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Network pharmacology

Network pharmacology emphasizes the multi-channel regulation of signal pathway to improve the therapeutic effect of drugs and reduce the toxic and side effects, so as to improve the success rate of clinical trials of new drugs and save drug research and development costs
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Systematic pharmacology analysis of Sodium 8-(((carboxymethyl)amino)methyl)-4’,7-bishydroxy-isoflavone-3’-sulfonate
Ze-Ping Luo, Li-Wei Pan, Hai-Lin Chen, Jun-Yu Lu
7Drug Combination Therapy    2019, 1 (4): 186-198.   https://doi.org/10.12032/DCT201904005
Abstract PDF (1125KB)  
The purpose of this study is to use the newly synthesized molecule Sodium 8-(((carboxymethyl)amino)methyl)-4’,7-bishydroxy-isoflavone-3’-sulfonate (M) as a research object, the pharmacological mechanism of the molecule was analyzed by using a series of Systematic pharmacology methods. The results show that the M molecule has a higher drug-like DL value of 0.59 and better molecular property parameters, namely Hdon=4, Hacc=10 and AlogP=0.94; A total of 11 M molecules related targets, namely F2, ESR1, AR, F10, CA2, DPP4, CCNA2, PRSS1, CDK2, GSK3B and PTPN1; A total of 140 diseases are associated with M molecule targets, and these diseases are mainly related to cancer and cardiovascular diseases; A total of 52 pathways involve the pharmacological mechanisms of M molecules, which are mainly related to cancer and other related diseases; GO-enriched analysis showed that these targets are closely related to the regulation of peptidase activity and biological processes such as blood coagulation and hemostasis. This article clearly demonstrated the pharmacological mechanism of M molecule, which provides references for exploring the pharmacological mechanism of new compounds.
Research trends and development status of TCM network pharmacology: a bibliometric study
Yu-Zhi Shang, Qing-Huai Zhang, Qiu-Xia Chen, Xiu-Song Tang, Yu-Zhou Pang, Gang Fang
7Drug Combination Therapy    2019, 1 (3): 102-116.   https://doi.org/10.12032/DCT201903002
Abstract PDF (818KB)  

Objective: To analyze the research status, development context and trend of traditional Chinese medicine (TCM) network pharmacology from birth to the present. Methods: In this study, bibliographic data and references of articles on TCM network pharmacology were collected from Web of Science Core Collection (WoSCC), and software including CiteSpace, VOSviewer and Microsoft Excel were applied for the bibliometric analysis of periodicals and the quantity of literature, and for the construction and analysis of the co-occurrence network of countries, journals, research institutes and authors, clusters of co-cited references, and time distribution network of keywords. Results: 249 articles were included in this study. The time span was from 2011 to 2018, and the annual volume of publications showed an increasing trend year by year. The 77 journals contain relevant literature, and the average impact factor of the journal is 3.215. Chinese Journal of Natural Medicines, Scientific Reports, PLoS One have high influence in the field of TCM network pharmacology. Universities and research institutes including China Academy of Chinese Medical Science and Northwest Agriculture & Forestry University are the major forces in this field. Wang Yonghua and Li Shao are authors with high influence in this field, with a considerable number of relevant documents and citations. According to the clustering results of co-cited references, research topics can be classified into 13 development contexts such as “compound danshen formula”, “computational tool”, and “new multi-compound drug discovery”. Hotspots of TCM network pharmacology include “drug discovery”, “mechanism” and “cardiovascular disease”, and relevant research methods and research contents including drugs and diseases tend to be constantly enriched. Conclusion: This study comprehensively demonstrates the research status, development context and trends of TCM network pharmacology, and provides a scientific reference for TCM network pharmacology researchers.

Dissecting the underlying pharmaceutical mechanism of traditional Chinese medicine Wenxin Keli acting on atrial fibrillation through network pharmacology
Xian-Jun Wu, Xin-Bin Zhou, Chen Chen, Wei Mao
7Drug Combination Therapy    2019, 1 (3): 117-133.   https://doi.org/10.12032/DCT201903003
Abstract PDF (1072KB)  

As a well-known Chinese medicine prescription, Wenxin Keli (WXKL) has been widely used in the treatment of many arrhythmias including atrial fibrillation and has achieved significant clinical effects, but the specific mechanism of its treatment of atrial fibrillation remains unclear. This study used a network pharmacology approach to reveal the potential molecular mechanisms of WXKL in the treatment of atrial fibrillation. It involves oral bioavailability screening of ingredients, drug-likeness evaluation, compound target fishing, H-C-T network and C-T-P network construction and analysis. Through the network pharmacology-based research strategy, the complex system of WXKL was analyzed. It was found that 14 representative compounds of WXKL, 30 protein targets and 12 related signaling pathways help us systematically understand the underlying mechanism of WXKL's anti-atrial fibrillation effects.

A clue to potential therapeutic targets: application of integrative medicine and bioinformatics
Shi-Lin Xia, Han Liu, Shinobu Mizushima, Akio Mizushima
7Drug Combination Therapy    2019, 1 (3): 165-172.   https://doi.org/10.12032/DCT201903004
Abstract PDF (912KB)  

More and more evidence show that the targets of traditional Chinese medicine are a resource pool that contributes to the modern medicine. A key aspect of medicine research is to address the issue how to look for a clue of potential therapeutic molecular targets by interdisciplinary approaches. With the development of high throughput technology, a considerable amount of data has been emerging. The application of these big data is not so efficient as the generation of them. This paper attempts to show that interdisciplinary analysis contributes to the discovery of targets at the initial stage of drug research, indicating that it is necessary to explore the drug research and development with interdisciplinary approaches between integrative medicine and bioinformatics.

Curcumin suppresses proliferation of MCF-7 breast cancer cells by modulating gap junction signaling
Xin-Qiang Song, Mu Zhang, Kai-Ming Li, Er-Qin Dai, Yu Zhang, Ning-Ning Yang, Lei Chen, Lei Wang
7Drug Combination Therapy    2019, 1 (3): 153-164.   https://doi.org/10.12032/DCT201904001
Abstract PDF (949KB)  

Curcumin, an agent isolated from turmeric, shows therapeutic potential against breast cancer. However, the mechanism underlying anticancer activity has not been fully expounded. In this research, bioinformatics was utilized to analyze molecular mechanism of curcumin. and the results have been proved in breast cancer cells subsequently. In order to generate a breast cancer molecular network with which curcumin interacts, target proteins of curcumin from PubChem were combined with genes implicated in breast cancer in the NCBI within Ingenuity Pathway Analysis software.Predicted curcumin targets were verified by reverse transcription-quantitative polymerase chain reaction. Bioinformatics identified gap junction signaling and 14-3-3-mediated adherens junctions as the main canonical signaling pathways targeted by curcumin. Moreover, curcumin can substantially up-regulates the gap junction protein connexin in breast cancer cells. Our results suggest that curcumin through modulation of the gap junction signaling pathway to inhibit cell proliferation and differentiation in breast cancer cells.

A network pharmacological study on the potential mechanism of Yinchenhao Decoction in treatment of chronic hepatitis B
Jin-Yu Zhang, Xian-Fa Cai
7Drug Combination Therapy    2019, 1 (3): 134-152.   https://doi.org/10.12032/DCT201904002
Abstract PDF (1206KB)  

Background: Yinchenhao Decoction (YCHD), an ancient Chinese herbal medicinal compound prescribe for the treatment of jaundice, which long-term clinical experience and randomized trials have shown was effective against chronic hepatitis B (CHB). However, its mechanism remained unknown. With the gradual separation of pharmacodynamic components in YCHD and the development of computer virtual technology, network pharmacology provides an opportunity. Our study is to explore the underlying mechanism of YCHD for the treatment of CHB. Methods: The active compounds of YCHD were screened from TCMSP database, whose targets were predicted based on the ligands structures and the targets of CHB was selected from the TTD, DisGeNET, and Drugbank databases to obtain the potential targets of YCHD for CHB treating. Cytoscape 3.6.1 was applied for network analysis to identify key targets, and gene enrichment of the targets shared by both YCHD and CHB was performed by DAVID database. The virtual verification of binding activities between the target protein and the small molecule was finally performed by the Sytems Dock platform. Results: The potentially important targets associated with CHB corresponding to 33 compound components from YCHD included ESR1, CYP1A2, PTGS2, CYP1A1, ABCG2, MMP9. Besides, enriched were the related 8 KEGG pathways (P<0.05) such as ABC transporters, Bile secretion, TNF signaling pathway. Conclusions: This study used network pharmacology method to reveal the characteristics, “multi-component and multi-target and multi-pathway”, of YCHD on CHB treatment, providing thoughts for further research.

Editor-in-Chief of Special Issue on Network Pharmacology
7Drug Combination Therapy    2019, 1 (3): 0-.  
Abstract PDF (134KB)  

Dr. Yong-Hua Wang is working as a Professor and Doctoral supervisor in Northwest University, China. Dr. Wang also serves as the vice president of the National Medicine Information and Big Data Branch, the director of Network Pharmacology Society, etc.

 

Dr. Wang focuses on the research of systems pharmacology and technology application in the past decades. He has published 110 SCI papers. Among them, 49 SCI papers (in the past five years) were published in Science (special issue of ethnomedicine), Brief Bioinform, Bioinformatics, ACS Chem Bio, etc., including one ESI “Highly Cited Paper”. And the citation of the papers has reached 4100 times (H-index 35). Besides, the unique TCM systems pharmacology platform developed by Dr. Wang, called TCMSP (http://lsp.nwu.edu.cn/tcmsp.php), has been used by scientific research institutions in 83 countries and regions. In the past four years, the paper of TCMSP has been cited more than 700 times. Furthermore, by integrating the rich research experiences over the past decades of himself, Dr. Wang wrote a monograph: “Systematic Pharmacology”.

 

So far, Dr. Wang has won the second prize of Shaanxi Science and Technology Progress Award, China (No.1), Shaanxi Youth Science and Technology Award, China (No.1), and the second prize of National Science and Technology Progress Award, China (No.5). And Dr. Wang was also been selected as a special professor of the “Thousand Talents Program” of Shaanxi Province of China and a new century talent of the Ministry of Education of the People’s Republic of China. Until now, Dr. Wang presides over four projects of the National Natural Science Foundation of China.

Network pharmacology: an important breakthrough in traditional Chinese medicine research
Yuan Jin-Wei, Hao Jian, Chen Dan
2TMR Integrative Medicine    2018, 2 (3): 92-98.   https://doi.org/10.12032/TMRIM201802026
Abstract HTML PDF (979KB)  

Highlights

Network pharmacology breaks through the traditional linear research model and coincides with the complexity of traditional Chinese medicine, provides technical support and new strategy in the research of traditional Chinese medicine.

Abstract

Objective: To study the relationship between traditional Chinese medicine (TCM) research and network pharmacology. Methods: Discuss the common features of TCM and network pharmacology through the analysis of the characteristics of TCM, the background of network pharmacology, so as better interpretation of TCM and in-depth understanding of TCM research and network pharmacology. Results: Multicomponent and multitarget characteristics of TCM as same as the study thought of network pharmacology. Network pharmacology breaks through the research model of linear and coincides with the complexity of TCM, provides technical support for rational design of TCM formulae, both and a new way in the research of TCM. It becomes a new strategy for modern TCM research. Conclusion: Network pharmacology is an important breakthrough in TCM research, its research promote modernization and internationalization process of TCM conduce to the research and development of TCM and have important significance for the integration of Chinese and Western medicine.

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