Evidence map›Paper›PMID 33082858›Full record

ArticleBioData mining2020

Examining the effector mechanisms of Xuebijing injection on COVID-19 based on network pharmacology.

Wen-Jiang Zheng, Qian Yan, Yong-Shi Ni, Shao-Feng Zhan, Liu-Liu Yang, Hong-Fa Zhuang, Xiao-Hong Liu, Yong Jiang

Open access · goldAbstract read
In one paragraph

Article in BioData mining, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 3 pooled it
5.7field-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

25 citing papers in PubMed, 3 syntheses or guidelines pooled it, 45 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

8 authors at 3 institutions in 1 country.

Wen-Jiang Zheng *The First Clinical Medical School of Guangzhou University of Chinese Medicine, Guangzhou, China.
Qian Yan *The First Clinical Medical School of Guangzhou University of Chinese Medicine, Guangzhou, China.
Yong-Shi NiThe Second Clinical Medical School of Guangzhou University of Chinese Medicine, Guangzhou, China.
Shao-Feng ZhanThe First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.
Liu-Liu YangThe First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.
Hong-Fa ZhuangThe First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.
Xiao-Hong LiuThe First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.
Yong JiangShenzhen Hospital of Integrated Traditional Chinese and Western Medicine, Shenzhen, China.ORCID 0000-0002-3609-2280
First Affiliated Hospital of Guangzhou University of Chinese Medicine · CNGuangzhou University of Chinese Medicine · CNShenzhen Pingle Orthopedic Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundChinese medicine Xuebijing (XBJ) has proven to be effective in the treatment of mild coronavirus disease 2019 (COVID-19) cases. But the bioactive compounds and potential mechanisms of XBJ for COVID-19 prevention and treatment are unclear. This study aimed to examine the potential effector mechanisms of XBJ on COVID-19 based on network pharmacology.

methodsWe searched Chinese and international papers to obtain the active ingredients of XBJ. Then, we compiled COVID-19 disease targets from the GeneCards gene database and via literature searches. Next, we used the SwissTargetPrediction database to predict XBJ's effector targets and map them to the abovementioned COVID-19 disease targets in order to obtain potential therapeutic targets of XBJ. Cytoscape software version 3.7.0 was used to construct a "XBJ active-compound-potential-effector target" network and protein-protein interaction (PPI) network, and then to carry out network topology analysis of potential targets. We used the ClueGO and CluePedia plugins in Cytoscape to conduct gene ontology (GO) biological process (BP) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway enrichment analysis of XBJ's effector targets. We used AutoDock vina and PyMOL software for molecular docking.

resultsWe obtained 144 potential COVID-19 effector targets of XBJ. Fourteen of these targets-glyceraldehyde 3-phosphate dehydrogenase (

conclusionThe active ingredients of XBJ regulated different genes, acted on different pathways, and synergistically produced anti-inflammatory and immune-regulatory effects, which fully demonstrated the synergistic effects of different components on multiple targets and pathways. Our study demonstrated that key ingredients and their targets have potential binding activity, the existing studies on the pharmacological mechanisms of XBJ in the treatment of sepsis and severe pneumonia, could explain the effector mechanism of XBJ in COVID-19 treatment, and those provided a preliminary examination of the potential effector mechanism in this disease.

Indexed as

Active ingredientCoronavirus disease 2019Effector mechanismMolecular dockingNetwork pharmacologyXuebijing

Identifiers

PMID33082858
PMCPMC7563914
OpenAlexW3093259931

What OpenQuestion holds

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LicenceCC BY
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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.