Monte Carlo simulation of the alpha-amylolysis of amylopectin potato starch. 2. alpha-amylolysis of amylopectin
Popis souboru: | application/pdf; application/octet-stream |
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ISSN: | 1615-7591 |
Přístupová URL adresa: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::93805306df6cf80bf3eeae876bd8e023 https://pubmed.ncbi.nlm.nih.gov/14618387 |
Rights: | RESTRICTED |
Přírůstkové číslo: | edsair.doi.dedup.....93805306df6cf80bf3eeae876bd8e023 |
Autor: | C. D. de Gooijer, Rein V. Ulijn, L. M. Marchal, G. T. Franke, Johannes Tramper |
Rok vydání: | 2003 |
Předmět: |
Bio Process Engineering
amylase Starch enzymes Monte Carlo method Amylopectin Bioengineering Bacillus subsite affinities substrate Substrate Specificity chemistry.chemical_compound Hydrolysis rate parameters Residual sum of squares Computational chemistry Computer Simulation Amylase Potato starch VLAG Binding Sites Models Statistical biology Wageningen Food Safety Research General Medicine Enzyme Activation Crystallography Kinetics hydrolysis chemistry Models Chemical biology.protein alpha-Amylases Alpha-amylase Monte Carlo Method Biotechnology Protein Binding |
Zdroj: | Bioprocess and Biosystems Engineering 26 (2003) Bioprocess and Biosystems Engineering, 26, 123-132 |
ISSN: | 1615-7591 |
Popis: | A model is presented that describes all the saccharides that are produced during the hydrolysis of starch by an alpha-amylase. Potato amylopectin, the substrate of the hydrolysis reaction, was modeled in a computer matrix. The four different subsite maps presented in literature for alpha-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 alpha(1-->6) linkage on the rate of hydrolysis of nearby alpha(1-->4) linkages by the alpha-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. |
Databáze: | OpenAIRE |
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