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.