There are thousands of known cellular phosphorylation sites, but the paucity of ways to identify kinases for particular phosphorylation events remains a major roadblock for understanding kinase signaling. To address this, we here develop a generally applicable method that exploits the large number of kinase inhibitors that have been profiled on near-kinome-wide panels of protein kinases. The inhibition profile for each kinase provides a fingerprint that allows identification of unknown kinases acting on target phosphosites in cell extracts. We validate the method on diverse known kinase-phosphosite pairs, including histone kinases, EGFR autophosphorylation, and Integrin β1 phosphorylation by Src-family kinases. We also use our approach to identify the previously unknown kinases responsible for phosphorylation of INCENP at a site within a commonly phosphorylated motif in mitosis (a non-canonical target of Cyclin B-Cdk1), and of BCL9L at S915 (PKA). We show that the method has clear advantages over in silico and genetic screening.

有成千上万个已知的细胞磷酸化位点，但是缺乏针对特定磷酸化事件识别激酶的方法仍然是理解激酶信号传导的主要障碍。为了解决这个问题，我们在这里开发了一种普遍适用的方法，该方法利用了已在蛋白激酶的近全基因组上进行分析的大量激酶抑制剂。每种激酶的抑制谱提供了一个指纹，可以鉴定作用于细胞提取物中目标磷酸位的未知激酶。我们在多种已知的激酶-磷酸位对上验证了该方法，包括组蛋白激酶，EGFR自磷酸化和Src家族激酶整合素β1磷酸化。我们还使用我们的方法来鉴定负责有丝分裂（细胞周期蛋白B-Cdk1的非典型靶标）和S915的BCL9L（PKA）的常见磷酸化基序内INCENP磷酸化的激酶。我们表明，该方法比计算机模拟和遗传筛选具有明显的优势。