Abstract

RNA tertiary structures are highly modular. Canonical Watson-Crick base pairs form what is called the secondary structure, composed of helices interspersed with other secondary structure elements such as multiloops, interior loops, bulges, terminal loops. Additional long range interactions and non canonical interactions make the molecule adopt its three-dimensional tertiary structure.
RNA modules are small substructures which appear in multiple locations in a variety of different RNA molecules, and which fold identically or almost identically. They are formed of assemblies of non-Watson-Crick base pairs, they mediate the folding of the molecule and they can also constitute specific protein or ligand binding sites. Well known RNA modules are, for example, GNRA loops, Kink-turns, G-bulges, and the A-minor interactions.

RNA modules can be classified in two different classes:
+ Local modules are located within secondary structure elements: they are mainly formed of non-Watson-Crick base pairings inside the loops (internal, multiple or terminal loops, or bulges) of the secondary structure. Most known modules are mainly local, as the G-bulges and the Kink-turn loops.
+ Interaction modules connect two generally distant secondary structure elements (helices or loops). A well known element of this class is the “A- minor” Type I/II.

We distinguish recurrent interaction networks (RINs) from interaction modules. As will be precised below, a recurrent interaction network does not contain any sequence information, but only topological information about the interactions between nucleotides and the nature of these interactions. When considering sequence information, a same recurrent interaction network can give raise to one or several interaction modules.

We developed a graph-based methodology to extract all recurrent interaction networks in RNA tertiary structures and to cluster them according to their similarity. We applied our methodology to a large set of experimentally resolved RNA structures. Not only we retrieved the known recurrent interaction network (as the different types of A-minors), but we also get new ones. Additionally, our method gives a global view on interaction networks and their modularity, by organizing them in families according to their inclusion relations. We also discover modules, in other words new sequences adopting those particular interaction network configurations.

Notes

This website is designed to be a comprehensive ensemble of recurrent interaction networks and to allow researchers to easily find interesting candidates for future work.
We would like to thank Anton Petrov for letting us use his 3D vizualisation plugin.



How to cite

Vladimir Reinharz, Antoine Soulé, Eric Westhof, Jérôme Waldispühl, and Alain Denise. "Mining for recurrent long-range interactions in RNA structures reveals embedded hierarchies in network families." Nucleic acids research (2018).
DOI: 10.1093/nar/gky197