -22.925 28.177 1.00 0.00 H \\\\nATOM 5541 HD11 ILE C 90 -19.210 -23.736 24.579 1.00 0.00 H \\\\nATOM 5542 HD12 ILE C 90 -18.337 -24.832 25.317 1.00 0.00 H \\\\nATOM 5543 HD13 ILE C 90 -19.282 -23.876 26.154 1.00 0.00 H \\\\nATOM 5544 N GLY C 91 -15.915 -21.083 29.393 1.00 0.00 N \\\\nATOM 5545 CA GLY C 91 -15.409 -20.943 30.740 1.00 0.00 C \\\\nATOM 5546 C GLY C 91 -14.501 -19.751 30.947 1.00 0.00 C \\\\nATOM 5547 O GLY C 91 -14.140 -19.462 32.096 1.00 0.00 O \\\\nATOM 5548 H GLY C 91 -16.606 -20.598 29.226 1.00 0.00 H \\\\nATOM 5549 HA2 GLY C 91 -16.160 -20.873 31.350 1.00 0.00 H \\\\nATOM 5550 HA3 GLY C 91 -14.925 -21.749 30.977 1.00 0.00 H \\\\nATOM 5551 N SER C 92 -14.114 -19.062 29.873 1.00 0.00 N \\\\nATOM 5552 CA SER C 92 -13.301 -17.861 30.003 1.00 0.00 C \\\\nATOM 5553 C SER C 92 -14.032 -16.800 30.814 1.00 0.00 C \\\\nATOM 5554 O SER C 92 -15.262 -16.702 30.796 1.00 0.00 O \\\\nATOM 5555 CB SER C 92 -12.934 -17.305 28.627 1.00 0.00 C \\\\nATOM 5556 OG SER C 92 -11.978 -18.127 27.979 1.00 0.00 O \\\\nATOM 5557 H SER C 92 -14.313 -19.275 29.064 1.00 0.00 H \\\\nATOM 5558 HA SER C 92 -12.485 -18.102 30.469 1.00 0.00 H \\\\nATOM 5559 HB2 SER C 92 -13.732 -17.239 28.079 1.00 0.00 H \\\\nATOM 5560 HB3 SER C 92 -12.580 -16.407 28.722 1.00 0.00 H \\\\nATOM 5561 HG SER C 92 -11.496 -17.655 27.479 1.00 0.00 H \\\\nATOM 5562 N VAL C 93 -13.255 -16.000 31.535 1.00 0.00 N \\\\nATOM 5563 CA VAL C 93 -13.776 -14.965 32.416 1.00 0.00 C \\\\nATOM 5564 C VAL C 93 -13.105 -13.648 32.058 1.00 0.00 C \\\\nATOM 5565 O VAL C 93 -11.872 -13.565 32.023 1.00 0.00 O \\\\nATOM 5566 CB VAL C 93 -13.537 -15.310 33.898 1.00 0.00 C \\\\nATOM 5567 CG1 VAL C 93 -13.485 -14.050 34.734 1.00 0.00 C \\\\nATOM 5568 CG2 VAL C 93 -14.621 -16.243 34.408 1.00 0.00 C \\\\nATOM 5569 H VAL C 93 -12.396 -16.045 31.525 1.00 0.00 H \\\\nATOM 5570 HA VAL C 93 -14.736 -14.896 32.294 1.00 0.00 H \\\\nATOM 5571 HB VAL C 93 -12.683 -15.763 33.973 1.00 0.00 H \\\\nATOM 5572 HG11 VAL C 93 -13.334 -14.284 35.663 1.00 0.00 H \\\\nATOM 5573 HG12 VAL C 93 -12.762 -13.484 34.422 1.00 0.00 H \\\\nATOM 5574 HG13 VAL C 93 -14.326 -13.573 34.654 1.00 0.00 H \\\\nATOM 5575 HG21 VAL C 93 -14.457 -16.451 35.341 1.00 0.00 H \\\\nATOM 5576 HG22 VAL C 93 -15.486 -15.813 34.320 1.00 0.00 H \\\\nATOM 5577 HG23 VAL C 93 -14.614 -17.062 33.889 1.00 0.00 H \\\\nATOM 5578 N ARG C 94 -13.911 -12.624 31.792 1.00 0.00 N \\\\nATOM 5579 CA ARG C 94 -13.403 -11.286 31.545 1.00 0.00 C \\\\nATOM 5580 C ARG C 94 -13.746 -10.388 32.726 1.00 0.00 C \\\\nATOM 5581 O ARG C 94 -14.800 -10.529 33.351 1.00 0.00 O \\\\nATOM 5582 CB ARG C 94 -13.974 -10.703 30.247 1.00 0.00 C \\\\nATOM 5583 CG ARG C 94 -15.489 -10.543 30.219 1.00 0.00 C \\\\nATOM 5584 CD ARG C 94 -15.957 -9.966 28.888 1.00 0.00 C \\\\nATOM 5585 NE ARG C 94 -17.411 -9.838 28.812 1.00 0.00 N \\\\nATOM 5586 CZ ARG C 94 -18.090 -9.697 27.678 1.00 0.00 C \\\\nATOM 5587 NH1 ARG C 94 -17.449 -9.664 26.517 1.00 0.00 N \\\\nATOM 5588 NH2 ARG C 94 -19.411 -9.590 27.701 1.00 0.00 N \\\\nATOM 5589 H ARG C 94 -14.768 -12.689 31.750 1.00 0.00 H \\\\nATOM 5590 HA ARG C 94 -12.440 -11.336 31.444 1.00 0.00 H \\\\nATOM 5591 HB2 ARG C 94 -13.569 -9.835 30.093 1.00 0.00 H \\\\nATOM 5592 HB3 ARG C 94 -13.710 -11.274 29.509 1.00 0.00 H \\\\nATOM 5593 HG2 ARG C 94 -15.911 -11.404 30.368 1.00 0.00 H \\\\nATOM 5594 HG3 ARG C 94 -15.769 -9.961 30.943 1.00 0.00 H \\\\nATOM 5595 HD2 ARG C 94 -15.552 -9.095 28.756 1.00 0.00 H \\\\nATOM 5596 HD3 ARG C 94 -15.647 -10.535 28.166 1.00 0.00 H \\\\nATOM 5597 HE ARG C 94 -17.856 -9.855 29.548 1.00 0.00 H \\\\nATOM 5598 HH11 ARG C 94 -16.592 -9.734 26.497 1.00 0.00 H \\\\nATOM 5599 HH12 ARG C 94 -17.890 -9.573 25.785 1.00 0.00 H \\\\nATOM 5600 HH21 ARG C 94 -19.831 -9.612 28.451 1.00 0.00 H \\\\nATOM 5601 HH22 ARG C 94 -19.848 -9.499 26.966 1.00 0.00 H \\\\nATOM 5602 N GLU C 95 -12.838 -9.467 33.029 1.00 0.00 N \\\\nATOM 5603 CA GLU C 95 -13.008 -8.512 34.119 1.00 0.00 C \\\\nATOM 5604 C GLU C 95 -13.277 -7.154 33.487 1.00 0.00 C \\\\nATOM 5605 O GLU C 95 -12.400 -6.585 32.829 1.00 0.00 O \\\\nATOM 5606 CB GLU C 95 -11.775 -8.475 35.020 1.00 0.00 C \\\\nATOM 5607 CG GLU C 95 -11.920 -7.573 36.236 1.00 0.00 C \\\\nATOM 5608 CD GLU C 95 -13.033 -8.016 37.165 1.00 0.00 C \\\\nATOM 5609 OE1 GLU C 95 -13.667 -7.142 37.794 1.00 0.00 O \\\\nATOM 5610 OE2 GLU C 95 -13.277 -9.238 37.267 1.00 0.00 O \\\\nATOM 5611 H GLU C 95 -12.097 -9.378 32.602 1.00 0.00 H \\\\nATOM 5612 HA GLU C 95 -13.750 -8.772 34.687 1.00 0.00 H \\\\nATOM 5613 HB2 GLU C 95 -11.578 -9.376 35.320 1.00 0.00 H \\\\nATOM 5614 HB3 GLU C 95 -11.014 -8.177 34.498 1.00 0.00 H \\\\nATOM 5615 HG2 GLU C 95 -11.082 -7.559 36.725 1.00 0.00 H \\\\nATOM 5616 HG3 GLU C 95 -12.092 -6.665 35.942 1.00 0.00 H \\\\nATOM 5617 N VAL C 96 -14.482 -6.636 33.697 1.00 0.00 N \\\\nATOM 5618 CA VAL C 96 -14.966 -5.446 33.009 1.00 0.00 C \\\\nATOM 5619 C VAL C 96 -14.978 -4.287 33.991 1.00 0.00 C \\\\nATOM 5620 O VAL C 96 -15.505 -4.411 35.103 1.00 0.00 O \\\\nATOM 5621 CB VAL C 96 -16.366 -5.678 32.416 1.00 0.00 C \\\\nATOM 5622 CG1 VAL C 96 -16.878 -4.412 31.743 1.00 0.00 C \\\\nATOM 5623 CG2 VAL C 96 -16.340 -6.844 31.440 1.00 0.00 C \\\\nATOM 5624 H VAL C 96 -15.049 -6.971 34.251 1.00 0.00 H \\\\nATOM 5625 HA VAL C 96 -14.374 -5.239 32.269 1.00 0.00 H \\\\nATOM 5626 HB VAL C 96 -16.976 -5.901 33.137 1.00 0.00 H \\\\nATOM 5627 HG11 VAL C 96 -17.760 -4.575 31.375 1.00 0.00 H \\\\nATOM 5628 HG12 VAL C 96 -16.928 -3.696 32.395 1.00 0.00 H \\\\nATOM 5629 HG13 VAL C 96 -16.273 -4.157 31.029 1.00 0.00 H \\\\nATOM 5630 HG21 VAL C 96 -17.228 -6.980 31.074 1.00 0.00 H \\\\nATOM 5631 HG22 VAL C 96 -15.720 -6.650 30.720 1.00 0.00 H \\\\nATOM 5632 HG23 VAL C 96 -16.056 -7.648 31.903 1.00 0.00 H \\\\nATOM 5633 N ASN C 97 -14.398 -3.164 33.581 1.00 0.00 N \\\\nATOM 5634 CA ASN C 97 -14.474 -1.914 34.324 1.00 0.00 C \\\\nATOM 5635 C ASN C 97 -15.327 -0.931 33.535 1.00 0.00 C \\\\nATOM 5636 O ASN C 97 -15.070 -0.695 32.349 1.00 0.00 O \\\\nATOM 5637 CB ASN C 97 -13.079 -1.337 34.574 1.00 0.00 C \\\\nATOM 5638 CG ASN C 97 -12.302 -2.122 35.612 1.00 0.00 C \\\\nATOM 5639 OD1 ASN C 97 -12.400 -1.854 36.809 1.00 0.00 O \\\\nATOM 5640 ND2 ASN C 97 -11.524 -3.096 35.157 1.00 0.00 N \\\\nATOM 5641 H ASN C 97 -13.943 -3.107 32.853 1.00 0.00 H \\\\nATOM 5642 HA ASN C 97 -14.878 -2.079 35.190 1.00 0.00 H \\\\nATOM 5643 HB2 ASN C 97 -12.582 -1.328 33.741 1.00 0.00 H \\\\nATOM 5644 HB3 ASN C 97 -13.161 -0.415 34.865 1.00 0.00 H \\\\nATOM 5645 HD21 ASN C 97 -11.062 -3.570 35.707 1.00 0.00 H \\\\nATOM 5646 HD22 ASN C 97 -11.482 -3.254 34.313 1.00 0.00 H \\\\nATOM 5647 N VAL C 98 -16.334 -0.362 34.189 1.00 0.00 N \\\\nATOM 5648 CA VAL C 98 -17.255 0.550 33.534 1.00 0.00 C \\\\nATOM 5649 C VAL C 98 -16.928 1.980 33.947 1.00 0.00 C \\\\nATOM 5650 O VAL C 98 -16.260 2.234 34.953 1.00 0.00 O \\\\nATOM 5651 CB VAL C 98 -18.730 0.200 33.838 1.00 0.00 C \\\\nATOM 5652 CG1 VAL C 98 -19.071 -1.182 33.296 1.00 0.00 C \\\\nATOM 5653 CG2 VAL C 98 -18.996 0.272 35.321 1.00 0.00 C \\\\nATOM 5654 H VAL C 98 -16.500 -0.495 35.022 1.00 0.00 H \\\\nATOM 5655 HA VAL C 98 -17.145 0.462 32.574 1.00 0.00 H \\\\nATOM 5656 HB VAL C 98 -19.298 0.850 33.396 1.00 0.00 H \\\\nATOM 5657 HG11 VAL C 98 -19.998 -1.388 33.494 1.00 0.00 H \\\\nATOM 5658 HG12 VAL C 98 -18.935 -1.196 32.336 1.00 0.00 H \\\\nATOM 5659 HG13 VAL C 98 -18.497 -1.844 33.713 1.00 0.00 H \\\\nATOM 5660 HG21 VAL C 98 -19.924 0.050 35.495 1.00 0.00 H \\\\nATOM 5661 HG22 VAL C 98 -18.421 -0.358 35.784 1.00 0.00 H \\\\nATOM 5662 HG23 VAL C 98 -18.814 1.170 35.639 1.00 0.00 H \\\\nATOM 5663 N LYS C 99 -17.407 2.933 33.147 1.00 0.00 N \\\\nATOM 5664 CA LYS C 99 -17.061 4.335 33.320 1.00 0.00 C \\\\nATOM 5665 C LYS C 99 -17.895 4.974 34.430 1.00 0.00 C \\\\nATOM 5666 O LYS C 99 -18.691 4.319 35.110 1.00 0.00 O \\\\nATOM 5667 CB LYS C 99 -17.249 5.089 32.006 1.00 0.00 C \\\\nATOM 5668 CG LYS C 99 -16.837 4.308 30.772 1.00 0.00 C \\\\nATOM 5669 CD LYS C 99 -17.000 5.134 29.510 1.00 0.00 C \\\\nATOM 5670 CE LYS C 99 -16.153 4.577 28.378 1.00 0.00 C \\\\nATOM 5671 NZ LYS C 99 -16.634 5.034 27.047 1.00 0.00 N \\\\nATOM 5672 H LYS C 99 -17.941 2.781 32.490 1.00 0.00 H \\\\nATOM 5673 HA LYS C 99 -16.128 4.388 33.581 1.00 0.00 H \\\\nATOM 5674 HB2 LYS C 99 -18.182 5.340 31.920 1.00 0.00 H \\\\nATOM 5675 HB3 LYS C 99 -16.736 5.912 32.041 1.00 0.00 H \\\\nATOM 5676 HG2 LYS C 99 -15.913 4.027 30.859 1.00 0.00 H \\\\nATOM 5677 HG3 LYS C 99 -17.373 3.502 30.704 1.00 0.00 H \\\\nATOM 5678 HD2 LYS C 99 -17.933 5.144 29.245 1.00 0.00 H \\\\nATOM 5679 HD3 LYS C 99 -16.745 6.053 29.686 1.00 0.00 H \\\\nATOM 5680 HE2 LYS C 99 -15.231 4.852 28.500 1.00 0.00 H \\\\nATOM 5681 HE3 LYS C 99 -16.167 3.608 28.411 1.00 0.00 H \\\\nATOM 5682 HZ1 LYS C 99 -16.490 4.396 26.444 1.00 0.00 H \\\\nATOM 5683 HZ2 LYS C 99 -17.505 5.210 27.090 1.00 0.00 H \\\\nATOM 5684 HZ3 LYS C 99 -16.195 5.771 26.809 1.00 0.00 H \\\\nATOM 5685 N SER C 100 -17.699 6.278 34.617 1.00 0.00 N \\\\nATOM 5686 CA SER C 100 -18.418 7.030 35.633 1.00 0.00 C \\\\nATOM 5687 C SER C 100 -19.889 7.191 35.249 1.00 0.00 C \\\\nATOM 5688 O SER C 100 -20.295 6.965 34.106 1.00 0.00 O \\\\nATOM 5689 CB SER C 100 -17.770 8.399 35.840 1.00 0.00 C \\\\nATOM 5690 OG SER C 100 -17.542 9.048 34.601 1.00 0.00 O \\\\nATOM 5691 H SER C 100 -17.145 6.748 34.157 1.00 0.00 H \\\\nATOM 5692 HA SER C 100 -18.373 6.535 36.466 1.00 0.00 H \\\\nATOM 5693 HB2 SER C 100 -18.342 8.950 36.397 1.00 0.00 H \\\\nATOM 5694 HB3 SER C 100 -16.930 8.294 36.313 1.00 0.00 H \\\\nATOM 5695 HG SER C 100 -17.334 9.850 34.739 1.00 0.00 H \\\\nATOM 5696 N GLY C 101 -20.693 7.591 36.232 1.00 0.00 N \\\\nATOM 5697 CA GLY C 101 -22.105 7.816 36.000 1.00 0.00 C \\\\nATOM 5698 C GLY C 101 -22.961 6.573 36.018 1.00 0.00 C \\\\nATOM 5699 O GLY C 101 -24.051 6.577 35.437 1.00 0.00 O \\\\nATOM 5700 H GLY C 101 -20.434 7.736 37.039 1.00 0.00 H \\\\nATOM 5701 HA2 GLY C 101 -22.436 8.430 36.674 1.00 0.00 H \\\\nATOM 5702 HA3 GLY C 101 -22.212 8.254 35.141 1.00 0.00 H \\\\nATOM 5703 N LEU C 102 -22.503 5.508 36.661 1.00 0.00 N \\\\nATOM 5704 CA LEU C 102 -23.192 4.229 36.690 1.00 0.00 C \\\\nATOM 5705 C LEU C 102 -23.294 3.731 38.124 1.00 0.00 C \\\\nATOM 5706 O LEU C 102 -22.552 4.186 39.000 1.00 0.00 O \\\\nATOM 5707 CB LEU C 102 -22.454 3.203 35.818 1.00 0.00 C \\\\nATOM 5708 CG LEU C 102 -22.480 3.536 34.323 1.00 0.00 C \\\\nATOM 5709 CD1 LEU C 102 -21.527 2.638 33.546 1.00 0.00 C \\\\nATOM 5710 CD2 LEU C 102 -23.895 3.433 33.774 1.00 0.00 C \\\\nATOM 5711 H LEU C 102 -21.765 5.510 37.103 1.00 0.00 H \\\\nATOM 5712 HA LEU C 102 -24.086 4.345 36.333 1.00 0.00 H \\\\nATOM 5713 HB2 LEU C 102 -21.532 3.144 36.112 1.00 0.00 H \\\\nATOM 5714 HB3 LEU C 102 -22.852 2.329 35.954 1.00 0.00 H \\\\nATOM 5715 HG LEU C 102 -22.179 4.452 34.213 1.00 0.00 H \\\\nATOM 5716 HD11 LEU C 102 -21.561 2.868 32.604 1.00 0.00 H \\\\nATOM 5717 HD12 LEU C 102 -20.623 2.762 33.876 1.00 0.00 H \\\\nATOM 5718 HD13 LEU C 102 -21.788 1.711 33.662 1.00 0.00 H \\\\nATOM 5719 HD21 LEU C 102 -23.892 3.647 32.828 1.00 0.00 H \\\\nATOM 5720 HD22 LEU C 102 -24.226 2.530 33.900 1.00 0.00 H \\\\nATOM 5721 HD23 LEU C 102 -24.471 4.056 34.244 1.00 0.00 H \\\\nATOM 5722 N PRO C 103 -24.207 2.792 38.396 1.00 0.00 N \\\\nATOM 5723 CA PRO C 103 -24.294 2.239 39.759 1.00 0.00 C \\\\nATOM 5724 C PRO C 103 -23.160 1.293 40.106 1.00 0.00 C \\\\nATOM 5725 O PRO C 103 -22.894 1.089 41.296 1.00 0.00 O \\\\nATOM 5726 CB PRO C 103 -25.646 1.509 39.768 1.00 0.00 C \\\\nATOM 5727 CG PRO C 103 -26.292 1.796 38.447 1.00 0.00 C \\\\nATOM 5728 CD PRO C 103 -25.226 2.218 37.503 1.00 0.00 C \\\\nATOM 5729 HA PRO C 103 -24.223 2.939 40.427 1.00 0.00 H \\\\nATOM 5730 HB2 PRO C 103 -25.523 0.555 39.892 1.00 0.00 H \\\\nATOM 5731 HB3 PRO C 103 -26.202 1.821 40.499 1.00 0.00 H \\\\nATOM 5732 HG2 PRO C 103 -26.749 1.008 38.114 1.00 0.00 H \\\\nATOM 5733 HG3 PRO C 103 -26.960 2.493 38.539 1.00 0.00 H \\\\nATOM 5734 HD2 PRO C 103 -24.878 1.469 36.995 1.00 0.00 H \\\\nATOM 5735 HD3 PRO C 103 -25.551 2.869 36.862 1.00 0.00 H \\\\nATOM 5736 N ALA C 104 -22.483 0.718 39.119 1.00 0.00 N \\\\nATOM 5737 CA ALA C 104 -21.417 -0.245 39.349 1.00 0.00 C \\\\nATOM 5738 C ALA C 104 -20.102 0.291 38.798 1.00 0.00 C \\\\nATOM 5739 O ALA C 104 -20.058 1.312 38.110 1.00 0.00 O \\\\nATOM 5740 CB ALA C 104 -21.747 -1.596 38.703 1.00 0.00 C \\\\nATOM 5741 H ALA C 104 -22.632 0.879 38.287 1.00 0.00 H \\\\nATOM 5742 HA ALA C 104 -21.331 -0.380 40.306 1.00 0.00 H \\\\nATOM 5743 HB1 ALA C 104 -21.023 -2.220 38.870 1.00 0.00 H \\\\nATOM 5744 HB2 ALA C 104 -22.568 -1.945 39.084 1.00 0.00 H \\\\nATOM 5745 HB3 ALA C 104 -21.859 -1.479 37.747 1.00 0.00 H \\\\nATOM 5746 N THR C 105 -19.025 -0.407 39.128 1.00 0.00 N \\\\nATOM 5747 CA THR C 105 -17.692 -0.077 38.637 1.00 0.00 C \\\\nATOM 5748 C THR C 105 -17.001 -1.262 37.984 1.00 0.00 C \\\\nATOM 5749 O THR C 105 -16.265 -1.079 37.010 1.00 0.00 O \\\\nATOM 5750 CB THR C 105 -16.814 0.449 39.784 1.00 0.00 C \\\\nATOM 5751 OG1 THR C 105 -16.649 -0.580 40.769 1.00 0.00 O \\\\nATOM 5752 CG2 THR C 105 -17.455 1.669 40.435 1.00 0.00 C \\\\nATOM 5753 H THR C 105 -19.045 -1.092 39.648 1.00 0.00 H \\\\nATOM 5754 HA THR C 105 -17.808 0.610 37.962 1.00 0.00 H \\\\nATOM 5755 HB THR C 105 -15.951 0.704 39.422 1.00 0.00 H \\\\nATOM 5756 HG1 THR C 105 -17.352 -1.038 40.816 1.00 0.00 H \\\\nATOM 5757 HG21 THR C 105 -16.888 1.987 41.155 1.00 0.00 H \\\\nATOM 5758 HG22 THR C 105 -17.561 2.371 39.774 1.00 0.00 H \\\\nATOM 5759 HG23 THR C 105 -18.324 1.427 40.791 1.00 0.00 H \\\\nATOM 5760 N ARG C 106 -17.234 -2.472 38.483 1.00 0.00 N \\\\nATOM 5761 CA ARG C 106 -16.559 -3.660 37.990 1.00 0.00 C \\\\nATOM 5762 C ARG C 106 -17.573 -4.781 37.835 1.00 0.00 C \\\\nATOM 5763 O ARG C 106 -18.646 -4.769 38.443 1.00 0.00 O \\\\nATOM 5764 CB ARG C 106 -15.429 -4.096 38.930 1.00 0.00 C \\\\nATOM 5765 CG ARG C 106 -15.916 -4.503 40.303 1.00 0.00 C \\\\nATOM 5766 CD ARG C 106 -14.762 -4.777 41.245 1.00 0.00 C \\\\nATOM 5767 NE ARG C 106 -15.206 -4.791 42.633 1.00 0.00 N \\\\nATOM 5768 CZ ARG C 106 -15.781 -5.835 43.220 1.00 0.00 C \\\\nATOM 5769 NH1 ARG C 106 -15.979 -6.954 42.536 1.00 0.00 N \\\\nATOM 5770 NH2 ARG C 106 -16.158 -5.760 44.488 1.00 0.00 N \\\\nATOM 5771 H ARG C 106 -17.791 -2.624 39.120 1.00 0.00 H \\\\nATOM 5772 HA ARG C 106 -16.160 -3.454 37.130 1.00 0.00 H \\\\nATOM 5773 HB2 ARG C 106 -14.952 -4.840 38.529 1.00 0.00 H \\\\nATOM 5774 HB3 ARG C 106 -14.794 -3.368 39.022 1.00 0.00 H \\\\nATOM 5775 HG2 ARG C 106 -16.475 -3.800 40.670 1.00 0.00 H \\\\nATOM 5776 HG3 ARG C 106 -16.470 -5.296 40.229 1.00 0.00 H \\\\nATOM 5777 HD2 ARG C 106 -14.356 -5.630 41.024 1.00 0.00 H \\\\nATOM 5778 HD3 ARG C 106 -14.078 -4.099 41.128 1.00 0.00 H \\\\nATOM 5779 HE ARG C 106 -15.089 -4.079 43.101 1.00 0.00 H \\\\nATOM 5780 HH11 ARG C 106 -15.735 -7.004 41.713 1.00 0.00 H \\\\nATOM 5781 HH12 ARG C 106 -16.351 -7.630 42.916 1.00 0.00 H \\\\nATOM 5782 HH21 ARG C 106 -16.031 -5.035 44.932 1.00 0.00 H \\\\nATOM 5783 HH22 ARG C 106 -16.530 -6.437 44.867 1.00 0.00 H \\\\nATOM 5784 N SER C 107 -17.217 -5.759 37.009 1.00 0.00 N \\\\nATOM 5785 CA SER C 107 -18.092 -6.892 36.744 1.00 0.00 C \\\\nATOM 5786 C SER C 107 -17.240 -8.042 36.236 1.00 0.00 C \\\\nATOM 5787 O SER C 107 -16.420 -7.856 35.333 1.00 0.00 O \\\\nATOM 5788 CB SER C 107 -19.176 -6.530 35.726 1.00 0.00 C \\\\nATOM 5789 OG SER C 107 -19.650 -7.678 35.052 1.00 0.00 O \\\\nATOM 5790 H SER C 107 -16.467 -5.784 36.590 1.00 0.00 H \\\\nATOM 5791 HA SER C 107 -18.546 -7.150 37.562 1.00 0.00 H \\\\nATOM 5792 HB2 SER C 107 -19.913 -6.090 36.178 1.00 0.00 H \\\\nATOM 5793 HB3 SER C 107 -18.820 -5.898 35.082 1.00 0.00 H \\\\nATOM 5794 HG SER C 107 -20.324 -7.476 34.593 1.00 0.00 H \\\\nATOM 5795 N THR C 108 -17.438 -9.222 36.812 1.00 0.00 N \\\\nATOM 5796 CA THR C 108 -16.772 -10.441 36.375 1.00 0.00 C \\\\nATOM 5797 C THR C 108 -17.802 -11.306 35.664 1.00 0.00 C \\\\nATOM 5798 O THR C 108 -18.824 -11.673 36.255 1.00 0.00 O \\\\nATOM 5799 CB THR C 108 -16.164 -11.183 37.564 1.00 0.00 C \\\\nATOM 5800 OG1 THR C 108 -15.668 -10.232 38.513 1.00 0.00 O \\\\nATOM 5801 CG2 THR C 108 -15.021 -12.067 37.111 1.00 0.00 C \\\\nATOM 5802 H THR C 108 -17.971 -9.338 37.477 1.00 0.00 H \\\\nATOM 5803 HA THR C 108 -16.044 -10.226 35.771 1.00 0.00 H \\\\nATOM 5804 HB THR C 108 -16.851 -11.736 37.969 1.00 0.00 H \\\\nATOM 5805 HG1 THR C 108 -15.449 -9.526 38.114 1.00 0.00 H \\\\nATOM 5806 HG21 THR C 108 -14.647 -12.530 37.877 1.00 0.00 H \\\\nATOM 5807 HG22 THR C 108 -15.349 -12.716 36.469 1.00 0.00 H \\\\nATOM 5808 HG23 THR C 108 -14.334 -11.521 36.696 1.00 0.00 H \\\\nATOM 5809 N GLU C 109 -17.528 -11.641 34.406 1.00 0.00 N \\\\nATOM 5810 CA GLU C 109 -18.491 -12.335 33.566 1.00 0.00 C \\\\nATOM 5811 C GLU C 109 -17.829 -13.539 32.916 1.00 0.00 C \\\\nATOM 5812 O GLU C 109 -16.678 -13.467 32.475 1.00 0.00 O \\\\nATOM 5813 CB GLU C 109 -19.053 -11.388 32.495 1.00 0.00 C \\\\nATOM 5814 CG GLU C 109 -19.103 -9.930 32.947 1.00 0.00 C \\\\nATOM 5815 CD GLU C 109 -19.582 -8.970 31.872 1.00 0.00 C \\\\nATOM 5816 OE1 GLU C 109 -19.206 -9.148 30.695 1.00 0.00 O \\\\nATOM 5817 OE2 GLU C 109 -20.336 -8.033 32.212 1.00 0.00 O \\\\nATOM 5818 H GLU C 109 -16.779 -11.471 34.019 1.00 0.00 H \\\\nATOM 5819 HA GLU C 109 -19.229 -12.639 34.118 1.00 0.00 H \\\\nATOM 5820 HB2 GLU C 109 -18.508 -11.454 31.695 1.00 0.00 H \\\\nATOM 5821 HB3 GLU C 109 -19.947 -11.676 32.254 1.00 0.00 H \\\\nATOM 5822 HG2 GLU C 109 -19.689 -9.859 33.717 1.00 0.00 H \\\\nATOM 5823 HG3 GLU C 109 -18.218 -9.660 33.239 1.00 0.00 H \\\\nATOM 5824 N ARG C 110 -18.575 -14.639 32.838 1.00 0.00 N \\\\nATOM 5825 CA ARG C 110 -18.041 -15.931 32.432 1.00 0.00 C \\\\nATOM 5826 C ARG C 110 -18.713 -16.381 31.144 1.00 0.00 C \\\\nATOM 5827 O ARG C 110 -19.944 -16.400 31.056 1.00 0.00 O \\\\nATOM 5828 CB ARG C 110 -18.240 -16.981 33.529 1.00 0.00 C \\\\nATOM 5829 CG ARG C 110 -17.862 -18.393 33.102 1.00 0.00 C \\\\nATOM 5830 CD ARG C 110 -17.934 -19.377 34.262 1.00 0.00 C \\\\nATOM 5831 NE ARG C 110 -19.226 -20.055 34.339 1.00 0.00 N \\\\nATOM 5832 CZ ARG C 110 -19.852 -20.346 35.475 1.00 0.00 C \\\\nATOM 5833 NH1 ARG C 110 -19.307 -20.017 36.638 1.00 0.00 N \\\\nATOM 5834 NH2 ARG C 110 -21.024 -20.965 35.449 1.00 0.00 N \\\\nATOM 5835 H ARG C 110 -19.415 -14.653 33.022 1.00 0.00 H \\\\nATOM 5836 HA ARG C 110 -17.088 -15.836 32.281 1.00 0.00 H \\\\nATOM 5837 HB2 ARG C 110 -17.710 -16.733 34.303 1.00 0.00 H \\\\nATOM 5838 HB3 ARG C 110 -19.169 -16.974 33.808 1.00 0.00 H \\\\nATOM 5839 HG2 ARG C 110 -18.456 -18.686 32.393 1.00 0.00 H \\\\nATOM 5840 HG3 ARG C 110 -16.964 -18.390 32.736 1.00 0.00 H \\\\nATOM 5841 HD2 ARG C 110 -17.230 -20.038 34.166 1.00 0.00 H \\\\nATOM 5842 HD3 ARG C 110 -17.769 -18.905 35.093 1.00 0.00 H \\\\nATOM 5843 HE ARG C 110 -19.606 -20.280 33.601 1.00 0.00 H \\\\nATOM 5844 HH11 ARG C 110 -18.547 -19.615 36.658 1.00 0.00 H \\\\nATOM 5845 HH12 ARG C 110 -19.713 -20.206 37.372 1.00 0.00 H \\\\nATOM 5846 HH21 ARG C 110 -21.381 -21.179 34.696 1.00 0.00 H \\\\nATOM 5847 HH22 ARG C 110 -21.428 -21.153 36.185 1.00 0.00 H \\\\nATOM 5848 N LEU C 111 -17.902 -16.747 30.154 1.00 0.00 N \\\\nATOM 5849 CA LEU C 111 -18.419 -17.240 28.883 1.00 0.00 C \\\\nATOM 5850 C LEU C 111 -18.977 -18.645 29.073 1.00 0.00 C \\\\nATOM 5851 O LEU C 111 -18.230 -19.586 29.356 1.00 0.00 O \\\\nATOM 5852 CB LEU C 111 -17.312 -17.227 27.833 1.00 0.00 C \\\\nATOM 5853 CG LEU C 111 -17.640 -17.799 26.453 1.00 0.00 C \\\\nATOM 5854 CD1 LEU C 111 -18.863 -17.111 25.867 1.00 0.00 C \\\\nATOM 5855 CD2 LEU C 111 -16.443 -17.661 25.521 1.00 0.00 C \\\\nATOM 5856 H LEU C 111 -17.044 -16.717 30.200 1.00 0.00 H \\\\nATOM 5857 HA LEU C 111 -19.135 -16.663 28.574 1.00 0.00 H \\\\nATOM 5858 HB2 LEU C 111 -17.022 -16.309 27.715 1.00 0.00 H \\\\nATOM 5859 HB3 LEU C 111 -16.556 -17.720 28.189 1.00 0.00 H \\\\nATOM 5860 HG LEU C 111 -17.842 -18.743 26.551 1.00 0.00 H \\\\nATOM 5861 HD11 LEU C 111 -19.057 -17.485 24.993 1.00 0.00 H \\\\nATOM 5862 HD12 LEU C 111 -19.624 -17.248 26.453 1.00 0.00 H \\\\nATOM 5863 HD13 LEU C 111 -18.689 -16.161 25.780 1.00 0.00 H \\\\nATOM 5864 HD21 LEU C 111 -16.666 -18.028 24.651 1.00 0.00 H \\\\nATOM 5865 HD22 LEU C 111 -16.212 -16.724 25.427 1.00 0.00 H \\\\nATOM 5866 HD23 LEU C 111 -15.687 -18.144 25.891 1.00 0.00 H \\\\nATOM 5867 N GLU C 112 -20.290 -18.793 28.914 1.00 0.00 N \\\\nATOM 5868 CA GLU C 112 -20.951 -20.084 29.061 1.00 0.00 C \\\\nATOM 5869 C GLU C 112 -21.159 -20.793 27.732 1.00 0.00 C \\\\nATOM 5870 O GLU C 112 -20.971 -22.010 27.649 1.00 0.00 O \\\\nATOM 5871 CB GLU C 112 -22.303 -19.915 29.761 1.00 0.00 C \\\\nATOM 5872 CG GLU C 112 -22.213 -19.297 31.147 1.00 0.00 C \\\\nATOM 5873 CD GLU C 112 -21.774 -20.293 32.203 1.00 0.00 C \\\\nATOM 5874 OE1 GLU C 112 -20.572 -20.631 32.243 1.00 0.00 O \\\\nATOM 5875 OE2 GLU C 112 -22.633 -20.742 32.991 1.00 0.00 O \\\\nATOM 5876 H GLU C 112 -20.822 -18.146 28.718 1.00 0.00 H \\\\nATOM 5877 HA GLU C 112 -20.362 -20.635 29.600 1.00 0.00 H \\\\nATOM 5878 HB2 GLU C 112 -22.876 -19.361 29.207 1.00 0.00 H \\\\nATOM 5879 HB3 GLU C 112 -22.730 -20.783 29.832 1.00 0.00 H \\\\nATOM 5880 HG2 GLU C 112 -21.588 -18.556 31.127 1.00 0.00 H \\\\nATOM 5881 HG3 GLU C 112 -23.078 -18.932 31.391 1.00 0.00 H \\\\nATOM 5882 N LEU C 113 -21.539 -20.060 26.689 1.00 0.00 N \\\\nATOM 5883 CA LEU C 113 -21.799 -20.656 25.386 1.00 0.00 C \\\\nATOM 5884 C LEU C 113 -21.388 -19.670 24.305 1.00 0.00 C \\\\nATOM 5885 O LEU C 113 -21.703 -18.480 24.396 1.00 0.00 O \\\\nATOM 5886 CB LEU C 113 -23.281 -21.029 25.239 1.00 0.00 C \\\\nATOM 5887 CG LEU C 113 -23.716 -21.911 24.064 1.00 0.00 C \\\\nATOM 5888 CD1 LEU C 113 -24.912 -22.754 24.469 1.00 0.00 C \\\\nATOM 5889 CD2 LEU C 113 -24.053 -21.081 22.832 1.00 0.00 C \\\\nATOM 5890 H LEU C 113 -21.652 -19.208 26.718 1.00 0.00 H \\\\nATOM 5891 HA LEU C 113 -21.282 -21.472 25.298 1.00 0.00 H \\\\nATOM 5892 HB2 LEU C 113 -23.552 -21.476 26.056 1.00 0.00 H \\\\nATOM 5893 HB3 LEU C 113 -23.786 -20.203 25.187 1.00 0.00 H \\\\nATOM 5894 HG LEU C 113 -22.973 -22.490 23.834 1.00 0.00 H \\\\nATOM 5895 HD11 LEU C 113 -25.184 -23.310 23.722 1.00 0.00 H \\\\nATOM 5896 HD12 LEU C 113 -24.671 -23.318 25.221 1.00 0.00 H \\\\nATOM 5897 HD13 LEU C 113 -25.646 -22.173 24.723 1.00 0.00 H \\\\nATOM 5898 HD21 LEU C 113 -24.324 -21.669 22.110 1.00 0.00 H \\\\nATOM 5899 HD22 LEU C 113 -24.778 -20.471 23.041 1.00 0.00 H \\\\nATOM 5900 HD23 LEU C 113 -23.272 -20.573 22.560 1.00 0.00 H \\\\nATOM 5901 N LEU C 114 -20.682 -20.171 23.291 1.00 0.00 N \\\\nATOM 5902 CA LEU C 114 -20.337 -19.392 22.102 1.00 0.00 C \\\\nATOM 5903 C LEU C 114 -20.439 -20.338 20.911 1.00 0.00 C \\\\nATOM 5904 O LEU C 114 -19.505 -21.094 20.633 1.00 0.00 O \\\\nATOM 5905 CB LEU C 114 -18.949 -18.768 22.204 1.00 0.00 C \\\\nATOM 5906 CG LEU C 114 -18.719 -17.526 21.333 1.00 0.00 C \\\\nATOM 5907 CD1 LEU C 114 -17.635 -16.639 21.923 1.00 0.00 C \\\\nATOM 5908 CD2 LEU C 114 -18.374 -17.900 19.896 1.00 0.00 C \\\\nATOM 5909 H LEU C 114 -20.388 -20.979 23.274 1.00 0.00 H \\\\nATOM 5910 HA LEU C 114 -20.947 -18.644 22.003 1.00 0.00 H \\\\nATOM 5911 HB2 LEU C 114 -18.786 -18.529 23.130 1.00 0.00 H \\\\nATOM 5912 HB3 LEU C 114 -18.291 -19.439 21.964 1.00 0.00 H \\\\nATOM 5913 HG LEU C 114 -19.552 -17.029 21.319 1.00 0.00 H \\\\nATOM 5914 HD11 LEU C 114 -17.508 -15.862 21.356 1.00 0.00 H \\\\nATOM 5915 HD12 LEU C 114 -17.900 -16.351 22.811 1.00 0.00 H \\\\nATOM 5916 HD13 LEU C 114 -16.804 -17.137 21.979 1.00 0.00 H \\\\nATOM 5917 HD21 LEU C 114 -18.236 -17.093 19.376 1.00 0.00 H \\\\nATOM 5918 HD22 LEU C 114 -17.564 -18.434 19.886 1.00 0.00 H \\\\nATOM 5919 HD23 LEU C 114 -19.103 -18.412 19.511 1.00 0.00 H \\\\nATOM 5920 N ASP C 115 -21.566 -20.294 20.213 1.00 0.00 N \\\\nATOM 5921 CA ASP C 115 -21.778 -21.106 19.018 1.00 0.00 C \\\\nATOM 5922 C ASP C 115 -21.476 -20.224 17.813 1.00 0.00 C \\\\nATOM 5923 O ASP C 115 -22.264 -19.346 17.456 1.00 0.00 O \\\\nATOM 5924 CB ASP C 115 -23.198 -21.662 18.971 1.00 0.00 C \\\\nATOM 5925 CG ASP C 115 -23.336 -22.827 18.005 1.00 0.00 C \\\\nATOM 5926 OD1 ASP C 115 -22.646 -22.830 16.964 1.00 0.00 O \\\\nATOM 5927 OD2 ASP C 115 -24.137 -23.739 18.290 1.00 0.00 O \\\\nATOM 5928 H ASP C 115 -22.233 -19.791 20.418 1.00 0.00 H \\\\nATOM 5929 HA ASP C 115 -21.190 -21.877 19.021 1.00 0.00 H \\\\nATOM 5930 HB2 ASP C 115 -23.459 -21.950 19.860 1.00 0.00 H \\\\nATOM 5931 HB3 ASP C 115 -23.810 -20.956 18.711 1.00 0.00 H \\\\nATOM 5932 N ASP C 116 -20.320 -20.460 17.191 1.00 0.00 N \\\\nATOM 5933 CA ASP C 116 -19.897 -19.640 16.063 1.00 0.00 C \\\\nATOM 5934 C ASP C 116 -20.659 -19.970 14.787 1.00 0.00 C \\\\nATOM 5935 O ASP C 116 -20.637 -19.170 13.846 1.00 0.00 O \\\\nATOM 5936 CB ASP C 116 -18.395 -19.814 15.830 1.00 0.00 C \\\\nATOM 5937 CG ASP C 116 -17.716 -18.528 15.410 1.00 0.00 C \\\\nATOM 5938 OD1 ASP C 116 -18.253 -17.440 15.708 1.00 0.00 O \\\\nATOM 5939 OD2 ASP C 116 -16.640 -18.605 14.780 1.00 0.00 O \\\\nATOM 5940 H ASP C 116 -19.772 -21.086 17.407 1.00 0.00 H \\\\nATOM 5941 HA ASP C 116 -20.094 -18.717 16.287 1.00 0.00 H \\\\nATOM 5942 HB2 ASP C 116 -17.981 -20.143 16.643 1.00 0.00 H \\\\nATOM 5943 HB3 ASP C 116 -18.253 -20.488 15.147 1.00 0.00 H \\\\nATOM 5944 N ASN C 117 -21.333 -21.119 14.734 1.00 0.00 N \\\\nATOM 5945 CA ASN C 117 -22.156 -21.460 13.580 1.00 0.00 C \\\\nATOM 5946 C ASN C 117 -23.569 -20.909 13.702 1.00 0.00 C \\\\nATOM 5947 O ASN C 117 -24.138 -20.439 12.711 1.00 0.00 O \\\\nATOM 5948 CB ASN C 117 -22.219 -22.978 13.394 1.00 0.00 C \\\\nATOM 5949 CG ASN C 117 -20.981 -23.685 13.907 1.00 0.00 C \\\\nATOM 5950 OD1 ASN C 117 -19.881 -23.496 13.386 1.00 0.00 O \\\\nATOM 5951 ND2 ASN C 117 -21.157 -24.511 14.932 1.00 0.00 N \\\\nATOM 5952 H ASN C 117 -21.325 -21.712 15.356 1.00 0.00 H \\\\nATOM 5953 HA ASN C 117 -21.738 -21.052 12.806 1.00 0.00 H \\\\nATOM 5954 HB2 ASN C 117 -22.999 -23.324 13.856 1.00 0.00 H \\\\nATOM 5955 HB3 ASN C 117 -22.335 -23.180 12.452 1.00 0.00 H \\\\nATOM 5956 HD21 ASN C 117 -20.487 -24.940 15.259 1.00 0.00 H \\\\nATOM 5957 HD22 ASN C 117 -21.941 -24.617 15.269 1.00 0.00 H \\\\nATOM 5958 N GLU C 118 -24.140 -20.943 14.904 1.00 0.00 N \\\\nATOM 5959 CA GLU C 118 -25.499 -20.478 15.138 1.00 0.00 C \\\\nATOM 5960 C GLU C 118 -25.548 -19.068 15.700 1.00 0.00 C \\\\nATOM 5961 O GLU C 118 -26.644 -18.544 15.927 1.00 0.00 O \\\\nATOM 5962 CB GLU C 118 -26.224 -21.429 16.096 1.00 0.00 C \\\\nATOM 5963 CG GLU C 118 -26.066 -22.898 15.757 1.00 0.00 C \\\\nATOM 5964 CD GLU C 118 -26.600 -23.233 14.383 1.00 0.00 C \\\\nATOM 5965 OE1 GLU C 118 -25.860 -23.855 13.592 1.00 0.00 O \\\\nATOM 5966 OE2 GLU C 118 -27.760 -22.872 14.092 1.00 0.00 O \\\\nATOM 5967 H GLU C 118 -23.745 -21.239 15.609 1.00 0.00 H \\\\nATOM 5968 HA GLU C 118 -25.942 -20.466 14.275 1.00 0.00 H \\\\nATOM 5969 HB2 GLU C 118 -25.894 -21.278 16.996 1.00 0.00 H \\\\nATOM 5970 HB3 GLU C 118 -27.169 -21.209 16.100 1.00 0.00 H \\\\nATOM 5971 HG2 GLU C 118 -25.128 -23.139 15.804 1.00 0.00 H \\\\nATOM 5972 HG3 GLU C 118 -26.530 -23.432 16.421 1.00 0.00 H \\\\nATOM 5973 N HIS C 119 -24.391 -18.444 15.925 1.00 0.00 N \\\\nATOM 5974 CA HIS C 119 -24.302 -17.070 16.416 1.00 0.00 C \\\\nATOM 5975 C HIS C 119 -25.079 -16.905 17.725 1.00 0.00 C \\\\nATOM 5976 O HIS C 119 -26.037 -16.135 17.823 1.00 0.00 O \\\\nATOM 5977 CB HIS C 119 -24.790 -16.081 15.353 1.00 0.00 C \\\\nATOM 5978 CG HIS C 119 -24.374 -16.427 13.956 1.00 0.00 C \\\\nATOM 5979 ND1 HIS C 119 -23.055 -16.513 13.570 1.00 0.00 N \\\\nATOM 5980 CD2 HIS C 119 -25.108 -16.688 12.848 1.00 0.00 C \\\\nATOM 5981 CE1 HIS C 119 -22.992 -16.823 12.287 1.00 0.00 C \\\\nATOM 5982 NE2 HIS C 119 -24.224 -16.934 11.825 1.00 0.00 N \\\\nATOM 5983 H HIS C 119 -23.625 -18.813 15.794 1.00 0.00 H \\\\nATOM 5984 HA HIS C 119 -23.370 -16.874 16.600 1.00 0.00 H \\\\nATOM 5985 HB2 HIS C 119 -25.758 -16.034 15.389 1.00 0.00 H \\\\nATOM 5986 HB3 HIS C 119 -24.455 -15.197 15.570 1.00 0.00 H \\\\nATOM 5987 HD1 HIS C 119 -22.378 -16.385 14.084 1.00 0.00 H \\\\nATOM 5988 HD2 HIS C 119 -26.036 -16.699 12.790 1.00 0.00 H \\\\nATOM 5989 HE1 HIS C 119 -22.213 -16.943 11.794 1.00 0.00 H \\\\nATOM 5990 HE2 HIS C 119 -24.438 -17.129 11.015 1.00 0.00 H \\\\nATOM 5991 N ILE C 120 -24.647 -17.656 18.738 1.00 0.00 N \\\\nATOM 5992 CA ILE C 120 -25.228 -17.605 20.076 1.00 0.00 C \\\\nATOM 5993 C ILE C 120 -24.121 -17.302 21.075 1.00 0.00 C \\\\nATOM 5994 O ILE C 120 -23.072 -17.956 21.062 1.00 0.00 O \\\\nATOM 5995 CB ILE C 120 -25.941 -18.918 20.449 1.00 0.00 C \\\\nATOM 5996 CG1 ILE C 120 -26.853 -19.387 19.315 1.00 0.00 C \\\\nATOM 5997 CG2 ILE C 120 -26.742 -18.738 21.730 1.00 0.00 C \\\\nATOM 5998 CD1 ILE C 120 -27.385 -20.793 19.512 1.00 0.00 C \\\\nATOM 5999 H ILE C 120 -23.999 -18.217 18.664 1.00 0.00 H \\\\nATOM 6000 HA ILE C 120 -25.901 -16.906 20.094 1.00 0.00 H \\\\nATOM 6001 HB ILE C 120 -25.265 -19.598 20.594 1.00 0.00 H \\\\nATOM 6002 HG12 ILE C 120 -27.600 -18.774 19.236 1.00 0.00 H \\\\nATOM 6003 HG13 ILE C 120 -26.364 -19.348 18.478 1.00 0.00 H \\\\nATOM 6004 HG21 ILE C 120 -27.186 -19.571 21.954 1.00 0.00 H \\\\nATOM 6005 HG22 ILE C 120 -26.146 -18.486 22.452 1.00 0.00 H \\\\nATOM 6006 HG23 ILE C 120 -27.406 -18.043 21.602 1.00 0.00 H \\\\nATOM 6007 HD11 ILE C 120 -27.954 -21.032 18.764 1.00 0.00 H \\\\nATOM 6008 HD12 ILE C 120 -26.643 -21.416 19.565 1.00 0.00 H \\\\nATOM 6009 HD13 ILE C 120 -27.899 -20.833 20.334 1.00 0.00 H \\\\nATOM 6010 N LEU C 121 -24.352 -16.309 21.930 1.00 0.00 N \\\\nATOM 6011 CA LEU C 121 -23.402 -15.923 22.968 1.00 0.00 C \\\\nATOM 6012 C LEU C 121 -24.117 -15.905 24.310 1.00 0.00 C \\\\nATOM 6013 O LEU C 121 -25.071 -15.143 24.497 1.00 0.00 O \\\\nATOM 6014 CB LEU C 121 -22.785 -14.554 22.669 1.00 0.00 C \\\\nATOM 6015 CG LEU C 121 -21.879 -13.980 23.760 1.00 0.00 C \\\\nATOM 6016 CD1 LEU C 121 -20.551 -14.714 23.788 1.00 0.00 C \\\\nATOM 6017 CD2 LEU C 121 -21.661 -12.493 23.549 1.00 0.00 C \\\\nATOM 6018 H LEU C 121 -25.071 -15.837 21.923 1.00 0.00 H \\\\nATOM 6019 HA LEU C 121 -22.679 -16.569 22.992 1.00 0.00 H \\\\nATOM 6020 HB2 LEU C 121 -22.272 -14.621 21.848 1.00 0.00 H \\\\nATOM 6021 HB3 LEU C 121 -23.503 -13.923 22.504 1.00 0.00 H \\\\nATOM 6022 HG LEU C 121 -22.317 -14.104 24.616 1.00 0.00 H \\\\nATOM 6023 HD11 LEU C 121 -19.988 -14.339 24.484 1.00 0.00 H \\\\nATOM 6024 HD12 LEU C 121 -20.705 -15.655 23.969 1.00 0.00 H \\\\nATOM 6025 HD13 LEU C 121 -20.110 -14.618 22.929 1.00 0.00 H \\\\nATOM 6026 HD21 LEU C 121 -21.085 -12.148 24.249 1.00 0.00 H \\\\nATOM 6027 HD22 LEU C 121 -21.243 -12.346 22.686 1.00 0.00 H \\\\nATOM 6028 HD23 LEU C 121 -22.515 -12.033 23.577 1.00 0.00 H \\\\nATOM 6029 N SER C 122 -23.660 -16.742 25.240 1.00 0.00 N \\\\nATOM 6030 CA SER C 122 -24.241 -16.840 26.574 1.00 0.00 C \\\\nATOM 6031 C SER C 122 -23.198 -16.453 27.612 1.00 0.00 C \\\\nATOM 6032 O SER C 122 -22.085 -16.989 27.610 1.00 0.00 O \\\\nATOM 6033 CB SER C 122 -24.758 -18.253 26.847 1.00 0.00 C \\\\nATOM 6034 OG SER C 122 -25.499 -18.742 25.743 1.00 0.00 O \\\\nATOM 6035 H SER C 122 -22.997 -17.274 25.111 1.00 0.00 H \\\\nATOM 6036 HA SER C 122 -24.994 -16.231 26.629 1.00 0.00 H \\\\nATOM 6037 HB2 SER C 122 -24.011 -18.845 27.028 1.00 0.00 H \\\\nATOM 6038 HB3 SER C 122 -25.316 -18.250 27.640 1.00 0.00 H \\\\nATOM 6039 HG SER C 122 -25.703 -19.546 25.876 1.00 0.00 H \\\\nATOM 6040 N VAL C 123 -23.563 -15.525 28.496 1.00 0.00 N \\\\nATOM 6041 CA VAL C 123 -22.672 -15.015 29.530 1.00 0.00 C \\\\nATOM 6042 C VAL C 123 -23.356 -15.148 30.886 1.00 0.00 C \\\\nATOM 6043 O VAL C 123 -24.581 -15.047 30.997 1.00 0.00 O \\\\nATOM 6044 CB VAL C 123 -22.278 -13.545 29.242 1.00 0.00 C \\\\nATOM 6045 CG1 VAL C 123 -21.457 -12.953 30.373 1.00 0.00 C \\\\nATOM 6046 CG2 VAL C 123 -21.517 -13.449 27.928 1.00 0.00 C \\\\nATOM 6047 H VAL C 123 -24.347 -15.171 28.510 1.00 0.00 H \\\\nATOM 6048 HA VAL C 123 -21.853 -15.535 29.536 1.00 0.00 H \\\\nATOM 6049 HB VAL C 123 -23.096 -13.029 29.172 1.00 0.00 H \\\\nATOM 6050 HG11 VAL C 123 -21.228 -12.035 30.161 1.00 0.00 H \\\\nATOM 6051 HG12 VAL C 123 -21.973 -12.976 31.194 1.00 0.00 H \\\\nATOM 6052 HG13 VAL C 123 -20.644 -13.470 30.488 1.00 0.00 H \\\\nATOM 6053 HG21 VAL C 123 -21.277 -12.524 27.760 1.00 0.00 H \\\\nATOM 6054 HG22 VAL C 123 -20.712 -13.988 27.980 1.00 0.00 H \\\\nATOM 6055 HG23 VAL C 123 -22.077 -13.774 27.205 1.00 0.00 H \\\\nATOM 6056 N ARG C 124 -22.553 -15.377 31.925 1.00 0.00 N \\\\nATOM 6057 CA ARG C 124 -23.039 -15.443 33.298 1.00 0.00 C \\\\nATOM 6058 C ARG C 124 -22.187 -14.534 34.172 1.00 0.00 C \\\\nATOM 6059 O ARG C 124 -20.956 -14.544 34.069 1.00 0.00 O \\\\nATOM 6060 CB ARG C 124 -23.007 -16.879 33.836 1.00 0.00 C \\\\nATOM 6061 CG ARG C 124 -23.636 -17.036 35.212 1.00 0.00 C \\\\nATOM 6062 CD ARG C 124 -23.800 -18.500 35.586 1.00 0.00 C \\\\nATOM 6063 NE ARG C 124 -25.206 -18.895 35.635 1.00 0.00 N \\\\nATOM 6064 CZ ARG C 124 -26.020 -18.649 36.656 1.00 0.00 C \\\\nATOM 6065 NH1 ARG C 124 -25.572 -18.006 37.726 1.00 0.00 N \\\\nATOM 6066 NH2 ARG C 124 -27.283 -19.049 36.608 1.00 0.00 N \\\\nATOM 6067 H ARG C 124 -21.705 -15.499 31.850 1.00 0.00 H \\\\nATOM 6068 HA ARG C 124 -23.962 -15.146 33.315 1.00 0.00 H \\\\nATOM 6069 HB2 ARG C 124 -23.469 -17.459 33.211 1.00 0.00 H \\\\nATOM 6070 HB3 ARG C 124 -22.086 -17.180 33.875 1.00 0.00 H \\\\nATOM 6071 HG2 ARG C 124 -23.084 -16.592 35.874 1.00 0.00 H \\\\nATOM 6072 HG3 ARG C 124 -24.502 -16.599 35.225 1.00 0.00 H \\\\nATOM 6073 HD2 ARG C 124 -23.331 -19.053 34.941 1.00 0.00 H \\\\nATOM 6074 HD3 ARG C 124 -23.389 -18.661 36.450 1.00 0.00 H \\\\nATOM 6075 HE ARG C 124 -25.528 -19.315 34.957 1.00 0.00 H \\\\nATOM 6076 HH11 ARG C 124 -24.753 -17.747 37.760 1.00 0.00 H \\\\nATOM 6077 HH12 ARG C 124 -26.101 -17.848 38.385 1.00 0.00 H \\\\nATOM 6078 HH21 ARG C 124 -27.575 -19.468 35.916 1.00 0.00 H \\\\nATOM 6079 HH22 ARG C 124 -27.810 -18.890 37.269 1.00 0.00 H \\\\nATOM 6080 N PHE C 125 -22.845 -13.754 35.028 1.00 0.00 N \\\\nATOM 6081 CA PHE C 125 -22.150 -12.866 35.952 1.00 0.00 C \\\\nATOM 6082 C PHE C 125 -21.711 -13.657 37.180 1.00 0.00 C \\\\nATOM 6083 O PHE C 125 -22.532 -14.318 37.825 1.00 0.00 O \\\\nATOM 6084 CB PHE C 125 -23.053 -11.702 36.357 1.00 0.00 C \\\\nATOM 6085 CG PHE C 125 -23.270 -10.685 35.267 1.00 0.00 C \\\\nATOM 6086 CD1 PHE C 125 -22.646 -10.809 34.036 1.00 0.00 C \\\\nATOM 6087 CD2 PHE C 125 -24.110 -9.603 35.477 1.00 0.00 C \\\\nATOM 6088 CE1 PHE C 125 -22.852 -9.873 33.039 1.00 0.00 C \\\\nATOM 6089 CE2 PHE C 125 -24.320 -8.666 34.484 1.00 0.00 C \\\\nATOM 6090 CZ PHE C 125 -23.691 -8.800 33.264 1.00 0.00 C \\\\nATOM 6091 H PHE C 125 -23.702 -13.726 35.088 1.00 0.00 H \\\\nATOM 6092 HA PHE C 125 -21.367 -12.499 35.514 1.00 0.00 H \\\\nATOM 6093 HB2 PHE C 125 -23.913 -12.054 36.634 1.00 0.00 H \\\\nATOM 6094 HB3 PHE C 125 -22.666 -11.258 37.128 1.00 0.00 H \\\\nATOM 6095 HD1 PHE C 125 -22.081 -11.531 33.878 1.00 0.00 H \\\\nATOM 6096 HD2 PHE C 125 -24.538 -9.506 36.297 1.00 0.00 H \\\\nATOM 6097 HE1 PHE C 125 -22.426 -9.966 32.218 1.00 0.00 H \\\\nATOM 6098 HE2 PHE C 125 -24.886 -7.944 34.638 1.00 0.00 H \\\\nATOM 6099 HZ PHE C 125 -23.832 -8.170 32.595 1.00 0.00 H \\\\nATOM 6100 N VAL C 126 -20.421 -13.588 37.506 1.00 0.00 N \\\\nATOM 6101 CA VAL C 126 -19.864 -14.318 38.637 1.00 0.00 C \\\\nATOM 6102 C VAL C 126 -19.157 -13.382 39.617 1.00 0.00 C \\\\nATOM 6103 O VAL C 126 -18.348 -13.825 40.424 1.00 0.00 O \\\\nATOM 6104 CB VAL C 126 -18.922 -15.443 38.166 1.00 0.00 C \\\\nATOM 6105 CG1 VAL C 126 -19.704 -16.511 37.414 1.00 0.00 C \\\\nATOM 6106 CG2 VAL C 126 -17.810 -14.876 37.299 1.00 0.00 C \\\\nATOM 6107 H VAL C 126 -19.846 -13.115 37.075 1.00 0.00 H \\\\nATOM 6108 HA VAL C 126 -20.605 -14.729 39.109 1.00 0.00 H \\\\nATOM 6109 HB VAL C 126 -18.518 -15.856 38.945 1.00 0.00 H \\\\nATOM 6110 HG11 VAL C 126 -19.099 -17.211 37.124 1.00 0.00 H \\\\nATOM 6111 HG12 VAL C 126 -20.380 -16.889 37.998 1.00 0.00 H \\\\nATOM 6112 HG13 VAL C 126 -20.132 -16.114 36.640 1.00 0.00 H \\\\nATOM 6113 HG21 VAL C 126 -17.226 -15.595 37.010 1.00 0.00 H \\\\nATOM 6114 HG22 VAL C 126 -18.195 -14.441 36.522 1.00 0.00 H \\\\nATOM 6115 HG23 VAL C 126 -17.298 -14.230 37.810 1.00 0.00 H \\\\nATOM 6116 N GLY C 127 -19.457 -12.091 39.557 1.00 0.00 N \\\\nATOM 6117 CA GLY C 127 -18.862 -11.144 40.479 1.00 0.00 C \\\\nATOM 6118 C GLY C 127 -19.127 -9.725 40.033 1.00 0.00 C \\\\nATOM 6119 O GLY C 127 -19.638 -9.470 38.938 1.00 0.00 O \\\\nATOM 6120 H GLY C 127 -20.003 -11.746 38.989 1.00 0.00 H \\\\nATOM 6121 HA2 GLY C 127 -19.224 -11.281 41.369 1.00 0.00 H \\\\nATOM 6122 HA3 GLY C 127 -17.906 -11.297 40.535 1.00 0.00 H \\\\nATOM 6123 N GLY C 128 -18.757 -8.794 40.909 1.00 0.00 N \\\\nATOM 6124 CA GLY C 128 -18.941 -7.382 40.639 1.00 0.00 C \\\\nATOM 6125 C GLY C 128 -19.865 -6.695 41.624 1.00 0.00 C \\\\nATOM 6126 O GLY C 128 -20.669 -7.349 42.296 1.00 0.00 O \\\\nATOM 6127 H GLY C 128 -18.395 -8.967 41.670 1.00 0.00 H \\\\nATOM 6128 HA2 GLY C 128 -18.077 -6.941 40.655 1.00 0.00 H \\\\nATOM 6129 HA3 GLY C 128 -19.297 -7.275 39.743 1.00 0.00 H \\\\nATOM 6130 N ASP C 129 -19.753 -5.371 41.721 1.00 0.00 N \\\\nATOM 6131 CA ASP C 129 -20.567 -4.559 42.617 1.00 0.00 C \\\\nATOM 6132 C ASP C 129 -21.864 -4.081 41.968 1.00 0.00 C \\\\nATOM 6133 O ASP C 129 -22.424 -3.066 42.399 1.00 0.00 O \\\\nATOM 6134 CB ASP C 129 -19.761 -3.356 43.115 1.00 0.00 C \\\\nATOM 6135 CG ASP C 129 -19.114 -2.572 41.985 1.00 0.00 C \\\\nATOM 6136 OD1 ASP C 129 -19.359 -2.900 40.804 1.00 0.00 O \\\\nATOM 6137 OD2 ASP C 129 -18.362 -1.619 42.279 1.00 0.00 O \\\\nATOM 6138 H ASP C 129 -19.191 -4.913 41.258 1.00 0.00 H \\\\nATOM 6139 HA ASP C 129 -20.813 -5.126 43.365 1.00 0.00 H \\\\nATOM 6140 HB2 ASP C 129 -20.344 -2.767 43.619 1.00 0.00 H \\\\nATOM 6141 HB3 ASP C 129 -19.073 -3.663 43.725 1.00 0.00 H \\\\nATOM 6142 N HIS C 130 -22.354 -4.788 40.950 1.00 0.00 N \\\\nATOM 6143 CA HIS C 130 -23.511 -4.361 40.172 1.00 0.00 C \\\\nATOM 6144 C HIS C 130 -24.858 -4.753 40.770 1.00 0.00 C \\\\nATOM 6145 O HIS C 130 -25.887 -4.275 40.277 1.00 0.00 O \\\\nATOM 6146 CB HIS C 130 -23.416 -4.932 38.757 1.00 0.00 C \\\\nATOM 6147 CG HIS C 130 -22.932 -6.348 38.713 1.00 0.00 C \\\\nATOM 6148 ND1 HIS C 130 -23.712 -7.413 39.108 1.00 0.00 N \\\\nATOM 6149 CD2 HIS C 130 -21.742 -6.873 38.337 1.00 0.00 C \\\\nATOM 6150 CE1 HIS C 130 -23.026 -8.534 38.970 1.00 0.00 C \\\\nATOM 6151 NE2 HIS C 130 -21.827 -8.234 38.505 1.00 0.00 N \\\\nATOM 6152 H HIS C 130 -22.019 -5.536 40.691 1.00 0.00 H \\\\nATOM 6153 HA HIS C 130 -23.482 -3.391 40.172 1.00 0.00 H \\\\nATOM 6154 HB2 HIS C 130 -24.289 -4.884 38.338 1.00 0.00 H \\\\nATOM 6155 HB3 HIS C 130 -22.818 -4.377 38.232 1.00 0.00 H \\\\nATOM 6156 HD1 HIS C 130 -24.519 -7.357 39.399 1.00 0.00 H \\\\nATOM 6157 HD2 HIS C 130 -21.005 -6.401 38.024 1.00 0.00 H \\\\nATOM 6158 HE1 HIS C 130 -23.335 -9.389 39.167 1.00 0.00 H \\\\nATOM 6159 HE2 HIS C 130 -21.201 -8.799 38.335 1.00 0.00 H \\\\nATOM 6160 N ARG C 131 -24.882 -5.611 41.794 1.00 0.00 N \\\\nATOM 6161 CA ARG C 131 -26.103 -6.064 42.466 1.00 0.00 C \\\\nATOM 6162 C ARG C 131 -26.986 -6.945 41.587 1.00 0.00 C \\\\nATOM 6163 O ARG C 131 -28.177 -7.103 41.873 1.00 0.00 O \\\\nATOM 6164 CB ARG C 131 -26.937 -4.887 42.988 1.00 0.00 C \\\\nATOM 6165 CG ARG C 131 -26.219 -3.969 43.953 1.00 0.00 C \\\\nATOM 6166 CD ARG C 131 -27.221 -3.269 44.853 1.00 0.00 C \\\\nATOM 6167 NE ARG C 131 -28.408 -2.843 44.115 1.00 0.00 N \\\\nATOM 6168 CZ ARG C 131 -29.655 -3.021 44.540 1.00 0.00 C \\\\nATOM 6169 NH1 ARG C 131 -29.881 -3.618 45.703 1.00 0.00 N \\\\nATOM 6170 NH2 ARG C 131 -30.677 -2.600 43.807 1.00 0.00 N \\\\nATOM 6171 H ARG C 131 -24.167 -5.955 42.126 1.00 0.00 H \\\\nATOM 6172 HA ARG C 131 -25.792 -6.600 43.212 1.00 0.00 H \\\\nATOM 6173 HB2 ARG C 131 -27.241 -4.363 42.230 1.00 0.00 H \\\\nATOM 6174 HB3 ARG C 131 -27.728 -5.238 43.426 1.00 0.00 H \\\\nATOM 6175 HG2 ARG C 131 -25.593 -4.479 44.490 1.00 0.00 H \\\\nATOM 6176 HG3 ARG C 131 -25.702 -3.312 43.461 1.00 0.00 H \\\\nATOM 6177 HD2 ARG C 131 -27.483 -3.866 45.571 1.00 0.00 H \\\\nATOM 6178 HD3 ARG C 131 -26.802 -2.497 45.265 1.00 0.00 H \\\\nATOM 6179 HE ARG C 131 -28.293 -2.452 43.358 1.00 0.00 H \\\\nATOM 6180 HH11 ARG C 131 -29.221 -3.890 46.182 1.00 0.00 H \\\\nATOM 6181 HH12 ARG C 131 -30.688 -3.733 45.978 1.00 0.00 H \\\\nATOM 6182 HH21 ARG C 131 -30.534 -2.210 43.054 1.00 0.00 H \\\\nATOM 6183 HH22 ARG C 131 -31.482 -2.717 44.085 1.00 0.00 H \\\\nATOM 6184 N LEU C 132 -26.440 -7.523 40.523 1.00 0.00 N \\\\nATOM 6185 CA LEU C 132 -27.181 -8.412 39.627 1.00 0.00 C \\\\nATOM 6186 C LEU C 132 -26.646 -9.825 39.849 1.00 0.00 C \\\\nATOM 6187 O LEU C 132 -25.677 -10.241 39.213 1.00 0.00 O \\\\nATOM 6188 CB LEU C 132 -27.042 -7.984 38.166 1.00 0.00 C \\\\nATOM 6189 CG LEU C 132 -27.601 -6.620 37.757 1.00 0.00 C \\\\nATOM 6190 CD1 LEU C 132 -26.959 -6.160 36.461 1.00 0.00 C \\\\nATOM 6191 CD2 LEU C 132 -29.114 -6.678 37.613 1.00 0.00 C \\\\nATOM 6192 H LEU C 132 -25.618 -7.410 40.296 1.00 0.00 H \\\\nATOM 6193 HA LEU C 132 -28.130 -8.374 39.825 1.00 0.00 H \\\\nATOM 6194 HB2 LEU C 132 -26.098 -7.997 37.942 1.00 0.00 H \\\\nATOM 6195 HB3 LEU C 132 -27.473 -8.658 37.617 1.00 0.00 H \\\\nATOM 6196 HG LEU C 132 -27.390 -5.979 38.454 1.00 0.00 H \\\\nATOM 6197 HD11 LEU C 132 -27.320 -5.295 36.210 1.00 0.00 H \\\\nATOM 6198 HD12 LEU C 132 -26.000 -6.087 36.583 1.00 0.00 H \\\\nATOM 6199 HD13 LEU C 132 -27.147 -6.804 35.760 1.00 0.00 H \\\\nATOM 6200 HD21 LEU C 132 -29.448 -5.805 37.354 1.00 0.00 H \\\\nATOM 6201 HD22 LEU C 132 -29.350 -7.329 36.934 1.00 0.00 H \\\\nATOM 6202 HD23 LEU C 132 -29.510 -6.937 38.460 1.00 0.00 H \\\\nATOM 6203 N LYS C 133 -27.286 -10.566 40.748 1.00 0.00 N \\\\nATOM 6204 CA LYS C 133 -26.796 -11.881 41.131 1.00 0.00 C \\\\nATOM 6205 C LYS C 133 -27.521 -12.980 40.367 1.00 0.00 C \\\\nATOM 6206 O LYS C 133 -28.712 -12.874 40.063 1.00 0.00 O \\\\nATOM 6207 CB LYS C 133 -26.965 -12.106 42.635 1.00 0.00 C \\\\nATOM 6208 CG LYS C 133 -26.311 -11.041 43.499 1.00 0.00 C \\\\nATOM 6209 CD LYS C 133 -25.219 -11.635 44.370 1.00 0.00 C \\\\nATOM 6210 CE LYS C 133 -24.022 -10.704 44.469 1.00 0.00 C \\\\nATOM 6211 NZ LYS C 133 -22.742 -11.457 44.598 1.00 0.00 N \\\\nATOM 6212 H LYS C 133 -28.008 -10.323 41.148 1.00 0.00 H \\\\nATOM 6213 HA LYS C 133 -25.853 -11.917 40.909 1.00 0.00 H \\\\nATOM 6214 HB2 LYS C 133 -27.912 -12.141 42.843 1.00 0.00 H \\\\nATOM 6215 HB3 LYS C 133 -26.592 -12.971 42.867 1.00 0.00 H \\\\nATOM 6216 HG2 LYS C 133 -25.936 -10.348 42.934 1.00 0.00 H \\\\nATOM 6217 HG3 LYS C 133 -26.981 -10.619 44.059 1.00 0.00 H \\\\nATOM 6218 HD2 LYS C 133 -25.570 -11.809 45.257 1.00 0.00 H \\\\nATOM 6219 HD3 LYS C 133 -24.938 -12.488 44.003 1.00 0.00 H \\\\nATOM 6220 HE2 LYS C 133 -23.986 -10.139 43.682 1.00 0.00 H \\\\nATOM 6221 HE3 LYS C 133 -24.131 -10.118 45.234 1.00 0.00 H \\\\nATOM 6222 HZ1 LYS C 133 -22.137 -11.112 44.044 1.00 0.00 H \\\\nATOM 6223 HZ2 LYS C 133 -22.445 -11.397 45.435 1.00 0.00 H \\\\nATOM 6224 HZ3 LYS C 133 -22.878 -12.312 44.393 1.00 0.00 H \\\\nATOM 6225 N ASN C 134 -26.777 -14.051 40.077 1.00 0.00 N \\\\nATOM 6226 CA ASN C 134 -27.237 -15.135 39.210 1.00 0.00 C \\\\nATOM 6227 C ASN C 134 -27.782 -14.601 37.887 1.00 0.00 C \\\\nATOM 6228 O ASN C 134 -28.764 -15.108 37.343 1.00 0.00 O \\\\nATOM 6229 CB ASN C 134 -28.271 -16.005 39.924 1.00 0.00 C \\\\nATOM 6230 CG ASN C 134 -27.677 -16.767 41.097 1.00 0.00 C \\\\nATOM 6231 OD1 ASN C 134 -26.484 -17.078 41.109 1.00 0.00 O \\\\nATOM 6232 ND2 ASN C 134 -28.507 -17.067 42.091 1.00 0.00 N \\\\nATOM 6233 H ASN C 134 -25.982 -14.168 40.383 1.00 0.00 H \\\\nATOM 6234 HA ASN C 134 -26.470 -15.692 39.003 1.00 0.00 H \\\\nATOM 6235 HB2 ASN C 134 -28.998 -15.446 40.240 1.00 0.00 H \\\\nATOM 6236 HB3 ASN C 134 -28.652 -16.635 39.292 1.00 0.00 H \\\\nATOM 6237 HD21 ASN C 134 -28.218 -17.495 42.778 1.00 0.00 H \\\\nATOM 6238 HD22 ASN C 134 -29.333 -16.833 42.047 1.00 0.00 H \\\\nATOM 6239 N TYR C 135 -27.137 -13.563 37.360 1.00 0.00 N \\\\nATOM 6240 CA TYR C 135 -27.513 -13.026 36.059 1.00 0.00 C \\\\nATOM 6241 C TYR C 135 -26.987 -13.949 34.968 1.00 0.00 C \\\\nATOM 6242 O TYR C 135 -25.775 -14.160 34.853 1.00 0.00 O \\\\nATOM 6243 CB TYR C 135 -26.973 -11.607 35.879 1.00 0.00 C \\\\nATOM 6244 CG TYR C 135 -27.266 -10.997 34.522 1.00 0.00 C \\\\nATOM 6245 CD1 TYR C 135 -26.427 -11.226 33.437 1.00 0.00 C \\\\nATOM 6246 CD2 TYR C 135 -28.379 -10.187 34.327 1.00 0.00 C \\\\nATOM 6247 CE1 TYR C 135 -26.690 -10.672 32.200 1.00 0.00 C \\\\nATOM 6248 CE2 TYR C 135 -28.648 -9.627 33.088 1.00 0.00 C \\\\nATOM 6249 CZ TYR C 135 -27.799 -9.876 32.029 1.00 0.00 C \\\\nATOM 6250 OH TYR C 135 -28.058 -9.325 30.796 1.00 0.00 O \\\\nATOM 6251 H TYR C 135 -26.481 -13.157 37.740 1.00 0.00 H \\\\nATOM 6252 HA TYR C 135 -28.480 -12.979 36.000 1.00 0.00 H \\\\nATOM 6253 HB2 TYR C 135 -27.352 -11.038 36.567 1.00 0.00 H \\\\nATOM 6254 HB3 TYR C 135 -26.013 -11.617 36.017 1.00 0.00 H \\\\nATOM 6255 HD1 TYR C 135 -25.675 -11.762 33.547 1.00 0.00 H \\\\nATOM 6256 HD2 TYR C 135 -28.952 -10.018 35.040 1.00 0.00 H \\\\nATOM 6257 HE1 TYR C 135 -26.119 -10.836 31.484 1.00 0.00 H \\\\nATOM 6258 HE2 TYR C 135 -29.396 -9.087 32.971 1.00 0.00 H \\\\nATOM 6259 HH TYR C 135 -27.887 -9.887 30.196 1.00 0.00 H \\\\nATOM 6260 N SER C 136 -27.898 -14.498 34.173 1.00 0.00 N \\\\nATOM 6261 CA SER C 136 -27.565 -15.295 33.002 1.00 0.00 C \\\\nATOM 6262 C SER C 136 -28.274 -14.690 31.801 1.00 0.00 C \\\\nATOM 6263 O SER C 136 -29.450 -14.329 31.888 1.00 0.00 O \\\\nATOM 6264 CB SER C 136 -27.980 -16.759 33.186 1.00 0.00 C \\\\nATOM 6265 OG SER C 136 -28.359 -17.343 31.953 1.00 0.00 O \\\\nATOM 6266 H SER C 136 -28.744 -14.415 34.303 1.00 0.00 H \\\\nATOM 6267 HA SER C 136 -26.604 -15.286 32.868 1.00 0.00 H \\\\nATOM 6268 HB2 SER C 136 -27.244 -17.260 33.572 1.00 0.00 H \\\\nATOM 6269 HB3 SER C 136 -28.719 -16.812 33.812 1.00 0.00 H \\\\nATOM 6270 HG SER C 136 -28.580 -18.144 32.078 1.00 0.00 H \\\\nATOM 6271 N SER C 137 -27.568 -14.586 30.676 1.00 0.00 N \\\\nATOM 6272 CA SER C 137 -28.128 -13.922 29.509 1.00 0.00 C \\\\nATOM 6273 C SER C 137 -27.785 -14.684 28.239 1.00 0.00 C \\\\nATOM 6274 O SER C 137 -26.732 -15.318 28.136 1.00 0.00 O \\\\nATOM 6275 CB SER C 137 -27.629 -12.475 29.396 1.00 0.00 C \\\\nATOM 6276 OG SER C 137 -26.429 -12.407 28.647 1.00 0.00 O \\\\nATOM 6277 H SER C 137 -26.771 -14.891 30.571 1.00 0.00 H \\\\nATOM 6278 HA SER C 137 -29.092 -13.907 29.619 1.00 0.00 H \\\\nATOM 6279 HB2 SER C 137 -28.309 -11.927 28.974 1.00 0.00 H \\\\nATOM 6280 HB3 SER C 137 -27.482 -12.110 30.283 1.00 0.00 H \\\\nATOM 6281 HG SER C 137 -26.437 -11.718 28.166 1.00 0.00 H \\\\nATOM 6282 N ILE C 138 -28.692 -14.600 27.267 1.00 0.00 N \\\\nATOM 6283 CA ILE C 138 -28.564 -15.269 25.977 1.00 0.00 C \\\\nATOM 6284 C ILE C 138 -28.692 -14.206 24.893 1.00 0.00 C \\\\nATOM 6285 O ILE C 138 -29.703 -13.495 24.835 1.00 0.00 O \\\\nATOM 6286 CB ILE C 138 -29.632 -16.361 25.791 1.00 0.00 C \\\\nATOM 6287 CG1 ILE C 138 -29.616 -17.363 26.952 1.00 0.00 C \\\\nATOM 6288 CG2 ILE C 138 -29.443 -17.072 24.461 1.00 0.00 C \\\\nATOM 6289 CD1 ILE C 138 -28.310 -18.091 27.134 1.00 0.00 C \\\\nATOM 6290 H ILE C 138 -29.415 -14.141 27.343 1.00 0.00 H \\\\nATOM 6291 HA ILE C 138 -27.703 -15.713 25.925 1.00 0.00 H \\\\nATOM 6292 HB ILE C 138 -30.501 -15.930 25.788 1.00 0.00 H \\\\nATOM 6293 HG12 ILE C 138 -29.827 -16.892 27.773 1.00 0.00 H \\\\nATOM 6294 HG13 ILE C 138 -30.320 -18.016 26.810 1.00 0.00 H \\\\nATOM 6295 HG21 ILE C 138 -30.123 -17.756 24.360 1.00 0.00 H \\\\nATOM 6296 HG22 ILE C 138 -29.520 -16.431 23.737 1.00 0.00 H \\\\nATOM 6297 HG23 ILE C 138 -28.565 -17.484 24.436 1.00 0.00 H \\\\nATOM 6298 HD11 ILE C 138 -28.382 -18.702 27.884 1.00 0.00 H \\\\nATOM 6299 HD12 ILE C 138 -28.103 -18.591 26.329 1.00 0.00 H \\\\nATOM 6300 HD13 ILE C 138 -27.603 -17.450 27.307 1.00 0.00 H \\\\nATOM 6301 N LEU C 139 -27.676 -14.095 24.040 1.00 0.00 N \\\\nATOM 6302 CA LEU C 139 -27.707 -13.195 22.893 1.00 0.00 C \\\\nATOM 6303 C LEU C 139 -27.628 -14.014 21.613 1.00 0.00 C \\\\nATOM 6304 O LEU C 139 -26.739 -14.860 21.467 1.00 0.00 O \\\\nATOM 6305 CB LEU C 139 -26.556 -12.181 22.947 1.00 0.00 C \\\\nATOM 6306 CG LEU C 139 -26.593 -11.003 21.961 1.00 0.00 C \\\\nATOM 6307 CD1 LEU C 139 -25.893 -9.790 22.552 1.00 0.00 C \\\\nATOM 6308 CD2 LEU C 139 -25.965 -11.362 20.616 1.00 0.00 C \\\\nATOM 6309 H LEU C 139 -26.946 -14.543 24.112 1.00 0.00 H \\\\nATOM 6310 HA LEU C 139 -28.538 -12.695 22.913 1.00 0.00 H \\\\nATOM 6311 HB2 LEU C 139 -26.521 -11.817 23.845 1.00 0.00 H \\\\nATOM 6312 HB3 LEU C 139 -25.727 -12.663 22.804 1.00 0.00 H \\\\nATOM 6313 HG LEU C 139 -27.527 -10.791 21.805 1.00 0.00 H \\\\nATOM 6314 HD11 LEU C 139 -25.925 -9.057 21.918 1.00 0.00 H \\\\nATOM 6315 HD12 LEU C 139 -26.338 -9.527 23.373 1.00 0.00 H \\\\nATOM 6316 HD13 LEU C 139 -24.968 -10.011 22.743 1.00 0.00 H \\\\nATOM 6317 HD21 LEU C 139 -26.008 -10.595 20.024 1.00 0.00 H \\\\nATOM 6318 HD22 LEU C 139 -25.038 -11.616 20.749 1.00 0.00 H \\\\nATOM 6319 HD23 LEU C 139 -26.449 -12.103 20.220 1.00 0.00 H \\\\nATOM 6320 N THR C 140 -28.561 -13.767 20.692 1.00 0.00 N \\\\nATOM 6321 CA THR C 140 -28.560 -14.394 19.378 1.00 0.00 C \\\\nATOM 6322 C THR C 140 -28.762 -13.334 18.302 1.00 0.00 C \\\\nATOM 6323 O THR C 140 -29.395 -12.301 18.540 1.00 0.00 O \\\\nATOM 6324 CB THR C 140 -29.658 -15.465 19.256 1.00 0.00 C \\\\nATOM 6325 OG1 THR C 140 -30.946 -14.844 19.348 1.00 0.00 O \\\\nATOM 6326 CG2 THR C 140 -29.522 -16.516 20.353 1.00 0.00 C \\\\nATOM 6327 H THR C 140 -29.217 -13.225 20.818 1.00 0.00 H \\\\nATOM 6328 HA THR C 140 -27.702 -14.830 19.259 1.00 0.00 H \\\\nATOM 6329 HB THR C 140 -29.562 -15.904 18.396 1.00 0.00 H \\\\nATOM 6330 HG1 THR C 140 -30.885 -14.138 19.799 1.00 0.00 H \\\\nATOM 6331 HG21 THR C 140 -30.224 -17.179 20.255 1.00 0.00 H \\\\nATOM 6332 HG22 THR C 140 -28.657 -16.949 20.281 1.00 0.00 H \\\\nATOM 6333 HG23 THR C 140 -29.599 -16.090 21.221 1.00 0.00 H \\\\nATOM 6334 N VAL C 141 -28.216 -13.596 17.113 1.00 0.00 N \\\\nATOM 6335 CA VAL C 141 -28.328 -12.696 15.969 1.00 0.00 C \\\\nATOM 6336 C VAL C 141 -28.830 -13.504 14.775 1.00 0.00 C \\\\nATOM 6337 O VAL C 141 -28.307 -14.586 14.486 1.00 0.00 O \\\\nATOM 6338 CB VAL C 141 -27.002 -11.967 15.653 1.00 0.00 C \\\\nATOM 6339 CG1 VAL C 141 -26.475 -11.255 16.891 1.00 0.00 C \\\\nATOM 6340 CG2 VAL C 141 -25.950 -12.899 15.102 1.00 0.00 C \\\\nATOM 6341 H VAL C 141 -27.766 -14.310 16.949 1.00 0.00 H \\\\nATOM 6342 HA VAL C 141 -28.961 -11.992 16.181 1.00 0.00 H \\\\nATOM 6343 HB VAL C 141 -27.197 -11.312 14.965 1.00 0.00 H \\\\nATOM 6344 HG11 VAL C 141 -25.644 -10.803 16.676 1.00 0.00 H \\\\nATOM 6345 HG12 VAL C 141 -27.128 -10.604 17.192 1.00 0.00 H \\\\nATOM 6346 HG13 VAL C 141 -26.317 -11.903 17.595 1.00 0.00 H \\\\nATOM 6347 HG21 VAL C 141 -25.139 -12.400 14.919 1.00 0.00 H \\\\nATOM 6348 HG22 VAL C 141 -25.762 -13.595 15.751 1.00 0.00 H \\\\nATOM 6349 HG23 VAL C 141 -26.273 -13.302 14.281 1.00 0.00 H \\\\nATOM 6350 N HIS C 142 -29.880 -13.008 14.120 1.00 0.00 N \\\\nATOM 6351 CA HIS C 142 -30.543 -13.738 13.048 1.00 0.00 C \\\\nATOM 6352 C HIS C 142 -30.603 -12.910 11.773 1.00 0.00 C \\\\nATOM 6353 O HIS C 142 -30.714 -11.678 11.832 1.00 0.00 O \\\\nATOM 6354 CB HIS C 142 -31.959 -14.145 13.482 1.00 0.00 C \\\\nATOM 6355 CG HIS C 142 -32.043 -14.603 14.904 1.00 0.00 C \\\\nATOM 6356 ND1 HIS C 142 -31.897 -15.924 15.270 1.00 0.00 N \\\\nATOM 6357 CD2 HIS C 142 -32.245 -13.916 16.053 1.00 0.00 C \\\\nATOM 6358 CE1 HIS C 142 -32.013 -16.031 16.581 1.00 0.00 C \\\\nATOM 6359 NE2 HIS C 142 -32.224 -14.827 17.081 1.00 0.00 N \\\\nATOM 6360 H HIS C 142 -30.226 -12.238 14.287 1.00 0.00 H \\\\nATOM 6361 HA HIS C 142 -30.025 -14.537 12.863 1.00 0.00 H \\\\nATOM 6362 HB2 HIS C 142 -32.556 -13.391 13.357 1.00 0.00 H \\\\nATOM 6363 HB3 HIS C 142 -32.275 -14.856 12.902 1.00 0.00 H \\\\nATOM 6364 HD1 HIS C 142 -31.753 -16.577 14.729 1.00 0.00 H \\\\nATOM 6365 HD2 HIS C 142 -32.374 -12.998 16.132 1.00 0.00 H \\\\nATOM 6366 HE1 HIS C 142 -31.956 -16.820 17.069 1.00 0.00 H \\\\nATOM 6367 HE2 HIS C 142 -32.331 -14.643 17.914 1.00 0.00 H \\\\nATOM 6368 N PRO C 143 -30.516 -13.551 10.604 1.00 0.00 N \\\\nATOM 6369 CA PRO C 143 -30.589 -12.803 9.341 1.00 0.00 C \\\\nATOM 6370 C PRO C 143 -31.980 -12.260 9.057 1.00 0.00 C \\\\nATOM 6371 O PRO C 143 -32.994 -12.894 9.357 1.00 0.00 O \\\\nATOM 6372 CB PRO C 143 -30.167 -13.835 8.287 1.00 0.00 C \\\\nATOM 6373 CG PRO C 143 -30.428 -15.157 8.916 1.00 0.00 C \\\\nATOM 6374 CD PRO C 143 -30.236 -14.981 10.393 1.00 0.00 C \\\\nATOM 6375 HA PRO C 143 -30.024 -12.014 9.355 1.00 0.00 H \\\\nATOM 6376 HB2 PRO C 143 -30.676 -13.729 7.468 1.00 0.00 H \\\\nATOM 6377 HB3 PRO C 143 -29.231 -13.736 8.054 1.00 0.00 H \\\\nATOM 6378 HG2 PRO C 143 -31.329 -15.459 8.720 1.00 0.00 H \\\\nATOM 6379 HG3 PRO C 143 -29.821 -15.829 8.568 1.00 0.00 H \\\\nATOM 6380 HD2 PRO C 143 -30.841 -15.543 10.902 1.00 0.00 H \\\\nATOM 6381 HD3 PRO C 143 -29.335 -15.213 10.667 1.00 0.00 H \\\\nATOM 6382 N GLU C 144 -32.013 -11.063 8.475 1.00 0.00 N \\\\nATOM 6383 CA GLU C 144 -33.260 -10.403 8.118 1.00 0.00 C \\\\nATOM 6384 C GLU C 144 -33.006 -9.464 6.950 1.00 0.00 C \\\\nATOM 6385 O GLU C 144 -31.889 -8.977 6.759 1.00 0.00 O \\\\nATOM 6386 CB GLU C 144 -33.843 -9.622 9.297 1.00 0.00 C \\\\nATOM 6387 CG GLU C 144 -35.084 -10.245 9.895 1.00 0.00 C \\\\nATOM 6388 CD GLU C 144 -35.703 -9.374 10.967 1.00 0.00 C \\\\nATOM 6389 OE1 GLU C 144 -35.155 -8.284 11.237 1.00 0.00 O \\\\nATOM 6390 OE2 GLU C 144 -36.738 -9.777 11.539 1.00 0.00 O \\\\nATOM 6391 H GLU C 144 -31.308 -10.612 8.277 1.00 0.00 H \\\\nATOM 6392 HA GLU C 144 -33.907 -11.082 7.869 1.00 0.00 H \\\\nATOM 6393 HB2 GLU C 144 -33.166 -9.545 9.988 1.00 0.00 H \\\\nATOM 6394 HB3 GLU C 144 -34.054 -8.722 9.004 1.00 0.00 H \\\\nATOM 6395 HG2 GLU C 144 -35.735 -10.403 9.193 1.00 0.00 H \\\\nATOM 6396 HG3 GLU C 144 -34.860 -11.110 10.273 1.00 0.00 H \\\\nATOM 6397 N VAL C 145 -34.039 -9.246 6.146 1.00 0.00 N \\\\nATOM 6398 CA VAL C 145 -33.991 -8.275 5.062 1.00 0.00 C \\\\nATOM 6399 C VAL C 145 -34.637 -6.993 5.565 1.00 0.00 C \\\\nATOM 6400 O VAL C 145 -35.824 -6.982 5.912 1.00 0.00 O \\\\nATOM 6401 CB VAL C 145 -34.700 -8.792 3.803 1.00 0.00 C \\\\nATOM 6402 CG1 VAL C 145 -34.532 -7.809 2.643 1.00 0.00 C \\\\nATOM 6403 CG2 VAL C 145 -34.218 -10.190 3.434 1.00 0.00 C \\\\nATOM 6404 H VAL C 145 -34.790 -9.659 6.214 1.00 0.00 H \\\\nATOM 6405 HA VAL C 145 -33.069 -8.114 4.807 1.00 0.00 H \\\\nATOM 6406 HB VAL C 145 -35.648 -8.858 3.995 1.00 0.00 H \\\\nATOM 6407 HG11 VAL C 145 -34.986 -8.153 1.858 1.00 0.00 H \\\\nATOM 6408 HG12 VAL C 145 -34.914 -6.952 2.887 1.00 0.00 H \\\\nATOM 6409 HG13 VAL C 145 -33.589 -7.698 2.447 1.00 0.00 H \\\\nATOM 6410 HG21 VAL C 145 -34.681 -10.492 2.637 1.00 0.00 H \\\\nATOM 6411 HG22 VAL C 145 -33.263 -10.169 3.265 1.00 0.00 H \\\\nATOM 6412 HG23 VAL C 145 -34.403 -10.800 4.165 1.00 0.00 H \\\\nATOM 6413 N ILE C 146 -33.865 -5.912 5.590 1.00 0.00 N \\\\nATOM 6414 CA ILE C 146 -34.368 -4.617 6.036 1.00 0.00 C \\\\nATOM 6415 C ILE C 146 -34.240 -3.584 4.920 1.00 0.00 C \\\\nATOM 6416 O ILE C 146 -33.132 -3.196 4.550 1.00 0.00 O \\\\nATOM 6417 CB ILE C 146 -33.613 -4.115 7.281 1.00 0.00 C \\\\nATOM 6418 CG1 ILE C 146 -33.592 -5.196 8.364 1.00 0.00 C \\\\nATOM 6419 CG2 ILE C 146 -34.248 -2.838 7.809 1.00 0.00 C \\\\nATOM 6420 CD1 ILE C 146 -32.817 -4.804 9.602 1.00 0.00 C \\\\nATOM 6421 H ILE C 146 -33.039 -5.908 5.350 1.00 0.00 H \\\\nATOM 6422 HA ILE C 146 -35.302 -4.734 6.268 1.00 0.00 H \\\\nATOM 6423 HB ILE C 146 -32.697 -3.918 7.029 1.00 0.00 H \\\\nATOM 6424 HG12 ILE C 146 -34.504 -5.406 8.617 1.00 0.00 H \\\\nATOM 6425 HG13 ILE C 146 -33.206 -6.005 7.994 1.00 0.00 H \\\\nATOM 6426 HG21 ILE C 146 -33.762 -2.535 8.592 1.00 0.00 H \\\\nATOM 6427 HG22 ILE C 146 -34.216 -2.153 7.123 1.00 0.00 H \\\\nATOM 6428 HG23 ILE C 146 -35.172 -3.011 8.049 1.00 0.00 H \\\\nATOM 6429 HD11 ILE C 146 -32.844 -5.530 10.244 1.00 0.00 H \\\\nATOM 6430 HD12 ILE C 146 -31.896 -4.619 9.362 1.00 0.00 H \\\\nATOM 6431 HD13 ILE C 146 -33.214 -4.011 9.995 1.00 0.00 H \\\\nATOM 6432 N ASP C 147 -35.375 -3.143 4.385 1.00 0.00 N \\\\nATOM 6433 CA ASP C 147 -35.374 -2.180 3.327 1.00 0.00 C \\\\nATOM 6434 C ASP C 147 -34.749 -2.757 2.070 1.00 0.00 C \\\\nATOM 6435 O ASP C 147 -34.106 -2.091 1.372 1.00 0.00 O \\\\nATOM 6436 CB ASP C 147 -34.631 -0.939 3.759 1.00 0.00 C \\\\nATOM 6437 CG ASP C 147 -35.247 -0.276 4.945 1.00 0.00 C \\\\nATOM 6438 OD1 ASP C 147 -36.426 -0.457 5.166 1.00 0.00 O \\\\nATOM 6439 OD2 ASP C 147 -34.552 0.450 5.649 1.00 0.00 O \\\\nATOM 6440 H ASP C 147 -36.157 -3.401 4.633 1.00 0.00 H \\\\nATOM 6441 HA ASP C 147 -36.293 -1.945 3.126 1.00 0.00 H \\\\nATOM 6442 HB2 ASP C 147 -33.713 -1.173 3.966 1.00 0.00 H \\\\nATOM 6443 HB3 ASP C 147 -34.604 -0.310 3.021 1.00 0.00 H \\\\nATOM 6444 N GLY C 148 -34.941 -4.026 1.822 1.00 0.00 N \\\\nATOM 6445 CA GLY C 148 -34.362 -4.678 0.687 1.00 0.00 C \\\\nATOM 6446 C GLY C 148 -32.896 -4.996 0.765 1.00 0.00 C \\\\nATOM 6447 O GLY C 148 -32.394 -5.572 -0.133 1.00 0.00 O \\\\nATOM 6448 H GLY C 148 -35.420 -4.541 2.317 1.00 0.00 H \\\\nATOM 6449 HA2 GLY C 148 -34.844 -5.506 0.536 1.00 0.00 H \\\\nATOM 6450 HA3 GLY C 148 -34.509 -4.118 -0.091 1.00 0.00 H \\\\nATOM 6451 N ARG C 149 -32.219 -4.594 1.836 1.00 0.00 N \\\\nATOM 6452 CA ARG C 149 -30.785 -4.858 1.968 1.00 0.00 C \\\\nATOM 6453 C ARG C 149 -30.500 -5.853 3.087 1.00 0.00 C \\\\nATOM 6454 O ARG C 149 -31.394 -6.183 3.866 1.00 0.00 O \\\\nATOM 6455 CB ARG C 149 -30.021 -3.556 2.214 1.00 0.00 C \\\\nATOM 6456 CG ARG C 149 -30.540 -2.371 1.416 1.00 0.00 C \\\\nATOM 6457 CD ARG C 149 -29.522 -1.243 1.376 1.00 0.00 C \\\\nATOM 6458 NE ARG C 149 -29.981 -0.066 2.106 1.00 0.00 N \\\\nATOM 6459 CZ ARG C 149 -29.295 1.069 2.202 1.00 0.00 C \\\\nATOM 6460 NH1 ARG C 149 -28.113 1.183 1.612 1.00 0.00 N \\\\nATOM 6461 NH2 ARG C 149 -29.791 2.090 2.887 1.00 0.00 N \\\\nATOM 6462 H ARG C 149 -32.568 -4.168 2.497 1.00 0.00 H \\\\nATOM 6463 HA ARG C 149 -30.482 -5.250 1.134 1.00 0.00 H \\\\nATOM 6464 HB2 ARG C 149 -30.064 -3.341 3.159 1.00 0.00 H \\\\nATOM 6465 HB3 ARG C 149 -29.086 -3.695 1.997 1.00 0.00 H \\\\nATOM 6466 HG2 ARG C 149 -30.748 -2.654 0.512 1.00 0.00 H \\\\nATOM 6467 HG3 ARG C 149 -31.366 -2.050 1.810 1.00 0.00 H \\\\nATOM 6468 HD2 ARG C 149 -28.684 -1.551 1.755 1.00 0.00 H \\\\nATOM 6469 HD3 ARG C 149 -29.344 -1.001 0.454 1.00 0.00 H \\\\nATOM 6470 HE ARG C 149 -30.744 -0.109 2.500 1.00 0.00 H \\\\nATOM 6471 HH11 ARG C 149 -27.789 0.522 1.167 1.00 0.00 H \\\\nATOM 6472 HH12 ARG C 149 -27.670 1.918 1.675 1.00 0.00 H \\\\nATOM 6473 HH21 ARG C 149 -30.558 2.019 3.270 1.00 0.00 H \\\\nATOM 6474 HH22 ARG C 149 -29.346 2.823 2.948 1.00 0.00 H \\\\nATOM 6475 N PRO C 150 -29.261 -6.333 3.175 1.00 0.00 N \\\\nATOM 6476 CA PRO C 150 -28.930 -7.294 4.236 1.00 0.00 C \\\\nATOM 6477 C PRO C 150 -29.055 -6.709 5.650 1.00 0.00 C \\\\nATOM 6478 O PRO C 150 -28.461 -5.670 5.936 1.00 0.00 O \\\\nATOM 6479 CB PRO C 150 -27.470 -7.644 3.941 1.00 0.00 C \\\\nATOM 6480 CG PRO C 150 -27.330 -7.440 2.471 1.00 0.00 C \\\\nATOM 6481 CD PRO C 150 -28.222 -6.278 2.131 1.00 0.00 C \\\\nATOM 6482 HA PRO C 150 -29.537 -8.050 4.230 1.00 0.00 H \\\\nATOM 6483 HB2 PRO C 150 -26.862 -7.073 4.437 1.00 0.00 H \\\\nATOM 6484 HB3 PRO C 150 -27.268 -8.559 4.192 1.00 0.00 H \\\\nATOM 6485 HG2 PRO C 150 -26.409 -7.253 2.232 1.00 0.00 H \\\\nATOM 6486 HG3 PRO C 150 -27.594 -8.236 1.983 1.00 0.00 H \\\\nATOM 6487 HD2 PRO C 150 -27.738 -5.437 2.151 1.00 0.00 H \\\\nATOM 6488 HD3 PRO C 150 -28.602 -6.366 1.243 1.00 0.00 H \\\\nATOM 6489 N GLY C 151 -29.832 -7.352 6.519 1.00 0.00 N \\\\nATOM 6490 CA GLY C 151 -30.024 -6.852 7.874 1.00 0.00 C \\\\nATOM 6491 C GLY C 151 -29.726 -7.850 8.977 1.00 0.00 C \\\\nATOM 6492 O GLY C 151 -29.177 -8.921 8.716 1.00 0.00 O \\\\nATOM 6493 H GLY C 151 -30.256 -8.079 6.342 1.00 0.00 H \\\\nATOM 6494 HA2 GLY C 151 -29.459 -6.074 8.000 1.00 0.00 H \\\\nATOM 6495 HA3 GLY C 151 -30.942 -6.553 7.967 1.00 0.00 H \\\\nATOM 6496 N THR C 152 -30.083 -7.506 10.215 1.00 0.00 N \\\\nATOM 6497 CA THR C 152 -29.830 -8.405 11.335 1.00 0.00 C \\\\nATOM 6498 C THR C 152 -30.815 -8.114 12.454 1.00 0.00 C \\\\nATOM 6499 O THR C 152 -31.065 -6.948 12.764 1.00 0.00 O \\\\nATOM 6500 CB THR C 152 -28.394 -8.256 11.849 1.00 0.00 C \\\\nATOM 6501 OG1 THR C 152 -27.471 -8.518 10.786 1.00 0.00 O \\\\nATOM 6502 CG2 THR C 152 -28.127 -9.219 13.000 1.00 0.00 C \\\\nATOM 6503 H THR C 152 -30.468 -6.766 10.424 1.00 0.00 H \\\\nATOM 6504 HA THR C 152 -29.946 -9.318 11.028 1.00 0.00 H \\\\nATOM 6505 HB THR C 152 -28.277 -7.348 12.170 1.00 0.00 H \\\\nATOM 6506 HG1 THR C 152 -27.387 -7.830 10.312 1.00 0.00 H \\\\nATOM 6507 HG21 THR C 152 -27.214 -9.108 13.310 1.00 0.00 H \\\\nATOM 6508 HG22 THR C 152 -28.740 -9.031 13.728 1.00 0.00 H \\\\nATOM 6509 HG23 THR C 152 -28.256 -10.131 12.696 1.00 0.00 H \\\\nATOM 6510 N LEU C 153 -31.377 -9.164 13.048 1.00 0.00 N \\\\nATOM 6511 CA LEU C 153 -32.129 -9.045 14.291 1.00 0.00 C \\\\nATOM 6512 C LEU C 153 -31.279 -9.600 15.426 1.00 0.00 C \\\\nATOM 6513 O LEU C 153 -30.871 -10.766 15.388 1.00 0.00 O \\\\nATOM 6514 CB LEU C 153 -33.466 -9.783 14.215 1.00 0.00 C \\\\nATOM 6515 CG LEU C 153 -34.263 -9.760 15.524 1.00 0.00 C \\\\nATOM 6516 CD1 LEU C 153 -34.642 -8.331 15.892 1.00 0.00 C \\\\nATOM 6517 CD2 LEU C 153 -35.503 -10.645 15.440 1.00 0.00 C \\\\nATOM 6518 H LEU C 153 -31.332 -9.966 12.740 1.00 0.00 H \\\\nATOM 6519 HA LEU C 153 -32.330 -8.109 14.449 1.00 0.00 H \\\\nATOM 6520 HB2 LEU C 153 -34.004 -9.387 13.512 1.00 0.00 H \\\\nATOM 6521 HB3 LEU C 153 -33.303 -10.705 13.962 1.00 0.00 H \\\\nATOM 6522 HG LEU C 153 -33.695 -10.119 16.224 1.00 0.00 H \\\\nATOM 6523 HD11 LEU C 153 -35.145 -8.333 16.721 1.00 0.00 H \\\\nATOM 6524 HD12 LEU C 153 -33.837 -7.801 16.004 1.00 0.00 H \\\\nATOM 6525 HD13 LEU C 153 -35.185 -7.948 15.186 1.00 0.00 H \\\\nATOM 6526 HD21 LEU C 153 -35.984 -10.609 16.281 1.00 0.00 H \\\\nATOM 6527 HD22 LEU C 153 -36.078 -10.330 14.725 1.00 0.00 H \\\\nATOM 6528 HD23 LEU C 153 -35.236 -11.560 15.260 1.00 0.00 H \\\\nATOM 6529 N VAL C 154 -31.018 -8.769 16.431 1.00 0.00 N \\\\nATOM 6530 CA VAL C 154 -30.292 -9.171 17.629 1.00 0.00 C \\\\nATOM 6531 C VAL C 154 -31.280 -9.229 18.783 1.00 0.00 C \\\\nATOM 6532 O VAL C 154 -32.026 -8.272 19.016 1.00 0.00 O \\\\nATOM 6533 CB VAL C 154 -29.137 -8.204 17.940 1.00 0.00 C \\\\nATOM 6534 CG1 VAL C 154 -28.380 -8.657 19.178 1.00 0.00 C \\\\nATOM 6535 CG2 VAL C 154 -28.206 -8.088 16.746 1.00 0.00 C \\\\nATOM 6536 H VAL C 154 -31.262 -7.944 16.435 1.00 0.00 H \\\\nATOM 6537 HA VAL C 154 -29.892 -10.044 17.489 1.00 0.00 H \\\\nATOM 6538 HB VAL C 154 -29.509 -7.326 18.120 1.00 0.00 H \\\\nATOM 6539 HG11 VAL C 154 -27.656 -8.037 19.360 1.00 0.00 H \\\\nATOM 6540 HG12 VAL C 154 -28.984 -8.680 19.937 1.00 0.00 H \\\\nATOM 6541 HG13 VAL C 154 -28.016 -9.544 19.029 1.00 0.00 H \\\\nATOM 6542 HG21 VAL C 154 -27.484 -7.476 16.957 1.00 0.00 H \\\\nATOM 6543 HG22 VAL C 154 -27.839 -8.961 16.536 1.00 0.00 H \\\\nATOM 6544 HG23 VAL C 154 -28.700 -7.753 15.981 1.00 0.00 H \\\\nATOM 6545 N ILE C 155 -31.279 -10.345 19.505 1.00 0.00 N \\\\nATOM 6546 CA ILE C 155 -32.129 -10.536 20.673 1.00 0.00 C \\\\nATOM 6547 C ILE C 155 -31.240 -10.900 21.849 1.00 0.00 C \\\\nATOM 6548 O ILE C 155 -30.405 -11.805 21.745 1.00 0.00 O \\\\nATOM 6549 CB ILE C 155 -33.189 -11.629 20.442 1.00 0.00 C \\\\nATOM 6550 CG1 ILE C 155 -33.980 -11.358 19.159 1.00 0.00 C \\\\nATOM 6551 CG2 ILE C 155 -34.125 -11.727 21.641 1.00 0.00 C \\\\nATOM 6552 CD1 ILE C 155 -34.942 -12.468 18.796 1.00 0.00 C \\\\nATOM 6553 H ILE C 155 -30.778 -11.021 19.327 1.00 0.00 H \\\\nATOM 6554 HA ILE C 155 -32.612 -9.714 20.851 1.00 0.00 H \\\\nATOM 6555 HB ILE C 155 -32.732 -12.479 20.340 1.00 0.00 H \\\\nATOM 6556 HG12 ILE C 155 -34.476 -10.531 19.262 1.00 0.00 H \\\\nATOM 6557 HG13 ILE C 155 -33.358 -11.226 18.426 1.00 0.00 H \\\\nATOM 6558 HG21 ILE C 155 -34.786 -12.419 21.480 1.00 0.00 H \\\\nATOM 6559 HG22 ILE C 155 -33.613 -11.948 22.434 1.00 0.00 H \\\\nATOM 6560 HG23 ILE C 155 -34.573 -10.877 21.772 1.00 0.00 H \\\\nATOM 6561 HD11 ILE C 155 -35.410 -12.237 17.978 1.00 0.00 H \\\\nATOM 6562 HD12 ILE C 155 -34.449 -13.293 18.664 1.00 0.00 H \\\\nATOM 6563 HD13 ILE C 155 -35.585 -12.587 19.513 1.00 0.00 H \\\\nATOM 6564 N GLU C 156 -31.415 -10.192 22.961 1.00 0.00 N \\\\nATOM 6565 CA GLU C 156 -30.716 -10.507 24.199 1.00 0.00 C \\\\nATOM 6566 C GLU C 156 -31.754 -10.658 25.297 1.00 0.00 C \\\\nATOM 6567 O GLU C 156 -32.485 -9.708 25.598 1.00 0.00 O \\\\nATOM 6568 CB GLU C 156 -29.694 -9.423 24.561 1.00 0.00 C \\\\nATOM 6569 CG GLU C 156 -28.768 -9.810 25.705 1.00 0.00 C \\\\nATOM 6570 CD GLU C 156 -27.577 -8.881 25.836 1.00 0.00 C \\\\nATOM 6571 OE1 GLU C 156 -27.680 -7.714 25.403 1.00 0.00 O \\\\nATOM 6572 OE2 GLU C 156 -26.534 -9.316 26.373 1.00 0.00 O \\\\nATOM 6573 H GLU C 156 -31.943 -9.515 23.017 1.00 0.00 H \\\\nATOM 6574 HA GLU C 156 -30.218 -11.332 24.090 1.00 0.00 H \\\\nATOM 6575 HB2 GLU C 156 -29.159 -9.220 23.778 1.00 0.00 H \\\\nATOM 6576 HB3 GLU C 156 -30.167 -8.611 24.800 1.00 0.00 H \\\\nATOM 6577 HG2 GLU C 156 -29.268 -9.807 26.536 1.00 0.00 H \\\\nATOM 6578 HG3 GLU C 156 -28.452 -10.717 25.567 1.00 0.00 H \\\\nATOM 6579 N SER C 157 -31.814 -11.846 25.889 1.00 0.00 N \\\\nATOM 6580 CA SER C 157 -32.703 -12.125 27.002 1.00 0.00 C \\\\nATOM 6581 C SER C 157 -31.865 -12.489 28.218 1.00 0.00 C \\\\nATOM 6582 O SER C 157 -30.675 -12.791 28.106 1.00 0.00 O \\\\nATOM 6583 CB SER C 157 -33.684 -13.258 26.669 1.00 0.00 C \\\\nATOM 6584 OG SER C 157 -32.998 -14.471 26.414 1.00 0.00 O \\\\nATOM 6585 H SER C 157 -31.333 -12.518 25.651 1.00 0.00 H \\\\nATOM 6586 HA SER C 157 -33.232 -11.333 27.188 1.00 0.00 H \\\\nATOM 6587 HB2 SER C 157 -34.302 -13.382 27.407 1.00 0.00 H \\\\nATOM 6588 HB3 SER C 157 -34.213 -13.014 25.894 1.00 0.00 H \\\\nATOM 6589 HG SER C 157 -32.172 -14.322 26.370 1.00 0.00 H \\\\nATOM 6590 N PHE C 158 -32.496 -12.459 29.388 1.00 0.00 N \\\\nATOM 6591 CA PHE C 158 -31.747 -12.645 30.621 1.00 0.00 C \\\\nATOM 6592 C PHE C 158 -32.662 -13.162 31.721 1.00 0.00 C \\\\nATOM 6593 O PHE C 158 -33.887 -13.025 31.658 1.00 0.00 O \\\\nATOM 6594 CB PHE C 158 -31.077 -11.339 31.064 1.00 0.00 C \\\\nATOM 6595 CG PHE C 158 -32.051 -10.241 31.383 1.00 0.00 C \\\\nATOM 6596 CD1 PHE C 158 -32.472 -9.362 30.399 1.00 0.00 C \\\\nATOM 6597 CD2 PHE C 158 -32.545 -10.085 32.668 1.00 0.00 C \\\\nATOM 6598 CE1 PHE C 158 -33.370 -8.353 30.688 1.00 0.00 C \\\\nATOM 6599 CE2 PHE C 158 -33.442 -9.079 32.965 1.00 0.00 C \\\\nATOM 6600 CZ PHE C 158 -33.855 -8.213 31.975 1.00 0.00 C \\\\nATOM 6601 H PHE C 158 -33.341 -12.335 29.487 1.00 0.00 H \\\\nATOM 6602 HA PHE C 158 -31.052 -13.300 30.453 1.00 0.00 H \\\\nATOM 6603 HB2 PHE C 158 -30.531 -11.514 31.846 1.00 0.00 H \\\\nATOM 6604 HB3 PHE C 158 -30.479 -11.037 30.362 1.00 0.00 H \\\\nATOM 6605 HD1 PHE C 158 -32.146 -9.452 29.533 1.00 0.00 H \\\\nATOM 6606 HD2 PHE C 158 -32.268 -10.666 33.339 1.00 0.00 H \\\\nATOM 6607 HE1 PHE C 158 -33.647 -7.770 30.019 1.00 0.00 H \\\\nATOM 6608 HE2 PHE C 158 -33.767 -8.985 33.831 1.00 0.00 H \\\\nATOM 6609 HZ PHE C 158 -34.460 -7.535 32.173 1.00 0.00 H \\\\nATOM 6610 N VAL C 159 -32.036 -13.765 32.730 1.00 0.00 N \\\\nATOM 6611 CA VAL C 159 -32.665 -14.085 34.004 1.00 0.00 C \\\\nATOM 6612 C VAL C 159 -31.723 -13.632 35.107 1.00 0.00 C \\\\nATOM 6613 O VAL C 159 -30.501 -13.774 34.983 1.00 0.00 O \\\\nATOM 6614 CB VAL C 159 -32.972 -15.589 34.151 1.00 0.00 C \\\\nATOM 6615 CG1 VAL C 159 -34.241 -15.936 33.427 1.00 0.00 C \\\\nATOM 6616 CG2 VAL C 159 -31.814 -16.423 33.629 1.00 0.00 C \\\\nATOM 6617 H VAL C 159 -31.211 -14.005 32.689 1.00 0.00 H \\\\nATOM 6618 HA VAL C 159 -33.518 -13.627 34.058 1.00 0.00 H \\\\nATOM 6619 HB VAL C 159 -33.091 -15.789 35.093 1.00 0.00 H \\\\nATOM 6620 HG11 VAL C 159 -34.422 -16.884 33.527 1.00 0.00 H \\\\nATOM 6621 HG12 VAL C 159 -34.977 -15.425 33.800 1.00 0.00 H \\\\nATOM 6622 HG13 VAL C 159 -34.145 -15.724 32.485 1.00 0.00 H \\\\nATOM 6623 HG21 VAL C 159 -32.023 -17.365 33.729 1.00 0.00 H \\\\nATOM 6624 HG22 VAL C 159 -31.667 -16.222 32.691 1.00 0.00 H \\\\nATOM 6625 HG23 VAL C 159 -31.012 -16.215 34.133 1.00 0.00 H \\\\nATOM 6626 N VAL C 160 -32.285 -13.089 36.183 1.00 0.00 N \\\\nATOM 6627 CA VAL C 160 -31.469 -12.563 37.270 1.00 0.00 C \\\\nATOM 6628 C VAL C 160 -32.305 -12.563 38.540 1.00 0.00 C \\\\nATOM 6629 O VAL C 160 -33.527 -12.397 38.498 1.00 0.00 O \\\\nATOM 6630 CB VAL C 160 -30.934 -11.149 36.924 1.00 0.00 C \\\\nATOM 6631 CG1 VAL C 160 -32.083 -10.168 36.738 1.00 0.00 C \\\\nATOM 6632 CG2 VAL C 160 -29.960 -10.657 37.986 1.00 0.00 C \\\\nATOM 6633 H VAL C 160 -33.134 -13.016 36.302 1.00 0.00 H \\\\nATOM 6634 HA VAL C 160 -30.690 -13.124 37.406 1.00 0.00 H \\\\nATOM 6635 HB VAL C 160 -30.451 -11.208 36.085 1.00 0.00 H \\\\nATOM 6636 HG11 VAL C 160 -31.728 -9.291 36.523 1.00 0.00 H \\\\nATOM 6637 HG12 VAL C 160 -32.654 -10.472 36.015 1.00 0.00 H \\\\nATOM 6638 HG13 VAL C 160 -32.599 -10.115 37.557 1.00 0.00 H \\\\nATOM 6639 HG21 VAL C 160 -29.640 -9.773 37.747 1.00 0.00 H \\\\nATOM 6640 HG22 VAL C 160 -30.410 -10.617 38.844 1.00 0.00 H \\\\nATOM 6641 HG23 VAL C 160 -29.208 -11.267 38.044 1.00 0.00 H \\\\nATOM 6642 N ASP C 161 -31.638 -12.751 39.677 1.00 0.00 N \\\\nATOM 6643 CA ASP C 161 -32.297 -12.612 40.966 1.00 0.00 C \\\\nATOM 6644 C ASP C 161 -32.691 -11.160 41.195 1.00 0.00 C \\\\nATOM 6645 O ASP C 161 -31.904 -10.242 40.947 1.00 0.00 O \\\\nATOM 6646 CB ASP C 161 -31.372 -13.076 42.094 1.00 0.00 C \\\\nATOM 6647 CG ASP C 161 -31.136 -14.571 42.084 1.00 0.00 C \\\\nATOM 6648 OD1 ASP C 161 -31.915 -15.300 41.440 1.00 0.00 O \\\\nATOM 6649 OD2 ASP C 161 -30.160 -15.023 42.719 1.00 0.00 O \\\\nATOM 6650 H ASP C 161 -30.805 -12.959 39.720 1.00 0.00 H \\\\nATOM 6651 HA ASP C 161 -33.093 -13.166 40.965 1.00 0.00 H \\\\nATOM 6652 HB2 ASP C 161 -30.520 -12.618 42.017 1.00 0.00 H \\\\nATOM 6653 HB3 ASP C 161 -31.756 -12.819 42.947 1.00 0.00 H \\\\nATOM 6654 N VAL C 162 -33.918 -10.953 41.660 1.00 0.00 N \\\\nATOM 6655 CA VAL C 162 -34.347 -9.621 42.071 1.00 0.00 C \\\\nATOM 6656 C VAL C 162 -33.700 -9.330 43.418 1.00 0.00 C \\\\nATOM 6657 O VAL C 162 -33.987 -10.032 44.398 1.00 0.00 O \\\\nATOM 6658 CB VAL C 162 -35.877 -9.520 42.157 1.00 0.00 C \\\\nATOM 6659 CG1 VAL C 162 -36.279 -8.181 42.743 1.00 0.00 C \\\\nATOM 6660 CG2 VAL C 162 -36.503 -9.719 40.789 1.00 0.00 C \\\\nATOM 6661 H VAL C 162 -34.515 -11.566 41.745 1.00 0.00 H \\\\nATOM 6662 HA VAL C 162 -34.070 -8.965 41.412 1.00 0.00 H \\\\nATOM 6663 HB VAL C 162 -36.203 -10.222 42.741 1.00 0.00 H \\\\nATOM 6664 HG11 VAL C 162 -37.246 -8.127 42.793 1.00 0.00 H \\\\nATOM 6665 HG12 VAL C 162 -35.904 -8.091 43.633 1.00 0.00 H \\\\nATOM 6666 HG13 VAL C 162 -35.944 -7.467 42.178 1.00 0.00 H \\\\nATOM 6667 HG21 VAL C 162 -37.468 -9.652 40.862 1.00 0.00 H \\\\nATOM 6668 HG22 VAL C 162 -36.177 -9.037 40.181 1.00 0.00 H \\\\nATOM 6669 HG23 VAL C 162 -36.265 -10.595 40.448 1.00 0.00 H \\\\nATOM 6670 N PRO C 163 -32.822 -8.336 43.525 1.00 0.00 N \\\\nATOM 6671 CA PRO C 163 -32.227 -8.041 44.830 1.00 0.00 C \\\\nATOM 6672 C PRO C 163 -33.275 -7.462 45.763 1.00 0.00 C \\\\nATOM 6673 O PRO C 163 -34.207 -6.778 45.335 1.00 0.00 O \\\\nATOM 6674 CB PRO C 163 -31.137 -7.016 44.504 1.00 0.00 C \\\\nATOM 6675 CG PRO C 163 -31.609 -6.352 43.256 1.00 0.00 C \\\\nATOM 6676 CD PRO C 163 -32.386 -7.391 42.481 1.00 0.00 C \\\\nATOM 6677 HA PRO C 163 -31.872 -8.823 45.281 1.00 0.00 H \\\\nATOM 6678 HB2 PRO C 163 -31.027 -6.376 45.225 1.00 0.00 H \\\\nATOM 6679 HB3 PRO C 163 -30.277 -7.445 44.372 1.00 0.00 H \\\\nATOM 6680 HG2 PRO C 163 -32.168 -5.587 43.463 1.00 0.00 H \\\\nATOM 6681 HG3 PRO C 163 -30.859 -6.023 42.736 1.00 0.00 H \\\\nATOM 6682 HD2 PRO C 163 -33.141 -6.999 42.015 1.00 0.00 H \\\\nATOM 6683 HD3 PRO C 163 -31.834 -7.826 41.812 1.00 0.00 H \\\\nATOM 6684 N GLU C 164 -33.113 -7.736 47.053 1.00 0.00 N \\\\nATOM 6685 CA GLU C 164 -34.132 -7.333 48.011 1.00 0.00 C \\\\nATOM 6686 C GLU C 164 -34.157 -5.818 48.146 1.00 0.00 C \\\\nATOM 6687 O GLU C 164 -33.114 -5.165 48.240 1.00 0.00 O \\\\nATOM 6688 CB GLU C 164 -33.915 -7.993 49.370 1.00 0.00 C \\\\nATOM 6689 CG GLU C 164 -35.153 -7.891 50.244 1.00 0.00 C \\\\nATOM 6690 CD GLU C 164 -35.385 -9.114 51.104 1.00 0.00 C \\\\nATOM 6691 OE1 GLU C 164 -36.206 -9.970 50.708 1.00 0.00 O \\\\nATOM 6692 OE2 GLU C 164 -34.762 -9.211 52.180 1.00 0.00 O \\\\nATOM 6693 H GLU C 164 -32.435 -8.146 47.388 1.00 0.00 H \\\\nATOM 6694 HA GLU C 164 -34.992 -7.632 47.677 1.00 0.00 H \\\\nATOM 6695 HB2 GLU C 164 -33.683 -8.926 49.244 1.00 0.00 H \\\\nATOM 6696 HB3 GLU C 164 -33.165 -7.572 49.819 1.00 0.00 H \\\\nATOM 6697 HG2 GLU C 164 -35.073 -7.112 50.816 1.00 0.00 H \\\\nATOM 6698 HG3 GLU C 164 -35.929 -7.749 49.679 1.00 0.00 H \\\\nATOM 6699 N GLY C 165 -35.363 -5.264 48.154 1.00 0.00 N \\\\nATOM 6700 CA GLY C 165 -35.571 -3.836 48.130 1.00 0.00 C \\\\nATOM 6701 C GLY C 165 -35.934 -3.292 46.768 1.00 0.00 C \\\\nATOM 6702 O GLY C 165 -36.198 -2.090 46.649 1.00 0.00 O \\\\nATOM 6703 H GLY C 165 -36.092 -5.720 48.174 1.00 0.00 H \\\\nATOM 6704 HA2 GLY C 165 -36.276 -3.610 48.757 1.00 0.00 H \\\\nATOM 6705 HA3 GLY C 165 -34.764 -3.395 48.440 1.00 0.00 H \\\\nATOM 6706 N ASN C 166 -35.956 -4.139 45.739 1.00 0.00 N \\\\nATOM 6707 CA ASN C 166 -36.349 -3.747 44.396 1.00 0.00 C \\\\nATOM 6708 C ASN C 166 -37.445 -4.688 43.912 1.00 0.00 C \\\\nATOM 6709 O ASN C 166 -37.570 -5.820 44.383 1.00 0.00 O \\\\nATOM 6710 CB ASN C 166 -35.161 -3.784 43.424 1.00 0.00 C \\\\nATOM 6711 CG ASN C 166 -34.175 -2.655 43.663 1.00 0.00 C \\\\nATOM 6712 OD1 ASN C 166 -33.025 -2.889 44.035 1.00 0.00 O \\\\nATOM 6713 ND2 ASN C 166 -34.624 -1.423 43.456 1.00 0.00 N \\\\nATOM 6714 H ASN C 166 -35.739 -4.968 45.807 1.00 0.00 H \\\\nATOM 6715 HA ASN C 166 -36.674 -2.834 44.423 1.00 0.00 H \\\\nATOM 6716 HB2 ASN C 166 -34.702 -4.634 43.512 1.00 0.00 H \\\\nATOM 6717 HB3 ASN C 166 -35.491 -3.733 42.513 1.00 0.00 H \\\\nATOM 6718 HD21 ASN C 166 -34.105 -0.749 43.582 1.00 0.00 H \\\\nATOM 6719 HD22 ASN C 166 -35.434 -1.299 43.196 1.00 0.00 H \\\\nATOM 6720 N THR C 167 -38.244 -4.209 42.965 1.00 0.00 N \\\\nATOM 6721 CA THR C 167 -39.299 -5.006 42.357 1.00 0.00 C \\\\nATOM 6722 C THR C 167 -38.803 -5.661 41.069 1.00 0.00 C \\\\nATOM 6723 O THR C 167 -37.751 -5.313 40.528 1.00 0.00 O \\\\nATOM 6724 CB THR C 167 -40.540 -4.149 42.088 1.00 0.00 C \\\\nATOM 6725 OG1 THR C 167 -40.233 -3.155 41.098 1.00 0.00 O \\\\nATOM 6726 CG2 THR C 167 -41.001 -3.463 43.375 1.00 0.00 C \\\\nATOM 6727 H THR C 167 -38.188 -3.408 42.656 1.00 0.00 H \\\\nATOM 6728 HA THR C 167 -39.547 -5.708 42.979 1.00 0.00 H \\\\nATOM 6729 HB THR C 167 -41.253 -4.722 41.765 1.00 0.00 H \\\\nATOM 6730 HG1 THR C 167 -39.544 -2.733 41.328 1.00 0.00 H \\\\nATOM 6731 HG21 THR C 167 -41.786 -2.924 43.191 1.00 0.00 H \\\\nATOM 6732 HG22 THR C 167 -41.219 -4.135 44.040 1.00 0.00 H \\\\nATOM 6733 HG23 THR C 167 -40.291 -2.894 43.711 1.00 0.00 H \\\\nATOM 6734 N LYS C 168 -39.581 -6.633 40.584 1.00 0.00 N \\\\nATOM 6735 CA LYS C 168 -39.328 -7.192 39.258 1.00 0.00 C \\\\nATOM 6736 C LYS C 168 -39.429 -6.126 38.175 1.00 0.00 C \\\\nATOM 6737 O LYS C 168 -38.649 -6.133 37.214 1.00 0.00 O \\\\nATOM 6738 CB LYS C 168 -40.302 -8.335 38.973 1.00 0.00 C \\\\nATOM 6739 CG LYS C 168 -40.227 -9.473 39.970 1.00 0.00 C \\\\nATOM 6740 CD LYS C 168 -41.053 -10.663 39.508 1.00 0.00 C \\\\nATOM 6741 CE LYS C 168 -41.082 -11.749 40.571 1.00 0.00 C \\\\nATOM 6742 NZ LYS C 168 -41.793 -12.966 40.098 1.00 0.00 N \\\\nATOM 6743 H LYS C 168 -40.250 -6.977 41.001 1.00 0.00 H \\\\nATOM 6744 HA LYS C 168 -38.422 -7.538 39.248 1.00 0.00 H \\\\nATOM 6745 HB2 LYS C 168 -41.206 -7.983 38.966 1.00 0.00 H \\\\nATOM 6746 HB3 LYS C 168 -40.126 -8.683 38.085 1.00 0.00 H \\\\nATOM 6747 HG2 LYS C 168 -39.303 -9.743 40.087 1.00 0.00 H \\\\nATOM 6748 HG3 LYS C 168 -40.546 -9.171 40.835 1.00 0.00 H \\\\nATOM 6749 HD2 LYS C 168 -41.958 -10.376 39.309 1.00 0.00 H \\\\nATOM 6750 HD3 LYS C 168 -40.682 -11.020 38.686 1.00 0.00 H \\\\nATOM 6751 HE2 LYS C 168 -40.174 -11.981 40.821 1.00 0.00 H \\\\nATOM 6752 HE3 LYS C 168 -41.517 -11.409 41.368 1.00 0.00 H \\\\nATOM 6753 HZ1 LYS C 168 -41.394 -13.690 40.428 1.00 0.00 H \\\\nATOM 6754 HZ2 LYS C 168 -42.639 -12.942 40.374 1.00 0.00 H \\\\nATOM 6755 HZ3 LYS C 168 -41.772 -12.996 39.209 1.00 0.00 H \\\\nATOM 6756 N ASP C 169 -40.389 -5.207 38.305 1.00 0.00 N \\\\nATOM 6757 CA ASP C 169 -40.558 -4.183 37.283 1.00 0.00 C \\\\nATOM 6758 C ASP C 169 -39.383 -3.216 37.276 1.00 0.00 C \\\\nATOM 6759 O ASP C 169 -39.013 -2.700 36.216 1.00 0.00 O \\\\nATOM 6760 CB ASP C 169 -41.868 -3.429 37.507 1.00 0.00 C \\\\nATOM 6761 CG ASP C 169 -43.080 -4.208 37.033 1.00 0.00 C \\\\nATOM 6762 OD1 ASP C 169 -42.912 -5.139 36.219 1.00 0.00 O \\\\nATOM 6763 OD2 ASP C 169 -44.205 -3.886 37.476 1.00 0.00 O \\\\nATOM 6764 H ASP C 169 -40.940 -5.162 38.964 1.00 0.00 H \\\\nATOM 6765 HA ASP C 169 -40.590 -4.620 36.418 1.00 0.00 H \\\\nATOM 6766 HB2 ASP C 169 -41.965 -3.230 38.451 1.00 0.00 H \\\\nATOM 6767 HB3 ASP C 169 -41.832 -2.579 37.041 1.00 0.00 H \\\\nATOM 6768 N GLU C 170 -38.787 -2.961 38.443 1.00 0.00 N \\\\nATOM 6769 CA GLU C 170 -37.620 -2.088 38.503 1.00 0.00 C \\\\nATOM 6770 C GLU C 170 -36.387 -2.778 37.936 1.00 0.00 C \\\\nATOM 6771 O GLU C 170 -35.626 -2.172 37.172 1.00 0.00 O \\\\nATOM 6772 CB GLU C 170 -37.361 -1.658 39.946 1.00 0.00 C \\\\nATOM 6773 CG GLU C 170 -38.317 -0.610 40.477 1.00 0.00 C \\\\nATOM 6774 CD GLU C 170 -38.133 -0.387 41.966 1.00 0.00 C \\\\nATOM 6775 OE1 GLU C 170 -37.804 -1.364 42.671 1.00 0.00 O \\\\nATOM 6776 OE2 GLU C 170 -38.308 0.761 42.425 1.00 0.00 O \\\\nATOM 6777 H GLU C 170 -39.041 -3.280 39.200 1.00 0.00 H \\\\nATOM 6778 HA GLU C 170 -37.803 -1.304 37.962 1.00 0.00 H \\\\nATOM 6779 HB2 GLU C 170 -37.409 -2.441 40.517 1.00 0.00 H \\\\nATOM 6780 HB3 GLU C 170 -36.456 -1.315 40.011 1.00 0.00 H \\\\nATOM 6781 HG2 GLU C 170 -38.177 0.225 40.005 1.00 0.00 H \\\\nATOM 6782 HG3 GLU C 170 -39.230 -0.886 40.301 1.00 0.00 H \\\\nATOM 6783 N THR C 171 -36.170 -4.043 38.306 1.00 0.00 N \\\\nATOM 6784 CA THR C 171 -34.983 -4.759 37.851 1.00 0.00 C \\\\nATOM 6785 C THR C 171 -34.995 -4.951 36.339 1.00 0.00 C \\\\nATOM 6786 O THR C 171 -33.971 -4.756 35.673 1.00 0.00 O \\\\nATOM 6787 CB THR C 171 -34.875 -6.108 38.562 1.00 0.00 C \\\\nATOM 6788 OG1 THR C 171 -34.858 -5.904 39.981 1.00 0.00 O \\\\nATOM 6789 CG2 THR C 171 -33.597 -6.819 38.151 1.00 0.00 C \\\\nATOM 6790 H THR C 171 -36.694 -4.498 38.815 1.00 0.00 H \\\\nATOM 6791 HA THR C 171 -34.206 -4.223 38.074 1.00 0.00 H \\\\nATOM 6792 HB THR C 171 -35.639 -6.652 38.314 1.00 0.00 H \\\\nATOM 6793 HG1 THR C 171 -34.677 -6.628 40.366 1.00 0.00 H \\\\nATOM 6794 HG21 THR C 171 -33.540 -7.673 38.608 1.00 0.00 H \\\\nATOM 6795 HG22 THR C 171 -33.602 -6.966 37.192 1.00 0.00 H \\\\nATOM 6796 HG23 THR C 171 -32.832 -6.273 38.390 1.00 0.00 H \\\\nATOM 6797 N CYS C 172 -36.142 -5.345 35.780 1.00 0.00 N \\\\nATOM 6798 CA CYS C 172 -36.248 -5.494 34.332 1.00 0.00 C \\\\nATOM 6799 C CYS C 172 -36.035 -4.162 33.624 1.00 0.00 C \\\\nATOM 6800 O CYS C 172 -35.287 -4.079 32.643 1.00 0.00 O \\\\nATOM 6801 CB CYS C 172 -37.611 -6.084 33.965 1.00 0.00 C \\\\nATOM 6802 SG CYS C 172 -37.791 -7.848 34.323 1.00 0.00 S \\\\nATOM 6803 H CYS C 172 -36.860 -5.528 36.217 1.00 0.00 H \\\\nATOM 6804 HA CYS C 172 -35.551 -6.101 34.037 1.00 0.00 H \\\\nATOM 6805 HB2 CYS C 172 -38.300 -5.597 34.444 1.00 0.00 H \\\\nATOM 6806 HB3 CYS C 172 -37.768 -5.941 33.019 1.00 0.00 H \\\\nATOM 6807 HG CYS C 172 -38.338 -7.988 35.382 1.00 0.00 H \\\\nATOM 6808 N TYR C 173 -36.684 -3.103 34.117 1.00 0.00 N \\\\nATOM 6809 CA TYR C 173 -36.546 -1.786 33.501 1.00 0.00 C \\\\nATOM 6810 C TYR C 173 -35.100 -1.308 33.530 1.00 0.00 C \\\\nATOM 6811 O TYR C 173 -34.626 -0.679 32.578 1.00 0.00 O \\\\nATOM 6812 CB TYR C 173 -37.454 -0.786 34.213 1.00 0.00 C \\\\nATOM 6813 CG TYR C 173 -37.586 0.554 33.526 1.00 0.00 C \\\\nATOM 6814 CD1 TYR C 173 -36.652 1.561 33.735 1.00 0.00 C \\\\nATOM 6815 CD2 TYR C 173 -38.650 0.815 32.674 1.00 0.00 C \\\\nATOM 6816 CE1 TYR C 173 -36.769 2.787 33.111 1.00 0.00 C \\\\nATOM 6817 CE2 TYR C 173 -38.779 2.039 32.049 1.00 0.00 C \\\\nATOM 6818 CZ TYR C 173 -37.838 3.020 32.269 1.00 0.00 C \\\\nATOM 6819 OH TYR C 173 -37.964 4.240 31.646 1.00 0.00 O \\\\nATOM 6820 H TYR C 173 -37.204 -3.128 34.802 1.00 0.00 H \\\\nATOM 6821 HA TYR C 173 -36.813 -1.855 32.571 1.00 0.00 H \\\\nATOM 6822 HB2 TYR C 173 -38.337 -1.177 34.303 1.00 0.00 H \\\\nATOM 6823 HB3 TYR C 173 -37.115 -0.643 35.110 1.00 0.00 H \\\\nATOM 6824 HD1 TYR C 173 -35.934 1.406 34.306 1.00 0.00 H \\\\nATOM 6825 HD2 TYR C 173 -39.287 0.154 32.522 1.00 0.00 H \\\\nATOM 6826 HE1 TYR C 173 -36.133 3.450 33.257 1.00 0.00 H \\\\nATOM 6827 HE2 TYR C 173 -39.498 2.200 31.482 1.00 0.00 H \\\\nATOM 6828 HH TYR C 173 -38.134 4.831 32.218 1.00 0.00 H \\\\nATOM 6829 N PHE C 174 -34.385 -1.595 34.616 1.00 0.00 N \\\\nATOM 6830 CA PHE C 174 -32.997 -1.162 34.732 1.00 0.00 C \\\\nATOM 6831 C PHE C 174 -32.101 -1.917 33.758 1.00 0.00 C \\\\nATOM 6832 O PHE C 174 -31.262 -1.314 33.078 1.00 0.00 O \\\\nATOM 6833 CB PHE C 174 -32.527 -1.343 36.177 1.00 0.00 C \\\\nATOM 6834 CG PHE C 174 -31.037 -1.294 36.355 1.00 0.00 C \\\\nATOM 6835 CD1 PHE C 174 -30.324 -0.142 36.066 1.00 0.00 C \\\\nATOM 6836 CD2 PHE C 174 -30.354 -2.396 36.837 1.00 0.00 C \\\\nATOM 6837 CE1 PHE C 174 -28.954 -0.098 36.241 1.00 0.00 C \\\\nATOM 6838 CE2 PHE C 174 -28.985 -2.359 37.014 1.00 0.00 C \\\\nATOM 6839 CZ PHE C 174 -28.283 -1.210 36.715 1.00 0.00 C \\\\nATOM 6840 H PHE C 174 -34.683 -2.036 35.291 1.00 0.00 H \\\\nATOM 6841 HA PHE C 174 -32.939 -0.222 34.499 1.00 0.00 H \\\\nATOM 6842 HB2 PHE C 174 -32.930 -0.652 36.726 1.00 0.00 H \\\\nATOM 6843 HB3 PHE C 174 -32.853 -2.194 36.508 1.00 0.00 H \\\\nATOM 6844 HD1 PHE C 174 -30.772 0.610 35.751 1.00 0.00 H \\\\nATOM 6845 HD2 PHE C 174 -30.823 -3.172 37.045 1.00 0.00 H \\\\nATOM 6846 HE1 PHE C 174 -28.484 0.679 36.040 1.00 0.00 H \\\\nATOM 6847 HE2 PHE C 174 -28.537 -3.108 37.335 1.00 0.00 H \\\\nATOM 6848 HZ PHE C 174 -27.361 -1.183 36.832 1.00 0.00 H \\\\nATOM 6849 N VAL C 175 -32.268 -3.239 33.673 1.00 0.00 N \\\\nATOM 6850 CA VAL C 175 -31.439 -4.035 32.773 1.00 0.00 C \\\\nATOM 6851 C VAL C 175 -31.790 -3.745 31.317 1.00 0.00 C \\\\nATOM 6852 O VAL C 175 -30.901 -3.616 30.465 1.00 0.00 O \\\\nATOM 6853 CB VAL C 175 -31.575 -5.533 33.103 1.00 0.00 C \\\\nATOM 6854 CG1 VAL C 175 -30.810 -6.366 32.086 1.00 0.00 C \\\\nATOM 6855 CG2 VAL C 175 -31.081 -5.818 34.515 1.00 0.00 C \\\\nATOM 6856 H VAL C 175 -32.848 -3.687 34.123 1.00 0.00 H \\\\nATOM 6857 HA VAL C 175 -30.510 -3.786 32.902 1.00 0.00 H \\\\nATOM 6858 HB VAL C 175 -32.513 -5.777 33.058 1.00 0.00 H \\\\nATOM 6859 HG11 VAL C 175 -30.902 -7.307 32.303 1.00 0.00 H \\\\nATOM 6860 HG12 VAL C 175 -31.167 -6.203 31.199 1.00 0.00 H \\\\nATOM 6861 HG13 VAL C 175 -29.872 -6.120 32.106 1.00 0.00 H \\\\nATOM 6862 HG21 VAL C 175 -31.174 -6.765 34.706 1.00 0.00 H \\\\nATOM 6863 HG22 VAL C 175 -30.148 -5.564 34.589 1.00 0.00 H \\\\nATOM 6864 HG23 VAL C 175 -31.606 -5.308 35.151 1.00 0.00 H \\\\nATOM 6865 N GLU C 176 -33.086 -3.654 31.005 1.00 0.00 N \\\\nATOM 6866 CA GLU C 176 -33.505 -3.391 29.631 1.00 0.00 C \\\\nATOM 6867 C GLU C 176 -32.959 -2.061 29.128 1.00 0.00 C \\\\nATOM 6868 O GLU C 176 -32.600 -1.936 27.953 1.00 0.00 O \\\\nATOM 6869 CB GLU C 176 -35.030 -3.414 29.530 1.00 0.00 C \\\\nATOM 6870 CG GLU C 176 -35.641 -4.803 29.608 1.00 0.00 C \\\\nATOM 6871 CD GLU C 176 -37.145 -4.763 29.797 1.00 0.00 C \\\\nATOM 6872 OE1 GLU C 176 -37.670 -5.579 30.584 1.00 0.00 O \\\\nATOM 6873 OE2 GLU C 176 -37.802 -3.913 29.161 1.00 0.00 O \\\\nATOM 6874 H GLU C 176 -33.729 -3.741 31.569 1.00 0.00 H \\\\nATOM 6875 HA GLU C 176 -33.141 -4.092 29.068 1.00 0.00 H \\\\nATOM 6876 HB2 GLU C 176 -35.399 -2.869 30.243 1.00 0.00 H \\\\nATOM 6877 HB3 GLU C 176 -35.294 -3.002 28.692 1.00 0.00 H \\\\nATOM 6878 HG2 GLU C 176 -35.432 -5.291 28.796 1.00 0.00 H \\\\nATOM 6879 HG3 GLU C 176 -35.238 -5.290 30.344 1.00 0.00 H \\\\nATOM 6880 N ALA C 177 -32.898 -1.052 29.999 1.00 0.00 N \\\\nATOM 6881 CA ALA C 177 -32.392 0.253 29.585 1.00 0.00 C \\\\nATOM 6882 C ALA C 177 -30.924 0.172 29.184 1.00 0.00 C \\\\nATOM 6883 O ALA C 177 -30.505 0.793 28.201 1.00 0.00 O \\\\nATOM 6884 CB ALA C 177 -32.590 1.274 30.706 1.00 0.00 C \\\\nATOM 6885 H ALA C 177 -33.141 -1.103 30.822 1.00 0.00 H \\\\nATOM 6886 HA ALA C 177 -32.895 0.541 28.807 1.00 0.00 H \\\\nATOM 6887 HB1 ALA C 177 -32.251 2.137 30.421 1.00 0.00 H \\\\nATOM 6888 HB2 ALA C 177 -33.535 1.350 30.911 1.00 0.00 H \\\\nATOM 6889 HB3 ALA C 177 -32.110 0.983 31.497 1.00 0.00 H \\\\nATOM 6890 N LEU C 178 -30.127 -0.586 29.939 1.00 0.00 N \\\\nATOM 6891 CA LEU C 178 -28.714 -0.733 29.609 1.00 0.00 C \\\\nATOM 6892 C LEU C 178 -28.524 -1.594 28.366 1.00 0.00 C \\\\nATOM 6893 O LEU C 178 -27.690 -1.278 27.508 1.00 0.00 O \\\\nATOM 6894 CB LEU C 178 -27.961 -1.324 30.800 1.00 0.00 C \\\\nATOM 6895 CG LEU C 178 -27.801 -0.382 31.996 1.00 0.00 C \\\\nATOM 6896 CD1 LEU C 178 -27.265 -1.131 33.206 1.00 0.00 C \\\\nATOM 6897 CD2 LEU C 178 -26.893 0.783 31.631 1.00 0.00 C \\\\nATOM 6898 H LEU C 178 -30.383 -1.017 30.637 1.00 0.00 H \\\\nATOM 6899 HA LEU C 178 -28.351 0.145 29.413 1.00 0.00 H \\\\nATOM 6900 HB2 LEU C 178 -28.425 -2.123 31.095 1.00 0.00 H \\\\nATOM 6901 HB3 LEU C 178 -27.080 -1.601 30.503 1.00 0.00 H \\\\nATOM 6902 HG LEU C 178 -28.674 -0.028 32.229 1.00 0.00 H \\\\nATOM 6903 HD11 LEU C 178 -27.171 -0.517 33.951 1.00 0.00 H \\\\nATOM 6904 HD12 LEU C 178 -27.882 -1.840 33.447 1.00 0.00 H \\\\nATOM 6905 HD13 LEU C 178 -26.400 -1.514 32.992 1.00 0.00 H \\\\nATOM 6906 HD21 LEU C 178 -26.799 1.372 32.396 1.00 0.00 H \\\\nATOM 6907 HD22 LEU C 178 -26.021 0.446 31.375 1.00 0.00 H \\\\nATOM 6908 HD23 LEU C 178 -27.280 1.275 30.890 1.00 0.00 H \\\\nATOM 6909 N LEU C 179 -29.287 -2.685 28.252 1.00 0.00 N \\\\nATOM 6910 CA LEU C 179 -29.205 -3.526 27.063 1.00 0.00 C \\\\nATOM 6911 C LEU C 179 -29.653 -2.770 25.818 1.00 0.00 C \\\\nATOM 6912 O LEU C 179 -29.054 -2.915 24.746 1.00 0.00 O \\\\nATOM 6913 CB LEU C 179 -30.039 -4.792 27.256 1.00 0.00 C \\\\nATOM 6914 CG LEU C 179 -29.595 -5.764 28.349 1.00 0.00 C \\\\nATOM 6915 CD1 LEU C 179 -30.460 -7.015 28.332 1.00 0.00 C \\\\nATOM 6916 CD2 LEU C 179 -28.127 -6.121 28.192 1.00 0.00 C \\\\nATOM 6917 H LEU C 179 -29.850 -2.950 28.845 1.00 0.00 H \\\\nATOM 6918 HA LEU C 179 -28.277 -3.779 26.934 1.00 0.00 H \\\\nATOM 6919 HB2 LEU C 179 -30.952 -4.524 27.445 1.00 0.00 H \\\\nATOM 6920 HB3 LEU C 179 -30.053 -5.273 26.414 1.00 0.00 H \\\\nATOM 6921 HG LEU C 179 -29.706 -5.327 29.208 1.00 0.00 H \\\\nATOM 6922 HD11 LEU C 179 -30.166 -7.621 29.030 1.00 0.00 H \\\\nATOM 6923 HD12 LEU C 179 -31.386 -6.770 28.485 1.00 0.00 H \\\\nATOM 6924 HD13 LEU C 179 -30.380 -7.452 27.470 1.00 0.00 H \\\\nATOM 6925 HD21 LEU C 179 -27.867 -6.737 28.894 1.00 0.00 H \\\\nATOM 6926 HD22 LEU C 179 -27.986 -6.538 27.328 1.00 0.00 H \\\\nATOM 6927 HD23 LEU C 179 -27.590 -5.316 28.254 1.00 0.00 H \\\\nATOM 6928 N LYS C 180 -30.712 -1.966 25.939 1.00 0.00 N \\\\nATOM 6929 CA LYS C 180 -31.209 -1.214 24.791 1.00 0.00 C \\\\nATOM 6930 C LYS C 180 -30.169 -0.217 24.293 1.00 0.00 C \\\\nATOM 6931 O LYS C 180 -29.986 -0.054 23.080 1.00 0.00 O \\\\nATOM 6932 CB LYS C 180 -32.508 -0.498 25.165 1.00 0.00 C \\\\nATOM 6933 CG LYS C 180 -33.217 0.194 24.015 1.00 0.00 C \\\\nATOM 6934 CD LYS C 180 -34.398 1.011 24.526 1.00 0.00 C \\\\nATOM 6935 CE LYS C 180 -35.381 1.329 23.411 1.00 0.00 C \\\\nATOM 6936 NZ LYS C 180 -36.796 1.207 23.865 1.00 0.00 N \\\\nATOM 6937 H LYS C 180 -31.150 -1.845 26.669 1.00 0.00 H \\\\nATOM 6938 HA LYS C 180 -31.387 -1.836 24.069 1.00 0.00 H \\\\nATOM 6939 HB2 LYS C 180 -33.115 -1.144 25.559 1.00 0.00 H \\\\nATOM 6940 HB3 LYS C 180 -32.312 0.161 25.849 1.00 0.00 H \\\\nATOM 6941 HG2 LYS C 180 -32.595 0.773 23.547 1.00 0.00 H \\\\nATOM 6942 HG3 LYS C 180 -33.527 -0.466 23.375 1.00 0.00 H \\\\nATOM 6943 HD2 LYS C 180 -34.852 0.520 25.229 1.00 0.00 H \\\\nATOM 6944 HD3 LYS C 180 -34.075 1.837 24.919 1.00 0.00 H \\\\nATOM 6945 HE2 LYS C 180 -35.222 2.230 23.087 1.00 0.00 H \\\\nATOM 6946 HE3 LYS C 180 -35.228 0.728 22.665 1.00 0.00 H \\\\nATOM 6947 HZ1 LYS C 180 -37.291 0.870 23.207 1.00 0.00 H \\\\nATOM 6948 HZ2 LYS C 180 -36.836 0.668 24.572 1.00 0.00 H \\\\nATOM 6949 HZ3 LYS C 180 -37.107 2.011 24.088 1.00 0.00 H \\\\nATOM 6950 N CYS C 181 -29.483 0.464 25.214 1.00 0.00 N \\\\nATOM 6951 CA CYS C 181 -28.412 1.373 24.820 1.00 0.00 C \\\\nATOM 6952 C CYS C 181 -27.251 0.632 24.166 1.00 0.00 C \\\\nATOM 6953 O CYS C 181 -26.619 1.163 23.244 1.00 0.00 O \\\\nATOM 6954 CB CYS C 181 -27.922 2.163 26.033 1.00 0.00 C \\\\nATOM 6955 SG CYS C 181 -26.492 3.223 25.706 1.00 0.00 S \\\\nATOM 6956 H CYS C 181 -29.622 0.413 26.061 1.00 0.00 H \\\\nATOM 6957 HA CYS C 181 -28.773 1.987 24.162 1.00 0.00 H \\\\nATOM 6958 HB2 CYS C 181 -28.650 2.713 26.363 1.00 0.00 H \\\\nATOM 6959 HB3 CYS C 181 -27.694 1.540 26.741 1.00 0.00 H \\\\nATOM 6960 HG CYS C 181 -26.627 4.267 26.282 1.00 0.00 H \\\\nATOM 6961 N ASN C 182 -26.959 -0.589 24.621 1.00 0.00 N \\\\nATOM 6962 CA ASN C 182 -25.855 -1.347 24.041 1.00 0.00 C \\\\nATOM 6963 C ASN C 182 -26.204 -1.872 22.655 1.00 0.00 C \\\\nATOM 6964 O ASN C 182 -25.344 -1.910 21.766 1.00 0.00 O \\\\nATOM 6965 CB ASN C 182 -25.468 -2.500 24.963 1.00 0.00 C \\\\nATOM 6966 CG ASN C 182 -24.480 -2.081 26.023 1.00 0.00 C \\\\nATOM 6967 OD1 ASN C 182 -23.894 -1.003 25.952 1.00 0.00 O \\\\nATOM 6968 ND2 ASN C 182 -24.281 -2.936 27.011 1.00 0.00 N \\\\nATOM 6969 H ASN C 182 -27.382 -0.989 25.254 1.00 0.00 H \\\\nATOM 6970 HA ASN C 182 -25.099 -0.747 23.947 1.00 0.00 H \\\\nATOM 6971 HB2 ASN C 182 -26.265 -2.852 25.389 1.00 0.00 H \\\\nATOM 6972 HB3 ASN C 182 -25.087 -3.219 24.435 1.00 0.00 H \\\\nATOM 6973 HD21 ASN C 182 -23.723 -2.747 27.637 1.00 0.00 H \\\\nATOM 6974 HD22 ASN C 182 -24.710 -3.681 27.027 1.00 0.00 H \\\\nATOM 6975 N LEU C 183 -27.456 -2.285 22.450 1.00 0.00 N \\\\nATOM 6976 CA LEU C 183 -27.859 -2.753 21.130 1.00 0.00 C \\\\nATOM 6977 C LEU C 183 -27.944 -1.601 20.139 1.00 0.00 C \\\\nATOM 6978 O LEU C 183 -27.620 -1.769 18.957 1.00 0.00 O \\\\nATOM 6979 CB LEU C 183 -29.186 -3.503 21.217 1.00 0.00 C \\\\nATOM 6980 CG LEU C 183 -29.117 -4.806 22.022 1.00 0.00 C \\\\nATOM 6981 CD1 LEU C 183 -30.411 -5.587 21.887 1.00 0.00 C \\\\nATOM 6982 CD2 LEU C 183 -27.929 -5.650 21.583 1.00 0.00 C \\\\nATOM 6983 H LEU C 183 -28.073 -2.301 23.049 1.00 0.00 H \\\\nATOM 6984 HA LEU C 183 -27.181 -3.366 20.804 1.00 0.00 H \\\\nATOM 6985 HB2 LEU C 183 -29.850 -2.921 21.619 1.00 0.00 H \\\\nATOM 6986 HB3 LEU C 183 -29.492 -3.705 20.319 1.00 0.00 H \\\\nATOM 6987 HG LEU C 183 -28.996 -4.579 22.957 1.00 0.00 H \\\\nATOM 6988 HD11 LEU C 183 -30.350 -6.407 22.402 1.00 0.00 H \\\\nATOM 6989 HD12 LEU C 183 -31.148 -5.052 22.219 1.00 0.00 H \\\\nATOM 6990 HD13 LEU C 183 -30.563 -5.803 20.954 1.00 0.00 H \\\\nATOM 6991 HD21 LEU C 183 -27.903 -6.468 22.103 1.00 0.00 H \\\\nATOM 6992 HD22 LEU C 183 -28.017 -5.868 20.642 1.00 0.00 H \\\\nATOM 6993 HD23 LEU C 183 -27.109 -5.152 21.724 1.00 0.00 H \\\\nATOM 6994 N LYS C 184 -28.385 -0.427 20.597 1.00 0.00 N \\\\nATOM 6995 CA LYS C 184 -28.406 0.737 19.717 1.00 0.00 C \\\\nATOM 6996 C LYS C 184 -26.994 1.141 19.311 1.00 0.00 C \\\\nATOM 6997 O LYS C 184 -26.760 1.565 18.171 1.00 0.00 O \\\\nATOM 6998 CB LYS C 184 -29.125 1.900 20.402 1.00 0.00 C \\\\nATOM 6999 CG LYS C 184 -28.930 3.245 19.719 1.00 0.00 C \\\\nATOM 7000 CD LYS C 184 -30.243 4.002 19.579 1.00 0.00 C \\\\nATOM 7001 CE LYS C 184 -30.989 4.088 20.903 1.00 0.00 C \\\\nATOM 7002 NZ LYS C 184 -32.361 4.641 20.723 1.00 0.00 N \\\\nATOM 7003 H LYS C 184 -28.670 -0.287 21.396 1.00 0.00 H \\\\nATOM 7004 HA LYS C 184 -28.890 0.502 18.910 1.00 0.00 H \\\\nATOM 7005 HB2 LYS C 184 -30.074 1.703 20.440 1.00 0.00 H \\\\nATOM 7006 HB3 LYS C 184 -28.812 1.966 21.318 1.00 0.00 H \\\\nATOM 7007 HG2 LYS C 184 -28.301 3.779 20.229 1.00 0.00 H \\\\nATOM 7008 HG3 LYS C 184 -28.540 3.109 18.841 1.00 0.00 H \\\\nATOM 7009 HD2 LYS C 184 -30.067 4.897 19.248 1.00 0.00 H \\\\nATOM 7010 HD3 LYS C 184 -30.802 3.561 18.921 1.00 0.00 H \\\\nATOM 7011 HE2 LYS C 184 -31.045 3.206 21.302 1.00 0.00 H \\\\nATOM 7012 HE3 LYS C 184 -30.492 4.648 21.520 1.00 0.00 H \\\\nATOM 7013 HZ1 LYS C 184 -32.905 4.290 21.334 1.00 0.00 H \\\\nATOM 7014 HZ2 LYS C 184 -32.340 5.526 20.819 1.00 0.00 H \\\\nATOM 7015 HZ3 LYS C 184 -32.659 4.438 19.909 1.00 0.00 H \\\\nATOM 7016 N SER C 185 -26.036 1.009 20.231 1.00 0.00 N \\\\nATOM 7017 CA SER C 185 -24.648 1.303 19.893 1.00 0.00 C \\\\nATOM 7018 C SER C 185 -24.064 0.232 18.980 1.00 0.00 C \\\\nATOM 7019 O SER C 185 -23.265 0.538 18.087 1.00 0.00 O \\\\nATOM 7020 CB SER C 185 -23.820 1.447 21.168 1.00 0.00 C \\\\nATOM 7021 OG SER C 185 -22.434 1.476 20.880 1.00 0.00 O \\\\nATOM 7022 H SER C 185 -26.168 0.755 21.042 1.00 0.00 H \\\\nATOM 7023 HA SER C 185 -24.621 2.143 19.408 1.00 0.00 H \\\\nATOM 7024 HB2 SER C 185 -24.074 2.261 21.631 1.00 0.00 H \\\\nATOM 7025 HB3 SER C 185 -24.013 0.709 21.767 1.00 0.00 H \\\\nATOM 7026 HG SER C 185 -22.009 1.119 21.510 1.00 0.00 H \\\\nATOM 7027 N LEU C 186 -24.448 -1.031 19.187 1.00 0.00 N \\\\nATOM 7028 CA LEU C 186 -24.044 -2.083 18.260 1.00 0.00 C \\\\nATOM 7029 C LEU C 186 -24.596 -1.812 16.867 1.00 0.00 C \\\\nATOM 7030 O LEU C 186 -23.917 -2.050 15.861 1.00 0.00 O \\\\nATOM 7031 CB LEU C 186 -24.507 -3.449 18.773 1.00 0.00 C \\\\nATOM 7032 CG LEU C 186 -24.315 -4.651 17.846 1.00 0.00 C \\\\nATOM 7033 CD1 LEU C 186 -22.837 -4.923 17.595 1.00 0.00 C \\\\nATOM 7034 CD2 LEU C 186 -25.004 -5.887 18.420 1.00 0.00 C \\\\nATOM 7035 H LEU C 186 -24.934 -1.293 19.847 1.00 0.00 H \\\\nATOM 7036 HA LEU C 186 -23.076 -2.090 18.203 1.00 0.00 H \\\\nATOM 7037 HB2 LEU C 186 -24.039 -3.632 19.602 1.00 0.00 H \\\\nATOM 7038 HB3 LEU C 186 -25.451 -3.384 18.988 1.00 0.00 H \\\\nATOM 7039 HG LEU C 186 -24.726 -4.440 16.993 1.00 0.00 H \\\\nATOM 7040 HD11 LEU C 186 -22.744 -5.688 17.006 1.00 0.00 H \\\\nATOM 7041 HD12 LEU C 186 -22.430 -4.146 17.181 1.00 0.00 H \\\\nATOM 7042 HD13 LEU C 186 -22.394 -5.109 18.438 1.00 0.00 H \\\\nATOM 7043 HD21 LEU C 186 -24.873 -6.638 17.821 1.00 0.00 H \\\\nATOM 7044 HD22 LEU C 186 -24.624 -6.096 19.288 1.00 0.00 H \\\\nATOM 7045 HD23 LEU C 186 -25.953 -5.713 18.516 1.00 0.00 H \\\\nATOM 7046 N ALA C 187 -25.831 -1.315 16.791 1.00 0.00 N \\\\nATOM 7047 CA ALA C 187 -26.418 -0.964 15.502 1.00 0.00 C \\\\nATOM 7048 C ALA C 187 -25.638 0.162 14.832 1.00 0.00 C \\\\nATOM 7049 O ALA C 187 -25.341 0.098 13.633 1.00 0.00 O \\\\nATOM 7050 CB ALA C 187 -27.886 -0.573 15.687 1.00 0.00 C \\\\nATOM 7051 H ALA C 187 -26.341 -1.175 17.469 1.00 0.00 H \\\\nATOM 7052 HA ALA C 187 -26.371 -1.739 14.921 1.00 0.00 H \\\\nATOM 7053 HB1 ALA C 187 -28.270 -0.341 14.827 1.00 0.00 H \\\\nATOM 7054 HB2 ALA C 187 -28.374 -1.320 16.068 1.00 0.00 H \\\\nATOM 7055 HB3 ALA C 187 -27.945 0.190 16.283 1.00 0.00 H \\\\nATOM 7056 N GLU C 188 -25.305 1.209 15.593 1.00 0.00 N \\\\nATOM 7057 CA GLU C 188 -24.550 2.324 15.026 1.00 0.00 C \\\\nATOM 7058 C GLU C 188 -23.162 1.885 14.575 1.00 0.00 C \\\\nATOM 7059 O GLU C 188 -22.696 2.280 13.498 1.00 0.00 O \\\\nATOM 7060 CB GLU C 188 -24.449 3.465 16.040 1.00 0.00 C \\\\nATOM 7061 CG GLU C 188 -23.307 4.447 15.773 1.00 0.00 C \\\\nATOM 7062 CD GLU C 188 -23.626 5.461 14.683 1.00 0.00 C \\\\nATOM 7063 OE1 GLU C 188 -23.996 5.053 13.561 1.00 0.00 O \\\\nATOM 7064 OE2 GLU C 188 -23.506 6.674 14.954 1.00 0.00 O \\\\nATOM 7065 H GLU C 188 -25.504 1.291 16.426 1.00 0.00 H \\\\nATOM 7066 HA GLU C 188 -25.027 2.641 14.243 1.00 0.00 H \\\\nATOM 7067 HB2 GLU C 188 -25.287 3.954 16.045 1.00 0.00 H \\\\nATOM 7068 HB3 GLU C 188 -24.336 3.087 16.926 1.00 0.00 H \\\\nATOM 7069 HG2 GLU C 188 -23.097 4.919 16.594 1.00 0.00 H \\\\nATOM 7070 HG3 GLU C 188 -22.513 3.949 15.521 1.00 0.00 H \\\\nATOM 7071 N VAL C 189 -22.484 1.073 15.389 1.00 0.00 N \\\\nATOM 7072 CA VAL C 189 -21.149 0.601 15.030 1.00 0.00 C \\\\nATOM 7073 C VAL C 189 -21.214 -0.280 13.788 1.00 0.00 C \\\\nATOM 7074 O VAL C 189 -20.417 -0.128 12.855 1.00 0.00 O \\\\nATOM 7075 CB VAL C 189 -20.501 -0.136 16.217 1.00 0.00 C \\\\nATOM 7076 CG1 VAL C 189 -19.243 -0.858 15.772 1.00 0.00 C \\\\nATOM 7077 CG2 VAL C 189 -20.187 0.843 17.334 1.00 0.00 C \\\\nATOM 7078 H VAL C 189 -22.777 0.787 16.145 1.00 0.00 H \\\\nATOM 7079 HA VAL C 189 -20.590 1.366 14.820 1.00 0.00 H \\\\nATOM 7080 HB VAL C 189 -21.128 -0.796 16.552 1.00 0.00 H \\\\nATOM 7081 HG11 VAL C 189 -18.848 -1.316 16.530 1.00 0.00 H \\\\nATOM 7082 HG12 VAL C 189 -19.467 -1.505 15.084 1.00 0.00 H \\\\nATOM 7083 HG13 VAL C 189 -18.609 -0.215 15.417 1.00 0.00 H \\\\nATOM 7084 HG21 VAL C 189 -19.780 0.368 18.076 1.00 0.00 H \\\\nATOM 7085 HG22 VAL C 189 -19.574 1.520 17.008 1.00 0.00 H \\\\nATOM 7086 HG23 VAL C 189 -21.007 1.267 17.633 1.00 0.00 H \\\\nATOM 7087 N SER C 190 -22.162 -1.219 13.760 1.00 0.00 N \\\\nATOM 7088 CA SER C 190 -22.277 -2.111 12.611 1.00 0.00 C \\\\nATOM 7089 C SER C 190 -22.607 -1.339 11.340 1.00 0.00 C \\\\nATOM 7090 O SER C 190 -22.044 -1.615 10.274 1.00 0.00 O \\\\nATOM 7091 CB SER C 190 -23.338 -3.180 12.877 1.00 0.00 C \\\\nATOM 7092 OG SER C 190 -23.085 -3.879 14.080 1.00 0.00 O \\\\nATOM 7093 H SER C 190 -22.737 -1.353 14.385 1.00 0.00 H \\\\nATOM 7094 HA SER C 190 -21.419 -2.544 12.480 1.00 0.00 H \\\\nATOM 7095 HB2 SER C 190 -24.213 -2.764 12.922 1.00 0.00 H \\\\nATOM 7096 HB3 SER C 190 -23.360 -3.806 12.137 1.00 0.00 H \\\\nATOM 7097 HG SER C 190 -23.203 -3.364 14.733 1.00 0.00 H \\\\nATOM 7098 N GLU C 191 -23.510 -0.359 11.433 1.00 0.00 N \\\\nATOM 7099 CA GLU C 191 -23.948 0.368 10.247 1.00 0.00 C \\\\nATOM 7100 C GLU C 191 -22.930 1.377 9.749 1.00 0.00 C \\\\nATOM 7101 O GLU C 191 -23.001 1.782 8.584 1.00 0.00 O \\\\nATOM 7102 CB GLU C 191 -25.264 1.094 10.528 1.00 0.00 C \\\\nATOM 7103 CG GLU C 191 -26.472 0.197 10.429 1.00 0.00 C \\\\nATOM 7104 CD GLU C 191 -27.618 0.684 11.283 1.00 0.00 C \\\\nATOM 7105 OE1 GLU C 191 -28.615 -0.056 11.416 1.00 0.00 O \\\\nATOM 7106 OE2 GLU C 191 -27.526 1.808 11.821 1.00 0.00 O \\\\nATOM 7107 H GLU C 191 -23.876 -0.104 12.168 1.00 0.00 H \\\\nATOM 7108 HA GLU C 191 -24.063 -0.299 9.552 1.00 0.00 H \\\\nATOM 7109 HB2 GLU C 191 -25.229 1.482 11.416 1.00 0.00 H \\\\nATOM 7110 HB3 GLU C 191 -25.362 1.828 9.901 1.00 0.00 H \\\\nATOM 7111 HG2 GLU C 191 -26.759 0.146 9.504 1.00 0.00 H \\\\nATOM 7112 HG3 GLU C 191 -26.228 -0.702 10.700 1.00 0.00 H \\\\nATOM 7113 N ARG C 192 -21.998 1.802 10.594 1.00 0.00 N \\\\nATOM 7114 CA ARG C 192 -20.964 2.728 10.166 1.00 0.00 C \\\\nATOM 7115 C ARG C 192 -19.673 1.999 9.827 1.00 0.00 C \\\\nATOM 7116 O ARG C 192 -18.630 2.634 9.639 1.00 0.00 O \\\\nATOM 7117 CB ARG C 192 -20.765 3.820 11.224 1.00 0.00 C \\\\nATOM 7118 CG ARG C 192 -19.841 3.524 12.376 1.00 0.00 C \\\\nATOM 7119 CD ARG C 192 -19.216 4.823 12.818 1.00 0.00 C \\\\nATOM 7120 NE ARG C 192 -18.511 5.490 11.716 1.00 0.00 N \\\\nATOM 7121 CZ ARG C 192 -19.041 6.421 10.933 1.00 0.00 C \\\\nATOM 7122 NH1 ARG C 192 -20.251 6.874 11.187 1.00 0.00 N \\\\nATOM 7123 NH2 ARG C 192 -18.325 6.946 9.956 1.00 0.00 N \\\\nATOM 7124 H ARG C 192 -21.949 1.565 11.419 1.00 0.00 H \\\\nATOM 7125 HA ARG C 192 -21.251 3.163 9.348 1.00 0.00 H \\\\nATOM 7126 HB2 ARG C 192 -20.435 4.614 10.774 1.00 0.00 H \\\\nATOM 7127 HB3 ARG C 192 -21.635 4.042 11.590 1.00 0.00 H \\\\nATOM 7128 HG2 ARG C 192 -20.331 3.117 13.108 1.00 0.00 H \\\\nATOM 7129 HG3 ARG C 192 -19.156 2.892 12.107 1.00 0.00 H \\\\nATOM 7130 HD2 ARG C 192 -19.904 5.412 13.165 1.00 0.00 H \\\\nATOM 7131 HD3 ARG C 192 -18.595 4.653 13.544 1.00 0.00 H \\\\nATOM 7132 HE ARG C 192 -17.696 5.261 11.567 1.00 0.00 H \\\\nATOM 7133 HH11 ARG C 192 -20.693 6.567 11.857 1.00 0.00 H \\\\nATOM 7134 HH12 ARG C 192 -20.599 7.477 10.683 1.00 0.00 H \\\\nATOM 7135 HH21 ARG C 192 -17.516 6.685 9.827 1.00 0.00 H \\\\nATOM 7136 HH22 ARG C 192 -18.668 7.549 9.448 1.00 0.00 H \\\\nATOM 7137 N LEU C 193 -19.739 0.672 9.767 1.00 0.00 N \\\\nATOM 7138 CA LEU C 193 -18.725 -0.178 9.165 1.00 0.00 C \\\\nATOM 7139 C LEU C 193 -19.224 -0.829 7.882 1.00 0.00 C \\\\nATOM 7140 O LEU C 193 -18.465 -1.541 7.217 1.00 0.00 O \\\\nATOM 7141 CB LEU C 193 -18.252 -1.243 10.159 1.00 0.00 C \\\\nATOM 7142 CG LEU C 193 -17.204 -0.723 11.148 1.00 0.00 C \\\\nATOM 7143 CD1 LEU C 193 -17.277 -1.479 12.461 1.00 0.00 C \\\\nATOM 7144 CD2 LEU C 193 -15.804 -0.800 10.544 1.00 0.00 C \\\\nATOM 7145 H LEU C 193 -20.402 0.228 10.089 1.00 0.00 H \\\\nATOM 7146 HA LEU C 193 -17.972 0.388 8.933 1.00 0.00 H \\\\nATOM 7147 HB2 LEU C 193 -19.016 -1.578 10.653 1.00 0.00 H \\\\nATOM 7148 HB3 LEU C 193 -17.881 -1.993 9.668 1.00 0.00 H \\\\nATOM 7149 HG LEU C 193 -17.398 0.209 11.332 1.00 0.00 H \\\\nATOM 7150 HD11 LEU C 193 -16.606 -1.134 13.071 1.00 0.00 H \\\\nATOM 7151 HD12 LEU C 193 -18.158 -1.365 12.852 1.00 0.00 H \\\\nATOM 7152 HD13 LEU C 193 -17.114 -2.422 12.301 1.00 0.00 H \\\\nATOM 7153 HD21 LEU C 193 -15.156 -0.467 11.185 1.00 0.00 H \\\\nATOM 7154 HD22 LEU C 193 -15.596 -1.722 10.324 1.00 0.00 H \\\\nATOM 7155 HD23 LEU C 193 -15.769 -0.260 9.739 1.00 0.00 H \\\\nATOM 7156 N VAL C 194 -20.490 -0.615 7.534 1.00 0.00 N \\\\nATOM 7157 CA VAL C 194 -21.017 -1.024 6.239 1.00 0.00 C \\\\nATOM 7158 C VAL C 194 -20.823 0.092 5.218 1.00 0.00 C \\\\nATOM 7159 O VAL C 194 -20.667 -0.179 4.022 1.00 0.00 O \\\\nATOM 7160 CB VAL C 194 -22.506 -1.409 6.372 1.00 0.00 C \\\\nATOM 7161 CG1 VAL C 194 -23.208 -1.414 5.019 1.00 0.00 C \\\\nATOM 7162 CG2 VAL C 194 -22.649 -2.759 7.038 1.00 0.00 C \\\\nATOM 7163 H VAL C 194 -21.066 -0.229 8.043 1.00 0.00 H \\\\nATOM 7164 HA VAL C 194 -20.531 -1.803 5.927 1.00 0.00 H \\\\nATOM 7165 HB VAL C 194 -22.932 -0.737 6.927 1.00 0.00 H \\\\nATOM 7166 HG11 VAL C 194 -24.139 -1.659 5.138 1.00 0.00 H \\\\nATOM 7167 HG12 VAL C 194 -23.155 -0.530 4.623 1.00 0.00 H \\\\nATOM 7168 HG13 VAL C 194 -22.777 -2.056 4.433 1.00 0.00 H \\\\nATOM 7169 HG21 VAL C 194 -23.589 -2.985 7.113 1.00 0.00 H \\\\nATOM 7170 HG22 VAL C 194 -22.197 -3.432 6.506 1.00 0.00 H \\\\nATOM 7171 HG23 VAL C 194 -22.253 -2.727 7.923 1.00 0.00 H \\\\nATOM 7172 N VAL C 195 -20.777 1.337 5.677 1.00 0.00 N \\\\nATOM 7173 CA VAL C 195 -20.526 2.476 4.814 1.00 0.00 C \\\\nATOM 7174 C VAL C 195 -19.103 2.410 4.274 1.00 0.00 C \\\\nATOM 7175 O VAL C 195 -18.149 2.243 5.034 1.00 0.00 O \\\\nATOM 7176 CB VAL C 195 -20.762 3.797 5.562 1.00 0.00 C \\\\nATOM 7177 CG1 VAL C 195 -20.112 4.952 4.818 1.00 0.00 C \\\\nATOM 7178 CG2 VAL C 195 -22.253 4.039 5.760 1.00 0.00 C \\\\nATOM 7179 H VAL C 195 -20.892 1.543 6.504 1.00 0.00 H \\\\nATOM 7180 HA VAL C 195 -21.148 2.444 4.070 1.00 0.00 H \\\\nATOM 7181 HB VAL C 195 -20.351 3.736 6.438 1.00 0.00 H \\\\nATOM 7182 HG11 VAL C 195 -20.269 5.778 5.302 1.00 0.00 H \\\\nATOM 7183 HG12 VAL C 195 -19.157 4.796 4.748 1.00 0.00 H \\\\nATOM 7184 HG13 VAL C 195 -20.494 5.020 3.929 1.00 0.00 H \\\\nATOM 7185 HG21 VAL C 195 -22.385 4.875 6.233 1.00 0.00 H \\\\nATOM 7186 HG22 VAL C 195 -22.691 4.084 4.896 1.00 0.00 H \\\\nATOM 7187 HG23 VAL C 195 -22.633 3.312 6.277 1.00 0.00 H \",\n \"ligand\": \"asdasdadas asdfsd f### \\\\n### Created by X-TOOL on Mon Aug 2 16:12:23 2021\\\\n### \\\\n\\\\n@\u003cTRIPOS\u003eMOLECULE\\\\n5zcu_ligand\\\\n 35 37 1 0 0\\\\nSMALL\\\\nGAST_HUCK\\\\n\\\\n\\\\n@\u003cTRIPOS\u003eATOM\\\\n 1 S -21.9840 -3.4930 30.2670 S.o2 1 PYV 0.0724\\\\n 2 BR -24.1210 -0.6400 35.6790 Br 1 PYV -0.0495\\\\n 3 C1 -23.4470 -1.7030 34.2030 C.ar 1 PYV 0.0197\\\\n 4 N1 -23.0330 -4.7560 29.7870 N.am 1 PYV -0.2334\\\\n 5 O1 -20.5870 -3.9290 30.2880 O.2 1 PYV -0.1496\\\\n 6 C2 -23.0400 -3.0490 34.2500 C.ar 1 PYV -0.0084\\\\n 7 N2 -25.6720 -6.3800 30.7570 N.ar 1 PYV -0.2964\\\\n 8 O2 -21.9450 -2.4040 29.2880 O.2 1 PYV -0.1496\\\\n 9 C3 -22.5840 -3.6600 33.1100 C.ar 1 PYV 0.0112\\\\n 10 C4 -22.5270 -2.9450 31.9060 C.ar 1 PYV 0.1195\\\\n 11 C5 -22.9290 -1.6180 31.8510 C.ar 1 PYV -0.0306\\\\n 12 C6 -23.3900 -0.9950 33.0070 C.ar 1 PYV -0.0494\\\\n 13 C7 -22.1770 -5.0060 33.1320 C.ar 1 PYV -0.0511\\\\n 14 C8 -22.2310 -5.7250 34.3150 C.ar 1 PYV -0.0605\\\\n 15 C9 -22.6880 -5.1080 35.4720 C.ar 1 PYV -0.0607\\\\n 16 C10 -23.0940 -3.7790 35.4510 C.ar 1 PYV -0.0538\\\\n 17 C11 -24.4580 -4.5040 29.6550 C.3 1 PYV 0.0756\\\\n 18 C12 -25.2580 -5.0960 30.8150 C.ar 1 PYV 0.0465\\\\n 19 C13 -26.3850 -6.9080 31.7770 C.ar 1 PYV 0.0028\\\\n 20 C14 -26.7010 -6.1340 32.8800 C.ar 1 PYV -0.0410\\\\n 21 C15 -26.2930 -4.8430 32.9390 C.ar 1 PYV -0.0488\\\\n 22 C16 -25.5800 -4.3150 31.9150 C.ar 1 PYV -0.0308\\\\n 23 H1 -22.6660 -5.6667 29.5974 H 1 PYV 0.1703\\\\n 24 H2 -22.8844 -1.0714 30.9159 H 1 PYV 0.0646\\\\n 25 H3 -23.7046 0.0419 32.9754 H 1 PYV 0.0655\\\\n 26 H4 -21.8215 -5.4803 32.2244 H 1 PYV 0.0630\\\\n 27 H5 -21.9185 -6.7627 34.3373 H 1 PYV 0.0618\\\\n 28 H6 -22.7284 -5.6677 36.3995 H 1 PYV 0.0624\\\\n 29 H7 -23.4516 -3.3060 36.3584 H 1 PYV 0.0620\\\\n 30 H8 -24.8117 -4.9528 28.7151 H 1 PYV 0.0668\\\\n 31 H9 -24.6247 -3.4171 29.6279 H 1 PYV 0.0668\\\\n 32 H10 -26.7103 -7.9410 31.7308 H 1 PYV 0.0803\\\\n 33 H11 -27.2741 -6.5599 33.6956 H 1 PYV 0.0652\\\\n 34 H12 -26.5363 -4.2348 33.8027 H 1 PYV 0.0719\\\\n 35 H13 -25.2605 -3.2799 31.9555 H 1 PYV 0.0652\\\\n@\u003cTRIPOS\u003eBOND\\\\n 1 4 1 am \\\\n 2 1 5 2 \\\\n 3 1 8 2 \\\\n 4 1 10 1 \\\\n 5 3 2 1 \\\\n 6 6 3 ar \\\\n 7 12 3 ar \\\\n 8 17 4 1 \\\\n 9 9 6 ar \\\\n 10 6 16 ar \\\\n 11 18 7 ar \\\\n 12 7 19 ar \\\\n 13 10 9 ar \\\\n 14 9 13 ar \\\\n 15 10 11 ar \\\\n 16 11 12 ar \\\\n 17 13 14 ar \\\\n 18 14 15 ar \\\\n 19 16 15 ar \\\\n 20 17 18 1 \\\\n 21 18 22 ar \\\\n 22 19 20 ar \\\\n 23 20 21 ar \\\\n 24 21 22 ar \\\\n 25 4 23 1 \\\\n 26 11 24 1 \\\\n 27 12 25 1 \\\\n 28 13 26 1 \\\\n 29 14 27 1 \\\\n 30 15 28 1 \\\\n 31 16 29 1 \\\\n 32 17 30 1 \\\\n 33 17 31 1 \\\\n 34 19 32 1 \\\\n 35 20 33 1 \\\\n 36 21 34 1 \\\\n 37 22 35 1 \\\\n@\u003cTRIPOS\u003eSUBSTRUCTURE\\\\n 1 PYV 1\\\\n\"\n}"])</script><script>self.__next_f.push([1,"da:T655,import sys\nimport requests\nimport time\n\nurl = \"https://health.api.nvidia.com/v1/biology/mit/diffdock\"\nheader_auth = \"Bearer $NVIDIA_API_KEY\"\n\ndef _upload_asset(input):\n assets_url = \"https://api.nvcf.nvidia.com/v2/nvcf/assets\"\n\n headers = {\n \"Authorization\": header_auth,\n \"Content-Type\": \"application/json\",\n \"accept\": \"application/json\",\n }\n\n s3_headers = {\n \"x-amz-meta-nvcf-asset-description\": \"diffdock-file\",\n \"content-type\": \"text/plain\",\n }\n\n payload = {\n \"contentType\": \"text/plain\", \n \"description\": \"diffdock-file\"\n }\n\n response = requests.post(\n assets_url, headers=headers, json=payload, timeout=30\n )\n\n response.raise_for_status()\n\n asset_url = response.json()[\"uploadUrl\"]\n asset_id = response.json()[\"assetId\"]\n\n response = requests.put(\n asset_url,\n data=input,\n headers=s3_headers,\n timeout=300,\n )\n\n response.raise_for_status()\n return asset_id\n\nprotein_id = _upload_asset(\u003c%- request.protein %\u003e,)\nligand_id = _upload_asset(\u003c%- request.ligand %\u003e)\n\nheaders = {\n \"Content-Type\": \"application/json\",\n \"NVCF-INPUT-ASSET-REFERENCES\": \",\".join([protein_id, ligand_id]),\n \"Authorization\": header_auth\n}\n\nr = requests.post(url, headers=headers, json={\n \"ligand\": ligand_id,\n \"ligand_file_type\": \u003c%- request.ligand_file_type %\u003e,\n \"protein\": protein_id,\n \"num_poses\": \u003c%- request.num_poses %\u003e,\n \"time_divisions\": \u003c%- request.time_divisions %\u003e,\n \"steps\": \u003c%- request.steps %\u003e,\n \"save_trajectory\": True,\n \"is_staged\": True\n})\n\n\nprint(r, url, r.text)db:Tad3,"])</script><script>self.__next_f.push([1,"import fetch from 'node-fetch';\n\nconst invokeUrl = 'https://health.api.nvidia.com/v1/biology/mit/diffdock';\nconst assetUploadUrl = 'https://api.nvcf.nvidia.com/v2/nvcf/assets';\n\nconst headers = {\n Authorization: 'Bearer $NVIDIA_API_KEY',\n Accept: 'application/json',\n};\n\nconst main = async (payload) =\u003e {\n\n const [proteinAssetId, ligandAssetId] = await Promise.all(\n [\n { description: 'Protein', payload: payload.protein },\n { description: 'Ligand', payload: payload.ligand },\n ].map(({ description, payload }) =\u003e\n fetch(assetUploadUrl, {\n method: 'POST',\n body: JSON.stringify({\n contentType: 'text/plain',\n description,\n }),\n headers: {\n 'Content-Type': 'application/json',\n ...headers,\n },\n })\n .then((res) =\u003e {\n if (!res.ok) {\n throw new Error(\n `${res.status} (${res.statusText}): ${res.headers.get(\n 'x-nv-error-msg'\n )}`\n );\n }\n\n return res\n .json()\n .then(({ assetId, uploadUrl, contentType, description }) =\u003e {\n return fetch(uploadUrl, {\n method: 'PUT',\n body: payload,\n headers: {\n 'Content-Type': contentType,\n 'x-amz-meta-nvcf-asset-description': description,\n },\n }).then((res) =\u003e {\n if (!res.ok) {\n return res.text().then((text) =\u003e {\n throw new Error(`${res.status} (${res.statusText}): ${text}`);\n });\n }\n return assetId;\n });\n });\n })\n\n .catch((error) =\u003e console.error(error.message))\n )\n );\n\n const response = await fetch(invokeUrl, {\n method: 'POST',\n body: JSON.stringify({\n ...payload,\n protein: proteinAssetId,\n ligand: ligandAssetId,\n is_staged: true,\n }),\n headers: {\n 'Content-Type': 'application/json',\n 'NVCF-INPUT-ASSET-REFERENCES': [proteinAssetId, ligandAssetId],\n ...headers,\n },\n });\n\n if (!response.ok) {\n throw new Error(\n `HTTP error! Status: ${response.status} ${\n response.statusText\n } ${response.headers.get('x-nv-error-msg')}`\n );\n }\n\n return response.json();\n}\n\nconst payload = {\n protein: \u003c%- request.protein %\u003e,\n ligand: \u003c%- request.ligand %\u003e,\n ligand_file_type: \u003c%- request.ligand_file_type %\u003e,\n num_poses: \u003c%- request.num_poses %\u003e,\n steps: \u003c%- request.steps %\u003e,\n time_divisions: \u003c%- request.time_divisions %\u003e,\n save_trajectory: \u003c%- request.save_trajectory %\u003e,\n}\n\nlet response_body = await main(payload);\n\nconsole.log(JSON.stringify(response_body));\n"])</script><script>self.__next_f.push([1,"dc:T8d2,"])</script><script>self.__next_f.push([1,"#! /usr/bin/env bash\n\necho \u003c%- request.protein %\u003e | sed 's/\\\\n/\\n/g' \u003e file_protein.pdb\n\necho \u003c%- request.ligand %\u003e | sed 's/\\\\n/\\n/g' \u003e file_ligand.sdf\n\ninvoke_url='https://health.api.nvidia.com/v1/biology/mit/diffdock'\nasset_upload_url='https://api.nvcf.nvidia.com/v2/nvcf/assets'\n\nauthorization_header='Authorization: Bearer $NVIDIA_API_KEY'\naccept_header='Accept: application/json'\ncontent_type_header='Content-Type: application/json'\n\nprotein_upload_info=$(curl --silent --request POST \\\n --url \"$asset_upload_url\" \\\n --header \"$authorization_header\" \\\n --header \"$accept_header\" \\\n --header \"$content_type_header\" \\\n --data '{\n \"contentType\": \"text/plain\",\n \"description\": \"Protein file\"\n }'\n)\n\nprotein_upload_url=$(echo $protein_upload_info | jq -r \".uploadUrl\")\nprotein_asset_id=$(echo $protein_upload_info | jq -r \".assetId\")\n\ncurl --silent --request PUT \\\n --url \"$protein_upload_url\" \\\n --header \"Content-Type: text/plain\" \\\n --header \"x-amz-meta-nvcf-asset-description: Protein file\" \\\n --data-binary \"@file_protein.pdb\"\n\n\nligand_upload_info=$(curl --silent --request POST \\\n --url \"$asset_upload_url\" \\\n --header \"$authorization_header\" \\\n --header \"$accept_header\" \\\n --header \"$content_type_header\" \\\n --data '{\n \"contentType\": \"text/plain\",\n \"description\": \"Ligand file\"\n }'\n)\n\nligand_upload_url=$(echo $ligand_upload_info | jq -r \".uploadUrl\")\nligand_asset_id=$(echo $ligand_upload_info | jq -r \".assetId\")\n\ncurl --silent --request PUT \\\n --url \"$ligand_upload_url\" \\\n --header \"Content-Type: text/plain\" \\\n --header \"x-amz-meta-nvcf-asset-description: Ligand file\" \\\n --data-binary \"@file_ligand.sdf\"\n\nresponse=$(curl --silent --request POST \\\n --url \"$invoke_url\" \\\n --header \"$authorization_header\" \\\n --header \"$accept_header\" \\\n --header \"$content_type_header\" \\\n --header \"NVCF-INPUT-ASSET-REFERENCES: $protein_asset_id, $ligand_asset_id\" \\\n --data '{\n \"protein\": \"'\"$protein_asset_id\"'\",\n \"ligand\": \"'\"$ligand_asset_id\"'\",\n \"ligand_file_type\": \u003c%- request.ligand_file_type %\u003e,\n \"num_poses\": \u003c%- request.num_poses %\u003e,\n \"steps\": \u003c%- request.steps %\u003e,\n \"time_divisions\": \u003c%- request.time_divisions %\u003e,\n \"save_trajectory\": true,\n \"is_staged\": true\n }'\n)\n\necho \"$response\""])</script><script>self.__next_f.push([1,"dd:T502,Pull and run the NVIDIA NIM with the command below. This will download the optimized model for your infrastructure.\n```bash\nexport NGC_API_KEY=\u003cPASTE_API_KEY_HERE\u003e\n\ndocker run -it --rm \\\n --runtime=nvidia -e NVIDIA_VISIBLE_DEVICES=0 \\\n --shm-size=2G \\\n --ulimit memlock=-1 \\\n --ulimit stack=67108864 \\\n -e NGC_API_KEY=$NGC_API_KEY \\\n -p 8000:8000 \\\n nvcr.io/nim/mit/diffdock:2.0.0\n```\n\nYou can now make a local API call using this curl command:\n```bash\nprotein_bytes=`curl -s https://files.rcsb.org/download/8G43.pdb | grep -E '^ATOM' | sed -z 's/\\n/\\\\\\n/g'`; \\\n ligand_bytes=`curl -s https://files.rcsb.org/ligands/download/ZU6_ideal.sdf | sed -z 's/\\n/\\\\\\n/g'`; \\\n echo \"{\n \\\"ligand\\\": \\\"${ligand_bytes}\\\",\n \\\"ligand_file_type\\\": \\\"sdf\\\",\n \\\"protein\\\": \\\"${protein_bytes}\\\",\n \\\"num_poses\\\": 1,\n \\\"time_divisions\\\": 20,\n \\\"steps\\\": 18,\n \\\"save_trajectory\\\": false,\n \\\"is_staged\\\": false\n }\" \u003e diffdock.json\n\ncurl --header \"Content-Type: application/json\" \\\n --request POST \\\n --data @diffdock.json \\\n --output output.json \\\n http://localhost:8000/molecular-docking/diffdock/generate\n```\n\nFor more details on getting started with this NIM, visit the [NVIDIA NIM Docs](https://docs.nvidia.com/nim/index.html#bionemo).\nde:T1140,"])</script><script>self.__next_f.push([1,"## Model Overview\n\n### Description:\n\nESMFold is a protein structure prediction deep learning model developed by Facebook AI Research (FAIR) `lin2023esmfold`. The model was inspired by AlphaFold, but does not require multiple sequence alignment (MSA) as an input, leading to significantly faster inference times for protein structure prediction that is nearly as accurate as alignment-based methods.\n\u003cbr\u003e\n\n### Third-Party Community Consideration\n\nThis model is not owned or developed by NVIDIA. This model has been developed and built to a third-party’s requirements for this application and use case; see link to Non-NVIDIA Model Card.\n\n### References:\n\n```\n@ARTICLE{lin2023esmfold,\n title = \"Evolutionary-scale prediction of atomic-level protein structure\n with a language model\",\n author = \"Lin, Zeming and Akin, Halil and Rao, Roshan and Hie, Brian and\n Zhu, Zhongkai and Lu, Wenting and Smetanin, Nikita and Verkuil,\n Robert and Kabeli, Ori and Shmueli, Yaniv and Dos Santos Costa,\n Allan and Fazel-Zarandi, Maryam and Sercu, Tom and Candido,\n Salvatore and Rives, Alexander\",\n journal = \"Science\",\n volume = 379,\n number = 6637,\n pages = \"1123--1130\",\n month = mar,\n year = 2023,\n language = \"en\",\n doi = {10.1101/2022.07.20.500902}\n}\n\n```\n\n### Model Architecture:\n\n**Architecture Type:** Pose Estimation \u003cbr\u003e\n**Network Architecture:** ESMFold \u003cbr\u003e\n\n### Input:\n\n**Input Type(s):** Protein Sequence \u003cbr\u003e\n**Input Format(s):** String \u003cbr\u003e\n**Input Parameters:** 1D \u003cbr\u003e\n**Other Properties Related to Input:** Protein Sequence matching the regular expression `^[ARNDCQEGHILKMFPSTWYVXBOU]*$` upto 1024 characters\u003cbr\u003e\n\n### Output:\n\n**Output Type(s):** Protrin Structure Pose(s) \u003cbr\u003e\n**Output Format:** PDB (text file)\u003cbr\u003e\n**Output Parameters:** 1D \u003cbr\u003e\n**Other Properties Related to Output:** Pose\u003cbr\u003e\n\n### Software Integration:\n\n**Runtime Engine(s):**\n* [Not Applicable (N/A)- Name Platform If Multiple] \u003cbr\u003e\n\n**Supported Hardware Microarchitecture Compatibility:** \u003cbr\u003e\n* [Ampere] \u003cbr\u003e\n* [L40] \u003cbr\u003e\n\n**[Preferred/Supported] Operating System(s):** \u003cbr\u003e\n* [Linux] \u003cbr\u003e\n\n### Model Version(s): ESMFold \u003cbr\u003e\n\n## Training \u0026 Evaluation:\n\n### Training Dataset:\n\n**Link:**\n[UniRef50](https://www.uniprot.org/help/uniref) \u003cbr\u003e\n\n** Data Collection Method by dataset \u003cbr\u003e\n* [Not Applicable] \u003cbr\u003e\n\n** Labeling Method by dataset \u003cbr\u003e\n* [Not Applicable] \u003cbr\u003e\n\n**Properties (Quantity, Dataset Descriptions, Sensor(s)):** [UniRef50](https://www.uniprot.org/help/uniref), September 2021 version, is used for the training of ESM models. The training dataset was partitioned by randomly selecting 0.5% (≈ 250,000) sequences to form the validation set. The training set has sequences removed via the procedure described \u003cbr\u003e\n\n**Dataset License(s):** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/). \u003cbr\u003e\n\n### Evaluation Dataset:\n\n[UniRef50](https://www.uniprot.org/help/uniref) \u003cbr\u003e\n** Data Collection Method by dataset \u003cbr\u003e\n* [Not Applicable] \u003cbr\u003e\n\n** Labeling Method by dataset \u003cbr\u003e\n* [Not Applicable] \u003cbr\u003e\n\n**Properties (Quantity, Dataset Descriptions, Sensor(s)):** [UniRef50](https://www.uniprot.org/help/uniref), September 2021 version, is used for the training of ESM models. The training dataset was partitioned by randomly selecting 0.5% (≈ 250,000) sequences to form the validation set. The training set has sequences removed via the procedure described \u003cbr\u003e\n\n**Dataset License(s):** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/). \u003cbr\u003e\n\n### Inference:\n\n**Engine:** Triton \u003cbr\u003e\n**Test Hardware:** \u003cbr\u003e\n* [Other (Not Listed)] \u003cbr\u003e\n\n### Ethical Considerations:\n\nNVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their supporting model team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse. For more detailed information on ethical considerations for this model, please see the Model Card++ Explainability, Bias, Safety \u0026 Security, and Privacy Subcards. Please report security vulnerabilities or NVIDIA AI Concerns [here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/).\n"])</script><script>self.__next_f.push([1,"df:T7539,"])</script><script>self.__next_f.push([1,"{\n \"pdbs\": [\n \"PARENT N/A\\nATOM 1 N MET A 1 12.501 2.331 -26.921 1.00 47.72 N \\nATOM 2 CA MET A 1 12.036 1.790 -25.647 1.00 50.64 C \\nATOM 3 C MET A 1 10.886 2.622 -25.090 1.00 50.01 C \\nATOM 4 CB MET A 1 13.182 1.737 -24.635 1.00 43.04 C \\nATOM 5 O MET A 1 11.032 3.828 -24.879 1.00 48.15 O \\nATOM 6 CG MET A 1 13.327 0.391 -23.944 1.00 41.60 C \\nATOM 7 SD MET A 1 14.560 0.428 -22.585 1.00 39.32 S \\nATOM 8 CE MET A 1 14.275 -1.206 -21.850 1.00 35.36 C \\nATOM 9 N SER A 2 9.707 2.634 -25.722 1.00 54.18 N \\nATOM 10 CA SER A 2 8.571 3.356 -25.157 1.00 55.29 C \\nATOM 11 C SER A 2 8.396 3.039 -23.675 1.00 54.83 C \\nATOM 12 CB SER A 2 7.288 3.015 -25.915 1.00 49.15 C \\nATOM 13 O SER A 2 8.428 1.873 -23.277 1.00 52.08 O \\nATOM 14 OG SER A 2 6.187 2.929 -25.027 1.00 48.74 O \\nATOM 15 N LEU A 3 9.218 3.712 -22.773 1.00 56.59 N \\nATOM 16 CA LEU A 3 8.914 3.579 -21.352 1.00 57.28 C \\nATOM 17 C LEU A 3 7.407 3.556 -21.119 1.00 57.34 C \\nATOM 18 CB LEU A 3 9.548 4.724 -20.558 1.00 52.72 C \\nATOM 19 O LEU A 3 6.702 4.494 -21.495 1.00 55.22 O \\nATOM 20 CG LEU A 3 11.023 4.558 -20.188 1.00 50.52 C \\nATOM 21 CD1 LEU A 3 11.657 5.918 -19.916 1.00 46.13 C \\nATOM 22 CD2 LEU A 3 11.170 3.641 -18.978 1.00 46.40 C \\nATOM 23 N LYS A 4 6.644 2.377 -21.470 1.00 56.17 N \\nATOM 24 CA LYS A 4 5.297 2.253 -20.921 1.00 56.33 C \\nATOM 25 C LYS A 4 5.160 3.037 -19.619 1.00 56.26 C \\nATOM 26 CB LYS A 4 4.946 0.783 -20.686 1.00 52.46 C \\nATOM 27 O LYS A 4 6.059 3.014 -18.777 1.00 54.00 O \\nATOM 28 CG LYS A 4 4.160 0.145 -21.822 1.00 50.74 C \\nATOM 29 CD LYS A 4 3.742 -1.280 -21.482 1.00 51.22 C \\nATOM 30 CE LYS A 4 2.972 -1.926 -22.626 1.00 46.00 C \\nATOM 31 NZ LYS A 4 2.570 -3.327 -22.301 1.00 41.10 N \\nATOM 32 N ARG A 5 4.654 4.355 -19.659 1.00 57.17 N \\nATOM 33 CA ARG A 5 4.370 5.118 -18.448 1.00 56.75 C \\nATOM 34 C ARG A 5 4.145 4.191 -17.258 1.00 57.30 C \\nATOM 35 CB ARG A 5 3.147 6.014 -18.652 1.00 54.00 C \\nATOM 36 O ARG A 5 3.305 3.291 -17.315 1.00 55.39 O \\nATOM 37 CG ARG A 5 3.418 7.241 -19.507 1.00 52.34 C \\nATOM 38 CD ARG A 5 2.248 8.215 -19.485 1.00 51.80 C \\nATOM 39 NE ARG A 5 2.490 9.368 -20.347 1.00 47.80 N \\nATOM 40 NH1 ARG A 5 0.476 10.400 -19.880 1.00 36.09 N \\nATOM 41 NH2 ARG A 5 1.963 11.379 -21.324 1.00 30.93 N \\nATOM 42 CZ ARG A 5 1.642 10.380 -20.515 1.00 48.53 C \\nATOM 43 N LYS A 6 5.076 3.542 -16.648 1.00 56.74 N \\nATOM 44 CA LYS A 6 4.941 3.003 -15.298 1.00 55.91 C \\nATOM 45 C LYS A 6 4.159 3.957 -14.400 1.00 57.02 C \\nATOM 46 CB LYS A 6 6.317 2.722 -14.692 1.00 53.22 C \\nATOM 47 O LYS A 6 4.437 5.158 -14.370 1.00 55.13 O \\nATOM 48 CG LYS A 6 7.043 1.544 -15.323 1.00 51.42 C \\nATOM 49 CD LYS A 6 8.240 1.111 -14.486 1.00 51.12 C \\nATOM 50 CE LYS A 6 8.985 -0.049 -15.132 1.00 46.58 C \\nATOM 51 NZ LYS A 6 10.148 -0.490 -14.305 1.00 40.34 N \\nATOM 52 N ASN A 7 2.844 3.954 -14.515 1.00 59.23 N \\nATOM 53 CA ASN A 7 2.185 4.649 -13.414 1.00 58.05 C \\nATOM 54 C ASN A 7 3.018 4.592 -12.137 1.00 59.52 C \\nATOM 55 CB ASN A 7 0.793 4.064 -13.167 1.00 55.24 C \\nATOM 56 O ASN A 7 3.423 3.513 -11.702 1.00 57.25 O \\nATOM 57 CG ASN A 7 -0.186 4.395 -14.276 1.00 52.37 C \\nATOM 58 ND2 ASN A 7 -0.992 3.415 -14.668 1.00 50.08 N \\nATOM 59 OD1 ASN A 7 -0.217 5.522 -14.777 1.00 53.79 O \\nATOM 60 N ILE A 8 4.069 5.352 -12.056 1.00 59.68 N \\nATOM 61 CA ILE A 8 4.815 5.542 -10.817 1.00 59.01 C \\nATOM 62 C ILE A 8 3.902 6.142 -9.751 1.00 59.98 C \\nATOM 63 CB ILE A 8 6.050 6.445 -11.034 1.00 55.49 C \\nATOM 64 O ILE A 8 3.251 7.163 -9.985 1.00 57.77 O \\nATOM 65 CG1 ILE A 8 6.987 5.827 -12.078 1.00 48.43 C \\nATOM 66 CG2 ILE A 8 6.785 6.683 -9.711 1.00 50.12 C \\nATOM 67 CD1 ILE A 8 8.131 6.738 -12.500 1.00 48.88 C \\nATOM 68 N ALA A 9 3.305 5.411 -8.843 1.00 61.62 N \\nATOM 69 CA ALA A 9 2.704 5.967 -7.633 1.00 60.50 C \\nATOM 70 C ALA A 9 3.767 6.566 -6.717 1.00 61.95 C \\nATOM 71 CB ALA A 9 1.909 4.894 -6.892 1.00 57.91 C \\nATOM 72 O ALA A 9 4.802 5.943 -6.467 1.00 59.91 O \\nATOM 73 N LEU A 10 4.029 7.816 -6.856 1.00 59.55 N \\nATOM 74 CA LEU A 10 4.825 8.505 -5.845 1.00 58.84 C \\nATOM 75 C LEU A 10 4.129 8.470 -4.489 1.00 59.62 C \\nATOM 76 CB LEU A 10 5.083 9.955 -6.262 1.00 55.09 C \\nATOM 77 O LEU A 10 3.007 8.963 -4.349 1.00 56.92 O \\nATOM 78 CG LEU A 10 6.506 10.287 -6.715 1.00 52.00 C \\nATOM 79 CD1 LEU A 10 6.495 10.832 -8.139 1.00 47.29 C \\nATOM 80 CD2 LEU A 10 7.153 11.285 -5.760 1.00 47.91 C \\nATOM 81 N ILE A 11 4.324 7.555 -3.640 1.00 63.93 N \\nATOM 82 CA ILE A 11 3.807 7.436 -2.281 1.00 62.81 C \\nATOM 83 C ILE A 11 4.630 8.311 -1.338 1.00 64.11 C \\nATOM 84 CB ILE A 11 3.820 5.968 -1.798 1.00 60.05 C \\nATOM 85 O ILE A 11 5.827 8.080 -1.152 1.00 62.31 O \\nATOM 86 CG1 ILE A 11 3.044 5.078 -2.775 1.00 55.32 C \\nATOM 87 CG2 ILE A 11 3.243 5.860 -0.383 1.00 56.55 C \\nATOM 88 CD1 ILE A 11 3.024 3.605 -2.388 1.00 56.02 C \\nATOM 89 N PRO A 12 4.236 9.559 -1.122 1.00 59.69 N \\nATOM 90 CA PRO A 12 4.957 10.421 -0.183 1.00 57.99 C \\nATOM 91 C PRO A 12 5.285 9.717 1.132 1.00 59.47 C \\nATOM 92 CB PRO A 12 3.985 11.582 0.047 1.00 55.24 C \\nATOM 93 O PRO A 12 4.386 9.199 1.800 1.00 56.72 O \\nATOM 94 CG PRO A 12 2.679 11.101 -0.497 1.00 52.39 C \\nATOM 95 CD PRO A 12 2.920 9.830 -1.261 1.00 51.89 C \\nATOM 96 N ALA A 13 6.303 8.725 1.183 1.00 58.14 N \\nATOM 97 CA ALA A 13 6.956 8.140 2.351 1.00 56.61 C \\nATOM 98 C ALA A 13 7.721 9.198 3.139 1.00 58.03 C \\nATOM 99 CB ALA A 13 7.895 7.014 1.927 1.00 54.18 C \\nATOM 100 O ALA A 13 8.747 9.705 2.677 1.00 56.02 O \\nATOM 101 N ALA A 14 7.310 10.425 3.224 1.00 55.08 N \\nATOM 102 CA ALA A 14 8.297 11.292 3.863 1.00 53.30 C \\nATOM 103 C ALA A 14 7.694 12.017 5.063 1.00 54.76 C \\nATOM 104 CB ALA A 14 8.849 12.301 2.858 1.00 49.07 C \\nATOM 105 O ALA A 14 6.582 12.545 4.983 1.00 51.84 O \\nATOM 106 N GLY A 15 7.542 11.287 6.272 1.00 56.09 N \\nATOM 107 CA GLY A 15 7.794 11.777 7.617 1.00 54.70 C \\nATOM 108 C GLY A 15 7.422 10.777 8.696 1.00 55.87 C \\nATOM 109 O GLY A 15 6.534 9.945 8.498 1.00 53.38 O \\nATOM 110 N ILE A 16 8.382 10.048 9.409 1.00 54.33 N \\nATOM 111 CA ILE A 16 8.033 9.496 10.713 1.00 52.91 C \\nATOM 112 C ILE A 16 6.988 10.383 11.386 1.00 54.37 C \\nATOM 113 CB ILE A 16 9.278 9.354 11.618 1.00 50.66 C \\nATOM 114 O ILE A 16 7.218 11.576 11.595 1.00 52.62 O \\nATOM 115 CG1 ILE A 16 10.421 8.679 10.852 1.00 45.57 C \\nATOM 116 CG2 ILE A 16 8.934 8.574 12.890 1.00 47.18 C \\nATOM 117 CD1 ILE A 16 11.747 8.668 11.601 1.00 43.25 C \\nATOM 118 N GLY A 17 5.897 10.652 10.712 1.00 51.05 N \\nATOM 119 CA GLY A 17 4.889 11.495 11.333 1.00 49.41 C \\nATOM 120 C GLY A 17 4.616 11.131 12.781 1.00 51.34 C \\nATOM 121 O GLY A 17 4.557 9.950 13.129 1.00 49.32 O \\nATOM 122 N VAL A 18 5.390 11.622 13.767 1.00 52.37 N \\nATOM 123 CA VAL A 18 5.180 11.695 15.209 1.00 51.47 C \\nATOM 124 C VAL A 18 3.749 11.281 15.545 1.00 52.74 C \\nATOM 125 CB VAL A 18 5.467 13.112 15.754 1.00 47.82 C \\nATOM 126 O VAL A 18 3.482 10.780 16.640 1.00 50.91 O \\nATOM 127 CG1 VAL A 18 5.921 13.049 17.211 1.00 40.43 C \\nATOM 128 CG2 VAL A 18 6.518 13.811 14.894 1.00 42.74 C \\nATOM 129 N ARG A 19 2.843 11.411 14.494 1.00 54.51 N \\nATOM 130 CA ARG A 19 1.471 11.191 14.939 1.00 53.31 C \\nATOM 131 C ARG A 19 1.173 9.702 15.081 1.00 54.54 C \\nATOM 132 CB ARG A 19 0.480 11.834 13.966 1.00 49.59 C \\nATOM 133 O ARG A 19 0.258 9.313 15.809 1.00 52.50 O \\nATOM 134 CG ARG A 19 0.116 13.268 14.315 1.00 46.93 C \\nATOM 135 CD ARG A 19 -1.015 13.792 13.441 1.00 47.92 C \\nATOM 136 NE ARG A 19 -1.345 15.178 13.759 1.00 41.79 N \\nATOM 137 NH1 ARG A 19 -3.052 15.344 12.211 1.00 32.33 N \\nATOM 138 NH2 ARG A 19 -2.521 17.138 13.535 1.00 28.40 N \\nATOM 139 CZ ARG A 19 -2.305 15.883 13.168 1.00 42.08 C \\nATOM 140 N PHE A 20 2.037 8.828 14.567 1.00 53.76 N \\nATOM 141 CA PHE A 20 1.640 7.435 14.728 1.00 52.52 C \\nATOM 142 C PHE A 20 2.579 6.711 15.685 1.00 53.62 C \\nATOM 143 CB PHE A 20 1.619 6.720 13.373 1.00 50.12 C \\nATOM 144 O PHE A 20 2.336 5.558 16.049 1.00 52.09 O \\nATOM 145 CG PHE A 20 0.410 7.041 12.536 1.00 47.89 C \\nATOM 146 CD1 PHE A 20 -0.794 6.379 12.747 1.00 45.18 C \\nATOM 147 CD2 PHE A 20 0.477 8.004 11.538 1.00 46.49 C \\nATOM 148 CE1 PHE A 20 -1.915 6.674 11.974 1.00 47.12 C \\nATOM 149 CE2 PHE A 20 -0.639 8.304 10.762 1.00 46.89 C \\nATOM 150 CZ PHE A 20 -1.833 7.637 10.981 1.00 45.52 C \\nATOM 151 N GLY A 21 3.306 7.533 16.434 1.00 57.48 N \\nATOM 152 CA GLY A 21 4.107 6.863 17.445 1.00 55.82 C \\nATOM 153 C GLY A 21 4.934 5.719 16.891 1.00 57.70 C \\nATOM 154 O GLY A 21 5.405 4.864 17.644 1.00 55.16 O \\nATOM 155 N ALA A 22 5.071 5.575 15.673 1.00 56.68 N \\nATOM 156 CA ALA A 22 5.774 4.435 15.093 1.00 55.11 C \\nATOM 157 C ALA A 22 7.162 4.838 14.602 1.00 56.79 C \\nATOM 158 CB ALA A 22 4.962 3.835 13.948 1.00 52.06 C \\nATOM 159 O ALA A 22 7.398 6.004 14.277 1.00 54.83 O \\nATOM 160 N ASP A 23 8.194 4.133 15.107 1.00 64.08 N \\nATOM 161 CA ASP A 23 9.572 4.078 14.630 1.00 63.11 C \\nATOM 162 C ASP A 23 9.624 3.822 13.126 1.00 64.36 C \\nATOM 163 CB ASP A 23 10.355 2.995 15.375 1.00 59.64 C \\nATOM 164 O ASP A 23 10.706 3.693 12.549 1.00 62.57 O \\nATOM 165 CG ASP A 23 10.227 3.103 16.884 1.00 56.58 C \\nATOM 166 OD1 ASP A 23 10.042 4.225 17.402 1.00 55.54 O \\nATOM 167 OD2 ASP A 23 10.316 2.056 17.562 1.00 58.07 O \\nATOM 168 N LYS A 24 8.455 3.717 12.487 1.00 67.05 N \\nATOM 169 CA LYS A 24 8.508 3.334 11.079 1.00 65.58 C \\nATOM 170 C LYS A 24 7.828 4.379 10.199 1.00 66.66 C \\nATOM 171 CB LYS A 24 7.854 1.967 10.869 1.00 63.36 C \\nATOM 172 O LYS A 24 6.937 5.098 10.656 1.00 63.65 O \\nATOM 173 CG LYS A 24 8.521 0.837 11.639 1.00 60.44 C \\nATOM 174 CD LYS A 24 7.852 -0.502 11.357 1.00 59.53 C \\nATOM 175 CE LYS A 24 8.471 -1.622 12.184 1.00 54.94 C \\nATOM 176 NZ LYS A 24 7.733 -2.909 12.012 1.00 48.19 N \\nATOM 177 N PRO A 25 8.378 4.698 8.980 1.00 72.42 N \\nATOM 178 CA PRO A 25 7.719 5.610 8.041 1.00 71.65 C \\nATOM 179 C PRO A 25 6.249 5.265 7.817 1.00 72.81 C \\nATOM 180 CB PRO A 25 8.525 5.431 6.752 1.00 70.34 C \\nATOM 181 O PRO A 25 5.866 4.096 7.900 1.00 70.73 O \\nATOM 182 CG PRO A 25 9.826 4.841 7.193 1.00 67.60 C \\nATOM 183 CD PRO A 25 9.587 4.038 8.439 1.00 66.12 C \\nATOM 184 N LYS A 26 5.283 6.270 7.722 1.00 73.08 N \\nATOM 185 CA LYS A 26 3.827 6.180 7.685 1.00 72.63 C \\nATOM 186 C LYS A 26 3.367 5.116 6.692 1.00 73.79 C \\nATOM 187 CB LYS A 26 3.214 7.534 7.323 1.00 70.90 C \\nATOM 188 O LYS A 26 2.394 4.402 6.945 1.00 73.26 O \\nATOM 189 CG LYS A 26 3.306 8.571 8.432 1.00 66.73 C \\nATOM 190 CD LYS A 26 2.631 9.877 8.033 1.00 63.11 C \\nATOM 191 CE LYS A 26 2.752 10.928 9.129 1.00 56.23 C \\nATOM 192 NZ LYS A 26 2.143 12.229 8.719 1.00 51.14 N \\nATOM 193 N GLN A 27 4.004 5.040 5.619 1.00 74.47 N \\nATOM 194 CA GLN A 27 3.545 4.126 4.578 1.00 74.03 C \\nATOM 195 C GLN A 27 3.680 2.673 5.023 1.00 75.08 C \\nATOM 196 CB GLN A 27 4.326 4.352 3.282 1.00 72.50 C \\nATOM 197 O GLN A 27 3.068 1.778 4.435 1.00 73.98 O \\nATOM 198 CG GLN A 27 5.800 3.985 3.380 1.00 69.45 C \\nATOM 199 CD GLN A 27 6.665 5.146 3.836 1.00 66.53 C \\nATOM 200 NE2 GLN A 27 7.945 5.106 3.484 1.00 61.05 N \\nATOM 201 OE1 GLN A 27 6.186 6.071 4.499 1.00 64.36 O \\nATOM 202 N TYR A 28 4.486 2.408 6.120 1.00 77.28 N \\nATOM 203 CA TYR A 28 4.684 1.029 6.551 1.00 77.08 C \\nATOM 204 C TYR A 28 3.824 0.708 7.767 1.00 77.45 C \\nATOM 205 CB TYR A 28 6.160 0.772 6.872 1.00 75.60 C \\nATOM 206 O TYR A 28 3.894 -0.396 8.311 1.00 76.21 O \\nATOM 207 CG TYR A 28 7.063 0.827 5.664 1.00 73.99 C \\nATOM 208 CD1 TYR A 28 6.847 -0.008 4.570 1.00 72.59 C \\nATOM 209 CD2 TYR A 28 8.134 1.713 5.614 1.00 73.01 C \\nATOM 210 CE1 TYR A 28 7.678 0.038 3.455 1.00 71.16 C \\nATOM 211 CE2 TYR A 28 8.971 1.767 4.505 1.00 71.93 C \\nATOM 212 OH TYR A 28 9.561 0.977 2.331 1.00 69.53 O \\nATOM 213 CZ TYR A 28 8.735 0.927 3.432 1.00 66.43 C \\nATOM 214 N VAL A 29 3.056 1.727 8.204 1.00 77.93 N \\nATOM 215 CA VAL A 29 2.120 1.461 9.291 1.00 77.90 C \\nATOM 216 C VAL A 29 1.004 0.542 8.799 1.00 79.01 C \\nATOM 217 CB VAL A 29 1.524 2.768 9.860 1.00 76.49 C \\nATOM 218 O VAL A 29 0.498 0.710 7.687 1.00 78.77 O \\nATOM 219 CG1 VAL A 29 0.448 2.462 10.901 1.00 72.72 C \\nATOM 220 CG2 VAL A 29 2.624 3.638 10.463 1.00 72.65 C \\nATOM 221 N GLU A 30 0.558 -0.456 9.611 1.00 78.48 N \\nATOM 222 CA GLU A 30 -0.443 -1.461 9.265 1.00 78.57 C \\nATOM 223 C GLU A 30 -1.843 -1.006 9.667 1.00 79.17 C \\nATOM 224 CB GLU A 30 -0.114 -2.800 9.931 1.00 76.54 C \\nATOM 225 O GLU A 30 -2.036 -0.462 10.757 1.00 78.29 O \\nATOM 226 CG GLU A 30 1.134 -3.472 9.376 1.00 72.78 C \\nATOM 227 CD GLU A 30 1.473 -4.778 10.075 1.00 70.99 C \\nATOM 228 OE1 GLU A 30 0.938 -5.033 11.178 1.00 68.94 O \\nATOM 229 OE2 GLU A 30 2.281 -5.553 9.517 1.00 65.31 O \\nATOM 230 N ILE A 31 -2.732 -1.003 8.730 1.00 79.81 N \\nATOM 231 CA ILE A 31 -4.173 -0.906 8.940 1.00 80.21 C \\nATOM 232 C ILE A 31 -4.838 -2.232 8.576 1.00 81.01 C \\nATOM 233 CB ILE A 31 -4.788 0.246 8.114 1.00 78.02 C \\nATOM 234 O ILE A 31 -4.964 -2.567 7.396 1.00 80.31 O \\nATOM 235 CG1 ILE A 31 -4.087 1.570 8.439 1.00 71.79 C \\nATOM 236 CG2 ILE A 31 -6.295 0.348 8.367 1.00 71.33 C \\nATOM 237 CD1 ILE A 31 -4.572 2.748 7.606 1.00 68.69 C \\nATOM 238 N GLY A 32 -5.258 -3.027 9.817 1.00 80.95 N \\nATOM 239 CA GLY A 32 -5.635 -4.404 9.541 1.00 81.75 C \\nATOM 240 C GLY A 32 -4.460 -5.275 9.134 1.00 79.05 C \\nATOM 241 O GLY A 32 -3.422 -5.274 9.798 1.00 73.40 O \\nATOM 242 N SER A 33 -4.521 -6.074 8.047 1.00 82.85 N \\nATOM 243 CA SER A 33 -3.462 -6.968 7.590 1.00 84.02 C \\nATOM 244 C SER A 33 -2.611 -6.309 6.509 1.00 82.91 C \\nATOM 245 CB SER A 33 -4.055 -8.274 7.058 1.00 78.34 C \\nATOM 246 O SER A 33 -1.711 -6.939 5.950 1.00 79.75 O \\nATOM 247 OG SER A 33 -4.887 -8.029 5.937 1.00 68.18 O \\nATOM 248 N LYS A 34 -2.932 -5.116 6.176 1.00 85.34 N \\nATOM 249 CA LYS A 34 -2.201 -4.485 5.081 1.00 84.95 C \\nATOM 250 C LYS A 34 -1.574 -3.167 5.527 1.00 85.12 C \\nATOM 251 CB LYS A 34 -3.125 -4.247 3.886 1.00 83.34 C \\nATOM 252 O LYS A 34 -2.094 -2.496 6.420 1.00 83.10 O \\nATOM 253 CG LYS A 34 -3.633 -5.525 3.232 1.00 78.44 C \\nATOM 254 CD LYS A 34 -4.507 -5.224 2.021 1.00 75.88 C \\nATOM 255 CE LYS A 34 -5.014 -6.501 1.366 1.00 70.89 C \\nATOM 256 NZ LYS A 34 -5.878 -6.211 0.182 1.00 63.91 N \\nATOM 257 N THR A 35 -0.405 -2.863 4.935 1.00 81.15 N \\nATOM 258 CA THR A 35 0.219 -1.568 5.181 1.00 80.99 C \\nATOM 259 C THR A 35 -0.504 -0.465 4.413 1.00 81.04 C \\nATOM 260 CB THR A 35 1.708 -1.581 4.787 1.00 79.53 C \\nATOM 261 O THR A 35 -1.241 -0.742 3.465 1.00 79.37 O \\nATOM 262 CG2 THR A 35 2.451 -2.715 5.485 1.00 75.12 C \\nATOM 263 OG1 THR A 35 1.819 -1.753 3.369 1.00 76.52 O \\nATOM 264 N VAL A 36 -0.411 0.819 4.846 1.00 80.11 N \\nATOM 265 CA VAL A 36 -0.934 1.965 4.110 1.00 79.63 C \\nATOM 266 C VAL A 36 -0.466 1.903 2.658 1.00 80.06 C \\nATOM 267 CB VAL A 36 -0.500 3.300 4.754 1.00 78.52 C \\nATOM 268 O VAL A 36 -1.251 2.137 1.736 1.00 78.93 O \\nATOM 269 CG1 VAL A 36 -0.881 4.480 3.862 1.00 75.72 C \\nATOM 270 CG2 VAL A 36 -1.124 3.451 6.140 1.00 75.36 C \\nATOM 271 N LEU A 37 0.847 1.469 2.453 1.00 78.80 N \\nATOM 272 CA LEU A 37 1.378 1.370 1.098 1.00 78.45 C \\nATOM 273 C LEU A 37 0.594 0.350 0.280 1.00 79.14 C \\nATOM 274 CB LEU A 37 2.860 0.986 1.130 1.00 77.10 C \\nATOM 275 O LEU A 37 0.245 0.609 -0.874 1.00 78.31 O \\nATOM 276 CG LEU A 37 3.551 0.837 -0.227 1.00 73.70 C \\nATOM 277 CD1 LEU A 37 3.479 2.147 -1.005 1.00 70.12 C \\nATOM 278 CD2 LEU A 37 4.999 0.396 -0.045 1.00 70.38 C \\nATOM 279 N GLU A 38 0.326 -0.772 0.910 1.00 81.00 N \\nATOM 280 CA GLU A 38 -0.398 -1.831 0.214 1.00 80.69 C \\nATOM 281 C GLU A 38 -1.823 -1.399 -0.120 1.00 80.97 C \\nATOM 282 CB GLU A 38 -0.421 -3.111 1.054 1.00 79.72 C \\nATOM 283 O GLU A 38 -2.351 -1.745 -1.179 1.00 79.93 O \\nATOM 284 CG GLU A 38 0.907 -3.854 1.079 1.00 78.36 C \\nATOM 285 CD GLU A 38 0.922 -5.025 2.048 1.00 77.16 C \\nATOM 286 OE1 GLU A 38 0.633 -4.822 3.250 1.00 75.05 O \\nATOM 287 OE2 GLU A 38 1.225 -6.154 1.603 1.00 73.48 O \\nATOM 288 N HIS A 39 -2.457 -0.687 0.816 1.00 81.53 N \\nATOM 289 CA HIS A 39 -3.795 -0.168 0.558 1.00 81.42 C \\nATOM 290 C HIS A 39 -3.799 0.775 -0.641 1.00 81.14 C \\nATOM 291 CB HIS A 39 -4.338 0.552 1.793 1.00 80.11 C \\nATOM 292 O HIS A 39 -4.679 0.690 -1.500 1.00 79.71 O \\nATOM 293 CG HIS A 39 -4.855 -0.374 2.848 1.00 77.94 C \\nATOM 294 CD2 HIS A 39 -4.368 -0.687 4.072 1.00 76.33 C \\nATOM 295 ND1 HIS A 39 -6.012 -1.106 2.694 1.00 75.15 N \\nATOM 296 CE1 HIS A 39 -6.215 -1.832 3.781 1.00 75.03 C \\nATOM 297 NE2 HIS A 39 -5.232 -1.595 4.633 1.00 74.02 N \\nATOM 298 N VAL A 40 -2.828 1.745 -0.721 1.00 78.76 N \\nATOM 299 CA VAL A 40 -2.721 2.734 -1.789 1.00 78.03 C \\nATOM 300 C VAL A 40 -2.453 2.031 -3.118 1.00 78.38 C \\nATOM 301 CB VAL A 40 -1.608 3.766 -1.498 1.00 76.80 C \\nATOM 302 O VAL A 40 -3.062 2.365 -4.138 1.00 76.89 O \\nATOM 303 CG1 VAL A 40 -1.357 4.647 -2.720 1.00 72.40 C \\nATOM 304 CG2 VAL A 40 -1.977 4.619 -0.286 1.00 72.27 C \\nATOM 305 N LEU A 41 -1.533 1.030 -3.081 1.00 77.58 N \\nATOM 306 CA LEU A 41 -1.216 0.308 -4.309 1.00 77.11 C \\nATOM 307 C LEU A 41 -2.433 -0.455 -4.819 1.00 77.56 C \\nATOM 308 CB LEU A 41 -0.052 -0.659 -4.077 1.00 75.74 C \\nATOM 309 O LEU A 41 -2.640 -0.564 -6.030 1.00 76.53 O \\nATOM 310 CG LEU A 41 1.326 -0.026 -3.878 1.00 72.48 C \\nATOM 311 CD1 LEU A 41 2.355 -1.095 -3.528 1.00 69.28 C \\nATOM 312 CD2 LEU A 41 1.748 0.741 -5.127 1.00 69.52 C \\nATOM 313 N GLY A 42 -3.206 -1.059 -3.937 1.00 80.25 N \\nATOM 314 CA GLY A 42 -4.423 -1.754 -4.325 1.00 79.71 C \\nATOM 315 C GLY A 42 -5.423 -0.859 -5.030 1.00 79.88 C \\nATOM 316 O GLY A 42 -6.161 -1.313 -5.907 1.00 78.27 O \\nATOM 317 N ILE A 43 -5.531 0.394 -4.566 1.00 78.63 N \\nATOM 318 CA ILE A 43 -6.434 1.357 -5.189 1.00 77.91 C \\nATOM 319 C ILE A 43 -6.013 1.597 -6.637 1.00 77.95 C \\nATOM 320 CB ILE A 43 -6.461 2.691 -4.411 1.00 76.47 C \\nATOM 321 O ILE A 43 -6.860 1.694 -7.528 1.00 76.49 O \\nATOM 322 CG1 ILE A 43 -7.132 2.500 -3.046 1.00 73.27 C \\nATOM 323 CG2 ILE A 43 -7.173 3.776 -5.224 1.00 72.94 C \\nATOM 324 CD1 ILE A 43 -6.943 3.672 -2.093 1.00 70.53 C \\nATOM 325 N PHE A 44 -4.748 1.699 -6.863 1.00 73.12 N \\nATOM 326 CA PHE A 44 -4.249 1.975 -8.205 1.00 72.40 C \\nATOM 327 C PHE A 44 -4.421 0.758 -9.107 1.00 72.33 C \\nATOM 328 CB PHE A 44 -2.774 2.388 -8.157 1.00 70.49 C \\nATOM 329 O PHE A 44 -4.595 0.898 -10.319 1.00 70.65 O \\nATOM 330 CG PHE A 44 -2.551 3.782 -7.636 1.00 66.97 C \\nATOM 331 CD1 PHE A 44 -2.949 4.888 -8.377 1.00 63.88 C \\nATOM 332 CD2 PHE A 44 -1.944 3.986 -6.404 1.00 64.30 C \\nATOM 333 CE1 PHE A 44 -2.743 6.180 -7.897 1.00 61.63 C \\nATOM 334 CE2 PHE A 44 -1.736 5.274 -5.917 1.00 60.85 C \\nATOM 335 CZ PHE A 44 -2.135 6.369 -6.666 1.00 60.58 C \\nATOM 336 N GLU A 45 -4.220 -0.483 -8.572 1.00 73.09 N \\nATOM 337 CA GLU A 45 -4.439 -1.686 -9.370 1.00 72.37 C \\nATOM 338 C GLU A 45 -5.852 -1.718 -9.943 1.00 72.92 C \\nATOM 339 CB GLU A 45 -4.182 -2.941 -8.532 1.00 69.91 C \\nATOM 340 O GLU A 45 -6.084 -2.302 -11.004 1.00 71.77 O \\nATOM 341 CG GLU A 45 -2.707 -3.234 -8.298 1.00 65.37 C \\nATOM 342 CD GLU A 45 -2.469 -4.459 -7.430 1.00 62.84 C \\nATOM 343 OE1 GLU A 45 -3.437 -4.968 -6.820 1.00 61.26 O \\nATOM 344 OE2 GLU A 45 -1.305 -4.913 -7.358 1.00 57.67 O \\nATOM 345 N ARG A 46 -6.746 -1.213 -9.196 1.00 72.48 N \\nATOM 346 CA ARG A 46 -8.117 -1.239 -9.693 1.00 71.19 C \\nATOM 347 C ARG A 46 -8.294 -0.274 -10.861 1.00 70.30 C \\nATOM 348 CB ARG A 46 -9.102 -0.893 -8.574 1.00 68.43 C \\nATOM 349 O ARG A 46 -9.281 -0.356 -11.596 1.00 67.62 O \\nATOM 350 CG ARG A 46 -9.252 -1.984 -7.526 1.00 64.68 C \\nATOM 351 CD ARG A 46 -10.310 -1.630 -6.490 1.00 62.70 C \\nATOM 352 NE ARG A 46 -9.869 -1.955 -5.137 1.00 52.56 N \\nATOM 353 NH1 ARG A 46 -11.980 -1.859 -4.203 1.00 46.86 N \\nATOM 354 NH2 ARG A 46 -10.165 -2.358 -2.895 1.00 43.74 N \\nATOM 355 CZ ARG A 46 -10.672 -2.057 -4.082 1.00 57.43 C \\nATOM 356 N HIS A 47 -7.201 0.509 -11.001 1.00 63.25 N \\nATOM 357 CA HIS A 47 -7.372 1.411 -12.134 1.00 63.43 C \\nATOM 358 C HIS A 47 -6.377 1.094 -13.245 1.00 61.36 C \\nATOM 359 CB HIS A 47 -7.216 2.866 -11.688 1.00 58.29 C \\nATOM 360 O HIS A 47 -6.706 1.206 -14.429 1.00 58.05 O \\nATOM 361 CG HIS A 47 -8.300 3.331 -10.768 1.00 54.95 C \\nATOM 362 CD2 HIS A 47 -8.262 3.709 -9.469 1.00 54.55 C \\nATOM 363 ND1 HIS A 47 -9.615 3.444 -11.165 1.00 53.98 N \\nATOM 364 CE1 HIS A 47 -10.340 3.874 -10.146 1.00 50.05 C \\nATOM 365 NE2 HIS A 47 -9.543 4.042 -9.105 1.00 45.43 N \\nTER 366 HIS A 47\\nEND\\n\"\n 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-e 1R42.pdb ]; then curl -O https://files.rcsb.org/download/1R42.pdb; fi\\n\\npdb=$(cat 1R42.pdb | grep ^ATOM | head -n 400 | awk '{printf \\\"%s\\\\\\\\n\\\", $0}')\\n\\nrequest='{\\n \\\"input_pdb\\\": \\\"'\\\"$pdb\\\"'\\\",\\n \\\"contigs\\\": \\\"A20-60/0 50-100\\\",\\n \\\"hotspot_res\\\": [\\\"A50\\\",\\\"A51\\\",\\\"A52\\\",\\\"A53\\\",\\\"A54\\\"],\\n \\\"diffusion_steps\\\": 15\\n}'\\ncurl -H 'Content-Type: application/json' \\\\\\n -H \\\"Authorization: Bearer $NVCF_RUN_KEY\\\" \\\\\\n -H \\\"nvcf-poll-seconds: 300\\\" \\\\\\n -d \\\"$request\\\" \\\"$URL\\\"\\n\",\"python\":\"#!/usr/bin/env python3\\nimport requests\\nimport os\\nimport json\\nfrom pathlib import Path\\n\\nkey = os.getenv(\\\"NVCF_RUN_KEY\\\") or input(\\\"Paste the Run Key: \\\")\\n\\ndef get_reduced_pdb():\\n pdb = Path(\\\"1R42.pdb\\\")\\n if not pdb.exists():\\n pdb.write_text(requests.get(f\\\"https://files.rcsb.org/download/{pdb}\\\").text)\\n lines = filter(lambda line: line.startswith(\\\"ATOM\\\"), pdb.read_text().split(\\\"\\\\n\\\"))\\n return \\\"\\\\n\\\".join(list(lines)[:400])\\n\\nr = requests.post(\\n url=os.getenv(\\\"URL\\\", \\\"https://health.api.nvidia.com/v1/biology/ipd/rfdiffusion/generate\\\"),\\n headers={\\\"Authorization\\\": f\\\"Bearer {key}\\\"},\\n json={\\n \\\"input_pdb\\\": get_reduced_pdb(),\\n \\\"contigs\\\": \\\"A20-60/0 50-100\\\",\\n \\\"hotspot_res\\\": [\\\"A50\\\",\\\"A51\\\",\\\"A52\\\",\\\"A53\\\",\\\"A54\\\"],\\n \\\"diffusion_steps\\\": 15,\\n },\\n)\\nprint(r, \\\"Saving to output.pdb:\\\\n\\\", r.text[:200], \\\"...\\\")\\nPath(\\\"output.pdb\\\").write_text(json.loads(r.text)[\\\"output_pdb\\\"])\\n\"}}]},\"description\":\"Generate new protein structures (binder designs, motif scaffoldings, etc.)\"}},\"/v1/health/live\":{\"get\":{\"summary\":\"Health Live\",\"description\":\"Handler for liveness endpoint.\",\"operationId\":\"health_live_v1_health_live_get\",\"responses\":{\"200\":{\"description\":\"Successful Response\",\"content\":{\"application/json\":{\"schema\":{}}}}}}},\"/v1/health/ready\":{\"get\":{\"summary\":\"Health Ready\",\"description\":\"Handler for readiness endpoint.\",\"operationId\":\"health_ready_v1_health_ready_get\",\"responses\":{\"200\":{\"description\":\"Successful Response\",\"content\":{\"application/json\":{\"schema\":{}}}}}}},\"/v1/metrics\":{\"get\":{\"summary\":\"Metrics\",\"description\":\"Handler for metrics endpoint.\",\"operationId\":\"metrics_v1_metrics_get\",\"responses\":{\"200\":{\"description\":\"Successful Response\",\"content\":{\"application/json\":{\"schema\":{\"type\":\"string\",\"title\":\"Response Metrics V1 Metrics Get\"}}}}}}},\"/v1/license\":{\"get\":{\"summary\":\"License\",\"description\":\"Handler for license endpoint.\",\"operationId\":\"license_v1_license_get\",\"responses\":{\"200\":{\"description\":\"Successful Response\",\"content\":{\"application/json\":{\"schema\":{}}}}}}},\"/v1/metadata\":{\"get\":{\"summary\":\"Metadata\",\"description\":\"Handler for metadata endpoint.\",\"operationId\":\"metadata_v1_metadata_get\",\"responses\":{\"200\":{\"description\":\"Successful Response\",\"content\":{\"application/json\":{\"schema\":{}}}}}}},\"/v1/manifest\":{\"get\":{\"summary\":\"Manifest\",\"description\":\"Handler for the manifest endpoint.\",\"operationId\":\"manifest_v1_manifest_get\",\"responses\":{\"200\":{\"description\":\"Successful Response\",\"content\":{\"application/json\":{\"schema\":{}}}}}}}},\"components\":{\"schemas\":{\"HTTPValidationError\":{\"properties\":{\"detail\":{\"items\":{\"$ref\":\"#/components/schemas/ValidationError\"},\"type\":\"array\",\"title\":\"Detail\"}},\"type\":\"object\",\"title\":\"HTTPValidationError\"},\"RFdiffusionInputs\":{\"properties\":{\"input_pdb\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Input protein content or file name\",\"description\":\"This is an input PDB (Protein Data Bank) file: protein chains and amino acids from this file are used to select binder target and motifs.\",\"numpy_dtype\":\"bytes\",\"triton_shape\":[1]},\"input_pdb_asset\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Input protein asset\",\"description\":\"Optional pre-uploaded NVCF Asset ID. If using this field, original file name should be provided via input_pdb argument.\",\"numpy_dtype\":\"bytes\",\"triton_shape\":[1]},\"contigs\":{\"type\":\"string\",\"title\":\"Contiguous Regions\",\"description\":\"Historically, contigs stands for 'contiguous [protein regions]'. This string defines a protein that is being generated. It is a specification written in a domain-specific language that tells RFdiffusion which part of the input protein are to be kept and what kind of a binder (or a scaffold) needs to be constructed. As an example, a string 'A10-100/0 50-150' instructs RFdiffusion to keep amino acids 10-100 in Chain A [from the input PDB file], then break the chain (special '/0' notation, which signifies the end of the chain and thus effectively makes 'A10-100' a new target protein), and construct a new chain (effectively a binder protein) of length 50 to 150 amino acids.\",\"numpy_dtype\":\"bytes\",\"triton_shape\":[1]},\"hotspot_res\":{\"anyOf\":[{\"items\":{\"type\":\"string\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Hotspot Residues\",\"description\":\"The hotspot residues string provides a way to specify which region the new protein (binder) must contact with the original input protein (a target), therefore we can guide a binder to a specific region. In UI, the format of the string is a comma-separated list of amino acids present in the input PDB file, e.g. 'A50,A51,A52' specifies three hotspot residues in the Chain A, at positions 50, 51 and 52. Note that in API, however, the amino acids are specified as a list of strings, e.g. ['A50', 'A51', ...].\",\"numpy_dtype\":\"bytes\",\"triton_shape\":[-1]},\"diffusion_steps\":{\"anyOf\":[{\"type\":\"integer\",\"maximum\":90,\"minimum\":15},{\"type\":\"null\"}],\"title\":\"Number of diffusion steps\",\"description\":\"RFdiffusion is a diffusion generative model, it was trained by diffusing (adding noise) to a training data set. The generative process works by reversing the time steps (i.e. denoising): starting from randomly placed atoms, and reverse-diffusing the positions to arrive at a probable atom positions. The diffusion steps parameter tells RFdiffusion how many steps it will run the denoising process for. 15 is the minimum, 50 is the default.\",\"default\":15,\"numpy_dtype\":\"uint16\",\"triton_shape\":[1]},\"random_seed\":{\"anyOf\":[{\"type\":\"integer\"},{\"type\":\"null\"}],\"title\":\"Random Seed\",\"description\":\"RFdiffusion is a generative model, its function is to generate novel and diverse proteins. Setting random seed allows to turn RFdiffusion into a deterministic model, where an input protein, a task and a fixed seed would always produce the same output. This argument is useful for development purposes, but otherwise should be unset.\",\"numpy_dtype\":\"int64\",\"triton_shape\":[1]}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"contigs\"],\"title\":\"RFdiffusionInputs\"},\"RFdiffusionOutputs\":{\"properties\":{\"output_pdb\":{\"type\":\"string\",\"title\":\"Output protein in PDB format\",\"description\":\"Output protein in PDB format\",\"numpy_dtype\":\"bytes\",\"triton_shape\":[1]},\"elapsed_ms\":{\"type\":\"integer\",\"title\":\"Elapsed time on server side\",\"description\":\"Elapsed time on server side\",\"numpy_dtype\":\"int64\",\"triton_shape\":[1]}},\"additionalProperties\":false,\"type\":\"object\",\"required\":[\"output_pdb\",\"elapsed_ms\"],\"title\":\"RFdiffusionOutputs\"},\"ValidationError\":{\"properties\":{\"loc\":{\"items\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"integer\"}]},\"type\":\"array\",\"title\":\"Location\"},\"msg\":{\"type\":\"string\",\"title\":\"Message\"},\"type\":{\"type\":\"string\",\"title\":\"Error Type\"}},\"type\":\"object\",\"required\":[\"loc\",\"msg\",\"type\"],\"title\":\"ValidationError\"}}}},\"namespace\":\"qc69jvmznzxy\",\"updatedDate\":\"2024-11-20T02:49:52.056Z\",\"nvcfFunctionId\":\"e469fc55-91c0-460d-a444-15d9921ac277\",\"createdDate\":\"2024-05-22T22:30:00.967Z\",\"attributes\":{\"dockerRun\":\"$d2\",\"dockerTermsOfUse\":\"By running the below commands, you accept the \u003ca href=\\\"https://www.nvidia.com/en-us/data-center/products/nvidia-ai-enterprise/eula/\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA AI Enterprise Terms of Use\u003c/a\u003e and the \u003ca href=\\\"https://docs.nvidia.com/ai-foundation-models-community-license.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA Community Models License\u003c/a\u003e.\\n\",\"requiresLogin\":false,\"showUnavailableBanner\":false,\"apiDocsUrl\":\"https://docs.api.nvidia.com/nim/reference/ipd-rfdiffusion\",\"termsOfUse\":\"\u003cb\u003eGOVERNING TERMS\u003c/b\u003e: Your use of this API is governed by the \u003ca href=\\\"https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA API Trial Service Terms of Use\u003c/a\u003e; and the use of this model is governed by the \u003ca href=\\\"https://docs.nvidia.com/ai-foundation-models-community-license.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA AI Foundation Models Community License\u003c/a\u003e and the \u003ca href=\\\"https://github.com/RosettaCommons/RFdiffusion?tab=License-1-ov-file#readme\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eBSD License\u003c/a\u003e.\\n\",\"projects\":[{\"name\":\"BioNemo Examples\",\"url\":\"https://github.com/NVIDIA/BioNeMo/tree/main/examples/nims\",\"imageUrl\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/github-logo.jpg\",\"workbench\":false}]},\"artifactName\":\"rfdiffusion\"},\"config\":{\"name\":\"rfdiffusion\",\"type\":\"model\"}},{\"endpoint\":{\"requestStatus\":{\"statusCode\":\"SUCCESS\",\"requestId\":\"bdaa924d-99b0-4d35-bcfb-043d5dce445f\"},\"artifact\":{\"orgName\":\"qc69jvmznzxy\",\"labels\":[\"Drug Discovery\",\"Molecule Generation\",\"Drug Discovery\"],\"bias\":\"Field | Response\\n:---------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------\\nParticipation considerations from adversely impacted groups ([protected classes](https://www.senate.ca.gov/content/protected-classes)) in model design and testing: | None of the above\\nMeasures taken to mitigate against unwanted bias: | None\",\"logo\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/molmim-generate.jpg\",\"shortDescription\":\"MolMIM performs controlled generation, finding molecules with the right properties.\",\"safetyAndSecurity\":\"Field | Response\\n:---------------------------------------------------|:----------------------------------\\nModel Application(s): | Small Molecular sampling and generation\\nDescribe the life-critical impacts (if present). | None \\nUse Case Restriction(s): | Abide by https://docs.nvidia.com/ai-foundation-models-community-license.pdf\\nModel and Dataset Restriction(s): | The Principle of least privilege (PoLP) is applied limiting access for dataset generation and model development. Restrictions enforce dataset access during training, and dataset license constraints adhered toThe Principle of least privilege (PoLP) is applied limiting access for dataset generation and model development. Restrictions enforce dataset access during training, and dataset license constraints adhered to.\",\"privacy\":\"$d3\",\"isReadOnly\":true,\"description\":\"$d4\",\"canGuestDownload\":true,\"isPublic\":true,\"createdDate\":\"2024-03-15T04:47:28.130Z\",\"publisher\":\"nvidia\",\"displayName\":\"molmim\",\"name\":\"molmim-generate\",\"explainability\":\"$d5\",\"updatedDate\":\"2024-11-20T02:28:43.241Z\",\"attributes\":[{\"key\":\"AVAILABLE\",\"value\":\"true\"},{\"key\":\"PREVIEW\",\"value\":\"false\"}],\"artifactType\":\"ENDPOINT\"}},\"spec\":{\"openAPISpec\":{\"openapi\":\"3.1.0\",\"info\":{\"title\":\"NVIDIA NIM API for MolMIM\",\"description\":\"The NVIDIA NIM REST API. Please see https://docs.api.nvidia.com/nim for more details.\",\"termsOfService\":\"https://nvidia.com/legal/terms-of-use\",\"contact\":{\"name\":\"NVIDIA Support\",\"url\":\"https://help.nvidia.com/\"},\"version\":\"0.0.1\",\"license\":{\"name\":\"Nvidia\",\"url\":\"TODO - Get the link\"}},\"servers\":[{\"url\":\"https://health.api.nvidia.com/v1/\"}],\"paths\":{\"/biology/nvidia/molmim/generate\":{\"post\":{\"tags\":[\"Default\"],\"summary\":\"Molecule Generation\",\"description\":\"Samples novel molecules around the encoded input SMILES.\",\"operationId\":\"molecule_generate\",\"requestBody\":{\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/MoleculeGenerationBody\"}}},\"required\":true},\"responses\":{\"200\":{\"description\":\"Successful Response\",\"content\":{\"application/json\":{\"schema\":{}}}},\"422\":{\"description\":\"Validation Error\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/HTTPValidationError\"}}}}},\"x-nvai-meta\":{\"name\":\"MolMIM moleculer generator\",\"returns\":\"Returns SMILES\",\"path\":\"decoder\",\"examples\":[{\"name\":\"Embeddings\",\"requestJson\":\"'{\\n \\\"algorithm\\\": \\\"CMA-ES\\\",\\n \\\"smi\\\": \\\"CCN=CC(C)NC1=CN(CCl)C1\\\",\\n \\\"iterations\\\": 1,\\n \\\"particles\\\": 20,\\n \\\"minimize\\\": true,\\n \\\"min_similarity\\\": 0.999,\\n \\\"num_samples\\\": 10\\n}'\",\"responseJson\":\"{\\n \\\"molecules\\\": \\\"[{\\\\\\\"sample\\\\\\\": \\\\\\\"CCNC1=C(Br)CN(CCCl)CC1\\\\\\\", \\\\\\\"score\\\\\\\": 0.18867924528301888}, {\\\\\\\"sample\\\\\\\": \\\\\\\"CCNC(=S)NCCN1CC=C(Cl)C1\\\\\\\", \\\\\\\"score\\\\\\\": 0.17857142857142858}, {\\\\\\\"sample\\\\\\\": \\\\\\\"CCN(CCCl)C1=NCC(C)=N1\\\\\\\", \\\\\\\"score\\\\\\\": 0.1568627450980392}, {\\\\\\\"sample\\\\\\\": \\\\\\\"C=CCn1nc(C)n(CCCl)c1=O\\\\\\\", \\\\\\\"score\\\\\\\": 0.14545454545454545}, {\\\\\\\"sample\\\\\\\": \\\\\\\"C=CCN1CCN(C/C(=C\\\\\\\\Cl)CNCC)CC1\\\\\\\", \\\\\\\"score\\\\\\\": 0.14035087719298245}, {\\\\\\\"sample\\\\\\\": \\\\\\\"CCNC(=O)NN=C1CCCC1\\\\\\\", \\\\\\\"score\\\\\\\": 0.13725490196078433}, {\\\\\\\"sample\\\\\\\": \\\\\\\"CNCCCN(C)C1=NCC(Cl)=CS1\\\\\\\", \\\\\\\"score\\\\\\\": 0.11864406779661017}, {\\\\\\\"sample\\\\\\\": \\\\\\\"C=CCNCCN1CC(CNC)C1\\\\\\\", \\\\\\\"score\\\\\\\": 0.10714285714285714}, {\\\\\\\"sample\\\\\\\": \\\\\\\"C=CCNCC(=O)NC(C)(C)CN1CCN(CCOC)CC1\\\\\\\", \\\\\\\"score\\\\\\\": 0.08955223880597014}, {\\\\\\\"sample\\\\\\\": \\\\\\\"C=CCN(CC=C)C1CSC1\\\\\\\", \\\\\\\"score\\\\\\\": 0.061224489795918366}]\\\",\\n \\\"score_type\\\": \\\"tanimoto_similarity\\\"\\n}\"}],\"templates\":[{\"title\":\"Synchronous requests\",\"requestEjs\":{\"curl\":\"invoke_url='https://health.api.nvidia.com/v1/biology/nvidia/molmim/generate'\\n\\nauthorization_header='Authorization: Bearer $NVIDIA_API_KEY'\\naccept_header='Accept: application/json'\\ncontent_type_header='Content-Type: application/json'\\n\\ndata='{\\n \\\"algorithm\\\": \\\"CMA-ES\\\",\\n \\\"num_molecules\\\": 30,\\n \\\"property_name\\\": \\\"QED\\\",\\n \\\"minimize\\\": false,\\n \\\"min_similarity\\\": 0.3,\\n \\\"particles\\\": 30,\\n \\\"iterations\\\": 10,\\n \\\"smi\\\": \\\"[H][C@@]12Cc3c[nH]c4cccc(C1=C[C@H](NC(=O)N(CC)CC)CN2C)c34\\\"\\n}'\\n\\nresponse=$(curl --silent -i -w \\\"\\n%{http_code}\\\" --request POST \\\\\\n --url \\\"$invoke_url\\\" \\\\\\n --header \\\"$authorization_header\\\" \\\\\\n --header \\\"$accept_header\\\" \\\\\\n --header \\\"$content_type_header\\\" \\\\\\n --data \\\"$data\\\"\\n)\\n\\necho \\\"$response\\\"\\n\",\"python\":\"import requests\\n\\ninvoke_url = \\\"https://health.api.nvidia.com/v1/biology/nvidia/molmim/generate\\\"\\n\\nheaders = {\\n \\\"Authorization\\\": \\\"Bearer $NVIDIA_API_KEY\\\",\\n \\\"Accept\\\": \\\"application/json\\\",\\n}\\n\\npayload = {\\n \\\"algorithm\\\": \\\"CMA-ES\\\",\\n \\\"num_molecules\\\": 30,\\n \\\"property_name\\\": \\\"QED\\\",\\n \\\"minimize\\\": False,\\n \\\"min_similarity\\\": 0.3,\\n \\\"particles\\\": 30,\\n \\\"iterations\\\": 10,\\n \\\"smi\\\": \\\"[H][C@@]12Cc3c[nH]c4cccc(C1=C[C@H](NC(=O)N(CC)CC)CN2C)c34\\\"\\n}\\n\\n# re-use connections\\nsession = requests.Session()\\n\\nresponse = session.post(invoke_url, headers=headers, json=payload)\\n\\nresponse.raise_for_status()\\nresponse_body = response.json()\\nprint(response_body)\\n\"}}]}}}},\"components\":{\"schemas\":{\"ControlGenerationAlgo\":{\"type\":\"string\",\"enum\":[\"CMA-ES\",\"none\"],\"title\":\"ControlGenerationAlgo\"},\"ControlGenerationProp\":{\"type\":\"string\",\"enum\":[\"QED\",\"plogP\"],\"title\":\"ControlGenerationProp\"},\"EmbeddingFormat\":{\"type\":\"string\",\"enum\":[\"npz\",\"h5\"],\"title\":\"EmbeddingFormat\"},\"HTTPValidationError\":{\"properties\":{\"detail\":{\"items\":{\"$ref\":\"#/components/schemas/ValidationError\"},\"type\":\"array\",\"title\":\"Detail\"}},\"type\":\"object\",\"title\":\"HTTPValidationError\"},\"MolecularDecodeRequest\":{\"properties\":{\"shape\":{\"anyOf\":[{\"items\":{\"type\":\"integer\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Shape\"},\"embeddings\":{\"anyOf\":[{\"items\":{\"type\":\"number\"},\"type\":\"array\"},{\"type\":\"null\"}],\"title\":\"Embeddings\"},\"asset_id\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"null\"}],\"title\":\"Asset Id\"},\"format\":{\"anyOf\":[{\"$ref\":\"#/components/schemas/EmbeddingFormat\"},{\"type\":\"null\"}],\"title\":\"Input format(npz|h5)\",\"description\":\"Input format\",\"default\":\"npz\"}},\"type\":\"object\",\"required\":[\"shape\",\"embeddings\"],\"title\":\"MolecularDecodeRequest\"},\"MolecularEmbeddingRequest\":{\"properties\":{\"smis\":{\"items\":{\"type\":\"string\",\"maxLength\":510,\"minLength\":1,\"pattern\":\"\\\\[[^\\\\]]+]|Br?|Cl?|N|O|S|P|F|I|b|c|n|o|s|p|\\\$|\\\$|\\\\.|=|#|-|\\\\+|\\\\\\\\|\\\\/|:|~|@|\\\\?|\u003e|\\\\*|\\\\$|\\\\%[0-9]{2}|[0-9]\"},\"type\":\"array\",\"maxItems\":32,\"minItems\":1,\"title\":\"SMILES\",\"description\":\"SMILES\"},\"format\":{\"allOf\":[{\"$ref\":\"#/components/schemas/EmbeddingFormat\"}],\"title\":\"Expected output format(npz|h5)\",\"description\":\"Expected embedding output format\",\"default\":\"npz\"}},\"type\":\"object\",\"required\":[\"smis\"],\"title\":\"MolecularEmbeddingRequest\"},\"MoleculeGenerationBody\":{\"properties\":{\"algorithm\":{\"allOf\":[{\"$ref\":\"#/components/schemas/ControlGenerationAlgo\"}],\"default\":\"CMA-ES\"},\"smi\":{\"type\":\"string\",\"title\":\"Smi\"},\"num_molecules\":{\"type\":\"integer\",\"maximum\":100,\"minimum\":1,\"title\":\"Num Molecules\",\"default\":10},\"iterations\":{\"type\":\"integer\",\"maximum\":1000,\"minimum\":1,\"title\":\"Iterations\",\"default\":10},\"property_name\":{\"allOf\":[{\"$ref\":\"#/components/schemas/ControlGenerationProp\"}],\"default\":\"QED\"},\"particles\":{\"type\":\"integer\",\"maximum\":1000,\"minimum\":2,\"title\":\"Particles\",\"default\":20},\"minimize\":{\"type\":\"boolean\",\"title\":\"Minimize\",\"default\":false},\"min_similarity\":{\"type\":\"number\",\"maximum\":1,\"minimum\":0,\"title\":\"Min Similarity\",\"default\":0.7},\"scaled_radius\":{\"type\":\"number\",\"maximum\":2,\"minimum\":0,\"title\":\"Scaled Radius\",\"default\":1}},\"type\":\"object\",\"title\":\"MoleculeGenerationBody\"},\"ValidationError\":{\"properties\":{\"loc\":{\"items\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"integer\"}]},\"type\":\"array\",\"title\":\"Location\"},\"msg\":{\"type\":\"string\",\"title\":\"Message\"},\"type\":{\"type\":\"string\",\"title\":\"Error Type\"}},\"type\":\"object\",\"required\":[\"loc\",\"msg\",\"type\"],\"title\":\"ValidationError\"}}}},\"namespace\":\"qc69jvmznzxy\",\"updatedDate\":\"2024-11-20T02:28:43.915Z\",\"nvcfFunctionId\":\"72be0b68-179f-412c-ac03-9a481f78cb9f\",\"createdDate\":\"2024-03-15T04:47:28.595Z\",\"attributes\":{\"dockerRun\":\"$d6\",\"dockerTermsOfUse\":\"By running the below commands, you accept the \u003ca href=\\\"https://www.nvidia.com/en-us/data-center/products/nvidia-ai-enterprise/eula/\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA AI Enterprise Terms of Use\u003c/a\u003e and the \u003ca href=\\\"https://docs.nvidia.com/ai-foundation-models-community-license.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA Community Models License\u003c/a\u003e.\\n\",\"requiresLogin\":false,\"showUnavailableBanner\":false,\"apiDocsUrl\":\"https://docs.api.nvidia.com/nim/reference/nvidia-molmlm\",\"termsOfUse\":\"\u003cb\u003eGOVERNING TERMS\u003c/b\u003e: Your use of this API is governed by the \u003ca href=\\\"https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA API Trial Service Terms of Use\u003c/a\u003e; and the use of this model is governed by the \u003ca href=\\\"https://docs.nvidia.com/ai-foundation-models-community-license.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA AI Foundation Models Community License\u003c/a\u003e.\\n\",\"cta\":{\"text\":\"Build with this NIM\",\"url\":\"https://www.nvidia.com/en-us/ai/nim-notifyme/\",\"nim_available_override_url\":\"https://catalog.ngc.nvidia.com/orgs/nim/teams/nvidia/containers/molmim\"},\"projects\":[{\"name\":\"BioNemo Examples\",\"url\":\"https://github.com/NVIDIA/BioNeMo/tree/main/examples/nims\",\"imageUrl\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/github-logo.jpg\",\"workbench\":false}]},\"artifactName\":\"molmim-generate\"},\"config\":{\"name\":\"molmim-generate\",\"type\":\"model\"}},{\"endpoint\":{\"requestStatus\":{\"statusCode\":\"SUCCESS\",\"requestId\":\"517c633a-b35b-47eb-879a-539cc7845496\"},\"artifact\":{\"orgName\":\"qc69jvmznzxy\",\"labels\":[\"Docking\",\"Drug Discovery\",\"Drug Discovery\"],\"logo\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/diffdock.jpg\",\"shortDescription\":\"Predicts the 3D structure of how a molecule interacts with a protein.\",\"isReadOnly\":true,\"description\":\"$d7\",\"canGuestDownload\":true,\"isPublic\":true,\"createdDate\":\"2024-03-15T04:47:25.901Z\",\"publisher\":\"mit\",\"displayName\":\"diffdock\",\"name\":\"diffdock\",\"updatedDate\":\"2024-10-30T22:38:57.723Z\",\"attributes\":[{\"key\":\"AVAILABLE\",\"value\":\"true\"},{\"key\":\"PREVIEW\",\"value\":\"false\"}],\"artifactType\":\"ENDPOINT\"}},\"spec\":{\"openAPISpec\":{\"openapi\":\"3.1.0\",\"info\":{\"title\":\"NVIDIA NIM API for DiffDock\",\"description\":\"The NVIDIA NIM REST API. Please see https://docs.api.nvidia.com/nim for more details.\",\"termsOfService\":\"https://nvidia.com/legal/terms-of-use\",\"contact\":{\"name\":\"NVIDIA Support\",\"url\":\"https://help.nvidia.com/\"},\"version\":\"0.0.1\",\"license\":{\"name\":\"MIT\",\"url\":\"https://github.com/gcorso/DiffDock?tab=MIT-1-ov-file#readme\"}},\"servers\":[{\"url\":\"https://health.api.nvidia.com/v1/\"}],\"paths\":{\"/biology/mit/diffdock\":{\"post\":{\"tags\":[\"Default\"],\"summary\":\"Molecular Docking Pose Generation\",\"description\":\"Predict molecular docking\",\"operationId\":\"molecular_docking\",\"requestBody\":{\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/MolecularDockingRequest\"}}},\"required\":true},\"responses\":{\"200\":{\"description\":\"Successful Response\",\"content\":{\"application/json\":{\"schema\":{}}}},\"422\":{\"description\":\"Validation Error\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/HTTPValidationError\"}}}}},\"x-nvai-meta\":{\"name\":\"Generate docking post\",\"returns\":\"Returns predicted molecular docking poses of input ligand in the input protein.\",\"path\":\"generate\",\"examples\":[{\"name\":\"Predict ligand poses\",\"requestJson\":\"$d8\",\"responseJson\":\"$d9\"}],\"templates\":[{\"title\":\"Synchronous requests\",\"requestEjs\":{\"python\":\"$da\",\"node.js\":\"$db\",\"curl\":\"$dc\"}}]}}}},\"components\":{\"schemas\":{\"HTTPValidationError\":{\"properties\":{\"detail\":{\"items\":{\"$ref\":\"#/components/schemas/ValidationError\"},\"type\":\"array\",\"title\":\"Detail\"}},\"type\":\"object\",\"title\":\"HTTPValidationError\"},\"LigandFormat\":{\"type\":\"string\",\"enum\":[\"mol2\",\"sdf\"],\"title\":\"LigandFormat\"},\"MolecularDockingRequest\":{\"properties\":{\"ligand\":{\"type\":\"string\",\"title\":\"Ligand(mol2, SDF or NVCF Asset)\",\"description\":\"Ligand to be docked. Mol2 string or NVCF asset id\"},\"ligand_file_type\":{\"allOf\":[{\"$ref\":\"#/components/schemas/LigandFormat\"}],\"title\":\"Ligand data Format (mol2 or SDF)\",\"description\":\"Ligand(mol2) to be docked. Mol2 string or NVCF asset id\"},\"protein\":{\"type\":\"string\",\"title\":\"Protein(PDB)\",\"description\":\"Protein(PDB). PDB string or NVCF asset id\"},\"num_poses\":{\"type\":\"integer\",\"maximum\":100,\"minimum\":1,\"title\":\"Number of poses\",\"description\":\"Number of poses to generate\",\"default\":20},\"time_divisions\":{\"type\":\"integer\",\"maximum\":20,\"minimum\":3,\"title\":\"Number of diffusion time divisions\",\"description\":\"Number of diffusion time divisions\",\"default\":20},\"steps\":{\"type\":\"integer\",\"maximum\":18,\"minimum\":1,\"title\":\"Number of diffusion steps\",\"description\":\"Number of diffusion steps to be computed\",\"default\":18},\"save_trajectory\":{\"type\":\"boolean\",\"title\":\"Return the trajectory\",\"description\":\"Return the trajectory\",\"default\":false},\"is_staged\":{\"type\":\"boolean\",\"title\":\"Is staged?\",\"description\":\"Are the files for ligand and protein staged?\",\"default\":true}},\"type\":\"object\",\"required\":[\"ligand\",\"ligand_file_type\",\"protein\"],\"title\":\"MolecularDockingRequest\"},\"ValidationError\":{\"properties\":{\"loc\":{\"items\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"integer\"}]},\"type\":\"array\",\"title\":\"Location\"},\"msg\":{\"type\":\"string\",\"title\":\"Message\"},\"type\":{\"type\":\"string\",\"title\":\"Error Type\"}},\"type\":\"object\",\"required\":[\"loc\",\"msg\",\"type\"],\"title\":\"ValidationError\"}}}},\"namespace\":\"qc69jvmznzxy\",\"updatedDate\":\"2024-10-30T22:38:58.699Z\",\"nvcfFunctionId\":\"f3dda972-561a-4772-8c09-873594b6fb72\",\"createdDate\":\"2024-03-15T04:47:26.695Z\",\"attributes\":{\"dockerRun\":\"$dd\",\"dockerTermsOfUse\":\"By running the below commands, you accept the \u003ca href=\\\"https://www.nvidia.com/en-us/data-center/products/nvidia-ai-enterprise/eula/\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA AI Enterprise Terms of Use\u003c/a\u003e and the \u003ca href=\\\"https://docs.nvidia.com/ai-foundation-models-community-license.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA Community Models License\u003c/a\u003e.\\n\",\"requiresLogin\":false,\"showUnavailableBanner\":false,\"apiDocsUrl\":\"https://docs.api.nvidia.com/nim/reference/mit-diffdock\",\"termsOfUse\":\"\u003cb\u003eGOVERNING TERMS\u003c/b\u003e: Your use of this API is governed by the \u003ca href=\\\"https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA API Trial Service Terms of Use\u003c/a\u003e; and the use of this model is governed by the \u003ca href=\\\"https://docs.nvidia.com/ai-foundation-models-community-license.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA AI Foundation Models Community License\u003c/a\u003e and \u003ca href=\\\"https://opensource.org/license/MIT\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eMIT License\u003c/a\u003e.\\n\",\"cta\":{\"text\":\"Build with this NIM\",\"url\":\"https://www.nvidia.com/en-us/ai/nim-notifyme/\",\"nim_available_override_url\":\"https://catalog.ngc.nvidia.com/orgs/nim/teams/mit/containers/diffdock\"},\"projects\":[{\"name\":\"BioNemo Examples\",\"url\":\"https://github.com/NVIDIA/BioNeMo/tree/main/examples/nims\",\"imageUrl\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/github-logo.jpg\",\"workbench\":false}]},\"artifactName\":\"diffdock\"},\"config\":{\"name\":\"diffdock\",\"type\":\"model\"}},{\"endpoint\":{\"requestStatus\":{\"statusCode\":\"SUCCESS\",\"requestId\":\"d55388cb-c9fd-4c89-a9e4-7cb7a1a204fe\"},\"artifact\":{\"orgName\":\"qc69jvmznzxy\",\"labels\":[\"Drug Discovery\",\"Protein Folding\",\"Drug Discovery\"],\"logo\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/esmfold.jpg\",\"shortDescription\":\"Predicts the 3D structure of a protein from its amino acid sequence.\",\"isReadOnly\":true,\"description\":\"$de\",\"canGuestDownload\":true,\"isPublic\":true,\"createdDate\":\"2024-03-15T04:47:26.399Z\",\"publisher\":\"meta\",\"displayName\":\"esmfold\",\"name\":\"esmfold\",\"updatedDate\":\"2024-09-11T19:41:48.132Z\",\"attributes\":[{\"key\":\"PREVIEW\",\"value\":\"true\"}],\"artifactType\":\"ENDPOINT\"}},\"spec\":{\"openAPISpec\":{\"openapi\":\"3.1.0\",\"info\":{\"title\":\"NVIDIA NIM API for ESMFold\",\"description\":\"The NVIDIA NIM REST API. Please see https://docs.api.nvidia.com/nim for more details.\",\"termsOfService\":\"https://nvidia.com/legal/terms-of-use\",\"contact\":{\"name\":\"NVIDIA Support\",\"url\":\"https://help.nvidia.com/\"},\"version\":\"0.0.1\",\"license\":{\"name\":\"MIT\",\"url\":\"https://github.com/facebookresearch/esm/blob/main/LICENSE\"}},\"servers\":[{\"url\":\"https://health.api.nvidia.com/v1/\"}],\"paths\":{\"/biology/nvidia/esmfold\":{\"post\":{\"tags\":[\"Default\"],\"summary\":\"Protein Structure Prediction (Alignment-free)\",\"description\":\"Call predict function of a model that does not use multiple sequence alignments for prediction\",\"operationId\":\"protein_structure_predict_no_aln\",\"requestBody\":{\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/ProteinStructurePredictRequest\"}}},\"required\":true},\"responses\":{\"200\":{\"description\":\"Successful Response\",\"content\":{\"application/json\":{\"schema\":{}}}},\"422\":{\"description\":\"Validation Error\",\"content\":{\"application/json\":{\"schema\":{\"$ref\":\"#/components/schemas/HTTPValidationError\"}}}}},\"x-nvai-meta\":{\"name\":\"Predict protein 3D structure\",\"returns\":\"Returns the predicted 3D structure of input protein sequence.\",\"path\":\"predict\",\"examples\":[{\"name\":\"Predict protein 3D structure\",\"requestJson\":\"'MSLKRKNIALIPAAGIGVRFGADKPKQYVEIGSKTVLEHVLGIFERH'\",\"responseJson\":\"$df\"}],\"templates\":[{\"title\":\"Synchronous requests\",\"requestEjs\":{\"curl\":\"invoke_url='https://health.api.nvidia.com/v1/biology/nvidia/esmfold'\\n\\nauthorization_header='Authorization: Bearer $NVIDIA_API_KEY'\\naccept_header='Accept: application/json'\\ncontent_type_header='Content-Type: application/json'\\n\\ndata='{\\n \\\"sequence\\\": \\\"MDILCEENTSLSSTTNSLMQLNDDTRLYSNDFNSGEANTSDAFNWTVDSENRTNLSCEGCLSPSCLSLLHLQEKNWSALLTAVVIILTIAGNILVIMAVSLEKKLQNATNYFLMSLAIADMLLGFLVMPVSMLTILYGYRWPLPSKLCAVWIYLDVLFSTASIMHLCAISLDRYVAIQNPIHHSRFNSRTKAFLKIIAVWTISVGISMPIPVFGLQDDSKVFKEGSCLLADDNFVLIGSFVSFFIPLTIMVITYFLTIKSLQKEATLCVSDLGTRAKLASFSFLPQSSLSSEKLFQRSIHREPGSYTGRRTMQSISNEQKACKVLGIVFFLFVVMWCPFFITNIMAVICKESCNEDVIGALLNVFVWIGYLSSAVNPLVYTLFNKTYRSAFSRYIQCQYKENKKPLQLILVNTIPALAYKSSQLQMGQKKNSKQDAKTTDNDCSMVALGKQHSEEASKDNSDGVNEKVSCV\\\"\\n}'\\n\\nresponse=$(curl --silent -i -w \\\"\\n%{http_code}\\\" --request POST \\\\\\n --url \\\"$invoke_url\\\" \\\\\\n --header \\\"$authorization_header\\\" \\\\\\n --header \\\"$accept_header\\\" \\\\\\n --header \\\"$content_type_header\\\" \\\\\\n --data \\\"$data\\\"\\n)\\n\\necho \\\"$response\\\"\\n \",\"python\":\"import requests\\n\\ninvoke_url = \\\"https://health.api.nvidia.com/v1/biology/nvidia/esmfold\\\"\\n\\nheaders = {\\n \\\"Authorization\\\": \\\"Bearer $NVIDIA_API_KEY\\\",\\n \\\"Accept\\\": \\\"application/json\\\",\\n}\\n\\npayload = {\\n \\\"sequence\\\": \\\"MDILCEENTSLSSTTNSLMQLNDDTRLYSNDFNSGEANTSDAFNWTVDSENRTNLSCEGCLSPSCLSLLHLQEKNWSALLTAVVIILTIAGNILVIMAVSLEKKLQNATNYFLMSLAIADMLLGFLVMPVSMLTILYGYRWPLPSKLCAVWIYLDVLFSTASIMHLCAISLDRYVAIQNPIHHSRFNSRTKAFLKIIAVWTISVGISMPIPVFGLQDDSKVFKEGSCLLADDNFVLIGSFVSFFIPLTIMVITYFLTIKSLQKEATLCVSDLGTRAKLASFSFLPQSSLSSEKLFQRSIHREPGSYTGRRTMQSISNEQKACKVLGIVFFLFVVMWCPFFITNIMAVICKESCNEDVIGALLNVFVWIGYLSSAVNPLVYTLFNKTYRSAFSRYIQCQYKENKKPLQLILVNTIPALAYKSSQLQMGQKKNSKQDAKTTDNDCSMVALGKQHSEEASKDNSDGVNEKVSCV\\\"\\n}\\n\\n# re-use connections\\nsession = requests.Session()\\n\\nresponse = session.post(invoke_url, headers=headers, json=payload)\\n\\nresponse.raise_for_status()\\nresponse_body = response.json()\\nprint(response_body)\\n\"}}]}}}},\"components\":{\"schemas\":{\"HTTPValidationError\":{\"properties\":{\"detail\":{\"items\":{\"$ref\":\"#/components/schemas/ValidationError\"},\"type\":\"array\",\"title\":\"Detail\"}},\"type\":\"object\",\"title\":\"HTTPValidationError\"},\"ProteinStructurePredictRequest\":{\"properties\":{\"sequence\":{\"type\":\"string\",\"maxLength\":1024,\"minLength\":1,\"pattern\":\"^[ARNDCQEGHILKMFPSTWYV]*$\",\"title\":\"Amino acid sequence\",\"description\":\"Amino acid sequence of a protein\"}},\"type\":\"object\",\"required\":[\"sequence\"],\"title\":\"ProteinStructurePredictRequest\"},\"ValidationError\":{\"properties\":{\"loc\":{\"items\":{\"anyOf\":[{\"type\":\"string\"},{\"type\":\"integer\"}]},\"type\":\"array\",\"title\":\"Location\"},\"msg\":{\"type\":\"string\",\"title\":\"Message\"},\"type\":{\"type\":\"string\",\"title\":\"Error Type\"}},\"type\":\"object\",\"required\":[\"loc\",\"msg\",\"type\"],\"title\":\"ValidationError\"}}}},\"namespace\":\"qc69jvmznzxy\",\"updatedDate\":\"2024-09-11T19:41:48.735Z\",\"nvcfFunctionId\":\"a68c59e0-47a6-4a50-bf64-6d88766d56bf\",\"createdDate\":\"2024-03-15T04:47:26.839Z\",\"attributes\":{\"requiresLogin\":false,\"showUnavailableBanner\":false,\"apiDocsUrl\":\"https://docs.api.nvidia.com/nim/reference/meta-esmfold\",\"termsOfUse\":\"\u003cb\u003eGOVERNING TERMS\u003c/b\u003e: Your use of this API is governed by the \u003ca href=\\\"https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA API Trial Service Terms of Use\u003c/a\u003e; and the use of this model is governed by the \u003ca href=\\\"https://docs.nvidia.com/ai-foundation-models-community-license.pdf\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eNVIDIA AI Foundation Models Community License\u003c/a\u003e and \u003ca href=\\\"https://opensource.org/license/MIT\\\" rel=\\\"noreferrer\\\" target=\\\"_blank\\\"\u003eMIT License\u003c/a\u003e.\\n\",\"cta\":{\"text\":\"Apply to Self-Host\",\"url\":\"https://www.nvidia.com/en-us/ai/nim-notifyme/\"},\"projects\":[{\"name\":\"BioNemo Examples\",\"url\":\"https://github.com/NVIDIA/BioNeMo/tree/main/examples/nims\",\"imageUrl\":\"https://assets.ngc.nvidia.com/products/api-catalog/images/github-logo.jpg\",\"workbench\":false}]},\"artifactName\":\"esmfold\"},\"config\":{\"name\":\"esmfold\",\"type\":\"model\"}}]}]\n"])</script></body></html>

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