Evidence map›Paper›PMID 30108199›Full record

ArticleMedical science monitor : international medical journal of experimental and clinical research2018

Deciphering Key Pharmacological Pathways of Qingdai Acting on Chronic Myeloid Leukemia Using a Network Pharmacology-Based Strategy.

Huayao Li, Lijuan Liu, Cun Liu, Jing Zhuang, Chao Zhou, Jing Yang, Chundi Gao, Gongxi Liu, Qingliang Lv, Changgang Sun

Abstract read
In one paragraph

Article in Medical science monitor : international medical journal of experimental and clinical research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Proangiogenesis effects of compound danshen dripping pills in zebrafish.BMC complementary medicine and therapies · 2022
    Article
  6. Article
  7. Optimization of Extraction of Bioactive Compounds fromMolecules (Basel, Switzerland) · 2021
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. 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

10 authors.

Huayao LiCollege of First Clinical Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China (mainland).
Lijuan LiuCollege of First Clinical Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China (mainland).
Cun LiuCollege of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China (mainland).
Jing ZhuangDepartmen of Oncology, Weifang Traditional Chinese Hospital, Weifang, Shandong, China (mainland).
Chao ZhouDepartmen of Oncology, Weifang Traditional Chinese Hospital, Weifang, Shandong, China (mainland).
Jing YangDepartmen of Oncology, Weifang Traditional Chinese Hospital, Weifang, Shandong, China (mainland).
Chundi GaoCollege of First Clinical Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China (mainland).
Gongxi LiuDepartmen of Oncology, Weifang Traditional Chinese Hospital, Weifang, Shandong, China (mainland).
Qingliang LvDepartment of Interventional Radiology, Weifang People's Hospital, Weifang, Shandong, China (mainland).
Changgang SunDepartment of Oncology, Affilited Hospital of Weifang Medical University, Weifang, Shandong, China (mainland).

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Qingdai, a traditional Chinese medicine (TCM) used for the treatment of chronic myeloid leukemia (CML) with good efficacy, has been used in China for decades. However, due to the complexity of traditional Chinese medicinal compounds, the pharmacological mechanism of Qingdai needs further research. In this study, we investigated the pharmacological mechanisms of Qingdai in the treatment of CML using network pharmacology approaches. First, components in Qingdai that were selected by pharmacokinetic profiles and biological activity predicted putative targets based on a combination of 2D and 3D similarity measures with known ligands. Then, an interaction network of Qingdai putative targets and known therapeutic targets for the treatment of chronic myeloid leukemia was constructed. By calculating the 4 topological features (degree, betweenness, closeness, and coreness) of each node in the network, we identified the candidate Qingdai targets according to their network topological importance. The composite compounds of Qingdai and the corresponding candidate major targets were further validated by a molecular docking simulation. Seven components in Qingdai were selected and 32 candidate Qingdai targets were identified; these were more frequently involved in cytokine-cytokine receptor interaction, cell cycle, p53 signaling pathway, MAPK signaling pathway, and immune system-related pathways, which all play important roles in the progression of CML. Finally, the molecular docking simulation showed that 23 pairs of chemical components and candidate Qingdai targets had effective binding. This network-based pharmacology study suggests that Qingdai acts through the regulation of candidate targets to interfere with CML and thus regulates the occurrence and development of CML.

Indexed as

Drugs, Chinese HerbalGene OntologyHumansLeukemia, Myelogenous, Chronic, BCR-ABL PositiveMolecular Docking SimulationReproducibility of ResultsSignal TransductionDrugs, Chinese HerbalQingdai compound

Identifiers

PMID30108199
PMCPMC6106618

What OpenQuestion holds

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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 OpenQuestion graph.