Dataset Information

Multi Epitope-Based Vaccine Design for Protection Against Mycobacterium tuberculosis and SARS-CoV-2 Coinfection.

ABSTRACT:

Background

A prophylactic and immunotherapeutic vaccine for Mycobacterium tuberculosis (MTB) and SARS-CoV-2 coinfection needs to be developed for a proactive and effective therapeutic approach. Therefore, this study aims to use immunoinformatics to design a multi-epitope vaccine for protection against MTB and SARS-CoV-2 coinfection.

Methods

The bioinformatic techniques were used to screen and construct potential epitopes from outer membrane protein A Rv0899 of MTB and spike glycoprotein of SARS-CoV-2 for B and T cells. The antigenicity, allergenicity, and several physiochemical properties of the developed multi-epitope vaccination were then evaluated. Additionally, molecular docking and normal mode analysis (NMA) were utilized in evaluating the vaccine's immunogenicity and complex stability.

Results

Selected proteins and predicted epitopes suggest that the vaccine prediction can be helpful in the protection against both SARS-CoV-2 and MTB coinfection. Through docking molecular and NMA, the vaccine-TLR4 protein interaction was predicted to be efficient with a high level of IgG, T-helper cells, T-cytotoxic cells, andIFN-γ.

Conclusion

This epitope-based vaccine is a potentially attractive tool for SARS-CoV-2 and MTB coinfection vaccine development.

SUBMITTER: Pitaloka DAE

PROVIDER: S-EPMC9356608 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Publications

Multi Epitope-Based Vaccine Design for Protection Against <i>Mycobacterium tuberculosis</i> and SARS-CoV-2 Coinfection.

Pitaloka Dian Ayu Eka DAE Izzati Afifah A Amirah Siti Rafa SR Syakuran Luqman Abdan LA

Advances and applications in bioinformatics and chemistry : AABC 20220802

<h4>Background</h4>A prophylactic and immunotherapeutic vaccine for <i>Mycobacterium tuberculosis</i> (MTB) and SARS-CoV-2 coinfection needs to be developed for a proactive and effective therapeutic approach. Therefore, this study aims to use immunoinformatics to design a multi-epitope vaccine for protection against MTB and SARS-CoV-2 coinfection.<h4>Methods</h4>The bioinformatic techniques were used to screen and construct potential epitopes from outer membrane protein A Rv0899 of MTB and spike ...[more]

PMID: 35941993

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Project description: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.