Halicin, an antibiotic found by a neural network screening a compound library
Halicin, an antibiotic found by a neural network screening a compound library is graded peer reviewed on whataifound.org, with the AI's role graded search scaffold.
A graph neural network trained on 2,335 molecules picked halicin out of a repurposing library; it killed multidrug-resistant bacteria including Acinetobacter baumannii and Mycobacterium tuberculosis in vitro and cleared infections in mice.
- Verification
- Peer reviewed
- Autonomy
- Search scaffold
- Lab
- MIT / Broad Institute
- Model
- Directed message-passing graph neural network (Chemprop)
- Field
- Medicine
- Date
- 2020-02-20
- Human collaborators
- Jonathan Stokes, Regina Barzilay, James Collins
What was found
The model was trained to predict growth inhibition of E. coli from structure alone, then applied to the Drug Repurposing Hub. Halicin — an abandoned diabetes candidate — scored highly despite being structurally unlike known antibiotics. It kills by dissipating the proton-motive force across the bacterial membrane, and the team could not evolve resistant E. coli over 30 days of serial passage. A follow-up screen of about 107 million molecules from ZINC15 produced eight further candidates. Published in Cell.
Novelty check
Virtual screening long predates deep learning. What was new was a model surfacing a hit structurally distant from its training set, with a mechanism distinct from existing antibiotic classes, and the follow-through to efficacy in animals. Halicin itself was a known molecule; the discovery is of its antibacterial activity, not of the compound.
Caveats
Halicin had not entered clinical trials six years on, which is the usual fate of antibiotic leads and a reminder that discovery is not the bottleneck in this field. The model ranked compounds; the mechanism work, the animal studies and the interpretation are human. Membrane-disrupting antibacterials carry a known selectivity risk in mammals.
Sources
How this is graded
whataifound.org grades every entry on two axes: verification (how solid the result is, from a machine-checked proof down to refuted) and autonomy (how much the AI did versus its human collaborators). This finding is peer reviewed and search scaffold. Full definitions are in the methodology.
Cite this entry
whataifound.org (2020). Halicin, an antibiotic found by a neural network screening a compound library. whataifound.org: A Registry of AI Scientific and Mathematical Discoveries. https://whataifound.org/finding/2020-02-20-halicin