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How can we best use structural information on P-glycoprotein to design inhibitors?

期刊

PHARMACOLOGY & THERAPEUTICS
卷 113, 期 2, 页码 429-441

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.pharmthera.2006.10.003

关键词

P-glycoprotein; multidrug resistance; cancer; structure-based drug design; membrane protein structure; ABC transporters

资金

  1. Medical Research Council [G0400631] Funding Source: Medline
  2. Medical Research Council [G0400631] Funding Source: researchfish
  3. MRC [G0400631] Funding Source: UKRI

向作者/读者索取更多资源

This year marks the 30th anniversary of the discovery of the multidrug resistance (MDR) ATP-binding cassette (ABC) transporter P-glycoprotein (P-gp). Since then a considerable research effort has attempted to provide a greater understanding of the biological enigma of I'multidrug efflux. Moreover, the growing correlation between P-gp expression and a negative prognosis or poor outcome for chemotherapy has sparked significant interest in the generation of inhibitors. How close are we to overcoming the unwanted actions of P-gp in resistant cancer following 30 years of research? The initial inhibitors were pre-existing clinically used compounds and exploited the broad specificity of P-gp. Unfortunately, the concentrations required to inhibit P-gp meant that these compounds generated considerable toxicity. Pharmacological investigations progressed to rational design using the 1st generation compounds as a template structure. Inherent toxicity of the drugs was reduced; however, pharmacokinetic interactions with the anticancer drugs were unsustainable. Generation of the most recent of inhibitors employed combinatorial chemistry to produce a handful of potent and selective P-gp inhibitors. Some of these drugs have progressed to clinical trials with poor results or in some cases, undisclosed progress. There remains a clear need for the generation of P-gp inhibitors and this review describes the potential for a structure-based design to facilitate this undertaking. In particular, the plethora of functional data can provide important regions on the protein that could conceivably be exploited as inhibitor targets. (c) 2006 Elsevier Inc. All rights reserved.

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