Large Scale Lattice Boltzmann for Biocolloidal Systems

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。例子包括长聚合物（如DNA或柔性蛋白质）、致密物体，如球状蛋白质（要么是孤立的，要么是结构组装的，如病毒体）；以及脂质双分子膜（如我们体内包裹细胞的壁）。这个长度范围被称为胶体域。在这个过程中，物理过程至少可以和生化过程一样重要；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），寻找优先的附着位置（然后它们控制其他蛋白质的产生）。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，当胶体尺度上的粒子受到周围溶剂（水）分子的热能轰击时，这种运动就会发生。这个扩散过程相当复杂，因为一个胶体物体的运动会引起周围溶剂的运动，从而引起附近所有物体的运动。这被称为水动力相互作用。类似地，如果一个人设计了一个药物输送系统，其中药物分子被包裹起来，胶囊还是在胶体尺度上，但它们在血液中的运动是由它们被血流冲走所控制的，这是另一种形式的流体动力学效应。在一些现代疗法中，磁性胶体通过一个外场来引导或反对这种流动；在这种情况下，理解流体力学对力响应的影响是很重要的。因此，生物胶体系统中流体动力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，其中省略了胶体物体的生化细节。幸运的是，这些问题可以越来越多地通过世界上一些最强大的计算机上的大规模计算机模拟来解决。所谓的晶格玻尔兹曼算法（LB）通过使用离散晶格来模拟流体从一个地方到另一个地方的流动，为流体力学的挑战提供了一种特殊的技术解决方案。与其他一些方法不同，它可以包括导致布朗运动的随机力。此外，除了模拟被水等简单溶剂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“亲水中间相”，在这种中间相中，小分子（头部亲水，尾部憎水）自我组装成一个迷宫，蛋白质或纳米胶体可以在迷宫中生存。我们的目标是在生物胶体环境中开发LB算法，并应用这些算法来创造迄今为止遥不可及的新科学知识。事实上，我们计划对一系列流体力学问题进行非常大规模的模拟，这些问题位于物理学和生命科学之间的界面。这些问题包括：磁性胶体在血液中的流动，作为对真实患者进行“磁性药物靶向”（MDT）的模型；纳米胶体在适合药物输送应用的两亲性中间相中的运动；当病毒感染细胞时，从病毒体内排出DNA；在细菌和其他细胞中发现的高度受限的DNA的动态行为；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通过调控蛋白进行基因组探索的问题至关重要，我们也计划解决这个问题。在所有这些领域，大规模计算机模拟有可能改变科学研究的方式。我们希望英国在这一新兴领域处于世界领先地位。

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.