Multi-strategy computational screening and single-point saturation mutation optimize catalytic efficiency and thermal stability of glucose oxidase

Glucose oxidase (GOX) holds significant application value in food, animal husbandry, and medical fields. However, its industrial use is limited by inherently insufficient thermostability and suboptimal catalytic efficiency. To address this challenge, a semi-rational design workflow was developed in this study, which combines multi-strategy computational screening with single-site saturation mutagenesis. Strategy I integrates molecular docking, co-evolutionary analysis, and consensus residue identification to enhance catalytic efficiency. Strategy II combines B-factor, solvent-accessible surface area, conservation analysis, and FoldX free energy prediction to improve thermostability. Mutant libraries were constructed based on the identified sites. Through high-throughput screening and multi-site combinatorial optimization, a high-performance mutant, V4 (T10K/E363P/T34I/M556L), was successfully obtained. Compared to the wild-type enzyme, this mutant showed 2.19-fold higher specific activity and a 1.67-fold longer half-life (t_1/2) at 65 °C, achieving synergistic optimization of both catalytic efficiency and thermostability. This study's enzyme engineering strategy provides technical support for enzyme engineering design.