Chai-1
Benefit
+0.32
Harm
0.00
Net Good
0.32
Verified benefit
0.00
History
Cumulative score
- Benefit
- Harm
- Net
Domains
Release
Status released. First dated 9 Sep 2024.
Event timeline
Reaction-aware hypergraph learning of chemical representations with LARK
Molecular pretraining offers a route to learning transferable chemical representations from unlabelled data. However, existing approaches pretrained on isolated molecular structures struggle to generalize to reaction-specific tasks because their pretraining objectives provide limited information about chemical transformations. A key challenge is to integrate this reaction information into chemical representations. Here we introduce LARK, a unified framework for learning atom-molecule-reaction knowledge from chemical transformations. Using approximately 0.6 million reactions encompassing 0.88 m
Chai-1 offers an open model for biomolecular complex prediction
Chai Discovery released Chai-1 in September–October 2024 as an open multi-modal structure model reporting PoseBusters and CASP15 scores near AlphaFold 3, with a web server usable for commercial drug discovery.