QSAR model development of 39 indoyl aryl sulfones was carried out to predict reverse transcriptase inhibition activity. EC50 for reverse transcriptase binding was taken as biological activity. Physicochemical parameters were calculated using PaDEL descriptor software, version 2.1. Stepwise multiple linear regression analysis was applied to derive QSAR models, which were further evaluated for statistical significance and predictive power by internal and external validation. The best quantitative structure activity relationship model was selected having a correlation coefficient (R2) of 0.835, cross-validated correlation coefficient (Q2) of 0780 and, R2 pred of 0.830. The predictive ability of the selected model was also confirmed by leave one-out cross-validation. The QSAR model indicates that the descriptors (nHBint, SaaNH, MDEO-11 and minaaaC) play an important role in enzyme binding. The information derived from the present study may be useful in the design of more potent substituted indoyl aryl sulfones.
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