Evidence map›Paper›PMID 35249866›Full record

ArticleNan fang yi ke da xue xue bao = Journal of Southern Medical University2022

[Identification of traditional Chinese drugs containing active ingredients for treating myocardial infarction and analysis of their therapeutic mechanisms by network pharmacology and molecular docking].

S Zhao, K Liu, J Duan, X Tao, W Li, Y Bai, P Wei, M Xi, H Yang

Open access · greenAbstract read
In one paragraph

Article in Nan fang yi ke da xue xue bao = Journal of Southern Medical University, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.5field-weighted citation impact, top 36% 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

4 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. The bioactivities of sclareol: A mini review.Frontiers in pharmacology · 2022
    Review
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

9 authors at 1 institution in 1 country.

S ZhaoSchool of Pharmacy, Shaanxi University of Chinese Medicine, Xianyang 712046, China.
K LiuSchool of Pharmacy, Shaanxi University of Chinese Medicine, Xianyang 712046, China.
J DuanInstitute of Medicine, Northwestern Polytechnical University, Xi'an 710072, China.
X TaoSchool of Pharmacy, Shaanxi University of Chinese Medicine, Xianyang 712046, China.
W LiSchool of Pharmacy, Shaanxi University of Chinese Medicine, Xianyang 712046, China.
Y BaiNational Institute of Drug Clinical Trials, Second Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang 712021, China.
P WeiNational Institute of Drug Clinical Trials, Second Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang 712021, China.
M XiNational Institute of Drug Clinical Trials, Second Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang 712021, China.
H YangClinical Medical Research Center, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang 712099, China.
Shaanxi University of Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo identify traditional Chinese drugs that contain active ingredients for treatment of myocardial infarction (MI) and explore their therapeutic mechanisms using network pharmacology and molecular docking technology.

methodsThe TCMSP database was used for screening the traditional Chinese drugs containing active ingredients for treating MI, and the related targets of MI and the candidate drugs were obtained from Genecards, OMIM, PharmGkb and PharmMapper databases. The common target network of the drug targets and disease targets was established using Venny2.1.0 software. GO and KEGG signal pathway enrichment analysis of the common targets was performed, and the protein-protein interaction (PPI) network was constructed for the targets. The targets in the PPI network were analyzed to identify the key targets, for which GO and KEGG pathway enrichment analyses were performed. Molecular docking was performed for the candidate ingredients and the key targets, and a total score ≥6 was used as the criteria for screening the therapeutic ingredients and their docking binding with key targets was verified. A human umbilical vein endothelial cell (HUVEC) model of oxygen-glucose deprivation (OGD) was used to validate the candidate ingredients and the key therapeutic targets for MI by Western blotting.

resultsOur analysis identified Salvia miltiorrhiza and Dalbergiae odoriferae as the candidate drugs rich in active ingredients for treatment of MI. These ingredients involved 16 key therapeutic targets for MI, which participated in such biological processes as inflammatory response, angiogenesis, energy metabolism and oxidative stress and the pathways including HIF-1, VEGF, and TNF pathways. Sclareol and PTGS2 in Salvia miltiorrhiza and formononetin and KDR in Dalbergiae odoriferae all had high docking total scores. Western blotting showed that at medium and high doses, sclareol significantly inhibited PTGS2 expression and formononetin promoted KDR expressions in the cell models in a dose-dependent manner (

conclusionBoth Salvia miltiorrhiza and Dalbergiae odoriferae have good therapeutic effects on MI. Sclareol in Salvia miltiorrhiza and formononetin in Dalbergiae odoriferae regulate the expressions of KDR and PTGS2, respectively, to modulate the inflammatory response, angiogenesis, oxidative stress and energy metabolism and thus produce myocardial protective effects.

Indexed as

Drugs, Chinese HerbalMyocardial InfarctionChinaHumansMedicine, Chinese TraditionalMolecular Docking SimulationNetwork PharmacologyDrugs, Chinese Herbalmolecular dockingmyocardial infarctionnetwork pharmacologypharmacodynamic substancestraditional Chinese drugs

Identifiers

PMID35249866
PMCPMC8901397
OpenAlexW4220733202

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.