A systems biology approach to uncovering pharmacological synergy in herbal medicines with applications to cardiovascular disease

Predicting herb-disease associations using network-based measures in human protein interactome

BACKGROUND

Natural herbs are frequently used to treat diseases or to relieve symptoms in many countries. Moreover, as their safety has been proven for a long time, they are considered as main sources of new drug development. However, in many cases, the herbs are still prescribed relying on ancient records and/or traditional practices without scientific evidences. More importantly, the medicinal efficacy of the herbs has to be evaluated in the perspective of MCMT (multi-compound multi-target) effects, but most efforts focus on identifying and analyzing a single compound experimentally. To overcome these hurdles, computational approaches which are based on the scientific evidences and are able to handle the MCMT effects are needed to predict the herb-disease associations.

RESULTS

In this study, we proposed a network-based in silico method to predict the herb-disease associations. To this end, we devised a new network-based measure, WACP (weighted average closest path length), which not only quantifies proximity between herb-related genes and disease-related genes but also considers compound compositions of each herb. As a result, we confirmed that our method successfully predicts the herb-disease associations in the human protein interactome (AUROC = 0.777). In addition, we observed that our method is superior than the other simple network-based proximity measures (e.g. average shortest and closest path length). Additionally, we analyzed the associations between Brassica oleracea var. italica and its known associated diseases more specifically as case studies. Finally, based on the prediction results of the WACP, we suggested novel herb-disease pairs which are expected to have potential relations and their literature evidences.

CONCLUSIONS

This method could be a promising solution to modernize the use of the natural herbs by providing the scientific evidences about the molecular associations between the herb-related genes targeted by multiple compounds and the disease-related genes in the human protein interactome.

The Mechanism of "Treating Different Diseases with the Same Treatment" by Qiangji Jianpi Decoction in Ankylosing Spondylitis Combined with Inflammatory Bowel Disease: A Comprehensive Analysis of Multiple Methods

Background

Ankylosing spondylitis (AS) and inflammatory bowel disease (IBD) are prevalent autoimmune disorders that often co-occur, posing significant treatment challenges. This investigation adopts a multidisciplinary strategy, integrating bioinformatics, network pharmacology, molecular docking, and Mendelian randomization, to elucidate the relationship between AS and IBD and to investigate the potential mechanisms of traditional Chinese medicine formulations, represented by Qiangji Jianpi (QJJP) decoction, in treating these comorbid conditions.

Methods

We utilized databases to pinpoint common targets among AS, IBD, and QJJP decoction's active compounds through intersection analysis. Through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses, we mapped a network in Cytoscape, isolating critical targets. Molecular docking with AutoDock validated the affinity between targets and compounds. ROC analysis and dataset validation assessed diagnostic performance, while Gene Set Enrichment Analysis (GSEA) offered pathway insights. Mendelian randomization explored the AS-IBD causal relationship.

Results

Screening identified 105 targets for QJJP decoction, 414 for AS, and 2420 for IBD, with 85 overlapping. These targets predominantly participate in organismal responses and DNA transcription factor binding, with a significant cellular presence in the endoplasmic reticulum and vesicle lumen. Molecular docking, facilitated by Cytoscape, confirmed IL1A, IFNG, TGFB1, and EDN1 as critical targets, with IFNG demonstrating diagnostic potential through GEO dataset validation. The integration of GSEA with network pharmacology highlighted the therapeutic significance of the relaxin, osteoclast differentiation, HIF-1, and AGE-RAGE signaling pathways in QJJP decoction's action. Mendelian randomization analysis indicated a positive causal relationship between IBD and AS, pinpointing rs2193041 as a key SNP influencing IFNG.

Conclusion

Based on the principle of "treating different diseases with the same method" in traditional Chinese medicine theory, we explored the intricate mechanisms through which QJJP decoction addresses AS and IBD comorbidity. Our research spotlighted the pivotal role of the IFNG gene. IFNG emerges not only as a key therapeutic target but also assumes significance as a potential diagnostic biomarker through its genetic underpinnings. This investigation establishes a solid base for subsequent experimental inquiries. Our findings introduce novel approaches for incorporating traditional Chinese medicine into the treatment of AS-IBD comorbidity, setting the stage for groundbreaking research directions.

Molecular basis and mechanism of action of Albizia julibrissin in depression treatment and clinical application of its formulae

Albizzia julibrissin is empirically used as an antidepressant in clinical practice. Preclinical studies have indicated that its total extracts or bioactive constituents exerted antidepressant-like responses in animal models, providing the molecular basis to reveal its underlying mechanism of action. While attempts have been made to understand the antidepressant effect of A. julibrissin, many fundamental questions regarding its mechanism of action remain to be addressed at the molecular and systems levels. In this review, we conclusively discussed the mechanism of action of A. julibrissin and A. julibrissin formulae by reviewing recent preclinical and clinical studies conducted by using depressive animal models and depressive patients. Several representative bioactive constituents and formulae were highlighted as examples, and their mechanisms of action were discussed. In addition, some representative A. julibrissin formulae that have been shown to be compatible with conventional antidepressants in clinical practice were also reviewed. Furthermore, we discussed the future research directions to reveal the underlying mechanism of A. julibrissin at the molecular and systems levels in depression treatment. The integrated study using both the molecular and systematic approaches is required not only for improving our understanding of its molecular basis and mechanisms of action, but also for providing a way to discover novel agents or approaches for the effective and systematic treatment of depression.

Huangjia Ruangan Granule Inhibits Inflammation in a Rat Model with Liver Fibrosis by Regulating TNF/MAPK and NF-κB Signaling Pathways

The Huangjia Ruangan granule (HJRG) is a clinically effective Kampo formula, which has a significant effect on liver fibrosis and early liver cirrhosis. However, the mechanism underlying HJRG in treating liver fibrosis remains unclear. In this study, carbon tetrachloride (CCl₄) was used to induce liver fibrosis in rats to clarify the effect of HJRG on liver fibrosis and its mechanism. Using network pharmacology, the potential mechanism of HJRG was initially explored, and a variety of analyses were performed to verify this mechanism. In the liver fibrosis model, treatment with HJRG can maintain the liver morphology, lower the levels of AST and ALT in the serum, and ameliorate pathological damage. Histopathological examinations revealed that the liver structure was significantly improved and fibrotic changes were alleviated. It can effectively inhibit collagen deposition and the expression of α-SMA, reduce the levels of the rat serum (HA, LN, PC III, and Col IV), and inhibit the expression of desmin, vimentin, and HYP content in the liver. Analyzing the results of network pharmacology, the oxidative stress, inflammation, and the related pathways (primarily the TNF signaling pathway) were identified as the potential mechanism of HJRG against liver fibrosis. Experiments confirmed that HJRG can significantly increase the content of superoxide dismutase and glutathione and reduce the levels of malondialdehyde and myeloperoxidase in the rat liver; in addition, HJRG significantly inhibited the content of proinflammatory cytokines (TNF-α, IL-1β, and IL-6) and reduced the expression of inflammatory regulators (Cox2 and iNOS). Meanwhile, treatment with HJRG inhibited the phosphorylation of NF-κB P65, IκBα, ERK, JNK, and MAPK P38. Moreover, HJRG treatment reversed the increased expression of TNFR1. The Huangjia Ruangan granule can effectively inhibit liver fibrosis through antioxidation, suppressing liver inflammation by regulating the TNF/MAPK and NF-κB signaling pathways, thereby preventing the effect of liver fibrosis.

Interactions between Medical Plant-Derived Bioactive Compounds: Focus on Antimicrobial Combination Effects

It is accepted that the medicinal use of complex mixtures of plant-derived bioactive compounds is more effective than purified bioactive compounds due to beneficial combination interactions. However, synergy and antagonism are very difficult to study in a meticulous fashion since most established methods were designed to reduce the complexity of mixtures and identify single bioactive compounds. This study represents a critical review of the current scientific literature on the combined effects of plant-derived extracts/bioactive compounds. A particular emphasis is provided on the identification of antimicrobial synergistic or antagonistic combinations using recent metabolomics methods and elucidation of approaches identifying potential mechanisms that underlie their interactions. Proven examples of synergistic/antagonistic antimicrobial activity of bioactive compounds are also discussed. The focus is also put on the current challenges, difficulties, and problems that need to be overcome and future perspectives surrounding combination effects. The utilization of bioactive compounds from medicinal plant extracts as appropriate antimicrobials is important and needs to be facilitated by means of new metabolomics technologies to discover the most effective combinations among them. Understanding the nature of the interactions between medicinal plant-derived bioactive compounds will result in the development of new combination antimicrobial therapies.

Deciphering the Therapeutic Mechanisms of Wuzi Ershen Decoction in Treating Oligoasthenozoospermia through the Network Pharmacology Approach

Background

Infertility affects approximately 15% of couples around the world, and male factors are accounted for 40–50%. Oligoasthenozoospermia is the most common reason for male infertility. Unfortunately, effective drug therapy is still lacking except for assisted reproductive technology (ART). Previous researchers found that Wuzi Ershen decoction (WZESD) can increase sperm count, enhance sperm vitality, and improve semen quality. However, the pharmacological mechanisms remain unclear.

Methods

In this study, we screened compounds and predicted the targets of WZESD based on the TCMSP and BATMAN-TCM database combined with literature searching in the PubMed database. We obtained proteins related to oligoasthenozoospermia through GeneCards and submitted them to STRING to obtain the protein-protein interaction (PPI) network. Potential targets of WZESD were mapped to the network, and the hub targets were screened by topology. We used online platform Metascape and Enrichr for GO and KEGG enrichment analyses. AutoDock Vina was utilized for further verification of the binding mode between compounds and targets.

Results

Totally, 276 bioactive compounds were obtained and targeted 681 proteins. 446 oligoasthenozoospermia disease-specific proteins were acquired, and further bioinformatics analysis found that they were mainly involved in the formation of gametes, meiosis, and sperm differentiation. Protein interaction network analysis revealed that target proteins of WZESD were associated with oligoasthenozoospermia disease-specific proteins. The 79 targets of disease-specific proteins, which were anchored by WZESD, mainly participate in the cellular response to the organic cyclic compound, regulation of the apoptotic process, nitricoxide biosynthetic and metabolic process, oxidative stress, and protein phosphorylation regulation, which are the causes for oligoasthenozoospermia. Molecular docking simulation further validated that bioactive compounds originated from WZESD with targeted proteins showed high binding efficiency.

Conclusions

This study uncovers the therapeutic mechanisms of WZESD for oligoasthenozoospermia treatment from the perspective of network pharmacology and may provide a valuable reference for further experimental research studies and clinical applications.

Anti-Autophagy Mechanism of Zhi Gan Prescription Based on Network Pharmacology in Nonalcoholic Steatohepatitis Rats

Background and Aims: Zhi Gan prescription (ZGP) has been clinically proven to exert a favorable therapeutic effect on nonalcoholic steatohepatitis (NASH). This study purpose to reveal the underlying molecular mechanisms of ZGP action in NASH. Methods: Systematic network pharmacology was used to identify bioactive components, potential targets, and the underlying mechanism of ZGP action in NASH. High fat (HF)-induced NASH model rats were used to assess the effect of ZGP against NASH, and to verify the possible molecular mechanisms as predicted by network pharmacology. Results: A total of 138 active components and 366 potential targets were acquired in ZGP. In addition, 823 targets of NASH were also screened. In vivo experiments showed that ZGP significantly improved the symptoms in HF-induced NASH rats. qRT-PCR and western blot analyses showed that ZGP could regulate the hub genes, PTEN, IL-6 and TNF in NASH model rats. In addition, ZGP suppressed mitochondrial autophagy through mitochondrial fusion and fission via the PINK/Parkin pathway. Conclusion: ZGP exerts its effects on NASH through mitochondrial autophagy. These findings provide novel insights into the mechanisms of ZGP in NASH.

Network Pharmacological Analysis and Experimental Validation of the Mechanisms of Action of Si-Ni-San Against Liver Fibrosis

Background: Si-Ni-San (SNS), a commonly used traditional Chinese medicine (TCM) formula, has potency against liver diseases, such as hepatitis and non-alcoholic fatty liver disease (NAFLD). However, the therapeutic efficacy and pharmacological mechanisms of action of SNS against liver fibrosis remain largely unclear. Methods: A carbon tetrachloride (CCl4)-induced liver fibrosis mouse model was adopted for the first time to investigate the beneficial effects of SNS on liver fibrosis. The potential mechanisms of action of SNS were explored using the network pharmacology-based strategy and validated with the aid of diverse assays. Results: SNS treatment reduced collagen and ECM deposition, downregulated fibrosis-related factor (hyaluronic acid and laminin) contents in serum, maintained the morphological structure of liver tissue, and improved liver function in the liver fibrosis model. Based on network pharmacology results, apoptosis, inflammation and angiogenesis, together with the associated pathways (including VEGF, TNF, caspase, PPAR-γ and NF-κB), were identified as the mechanisms underlying the effects of SNS on liver fibrosis. Further in vivo experiments validated the significant mitigatory effects of SNS on inflammatory infiltration and pro-inflammatory cytokine contents (IFNγ, IL-1β and TGF-β1) in liver tissues of mice with liver fibrosis. SNS suppressed pathologic neovascularization as well as levels of VEGFR1, VEGF and VEGFR2 in liver tissues. SNS treatment additionally inhibited hepatic parenchyma cell apoptosis in liver tissues of mice with liver fibrosis and regulated apoptin expression while protecting L02 cells against apoptosis induced by TNF-α and Act D in vitro. Activation of hepatic stellate cells was suppressed and the balance between MMP13 and TIMP1 maintained in vitro by SNS. These activities may be associated with SNS-induced NF-κB suppression and PPAR-γ activation. Conclusion: SNS effectively impedes liver fibrosis progression through alleviating inflammation, ECM accumulation, aberrant angiogenesis and apoptosis of hepatic parenchymal cells along with inhibiting activation of hepatic stellate cells through effects on multiple targets and may thus serve as a novel therapeutic regimen for this condition.

Effect of Diterpene Manool on the Arterial Blood Pressure and Vascular Reactivity in Normotensive and Hypertensive Rats

BACKGROUND

Many studies have shown that the diterpenoid classes exert a significant effect on the cardiovascular system. Diterpenes, in particular, are among the main compound links to cardiovascular properties such as vasorelaxant, inotropic, diuretic and hypotensive activity. While the manool vasorelaxation mechanism is visible, its effect on blood pressure (BP) is still unknown.

OBJECTIVE

To evaluate the in vivo hypotensive effect of manool and check the ex vivo vasorelaxation effect in rat aortic rings.

METHODS

The animals were divided randomly into two groups: normotensive and hypertensive. The normotensive group was sham-operated, and the 2K1C model was adopted for the hypertensive group. Invasive BP monitoring was performed for manool tests at different doses (10, 20 and 40 mg/kg). Concentration-response curves for manool were obtained in the aorta rings, with endothelium, pre-contracted with phenylephrine (Phe) after incubation with Nω-nitro-L-arginine methyl ester(L-NAME) or oxadiazole [4,3-a]quinoxalin-1-one (ODQ). Nitric oxide (NOx) plasma levels were measured by chemiluminescence assay.

RESULTS

After manool administration, BP was reduced in normotensive and hypertensive groups, and this effect was inhibited by L-NAME in hypertensive animals only in 10 mg/kg dose. Ex vivo manool promoted vasorelaxation, which was inhibited by L-NAME and ODQ incubation or endothelium removal. NOx plasma levels increased in the hypertensive group after manool administration. Manool elicits endothelium-dependent vascular relaxation in rat aorta mediated by the NO/cGMP signaling pathway and BP reduction, also by NOx plasma increase. These combined effects could be involved in modulating peripheral resistance, contributing to the antihypertensive effect of diterpene.

CONCLUSION

These effects together could be involved in modulating peripheral resistance, contributing to the antihypertensive effect of diterpene.

Systematic Understanding of Mechanism of Yi-Qi-Huo-Xue Decoction Against Intracerebral Hemorrhagic Stroke Using a Network Pharmacology Approach

Background

Intracerebral hemorrhage (ICH), a fatal type of stroke, profoundly affects public health. Yi-Qi-Huo-Xue decoction (YQHXD), a traditional Chinese medicine (TCM) prescription, is verified to be an efficient method to treat ICH stroke among the Chinese population. Nevertheless, the pharmacological mechanisms of YQHXD have been unclear.

Material/Methods

We used a strategy based on network pharmacology to explore the possible multi-component, multi-target, and multi-pathway pattern of YQHXD in treating ICH. First, candidate targets for YQHXD were identified using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). Then, these candidate YQHXD targets were used in combination with the known targets for the treatment of ICH stroke to construct the core network (cPPI) using data on protein–protein interaction (PPI). We calculated 5 topological parameters for identification of the main hubs. Pathway enrichment and GO biological process enrichment analyses were performed after the incorporation of the main hubs into ClueGO.

Results

In total, 55 candidate YQHXD targets for ICH were recognized to be the major hubs in accordance with their topological importance. As suggested by enrichment analysis, the YQHXD targets for ICH were roughly classified into several biological processes (related to redox equilibrium, cell–cell communication, adhesion and collagen biosynthesis, cytokine generation, lymphocyte differentiation and activation, neurocyte apoptosis and development, neuroendocrine system, and vascular development) and related pathways (VEGF, mTOR, NF-kB, RAS/MAPK, JAK/STAT and cytokine–cytokine receptors interaction), indicating those mechanisms underlying the therapeutic effect of YQHXD.

Conclusions

The present results may serve as a pharmacological framework for TCM studies in the future, helping to promote the use of YQHXD in clinical treatment of ICH.

Investigation on the Mechanism of Qubi Formula in Treating Psoriasis Based on Network Pharmacology

Objective

To elucidate the pharmacological mechanisms of Qubi Formula (QBF), a traditional Chinese medicine (TCM) formula which has been demonstrated as an effective therapy for psoriasis in China.

Methods

The Traditional Chinese Medicine Systems Pharmacology (TCMSP) database, BATMAN-TCM database, and literature search were used to excavate the pharmacologically active ingredients of QBF and to predict the potential targets. Psoriasis-related targets were obtained from Therapeutic Target Database (TTD), DrugBank database (DBD), MalaCards database, and DisGeNET database. Then, we established the network concerning the interactions of potential targets of QBF with well-known psoriasis-related targets by using protein-protein interaction (PPI) data in String database. Afterwards, topological parameters (including DNMC, Degree, Closeness, and Betweenness) were calculated to excavate the core targets of Qubi Formula in treating psoriasis (main targets in the PPI network). Cytoscape was used to construct the ingredients-targets core network for Qubi Formula in treating psoriasis, and ClueGO was used to perform GO-BP and KEGG pathway enrichment analysis on these core targets.

Results

The ingredient-target-disease core network of QBF in treating psoriasis was screened to contain 175 active ingredients, which corresponded to 27 core targets. Additionally, enrichment analysis suggested that targets of QBF in treating psoriasis were mainly clustered into multiple biological processes (associated with nuclear translocation of proteins, cellular response to multiple stimuli (immunoinflammatory factors, oxidative stress, and nutrient substance), lymphocyte activation, regulation of cyclase activity, cell-cell adhesion, and cell death) and related pathways (VEGF, JAK-STAT, TLRs, NF-κB, and lymphocyte differentiation-related pathways), indicating the underlying mechanisms of QBF on psoriasis.

Conclusion

In this work, we have successfully illuminated that Qubi Formula could relieve a wide variety of pathological factors (such as inflammatory infiltration and abnormal angiogenesis) of psoriasis in a "multicompound, multitarget, and multipathway" manner by using network pharmacology. Moreover, our present outcomes might shed light on the further clinical application of QBF on psoriasis treatment.

Gene ontology enrichment analysis of α-amylase inhibitors from Duranta repens in diabetes mellitus

Background

Although α-amylase is the choice of target to manage postprandial hyperglycemia, inhibitors of this enzyme may get absorbed into the systemic circulation and modulate proteins involved in the pathogenesis of diabetes mellitus. Hence, the present study aimed to identify α-amylase inhibitors from Duranta repens via in silico and in vitro and predict their role in the modulation of multiple pathways involved in diabetes mellitus.

Methods

α-amylase inhibitory activity of hydroalcoholic extract/fractions (s) and pure compounds from D. repens was performed using in vitro enzyme inhibitory assay. Multiple open-source databases and published literature were used to retrieve reported phytoconstituents present in D. repens and their targets. The network was constructed between α-amylase inhibitors, modulated proteins, and expressed pathways. Further, hit molecules were also confirmed for their potency to inhibit α-amylase using in silico molecular docking and in vitro enzyme inhibitory assay. The glucose uptake assay was performed to assess the effect of hydrolcoholic extract/fraction(s) using rat hemidiaphragm.

Results

Fraction rich in flavonoids showed the highest α-amylase inhibitory activity with a IC₅₀ of 644.29 ± 4.36 µg/ml compared to other fractions. PI3K-Akt signaling pathway and p53 signaling pathway were predicted to be primarily modulated in the compound-protein-pathway network. Similarly, scutellarein was predicted as lead hit based on α-amylase inhibitory action, binding affinity, and regulated pathways. Further, α-amylase inhibitors were also predicted to modulate the pathways involved in diabetes complications like AGE-RAGE and FoxO signaling pathway. Fraction rich in flavonoids showed the highest glucose uptake in rat hemidiaphragm with an effective concentration of 534.73 ± 0.79 µg/ml.

Conclusions

The α-amylase inhibitors from D. repens may not be limited within the gastrointestinal tract to inhibit α-amylase but may get absorbed into the systemic circulation and modulate multiple pathways involved in the pathogenesis of diabetes mellitus to produce synergistic/additive effect.

Traditional Chinese Medicine in Depression Treatment: From Molecules to Systems

Depression is a multigenetic or multifactorial syndrome. The central neuron system (CNS)-orientated, single target, and conventional antidepressants are insufficient and far from ideal. Traditional Chinese Medicine (TCM) has historically been used to treat depression up till today, particularly in Asia. Its holistic, multidrug, multitarget nature fits well with the therapeutic idea of systems medicine in depression treatment. Over the past two decades, although efforts have been made to understand TCM herbal antidepressants at the molecular level, many fundamental questions regarding their mechanisms of action remain to be addressed at the systems level in order to better understand the complicated herbal formulations in depression treatment. In this Mini Review, we review and discuss the mechanisms of action of herbal antidepressants and their acting targets in the pathological systems in the brain, such as monoamine neurotransmissions, hypothalamic–pituitary–adrenal (HPA) axis, neurotropic factor brain-derived neurotrophic factor (BDNF) cascade, and glutamate transmission. Some herbal molecules, constituents, and formulas are highlighted as examples to discuss their mechanisms of action and future directions for comprehensive researches at the systems level. Furthermore, we discuss pharmacological approaches to integrate the mechanism of action from the molecular level into the systems level for understanding of systems pharmacology of TCM formulations. Integration of the studies at the molecular level into the systems level not only represents a trend in TCM study but also promotes our understanding of the system-wide mechanism of action of herbal antidepressant formulations.

Inhibitory effect of a weight-loss Chinese herbal formula RCM-107 on pancreatic α-amylase activity: Enzymatic and in silico approaches

Reducing carbohydrates digestion by having a low glycaemic index (GI) foods has been linked to weight loss. Inhibiting related enzymes is an alternative way to decrease carbohydrate digestion. RCM-107 (Slimming Plus), an eight-herb formula that is modified from RCM-104, indicated significant weight-loss action in clinical trials. However, no published research has studied its mechanism of action on reducing carbohydrate absorption via suppressing the activities of porcine pancreatic alpha-amylase (PPA). In this paper, we used fluorescence PPA inhibition assay to investigate the inhibitory effects of RCM-107 and the individual herbs present in this herbal mixture on amylase activity. Subsequently, molecular docking predicted the key active compounds that may be responsible for the enzyme inhibition. According to our results, both the RCM-107 formula and several individual herbs displayed α-amylase inhibitory effects. Also, marginal synergistic effects of RCM-107 were detected. In addition, alisol B, (-)-epigallocatechin-3-gallate (EGCG) and plantagoside have been predicted as the key active compounds that may be responsible for the α-amylase inhibition effect of RCM-107 according to inter-residue contact analysis. Finally, Glu233, Gln63, His305, Asp300 and Tyr151 are predicted to be markers of important areas with which potential amylase inhibitors would interact. Therefore, our data has provided new knowledge on the mechanisms of action of the RCM-107 formula and its individual herbal ingredients for weight loss, in terms of decreasing carbohydrate digestion via the inhibition of pancreatic alpha-amylase.

Integrating Chinese and Western medicines reduced the incidence of hepatocellular carcinoma in patients with diabetes mellitus: A Taiwanese population-based cohort study

OBJECTIVES

Much epidemiological evidence links diabetes mellitus (DM) to the development of multiple cancers and, in particular, the development of hepatocellular carcinoma (HCC). The aim of this study was to investigate whether Chinese herbal medicine (CHM) reduces the incidence of HCC in patients receiving Western antidiabetic drugs.

INTERVENTIONS AND MAIN OUTCOME MEASURES

This retrospective cohort study used data from the National Health Insurance Research Database involving 81,105 diabetic patients, including 5122 CHM users and 25,966 non-CHM users. Analyses of treatment effects were adjusted for covariates including gender, age, comorbidities, antidiabetic drugs and liver medications. NodeXL software performed a network analysis to identify the 50 most commonly used CHM herbs and formulas.

RESULTS

In Cox proportional hazards models adjusted for demographic and clinical characteristics, DM patients exposed to adjuvant CHM therapy were significantly less likely to develop HCC compared with non-CHM users (adjusted hazard ratio [aHR] 0.59; 95 % confidence interval [CI], 0.41-0.87; p = 0.01). Kaplan-Meier analysis revealed a lower 10-year cumulative risk of HCC among CHM users compared with non-CHM users. Amongst the 10 individual CHM herbs and herbal formulas most commonly prescribed for DM, the most frequent were Salvia miltiorrhiza (Dan Shen) and Liu Wei Di Huang Wan, respectively.

CONCLUSION

This nationwide retrospective cohort study from Taiwan provides some valuable insights into the prescribing characteristics of CHM treatment in patients with DM. Compared with use of Western antidiabetic medications alone, use of adjuvant CHM effectively reduces the incidence of HCC in patients with DM.

A Systems Pharmacology Approach for Identifying the Multiple Mechanisms of Action for the Rougui-Fuzi Herb Pair in the Treatment of Cardiocerebral Vascular Diseases

Cardiocerebral vascular diseases (CCVDs) are the main reasons for high morbidity and mortality all over the world, including atherosclerosis, hypertension, myocardial infarction, stroke, and so on. Chinese herbs pair of the Cinnamomum cassia Presl (Chinese name, rougui) and the Aconitum carmichaelii Debx (Chinese name, fuzi) can be effective in CCVDs, which is recorded in the ancient classic book Shennong Bencao Jing, Mingyibielu and Thousand Golden Prescriptions. However, the active ingredients and the molecular mechanisms of rougui-fuzi in treatment of CCVDs are still unclear. This study was designed to apply a system pharmacology approach to reveal the molecular mechanisms of the rougui-fuzi anti-CCVDs. The 163 candidate compounds were retrieved from Traditional Chinese Medicine System Pharmacology Database and Analysis Platform (TCMSP). And 84 potential active compounds and the corresponding 42 targets were obtained from systematic model. The underlying mechanisms of the therapeutic effect for rougui-fuzi were investigated with gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Then, component-target-disease (C-T-D) and target-pathway (T-P) networks were constructed to further dissect the core pathways, potential targets, and active compounds in treatment of CCVDs for rougui-fuzi. We also constituted protein-protein in interaction (PPI) network by the reflect target protein of the crucial pathways against CCVDs. As a result, 21 key compounds, 8 key targets, and 3 key pathways were obtained for rougui-fuzi. Afterwards, molecular docking was performed to validate the reliability of the interactions between some compounds and their corresponding targets. Finally, UPLC-Q-Exactive-MS^E and GC-MS/MS were analyzed to detect the active ingredients of rougui-fuzi. Our results may provide a new approach to clarify the molecular mechanisms of Chinese herb pair in treatment with CCVDs at a systematic level.

Synergistic Effect of Network-Based Multicomponent Drugs: An Investigation on the Treatment of Non-Small-Cell Lung Cancer with Compound Liuju Formula

Lung cancer is the most common cause of cancer death with high morbidity and mortality, which non-small-cell lung cancer (NSCLC) accounting for the majority. Traditional Chinese Medicine (TCM) is effective in the treatment of complex diseases, especially cancer. However, TCM is still in the conceptual stage. The interaction between different components remains unknown due to its multicomponent and multitarget characteristics. In this study, compound Liuju formula was taken as an example to isolate compounds with synergistic biological activity through systems pharmacology strategy. Through pharmacokinetic evaluation, 37 potentially active compounds were screened out. Meanwhile, 116 targets of these compounds were obtained by combing with the target prediction model. Through network analysis, we found that multicomponent drugs can present a synergistic effect through regulating inflammatory signaling pathway, invasion pathway, proliferation, and apoptosis pathway. Finally, it was confirmed that the bioactive compounds of compound Liuju formula have not only a killing effect on NSCLC tumor cells but also a synergistic effect on inhibiting the secretion of correlative inflammatory mediators, including TNF-α and IL-1β. The systems pharmacology method was applied in this study, which provides a new direction for analyzing the mechanism of TCM.

The Methodological Trends of Traditional Herbal Medicine Employing Network Pharmacology

Natural products, including traditional herbal medicine (THM), are known to exert their therapeutic effects by acting on multiple targets, so researchers have employed network pharmacology methods to decipher the potential mechanisms of THM. To conduct THM-network pharmacology (THM-NP) studies, researchers have employed different tools and databases for constructing and analyzing herb–compound–target networks. In this study, we attempted to capture the methodological trends in THM-NP research. We identified the tools and databases employed to conduct THM-NP studies and visualized their combinatorial patterns. We also constructed co-author and affiliation networks to further understand how the methodologies are employed among researchers. The results showed that the number of THM-NP studies and employed databases/tools have been dramatically increased in the last decade, and there are characteristic patterns in combining methods of each analysis step in THM-NP studies. Overall, the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) was the most frequently employed network pharmacology database in THM-NP studies. Among the processes involved in THM-NP research, the methodology for constructing a compound–target network has shown the greatest change over time. In summary, our analysis describes comprehensive methodological trends and current ideas in research design for network pharmacology researchers.

Systems Pharmacology for Investigation of the Mechanisms of Action of Traditional Chinese Medicine in Drug Discovery

As a traditional medical intervention in Asia and a complementary and alternative medicine in western countries, traditional Chinese medicine (TCM) has attracted global attention in the life science field. TCM provides extensive natural resources for medicinal compounds, and these resources are generally regarded as effective and safe for use in drug discovery. However, owing to the complexity of compounds and their related multiple targets of TCM, it remains difficult to dissect the mechanisms of action of herbal medicines at a holistic level. To solve the issue, in the review, we proposed a novel approach of systems pharmacology to identify the bioactive compounds, predict their related targets, and illustrate the molecular mechanisms of action of TCM. With a predominant focus on the mechanisms of actions of TCM, we also highlighted the application of the systems pharmacology approach for the prediction of drug combination and dynamic analysis, the synergistic effects of TCMs, formula dissection, and theory analysis. In summary, the systems pharmacology method contributes to understand the complex interactions among biological systems, drugs, and complex diseases from a network perspective. Consequently, systems pharmacology provides a novel approach to promote drug discovery in a precise manner and a systems level, thus facilitating the modernization of TCM.

Proteomic studies of putative molecular signatures for biological effects by Korean Red Ginseng

Background

Korean Red Ginseng (KRG) has been widely used as an herbal medicine to normalize and strengthen body functions. Although many researchers have focused on the biological effects of KRG, more studies on the action mechanism of red ginseng are still needed. Previously, we investigated the proteomic changes of the rat spleen while searching for molecular signatures and the action mechanism of KRG. The proteomic analysis revealed that differentially expressed proteins (DEPs) were involved in the increased immune response and phagocytosis. The aim of this study was to evaluate the biological activities of KRG, especially the immune-enhancing response of KRG.

Methods

Rats were divided into 4 groups: 0 (control group), 500, 1000, and 2000 mg/kg administration of KRG powder for 6 weeks, respectively. Isobaric tags for relative and absolute quantitation was performed with Q-Exactive LC-MS/MS to compare associated proteins between the groups. The putative DEPs were identified by a current UniProt rat protein database search and by the Gene Ontology annotations.

Results

The DEPs appear to increase the innate and acquired immunity as well as immune cell movement. These results suggest that KRG can stimulate immune responses. This analysis refined our targets of interest to include the potential functions of KRG. Furthermore, we validated the potential molecular targets of the functions, representatively LCN2, CRAMP, and HLA-DQB1, by Western blotting.

Conclusion

These results may provide molecular signature candidates to elucidate the mechanisms of the immune response by KRG. Here, we demonstrate a strategy of tissue proteomics for the discovery of the molecular function of KRG.

Understanding the Multitarget Pharmacological Mechanism of the Traditional Mongolian Common Herb Pair GuangZao-RouDouKou Acting on Coronary Heart Disease Based on a Bioinformatics Approach

GuangZao and RouDouKou (Fructus Choerospondiatis and Nutmeg, FCN) are one of the most common herb pairs in traditional Mongolian medicine for the treatment of coronary heart disease (CHD). However, evidence for the protective effect of FCN is limited, and its underlying mechanism of action remains unclear. The present study employed a network pharmacology approach to identify the potentially active ingredients and synergistic effects of the herb pair FCN as traditional Mongolian medicine. We predicted the targets of all available FCN ingredients with PharmMapper, SWISS, and SuperPred Server and clustered CHD-related targets from the DrugBank and the OMIM database. We also evaluated the links between herbal ingredients and pharmacological actions to explore the potential mechanism of action of FCN. We found that FCN targets a network of CHD-related key processes, including stress responses, cell adhesion and connections, angiogenesis, cell apoptosis and necrosis, the endocrine system, inflammatory and immune responses, and other biological processes. To confirm the predicted results, we investigated the protective effect of FCN on isoproterenol- (ISO-) induced myocardial ischemia in rats. Pathological assessment indicated that FCN inhibits apoptosis and inflammatory responses involving the myocardium. Quantitative real-time polymerase chain reaction (qRT-PCR) and western blotting analyses demonstrated the therapeutic effects of FCN on ISO-induced myocardial ischemia rats, possibly via regulating stress and inflammatory responses and inhibiting cardiomyocyte apoptosis. The findings of the present study indicate that bioinformatics combined with experimental verification provide a credible and objective method to elucidate the complex multitarget mechanism of action of FCN.

Systems pharmacology approach to investigate the molecular mechanisms of herb Rhodiola rosea L. radix

Rhodiola rosea L. radix (RRL) is one of the most popular medical herb which has been widely used for the treatment of different diseases effectively, including cardiovascular diseases and nerve system diseases. However, due to the multiple compounds in RRL, the underlying molecular mechanisms of RRL are remained unclear. To decipher the action mechanisms of RRL from a systematic perspective, a systems pharmacology approach integrated absorption, distribution, metabolism, and excretion (ADME) system, drug targeting, and network analysis was introduced. First, by the ADME screening system and the target fishing process, 56 potential active compounds and 62 targets were obtained, respectively. In addition, compound-target network demonstrated that most compounds interacted with multiple targets, indicating that RRL may enhance its therapeutic effects probably through hitting on multiple targets in a holistic level. Moreover, target-pathway network and gene ontology analysis showed that multiple targets of RRL were involved in several biological pathways, i.e. Neuroactive ligand-receptor interaction, calcium signaling pathway, adrenergic signaling in cardiomyocytes, and VEGF signaling pathway, which dissecting the therapeutic effects of RRL on various diseases, such as cardiovascular diseases, depression, adaptation diseases, etc. In summary, this work successfully explains the potential active compounds and the multi-scale curative action mechanisms of RRL for treating various diseases; meanwhile, it implies that RRL could be applied as a novel therapeutic agent in arthritic diseases. Most importantly, this work provides an in silico strategy to understand the action mechanisms of herbal medicines from molecular/system levels, which will promote the new drug development of traditional Chinese medicine.

A Network Pharmacology Approach to Uncover the Molecular Mechanisms of Herbal Formula Ban-Xia-Xie-Xin-Tang

Ban-Xia-Xie-Xin-Tang (BXXXT) is a classical formula from Shang-Han-Lun which is one of the earliest books of TCM clinical practice. In this work, we investigated the therapeutic mechanisms of BXXXT for the treatment of multiple diseases using a network pharmacology approach. Here three BXXXT representative diseases (colitis, diabetes mellitus, and gastric cancer) were discussed, and we focus on in silico methods that integrate drug-likeness screening, target prioritizing, and multilayer network extending. A total of 140 core targets and 72 representative compounds were finally identified to elucidate the pharmacology of BXXXT formula. After constructing multilayer networks, a good overlap between BXXXT nodes and disease nodes was observed at each level, and the network-based proximity analysis shows that the relevance between the formula targets and disease genes was significant according to the shortest path distance (SPD) and a random walk with restart (RWR) based scores for each disease. We found that there were 22 key pathways significantly associated with BXXXT, and the therapeutic effects of BXXXT were likely addressed by regulating a combination of targets in a modular pattern. Furthermore, the synergistic effects among BXXXT herbs were highlighted by elucidating the molecular mechanisms of individual herbs, and the traditional theory of "Jun-Chen-Zuo-Shi" of TCM formula was effectively interpreted from a network perspective. The proposed approach provides an effective strategy to uncover the mechanisms of action and combinatorial rules of BXXXT formula in a holistic manner.

Network Pharmacology-Based Approach to Investigate the Analgesic Efficacy and Molecular Targets of Xuangui Dropping Pill for Treating Primary Dysmenorrhea

This study aimed to evaluate the clinical analgesic efficacy and identify the molecular targets of XGDP for treating primary dysmenorrhea (PD) by a network pharmacology approach. Analysis of pain disappearance rate of XGDP in PD treatment was conducted based on data from phase II and III randomized, double-blind, double-simulation, and positive parallel controlled clinical trials. The bioactive compounds were obtained by the absorption, distribution, metabolism, and excretion processes with oral bioavailability (OB) and drug-likeness (DL) evaluation. Subsequently, target prediction, pathway identification, and network construction were employed to clarify the mechanisms of the analgesic effect of XGDP on PD. The pain disappearance rates in phase II and III clinical trials of XGDP in PD treatment were 62.5% and 55.8%, respectively, yielding a significant difference (P < 0.05) when compared with the control group using Tongjingbao granules (TJBG). Among 331 compounds, 53 compounds in XGDP were identified as the active compounds related to PD through OB, DL, and target prediction. The active compounds and molecular targets of XGDP were identified, and our study showed that XGDP may exert its therapeutic effects on PD through the regulation of the targets related to anti-inflammation analgesia and central analgesia and relieving smooth muscle contraction.

Transcriptome inference and systems approaches to polypharmacology and drug discovery in herbal medicine

ETHNOPHARMACOLOGICAL RELEVANCE

Herbal medicine is a concoction of numerous chemical ingredients, and it exhibits polypharmacological effects to act on multiple pharmacological targets, regulating different biological mechanisms and treating a variety of diseases. Thus, this complexity is impossible to deconvolute by the reductionist method of extracting one active ingredient acting on one biological target.

AIM OF THE STUDY

To dissect the polypharmacological effects of herbal medicines and their underling pharmacological targets as well as their corresponding active ingredients.

MATERIALS AND METHODS

We propose a system-biology strategy that combines omics and bioinformatical methodologies for exploring the polypharmacology of herbal mixtures. The myocardial ischemia model was induced by Ameroid constriction of the left anterior descending coronary in Ba-Ma miniature pigs. RNA-seq analysis was utilized to find the differential genes induced by myocardial ischemia in pigs treated with formula QSKL. A transcriptome-based inference method was used to find the landmark drugs with similar mechanisms to QSKL.

RESULTS

Gene-level analysis of RNA-seq data in QSKL-treated cases versus control animals yields 279 differential genes. Transcriptome-based inference methods identified 80 landmark drugs that covered nearly all drug classes. Then, based on the landmark drugs, 155 potential pharmacological targets and 57 indications were identified for QSKL.

CONCLUSION

Our results demonstrate the power of a combined approach for exploring the pharmacological target and chemical space of herbal medicines. We hope that our method could enhance our understanding of the molecular mechanisms of herbal systems and further accelerate the exploration of the value of traditional herbal medicine systems.

Systems pharmacology exploration of botanic drug pairs reveals the mechanism for treating different diseases

Multi-herb therapy has been widely used in Traditional Chinese medicine and tailored to meet the specific needs of each individual. However, the potential molecular or systems mechanisms of them to treat various diseases have not been fully elucidated. To address this question, a systems pharmacology approach, integrating pharmacokinetics, pharmacology and systems biology, is used to comprehensively identify the drug-target and drug-disease networks, exemplified by three representative Radix Salviae Miltiorrhizae herb pairs for treating various diseases (coronary heart disease, dysmenorrheal and nephrotic syndrome). First, the compounds evaluation and the multiple targeting technology screen the active ingredients and identify the specific targets for each herb of three pairs. Second, the herb feature mapping reveals the differences in chemistry and pharmacological synergy between pairs. Third, the constructed compound-target-disease network explains the mechanisms of treatment for various diseases from a systematic level. Finally, experimental verification is taken to confirm our strategy. Our work provides an integrated strategy for revealing the mechanism of synergistic herb pairs, and also a rational way for developing novel drug combinations for treatments of complex diseases.

Synergistic Effects of Chinese Herbal Medicine: A Comprehensive Review of Methodology and Current Research

Traditional Chinese medicine (TCM) is an important part of primary health care in Asian countries that has utilized complex herbal formulations (consisting 2 or more medicinal herbs) for treating diseases over thousands of years. There seems to be a general assumption that the synergistic therapeutic effects of Chinese herbal medicine (CHM) derive from the complex interactions between the multiple bioactive components within the herbs and/or herbal formulations. However, evidence to support these synergistic effects remains weak and controversial due to several reasons, including the very complex nature of CHM, misconceptions about synergy and methodological challenges to study design. In this review, we clarify the definition of synergy, identify common errors in synergy research and describe current methodological approaches to test for synergistic interaction. We discuss the strengths and weaknesses of these models in the context of CHM and summarize the current status of synergy research in CHM. Despite the availability of some scientific data to support the synergistic effects of multi-herbal and/or herb-drug combinations, the level of evidence remains low, and the clinical relevancy of most of these findings is undetermined. There remain significant challenges in the development of suitable methods for synergistic studies of complex herbal combinations.

A systems pharmacology approach to investigate the mechanisms of action of Semen Strychni and Tripterygium wilfordii Hook F for treatment of rheumatoid arthritis

ETHNOPHARMACOLOGY RELEVANCE

The angiogenesis control at the initiation of rheumatoid arthritis (RA) that mainly blocks the inflammatory cascades expects to attenuate the action of angiogenic mediators, synovial angiogenesis, and to partially reverse the erosive bone damage. Two typical Chinese herbs, Semen Strychni and Tripterygium wilfordii Hook F (TwHF) have been used as a remedy to treat RA since ancient time. However, their functioning mechanisms are still unknown. Thus it is necessary to exploit their underlying mechanism for the treatment of RA.

METHODS

This study was undertaken to analyze their underlying mechanism based on a systems biology platform. Firstly, active components of the two herbs were screened out from TcmSP database based on their OB and DL values. Then their potential targets were predicted by using Random Forest, Support Vector Machine, and validated via docking process. Finally, a network of compound-target was constructed.

RESULTS

In this work, 27 and 33 active compounds were screened out from Semen Strychni and TwHF, targeting 28 and 32 potential proteins, respectively. The results show that the two herbs modulate the angiogenesis mediators through both direct and indirect pathways, and 21 common targets shared by Semen Strychni and TwHF bear major responsibility for treating RA.

CONCLUSIONS

The underlying mechanism of Semen Strychni and TwHF in treatment of RA is through multiple targets interaction by their blocking of the angiogenesis mediator cascades. This may provide us a better understanding of the function of the two herbs for the treatment of RA, as well as a clue to unveil their possible treatment effects of other systemic diseases, and in this way, hopefully the screening models may facilitate the discovery of novel combined drugs.

Systems Biology - A Pivotal Research Methodology for Understanding the Mechanisms of Traditional Medicine

Objectives:

Systems biology is a novel subject in the field of life science that aims at a systems’ level understanding of biological systems. Because of the significant progress in high-throughput technologies and molecular biology, systems biology occupies an important place in research during the post-genome era.

Methods:

The characteristics of systems biology and its applicability to traditional medicine research have been discussed from three points of view: data and databases, network analysis and inference, and modeling and systems prediction.

Results:

The existing databases are mostly associated with medicinal herbs and their activities, but new databases reflecting clinical situations and platforms to extract, visualize and analyze data easily need to be constructed. Network pharmacology is a key element of systems biology, so addressing the multi-component, multi-target aspect of pharmacology is important. Studies of network pharmacology highlight the drug target network and network target. Mathematical modeling and simulation are just in their infancy, but mathematical modeling of dynamic biological processes is a central aspect of systems biology. Computational simulations allow structured systems and their functional properties to be understood and the effects of herbal medicines in clinical situations to be predicted.

Conclusion:

Systems biology based on a holistic approach is a pivotal research methodology for understanding the mechanisms of traditional medicine. If systems biology is to be incorporated into traditional medicine, computational technologies and holistic insights need to be integrated.

Unoprostone activation of BK (KCa1.1) channel splice variants

This investigation was conducted to study the relationship between intracellular Ca(2+) and activation of large conductance Ca(2+)-activated K(+) (BK) currents by unoprostone, the first synthetic docosanoid. We used HEK293 cells stably transfected with two BK channel splice variants, one sensitive to unoprostone and the other insensitive. We examined the effects of unoprostone on channel activity in excised inside-out patches and cell-attached patches. The half-maximal stimulation of the sensitive BK channels by Ca(2+) was shifted from 3.4±0.017 nM to 0.81±.0058 nM in the presence of 10 nM unoprostone. There was no effect on insensitive channels even at unoprostone concentrations as high as 1000 nM. There was no effect of unoprostone on the voltage dependence of the BK channels. Changes in open probability and effects of Ca(2+) and unoprostone were best described by a synergistic binding model. These data would suggest that Ca(2+) and unoprostone were binding to sites close to one another on the channel protein and that unoprostone binding causes the affinity of the calcium binding site to increase. This idea is consistent with three dimensional models of the Ca(2+) binding site and a putative unoprostone binding domain. Our results have important implications for the clinical use of unoprostone to activate BK channels. Channel activation will be limited if intracellular Ca(2+) is not elevated.

Network pharmacological identification of active compounds and potential actions of Erxian decoction in alleviating menopause-related symptoms

BACKGROUND

Erxian decoction (EXD) is used to treat menopause-related symptoms in Chinese medicine. This study aims to identify the bioactive compounds and potential actions of EXD by network pharmacological analysis.

METHODS

Two databases, the Traditional Chinese Medicine Systems Pharmacology database and TCM Database@Taiwan, were used to retrieve literature of phytochemicals of EXD. STITCH 4.0 and the Comparative Toxicogenomics Database were used to search for compound-protein and compound-gene interactions, respectively. DAVID Bioinformatics Resources 6.7 and Cytoscape 3.01 with Jepetto plugin software were used to perform a network pharmacological analysis of EXD.

RESULTS

A total of 721 compounds were identified in EXD, of which 155 exhibited 2,656 compound-protein interactions with 1,963 associated proteins determined by STITCH4.0 database, and of which 210 had 14,893 compound-gene interactions with 8,536 associated genes determined by Comparative Toxicogenomics Database. Sixty three compounds of EXD followed the Lipinski's Rule with OB ≥30% and DL index ≥0.18, of which 20 related to 34 significant pathway- or 12 gene- associated with menopause.

CONCLUSIONS

Twenty compounds were identified by network pharmacology as potential effective ingredients of EXD for relieving menopause with acceptable oral bioavailability and druggability.

Pathway as a pharmacological target for herbal medicines: an investigation from reduning injection

As a rich natural resource for drug discovery, Traditional Chinese Medicine (TCM) plays an important role in complementary and alternative medical systems. TCM shows a daunting complexity of compounds featuring multi-components and multi-targets to cure diseases, which thus always makes it extremely difficult to systematically explain the molecular mechanisms adequately using routine methods. In the present work, to reveal the systematic mechanism of herbal formulae, we developed a pathway-based strategy by combining the pathways integrating, target selection, reverse drug targeting and network analysis together, and then exemplified it by Reduning injection (RDN), a clinically widely used herbal medicine injection, in combating inflammation. The anti-inflammatory effects exerted by the major ingredients of RDN at signaling pathways level were systematically investigated. More importantly, our predicted results were also experimentally validated. Our strategy provides a deep understanding of the pharmacological functions of herbal formulae from molecular to systematic level, which may lead to more successful applications of systems pharmacology for drug discovery and development.

Large-scale exploration and analysis of drug combinations

MOTIVATION

Drug combinations are a promising strategy for combating complex diseases by improving the efficacy and reducing corresponding side effects. Currently, a widely studied problem in pharmacology is to predict effective drug combinations, either through empirically screening in clinic or pure experimental trials. However, the large-scale prediction of drug combination by a systems method is rarely considered.

RESULTS

We report a systems pharmacology framework to predict drug combinations (PreDCs) on a computational model, termed probability ensemble approach (PEA), for analysis of both the efficacy and adverse effects of drug combinations. First, a Bayesian network integrating with a similarity algorithm is developed to model the combinations from drug molecular and pharmacological phenotypes, and the predictions are then assessed with both clinical efficacy and adverse effects. It is illustrated that PEA can predict the combination efficacy of drugs spanning different therapeutic classes with high specificity and sensitivity (AUC = 0.90), which was further validated by independent data or new experimental assays. PEA also evaluates the adverse effects (AUC = 0.95) quantitatively and detects the therapeutic indications for drug combinations. Finally, the PreDC database includes 1571 known and 3269 predicted optimal combinations as well as their potential side effects and therapeutic indications.

AVAILABILITY AND IMPLEMENTATION

The PreDC database is available at http://sm.nwsuaf.edu.cn/lsp/predc.php.

A novel systems pharmacology model for herbal medicine injection: a case using Reduning injection

BACKGROUND

Compared with the traditional oral administration form, injection administration is basically superior in terms of both biological availability and therapeutic effects. However, few researches have focused on the traditional Chinese medicinal injection due to the complicated constituents and the intricate mechanism of action.

METHODS

In the present work, a novel systems pharmacology model, integrating ADME (absorption, distribution, metabolism, and excretion) filtering such as half-life evaluation, network targeting, pathway and systems analyses, is specifically developed for the identification of active compounds and the study of the mechanism of action of TCM injection, which is exemplified by Reduning injection confronting the influenza.

RESULTS

The ADME filter successfully identifies 35 bioactive compounds (31 molecules and 4 metabolites) from the Reduning injection. The systems analysis and experimental validation further reveal a new way of confronting influenza disease of this injection: 1) stimulating the immunomodulatory agents for immune response activation, and 2) regulating the inflammatory agents for anti-inflammation.

CONCLUSIONS

The novel systems pharmacology method used in this study has the potential to advance the understanding of the molecular mechanisms of action of multicomponent herbal injections, and provide clues to discovering more effective drugs against complex diseases.

Systems pharmacology-based approach for dissecting the addition and subtraction theory of traditional Chinese medicine: An example using Xiao-Chaihu-Decoction and Da-Chaihu-Decoction

BACKGROUND

Addition and subtraction theory (AST), a basic theory of herb combination in traditional Chinese medicine (TCM), is often used to add or subtract the "fundamental formulae" to generate more targeted prescriptions. This theory plays a core role in individualized medicine and compound compatibility of TCM. However, the mechanisms underlying AST have largely remained elusive.

METHODS

An integrated platform of systems pharmacology was proposed for revealing how the oral administration, drug half-life, and target interactions affect the pharmacological functions of herbal medicines. This platform was further applied on two classical prescriptions, i.e., Xiao Chaihu decoction (XCHD) and Da Chaihu decoction (DCHD) to dissect the addition and subtraction theory (AST).

RESULTS

We uncovered the candidate compounds, key molecular targets and interaction network involved in XCHD and DCHD, and summarized its pharmacological characters and therapeutic indications. The results show that the "fundamental formula" is responsible for the major therapeutic effects, whereas the "additive herbs" synergistically enhance the treatment outcomes by targeting the same or complementary proteins between the foundational and additive herbs.

CONCLUSION

This work has established a novel method to comprehensively understand the mechanism of AST, which would be beneficial for the TCM recipe optimization as well as the production of new herbal formula with desirable therapeutic effects.

Exploration of the mechanism of pattern-specific treatments in coronary heart disease with network pharmacology approach

Traditional Chinese medicine (TCM) pattern is a valuable classification method in the treatment of complex disease such as coronary heart disease (CHD). In accordance to TCM patterns, our ancestors created many pertinent TCM formulae, which have been used in China for thousands of years and are still playing an important role in China today. However, the biological mechanism of TCM pattern-specific formulae remains elusive. In this paper, we chose CHD patterns (Qi-stagnation induced blood-stasis syndrome, abbreviated as QSB; Qi-deficiency induced blood-stasis syndrome, abbreviated as QDB) as examples to illustrate the mechanism of their pattern-specific formulae. Using entity grammar systems (EGS) formalism, we built two pharmacologic networks of the formulae and obtained the intersection and difference networks by network comparison. Then we analyzed their common and different mechanisms for treating CHD by GO enrichment analysis. The results indicate that QDB-specific formula takes more special molecular paths to treat CHD, which contribute to more severe pathological changes in comparison with QSB. In this paper, we achieved a better understanding of the pharmacological characteristics of CHD patterns-specific formulae, which is beneficial to explore different therapies for a disease to enhance the effectiveness and pertinence of treatment.

TCMSP: a database of systems pharmacology for drug discovery from herbal medicines

Background

Modern medicine often clashes with traditional medicine such as Chinese herbal medicine because of the little understanding of the underlying mechanisms of action of the herbs. In an effort to promote integration of both sides and to accelerate the drug discovery from herbal medicines, an efficient systems pharmacology platform that represents ideal information convergence of pharmacochemistry, ADME properties, drug-likeness, drug targets, associated diseases and interaction networks, are urgently needed.

Description

The traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP) was built based on the framework of systems pharmacology for herbal medicines. It consists of all the 499 Chinese herbs registered in the Chinese pharmacopoeia with 29,384 ingredients, 3,311 targets and 837 associated diseases. Twelve important ADME-related properties like human oral bioavailability, half-life, drug-likeness, Caco-2 permeability, blood-brain barrier and Lipinski’s rule of five are provided for drug screening and evaluation. TCMSP also provides drug targets and diseases of each active compound, which can automatically establish the compound-target and target-disease networks that let users view and analyze the drug action mechanisms. It is designed to fuel the development of herbal medicines and to promote integration of modern medicine and traditional medicine for drug discovery and development.

Conclusions

The particular strengths of TCMSP are the composition of the large number of herbal entries, and the ability to identify drug-target networks and drug-disease networks, which will help revealing the mechanisms of action of Chinese herbs, uncovering the nature of TCM theory and developing new herb-oriented drugs. TCMSP is freely available at http://sm.nwsuaf.edu.cn/lsp/tcmsp.php.

Astragaloside Ⅳ reduces the expression level of P-glycoprotein in multidrug-resistant human hepatic cancer cell lines

Astragaloside is a saponin widely used in traditional Chinese medicine and has been reported to be a potent multidrug resistance (MDR) reversal agent. The present study investigated the role of astragaloside Ⅳ (ASIV) in the regulation of P-glycoprotein (P-gp, encoded by the mdr1 gene) and its effect on the reversal of MDR. The activity of ASIV was evaluated using human hepatic cancer cells Bel-7402 and the corresponding 5-fluorouracil (5-FU) resistant cells Bel-7402/FU. ASIV (0.08 mg/ml) potentiated the cytotoxicity of 5-FU which was demonstrated using the MTT assay on Bel-7402/FU cells. ASIV reduced the expression of P-gp as was revealed by immunocytochemistry. Accumulation and efflux studies with the P-gp substrate, rhodamine 123 (Rh123), demonstrated that ASIV inhibited P-gp-mediated drug efflux. Furthermore, it was demonstrated that ASⅣ enhanced the drug accumulation of 5-FU using a high performance liquid chromatography (HPLC) assay for drug resistant cells. Furthermore, ASIV may downregulate the expression of P-gp, which was examined using western blot analysis and polymerase chain reaction. In conclusion, the results of the present study indicated that ASIV reverses the drug resistance of Bel-7402/FU cells by downregulating the expression of mdr1. ASIV may represent a potent modulator of P-gp-mediated MDR in hepatic cancer therapy.

Investigation into the mechanism of Eucommia ulmoides Oliv. based on a systems pharmacology approach

ETHNOPHARMACOLOGY RELEVANCE

Though Traditional Chinese Medicine (TCM) has long been playing a significant role in the maintenance of health for people in Asia as well as many other places, the mechanism of its action still remains ambiguous for most of the plants used in TCM, such as Eucommia ulmoides Oliv., a kind of herb that is widely used to help regulate hypertension and the immune system nowadays. However, its functioning mechanism is still unknown. Thus it is necessary to exploit the mechanism of Eucommia ulmoides Oliv.

METHODS

A systems pharmacology approach combining drug-likeness evaluation, oral bioavailability prediction, multiple drug targets prediction as well as network pharmacology techniques has been used.

RESULTS

This comprehensive systematic approach helps successfully to identify 41 candidate compounds contained in Eucommia ulmoides Oliv. while 39 potential targets hit by these ingredients and helps to uncover the synergistic mechanism of action on a systematic level.

CONCLUSIONS

Our work successfully explains the mechanism of the efficiency of Eucommia ulmoides Oliv. for the treatment of hypertension and enhancing immune. These results not only provide a new insight for the understanding of the chemical and pharmacological basis of Eucommia ulmoides Oliv., but also provide an efficient way for drug discovery from herbal medicine.

Navigating traditional chinese medicine network pharmacology and computational tools

The concept of "network target" has ushered in a new era in the field of traditional Chinese medicine (TCM). As a new research approach, network pharmacology is based on the analysis of network models and systems biology. Taking advantage of advancements in systems biology, a high degree of integration data analysis strategy and interpretable visualization provides deeper insights into the underlying mechanisms of TCM theories, including the principles of herb combination, biological foundations of herb or herbal formulae action, and molecular basis of TCM syndromes. In this study, we review several recent developments in TCM network pharmacology research and discuss their potential for bridging the gap between traditional and modern medicine. We briefly summarize the two main functional applications of TCM network models: understanding/uncovering and predicting/discovering. In particular, we focus on how TCM network pharmacology research is conducted and highlight different computational tools, such as network-based and machine learning algorithms, and sources that have been proposed and applied to the different steps involved in the research process. To make network pharmacology research commonplace, some basic network definitions and analysis methods are presented.

Systems pharmacology strategies for drug discovery and combination with applications to cardiovascular diseases

ETHNOPHARMACOLOGICAL RELEVANCE

Multi-target therapeutics is a promising paradigm for drug discovery which is expected to produce greater levels of efficacy with fewer adverse effects and toxicity than monotherapies. Medical herbs featuring multi-components and multi-targets may serve as valuable resources for network-based multi-target drug discovery.

MATERIALS AND METHODS

In this study, we report an integrated systems pharmacology platform for drug discovery and combination, with a typical example applied to herbal medicines in the treatment of cardiovascular diseases.

RESULTS

First, a disease-specific drug-target network was constructed and examined at systems level to capture the key disease-relevant biology for discovery of multi-targeted agents. Second, considering an integration of disease complexity and multilevel connectivity, a comprehensive database of literature-reported associations, chemicals and pharmacology for herbal medicines was designed. Third, a large-scale systematic analysis combining pharmacokinetics, chemogenomics, pharmacology and systems biology data through computational methods was performed and validated experimentally, which results in a superior output of information for systematic drug design strategies for complex diseases.

CONCLUSIONS

This strategy integrating different types of technologies is expected to help create new opportunities for drug discovery and combination.

Network pharmacology: a new approach for chinese herbal medicine research

The dominant paradigm of "one gene, one target, one disease" has influenced many aspects of drug discovery strategy. However, in recent years, it has been appreciated that many effective drugs act on multiple targets rather than a single one. As an integrated multidisciplinary concept, network pharmacology, which is based on system biology and polypharmacology, affords a novel network mode of "multiple targets, multiple effects, complex diseases" and replaces the "magic bullets" by "magic shotguns." Chinese herbal medicine (CHM) has been recognized as one of the most important strategies in complementary and alternative medicine. Though CHM has been practiced for a very long time, its effectiveness and beneficial contribution to public health has not been fully recognized. Also, the knowledge on the mechanisms of CHM formulas is scarce. In the present review, the concept and significance of network pharmacology is briefly introduced. The application and potential role of network pharmacology in the CHM fields is also discussed, such as data collection, target prediction, network visualization, multicomponent interaction, and network toxicology. Furthermore, the developing tendency of network pharmacology is also summarized, and its role in CHM research is discussed.

An Integrative Platform of TCM Network Pharmacology and Its Application on a Herbal Formula, Qing-Luo-Yin

The scientific understanding of traditional Chinese medicine (TCM) has been hindered by the lack of methods that can explore the complex nature and combinatorial rules of herbal formulae. On the assumption that herbal ingredients mainly target a molecular network to adjust the imbalance of human body, here we present a-self-developed TCM network pharmacology platform for discovering herbal formulae in a systematic manner. This platform integrates a set of network-based methods that we established previously to catch the network regulation mechanism and to identify active ingredients as well as synergistic combinations for a given herbal formula. We then provided a case study on an antirheumatoid arthritis (RA) formula, Qing-Luo-Yin (QLY), to demonstrate the usability of the platform. We revealed the target network of QLY against RA-related key processes including angiogenesis, inflammatory response, and immune response, based on which we not only predicted active and synergistic ingredients from QLY but also interpreted the combinatorial rule of this formula. These findings are either verified by the literature evidence or have the potential to guide further experiments. Therefore, such a network pharmacology strategy and platform is expected to make the systematical study of herbal formulae achievable and to make the TCM drug discovery predictable.