To accurately quantify protein-ligand interactions without the knowledge of any protein structure data, we have developed a computational technology, Raptor, which correlates physico-chemical properties of the ligands binding to the same protein with their associated binding affinity (quantitative structure-activity relationships, QSAR). The uniqueness of this approach is its simulation of adapting physicochemical properties of the binding site triggered by the ligand binding. It further uses a dual-shell representation of the binding site allowing simulation of various protein substates adopted by different compounds binding to it. The algorithm has been proven to provide realistic 3D binding-site models of the protein and to accurately predict the affinities for sets of structurally similar as well as structurally diverse ligands.
By virtue of the accuracy of Raptor in quantifying protein-ligand interactions, we frequently combine docking for generating ligand alignment with subsequent prediction of binding affinities using Raptor. This procedure has been successfully applied to nuclear receptor, GPCRs and cytochrome P450 enzymes.