Multimodal integrated strategy for the discovery and identification of quality markers in traditional Chinese medicine

With the modernization and internationalization of traditional Chinese medicine (TCM), the requirement for quality control has increased. The quality marker (Q-marker) is an important standard in this field and has been implemented with remarkable success in recent years. However, the establishment of Q-markers remains fragmented and the process lacks systematicity, resulting in inconsistent quality control and insufficient correlation with clinical efficacy and safety of TCM. This review introduces four multimodal integrated approaches that contribute to the discovery of more comprehensive and accurate Q-markers, thus aiding in the establishment of new quality control patterns based on the characteristics and principles of TCM. These include the whole-process quality control strategy, chemical-activity-based screening method, efficacy, safety, and consistent combination strategy, and TCM theory-guided approach. Furthermore, methodologies and representative examples of these strategies are described, and important future directions and questions in this field are also proposed.

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Four multimodal integrated strategies were introduced to establish Q-markers.

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Quality control of TCM should focus on the entire process chain.

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The identification of Q-markers needs to be guided by TCM theory.

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Ensuring efficacy, safety, and consistency is an essential goal of Q-markers.

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Multidisciplinary techniques are the driving force for improving Q-markers.

Machine Learning Approaches in Traditional Chinese Medicine: A Systematic Review

Machine learning (ML), as a branch of artificial intelligence, acquires the potential and meaningful rules from the mass of data via diverse algorithms. Owing to all research of traditional Chinese medicine (TCM) belonging to the digitalization of clinical records or experimental works, a massive and complex amount of data has become an inextricable part of the related studies. It is thus not surprising that ML approaches, as novel and efficient tools to mine the useful knowledge from data, have created inroads in a diversity of scopes of TCM over the past decade of years. However, by browsing lots of literature, we find that not all of the ML approaches perform well in the same field. Upon further consideration, we infer that the specificity may inhere between the ML approaches and their applied fields. This systematic review focuses its attention on the four categories of ML approaches and their eight application scopes in TCM. According to the function, ML approaches are classified into four categories, including classification, regression, clustering, and dimensionality reduction, and into 14 models as follows in more detail: support vector machine, least square-support vector machine, logistic regression, partial least squares regression, k-means clustering, hierarchical cluster analysis, artificial neural network, back propagation neural network, convolutional neural network, decision tree, random forest, principal component analysis, partial least squares-discriminant analysis, and orthogonal partial least squares-discriminant analysis. The eight common applied fields are divided into two parts: one for TCM, such as the diagnosis of diseases, the determination of syndromes, and the analysis of prescription, and the other for the related researches of Chinese herbal medicine, such as the quality control, the identification of geographic origins, the pharmacodynamic material basis, the medicinal properties, and the pharmacokinetics and pharmacodynamics. Additionally, this paper discusses the function and feature difference among ML approaches when they are applied to the corresponding fields via comparing their principles. The specificity of each approach to its applied fields has also been affirmed, whereby laying a foundation for subsequent studies applying ML approaches to TCM.

Bioactivity assessment of essential oils of Cymbopogon species using a network pharmacology approach

Essential oils of Cymbopogon species have wide commercial applications in fragrance, perfumery, and pharmaceuticals as they exhibit a horizon of bioactivities. Here, essential oils of C. flexuosus and C. martinii were analysed to identify bioactive constituents and bioactivities using a network pharmacology approach. Essential oils were isolated using hydro-distillation in a mini Clevenger apparatus. Analysis of essential oils by GC-MS revealed 20 and 15 chemical constituents in C. flexuosus and C. martinii, respectively. An ingredient-target protein-pathway network was constructed comprising 10 oil constituents (citral, geraniol, geranyl acetate, limonene, linalool, α-terpineol, borneol, α-pinene, myrcene, and n-decanol), 14 target proteins, 51 related pathways, and 108 connections. Analyses of the network showed geraniol, geranyl acetate, limonene, linalool, and citral as major active constituents. A core sub-network constructed from the ingredient-target protein-pathway network revealed bioactivities including anti-cancer, anti-inflammatory and neuroprotective. The protein association network pointed out the major target proteins viz., THRB, FXR, ALOX15, and TSHR and pathways like metabolic, and neuroactive ligand-receptor interaction pathways of essential oil constituents. The target proteins and pathways provided insights into the mechanism of action of bioactive constituents. Based on the results of the study, geraniol was correlated with neuroprotective, citral to chemo-preventive, and limonene to anti-inflammatory activities. Thus, the study offers a new way for the assessment of the bioactivities of Cymbopogon species essential oils leading to the development of new biomedicines.

Deciphering functional biomolecule potential of marine diatoms through complex network approach

Marine diatoms are unique reservoirs of bioactive compounds having enormous applications in therapeutics. But high-throughput screening methods are needed to elucidate the interaction between numerous biomolecules and their targets, facilitating rapid screening for novel drug molecules. So, in the present study chemical constituents were extracted from five marine diatoms using un-targeted metabolite profiling and in-silico virtual screening bioinformatics was employed to predict their bioactivity and molecular targets. A total of 17 chemical constituents out of 51 showed interactions with 76 protein targets associated with 213 pathways. Ingredient-target-pathway network revealed oleic acid, linoleic acid and cholest-5-en-3-ol as major active constituents. Core subnetwork and protein association network showed involvement of these compounds in key metabolic pathways related to cell signaling, cell growth and metabolism of xenobiotics. Thus, the present study for the first time revealed the main active ingredients and their associated pathways from marine diatoms using complex network approach.

A Bioassay-Based Approach for the Batch-To-Batch Consistency Evaluation of Xuesaitong Injection on a Zebrafish Thrombosis Model

Quality control of Chinese medicine (CM) is mainly based on chemical testing, which sometimes shows weak correlation to pharmacological effects. Thus, there is a great demand to establish bioactivity-based assays to ensure the quality of CM. The aim of the present study was to establish a bioassay-based approach to evaluate the biological activity of Xuesaitong injection (XST) based on an in vivo zebrafish model. Zebrafish larvae with arachidonic acid (AA)-induced thrombus were applied to evaluate anti-thrombosis effects of XST and explore the potential mechanism of XST. Analysis of major components in normal and abnormal XST samples was performed by high performance liquid chromatography (HPLC). The results indicate that XST could significantly restore heart red blood cells (RBCs) intensity of thrombotic zebrafish in a dose-dependent manner, whilst decreasing RBCs accumulation in the caudal vein. The results were confirmed using a green fluorescence protein (GFP)-labeled zebrafish thrombosis model. Moreover, we could show that XST downregulates the expression of the fibrinogen alpha chain (fga) gene to inhibit the coagulation cascade during the process of thrombosis in zebrafish. Notoginsenoside R_1, ginsenoside Rg₁, ginsenoside Rb₁ and ginsenoside Rd, which were considered to be the major components of XST, also showed moderate anti-thrombosis efficacy. Further results showed that the zebrafish thrombosis model could efficiently distinguish five abnormal batches of XST from 24 normal batches. Furthermore, the inhibition rates of different batches were correlated with the content level of major components. Our results suggested that the proposed zebrafish thrombosis model could be successfully used to evaluate the batch-to-batch consistency of XST, which provided an alternative way for the quality control of CM.

A network pharmacology study on analgesic mechanism of Yuanhu-Baizhi herb pair

BACKGROUND

Millions of people are suffering from chronic pain conditions, such as headache, arthritis, cancer. Apart from western medicines, traditional Chinese medicines are also well accepted for pain management, especially in Asian countries. Yuanhu-Baizhi herb pair (YB) is a typical herb pair applied to the treatment of stomach pain, hypochondriac pain, headache, and dysmenorrhea, due to its effects on analgesia and sedation. This study is to identify potentially active compounds and the underlying mechanisms of YB in the treatment of pain.

METHODS

Compounds in YB were collected from 3 online databases and then screened by bioavailability and drug likeness parameters. Swiss target prediction was applied to obtain targets information of the active compounds. Pain-related genes were conducted for Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Protein-protein interaction (PPI) networks of the genes were constructed using Cytoscape software. In addition, the hub genes were screened using maximal clique centrality (MCC) algorithm.

RESULTS

In total, 31 compounds from Yuanhu were screened out with 35 putative target genes, while 26 compounds in Baizhi with 43 target genes were discovered. Hence, 78 potential target genes of YB were selected for further study. After overlap analysis of the 78 genes of YB and 2408 pain-associated genes, we finally achieved 34 YB-pain target genes, as well as 10 hub genes and 23 core compounds. Go enrichment and KEGG pathway analysis indicated that YB had a strong integration with neuro system, which might significantly contribute to antinociceptive effect.

CONCLUSION

Our data provide deep understanding of the pharmacological mechanisms of YB in attenuating pain. The discovery shed new light on the development of active compounds of YB for the treatment of pain.

A systematic analysis of natural α-glucosidase inhibitors from flavonoids of Radix scutellariae using ultrafiltration UPLC-TripleTOF-MS/MS and network pharmacology

BACKGROUND

Flavonoids from plant medicines are supposed to be viable alternatives for the treatment of type 2 diabetes (T2D) as less toxicity and side effects. Radix scutellariae (RS) is a widely used traditional medicine in Asia. It has shown great potential in the research of T2D. However, the pharmacological actions remain obscured due to the complex chemical nature of plant medicines.

METHODS

In the present study, a systematic method combining ultrafiltration UPLC-TripleTOF-MS/MS and network pharmacology was developed to screen α-glucosidase inhibitors from flavonoids of RS, and explore the underlying mechanism for the treatment of T2D.

RESULTS

The n-butanol part of ethanol extract from RS showed a strong α-glucosidase inhibition activity (90.55%, IC50 0.551 mg/mL) against positive control acarbose (90.59%, IC50 1.079 mg/mL). A total of 32 kinds of flavonoids were identified from the extract, and their ESI-MS/MS behaviors were elucidated. Thirteen compounds were screened as α-glucosidase inhibitors, including viscidulin III, 2',3,5,6',7-pentahydroxyflavanone, and so on. A compound-target-pathway (CTP) network was constructed by integrating these α-glucosidase inhibitors, target proteins, and related pathways. This network exhibited an uneven distribution and approximate scale-free property. Chrysin (k = 87), 5,8,2'-trihydroxy-7-methoxyflavone (k = 21) and wogonin (k = 20) were selected as the main active constituents with much higher degree values. A protein-protein interaction (PPI) weighted network was built for target proteins of these α-glucosidase inhibitors and drug targets of T2D. PPARG (Cd = 0.165, Cb = 0.232, Cc = 0.401), ACACB (Cd = 0.155, Cb = 0.184, Cc = 0.318), NFKB1 (Cd = 0.233, Cb = 0.161, Cc = 0.431), and PGH2 (Cd = 0.194, Cb = 0.157, Cc = 0.427) exhibited as key targets with the highest scores of centrality indices. Furthermore, a core subnetwork was extracted from the CTP and PPI weighted network. Type II diabetes mellitus (hsa04930) and PPAR signaling pathway (hsa03320) were confirmed as the critical pathways.

CONCLUSIONS

These results improved current understanding of natural flavonoids on the treatment of T2D. The combination of ultrafiltration UPLC-TripleTOF-MS/MS and network pharmacology provides a novel strategy for the research of plant medicines and complex diseases.

MiR-30c-5p mediates the effects of panax notoginseng saponins in myocardial ischemia reperfusion injury by inhibiting oxidative stress-induced cell damage

Myocardial ischemia reperfusion (MI/R) injury is a severe pathological process that threatens human health all over the world. The role of microRNAs (miRNAs) in the pathogenesis of MI/R injury has been increasingly recognized in recent years. Here, we conducted a miRNA profiling of the hearts of MI/R injured rat model, and identified 46 miRNAs which were differentially expressed between the MI/R injury and the control groups. With a special focus on one of the most significantly changed miRNA, miR-30c-5p, we demonstrated its protective role against cardiomyocyte injury in tBHP-treated H9c2 cells. Overexpression of miR-30c-5p increased cell viability, decreased LDH release, and reduced cell apoptosis of cardiomyocytes after tBHP stimulation, accompanied with downregulated p53 expression. Noticeably, the level of miR-30c-5p was markedly upregulated in MI/R injury cells treated with panax notoginseng saponins (PNS), a traditional Chinese Medicine with significant clinical effects in the treatment of human MI/R injury. Moreover, miR-30c-5p inhibitor is sufficient to block the protection of PNS, as well as its active ingredient ginsenoside Re, against tBHP induced cardiomyocyte injury. The expression of p53 protein was also reduced in PNS treated cells. In summary, our study identified novel miRNA hits of MI/R injury, revealed a pivotal role of miR-30c-5p in cardiomyocyte damage and apoptosis after MI/R, and illustrated a miR-30c-5p-dependent therapeutic mechanism of PNS of this pathologic process. Future studies are warranted to examine the endogenous significance of miR-30c-5p, along with multiple other miRNA hits, in the pathogenesis and treatment of MI/R injury.

Fabrication of paper-based enzyme immobilized microarray by 3D-printing technique for screening α-glucosidase inhibitors in mulberry leaves and lotus leaves

Background

The discovery of bioactive compounds in traditional Chinese medicine (TCM) has become an important field in TCM modernization. Ligand fishing is a suitable method for discovery of bioactive compounds in complex mixtures such as TCM with high selectivity. Because of unique advantage of low cost and convenience, paper-based microdevices can be good carriers for enzyme immobilized ligand fishing.

Methods

As an important enzyme for glucose metabolism, α-glucosidase was immobilized on polycaprolactone–chitosan-modified paper to prepare the microdevice with unique microfluid structure generated by 3D printing technology, which can be easily applied to screen active compounds in herbal extracts. The preparation conditions of the paper microarray were optimized. The activity of immobilized α-glucosidase was verified by colorimetric reactions which can be easily monitored by cellphone. The paper microarray with α-glucosidase immobilized was used to screen active compounds in the water extracts of mulberry leaves and lotus leaves.

Results

Several key parameters including Na₂CO₃ solution concentration, Na₂CO₃ solution volume, glutaraldehyde concentration, crosslinking time of glutaraldehyde and time of α-glucosidase immobilization were optimized. The proposed paper-based microarray was successfully applied in screening active compounds in two herbal extracts. Four compounds including chlorogenic acid, quercetin-3-O-glucuronide, isoquercetin, and quercetin were identified as α-glucosidase inhibitors. The compounds with significant non-specific adsorption caused by chitosan, such as isoquercitrin, astragalin, quercetin, were also found to be active compounds.

Conclusions

An enzyme immobilized paper microarray was designed and fabricated in this work. Polycaprolactone and chitosan were used to modify filter paper to prepare paper microarrays. Parameters of paper device preparation were optimized. Our findings suggested that 3D-printing paper-based microarrays can be a simple and low-cost approach for discovery of active compounds of TCM.

Electronic supplementary material

The online version of this article (10.1186/s13020-019-0236-y) contains supplementary material, which is available to authorized users.

Network Pharmacology in Research of Chinese Medicine Formula: Methodology, Application and Prospective

Chinese medicine (CM) is usually prescribed as CM formula to treat disease. The lack of effective research approach makes it difficult to elucidate the molecular mechanisms of CM formula owing to its complicated chemical compounds. Network pharmacology is increasingly applied in CM formula research in recent years, which is identified suitable for the study of CM formula. In this review, we summarized the methodology of network pharmacology, including network construction, network analysis and network verification. The aim of constructing a network is to achieve the interaction between the bioactive compounds and targets and the interaction between various targets, and then find out and validate the key nodes via network analysis and network verification. Besides, we reviewed the application in CM formula research, mainly including targets discovery, bioactive compounds screening, toxicity evaluation, mechanism research and quality control research. Finally, we proposed prospective in the future and limitations of network pharmacology, expecting to provide new strategy and thinking on study for CM formula.

The Recent Applications and Developments of Bioinformatics and Omics Technologies in Traditional Chinese Medicine

Background:

Traditional Chinese Medicine (TCM) is widely utilized as complementary health care in China whose acceptance is still hindered by conventional scientific research methodology, although it has been exercised and implemented for nearly 2000 years. Identifying the molecular mechanisms, targets and bioactive components in TCM is a critical step in the modernization of TCM because of the complexity and uniqueness of the TCM system. With recent advances in computational approaches and high throughput technologies, it has become possible to understand the potential TCM mechanisms at the molecular and systematic level, to evaluate the effectiveness and toxicity of TCM treatments. Bioinformatics is gaining considerable attention to unearth the in-depth molecular mechanisms of TCM, which emerges as an interdisciplinary approach owing to the explosive omics data and development of computer science. Systems biology, based on the omics techniques, opens up a new perspective which enables us to investigate the holistic modulation effect on the body.

Objective:

This review aims to sum up the recent efforts of bioinformatics and omics techniques in the research of TCM including Systems biology, Metabolomics, Proteomics, Genomics and Transcriptomics.

Conclusion:

Overall, bioinformatics tools combined with omics techniques have been extensively used to scientifically support the ancient practice of TCM to be scientific and international through the acquisition, storage and analysis of biomedical data.

Network pharmacology study reveals energy metabolism and apoptosis pathways-mediated cardioprotective effects of Shenqi Fuzheng

ETHNOPHARMACOLOGICAL RELEVANCE

Shenqi Fuzheng (SQ) is a renowned traditional Chinese medicine extracted from Radix Codonopsis and Radix Astragali. Although SQ is widely used to treat myocardial ischemia-reperfusion (I/R) injury, the molecular mechanisms supporting its clinical application remain elusive.

AIM OF THE STUDY

The purpose of current study was to understand its cardioprotective effects at the molecular level using network pharmacology approach.

MATERIALS AND METHOD

In an I/R injury animal model, the beneficial pharmacological activities of SQ were confirmed by decreased infarct range observed on drug treated rats versus control group. Additionally, several serum biochemical indicators were in concord with this observation. Subsequently, a microarray experiment was performed to reveal the influence on injured heart at the gene expression level by this TCM injection. We then proposed a network analysis algorithm NTRA to discover the key nodes based on both disease network structure and transcriptomics. Using NRI_ODN, a method developed by our group previously, the holistic changes on the gene network induced by for I/R injury and SQ treatment were evaluated.

RESULTS

Pathway enrichment analysis of highly ranked genes by NTRA showed that PPAR and apoptosis pathways were highly related to I/R injury. Finally, western blot results showed increased level of the PPARα and BAX protein in the heart after injection treatment which confirmed the hypothesis.

CONCLUSION

In conclusion, our results suggest that SQ injection exerts protective effect against myocardial ischemia-reperfusion injury through multiple pathways, including myocardial energy metabolism improvement, cell adhesion inhibition, inflammatory reaction perturbation, myocardial apoptosis reduction and ventricular remodeling avoidance.

Q-marker based strategy for CMC research of Chinese medicine: A case study of Panax Notoginseng saponins

BACKGROUND

To ensure pharmaceutical quality, chemistry, manufacturing and control (CMC) research is essential. However, due to the inherent complexity of Chinese medicine (CM), CMC study of CM remains a great challenge for academia, industry, and regulatory agencies. Recently, quality-marker (Q-marker) was proposed to establish quality standards or quality analysis approaches of Chinese medicine, which sheds a light on Chinese medicine's CMC study.

PURPOSE

Here manufacture processes of Panax Notoginseng Saponins (PNS) is taken as a case study and the present work is to establish a Q-marker based research strategy for CMC of Chinese medicine.

STUDY DESIGN

The Q-markers of Panax Notoginseng Saponins (PNS) is selected and established by integrating chemical profile with pharmacological activities. Then, the key processes of PNS manufacturing are identified by material flow analysis. Furthermore, modeling algorithms are employed to explore the relationship between Q-markers and critical process parameters (CPPs) of the key processes. At last, CPPs of the key processes are optimized in order to improving the process efficiency.

RESULTS

Among the 97 identified compounds, Notoginsenoside R₁, ginsenoside Rg₁, Re, Rb₁ and Rd are selected as the Q-markers of PNS. Our analysis on PNS manufacturing show the extraction process and column chromatography process are the key processes. With the CPPs of each process as the inputs and Q-markers' contents as the outputs, two process prediction models are built separately for the extraction process and column chromatography process of Panax notoginseng, which both possess good prediction ability. Based on the efficiency models of extraction process and column chromatography process we constructed, the optimal CPPs of both processes are calculated.

CONCLUSION

Our results show that the Q-markers derived from CMC research strategy can be applied to analyze the manufacturing processes of Chinese medicine to assure product's quality and promote key processes' efficiency simultaneously.

Analysis of the main active ingredients and bioactivities of essential oil from Osmanthus fragrans Var. thunbergii using a complex network approach

BACKGROUND

Osmanthus fragrans has been used as folk medicine for thousands of years. The extracts of Osmanthus fragrans flowers were reported to have various bioactivities including free radical scavenging, anti-inflammation, neuroprotection and antitumor effects. However, there is still lack of knowledge about its essential oil.

METHODS

In this work, we analyzed the chemical composition of the essential oil from Osmanthus fragrans var. thunbergii by GC-MS. A complex network approach was applied to investigate the interrelationships between the ingredients, target proteins, and related pathways for the essential oil. Statistical characteristics of the networks were further studied to explore the main active ingredients and potential bioactivities of O. fragrans var. thunbergii essential oil.

RESULTS

A total of 44 ingredients were selected from the chemical composition of O. fragrans var. thunbergii essential oil, and that 191 potential target proteins together with 70 pathways were collected for these compounds. An ingredient-target-pathway network was constructed based on these data and showed scale-free property as well as power-law degree distribution. Eugenol and geraniol were screened as main active ingredients with much higher degree values. Potential neuroprotective and anti-tumor effect of the essential oil were also found. A core subnetwork was extracted from the ingredient-target-pathway network, and indicated that eugenol and geraniol contributed most to the neuroprotection of this essential oil. Furthermore, a pathway-based protein association network was built and exhibited small-world property. MAPK1 and MAPK3 were considered as key proteins with highest scores of centrality indices, which might play an important role in the anti-tumor effect of the essential oil.

CONCLUSIONS

This work predicted the main active ingredients and bioactivities of O. fragrans var. thunbergii essential oil, which would benefit the development and utilization of Osmanthus fragrans flowers. The application of complex network theory was proved to be effective in bioactivities studies of essential oil. Moreover, it provides a novel strategy for exploring the molecular mechanisms of traditional medicines.

A Bioactive Chemical Markers Based Strategy for Quality Assessment of Botanical Drugs: Xuesaitong Injection as a Case Study

Current chemical markers based quality assessment methods largely fail to reflect intrinsic chemical complexity and multiple mechanisms of action of botanical drugs (BD). The development of novel quality markers is greatly needed. Here we propose bioactive chemical markers (BCM), defined as a group of chemo-markers that exhibit similar pharmacological activities comparable to the whole BD, which can therefore be used to effectively assess the quality of BD. As a proof-of-concept, a BCM-based strategy was developed and applied to Xuesaitong Injection (XST) for assessing the efficacy and consistency of different batches. Firstly, systemic characterization of chemical profile of XST revealed a total number of 97 compounds. Secondly, notoginsenoside R₁, ginsenoside Rg₁, Re, Rb₁ and Rd were identified as BCM of XST on treating cardiovascular and cerebrovascular diseases according to Adjusted Efficacy Score following an in vivo validation. Analytical method for quantification of BCM was then developed to ensure the efficacy of XST. Finally, chemical fingerprinting was developed and used to evaluate the batch-to-batch consistency. Our present case study on XST demonstrates that BCM-based strategy offers a rational approach for quality assessment of BD and provides a workflow for chemistry, manufacturing, and controls (CMC) study of BD required by regulatory authority.

Investigating chemical features of Panax notoginseng based on integrating HPLC fingerprinting and determination of multiconstituents by single reference standard

Background

Panax notoginseng is a highly valued medicine and functional food, whose quality is considered to be influenced by the size, botanical parts, and growth environments.

Methods

In this study, a HPLC method integrating fingerprinting and determination of multiconstituents by single reference standard was established and adopted to investigate the chemical profiles and active constituent contents of 215 notoginseng samples with different sizes, from different botanical parts and geographical regions.

Results

Chemical differences among main root, branch root, and rotten root were not distinct, while rhizome and fibrous root could be discriminated from other parts. The notoginseng samples from Wenshan Autonomous Prefecture and cities nearby were similar, whereas samples from cities far away were not. The contents of major active constituents in main root did not correlate with the market price.

Conclusion

This study provided comprehensive chemical evidence for the rational usage of different parts, sizes, and growth regions of notoginseng in practice.

Therapeutic properties of Scutellaria baicalensis in db/db mice evaluated using Connectivity Map and network pharmacology

We have reported that an extract of Scutellaria baicalensis (ESB) has effects against obesity and hypertriglyceridemia in type 2 diabetic animal model (db/db mouse). In the present study, we tried to explain the pharmacological effects of ESB by integrating gene expression information from db/db mouse liver with that of ESB-treated HepG2 hepatocellular carcinoma cells. Using Connectivity Map (cmap) analysis, we found an inverse relationship in the pharmaceutical profiles based on gene expression between db/db mouse liver and ESB-treated HepG2 cells. This inverse relationship between the two data sets was also observed for pathway activities. Functional network analysis showed that biological functions associated with diabetes and lipid metabolism were commonly enriched in both data sets. We also observed a similarity in distribution of cmap enrichment scores between db/db mouse liver and human diabetic liver, whereas there was an inverse pattern of cmap enrichment scores in human diabetic liver compared with ESB-treated HepG2 cells. This relationship might explain the pharmacological activities of ESB against db/db mouse and possible effectiveness of ESB against human diabetes. We expect that our approach using in vitro cell lines could be applied in predicting the pharmacological effectiveness of herbal drugs in in vivo systems.

Combining Chemical Profiling and Network Analysis to Investigate the Pharmacology of Complex Prescriptions in Traditional Chinese Medicine

We present a paradigm, combining chemical profiling, absorbed components detection in plasma and network analysis, for investigating the pharmacology of combination drugs and complex formulae. On the one hand, the composition of the formula is investigated comprehensively via mass spectrometry analysis, followed by pharmacological studies of the fractions as well as the plasma concentration testing for the ingredients. On the other hand, both the candidate target proteins and the effective ingredients of the formula are predicted via analyzing the corresponding networks. The most probable active compounds can then be identified by combining the experimental results with the network analysis. In order to illustrate the performance of the paradigm, we apply it to the Danggui-Jianzhong formula (DJF) from traditional Chinese medicine (TCM) and predict 4 probably active ingredients, 3 of which are verified experimentally to display anti-platelet activity, i.e., (Z)-Ligustilide, Licochalcone A and Pentagalloylglucose. Moreover, the 3-compound formulae composed of these 3 chemicals show better anti-platelet activity than DJF. In addition, the paradigm predicts the association between these 3 compounds and COX-1, and our experimental validation further shows that such association comes from the inhibitory effects of the compounds on the activity of COX-1.

Dissecting Xuesaitong's mechanisms on preventing stroke based on the microarray and connectivity map

Elucidating action mechanisms of Chinese medicines has remained a challenging task due to the chemical and biological complexity that needs to be resolved. In this study we applied a gene expression data and connectivity map (CMAP) based approach to study action mechanisms of a Chinese medicine Xuesaitong injection (XST) on preventing cerebral ischemia-reperfusion injury. XST is a standardized patent Chinese medicine of Panax notoginseng roots and it has long been used for the effective prevention and treatment of stroke in China. However, more research is needed to understand the mechanisms underlying its effects against ischemic stroke. We first evaluated the effect of XST against ischemic stroke in an ischemia-reperfusion rat animal model and dissected its mechanisms based on gene expression data of injured brain. The results showed that treatment with XST significantly attenuated infarct area and histological damage. Based upon pathway analysis and the CMAP query of microarray data, anti-inflammatory response and anti-platelet coagulation were found as the major mechanisms of XST against stroke, which were further validated in vitro and with pharmacological assays of serum. We demonstrated the feasibility of applying the combination of the microarray with the CMAP in identifying mechanisms of Chinese medicine.

A novel strategy of profiling the mechanism of herbal medicines by combining network pharmacology with plasma concentration determination and affinity constant measurement

Herbal medicines have long been widely used in the treatment of various complex diseases in China.

Transcriptomics: a sword to cut the Gordian knot of traditional Chinese medicine

The systemic effects of traditional Chinese medicine (TCM) seem to be a Gordian knot, impossible to untie for decades. With the advent of transcriptomics, a useful sword is provided to cut the knot and shed some light on complex bioprocesses and intrinsic connections among them. Here, we revisit studies on TCM ZHENGs using this approach, highlight its applications on elucidating the potential scientific basis of ZHENG and investigating mechanisms of action for the TCM formula, and demonstrating its unique role in novel TCM drug design and discovery through active ingredient detection from TCM and compatibility theory study of TCM. The limitations and future perspectives of transcriptomics approaches to TCM study are also discussed.

Identifying roles of "Jun-Chen-Zuo-Shi" component herbs of QiShenYiQi formula in treating acute myocardial ischemia by network pharmacology

BACKGROUND

The role of "Jun-Chen-Zuo-Shi" (also known as "sovereign-minister-assistant-courier") component herbs of Chinese medicine is not fully understood. This study aims to test the "Jun-Chen-Zuo-Shi" rule with the QiShenYiQi formula (QSYQ) on treating acute myocardial ischemia (AMI) by a network pharmacology approach.

METHODS

An Acute Myocardial Ischemia (AMI) specific Organism Disturbed Network (AMI-ODN), was constructed by integrating data of disease-associated genes, protein-protein interaction and microarray experiments. A network-based index, Network Recovery Index for Organism Disturbed Network (NRI-ODN), was developed to measure the therapeutic efficacy of QSYQ and its ingredients, i.e., the ability to recover disturbed AMI network model back to normal state.

RESULTS

The whole formula of QSYQ got a NRI-ODN score of 864.48, which outperformed all individual herbs. Additionally, the primary component herbs, Radix Astragalus membranaceus and Radix Salvia miltiorrrhiza showed NRI-DON score of 680.27 and 734.31 respectively, which meant a better performance to recover disturbed AMI network than the supplementary component herbs, Panax notoginseng and Dalbergia sissoo did (545.76 and 584.88, respectively).

CONCLUSION

AMI-ODN model and NRI-ODN identified the possible roles of "Jun-Chen-Zuo-Shi" component herbs of QSYQ in treating AMI at molecular network and pathway level.