Sequence and structure-based prediction of eukaryotic protein phosphorylation sites
Sequence and structure-based prediction of eukaryotic protein phosphorylation sites
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DOI：
10.1006/jmbi.1999.3310
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发表时间：
1999-12-17
影响因子：
5.6
通讯作者：
Brunak, S
中科院分区：
文献类型：
--
作者：
Blom, N;Gammeltoft, S;Brunak, S
丝氨酸、苏氨酸或酪氨酸残基的蛋白磷酸化影响多种细胞信号传导过程。底物识别和蛋白激酶磷酸化的特异性是如何实现的？在这里，我们提出了一种人工神经网络方法，可以预测独立序列中的磷酸化位点，灵敏度在69%到96%之间。例如，我们预测了p300/CBP蛋白中可能调节与转录因子和组蛋白乙酰转移酶活性相互作用的新磷酸化位点。此外，p300/CBP中的丝氨酸和苏氨酸残基可以用n -乙酰氨基葡萄糖进行o -链糖基化修饰。糖基化可以阻止这些位点的磷酸化，这种机制被称为阴阳调节。预测服务器可在因特网上（http://www.cbs.dtu.dk/services/NetPhos/）或通过电子邮件（NetPhos@cbs.dtu.dk）获得。(C) 1999学术出版社。
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. (C) 1999 Academic Press.