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Application of an integrated computational antibody engineering platform to design SARS-CoV-2 neutralizers
As the COVID-19 pandemic continues to spread, hundreds of new initiatives including studies on existing medicines are running to fight the disease. To deliver a potentially immediate and lasting treatment to current and emerging SARS-CoV-2 variants, new collaborations and ways of sharing are require...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8344454/ https://www.ncbi.nlm.nih.gov/pubmed/34396040 http://dx.doi.org/10.1093/abt/tbab011 |
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author | Riahi, Saleh Lee, Jae Hyeon Wei, Shuai Cost, Robert Masiero, Alessandro Prades, Catherine Olfati-Saber, Reza Wendt, Maria Park, Anna Qiu, Yu Zhou, Yanfeng |
author_facet | Riahi, Saleh Lee, Jae Hyeon Wei, Shuai Cost, Robert Masiero, Alessandro Prades, Catherine Olfati-Saber, Reza Wendt, Maria Park, Anna Qiu, Yu Zhou, Yanfeng |
author_sort | Riahi, Saleh |
collection | PubMed |
description | As the COVID-19 pandemic continues to spread, hundreds of new initiatives including studies on existing medicines are running to fight the disease. To deliver a potentially immediate and lasting treatment to current and emerging SARS-CoV-2 variants, new collaborations and ways of sharing are required to create as many paths forward as possible. Here, we leverage our expertise in computational antibody engineering to rationally design/engineer three previously reported SARS-CoV neutralizing antibodies and share our proposal towards anti-SARS-CoV-2 biologics therapeutics. SARS-CoV neutralizing antibodies, m396, 80R and CR-3022 were chosen as templates due to their diversified epitopes and confirmed neutralization potency against SARS-CoV (but not SARS-CoV-2 except for CR3022). Structures of variable fragment (Fv) in complex with receptor binding domain (RBD) from SARS-CoV or SARS-CoV-2 were subjected to our established in silico antibody engineering platform to improve their binding affinity to SARS-CoV-2 and developability profiles. The selected top mutations were ensembled into a focused library for each antibody for further screening. In addition, we convert the selected binders with different epitopes into the trispecific format, aiming to increase potency and to prevent mutational escape. Lastly, to avoid antibody-induced virus activation or enhancement, we suggest application of NNAS and DQ mutations to the Fc region to eliminate effector functions and extend half-life. |
format | Online Article Text |
id | pubmed-8344454 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-83444542021-08-10 Application of an integrated computational antibody engineering platform to design SARS-CoV-2 neutralizers Riahi, Saleh Lee, Jae Hyeon Wei, Shuai Cost, Robert Masiero, Alessandro Prades, Catherine Olfati-Saber, Reza Wendt, Maria Park, Anna Qiu, Yu Zhou, Yanfeng Antib Ther Research Article As the COVID-19 pandemic continues to spread, hundreds of new initiatives including studies on existing medicines are running to fight the disease. To deliver a potentially immediate and lasting treatment to current and emerging SARS-CoV-2 variants, new collaborations and ways of sharing are required to create as many paths forward as possible. Here, we leverage our expertise in computational antibody engineering to rationally design/engineer three previously reported SARS-CoV neutralizing antibodies and share our proposal towards anti-SARS-CoV-2 biologics therapeutics. SARS-CoV neutralizing antibodies, m396, 80R and CR-3022 were chosen as templates due to their diversified epitopes and confirmed neutralization potency against SARS-CoV (but not SARS-CoV-2 except for CR3022). Structures of variable fragment (Fv) in complex with receptor binding domain (RBD) from SARS-CoV or SARS-CoV-2 were subjected to our established in silico antibody engineering platform to improve their binding affinity to SARS-CoV-2 and developability profiles. The selected top mutations were ensembled into a focused library for each antibody for further screening. In addition, we convert the selected binders with different epitopes into the trispecific format, aiming to increase potency and to prevent mutational escape. Lastly, to avoid antibody-induced virus activation or enhancement, we suggest application of NNAS and DQ mutations to the Fc region to eliminate effector functions and extend half-life. Oxford University Press 2021-06-24 /pmc/articles/PMC8344454/ /pubmed/34396040 http://dx.doi.org/10.1093/abt/tbab011 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of Antibody Therapeutics. All rights reserved. For Permissions, please email: journals.permissions@oup.com. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Research Article Riahi, Saleh Lee, Jae Hyeon Wei, Shuai Cost, Robert Masiero, Alessandro Prades, Catherine Olfati-Saber, Reza Wendt, Maria Park, Anna Qiu, Yu Zhou, Yanfeng Application of an integrated computational antibody engineering platform to design SARS-CoV-2 neutralizers |
title | Application of an integrated computational antibody engineering platform to
design SARS-CoV-2 neutralizers |
title_full | Application of an integrated computational antibody engineering platform to
design SARS-CoV-2 neutralizers |
title_fullStr | Application of an integrated computational antibody engineering platform to
design SARS-CoV-2 neutralizers |
title_full_unstemmed | Application of an integrated computational antibody engineering platform to
design SARS-CoV-2 neutralizers |
title_short | Application of an integrated computational antibody engineering platform to
design SARS-CoV-2 neutralizers |
title_sort | application of an integrated computational antibody engineering platform to
design sars-cov-2 neutralizers |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8344454/ https://www.ncbi.nlm.nih.gov/pubmed/34396040 http://dx.doi.org/10.1093/abt/tbab011 |
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