Engineering Distant Allosteric Networks To Remodel the Substrate Access Channel for Efficient β-Arbutin Biosynthesis

Area of Science:

• Biocatalysis and Enzyme Engineering
• Metabolic Engineering
• Synthetic Biology

Background:

• Efficient production of beta-arbutin (a skin-lightening agent) is limited by the low catalytic efficiency of glycosyltransferases.
• Conventional enzyme engineering strategies often focus on active-site modifications, which have limitations.

Purpose of the Study:

• To develop a novel global dynamic design strategy for improving glycosyltransferase performance in whole-cell biocatalysis.
• To enhance the catalytic efficiency and stability of enzymes for beta-arbutin production.

Main Methods:

• Integrated dynamic cross-correlation matrix analysis with computational screening to identify key distal flexible residues.
• Employed principal component analysis, free energy landscapes, and double mutant cycles for mechanistic elucidation.
• Engineered a variant (G35L) by targeting a distal residue.

Main Results:

• The G35L variant showed significantly improved enzyme kinetics and thermal stability compared to the wild type.
• Mechanistic studies revealed functional coupling between the distal mutation and the active site, stabilizing the transition state and optimizing the substrate tunnel.
• Optimized whole-cell biocatalysis with the G35L variant achieved a beta-arbutin titer of 8.99 g/L, a 4.14-fold improvement.

Conclusions:

• Distal dynamic network targeting is a powerful and effective paradigm for optimizing biocatalyst performance.
• This strategy offers a promising approach for enhancing the production of valuable compounds like beta-arbutin.