We propose a novel robotics-inspired algorithm to compute physically-realistic motions connecting thermodynamically-stable and semi-stable structural states in protein molecules. Protein motion computation is a challenging problem due to the high-dimensionality of the search space involved and ruggedness of the potential energy surface underlying the space. To handle the multiple local minima issue, we propose a novel algorithm that is not based on the traditional Molecular Dynamics or Monte Carlo frameworks but instead adapts ideas from robot motion planning. In particular, the algorithm balances computational resources between a global search aimed at obtaining a global view of the network of protein conformations and their connectivity and a detailed local search focused on realizing such connections with physically-realistic models. We present here promising results on a variety of proteins and demonstrate the general utility of the algorithm and its capability to improve the state of the art without employing system-specific insight.
CITATION STYLE
Molloy, K., & Shehu, A. (2015). Interleaving global and local search for protein motion computation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9096, pp. 175–186). Springer Verlag. https://doi.org/10.1007/978-3-319-19048-8_15
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