F. Sesterhenn

Targeted finetuning enables co-folding models to learn ligand-induced protein conformational states

This approach provides a blueprint for adapting foundation models as new structural and mechanistic data emerge, enabling co-folding networks to capture ligand-induced conformational switches and binding poses absent from their training data but central to biological regulation and therapeutic intervention.