Traditional chinese medicine-based network pharmacology could lead to new multicompound drug discovery. Evid Based Complement Alternat Med. 2012;2012:149762. [PMID: 23346189 PMCID: PMC3541710 DOI: 10.1155/2012/149762]

Identification of diagnose related therapeutic targets of Danggui buxue decoction in Parkinson's disease

BACKGROUND

Parkinson's disease (PD) is the fastest growing neurological disease. Currently, there is no disease-modifying therapy to slow the progression of the disease. Danggui buxue decoction (DBD) is widely used in the clinic because of its therapeutic effect. However, little is known about the molecular mechanism of DBD against PD. This study intends to explore the possible molecular mechanisms involved in DBD treatment of PD based on network pharmacology, and provide potential research directions for future research.

METHODS

Firstly, the active components and target genes of DBD were screened from the traditional Chinese medicine systems pharmacology (TCMSP), DrugBank and UniProt database. Secondly, target genes of PD were identified from the (GEO) dataset, followed by identification of common target genes of DBD and PD. Thirdly, analysis of protein-protein interaction (PPI), functional enrichment and diagnosis was performed on common target genes, followed by correlation analysis between core target genes, immune cell, miRNAs, and transcription factors (TFs). Finally, molecular docking between core target genes and active components, and real-time PCR were performed.

RESULTS

A total of 72 common target genes were identified between target genes of DBD and target genes of PD. Among which, 11 target genes with potential diagnostic value were further identified, including TP53, AKT1, IL1B, MMP9, NOS3, RELA, MAPK14, HMOX1, TGFB1, NOS2, and ERBB2. The combinations with the best docking binding were identified, including kaempferol-AKT1/HMOX1/NOS2/NOS3, quercetin-AKT1/ERBB2/IL1B/HMOX1/MMP9/TP53/NOS3/TGFB1. Moreover, IL1B and NOS2 respectively positively and negatively correlated with neutrophil and Type 1 T helper cell. Some miRNA-core target gene regulatory pairs were identified, such as hsa-miR-185-5p-TP53/TGFB1/RELA/MAPK14/IL1B/ERBB2/AKT1 and hsa-miR-214-3p-NOS3. These core target genes were significantly enriched in focal adhesion, TNF, HIF-1, and ErbB signaling pathway.

CONCLUSION

Diagnostic TP53, AKT1, IL1B, MMP9, NOS3, RELA, MAPK14, HMOX1, TGFB1, NOS2, and ERBB2 may be considered as potential therapeutic targets of DBD in the treatment of PD.

Design, Synthesis, and Biological Evaluation of Pierardine Derivatives as Novel Brain-Penetrant and In Vivo Potent NMDAR-GluN2B Antagonists for Ischemic Stroke Treatment

A series of structurally novel GluN2B NMDAR antagonists were designed, synthesized, and biologically evaluated as anti-stroke therapeutics by optimizing the chemical structure of Pierardine, the active ingredient of traditional Chinese medicine Dendrobium aphyllum (Roxb.) C. E. Fischer identified via in silico screening. The systematic structure-activity relationship study led to the discovery of 58 with promising NMDAR-GluN2B binding affinity and antagonistic activity. Of the two enantiomers, S-58 exhibited significant inhibition (IC50 = 74.01 ± 12.03 nM) against a GluN1/GluN2B receptor-mediated current in a patch clamp assay. In addition, it displayed favorable specificity over other subtypes and off-target receptors. In vivo, S-58 exerted therapeutic efficacy comparable to that of the approved GluN2B NMDAR antagonist ifenprodil and excellent safety profiles. In addition to the attractive in vitro and in vivo potency, S-58 exhibited excellent brain exposure. In light of these merits, S-58 has been advanced to further preclinical investigation as a potential anti-stroke candidate.

The OREGANO knowledge graph for computational drug repurposing

Drug repositioning is a faster and more affordable solution than traditional drug discovery approaches. From this perspective, computational drug repositioning using knowledge graphs is a very promising direction. Knowledge graphs constructed from drug data and information can be used to generate hypotheses (molecule/drug - target links) through link prediction using machine learning algorithms. However, it remains rare to have a holistically constructed knowledge graph using the broadest possible features and drug characteristics, which is freely available to the community. The OREGANO knowledge graph aims at filling this gap. The purpose of this paper is to present the OREGANO knowledge graph, which includes natural compounds related data. The graph was developed from scratch by retrieving data directly from the knowledge sources to be integrated. We therefore designed the expected graph model and proposed a method for merging nodes between the different knowledge sources, and finally, the data were cleaned. The knowledge graph, as well as the source codes for the ETL process, are openly available on the GitHub of the OREGANO project ( https://gitub.u-bordeaux.fr/erias/oregano ).

On Finding Natural Antibiotics based on TCM Formulae

CONTEXT

Novel kinds of antibiotics are needed to combat the emergence of antibacterial resistance. Natural products (NPs) have shown potential as antibiotic candidates. Current experimental methods are not yet capable of exploring the massive, redundant, and noise-involved chemical space of NPs. In silico approaches are needed to select NPs as antibiotic candidates.

OBJECTIVE

This study screens out NPs with antibacterial efficacy guided by both TCM and modern medicine and constructed a dataset aiming to serve the new antibiotic design.

METHOD

A knowledge-based network is proposed in this study involving NPs, herbs, the concepts of TCM, and the treatment protocols (or etiologies) of infectious in modern medicine. Using this network, the NPs candidates are screened out and compose the dataset. Feature selection of machine learning approaches is conducted to evaluate the constructed dataset and statistically validate the im- portance of all NPs candidates for different antibiotics by a classification task.

RESULTS

The extensive experiments prove the constructed dataset reaches a convincing classification performance with a 0.9421 weighted accuracy, 0.9324 recall, and 0.9409 precision. The further visu- alizations of sample importance prove the comprehensive evaluation for model interpretation based on medical value considerations.

Disease-related compound identification based on deeping learning method

Acute lung injury (ALI) is a serious respiratory disease, which can lead to acute respiratory failure or death. It is closely related to the pathogenesis of New Coronavirus pneumonia (COVID-19). Many researches showed that traditional Chinese medicine (TCM) had a good effect on its intervention, and network pharmacology could play a very important role. In order to construct "disease-gene-target-drug" interaction network more accurately, deep learning algorithm is utilized in this paper. Two ALI-related target genes (REAL and SATA3) are considered, and the active and inactive compounds of the two corresponding target genes are collected as training data, respectively. Molecular descriptors and molecular fingerprints are utilized to characterize each compound. Forest graph embedded deep feed forward network (forgeNet) is proposed to train. The experimental results show that forgeNet performs better than support vector machines (SVM), random forest (RF), logical regression (LR), Naive Bayes (NB), XGBoost, LightGBM and gcForest. forgeNet could identify 19 compounds in Erhuang decoction (EhD) and Dexamethasone (DXMS) more accurately.

Exploring the mechanism of Epimedii folium and notoginseng radix against vascular dementia based on network pharmacology and molecular docking analysis: pharmacological mechanisms of EH-PN for VD

To explore the mechanism of Epimedii Folium (HF) and Notoginseng Radix (NR) intervention in vascular dementia (VD). This study used the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database to collect the active ingredients and potential drug targets of HF and NR, the Uniprot database to convert drug target names into gene names, GeneCards, Drugbank, Therapeutic Target Database, and Online Mendelian Inheritance in Man database to collect the potential disease targets of VD, and then combined them with the drug targets to construct the HF-NR-VD protein-protein interaction (PPI) network by Search Tool for the Retrieval of Interacting (STRING). Cytoscape (version 3.7.1) was used to perform cluster analysis of the PPI network. Metascape database was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. The potential interaction of the main components of the HF-NR couplet medicine with core disease targets was revealed by molecular docking simulations. There were 23 predicted active ingredients in HF and NR, and 109 common drug targets that may be involved in the treatment of VD. Through PPI network analysis, 30 proteins were identified as core proteins owing to their topological importance. GO functional analysis revealed that the primary biological processes were mainly related to inflammation, apoptosis, and the response to oxidative stress. KEGG pathway enrichment analysis revealed that TNF and PI3K/Akt signaling pathways may occupy the core status in the anti-VD system. Molecular docking results confirmed that the core targets of VD had a high affinity for the main compounds of the HF-NR couplet medicine. We demonstrated the multi-component, multi-target, and multi-pathway characteristics of HF-NR couplet medicine for the treatment of VD and provided a foundation for further clinical application and experimental research.

Anti-inflammatory effects of Chaishi Tuire Granules on influenza A treatment by mediating TRAF6/MAPK14 axis

Objectives

Influenza is an infectious respiratory disease that can cause severe inflammatory reactions and threaten human life. Chaishi Tuire Granules (CSTRG), a Chinese patent medicine widely used clinically in the treatment of respiratory diseases in China, has a definite anti-inflammatory effect. However, the mechanism of CSTRG in the treatment of influenza is still unclear. This study aimed to demonstrate the anti-inflammatory effect of CSTRG on influenza A treatment and potential mechanisms.

Methods

Influenza-associated mice pneumonia model was used to explore the antiviral and anti-inflammatory effects of CSTRG in vivo. Bioinformatics analysis methods such as network pharmacology and molecular docking were carried out to predict the main active components and potential anti-inflammatory targets of CSTRG. The anti-inflammatory activity of CSTRG was determined using the lipopolysaccharide (LPS)-induced macrophages RAW264.7 cells in vitro.

Results

In vivo results showed that CSTRG can reduce the viral load in the lung tissue of infected mice, reduce the expression of TNF-α and IL-6 in lung tissue and serum, and regulate the host inflammatory response. Additionally, CSTRG treatment markedly improves the sick signs, weight loss, lung index, and lung pathological changes. Bioinformatics analysis predicted that six active compounds of CSTRG including quercetin, kaempferol, luteolin, beta-sitosterol, sitosterol, and stigmasterol could contribute to the anti-influenza activity through regulating the TRAF6/MAPK14 axis. The following research confirmed that CSTRG significantly inhibited pro-inflammatory cytokines (TNF-α and IL-6) by suppressing the expression of TRAF6 and MAPK14 in LPS-stimulated macrophages RAW264.7 cells.

Conclusion

CSTRG might inhibit the inflammatory response by mediating the TRAF6/MAPK14 axis. In the future, in-depth research is still needed to verify the mechanism of CSTRG in the treatment of influenza.

Network Pharmacology-Based Exploration on the Intervention of Qinghao Biejia Decoction on the Inflammation-Carcinoma Transformation Process of Chronic Liver Disease via MAPK and PI3k/AKT Pathway

Chronic liver disease(CLD) is a slow-developing and long-term disease that can cause serious damage to the liver. Thus far, it has been associated with viral hepatitis, non-alcoholic fatty liver disease(NAFLD), alcoholic liver disease(ALD), hepatic fibrosis(HF), liver cirrhosis (LC), and liver cancer. Qinghao Biejia Decoction (QBD) is a classic ancient Chinese herbal prescription with strong immune-enhancing, anti-inflammatory, and anti-tumor effects. In this study, we used a network pharmacology approach to investigate the molecular mechanisms of QBD in the inflammation-carcinoma transformation process of chronic liver disease. Two key drug targets, MAPK1 and PIK3CA, were screened using network pharmacology and molecular docking techniques, revealing dihydroartemisinin, artesunate, 12-O-Nicotinoylisolineolone, caffeic acid, and diincarvilone A as active ingredients involved in QBD mechanisms. The main signaling pathways involved were the PI3K-AKT signaling pathway and MAPK signaling pathway. In summary, our results indicated that QBD affects the inflammatory transformation of chronic liver disease through MAPK1 and PIK3CA and signaling pathways MAPK and PI3K/AKT. These data provide research direction for investigating the mechanisms underlying the inflammation-carcinoma transformation process in QBD for chronic liver disease.

Protective Effect of Hedyotis diffusa Willd. Ethanol Extract on Isoniazid-Induced Liver Injury in the Zebrafish Model

Objective

Methods

Results

Conclusion

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.

Mechanism of Huashi Xingyu Qingre recipe in treating oral lichen planus based on network pharmacology and clinical trial verification

OBJECTIVE

To identify the main active components and targets of Huashi Xingyu Qingre recipe (, HXQR) and to investigate its mechanism in the treatment of oral lichen planus (OLP).

METHODS

The Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform was searched to identify the active ingredients and corresponding targets of HXQR. Disease genes were obtained from the GeneCards database, and a "drug-disease regulatory network" was constructed using Cytoscape software and PERL programming language. The STRING database was used to build a protein-protein interaction network. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) terms were analyzed using R software with a Bioconducter plugin. Finally, the results and the efficacy of HXQR in treating OLP were validated in a clinical trial that included enzyme-linked immunosorbent assay (ELISA) testing and observations of the post-treatment changes in clinical symptoms.

RESULTS

HXQR contained 167 active components and 261 targets, with 391 disease targets. The intersection of these two categories in a Venn diagram revealed 57 drug-disease common targets. A compound-target network was constructed and revealed that the six key pharmaceutical ingredients of HXQR were quercetin, luteolin, wogonin, kaempferol, beta-carotene, and baicalein. The protein-protein interaction network mainly involved core proteins such as ALB, interleukin-6, and AKT1. Drug-disease common targets were enriched in 1628 GO terms and 117 KEGG terms, mainly involving inflammatory responses, viral infections, and tumor-related pathways. ELISA testing indicated that HXQR inhibited the tumor necrosis factor (TNF) signaling pathway by reducing the expression of interleukin-6, matrix metalloproteinase-9, and intercellular adhesion molecule-1. The clinical symptoms of the patients with OLP were significantly improved after 8 weeks of treatment with HXQR.

CONCLUSION

HXQR treats OLP by regulating the TNF signaling pathway, resulting in a marked treatment effect with few adverse effects.

Mechanism of Zhen Wu Decoction in the Treatment of Heart Failure Based on Network Pharmacology and Molecular Docking

Heart failure (HF) is a serious manifestation or advanced stage of various cardiovascular diseases, and its mortality and rehospitalization rate are still on the rise in China. Based on the network pharmacology method, 59 components of Zhen Wu decoction (ZWD) and 83 target genes related to HF were obtained. Through the PPI network, four potential therapeutic targets were identified: AKT1, IL6, JUN, and MAPK8. The beneficial components of ZWD might intervene HF through the AGE-RAGE signalling pathway in the diabetes component, fluid shear stress and atherosclerosis, the TNF signalling pathway, TB, and Kaposi sarcoma related herpesvirus infection, according to a KEGG enrichment study. The protein interaction network of candidate targets was constructed by the STRING database, and the protein interaction network was clustered by MEODE software. GO and KEGG enrichment analyses were performed on the core modules obtained by clustering. Finally, AutoDock Vina software was used for molecular docking verification of key targets and active ingredients. The result was that 75 active ingredients and 109 genes were screened as potential active ingredients and potential targets of Shengjie Tongyu decoction for CHF treatment. The main active components were quercetin, luteolin, kaempferol, dehydrated icariin, isorhamnetin, formononetin, and other flavonoids. Il-6, MAPK1, MAPK8, AKT1, VEGFA, and JUN were selected as the core targets. Molecular docking showed that the key components were well connected with the target. GO enrichment analysis showed that Shengjie Tongyu decoction could play a role through multiple biological pathways including angiogenesis, regulation of endothelial cell proliferation, binding of cytokine receptors, negative regulation of apoptotic signalling pathways, regulation of nitric oxide synthase activity, and reactive oxygen metabolism. Key pathways mainly focus on the toll-like receptor signalling pathway, nod-like receptor signalling pathway, MAPK signalling pathway, mTOR signalling pathway, JAK-STAT signalling pathway, VEGF signalling pathway, and other pathways. Through molecular docking technology, it was found that a variety of effective components in ZWD, such as kaempferol. Molecular docking technology has preliminatively verified the network pharmacology and laid a foundation for the follow-up pharmacological research.

Integrated UPLC-MS and Network Pharmacology Approach to Explore the Active Components and the Potential Mechanism of Yiqi Huoxue Decoction for Treating Nephrotic Syndrome

Background: Yiqi Huoxue Decoction (YQHXD) is a traditional Chinese medicine that promotes blood circulation, removes blood stasis, facilitates diuresis, and alleviates edema. It is composed of 10 herbal medicines and has extensive application in treating nephrotic syndrome (NS). However, the active components and the potential mechanism of YQHXD for treating NS remain unclear.

Methods: We set up a sensitive and rapid method based on Ultra-High Performance Liquid Chromatograph-Mass (UPLC-MS) to identify the compounds in YQHXD and constituents absorbed into the blood. Disease genes were collected through GeneCards, DisGeNET, and OMIM database. Genes of compounds absorbed into blood were predicted by the TCMSP database. We constructed Disease-Drug-Ingredient-Gene (DDIG) network using Cytoscape, established a Protein-protein interaction (PPI) network using String, Gene biological process (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was performed using DAVID. Cellular experiments were performed to validate the results of network pharmacology.

Result: A total of 233 compounds in YQHXD and 50 constituents absorbed into the blood of rats were identified. The 36 core targets in the PPI network were clustered in the phosphatidylinositol 3 kinase-RAC serine/threonine-protein kinase (PI3K-AKT) and nuclear factor kappa-B (NF-κB) signaling pathways. Luteolin, Wogonin, Formononetin, and Calycosin were top-ranking components as potentially active compounds.

Conclusion: The results of our studies show that YQHXD is able to enhance renal function, alleviate podocyte injury, and improve adriamycin nephrotic syndrome.

Discovery of novel brain-penetrant GluN2B NMDAR antagonists via pharmacophore-merging strategy as anti-stroke therapeutic agents

In this work, a novel structural series of brain-penetrant GluN2B NMDAR antagonists were designed, synthesized and biologically evaluated as anti-stroke therapeutic agents via merging the structures of NBP and known GluN2B ligands. Approximately half of them exhibited superior neuroprotective activity to NBP against NMDA-induced neurotoxicity in hippocampal neurons at 10 μM, and compound 45e and 45f exerted equipotent activity to ifenprodil, an approved GluN2B- selective NMDAR antagonist. In particular, 45e, with the most potent neuroprotective activity throughout this series, displayed dramatically enhanced activity (K_i = 3.26 nM) compared to ifenprodil (K_i = 14.80 nM) in Radioligand Competitive Binding Assay, and remarkable inhibition (IC₅₀ = 79.32 nM) against GluN1/GluN2B receptor-mediated current in Patch Clamp Assay. Meanwhile, 45e and its enantiomers exhibited low inhibition rate against the current mediated by other investigated receptors at the concentration of 10 μM, indicating their favorable selectivity for GluN1/GluN2B. In the rat model of middle cerebral artery ischemia (MCAO), 45e exerted comparable therapeutic efficacy to ifenprodil at the same dosage. In addition to the attractive in vitro and in vivo potency, 45e displayed a favorable bioavailability (F = 63.37%) and an excellent brain exposure. In further repeated dose toxicity experiments, compound 45e demonstrated an acceptable safety profile. With the above merits, 45e is worthy of further functional investigation as a novel anti-stroke therapeutic agent.

Immunomodulatory drug discovery from herbal medicines: Insights from organ-specific activity and xenobiotic defenses

Traditional herbal medicines, which emphasize a holistic, patient-centric view of disease treatment, provide an exciting starting point for discovery of new immunomodulatory drugs. Progress on identification of herbal molecules with proven single agent activity has been slow, in part because of insufficient consideration of pharmacology fundamentals. Many molecules derived from medicinal plants exhibit low oral bioavailability and rapid clearance, leading to low systemic exposure. Recent research suggests that such molecules can act locally in the gut or liver to activate xenobiotic defense pathways that trigger beneficial systemic effects on the immune system. We discuss this hypothesis in the context of four plant-derived molecules with immunomodulatory activity: indigo, polysaccharides, colchicine, and ginsenosides. We end by proposing research strategies for identification of novel immunomodulatory drugs from herbal medicine sources that are informed by the possibility of local action in the gut or liver, leading to generation of systemic immune mediators.

Huanglianjiedu Decoction as an effective treatment for oral squamous cell carcinoma based on network pharmacology and experimental validation

Background

Oral squamous cell carcinoma (OSCC) is one of malignant tumors in oral and maxillofacial region with high fatality. Huanglianjiedu Decoction (HLJDD) is a well-known traditional Chinese medicinal prescription, which consists of Coptis chinensis Franch, Scutellaria baicalensis Georgi, Phellodendron amurense Rupr and Gardenia jasminoides J.Ellis. Some clinical studies showed HLJDD had good effectiveness on OSCC, but the mechanism is unclear.

Methods

In this study, potential components of HLJDD and putative targets were screened by Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). Combining with potential targets of OSCC searched from Therapeutic Target Database (TTD) and Online Mendelian Inheritance in Man (OMIM), we drew protein–protein interaction (PPI) network by Cytoscape v3.2.0 software. After topological analysis we got core targets and further did Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Then we did the in vitro experiments to verify the major biological processes (cell cycle, apoptosis and proliferation) and signaling pathways (mitogen-activated protein kinase (MAPK), nuclear factor-kappa B (NF-κB), protein kinase B (AKT)) on OSCC cell lines, SCC-25 and CAL-27.

Results

The potential component targets number of Coptis chinensis Franch, Scutellaria baicalensis Georgi, Phellodendron amurense Rupr and Gardenia jasminoides J.Ellis were 39, 93, 81and 88, respectively. Then we got 52 core targets which enriched in cell cycle, apoptosis, proliferation, MAPK activation etc. and obtained TOP30 pathways. On SCC-25 and CAL-27, HLJDD suppressed cell proliferation, induced late apoptosis and inhibited cell invasion and migration which were consistent with the results from network pharmacology analysis. Additionally, in cell cycle, we confirmed HLJDD inhibited G1 phase and arrested in S phase to reduce cell proliferation on SCC-25. In signaling pathways, HLJDD inhibited the phosphorylation of extracellular regulatory protein kinase 1/2 (ERK1/2) and NF-κB p65 (S468) on SCC-25 and CAL-27.

Conclusions

HLJDD played a potential therapeutic role on OSCC via inhibiting p-ERK1/2 and p-NF-κB p65 (S468).

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02201-6.

Nardosinone Alleviates Parkinson's Disease Symptoms in Mice by Regulating Dopamine D2 Receptor

Nardostachyos Radix et Rhizoma (nardostachys) is the root and rhizome of Nardostachys jatamansi DC. Recent studies have shown that nardostachys may exert an anti-PD effect. In this study, the UHPLC-LTQ-Orbitrap-MS method was used to analyze the brain components of nardostachys in rats. Based on the results of UHPLC-LTQ-Orbitrap-MS analysis, nardosinone was identified to be the most effective anti-PD compound in nardostachys. To further verify this inference, a mouse PD model was established and the effect of nardosinone on PD mice was determined using classic behavioral tests. The results showed that nardosinone was indeed effective for relieving PD symptoms in mice. Moreover, network pharmacology analysis was used to elucidate the mechanism underlying the anti-PD effect of nardosinone. Dopamine receptor D2 (DRD2) was identified as the key target of nardosinone-PD interaction network, which was further verified by molecular docking and Western blotting. The results demonstrated that nardosinone and DRD2 could interact with each other. Furthermore, the expression level of DRD2 was decreased in the brain tissue of PD mice, and nardosinone could restore its expression to a certain extent. In conclusion, our findings suggest that nardosinone may reduce the motor and cognitive symptoms in the animal PD model by regulating DRD2 expression.

Evaluating the Therapeutic Mechanisms of Selected Active Compounds in Cornus Officinalis and Paeonia Lactiflora in Rheumatoid Arthritis via Network Pharmacology Analysis

Cornus officinalis Sieb et. Zucc and Paeonia lactiflora Pall. have exhibited favorable therapeutic effects against rheumatoid arthritis (RA), but the specific mechanisms of their active compounds remain unclear. The aim of this study was to comprehensively analyze the therapeutic mechanisms of selected active compounds in Cornus officinalis (loganin, ursolic acid, and morroniside) and Paeonia lactiflora (paeoniflorin and albiflorin) via network pharmacology. The pharmacological properties of the five active compounds were evaluated and their potential target genes were identified by database screening. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes functional analysis were performed to determine the enriched molecular pathways associated with the active compounds. Using network pharmacology tools, eight genes (IL1β, VEGFA, STAT3, TP53, IL6, TNF, FOS, and LGALS3) were identified as common targets between RA and the five active compounds. Molecular docking simulation revealed the compound-target relationship between the five active compounds and three selected targets from the eight common ones (LGALS3, STAT3, and VEGFA). The compound-target relationships were subsequently validated via preliminary in vivo experiments in a rat model of collagen-induced arthritis. Rats subjected to collagen-induced arthritis showed increased protein expression of LGALS3, STAT3, and VEGFA in synovial tissues. However, treatment using Cornus officinalis or/and Paeonia lactiflora, as well as their most drug-like active compounds (ursolic acid or/and paeoniflorin, respectively, identified based on pharmacological properties), attenuated the expression of these three targets, as previously predicted. Collectively, network pharmacology allowed the pharmacological and molecular roles of Cornus officinalis and Paeonia lactiflora to be systematically revealed, further establishing them as important candidate drugs in the treatment and management of RA.

A review on drug repurposing applicable to COVID-19

Drug repurposing involves the identification of new applications for existing drugs at a lower cost and in a shorter time. There are different computational drug-repurposing strategies and some of these approaches have been applied to the coronavirus disease 2019 (COVID-19) pandemic. Computational drug-repositioning approaches applied to COVID-19 can be broadly categorized into (i) network-based models, (ii) structure-based approaches and (iii) artificial intelligence (AI) approaches. Network-based approaches are divided into two categories: network-based clustering approaches and network-based propagation approaches. Both of them allowed to annotate some important patterns, to identify proteins that are functionally associated with COVID-19 and to discover novel drug–disease or drug–target relationships useful for new therapies. Structure-based approaches allowed to identify small chemical compounds able to bind macromolecular targets to evaluate how a chemical compound can interact with the biological counterpart, trying to find new applications for existing drugs. AI-based networks appear, at the moment, less relevant since they need more data for their application.

FangNet: Mining herb hidden knowledge from TCM clinical effective formulas using structure network algorithm

The use of herbs to treat various human diseases has been recorded for thousands of years. In Asia's current medical system, numerous herbal formulas have been repeatedly verified to confirm their effectiveness in different periods, which is a great resource for drug innovation and discovery. Through the mining of these clinical effective formulas by network pharmacology and bioinformatics analysis, important biologically active ingredients derived from these natural products might be discovered. As modern medicine requires a combination of multiple drugs for the treatment of complex diseases, previously clinical formulas are also combinations of various herbs according to the main causes and accompanying symptoms. However, the herbs that play a major role in the treatment of diseases are always unclear. Therefore, how to rank each herb's relative importance and determine the core herbs, is the first step to assisting herb selection for active ingredients discovery. To solve this problem, we built the platform FangNet, which ranks all herbs on their relative topological importance using the PageRank algorithm, based on the constructed symptom-herb network from a collection of clinical empirical prescriptions. Three types of herb hidden knowledge, including herb importance rank, herb-herb co-occurrence, and associations to symptoms, were provided in an interactive visualization. Moreover, FangNet has designed role-based permission for teams to store, analyze, and jointly interpret their clinical formulas, in an easy and secure collaboration environment, aiming at creating a central hub for massive symptom-herb connections. FangNet can be accessed at http://fangnet.org or http://fangnet.herb.ac.cn.

Mechanism of Action of Bu-Fei-Yi-Shen Formula in Treating Chronic Obstructive Pulmonary Disease Based on Network Pharmacology Analysis and Molecular Docking Validation

Objective

To explore the mechanism of action of Bu-Fei-Yi-Shen formula (BFYSF) in treating chronic obstructive pulmonary disease (COPD) based on network pharmacology analysis and molecular docking validation.

Methods

First of all, the pharmacologically active ingredients and corresponding targets in BFYSF were mined by the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database, the analysis platform, and literature review. Subsequently, the COPD-related targets (including the pathogenic targets and known therapeutic targets) were identified through the TTD, CTD, DisGeNet, and GeneCards databases. Thereafter, Cytoscape was employed to construct the candidate component-target network of BFYSF in the treatment of COPD. Moreover, the cytoHubba plug-in was utilized to calculate the topological parameters of nodes in the network; then, the core components and core targets of BFYSF in the treatment of COPD were extracted according to the degree value (greater than or equal to the median degree values for all nodes in the network) to construct the core network. Further, the Autodock vina software was adopted for molecular docking study on the core active ingredients and core targets, so as to verify the above-mentioned network pharmacology analysis results. Finally, the Omicshare database was applied in enrichment analysis of the biological functions of core targets and the involved signaling pathways.

Results

In the core component-target network of BFYSF in treating COPD, there were 30 active ingredients and 37 core targets. Enrichment analysis suggested that these 37 core targets were mainly involved in the regulation of biological functions, such as response to biological and chemical stimuli, multiple cellular life processes, immunity, and metabolism. Besides, multiple pathways, including IL-17, Toll-like receptor (TLR), TNF, and HIF-1, played certain roles in the effect of BFYSF on treating COPD.

Conclusion

BFYSF can treat COPD through the multicomponent, multitarget, and multipathway synergistic network, which provides basic data for intensively exploring the mechanism of action of BFYSF in treating COPD.

Anti-Alzheimer's Disease Molecular Mechanism of Acori Tatarinowii Rhizoma Based on Network Pharmacology

BACKGROUND Acori Tatarinowii Rhizoma (ATR), a traditional Chinese herbal medicine, is used to treat Alzheimer's disease (AD), which is a worldwide degenerative brain disease. The aim of this study was to identify the potential mechanism and molecular targets of ATR in AD by using network pharmacology. MATERIAL AND METHODS The potential targets of the active ingredients of ATR were predicted by PharmMapper, and the targets of Alzheimer's disease were searched by DisGeNET. All screened genes were intersected to obtain potential targets for the active ingredients of ATR. The protein-protein interaction network of possible targets was established by STRING, GO Enrichment, and KEGG pathway enrichment analyses using the Annotation of DAVID database. Next, Cytoscape was used to build the "components-targets-pathways" networks. Additionally, a "disease-component-gene-pathways" network was constructed and verified by molecular docking methods. In addition, the active constituents ß-asarone and ß-caryophyllene were used to detect Aß₁₋₄₂-mediated SH-SY5Y cells, and mRNA expression levels of APP, Tau, and core target genes were estimated by qRT-PCR. RESULTS The results showed that the active components of ATR participate in related biological processes such as cancer, inflammation, cellular metabolism, and metabolic pathways and are closely related to the 13 predictive targets: ESR1, PPARG, AR, CASP3, JAK2, MAPK14, MAP2K1, ABL1, PTPN1, NR3C1, MET, INSR, and PRKACA. The ATR active components of ß-caryophyllene significantly reduced the mRNA expression levels of APP, TAU, ESR1, PTPN1, and JAK2. CONCLUSIONS The targets and mechanism corresponding to the active ingredients of ATR were investigated systematically, and novel ideas and directions were provided to further study the mechanism of ATR in AD.

Synergistic Effects of Erzhi Pill Combined With Methotrexate on Osteoblasts Mediated via the Wnt1/LRP5/β-Catenin Signaling Pathway in Collagen-Induced Arthritis Rats

Rheumatoid arthritis (RA) is a chronic systemic autoimmune disease characterized by chronic synovitis, bone erosion, and bone loss. Erzhi Pill (EZP), a classic Chinese patent medicine, is often used to treat osteoporosis and shows a capacity for bone metabolism regulation. Methotrexate (MTX), an essential drug for RA treatment, has been reported to inhibit generalized bone loss in RA patients. However, the combined therapeutic effects and mechanism of EZP and MTX in RA have not been fully elucidated. The aim of this study was to investigate the synergistic effect of EZP and MTX on RA and to explore the underlying mechanism through network pharmacological prediction and experimental verification. Chemical compounds of EZP, human target proteins of EZP and MTX, and RA-related human genes were identified in the Encyclopedia of Traditional Chinese Medicine database, PubChem database, and NCBI database, respectively. The molecular network of EZP and MTX in RA was generated and analyzed with Ingenuity Pathway Analysis software according to the datasets. Then, MTX monotherapy, EZP monotherapy, and combined MTX and EZP therapy were administered to collagen-induced arthritis rats, followed by assessment of pathological score, bone damage, bone alkaline phosphatases (BALP), and tartrate-resistant acid phosphatase (TRACP), and of gene levels related to the Wnt1/LRP5/β-catenin pathway according to network pharmacological analysis. Finally, serum samples from MTX-, EZP- and MTX+EZP-treated rats were used to treat the rat osteoblast (OB)-like UMR-106 cell line to evaluate gene levels related to Wnt1/LRP5/β-catenin. Network pharmacological analysis showed that the Wnt/β-catenin signaling pathway was the top signaling pathway shared among MTX, EZP, and RA. The results from in vivo experiments indicated that EZP combined with MTX reduced arthritis severity, alleviated ankle bone damage, increased BALP and decreased TRACP serum levels, and regulated the mRNA expression of Wnt1, LRP5, β-catenin, Runx2, BALP, and BGP in the ankles. In vitro experiments showed that EZP combined with MTX could also improve the expression of genes related to the Wnt1/LRP5/β-catenin pathway. This study demonstrated that EZP in combination with MTX played a synergistic role in regulating OBs in RA, which was connected to the modulatory effect of EZP and MTX on the Wnt1/LRP5/β-catenin signaling pathway.

Associating 197 Chinese herbal medicine with drug targets and diseases using the similarity ensemble approach

Chinese herbal medicine (CHM) addresses complex diseases through polypharmacological interactions. However, systematic studies of herbal medicine pharmacology remain challenging due to the complexity of CHM ingredients and their interactions with various targets. In this study, we aim to address this challenge with computational approaches. We investigated the herb-target-disease associations of 197 commonly prescribed CHMs using the similarity ensemble approach and DisGeNET database. We demonstrated that this method can be applied to associate herbs with their putative targets. In the case study of three well-known herbs, Radix Glycyrrhizae, Flos Lonicerae, and Rhizoma Coptidis, approximately 70% of the predicted targets were supported by scientific literature. By linking 406 targets to 2439 annotated diseases, we further analyzed the pharmacological functions of 197 herbs. Finally, we proposed a strategy of target-oriented herbal formula design and illustrated the target profiles for four common chronic diseases, namely, Alzheimer's disease, depressive disorder, hypertensive disease, and non-insulin-dependent diabetes mellitus. This computational approach holds great potential in the target identification of herbs, understanding the molecular mechanisms of CHM, and designing novel herbal formulas.

UPLC-Q-TOF-MS Study of the Mechanism of THSWD for Breast Cancer Treatment

Taohong Siwu decoction (THSWD) is a classic traditional Chinese medicine (TCM) prescription that is widely used in the clinical treatment of gynecological and cerebrovascular diseases. Here we used a method that coupled ultra-performance liquid chromatography to quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) in which both positive and negative ion modes were established to investigate the major constituents in THSWD. A Waters ACQUITY UPLC BEH C18 column (2.1 mm×100 mm, 1.7 μm) was used to separate the aqueous extract of THSWD. The mobile phase consisted of 0.1% aqueous formic acid (A) and acetonitrile (B). Ninety-five components were identified in two different ion modes, including aromatic acids, flavones, polysaccharides, volatile oils monoterpene glycosides, aromatic cyanogenic glycosides, and others. Pathological changes in tumors and serum expression of interleukin-4 in a mouse model of breast cancer were detected after THSWD treatment. The results showed that THSWD had obvious therapeutic effects. This study establishes a material basis for the use of THSWD in the treatment of breast cancer.

Combined network pharmacology and virtual reverse pharmacology approaches for identification of potential targets to treat vascular dementia

Dementia is a major cause of disability and dependency among older people. If the lives of people with dementia are to be improved, research and its translation into druggable target are crucial. Ancient systems of healthcare (Ayurveda, Siddha, Unani and Sowa-Rigpa) have been used from centuries for the treatment vascular diseases and dementia. This traditional knowledge can be transformed into novel targets through robust interplay of network pharmacology (NetP) with reverse pharmacology (RevP), without ignoring cutting edge biomedical data. This work demonstrates interaction between recent and traditional data, and aimed at selection of most promising targets for guiding wet lab validations. PROTEOME, DisGeNE, DISEASES and DrugBank databases were used for selection of genes associated with pathogenesis and treatment of vascular dementia (VaD). The selection of new potential drug targets was made by methods of NetP (DIAMOnD algorithm, enrichment analysis of KEGG pathways and biological processes of Gene Ontology) and manual expert analysis. The structures of 1976 phytomolecules from the 573 Indian medicinal plants traditionally used for the treatment of dementia and vascular diseases were used for computational estimation of their interactions with new predicted VaD-related drug targets by RevP approach based on PASS (Prediction of Activity Spectra for Substances) software. We found 147 known genes associated with vascular dementia based on the analysis of the databases with gene-disease associations. Six hundred novel targets were selected by NetP methods based on 147 gene associations. The analysis of the predicted interactions between 1976 phytomolecules and 600 NetP predicted targets leaded to the selection of 10 potential drug targets for the treatment of VaD. The translational value of these targets is discussed herewith. Twenty four drugs interacting with 10 selected targets were identified from DrugBank. These drugs have not been yet studied for the treatment of VaD and may be investigated in this field for their repositioning. The relation between inhibition of two selected targets (GSK-3, PTP1B) and the treatment of VaD was confirmed by the experimental studies on animals and reported separately in our recent publications.

Chinese Medicinal Herbs Targeting the Gut-Liver Axis and Adipose Tissue-Liver Axis for Non-Alcoholic Fatty Liver Disease Treatments: The Ancient Wisdom and Modern Science

Non-alcoholic fatty liver disease (NAFLD) is one of the most common chronic liver diseases worldwide. The pathogenesis of NAFLD is complex. Frontline western medicines only ameliorate the symptoms of NAFLD. On the contrary, the uniqueness of Chinese medicine in its interpretation of NAFLD and the holistic therapeutic approach lead to a promising therapeutic efficacy. Recent studies reveal that the gut-liver axis and adipose tissue-liver axis play important roles in the development of NAFLD. Interestingly, with advanced technology, many herbal formulae are found to target the gut-liver axis and adipose tissue-liver axis and resolve the inflammation in NAFLD. This is the first review summarizes the current findings on the Chinese herbal formulae that target the two axes in NAFLD treatment. This review not only demonstrates how the ancient wisdom of Chinese medicine is being interpreted by modern pharmacological studies, but also provides valuable information for the further development of the herbal-based treatment for NAFLD.

A System-Level Investigation into the Mechanisms of Apigenin Against Inflammation

Apigenin is a natural flavone that possesses excellent biological activities especially against aging and cancer. However, the underlying mode of its action is not yet revealed. The purpose of this study was to examine the pharmacological mechanisms of apigenin using the knowledge of network pharmacology, protein-protein interaction (PPI) databases and biological processes analysis through Cytoscape.

Apigenin targets were retrieved through PASS Prediction and STITCH database and the interactive associations between these targets were studied using STITCH, followed by GO (gene ontology) and pathway enrichment analysis.

As a result of target search, 125 protein targets were retrieved. Moreover, 216 GO terms related to various biological processes, 16 GO terms for various molecular processes, 5 GO terms for the cellular components, and 52 Kyoto Encyclopedia of Genes and Genomes pathway terms were achieved by analyzing gene functional annotation clusters and abundance values of these targets. Most of these terms are strongly associated with inflammation through various pathways, for example, FOXO, mammalian target of rapamycin, tumor necrosis factor, p53, AMP-activated protein kinase, p13K-AKT, and mitogen-activated protein kinase, which play an important role in inflammation, aging and cancer.

Apigenin can be used to treat inflammation, aging, and cancer with an underlying mechanism of inflammation suppression. This study contributed excellent information for a better understanding of the modes of action of apigenin. However, further studies such as docking and MD simulation are required to understand the therapeutic and toxicological roles of these targets of apigenin.

Drug repurposing in alternative medicine: herbal digestive Sochehwan exerts multifaceted effects against metabolic syndrome

New drug development is a challenging process that requires high-risk, huge costs and long lead times. Therefore, drug repurposing is considered a strategic and economic way towards successful drug development. Sochehwan (SCH) is a herbal formula well known as a digestive aid in traditional oriental medicine, is referred to in classic medical texts, and is available as an over-the-counter drug for indications of digestive ailments. Interestingly, another medical text written in earlier age describes different indication of SCH yet to be examined. We conducted a series of investigations using maturated adipocytes, free fatty acid (FFA) induced hepatic steatosis model in vitro and high-fat diet (HFD) mice model in vivo. Exposure to SCH regulated expression of adipogenic genes and proteins, significantly inhibiting formation of lipid droplets in 3T3-L1 cells. Similarly, SCH treatment modulated proteins related with energy metabolism decreasing lipid accumulation in FFA induced HepG2 cells. Furthermore, HFD-fed c57BL/6 J mice supplemented with SCH exhibited significant changes in serum glucose and lipid profiles. Histologic analysis of mice liver and adipose tissue showed that SCH administration attenuated hepatic steatosis and hypertrophy of adipose tissue. In overall, the results show that SCH can potentially be used to treat metabolic syndrome (MetS) by enhancing glucose metabolism and inhibiting lipogenesis through activating AMP-activated protein kinase (AMPK) and its downstream signaling. Furthermore, it seems to be a feasible drug repurposing strategy for drugs originating from alternative medicine to revise the value for buried indications of some herbal prescription in old traditional Chinese Medicine (TCM) classics.

Drug repositioning of herbal compounds via a machine-learning approach

Background

Drug repositioning, also known as drug repurposing, defines new indications for existing drugs and can be used as an alternative to drug development. In recent years, the accumulation of large volumes of information related to drugs and diseases has led to the development of various computational approaches for drug repositioning. Although herbal medicines have had a great impact on current drug discovery, there are still a large number of herbal compounds that have no definite indications.

Results

In the present study, we constructed a computational model to predict the unknown pharmacological effects of herbal compounds using machine learning techniques. Based on the assumption that similar diseases can be treated with similar drugs, we used four categories of drug-drug similarity (e.g., chemical structure, side-effects, gene ontology, and targets) and three categories of disease-disease similarity (e.g., phenotypes, human phenotype ontology, and gene ontology). Then, associations between drug and disease were predicted using the employed similarity features. The prediction models were constructed using classification algorithms, including logistic regression, random forest and support vector machine algorithms. Upon cross-validation, the random forest approach showed the best performance (AUC = 0.948) and also performed well in an external validation assessment using an unseen independent dataset (AUC = 0.828). Finally, the constructed model was applied to predict potential indications for existing drugs and herbal compounds. As a result, new indications for 20 existing drugs and 31 herbal compounds were predicted and validated using clinical trial data.

Conclusions

The predicted results were validated manually confirming the performance and underlying mechanisms – for example, irinotecan as a treatment for neuroblastoma. From the prediction, herbal compounds were considered to be drug candidates for related diseases which is important to be further developed. The proposed prediction model can contribute to drug discovery by suggesting drug candidates from herbal compounds which have potentials but few were studied.

Electronic supplementary material

The online version of this article (10.1186/s12859-019-2811-8) 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.

A Network Pharmacology Analysis to Explore the Effect of Astragali Radix-Radix Angelica Sinensis on Traumatic Brain Injury

Traumatic brain injury (TBI) is a critical public health and socioeconomic problem worldwide. The herb pair Astragali Radix (AR)-Radix Angelica Sinensis (RAS) is a common prescribed herbal formula or is added to other Chinese medicine prescriptions for traumatic brain injury (TBI) treatment. However, the underlying mechanisms are unclear. In this study, we aimed to explore the active ingredients and action targets of AR-RAS based on the combined methods of network pharmacology prediction and experimental verification. Furthermore, the corresponding potential mechanisms of “multicomponents, multitargets, and multipathways” were disclosed. Methods. A network pharmacology approach including ADME (absorption, distribution, metabolism, and excretion) filter analysis, target prediction, known therapeutic targets collection, Gene Ontology (GO), pathway enrichment analysis, and network construction was used in this study. Further verification experiments were performed to reveal the therapeutic effects of AR-RAS in a rat model of TBI. Results. The comprehensive systematic approach was to successfully identify 14 bioactive ingredients in AR-RAS, while 33 potential targets hit by these ingredients related to TBI. Based on GO annotation analysis, multiple biological processes were significantly regulated by AR-RAS. In addition, 89 novel signaling pathways (P<0.05) underlying the effects of AR-RAS for TBI treatment were identified by DAVID. The neurotrophin signaling pathway was suggested as the major related pathway targeted by AR-RAS to improve axonal growth. The animal experiment confirmed that AR-RAS significantly induced tissue recovery and improved neurological deficits on the 14th day (P<0.01). Treatment with AR-RAS markedly reduced the protein and mRNA expression level of NogoA in the hippocampus of TBI rats. Conclusion. Our work illuminates the “multicompounds, multitargets, and multipathways” curative action of AR-RAS in the treatment of TBI by network pharmacology. The animal experiment verifies the effects of AR-RAS on neurological function improvement and axonal outgrowth via downregulation of NogoA expression, providing a theoretical basis for further research on treatment of TBI.

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.

Approaches in studying the pharmacology of Chinese Medicine formulas: bottom-up, top-down-and meeting in the middle

Investigating the pharmacology is key to the modernization of Chinese Medicine (CM) formulas. However, identifying which are the active compound(s) of CM formulas, which biological entities they target, and through which signaling pathway(s) they act to modify disease symptoms, are still difficult tasks for researchers, even when equipped with an arsenal of advanced modern technologies. Multiple approaches, including network pharmacology, pharmaco-genomics, -proteomics, and -metabolomics, have been developed to study the pharmacology of CM formulas. They fall into two general categories in terms of how they tackle a problem: bottom-up and top-down. In this article, we compared these two different approaches in several dimensions by using the case of MaZiRenWan (MZRW, also known as Hemp Seed Pill), a CM herbal formula for functional constipation. Multiple hypotheses are easy to be proposed in the bottom-up approach (e.g. network pharmacology); but these hypotheses are usually false positives and hard to be tested. In contrast, it is hard to suggest hypotheses in the top-down approach (e.g. pharmacometabolomics); however, once a hypothesis is proposed, it is much easier to be tested. Merging of these two approaches could results in a powerful approach, which could be the new paradigm for the pharmacological study of CM formulas.

Network pharmacology-based and clinically relevant prediction of the active ingredients and potential targets of Chinese herbs in metastatic breast cancer patients

Chinese Herbal Medicine (CHM) plays a significant role in breast cancer treatment. We conduct the study to ascertain the relative molecular targets of effective Chinese herbs in treating stage IV breast cancer.Survival benefit of CHM was verified by Kaplan-Meier method and Cox regression analysis. A bivariate correlation analysis was used to find and establish the effect of herbs in complex CHM formulas. A network pharmacological approach was adopted to explore the potential mechanisms of CHM.Patients in the CHM group had a median survival time of 55 months, which was longer than the 23 months of patients in the non-CHM group. Cox regression analysis indicated that CHM was an independent protective factor. Correlation analysis showed that 10 herbs were strongly correlated with favorable survival outcomes (P<0.01). Bioinformatics analyses suggested that the 10 herbs might achieve anti-breast cancer activity primarily through inhibiting HSP90, ERα and TOP-II related pathways.

Matrine Ameliorates Colorectal Cancer in Rats via Inhibition of HMGB1 Signaling and Downregulation of IL-6, TNF-α, and HMGB1

Matrine may be protective against colorectal cancer (CRC), but how it may work is unclear. Thus, we explored the underlying mechanisms of matrine in CRC. Matrine-related proteins and CRC-related genes and therapeutic targets of matrine in CRC were predicted using a network pharmacology approach. Five targets, including interleukin 6 (IL-6), the 26S proteasome, tumor necrosis factor alpha (TNF-α), transforming growth factor beta 1 (TGF-β1) and p53, and corresponding high-mobility group box 1 (HMGB1) signaling and T helper cell differentiation were thought to be associated with matrine's mechanism. Expression of predicted serum targets were verified in a 1,2-dimethylhydrazine dihydrochloride-induced CRC model rats that were treated with matrine (ip) for 18 weeks. Data show that matrine suppressed CRC growth and decreased previously elevated expression of IL-6, TNF-α, p53, and HMGB1. Matrine may have had a therapeutic effect on CRC via inhibition of HMGB1 signaling, and this occurred through downregulation of IL-6, TNF-α, and HMGB1.

Effects of Tao-Hong-Si-Wu decoction on acute blood stasis in rats based on a LC-Q/TOF-MS metabolomics and network approach

A novel approach using metabolomics coupled with a metabolic network was used to investigate the effects of Tao-Hong-Si-Wu decoction (THSWD) on the rat model of acute blood stasis syndrome. Acute blood stasis syndrome was induced by placing the rats in ice-cold water following two injections with epinephrine. The hemorheological indicators [whole blood viscosity (WBV) and plasma viscosity (PV)] and the blood coagulation indicators [thrombin time (TT), prothrombin time (PT), activated partial thromboplastin time (APTT) and fibrinogen (FIB)] were detected. The nonparametric univariate method and multivariate statistical analysis were performed for determining the potential biomarkers. A correlation map was structured between biochemical indicators and hub metabolites to explain the effects mechanism of THSWD. After the administration of THSWD, the levels of WBV, PV, TT, APTT and FIB returned to levels observed in the control group. According to metabolomics coupled with metabolic network analysis, the intervention of THSWD in rats with acute blood stasis syndrome induced substantial and characteristic changes in their metabolic profiles. Fifteen metabolites were screened, which mainly involved 10 pathways and five hub metabolites, namely, l-glutamate, l-phenylalanine, N-acylsphingosine, arachidonic acid and phosphatidate. The biochemical indicators and hub metabolites could be adjusted to close to normal levels by THSWD. Therefore, combining metabolomics and metabolic network helped to evaluate the effects of THSWD on acute blood stasis.

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.

Chinese Herbal Medicine Meets Biological Networks of Complex Diseases: A Computational Perspective

With the rapid development of cheminformatics, computational biology, and systems biology, great progress has been made recently in the computational research of Chinese herbal medicine with in-depth understanding towards pharmacognosy. This paper summarized these studies in the aspects of computational methods, traditional Chinese medicine (TCM) compound databases, and TCM network pharmacology. Furthermore, we chose arachidonic acid metabolic network as a case study to demonstrate the regulatory function of herbal medicine in the treatment of inflammation at network level. Finally, a computational workflow for the network-based TCM study, derived from our previous successful applications, was proposed.

Study on material base and action mechanism of compound Danshen dripping pills for treatment of atherosclerosis based on modularity analysis

ETHNOPHARMACOLOGICAL RELEVANCE

Traditional Chinese medicine (TCM) has been widely used in China and its surrounding countries in clinical treatments for centuries-long time. However, due to the complexity of TCM constituents, both action mechanism and material base of TCM remain nearly unknown.

AIM OF THE STUDY

The present study was designed to uncover the action mechanism and material base of TCM in a low-cost manner.

MATERIALS AND METHODS

Compound Danshen dripping pills (DSP) is a widely used TCM for treatment of atherosclerosis, and was researched here to demonstrate the effectiveness of our method. We constructed a heterogeneous network for DSP, identified the significant network module, and analyzed the primary pharmacological units by performing GO and pathways enrichment analysis.

RESULTS

Two significant network modules were identified from the heterogeneous network of DSP, and three compounds out of four hub nodes in the network were found to intervene in the process of atherosclerosis. Moreover, 13 out of 20 enriched pathways that were ranked in top 10 corresponding to both the two pharmacological units were found to be involved in the process of atherosclerosis.

CONCLUSIONS

Quercetin, luteolin and apigenin may be the main active compounds which modulate the signaling pathways, such as metabolism of xenobiotics by cytochrome P450, retinol metabolism, etc. The present method helps reveal the action mechanism and material base of DSP for treatment of atherosclerosis.

To Unveil the Molecular Mechanisms of Qi and Blood through Systems Biology-Based Investigation into Si-Jun-Zi-Tang and Si-Wu-Tang formulae

Traditional Chinese Medicine (TCM) is increasingly getting clinical application worldwide. But its theory like QI-Blood is still abstract. Actually, Qi deficiency and blood deficiency, which were treated by Si-Jun-Zi-Tang (SJZT) and Si-Wu-Tang (SWT) respectively, have characteristic clinical manifestations. Here, we analyzed targets of the ingredients in SJZT and SWT to unveil potential biologic mechanisms between Qi deficiency and blood deficiency through biomedical approaches. First, ingredients in SWT and SJZT were retrieved from TCMID database. The genes targeted by these ingredients were chosen from STITCH. After enrichment analysis by Gene Ontology (GO) and DAVID, enriched GO terms with p-value less than 0.01 were collected and interpreted through DAVID and KEGG. Then a visualized network was constructed with ClueGO. Finally, a total of 243 genes targeted by 195 ingredients of SWT formula and 209 genes targeted by 61 ingredients of SJZT were obtained. Six metabolism pathways and two environmental information processing pathways enriched by targets were correlated with 2 or more herbs in SWT and SJZT formula, respectively.

Hwang-Heuk-San induces apoptosis in HCT116 human colorectal cancer cells through the ROS-mediated activation of caspases and the inactivation of the PI3K/Akt signaling pathway

Hwang-Heuk-San (HHS) is a polyherbal formulation that has been used in traditional Korean medicine for hundreds of years to treat gastrointestinal malignancy. However, to date, the mechanisms responsible for the anticancer effects remain unclear. In the present study, we investigated the anticancer effects of HHS using HCT116 human colorectal cancer (CRC) cells. Our results showed that HHS treatment significantly reduced cell survival and increased apoptotic cell death in a concentration-dependent manner. The treatment of HCT116 cells with HHS also significantly elevated the accumulation of reactive oxygen species (ROS), which was followed by the attenuation of the mitochondrial membrane potential through the upregulation of Bax and the downregulation of Bcl-2, which was accompanied by the release of cytochrome c to the cytosol. In addition, HHS treatment caused the truncation of Bid and activated the caspases (caspase-8, -9 and -3), which was associated with the induction of the Fas ligand, the death receptors (DRs), DR4 and DR5, downregulation of the inhibitors of protein expression in the apoptosis protein family, and the degradation of poly(ADP-ribose)-polymerase. However, a pan-caspase inhibitor reversed the HHS-induced apoptosis and growth suppression, indicating that HHS induces apoptosis though a caspase-dependent intrinsic and extrinsic apoptotic pathway in HCT116 cells. Moreover, HHS treatment inhibited the activation of phosphatidylinositol-3-kinase (PI3K)/Akt signaling, and a pharmacological inhibitor of PI3K significantly potentiated the apoptotic effects of HHS when employed in combination in HCT116 cells. Furthermore, the blocking of ROS generation by antioxidant N-acetyl cysteine attenuated the HHS-induced release of cytochrome c, caspase activation and PI3K/Akt inactivation, thereby preventing HHS-induced apoptosis and reduction in cell viability. These findings suggest that HHS-induced ROS generation is required for caspase-dependent apoptotic cell death involving inhibition of the PI3K/Akt signaling pathway in HCT116 cells. Overall, our findings suggest that HHS may be an effective treatment for CRC cancer, and further studies are required to identify the active compounds in HHS.

Herbal traditional Chinese medicine and its evidence base in gastrointestinal disorders

Herbal traditional Chinese medicine (TCM) is used to treat several ailments, but its efficiency is poorly documented and hence debated, as opposed to modern medicine commonly providing effective therapies. The aim of this review article is to present a practical reference guide on the role of herbal TCM in managing gastrointestinal disorders, supported by systematic reviews and evidence based trials. A literature search using herbal TCM combined with terms for gastrointestinal disorders in PubMed and the Cochrane database identified publications of herbal TCM trials. Results were analyzed for study type, inclusion criteria, and outcome parameters. Quality of placebo controlled, randomized, double-blind clinical trials was poor, mostly neglecting stringent evidence based diagnostic and therapeutic criteria. Accordingly, appropriate Cochrane reviews and meta-analyses were limited and failed to support valid, clinically relevant evidence based efficiency of herbal TCM in gastrointestinal diseases, including gastroesophageal reflux disease, gastric or duodenal ulcer, dyspepsia, irritable bowel syndrome, ulcerative colitis, and Crohn's disease. In conclusion, the use of herbal TCM to treat various diseases has an interesting philosophical background with a long history, but it received increasing skepticism due to the lack of evidence based efficiency as shown by high quality trials; this has now been summarized for gastrointestinal disorders, with TCM not recommended for most gastrointestinal diseases. Future studies should focus on placebo controlled, randomized, double-blind clinical trials, herbal product quality and standard criteria for diagnosis, treatment, outcome, and assessment of adverse herb reactions. This approach will provide figures of risk/benefit profiles that hopefully are positive for at least some treatment modalities of herbal TCM. Proponents of modern herbal TCM best face these promising challenges of pragmatic modern medicine by bridging the gap between the two medicinal cultures.

Novel Holistic Approaches for Overcoming Therapy Resistance in Pancreatic and Colon Cancers

Gastrointestinal (GI) cancers, such as of the colon and pancreas, are highly resistant to both standard and targeted therapeutics. Therapy-resistant and heterogeneous GI cancers harbor highly complex signaling networks (the resistome) that resist apoptotic programming. Commonly used gemcitabine or platinum-based regimens fail to induce meaningful (i.e. disease-reversing) perturbations in the resistome, resulting in high rates of treatment failure. The GI cancer resistance networks are, in part, due to interactions between parallel signaling and aberrantly expressed microRNAs (miRNAs) that collectively promote the development and survival of drug-resistant cancer stem cells with epithelial-to-mesenchymal transition (EMT) characteristics. The lack of understanding of the resistance networks associated with this subpopulation of cells as well as reductionist, single protein-/pathway-targeted approaches have made 'effective drug design' a difficult task. We propose that the successful design of novel therapeutic regimens to target drug-resistant GI tumors is only possible if network-based drug avenues and agents, in particular 'natural agents' with no known toxicity, are correctly identified. Natural agents (dietary agents or their synthetic derivatives) can individually alter miRNA profiles, suppress EMT pathways and eliminate cancer stem-like cells that derive from pancreatic cancer and colon cancer, by partially targeting multiple yet meaningful networks within the GI cancer resistome. However, the efficacy of these agents as combinations (e.g. consumed in the diet) against this resistome has never been studied. This short review article provides an overview of the different challenges involved in the understanding of the GI resistome, and how novel computational biology can help in the design of effective therapies to overcome resistance.

Therapeutic effects of traditional Chinese medicine in patients with symptomatic cervical ectopy

PURPOSE

The aim of this study is to evaluate the treatment and efficacy of Badushengjigao, a traditional Chinese medicine (TCM) formula, for symptomatic cervical ectopy.

METHOD

A patient self-selected two group comparison study was performed. One hundred patients with symptomatic cervical ectopy admitted to the Central Hospital of E-Zhou (Hubei, China) between July 2013 and July 2014 were enrolled in the study. The patients treated with Badushengjigao were the study group and the patients treated with policresulen suppository were the control group. The medicine was administered through vagina. Patients received a three-month follow-up (once a month). The treatment results were evaluated and analyzed by variance analysis and X(2) test.

RESULTS

The curative rates of the two groups with symptomatic cervical ectopy grade 1 shows no statistical significance. As for grade 2 and grade 3, the curative rates of the study group (phase 2: 72.0%; phase 3: 62.5%) are higher than that of the control group (phase 2: 44.4%; grade 3: 54.5%) with statistical difference (P < 0.05). The study group has less adverse effects (2.5 ± 1.3 days of vagina bleeding, 6 cases of abdominal pain and 2 cases of increased discharge) than the control group (12.5 ± 1.1 days of vagina bleeding, 15 cases of abdominal pain and 42 cases of increased discharge) with distinctive statistical difference (P < 0.01).

CONCLUSION

The TCM formula, Badushengjigao, seems to be more effective than policresulen suppositories in treating symptomatic cervical ectopy phase 2 and phase 3. We suggest that it could be used as an alternative method for symptomatic cervical ectopy treatment, but further study is needed.

Long-term outcome of 31 cases of refractory acute promyelocytic leukemia treated with compound realgar natural indigo tablets administered alternately with chemotherapy

The aim of the present study was to investigate the long-term survival of patients with refractory acute promyelocytic leukemia (APL) that were administered alternately with compound realgar natural indigo tablet (CRNIT) treatment and chemotherapy. In total, 31 patients with refractory APL were administered with CRNIT treatment alternately with chemotherapy. The complete remission (CR) and relapse rates were estimated by bone marrow (BM) examination. The expression of the promyelocytic leukemia-retinoic acid receptor α (PML-RARα) fusion protein and the apoptosis rate in the retinoic acid (RA)-resistant NB4-R1 cell line administered with CRNIT treatment in vitro were measured by western blot analysis and flow cytometry, respectively. The patients were followed up for 12-60 months, with a median follow-up time of 43 months. The total continuous CR rate was 90.32% (28/31), and the duration of response was between 10.3 and 60 months (median, 42.4 months). The total relapse rate was 9.68% (3/31), and the median time of relapse was 13 months (range, 8-27 months). During the treatment with CRNITs, there was no evident BM depression and only limited side-effects were experienced. Additionally, in vitro cell molecular biology results revealed that CRNIT treatment resulted in a marked induction of apoptosis and degradation of the PML-RARα fusion protein. The present results revealed that CRNIT treatment in combination with chemotherapy is an effective and feasible therapy for the treatment of patients with refractory APL.

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.

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.