ArticleEvidence-based complementary and alternative medicine : eCAM2021
Network Pharmacology-Based Approach to Investigate the Molecular Targets of Rhubarb for Treating Cancer.
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 12 papers.
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Who cites it
12 citing papers in PubMed, 19 citations in OpenAlex.
- Pan-Cancer Bioinformatics-Guided Evaluation of San-Huang-Xie-Xin-Tang Identifies Kidney Renal Clear Cell Carcinoma as a Potentially Responsive Cancer Type.Pharmaceuticals (Basel, Switzerland) · 2026Article
- Network pharmacology of olive stem extract, UPLC-HR-QTOF-MS profiling and antiviral activities aligned with UN sustainable development goals.Scientific reports · 2025Article
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- Exploring the Mechanism of Salvianolic Acid B against Myocardial Ischemia-Reperfusion Injury Based on Network Pharmacology.Pharmaceuticals (Basel, Switzerland) · 2024Article
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- The foundation of the rhubarb industry economy: investigating metabolites disparities of rhubarb between varieties and growing environments on the Tibetan plate.Frontiers in pharmacology · 2024Article
- Network pharmacology: a bright guiding light on the way to explore the personalized precise medication of traditional Chinese medicine.Chinese medicine · 2023Review
- Molecular mechanism of Rhubarb in the treatment of non-small cell lung cancer based on network pharmacology and molecular docking technology.Molecular diversity · 2023Article
- Combination of HPLC-Q-TOF-MS/MS, Network Pharmacology, and Molecular Docking to Reveal the Mechanism of Apple Pollen in the Treatment of Type 2 Diabetes Mellitus.Evidence-based complementary and alternative medicine : eCAM · 2022Article
- Potential Molecular Mechanisms of Ephedra Herb in the Treatment of Nephrotic Syndrome Based on Network Pharmacology and Molecular Docking.BioMed research international · 2022Article
- Molecular Mechanism ofEvidence-based complementary and alternative medicine : eCAM · 2022Article
- Network Pharmacology-Based Study on the Mechanism of Aloe Vera for Treating Cancer.Evidence-based complementary and alternative medicine : eCAM · 2021Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAs a traditional Chinese medicine, rhubarb (also named Dahuang) is used to treat various diseases.
objectiveTo explore the possible antitumor mechanism of rhubarb by using network pharmacology and molecular docking in this study.
methodsBioactive ingredients and related targets of rhubarb were obtained from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. And the gene names corresponding to the proteins were found in the UniProt database. Then, the tumor-related targets were screened out from GeneCards and OMIM databases. Key antitumor targets of rhubarb were acquired by overlapping the above targets via the Venn diagram. The antitumor targets network of rhubarb active components was constructed by using Cytoscape 3.6.0 software. The protein interactions network was constructed using the STRING database. The GO and KEGG pathways involved in the targets were analyzed by using the DAVID database. Autodock Vina software was used to verify the molecular docking of rhubarb components and key targets.
resultsThrough screening and analysis, 10 active ingredients and 58 antitumor prediction targets were obtained and constructed a compound-target network. The targets such as CASP3, JUN, MYC, TNF, and PTGS2 may play a crucial role. These targets are involved in cancer pathway, calcium signaling pathway, cell apoptosis, small-cell lung cancer pathway, p53 signaling pathway, and TNF signaling pathway. The docking results indicated that the rhein binding with the CASP3 showed the highest binding energy.
conclusionBased on the network pharmacology, the characteristics of multicomponent, multitarget, and multipathway of rhubarb were discussed, which provided a scientific basis for explaining the mechanism in treating cancer and new ideas for further research.
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Registered trials
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.