ArticleVaccines2020
Immunogenic SARS-CoV-2 Epitopes: In Silico Study Towards Better Understanding of COVID-19 Disease-Paving the Way for Vaccine Development.
Article in Vaccines, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
13 citing papers in PubMed, 17 citations in OpenAlex.
- "Just the Best Ones" combination: a new strategy for multi-epitope vaccine candidate based on immunoinformatics analysis to induce protective immunity against MRSA infection.Microbiology spectrum · 2026Article
- Designing a novel vaccine against COVID-19 based on spike SARS-Cov-2 notable mutations using immunoinformatics approaches.PloS one · 2026Article
- The role of HLA genotypes in understanding the pathogenesis of severe COVID-19.The Egyptian journal of medical human genetics · 2023Review
- Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2.Chemical reviews · 2022Review
- T Cell Epitope Discovery in the Context of Distinct and Unique Indigenous HLA Profiles.Frontiers in immunology · 2022Review
- Article
- SARS-CoV-2 specific memory T cell epitopes identified in COVID-19-recovered subjects.Virus research · 2021Article
- Multi-Epitope Vaccine Design Using an Immunoinformatic Approach for SARS-CoV-2.Pathogens (Basel, Switzerland) · 2021Article
- Identification of Highly Conserved SARS-CoV-2 Antigenic Epitopes with Wide Coverage Using Reverse Vaccinology Approach.Viruses · 2021Article
- In silico T cell epitope identification for SARS-CoV-2: Progress and perspectives.Advanced drug delivery reviews · 2021Review
- Lessons Learned from Cutting-Edge Immunoinformatics on Next-Generation COVID-19 Vaccine Research.International journal of peptide research and therapeutics · 2021Article
- Development of an in silico multi-epitope vaccine against SARS-COV-2 by précised immune-informatics approaches.Informatics in medicine unlocked · 2021Article
- Papain-like cysteine proteinase zone (PCP-zone) and PCP structural catalytic core (PCP-SCC) of enzymes with cysteine proteinase fold.International journal of biological macromolecules · 2020Article
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
The emergence of the COVID-19 outbreak at the end of 2019, caused by the novel coronavirus SARS-CoV-2, has, to date, led to over 13.6 million infections and nearly 600,000 deaths. Consequently, there is an urgent need to better understand the molecular factors triggering immune defense against the virus and to develop countermeasures to hinder its spread. Using in silico analyses, we showed that human major histocompatibility complex (MHC) class I cell-surface molecules vary in their capacity for binding different SARS-CoV-2-derived epitopes, i.e., short sequences of 8-11 amino acids, and pinpointed five specific SARS-CoV-2 epitopes that are likely to be presented to cytotoxic T-cells and hence activate immune responses. The identified epitopes, each one of nine amino acids, have high sequence similarity to the equivalent epitopes of SARS-CoV virus, which are known to elicit an effective T cell response in vitro. Moreover, we give a structural explanation for the binding of SARS-CoV-2-epitopes to MHC molecules. Our data can help us to better understand the differences in outcomes of COVID-19 patients and may aid the development of vaccines against SARS-CoV-2 and possible future outbreaks of novel coronaviruses.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.