Premium
Grid potential analysis, virtual screening studies and ADME/T profiling on N‐arylsulfonylindoles as anti‐HIV‐1 agents
Author(s) -
Kumar Surendra,
Tiwari Meena
Publication year - 2013
Publication title -
journal of chemometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.47
H-Index - 92
eISSN - 1099-128X
pISSN - 0886-9383
DOI - 10.1002/cem.2502
Subject(s) - adme , quantitative structure–activity relationship , pharmacophore , virtual screening , in silico , chemistry , computational biology , stereochemistry , biology , biochemistry , in vitro , gene
A grid potential analysis employing a novel approach of 3D quantitative structure–activity relationships (QSAR) as AutoGPA module in MOE2009.10 was performed on a dataset of 42 compounds of N‐arylsulfonylindoles as anti‐HIV‐1 agents. The uniqueness of AutoGPA module is that it automatically builds the 3D‐QSAR model on the pharmacophore‐based molecular alignment. The AutoGPA‐based 3D‐QSAR model obtained in the present study gave the cross‐validated Q 2 value of 0.588, r 2 pred value of 0.701, r 2 m statistics of 0.732 and Fisher value of 94.264. The results of 3D‐QSAR analysis indicated that hydrophobic groups at R 1 and R 2 positions and electron releasing groups at R 3 position are favourable for good activity. To find similar analogues, virtual screening on ZINC database was carried out using generated AutoGPA‐based 3D‐QSAR model and showed good prediction. In addition to those mentioned earlier, in‐silico ADME absorption, distribution, metabolism and excretion profiling and toxicity risk assessment test was performed, and results showed that majority of compounds from current dataset and newly virtually screened hits generated were within their standard limit. Copyright © 2013 John Wiley & Sons, Ltd.