4.6 Article

Preparation of graphene oxide-modified affinity capillary monoliths based on three types of amino donor for chiral separation and proteolysis

Journal

JOURNAL OF CHROMATOGRAPHY A
Volume 1456, Issue -, Pages 249-256

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/j.chroma.2016.06.025

Keywords

Chiral separation; Capillary electrochromatography; Enzyme; Graphene; Protein; Silica monolith

Funding

  1. Fundamental Research Funds for the Central Universities [2015PY002]
  2. Priority Academic Program Development of Jiangsu Higher Education Institutions

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Novel graphene oxide (GO)-modified affinity capillary monoliths were developed employing human serum albumin (HSA) or pepsin as chiral selector. Three types of amino donors for GO immobilization, including ammonium hydroxide (NH4OH), ethanediamine (EDA) and polyethyleneimine (PEI), were applied to explore the effect of spacer arm on enantioseparation. It was observed that HSA-GO-EDA-based affinity capillary monoliths exhibited better chiral recognition ability in comparison with the other two spacer-based monoliths. Under the optimized conditions, the obtained columns revealed satisfactory repeatability concerning column-to-column, run-to-run and interday repeatability. In addition, the impact of GO concentration on enantiomeric separation was also investigated. HSA-GO-EDA-based affinity capillary monoliths provided higher chiral selectivity for nine pairs of enantiomers compared to the columns without GO. Furthermore, the influence of amino donors and GO on proteolytic activity of pepsin-based immobilized enzymatic reactor (IMER) was discussed. Unfortunately, pepsin-GO-PEI-based affinity capillary monoliths possessed the highest protein digestion capacity, which was different from the effect of amino donors on enantiorecognition. Moreover, GO presented as a favorable choice to improve the enzymatic activity of IMER. These results proved that GO-functionalized affinity capillary monoliths have promising potential for chiral separation and proteolysis. (C) 2016 Elsevier B.V. All rights reserved.

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