A stochastic model for predicting dextrose equivalent and saccharide composition during hydrolysis of starch by [alpha]-amylase

A stochastic model was developed that was used to describe the formation and breakdown of all saccharides involved during α-amylolytic starch hydrolysis in time. This model is based on the subsite maps found in literature for Bacillus amyloliquefaciens α-amylase (BAA) and Bacillus licheniformis α-am...

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Veröffentlicht in:Biotechnology and bioengineering 2008-07, Vol.100 (4), p.684
Hauptverfasser: Besselink, Tamara, Baks, Tim, Janssen, Anja EM, Boom, Remko M
Format: Artikel
Sprache:eng
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Zusammenfassung:A stochastic model was developed that was used to describe the formation and breakdown of all saccharides involved during α-amylolytic starch hydrolysis in time. This model is based on the subsite maps found in literature for Bacillus amyloliquefaciens α-amylase (BAA) and Bacillus licheniformis α-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 a-amylase. In addition, this model also seems to be applicable to other depolymerase-based systems. [PUBLICATION ABSTRACT]
ISSN:0006-3592
1097-0290