PreprintCited by 0Advanced Physical and Chemical Molecular InteractionsAdvanced Thermodynamics and Statistical Mechanicsstochastic dynamics and bifurcation

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Potential Energy Weighted Reactive Flux and Total Rate of Change of Potential Energy: Theory and Illustrative Applications

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Li, Wenjin·2022·The Journal of Physical Chemistry A

Preprint — published as 10.1021/acs.jpca.2c04886

Abstract

Reactive flux can be largely non-zero in a nonequilibrium ensemble of trajectories and provide insightful information for reactive transitions from the reactant state to the product state. Based on the reactive flux, a theoretical framework is proposed here for two quantities, the potential energy weighted reactive flux and the total rate of change of potential energy, which are useful for the identification of mechanism from a nonequilibrium ensemble. From such quantities, two multidimensional free energy analogues can be derived in the subspace of collective variables and they are equivalent in the regions where the reactive flux is divergence-free. These free energy analogues are assumed to be closely related to the free energy in the subspace of collective variables and they are reduced in the one-dimensional case to be the ensemble average of the potential energy weighted with reactive flux intensity, which was proposed recently and could be decomposed into energy components at the per-coordinate level. In the subspace of collective variables, the decomposition of the multidimensional free energy analogues at the per-coordinate level is theoretically possible and is numerically difficult to be calculated. Interestingly, the total rate of change of potential energy is able to identify the location of the transition state ensemble or the stochastic separatrix, in addition to the locations of the reactant and product states. The total rate of change of potential energy can be decomposed at the per-coordinate level and its components can quantify the contribution of a coordinate to the reactive transition in the subspace of collective variables. We then illustrated the main insights and objects that can be provided by the approach in the application to the alanine peptide in vacuum in various nonequilibrium ensembles of short trajectories and the results from these ensembles were found to be consistent.

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  1. 10.1038/nsb0902-646 · DOI
  2. Wang, X. ; Singh, N. ; Li, W. Systems Medicine; Elsevier, 2021; pp 182–189. · DOI
  3. 10.1063/1.436049 · DOI
  4. 10.1063/1.478569 · DOI
  5. 10.1063/1.1630572 · DOI
  6. 2011, Toward identification of the reaction coordinate directly from the transition state ensemble using the kernel PCA method, J. Phys. Chem. B, 115, 2465, 10.1021/jp111682x · DOI
  7. 10.1080/08927022.2014.907898 · DOI
  8. 10.1063/1.475562 · DOI
  9. 10.1039/a801266k · DOI
  10. 10.1146/annurev.physchem.53.082301.113146 · DOI · Paper page
  11. 2002, Transition path sampling, Adv. in Chem. Phys, 123, 1
  12. Jonsson, H. ; Mills, G. ; Jacobsen, K. W. Classical and Quantum Dynamics in Condensed Phase Simulations; World Scientific, 1998; pp 385–404.
  13. 10.1063/1.1329672 · DOI
  14. 10.1063/1.2212942 · DOI
  15. 10.1021/jp0777059 · DOI
  16. 10.1088/0953-8984/21/46/463102 · DOI
  17. 10.1063/1.2776270 · DOI
  18. 10.1103/PhysRev.54.554 · DOI
  19. 1987, On the eigenfunctions of the Fokker-Planck operator and of its adjoint, Phys. A: Stat. Mech. Appl, 142, 103, 10.1016/0378-4371(87)90019-7 · DOI
  20. 10.1063/1.475393 · DOI
  21. 10.1063/1.1818091 · DOI
  22. 10.1021/jp045544s · DOI
  23. 10.1021/jp045546c · DOI · Paper page
  24. 10.1063/1.2234477 · DOI · Paper page
  25. 10.1063/1.2748396 · DOI
  26. 2013, Reaction coordinates, onedimensional Smoluchowski equations, and a test for dynamical self-consistency, J. Chem. Phys, 138, 054106, 10.1063/1.4775807 · DOI
  27. 2018, Equipartition terms in transition path ensemble: Insights from molecular dynamics simulations of alanine dipeptide, J. Chem. Phys, 148, 084105, 10.1063/1.5010408 · DOI
  28. 2022, Optimizing reaction coordinate by flux maximization in the transition path ensemble, J. Chem. Phys, 156, 054117, 10.1063/5.0079390 · DOI · Paper page
  29. 10.1146/annurev.physchem.040808.090412 · DOI
  30. 2022, Time-lagged Flux in the Transition Path Ensemble: Flux Maximization and Relation to Transition Path Theory, J. Phys. Chem. A, 126, 3797, 10.1021/acs.jpca.2c02221 · DOI
  31. 2015, Reducing the cost of evaluating the committor by a fitting procedure, J. Chem. Phys, 143, 174103, 10.1063/1.4934782 · DOI
  32. 2021, Nonparametric Analysis of Nonequilibrium Simulations, J. Chem. Theory Comput, 17, 5466, 10.1021/acs.jctc.1c00218 · DOI
  33. 2017, Calculating isocommittor surfaces as optimal reaction coordinates with milestoning, Entropy, 19, 219, 10.3390/e19050219 · DOI
  34. 2017, Variational Koopman models: slow collective variables and molecular kinetics from short off-equilibrium simulations, J. Chem. Phys, 146, 154104, 10.1063/1.4979344 · DOI
  35. 2018, Machine learning of biomolecular reaction coordinates, J. Phys. Chem. Lett, 9, 2144, 10.1021/acs.jpclett.8b00759 · DOI
  36. Jung, H. ; Covino, R. ; Hummer, G. Artificial intelligence assists discovery of reaction coordinates and mechanisms from molecular dynamics simulations. arXiv 2019, 1901.04595.
  37. 2009, The stochastic separatrix and the reaction coordinate for complex systems, J. Chem. Phys, 130, 151103, 10.1063/1.3123162 · DOI
  38. 2016, A benchmark for reaction coordinates in the transition path ensemble, J. Chem. Phys, 144, 134104, 10.1063/1.4945337 · DOI
  39. 10.1073/pnas.100127697 · DOI · Paper page
  40. 2016, Reaction mechanism and reaction coordinates from the viewpoint of energy flow, J. Chem. Phys, 144, 114103, 10.1063/1.4943581 · DOI
  41. 2020, Learning reaction coordinates via cross-entropy minimization: Application to alanine dipeptide, J. Chem. Phys, 153, 054115, 10.1063/5.0009066 · DOI
  42. 2020, Residue–Residue Mutual Work Analysis of Retinal–Opsin Interaction in Rhodopsin: Implications for Protein–Ligand Binding, J. Chem. Theory Comput, 16, 1834, 10.1021/acs.jctc.9b01035 · DOI
  43. 2021, String Method with Swarms-of-Trajectories, Mean Drifts, Lag Time, and Committor, J. Phys. Chem. A, 125, 7558, 10.1021/acs.jpca.1c04110 · DOI
  44. 2012, Characterization of a dynamic string method for the construction of transition pathways in molecular reactions, J. Phys. Chem. B, 116, 8573, 10.1021/jp212611k · DOI
  45. 10.1016/j.softx.2015.06.001 · DOI · Paper page

Metadata

Authors
Li, W.
Affiliations
Shenzhen University (CN)
Corresponding author
Li, Wenjin
Venue
The Journal of Physical Chemistry A
Publisher
openRxiv
Published
2022-07-10
Volume
126
Issue
42
Pages
7774-7786
ISSN
1089-5639 (ISSN-L)
OpenAlex
W4306410250
Cited by
0
References
1
FWCI
0.00
Type
journal article
Language
en
Open access
Licence
cc-by-nc-nd
Locations
  • The Journal of Physical Chemistry A (publishedVersion)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
Funders
  • Natural Science Foundation of Guangdong Province (2020A1515010984, 860-000002110384)
  • Shenzhen University (860-000002110384)
Topics
  • Physical Sciences › Chemistry › Physical and Theoretical Chemistry › Advanced Physical and Chemical Molecular Interactions
  • Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Advanced Thermodynamics and Statistical Mechanics
  • Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › stochastic dynamics and bifurcation
Keywords
reactive flux, collective variables, transition state ensemble, diffusion anisotropy, alanine peptides
MeSH terms
Alanine

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