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Biomass activated carbon–derived imprinted polymer with multi-boronic acid sites for selective capture of glycoprotein

Biomass activated carbon–derived imprinted polymer with multi-boronic acid sites for selective capture of glycoprotein

Authors :
Hao Yu
Wei Chen
Qingyun Liu
Zhiyang Guo
Xixi Zhu
Min Fu
Qian Ding
Source :
Journal of Colloid and Interface Science. 596:225-232
Publication Year :
2021
Publisher :
Elsevier BV, 2021.

Abstract

Glycoproteins play crucial roles in many biological events such as protein folding, information transmission, nerve conduction, and molecular recognition. Some glycoproteins serve as disease biomarkers in clinical settings. However, selective detection of glycoprotein often faces great challenges, owing to its low abundance in complex biological samples. In this case, develop a highly sensitive and selective approach for glycoprotein detection is urgently needed. Molecularly imprinted polymers (MIPs) have proved to be an ideal absorbent material in detection and separation science. Herein, a novel biomass activated carbon–derived imprinted polymer (BAC@PEI/PBA/MIPs) was fabricated for selective recognition of glycoprotein. The as-prepared BAC@PEI/PBA/MIPs was synthesized using waste tea derived carbon as matrix, albumin chicken egg (OVA) as template, and dopamine as functional monomer. Branched polyethyleneimine (PEI) was covalently bonded on the BAC surface to increase the number of boronic acid moieties. Benefiting from the self-polymerization of dopamine and multi-boronic acid sites, a great number of recognition sites were presented under mild conditions. The static adsorption experiment showed that the BAC@PEI/PBA/MIPs exhibited a high binding capacity of 196.2 mg/g, rapid adsorption dynamics of 40 min, excellent selectivity and satisfactory reusability for OVA. Furthermore, the practicability of BAC@PEI/PBA/MIPs was verified by isolation of OVA from egg white. The good binding performance and facile preparation process make BAC@PEI/PBA/MIPs attractive for glycoprotein recognition, indicating its potential applications in biomedical research and clinical diagnostics.

Details

ISSN :
00219797
Volume :
596
Database :
OpenAIRE
Journal :
Journal of Colloid and Interface Science
Accession number :
edsair.doi.dedup.....23a35c9ab45d64c607abf0927f36f663
Full Text :
https://doi.org/10.1016/j.jcis.2021.03.151