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Título

Randomized tree construction algorithm to explore energy landscapes

Autor Jaillet, Léonard ; Corcho, Francesc J.; Pérez, Juan Jesús; Cortés, Juan
Palabras clave Robot path planning algorithms
Monte Carlo methods
Conformational transition paths
Peptides
Energy landscape exploration
Fecha de publicación 2011
EditorJohn Wiley & Sons
Citación Journal of Computational Chemistry 32(16): 3464-3474 (2011)
ResumenIn 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. Copyright © 2011 Wiley Periodicals, Inc.
Versión del editorhttp://dx.doi.org/10.1002/jcc.21931
URI http://hdl.handle.net/10261/96864
DOI10.1002/jcc.21931
Identificadoresdoi: 10.1002/jcc.21931
issn: 0192-8651
e-issn: 1096-987X
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