State-specific binding thermodynamics predicts ligand efficacy across ion-channel families.
Predicting ligand efficacy is a critical challenge in drug discovery, as a target's functional response is often determined by the way a ligand shifts conformational equilibria between different functional states, a process that is particularly intricate in ion channels. We classify ligands based on the difference of their binding free energies on putative active and inactive conformations, calculated via free energy perturbation (FEP) for 78 protein-ligand pairs across six ion channels from four structural superfamilies: GluA2, GABAAR {rho}1, 3{beta}4 nAChR, 5-HT3AR, TRPML1, and KCNQ2. This approach accurately distinguishes agonists from antagonists across all these ion-channel families with large or subtle structural differences, including at membrane-facing sites, and enables quantitative prediction of maximum response and partial agonism. Importantly, we find that local binding-pocket conformations encode the bound ligand's efficacy even when global channel states are ambiguous. Our results demonstrate that state-specific binding thermodynamics provides a robust framework for leveraging ion channel structures of diverse conformational states to elucidate mechanisms of action and to advance ion-channel drug discovery beyond simple affinity measurements, enabling the identification of new chemical matter with desired functional attributes.