3D molecular design and visualisation

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See what life is like at Optibrium and browse our jobs</div> <div id='header-sub-menu-1705' class='sub-menu-outer'><div class='sub-menu-inner'><ul class='sub-menu'> <li id="menu-item-1835" class="menu-item menu-item-type-post_type menu-item-object-page menu-item-1835"><a href="https://optibrium.com/jobs/">Browse jobs</a></li> </ul></div></div> </li> <li id="menu-item-1711" class="menu-item menu-item-type-post_type menu-item-object-page has-icon menu-item-1711"><div class="menu-item-heading"><a class="menu-item-has-icon" href="https://optibrium.com/about-optibrium/contact-us/">Contact us<span class="menu-item-icon img-fit" aria-hidden="true" style="mask-image: url('https://optibrium.com/wp-content/themes/optibrium/assets/images/theme-icons/email.svg')"></span></a></div><div class="menu-item-content nflm">Our global team is always here to talk and there are a number of ways to get in touch</div></li> </ul></div></div> </li> </ul> <div class="header-search"> <button class="header-search__toggle" type="button" aria-controls="header-search-outer" aria-expanded="false" aria-label="Toggle search"></button> <div id="header-search-outer" class="header-search__outer"> <div class="header-search__inner"> <form role="search" method="get" class="search-form" action="https://optibrium.com/"> <label> <span class="screen-reader-text">Search for:</span> <input type="search" class="search-field" placeholder="Enter a search word..." value="" name="s" /> </label> <input type="submit" class="search-submit" value="Search" /> </form> </div> </div> </div> </div> </div> </nav> </div> </header> <main id="main" class="site-main nflm"> <div class="site-main__inner"> <div class="site-main__content blocks"> <div class="page-header wp-block alignfull has-breadcrumbs is-style-equal"> <div class="page-header__wrapper"> <div class="page-header__outer"> <nav class="breadcrumbs" aria-label="breadcrumbs"> <span class="breadcrumbs__yoast-wrapper"><span><a href="https://optibrium.com/">Home</a></span> <span class="breadcrumbs__yoast-separator"></span> <span><a href="https://optibrium.com/solutions/">Solutions</a></span> <span class="breadcrumbs__yoast-separator"></span> <span class="breadcrumb_last" aria-current="page">3D molecular design and visualisation</span></span></nav> <div class="page-header__inner"> <h1 class="page-header__heading">3D molecular design and visualisation</h1> <div class="page-header__content nflm"> <p>Understand structure-activity and structure-property relationships in 3D, with cutting-edge computational modelling. Overcome challenges around predicting conformations and binding affinities with our range of software solutions, supporting your drug discovery from small molecules to large peptidic macrocycles.</p> </div> </div> </div> </div> </div> <section class="flags wp-block has-even-items alignfull"> <div class="flags__outer"> <div class="flags__inner"> <div class="flags__items"> <div class="flags__item"> <div class="flags__item-inner nflm"> <h2 class="flags__item-heading is-style-typestyle-h3 has-tags"> From 2D to 3D </h2> <div class="flags__item-content nflm"> <p>Going from a flat, 2D image of a molecule to a useful 3D model requires accurate generation of low-energy conformational ensembles, factoring in chirality and protonation at physiological pH. Our <a href="https://optibrium.com/products/biopharmics/">BioPharmics</a> platform includes the ForceGen methodology for fast, accurate and template-free conformer generation, even on complex macrocycles.</p> </div> <div class="flags__item-pills nflm"> <ul class="flags__item-pills-list"> <li> <a href="https://optibrium.com/methodology/forcegen/" class="g-button is-small">BioPharmics – ForceGen</a> </li> <li> </li> </ul> </div> </div> <div class="flags__item-media"> <div class="flags__item-media-inner "> <div class="img-fit"><img decoding="async" width="768" height="768" src="data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHZpZXdCb3g9IjAgMCAxMDAwIDEwMDAiIHdpZHRoPSIxMDAwIiBoZWlnaHQ9IjEwMDAiIGRhdGEtdT0iaHR0cHMlM0ElMkYlMkZvcHRpYnJpdW0uY29tJTJGd3AtY29udGVudCUyRnVwbG9hZHMlMkYyMDI0JTJGMDUlMkZmb3JjZWdlbl9zcV9oZF92Mi5qcGciIGRhdGEtdz0iMTAwMCIgZGF0YS1oPSIxMDAwIj48L3N2Zz4=" data-spai="1" class="attachment-medium_large size-medium_large" alt="ForceGen in action modelling macrocyclic compounds" srcset=" " sizes="auto, (max-width: 768px) 100vw, 768px" /></div> </div> </div> </div> <div class="flags__item"> <div class="flags__item-inner nflm"> <h2 class="flags__item-heading is-style-typestyle-h3 has-tags"> Structure-based drug design <span>that works</span> </h2> <div class="flags__item-content nflm"> <p>Setting up docking models can be time-consuming, and the results are often unreliable. With Surflex-Dock, you can enhance your workflows and make docking easier with robust, automated docking procedures and easy-to-use workflows, providing top-tier enrichment. This means you’ll find more active compounds when you screen the top-ranked compounds.</p> <p>With Surflex-Dock, ensembles of protein conformations take into account the variability in the binding pocket and relevant interactions to give a more realistic picture of molecular docking and further enhance the performance of virtual screens.</p> <p>And to guide the design of more potent compounds, you’ll need accurate non-cognate ligand docking to correctly predict the poses of new ligands for your protein target. The unique combination of eSim and Surflex-Dock in the BioPharmics platform offers industry-leading pose prediction, helping you quickly reach high-affinity compounds.</p> </div> <div class="flags__item-pills nflm"> <ul class="flags__item-pills-list"> <li> <a href="https://optibrium.com/methodology/surflex-dock/" class="g-button is-small">BioPharmics – Surflex-Dock</a> </li> <li> <a href="https://optibrium.com/products/stardrop/modules/seesar/" class="g-button is-small">StarDrop – SeeSAR</a> </li> </ul> </div> </div> <div class="flags__item-media"> <div class="flags__item-media-inner "> <div class="img-fit"><img decoding="async" width="768" height="704" src="data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHZpZXdCb3g9IjAgMCAxMTc4IDEwODAiIHdpZHRoPSIxMTc4IiBoZWlnaHQ9IjEwODAiIGRhdGEtdT0iaHR0cHMlM0ElMkYlMkZvcHRpYnJpdW0uY29tJTJGd3AtY29udGVudCUyRnVwbG9hZHMlMkYyMDI0JTJGMDUlMkZTdXJmbGV4LURvY2tfc3EucG5nIiBkYXRhLXc9IjExNzgiIGRhdGEtaD0iMTA4MCI+PC9zdmc+" data-spai="1" class="attachment-medium_large size-medium_large" alt="Docking as studied using the Surflex-Dock" srcset=" " sizes="auto, (max-width: 768px) 100vw, 768px" /></div> </div> </div> </div> <div class="flags__item"> <div class="flags__item-inner nflm"> <h2 class="flags__item-heading is-style-typestyle-h3 has-tags"> No target structure? <span>No problem</span> </h2> <div class="flags__item-content nflm"> <p>In some projects, you may have little or no target structural information. 3D ligand-based drug design can overcome these challenges.</p> <p>Ligand-based methods such as eSim can create a surface representation of the molecule based on shape, electrostatic field, and hydrogen-bond preferences to assess the similarity of new compounds with a known active. eSim offers unparalleled accuracy in virtual screening and pose prediction, helping you find and optimise novel, active compounds more quickly. And, if you have more than one active ligand, eSim can find binding hypotheses that explain their common activity, helping you to understand the SAR for your target and giving even better results for virtual screening.</p> <p><a class="g-button has-arrow" href="https://optibrium.com/webinars/challenges-and-approaches-in-3d-ligand-based-drug-design/">Watch our webinar on ligand-based drug design</a></p> </div> <div class="flags__item-pills nflm"> <ul class="flags__item-pills-list"> <li> <a href="https://optibrium.com/products/biopharmics/#methodology" class="g-button is-small">BioPharmics – eSim</a> </li> <li> <a href="https://optibrium.com/products/stardrop/modules/esim3d/" class="g-button is-small">StarDrop – eSim</a> </li> </ul> </div> </div> <div class="flags__item-media"> <div class="flags__item-media-inner "> <div class="img-fit"><img decoding="async" width="768" height="768" src="data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHZpZXdCb3g9IjAgMCAxMDAwIDEwMDAiIHdpZHRoPSIxMDAwIiBoZWlnaHQ9IjEwMDAiIGRhdGEtdT0iaHR0cHMlM0ElMkYlMkZvcHRpYnJpdW0uY29tJTJGd3AtY29udGVudCUyRnVwbG9hZHMlMkYyMDI0JTJGMDUlMkZlc2ltX3NxX2hkLmpwZyIgZGF0YS13PSIxMDAwIiBkYXRhLWg9IjEwMDAiPjwvc3ZnPg==" data-spai="1" class="attachment-medium_large size-medium_large" alt="eSim molecular similarity model" srcset=" " sizes="auto, (max-width: 768px) 100vw, 768px" /></div> </div> </div> </div> <div class="flags__item"> <div class="flags__item-inner nflm"> <h2 class="flags__item-heading is-style-typestyle-h3 has-tags"> <span>Accurate</span> affinity prediction </h2> <div class="flags__item-content nflm"> <p><span data-contrast="auto">Predicting the affinity of new compounds is a big challenge. Using the BioPharmics QuanSA (Quantitative Surface-field Analysis) method, you can predict binding affinity with equivalent accuracy to market-leading structure-based methods such as FEP+ and with greater transferability to novel chemistries. This unique, ligand-based approach enables you to build accurate affinity models, even in the absence of protein structure information and with only a small number of known actives, to find novel active compounds.</span><span data-ccp-props="{"201341983":0,"335559739":160,"335559740":259}"> </span></p> <p><span data-contrast="auto">QuanSA’s multiple-instance machine learning models are physically motivated, accurate, and scaffold-independent. QuanSA also provides prediction confidence metrics, enabling you to confidently predict ligand binding affinity and pose.</span></p> </div> <div class="flags__item-pills nflm"> <ul class="flags__item-pills-list"> <li> <a href="https://optibrium.com/methodology/quansa/" class="g-button is-small">BioPharmics – QuanSA</a> </li> </ul> </div> </div> <div class="flags__item-media"> <div class="flags__item-media-inner "> <div class="img-fit"><img decoding="async" width="768" height="768" src="data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHZpZXdCb3g9IjAgMCAxMDAwIDEwMDAiIHdpZHRoPSIxMDAwIiBoZWlnaHQ9IjEwMDAiIGRhdGEtdT0iaHR0cHMlM0ElMkYlMkZvcHRpYnJpdW0uY29tJTJGd3AtY29udGVudCUyRnVwbG9hZHMlMkYyMDI0JTJGMDUlMkZxdWFuc2Ffc3FfaGQuanBnIiBkYXRhLXc9IjEwMDAiIGRhdGEtaD0iMTAwMCI+PC9zdmc+" data-spai="1" class="attachment-medium_large size-medium_large" alt="A QuanSA pocket field model" srcset=" " sizes="auto, (max-width: 768px) 100vw, 768px" /></div> </div> </div> </div> <div class="flags__item"> <div class="flags__item-inner nflm"> <h2 class="flags__item-heading is-style-typestyle-h3 has-tags"> Macrocycle modelling <span>made simple</span> </h2> <div class="flags__item-content nflm"> <p>Macrocycles hold vast potential against previously “undruggable” targets. But the size and complexity of these molecules means that their design and optimisation is far from easy. To accelerate macrocyclic lead optimisation, you can accurately predict the conformations and properties of macrocycles with the BioPharmics platform.</p> <p>The BioPharmics platform enables you to apply biophysical constraints to help model very large peptidic macrocycles. You can access different modelling methods including both structure-based and ligand-based machine learning approaches, to support your macrocyclic discovery projects.</p> <p><a class="g-button has-arrow" href="https://optibrium.com/webinars/macrocyclic-lead-optimisation/">Watch our webinar on macrocyclic lead optimisation</a></p> </div> </div> <div class="flags__item-media"> <div class="flags__item-media-inner "> <div class="img-fit"><img decoding="async" width="768" height="768" src="data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHZpZXdCb3g9IjAgMCAxMDAwIDEwMDAiIHdpZHRoPSIxMDAwIiBoZWlnaHQ9IjEwMDAiIGRhdGEtdT0iaHR0cHMlM0ElMkYlMkZvcHRpYnJpdW0uY29tJTJGd3AtY29udGVudCUyRnVwbG9hZHMlMkYyMDI0JTJGMDUlMkZmb3JjZWdlbl9zcV9oZC5qcGciIGRhdGEtdz0iMTAwMCIgZGF0YS1oPSIxMDAwIj48L3N2Zz4=" data-spai="1" class="attachment-medium_large size-medium_large" alt="macrocycle with forcegen" srcset=" " sizes="auto, (max-width: 768px) 100vw, 768px" /></div> </div> </div> </div> <div class="flags__item"> <div class="flags__item-inner nflm"> <h2 class="flags__item-heading is-style-typestyle-h3 has-tags"> <span>Seamlessly link</span> 2D and 3D SAR </h2> <div class="flags__item-content nflm"> <p>Linking 3D structure- and ligand-based design with predictive modelling and SAR analysis gives you a comprehensive picture of the activity and quality of your compounds, to quickly achieve optimal compounds. StarDrop’s SeeSAR modules are fully integrated within its comprehensive environment for small molecule design, optimisation and data analysis. The SeeSAR modules enable easy visualisation of your ligands in their protein environment, assessment of binding affinities, pose generation and fast template docking for interactive 3D design.</p> <p>Whatever docking platform you prefer, you can run pre-prepared 3D docking and alignment models directly from StarDrop’s SeeSAR module. The Pose Generation Interface (PGI) is compatible with most major docking software platforms, including our Surflex-Dock method and third-party platforms such as <a download="flexx.pdf" href="https://www.biosolveit.de/wp-content/uploads/2021/01/FlexX.pdf">FlexX™</a>, <a href="https://www.ccdc.cam.ac.uk/solutions/software/gold/" target="_blank" rel="noopener">Gold™</a>, <a href="https://www.chemcomp.com/Products.htm" target="_blank" rel="noopener">MOE™</a>, <a href="https://vina.scripps.edu/" target="_blank" rel="noopener">AutoDock Vina™</a>, <a href="https://posit.co/" target="_blank" rel="noopener">POSIT™</a> and more.</p> </div> <div class="flags__item-pills nflm"> <ul class="flags__item-pills-list"> <li> <a href="https://optibrium.com/products/stardrop/customisations-and-collaboration/3d-docking-and-alignment/" class="g-button is-small">StarDrop – PGI</a> </li> <li> <a href="https://optibrium.com/products/stardrop/modules/seesar/" class="g-button is-small">StarDrop – SeeSAR</a> </li> <li> <a href="https://optibrium.com/products/stardrop/modules/esim3d/" class="g-button is-small">StarDrop – eSim3D</a> </li> </ul> </div> </div> <div class="flags__item-media"> <div class="flags__item-media-inner "> <div class="img-fit"><img decoding="async" width="768" height="768" src="data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHZpZXdCb3g9IjAgMCAxMDAwIDEwMDAiIHdpZHRoPSIxMDAwIiBoZWlnaHQ9IjEwMDAiIGRhdGEtdT0iaHR0cHMlM0ElMkYlMkZvcHRpYnJpdW0uY29tJTJGd3AtY29udGVudCUyRnVwbG9hZHMlMkYyMDI0JTJGMDUlMkZTZWVTQVItc3EuanBnIiBkYXRhLXc9IjEwMDAiIGRhdGEtaD0iMTAwMCI+PC9zdmc+" data-spai="1" class="attachment-medium_large size-medium_large" alt="SeeSAR view" srcset=" " sizes="auto, (max-width: 768px) 100vw, 768px" /></div> </div> </div> </div> </div> </div> </div> </section> <section class="cards wp-block alignfull"> <div class="cards__outer"> <div class="cards__inner"> <div class="cards__header"> <h2 aria-label="Resources from across the site" class="cards__heading is-style-typestyle-h1 has-tags">Resources <span>from across the site</span></h2> </div> <div class="cards__items"> <article class="g-card is-resource has-image has-link"> <div class="g-card__outer"> <div class="g-card__inner"> <h2 class="g-card__heading"><a href="https://optibrium.com/resources/seesar-affinity-binding-affinity-and-torsion-angle-analysis-of-virtual-libraries/">SeeSAR affinity – binding affinity and torsion angle analysis of virtual libraries</a> </h2> <div class="g-card__content"> <p>This worked example explores ways to assess the binding affinity of docked compounds. </p> </div> </div> <div class="g-card__footer"> <div class="g-card__labels"> <div class="g-card__labels__items"> <a href="https://optibrium.com/solution/3d-drug-design-and-visualisation/" class="g-button is-small">3D molecular design and visualisation</a> </div> </div> <div class="g-card__meta"> 18 May 2022 </div> </div> </div> <div class="g-card__media img-fit"> <img decoding="async" width="768" height="432" src="data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHZpZXdCb3g9IjAgMCAxMjgwIDcyMCIgd2lkdGg9IjEyODAiIGhlaWdodD0iNzIwIiBkYXRhLXU9Imh0dHBzJTNBJTJGJTJGb3B0aWJyaXVtLmNvbSUyRndwLWNvbnRlbnQlMkZ1cGxvYWRzJTJGMjAyNCUyRjA1JTJGU0VFMDYtVGh1bWJuYWlsLmpwZyIgZGF0YS13PSIxMjgwIiBkYXRhLWg9IjcyMCI+PC9zdmc+" data-spai="1" class="attachment-medium_large size-medium_large" alt="" id="2960" srcset=" " sizes="auto, (max-width: 768px) 100vw, 768px" /> </div> </article> <article class="g-card is-resource has-image has-link"> <div class="g-card__outer"> <div class="g-card__inner"> <h2 class="g-card__heading"><a href="https://optibrium.com/resources/3d-virtual-screening-with-surflex-esim3d/">3D virtual screening with Surflex eSim3D</a> </h2> <div class="g-card__content"> <p>When exploring chemistry space around a known hit or lead, you can use 3D virtual screening to identify new compounds…</p> </div> </div> <div class="g-card__footer"> <div class="g-card__labels"> <div class="g-card__labels__items"> <a href="https://optibrium.com/topic/ligand-based-drug-design/" class="g-button is-small">Ligand-based drug design</a> </div> </div> <div class="g-card__meta"> 21 September 2023 </div> </div> </div> <div class="g-card__media img-fit"> <img decoding="async" width="267" height="284" src="data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHZpZXdCb3g9IjAgMCAyNjcgMjg0IiB3aWR0aD0iMjY3IiBoZWlnaHQ9IjI4NCIgZGF0YS11PSJodHRwcyUzQSUyRiUyRm9wdGlicml1bS5jb20lMkZ3cC1jb250ZW50JTJGdXBsb2FkcyUyRjIwMjMlMkYwOSUyRlZpcnV0YWwtU2NyZWVuLWluLVN1cmZsZXgtZXNpbS1Nb2xQb3J0LWNvbGxlY3Rpb25zLTEucG5nIiBkYXRhLXc9IjI2NyIgZGF0YS1oPSIyODQiPjwvc3ZnPg==" data-spai="1" class="attachment-medium_large size-medium_large" alt="" id="1781" /> </div> </article> <article class="g-card is-resource has-image has-link"> <div class="g-card__outer"> <div class="g-card__inner"> <h2 class="g-card__heading"><a href="https://optibrium.com/resources/autodock-models-for-the-stardrop-pose-generation-interface-pgi/">AutoDock Models for the StarDrop Pose Generation Interface (PGI)</a> </h2> <div class="g-card__content"> <p>From the manuscript “DOCKSTRING: Easy Molecular Docking Yields Better Benchmarks for Ligand Design”, Miguel García-Ortegón, Sergio Bacallado, et al¹ have developed…</p> </div> </div> <div class="g-card__footer"> <div class="g-card__labels"> <div class="g-card__labels__items"> <a href="https://optibrium.com/solution/3d-drug-design-and-visualisation/" class="g-button is-small">3D molecular design and visualisation</a> </div> </div> <div class="g-card__meta"> 31 October 2022 </div> </div> </div> <div class="g-card__media img-fit"> <img decoding="async" width="768" height="512" src="data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHZpZXdCb3g9IjAgMCAxMjAwIDgwMCIgd2lkdGg9IjEyMDAiIGhlaWdodD0iODAwIiBkYXRhLXU9Imh0dHBzJTNBJTJGJTJGb3B0aWJyaXVtLmNvbSUyRndwLWNvbnRlbnQlMkZ1cGxvYWRzJTJGMjAyNCUyRjA1JTJGaW50ZWdyYXRpb24tdmVubi5qcGciIGRhdGEtdz0iMTIwMCIgZGF0YS1oPSI4MDAiPjwvc3ZnPg==" data-spai="1" class="attachment-medium_large size-medium_large" alt="" id="4649" srcset=" " sizes="auto, (max-width: 768px) 100vw, 768px" /> </div> </article> </div> </div> </div> </section> <section class="two-column-content wp-block alignwide"> <div class="two-column-content__outer"> <div class="two-column-content__column nflm is-first"> <h2 aria-label="Ready to explore in 3D?" class="two-column-content__heading is-style-typestyle-h1 has-tags">Ready to <span>explore in 3D?</span></h2> <div class="two-column-content__content nflm"> <p>Contact us to discuss the best solution to support your objectives. 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