Marquez-Lago Tatiana T, Burrage Kevin
Advanced Computational Modeling Centre, The University of Queensland, Brisbane QLD 4072, Australia.
J Chem Phys. 2007 Sep 14;127(10):104101. doi: 10.1063/1.2771548.
In cell biology, cell signaling pathway problems are often tackled with deterministic temporal models, well mixed stochastic simulators, and/or hybrid methods. But, in fact, three dimensional stochastic spatial modeling of reactions happening inside the cell is needed in order to fully understand these cell signaling pathways. This is because noise effects, low molecular concentrations, and spatial heterogeneity can all affect the cellular dynamics. However, there are ways in which important effects can be accounted without going to the extent of using highly resolved spatial simulators (such as single-particle software), hence reducing the overall computation time significantly. We present a new coarse grained modified version of the next subvolume method that allows the user to consider both diffusion and reaction events in relatively long simulation time spans as compared with the original method and other commonly used fully stochastic computational methods. Benchmarking of the simulation algorithm was performed through comparison with the next subvolume method and well mixed models (MATLAB), as well as stochastic particle reaction and transport simulations (CHEMCELL, Sandia National Laboratories). Additionally, we construct a model based on a set of chemical reactions in the epidermal growth factor receptor pathway. For this particular application and a bistable chemical system example, we analyze and outline the advantages of our presented binomial tau-leap spatial stochastic simulation algorithm, in terms of efficiency and accuracy, in scenarios of both molecular homogeneity and heterogeneity.
在细胞生物学中，细胞信号通路问题通常采用确定性时间模型、均相随机模拟器和/或混合方法来解决。但实际上，为了全面理解这些细胞信号通路，需要对细胞内发生的反应进行三维随机空间建模。这是因为噪声效应、低分子浓度和空间异质性都会影响细胞动力学。然而，有一些方法可以在不使用高分辨率空间模拟器（如单粒子软件）的情况下考虑重要效应，从而显著减少总体计算时间。我们提出了一种新的粗粒度改进版的下一个子体积方法，与原始方法和其他常用的完全随机计算方法相比，该方法允许用户在相对较长的模拟时间跨度内同时考虑扩散和反应事件。通过与下一个子体积方法和均相模型（MATLAB）以及随机粒子反应和传输模拟（CHEMCELL，桑迪亚国家实验室）进行比较，对模拟算法进行了基准测试。此外，我们基于表皮生长因子受体通路中的一组化学反应构建了一个模型。对于这个特定的应用和一个双稳化学系统示例，我们在分子均一性和异质性的场景下，从效率和准确性方面分析并概述了我们提出的二项式τ跳跃空间随机模拟算法的优点。
