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Designing a multi-epitope vaccine candidate to combat MERS-CoV by employing an immunoinformatics approach.

ABSTRACT: Currently, no approved vaccine is available against the Middle East respiratory syndrome coronavirus (MERS-CoV), which causes severe respiratory disease. The spike glycoprotein is typically considered a suitable target for MERS-CoV vaccine candidates. A computational strategy can be used to design an antigenic vaccine against a pathogen. Therefore, we used immunoinformatics and computational approaches to design a multi-epitope vaccine that targets the spike glycoprotein of MERS-CoV. After using numerous immunoinformatics tools and applying several immune filters, a poly-epitope vaccine was constructed comprising cytotoxic T-cell lymphocyte (CTL)-, helper T-cell lymphocyte (HTL)-, and interferon-gamma (IFN-γ)-inducing epitopes. In addition, various physicochemical, allergenic, and antigenic profiles were evaluated to confirm the immunogenicity and safety of the vaccine. Molecular interactions, binding affinities, and the thermodynamic stability of the vaccine were examined through molecular docking and dynamic simulation approaches, during which we identified a stable and strong interaction with Toll-like receptors (TLRs). In silico immune simulations were performed to assess the immune-response triggering capabilities of the vaccine. This computational analysis suggested that the proposed vaccine candidate would be structurally stable and capable of generating an effective immune response to combat viral infections; however, experimental evaluations remain necessary to verify the exact safety and immunogenicity profile of this vaccine.

SUBMITTER: Mahmud S

PROVIDER: S-EPMC8322212 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature

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Designing a multi-epitope vaccine candidate to combat MERS-CoV by employing an immunoinformatics approach.

Mahmud Shafi S Rafi Md Oliullah MO Paul Gobindo Kumar GK Promi Maria Meha MM Shimu Mst Sharmin Sultana MSS Biswas Suvro S Emran Talha Bin TB Dhama Kuldeep K Alyami Salem A SA Moni Mohammad Ali MA Saleh Md Abu MA

Scientific reports 20210729 1

Currently, no approved vaccine is available against the Middle East respiratory syndrome coronavirus (MERS-CoV), which causes severe respiratory disease. The spike glycoprotein is typically considered a suitable target for MERS-CoV vaccine candidates. A computational strategy can be used to design an antigenic vaccine against a pathogen. Therefore, we used immunoinformatics and computational approaches to design a multi-epitope vaccine that targets the spike glycoprotein of MERS-CoV. After using ...[more]

PMID: 34326355

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Project description:Human rhinovirus C (HRV-C) is a significant contributor to respiratory tract infections in children and is implicated in asthma exacerbations across all age groups. Despite its impact, there is currently no licensed vaccine available for HRV-C. Here, we present a novel approach to address this gap by employing immunoinformatics techniques for the design of a multi-epitope-based vaccine against HRV-C. The sequences of the chosen structural proteins VP1 and VP2, along with the non-structural protein 2C of HRV-C, were downloaded in FASTA format from the NCBI server for further analysis. Through an exhaustive analysis of HRV-C genomic sequences, we identified highly conserved immunogenic regions capable of eliciting a protective immune response. Leveraging advanced immunoinformatics tools, we predicted epitopes for B-cells, Cytotoxic T lymphocytes, and Helper T lymphocytes, ensuring broad coverage across different HRV-C strains. The vaccine candidate was constructed by integrating selected antigens with immunogenic epitopes and adjuvants, employing optimal linkers. Three vaccine constructs were developed, with V2 being the most promising, consisting of 480 amino acids residues. V2 exhibited strong antigenicity, non-allergenicity, and solubility, with a solubility score greater than 0.550, and demonstrated excellent structural stability, with 91.9% of residues in the most favorable regions of the Ramachandran plot. Molecular dynamics and simulation studies revealed a stable Vaccine-TLR8 complex, with a binding energy of -296.15 and consistent RMSD values. Furthermore, in silico cloning and sequence optimization ensured efficient expression in E. coli, with a Codon Adaptation Index of 0.99 and GC content of 54.58%. The minimum free energy of the RNA secondary structure was -494.90 kcal/mol. While our findings suggest the potential effectiveness of the designed vaccine candidate against HRV-C, further in vitro and in vivo investigations are warranted to validate its safety and efficacy.

Project description:Introduction: The current incidence of the novel coronavirus disease has shown only small reductions of cases and has become a major public health challenge. Development of effective vaccines against the virus is still being encouraged such as multi-epitope vaccines designed from the components of SARS-CoV-2 including its spike, nucleocapsid and ORF1a proteins. Since the addition of adjuvants including HABA protein and L7/L12 ribosomal are considered helpful to increase the effectiveness of the designed vaccine, we proposed to design multiepitope vaccines by two different adjuvants. Methods: We used the IEDB server to predict BCL and TCL epitopes that were characterized using online tools including VaxiJen, AllPred and IL-10 Prediction. The selected epitopes were further constructed into multiepitope vaccines. We also added two different adjuvants to the vaccine components in order to increase the effectiveness of the vaccines. The 3D-structured vaccines were built using trRosetta. They were further docked with different Toll-like-receptors (TLR 3, 4 and 8) and the entry receptor of SARS-CoV-2, ACE2 using ClusPro, PatchDock and refined by FireDock. All structures were visualized by USCF Chimera and PyMOL. Results: In this study, we succeeded in designing two different candidate vaccines by the addition of HABA protein and L7/L12 ribosomal as adjuvants. The two vaccines were almost equally good in terms of their physicochemical properties and characteristics. Likewise, their strong interactions with TLR3 4, 8 and ACE2 show the lowest energy level of both was estimated at more than -1,000. Interactions of vaccines with ACE2 and TLRs are essential for activation of immune responses and production of antibodies. Conclusion: The two designed and constructed multiepitope vaccine have good characteristics and may have the potential to activate humoral and cellular immune responses against SARS-CoV-2. Further research is worth considering to confirm the findings of this study.

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Designing a multi-epitope vaccine candidate to combat MERS-CoV by employing an immunoinformatics approach.

Publications

Designing a multi-epitope vaccine candidate to combat MERS-CoV by employing an immunoinformatics approach.

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