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Briefings in Bioinformatics Advance Access originally published online on March 26, 2009
Briefings in Bioinformatics 2009 10(4):378-391; doi:10.1093/bib/bbp017
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© The Author 2009. Published by Oxford University Press. For Permissions, please email: journals.permissions@oxfordjournals.org

This article appears in the following Briefings in Bioinformatics issue: Special Issue: Challenges in Bioinformatics and Computational Biology [View the issue table of contents]

FINDSITE: a combined evolution/structure-based approach to protein function prediction

Jeffrey Skolnick and Michal Brylinski

Corresponding author. Jeffrey Skolnick, Center for the Study of Systems Biology, School of Biology, Georgia Institute of Technology 250 14th St NW, Atlanta, GA 30318, USA. Tel: +1-404-407-8975; Fax: +1-404-385-7484; E-mail: skolnick{at}gatech.edu

A key challenge of the post-genomic era is the identification of the function(s) of all the molecules in a given organism. Here, we review the status of sequence and structure-based approaches to protein function inference and ligand screening that can provide functional insights for a significant fraction of the ~50% of ORFs of unassigned function in an average proteome. We then describe FINDSITE, a recently developed algorithm for ligand binding site prediction, ligand screening and molecular function prediction, which is based on binding site conservation across evolutionary distant proteins identified by threading. Importantly, FINDSITE gives comparable results when high-resolution experimental structures as well as predicted protein models are used.

Keywords: protein function prediction, ligand binding site prediction, virtual ligand screening, protein structure prediction, low-resolution protein structures

Submitted: January 26, 2009. Received (in revised form): February 25, 2009.


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