Sequence and structure-based prediction of eukaryotic protein phosphorylation sites

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 pres ent 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 pro tein that may regulate interaction with transcription factors and histone a cetyltransferase activity. In addition, serine and threonine residues in p3 00/CBP that can be modified by O-linked glycosylation with N-acetylglucosam ine are identified. Glycosylation may prevent phosphorylation at these site s, 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. (C) 1999 Academic P ress.