Here we present a novel, end-point method using the dead-end-elimination and A* algorithms to efficiently and accurately calculate the change in free energy, enthalpy, and configurational entropy of binding for ligand–receptor association reactions. We apply the new approach to the binding of a series of human immunodeficiency virus (HIV-1) protease inhibitors to examine the effect ensemble reranking has on relative accuracy as well as to evaluate the role of the absolute and relative ligand configurational entropy losses upon binding in affinity differences for structurally related inhibitors. Our results suggest that most thermodynamic parameters can be estimated using only a small fraction of the full configurational space, and we see significant improvement in relative accuracy when using an ensemble versus single-conformer approach to ligand ranking. We also find that using approximate metrics based on the single-conformation enthalpy differences between the global minimum energy configuration in the bound as well as unbound states also correlates well with experiment.Using a novel, additive entropy expansion based on conditional mutualinformation, we also analyze the source of ligand configurationalentropy loss upon binding in terms of both uncoupled per degree offreedom losses as well as changes in coupling between inhibitor degreesof freedom. We estimate entropic free energy losses of approximately+24 kcal/mol, 12 kcal/mol of which stems from loss of translationaland rotational entropy. Coupling effects contribute only a small fractionto the overall entropy change (1–2 kcal/mol) but suggest differencesin how inhibitor dihedral angles couple to each other in the boundversus unbound states. The importance of accounting for flexibilityin drug optimization and design is also discussed.
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