Multiscale Ensemble Computing for Modelling Biological Catalysts

该项目的目标是利用HPCx上可获得的灵活的HPC资源，对脂肪酸酰胺水解酶（FAAH）催化的化学反应机制进行详细的研究，FAAH是药物开发的重要靶点。高性能计算资源越来越有助于阐明和分析生物“分子机器”的基本机制。酶催化就是一个例子。酶是非常有效的天然催化剂。了解它们的工作原理是实现利用它们的力量用于工业和制药应用的目标的重要的第一步。例如，许多药物通过阻止酶的功能起作用。酶催化反应的原子细节计算机模型提供了对酶的能量来源的深入了解。由于生物分子的大尺寸，原子相互作用的简化经典模型被使用。这些分子力学（MM）模型已被成功地用于理解蛋白质的分子动力学。然而，MM只能提供一个低质量的化学反应模型，因为电子是隐式表示的。量子力学（QM）提供了质量最好的化学模型。QM计算的计算成本很高，因此求解整个酶系统的QM模型将具有挑战性。一种解决方案是使用多尺度方法，将酶的反应区域的QM表示嵌入到系统其余部分的MM模型中。生物系统的多级模拟在高性能计算资源上可用的许多处理器上很难扩展。新的多尺度建模方法(4)将单个计算分解为松散耦合模拟的集合，因此是利用最大计算能力的有希望的新方向。其目的是通过将多个单独的模拟有效地耦合到一个超级模拟中，从而充分利用大量的处理器。这种方法应用于HPC资源，有望导致酶催化反应建模质量的一步改变，并将为这些非凡的生物分子提供新的见解。

The goal of this project is to use the flexible HPC resource made available on HPCx to perform a detailed investigation of the mechanism of chemical reactions catalysed by the enzyme fatty acid amide hydrolase (FAAH), an important target for drug development. HPC resources are increasingly helping to illuminate and analyse the fundamental mechanisms of biological 'molecular machines'. An example is enzyme catalysis. Enzymes are very efficient natural catalysts. Understanding how they work is a vital first step to the goal of harnessing their power for industrial and pharmaceutical applications. For example, many drugs work by stopping enzymes from functioning.Atomically detailed computer models of enzyme-catalysed reactions provide an insight into the source of an enzyme's power. Due to the large size of biological molecules, simplified classical models of atomic interactions are used. These molecular mechanics (MM) models have been used successfully to understand the molecular dynamics of proteins. However, MM can provide only a low-quality model of a chemical reaction, as electrons are represented implicitly. The best quality chemical models are provided by quantum mechanics (QM). QM calculations are highly computationally expensive, so it would be challenging to solve a QM model of an entire enzyme system. One solution is to use multiscale methods that embed a QM representation of the reactive region of the enzyme within an MM model of the rest of the system. Multilevel simulations of biological systems scale poorly over the many processors available on an HPC resource. New multiscale modelling methods(4) that split a single calculation into an ensemble of loosely-coupled simulations, are therefore a promising new direction to utilize maximum computingpower. The aim is to make best use of the large numbers of processors by effectively coupling multiple individual simulations into a single supra-simulation. This method, applied on an HPC resource, promises to lead to a step change in the quality of the modelling of enzyme-catalysed reactions, and will provide new insights into these remarkable biological molecules.