Structural databases storing information about geometrical and physicochemical properties of proteins are becoming increasingly important in the field of bioinformatics, where they complement sequence databases in a reasonable way. Structural information is especially important for applications in computational chemistry and pharmacy, such as drug design. A functionality commonly offered by a structural database is similarity retrieval : Given a novel protein structure with unknown function, one is interested in finding similar proteins stored in the database— the known function of the latter may then provide an indication of the function of the query protein. In this paper, we make use of the recently developed methodology of preference-based CBR to support similarity retrieval in a protein structure database called CavBase. The efficacy of our approach is shown by means of an experimental study.
分享
引用
