Network pharmacology-based study on the mechanism of action for herbal medicines in Alzheimer treatment

Fang, Jiansong; Wang, Ling; Wu, Tian Shung; Yang, Cong; Gao, Li; Cai, Hao; Liu, Junhui; Fang, Shuhuan; Chen, Yunbo; Tan, Wen; Wang, Qi

doi:10.1016/j.jep.2016.11.034

Cited by 100 publications

(63 citation statements)

References 48 publications

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“…The network pharmacology "disease-gene-target-drug" research model is very consistent with the synergistic effect of the TCM "multicomponent, multichannel, multitarget" model, which more effectively reveals the relationship between TCM compound preparation and disease [16]. As a new field, network pharmacology provides a deeper insight into the basic mechanisms of TCM theory by using systems biology, highly integrated data analysis strategies and visualizations of the interpretations [17]. TCM network pharmacology has the role of discovering biologically active compounds and elucidating the mechanisms of action of TCM formulas, with the significance of accelerating the discovery of TCM and improving current drug discovery strategies [18].…”

Section: Introductionmentioning

confidence: 57%

Study on the mechanisms of compound Kushen injection for the treatment of gastric cancer based on network pharmacology

Zhou

Zhu

et al. 2020

BMC Complement Med Ther

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Background: As an effective prescription for gastric cancer (GC), Compound Kushen Injection (CKI) has been widely used even though few molecular mechanism analyses have been carried out. Methods: In this study, we identified 16 active ingredients and 60 GC target proteins. Then, we established a compound-predicted target network and a GC target protein-protein interaction (PPI) network by Cytoscape 3.5.1 and systematically analyzed the potential targets of CKI for the treatment of GC. Finally, molecular docking was applied to verify the key targets. In addition, we analyzed the mechanism of action of the predicted targets by Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses. Results: The results showed that the potential targets, including CCND1, PIK3CA, AKT1, MAPK1, ERBB2, and MMP2, are the therapeutic targets of CKI for the treatment of GC. Functional enrichment analysis indicated that CKI has a therapeutic effect on GC by synergistically regulating some biological pathways, such as the cell cycle, pathways in cancer, the PI3K-AKT signaling pathway, the mTOR signaling pathway, and the FoxO signaling pathway. Moreover, molecular docking simulation indicated that the compounds had good binding activity to PIK3CA, AKT1, MAPK1, ERBB2, and MMP2 in vivo. Conclusion: This research partially highlighted the molecular mechanism of CKI for the treatment of GC, which has great potential in the identification of the effective compounds in CKI and biomarkers to treat GC.

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Section: Introductionmentioning

confidence: 57%

Study on the mechanisms of compound Kushen injection for the treatment of gastric cancer based on network pharmacology

Zhou

Zhu

et al. 2020

BMC Complement Med Ther

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“…Systems pharmacology is a cutting-edge methodology that combines computational and experimental tools toward discovering novel therapeutic agents and understanding the therapeutic mechanisms of complex diseases. (Fang et al, 2017a;Fang et al, 2019). In recent years, systems pharmacology-based approaches have provided new insights into elucidating the mechanisms of TCM in the treatment of diseases such as cardiovascular diseases and AD (Zhou and Wang, 2014;Fang et al, 2017a;Cai et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

“…(Fang et al, 2017a;Fang et al, 2019). In recent years, systems pharmacology-based approaches have provided new insights into elucidating the mechanisms of TCM in the treatment of diseases such as cardiovascular diseases and AD (Zhou and Wang, 2014;Fang et al, 2017a;Cai et al, 2018). In this study, we employed a systems pharmacology approach to identify potential compounds, candidate targets, and therapeutic mechanisms of KXS against AD disease from a holistic prospect (Figure 1).…”

Section: Introductionmentioning

confidence: 99%

Systems Pharmacology Approach to Investigate the Mechanism of Kai-Xin-San in Alzheimer’s Disease

Luo

Liao

et al. 2020

Front. Pharmacol.

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Alzheimer's disease (AD) is a complex neurodegenerative disease characterized by cognitive dysfunction. Kai-Xin-San (KXS) is a traditional Chinese medicine (TCM) formula that has been used to treat AD patients for over a thousand years in China. However, the therapeutic mechanisms of KXS for treating AD have not been fully explored. Herein, we used a comprehensive network pharmacology approach to investigate the mechanism of action of KXS in the treatment of AD. This approach consists of construction of multiple networks and Gene Ontology enrichment and pathway analyses. Furthermore, animal experiments were performed to validate the predicted molecular mechanisms obtained from the systems pharmacology-based analysis. As a result, 50 chemicals in KXS and 39 AD-associated proteins were identified as major active compounds and targets, respectively. The therapeutic mechanisms of KXS in treating AD were primarily related to the regulation of four pathology modules, including amyloid beta metabolism, tau protein hyperphosphorylation process, cholinergic dysfunction, and inflammation. In scopolamine-induced cognitive dysfunction mice, we validated the anti-inflammatory effects of KXS on AD by determining the levels of inflammation cytokines including interleukin (IL)-6, IL-1b, and tumor necrosis factor (TNF)-a. We also found cholinergic system dysfunction amelioration of KXS is correlated with upregulation of the cholinergic receptor CHRNB2. In conclusion, our work proposes a comprehensive systems pharmacology approach to explore the underlying therapeutic mechanism of KXS for the treatment of AD.

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“…The network pharmacology method has been increasingly engaged in TCM researches, due to its focuses on the multi-component and multi-target features of TCM 44, 45 . In this study, involving compounds was complicated, and pathways were numerous.…”

Section: Discussionmentioning

confidence: 99%

How impaired efficacy happened between Gancao and Yuanhua: Compounds, targets and pathways

Guo

Zhu

et al. 2017

Sci Rep

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As recorded in Traditional Chinese Medicine (TCM) theory, Gancao (Glycyrrhizae Radix et Rhizoma) could weaken the pharmacological effect or increase the toxicity of Yuanhua (Genkwa Flos). However, the theory has been suspected due to lack of evidence. Here, we investigate whether Gancao could weaken Yuanhua’s diuretic effect, if so, which chemicals and which targets may be involved. Results showed that Yuanhua exerted diuretic effect through down-regulating renal AQP 2, without electrolyte disturbances such as K+ loss which has been observed as side-effect of most diuretics. Gancao had no diuretic effect, but could impair Yuanhua’s diuretic effect through up-regulating renal AQP 2. Glycyrrhetinic acid (GRA) in Gancao could up-regulate AQP 2 and counteract the AQP 2 regulation effect of Yuanhuacine (YHC) and Ginkwanin (GKW) in Yuanhua. Network pharmacology method suggested that YHC, GKW and GRA could bind to MEK1/FGFR1 protein and influence ERK-MAPK pathway, which was verified by Western blotting. This study supports TCM theory and reminds that more attention should be paid to the safety and efficacy problems induced by improper combination between herbs. Moreover, we suggested that promising diuretics with less side effects can be developed from Chinese Medicines such as Yuanhua.

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Network pharmacology-based study on the mechanism of action for herbal medicines in Alzheimer treatment

Cited by 100 publications

References 48 publications

Study on the mechanisms of compound Kushen injection for the treatment of gastric cancer based on network pharmacology

Study on the mechanisms of compound Kushen injection for the treatment of gastric cancer based on network pharmacology

Systems Pharmacology Approach to Investigate the Mechanism of Kai-Xin-San in Alzheimer’s Disease

How impaired efficacy happened between Gancao and Yuanhua: Compounds, targets and pathways

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