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Title: Biomimetic catalysts of iron-based metal–organic frameworks with high peroxidase-mimicking activity for colorimetric biosensing

Abstract

The field of metal–organic framework (MOF)-based biomimetic catalysts has achieved great progress but is still in its infancy. The systematic investigation of the tailored construction of MOF-based biomimetic catalysts is required for further development. Herein, two iron-based MOFs, namely, [(Fe3O)2(H2O)4(HCOO)(L)2]n (HUST-5: H6L = hexakis(4-formylphenoxy) cyclotriphosphazene; HUST = Huazhong University of Science and Technology) and [(Fe3O)(H2O)3(L)]n (HUST-7) have been fabricated through the assembly of different iron clusters and hexa-carboxylate ligand under the control of the added acid species. The two MOFs exhibit distinct secondary building units (SBUs) and topological structures, which could be used as biomimetic catalysts for the systematic comparisons of structural characteristics and the catalytic activity. Both MOFs possess catalytic activity similar to that of natural peroxidases towards the catalysis of the oxidation of a variety of substrates. Significantly, HUST-5 and HUST-7 can effectively catalyze the oxidation of 3,3',5,5'-tetramethylbenzidine (TMB) by H2O2 accompanied by significant colorimetric biosensing. With same compositions, different catalytic performances were obtained due to differences in the porous structures and characteristics of SBUs in two Fe-MOFs, which was also validated by theoretical calculation results. Furthermore, the phenomenon of colorimetric biosensing could be significantly suppressed by the addition of ascorbic acid (AA) during the oxidation process ofmore » TMB. It was observed from these findings that a facile colorimetric biosensing platform for detecting H2O2 and ascorbic acid has been successfully explored. Therefore, this work provides another unique perspective for the tailor-made preparation of stable MOF-based peroxidase mimics with excellent catalytic performance and colorimetric biosensing.« less

Authors:
 [1];  [2]; ORCiD logo [3];  [3];  [1];  [2]; ORCiD logo [3]
  1. Wuhan Textile Univ. (China)
  2. Huazhong Univ. of Science and Technology, Wuhan (China)
  3. Texas A & M Univ., College Station, TX (United States)
Publication Date:
Research Org.:
Texas A & M Univ., College Station, TX (United States)
Sponsoring Org.:
USDOE Office of Fossil Energy (FE); USDOE Office of Science (SC), Basic Energy Sciences (BES); USDOE Office of Fossil Energy and Carbon Management (FECM)
OSTI Identifier:
1849174
Alternate Identifier(s):
OSTI ID: 1768901
Grant/Contract Number:  
FE0026472; SC0001015; DESC0001015
Resource Type:
Accepted Manuscript
Journal Name:
Dalton Transactions
Additional Journal Information:
Journal Volume: 50; Journal Issue: 11; Journal ID: ISSN 1477-9226
Publisher:
Royal Society of Chemistry
Country of Publication:
United States
Language:
English
Subject:
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY

Citation Formats

Wang, Xiao-Ning, Zhao, Yumeng, Li, Jia-Luo, Pang, Jian-Dong, Wang, Qiang, Li, Bao, and Zhou, Hong-Cai. Biomimetic catalysts of iron-based metal–organic frameworks with high peroxidase-mimicking activity for colorimetric biosensing. United States: N. p., 2021. Web. doi:10.1039/d0dt02504f.
Wang, Xiao-Ning, Zhao, Yumeng, Li, Jia-Luo, Pang, Jian-Dong, Wang, Qiang, Li, Bao, & Zhou, Hong-Cai. Biomimetic catalysts of iron-based metal–organic frameworks with high peroxidase-mimicking activity for colorimetric biosensing. United States. https://doi.org/10.1039/d0dt02504f
Wang, Xiao-Ning, Zhao, Yumeng, Li, Jia-Luo, Pang, Jian-Dong, Wang, Qiang, Li, Bao, and Zhou, Hong-Cai. Fri . "Biomimetic catalysts of iron-based metal–organic frameworks with high peroxidase-mimicking activity for colorimetric biosensing". United States. https://doi.org/10.1039/d0dt02504f. https://www.osti.gov/servlets/purl/1849174.
@article{osti_1849174,
title = {Biomimetic catalysts of iron-based metal–organic frameworks with high peroxidase-mimicking activity for colorimetric biosensing},
author = {Wang, Xiao-Ning and Zhao, Yumeng and Li, Jia-Luo and Pang, Jian-Dong and Wang, Qiang and Li, Bao and Zhou, Hong-Cai},
abstractNote = {The field of metal–organic framework (MOF)-based biomimetic catalysts has achieved great progress but is still in its infancy. The systematic investigation of the tailored construction of MOF-based biomimetic catalysts is required for further development. Herein, two iron-based MOFs, namely, [(Fe3O)2(H2O)4(HCOO)(L)2]n (HUST-5: H6L = hexakis(4-formylphenoxy) cyclotriphosphazene; HUST = Huazhong University of Science and Technology) and [(Fe3O)(H2O)3(L)]n (HUST-7) have been fabricated through the assembly of different iron clusters and hexa-carboxylate ligand under the control of the added acid species. The two MOFs exhibit distinct secondary building units (SBUs) and topological structures, which could be used as biomimetic catalysts for the systematic comparisons of structural characteristics and the catalytic activity. Both MOFs possess catalytic activity similar to that of natural peroxidases towards the catalysis of the oxidation of a variety of substrates. Significantly, HUST-5 and HUST-7 can effectively catalyze the oxidation of 3,3',5,5'-tetramethylbenzidine (TMB) by H2O2 accompanied by significant colorimetric biosensing. With same compositions, different catalytic performances were obtained due to differences in the porous structures and characteristics of SBUs in two Fe-MOFs, which was also validated by theoretical calculation results. Furthermore, the phenomenon of colorimetric biosensing could be significantly suppressed by the addition of ascorbic acid (AA) during the oxidation process of TMB. It was observed from these findings that a facile colorimetric biosensing platform for detecting H2O2 and ascorbic acid has been successfully explored. Therefore, this work provides another unique perspective for the tailor-made preparation of stable MOF-based peroxidase mimics with excellent catalytic performance and colorimetric biosensing.},
doi = {10.1039/d0dt02504f},
journal = {Dalton Transactions},
number = 11,
volume = 50,
place = {United States},
year = {Fri Feb 19 00:00:00 EST 2021},
month = {Fri Feb 19 00:00:00 EST 2021}
}

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