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   Table of Contents - Current issue
October-December 2018
Volume 4 | Issue 4
Page Nos. 135-180

Online since Tuesday, November 6, 2018

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Network pharmacology: An approach to the analysis of complex systems underlying traditional chinese medicine p. 135
Shao Li, Yuan-Jia Hu
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Exploring the pathways and targets of Shexiang Baoxin pill for coronary heart disease through a network pharmacology approach p. 137
Shou-De Zhang, Zhan-Hai Su, Rui-Hui Liu, Yan-Yan Diao, Shi-Liang Li, Ya-Ping-Hua , Hong-Lin Li, Wei-Dong Zhang
Objective: To investigate the network pharmacology of Shexiang Baoxin pill (SBP) and systematically analyze the mechanisms of SBP. Methods: In this study, we excavated all the targets of 26 constituents of SBP which were identified in rat plasma though literature mining and target calculation (reverse docking and similarity search) and analyzed the multiple pharmacology actions of SBP comprehensively through a network pharmacology approach. Results: In the end, a total of 330 Homo sapiens targets were identified for 26 blood constituents of SBP. Moreover, the pathway enrichment analysis found that these targets mapped into 171 KEGG pathways and 31 of which were more enriched. Among these identified pathways, 3 pathways were selected for analyzing the mechanisms of SBP for treating coronary heart disease. Conclusion: This study systematically illustrated the mechanisms of the SBP by analyzing the corresponding “drug-target-pathway-disease” interaction network.
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A network pharmacology approach to decipher the mechanisms of anti-depression of Xiaoyaosan formula p. 147
Yao Gao, Li Gao, Jun-Sheng Tian, Xue-Mei Qin, Xiang Zhang
Objective: Depression is one of the prevalent and prominent complex psychiatric diseases, and the number of depressed patients has been on the rise globally during the recent decades. Xiaoyaosan, as a famous Chinese herbal formula, has been widely used in depression patients for a long time. However, the therapeutic mechanisms remain uncertain because of the difficulty of depression pathophysiology and the lack of bioinformatic approach to understand the molecular connection. Materials and Methods: In this thesis, we applied a network pharmacology approach to explain the potential mechanisms between Xiaoyaosan and depression involved in oral bioavailability screening, drug-likeness assessment, caco-2 permeability, blood–brain barrier target recognition, and network analysis. Results: Sixty-six active compounds in Xiaoyaosan formula with favorable pharmacokinetic profiles are predicted as active compounds for antidepression treatment. Network analyses showed that these 66 compounds target 40 depression-associated proteins including especially HTR2A, NR 3C1, monoamine oxidase inhibitor B, XDH, and CNR2. These proteins are mainly involved in the neuroactive ligand–receptor interaction, serotonergic synapse, cAMP signaling pathways, and calcium signaling pathways. Conclusion: The integrated network pharmacology method can provide a new approach for understanding the pathogenesis of depression and uncovering the molecular mechanisms of Xiaoyansan, which will also facilitate the application of traditional Chinese herbs in modern medicine.
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A visual analysis of network pharmacology research trends p. 163
Shen Xiao, Fang-Qing Zhao, Qi-Ming Wang, Yun-Ru Dong, Shein-Chung Chow, Meng-Zhen Fan, Bo Xing, Fei Zhai, Rong-Wu Xiang
Objective: To understand the current situation of network pharmacology, and to analyze external and internal characteristics of literature, is of great significance for the development of network pharmacology in the future and its application in the modernization of Chinese medicine. Methods: Bibliometrics were adapted to perform visual analysis on the research status of network pharmacology with Citespace and SPSS for windows 22.0 version (IBM, Armonk, New York, USA). Knowledge map was used to analyze the knowledge system in the field, to identify the research hotspots and dynamic frontiers, and to elaborate the research status and development trend of domestic network pharmacology. Results: The research on network pharmacology in China is at the stage of the formation and construction of basic theories. At present, we focuses on the solution of actual disease problems and basic theoretical research, while the application in the research field of traditional Chinese medicine is a new hot spot and trend in the future development. Conclusions: It is important to pay attention to the connection and communication among the knowledge groups, so that a systematic knowledge system can be formed in the field of network pharmacology in domestic as soon as possible.
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Compound-target-pathway network analysis and effective mechanisms prediction of Bu-Shen-Jian-Pi formula p. 170
Xiao-Yan Li, Meng-Die Yang, Xue-Qing Hu, Fei-Fei Cai, Xiao-Le Chen, Qi-Long Chen, Shi-Bing Su
Objective: The aim of this study was to predict the active compounds, therapy targets, and diseases of Bu-Shen-Jian-Pi formula (BSJPF) through the system pharmacology-based approach. Methods: Traditional Chinese Medicine Systems Pharmacology (TCMSP) and TCM Database@Taiwan Databases were used to obtain Chinese herbal medicine compounds. Oral bioavailability (OB) and drug-likeness (DL) based on the TCMSP database were used to screen the active compounds of BSJPF and related diseases. Therapy targets were defined according to the DrugBank database. The compounds-targets-disease network was constructed by Cytoscape and function and signaling pathways were also analyzed. Results: A total of 143 of 2106 compounds in BSJPF were screened out (OB ≥30%, DL index ≥0.18). Two hundred and sixty-five targets were found and 334 diseases were enriched. The diseases such as cancer, Alzheimer's disease, inflammation, and asthma were most closely correlated with the formula. BSJPF, Liu-Wei-Di-Huang decoction (LWDHD), and Si-Jun-Zi decoction (SJZD) could regulate cell proliferation and apoptosis; LWDHD also regulated biological processes and cellular processes and regulated stress on chemical stimuli and SJZD focused on the regulation of anabolic reaction. All had enriched the signaling pathways in cancer, nonsmall cell lung cancer, and thyroid cancer pathways. There were more pathways in both BSJPF and LWDHD, mainly including cancer, colorectal cancer pathways, toll-like receptors, T-cell receptors and P53 signaling pathways, and apoptosis. LWDHD was also involved in Wnt, natural killer cell cytotoxicity, and lymphocyte migration signaling pathways. SJZD had no separate pathways. In the tumor-related pathways, targets were more concentrated in the PI3K/Akt pathway and the MAPK/ERK signaling pathway. Conclusions: BSJPF owns multiple targets and pathways to treat various diseases under the guidance of “treating different diseases with the same method.”
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Study on the biological basis of hypertension and syndrome with liver-fire hyperactivity based on data mining technology p. 176
Xue-Ling Ma, Xing Zhai, Jing-Wei Liu, Xiao-Xing Xue, Shu-Zhen Guo, Hua Xie, Jian-Xin Chen, Hui-Hui Zhao, Wei Wang
Objective: To construct gene co-occurrence network of hypertension and liver-fire hyperactivity syndrome, to investigate the biological basis of hypertension and liver-fire hyperactivity syndrome and the characteristics of the molecular network from gene level. Materials and Methods: Applying GenCLip 2.0 online platform to retrieve the up-to-date literature referred to essential hypertension from PubMed database, cluster the abnormal expression of essential hypertension-related genes and analyze their function, combining Kyoto encyclopedia of genes and genomes-pathway analysis to investigate the closely related genes and the signaling molecules. Based on the genes closely related to hypertension, standard diagnostic symptoms of liver-fire hyperactivity were used as keywords to conduct hypertension liver-fire hyperactivity-related gene cluster analysis. Results: The top 1000 genes of essential hypertension were retrieved from GenCLip 2.0 online platform, which mainly clustered in the regulation of ambulatory blood pressure, regulation of renin-angiotensin-aldosterone system (RAAS), and sympathetic nervous system activity, as well as endothelial dysfunction; the closely related genes of hypertension with liver-fire hyperactivity are related to RAAS, gene REN, angiotensin converting enzyme, angiotensinogen, and cytochrome P450 family CYP2D6. Conclusion: A combination of literature mining and data mining can construct the gene network of hypertension and the syndrome-related genes, which provides a new method for the study of the biological basis of hypertension from the genetic level.
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