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

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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.