基于细胞Rho家族gtp酶调控的串链磷酸化和去磷酸化途径的可扩展生物分子计算机

Jian-Qin Liu, K. Shimohara
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引用次数: 0

摘要

活细胞是构建用于大规模并行计算的纳米生物机器的最有前途的功能材料之一,基于此,我们提出了一种新的生物分子计算方法,该方法基于活细胞中激酶和磷酸盐开关的磷酸化和去磷酸化信号通路,并由Rho家族gtpase的上游通路调节,这种方法不同于DNA计算机的Adleman-Lipton范式。这种基于Rho家族GTPases的生物分子计算过程的两个主要优点是,当为生物分子计算机的工程路径单元设计一定的路径控制器时,细胞路径控制的成本低,相关计算过程的效率高。在本文中,我们报告了在Rho家族GTPases调控下设计实验可行的细胞工程通路算子和相关计算机体系结构的最新成果,用于生物分子计算机解决大规模基准问题,其中通路之间的串扰过程,下游和上游通路之间的反馈以及与细胞核受体的相互作用。这是基于活细胞形式的Rho家族gtpase信号通路的计算纳米生物机器的实验实现的先决条件,当通路的相互作用等级在整个细胞的规模上进行调节时,它可以减少工程通路的受控分子数量的成本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On Scalable Biomolecular Computers Based on Crosstalked Phosphorylation and Dephosphorylation Pathways Regulated by Rho Family GTPases of Cells
Based on the living cell, which is one of the most promising functional materials for building nanobiomachines for massively parallel computation, we propose a new biomolecular computing method based on the signaling pathways of phosphorylation and dephosphorylation switched by kinases and phosphates and regulated by upstream pathways of Rho family GTPases in living cells, a method that differs from the Adleman-Lipton paradigm of DNA computers. The two main merits of this type of biomolecular computing process based on Rho family GTPases are the low cost of pathway control for cells and the high efficiency of the related computing processes, when certain pathway controllers are designed for the engineered pathway units of biomolecular computers. In this paper, we report our latest results on designing experimentally feasible operators and the related computer architecture of the engineered pathways in cells under the regulation of Rho family GTPases for solving large-scale benchmark problems by biomolecular computers, where the crosstalking processes among the pathways, feedback between the downstream and upstream pathways, and interaction with the nuclear receptors of cells are employed. This is a prerequisite for experimental implementation of a computing nanobiomachine based on the signaling pathways of Rho family GTPases in the form of living cells, which can cut costs in the number of controlled molecules for engineered pathways when the interaction ratings of pathways is regulated on the scale of an entire cell.
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