Fragment-based computational design of antibodies targeting structured epitopes.

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Aguilar Rangel, Mauricio  ORCID logo
Bedwell, Alice 
Costanzi, Elisa 
Taylor, Ross J 

De novo design methods hold the promise of reducing the time and cost of antibody discovery while enabling the facile and precise targeting of predetermined epitopes. Here, we describe a fragment-based method for the combinatorial design of antibody binding loops and their grafting onto antibody scaffolds. We designed and tested six single-domain antibodies targeting different epitopes on three antigens, including the receptor-binding domain of the SARS-CoV-2 spike protein. Biophysical characterization showed that all designs are stable and bind their intended targets with affinities in the nanomolar range without in vitro affinity maturation. We further discuss how a high-resolution input antigen structure is not required, as similar predictions are obtained when the input is a crystal structure or a computer-generated model. This computational procedure, which readily runs on a laptop, provides a starting point for the rapid generation of lead antibodies binding to preselected epitopes.

Humans, Epitopes, Antibody Affinity, Antibodies, Monoclonal, Models, Molecular, SARS-CoV-2, COVID-19, Antigens
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Sci Adv
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American Association for the Advancement of Science (AAAS)