Immunoinformatics guided rational design of a next generation multi epitope based peptide (MEBP) vaccine by exploring Zika virus proteome

Shahid, Farah; Ashfaq, Usman Ali; Javaid, Anam; Khalid, Hina

doi:10.1016/j.meegid.2020.104199

Cited by 65 publications

(47 citation statements)

References 79 publications

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“…The subunit vaccine contains the fragments of antigenic proteins of pathogen that can trigger an immune response against the target pathogen [16, 17]. In recent studies, few candidate vaccine constructs were reported against MERS-CoV [18], Chikungunya virus [19], Ebola virus [20], Zika virus [21], HCV [22], Flavivirus [23] and Cytomegalovirus [24] with promising results. The in silico methods reduce the number of in vitro experiments and save time, overcome cost obstacles and increase the potential for successful vaccine design [25-27].…”

Section: Introductionmentioning

confidence: 99%

“…The subunit vaccine contains the fragments of antigenic proteins that can mimic the presence of the natural pathogen and cause an immune response to the target pathogen 14, 15 . The design of the vaccine candidate against chikungunya, MERS virus, Ebola virus and Zika has produced promising results 16–19 . The in silico methods reduce the number of in vitro experiments and save time, overcome cost obstacles and increase the potential for successful vaccine design 20, 21 .…”

Section: Introductionmentioning

confidence: 99%

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Designing of a next generation multiepitope based vaccine (MEV) against SARS-COV-2: Immunoinformatics andin silicoapproaches

Qamar¹,

Rehman

Ashfaq

et al. 2020

Preprint

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1Coronavirus disease 2019 (COVID-19) associated pneumonia caused by severe acute respiratory 2 coronavirus 2 (SARS-COV-2) was first reported in Wuhan, China in December 2019. Till date, 3 no vaccine or completely effective drug is available for the cure of COVID-19. Therefore, an 4 effective vaccine against SARS-COV-2 is needed to be design. This study was conducted to 5 design an effective multi-epitope vaccine (MEV) against SARS-COV-2. Seven antigenic 6 proteins were taken as a target and epitopes (B cell, IFNγ and T cell) were predicted. Highly 7 antigenic and overlapping epitopes were shortlisted. Selected T cell epitopes indicated significant 8 interactions with the HLA-binding alleles and 99.29% coverage of the world's population. 9 Finally, 505 amino acids long MEV was designed by connecting sixteen MHC class I and twelve 1 0 MHC class II epitopes with suitable linkers and adjuvant. Linkers and adjuvant were added to 1 1 enhance the immunogenicity response of the vaccine. The allergenicity, physiochemical 1 2 properties, antigenicity and structural details of MEV were analyzed in order to ensure safety and 1 3 immunogenicity. MEV construct was non-allergenic and antigenic. Molecular docking 1 4 demonstrated a stable and strong binding affinity of MEV with TLR3 and TLR8. Codon 1 5 optimization and in silico cloning ensured increased expression in the Escherichia coli K-12 1 6system. However, to ensure its safety and immunogenic profile, the proposed vaccine needs to be 1 7 experimentally validated. 1 8

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Designing of a next generation multiepitope based vaccine (MEV) against SARS-COV-2: Immunoinformatics andin silicoapproaches

Qamar¹,

Rehman

Ashfaq

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

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“…Bioinformatic approaches are very helpful to identify the effective epitopes and developing vaccine. Several vaccines for virus diseases were designed based on these approaches that include effective vaccines on Human papilloma viridea (HPV) [23],Ebola [24], Zika[25]and MERS[26, 27]viruses. There are also few reports of a vaccine candidate for COVID19[28, 29].…”

Section: Introductionmentioning

confidence: 99%

Design an efficient multi-epitope peptide vaccine candidate against SARS-CoV-2: An in silico analysis

Yazdani

Rafiei

Yazdani

et al. 2020

Preprint

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Background: To date, no specific vaccine or drug has been proven to be effective for SARS-CoV-2 infection. Therefore, we implemented immunoinformatics approach to design an efficient multi-epitopes vaccine against SARS-CoV-2.Results: The designed vaccine construct has several immunodominant epitopes from structural proteins of Spike, Nucleocapsid, Membrane and Envelope. These peptides promote cellular and humoral immunity and Interferon gamma responses. In addition, these epitopes have antigenicity ability and no allergenicity probability. To enhance the vaccine immunogenicity, we used three potent adjuvants; Flagellin, a driven peptide from high mobility group box 1 as HP-91 and human beta defensin 3 protein. The physicochemical and immunological properties of the vaccine structure were evaluated. Tertiary structure of the vaccine protein was predicted and refined by I-Tasser and galaxi refine and validated using Rampage and ERRAT. Results of Ellipro showed 242 residues from vaccine might be conformational B cell epitopes. Docking of vaccine with Toll-Like Receptors 3, 5 and 8 proved an appropriate interaction between the vaccine and receptor proteins. In silico cloning demonstrated that the vaccine can be efficiently expressed in Escherichia coli.Conclusions: The designed multi epitope vaccine is potentially antigenic in nature and has the ability to induce humoral and cellular immune responses against SARS-CoV-2. This vaccine can interact appropriately with the TLR3, 5, and 8. Also, this vaccine has high quality structure and suitable characteristics such as high stability and potential for expression in Escherichia coli.

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“…RS09, and FlgC) can activate both TLRs 4 and 5, respectively (6). Second, protein is degraded by proteasomes to the small peptide fragments (7). The peptide fragments are processed by the endoplasmic reticulum (8).…”

Section: Figure 10mentioning

confidence: 99%

“…The empirical vaccinology against emerging and re-emerging infectious (EREI) pathogens such as SARS-CoV-2 might contend with several critical challenges, in large measure because of the paucity of the basic knowledge about their pathogenic mechanisms and behavior 5 . In contrast, the rational vaccinology through the bioinformatics, statistical meta-analyses (or mining) among the pathogen's genome/proteome, and comparative pathogenomic analyses might provide key detailed estimates for the vaccine design [6][7][8] .…”

Section: Introductionmentioning

confidence: 99%

Prophylactic domain-based vaccine against SARS-CoV-2, causative agent of COVID-19 pandemic

Pourseif

Parvizpour

Jafari

et al. 2020

Preprint

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Coronavirus disease 2019 (COVID-19) is undoubtedly the most challenging pandemic in the current century with more than 253,381 deaths worldwide since its emergence in late 2019 (updated May 6th, 2020). COVID-19 is caused by a novel emerged coronavirus named as Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Today, the world needs crucially to develop a prophylactic vaccine scheme for such emerged and emerging infectious pathogens. In this study, we have targeted spike (S) glycoprotein, as an important surface antigen of SARS-CoV-2, to identify its immunodominant B- and T-cell epitopes. We have conducted a multi-method B-cell epitope (BCE) prediction approach using different predictor algorithms to discover most potential BCEs. Besides, we sought among a pool of MHC class I and II-associated peptide binders provided by the IEDB server through the strict cut-off values. To design a broad-coverage vaccine, we carried out a population coverage analysis for a set of candidate T-cell epitopes and based on the HLA allele frequency in the top most-affected countries by COVID-19 (update 02 April 2020). The final determined B- and T-cell epitopes were mapped on the S glycoprotein sequence, and three potential hub regions covering the largest number of overlapping epitopes were identified for the vaccine designing (I531–N711; T717–C877; and V883–E973). Here, we have designed two domain-based constructs to be produced and delivered through the recombinant protein- and gene-based approaches, including (i) an adjuvanted domain-based protein vaccine construct (DPVC), and (ii) a self-amplifying mRNA vaccine (SAMV) construct. The safety, stability, and immunogenicity of the DPVC were validated using the integrated sequential (i.e. allergenicity, autoimmunity, and physicochemical features) and structural (i.e. molecular docking between the vaccine and human Toll-like receptors (TLRs) 4 and 5) analysis. The stability of the docked complexes was evaluated using the molecular dynamics (MD) simulations. These rigorous in silico validations supported the potential of the DPVC and SAMV to promote both innate and specific immune responses in the animal studies.

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Immunoinformatics guided rational design of a next generation multi epitope based peptide (MEBP) vaccine by exploring Zika virus proteome

Cited by 65 publications

References 79 publications

Designing of a next generation multiepitope based vaccine (MEV) against SARS-COV-2: Immunoinformatics andin silicoapproaches

Designing of a next generation multiepitope based vaccine (MEV) against SARS-COV-2: Immunoinformatics andin silicoapproaches

Design an efficient multi-epitope peptide vaccine candidate against SARS-CoV-2: An in silico analysis

Prophylactic domain-based vaccine against SARS-CoV-2, causative agent of COVID-19 pandemic

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