Junior B.
817bcda7dc
Start the structure-based binding branch (PLAN §12), baseline-first. - src/binding.py: validated RDKit ligand retrieval (morgan_fp, tanimoto, retrieve_nearest = the §12.9 engine) + dock() stub documenting the blocked ARM-Mac toolchain - scripts/binding_ligand_baseline.py: 300 drugs vs known binders - docs/structure_binding_notes.md: status, toolchain blocker, next steps - pyproject: [structure] extra (rdkit); data/raw/structures/ for PDBs Step-0 finding: retrieval engine VALIDATED on in-set classes (decitabine->azacitidine 0.62; vorinostat->scriptaid/belinostat) but the distinctive binders voxelotor/mitapivat have no analog in our 300-drug set (Tanimoto ~0.2). Needs (a) bigger library, (b) real docking (§12.3), which is blocked on the ARM-Mac docking toolchain (§12.6 pitfall 4). Structures 5E83 (Hb+voxelotor) and 8XFD (PKR+mitapivat) fetched. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
35 lines
1.9 KiB
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35 lines
1.9 KiB
Markdown
# Structure-based binding track — working notes
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Branch `structure-based-binding`. Implements PLAN §12. Baseline-first, start with the two cleanest
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targets (Hemoglobin + PKR), de-risk the harness before scaling.
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## Status (2026-06-23)
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**Toolchain check (PLAN §12.6 pitfall 4, confirmed real):**
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- ✅ RDKit installs on ARM Mac — ligand side ready.
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- ❌ AutoDock Vina does NOT pip-install on ARM Mac; no docking binary available. Docking (§12.3)
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is **blocked on toolchain** — must resolve via conda/micromamba (`vina`/`smina`), a GPU AF3-class
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model (Boltz-2/Chai-1/DiffDock), or an x86 Vina binary under Rosetta.
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**Structures obtained:** `5E83` (hemoglobin + voxelotor), `8XFD` (PKR + mitapivat) in
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`data/raw/structures/`.
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**Step 0 — ligand-based retrieval baseline (`scripts/binding_ligand_baseline.py`):**
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RDKit Tanimoto of our 300 drugs vs known sickle binders.
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- Engine VALIDATED on in-set classes: `decitabine`→azacitidine (0.62); `vorinostat`→scriptaid
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(0.42), belinostat (0.28). Correctly clusters DNMT1 / HDAC HbF-inducers.
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- But voxelotor / mitapivat have **no analog** in our set (max Tanimoto ~0.20–0.26). A 300-drug
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library is too sparse to contain look-alikes of distinctive scaffolds.
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**Takeaways:**
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1. Ligand retrieval works but needs a **bigger drug library** to be useful for distinctive targets.
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2. The targets without in-set analogs (Hb, PKR) need **actual docking** (§12.3) — which scores
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binding directly, no look-alike required. That is the gating next step, and it needs the
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toolchain solved.
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## Next steps
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- [ ] Resolve the docking toolchain (recommend: micromamba + smina/vina, CPU, no GPU needed for baseline).
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- [ ] Dock the known binders (voxelotor→5E83, mitapivat→8XFD) as positive controls (§12.4 recovery test).
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- [ ] Expand the ligand library (full ChEMBL/LINCS) for retrieval to have reach.
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- [ ] Only then: AF3-class co-folding (Boltz-2/DiffDock) vs the docking baseline; and §12.9 generative beacon.
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