Material basis of Chinese herbal formulas explored by combining pharmacokinetics with network pharmacology

Analysis of 12 Chemical Compounds And Pattern Recognition of Different Parts of Angelicae Sinensis Radix by Liquid Chromatography-Tandem Mass Spectrometry And Chemometrics Methods

To evaluate the quality and quantify bioactive constituents in different parts of Angelicae Sinensis Radix, an efficient, high-speed, high-sensitivity high-performance liquid chromatography and triple quadrupole mass spectrometry method was used for simultaneous detection of 12 chemical compounds including L-tryptophan, chlorogenic acid, caffeic acid, ferulic acid, isoferulic acid, senkyunolide I, guanosine, proline, L-glutamine, γ-aminobutyric acid, glutamic acid, and arginine in 52 batches of Angelicae Sinensis Radix from Gansu, China. The established methods were validated by good linearity (R2≥0.9921), limits of detection (0.0001-0.0156 μg/mL), limits of quantitation (0.0006-0.0781 μg/mL), stability (RSD≤7.77%), repeatability (RSD≤6.79%), intra- and interday precisions (RSD≤6.00% and RSD≤6.39%, respectively) and recovery (90.90-107.16%). According to the quantitative results, the contents of the hydrophilic compounds were higher in the head, while the medium and weak polar components were mainly concentrated in the tail. Finally, principal component analysis results revealed that Angelicae Sinensis Radix could be divided into different medicinal sites based on polar components such as amino acids, nucleosides. The combination of liquid chromatography-tandem mass spectrometry and principal component analysis is a simple and reliable method for pattern recognition and quality evaluation of Angelicae Sinensis Radix.

Network Pharmacology Approach for Medicinal Plants: Review and Assessment

Natural products have played a critical role in medicine due to their ability to bind and modulate cellular targets involved in disease. Medicinal plants hold a variety of bioactive scaffolds for the treatment of multiple disorders. The less adverse effects, affordability, and easy accessibility highlight their potential in traditional remedies. Identifying pharmacological targets from active ingredients of medicinal plants has become a hot topic for biomedical research to generate innovative therapies. By developing an unprecedented opportunity for the systematic investigation of traditional medicines, network pharmacology is evolving as a systematic paradigm and becoming a frontier research field of drug discovery and development. The advancement of network pharmacology has opened up new avenues for understanding the complex bioactive components found in various medicinal plants. This study is attributed to a comprehensive summary of network pharmacology based on current research, highlighting various active ingredients, related techniques/tools/databases, and drug discovery and development applications. Moreover, this study would serve as a protocol for discovering novel compounds to explore the full range of biological potential of traditionally used plants. We have attempted to cover this vast topic in the review form. We hope it will serve as a significant pioneer for researchers working with medicinal plants by employing network pharmacology approaches.

A Comparative Study of Systems Pharmacology and Gene Chip Technology for Predicting Targets of a Traditional Chinese Medicine Formula in Primary Liver Cancer Treatment

Background: The systems pharmacology approach is a target prediction model for traditional Chinese medicine and has been used increasingly in recent years. However, the accuracy of this model to other prediction models is yet to be established.

Objective: To compare the systems pharmacology modelwithexperimental gene chip technology by using these models to predict targets of a traditional Chinese medicine formulain the treatment of primary liver cancer.

Methods: Systems pharmacology and gene chip target predictions were performed for the traditional Chinese medicine formula ZhenzhuXiaojiTang (ZZXJT). A third square alignment was performed with molecular docking.

Results: Identification of systems pharmacology accounted for 17% of targets, whilegene chip-predicted outcomes accounted for 19%.Molecular docking showed that the top ten targets (excludingcommon targets) of the system pharmacology model had better binding free energies than the gene chip model using twocommon targets as a benchmark. For both models, the core drugs predictions were more consistent than the core small molecules predictions.

Conclusion:In this study, the identified targets of systems pharmacology weredissimilar to those identified by gene chip technology; whereas the core drug and small molecule predictions were similar.

Transcriptional profiling and network pharmacology analysis identify the potential biomarkers from Chinese herbal formula Huosu Yangwei Formula treated gastric cancer in vivo

Huosu Yangwei (HSYW) Formula is a traditioanl Chinese herbal medicine that has been extensively used to treat chronic atrophic gastritis, precancerous lesions of gastric cancer and advanced gastric cancer. However, the effective compounds of HSYW and its related anti-tumor mechanisms are not completely understood. In the current study, 160 ingredients of HSYW were identified and 64 effective compounds were screened by the ADMET evaluation. Furthermore, 64 effective compounds and 2579 potential targets were mapped based on public databases. Animal experiments demonstrated that HSYW significantly inhibited tumor growth in vivo. Transcriptional profiles revealed that 81 mRNAs were differentially expressed in HSYW-treated N87-bearing Balb/c mice. Network pharmacology and PPI network showed that 12 core genes acted as potential markers to evaluate the curative effects of HSYW. Bioinformatics and qRT-PCR results suggested that HSYW might regulate the mRNA expression of DNAJB4, CALD, AKR1C1, CST1, CASP1, PREX1, SOCS3 and PRDM1 against tumor growth in N87-bearing Balb/c mice.

Protective effects of Re-yan-ning mixture on Streptococcus pneumonia in rats based on network pharmacology

CONTEXT

Re-yan-ning mixture (RYNM) is a new national drug approved by China's State Food and Drug Administration for the treatment of colds, simple pneumonia and acute bronchitis.

OBJECTIVE

To determine the mechanism of action of RYNM in the treatment of bacterial pneumonia.

MATERIALS AND METHODS

Using the network pharmacology approach, the multiple components, component candidate targets and multiple therapeutic targets of RYNM were screened and functionally enriched. Also, we established a rat Streptococcus pneumonia model to verify the results of network pharmacology enrichment analysis. Forty male SPF Sprague Dawley rats were divided into four groups of 10 rats: control (normal saline), model (normal saline), levofloxacin-intervened and RYNM-intervened groups. IL-10, NOS2, COX-1, IL-6, TNF-α and NF-κB in serum and BALF were detected by ELISA. Western blot detected IL-17, IL-6, TNF-α, COX-2 and Bcl-2.

RESULTS

The network pharmacology approach successfully identified 48 bioactive components in RYNM, and 65 potential targets and 138 signal pathways involved in the treatment of Streptococcus pneumonia with RYNM. The in vivo experiments indicated that model group has visible inflammation and lesions while RYNM and levofloxacin groups have not. The RYNM exhibited its therapeutic effects on Streptococcus pneumonia mainly via the regulation of cell proliferation and survival through the IL-6/IL-10/IL-17, Bax/Bcl-2, COX-1/COX-2, NF-κB and TNF-α signalling pathways.

DISCUSSION AND CONCLUSIONS

The present study demonstrated the protective effects of RYNM on Streptococcus pneumonia, providing a potential mechanism for the treatment of bacterial pneumonia with RYNM.

A Mass Spectrometry Based Metabolite Profiling Workflow for Selecting Abundant Specific Markers and Their Structurally Related Multi-Component Signatures in Traditional Chinese Medicine Multi-Herb Formulae

In Traditional Chinese Medicine (TCM), herbal preparations often consist of a mixture of herbs. Their quality control is challenging because every single herb contains hundreds of components (secondary metabolites). A typical 10 herb TCM formula was selected to develop an innovative strategy for its comprehensive chemical characterization and to study the specific contribution of each herb to the formula in an exploratory manner. Metabolite profiling of the TCM formula and the extract of each single herb were acquired with liquid chromatography coupled to high-resolution mass spectrometry for qualitative analyses, and to evaporative light scattering detection (ELSD) for semi-quantitative evaluation. The acquired data were organized as a feature-based molecular network (FBMN) which provided a comprehensive view of all types of secondary metabolites and their occurrence in the formula and all single herbs. These features were annotated by combining MS/MS-based in silico spectral match, manual evaluation of the structural consistency in the FBMN clusters, and taxonomy information. ELSD detection was used as a filter to select the most abundant features. At least one marker per herb was highlighted based on its specificity and abundance. A single large-scale fractionation from the enriched formula enabled the isolation and formal identification of most of them. The obtained markers allowed an improved annotation of associated features by manually propagating this information through the FBMN. These data were incorporated in the high-resolution metabolite profiling of the formula, which highlighted specific series of related components to each individual herb markers. These series of components, named multi-component signatures, may serve to improve the traceability of each herb in the formula. Altogether, the strategy provided highly informative compositional data of the TCM formula and detailed visualizations of the contribution of each herb by FBMN, filtered feature maps, and reconstituted chromatogram traces of all components linked to each specific marker. This comprehensive MS-based analytical workflow allowed a generic and unbiased selection of specific and abundant markers and the identification of multiple related sub-markers. This exploratory approach could serve as a starting point to develop more simple and targeted quality control methods with adapted marker specificity selection criteria to given TCM formula.

Comparative pharmacokinetics of six coumarins in normal and breast cancer bone-metastatic mice after oral administration of Wenshen Zhuanggu Formula

ETHNOPHARMACOLOGICAL RELEVANCE

Wenshen Zhuanggu Formula (WSZG) is a traditional Chinese medicine (TCM) prescription used in clinics for adjuvant treatment of breast cancer bone metastases in Longhua Hospital in China. WSZG has been reported to decrease the risk of bone metastases and alleviate the severity of bone lesions in a breast cancer xenograft model.

AIM OF THE STUDY

The present study aimed at investigating the pharmacokinetic behaviors of six coumarins in normal and breast cancer bone-metastatic mice following oral administration of WSZG extract.

MATERIALS AND METHODS

A bone-metastatic mouse model was established by intracardiac injection of MDA-MB-231BO breast cancer cells, and WSZG extract (1.60 g/kg) was given orally to the model and normal mice for 4 weeks. Then, the blood pharmacokinetic parameters of six bioactive components from WSZG (psoralen, isopsoralen, bergapten, xanthotoxin, osthole, and imperatorin) were analyzed by liquid chromatography tandem mass spectrometry.

RESULTS

There were significant differences in pharmacokinetic behaviors between normal and pathological states. Compared with normal mice, the model mice showed significantly increased AUC_0-t and AUC_0-∞ of the bioactive compounds (P < 0.05) and significantly decreased total blood clearance (CL_Z/F) (P < 0.05).

CONCLUSIONS

The different pharmacokinetic behaviors might be partly ascribed to intestinal functional disorders and imbalance of gastrointestinal microbiota under the morbid state. The findings provide some valuable information to evaluate the clinical efficacy and safety of this TCM formula.

Integrated Modules Analysis to Explore the Molecular Mechanisms of Phlegm-Stasis Cementation Syndrome with Ischemic Heart Disease

Background: Ischemic heart disease (IHD) has been the leading cause of death for several decades globally, IHD patients usually hold the symptoms of phlegm-stasis cementation syndrome (PSCS) as significant complications. However, the underlying molecular mechanisms of PSCS complicated with IHD have not yet been fully elucidated. Materials and Methods: Network medicine methods were utilized to elucidate the underlying molecular mechanisms of IHD phenotypes. Firstly, high-quality IHD-associated genes from both human curated disease-gene association database and biomedical literatures were integrated. Secondly, the IHD disease modules were obtained by dissecting the protein-protein interaction (PPI) topological modules in the String V9.1 database and the mapping of IHD-associated genes to the PPI topological modules. After that, molecular functional analyses (e.g., Gene Ontology and pathway enrichment analyses) for these IHD disease modules were conducted. Finally, the PSCS syndrome modules were identified by mapping the PSCS related symptom-genes to the IHD disease modules, which were further validated by both pharmacological and physiological evidences derived from published literatures. Results: The total of 1,056 high-quality IHD-associated genes were integrated and evaluated. In addition, eight IHD disease modules (the PPI sub-networks significantly relevant to IHD) were identified, in which two disease modules were relevant to PSCS syndrome (i.e., two PSCS syndrome modules). These two modules had enriched pathways on Toll-like receptor signaling pathway (hsa04620) and Renin-angiotensin system (hsa04614), with the molecular functions of angiotensin maturation (GO:0002003) and response to bacterium (GO:0009617), which had been validated by classical Chinese herbal formulas-related targets, IHD-related drug targets, and the phenotype features derived from human phenotype ontology (HPO) and published biomedical literatures. Conclusion: A network medicine-based approach was proposed to identify the underlying molecular modules of PSCS complicated with IHD, which could be used for interpreting the pharmacological mechanisms of well-established Chinese herbal formulas (e.g., Tao Hong Si Wu Tang, Dan Shen Yin, Hunag Lian Wen Dan Tang and Gua Lou Xie Bai Ban Xia Tang). In addition, these results delivered novel understandings of the molecular network mechanisms of IHD phenotype subtypes with PSCS complications, which would be both insightful for IHD precision medicine and the integration of disease and TCM syndrome diagnoses.

Network pharmacology analysis of the anti-cancer pharmacological mechanisms of Ganoderma lucidum extract with experimental support using Hepa1-6-bearing C57 BL/6 mice

ETHNOPHARMACOLOGICAL RELEVANCE

Ganoderma lucidum (GL) is an oriental medical fungus, which was used to prevent and treat many diseases. Previously, the effective compounds of Ganoderma lucidum extract (GLE) were extracted from two kinds of GL, [Ganoderma lucidum (Leyss. Ex Fr.) Karst.] and [Ganoderma sinense Zhao, Xu et Zhang], which have been used for adjuvant anti-cancer clinical therapy for more than 20 years. However, its concrete active compounds and its regulation mechanisms on tumor are unclear.

AIM OF THE STUDY

In this study, we aimed to identify the main active compounds from GLE and to investigate its anti-cancer mechanisms via drug-target biological network construction and prediction.

MATERIALS AND METHODS

The main active compounds of GLE were identified by HPLC, EI-MS and NMR, and the compounds related targets were predicted using docking program. To investigate the functions of GL holistically, the active compounds of GL and related targets were predicted based on four public databases. Subsequently, the Identified-Compound-Target network and Predicted-Compound-Target network were constructed respectively, and they were overlapped to detect the hub potential targets in both networks. Furthermore, the qRT-PCR and western-blot assays were used to validate the expression levels of target genes in GLE treated Hepa1-6-bearing C57 BL/6 mice.

RESULTS

In our work, 12 active compounds of GLE were identified, including Ganoderic acid A, Ganoderenic acid A, Ganoderic acid B, Ganoderic acid H, Ganoderic acid C2, Ganoderenic acid D, Ganoderic acid D, Ganoderenic acid G, Ganoderic acid Y, Kaemferol, Genistein and Ergosterol. Using the docking program, 20 targets were mapped to 12 compounds of GLE. Furthermore, 122 effective active compounds of GL and 116 targets were holistically predicted using public databases. Compare with the Identified-Compound-Target network and Predicted-Compound-Target network, 6 hub targets were screened, including AR, CHRM2, ESR1, NR3C1, NR3C2 and PGR, which was considered as potential markers and might play important roles in the process of GLE treatment. GLE effectively inhibited tumor growth in Hepa1-6-bearing C57 BL/6 mice. Finally, consistent with the results of qRT-PCR data, the results of western-blot assay demonstrated the expression levels of PGR and ESR1 were up-regulated, as well as the expression levels of NR3C2 and AR were down-regulated, while the change of NR3C1 and CHRM2 had no statistical significance.

CONCLUSIONS

The results indicated that these 4 hub target genes, including NR3C2, AR, ESR1 and PGR, might act as potential markers to evaluate the curative effect of GLE treatment in tumor. And, the combined data provide preliminary study of the pharmacological mechanisms of GLE, which may be a promising potential therapeutic and chemopreventative candidate for anti-cancer.

Combination of cheminformatics and bioinformatics to explore the chemical basis of the rhizomes and aerial parts of Dioscorea nipponica Makino

OBJECTIVES

This study was aimed to explore the chemical basis of the rhizomes and aerial parts of Dioscorea nipponica Makino (DN).

METHODS

The pharmacokinetic profiles of the compounds from DN were calculated via ACD/I-Lab and PreADMET program. Their potential therapeutic and toxicity targets were screened through the DrugBank's or T3DB's ChemQuery structure search.

KEY FINDINGS

Eleven of 48 compounds in the rhizomes and over half of the compounds in the aerial parts had moderate or good human oral bioavailability. Twenty-three of 48 compounds in the rhizomes and 40/43 compounds from the aerial parts had moderate or good permeability to intestinal cells. Forty-three of 48 compounds from the rhizomes and 18/43 compounds in the aerial parts bound weakly to the plasma proteins. Eleven of 48 compounds in the rhizomes and 36/43 compounds of the aerial parts might pass across the blood-brain barrier. Forty-three 48 compounds in the rhizomes and 18/43 compounds from the aerial parts showed low renal excretion ability. The compounds in the rhizomes possessed 391 potential therapeutic targets and 216 potential toxicity targets. Additionally, the compounds from the aerial parts possessed 101 potential therapeutic targets and 183 potential toxicity targets.

CONCLUSIONS

These findings indicated that combination of cheminformatics and bioinformatics may facilitate achieving the objectives of this study.

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.

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 Applications and Features of Liquid Chromatography-Mass Spectrometry in the Analysis of Traditional Chinese Medicine

With increasingly improved separation of complex samples and detection of unknown material capabilities, liquid chromatography coupled with mass spectrometry (LC-MS) has been widely used in traditional Chinese medicine (TCM) research. This article describes the principles of liquid chromatography (LC) and mass spectrometry (MS) and their advantages and disadvantages in qualitative and quantitative analysis of TCM. We retrieved research literatures about the application of LC-MS in TCM published during the past five years at home and abroad. To better guide the analysis of TCM, this review mainly focuses on the applications category of LC-MS, how often different kinds of LC-MS are used, and the qualitative and quantitative ability of various LC-MS in the study of TCM.

Systematic Analysis of Absorbed Anti-Inflammatory Constituents and Metabolites of Sarcandra glabra in Rat Plasma Using Ultra-High-Pressure Liquid Chromatography Coupled with Linear Trap Quadrupole Orbitrap Mass Spectrometry

Ultra-high-pressure liquid chromatography (UHPLC) was coupled with linear ion trap quadrupole Orbitrap mass spectrometry (LTQ-Orbitrap) and was used for the first time to systematically analyze the absorbed components and metabolites in rat plasma after oral administration of the water extract of Sarcandra glabra. This extract is a well-known Chinese herbal medicine for the treatment of inflammation and immunity related diseases. The anti-inflammatory activities of the absorbed components were evaluated by measuring nitric oxide (NO) production and proinflammatory genes expression in lipopolysaccharide (LPS)-stimulated murine RAW 264.7 macrophages. As a result, 54 components in Sarcandra glabra were detected in dosed rat plasma, and 36 of them were positively identified. Moreover, 23 metabolites were characterized and their originations were traced. Furthermore, 20 of the 24 studied components showed anti-inflammatory activities. These results provide evidence that this method efficiency detected constituents in plasma based on the anti-inflammatory mechanism of multiple components and would be a useful technique for screening multiple targets for natural medicine research.

Peony-Glycyrrhiza Decoction, an Herbal Preparation, Inhibits Clozapine Metabolism via Cytochrome P450s, but Not Flavin-Containing Monooxygenase in In Vitro Models

Our previous studies have shown the therapeutic efficacy and underlying mechanisms of Peony-Glycyrrhiza Decoction (PGD), an herbal preparation, in treating antipsychotic-induced hyperprolactinemia in cultured cells, animal models, and human subjects. In the present study, we further evaluated pharmacokinetic interactions of PGD with clozapine (CLZ) in human liver microsomes (HLM), recombinantly expressed cytochrome P450s (P450s), and flavin-containing monooxygenases (FMOs). CLZ metabolites, N-demethyl-clozapine and clozapine-N-oxide, were measured. PGD, individual peony and glycyrrhiza preparations, and the two individual preparations in combination reduced production of CLZ metabolites to different extents in HLM. While the known bioactive constituents of PGD play a relatively minor role in the kinetic effects of PGD on P450 activity, PGD as a whole had a weak-to-moderate inhibitory potency toward P450s, in particular CYP1A2 and CYP3A4. FMOs are less actively involved in mediating CLZ metabolism and the PGD inhibition of CLZ. These results suggest that PGD has the capacity to suppress CLZ metabolism in the human liver microsomal system. This suppression is principally associated with the inhibition of related P450 activity but not FMOs. The present study provides in vitro evidence of herb-antipsychotic interactions.

An analysis of chemical ingredients network of Chinese herbal formulae for the treatment of coronary heart disease

As a complex system, the complicated interactions between chemical ingredients, as well as the potential rules of interactive associations among chemical ingredients of traditional Chinese herbal formulae are not yet fully understood by modern science. On the other hand, network analysis is emerging as a powerful approach focusing on processing complex interactive data. By employing network approach in selected Chinese herbal formulae for the treatment of coronary heart disease (CHD), this article aims to construct and analyze chemical ingredients network of herbal formulae, and provide candidate herbs, chemical constituents, and ingredient groups for further investigation. As a result, chemical ingredients network composed of 1588 ingredients from 36 herbs used in 8 core formulae for the treatment of CHD was produced based on combination associations in herbal formulae. In this network, 9 communities with relative dense internal connections are significantly associated with 14 kinds of chemical structures with P<0.001. Moreover, chemical structural fingerprints of network communities were detected, while specific centralities of chemical ingredients indicating different levels of importance in the network were also measured. Finally, several distinct herbs, chemical ingredients, and ingredient groups with essential position in the network or high centrality value are recommended for further pharmacology study in the context of new drug development.

Comparative pharmacokinetics study of sinomenine in rats after oral administration of sinomenine monomer and Sinomenium acutum extract

Various products containing sinomenine monomer and extracts of Sinomenium acutum have been widely applied in clinical treatments. The goal of the present study was to compare the pharmacokinetics of sinomenine in rats after oral administration of sinomenine monomer and Sinomenium acutum extract, and to attempt to explore potential component-component interactions between the constituents of this traditional Chinese herbal medicine. A reliable and specific reversed phase high performance liquid chromatography method was developed to analyze sinomenine in rat plasma. Pharmacokinetic parameters for sinomenine were processed by non-compartmental analysis. The results showed that the maximum concentration, the area under the concentration-time curve, clearance and the apparent volume of distribution of sinomenine in the Sinomenium acutum extract statistically differed from those of sinomenine monomer (p < 0.05); however, the mean residence time, time of peak concentration, and half-life did not show significant differences between the two groups. These findings suggested that some additional components in the Sinomenium acutum extract may decrease the absorption of sinomenine. The complex interactions between sinomenine and other components of the herbal extract could result in the altered pharmacokinetic behavior of sinomenine, which may subsequently cause different therapeutic and detoxification effects.

Network pharmacology analyses of the antithrombotic pharmacological mechanism of Fufang Xueshuantong Capsule with experimental support using disseminated intravascular coagulation rats

ETHNOPHARMACOLOGICAL RELEVANCE

Fufang Xueshuantong (FXST) Capsule is developed on a traditional Chinese medicine remedy, with a four-herb formula of Panax notoginseng, Radix astragali, Salvia miltiorrhizae and Radix scrophulariaceae. It has been used for treatment of the clinic cardiovascular disease for many years.

MATERIALS AND METHODS

Due to its complexity of compositions and polypharmacological effects, it often complicates understanding of the mechanisms of action. In the present work, we have constructed an integrated model of system pharmacology to investigate the polypharmacological mechanisms of FXST formulation for treatment of thrombosis disease.

RESULTS

The predicted results showed that 22 ingredients in FXST were closely associated with 41 protein targets related to blood coagulation, fibrinolysis and platelet aggregation. Through analysis of the compound-protein target association, significant cross-targets between each herb indicated the multiple active chemical ingredients might interact with the same target simultaneously and thus explained the synergistic mechanisms of the principle of Traditional Chinese medicines (TCMs) as ''Jun (emperor) - Chen (minister) - Zuo (adjuvant) - Shi (courier)''. To validate the polypharmacological effects predicted by our network pharmacology (NetPharm) analysis, we have carried out experimental investigation the effects of FXST on the disorders of the blood coagulation system in a lipopolysaccharide-induced disseminated intravascular coagulation (DIC) rat model. The results showed that FXST could significantly ameliorate the activation of coagulation system, which is congruent with the cross-target prediction by NetPharm approach.

CONCLUSIONS

The combined investigations provide more insight into better understanding of the pharmacological mechanisms of FXST, and may also offer an alternative avenue to further explore the chemical and pharmacological basis of TCMs.

Rectifying cancer drug discovery through network pharmacology

In spite of the expensive preclinical testing, the consistent failure to translate many promising targeted drugs from the laboratory bench to the clinic raises the question of whether the single-pathway drug-discovery strategies offer the correct perspective. As revealed by network biology, cancers harbor robust biological networks that are inherently resistant to changes, such as those induced by drugs with very narrow mechanisms of action. Therefore, network pharmacology strategies, the treatment of cancer by modulating more than one target, are needed. Different promiscuous approaches targeting multiple avenues within cancer-associated networks, such as the pleiotropic natural products, are emerging. Nevertheless, there is a long way before such 'proof-of-concept strategies' can be successfully applied in the clinical setting. This article provides a perspective on the current challenges in drug discovery, the reasons for high failure rates and how network pharmacology can aid the successful design of agents against cancer.

A network pharmacology approach to understanding the mechanisms of action of traditional medicine: Bushenhuoxue formula for treatment of chronic kidney disease

Traditional Chinese medicine (TCM) has unique therapeutic effects for complex chronic diseases. However, for the lack of an effective systematic approach, the research progress on the effective substances and pharmacological mechanism of action has been very slow. In this paper, by incorporating network biology, bioinformatics and chemoinformatics methods, an integrated approach was proposed to systematically investigate and explain the pharmacological mechanism of action and effective substances of TCM. This approach includes the following main steps: First, based on the known drug targets, network biology was used to screen out putative drug targets; Second, the molecular docking method was used to calculate whether the molecules from TCM and drug targets related to chronic kidney diseases (CKD) interact or not; Third, according to the result of molecular docking, natural product-target network, main component-target network and compound-target network were constructed; Finally, through analysis of network characteristics and literature mining, potential effective multi-components and their synergistic mechanism were putatively identified and uncovered. Bu-shen-Huo-xue formula (BSHX) which was frequently used for treating CKD, was used as the case to demonstrate reliability of our proposed approach. The results show that BSHX has the therapeutic effect by using multi-channel network regulation, such as regulating the coagulation and fibrinolytic balance, and the expression of inflammatory factors, inhibiting abnormal ECM accumulation. Tanshinone IIA, rhein, curcumin, calycosin and quercetin may be potential effective ingredients of BSHX. This research shows that the integration approach can be an effective means for discovering active substances and revealing their pharmacological mechanisms of TCM.

Effect of Chunyangzhengqi capsules on cell proliferation and apoptosis in human gastric cancer cell line MGC-803

AIM: To observe the effect of Chunyangzhengqi capsules on the growth of gastric cancer MGC-803 cells.

METHODS: MGC-803 cells were treated with Chunyangzhengqi capsules at a concentration of 200, 400, 800 or 1600 μg/mL. Cell morphological changes were observed under an inverted microscope. Cell cycle was examined by flow cytometry (FCM). Apoptosis was analyzed by Hoechest-33258 staining. The spectrometry was used to detect Caspase3 activity.

RESULTS: Chunyangzhengqi capsules inhibited the proliferation of MGC-803 cells in a dose- and time-dependent manner. The IC50 values of Chunyangzhengqi capsules at 24, 48 and 72 h were 1734, 1534 and 1094 μg/mL, respectively. After treatment, cells exhibited apoptosis in morphology. Chunyangzhengqi capsules could induce apoptosis of MGC-803 cells and block cells at S phase. The activity of Caspase3 was significantly increased in cells treated with Chunyangzhengqi capsules at a concentration of 1600 μg/mL for 16 h.

CONCLUSION: Chunyangzhengqi capsules inhibit cell proliferation and induce apoptosis in human gastric cancer cell line MGC-803.

A Drug-Target Network-Based Approach to Evaluate the Efficacy of Medicinal Plants for Type II Diabetes Mellitus

The use of plants as natural medicines in the treatment of type II diabetes mellitus (T2DM) has long been of special interest. In this work, we developed a docking score-weighted prediction model based on drug-target network to evaluate the efficacy of medicinal plants for T2DM. High throughput virtual screening from chemical library of natural products was adopted to calculate the binding affinity between natural products contained in medicinal plants and 33 T2DM-related proteins. The drug-target network was constructed according to the strength of the binding affinity if the molecular docking score satisfied the threshold. By linking the medicinal plant with T2DM through drug-target network, the model can predict the efficacy of natural products and medicinal plant for T2DM. Eighteen thousand nine hundred ninety-nine natural products and 1669 medicinal plants were predicted to be potentially bioactive.