Signaling through receptors and scaffolds: Independent interactions reduce combinatorial complexity
Signaling through receptors and scaffolds: Independent interactions reduce combinatorial complexity
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DOI：
10.1529/biophysj.105.060533
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发表时间：
2005-08-01
影响因子：
3.4
通讯作者：
Kholodenko, BN
中科院分区：
文献类型：
--
作者：
Borisov, NM;Markevich, NI;Kholodenko, BN
活化后，许多受体和它们的衔接蛋白充当支架，展示许多对接位点并接合多个靶标。随之而来的各种蛋白质复合物的组装导致呈现不同状态的受体-支架信号传导模块的可行分子种类的数量的组合增加。即使对于最初的信号传播事件，也会出现数万个这样的微观状态，这极大地阻碍了网络的定量分析。在这里，我们证明了在不同位点发生的分子事件的独立性的假设使我们能够通过对单独结构域的状态的宏观描述来近似所有可能的微观状态的机械图，即，对应于实验验证的宏观状态。able变量该分析将一个高度分支的网络解剖成相互作用的通路，这些通路由在受体和支架的不同位点上组装的蛋白质复合物产生。我们指定的时间动态的任何给定的微观状态可以表示使用产品的相对浓度的各个网站。这里提出的方法同样适用于确定性和随机计算的时间动态。我们的领域为导向的方法大大减少了数量的状态，过程和动力学参数被认为是quanti。传播不同生理反应的复杂信号网络的阳离子。
After activation, many receptors and their adaptor proteins act as scaffolds displaying numerous docking sites and engaging multiple targets. The consequent assemblage of a variety of protein complexes results in a combinatorial increase in the number of feasible molecular species presenting different states of a receptor-scaffold signaling module. Tens of thousands of such microstates emerge even for the initial signal propagation events, greatly impeding a quantitative analysis of networks. Here, we demonstrate that the assumption of independence of molecular events occurring at distinct sites enables us to approximate a mechanistic picture of all possible microstates by a macrodescription of states of separate domains, i.e., macrostates that correspond to experimentally veri. able variables. This analysis dissects a highly branched network into interacting pathways originated by protein complexes assembled on different sites of receptors and scaffolds. We specify when the temporal dynamics of any given microstate can be expressed using the product of the relative concentrations of individual sites. The methods presented here are equally applicable to deterministic and stochastic calculations of the temporal dynamics. Our domain-oriented approach drastically reduces the number of states, processes, and kinetic parameters to be considered for quanti. cation of complex signaling networks that propagate distinct physiological responses.