DOI: 10.5281/zenodo.18456110
title: MHC-Diff 8K pMHC Structure Dataset (HLA-A*02:01 9-mer)

description: # MHC-Diff 8K Dataset: HLA-A*02:01 9-mer pMHC Structures


[![License: CC BY 4.0](https://img.shields.io/badge/License-CC_BY_4.0-lightgrey.svg)](https://creativecommons.org/licenses/by/4.0/)


## Overview


This dataset contains **7,928 peptide-MHC class I (pMHC-I) structures** for the HLA-A*02:01 allele with 9-mer peptides. It is designed for training and evaluating machine learning models for pMHC structure prediction.


| Property | Value |

|----------|-------|

| **Total structures** | 7,928 |

| **X-ray structures** | 202 (from PDB) |

| **PANDORA structures** | 7,726 (computationally modeled) |

| **MHC allele** | HLA-A\*02:01 |

| **Peptide length** | 9 amino acids |

| **Number of clusters** | 10 |

| **Total size** | ~600 MB |


## Data Sources


- **X-ray structures**: Experimental structures from the [Protein Data Bank (PDB)](https://www.rcsb.org/)

- **PANDORA structures**: Computationally modeled structures from the [PANDORA database](https://github.com/X-lab-3D/PANDORA)


## Clustering Strategy


Peptides were clustered using **GibbsCluster** based on sequence similarity into 10 clusters. This ensures that test peptides share no close sequence similarity with training peptides, enabling rigorous evaluation of generalization to novel peptide sequences.


## Files


```

mhc-diff-8k-v1.0/

├── README.md # This file

├── LICENSE # CC-BY-4.0 license

├── SHA256SUMS # Checksums for all files

├── samples.parquet # Sample index (recommended)

├── samples.tsv.gz # Sample index (alternative format)

├── split_recipes/ # Cross-validation fold definitions

│ ├── fold_0.json # Leave cluster 0 out

│ ├── fold_1.json # Leave cluster 1 out

│ ├── ...

│ └── README.json # Split recipe documentation

└── structures/ # HDF5 structure files

├── combined_cluster0.hdf5

├── combined_cluster1.hdf5

├── ...

└── combined_cluster9.hdf5

```


## Data Format


### Sample Index (`samples.parquet`)


| Column | Description |

|--------|-------------|

| `sample_id` | Unique structure identifier |

| `cluster_id` | Cluster assignment (0-9) |

| `source` | `xray` or `pandora` |

| `structure_file` | HDF5 file containing the structure |

| `allele` | MHC allele (all HLA-A\*02:01) |

| `peptide_length` | Peptide length (all 9) |


### HDF5 Structure Files


Each HDF5 file contains multiple structures indexed by `sample_id`:


**X-ray structures** (4-letter PDB codes):

```python

import h5py

with h5py.File('combined_cluster0.hdf5', 'r') as f:

pdb_string = f['1AKJ'][()].decode('utf-8') # Raw PDB format

```


**PANDORA structures** (IDs starting with `BA-`):

```python

with h5py.File('combined_cluster0.hdf5', 'r') as f:

entry = f['BA-12345']

peptide_coords = entry['peptide']['atom14_gt_positions'][:, 1, :] # Cα coords

protein_coords = entry['protein']['atom14_gt_positions'][:, 1, :] # Cα coords

```


## Usage


### 10-Fold Cross-Validation


```python

import pandas as pd

import json


# Load sample index

samples = pd.read_parquet('samples.parquet')


# Load fold definition

with open('split_recipes/fold_0.json') as f:

fold = json.load(f)


# Split data

train = samples[samples['cluster_id'].isin(fold['train_clusters'])]

test = samples[samples['cluster_id'].isin(fold['test_clusters'])]

```


## Related Datasets


This dataset is a **subset** of the larger MHC-Diff 100K dataset, which covers 110 diverse MHC alleles and peptide lengths 8-13.


- **MHC-Diff 100K Dataset**: [Zenodo DOI to be added]


## Citation


If you use this dataset, please cite:


```bibtex

@article{fruhbuss2025mhcdiff,

title={MHC-Diff: Fast and Accurate Peptide-MHC Structure Prediction via an Equivariant Diffusion Model},

author={Fr{\"u}hbu{\ss}, David and Baakman, Coos and Teusink, Siem and Bekkers, Erik and Jegelka, Stefanie and Xue, Li},

year={2025}

}

```


## References


1. Berman, H.M., et al. "The Protein Data Bank." *Nucleic Acids Research* 28(1), 235–242 (2000). https://doi.org/10.1093/nar/28.1.235

2. Marzella, D.F., et al. "PANDORA: a fast, anchor-restrained modelling protocol for peptide:MHC complexes." *Frontiers in Immunology* 13, 878762 (2022). https://doi.org/10.3389/fimmu.2022.878762

3. Andreatta, M., et al. "GibbsCluster: unsupervised clustering and alignment of peptide sequences." *Nucleic Acids Research* 45(W1), W458–W463 (2017). https://doi.org/10.1093/nar/gkx248


## License


This dataset is released under the [Creative Commons Attribution 4.0 International License (CC-BY-4.0)](https://creativecommons.org/licenses/by/4.0/).


## Contact


- Li Xue: Li.Xue@radboudumc.nl