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Bioinformatics Advance Access published online on May 1, 2008
Bioinformatics, doi:10.1093/bioinformatics/btn214
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© 2008 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Characterization and Prediction of Residues Determining Protein Functional Specificity

John A. Capra and Mona Singh *

Department of Computer Science, Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08540, USA

*To whom correspondence should be addressed. Prof. Mona Singh, E-mail: msingh{at}cs.princeton.edu


  Abstract

Motivation: Within a homologous protein family, proteins may be grouped into subtypes that share specific functions that are not common to the entire family. Often, the amino acids present in a small number of sequence positions determine each protein's particular functional specificity. Knowledge of these specificity determining positions (SDPs) aids in protein function prediction, drug design, and experimental analysis. A number of sequence-based computational methods have been introduced for identifying SDPs; however, their further development and evaluation have been hindered by the limited number of known experimentally-determined SDPs.

Results: We combine several bioinformatics resources to automate a process, typically undertaken manually, to build a data set of SDPs. The resulting large data set, which consists of SDPs in enzymes, enables us to characterize SDPs in terms of their physicochemical and evolutionary properties. It also facilitates the large-scale evaluation of sequence-based SDP prediction methods. We present a simple sequence-based SDP prediction method, GroupSim, and show that, surprisingly, it is competitive with a representative set of current methods. We also describe ConsWin, a heuristic that considers sequence conservation of neighboring amino acids, and demonstrate that it improves the performance of all methods tested on our large data set of enzyme SDPs.

Availability: Data sets and GroupSim code are available online at http://compbio.cs.princeton.edu/specificity/.

Contact: msingh{at}cs.princeton.edu

Associate Editor: Prof. Burkhard Rost

Received on March 21, 2008; revised on April 22, 2008; accepted on April 28, 2008

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