(453e) New Modeling Framework of Enzymatic Hydrolysis of Cellulose

Cellulose has long been recognized as a renewable carbohydrate source for human energy use. It is available in large quantities in plant biomass. In recent years, for both economic and environmental reasons, intense research efforts have been directed at the utilization of cellulose to produce short-chain soluble sugar oligomers, such as glucose or cellobiose, which are subsequently or concurrently metabolized by microorganisms to produce biofuels such as bioethanol. The hydrolytic conversion of cellulose into soluble, fermentable sugars is achieved by means of cellulase systems which contain three major types of enzymatic activities: (1) endoglucanases which cut beta(1,4) glucosidic bonds randomly at all internal bond sites of insoluble cellulose chains in solid substrates; (2) exoglucanases which cut bonds only at the ends of insoluble cellulose chains; and (3) b-glucosidases which hydrolyze soluble oligomer sugars into glucose. The endoglucanases and exoglucanases thus depolymerize long solid cellulose chains into short soluble sugars and this is believed to be the rate-limiting step of the cellulose hydrolysis process.

In this work, we develop a general framework for a realistic rate equation modeling of cellulose hydrolysis using noncomplexed cellulase. Our proposed formalism, for the first time, takes into account explicitly the time evolution of the random substrate morphology resulting from the hydrolytic cellulose chain fragmentation and solubilization. This is achieved by integrating novel geometrical concepts to quantitatively capture the time-dependent random morphology, together with the enzymatic chain fragmentation, into a coupled morphology-plus-kinetics rate equation approach. In addition, an innovative site number representation, based on tracking available numbers of beta(1,4) glucosidic bonds, of different site types, exposed to attacks by different enzyme types, is presented. This site number representation results in an ordinary differential equation (ODE) system, with a substantially reduced ODE system size, compared to earlier chain fragmentation kinetics approaches. This formalism enables us to quantitatively simulate both the hydrolytically evolving random substrate morphology and the profound, and heretofore neglected, morphology effects on the hydrolysis kinetics. By incorporating the evolving morphology on an equal footing with the hydrolytic chain fragmentation, our formalism provides a framework for the realistic modeling of the entire solubilization process, beyond the short-time limit and through near-complete hydrolytic conversion.