Exploring QSAR for substituted 2-sulfonyl-phenyl-indol derivatives as potent and selective COX-2 inhibitors using different chemometrics tools.

Selective inhibition of cyclooxygenase-2 inhibitors is an important strategy in designing of potent anti-inflammatory compounds with significantly reduced side effects. The present quantitative structure-activity relationship study, attempts to explore the structural and physicochemical requirements of 2-sulfonyl-phenyl-indol derivatives (n = 30) for COX-2 inhibitory activity using chemical, topological, geometrical, and quantum descriptors. Some statistical techniques like stepwise regression, multiple linear regression with factor analysis as the data preprocessing (FA-MLR), principal component regression analysis, and genetic algorithms partial least squares analysis were applied to derive the quantitative structure-activity relationship models. The generated equations were statistically validated using cross-validation and external test set. The quality of equations obtained from stepwise multiple linear regression, FA-MLR, principal component regression analysis and PLS were in the acceptable statistical range. The best multiple linear regression equation obtained from factor analysis (FA-MLR) as the preprocessing step could predict 77.5% of the variance of the cyclooxygenase-2 inhibitory activity whereas that derived from genetic algorithms partial least squares could predict 84.2% of variances. The results of quantitative structure-activity relationship models suggested the importance of lipophilicity, electronegativity, molecular area and steric parameters on the cyclooxygenase-2 inhibitory activity.