ArticleIn silico pharmacology2022
Identification of vaccine candidate against Omicron variant of SARS-CoV-2 using immunoinformatic approaches.
Article in In silico pharmacology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Designing potent and immunogenic epitope based peptide vaccine against all serotypes of DENV via structural, physico-chemical and immunoinformatics-based approaches.Scientific reports · 2026Article
- Development of a multi-epitope vaccine candidate targeting conserved regions of human metapneumovirus.Virusdisease · 2025Article
- Immunoinformatics-guided design of a multiepitope peptide vaccine targeting the receptor-binding domain of SARS-CoV-2 spike glycoprotein: insights from Indonesian samples.Journal of integrative bioinformatics · 2025Article
- Design of multi-epitope chimeric vaccine against Monkeypox virus and SARS-CoV-2: A vaccinomics perspective.Journal of cellular and molecular medicine · 2024Article
- Article
- mRNA vaccine design for Epstein-Barr virus: an immunoinformatic approach.In silico pharmacology · 2024Article
- Harnessing immunoinformatics for developing a multiple-epitope peptide-based vaccination approach against SARS-CoV-2 spike protein.Saudi journal of biological sciences · 2023Article
- In silico design of a novel peptide-based vaccine against the ubiquitous apicomplexanIn silico pharmacology · 2023Article
- Designing multi-epitope based peptide vaccine targeting spike protein SARS-CoV-2 B1.1.529 (Omicron) variant using computational approaches.Structural chemistry · 2022Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Despite the availability of COVID-19 vaccines, additional more potent vaccines are still required against the emerging variations of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In the present investigation, we have identified a promising vaccine candidate against the Omicron (B.1.1.529) using immunoinformatics approaches. Various available tools like, the Immune Epitope Database server resource, and NetCTL-1.2, have been used for the identification of the promising T-cell and B-cell epitopes. The molecular docking was performed to check the interaction of TLR-3 receptors and validated 3D model of vaccine candidate. The codon optimization was done followed by cloning using SnapGene. Finally, In-silico immune simulation profile was also checked. The identified T-cell and B-cell epitopes have been selected based on their antigenicity (VaxiJen v2.0) and, allergenicity (AllerTOP v2.0). The identified epitopes with antigenic and non-allergenic properties were fused with the specific peptide linkers. In addition, the 3D model was constructed by the PHYRE2 server and validated using ProSA-web. The validated 3D model was further docked with the Toll-like receptor 3 (TLR3) and showed good interaction with the amino acids which indicate a promising vaccine candidate against the Omicron variant of SARS-CoV-2. Finally, the codon optimization,
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