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Bioinformatics Advance Access published online on November 13, 2005
Bioinformatics, doi:10.1093/bioinformatics/bti723
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© The Author (2005). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org
Received June 23, 2005
Revised October 7, 2005
Accepted October 16, 2005

Article

Inferring functional information from domain co-evolution

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

1 Dept. of Chem. and Biochem., University of California at San Diego, La Jolla, CA 92093, USA
2 Dept. of Computer Sciences, Purdue University, West Lafayette, IN, 47907, USA
3 Dept. of Chem. and Biochem., University of California at San Diego, La Jolla, CA 92093, USA; Dept. of Bioengineering, University of California at San Diego, La Jolla, CA 92093, USA

* To whom correspondence should be addressed.
Shankar Subramaniam, E-mail: shankar{at}sdsc.edu


  Abstract

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 (Pellegrini et al., 1999). 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 E. coli proteins when compared with earlier implementation 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.


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[Abstract] [Full Text] [PDF]


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