colabfit/Chig-AIMD_random_train

Cite this dataset

Wang, T., He, X., Li, M., Shao, B., and Liu, T. Chig-AIMD random train. ColabFit, 2023. https://doi.org/10.60732/fac841ac

This dataset has been curated and formatted for the ColabFit Exchange

This dataset is also available on the ColabFit Exchange:

https://materials.colabfit.org/id/DS_dsikv10na4f8_0

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Dataset Name

Chig-AIMD random train

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.

Dataset authors

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

Publication

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

Original data link

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

License

CC-BY-4.0

Number of unique molecular configurations

1592677

Number of atoms

264384382

Elements included

C, H, N, O

Properties included

energy, atomic forces

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Usage

• ds.parquet : Aggregated dataset information.
• co/ directory: Configuration rows each include a structure, calculated properties, and metadata.
• cs/ directory : Configuration sets are subsets of configurations grouped by some common characteristic. If cs/ does not exist, no configurations sets have been defined for this dataset.
• cs_co_map/ directory : The mapping of configurations to configuration sets (if defined).
  

ColabFit Exchange documentation includes descriptions of content and example code for parsing parquet files:

• Parquet parsing: example code
• Dataset info schema
• Configuration schema
• Configuration set schema
• Configuration set to configuration mapping schema