title: Randomized tree construction algorithm to explore energy landscapes.
abstract: In this work, a new method for exploring conformational energy landscapes is described. The method, called transition-rapidly exploring random tree (T-RRT), combines ideas from statistical physics and robot path planning algorithms. A search tree is constructed on the conformational space starting from a given state. The tree expansion is driven by a double strategy: on the one hand, it is naturally biased toward yet unexplored regions of the space; on the other, a Monte Carlo-like transition test guides the expansion toward energetically favorable regions. The balance between these two strategies is automatically achieved due to a self-tuning mechanism. The method is able to efficiently find both energy minima and transition paths between them. As a proof of concept, the method is applied to two academic benchmarks and the alanine dipeptide.
authors.affiliation: Institut de Robòtica i Informàtica Industrial, CSIC-UPC, C/ Llorens i Artigas 4-6, Barcelona 08028, Spain.
authors.forename: Léonard
authors.initials: L
authors.lastname: Jaillet
authors.forename: Francesc J
authors.initials: FJ
authors.lastname: Corcho
authors.forename: Juan-Jesús
authors.initials: JJ
authors.lastname: Pérez
authors.forename: Juan
authors.initials: J
authors.lastname: Cortés
mesh_terms: D000409:Alanine / Q000737:chemistry; D000465:Algorithms; D019295:Computational Biology; D004151:Dipeptides / Q000737:chemistry; D056004:Molecular Dynamics Simulation; D009010:Monte Carlo Method; D011487:Protein Conformation
chemical_list: D004151:Dipeptides; D000409:Alanine