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• W2783901906 abstract "Multivalency achieves strong, yet reversible binding by the simultaneous formation of multiple weak bonds. It is a key interaction principle in biology and promising for the synthesis of high-affinity inhibitors of pathogens. We present a molecular model for the binding affinity of synthetic multivalent ligands onto multivalent receptors consisting of n receptor units arranged on a regular polygon. Ligands consist of a geometrically matching rigid polygonal core to which monovalent ligand units are attached via flexible linker polymers, closely mimicking existing experimental designs. The calculated binding affinities quantitatively agree with experimental studies for cholera toxin (n = 5) and anthrax receptor (n = 7) and allow to predict optimal core size and optimal linker length. Maximal binding affinity is achieved for a core that matches the receptor size and for linkers that have an equilibrium end-to-end distance that is slightly longer than the geometric separation between ligand core and receptor sites. Linkers that are longer than optimal are greatly preferable compared to shorter linkers. The angular steric restriction between ligand unit and linker polymer is shown to be a key parameter. We construct an enhancement diagram that quantifies the multivalent binding affinity compared to monovalent ligands. We conclude that multivalent ligands against influenza viral hemagglutinin (n = 3), cholera toxin (n = 5), and anthrax receptor (n = 7) can outperform monovalent ligands only for a monovalent ligand affinity that exceeds a core-size dependent threshold value. Thus, multivalent drug design needs to balance core size, linker length, as well as monovalent ligand unit affinity." @default.
• W2783901906 created "2018-01-26" @default.
• W2783901906 creator A5018774182 @default.
• W2783901906 creator A5035250426 @default.
• W2783901906 date "2018-02-23" @default.
• W2783901906 modified "2023-10-16" @default.
• W2783901906 title "Quantitative Prediction of Multivalent Ligand–Receptor Binding Affinities for Influenza, Cholera, and Anthrax Inhibition" @default.
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• W2783901906 doi "https://doi.org/10.1021/acsnano.7b08479" @default.
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• W2783901906 hasPublicationYear "2018" @default.
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