Sequence- and structure-based prediction of eukaryotic proteinphosphorylation sites

Protein phosphorylation at serine, threonine or tyrosine residues affects a multitude of cellular signaling processes. Howis specificity in substrate recognition and phosphorylation by protein kinases achieved? Here, we present an artificialneural network method that predicts phosphorylation sites in independent sequences with a sensitivity in the range from69 % to 96 %. As an example, we predict novel phosphorylation sites in the p300/CBP protein that may regulateinteraction with transcription factors and histone acetyltransferase activity. In addition, serine and threonine residues inp300/CBP that can be modified by O-linked glycosylation with N-acetylglucosamine are identified. Glycosylation mayprevent phosphorylation at these sites, a mechanism named yin-yang regulation. The prediction server is available on theInternet at http://www.cbs.dtu.dk/services/NetPhos/or via e-mail to NetPhos@cbs. dtu.dk. Copyright 1999 AcademicPress.