Inferring functional information from domain co-evolution
Author(s) -
Yo-Han Kim,
Mehmet Koyutürk,
Umut Topkara,
Ananth Grama,
Shankar Subramaniam
Publication year - 2005
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/bti723
Subject(s) - domain (mathematical analysis) , computer science , phylogenetic tree , coevolution , function (biology) , protein domain , exploit , sequence (biology) , computational biology , protein function , theoretical computer science , biology , evolutionary biology , genetics , mathematics , gene , mathematical analysis , computer security
Co-evolution is a powerful mechanism for understanding protein function. Prior work in this area has shown that co-evolving proteins are more likely to share the same function than those that do not because of functional constraints. Many of the efforts founded on this observation, however, are at the level of entire sequences, implicitly assuming that the complete protein sequence follows a single evolutionary trajectory. Since it is well known that a domain can exist in various contexts, this assumption is not valid for numerous multi-domain proteins. Motivated by these observations, we introduce a novel technique called Coevolutionary-Matrix that captures co-evolution between regions of two proteins. Instead of using existing domain information, the method exploits residue-level conservation to identify co-evolving regions that might correspond to domains.
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