scholarly journals Uncovering the Mechanisms of Chinese Herbal Medicine (MaZiRenWan) for Functional Constipation by Focused Network Pharmacology Approach

2018 ◽  
Vol 9 ◽  
Author(s):  
Tao Huang ◽  
Ziwan Ning ◽  
Dongdong Hu ◽  
Man Zhang ◽  
Ling Zhao ◽  
...  
Keyword(s):  
Herbal Medicine ◽  
Chinese Herbal Medicine ◽  
Functional Constipation ◽  
Network Pharmacology ◽  
Chinese Herbal

scholarly journals Knowledge discovery in Chinese herbal medicine: a machine learning perspective

2021 ◽  
Vol 336 ◽  
pp. 06024
Author(s):  
Nan Liang ◽  
Qing Liang ◽  
Fenglei Ji
Keyword(s):  
Machine Learning ◽  
Herbal Medicine ◽  
Knowledge Discovery ◽  
Chinese Herbal Medicine ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Current Status ◽  
Network Pharmacology ◽  
Valuable Insight ◽  
Chinese Herbal

Traditional Chinese Medicine (TCM) has attracted more and more attention due to its remarkable effects on treating diseases, and Chinese herbal medicine (CHM) is an important partition of TCM, rich in natural active ingredients. Researchers are trying multiple analytical methods to dig out more valuable information about CHM and reveal the principle of TCM. Machine learning is playing an important role in the studies. Knowledge discovery of CHM using machine learning mainly includes quality control of CHM, network pharmacology in CHM, and medical prescriptions composed by CHM, aiming to understand TCM better, provide more efficiency methods in the production of CHM and find novel treatment of disease not curable nowadays. In this paper, we summarized the basic idea of frequently used classification and clustering machine learning algorithms, introduced pre-processing algorithms commonly used to simplify and accelerate machine learning procedure, presented current status of machine learning algorithms’ applications in knowledge discovery of CHM, discussed challenges and future trends of machine learning’s application in CHM. It is believed that the paper provides a valuable insight for the starters trying to apply machine learning in the study of CHM and catch up the recent status of related researches.

scholarly journals A Review of the Traditional Uses, Botany, Phytochemistry, Pharmacology, Pharmacokinetics, and Toxicology of Corydalis yanhusuo

2020 ◽  
Vol 15 (9) ◽  
pp. 1934578X2095775
Author(s):  
Jingxia Zhang ◽  
Surong He ◽  
Jing Wang ◽  
Changli Wang ◽  
Jianhua Wu ◽  
...  
Keyword(s):  
Herbal Medicine ◽  
Chinese Herbal Medicine ◽  
Therapeutic Potential ◽  
Gastric Ulcers ◽  
Network Pharmacology ◽  
Chemical Components ◽  
China National Knowledge Infrastructure ◽  
Traditional Chinese Herbal Medicine ◽  
Chinese Herbal ◽  
Traditional Uses

Corydalis yanhusuo W. T. Wang (Papaveraceae) is a traditional Chinese herbal medicine that has long been used to treat several conditions and is widely distributed in Asian countries. This review focuses on the traditional uses, botany, phytochemistry, pharmacology, pharmacokinetics, and toxicology of C. yanhusuo. The literature on C. yanhusuo was reviewed using several resources, including classic books on Chinese herbal medicine and scientific databases, namely, PubMed, Springer, Web of Science, Science Direct, and China National Knowledge Infrastructure. Based on information from these databases regarding the chemical components of C. yanhusuo, we evaluated the underlying interaction network between chemical components, biological targets, and associated diseases using Cytoscape software. To date, more than 160 compounds have been isolated and identified from C. yanhusuo, including alkaloids, organic acids, volatile oils, amino acids, nucleosides, alcohols, and sugars. The crude extracts and purified compounds of this plant have analgesic, antiarrhythmic, and antipeptic ulcer properties, along with hypnotic effects. However, studies on the pharmacokinetics of C. yanhusuo extracts remain limited. C. yanhusuo has therapeutic potential in diseases such as cancer and depression, probably due to glaucine and corydaline. Our network pharmacology analysis revealed interactions between 20 compounds, 54 corresponding targets, and 4 health conditions. We found that leonticine, tetrahydroberberine, and corydalmine may regulate the expression of PTGS2, PTGS1, KCNH2, SCN5A, RXRA, CAMKK2, NCOA2, and ESR1, representing a potential treatment strategy against pain, gastric ulcers, inflammation, and cardiac arrhythmias. Additionally, this article discusses the future directions of research on C. yanhusuo.

scholarly journals Network Pharmacology: A New Approach for Chinese Herbal Medicine Research

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Gui-biao Zhang ◽  
Qing-ya Li ◽  
Qi-long Chen ◽  
Shi-bing Su
Keyword(s):  
Herbal Medicine ◽  
Chinese Herbal Medicine ◽  
Target Prediction ◽  
Network Pharmacology ◽  
Multiple Targets ◽  
Medicine Research ◽  
Chinese Herbal ◽  
Long Time ◽  
Effective Drugs

The dominant paradigm of “one gene, one target, one disease” has influenced many aspects of drug discovery strategy. However, in recent years, it has been appreciated that many effective drugs act on multiple targets rather than a single one. As an integrated multidisciplinary concept, network pharmacology, which is based on system biology and polypharmacology, affords a novel network mode of “multiple targets, multiple effects, complex diseases” and replaces the “magic bullets” by “magic shotguns.” Chinese herbal medicine (CHM) has been recognized as one of the most important strategies in complementary and alternative medicine. Though CHM has been practiced for a very long time, its effectiveness and beneficial contribution to public health has not been fully recognized. Also, the knowledge on the mechanisms of CHM formulas is scarce. In the present review, the concept and significance of network pharmacology is briefly introduced. The application and potential role of network pharmacology in the CHM fields is also discussed, such as data collection, target prediction, network visualization, multicomponent interaction, and network toxicology. Furthermore, the developing tendency of network pharmacology is also summarized, and its role in CHM research is discussed.

scholarly journals Chinese Herbal Medicine Meets Biological Networks of Complex Diseases: A Computational Perspective

2017 ◽  
Vol 2017 ◽  
pp. 1-7 ◽  
Author(s):  
Shuo Gu ◽  
Jianfeng Pei
Keyword(s):  
Herbal Medicine ◽  
Chinese Herbal Medicine ◽  
Biological Networks ◽  
Rapid Development ◽  
Regulatory Function ◽  
Network Pharmacology ◽  
Chinese Herbal ◽  
Computational Workflow ◽  
Computational Research

With the rapid development of cheminformatics, computational biology, and systems biology, great progress has been made recently in the computational research of Chinese herbal medicine with in-depth understanding towards pharmacognosy. This paper summarized these studies in the aspects of computational methods, traditional Chinese medicine (TCM) compound databases, and TCM network pharmacology. Furthermore, we chose arachidonic acid metabolic network as a case study to demonstrate the regulatory function of herbal medicine in the treatment of inflammation at network level. Finally, a computational workflow for the network-based TCM study, derived from our previous successful applications, was proposed.

scholarly journals Untargeted Metabolomics Profiling and Global Semi-quantitation of a Prescription Chinese Herbal Medicine Formula Yinqiaosan Using UPLC-QTOF-MS with a Single Exogenous Reference Internal Standard

2020 ◽  
Vol 07 (02) ◽  
pp. e45-e57
Author(s):  
Yachun Shu ◽  
Chandana Mannem ◽  
Gang Xu ◽  
Shashank Gorityala ◽  
Xiao Liu ◽  
...  
Keyword(s):  
Herbal Medicine ◽  
Chinese Herbal Medicine ◽  
Viral Infections ◽  
Chemical Constituents ◽  
Internal Standard ◽  
Untargeted Metabolomics ◽  
Network Pharmacology ◽  
Qualitative And Quantitative ◽  
Chinese Herbal ◽  
Chinese Herbal Medicine Formula

Abstract Yinqiaosan is a classic Chinese herbal medicine formula that has been used to treat various bacterial and viral infections by Chinese medicine doctors for over two centuries. In this work, we developed a comprehensive qualitative and quantitative method for identification, quantitation, and quality assessment of chemical constituents of Yinqiaosan formula in four different preparation forms (i.e., decoction, granule, pill, and tablet), which employed ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry with a single exogenous reference internal standard for untargeted metabolomics profiling and global semiquantitative analysis. The use of a single exogenous reference internal standard permitted not only qualitative and quantitative analyses of multiple herbal components in a single instrument run, but also cross-comparison of chemical contents in between all four Yinqiaosan preparation forms. The acquired mass chromatograms were analyzed, quantitated, and compared using multivariate data analysis for similarities and differences of chemical constituents in four Yinqiaosan preparation forms. For the first time, we were able to identify over 100 chemical constituents from each preparation form using the available database. Among the 49 commonly identified compounds in the 4 Yinqiaosan preparation forms, 16 have been reported to have pharmacological activities, which may be used in a network pharmacology study of Yinqiaosan for exploring the underlying mechanism of the herbal formula.

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