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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.


Related in: MedlinePlus

Hydrolysis by endo-cellulases for imperfect crystals. Time course of hydrolysis by endo-cellulases when various glycosidic bond percentages are initially cleaved in the cellulose layer. The inset shows the same curves for a short time scale.
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Figure 9: Hydrolysis by endo-cellulases for imperfect crystals. Time course of hydrolysis by endo-cellulases when various glycosidic bond percentages are initially cleaved in the cellulose layer. The inset shows the same curves for a short time scale.

Mentions: Although the simulation results show good agreement with the experiments, the lag phase observed in the hydrolysis curve (Figure 7a) is unexpected, as it was not observed in any bulk measurements involving enzymatic hydrolysis of cellulose. It was, however, observed during acid hydrolysis of bacterial cellulose [51] and during anaerobic bacterial digestion of cellulose [52]. The possible reasons behind the occurrence of the lag phase are various. (i) At the beginning, the random glycosidic bond cleavages are too far from each other to release glucose, cellobiose or cellotriose, as this requires a finite amount of time for cellulases to revisit the neighborhood of a cleaved bond. (ii) The model used here does not take into account enzyme diffusion [53], which could accelerate the ability of the enzyme to locate the neighborhood of a cleaved glycosidic bond. (iii) In contrast to a realistic cellulose crystal surface with impurities and pre-existing broken inter- and intra-chain bonds, the simulated initial cellulose surface is perfectly regular and fully crystalline. Already, with only 5% of bonds hydrolyzed, the substrate becomes highly irregular (Shishir Chundawat, Personal Communication). In order to observe the effect of these irregularities, simulations were performed with an initial percentage of broken glycosidic bonds. Figure 9 shows how the initial slow hydrolysis phase diminishes as the initial cellulose substrate becomes more and more irregular.


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)

Hydrolysis by endo-cellulases for imperfect crystals. Time course of hydrolysis by endo-cellulases when various glycosidic bond percentages are initially cleaved in the cellulose layer. The inset shows the same curves for a short time scale.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 9: Hydrolysis by endo-cellulases for imperfect crystals. Time course of hydrolysis by endo-cellulases when various glycosidic bond percentages are initially cleaved in the cellulose layer. The inset shows the same curves for a short time scale.
Mentions: Although the simulation results show good agreement with the experiments, the lag phase observed in the hydrolysis curve (Figure 7a) is unexpected, as it was not observed in any bulk measurements involving enzymatic hydrolysis of cellulose. It was, however, observed during acid hydrolysis of bacterial cellulose [51] and during anaerobic bacterial digestion of cellulose [52]. The possible reasons behind the occurrence of the lag phase are various. (i) At the beginning, the random glycosidic bond cleavages are too far from each other to release glucose, cellobiose or cellotriose, as this requires a finite amount of time for cellulases to revisit the neighborhood of a cleaved bond. (ii) The model used here does not take into account enzyme diffusion [53], which could accelerate the ability of the enzyme to locate the neighborhood of a cleaved glycosidic bond. (iii) In contrast to a realistic cellulose crystal surface with impurities and pre-existing broken inter- and intra-chain bonds, the simulated initial cellulose surface is perfectly regular and fully crystalline. Already, with only 5% of bonds hydrolyzed, the substrate becomes highly irregular (Shishir Chundawat, Personal Communication). In order to observe the effect of these irregularities, simulations were performed with an initial percentage of broken glycosidic bonds. Figure 9 shows how the initial slow hydrolysis phase diminishes as the initial cellulose substrate becomes more and more irregular.

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