Validated predictive QSAR modeling of N-aryl-oxazolidinone-5-carboxamides for anti-HIV protease activity.
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.
Halder
Amit Kumar
AK
Division of Medicinal and Pharmaceutical Chemistry, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India.
Jha
Tarun
T
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
D017320:HIV Protease Inhibitors; D023303:Oxazolidinones; D016333:HIV Protease