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EdwardNSeven
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sharp-data

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biology
protein
cath
tm-vec
igem
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sharp-data
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---
license: cc-by-4.0
pretty_name: S(H)ARP reference data
tags:
- biology
- protein
- cath
- tm-vec
- igem
---

# S(H)ARP reference data

Reference data for [S(H)ARP](https://gitlab.igem.org/2026/software/usp-brazil/sharp)
(*Streptomyces* Hidden Antibiotic Regulated Pathways), iGEM USP-Brazil 2026.
The S(H)ARP repository does not ship these files; its `scripts/fetch_data.sh`
and its Colab notebook download them.

| File | Contents |
|---|---|
| `sharp-tmvec-cath-v1.0.tar.gz` | TM-Vec 2s index of the CATH S95 v4.4.0 domains, unpacks to `sharp/data/tmvec_indexes/cath_s95.*` |
| `sharp-tmvec-cath-v1.0.tar.gz.sha256` | its SHA-256 checksum |

## Versions

Each change to this repository is a commit. Use a URL pinned to a commit, not
to `main`: it always serves the same files, and the commit's date shows when
they were uploaded.

```
https://huggingface.co/datasets/EdwardNSeven/sharp-data/resolve/<commit>
```

## Use

In the S(H)ARP Colab notebook, set `TMVEC_INDEX_SOURCE` in *Advanced
parameters* to the URL above. With a local install:

```bash
SHARP_DATA_SOURCE=https://huggingface.co/datasets/EdwardNSeven/sharp-data/resolve/<commit> \
    scripts/fetch_data.sh --tmvec-only
```

Both check the archive against its `.sha256` before unpacking it.

## How the index was made

- Sequences: `cath-domain-seqs-S95-v4_4_0.fa` from
  <https://download.cathdb.info/cath/releases/all-releases/v4_4_0/sequence-data/>,
  73,535 domains (SHA-256 `f93265164dc65340feebfbbffb711fe32bf326037c2bb8422f9fa432e2637387`).
- Model: the TM-Vec 2s student model, `tmvec2_student.pt`
  (SHA-256 `fa79c537849f882a805cd583dd1022ed6c927aae55ab8ba80e89b6ad6f1ea76f`), from
  [tmvec-bench](https://github.com/paarth-b/tmvec-bench).
- Command: `tmvec2s-search build` from S(H)ARP's `sharp/tmvec2s_search.py`,
  with sequences over 600 residues split into overlapping windows and pooled
  (`--long pool --overlap 200`). One 512-dimension float32 vector per domain.

The S(H)ARP Colab notebook can also rebuild the index from the same sequences
(`TMVEC_INDEX_SOURCE = build`).

## License and citation

The index is derived from CATH, which is licensed under the
[Creative Commons Attribution 4.0 International License](https://creativecommons.org/licenses/by/4.0/).

- CATH: Waman, V. P., et al. (2025). CATH v4.4: major expansion of CATH by
  experimental and predicted structural data. *Nucleic Acids Research*,
  53(D1), D348–D355. [doi:10.1093/nar/gkae1087](https://doi.org/10.1093/nar/gkae1087)
- TM-Vec 2s: Keluskar, A., Batra, P., Bezshapkin, V., Morton, J. T., &
  Zhu, Q. (2026). TM-Vec 2s: Accelerated Protein Remote Homology
  Detection. *bioRxiv*. [doi:10.64898/2026.02.05.704073](https://doi.org/10.64898/2026.02.05.704073)
- TM-Vec: Hamamsy, T., et al. (2024). Protein remote homology detection
  and structural alignment using deep learning. *Nature Biotechnology*,
  42(6), 975–985. [doi:10.1038/s41587-023-01917-2](https://doi.org/10.1038/s41587-023-01917-2)