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一种用于模拟细胞内拥挤系统中扩散的格子玻尔兹曼方法。

A Lattice-Boltzmann scheme for the simulation of diffusion in intracellular crowded systems.

作者信息

Angeles-Martinez Liliana, Theodoropoulos Constantinos

机构信息

School of Chemical Engineering and Analytical Science, University of Manchester, Manchester, M13 9PL, UK.

出版信息

BMC Bioinformatics. 2015 Nov 3;16:353. doi: 10.1186/s12859-015-0769-8.

Abstract

BACKGROUND

The intracellular environment is a complex and crowded medium where the diffusion of proteins, metabolites and other molecules can be decreased. One of the most popular methodologies for the simulation of diffusion in crowding systems is the Monte Carlo algorithm (MC) which tracks the movement of each particle. This can, however, be computationally expensive for a system comprising a large number of molecules. On the other hand, the Lattice Boltzmann Method (LBM) tracks the movement of collections of molecules, which represents significant savings in computational time. Nevertheless in the classical manifestation of such scheme the crowding conditions are neglected.

METHODS

In this paper we use Scaled Particle Theory (SPT) to approximate the probability to find free space for the displacement of hard-disk molecules and in this way to incorporate the crowding effect to the LBM. This new methodology which couples SPT and LBM is validated using a kinetic Monte Carlo (kMC) algorithm, which is used here as our "computational experiment".

RESULTS

The results indicate that LBM over-predicts the diffusion in 2D crowded systems, while the proposed coupled SPT-LBM predicts the same behaviour as the kinetic Monte Carlo (kMC) algorithm but with a significantly reduced computational effort. Despite the fact that small deviations between the two methods were observed, in part due to the mesoscopic and microscopic nature of each method, respectively, the agreement was satisfactory both from a qualitative and a quantitative point of view.

CONCLUSIONS

A crowding-adaptation to LBM has been developed using SPT, allowing fast simulations of diffusion-systems of different size hard-disk molecules in two-dimensional space. This methodology takes into account crowding conditions; not only the space fraction occupied by the crowder molecules but also the influence of the size of the crowder which can affect the displacement of molecules across the lattice system.

摘要

背景

细胞内环境是一个复杂且拥挤的介质,蛋白质、代谢物和其他分子在其中的扩散可能会减慢。模拟拥挤系统中扩散的最常用方法之一是蒙特卡罗算法(MC),它跟踪每个粒子的运动。然而,对于包含大量分子的系统,这在计算上可能成本很高。另一方面,格子玻尔兹曼方法(LBM)跟踪分子集合的运动,这在计算时间上有显著节省。然而,在这种方案的经典表现形式中,拥挤条件被忽略了。

方法

在本文中,我们使用尺度粒子理论(SPT)来近似硬磁盘分子位移时找到自由空间的概率,从而将拥挤效应纳入LBM。这种将SPT和LBM相结合的新方法使用动力学蒙特卡罗(kMC)算法进行了验证,这里将其用作我们的“计算实验”。

结果

结果表明,LBM在二维拥挤系统中过度预测了扩散,而提出的耦合SPT-LBM预测的行为与动力学蒙特卡罗(kMC)算法相同,但计算量显著减少。尽管观察到两种方法之间存在小的偏差,部分原因分别是每种方法的介观和微观性质,但从定性和定量的角度来看,一致性都令人满意。

结论

利用SPT开发了一种适用于LBM的拥挤适应方法,能够快速模拟二维空间中不同大小硬磁盘分子的扩散系统。这种方法考虑了拥挤条件;不仅考虑了拥挤分子占据的空间分数,还考虑了拥挤分子大小的影响,这可能会影响分子在晶格系统中的位移。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c15/4632338/e320cf3837b1/12859_2015_769_Fig1_HTML.jpg

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