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

In this present study, three-dimensional quantitative structureactivity 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 (q(2)= 0.600, r(2) = 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 (q(2) = 0.691, r(2) = 0.889). A reliable CoMSIA model out of 31 different combinations with the higher leave-one-out cross-validation correlation coefficients (q(2)) were obtained and indicated suitable statistical results (q(2) = 0.664, r(2) = 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 (R-train(2) = 0.833, R-test(2) = 0.773, Q(LOO)(2) = 0.758, Q(BOOT)(2) = 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.