Hepatocellular carcinoma (HCC) is a kind of complicated disease with an increasing incidence all over the world. A classic Chinese medicine formula, Zuojin pill (ZJP), was shown to exert therapeutic effects on HCC. However, its chemical and pharmacological profiles remain to be elucidated. In the current study, network pharmacology approach was applied to characterize the action mechanism of ZJP on HCC. All compounds were obtained from the corresponding databases, and active compounds were selected according to their oral bioavailability and drug-likeness index. The potential proteins of ZJP were obtained from the traditional Chinese medicine systems pharmacology (TCMSP) database and the traditional Chinese medicine integrated database (TCMID), whereas the potential genes of HCC were obtained from OncoDB.HCC and Liverome databases. The potential pathways related to genes were determined by gene ontology (GO) and pathway enrichment analyses. The compound-target and target-pathway networks were constructed. Subsequently, the potential underlying action mechanisms of ZJP on HCC predicted by the network pharmacology analyses were experimentally validated in HCC cellular and orthotopic HCC implantation murine models. A total of 224 components in ZJP were obtained, among which, 42 were chosen as bioactive components. The compound-target network included 32 compounds and 86 targets, whereas the target-pathway network included 70 proteins and 75 pathways. The in vitro and in vivo experiments validated that ZJP exhibited its prominent therapeutic effects on HCC mainly via the regulation of cell proliferation and survival though the EGFR/MAPK, PI3K/NF-κB, and CCND1 signaling pathways. In conclusion, our study suggested combination of network pharmacology prediction with experimental validation may offer a useful tool to characterize the molecular mechanism of traditional Chinese medicine (TCM) ZJP on HCC.

Yinchenhao decoction (YCHD) is a traditional Chinese medicine formulation, which has been widely used for the treatment of jaundice for 2,000 years. Currently, YCHD is used to treat various liver disorders and metabolic diseases, however its chemical/pharmacologic profiles remain to be elucidated. The present study identified the active compounds and significant pathways of YCHD based on network pharmacology. All of the chemical ingredients of YCHD were retrieved from the Traditional Chinese Medicine Systems Pharmacology database. Absorption, distribution, metabolism and excretion screening with oral bioavailability (OB) screening, drug-likeness (DL) and intestinal epithelial permeability (Caco-2) evaluation were applied to discover the bioactive compounds in YCHD. Following this, target prediction, pathway identification and network construction were employed to clarify the mechanism of action of YCHD. Following OB screening, and evaluation of DL and Caco-2, 34 compounds in YCHD were identified as potential active ingredients, of which 30 compounds were associated with 217 protein targets. A total of 31 significant pathways were obtained by performing enrichment analyses of 217 proteins using the JEPETTO 3.x plugin, and 16 classes of gene-associated diseases were revealed by performing enrichment analyses using Database for Annotation, Visualization and Integrated Discovery v6.7. The present study identified potential active compounds and significant pathways in YCHD. In addition, the mechanism of action of YCHD in the treatment of various diseases through multiple pathways was clarified.

Herbal medicines are widely used for treating liver diseases and generally regarded as safe due to their extensive use in Traditional Chinese Medicine practice for thousands of years. However, in recent years, there have been increased concerns regarding the long-term risk of Herb-Induced Liver Injury (HILI) in patients with liver dysfunction. Herein, two representative Chinese herbal medicines: one—Xiao-Chai-Hu-Tang (XCHT)—a composite formula, and the other—Radix Polygoni Multiflori (Heshouwu)—a single herb, were analyzed by network pharmacology study. Based on the network pharmacology framework, we exploited the potential HILI effects of XCHT and Heshouwu by predicting the molecular mechanisms of HILI and identified the potential hepatotoxic ingredients in XCHT and Heshouwu. According to our network results, kaempferol and thymol in XCHT and rhein in Heshouwu exhibit the largest number of liver injury target connections, whereby CASP3, PPARG and MCL1 may be potential liver injury targets for these herbal medicines. This network pharmacology assay might serve as a useful tool to explore the underlying molecular mechanism of HILI. Based on the theoretical predictions, further experimental verification should be performed to validate the accuracy of the predicted interactions between herbal ingredients and protein targets in the future.

Hyperplasia of mammary glands (HMG) is common in middle-aged women. Danlu capsules (DLCs) can effectively relieve pain and improve clinical symptoms and are safe for treating HMG. However, the active substances in DLCs and the molecular mechanisms of DLCs in HMG remain unclear. This study identified the bioactive compounds and delineated the molecular targets and potential pathways of DLCs by using a systems pharmacology approach. The candidate compounds were retrieved from the traditional Chinese medicine systems pharmacology (TCMSP) database and analysis platform. Each candidate's druggability was analyzed according to its oral bioavailability and drug-likeness indices. The candidate proteins and genes were extracted in the TCMSP and UniProt Knowledgebase, respectively. The potential pathways associated with the genes were identified by performing gene enrichment analysis with DAVID Bioinformatics Resources 6.7. A total of 603 compounds were obtained from DLCs, and 39 compounds and 66 targets associated with HMG were obtained. Gene enrichment analysis yielded 10 significant pathways with 34 targets. The integrated HMG pathway revealed that DLCs probably act in patients with HMG through multiple mechanisms of anti-inflammation, analgesic effects, and hormonal regulation. This study provides novel insights into the mechanisms of DLCs in HMG, from the molecular level to the pathway level.

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Unlike Western medicines with single-target, the traditional Chinese medicines (TCM) always exhibit diverse curative effects against multiple diseases through its “multi-components” and “multi-targets” manifestations. However, discovery and identification of the major therapeutic diseases and the underlying molecular mechanisms of TCM remain to be challenged. In the current study, we, for the first time, applied an integrated strategy by combining network pharmacology with experimental evaluation, for exploration and demonstration of the therapeutic potentials and the underlying possible mechanisms of a classic TCM formula, Huanglian Jiedu decoction (HLJDD). First, the herb–compound, compound–protein, protein–pathway, and gene–disease networks were constructed to predict the major therapeutic diseases of HLJDD and explore the underlying molecular mechanisms. Network pharmacology analysis showed the top one predicted disease of HLJDD treatment was cancer, especially hepatocellular carcinoma (HCC) and inflammation-related genes played an important role in the treatment of HLJDD on cancer. Next, based on the prediction by network pharmacology analysis, both in vitro HCC cell and in vivo orthotopic HCC implantation mouse models were established to validate the curative role of HLJDD. HLJDD exerted its antitumor activity on HCC in vitro, as demonstrated by impaired cell proliferation and colony formation abilities, induced apoptosis and cell cycle arrest, as well as inhibited migratory and invasive properties of HCC cells. The orthotopic HCC implantation mouse model further demonstrated the remarkable antitumour effects of HLJDD on HCC in vivo. In conclusion, our study demonstrated the effectiveness of integrating network pharmacology with experimental study for discovery and identification of the major therapeutic diseases and the underlying molecular mechanisms of TCM.

The amount of drug remaining after previous doses, or drug accumulation, is closely related to drug efficacy and safety. An accurate calculation of the accumulation index or ratio (R(ac)) is crucial for dose finding. However, in drug accumulation studies little consensus exists with regard to experimental design or data analysis. We conducted a systematic review of the literature to produce a detailed profile of drug accumulation studies of the last 30 years (1980-2011). Ninety-six articles comprising 122 studies were analyzed. A typical drug accumulation study enrolled 10 to 20 subjects randomly assigned into treatment groups of 1 or 2 dose levels to observe pharmacokinetic behaviors. The median washout period between single and multiple dosing was 7 days, and the dose interval was 1-2 elimination half-lives in non- or one-compartmental models. Generally, the number of repeated times of administration for multiple dosing was 7-14, and the median number of sampling time points was 11. Eight different methods were used to calculate R(ac). The most frequently used method, in 72.9% of the studies, was to set R(ac) equal to the ratio of the area under a plasma concentration-time curve (AUC) during a dosage interval at steady state to the AUC of a dosage interval after the first dose, i.e., R(ac) = AUC(0-τ,ss) / AUC(0-τ,1). The values of R(ac) in the included studies ranged from 0.85 to 18.8, and 68.03% were <2. We suggest that sample size estimation for an accumulation study should be similar to that of a bioequivalence study, and in most studies, 18-24 subjects will be needed. Appropriate calculation methods for R(ac) should be selected based on the experimental design and data characteristics. The crucial values for non-, weak, moderate, and strong accumulation can be set at R(ac) < 1.2, 1.2 ≤ R(ac) < 2, 2 ≤ R(ac) < 5, and R(ac) ≥ 5, respectively. Accumulations studies should also give more regard to drug metabolism and increased accumulation in kidney or liver damaged patients.

Objective The aim of this review is to characterize current status of global TCM clinical trials registered in ClinicalTrials.gov. Methods We examined all the trials registered within ClinicalTrials.gov up to 25 September 2015, focusing on study interventions to identify TCM-related trials, and extracted 1,270 TCM trials from the data set. Results Overall, 691 (54.4%) trials were acupuncture, and 454 (35.8%) trials were herbal medicines. Differences in TCM trial intervention types were also evident among the specific therapeutic areas. Among all trials, 55.7% that were small studies enrolled <100 subjects, and only 8.7% of completed studies had reported results of trials. As for the location, the United States was second to China in conducting the most TCM trials. ConclusionThis review is the first snapshot of the landscape of TCM clinical trials registered in ClinicalTrials.gov, providing the basis for treatment and prevention of diseases within TCM and offering useful information that will guide future research on TCM.