GLOW: A Workflow Integrating Gaussian-Accelerated Molecular Dynamics and Deep Learning for Free Energy Profiling

Do, Hung N.; Wang, Jinan; Bhattarai, Apurba; Miao, Yinglong

doi:10.1021/acs.jctc.1c01055

GLOW: A Workflow Integrating Gaussian-Accelerated Molecular Dynamics and Deep Learning for Free Energy Profiling

Journal Article · 24 February 2022 · Journal of Chemical Theory and Computation

DOI:https://doi.org/10.1021/acs.jctc.1c01055· OSTI ID:1981884

Do, Hung N. ^[1]; ^[1]; Bhattarai, Apurba ^[1]; ^[1]

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

Not provided.

Research Organization:: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC)

Sponsoring Organization:: USDOE

DOE Contract Number:: AC02-05CH11231

OSTI ID:: 1981884

Journal Information:: Journal of Chemical Theory and Computation, Vol. 18, Issue 3; ISSN 1549-9618

Publisher:: American Chemical Society

Country of Publication:: United States

Language:: English

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