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

Corinna Theis, Christian Höner zu Siederdissen, Ivo L. Hofacker, Jan Gorodkin

    9 Citationer (Scopus)

    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 FR3D 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. The metaRNAmodules pipeline source for the internal loop modules is available at
    http://rth.dk/resources/mrm.
    OriginalsprogEngelsk
    TidsskriftNucleic Acids Research
    Vol/bind41
    Udgave nummer22
    Sider (fra-til)9999-10009
    Antal sider11
    ISSN0305-1048
    DOI
    StatusUdgivet - dec. 2013

    Emneord

    • Det Sundhedsvidenskabelige Fakultet

    Fingeraftryk

    Dyk ned i forskningsemnerne om 'Automated identification of RNA 3D modules with discriminative power in RNA structural alignments'. Sammen danner de et unikt fingeraftryk.

    Citationsformater