Literature DB >> 23458856

Emerging methods in protein co-evolution.

David de Juan1, Florencio Pazos, Alfonso Valencia.   

Abstract

Co-evolution is a fundamental component of the theory of evolution and is essential for understanding the relationships between species in complex ecological networks. A wide range of co-evolution-inspired computational methods has been designed to predict molecular interactions, but it is only recently that important advances have been made. Breakthroughs in the handling of phylogenetic information and in disentangling indirect relationships have resulted in an improved capacity to predict interactions between proteins and contacts between different protein residues. Here, we review the main co-evolution-based computational approaches, their theoretical basis, potential applications and foreseeable developments.

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Year:  2013        PMID: 23458856     DOI: 10.1038/nrg3414

Source DB:  PubMed          Journal:  Nat Rev Genet        ISSN: 1471-0056            Impact factor:   53.242


  102 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.  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

3.  Tight coevolution of proliferating cell nuclear antigen (PCNA)-partner interaction networks in fungi leads to interspecies network incompatibility.

Authors:  Lyad Zamir; Marianna Zaretsky; Yearit Fridman; Hadas Ner-Gaon; Eitan Rubin; Amir Aharoni
Journal:  Proc Natl Acad Sci U S A       Date:  2012-01-17       Impact factor: 11.205

4.  Inferring functional linkages between proteins from evolutionary scenarios.

Authors:  Yun Zhou; Rui Wang; Li Li; Xuefeng Xia; Zhirong Sun
Journal:  J Mol Biol       Date:  2006-04-24       Impact factor: 5.469

Review 5.  Predicting biological networks from genomic data.

Authors:  Eoghan D Harrington; Lars J Jensen; Peer Bork
Journal:  FEBS Lett       Date:  2008-02-21       Impact factor: 4.124

6.  Protein interactions and ligand binding: from protein subfamilies to functional specificity.

Authors:  Antonio Rausell; David Juan; Florencio Pazos; Alfonso Valencia
Journal:  Proc Natl Acad Sci U S A       Date:  2010-01-19       Impact factor: 11.205

7.  Learning generative models for protein fold families.

Authors:  Sivaraman Balakrishnan; Hetunandan Kamisetty; Jaime G Carbonell; Su-In Lee; Christopher James Langmead
Journal:  Proteins       Date:  2011-01-25

8.  Hot spots for allosteric regulation on protein surfaces.

Authors:  Kimberly A Reynolds; Richard N McLaughlin; Rama Ranganathan
Journal:  Cell       Date:  2011-12-23       Impact factor: 41.582

9.  Combining specificity determining and conserved residues improves functional site prediction.

Authors:  Olga V Kalinina; Mikhail S Gelfand; Robert B Russell
Journal:  BMC Bioinformatics       Date:  2009-06-09       Impact factor: 3.169

10.  Coevolution of interacting fertilization proteins.

Authors:  Nathaniel L Clark; Joe Gasper; Masashi Sekino; Stevan A Springer; Charles F Aquadro; Willie J Swanson
Journal:  PLoS Genet       Date:  2009-07-24       Impact factor: 5.917

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  232 in total

1.  From residue coevolution to protein conformational ensembles and functional dynamics.

Authors:  Ludovico Sutto; Simone Marsili; Alfonso Valencia; Francesco Luigi Gervasio
Journal:  Proc Natl Acad Sci U S A       Date:  2015-10-20       Impact factor: 11.205

2.  Protein contact prediction by integrating joint evolutionary coupling analysis and supervised learning.

Authors:  Jianzhu Ma; Sheng Wang; Zhiyong Wang; Jinbo Xu
Journal:  Bioinformatics       Date:  2015-08-14       Impact factor: 6.937

3.  Constructing sequence-dependent protein models using coevolutionary information.

Authors:  Ryan R Cheng; Mohit Raghunathan; Jeffrey K Noel; José N Onuchic
Journal:  Protein Sci       Date:  2015-08-10       Impact factor: 6.725

Review 4.  Applying evolutionary genetics to developmental toxicology and risk assessment.

Authors:  Maxwell C K Leung; Andrew C Procter; Jared V Goldstone; Jonathan Foox; Robert DeSalle; Carolyn J Mattingly; Mark E Siddall; Alicia R Timme-Laragy
Journal:  Reprod Toxicol       Date:  2017-03-04       Impact factor: 3.143

5.  An evolution-based strategy for engineering allosteric regulation.

Authors:  David Pincus; Orna Resnekov; Kimberly A Reynolds
Journal:  Phys Biol       Date:  2017-04-28       Impact factor: 2.583

Review 6.  Engineering the acyltransferase substrate specificity of assembly line polyketide synthases.

Authors:  Briana J Dunn; Chaitan Khosla
Journal:  J R Soc Interface       Date:  2013-05-29       Impact factor: 4.118

Review 7.  The functional importance of co-evolving residues in proteins.

Authors:  Inga Sandler; Nitzan Zigdon; Efrat Levy; Amir Aharoni
Journal:  Cell Mol Life Sci       Date:  2013-09-01       Impact factor: 9.261

Review 8.  Aspartate aminotransferase: an old dog teaches new tricks.

Authors:  Michael D Toney
Journal:  Arch Biochem Biophys       Date:  2013-10-09       Impact factor: 4.013

9.  Coevolutionary signals across protein lineages help capture multiple protein conformations.

Authors:  Faruck Morcos; Biman Jana; Terence Hwa; José N Onuchic
Journal:  Proc Natl Acad Sci U S A       Date:  2013-12-02       Impact factor: 11.205

10.  Molecular Evolution of rbcL in Orthotrichales (Bryophyta): Site Variation, Adaptive Evolution, and Coevolutionary Patterns of Amino Acid Replacements.

Authors:  Moisès Bernabeu; Josep A Rosselló
Journal:  J Mol Evol       Date:  2021-02-20       Impact factor: 2.395

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