Tools for Understanding and Controlling the Non-Equilibrium Self-Assembly of Multi-Component Macromolecular Systems

在化学、生物学和工程学中，一些最有趣和最重要的大分子自组装过程发生在几十纳米和秒的长度和时间尺度上，并且经常发生在非平衡条件下。例如，在化学领域，人们正在开发天然和合成纳米孔来分解DNA并读取遗传密码，目标是实现“1000美元基因组”。在生物学中，前沿实验正在探索核糖体分子机制合成过程中蛋白质自组装的基本方面。在工程方面，利用蛋白质和核酸聚合物的智能材料正在开发中，以控制介观结构的组装，以响应溶液条件的变化。因此，理解和控制在这种尺度上发生的软物质自组装过程是极其重要的，因为它将产生科学和经济上的好处。然而，由于这些聚合物的自组装具有复杂的多组分性质，这是一项艰巨的挑战。计算机模拟和基于物理的理论工具为理解自组装和确定控制机制提供了极好的手段。在过去的二十年中，使用全原子模型的计算机模拟有助于我们理解小于纳米和微秒尺度的自组装。然而，这种全原子模型不能达到秒的时间尺度，这是研究几十纳米长度尺度上的自组装所必需的。因此，为了提供对这一机制的分子见解，并帮助指导新的实验和新的智能材料的设计，必须开发保留基本物理原理的适当的粗粒度模型。至关重要的是，虽然传统的研究经常在平衡状态下探测系统，但大多数实际应用涉及非平衡自组装。因此，必须开发新的理论工具来分析和预测非平衡条件下自组装的未探索方面。本提案的主要目的是开发广泛使用的模拟和理论工具，以理解和控制由蛋白质和核酸组成的多组分大分子系统的非平衡自组装。为此，我们将：(1)推广分子自组装的粗粒度模拟模型，使其适用于更广泛的自组装现象；(2)开发新的理论工具来分析和预测非平衡自组装过程。我们将在一个特定的系统上测试这些工具，我们已经有了一个既定的记录，代表了一个多组分自组装的范例-合成过程中的蛋白质折叠。我们将研究在蛋白质生物合成过程中控制有序新生链结构的非平衡获取的物理原理。我们将根据正在进行的非常成功的合作的核磁共振数据验证这些发现，从而测试我们开发的模型的准确性。本提案将为理论家和实验家提供一套有用的工具，以解决涉及化学，生物学和工程领域广泛的自组装系统的重要问题和及时主题。

Some of the most intriguing and important macromolecular self-assembly processes in chemistry, biology, and engineering occur on the length and time scales of tens-of-nanometres and seconds, and often occur under non-equilibrium conditions. For example, in chemistry, natural and synthetic nanopores are being developed to disassemble DNA and read off the genetic code with the goal of reaching the '$1000 genome'. In biology, cutting edge experiments are probing fundamental aspects of protein self-assembly during their synthesis by the ribosome molecular machinery. And in engineering, smart materials that utilize protein and nucleic acid polymers are being developed to control the assembly of mesoscopic structures in response to changes in solution conditions. Therefore, understanding and controlling soft matter self-assembly processes that occur on such scales is extremely important because of the benefits it would yield both scientifically and economically. This is a difficult challenge, however, due to the complex multi-component nature of the self assembly of these polymers. Computer simulations and physics-based theoretical tools offer an excellent means by which to understand self assembly and identify mechanisms to control it. Over the past two decades computer simulations using all-atom models have contributed to our understanding of self assembly on scales less than nanometres and microseconds. However, such all-atom models cannot reach the seconds time scale that is necessary to study self assembly on the tens-of-nanometre length scale. Therefore, to provide molecular insights into this regime and to help guide new experiments and the design of new smart materials, appropriate coarse-grained models that retain the essential physics must be developed. Crucially, while conventional studies often probe systems at equilibrium, most real-world applications involve non-equilibrium self assembly. New theoretical tools must therefore be developed to analyze and predict unexplored aspects of self assembly under non-equilibrium conditions.The primary aim of this proposal is to develop simulation and theoretical tools of broad use to understand and control non-equilibrium self-assembly of multi-component macromolecular systems comprised of proteins and nucleic acids. To do this we will: (1) generalise our coarse-grained simulation model for molecular self-assembly to make it applicable to a much wider class of self-assembly phenomena; and (2) develop new theoretical tools to analyze and predict non-equilibrium self-assembly processes. We will test these tools on a specific system for which we already have an established track record and that represents a paradigm of multi-component self-assembly - protein folding during synthesis. We will investigate the physical principles governing the non-equilibrium acquisition of ordered nascent-chain structure during protein biosynthesis. We will validate these findings against NMR data from an ongoing, highly successful collaboration, and thereby test the accuracy of the models we develop. This proposal will provide a set of tools useful to both theoreticians and experimentalists to address important questions and timely topics involving a broad class of self-assembling systems across the fields of chemistry, biology, and engineering.