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
Name: Chig-AIMD_random_train
Extended ID: Chig-AIMD_random_train__Wang-He-Li-Shao-Liu__DS_dsikv10na4f8_0
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
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
Number of Configurations: 1,592,677
Number of Atoms: 264,384,382
Publication Link: https://doi.org/10.6084/m9.figshare.22786730.v4
Data Source Link: https://doi.org/10.1038/s41597-023-02465-9
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