Bioinformatics Advance Access originally published online on November 17, 2007
Bioinformatics 2008 24(1):18-25; doi:10.1093/bioinformatics/btm537
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Multi-RELIEF: a method to recognize specificity determining residues from multiple sequence alignments using a Machine-Learning approach for feature weighting
1Division of Medical Chemistry, LACDR, Leiden University, P.O. Box 9502, 2300 RA, Leiden and 2Department of Computer Science, IBIVU, Vrije Universiteit, De Boelelaan 1081A, 1081 HV, Amsterdam, The Netherlands
*To whom correspondence should be addressed.
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Abstract |
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Motivation: Identification of residues that account for protein function specificity is crucial, not only for understanding the nature of functional specificity, but also for protein engineering experiments aimed at switching the specificity of an enzyme, regulator or transporter. Available algorithms generally use multiple sequence alignments to identify residue positions conserved within subfamilies but divergent in between. However, many biological examples show a much subtler picture than simple intra-group conservation versus inter-group divergence.
Results: We present multi-RELIEF, a novel approach for identifying specificity residues that is based on RELIEF, a state-of-the-art Machine-Learning technique for feature weighting. It estimates the expected ‘local’ functional specificity of residues from an alignment divided in multiple classes. Optionally, 3D structure information is exploited by increasing the weight of residues that have high-weight neighbors. Using ROC curves over a large body of experimental reference data, we show that (a) multi-RELIEF identifies specificity residues for the seven test sets used, (b) incorporating structural information improves prediction for specificity of interaction with small molecules and (c) comparison of multi-RELIEF with four other state-of-the-art algorithms indicates its robustness and best overall performance.
Availability: A web-server implementation of multi-RELIEF is available at www.ibi.vu.nl/programs/multirelief. Matlab source code of the algorithm and data sets are available on request for academic use.
Contact: elena{at}few.vu.nl
Supplementary information: Supplemenmtary data are available at Bioinformatics online
Associate Editor: Burkhard Rost
Received on July 28, 2007; revised on October 18, 2007; accepted on October 18, 2007
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  J. E. Donald and E. I. Shakhnovich SDR: a database of predicted specificity-determining residues in proteins Nucleic Acids Res., January 1, 2009; 37(suppl_1): D191 - D194. [Abstract] [Full Text] [PDF]
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