Title:Classification SAR Modeling of Diverse Quinolone Compounds for Antimalarial Potency Against Plasmodium falciparum
VOLUME: 17 ISSUE: 5
Author(s):Rahul Balasaheb Aher and Kunal Roy
Affiliation:Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology, Jadavpur University, Kolkata 700032, India.
Keywords:3D-pharmacophore, antimalarial activity, discriminant analysis, Plasmodium falciparum, QSAR, quinolone
derivatives.
Abstract:Both a development of resistance to artemisinin monotherapy and lack of effective vaccine against malaria
have created the urgent need for the development of new and efficient antimalarial agents. In this background, we have
developed here a linear discriminant analysis (LDA) model and a few 3D-pharmacophore models for the classification of
diverse quinolone compounds based on their antimalarial potency against Plasmodium falciparum. The discriminant
model shows 70% correct classification for the test set compounds into higher active and lower active analogues. The best
pharmacophore model (Hypo-1) with a correlation coefficient of 0.83 shows one hydrogen bond acceptor (HBA) and two
ring aromatic (RA) features as the essential structural requirements for antimalarial activity against P falciparum. Both the
models may act as in silico filters for a virtual screening and could be utilized for the selection of higher active molecules
falling within the applicability of the models.
