Engineering a Robust UDP-Glucose Pyrophosphorylase for Enhanced Biocatalytic Synthesis via ProteinMPNN and Ancestral Sequence Reconstruction

Abstract

UDP-glucose is a key metabolite in carbohydrate metabolism and plays a vital role in glycosyl transfer reactions. Its significance spans across the food and agricultural industries. This study focuses on UDP-glucose synthesis via multienzyme catalysis using dextrin, incorporating UTP production and ATP regeneration modules to reduce costs. To address thermal stability limitations of the key UDP-glucose pyrophosphorylase (UGP), a deep learning-based protein sequence design approach and ancestral sequence reconstruction are employed to engineer a thermally stable UGP variant. The engineered UGP variant is significantly 500-fold more thermally stable at 60 °C and has a half-life of 49.8 h compared to the wild-type enzyme. MD simulations and umbrella sampling calculations provide insights into the mechanism behind the enhanced thermal stability. Experimental validation demonstrates that the engineered UGP variant can produce 52.6 mM UDP-glucose within 6 h in an in vitro cascade reaction. This study offers practical insights for efficient UDP-glucose synthesis methods.