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 :

Num. Atoms :

117

Downloads :

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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