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In silico designing of multi-epitope vaccine construct against human coronavirus infections.

ABSTRACT: Single stranded RNA viruses were known to cause variety of diseases since many years and are gaining much importance due to pandemic after the identification of a novel corona virus (severe acute respiratory syndrome-coronavirus (SARS-CoV-2)). Seven coronaviruses (CoVs) are known to infect humans and they are OC43 CoV, NL63 CoV, HKU1 CoV, Middle East respiratory syndrome, SARS CoV, and SARS CoV-2. Virus replication weakens the immune system of host thereby altering T-cell count and much of interferon response. Although no vaccine or therapeutic treatment has been approved till now for CoV infection, trials of vaccine against SARS CoV-2 are in progress. One of the epitopes used for vaccine production is of the spike protein on the surface of virus. The work focuses on designing of multi-epitope vaccine construct for treatment of seven human CoV infections using the epitopes present on the spike protein of human CoVs. To address this, immuno-informatics techniques have been employed to design multi-epitope vaccine construct. B- and T-cell epitopes of the spike proteins have been predicted and designed into a multi-epitope vaccine construct. The tertiary structure of the vaccine construct along with the adjuvant has been modelled and the physiochemical properties have been predicted. The multi-epitope vaccine construct has antigenic and non-allergenic property. After validation, refinement and disulphide engineering of the vaccine construct, molecular docking with toll-like receptors (TLRs) have been performed. Molecular dynamics simulation in aqueous environment predicted that the vaccine-TLRs complexes were stable. The vaccine construct is predicted to be able to trigger primary immune response in silico. Communicated by Ramaswamy H. Sarma.

SUBMITTER: Devi A

PROVIDER: S-EPMC7484569 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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<i>In silico</i> designing of multi-epitope vaccine construct against human coronavirus infections.

Devi Arpita A Chaitanya Nyshadham S N NSN

Journal of biomolecular structure & dynamics 20200810 18

Single stranded RNA viruses were known to cause variety of diseases since many years and are gaining much importance due to pandemic after the identification of a novel corona virus (severe acute respiratory syndrome-coronavirus (SARS-CoV-2)). Seven coronaviruses (CoVs) are known to infect humans and they are OC43 CoV, NL63 CoV, HKU1 CoV, Middle East respiratory syndrome, SARS CoV, and SARS CoV-2. Virus replication weakens the immune system of host thereby altering T-cell count and much of inter ...[more]

PMID: 32772892

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Project description:Brucella suis mediates the transmission of brucellosis in humans and animals and a significant facultative zoonotic pathogen found in livestock. It has the capacity to survive and multiply in a phagocytic environment and to acquire resistance under hostile conditions thus becoming a threat globally. Antibiotic resistance is posing a substantial public health threat, hence there is an unmet and urgent clinical need for immune-based non-antibiotic methods to treat brucellosis. Hence, we aimed to explore the whole proteome of Brucella suis to predict antigenic proteins as a vaccine target and designed a novel chimeric vaccine (multi-epitope vaccine) through subtractive genomics-based reverse vaccinology approaches. The applied subsequent hierarchical shortlisting resulted in the identification of Multidrug efflux Resistance-nodulation-division (RND) transporter outer membrane subunit (gene BepC) that may act as a potential vaccine target. T-cell and B-cell epitopes have been predicted from target proteins using a number of immunoinformatic methods. Six MHC I, ten MHC II, and four B-cell epitopes were used to create a 324-amino-acid MEV construct, which was coupled with appropriate linkers and adjuvant. To boost the immunological response to the vaccine, the vaccine was combined with the TLR4 agonist HBHA protein. The MEV structure predicted was found to be highly antigenic, non-toxic, non-allergenic, flexible, stable, and soluble. To confirm the interactions with the receptors, a molecular docking simulation of the MEV was done using the human TLR4 (toll-like receptor 4) and HLAs. The stability and binding of the MEV-docked complexes with TLR4 were assessed using molecular dynamics (MD) simulation. Finally, MEV was reverse translated, its cDNA structure was evaluated, and then, in silico cloning into an E. coli expression host was conducted to promote maximum vaccine protein production with appropriate post-translational modifications. These comprehensive computer calculations backed up the efficacy of the suggested MEV in protecting against B. suis infections. However, more experimental validations are needed to adequately assess the vaccine candidate's potential. HIGHLIGHTS: • Subtractive genomic analysis and reverse vaccinology for the prioritization of novel vaccine target • Examination of chimeric vaccine in terms of allergenicity, antigenicity, MHC I, II binding efficacy, and structural-based studies • Molecular docking simulation method to rank based vaccine candidate and understand their binding modes.

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.

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In silico designing of multi-epitope vaccine construct against human coronavirus infections.

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<i>In silico</i> designing of multi-epitope vaccine construct against human coronavirus infections.

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