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

Eleonora De leonardis (1, 2) , Benjamin Lutz (3, 4) , Sebastian Ratz (3, 4) , Simona Cocco (5) , Rémi Monasson (2) , Alexander Schug (4) , Martin Weigt (1)

1 LCQB - Biologie Computationnelle et Quantitative = Laboratory of Computational and Quantitative Biology
2 LPTENS - Laboratoire de Physique Théorique de l'ENS [École Normale Supérieure]
3 Fakultät für Physik [Karlsruhe]
4 SCC - Steinbuch Centre for Computing [Karlsruhe]
5 LPS - Laboratoire de Physique Statistique de l'ENS

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 model-ing tools, systematically improved tertiary structure predictions can be obtained, as compared to using secondary structure information alone.

Domaines: Bio-informatique [q-bio.QM]

Eleonora De leonardis, Benjamin Lutz, Sebastian Ratz, Simona Cocco, Rémi Monasson, et al.. Direct-Coupling Analysis of nucleotide coevolution facilitates RNA secondary and tertiary structure prediction. Nucleic Acids Research, 2015, 43 (21), pp.10444-10455. ⟨10.1093/nar/gkv932⟩. ⟨hal-01271548⟩