Enhancing protein–ligand pose prediction via dual-branch deep learning with docking-oriented multi-component loss and iterative refinement
Protein-ligand pose prediction is a core task in structure-based drug discovery because it determines how a ligand fits within a protein pocket and directly affects downstream virtual screening and lead-optimization workflows. Recent graph neural network (GNN) methods have shown promise for protein-ligand pose predicti...