A network pharmacology approach to determine active compounds and action mechanisms of ge-gen-qin-lian decoction for treatment of type 2 diabetes

Network Pharmacology-Based Study on the Mechanism of Gegen Qinlian Decoction against Colorectal Cancer

Purpose

Gegen Qinlian decoction (GQD) has been used to treat gastrointestinal diseases, such as diarrhea and ulcerative colitis (UC). A recent study demonstrated that GQD enhanced the effect of PD-1 blockade in colorectal cancer (CRC). This study used network pharmacology analysis to investigate the mechanisms of GQD as a potential therapeutic approach against CRC.

Materials and Methods

Bioactive chemical ingredients (BCIs) of GQD were collected from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. CRC-specific genes were obtained using the gene expression profile GSE110224 from the Gene Expression Omnibus (GEO) database. Target genes related to BCIs of GQD were then screened out. The GQD-CRC ingredient-target pharmacology network was constructed and visualized using Cytoscape software. A protein-protein interaction (PPI) network was subsequently constructed and analyzed with BisoGenet and CytoNCA plug-in in Cytoscape. Gene Ontology (GO) functional and the Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment analysis for target genes were then performed using the R package of clusterProfiler.

Results

One hundred and eighteen BCIs were determined to be effective on CRC, including quercetin, wogonin, and baicalein. Twenty corresponding target genes were screened out including PTGS2, CCNB1, and SPP1. Among these genes, CCNB1 and SPP1 were identified as crucial to the PPI network. A total of 212 GO terms and 6 KEGG pathways were enriched for target genes. Functional analysis indicated that these targets were closely related to pathophysiological processes and pathways such as biosynthetic and metabolic processes of prostaglandins and prostanoids, cytokine and chemokine activities, and the IL-17, TNF, Toll-like receptor, and nuclear factor-kappa B (NF-κB) signaling pathways.

Conclusion

The study elucidated the “multiingredient, multitarget, and multipathway” mechanisms of GQD against CRC from a systemic perspective, indicating GQD to be a candidate therapy for CRC treatment.

Exploring the potential therapeutic effect of traditional Chinese medicine on coronavirus disease 2019 (COVID-19) through a combination of data mining and network pharmacology analysis

Introduction

Historically traditional Chinese medicine (TCM) has been used as treatment during epidemics. During the recent COVID-19 pandemic patients evidence suggests that the use of TCM has provided health benefits and has been successfully used to control the spread of the disease in China. The aim of this study was to systematically explore the TCM formulae which have been used for the prevention and treatment of pneumonia or ‘pestilence’ to investigate their compatibility with the Chinese materia medica (CMM) and understand their potential mechanisms in the treatment of COVID-19.

Methods

Frequency analysis was performed to identify high-frequency CMM and CMM groups. Association rules analysis was applied to investigate the compatibility law of CMMs and generate the commonly used CMM groups.

Results

A total of 173 prescriptions were collected. The frequency analysis showed that seven out of ten high-frequency CMMs overlapped with Lianhua Qingwen Capsules (LHQWC), and five high-frequency pair-CMMs and four triple-CMMs were included in LHQWC, respectively. Then three groups of CMM were generated from association rules analysis, one of which is Ma Xing Shi Gan Decoction (MXSGD). The results of the protein-protein interaction network and enrichment analysis showed that the potential therapeutic mechanisms of the generated prescriptions were involved in the anti-inflammatory, anti-viral, and neuroprotective effects.

Conclusion

This study showed the importance of systematic research on TCM prescriptions and provided candidate CMM groups that have the potential to treat COVID-19. In vitro and in vivo experiments should be conducted to validate these network pharmacology results, which can provide more information for the development of potential antiviral drugs from TCM prescriptions. The combination of TCM treatment and modern medical approaches will benefit patients with COVID-19 and help to overcome the current epidemic.

Herbal Formula Gegen-Qinlian Decoction for Type 2 Diabetes Mellitus: A Meta-Analysis of Randomized Controlled Trials

Background

Herbal formula Gegen-Qinlian Decoction (GQD) has been widely used in China for the treatment of type 2 diabetes mellitus (T2DM), but its efficacy and safety are unclear.

Method

The studies were identified from the PubMed, EMBASE, Cochrane Library, China National Knowledge Infrastructure database, Wanfang database, and VIP database using the keywords “Gegenqinlian” or “Gegen-Qinlian” or “Gegen-Qin-Lian” or “Ge Gen Qin Lian.” Relevant studies were selected according to predefined inclusion and exclusion criteria. Study selection, data extraction, and validation were carried out by, at least, two reviewers with disagreements being settled by discussion.

Results

After literature search, a total of 26 randomized controlled trials were included with a total of 2553 patients. There was evidence that compared with metformin, the combination of GQD and metformin significantly reduced the fasting plasma glucose levels (MD −1.79, 95% CI (−2.31, −1.27), p < 0.00001); 2-hour postprandial plasma glucose levels (MD −1.72, 95% CI (−2.12, −1.31), p < 0.00001); and glycosylated hemoglobin levels (MD −1.26, 95% CI (−1.80, −0.72), p < 0.00001), and no serious side effects were identified.

Conclusion

These data suggest that GQD may be an effective herbal formula in treating T2DM without serious side effects. The addition of GQD also enhances the hypoglycemic effects of metformin. However, the evidence remains weak due to methodological flaws, which may amplify the therapeutic benefit of GQD.

A network pharmacology-based approach to explore potential targets of Caesalpinia pulcherima: an updated prototype in drug discovery

Caesalpinia pulcherima (CP) is a traditional herb used for the treatment of asthma, bronchitis, cancer, anti-bacterial, anti-fungal and as abortifacient. In the present study, bioactive components and potential targets in the treatment of breast cancer validated through in silico, in vitro and in vivo approach. The results for the analysis were as among 29 components, only four components were found active for further study which proved the use of CP as a multi-target herb for betterment of clinical uses. The results found by PPI states that our network has significant interactions which include the ESR-1, ESR-2, ESRRA, MET, VEGF, FGF, PI3K, PDK-1, MAPK, PLK-1, NEK-2, and GRK. Compound-target network involves 4 active compound and 150 target genes which elucidate the mechanisms of drug action in breast cancer treatment. Furthermore, on the basis of the above results the important proteins were fetched for the docking study which helps in predicting the possible interaction between components and targets. The results of the western blotting showed that CP regulates ER and EGFR expression in MCF-7 cell. In addition to this animal experimentation showed that CP significantly improved immunohistological status in MNU induced carcinoma rats. Network pharmacology approach not only helps us to confirm the study of the chosen target but also gave an idea of compound-target network as well as pathways associated to the CP for treating the complex metabolic condition as breast cancer and they importance for experimental verification.

The Effect of Hedysarum multijugum Maxim.-Chuanxiong rhizoma Compound on Ischemic Stroke: A Research Based on Network and Experimental Pharmacology

Background

Hedysarum multijugum Maxim.-Chuanxiong rhizoma compound (HCC) is a common herbal formula modified from Buyang Huanwu decoction. Clinical trials have demonstrated its therapeutic potential for ischemic stroke (IS). However, the mechanism of HCC remains unclear.

Methods

The HCC's components were collected from the TCMSP database and TCM@Taiwan database. After that, the HCC's compound targets were predicted by PharmMapper. The IS-related genes were obtained from GeneCards, and OMIM and the protein-protein interaction (PPI) data of HCC's targets and IS genes were obtained from the String database. After that, the DAVID platform was applied for Gene Ontology (GO) enrichment analysis and pathway enrichment analysis and the Cytoscape 3.7.2 was utilized to construct and analyze the networks. Finally, a series of animal experiments were carried out to validate the prediction results of network pharmacology. The expressions of GRP78, p-PERK, and CHOP proteins and mRNAs in different time periods after HCC intervention were detected by Western blot, immunohistochemistry, and RT-qPCR.

Results

A total of 440 potential targets and 388 IS genes were obtained. The results of HCC-IS PPI network analysis showed that HCC may regulate IS-related targets (such as ALB, AKT1, MMP9, IGF1, and CASP3), biological processes (such as endoplasmic reticulum stress, inflammation modules, hypoxia modules, regulation of neuronal apoptosis and proliferation, and angiogenesis), and signaling pathways (such as PI3K-Akt, FoxO, TNF, HIF-1, and Rap1 signaling). The animal experiments showed that HCC can improve the neurobehavioral scores and protect the neurons of IS rats (P < 0.05). HCC inhibited the expression of p-PERK in the PERK pathway from 12 h after surgery, significantly promoted the expression of GRP78 protein, and inhibited the expression of CHOP protein after surgery, especially at 24 h after surgery (P < 0.05). The results of RT-qPCR showed that HCC can significantly reduce the expression of CHOP mRNA in the neurons in the CA1 region of the hippocampus 72 h after MCAO (P < 0.05).

Conclusion

HCC may achieve a role in the treatment of IS by intervening in a series of targets, signaling pathways, and biological processes such as inflammation, oxidative stress, endoplasmic reticulum stress, and angiogenesis.

Mechanisms of indigo naturalis on treating ulcerative colitis explored by GEO gene chips combined with network pharmacology and molecular docking

Oral administration of indigo naturalis (IN) can induce remission in ulcerative colitis (UC); however, the underlying mechanism remains unknown. The main active components and targets of IN were obtained by searching three traditional Chinese medicine network databases such as TCMSP and five Targets fishing databases such as PharmMapper. UC disease targets were obtained from three disease databases such as DrugBank,combined with four GEO gene chips. IN-UC targets were identified by matching the two. A protein–protein interaction network was constructed, and the core targets were screened according to the topological structure. GO and KEGG enrichment analysis and bioGPS localization were performed,and an Herbs-Components-Targets network, a Compound Targets-Organs location network, and a Core Targets-Signal Pathways network were established. Molecular docking technology was used to verify the main compounds-targets. Ten core active components and 184 compound targets of IN-UC, of which 43 were core targets, were enriched and analyzed by bioGPS, GO, and KEGG. The therapeutic effect of IN on UC may involve activation of systemic immunity, which is involved in the regulation of nuclear transcription, protein phosphorylation, cytokine activity, reactive oxygen metabolism, epithelial cell proliferation, and cell apoptosis through Th17 cell differentiation, the Jak-STAT and IL-17 signaling pathways, toll-like and NOD-like receptors, and other cellular and innate immune signaling pathways. The molecular mechanism underlying the effect of IN on inducing UC remission was predicted using a network pharmacology method, thereby providing a theoretical basis for further study of the effective components and mechanism of IN in the treatment of UC.

The Active Compounds and Therapeutic Mechanisms of Pentaherbs Formula for Oral and Topical Treatment of Atopic Dermatitis Based on Network Pharmacology

To examine the molecular targets and therapeutic mechanism of a clinically proven Chinese medicinal pentaherbs formula (PHF) in atopic dermatitis (AD), we analyzed the active compounds and core targets, performed network and molecular docking analysis, and investigated interacting pathways. Information on compounds in PHF was obtained from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database, and target prediction was performed using the Drugbank database. AD-related genes were gathered using the GeneCards and Online Mendelian Inheritance in Man (OMIM) databases. Network analysis was performed by Cytoscape software and protein-protein interaction was analyzed by the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING). The Database for Annotation, Visualization and Integrated Discovery (DAVID) Bioinformatics Resources were applied for the enrichment analysis of the potential biological process and pathways associated with the intersection targets between PHF and AD. Autodock software was used to perform protein compound docking analysis. We identified 43 active compounds in PHF associated with 117 targets, and 57 active compounds associated with 107 targets that form the main pathways linked to oral and topical treatment of AD, respectively. Among them, quercetin, luteolin, and kaempferol are key chemicals targeting the core genes involved in the oral use of PHF against AD, while apigenin, ursolic acid, and rosmarinic acid could be used in topical treatment of PHF against AD. The compound–target–disease network constructed in the current study reveals close interactions between multiple components and multiple targets. Enrichment analysis further supports the biological processes and signaling pathways identified, indicating the involvement of IL-17 and tumor necrosis factor signaling pathways in the action of PHF on AD. Our data demonstrated the main compounds and potential pharmacological mechanisms of oral and topical application of PHF in AD.

Network Pharmacology to Uncover the Biological Basis of Spleen Qi Deficiency Syndrome and Herbal Treatment

Spleen qi deficiency (SQD) syndrome is one of the basic traditional Chinese medicine (TCM) syndromes related to various diseases including chronic inflammation and hypertension and guides the use of many herbal formulae. However, the biological basis of SQD syndrome has not been clearly elucidated due to the lack of appropriate methodologies. Here, we propose a network pharmacology strategy integrating computational, clinical, and experimental investigation to study the biological basis of SQD syndrome. From computational aspects, we used a powerful disease gene prediction algorithm to predict the SQD syndrome biomolecular network which is significantly enriched in biological functions including immune regulation, oxidative stress, and lipid metabolism. From clinical aspects, SQD syndrome is involved in both the local and holistic disorders, that is, the digestive diseases and the whole body's dysfunctions. We, respectively, investigate SQD syndrome-related digestive diseases including chronic gastritis and irritable bowel syndrome and the whole body's dysfunctions such as chronic fatigue syndrome and hypertension. We found innate immune and oxidative stress modules of SQD syndrome biomolecular network dysfunction in chronic gastritis patients and irritable bowel syndrome patients. Lymphocyte modules were downregulated in chronic fatigue syndrome patients and hypertension patients. From experimental aspects, network pharmacology analysis suggested that targets of Radix Astragali and other four herbs commonly used for SQD syndrome are significantly enriched in the SQD syndrome biomolecular network. Experiments further validated that Radix Astragali ingredients promoted immune modules such as macrophage proliferation and lymphocyte proliferation. These findings indicate that the biological basis of SQD syndrome is closely related to insufficient immune response including decreased macrophage activity and reduced lymphocyte proliferation. This study not only demonstrates the potential biological basis of SQD syndrome but also provides a novel strategy for exploring relevant molecular mechanisms of disease-syndrome-herb from the network pharmacology perspective.

Investigation of the Mechanism of Shengmai Injection on Sepsis by Network Pharmacology Approaches

Shengmai injection (SMI) contains Ginsen Radix et Rhizoma Rubra, Ophiopogon japonicus, and Schisandrae Chinensis Fructus. It is used as a supportive herbal medicine in the management of sepsis, systemic inflammatory response syndrome, and septic or hemorrhagic shock. An UPLC method was established to identify and evaluate SMI fingerprints. Fingerprint similarities of 9 batches of SMI were compared. The network platform, “TCM-components-core targets-key pathways,” was established, and the mechanism of SMI in the treatment of sepsis was investigated. The similarity of 9 batches of SMI fingerprints was greater than 0.91. 44 peaks were selected as the common peaks, of which 11 peaks were identified. KEGG functional pathway analysis showed SMI was mainly involved in the pathways of cancer, cell cycle, and p53 signaling, suggesting SMI protects multiple organs via regulating immunity, inflammation, apoptosis, and energy metabolism. GO enrichment analysis showed active SMI components regulated various biological processes and altered the pathophysiology of sepsis. The interplays between SMI and multiple energy metabolism signaling cascades confer protection from life-threatening multiple organ failure in sepsis.

Integrated bioinformatics analysis to decipher molecular mechanism of compound Kushen injection for esophageal cancer by combining WGCNA with network pharmacology

Compound Kushen injection (CKI), a medicine in widespread clinical use in China, has proven therapeutic effects on cancer. However, few molecular mechanism analyses have been carried out. To address this problem, bioinformatics approaches combining weighted gene co-expression network analysis with network pharmacology methods were undertaken to elucidate the underlying molecular mechanisms of CKI in the treatment of esophageal cancer (ESCA). First, the key gene modules related to the clinical traits of ESCA were analysed by WCGNA. Based on the results, the hub genes related to CKI treatment for ESCA were explored through network pharmacology. Molecular docking simulation was performed to recognize the binding activity of hub genes with CKI compounds. The results showed that the potential hub targets, including EGFR, ErbB2, CCND1 and IGF1R, are therapeutic targets of CKI for the treatment of ESCA. Moreover, these targets were significantly enriched in many pathways related to cancer and signalling pathways, such as the PI3K-Akt signalling pathway and ErbB signalling pathway. In conclusion, this research partially highlighted the molecular mechanism of CKI in the treatment of ESCA, offering great potential in the identification of the effective compounds in CKI and biomarkers for ESCA treatment.

Gegen Qinlian Decoction Ameliorates Hepatic Insulin Resistance by Silent Information Regulator1 (SIRT1)-Dependent Deacetylation of Forkhead Box O1 (FOXO1)

Background

Gegen qinlian decoction (GGQLD) is a form of traditional Chinese medicine used for hundreds of years for its efficacy in treating diabetes. However, the mechanisms underlying the therapeutic effects of GGQLD on diabetes are still not clear. We aimed to evaluate the effect of GGQLD on hepatic insulin resistance (IR) through silent information regulator1 (SIRT1)/forkhead box O1 (FOXO1) in an IR mouse model.

Material/Methods

A high-fat diet (HFD) mouse model was established and GGQLD was administrated by oral gavage. Metabolic parameters were detected, including body weights, triglyceride, fasting glucose, fasting insulin and HOMA-IR index, glucose intolerance, and insulin resistance. HE-stained sections were used to observe the histopathology of liver tissue. For in vitro study, GGQLD-medicated serum was used to treat palmitic acid-stimulated HepG2 cells. The glycogen synthesis and downstream SIRT1/FOXO1 signaling pathways were examined. Specific siRNAs were used to knock down SIRT1 in HepG2 cells.

Results

GGQLD administration significantly decreased body weights, triglyceride level, fasting glucose level, fasting insulin level, and HOMA-IR index, and improved IR in HFD mice. GGQLD enhanced SIRT1 expression and suppressed the expression of Ac-FOXO1 in liver tissues. Further, GGQLD-medicated serum promoted SIRT1 upregulation and suppressed Ac-FOXO1 levels in palmitate-stimulated HepG2 cells. GGQLD-medicated serum also increased the protein expression of PPARγ and reduced the expression of FABP4 in palmitate-stimulated HepG2 cells.

Conclusions

We found that GGQLD alleviates insulin resistance through SIRT1-dependent deacetylation of FOXO1.

Anil Kumar N, Sharopov F, Ramírez-Alarcón K, Ruiz-Ortega A, Abdulmajid Ayatollahi S, Valere Tsouh Fokou P, Kobarfard F, Amiruddin Zakaria Z, Iriti M, Taheri Y, Martorell M, Sureda A, N. Setzer W, Durazzo A, Lucarini M, Santini A, Capasso R, Adrian Ostrander E, -ur-Rahman A, Iqbal Choudhary M, C. Cho W, Sharifi-Rad J. Antidiabetic Potential of Medicinal Plants and Their Active Components

Diabetes mellitus is one of the major health problems in the world, the incidence and associated mortality are increasing. Inadequate regulation of the blood sugar imposes serious consequences for health. Conventional antidiabetic drugs are effective, however, also with unavoidable side effects. On the other hand, medicinal plants may act as an alternative source of antidiabetic agents. Examples of medicinal plants with antidiabetic potential are described, with focuses on preclinical and clinical studies. The beneficial potential of each plant matrix is given by the combined and concerted action of their profile of biologically active compounds.

A Network Pharmacology Approach Used to Estimate the Active Ingredients of Moutan Cortex Charcoal and the Potential Targets in Hemorrhagic Diseases

Moutan Cortex charcoal has been used to ameliorate blood heat symptoms and treat pathologic hemorrhage down the ages. Although well known as an agent with the effect of astringency and hemostasis, its active ingredients and action mechanism remain unclear. In the present study, molecular docking technology was employed to screen the potential hemostatic compounds in Moutan Cortex charcoal and their target proteins. Protein-protein-interaction (PPI) analysis was performed to explain the functions and enrichment pathways of the target proteins. The results showed that a total of 25 compounds were estimated as active constituents targeting multiple proteins related to hemostatic diseases, including 5 proteins (SERPINC1, FVIII, FX, FII and FXII) that were considered as the key targets. Then the drug-target (D-T) network was constructed to analyze the underlying hemostatic mechanism of Moutan Cortex charcoal, followed by a hierarchical cluster analysis (HCA) for compounds clustering, and a coagulation screening test for compound verification on their coagulation activities, with the results indicating that M15 (5-Tetradecenoic acid) and M31 (1-Monolinolein) might be the key compounds contributing to the hemostasis effect of Moutan Cortex charcoal by involving in the pathways related to complement, coagulation cascades and the platelet activation, particularly by activating FVIII, FX, FII and FXII and inhibiting SERPINC1. This study has demonstrated that Moutan Cortex charcoal may work as a hemostatic through the interaction between multiple-compounds and multiple-proteins, which provides the basis for further researches on the hemostasis mechanism of Moutan Cortex charcoal.

Utilising network pharmacology to explore the underlying mechanism of Wumei Pill in treating pancreatic neoplasms

Background

Wumei Pill (WMP), a famous herbal formula, has been widely used to treat digestive system diseases in clinical practice in China for centuries. We have found a correlation between the indications of WMP and the typical symptoms of pancreatic neoplasms. However, the pharmacological mechanisms of WMP still remain unknown.

Methods

In the present work, we used a network pharmacological method to predict its underlying complex mechanism of treating pancreatic neoplasms. Firstly, we obtained relative compounds of WMP based on TCMSP database, TCM database@Taiwan and TCMID database and collected potential targets of these compounds by target fishing. Then we built the pancreatic neoplasms target database by CTD, TTD, PharmGKB. Based on the matching results between WMP potential targets and pancreatic neoplasms targets, we built a PPI network to analyze the interactions among these targets and screen the hub targets by topology. Furthermore, DAVID bioinformatics resources were utilized for the enrichment analysis on GO_BP and KEGG.

Results

A total of 80 active ingredients and 77 targets of WMP were picked out. The results of DAVID enrichment analysis indicated that 58 cellular biological processes (FDR < 0.01) and 17 pathways (FDR < 0.01) of WMP mostly participated in the complex treating effects associated with proliferation, apoptosis, inflammatory response and angiogenesis. Moreover, 17 hub nodes of WMP (PTGS2, BCL2, TP53, IL6, MAPK1, EGFR, EGF, CASP3, JUN, MAPK8, MMP9, VEGFA, TNF, MYC, AKT1, FOS and TGFB1) were recognized as potential targets of treatments, implying the underlying mechanisms of WMP acting on pancreatic neoplasms.

Conclusion

WMP could alleviate the symptoms of pancreatic neoplasms through the molecular mechanisms predicted by network pharmacology. This study proposes a strategy to elucidate the mechanisms of Traditional Chinese Medicine (TCM) at the level of network pharmacology.

Electronic supplementary material

The online version of this article (10.1186/s12906-019-2580-y) contains supplementary material, which is available to authorized users.

The mechanism of mulberry leaves against renal tubular interstitial fibrosis through ERK1/2 signaling pathway was predicted by network pharmacology and validated in human tubular epithelial cells

Mulberry leaf was reported that it has antidiabetic activity, although the mechanisms underlying the function have not been fully elucidated. In the present study, the results of network pharmacology suggested that mulberry leaves could regulate key biological process in development of diabetes, and the process implicates multiple signaling pathways, such as JAK-STAT, MAPK, VEGF, PPAR, and Wnt. Then, the research in vitro indicated that mulberry leaves remarkably ameliorated high glucose-induced epithelial to mesenchymal transition, which was characterized with significant reduction of intracellular reactive oxygen species (ROS) levels as well as downregulation of NADPH oxidase subunits NOX1, NOX2, and NOX4, and it was found to be connected with the ERK1/2 signaling pathway in human tubular epithelial cells (HK-2). Moreover, the results of bioinformatics and the dual luciferase report showed that ZEB1 might be a target gene of miR-302a; decreased miR-302a and increased ZEB1 expressions could significantly promote epithelial to mesenchymal transition. However, mulberry leaves could reverse these modulations. Our results demonstrated that network pharmacology could provide a guidance role for traditional Chinese medicine research, and mulberry leaves could be of benefit in preventing high glucose-induced EMT in HK-2 cells, which proved that it was related to the upregulation of miR-302a by targeting ZEB1 and the inhibition of NADPH oxidase/ROS/ERK1/2 pathway.

Network Pharmacology Databases for Traditional Chinese Medicine: Review and Assessment

The research field of systems biology has greatly advanced and, as a result, the concept of network pharmacology has been developed. This advancement, in turn, has shifted the paradigm from a “one-target, one-drug” mode to a “network-target, multiple-component-therapeutics” mode. Network pharmacology is more effective for establishing a “compound-protein/gene-disease” network and revealing the regulation principles of small molecules in a high-throughput manner. This approach makes it very powerful for the analysis of drug combinations, especially Traditional Chinese Medicine (TCM) preparations. In this work, we first summarized the databases and tools currently used for TCM research. Second, we focused on several representative applications of network pharmacology for TCM research, including studies on TCM compatibility, TCM target prediction, and TCM network toxicology research. Third, we compared the general statistics of several current TCM databases and evaluated and compared the search results of these databases based on 10 famous herbs. In summary, network pharmacology is a rational approach for TCM studies, and with the development of TCM research, powerful and comprehensive TCM databases have emerged but need further improvements. Additionally, given that several diseases could be treated by TCMs, with the mediation of gut microbiota, future studies should focus on both the microbiome and TCMs to better understand and treat microbiome-related diseases.

Comparing the antidiabetic effects and chemical profiles of raw and fermented Chinese Ge-Gen-Qin-Lian decoction by integrating untargeted metabolomics and targeted analysis

Background

Microbial fermentation has been widely applied in traditional Chinese medicine (TCM) for thousands of years in China. Various beneficial effects of fermentation for applications in TCM or herbals have been reported, such as enhanced anti-ovarian cancer, antioxidative activity, and neuroprotective effects. Ge-Gen-Qin-Lian decoction (GQD), a classic TCM formula, has been used to treat type 2 diabetes mellitus in China. In this study, GQD was fermented with Saccharomyces cerevisiae, and the antidiabetic activities and overall chemical profiles of raw and fermented GQD (FGQD) were systematically compared.

Methods

First, the antidiabetic effects of GQD and FGQD on high-fat diet and streptozotocin (STZ)-induced diabetic rats were compared. Then, high-performance liquid chromatography Q Exactive MS was applied for rapid characterization of the chemical components of GQD. Additionally, we proposed an integrated chromatographic technique based untargeted metabolomics identifying differential chemical markers between GQD and FGQD and targeted analysis determining the fermenting-induced quantitative variation tendencies of chemical marker strategy for overall chemical profiling of raw and fermented GQD.

Results

Both GQD and FGQD displayed effects against HFD and STZ-induced diabetes, and FGQD showed a better recovery trend associated with profound changes in the serum lipoprotein profile and body weight gain. In addition, 133 compounds were characterized from GQD. It was demonstrated that the integrated strategy holistically illuminated 30 chemical markers contributed to the separation of GQD and FGQD, and further elucidated the fermenting-induced chemical transformation mechanisms and inherent chemical connections of secondary metabolites. Although there were no new secondary metabolites in FGQD compared with GQD, the amounts of secondary metabolites, which were mostly deglycosylated, were redistributed in FGQD.

Conclusion

The anti-diabetic activities of GQD could be improved by applying fermentation technology. Moreover, the proposed strategy could serve as a powerful tool for systematically exploring the chemical profiles of raw and fermented formulas.

Electronic supplementary material

The online version of this article (10.1186/s13020-018-0208-7) contains supplementary material, which is available to authorized users.

A Computational Systems Pharmacology Approach to Investigate Molecular Mechanisms of Herbal Formula Tian-Ma-Gou-Teng-Yin for Treatment of Alzheimer's Disease

Traditional Chinese medicine (TCM) is typically prescribed as formula to treat certain symptoms. A TCM formula contains hundreds of chemical components, which makes it complicated to elucidate the molecular mechanisms of TCM. Here, we proposed a computational systems pharmacology approach consisting of network link prediction, statistical analysis, and bioinformatics tools to investigate the molecular mechanisms of TCM formulae. Taking formula Tian-Ma-Gou-Teng-Yin as an example, which shows pharmacological effects on Alzheimer’s disease (AD) and its mechanism is unclear, we first identified 494 formula components together with corresponding 178 known targets, and then predicted 364 potential targets for these components with our balanced substructure-drug–target network-based inference method. With Fisher’s exact test and statistical analysis we identified 12 compounds to be most significantly related to AD. The target genes of these compounds were further enriched onto pathways involved in AD, such as neuroactive ligand–receptor interaction, serotonergic synapse, inflammatory mediator regulation of transient receptor potential channel and calcium signaling pathway. By regulating key target genes, such as ACHE, HTR2A, NOS2, and TRPA1, the formula could have neuroprotective and anti-neuroinflammatory effects against the progression of AD. Our approach provided a holistic perspective to study the relevance between TCM formulae and diseases, and implied possible pharmacological effects of TCM components.

Chinese herbal formula Fuzheng Huayu alleviates CCl4-induced liver fibrosis in rats: a transcriptomic and proteomic analysis

Liver fibrosis is a consequence of chronic liver disease that can progress to liver cirrhosis or even hepatocarcinoma. Fuzheng Huayu (FZHY), a Chinese herbal formula, has been shown to exert anti-fibrotic effects. To better understand the molecular mechanisms underlying the anti-fibrotic effects of FZHY, we analyzed transcriptomic and proteomic combination profiles in CCl₄-induced liver fibrosis in rats, which were treated with extracted FZHY powder (0.35 g·kg^-1·d^-1, ig) for 3 weeks. We showed that FZHY administration significantly improved liver function, alleviated hepatic inflammatory and fibrotic changes, and decreased the hydroxyproline content in the livers of CCl₄-treated rats. When their liver tissues were examined using microarray and iTRAQ, we found 255 differentially expressed genes (fold change ≥1.5, P<0.05) and 499 differentially expressed proteins (fold change ≥1.2, P<0.05) in the FZHY and model groups. Functional annotation with DAVID (The Database for Annotation, Visualization and Integrated Discovery) showed that 15 enriched gene ontology terms, including drug metabolic process, response to extracellular stimulus, response to vitamins, arachidonic acid metabolic process, response to wounding, and oxidation reduction might be involved in the anti-fibrotic effects of FZHY; whereas KEGG pathway analysis revealed that eight enriched pathways, including arachidonic acid metabolism, retinol metabolism, metabolism of xenobiotics by cytochrome P450, and drug metabolism might also be involved. Moreover, the protein-protein interaction network demonstrated that 10 core genes/proteins overlapped, with Ugt2a3, Cyp2b1 and Cyp3a18 in retinol metabolism pathway overlapped to a higher degree. Compared to the model rats, the livers of FZHY-treated rats had significantly higher mRNA and protein expression levels of Ugt2a3, Cyp2b1 and Cyp3a18. Furthermore, the concentration of retinoic acid was significantly higher in the FZHY-treated rats compared with the model rats. The results suggest that the anti-fibrotic effects of FZHY emerge through multiple targets, multiple functions, and multiple pathways, including FZHY-regulated retinol metabolism, xenobiotic metabolism by cytochrome P450, and drug metabolism through up-regulated Ugt2a3, Cyp2b1, and Cyp3a18. These genes may play important anti-fibrotic roles in FZHY-treated rats.

The Effect of Sanggua Drink Extract on Insulin Resistance through the PI3K/AKT Signaling Pathway

Treating type 2 diabetes mellitus (T2DM) using thiazolidinediones and biguanides can present several challenges for patients. Sanggua Drink (SGD) is a commonly used agent in traditional Chinese medicine, and it consists of Folium Mori, Fructus Momordicae Charantiae, Radix Puerariae Lobatae, and Rhizoma Dioscorea. The hypoglycemic effects and mechanisms of SGD extracts on insulin resistance in diabetic rats were investigated. SGD (1.24 g/kg orally) was verified in T2DM rats induced by a high-fat diet and streptozotocin. The results showed that SGD treatment was observed to reduce fasting blood glucose, water and food intake, total cholesterol triglycerides, and LDL, OGTT, FINS, HOMA-IR, GHb, and MDA and increase hepatic glycogen, HDL, SOD, CAT, and GSH-Px in diabetic rats. Simultaneously, SGD treatment by T2DM showed significantly ameliorated pathological changes and reduced inflammation in the pancreas. Treatment was also observed to increase gene and protein expressions of InsR, IRS-2, PI3K, AKT, and Glut4 in the livers of diabetic treated rats. These results suggest that SGD extracts have hypoglycemic properties and may alleviate insulin resistance in T2DM rats through the PI3K/AKT pathway. Therefore, SGD appears to be a promising insulin sensitizer.

Matrine Is Identified as a Novel Macropinocytosis Inducer by a Network Target Approach

Comprehensively understanding pharmacological functions of natural products is a key issue to be addressed for the discovery of new drugs. Unlike some single-target drugs, natural products always exert diverse therapeutic effects through acting on a "network" that consists of multiple targets, making it necessary to develop a systematic approach, e.g., network pharmacology, to reveal pharmacological functions of natural products and infer their mechanisms of action. In this work, to identify the "network target" of a natural product, we perform a functional analysis of matrine, a marketed drug in China extracted from a medical herb Ku-Shen (Radix Sophorae Flavescentis). Here, the network target of matrine was firstly predicted by drugCIPHER, a genome-wide target prediction method. Based on the network target of matrine, we performed a functional gene set enrichment analysis to computationally identify the potential pharmacological functions of matrine, most of which are supported by the literature evidence, including neurotoxicity and neuropharmacological activities of matrine. Furthermore, computational results demonstrated that matrine has the potential for the induction of macropinocytosis and the regulation of ATP metabolism. Our experimental data revealed that the large vesicles induced by matrine are consistent with the typical characteristics of macropinosome. Our verification results also suggested that matrine could decrease cellular ATP level. These findings demonstrated the availability and effectiveness of the network target strategy for identifying the comprehensive pharmacological functions of natural products.

Bioinformatics facilitating the use of microarrays to delineate potential miRNA biomarkers in aristolochic acid nephropathy

Aristolochic acid nephropathy (AAN) is a rapidly progressive acute or chronic tubulointerstitial nephritis (TIN). The present study attempted to explore the molecular mechanisms underlying the miRNA-directed development of AAN. Our differentially expressed analysis identified 11 DE-miRNAs and retrieved the target genes of these DE-miRNAs; then, network analysis and functional analysis further identified 6 DE-miRNAs (has-miR-192, has-miR-194, has-miR-542-3p, has-miR-450a, has-miR-584, has-miR-33a) as phenotypic biomarkers of AAN. Surprisingly, of has-miR-192 has been reported to be associated with the pathogenesis of AAN, and has-miR-194, has-miR-542-3p and has-miR-450a was first-time identified to link to the development of AAN. In addition, the expressional changes of has-miR-584 and has-miR-33a may be associated with the development of AAN as well, which must be further confirmed by the associated experiments. Taken together, our work reveals for the first time the regulatory mechanisms of miRNAs in the development of AAN and this will contribute to miRNA-based diagnosis and treatment of AAN.

A census of P. longum's phytochemicals and their network pharmacological evaluation for identifying novel drug-like molecules against various diseases, with a special focus on neurological disorders

Piper longum (P. longum, also called as long pepper) is one of the common culinary herbs that has been extensively used as a crucial constituent in various indigenous medicines, specifically in traditional Indian medicinal system known as Ayurveda. For exploring the comprehensive effect of its constituents in humans at proteomic and metabolic levels, we have reviewed all of its known phytochemicals and enquired about their regulatory potential against various protein targets by developing high-confidence tripartite networks consisting of phytochemical—protein target—disease association. We have also (i) studied immunomodulatory potency of this herb; (ii) developed subnetwork of human PPI regulated by its phytochemicals and could successfully associate its specific modules playing important role in diseases, and (iii) reported several novel drug targets. P10636 (microtubule-associated protein tau, that is involved in diseases like dementia etc.) was found to be the commonly screened target by about seventy percent of these phytochemicals. We report 20 drug-like phytochemicals in this herb, out of which 7 are found to be the potential regulators of 5 FDA approved drug targets. Multi-targeting capacity of 3 phytochemicals involved in neuroactive ligand receptor interaction pathway was further explored via molecular docking experiments. To investigate the molecular mechanism of P. longum’s action against neurological disorders, we have developed a computational framework that can be easily extended to explore its healing potential against other diseases and can also be applied to scrutinize other indigenous herbs for drug-design studies.

How Can Synergism of Traditional Medicines Benefit from Network Pharmacology?

Many prescriptions of traditional medicines (TMs), whose efficacy has been tested in clinical practice, have great therapeutic value and represent an excellent resource for drug discovery. Research into single compounds of TMs, such as artemisinin from Artemisia annua L., has achieved great success; however, it has become evident that a TM prescription (which frequently contains various herbs or other components) has a synergistic effect in effecting a cure or reducing toxicity. Network pharmacology targets biological networks and analyzes the links among drugs, targets, and diseases in those networks. Comprehensive, systematic research into network pharmacology is consistent with the perspective of holisticity, which is a main characteristic of many TMs. By means of network pharmacology, research has demonstrated that many a TM show a synergistic effect by acting at different levels on multiple targets and pathways. This approach effectively bridges the gap between modern medicine and TM, and it greatly facilitates studies into the synergistic actions of TMs. There are different kinds of synergistic effects with TMs, such as synergy among herbs, effective parts, and pure compounds; however, for various reasons, new drug discovery should at present focus on synergy among pure compounds.

A Biomedical Investigation of the Hepatoprotective Effect of Radix salviae miltiorrhizae and Network Pharmacology-Based Prediction of the Active Compounds and Molecular Targets

Radix salviae miltiorrhizae (Danshen in Chinese), a classic traditional Chinese medicine (TCM) herb, has been used for centuries to treat liver diseases. In this study, the preventive and curative potential of Danshen aqueous extract on acute/chronic alcoholic liver disease (ALD) and non-alcoholic fatty liver disease (NAFLD) was studied. The in vivo results indicated that Danshen could alleviate hepatic inflammation, fatty degeneration, and haptic fibrogenesis in ALD and NAFLD models. In the aspect of mechanism of action, the significant reduction in MDA levels in both ALD and NAFLD models implies the decreased levels of oxidative stress by Danshen. However, Danshen treatment could not activate the internal enzymatic antioxidant system in ALD and NAFLD models. To further explore the hepatoprotective mechanism of Danshen, an in silico-based network pharmacology approach was employed in the present study. The pharmacological network analysis result revealed that six potential active ingredients such as tanshinone iia, salvianolic acid b, and Danshensu may contribute to the hepatoprotective effects of Danshen on ALD and NAFLD. The action mechanism may relate with regulating the intracellular molecular targets such as PPARα, CYP1A2, and MMP2 for regulation of lipid metabolism, antioxidant and anti-fibrogenesis by these potential active ingredients. Our studies suggest that the combination of network pharmacology strategy with in vivo experimental study may provide a forceful tool for exploring the mechanism of action of traditional Chinese medicine (TCM) herb and developing novel bioactive ingredients.

Network Pharmacology Studies on the Bioactive Compounds and Action Mechanisms of Natural Products for the Treatment of Diabetes Mellitus: A Review

Diabetes mellitus (DM) is a kind of chronic and metabolic disease, which can cause a number of diseases and severe complications. Network pharmacology approach is introduced to study DM, which can combine the drugs, target proteins and disease and form drug-target-disease networks. Network pharmacology has been widely used in the studies of the bioactive compounds and action mechanisms of natural products for the treatment of DM due to the multi-components, multi-targets, and lower side effects. This review provides a balanced and comprehensive summary on network pharmacology from current studies, highlighting different bioactive constituents, related databases and applications in the investigations on the treatment of DM especially type 2. The mechanisms related to type 2 DM, including α-amylase and α-glucosidase inhibitory, targeting β cell dysfunction, AMPK signal pathway and PI3K/Akt signal pathway are summarized and critiqued. It suggests that the network pharmacology approach cannot only provide a new research paradigm for natural products, but also improve the current antidiabetic drug discovery strategies. Furthermore, we put forward the perspectives on the reasonable applications of network pharmacology for the therapy of DM and related drug discovery.

Natural formulas and the nature of formulas: Exploring potential therapeutic targets based on traditional Chinese herbal formulas

By comparing the target proteins (TPs) of classic traditional Chinese medicine (TCM) herbal formulas and modern drugs used for treating coronary artery disease (CAD), this study aimed to identify potential therapeutic TPs for treating CAD. Based on the theory of TCM, the Xuefu-Zhuyu decoction (XZD) and Gualou-Xiebai-Banxia decoction (GXBD), both of which are classic herbal formulas, were selected for treating CAD. Data on the chemical ingredients and corresponding TPs of the herbs in these two formulas and data on modern drugs approved for treating CAD and related TPs were retrieved from professional TCM and bioinformatics databases. Based on the associations between the drugs or ingredients and their TPs, the TP networks of XZD, GXBD, and modern drugs approved for treating CAD were constructed separately and then integrated to create a complex master network in which the vertices represent the TPs and the edges, the ingredients or drugs that are linked to the TPs. The reliability of this master network was validated through statistical tests. The common TPs of the two herbal formulas have a higher possibility of being targeted by modern drugs in comparison with the formula-specific TPs. A total of 114 common XZD and GXBD TPs that are not yet the target of modern drugs used for treating CAD should be experimentally investigated as potential therapeutic targets for treating CAD. Among these TPs, the top 10 are NOS3, PTPN1, GABRA1, PRKACA, CDK2, MAOB, ESR1, ADH1C, ADH1B, and AKR1B1. The results of this study provide a valuable reference for further experimental investigations of therapeutic targets for CAD. The established method shows promise for searching for potential therapeutic TPs based on herbal formulas. It is crucial for this work to select beneficial therapeutic targets of TCM, typical TCM syndromes, and corresponding classic formulas.

The anti-hyperglycemic efficacy of a lipid-lowering drug Daming capsule and the underlying signaling mechanisms in a rat model of diabetes mellitus

Diabetes mellitus (DM) is a metabolic disorder manifested by hyperglycemia. Daming Capsule (DMC), a combination of traditional Chinese herbs, is used clinically as a lipid-lowering drug. This study was designed to evaluate if DMC possesses an anti-hyperglycemic effect and to elucidate the underlying mechanisms. Compared to diabetic rats, the rats received DMC (200 mg/kg/d) had significantly lower blood lipid and glucose levels. DMC markedly restored the decreased secretion of GLP-1 and GIP as well as the coding gene GCG and GIP in ileum. Moreover, DMC normalized depressed GCG and GIP transcription by significantly enhancing the GSK-3β/β-catenin signaling pathway and expression of TCF7L2, a transactivator of GCG and GIP in diabetic rats. DMC possesses an anti-hyperglycemic property characterized by preservation/stimulation of GLP-1 and GIP secretion in DM rats. Here, we proposed DMC → GSK-3β/β-catenin↑ → TCF7L2↑ → GLP-1, GIP secretion↑ → blood glucose↓ as a regulatory pathway of blood glucose homeostasis. Our findings suggest DMC as a promising therapeutic drug in the clinical treatment of diabetes.

Network pharmacology-based prediction of the active ingredients and potential targets of Mahuang Fuzi Xixin decoction for application to allergic rhinitis

ETHNOPHARMACOLOGICAL RELEVANCE

Certain herbal formulae from Traditional Chinese Medicine (TCM) are effective for treating and preventing diseases in clinical practice. Mahuang fuzi Xixin Decoction (MFXD) is a TCM that is used to treat allergic rhinitis (AR); however, the active ingredients and potential targets of its action against AR remain unclear. Therefore, further investigation is required.

METHODS

A network pharmacology approach comprising drug-likeness evaluation, oral bioavailability prediction, multiple drug target prediction, and network analysis has been used in this study.

RESULTS

The comprehensive systematic approach was successfully to indentify 41 bioactive ingredients in MFXD, while 37 potential targets hit by these ingredients related to AR. Moreover, wherein four predicted ingredients possess anti-inflammatory effects were found by this technique.

CONCLUSIONS

Our works successfully predict the active ingredients and potential targets of MFXD for application to allergic rhinitis and helps to illustrate mechanism of action on a systematic level. This study not only provides new insights into the chemical basis and pharmacology of MFXD but also demonstrates a feasible method for discovering potential drugs from herbal medicine.

Tetramethylpyrazine identified by a network pharmacology approach ameliorates methotrexate-induced oxidative organ injury

ETHNOPHARMACOLOGICAL RELEVANCE

Tetramethylpyrazine (TMP) is one of the active constituents extracted from a frequently used herb, Ligusticum wallichii Franchat (Chuan-Xiong in Chinese), in traditional Chinese medicine. TMP can exert multiple pharmacological actions such as anti-inflammatory, anti-oxidative damage, anti-platelet and neuroprotective effects, and its applications deserve further explored.

AIM OF THE STUDY

This study aimed to determine the new role of TMP identified by a network pharmacology approach to alleviate the methotrexate (MTX)-induced oxidative injury and characterize their mechanism of combinational actions.

MATERIALS AND METHODS

A network pharmacology-based screening strategy is applied for target profile prediction and pharmacological characterization of herbal compounds, which is used to guide the following in vitro and in vivo experiments. The effect of herbal compounds identified by network pharmacology approaches to reduce the toxicity of MTX was assessed by MTX-induced rat toxicity model. The potential targets of TMP in this study were evaluated using standard protocols provided by Cerep, Inc.

RESULTS

This strategy identified TMP from Ligusticum wallichii Franchat as a potent compound for ameliorating the oxidative organ injury of MTX. According to the predicted target profiles of TMP, a possible mechanism of the abrogation of MTX-induced toxicity is that TMP could upregulate cAMP by inhibiting phosphodiesterase (PDE) 10A2 activity. Another novel finding is that the competitive binding and antagonistic effects of TMP on adenosine receptor 2A and 2B appear to play important roles in the TMP-mediated reversal of MTX-induced hepatic injury.

CONCLUSION

TMP identified by a network pharmacology approach could ameliorate MTX-induced oxidative organ injury. This study provides important evidence for the preclinical evaluation of TMP and MTX as a novel combinatorial remedy.

Prediction and Characterisation of the System Effects of Aristolochic Acid: A Novel Joint Network Analysis towards Therapeutic and Toxicological Mechanisms

Aristolochic acid (AA) is the major active component of medicinal plants from the Aristolochiaceae family of flowering plants widely utilized for medicinal purposes. However, the molecular mechanisms of AA systems effects remain poorly understood. Here, we employed a joint network analysis that combines network pharmacology, a protein–protein interaction (PPI) database, biological processes analysis and functional annotation analysis to explore system effects. Firstly, we selected 15 protein targets (14 genes) in the PubChem database as the potential target genes and used PPI knowledge to incorporate these genes into an AA-specific gene network that contains 129 genes. Secondly, we performed biological processes analysis for these AA-related targets using ClueGO, some of new targeted genes were randomly selected and experimentally verified by employing the Quantitative Real-Time PCR assay for targeting the systems effects of AA in HK-2 cells with observed dependency of concentration. Thirdly, the pathway-based functional enrichment analysis was manipulated using WebGestalt to identify the mostly significant pathways associated with AA. At last, we built an AA target pathway network of significant pathways to predict the system effects. Taken together, this joint network analysis revealed that the systematic regulatory effects of AA on multidimensional pathways involving both therapeutic action and toxicity.

The potential of translational bioinformatics approaches for pharmacology research

The field of bioinformatics has allowed the interpretation of massive amounts of biological data, ushering in the era of 'omics' to biomedical research. Its potential impact on pharmacology research is enormous and it has shown some emerging successes. A full realization of this potential, however, requires standardized data annotation for large health record databases and molecular data resources. Improved standardization will further stimulate the development of system pharmacology models, using translational bioinformatics methods. This new translational bioinformatics paradigm is highly complementary to current pharmacological research fields, such as personalized medicine, pharmacoepidemiology and drug discovery. In this review, I illustrate the application of transformational bioinformatics to research in numerous pharmacology subdisciplines.

Deciphering the therapeutic mechanisms of Xiao-Ke-An in treatment of type 2 diabetes in mice by a Fangjiomics approach

AIM

Xiao-Ke-An (XKA) is a traditional Chinese medicine (TCM) formula for the treatment of type 2 diabetes (T2D), and the effective ingredients and their targets as well as the mechanisms of XKA remain to be elucidated. In this study we investigated the therapeutic mechanisms of XKA in the treatment of T2D in mice using a Fangjiomics approach.

METHODS

KKAy mice feeding on a high-fat diet were used as models of T2D, and were orally treated with XKA (0.75 or 1.5 g · kg(-1) · d(-1)) for 32 d. Microarray mRNA expression data were obtained from the livers of the mice. Differentially expressed genes (DEGs) were identified by reverse rate analysis and ANOVA analysis. The compounds in XKA were identified by LC-MS analysis or collected from TCM databases. The relationships between the compounds and targets were established by combining the DEGs with information derived from mining literature or herb target databases. Relevant pathways were identified through a Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis using WebGestalt.

RESULTS

The compound-target-pathway network based on compounds identified by LC-MS analysis (NCA) included 20 constituent compounds, 46 targets and 36 T2D-related pathways, whereas the compound-target-pathway network based on compounds collected from databases (NCD) consisted of 40 compounds, 68 targets and 21 pathways. In the treatment of T2D, XKA might act mainly by improving carbohydrate and lipid metabolism, as well as ameliorating insulin resistance, inflammation and diabetic vascular complications.

CONCLUSION

The network-based approach reveals complex therapeutic mechanisms of XKA in the treatment of T2D in mice that involve numerous compounds, targets, and signaling pathways.

A modularity-based method reveals mixed modules from chemical-gene heterogeneous network

For a multicomponent therapy, molecular network is essential to uncover its specific mode of action from a holistic perspective. The molecular system of a Traditional Chinese Medicine (TCM) formula can be represented by a 2-class heterogeneous network (2-HN), which typically includes chemical similarities, chemical-target interactions and gene interactions. An important premise of uncovering the molecular mechanism is to identify mixed modules from complex chemical-gene heterogeneous network of a TCM formula. We thus proposed a novel method (MixMod) based on mixed modularity to detect accurate mixed modules from 2-HNs. At first, we compared MixMod with Clauset-Newman-Moore algorithm (CNM), Markov Cluster algorithm (MCL), Infomap and Louvain on benchmark 2-HNs with known module structure. Results showed that MixMod was superior to other methods when 2-HNs had promiscuous module structure. Then these methods were tested on a real drug-target network, in which 88 disease clusters were regarded as real modules. MixMod could identify the most accurate mixed modules from the drug-target 2-HN (normalized mutual information 0.62 and classification accuracy 0.4524). In the end, MixMod was applied to the 2-HN of Buchang naoxintong capsule (BNC) and detected 49 mixed modules. By using enrichment analysis, we investigated five mixed modules that contained primary constituents of BNC intestinal absorption liquid. As a matter of fact, the findings of in vitro experiments using BNC intestinal absorption liquid were found to highly accord with previous analysis. Therefore, MixMod is an effective method to detect accurate mixed modules from chemical-gene heterogeneous networks and further uncover the molecular mechanism of multicomponent therapies, especially TCM formulae.

Network pharmacology-based antioxidant effect study of zhi-zi-da-huang decoction for alcoholic liver disease

Zhi-Zi-Da-Huang decoction (ZZDHD), a classic traditional Chinese medicine (TCM) formula, has been used for centuries to treat alcoholic liver disease. Reliable therapeutics of ZZDHD has also been validated in clinical practice. In this study, molecular docking and network analysis were carried out to explore the antioxidative mechanism of ZZDHD as an effective therapeutic approach to treat alcoholic liver disease. Multiple active compounds of ZZDHD were screened based on four key original enzymes (cytochrome P450 2E1, xanthine oxidase, inducible nitric oxide synthase, and cyclooxygenase-2) involved in ethanol-induced oxidative stress damage. A drug-target network was constructed through network pharmacology analysis, which predicted the relationships of active ingredients to the targets. Some results had been verified by the previous experimental pharmacological studies; meanwhile, it was first reported that xanthine oxidase and eriocitrin, neoeriocitrin, isorhoifolin, and poncirin had interactions. The network pharmacology strategy used provided a forceful tool for searching the mechanism of action of TCM formula and novel bioactive ingredients.

Integrating traditional Chinese medicine healthcare into diabetes care by reducing the risk of developing kidney failure among type 2 diabetic patients: a population-based case control study

ETHNOPHARMACOLOGICAL RELEVANCE

Our previous study indicated that the traditional Chinese medicine (TCM) formula Liu-Wei-Di-Huang-Wan, which consists of six type of herbs, namely Rehmannia glutinosa (Gaertn.) DC., root, dried; Cornus officinalis Siebold & Zucc., fructus, dried; Dioscorea oppositifolia L., root, dried; Alisma plantago-aquatica subsp. orientale (Sam.) Sam., tuber, dried; Paeonia × suffruticosa Andrews, bark, dried; Poria cocos (Fr.) Wolf., sclerotium, dried, is the most frequently prescribed herbal formula used to treat type 2 diabetes patients. The aim of the study was to evaluate the integration of TCM into diabetes care in terms of how it reduces the risk of developing kidney failure.

MATERIALS AND METHODS

The Taiwan׳s National Health Insurance Research Database (NHIRD) provided detailed information of health care services for each patient and covers 98% of all Taiwan residents as of 2007. Case and control subjects were selected from the NHIRD. Two multivariable logistic regression models were constructed in order to explore two types of exposure assessments including prescription of TCMs (model 1) and prescription of different estimated dosages of Liu-Wei-Di-Huang-Wan (model 2).

RESULTS

Using logistic regression model 1, having used TCMs was independently associated with a decreased risk of kidney failure by multivariable analysis (OR=0.69, 95% CI: 0.61-0.77). Using logistic regression model 2, there was no difference between non-Liu-Wei-Di-Huang-Wan TCM users and Liu-Wei-Di-Huang-Wan TCM users in terms of the risk of developing kidney failure. Furthermore, there was also no linear dose-response trend when we used exposure to prescribed Liu-Wei-Di-Huang-Wan as a continuous variable (for non-Liu-Wei-Di-Huang-Wan TCM users, OR=0.68, 95% CI: 0.60-0.77; for TCM users consuming 1-30 g of Liu-Wei-Di-Huang-Wan, OR=0.69, 95% CI: 0.54-0.87; for >30 g of Liu-Wei-Di-Huang-Wan, OR=0.84, 95% CI: 0.49-1.44).

CONCLUSIONS

Integrating TCM healthcare into diabetes care was found to be associated with a decreased risk of developing kidney failure. Having recognized the use of TCM, exploring any potential interactions and adverse effects, and integrating both technologies into a holistic treatment system may be beneficial to the relief of diabetic nephropathy on patients with type 2 diabetes.