CoFold: thermodynamic RNA structure prediction with a kinetic twist

TL;DR

CoFold is a novel RNA secondary-structure prediction method that integrates thermodynamic stability with kinetic folding processes, leading to improved accuracy especially for long RNA sequences.

Contribution

It introduces a new approach combining thermodynamic and kinetic factors for RNA structure prediction, advancing beyond existing thermodynamic-only methods.

Findings

Significantly improves prediction accuracy for long RNAs

Outperforms existing thermodynamic methods

Effective for sequences over a thousand nucleotides

Abstract

Existing state-of-the-art methods that take a single RNA sequence and predict the corresponding RNA secondary-structure are thermodynamic methods. These predict the most stable RNA structure, but do not consider the process of structure formation. We have by now ample experimental and theoretical evidence, however, that sequences in vivo fold while being transcribed and that the process of structure formation matters. We here present a conceptually new method for predicting RNA secondary-structure, called CoFold, that combines thermodynamic with kinetic considerations. Our method significantly improves the state-of-art in terms of prediction accuracy, especially for long sequences of more than a thousand nucleotides length such as ribosomal RNAs.