We present an implementation of a scalable path deviation algorithm to find the k most kinetically relevant paths in a transition network, where each path is distinguished on the basis of having a distinct rate-limiting edge. The potential of the algorithm to identify distinct pathways that exist in separate regions of the configuration space is demonstrated for two benchmark systems with double-funnel energy landscapes, namely a model “three-hole” network embedded on a 2D potential energy surface and the cluster of 38 Lennard-Jones atoms (LJ38). The path cost profiles for the interbasin transitions of the two systems reflect the contrasting nature of the landscapes. There are multiple well-defined pathway ensembles for the three-hole system, whereas the transition in LJ38 effectively involves a single ensemble of pathways via disordered structures. A by-product of the algorithm is a set of edges that constitute a cut of the network, which is related to the discrete analog of a transition dividing surface. The algorithm ought to be useful for determining the existence, or otherwise, of competing mechanisms in large stochastic network models of dynamical processes and for assessing the kinetic relevance of distinguishable ensembles of pathways. This capability will provide insight into conformational transitions in biomolecules and other complex slow processes.
Skip Nav Destination
Article navigation
28 September 2019
Research Article|
September 24 2019
Identifying mechanistically distinct pathways in kinetic transition networks
Daniel J. Sharpe
;
Daniel J. Sharpe
Department of Chemistry, University of Cambridge
, Lensfield Road, Cambridge CB2 1EW, United Kingdom
Search for other works by this author on:
David J. Wales
David J. Wales
a)
Department of Chemistry, University of Cambridge
, Lensfield Road, Cambridge CB2 1EW, United Kingdom
Search for other works by this author on:
a)
Electronic mail: dw34@cam.ac.uk
J. Chem. Phys. 151, 124101 (2019)
Article history
Received:
May 31 2019
Accepted:
August 16 2019
Citation
Daniel J. Sharpe, David J. Wales; Identifying mechanistically distinct pathways in kinetic transition networks. J. Chem. Phys. 28 September 2019; 151 (12): 124101. https://doi.org/10.1063/1.5111939
Download citation file:
Sign in
Don't already have an account? Register
Sign In
You could not be signed in. Please check your credentials and make sure you have an active account and try again.
Pay-Per-View Access
$40.00
Citing articles via
A theory of pitch for the hydrodynamic properties of molecules, helices, and achiral swimmers at low Reynolds number
Anderson D. S. Duraes, J. Daniel Gezelter
DeePMD-kit v2: A software package for deep potential models
Jinzhe Zeng, Duo Zhang, et al.
Electronic structure simulations in the cloud computing environment
Eric J. Bylaska, Ajay Panyala, et al.
Related Content
Single-root networks for describing the potential energy surface of Lennard-Jones clusters
J. Chem. Phys. (August 2018)
Quantum-induced solid-solid transitions and melting in the Lennard-Jones LJ38 cluster
J. Chem. Phys. (September 2018)
Simulating structural transitions by direct transition current sampling: The example of LJ38
J. Chem. Phys. (July 2011)
Particle-swarm structure prediction on clusters
J. Chem. Phys. (August 2012)
Minima hopping guided path search: An efficient method for finding complex chemical reaction pathways
J. Chem. Phys. (June 2014)