SURFACE MOTIFS BY A COMPUTER VISION TECHNIQUE - SEARCHES, DETECTION, AND IMPLICATIONS FOR PROTEIN LIGAND RECOGNITION

We describe the application of a method geared toward structural and s urface comparison of proteins. The method is based on the Geometric Ha shing 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. He re we apply our method to 4 types of comparisons between pairs of mole cules: (1) comparison of the backbones of two protein domains; (2) sea rch for a predefined 3-D C. motif within the full backbone of a domain ; and in particular, (3) comparison of the surfaces of two receptor pr oteins; and (4) comparison of the surface of a receptor to the surface of a ligand. These aspects complement each other and can contribute t oward a better understanding of protein structure and biomolecular rec ognition. Searches for 3-D surface motifs can be carried out on either receptors or on ligands. The latter may result in the detection of ph armacophoric patterns. If the surfaces of the binding sites of either the receptors or of the ligands are relatively similar, surface superp ositioning may aid significantly in the docking problem. Currently, on ly distance invariants are used in the matching, although additional g eometric surface invariants are considered. The speed of our Geometric Hashing algorithm is encouraging, with a typical surface comparison t aking 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 applicati on to two members of the globin family and to two dehydrogenases.