Traditional Chinese Medicine Systems Pharmacology Database And Analysis Platform Research Articles

Study on mechanism of Rehmanniae Radix Praeparata for treatment of osteoarthritis based on network pharmacology and molecular docking

The mechanism of Rehmanniae Radix Praeparata against osteoarthritis was investigated based on network pharmacology, molecular docking, and in vitro experiments in the present study. Osteoclast models were established via receptor activator of nuclear factor-κB ligand(RANKL) and macrophage colony-stimulating factor(M-CSF) inducing RAW264.7 cells. Further, the influence of Rehmanniae Radix Praeparata on the activity of tartrate-resistant acid phosphatase(TRAP) was evaluated and the efficacy of Rehmanniae Radix Praeparata in the treatment of osteoarthritis was verified. The active components of Rehmanniae Radix Praeparata were obtained from Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP) and literature, and the potential targets of the components were collected from SwissTargetPrediction. Osteoarthritis disease targets were searched in Online Mendelian Inheritance in Man(OMIM), Therapeutic Target Database(TTD), GeneCards, and DisGeNET. The intersection targets of Rehmanniae Radix Praeparata and osteoarthritis were obtained by Venny platform. The protein-protein interaction(PPI) network was constructed by Cytoscape 3.8.2, and key targets were obtained based on topology algorithm. The Database for Annotation, Visualization and Integrated Discovery(DAVID) was used to perform Gene Ontology(GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analysis. Finally, the mRNA expression of the key targets was determined by RT-qPCR and the binding activity between the components and key targets was validated by molecular docking. The results showed that Rehmanniae Radix Prae-parata inhibited the TRAP activity, thus inhibiting bone resorption by osteoclasts and treating osteoarthritis. By network pharmacology, 14 active components of Rehmanniae Radix Praeparata and 126 intersection targets were obtained. The network pharmacology enrichment results revealed 432 biological processes and 139 signaling pathways. Key targets such as proto-oncogene tyrosine-protein kinase Src(SRC), signal transducer and activator of transcription 3(STAT3) and transcription factor p65(RELA) were obtained according to the degree in topological analysis. SRC was highly expressed in osteoclasts, which accelerated the development of osteoarthritis. Therefore, SRC was selected for subsequent verification, and Rehmanniae Radix Praeparata decreased the gene expression level of SRC. The molecular docking showed that acteoside, isoacteoside, raffinose had good bonding activity with SRC, suggesting that they might be the critical components in treating osteoarthritis. In conclusion, Rehmanniae Radix Praeparata can inhibit bone resorption by osteoclasts and balance the metabolism of articular cartilage and subchondral bone via acting on SRC, thus playing a therapeutic role in osteoarthritis. In addition, Rehmanniae Radix Praeparata may exert overall efficacy on osteoarthritis through other targets such as STAT3 and RELA, and other related pathways such as PI3 K-AKT and IL-17 signaling pathways.

Hedysarum multijugum Maxim treats ulcerative colitis through the PI3K-AKT and TNF signaling pathway according to network pharmacology and molecular docking.

Ulcerative colitis (UC) is a chronic inflammatory bowel disease (IBD) that prevails mainly in western countries. Due to the unknown etiology of UC, the purpose of treatments has predominantly comprised symptomatic and pain relief. With extensive research focusing on the pathogenesis of UC, various novel treatments have emerged, although their efficiency has remained unsatisfactory. Hedysarum multijugum Maxim (HMM), a crucial constituent of traditional Chinese medicine, has a broad application in many diseases and has been found beneficial for UC patients. In this study, network pharmacology and molecular docking analyses were applied to explore the potential mechanism of HMM treating UC. Active ingredients of HMM and target genes were acquired from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). UC-related genes were obtained from three disease databases. Common genes were selected from these two gene sets, and a compound-genes network was drawn by Cytoscape. Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO) enrichment, and protein-protein interaction (PPI) analyses were performed to identify the essential pathways and proteins in UC. A total of 121 genes were found related to UC and targeted by HMM. The GO and KEGG analyses showed that these genes were associated with inflammation and immune signaling pathways and inflammation-related biological processes (BP) such as the tumor necrosis factor (TNF) and PI3K-AKT signaling pathways. Four active ingredients (quercetin, kaempferol, formononetin, and isorhamnetin) and five genes (RELA, MAPK14, MAPK1, JUN, AKT1) were reserved after screening. Molecular docking further showed that the receptor had a high binding affinity with HMM active ingredients. This study revealed that HMM treats UC through four active ingredients (quercetin, kaempferol, formononetin, and isorhamnetin) targeting five hub genes (RELA, MAPK14, MAPK1, JUN, AKT1) by regulating the PI3K-AKT1 and TNF signaling pathways.

Network pharmacology-based screening of the active ingredients and mechanisms of evodiae fructus anti-glioblastoma multiforme.

Background:Evodiae fructus has been shown to have anti-glioblastoma multiforme (GBM) effects. However, its anti-GBM active components and mechanism remain unclear. In this study, the active components of evodiae fructus were screened by network pharmacology to explore the possible molecular mechanism of resistance to GBM.Materials and methods:The main active ingredients of evodiae fructus were derived from Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and Batch-traditional Chinese medicine (TCM). TCMSP and Swiss absorption, distribution, metabolism and elimination (ADME) predict genetic targets for ingredients that meet pharmacological criteria. GBM-related targets were obtained from DisGeNet, GeneCards, Online Mendelian Inheritance in Man (OMIM), Therapeutic Target Database (TTD), and TCGA. A Venn diagram was used to obtain the common targets of evodiae fructus and GBM. Protein–protein interaction (PPI) networks and component-disease target networks were constructed using Cytoscape 3.8.1 software for visualization. GBM gene differential expression was visualized by VolcaNoseR, and potential targets were enriched by Gene Ontology (GO) function and annotated by the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway by SRplot. Molecular docking verification was conducted using AutoDock Vina software.Results:According to the screening conditions, 24 active components and 80 drug targets were obtained. The PPI network contains 80 proteins. The molecular docking verification showed the molecular docking affinity of the core active compounds in evodiae fructus with CASP3, JUN, EGFR, and AKT1.Conclusions:This study preliminarily identified the various molecular targets and multiple pathways of evodiae fructus against GBM.

Mechanism of Glycitein in the Treatment of Colon Cancer Based on Network Pharmacology and Molecular Docking

Introduction: The prevalence of colon cancer remains high across the world. The early diagnosis of colon cancer is challenging. Moreover, patients with colon cancer frequently suffer from poor prognoses. Methods: Differentially expressed genes (DEGs) in colon cancer were acquired based on TCGA-COAD dataset screening. DEGs were input into the Connectivity Map (CMap) database to screen small molecule compounds with the potential to reverse colon cancer pathological function. Glycitein ranked first among the screened small-molecule compounds. We downloaded the main targets of glycitein from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) database and constructed protein-protein interaction (PPI) networks of those which were closely related to targets by the Search Tool for the Retrieval of Interaction Gene/Proteins (STRING). Five potential targets of glycitein for treating colon cancer were identified (CCNA2, ESR1, ESR2, MAPK14, and PTGS2). These targets were used as seeds for random walk with restart (RWR) analysis of PPI networks. Then, the interaction network of glycitein-colon cancer-related genes was constructed based on the top 50 genes in affinity coefficients. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted on the potential genes targeted by glycitein in colon cancer treatment and those that were closely bound up with targets. Results: GO analysis demonstrated that the enrichment of these genes was primarily discovered in biological functions including regulation of fibroblast proliferation, response to oxygen levels, and epithelial cell proliferation. The KEGG analysis results illustrated that the signaling pathways where these genes were mostly involved consisted of the mitogen-activated protein kinase signaling pathway, the phosphatidylinositol-3-kinase-Akt signaling pathway, and the p53 signaling pathway. Finally, stable binding of glycitein to five potential targets in colon cancer was verified by molecular docking. Conclusion: This study elucidated the key targets and main pathways of glycitein on the basis of network pharmacology and preliminarily analyzed molecular mechanisms in the treatment of colon cancer. A scientific basis is provided for glycitein application in treating colon cancer.

Network Pharmacology-Based Study on the Active Ingredients and Mechanism of Pan Ji Sheng Traditional Chinese Medicine Formula in the Treatment of Inflammation

Background Pan Ji Sheng Formula is a Chinese medicine formula that enables heat-free detoxification as well as anti-inflammatory and immune-boosting properties. This formula contains eight herbs. Its underlying mechanism is unknown. The bioactive ingredients were screened in our work, and the mechanism of this formula was investigated. Methods Using traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP), ingredients in Pan Ji Sheng Chinese medicine formula were screened, and we selected the main bioactive ingredients for web-based research. The targets of bioactive ingredients are primarily obtained from the SwissTargetPrediction and TCMSP databases, and the text mining method is used. STRING and Cytoscape were then used to examine the protein-protein interaction (PPI) networks. To explore the biological function and related pathways, functional annotation and pathway analysis were performed. Results This research discovered 96 bioactive ingredients. Then, 215 potential targets of bioactive ingredients were screened. Through the analysis of the PPI network, we discovered 25 key target genes, which can be described as hub target genes regulated by bioactive ingredients. Bioactive ingredients primarily regulate CASP3, AKT1, JUN, and other proteins. The formula works synergistically to enhance immune response and antiinfection by regulating immune-related pathways, TNF signaling pathways, and apoptosis. Conclusions A variety of bioactive ingredients in the formula could play roles in regulating CASP3, AKT1, and other genes in immune, infection, apoptosis, and tumor-related signaling pathways. Our data point the way forward for future studies on the mechanism of action of this formula.

Exploring the Ferroptosis Mechanism of Zhilong Huoxue Tongyu Capsule for the Treatment of Intracerebral Hemorrhage Based on Network Pharmacology and In Vivo Validation.

Objective The purpose of this study is to explore the mechanism of the Zhilong Huoxue Tongyu (ZL) capsule in the treatment of intracerebral hemorrhage (ICH) via targeting ferroptosis based on network pharmacology. Methods The active ingredients and related key targets of the ZL capsule were screened using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). The gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were also performed. Finally, identified targets were validated in an in-vivo model of ICH. Results A total of 30 active ingredients and 33 intersecting targets were identified through a TCMSP database search. Ingredients-Targets-Pathways network was constructed to filter out the key targets according to the degree value. TP53 was selected as the key target. The in-vivo validation studies demonstrated that TP53 was down-regulated and GPX4 was upregulated in rats following ZL capsule treatment. Conclusions It is concluded that the ZL capsule could alleviate ICH in a muti-target and multi-pathway manner. ZL capsule could alleviate ICH by inhibiting ferroptosis, and TP53 is identified to be the potential target. Further research is needed to clarify the detailed anti-ferroptotic mechanism of the ZL capsule.

Systems Network Pharmacology-Based Prediction and Analysis of Potential Targets and Pharmacological Mechanism of Actinidia chinensis Planch. Root Extract for Application in Hepatocellular Carcinoma.

Purpose Traditional Chinese medicine (TCM) sometimes plays a crucial role in advanced cancer treatment. Despite the significant therapeutic efficacy in hepatocellular carcinoma (HCC) that Actinidia chinensis Planch root extract (acRoots) has proven, its complex composition and underlying mechanism have not been fully elucidated. Therefore, this study analyzed the multiple chemical compounds in acRoots and their targets via network pharmacology and bioinformatics analysis, with the overarching goal of revealing the potential mechanisms of the anti-HCC effect. Methods The main ingredients contained in acRoots were initially screened from the traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), and the candidate bioactive ingredient targets were identified using DrugBank and the UniProt public databases. Second, the biological processes of the targets of active molecules filtered from the ingredients of acRoots were evaluated using gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Third, weighted gene coexpression network analysis (WGCNA) was performed to identify gene coexpression modules associated with HCC. The hub genes of acRoots in HCC were defined via contrasting the above module eigengenes with candidate target genes of acRoots. Furthermore, the target-pathway network was analyzed to explore the mechanism for anti-HCC effect of hub genes. Kaplan–Meier plotter database analysis was performed to validate the hub genes of acRoots correlation with prognostic values in HCC. In order to verify the results of the network pharmacological analysis, we performed a molecular docking approach on the active ingredients and key targets using the Discovery Studio software. The viability of SMMC-7721 and HL-7702 cells was determined by Cell counting kit-8 (CCK-8) after being treated with different concentrations of (+)-catechin (0, 50, 100, 150, 200, and 250 g/ml) for 24, 48, and 72 hours, respectively. Finally, qRT-PCR and Western blot involving human hepatocarcinoma cells were utilized to verify the impact of (+)-catechin on the hub genes associated with prognosis. Results 6 out of 26 active ingredients extracted from TCMSP were deemed as the core ingredients of acRoots. 175 bioactive-ingredient targets of acRoots were obtained and a bioactive-ingredient targets network was established correspondingly. The biological processes (BP) of target genes mainly involved processes, such as toxic substance and wounding. The results of KEGG pathways indicated that the target genes were mainly enriched in pathways in cancer, AGE-RAGE signaling pathway in diabetic complications, IL-17 signaling pathway, and other pathways. Also, the two hub genes (i.e., ESR1 and CAT) were closely associated with the prognosis of HCC patients. As a consequence, we predicated a series of signaling pathways, including estrogen signaling pathway and longevity regulation pathway, through which acRoots could facilitate the treatment for HCC. The molecular docking experiment ascertained that ESR1 and CAT had an effective binding force with (+)-catechin, one of the core ingredients of acRoots. Furthermore, (+)-catechin inhibited SMMC-7721 cell growth in a dose-dependent manner and a time-dependent manner. Finally, we suggest that the expression level of ESR1 and CAT is positively related to the (+)-catechin concentrations in in-vitro experiments. Conclusion The bioactive ingredients of acRoots, including quercetin, (+)-catechin, beta-sitosterol, and aloe-emodin, have synergistic interactions in reinforcing the anticancer effect in HCC. Evidently, acRoots took effect by regulating multitargets and multipathways through its active ingredients. Further, (+)-catechin, the possible paramount anti-HCC active ingredient in acRoots, helped improve the prognosis of HCC patients by increasing the expression of ESR1 and CAT. Additionally, the findings yielded provide a conceptual guidance for the clinical treatment of HCC and the methods adopted are potentially applicable in the future comprehensive analysis of the underlying mechanisms of TCMs.

Identification of Interleukin-1-Beta Inhibitors in Gouty Arthritis Using an Integrated Approach Based on Network Pharmacology, Molecular Docking, and Cell Experiments.

Background This study aimed to investigate the molecular mechanism of Tongfengding capsule (TFDC) in treating immune-inflammatory diseases of gouty arthritis (GA) and interleukin-1-beta (IL-1β) inhibitors by using network pharmacology, molecular docking, and cell experiments. Methods In this study, the compounds of TFDC and the potential inflammatory targets of GA were obtained from Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), Online Mendelian Inheritance in Man (OMIM), and GeneCards databases. The TFDC-GA-potential targets interaction network was accomplished by the STRING database. The TFDC-active compound-potential target-GA network was constructed using Cytoscape software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were used to further explore the GA mechanism and therapeutic effects of TFDC. Quantitative real-time PCR (qPCR) was used to verify whether the TFDC inhibited IL-1β in GA. Molecular docking technology was used to analyze the optimal effective compounds from the TFDC for docking with IL-1β. Result 133 active compounds and 242 targets were screened from the TFDC, and 25 of the targets intersected with GA inflammatory targets, which were considered as potential therapeutic targets. Network pharmacological analysis showed that the TFDC active compounds such as quercetin, stigmasterol, betavulgarin, rutaecarpine, naringenin, dihydrochelerythrine, and dihydrosanguinarine had better correlation with GA inflammatory targets such as PTGS2, PTGS1, NOS2, SLC6A3, HTR3A, PPARG, MAPK14, RELA, MMP9, and MMP2. The immune-inflammatory signaling pathways of the active compounds for treating GA are IL-17 signaling pathway, TNF signaling pathway, NOD-like receptor signaling pathway, NF-kappa B signaling pathway, Toll-like receptor signaling pathway, HIF-1 signaling pathway, etc. The TFDC reduced IL-1β mRNA expression in GA by qPCR. Molecular docking results suggested that rutaecarpine was the most appropriate natural IL-1β inhibitor. Conclusion Our findings provide an essential role and bases for further immune-inflammatory studies on the molecular mechanisms of TFDC and IL-1β inhibitors development in GA.

Investigation into the potential mechanism and molecular targets of Fufang Xueshuantong capsule for the treatment of ischemic stroke based on network pharmacology and molecular docking.

Fufang Xueshuantong (FFXST) capsule is a traditional Chinese medicine (TCM) preparation used to activate blood circulation, resolve stasis, benefit qi, and nourish yin in clinical practice. However, its potential mechanism and molecular targets after ischemic stroke (IS) have not been investigated. The aim of this research was to investigate the molecular mechanisms of FFXST in the treatment of IS based on network pharmacology and molecular docking. We used the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) to collect candidate compounds of four herbs in FFXST; disease-related differential genes were screened using the Gene Expression Omnibus (GEO) database, and a compound–disease network was created using Cytoscape 3.8.2 software. The topological analysis of the protein–protein interaction (PPI) network was then created to determine the candidate targets of FFXST against IS. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted using the clusterProfiler package in R. The gene–pathway network of FFXST against IS was created to obtain the key target genes. Molecular docking was used to validate the core targets using AutoDock Vina 1.1.2. A total of 455 candidate compounds of FFXST and 18,544 disease-related differential genes were screened. Among them, FFXST targets for IS treatment had 67 active compounds and 10 targets in the PPI network related to STAT1, STAT3, and HIF1A. The biological processes of GO analysis included the regulation of reactive oxygen species metabolic process, cellular response to chemical stress, regulation of angiogenesis, regulation of vasculature development, positive regulation of cytokine production, and response to oxidative stress. The KEGG enrichment analysis showed that Kaposi sarcoma-associated herpesvirus infection, microRNAs in the cancer signaling pathway, Th17 cell differentiation, and HIF-1 signaling pathway were significantly enriched. The network pharmacology outcomes were further verified by molecular docking. We demonstrated that FFXST protection against IS may relate to the regulation of oxidative stress, immune inflammatory response, and angiogenesis through the relevant signaling pathways. Our study systematically illustrated the application of network pharmacology and molecular docking in evaluating characteristics of multi-component, multi-target, and multi-pathway of FFXST for IS.

Pharmacological effects of the Cassia Seed on atherosclerosis: A meta-analysis based on network pharmacology.

The aim of this study was to shed light on the active ingredients and potential targets of Cassia Seed about anti-atherosclerosis based on network pharmacology. The active ingredients and potential targets of Cassia Seed were obtained from traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP) and SwissTargetPrediction database. Then, atherosclerosis-related targets were screened via GeneCards, online mendelian inheritance in man, therapeutic target database and DrugBank database. The common targets and protein-protein interaction (PPI) network was later identified and built. Furthermore, we used the database for annotation, visualization and integrated discovery (DAVID) database server to accomplish the enrichment analysis. The compounds-targets-pathways network was ultimately constructed by Cytoscape. A total of 14 active ingredients and 475 related targets were sifted from Cassia Seed. Among 574 potential atherosclerotic targets, there were 99 targets overlapped with those of Cassia Seed. Topological analysis with Cytoscape revealed that proto-oncogene tyrosine-protein kinase proto-oncogene tyrosine-protein kinase Src, transcription factor AP-1 (JUN), mitogen-activated protein kinase 8 (MAPK8), mitogen-activated protein kinase 14 (MAPK14) and catenin beta-1 were considered as the hub gene. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis suggested that the Cassia Seed had the potential to influence varieties of biological processes and pathways, including positive regulation of smooth muscle cell proliferation, inflammatory response, tumor necrosis factor (TNF) signaling pathway, vascular endothelial growth factor (VEGF) signaling pathway and arachidonic acid (ARA) metabolism. Taken together, our findings support that anti-atherosclerosis effects of Cassia Seed are characterized by multi-component, multi-target and multi-path mechanism of action.

Molecular Mechanism of YuPingFeng in the Treatment of Asthma Based on Network Pharmacology and Molecular Docking Technology.

Objective To explore the molecular targets and mechanism of YuPingFeng (YPF) for the treatment of asthma by using network pharmacology and molecular docking. Methods The potential active ingredients and relevant targets of YPF were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). Asthma-related gene targets were retrieved from GeneCards, OMIM, DrugBank, PharmGKB, and TTD databases. The protein-protein (PPI) network between YPF and asthma common targets was constructed by SRING online database and Cytoscape software. GO and KEGG analyses were performed to explore the complicated molecular biological processes and potential pathways. Finally, a molecular docking approach was carried out to verify the results. Results We obtained 100 potential targets of the 35 active ingredients in YPF and 1610 asthma-related targets. 60 YPF-asthma common targets were selected to perform PPI analysis. Seven core genes were screened based on two topological calculation methods. GO and KEGG results showed that the main pathways of YPF in treating asthma include TNF signaling pathway and PI3K-Akt signaling pathway. Finally, the molecular docking results indicated that the key ingredients of YPF had a good affinity with the relevant core genes. Conclusion This study reflects the multicomponent, multitarget, and multipathway characteristics of YPF in treating asthma, providing a theoretical and scientific basis for the intervention of asthma by traditional Chinese medicine YPF.

Active Compounds Screening and Hepatoprotective Mechanism of Shuganning Injection Based on Network Pharmacology and Experimental Validation

Objective: The study aimed to analyze the core active compounds and the potential mechanism of Shuganning injection (SGNI) through network pharmacology with biological experiments. Methods: Active compounds and targets of SGNI were screened from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and Targetnet database, whereas the liver disease-related targets were identified through the Genecards and Online Mendelian Inheritance in Man databases. The “compound-target” and “protein-protein interaction” networks construction, core target identification, and pathway enrichment were then performed. Finally, the exploration of the mechanism of action for SGNI against acetaminophen (APAP)-induced liver injury in the HepaRG cells and validation of three identified protein targets was also carried out through western blot assay, including tumor protein p53 (p53, TP53), transcription factor Jun (Jun), and Caspase 3 (CASP3). Results: The result showed that a total of 312 active compounds of SGNI and 408 liver disease-related targets, as well as 131 core targets were revealed through databases, such as prostaglandin G/H synthase 1, prostaglandin G/H synthase 2, and nuclear factor NF-kappa B (NF-kB) p65 subunit (RELA). The core targets of SGNI were involved in regulating hepatitis B signaling pathway, NF-kB signaling pathway, Toll-like receptor signaling pathway, and tumor necrosis factor (TNF) signaling pathway. Moreover, results of molecular docking in this study indicated that chlorogenic acid, geniposide, baicalin, indirubin, and ganoderic acid A could act on RELA, JUN, TP53, TNF, CASP3, Caspase 8 (CASP8) and nuclear factor NF-kB p105 subunit (NFKB1). Similarly, results of western blot revealed that SGNI reduced the expression of p53, Jun, and Caspase 3 proteins in HepaRG cells as compared with the APAP group ( P < 0.01 or P < 0.05). Conclusion: The present study verified the therapeutic effects and mechanism of SGNI on liver diseases and pointed out new directions for further research.

Network pharmacology analysis of the mechanism of Huisheng oral liquid in the treatment of lung cancer.

BackgroundTo study the active ingredient and possible mechanism of Huisheng oral liquid in the treatment of lung cancer by network pharmacology.MethodsThe active ingredient and drug targets of Huisheng oral liquid were screened using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and Traditional Chinese Medicine Integrated Database (TCMID), and lung cancer targets were screened using the Gene Expression Omnibus (GEO) database. The drug targets of the effective components of Huisheng oral liquid were matched with disease targets and the obtained intersecting targets were imported into the Search Tool for the Retrieval of Interaction Gene/Proteins (STRING) database to construct a protein-protein interaction (PPI) network. R software and the Kyoto Encyclopedia of Genes and Genomes (KEGG) database were used for Gene Ontology (GO) and KEGG enrichment analyses, and Cytoscape software was used to construct a Huisheng oral liquid component target-lung cancer target network. The function and pathway of the therapeutic target of Huisheng oral liquid for lung cancer were analyzed.ResultsA total of 1,376 differentially expressed genes (DEGs) of lung cancer were obtained, and 185 potential effective components of Huisheng oral liquid in the treatment of lung cancer were obtained, including quercetin, luteolin, kaempferol, and baicalein. There were 36 intersecting targets between Huisheng oral liquid and lung cancer, and the key targets for lung cancer treatment were CDKN1A, CCNB1, MDM2, CDK1, ErbB2, E2F1, EGFR, etc. Huisheng oral liquid mainly regulates the p53 signaling pathway.ConclusionsThe mechanism of Huisheng oral liquid in the treatment of lung cancer is mainly reflected in regulating tumor cell apoptosis, inhibiting angiogenesis, and improving immunity.

Network Pharmacology and Molecular Docking-Based Mechanism Study to Reveal Antihypertensive Effect of Gedan Jiangya Decoction

Primary hypertension is understood as a disease with diverse etiology, a complicated pathological mechanism, and progressive changes. Gedan Jiangya Decoction (GJD), with the patent publication number CN114246896A, was designed to treat primary hypertension. It contains six botanical drugs; however, the underlying mechanism is uncertain. We utilized network pharmacology to predict the active components, targets, and signaling pathways of GJD in the treatment of primary hypertension. We also investigated the potential molecular mechanism using molecular docking and animal experiments. The Traditional Chinese Medicine System Pharmacology Database and Analysis Platform (TCMSP), the Protein Database (UniProt), and a literature review were used to identify the active components and related targets of GJD's pharmacological effects. The GeneCards, Online Mendelian Inheritance in Man (OMIM), Therapeutic Target Database (TTD), and DrugBank databases were utilized to identify hypertension-related targets. Based on a Venn diagram of designed intersection targets, 214 intersection targets were obtained and 35 key targets for the treatment of hypertension were determined using the STRING data platform and Cytoscape software. The Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of key targets revealed that the relevant molecular action pathways of GJD in the treatment of hypertension include the Toll-like receptor, MAPK, PI3K-Akt, and renin-angiotensin signaling pathways. A GJD active ingredient-key target-pathway connection diagram was created using Cytoscape software, and 11 essential active components were selected. Molecular docking was then used to verify the binding activity of key targets and key active ingredients in GJD to treat primary hypertension. The results of this study indicate that AGTR1, AKT1 with puerarin, EDNRA with tanshinone IIA, MAPK14 with daidzein, MAPK8 with ursolic acid, and CHRM2 with cryptotanshinone had high binding activity to the targets with active components, whereas AGTR1 was selected as target genes verified by our experiment. HPLC was utilized to identify the five active ingredients. Experiments in high-salt rats demonstrated that GJD might decrease the expression of AGTR1 in the kidney and thoracic aorta while increasing the expression of eNOS by preventing the activation of the renin-angiotensin pathway, thereby reducing lowering systolic and diastolic blood pressure.

Potential Mechanisms of White Peony against Primary Sjögren's Syndrome Based on Network Pharmacology and Molecular Docking.

Background Multiple system and organ damage occurs with the continuous progression of primary Sjögren's syndrome (pSS), and the lack of specific drugs against this disease is a huge challenge. White peony (WP), a widely used traditional Chinese herb, has been confirmed to have a therapeutic value in pSS. However, the specific mechanisms of WP in the treatment of pSS are unknown. Methods The active ingredients and their targets in WP were searched on the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), and disease-related targets were collected from GeneCards, Online Mendelian Inheritance in Man (OMIM), and the Therapeutic Target Database (TTD). The overlapping targets were acquired by taking the intersection. A protein-protein interaction (PPI) network was structured using the STRING database. A disease-drug-ingredient-target (D-D-I-T) network was built using Cytoscape software. By filtering twice, core targets were acquired. Gene Ontology (GO) and Kyoto Encyclopedia Gene and Genome (KEGG) pathway enrichment analysis were accompanied by R packages. Finally, molecular docking was used to verify the abovementioned results. Results In total, we screened 88 WP-related targets, 1480 pSS-related targets, and 32 overlapping targets. D-D-I-T Network analysis displayed six main active ingredients of WP, which played a significant therapeutic role in pSS. Further topological analysis selected seven core target genes, including IL-6, TNF, PPARγ, AKT1, CASP3, NOS3, and JUN. GO and KEGG analysis were used to elucidate pharmacological mechanisms, mainly acting in the AGE-RAGE signaling pathway. Molecular docking proved that paeoniflorin bound well with core targets. Conclusion Our study revealed that IL-6, TNF, AKT1, CASP3, NOS3, and JUN may be pathogenic target genes, and PPARγ may be a protective target gene. The main active ingredients of WP mainly played a therapeutic role via the AGE-RAGE signaling pathway. These findings provide a fundamental and theoretical basis for the clinical application of WP.

Molecular mechanism analysis of Miao medicine Jinwujiangu decoction in treating osteoarthritis based on a network pharmacology approach.

To investigate molecular mechanisms of Jinwujiangu decoction (, JWJG) in treating osteoarthritis (OA) using network pharmacology analysis. Principal active compounds of JWJG were screened out via the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and BATMAN-TCM, and potential targets for OA treatment were identified through Online Mendelian Inheritance in Man (OMIM) and GeneCards databases. The JWJG network diagrams of both principal chemical compound-action targets and OA treatment target-OA disease were constructed applying the Cytoscape 3.7.2 software. The diagram of protein-protein interaction network was plotted for core analysis. Meanwhile, the common targets and relevant signaling pathways involved in both networks were analyzed using the Gene Ontology function analysis and Kyoto Encyclopedia of Genes and Genomes pathway enrichment. The predicted results were ultimately verified through animal experiments. Effects of JWJG were indicated in acting on key targets interleukin-6, insulin, protein kinase B, glyceraldehyde-3-phosphate dehydrogenase, and mitosis-specific MRE11-RAD50-NBS1 associated protein by regulating signaling pathways of phosphoinositide 3-kinase- protein kinase B, mitogen-activated protein kinases, tumor necrosis factor, and colorectal cancer. Meanwhile, it inhibited the over-activation of signaling pathways and the release of inflammatory factors in OA treatment. Following a signaling pathway analysis utilizing network pharmacology technique, it was demonstrated that JWJG could treat OA through the Wnt/β-catenin signaling pathway verified by animal experiments. The present study preliminarily analyzed the pharmacological mechanism of JWJG in treating OA on a network pharmacology approach and provided a great theoretical significance for clinical application.

Study on the Action Mechanism of the Yifei Jianpi Tongfu Formula in Treatment of Colorectal Cancer Lung Metastasis Based on Network Analysis, Molecular Docking, and Experimental Validation.

Objective The lung is the second most common site of colorectal cancer (CRC) metastasis. This study aims to investigate the therapeutic effects and potential action mechanisms of Yifei Jianpi Tongfu formula (YJTF) in CRC lung metastasis in a comprehensive and systematic way by network analysis, molecular docking, and experimental verification. Methods The main ingredients in YJTF were screened from the Traditional Chinese Medicine System Pharmacology Database and Analysis Platform (TCMSP) and Traditional Chinese Medicine Integrated Database (TCMID), and the disease-related targets from the Online Mendelian Inheritance in Man (OMIM) and GeneCards and the compound-related targets from SwissTargetPrediction were collected. Then, Metascape was used for pathway annotation and enrichment analysis, and meanwhile, a protein-protein interaction (PPI) network was constructed. Molecular docking was carried out to investigate interactions between the active compounds and the potential targets. The in vivo effect of YJTF on CRC lung metastasis was observed in a tail vein injection mouse model. Results A total of 243 active compounds and 81 disease-related targets of YJTF were selected for analysis. The results of multiple network analysis showed that the core targets of YJTF were enriched onto various cancer-related pathways, especially focal adhesion and adherens junction. The results of molecular docking demonstrated that all core compounds (quercetin, kaempferol, luteolin, apigenin, and isorhamnetin) were capable of binding with AKT1, EGFR, SRC, ESR1, and PTGS2. Experimental validation in vivo demonstrated that YJTF combined with oxaliplatin could significantly reduce the number of lung metastases and improve the quality of life in mice. Further research suggested that YJTF inhibited CRC lung metastasis probably by modulating epithelial-to-mesenchymal transition (EMT). Conclusions According to the analysis, YJTF can be considered as an effective adjuvant therapy for CRC lung metastasis.

Mechanism of action of Bu Zhong Yi Qi Decoction in the treatment of chronic fatigue syndrome based on network pharmacology and molecular docking

ObjectiveBu Zhong Yi Qi (BZYQ) decoction is a classic prescription in Chinese history that has an obvious effect on improving fatigue symptoms. The objective was to investigate the substance basis and mechanism of BZYQ in the treatment of chronic fatigue syndrome (CFS) at the molecular level based on network pharmacology and molecular docking technology. MethodThe active components and their targets of Huangqi, Baizhu, Renshen, Gancao, Danggui, Chaihu, Chenpi, Shenma in BZYQ were screened by the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) database and the Encyclopedia of Traditional Chinese Medicine (ETCM). The UniProt database was used to calibrate the target information in BZYQ. CFS target genes were obtained from the GeneCards and DisGeNET databases. Cytoscape 3.7.2 software and the STRING 11.0 database were used to construct a protein–protein interaction (PPI) network and screen core targets. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID) database. Subsequently, the binding affinity of BZYQ with key target receptors was assessed by molecular docking analysis. ResultBZYQ consists of 329 active components, 198 targets, and 6490 CFS-related targets. There were 180 common targets of BZYQ and CFS, including nitric oxide synthase Ⅱ (NOS2), estrogen receptor beta (ESR2), interleukin-2 (IL2), interleukin-6 (IL6), interleukin-1 beta (IL1B), MAP kinase-activated protein kinase 3 (MAPK3), vascular endothelial growth factor A (VEGFA), nitric oxide synthase Ⅲ (NOS3), and matrix metallopeptidase 2 (MMP2). More than 600 GO terms were obtained (Biological Process 630; Cellular Component: 95; Molecular Function:152) and 185 related signaling pathways, involving the AGE-RAGE signaling pathway in diabetic complications, pathways in cancer, TNF signaling pathway, lipid and atherosclerosis, cAMP signaling pathway, VEGF signaling pathway, calcium signaling pathway, and NF-kappa B signaling pathway. ConclusionBZYQ achieves the purpose of treating CFS through the interaction mechanism of multiple components, multiple targets and multiple pathways. It advances the study of BZYQ to the clinical stage, expounds the effective mechanism of Traditional Chinese Medicine from an overall perspective, and provides ideas at the molecular level for future experimental study.

Mechanisms of Qing-Gan Li-Shui Formulation in Ameliorating Primary Open Angle Glaucoma: An Analysis Based on Network Pharmacology.

Objective In this study, we investigated the mechanism of Qing-Gan Li-Shui formulation (QGLSF) in treating primary open glaucoma (POAG) by network pharmacology and in vitro experiments. Methods The active pharmaceutical ingredients (APIs) of GLQSF (prepared with Prunella vulgaris, Kudzu root, Plantago asiatica, and Lycium barbarum) were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and Yet Another Traditional Chinese Medicine database (YATCM). The targets of POAG were screened out with GeneCards, OMIM, PharmGKB, Therapeutic Target Database (TTD), and DrugBank databases. The Venny platform was used to summarize the core targets. Topological analysis was performed using Cytoscape3.8.0. A protein-protein interaction network was plotted by STRING online. The key targets were subjected to GO and KEGG enrichment analyses. Finally, the effects of APIs were verified by a model of chloride hexahydrate (CoCl2)-induced retinal ganglion cells-5 (RGC-5). Results The main APIs were selected as quercetin (Que) by network pharmacology. Nine clusters of QGLSF targets were obtained by the PPI network analysis, including AKT-1, TP53, and JUN. KEGG enrichment analysis showed that these targets were mainly involved in the AGE-RAGE signaling pathway. By in vitro experiments, Que promoted cell proliferation. The secretion of AKT-1, TP53, JUN, AGE, and RAGE in the cell culture supernatant decreased, as shown by ELISA. The mRNA levels of AKT-1, TP53, JUN, and RAGE decreased, as shown by RT-PCR. QGLSF may employ the AGE-RAGE signaling pathway to counter POAG. Conclusion This study preliminarily elucidates the efficacy and mechanism of QGLSF in the treatment of POAG.

Network Pharmacology-Based Investigation on the Mechanism of the JinGuanLan Formula in Treating Acne Vulgaris.

Background JinGuanLan (JGL) formula is a traditional Chinese medicine (TCM) developed by the Department of Pharmacology at the First Hospital of Lanzhou University. The network pharmacology approach was applied to determine the potential active compounds, therapeutic targets, and main pathways of the JGL formula to evaluate its application value in acne vulgaris. Methods Data on the active compounds and their related targets were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). Acne vulgaris-related targets were searched from the Online Mendelian Inheritance in Man (OMIM) database, GeneCards Database, Comparative Toxicogenomics Database (CTD), Therapeutic Target Database (TTD), and DisGeNET Database. Targets intersecting between JGL- and acne vulgaris-related targets were chosen as potential therapeutic targets. The protein-protein interaction (PPI) network of potential therapeutic targets was visualized using Cytoscape software based on the PPI data collected from the STRING database. Three topological features, namely, “Degree,” “MCC,” and “EPC” of each node in the PPI network were calculated using the cytoHubba plugin of Cytoscape to excavate the core targets. R program was used for the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of the potential therapeutic targets. Finally, the compound–target–pathway network was constructed. Result Among the 148 active compounds that were identified, quercetin and kaempferol showed the highest degree of target interaction and thus may play essential roles in the pharmacological effect of the JGL formula for acne treatment. Among the 97 potential therapeutic targets that were screened out, the 6 core targets were TNF, JUN, IL6, STAT3, MAPK1, and MAPK3. A total of 2260 terms of GO enrichment analysis were obtained, including 2090 for biological processes (BP), 37 for cellular components (CC), and 133 for molecular function (MF). A total of 156 enriched KEGG pathways were identified, including TNF, IL-17, Th17 cell differentiation, MAPK, PI3K-Akt, T cell receptor, and Toll-like receptor signalling pathways. Conclusion This work showed that the JGL formula might reverse the pathological changes associated with acne vulgaris through its antiinflammatory effect and regulate the excessive lipogenesis in sebaceous glands via different signalling pathways. This new drug has application value and is worthy of further research and development.