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|dc.description.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.||en_US|
|dc.subject||Antimalarial; 7-substituted-4-aminoquinoline; QSAR; PCA; MLR ;MNLR; MLR||en_US|
|dc.title||ETUDE QSAR DE CERTAIN DERIVES 7-SUBSTUTUÉ 4-AMINOQUINOLINE COMME DES AGENTS ANTIPALUDIQUE.||en_US|
|Appears in Collections:||Faculté des Sciences Exactes et des Sciences de la Nature et de la Vie (FSESNV)|
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