TBI-p-2013-9

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Titel:
Automated identification of 3D modules with discriminative power in RNA structural alignments

Author(s):
Corinna Theis, Christian Höner zu Siederdissen, Ivo L. Hofacker, and Jan Gorodkin

submitted to:
Nucleic Acids Research. 41, no. 22. 41. : 9999–10009

Abstract:
Recent progress in predicting RNA structure is moving towards filling the 'gap' in 2D RNA structure prediction where, for example, predicted internal loops often form non-canonical base pairs. This is increasingly recognized with the steady increase of known RNA 3D modules. There is a general interest in matching structural modules known from one molecule to other molecules for which the 3D structure is not known yet. We have created a pipeline, metaRNAmodules, which completely automates extracting putative modules from the Fred database and mapping of such modules to Rfam alignments to obtain comparative evidence. Subsequently, the modules, initially represented by a graph, are turned into models for the RMDetect program, which allows to test their discriminative power using real and randomized Rfam alignments. An initial extraction of 22495 3D modules in all PDB files results in 977 internal loop and 17 hairpin modules with clear discriminatory power. Many of these modules describe only minor variants of each other. Indeed, mapping of the modules onto \rfam{} families results in 35 unique locations in 11 different families.


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