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

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


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