Frustration Quenching and Network Topology of the Energy Landscape as Primary Determinants of Protein–Ligand Binding Pose Prediction by Deep Learning Models
Deep learning co-folding and docking models accurately predict ligand binding poses at orthosteric sites yet systematically underperform at allosteric pockets. Here, we demonstrate that this accuracy gap reflects a fundamental biophysical property of local energy landscape topology specifically, the magnitude of frustr...
L. Turano, Brandon Foley, Ryan Dennis et al.
· bioRxiv · 0 citations