--- 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/ ``` ## 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/ \ 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 , 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)