Form follows function: shape analysis of protein cavities for receptor-based drug design.

Identification of potential ligand-binding pockets is an initial step in receptor-based drug design. While many geometric or energy-based binding-site prediction methods characterize the size and shape of protein cavities, few of them offer an estimate of the pocket's ability to bind small drug-like molecules. Here, we present a shape-based technique to examine binding-site druggability from the crystal structure of a given protein target. The method includes the PocketPicker algorithm to determine putative binding-site volumes for ligand-interaction. Pocket shape descriptors were calculated for both known ligand binding sites and empty pockets and were then subjected to self-organizing map clustering. Descriptors were calculated for structures derived from a database of representative drug-protein complexes with experimentally determined binding affinities to characterize the "druggable pocketome". The new method provides a means for selecting drug targets and potential ligand-binding pockets based on structural considerations and addresses orphan binding sites.