Multi-scale Systems Pharmacology-based Analysis For P53 Protein Regulation Network

In multicellular organisms, homeostasis is maintained through a balance between cell proliferation and cell death, which refers to the regulation of synthesis of molecules within the cell as well as the organization and function of cells and tissues. Cell survival and death appear when the homeostasis is disrupted, and the dysregulation plays important roles in the pathogenesis of many complex diseases. The determination of cell fate has been investigated with both an experiment and mathematic model simulation, and is regulated by both cell-intrinsic and cell-extrinsic factors. Although much are known about large number of proteins are shown the close relationships about the cell apoptosis, less are known about the mechanisms of cell death. So elucidation of the mechanisms of cell-fate determination and the search for chemopreventive agents are important and urgent tasks.The p53 protein is a major protein in the elucidation of cell fate through two aspects: the single-cell and multiple-cell levels. The gene expression dynamics and the natural oscillators of p53-Mdm2 have been obtained in response to DAN damage caused by gamma irradiation and a series of discrete pluses in identical cells. However, the expression of other related-factors of p53 network(PTEN, p21, ARF, etc.) have not yet been shown, which are pivotal downstream targets of p53 regulatory network. Deeply studies show the close relationship between p53 protein and miRNAs, which can help us to known the cell fate determination.Recently, a series of mathematical models have been proposed to explain the dynamics and kinetic processes of p53 stress response network under certain treatment, either in cell population or in a single-cell, and most of which are deterministic model produced by ordinary differential equations(ODEs). These mathematical models of the dynamics of p53 signaling pathways make it possible to understand the decision of cell survival or death through systems-based dynamic analysis. Unfortunately, the existing modeling efforts have not explored sustained pulses as found on internal and external stress responses, respectively, and also have not explained why the survival and death can be observed for the same samples treated by the same conditions.In this study, we propose a systems pharmacology-based framework to simulate the p53-dependent cellular stress response in single-cell and multiple cell levels for cell fate determination, respectively. The model is consisted of three modules: a DNA damage repair module, an ataxia telangiectasia mutated(ATM) switch, and the p53 network. The Cellular Potts Model(CPM) coupled with ODE is applied to investigate the stress response of p53 network in the cell-fate determination process. Based on the dynamic result, we attempt to establish a two-factors randomized mathematic model to explain the cell-fate determination. The results are shown as follow:1. We propose a framework to simulate the p53-dependent cellular stress response, this model can predicte the dynamic behavior for cell.2. The role of miRNA in p53 regulatory network is not as strong as we expect, through the dynamic results of the continuous and short-term treatments for seven internal stress, this may show the keeper for life about microRNA.3. We postulate a two-factors model to explain the existence of apoptosis rate, as a measure of cell-fate determination of the cell population, this model can show the relationship among p53 protein, apoptosis and stress level.4. Built a multi-scale model to coupling the the dynamic of molecule and cell behavious.Our approaches and modeling results have provided valuable to achieve the relationship between the monitoring of multidimensional(different conditions, times, and proteins) pathway dynamics and cell behavior. At same time, in order to ensure the integrity of our analog network access, TNF-α, as an example of down-regulated protein of p53 regulatory network, by using the distance comparison technique(DISCOtech), comparative molecular field analysis(CoMFA), and comparative molecular similarity index analysis(CoMSIA) methods, inhibitory activities at the TNF-α release were investigated, We do hope the results of the present study may provide further support to the design of imidazoles as potential inhibitors of TNF-α release.