Dataset

TSFF_PLOS_2022



Download Dataset XYZ files Download Dataset Parquet files

Name TSFF_PLOS_2022
Extended ID TSFF_PLOS_2022__Quinn-Patel-Koh-Haines-Norrby-Helquist-Wiest__DS_a0bxs66goqvv_0
Description One configuration of an enzyme: training data for a quantum-guided molecular mechanics model.
Authors Taylor R. Quinn
Himani N. Patel
Kevin H. Koh
Brandon E. Haines
Per-Ola Norrby
Paul Helquist
Olaf Wiest
DOI 10.60732/e75f2602
https://commons.datacite.org/doi.org/10.60732/e75f2602
https://doi.datacite.org/dois/10.60732%2Fe75f2602
https://doi.org/10.60732/e75f2602

Cite as: Quinn, T. R., Patel, H. N., Koh, K. H., Haines, B. E., Norrby, P., Helquist, P., and Wiest, O. "TSFF PLOS 2022." ColabFit, 2023. https://doi.org/10.60732/e75f2602.
For other citation formats, see the DataCite Fabrica page for this dataset.
Calculated Property Types atomic_forces
cauchy_stress
energy
Elements C (29.06%)
H (52.14%)
N (6.84%)
O (11.11%)
S (0.85%)
Number of Configurations 1
Number of Atoms 117
Links https://doi.org/10.1371/journal.pone.0264960.s001
https://doi.org/10.1371/journal.pone.0264960
Configuration Sets by Name (None)
Configuration Sets by ID (None)
Calculated Properties
ColabFit ID DS_a0bxs66goqvv_0
Files colabfitspec.json

No uploaded content is transferred in ownership from the original creators to ColabFit. All content is distributed under the license specified by its contributor who has stated that he or she has the authority to share it under the specified license.