Evolutionary Dynamics and Optimization: Neutral Networks as Model-Landscapes for RNA Secondary-Structure Folding-Landscapes

TL;DR

This paper models RNA secondary-structure folding landscapes as neutral networks, extending Eigen's error threshold concept, and explores how interactions between different networks influence the search for optimal structures.

Contribution

It introduces a novel framework linking RNA folding landscapes to neutral networks and extends the error threshold concept to these structures, supported by analytical and simulation results.

Findings

Intersection of compatible sequence sets influences structure optimization

Analytical results derived for single shape landscapes

Simulations show interaction effects between different networks

Abstract

We view the folding of RNA-sequences as a map that assigns a pattern of base pairings to each sequence, known as secondary structure. These preimages can be constructed as random graphs (i.e. the neutral networks associated to the structure $s$). By interpreting the secondary structure as biological information we can formulate the so called Error Threshold of Shapes as an extension of Eigen's et al. concept of an error threshold in the single peak landscape. Analogue to the approach of Derrida & Peliti for a of the population on the neutral network. On the one hand this model of a single shape landscape allows the derivation of analytical results, on the other hand the concept gives rise to study various scenarios by means of simulations, e.g. the interaction of two different networks. It turns out that the intersection of two sets of compatible sequences (with respect to the pair of secondary structures) plays a key role in the search for ''fitter'' secondary structures.