Nucleic Acids Research Advance Access originally published online on April 24, 2009
Nucleic Acids Research 2009 37(10):e74; doi:10.1093/nar/gkp251
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Nucleic Acids Research, 2009, Vol. 37, No. 10 e74
© 2009
The Author(s) This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Methods Online |
Identification of HCV protease inhibitor resistance mutations by selection pressure-based method
1Molecular Design and Informatics, Schering-Plough Research Institute, 2015 Galloping Hill Road, Kenilworth, NJ 07033, 2Preclinical and Clinical Bioanalytics, Schering-Plough Research Institute, 1011 Morris Avenue, Union, NJ 07083, 3Department of Virology and 4Department of Structural Chemistry, Schering-Plough Research Institute, 2015 Galloping Hill Road, Kenilworth, NJ 07033, USA
*To whom correspondence should be addressed. Tel: +1 980 740 4145; Fax: +1 908 740 4496; Email: ping.qiu{at}spcorp.com Correspondence may also be addressed to X. Tong. Tel: +1 980 740 7446; Fax: +1 908 740 3032; Email: xiao.tong{at}spcorp.com
Received December 23, 2008. Revised March 18, 2009. Accepted April 2, 2009.
A major challenge to successful antiviral therapy is the emergence of drug-resistant viruses. Recent studies have developed several automated analyses of HIV sequence polymorphism based on calculations of selection pressure (Ka/Ks) to predict drug resistance mutations. Similar resistance analysis programs for HCV inhibitors are not currently available. Taking advantage of the recently available sequence data of patient HCV samples from a Phase II clinical study of protease inhibitor boceprevir, we calculated the selection pressure for all codons in the HCV protease region (amino acid 1–181) to identify potential resistance mutations. The correlation between mutations was also calculated to evaluate linkage between any two mutations. Using this approach, we identified previously known major resistant mutations, including a recently reported mutation V55A. In addition, a novel mutation V158I was identified, and we further confirmed its resistance to boceprevir in protease enzyme and replicon assay. We also extended the approach to analyze potential interactions between individual mutations and identified three pairs of correlated changes. Our data suggests that selection pressure-based analysis and correlation mapping could provide useful tools to analyze large amount of sequencing data from clinical samples and to identify new drug resistance mutations as well as their linkage and correlations.
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