CINXE.COM

<!DOCTYPE html> <html lang="en" dir="ltr"> <head>  <script async src="https://www.googletagmanager.com/gtag/js?id=G-P63WKM1TM1"></script> <script> window.dataLayer = window.dataLayer || []; function gtag(){dataLayer.push(arguments);} gtag('js', new Date()); gtag('config', 'G-P63WKM1TM1'); </script>  <script type="text/javascript" > (function(m,e,t,r,i,k,a){m[i]=m[i]||function(){(m[i].a=m[i].a||[]).push(arguments)}; m[i].l=1*new Date(); for (var j = 0; j < document.scripts.length; j++) {if (document.scripts[j].src === r) { return; }} k=e.createElement(t),a=e.getElementsByTagName(t)[0],k.async=1,k.src=r,a.parentNode.insertBefore(k,a)}) (window, document, "script", "https://mc.yandex.ru/metrika/tag.js", "ym"); ym(55165297, "init", { clickmap:false, trackLinks:true, accurateTrackBounce:true, webvisor:false }); </script> <noscript><div><img src="https://mc.yandex.ru/watch/55165297" style="position:absolute; left:-9999px;" alt="" /></div></noscript>    <title>Search results for: molecular descriptors</title> <meta name="description" content="Search results for: molecular descriptors"> <meta name="keywords" content="molecular descriptors"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none navbar-toggler ml-auto" type="button" data-toggle="collapse" data-target="#navbarMenu" aria-controls="navbarMenu" aria-expanded="false" aria-label="Toggle navigation"> <span class="navbar-toggler-icon"></span> </button> <div class="w-100"> <div class="d-none d-lg-flex flex-row-reverse"> <form method="get" action="https://waset.org/search" class="form-inline my-2 my-lg-0"> <input class="form-control mr-sm-2" type="search" placeholder="Search Conferences" value="molecular descriptors" name="q" aria-label="Search"> <button class="btn btn-light my-2 my-sm-0" type="submit"><i class="fas fa-search"></i></button> </form> </div> <div class="collapse navbar-collapse mt-1" id="navbarMenu"> <ul class="navbar-nav ml-auto align-items-center" id="mainNavMenu"> <li class="nav-item"> <a class="nav-link" href="https://waset.org/conferences" title="Conferences in 2024/2025/2026">Conferences</a> </li> <li class="nav-item"> <a class="nav-link" href="https://waset.org/disciplines" title="Disciplines">Disciplines</a> </li> <li class="nav-item"> <a class="nav-link" href="https://waset.org/committees" rel="nofollow">Committees</a> </li> <li class="nav-item dropdown"> <a class="nav-link dropdown-toggle" href="#" id="navbarDropdownPublications" role="button" data-toggle="dropdown" aria-haspopup="true" aria-expanded="false"> Publications </a> <div class="dropdown-menu" aria-labelledby="navbarDropdownPublications"> <a class="dropdown-item" href="https://publications.waset.org/abstracts">Abstracts</a> <a class="dropdown-item" href="https://publications.waset.org">Periodicals</a> <a class="dropdown-item" href="https://publications.waset.org/archive">Archive</a> </div> </li> <li class="nav-item"> <a class="nav-link" href="https://waset.org/page/support" title="Support">Support</a> </li> </ul> </div> </div> </nav> </div> </header> <main> <div class="container mt-4"> <div class="row"> <div class="col-md-9 mx-auto"> <form method="get" action="https://publications.waset.org/abstracts/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="molecular descriptors"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 2223</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: molecular descriptors</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2223</span> Using Combination of Sets of Features of Molecules for Aqueous Solubility Prediction: A Random Forest Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Muhammet%20Baldan">Muhammet Baldan</a>, <a href="https://publications.waset.org/abstracts/search?q=Emel%20Timu%C3%A7in"> Emel Timuçin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Generally, absorption and bioavailability increase if solubility increases; therefore, it is crucial to predict them in drug discovery applications. Molecular descriptors and Molecular properties are traditionally used for the prediction of water solubility. There are various key descriptors that are used for this purpose, namely Drogan Descriptors, Morgan Descriptors, Maccs keys, etc., and each has different prediction capabilities with differentiating successes between different data sets. Another source for the prediction of solubility is structural features; they are commonly used for the prediction of solubility. However, there are little to no studies that combine three or more properties or descriptors for prediction to produce a more powerful prediction model. Unlike available models, we used a combination of those features in a random forest machine learning model for improved solubility prediction to better predict and, therefore, contribute to drug discovery systems. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=solubility" title="solubility">solubility</a>, <a href="https://publications.waset.org/abstracts/search?q=random%20forest" title=" random forest"> random forest</a>, <a href="https://publications.waset.org/abstracts/search?q=molecular%20descriptors" title=" molecular descriptors"> molecular descriptors</a>, <a href="https://publications.waset.org/abstracts/search?q=maccs%20keys" title=" maccs keys"> maccs keys</a> </p> <a href="https://publications.waset.org/abstracts/186736/using-combination-of-sets-of-features-of-molecules-for-aqueous-solubility-prediction-a-random-forest-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/186736.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">46</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2222</span> Quantitative Structure–Activity Relationship Analysis of Some Benzimidazole Derivatives by Linear Multivariate Method</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Strahinja%20Z.%20Kova%C4%8Devi%C4%87">Strahinja Z. Kovačević</a>, <a href="https://publications.waset.org/abstracts/search?q=Lidija%20R.%20Jevri%C4%87"> Lidija R. Jevrić</a>, <a href="https://publications.waset.org/abstracts/search?q=Sanja%20O.%20Podunavac%20Kuzmanovi%C4%87"> Sanja O. Podunavac Kuzmanović</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The relationship between antibacterial activity of eighteen different substituted benzimidazole derivatives and their molecular characteristics was studied using chemometric QSAR (Quantitative Structure–Activity Relationships) approach. QSAR analysis has been carried out on inhibitory activity towards Staphylococcus aureus, by using molecular descriptors, as well as minimal inhibitory activity (MIC). Molecular descriptors were calculated from the optimized structures. Principal component analysis (PCA) followed by hierarchical cluster analysis (HCA) and multiple linear regression (MLR) was performed in order to select molecular descriptors that best describe the antibacterial behavior of the compounds investigated, and to determine the similarities between molecules. The HCA grouped the molecules in separated clusters which have the similar inhibitory activity. PCA showed very similar classification of molecules as the HCA, and displayed which descriptors contribute to that classification. MLR equations, that represent MIC as a function of the in silico molecular descriptors were established. The statistical significance of the estimated models was confirmed by standard statistical measures and cross-validation parameters (SD = 0.0816, F = 46.27, R = 0.9791, R2CV = 0.8266, R2adj = 0.9379, PRESS = 0.1116). These parameters indicate the possibility of application of the established chemometric models in prediction of the antibacterial behaviour of studied derivatives and structurally very similar compounds. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=antibacterial" title="antibacterial">antibacterial</a>, <a href="https://publications.waset.org/abstracts/search?q=benzimidazole" title=" benzimidazole"> benzimidazole</a>, <a href="https://publications.waset.org/abstracts/search?q=molecular%20descriptors" title=" molecular descriptors"> molecular descriptors</a>, <a href="https://publications.waset.org/abstracts/search?q=QSAR" title=" QSAR"> QSAR</a> </p> <a href="https://publications.waset.org/abstracts/26542/quantitative-structure-activity-relationship-analysis-of-some-benzimidazole-derivatives-by-linear-multivariate-method" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/26542.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">364</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2221</span> A DFT-Based QSARs Study of Kovats Retention Indices of Adamantane Derivatives</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Z.%20Bayat">Z. Bayat</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A quantitative structure–property relationship (QSPR) study was performed to develop models those relate the structures of 65 Kovats retention index (RI) of adamantane derivatives. Molecular descriptors derived solely from 3D structures of the molecular compounds. The usefulness of the quantum chemical descriptors, calculated at the level of the DFT theories using 6-311+G** basis set for QSAR study of adamantane derivatives was examined. The use of descriptors calculated only from molecular structure eliminates the need to experimental determination of properties for use in the correlation and allows for the estimation of RI for molecules not yet synthesized. The prediction results are in good agreement with the experimental value. A multi-parametric equation containing maximum Four descriptors at B3LYP/6-31+G** method with good statistical qualities (R2train=0.913, Ftrain=97.67, R2test=0.770, Ftest=3.21, Q2LOO=0.895, R2adj=0.904, Q2LGO=0.844) was obtained by Multiple Linear Regression using stepwise method. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=DFT" title="DFT">DFT</a>, <a href="https://publications.waset.org/abstracts/search?q=adamantane" title=" adamantane"> adamantane</a>, <a href="https://publications.waset.org/abstracts/search?q=QSAR" title=" QSAR"> QSAR</a>, <a href="https://publications.waset.org/abstracts/search?q=Kovat" title=" Kovat"> Kovat</a> </p> <a href="https://publications.waset.org/abstracts/40141/a-dft-based-qsars-study-of-kovats-retention-indices-of-adamantane-derivatives" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/40141.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">366</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2220</span> Chemometric QSRR Evaluation of Behavior of s-Triazine Pesticides in Liquid Chromatography</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Lidija%20R.%20Jevri%C4%87">Lidija R. Jevrić</a>, <a href="https://publications.waset.org/abstracts/search?q=Sanja%20O.%20Podunavac-Kuzmanovi%C4%87"> Sanja O. Podunavac-Kuzmanović</a>, <a href="https://publications.waset.org/abstracts/search?q=Strahinja%20Z.%20Kova%C4%8Devi%C4%87"> Strahinja Z. Kovačević</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study considers the selection of the most suitable in silico molecular descriptors that could be used for s-triazine pesticides characterization. Suitable descriptors among topological, geometrical and physicochemical are used for quantitative structure-retention relationships (QSRR) model establishment. Established models were obtained using linear regression (LR) and multiple linear regression (MLR) analysis. In this paper, MLR models were established avoiding multicollinearity among the selected molecular descriptors. Statistical quality of established models was evaluated by standard and cross-validation statistical parameters. For detection of similarity or dissimilarity among investigated s-triazine pesticides and their classification, principal component analysis (PCA) and hierarchical cluster analysis (HCA) were used and gave similar grouping. This study is financially supported by COST action TD1305. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=chemometrics" title="chemometrics">chemometrics</a>, <a href="https://publications.waset.org/abstracts/search?q=classification%20analysis" title=" classification analysis"> classification analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=molecular%20descriptors" title=" molecular descriptors"> molecular descriptors</a>, <a href="https://publications.waset.org/abstracts/search?q=pesticides" title=" pesticides"> pesticides</a>, <a href="https://publications.waset.org/abstracts/search?q=regression%20analysis" title=" regression analysis "> regression analysis </a> </p> <a href="https://publications.waset.org/abstracts/45198/chemometric-qsrr-evaluation-of-behavior-of-s-triazine-pesticides-in-liquid-chromatography" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/45198.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">393</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2219</span> Evaluation of Newly Synthesized Steroid Derivatives Using In silico Molecular Descriptors and Chemometric Techniques</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Milica%20%C5%BD.%20Karad%C5%BEi%C4%87">Milica Ž. Karadžić</a>, <a href="https://publications.waset.org/abstracts/search?q=Lidija%20R.%20Jevri%C4%87"> Lidija R. Jevrić</a>, <a href="https://publications.waset.org/abstracts/search?q=Sanja%20Podunavac-Kuzmanovi%C4%87"> Sanja Podunavac-Kuzmanović</a>, <a href="https://publications.waset.org/abstracts/search?q=Strahinja%20Z.%20Kova%C4%8Devi%C4%87"> Strahinja Z. Kovačević</a>, <a href="https://publications.waset.org/abstracts/search?q=Anamarija%20I.%20Mandi%C4%87"> Anamarija I. Mandić</a>, <a href="https://publications.waset.org/abstracts/search?q=Katarina%20Penov-Ga%C5%A1i"> Katarina Penov-Gaši</a>, <a href="https://publications.waset.org/abstracts/search?q=Andrea%20R.%20Nikoli%C4%87"> Andrea R. Nikolić</a>, <a href="https://publications.waset.org/abstracts/search?q=Aleksandar%20M.%20Oklje%C5%A1a"> Aleksandar M. Oklješa</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study considered selection of the in silico molecular descriptors and the models for newly synthesized steroid derivatives description and their characterization using chemometric techniques. Multiple linear regression (MLR) models were established and gave the best molecular descriptors for quantitative structure-retention relationship (QSRR) modeling of the retention of the investigated molecules. MLR models were without multicollinearity among the selected molecular descriptors according to the variance inflation factor (VIF) values. Used molecular descriptors were ranked using generalized pair correlation method (GPCM). In this method, the significant difference between independent variables can be noticed regardless almost equal correlation between dependent variable. Generated MLR models were statistically and cross-validated and the best models were kept. Models were ranked using sum of ranking differences (SRD) method. According to this method, the most consistent QSRR model can be found and similarity or dissimilarity between the models could be noticed. In this study, SRD was performed using average values of experimentally observed data as a golden standard. Chemometric analysis was conducted in order to characterize newly synthesized steroid derivatives for further investigation regarding their potential biological activity and further synthesis. This article is based upon work from COST Action (CM1105), supported by COST (European Cooperation in Science and Technology). <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=generalized%20pair%20correlation%20method" title="generalized pair correlation method">generalized pair correlation method</a>, <a href="https://publications.waset.org/abstracts/search?q=molecular%20descriptors" title=" molecular descriptors"> molecular descriptors</a>, <a href="https://publications.waset.org/abstracts/search?q=regression%20analysis" title=" regression analysis"> regression analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=steroids" title=" steroids"> steroids</a>, <a href="https://publications.waset.org/abstracts/search?q=sum%20of%20ranking%20differences" title=" sum of ranking differences"> sum of ranking differences</a> </p> <a href="https://publications.waset.org/abstracts/49456/evaluation-of-newly-synthesized-steroid-derivatives-using-in-silico-molecular-descriptors-and-chemometric-techniques" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/49456.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">347</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2218</span> Quantitative Structure-Property Relationship Study of Base Dissociation Constants of Some Benzimidazoles</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sanja%20O.%20Podunavac-Kuzmanovi%C4%87">Sanja O. Podunavac-Kuzmanović</a>, <a href="https://publications.waset.org/abstracts/search?q=Lidija%20R.%20Jevri%C4%87"> Lidija R. Jevrić</a>, <a href="https://publications.waset.org/abstracts/search?q=Strahinja%20Z.%20Kova%C4%8Devi%C4%87"> Strahinja Z. Kovačević</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Benzimidazoles are a group of compounds with significant antibacterial, antifungal and anticancer activity. The studied compounds consist of the main benzimidazole structure with different combinations of substituens. This study is based on the two-dimensional and three-dimensional molecular modeling and calculation of molecular descriptors (physicochemical and lipophilicity descriptors) of structurally diverse benzimidazoles. Molecular modeling was carried out by using ChemBio3D Ultra version 14.0 software. The obtained 3D models were subjected to energy minimization using molecular mechanics force field method (MM2). The cutoff for structure optimization was set at a gradient of 0.1 kcal/Åmol. The obtained set of molecular descriptors was used in principal component analysis (PCA) of possible similarities and dissimilarities among the studied derivatives. After the molecular modeling, the quantitative structure-property relationship (QSPR) analysis was applied in order to get the mathematical models which can be used in prediction of pKb values of structurally similar benzimidazoles. The obtained models are based on statistically valid multiple linear regression (MLR) equations. The calculated cross-validation parameters indicate the high prediction ability of the established QSPR models. This study is financially supported by COST action CM1306 and the project No. 114-451-347/2015-02, financially supported by the Provincial Secretariat for Science and Technological Development of Vojvodina. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=benzimidazoles" title="benzimidazoles">benzimidazoles</a>, <a href="https://publications.waset.org/abstracts/search?q=chemometrics" title=" chemometrics"> chemometrics</a>, <a href="https://publications.waset.org/abstracts/search?q=molecular%20modeling" title=" molecular modeling"> molecular modeling</a>, <a href="https://publications.waset.org/abstracts/search?q=molecular%20descriptors" title=" molecular descriptors"> molecular descriptors</a>, <a href="https://publications.waset.org/abstracts/search?q=QSPR" title=" QSPR"> QSPR</a> </p> <a href="https://publications.waset.org/abstracts/45055/quantitative-structure-property-relationship-study-of-base-dissociation-constants-of-some-benzimidazoles" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/45055.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">289</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2217</span> Non-Linear Assessment of Chromatographic Lipophilicity of Selected Steroid Derivatives</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Milica%20Karad%C5%BEi%C4%87">Milica Karadžić</a>, <a href="https://publications.waset.org/abstracts/search?q=Lidija%20Jevri%C4%87"> Lidija Jevrić</a>, <a href="https://publications.waset.org/abstracts/search?q=Sanja%20Podunavac-Kuzmanovi%C4%87"> Sanja Podunavac-Kuzmanović</a>, <a href="https://publications.waset.org/abstracts/search?q=Strahinja%20Kova%C4%8Devi%C4%87"> Strahinja Kovačević</a>, <a href="https://publications.waset.org/abstracts/search?q=Anamarija%20Mandi%C4%87"> Anamarija Mandić</a>, <a href="https://publications.waset.org/abstracts/search?q=Aleksandar%20Oklje%C5%A1a"> Aleksandar Oklješa</a>, <a href="https://publications.waset.org/abstracts/search?q=Andrea%20Nikoli%C4%87"> Andrea Nikolić</a>, <a href="https://publications.waset.org/abstracts/search?q=Marija%20Saka%C4%8D"> Marija Sakač</a>, <a href="https://publications.waset.org/abstracts/search?q=Katarina%20Penov%20Ga%C5%A1i"> Katarina Penov Gaši</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Using chemometric approach, the relationships between the chromatographic lipophilicity and in silico molecular descriptors for twenty-nine selected steroid derivatives were studied. The chromatographic lipophilicity was predicted using artificial neural networks (ANNs) method. The most important in silico molecular descriptors were selected applying stepwise selection (SS) paired with partial least squares (PLS) method. Molecular descriptors with satisfactory variable importance in projection (VIP) values were selected for ANN modeling. The usefulness of generated models was confirmed by detailed statistical validation. High agreement between experimental and predicted values indicated that obtained models have good quality and high predictive ability. Global sensitivity analysis (GSA) confirmed the importance of each molecular descriptor used as an input variable. High-quality networks indicate a strong non-linear relationship between chromatographic lipophilicity and used in silico molecular descriptors. Applying selected molecular descriptors and generated ANNs the good prediction of chromatographic lipophilicity of the studied steroid derivatives can be obtained. This article is based upon work from COST Actions (CM1306 and CA15222), supported by COST (European Cooperation and Science and Technology). <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=artificial%20neural%20networks" title="artificial neural networks">artificial neural networks</a>, <a href="https://publications.waset.org/abstracts/search?q=chemometrics" title=" chemometrics"> chemometrics</a>, <a href="https://publications.waset.org/abstracts/search?q=global%20sensitivity%20analysis" title=" global sensitivity analysis"> global sensitivity analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=liquid%20chromatography" title=" liquid chromatography"> liquid chromatography</a>, <a href="https://publications.waset.org/abstracts/search?q=steroids" title=" steroids"> steroids</a> </p> <a href="https://publications.waset.org/abstracts/60203/non-linear-assessment-of-chromatographic-lipophilicity-of-selected-steroid-derivatives" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/60203.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">345</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2216</span> QSAR Modeling of Germination Activity of a Series of 5-(4-Substituent-Phenoxy)-3-Methylfuran-2(5H)-One Derivatives with Potential of Strigolactone Mimics toward Striga hermonthica</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Strahinja%20Kova%C4%8Devi%C4%87">Strahinja Kovačević</a>, <a href="https://publications.waset.org/abstracts/search?q=Sanja%20Podunavac-Kuzmanovi%C4%87"> Sanja Podunavac-Kuzmanović</a>, <a href="https://publications.waset.org/abstracts/search?q=Lidija%20Jevri%C4%87"> Lidija Jevrić</a>, <a href="https://publications.waset.org/abstracts/search?q=Cristina%20Prandi"> Cristina Prandi</a>, <a href="https://publications.waset.org/abstracts/search?q=Piermichele%20Kobauri"> Piermichele Kobauri</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The present study is based on molecular modeling of a series of twelve 5-(4-substituent-phenoxy)-3-methylfuran-2(5H)-one derivatives which have potential of strigolactones mimics toward Striga hermonthica. The first step of the analysis included the calculation of molecular descriptors which numerically describe the structures of the analyzed compounds. The descriptors ALOGP (lipophilicity), AClogS (water solubility) and BBB (blood-brain barrier penetration), served as the input variables in multiple linear regression (MLR) modeling of germination activity toward S. hermonthica. Two MLR models were obtained. The first MLR model contains ALOGP and AClogS descriptors, while the second one is based on these two descriptors plus BBB descriptor. Despite the braking Topliss-Costello rule in the second MLR model, it has much better statistical and cross-validation characteristics than the first one. The ALOGP and AClogS descriptors are often very suitable predictors of the biological activity of many compounds. They are very important descriptors of the biological behavior and availability of a compound in any biological system (i.e. the ability to pass through the cell membranes). BBB descriptor defines the ability of a molecule to pass through the blood-brain barrier. Besides the lipophilicity of a compound, this descriptor carries the information of the molecular bulkiness (its value strongly depends on molecular bulkiness). According to the obtained results of MLR modeling, these three descriptors are considered as very good predictors of germination activity of the analyzed compounds toward S. hermonthica seeds. This article is based upon work from COST Action (FA1206), supported by COST (European Cooperation in Science and Technology). <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=chemometrics" title="chemometrics">chemometrics</a>, <a href="https://publications.waset.org/abstracts/search?q=germination%20activity" title=" germination activity"> germination activity</a>, <a href="https://publications.waset.org/abstracts/search?q=molecular%20modeling" title=" molecular modeling"> molecular modeling</a>, <a href="https://publications.waset.org/abstracts/search?q=QSAR%20analysis" title=" QSAR analysis"> QSAR analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=strigolactones" title=" strigolactones"> strigolactones</a> </p> <a href="https://publications.waset.org/abstracts/49457/qsar-modeling-of-germination-activity-of-a-series-of-5-4-substituent-phenoxy-3-methylfuran-25h-one-derivatives-with-potential-of-strigolactone-mimics-toward-striga-hermonthica" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/49457.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">287</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2215</span> Molecular Modeling of Structurally Diverse Compounds as Potential Therapeutics for Transmissible Spongiform Encephalopathy</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sanja%20O.%20Podunavac-Kuzmanovi%C4%87">Sanja O. Podunavac-Kuzmanović</a>, <a href="https://publications.waset.org/abstracts/search?q=Strahinja%20Z.%20Kova%C4%8Devi%C4%87"> Strahinja Z. Kovačević</a>, <a href="https://publications.waset.org/abstracts/search?q=Lidija%20R.%20Jevri%C4%87"> Lidija R. Jevrić</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Prion is a protein substance whose certain form is considered as infectious agent. It is presumed to be the cause of the transmissible spongiform encephalopathies (TSEs). The protein it is composed of, called PrP, can fold in structurally distinct ways. At least one of those 3D structures is transmissible to other prion proteins. Prions can be found in brain tissue of healthy people and have certain biological role. The structure of prions naturally occurring in healthy organisms is marked as PrPc, and the structure of infectious prion is labeled as PrPSc. PrPc may play a role in synaptic plasticity and neuronal development. Also, it may be required for neuronal myelin sheath maintenance, including a role in iron uptake and iron homeostasis. PrPSc can be considered as an environmental pollutant. The main aim of this study was to carry out the molecular modeling and calculation of molecular descriptors (lipophilicity, physico-chemical and topological descriptors) of structurally diverse compounds which can be considered as anti-prion agents. Molecular modeling was conducted applying ChemBio3D Ultra version 12.0 software. The obtained 3D models were subjected to energy minimization using molecular mechanics force field method (MM2). The cutoff for structure optimization was set at a gradient of 0.1 kcal/Åmol. The Austin Model 1 (AM-1) was used for full geometry optimization of all structures. The obtained set of molecular descriptors is applied in analysis of similarities and dissimilarities among the tested compounds. This study is an important step in further development of quantitative structure-activity relationship (QSAR) models, which can be used for prediction of anti-prion activity of newly synthesized compounds. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=chemometrics" title="chemometrics">chemometrics</a>, <a href="https://publications.waset.org/abstracts/search?q=molecular%20modeling" title=" molecular modeling"> molecular modeling</a>, <a href="https://publications.waset.org/abstracts/search?q=molecular%20descriptors" title=" molecular descriptors"> molecular descriptors</a>, <a href="https://publications.waset.org/abstracts/search?q=prions" title=" prions"> prions</a>, <a href="https://publications.waset.org/abstracts/search?q=QSAR" title=" QSAR"> QSAR</a> </p> <a href="https://publications.waset.org/abstracts/41747/molecular-modeling-of-structurally-diverse-compounds-as-potential-therapeutics-for-transmissible-spongiform-encephalopathy" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/41747.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">322</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2214</span> Molecular Modeling of 17-Picolyl and 17-Picolinylidene Androstane Derivatives with Anticancer Activity</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sanja%20Podunavac-Kuzmanovi%C4%87">Sanja Podunavac-Kuzmanović</a>, <a href="https://publications.waset.org/abstracts/search?q=Strahinja%20Kova%C4%8Devi%C4%87"> Strahinja Kovačević</a>, <a href="https://publications.waset.org/abstracts/search?q=Lidija%20Jevri%C4%87"> Lidija Jevrić</a>, <a href="https://publications.waset.org/abstracts/search?q=Evgenija%20Djurendi%C4%87"> Evgenija Djurendić</a>, <a href="https://publications.waset.org/abstracts/search?q=Jovana%20Ajdukovi%C4%87"> Jovana Ajduković</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In the present study, the molecular modeling of a series of 24 17-picolyl and 17-picolinylidene androstane derivatives whit significant anticancer activity was carried out. Modelling of studied compounds was performed by CS ChemBioDraw Ultra v12.0 program for drawing 2D molecular structures and CS ChemBio3D Ultra v12.0 for 3D molecular modelling. The obtained 3D structures were subjected to energy minimization using molecular mechanics force field method (MM2). The cutoff for structure optimization was set at a gradient of 0.1 kcal/Åmol. Full geometry optimization was done by the Austin Model 1 (AM1) until the root mean square (RMS) gradient reached a value smaller than 0.0001 kcal/Åmol using Molecular Orbital Package (MOPAC) program. The obtained physicochemical, lipophilicity and topological descriptors were used for analysis of molecular similarities and dissimilarities applying suitable chemometric methods (principal component analysis and cluster analysis). These results are the part of the project No. 114-451-347/2015-02, financially supported by the Provincial Secretariat for Science and Technological Development of Vojvodina and CMST COST Action CM1306. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=androstane%20derivatives" title="androstane derivatives">androstane derivatives</a>, <a href="https://publications.waset.org/abstracts/search?q=anticancer%20activity" title=" anticancer activity"> anticancer activity</a>, <a href="https://publications.waset.org/abstracts/search?q=chemometrics" title=" chemometrics"> chemometrics</a>, <a href="https://publications.waset.org/abstracts/search?q=molecular%20descriptors" title=" molecular descriptors"> molecular descriptors</a> </p> <a href="https://publications.waset.org/abstracts/38072/molecular-modeling-of-17-picolyl-and-17-picolinylidene-androstane-derivatives-with-anticancer-activity" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/38072.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">361</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2213</span> Application of Artificial Neural Network for Prediction of Retention Times of Some Secoestrane Derivatives</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nata%C5%A1a%20Kalajd%C5%BEija">Nataša Kalajdžija</a>, <a href="https://publications.waset.org/abstracts/search?q=Strahinja%20Kova%C4%8Devi%C4%87"> Strahinja Kovačević</a>, <a href="https://publications.waset.org/abstracts/search?q=Davor%20Lon%C4%8Dar"> Davor Lončar</a>, <a href="https://publications.waset.org/abstracts/search?q=Sanja%20Podunavac%20Kuzmanovi%C4%87"> Sanja Podunavac Kuzmanović</a>, <a href="https://publications.waset.org/abstracts/search?q=Lidija%20Jevri%C4%87"> Lidija Jevrić</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In order to investigate the relationship between retention and structure, a quantitative Structure Retention Relationships (QSRRs) study was applied for the prediction of retention times of a set of 23 secoestrane derivatives in a reversed-phase thin-layer chromatography. After the calculation of molecular descriptors, a suitable set of molecular descriptors was selected by using step-wise multiple linear regressions. Artificial Neural Network (ANN) method was employed to model the nonlinear structure-activity relationships. The ANN technique resulted in 5-6-1 ANN model with the correlation coefficient of 0.98. We found that the following descriptors: Critical pressure, total energy, protease inhibition, distribution coefficient (LogD) and parameter of lipophilicity (miLogP) have a significant effect on the retention times. The prediction results are in very good agreement with the experimental ones. This approach provided a new and effective method for predicting the chromatographic retention index for the secoestrane derivatives investigated. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=lipophilicity" title="lipophilicity">lipophilicity</a>, <a href="https://publications.waset.org/abstracts/search?q=QSRR" title=" QSRR"> QSRR</a>, <a href="https://publications.waset.org/abstracts/search?q=RP%20TLC%20retention" title=" RP TLC retention"> RP TLC retention</a>, <a href="https://publications.waset.org/abstracts/search?q=secoestranes" title=" secoestranes"> secoestranes</a> </p> <a href="https://publications.waset.org/abstracts/2743/application-of-artificial-neural-network-for-prediction-of-retention-times-of-some-secoestrane-derivatives" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/2743.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">456</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2212</span> Quantitative Structure-Activity Relationship Analysis of Binding Affinity of a Series of Anti-Prion Compounds to Human Prion Protein</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Strahinja%20Kova%C4%8Devi%C4%87">Strahinja Kovačević</a>, <a href="https://publications.waset.org/abstracts/search?q=Sanja%20Podunavac-Kuzmanovi%C4%87"> Sanja Podunavac-Kuzmanović</a>, <a href="https://publications.waset.org/abstracts/search?q=Lidija%20Jevri%C4%87"> Lidija Jevrić</a>, <a href="https://publications.waset.org/abstracts/search?q=Milica%20Karad%C5%BEi%C4%87"> Milica Karadžić</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The present study is based on the quantitative structure-activity relationship (QSAR) analysis of eighteen compounds with anti-prion activity. The structures and anti-prion activities (expressed in response units, RU%) of the analyzed compounds are taken from CHEMBL database. In the first step of analysis 85 molecular descriptors were calculated and based on them the hierarchical cluster analysis (HCA) and principal component analysis (PCA) were carried out in order to detect potential significant similarities or dissimilarities among the studied compounds. The calculated molecular descriptors were physicochemical, lipophilicity and ADMET (absorption, distribution, metabolism, excretion and toxicity) descriptors. The first stage of the QSAR analysis was simple linear regression modeling. It resulted in one acceptable model that correlates Henry's law constant with RU% units. The obtained 2D-QSAR model was validated by cross-validation as an internal validation method. The validation procedure confirmed the model’s quality and therefore it can be used for prediction of anti-prion activity. The next stage of the analysis of anti-prion activity will include 3D-QSAR and molecular docking approaches in order to select the most promising compounds in treatment of prion diseases. These results are the part of the project No. 114-451-268/2016-02 financially supported by the Provincial Secretariat for Science and Technological Development of AP Vojvodina. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=anti-prion%20activity" title="anti-prion activity">anti-prion activity</a>, <a href="https://publications.waset.org/abstracts/search?q=chemometrics" title=" chemometrics"> chemometrics</a>, <a href="https://publications.waset.org/abstracts/search?q=molecular%20modeling" title=" molecular modeling"> molecular modeling</a>, <a href="https://publications.waset.org/abstracts/search?q=QSAR" title=" QSAR"> QSAR</a> </p> <a href="https://publications.waset.org/abstracts/60009/quantitative-structure-activity-relationship-analysis-of-binding-affinity-of-a-series-of-anti-prion-compounds-to-human-prion-protein" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/60009.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">304</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2211</span> Molecular Topology and TLC Retention Behaviour of s-Triazines: QSRR Study</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Lidija%20R.%20Jevri%C4%87">Lidija R. Jevrić</a>, <a href="https://publications.waset.org/abstracts/search?q=Sanja%20O.%20Podunavac-Kuzmanovi%C4%87"> Sanja O. Podunavac-Kuzmanović</a>, <a href="https://publications.waset.org/abstracts/search?q=Strahinja%20Z.%20Kova%C4%8Devi%C4%87"> Strahinja Z. Kovačević</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Quantitative structure-retention relationship (QSRR) analysis was used to predict the chromatographic behavior of s-triazine derivatives by using theoretical descriptors computed from the chemical structure. Fundamental basis of the reported investigation is to relate molecular topological descriptors with chromatographic behavior of s-triazine derivatives obtained by reversed-phase (RP) thin layer chromatography (TLC) on silica gel impregnated with paraffin oil and applied ethanol-water (φ = 0.5-0.8; v/v). Retention parameter (RM0) of 14 investigated s-triazine derivatives was used as dependent variable while simple connectivity index different orders were used as independent variables. The best QSRR model for predicting RM0 value was obtained with simple third order connectivity index (3χ) in the second-degree polynomial equation. Numerical values of the correlation coefficient (r=0.915), Fisher's value (F=28.34) and root mean square error (RMSE = 0.36) indicate that model is statistically significant. In order to test the predictive power of the QSRR model leave-one-out cross-validation technique has been applied. The parameters of the internal cross-validation analysis (r2CV=0.79, r2adj=0.81, PRESS=1.89) reflect the high predictive ability of the generated model and it confirms that can be used to predict RM0 value. Multivariate classification technique, hierarchical cluster analysis (HCA), has been applied in order to group molecules according to their molecular connectivity indices. HCA is a descriptive statistical method and it is the most frequently used for important area of data processing such is classification. The HCA performed on simple molecular connectivity indices obtained from the 2D structure of investigated s-triazine compounds resulted in two main clusters in which compounds molecules were grouped according to the number of atoms in the molecule. This is in agreement with the fact that these descriptors were calculated on the basis of the number of atoms in the molecule of the investigated s-triazine derivatives. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=s-triazines" title="s-triazines">s-triazines</a>, <a href="https://publications.waset.org/abstracts/search?q=QSRR" title=" QSRR"> QSRR</a>, <a href="https://publications.waset.org/abstracts/search?q=chemometrics" title=" chemometrics"> chemometrics</a>, <a href="https://publications.waset.org/abstracts/search?q=chromatography" title=" chromatography"> chromatography</a>, <a href="https://publications.waset.org/abstracts/search?q=molecular%20descriptors" title=" molecular descriptors"> molecular descriptors</a> </p> <a href="https://publications.waset.org/abstracts/29063/molecular-topology-and-tlc-retention-behaviour-of-s-triazines-qsrr-study" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/29063.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">393</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2210</span> Computational Study of Chromatographic Behavior of a Series of S-Triazine Pesticides Based on Their in Silico Biological and Lipophilicity Descriptors</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Lidija%20R.%20Jevri%C4%87">Lidija R. Jevrić</a>, <a href="https://publications.waset.org/abstracts/search?q=Sanja%20O.%20Podunavac-Kuzmanovi%C4%87"> Sanja O. Podunavac-Kuzmanović</a>, <a href="https://publications.waset.org/abstracts/search?q=Strahinja%20Z.%20Kova%C4%8Devi%C4%87"> Strahinja Z. Kovačević</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, quantitative structure-retention relationships (QSRR) analysis was applied in order to correlate in silico biological and lipophilicity molecular descriptors with retention values for the set of selected s-triazine herbicides. In silico generated biological and lipophilicity descriptors were discriminated using generalized pair correlation method (GPCM). According to this method, the significant difference between independent variables can be noticed regardless almost equal correlation with dependent variable. Using established multiple linear regression (MLR) models some biological characteristics could be predicted. Established MLR models were evaluated statistically and the most suitable models were selected and ranked using sum of ranking differences (SRD) method. In this method, as reference values, average experimentally obtained values are used. Additionally, using SRD method, similarities among investigated s-triazine herbicides can be noticed. These analysis were conducted in order to characterize selected s-triazine herbicides for future investigations regarding their biodegradability. This study is financially supported by COST action TD1305. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=descriptors" title="descriptors">descriptors</a>, <a href="https://publications.waset.org/abstracts/search?q=generalized%20pair%20correlation%20method" title=" generalized pair correlation method"> generalized pair correlation method</a>, <a href="https://publications.waset.org/abstracts/search?q=pesticides" title=" pesticides"> pesticides</a>, <a href="https://publications.waset.org/abstracts/search?q=sum%20of%20ranking%20differences" title=" sum of ranking differences "> sum of ranking differences </a> </p> <a href="https://publications.waset.org/abstracts/45126/computational-study-of-chromatographic-behavior-of-a-series-of-s-triazine-pesticides-based-on-their-in-silico-biological-and-lipophilicity-descriptors" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/45126.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">295</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2209</span> A Machine Learning-Based Model to Screen Antituberculosis Compound Targeted against LprG Lipoprotein of Mycobacterium tuberculosis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Syed%20Asif%20Hassan">Syed Asif Hassan</a>, <a href="https://publications.waset.org/abstracts/search?q=Syed%20Atif%20Hassan"> Syed Atif Hassan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Multidrug-resistant Tuberculosis (MDR-TB) is an infection caused by the resistant strains of Mycobacterium tuberculosis that do not respond either to isoniazid or rifampicin, which are the most important anti-TB drugs. The increase in the occurrence of a drug-resistance strain of MTB calls for an intensive search of novel target-based therapeutics. In this context LprG (Rv1411c) a lipoprotein from MTB plays a pivotal role in the immune evasion of Mtb leading to survival and propagation of the bacterium within the host cell. Therefore, a machine learning method will be developed for generating a computational model that could predict for a potential anti LprG activity of the novel antituberculosis compound. The present study will utilize dataset from PubChem database maintained by National Center for Biotechnology Information (NCBI). The dataset involves compounds screened against MTB were categorized as active and inactive based upon PubChem activity score. PowerMV, a molecular descriptor generator, and visualization tool will be used to generate the 2D molecular descriptors for the actives and inactive compounds present in the dataset. The 2D molecular descriptors generated from PowerMV will be used as features. We feed these features into three different classifiers, namely, random forest, a deep neural network, and a recurring neural network, to build separate predictive models and choosing the best performing model based on the accuracy of predicting novel antituberculosis compound with an anti LprG activity. Additionally, the efficacy of predicted active compounds will be screened using SMARTS filter to choose molecule with drug-like features. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=antituberculosis%20drug" title="antituberculosis drug">antituberculosis drug</a>, <a href="https://publications.waset.org/abstracts/search?q=classifier" title=" classifier"> classifier</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title=" machine learning"> machine learning</a>, <a href="https://publications.waset.org/abstracts/search?q=molecular%20descriptors" title=" molecular descriptors"> molecular descriptors</a>, <a href="https://publications.waset.org/abstracts/search?q=prediction" title=" prediction"> prediction</a> </p> <a href="https://publications.waset.org/abstracts/65730/a-machine-learning-based-model-to-screen-antituberculosis-compound-targeted-against-lprg-lipoprotein-of-mycobacterium-tuberculosis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/65730.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">391</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2208</span> Exploring 1,2,4-Triazine-3(2H)-One Derivatives as Anticancer Agents for Breast Cancer: A QSAR, Molecular Docking, ADMET, and Molecular Dynamics</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Said%20Belaaouad">Said Belaaouad</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study aimed to explore the quantitative structure-activity relationship (QSAR) of 1,2,4-Triazine-3(2H)-one derivative as a potential anticancer agent against breast cancer. The electronic descriptors were obtained using the Density Functional Theory (DFT) method, and a multiple linear regression techniques was employed to construct the QSAR model. The model exhibited favorable statistical parameters, including R2=0.849, R2adj=0.656, MSE=0.056, R2test=0.710, and Q2cv=0.542, indicating its reliability. Among the descriptors analyzed, absolute electronegativity (χ), total energy (TE), number of hydrogen bond donors (NHD), water solubility (LogS), and shape coefficient (I) were identified as influential factors. Furthermore, leveraging the validated QSAR model, new derivatives of 1,2,4-Triazine-3(2H)-one were designed, and their activity and pharmacokinetic properties were estimated. Subsequently, molecular docking (MD) and molecular dynamics (MD) simulations were employed to assess the binding affinity of the designed molecules. The Tubulin colchicine binding site, which plays a crucial role in cancer treatment, was chosen as the target protein. Through the simulation trajectory spanning 100 ns, the binding affinity was calculated using the MMPBSA script. As a result, fourteen novel Tubulin-colchicine inhibitors with promising pharmacokinetic characteristics were identified. Overall, this study provides valuable insights into the QSAR of 1,2,4-Triazine-3(2H)-one derivative as potential anticancer agent, along with the design of new compounds and their assessment through molecular docking and dynamics simulations targeting the Tubulin-colchicine binding site. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=QSAR" title="QSAR">QSAR</a>, <a href="https://publications.waset.org/abstracts/search?q=molecular%20docking" title=" molecular docking"> molecular docking</a>, <a href="https://publications.waset.org/abstracts/search?q=ADMET" title=" ADMET"> ADMET</a>, <a href="https://publications.waset.org/abstracts/search?q=1" title=" 1"> 1</a>, <a href="https://publications.waset.org/abstracts/search?q=2" title="2">2</a>, <a href="https://publications.waset.org/abstracts/search?q=4-triazin-3%282H%29-ones" title="4-triazin-3(2H)-ones">4-triazin-3(2H)-ones</a>, <a href="https://publications.waset.org/abstracts/search?q=breast%20cancer" title=" breast cancer"> breast cancer</a>, <a href="https://publications.waset.org/abstracts/search?q=anticancer" title=" anticancer"> anticancer</a>, <a href="https://publications.waset.org/abstracts/search?q=molecular%20dynamic%20simulations" title=" molecular dynamic simulations"> molecular dynamic simulations</a>, <a href="https://publications.waset.org/abstracts/search?q=MMPBSA%20calculation" title=" MMPBSA calculation"> MMPBSA calculation</a> </p> <a href="https://publications.waset.org/abstracts/167402/exploring-124-triazine-32h-one-derivatives-as-anticancer-agents-for-breast-cancer-a-qsar-molecular-docking-admet-and-molecular-dynamics" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/167402.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">97</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2207</span> Computing Some Topological Descriptors of Single-Walled Carbon Nanotubes</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Amir%20Bahrami">Amir Bahrami</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In the fields of chemical graph theory, molecular topology, and mathematical chemistry, a topological index or a descriptor index also known as a connectivity index is a type of a molecular descriptor that is calculated based on the molecular graph of a chemical compound. Topological indices are numerical parameters of a graph which characterize its topology and are usually graph invariant. Topological indices are used for example in the development of quantitative structure-activity relationships (QSARs) in which the biological activity or other properties of molecules are correlated with their chemical structure. In this paper some descriptor index (descriptor index) of single-walled carbon nanotubes, is determined. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=chemical%20graph%20theory" title="chemical graph theory">chemical graph theory</a>, <a href="https://publications.waset.org/abstracts/search?q=molecular%20topology" title=" molecular topology"> molecular topology</a>, <a href="https://publications.waset.org/abstracts/search?q=molecular%20descriptor" title=" molecular descriptor"> molecular descriptor</a>, <a href="https://publications.waset.org/abstracts/search?q=single-walled%20carbon%20nanotubes" title=" single-walled carbon nanotubes"> single-walled carbon nanotubes</a> </p> <a href="https://publications.waset.org/abstracts/39279/computing-some-topological-descriptors-of-single-walled-carbon-nanotubes" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/39279.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">338</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2206</span> Binding Studies of Complexes of Anticancer Drugs with DNA and Enzymes Involved in DNA Replication Using Molecular Docking and Cell Culture Techniques</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Fouzia%20Perveen">Fouzia Perveen</a>, <a href="https://publications.waset.org/abstracts/search?q=Rumana%20Qureshi"> Rumana Qureshi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The presently studied twelve anticancer drugs are the cytotoxic agents which inhibit the replication of DNA and activity of enzymes involved in DNA replication namely topoisomerase-II, polymerase and helicase and have shown remarkable anticancer activity in clinical trials. In this study, we performed molecular docking studies of twelve antitumor drugs against DNA and DNA enzymes in the presence and absence of ascorbic acid (AA) and developed the quantitative structure-activity relationship (QSAR) model for anticancer activity screening. A number of electronic and steric descriptors were calculated using MOE software package. QSAR was established showing a correlation of binding strength with various physicochemical descriptors. Out of these twelve, eight cytotoxic drugs were tested on Non-Small Cell Lung Cancer cell lines (H-157 and H-1299) in the absence and presence of ascorbic acid and experimental IC50 values were calculated. From the docking studies, binding constants were calculated indicating the strength of drug-DNA and drug-enzyme complex formation and it was correlated to the IC50 values (both experimental and theoretical). These results can offer useful references for directing the molecular design of DNA enzyme inhibitor with improved anticancer activity. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ascorbic%20acid" title="ascorbic acid">ascorbic acid</a>, <a href="https://publications.waset.org/abstracts/search?q=binding%20constant" title=" binding constant"> binding constant</a>, <a href="https://publications.waset.org/abstracts/search?q=cytotoxic%20agents" title=" cytotoxic agents"> cytotoxic agents</a>, <a href="https://publications.waset.org/abstracts/search?q=cell%20culture" title=" cell culture"> cell culture</a>, <a href="https://publications.waset.org/abstracts/search?q=DNA" title=" DNA"> DNA</a>, <a href="https://publications.waset.org/abstracts/search?q=DNA%20enzymes" title=" DNA enzymes"> DNA enzymes</a>, <a href="https://publications.waset.org/abstracts/search?q=molecular%20docking" title=" molecular docking"> molecular docking</a> </p> <a href="https://publications.waset.org/abstracts/23535/binding-studies-of-complexes-of-anticancer-drugs-with-dna-and-enzymes-involved-in-dna-replication-using-molecular-docking-and-cell-culture-techniques" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/23535.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">427</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2205</span> A 7 Dimensional-Quantitative Structure-Activity Relationship Approach Combining Quantum Mechanics Based Grid and Solvation Models to Predict Hotspots and Kinetic Properties of Mutated Enzymes: An Enzyme Engineering Perspective</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=R.%20Pravin%20Kumar">R. Pravin Kumar</a>, <a href="https://publications.waset.org/abstracts/search?q=L.%20Roopa"> L. Roopa</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Enzymes are molecular machines used in various industries such as pharmaceuticals, cosmetics, food and animal feed, paper and leather processing, biofuel, and etc. Nevertheless, this has been possible only by the breath-taking efforts of the chemists and biologists to evolve/engineer these mysterious biomolecules to work the needful. Main agenda of this enzyme engineering project is to derive screening and selection tools to obtain focused libraries of enzyme variants with desired qualities. The methodologies for this research include the well-established directed evolution, rational redesign and relatively less established yet much faster and accurate insilico methods. This concept was initiated as a Receptor Rependent-4Dimensional Quantitative Structure Activity Relationship (RD-4D-QSAR) to predict kinetic properties of enzymes and extended here to study transaminase by a 7D QSAR approach. Induced-fit scenarios were explored using Quantum Mechanics/Molecular Mechanics (QM/MM) simulations which were then placed in a grid that stores interactions energies derived from QM parameters (QMgrid). In this study, the mutated enzymes were immersed completely inside the QMgrid and this was combined with solvation models to predict descriptors. After statistical screening of descriptors, QSAR models showed > 90% specificity and > 85% sensitivity towards the experimental activity. Mapping descriptors on the enzyme structure revealed hotspots important to enhance the enantioselectivity of the enzyme. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=QMgrid" title="QMgrid">QMgrid</a>, <a href="https://publications.waset.org/abstracts/search?q=QM%2FMM%20simulations" title=" QM/MM simulations"> QM/MM simulations</a>, <a href="https://publications.waset.org/abstracts/search?q=RD-4D-QSAR" title=" RD-4D-QSAR"> RD-4D-QSAR</a>, <a href="https://publications.waset.org/abstracts/search?q=transaminase" title=" transaminase"> transaminase</a> </p> <a href="https://publications.waset.org/abstracts/97410/a-7-dimensional-quantitative-structure-activity-relationship-approach-combining-quantum-mechanics-based-grid-and-solvation-models-to-predict-hotspots-and-kinetic-properties-of-mutated-enzymes-an-enzyme-engineering-perspective" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/97410.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">137</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2204</span> Mostar Type Indices and QSPR Analysis of Octane Isomers</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=B.%20Roopa%20Sri">B. Roopa Sri</a>, <a href="https://publications.waset.org/abstracts/search?q=Y%20Lakshmi%20Naidu"> Y Lakshmi Naidu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Chemical Graph Theory (CGT) is the branch of mathematical chemistry in which molecules are modeled to study their physicochemical properties using molecular descriptors. Amongst these descriptors, topological indices play a vital role in predicting the properties by defining the graph topology of the molecule. Recently, the bond-additive topological index known as the Mostar index has been proposed. In this paper, we compute the Mostar-type indices of octane isomers and use the data obtained to perform QSPR analysis. Furthermore, we show the correlation between the Mostar type indices and the properties. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=chemical%20graph%20theory" title="chemical graph theory">chemical graph theory</a>, <a href="https://publications.waset.org/abstracts/search?q=mostar%20type%20indices" title=" mostar type indices"> mostar type indices</a>, <a href="https://publications.waset.org/abstracts/search?q=octane%20isomers" title=" octane isomers"> octane isomers</a>, <a href="https://publications.waset.org/abstracts/search?q=qspr%20analysis" title=" qspr analysis"> qspr analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=topological%20index" title=" topological index"> topological index</a> </p> <a href="https://publications.waset.org/abstracts/153959/mostar-type-indices-and-qspr-analysis-of-octane-isomers" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/153959.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">130</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2203</span> Computational Approach to Cyclin-Dependent Kinase 2 Inhibitors Design and Analysis: Merging Quantitative Structure-Activity Relationship, Absorption, Distribution, Metabolism, Excretion, and Toxicity, Molecular Docking, and Molecular Dynamics Simulations </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohamed%20Moussaoui">Mohamed Moussaoui</a>, <a href="https://publications.waset.org/abstracts/search?q=Mouna%20Baassi"> Mouna Baassi</a>, <a href="https://publications.waset.org/abstracts/search?q=Soukayna%20Baammi"> Soukayna Baammi</a>, <a href="https://publications.waset.org/abstracts/search?q=Hatim%20Soufi"> Hatim Soufi</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohammed%20Salah"> Mohammed Salah</a>, <a href="https://publications.waset.org/abstracts/search?q=Rachid%20Daoud"> Rachid Daoud</a>, <a href="https://publications.waset.org/abstracts/search?q=Achraf%20EL%20Allali"> Achraf EL Allali</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohammed%20Elalaoui%20Belghiti"> Mohammed Elalaoui Belghiti</a>, <a href="https://publications.waset.org/abstracts/search?q=Said%20Belaaouad"> Said Belaaouad</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The present study aims to investigate the quantitative structure-activity relationship (QSAR) of a series of Thiazole derivatives reported as anticancer agents (hepatocellular carcinoma), using principally the electronic descriptors calculated by the density functional theory (DFT) method and by applying the multiple linear regression method. The developed model showed good statistical parameters (R²= 0.725, R²ₐ𝒹ⱼ= 0.653, MSE = 0.060, R²ₜₑₛₜ= 0.827, Q²𝒸ᵥ = 0.536). The energy of the highest occupied molecular orbital (EHOMO) orbital, electronic energy (TE), shape coefficient (I), number of rotatable bonds (NROT), and index of refraction (n) were revealed to be the main descriptors influencing the anti-cancer activity. Additional Thiazole derivatives were then designed and their activities and pharmacokinetic properties were predicted using the validated QSAR model. These designed molecules underwent evaluation through molecular docking (MD) and molecular dynamic (MD) simulations, with binding affinity calculated using the MMPBSA script according to a 100 ns simulation trajectory. This process aimed to study both their affinity and stability towards Cyclin-Dependent Kinase 2 (CDK2), a target protein for cancer disease treatment. The research concluded by identifying four CDK2 inhibitors - A1, A3, A5, and A6 - displaying satisfactory pharmacokinetic properties. MDs results indicated that the designed compound A5 remained stable in the active center of the CDK2 protein, suggesting its potential as an effective inhibitor for the treatment of hepatocellular carcinoma. The findings of this study could contribute significantly to the development of effective CDK2 inhibitors. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=QSAR" title="QSAR">QSAR</a>, <a href="https://publications.waset.org/abstracts/search?q=ADMET" title=" ADMET"> ADMET</a>, <a href="https://publications.waset.org/abstracts/search?q=Thiazole" title=" Thiazole"> Thiazole</a>, <a href="https://publications.waset.org/abstracts/search?q=anticancer" title=" anticancer"> anticancer</a>, <a href="https://publications.waset.org/abstracts/search?q=molecular%20docking" title=" molecular docking"> molecular docking</a>, <a href="https://publications.waset.org/abstracts/search?q=molecular%20dynamic%20simulations" title=" molecular dynamic simulations"> molecular dynamic simulations</a>, <a href="https://publications.waset.org/abstracts/search?q=MMPBSA%20calculation" title=" MMPBSA calculation"> MMPBSA calculation</a> </p> <a href="https://publications.waset.org/abstracts/167390/computational-approach-to-cyclin-dependent-kinase-2-inhibitors-design-and-analysis-merging-quantitative-structure-activity-relationship-absorption-distribution-metabolism-excretion-and-toxicity-molecular-docking-and-molecular-dynamics-simulations" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/167390.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">107</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2202</span> QSRR Analysis of 17-Picolyl and 17-Picolinylidene Androstane Derivatives Based on Partial Least Squares and Principal Component Regression</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sanja%20Podunavac-Kuzmanovi%C4%87">Sanja Podunavac-Kuzmanović</a>, <a href="https://publications.waset.org/abstracts/search?q=Strahinja%20Kova%C4%8Devi%C4%87"> Strahinja Kovačević</a>, <a href="https://publications.waset.org/abstracts/search?q=Lidija%20Jevri%C4%87"> Lidija Jevrić</a>, <a href="https://publications.waset.org/abstracts/search?q=Evgenija%20Djurendi%C4%87"> Evgenija Djurendić</a>, <a href="https://publications.waset.org/abstracts/search?q=Jovana%20Ajdukovi%C4%87"> Jovana Ajduković</a> </p> <p class="card-text"><strong>Abstract:</strong></p> There are several methods for determination of the lipophilicity of biologically active compounds, however chromatography has been shown as a very suitable method for this purpose. Chromatographic (C18-RP-HPLC) analysis of a series of 24 17-picolyl and 17-picolinylidene androstane derivatives was carried out. The obtained retention indices (logk, methanol (90%) / water (10%)) were correlated with calculated physicochemical and lipophilicity descriptors. The QSRR analysis was carried out applying principal component regression (PCR) and partial least squares regression (PLS). The PCR and PLS model were selected on the basis of the highest variance and the lowest root mean square error of cross-validation. The obtained PCR and PLS model successfully correlate the calculated molecular descriptors with logk parameter indicating the significance of the lipophilicity of compounds in chromatographic process. On the basis of the obtained results it can be concluded that the obtained logk parameters of the analyzed androstane derivatives can be considered as their chromatographic lipophilicity. These results are the part of the project No. 114-451-347/2015-02, financially supported by the Provincial Secretariat for Science and Technological Development of Vojvodina and CMST COST Action CM1105. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=androstane%20derivatives" title="androstane derivatives">androstane derivatives</a>, <a href="https://publications.waset.org/abstracts/search?q=chromatography" title=" chromatography"> chromatography</a>, <a href="https://publications.waset.org/abstracts/search?q=molecular%20structure" title=" molecular structure"> molecular structure</a>, <a href="https://publications.waset.org/abstracts/search?q=principal%20component%20regression" title=" principal component regression"> principal component regression</a>, <a href="https://publications.waset.org/abstracts/search?q=partial%20least%20squares%20regression" title=" partial least squares regression"> partial least squares regression</a> </p> <a href="https://publications.waset.org/abstracts/38073/qsrr-analysis-of-17-picolyl-and-17-picolinylidene-androstane-derivatives-based-on-partial-least-squares-and-principal-component-regression" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/38073.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">277</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2201</span> Bag of Words Representation Based on Fusing Two Color Local Descriptors and Building Multiple Dictionaries </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Fatma%20Abdedayem">Fatma Abdedayem</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We propose an extension to the famous method called Bag of words (BOW) which proved a successful role in the field of image categorization. Practically, this method based on representing image with visual words. In this work, firstly, we extract features from images using Spatial Pyramid Representation (SPR) and two dissimilar color descriptors which are opponent-SIFT and transformed-color-SIFT. Secondly, we fuse color local features by joining the two histograms coming from these descriptors. Thirdly, after collecting of all features, we generate multi-dictionaries coming from n random feature subsets that obtained by dividing all features into n random groups. Then, by using these dictionaries separately each image can be represented by n histograms which are lately concatenated horizontally and form the final histogram, that allows to combine Multiple Dictionaries (MDBoW). In the final step, in order to classify image we have applied Support Vector Machine (SVM) on the generated histograms. Experimentally, we have used two dissimilar image datasets in order to test our proposition: Caltech 256 and PASCAL VOC 2007. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=bag%20of%20words%20%28BOW%29" title="bag of words (BOW)">bag of words (BOW)</a>, <a href="https://publications.waset.org/abstracts/search?q=color%20descriptors" title=" color descriptors"> color descriptors</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-dictionaries" title=" multi-dictionaries"> multi-dictionaries</a>, <a href="https://publications.waset.org/abstracts/search?q=MDBoW" title=" MDBoW"> MDBoW</a> </p> <a href="https://publications.waset.org/abstracts/14637/bag-of-words-representation-based-on-fusing-two-color-local-descriptors-and-building-multiple-dictionaries" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/14637.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">297</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2200</span> Assisted Video Colorization Using Texture Descriptors</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Andre%20Peres%20Ramos">Andre Peres Ramos</a>, <a href="https://publications.waset.org/abstracts/search?q=Franklin%20Cesar%20Flores"> Franklin Cesar Flores</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Colorization is the process of add colors to a monochromatic image or video. Usually, the process involves to segment the image in regions of interest and then apply colors to each one, for videos, this process is repeated for each frame, which makes it a tedious and time-consuming job. We propose a new assisted method for video colorization; the user only has to colorize one frame, and then the colors are propagated to following frames. The user can intervene at any time to correct eventual errors in color assignment. The method consists of to extract intensity and texture descriptors from the frames and then perform a feature matching to determine the best color for each segment. To reduce computation time and give a better spatial coherence we narrow the area of search and give weights for each feature to emphasize texture descriptors. To give a more natural result, we use an optimization algorithm to make the color propagation. Experimental results in several image sequences, compared to others existing methods, demonstrates that the proposed method perform a better colorization with less time and user interference. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=colorization" title="colorization">colorization</a>, <a href="https://publications.waset.org/abstracts/search?q=feature%20matching" title=" feature matching"> feature matching</a>, <a href="https://publications.waset.org/abstracts/search?q=texture%20descriptors" title=" texture descriptors"> texture descriptors</a>, <a href="https://publications.waset.org/abstracts/search?q=video%20segmentation" title=" video segmentation"> video segmentation</a> </p> <a href="https://publications.waset.org/abstracts/97191/assisted-video-colorization-using-texture-descriptors" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/97191.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">162</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2199</span> Non-Linear Assessment of Chromatographic Lipophilicity and Model Ranking of Newly Synthesized Steroid Derivatives</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Milica%20Karadzic">Milica Karadzic</a>, <a href="https://publications.waset.org/abstracts/search?q=Lidija%20Jevric"> Lidija Jevric</a>, <a href="https://publications.waset.org/abstracts/search?q=Sanja%20Podunavac-Kuzmanovic"> Sanja Podunavac-Kuzmanovic</a>, <a href="https://publications.waset.org/abstracts/search?q=Strahinja%20Kovacevic"> Strahinja Kovacevic</a>, <a href="https://publications.waset.org/abstracts/search?q=Anamarija%20Mandic"> Anamarija Mandic</a>, <a href="https://publications.waset.org/abstracts/search?q=Katarina%20Penov%20Gasi"> Katarina Penov Gasi</a>, <a href="https://publications.waset.org/abstracts/search?q=Marija%20Sakac"> Marija Sakac</a>, <a href="https://publications.waset.org/abstracts/search?q=Aleksandar%20Okljesa"> Aleksandar Okljesa</a>, <a href="https://publications.waset.org/abstracts/search?q=Andrea%20Nikolic"> Andrea Nikolic</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The present paper deals with chromatographic lipophilicity prediction of newly synthesized steroid derivatives. The prediction was achieved using in silico generated molecular descriptors and quantitative structure-retention relationship (QSRR) methodology with the artificial neural networks (ANN) approach. Chromatographic lipophilicity of the investigated compounds was expressed as retention factor value logk. For QSRR modeling, a feedforward back-propagation ANN with gradient descent learning algorithm was applied. Using the novel sum of ranking differences (SRD) method generated ANN models were ranked. The aim was to distinguish the most consistent QSRR model that can be found, and similarity or dissimilarity between the models that could be noticed. In this study, SRD was performed with average values of retention factor value logk as reference values. An excellent correlation between experimentally observed retention factor value logk and values predicted by the ANN was obtained with a correlation coefficient higher than 0.9890. Statistical results show that the established ANN models can be applied for required purpose. This article is based upon work from COST Action (TD1305), supported by COST (European Cooperation in Science and Technology). <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=artificial%20neural%20networks" title="artificial neural networks">artificial neural networks</a>, <a href="https://publications.waset.org/abstracts/search?q=liquid%20chromatography" title=" liquid chromatography"> liquid chromatography</a>, <a href="https://publications.waset.org/abstracts/search?q=molecular%20descriptors" title=" molecular descriptors"> molecular descriptors</a>, <a href="https://publications.waset.org/abstracts/search?q=steroids" title=" steroids"> steroids</a>, <a href="https://publications.waset.org/abstracts/search?q=sum%20of%20ranking%20differences" title=" sum of ranking differences"> sum of ranking differences</a> </p> <a href="https://publications.waset.org/abstracts/50587/non-linear-assessment-of-chromatographic-lipophilicity-and-model-ranking-of-newly-synthesized-steroid-derivatives" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/50587.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">319</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2198</span> Determining the Octanol-Water Partition Coefficient for Armchair Polyhex BN Nanotubes Using Topological Indices</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Esmat%20Mohammadinasab">Esmat Mohammadinasab</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The aim of this paper is to investigate theoretically and establish a predictive model for determination LogP of armchair polyhex BN nanotubes by using simple descriptors. The relationship between the octanol-water partition coefficient (LogP) and quantum chemical descriptors, electric moments, and topological indices of some armchair polyhex BN nanotubes with various lengths and fixed circumference are represented. Based on density functional theory (DFT) electric moments and physico-chemical properties of those nanotubes are calculated. The DFT method performed based on the Becke’s 3-parameter formulation with the Lee-Yang-Parr functional (B3LYP) method and 3-21G standard basis sets. For the first time, the relationship between partition coefficient and different properties of polyhex BN nanotubes is investigated. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=topological%20indices" title="topological indices">topological indices</a>, <a href="https://publications.waset.org/abstracts/search?q=quantum%20descriptors" title=" quantum descriptors"> quantum descriptors</a>, <a href="https://publications.waset.org/abstracts/search?q=DFT%20method" title=" DFT method"> DFT method</a>, <a href="https://publications.waset.org/abstracts/search?q=nanotubes" title=" nanotubes"> nanotubes</a> </p> <a href="https://publications.waset.org/abstracts/23476/determining-the-octanol-water-partition-coefficient-for-armchair-polyhex-bn-nanotubes-using-topological-indices" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/23476.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">335</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2197</span> Computational Studies of the Reactivity Descriptors and the Optoelectronic Properties on the Efficiency Free-Base- and Zn-Porphyrin-Sensitized Solar Cells</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Soraya%20Abtouche">Soraya Abtouche</a>, <a href="https://publications.waset.org/abstracts/search?q=Zeyneb%20Ghoualem"> Zeyneb Ghoualem</a>, <a href="https://publications.waset.org/abstracts/search?q=Syrine%20Daoudi"> Syrine Daoudi</a>, <a href="https://publications.waset.org/abstracts/search?q=Lina%20Ouldmohamed"> Lina Ouldmohamed</a>, <a href="https://publications.waset.org/abstracts/search?q=Xavier%20Assfeld"> Xavier Assfeld</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This work reports density functional theory calculations of the optimized geometries, molecular reactivity, energy gap,and thermodynamic properties of the free base (H2P) and their Zn (II) metallated (ZnP), bearing one, two, or three carboxylic acid groups using the hybrid functional B3LYP, Cam-B3lYP, wb97xd with 6-31G(d,p) basis sets. When donating groups are attached to the molecular dye, the bond lengths are slightly decreased, which is important for the easy transfer of an electron from donating to the accepting group. For all dyes, the highest occupied molecular orbital/lowest occupied molecular orbital analysis results in positive outcomes upon electron injection to the semiconductor and subsequent dye regeneration by the electrolyte. The ionization potential increases with increasing conjugation; therefore, the compound dye attached to one carboxylic acid group has the highest ionization potential. The results show higher efficiencies of those sensitized with ZnP. These results have been explained, taking into account the electronic character of the metal ion, which acts as a mediator in the injection step, and, on the other hand, considering the number of anchoring groups to which it binds to the surface of TiO2. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=DSSC" title="DSSC">DSSC</a>, <a href="https://publications.waset.org/abstracts/search?q=porphyrin" title=" porphyrin"> porphyrin</a>, <a href="https://publications.waset.org/abstracts/search?q=TD-DFT" title=" TD-DFT"> TD-DFT</a>, <a href="https://publications.waset.org/abstracts/search?q=electronic%20properties" title=" electronic properties"> electronic properties</a>, <a href="https://publications.waset.org/abstracts/search?q=donor-acceptor%20groups" title=" donor-acceptor groups"> donor-acceptor groups</a> </p> <a href="https://publications.waset.org/abstracts/164820/computational-studies-of-the-reactivity-descriptors-and-the-optoelectronic-properties-on-the-efficiency-free-base-and-zn-porphyrin-sensitized-solar-cells" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/164820.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">78</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2196</span> Evaluation of Robust Feature Descriptors for Texture Classification</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jia-Hong%20Lee">Jia-Hong Lee</a>, <a href="https://publications.waset.org/abstracts/search?q=Mei-Yi%20Wu"> Mei-Yi Wu</a>, <a href="https://publications.waset.org/abstracts/search?q=Hsien-Tsung%20Kuo"> Hsien-Tsung Kuo</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Texture is an important characteristic in real and synthetic scenes. Texture analysis plays a critical role in inspecting surfaces and provides important techniques in a variety of applications. Although several descriptors have been presented to extract texture features, the development of object recognition is still a difficult task due to the complex aspects of texture. Recently, many robust and scaling-invariant image features such as SIFT, SURF and ORB have been successfully used in image retrieval and object recognition. In this paper, we have tried to compare the performance for texture classification using these feature descriptors with k-means clustering. Different classifiers including K-NN, Naive Bayes, Back Propagation Neural Network , Decision Tree and Kstar were applied in three texture image sets － UIUCTex, KTH-TIPS and Brodatz, respectively. Experimental results reveal SIFTS as the best average accuracy rate holder in UIUCTex, KTH-TIPS and SURF is advantaged in Brodatz texture set. BP neuro network works best in the test set classification among all used classifiers. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=texture%20classification" title="texture classification">texture classification</a>, <a href="https://publications.waset.org/abstracts/search?q=texture%20descriptor" title=" texture descriptor"> texture descriptor</a>, <a href="https://publications.waset.org/abstracts/search?q=SIFT" title=" SIFT"> SIFT</a>, <a href="https://publications.waset.org/abstracts/search?q=SURF" title=" SURF"> SURF</a>, <a href="https://publications.waset.org/abstracts/search?q=ORB" title=" ORB"> ORB</a> </p> <a href="https://publications.waset.org/abstracts/11046/evaluation-of-robust-feature-descriptors-for-texture-classification" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/11046.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">369</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2195</span> Halogenated Methoxy- and Methyl-benzoic Acids: Joint Experimental and DFT Study For Molecular Structure, Vibrational Analysis, and Other Molecular Properties</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Boda%20Sreenivas">Boda Sreenivas</a>, <a href="https://publications.waset.org/abstracts/search?q=Lyathakula%20Ravindranath"> Lyathakula Ravindranath</a>, <a href="https://publications.waset.org/abstracts/search?q=Kanugula%20Srishailam"> Kanugula Srishailam</a>, <a href="https://publications.waset.org/abstracts/search?q=Byru%20Venkatram%20Reddy"> Byru Venkatram Reddy</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Extensive research into the optimized structure and molecular properties of 3-Flouro-2-methylbenzoicacid(FMB), 3-Chloro-2-methoxybenzoicacid (CMB), and 3-Bromo-2-methylbenzoicacid (BMB) was carried out using FT-IR, FT-Raman and UV-Visible spectra, as well as theoretically using the DFT approach with B3LYPfunctional in conjunction with 6-311++G(d,p) basis set. The optimized structure was determined by evaluating torsional scans about free rotation bonds. Structure parameters, harmonic vibrational frequencies, potential energy distribution(PED), and infrared and Raman intensities were computed. The computational results from the DFT approach, such asFT-IR, FT-Raman, and UV-Visible spectra, were compared with the experimental results and found good agreement. Observed and calculated frequencies agreed with an rms error of 8.42, 6.60, and 6.95 cm-1 for FMB, CMB, and BMB, respectively. Unambiguous vibrational assignments were made for all fundamentals using PED and eigenvectors. The electronic HOMO-LUMO, H-bonding, and strong conjugative interactions across different molecular entities are discussed using experimental and simulated Ultraviolet-Visible spectra. The title molecules' molecular properties such as dipole moment, mean polarizability, and first-order hyperpolarizability, were calculated to study their non-linear optical (NLO) behavior. The chemical reactivity descriptors and mapped electrostatic surface potential (MESP) were also evaluated. Natural bond orbital (NBO) analysis was used to examine the stability of molecules resulting from hyperconjugative interactions and charge delocalization. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ftir%2Framan%20spectra" title="ftir/raman spectra">ftir/raman spectra</a>, <a href="https://publications.waset.org/abstracts/search?q=DFT" title=" DFT"> DFT</a>, <a href="https://publications.waset.org/abstracts/search?q=NLO" title=" NLO"> NLO</a>, <a href="https://publications.waset.org/abstracts/search?q=homo-lumo" title=" homo-lumo"> homo-lumo</a>, <a href="https://publications.waset.org/abstracts/search?q=NBO" title=" NBO"> NBO</a>, <a href="https://publications.waset.org/abstracts/search?q=halogenated%20benzoic%20acids" title=" halogenated benzoic acids"> halogenated benzoic acids</a> </p> <a href="https://publications.waset.org/abstracts/162874/halogenated-methoxy-and-methyl-benzoic-acids-joint-experimental-and-dft-study-for-molecular-structure-vibrational-analysis-and-other-molecular-properties" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/162874.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">76</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2194</span> Towards Designing of a Potential New HIV-1 Protease Inhibitor Using Quantitative Structure-Activity Relationship Study in Combination with Molecular Docking and Molecular Dynamics Simulations</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mouna%20Baassi">Mouna Baassi</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohamed%20Moussaoui"> Mohamed Moussaoui</a>, <a href="https://publications.waset.org/abstracts/search?q=Hatim%20Soufi"> Hatim Soufi</a>, <a href="https://publications.waset.org/abstracts/search?q=Sanchaita%20RajkhowaI"> Sanchaita RajkhowaI</a>, <a href="https://publications.waset.org/abstracts/search?q=Ashwani%20Sharma"> Ashwani Sharma</a>, <a href="https://publications.waset.org/abstracts/search?q=Subrata%20Sinha"> Subrata Sinha</a>, <a href="https://publications.waset.org/abstracts/search?q=Said%20Belaaouad"> Said Belaaouad</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Human Immunodeficiency Virus type 1 protease (HIV-1 PR) is one of the most challenging targets of antiretroviral therapy used in the treatment of AIDS-infected people. The performance of protease inhibitors (PIs) is limited by the development of protease mutations that can promote resistance to the treatment. The current study was carried out using statistics and bioinformatics tools. A series of thirty-three compounds with known enzymatic inhibitory activities against HIV-1 protease was used in this paper to build a mathematical model relating the structure to the biological activity. These compounds were designed by software; their descriptors were computed using various tools, such as Gaussian, Chem3D, ChemSketch and MarvinSketch. Computational methods generated the best model based on its statistical parameters. The model’s applicability domain (AD) was elaborated. Furthermore, one compound has been proposed as efficient against HIV-1 protease with comparable biological activity to the existing ones; this drug candidate was evaluated using ADMET properties and Lipinski’s rule. Molecular Docking performed on Wild Type and Mutant Type HIV-1 proteases allowed the investigation of the interaction types displayed between the proteases and the ligands, Darunavir (DRV) and the new drug (ND). Molecular dynamics simulation was also used in order to investigate the complexes’ stability, allowing a comparative study of the performance of both ligands (DRV & ND). Our study suggested that the new molecule showed comparable results to that of Darunavir and may be used for further experimental studies. Our study may also be used as a pipeline to search and design new potential inhibitors of HIV-1 proteases. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=QSAR" title="QSAR">QSAR</a>, <a href="https://publications.waset.org/abstracts/search?q=ADMET%20properties" title=" ADMET properties"> ADMET properties</a>, <a href="https://publications.waset.org/abstracts/search?q=molecular%20docking" title=" molecular docking"> molecular docking</a>, <a href="https://publications.waset.org/abstracts/search?q=molecular%20dynamics%20simulation." title=" molecular dynamics simulation."> molecular dynamics simulation.</a> </p> <a href="https://publications.waset.org/abstracts/187453/towards-designing-of-a-potential-new-hiv-1-protease-inhibitor-using-quantitative-structure-activity-relationship-study-in-combination-with-molecular-docking-and-molecular-dynamics-simulations" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/187453.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">39</span> </span> </div> </div> <ul class="pagination"> <li class="page-item disabled"><span class="page-link">&lsaquo;</span></li> <li class="page-item active"><span class="page-link">1</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=molecular%20descriptors&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=molecular%20descriptors&page=3">3</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=molecular%20descriptors&page=4">4</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=molecular%20descriptors&page=5">5</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=molecular%20descriptors&page=6">6</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=molecular%20descriptors&page=7">7</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=molecular%20descriptors&page=8">8</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=molecular%20descriptors&page=9">9</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=molecular%20descriptors&page=10">10</a></li> <li class="page-item disabled"><span class="page-link">...</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=molecular%20descriptors&page=74">74</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=molecular%20descriptors&page=75">75</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=molecular%20descriptors&page=2" rel="next">&rsaquo;</a></li> </ul> </div> </main> <footer> <div id="infolinks" class="pt-3 pb-2"> <div class="container"> <div style="background-color:#f5f5f5;" class="p-3"> <div class="row"> <div class="col-md-2"> <ul class="list-unstyled"> About <li><a href="https://waset.org/page/support">About Us</a></li> <li><a href="https://waset.org/page/support#legal-information">Legal</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/WASET-16th-foundational-anniversary.pdf">WASET celebrates its 16th foundational anniversary</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Account <li><a href="https://waset.org/profile">My Account</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Explore <li><a href="https://waset.org/disciplines">Disciplines</a></li> <li><a href="https://waset.org/conferences">Conferences</a></li> <li><a href="https://waset.org/conference-programs">Conference Program</a></li> <li><a href="https://waset.org/committees">Committees</a></li> <li><a href="https://publications.waset.org">Publications</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Research <li><a href="https://publications.waset.org/abstracts">Abstracts</a></li> <li><a href="https://publications.waset.org">Periodicals</a></li> <li><a href="https://publications.waset.org/archive">Archive</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Open Science <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Science-Philosophy.pdf">Open Science Philosophy</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Science-Award.pdf">Open Science Award</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Society-Open-Science-and-Open-Innovation.pdf">Open Innovation</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Postdoctoral-Fellowship-Award.pdf">Postdoctoral Fellowship Award</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Scholarly-Research-Review.pdf">Scholarly Research Review</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Support <li><a href="https://waset.org/page/support">Support</a></li> <li><a href="https://waset.org/profile/messages/create">Contact Us</a></li> <li><a href="https://waset.org/profile/messages/create">Report Abuse</a></li> </ul> </div> </div> </div> </div> </div> <div class="container text-center"> <hr style="margin-top:0;margin-bottom:.3rem;"> <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank" class="text-muted small">Creative Commons Attribution 4.0 International License</a> <div id="copy" class="mt-2">© 2024 World Academy of Science, Engineering and Technology</div> </div> </footer> <a href="javascript:" id="return-to-top"><i class="fas fa-arrow-up"></i></a> <div class="modal" id="modal-template"> <div class="modal-dialog"> <div class="modal-content"> <div class="row m-0 mt-1"> <div class="col-md-12"> <button type="button" class="close" data-dismiss="modal" aria-label="Close"><span aria-hidden="true">×</span></button> </div> </div> <div class="modal-body"></div> </div> </div> </div> <script src="https://cdn.waset.org/static/plugins/jquery-3.3.1.min.js"></script> <script src="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/js/bootstrap.bundle.min.js"></script> <script src="https://cdn.waset.org/static/js/site.js?v=150220211556"></script> <script> jQuery(document).ready(function() { /*jQuery.get("https://publications.waset.org/xhr/user-menu", function (response) { jQuery('#mainNavMenu').append(response); });*/ jQuery.get({ url: "https://publications.waset.org/xhr/user-menu", cache: false }).then(function(response){ jQuery('#mainNavMenu').append(response); }); }); </script> </body> </html>