Large Scale Lattice Boltzmann for Biocolloidal Systems

用于生物胶体系统的大规模格子玻尔兹曼

• 批准号: EP/I034602/1
• 负责人: Peter Coveney
• 金额: $ 66.17万
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2012
• 资助国家: 英国
• 起止时间: 2012 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FI034602%2F1
• 关键词: Large; Scale; Lattice; Boltzmann; Biocolloidal

Many of the most important structural components of biological materials exist on length scales of nanometres to microns. Examples include long polymers (such as DNA or flexible proteins), compact objects such as globular proteins (either in isolation or in structured assemblies such as the body of a virus); and lipid bilayer membranes (such as the walls that enclose the cells in our bodies). This range of length-scales is known as the colloidal domain. It is one where physical processes can be at least as important as biochemical ones; for instance, inside every cell, there are 'regulatory' proteins which have to search the genome (DNA) seeking preferential places of attachment (from which they then control the production of other proteins). To find these places, the regulatory proteins depend, at least in part, on the completely random motion, called Brownian motion, that occurs when particles on the colloidal scale are bombarded by the thermal energy of the surrounding solvent (water) molecules. This diffusive process is considerably complicated by the fact that motion of one colloidal object sets the surrounding solvent into motion, which causes all nearby objects also to move. This is referred to as a hydrodynamic interaction. Similarly, if one designs a drug delivery system in which drug molecules are encapsulated, the capsules are again on the colloidal scale but their motion in the bloodstream is dominated by their being swept along by the flow of blood, which is another form of hydrodynamic effect. In some modern therapies, magnetic colloids are steered with or against this flow by an external field; in such cases it is important to understand the effect of hydrodynamics on the response to a force.The physical consequences of hydrodynamic couplings in bio-colloidal systems are thus wide ranging. However, it is currently very difficult to predict any of these important effects, even using simplified models in which the biochemical detail of the colloidal objects is omitted. Fortunately, such problems can increasingly be addressed using very large scale computer simulation on some of the world's most powerful computers. The so-called lattice Boltzmann algorithm (LB) offers a specific technical solution to the challenges of hydrodynamics, by using a discrete lattice to model the flow of fluid from place to place. Unlike some other methods it can include the random forces responsible for Brownian motion. Also, as well as modelling colloids and polymers surrounded by simple solvents such as water, LB can also address solvents comprising complex fluids. The latter include the so-called 'amphiphilic mesophases' in which small molecules (with a water-loving head and water-hating tail) self-assemble into a labyrinth within which proteins or nanocolloids can reside. We aim to develop LB algorithms in the bio-colloidal context, and apply these to create new scientific knowledge that has been out of reach until now. Indeed we plan very large simulations of a range of hydrodynamic problems that lie at the interface between physics and the life sciences. These problems include: the flow of magnetic colloids in the blood stream as a model for 'Magnetic Drug Targetting' (MDT) on real patients; the motion of nanocolloids within amphiphilic mesophases suitable for drug delivery applications; the ejection of DNA from the body of a virus as it infects a cell; the dynamical behaviour of the highly confined DNA that is found within the bacterial and other cells; and the interaction between colloidal particles and DNA within the cellular environment. The last of these topics is crucial to understanding the problem of genome exploration by regulatory proteins as mentioned earlier, which we also plan to address. In all these areas, large-scale computer simulation has the potential to change the way science is done. We hope to establish a world lead for the UK in this emerging field.

生物材料的许多最重要的结构成分存在于纳米到微米的长度尺度上。例子包括长的聚合物（如DNA或柔性蛋白质），紧凑的物体，如球状蛋白质（无论是在隔离或在结构组装，如病毒的身体）;和脂质双层膜（如在我们的身体包围细胞的墙壁）。这个长度范围被称为胶体域。这是一个物理过程至少可以与生物化学过程一样重要的过程;例如，在每个细胞内，都有“调节”蛋白质，它们必须搜索基因组（DNA），寻找优先附着的位置（然后它们控制其他蛋白质的生产）。为了找到这些位置，调节蛋白至少部分依赖于完全随机的运动，称为布朗运动，当胶体尺度上的颗粒受到周围溶剂（水）分子的热能轰击时，就会发生这种运动。这个扩散过程相当复杂，因为一个胶体物体的运动会使周围的溶剂运动，从而导致所有附近的物体也运动。这被称为流体动力学相互作用。类似地，如果设计药物分子被封装在其中的药物递送系统，则胶囊再次处于胶体尺度上，但是它们在血流中的运动由它们被血流沿着扫过所支配，这是另一种形式的流体动力学效应。在一些现代疗法中，磁性胶体通过外部场与这种流动一起或相反地被操纵;在这种情况下，重要的是要理解流体动力学对力的响应的影响。因此，生物胶体系统中的流体动力学耦合的物理后果是广泛的。然而，目前很难预测任何这些重要的影响，即使使用简化的模型，其中的胶体物体的生化细节被省略。幸运的是，这些问题可以越来越多地使用非常大规模的计算机模拟在世界上最强大的计算机上解决。所谓的格子玻尔兹曼算法（LB）通过使用离散格子来模拟流体从一个地方到另一个地方的流动，为流体动力学的挑战提供了一个特定的技术解决方案。与其他一些方法不同，它可以包括布朗运动的随机力。此外，除了模拟被简单溶剂（如水）包围的胶体和聚合物外，LB还可以处理包含复杂流体的溶剂。后者包括所谓的“两亲性中间相”，其中小分子（具有喜水的头部和讨厌水的尾部）自组装成蛋白质或纳米胶体可以驻留的迷宫。我们的目标是在生物胶体背景下开发LB算法，并应用这些算法来创造迄今为止尚无法获得的新科学知识。事实上，我们计划非常大的一系列流体力学问题，位于物理学和生命科学之间的接口模拟。这些问题包括：作为真实的患者的“磁性药物靶向”（MDT）模型的磁性胶体在血流中的流动;适于药物递送应用的两亲性中间相内的纳米胶体的运动;当病毒感染细胞时DNA从病毒体中的排出;在细菌和其它细胞内发现的高度受限的DNA的动力学行为;以及细胞环境中胶体颗粒和DNA之间的相互作用。这些主题中的最后一个对于理解前面提到的调节蛋白的基因组探索问题至关重要，我们也计划解决这个问题。在所有这些领域，大规模计算机模拟都有可能改变科学研究的方式。我们希望在这一新兴领域为英国建立世界领先地位。

项目成果

Uncertainty Quantification in Alchemical Free Energy Methods.

• DOI: 10.1021/acs.jctc.7b01143
• 发表时间: 2018-06-12
• 期刊: Journal of chemical theory and computation
• 影响因子: 5.5
• 作者: Bhati AP;Wan S;Hu Y;Sherborne B;Coveney PV
• 通讯作者: Coveney PV

Characterization of parafoveal hemodynamics associated with diabetic retinopathy with adaptive optics scanning laser ophthalmoscopy and computational fluid dynamics.

• DOI: 10.1109/embc.2015.7320266
• 发表时间: 2015-08
• 期刊: Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
• 作者: Bernabeu MO;Yang Lu;Lammer J;Aiello LP;Coveney PV;Sun JK
• 通讯作者: Sun JK

Distributed multiscale computing with MUSCLE 2, the Multiscale Coupling Library and Environment

• DOI: 10.1016/j.jocs.2014.04.004
• 发表时间: 2014-09-01
• 期刊: JOURNAL OF COMPUTATIONAL SCIENCE
• 影响因子: 3.3
• 作者: Borgdorff, J.;Mamonski, M.;Hoekstra, A. G.
• 通讯作者: Hoekstra, A. G.

An Ensemble-Based Protocol for the Computational Prediction of Helix-Helix Interactions in G Protein-Coupled Receptors using Coarse-Grained Molecular Dynamics.

• DOI: 10.1021/acs.jctc.6b01246
• 发表时间: 2017-05-09
• 期刊: Journal of chemical theory and computation
• 影响因子: 5.5
• 作者: Altwaijry NA;Baron M;Wright DW;Coveney PV;Townsend-Nicholson A
• 通讯作者: Townsend-Nicholson A

Performance of distributed multiscale simulations.

• DOI: 10.1098/rsta.2013.0407
• 发表时间: 2014-08-06
• 期刊: Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
• 作者: Borgdorff J;Ben Belgacem M;Bona-Casas C;Fazendeiro L;Groen D;Hoenen O;Mizeranschi A;Suter JL;Coster D;Coveney PV;Dubitzky W;Hoekstra AG;Strand P;Chopard B
• 通讯作者: Chopard B