Surface motifs by a computer vision technique: Searches, detection, and implications for protein–ligand recognition

Abstract

We describe the application of a method geared toward structural and surface comparison of proteins. The method is based on the Geometric Hashing Paradigm adapted from Computer Vision. It allows for comparison of any two sets of 3-D coordinates, such as protein backbones, protein core or protein surface motifs, and small molecules such as drugs. Here we apply our method to 4 types of comparisons between pairs of molecules: (1) comparison of the backbones of two protein domains; (2) search for a predefined 3-D C alpha motif within the full backbone of a domain; and in particular, (3) comparison of the surfaces of two receptor proteins; and (4) comparison of the surface of a receptor to the surface of a ligand. These aspects complement each other and can contribute toward a better understanding of protein structure and biomolecular recognition. Searches for 3-D surface motifs can be carried out on either receptors or on ligands. The latter may result in the detection of pharmacophoric patterns. If the surfaces of the binding sites of either the receptors or of the ligands are relatively similar, surface superpositioning may aid significantly in the docking problem. Currently, only distance invariants are used in the matching, although additional geometric surface invariants are considered. The speed of our Geometric Hashing algorithm is encouraging, with a typical surface comparison taking only seconds or minutes of CPU time on a SUN 4 SPARC workstation. The direct application of this method to the docking problem is also discussed. We demonstrate the success of this method in its application to two members of the globin family and to two dehydrogenases.