Potential immune-related therapeutic mechanisms of multiple traditional Chinese medicines on type 2 diabetic nephropathy based on bioinformatics, network pharmacology and molecular docking.

BACKGROUND: The prevalence of type 2 diabetic nephropathy (T2DN) ranges from 20 % to 40 % among individuals with type 2 diabetes. Multiple immune pathways play a pivotal role in the pathogenesis of T2DN. This study aimed to investigate the immunomodulatory effects of active ingredients derived from 14 traditional Chinese medicines (TCMs) on T2DN. METHODS: By removing batch effect on the GSE30528 and GSE96804 datasets, we employed a combination of weighted gene co-expression network analysis, least absolute shrinkage and selection operator analysis, protein-protein interaction network analysis, and the CIBERSORT algorithm to identify the active ingredients of TCMs as well as potential hub biomarkers associated with immune cells. Functional analysis was conducted using Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), and gene set variation analysis (GSVA). Additionally, molecular docking was employed to evaluate interactions between active ingredients and potential immunotherapy targets. RESULTS: A total of 638 differentially expressed genes (DEGs) were identified in this study, comprising 5 hub genes along with 4 potential biomarkers. Notably, CXCR1, CXCR2, and FOS exhibit significant associations with immune cells while displaying robust or favorable affinities towards the active ingredients kaempferol, quercetin, and luteolin. Furthermore, functional analysis unveiled intricate involvement of DEGs, hub genes and potential biomarkers in pathways closely linked to immunity and diabetes. CONCLUSION: The potential hub biomarkers and immunotherapy targets associated with immune cells of T2DN comprise CXCR1, CXCR2, and FOS. Furthermore, kaempferol, quercetin, and luteolin demonstrate potential immunomodulatory effects in modulating T2DN through the regulation of CXCR1, CXCR2, and FOS expression.

Analysis of mechanism of core points in acupuncture and moxibustion treatment for epilepsy based on data mining. / åŸºäºŽæ•°æ®æŒ–æŽ˜æŽ¢è®¨é’ˆç¸æ²»ç–—ç™«ç—«æ ¸å¿ƒç©´ä½çš„ä½œç”¨æœºåˆ¶.

OBJECTIVES: To explore the mechanism of core points in acupuncture and moxibustion treatment for epilepsy by using data mining technique, so as to provide a reference for clinical practice and experimental research. METHODS: The data comes from relevant documents collected from CNKI, Wanfang, SinoMed, VIP, PubMed, Embase, Cochrane Library, EBSCO, Web of Science databases. The selected acupoints were analyzed in descriptive statistics, high-frequency acupoints group and core acupoint prescription. Further, potential target mining, "core acupoint prescription-target-epilepsy" network construction, protein-protein interactions (PPI) network establishment and core target extraction, gene ontology (GO) and KEGG gene enrichment analysis of the core acupoint prescription were carried out to predict its anti-epileptic potential mechanism. RESULTS: A total of 122 acupoint prescriptions were included. The core acupoint prescriptions were Baihui (GV20), Hegu (LI4), Neiguan (PC6), Shuigou (GV26) and Taichong (LR3). 277 potential targets were identified, among which 134 were shared with epilepsy. The core targets were extracted by PPI network topology analysis, including signal transducer and activator of transcription 3, tumor necrosis factor (TNF), interleukin (IL)-6, protein kinase B1, c-Jun N-terminal kinase, brain-derived neurotrophic factor, tumor protein 53, vascular endothelial growth factor A, Caspase-3, epidermal growth factor receptor, etc. The main anti-epileptic pathways of the core acupoints were predicted by KEGG enrichment, including lipid and atherosclerosis, neurodegeneration, phosphatidylinositol-3-kinase/protein B kinase signaling pathway, mitogen-activated protein kinase signaling pathway, cyclic adenosine monophosphate signaling pathway, TNF signaling pathway, IL-17 signaling pathway, hypoxia-inducible factor-1 signaling pathway, apoptosis, etc., involving neuronal death, synaptic plasticity, oxidative stress, inflammation and other related biological process. CONCLUSIONS: The core acupoint prescription of acupuncture and moxibustion intervention for epilepsy can act on multiple targets and multiple pathways to exert anti-epileptic effects, which can provide a theoretical basis for further clinical application and mechanism research.

Integrative analysis of network pharmacology and proteomics reveal the protective effect of Xiaoqinglong Decotion on neutrophilic asthma.

ETHNOPHARMACOLOGICAL RELEVANCE: Xiaoqinglong Decotion (XQLD) is a commonly used Chinese herbal formula in clinical practice, especially for allergic diseases such as asthma. However, its intrinsic mechanism for the treatment of neutrophilic asthma (NA) remains unclear. AIM OF THE STUDY: The aim of this study was to evaluate the efficacy and potential mechanisms of XQLD on NA using network pharmacology and in vivo experiments. MATERIALS AND METHODS: First, the active compounds, potential targets and mechanisms of XQLD against NA were initially elucidated by network pharmacology. Then, OVA/CFA-induced NA mice were treated with XQLD to assess its efficacy. Proteins were then analyzed and quantified using a Tandem Mass Tags approach for differentially expressed proteins (DEPs) to further reveal the mechanisms of NA treatment by XQLD. Finally, the hub genes, critical DEPs and potential pathways were validated. RESULTS: 176 active compounds and 180 targets against NA were identified in XQLD. Protein-protein interaction (PPI) network revealed CXCL10, CX3CR1, TLR7, NCF1 and FABP4 as hub genes. In vivo experiments showed that XQLD attenuated inflammatory infiltrates, airway mucus secretion and remodeling in the lungs of NA mice. Moreover, XQLD significantly alleviated airway neutrophil inflammation in NA mice by decreasing the expression of IL-8, MPO and NE. XQLD also reduced the levels of CXCL10, CX3CR1, TLR7, NCF1 and FABP4, which are closely associated with neutrophil inflammation. Proteomics analysis identified 28 overlapping DEPs in the control, NA and XQLD groups, and we found that XQLD inhibited ferroptosis signal pathway (elevated GPX4 and decreased ASCL3) as well as the expression of ARG1, MMP12 and SPP1, while activating the Rap1 signaling pathway. CONCLUSION: This study revealed that inhibition of ARG1, MMP12 and SPP1 expression as well as ferroptosis pathways, and activation of the Rap1 signaling pathway contribute to the therapeutic effect of XQLD on NA.

Exploring the mechanism of Corbrin capsules in the intervention of AKI-COVID-19 based on network pharmacology combined with GEO dataset.

AIM: of the study: This study used network pharmacology and the Gene Expression Omnibus (GEO) database to investigate the therapeutic effects of Corbrin capsules on acute kidney injury (AKI)-COVID-19 (coronavirus disease 2019). MATERIALS AND METHODS: The active constituents and specific molecular targets of Corbrin capsules were obtained from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) and Swiss Target Prediction databases. The targets related to AKI and COVID-19 disease were obtained from the Online Mendelian Inheritance in Man (OMIM), GeneCards, and GEO databases. A protein-protein interaction (PPI) network was constructed by utilizing Cytoscape. To enhance the analysis of pathways associated with the pathogenesis of AKI-COVID-19, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed. Furthermore, immune infiltration analysis was performed by using single-sample gene set enrichment analysis (ssGSEA) and CIBERSORT. Molecular docking was used to assess interactions between differentially expressed genes and active ingredients. Verification was performed by utilizing GEO databases and in vivo assays. RESULTS: This study revealed an overlap of 18 significantly differentially expressed genes between the Corbrin capsules group and the AKI-COVID-19 target group. Analysis of the PPI network identified TP53, JAK2, PIK3CA, PTGS2, KEAP1, and MCL1 as the top six core protein targets with the highest degrees. The results obtained from GO and KEGG analyses demonstrated that the target genes were primarily enriched in the apoptosis and JAK-STAT signaling pathways. Moreover, the analysis of immune infiltration revealed a notable disparity in the percentage of quiescent memory CD4 + T cells. Western blot analyses provided compelling evidence suggesting that the dysregulation of 6 core protein targets could be effectively reversed by Corbrin capsules. CONCLUSION: This study revealed the key components, targets, and pathways involved in treating AKI-related COVID-19 using Corbrin capsules. This study also provided a new understanding of the molecular mechanisms underlying this treatment.

Exploring the mechanism of ShenGui capsule in treating heart failure based on network pharmacology and molecular docking: A review.

ShenGui capsule (SGC), as a herbal compound, has significant effects on the treatment of heart failure (HF), but its mechanism of action is unclear. In this study, we aimed to explore the potential pharmacological targets and mechanisms of SGC in the treatment of HF using network pharmacology and molecular docking approaches. Potential active ingredients of SGC were obtained from the traditional Chinese medicine systems pharmacology database and analysis platform database and screened by pharmacokinetic parameters. Target genes of HF were identified by comparing the toxicogenomics database, GeneCards, and DisGeNET databases. Protein interaction networks and gene-disorder-target networks were constructed using Cytoscape for visual analysis. Gene ontology and Kyoto Encyclopedia of Genes and Genomes were also performed to identify protein functional annotations and potential target signaling pathways through the DAVID database. CB-DOCK was used for molecular docking to explore the role of IL-1ß with SGC compounds. Sixteen active ingredients in SGC were screened from the traditional Chinese medicine systems pharmacology database and analysis platform, of which 36 target genes intersected with HF target genes. Protein-protein interactions suggested that each target gene was closely related, and interleukin-1ß (IL-1ß) was identified as Hub gene. The network pharmacology analysis suggested that these active ingredients were well correlated with HF. Kyoto Encyclopedia of Genes and Genomes enrichment analysis suggested that target genes were highly enriched in pathways such as inflammation. Molecular docking results showed that IL-1ß binds tightly to SGC active components. This experiment provides an important research basis for the mechanism of action of SGC in the treatment of HF. In this study, the active compounds of SGC were found to bind IL-1ß for the treatment of heart failure.

Exploring the anti-atherosclerosis mechanism of ginsenoside Rb1 by integrating network pharmacology and experimental verification.

Ginsenoside Rb1 is the major active constituent of ginseng, which is widely used in traditional Chinese medicine for the atherosclerosis treatment by anti-inflammatory, anti-oxidant and reducing lipid accumulation. We explored cellular target and molecular mechanisms of ginsenoside Rb1 based on network pharmacology and in vitro experimental validation. In this study, we predicted 17 potential therapeutic targets for ginsenoside Rb1 with atherosclerosis from public databases. We then used protein-protein interaction network to screen the hub targets. Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway enrichment showed that the effects of ginsenoside Rb1 were meditated through multiple targets and pathways. Next, molecular docking results revealed that in the 10 core targets, CCND1 has the highest binding energy with ginsenoside Rb1. Vascular cell proliferation plays a critical role in atherosclerosis development. However, the effect and direct target of ginsenoside Rb1 in regulating vascular cell proliferation in atherosclerosis remains unclear. Edu straining results indicated that ginsenoside Rb1 inhibited the cell proliferation of endothelial cells, macrophages, and vascular smooth muscle cells. The protein immunoprecipitation (IP) analysis showed that ginsenoside Rb1 inhibited the vascular cell proliferation by suppressing the interaction of CCDN1 and CDK4. These findings systematically reveal that the anti-atherosclerosis mechanism of ginsenoside Rb1 by integrating network pharmacology and experimental validation, which provide evidence to treat atherosclerosis by using ginsenoside Rb1 and targeting CCND1.

Inhibitory role of remifentanil in hepatic ischemia-reperfusion injury through activation of Fmol/Parkin signaling pathway: A study based on network pharmacology analysis and high-throughput sequencing.

BACKGROUND: This study was conducted to elucidate the critical molecular pathways underlying the protective effects of remifentanil against hepatic ischemia-reperfusion injury in rats. Our approach integrated network pharmacology analysis with high-throughput sequencing to achieve a comprehensive understanding of the mechanisms involved. STUDY DESIGN/METHODS: The study utilized GSE24430 gene expression data from GEO to investigate remifentanil's impact on Hepatic Ischemia-Reperfusion Injury in rats. Weighted Correlation Network Analysis (WGCNA) was employed to pinpoint crucial genes and identify modules of co-expressed genes. Differential analysis with the "Limma" package revealed genes differentially expressed in IRI vs. control groups. PubChem and PharmMapper provided target genes affected by remifentanil. Protein-protein interaction networks were constructed via GeneCards and STRING. Functional analysis pinpointed core genes involved in remifentanil's IRI alleviation. IRI rat models were established, and hepatic injury indicators, liver structure via H&E staining, autophagosome counts via electron microscopy, and gene/protein expression via RT-qPCR and Western blot were assessed. High-throughput sequencing analyzed molecular pathways affected by varying remifentanil doses in IRI rats. RESULTS: In the study, we discovered four primary co-expression modules associated with hepatic IRI, and the grey module exhibited the highest correlation with hepatic IRI.A total of sixty-eight genes that were differentially expressed were found to have a connection with hepatic IRI.Network pharmacology analysis found that remifentanil may alleviate hepatic IRI through Fmol.found that the Fmol/Parkin signaling pathway may alleviate hepatic IRI via Additionally, the database autophagy. The established hepatic IRI rat models further confirmed the above findings. CONCLUSION: Our study established that remifentanil triggers the Fmol/Parkin signaling cascade, amplifying the expression levels of Fmol and Parkin. This process culminates in the activation of autophagy within hepatic cells, ultimately alleviating hepatic ischemia-reperfusion injury (IRI).

Network Pharmacology and Experimental Verification Reveal the Regulatory Mechanism of Chuanbeimu in Treating Chronic Obstructive Pulmonary Disease.

Background: Chronic obstructive pulmonary disease (COPD) is a common respiratory disorder in pulmonology. Chuanbeimu (CBM) is a traditional Chinese medicinal herb for treating COPD and has been widely utilized in clinical practice. However, the mechanism of CBM in the treatment of COPD remains incompletely understood. This study aims to investigate the underlying therapeutic mechanism of CBM for COPD using network pharmacology and experimental approaches. Methods: Active ingredients and their targets were obtained from the Traditional Chinese Medicine Systems Pharmacology database. COPD-associated targets were retrieved from the GeneCards database. The common targets for CBM and COPD were identified through Venn diagram analysis. Protein-protein interaction (PPI) networks and disease-herb-ingredient-target networks were constructed. Subsequently, the results of the network pharmacology were validated by molecular docking and in vitro experiments. Results: Seven active ingredients and 32 potential targets for CBM were identified as closely associated with COPD. The results of the disease-herb-ingredient-target network and PPI network showed that peimisine emerged as the core ingredient, and SRC, ADRB2, MMP2, and NOS3 were the potential targets for CBM in treating COPD. Molecular docking analysis confirmed that peimisine exhibited high binding affinity with SRC, ADRB2, MMP2, and NOS3. In vitro experiments demonstrated that peimisine significantly upregulated the expression of ADRB2 and NOS3 and downregulated the expression of SRC and MMP2. Conclusion: These findings indicate that CBM may modulate the expression of SRC, ADRB2, MMP2, and NOS3, thereby exerting a protective effect against COPD.

The antitumor effects of herbal medicine Triphala on oral cancer by inactivating PI3K/Akt signaling pathway: based on the network pharmacology, molecular docking, in vitro and in vivo experimental validation.

BACKGROUND: This research aimed to investigate the anti-tumor effects and underlying genetic mechanisms of herbal medicine Triphala (TRP) in oral squamous cell carcinoma (OSCC). METHODS: The target genes of Triphala (TRP) in oral squamous cell carcinoma (OSCC) were identified, and subsequent functional enrichment analysis was conducted to determine the enriched signaling pathways. Based on these genes, a protein-protein interaction network was constructed to identify the top 10 genes with the highest degree. Genes deregulated in OSCC tumor samples were identified to be hub genes among the top 10 genes. In vitro experiments were performed to investigate the influence of TRP extracts on the cell metabolic activity, migration, invasion, apoptosis, and proliferation of two OSCC cell lines (CAL-27 and SCC-9). The functional rescue assay was conducted to investigate the effect of applying the inhibitor and activator of an enriched pathway on the phenotypes of cancer cells. In addition, the zebrafish xenograft tumor model was established to investigate the influence of TRP extracts on tumor growth and metastasis in vivo. RESULTS: The target genes of TRP in OSCC were prominently enriched in the PI3K-Akt signaling pathway, with the identification of five hub genes (JUN, EGFR, ESR1, RELA, and AKT1). TRP extracts significantly inhibited cell metabolic activity, migration, invasion, and proliferation and promoted cell apoptosis in OSCC cells. Notably, the application of TRP extracts exhibited the capacity to downregulate mRNA and phosphorylated protein levels of AKT1 and ESR1, while concomitantly inducing upregulation of mRNA and phosphorylated protein levels in the remaining three hub genes (EGFR, JUN, and RELA). The functional rescue assay demonstrated that the co-administration of TRP and the PI3K activator 740Y-P effectively reversed the impact of TRP on the phenotypes of OSCC cells. Conversely, the combination of TRP and the PI3K inhibitor LY294002 further enhanced the effect of TRP on the phenotypes of OSCC cells. Remarkably, treatment with TRP in zebrafish xenograft models demonstrated a significant reduction in both tumor growth and metastatic spread. CONCLUSIONS: Triphala exerted significant inhibitory effects on cell metabolic activity, migration, invasion, and proliferation in OSCC cell lines, accompanied by the induction of apoptosis, which was mediated through the inactivation of the PI3K/Akt pathway.

A Strategy based on Bioinformatics and Machine Learning Algorithms Reveals Potential Mechanisms of Shelian Capsule against Hepatocellular Carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is a prevalent and life-threatening form of cancer, with Shelian Capsule (SLC), a traditional Chinese medicine (TCM) formulation, being recommended for clinical treatment. However, the mechanisms underlying its efficacy remain elusive. This study sought to uncover the potential mechanisms of SLC in HCC treatment using bioinformatics methods. METHODS: Bioactive components of SLC were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), and HCC-related microarray chip data were sourced from the Gene Expression Omnibus (GEO) database. The selection criteria for components included OB ≧ 30% and DL ≧ 0.18. By integrating the results of differential expression analysis and weighted gene co-expression network analysis (WGCNA), disease-related genes were identified. Therapeutic targets were determined as shared items between candidate targets and disease genes. Protein-protein interaction (PPI) network analysis was conducted for concatenated genes, with core protein clusters identified using the MCODE plugin. Machine learning algorithms were applied to identify signature genes within therapeutic targets. Subsequently, immune cell infiltration analysis, single-cell RNA sequencing (sc-RNA seq) analysis, molecular docking, and ADME analysis were performed for the screened genes. RESULTS: A total of 153 SLC ingredients and 170 candidate targets were identified, along with 494 HCCrelated disease genes. Overlapping items between disease genes and drug candidates represented therapeutic genes, and PPI network analysis was conducted using concatenated genes. MCODE1 and MCODE2 cluster genes underwent Disease Ontology (DO), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Four signature genes (TOP2A, CYP1A2, CYP2B6, and IGFBP3) were identified from 28 therapeutic genes using 3 machine learning algorithms, with ROC curves plotted. Molecular docking validated the interaction modes and binding abilities between signature genes and corresponding compounds, with free binding energy all <-7 kcal/mol. Finally, ADME analysis revealed similarities between certain SLC components and the clinical drugs Sorafenib and Lenvatinib. CONCLUSION: In summary, our study revealed that the mechanism underlying the anti-HCC effects of SLC involves interactions at three levels: components (quercetin, beta-sitosterol, kaempferol, baicalein, stigmasterol, and luteolin), pathways (PI3K-Akt signaling pathway, TNF signaling pathway, and IL-17 signaling pathway), and targets (TOP2A, CYP1A2, CYP2B6, and IGFBP3). This study provides preliminary insights into the potential pharmacological mechanisms of SLC in HCC treatment, aiming to support its clinical application and serve as a reference for future laboratory investigations.

Transcriptomic analysis of the HPG axis-related tissues reveals potential candidate genes and regulatory pathways associated with testicular size in Hu sheep.

Testicular size is an excellent proxy for selecting high-fertility rams. The hypothalamus-pituitary-gonadal (HPG) axis plays an important role in regulating reproductive capacity in vertebrates, while key genes and regulatory pathways within the HPG axis associated with testicular size remain largely unknown in sheep. This study comprehensively compared the transcriptomic profiles in the hypothalamus, pituitary and testis of rams after sexual maturity between the large-testis group (LTG, testicular weight = 454.29 ± 54.24 g) and the small-testis group (STG, testicular weight = 77.29 ± 10.76 g). In total, 914, 795 and 10518 differentially expressed genes (DEGs) were identified in the hypothalamus, pituitary and testis between LTG and STG, respectively. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses showed that these DEGs were mainly involved in the biological processes of reproduction, biological regulation, and development process. Notably, the neuroactive ligand-receptor interaction and cAMP signaling pathways, commonly enriched by the DEGs in the hypothalamus and pituitary between two groups, were considered as two key signal pathways regulating testicular development through the HPGs axis. Weighted gene co-expression network analysis (WGCNA) identified two modules that were significantly associated with testicular size, and 97 key genes were selected with high module membership (MM) and gene significance (GS) in these two modules. Finally, a protein-protein interaction (PPI) network was constructed, and ten genes with the highest degree were represented as hub genes, including FOS, NPY, SST, F2, AGT, NTS, OXT, EDN1, VIP and TAC1. Taken together, these results provide new insights into the molecular mechanism underlying the HPG axis regulating testicular size of Hu sheep.

Analysis of Enrichment Pathway, Hub Gene, and Protein-Protein Interaction Network in Rheumatoid Arthritis and Construction of Molecular Subtypes in Peripheral Blood.

Objective: To analyze the enrichment pathway, hub gene, and Protein-protein interaction (PPI) network of rheumatoid arthritis (RA) and construct peripheral blood subtypes based on integrated bioinformatics analysis. Methods: Suitable datasets were screened from the GEO database based on titles and abstracts, batch positive analysis was performed using R language, and KEGG enrichment analysis and GO enrichment analysis were performed. After screening the differential genes, the PPI network was constructed, and the hubba plug-in of Cytoscape software was used to obtain the top 10 hub genes(key regulatory genes). hub genes were used as the typing condition to identify the molecular subtypes of synovial tissue and peripheral blood of arthritis. Results: GSE12021 and GSE93272 have been chosen for analysis. GSE12021 presents the transcriptome analysis of human joint synovial tissue, comprising 12 samples from patients with rheumatoid arthritis and 9 samples from normal healthy individuals. On the other hand, GSE93272 includes human peripheral blood samples, comprising 232 samples from patients with rheumatoid arthritis and 43 samples from normal healthy individuals. The main results of GSE12021 KEGG enrichment were Parathyroid hormone synthesis, Relaxin signaling pathway, TNF signaling pathway, Rheumatoid arthritis, T cell receptor signaling pathway, Th1 and Th2 cell differentiation, Th17 cell differentiation, Toll-like receptor signaling pathway and so on. The main results of GSE12021 GO enrichment were regulation of feeding behavior, regulation of neuron death, positive regulation of cell-cell adhesion, and positive regulation of leukocyte activation. The top 10 hub genes were CD8A, JUN, CTLA4, CD19, LCK, FOS, CCL5, IL7R, CCR7 and CD247. Synovial tissue and peripheral blood subtypes of rheumatoid arthritis showed that the two classification methods maintained consistency. Conclusion: Identifying the Hub gene in peripheral blood helps screen molecular subtypes of rheumatoid arthritis.

Mechanism of action of Huangbaichen Sanwei formulation in treating T2DM based on network pharmacology and molecular docking.

Huangbaichen Sanwei formulation (HBCS) has been reported to have a good hypoglycemic effect, but its pharmacological mechanism of action remains unclear. We used network pharmacology and molecular docking to explore the potential mechanism of action of HBCS against type-2 diabetes mellitus (T2DM). Fifty-five active components from HBCS interfered with T2DM. Twenty-five core targets, such as AKT1, INS, INSR, MAPK1 were identified. Enrichment analyses showed that HBCS was involved mainly including insulin receptor signaling pathway, extracellular region, and insulin-like growth factor receptor binding and other biological processes; common targets had roles in treating T2DM by regulating diabetic cardiomyopathy and insulin resistance. Molecular docking verified that components combined with core targets. HBCS play a part in treating T2DM through multiple components and targets at the molecular level, which lays a theoretical foundation for research using HBCS to treat T2DM. The components, predicted targets, and T2DM targets of HBCS were searched through databases, and common targets were determined. Further screening of the core targets was conducted through the establishment of a protein -protein interaction network. The core targets were analyzed by Gene Ontology (GO) annotation utilizing the DAVID platform. And the enrichment of signaling pathways was explored by employing the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Cytoscape 3.9.1 was employed to construct a "TCM-components-core target-pathway" network. Autodock Vina was used to dock molecules to compare the binding activity of active molecules with targets.

Exploring the mechanism of Erchen decoction in the treatment of atherosclerosis based on network pharmacology and molecular docking.

BACKGROUND: Atherosclerosis (AS) is the cause of most cardiovascular diseases and imposes a huge economic burden on society. Erchen decoction (ECD) is an effective formula for treating AS, but its therapeutic mechanism remains unclear. This study will explore the mechanism of ECD mechanism for treating AS using network pharmacology and molecular docking. METHODS: We searched ECD chemical composition information and related targets via Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform and SwissTargetPrediction databases, and gene names correction was performed using the UniProt database. AS-related targets were retrieved from OMIM, GeneCards, and DrugBank databases, and Venny 2.1 were used for intersection analysis. Protein-protein interaction network was constructed by the STRING database, and an interactive network of the drug-component-target-disease was drawn using the Cytoscape 3.9.0 software. Gene ontology and Kyoto Gene and Genome Encyclopedia enrichment analysis were performed by the DAVID database, and molecular docking validation of vital active ingredients and action targets of ECD was performed using AutoDock Vina software. RESULTS: The 127 active components of ECD act on AS by regulating 231 targets and 151 pathways. The 6 core components are quercetin, polyporenic acid C, 18α-hydroxyglycyrrhetic acid, glyuranolide, 3beta-hydroxychloroxy-24-methylene-8-lanostene-21-oic acid, and obacunone. They may regulate AS by regulating core target genes, such as JUN, SRC, AKT1, PTGS2, ESR1, AR, MAPK1, MAPK3, and RELA, and acting on multiple vital pathways, such as AGE-RAGE signaling pathway in diabetic complications, Lipid and AS, and Fluid shear stress and AS. Molecular docking showed that the selected target protein had good binding activity to the active ingredient. CONCLUSIONS: ECD has the characteristics of multi-components, multi-targets and multi-pathways in the treatment of AS. The results provide a theoretical basis for the clinical application of ECD and its mechanism.

Exploring the pathogenesis of depression and potential antidepressants through the integration of reverse network pharmacology, molecular docking, and molecular dynamics.

Depression is characterized by a significant and persistent decline in mood and is currently a major threat to physical and mental health. Traditional Chinese medicine can effectively treat depression with few adverse effects. Therefore, this study aimed to examine the use of reverse network pharmacology and computer simulations to identify effective ingredients and herbs for treating depression. Differentially expressed genes associated with depression were obtained from the Gene Expression Omnibus database, after which enrichment analyses were performed. A protein-protein interaction network was constructed using the STRING database to screen core targets. The Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform database was used to screen ingredients related to these core targets, and the core ingredients were screened by constructing the "Targets-Ingredients-Herbs" network. Drug evaluation analysis was performed using the SwissADME and ADMETlab platforms, according to Lipinski Rule of 5. The binding between the targets and ingredients was simulated using molecular docking software. The binding stability was determined using molecular dynamics analysis. The "Ingredients-Herbs" network was constructed, and we annotated it for its characteristics and meridians. Finally, the selected herbs were classified to determine the formulation for treating depression in traditional Chinese medicine. The pathogenesis of depression was associated with changes in SPP1, Plasminogen activator inhibitor 1, CCNB1 protein, CCL3, and other genes. Computer simulations have verified the use of quercetin, luteolin, apigenin, and other ingredients as drugs for treating depression. Most of the top 10 herbs containing these ingredients were attributed to the liver meridian, and their taste was symplectic. Perilla Frutescen, Cyperi Rhizoma, and Linderae Radix, the main components of "Tianxiang Zhengqi Powder," can treat depression owing to Qi stagnation. Epimedium and Citicola, the main traditional Chinese herbs in "Wenshen Yiqi Decoction," have a positive effect on depression of the Yang asthenia type. Fructus Ligustri Lucidi and Ecliptae Herba are from the classic prescription "Erzhi Pills" and can treat depression of the Yin deficiency type. This study identified the key targets and effective medicinal herbs for treating depression. It provides herbal blend references for treating different types of depression according to the theory of traditional Chinese medicine.

Network pharmacology and molecular docking-based study on exploring the potential mechanism of Lycium barbarum L: In the treatment of atherosclerosis.

BACKGROUND: Goji berries (Lycium barbarum L) are herbal medicine that have a long history of use and multiple pharmacological activities. In this study, we investigated the potential therapeutic effects of Goji berries on atherosclerosis (AS) using network pharmacology and molecular docking. METHODS: The active compounds of Goji berries were identified using the Traditional Chinese Medicine Systems Pharmacology platform, as well as the literature and the targets of each active compound were obtained using the Swiss Target Prediction database. The AS-related targets were collected from the GeneCards and OMIM databases to obtain the common targets of Goji berries and AS. The drug-compound-target-disease network and protein-protein interaction network were constructed using the Cytoscape software to obtain the core target proteins of Goji berries related to AS. Gene ontology analysis of the core targets and Kyoto encyclopedia of genes and genomes pathway enrichment analysis were performed by Metascape. The target-chemical correlations were verified using AutoDock molecular docking. RESULTS: After analysis, 44 active compounds within Goji berries were obtained that exhibit associations with AS. Among these, the proteins exhibiting the highest degrees of interaction within the compound-targeted protein protein-protein interaction network were AKT1, SRC, MAPK3, MAPK1, RELA, and STAT3. The gene ontology-biology process analysis showed that compound-targeted proteins were mainly involved in regulating small molecule metabolic process, cellular response to chemical stress, reactive oxygen species metabolic process, and regulation of inflammatory response. Kyoto encyclopedia of genes and genomes pathway mainly included lipid and AS in which AKT1, SRC, MAPK3, and MAPK1 were involved. Advanced glycation end-product-receptor for advanced glycation end-product signaling pathway in diabetic complications, Chagas disease, and pancreatic disease. Molecular docking assessment showed that fucosterol is bound to AKT1, MAPK3, and SRC. CONCLUSION: This study demonstrates that network pharmacology and molecular docking analyses contribute to a better understanding of Goji berries active compounds and targets as potential therapeutic drugs for treating AS.

Potential molecular targets and drugs for basement membranes-related intervertebral disk degeneration through bioinformatics analysis and molecular docking.

BACKGROUND: Through bioinformatics analysis to identify the hub genes of Intervertebral disc degeneration (IVDD) associated with basement membranes (BMs) and find out the potential molecular targets and drugs for BMs-related annulus fibrosus (AF) degeneration based on bioinformatic analysis and molecular approach. METHODS: Intervertebral disc degeneration (IVDD) related targets were obtained from GeneCards, DisGenet and OMIM databases. BMs related genes were obtained from Basement membraneBASE database. The intersection targets were identified and subjected to protein-to-protein interaction (PPI) construction via STRING. Hub genes were identified and conducted Gene ontology (GO) and pathway enrichment analysis through MCODE and Clue GO in Cytospace respectively. DSigDB database was retrieved to predict therapeutic drugs and molecular docking was performed through PyMOL, AutoDock 1.5.6 to verify the binding energy between the drug and the different expressed hub genes. Finally, GSE70362 from GEO database was obtained to verify the different expression and correlation of each hub gene for AF degeneration. RESULTS: We identified 41 intersection genes between 3 disease targets databases and Basement membraneBASE database. PPI network revealed 25 hub genes and they were mainly enriched in GO terms relating to glycosaminoglycan catabolic process, the TGF-ß signaling pathway. 4 core targets were found to be significant via comparison of microarray samples and they showed strong correlation. The molecular docking results showed that the core targets have strong binding energy with predicting drugs including chitosamine and retinoic acid. CONCLUSIONS: In this study, we identified hub genes, pathways, potential targets, and drugs for treatment in BMs-related AF degeneration and IVDD.

Network pharmacology-based and molecular docking-based analysis of You-Gui-Yin for the treatment of osteonecrosis of the femoral head.

You-Gui-Yin (YGY) is a classic prescription for warming up kidney-Yang and filling in kidney essence in traditional Chinese medicine, and has been used to treat osteonecrosis of the femoral head (ONFH) effectively. However, the underlying mechanisms are still unknown. This study is aimed at exploring the possible mechanisms of action of the YGY in the treatment of ONFH based on network pharmacology and molecular docking. TCMSP was used to screen the active components and targets of YGY. The disease targets of ONFH were collected in several public databases. The protein-protein interaction (PPI) Network was constructed using the STRING platform. The Metascape database platform was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. The key active components and core target proteins of YGY in the treatment of ONFH were verified by the molecular docking. 120 active components were obtained from YGY, among which 73 components were hit by the 117 drug-disease intersection targets. Key effective components included quercetin, kaempferol, beta-sitosterol, glycitein, beta-carotene, and so on. Core target proteins included ALB, AKT1, TNF, IL6, TP53, and so on. According to GO and KEGG analyses, there were 1762 biological processes, 94 cellular component, 138 molecular function and 187 signaling pathways involved. we selected the top 20 biological processes (BP), cellular components (CC), molecular functions (MF) and signaling pathways to draw the heat maps, showing that Lipid and atherosclerosis signaling pathway, IL-17 signaling pathway, HIF-1 signaling pathway, relaxin signaling pathway and MAPK signaling pathway and other pathways may play a key role in the treatment of ONFH by YGY. The results of molecular docking showed that key effective components and corresponding core target proteins exhibited the good binding activity. YGY can treat ONFH through multicomponents, multitargets, and multipathways, which provides a reference for the subsequent research, development of targeted drugs and clinical application.

Exploration of Simiao-Yongan Decoction on knee osteoarthritis based on network pharmacology and molecular docking.

Use network pharmacology combined with molecular docking to study the effects of Simiao-Yongan Decoction (SMYAD) intervenes in Knee Osteoarthritis (KOA) related targets and signaling pathways, and explores the molecular mechanism of SMYAD in treating KOA. The active ingredients and targets of SMYAD, which concluded 4 traditional Chinese medicines, were screened in TCMSP, and the related gene targets of KOA were screened in the disease databases GeneCards, MalaCards, DisGeNET, and Comparative Toxicogenomics Database, and their intersection data were obtained after integration. And used Cytoscape 3.9.1, the software topologies the network diagram of "compound-drug-active ingredient-target protein-disease." Obtains the protein-protein interaction network diagram through STRING, and enriches and analyzes the obtained core targets. Carry out molecular docking matching verification on the main active ingredients and key targets of the drug. 106 active ingredients and 175 targets were screened from SMYAD to intervene in KOA, 36 core targets were obtained through protein-protein interaction screening, and 10 key targets played an important role. The enrichment results showed that the biological process of gene ontology mainly involved positive regulation of gene expression, negative regulation of apoptosis process, and positive regulation of apoptosis process. KEGG signaling pathway mainly involves AGE-RAGE signaling pathway in diabetic complications, TNF signaling pathway, hypoxia-inducible factor-1 signaling pathway, IL-17 signaling pathway. The pathway of Reactome mainly involves interleukin-4 and interleukin-13 signaling, cytokine signaling in immune system, immune system, apoptosis. Molecular docking showed that the mainly effective components of SMYAD can fully combine with TNF, IL1B, IL6, and CASP3. The results show that the main active ingredients and potential mechanism of action of SMYAD in the treatment of KOA have the characteristics of multiple targets and multiple pathways, which provides ideas and basis for further in-depth exploration of its specific mechanism.

Network module analysis and molecular docking-based study on the mechanism of astragali radix against non-small cell lung cancer.

BACKGROUND: Most lung cancer patients worldwide (stage IV non-small cell lung cancer, NSCLC) have a poor survival: 25%-30% patients die < 3 months. Yet, of those surviving > 3 months, 10%-15% patients survive (very) long. Astragali radix (AR) is an effective traditional Chinese medicine widely used for non-small cell lung cancer (NSCLC). However, the pharmacological mechanisms of AR on NSCLC remain to be elucidated. METHODS: Ultra Performance Liquid Chromatography system coupled with Q-Orbitrap HRMS (UPLC-Q-Orbitrap HRMS) was performed for the qualitative analysis of AR components. Then, network module analysis and molecular docking-based approach was conducted to explore underlying mechanisms of AR on NSCLC. The target genes of AR were obtained from four databases including TCMSP (Traditional Chinese Medicine Systems Pharmacology) database, ETCM (The Encyclopedia of TCM) database, HERB (A high-throughput experiment- and reference-guided database of TCM) database and BATMAN-TCM (a Bioinformatics Analysis Tool for Molecular mechanism of TCM) database. NSCLC related genes were screened by GEO (Gene Expression Omnibus) database. The STRING database was used for protein interaction network construction (PIN) of AR-NSCLC shared target genes. The critical PIN were further constructed based on the topological properties of network nodes. Afterwards the hub genes and network modules were analyzed, and enrichment analysis were employed by the R package clusterProfiler. The Autodock Vina was utilized for molecular docking, and the Gromacs was utilized for molecular dynamics simulations Furthermore, the survival analysis was performed based on TCGA (The Cancer Genome Atlas) database. RESULTS: Seventy-seven AR components absorbed in blood were obtained. The critical network was constructed with 1447 nodes and 28,890 edges. Based on topological analysis, 6 hub target genes and 7 functional modules were gained. were obtained including TP53, SRC, UBC, CTNNB1, EP300, and RELA. After module analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed that AR may exert therapeutic effects on NSCLC by regulating JAK-STAT signaling pathway, PI3K-AKT signaling pathway, ErbB signaling pathway, as well as NFkB signaling pathway. After the intersection calculation of the hub targets and the proteins participated in the above pathways, TP53, SRC, EP300, and RELA were obtained. These proteins had good docking affinity with astragaloside IV. Furthermore, RELA was associated with poor prognosis of NSCLC patients. CONCLUSIONS: This study could provide chemical component information references for further researches. The potential pharmacological mechanisms of AR on NSCLC were elucidated, promoting the clinical application of AR in treating NSCLC. RELA was selected as a promising candidate biomarker affecting the prognosis of NSCLC patients.