Engineering thermostability of industrial enzymes for enhanced application performance

Abstract

Thermostability is a key factor for the industrial application of enzymes. This review categorizes enzymes by their applications and discusses the importance of engineering thermostability for practical use. It summarizes fundamental theories and recent advancements in enzyme thermostability modification, including directed evolution, semi-rational design, and rational design. Directed evolution uses high-throughput screening to generate random mutations, while semi-rational design combines hotspot identification with screening. Rational design focuses on key residues to enhance stability by improving rigidity, foldability, and reducing aggregation. The review also covers rational strategies like engineering folding energy, surface charge, machine learning methods, and consensus design, along with tools that support these approaches. Practical examples are critically assessed to highlight the benefits and limitations of these strategies. Finally, the challenges and potential contributions of artificial intelligence in enzyme thermostability engineering are discussed.

Keywords: Directed evolution; Machine learning; Protein engineering; Rational design; Thermostability.