结构可控性揭示未折叠蛋白反应中隐藏的调控机制：网络模型的作用
Structural Controllability to Unveil Hidden Regulation Mechanisms in Unfolded Protein Response: the Role of Network Models
AI总结：
本研究将复杂网络的结构可控性分析应用于未折叠蛋白反应网络，通过构建多个基于蛋白质相互作用数据库的网络模型，识别出与已知内质网应激传感器匹配的关键驱动节点，证明了结构可控性是研究生物信号通路的可靠定量工具。
摘要：
未折叠蛋白反应是细胞维持内质网（专门的细胞区室）中正确折叠蛋白质平衡的机制。尽管从生物学角度对此进行了大量研究，但大部分文献缺乏对这一核心信号通路的定量分析。在本研究中，我们旨在通过将复杂网络的结构可控性分析应用于多个未折叠蛋白反应网络，以填补这一空白，从而识别信号流中的关键节点。具体而言，我们首先利用包含在各种蛋白质-蛋白质相互作用数据库中的数据，构建了未折叠蛋白反应机制的不同网络模型。然后，我们识别了对整体网络控制至关重要的驱动节点，即那些可以最优地施加外部刺激以控制网络行为的关键蛋白质。我们的结构可控性分析结果表明，在不同数据库中共同识别出的驱动节点与已知的内质网应激传感器相匹配。这潜在地证实了理论上识别出的驱动因子对应于与基础细胞活动和疾病相关的生物学关键蛋白质。总之，我们证明了结构可控性是研究生物信号通路的可靠定量工具，并且有可能应用于比未折叠蛋白反应更复杂、更少被探索的网络。
英文摘要：
The Unfolded Protein Response is the cell mechanism for maintaining the balance of properly folded proteins in the endoplasmic reticulum , the specialized cellular compartment. Although it is largely studied from a biological point of view, much of the literature lacks a quantitative analysis of such a central signaling pathway. In this work, we aim to fill this gap by applying structural controllability analysis of complex networks to several Unfolded Protein Response networks to identify crucial nodes in the signaling flow. In particular, we first build different network models of the Unfolded Protein Response mechanism, relying on data contained in various protein-protein interaction databases. Then, we identify the driver nodes, essential for overall network control, i.e., the key proteins on which external stimulation may be optimally delivered to control network behavior. Our structural controllability analysis results show that the driver nodes commonly identified across databases match with known endoplasmic reticulum stress sensors. This potentially confirms that the theoretically identified drivers correspond to the biological key proteins associated with fundamental cellular activities and diseases. In conclusion, we prove that structural controllability is a reliable quantitative tool to investigate biological signaling pathways, and it can be potentially applied to networks more complex and less explored than Unfolded Protein Response.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
