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Data-informed discovery of hydrolytic nanozymes.

Sirong LiZijun ZhouZuoxiu TieBing WangMeng YeLei DuRan CuiWei LiuCuihong WanQuanyi LiuSheng ZhaoQuan WangYihong ZhangShuo ZhangHuigang ZhangYan DuHui Wei
Published in: Nature communications (2022)
Nanozyme is a collection of nanomaterials with enzyme-like activity but higher environmental tolerance and long-term stability than their natural counterparts. Improving the catalytic activity and expanding the category of nanozymes are prerequisites to complement or even supersede enzymes. However, the development of hydrolytic nanozymes is still challenged by diverse hydrolytic substrates and following complicated mechanisms. Here, two strategies are informed by data to screen and predict catalytic active sites of MOF (metal-organic framework) based hydrolytic nanozymes: (1) to increase the intrinsic activity by finely tuned Lewis acidity of the metal clusters; (2) to improve the density of active sites by shortening the length of ligands. Finally, as-obtained Ce-FMA-MOF-based hydrolytic nanozyme is capable of cleaving phosphate bonds, amide bonds, glycosidic bonds, and even their mixture, biofilms. This work provides a rational methodology to design hydrolytic nanozyme, enriches the diversity of nanozymes, and potentially sheds light on future evolution of enzyme engineering.
Keyphrases
  • metal organic framework
  • electronic health record
  • high throughput
  • small molecule
  • current status
  • machine learning
  • data analysis
  • deep learning