title: An algorithmic game-theory approach for coarse-grain prediction of RNA 3D structure.
abstract: We present a new approach for the prediction of the coarse-grain 3D structure of RNA molecules. We model a molecule as being made of helices and junctions. Those junctions are classified into topological families that determine their preferred 3D shapes. All the parts of the molecule are then allowed to establish long-distance contacts that induce a 3D folding of the molecule. An algorithm relying on game theory is proposed to discover such long-distance contacts that allow the molecule to reach a Nash equilibrium. As reported by our experiments, this approach allows one to predict the global shape of large molecules of several hundreds of nucleotides that are out of reach of the state-of-the-art methods.
authors.affiliation: PRiSM, Université de Versailles-St-Quentin-en-Yvelines/CNRS, France.
authors.forename: Alexis
authors.initials: A
authors.lastname: Lamiable
authors.forename: Franck
authors.initials: F
authors.lastname: Quessette
authors.forename: Sandrine
authors.initials: S
authors.lastname: Vial
authors.forename: Dominique
authors.initials: D
authors.lastname: Barth
authors.forename: Alain
authors.initials: A
authors.lastname: Denise
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D003460:Crystallization; D005716:Game Theory; D008956:Models, Chemical; D008958:Models, Molecular; D009690:Nucleic Acid Conformation; D012313:RNA / Q000737:chemistry* / Q000235:genetics / Q000378:metabolism; D012984:Software
chemical_list: D012313:RNA