Dataset

Chig-AIMD_random_train

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Name :

Chig-AIMD_random_train

Extended ID :

Chig-AIMD_random_train__Wang-He-Li-Shao-Liu__DS_dsikv10na4f8_0

ColabFit ID :

DS_dsikv10na4f8_0

Files :

colabfitspec.json

Description :

Training configurations from the 'random' split of Chig-AIMD. This dataset covers the conformational space of chignolin with DFT-level precision. We sequentially applied replica exchange molecular dynamics (REMD), conventional MD, and ab initio MD (AIMD) simulations on a 10 amino acid protein, Chignolin, and finally collected 2 million biomolecule structures with quantum level energy and force records.

Authors :

Tong Wang, Xinheng He, Mingyu Li, Bin Shao, Tie-Yan Liu

DOI :

10.60732/fac841ac https://commons.datacite.org/doi.org/10.60732/fac841ac https://doi.datacite.org/dois/10.60732%2Ffac841ac https://doi.org/10.60732/fac841ac Cite as: Wang, T., He, X., Li, M., Shao, B., and Liu, T. "Chig-AIMD random train." ColabFit, 2023. https://doi.org/10.60732/fac841ac.
For other citation formats, see the DataCite Fabrica page for this dataset.

Num. Configurations :

1,592,677

Num. Atoms :

264,384,382

Downloads :

168

Calculated Property Types :

atomic_forces cauchy_stress energy

Elements :

C (37.35%) H (43.98%) N (6.63%) O (12.05%)

Methods :

DFT-M06-2X

Software :

ORCA 4.2.1

Publication Link :

https://doi.org/10.6084/m9.figshare.22786730.v4

Data Source Link :

https://doi.org/10.1038/s41597-023-02465-9

Configuration Sets by Name :

Configuration Sets by ID :

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