Using motion planning to study RNA folding kinetics

Xinyu Tang, Bonnie Kirkpatrick, Shawna Thomas, Guang Song, Nancy M. Amato

Research output: Contribution to journalArticlepeer-review


We propose a novel, motion planning based approach to approximately map the energy landscape of an RNA molecule. A key feature of our method is that it provides a sparse map that captures the main features of the energy landscape which can be analyzed to compute folding kinetics. Our method is based on probabilistic roadmap motion planners that we have previously successfully applied to protein folding. In this paper, we provide evidence that this approach is also well suited to RNA. We compute population kinetics and transition rates on our roadmaps using the master equation for a few moderately sized RNA and show that our results compare favorably with results of other existing methods.

Original languageEnglish (US)
Pages (from-to)862-881
Number of pages20
JournalJournal of Computational Biology
Issue number6
StatePublished - Jul 2005
Externally publishedYes


  • Folding kinetics
  • Motion planning
  • RNA

ASJC Scopus subject areas

  • Modeling and Simulation
  • Molecular Biology
  • Genetics
  • Computational Mathematics
  • Computational Theory and Mathematics


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