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Article

Genome-Wide Analysis of Whole Human Glycoside Hydrolases by Data-Driven Analysis in Silico

1
Advanced Life Sciences Program, Graduate School of Life Sciences, Ritsumeikan University, 1-1-1 Nojihigashi, Kusatsu, Shiga 525-8577, Japan
2
Department of Bioinformatics, College of Life Sciences, Ritsumeikan University, 1-1-1 Nojihigashi, Kusatsu, Shiga 525-8577, Japan
*
Author to whom correspondence should be addressed.
These authors have equal contribution to this work.
Int. J. Mol. Sci. 2019, 20(24), 6290; https://doi.org/10.3390/ijms20246290
Received: 20 November 2019 / Revised: 10 December 2019 / Accepted: 11 December 2019 / Published: 13 December 2019
Glycans are involved in various metabolic processes via the functions of glycosyltransferases and glycoside hydrolases. Analysing the evolution of these enzymes is essential for improving the understanding of glycan metabolism and function. Based on our previous study of glycosyltransferases, we performed a genome-wide analysis of whole human glycoside hydrolases using the UniProt, BRENDA, CAZy and KEGG databases. Using cluster analysis, 319 human glycoside hydrolases were classified into four clusters based on their similarity to enzymes conserved in chordates or metazoans (Class 1), metazoans (Class 2), metazoans and plants (Class 3) and eukaryotes (Class 4). The eukaryote and metazoan clusters included N- and O-glycoside hydrolases, respectively. The significant abundance of disordered regions within the most conserved cluster indicated a role for disordered regions in the evolution of glycoside hydrolases. These results suggest that the biological diversity of multicellular organisms is related to the acquisition of N- and O-linked glycans. View Full-Text
Keywords: glycoside hydrolase; glycan; phylogenetic profiling glycoside hydrolase; glycan; phylogenetic profiling
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MDPI and ACS Style

Nakamura, T.; Fahmi, M.; Tanaka, J.; Seki, K.; Kubota, Y.; Ito, M. Genome-Wide Analysis of Whole Human Glycoside Hydrolases by Data-Driven Analysis in Silico. Int. J. Mol. Sci. 2019, 20, 6290. https://doi.org/10.3390/ijms20246290

AMA Style

Nakamura T, Fahmi M, Tanaka J, Seki K, Kubota Y, Ito M. Genome-Wide Analysis of Whole Human Glycoside Hydrolases by Data-Driven Analysis in Silico. International Journal of Molecular Sciences. 2019; 20(24):6290. https://doi.org/10.3390/ijms20246290

Chicago/Turabian Style

Nakamura, Takahiro, Muhamad Fahmi, Jun Tanaka, Kaito Seki, Yukihiro Kubota, and Masahiro Ito. 2019. "Genome-Wide Analysis of Whole Human Glycoside Hydrolases by Data-Driven Analysis in Silico" International Journal of Molecular Sciences 20, no. 24: 6290. https://doi.org/10.3390/ijms20246290

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