Structure-Aware Prediction of PROTAC-Mediated Protein Degradability via Graph Neural Networks
Proteolysis-targeting chimeras (PROTACs) can selectively degrade disease-causing proteins, yet predicting which targets are amenable to degradation remains a critical bottleneck: existing computational methods require the complete PROTAC molecular structure, information unavailable before synthesis. We present DegradoMap, a graph neural network that predicts PROTAC-mediated degradability from protein structure and E3 ligase identity alone -- the minimal information available at the target selection stage. The model encodes biophysical priors through lysine-weighted graph pooling with per-protein normalization, models protein-E3 compatibility via cross-attention, and integrates cellular co...
| Authors | Bryan Cheng, Austin Jin |
|---|---|
| Primary category | q-bio.QM |
| Published | 1 June 2026 |
| Last updated at source | 1 June 2026 |
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