Evidence map›Paper›PMID 31040644›Full record

ArticleDrug design, development and therapy2019

Systematic elucidation of the mechanism of geraniol via network pharmacology.

Yun-Fei Zhang, Yue Huang, Yi-Hua Ni, Zheng-Min Xu

Abstract read
In one paragraph

Article in Drug design, development and therapy, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.

0numbers the graph read from it
0cells of the map it votes in
43citing 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

43 citing papers in PubMed.

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  15. Exploring potential pharmacological mechanisms ofAnnals of medicine and surgery (2012) · 2023
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  18. World journal of diabetes · 2022
    Article
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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

4 authors.

Yun-Fei ZhangDepartment of Otolaryngology-Head and Neck Surgery, Children's Hospital of Fudan University, Shanghai, People's Republic of China, xuzhengminsh@126.com.
Yue HuangDepartment of Otolaryngology-Head and Neck Surgery, Children's Hospital of Fudan University, Shanghai, People's Republic of China, xuzhengminsh@126.com.
Yi-Hua NiDepartment of Otolaryngology-Head and Neck Surgery, Children's Hospital of Fudan University, Shanghai, People's Republic of China, xuzhengminsh@126.com.
Zheng-Min XuDepartment of Otolaryngology-Head and Neck Surgery, Children's Hospital of Fudan University, Shanghai, People's Republic of China, xuzhengminsh@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGeraniol is an acyclic monoterpene alcohol, which is extracted from the ethereal oils of aromatic plants. A systematic analysis of its mechanism of action has not yet been carried out.

methodsIn this study, the druggability of geraniol was assessed via Traditional Chinese Medicine Systems Pharmacology Database (TCMSP), and the potential targets of geraniol were identified using the Comparative Toxicogenomics Database (CTD). Additionally, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed using WebGestalt. Drug-target-pathway networks were constructed using Cytoscape to give a visual view.

resultsOur findings showed that geraniol has superb druggability with 38 putative identified target genes. GO, KEGG, and network analyses revealed that these targets were associated with cancer, inflammatory immunoreactions, and other physiological processes.

conclusionGeraniol is predicted to target multiple proteins and pathways that shape a network which can exert systematic pharmacological effects.

Indexed as

Databases, PharmaceuticalAcyclic MonoterpenesDrugs, Chinese HerbalHumansInflammationMedicine, Chinese TraditionalMolecular StructureNeoplasmsTerpenesAcyclic MonoterpenesDrugs, Chinese HerbalgeraniolTerpenesdruggabilityenrichment analysisgeraniolnetwork pharmacologytarget prediction

Identifiers

PMID31040644
PMCPMC6455000

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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.