ArticleMolecular diversity2010
A combined LS-SVM & MLR QSAR workflow for predicting the inhibition of CXCR3 receptor by quinazolinone analogs.
Article in Molecular diversity, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Article
- Enhanced QSAR model performance by integrating structural and gene expression information.Molecules (Basel, Switzerland) · 2013Article
- Molecular dynamics directed CoMFA studies on carbocyclic neuraminidase inhibitors.Molecular diversity · 2011Article
- QSAR study of C allosteric binding site of HCV NS5B polymerase inhibitors by support vector machine.Molecular diversity · 2011Article
- Prediction of PKCθ inhibitory activity using the Random Forest Algorithm.International journal of molecular sciences · 2010Article
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Authors and funding
6 authors.
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Abstract
A novel QSAR workflow is constructed that combines MLR with LS-SVM classification techniques for the identification of quinazolinone analogs as "active" or "non-active" CXCR3 antagonists. The accuracy of the LS-SVM classification technique for the training set and test was 100% and 90%, respectively. For the "active" analogs a validated MLR QSAR model estimates accurately their I-IP10 IC(50) inhibition values. The accuracy of the QSAR model (R (2) = 0.80) is illustrated using various evaluation techniques, such as leave-one-out procedure (R(LOO2)) = 0.67) and validation through an external test set (R(pred2) = 0.78). The key conclusion of this study is that the selected molecular descriptors, Highest Occupied Molecular Orbital energy (HOMO), Principal Moment of Inertia along X and Y axes PMIX and PMIZ, Polar Surface Area (PSA), Presence of triple bond (PTrplBnd), and Kier shape descriptor ((1) kappa), demonstrate discriminatory and pharmacophore abilities.
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Registered trials
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