1. Multivalent Pattern Recognition through Control of Nano-Spacing in Low-Valency Super-Selective Materials
- Author
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Hale Bila, Kaltrina Paloja, Vincenzo Caroprese, Artem Kononenko, and Maartje M.C. Bastings
- Subjects
density ,binding ,receptor ,DNA ,General Chemistry ,organization ,Ligands ,Biochemistry ,recombination ,peptide ,Catalysis ,folding dna ,weak-interactions ,Colloid and Surface Chemistry ,Nanotechnology ,affinity - Abstract
Super-selective multivalent ligand-receptor interactions display a signature step-like onset in binding when meeting a characteristic density of target receptors. Materials engineered for super-selective binding generally display a high number of flexible ligands to enhance the systems' avidity. In many biological processes, however, ligands are present in moderate copy numbers and arranged in spatio-temporal patterns. In this low-valency regime, the rigidity of the ligand-presenting architecture plays a critical role in the selectivity of the multivalent complex through decrease of the entropic penalty of binding. Exploiting the precision in spatial design inherent to the DNA nanotechnology, we engineered a library of rigid architectures to explore how valency, affinity, and nano-spacing control the presence of super-selectivity in multivalent binding. A micromolar monovalent affinity was required for super-selective binding to be observed within low-valency systems, and the transition point for stable interactions was measured at hexavalent ligand presentation, setting the limits of the low valency regime. Super-selective binding was observed for all hexavalent architectures, and, more strikingly, the ligand pattern determined the selectivity onset. Hereby, we demonstrate for the first time that nano-control of geometric patterns can be used to discriminate between receptor densities in a super-selective manner. Materials that were indistinguishable in their molecular composition and ligand valency bound with various efficacies on surfaces with constant receptor densities. We define this new phenomenon in super-selective binding as multivalent pattern recognition.
- Published
- 2022
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