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  Development and Benchmarking of Open Force Field 2.0.0: The Sage Small Molecule Force Field

Boothroyd, S., Behara, P. K., Madin, O. C., Hahn, D. F., Jang, H., Gapsys, V., et al. (2023). Development and Benchmarking of Open Force Field 2.0.0: The Sage Small Molecule Force Field. Journal of Chemical Theory and Computation, 19(11), 3251-3275. doi:10.1021/acs.jctc.3c00039.

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 Creators:
Boothroyd, Simon, Author
Behara, Pavan Kumar, Author
Madin, Owen C., Author
Hahn, David F., Author
Jang, Hyesu, Author
Gapsys, Vytautas1, 2, Author           
Wagner, Jeffrey R., Author
Horton, Joshua T., Author
Dotson, David L., Author
Thompson, Matthew W., Author
Maat, Jessica, Author
Gokey, Trevor, Author
Wang, Lee-Ping, Author
Cole, Daniel J., Author
Gilson, Michael K., Author
Chodera, John D., Author
Bayly, Christopher I., Author
Shirts, Michael R., Author
Mobley, David L., Author
Affiliations:
1Research Group of Computational Biomolecular Dynamics, Max Planck Institute for Multidisciplinary Sciences, Max Planck Society, ou_3350134              
2Department of Theoretical and Computational Biophysics, Max Planck Institute for Multidisciplinary Sciences, Max Planck Society, Göttingen, DE, ou_3350132              

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 Abstract: We introduce the Open Force Field (OpenFF) 2.0.0 small molecule force field for drug-like molecules, code-named Sage, which builds upon our previous iteration, Parsley. OpenFF force fields are based on direct chemical perception, which generalizes easily to highly diverse sets of chemistries based on substructure queries. Like the previous OpenFF iterations, the Sage generation of OpenFF force fields was validated in protein–ligand simulations to be compatible with AMBER biopolymer force fields. In this work, we detail the methodology used to develop this force field, as well as the innovations and improvements introduced since the release of Parsley 1.0.0. One particularly significant feature of Sage is a set of improved Lennard-Jones (LJ) parameters retrained against condensed phase mixture data, the first refit of LJ parameters in the OpenFF small molecule force field line. Sage also includes valence parameters refit to a larger database of quantum chemical calculations than previous versions, as well as improvements in how this fitting is performed. Force field benchmarks show improvements in general metrics of performance against quantum chemistry reference data such as root-mean-square deviations (RMSD) of optimized conformer geometries, torsion fingerprint deviations (TFD), and improved relative conformer energetics (ΔΔE). We present a variety of benchmarks for these metrics against our previous force fields as well as in some cases other small molecule force fields. Sage also demonstrates improved performance in estimating physical properties, including comparison against experimental data from various thermodynamic databases for small molecule properties such as ΔHmix, ρ(x), ΔGsolv, and ΔGtrans. Additionally, we benchmarked against protein–ligand binding free energies (ΔGbind), where Sage yields results statistically similar to previous force fields. All the data is made publicly available along with complete details on how to reproduce the training results at https://github.com/openforcefield/openff-sage.

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Language(s): eng - English
 Dates: 2023-05-112023-06-13
 Publication Status: Issued
 Pages: -
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 Rev. Type: Peer
 Identifiers: DOI: 10.1021/acs.jctc.3c00039
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Project name : We thank the Open Force Field Consortium for funding, including our industry partners as listed at the Open Force Field website. We thank the Open Force Field Consortium and Initiative for financial and scientific support, and the Open Molecular Software Foundation (OMSF) for its support of the Open Force Field Initiative. Particularly, we gratefully acknowledge Karmen Condic-Jurkic for helpful discussions, along with all current and former members of the Open Force Field Initiative and the Open Force Field Scientific Advisory Board. Grants: We thank the National Institutes of Health (NIGMS R01GM132386) for funding longer term aspects of this initiative. MKG acknowledges funding from the National Institute of General Medical Sciences (GM061300). LPW and HJ acknowledge support from ACS PRF 58158-DNI6. MRS and JDC acknowledge support from NSF CHE-1738975. DJC and JH acknowledge support from a UKRI Future Leaders Fellowship (grant MR/T019654/1). These findings are solely of the authors and do not necessarily represent the views of the NIH or NSF.
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Title: Journal of Chemical Theory and Computation
  Other : J. Chem. Theory Comput.
  Abbreviation : JCTC
Source Genre: Journal
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Publ. Info: Washington, D.C. : American Chemical Society
Pages: - Volume / Issue: 19 (11) Sequence Number: - Start / End Page: 3251 - 3275 Identifier: ISSN: 1549-9618
CoNE: https://pure.mpg.de/cone/journals/resource/111088195283832