Dataset Information

Computational Design and Analysis of a Multi-epitope Against Influenza A virus.

ABSTRACT: Influenza A viruses are among the most studied viruses, however no effective prevention against influenza infection has been developed. So, designing an effective vaccine against Influenza A virus is a critical issue in the field of medical biotechnology. For this reason, to combat this disease, we have designed a novel multi-epitope vaccine candidate based on the several conserved and potential linear B-cell and T-cell binding epitopes by using the in silico approach. This vaccine consists of an ER signal conserved sequence, the PADRE conserved epitope and two conserved epitopes of Influenza matrix protein 2. T-cell binding epitopes from Matrix protein 2 were predicted by in silico tools of epitope prediction. The selected epitopes were joined by flexible linkers and physicochemical properties, toxicity, and allergenecity were investigated. The designed vaccine was antigenic, immunogenic, and non-allergenic with suitable physicochemical properties and has higher solubility. The final multi-epitope construct was modeled, confirmed by different programs and the molecular interactions with immune receptors were considered. The molecular docking assay indicated the interactions with immune-stimulatory toll-like receptor 3 (TLR3) and major histocompatibility complex class I (MHCI). The HADDOCK and H DOCK servers were used to make docking analysis, respectively. The docking analysis indicated a strong and stable binding interaction between the vaccine construct with major histocompatibility complex (MHC) class I and toll-like receptor 3. Overall, the findings suggest that the current vaccine may be a promising vaccine to prevent Influenza infection.

SUBMITTER: Rostaminia S

PROVIDER: S-EPMC8435298 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundInfluenza A virus is one of the leading causes of annual mortality. The emerging of novel escape variants of the influenza A virus is still a considerable challenge in the annual process of vaccine production. The evolution of vaccines ranks among the most critical successes in medicine and has eradicated numerous infectious diseases. Recently, multi-epitope vaccines, which are based on the selection of epitopes, have been increasingly investigated.ResultsThis study utilized an immunoinformatic approach to design a recombinant multi-epitope vaccine based on a highly conserved epitope of hemagglutinin, neuraminidase, and membrane matrix proteins with fewer changes or mutate over time. The potential B cells, cytotoxic T lymphocytes (CTL), and CD4 T cell epitopes were identified. The recombinant multi-epitope vaccine was designed using specific linkers and a proper adjuvant. Moreover, some bioinformatics online servers and datasets were used to evaluate the immunogenicity and chemical properties of selected epitopes. In addition, Universal Immune System Simulator (UISS) in silico trial computational framework was run after influenza exposure and recombinant multi-epitope vaccine administration, showing a good immune response in terms of immunoglobulins of class G (IgG), T Helper 1 cells (TH1), epithelial cells (EP) and interferon gamma (IFN-g) levels. Furthermore, after a reverse translation (i.e., convertion of amino acid sequence to nucleotide one) and codon optimization phase, the optimized sequence was placed between the two EcoRV/MscI restriction sites in the PET32a+ vector.ConclusionsThe proposed "Recombinant multi-epitope vaccine" was predicted with unique and acceptable immunological properties. This recombinant multi-epitope vaccine can be successfully expressed in the prokaryotic system and accepted for immunogenicity studies against the influenza virus at the in silico level. The multi-epitope vaccine was then tested with the Universal Immune System Simulator (UISS) in silico trial platform. It revealed slight immune protection against the influenza virus, shedding the light that a multistep bioinformatics approach including molecular and cellular level is mandatory to avoid inappropriate vaccine efficacy predictions.

Project description:The family members of Arenaviridae include members of the genus Machupo virus, which have bi-segmented negative sense RNA inside the envelope and can be transferred to humans through rodent carriers. Machupo virus, a member of the mammarenavirus genus, causes Bolivian hemorrhage fever, its viral nucleocapsid protein being a significant virulence factor. Currently, no treatment is available for Bolivian hemorrhage fever and work to develop a protective as well as post-diagnosis treatment is underway. Adding to these efforts, this study employed a reverse-vaccinology approach to design a vaccine with B and T-cell epitopes of the viral nucleocapsid protein of the Machupo virus. Five B-cell specific, eight MHC-I restricted, and 14 MHC-II restricted epitopes were finalized for the construct based on an antigenicity score of >0.5 and non-allergenicity as a key characteristic. The poly-histidine tag was used to construct an immunogenic and stable vaccine construct and 50S ribosomal 46 protein L7/L12 adjuvant with linkers (EAAAK, GPGPG, and AYY). It covers 99.99% of the world's population, making it highly efficient. The physicochemical properties like the aliphatic index (118.31) and the GRAVY index (0.302) showed that the vaccine is easily soluble. The overall Ramachandran score of the construct was 90.7%, and the instability index was 35.13, endorsing a stable structure. The immune simulations demonstrated a long-lasting antibody response even after the excretion of the antigen from the body in the first 5 days of injection. The IgM + IgG titers were predicted to rise to 6000 10 days post-injection and were illustrated to be stable (around 3000) after a month, elucidating that the vaccine would be effective and provide enduring protection. Lastly, the molecular interaction between the construct and the IKBKE receptor was significant and a higher eigenfactor value in MD simulations confirmed the stable molecular interaction between the receptor and the vaccine, validating our construct.

Dataset Information

Computational Design and Analysis of a Multi-epitope Against Influenza A virus.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets