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A coarse-grained model for synergistic action of multiple enzymes on cellulose.

Asztalos A, Daniels M, Sethi A, Shen T, Langan P, Redondo A, Gnanakaran S - Biotechnol Biofuels (2012)

Bottom Line: We present a coarse-grained stochastic model for capturing the key events associated with the enzymatic degradation of cellulose at the mesoscopic level.Importantly, it captures the endo-exo synergism of cellulase enzyme cocktails.This model constitutes a critical step towards testing hypotheses and understanding approaches for maximizing synergy and substrate properties with a goal of cost effective enzymatic hydrolysis.

View Article: PubMed Central - HTML - PubMed

Affiliation: Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM, 87545, USA. gnana@lanl.gov.

ABSTRACT

Background: Degradation of cellulose to glucose requires the cooperative action of three classes of enzymes, collectively known as cellulases. Endoglucanases randomly bind to cellulose surfaces and generate new chain ends by hydrolyzing β-1,4-D-glycosidic bonds. Exoglucanases bind to free chain ends and hydrolyze glycosidic bonds in a processive manner releasing cellobiose units. Then, β-glucosidases hydrolyze soluble cellobiose to glucose. Optimal synergistic action of these enzymes is essential for efficient digestion of cellulose. Experiments show that as hydrolysis proceeds and the cellulose substrate becomes more heterogeneous, the overall degradation slows down. As catalysis occurs on the surface of crystalline cellulose, several factors affect the overall hydrolysis. Therefore, spatial models of cellulose degradation must capture effects such as enzyme crowding and surface heterogeneity, which have been shown to lead to a reduction in hydrolysis rates.

Results: We present a coarse-grained stochastic model for capturing the key events associated with the enzymatic degradation of cellulose at the mesoscopic level. This functional model accounts for the mobility and action of a single cellulase enzyme as well as the synergy of multiple endo- and exo-cellulases on a cellulose surface. The quantitative description of cellulose degradation is calculated on a spatial model by including free and bound states of both endo- and exo-cellulases with explicit reactive surface terms (e.g., hydrogen bond breaking, covalent bond cleavages) and corresponding reaction rates. The dynamical evolution of the system is simulated by including physical interactions between cellulases and cellulose.

Conclusions: Our coarse-grained model reproduces the qualitative behavior of endoglucanases and exoglucanases by accounting for the spatial heterogeneity of the cellulose surface as well as other spatial factors such as enzyme crowding. Importantly, it captures the endo-exo synergism of cellulase enzyme cocktails. This model constitutes a critical step towards testing hypotheses and understanding approaches for maximizing synergy and substrate properties with a goal of cost effective enzymatic hydrolysis.

No MeSH data available.


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(a) Effect of initial concentration of exo-cellulases. Change in convencion time as initial enzyme concentration is varied(b) Sugar production over time. System parameters are: N = 25000 glucose units, kon = 105 1/(sM), koff = 100 1/s.
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Figure 11: (a) Effect of initial concentration of exo-cellulases. Change in convencion time as initial enzyme concentration is varied(b) Sugar production over time. System parameters are: N = 25000 glucose units, kon = 105 1/(sM), koff = 100 1/s.

Mentions: The effect of varying the initial [E]0 enzyme concentration upon conversion times is plotted in Figure 11a. In contrast to Figure 8a, the substrate becomes saturated by exo-cellulases at lower enzyme concentrations than we observed in the case of endo-cellulases. This is because the number of free chain ends always remains small compared to the number of enzyme particles in solution. Figure 11b shows that the only sugar produced by exo-cellulases is cellobiose. Experimental results, however, report the production of both glucose and cellotriose along with cellobiose, although cellobiose is the major product [16,50]. The relatively constant processive speed of exo-R cellulases along the glucan chain explains the constant hydrolysis rate observed in Figure 10 and the non-decreasing gap between the two curves in Figure 11a.


A coarse-grained model for synergistic action of multiple enzymes on cellulose.

Asztalos A, Daniels M, Sethi A, Shen T, Langan P, Redondo A, Gnanakaran S - Biotechnol Biofuels (2012)

(a) Effect of initial concentration of exo-cellulases. Change in convencion time as initial enzyme concentration is varied(b) Sugar production over time. System parameters are: N = 25000 glucose units, kon = 105 1/(sM), koff = 100 1/s.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3475064&req=5

Figure 11: (a) Effect of initial concentration of exo-cellulases. Change in convencion time as initial enzyme concentration is varied(b) Sugar production over time. System parameters are: N = 25000 glucose units, kon = 105 1/(sM), koff = 100 1/s.
Mentions: The effect of varying the initial [E]0 enzyme concentration upon conversion times is plotted in Figure 11a. In contrast to Figure 8a, the substrate becomes saturated by exo-cellulases at lower enzyme concentrations than we observed in the case of endo-cellulases. This is because the number of free chain ends always remains small compared to the number of enzyme particles in solution. Figure 11b shows that the only sugar produced by exo-cellulases is cellobiose. Experimental results, however, report the production of both glucose and cellotriose along with cellobiose, although cellobiose is the major product [16,50]. The relatively constant processive speed of exo-R cellulases along the glucan chain explains the constant hydrolysis rate observed in Figure 10 and the non-decreasing gap between the two curves in Figure 11a.

Bottom Line: We present a coarse-grained stochastic model for capturing the key events associated with the enzymatic degradation of cellulose at the mesoscopic level.Importantly, it captures the endo-exo synergism of cellulase enzyme cocktails.This model constitutes a critical step towards testing hypotheses and understanding approaches for maximizing synergy and substrate properties with a goal of cost effective enzymatic hydrolysis.

View Article: PubMed Central - HTML - PubMed

Affiliation: Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM, 87545, USA. gnana@lanl.gov.

ABSTRACT

Background: Degradation of cellulose to glucose requires the cooperative action of three classes of enzymes, collectively known as cellulases. Endoglucanases randomly bind to cellulose surfaces and generate new chain ends by hydrolyzing β-1,4-D-glycosidic bonds. Exoglucanases bind to free chain ends and hydrolyze glycosidic bonds in a processive manner releasing cellobiose units. Then, β-glucosidases hydrolyze soluble cellobiose to glucose. Optimal synergistic action of these enzymes is essential for efficient digestion of cellulose. Experiments show that as hydrolysis proceeds and the cellulose substrate becomes more heterogeneous, the overall degradation slows down. As catalysis occurs on the surface of crystalline cellulose, several factors affect the overall hydrolysis. Therefore, spatial models of cellulose degradation must capture effects such as enzyme crowding and surface heterogeneity, which have been shown to lead to a reduction in hydrolysis rates.

Results: We present a coarse-grained stochastic model for capturing the key events associated with the enzymatic degradation of cellulose at the mesoscopic level. This functional model accounts for the mobility and action of a single cellulase enzyme as well as the synergy of multiple endo- and exo-cellulases on a cellulose surface. The quantitative description of cellulose degradation is calculated on a spatial model by including free and bound states of both endo- and exo-cellulases with explicit reactive surface terms (e.g., hydrogen bond breaking, covalent bond cleavages) and corresponding reaction rates. The dynamical evolution of the system is simulated by including physical interactions between cellulases and cellulose.

Conclusions: Our coarse-grained model reproduces the qualitative behavior of endoglucanases and exoglucanases by accounting for the spatial heterogeneity of the cellulose surface as well as other spatial factors such as enzyme crowding. Importantly, it captures the endo-exo synergism of cellulase enzyme cocktails. This model constitutes a critical step towards testing hypotheses and understanding approaches for maximizing synergy and substrate properties with a goal of cost effective enzymatic hydrolysis.

No MeSH data available.


Related in: MedlinePlus