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Simulation Benchmark Report

Phase 3 Closeout

Phase 3 (virtual assay scaffolding, Loops 30–39) built two simulation modules, three benchmarks, a weighted-mode gate, a CLI flag, and an external adapter protocol. Simulation does not improve ranking. The honest finding across all benchmarks: simulation does not improve ranking.

Current verdict: simulation remains informational only. Weighted mode is blocked by the gate and will remain blocked until a future module demonstrably beats its cheapest heuristic baseline.

weighted simulation remains blocked.


What Was Built

Loop Module Status
30 Virtual assay scope document ✅ Scope defined
31 MembraneProxy (Wimley-White scales) ✅ Ships in info mode
32 StructureProxy (Chou-Fasman 3-state) ✅ Ships in info mode
33 AMP-vs-decoy ablation benchmark ✅ No improvement
34 Within-AMP hemolysis ablation ✅ No improvement
35 Weighted-mode simulation gate ✅ Blocks weighted mode
36 Cheap-baseline comparison benchmark ✅ 0/4 signals beat baselines
37 rank --simulation-mode CLI flag ✅ Users can inspect scores
38 ExternalSimulationAdapter protocol ✅ Third-party integration ready
39 This report ✅ Phase 3 closed

Phase 3 Exit Criteria

Criterion Required Status Evidence
≥2 simulation modules exist and are benchmarked ✅ ✅ Met MembraneProxy (Loop 31), StructureProxy (Loop 32). Both benchmarked (Loops 33–36)
Simulation improves strict triage by >0.03 AUROC on any pairwise metric Delta > 0.03 ❌ Not met Best simulation helix_weight AUROC 0.6458; best existing rich_selectivity AUROC 0.7453 (delta −0.0995)
Modules that fail ablation are removed or permanently experimental All failed ✅ Met All modules flagged permanent experimental (Loop 36 verdict)
Uncertainty propagated through to evidence certificate Via SimulationResult ✅ Met Each module returns uncertainty in range [0, 1]; information added to scores dict in info mode
External adapter protocol documented ARCHITECTURE.md ✅ Met ExternalSimulationAdapter documented in ARCHITECTURE.md extension points (Loop 38)

Verdict: Phase 3 exit criteria partially met. Simulation does NOT earn ranking impact, but the infrastructure and honesty guardrails are complete.


Reproducible Commands

PYTHONPATH=src python3 scripts/benchmark_simulation_ablation.py \
  --mode amp-vs-decoy --out outputs/simulation_ablation.json || test $? -eq 3

PYTHONPATH=src python3 scripts/benchmark_simulation_ablation.py \
  --mode within-amp --out outputs/simulation_ablation_within_amp.json || test $? -eq 3

PYTHONPATH=src python3 scripts/benchmark_simulation_baselines.py \
  --out outputs/simulation_baselines.json || test $? -eq 3

PYTHONPATH=src python3 -m openamp_foundry.cli bench simulation-gate \
  --amp-vs-decoy-json outputs/simulation_ablation.json \
  --within-amp-json outputs/simulation_ablation_within_amp.json \
  --out outputs/simulation_gate_verdict.json || test $? -eq 3

Exit code 3 is expected for benchmarks or gates that correctly reject weighted simulation.


Current Results

Benchmark Baseline / incumbent Simulation result Delta Verdict
AMP-vs-decoy ablation Ensemble AUROC 0.7792 Ensemble + simulation AUROC 0.6640 -0.1153 No improvement
Within-AMP hemolysis detection Rich selectivity AUROC 0.7453 Best simulation AUROC 0.6458 -0.0995 No improvement
Cheap baseline: bacterial binding Mean Eisenberg AUROC 0.5469 Bacterial binding AUROC 0.4876 -0.0593 No improvement
Cheap baseline: selectivity ratio Selectivity proxy AUROC 0.3905 Selectivity ratio AUROC 0.3615 -0.0290 No improvement
Cheap baseline: helix weight Helix propensity AUROC 0.6489 Helix weight AUROC 0.6458 -0.0031 No improvement
Cheap baseline: non-helical flag Proline fraction AUROC 0.4929 Non-helical flag AUROC 0.4124 -0.0805 No improvement

Gate Decision

openamp-foundry bench simulation-gate blocks weighted mode.

Reasons:

  • AMP-vs-decoy ablation does not improve over ensemble.
  • Within-AMP ablation does not improve over existing scorers.
  • Cheap-baseline comparison shows zero of four simulation signals beat their simplest meaningful heuristic.

Weighted mode will remain blocked until a future module passes all three checks.


Interpretation

The current simulation layer (1D Chou-Fasman propensities, averaged Wimley-White scales) is not rich enough to beat existing heuristics. Two reasons dominate:

  1. Composition dominance: The existing pipeline already extracts charge, hydrophobicity, aromatic fraction, and GRAVY — features that correlate strongly with membrane interaction. Averaged hydrophobicity scales add little beyond what these composition features already capture.

  2. No structural context: 1D per-residue averages lose all sequence-order and spatial information. A proper membrane interaction model requires coarse-grained dynamics (Martini), structural ensembles (AlphaFold), or at minimum a windowed context that captures local sequence patterns.

Future simulation work must use fundamentally richer inputs than 1D propensities. Any new module must still beat its cheap baseline before earning ranking impact.


Policy

Until this report changes with stronger evidence:

  • rank --simulation-mode info is allowed for exploratory reports.
  • weighted simulation remains blocked.
  • Evidence certificates may include simulation values only as experimental context, not as activity, safety, or selectivity proof.
  • Evidence certificates now include sim_membrane_uncertainty, sim_structure_uncertainty, and sim_max_uncertainty when simulation info mode is used.
  • No public claim may imply simulation-validated antimicrobial activity.
  • Any future simulation module must pass the gate (Loop 35) before affecting ranking. The gate will not be bypassed even if the module appears plausible.

Transition to Phase 4

Phase 4 (wet-lab readiness, Loops 40–49) shifts focus from virtual assay scaffolding to preparing for real lab partners. The simulation modules ship in info mode — usable for human inspection but not trusted for ranking.

The honest signal from Phase 3 is: simulation is not ready to compress wet-lab experiments. Phase 4 work should prioritize getting the existing pipeline into a lab partnership rather than deepening the simulation layer.