Abstract
Human multidrug resistance ABC transporters are ubiquitous membrane proteins responsible for the efflux of multiple, endogenous or exogenous, compounds out of the cells, and therefore they are involved in multi-drug resistance phenotype (MDR). They thus deeply impact the pharmacokinetic parameters and toxicity properties of drugs. A great pressure to develop inhibitors of these pumps is carried out, by either ligand-based drug design or (more ideally) structure-based drug design. In that goal, many biochemical studies have been carried out to characterize their transport functions, and many efforts have been spent to get high-resolution structures. Currently, beside the 3D-structures of bacterial ABC transporters Sav1866 and MsbA, only the mouse ABCB1 complete structure has been published at high-resolution, illustrating the tremendous difficulty in getting such information, taking into account that the human genome accounts for 48 ABC transporters encoding genes. Homology modeling is consequently a reasonable approach to overcome this obstacle. The present review describes, in the first part, the different approaches which have been published to set up human ABC pump 3D-homology models allowing the localization of binding sites for drug candidates, and the identification of critical residues therein. In a second part, the review proposes a more accurate strategy and practical keys to use such biological tools for initiating structure-based drug design.
Keywords: Human, ABC transporter, 3D-Structure, Homology, Modeling, Docking, Drug Disposition, Multidrug resistance, pharmacokinetic parameters, multi-drug resistance phenotype (MDR), structure-based drug design
Current Drug Metabolism
Title: Multidrug Resistance ABC Transporter Structure Predictions by Homology Modeling Approaches
Volume: 12 Issue: 3
Author(s): Mylene Honorat, Pierre Falson, Raphael Terreux, Attilio Di Pietro, Charles Dumontet and Lea Payen
Affiliation:
Keywords: Human, ABC transporter, 3D-Structure, Homology, Modeling, Docking, Drug Disposition, Multidrug resistance, pharmacokinetic parameters, multi-drug resistance phenotype (MDR), structure-based drug design
Abstract: Human multidrug resistance ABC transporters are ubiquitous membrane proteins responsible for the efflux of multiple, endogenous or exogenous, compounds out of the cells, and therefore they are involved in multi-drug resistance phenotype (MDR). They thus deeply impact the pharmacokinetic parameters and toxicity properties of drugs. A great pressure to develop inhibitors of these pumps is carried out, by either ligand-based drug design or (more ideally) structure-based drug design. In that goal, many biochemical studies have been carried out to characterize their transport functions, and many efforts have been spent to get high-resolution structures. Currently, beside the 3D-structures of bacterial ABC transporters Sav1866 and MsbA, only the mouse ABCB1 complete structure has been published at high-resolution, illustrating the tremendous difficulty in getting such information, taking into account that the human genome accounts for 48 ABC transporters encoding genes. Homology modeling is consequently a reasonable approach to overcome this obstacle. The present review describes, in the first part, the different approaches which have been published to set up human ABC pump 3D-homology models allowing the localization of binding sites for drug candidates, and the identification of critical residues therein. In a second part, the review proposes a more accurate strategy and practical keys to use such biological tools for initiating structure-based drug design.
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Cite this article as:
Honorat Mylene, Falson Pierre, Terreux Raphael, Di Pietro Attilio, Dumontet Charles and Payen Lea, Multidrug Resistance ABC Transporter Structure Predictions by Homology Modeling Approaches, Current Drug Metabolism 2011; 12 (3) . https://dx.doi.org/10.2174/138920011795101804
DOI https://dx.doi.org/10.2174/138920011795101804 |
Print ISSN 1389-2002 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-5453 |
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