Dataset

TSFF_PLOS_2022


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Name :
TSFF_PLOS_2022
Extended ID :
TSFF_PLOS_2022__Quinn-Patel-Koh-Haines-Norrby-Helquist-Wiest__DS_a0bxs66goqvv_0
ColabFit ID :
DS_a0bxs66goqvv_0
Files :
colabfitspec.json
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.
Num. Configurations :
1
Num. Atoms :
117
Downloads :
21
Calculated Property Types :
atomic_forces cauchy_stress energy
Elements :
C (29.06%) H (52.14%) N (6.84%) O (11.11%) S (0.85%)
Methods :
DFT-RM06
Software :
Gaussian 09
Publication Link :
https://doi.org/10.1371/journal.pone.0264960
Data Source Link :
https://doi.org/10.1371/journal.pone.0264960.s001
Configuration Sets by Name :
Configuration Sets by ID :
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