Evidence map›Paper›PMID 34567221›Full record

ArticleEvidence-based complementary and alternative medicine : eCAM2021

Idebenone-Activating Autophagic Degradation of

Pei Kun He, Yu Yuan Gao, Feng-Juan Lyu, Jia Ning Chen, Yu Hu Zhang, Kun Nie, Qing Xi Zhang, Rui Huang, Qing Rui Duan, Man Li Guo and 5 more

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Evidence-based complementary and alternative medicine : eCAM, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.9field-weighted citation impact, top 23% 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

6 citing papers in PubMed, 11 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Nutraceuticals as Modulators of Autophagy: Relevance in Parkinson's Disease.International journal of molecular sciences · 2022
    Review
  6. 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

15 authors at 2 institutions in 1 country.

Pei Kun He *School of Medicine, South China University of Technology, Guangzhou 510006, China.ORCID https://orcid.org/0000-0002-4732-7137
Yu Yuan Gao *School of Medicine, South China University of Technology, Guangzhou 510006, China.
Feng-Juan LyuSchool of Medicine, South China University of Technology, Guangzhou 510006, China.
Jia Ning ChenSchool of Medicine, South China University of Technology, Guangzhou 510006, China.
Yu Hu ZhangDepartment of Neurology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangdong Neuroscience Institute, No. 106 Zhongshan Second Road, Guangzhou 510080, China.
Kun NieDepartment of Neurology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangdong Neuroscience Institute, No. 106 Zhongshan Second Road, Guangzhou 510080, China.
Qing Xi ZhangDepartment of Neurology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangdong Neuroscience Institute, No. 106 Zhongshan Second Road, Guangzhou 510080, China.
Rui HuangSchool of Medicine, South China University of Technology, Guangzhou 510006, China.
Qing Rui DuanSchool of Medicine, South China University of Technology, Guangzhou 510006, China.
Man Li GuoDepartment of Neurology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangdong Neuroscience Institute, No. 106 Zhongshan Second Road, Guangzhou 510080, China.
Zhi Hua LiuSchool of Medicine, South China University of Technology, Guangzhou 510006, China.
He Ling HuangSchool of Medicine, South China University of Technology, Guangzhou 510006, China.
Gui Xian MaDepartment of Neurology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangdong Neuroscience Institute, No. 106 Zhongshan Second Road, Guangzhou 510080, China.
Li Juan WangSchool of Medicine, South China University of Technology, Guangzhou 510006, China.ORCID https://orcid.org/0000-0003-1727-2670
Li Min WangSchool of Medicine, South China University of Technology, Guangzhou 510006, China.ORCID https://orcid.org/0000-0001-6584-8617
Guangdong Academy of Medical Sciences · CNSouth China University of Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundParkinson's disease (PD) is the second most common neurodegenerative disease worldwide, which currently lacks disease-modifying therapy to slow down its progression. Idebenone, a coenzyme Q10 (CQ10) analogue, is a well-known antioxidant and has been used to treat neurological disorders. However, the mechanism of Idebenone on PD has not been fully elucidated. This study aims to predict the potential targets of Idebenone and explore its therapeutic mechanism against PD.

methodWe obtained potential therapeutic targets through database prediction, followed by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. Next, we constructed and analyzed a protein-protein interaction network (PPI) and a drug-target-pathway-disease network. A molecular docking test was conducted to identify the interactions between Idebenone and potential targets. Lastly, a PD cell line of SH-SY5Y overexpressing mutant

resultA total of 87 targets were identified based on network pharmacology. The enrichment analysis highlighted manipulation of MAP kinase activity and the PI3K-AKT signaling pathway as potential pharmacological targets for Idebenone against PD. Additionally, molecular docking showed that AKT and MAPK could bind tightly with Idebenone. In the cell model of PD, Idebenone activated autophagy and promoted

conclusionThis study demonstrated that Idebenone exerts its anti-PD effects by enhancing autophagy and clearance of

Identifiers

PMID34567221
PMCPMC8463184
OpenAlexW3199090301

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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.