Structure-based methods for predicting target mutation-induced drug resistance and rational drug design to overcome the problem

Ge Fei Hao, Guang Fu Yang, Chang Guo Zhan

Research output: Contribution to journalReview articlepeer-review

44 Scopus citations

Abstract

Drug resistance has become one of the biggest challenges in drug discovery and/or development and has attracted great research interests worldwide. During the past decade, computational strategies have been developed to predict target mutation-induced drug resistance. Meanwhile, various molecular design strategies, including targeting protein backbone, targeting highly conserved residues and dual/multiple targeting, have been used to design novel inhibitors for combating the drug resistance. In this article we review recent advances in development of computational methods for target mutation-induced drug resistance prediction and strategies for rational design of novel inhibitors that could be effective against the possible drug-resistant mutants of the target.

Original languageEnglish
Pages (from-to)1121-1126
Number of pages6
JournalDrug Discovery Today
Volume17
Issue number19-20
DOIs
StatePublished - Oct 2012

Bibliographical note

Funding Information:
This work was supported in part by the National Basic Research Program of China (grant no. 2010CB126103 ), NSFC (grants nos. 20925206 and 20932005 ), NSF (grant CHE-1111761 ) and NIH (grant RC1MH088480 ).

ASJC Scopus subject areas

  • Pharmacology
  • Drug Discovery

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