Investigation of Empirical and Semi‐Empirical Charges to Study the Effects of Partial Charges on Quality and Prediction Accuracy in 3D‐QSAR

Abstract

AbstractIn Quantitative Structure‐Activity Relationship (QSAR) studies, selection of an appropriate method to assign the partial charge is crucial to derive a reliable model. The prediction accuracy of 3D‐QSAR models depends mainly on the method by which the partial charges were calculated. Therefore, we are interested in examining the effects of empirical and semi‐empirical partial charges on 3D‐QSAR methods, Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA). The feasibility and performance of these charges have been tested on Janus Kinase 2 inhibitors. Both empirical (Gasteiger‐Huckel, Del‐Re, Gasteiger Marsili, Huckel, Merck Molecular Force Field 94 (MMFF94), Pullman) and semi‐empirical (Austin Model 1 (AM1), Parameterized Model 3 (PM3), Recife Model 1 (RM1), and Modified Neglect of Diatomic Overlap (MNDO)) charges exhibited statistically significant quality. Among them, MMFF94, MNDO and AM1 charges yielded higher cross‐validation correlation coefficient (q2) values whereas Del‐Re and MMFF94 charges produced topmost predictive ability (r2pred). Overall, MMFF94 in CoMFA and MMFF94 and MNDO in CoMSIA models was found to be the best charges when both q2 and r2pred values were used as an evaluation criterion. Our results could provide an idea of selection of appropriate charge rather than using default charge to enhance the quality of 3D‐QSAR when prediction accuracy and predictive ability were employed.