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Title: QSAR modeling of HIV-1 reverse transcriptase inhibitor of aryluracil derivatives using ab initio and empirical calculations
Authors: Sharma, Neetu
Dwivedi, Amrita
Srivastava, A K
Singh, Ajeet
Keywords: DFT;QSAR;Regression analysis;Molecular descriptor
Issue Date: Jun-2016
Publisher: NISCAIR-CSIR, India
Abstract: Quantitative structure–activity relationship (QSAR) studies have been performed on a series of 1-[(2-benzyloxyl/alkoxyl)methyl]-5-halo-6-aryluracil derivatives that are non-nucleoside reverse transcriptase inhibitors.  Various descriptors have been calculated based on empirical and density functional theory (DFT). Density functional theory based descriptors have been calculated at GGA-PW91 level. Several QSAR equations have been formulated through regression analysis and tested with external and internal validation tests. The best equations have been selected from the various statistically significant equations. Model equations have been cross validated by leave one out (LOO) technique. The calculated results suggest that the introduction of a halogen at the R2 position may contribute to the effectiveness of these compounds against RTI-resistant variants.
Page(s): 752-760
ISSN: 0975-0983(Online); 0376-4699(Print)
Appears in Collections:IJC-B Vol.55B(06) [June 2016]

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