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NetOglyc: Prediction of mucin type O-glycosylation sites based on sequence context and surface accessibility
Authors:Jan E Hansen  Ole Lund  Niels Tolstrup  Andrew A Gooley  Keith L Williams  Søren Brunak
Institution:(1) Center for Biological Sequence Analysis, The Technical University of Denmark, Building 206, Lyngby, DK-2800, Denmark;(2) School of Biological Sciences, Macquarie University Sydney, 2109, NSW, Australia
Abstract:The specificities of the UDP-GalNAc:polypeptide N-acetylgalactosaminyltransferases which link the carbohydrate GalNAc to the side-chain of certain serine and threonine residues in mucin type glycoproteins, are presently unknown. The specificity seems to be modulated by sequence context, secondary structure and surface accessibility. The sequence context of glycosylated threonines was found to differ from that of serine, and the sites were found to cluster. Non-clustered sites had a sequence context different from that of clustered sites. Charged residues were disfavoured at position – 1 and +3. A jury of artificial neural networks was trained to recognize the sequence context and surface accessibility of 299 known and verified mucin type O-glycosylation sites extracted from O-GLYCBASE. The cross-validated NetOglyc network system correctly found 83% of the glycosylated and 90% of the non-glycosylated serine and threonine residues in independent test sets, thus proving more accurate than matrix statistics and vector projection methods. Predictions of O-glycosylation sites in the envelope glycoprotein gp120 from the primate lentiviruses HIV-1, HIV-2 and SIV are presented. The most conserved O-glycosylation signals in these evolutionary-related glycoproteins were found in their first hypervariable loop, V1. However, the strain variation for HIV-1 gp120 was significant. A computer server, available through WWW or E-mail, has been developed for prediction of mucin type O-glycosylation sites in proteins based on the amino acid sequence. The server addresses are http://www.cbs.dtu.dk/services/NetOGlyc/ and netOglyc@cbs.dtu.dk.
Keywords:mucin type O-glycosylation  specificity  GalNAc transferase  prediction  neural networks  gp120  SIV  HIV
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