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QSAR modeling of the inhibition of reverse transcriptase enzyme with benzimidazolone analogs

Research paper by Surendra Kumar, Vineet Singh, Meena Tiwari

Indexed on: 19 Aug '10Published on: 19 Aug '10Published in: Medicinal Chemistry Research



Abstract

The reverse transcriptase inhibitory activity of a set of 27 compounds of benzimidazolone analogs is predicted, applying the quantitative structure activity relationship (QSAR) theory. The physicochemical properties representing the 2D and 3D features of molecules were calculated from MOE 2008.10 software. For building the regression models three different variable selection approaches namely, enhanced replacement method (ERM), forward stepwise regression (FSWR), genetic function approximation (GFA) were used and compared to predict the inhibition activity. The ERM outperform at four variables against both FSWR and GFA as evidenced by statistical parameters (n = 21, rtraining2 = 0.8864, Q2 = 0.8243, rpred2 = 0.6423, rm2 = 0.5614). The derived QSAR models have shown that hydrophobicity and size of molecules holds promise for rationalizing the reverse transcriptase inhibitory activity of benzimidazolone analogs. The result of present study may help in designing analogs with better activity.