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Nucleic Acids Research Advance Access published online on May 5, 2007
Nucleic Acids Research, doi:10.1093/nar/gkm294
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© 2007 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.

Web Server Issue

RNABindR: a server for analyzing and predicting RNA-binding sites in proteins

Michael Terribilini1,2,*, Jeffry D. Sander1,2, Jae-Hyung Lee1,2, Peter Zaback1,2, Robert L. Jernigan2,3, Vasant Honavar2,4 and Drena Dobbs1,2

1Department of Genetics, Development & Cell Biology, 2Bioinformatics & Computational Biology Program, 3Department of Biochemistry, Biophysics and Molecular Biology and 4Department of Computer Science, Iowa State University, Ames, Iowa, 50011, USA

*To whom correspondence should be addressed. Tel: +1 515 294 4991; Fax: +1 515 294 6790; Email: terrible{at}iastate.edu

Received January 31, 2007. Revised April 3, 2007. Accepted April 12, 2007.

Understanding interactions between proteins and RNA is key to deciphering the mechanisms of many important biological processes. Here we describe RNABindR, a web-based server that identifies and displays RNA-binding residues in known protein–RNA complexes and predicts RNA-binding residues in proteins of unknown structure. RNABindR uses a distance cutoff to identify which amino acids contact RNA in solved complex structures (from the Protein Data Bank) and provides a labeled amino acid sequence and a Jmol graphical viewer in which RNA-binding residues are displayed in the context of the three-dimensional structure. Alternatively, RNABindR can use a Naive Bayes classifier trained on a non-redundant set of protein–RNA complexes from the PDB to predict which amino acids in a protein sequence of unknown structure are most likely to bind RNA. RNABindR automatically displays ‘high specificity’ and ‘high sensitivity’ predictions of RNA-binding residues. RNABindR is freely available at http://bindr.gdcb.iastate.edu/RNABindR.


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