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Cited by 383

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Control of Multivalent Interactions by Binding Epitope Density

Cairo, Christopher W., Gestwicki, Jason E., Kanai, Motomu, Kiessling, Laura L.·2002·Journal of the American Chemical Society

Abstract

Receptor clustering by multivalent ligands can activate signaling pathways. In principle, multivalent ligand features can control clustering and the downstream signals that result, but the influence of ligand structure on these processes is incompletely understood. Using a series of synthetic polymers that vary systematically, we studied the influence of multivalent ligand binding epitope density on the clustering of a model receptor, concanavalin A (Con A). We analyze three aspects of receptor clustering: the stoichiometry of the complex, rate of cluster formation, and receptor proximity. Our experiments reveal that the density of binding sites on a multivalent ligand strongly influences each of these parameters. In general, high binding epitope density results in greater numbers of receptors bound per polymer, faster rates of clustering, and reduced inter-receptor distances. Ligands with low binding epitope density, however, are the most efficient on a binding epitope basis. Our results provide insight into the design of ligands for controlling receptor-receptor interactions and can be used to illuminate mechanisms by which natural multivalent displays function.

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Metadata

Authors
Cairo, C. W., Gestwicki, J. E., Kanai, M., & Kiessling, L. L.
Venue
Journal of the American Chemical Society
Published
2002-02-01
Volume
124
Issue
8
Pages
1615-1619
ISSN
  • 0002-7863 (ISSN-L)
  • 1520-5126
OpenAlex
W2046884231
Cited by
383
References
3
FWCI
13.44
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Control of Multivalent Interactions by Binding Epitope Density. https://app.cochat.ai/papers/10.1021/ja016727k
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Cairo, C. W., Gestwicki, J. E., Kanai, M., & Kiessling, L. L. (2002). Control of Multivalent Interactions by Binding Epitope Density. Journal of the American Chemical Society. https://doi.org/10.1021/ja016727k

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.