Abstract
Microarray assay formats gained popularity in the 1990s, first implemented in DNA-based arrays but later adopted for use with proteins, namely antibodies, peptides, low molecular weight (LMW) molecules, such as lipids, and even tissues. In nucleic acid-based affinity assays and arrays, but not in protein or peptide arrays, the specificity and affinity of complementary strand interactions can be deduced from or adjusted through modifications to the nucleotide sequence. Arrays of LMW molecules are characterized by largely uniform but low binding affinities. Multiplexed protein-based affinity assays, such as microarrays, might present an additional challenge due to heterogeneity of antigen properties and of their binding affinities. The use of peptides instead of proteins reduces physical heterogeneity of these reagents through either the widened peptide selection options or rational sequence engineering. However, rational engineering of binding affinities remains an unmet need, and peptide-binding affinities to the respective antipeptide antibodies could vary by orders of magnitude. Hence, multiplexing of such assays by using a microarray format and data analysis and interpretation requires some knowledge of their binding affinities. Low-throughput binding assays to characterize such peptide–antipeptide antibodies interactions are widely available, but scaling-up of traditional protein- and peptide-binding assays might present practical challenges. Here, we describe fast label-free practical approach especially suitable for estimating peptide-binding affinities. The method in question relies on commercially available biolayer interferometry-based equipment with a protocol which can be easily scaled-up, subject to user needs and equipment availability.
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Cleaver, S., Gardner, M., Barlow, A., Ferrari, E., Soloviev, M. (2023). Fast Protocols for Characterizing Antibody–Peptide Binding. In: Cretich, M., Gori, A. (eds) Peptide Microarrays. Methods in Molecular Biology, vol 2578. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2732-7_7
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DOI: https://doi.org/10.1007/978-1-0716-2732-7_7
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Publisher Name: Humana, New York, NY
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Online ISBN: 978-1-0716-2732-7
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