Combining Simulation and Spectroscopy to Determine the Structure and Dynamics of Adsorbed Proteins - Application to Biomass Conversion

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Society's ability to engineer new systems for converting renewable resources into useful products is, in many cases, dependent on interfacial processes (e.g., enzymatic conversion of an insoluble polysaccharide). These interfaces are incredibly challenging to study at the atomic scale, with comparatively little success over the last decade in engineering improved systems. Therefore, we propose a collaborative research effort between the University of Washington and the Max Planck Institute for Polymer Research to deeply integrate state of the art multiscale molecular modeling tools with sum frequency generation spectroscopy (SFG). Enzymatic biomass conversion, like many biological processes, is rate-controlled by interfacial phenomena. In the case of biomass conversion, the insoluble cellulose microfibril creates diffusion limitations as the reaction cannot proceed prior to collision and proper alignment/binding. Cellulase enzymes have evolved precise carbohydrate binding modules (CBMs) to provide an increase in concentration of enzyme active sites near the interface, which leads to concomitant rate enhancement. Some CBMs may also promote rates by beneficially altering the microfibril structure. However, due to the general difficulty of studying protein structure at interfaces, only very little is known about the structural basis of specific CBM binding. Questions we ask are: What structural motives are involved in cellulose binding? What amino acids side chains bind the cellulose surface? Successful completion of this research project will lead to a wealth of new fundamental and applied knowledge about interfacial biocatalysis. Specifically, by providing the atomic scale structure and dynamics of the binding module on a cellulose surface we will provide needed insight into the governing kinetic and energetic contributions that give rise to the mechanism of cellulase action. Such information is a precursor for rational engineering studies to improve catalytic rates. More broadly, successful demonstration of our approach to strongly couple molecular simulation and SFG experiments will transform the way researchers investigate biomolecules at interfaces. We believe this work will lead to a general computational/experimental framework for studying interfacial biocatalysis, which does not currently exist.