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Bioinformatics Advance Access originally published online on December 1, 2007
Bioinformatics 2008 24(2):290-292; doi:10.1093/bioinformatics/btm584
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© 2007 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.

An integrated system for studying residue coevolution in proteins

Kevin Y. Yip 1,{dagger}, Prianka Patel 2,{dagger}, Philip M. Kim 2, Donald M. Engelman 2, Drew McDermott 1 and Mark Gerstein 1,2,3,*

1Department of Computer Science, Yale University, 51 Prospect Street, New Haven, CT 06511, USA, 2Department of Molecular Biophysics and Biochemistry, Yale University, 266 Whitney Avenue, New Haven, CT 06520, USA and 3Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA

*To whom correspondence should be addressed.


  Abstract

Residue coevolution has recently emerged as an important concept, especially in the context of protein structures. While a multitude of different functions for quantifying it have been proposed, not much is known about their relative strengths and weaknesses. Also, subtle algorithmic details have discouraged implementing and comparing them. We addressed this issue by developing an integrated online system that enables comparative analyses with a comprehensive set of commonly used scoring functions, including Statistical Coupling Analysis (SCA), Explicit Likelihood of Subset Variation (ELSC), mutual information and correlation-based methods. A set of data preprocessing options are provided for improving the sensitivity and specificity of coevolution signal detection, including sequence weighting, residue grouping and the filtering of sequences, sites and site pairs. A total of more than 100 scoring variations are available. The system also provides facilities for studying the relationship between coevolution scores and inter-residue distances from a crystal structure if provided, which may help in understanding protein structures.

Availability: The system is available at http://coevolution.gersteinlab.org. The source code and JavaDoc API can also be downloaded from the web site.

Contact: mark.gerstein{at}yale.edu

Supplementary information: Additional materials can be found at http://coevolution.gersteinlab.org/coevolution/supp.jsp

{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: Olga Troyanskaya

Received on July 5, 2007; revised on October 4, 2007; accepted on November 20, 2007

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