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三维随机无格点模型在拥挤环境中的结合化学。

Three-dimensional stochastic off-lattice model of binding chemistry in crowded environments.

机构信息

Department of Biological Sciences and Lane Center for Computational Biology, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.

出版信息

PLoS One. 2012;7(1):e30131. doi: 10.1371/journal.pone.0030131. Epub 2012 Jan 17.

Abstract

Molecular crowding is one of the characteristic features of the intracellular environment, defined by a dense mixture of varying kinds of proteins and other molecules. Interaction with these molecules significantly alters the rates and equilibria of chemical reactions in the crowded environment. Numerous fundamental activities of a living cell are strongly influenced by the crowding effect, such as protein folding, protein assembly and disassembly, enzyme activity, and signal transduction. Quantitatively predicting how crowding will affect any particular process is, however, a very challenging problem because many physical and chemical parameters act synergistically in ways that defy easy analysis. To build a more realistic model for this problem, we extend a prior stochastic off-lattice model from two-dimensional (2D) to three-dimensional (3D) space and examine how the 3D results compare to those found in 2D. We show that both models exhibit qualitatively similar crowding effects and similar parameter dependence, particularly with respect to a set of parameters previously shown to act linearly on total reaction equilibrium. There are quantitative differences between 2D and 3D models, although with a generally gradual nonlinear interpolation as a system is extended from 2D to 3D. However, the additional freedom of movement allowed to particles as thickness of the simulation box increases can produce significant quantitative change as a system moves from 2D to 3D. Simulation results over broader parameter ranges further show that the impact of molecular crowding is highly dependent on the specific reaction system examined.

摘要

分子拥挤是细胞内环境的特征之一,由各种不同种类的蛋白质和其他分子的密集混合物定义。与这些分子的相互作用显著改变了拥挤环境中化学反应的速率和平衡。许多生命细胞的基本活动都受到拥挤效应的强烈影响,如蛋白质折叠、蛋白质组装和拆卸、酶活性和信号转导。然而,定量预测拥挤将如何影响任何特定过程是一个非常具有挑战性的问题,因为许多物理和化学参数以协同方式作用,难以进行简单分析。为了解决这个问题,我们将先前的二维(2D)无格点随机模型扩展到三维(3D)空间,并研究了 3D 结果与 2D 结果的比较。结果表明,两种模型都表现出类似的拥挤效应和相似的参数依赖性,特别是对于一组先前被证明对总反应平衡呈线性作用的参数。2D 和 3D 模型之间存在定量差异,尽管随着系统从 2D 扩展到 3D,存在一般的渐变非线性插值。然而,随着模拟盒厚度的增加,粒子的自由度增加可以在系统从 2D 移动到 3D 时产生显著的定量变化。在更广泛的参数范围内的模拟结果进一步表明,分子拥挤的影响高度取决于所研究的特定反应系统。

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