TriGlue: A Biology-Inspired Generative Framework for Molecular Glue Design
Yuliang Yan · hf · 2026-08-06
Designing molecular glue degraders is computationally challenging due to unknown protein-protein interfaces. This paper formulates it as a ternary complex generation problem and proposes TriGlue.
- Two-Stage Generation: Decouples the process into interface estimation and interface-conditioned complex generation.
- Technical Details: Uses an SE(3)-equivariant module to predict geometrically constrained interfaces, and a flow matching network to jointly generate the glue and predict rigid-body transformations.
- Validation: Demonstrates TriGlue generates chemically valid molecules and plausible complexes, accelerating molecular glue discovery.
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