Abstract
Multi-drug resistance to the available antimalarial drugs is a major threat for malaria treatment. Due to the recent characterization of human and parasite genome sequences, both ligand and target based drug design strategies may be helpful for the design of potential antimalarial compounds with reduced degree of resistance. The present work deals with quantitative structure-activity relationship (QSAR) modeling, pharmacophore mapping and docking studies of a series of 95 nucleoside analogs as inhibitors of Plasmodium falciparum deoxyuridine-5'-triphosphate nucleotidohydrolase (PfdUTPase), an enzyme involved in nucleotide metabolism that acts as a first line of defence against uracil incorporation into DNA. The QSAR and pharmacophore models were validated both internally and externally showing good statistical results. The docking study was performed and validated using three different software tools namely Discovery Studio 2.1 (Accelrys), Maestro 9.3 (Schrodinger) and MOE (Chemical Computing Group). The QSAR studies revealed that compounds containing substituted aromatic carbons (aasC fragment) and those bearing hydroxyl groups without an noxolane ring exert potent PfdUTPase inhibitory activity. The best pharmacophore hypothesis (hypothesis 1) possessed four features: (i) one hydrogen bond donor (HBD), (ii) one hydrogen bond acceptor (HBA), (iii) one hydrophobic (HYD) and (iv) one ring aromatic (RA). The docking studies revealed that the PfdUTPase inhibitors interact with a pocket containing Phe46, Lys48, Leu88, Asn103, Gly106, Leu107, Ile108, Tyr112, Ile116, Ile117, Ala118 and Ala119 amino acid residues. The interaction pattern of all the PfdUTPase inhibitors was almost same in case of docking using Discovery Studio 2.1, Maestro 9.3 and MOE software. This work thus presents the first QSAR report for nucleoside analogs which may serve as an efficient tool to address the increasing threat of malaria in the developing countries.
Keywords: Docking, malaria, nucleoside analogs, PfdUTPase, pharmacophore, QSAR.
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Current Computer-Aided Drug Design
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