Abstract Motivation: Protein structure classification has been recognized as one of the most important research issues in protein structure analysis. A substantial number of methods for the classification have been proposed, and several databases have been constructed using these methods. Since some proteins with very similar sequences may exhibit structural diversities, we have proposed PDB-REPRDB: a database of representative protein chains from the Protein Data Bank (PDB), which strategy of selection is based not only on sequence similarity but also on structural similarity. Forty-eight representative sets whose similarity criteria were predetermined were made available over the World Wide Web (WWW). However, the sets were insufficient in number to satisfy users researching protein structures by various methods. Result: We have improved the system for PDB-REPRDB so that the user may obtain a quick selection of representative chains from PDB. The selection of representative chains can be dynamically configured according to the user’s requirement. The WWW interface provides a large degree of freedom in setting parameters, such as cut-off scores of sequence and structural similarity. This paper describes the method we use to classify chains and select the representatives in the system. We also describe the interface used to set the parameters. Availability: The system for PDB-REPRDB is available at the PAPIA WWW server (http://www.rwcp.or.jp/papia/). Contact: [email protected] * To whom correspondence should be addressed. 3 Present address: Information Processing Systems Department, NKK Corporation, 1-1-2 Marunouchi, Chiyoda-ku, Tokyo 100-8202, Japan

MOTIVATION: Since the protein structure database has been growing very rapidly in recent years, the development of efficient methods for searching for similar structures is very important. RESULTS: This paper presents a novel method for searching for similar fragments of proteins. In this method, a hash vector (a vector of real numbers) is associated with each fixed-length fragment of three-dimensional protein structure. Each vector consists of low-frequency components of the Fourier-like spectrum for the distances between C alpha atoms and the centroid. Then, we can analyze the similarity between fragments by evaluating the difference between hash vectors. The novel aspect of the method is that the following property is proved theoretically: if the root mean square distance between two fragments is small, then the distance between the hash vectors is small. Several variants of this method were compared with a naive method and a previous method using PDB data. The results show that the fastest one among the variants is 18-80 times faster than the naive method, and 3-10 times faster than the previous method.