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• W2023340879 abstract "In this present study, three-dimensional quantitative structure–activity relationship (3D-QSAR) and 2D-QSAR analyses were performed on the series of compounds Hepatitis C Virus NS5B polymerase inhibitors using comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), and stepwise multiple linear regression (SW-MLR) approaches. A CoMFA model with good predictive ability was generated based on training set of 39 compounds and showed satisfactory statistical results (q2= 0.600, r2 = 0.871). To improve the contribution of points for next analyses, CoMFA (after region focusing) was employed in biases of similar alignment and showed appropriate predictive results (q2 = 0.691, r2 = 0.889). A reliable CoMSIA model out of 31 different combinations with the higher “leave-one-out’” cross-validation correlation coefficients (q2) were obtained and indicated suitable statistical results (q2 = 0.664, r2 = 0.911). An external test set of nine compounds were used to evaluate the predictive ability of generated models. The 2D-QSAR model was built with the four descriptors selected by stepwise technique and presented high predictive ability (Rtrain2 = 0.833, Rtest2 = 0.773, QLOO2 = 0.758, QBOOT2 = 0.736). The derived contour maps from each model were assessed to identify the significant structural features required for improving biological activity so as to design potent HCV NS5B polymerase inhibitors." @default.
• W2023340879 created "2016-06-24" @default.
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• W2023340879 date "2014-09-16" @default.
• W2023340879 modified "2023-09-26" @default.
• W2023340879 title "2D and 3D Quantitative Structure–Activity Relationship Study of Hepatitis C Virus NS5B Polymerase Inhibitors by Comparative Molecular Field Analysis and Comparative Molecular Similarity Indices Analysis Methods" @default.
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• W2023340879 doi "https://doi.org/10.1021/ci500216c" @default.
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• W2023340879 hasPublicationYear "2014" @default.
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