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Recently, metal-organic framework (MOF)-based multienzyme systems integrating different functional natural enzymes and/or nanomaterial-based artificial enzymes are attracting increasing attention due to their high catalytic efficiency and promising application in sensing. Simple and controllable integration of enzymes or nanozymes within MOFs is crucial for achieving efficient cascade catalysis and high stability. Here, we report a facile electrochemical assisted biomimetic mineralization strategy to prepare an artificial multienzyme system for efficient electrochemical detection of biomolecules. By using the GOx@Cu-MOF/copper foam (GOx@Cu-MOF/CF) architecture as a proof of concept, efficient enzyme immobilization and cascade catalysis were achieved by in situ encapsulation of glucose oxidase (GOx) within MOFs layer grown on three-dimensional (3D) porous conducting CF via a facile one-step electrochemical assisted biomimetic mineralization strategy. Due to the bio-electrocatalytic cascade reaction mechanism, this well-designed GOx@Cu-MOF modified electrode exhibited superior catalytic activity and thermal stability for glucose sensing. Notably, the activity of GOx@Cu-MOF/CF still remained at ca. 80% after being incubated at 80 ℃. In sharp contrast, the activity of the unprotected electrode was reduced to the original 10% after the same treatment. The design strategy presented here may be useful in fabricating highly stable enzyme@MOF composites applied for efficient photothermal therapy and other platform under high temperature.


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One-step synthesis of thermally stable artificial multienzyme cascade system for efficient enzymatic electrochemical detection

Show Author's information Xiqing Cheng1Jinhong Zhou1Jiayu Chen1Zhaoxiong Xie1,2Qin Kuang1( )Lansun Zheng1
State Key Laboratory of Physical Chemistry of Solid SurfacesCollaborative Innovation Center of Chemistry for Energy Materialsand Department of ChemistryCollege of Chemistry and Chemical EngineeringXiamen UniversityXiamen361005China
Pen-Tung Sah Institute of Micro-Nano Science and TechnologyXiamen UniversityXiamen361005China

Abstract

Recently, metal-organic framework (MOF)-based multienzyme systems integrating different functional natural enzymes and/or nanomaterial-based artificial enzymes are attracting increasing attention due to their high catalytic efficiency and promising application in sensing. Simple and controllable integration of enzymes or nanozymes within MOFs is crucial for achieving efficient cascade catalysis and high stability. Here, we report a facile electrochemical assisted biomimetic mineralization strategy to prepare an artificial multienzyme system for efficient electrochemical detection of biomolecules. By using the GOx@Cu-MOF/copper foam (GOx@Cu-MOF/CF) architecture as a proof of concept, efficient enzyme immobilization and cascade catalysis were achieved by in situ encapsulation of glucose oxidase (GOx) within MOFs layer grown on three-dimensional (3D) porous conducting CF via a facile one-step electrochemical assisted biomimetic mineralization strategy. Due to the bio-electrocatalytic cascade reaction mechanism, this well-designed GOx@Cu-MOF modified electrode exhibited superior catalytic activity and thermal stability for glucose sensing. Notably, the activity of GOx@Cu-MOF/CF still remained at ca. 80% after being incubated at 80 ℃. In sharp contrast, the activity of the unprotected electrode was reduced to the original 10% after the same treatment. The design strategy presented here may be useful in fabricating highly stable enzyme@MOF composites applied for efficient photothermal therapy and other platform under high temperature.

Keywords: metal-organic frameworks, thermal stability, artificial multienzyme, electrochemical assisted biomimetic mineralization, glucose detection

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Publication history
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Acknowledgements

Publication history

Received: 10 September 2019
Revised: 06 October 2019
Accepted: 17 October 2019
Published: 06 November 2019
Issue date: December 2019

Copyright

© Tsinghua University Press and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Acknowledgements

Acknowledgementsc

This work was supported by the National Key Research and Development Program of China (Nos. 2017YFA0206500 and 2017YFA0206801), the National Basic Research Program of China (No. 2015CB932301), and the National Natural Science Foundation of China (Nos. 21671163, 21721001, and J1310024).

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