Positioning-Group-Enabled Biocatalytic Oxidative Dearomatization.

Area of Science:

• Biocatalysis and Protein Engineering
• Computational Chemistry
• Synthetic Chemistry

Background:

• Biocatalysts offer high selectivity and efficiency but are limited by substrate scope.
• Existing methods for expanding substrate scope, like protein engineering, are time-consuming and require specialized equipment.
• Accessible strategies for synthetic chemists to broaden enzyme substrate scope are needed.

Purpose of the Study:

• To develop a computationally guided substrate engineering strategy to expand the utility of a flavin-dependent monooxygenase.
• To identify and leverage critical substrate-protein interactions for improved catalytic orientation.
• To enable synthetic chemists to access new biocatalytic transformations with high selectivity.

Main Methods:

• Employed a computationally guided substrate engineering strategy.
• Utilized computational modeling and experimental observations to identify key substrate-protein interactions.
• Incorporated a positioning group into substrates via a cleavable ester linkage.
• Performed binding and kinetic assays to validate the strategy.

Main Results:

• Identified a critical interaction orienting the substrate for catalysis.
• Demonstrated that modified substrates are efficiently oxidized by the wild-type enzyme SorbC.
• Achieved the highest known site- and stereoselectivity for the oxidative dearomatization transformation.
• Transformed previously unreactive compounds into effective substrates.

Conclusions:

• Computationally guided substrate engineering is an effective strategy for expanding biocatalyst substrate scope.
• The positioning group strategy enhances enzyme utility for synthetic chemists.
• This approach provides a practical method for achieving high site- and stereoselectivity in biocatalytic reactions.