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Colorimetric logic gate for alkaline phosphatase based on copper (II)-based metal-organic frameworks with peroxidase-like activity.

Authors :
Wang C
Gao J
Cao Y
Tan H
Source :
Analytica chimica acta [Anal Chim Acta] 2018 Apr 03; Vol. 1004, pp. 74-81. Date of Electronic Publication: 2017 Dec 12.
Publication Year :
2018

Abstract

Nanozymes have been extensively exploited in the construction of colorimetric sensors in the past decade. However, as lack of specific recognition element, these sensors are mostly limited in the detection of hydrogen peroxide and its related agents. In this work, a colorimetric assay for the detection of alkaline phosphatase (ALP) activity was developed by employing copper (II)-based metal-organic frameworks (Cu-MOFs) as peroxidase mimic and pyrophosphate (PPi) as recognition element. Benefiting from its intrinsic porosity, Cu-MOFs built from one-step self-assembly showed a superior catalytic activity over horseradish peroxidase. It was found that, in the presence of PPi, the catalytic activity of Cu-MOFs was greatly inhibited due to the ultrastrong binding ability of Cu <superscript>2+</superscript> with PPi, and no colorimetric signal was recorded. However, after incubation with ALP, such negative behavior of PPi can be suppressed as the hydrolysis of PPi into orthophosphates (Pi) with low affinity to Cu <superscript>2+</superscript> , producing a colorimetric signal depending on ALP level. On this basis, a way for quantitative analysis of ALP activity was paved accordingly. Compared with previously reported ALP assays based on nanomaterials, this assay is simple, cost-effective and visualized, which not only allows highly sensitive analysis of ALP activity with a detection limit of 0.19 U/L, but also exhibits a good sensing performance in serum samples. Furthermore, based on the distinct colorimetric signals induced by PPi and ALP, an IMPLICATION logic gate was constructed. We hope that this study could provide a new insight for designing nanozyme-based highly specific colorimetric sensors.<br /> (Copyright © 2017 Elsevier B.V. All rights reserved.)

Details

Language :
English
ISSN :
1873-4324
Volume :
1004
Database :
MEDLINE
Journal :
Analytica chimica acta
Publication Type :
Academic Journal
Accession number :
29329711
Full Text :
https://doi.org/10.1016/j.aca.2017.11.078