Prediction of Protein–Ligand Binding Affinities Using Atomic Surface Site Interaction Points

Atom surface site Interaction Points (AIP) which were previously used to predict association constants for synthetic host–guest systems has been extended to protein–ligand complexes. AIP descriptions of protein binding sites were obtained by combining a library of precomputed AIP descriptors for all protein functional groups with a graph-based substructure matching algorithm. The corresponding AIP description of ligands was obtained directly by footprinting the molecular electrostatic potential surface calculated using density functional theory. These AIP descriptions were projected onto X-ray crystal structures of protein–ligand complexes to identify pairs of AIPs that were sufficiently close in space to constitute an intermolecular interaction. The overall free energy of binding was calculated by summing the contributions of each AIP contact and associated desolvation. Application to the 94 complexes involving uncharged ligands in CASF benchmark data set showed that the method achieves a Pearson correlation coefficient of 0.76 and an RMSD of 11 kJ mol–1 for absolute free energies of binding.