The reaction coordinate (RC) is the principal collective variable or feature that determines the progress along an activated or reactive process. In a molecular simulation using enhanced sampling, a good description of the RC is crucial for generating sufficient statistics. Moreover, the RC provides invaluable atomistic insight into the process under study. The optimal RC is the committor, which represents the likelihood of a system to evolve toward a given state based on the coordinates of all its particles. As the interpretability of such a high dimensional function is low, a more practical approach is to describe the RC by some low-dimensional molecular collective variables or order parameters. While several methods can perform this dimensionality reduction, they usually require a preselection of these low-dimension collective variables (CVs). Here, we propose to automate this dimensionality reduction using an extended autoencoder, which maps the input (many CVs) onto a lower-dimensional latent space, which is subsequently used for the reconstruction of the input as well as the prediction of the committor function. As a consequence, the latent space is optimized for both reconstruction and committor prediction and is likely to yield the best non-linear low-dimensional representation of the committor. We test our extended autoencoder model on simple but nontrivial toy systems, as well as extensive molecular simulation data of methane hydrate nucleation. The extended autoencoder model can effectively extract the underlying mechanism of a reaction, make reliable predictions about the committor of a given configuration, and potentially even generate new paths representative for a reaction.
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14 August 2021
Research Article|
August 09 2021
An extended autoencoder model for reaction coordinate discovery in rare event molecular dynamics datasets
Special Collection:
JCP Editors' Choice 2021
M. Frassek
;
M. Frassek
van’t Hoff Institute for Molecular Sciences, University of Amsterdam
, P.O. Box 94157, 1090 GD Amsterdam, The Netherlands
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A. Arjun
;
A. Arjun
van’t Hoff Institute for Molecular Sciences, University of Amsterdam
, P.O. Box 94157, 1090 GD Amsterdam, The Netherlands
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P. G. Bolhuis
P. G. Bolhuis
a)
van’t Hoff Institute for Molecular Sciences, University of Amsterdam
, P.O. Box 94157, 1090 GD Amsterdam, The Netherlands
a)Author to whom correspondence should be addressed: [email protected]
Search for other works by this author on:
M. Frassek
P. G. Bolhuis
a)
van’t Hoff Institute for Molecular Sciences, University of Amsterdam
, P.O. Box 94157, 1090 GD Amsterdam, The Netherlands
a)Author to whom correspondence should be addressed: [email protected]
J. Chem. Phys. 155, 064103 (2021)
Article history
Received:
June 01 2021
Accepted:
July 15 2021
Citation
M. Frassek, A. Arjun, P. G. Bolhuis; An extended autoencoder model for reaction coordinate discovery in rare event molecular dynamics datasets. J. Chem. Phys. 14 August 2021; 155 (6): 064103. https://doi.org/10.1063/5.0058639
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