Literature DB >> 10074416

Coevolving protein residues: maximum likelihood identification and relationship to structure.

D D Pollock1, W R Taylor, N Goldman.   

Abstract

The identification of protein sites undergoing correlated evolution (coevolution) is of great interest due to the possibility that these pairs will tend to be adjacent in the three-dimensional structure. Identification of such pairs should provide useful information for understanding the evolutionary process, predicting the effects of site-directed substitution, and potentially for predicting protein structure. Here, we develop and apply a maximum likelihood method with the aim of improving detection of coevolution. Unlike previous methods which have had limited success, this method allows for correlations induced by phylogenetic relationships and for variation in rate of evolution along branches, and does not rely on accurate reconstruction of ancestral nodes. In order to reduce the complexity of coevolutionary relationships and identify the primary component of pairwise coevolution between two sites, we reduce the data to a two-state system at each site, regardless of the actual number of residues observed at that site. Simulations show that this strategy is good at identifying simple correlations and at recognizing cases in which the data are insufficient to distinguish between coevolution and spurious correlations. The new method was tested by using size and charge characteristics to group the residues at each site, and then evaluating coevolution in myoglobin sequences. Grouping based on physicochemical characteristics allows categorization of coevolving sites into positive and negative coevolution, depending on the correlation between equilibrium state frequencies. We detected a striking excess of negative coevolution (corresponding to charge) at sites brought into proximity by the periodicity of the alpha-helix, and there was also a tendency for sites with significant likelihood ratios to be close in the three-dimensional structure. Sites on the surface of the protein appear to coevolve both when they are close in the structure, and when they are distant, implying a role for folding and/or avoidance of quaternary structure in the coevolution process. Copyright 1998 Academic Press.

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Year:  1999        PMID: 10074416     DOI: 10.1006/jmbi.1998.2601

Source DB:  PubMed          Journal:  J Mol Biol        ISSN: 0022-2836            Impact factor:   5.469


  88 in total

1.  A likelihood ratio test for evolutionary rate shifts and functional divergence among proteins.

Authors:  B Knudsen; M M Miyamoto
Journal:  Proc Natl Acad Sci U S A       Date:  2001-12-04       Impact factor: 11.205

2.  Finding important sites in protein sequences.

Authors:  Peter J Bickel; Katherina J Kechris; Philip C Spector; Gary J Wedemayer; Alexander N Glazer
Journal:  Proc Natl Acad Sci U S A       Date:  2002-11-04       Impact factor: 11.205

3.  Inferring functional constraints and divergence in protein families using 3D mapping of phylogenetic information.

Authors:  Christian Blouin; Yan Boucher; Andrew J Roger
Journal:  Nucleic Acids Res       Date:  2003-01-15       Impact factor: 16.971

Review 4.  Genomic biodiversity, phylogenetics and coevolution in proteins.

Authors:  David D Pollock
Journal:  Appl Bioinformatics       Date:  2002

5.  Estimating the degree of saturation in mutant screens.

Authors:  David D Pollock; John C Larkin
Journal:  Genetics       Date:  2004-09       Impact factor: 4.562

6.  Protein topology from predicted residue contacts.

Authors:  William R Taylor; David T Jones; Michael I Sadowski
Journal:  Protein Sci       Date:  2011-12-21       Impact factor: 6.725

7.  Amino acid coevolution induces an evolutionary Stokes shift.

Authors:  David D Pollock; Grant Thiltgen; Richard A Goldstein
Journal:  Proc Natl Acad Sci U S A       Date:  2012-04-30       Impact factor: 11.205

8.  Incorporating gene-specific variation when inferring and evaluating optimal evolutionary tree topologies from multilocus sequence data.

Authors:  Tae-Kun Seo; Hirohisa Kishino; Jeffrey L Thorne
Journal:  Proc Natl Acad Sci U S A       Date:  2005-03-11       Impact factor: 11.205

9.  Context dependence and coevolution among amino acid residues in proteins.

Authors:  Zhengyuan O Wang; David D Pollock
Journal:  Methods Enzymol       Date:  2005       Impact factor: 1.600

Review 10.  Co-evolution analysis on endocrine research: a methodological approach.

Authors:  Tonghai Dou; Shuai Chen; Chaoneng Ji; Yi Xie; Yumin Mao
Journal:  Endocrine       Date:  2005-11       Impact factor: 3.633

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