scholarly journals A combination of metabolite profiling and network pharmacology to explore the potential pharmacological changes of secoisolariciresinol-diglycoside

RSC Advances ◽  
2020 ◽  
Vol 10 (57) ◽  
pp. 34847-34858
Author(s):  
Fengxiang Zhang ◽  
ShuangShuang Cui ◽  
Ziting Li ◽  
Yulinlan Yuan ◽  
Chang Li ◽  
...  
Keyword(s):  
Side Effects ◽  
Metabolite Profiling ◽  
Network Pharmacology ◽  
Traditional Chinese Medicines ◽  
Chinese Medicines ◽  
Therapeutic Results ◽  
Secoisolariciresinol Diglycoside

The prototypes and metabolites formed from the use of traditional Chinese medicines (TCM) are typically the cause of both side side-effects and therapeutic results.

Prediction of quality markers of traditional Chinese medicines based on network pharmacology

2019 ◽  
Vol 11 (4) ◽  
pp. 349-356 ◽  
Author(s):  
Yu-li Wang ◽  
Tao Cui ◽  
Ya-zhuo Li ◽  
Mao-liang Liao ◽  
Hong-bing Zhang ◽  
...  
Keyword(s):  
Network Pharmacology ◽  
Traditional Chinese Medicines ◽  
Chinese Medicines ◽  
Quality Markers

scholarly journals Study on Hypoglycemic Effect of the Drug Pair of Astragalus Radix and Dioscoreae Rhizoma in T2DM Rats by Network Pharmacology and Metabonomics

Molecules ◽  
2019 ◽  
Vol 24 (22) ◽  
pp. 4050 ◽  
Author(s):  
Guo ◽  
Niu ◽  
Li ◽  
Guo ◽  
Zhang ◽  
...  
Keyword(s):  
Metabolic Profiling ◽  
Network Pharmacology ◽  
Traditional Chinese Medicines ◽  
Acetyl Coa Carboxylase ◽  
Active Components ◽  
Active Compounds ◽  
Drug Pair ◽  
Chinese Medicines ◽  
Metabolic Perturbation

Type 2 diabetes mellitus (T2DM) is a metabolic disease accompanied by a series of diseases such as diabetic nephropathy. The drug pair (HS) of Astragalus Radix (HQ) and Dioscoreae Rhizoma (SY) was designed by Dr. Shi Jinmo to improve the treatment of T2DM. However, the exact mechanism involved requires further clarification. In this work, 1H NMR–based metabonomics and network pharmacology were adopted. Metabolic profiling indicated that the metabolic perturbation was reduced after HS treatment. The results found 21 biomarkers. According to the network pharmacology, we found that the regulation of T2DM was primarily associated with 18 active compounds in HS. These active compounds mainly had an effect on 135 targets. Subsequently, combining network pharmacology and metabonomics, we found four target proteins, which indicated that HS has potential hypoglycemic effects through regulating monoamine oxidases B (MAOB), acetyl-CoA carboxylase 1 (ACACA), carbonic anhydrase 2 (CA2), and catalase (CAT). In conclusion, the result showed that these four targets might be the most relevant targets for the treatment of T2DM with HS. This study clarified the mechanism of HS in the treatment of T2DM and also confirmed the feasibility of combining metabonomics and network pharmacology to study the mechanisms of traditional Chinese medicine (TCM). In the future, this approach may be a potentially powerful tool to discovery active components of traditional Chinese medicines and elucidate their mechanisms.

scholarly journals Network Pharmacology-Based Analysis of the Pharmacological Mechanisms of Aloperine on Cardiovascular Disease

2020 ◽  
Vol 2020 ◽  
pp. 1-8 ◽  
Author(s):  
Bingwu Huang ◽  
Juncheng Xiong ◽  
Xuyong Zhao ◽  
Yihan Zheng ◽  
Ning Zhu
Keyword(s):  
Cardiovascular Disease ◽  
Nitrogen Metabolism ◽  
Molecular Mechanisms ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Mendelian Inheritance ◽  
Network Pharmacology ◽  
Traditional Chinese Medicines ◽  
Protective Effects ◽  
Chinese Medicines

Background. Aloperine is an active component of Sophora alopecuroides Linn, which has been extensively applied for the treatment of cardiovascular disease (CVD). However, our current understanding of the molecular mechanisms supporting the effects of aloperine on CVD remains unclear. Methods. Systematic network pharmacology was conducted to provide testable hypotheses about pharmacological mechanisms of the protective effects of aloperine against CVD. Detailed structure was obtained from Traditional Chinese Medicines Integrated Database (TCMID). Target genes of aloperine against CVD were collected from SwissTargetPrediction, DrugBank database, and Online Mendelian Inheritance in Man (OMIM) database. Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway performance, and network construction were adopted to explore common target genes. Results. Our findings showed that 25 candidate targets were the interacting genes between aloperine and CVD. GO analysis revealed biological process, cellular component, and molecular function of these target genes. More importantly, the majority of enrichment pathways was found to be highly associated with the nitrogen metabolism by KEGG analysis. Core genes particularly in nitrogen metabolism pathway including carbonic anhydrase (CA) III, CA IV, CA VA, CA VB, CA VI, CA VII, CA IX, CA XII, and CA XIV can be modulated by aloperine in the nitrogen metabolism. Conclusion. Our work revealed the pharmacological and molecular mechanisms of aloperine against CVD and provided a feasible tool to identify the pharmacological mechanisms of single active ingredient of traditional Chinese medicines.

Network pharmacology study of traditional Chinese medicines for stroke treatment and effective constituents screening

2019 ◽  
Vol 242 ◽  
pp. 112044 ◽  
Author(s):  
Liwen Ren ◽  
Xiangjin Zheng ◽  
Jinyi Liu ◽  
Wan Li ◽  
Weiqi Fu ◽  
...  
Keyword(s):  
Network Pharmacology ◽  
Traditional Chinese Medicines ◽  
Chinese Medicines ◽  
Stroke Treatment
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