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Reference type: Journal
Authors: Morishige T, Takano E, Sunayama H, Kitayama Y, Takeuchi T
Article Title: Post-Imprinting-Modified Molecularly Imprinted Nanocavities with Two Synergetic, Orthogonal, Glycoprotein-Binding Sites to Transduce Binding Events into Fluorescence Changes.
Publication date: 2019
Journal: ChemNanoMat
Volume: 5
Issue: (2)
Page numbers: 224-229.
DOI: 10.1002/cnma.201800519

Abstract: We developed sensitive and selective polymeric nanocavities for glycoprotein detection using a novel molecular imprinting technique involving post-imprinting modification (PIM). It allowed the introduction of two different interaction sites and a fluorescent reporter within each nanocavity. The hepatocellular carcinoma biomarker α-fetoprotein (AFP) was used as a model glycoprotein. For PIM-based molecular imprinting, AFP conjugated with polymerizable groups by disulfide bonding was prepared and immobilized on a 4-carboxy-3-fluorophenylboronic acid-immobilized substrate by cyclic diester formation between AFP glycans in an oriented immobilization manner, facilitating the creation of homogeneous AFP-imprinted nanocavities. Surface-initiated controlled/living radical polymerization was performed with a functional monomer, co-monomer, and crosslinker. The disulfide bonds and cyclic diesters were cleaved to create AFP-imprinted nanocavities, generating free thiol groups present inside the nanocavities only. A thiol-reactive fluorescent dye was added to the nanocavities by in-cavity PIM, yielding signaling AFP-imprinted nanocavities capable of transducing AFP-binding events into fluorescence changes. Reference proteins showed little response, while the limit of detection of AFP was 0.27 ng/mL (ca. 3.9 pM) in diluted human serum. Thus, the proposed in-cavity PIM-based molecular imprinting technique is effective for ELISA-relevant, antibody-free sensing systems for glycoproteins
Template and target information: glycoprotein, α-fetoprotein, AFP
Author keywords: molecular imprinting, Post-imprinting modification, molecular recognition, glycoproteins, sensors


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