Complexa Evaluate-PDBs Skill

Score a directory of pre-existing PDB files against the same metrics Proteina-Complexa uses internally. Wraps complexa analysis <evaluate_config> ++sample_storage_path=<dir>: the CLI runs the evaluate step (refold + interface metrics + monomer metrics) and then the analyze step (success thresholds, diversity, pass-rate CSVs). Do not run complexa generate here, the inputs already exist.

What this skill enables

• Re-fold a directory of designed PDBs with AF2 (colabdesign), RF3 (rf3_latest), ESMFold (esmfold), or Boltz2 (boltz2_default).
• Compute binder interface metrics: i_pAE, min_ipAE, i_pTM, pLDDT, binder/complex scRMSD.
• Compute monomer designability (ProteinMPNN-redesigned scRMSD) and codesignability (original sequence refold scRMSD).
• For motif inputs: motif RMSD (CA + all-atom), motif-region designability/codesignability, sequence recovery.
• Aggregate into per-PDB CSVs plus pass-rate summaries using the default thresholds for the result_type.

Step 1: Pre-flight

Always check GPU / disk / tool binaries before launching a refold job. RF3 and ColabDesign-AF2 are large.

bash scripts/preflight.sh

Surface from preflight.json:

• gpu.available and gpu.vram_gb, colabdesign/RF3 need ≥40 GB; ESMFold tolerates ≥24 GB.
• env.missing_required, must include the keys for the chosen folding backend:
  • colabdesign → AF2_DIR
  • rf3_latest → RF3_CKPT_PATH, RF3_EXEC_PATH
  • esmfold → ESMFold weights resolvable
• tools.{foldseek,mmseqs}, required by aggregation.compute_diversity / compute_mmseqs_diversity (both default true).

If any required key is missing, route the user to the complexa-setup skill.

Step 2: Identify the design type