Abstract
This study critically examines the role of conceptual DFT descriptors and docking scores on a diverse set of 156 inhibitors of HIV proteases. Five QSAR models were developed on the basis of available experimental IC50 values (HIV-I and HIV-IIIB infected MT4 and CEMSS cells and HIV-I infected C8166 cells) and sixth QSAR model was generated by combining the inhibitors of all five models. B3LYP/6-31G(d) optimizations were carried out on all considered inhibitors, and the results are compared with more economic semi-empirical SCF AM1 results in order to find out the best and efficient way of descriptor calculations. Interestingly semi-empirical results appear to be satisfactory for this class of inhibitors. Selected QSAR models were validated by taking about 20% of inhibitors in the test sets. The effect of the number of descriptors on the R2 and R2 cv values was tested and three to four orthogonal descriptors based models were selected to be the optimum ones to avoid over correlation.
Keywords: Conceptual DFT descriptors, Docking, HIV protease inhibitors, QM calculations, QSAR, Statistical correlation, immunodeficiency, virus, AIDS, oxygens
Medicinal Chemistry
Title:The Efficacy of Conceptual DFT Descriptors and Docking Scores on the QSAR Models of HIV Protease Inhibitors
Volume: 8 Issue: 5
Author(s): Hemant Kumar Srivastava, Chinmayee Choudhury and G. Narahari Sastry
Affiliation:
Keywords: Conceptual DFT descriptors, Docking, HIV protease inhibitors, QM calculations, QSAR, Statistical correlation, immunodeficiency, virus, AIDS, oxygens
Abstract: This study critically examines the role of conceptual DFT descriptors and docking scores on a diverse set of 156 inhibitors of HIV proteases. Five QSAR models were developed on the basis of available experimental IC50 values (HIV-I and HIV-IIIB infected MT4 and CEMSS cells and HIV-I infected C8166 cells) and sixth QSAR model was generated by combining the inhibitors of all five models. B3LYP/6-31G(d) optimizations were carried out on all considered inhibitors, and the results are compared with more economic semi-empirical SCF AM1 results in order to find out the best and efficient way of descriptor calculations. Interestingly semi-empirical results appear to be satisfactory for this class of inhibitors. Selected QSAR models were validated by taking about 20% of inhibitors in the test sets. The effect of the number of descriptors on the R2 and R2 cv values was tested and three to four orthogonal descriptors based models were selected to be the optimum ones to avoid over correlation.
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Kumar Srivastava Hemant, Choudhury Chinmayee and Narahari Sastry G., The Efficacy of Conceptual DFT Descriptors and Docking Scores on the QSAR Models of HIV Protease Inhibitors, Medicinal Chemistry 2012; 8 (5) . https://dx.doi.org/10.2174/157340612802084351
DOI https://dx.doi.org/10.2174/157340612802084351 |
Print ISSN 1573-4064 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-6638 |
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