Fragment-based computational design of antibodies targeting structured epitopes

ABSTRACT

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 characterisation showed that all designs are highly stable, and bind their intended targets with affinities in the nanomolar range without any in vitro affinity maturation. We further discuss how a high-resolution input antigen structure is not required, as our method yields similar predictions 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 pre-selected epitopes. summaryA combinatorial method can rapidly design nanobodies for predetermined epitopes, which bind with KDs in the nanomolar range.