Bioinformatics Prediction of SARS-CoV-2 Epitopes as Vaccine Candidates for the Colombian Population
Coronavirus disease (COVID-19) pandemic caused by the coronavirus SARS-CoV-2 represents an enormous challenge to global public health, with thousands of infections and deaths in over 200 countries worldwide. The purpose of this study was to identify SARS-CoV-2 epitopes with potential to interact in...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-07-01
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| Series: | Vaccines |
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| Online Access: | https://www.mdpi.com/2076-393X/9/7/797 |
| _version_ | 1797525892371578880 |
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| author | Diana Montes-Grajales Jesus Olivero-Verbel |
| author_facet | Diana Montes-Grajales Jesus Olivero-Verbel |
| author_sort | Diana Montes-Grajales |
| collection | DOAJ |
| description | Coronavirus disease (COVID-19) pandemic caused by the coronavirus SARS-CoV-2 represents an enormous challenge to global public health, with thousands of infections and deaths in over 200 countries worldwide. The purpose of this study was to identify SARS-CoV-2 epitopes with potential to interact in silico with the alleles of the human leukocyte antigen class I (HLA I) and class II (HLA II) commonly found in the Colombian population to promote both CD4 and CD8 immune responses against this virus. The generation and evaluation of the peptides in terms of HLA I and HLA II binding, immune response, toxicity and allergenicity were performed by using computer-aided tools, such as NetMHCpan 4.1, NetMHCIIpan 4.0, VaxiJem, ToxinPred and AllerTop. Furthermore, the interaction between the predicted epitopes with HLA I and HLA II proteins frequently found in the Colombian population was studied through molecular docking simulations in AutoDock Vina and interaction analysis in LigPlot+. One of the promising peptides proposed in this study is the HLA I epitope YQPYRVVVL, which displayed an estimated coverage of over 82% and 96% for the Colombian and worldwide population, respectively. These findings could be useful for the design of new epitope-vaccines that include Colombia among their population target. |
| first_indexed | 2024-03-10T09:20:25Z |
| format | Article |
| id | doaj.art-0fe62bf2edb546d1b0a42a46cde09472 |
| institution | Directory Open Access Journal |
| issn | 2076-393X |
| language | English |
| last_indexed | 2024-03-10T09:20:25Z |
| publishDate | 2021-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Vaccines |
| spelling | doaj.art-0fe62bf2edb546d1b0a42a46cde094722023-11-22T05:13:13ZengMDPI AGVaccines2076-393X2021-07-019779710.3390/vaccines9070797Bioinformatics Prediction of SARS-CoV-2 Epitopes as Vaccine Candidates for the Colombian PopulationDiana Montes-Grajales0Jesus Olivero-Verbel1Environmental and Computational Chemistry Group, School of Pharmaceutical Sciences, Zaragocilla Campus, University of Cartagena, Cartagena 130015, ColombiaEnvironmental and Computational Chemistry Group, School of Pharmaceutical Sciences, Zaragocilla Campus, University of Cartagena, Cartagena 130015, ColombiaCoronavirus disease (COVID-19) pandemic caused by the coronavirus SARS-CoV-2 represents an enormous challenge to global public health, with thousands of infections and deaths in over 200 countries worldwide. The purpose of this study was to identify SARS-CoV-2 epitopes with potential to interact in silico with the alleles of the human leukocyte antigen class I (HLA I) and class II (HLA II) commonly found in the Colombian population to promote both CD4 and CD8 immune responses against this virus. The generation and evaluation of the peptides in terms of HLA I and HLA II binding, immune response, toxicity and allergenicity were performed by using computer-aided tools, such as NetMHCpan 4.1, NetMHCIIpan 4.0, VaxiJem, ToxinPred and AllerTop. Furthermore, the interaction between the predicted epitopes with HLA I and HLA II proteins frequently found in the Colombian population was studied through molecular docking simulations in AutoDock Vina and interaction analysis in LigPlot+. One of the promising peptides proposed in this study is the HLA I epitope YQPYRVVVL, which displayed an estimated coverage of over 82% and 96% for the Colombian and worldwide population, respectively. These findings could be useful for the design of new epitope-vaccines that include Colombia among their population target.https://www.mdpi.com/2076-393X/9/7/797severe acute respiratory syndromeimmuno-informaticsHLAvaccine designT-cell epitopepeptide |
| spellingShingle | Diana Montes-Grajales Jesus Olivero-Verbel Bioinformatics Prediction of SARS-CoV-2 Epitopes as Vaccine Candidates for the Colombian Population Vaccines severe acute respiratory syndrome immuno-informatics HLA vaccine design T-cell epitope peptide |
| title | Bioinformatics Prediction of SARS-CoV-2 Epitopes as Vaccine Candidates for the Colombian Population |
| title_full | Bioinformatics Prediction of SARS-CoV-2 Epitopes as Vaccine Candidates for the Colombian Population |
| title_fullStr | Bioinformatics Prediction of SARS-CoV-2 Epitopes as Vaccine Candidates for the Colombian Population |
| title_full_unstemmed | Bioinformatics Prediction of SARS-CoV-2 Epitopes as Vaccine Candidates for the Colombian Population |
| title_short | Bioinformatics Prediction of SARS-CoV-2 Epitopes as Vaccine Candidates for the Colombian Population |
| title_sort | bioinformatics prediction of sars cov 2 epitopes as vaccine candidates for the colombian population |
| topic | severe acute respiratory syndrome immuno-informatics HLA vaccine design T-cell epitope peptide |
| url | https://www.mdpi.com/2076-393X/9/7/797 |
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