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The Pseudo-Torsional Space of RNA

Grille, L.; Gallego, D.; Darre, L.; da Rosa, G.; Battistini, F.; Orozco, M.; Dans, P. D.

2022-06-28 bioinformatics
10.1101/2022.06.24.497007 bioRxiv
Show abstract

The characterization of the conformational landscape of the RNA backbone is rather complex due to the ability of RNA to assume a big variety of conformations. These backbone conformations can be depicted by pseudo-torsional angles linking RNA backbone atoms, from which Ramachandran-like plots can be built. We explored here different definitions of these pseudo-torsional angles, finding that the most accurate ones are the traditional {eta} (eta) and {theta} (theta) angles, which represent the relative position of RNA backbone atoms P and C4. We explore the distribution of {eta}-{theta} in known experimental structures, comparing the pseudo-torsional space generated with structures determined exclusively by one experimental technique. We found that the complete picture only appears when combining data from different sources. The maps provide a quite comprehensive representation of the RNA accessible space, which can be used in RNA-structural prediction. Finally, our results highlight that protein interactions leads to significant changes in the population of the {eta}-{theta} space, pointing towards the role of induced-fit mechanisms in protein-RNA recognition.

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