Literature DB >> 18831050

Coevolution in defining the functional specificity.

Saikat Chakrabarti1, Anna R Panchenko.   

Abstract

Covariation between sites can arise due to a common evolutionary history. At the same time, structure and function of proteins play significant role in evolvability of different sites that are not directly connected with the common ancestry. The nature of forces which cause residues to coevolve is still not thoroughly understood, it is especially not clear how coevolutionary processes are related to functional diversification within protein families. We analyzed both functional and structural factors that might cause covariation of specificity determinants and showed that they more often participate in coevolutionary relationships with each other and other sites compared with functional sites and those sites that are not under strong functional constraints. We also found that protein sites with higher number of coevolutionary connections with other sites have a tendency to evolve slower. Our results indicate that in some cases coevolutionary connections exist between specificity sites that are located far away in space but are under similar functional constraints. Such correlated changes and compensations can be realized through the stepwise coevolutionary processes which in turn can shed light on the mechanisms of functional diversification. (c) 2008 Wiley-Liss, Inc.

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Year:  2009        PMID: 18831050      PMCID: PMC2649964          DOI: 10.1002/prot.22239

Source DB:  PubMed          Journal:  Proteins        ISSN: 0887-3585


  62 in total

1.  Co-evolution of proteins with their interaction partners.

Authors:  C S Goh; A A Bogan; M Joachimiak; D Walther; F E Cohen
Journal:  J Mol Biol       Date:  2000-06-02       Impact factor: 5.469

2.  Effective use of sequence correlation and conservation in fold recognition.

Authors:  O Olmea; B Rost; A Valencia
Journal:  J Mol Biol       Date:  1999-11-12       Impact factor: 5.469

3.  Correlations among amino acid sites in bHLH protein domains: an information theoretic analysis.

Authors:  W R Atchley; K R Wollenberg; W M Fitch; W Terhalle; A W Dress
Journal:  Mol Biol Evol       Date:  2000-01       Impact factor: 16.240

4.  Analysis of covariation in an SH3 domain sequence alignment: applications in tertiary contact prediction and the design of compensating hydrophobic core substitutions.

Authors:  S M Larson; A A Di Nardo; A R Davidson
Journal:  J Mol Biol       Date:  2000-10-27       Impact factor: 5.469

5.  Exploring a phylogenetic approach for the detection of correlated substitutions in proteins.

Authors:  P Tuff; P Darlu
Journal:  Mol Biol Evol       Date:  2000-11       Impact factor: 16.240

6.  Analysis and prediction of functional sub-types from protein sequence alignments.

Authors:  S S Hannenhalli; R B Russell
Journal:  J Mol Biol       Date:  2000-10-13       Impact factor: 5.469

7.  AL2CO: calculation of positional conservation in a protein sequence alignment.

Authors:  J Pei; N V Grishin
Journal:  Bioinformatics       Date:  2001-08       Impact factor: 6.937

8.  Evaluation of a novel method for the identification of coevolving protein residues.

Authors:  L Pritchard; P Bladon; J M O Mitchell; M J Dufton
Journal:  Protein Eng       Date:  2001-08

9.  Separation of phylogenetic and functional associations in biological sequences by using the parametric bootstrap.

Authors:  K R Wollenberg; W R Atchley
Journal:  Proc Natl Acad Sci U S A       Date:  2000-03-28       Impact factor: 11.205

10.  Determinants of protein function revealed by combinatorial entropy optimization.

Authors:  Boris Reva; Yevgeniy Antipin; Chris Sander
Journal:  Genome Biol       Date:  2007       Impact factor: 13.583

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  33 in total

1.  Basis for substrate recognition and distinction by matrix metalloproteinases.

Authors:  Boris I Ratnikov; Piotr Cieplak; Kosi Gramatikoff; James Pierce; Alexey Eroshkin; Yoshinobu Igarashi; Marat Kazanov; Qing Sun; Adam Godzik; Andrei Osterman; Boguslaw Stec; Alex Strongin; Jeffrey W Smith
Journal:  Proc Natl Acad Sci U S A       Date:  2014-09-22       Impact factor: 11.205

2.  Intramolecular allosteric communication in dopamine D2 receptor revealed by evolutionary amino acid covariation.

Authors:  Yun-Min Sung; Angela D Wilkins; Gustavo J Rodriguez; Theodore G Wensel; Olivier Lichtarge
Journal:  Proc Natl Acad Sci U S A       Date:  2016-03-15       Impact factor: 11.205

Review 3.  Correlated positions in protein evolution and engineering.

Authors:  Jorick Franceus; Tom Verhaeghe; Tom Desmet
Journal:  J Ind Microbiol Biotechnol       Date:  2016-08-11       Impact factor: 3.346

4.  Evolutionary coupling analysis identifies the impact of disease-associated variants at less-conserved sites.

Authors:  Donghyo Kim; Seong Kyu Han; Kwanghwan Lee; Inhae Kim; JungHo Kong; Sanguk Kim
Journal:  Nucleic Acids Res       Date:  2019-09-19       Impact factor: 16.971

5.  Engineering repressors with coevolutionary cues facilitates toggle switches with a master reset.

Authors:  Rey P Dimas; Xian-Li Jiang; Jose Alberto de la Paz; Faruck Morcos; Clement T Y Chan
Journal:  Nucleic Acids Res       Date:  2019-06-04       Impact factor: 16.971

6.  Functionally important positions can comprise the majority of a protein's architecture.

Authors:  Sudheer Tungtur; Daniel J Parente; Liskin Swint-Kruse
Journal:  Proteins       Date:  2011-03-04

7.  Networks of high mutual information define the structural proximity of catalytic sites: implications for catalytic residue identification.

Authors:  Cristina Marino Buslje; Elin Teppa; Tomas Di Doménico; José María Delfino; Morten Nielsen
Journal:  PLoS Comput Biol       Date:  2010-11-04       Impact factor: 4.475

8.  Comparing the functional roles of nonconserved sequence positions in homologous transcription repressors: implications for sequence/function analyses.

Authors:  Sudheer Tungtur; Sarah Meinhardt; Liskin Swint-Kruse
Journal:  J Mol Biol       Date:  2009-10-08       Impact factor: 5.469

9.  Structural and functional roles of coevolved sites in proteins.

Authors:  Saikat Chakrabarti; Anna R Panchenko
Journal:  PLoS One       Date:  2010-01-06       Impact factor: 3.240

10.  Ensemble approach to predict specificity determinants: benchmarking and validation.

Authors:  Saikat Chakrabarti; Anna R Panchenko
Journal:  BMC Bioinformatics       Date:  2009-07-02       Impact factor: 3.169

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