title: Validated predictive QSAR modeling of N-aryl-oxazolidinone-5-carboxamides for anti-HIV protease activity.
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.
authors.affiliation: Division of Medicinal and Pharmaceutical Chemistry, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India.
authors.forename: Amit Kumar
authors.initials: AK
authors.lastname: Halder
authors.forename: Tarun
authors.initials: T
authors.lastname: Jha
mesh_terms: D015658:HIV Infections / Q000188:drug therapy / Q000201:enzymology; D016333:HIV Protease / Q000378:metabolism*; D017320:HIV Protease Inhibitors / Q000737:chemistry* / Q000494:pharmacology*; D015497:HIV-1 / Q000201:enzymology*; D006801:Humans; D008954:Models, Biological; D023303:Oxazolidinones / Q000737:chemistry* / Q000494:pharmacology*; D021281:Quantitative Structure-Activity Relationship
chemical_list: D017320:HIV Protease Inhibitors; D023303:Oxazolidinones; D016333:HIV Protease