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Design of a multi-epitope vaccine against SARS-CoV-2: immunoinformatic and computational methods.

ABSTRACT: A novel infectious agent, SARS-CoV-2, is responsible for causing the severe respiratory disease COVID-19 and death in humans. Spike glycoprotein plays a key role in viral particles entering host cells, mediating receptor recognition and membrane fusion, and are considered useful targets for antiviral vaccine candidates. Therefore, computational techniques can be used to design a safe, antigenic, immunogenic, and stable vaccine against this pathogen. Drawing upon the structure of the S glycoprotein, we are trying to develop a potent multi-epitope subunit vaccine against SARS-CoV-2. The vaccine was designed based on cytotoxic T-lymphocyte and helper T-lymphocyte epitopes with an N-terminal adjuvant via conducting immune filters and an extensive immunoinformatic investigation. The safety and immunogenicity of the designed vaccine were further evaluated via using various physicochemical, allergenic, and antigenic characteristics. Vaccine-target (toll-like receptors: TLR2 and TLR4) interactions, binding affinities, and dynamical stabilities were inspected through molecular docking and molecular dynamic (MD) simulation methods. Moreover, MD simulations for dimeric TLRs/vaccine in the membrane-aqueous environment were performed to understand the differential domain organization of TLRs/vaccine. Further, dynamical behaviors of vaccine/TLR systems were inspected via identifying the key residues (named HUB nodes) that control interaction stability and provide a clear molecular mechanism. The obtained results from molecular docking and MD simulation revealed a strong and stable interaction between vaccine and TLRs. The vaccine's ability to stimulate the immune response was assessed by using computational immune simulation. This predicted a significant level of cytotoxic T cell and helper T cell activation, as well as IgG, interleukin 2, and interferon-gamma production. This study shows that the designed vaccine is structurally and dynamically stable and can trigger an effective immune response against viral infections.

SUBMITTER: Rafi MO

PROVIDER: S-EPMC8981096 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature

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Design of a multi-epitope vaccine against SARS-CoV-2: immunoinformatic and computational methods.

Rafi Md Oliullah MO Al-Khafaji Khattab K Sarker Md Takim MT Taskin-Tok Tugba T Rana Abdus Samad AS Rahman Md Shahedur MS

RSC advances 20220101 7

A novel infectious agent, SARS-CoV-2, is responsible for causing the severe respiratory disease COVID-19 and death in humans. Spike glycoprotein plays a key role in viral particles entering host cells, mediating receptor recognition and membrane fusion, and are considered useful targets for antiviral vaccine candidates. Therefore, computational techniques can be used to design a safe, antigenic, immunogenic, and stable vaccine against this pathogen. Drawing upon the structure of the S glycoprote ...[more]

PMID: 35425433

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Project description:Helicobacter pylori is a gram-negative bacterium that persistently infects the human stomach, leading to peptic ulcers, gastritis, and an increased risk of gastric cancer. The extremophilic characteristics of this bacterium make it resistant to current drug treatments, and there are no licensed vaccines available against H. pylori. Computational approaches offer a viable alternative for designing antigenic, stable, and safe vaccines to control infections caused by this pathogen. In this study, we employed an immunoinformatic strategy to design a set of candidate multi-epitope subunit vaccines by combining the most potent B and T cell epitopes from three targeted antigenic proteins (BabA, CagA, and VacA). Out of the 12 hypothetical vaccines generated, two (HP_VaX_V1 and HP_VaX_V2) were found to be strongly immunogenic, non-allergenic, and structurally stable. The proposed vaccine candidates were evaluated based on population coverage, molecular docking, immune simulations, codon adaptation, secondary mRNA structure, and in silico cloning. The vaccine candidates exhibited antigenic scores of 1.19 and 1.01, with 93.5% and 90.4% of the most rama-favored regions, respectively. HP_VaX_V1 and HP_VaX_V2 exhibited the strongest binding affinity towards TLR-7 and TLR-8, as determined by molecular docking simulations (ΔG = -20.3 and -20.9, respectively). Afterward, multi-scale normal mode analysis simulation revealed the structural flexibility and stability of vaccine candidates. Additionally, immune simulations showed elevated levels of cell-mediated immunity, while repeated exposure simulations indicated rapid antigen clearance. Finally, in silico cloning was performed using the expression vector pET28a (+) with optimized restriction sites to develop a viable strategy for large-scale production of the chosen vaccine constructs. These analyses suggest that the proposed vaccines may elicit potent immune responses against H. pylori, but laboratory validation is needed to verify their safety and immunogenicity.

Dataset Information

Design of a multi-epitope vaccine against SARS-CoV-2: immunoinformatic and computational methods.

Publications

Design of a multi-epitope vaccine against SARS-CoV-2: immunoinformatic and computational methods.

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