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The antimalarial activity of a series of 4-anilinoquinolines was modeled with topological and other functional descriptors using feature selection approaches CP-MLR and GA. Five models were identified from each approach to explain the activity of the compounds. They jointly shared eighteen descriptors. Among them five descriptors, namely, H-052, MATS4m, MATS7e, Mor30p, and R7m, were common to both approaches. In PLS analysis the eighteen descriptors have led to a three-component model (, , ). and the common descriptors were among the most influential ones to modulate the activity. Among them, MATS7e indicated the favorability of nonlinear and branched molecular topology for higher activity. MATS4m has also advocated in favor of branching/nonlinearity in the molecule for the activity. The H-052 argued that R'CH2-CHX-CH2R fragments (X is halogen) in the scaffold enhance the activity. In BP-ANN these descriptors led to very good predictive models (training  validation ; test ). The study has offered direction to understand the patterns of the antimalarial activity of anilinoquinolines for exploring potential prototype compounds

Topological Features in Profiling the Antimalarial Activity Landscape of Anilinoquinolines: A Multipronged QSAR Study