| Title: |
Computationally designed proteins mimic antibody immune evasion in viral evolution |
| Authors: |
Youssef, Noor; Gurev, Sarah; Ghantous, Fadi; Brock, Kelly P; Jaimes, Javier A; Thadani, Nicole N; Dauphin, Ann; Sherman, Amy C; Yurkovetskiy, Leonid; Soto, Daria; Estanboulieh, Ralph; Kotzen, Ben; Notin, Pascal; Kollasch, Aaron W; Cohen, Alexander A; Dross, Sandra E; Erasmus, Jesse; Fuller, Deborah H; Bjorkman, Pamela J; Lemieux, Jacob E; Luban, Jeremy; Seaman, Michael S; Marks, Debora S |
| Contributors: |
Program in Molecular Medicine |
| Source: |
Immunity ; United States |
| Publication Year: |
2025 |
| Collection: |
University of Massachusetts, Medical School: eScholarship@UMMS |
| Subject Terms: |
antibody escape; generative protein models; immune landscape; machine learning; protein design; vaccine evaluation; viral evolution |
| Description: |
Recurrent waves of viral infection necessitate vaccines and therapeutics that remain effective against emerging viruses. Our ability to evaluate interventions is currently limited to assessments against past or circulating variants, which likely differ in their immune escape potential compared with future variants. To address this, we developed EVE-Vax, a computational method for designing antigens that foreshadow immune escape observed in future viral variants. We designed 83 SARS-CoV-2 spike proteins that transduced ACE2-positive cells and displayed neutralization resistance comparable to variants that emerged up to 12 months later in the COVID-19 pandemic. Designed spikes foretold antibody escape from B.1-BA.4/5 bivalent booster sera seen in later variants. The designed constructs also highlighted the increased neutralization breadth elicited by nanoparticle-based, compared with mRNA-based, boosters in non-human primates. Our approach offers targeted panels of synthetic proteins that map the immune landscape for early vaccine and therapeutic evaluation against future viral strains. ; No embargo |
| Document Type: |
article in journal/newspaper |
| File Description: |
application/pdf |
| Language: |
English |
| Relation: |
Immunity; https://doi.org/10.1016/j.immuni.2025.04.015; https://hdl.handle.net/20.500.14038/54417 |
| DOI: |
10.1016/j.immuni.2025.04.015 |
| Availability: |
https://doi.org/10.1016/j.immuni.2025.04.015; https://hdl.handle.net/20.500.14038/54417 |
| Rights: |
© 2025 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). ; http://creativecommons.org/licenses/by/4.0/ |
| Accession Number: |
edsbas.5131D266 |
| Database: |
BASE |