A network pharmacology approach to evaluating the efficacy of chinese medicine using genome-wide transcriptional expression data

Efficacy and safety of herbal medicine (Binafuxi granules) for the common cold with fever: A multicenter, randomized, double-blind, placebo-controlled, phase II clinical trial

Background

Binafuxi granules are a traditional Uighur medicine (TUM) for treating the common cold with fever. However, high-quality clinical studies supporting its efficacy and safety are lacking.

Methods

In this multicenter, randomized, double-blind, placebo-controlled, phase II clinical trial, patients with common cold and fever were randomly assigned to a high-dose group, low-dose group, and placebo group in a 1:1:1 ratio. Outcomes were time to fever relief, time to fever clearance, proportion of afebrile patients, time to symptom disappearance, rate of symptom disappearance, effective rate, emergency drug usage and safety assessment.

Results

A total of 235 patients were recruited. Of these, 234 were included in the full analysis set (FAS), and 217 were included in the per-protocol set (PPS). In the FAS analysis, the median time to fever relief was 6.00 h, 5.54 h and 10.65 h (P = 0.31) in the high-dose group, low-dose group and placebo group, respectively. The median time to fever clearance was 18.29 h, 20.08 h and 25.00 h (P = 0.0018), respectively, and the proportion of afebrile patients was 92.4%, 89.7% and 71.4% (P = 0.0002), respectively. There was a significant difference in the disappearance time and disappearance rate of all symptoms and of individual symptoms. No serious adverse events were found.

Conclusions

Binafuxi granules can dose-dependently shorten the fever course and improve clinical symptoms in patients suffering from the common cold with fever.

Trial Registration

This trial was registered at Chinese Clinical Trial Registry (ChiCTR-IIR-17013379).

A systematic pharmacology-based in vivo study to reveal the effective mechanism of Yupingfeng in asthma treatment

BACKGROUND

The clinical effect of Yupingfeng (YPF) has been confirmed in asthma patients, however, it lacks a study to verify its pharmacological mechanism.

HYPOTHESIS/PURPOSE

To reveal the molecular basis and potential pharmacological mechanism of YPF in the treatment of asthma.

STUDY DESIGN AND METHODS

First, a systems pharmacology-based method integrating pharmacokinetic screening, target prediction, network analyses, GO and KEGG analyses were used for the systematic deciphering of the mechanism of YPF in asthma. Second, differentially expressed genes (DEGs) between asthma patients and healthy controls were identified by GEO2R online tool. Third, based on systems pharmacology and DEGs results, molecular docking was performed utilizing the Discovery Studio 2020 Client version to detect the binding capacity between compounds and targets. Finally, ovalbumin (OVA)-challenged C57BL/6 mice were treated with YPF or its effective compound to assess the predictions.

RESULTS

A total of 35 active compounds were filtered out, with 87 potential targets being identified for further analysis after target fishing and matching. Quercetin, kaempferol, and wogonin were identified as the main ingredients in YPF. The signaling pathways of phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT), tumor necrosis factor (TNF) and IL-17 were identified as the top signaling pathways in KEGG enrichment analysis. GEO2R tools of NCBI discovered five DEGs that overlapped with the therapeutic targets of YPF. Wogonin was proven to be the top active compound in YPF through the results of molecular docking. In vivo experiments indicated that YPF and wogonin significantly attenuated airway resistance and lung inflammation by decreasing the levels of inflammatory cytokines and key factors in PI3K/AKT, IL-17, and TNF signaling pathways.

CONCLUSIONS

YPF and its main active compound wogonin may exert some therapeutic effects on asthma inflammation through multiple molecular targets and signaling pathways including PI3K/AKT, IL-17 and TNF-α.

Network pharmacology approaches for research of Traditional Chinese Medicines

Pharmacodynamics material basis and effective mechanisms are the two main issues to decipher the mechnisms of action of Traditional Chinese medicines (TCMs) for the treatment of diseases. TCMs, in "multi-component, multi-target, multi-pathway" paradigm, show satisfactory clinical results in complex diseases. New ideas and methods are urgently needed to explain the complex interactions between TCMs and diseases. Network pharmacology (NP) provides a novel paradigm to uncover and visualize the underlying interaction networks of TCMs against multifactorial diseases. The development and application of NP has promoted the safety, efficacy, and mechanism investigations of TCMs, which then reinforces the credibility and popularity of TCMs. The current organ-centricity of medicine and the "one disease-one target-one drug" dogma obstruct the understanding of complex diseases and the development of effective drugs. Therefore, more attentions should be paid to shift from "phenotype and symptom" to "endotype and cause" in understanding and redefining current diseases. In the past two decades, with the advent of advanced and intelligent technologies (such as metabolomics, proteomics, transcriptomics, single-cell omics, and artificial intelligence), NP has been improved and deeply implemented, and presented its great value and potential as the next drug-discovery paradigm. NP is developed to cure causal mechanisms instead of treating symptoms. This review briefly summarizes the recent research progress on NP application in TCMs for efficacy research, mechanism elucidation, target prediction, safety evaluation, drug repurposing, and drug design.

GC–MS and Network Pharmacology Analysis of the Ayurvedic Fermented Medicine, Chandanasava, Against Chronic Kidney and Cardiovascular Diseases

Chandanasava is an Ayurvedic polyherbal fermented traditional medicine (FTM) used by traditional practitioners for millennia. Nevertheless, the mode of action and functional targets are still unknown. The current study includes a pharmacological network analysis to identify the Chandanasava compounds interacting with target proteins involved in chronic kidney disease (CKD) and cardiovascular disease (CVD). Sixty-one Chandanasava phytochemicals were obtained by GC-MS and screened using the Traditional Chinese Medicine Systems Pharmacology Database (TCMSP). The disease target genes were obtained from DisGeNET and GeneCards databases. Forty-five phytocompounds and 135 potential targets were screened for CKD and CVD target proteins and protein interaction networks were constructed. The pharmacological network was deciphered employing target proteins involved in the mechanical action of Chandanasava. The results indicated that 10 bioactive compounds exhibited higher binding affinity patterns with the screened 42 CKD and CVD target proteins. Gene Ontology and KEGG analysis revealed target pathways involved in CKD and CVD, which were further explored by detailed analysis and network-coupled drug profile screening. The molecular docking results showed piperine and melatonin as effective inhibitors/regulators of the hub genes of CKD and CVD. The current study establishing authentic bioactive compounds in FTM is based on deeper insights into recognized Ayurvedic medicines. Representing the workflow of the network pharmacological analysis.

Bipartite graph search optimization for type II diabetes mellitus Jamu formulation using branch and bound algorithm

Jamu is an Indonesian traditional herbal medicine that has been practiced for generations. Jamu is made from various medicinal plants. Each plant has several compounds directly related to the target protein that are directly associated with a disease. A pharmacological graph can form relationships between plants, compounds, and target proteins. Research related to the prediction of Jamu formulas for some diseases has been carried out, but there are problems in finding combinations or compositions of Jamu formulas because of the increase in search space size. Some studies adopted the drug–target interaction (DTI) implemented using machine learning or deep learning to predict the DTI for discovering the Jamu formula. However, this approach raises important issues, such as imbalanced and high-dimensional dataset, overfitting, and the need for more procedures to trace compounds to their plants. This study proposes an alternative approach by implementing bipartite graph search optimization using the branch and bound algorithm to discover the combination or composition of Jamu formulas by optimizing the search on a plant–protein bipartite graph. The branch and bound technique is implemented using the search strategy of breadth first search (BrFS), Depth First Search, and Best First Search. To show the performance of the proposed method, we compared our method with a complete search algorithm, searching all nodes in the tree without pruning. In this study, we specialize in applying the proposed method to search for the Jamu formula for type II diabetes mellitus (T2DM). The result shows that the bipartite graph search with the branch and bound algorithm reduces computation time up to 40 times faster than the complete search strategy to search for a composition of plants. The binary branching strategy is the best choice, whereas the BrFS strategy is the best option in this research. In addition, the the proposed method can suggest the composition of one to four plants for the T2DM Jamu formula. For a combination of four plants, we obtain Angelica Sinensis, Citrus aurantium, Glycyrrhiza uralensis, and Mangifera indica. This approach is expected to be an alternative way to discover the Jamu formula more accurately.

Exploration of the Molecular Mechanism of Danzhi Xiaoyao Powder in Endometrial Cancer through Network Pharmacology

Endometrial cancer (EC) is a common malignant tumor of the female reproductive system. Current treatments such as surgery and long-term hormone therapy are ineffective and have side effects. Danzhi Xiaoyao powder (DXP) can inhibit the growth of EC cells and induce apoptosis, but the pharmacological and molecular mechanisms of anticancer effects are still unclear. In this study, active components and potential targets of DXP were obtained from public databases. Protein effects and regulatory pathways of common targets were analyzed by protein-protein interaction (PPI), GO and KEGG. The results of network pharmacology showed that there are 87 common targets between EC and DXP. GO enrichment analysis showed that these targets were associated with response to oxidative stress, response to nutrient levels, hormone receptor binding and nuclear hormone receptor binding, etc. The results of KEGG analysis indicated that IL-17, TNF, PI3K/AKT, and RAS/RAF/MEK/ERK (ERK) signaling pathway were enriched in the anti-EC of DXP. Additionally, we cultured HEC-1B and KLE cells for validate experiments. DXP showed an inhibition of proliferation, migration, and cell cycle of both cells. Moreover, the expression of RAS, p-RAF, p-MEK, ERK, and p-ERK related proteins were downregulated. In conclusion, DXP might inhibit the proliferation of EC cells via apoptosis. Furthermore, DXP-induced inhibition of EC development might involve RAS/RAF/MEK/ERK pathway.

Systemic Analysis of the Anticancer Effects of Sijunzi Decoction on Gastric Cancer Based on Network Pharmacology

Objective:

Sijunzi decoction (SJZD) has been used for alleviating peptic ulcer or gastric discomfort, and treating spleen disorders since the Song Dynasty, but its pharmacological effect on human gastric cancer (GC) is still unclear. In this research, a network pharmacology-based strategy was applied to explore active ingredients, potential targets, and molecular mechanisms of SJZD against GC.

Methods:

The active compounds and potential targets of SJZD, as well as GC-associated gene targets, were retrieved from publicly available databases. Bioinformatics approaches were used to assess the network interaction, functional regulation, and signaling pathways between SJZD ingredients and GC targets. The anticancer effects of SJZD against GC were verified in vivo by a mouse subcutaneous model.

Results:

The results of network analysis showed that quercetin was the most active ingredient in SJZD. Several prominent target genes of SJZD were identified, such as AKT1 and STAT3. Gene ontology analysis revealed that the core anti-GC targets of SJZD included transcription factor activity and kinase activity. Pathway enrichment analysis indicated that GC patients could be benefited from SJZD treatment via modulation of signaling pathways related to endocrine system, cancer, and infectious disease. Furthermore, in vivo experiments showed that high-dose SJZD could inhibit GC xenograft tumor growth, reduce GC cell proliferation, induce GC cell apoptosis, and decrease the expression of p-AKT1 and p-STAT3.

Conclusions:

Taken together, our results suggest that SJZD can serve as an effective adjuvant therapeutic agent for GC patients.

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.

Bioinformatics and experimental studies of anti-leukemic activity from 6-gingerol demonstrate its role in p53 mediated apoptosis pathway

6-gingerol is a traditional medicine that possesses anti-cancer activity against several types of cancer. However, the mechanism of action still remains unclear. Therefore, this study explored the effects of 6-gingerol on anti-leukemic mechanisms in NB4, MOLT4, and Raji leukemic cell. Results indicated that 6-gingerol inhibited cell proliferation and induced cell apoptosis in these 3 cell lines. Moreover, 6-gingerol was shown to increase the mRNA expression of the caspase family thereby suggesting that 6-gingerol induced apoptosis through the caspase-dependent pathway. To explore the signaling pathway regulating 6-gingerol induced apoptosis, we utilized and integrated the network pharmacology approach together with experimental investigations. Targets of 6-gingerol were identified from ChEMBL and STITCH databases, which were used for constructing the protein-protein interaction (PPI) network. Results from the PPI network indicated that p53 was a key regulator. Moreover, it was found that 6-gingerol could increase the levels of p53 mRNA in all leukemic cell lines. Thus, 6-gingerol has shown to have anti-cancer activity. In addition, p53, BAX and BCL2 could be involved in the apoptosis pathway of these leukemic cells. This study is anticipated to be useful for the development of 6-gingerol as an anti-leukemic drug in the future.

Shenmai Injection Improves Energy Metabolism in Patients With Heart Failure: A Randomized Controlled Trial

Background

In recent years, the application of Shenmai (SM) injection, a traditional Chinese medicine (TCM), to treat heart failure (HF) has been gradually accepted in China. However, whether SM improves energy metabolism in patients with HF has not been determined due to the lack of high-quality studies. We aimed to investigate the influence of SM on energy metabolism in patients with HF.

Methods

This single-blind, controlled study randomly assigned 120 eligible patients equally into three groups receiving SM, trimetazidine (TMZ), or control in addition to standard medical treatment for HF for 7 days. The primary endpoints were changes in free fatty acids (FFAs), glucose, lactic acid (LA), pyroracemic acid (pyruvate, PA) and branched chain amino acids (BCAAs) in serum. The secondary outcomes included the New York Heart Association (NYHA) functional classification, TCM syndrome score (TCM-s), left ventricular injection fraction (LVEF), left ventricular internal diastolic diameter (LVIDd), left ventricular internal dimension systole (LVIDs), and B-type natriuretic peptide (BNP).

Results

After treatment for 1 week, the NYHA functional classification, TCM-s, and BNP level gradually decreased in the patients in all three groups, but these metrics were significantly increased in the patients in the SM group compared with those in the patients in the TMZ and control groups (P < 0.05). Moreover, energy metabolism was improved in the NYHA III–IV patients in the SM group compared with those in the patients in the TMZ and control groups as evidenced by changes in the serum levels of FFA, LA, PA, and BCAA.

Conclusions

Integrative treatment with SM in addition to standard medical treatment for HF was associated with improved cardiac function compared to standard medical treatment alone. The benefit of SM in HF may be related to an improvement in energy metabolism, which seems to be more remarkable than that following treatment with TMZ.

Investigation of cardiovascular protective effect of Shenmai injection by network pharmacology and pharmacological evaluation

BACKGROUND

Shenmai injection (SMI) has been used in the treatment of cardiovascular disease (CVD), such as heart failure, myocardial ischemia and coronary heart disease. It has been found to have efficacy on doxorubicin (DOX)-induced cardiomyopathy. The aims of this study were to explore the underlying molecular mechanisms of SMI treatment on CVD by using network pharmacology and its protective effect on DOX-induced cardiotoxicity by in vitro and in vivo experiment based on network pharmacology prediction.

METHODS

Network pharmacology method was used to reveal the relationship between ingredient-target-disease and function-pathway of SMI on the treatment of CVD. Chemical ingredients of SMI were collected form TCMSP, BATMAN-TCM and HIT Database. Drugbank, DisGeNET and OMIM Database were used to obtain potential targets for CVD. Networks were visualized utilizing Cytoscape software, and the enrichment analysis was performed using IPA system. Finally, cardioprotective effects and predictive mechanism confirmation of SMI were investigated in H9c2 rat cardiomyocytes and DOX-injured C57BL/6 mice.

RESULTS

An ingredient-target-disease & function-pathway network demonstrated that 28 ingredients derived from SMI modulated 132 common targets shared by SMI and CVD. The analysis of diseases & functions, top pathways and upstream regulators indicated that the cardioprotective effects of SMI might be associated with 28 potential ingredients, which regulated the 132 targets in cardiovascular disease through regulation of G protein-coupled receptor signaling. In DOX-injured H9c2 cardiomyocytes, SMI increased cardiomyocytes viability, prevented cell apoptosis and increased PI3K and p-Akt expression. This protective effect was markedly weakened by PI3K inhibitor LY294002. In DOX-treated mice, SMI treatment improved cardiac function, including enhancement of ejection fraction and fractional shortening.

CONCLUSIONS

Collectively, the protective effects of SMI on DOX-induced cardiotoxicity are possibly related to the activation of the PI3K/Akt pathway, as the downstream of G protein-coupled receptor signaling pathway.

Uncovering Synergistic Mechanism of Chinese Herbal Medicine in the Treatment of Atrial Fibrillation with Obstructive Sleep Apnea Hypopnea Syndrome by Network Pharmacology

Paroxysmal atrial fibrillation (AF) combined with obstructive sleep apnea hypopnea syndrome (OSAHS) is very common in clinical practice. Traditional Chinese medicine (TCM) rule of regulating the liver based on psycho-cardiology shows satisfactory effectiveness in the treatment of paroxysmal AF combined with OSAHS. However, its underlying pharmacological mechanism has not yet been elucidated. This study applied network pharmacology to identify 94 active components in the six TCM liver-regulating herbs and 182 corresponding targets from several databases and comprehensive literature studies, as well as retrieved AF combined with OSAHS-related targets. Cytoscape software was adopted to construct the component-component target network and component-putative target-AF combined with OSAHS target network. Then, we obtained 38 putative therapeutic targets against AF combined with OSAHS. After the production of a putative therapeutic target interaction network, topological analysis was adopted to determine the core targets of TCM liver-regulating herbs in the treatment of paroxysmal AF combined with OSAHS. For all putative therapeutic targets, biological process analysis and pathway enrichment analysis were utilized to investigate the possible mechanism of TCM liver-regulating herbs in the treatment of paroxysmal AF combined with OSAHS. Mechanistically, it included positive regulation of nitric oxide biosynthetic process, aging, response to hypoxia, TNF signaling pathway, HIF-1 signaling pathway, PI3K-Akt signaling pathway, neuroactive ligand-receptor interaction, and calcium signaling pathway. Especially, six core targets of TCM liver-regulating herbs, namely, TNF, STAT3, AKT1, IL-6, TP53, and INS, were significant in the regulation of the above biological processes and pathways. This study demonstrates the multicomponent, multitarget, and multipathway feature of TCM liver-regulating herbs, provides an extensional foundation for further research, and facilitates the reasonable application of TCM liver-regulating herbs in treating paroxysmal AF combined with OSAHS.

Insights about multi-targeting and synergistic neuromodulators in Ayurvedic herbs against epilepsy: integrated computational studies on drug-target and protein-protein interaction networks

Epilepsy, that comprises a wide spectrum of neuronal disorders and accounts for about one percent of global disease burden affecting people of all age groups, is recognised as apasmara in the traditional medicinal system of Indian antiquity commonly known as Ayurveda. Towards exploring the molecular level complex regulatory mechanisms of 63 anti-epileptic Ayurvedic herbs and thoroughly examining the multi-targeting and synergistic potential of 349 drug-like phytochemicals (DPCs) found therein, in this study, we develop an integrated computational framework comprising of network pharmacology and molecular docking studies. Neuromodulatory prospects of anti-epileptic herbs are probed and, as a special case study, DPCs that can regulate metabotropic glutamate receptors (mGluRs) are inspected. A novel methodology to screen and systematically analyse the DPCs having similar neuromodulatory potential vis-à-vis DrugBank compounds (NeuMoDs) is developed and 11 NeuMoDs are reported. A repertoire of 74 DPCs having poly-pharmacological similarity with anti-epileptic DrugBank compounds and those under clinical trials is also reported. Further, high-confidence PPI-network specific to epileptic protein-targets is developed and the potential of DPCs to regulate its functional modules is investigated. We believe that the presented schema can open-up exhaustive explorations of indigenous herbs towards meticulous identification of clinically relevant DPCs against various diseases and disorders.

Protective mechanism of shenmai on myocardial ischemia-reperfusion through the energy metabolism pathway

Shenmai (SM) injection has been reported to attenuate ischemia-reperfusion (I/R) injury, but its effect on energy metabolism during I/R and the underlying mechanism remain unknown. To explore the protective mechanism of SM on ischemic cardiomyopathy, primary cardiomyocytes from SD rats were treated with SM, total saponins of Panax ginseng (TSPG), L-carnitine (LC) and trimetazidine (TMZ). Changes in glucose, free fatty acids (FFAs), pyruvic acid (PA), lactic acid (LA) and intracellular ATP capacity were observed with the appropriate assays. For each treatment group, the key enzymes and transporters of myocardial energy metabolism were detected and compared via Western blot. Furthermore, impairments after I/R were assessed by examining cardiomyocyte apoptosis and LDH and PK activity in the culture medium. Our results indicated that SM and TSPG markedly alleviated the decrease in key enzymes and transporters and the utilization of metabolic substrates following I/R, while SM prevented aberrant apoptosis and restored the depleted ATP resulting from I/R. Notably, the effects of SM were superior to those of its main components TSPG, LC and TMZ. Thus, the protective effect of SM in ischemic cardiomyopathy may be mediated by the upregulation of key enzymes and restoration of the depleted ATP content in the energy metabolism process.

A Network Pharmacology Approach to Explore Mechanism of Action of Longzuan Tongbi Formula on Rheumatoid Arthritis

Longzuan Tongbi Formula (LZTB) is an effective proved prescription in Zhuang medicine for treating active rheumatoid arthritis (RA). However, its active ingredients, underlying targets, and pharmacological mechanism are still not clear in treating RA. We have applied network pharmacology to study LZTB and found that 8 herbs in LZTB and 67 compounds in the 8 herbs are involved in the regulation of RA-related genes; we have conducted pathway analysis of overlapping genes and found that 7 herbs participate in the regulations of 24 pathways associated with RA and that 5 herbs in the 7 herbs and 25 compounds in the 5 herbs participate in the regulation of hsa05323 (rheumatoid arthritis). The results indicated that all herbs in LZTB and some compounds in those herbs participate in the treatment of RA; 25 compounds are main active ingredients and hsa05323 (rheumatoid arthritis) is the major pathway in the treatment of RA. We have also found that three pathways (inflammatory mediator regulation of TRP channels, PPAR signaling pathway, and mTOR signaling pathway) might have some effect on the treatment of RA.

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

ETHNOPHARMACOLOGICAL RELEVANCE

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

AIM OF THE STUDY

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

MATERIALS AND METHOD

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

RESULTS

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

CONCLUSION

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

Potential Root Foraging Strategy of Wheat (Triticum aestivum L.) for Potassium Heterogeneity

Potassium (K) distribution is horizontally heterogeneous under the conservation agriculture approach of no-till with strip fertilization. The root foraging strategy of wheat for K heterogeneity is poorly understood. In this study, WinRHIZO, microarray, Non-invasive Micro-test Technology (NMT) and a split-root system were performed to investigate root morphology, gene expression profiling and fluxes of K+ and O2 under K heterogeneity and homogeneity conditions. The split-root system was performed as follows: C. LK (both compartments had low K), C. NK (both compartments had normal K), Sp. LK (one compartment had low K) and Sp. NK (the other compartment had normal K). The ratio of total root length and root tips in Sp. NK was significantly higher than that in C. NK, while no significant differences were found between Sp. LK and C. LK. Differential expression genes in C. LK vs. C. NK had opposite responses in Sp. LK vs. C. LK and similar responses in Sp. NK vs. C. NK. Low-K responsive genes, such as peroxidases, mitochondrion, transcription factor activity, calcium ion binding, glutathione transferase and cellular respiration genes were found to be up-regulated in Sp. NK. However, methyltransferase activity, protein amino acid phosphorylation, potassium ion transport, and protein kinase activity genes were found to be down-regulated in Sp. LK. The up-regulated gene with function in respiration tended to increase K+ uptake through improving O2 influx on the root surface in Sp. NK, while the down-regulated genes with functions of K+ and O2 transport tended to reduce K+ uptake on the root surface in Sp. LK. To summarize, wheat roots tended to perform active-foraging strategies in Sp. NK and dormant-foraging strategies in Sp. LK through the following patterns: (1) root development in Sp. NK but not in Sp. LK; (2) low-K responsive genes, such as peroxidases, mitochondrion, transcription factor activity, calcium ion binding and respiration, were up-regulated in Sp. NK but not in Sp. LK; and (3) root K+ and O2 influxes increased in Sp. NK but not in Sp. LK. Our findings may better explain the optimal root foraging strategy for wheat grown with heterogeneous K distribution in the root zone.

Exploring the Pharmacological Mechanism of Danzhi Xiaoyao Powder on ER-Positive Breast Cancer by a Network Pharmacology Approach

Background

Breast cancer is the most common malignancy among women worldwide, but the long-term endocrine therapy is frequently associated with adverse side effects. Danzhi Xiaoyao powder (DXP) is a herbal formula that has an effect on breast cancer, especially ER-positive breast cancer. However, the active compounds, potential targets, and pharmacological and molecular mechanism of its action against cancer remain unclear.

Methods

A network pharmacology approach comprising drug-likeness evaluation, oral bioavailability prediction, Caco-2 permeability prediction, multiple compound target prediction, multiple known target collection, breast cancer genes collection, and network analysis has been used in this study.

Results

Four networks are set up—namely, ER-positive breast cancer network, compound-compound target network of DXP, DXP-ER-positive breast cancer network, and compound-known target-ER-positive breast cancer network. Some ER-positive breast cancer and DXP related targets, clusters, biological processes, and pathways, and several potential anticancer compounds are found.

Conclusion

This network analysis successfully predicted, illuminated, and confirmed the molecular synergy of DXP for ER-positive breast cancer, got potential anticancer active compounds, and found the potential ER-positive breast cancer associated targets, cluster, biological processes, and pathways. This work also provides clues to the researcher who explores ethnopharmacological or/and herbal medicine's or even multidrugs' various synergies.

iTRAQ-Based Proteomic Analysis Reveals Recovery of Impaired Mitochondrial Function in Ischemic Myocardium by Shenmai Formula

Shenmai formula (SM) has been a traditional medicinal remedy for treating cardiovascular diseases in China for 800 years; however, its mechanism of action remains unclear. To explore the mechanism underlying cardioprotective effects of SM, iTRAQ-based proteomic approach was applied to analyze protein of myocardium in rats with myocardial ischemic injury. Upon treatment with SM and its two major components Red ginseng (RG) and Radix Ophiopogonis (OP), 101 differentially expressed proteins were filtered from a total of 712 detected and annotated proteins. They can be classified according to their locations and functions, while most of them are located in intracellular organelle, participating in cellular metabolic process. The functions of them are mostly associated with mitochondrial oxidative phosphorylation/respiration. The differentially expressed proteins were validated by liquid chromatography-tandem mass spectrometry and Western blotting (ATP5D, NDUFB10, TNNC1). Further in vitro experiments found that SM could attenuate hypoxia induced impairment of mitochondrial membrane potential and cellular ATP concentration in neonatal rat ventricular myocytes. Interestingly, the result of quantitative mitochondrial biogenesis assays revealed that SM had dominant positive effects on the maximum respiration, ATP-coupled respiration, and spare capacity of mitochondria in response to hypoxia. Hence, our findings suggest that SM promotes mitochondrial function to protect cardiomyocytes against hypoxia, which provides a possible illustration for conventional botanical therapy on a molecular level.

Uncovering the Pharmacological Mechanism of Astragalus Salvia Compound on Pregnancy-Induced Hypertension Syndrome by a Network Pharmacology Approach

To uncover the pharmacological mechanism of Astragalus Salvia compound (ASC) on pregnancy-induced hypertension syndrome (PIH), to provide useful information for clinical, as well as to connect the basic and clinical by a network pharmacological approach, we used network pharmacological approach. We collected ASC's compounds by traditional Chinese Medicine databases, and input them into PharmMapper to got their targets. Then we acquired PIH targets from Genecards and OMIM, collected the interactions of all the targets and other human proteins via String and INACT. We also constructed the network by Cytoscape and analyze it by MCODE so as to get clusters. Finally, we put all the targets of clusters into DAVID to do GO enrichment analysis. After these, four networks are constructed by Cytoscape; they are PIH network, compound-compound target network of ASC, ASC-PIH network, and compound target-PIH target-other human proteins' PPI network. According to the results, we think that ASC may directly regulate several biological processes and their genes in "endothelial cell activation and injury" and "placental or trophoblast cell ischemia" models to treat PIH. And it may indirectly act on the rest of the biological process to treat PIH or may not.

A randomized, double-blind, multicenter, placebo-controlled clinical study on the efficacy and safety of Shenmai injection in patients with chronic heart failure

ETHNOPHARMACOLOGICAL RELEVANCE

Shenmai injection (SMI) is a traditional Chinese herbal medicine extracted from Panax ginseng (Panax ginseng C.A. Mey, steamed and dry) and Ophiopogon japonicus (Ophiopogon japonicus (L.f.) Ker-Gawl, root). It has been widely used for the treatment of chronic heart failure (CHF) in China. However, the evidence supporting its effects remains unclear due to lack of high quality trials. The aim of this study was to investigate the efficacy and safety of SMI in CHF patients with coronary artery disease (CAD).

MATERIALS AND METHODS

This double-blind, multicenter study randomized 240 eligible patients equally to receive SMI or placebo (100ml/day) in addition to standard medicines for the treatment of CHF. The primary endpoint was the New York Heart Association (NYHA) functional classification. The secondary endpoints were 6-min walking distance (6MWD), short-form 36 (SF-36) hearth survey score, traditional Chinese medicines (TCM) syndrome score, left ventricular ejection fractions (LVEF) and B-type natriuretic peptide (BNP) level.

RESULTS

During treatment of 1 week, the NYHA functional classification was gradually improved in both groups, but the SMI group demonstrated a significantly greater improvement compared with the placebo group (p=0.001). Moreover, the improvement in patients received SMI was superior to those in control group with respect to 6MWD, SF-36 score and TCM syndrome score. Treatment with SMI within 1 week was well tolerated with no apparent safety concerns.

CONCLUSIONS

The integrative treatment with standard medicines plus SMI can further improve NYHA functional classification for patients with CHF and CAD. Therefore, SMI could be recommended in the combination therapy for CHF accompanied with CAD.

Actions of Huangqi decoction against rat liver fibrosis: a gene expression profiling analysis

Background

Huangqi decoction (HQD) is used for liver fibrosis and cirrhosis treatment in Chinese medicine. This study aims to investigate the pharmacological actions of HQD against liver fibrosis in rats by high-throughput gene expression profiling, network analysis and real-time qRT-PCR.

Methods

We analyzed the profiles of differentially expressed genes (DEGs) in dimethylnitrosamine (DMN)-induced liver fibrosis in rat. The liver tissue samples of control group (n = 3), model group (n = 3) and HQD group (n = 3) were examined by microarrays. Pathways were analyzed by KEGG. Pathway-gene and protein–protein interaction (PPI) networks were constructed with Cytoscape software. The expression of candidate genes was verified by qRT-PCR. P values less than 0.05 indicated statistical significance.

Results

Collagen deposition and hydroxyproline (Hyp) content were decreased in the HQD group compared with the model group (P < 0.001), while that of Hyp in the model group were increased compared with the control group (P < 0.001). In comparison with the model group, 1085 DEGs (all P < 0.05, |fold change| >1.5) and 52 pathways in the HQD group were identified. TGF-beta, ECM-receptor interaction, and the cell adhesion molecules pathways were significantly recovered by HQD (P < 0.001). A pathway-gene network was constructed, including 303 DEGs and 52 pathways, and 514 nodes and 2602 edges, among 142 genes with node degrees greater than 10. The expressions of PDGFra, PDGFrb, PDGFb, PDGFd, COL1A1, COL1A2, COL5A2, and THBS1 were significantly down-regulated by HQD (P < 0.001).

Conclusion

HQD down-regulated the expressions of PDGFra, PDGFrb, PDGFb, PDGFd, COL1A1, COL1A2, COL5A2 and THBS1, and TGF-β and PDGF signaling pathways in the DMN-induced liver fibrosis in rats.

Electronic supplementary material

The online version of this article (doi:10.1186/s13020-015-0066-5) contains supplementary material, which is available to authorized users.

NETBAGs: a network-based clustering approach with gene signatures for cancer subtyping analysis

AIM

To evaluate gene signature and network-based approach for cancer subtyping and classification.

MATERIALS & METHODS

Here we introduced NETwork Based clustering Approach with Gene signatures (NETBAGs) algorithm, which clustered samples based on gene signatures and identified molecular markers based on their significantly expressed gene network profiles.

RESULTS

Applying NETBAGs to multiple independent breast cancer datasets, we demonstrated that the clustering results were highly associated with the clinical subtypes and clearly revealed the genomic diversity of breast cancer samples.

CONCLUSION

NETBAGs algorithm is able to classify samples by their genomic signatures into clinically significant phenotypes so that potential biomarkers can be identified. The approach may contribute to cancer research and clinical study of complex diseases.

Evaluating the antidiabetic effects of Chinese herbal medicine: Xiao-Ke-An in 3T3-L1 cells and KKAy mice using both conventional and holistic omics approaches

BACKGROUND

Xiao-Ke-An (XKA) is a Chinese medicine widely used for treating type 2 diabetes mellitus (T2D). It is composed of eight herbal medicines traditionally used for T2D, including Rehmannia glutinosa Libosch, Anemarrhena asphodeloides Bunge, Coptis chinensis Franch, etc. The aim of the present study was to investigate the antidiabetic effects of XKA with both conventional and holistic omics approaches.

METHODS

The antidiabetic effect of XKA was first investigated in 3T3-L1 cells to study the effect of XKA on adipogenesis in vitro. Oil Red O staining was performed to determine the lipid accumulation. The intracellular total cholesterol (TC) and triglyceride (TG) contents in XKA treated 3T3-L1 cells were also evaluated. The therapeutic effects of XKA was further evaluated in KKAy mice with both conventional and holistic omics approaches. Body weight, fasting and non-fasting blood glucose, and oral glucose tolerance were measured during the experiment. At the time of sacrifice, serum was collected for the measurement of TG, TC, high-density lipoprotein cholesterol (HDL-c) and low-density lipoprotein cholesterol (LDL-c). The liver, kidney, spleen, pancreas, heart and adipose tissues were harvested and weighted. The liver was used for further microarray experiment. Omics approaches were adopted to evaluate the holistic rebalancing effect of XKA at molecular network level.

RESULTS

XKA significantly inhibited adipogenic differentiation, lowered the intracellular TC and TG contents in 3T3-L1 cells. XKA improved the glucose homeostasis and lipid metabolism, ameliorated insulin resistance in KKAy mice. Furthermore, XKA also exhibited effective therapeutic effects by reversing the molecular T2D disease network from an unbalanced state.

CONCLUSIONS

This study investigated the antidiabetic effects of XKA with both conventional and holistic omics approaches, providing both phenotypic evidence and underlying action mechanisms for the clinical use of XKA treating T2D.

Comparative analysis of potassium deficiency-responsive transcriptomes in low potassium susceptible and tolerant wheat (Triticum aestivum L.)

Potassium (K⁺) deficiency as a common abiotic stress can inhibit the growth of plants and thus reduce the agricultural yields. Nevertheless, scarcely any development has been promoted in wheat transcriptional changes under K⁺ deficiency. Here we investigated root transcriptional changes in two wheat genotypes, namely, low-K⁺ tolerant “Tongzhou916” and low-K⁺ susceptible “Shiluan02-1”. There were totally 2713 and 2485 probe sets displayed expression changes more than 1.5-fold in Tongzhou916 and Shiluan02-1, respectively. Low-K⁺ responsive genes mainly belonged to the categories as follows: metabolic process, cation binding, transferase activity, ion transporters and so forth. We made a comparison of gene expression differences between the two wheat genotypes. There were 1321 and 1177 up-regulated genes in Tongzhou916 and Shiluan02-1, respectively. This result indicated that more genes took part in acclimating to low-K⁺ stress in Tongzhou916. In addition, there were more genes associated with jasmonic acid, defense response and potassium transporter up-regulated in Tongzhou916. Moreover, totally 19 genes encoding vacuolar H⁺-pyrophosphatase, ethylene-related, auxin response, anatomical structure development and nutrient reservoir were uniquely up-regulated in Tongzhou916. For their important role in root architecture, K⁺ uptake and nutrient storage, unique genes above may make a great contribution to the strong low-K⁺ tolerance in Tongzhou916.

Using systems biology approaches to understand cardiac inflammation and extracellular matrix remodeling in the setting of myocardial infarction

Inflammation and extracellular matrix (ECM) remodeling are important components regulating the response of the left ventricle to myocardial infarction (MI). Significant cellular- and molecular-level contributors can be identified by analyzing data acquired through high-throughput genomic and proteomic technologies that provide expression levels for thousands of genes and proteins. Large-scale data provide both temporal and spatial information that need to be analyzed and interpreted using systems biology approaches in order to integrate this information into dynamic models that predict and explain mechanisms of cardiac healing post-MI. In this review, we summarize the systems biology approaches needed to computationally simulate post-MI remodeling, including data acquisition, data analysis for biomarker classification and identification, data integration to build dynamic models, and data interpretation for biological functions. An example for applying a systems biology approach to ECM remodeling is presented as a reference illustration.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Dissecting active ingredients of Chinese medicine by content-weighted ingredient–target network

A novel approach integrating network pharmacology analysis with ingredient content and ingredient–target relationships to identify active ingredients of Chinese medicine.

A network study of chinese medicine xuesaitong injection to elucidate a complex mode of action with multicompound, multitarget, and multipathway

Chinese medicine has evolved from thousands of years of empirical applications and experiences of combating diseases. It has become widely recognized that the Chinese medicine acts through complex mechanisms featured as multicompound, multitarget and multipathway. However, there is still a lack of systematic experimental studies to elucidate the mechanisms of Chinese medicine. In this study, the differentially expressed genes (DEGs) were identified from myocardial infarction rat model treated with Xuesaitong Injection (XST), a Chinese medicine consisting of the total saponins from Panax notoginseng (Burk.) F. H. Chen (Chinese Sanqi). A network-based approach was developed to combine DEGs related to cardiovascular diseases (CVD) with lines of evidence from the literature mining to investigate the mechanism of action (MOA) of XST on antimyocardial infarction. A compound-target-pathway network of XST was constructed by connecting compounds to DEGs validated with literature lines of evidence and the pathways that are functionally enriched. Seventy potential targets of XST were identified in this study, of which 32 were experimentally validated either by our in vitro assays or by CVD-related literatures. This study provided for the first time a network view on the complex MOA of antimyocardial infarction through multiple targets and pathways.