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Bioinformatics Advance Access originally published online on April 28, 2005
Bioinformatics 2005 21(13):2969-2977; doi:10.1093/bioinformatics/bti471
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© The Author 2005. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions{at}oupjournals.org

FSSA: a novel method for identifying functional signatures from structural alignments

Kai Wang and Ram Samudrala *

Computational Genomics Group, Department of Microbiology, University of Washington Seattle, WA 98195, USA

*To whom correspondence should be addressed.

Motivation: It is commonly believed that sequence determines structure, which in turn determines function. However, the presence of many proteins with the same structural fold but different functions suggests that global structure and function do not always correlate well.

Results: We propose a method for accurate functional annotation, based on identification of functional signatures from structural alignments (FSSA) using the Structural Classification of Proteins (SCOP) database. The FSSA method is superior at function discrimination and classification compared with several methods that directly inherit functional annotation information from homology inference, such as Smith–Waterman, PSI-BLAST, hidden Markov models and structure comparison methods, for a large number of structural fold families. Our results indicate that the contributions of amino acid residue types and positions to structure and function are largely separable for proteins in multi-functional fold families.

Availability: The FSSA software is available at http://software.compbio.washington.edu/fssa

Contact: ram{at}compbio.washington.edu

Supplementary information: http://data.compbio.washington.edu/fssa/bioinformatics_supplement


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