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New Delhi metallo-β-lactamase-1 (NDM-1) has potential as a biocatalytic recognition element for β-lactam antibiotic sensing; however, the limited stability of the free enzyme may hinder its subsequent integration into sensing interfaces. In this study, ZIF-8, multi-walled carbon nanotubes (MWCNTs), graphene oxide (GO), and magnetic Fe3O4 were evaluated as candidate carriers for NDM-1 immobilization, with the aim of identifying an immobilized preparation with favorable catalytic activity and stability for future biosensor development. Among the immobilized preparations, NDM-1@ZIF-8 exhibited the highest apparent maximum reaction rate (Vmax,app=100.21 ± 1.98 μM·min−1), corresponding to approximately 70.7% of that of free NDM-1 (141.78 ± 0.26 μM·min−1). SEM and FT-IR provided complementary physicochemical characterization of the resulting ZIF-8-based composite, with protein-associated spectral features observed after biomimetic mineralization. NDM-1@ZIF-8 also showed improved activity retention during storage, retaining 92.37 ± 2.95% of its initial activity after 30 days compared with 79.77 ± 0.46% for free NDM-1. In addition, the immobilized enzyme exhibited a broader pH-response profile and retained approximately 78.6% of its initial activity after incubation at 40 °C for 90 min, whereas free NDM-1 retained approximately 24.8%. Molecular docking and molecular dynamics simulations further suggested plausible NDM-1–ZIF-8 interfacial interactions, redistribution of local conformational flexibility, altered solvent exposure, and no pronounced disruption of the modeled binuclear Zn-center geometry. These computational observations provide possible molecular-level explanations for the experimentally observed activity-retention behavior rather than direct evidence of enzyme stabilization. Overall, this study identifies ZIF-8 as a suitable carrier for maintaining the catalytic function and stability of immobilized NDM-1 and establishes a foundational immobilization platform for its future integration into electrochemical biosensing systems.
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Liu et al. (2026) studied this question.
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