Yoshiyuki Hizukuri (firstname.lastname@example.org)
Yoshihiro Yamanishi (email@example.com)
Kosuke Hashimoto (firstname.lastname@example.org)
Minoru Kanehisa (email@example.com)
Bioinformatics center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611-0011, Japan
Glycans, which are carbohydrate sugar chains attached to some lipids or proteins, have a huge variety of structures and play a key role in cell communication, protein interaction and immunity. The availability of a number of glycan structures stored in the KEGG/GLYCAN database makes it possible for us to conduct a large-scale comparative research of glycans. In this paper, we present a novel approach to compare glycan structures and extract characteristic glycan substructures of certain organisms. In the algorithm we developed a new similarity measure of glycan structures taking into account of several biological aspects of glycan synthesis and glycosyltransferases, and we confirmed the validity of our similarity measure by conducting experiments on its ability to classify glycans between organisms in the framework of a support vector machine. Finally, our method successfully extracted a set of candidates of substructrues which are characteristic to human, rat, mouse, bovine, pig, chicken, yeast, wheat and sycamore, respectively. We confirmed that the characteristic substructures extracted by our method correspond to the substructures which are known as the species-specific sugar chain of γ-glutamyltranspeptidases in the kidney.