Sequence-based database mining and characterization of cutinases for efficient synthesis of aromatic esters

The discovery of cutinases with desirable catalytic properties is important for expanding their applications in the synthesis of value-added food and pharmaceutical molecules, particularly for the aromatic esters. However, many efficient enzymes remain hidden within the growing sequence data. We used sequence-based database mining to identify an uncharacterized cutinase, NlCut, and investigated its structural features, biochemical properties and catalytic performance. NlCut was heterologously expressed in Escherichia coli BL21(DE3) at 55.92 mg protein L^-1 culture and exhibited a specific activity of 198.26 U/mg toward p-nitrophenyl butyrate. Notably, immobilization on Fe₃O₄@SiO₂-NH-CHO magnetic nanoparticles markedly enhanced its stability in organic solvents. In toluene, the immobilized NlCut catalyzed the transesterification of benzyl alcohol with vinyl acetate, affording benzyl acetate in 96.11% yield within 1 h. Moreover, the yield remained above 80% after eight consecutive reuse cycles. This work highlights the potential of immobilized NlCut as an efficient biocatalyst for non-aqueous synthesis of aromatic esters.