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.
Highlights
Global searching for reaction pathways is a long-standing challenge in computational chemistry and biology
Passerone and Parrinello suggested the action-derived molecular dynamics (ADMD) method based on the combination of classical action and a penalty term that conserves the total energy of a system[18,19]
The ADMD approaches yield physically relevant pathways, they have two practical limitations[20,24]: (a) they strongly depend on the initial guesses of a pathway; and (b) they cannot identify the relative dominance of multiple pathways because the classical principle of least action is an extremum principle[25]
Summary
Global searching for reaction pathways is a long-standing challenge in computational chemistry and biology. 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. Developing an efficient computational method to find multiple possible reaction pathways connecting two end states can serve as the ultimate and practical solution of the challenge. Various chain-of-states methods have been suggested based on the assumption that a dominant transition pathway between two states follows the minimum energy pathway[11,12,13] The limitations of these methods are that they do not consider the dynamics of a system and find only the nearest local minimum solution from a given initial pathway[1,9]. Finding multiple low action pathways is a challenging task because the minimization of SOM requires the second derivatives of a potential function, which are computationally expensive, at best, and wholly unavailable for many quantum mechanical energy surfaces
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call