Skip Navigation



Bioinformatics Advance Access published online on November 13, 2005
Bioinformatics, doi:10.1093/bioinformatics/bti723
This Article
Right arrow Advance Access manuscript (PDF) Freely available
Right arrowOA All Versions of this Article:
22/1/40    most recent
bti723v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Google Scholar
Right arrow Articles by Kim, Y.
Right arrow Articles by Subramaniam, S.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Kim, Y.
Right arrow Articles by Subramaniam, S.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© 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.


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?




Disclaimer:
Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.