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Insight into the first multi-epitope-based peptide subunit vaccine against avian influenza A virus (H5N6): An immunoinformatics approach.

ABSTRACT: The rampant spread of highly pathogenic avian influenza A (H5N6) virus has drawn additional concerns along with ongoing Covid-19 pandemic. Due to its migration-related diffusion, the situation is deteriorating. Without an existing effective therapy and vaccines, it will be baffling to take control measures. In this regard, we propose a revers vaccinology approach for prediction and design of a multi-epitope peptide based vaccine. The induction of humoral and cell-mediated immunity seems to be the paramount concern for a peptide vaccine candidate; thus, antigenic B and T cell epitopes were screened from the surface, membrane and envelope proteins of the avian influenza A (H5N6) virus, and passed through several immunological filters to determine the best possible one. Following that, the selected antigenic with immunogenic epitopes and adjuvant were linked to finalize the multi-epitope-based peptide vaccine by appropriate linkers. For the prediction of an effective binding, molecular docking was carried out between the vaccine and immunological receptors (TLR8). Strong binding affinity and good docking scores clarified the stringency of the vaccines. Furthermore, molecular dynamics simulation was performed within the highest binding affinity complex to observe the stability, and minimize the designed vaccine's high mobility region to order to increase its stability. Then, Codon optimization and other physicochemical properties were performed to reveal that the vaccine would be suitable for a higher expression at cloning level and satisfactory thermostability condition. In conclusion, predicting the overall in silico assessment, we anticipated that our designed vaccine would be a plausible prevention against avian influenza A (H5N6) virus.

SUBMITTER: Mia MM

PROVIDER: S-EPMC9394107 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature

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Insight into the first multi-epitope-based peptide subunit vaccine against avian influenza A virus (H5N6): An immunoinformatics approach.

Mia Md Mukthar MM Hasan Mahamudul M Ahmed Shakil S Rahman Mohammad Nahian MN

Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases 20220822

The rampant spread of highly pathogenic avian influenza A (H5N6) virus has drawn additional concerns along with ongoing Covid-19 pandemic. Due to its migration-related diffusion, the situation is deteriorating. Without an existing effective therapy and vaccines, it will be baffling to take control measures. In this regard, we propose a revers vaccinology approach for prediction and design of a multi-epitope peptide based vaccine. The induction of humoral and cell-mediated immunity seems to be th ...[more]

PMID: 36007760

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Project description:COVID-19 has recently become the most serious threat to public health, and its prevalence has been increasing at an alarming rate. The incubation period for the virus is ~1-14 days and all age groups may be susceptible to a fatality rate of about 5.9%. COVID-19 is caused by a novel single-stranded, positive (+) sense RNA beta coronavirus. The development of a vaccine for SARS-CoV-2 is an urgent need worldwide. Immunoinformatics approaches are both cost-effective and convenient, as in silico predictions can reduce the number of experiments needed. In this study, with the aid of immunoinformatics tools, we tried to design a multi-epitope vaccine that can be used for the prevention and treatment of COVID-19. The epitopes were computed by using B cells, cytotoxic T lymphocytes (CTL), and helper T lymphocytes (HTL) base on the proteins of SARS-CoV-2. A vaccine was devised by fusing together the B cell, HTL, and CTL epitopes with linkers. To enhance the immunogenicity, the β-defensin (45 mer) amino acid sequence, and pan-HLA DR binding epitopes (13aa) were adjoined to the N-terminal of the vaccine with the help of the EAAAK linker. To enable the intracellular delivery of the modeled vaccine, a TAT sequence (11aa) was appended to C-terminal. Linkers play vital roles in producing an extended conformation (flexibility), protein folding, and separation of functional domains, and therefore, make the protein structure more stable. The secondary and three-dimensional (3D) structure of the final vaccine was then predicted. Furthermore, the complex between the final vaccine and immune receptors (toll-like receptor-3 (TLR-3), major histocompatibility complex (MHC-I), and MHC-II) were evaluated by molecular docking. Lastly, to confirm the expression of the designed vaccine, the mRNA of the vaccine was enhanced with the aid of the Java Codon Adaptation Tool, and the secondary structure was generated from Mfold. Then we performed in silico cloning. The final vaccine requires experimental validation to determine its safety and efficacy in controlling SARS-CoV-2 infections.

Project description:IntroductionLeptospirosis, caused by Leptospira interrogans, is a neglected zoonotic disease that poses a significant global health risk to both humans and animals. The rise of antimicrobial resistance and the inefficacy of existing vaccines highlight the urgent need for new preventive strategies.MethodsAn immunoinformatics approach was employed to design a multi-epitope subunit vaccine (MESV) against leptospirosis. B-cell, cytotoxic T lymphocyte (CTL), and helper T lymphocyte (HTL) epitopes were selected from five key Leptospira proteins. These epitopes were fused with a heparin-binding hemagglutinin (HBHA) adjuvant and appropriate linkers to construct the broad-spectrum vaccine. The physicochemical properties of the vaccine were assessed, including antigenicity, immunogenicity, allergenicity, and conservation. The vaccine's 3D structure was modeled, optimized, and validated. Molecular docking, molecular dynamics simulations, and MM-GBSA analysis were performed to assess the vaccine's binding interactions with Toll-like receptors (TLR2 and TLR4). Immune simulations and in silico cloning were also conducted to evaluate the vaccine's immune response and expression potential.ResultsThe MESV demonstrated high antigenicity, immunogenicity, non-allergenicity, and conservation across different Leptospira strains. Population coverage analysis revealed that T-cell epitopes significantly interacted with HLA molecules, covering 95.7% of the global population. Molecular docking showed strong and stable binding with TLR2 and TLR4, with binding energies of -1,357.1 kJ/mol and -1,163.7 kJ/mol, respectively. Molecular dynamics simulations and MM-GBSA analysis confirmed the stability of these interactions and accurately calculated the intermolecular binding free energies. Immune simulations indicated robust B and T cell responses, and in silico cloning demonstrated that the vaccine could be successfully expressed in E. coli.DiscussionThese findings suggest that MESV is a promising candidate for leptospirosis prevention, providing robust immune responses and broad population coverage. However, further in vivo studies are necessary to validate its efficacy and safety.

Project description:Tuberculosis is a highly contagious disease caused by Mycobacterium tuberculosis (Mtb), which is one of the prominent reasons for the death of millions worldwide. The bacterium has a substantially higher mortality rate than other bacterial diseases, and the rapid rise of drug-resistant strains only makes the situation more concerning. Currently, the only licensed vaccine BCG (Bacillus Calmette-Guérin) is ineffective in preventing adult pulmonary tuberculosis prophylaxis and latent tuberculosis re-activation. Therefore, there is a pressing need to find novel and safe vaccines that provide robust immune defense and have various applications. Vaccines that combine epitopes from multiple candidate proteins have been shown to boost immunity against Mtb infection. This study applies an immunoinformatic strategy to generate an adequate multi-epitope immunization against Mtb employing five antigenic proteins. Potential B-cell, cytotoxic T lymphocyte, and helper T lymphocyte epitopes were speculated from the intended proteins and coupled with 50 s ribosomal L7/L12 adjuvant, and the vaccine was constructed. The vaccine's physicochemical profile demonstrates antigenic, soluble, and non-allergic. In the meantime, docking, molecular dynamics simulations, and essential dynamics analysis revealed that the multi-epitope vaccine structure interacted strongly with Toll-like receptors (TLR2 and TLR3). MM-PBSA analysis was performed to ascertain the system's intermolecular binding free energies accurately. The immune simulation was applied to the vaccine to forecast its immunogenic profile. Finally, in silico cloning was used to validate the vaccine's efficacy. The immunoinformatics analysis suggests the multi-epitope vaccine could induce specific immune responses, making it a potential candidate against Mtb. However, validation through the in-vivo study of the developed vaccine is essential to assess its efficacy and immunogenicity profile, which will assure active protection against Mtb.

Dataset Information

Insight into the first multi-epitope-based peptide subunit vaccine against avian influenza A virus (H5N6): An immunoinformatics approach.

Publications

Insight into the first multi-epitope-based peptide subunit vaccine against avian influenza A virus (H5N6): An immunoinformatics approach.

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