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化学反应动力学中小数效应的基序分析。

Motif analysis for small-number effects in chemical reaction dynamics.

作者信息

Saito Nen, Sughiyama Yuki, Kaneko Kunihiko

机构信息

Research Center for Complex Systems Biology, Graduate School of Arts and Sciences, The University of Tokyo, 3-8-1 Komaba, Meguro-ku, Tokyo 153-8902, Japan.

Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan.

出版信息

J Chem Phys. 2016 Sep 7;145(9):094111. doi: 10.1063/1.4961675.

Abstract

The number of molecules involved in a cell or subcellular structure is sometimes rather small. In this situation, ordinary macroscopic-level fluctuations can be overwhelmed by non-negligible large fluctuations, which results in drastic changes in chemical-reaction dynamics and statistics compared to those observed under a macroscopic system (i.e., with a large number of molecules). In order to understand how salient changes emerge from fluctuations in molecular number, we here quantitatively define small-number effect by focusing on a "mesoscopic" level, in which the concentration distribution is distinguishable both from micro- and macroscopic ones and propose a criterion for determining whether or not such an effect can emerge in a given chemical reaction network. Using the proposed criterion, we systematically derive a list of motifs of chemical reaction networks that can show small-number effects, which includes motifs showing emergence of the power law and the bimodal distribution observable in a mesoscopic regime with respect to molecule number. The list of motifs provided herein is helpful in the search for candidates of biochemical reactions with a small-number effect for possible biological functions, as well as for designing a reaction system whose behavior can change drastically depending on molecule number, rather than concentration.

摘要

参与细胞或亚细胞结构的分子数量有时相当少。在这种情况下,普通的宏观层面波动可能会被不可忽略的大幅波动所掩盖,这导致与宏观系统(即分子数量众多)下观察到的化学反应动力学和统计学相比发生剧烈变化。为了理解分子数量波动如何产生显著变化,我们在此通过关注“介观”层面来定量定义小数量效应,在该层面浓度分布既不同于微观层面也不同于宏观层面,并提出一个标准来确定在给定的化学反应网络中是否会出现这种效应。使用所提出的标准,我们系统地推导了可能显示小数量效应的化学反应网络基序列表,其中包括在介观体系中相对于分子数量可观察到的幂律和双峰分布出现的基序。本文提供的基序列表有助于寻找具有小数量效应以实现可能生物学功能的生化反应候选物,以及设计一种反应系统,其行为可根据分子数量而非浓度发生剧烈变化。

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