title: Protein function annotation from sequence: prediction of residues interacting with RNA.
abstract: BACKGROUND
  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.
  
  
  METHODS
  Freely available on the web at www.bioinformatics.sussex.ac.uk/PIRANHA or http://piranha.protein.osaka-u.ac.jp.
  
  
  BACKGROUND
  Supplementary data are available at the Bioinformatics online.
authors.affiliation: Department of Chemistry and Biochemistry, School of Life Sciences, John Maynard-Smith Building, University of Sussex, Falmer, Brighton, UK.
authors.forename: R V
authors.initials: RV
authors.lastname: Spriggs
authors.forename: Y
authors.initials: Y
authors.lastname: Murakami
authors.forename: H
authors.initials: H
authors.lastname: Nakamura
authors.forename: S
authors.initials: S
authors.lastname: Jones
mesh_terms: D000465:Algorithms; D001665:Binding Sites; D019295:Computational Biology / Q000379:methods; D030562:Databases, Protein; D012313:RNA / Q000737:chemistry* / Q000378:metabolism; D016601:RNA-Binding Proteins / Q000737:chemistry* / Q000378:metabolism
chemical_list: D016601:RNA-Binding Proteins; D012313:RNA