(254d) Computational Insights into the Catalytic Function of Processive Cellulases | AIChE

(254d) Computational Insights into the Catalytic Function of Processive Cellulases


Knott, B. C. - Presenter, National Renewable Energy Laboratory
Ståhlberg, J., Swedish University of Agricultural Sciences
Beckham, G., National Renewable Energy Laboratory
Crowley, M. F., National Renewable Energy Laboratory
Vermaas, J., National Renewable Energy Laboratoray
Cellulase enzymes naturally produced by fungi and bacteria are utilized industrially for many purposes, including the production of clean sugar streams from biomass that can be subsequently upgraded to fuels, chemicals, and products. The development of structure-function relationships in these enzymes is a collaborative effort between biochemical experimentation, structural characterization, and computational simulation. Here, we detail recent success stories from our group wherein molecular simulations are able to provide mechanistic insight with atomistic and dynamic resolution not generally attainable via experiment. In the present contribution, we probe different mechanisms for how a processive cellulase may dissociate from a cellulose chain on the surface of cellulose. Under certain conditions, dissociation from a cellulose strand has been demonstrated to be the overall rate-limiting step of catalytic action for cellobiohydrolases. Despite the growing evidence to support this conclusion, the literature is largely silent on the question of how dissociation occurs. In the published literature, “dissociation” is defined purely by the beginning (complexed upon a cellulose strand with the complete binding tunnel occupied) and the end (enzyme binding tunnel empty, and perhaps also “lifted off” of the cellulose surface into solution) states of the process. However, several possibilities exist for how the enzyme may proceed from the former to the latter state. Given the importance of this process within the context of cellulase performance (and thus potential cellulase engineering), we formulate several paths for this process (utilizing Trichoderma reesei Cel7A) and then compute free energy profiles for each. In so doing, we identify engineering targets for the production of processive cellulases of enhanced efficiency.