Rational Design Strategies for Nanozymes

被引:129
|
作者
Chen, Zhen [1 ]
Yu, Yixin [1 ]
Gao, Yonghui [1 ]
Zhu, Zhiling [1 ]
机构
[1] Qingdao Univ Sci & Technol, Coll Mat Sci & Engn, Qingdao 266042, Shandong, Peoples R China
基金
中国国家自然科学基金;
关键词
nanozyme; rational design; data-driven; computing-driven; high-throughputscreening; machinelearning; database; descriptor; mechanism; ENZYME; DISCOVERY; OXIDASE;
D O I
10.1021/acsnano.3c04378
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Nanozymesconstitute an emerging class of nanomaterialswith enzyme-likecharacteristics. Over the past 15 years, more than 1200 nanozymeshave been developed, and they have demonstrated promising potentialsin broad applications. With the diversification and complexity ofits applications, traditional empirical and trial-and-error designstrategies no longer meet the requirements for efficient nanozymedesign. Thanks to the rapid development of computational chemistryand artificial intelligence technologies, first-principles methodsand machine-learning algorithms are gradually being adopted as a moreefficient and easier means to assist nanozyme design. This reviewfocuses on the potential elementary reaction mechanisms in the rationaldesign of nanozymes, including peroxidase (POD)-, oxidase (OXD)-,catalase (CAT)-, superoxide dismutase (SOD)-, and hydrolase (HYL)-likenanozymes. The activity descriptors are introduced, with the aim ofproviding further guidelines for nanozyme active material screening.The computing- and data-driven approaches are thoroughly reviewedto give a proposal on how to proceed with the next-generation paradigmrational design. At the end of this review, personal perspectiveson the prospects and challenges of the rational design of nanozymesare put forward, hoping to promote the further development of nanozymestoward superior application performance in the future.
引用
收藏
页码:13062 / 13080
页数:19
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