Monte Carlo simulation of the α -amylolysis of amylopectin potato starch

Marchal, Luc; Zondervan, J.; Bergsma, Jack; Beeftink, H.H.; Tramper, J.

doi:10.1007/s004490100247

Cited by 11 publications

(2 citation statements)

References 27 publications

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“…Action of various cellulase enzymes on cellulose structure was modeled using Monte Carlo simulation technique [38-40,42]. Each minute, a sequence of N hij potential hydrolysis bond locations were randomly selected (with uniform probability distribution) from the list of bond locations appropriate for the type of enzyme under consideration.…”

Section: Methodsmentioning

confidence: 99%

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Stochastic molecular model of enzymatic hydrolysis of cellulose for ethanol production

Kumar

Murthy

2013

Biotechnol Biofuels

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BackgroundDuring cellulosic ethanol production, cellulose hydrolysis is achieved by synergistic action of cellulase enzyme complex consisting of multiple enzymes with different mode of actions. Enzymatic hydrolysis of cellulose is one of the bottlenecks in the commercialization of the process due to low hydrolysis rates and high cost of enzymes. A robust hydrolysis model that can predict hydrolysis profile under various scenarios can act as an important forecasting tool to improve the hydrolysis process. However, multiple factors affecting hydrolysis: cellulose structure and complex enzyme-substrate interactions during hydrolysis make it diffucult to develop mathematical kinetic models that can simulate hydrolysis in presence of multiple enzymes with high fidelity. In this study, a comprehensive hydrolysis model based on stochastic molecular modeling approch in which each hydrolysis event is translated into a discrete event is presented. The model captures the structural features of cellulose, enzyme properties (mode of actions, synergism, inhibition), and most importantly dynamic morphological changes in the substrate that directly affect the enzyme-substrate interactions during hydrolysis.ResultsCellulose was modeled as a group of microfibrils consisting of elementary fibrils bundles, where each elementary fibril was represented as a three dimensional matrix of glucose molecules. Hydrolysis of cellulose was simulated based on Monte Carlo simulation technique. Cellulose hydrolysis results predicted by model simulations agree well with the experimental data from literature. Coefficients of determination for model predictions and experimental values were in the range of 0.75 to 0.96 for Avicel hydrolysis by CBH I action. Model was able to simulate the synergistic action of multiple enzymes during hydrolysis. The model simulations captured the important experimental observations: effect of structural properties, enzyme inhibition and enzyme loadings on the hydrolysis and degree of synergism among enzymes.ConclusionsThe model was effective in capturing the dynamic behavior of cellulose hydrolysis during action of individual as well as multiple cellulases. Simulations were in qualitative and quantitative agreement with experimental data. Several experimentally observed phenomena were simulated without the need for any additional assumptions or parameter changes and confirmed the validity of using the stochastic molecular modeling approach to quantitatively and qualitatively describe the cellulose hydrolysis.

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Section: Methodsmentioning

confidence: 99%

“…This approach relying on modeling enzymatic hydrolysis process at molecular and enzymatic levels has been successful in describing starch hydrolysis [38-42]. These studies concluded that stochastic molecular modeling technique can be used to predict hydrolysis profile and addressing the limitations of kinetic models (e.g.…”

Section: Introductionmentioning

confidence: 99%

Stochastic molecular model of enzymatic hydrolysis of cellulose for ethanol production

Kumar

Murthy

2013

Biotechnol Biofuels

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A stochastic model for predicting dextrose equivalent and saccharide composition during hydrolysis of starch by α‐amylase

Baks

Janssen

Boom

2008

Biotech & Bioengineering

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A stochastic model was developed that was used to describe the formation and breakdown of all saccharides involved during alpha-amylolytic starch hydrolysis in time. This model is based on the subsite maps found in literature for Bacillus amyloliquefaciens alpha-amylase (BAA) and Bacillus licheniformis alpha-amylase (BLA). Carbohydrate substrates were modeled in a relatively simple two-dimensional matrix. The predicted weight fractions of carbohydrates ranging from glucose to heptasaccharides and the predicted dextrose equivalent showed the same trend and order of magnitude as the corresponding experimental values. However, the absolute values were not the same. In case a well-defined substrate such as maltohexaose was used, comparable differences between the experimental and simulated data were observed indicating that the substrate model for starch does not cause these deviations. After changing the subsite map of BLA and the ratio between the time required for a productive and a non-productive attack for BAA, a better agreement between the model data and the experimental data was observed. Although the model input should be improved for more accurate predictions, the model can already be used to gain knowledge about the concentrations of all carbohydrates during hydrolysis with an alpha-amylase. In addition, this model also seems to be applicable to other depolymerase-based systems.

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Analysis of the sol and gel structures of potato starch over a wide spatial scale

Nagasaki

Matsuba

Ikemoto

et al. 2021

Food Science & Nutrition

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The fine structure of amylopectin differs significantly from the structure of glycogen. Amylopectin has a unit structure designated as a cluster, whereas glycogen exhibits no such structure because the α-1,6 branch points in glycogen are randomly distributed. Amylopectin clusters are interconnected by long chains that span across two or three clusters. The short and intermediate chains within a single cluster are called nonbranched chains or branched chains (Jane et al., 1997;Peat et al., 1956).Starch is a vital source of energy that helps sustain human life.Starch that stores nutritive energy in plant roots, tubers, or endosperms such as potato, tapioca, corn, and rice primarily comprises of carbohydrates in the form of polysaccharides. On the micrometer scale, starch granules ∼1-100 µm in size have a growth-ring structure composed of alternately arranged semicrystalline and amorphous shells. The semicrystalline shells are composed primarily of branched-chain amylopectin clusters, in contrast to the amorphous shells, which contain long linear-chain amylose and low-molecularmass amylopectin. On the nanometer scale, each semicrystalline shell consists of lamellae of alternating crystalline and amorphous layers, with a typical lamellar spacing of ~9 nm (also known as the 9-nm repeat structure), with crystallinity ranging from 15% to 45%.At the atomic level, the packing of the crystal structure of starch can be classified as either monoclinic (A-type) or hexagonal (B-type)

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Monte Carlo simulation of the α -amylolysis of amylopectin potato starch

Cited by 11 publications

References 27 publications

Stochastic molecular model of enzymatic hydrolysis of cellulose for ethanol production

Stochastic molecular model of enzymatic hydrolysis of cellulose for ethanol production

A stochastic model for predicting dextrose equivalent and saccharide composition during hydrolysis of starch by α‐amylase

Analysis of the sol and gel structures of potato starch over a wide spatial scale

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