Improved RNA pseudoknots prediction and classification using a new topological invariant

Graziano Vernizzi (1) , Henri Orland (2, 3) , A. Zee (4, 5)

1 Siena College
2 IPHT - Institut de Physique Théorique - UMR CNRS 3681
3 Institute of Applied Physics and Computational Mathematics - IACM (Beijing, China))
4 UC Santa Barbara - University of California [Santa Barbara]
5 KITP - Kavli Institute for Theoretical Physics [Santa Barbara]

We propose a new topological characterization of RNA secondary structures with pseudoknots based on two topological invariants. Starting from the classic arc-representation of RNA secondary structures, we consider a model that couples both I) the topological genus of the graph and II) the number of crossing arcs of the corresponding primitive graph. We add a term proportional to these topological invariants to the standard free energy of the RNA molecule, thus obtaining a novel free energy parametrization which takes into account the abundance of topologies of RNA pseudoknots observed in RNA databases.

Keywords: Secondary structure; pseudoknot; RNA; structure classification; topology

Domains: Physics [physics]

Graziano Vernizzi, Henri Orland, A. Zee. Improved RNA pseudoknots prediction and classification using a new topological invariant. 2016. ⟨cea-01327864⟩