Improved detection and recognition of glycoproteins using fluorescent polymers with a molecular imprint based on glycopeptides

• Published in: Mikrochimica acta (1966) Vol. 188; no. 12; p. 439
• Main Authors: Li, Jing, Yang, Yixuan, Zhu, Aihong, Li, Lujun, Liu, Xia, Xie, Xiaoyu
• Format: Journal Article
• Language: English
• Published: Vienna Springer Vienna 01.12.2021; Springer; Springer Nature B.V
• Subjects: Adsorption; Albumin; Analytical Chemistry; Antibiotics; Biological properties; Characterization and Evaluation of Materials; Chemistry; Chemistry and Materials Science; Fluorescence; Glycan; Glycopeptides; Glycopeptides - metabolism; Glycoproteins; Glycoproteins - metabolism; Graphene; Imprinted polymers; Microengineering; Molecular Imprinting - methods; Nanochemistry; Nanotechnology; Nitrogen; Original Paper; Ovalbumin; Peptides; Polymer industry; Polymers - metabolism; Quantum dots; Recognition; Selectivity; Precision recognition; Glycoprotein detection; Glycopeptide template; Fluorescent molecularly imprinting
• ISSN: 0026-3672; 1436-5073
• DOI: 10.1007/s00604-021-05099-z

Highly specific novel glycopeptide-based fluorescent molecularly imprinting polymers (g-FMIPs) were constructed to recognize and determine the target glycoprotein in complex biological samples. The glycopeptide of ovalbumin (OVA), with the unique structural characteristics of glycan and peptide, and potential application in improving the specificity recognition of g-FMIPs, was selected as the template molecule. The nitrogen-doped graphene quantum dots (N-GQDs) were introduced for fluorescence response. The obtained g-FMIPs possessed rapid binding kinetics and high adsorption capacity. Notably, the g-FMIPs exhibited remarkable selectivity and sensitivity with a high imprinting factor of 6.57, good linearity of 0.625 − 5.00 μM, and limit of detection of 0.208 μM. After treatment with g-FMIPs, the concentration of OVA in eluted solution was 1.07 μM. The obtained recoveries at 1.43 μM, 2.86 μM, and 4.29 μM spiked concentrations were 97.2%, 93.5%, and 101%, respectively, and the relative standard deviations were 2.6%, 4.2%, and 1.1%, respectively. In summary, the proposed strategy will expand the MIPs construction method and its application prospects in precision recognition and sensitive detection of trace glycoproteins from complex biosamples. Graphical abstract