license: mit
Timewarp datasets
This dataset contains molecular dynamics simulation data that was used to train the neural networks in the NeurIPS 2023 paper Timewarp: Transferable Acceleration of Molecular Dynamics by Learning Time-Coarsened Dynamics.
This dataset consists of many molecular dynamics trajectories of small peptides (2-4 amino acids) simulated with an implicit water force field. For each protein two files are available:
protein-state0.pdb: contains the topology and initial 3D XYZ coordinates.protein-arrays.npz: contains trajectory information.
The datasets are are split into the following directories:
2AA-1-big "Two Amino Acid" data set
This folder contains a data set of all-atom molecular dynamics trajectories for 380
of the 400 dipeptides, i.e. small proteins composed of two amino acids.
This dataset was orginally created missing 20 of the 400 possible dipeptides.
The 2AA-1-complete dataset completes this by including all 400.
Each peptide is simulated using classical molecular dynamics and the
water is simulated using an implicit water model.
The trajectories are only saved every 10000 MD steps. There is no intermediate
spacing as for the other datasets for the Timewarp project.
2AA-1-complete "Two Amino Acid" data set
This folder contains a data set of all-atom molecular dynamics trajectories for all 400 dipeptides, i.e. small proteins composed of two amino acids. This includes also the peptides missing in the other 2AA datasets. Each peptide is simulated using classical molecular dynamics and the water is simulated using an implicit water model.
4AA-huge "Four Amino Acid" data set, tetrapeptides
This folder contains a data set of all-atom molecular dynamics trajectories for tetrapeptides, i.e. small proteins composed of four amino acids. The data set contains mostly validation and test trajectories as it was mostly used to validation and test purposes. The training trajectories used are usually shorter. Each peptide is simulated for 1 micro second using classical molecular dynamics and the water is simulated using an implicit water model.
4AA-large "Four Amino Acid" data set, tetrapeptides
This folder contains a data set of all-atom molecular dynamics trajectories for 2333 tetrapeptides, i.e. small proteins composed of four amino acids. The data set is split into 1500 tetra-peptides in the train set, 400 in validation, and 433 in test. Each peptide in the train set is simulated for 50ns using classical molecular dynamics and the water is simulated using an implicit water model. Each other peptide is simulated for 500ns.