Evidence map›Paper›PMID 39525081›Full record

ArticleComputational and structural biotechnology journal2024

Revealing SARS-CoV-2 M

Victor Barozi, Shrestha Chakraborty, Shaylyn Govender, Emily Morgan, Rabelani Ramahala, Stephen C Graham, Nigel T Bishop, Özlem Tastan Bishop

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Computational and structural biotechnology journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Decoding the cross-immune pressure: Dengue's role in SARS-CoV-2 evolution.Computational and structural biotechnology journal · 2025
    Article
  7. 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

8 authors.

Victor BaroziResearch Unit in Bioinformatics (RUBi), Department of Biochemistry, Microbiology and Bioinformatics, Rhodes University, Makhanda 6139, South Africa.
Shrestha ChakrabortyDivision of Virology, Department of Pathology, University of Cambridge, Cambridge CB2 1QP, UK.
Shaylyn GovenderResearch Unit in Bioinformatics (RUBi), Department of Biochemistry, Microbiology and Bioinformatics, Rhodes University, Makhanda 6139, South Africa.
Emily MorganResearch Unit in Bioinformatics (RUBi), Department of Biochemistry, Microbiology and Bioinformatics, Rhodes University, Makhanda 6139, South Africa.
Rabelani RamahalaResearch Unit in Bioinformatics (RUBi), Department of Biochemistry, Microbiology and Bioinformatics, Rhodes University, Makhanda 6139, South Africa.
Stephen C GrahamDivision of Virology, Department of Pathology, University of Cambridge, Cambridge CB2 1QP, UK.
Nigel T BishopDepartment of Pure and Applied Mathematics, Rhodes University, Makhanda 6139, South Africa.
Özlem Tastan BishopResearch Unit in Bioinformatics (RUBi), Department of Biochemistry, Microbiology and Bioinformatics, Rhodes University, Makhanda 6139, South Africa.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Deciphering the effect of evolutionary mutations of viruses and predicting future mutations is crucial for designing long-lasting and effective drugs. While understanding the impact of current mutations on protein drug targets is feasible, predicting future mutations due to natural evolution of viruses and environmental pressures remains challenging. Here, we leveraged existing mutation data during the evolution of the SARS-CoV-2 protein drug target main protease (M

Indexed as

3CLproArtificial neural networksChymotrypsin-like proteaseCOVID-19Decision treeDrug designDrug resistanceMproNetwork analysisNsp5Pathogen evolutionSARS-CoV

Identifiers

PMID39525081
PMCPMC11550722

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.