| # Structures for the GPBridge expanded-GO dataset |
|
|
| One structure per sequence for **322,992 sequences**, assembled from three |
| sources. They are meant to be used together, so the first thing to read is |
| `structure_index.tsv`: it resolves any `seq_id` to a file, whichever source |
| provides it. |
|
|
| Sequence ids are `seq_<sha256(sequence)[:20]>`, so an id always identifies an |
| exact sequence. |
|
|
| ## Coverage |
|
|
| | Source | Sequences | What it is | |
| |---|---:|---| |
| | `gpbridge/afdb/` | 304,787 | AlphaFold DB, **AlphaFold 2**, model v6 | |
| | `gpbridge/pdb/` | 11,495 | experimental structures from RCSB | |
| | `predictions/missing_pdb_afdb/` | 6,540 | **AlphaFold 3**, predicted here | |
| | no structure | 11,075 | neither source has one | |
|
|
| 10,904 sequences have both an AFDB model and a PDB entry — the index exposes |
| both so you can choose per use case. |
|
|
| **These come from three different methods.** AF2, AF3 and experiment are not |
| interchangeable, and the split is not random: see *Provenance* below before |
| training on the union. |
|
|
| ## Resolve a sequence to a file |
|
|
| `structure_index.tsv` — one row per sequence, all sources on the same row: |
|
|
| ``` |
| seq_id length split best af3_archive afdb_archive afdb_file |
| pdb_archive pdb_file pdb_all_ids note |
| ``` |
|
|
| `best` is a suggested default, not a judgement: `af3` where one was predicted, |
| otherwise `afdb`, otherwise `pdb`. That ordering follows the source bundle's own |
| guidance — AFDB is the workhorse, while a PDB hit may be a construct, a single |
| domain, or one chain of a complex and is not guaranteed to cover the full |
| sequence. For experimental ground truth, prefer `pdb_archive` explicitly. |
|
|
| ```python |
| import csv, io, json, tarfile, zstandard |
| from huggingface_hub import hf_hub_download |
| REPO = "tonynzh2/afdb" |
| |
| idx = {r["seq_id"]: r for r in csv.DictReader( |
| open(hf_hub_download(REPO, "structure_index.tsv", repo_type="dataset")), |
| delimiter="\t")} |
| |
| def structure(seq_id, prefer=None): |
| """Returns (source, text). prefer='pdb' to force experimental when present.""" |
| r = idx[seq_id] |
| order = [prefer] if prefer else [] |
| order += ["af3", "afdb", "pdb"] |
| for src in order: |
| if src == "af3" and r["af3_archive"]: |
| return "af3", _from_zst(r["af3_archive"], seq_id) |
| if src == "afdb" and r["afdb_archive"]: |
| return "afdb", _from_tar(r["afdb_archive"], r["afdb_file"], gz=True) |
| if src == "pdb" and r["pdb_archive"]: |
| return "pdb", _from_tar(r["pdb_archive"], r["pdb_file"], gz=True) |
| return "none", None |
| |
| def _from_tar(archive, member, gz=False): |
| import gzip |
| path = hf_hub_download(REPO, archive, repo_type="dataset") |
| with tarfile.open(path) as tar: # plain tar, members are .gz |
| raw = tar.extractfile(member).read() |
| return gzip.decompress(raw).decode() if gz else raw.decode() |
| |
| def _from_zst(archive, seq_id): |
| path = hf_hub_download(REPO, archive, repo_type="dataset") |
| with open(path, "rb") as fh: |
| stream = zstandard.ZstdDecompressor().stream_reader(fh) |
| with tarfile.open(fileobj=stream, mode="r|") as tar: |
| for m in tar: |
| if m.isfile() and m.name == f"{seq_id}/{seq_id}_model.cif": |
| return tar.extractfile(m).read().decode() |
| return None |
| ``` |
|
|
| The AFDB and PDB archives are plain `.tar` holding already-gzipped `.cif.gz` |
| members; the AF3 archives are `.tar.zst` holding whole output directories. Both |
| are bundled by shard because 350,000+ loose objects would make the repo |
| unusable. |
|
|
| ## Provenance — read before combining |
|
|
| The three sources differ in method, and **which source a sequence gets is not |
| random**: |
|
|
| - Reconstructed ancestral sequences have no UniProt accession, so they can never |
| have an AFDB model. They are predicted or nothing. |
| - Well-studied proteins are the ones with PDB entries. |
| - The 6,540 AF3 predictions are, by construction, the sequences with *neither* a |
| PDB entry nor an AFDB model — i.e. the thinnest-homology corner of the dataset. |
|
|
| So source correlates with sequence properties. If a model trained on the union |
| behaves differently on AF2-labelled versus AF3-labelled sequences, that is |
| confounded with those properties and not attributable to the structures alone. |
| Record which source each label came from — the index's `best` column does this — |
| and check it as a covariate rather than assuming exchangeability. |
|
|
| Version details worth recording: AFDB files are **model v6** (not the v4 many |
| papers cite), and the AF3 predictions use v3.0.4 with stock settings, seed |
| 20260916, 5 diffusion samples, 10 recycles, full 4-database MSA and template |
| search. Per-shard details are in `predictions/missing_pdb_afdb/README.md`. |
|
|
| ## Known gaps |
|
|
| | Issue | Count | Handling | |
| |---|---:|---| |
| | AFDB accession linked but **no model exists** at any version | 1,508 | in `gpbridge/afdb_no_model_needs_af3.fasta`; not in any fetch list and not in `missing_pdb_afdb_training.fasta` either — they need prediction | |
| | PDB entries **withdrawn** by RCSB | 7 | fetched into `gpbridge/pdb_obsolete/`, flagged in the index's `note` | |
| | No structure from any source | 11,075 | `best = none` | |
|
|
| The 1,508 are worth emphasising: the source bundle's coverage table counts them |
| as having an AlphaFold DB model. They do not — they are live UniProt entries of |
| ordinary length returning 404 on both v6 and v4. Nothing in the original |
| pipeline covered them. |
|
|
| ## Not part of this dataset |
|
|
| The repository also holds `predictions/00001_00256/` and |
| `predictions/00257_00512/`. These are **a different dataset** - the GO + ASR |
| catalog (292,804 sequences: Gene Ontology couplings and ancestral sequence |
| reconstructions), predicted with the same stock AlphaFold 3 settings but |
| unrelated to the GPBridge expanded-GO set documented here. |
|
|
| They are deliberately absent from `structure_index.tsv`, which covers only the |
| 322,992 GPBridge sequences. Do not join them by `seq_id` and assume membership: |
| both datasets use `seq_<sha256(sequence)[:20]>` ids, so an id collision means |
| the two sets genuinely share that exact sequence, not that the row belongs here. |
| That campaign is partially complete and its shards are named by length band. |
|
|
| ## Layout |
|
|
| ``` |
| structure_index.tsv every sequence -> its file(s) |
| gpbridge/join.tsv.gz original join table from the source bundle |
| gpbridge/coverage.csv source bundle's coverage, all 13 populations |
| gpbridge/BUNDLE_README.md source bundle's own documentation |
| gpbridge/afdb/<2-char>.tar 211 archives, AF2 model v6 |
| gpbridge/pdb/<2-char>.tar 1,088 archives, experimental |
| gpbridge/pdb_obsolete/ 7 withdrawn entries |
| gpbridge/afdb_no_model.tsv the 1,508, with their 404s |
| gpbridge/afdb_no_model_needs_af3.fasta their sequences |
| predictions/missing_pdb_afdb/ AF3 output + its own README and index |
| predictions/00001_00256/ GO+ASR catalog - a DIFFERENT dataset |
| predictions/00257_00512/ GO+ASR catalog - a DIFFERENT dataset |
| ``` |
|
|
| ### Completeness |
|
|
| `predictions/missing_pdb_afdb/` is **still being produced**: 6 of 14 archives |
| are published at the time of writing. `structure_index.tsv` lists all 6,540 of |
| those sequences regardless, because the index describes the dataset, not the |
| current upload state. Check which archives exist before assuming a sequence is |
| retrievable: |
|
|
| ```python |
| from huggingface_hub import HfApi |
| have = {x.rfilename for x in HfApi().repo_info("tonynzh2/afdb", |
| repo_type="dataset").siblings} |
| missing = {s: r for s, r in idx.items() |
| if r["af3_archive"] and r["af3_archive"] not in have} |
| ``` |
|
|
| The AFDB and PDB portions are complete: 211 and 1,088 archives respectively. |
|
|
| ## Terms of use |
|
|
| AlphaFold 3 output in `predictions/` is subject to the |
| [AlphaFold 3 Output Terms of Use](OUTPUT_TERMS_OF_USE.md) — non-commercial, and |
| redistribution must carry the terms. AlphaFold DB structures are CC-BY-4.0 from |
| EMBL-EBI. PDB entries are in the public domain. |
|
|
| Cite AlphaFold 3: Abramson, J. et al. *Nature* **630**, 493–500 (2024). |
| Cite AlphaFold DB: Varadi, M. et al. *Nucleic Acids Research* (2024). |
|
|
