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Bioinformatics Advance Access originally published online on March 28, 2008
Bioinformatics 2008 24(10):1243-1250; doi:10.1093/bioinformatics/btn110
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© 2008 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 correlated mutations in HIV-1 protease using spectral clustering

Ying Liu {dagger}, Eran Eyal {dagger} and Ivet Bahar *

Department of Computational Biology, School of Medicine, University of Pittsburgh, PA 15232, USA

*To whom correspondence should be addressed.


  Abstract

Motivation: The ability of human immunodeficiency virus-1 (HIV-1) protease to develop mutations that confer multi-drug resistance (MDR) has been a major obstacle in designing rational therapies against HIV. Resistance is usually imparted by a cooperative mechanism that can be elucidated by a covariance analysis of sequence data. Identification of such correlated substitutions of amino acids may be obscured by evolutionary noise.

Results: HIV-1 protease sequences from patients subjected to different specific treatments (set 1), and from untreated patients (set 2) were subjected to sequence covariance analysis by evaluating the mutual information (MI) between all residue pairs. Spectral clustering of the resulting covariance matrices disclosed two distinctive clusters of correlated residues: the first, observed in set 1 but absent in set 2, contained residues involved in MDR acquisition; and the second, included those residues differentiated in the various HIV-1 protease subtypes, shortly referred to as the phylogenetic cluster. The MDR cluster occupies sites close to the central symmetry axis of the enzyme, which overlap with the global hinge region identified from coarse-grained normal-mode analysis of the enzyme structure. The phylogenetic cluster, on the other hand, occupies solvent-exposed and highly mobile regions. This study demonstrates (i) the possibility of distinguishing between the correlated substitutions resulting from neutral mutations and those induced by MDR upon appropriate clustering analysis of sequence covariance data and (ii) a connection between global dynamics and functional substitution of amino acids.

Contact: bahar{at}ccbb.pitt.edu

Supplementary information: Supplementary data are available at Bioinformatics online.

{dagger}The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First Authors.

Associate Editor: Burkhard Rost

Received on December 19, 2007; revised on February 29, 2008; accepted on March 24, 2008

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