Evidence map›Paper›PMID 33035337›Full record

ArticleNucleic acids research2021

DockCoV2: a drug database against SARS-CoV-2.

Ting-Fu Chen, Yu-Chuan Chang, Yi Hsiao, Ko-Han Lee, Yu-Chun Hsiao, Yu-Hsiang Lin, Yi-Chin Ethan Tu, Hsuan-Cheng Huang, Chien-Yu Chen, Hsueh-Fen Juan

Abstract read
In one paragraph

Article in Nucleic acids research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 1 pooled it
–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

31 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  5. Article
  6. Review
  7. Article
  8. Review
  9. Review
  10. Applying the digital data and the bioinformatics tools in SARS-CoV-2 research.Computational and structural biotechnology journal · 2023
    Review
  11. Article
  12. Article
  13. Review
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  15. Article
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  18. Review
  19. Implications ofFrontiers in cellular and infection microbiology · 2022
    Review
  20. Recent computational drug repositioning strategies against SARS-CoV-2.Computational and structural biotechnology journal · 2022
    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

10 authors.

Ting-Fu ChenTaiwan AI Labs, Taipei 10351, Taiwan.
Yu-Chuan ChangTaiwan AI Labs, Taipei 10351, Taiwan.
Yi HsiaoTaiwan AI Labs, Taipei 10351, Taiwan.
Ko-Han LeeTaiwan AI Labs, Taipei 10351, Taiwan.
Yu-Chun HsiaoTaiwan AI Labs, Taipei 10351, Taiwan.
Yu-Hsiang LinTaiwan AI Labs, Taipei 10351, Taiwan.
Yi-Chin Ethan TuTaiwan AI Labs, Taipei 10351, Taiwan.
Hsuan-Cheng HuangInstitute of Biomedical Informatics, National Yang-Ming University, Taipei 11221, Taiwan.
Chien-Yu ChenTaiwan AI Labs, Taipei 10351, Taiwan.
Hsueh-Fen JuanTaiwan AI Labs, Taipei 10351, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The current state of the COVID-19 pandemic is a global health crisis. To fight the novel coronavirus, one of the best-known ways is to block enzymes essential for virus replication. Currently, we know that the SARS-CoV-2 virus encodes about 29 proteins such as spike protein, 3C-like protease (3CLpro), RNA-dependent RNA polymerase (RdRp), Papain-like protease (PLpro), and nucleocapsid (N) protein. SARS-CoV-2 uses human angiotensin-converting enzyme 2 (ACE2) for viral entry and transmembrane serine protease family member II (TMPRSS2) for spike protein priming. Thus in order to speed up the discovery of potential drugs, we develop DockCoV2, a drug database for SARS-CoV-2. DockCoV2 focuses on predicting the binding affinity of FDA-approved and Taiwan National Health Insurance (NHI) drugs with the seven proteins mentioned above. This database contains a total of 3,109 drugs. DockCoV2 is easy to use and search against, is well cross-linked to external databases, and provides the state-of-the-art prediction results in one site. Users can download their drug-protein docking data of interest and examine additional drug-related information on DockCoV2. Furthermore, DockCoV2 provides experimental information to help users understand which drugs have already been reported to be effective against MERS or SARS-CoV. DockCoV2 is available at https://covirus.cc/drugs/.

Indexed as

COVID-19 Drug TreatmentAntiviral AgentsCOVID-19Databases, PharmaceuticalData CurationData MiningHumansInternetModels, MolecularPandemicsProtein BindingProtein DomainsSARS-CoV-2Viral ProteinsVirus ReplicationAntiviral AgentsViral Proteins

Identifiers

PMID33035337
PMCPMC7778986

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.