Classification SAR Modeling of Diverse Quinolone Compounds for Antimalarial Potency Against Plasmodium falciparum

ISSN: 1875-5402 (Online)
ISSN: 1386-2073 (Print)

Volume 19, 10 Issues, 2016

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Combinatorial Chemistry & High Throughput Screening

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Classification SAR Modeling of Diverse Quinolone Compounds for Antimalarial Potency Against Plasmodium falciparum

Combinatorial Chemistry & High Throughput Screening, 17(5): 396-406.

Author(s): Rahul Balasaheb Aher and Kunal Roy.

Affiliation: Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology, Jadavpur University, Kolkata 700032, India.


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.


3D-pharmacophore, antimalarial activity, discriminant analysis, Plasmodium falciparum, QSAR, quinolone derivatives.

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Article Details

Volume: 17
Issue Number: 5
First Page: 396
Last Page: 406
Page Count: 11
DOI: 10.2174/1386207316666131230093802
Global Biotechnology Congress 2016Drug Discovery and Therapy World Congress 2016

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