Cells utilize protein-protein interaction (PPI) networks to receive, transduce, and respond to stimuli. Interaction network rewiring drives devastating diseases like cancers, making PPIs attractive targets for pharmacological intervention. Kinases are druggable nodes in PPI networks but high-throughput proteomics approaches to quantify disease-associated kinome PPI rewiring are lacking. We introduce kinobead competition and correlation analysis (Ki-CCA), a chemoproteomics approach to simultaneously map hundreds of endogenous kinase PPIs. We identified 2,305 PPIs of 300 kinases across 18 diverse cancer lines, quantifying the high plasticity of interaction networks between cancer types, signaling, and phenotypic states; this database of dynamic kinome PPIs provides deep insights into cancer cell signaling. We discovered an AAK1 complex promoting epithelial-mesenchymal transition and drug resistance, and depleting its components sensitized cells to targeted therapy. Ki-CCA enables rapid and highly multiplexed mapping of kinome PPIs in native cell and tissue lysates, without epitope tagged baits, protein labeling, or antibodies.

中文翻译：

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激酶相互作用组的多重分析量化了细胞网络的可塑性

细胞利用蛋白质-蛋白质相互作用 (PPI) 网络来接收、转导和响应刺激。交互网络重新布线驱动了癌症等毁灭性疾病，使 PPI 成为药物干预的有吸引力的目标。激酶是 PPI 网络中的可药物节点，但缺乏量化疾病相关激酶组 PPI 重新布线的高通量蛋白质组学方法。我们介绍了 kinobead 竞争和相关分析 (Ki-CCA)，这是一种化学蛋白质组学方法，可同时绘制数百种内源性激酶 PPI。我们在 18 个不同的癌症系中鉴定了 300 种激酶的 2,305 个 PPI，量化了癌症类型、信号传导和表型状态之间相互作用网络的高度可塑性；这个动态激酶组 PPI 数据库提供了对癌细胞信号传导的深入见解。我们发现了一种 AAK1 复合物，可促进上皮间充质转化和耐药性，并消耗其成分使细胞对靶向治疗敏感。Ki-CCA 能够在天然细胞和组织裂解物中快速和高度多重定位激酶组 PPI，无需表位标记诱饵、蛋白质标记或抗体。