Actin Automata: Phenomenology and Localizations
Actin Automata: Phenomenology and Localizations
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DOI：
10.1142/s0218127415500303
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发表时间：
2015-02-01
影响因子：
2.2
通讯作者：
Mayne, Richard
中科院分区：
文献类型：
--
作者：
Adamatzky, Andrew;Mayne, Richard
肌动蛋白是一种在真核细胞骨架中形成长丝的球状蛋白，其在细胞功能中的作用包括对细胞内信号的结构支持、收缩活动。我们将肌动蛋白细丝建模为两个一维二态半全自动机阵列的链，以描述其中的假设信号事件。肌动蛋白自动机的每个节点都处于状态“0”(休息)或“1”(兴奋)，并根据其邻居的状态以离散时间更新其状态。我们利用这些规则生成的时空构型的整体特征，分析了动作自动机的完整规则空间，并计算出支持移动和移动局部化的状态转移规则。概述了利用全局特征选择本地化支持规则的方法。我们发现，肌动蛋白自动机规则的一些性质可以用Shannon熵、活性和高分子链之间的激发不一致性来预测。我们还表明，通过观察对几代局部化至关重要的兴奋邻居的比率，可以推断给定规则是否支持行进或静止的局部化。最后，我们将生物分子假说应用到这个模型中，并讨论了我们的发现在细胞信号和细胞计算中紧急行为方面的意义。
Actin is a globular protein which forms long filaments in the eukaryotic cytoskeleton, whose roles in cell function include structural support, contractile activity to intracellular signaling. We model actin filaments as two chains of one-dimensional binary-state semi-totalistic automaton arrays to describe hypothetical signaling events therein. Each node of the actin automaton takes state "0" (resting) or "1" (excited) and updates its state in discrete time depending on its neighbor's states. We analyze the complete rule space of actin automata using integral characteristics of space-time configurations generated by these rules and compute state transition rules that support traveling and mobile localizations. Approaches towards selection of the localization supporting rules using the global characteristics are outlined. We find that some properties of actin automata rules may be predicted using Shannon entropy, activity and incoherence of excitation between the polymer chains. We also show that it is possible to infer whether a given rule supports traveling or stationary localizations by looking at ratios of excited neighbors that are essential for generations of the localizations. We conclude by applying biomolecular hypotheses to this model and discuss the significance of our findings in context with cell signaling and emergent behavior in cellular computation.