Franciosa Giulia, Locard-Paulet Marie, Jensen Lars J, Olsen Jesper V
Proteomics Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
Disease Systems Biology Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
Curr Opin Chem Biol. 2023 Apr;73:102260. doi: 10.1016/j.cbpa.2022.102260. Epub 2023 Jan 18.
Mass spectrometry-based phosphoproteomics is currently the leading methodology for the study of global kinase signaling. The scientific community is continuously releasing technological improvements for sensitive and fast identification of phosphopeptides, and their accurate quantification. To interpret large-scale phosphoproteomics data, numerous bioinformatic resources are available that help understanding kinase network functional role in biological systems upon perturbation. Some of these resources are databases of phosphorylation sites, protein kinases and phosphatases; others are bioinformatic algorithms to infer kinase activity, predict phosphosite functional relevance and visualize kinase signaling networks. In this review, we present the latest experimental and bioinformatic tools to profile protein kinase signaling networks and provide examples of their application in biomedicine.
基于质谱的磷酸化蛋白质组学是目前用于研究全局激酶信号传导的主要方法。科学界不断推出技术改进，以实现对磷酸肽的灵敏、快速鉴定及其准确定量。为了解释大规模磷酸化蛋白质组学数据，有许多生物信息学资源可帮助理解激酶网络在生物系统受到扰动时的功能作用。其中一些资源是磷酸化位点、蛋白激酶和磷酸酶的数据库；其他的则是用于推断激酶活性、预测磷酸化位点功能相关性以及可视化激酶信号网络的生物信息学算法。在本综述中，我们介绍了用于分析蛋白激酶信号网络的最新实验和生物信息学工具，并提供了它们在生物医学中的应用实例。
