
doi: 10.1002/prot.26703
pmid: 38742930
AbstractThe Puumala orthohantavirus is present in the body of the bank vole (Myodes glareolus). Humans infected with this virus may develop hemorrhagic fever accompanying renal syndrome. In addition, the infection may further lead to the failure of an immune system completely. The present study aimed to propose a possible vaccine by employing bioinformatics techniques to identify B and T‐cell antigens. The best multi‐epitope of potential immunogenicity was generated by combining epitopes. Additionally, the linkers EAAAK, AAY, and GPGPG were utilized in order to link the epitopes successfully. Further, C‐ImmSim was used to perform in silico immunological simulations upon the vaccine. For the purpose of conducting expression tests in Escherichia coli, the chimeric protein construct was cloned using Snapgene into the pET‐9c vector. The designed vaccine showed adequate results, evidenced by the global population coverage and favorable immune response. The developed vaccine was found to be highly effective and to have excellent population coverage in a number of computer‐based assessments. This work is fully dependent on the development of nucleoprotein‐based vaccines, which would constitute a significant step forward if our findings were used in developing a global vaccination to combat the Puumala virus.
Arvicolinae, Epitopes, T-Lymphocyte, Computational Biology, Viral Vaccines, Puumala virus, Nucleoproteins, Hemorrhagic Fever with Renal Syndrome, Escherichia coli, Animals, Humans, Epitopes, B-Lymphocyte, Computer Simulation
Arvicolinae, Epitopes, T-Lymphocyte, Computational Biology, Viral Vaccines, Puumala virus, Nucleoproteins, Hemorrhagic Fever with Renal Syndrome, Escherichia coli, Animals, Humans, Epitopes, B-Lymphocyte, Computer Simulation
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 5 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
