Deep Boosted Molecular Dynamics: Accelerating Molecular Simulations with Gaussian Boost Potentials Generated Using Probabilistic Bayesian Deep Neural Network-Reference-Cited by-同舟云学术

Deep Boosted Molecular Dynamics: Accelerating Molecular Simulations with Gaussian Boost Potentials Generated Using Probabilistic Bayesian Deep Neural Network

Published:2023-05-23 Issue:21 Volume:14 Page:4970-4982
ISSN:1948-7185
Container-title:The Journal of Physical Chemistry Letters
language:en
Short-container-title:J. Phys. Chem. Lett.

Author:

Do Hung N.¹^ORCID,Miao Yinglong¹^ORCID

Affiliation:

1. Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas 66047, United States

Funder

National Institutes of Health

National Science Foundation

Publisher

American Chemical Society (ACS)

Subject

General Materials Science,Physical and Theoretical Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jpclett.3c00926

Reference43 articles.

1. Molecular dynamics simulations of biomolecules

2. Molecular Dynamics Simulation for All

3. Gaussian accelerated molecular dynamics: Principles and applications

4. ACEMD: Accelerating Biomolecular Dynamics in the Microsecond Time Scale

5. Anton 3

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