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Sci Rep ; 10(1): 20465, 2020 11 24.
Artigo em Inglês | MEDLINE | ID: mdl-33235258

RESUMO

The outbreak of SARS-CoV-2 (2019-nCoV) virus has highlighted the need for fast and efficacious vaccine development. Stimulation of a proper immune response that leads to protection is highly dependent on presentation of epitopes to circulating T-cells via the HLA complex. SARS-CoV-2 is a large RNA virus and testing of all of its overlapping peptides in vitro to deconvolute an immune response is not feasible. Therefore HLA-binding prediction tools are often used to narrow down the number of peptides to test. We tested NetMHC suite tools' predictions by using an in vitro peptide-MHC stability assay. We assessed 777 peptides that were predicted to be good binders across 11 MHC alleles in a complex-stability assay and tested a selection of 19 epitope-HLA-binding prediction tools against the assay. In this investigation of potential SARS-CoV-2 epitopes we found that current prediction tools vary in performance when assessing binding stability, and they are highly dependent on the MHC allele in question. Designing a COVID-19 vaccine where only a few epitope targets are included is therefore a very challenging task. Here, we present 174 SARS-CoV-2 epitopes with high prediction binding scores, validated to bind stably to 11 HLA alleles. Our findings may contribute to the design of an efficacious vaccine against COVID-19.


Assuntos
Vacinas contra COVID-19/imunologia , COVID-19/prevenção & controle , Biologia Computacional/métodos , Epitopos de Linfócito T/imunologia , Aprendizado de Máquina , SARS-CoV-2/imunologia , Alelos , Sequência de Bases , COVID-19/virologia , Antígenos HLA/genética , Antígenos de Histocompatibilidade Classe I/genética , Antígenos de Histocompatibilidade Classe II/genética , Humanos , Peptídeos/genética , Peptídeos/imunologia , Glicoproteína da Espícula de Coronavírus/genética
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