An integrated bioinformatics and immunoinformatics approach to design a multi-epitope-based vaccine against Langya henipavirus
Abstract Background In July 2022, a newly emerged viral infection called Langya virus, a type of Henipavirus identified in febrile patients in China and closely linked to two other henipaviruses (Hendra and Nipah) was considered a potential threat and can lead to the endemic situation. At present, n...
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| Language: | English |
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SpringerOpen
2025-05-01
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| Series: | Future Journal of Pharmaceutical Sciences |
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| Online Access: | https://doi.org/10.1186/s43094-025-00815-5 |
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| author | Saurav Kumar Mishra Gyan Prakash Rai Neeraj Kumar Asheesh Shanker John J. Georrge |
| author_facet | Saurav Kumar Mishra Gyan Prakash Rai Neeraj Kumar Asheesh Shanker John J. Georrge |
| author_sort | Saurav Kumar Mishra |
| collection | DOAJ |
| description | Abstract Background In July 2022, a newly emerged viral infection called Langya virus, a type of Henipavirus identified in febrile patients in China and closely linked to two other henipaviruses (Hendra and Nipah) was considered a potential threat and can lead to the endemic situation. At present, no appropriate vaccine exists. Therefore, this investigation aims to design a multi-epitope vaccine against this infection via an integrated bioinformatics and immunoinformatics approach focusing on attachment glycoprotein and fusion protein. Results A total of 26 immunodominant epitopes were carefully chosen for vaccine formulation grounded on their antigenic, nonallergenic and nontoxic features and linked via precise linkers, along with HIV-TAT peptide, PADRE epitope and 6 × His-tag. The intended vaccine is forecast to be immunodominant, with broader population coverage encouraging physicochemical features and highly soluble. The 3D structure was anticipated and verified, and a docking study with toll-like receptors (TLR2, TLR3, TLR8 and TLR9) indicates significant binding with TLR3 and TLR9 based on the highest molecular interaction and high binding affinity score of − 25.2 and − 24.2 kcal mol−1. NMA analysis revealed that vaccines with TLR3 and TLR9 have eigenvalues of 1.953251e−05 and 4.814201e−05, indicating proper molecular motion and flexibility. Further, the simulation (100 ns) showed constancy of complex (vaccine with TLR3 and TLR9). The generated immune activity indicates that the vaccines can trigger an intense immunological response. Furthermore, in silico cloning ensured a significant expression, followed by CAI values of 1 and GC (53.78%) content. Conclusion This study successfully designed a promising vaccine with strong immune activity. The vaccine revealed strong activity towards TLR3 and TLR9, with binding affinity of − 25.2 and − 24.2 kcal mol−1, and over 100-ns simulation demonstrated minor deviation followed by the range of RMSD value. Further, the immune stimulation and cloning demonstrated potent activity and suggested the vaccine is able to evoke immune activity. However, experimental and clinical analyses are essential to authenticate these findings. |
| format | Article |
| id | doaj-art-9003a71b1edb446a9a44b1e936ecb0ee |
| institution | OA Journals |
| issn | 2314-7253 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Future Journal of Pharmaceutical Sciences |
| spelling | doaj-art-9003a71b1edb446a9a44b1e936ecb0ee2025-08-20T02:39:03ZengSpringerOpenFuture Journal of Pharmaceutical Sciences2314-72532025-05-0111112410.1186/s43094-025-00815-5An integrated bioinformatics and immunoinformatics approach to design a multi-epitope-based vaccine against Langya henipavirusSaurav Kumar Mishra0Gyan Prakash Rai1Neeraj Kumar2Asheesh Shanker3John J. Georrge4Department of Bioinformatics, University of North BengalDepartment of Bioinformatics, Central University of South BiharDepartment of Pharmaceutical Chemistry, Bhupal Nobles’ College of Pharmacy, Bhupal Nobles’ UniversityDepartment of Bioinformatics, Central University of South BiharDepartment of Bioinformatics, University of North BengalAbstract Background In July 2022, a newly emerged viral infection called Langya virus, a type of Henipavirus identified in febrile patients in China and closely linked to two other henipaviruses (Hendra and Nipah) was considered a potential threat and can lead to the endemic situation. At present, no appropriate vaccine exists. Therefore, this investigation aims to design a multi-epitope vaccine against this infection via an integrated bioinformatics and immunoinformatics approach focusing on attachment glycoprotein and fusion protein. Results A total of 26 immunodominant epitopes were carefully chosen for vaccine formulation grounded on their antigenic, nonallergenic and nontoxic features and linked via precise linkers, along with HIV-TAT peptide, PADRE epitope and 6 × His-tag. The intended vaccine is forecast to be immunodominant, with broader population coverage encouraging physicochemical features and highly soluble. The 3D structure was anticipated and verified, and a docking study with toll-like receptors (TLR2, TLR3, TLR8 and TLR9) indicates significant binding with TLR3 and TLR9 based on the highest molecular interaction and high binding affinity score of − 25.2 and − 24.2 kcal mol−1. NMA analysis revealed that vaccines with TLR3 and TLR9 have eigenvalues of 1.953251e−05 and 4.814201e−05, indicating proper molecular motion and flexibility. Further, the simulation (100 ns) showed constancy of complex (vaccine with TLR3 and TLR9). The generated immune activity indicates that the vaccines can trigger an intense immunological response. Furthermore, in silico cloning ensured a significant expression, followed by CAI values of 1 and GC (53.78%) content. Conclusion This study successfully designed a promising vaccine with strong immune activity. The vaccine revealed strong activity towards TLR3 and TLR9, with binding affinity of − 25.2 and − 24.2 kcal mol−1, and over 100-ns simulation demonstrated minor deviation followed by the range of RMSD value. Further, the immune stimulation and cloning demonstrated potent activity and suggested the vaccine is able to evoke immune activity. However, experimental and clinical analyses are essential to authenticate these findings.https://doi.org/10.1186/s43094-025-00815-5BioinformaticsImmunoinformaticsLangya henipavirusMulti-epitope vaccineVaccine designing |
| spellingShingle | Saurav Kumar Mishra Gyan Prakash Rai Neeraj Kumar Asheesh Shanker John J. Georrge An integrated bioinformatics and immunoinformatics approach to design a multi-epitope-based vaccine against Langya henipavirus Future Journal of Pharmaceutical Sciences Bioinformatics Immunoinformatics Langya henipavirus Multi-epitope vaccine Vaccine designing |
| title | An integrated bioinformatics and immunoinformatics approach to design a multi-epitope-based vaccine against Langya henipavirus |
| title_full | An integrated bioinformatics and immunoinformatics approach to design a multi-epitope-based vaccine against Langya henipavirus |
| title_fullStr | An integrated bioinformatics and immunoinformatics approach to design a multi-epitope-based vaccine against Langya henipavirus |
| title_full_unstemmed | An integrated bioinformatics and immunoinformatics approach to design a multi-epitope-based vaccine against Langya henipavirus |
| title_short | An integrated bioinformatics and immunoinformatics approach to design a multi-epitope-based vaccine against Langya henipavirus |
| title_sort | integrated bioinformatics and immunoinformatics approach to design a multi epitope based vaccine against langya henipavirus |
| topic | Bioinformatics Immunoinformatics Langya henipavirus Multi-epitope vaccine Vaccine designing |
| url | https://doi.org/10.1186/s43094-025-00815-5 |
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