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Encoding biological recognition in a bicomponent cell-membrane mimic.

Authors :
Rodriguez-Emmenegger C
Xiao Q
Kostina NY
Sherman SE
Rahimi K
Partridge BE
Li S
Sahoo D
Reveron Perez AM
Buzzacchera I
Han H
Kerzner M
Malhotra I
Möller M
Wilson CJ
Good MC
Goulian M
Baumgart T
Klein ML
Percec V
Source :
Proceedings of the National Academy of Sciences of the United States of America [Proc Natl Acad Sci U S A] 2019 Mar 19; Vol. 116 (12), pp. 5376-5382. Date of Electronic Publication: 2019 Feb 28.
Publication Year :
2019

Abstract

Self-assembling dendrimers have facilitated the discovery of periodic and quasiperiodic arrays of supramolecular architectures and the diverse functions derived from them. Examples are liquid quasicrystals and their approximants plus helical columns and spheres, including some that disregard chirality. The same periodic and quasiperiodic arrays were subsequently found in block copolymers, surfactants, lipids, glycolipids, and other complex molecules. Here we report the discovery of lamellar and hexagonal periodic arrays on the surface of vesicles generated from sequence-defined bicomponent monodisperse oligomers containing lipid and glycolipid mimics. These vesicles, known as glycodendrimersomes, act as cell-membrane mimics with hierarchical morphologies resembling bicomponent rafts. These nanosegregated morphologies diminish sugar-sugar interactions enabling stronger binding to sugar-binding proteins than densely packed arrangements of sugars. Importantly, this provides a mechanism to encode the reactivity of sugars via their interaction with sugar-binding proteins. The observed sugar phase-separated hierarchical arrays with lamellar and hexagonal morphologies that encode biological recognition are among the most complex architectures yet discovered in soft matter. The enhanced reactivity of the sugar displays likely has applications in material science and nanomedicine, with potential to evolve into related technologies.<br />Competing Interests: The authors declare no conflict of interest.<br /> (Copyright © 2019 the Author(s). Published by PNAS.)

Details

Language :
English
ISSN :
1091-6490
Volume :
116
Issue :
12
Database :
MEDLINE
Journal :
Proceedings of the National Academy of Sciences of the United States of America
Publication Type :
Academic Journal
Accession number :
30819900
Full Text :
https://doi.org/10.1073/pnas.1821924116