Assessment of tools for RNA secondary structure prediction and extraction: a final-user perspective

Abstract

The study of RNA structure is fundamental to clarify the RNA molecular functioning. The flexible RNA nature, the huge number of expressed RNAs, and the variety of functions make it challenging to obtain a quantity of structural information comparable to what is already available for proteins. The in silico prediction of RNA 3D structures is of particular relevance, to understand the fundamental features of the structure-function relationship, because the 3D structure drives the molecular interaction with DNA or protein complexes. The quality of the prediction of the RNA 3D structure is determined by the knowledge of a properly predicted or measured secondary structure. In this paper, we comparatively evaluate computational tools to model RNA secondary structure, focusing our investigation, among the dozens of methods in literature, on tools which are freely available and implemented in web-server versions, providing a more direct access to the final users, not necessarily bioinformatics experts. Our focus is on assessing performances for long sequences, with the final aim of selecting best methods for perspective lncRNAs investigation. Indeed, among RNAs, the non-coding and long non-coding RNAs (lncRNAs, with sequence length larger than 200 nts) assume special relevance, due to their function in regulatory mechanisms, which is still largely unexplored in the case of lncRNAs. As lncRNA experimental structures are at present missing, other families of large RNAs are here used as test cases, to establish the reliability of predictive bioinformatics tools and their perspective applicability to the case of lncRNAs. Communicated by Ramaswamy H. Sarma