Validated predictive QSAR modeling of N-aryl-oxazolidinone-5-carboxamides for anti-HIV protease activity

Amit Kumar Halder; Tarun Jha

doi:10.1016/j.bmcl.2010.08.050

Validated predictive QSAR modeling of N-aryl-oxazolidinone-5-carboxamides for anti-HIV protease activity

Bioorg Med Chem Lett. 2010 Oct 15;20(20):6082-7. doi: 10.1016/j.bmcl.2010.08.050. Epub 2010 Aug 13.

Authors

Amit Kumar Halder¹, Tarun Jha

Affiliation

¹ Division of Medicinal and Pharmaceutical Chemistry, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India.

PMID: 20832304
DOI: 10.1016/j.bmcl.2010.08.050

Abstract

Validated predictive QSAR modeling was done on some N-aryl-oxazolidinone-5-carboxamides for higher anti-HIV protease activities. Stepwise regression developed significant models showing importance of atom based descriptors like RTSA indices, Wang-Ford charges and different whole molecular descriptors. The true predictabilities of QSAR models were justified by challenging these against an external dataset. A representative high active compound was predicted by this modeling. It showed that internal and external validations may lead to the same conclusion.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

HIV Infections / drug therapy
HIV Infections / enzymology
HIV Protease / metabolism*
HIV Protease Inhibitors / chemistry*
HIV Protease Inhibitors / pharmacology*
HIV-1 / enzymology*
Humans
Models, Biological
Oxazolidinones / chemistry*
Oxazolidinones / pharmacology*
Quantitative Structure-Activity Relationship

Substances

HIV Protease Inhibitors
Oxazolidinones
HIV Protease