ETUDE QSAR DE CERTAIN DERIVES 7-SUBSTUTUÉ 4-AMINOQUINOLINE COMME DES AGENTS ANTIPALUDIQUE.

Abstract

The quinoline moiety is one of the widely studied scaffolds for generating derivatives with various pharmacophoric groups due to its potential antimalarial activities. In the present study, a series of 7-substituted-4-aminoquinoline derivatives were selected to understand their antimalarial properties computationally by molecular modeling techniques including 2D QSAR, and find a correlation between the different physic-chemical parameters (descriptors) of these compounds and its biological activity, using principal components analysis (PCA), multiple linear regression (MLR), to a regression partial least squares (PLS).multiple non-linear regression (MNLR)). The principal component analysis (PCA) has been used to select descriptors that show a high correlation with activities. Based on our result, a comparison of the quality of, MLR, PLS, and MNLR models shows that the MNLR (R = 0.914 and R2 = 0.835;RCV= 0.853) models have substantially better predictive capability because the MNLR approach gives better results than MLR(R = 0.835 and R2 = 0,752;RCV=0.601)), PLS (R = 0.742 and R2 = 0.552; RCV=0.550) . The model of MNLR gave statistically significant results and showed good stability to data variation in leave-one-out cross-validation.