Solvent Accessible Surface Representation in a Database System for Protein Docking

Proceedings of the Twentieth International Conference on Machine Learning, 1995

Volume

Proceedings of the Twentieth International Conference on Machine Learning, 1995

Contents

Protein docking is a new and challenging application for query processing in database systems. Our architecture for an efficient support of docking queries is based on the multi-step query processing paradigm, a technique well-known from spatial database systems. Along with physicochemical parameters, the geometry of the molecules plays a fundamental role for docking retrieval. Thus, 3D structures and 3D surfaces of molecules are basic objects in molecular databases. We specify a molecular surface representation based on topology, define a class of neighborhood queries, and sketch some applications with respect to the docking problem. We suggest a patch-based data structure called the TriEdge structure, first, to efficiently support topological query processing, and second, to save space in comparison to common planar graph representations such as the quad-edge structure. In analogy to the quad-edge structure, the TriEdge structure has an algebraic interface and is implemented via complex pointers. However, we achieve a reduction of the space requirement by a factor of four. Finally, we investigate the time performance of our prototype.