Deep Mutational Learning Predicts ACE2 Binding and Antibody Escape to Combinatorial Mutations in the SARS-CoV-2 Receptor Binding Domain. Taft, Weber et al.
Description
Yeast displayed RBD-library NGS sequencing data from FACS sorted binding/escape populations to ACE2 and 13 different SARS-CoV-2 binding antibodies, used to train and evaluate predictive models in "Deep Mutational Learning Predicts ACE2 Binding and Antibody Escape to Combinatorial Mutations in the SARS-CoV-2 Receptor Binding Domain" (Taft J, Weber C, et al, 2022) Datasets are annotated by RBD sequence ('sequence_aa'), Binding Label (0 - escape, 1 - binding), distance from wild type RBD sequence ('Distance'), mAb tested ('Antibody'), and the RBM region and library each sequence is derived from ('Library') All sequences/data combined is available as "Taft_Weber_Cell2022_FullData.csv". Alternatively, datasets for individual mAbs, and individual libraries are available in the "Full_sets" folder, separated first by library and then by mAb.