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• W2989720376 abstract "The ability of antibodies to bind a wide variety of analytes with high specificity and high affinity makes them ideal candidates for therapeutic and diagnostic applications. However, the poor stability and high production cost of antibodies have prompted exploration of a variety of synthetic materials capable of specific molecular recognition. Unfortunately, it remains a fundamental challenge to create a chemically diverse population of protein-like, folded synthetic nanostructures with defined molecular conformations in water. Here we report the synthesis and screening of combinatorial libraries of sequence-defined peptoid polymers engineered to fold into ordered, supramolecular nanosheets displaying a high spatial density of diverse, conformationally constrained peptoid loops on their surface. These polyvalent, loop-functionalized nanosheets were screened using a homogeneous Förster resonance energy transfer (FRET) assay for binding to a variety of protein targets. Peptoid sequences were identified that bound to the heptameric protein, anthrax protective antigen, with high avidity and selectivity. These nanosheets were shown to be resistant to proteolytic degradation, and the binding was shown to be dependent on the loop display density. This work demonstrates that key aspects of antibody structure and function-the creation of multivalent, combinatorial chemical diversity within a well-defined folded structure-can be realized with completely synthetic materials. This approach enables the rapid discovery of biomimetic affinity reagents that combine the durability of synthetic materials with the specificity of biomolecular materials." @default.
• W2989720376 created "2019-12-05" @default.
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• W2989720376 date "2019-12-02" @default.
• W2989720376 modified "2023-09-27" @default.
• W2989720376 title "Discovery of Stable and Selective Antibody Mimetics from Combinatorial Libraries of Polyvalent, Loop-Functionalized Peptoid Nanosheets" @default.
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• W2989720376 doi "https://doi.org/10.1021/acsnano.9b07498" @default.
• W2989720376 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/31789500" @default.
• W2989720376 hasPublicationYear "2019" @default.
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