Literature DB >> 15944362

The exchangeability of amino acids in proteins.

Lev Y Yampolsky1, Arlin Stoltzfus.   

Abstract

The comparative analysis of protein sequences depends crucially on measures of amino acid similarity or distance. Many such measures exist, yet it is not known how well these measures reflect the operational exchangeability of amino acids in proteins, since most are derived by methods that confound a variety of effects, including effects of mutation. In pursuit of a pure measure of exchangeability, we present (1) a compilation of data on the effects of 9671 amino acid exchanges engineered and assayed in a set of 12 proteins; (2) a statistical procedure to combine results from diverse assays of exchange effects; (3) a matrix of "experimental exchangeability" values EX(ij) derived from applying this procedure to the compiled data; and (4) a set of three tests designed to evaluate the power of an exchangeability measure to (i) predict the effects of amino acid exchanges in the laboratory, (ii) account for the disease-causing potential of missense mutations in the human population, and (iii) model the probability of fixation of missense mutations in evolution. EX not only captures useful information on exchangeability while remaining free of other effects, but also outperforms all measures tested except for the best-performing alignment scoring matrix, which is comparable in performance.

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Year:  2005        PMID: 15944362      PMCID: PMC1449787          DOI: 10.1534/genetics.104.039107

Source DB:  PubMed          Journal:  Genetics        ISSN: 0016-6731            Impact factor:   4.562


  57 in total

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4.  Nucleotide bias causes a genomewide bias in the amino acid composition of proteins.

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5.  Identification of residues critical for metallo-beta-lactamase function by codon randomization and selection.

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Journal:  Protein Sci       Date:  2001-12       Impact factor: 6.725

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8.  Estimate of the mutation rate per nucleotide in humans.

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9.  Predicting surface exposure of amino acids from protein sequence.

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Journal:  Protein Eng       Date:  1990-08

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Journal:  Gene       Date:  2000-12-30       Impact factor: 3.688

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  58 in total

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Journal:  J Biosci       Date:  2012-07       Impact factor: 1.826

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3.  Error-reducing structure of the genetic code indicates code origin in non-thermophile organisms.

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Authors:  Arlin Stoltzfus; Lev Y Yampolsky
Journal:  J Mol Evol       Date:  2007-09-26       Impact factor: 2.395

5.  Genetic Basis of Common Human Disease: Insight into the Role of Missense SNPs from Genome-Wide Association Studies.

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Journal:  J Mol Biol       Date:  2015-05-01       Impact factor: 5.469

6.  Searching of code space for an error-minimized genetic code via codon capture leads to failure, or requires at least 20 improving codon reassignments via the ambiguous intermediate mechanism.

Authors:  Steven E Massey
Journal:  J Mol Evol       Date:  2010-01-28       Impact factor: 2.395

7.  Classic Ehlers-Danlos Syndrome in a Son and Father with a Heart Transplant Performed in the Father.

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Journal:  J Pediatr Genet       Date:  2018-10-13

Review 8.  Causes of molecular convergence and parallelism in protein evolution.

Authors:  Jay F Storz
Journal:  Nat Rev Genet       Date:  2016-03-14       Impact factor: 53.242

9.  The action of key factors in protein evolution at high temporal resolution.

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Journal:  PLoS One       Date:  2009-03-12       Impact factor: 3.240

10.  A model for protein sequence evolution based on selective pressure for protein stability: application to hemoglobins.

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Journal:  Evol Bioinform Online       Date:  2009-08-27       Impact factor: 1.625

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