Abstract

IN SILICO MOLECULAR MODELING OF NOVEL PYRIDINONE DERIVATIVES AS HIV-1 NNRTIS USING QSAR

Neetu Sharma, Ranjana, Amrita Dwivedi, Ajeet Singh and A. K. Srivastava*

Abstract

The Quantitative relationship between molecular properties andbiological activity of Pyridinone a derivative as non-nucleoside reversetranscriptase inhibitors (NNRTIs) has been studied to explore theimportant factors affecting their biological activity along withQuantum chemical parameters based on Density Functional Theory(DFT-based) along with topological and physicochemical parameterswere used for the present analysis. Density functional theory-baseddescriptors were calculated at GGA-PW91 level. In this study,stepwise linear regression (MLR) was used to select significantmolecular descriptors and by grouping these descriptors somesignificant QSAR models were constructed. The QSAR models suggest that presence of 2-methylhexyl and benzyl at R1 and R3 position respectively enhances the activity. Thepredictive ability of QSAR models were cross validated by evaluating the residual activity,appreciable cross validated R2 values (R2cv) and by leave one out (LOO) technique.

Keywords: HIV-1 NNRT inhibitors, DFT, Pyridinone, QSAR and Regression analysis.