Applied Mathematics and Nonlinear Sciences
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Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 10, Issue 1


Published
on

September 23, 2025


Pages


DOI

Article

Enzyme-catalyzed reaction path optimization and biosynthetic design based on genetic algorithm

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Authors

Xiaoqian Zhang Affiliation:
Chinese Medicine College, Bozhou University, Bozhou, Anhui, 236800, China.
, Tong Sun Affiliation:
Chinese Medicine College, Bozhou University, Bozhou, Anhui, 236800, China.
, Zhen Xu Affiliation:
Chinese Medicine College, Bozhou University, Bozhou, Anhui, 236800, China.
, Haiying Sun Affiliation:
Chinese Medicine College, Bozhou University, Bozhou, Anhui, 236800, China.
and Xinyao Su Affiliation:
Chinese Medicine College, Bozhou University, Bozhou, Anhui, 236800, China.


Abstract

Conjugated linoleic acid has a large medicinal value, and the biosynthesis of conjugated linoleic acid has advantages that traditional chemical synthesis methods do not have. In this paper, taking Lactobacillus acidophilus mutant strain B-5 as an example, a kinetic model of conjugated linoleic acid synthesis catalysed by conjugated linoleic acid isomerase was constructed, and genetic algorithm was used to solve the parameters of the model and experimentally verified the fitting effect of the model to the real value. The pathway for the isomerase-catalysed synthesis of conjugated linoleic acid was optimised experimentally, and it was found that factors such as linoleic acid concentration, pH and reaction temperature had the greatest influence on the yield of conjugated linoleic acid. Experimental and orthogonal tests showed that the theoretical yield of conjugated linoleic acid was maximum when the substrate concentration was 2%, pH was 6 and the reaction temperature was 36°C.


Keywords

Genetic algorithm, Conjugated linoleic acid isomerase catalysis, Pathway optimisation, Kinetic modelling, 97B20


Citation

Zhang, X., Sun, T., Xu, Z., Sun, H., & Su, X. (2025). Enzyme-catalyzed reaction path optimization and biosynthetic design based on genetic algorithm. Applied Mathematics and Nonlinear Sciences, 10(1). https://doi.org/10.2478/amns-2025-1110

Published by: Engineering Journals

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