Introduction

The function of an RNA molecule is not only linked to its native structure, which is usually taken to be the ground state of its folding landscape, but also in many cases crucially depends on the details of the folding pathways such as stable folding intermediates or the timing of the folding process itself. To model and understand these processes, it is necessary to go beyond ground state structures. The study of rugged RNA folding landscapes holds the key to answer these questions. Efficient coarse-graining methods are required to reduce the intractably vast energy landscapes into condensed representations such as barrier trees or basin hopping graphs : BHG) that convey an approximate but comprehensive picture of the folding kinetics. So far, exact and heuristic coarse-graining methods have been mostly restricted to the pseudoknot-free secondary structures. Pseudoknots, which are common motifs and have been repeatedly hypothesized to play an important role in guiding folding trajectories, were usually excluded.We generalize the BHG framework to include pseudoknotted RNA structures and systematically study the differences in predicted folding behavior depending on whether pseudoknotted structures are allowed to occur as folding intermediates or not. We observe that RNAs with pseudoknotted ground state structures tend to have more pseudoknotted folding intermediates than RNAs with pseudoknot-free ground state structures. The occurrence and influence of pseudoknotted intermediates on the folding pathway, however, appear to depend very strongly on the individual RNAs so that no general rule can be inferred.The algorithms described here are implemented in C++ as standalone programs. Its source code and Supplemental material can be freely downloaded from http://www.tbi.univie.ac.at/bhg.html.qin@bioinf.uni-leipzig.deSupplementary data are available at Bioinformatics online.

Publications

  1. Pseudoknots in RNA folding landscapes.
    Cite this
    Kucharík M, Hofacker IL, Stadler PF, Qin J, 2016-01-01 - Bioinformatics (Oxford, England)
  2. Basin Hopping Graph: a computational framework to characterize RNA folding landscapes.
    Cite this
    Kucharík M, Hofacker IL, Stadler PF, Qin J, 2014-07-01 - Bioinformatics (Oxford, England)

Credits

  1. Marcel Kucharík
    Developer

  2. Ivo L Hofacker
    Developer

    Institute for Theoretical Chemistry, Research Group BCB, Denmark

  3. Peter F Stadler
    Developer

    Institute for Theoretical Chemistry, RTH, Denmark

  4. Jing Qin
    Investigator

    Institute for Theoretical Chemistry, RTH, Denmark

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Summary
AccessionBT000365
Tool TypeApplication
Category
PlatformsLinux/Unix
TechnologiesC++
User InterfaceTerminal Command Line
Download Count0
Country/RegionDenmark
Submitted ByJing Qin