Abstract:
:Protein phosphorylation at serine, threonine or tyrosine residues affects a multitude of cellular signaling processes. How is specificity in substrate recognition and phosphorylation by protein kinases achieved? Here, we present an artificial neural network method that predicts phosphorylation sites in independent sequences with a sensitivity in the range from 69 % to 96 %. As an example, we predict novel phosphorylation sites in the p300/CBP protein that may regulate interaction with transcription factors and histone acetyltransferase activity. In addition, serine and threonine residues in p300/CBP that can be modified by O-linked glycosylation with N-acetylglucosamine are identified. Glycosylation may prevent phosphorylation at these sites, a mechanism named yin-yang regulation. The prediction server is available on the Internet at http://www.cbs.dtu.dk/services/NetPhos/or via e-mail to NetPhos@cbs. dtu.dk.
journal_name
J Mol Bioljournal_title
Journal of molecular biologyauthors
Blom N,Gammeltoft S,Brunak Sdoi
10.1006/jmbi.1999.3310keywords:
subject
Has Abstractpub_date
1999-12-17 00:00:00pages
1351-62issue
5eissn
0022-2836issn
1089-8638pii
S0022283699933107journal_volume
294pub_type
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