Self‐Assembly of Minimalist Amyloid Peptides to Produce Metal‐Free Nanofibrils Possessing Robust and Photoswitchable Metallooxidase‐Mimetic Catalytic Functions

Achieving metal-free biomimetic catalysis, traditionally mediated by metalloenzymes, has been intriguing research for the development of metal-free carbon catalysts and for understanding the natural evolution of enzymes. In this study, the self-assembly of Fmoc-F-based dipeptides as minimalistic building blocks is reported, which, in the absence of metal or organic cofactors, exhibit catalytic functions similar to those of heme-dependent peroxidases. These dipeptides form β-sheet-based nanofibrils that organize functional groups in an ordered arrangement, facilitating the catalysis of H₂O₂ reduction through the formation of ternary complex intermediates. The influence of metal impurities on the catalysis is also ruled out through ICP-MS analysis and the addition of transition metal ions. Remarkably, the activity of this biomimetic catalyst can be fully restored after ten or more cycles of thermal or acid treatment. Additionally, the catalyst can be dynamically photo-switched between ON and OFF states by the noncovalent introduction of a photoisomerizable azobenzene derivative into the assemblies, indicating its robustness and adaptability. These findings provide new insights into the design of advanced catalytic materials and offer a valuable understanding of the functional principles of primitive cofactor-free enzymes.

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Publication Details

Journal
Small
Published
2025-06-16
DOI
https://doi.org/10.1002/smll.202501778
Citations
3
Primary Topic
Supramolecular Self-Assembly in Materials
Type
article
Field-Weighted Citation Impact
1.79

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article

Self‐Assembly of Minimalist Amyloid Peptides to Produce Metal‐Free Nanofibrils Possessing Robust and Photoswitchable Metallooxidase‐Mimetic Catalytic Functions

Baoli Zhang, Haifeng Wu, Yuanxi Liu, Shichao Xu et al.
3 citations
Small
Supramolecular Self-Assembly in Materials
1.79
article

Self‐Assembly of Minimalist Amyloid Peptides to Produce Metal‐Free Nanofibrils Possessing Robust and Photoswitchable Metallooxidase‐Mimetic Catalytic Functions

Baoli Zhang, Haifeng Wu, Yuanxi Liu, Shichao Xu, Zhen‐Gang Wang
article en
3 citations

Abstract

Achieving metal-free biomimetic catalysis, traditionally mediated by metalloenzymes, has been intriguing research for the development of metal-free carbon catalysts and for understanding the natural evolution of enzymes. In this study, the self-assembly of Fmoc-F-based dipeptides as minimalistic building blocks is reported, which, in the absence of metal or organic cofactors, exhibit catalytic functions similar to those of heme-dependent peroxidases. These dipeptides form β-sheet-based nanofibrils that organize functional groups in an ordered arrangement, facilitating the catalysis of H₂O₂ reduction through the formation of ternary complex intermediates. The influence of metal impurities on the catalysis is also ruled out through ICP-MS analysis and the addition of transition metal ions. Remarkably, the activity of this biomimetic catalyst can be fully restored after ten or more cycles of thermal or acid treatment. Additionally, the catalyst can be dynamically photo-switched between ON and OFF states by the noncovalent introduction of a photoisomerizable azobenzene derivative into the assemblies, indicating its robustness and adaptability. These findings provide new insights into the design of advanced catalytic materials and offer a valuable understanding of the functional principles of primitive cofactor-free enzymes.

SmallVol. 21(32)
Beijing University of Chemical Technology (CN)
National Natural Science Foundation of China, Natural Science Foundation of Beijing Municipality, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 16%
Supramolecular Self-Assembly in Materials
1.79
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Self‐Assembly of Minimalist Amyloid Peptides to Produce Metal‐Free Nanofibrils Possessing Robust and Photoswitchable Metallooxidase‐Mimetic Catalytic Functions — Baoli Zhang, Haifeng Wu, et al. · Small (2025) | TGRS Research Map | TGRS