Algebraic dependency models of protein signal transduction networks from time-series data
Algebraic dependency models of protein signal transduction networks from time-series data
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DOI：
10.1016/j.jtbi.2005.05.010
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发表时间：
2006-01-21
影响因子：
2
通讯作者：
John, DJ
中科院分区：
文献类型：
--
作者：
Allen, EE;Fetrow, JS;John, DJ
信号转导网络对于细胞间和细胞内信号转导至关重要。信号通常通过蛋白质结构的共价修饰来传递，主要的例子是磷酸化/去磷酸化。在本文中，我们将最近描述的计算代数方法应用于基于时程蛋白质修饰数据的信令网络的建模。使用计算代数技术来构造下一状态函数。蒙特卡罗方法被用来近似对应于各个变量的Deegan-Packel指数。Deegan-Packel功率指数被用来推测蜂窝信令网络中的相关性。我们将这种方法应用于文献中可用的两个蛋白质修饰时程数据的例子。这些实验确定了当细胞暴露在亚致死浓度的铜中时，蛋白质发生甲基化。我们证明，这种方法可以识别可能对应于调节机制的蛋白质依赖性，以反向、循序渐进的方式关闭糖酵解，以响应铜诱导的酵母氧化应激。这些例子表明，计算代数方法可以识别依赖关系，这些依赖关系可能勾勒出糖酵解酶对铜引起的氧化应激反应所涉及的信号网络。(C)2005爱思唯尔有限公司。保留所有权利。
Signal transduction networks are crucial for inter- and intra-cellular signaling. Signals are often transmitted via covalent modification of protein structure, with phosphorylition/dephosphorylation as the primary example. In this paper, we apply a recently described method of cornputational algebra to the modeling of signaling networks, based on time-course protein modification data. Computational algebraic techniques are employed to construct next-state functions. A Monte Carlo method is used to approximate the Deegan-Packel Index of Power corresponding to the respective variables. The Deegan-Packel Index of Power is used to conjecture dependencies in the cellular signaling networks. We apply this method to two examples of protein modification time-course data available in the literature. These experiments identified protein carbonylation upon exposure of cells to sub-lethal concentrations of copper. We demonstrate that this method can identify protein dependencies that might correspond to regulatory mechanisms to shut down glycolysis in a reverse, step-wise fashion in response to copper-induced oxidative stress in yeast. These examples show that the computational algebra approach can identify dependencies that may outline signaling networks involved in the response of glycolytic enzymes to the oxidative stress caused by copper. (c) 2005 Elsevier Ltd. All rights reserved.