Evidence map›Paper›PMID 32828312›Full record

ArticleBiochemical and biophysical research communications2020

Establishment and validation of a drug-target microarray for SARS-CoV-2.

Peng Chen, Zehua Zeng, Hongwu Du

Abstract read
In one paragraph

Article in Biochemical and biophysical research communications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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.

Peng ChenBeijing Key Laboratory of Traditional Chinese Medicine Basic Research on Prevention and Treatment for Major Diseases, Experimental Research Center, China Academy of Chinese Medical Sciences, Beijing, China.
Zehua ZengSchool of Chemistry and Biological Engineering, University of Science and Technology Beijing, Beijing, China.
Hongwu DuSchool of Chemistry and Biological Engineering, University of Science and Technology Beijing, Beijing, China. Electronic address: hwdu93@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

COVID-19 has become one of the worst epidemic in the world, currently already more than four million people have been infected, which probably co-exist with human beings, and has a significant impact on the global economy and political order. In the process of fighting against the epidemic in China, the clinical value of a variety of herbal medicines has been recognized and written into the clinical application guide. However, their effective molecular mechanism and potential targets are still not clear. Pathology and pharmacology research will gradually attract attention in the post-epidemic outbreak term. Here, we constructed a COVID-19 protein microarray of potential therapy targets, which contains the main drug targets to the SARS-CoV-2 virus and the anti-virus, anti-inflammatory cellar targets of the host. Series of quality controls test has been carried out, which showed that it could be applied for drug target screening of bio-active natural products. The establishment of this microarray will provide a useful tool for the study of the molecular pharmacology of natural products.

Indexed as

Antiviral AgentsBetacoronavirusBiological ProductsChlorogenic AcidCoronavirus InfectionsCOVID-19DiterpenesDrug DiscoveryDrugs, Chinese HerbalGlucosidesHEK293 CellsHumansMolecular Docking SimulationMolecular Targeted TherapyPandemicsPneumonia, ViralandrographolideAntiviral AgentsBiological ProductsChlorogenic AcidDiterpenesDrugs, Chinese HerbalGlucosidespolydatinProteinsStilbenesViral ProteinsCOVID-19Drug targetMicroarraySARS-CoV-2

Identifiers

PMID32828312
PMCPMC7373225

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.