Minimum-Free-Energy Distribution of RNA Secondary Structures: Entropic and Thermodynamic Properties of Rare Events

TL;DR

This study investigates the distribution of minimum free energy in RNA secondary structures, focusing on rare low-energy events, using advanced Monte Carlo methods to explore their properties and compare with natural RNA.

Contribution

It introduces a novel application of generalized ensemble Markov-chain Monte Carlo methods to analyze rare low free energy events in RNA structures, revealing their entropic and structural characteristics.

Findings

Rare low free energy RNA structures have distinct entropic properties.

Structural features of low-energy ensembles differ from typical RNA.

Natural RNAs show similar MFE distribution patterns.

Abstract

We study the distribution of the minimum free energy (MFE) for the Turner model of pseudoknot free RNA secondary structures over ensembles of random RNA sequences. In particular, we are interested in those rare and intermediate events of unexpected low MFEs. Generalized ensemble Markov-chain Monte Carlo methods allow us to explore the rare-event tail of the MFE distribution down to probabilities like $10^{-70}$ and to study the relationship between the sequence entropy and structural properties for sequence ensembles with fixed MFEs. Entropic and structural properties of those ensembles are compared with natural RNA of the same reduced MFE (z-score).