Publication
Randomized tree construction algorithm to explore energy landscapes
Journal Article (2011)
Journal
Journal of Computational Chemistry
Pages
3464–3474
Volume
32
Number
16
Doc link
http://dx.doi.org/10.1002/jcc.21931
File
Authors
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Jaillet, Léonard
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Corcho Sanchez, Francesc
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Pérez González, Juan Jesús
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Cortés, Juan
Projects associated
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.
Categories
robots.
Author keywords
energy landscape exploration, robot path planning algorithms, Monte Carlo methods, conformational transition paths, peptides
Scientific reference
L. Jaillet, F. Corcho, J.J. Pérez and J. Cortés. Randomized tree construction algorithm to explore energy landscapes. Journal of Computational Chemistry, 32(16): 3464–3474, 2011.
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