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Correlated mutations: A hallmark of phenotypic amino acid substitutions.
PLoS Comput. Biol. 6:e1000923 (2010)
Point mutations resulting in the substitution of a single amino acid can cause severe functional consequences, but can also be completely harmless. Understanding what determines the phenotypical impact is important both for planning targeted mutation experiments in the laboratory and for analyzing naturally occurring mutations found in patients. Common wisdom suggests using the extent of evolutionary conservation of a residue or a sequence motif as an indicator of its functional importance and thus vulnerability in case of mutation. In this work, we put forward the hypothesis that in addition to conservation, co-evolution of residues in a protein influences the likelihood of a residue to be functionally important and thus associated with disease. While the basic idea of a relation between co-evolution and functional sites has been explored before, we have conducted the first systematic and comprehensive analysis of point mutations causing disease in humans with respect to correlated mutations. We included 14,211 distinct positions with known disease-causing point mutations in 1,153 human proteins in our analysis. Our data show that (1) correlated positions are significantly more likely to be disease-associated than expected by chance, and that (2) this signal cannot be explained by conservation patterns of individual sequence positions. Although correlated residues have primarily been used to predict contact sites, our data are in agreement with previous observations that (3) many such correlations do not relate to physical contacts between amino acid residues. Access to our analysis results are provided at http://webclu.bio.wzw.tum.de/~pagel/supplements/correlated-positions/.
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Publication type
Article: Journal article
Document type
Scientific Article
Keywords
disease-associated genes; HGMD; OMES algorithm; MULTIPLE SEQUENCE ALIGNMENTS; LONG-RANGE INTERACTIONS; HUMAN GENETIC-DISEASE; PROLIDASE DEFICIENCY; RESIDUE CONTACTS; EVOLUTIONARY INFORMATION; COEVOLVING RESIDUES; MUTUAL INFORMATION; PROTEIN RESIDUES; PEPTIDASE-D
ISSN (print) / ISBN
1553-734X
e-ISSN
1553-7358
Journal
PLoS Computational Biology
Quellenangaben
Volume: 6,
Issue: 9,
Article Number: e1000923
Publisher
Public Library of Science (PLoS)
Non-patent literature
Publications
Reviewing status
Peer reviewed