Chem-Bioinformatics : Computational Modeling of TIBO Derivatives

ISSN: 2211-3533 (Online)
ISSN: 2211-3525 (Print)

Volume 15, 2 Issues, 2017

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Anti-Infective Agents

Formerly: Anti-Infective Agents in Medicinal Chemistry

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Chem-Bioinformatics : Computational Modeling of TIBO Derivatives

Anti-Infective Agents, 9(2): 52-58.

Author(s): Abhilash Thakur, Mamta Thakur, Neelu Agrawal and Sanjay Bhadoria.

Affiliation: 205, Sudama Nagar (anp sec.) Indore, India 452009.


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.


QSAR, anti HIV-1, Topological indices, Physicochemical properties, logP.

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Article Details

Volume: 9
Issue Number: 2
First Page: 52
Last Page: 58
Page Count: 7
DOI: 10.2174/187152110791383751
Price: $58
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