Figure 1.

Overview of deep mutational learning of the RBD for prediction of ACE2 binding and antibody escape

The RBD or the SARS-CoV-2 spike protein is expressed on the surface of yeast, and mutagenesis libraries are designed on the RBM of the RBD (RBM-3, RBM-1, and RBM-2), which are the sites of interaction with ACE2 and neutralizing antibodies (e.g., therapeutic antibody drugs). RBD libraries are screened by FACS for binding to ACE2 and neutralizing antibodies, both binding and non-binding (escape) populations are isolated and subjected to deep sequencing. Machine learning models are trained to predict binding status to ACE2 or antibodies based on RBD sequence. Machine learning models are then used to predict ACE2 binding and antibody escape on current and prospective variants and lineages.