Literature DB >> 19597162

Structural determinants of protein evolution are context-sensitive at the residue level.

Eric A Franzosa1, Yu Xia.   

Abstract

Structural properties of a protein residue's microenvironment have long been implicated as agents of selective constraint. Although these properties are inherently quantitative, structure-based studies of protein evolution tend to rely upon coarse distinctions between "surface" and "buried" residues and between "interfacial" and "noninterfacial" residues. Using homology-mapped yeast protein structures, we explore the relationships between residue evolution and continuous structural properties of the residue microenvironment, including solvent accessibility, density and distribution of residue-residue contacts, and burial depth. We confirm the role of solvent exposure as a major structural determinant of residue evolution and also identify a weak secondary effect arising from packing density. The relationship between solvent exposure and evolutionary rate (d(N)/d(S)) is found to be strong, positive, and linear. This reinforces the notion that residue burial is a continuous property with quantitative fitness implications. Next, we demonstrate systematic variation in residue-level structure-evolution relationships resulting from changes in global physical and biological contexts. We find that increasing protein-core size yields a more rapid relaxation of selective constraint as solvent exposure increases, although solvent-excluded residues remain similarly constrained. Finally, we analyze the selective constraint in protein-protein interfaces, revealing two fundamentally different yet separable components: continuous structural constraint that scales with total residue burial and a more surprising fixed functional constraint that accompanies any degree of interface involvement. These discoveries serve to elucidate and unite structure-evolution relationships at the residue and whole-protein levels.

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Year:  2009        PMID: 19597162     DOI: 10.1093/molbev/msp146

Source DB:  PubMed          Journal:  Mol Biol Evol        ISSN: 0737-4038            Impact factor:   16.240


  82 in total

1.  Thermodynamic stability explains the differential evolutionary dynamics of cytochrome b and COX I in mammals.

Authors:  Juan Carlos Aledo; Héctor Valverde; Manuel Ruíz-Camacho
Journal:  J Mol Evol       Date:  2012-02-24       Impact factor: 2.395

2.  Structural principles within the human-virus protein-protein interaction network.

Authors:  Eric A Franzosa; Yu Xia
Journal:  Proc Natl Acad Sci U S A       Date:  2011-06-16       Impact factor: 11.205

3.  The relationship between relative solvent accessibility and evolutionary rate in protein evolution.

Authors:  Duncan C Ramsey; Michael P Scherrer; Tong Zhou; Claus O Wilke
Journal:  Genetics       Date:  2011-04-05       Impact factor: 4.562

4.  Testing whether metazoan tyrosine loss was driven by selection against promiscuous phosphorylation.

Authors:  Siddharth Pandya; Travis J Struck; Brian K Mannakee; Mary Paniscus; Ryan N Gutenkunst
Journal:  Mol Biol Evol       Date:  2014-10-13       Impact factor: 16.240

5.  Maximum-Likelihood Phylogenetic Inference with Selection on Protein Folding Stability.

Authors:  Miguel Arenas; Agustin Sánchez-Cobos; Ugo Bastolla
Journal:  Mol Biol Evol       Date:  2015-04-02       Impact factor: 16.240

6.  Comparative laboratory evolution of ordered and disordered enzymes.

Authors:  Cindy Schulenburg; Yvonne Stark; Matthias Künzle; Donald Hilvert
Journal:  J Biol Chem       Date:  2015-02-19       Impact factor: 5.157

7.  Two frequenins in Drosophila: unveiling the evolutionary history of an unusual neuronal calcium sensor (NCS) duplication.

Authors:  Alejandro Sánchez-Gracia; Jesús Romero-Pozuelo; Alberto Ferrús
Journal:  BMC Evol Biol       Date:  2010-02-19       Impact factor: 3.260

8.  Gene promoter evolution targets the center of the human protein interaction network.

Authors:  Jordi Planas; Josep M Serrat
Journal:  PLoS One       Date:  2010-07-08       Impact factor: 3.240

9.  Intermediate divergence levels maximize the strength of structure-sequence correlations in enzymes and viral proteins.

Authors:  Eleisha L Jackson; Amir Shahmoradi; Stephanie J Spielman; Benjamin R Jack; Claus O Wilke
Journal:  Protein Sci       Date:  2016-03-24       Impact factor: 6.725

10.  Semirational Directed Evolution of Loop Regions in Aspergillus japonicus β-Fructofuranosidase for Improved Fructooligosaccharide Production.

Authors:  K M Trollope; J F Görgens; H Volschenk
Journal:  Appl Environ Microbiol       Date:  2015-08-07       Impact factor: 4.792

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