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Int. J. Mol. Sci. 2012, 13(7), 7952-7962; doi:10.3390/ijms13077952
Article

Artificial Intelligence Techniques to Optimize the EDC/NHS-Mediated Immobilization of Cellulase on Eudragit L-100

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Received: 9 April 2012 / Revised: 21 May 2012 / Accepted: 19 June 2012 / Published: 26 June 2012
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Abstract

Two artificial intelligence techniques, namely artificial neural network (ANN) and genetic algorithm (GA) were combined to be used as a tool for optimizing the covalent immobilization of cellulase on a smart polymer, Eudragit L-100. 1-Ethyl-3-(3-dimethyllaminopropyl) carbodiimide (EDC) concentration, N-hydroxysuccinimide (NHS) concentration and coupling time were taken as independent variables, and immobilization efficiency was taken as the response. The data of the central composite design were used to train ANN by back-propagation algorithm, and the result showed that the trained ANN fitted the data accurately (correlation coefficient R2 = 0.99). Then a maximum immobilization efficiency of 88.76% was searched by genetic algorithm at a EDC concentration of 0.44%, NHS concentration of 0.37% and a coupling time of 2.22 h, where the experimental value was 87.97 ± 6.45%. The application of ANN based optimization by GA is quite successful.
Keywords: immobilized enzyme; cellulase; artificial intelligence based optimization; smart biocatalyst; carbodiimide coupling immobilized enzyme; cellulase; artificial intelligence based optimization; smart biocatalyst; carbodiimide coupling
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Zhang, Y.; Xu, J.-L.; Yuan, Z.-H.; Qi, W.; Liu, Y.-Y.; He, M.-C. Artificial Intelligence Techniques to Optimize the EDC/NHS-Mediated Immobilization of Cellulase on Eudragit L-100. Int. J. Mol. Sci. 2012, 13, 7952-7962.

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