Institute of Biochemistry and Center for Molecular Biosciences Innsbruck, University of Innsbruck, Innsbruck, Austria.
Laboratory of Pediatrics, Section Systems Medicine of Metabolism and Signaling, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
Biochem Soc Trans. 2021 Feb 26;49(1):41-54. doi: 10.1042/BST20190730.
Cells have evolved highly intertwined kinase networks to finely tune cellular homeostasis to the environment. The network converging on the mechanistic target of rapamycin (MTOR) kinase constitutes a central hub that integrates metabolic signals and adapts cellular metabolism and functions to nutritional changes and stress. Feedforward and feedback loops, crosstalks and a plethora of modulators finely balance MTOR-driven anabolic and catabolic processes. This complexity renders it difficult - if not impossible - to intuitively decipher signaling dynamics and network topology. Over the last two decades, systems approaches have emerged as powerful tools to simulate signaling network dynamics and responses. In this review, we discuss the contribution of systems studies to the discovery of novel edges and modulators in the MTOR network in healthy cells and in disease.
细胞已经进化出高度交织的激酶网络，以精细地将细胞内稳态调整到环境中。汇聚到雷帕霉素（mTOR）激酶的这个网络构成了一个中央枢纽，整合代谢信号，并使细胞代谢和功能适应营养变化和应激。前馈和反馈回路、串扰以及大量的调节剂精细地平衡 mTOR 驱动的合成代谢和分解代谢过程。这种复杂性使得直观地破译信号转导动力学和网络拓扑结构变得困难（如果不是不可能的话）。在过去的二十年中，系统方法已经成为模拟信号网络动力学和反应的有力工具。在这篇综述中，我们讨论了系统研究在发现健康细胞和疾病中 mTOR 网络中的新边缘和调节剂方面的贡献。
