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PHARMACOGENOINFORMATICS: MODELING OF P-GLYCOPROTEIN AND NOVEL APPROACH OF In Silico DRUG DESIGNING BASED ON GENETIC VARIATION OF MDR1 GENE INVOLVED IN STATIN RESISTANCE

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Author(s): Sai Babu M., Venkateswara Rao A., Lakshman Teja G., Subash Kaul, Jyothy A. and Anjana Munshi

Journal: International Journal of Drug Discovery
ISSN 0975-4423

Volume: 4;
Issue: 1;
Start page: 145;
Date: 2012;
Original page

Keywords: Statin resistance | MDR1 gene | Polymorphism | P-gp | HMG Co-A | MOE | Modeling | drug designing | docking.

ABSTRACT
Statins are the most prescribed drugs, highly effective in reducing the risk of cardiovascular and cerebrovascular events, primarily by lowering low density lipoprotein (LDL) cholesterol. Although large clinical trials found a 27% average relative risk reduction of major coronary events, there is large variability in benefits from statin therapy. Researchers have found three SNPs (C3435T, G2677T/A, C1236T) of MDR1gene, which codes for P-Glycoprotein (P-gp) (a drug efflux transporter), responsible for the reduced bioavailability of statins. We aimed to design a new drug molecule based on synonymous and nonsynonymous SNPs of MDR1 gene, which is not a substrate to P-gp and acts directly on ßhydroxy methylglutaryl coenzyme A reductase (HMG-CoA), a target site for statins, using Insilico tools. Structural changes in mRNA due to synonymous and nonsynonymous SNPs were evaluated by SNPfold. The 3D structures of normal and mutant proteins of P-gp and HMG-CoA reductase were modeled by Molecular Operating Environment (MOE). A new lead molecule was designed from native structure by VegaZZ and parameters of drug were validated with HyperChem and Pharmacophore mapping was done using LigandScout. We docked the lead molecule with normal and mutant P-gp and found no interactions with P-gp showing that it is not a substrate for P-gp. However, it forms clear hydrogen bond interactions with HMG-CoA reductase. This is a novel approach in the field of bioinformatics and pharmacogenomics (pharmacogenoinformatics) for the development of new drug molecules based on the SNPs of genes involved in drug metabolism in a particular population.

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