ArticleAccounts of chemical research2023
Determinants of Superselectivity─Practical Concepts for Application in Biology and Medicine.
Article in Accounts of chemical research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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16 citing papers in PubMed, 33 citations in OpenAlex.
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- Important design rules discovered for supramolecular multivalent ligands interacting with dynamic receptors.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Real-Time Monitoring of DNA Origami-Cell Interactions via Single Particle Tracking.Small (Weinheim an der Bergstrasse, Germany) · 2025Article
- Molecularly Defined Glycocalyx Models Reveal ABJACS Au · 2025Article
- The Electric Field in Solid State Nanopores Causes Dissociation of Strong Biomolecular Interactions.Nano letters · 2025Article
- Structure and unusual binding mechanism of the hyaluronan receptor LYVE-1 mediating leucocyte entry to lymphatics.Nature communications · 2025Article
- Receptor clustering tunes and sharpens the selectivity of multivalent binding.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Optimizing Ligand Valency to Maximize Tendon Accumulation of Peptide-Targeted Nanoparticles.ACS applied materials & interfaces · 2024Article
- Sugar-Coated: Can Multivalent Glycoconjugates Improve upon Nature's Design?Journal of the American Chemical Society · 2024Review
- Synthesis and screening of a library of LewisNature communications · 2024Article
- Chemical modification of hyaluronan oligosaccharides differentially modulates hyaluronan-hyaladherin interactions.The Journal of biological chemistry · 2024Article
- Weak-cooperative binding of a long single-stranded DNA chain on a surface.Nucleic acids research · 2024Article
- Multivalent DNAzyme agents for cleaving folded RNA.Nucleic acids research · 2024Article
- Balancing the Nanoscale Organization in Multivalent Materials for Functional Inhibition of the Programmed Death-1 Immune Checkpoint.ACS nano · 2024Article
- Competitive Specific Anchorage of Molecules onto Surfaces: Quantitative Control of Grafting Densities and Contamination by Free Anchors.Langmuir : the ACS journal of surfaces and colloids · 2023Article
- The multivalency game ruling the biology of immunity.Biophysics reviews · 2023Review
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3 authors at 3 institutions in 3 countries.
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Abstract
Multivalent interactions are common in biological systems and are also widely deployed for targeting applications in biomedicine. A unique feature of multivalent binding is "superselectivity". Superselectivity refers to the sharp discrimination of surfaces (e.g., on cells or cell compartments) by their comparative surface densities of a given receptor. This feature is different from the conventional "type" selectivity, which discriminates surfaces by their distinct receptor types. In a broader definition, a probe is superselective if it converts a gradual change in any one interaction parameter into a sharp on/off dependency in probe binding.This Account describes our systematic experimental and theoretical efforts over the past decade to analyze the determinants of superselective binding. It aims to offer chemical biologists, biophysicists, biologists, and biomedical scientists a set of guidelines for the interpretation of multivalent binding data, and design rules for tuning superselective targeting. We first provide a basic introduction that identifies multiple low-affinity interactions and combinatorial entropy as the minimal set of conditions required for superselective recognition. We then introduce the main experimental and theoretical tools and analyze how salient features of the multivalent probes (i.e., their concentration, size, ligand valency, and scaffold type), of the surface receptors (i.e., their affinity for ligands, surface density, and mobility), and of competitors and cofactors (i.e., their concentration and affinity for the ligands and/or receptors) influence the sharpness and the position of the threshold for superselective recognition.Emerging from this work are a set of relatively simple yet quantitative data analysis guidelines and superselectivity design rules that apply to a broad range of probe types and interaction systems. The key finding is the scaling variable
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