A Multi-Tree Approach to Compute Transition Paths on Energy Landscapes

Exploring the conformational energy landscape of a molecule is an important but challenging problem because of the inherent complexity of this landscape. As part of this theme, various methods have been developed to compute transition paths between stable states of a molecule. Besides the methods classically used in biophysics/biochemistry, a recent approach originating from the robotics community has proven to be an efficient tool for conformational exploration. This approach, called the Transition-based RRT (T-RRT) is based on the combination of an effective path planning algorithm (RRT) with a Monte-Carlo-like transition test. In this paper, we propose an extension to TRRT based on a multi-tree approach, which we call Multi-T-RRT. It builds several trees rooted at different interesting points of the energy landscape and allows to quickly gain knowledge about possible conformational transition paths. We demonstrate this on the alanine dipeptide.

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