Finding recurring structural features among proteins three-dimensional (3D) structures is an important problem in bioinformatics. In this paper we apply a novel subgraph mining algorithm to three related graph representations of the sequence and proximity characteristics of a protein’s amino acid residues. The subgraph mining algorithm is used to discover spatial motifs that can be used to discriminate among proteins in different families found in the SCOP database. The results indicate that an Delaunay Tessellation (and its recent developed extension almost-Delaunay) subset of the contact graph is robust, sparse, and adequate to produce asymptotically simplified graphs (with increasing interaction radius) for mining spatial motifs, yielding motifs with discrimination qualities similar to, or better than, those obtained from the full contact graph
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