Literature DB >> 9094736

Mutation matrices and physical-chemical properties: correlations and implications.

J M Koshi1, R A Goldstein.   

Abstract

To investigate how the properties of individual amino acids result in proteins with particular structures and functions, we have examined the correlations between previously derived structure-dependent mutation rates and changes in various physical-chemical properties of the amino acids such as volume, charge, alpha-helical and beta-sheet propensity, and hydrophobicity. In most cases we found the delta G of transfer from octanol to water to be the best model for evolutionary constraints, in contrast to the much weaker correlation with the delta G of transfer from cyclohexane to water, a property found to be highly correlated to changes in stability in site-directed mutagenesis studies. This suggests that natural evolution may follow different rules than those suggested by results obtained in the laboratory. A high degree of conservation of a surface residue's relative hydrophobicity was also observed, a fact that cannot be explained by constraints on protein stability but that may reflect the consequences of the reverse-hydrophobic effect. Local propensity, especially alpha-helical propensity, is rather poorly conserved during evolution, indicating that non-local interactions dominate protein structure formation. We found that changes in volume were important in specific cases, most significantly in transitions among the hydrophobic residues in buried locations. To demonstrate how these techniques could be used to understand particular protein families, we derived and analyzed mutation matrices for the hypervariable and framework regions of antibody light chain V regions. We found surprisingly high conservation of hydrophobicity in the hypervariable region, possibly indicating an important role for hydrophobicity in antigen recognition.

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Year:  1997        PMID: 9094736     DOI: 10.1002/(sici)1097-0134(199703)27:3<336::aid-prot2>3.0.co;2-b

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


  13 in total

1.  Detecting site-specific biochemical constraints through substitution mapping.

Authors:  Julien Dutheil
Journal:  J Mol Evol       Date:  2008-08-12       Impact factor: 2.395

2.  How are model protein structures distributed in sequence space?

Authors:  E Bornberg-Bauer
Journal:  Biophys J       Date:  1997-11       Impact factor: 4.033

3.  Consensus sequence design as a general strategy to create hyperstable, biologically active proteins.

Authors:  Matt Sternke; Katherine W Tripp; Doug Barrick
Journal:  Proc Natl Acad Sci U S A       Date:  2019-05-20       Impact factor: 11.205

4.  Amino-acid interactions in psychrophiles, mesophiles, thermophiles, and hyperthermophiles: insights from the quasi-chemical approximation.

Authors:  Richard A Goldstein
Journal:  Protein Sci       Date:  2007-09       Impact factor: 6.725

5.  Mutagenesis Objective Search and Selection Tool (MOSST): an algorithm to predict structure-function related mutations in proteins.

Authors:  Alvaro Olivera-Nappa; Barbara A Andrews; Juan A Asenjo
Journal:  BMC Bioinformatics       Date:  2011-04-27       Impact factor: 3.169

6.  Prediction and analysis of surface hydrophobic residues in tertiary structure of proteins.

Authors:  Shambhu Malleshappa Gowder; Jhinuk Chatterjee; Tanusree Chaudhuri; Kusum Paul
Journal:  ScientificWorldJournal       Date:  2014-01-09

7.  Detecting regular sound changes in linguistics as events of concerted evolution.

Authors:  Daniel J Hruschka; Simon Branford; Eric D Smith; Jon Wilkins; Andrew Meade; Mark Pagel; Tanmoy Bhattacharya
Journal:  Curr Biol       Date:  2014-12-18       Impact factor: 10.834

8.  Revisiting the myths of protein interior: studying proteins with mass-fractal hydrophobicity-fractal and polarizability-fractal dimensions.

Authors:  Anirban Banerji; Indira Ghosh
Journal:  PLoS One       Date:  2009-10-16       Impact factor: 3.240

9.  Amino acid properties conserved in molecular evolution.

Authors:  Witold R Rudnicki; Teresa Mroczek; Paweł Cudek
Journal:  PLoS One       Date:  2014-06-26       Impact factor: 3.240

10.  SubVis: an interactive R package for exploring the effects of multiple substitution matrices on pairwise sequence alignment.

Authors:  Scott Barlowe; Heather B Coan; Robert T Youker
Journal:  PeerJ       Date:  2017-06-27       Impact factor: 2.984

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