Literature DB >> 19731380

A perturbative view of protein structural variation.

Julián Echave1, Francisco M Fernández.   

Abstract

It was recently found that the lowest-energy collective normal modes dominate the evolutionary divergence of protein structures. This was attributed to a presumed functional importance of such motions, i.e., to natural selection. In contrast to this selectionist explanation, we proposed that the observed behavior could be just the expected physical response of proteins to random mutations. This proposal was based on the success of a linearly forced elastic network model (LFENM) of mutational effects on structure to account for the observed pattern of structural divergence. Here, to further test the mutational explanation and the LFENM, we analyze the structural differences observed not only in homologous (globin-like) proteins but also in unselected experimentally engineered myoglobin mutants and in wild-type variants subject to other perturbations such as ligand-binding and pH changes. We show that the lowest normal modes dominate structural change in all the cases considered and that the LFENM reproduces this behavior quantitatively. The collective nature of the lowest normal modes results in global conformational changes that depend little on the exact nature or location of the perturbation. Significantly, the evolutionarily conserved structural core matches the regions observed to be more robust with respect to mutations, so that the core would be more conserved even under unselected random mutations. In a word, the observed patterns of structural variation can be seen as the natural response of proteins to perturbations and can be adequately modeled using the LFENM, which serves as a common framework to relate a priori different phenomena. (c) 2009 Wiley-Liss, Inc.

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Year:  2010        PMID: 19731380     DOI: 10.1002/prot.22553

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


  20 in total

Review 1.  The interface of protein structure, protein biophysics, and molecular evolution.

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Journal:  Protein Sci       Date:  2012-04-23       Impact factor: 6.725

2.  Principal component analysis of binding energies for single-point mutants of hT2R16 bound to an agonist correlate with experimental mutant cell response.

Authors:  Derek E Chen; Darryl L Willick; Joseph B Ruckel; Wely B Floriano
Journal:  J Comput Biol       Date:  2015-01       Impact factor: 1.479

3.  Conformational dynamics of nonsynonymous variants at protein interfaces reveals disease association.

Authors:  Brandon M Butler; Z Nevin Gerek; Sudhir Kumar; S Banu Ozkan
Journal:  Proteins       Date:  2015-01-13

4.  A phylogenetic analysis of normal modes evolution in enzymes and its relationship to enzyme function.

Authors:  Jason Lai; Jing Jin; Jan Kubelka; David A Liberles
Journal:  J Mol Biol       Date:  2012-05-28       Impact factor: 5.469

5.  Evolutionary coupling range varies widely among enzymes depending on selection pressure.

Authors:  Julian Echave
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6.  Predicting evolutionary site variability from structure in viral proteins: buriedness, packing, flexibility, and design.

Authors:  Amir Shahmoradi; Dariya K Sydykova; Stephanie J Spielman; Eleisha L Jackson; Eric T Dawson; Austin G Meyer; Claus O Wilke
Journal:  J Mol Evol       Date:  2014-09-13       Impact factor: 2.395

7.  Structural dynamics flexibility informs function and evolution at a proteome scale.

Authors:  Zeynep Nevin Gerek; Sudhir Kumar; Sefika Banu Ozkan
Journal:  Evol Appl       Date:  2013-02-13       Impact factor: 5.183

8.  Mechanisms of intramolecular communication in a hyperthermophilic acylaminoacyl peptidase: a molecular dynamics investigation.

Authors:  Elena Papaleo; Giulia Renzetti; Matteo Tiberti
Journal:  PLoS One       Date:  2012-04-27       Impact factor: 3.240

9.  Comparison of the Internal Dynamics of Metalloproteases Provides New Insights on Their Function and Evolution.

Authors:  Henrique F Carvalho; Ana C A Roque; Olga Iranzo; Ricardo J F Branco
Journal:  PLoS One       Date:  2015-09-23       Impact factor: 3.240

10.  Using THz Spectroscopy, Evolutionary Network Analysis Methods, and MD Simulation to Map the Evolution of Allosteric Communication Pathways in c-Type Lysozymes.

Authors:  Kristina N Woods; Juergen Pfeffer
Journal:  Mol Biol Evol       Date:  2015-09-03       Impact factor: 16.240

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