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Bump deeprank-gnn-esm from 1.1.0 to 2.0.0 - #1676

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Bump deeprank-gnn-esm from 1.1.0 to 2.0.0#1676
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Bumps deeprank-gnn-esm from 1.1.0 to 2.0.0.

Release notes

Sourced from deeprank-gnn-esm's releases.

v2.0.0 — Embedding generation pipeline refactor

[!NOTE]
This release note was AI-generated

Refactors the prediction pipeline to support heterogeneous, multi-chain, multi-model input instead of a fixed 2-chain complex. This is a breaking release.

Breaking changes

  • CLI signature changed. Chain IDs and core count are no longer positional arguments; chain pairing is now automatic.

    # before (1.x)
    deeprank-gnn-esm-predict 1B6C.pdb A B 1
    after (2.0)
    deeprank-gnn-esm-predict 1B6C.pdb --num_cores 1

    pdb_files now accepts one or more paths. Every chain pair in every input model is scored automatically — a 3-chain complex yields 3 pairwise predictions (A-B, A-C, B-C); an ensemble of N models yields predictions for every model.

  • Console entry point moved. deeprank-gnn-esm-predict now resolves to deeprank_gnn.main:main (was deeprank_gnn.predict:main). Anything importing deeprank_gnn.predict.main directly will break.

  • Output layout changed. Previously all intermediate files (renumbered PDB, fasta, embeddings, graph/prediction hdf5) were written to a permanent {pdb}-gnn_esm_pred_{chain_i}_{chain_j}/ directory in the CWD. Now they're written to a temporary directory that's deleted after the run; only the final GNN_esm_prediction.csv is copied back to the CWD. Pass --output-dir to keep intermediates around (new flag).

  • CSV output schema changed. Output is now pdb_id,chain_i,chain_j,predicted_fnat with one row per chain pair per input (previously implied a single pair per run). A new sibling file, <output>_summary.csv (pdb_id,combined_fnat), sums predicted fnat across all pairs of each model.

  • Library API changed — anyone importing deeprank_gnn.predict directly, not just the CLI:

    • Removed: renumber_pdb, three_to_one, pdb_to_fasta, process_batch, get_model_output, get_embedding, split_input_pdb (replaced by deeprank_gnn.input.PDBInput and deeprank_gnn.sequence.MultiFasta/Sequence).
    • setup_workspace(identificator: str)setup_workspace(output_dir: Optional[Path] = None).
    • parse_output(csv_output, workspace_path, chain_ids)parse_output(csv_output, pair_info: dict[str, tuple[str, str, str]]).
  • Input constraint added. When scoring multiple PDB files in one invocation, each input file must have a unique filename stem — the CLI now errors out otherwise.

New

  • --output-dir flag to persist intermediate files for inspection.
  • Multi-PDB / multi-model ensemble scoring in a single invocation, with embeddings deduplicated and batched once across all inputs.
  • <output>_summary.csv — combined predicted fnat per model, summed across its chain pairs.
  • e2e pytest marker for full-pipeline tests (downloads/loads the ESM model).

Migration

  • Drop the chain_id_1 chain_id_2 num_cores positional args; use --num_cores (optional, default 1) and pass PDB path(s) only — pairs are inferred.
  • If you relied on the old output directory sticking around, pass --output-dir <dir>.
  • If you parsed the CSV expecting exactly one row, update to handle one row per chain pair.
  • If you imported helper functions from deeprank_gnn.predict, switch to deeprank_gnn.input/deeprank_gnn.sequence equivalents.

version bumped 1.1.02.0.0 (pyproject.toml) accordingly.

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Bumps [deeprank-gnn-esm](https://github.com/haddocking/deeprank-gnn-esm) from 1.1.0 to 2.0.0.
- [Release notes](https://github.com/haddocking/deeprank-gnn-esm/releases)
- [Commits](haddocking/deeprank-gnn-esm@v1.1.0...v2.0.0)

---
updated-dependencies:
- dependency-name: deeprank-gnn-esm
  dependency-version: 2.0.0
  dependency-type: direct:development
  update-type: version-update:semver-major
...

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@dependabot dependabot Bot added dependencies Pull requests that update a dependency file python Pull requests that update python code labels Sep 1, 2026
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