Breaking the Stability-Activity-Selectivity Trilemma in Unspecific Peroxygenase through Computation-Based...

Area of Science:

• Enzyme Engineering
• Biocatalysis
• Computational Biology

Background:

• Understanding enzyme dynamics, particularly the interplay between distal and active site regions, is crucial but challenging.
• The simultaneous optimization of enzyme stability, catalytic activity, and enantioselectivity presents a significant hurdle in enzyme development for agrochemistry and other industries.

Purpose of the Study:

• To overcome the classical trade-off between stability, activity, and selectivity in enzymes.
• To engineer a more robust and efficient unspecific peroxygenase (UPO) for practical applications.

Main Methods:

• Utilized FoldX-based global saturation mutagenesis predictions, prioritizing functional regions like the N-terminal domain, substrate access pocket, and dimer interface.
• Validated computational predictions through experimental testing of selected mutation sites.
• Employed molecular dynamics (MD) simulations to elucidate the mechanisms behind enhanced enzyme performance.

Main Results:

• Successfully overcame the stability-activity-selectivity trade-off in Collariella virescens unspecific peroxygenase (CviUPO).
• A combinatorial variant (M1_T9P_G161L) exhibited a 36-fold longer half-life and 6-fold higher activity, maintaining >99% enantioselectivity, resulting in a 75-fold improvement over the wild type.
• Achieved efficient semipreparative-scale synthesis of (R)-6-bromochroman-4-ol.

Conclusions:

• Developed a novel computational strategy for cross-regional combinatorial mutagenesis, offering a new paradigm for engineering metalloenzymes.
• The engineered CviUPO demonstrates significant potential for industrial biocatalysis due to its enhanced stability, activity, and selectivity.
• MD simulations confirmed that mutations stabilized protein folding and optimized the catalytic pocket microenvironment.