Drug–target affinity is commonly interpreted through the geometry of a representative bound complex, yet an experimentally resolved or computationally predicted structure does not specify how frequently that conformation is occupied, how it is reached, or how alternative protein, ligand, and solvent states contribute to binding. This Perspective argues that affinity is more appropriately interpreted as an ensemble property emerging from coupled conformational populations and their redistribution upon ligand recognition. The argument does not make structural snapshots dispensable, nor does it reduce binding free energy to receptor populations alone. Instead, it separates structural realizability, state population, solvent and energetic contributions, transition kinetics, and simulation-dependent inference. Evidence from conformationally flexible targets, alternative ligand poses, alchemical free-energy calculations, enhanced-sampling methods, and binding-kinetic simulations shows why structurally similar complexes can encode different thermodynamic or kinetic behavior and why simulation-derived populations remain conditional on sampling and energy models. A proposed ensemble-based interpretation is developed in which affinity claims are evaluated against state identity, statistical population, transition connectivity, energetic representation, and observable-specific validation. This formulation turns conformational heterogeneity from a complication surrounding a preferred structure into a mechanistically testable component of affinity interpretation.
IJPRAS
