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Title: Glycosylated Peptoid Nanosheets as a Multivalent Scaffold for Protein Recognition

Abstract

Glycoproteins adhered on the cellular membrane play an important role in a wide range of cellular functions. Their significance is particularly relevant in the recognition process between infectious pathogens (such as viruses, bacteria, toxins) and their host cells. Multivalent interactions at the pathogen-cell interfaces govern binding events and can result in a strong and specific interaction. Here in this paper, we report an approach to mimic the cell surface presentation of carbohydrate ligands by the multivalent display of sugars on the surface of peptoid nanosheets. The constructs provide a highly organized 2D platform for recognition of carbohydrate-binding proteins. The sugars were displayed using different linker lengths or within loops containing 2-6 hydrophilic peptoid monomers. Both the linkers and the loops contained one alkyne-bearing monomer, to which different saccharides were attached by copper-catalyzed azide-alkyne cycloaddition reactions. Peptoid nanosheets functionalized with different saccharide groups were able to selectively bind multivalent lectins, Concanavalin A and Wheat Germ Agglutinin, as observed by fluorescence microscopy and a homogeneous Förster resonance energy transfer (FRET)-based binding assay. To evaluate the potential of this system as sensor for threat agents, the ability of functionalized peptoid nanosheets to bind Shiga toxin was also studied. Peptoid nanosheets were functionalized withmore » globotriose, the natural ligand of Shiga toxin, and the effective binding of the nanomaterial was verified by the FRET-based binding assay. In all cases, evidence for multivalent binding was observed by systematic variation of the ligand display density on the nanosheet surface. These cell surface mimetic nanomaterials may find utility in the inactivation of pathogens or as selective molecular recognition elements.« less

Authors:
 [1];  [1];  [2]; ORCiD logo [1];  [1];  [1];  [1];  [1]; ORCiD logo [1]
  1. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  2. New York Univ. (NYU), NY (United States)
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER)
OSTI Identifier:
1513795
Grant/Contract Number:  
AC02-05CH11231
Resource Type:
Accepted Manuscript
Journal Name:
ACS Nano
Additional Journal Information:
Journal Volume: 12; Journal Issue: 3; Journal ID: ISSN 1936-0851
Publisher:
American Chemical Society (ACS)
Country of Publication:
United States
Language:
English
Subject:
77 NANOSCIENCE AND NANOTECHNOLOGY; protein-mimetic materials; molecular recognition; multivalent binding; two-dimensional nanomaterials; bioinspired polymers; cell-surface mimetics

Citation Formats

Battigelli, Alessia, Kim, Jae Hong, Dehigaspitiya, Dilani C., Proulx, Caroline, Robertson, Ellen J., Murray, Daniel J., Rad, Behzad, Kirshenbaum, Kent, and Zuckermann, Ronald N. Glycosylated Peptoid Nanosheets as a Multivalent Scaffold for Protein Recognition. United States: N. p., 2018. Web. doi:10.1021/acsnano.7b08018.
Battigelli, Alessia, Kim, Jae Hong, Dehigaspitiya, Dilani C., Proulx, Caroline, Robertson, Ellen J., Murray, Daniel J., Rad, Behzad, Kirshenbaum, Kent, & Zuckermann, Ronald N. Glycosylated Peptoid Nanosheets as a Multivalent Scaffold for Protein Recognition. United States. doi:10.1021/acsnano.7b08018.
Battigelli, Alessia, Kim, Jae Hong, Dehigaspitiya, Dilani C., Proulx, Caroline, Robertson, Ellen J., Murray, Daniel J., Rad, Behzad, Kirshenbaum, Kent, and Zuckermann, Ronald N. Mon . "Glycosylated Peptoid Nanosheets as a Multivalent Scaffold for Protein Recognition". United States. doi:10.1021/acsnano.7b08018. https://www.osti.gov/servlets/purl/1513795.
@article{osti_1513795,
title = {Glycosylated Peptoid Nanosheets as a Multivalent Scaffold for Protein Recognition},
author = {Battigelli, Alessia and Kim, Jae Hong and Dehigaspitiya, Dilani C. and Proulx, Caroline and Robertson, Ellen J. and Murray, Daniel J. and Rad, Behzad and Kirshenbaum, Kent and Zuckermann, Ronald N.},
abstractNote = {Glycoproteins adhered on the cellular membrane play an important role in a wide range of cellular functions. Their significance is particularly relevant in the recognition process between infectious pathogens (such as viruses, bacteria, toxins) and their host cells. Multivalent interactions at the pathogen-cell interfaces govern binding events and can result in a strong and specific interaction. Here in this paper, we report an approach to mimic the cell surface presentation of carbohydrate ligands by the multivalent display of sugars on the surface of peptoid nanosheets. The constructs provide a highly organized 2D platform for recognition of carbohydrate-binding proteins. The sugars were displayed using different linker lengths or within loops containing 2-6 hydrophilic peptoid monomers. Both the linkers and the loops contained one alkyne-bearing monomer, to which different saccharides were attached by copper-catalyzed azide-alkyne cycloaddition reactions. Peptoid nanosheets functionalized with different saccharide groups were able to selectively bind multivalent lectins, Concanavalin A and Wheat Germ Agglutinin, as observed by fluorescence microscopy and a homogeneous Förster resonance energy transfer (FRET)-based binding assay. To evaluate the potential of this system as sensor for threat agents, the ability of functionalized peptoid nanosheets to bind Shiga toxin was also studied. Peptoid nanosheets were functionalized with globotriose, the natural ligand of Shiga toxin, and the effective binding of the nanomaterial was verified by the FRET-based binding assay. In all cases, evidence for multivalent binding was observed by systematic variation of the ligand display density on the nanosheet surface. These cell surface mimetic nanomaterials may find utility in the inactivation of pathogens or as selective molecular recognition elements.},
doi = {10.1021/acsnano.7b08018},
journal = {ACS Nano},
number = 3,
volume = 12,
place = {United States},
year = {2018},
month = {2}
}

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