Introducing the first optimized Open Force Field 1.0.0 (codename "Parsley")
Creators
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Qiu, Yudong1
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Smith, Daniel G. A.2
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Boothroyd, Simon3
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Wagner, Jeffrey4
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Bannan, Caitlin C.4
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Gokey, Trevor4
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Jang, Hyesu1
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Lim, Victoria T.4
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Stern, Chaya D.3
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Rizzi, Andrea3
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Lucas, Xavier5
- Tjanaka, Bryon4
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Shirts, Michael R.6
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Gilson, Michael K.7
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Chodera, John D.3
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Bayly, Christopher I.8
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Mobley, David L.4
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Wang, Lee-Ping1
- 1. University of California Davis
- 2. Molecular Sciences Software Institute
- 3. Memorial Sloan Kettering Cancer Center
- 4. University of California Irvine
- 5. F. Hoffman - La Roche AG
- 6. University of Colorado Boulder
- 7. University of California San Diego
- 8. OpenEye Scientific Software Inc.
Description
This is a record for the blog post entry published on the openforcefield.org website on Oct 19, 2019, announcing the first optimized Open Force Field 1.0.0 (codename Parsley).
The Open Force Field 1.0.0 (Parsley) small molecule force field is the first in a series of iteratively-improved small molecule force fields for biomolecular simulation funded in part by the Open Force Field Consortium . This is the first optimized force field to use the SMIRNOFF force field specification for atom type-free direct chemical perception, and provides substantially improved valence (bond, angle, and torsion) parameters relative to its predecessor, the AMBER-lineage SMIRNOFF99Frosst. This force field was optimized to improve agreement with quantum chemical geometries, energetics, and vibrational frequencies, and will likely provide improved accuracy (relative to its predecessor) for a wide variety of properties, especially energetics and geometries relative to gas phase quantum chemical calculations.
Files
OpenForceField1.0.0-BlogPost-Zenodo.pdf
Files
(2.8 MB)
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Additional details
Related works
- Documents
- Project deliverable: https://openforcefield.org/news/introducing-openforcefield-1.0/ (URL)
- Is supplemented by
- Software: https://github.com/openforcefield/openforcefields/tree/1.0.0 (URL)
- Software: https://github.com/openforcefield/openforcefield (URL)
- References
- Software: https://zenodo.org/record/3483227 (URL)
References
- Mobley, David. L. et al. (2018). Escaping atom types using direct chemical perception, https://dx.doi.org/10.1021/acs.jctc.8b00640
- Bannan, Caitlin C. et al. (2019). ChemPer: An Open Source Tool for Automatically Generating SMIRKS Patterns, https://dx.doi.org/10.1021/acs.jctc.9b00748
- Qiu, Yudong et al. (2020). Driving torsion scans with wavefront propagation, https://dx.doi.org/10.1021/acs.jctc.9b00748