Design of immunogens for eliciting antibody responses that may protect against SARS-CoV-2 variants
<jats:p>The rise of SARS-CoV-2 variants and the history of outbreaks caused by zoonotic coronaviruses point to the need for next-generation vaccines that confer protection against variant strains. Here, we combined analyses of diverse sequences and structures of coronavirus spikes with data fr...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2022
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| Online Access: | https://hdl.handle.net/1721.1/145848 |
| _version_ | 1811097816309694464 |
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| author | Wang, Eric Chakraborty, Arup K |
| author2 | Massachusetts Institute of Technology. Institute for Medical Engineering & Science |
| author_facet | Massachusetts Institute of Technology. Institute for Medical Engineering & Science Wang, Eric Chakraborty, Arup K |
| author_sort | Wang, Eric |
| collection | MIT |
| description | <jats:p>The rise of SARS-CoV-2 variants and the history of outbreaks caused by zoonotic coronaviruses point to the need for next-generation vaccines that confer protection against variant strains. Here, we combined analyses of diverse sequences and structures of coronavirus spikes with data from deep mutational scanning to design SARS-CoV-2 variant antigens containing the most significant mutations that may emerge. We trained a neural network to predict RBD expression and ACE2 binding from sequence, which allowed us to determine that these antigens are stable and bind to ACE2. Thus, they represent viable variants. We then used a computational model of affinity maturation (AM) to study the antibody response to immunization with different combinations of the designed antigens. The results suggest that immunization with a cocktail of the antigens is likely to promote evolution of higher titers of antibodies that target SARS-CoV-2 variants than immunization or infection with the wildtype virus alone. Finally, our analysis of 12 coronaviruses from different genera identified the S2’ cleavage site and fusion peptide as potential pan-coronavirus vaccine targets.</jats:p> |
| first_indexed | 2024-09-23T17:05:24Z |
| format | Article |
| id | mit-1721.1/145848 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T17:05:24Z |
| publishDate | 2022 |
| publisher | Public Library of Science (PLoS) |
| record_format | dspace |
| spelling | mit-1721.1/1458482024-03-19T17:36:21Z Design of immunogens for eliciting antibody responses that may protect against SARS-CoV-2 variants Wang, Eric Chakraborty, Arup K Massachusetts Institute of Technology. Institute for Medical Engineering & Science Massachusetts Institute of Technology. Department of Chemical Engineering Massachusetts Institute of Technology. Department of Physics Massachusetts Institute of Technology. Department of Chemistry <jats:p>The rise of SARS-CoV-2 variants and the history of outbreaks caused by zoonotic coronaviruses point to the need for next-generation vaccines that confer protection against variant strains. Here, we combined analyses of diverse sequences and structures of coronavirus spikes with data from deep mutational scanning to design SARS-CoV-2 variant antigens containing the most significant mutations that may emerge. We trained a neural network to predict RBD expression and ACE2 binding from sequence, which allowed us to determine that these antigens are stable and bind to ACE2. Thus, they represent viable variants. We then used a computational model of affinity maturation (AM) to study the antibody response to immunization with different combinations of the designed antigens. The results suggest that immunization with a cocktail of the antigens is likely to promote evolution of higher titers of antibodies that target SARS-CoV-2 variants than immunization or infection with the wildtype virus alone. Finally, our analysis of 12 coronaviruses from different genera identified the S2’ cleavage site and fusion peptide as potential pan-coronavirus vaccine targets.</jats:p> 2022-10-17T12:00:19Z 2022-10-17T12:00:19Z 2022-09 2022-10-17T11:56:32Z Article http://purl.org/eprint/type/JournalArticle https://hdl.handle.net/1721.1/145848 Wang, Eric and Chakraborty, Arup K. 2022. "Design of immunogens for eliciting antibody responses that may protect against SARS-CoV-2 variants." PLOS Computational Biology, 18 (9). en 10.1371/journal.pcbi.1010563 PLOS Computational Biology Creative Commons Attribution 4.0 International license https://creativecommons.org/licenses/by/4.0/ application/pdf Public Library of Science (PLoS) PLoS |
| spellingShingle | Wang, Eric Chakraborty, Arup K Design of immunogens for eliciting antibody responses that may protect against SARS-CoV-2 variants |
| title | Design of immunogens for eliciting antibody responses that may protect against SARS-CoV-2 variants |
| title_full | Design of immunogens for eliciting antibody responses that may protect against SARS-CoV-2 variants |
| title_fullStr | Design of immunogens for eliciting antibody responses that may protect against SARS-CoV-2 variants |
| title_full_unstemmed | Design of immunogens for eliciting antibody responses that may protect against SARS-CoV-2 variants |
| title_short | Design of immunogens for eliciting antibody responses that may protect against SARS-CoV-2 variants |
| title_sort | design of immunogens for eliciting antibody responses that may protect against sars cov 2 variants |
| url | https://hdl.handle.net/1721.1/145848 |
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