---
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:

> 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      |