Chem-Bioinformatics : Computational Modeling of TIBO Derivatives

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.

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