SGER: Discrete Event Simulation of Self-Assembly Kinetics

卡内基梅隆大学项目摘要：自组装动力学的离散事件模拟这个项目的目标是开发一种新的计算工具来模拟广义的自组装系统。自组装系统由许多小部件或亚单位组成，这些小部件或亚单位在适当的条件下自发地将自己排列成更大的结构。在许多医学上重要的自组装系统中，有病毒蛋白外壳或衣壳，它们在病毒遗传物质周围形成保护层；淀粉样蛋白，与阿尔茨海默氏病、亨廷顿病和普里恩病有关的蛋白质纤维聚集；以及不规则的蛋白质聚集体。对于所有这些系统，人们对组装过程只有部分了解。此外，自组装作为一种在纳米尺度上构建人造设备和材料的手段，最近也引起了人们的兴趣。由于许多自组装过程的小尺寸、速度和复杂性，它们被证明很难进行实验分析。因此，模拟方法已成为洞察自组装过程的重要途径。该项目寻求在该领域先前工作的基础上，通过创建一个足够通用的自组装过程模型来捕获各种自组装系统，同时足够快地在合理的时间内处理真实的模拟尺寸。基本方法论将包括将在先前关于这个问题的建模工作中开发的技术与以前没有用于自组装模拟的计算方法相结合。模拟器将使用很大程度上基于先前的局部规则动力学的自组装动力学模型。模型，该模型根据低级亚基相互作用提供了高级自组装行为的通用表示。它将使用称为离散事件优先级队列的计算数据结构有效地实现。这将允许模拟器在离散状态(例如相互绑定的亚单元)的变化之间步进，而不需要在所有时间步长上显式积分。其结果将是比以前的方法更快地模拟高度通用的自组装模型。该模拟器将用Java实现，以便于开发、可扩展性和可移植性。实施将分不同的阶段进行，致力于开发对象模型(指定计算机代码段如何相互作用)，编码和测试原型模拟器，并最终确定优化的和有良好文档记录的发布质量版本。最终的结果将是一个独立的模拟工具和一组可用于扩展和在其他程序中使用的计算类。这项工作主要需要在自组装过程的数学模型和通过离散事件队列方法对其进行有效模拟的算法方面进行创新。在整合生物物理学、算法、软件工程和用户界面设计等领域的现有知识方面需要进一步创新，以产生一个通用的、易于使用的图形模拟工具。可以预期，该项目将产生几个好处。它的影响将主要集中在自组装领域，通过提供一个通用工具，整个领域的研究人员可以使用该工具来对已知系统进行跨大小和时间尺度的建模，开发新系统的计算原型，并在两者中进行干预试验。它还将通过开发一种新的模拟方法，在计算模拟器中实施，以及对该问题的算法进行优化，为一般生物物理模拟领域提供新的方法和经验。该项目的跨学科性质将通过为计算界提供生物物理系统中发现的问题的新变化，并为生物物理界提供可应用于其他问题的新计算技术，从而加强其影响。这项工作还将具有教育价值，为包括两名本科生在内的学生提供跨学科研究经验，并提供既可用作研究又可用作教学工具的模拟器。

EIA-0320595Russell SchwartzCarnegie Mellon UniversityProject Summary: Discrete Event Simulation of Self-Assembly Kinetics The goal of this project is to develop a novel computational tool for simulating generalized self-assembly systems. Self-assembly systems consist of many small components, or subunits, that spontaneously arrange themselves into larger structures under appropriate conditions. Among the many medically important self-assembly systems are viral protein shells, or capsids, which form protective coats around the genetic material of viruses; amyloids, fibrous agglomerations of proteins that are implicated in Alzheimer.s disease, Huntington.s disease, and the prion diseases; and irregular protein aggregates. For all of these systems, the process of assembly is only partially understood. In addition, self-assembly has attracted recent interest as a means of constructing man-made devices and materials on the nanometer scale. Due to the small size, speed, and complexity of many self-assembly processes, they have proven difficulty to analyze experimentally. Simulation approaches have therefore emerged as a crucial avenue for gaining insight into the self-assembly process. This project seeks to build on the prior work in the area by creating a model of the self-assembly process sufficiently versatile to capture a wide variety of self-assembly systems, yet fast enough to handle realistic simulation sizes in a reasonable time. The basic methodology will involve combining techniques developed in prior modeling work on this problem with a computational method that has not previously been used for self-assembly simulation. The simulator will use a model of self-assembly dynamics based largely on the prior .local rules dynamics. model, which provided a versatile representation of high-level self-assembly behavior in terms of low-level subunit interactions. It will be efficiently implemented using a computational data structure called a .discrete event priority queue,. which will allow the simulator to step between changes in discrete state (such as subunits binding to one another) without the need for explicit integration over all time steps. The result will be faster simulation of a highly general self-assembly model than was possible with prior methods. The simulator will be implemented in Java to facilitate ease of development, extensibility, and portability. Implementation will be conducted through distinct phases devoted to developing an object model (which specifies how pieces of computer code interact with one another), coding and testing a prototype simulator, and finalizing an optimized and well documented release-quality version. The end result will be both a stand-alone simulation tool and a set of computational classes available for extension and use in other programs. This work will require innovation primarily in mathematical models of self-assembly processes and in algorithms for their efficient simulation by a discrete event queue methodology. Further innovation will be needed in the integration of existing knowledge from such areas as biophysics, algorithms, software engineering, and user interface design to produce a versatile, easy-to-use graphical simulation tool. The project can be expected to yield several benefits. Its impact will be primarily on the field of self-assembly, by providing a general tool that can be used by researchers throughout the field for modeling known systems across size and time scales, developing computational prototypes of novel systems, and experimenting with interventions in both. It will also provide new methods and experience to the general field of biophysical simulation through the development of a novel simulation methodology, its implementation in a computational simulator, and optimization of algorithms for this problem. The cross-disciplinary nature of the project will enhance its impact by providing for the computational community new variations on problems to be found in biophysical systems and providing for the biophysics community new computational techniques that can be brought to bear on other problems. The work will also have educational value by providing interdisciplinary research experience to students, including two undergraduates, and by providing a simulator that can be used as both a research and a teaching tool.