ArticleScientific reports2020
Immunoinformatic identification of B cell and T cell epitopes in the SARS-CoV-2 proteome.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
59 citing papers in PubMed, 106 citations in OpenAlex.
- Chimeric SARS-CoV-2 vaccine vectors stably incorporating the functional glycoprotein of VSV.iScience · 2026Article
- Multi-epitope design against emerging nipah virus towards peptide vaccine development.Bioinformation · 2026Article
- Development of SARS-CoV-2 as a viral vector: A novel intranasal bivalent vaccine for SARS-CoV-2 and RSV.Science advances · 2025Article
- VirusImmu: a novel ensemble machine learning approach for viral immunogenicity prediction.Briefings in functional genomics · 2025Article
- Promising Strategies to Reduce the SARS-CoV-2 Amyloid Deposition in the Brain and Prevent COVID-19-Exacerbated Dementia and Alzheimer's Disease.Pharmaceuticals (Basel, Switzerland) · 2024Review
- COVID-19 Variants and Vaccine Development.Viruses · 2024Review
- Prediction of antigenic peptides of SARS- CoV-2 pathogen using machine learning.PeerJ. Computer science · 2024Article
- Physicochemical properties-based hybrid machine learning technique for the prediction of SARS-CoV-2 T-cell epitopes as vaccine targets.PeerJ. Computer science · 2024Article
- Immunodominant conserved moieties on spike protein of SARS-CoV-2 renders virulence factor for the design of epitope-based peptide vaccines.Virusdisease · 2023Article
- Inferring linear-B cell epitopes using 2-step metaheuristic variant-feature selection using genetic algorithm.Scientific reports · 2023Article
- Serodominant SARS-CoV-2 Nucleocapsid Peptides Map to Unstructured Protein Regions.Microbiology spectrum · 2023Article
- Exploring the Intersection of Artificial Intelligence and Clinical Healthcare: A Multidisciplinary Review.Diagnostics (Basel, Switzerland) · 2023Review
- Review
- The race to understand immunopathology in COVID-19: Perspectives on the impact of quantitative approaches to understand within-host interactions.Immunoinformatics (Amsterdam, Netherlands) · 2023Review
- State of the art in epitope mapping and opportunities in COVID-19.Future science OA · 2023Review
- SARS-CoV-2 amyloid, is COVID-19-exacerbated dementia an amyloid disorder in the making?Frontiers in dementia · 2023Article
- Design and preclinical evaluation of a universal SARS-CoV-2 mRNA vaccine.Frontiers in immunology · 2023Article
- Mapping Potential Vaccine Candidates Predicted by VaxiJen for Different Viral Pathogens between 2017-2021-A Scoping Review.Vaccines · 2022Article
- Immune epitopes identification and designing of a multi-epitope vaccine against bovine leukemia virus: a molecular dynamics and immune simulation approaches.Cancer immunology, immunotherapy : CII · 2022Article
- Knowledge of SARS-CoV-2 Epitopes and Population HLA Types Is Important in the Design of COVID-19 Vaccines.Vaccines · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A novel coronavirus (SARS-CoV-2) emerged from China in late 2019 and rapidly spread across the globe, infecting millions of people and generating societal disruption on a level not seen since the 1918 influenza pandemic. A safe and effective vaccine is desperately needed to prevent the continued spread of SARS-CoV-2; yet, rational vaccine design efforts are currently hampered by the lack of knowledge regarding viral epitopes targeted during an immune response, and the need for more in-depth knowledge on betacoronavirus immunology. To that end, we developed a computational workflow using a series of open-source algorithms and webtools to analyze the proteome of SARS-CoV-2 and identify putative T cell and B cell epitopes. Utilizing a set of stringent selection criteria to filter peptide epitopes, we identified 41 T cell epitopes (5 HLA class I, 36 HLA class II) and 6 B cell epitopes that could serve as promising targets for peptide-based vaccine development against this emerging global pathogen. To our knowledge, this is the first study to comprehensively analyze all 10 (structural, non-structural and accessory) proteins from SARS-CoV-2 using predictive algorithms to identify potential targets for vaccine development.
Indexed as
Identifiers
What OpenQuestion holds
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.