Therapeutic Discovery — Overview¶
Kind: engine · Demo: E3 · Source: core/engines/therapeutic-discovery
Illustrative. Therapeutic Discovery at a glance.
What it is¶
Designs new candidate molecules shaped to fit a specific protein, and scores how well each might bind.
Why it matters¶
It attacks the hardest question in drug discovery — which molecule to even try — at the very front of a 10-15 year pipeline.
Decision support for a qualified clinician — never autonomous diagnosis or prescribing. Every output on this page is intended to inform a clinician's judgement, not replace it.
Honest limit¶
Molecule generation (MolMIM) and docking (DiffDock) are gated NVIDIA NIMs and are not installed. Candidates shown are pre-computed. This is the flagship demo and the easiest to overclaim.
Endpoints¶
:8505 — a single-service portal, so there is no separate API port
| Capability | Type | Status | Endpoint |
|---|---|---|---|
therapeutic-discovery-engine |
engine | live | localhost:8505 |
molmim-nim |
nim | live | localhost:8001 |
diffdock-nim |
nim | live | localhost:8002 |
genmol-nim |
nim | planned | — |
chemprop-admet |
model | live | localhost:8572 |
molecule-generator |
model | live | localhost:8574 |
Size and health¶
| Python files | 33 |
| Lines of code | 9,227 |
| Test files | 13 |
| Containerised | yes |
Verify at any time:
.venv/bin/python scripts/run_all_tests.py therapeutic-discovery
Where to go next¶
- Foundation Learning Guide — the concepts, no prior knowledge assumed
- Advanced Learning Guide — architecture, modules, extension points
- Demo Guide — how to run
E3