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Inference and design of antibody specificity: From experiments to models and back

Fig 3

Design and validation of antibodies with prescribed specificity.

A. Model-based energy plot where each sequence s is represented as a circle with coordinates (, with w₁ representing the binding mode associated with the Black hairpin and w₂ with the Blue hairpin. Sequences predicted to be specific to the Blue hairpin, specific to the Black hairpin, or cross-specific to the two hairpins are respectively highlighted in blue, black, and purple. We selected for experimental validation all the colored sequences that are not present in the training set. B. Experiment-based enrichment plot of the selected sequences where each sequence s is represented as a circle with coordinates (log ϵ_sBlack, log ϵ_sBlue), with ϵ_sBlack representing the enrichment against the Black complex and ϵ_sBlue against the Blue complex. Sequences with high enrichment in one experiment and low enrichment in the other are ligand-specific, those with high enrichment in both are cross-specific, and low-enrichment sequences are non-binders (false positives). We assess our computational approach’s effectiveness by calculating the percentage of designed sequences falling within the correct region. Cross-specific designed antibodies achieve a 45% true positive rate, while Black and Blue-specific binders yield lower percentages (19% and 8%, respectively), reflecting the capacity of our approach to design antibodies with desired properties despite the challenges arising from the close similarity of the two ligands (% in parenthesis indicate the total fraction of sequences in each quadrant; see also Fig I in S1 Text for the choice of the thresholds and Table C in S1 Text for p-values).

doi: https://doi.org/10.1371/journal.pcbi.1012522.g003