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Candidate Multi-Epitope Vaccine against Corona B.1.617 Lineage: In Silico Approach.

ABSTRACT: Various mutations have accumulated since the first genome sequence of SARS-CoV2 in 2020. Mutants of the virus carrying the D614G and P681R mutations in the spike protein are increasingly becoming dominant all over the world. The two mutations increase the viral infectivity and severity of the disease. This report describes an in silico design of SARS-CoV-2 multi-epitope carrying the spike D614G and P681R mutations. The designed vaccine harbors the D614G mutation that increases viral infectivity, fitness, and the P681R mutation that enhances the cleavage of S to S1 and S2 subunits. The designed multi-epitope vaccine showed an antigenic property with a value of 0.67 and the immunogenicity of the predicted vaccine was calculated and yielded 3.4. The vaccine construct is predicted to be non-allergenic, thermostable and has hydrophilic nature. The combination of the selected CTL and HTL epitopes in the vaccine resulted in 96.85% population coverage globally. Stable interactions of the vaccine with Toll-Like Receptor 4 were tested by docking studies. The multi-epitope vaccine can be a good candidate against highly infecting SARS-CoV-2 variants.

SUBMITTER: Seadawy MG

PROVIDER: S-EPMC9694184 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature

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Candidate Multi-Epitope Vaccine against Corona B.1.617 Lineage: In Silico Approach.

Seadawy Mohamed G MG Zekri Abdel Rahman N ARN Saeed Aya A AA San Emmanuel James EJ Ageez Amr M AM

Life (Basel, Switzerland) 20221027 11

Various mutations have accumulated since the first genome sequence of SARS-CoV2 in 2020. Mutants of the virus carrying the D614G and P681R mutations in the spike protein are increasingly becoming dominant all over the world. The two mutations increase the viral infectivity and severity of the disease. This report describes an in silico design of SARS-CoV-2 multi-epitope carrying the spike D614G and P681R mutations. The designed vaccine harbors the D614G mutation that increases viral infectivity, ...[more]

PMID: 36362871

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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:BackgroundNewcastle disease, is one of the most important illnesses in the aviculture industry which shows a constant threat. In this case, the vaccine could be considered an important solution to prevent and control this disease. So, the development of a new and more effective vaccine against Newcastle disease is an urgent need. Immune informatics is an important field that provides insight into the experimental procedure and could facilitate the analysis of large amounts of immunological data generated by experimental research and help to design a new vaccine candidate.ObjectivesThis study is aimed at bioinformatics to investigate and select the most immunogenic and conserved epitopes derived from F and HN glycoproteins, which play a key role in pathogenesis and immunity. This strategy could cover a wide range of Newcastle disease viruses.Materials and methodFor expression in both E. coli (as an injectable recombinant vaccine candidate) and maize plant (as an edible vaccine candidate) host, two constructs were designed and analyzed separately. Furthermore, the role of LTB as an effective bio-adjuvant for general eliciting of the immune system and simultaneous expressions with those two antigens was evaluated. Hence, here a multimeric recombinant protein with the abbreviation LHN2F from the highly immunogenic part of HN, F and LTB proteins were designed. The synthetic construct was analyzed based on different bioinformatics tools.ResultsThe proper immunogenicity and stability of this multimeric fusion protein have been shown by immunoinformatic methods from various servers. To confirm the function of the designed protein, the final molecule was docked to chicken MHC class I using the Pyrex-python 0.8 program. the results of Immune Epitope analysis were confirmed by the docking results between protein and receptor.Conclusions‎The results of structural and immunological computational studies proposed that the protein deduced from this novel construct could act as a vaccine candidate for Newcastle disease virus‎ control and prophylactic.

Dataset Information

Candidate Multi-Epitope Vaccine against Corona B.1.617 Lineage: In Silico Approach.

Publications

Candidate Multi-Epitope Vaccine against Corona B.1.617 Lineage: In Silico Approach.

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