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Traditional Medicine Research  2018, Vol. 3 Issue (6): 260-272    DOI: 10.12032/TMR201814086
Modernization of Traditional Medicine     
Recent advances in network pharmacology applications in Chinese herbal medicine
Jian Hao1,*(), Shi-Jun Li1
1 The Fourth Central Hospital Affiliated to Nankai University, Tianjin, China.
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Network pharmacology is a new discipline based on the theory of systems biology and network analysis of biological systems to design the drugs. It comprehensively observes the intervention and influence of drugs on the disease network, and reveals the mystery of multi-molecular drugs synergistically acting on disease. These concepts reflect the ideas of multi-component, multi-target and system regulation, and have many similarities with the research ideas of traditional Chinese medicine, which focuses on syndrome differentiation and treatment, emphasizes the overall understanding of the etiology and pathogenesis. Network pharmacology can be used to predict and identify the target and active component of traditional herbal medicine, to clarify the mechanism of action, to scientifically explain the rules of the prescription, to explore the rules of real-world prescription, to discover new indications and new active compounds, and to study drug relocation, etc. The applications of network pharmacology in traditional herbal medicine were systematically summarized to demonstrate the significant value in these areas.



Key wordsNetwork pharmacology      Applications      Traditional herbal medicine      Multi-molecular drugs      Traditional Chinese medicine     
Published: 04 November 2018
Corresponding Authors: Hao Jian     E-mail: haojian1111520@126.com.
Cite this article:

Jian Hao, Shi-Jun Li. Recent advances in network pharmacology applications in Chinese herbal medicine. Traditional Medicine Research, 2018, 3(6): 260-272. doi: 10.12032/TMR201814086

URL:

https://www.tmrjournals.com/tmr/EN/10.12032/TMR201814086     OR     https://www.tmrjournals.com/tmr/EN/Y2018/V3/I6/260

Figure 1 The main researches of Chinese herb medicine before (A) and after (B)
Figure 2 The main process of network pharmacology in the research of Chinese herb medicine
Type Name Website Function
Database TCMSP [2]
TCMDatabase@Taiwan [3]
ChEMBL [4]
Super Natural II [5]
TCMID [6]
TTD [7]
HIT [8]
STITCH [9]
PDTD [10]
Polysearch [11]
Drugbank [12]
BATMAN [13]
Reaxys [14]
TCMGeneDIT [15]
TCM-Mesh [16]
ChemMapper [17]
PharmMapper [18]
http://lsp.nwu.edu.cn/tcmspsearch.php
http://tcm.cmu.edu.tw/
https://www.ebi.ac.uk/chembl/
http://bioinformatics.charite.de/supernatural
http://bidd.nus.edu.sg/group/TCMsite/Default.aspx
http://bidd.nus.edu.sg/group/cjttd/
http://lifecenter.sgst.cn/hit/
http://stitch.embl.de/
http://www.dddc.ac.cn/pdtd/
http://polysearch.cs.ualberta.ca/
https://www.drugbank.ca/
http://www.tcm.com/tcmdb/title/490377/Batman/
https://www.reaxys.com/
http://tcm.lifescience.ntu.edu.tw/
http://mesh.tcm.microbioinformatics.org/
http://lilab.ecust.edu.cn/chemmapper/
http://lilab.ecust.edu.cn/pharmmapper/
Look for the ingredients
Find and predict the targets
Database GenBank [19]
GAD [20]
Genecard [21]
OMIM [22]
https://www.ncbi.nlm.nih.gov/genbank/
https://geneticassociationdb.nih.gov/
https://www.genecards.org/
http://www.omim.org/
Disease-associated gene
Database DisGeNET [23]
String [24]
BioGRID [25]
http://www.disgenet.org/
https://string-db.org/cgi/input.pl
https://thebiogrid.org/
Interaction of genes
Database HPRD [26]
PDZBase [27]
MINT [28]
PIPs [29]
DIP [30]
HAPPI [31]
STRING [24]
DIPOS [32]
http://www.hprd.org/
https://dl.acm.org/
https://mint.bio.uniroma2.it/
http://www.compbio.dundee.ac.uk/www-pips/
https://dip.doe-mbi.ucla.edu/dip/
http://discovery.informatics.uab.edu/HAPPI
https://string-db.org/cgi/input.pl
http://csb.shu.edu.cn/dipos
Protein-protein interaction
Database Biocarta [33]
KEGG [34]
https://cgap.nci.nih.gov/Pathways/BioCarta_Pathways
https://www.kegg.jp/
Signal path analysis
Saftware DrugCIPHER [35]
Drugable [36]
INVDOCK [37]
Autodock [38]
Drug Discovery [39]
https://github.com/judyboon/drugCIPHER/issues
https://www.drugable.com/

http://autodock.scripps.edu/
Predict the targets
Saftware Cytoscape [40]
Pajek [41]
NAViGaTOR [42]
IPA [43]
NetMiner [44]
NetworkX [45]
Osprey [46]
Gephi [47]
GuESS [48],
UCINET[49],
QuACN [50]
http://www.cytoscape.org/
http://mrvar.fdv.uni-lj.si/pajek/
https://ipa-virtual.software.informer.com/
http://www.netminer.com/
https://networkx.github.io/
https://resawntimberco.com/osprey-software-reed-reclaimed-hemlock/
https://gephi.org/
https://guess.software.informer.com/
http://www.analytictech.com/ucinet/
http://cran.r-project.org/web/packages/QuACN/
Network visualization tools
Table 1 The main databases and tools for traditional Chinese medicine research
Figure 3 The main applications of network pharmacology in the researches of Chinese herb medicine
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[3] Liang-Jun Yang, Dao-Rui Hou, Ya Li, Zhi-Peng Hu, Yong Zhang. A network pharmacology approach to investigate the mechanisms of Si-Jun-Zi decoction in the treatment of gastric precancerous lesions[J]. Traditional Medicine Research, 2018, 3(6): 273-285.
[4] Shang-Jin Song, Ren-Jie Xu, Li-Juan Xiu, Xuan Liu, Xiao-Qiang Yue. Network pharmacology-based approach to investigate the mechanisms of Yiyi Fuzi Baijiang Powder in the treatment of malignant tumors[J]. Traditional Medicine Research, 2018, 3(6): 295-306.
[5] Yang Hu, Dan Chen. Analysis of the action mechanism of Fang Ji Huang Qi decoction in treating rheumatoid arthritis by network pharmacology[J]. Traditional Medicine Research, 2018, 3(6): 286-294.
[6] Yue Ji, Jun-Chen Li, Jing-Yan Meng, Xue-Rou Yan, Jian-ang Li, Qing-Yun Zhao, Kang Yang, Chun- Liu. Study of dual-directional regulatory effect of Banxia (Pinellia ternata) and Huanglian (Coptis chinensis) drug pair on gastrointestinal movement of mice[J]. Traditional Medicine Research, 2018, 3(3): 148-156.
[7] Wen-Qi Huang, Zhu Yang, Dong-Xin Tang, Feng-Xi Long, Li Luo, Bing Yang, Juan Li, Jie Chen. Pharmacological intervention of traditional Chinese medicine for the quality of life in patients with colorectal cancer: a systematic review and meta-analysis[J]. Traditional Medicine Research, 2018, 3(2): 95-105.
[8] Li-Lin Yang, Jie Gao, Hai-Wang Wu, Song-Ping Luo. History of recurrent miscarriage in traditional Chinese medicine literature[J]. Traditional Medicine Research, 2018, 3(2): 62-69.
[9] Tian Ran, Dai Liang, Shang Hong-Cai, Li You-Ping, Bian Zhao-Xiang. How to establish precise proprietary Chinese medicine in post-marketing reappraisal?[J]. Traditional Medicine Research, 2017, 2(4): 155-160.
[10] Zhai Jing-Bo, Li Jiang, Chen Jing. The applications of Bayesian models in real-world studies of traditional Chinese medicine: a primer[J]. Traditional Medicine Research, 2017, 2(2): 88-93.
[11] Yang Xue, Wu Xiong-Zhi. The combination of disease and Zheng (syndrome) on the basic of differentiation of six channels: a new pattern of disease diagnosis and treatment of traditional Chinese medicine[J]. Traditional Medicine Research, 2017, 2(2): 100-104.
[12] Xu Wei, Chai Ni, Cheng Yue-Lei, Yang Qiong, Zhu Hui-Rong. Analysis on the principles of differentiation and prescription of traditional Chinese medicine in the treatment of cancerous fever[J]. Traditional Medicine Research, 2017, 2(1): 41-50.
[13] Shang Hong-Cai, Wu Xiong-Zhi, Qiu Rui-Jin, Wang Ya-Han, Wang Yong-Yan. Traditional Chinese medicine should not be ignored during the development of precision medicine with Chinese characteristics[J]. Traditional Medicine Research, 2016, 1(3): 105-114.
[14] Liu Li-Juan, Zhou Chao, Song Fu-Cheng, Zhang Sen-Sen, Teng Wen-Jing, Zhuang Jing, Sun Chang-Gang, Si Hong-Zong. Molecular docking study on the molecular mechanism of rhaponticin for treatment of chronic myelocytic leukemia[J]. Traditional Medicine Research, 2016, 1(3): 122-127.
[15] Yang Dao-Zheng, Luan Xin-Yuan, Wang Shu-Bin. Epigenetic regulations of hematopoietic stem cells ageing and the regulation of traditional Chinese medicine[J]. Traditional Medicine Research, 2016, 1(2): 75-82.