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Food safety is paramount to the health of consumers. Enzymatic time-temperature indicators are capable of monitoring the cumulative heat exposure after the production of food products and providing visual color changes indicative of product shelf life. However, the thermal stability of enzymes limits their widespread application. Enzyme engineering can enhance the thermal stability of enzymes through strategies such as immobilization, directed evolution, and rational design. In recent years, artificial intelligence methods like machine learning have been applied to enzyme engineering, demonstrating their unique advantages in predicting complex enzyme structures and addressing issues related to enzyme thermal stability, offering new possibilities for the design of enzyme molecules. This article reviews the primary enzyme engineering strategies for improving the thermal stability of enzymes, with a particular focus on the thermal stability modification of enzymes commonly used in time-temperature indicators, and discusses future development directions.
This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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