Rousseau Frederic, Schymkowitz Joost
Switch Laboratory, VIB (Flemish Interuniversity Institute of Biotechnology), Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium.
Curr Opin Struct Biol. 2005 Feb;15(1):23-30. doi: 10.1016/j.sbi.2005.01.007.
The functional dynamics of signal transduction through protein interaction networks are determined both by network topology and by the signal processing properties of component proteins. In order to understand the emergent properties of signal transduction networks in terms of information processing, storage and decision making, we not only need to map the so-called 'interactome' but, perhaps more importantly, we also have to understand how the structural dynamics of constituent proteins shape non-linear responses through cooperativity and allostery. Several in silico methods have been developed to identify networks of cooperative residues in proteins and help infer their mode of action. Applying this type of analysis to important classes of modular signal transduction domains should, in principle, allow the function of these proteins to be abstracted in terms of their information processing characteristics, permitting better comprehension of the systemic properties of biological networks.
通过蛋白质相互作用网络进行信号转导的功能动力学,既由网络拓扑结构决定,也由组成蛋白的信号处理特性决定。为了从信息处理、存储和决策方面理解信号转导网络的涌现特性,我们不仅需要绘制所谓的“相互作用组”,而且或许更重要的是,我们还必须了解组成蛋白的结构动力学如何通过协同性和别构作用形成非线性反应。已经开发了几种计算机模拟方法来识别蛋白质中协同残基的网络,并帮助推断其作用模式。原则上,将这类分析应用于重要的模块化信号转导结构域类别,应该能够根据其信息处理特征来抽象这些蛋白质的功能,从而更好地理解生物网络的系统特性。