GuacaMol
Goal-directed + distribution-learning benchmarks for molecular generative models.
Composite
80.5
Experimental validation
Retrospective
Stages
Lead ID / ADMETDevelopmental Candidate
Modalities
small-molecule
Task types
molecule-generation
Size
tasks: 20
train_set: 1,600,000
train_set: 1,600,000
License
MIT
First release
2019-03
Last updated
2022-07
Official site
Leaderboard
→ leaderboard
Dataset
→ dataset
Code / GitHub
HuggingFace
→ HF
Paper
GuacaMol: Benchmarking Models for de Novo Molecular Design · Brown N, Fiscato M, Segler MHS, Vaucher AC · 2019 · paper · doi:10.1021/acs.jcim.8b00839 · 820 citations
Flags
none
Experts
Groups
Hosted by
Related benchmarks
Rubric (7-criterion)
rigor
4
coverage
4
maintenance
2
adoption
5
quality
4
accessibility
5
industry_relevance
4
Notes
First-generation generative benchmark; largely superseded by PMO for goal-directed.