| --- |
| license: other |
| license_name: cc-by-4.0-and-apache-2.0 |
| license_link: LICENSE.md |
| pretty_name: BioBlobs data |
| tags: |
| - biology |
| - protein |
| - protein-function |
| - proteinshake |
| - venusx |
| size_categories: |
| - 100K<n<1M |
| --- |
| |
| # BioBlobs data |
|
|
| The ProteinShake and VenusX data behind **Unsupervised discovery of Functional Substructures** |
| (Xin Wang, Kaiwen Shi and Carlos Oliver, NeurIPS 2026), in the layout the BioBlobs code reads. |
| [Paper](https://arxiv.org/abs/2510.01632) · [Code](https://github.com/OliverLaboratory/BioBlobs) · |
| [Model](https://huggingface.co/xwang112358/BioBlobs) |
|
|
| It holds the protein structures, labels and train, validation and test splits. For VenusX it also |
| holds the paper's ESM2-T30 and SaProt-650M residue embeddings. Build the ProteinShake embeddings |
| with the code, as described below. |
|
|
| ## Contents |
|
|
| | Folder | Task | Structures | Source | |
| |---|---|---|---| |
| | `ec_proteinshake/` | EC-L3, enzyme class | 15,603 | ProteinShake, RCSB PDB | |
| | `pfam_proteinshake/` | Pfam, protein family | 31,109 | ProteinShake, RCSB PDB | |
| | `go_molecular_function_proteinshake/` | GO-MF, molecular function | 32,633 | ProteinShake, RCSB PDB | |
| | `scop_fam_proteinshake/` | SCOP-FAM, SCOP family | 10,066 | ProteinShake, RCSB PDB | |
| | `scop_sf_proteinshake/` | SCOP-SF, SCOP superfamily | 10,066 | ProteinShake, RCSB PDB | |
| | `venusx_site_fragment/{Act,BindI,Evo,Motif}/MF50/` | VenusX functional sites | 1,743 / 2,038 / 12,776 / 2,368 | VenusX, AlphaFold DB | |
|
|
| Each ProteinShake task has a `sequence` and a `structure` split, which assign clusters of similar |
| sequences or structures (0.7 similarity) to disjoint splits. VenusX uses its Mixed-Family MF-50 |
| split. SCOP-FAM and SCOP-SF share the same structures, which are included in both folders. |
|
|
| The VenusX embeddings are the ones behind the paper's VenusX results. They cover 1,732 / 2,028 / |
| 12,723 / 2,358 proteins of Act / BindI / Evo / Motif. The other 84 proteins have AlphaFold2 |
| structures with residues past the end of their VenusX site annotation, and the paper's embedding |
| build skipped them. The code leaves them out of every split, which gives the paper's test sets of |
| 186 / 203 / 1,291 / 249 samples. The embeddings take 33.0 GB: 11.0 GB for ESM2-T30 and 22.0 GB for |
| SaProt-650M, stored as float16. |
|
|
| ``` |
| <task>_proteinshake/ |
| pdb.tar.gz pdb/<pdb_id>.pdb |
| labels.csv, token_maps.json EC-L3 |
| targets.jsonl, token_map.json Pfam, GO-MF, SCOP-FAM, SCOP-SF |
| sequence/{train,val,test}_split.csv |
| structure/{train,val,test}_split.csv |
| venusx_site_fragment/<target>/MF50/ |
| pdb.tar.gz pdb/<uniprot_id>.pdb |
| samples.csv one row per protein and InterPro site |
| {train,val,test}_split.csv |
| token_maps.json, metadata.json |
| esm2_static_cache_mmap/ ESM2-T30 embeddings: embeddings.bin, meta.pt |
| saprot_static_cache_mmap/ SaProt-650M embeddings: embeddings.bin, meta.pt |
| ``` |
|
|
| `embeddings.bin` stacks the per-residue embeddings of all proteins. `meta.pt` holds the protein |
| names and row offsets and loads with `torch.load(..., weights_only=True)`. |
|
|
| The download is 38.2 GB, of which 33.0 GB are the VenusX embeddings. The structures unpack to |
| 23.6 GB. `SHA256SUMS` lists a checksum for every file (`sha256sum -c SHA256SUMS`). |
|
|
| ## Usage |
|
|
| Download the repository as the code's `data/` folder and unpack the structures: |
|
|
| ```bash |
| hf download xwang112358/BioBlobs-data --repo-type dataset --local-dir data |
| # To skip the 33 GB of VenusX embeddings, add --exclude "*_static_cache_mmap/*" |
| for f in data/*_proteinshake/pdb.tar.gz data/venusx_site_fragment/*/MF50/pdb.tar.gz; do |
| tar -xzf "$f" -C "$(dirname "$f")" |
| done |
| ``` |
|
|
| Then follow `docs/REPRODUCE.md` in the code repository. The data-preparation scripts find the |
| unpacked files, skip the download and parse the structures. For ProteinShake, then build the |
| ESM2-T30 or SaProt-650M residue embeddings with `preprocessing/prepare_plm_cache.py`. SaProt also |
| needs Foldseek, which reads the PDB files. VenusX training reads the downloaded embeddings, so skip |
| this step for VenusX. |
|
|
| ## Licenses |
|
|
| - ProteinShake files (`*_proteinshake/`): CC-BY-4.0, as released by ProteinShake. ProteinShake |
| builds these tasks from RCSB PDB structures and their annotations. Its documentation lists the |
| source of each task. |
| - VenusX files (`venusx_site_fragment/`): Apache-2.0, as released by VenusX |
| (`AI4Protein/VenusX_Res_*_MF50` and `AI4Protein/VenusX_*_AlphaFold2_PDB`). The site annotations |
| come from InterPro, and the structures are AlphaFold DB models (CC-BY-4.0). |
| - VenusX embeddings (`venusx_site_fragment/*/MF50/*_static_cache_mmap/`): Apache-2.0, like the |
| VenusX files they are computed from. They are outputs of ESM2-T30 and SaProt-650M, both released |
| under the MIT License. |
|
|
| ## Citation |
|
|
| If you use this data, please cite BioBlobs and the original datasets. |
|
|
| ```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} |
| } |
| ``` |
|
|
| Also cite ProteinShake (Kucera et al., NeurIPS 2023 Datasets and Benchmarks), VenusX |
| (Tan et al., 2025), InterPro and AlphaFold DB. If you use the VenusX embeddings, also cite ESM2 |
| (Lin et al., Science 2023) and SaProt (Su et al., ICLR 2024). |
|
|
