Monte Carlo simulation of the [alpha]-amylolysis of amylopectin potato starch. 2. [alpha]-amylolysis of amylopectin

A model is presented that describes all the saccharides that are produced during the hydrolysis of starch by an α-amylase. Potato amylopectin, the substrate of the hydrolysis reaction, was modeled in a computer matrix. The four different subsite maps presented in literature for α-amylase originating...

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Bibliographic Details
Published in:Bioprocess and biosystems engineering Vol. 26; no. 2; p. 123
Main Authors: Marchal, L M, Ulijn, R V, de Gooijer, C D, Franke, G T, Tramper, J
Format: Journal Article
Language:English
Published: Heidelberg Springer Nature B.V 01-12-2003
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Summary:A model is presented that describes all the saccharides that are produced during the hydrolysis of starch by an α-amylase. Potato amylopectin, the substrate of the hydrolysis reaction, was modeled in a computer matrix. The four different subsite maps presented in literature for α-amylase originating from Bacillus amyloliquefaciens were used to describe the hydrolysis reaction in a Monte Carlo simulation. The saccharide composition predicted by the model was evaluated with experimental values. Overall, the model predictions were acceptable, but no single subsite map gave the best predictions for all saccharides produced. The influence of an α(1[arrow right]6) linkage on the rate of hydrolysis of nearby α(1[arrow right]4) linkages by the α-amylase was evaluated using various inhibition constants. For all the subsites considered the use of inhibition constants led to an improvement in the predictions (a decrease of residual sum of squares), indicating the validity of inhibition constants as such. As without inhibition constants, no single subsite map gave the best fit for all saccharides. The possibility of generating a hypothetical subsite map by fitting was therefore investigated. With a genetic algorithm it was possible to construct hypothetical subsite maps (with inhibition constants) that gave further improvements in the average prediction for all saccharides. The advantage of this type of modeling over a regular fit is the additional information about all the saccharides produced during hydrolysis, including the ones that are difficult to measure experimentally.[PUBLICATION ABSTRACT]
ISSN:1615-7591
1615-7605
DOI:10.1007/s00449-003-0342-0