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Fragment-based computational design of antibodies targeting structured epitopes.
Aguilar Rangel, Mauricio; Bedwell, Alice; Costanzi, Elisa; Taylor, Ross J; Russo, Rosaria; Bernardes, Gonçalo J L; Ricagno, Stefano; Frydman, Judith; Vendruscolo, Michele; Sormanni, Pietro.
  • Aguilar Rangel M; Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, UK.
  • Bedwell A; Department of Biology, Stanford University, Stanford, CA, USA.
  • Costanzi E; Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, UK.
  • Taylor RJ; Department of Bioscience, Università degli Studi di Milano, Milano 20133, Italy.
  • Russo R; Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, UK.
  • Bernardes GJL; Department of Pathophysiology and Transplantation, Università degli Studi di Milano, Milano 20122, Italy.
  • Ricagno S; Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, UK.
  • Frydman J; Department of Bioscience, Università degli Studi di Milano, Milano 20133, Italy.
  • Vendruscolo M; Institute of Molecular and Translational Cardiology, IRCCS Policlinico San Donato, Milan 20097, Italy.
  • Sormanni P; Department of Biology, Stanford University, Stanford, CA, USA.
Sci Adv ; 8(45): eabp9540, 2022 11 11.
Artigo em Inglês | MEDLINE | ID: covidwho-2119147
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 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.
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Texto completo: Disponível Coleções: Bases de dados internacionais Base de dados: MEDLINE Assunto principal: COVID-19 / Anticorpos Monoclonais Tipo de estudo: Estudo prognóstico Limite: Humanos Idioma: Inglês Revista: Sci Adv Ano de publicação: 2022 Tipo de documento: Artigo País de afiliação: Sciadv.abp9540

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Texto completo: Disponível Coleções: Bases de dados internacionais Base de dados: MEDLINE Assunto principal: COVID-19 / Anticorpos Monoclonais Tipo de estudo: Estudo prognóstico Limite: Humanos Idioma: Inglês Revista: Sci Adv Ano de publicação: 2022 Tipo de documento: Artigo País de afiliação: Sciadv.abp9540