Introducing molecular imprinting onto nanozymes: toward selective catalytic analysis

Bu, Zhijian; Huang, Lian; Li, Shu; Tian, Qingzhen; Tang, Zheng; Diao, Qiaoqiao; Chen, Xinyu; Liu, Jinjin; Niu, Xiangheng

doi:10.1007/s00216-024-05183-2

Anal Bioanal Chem

2024

DOI: 10.1007/s00216-024-05183-2

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Introducing molecular imprinting onto nanozymes: toward selective catalytic analysis

Zhijian Bu,

Lian Huang,

Shu Li

et al.

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Cited by 3 publications

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Molecularly Imprinted Nanozymes with Substrate Specificity: Current Strategies and Future Direction

Zhang,

Luo,

Wang

et al. 2024

Small

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Molecular imprinting technology (MIT) stands out for its exceptional simplicity and customization capabilities and has been widely employed in creating artificial antibodies that can precisely recognize and efficiently capture target molecules. Concurrently, nanozymes have emerged as promising enzyme mimics in the biomedical field, characterized by their remarkable stability, ease of production scalability, robust catalytic activity, and high tunability. Drawing inspiration from natural enzymes, molecularly imprinted nanozymes combine the unique benefits of both MIT and nanozymes, thereby conferring biomimetic catalysts with substrate specificity and catalytic selectivity. In this review, the latest strategies for the fabrication of molecularly imprinted nanozymes, focusing on the use of organic polymers and inorganic nanomaterials are explored. Additionally, cutting‐edge techniques for generating atom‐layer‐imprinted islands with ultra‐thin atomic‐scale thickness is summarized. Their applications are particularly noteworthy in the fields of catalyst optimization, detection techniques, and therapeutic strategies, where they boost reaction selectivity and efficiency, enable precise identification and quantification of target substances, and enhance therapeutic effectiveness while minimizing adverse effects. Lastly, the prevailing challenges in the field and delineate potential avenues for future progress is encapsulated. This review will foster advancements in artificial enzyme technology and expand its applications.

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Molecularly Imprinted Nanozymes with Substrate Specificity: Current Strategies and Future Direction

Zhang,

Luo,

Wang

et al. 2024

Small

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Frontiers in laccase nanozymes-enabled colorimetric sensing: A review

Mekonnen,

Abda,

Csáki

et al. 2024

Analytica Chimica Acta

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Applications of Nanozymes in Chiral-Molecule Recognition through Electrochemical and Ultraviolet–Visible Analysis

Dai,

Chen,

et al. 2024

Molecules

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Chiral molecules have similar physicochemical properties, which are different in terms of physiological activities and toxicities, rendering their differentiation and recognition highly significant. Nanozymes, which are nanomaterials with inherent enzyme-like activities, have garnered significant interest owing to their high cost-effectiveness, enhanced stability, and straightforward synthesis. However, constructing nanozymes with high activity and enantioselectivity remains a significant challenge. This review briefly introduces the synthesis methods of chiral nanozymes and systematically summarizes the latest research progress in enantioselective recognition of chiral molecules based on electrochemical methods and ultraviolet–visible absorption spectroscopy. Moreover, the challenges and development trends in developing enantioselective nanozymes are discussed. It is expected that this review will provide new ideas for the design of multifunctional chiral nanozymes and broaden the application field of nanozymes.

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Introducing molecular imprinting onto nanozymes: toward selective catalytic analysis

Cited by 3 publications

References 64 publications

Molecularly Imprinted Nanozymes with Substrate Specificity: Current Strategies and Future Direction

Molecularly Imprinted Nanozymes with Substrate Specificity: Current Strategies and Future Direction

Frontiers in laccase nanozymes-enabled colorimetric sensing: A review

Applications of Nanozymes in Chiral-Molecule Recognition through Electrochemical and Ultraviolet–Visible Analysis

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