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Bioinformatics Advance Access originally published online on November 13, 2005
Bioinformatics 2006 22(1):40-49; doi:10.1093/bioinformatics/bti723
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Inferring functional information from domain co-evolution

Yohan Kim 1, Mehmet Koyutürk 2, Umut Topkara 2, Ananth Grama 2 and Shankar Subramaniam 1,3,*

1Department of Chemistry and Biochemistry, University of California at San Diego La Jolla, CA 92093, USA
2Department of Computer Sciences, Purdue University West Lafayette, IN 47907, USA
3Department of Bioengineering, University of California at San Diego La Jolla, CA 92093, USA

*To whom correspondence should be addressed.

Motivation: 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.

Results: We show that the Coevolutionary-Matrix method can detect greater number of known functional associations for the Escherichia coli proteins when compared with earlier implementations of phylogenetic profiles. Furthermore, co-evolving regions of proteins detected by our method enable us to make hypotheses about their specific functions, many of which are supported by existing biochemical studies.

Contact: shankar{at}sdsc.edu

Received on June 23, 2005; revised on October 7, 2005; accepted on October 16, 2005

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