Evidence map›Paper›PMID 34766004›Full record

ArticleMolecular biomedicine2021

Computationally repurposed drugs and natural products against RNA dependent RNA polymerase as potential COVID-19 therapies.

Sakshi Piplani, Puneet Kumar Singh, David A Winkler, Nikolai Petrovsky

Abstract read
In one paragraph

Article in Molecular biomedicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Computational Drug Design Strategies for Fighting the COVID-19 Pandemic.Advances in experimental medicine and biology · 2024
    Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Review
  8. 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

4 authors.

Sakshi PiplaniCollege of Medicine and Public Health, Flinders University, Bedford Park, 5046 Australia.
Puneet Kumar SinghVaxine Pty Ltd, 11 Walkley Avenue, Warradale, 5046 Australia.
David A WinklerSchool of Biochemistry and Genetics, La Trobe University, Bundoora, 3086 Australia.ORCID 0000-0002-7301-6076
Nikolai PetrovskyCollege of Medicine and Public Health, Flinders University, Bedford Park, 5046 Australia.ORCID 0000-0002-1580-5245

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Repurposing of existing drugs and drug candidates is an ideal approach to identify new potential therapies for SARS-CoV-2 that can be tested without delay in human trials of infected patients. Here we applied a virtual screening approach using Autodock Vina and molecular dynamics simulation in tandem to calculate binding energies for repurposed drugs against the SARS-CoV-2 RNA-dependent RNA polymerase (RdRp). We thereby identified 80 promising compounds with potential activity against SARS-Cov2, consisting of a mixture of antiviral drugs, natural products and drugs with diverse modes of action. A substantial proportion of the top 80 compounds identified in this study had been shown by others to have SARS-CoV-2 antiviral effects in vitro or in vivo, thereby validating our approach. Amongst our top hits not previously reported to have SARS-CoV-2 activity, were eribulin, a macrocyclic ketone analogue of the marine compound halichondrin B and an anticancer drug, the AXL receptor tyrosine kinase inhibitor bemcentinib. Our top hits from our RdRp drug screen may not only have utility in treating COVID-19 but may provide a useful starting point for therapeutics against other coronaviruses. Hence, our modelling approach successfully identified multiple drugs with potential activity against SARS-CoV-2 RdRp. Supplementary Information: The online version contains supplementary material available at 10.1186/s43556-021-00050-3.

Indexed as

Drug repurposingMolecular dockingMolecular dynamicsRNA-dependent RNA polymeraseSARS-CoV-2

Identifiers

PMID34766004
PMCPMC8450033

What OpenQuestion holds

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Registered trials

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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.