The RNA 3D Motif Atlas: Computational methods for extraction, organization and evaluation of RNA motifs

Abstract

RNA 3D motifs occupy places in structured RNA molecules that correspond to the hairpin, internal and multi-helix junction “loops” of their secondary structure representations. As many as 40% of the nucleotides of an RNA molecule can belong to these structural elements, which are distinct from the regular double helical regions formed by contiguous AU, GC, and GU Watson-Crick basepairs. With the large number of atomic- or near atomic-resolution 3D structures appearing in a steady stream in the PDB/NDB structure databases, the automated identification, extraction, comparison, clustering and visualization of these structural elements presents an opportunity to enhance RNA science. Three broad applications are: (1) identification of modular, autonomous structural units for RNA nanotechnology, nanobiology and synthetic biology applications; (2) bioinformatic analysis to improve RNA 3D structure prediction from sequence; and (3) creation of searchable databases for exploring the binding specificities, structural flexibility, and dynamics of these RNA elements. In this contribution, we review methods developed for computational extraction of hairpin and internal loop motifs from a non-redundant set of high-quality RNA 3D structures. We provide a statistical summary of the extracted hairpin and internal loop motifs in the most recent version of the RNA 3D Motif Atlas. We also explore the reliability and accuracy of the extraction process by examining its performance in clustering recurrent motifs from homologous ribosomal RNA (rRNA) structures. We conclude with a summary of remaining challenges, especially with regard to extraction of multi-helix junction motifs.