Network pharmacology-based prediction of the active ingredients, potential targets, and signaling pathways in compound Lian-Ge granules for treatment of diabetes

Bacoside a inhibits the growth of glioma by promoting apoptosis and autophagy in U251 and U87 cells

Bacoside A (gypenoside, Gyp) is a potent bioactive compound derived from Gynostemma pentaphyllum, known to exert inhibitory effects on various malignant tumors. However, the effects of Gyp on glioma as well as the underlying mechanisms remain unclear. In the present study, we first conducted a comprehensive investigation into the anti-glioma potential of gypenosides using network pharmacology to identify potential glioma-related targets. Protein-protein interaction networks were assembled, and GO and KEGG enrichment analyses were performed for shared targets. Experimental validation involved assessing the viability of U251 and U87 cell lines using the MTS method. Furthermore, trans-well and scratch migration assays evaluated the cell migration, while flow cytometry and Hoechst 33342 staining were utilized for apoptosis assessment. The study also monitored changes in autophagy flow through fluorescence microscopy. The expression levels of proteins pertinent to migration, apoptosis, and autophagy were tested using Western blotting. Findings revealed that Gyp upregulated apoptosis-related proteins (Bax and cleaved caspase-9), downregulated anti-apoptotic protein Bcl-2, and migration-associated matrix metalloproteinases (MMP-2 and MMP-9). Furthermore, autophagy-related proteins (Beclin1 and LC3 II) were upregulated, and p62 protein expression was downregulated. Gyp displayed considerable potential in suppressing glioma progression by inhibiting cell proliferation, invasion, and migration and promoting apoptosis and autophagy. Gyp may offer potential clinical therapeutic choices in glioma management.

The Mechanism of Plantaginis Semen in the Treatment of Diabetic Nephropathy based on Network Pharmacology and Molecular Docking Technology

BACKGROUND

Diabetic nephropathy (DN) is one of the common complications of diabetes. Plantaginis Semen (PS) has a variety of therapeutic effects, however its mechanism on DN is unclear.

OBJECTIVE

This paper aims to find the ingredients, the key targets, and the action pathways of PS on DN from the perspective of network pharmacology.

METHODS

The databases of network pharmacology, such as Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), Pharmmapper, OMIM, DrugBank, Gene- Cards, TTD, Disgenet, STRING, and Cytoscape software, were used to find the main ingredients and targets. Gene Ontology (GO) function and Kyoto Encyclopedia of Genome and Genomes (KEGG) pathway enrichment analysis were used to reveal the potential pathways of the PS on DN. The GEO database was used to find the targets of DN based on valid experimental research. The molecular docking technology was used to evaluate the combination between ingredients of PS and the targets.

RESULTS

A total of 9 active ingredients and 216 potential therapeutic targets were obtained for PS on DN. Hub targets were discovered by the Cytoscape software analysis. CASP3 was screened by Venn diagram by making intersection between GSE30529 and hub genes. Moreover, CASP3 was combined with one of the nine active ingredients, quercetin, by molecular docking analysis. The KEGG pathways were mainly involved in diabetic nephropathy, and were simultaneously associated with CASP3 as followed: AGE-RAGE signaling pathway in diabetic complications, apoptosis, lipid and atherosclerosis, MAPK signaling pathway, TNF signaling pathway, IL-17 signaling pathway, and p53 signaling pathway.

CONCLUSION

PS can have the treatment on DN through CASP3. Quercetin, as one of the nine active ingredients, can be bounded to CASP3 to inhibit apoptosis in DN. PS can also take action on DN probably through many pathways. The role of PS on DN through other pathways still needs to be further elaborated.

TCMSID: a simplified integrated database for drug discovery from traditional chinese medicine

Traditional Chinese Medicine (TCM) has been widely used in the treatment of various diseases for millennia. In the modernization process of TCM, TCM ingredient databases are playing more and more important roles. However, most of the existing TCM ingredient databases do not provide simplification function for extracting key ingredients in each herb or formula, which hinders the research on the mechanism of actions of the ingredients in TCM databases. The lack of quality control and standardization of the data in most of these existing databases is also a prominent disadvantage. Therefore, we developed a Traditional Chinese Medicine Simplified Integrated Database (TCMSID) with high storage, high quality and standardization. The database includes 499 herbs registered in the Chinese pharmacopeia with 20,015 ingredients, 3270 targets as well as corresponding detailed information. TCMSID is not only a database of herbal ingredients, but also a TCM simplification platform. Key ingredients from TCM herbs are available to be screened out and regarded as representatives to explore the mechanism of TCM herbs by implementing multi-tool target prediction and multilevel network construction. TCMSID provides abundant data sources and analysis platforms for TCM simplification and drug discovery, which is expected to promote modernization and internationalization of TCM and enhance its international status in the future. TCMSID is freely available at https://tcm.scbdd.com .

Potential Therapeutic Mechanism of Scutellaria baicalensis Georgi against Ankylosing Spondylitis Based on a Comprehensive Pharmacological Model

Background

Scutellaria baicalensis Georgi (SBG) has significant anti-inflammatory and immune-modulating activities and is widely used in the treatment of inflammatory and autoimmune diseases. However, the mechanism of SBG in the treatment of ankylosing spondylitis (AS) remains to be elucidated.

Methods

Differentially expressed genes (DEGs) related to AS were analyzed based on two GEO gene chips. The DEGs were merged with the data derived from OMIM, GeneCards, and PharmGKB databases to ascertain AS-related targets. Active components of SBG and their targets were acquired from the TCMSP database. After overlapping the targets of AS and SBG, the action targets were acquired. Subsequently, protein-protein interaction (PPI) network and core target screening were conducted using the STRING database and Cytoscape software. Moreover, the DAVID platform was used to perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of action targets. Finally, the affinity of major active components and core targets was validated with molecular docking.

Results

A total of 36 active components of SBG were acquired from TCMSP database. Among these, the main active components were baicalein, wogonin, and oroxylin A. The PPI network and screening showed TNF, IL-6, CXCL8, PTGS2, and VEGFA as core targets associated SBG against AS. GO and KEGG analyses indicated that SBG participated in various biological processes, via regulating IL-17, TNF, and NF-κB signaling pathways. Molecular docking results confirmed a strong binding activity between the main active components and the core targets.

Conclusion

The therapeutic mechanism of SBG associated with AS can be characterized as a multicomponent, multitarget, and multipathway mechanism. SBG may be a promising therapeutic candidate for AS.

Isolation of oligostilbenes from Iris lactea Pall. var. chinensis (Fisch.) Koidz and their anti-inflammatory activities

Iris lactea Pall. var. chinensis (Fisch.) Koidz (Iris lactea) is an herbaceous perennial widely distributed in China, India, and South Korea. Iris lactea has been extensively used in traditional Chinese medicine. The present study isolated a new oligostilbene (compound 1), together with three known oligostilbenes (compounds 2, 3 and 4) from the seeds of Iris lactea. The structures of these compounds were elucidated by HRESIMS, NMR, and chemical analyses. The network-based pharmacologic analysis platform was used to predict the target proteins related to inflammation of isolated compounds. Furthermore, the isolated compounds were tested for their anti-inflammatory effects in LPS-stimulated RAW 264.7 cells. In this network, 138 candidate targets of compounds related to its therapeutic effect on inflammation were identified. In addition, compounds 1, 2, 3 and 4 significantly decreased NO content and the IL-6 levels as well as the expression of COX-2 in LPS-stimulated RAW 264.7 cells.

Prediction of the Mechanisms by Which Quercetin Enhances Cisplatin Action in Cervical Cancer: A Network Pharmacology Study and Experimental Validation

Yimucao has been used as an herbal medicine to treat gynecological diseases. Common genes of Yimucao active compounds were investigated using network pharmacology. The components and targets of Yimucao were retrieved from the TCMSP database. Cervical cancer targets were collected from GeneCards, TTD, DisGeNET, and KEGG. Cisplatin-related genes were downloaded from GeneWeaver. The protein-protein interaction (PPI) network was created using the STRING database. A drug-bioactive compound-disease-target network was constructed using Cytoscape. GO and KEGG analyses were performed to investigate common targets of quercetin and cisplatin in cervical cancer. We found that quercetin was the highly bioactive compound in Yimucao. The drug-bioactive compound-disease-target network contained 93 nodes and 261 edges. Drug-related key targets were identified, including EGFR, IL6, CASP3, VEGFA, MYC, CCND1, ERBB2, FOS, PPARG, and CASP8. Core targets were primarily related to the response to metal ions, cellular response to xenobiotic stimulus, and transcription factor complex. The KEGG pathway analysis revealed that quercetin and cisplatin may affect cervical cancer through platinum drug resistance and the p53 and HIF-1 pathways. Furthermore, quercetin combined with cisplatin downregulated the expression of EGFR, MYC, CCND1, and ERBB2 proteins and upregulated CASP8 expression in HeLa and SiHa cells. Functionally, quercetin enhanced cisplatin-induced anticancer activity in cervical cancer cells. Our results indicate that quercetin can be used to overcome cisplatin resistance in cervical cancer cells.

Emerging Applications of Metabolomics to Assess the Efficacy of Traditional Chinese Medicines for Treating Type 2 Diabetes Mellitus

Diabetes is a common and complex disease that can exacerbate the complications related to cardiovascular disease, and this is especially true for type 2 diabetes mellitus (T2DM). In addition to the standard pharmacological therapies, T2DM has also been treated with nonconventional regimens such as traditional Chinese medicine (TCM), e.g., herbal medicines and TCM prescriptions, although the mechanisms underlying the therapeutic benefits remain unclear. In this regard, many studies have used metabolomics technology to elucidate the basis for the efficacy of TCM for T2DM. Metabolomics has recently attracted much attention with regard to drug discovery and pharmacologically relevant natural products. In this review, we summarize the application of metabolomics to the assessment of TCM efficacy for treating T2DM. Increasing evidence suggests that the metabolic profile of an individual patient may reflect a specific type of T2DM syndrome, which may provide a new perspective for disease diagnosis. In addition, TCM has proved effective for countering the metabolic disorders related to T2DM, and this may constitute the basis for TCM efficacy. Therefore, further determining how TCM contributes to the reversal of metabolic disorders, such as using network pharmacology or by assessing the contribution of host–gut microbiota interactions, will also provide researchers with new potential targets for pharmacologic-based therapies.

Medical Species Used in Russia for the Management of Diabetes and Related Disorders

Background: Polyherbal mixtures called "medical species" are part of traditional and officinal medicine in Russia. This review aimed to analyze medical species used in Russia for the treatment of diabetes and related disorders. The information relevant to medical species, diabetes, and obesity was collected from local libraries, the online service E-library.ru, and Google Scholar. The prediction of the antidiabetic activity for the principal compounds identified in plants was performed using the free web resource PASS Online. Results: We collected and analyzed information about the compositions, specificities of use, and posology of 227 medical species. The medical species represent mixtures of 2-15 plants, while the most frequently mentioned in the literature are species comprising 3-6 plants. The top 10 plants among the 158 mentioned in the literature include Vaccinium myrtillus L., Phaseolus vulgaris L., Taraxacum campylodes G.E. Haglund., Urtica dioica L., Rosa spp., Hypericum spp., Galega officinalis L., Mentha × piperita L., Arctium spp, and Fragaria vesca L. The leading binary combination found in medical species comprises the leaves of V. myrtillus and pericarp of P. vulgaris; leaves of V. myrtillus and leaves of U. dioica; and leaves of V. myrtillus and aerial parts of G. officinalis. In triple combinations, in addition to the above-mentioned components, the roots of T. campylodes are often used. These combinations can be regarded as basic mixtures. Other plants are added to improve the efficacy, treat associated disorders, improve gastrointestinal function, prevent allergic reactions, etc. Meanwhile, an increase in plants in the mixture necessitates advanced techniques for quality control. A feature of medical species in Russia is the addition of fresh juices, birch sap, seaweeds, and adaptogenic plants. Modern studies of the mechanisms of action and predicted activities of the principal compounds from medicinal plants support the rationality of polyherbal mixtures. Nevertheless, the mechanisms are not well studied and reported due to the limited number of compounds. Further investigations with calculations of synergistic or additive indices are important for strengthening the scientific fundamentals for the wider use of medical species in the therapy of diabetes. Two medical species, "Arfazetin" (7 medicinal plants) and "Myrphasinum" (12 medicinal plants), are approved for use in officinal medicine. The efficacy of these species was confirmed in several in vivo experiments and clinical trials. According to modern regulatory rules, additional experiments and clinical trials are required for more detailed investigations of the mechanisms of action and confirmation of efficacy. Conclusion: We believe that the scientifically based utilization of rich plant resources and knowledge of Russian herbal medicine can significantly contribute to the local economy as well as to the sectors seeking natural healing products.

Identification of phytochemicals from North African plants for treating Alzheimer's diseases and of their molecular targets by in silico network pharmacology approach

BACKGROUND

The global social expenses of Alzheimer's disease (AD) have been increased to US$1 trillion due to high cost, side-effects, and low efficiency of the current AD-therapies. Another reason is the lack of preventive drugs and the low-income situation of Asian and African countries. Accordingly, patients rather prefer traditional herbal remedies. Network-pharmacology has been a well-established method for the visualization and the construction of disorder target protein-drug framework. This could aid in the identification of drugs molecular-mechanisms.

AIM

The aim of this study is to investigate the phytochemical constituents that could target Alzheimer's disease from the North African plants. This could be done by exploring their possible mechanisms of action through molecular network pharmacology-based approach.

EXPERIMENTAL PROCEDURE

The Phytochemical-compounds of North-African plants (NAP) have been accessed from open-databank. ADME-screening has been conducted for filtering of the NAP phytochemical-constituents utilizing Qikprop-software. The open STITCH databank has been utilized for the prediction of the phytochemical-constituents target-proteins; UniProt and TDD-DB databanks have been utilized for distinguishing AD-related proteins. Phytochemical constituent-target protein (C-T) and plant-phytochemical constituent-target protein (P-C-T) frameworks have been assembled utilizing Cytoscape to interpret the anti-Alzheimer's disease mechanism of action of the targeted phytochemical constituents.

RESULTS

The NAP 6842 phytochemical-constituents (from more than 1000 plants) have been exposed to ADME and CNS modulating filtration, generating 94 phytochemical-constituents which have been subjected to target-prediction investigation. The 94 phytochemical-constituents and the 4 AD-identified targets have been associated through 155 edges which formed the main pathways related to AD. Cuparene, alpha-selinene, beta-sesquiphellandrene, calamenene, 2-4-dimethylheptane, undecane, n-tetradecane, hexadecane, nonadecane, n-eicosane, and heneicosane have had C-T network highest combined-score, whilst the proteins MAO-B, HMG-CoA, BACE1, and GCR have been the most enriched ones by comprising the uppermost combined-scores of C-T. Hypericum perforatum, Piper nigrum, Juniperus communis, Levisticum officinale, Origanum vulgare acquired the uppermost number of P-C-Target interactions.

CONCLUSION

The phytochemical-targets prediction of NAP utilizing molecular-network pharmacology-based investigation has paved the way for networking multi-target, multi-constituent, and multi-pathway mechanisms. This may introduce potential future targets for the regulation and the management of Alzheimer's disease.

TAXONOMY CLASSIFICATION BY EVISE

Alzheimer's disease, Network pharmacology, In-silico computer based approach.

Anti-Lung Cancer Targets of Radix Paeoniae Rubra and Biological Molecular Mechanism: Network Pharmacological Analyses and Experimental Validation

Objective

To systematically explore the pharmacological mechanism of Radix Paeoniae Rubra (RPR) against lung cancer (LC).

Methods

A network pharmacology approach, which involves active ingredients and target forecast, network construction, gene ontology and pathway enrichment, was employed in this research. In addition, the effect of Baicalein (BAI) in RPR on A549 cells was researched in vitro and in vivo.

Results

A total of 159 targets of the 29 active components in RPR were procured by pharmacokinetic parameters. The network analysis showed that β-sitosterol, baicalein, (+)-catechin, ellagic acid, stigmasterol, (2R, 3R)-4-methoxyl-distylin were the main ingredients and JUN, VEGFA, BCL2 were the hub targets of RPR in the treatment of LC. The functional enrichment analysis showed that RPR likely was useful to LC by regulating numerous pathways including Pathways in cancer, MAPK signaling pathway and so on. MTT results showed that 100μM, 200μM, 400μM of BAI had a time and dose-dependent inhibitory effect on A549 cells proliferation; Wound healing and transwell assays showed that 100μM, 200μM, 400μM of BAI could significantly restrain the migration and invasion of A549 cells; Flow cytometry assay results showed that 100μM, 200μM, 400μM of BAI could induce apoptosis of A549 cells. In vivo, BAI (50, 100 mg/kg) significantly inhibited tumor growth and promoted apoptosis of tumor cells compared with the control group.

Conclusion

BAI in RPR may exert anti-tumor effects by inhibiting the proliferation, migration and invasion of LC cells, and inducing the apoptosis of LC cells.

Prediction of Targets of Curculigoside A in Osteoporosis and Rheumatoid Arthritis Using Network Pharmacology and Experimental Verification

Purpose

Network pharmacology is considered to be the next-generation drug development model that uses bioinformatics to predict and identify multiple drug targets and interactions in diseases. Here, network pharmacology was used to investigate the mechanism by which Curculigoside A (CA) acts in rheumatoid arthritis (RA) and osteoporosis.

Methods

First, TCMSP and SwissADME were applied to predict the druggability of CA. Then, potential targets were identified from overlapping data in SwissTarget and TargetNet, and targets were analyzed using Genemania and DAVID6.8 to obtain information about the GO and KEGG pathways. Ultimately, the drug-target-pathway network was identified after using Cytoscape 3.0 for visualization. Besides, qPCR was used to validate the predicted five major genes targets (EGFR, MAP2K1, MMP2, FGFR1, and MCL1).

Results

The results of TCMSP and SwissADME demonstrated that CA exhibits good druggability; 26 potential protein targets were classified by SwissTarget and TargetNet. The results of Genemania and DAVID6.8 indicated that CA probably caused anti-osteoporosis and anti-RA effects by regulating some biological pathways, especially nitrogen metabolism, estrogen signaling pathway, Rap1 signaling pathway, and PI3K/Akt signaling pathway. Besides, the result of Cytoscape 3.0 showed that the 26 targets participate in osteoporosis and RA-related pathways, metabolism, and other physiological processes. In vitro induced inflammation cell model experiments, the qPCR results showed that CA pretreatment significantly decreased the expression of EGFR, MAP2K1, MMP2, FGFR1, and MCL1 genes.

Conclusion

These results suggested that network pharmacology may provide possible mechanism of how CA exerts therapeutic effects in osteoporosis and RA.

Systems Pharmacology Dissection of Mechanisms of Dengzhan Xixin Injection against Cardiovascular Diseases

Dengzhan Xixin injection (DZXXI), a herbal product prepared from a Chinese herb called Erigeron breviscapus, is a classical and traditional therapeutic for cadiovascular diseases (CVDs), including coronary heart disease (CHD), angina, and stroke, etc. However, its potential pharmacology mechanism against CVDs remains unclear. In this paper, a systems pharmacology-based strategy is presented for predicting drug targets and understanding therapeutic mechanisms of DZXXI against CVDs. The main ingredients were identified by HPLC-diode array detector (DAD). The target fishing was performed on the PharmMapper Server (http://lilab-ecust.cn/pharmmapper/). Potential targets were confirmed by two molecular docking tools, Sybyl-X 1.3 and Ledock to ensure the accuracy. The resulting target proteins were applied as baits to fish their related diseases and pathways from the molecular annotation system (MAS 3.0, http://bioinfo.capitalbio.com/mas3/) and Kyoto Encyclopedia of Genes and Genomes (KEGG) database (http://www.genome.jp/kegg/). Network generation and topological analysis were performed in Cytoscape 3.6.0. 15 main ingredients from DZXXI were identified. Forty five putative drug targets and 50 KEGG pathways, which have highly relevance to the therapeutic effects of DZXXI against CVDs, were then obtained. The systems analysis suggested that DZXXI could attenuate cardiac fibrosis, regulate cardiac contractility, and preserve heart function in adverse cardiac remodeling; meanwhile DZXXI also could have the function of activating blood circulation and dilating blood vessels. DZXXI exerts its therapeutic effects on CVDs possibly through multi-targets including CMA1, epidermal growth factor receptor (EGFR), phenylalanine-4-hydroxylase (PAH), SRC, F7, etc., and multi-pathways including Focal adhesion, mitogen-activated protein kinase (MAPK) signaling pathway, complement and coagulation cascades, Wnt signaling pathway, vascular endothelial growth factor (VEGF) signaling pathway, Renin-angiotensin system, etc.

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

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

Puerarin-loaded ultrasound microbubble contrast agent used as sonodynamic therapy for diabetic cardiomyopathy rats

In this study, a puerarin-loaded ultrasound sulfur hexafluoride microbubble contrast agent as a sonodynamic therapy (SDT) was developed to improve targeted drug delivery and pharmacodynamic effects in diabetic cardiomyopathy (DCM) treatment. Fluorescence microscope morphology was applied to confirm the fabrication of the puerarin - microbubbles (PMBs). The average size distribution and zeta potential of PMBs were 760.0 ± 101.2 nm and -20.4 ± 6.59 mV, respectively. In vitro and in vivo experiments were carried out to study the pharmacodynamic effects and targeted drug delivery of PMBs. The cytotoxicity, assessed by the cell viability of human umbilical vein endothelial cells (HUVECs), showed that the microbubbles were nontoxic even in high concentration of 2.500 mg/mL, and the wound healing scratch assay proved that PMBs cloud obviously improve the migration ability of HUVECs. Furthermore, streptozotocin (STZ) accompanied with high-energy diets was employed to build the DCM rat model. The blood glucose, histological changes of the pancreas and heart, and cardiac function were used to confirm the obtainment of the DCM rat model. Histological and physiological changes of the PMBs treatment group indicated that PMBs had a significant therapeutic efficacy when compared to the DCM model group. Therefore, PMBs are a promising strategy for a targeted drug delivery system and a novel noninvasive treatment for DCM.

Revealing synergistic mechanism of multiple components in Stauntonia brachyanthera Hand.-Mazz. for gout by virtual screening and system pharmacological approach

Stauntonia brachyanthera Hand.-Mazz. (SB), reported as a traditional Chinese medicine, displays a wide spectrum of interesting bioactivities, such as anti-inflammatory and analgesia. It is noteworthy that anti-gout effects of the components in SB have been reported. Hence, this study contributes to the prediction of promising active compounds and mechanisms for the treatment of gout. The active compounds with better oral bioavailability, and drug-likeness of SB were selected for further investigation by the approach of network pharmacology, molecular docking, gene ontology (GO) analysis, and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis, respectively. A total of 34 predicted targets and 98 compounds in SB were obtained. Sorted by structure types of compounds, phenylethanoid glycosides exhibited the best anti-gout activity, followed by phenolics and flavonoids. What's more, it was shown in the network analysis that Serine/threonine-protein kinase mTOR (mTOR), Mitogen-activated protein kinase 12 (MAPK12), tumor necrosis factor (TNF-α), Integrin alpha-4 (ITGA4) and Phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit gamma (PIK3CG) were the key targets with intensely interaction, which should be attached more attention for further study. The functional enrichment analysis indicated that SB probably produced the anti-gout effects by synergistically regulating many biological pathways, such as MAPK signaling pathway, PI3K-Akt signaling pathway, Toll-like receptor signaling pathway and NOD-like receptor signaling pathway, etc. In addition, C61, C67, C68 and C81 might be promising leading compounds with good molecular docking score. As a consequence, the active constituents and mechanisms based on data analysis were holistically illuminated, which was of vital importance to the development of new drugs for gout.

Lupenone is a good anti-inflammatory compound based on the network pharmacology

The dried rhizome of Musa basjoo Sieb. et Zucc. is Rhizoma Musae. It has been used to treat diabetes in Miao medicine in China. Lupenone was isolated from Rhizoma Musae and has good anti-diabetic activity. Its mechanism of action is unclear. Diabetes is a chronic low-level systemic inflammatory disease, and lupenone has anti-inflammatory activity, but the underlying mechanism is not fully elucidated. In this study, we aimed to construct the drug-target biologic network and predict the anti-inflammatory mechanism of lupenone. The network-based pharmacologic analysis platform was used to identify the target proteins related to inflammation. Furthermore, the effects of lupenone on acute, subacute and diabetic pancreatic inflammation were evaluated. The "component-target-disease" network was constructed using Cytoscape. Lupenone could regulate transcription factor p65, NF-kappa-B inhibitor alpha, transcription factor AP-1, NF-kappa-B essential modulator, nuclear factor NF-kappa-B p105 subunit, epidermal growth factor receptor, hypoxia-inducible factor 1-alpha and other proteins related to the PI3K-Akt, Toll-like receptor and NF-kappa B signaling pathways. In addition, lupenone significantly decreased acute and subacute inflammation in mice as well as the IL-1β and IFN-γ levels in the pancreas of diabetic rats. The above results provide strong support for studying the molecular mechanism of lupenone in the treatment of diabetes from the perspective of anti-inflammation.

Network pharmacology and RNA sequencing studies on triterpenoid saponins from Bupleurum chinense for the treatment of breast cancer

Breast cancer remains the most commonly diagnosed malignancy among women, which is frequently associated with adverse side-effects and high metastasis. Bupleurum chinense DC. has been empirically and extensively used as the core prescription for more than half of Chinese formulations for the adjuvant therapy of breast cancer, and its biological activity against breast cancer has been proven by both in vitro and in vivo experiments. Saikosaponin compounds are the characteristic constituent of B. chinense, which exhibit significant cytotoxicity toward several cancer cells. However, the specific mechanisms of these compounds in the treatment of breast cancer have not been comprehensively understood. Therefore, we aimed to determine more potentially therapeutic targets and investigate the biological mechanisms of B. chinense. In the present study, we adopted network pharmacology and bioinformatics analysis to facilitate this requirement. Consequently, the network analysis revealed that saikosaponin-f (39), saikosaponin-d (14), saikosaponin-c (26), saikosaponin-h (54), saikosaponin-g (41), 3′′,6′′-O-diacetylsaikosaponin-d (20), 11α-methoxy-saikosaponin-f (40), and 6′′-O-acetylsaikosaponin-b₁ (48) might play important roles in the treatment of breast cancer. In addition, the apoptosis regulator Bcl-2 (BCL-2), C-X-C chemokine receptor type 4 (CXCR4), probable ATP-dependent RNA helicase DDX5 (DDX5), protein kinase C alpha (PRKCA), and proto-oncogene tyrosine-protein kinase Src (SRC) were the potential therapeutic targets that exhibited intense interactions. Mechanistically, a gene enrichment analysis revealed that the action of B. chinense against breast cancer was achieved by the regulation of several biological signaling pathways, such as pathways in cancer, PI3K-Akt signaling pathway, EGFR tyrosine kinase inhibitor resistance, microRNAs in cancer, etc. More importantly, we verified that the predictions involving saikosaponin-d by the cytotoxicity assay, apoptosis analysis, and RNA sequencing methods were partly consistent with those obtained from the network pharmacology prediction.

The network pharmacology and RNA sequencing studies were used to explore potential therapeutic targets and biological mechanisms of B. chinense for the treatment of breast cancer.