Highlights d Prediction of antibody-antigen binding is a central question in immunology d A motif vocabulary of paratope-epitope interactions governs antibody specificity d Proof of principle that antibody-antigen binding is predictable d Implications for de novo antibody and (neo-)epitope design

Antibody recognition of antigen relies on the specific interaction of amino acids at the paratopeepitope interface. A long-standing question in the fields of immunology and structural biology is whether paratope-epitope interaction is predictable. A fundamental premise for the predictability of paratope-epitope binding is the existence of structural units that are universally shared among antibody-antigen binding complexes. Here, we identified structural interaction motifs, which together compose a vocabulary of paratope-epitope binding that is shared among investigated antibody-antigen complexes. The vocabulary (i) is finite with less than 10 4 motifs, (ii) mediates specific and non-redundant interactions between paratope-epitope pairs, (iii) is immunity-specific (distinct from the motif vocabulary used by non-immune protein-protein interactions), and (iv) enables the machine learning prediction of paratope or epitope. The discovery of a vocabulary of paratope-epitope interaction demonstrates the learnability and predictability of paratope-epitope interaction.

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A successful HIV vaccine eliciting broadly neutralizing antibodies (bnAbs) must overcome the hurdle of being able to activate naive precursor B cells encoding features within their germline B cell receptors (BCR) that allow recognition of broadly neutralizing epitopes. Knowledge of whether bnAb precursor B cells are circulating at sufficient frequencies within individuals in communities heavily impacted by HIV may be important. Using a germline-targeting eOD-GT8 immunogen and high-throughput droplet-based single-cell BCR sequencing, we demonstrate that large numbers of paired BCR sequences from multiple donors can be efficiently screened to elucidate precursor frequencies of rare, naive VRC01-class B cells. Further, we analyzed IGHV1-2 allelic usage among three different cohorts; we find that IGHV1-2 alleles traditionally thought to be incompatible with VRC01-class responses are relatively common in various human populations and that germline variation within IGHV1-2 associates with gene usage frequencies in the naive BCR repertoire.