Evidence map›Paper›PMID 35517103›Full record

ArticleRSC advances2020

Design and optimization of a subunit vaccine targeting COVID-19 molecular shreds using an immunoinformatics framework.

Neeraj Kumar, Damini Sood, Ramesh Chandra

Open access · goldAbstract read
In one paragraph

Article in RSC advances, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 1 pooled it
2.3field-weighted citation impact, top 11% 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

23 citing papers in PubMed, 1 synthesis or guideline pooled it, 37 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Immunoinformatics Approaches in Designing Vaccines Against COVID-19.Methods in molecular biology (Clifton, N.J.) · 2023
    Article
  10. Article
  11. Review
  12. Article
  13. Review
  14. Article
  15. Review
  16. A contemporary review on the important role ofInformatics in medicine unlocked · 2022
    Review
  17. Article
  18. Article
  19. Article
  20. Article
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

3 authors at 1 institution in 1 country.

Neeraj KumarDepartment of Chemistry, University of Delhi Delhi 110007 India rameshchandradu@gmail.com acbrdu@hotmail.com.
Damini SoodDepartment of Chemistry, University of Delhi Delhi 110007 India rameshchandradu@gmail.com acbrdu@hotmail.com.
Ramesh ChandraDepartment of Chemistry, University of Delhi Delhi 110007 India rameshchandradu@gmail.com acbrdu@hotmail.com.ORCID https://orcid.org/0000-0003-2993-3560
University of Delhi · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

COVID-19 has been declared as a global health emergency and exposed the world to a deadly virus, which has dramatically changed the lives of humans for an unknown period of time. In the battleground with the virus, we have employed an immunoinformatics framework to design a robust vaccine as an insurance plan for the future. The pathogenic sequence with cryptic epitope taken from patients in Wuhan, China, was harnessed to design a promiscuous cytotoxic T-lymphocyte, helper T-lymphocyte, and B-cell epitope based subunit vaccine, engineered with adjuvants and conformational linkers. The reported vaccine has high antigenicity and immunogenicity profiles with potential TAP affinity, which ensures elevated antigen processing capability. It has strong binding with major histocompatibility complex (MHC) receptors (MHC-1 and MHC-2) and virus-specific membrane receptor TLR-2, with scores of -1010.7, -1035.7, and -1076.3 kcal mol

Identifiers

PMID35517103
PMCPMC9056885
OpenAlexW3090347626

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.