Double crystallization-driven copper-2-methylimidazole nanoflowers: Stabilizing glucose oxidase and activating...

Based on the structural characteristics of metal-organic framework (MOF) synthesis, we designed a double-crystallized copper-2-methylimidazole nanoflower (DCu NF) platform in which glucose oxidase (GOx) was incorporated to form an enzyme-nanozyme hybrid for glucose sensing. The D-Cu@GOx NF system mimics a GOx-horseradish peroxidase-like multi-enzyme cascade, benefiting from synergistic oxidation capabilities. Double crystallization of Cu nanoflowers (Cu-NFs) was crucial for inducing nanozyme activity by creating a unique Fenton-like reaction site, enhancing both cascade activity and enzyme stability. The system was constructed using a self-assembly method, integrating Cu-NF synthesis with in situ GOx immobilization. The double crystallization of Cu-NFs expanded the surface area, forming D-Cu@GOx NFs, which significantly enhanced cascade activity and enzyme stability. The system demonstrated excellent glucose detection performance, maintaining 88 % of enzyme activity after 30 days at room temperature, with temperature resistance up to 60 °C and pH stability between 3 and 8. The enhanced oxidation from the Cu metal Fenton-like reaction site enabled sensitive glucose detection over a wide linear range (0-50 microM), with a limit of detection of 1.25 microM. The system also showed high reproducibility, with a relative standard deviation of <5 % across five replicate measurements. Furthermore, it successfully detected human blood glucose in real samples, with results comparable to standard clinical methods. This report presents Cu NF synthesis with an integrated GOx approach, demonstrating cost-effectiveness through enhanced stability and sensitivity that reduces enzyme usage and enables rapid, accurate glucose biosensing. The D-Cu@GOx NFs, a hybrid enzyme-nanozyme complex, offer improved sensitivity and stability for glucose detection in serum. By enhancing enzyme stability, the system eliminates the need for dual enzymes, reducing costs and improving efficiency, while maintaining cost-effectiveness for industrial and diagnostic applications.