Design of a Novel Multi Epitope-Based Vaccine for Pandemic Coronavirus Disease (COVID-19) by Vaccinomics and Probable Prevention Strategy against Avenging Zoonotics

Ahmad, Sajjad; Navid, Afifa; Farid, Rabia; Abbas, Ghulam; Ahmad, Faisal; Zaman, Naila; Parvaiz, Nousheen; Azam, Syed Sikander

doi:10.1016/j.ejps.2020.105387

Cited by 42 publications

(30 citation statements)

References 83 publications

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“…The Grand average of hydropathicity (GRAVY) value was computed to be negative (− 0.111), revealing that the vaccine is hydrophilic in nature and likely to interact with other protein molecules. The above observations that all the physicochemical properties of our MEBP construct are within the optimum range indicate that our vaccine construct has the properties of a good vaccine (Solanki et al 2019 ; Ahmad et al 2020 ).…”

Section: Discussionmentioning

confidence: 73%

Designing a next generation multi-epitope based peptide vaccine candidate against SARS-CoV-2 using computational approaches

Saha¹,

Ghosh

Burra³

2021

3 Biotech

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COVID-19 caused by SARS-CoV-2 was declared a global pandemic by WHO (World Health Organization) in March, 2020. Within 6 months, nearly 750,000 deaths are claimed by COVID-19 across the globe. This called for immediate social, scientific, technological, public and community interventions. Considering the severity of infection and the associated mortalities, global efforts are underway to develop preventive measures against SARS-CoV-2. Among the SARS-CoV-2 target proteins, Spike (S) glycoprotein (a.k.a S Protein) is the most studied target known to trigger strong host immune response. A detailed analysis of S protein-based epitopes enabled us to design a novel B-cell-derived T-cell Multi-epitope-based peptide (MEBP) vaccine candidate. This involved a systematic and comprehensive computational protocol consisting of prediction of dual-purpose epitopes and designing an MEBP vaccine construct. This was followed by 3D structure validation, MEBP complex interaction studies, in silico cloning and vaccine dose-based immune response simulation to evaluate the immunogenic potency of the vaccine construct. The dual-purpose epitope prediction protocol was designed such that the same epitope elicits both humoral and cellular immune response unlike the earlier designs. Further, the epitopes predicted were screened against stringent criteria to ensure selection of a potent candidate with maximum antigen coverage and best immune response. The vaccine dose-based immune response simulation studies revealed a rapid antigen clearance through antibody generation and elevated levels of cell-mediated immunity during repeated exposure of the vaccine. The favourable results of the analysis strongly indicate that the vaccine construct is indeed a potent vaccine candidate and ready to proceed to the next steps of experimental validation and efficacy studies.

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Section: Discussionmentioning

confidence: 73%

Designing a next generation multi-epitope based peptide vaccine candidate against SARS-CoV-2 using computational approaches

Saha¹,

Ghosh

Burra³

2021

3 Biotech

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“…This offers proof of the practical significance of immunoinformatics. Similarly, various studies reported MEV constructs for SARS-CoV-2 using one or multiple proteins [ 33 , 34 , 88 – 95 ]. But none of them used all anti-genic proteins of SARS-CoV-2 both structure and non-structure collectively to screen a pool of conserved/overlapping epitopes to design a comprehensive MEV construct.…”

Section: Discussionmentioning

confidence: 99%

Designing of a next generation multiepitope based vaccine (MEV) against SARS-COV-2: Immunoinformatics and in silico approaches

et al. 2020

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Coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory coronavirus 2 (SARS-COV-2) is a significant threat to global health security. Till date, no completely effective drug or vaccine is available to cure COVID-19. Therefore, an effective vaccine against SARS-COV-2 is crucially needed. This study was conducted to design an effective multiepitope based vaccine (MEV) against SARS-COV-2. Seven highly antigenic proteins of SARS-COV-2 were selected as targets and different epitopes (B-cell and T-cell) were predicted. Highly antigenic and overlapping epitopes were shortlisted. Selected epitopes indicated significant interactions with the HLA-binding alleles and 99.93% coverage of the world’s population. Hence, 505 amino acids long MEV was designed by connecting 16 MHC class I and eleven MHC class II epitopes with suitable linkers and adjuvant. MEV construct was non-allergenic, antigenic, stable and flexible. Furthermore, molecular docking followed by molecular dynamics (MD) simulation analyses, demonstrated a stable and strong binding affinity of MEV with human pathogenic toll-like receptors (TLR), TLR3 and TLR8. Finally, MEV codons were optimized for its in silico cloning into Escherichia coli K-12 system, to ensure its increased expression. Designed MEV in present study could be a potential candidate for further vaccine production process against COVID-19. However, to ensure its safety and immunogenic profile, the proposed MEV needs to be experimentally validated.

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“…Consequently, it has also been employed to search for multi-epitopes from various proteins (including S, N, etc.) to design the vaccine candidate for COVID-19 (Ahmad et al 2020 ; Kalita et al 2020 ; Jyotisha et al 2020 ; Enayatkhani et al 2020 ). The N protein of the coronavirus is the most abundant, highly conserved and immunogenic protein.…”

Section: Discussionmentioning

confidence: 99%

Designing of Nucleocapsid Protein Based Novel Multi-epitope Vaccine Against SARS-COV-2 Using Immunoinformatics Approach

Kumar

Qureshi

Sagurthi

et al. 2020

Int J Pept Res Ther

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Design of a Novel Multi Epitope-Based Vaccine for Pandemic Coronavirus Disease (COVID-19) by Vaccinomics and Probable Prevention Strategy against Avenging Zoonotics

Cited by 42 publications

References 83 publications

Designing a next generation multi-epitope based peptide vaccine candidate against SARS-CoV-2 using computational approaches

Designing a next generation multi-epitope based peptide vaccine candidate against SARS-CoV-2 using computational approaches

Designing of a next generation multiepitope based vaccine (MEV) against SARS-COV-2: Immunoinformatics and in silico approaches

Designing of Nucleocapsid Protein Based Novel Multi-epitope Vaccine Against SARS-COV-2 Using Immunoinformatics Approach

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