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In vitro platform reveals binding energy landscapes across 518 SARS-CoV-2 variants, highlighting rapid prediction tools for emerging antibody evasion.
SARS-CoV-2 variants continue to threaten public health, necessitating the study of cumulative and epistatic effects of receptor-binding domain (RBD) mutations on antibody evasion. We present a high-throughput platform combining cell-free protein synthesis and microfluidics to quantify the affinity of a large number of RBD triplet mutants covering the evolutionary space between the wild type and Omicron against two therapeutic antibodies and one engineered binder. Using rapid in vitro gene assembly and cell-free synthesis, we expressed 518 RBD variants and obtained 31,740 quantitative affinity measurements to generate three comprehensive binding energy landscapes. This approach enables rapid and large-scale in vitro affinity profiling and machine-learning-based predictions, providing a valuable tool for studying emerging variants.
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Han et al. (2026) studied this question.
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