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  • Title: Orientationally Fabricated Zwitterionic Molecularly Imprinted Nanocavities for Highly Sensitive Glycoprotein Recognition.
    Author: Saeki T, Sunayama H, Kitayama Y, Takeuchi T.
    Journal: Langmuir; 2019 Feb 05; 35(5):1320-1326. PubMed ID: 29940727.
    Abstract:
    Glycoprotein recognition has recently gained a lot of attention, since glycoproteins play important roles in a diverse range of biological processes. Robustly synthesized glycoprotein receptors, such as molecularly imprinted polymers (MIPs), which can be easily and sustainably handled, are highly attractive as antibody substitutes because of the difficulty in obtaining high-affinity antibodies specific for carbohydrate-containing antigens. Herein, molecularly imprinted nanocavities for glycoproteins have been fabricated via a bottom-up molecular imprinting approach using surface-initiated atom transfer radical polymerization (SI-ATRP). As a model glycoprotein, ovalbumin was immobilized in a specific orientation onto a surface plasmon resonance sensor chip by forming a conventional cyclic diester between boronic acid and cis-diol. Biocompatible polymer matrices were formed around the template molecule, ovalbumin, using SI-ATRP via a hydrophilic comonomer, 2-methacryloyloxyethyl phosphorylcholine, in the presence of pyrrolidyl acrylate (PyA), a functional monomer capable of electrostatically interacting with ovalbumin. The removal of ovalbumin left MIPs with binding cavities containing boronic acid and PyA residues located at suitable positions for specifically binding ovalbumin. Careful analysis revealed that strict control over the polymer significantly improved sensitivity and selectivity for ovalbumin recognition, with a limit of detection of 6.41 ng/mL. Successful detection of ovalbumin in an egg white matrix was demonstrated to confirm the practical utility of this approach. Thus, this strategy of using a polymer-based recognition of a glycoprotein through molecularly imprinted nanocavities precisely prepared using a bottom-up approach provides a potentially powerful approach for detection of other glycoproteins.
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