Bioinformatics Advance Access originally published online on April 23, 2009
Bioinformatics 2009 25(12):1492-1497; doi:10.1093/bioinformatics/btp257
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Protein function annotation from sequence: prediction of residues interacting with RNA
1Department of Chemistry and Biochemistry, School of Life Sciences, John Maynard-Smith Building, University of Sussex, Falmer, Brighton, BN1 9QG, UK and 2Research Centre for Structural and Functional Proteomics, Institute for Protein Research, Osaka University, Japan
*To whom correspondence should be addressed.
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Abstract |
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Motivation: All eukaryotic proteomes are characterized by a significant percentage of proteins of unknown function. Comp-utational function prediction methods are therefore essential as initial steps in the function annotation process. This article describes an annotation method (PiRaNhA) for the prediction of RNA-binding residues (RBRs) from protein sequence information. A series of sequence properties (position specific scoring matrices, interface propensities, predicted accessibility and hydrophobicity) are used to train a support vector machine. This method is then evaluated for its potential to be applied to RNA-binding function prediction at the level of the complete protein.
Results: The 5-fold cross-validation of PiRaNhA on a dataset of 81 RNA-binding proteins achieves a Matthews Correlation Coefficient (MCC) of 0.50 and accuracy of 87.2%. When used to predict RBRs in 42 proteins not used in training, PiRaNhA achieves an MCC of 0.41 and accuracy of 84.5%. Decision values from the PiRaNhA predictions were used in a second SVM to make predictions of RNA-binding function at the protein level, achieving an MCC of 0.53 and accuracy of 76.1%. The PiRaNhA RBR predictions allow experimentalists to perform more targeted experiments for function annotation; and the prediction of RNA-binding function at the protein level shows promise for proteome-wide annotations.
Availability and Implementation: Freely available on the web at www.bioinformatics.sussex.ac.uk/PIRANHA or http://piranha.protein.osaka-u.ac.jp.
Contact:s.jones{at}sussex.ac.uk.
Supplementary Information: Supplementary data are available at the Bioinformatics online.
The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First authors.
Associate Editor: Burkhard Rost
Received on January 28, 2009; revised on March 24, 2009; accepted on April 8, 2009
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