How to efficiently explore the lower portion of RNA energy landscapes

In this study we propose a memory-efficient approach for local flooding of the lower portion of an RNA folding landscape

Discrete energy landscapes provide a valuable means for analyzing non-equilibrium properties of biopolymers. RNA folding dynamics, for example, can be described by a continuous-time Markov process at the level of local minima, their corresponding basins of attraction and saddle points connecting them.

A connected set of structures, often denoted state space is required for energy landscape construction. While complete suboptimal folding of RNA is practically impossible for chain lengths above 100nt, alternative strategies to enumerate the lower part of the energy landscape emerged over the last years.

We have recently extended previous work on global flooding by a local flooding approach that minimizes memory consumption and published the method in Bioinformatics.

Posted by Michael T. Wolfinger on . updated