Evidence map›Paper›PMID 33041797›Full record

ArticleFrontiers in pharmacology2020

In Silico Prediction of Molecular Targets of Astragaloside IV for Alleviation of COVID-19 Hyperinflammation by Systems Network Pharmacology and Bioinformatic Gene Expression Analysis.

Chenliang Ge, Yan He

Open access · goldAbstract read
In one paragraph

Article in Frontiers in pharmacology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
4.5field-weighted citation impact, top 6% 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

15 citing papers in PubMed, 20 citations in OpenAlex.

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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

2 authors at 1 institution in 1 country.

Chenliang GeDepartment of Geriatrics Cardiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.
Yan HeDepartment of Geriatrics Cardiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.
Guangxi Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe overproduction of cytokines and chemokines caused by excessive and uncontrolled inflammation contributes to the development of COVID-19. Astragaloside IV is considered as an anti-inflammatory and antioxidant agent. This study aimed at undertaking a network pharmacology approach and bioinformatics analysis to uncover the pharmacological mechanisms of Astragaloside IV on COVID-19.

methodsPotential targets of Astragaloside IV were screened from public databases. Differentially expressed genes (DEGs) in SARS-CoV-2 were screened using bioinformatics analysis on the Gene Expression Omnibus (GEO) datasets GSE147507. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were subsequently performed. The overlapping genes, GO terms and KEGG pathways between Astragaloside IV targets and SARS-CoV-2 DEGs were confirmed, and the location of overlapping targets in the key pathways was queried using KEGG Mapper.

resultsA total of 425 potential targets of Astragaloside IV were screened. Besides, a total of 546 DEGs were identified between SARS-CoV-2 infected samples and control samples, including 380 up-regulated and 166 down-regulated genes. There was a significant overlap in GO terms and KEGG pathways between Astragaloside IV targets and SARS-CoV-2 DEGs. The shared genes included MMP13, NLRP3, TRIM21, GBP1, ADORA2A, PTAFR, TNF, MLNR, IL1B, NFKBIA, ADRB2, and IL6.

conclusionsThis study is the first to propose Astragaloside IV as a new drug candidate for alleviating hyper-inflammation in COVID-19 patients. Besides, the key targets and pathways may reveal the main pharmacological mechanism of Astragaloside IV in the treatment of COVID-19.

Indexed as

Astragaloside IVCOVID-19cytokine stormshyperinflammationnetwork pharmacological

Identifiers

PMID33041797
PMCPMC7525161
OpenAlexW3085413760

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.