Abstract
The work describes QSAR and SAR studies on the TIBO derivatives as non-nucleotide reverse transcriptase inhibitor of HIV-1 using the 2D-topological, physicochemical and hydrophobic parameters, indicator parameters along with the some 3D or quantum parameters. The set of TIBO derivatives chosen for the modeling is consists of 20 compounds. Application of multiple linear regression analysis indicated that a combination of adhoc molecular descriptors and the indicator parameters yielded a statistically significant model for the prediction of activity, log1/C (50% of Effective concentration for inhibition of reverse transcriptase-1 of HIV.). The final selection of a potential TIBO derivative as non-nucleotide reverse transcriptase inhibitor of HIV-1 is made by the quantum molecular modeling.
Keywords: QSAR, anti HIV-1, Topological indices, Physicochemical properties, logP
Anti-Infective Agents in Medicinal Chemistry
Title: Chem-Bioinformatics : Computational Modeling of TIBO Derivatives
Volume: 9 Issue: 2
Author(s): Abhilash Thakur, Mamta Thakur, Neelu Agrawal and Sanjay Bhadoria
Affiliation:
Keywords: QSAR, anti HIV-1, Topological indices, Physicochemical properties, logP
Abstract: The work describes QSAR and SAR studies on the TIBO derivatives as non-nucleotide reverse transcriptase inhibitor of HIV-1 using the 2D-topological, physicochemical and hydrophobic parameters, indicator parameters along with the some 3D or quantum parameters. The set of TIBO derivatives chosen for the modeling is consists of 20 compounds. Application of multiple linear regression analysis indicated that a combination of adhoc molecular descriptors and the indicator parameters yielded a statistically significant model for the prediction of activity, log1/C (50% of Effective concentration for inhibition of reverse transcriptase-1 of HIV.). The final selection of a potential TIBO derivative as non-nucleotide reverse transcriptase inhibitor of HIV-1 is made by the quantum molecular modeling.
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Cite this article as:
Thakur Abhilash, Thakur Mamta, Agrawal Neelu and Bhadoria Sanjay, Chem-Bioinformatics : Computational Modeling of TIBO Derivatives, Anti-Infective Agents in Medicinal Chemistry 2010; 9 (2) . https://dx.doi.org/10.2174/187152110791383751
DOI https://dx.doi.org/10.2174/187152110791383751 |
Print ISSN 1871-5214 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-6018 |
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