Defining Signal Network Plasticity

描述（由申请人提供）：信号网络的可塑性允许细胞反应根据不同的环境条件而改变行为。对信号网络可塑性有贡献的特征包括：1。对持续刺激的适应或脱敏（反馈调节）。2. 在共享关键信号成分的同时维持通路特异性。3. 在存在环境波动和内在波动的情况下进行稳健的活动。4. 通路活动的动态调节，以编码和传递有关细胞周围环境的信息。5. 亚细胞定位和信号组分活性的动态重组。6. 缓冲或稳健性对通路成分的扰动（例如，信号成分的删除，过表达或突变）。我们认为，正是信号网络的可塑性极大地削弱了单靶点小分子疗法有效治疗人类疾病的能力（即，控制网络激活和功能的单节点经常缺失）。我们提出的定义MAPK信号网络可塑性的研究允许对网络中的两个或多个节点进行计算预测和生化、遗传和药理学验证，这些节点的组合扰动将有效抑制或重建疾病失调网络的正常动态。该联盟的目标是：1。完成MAPK信号网络的全面定量蛋白质组学分析。2. 使用高度创新的特定gtpase和其他控制MAPK信号网络活性的蛋白质活性的时空成像与能够测量同一活细胞中ERK1/2， p38， JNK和ERK5活性的传感器相结合。3. 利用生物信息学方法对蛋白质组学数据集和MAPK信号网络分析进行注释，对MARK网络的活性和可塑性进行建模。建模将用于定义MAPK网络的可塑性，并确定对可塑性至关重要的节点。这些模型将在不同刺激、刺激组合以及MAPK信号网络的遗传和小分子扰动的迭代过程中进行实验测试。4. 开发用于干扰网络可塑性的节点蛋白小分子抑制剂。该分析将在细胞模型中进行测试，其中MAPK信号网络的重新布线和失调与转化或耐药性等疾病状态有关。

DESCRIPTION (provided by applicant): Signal network plasticity allows cellular responses to vary in behavior according to varying environmental conditions. Features that contribute to signal network plasticity include: 1. Adaptation or desensitization to persistent stimuli (feedback regulation). 2. Maintenance of pathway specificity while sharing key signaling components. 3. Robust activity in the presence of both environmental and intrinsic fluctuations. 4. Dynamical modulation of pathway activity to encode and transmit information about the cell's surroundings. 5. Dynamical reorganization of sub cellular location and activity of signaling components. 6. Buffering against or robustness to perturbations in pathway components (e. g., deletion, over expression or mutation of signaling components). We believe it is the plasticity of signaling networks that has greatly impaired the ability of single target small molecule therapeutics to be effective in treating human disease (i.e., the frequent absence of single nodes controlling network activation and function). Our proposed studies to define plasticity of the MAPK signaling network allows computational predictions and biochemical, genetic and pharmacological validation of two or more nodes within the network whose combinatorial perturbation will effectively inhibit or re-establish normal dynamics of a disease dysregulated network. The goals of the consortium are to: 1. Complete a comprehensive quantitative proteomic analysis of the MAPK signaling network. 2. Use highly innovative spatio-temporal imaging of the activity of specific GTPases and other proteins controlling MAPK signaling network activity multiplexed with sensors that are able to measure the activity of ERK1/2, p38, JNK, and ERK5 in the same living cell. 3. Use bioinformatics methods to annotate the proteomic datasets and MAPK signaling network analysis for modeling of the MARK network activity and plasticity. Modeling will be used to define MAPK network plasticity and to identify nodes that are critical for plasticity. The models will be experimentally tested in an iterative process with different stimuli, combinations of stimuli and genetic and small molecule perturbation of the MAPK signaling network. 4. Develop small molecule inhibitors of node proteins for use in perturbing network plasticity. The analysis will be tested in cell models where rewiring and dysregulation of the MAPK signaling network is involved in a disease state such as transformation or drug resistance. Relevance to public health: Defining signal network plasticity in this rigorous manner is required for paradigm shifts in our understanding of cell behavior whose dysregulation is at the root of most human diseases that affect people in the western hemisphere. A rigorous definition of signal network plasticity will accelerate the translation of basic discovery to therapeutic intervention of human disease, a stated goal of the NIH mission.