Metal–organic frameworks (MOFs): a novel support platform for ASNase immobilization
Source abstract
Abstract
Metal–organic frameworks (MOFs) have been recently studied for a variety of applications because of their huge surface area, large porosity, and tunable functionality. In this work, for the first time, the efficient immobilization of l-asparaginase (ASNase, EC 3.5.1.1) by using MOF as a simple and novel support is demonstrated. The functional groups, morphology, chemical composition, and crystal structure of the support and immobilized ASNase were investigated by using different methods, including Fourier transform infrared spectroscopy, scanning electron microscopy, energy-dispersive spectrometer, and X-ray diffraction. Afterward, the enzymatic activities and thermodynamic parameters of the immobilized l-ASNase (ASNase@ZIF-8) were compared with free one. After enzyme immobilization, the optimum temperature shifted from 50 to 60 °C, while the optimum pH remains unchanged at 9.0. However, the pH and thermal stability of the ASNase@ZIF-8 was significantly improved compared to the free one. The ASNase@ZIF-8 displayed an excellent long-term storage stability, which could protect more than 56% of the initial activity at 25 °C for 4 weeks. Besides, the ASNase@ZIF-8 had high reusability, which showed a high degree of activity (more than 45%) after 10 cycles. Km and Vmax values were 0.18 mM and 64.5 µmol/min for ASNase@ZIF-8 and those for free ASNase were 0.40 mM and 68.0 µmol/min, respectively. The proposed support based on ZIF-8 was superior in terms of high enzyme loading capacity (82.0%), high enzyme catalytic activity, and easy preparation process. Overall, newly developed support for ASNase may provide a new platform for its biotechnological applications.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Enzyme Production and Characterization · Enzyme Catalysis and Immobilization · Biofuel production and bioconversion
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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