Development of the disease is the result of several factors involved in biological network changes. The nature of drug intervention is to regulate these pathological changes to the normal range. Advantages of traditional Chinese medicine (TCM) are to integrally and systematically regulate this biological networks and systematic pathology through multi-targets, multi-levels, multi-channels. Structural components TCM provides the controlled and precise basis "substance" for this regulation and also to clarify the "truth" of the nature of the regulation by the network pharmacology. Network pharmacology provides new strategy for the research on mechanism of structural components TCM. This study not only reflects the overall characteristics of the development of the disease, but also fully embodies the essence of TCM for preventing and treating diseases through changing traditional model on "one drug, one gene, one disease". This paper explores systematically the integration essence, features and research strategies of structural components TCM and the network pharmacology, understand the interaction of structural components TCM and body from the perspective of the overall concept of improving or restoring the balance of.biological networks. It is effective measure to reveal the structure of a multi-component for regulating biological networks mechanisms, and also provide new ideas and methods for further scientific research and innovation of structural component TCM.
Drug Interactions ; Drug Therapy ; Drugs, Chinese Herbal ; chemistry ; pharmacology ; Gene Regulatory Networks ; drug effects ; Humans ; Medicine, Chinese Traditional

A complex disease is rarely a consequence of abnormality in a single gene. It is known that many drugs exhibit a therapeutic effect by acting on multiple targets, produce synergies to intervene the occurrence and development of diseases. Unlike the traditional methods which act on single molecule or pathway, this disease-drug target network constructed with high throughput data vividly showed the complex relationship between drugs, their targets and diseases. However, the networks are usually extremely complex. In order to reduce the complexity, it is necessary to deconstruct the network and identify module structures. In this study, framework of module analysis was summarized from four aspects: module concept, structure and identification methods, importance of disease-drug module identification, and its application. Module-based analysis provides a new perspective for deciphering the drug intervention mechanisms for complex diseases, and provides new ideas and pathways to reveal the mechanisms of multi-target and multi-component drugs.
Drug Delivery Systems ; Drugs, Chinese Herbal ; administration & dosage ; chemistry ; Gene Regulatory Networks ; drug effects ; Humans ; Molecular Targeted Therapy

OBJECTIVETo explore the intersection and regulation mechanism of "efficacy-toxicity network" of Glycyrrhizae Radix et Rhizoma, Zingiberis Rhizoma and Aconiti Lateralis Radix Praeparata's action gene in the combination environment of Sini decoction with the network pharmacological method.

METHODThe gene interaction network of Aconiti Lateralis Radix Praeparata, Glycyrrhizae Radix et Rhizoma, Zingiberis Rhizoma were mined and established with Cytoscape software and Agilent literature search plug-in. The "efficiency-toxicity network" intersection of Aconiti Lateralis Radix Praeparata was formed according to its effects in anti-heart failure, neurotoxicity and cardiotoxicity. The target genes were clustered with Clusterviz plug-in. And the possible pathways of the "efficacy-tox- icity network" intersection of Glycyrrhizae Radix et Rhizoma, Zingiberis Rhizoma and Aconiti Lateralis Radix Praeparata were forecasted in DAVID database.

RESULTThere were five genes related to neurotoxicity, cardiotoxicity and anti-heart failure function of Aconiti Lateralis Radix Praeparata, namely AKT1, BAX, HCC, IL6 and IL8, which formed 47 nodes genes in the "efficiency-toxicity network" intersection of Aconiti Lateralis Radix Praeparata. There were 29 and 27 coincident genes in the "efficiency-toxicity network" of Glycyrrhizae Radix et Rhizoma, Zingiberis Rhizoma and Aconiti Lateralis Radix Praeparata. There were 23 and 17 possible regulatory pathways.

CONCLUSIONIn the combination environment of Sini decoction, Glycyrrhizae Radix et Rhizoma and Zingiberis Rhizoma may regulate the efficiency-toxicity network of Aconiti Lateralis Radix Praeparata by influencing immune-inflammatory signaling pathway, apoptosis-autophagy signaling pathway, nerve cell and myocardial ischemia and hypoxia protection signaling pathways.

Aconitum ; chemistry ; toxicity ; Drugs, Chinese Herbal ; chemistry ; toxicity ; Gene Regulatory Networks ; drug effects ; Humans ; Rhizome ; chemistry ; toxicity

To collect small molecule drugs and their drug target data such as enzymes, ion channels, G-protein-coupled receptors and nuclear receptors from KEGG database as the training sets, in order to establish drug-target interaction models based on the random forest algorithm. The accuracies of the models were evaluated by the 10-fold cross-validation test, showing that the predicted success rates of the four drug target models were 71.34%, 67.08%, 73.17% and 67.83%, respectively. The models were adopted to predict the targets of 26 chemical components and establish the compound-target-disease network. The results were well verified by literatures. The models established in this paper are highly accurate, and can be used to discover potential targets in other traditional Chinese medicine ingredients.
Algorithms ; Drugs, Chinese Herbal ; pharmacology ; Gene Regulatory Networks ; drug effects ; Humans ; Ligusticum ; chemistry ; Molecular Targeted Therapy ; Rhizome ; chemistry

OBJECTIVETo investigate the mechanisms of Panax notoginseng saponins (PNS) in treating coronary heart disease (CHD) by integrating gene interaction network and functional enrichment analysis.

METHODSText mining was used to get CHD and PNS associated genes. Gene-gene interaction networks of CHD and PNS were built by the GeneMANIA Cytoscape plugin. Advanced Network Merge Cytoscape plugin was used to analyze the two networks. Their functions were analyzed by gene functional enrichment analysis via DAVID Bioinformatics. Joint subnetwork of CHD network and PNS network was identifified by network analysis.

RESULTSThe 11 genes of the joint subnetwork were the direct targets of PNS in CHD network and enriched in cytokine-cytokine receptor interaction pathway. PNS could affect other 85 genes by the gene-gene interaction of joint subnetwork and these genes were enriched in other 7 pathways. The direct mechanisms of PNS in treating CHD by targeting cytokines to relieve the inflflammation and the indirect mechanisms of PNS in treating CHD by affecting other 7 pathways through the interaction of joint subnetwork of PNS and CHD network. The genes in the 7 pathways could be potential targets for the immunologic adjuvant, anticoagulant, hypolipidemic, anti-platelet and anti-hypertrophic activities of PNS.

CONCLUSIONSThe key mechanisms of PNS in treating CHD could be anticoagulant and hypolipidemic which are indicated by analyzing biological functions of hubs in the merged network.

Coronary Disease ; drug therapy ; genetics ; Gene Expression Profiling ; Gene Regulatory Networks ; drug effects ; Humans ; Panax notoginseng ; chemistry ; Phytotherapy ; Saponins ; pharmacology ; therapeutic use

The mechanism of synergetic effects of multi-components on multi-targets in traditional Chinese medicine (TCM) is one of the bottlenecks for TCM modernization and internationalization. Network biology approach was developed in recent years and provided an important and novel idea to study the pharmacological mechanism of TCM. This review introduced the mathematical basis of network biology, as well as the feasibility and research idea of using network biology to study the pharmacological mechanism of TCM. Network biology was expected to be further used for analyzing the pharmacological mechanism of TCM, guiding drug development of TCM, inheriting and carrying forward the fundamental principle of TCM.
Algorithms ; Drug Therapy ; methods ; Drugs, Chinese Herbal ; administration & dosage ; pharmacology ; therapeutic use ; Gene Regulatory Networks ; drug effects ; Humans ; Medicine, Chinese Traditional ; methods ; Metabolic Networks and Pathways ; drug effects ; Models, Biological ; Proteins ; genetics ; metabolism ; Signal Transduction ; drug effects

As regulating the function of the liver and spleen of the famous traditional formula, Sini San is widely used in the treatment of various diseases caused by liver depression and Qi stagnation, and its efficacy is significant clinically. Recently it is discovered that Sini San is effective in the treatment of nervous system diseases such as depression. Furthermore, there is a lot of literature about the effect of Sini San on the molecular mechanism of antidepressant. However, the anti-depression mechanism of Sini San is not very clear, in our present study, based on the auxiliary mechanism elucidation system for Chinese medicine and network pharmacology system to construct the chemical ingredients of the target interactions and disease-related protein of the interaction network. Results show that there are 263 chemical ingredients and 19 corresponding targets of depression in Sini San network. Sini San can anti-depressant effect through G-protein coupled receptor protein signaling pathway, cAMP system, neurological system process and neurotransmitter secretion, inflammatory response, neuroendocrine, metal ion transport and so on. These studies provided valuable clues for the mechanism and treatment of anti-depressant.
Animals ; Antidepressive Agents ; administration & dosage ; chemistry ; Databases, Factual ; Depression ; drug therapy ; genetics ; metabolism ; Drugs, Chinese Herbal ; administration & dosage ; chemistry ; Gene Regulatory Networks ; drug effects ; Humans ; Signal Transduction

Salvia miltiorrhiza is a traditional Chinese medicine (TCM) and is widely used as a clinically medication for its efficiency in treating cardiovascular disease. Due to TCM is a comprehensive system, the mechanism of S. miltiorrhiza treating cardiovascular disease through integrated multiple pathways are still unclear in some aspects. With the rapid progress of bioinformatics and systems biology, network pharmacology is considered as a promising approach toward reveal the underlying complex relationship between an herb and the disease. In order to discover the mechanism of S. miltiorrhiza treating cardiovascular disease systematically, we use the auxiliary mechanism elucidation system for Chinese medicine, built up a molecule interaction network on the active component targets of S. miltiorrhiza and the therapeutic targets of cardiovascular disease to offer an opportunity for deep understanding the mechanism of S. miltiorrhiza treating cardiovascular disease from the perspective of network pharmacology. The results showed that S. miltiorrhiza treating cardiovascular disease through ten pathways as follows: improve lipid metabolism, anti-inflammation, regulate blood pressure, negatively regulates blood coagulation factor and antithrombotic, regulate cell proliferation, anti-stress injury, promoting angiogenesis, inhibited apoptosis, adjust vascular systolic and diastolic, promoting wound repair. The results of this paper provide theoretical guidance for the development of new drugs to treat cardiovascular disease and the discovery of new drugs through component compatibility.
Animals ; Cardiovascular Diseases ; drug therapy ; genetics ; metabolism ; Databases, Factual ; Drugs, Chinese Herbal ; administration & dosage ; chemistry ; Gene Regulatory Networks ; drug effects ; Humans ; Salvia miltiorrhiza ; chemistry ; Signal Transduction

Recently, compound Ejiao slurry (FFEJJ) had been applied to treat cancer patients in clinic, with obvious curative effect. In this study, data and literatures were collected from the TCM chemical component database to establish the chemical component database of FFEJJ. Afterwards, MetaDrug software was used to predict the targets of FFEJJ and obtain the compound-target network. Next, the compound-target network was compared and analyzed to obtain the "compound-target-tumor target" heterogeneous network. Besides, further analysis was made on gene functions and metabolic pathway. The results indicated that FFEJJ could directly resist tumors by regulating cancer cell differentiation, growth, proliferation and apoptosis, and show an adjuvant therapeutic effect by enriching the blood and increasing the immunity.
Adjuvants, Pharmaceutic ; therapeutic use ; Antineoplastic Agents ; therapeutic use ; Drugs, Chinese Herbal ; therapeutic use ; Gene Regulatory Networks ; drug effects ; Humans ; Molecular Targeted Therapy ; Neoplasms ; drug therapy ; genetics ; metabolism

Retinal vein occlusion (RVO) is a common clinical disease causing vision loss. Risk factors such as diabetes, atherosclerosis are closely associated with RVO. Xuesaitong injection is used extensively in clinical treatment of RVO, however the mechanism is still unclear. In this study, we investigated the protective effect of Xuesaitong injection on RVO rat model. Using a compound-target network of Xuesaitong on anti-RVO constructed by literature mining, we aim to elucidate the multi-compound, multi-target effect of Xuesaitong injection. Fifteen potential targets of Xuesaitong injection associated with inflammation, angiogenesis, apoptosis, and coagulation were identified in this study. VEGF, IL-1beta and IL-6, three important targets in the compound-target network were further experimentally validated. This study provided experimental evidence for Xuesaitong injection being effective in treating RVO and a network view on its anti-RVO mode of action through a multi-compound and multiple-target mechanism.
Animals ; Drugs, Chinese Herbal ; administration & dosage ; Gene Regulatory Networks ; drug effects ; Humans ; Interleukin-6 ; genetics ; metabolism ; Male ; Rats ; Rats, Sprague-Dawley ; Retinal Vein Occlusion ; drug therapy ; genetics ; metabolism