Frustration Quenching and Network Topology of the Energy Landscape as Primary Determinants of Protein-Ligand Binding Pose Prediction by Deep Learning Models
Lucas Turano, Brandon Foley, Ryan Dennis, Will Gatlin, Gennady M. Verkhivker
This paper shows that deep learning models' performance in predicting protein-ligand binding poses depends on the energy landscape's frustration quenching and network topology, not algorithmic flaws.
bioRxiv · Oct 9, 2026 · PreprintBiophysics