Quantitative structure activity relationship study of p38α MAP kinase inhibitors

Abstract

The quantitative structure activity relationship (QSAR) of the novel pyrazole derivatives as inhibitors of p38α mitogen activated protein (MAP) kinase was studied. The suitable set of the molecular descriptors was calculated and the important descriptors using the variable selections of the stepwise (SW) and the genetic algorithm (GA) were selected. The predictive quality of the QSAR models was tested for an external set of nine compounds, randomly chosen out of 44 compounds. A comparison between the attained results indicated the superiority of the genetic algorithm over the stepwise method in the feature selection. The genetic algorithm-multiple linear regression (GA-MLR) model with six selected descriptors was obtained. The accuracy of the proposed model is illustrated using the following evaluation techniques: cross-validation, validation through an external test set, applicability domain, and Y-randomization. The analyses may be used to design more potent pyrazole derivatives and predict their activity prior to synthesis.

Keywords

• QSAR
• Genetic algorithm
• Stepwise
• Multiple linear regression
• Pyrazole derivative