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通过整合磷酸化蛋白质组学和互作组学分析系统鉴定 ALK 的底物。

Systematic identification of ALK substrates by integrated phosphoproteome and interactome analysis.

机构信息

Laboratory of Proteomics for Drug Discovery, Center for Drug Design Research, National Institutes of Biomedical Innovation, Health and Nutrition, Osaka, Japan

Laboratory of Proteome Research, National Institutes of Biomedical Innovation, Health and Nutrition, Osaka, Japan.

出版信息

Life Sci Alliance. 2022 May 4;5(8). doi: 10.26508/lsa.202101202. Print 2022 Aug.

Abstract

The sensitivity of phosphorylation site identification by mass spectrometry has improved markedly. However, the lack of kinase-substrate relationship (KSR) data hinders the improvement of the range and accuracy of kinase activity prediction. In this study, we aimed to develop a method for acquiring systematic KSR data on anaplastic lymphoma kinase (ALK) using mass spectrometry and to apply this method to the prediction of kinase activity. Thirty-seven ALK substrate candidates, including 34 phosphorylation sites not annotated in the PhosphoSitePlus database, were identified by integrated analysis of the phosphoproteome and crosslinking interactome of HEK 293 cells with doxycycline-induced ALK overexpression. Furthermore, KSRs of ALK were validated by an in vitro kinase assay. Finally, using phosphoproteomic data from ALK mutant cell lines and patient-derived cells treated with ALK inhibitors, we found that the prediction of ALK activity was improved when the KSRs identified in this study were used instead of the public KSR dataset. Our approach is applicable to other kinases, and future identification of KSRs will facilitate more accurate estimations of kinase activity and elucidation of phosphorylation signals.

摘要

质谱法检测磷酸化位点的灵敏度有了显著提高。然而,激酶-底物关系(KSR)数据的缺乏限制了激酶活性预测的范围和准确性的提高。在这项研究中,我们旨在开发一种使用质谱法获取间变性淋巴瘤激酶(ALK)系统 KSR 数据的方法,并将该方法应用于激酶活性的预测。通过整合分析用强力霉素诱导过表达的 ALK 的 HEK 293 细胞的磷酸化组学和交联互作组学,鉴定了 37 个 ALK 底物候选物,其中包括 PhosphoSitePlus 数据库中未注释的 34 个磷酸化位点。此外,通过体外激酶测定验证了 ALK 的 KSR。最后,使用来自 ALK 突变细胞系和用 ALK 抑制剂处理的患者来源细胞的磷酸化组学数据,我们发现,当使用本研究中鉴定的 KSR 替代公共 KSR 数据集时,ALK 活性的预测得到了改善。我们的方法适用于其他激酶,未来 KSR 的鉴定将有助于更准确地估计激酶活性和阐明磷酸化信号。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/976c/9069051/302a7983f2f0/LSA-2021-01202_Fig1.jpg

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