NetOglyc ( was: removing o-glycosylation)
allanh at petrus.uit.no
Mon Sep 4 14:41:21 EST 1995
<Pine.A220.127.116.110903071318.18610B-100000 at freenet3.freenet.ufl.edu>,
afn26055 at freenet.ufl.edu says...
>You mentioned a NetOglyc prediction service. Could you follow up with
>info for accessing this service. Thank you.
NetOglyc is a free service for prediction of O-glycosylation, provided
by the Center for Biological Sequence Analysis at The Technical
University of Denmark in Lyngby, Denmark. I've taken the liberty of
copying the following from them:
*************** NetOglyc Mail Server V1.0 ***************
Prediction of O-glycosylation of mammalian proteins
Center for Biological Sequence Analysis
The Technical University of Denmark
DK-2800 Lyngby, Denmark
The NetOglyc mail server is a service producing neural network
predictions of mucin type O-glycosylation sites in mammalian proteins
as described in: J.E. Hansen, O. Lund, J. Engelbrecht, H. Bohr, J.O.
Nielsen, J.E.S. Hansen and S. Brunak, Prediction of O-glycosylation of
mammalian proteins: Specificity patterns of UDP-GalNAc:polypeptide
N-acetylgalactosaminyltransferase. The Biochemical Journal, 308,
The specificity of the enzyme(s) catalyzing the covalent link between
the hydroxyl side-chains of serine or threonine and the sugar moiety
GalNAc is unknown. Pattern recognition by artificial neural networks
and weight matrix algorithms was performed to determine the exact
position of in vivo O-linked GalNAc glycosylated serine and threonine
residues from the primary sequence exclusively. The acceptor sequence
context for O-glycosylation of serine was found to differ from that of
threonine and the two types were therefore treated separately. The
context of the sites showed a high abundance of proline, serine and
threonine extending far beyond the previously reported region covering
positions -4 through +4 relative to the glycosylated residue. The
O-glycosylation sites were found to cluster and to have a high
abundance in the amino-terminal part of the protein. The sites were
also found to have an increased preference for three different classes
of beta-turns. No simple consensus like rule could be deduced for the
complex glycosylation sequence acceptor patterns. The neural networks
were trained on the hitherto largest data material consisting of 48
carefully examined mammalian glycoproteins comprising 264
O-glycosylation sites. For detection neural network algorithms were
much more reliable than weight matrices. The networks correctly found
60-95% of the O-glycosylated serine/threonine residues and 89-97% of
the non-glycosylated residues in two independent test sets of known
glycoproteins. A computer server using E-mail for prediction of
O-glycosylation sites has been implemented and made publicly available.
The network will be updated and predictions can alter due to different
versions. The network is balanced to give optimal predictions whether
you submit sequences with no homology to the known O-glycosylated
proteins or not. If however the submitted sequence is very close to or
identical to the sequences in our training dataset, wewill notify you
by sending you both the assigment of the homologous (or identical)
sequence in our data set and the prediction.
The NetOglyc server returns a help file if the submitted file contains
the word `help'.
Your submitted sequences will be deleted automatically immediately
after processing by NetOglyc.
The procedure is to send an E-mail to netOglyc at genome.cbs.dtu.dk. The
first line should be a greater-then sign (>) followed by the name for
the sequence. On the next line put the sequence (in single letter
code), followed by an empty line to indicate the end of the sequence.
Several sequences can be submitted in the same e-mail. You get the
results back by e-mail - in my experience within a few hours of
submitting the sequence.
Hope this is of help to you!
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