Evidence map›Paper›PMID 37957903›Full record

ArticleCombinatorial chemistry & high throughput screening2024

Network Pharmacology and Experimental Validation of Qingwen Baidu Decoction Therapeutic Potential in COVID-19-related Lung Injury.

Ju Yang, Zhao Zhang, Honghong Liu, Jiawei Wang, Shuying Xie, Pengyan Li, Jianxia Wen, Shizhang Wei, Ruisheng Li, Xiao Ma and 1 more

Abstract read
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In one paragraph

Article in Combinatorial chemistry & high throughput screening, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 76% 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

1 citing paper in PubMed, 0 citations in OpenAlex.

  1. 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

11 authors at 2 institutions in 1 country.

Ju YangCollege of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu, 611137, China.ORCID 0000-0001-9521-2353
Zhao ZhangCollege of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu, 611137, China.
Honghong LiuDepartment of Pharmacy, 302 Military Hospital of China, Beijing, 100039, China.
Jiawei WangCollege of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu, 611137, China.
Shuying XieDepartment of Pharmacy, 302 Military Hospital of China, Beijing, 100039, China.
Pengyan LiDepartment of Pharmacy, 302 Military Hospital of China, Beijing, 100039, China.
Jianxia WenCollege of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu, 611137, China.
Shizhang WeiDepartment of Pharmacy, 302 Military Hospital of China, Beijing, 100039, China.
Ruisheng LiDepartment of Pharmacy, 302 Military Hospital of China, Beijing, 100039, China.
Xiao MaCollege of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu, 611137, China.
Yanling ZhaoDepartment of Pharmacy, 302 Military Hospital of China, Beijing, 100039, China.
302 Military Hospital of China · CNChengdu University of Traditional Chinese Medicine · CN

Funding

China Medical Education Association 2020 major scientific problems and medical technical problems 2020KTZ002National Key R&D Program of China 2018YFC1704504
6 · The paper itself

Abstract

background and purposeCoronavirus disease 2019 (COVID-19) is a lifethreatening disease worldwide due to its high infection and serious outcomes resulting from acute lung injury. Qingwen Baidu decoction (QBD), a well-known herbal prescription, has shown significant efficacy in patients with Coronavirus disease 2019. Hence, this study aims to uncover the molecular mechanism of QBD in treating COVID-19-related lung injury.

methodsTraditional Chinese Medicine Systems Pharmacology database (TCMSP), DrugBanks database, and Chinese Knowledge Infrastructure Project (CNKI) were used to retrieve the active ingredients of QBD. Drug and disease targets were collected using UniProt and Online Mendelian Inheritance in Man databases (OMIM). The core targets of QBD for pneumonia were analyzed by the Protein-Protein Interaction Network (PPI), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) to reveal the underlying molecular mechanisms. The analysis of key targets using molecular docking and animal experiments was also validated.

resultsA compound-direct-acting target network mainly containing 171 compounds and 110 corresponding direct targets was constructed. The key targets included STAT3, c-JUN, TNF-α, MAPK3, MAPK1, FOS, PPARG, MAPK8, IFNG, NFκB1, etc. Moreover, 117 signaling pathways mainly involved in cytokine storm, inflammatory response, immune stress, oxidative stress and glucose metabolism were found by KEGG. The molecular docking results showed that the quercetin, alanine, and kaempferol in QBD demonstrated the strongest affinity to STAT3, c- JUN, and TNF-α. Experimental results displayed that QBD could effectively reduce the pathological damage to lung tissue by LPS and significantly alleviate the expression levels of the three key targets, thus playing a potential therapeutic role in COVID-19.

conclusionQBD might be a promising therapeutic agent for COVID-19 via ameliorating STAT3-related signals.

Indexed as

COVID-19COVID-19 Drug TreatmentDrugs, Chinese HerbalMolecular Docking SimulationNetwork PharmacologySARS-CoV-2Acute Lung InjuryAnimalsHumansKaempferolsLung InjuryMedicine, Chinese TraditionalProtein Interaction MapsRatsSTAT3 Transcription FactorDrugs, Chinese HerbalKaempferolsSTAT3 Transcription Factoracute lung injuryCOVID-19decoctionmolecular dockingQingwen Baidu. network pharmacologyWHO.

Identifiers

PMID37957903
OpenAlexW4388670677

What Socratic holds

Textmetadata
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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 Socratic graph.