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Bioinformatics 2008 24(16):i112-i118; doi:10.1093/bioinformatics/btn288
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© The Author 2008. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

RNA structure alignment by a unit-vector approach

Emidio Capriotti and Marc A. Marti-Renom *

Bioinformatics and Genomics Department, Structural Genomics Unit, Centro de Investigación Príncipe Felipe (CIPF), Valencia, Spain

*To whom correspondence should be addressed.


  Abstract

Motivation: The recent discovery of tiny RNA molecules such as µRNAs and small interfering RNA are transforming the view of RNA as a simple information transfer molecule. Similar to proteins, the native three-dimensional structure of RNA determines its biological activity. Therefore, classifying the current structural space is paramount for functionally annotating RNA molecules. The increasing numbers of RNA structures deposited in the PDB requires more accurate, automatic and benchmarked methods for RNA structure comparison. In this article, we introduce a new algorithm for RNA structure alignment based on a unit-vector approach. The algorithm has been implemented in the SARA program, which results in RNA structure pairwise alignments and their statistical significance.

Results: The SARA program has been implemented to be of general applicability even when no secondary structure can be calculated from the RNA structures. A benchmark against the ARTS program using a set of 1275 non-redundant pairwise structure alignments results in ¡«6% extra alignments with at least 50% structurally superposed nucleotides and base pairs. A first attempt to perform RNA automatic functional annotation based on structure alignments indicates that SARA can correctly assign the deepest SCOR classification to >60% of the query structures.

Availability: The SARA program is freely available through a World Wide Web server http://sgu.bioinfo.cipf.es/services/SARA/

Contact: mmarti{at}cipf.es


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