Three-Dimensional Similarity in Molecular Docking: Prioritizing Ligand Poses on the Basis of Experimental Binding Modes

Molecular docking is the premier approach to structure-based virtual screening. While ligand posing is often successful, compound ranking using force field-based scoring functions remains difficult. Uncertainties associated with scoring often limit the ability to confidently identify new active compounds. In this study, we introduce an alternative approach to compound ranking. Rather than using scoring functions for final ranking, compounds are prioritized on the basis of computed 3D similarity to known crystallographic ligands. For different targets, it is shown that 3D similarity-based ranking consistently improves the enrichment of active compounds compared to ranking obtained using scoring functions, even if only a single crystallographic ligand is used as a reference. While the strategy is not applicable in cases where no cocrystal structure is available, it should be a promising alternative or complement to conventional scoring in many instances. Since ligand similarity calculations are used to rank docking poses, which are independently derived, the approach introduced herein also contributes to the integration of ligand- and structure-based computational screening methods.