Finding multiple reaction pathways via global optimization of action

Juyong Lee (), In-Ho Lee, InSuk Joung, Jooyoung Lee () and Bernard R. Brooks ()
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Juyong Lee: Laboratory of Computational Biology, National Heart, Lung, and Blood Institute (NHLBI), National Institutes of Health (NIH)
In-Ho Lee: Center for Materials Genome, Korea Research Institute of Standards and Science
InSuk Joung: Center for In Silico Protein Science, School of Computational Science, Korea Institute for Advanced Study
Jooyoung Lee: Center for In Silico Protein Science, School of Computational Science, Korea Institute for Advanced Study
Bernard R. Brooks: Laboratory of Computational Biology, National Heart, Lung, and Blood Institute (NHLBI), National Institutes of Health (NIH)

Nature Communications, 2017, vol. 8, issue 1, 1-8

Abstract: Abstract Global searching for reaction pathways is a long-standing challenge in computational chemistry and biology. Most existing approaches perform only local searches due to computational complexity. Here we present a computational approach, Action-CSA, to find multiple diverse reaction pathways connecting fixed initial and final states through global optimization of the Onsager–Machlup action using the conformational space annealing (CSA) method. Action-CSA successfully overcomes large energy barriers via crossovers and mutations of pathways and finds all possible pathways of small systems without initial guesses on pathways. The rank order and the transition time distribution of multiple pathways are in good agreement with those of long Langevin dynamics simulations. The lowest action folding pathway of FSD-1 is consistent with recent experiments. The results show that Action-CSA is an efficient and robust computational approach to study the multiple pathways of complex reactions and large-scale conformational changes.

Date: 2017
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DOI: 10.1038/ncomms15443

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