| | --- |
| | viewer: false |
| | license: cc-by-4.0 |
| | tags: |
| | - chemistry |
| | - biology |
| | - molecular dynamics |
| | - neural network potential |
| | pretty_name: 'mdCATH: A Large-Scale MD Dataset for Data-Driven Computational Biophysics' |
| | author: A. Mirarchi, T. Giorgino and G. De Fabritiis |
| | size_categories: |
| | - 10M<n<100M |
| | --- |
| | |
| |
|
| | # mdCATH: A Large-Scale MD Dataset for Data-Driven Computational Biophysics |
| |
|
| | This dataset comprises all-atom systems for 5,398 CATH domains, modeled with a state-of-the-art classical force field, and simulated in five replicates each at five temperatures from 320 K to 450 K. |
| |
|
| | ## Availability |
| | - [torchmd-net dataloader](https://github.com/torchmd/torchmd-net/blob/main/torchmdnet/datasets/mdcath.py) |
| | - [playmolecule](https://open.playmolecule.org/mdcath) |
| | - [scripts to load, convert and rebuild](https://github.com/compsciencelab/mdCATH) |
| |
|
| |
|
| | ## Citing The Dataset |
| | Please cite this manuscript for papers that use the mdCATH dataset: |
| | > Mirarchi, A., Giorgino, T. & De Fabritiis, G. mdCATH: A Large-Scale MD Dataset for Data-Driven Computational Biophysics. Sci Data 11, 1299 (2024). https://doi.org/10.1038/s41597-024-04140-z. Preprint available at [arXiv:2407.14794](https://arxiv.org/abs/2407.14794v1) (2024). |
| |
|
| | ## Dataset Size |
| |
|
| | | Description | Value | |
| | |:---------------------|:-------------| |
| | | Domains | 5,398 | |
| | | Trajectories | 134,950 | |
| | | Total sampled time | 62.6 ms | |
| | | Total atoms | 11,671,592 | |
| | | Total amino acids | 740,813 | |
| | | Avg. traj. length | 464 ns | |
| | | Avg. system size | 2,162 atoms | |
| | | Avg. domain length | 137 AAs | |
| | | Total file size | 3.3 TB | |
