Application of drug-target prediction technology in network pharmacology of traditional Chinese medicine

2016 ◽  
Keyword(s):  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Drug Target ◽  
Target Prediction ◽  
Network Pharmacology ◽  
Drug Target Prediction

scholarly journals Study on Medication Rules of Traditional Chinese Medicine against Antineoplastic Drug-Induced Cardiotoxicity Based on Network Pharmacology and Data Mining

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Wenchao Dan ◽  
Jinlei Liu ◽  
Xinyuan Guo ◽  
Boran Zhang ◽  
Yi Qu ◽  
...  
Keyword(s):  
Data Mining ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Target Prediction ◽  
Antineoplastic Drug ◽  
Matrix Metalloproteinase 2 ◽  
Network Pharmacology ◽  
China National Knowledge Infrastructure ◽  
Drug Induced ◽  
Mitogen Activated Protein

Background and Aim. Antineoplastic drug-induced cardiotoxicity (ADIC) becomes the second leading cause of death for tumor survivors after tumor recurrence and metastasis, and there may be great room for development in the future of traditional Chinese medicine (TCM). However, the theory of anticardiotoxicity of TCM has not yet formed a system. This study aimed to explore the material basis and the rule of TCM against ADIC based on network pharmacology and data mining. Methods. The targets of antineoplastic drugs with cardiotoxicity were obtained from the National Center for Biotechnology Information (NCBI) database, China national knowledge infrastructure (CNKI) database, and Swiss Target Prediction platform. Then, the cardiotoxicity-related targets were derived from the Gene Cards, Disgenet, OMIM, and DrugBank databases, as well as the drug of current clinical guidelines. The targets both in these two sets were regarded as potential targets to alleviate ADIC. Then, candidate compounds and herbs were matched via Traditional Chinese Medicine Systems Pharmacology (TCMSP) platform. Cytoscape3.7.1 was used to set up the target-compound-herb network. Molecular docking between core targets and compounds was performed with AutodockVina1.1.2. The rules of herbs were summarized by analyzing their property, flavor, and channel tropism. Results. Twenty-one potential targets, 332 candidate compounds, and 400 kinds of herbs were obtained. Five core targets including potassium voltage-gated channel subfamily H member 2 (KCNH2), cyclin-dependent kinase 1 (CDK1), matrix metalloproteinase 2 (MMP2), mitogen-activated protein kinase1 (MAPK1), and tumor protein p53 (TP53) and 29 core compounds (beta-sitosterol, quercetin, kaempferol, etc.) were collected. Five core herbs (Yanhusuo, Gouteng, Huangbai, Lianqiao, and Gancao) were identified. Also, the TCM against ADIC were mainly bitter and acrid in taste, warm in property, and distributed to the liver and lung meridians. Conclusion. TCM against ADIC has great potential. Our study provides a new method and ideas for clinical applications of integrated Chinese and western medicine in treating ADIC.

Drug–target prediction utilizing heterogeneous bio-linked network embeddings

2019 ◽  
Author(s):  
Nansu Zong ◽  
Rachael Sze Nga Wong ◽  
Yue Yu ◽  
Andrew Wen ◽  
Ming Huang ◽  
...  
Keyword(s):  
Drug Target ◽  
Target Prediction ◽  
Machine Learning Algorithms ◽  
Association Mining ◽  
Drug Target Prediction ◽  
Specific Prediction ◽  
Series Of Experiments ◽  
Inference Methods ◽  
Novel Drug ◽  
Prediction Strategy

Abstract To enable modularization for network-based prediction, we conducted a review of known methods conducting the various subtasks corresponding to the creation of a drug–target prediction framework and associated benchmarking to determine the highest-performing approaches. Accordingly, our contributions are as follows: (i) from a network perspective, we benchmarked the association-mining performance of 32 distinct subnetwork permutations, arranging based on a comprehensive heterogeneous biomedical network derived from 12 repositories; (ii) from a methodological perspective, we identified the best prediction strategy based on a review of combinations of the components with off-the-shelf classification, inference methods and graph embedding methods. Our benchmarking strategy consisted of two series of experiments, totaling six distinct tasks from the two perspectives, to determine the best prediction. We demonstrated that the proposed method outperformed the existing network-based methods as well as how combinatorial networks and methodologies can influence the prediction. In addition, we conducted disease-specific prediction tasks for 20 distinct diseases and showed the reliability of the strategy in predicting 75 novel drug–target associations as shown by a validation utilizing DrugBank 5.1.0. In particular, we revealed a connection of the network topology with the biological explanations for predicting the diseases, ‘Asthma’ ‘Hypertension’, and ‘Dementia’. The results of our benchmarking produced knowledge on a network-based prediction framework with the modularization of the feature selection and association prediction, which can be easily adapted and extended to other feature sources or machine learning algorithms as well as a performed baseline to comprehensively evaluate the utility of incorporating varying data sources.

scholarly journals Drug Target Prediction Based on the Herbs Components: The Study on the Multitargets Pharmacological Mechanism of Qishenkeli Acting on the Coronary Heart Disease

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Yong Wang ◽  
Zhongyang Liu ◽  
Chun Li ◽  
Dong Li ◽  
Yulin Ouyang ◽  
...  
Keyword(s):  
Coronary Heart Disease ◽  
Heart Disease ◽  
Angiotensin Ii ◽  
Drug Target ◽  
Drug Targets ◽  
Target Prediction ◽  
Coronary Artery Ligation ◽  
Potential Drug ◽  
Drug Target Prediction ◽  
Potential Drug Targets

In this paper, we present a case study of Qishenkeli (QSKL) to research TCM’s underlying molecular mechanism, based on drug target prediction and analyses of TCM chemical components and following experimental validation. First, after determining the compositive compounds of QSKL, we use drugCIPHER-CS to predict their potential drug targets. These potential targets are significantly enriched with known cardiovascular disease-related drug targets. Then we find these potential drug targets are significantly enriched in the biological processes of neuroactive ligand-receptor interaction, aminoacyl-tRNA biosynthesis, calcium signaling pathway, glycine, serine and threonine metabolism, and renin-angiotensin system (RAAS), and so on. Then, animal model of coronary heart disease (CHD) induced by left anterior descending coronary artery ligation is applied to validate predicted pathway. RAAS pathway is selected as an example, and the results show that QSKL has effect on both rennin and angiotensin II receptor (AT1R), which eventually down regulates the angiotensin II (AngII). Bioinformatics combing with experiment verification can provide a credible and objective method to understand the complicated multitargets mechanism for Chinese herbal formula.

scholarly journals Study on the Mechanism of Lianpu Drink for the Treatment of Chronic Gastritis Based on Network Pharmacology

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Shuhan Zhou ◽  
Yanjun Duan ◽  
Yu Deng ◽  
Miao Wang ◽  
Chaoqun Huang ◽  
...  
Keyword(s):  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Signaling Pathway ◽  
Chronic Gastritis ◽  
Mechanisms Of Action ◽  
Network Pharmacology ◽  
Biological Pathway ◽  
Disease Network ◽  
Target Disease ◽  
Compound Target

Chronic gastritis (CG) places a considerable burden on the healthcare system worldwide. Traditional Chinese Medicine (TCM) formulas characterized by multicompounds and multitargets have been acknowledged with striking effects in the treatment of CG in China’s history. Nevertheless, their accurate mechanisms of action are still ambiguous. In this study, we analyzed the effective compounds, potential targets, and related biological pathway of Lianpu Drink (LPD), a TCM formula which has been reported to have a therapeutic effect on CG, by contrasting a “compound-target-disease” network. According to the results, 92 compounds and 5762 putative targets of LPD were screened; among them, 8 compounds derived from different herbs in LPD and 30 common targets related to LPD and CG were selected as candidate compounds and precision targets, respectively. Meanwhile, the predicted common targets were verified by Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway analysis and pharmacological experiments. The results demonstrated that quercetin, ephedrine, trigonelline, crocetin, and β-sitosterol were major effective compounds of LPD responsible for the CG treatment by inhibiting the activation of the JAK 2-STAT 3 signaling pathway to reduce the expressions of cyclin D1 and Bcl-2 proteins. The study provides evidence for the mechanism of understanding of LPD for the treatment of CG.

scholarly journals Evidence of TCM Theory in Treating the Same Disease with Different Methods: Treatment of Pneumonia with Ephedra sinica and Scutellariae Radix as an Example

2020 ◽  
Vol 2020 ◽  
pp. 1-23
Author(s):  
Liping Sun ◽  
Dandan Wang ◽  
Yan Xu ◽  
Wenxiu Qi ◽  
Yanbo Wang
Keyword(s):  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Network Pharmacology ◽  
Ppi Network ◽  
Future Directions ◽  
Network Construction ◽  
Ephedra Sinica ◽  
Scutellariae Radix ◽  
Tcm Theory ◽  
Global Health Problem

Pneumonia is a serious global health problem and the leading cause of mortality in children. Antibiotics are the main treatment for bacterial pneumonia, but there are serious drug resistance problems. Traditional Chinese medicine (TCM) has been used to treat diseases for thousands of years and has a unique theory. This article takes the treatment of pneumonia with Ephedra sinica as a representative hot medicine and Scutellariae Radix as a representative cold medicine as an example. We explore and explain the theory of treating the same disease with different TCM treatments. Using transcriptomics and network pharmacology methods, GO, KEGG enrichment, and PPI network construction were carried out, demonstrating that Ephedra sinica plays a therapeutic role through the NF-κB and apoptosis signaling pathways targeting PLAU, CD40LG, BLC2L1, CASP7, and CXCL8. The targets of Scutellariae Radix through the IL-17 signaling pathway are MMP9, CXCL8, and MAPK14. Molecular docking technology was also used to verify the results. In short, our results provide evidence for the theory of treating the same disease with different treatments, and we also discuss future directions for traditional Chinese medicine.

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