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### Germinal Antibody Design (`germinal-design`) Runs one complete Germinal antibody-design campaign against a single target. Given a target PDB, a target chain, and the epitope hotspot residues, it runs a fixed (version-pinned) copy of the upstream `run_germinal.py` script, repeating hallucination, then AbMPNN redesign, then structure validation and filtering until either `max_trajectories` or `max_passing_designs` is reached, and returns ranked designs with predicted complex structures and per-design metrics (interface pTM, pAE, pDockQ2, pLDDT, and others). Upstream configuration defaults are preserved exactly; the only change is setting the structure-validation model (`structure_model`) to Chai-1, because Chai-1 installs automatically. #### API Reference

Source Target structure. Accepts a file path, raw PDB/CIF content string, `Structure` object, or a dict in the shape produced by `Structure.model_dump(mode='json')`. Must include a chain matching `target_chain`. Raw structure content in PDB or CIF format. Format of the content string (auto-detected if omitted). What the B-factor column represents. Optional source identifier (filepath or tool name). Associated metrics (e.g., pLDDT, pTM scores, per-chain lists, pairwise matrices). None values are stripped at construction. Chain ID(s) of the target. Single letter (e.g. `"A"`) or comma-separated for multi-chain targets (e.g. `"A,B"`). Chain ID assigned to the designed binder. Default `"B"` (matches Germinal's source convention in `configs/target/pdl1.yaml`). Hotspot residues on the target in `""` format (e.g. `["A37", "A39", "A41"]`). These are the residues the designed binder is forced to contact. Short identifier for this target. Used as the Hydra `target=` selector and as a prefix in output filenames. If `None`, the inference layer derives one from a hash of the PDB content. Optional single residue (e.g. `"W40"`) used as the Chai-1 contact-restraint anchor. Mirrors Germinal's `hotspot_residue` field in `configs/target/*.yaml`.

Source Run preset selector. Available options: `vhh`, `scfv` Hard cap on total trajectories before stopping. Cap on trajectories that complete the hallucination stage (before MPNN refinement). Stop early once this many designs pass all final filters. Cofolding backend for structure validation. Default `"chai"` (auto-installed); `"af3"` and `"protenix"` require user-provisioned weights/env (see README → Backend Configuration). Available options: `chai`, `af3`, `protenix` Override final `external_plddt` (VHH: `> 0.87`, scFv: `> 0.85`). Distinct from upstream's in-loop `plddt_threshold` save filter — use `germinal_overrides`. Override final `external_iptm` (preset: `> 0.74`). Override final `external_pae` in Å (VHH: `< 7.5`, scFv: `< 8`). Override final `external_ptm` (preset: `> 0.84`). Override final `pdockq2` (preset: `> 0.23`). Arbitrary Hydra overrides for `run_germinal.py` (e.g. `{"logits_steps": 100, "weights_iptm": 1.0}`). Applied verbatim as `=` CLI args. Override filter YAML values. Schema: `{"initial" | "final": {: {"value": , "operator": }}}`. Merged on top of the design\_type preset. Optional persistent output directory. If unset, a temp dir is used and discarded after the call. Verbosity level (0=quiet, 1=info, 2=debug, 3=raw subprocess stderr). `True` is coerced to `1` and `False` to `0`. Device for the Germinal subprocess. Requires `"cuda"` (CPU is unsupported). Maximum execution time in seconds. `None` waits indefinitely. Random seed. When set, tools run reproducibly up to small GPU float noise (see `BaseToolOutput.approx_equal`), and the seed participates in cache keys. When None, cacheable seed-sensitive tools skip cache until seeded.

Source All produced designs across the `accepted`, `redesign_candidate`, and `trajectory` stages. Heavy chain (or VHH) amino-acid sequence. Light chain sequence (scFv only). Predicted binder + target complex. Per-design quality metrics. Highest pipeline stage this design reached. Germinal's internal design identifier (`"__s"` for trajectory-only designs, `"__s_abmpnn_"` after AbMPNN redesign). Trajectory seed (parsed from `_s`). Germinal uses the seed as its unique trajectory identifier. AbMPNN sample index (1-based; 0 for trajectory-only designs that never reached the redesign stage). Per-stage counts from Germinal's `failure_counts.csv` (trajectories attempted, designs accepted, and per-filter failure counts). **Metrics** | Metric | Type | Range | Availability | | ----------------------------------------- | ----- | ---------- | ---------------- | | `plddt` | float | 0.0 to 1.0 | always | | `ptm` | float | 0.0 to 1.0 | always | | `i_ptm` | float | 0.0 to 1.0 | always | | `i_pae` | float | ≥ 0.0 | always | | `pae` | float | ≥ 0.0 | always | | `loss` | float | unbounded | always | | `lm_ll` | float | unbounded | always | | `helix` | float | unbounded | always | | `beta_strand` | float | unbounded | always | | `clashes` | int | ≥ 0.0 | after filtering | | `sc_rmsd` | float | ≥ 0.0 | after filtering | | `binder_near_hotspot` | bool | unbounded | after filtering | | `cdr3_hotspot_contacts` | int | ≥ 0.0 | after filtering | | `percent_interface_cdr` | float | 0.0 to 1.0 | after filtering | | `interface_shape_comp` | float | 0.0 to 1.0 | after filtering | | `interface_hbonds` | int | ≥ 0.0 | after filtering | | `surface_hydrophobicity` | float | 0.0 to 1.0 | after filtering | | `interface_hydrophobicity` | float | ≥ 0.0 | after filtering | | `pdockq2` | float | 0.0 to 1.0 | after filtering | | `external_plddt` | float | 0.0 to 1.0 | after validation | | `external_iptm` | float | 0.0 to 1.0 | after validation | | `external_ptm` | float | 0.0 to 1.0 | after validation | | `external_pae` | float | ≥ 0.0 | after validation | | `external_i_pae` | float | ≥ 0.0 | after validation | | `external_i_plddt` | float | 0.0 to 1.0 | after validation | | `external_plddt_binder` | float | 0.0 to 1.0 | after validation | | `external_chain_ptm` | float | 0.0 to 1.0 | after validation | | `external_binder_pae` | float | ≥ 0.0 | after validation | | `external_aggregate_score` | float | unbounded | after validation | | `ipsae` | float | 0.0 to 1.0 | after validation | | `ipsae_pdockq2` | float | 0.0 to 1.0 | after validation | | `lis_lis` | float | unbounded | after validation | | `lis_lia` | float | unbounded | after validation | | `binder_score` | float | unbounded | after filtering | | `interface_packstat` | float | 0.0 to 1.0 | after filtering | | `interface_dG` | float | unbounded | after filtering | | `interface_dSASA` | float | ≥ 0.0 | after filtering | | `interface_dG_SASA_ratio` | float | unbounded | after filtering | | `interface_fraction` | float | 0.0 to 1.0 | after filtering | | `interface_nres` | int | ≥ 0.0 | after filtering | | `interface_hbond_percentage` | float | 0.0 to 1.0 | after filtering | | `interface_delta_unsat_hbonds` | int | ≥ 0.0 | after filtering | | `interface_delta_unsat_hbonds_percentage` | float | 0.0 to 1.0 | after filtering | | `clashes_unrelaxed` | int | ≥ 0.0 | after filtering | | `hydrophobic_patches_binder` | int | ≥ 0.0 | after filtering | | `hydrophobic_patches_struct` | int | ≥ 0.0 | after filtering | | `sap_score` | float | unbounded | after filtering | | `cdr_sap` | float | unbounded | after filtering | | `cdr_hotspot_contacts` | int | ≥ 0.0 | after filtering | | `percent_interface_cdr3` | float | 0.0 to 1.0 | after filtering | | `alpha_interface` | float | 0.0 to 1.0 | after filtering | | `beta_interface` | float | 0.0 to 1.0 | after filtering | | `loops_interface` | float | 0.0 to 1.0 | after filtering | | `alpha_all` | float | 0.0 to 1.0 | after filtering | | `beta_all` | float | 0.0 to 1.0 | after filtering | | `loops_all` | float | 0.0 to 1.0 | after filtering | | `n_framework_mutations` | int | ≥ 0.0 | after filtering |

#### Applications This tool performs de novo therapeutic antibody discovery: generating epitope-targeted VHH or scFv binders against a chosen target. It requires only a target structure and an epitope definition, and produces a ranked set of designs with predicted complex structures and per-design quality metrics, ready for selection and experimental testing. #### Usage Tips * **`design_type` selects the run preset.** `"vhh"` (single-domain nanobody, the default) or `"scfv"`; each loads the upstream preset with different filter thresholds, so leave the `*_threshold` fields set to `None` to let the correct preset apply. * **Reduce `max_trajectories` when testing.** The upstream default of `10000` corresponds to a run that takes hours to days; use a small value while testing, and set `max_passing_designs` below `max_trajectories` to stop early once enough designs pass the filters. * **`structure_model` selects the structure-validation model.** Validation uses a model independent of the hallucination step. The published filter thresholds were calibrated against AlphaFold3, so acceptance rates may differ under the `"chai"` default and the `*_threshold` fields may need adjusting to match the reported rates. * **`germinal_overrides` passes additional settings to the underlying pipeline.** Any upstream configuration option that is not exposed as a dedicated field can be supplied here as a `=` pair.