Protein Science
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
QUICK SEARCH:   [advanced]


     

Protein Science (2007), 16:4-13. Published by Cold Spring Harbor Laboratory Press. Copyright © 2007 The Protein Society
This Article
Right arrow Full Text
Right arrow Full Text (PDF)
Right arrow Supplemental Research Data
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
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 Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Chakrabarti, S.
Right arrow Articles by Lanczycki, C. J.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Chakrabarti, S.
Right arrow Articles by Lanczycki, C. J.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati  
What's this?

Analysis and prediction of functionally important sites in proteins

Saikat Chakrabarti and Christopher J. Lanczycki

National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland 20894, USA

(RECEIVED August 18, 2006; FINAL REVISION October 12, 2006; ACCEPTED October 13, 2006)

The rapidly increasing volume of sequence and structure information available for proteins poses the daunting task of determining their functional importance. Computational methods can prove to be very useful in understanding and characterizing the biochemical and evolutionary information contained in this wealth of data, particularly at functionally important sites. Therefore, we perform a detailed survey of compositional and evolutionary constraints at the molecular and biological function level for a large set of known functionally important sites extracted from a wide range of protein families. We compare the degree of conservation across different functional categories and provide detailed statistical insight to decipher the varying evolutionary constraints at functionally important sites. The compositional and evolutionary information at functionally important sites has been compiled into a library of functional templates. We developed a module that predicts functionally important columns (FIC) of an alignment based on the detection of a significant "template match score" to a library template. Our template match score measures an alignment column's similarity to a library template and combines a term explicitly representing a column's residue composition with various evolutionary conservation scores (information content and position-specific scoring matrix-derived statistics). Our benchmarking studies show good sensitivity/specificity for the prediction of functional sites and high accuracy in attributing correct molecular function type to the predicted sites. This prediction method is based on information derived from homologous sequences and no structural information is required. Therefore, this method could be extremely useful for large-scale functional annotation.

Keywords: functionally important sites; function prediction; active sites; metal binding sites; protein binding sites; ligand binding sites; evolutionary conservation; compositional pattern


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




HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Copyright © 2007 by The Protein Society.