Chinese Academy of Sciences, Max Plank Society Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Shanghai, People's Republic of China.
IET Syst Biol. 2010 Nov;4(6):453-66. doi: 10.1049/iet-syb.2010.0015.
The authors propose a theoretical formalism, molecular finite automata (MFA), to describe individual proteins as rule-based computing machines. The MFA formalism provides a framework for modelling individual protein behaviours and systems-level dynamics via construction of programmable and executable machines. Models specified within this formalism explicitly represent the context-sensitive dynamics of individual proteins driven by external inputs and represent protein-protein interactions as synchronised machine reconfigurations. Both deterministic and stochastic simulations can be applied to quantitatively compute the dynamics of MFA models. They apply the MFA formalism to model and simulate a simple example of a signal-transduction system that involves an MAP kinase cascade and a scaffold protein.
作者提出了一种理论形式主义,即分子有限自动机(MFA),将个体蛋白质描述为基于规则的计算机器。MFA 形式主义为通过构建可编程和可执行的机器来模拟个体蛋白质行为和系统级动力学提供了一个框架。在此形式主义中指定的模型明确表示由外部输入驱动的个体蛋白质的上下文敏感动力学,并将蛋白质-蛋白质相互作用表示为同步机器重新配置。确定性和随机模拟都可以应用于定量计算 MFA 模型的动力学。他们应用 MFA 形式主义来对涉及 MAP 激酶级联和支架蛋白的信号转导系统的一个简单示例进行建模和模拟。