Literature DB >> 10860738

Co-evolution of proteins with their interaction partners.

C S Goh1, A A Bogan, M Joachimiak, D Walther, F E Cohen.   

Abstract

The divergent evolution of proteins in cellular signaling pathways requires ligands and their receptors to co-evolve, creating new pathways when a new receptor is activated by a new ligand. However, information about the evolution of binding specificity in ligand-receptor systems is difficult to glean from sequences alone. We have used phosphoglycerate kinase (PGK), an enzyme that forms its active site between its two domains, to develop a standard for measuring the co-evolution of interacting proteins. The N-terminal and C-terminal domains of PGK form the active site at their interface and are covalently linked. Therefore, they must have co-evolved to preserve enzyme function. By building two phylogenetic trees from multiple sequence alignments of each of the two domains of PGK, we have calculated a correlation coefficient for the two trees that quantifies the co-evolution of the two domains. The correlation coefficient for the trees of the two domains of PGK is 0. 79, which establishes an upper bound for the co-evolution of a protein domain with its binding partner. The analysis is extended to ligands and their receptors, using the chemokines as a model. We show that the correlation between the chemokine ligand and receptor trees' distances is 0.57. The chemokine family of protein ligands and their G-protein coupled receptors have co-evolved so that each subgroup of chemokine ligands has a matching subgroup of chemokine receptors. The matching subfamilies of ligands and their receptors create a framework within which the ligands of orphan chemokine receptors can be more easily determined. This approach can be applied to a variety of ligand and receptor systems. Copyright 2000 Academic Press.

Mesh:

Substances:

Year:  2000        PMID: 10860738     DOI: 10.1006/jmbi.2000.3732

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


  147 in total

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Authors:  S W Chensue
Journal:  Clin Microbiol Rev       Date:  2001-10       Impact factor: 26.132

2.  SiteLight: binding-site prediction using phage display libraries.

Authors:  Inbal Halperin; Haim Wolfson; Ruth Nussinov
Journal:  Protein Sci       Date:  2003-07       Impact factor: 6.725

3.  Coevolutionary patterns in plasminogen activation.

Authors:  Inna P Gladysheva; Ryan B Turner; Irina Y Sazonova; Lin Liu; Guy L Reed
Journal:  Proc Natl Acad Sci U S A       Date:  2003-07-23       Impact factor: 11.205

4.  Computational approaches to protein-protein interaction.

Authors:  Giacomo Franzot; Oliviero Carugo
Journal:  J Struct Funct Genomics       Date:  2003

5.  ADVICE: Automated Detection and Validation of Interaction by Co-Evolution.

Authors:  Soon-Heng Tan; Zhuo Zhang; See-Kiong Ng
Journal:  Nucleic Acids Res       Date:  2004-07-01       Impact factor: 16.971

6.  Coevolution of gene expression among interacting proteins.

Authors:  Hunter B Fraser; Aaron E Hirsh; Dennis P Wall; Michael B Eisen
Journal:  Proc Natl Acad Sci U S A       Date:  2004-06-02       Impact factor: 11.205

7.  Accelerated evolution and coevolution drove the evolutionary history of AGPase sub-units during angiosperm radiation.

Authors:  Jonathan Corbi; Julien Y Dutheil; Catherine Damerval; Maud I Tenaillon; Domenica Manicacci
Journal:  Ann Bot       Date:  2012-02-02       Impact factor: 4.357

8.  Evolutionary rate covariation reveals shared functionality and coexpression of genes.

Authors:  Nathan L Clark; Eric Alani; Charles F Aquadro
Journal:  Genome Res       Date:  2012-01-27       Impact factor: 9.043

Review 9.  Proteome-wide prediction of protein-protein interactions from high-throughput data.

Authors:  Zhi-Ping Liu; Luonan Chen
Journal:  Protein Cell       Date:  2012-06-22       Impact factor: 14.870

10.  Detecting coevolution through allelic association between physically unlinked loci.

Authors:  Rori V Rohlfs; Willie J Swanson; Bruce S Weir
Journal:  Am J Hum Genet       Date:  2010-04-08       Impact factor: 11.025

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