Active site mutants of Baeyer-Villiger monooxygenase: effect on turnover of levulinate substrates

In recent years, there has been increasing interest in sustainable production processes within the industrial sector, particularly through the use of biotechnologies as alternatives to traditional chemical methods. Among these, Flavin-containing monooxygenases (FMOs), particularly Baeyer-Villiger monooxygenases (BVMOs), have shown promise due to their ability to catalyze a wide range of reactions under mild conditions. These enzymes can be employed in the production of bio-based compounds, including 3-acetoxypropionates (3-APs), which are precursors to 3-hydroxypropionic acid (3-HP), a versatile chemical used in biofuels, bioplastics, and other industries. The production of 3-HP from renewable sources, such as lignocellulosic biomass, presents a more sustainable alternative to fossil-derived methods. This study focuses on the characterization of two Ar-BVMO mutants, Y141L and Y142L, which were created to improve the conversion of butyl levulinate (BuLev) to 3-HP precursors. The mutations were based on previous studies of a related enzyme, and their impact on enzyme activity was assessed through molecular docking simulations, protein expression, kinetic analysis, and whole-cell reactions. The Y142L mutant exhibited a higher catalytic efficiency and better substrate conversion than the wild-type (WT) Ar-BVMO, while the Y141L mutant showed improved regioselectivity, minimizing by-product formation. In addition, experiments demonstrated the successful use of these mutants in whole-cell reactions, achieving 100% conversion of BuLev to 3-HP precursors without the need for external NADPH regeneration. However, challenges related to the industrial scalability of these processes, including enzyme stability, mass transfer limitations, and product inhibition, remain. Despite these challenges, the results indicate that Ar-BVMO mutants, particularly Y142L, offer a promising pathway for the sustainable production of 3-HP precursors, with the potential for further optimization and industrial-scale application.