DFT-based QSAR Models to Predict the Antimycobacterial Activity of Chalcones

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Abstract

In this study, antimycobacterial activity of a set of synthesized chalcone derivatives against Mycobacterium tuberculosis H37Rv was investigated by quantitative structure-activity relationship (QSAR) analysis using density functional theory (DFT) and molecular mechanics (MM+)-based descriptors in both gas and solvent phases. The best molecular descriptors identified were hardness, E HOMO, MR A-4 and MR B-4′ that contributed to the antimycobacterial activity of the chalcones as independent factors. The correlation of these four descriptors with their antimycobacterial activity increases with the inclusion of solvent medium, indicating their importance in studying biological activity. QSAR models revealed that in gas phase, lower values of E HOMO, MR A-4 and MR B-4′ increase the antimycobacterial activity of the chalcone molecules. However, in solvent phase, lower values of E HOMO and MR B-4′ and higher values of MR A-4 increase their activity. © 2011 John Wiley & Sons A/S.

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Barua, N., Sarmah, P., Hussain, I., Deka, R. C., & Buragohain, A. K. (2012). DFT-based QSAR Models to Predict the Antimycobacterial Activity of Chalcones. Chemical Biology and Drug Design, 79(4), 553–559. https://doi.org/10.1111/j.1747-0285.2011.01289.x

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