QSAR and docking studies on the diaryltriazine analogs as HIV-1 reverse transcriptase inhibitors

Abstract

Quantitative structure–activity relationship (QSAR) study on a series of HIV-1 reverse transcriptase inhibitors (diaryltriazines, DATAs) was carried out using suitable molecular descriptors calculated by Hyperchem and Dragon softwares. Chemometrics methods including multiple linear regression, principal component analysis, and principal component regression analysis, were used to set up QSAR models to predict anti-HIV-1 activity of DATAs derivatives. Correlation coefficient obtained by different methods were compared with each other. Cross-validation was applied to verify the validity of models. The results showed that aromatic, nonpolar, and planar molecules have higher anti-HIV activity, and the substituent at C(4) of triazine ring is important in DATAs against HIV-1 RT wild-type. Docking study was performed using AutoDock program on all the compounds. Using docking study, it has shown that all the studied DATAs derivatives bind to the HIV-1 RT and have a common binding modes. The most active inhibitors had higher hydrogen bond and π–π stacking with receptor. These computational studies can offer useful references for understanding the action mechanism and molecular design or modification of this series of the anti-HIV agents.