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Reverse vaccinology approach to design a novel multi-epitope vaccine candidate against COVID-19: an in silico study.

ABSTRACT: At present, novel Coronavirus (2019-nCoV, the causative agent of COVID-19) has caused worldwide social and economic disruption. The disturbing statistics of this infection promoted us to develop an effective vaccine candidate against the COVID-19. In this study, bioinformatics approaches were employed to design and introduce a novel multi-epitope vaccine against 2019-nCoV that can potentially trigger both CD4+ and CD8+ T-cell immune responses and investigated its biological activities by computational tools. Three known antigenic proteins (Nucleocapsid, ORF3a, and Membrane protein, hereafter called NOM) from the virus were selected and analyzed for prediction of the potential immunogenic B and T-cell epitopes and then validated using bioinformatics tools. Based on in silico analysis, we have constructed a multi-epitope vaccine candidate (NOM) with five rich-epitopes domain including highly scored T and B-cell epitopes. After predicting and evaluating of the third structure of the protein candidate, the best 3?D predicted model was applied for docking studies with Toll-like receptor 4 (TLR4) and HLA-A*11:01. In the next step, molecular dynamics (MD) simulation was used to evaluate the stability of the designed fusion protein with TLR4 and HLA-A*11:01 receptors. MD studies demonstrated that the NOM-TLR4 and NOM-HLA-A*11:01 docked models were stable during simulation time. In silico evaluation showed that the designed chimeric protein could simultaneously elicit humoral and cell-mediated immune responses. Communicated by Ramaswamy H. Sarma.

SUBMITTER: Enayatkhani M

PROVIDER: S-EPMC7196925 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Reverse vaccinology approach to design a novel multi-epitope vaccine candidate against COVID-19: an in silico study.

Enayatkhani Maryam M Hasaniazad Mehdi M Faezi Sobhan S Gouklani Hamed H Davoodian Parivash P Ahmadi Nahid N Einakian Mohammad Ali MA Karmostaji Afsaneh A Ahmadi Khadijeh K

Journal of biomolecular structure & dynamics 20200502 8

At present, novel Coronavirus (2019-nCoV, the causative agent of COVID-19) has caused worldwide social and economic disruption. The disturbing statistics of this infection promoted us to develop an effective vaccine candidate against the COVID-19. In this study, bioinformatics approaches were employed to design and introduce a novel multi-epitope vaccine against 2019-nCoV that can potentially trigger both CD4+ and CD8+ T-cell immune responses and investigated its bio ...[more]

PMID: 32295479

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Project description:Staphylococcus saprophyticus is a Gram-positive coccus responsible for the occurrence of cystitis in sexually active, young females. While effective antibiotics against this organism exist, resistant strains are on the rise. Therefore, prevention via vaccines appears to be a viable solution to address this problem. In comparison to traditional techniques of vaccine design, computationally aided vaccine development demonstrates marked specificity, efficiency, stability, and safety. In the present study, a novel, multi-epitope vaccine construct was developed against S. saprophyticus by targeting fully sequenced proteomes of its five different strains, which were examined using a pangenome and subtractive proteomic strategy to characterize prospective vaccination targets. The three immunogenic vaccine targets which were utilized to map the probable immune epitopes were verified by annotating the entire proteome. The predicted epitopes were further screened on the basis of antigenicity, allergenicity, water solubility, toxicity, virulence, and binding affinity towards the DRB*0101 allele, resulting in 11 potential epitopes, i.e., DLKKQKEKL, NKDLKKQKE, QDKLKDKSD, NVMDNKDLE, TSGTPDSQA, NANSDGSSS, GSDSSSSNN, DSSSSNNDS, DSSSSDRNN, SSSDRNNGD, and SSDDKSKDS. All these epitopes have the efficacy to cover 99.74% of populations globally. Finally, shortlisted epitopes were joined together with linkers and three different adjuvants to find the most stable and immunogenic vaccine construct. The top-ranked vaccine construct was further scrutinized on the basis of its physicochemical characterization and immunological profile. The non-allergenic and antigenic features of modeled vaccine constructs were initially validated and then subjected to docking with immune receptor major histocompatibility complex I and II (MHC-I and II), resulting in strong contact. In silico cloning validations yielded a codon adaptation index (CAI) value of 1 and an ideal percentage of GC contents (46.717%), indicating a putative expression of the vaccine in E. coli. Furthermore, immune simulation demonstrated that, after injecting the proposed MEVC, powerful antibodies were produced, resulting in the sharpest peaks of IgM + IgG formation (>11,500) within 5 to 15 days. Experimental testing against S. saprophyticus can evaluate the safety and efficacy of these prophylactic vaccination designs.

Dataset Information

Reverse vaccinology approach to design a novel multi-epitope vaccine candidate against COVID-19: an in silico study.

Publications

Reverse vaccinology approach to design a novel multi-epitope vaccine candidate against COVID-19: an <i>in silico</i> study.

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