Predicting Small Molecule Transfer Free Energies by Combining Molecular Dynamics Simulations and Deep Learning.

Saved in:
Bibliographic Details
Title: Predicting Small Molecule Transfer Free Energies by Combining Molecular Dynamics Simulations and Deep Learning.
Authors: Bennett WFD; Biochemical and Biophysical Systems Group, Biosciences and Biotechnology Division, Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, California, United States., He S; Global Security Computing Applications, Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, California, United States., Bilodeau CL; Biochemical and Biophysical Systems Group, Biosciences and Biotechnology Division, Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, California, United States., Jones D; Global Security Computing Applications, Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, California, United States., Sun D; Biochemical and Biophysical Systems Group, Biosciences and Biotechnology Division, Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, California, United States., Kim H; Center for Applied Scientific Computing, Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, California, United States., Allen JE; Global Security Computing Applications, Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, California, United States., Lightstone FC; Biochemical and Biophysical Systems Group, Biosciences and Biotechnology Division, Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, California, United States., Ingólfsson HI; Biochemical and Biophysical Systems Group, Biosciences and Biotechnology Division, Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, California, United States.
Source: Journal of chemical information and modeling [J Chem Inf Model] 2020 Nov 23; Vol. 60 (11), pp. 5375-5381. Date of Electronic Publication: 2020 Sep 01.
Publication Type: Journal Article; Research Support, U.S. Gov't, Non-P.H.S.
Journal Info: Publisher: American Chemical Society Country of Publication: United States NLM ID: 101230060 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1549-960X (Electronic) Linking ISSN: 15499596 NLM ISO Abbreviation: J Chem Inf Model Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1549-960X
DOI:10.1021/acs.jcim.0c00318