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Cited by 536

The DOI matches its Crossref record; 38 of the 38 references it cites were found in a registry or an index.

Oxidase-like MOF-818 Nanozyme with High Specificity for Catalysis of Catechol Oxidation

Li, Minghua, Chen, Jinxing, Wu, Weiwei, Fang, Youxing, Dong, Shaojun·2020·Journal of the American Chemical Society

Abstract

Despite the extensive studies of the nanozymes showing their superior properties compared to natural enzymes and traditional artificial enzymes, the development of highly specific nanozymes is still a challenge. The catechol oxidase specifically catalyzing the oxidations of o -diphenol to the corresponding o -quinone is important to the biosynthesis of melanin and other polyphenolic natural products. In this study, we first propose that MOF-818, containing trinuclear copper centers mimicking the active sites of natural catechol oxidase, shows efficient catechol oxidase activity with good specificity and no peroxidase-like characteristics. MOF-818 has good specificity and high catalytic activity as a novel catechol oxidase nanozyme.

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Metadata

Authors
Li, M., Chen, J., Wu, W., Fang, Y., & Dong, S.
Venue
Journal of the American Chemical Society
Published
2020-08-13
Volume
142
Issue
36
Pages
15569-15574
ISSN
  • 0002-7863 (ISSN-L)
  • 1520-5126
OpenAlex
W3049707817
Cited by
536
References
38
FWCI
22.84
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Oxidase-like MOF-818 Nanozyme with High Specificity for Catalysis of Catechol Oxidation. https://app.cochat.ai/papers/10.1021/jacs.0c07273
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Li, M., Chen, J., Wu, W., Fang, Y., & Dong, S. (2020). Oxidase-like MOF-818 Nanozyme with High Specificity for Catalysis of Catechol Oxidation. Journal of the American Chemical Society. https://doi.org/10.1021/jacs.0c07273

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.