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Fragment-based computational design of antibodies targeting structured epitopes

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 sca...

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Autores principales: Aguilar Rangel, Mauricio, Bedwell, Alice, Costanzi, Elisa, Taylor, Ross J., Russo, Rosaria, Bernardes, Gonçalo J. L., Ricagno, Stefano, Frydman, Judith, Vendruscolo, Michele, Sormanni, Pietro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Association for the Advancement of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9651861/
https://www.ncbi.nlm.nih.gov/pubmed/36367941
http://dx.doi.org/10.1126/sciadv.abp9540
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author Aguilar Rangel, Mauricio
Bedwell, Alice
Costanzi, Elisa
Taylor, Ross J.
Russo, Rosaria
Bernardes, Gonçalo J. L.
Ricagno, Stefano
Frydman, Judith
Vendruscolo, Michele
Sormanni, Pietro
author_facet Aguilar Rangel, Mauricio
Bedwell, Alice
Costanzi, Elisa
Taylor, Ross J.
Russo, Rosaria
Bernardes, Gonçalo J. L.
Ricagno, Stefano
Frydman, Judith
Vendruscolo, Michele
Sormanni, Pietro
author_sort Aguilar Rangel, Mauricio
collection PubMed
description 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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spelling pubmed-96518612022-11-23 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 Sci Adv Physical and Materials Sciences 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. American Association for the Advancement of Science 2022-11-11 /pmc/articles/PMC9651861/ /pubmed/36367941 http://dx.doi.org/10.1126/sciadv.abp9540 Text en Copyright © 2022 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution License 4.0 (CC BY). https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution license (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Physical and Materials Sciences
Aguilar Rangel, Mauricio
Bedwell, Alice
Costanzi, Elisa
Taylor, Ross J.
Russo, Rosaria
Bernardes, Gonçalo J. L.
Ricagno, Stefano
Frydman, Judith
Vendruscolo, Michele
Sormanni, Pietro
Fragment-based computational design of antibodies targeting structured epitopes
title Fragment-based computational design of antibodies targeting structured epitopes
title_full Fragment-based computational design of antibodies targeting structured epitopes
title_fullStr Fragment-based computational design of antibodies targeting structured epitopes
title_full_unstemmed Fragment-based computational design of antibodies targeting structured epitopes
title_short Fragment-based computational design of antibodies targeting structured epitopes
title_sort fragment-based computational design of antibodies targeting structured epitopes
topic Physical and Materials Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9651861/
https://www.ncbi.nlm.nih.gov/pubmed/36367941
http://dx.doi.org/10.1126/sciadv.abp9540
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