Evidence map›Paper›PMID 32635180›Full record

ArticleVaccines2020

Immunoinformatic Analysis of T- and B-Cell Epitopes for SARS-CoV-2 Vaccine Design.

Dongliang Wang, Jinhui Mai, Wenfeng Zhou, Wanting Yu, Yang Zhan, Naidong Wang, Neal D Epstein, Yi Yang

Open access · goldAbstract read
In one paragraph

Article in Vaccines, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.

0numbers the graph read from it
0cells of the map it votes in
48citing papers in PubMed
1.4field-weighted citation impact, top 10% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

48 citing papers in PubMed, 60 citations in OpenAlex.

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  18. Development of a Multi-Epitope Vaccine forInternational journal of molecular sciences · 2022
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 3 institutions in 2 countries.

Dongliang WangHunan Provincial Key Laboratory of Protein Engineering in Animal Vaccines, Laboratory of Functional Proteomics (LFP), Research Center of Reverse Vaccinology (RCRV), College of Veterinary Medicine, Hunan Agricultural University, Changsha 410128, China.
Jinhui MaiHunan Provincial Key Laboratory of Protein Engineering in Animal Vaccines, Laboratory of Functional Proteomics (LFP), Research Center of Reverse Vaccinology (RCRV), College of Veterinary Medicine, Hunan Agricultural University, Changsha 410128, China.
Wenfeng ZhouHunan Provincial Key Laboratory of Protein Engineering in Animal Vaccines, Laboratory of Functional Proteomics (LFP), Research Center of Reverse Vaccinology (RCRV), College of Veterinary Medicine, Hunan Agricultural University, Changsha 410128, China.
Wanting YuHunan Provincial Key Laboratory of Protein Engineering in Animal Vaccines, Laboratory of Functional Proteomics (LFP), Research Center of Reverse Vaccinology (RCRV), College of Veterinary Medicine, Hunan Agricultural University, Changsha 410128, China.
Yang ZhanHunan Provincial Key Laboratory of Protein Engineering in Animal Vaccines, Laboratory of Functional Proteomics (LFP), Research Center of Reverse Vaccinology (RCRV), College of Veterinary Medicine, Hunan Agricultural University, Changsha 410128, China.
Naidong WangHunan Provincial Key Laboratory of Protein Engineering in Animal Vaccines, Laboratory of Functional Proteomics (LFP), Research Center of Reverse Vaccinology (RCRV), College of Veterinary Medicine, Hunan Agricultural University, Changsha 410128, China.
Neal D EpsteinCell and Developmental Biology Center, NHLBI, NIH, Bethesda, MD 20892, USA.
Yi YangHunan Provincial Key Laboratory of Protein Engineering in Animal Vaccines, Laboratory of Functional Proteomics (LFP), Research Center of Reverse Vaccinology (RCRV), College of Veterinary Medicine, Hunan Agricultural University, Changsha 410128, China.ORCID 0000-0003-2502-1011
Hunan Agricultural University · CNNational Institutes of Health · USPeking University · CN

Funding

Double first-class construction project of Hunan Agricultural University SYL2019048Hunan Education Department's Science & Research Project 18B092Hunan Provincial Key Laboratory of Protein Engineering in Animal Vaccine 2017TP1014Hunan Provincial Natural Science Foundation of China 2018JJ2177
6 · The paper itself

Abstract

Currently, there is limited knowledge about the immunological profiles of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). We used computer-based immunoinformatic analysis and the newly resolved 3-dimensional (3D) structures of the SARS-CoV-2 S trimeric protein, together with analyses of the immunogenic profiles of SARS-CoV, to anticipate potential B-cell and T-cell epitopes of the SARS-CoV-2 S protein for vaccine design, particularly for peptide-driven vaccine design and serological diagnosis. Nine conserved linear B-cell epitopes and multiple discontinuous B-cell epitopes composed of 69 residues on the surface of the SARS-CoV-2 trimeric S protein were predicted to be highly antigenic. We found that the SARS-CoV-2 S protein has a different antigenic profile than that of the SARS-CoV S protein due to the variations in their primary and 3D structures. Importantly, SARS-CoV-2 may exploit an immune evasion mechanism through two point mutations in the critical and conserved linear neutralization epitope (overlap with fusion peptide) around a sparsely glycosylated area. These mutations lead to a significant decrease in the antigenicity of this epitope in the SARS-CoV-2 S protein. In addition, 62 T-cell epitopes in the SARS-CoV-2 S protein were predicted in our study. The structure-based immunoinformatic analysis for the SARS-CoV-2 S protein in this study may improve vaccine design, diagnosis, and immunotherapy against the pandemic of COVID-19.

Indexed as

B-cell and T-cell epitopesSARS-CoV-2S proteinvaccine

Identifiers

PMID32635180
PMCPMC7563688
OpenAlexW3038307487

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.