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A novel coronavirus (SARS-CoV-2) emerged from China in late 2019 and rapidly spread across the globe, infecting millions of people and generating societal disruption on a level not seen since the 1918 influenza pandemic. A safe and effective vaccine is desperately needed to prevent the continued spread of SARS-CoV-2; yet, rational vaccine design efforts are currently hampered by the lack of knowledge regarding viral epitopes targeted during an immune response, and the need for more in-depth knowledge on betacoronavirus immunology. To that end, we developed a computational workflow using a series of open-source algorithms and webtools to analyze the proteome of SARS-CoV-2 and identify putative T cell and B cell epitopes. Utilizing a set of stringent selection criteria to filter peptide epitopes, we identified 41 T cell epitopes (5 HLA class I, 36 HLA class II) and 6 B cell epitopes that could serve as promising targets for peptide-based vaccine development against this emerging global pathogen. To our knowledge, this is the first study to comprehensively analyze all 10 (structural, non-structural and accessory) proteins from SARS-CoV-2 using predictive algorithms to identify potential targets for vaccine development.
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10.1038/s41598-020-70864-8
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document_parses/pdf_json/89155644fce8810cf06637809368fe77286ba118.json; document_parses/pdf_json/6fea72b24867711d8850dc178a9f47882cc255bc.json
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document_parses/pmc_json/PMC7447814.xml.json
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Immunoinformatic identification of B cell and T cell epitopes in the SARS-CoV-2 proteome
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