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A High Throughput MHC II Binding Assay for Quantitative Analysis of Peptide Epitopes
Published on: March 25, 2014
In silico Design of a Vaccine Candidate for SAR S-CoV-2 Based on Multiple T-cell and B-cell Epitopes
B J Oso1, I F Olaoye1,2, C O Ogidi3
1Department of Biochemistry, McPherson University, Seriki Sotayo, Ogun State, Nigeria.
Abstract:
Coronaviruses (2019-nCoV) are large single-stranded RNA viruses that usually cause respiratory infections with a crude lethality ratio of 3.8% and high levels of transmissibility. There is yet no applicable clinical evaluation to assess the efficacy of various therapeutic agents that have been suggested as investigational drugs against the viruses despite their respective supposed hypothetical claims due to their antiviral potentials. Moreover, the development of a safe and effective vaccine has been suggested as an intervention to control the 2019-nCoV pandemic. However, a major concern in the development of a 2019-nCoV vaccine is the possibility of stimulating a corresponding immune response without enhancing the induction of the disease and associated side effects. The present investigation was carried out by predicting the antigenicity of the primary sequences of 2019-nCoV structural proteins and identification of B-cell and T-cell epitopes through the Bepipred and PEPVAC servers, respectively. The peptides of the vaccine construct include the selected epitopes based on the VaxiJen score with a threshold of 1.0 and β-defensinas an adjuvant. The putative binding of the vaccine constructs to intracellular toll-like receptors (TLRs) was assessed through molecular docking analysis and molecular dynamics simulations. The selected epitopes for the final vaccine construct are DPNFKD, SPLSLN, and LELQDHNE as B-cell epitopes and EPKLGSLVV, NFKDQVILL, and SSRSSSRSR as T-cell epitopes. The molecular docking analysis showed the vaccine construct could have favorable interactions with TLRs as indicated by the negative values of the computed binding energies. The constructed immunogen based on the immune informatics study could be employed in the strategy to develop potential vaccine candidates against 2019-nCoV.
Insights
This study identified key viral epitopes to design a potential 2019-nCoV vaccine. Computational analysis predicted favorable interactions with immune receptors, suggesting a promising vaccine candidate strategy.
Area of Science:
- Virology
- Immunoinformatics
- Vaccine Development
Background:
- Coronaviruses (2019-nCoV) cause severe respiratory infections with high transmissibility.
- Existing treatments lack clinical validation, and vaccine development faces challenges in ensuring safety and efficacy.
- Preventing enhanced disease and side effects is crucial for 2019-nCoV vaccine development.
Purpose of the Study:
- To predict the antigenicity of 2019-nCoV structural proteins.
- To identify B-cell and T-cell epitopes for vaccine construct design.
- To assess the binding affinity of vaccine constructs to toll-like receptors (TLRs).
Main Methods:
- Antigenicity prediction using Bepipred and PEPVAC servers.
- Epitope selection based on VaxiJen scores and inclusion of β-defensins as adjuvants.
- Molecular docking and dynamics simulations to evaluate TLR binding.
Main Results:
- Identified specific B-cell (DPNFKD, SPLSLN, LELQDHNE) and T-cell (EPKLGSLVV, NFKDQVILL, SSRSSSRSR) epitopes.
- Vaccine constructs demonstrated favorable interactions with TLRs, indicated by negative binding energies.
- Computational analysis supported the potential of the constructed immunogen.
Conclusions:
- The immunoinformatics approach successfully identified potential vaccine epitopes.
- The constructed immunogen shows promise for developing effective 2019-nCoV vaccine candidates.
- Further research can utilize this immunogen in vaccine development strategies.
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