Issue 65, 2019, Issue in Progress

PEGylation of protein-imprinted nanocomposites sandwiching CdTe quantum dots with enhanced fluorescence sensing selectivity

Abstract

Fluorescent sensors combining the selective recognition of protein molecularly imprinted polymers (MIPs) and the fluorescent sensing of quantum dots (QDs) have been studied considerably, but their fluorescence sensing selectivity for the target proteins remains to be increased. Herein, we propose a strategy for increasing the sensing selectivity by post-imprinting PEGylation of surface protein-imprinted nanocomposites with embedded QDs. With bovine hemoglobin (BHb) as a model protein template, protein MIP nanolayers were anchored over the CdTe QD decorated SiO2 nanoparticles by the sol–gel process using aminopropyltriethoxy silane and tetraethoxysilicane. PEG chains were then grafted onto the surface of the imprinted nanostructures via the nucleophilic reaction of the surface amine groups with N-hydroxysuccinimide ester-terminal methoxy-PEG, followed by template removal. The resultant PEGylated sensors showed significantly improved aqueous dispersion stability compared with the non-PEGylated controls. More importantly, such PEGylation greatly increased the fluorescence response selectivity, with the Stern–Volmer equation based imprinting factor increasing from 2.7 to 5.4. The PEGylated sensors were applied to determine BHb in bovine serum samples with satisfactory recoveries at three spiking levels ranging from 94.3 to 103.7%, indicating their potential application in real samples.

Graphical abstract: PEGylation of protein-imprinted nanocomposites sandwiching CdTe quantum dots with enhanced fluorescence sensing selectivity

Supplementary files

Article information

Article type
Paper
Submitted
19 Oct 2019
Accepted
18 Nov 2019
First published
21 Nov 2019
This article is Open Access
Creative Commons BY-NC license

RSC Adv., 2019,9, 38165-38173

PEGylation of protein-imprinted nanocomposites sandwiching CdTe quantum dots with enhanced fluorescence sensing selectivity

X. Han, W. Han, S. Zhang, Z. Liu and G. Fu, RSC Adv., 2019, 9, 38165 DOI: 10.1039/C9RA08556D

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