Direct-Coupling Analysis of nucleotide coevolution facilitates RNA secondary and tertiary structure prediction

TL;DR

This paper demonstrates that direct-coupling analysis of nucleotide coevolution enhances RNA secondary and tertiary structure prediction, outperforming traditional methods and providing valuable contact information for molecular modeling.

Contribution

The study introduces a novel application of direct-coupling analysis to RNA, improving structural predictions by integrating coevolutionary contact data into existing modeling frameworks.

Findings

Improved RNA secondary structure prediction accuracy.

Enrichment of tertiary contact information from coevolution analysis.

Enhanced molecular modeling results using combined contact predictions.

Abstract

Despite the biological importance of non-coding RNA, their structural characterization remains challenging. Making use of the rapidly growing sequence databases, we analyze nucleotide coevolution across homologous sequences via Direct-Coupling Analysis to detect nucleotide-nucleotide contacts. For a representative set of riboswitches, we show that the results of Direct-Coupling Analysis in combination with a generalized Nussinov algorithm systematically improve the results of RNA secondary structure prediction beyond traditional covariance approaches based on mutual information. Even more importantly, we show that the results of Direct-Coupling Analysis are enriched in tertiary structure contacts. By integrating these predictions into molecular modeling tools, systematically improved tertiary structure predictions can be obtained, as compared to using secondary structure information alone.