Escaping Atom Types in Force Fields Using Direct Chemical Perception-Reference-Cited by-同舟云学术

Escaping Atom Types in Force Fields Using Direct Chemical Perception

Published:2018-10-11 Issue:11 Volume:14 Page:6076-6092
ISSN:1549-9618
Container-title:Journal of Chemical Theory and Computation
language:en
Short-container-title:J. Chem. Theory Comput.

Author:

Mobley David L.¹²^ORCID,Bannan Caitlin C.²^ORCID,Rizzi Andrea³⁴,Bayly Christopher I.⁵,Chodera John D.⁴^ORCID,Lim Victoria T.²,Lim Nathan M.¹,Beauchamp Kyle A.⁶,Slochower David R.⁷,Shirts Michael R.⁸^ORCID,Gilson Michael K.⁷,Eastman Peter K.⁹

Affiliation:

1. Department of Pharmaceutical Science, University of California, Irvine, California 92697, United States

2. Department of Chemistry, University of California, Irvine, California 92697, United States

3. Tri-Institutional Program in Computational Biology and Medicine, New York, New York 10065, United States

4. Computational and Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York, New York 10065, United States

5. OpenEye Scientific Software, Santa Fe, New Mexico 87507, United States

6. Counsyl, South San Francisco, California 94080, United States

7. Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, California 92093, United States

8. Department of Chemical and Biological Engineering, University of Colorado Boulder, Boulder, Colorado 80309, United States

9. Department of Chemistry, Stanford University, Stanford, California 94305, United States

Funder

Division of Chemistry

National Cancer Institute

Memorial Sloan-Kettering Cancer Center

National Institute of General Medical Sciences

Publisher

American Chemical Society (ACS)

Subject

Physical and Theoretical Chemistry,Computer Science Applications

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jctc.8b00640

Reference85 articles.

1. Advancing Drug Discovery through Enhanced Free Energy Calculations

2. GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers

3. Blind prediction of cyclohexane–water distribution coefficients from the SAMPL5 challenge

4. Toward Automated Benchmarking of Atomistic Force Fields: Neat Liquid Densities and Static Dielectric Constants from the ThermoML Data Archive

5. Perfluoropolyethers: Development of an All-Atom Force Field for Molecular Simulations and Validation with New Experimental Vapor Pressures and Liquid Densities

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