---
license: mit
tags:
  - biology
  - protein
  - enzyme
  - ec-number
  - interpretability
---

# BioBlobs

The BioBlobs model behind the M-CSA results of **Unsupervised discovery of Functional
Substructures** (Xin Wang, Kaiwen Shi and Carlos Oliver, NeurIPS 2026).
[Paper](https://arxiv.org/abs/2510.01632) · [Code](https://github.com/OliverLaboratory/BioBlobs)

The model predicts third-level Enzyme Commission (EC) classes, 242 in total, from frozen ESM2-T30
residue embeddings and the protein structure. It splits each protein into 8 spatially local blobs
and quantizes their embeddings with residual vector quantization. The blobs it relies on most
point to candidate catalytic sites, although training uses only protein-level EC labels.

## Files

| File | Contents |
| --- | --- |
| `model.safetensors` | model weights (59 MB) |
| `config.yaml` | model configuration |
| `classes.json` | EC class names and their indices |
| `training_log.jsonl` | training log |

## Use

```bash
git clone https://github.com/OliverLaboratory/BioBlobs.git
cd BioBlobs
uv sync && source .venv/bin/activate
hf download xwang112358/BioBlobs --local-dir bioblobs-mcsa-rvq-k8
python inference.py --model bioblobs-mcsa-rvq-k8 --pdb-dir my_pdbs --out results
```

For each protein, the output lists the top EC classes, the blobs ranked by importance score with
their residue numbers, and per-residue scores. The repository's `docs/PREDICT.md` describes the
options and outputs, and `docs/REPRODUCE.md` shows how to retrain the model and evaluate it on
M-CSA.

## Training data

Swiss-Prot enzymes from the [EC-Bench](https://github.com/dsaeedeh/EC-Bench) training set, with
AlphaFold DB v6 structures. Training keeps proteins of up to 1,000 residues with a complete
third-level EC number, split into training and validation sets at 30% sequence identity with
MMseqs2. The GitHub repository ships the training and validation ids.

## Limitations

- The model only knows the 242 EC classes in its training data.
- Class probabilities are softmax scores, not calibrated confidence.
- A blob that overlaps annotated catalytic residues is evidence for, not proof of, its role in
  catalysis.

## Citation

```bibtex
@inproceedings{wang2026bioblobs,
  title     = {Unsupervised discovery of Functional Substructures},
  author    = {Wang, Xin and Shi, Kaiwen and Oliver, Carlos},
  booktitle = {Advances in Neural Information Processing Systems},
  year      = {2026}
}
```

## License

MIT