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• W2086305890 abstract "The ability of antibodies to bind an antigen with a high degree of affinity and specificity has led them to become the largest and fastest growing class of therapeutic proteins. Clearly identifying the epitope at which they bind their cognate antigen provides insight into their mechanism of action and helps differentiate antibodies that bind the same antigen. Here, we describe a method to precisely and efficiently map the epitopes of a panel of antibodies in parallel over the course of several weeks. This method relies on the combination of rational library design, quantitative yeast surface display and next-generation DNA sequencing and was demonstrated by mapping the epitopes of several antibodies that neutralize alpha toxin from Staphylococcus aureus. The accuracy of this method was confirmed by comparing the results to the co-crystal structure of one antibody and alpha toxin and was further refined by the inclusion of a lower-affinity variant of the antibody. In addition, this method produced quantitative insight into the epitope residues most critical for the antibody-antigen interaction and enabled the relative affinities of each antibody toward alpha toxin variants to be estimated. This affinity estimate serves as a predictor of neutralizing antibody potency and was used to anticipate the ability of each antibody to effectively bind and neutralize naturally occurring alpha toxin variants secreted by strains of S. aureus, including clinically relevant strains. Ultimately this type information can be used to help select the best clinical candidate among a set of antibodies against a given antigen." @default.
• W2086305890 created "2016-06-24" @default.
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• W2086305890 date "2015-03-01" @default.
• W2086305890 modified "2023-10-03" @default.
• W2086305890 title "Precise and Efficient Antibody Epitope Determination through Library Design, Yeast Display and Next-Generation Sequencing" @default.
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• W2086305890 doi "https://doi.org/10.1016/j.jmb.2014.09.020" @default.
• W2086305890 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/25284753" @default.
• W2086305890 hasPublicationYear "2015" @default.
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