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Conserved T-cell epitopes predicted by bioinformatics in SARS-COV-2 variants
Feiyu Lu; Shengnan Wang; Ying Wang; Yunpeng Yao; Yangeng Wang; Shujun Liu; Yangyang Wang; Yongli Yu; Liying Wang.
Afiliação
  • Feiyu Lu; Jilin University
  • Shengnan Wang; Jilin University
  • Ying Wang; Jilin University
  • Yunpeng Yao; Jilin University
  • Yangeng Wang; Jilin University
  • Shujun Liu; Jilin University
  • Yangyang Wang; College of Basic Medical Sciences, Norman Bethune Health Science Center, Jilin University
  • Yongli Yu; Jilin University
  • Liying Wang; Jilin University
Preprint em Inglês | bioRxiv | ID: ppbiorxiv-456182
ABSTRACT
BackgroundFinding conservative T cell epitopes in the proteome of numerous variants of SARS-COV-2 is required to develop T cell activating SARS-COV-2 capable of inducing T cell responses against SARS-COV-2 variants. MethodsA computational workflow was performed to find HLA restricted CD8+ and CD4+ T cell epitopes among conserved amino acid sequences across the proteome of 474727 SARS-CoV-2 strains. ResultsA batch of covserved regions in the amino acid sequences were found in the proteome of the SARS-COV-2 strains. 2852 and 847 peptides were predicted to have high binding affinity to distint HLA class I and class II molecules. Among them, 1456 and 484 peptides are antigenic. 392 and 111 of the antigenic peptides were found in the conseved amino acid sequences. Among the antigenic-conserved peptides, 6 CD8+ T cell epitopes and 7 CD4+ T cell epitopes were identifed. The T cell epitopes could be presented to T cells by high-affinity HLA molecules which are encoded by the HLA alleles with high population coverage. ConclusionsThe T cell epitopes are conservative, antigenic and HLA presentable, and could be constructed into SARS-COV-2 vaccines for inducing protective T cell immunity against SARS-COV-2 and their variants.
Licença
cc_by_nc_nd
Texto completo: Disponível Coleções: Preprints Base de dados: bioRxiv Tipo de estudo: Estudo prognóstico Idioma: Inglês Ano de publicação: 2021 Tipo de documento: Preprint
Texto completo: Disponível Coleções: Preprints Base de dados: bioRxiv Tipo de estudo: Estudo prognóstico Idioma: Inglês Ano de publicação: 2021 Tipo de documento: Preprint
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