Network pharmacology-based study of the active constituents of Chinese medicinal formulae for antitumor mechanism

Bao-Yue Zhang; Yi-Fu Zheng; Xiao-Cong Pang; Zhe Wang; Hong Ding; Ai-Lin Liu

doi:10.4103/wjtcm.wjtcm_6_18

Users Online: 134

ORIGINAL ARTICLE

Year : 2018 | Volume : 4 | Issue : 2 | Page : 43-53

Network pharmacology-based study of the active constituents of Chinese medicinal formulae for antitumor mechanism

Bao-Yue Zhang¹, Yi-Fu Zheng², Xiao-Cong Pang¹, Zhe Wang¹, Hong Ding², Ai-Lin Liu³
¹ Institute of Materia Medica, Chinese Academy of Medical Sciences And Peking Union Medical College, Beijing 100050, China
² School of Pharmaceutical Sciences, Wuhan University, Wuhan 430072, China
³ Institute of Materia Medica, Chinese Academy of Medical Sciences And Peking Union Medical College; Beijing Key Laboratory of Drug Target and Screening Research; State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Beijing 100050, China

Correspondence Address:
Ai-Lin Liu
Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050
China

Source of Support: None, Conflict of Interest: None

DOI: 10.4103/wjtcm.wjtcm_6_18

Objective: To investigate the network pharmacology of anti-tumor Chinese medicinal formulae and explain the synergistic mechanism of various active ingredients of Chinese medicinal formulae. Methods: We collected the anti-tumor Chinese medicinal formulae and chose several single herbs with the top frequency for further study. The chemical constituents of these herbs were downloaded from databases CNPC and Traditional Chinese Medicine Systems Pharmacology and were analyzed to set up the anti-tumor material basis. The genes regulated by these constituents were retrieved in Traditional Chinese Medicine integrated database and Comparative Toxicogenomics database. Results: We collected 65 anti-tumor Chinese medicinal formulae, and 4 single herbs were selected, including Licorice, Radix astragali, Panax ginseng, and Radix scutellariae, which consist of 172, 70, 293, and 92 known constituents, respectively. The constituent–gene network, protein–protein interaction network, gene–pathway enrichment network, and gene–disease network were constructed. Moreover, molecular docking was employed to clarify the interactions between active constituents and key drug targets (PTG2, epidermal growth factor receptor, peroxisome proliferator-activated receptor gamma, estrogen receptor 1, mammalian target of rapamycin, AKT1, mitogen-activated protein kinase 1 [MAPK1], peroxisome proliferator-activated receptor alpha, and MAPK8). Most of the constituents could act on multiple targets, whose structures mainly belong to alkaloids, flavonoids, and their glycosides, organic acids, or dianthrone, and their representative chemical constituents include narcissus glycosides, rutin, dauricine, scutellarin, baicalin, isoschaftoside, and leucovorin. Conclusion: The network mechanism of the effective constituents from traditional Chinese medicines (TCMs) for anti-tumor therapy was partially uncovered by using statistical methods, network pharmacology methods, and molecular docking methods. This study will provide important information for new drug design with multiple targets for anti-tumor therapy.

[FULL TEXT] [PDF]*