Massively multiplexed affinity characterization of therapeutic antibodies against SARS-CoV-2 variants

• Published in: Antibody therapeutics 2022-04, Vol.5 (2), p.130-137
• Main Authors: Engelhart, Emily, Lopez, Randolph, Emerson, Ryan, Lin, Charles, Shikany, Colleen, Guion, Daniel, Kelley, Mary, Younger, David
• Format: Article
• Language: English
• Subjects: Brief Report
• ISSN: 2516-4236; 2516-4236
• DOI: 10.1093/abt/tbac011

Abstract Antibody therapies represent a valuable tool to reduce COVID-19 deaths and hospitalizations. Multiple antibody candidates have been granted emergency use authorization by the Food and Drug Administration and many more are in clinical trials. Most antibody therapies for COVID-19 are engineered to bind to the receptor-binding domain (RBD) of the SARS-CoV-2 Spike protein and disrupt its interaction with angiotensin-converting enzyme 2 (ACE2). Notably, several SARS-CoV-2 strains have accrued mutations throughout the RBD that improve ACE2 binding affinity, enhance viral transmission and escape some existing antibody therapies. Here, we measure the binding affinity of 33 therapeutic antibodies against a large panel of SARS-CoV-2 variants and related strains of clinical significance using AlphaSeq, a high-throughput yeast mating-based assay to determine epitopic residues, determine which mutations result in loss of binding and predict how future RBD variants may impact antibody efficacy. One-Sentence Summary: By measuring protein binding in vitro, we identify which clinical antibodies retain binding to various mutant SARS-CoV-2 strains. Statement of Significance: This work represents the first published demonstration of AlphaSeq, a synthetic yeast mating assay, as a tool for highly multiplexed characterization of clinical antibody candidates. We focused on the epitope and cross-reactivity characterization of 33 clinically relevant CoV-2 antibody therapeutics and found very good concordance with literature results, when available.