Literature Review: Computational Methods for Designing Thermostable, Efficient, and Cost-Effective Enzymes for Industrial Applications

Abstract

Enzymes play a vital role as biocatalysts in various industrial applications due to their high specificity and efficiency under mild conditions. However, their limited thermostability significantly constrains their operational lifespan and effectiveness at elevated temperatures. This review examines recent advancements in computational methods aimed at enhancing enzyme thermostability, focusing on structure-based rational design, machine learning, and hybrid approaches. Key findings highlight the effectiveness of structure-based methods, in optimizing enzyme structures, while machine learning approaches demonstrated potential in predicting stabilizing mutations. This review identifies key research gaps and proposes directions for future studies to facilitate the industrial adoption of thermostable enzymes.