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Bioinformatics Advance Access originally published online on October 4, 2006
Bioinformatics 2006 22(24):2975-2979; doi:10.1093/bioinformatics/btl508
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© 2006 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.

Analysis of HIV-1 pol sequences using Bayesian Networks: implications for drug resistance

K. Deforche *, T. Silander 1, R. Camacho 2, Z . Grossman 3, M. A. Soares 4, K. Van Laethem , R. Kantor 5, Y. Moreau 6, A.-M. Vandamme and on behalf of the non-B Workgroup

Rega Institute for Medical Research, Katholieke Universiteit Leuven Leuven, Belgium
1 Helsinki Institute for Information Technology Helsinki, Finland
2 Virology Laboratory, Hospital Egas Moniz Lisbon, Portugal
3 Chaim Sheba Medical Center, Ministry of Health Tel-Aviv, Israel
4 Departamento de Genética, Universidade Federal do Rio de Janeiro Brazil
5 Brown University Providence, RI
6 ESAT, Katholieke Universiteit Leuven Leuven, Belgium

*To whom correspondence should be addressed.

Human Immunodeficiency Virus-1 (HIV-1) antiviral resistance is a major cause of antiviral therapy failure and compromises future treatment options. As a consequence, resistance testing is the standard of care. Because of the high degree of HIV-1 natural variation and complex interactions, the role of resistance mutations is in many cases insufficiently understood. We applied a probabilistic model, Bayesian networks, to analyze direct influences between protein residues and exposure to treatment in clinical HIV-1 protease sequences from diverse subtypes. We can determine the specific role of many resistance mutations against the protease inhibitor nelfinavir, and determine relationships between resistance mutations and polymorphisms. We can show for example that in addition to the well-known major mutations 90M and 30N for nelfinavir resistance, 88S should not be treated as 88D but instead considered as a major mutation and explain the subtype-dependent prevalence of the 30N resistance pathway.

Contact: koen.deforche{at}uz.kuleuven.ac.be

Supplementary information: Supplementary data are available at Bioinformatics online.

Received on May 25, 2006; revised on September 26, 2006; accepted on September 28, 2006

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