Non-Equilibrium Protein Assembly: from Building Blocks to Biological Machines

ended

A key challenge in biological and soft-matter physics is to identify the principles that govern the organisation and functionality in non-equilibrium systems. Living systems are by definition out of equilibrium and a constant energy input is required to assemble and disassemble the molecular machinery of life. Only out of equilibrium, can proteins assemble to form functional sub-cellular structures, bind cells into dynamic tissues, and form complex biological machines. Our understanding of the physical mechanisms underlying robust protein assembly in driven systems is far from complete. Here I propose to develop a computer-simulation based framework to discover the physical principles of non-equilibrium protein assembly in biological or biomimetic systems. I will focus on systems where chemical gradients and active mechanical forces control protein assembly pathways and morphologies, and in which protein assembly far from equilibrium performs mechanical work. The particular case studies that I will investigate include mechanosensitive protein channels, fibrils of mechanical proteins, and active elastic filaments that remodel cells. As I aim to uncover generic design rules, my simulation model will only retain essential information on the shape and interaction of the assembling proteins needed to capture the complexity of the assembly. Using such minimal models, the simulations will be able to reach experimentally relevant time and length-scales, and will make quantitative predictions, which will be validated against data obtained by my experimental colleagues. The proposed programme will deliver an in-depth understanding of the molecular mechanisms that control the emergence of function in protein assemblies driven far from equilibrium. This knowledge should enable us to program or reprogram assembly phenomena in living organisms, and will provide principles that will guide the design and control of functional biomimetic assemblies and bio-inspired nano-machines.