(Received: February 13, 2001; Accepted for publication: April 4, 2001; Published on Web: May 18, 2001)
This paper describes an approach to automated identification of three-dimensional common structural features of proteins. The structure of a protein was represented by a set of secondary structure elements (SSEs) in the same manner used in our previous work, where only a-helix and b-strand secondary structure elements were considered. The maximal common subgraph algorithm, based on a graph theoretical clique finding approach, was used to identify the 3D common structural features between a pair of proteins. The program, called AIM (Automated Identification of 3D Motif of proteins), was developed and tested by computational experiments in searching for the secondary structure segments related to the Rossmann-fold motif as a 3D common structural feature between alcohol dehydrogenase and lactate dehydrogenase, which are known to have the 3D motif. The AIM successfully found the peptide segments related to the motif. A 3D substructure searching, in which the common structural feature identified was employed as a query pattern, will be discussed too.
Keywords: 3D motif finding, 3D substructure searching, maximal common subgraph, structural similarity, Rossmann-fold
Text in English