Literature DB >> 12149452

Roles of mutation and recombination in the evolution of protein thermodynamics.

Yu Xia1, Michael Levitt.   

Abstract

We present a comprehensive study of the evolutionary origin of the thermodynamic behavior of proteins. With the use of a simplified model, we exhaustively enumerate the space of all sequences and the space of all structures, simulate the evolutionary relationship between sequences and structures, and characterize the steady-state sequence distribution for all structures in terms of several thermodynamic variables. We assess the effects of two major forces of evolution: mutation and recombination. Three simplifications are made. First, a two-dimensional lattice model is used to represent protein sequences and structures. Second, proteins undergo neutral evolution so that the fitness landscape has a flat allowed region inside of which all sequences are equally fit. Third, we ignore otherwise important factors such as finite population size and evolutionary time. Two scenarios emerge from our study. The first occurs when evolution is dominated by mutation events. Even though the prototype sequence that is most mutationally robust is preferred by evolution, the preference is not strong enough to offset the huge size of sequence space. Most native sequences are located near the boundary of the fitness region and are marginally compatible with the native structure. The second scenario occurs when evolution is dominated by recombination events. Now evolutionary preference for prototype sequence is strong enough to overcome the size of sequence space so that most native sequences are located near the center of sequence-structure compatibility. We conclude that the relative frequency of mutation and recombination events is a major determinant of how optimal protein sequences are for their structures.

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Year:  2002        PMID: 12149452      PMCID: PMC124923          DOI: 10.1073/pnas.162097799

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  49 in total

1.  Computational method to reduce the search space for directed protein evolution.

Authors:  C A Voigt; S L Mayo; F H Arnold; Z G Wang
Journal:  Proc Natl Acad Sci U S A       Date:  2001-03-27       Impact factor: 11.205

2.  Hiking in the energy landscape in sequence space: a bumpy road to good folders.

Authors:  G Tiana; R A Broglia; E I Shakhnovich
Journal:  Proteins       Date:  2000-05-15

3.  The distribution of structures in evolving protein populations.

Authors:  D M Taverna; R A Goldstein
Journal:  Biopolymers       Date:  2000-01       Impact factor: 2.505

4.  Improving the performance of Rosetta using multiple sequence alignment information and global measures of hydrophobic core formation.

Authors:  R Bonneau; C E Strauss; D Baker
Journal:  Proteins       Date:  2001-04-01

5.  Prospects for ab initio protein structural genomics.

Authors:  K T Simons; C Strauss; D Baker
Journal:  J Mol Biol       Date:  2001-03-09       Impact factor: 5.469

6.  Native protein sequences are close to optimal for their structures.

Authors:  B Kuhlman; D Baker
Journal:  Proc Natl Acad Sci U S A       Date:  2000-09-12       Impact factor: 11.205

7.  Global mapping of meiotic recombination hotspots and coldspots in the yeast Saccharomyces cerevisiae.

Authors:  J L Gerton; J DeRisi; R Shroff; M Lichten; P O Brown; T D Petes
Journal:  Proc Natl Acad Sci U S A       Date:  2000-10-10       Impact factor: 11.205

8.  Ab initio construction of protein tertiary structures using a hierarchical approach.

Authors:  Y Xia; E S Huang; M Levitt; R Samudrala
Journal:  J Mol Biol       Date:  2000-06-30       Impact factor: 5.469

9.  De novo protein design. II. Plasticity in sequence space.

Authors:  P Koehl; M Levitt
Journal:  J Mol Biol       Date:  1999-11-12       Impact factor: 5.469

10.  Buried charged surface in proteins.

Authors:  T Kajander; P C Kahn; S H Passila; D C Cohen; L Lehtiö; W Adolfsen; J Warwicker; U Schell; A Goldman
Journal:  Structure       Date:  2000-11-15       Impact factor: 5.006

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  22 in total

1.  Stability and the evolvability of function in a model protein.

Authors:  Jesse D Bloom; Claus O Wilke; Frances H Arnold; Christoph Adami
Journal:  Biophys J       Date:  2004-05       Impact factor: 4.033

2.  Repeat-modulated population genetic effects in fungal proteins.

Authors:  F N Braun; D A Liberles
Journal:  J Mol Evol       Date:  2004-07       Impact factor: 2.395

3.  Statistical properties of neutral evolution.

Authors:  Ugo Bastolla; Markus Porto; H Eduardo Roman; Michele Vendruscolo
Journal:  J Mol Evol       Date:  2003       Impact factor: 2.395

4.  Funnel-like organization in sequence space determines the distributions of protein stability and folding rate preferred by evolution.

Authors:  Yu Xia; Michael Levitt
Journal:  Proteins       Date:  2004-04-01

5.  Imprint of evolution on protein structures.

Authors:  Guido Tiana; Boris E Shakhnovich; Nikolay V Dokholyan; Eugene I Shakhnovich
Journal:  Proc Natl Acad Sci U S A       Date:  2004-02-17       Impact factor: 11.205

6.  Evolvability and single-genotype fluctuation in phenotypic properties: a simple heteropolymer model.

Authors:  Tao Chen; David Vernazobres; Tetsuya Yomo; Erich Bornberg-Bauer; Hue Sun Chan
Journal:  Biophys J       Date:  2010-06-02       Impact factor: 4.033

7.  Comparing folding codes in simple heteropolymer models of protein evolutionary landscape: robustness of the superfunnel paradigm.

Authors:  Richard Wroe; Erich Bornberg-Bauer; Hue Sun Chan
Journal:  Biophys J       Date:  2004-10-22       Impact factor: 4.033

8.  Evolution of structural shape in bacterial globin-related proteins.

Authors:  Lorraine Marsh
Journal:  J Mol Evol       Date:  2006-04-11       Impact factor: 2.395

9.  A nonadaptive origin of a beneficial trait: in silico selection for free energy of folding leads to the neutral emergence of mutational robustness in single domain proteins.

Authors:  Rafael F Pagan; Steven E Massey
Journal:  J Mol Evol       Date:  2013-12-21       Impact factor: 2.395

10.  Quantifying the Mutational Robustness of Protein-Coding Genes.

Authors:  Evandro Ferrada
Journal:  J Mol Evol       Date:  2021-05-02       Impact factor: 2.395

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