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

56 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 ).

Funding

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 ).

FundersFunder number
National Science Foundation (NSF)CHE-1111761
National Institutes of Health (NIH)RC1MH088480
National Institute on Drug AbuseR01DA025100
National Natural Science Foundation of China (NSFC)20925206, 20932005
National Basic Research Program of China (973 Program)2010CB126103

    ASJC Scopus subject areas

    • Pharmacology
    • Drug Discovery

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