AUTOMATIC IDENTIFICATION AND REPRESENTATION OF PROTEIN-BINDING SITES FOR MOLECULAR DOCKING

Molecular docking is a popular way to screen for novel drug compounds. The method involves aligning small molecules to a protein structure a nd estimating their binding affinity. To do this rapidly for tens of t housands of molecules requires an effective representation of the bind ing region of the target protein. This paper presents an algorithm for representing a protein's binding site in a way that is specifically s uited to molecular docking applications. Initially, the protein's surf ace is coated with a collection of molecular fragments that could pote ntially interact with the protein. Each fragment, or probe, serves as a potential alignment point for atoms in a ligand, and is scored to re present that probe's affinity for the protein. Probes are then cluster ed by accumulating their affinities, where high affinity clusters are identified as being the ''stickiest'' portions of the protein surface. The stickiest cluster is used as a computational binding ''pocket'' f or docking. This method of site identification was tested on a number of ligand-protein complexes; in each case the pocket constructed by th e algorithm coincided with the known ligand binding site. Successful d ocking experiments demonstrated the effectiveness of the probe represe ntation.