P53蛋白调控网络的多尺度系统药理学研究

发布时间：2018-04-23 03:19

本文选题：细胞命运 + 多尺度动力学模拟　；参考：《西北农林科技大学》2015年博士论文

【摘要】：多细胞生物可以通过调节细胞增殖和细胞凋亡的平衡来维持生物机体内的稳定,即通过调控细胞内分子代谢的平衡以及细胞组织的结构和功能来保证生理功能的正常进行。当细胞内的稳态遭到破坏的时候,细胞会出现生存困难甚至死亡,因此在许多复杂疾病的发病机理中,细胞内分子间调控的失调均起着重要的作用。在决定细胞命运的复杂机理探究中,生物实验方法和数学建模方法已成为两种常用方法。此外,细胞命运的决定是由细胞的内在因素和外在因素相互作用共同决定的。尽管我们已经发现了许多与细胞凋亡有密切关系的蛋白质,但对于细胞死亡的机制并不了解。因此通过对决定细胞命运的生物学机制探究,进而寻求预防疾病、控制疾病的方法就成为当务之急。无论是单细胞水平还是多细胞水平的研究均表明,p53蛋白在细胞命运的决定中起着重要的作用。分子水平的天然振荡器p53-Mdm2的动力学行为表明,p53蛋白在经由一定IR处理后的细胞信号响应过程中起到重要作用,与细胞命运的决定呈现重要关联。但是,我们认不清楚p53蛋白调控网络(PTEN,p21,ARF,etc.)的下游重要调控靶点的相关作用机理。其中值得注意的一点是,microRNAs的加入为由p53蛋白介导的决定细胞命运的研究提供了新的着眼点,同时也有助于我们对生命机理的深入认知,从而为药理学和病理学的研究提供新的理论依据。由于实验数据的庞杂及实验手段的限制,运用数学模型去模拟单个细胞或一个细胞群的p53蛋白动力学变化,成为了一种不可或缺的手段。现在对蛋白网络的模拟大部分是由常微分方程组成的确定性模型。这些动力学数学模型可使我们通过对信号系统的动态分析来刻画细胞是存活还是死亡。但是,现有的模拟并没有同时从内外部应激信号这两个方面入手,对细胞命运的决定原理进行解析,因此目前也没有成功的模型来刻画在同等条件下同一细胞群体中各个个体的特异性命运决策。在本研究中,我们基于系统药理学的理念,模拟了依赖于p53蛋白的信号调控网络模型,该模型包括三个模块:DNA损伤修复模块,即刺激信号信号响应模块;ATM活化模块,即信号转导中介模块和p53及相关蛋白和microRNA的生化分子网络。通过体系中生化分子的含量变化来刻画和探究细胞命运决定过程中p53网络对内外部应激信号的响应情况。主要的结果如下:1.首先我们在三个子模块(DSB损伤修复模块,ATM激活模块,p53蛋白调控网络模块)的基础上成功构建了p53蛋白调控网络的系统动力学数学模型,该模型可以较准确地模拟真实细胞的生物学行为,其模拟结果与实验观察所得的结果高度吻合;2.通过对多种内应系统(三个大类区域,七小类区域)进行持续和短期外部应激信号刺激的动力学结果比较,发现单个的miRNA-145对整个蛋白网络具有微弱的调控作用,揭示了在生命活动中,microRNA作为守护者的作用;3.在p53蛋白调控网络的模拟基础上,提出了双因素的细胞命运决定模型,该模型能够较全面的刻画细胞凋亡的概率与蛋白水平,及其信号强度之间的关系;4.运用细胞生物学中的多尺度理念,将p53蛋白生化分子网络的动力学模拟与细胞行为的多尺度相耦合,实现了从分子水平到细胞水平的数学建模。最终将生化分子-细胞行为-细胞命运的决定相关联,发现细胞可以通过网络式的蛋白调控方式提高细胞本身的生存概率。综上所述,本文从多蛋白,单个miRNA参与的p53蛋白动力学模型的构建,到细胞命运的双因素模型的提出,最终将这些模型与细胞多尺度的模型耦合起来,构建了由内外部应激信号共同参与的p53蛋白调控网络的动力学响应模型,并通过计算模拟直接反映网络式的调控模式对细胞命运的作用。本文将系统的研究蛋白网络的动力学特性和细胞多尺度研究相耦合的研究框架可作为后期类似研究的范例,同时也可为后期的药理学病理学提供研究理论基础和可视化仿真模拟。此外,为保证模拟网络通路的完整性,我们还以p53调控蛋白网络的下游蛋白TNF-α为例,通过CoMFA法和CoMSIA法的分析预测,研究了构效关系中的咪唑基化合物对TNF-α的释放的抑制作用,从而为设计潜在的咪唑类TNF-α释放抑制剂提供新的理论依据。
[Abstract]:Multicellular organisms can maintain the stability of the organism by regulating the balance of cell proliferation and apoptosis, that is, the normal progress of physiological function is guaranteed by regulating the balance of intracellular metabolism and the structure and function of cell tissue. In the pathogenesis of many complex diseases, the imbalance between intracellular molecules plays an important role. In determining the complex mechanism of cell fate, the biological experiment method and mathematical modeling method have become two common methods. In addition, the cell fate is determined by the internal and external factors of the cell. Interaction is decided. Although we have found many proteins that are closely related to apoptosis, we do not understand the mechanism of cell death. Therefore, it is urgent to seek the prevention and control of the disease by exploring the biological mechanism that determines the fate of the cells. Multicellular level studies have shown that p53 protein plays an important role in the determination of cell fate. The kinetic behavior of the molecular level natural oscillator p53-Mdm2 indicates that the p53 protein plays an important role in the cellular signal response process after a certain IR treatment, and has an important association with the determination of the cell fate. But, we It is not clear that the p53 protein regulatory network (PTEN, p21, ARF, etc.) is the related mechanism of the downstream important regulatory targets. One of the noteworthy points is that the addition of microRNAs provides a new eye for the study of cell fate mediated by p53 protein, and also helps us to understand the mechanism of life, and thus for pharmacology. It provides a new theoretical basis for the study of pathology. Because of the complexity of experimental data and the limitation of experimental means, it is an indispensable means to simulate the dynamic changes of p53 protein in a single cell or a cell group by using mathematical models. The simulation of protein network is now mostly determined by the determination of ordinary differential equations. These dynamic mathematical models enable us to describe the survival or death of cells by dynamic analysis of the signal system. However, the existing simulation does not start with the two aspects of the internal and external stress signals, and analyzes the principle of cell fate determination, because there is no successful model to describe it at the same time. In this study, based on the concept of systematic pharmacology, we simulated the signal control network model dependent on p53 protein, which includes three modules: the DNA damage repair module, the stimulus signal signal response module, the ATM activation module, the signal transduction mediator model. Biochemical molecular networks of blocks and p53 and related proteins and microRNA. The response of p53 networks to internal and external stress signals in the process of cell fate determination is described and explored by changes in the content of biochemical molecules in the system. The main results are as follows: 1. first we are in the three sub modules (DSB damage repair module, ATM activation module, p53 protein modulation) On the basis of the control network module, a systematic dynamic mathematical model of the p53 protein regulation network is successfully constructed. The model can accurately simulate the biological behavior of real cells. The simulation results are highly consistent with the results obtained from the experimental observation; 2. through the multiple internal response systems (three large classes, seven small areas), the model is consistent. Compared with the dynamic results of short-term external stress signal stimulation, it is found that a single miRNA-145 has a weak regulatory effect on the whole protein network, and reveals the role of microRNA as a guardian in life activities. 3. on the basis of the simulation of the p53 protein regulation network, a two factor cell fate determination model is proposed, which can be compared. A comprehensive characterization of the relationship between the probability of apoptosis and the protein level and its signal intensity; 4. by using the multi-scale concept in cell biology, the kinetic modeling of the biochemical molecular network of p53 protein and the multiscale of cell behavior are coupled to achieve the mathematical modeling from the molecular level to the cell level. Associated with the decision of behavior cell fate, it is found that cells can improve the survival probability of cells themselves through a network of protein regulation. In summary, this paper proposes the construction of a p53 protein kinetic model involving multiple proteins, single miRNA, and a dual factor model of cell fate. Coupled with the model, the dynamic response model of the p53 protein regulation network, which is involved in the internal and external stress signals, is constructed, and the effect of the network mode on the cell fate is directly reflected by the calculation simulation. The research framework of the dynamic characteristics of the protein network and the multi-scale study of the cell is systematically studied in this paper. As an example of later similar studies, it can also provide theoretical basis and visual simulation for later pharmacological pathology. In addition, in order to ensure the integrity of analog network pathways, we also study the structure effect relationship by the analysis and prediction of the downstream protein TNF- alpha of the p53 regulation protein network by the analysis and prediction of the CoMFA and CoMSIA methods. The inhibitory effect of imidazolyl compounds on the release of TNF- alpha, thus providing a new theoretical basis for the design of potential imidazole TNF- alpha release inhibitors.

【学位授予单位】：西北农林科技大学
【学位级别】：博士
【学位授予年份】：2015
【分类号】：R96

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