Bioinformatic prediction of potential T cell epitopes for SARS-Cov-2
| dc.creator | Kiyotani, Kazuma | |
| dc.creator | Toyoshima, Yujiro | |
| dc.creator | Nemoto, Kensaku | |
| dc.creator | Nakamura, Yusuke | |
| dc.date.accessioned | 2020-09-08T15:03:21Z | |
| dc.date.available | 2020-09-08T15:03:21Z | |
| dc.date.created | 2020-05-06 | |
| dc.description.abstractenglish | To control and prevent the current COVID-19 pandemic, the development of novel vaccines is an emergent issue. In addition, we need to develop tools that can measure/monitor T-cell and B-cell responses to know how our immune system is responding to this deleterious virus. However, little information is currently available about the immune target epitopes of novel coronavirus (SARS-CoV-2) to induce host immune responses. Through a comprehensive bioinformatic screening of potential epitopes derived from the SARS-CoV-2 sequences for HLAs commonly present in the Japanese population, we identified 2013 and 1399 possible peptide epitopes that are likely to have the high affinity (<0.5%- and 2%-rank, respectively) to HLA class I and II molecules, respectively, that may induce CD8+ and CD4+ T-cell responses. These epitopes distributed across the structural (spike, envelope, membrane, and nucleocapsid proteins) and the nonstructural proteins (proteins corresponding to six open reading frames); however, we found several regions where high-affinity epitopes were significantly enriched. By comparing the sequences of these predicted T cell epitopes to the other coronaviruses, we identified 781 HLA-class I and 418 HLA-class II epitopes that have high homologies to SARS-CoV. To further select commonly-available epitopes that would be applicable to larger populations, we calculated population coverages based on the allele frequencies of HLA molecules, and found 2 HLA-class I epitopes covering 83.8% of the Japanese population. The findings in the current study provide us valuable information to design widely-available vaccine epitopes against SARS-CoV-2 and also provide the useful information for monitoring T-cell responses. | spa |
| dc.format.extent | 7 páginas | spa |
| dc.format.mimetype | application/pdf | spa |
| dc.identifier.doi | https://doi.org/10.1038/s10038-020-0771-5 | spa |
| dc.identifier.issn | 1435-232X | spa |
| dc.identifier.other | https://www.nature.com/articles/s10038-020-0771-5 | spa |
| dc.identifier.uri | https://hdl.handle.net/20.500.12010/12903 | |
| dc.language.iso | eng | spa |
| dc.publisher | journal of human genetics | spa |
| dc.rights.accessrights | info:eu-repo/semantics/restrictedAccess | spa |
| dc.rights.local | Acceso restringido | spa |
| dc.source | reponame:Expeditio Repositorio Institucional UJTL | spa |
| dc.source | instname:Universidad de Bogotá Jorge Tadeo Lozano | spa |
| dc.subject | Bioinformatic | spa |
| dc.subject | potential T cell epitopes | spa |
| dc.subject.lemb | Síndrome respiratorio agudo grave | spa |
| dc.subject.lemb | COVID-19 | spa |
| dc.subject.lemb | SARS-CoV-2 | spa |
| dc.subject.lemb | Coronavirus | spa |
| dc.title | Bioinformatic prediction of potential T cell epitopes for SARS-Cov-2 | spa |
| dc.type.coar | http://purl.org/coar/resource_type/c_6501 | spa |
| dc.type.hasversion | info:eu-repo/semantics/acceptedVersion | spa |
| dc.type.local | Artículo | spa |
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