Cureus | CyloFold: secondary structure prediction including pseudoknots
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Research Article

CyloFold: secondary structure prediction including pseudoknots

Eckart Bindewald, Tanner Kluth, Bruce A. Shapiro

Published: July 01, 2010

DOI: 10.1093/nar/gkq432

License: Published by Oxford University Press (2010).2010This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Computational RNA secondary structure prediction approaches differ by the way RNA pseudoknot interactions are handled. For reasons of computational efficiency, most approaches only allow a limited class of pseudoknot interactions or are not considering them at all. Here we present a computational method for RNA secondary structure prediction that is not restricted in terms of pseudoknot complexity. The approach is based on simulating a folding process in a coarse-grained manner by choosing helices based on established energy rules. The steric feasibility of the chosen set of helices is checked during the folding process using a highly coarse-grained 3D model of the RNA structures. Using two data sets of 26 and 241 RNA sequences we find that this approach is competitive compared to the existing RNA secondary structure prediction programs pknotsRG, HotKnots and UnaFold. The key advantages of the new method are that there is no algorithmic restriction in terms of pseudoknot complexity and a test is made for steric feasibility. Availability: The program is available as web server at the site: http://cylofold.abcc.ncifcrf.gov.


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Scholarly Impact Quotient™ (SIQ™) is our unique post-publication peer review rating process. SIQ™ assesses article importance and quality by embracing the collective intelligence of the Cureus community-at-large. All registered users are invited to contribute to the SIQ™ of any published article. (Authors cannot rate their own articles.)

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