Datasets:
File size: 1,570 Bytes
33cc182 751504f 867d2a0 751504f 33cc182 751504f 33cc182 6bd5e2f 33cc182 6bd5e2f 7c651dc 751504f 33cc182 751504f e62e3b6 33cc182 e8a3d88 33cc182 867d2a0 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 |
---
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'
authors: 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:
> Antonio Mirarchi, Toni Giorgino, Gianni De Fabritiis. "mdCATH: A Large-Scale MD Dataset for Data-Driven Computational Biophysics" ([arXiv:2407.14794](https://arxiv.org/abs/2407.14794v1))
## 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 | |