3D RNA and functional interactions from evolutionary couplings

TL;DR

This paper introduces a method using evolutionary couplings to predict RNA and RNA-protein 3D structures and functional interactions, significantly advancing understanding of non-coding RNAs.

Contribution

It applies maximum entropy models to infer nucleotide interactions, enabling accurate 3D structure prediction and functional insights for RNAs and complexes.

Findings

Accurate 3D structure prediction for known RNAs and complexes.

Predicted contacts for 160 non-coding RNA families.

Identification of functional interaction sites such as riboswitch switches.

Abstract

Non-coding RNAs are ubiquitous, but the discovery of new RNA gene sequences far outpaces research on their structure and functional interactions. We mine the evolutionary sequence record to derive precise information about function and structure of RNAs and RNA-protein complexes. As in protein structure prediction, we use maximum entropy global probability models of sequence co-variation to infer evolutionarily constrained nucleotide-nucleotide interactions within RNA molecules, and nucleotide-amino acid interactions in RNA-protein complexes. The predicted contacts allow all-atom blinded 3D structure prediction at good accuracy for several known RNA structures and RNA-protein complexes. For unknown structures, we predict contacts in 160 non-coding RNA families. Beyond 3D structure prediction, evolutionary couplings help identify important functional interactions, e.g., at switch points in riboswitches and at a complex nucleation site in HIV. Aided by accelerating sequence accumulation, evolutionary coupling analysis can accelerate the discovery of functional interactions and 3D structures involving RNA.