Evidence map›Paper›PMID 34226871›Full record

ArticleVirusdisease2021

Target-based drug discovery, ADMET profiling and bioactivity studies of antibiotics as potential inhibitors of SARS-CoV-2 main protease (M

Misbaudeen Abdul-Hammed, Ibrahim Olaide Adedotun, Victoria Adeola Falade, Adewusi John Adepoju, Sabitu Babatunde Olasupo, Modinat Wuraola Akinboade

Open access · bronzeAbstract read
In one paragraph

Article in Virusdisease, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
6.8field-weighted citation impact, top 3% 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

12 citing papers in PubMed, 69 citations in OpenAlex.

  1. Article
  2. Article
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  4. Computational identification ofFrontiers in pharmacology · 2024
    Article
  5. Article
  6. Eco-Friendly Synthesis of 1Pharmaceuticals (Basel, Switzerland) · 2023
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
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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

6 authors at 2 institutions in 1 country.

Misbaudeen Abdul-HammedDepartment of Pure and Applied Chemistry, Ladoke Akintola University of Technology, P.M.B. 4000, Ogbomoso, Nigeria.ORCID 0000-0002-5453-5858
Ibrahim Olaide AdedotunDepartment of Pure and Applied Chemistry, Ladoke Akintola University of Technology, P.M.B. 4000, Ogbomoso, Nigeria.
Victoria Adeola FaladeDepartment of Pure and Applied Chemistry, Ladoke Akintola University of Technology, P.M.B. 4000, Ogbomoso, Nigeria.
Adewusi John AdepojuDepartment of Pure and Applied Chemistry, Ladoke Akintola University of Technology, P.M.B. 4000, Ogbomoso, Nigeria.
Sabitu Babatunde OlasupoNational Agency for Food and Drug Administration and Control (NAFDAC), Abuja, Nigeria.
Modinat Wuraola AkinboadeDepartment of Biochemistry, Ladoke Akintola University of Technology, P.M.B. 4000, Ogbomoso, Nigeria.
Ladoke Akintola University of Technology · NGNational Agency for the Control of AIDS · NG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A recent outbreak of a new strain of Coronavirus (SARS-CoV-2) has become a global health burden, which has resulted in deaths. No proven drug has been found to effectively cure this fast-spreading infection, hence the need to explore old drugs with the known profile in tackling this pandemic. A computer-aided drug design approach involving virtual screening was used to obtain the binding scores and inhibiting efficiencies of previously known antibiotics against SARS-CoV-2 main protease (M

Indexed as

ADMET profilingAntibioticsCOVID-19Molecular dockingSARS-CoV-2 main protease (Mpro)

Identifiers

PMID34226871
PMCPMC8246438
OpenAlexW3136974273

What OpenQuestion holds

Textmetadata
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.