Generating Immune-aware SARS-CoV-2 Spike Proteins for Universal Vaccine Design

Dominic Phillips, Hans-Christof Gasser, Sebestyén Kamp, Aleksander Pałkowski, Lukasz Rabalski, Diego A. Oyarzún, Ajitha Rajan, Javier Antonio Alfaro

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

Dozens of SARS-CoV-2 vaccines have been approved for public use, yet there remains a risk that the virus evolves to escape vaccine protection. This motivates the development of universal vaccines capable of protecting against current and potentially new strains of the virus. A key challenge is the lack of computational tools to design new viral proteins capable of vaccine escape, which could serve as good targets for the development of universal vaccines. Here, we designed VAE capable of generating SARS-CoV-2 spike proteins with variable immune visibility to the cell-mediated immune response. We compared our model with two simpler generative models; a random-mutator and an 11-gram language model. All three models can generate stable, structurally valid sequences, yet only the VAE model can generate low immunogenicity sequences that interpolate smoothly along the principal variance directions of known natural sequences. This model provides an effective computational tool for the generation of spike protein sequences useful for universal vaccine design. We provide its source code at
Original languageEnglish
Title of host publicationProceedings of the 1st Workshop on Healthcare AI and COVID-19, ICML 2022
EditorsPeng Xu, Tingting Zhu, Pengkai Zhu, David A. Clifton, Danielle Belgrave, Yuanting Zhang
Number of pages17
Publication statusPublished - 22 Jul 2022
Event The 1st Workshop on Healthcare AI and COVID-19 - Baltimore, United States
Duration: 22 Jul 202222 Jul 2022

Publication series

NameProceedings of Machine Learning Research
ISSN (Electronic)2640-3498


Workshop The 1st Workshop on Healthcare AI and COVID-19
Country/TerritoryUnited States


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