Design of immunogens for eliciting antibody responses that may protect against SARS-CoV-2 variants
Name
journal.pcbi.1010563.pdf
Description
Published version
Size
1.9 MB
Format
Adobe PDF
Checksum (MD5)
3f0d2ceac722ecce24b6b4d48510b47b
Author(s)
Wang, Eric
Chakraborty, Arup K
Date Issued
September 2022
Journal
PLOS Computational Biology
Publisher
Public Library of Science (PLoS)
Citation
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).
Version
Final published version
Abstract
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.
MIT Department
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
Terms of Use
Creative Commons Attribution 4.0 International license
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1371/journal.pcbi.1010563
