pancreatic-lipase-pro-docking

Deterministic Vina screening against human pancreatic lipase. Scores come from Vina, never from a language model.

Rule 0 — do not invent numbers

Report only scores that appear in a generated CSV. If a tool did not run, say so. No estimated affinities, no remembered values, no "typical" numbers. Every claim traces to dock_results/results_all_sites.csv or it is not made.

If vina is missing, the run fails loudly — that is intended. Do not substitute a guess and do not describe a dry run as if it were docking.

Decide the route first

Run command -v vina micromamba conda first, then:

Local run

# 0. env (once). Python must be <=3.11.
micromamba create -p plenv -c conda-forge python=3.11 rdkit meeko vina gemmi openbabel pytest
export PATH="$PWD/plenv/bin:$PATH"

# 1. preflight — MUST print RESULT: OK before docking
python docking_professional_stack/multi_site_docking.py --check

# 2. dock (ligands.csv needs columns: name,smiles)
python docking_professional_stack/multi_site_docking.py \
  --ligands ligands.csv --precision balanced --workers 4 --outdir dock_results

# 3. gate the output — non-zero exit means do not report the numbers
python docking_professional_stack/validate_results.py \
  --results dock_results/results_all_sites.csv

Tiers: fast = ex4/1 seed (triage) · balanced = ex8/1 (default) · max = ex24/3 seeds + consensus (publication).

Read dock_results/results_all_sites.csv — one row per (ligand, site): score is the best affinity in kcal/mol (more negative = better); treat unstable(sd>0.5) rows as unranked.

The 5 sites

catalytic_triad (Ser152-Asp176-His263) · oxyanion_hole (backbone N of Phe77+Leu153) · lid (~239-259) · hydrophobic_pocket (hydrophobes ≤8 Å of Ser152-OG) · colipase_interface (41 cross-chain contacts ≤5 Å).

Centres are computed from the real coordinates at run time. Quote catalytic_triad for inhibitor ranking unless asked otherwise.

Trust the numbers before reporting them

# protocol gate: re-dock the co-crystallized MUP inhibitor (run once per receptor change)
python docking_professional_stack/validate_native.py        # PASS <=2 A, WARN <=3 A

# drift gate: docks ibuprofen+caffeine and compares against calibration/baseline.json
python scripts/selfcheck.py run --python plenv/bin/python   # exit 0 = calibrated, exit 1 = DRIFT

validate_native.py: RMSD ≤2 Å PASS · ≤3 Å WARN (proceed, disclose it) · >3 Å FAIL — stop, do not dock, do not report scores. The protocol is wrong.

selfcheck.py run performs the anchor check for you; you do not dock the controls by hand. Exit 1 means do not publish until the drift is explained. Its stored anchors at the catalytic site: ibuprofen −7.3 to −7.5, caffeine −6.6 to −6.8 kcal/mol.

Vina's own reproducibility band is ~0.5 kcal/mol. Differences smaller than that between two ligands are not a ranking. Say so instead of ranking noise.

Interpreting honestly

• Coarse filter, not binding free energies: rank order within a congeneric series is meaningful, absolute numbers are not. No score proves inhibition.
• Ser152 is a nucleophilic serine — covalent/mechanism-based inhibitors (e.g. orlistat's real mechanism) are not modelled by Vina. Say so.

What this skill does to the machine

Declared up front so nothing below is a surprise.

Not used: no sudo, no system package manager, no writes outside the working directory, no credentials read except the Kaggle token you point at, no telemetry.

Everything else

Authorized research and education only.