In silico Design of a Crimean-Congo Hemorrhagic Fever Virus Glycoprotein Multi-Epitope Antigen for Vaccine Development
No licensed vaccine is available to prevent the severe tick-borne disease Crimean-Congo hemorrhagic fever (CCHF), caused by the CCHF virus (CCHFV). This study sought to show that a combination of computational methods and data from published literature can inform the design of a multi-epitope antige...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Compuscript Ltd
2022-10-01
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| Series: | Zoonoses |
| Online Access: | https://www.scienceopen.com/hosted-document?doi=10.15212/ZOONOSES-2022-0029 |
| _version_ | 1827591973156945920 |
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| author | Megan C. Mears Dennis A. Bente |
| author_facet | Megan C. Mears Dennis A. Bente |
| author_sort | Megan C. Mears |
| collection | DOAJ |
| description | No licensed vaccine is available to prevent the severe tick-borne disease Crimean-Congo hemorrhagic fever (CCHF), caused by the CCHF virus (CCHFV). This study sought to show that a combination of computational methods and data from published literature can inform the design of a multi-epitope antigen for CCHFV with immunogenic potential. Cytotoxic and helper T-cell epitopes on the CCHFV glycoprotein precursor (GPC) were evaluated with bioinformatic servers. These data were combined with work from previous studies to identify potentially immunodominant regions of the GPC. Regions of the GPC were selected for generation of a model multi-epitope antigen in silico , and the percentage residue identity and similarity of each region were compared across sequences representing the widespread geographical and ecological distribution of CCHFV. Eleven multi-epitope regions were joined with flexible linkers in silico to generate a model multi-epitope antigen, termed EPIC , which included 812 (75.7%) of all predicted epitopes. EPIC was predicted to be antigenic by two independent bioinformatic servers, thus suggesting that multi-epitope antigens should be explored further for CCHFV vaccine development. The results presented herein provide information on potential targets within the CCHFV GPC for guiding future vaccine development. |
| first_indexed | 2024-03-09T01:40:12Z |
| format | Article |
| id | doaj.art-83cda0551ef64379ba6eb5cd81d89a5d |
| institution | Directory Open Access Journal |
| issn | 2737-7466 2737-7474 |
| language | English |
| last_indexed | 2024-03-09T01:40:12Z |
| publishDate | 2022-10-01 |
| publisher | Compuscript Ltd |
| record_format | Article |
| series | Zoonoses |
| spelling | doaj.art-83cda0551ef64379ba6eb5cd81d89a5d2023-12-08T17:00:07ZengCompuscript LtdZoonoses2737-74662737-74742022-10-012196610.15212/ZOONOSES-2022-0029In silico Design of a Crimean-Congo Hemorrhagic Fever Virus Glycoprotein Multi-Epitope Antigen for Vaccine DevelopmentMegan C. MearsDennis A. BenteNo licensed vaccine is available to prevent the severe tick-borne disease Crimean-Congo hemorrhagic fever (CCHF), caused by the CCHF virus (CCHFV). This study sought to show that a combination of computational methods and data from published literature can inform the design of a multi-epitope antigen for CCHFV with immunogenic potential. Cytotoxic and helper T-cell epitopes on the CCHFV glycoprotein precursor (GPC) were evaluated with bioinformatic servers. These data were combined with work from previous studies to identify potentially immunodominant regions of the GPC. Regions of the GPC were selected for generation of a model multi-epitope antigen in silico , and the percentage residue identity and similarity of each region were compared across sequences representing the widespread geographical and ecological distribution of CCHFV. Eleven multi-epitope regions were joined with flexible linkers in silico to generate a model multi-epitope antigen, termed EPIC , which included 812 (75.7%) of all predicted epitopes. EPIC was predicted to be antigenic by two independent bioinformatic servers, thus suggesting that multi-epitope antigens should be explored further for CCHFV vaccine development. The results presented herein provide information on potential targets within the CCHFV GPC for guiding future vaccine development.https://www.scienceopen.com/hosted-document?doi=10.15212/ZOONOSES-2022-0029 |
| spellingShingle | Megan C. Mears Dennis A. Bente In silico Design of a Crimean-Congo Hemorrhagic Fever Virus Glycoprotein Multi-Epitope Antigen for Vaccine Development Zoonoses |
| title | In silico Design of a Crimean-Congo Hemorrhagic Fever Virus Glycoprotein Multi-Epitope Antigen for Vaccine Development |
| title_full | In silico Design of a Crimean-Congo Hemorrhagic Fever Virus Glycoprotein Multi-Epitope Antigen for Vaccine Development |
| title_fullStr | In silico Design of a Crimean-Congo Hemorrhagic Fever Virus Glycoprotein Multi-Epitope Antigen for Vaccine Development |
| title_full_unstemmed | In silico Design of a Crimean-Congo Hemorrhagic Fever Virus Glycoprotein Multi-Epitope Antigen for Vaccine Development |
| title_short | In silico Design of a Crimean-Congo Hemorrhagic Fever Virus Glycoprotein Multi-Epitope Antigen for Vaccine Development |
| title_sort | in silico design of a crimean congo hemorrhagic fever virus glycoprotein multi epitope antigen for vaccine development |
| url | https://www.scienceopen.com/hosted-document?doi=10.15212/ZOONOSES-2022-0029 |
| work_keys_str_mv | AT megancmears insilicodesignofacrimeancongohemorrhagicfevervirusglycoproteinmultiepitopeantigenforvaccinedevelopment AT dennisabente insilicodesignofacrimeancongohemorrhagicfevervirusglycoproteinmultiepitopeantigenforvaccinedevelopment |