Detection of monosaccharide types from coordinates.
Almost half of biological molecules (proteins and metabolites) are extrapolated as glycosylated within cells. Detection of glycosylation patterns and of attached sugar types is therefore an important step in future glycomics research. We present two algorithms to detect sugar types in Haworth projection, i.e., from x-y coordinates. The algorithms were applied to the database of flavonoid and identified backbone-specific biases of sugar types and their conjugated positions. The algorithms contribute not only to bridge between polysaccharide databases and pathway databases, but also to detect structural errors in metabolic databases.
Arita
Masanori
M
Department of Computational Biology, Graduate School of Frontier Sciences, University of Tokyo and PRESTO JST, 5-1-5 CB05 Kashiwanoha, Kashiwa, 277-8561 Japan. arita@k.u-tokyo.ac.jp
Tokimatsu
Toshiaki
T
D000465:Algorithms; D002241:Carbohydrates / Q000737:chemistry; D019295:Computational Biology / Q000379:methods*; D006031:Glycosylation; D008956:Models, Chemical; D008968:Molecular Conformation; D009005:Monosaccharides / Q000737:chemistry*; D010944:Plants; D011134:Polysaccharides / Q000737:chemistry; D011381:Programming Languages; D013237:Stereoisomerism
D002241:Carbohydrates; D009005:Monosaccharides; D011134:Polysaccharides