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.

Graphical abstractA validated predictive QSAR modeling was done on some N-aryl-oxazolidinone-5-carboxamides. Models were developed by stepwise regression analysis using atom based and whole molecular descriptors. The developed models with whole molecular descriptors were validated internally and externally. Chance factors were eliminated as much as possible. A representative high active compound was predicted by this QSAR modeling. It showed that internal and external validations may lead to the same conclusion.Figure optionsDownload full-size imageDownload as PowerPoint slide