Design of a Multi-Valent SARS-CoV-2 Peptide Vaccine for Broad Immune Protection via Deep Learning

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants capable of evading both convalescent and vaccine-triggered antibody responses has underscored the pivotal role of T-cell immunity in antiviral defense. Here, we develop the ConFormer network for epitope prediction, which couples convolutional neural network (CNN) local features with Transformer global representations to enhance binding prediction performance, and employ a deep learning algorithm and bioinformatics workflows to identify conserved T-cell epitopes within the SARS-CoV-2 proteome. Five epitopes are identified as potential inducers of T-cell immune responses. Notably, the multi-valent vaccine composed of these five peptides significantly activates cluster of differentiation (CD)8⁺ and CD4⁺ T cells both in vitro and in vivo. The serum of mice immunized with this vaccine is able to neutralize the five major SARS-CoV-2 variants of concern. This study provides a candidate peptide vaccine with the potential to trigger antiviral T-cell responses, thereby offering the prospect of immune protection against SARS-CoV-2 variants.