Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Riahi, Saleh, Lee, Jae Hyeon, Wei, Shuai, Cost, Robert, Masiero, Alessandro, Prades, Catherine, Olfati-Saber, Reza, Wendt, Maria, Park, Anna, Qiu, Yu, Zhou, Yanfeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
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
_version_ 1783734475125948416
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
work_keys_str_mv AT riahisaleh applicationofanintegratedcomputationalantibodyengineeringplatformtodesignsarscov2neutralizers
AT leejaehyeon applicationofanintegratedcomputationalantibodyengineeringplatformtodesignsarscov2neutralizers
AT weishuai applicationofanintegratedcomputationalantibodyengineeringplatformtodesignsarscov2neutralizers
AT costrobert applicationofanintegratedcomputationalantibodyengineeringplatformtodesignsarscov2neutralizers
AT masieroalessandro applicationofanintegratedcomputationalantibodyengineeringplatformtodesignsarscov2neutralizers
AT pradescatherine applicationofanintegratedcomputationalantibodyengineeringplatformtodesignsarscov2neutralizers
AT olfatisaberreza applicationofanintegratedcomputationalantibodyengineeringplatformtodesignsarscov2neutralizers
AT wendtmaria applicationofanintegratedcomputationalantibodyengineeringplatformtodesignsarscov2neutralizers
AT parkanna applicationofanintegratedcomputationalantibodyengineeringplatformtodesignsarscov2neutralizers
AT qiuyu applicationofanintegratedcomputationalantibodyengineeringplatformtodesignsarscov2neutralizers
AT zhouyanfeng applicationofanintegratedcomputationalantibodyengineeringplatformtodesignsarscov2neutralizers