DisGeNET Database Research Articles

DeClUt: Decluttering differentially expressed genes through clustering of their expression profiles

Background and Objective:differential expression analysis is one of the most popular activities in transcriptomic studies based on next-generation sequencing technologies. In fact, differentially expressed genes (DEGs) between two conditions represent ideal prognostic and diagnostic candidate biomarkers for many pathologies. As a result, several algorithms, such as DESeq2 and edgeR, have been developed to identify DEGs. Despite their widespread use, there is no consensus on which model performs best for different types of data, and many existing methods suffer from high False Discovery Rates (FDR). Methods:we present a new algorithm, DeClUt, based on the intuition that the expression profile of differentially expressed genes should form two reasonably compact and well-separated clusters. This, in turn, implies that the bipartition induced by the two conditions being compared should overlap with the clustering. The clustering algorithm underlying DeClUt was designed to be robust to outliers typical of RNA-seq data. In particular, we used the average silhouette function to enforce membership assignment of samples to the most appropriate condition. Results:DeClUt was tested on real RNA-seq datasets and benchmarked against four of the most widely used methods (edgeR, DESeq2, NOISeq, and SAMseq). Experiments showed a higher self-consistency of results than the competitors as well as a significantly lower False Positive Rate (FPR). Moreover, tested on a real prostate cancer RNA-seq dataset, DeClUt has highlighted 8 DE genes, linked to neoplastic process according to DisGeNET database, that none of the other methods had identified. Conclusions:our work presents a novel algorithm that builds upon basic concepts of data clustering and exhibits greater consistency and significantly lower False Positive Rate than state-of-the-art methods. Additionally, DeClUt is able to highlight relevant differentially expressed genes not otherwise identified by other tools contributing to improve efficacy of differential expression analyses in various biological applications.

Mechanistic analyses reveal that Pueraria montana var. lobata (Willd.) is effective in inhibiting ovarian cancer progression.

Ovarian cancer (OC) is a common malignancies of the female genitalia. P. montana var. lobata (Willd.), a herb with anti-tumor effects, is widely used in the clinical treatment of ovarian cancer (OC), but the ingredients and molecular mechanism of action remains to be explored. In this study, we extracted the main active ingredients of P. montana var. lobata (Willd.) from the TCMSP database, and predicted its potential targets of action against OC from the DisGeNET and GeneCards databases. Protein-protein interaction (PPI) was constructed using the STRING database, while pathway enrichment analyses were performed using the DAVID database. Next, we generated an Ingredient-Target-Pathway network using Cytoscape 3.7.2, then processed the key targets of action and main active ingredients for molecular docking.The results showed that seven active ingredients of P montana var. lobata (Willd.) were associated with treating for OC, namely beta-sitosterol, coumestrol, daidzein, formononetin, genistein, puerarin and scoparone, two important targets Casp3 and Jun, and signaling pathways of P. montana var. lobata (Willd.) against the progression of OC. TUNEL staining, enzyme-linked immunosorbent assay (ELISA), and Western blot assays, the pharmacodynamic effect of puerarin in the treatment of OC and the major targets were verified. Animal experiment demonstrated that application of puerarin at different times of modeling not only upregulated expression of Casp3, Smac, and c-jun proteins, but also promoted apoptosis in tumor cells, hence inhibiting progression of OC. This study demonstrates that P. montana var. lobata (Willd.) can thereby induce apoptosis in tumor cells and inhibit malignant progression through activating expression of Casp3, smac, and c-jun proteins to regulate related apoptosis pathways, as validated by network pharmacology predictions and animal experiments, and can be verifed by large-scale clinical trials in the future. This study also provides theoretical support and new research perspectives for this disease.

The Therapeutic Target of IBD and the Mechanism of Dipyridamole in Treating IBD Explored by Geo Gene Chips, Network Pharmacology, and Molecular Docking.

Inflammatory Bowel Disease (IBD) is a refractory disease with repeated attacks, and there is no accurate treatment target at present. Dipyridamole, a phosphodiesterase (PDE) inhibitor, has been proven to be an effective treatment for IBD in a pilot study. This study explored the therapeutic target of IBD and the pharmacological mechanism of dipyridamole for the treatment of IBD. The candidate targets of dipyridamole were obtained by searching the pharmMapper online server and Swiss Target Prediction Database. The IBD-related targets were selected from four GEO chips and three databases, including Genecards, DisGeNET, and TTD database. A protein-protein interaction (PPI) network was constructed, and the core targets were identified according to the topological structure. KEGG and GO enrichment analysis and BioGPS location were performed. Finally, molecular docking was used to verify dipyridamole and the hub targets. We obtained 112 up-regulated genes and 157 down-regulated genes, as well as 105 composite targets of Dipyridamole-IBD. Through the PPI network analysis, we obtained the 7 hub targets, including SRC, EGFR, MAPK1, MAPK14, MAPK8, PTPN11, and LCK. The BioGPS showed that these genes were highly expressed in the immune system, digestive system, and endocrine system. In addition, the 7 hub targets had good intermolecular interactions with dipyridamole. The therapeutic effect of dipyridamole on IBD may involve immune system activation and regulation of inflammatory reactions involved in the regulation of extracellular matrix, perinuclear region of cytoplasm, protein kinase binding, and positive regulation of programmed cell death through cancer pathway (proteoglycans in cancer), lipid metabolism, Ras signaling pathway, MAPK signaling pathway, PI3K-AKT signaling pathway, Th17 cell differentiation, and other cellular and innate immune signaling pathways. This study predicted the therapeutic target of IBD and the molecular mechanism of dipyridamole in treating IBD, providing a new direction for the treatment of IBD and a theoretical basis for further research.

Study on the mechanism of Huangqi Guizhi Wuwu Decoction in treating diabetes peripheral neuropathy based on network pharmacology and molecular docking.

This study aimed to explore the effective substances and mechanism network of Huangqi Guizhi Wuwu Decoction in treating diabetes peripheral neuropathy. Based on the TCM systemic pharmacological analysis platform (TCMP) and UniProt database, the database of active Huqarqu Decoction was constructed, and the related targets of diabetic peripheral neuropathy were collected through the OMIM, CTD, DisGeNET, TTD and GeneCards databases. The intersection targets were obtained to construct the network diagram of Huangqi dis Guizhi Wuwu Decoction-Active Through the String database, the interaction between target proteins was analyzed, and molecular docking between active components and potential targets was carried out. Combined with the DAVID v6.8 database, GO function analysis and KEGG pathway analysis were performed on the targets. Guizhi Wuwu Decoction mainly acts on core targets such as IL6, MAPK3, VE GFA, JUN and ESR1 through quercetin, kaempferol and naringin and regulates the TNF signaling pathway, estrogen signaling pathway and MAPK signaling pathway, thus achieving the effect of treating diabetes peripheral neuropathy. Huangqi Guizhi Wu has multiple targets and regulates multiple signaling pathways in neuropathy, which lays a foundation for future pharmacological research.

Network pharmacology and transcriptomics analysis reveal the mechanism of BushenHuoxue formula attenuates premature ovarian failure via modulation PI3K/AKT pathway.

This study aims to analyze the active components and mechanism of Bushen Huoxue (BSHX) formula on the autoimmune premature ovarian insufficiency (POI) by combining network pharmacology and Transcriptomics. The active components and targets of BSHXF were screened through Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). POI-related targets were identified through Therapeutic Targets Database (TTD), DisGeNET and drugbank database. The Veen diagram was performed to obtain the action targets. The active compound-target network and Protein-Protein Interaction (PPI) network were built by using STRING database and Cytoscape software. Key targets and active compounds were further identified by topological analysis. Molecular docking shows that Kaempferol, Isorhamnetin and Anhydroicaritin have strong binding to AKT. Finally, a zp3-induced autoimmune ovarian function deficiency mouse model was used to explore the potential mechanism of POI. The potential pathways of BSHXF for the treatment of POI were identified by Transcriptomic analysis. PI3K-AKT and NF-kb pathways were the common pathways between network pharmacology and transcriptomics. Our results revealed that BSHXF could reduce the FSH expression levels and raise the E2, and AMH levels in the serum. Western bloting demonstrates that BSHXF could upregulate the expression of p-PI3K and p-AKT.

Exploration of Potential Targets and Molecular Mechanisms of the Yiqi Jianpi Tongqiao Formula in Treating Allergic Rhinitis Mouse Model based on Network Pharmacology and Molecular Docking.

To investigate the therapeutic effect of Yiqi Jianpi Tongqiao (YJT) formula (Hedysarum Multijugum Maxim, Magnoliae Flos, Xanthii Fructus, Notopterygii Rhizoma Et Radix, Kaempferiae Rhizoma, Acoritataninowii Rhizoma, Saposhnikoviae Radix) on an allergic rhinitis mouse model, and to explore the active ingredients, key targets, and molecular mechanisms of this formula using network pharmacology and molecular docking methods. An allergic rhinitis mouse model was established to observe changes in rhinitis symptoms, nasal mucosal morphology, and serum indicators after administering the YJT formula. The TCMSP, GeneCards, OMIM, and DisGeNET databases were used to screen for the active ingredients, action targets, and disease targets of the YJT formula. The Cytoscape software was used to construct a network of the active ingredients and action targets. The protein-protein interaction (PPI) network was used to predict hub genes. The corresponding active compounds with the hub genes' highest oral bioavailability (OB) values were identified, followed by molecular docking analysis. Animal experiments demonstrated that the YJT formula reduced rhinitis symptoms (nasal itching, runny nose, and face scratching) in allergic rhinitis mice, as well as decreased nasal mucosal inflammatory reactions and serum inflammatory indicators (histamine, OVAspecific IgE, IL-1β levels). Furthermore, 63 active components and 101 potential indicator targets of the YJT formula were identified, along with 5 hub genes (IL6, AKT1, IL1B, VEGFA, and PTGS2), and the corresponding active compounds with the highest OB values were quercetin, aloe-emodin, and denudanolide b. Molecular docking results revealed the binding energy between quercetin, aloe-emodin, denudanolide b and 5 hub genes (IL6, AKT1, IL1B, VEGFA, and PTGS2) were -5.78 to -10.22 kcal/mol, the binding energy between dexamethasone and 5 hub genes were -6.3 to -9.7 kcal/mol. In addition, GO and KEGG analysis suggested significant enrichment of these genes in biological processes such as response to lipopolysaccharide, response to molecule of bacterial origin, and response to reactive oxygen species, as well as signaling pathways like AGE-RAGE signaling pathway in diabetic complications, Lipid and atherosclerosis, and IL-17 signaling pathway. The YJT formula has therapeutic effects in an allergic rhinitis mouse model, with the main active components being quercetin, aloe-emodin, and denudanolide b, and the key targets being IL6, AKT1, IL1B, VEGFA, and PTGS2, involving multiple signaling pathways.

MiR-21-5p modulates LPS-induced acute injury in alveolar epithelial cells by targeting SLC16A10

Sepsis is a systemic inflammatory response syndrome resulting from the invasion of the human body by bacteria and other pathogenic microorganisms. One of its most prevalent complications is acute lung injury, which places a significant medical burden on numerous countries and regions due to its high morbidity and mortality rates. MicroRNA (miRNA) plays a critical role in the body's inflammatory response and immune regulation. Recent studies have focused on miR-21-5p in the context of acute lung injury, but its role appears to vary in different models of this condition. In the LPS-induced acute injury model of A549 cells, there is differential expression, but the specific mechanism remains unclear. Therefore, our aim is to investigate the changes in the expression of miR-21-5p and SLC16A10 in a type II alveolar epithelial cell injury model induced by LPS and explore the therapeutic effects of their targeted regulation. A549 cells were directly stimulated with 10 µg/ml of LPS to construct a model of LPS-induced cell injury. Cells were collected at different time points and the expression of interleukin 1 beta (IL-1β), tumor necrosis factor-α (TNF-α) and miR-21-5p were measured by RT-qPCR and western blot. Then miR-21-5p mimic transfection was used to up-regulate the expression of miR-21-5p in A549 cells and the expression of IL-1β and TNF-α in each group of cells was measured by RT-qPCR and western blot. The miRDB, TargetScan, miRWalk, Starbase, Tarbase and miR Tarbase databases were used to predict the miR-21-5p target genes and simultaneously, the DisGeNet database was used to search the sepsis-related gene groups. The intersection of the two groups was taken as the core gene. Luciferase reporter assay further verified SLC16A10 as the core gene with miR-21-5p. The expression of miR-21-5p and SLC16A10 were regulated by transfection or inhibitors in A549 cells with or without LPS stimulation. And then the expression of IL-1β and TNF-α in A549 cells was tested by RT-qPCR and western blot in different groups, clarifying the role of miR-21-5p-SLC16A10 axis in LPS-induced inflammatory injury in A549 cells. (1) IL-1β and TNF-α mRNA and protein expression significantly increased at 6, 12, and 24 h after LPS stimulation as well as the miR-21-5p expression compared with the control group (P < 0.05). (2) After overexpression of miR-21-5p in A549 cells, the expression of IL-1β and TNF-α was significantly reduced after LPS stimulation, suggesting that miR-21-5p has a protection against LPS-induced injury. (3) The core gene set, comprising 51 target genes of miR-21-5p intersecting with the 1448 sepsis-related genes, was identified. This set includes SLC16A10, TNPO1, STAT3, PIK3R1, and FASLG. Following a literature review, SLC16A10 was selected as the ultimate target gene. Dual luciferase assay results confirmed that SLC16A10 is indeed a target gene of miR-21-5p. (4) Knocking down SLC16A10 expression by siRNA significantly reduced the expression of IL-1β and TNF-α in A549 cells after LPS treatment (P < 0.05). (5) miR-21-5p inhibitor increased the expression levels of IL-1β and TNF-α in A549 cells after LPS stimulation (P < 0.05). In comparison to cells solely transfected with miR-21-5p inhibitor, co-transfection of miR-21-5p inhibitor and si-SLC6A10 significantly reduced the expression of IL-1β and TNF-α (P < 0.05). MiR-21-5p plays a protective role in LPS-induced acute inflammatory injury of A549 cells. By targeting SLC16A10, it effectively mitigates the inflammatory response in A549 cells induced by LPS. Furthermore, SLC16A10 holds promise as a potential target for the treatment of acute lung injury.

Exploring the Mechanisms of Yuanhu Zhitong Oral Liquid for Primary Dysmenorrhea through Network Pharmacology, Molecular Docking, and Molecular Dynamics Simulation

Objective: Primary dysmenorrhea (PD) is a prevalent gynecological disorder. Yuanhu Zhitong oral liquid (YHZT) presents a promising alternative treatment for PD. However, the mechanisms underlying its efficacy remain unclear. This study aims to investigate the potential targets and mechanisms of action of YHZT in treating PD using network pharmacology, molecular docking, and molecular dynamics simulations. Methods: Potential compounds from YHZT were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and the Traditional Chinese Medicine Information Database (TCMID). The relevant targets of these compounds were identified using the similarity ensemble approach (SEA) and the Swiss Target Prediction database. PD-related targets were retrieved from the Genecards, DrugBank, and Disgenet databases. ClusterProfiler was utilized for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. The compound-target-pathway (CTP) network was constructed to facilitate the identification of key compounds, core targets, and signaling pathways. Finally, molecular docking and molecular dynamics simulations were performed to evaluate the interactions between the targets and compounds. Results: A total of 153 putative compounds and 129 targets of YHZT were identified. Network topology analysis revealed eight core targets and six key compounds. The effects of YHZT were mediated by genes associated with hormone and steroid metabolism, as well as pathways involved in steroid hormone biosynthesis and cytochrome P450 enzymes. Docking results showed free-binding energies ranging from -6.06 to -10.85 kcal/mol, indicating strong binding affinity between the compounds and targets. Molecular dynamics simulation results further confirmed the stability of these interactions. Conclusion: This study demonstrates that YHZT treats PD by suppressing inflammatory reactions and modulating hormone and cytochrome P450 concentrations. Key compounds such as ferulic acid, (R)-canadine, (S)-canadine, canadine, and asristolone are implicated in this process. These findings offer insights into the mechanisms underlying the action of YHZT and provide a foundation for further research in this area.

Genetic-driven biomarkers for liver fibrosis through bioinformatic approach

BackgroundLiver fibrosis is a widespread chronic liver ailment linked to substantial mortality and limited therapeutic options. An in-depth comprehension of the genetic underpinnings of liver fibrogenesis is crucial for the development of effective management and treatment approaches.ResultsUsing bioinformatics tools and the DisGeNET database, we pinpointed 105 genes significantly linked to liver fibrosis. Subsequently, we conducted functional assessments, incorporating gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and the STRING database, to construct protein–protein interaction networks (PPI) for these 105 liver fibrosis-associated genes. These analyses were executed via the WebGestalt 2019 online platform. We employed Cytoscape plugins, MCODE, and CytoHubba, to identify potential biomarker genes from these functional networks. Noteworthy hub genes encompassed TGF-β1, MMP2, CTNNB1, FGF2, IL6, LOX, CTGF, SMAD3, ALB, and VEGFA. TGF-β1 and MMP-2 exhibited substantial promise as liver fibrosis biomarkers, as denoted by their high systemic scores determined through the MCC algorithm in the CytoHubba methodology.ConclusionsIn summary, this study presents a robust genetic biomarker strategy that may prove invaluable in the identification of potential liver fibrosis biomarkers.

Exploring the efficacy and molecular mechanism of Danhong injection comprehensively in the treatment of idiopathic pulmonary fibrosis by combining meta-analysis, network pharmacology, and molecular docking methods.

Danhong injection, a compound injection of Chinese herbal medicine, has been widely used in idiopathic pulmonary fibrosis (IPF) at present as an adjuvant treatment. However, the clinical efficacy and molecular mechanism of IPF are still unclear. This study will evaluate and explore the clinical efficacy and molecular mechanism of Danhong injection in the treatment of IPF. In meta-analysis, the computer was used to search 8 databases (PubMed, EMbase, CENTRAL, MEDLINE, CBM, CNKI, WanFang, and VIP) to collect the RCTs, and RevMan 5.3 and Stata 14.0 were used for statistical analysis. It has been registered on PROSPERO: CRD42020221096. In network pharmacology, the main chemical components and targets of the chemical components of Danhong injection were obtained in TCMSP and Swiss Target Prediction databases. The main targets of IPF were obtained through Gencards, Disgenet, OMIM, TTD, and DRUGBANK databases. The String platform was used to construct PPI networks. Cytoscape 3.8.2 was used to construct the "Danhong components - IPF targets-pathways" network. The molecular docking verification was conducted by Auto Dock. Twelve RCTs were finally included with a total of 896 patients. The meta-analysis showed that Danhong injection could improve the clinical efficiency ([OR] = 0.25, 95% CI [0.15, 0.41]), lung function, arterial blood gas analysis, inflammatory cytokines, and serum cytokines associated with pulmonary fibrosis of IPF patients, respectively (P < .05). The core active components of Danhong injection on IPF were Luteolin, Quercetin, and Kaempferol, and the core targets were PTGS2, AR, ESR1, PPARG, and RELA. Danhong injection mainly improved IPF through PD-L1 expression and PD-1 checkpoint path in cancer, pathways in cancer, PI3K-Akt signaling pathway, etc. These results provided scientific basis for the clinical use of Danhong injection for the treatment of IPF, and provided a new direction to explore the potential mechanism of action of Danhong injection.

Exploring the mechanism of agarwood moxa smoke in treating sleep disorders based on GC-MS and network pharmacology.

Agarwood moxibustion is a folk therapy developed by individuals of the Li nationality in China. There is evidence that agarwood moxa smoke (AMS) generated during agarwood moxibustion therapy can treat sleep disorders via traditional Chinese medicines' multiple target and pathway characteristics. However, the specific components and mechanisms involved have yet to be explored. GC-MS (Gas Chromatography-Mass Spectrometry) and network pharmacology were used to investigate AMS's molecular basis and mechanism in treating sleep deprivation. GC-MS was used to determine the chemical composition of AMS; component target information was collected from TCMSP (Traditional Chinese Medicine Systems Pharmacology), PubChem (Public Chemical Database), GeneCards (Human Gene Database), and DisGeNet (Database of Genes and Diseases) were used to identify disease targets, and JVenn (Joint Venn) was used to identify the common targets of AMS and sleep disorders. STRING was used to construct a protein interaction network, Cytoscape 3.9.1 was used to build a multilevel network diagram of the "core components-efficacy targets-action pathways," the targets were imported into Metascape and DAVID for GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) analyses and Autodock was used for molecular docking. This research used a network pharmacology methodology to investigate the therapeutic potential of Agarwood Moxa Smoke (AMS) in treating sleep problems. Examining the target genes and chemical constituents of AMS offers insights into the molecular processes and targets of the disease. Nine active ingredients comprising anti-inflammatory substances and antioxidants, such as caryophyllene and p-cymene, found seven sleep-regulating signaling pathways and eight targets linked to sleep disorders. GC-MS was used to identify the 94 active ingredients in AMS, and the active ingredients had strong binding with the key targets. Key findings included active components with known medicinal properties, such as p-cymene, eucalyptol, and caryophyllene. An investigation of network pharmacology revealed seven signaling pathways for sleep regulation and eight targets linked to sleep disorders, shedding light on AMS's effectiveness in enhancing sleep quality. AMS may alleviate sleep disorders by modulating cellular and synaptic signaling, controlling hormone and neurotransmitter pathways, etc. Understanding AMS's material basis and mechanism of action provides a foundation for future research on treating sleep disorders with AMS. According to the study, Agarwood Moxa Smoke (AMS) may improve sleep quality by modifying cellular and synaptic signaling pathways for those who suffer from sleep problems. This might lead to the development of innovative therapies with fewer side effects.

Decoding common genetic alterations between Barrett's esophagus and esophageal adenocarcinoma: A bioinformatics analysis

BackgroundEsophageal adenocarcinoma (EAC) is a common cancer with a poor prognosis in advanced stages. Therefore, early EAC diagnosis and treatment have gained attention in recent decades. It has been found that various pathological changes, particularly Barrett's Esophagus (BE), can occur in the esophageal tissue before the development of EAC. In this study, we aimed to identify the molecular contributor in BE to EAC progression by detecting the essential regulatory genes that are differentially expressed in both BE and EAC. Materials and methodsWe conducted a comprehensive bioinformatics analysis to detect BE and EAC-associated genes. The common differentially expressed genes (DEGs) and common single nucleotide polymorphisms (SNPs) were detected using the GEO and DisGeNET databases, respectively. Then, hub genes and the top modules within the protein-protein interaction network were identified. Moreover, the co-expression network of the top module by the HIPPIE database was constructed. Additionally, the gene regulatory network was constructed based on miRNAs and circRNAs. Lastly, we inspected the DGIdb database for possible interacted drugs. ResultsOur microarray dataset analysis identified 92 common DEGs between BE and EAC with significant enrichment in skin and epidermis development genes. The study also identified 22 common SNPs between BE and EAC. The top module of PPI network analysis included SCEL, KRT6A, SPRR1A, SPRR1B, SPRR3, PPL, SPRR2B, EVPL, and CSTA. We constructed a ceRNA network involving three specific mRNAs, 23 miRNAs, and 101 selected circRNAs. According to the results from the DGIdb database, TD101 was found to interact with the KRT6A gene. ConclusionThe present study provides novel potential candidate genes that may be involved in the molecular association between Esophageal adenocarcinoma and Barrett's Esophagus, resulting in developing the diagnostic tools and therapeutic targets to prevent progression of BE to EAC.

Network Pharmacology Study on Herb Pair Bletilla striata-Galla chinensis in the Treatment of Chronic Skin Ulcers.

Herb pair Bletilla striata-Galla chinensis (BS-GC) is a classic combination of topical traditional Chinese medicine formulae in the treatment of chronic skin ulcers (CSUs). The aim of this study is to explore the effective active ingredients of BS-GC, as well as the core targets and signal transduction pathways of its action on CSUs. The ingredients of BS-GC were obtained from TCMSP and HERB databases. The targets of all active ingredients were retrieved from the SwissTargetPrediction database. The targets of CSUs were obtained from OMIM, GeneCards, Drugbank, and DisGeNET databases. A drug-disease target protein-protein interaction (PPI) network was constructed to select the most core targets, and an herb-ingredient-target network was built by utilizing Cytoscape 3.7.2. Furthermore, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes database (KEGG) analysis and verified the results of network pharmacology through molecular docking. A total of 40 active ingredients from the herb pair BS-GC were initially screened, and a total of 528 targets were retrieved. Meanwhile, the total number of CSU targets was 1032. Then, the number of common targets between BS-GC and CSUs was 107. The 13 core targets of herb pair BS-GC with CSUs were filtered out according to the PPI network, including AKT1, TNF, EGFR, BCL2, HIF1A, MMP-9, etc. The 5 main core active ingredients were 1-(4-Hydroxybenzyl)-2-methoxy-9,10-dihydrophenanthrene-4,7-diol, 1-(4- Hydroxybenzyl)-4-methoxy-9,10-dihydrophenanthrene-2,7-diol, physcion, dihydromyricetin, and myricetin. The main biological processes were inflammation, oxidative stress, and immune response, involving the AGE-RAGE signaling pathway in diabetic complications, HIF-1 signaling pathway, NF-κB signaling pathway, and calcium signaling pathway. Molecular docking results showed good binding activity between the 5 main core active ingredients and 13 core targets. This study predicted the core targets and signal transduction pathways in the treatment of CSUs to provide a reference for further molecular mechanism research.

Elucidating the Mechanism of Buyanghuanwu Decoction Acting on Pulmonary Fibrosis based on Network Pharmacology and Animal Studies.

Buyanghuanwu Decoction (BYHWD) is a clinically proven prescription effective in treating pulmonary fibrosis (PF), but the molecular mechanism underlying its action remains unclear. The network pharmacology analysis was performed to elucidate the acting substances and related pathways of BYHWD in treating bleomycin (BLM) induced PF mouse. First, the pharmacologically active components and corresponding targets in BYHWD were identified through the TCMSP database and literature review. Second, PF¬-related targets were identified through the DisGeNet database. Then, the components-targets network of BYHWD in PF treatment was constructed using Cytoscape. The DAVID database was used for the enrichment analysis of GO terms and KEGG pathways. At last, the therapeutic effect of BYHWD on BLM-induced PF mice were verified, and the mRNA and protein expression of related targets was determined through RT-PCR and western blotting, respectively. The core component-target network contained 58 active components and 147 targets. Thirty-nine core targets were mainly involved in the regulation of biological functions and KEGG pathways, such as the positive regulation of nitric oxide biosynthesis and the TNF signaling pathway. These core targets were obtained through enrichment analysis. Moreover, animal studies revealed that BYHWD down-regulated the mRNA expression levels of TNF, IL-6, IL-1β, and NOS2 and inhibited NF-κB and p38 phosphorylation. The effects of BYHWD on PF mice are therapeutic, and its anti-PF mechanism mainly involves the effects on inflammatory factors and the NF-κB/p38 pathway.

Revealing the potential bioactive components and mechanism of Qianhua Gout Capsules in the treatment of gouty arthritis through network pharmacology, molecular docking and pharmacodynamic study strategies

Recent clinical studies have confirmed the effectiveness of Qianhua Gout Capsules (QGC) in the treatment of gouty arthritis (GA). However, the specific regulatory targets and mechanisms of action of QGC are still unclear. To address this gap, we utilized network pharmacology, molecular docking, and pharmacodynamic approaches to investigate the bioactive components and associated mechanisms of QGC in the treatment of GA. By employing UPLC-Q Exactive-MS, we identified the compounds present in QGC, with active ingredients defined as those with oral bioavailability ≥30 % and drug similarity ≥0.18. Subsequently, the targets of these active compounds were determined using the TCMSP database, while GA-related targets were identified from DisGeNET, GeneCards, TTD, OMIM, and DrugBank databases. Further analysis including PPI analysis, GO analysis, and KEGG pathway enrichment was conducted on the targets. Validation of the predicted results was performed using a GA rat model, evaluating pathological changes, inflammatory markers, and pathway protein expression. Our results revealed a total of 130 components, 44 active components, 16 potential shared targets, GO-enriched terms, and 47 signaling pathways related to disease targets. Key active ingredients included quercetin, kaempferol, β-sitosterol, luteolin, and wogonin. The PPI analysis highlighted five targets (PPARG, IL-6, MMP-9, IL-1β, CXCL-8) with the highest connectivity, predominantly enriched in the IL-17 signaling pathway. Molecular docking experiments demonstrated strong binding of CXCL8, IL-1β, IL-6, MMP9, and PPARG targets with the top five active compounds. Furthermore, animal experiments confirmed the efficacy of QGC in treating GA in rats, showing reductions in TNF-α, IL-6, and MDA levels, and increases in SOD levels in serum. In synovial tissues, QGC treatment upregulated CXCL8 and PPARG expression, while downregulating IL-1β, MMP9, and IL-6 expression. In conclusion, this study applied a network pharmacology approach to uncover the composition of QGC, predict its pharmacological interactions, and demonstrate its in vivo efficacy, providing insights into the anti-GA mechanisms of QGC. These findings pave the way for future investigations into the therapeutic mechanisms underlying QGC's effectiveness in the treatment of GA.

Identification of renal protective gut microbiome derived-metabolites in diabetic chronic kidney disease: An integrated approach using network pharmacology and molecular docking

Metabolites from the gut microbiota define molecules in the gut-kidney cross talks. However, the mechanistic pathway by which the kidneys actively sense gut metabolites and their impact on diabetic chronic kidney disease (DCKD) remains unclear. This study is an attempt to investigate the gut microbiome metabolites, their host targeting genes, and their mechanistic action against DCKD.Gut microbiome, metabolites, and host targets were extracted from the gutMgene database and metabolites from the PubChem database. DCKD targets were identified from DisGeNET, GeneCard, NCBI, and OMIM databases. Computational examination such as protein–protein interaction networks, enrichment pathway, identification of metabolites for potential targets using molecular docking, hubgene-microbes-metabolite-samplesource-substrate (HMMSS) network architecture were executed using Network analyst, ShinyGo, GeneMania, Cytoscape, Autodock tools. There were 574 microbial metabolites, 2861 DCKD targets, and 222 microbes targeting host genes. After screening, we obtained 27 final targets, which are used for computational examination. From enrichment analysis, we found NF-ΚB1, AKT1, EGFR, JUN, and RELA as the main regulators in the DCKD development through mitogen activated protein kinase (MAPK) pathway signalling. The (HMMSS) network analysis found F.prausnitzi, B.adolescentis,and B.distasonisprobiotic bacteriathat are found in the intestinal epithelium, colonic region, metabolize the substrates like tryptophan, other unknown substrates might have direct interaction with the NF-kB1 and epidermal growth factor receptor (EGFR) targets. On docking of these target proteins with 3- Indole propionic acid (IPA) showed high binding energy affinity of -5.9 kcal/mol and -7.4kcal/mol.From this study we identified, the 3 IPA produced byF. prausnitzi A2-165was found to have renal sensing properties inhibiting MAPK/NF-KB1 inflammatory pathway and would be useful in treating CKD in diabetics.

Yantiao Formula Intervention in Rats with Sepsis: Network Pharmacology and Experimental Analysis.

Traditional Chinese Medicine prescribes Yantiao Formula (YTF; peach kernel, mirabilite, Angelica sinensis, Radix Scrophulariae, raw rhubarb, Radix Paeoniae, Flos Lonicerae, Forsythia and Ophiopogon japonicus) to treat sepsis. Clinically, it reduced the inflammatory response of sepsis. It also reduced lung damage by decreasing the level of TNF-α in septic rats' serum. Using network pharmacology analysis, we investigated the efficacy network and mechanism of YTF in treating sepsis. We used the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and a Bioinformatics Analysis Tool for Molecular Mechanisms of Traditional Chinese Medicine (BATMAN-TCM) combined with literature to collect the main components in YTF and their targets. DisGeNET and GENECARDS databases were used for sepsis-related targets. Cytoscape 3.7.1 software was used to construct the herbcomponent- target and ingredient-target-disease interaction protein-protein interaction networks of YTF. The jvenn was used to perform the intersection of YTF targets and sepsis targets. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed． We also created a sepsis rat model using cecal ligation and perforation and stimulated alveolar macrophages (NR8383) with endotoxin to investigate the mechanisms of YTF. GO, and KEGG enrichment analysis revealed that these targets involved mineralocorticoid secretion, aldosterone secretion, active regulation of chronic inflammatory response, the exogenous coagulation pathway, and other pathophysiology. It was linked to various inflammatory factors and the MAPK pathway. YTF inhibits the p38MAPK pathway and decreases TNF- α, IL-6, and CXCL8 levels. YTF has a multi-component, multi-target, and multi-channel role in treating sepsis. The primary mechanisms may involve inhibiting the p38MAPK pathway to reduce the inflammatory response.

Mechanism of Fuzheng Huayu Tablets against hepatic fibrosis based on transcriptome and single-cell sequencing

This study aimed to investigate the role of macrophage polarization in the treatment of liver fibrosis by Fuzheng Huayu Tablets(FZHY) through single-cell, transcriptome sequencing and in vitro and in vivo experiments. Liver fibrosis-related datasets, transcriptomic datasets, and single-cell sequencing datasets were obtained from the Gene Expression Omnibus(GEO) database to screen differential genes. Liver fibrosis-related genes were obtained from GeneCards, DisGeNET, NCBI, PharmgKB, TTD and OMIM databases. Macrophage polarization-related genes were obtained from the GeneCards database. The above three gene sets were intersected to construct a protein-protein interaction(PPI) network. Cytoscape software was used to screen core proteins, and the expression pattern of core proteins was visualized by single-cell sequencing. A mouse model of liver fibrosis was constructed using carbon tetrachloride(CCl_4). Hematoxylin-eosin(HE) staining and Masson staining were used to observe the pathological morphology of liver tissues. The expressions of α-smooth muscle actin(α-SMA) and transforming growth factor-β1(TGF-β1) were detected by immunohistochemistry. The levels of alanine aminotransferase(ALT) and aspartate aminotransferase(AST) were detected by colorimetry. The le-vels of inflammatory factors in serum were detected by the enzyme-linked immunosorbent assay(ELISA). Furthermore, the expressions of α-SMA, TGF-β1, cluster of differentiation 86(CD86) and thrombospondin 1(THBS1) in liver tissues were detected by Western blot(WB). Lipopolysaccharide(LPS) was used to stimulate RAW264.7 cells to construct the M1 macrophage polarization model. The cell counting kit-8(CCK-8) method was used to detect cell viability. WB was used to detect the protein expressions of CD86 and THBS1 in cells, and the messenger ribonucleic acid(mRNA) expression levels of tumor necrosis factor-α(TNF-α) and interleukin(IL)-1β by real-time fluorescent quantitative reverse transcription polymerase chain reaction(RT-qPCR). The results showed that a total of 26 potential genes related to the polarization of liver fibrosis macrophages were obtained, and 10 core proteins related to the polarization of liver fibrosis macrophages such as THBS1, lumican(LUM) and fibulin-5(FBLN5) were screened. Single-cell data analysis indicated that THBS1, ranking highest, may be expressed by M1 macrophages. Animal experiments demonstrated that FZHY reduced inflammatory cell infiltration and collagen deposition in CCl_4-induced mouse liver, relieved liver injury and inflammation levels, and inhibited the expressions of α-SMA, TGF-β1, CD86, and THBS1 proteins. Cell experiments revealed that FZHY significantly reduced intracellular expression of CD86 and THBS1 proteins and mRNA levels of TNF-α and IL-1β. In conclusion, FZHY may ameliorate liver fibrosis by inhibiting THBS1 protein expression, suppressing M1 macrophage polarization, and reducing inflammation.

Identifying allergic-rhinitis-associated genes with random-walk-based method in PPI network

Allergic rhinitis is a common allergic disease with a complex pathogenesis and many unresolved issues. Studies have shown that the incidence of allergic rhinitis is closely related to genetic factors, and research on the related genes could help further understand its pathogenesis and develop new treatment methods. In this study, 446 allergic rhinitis-related genes were obtained on the basis of the DisGeNET database. The protein–protein interaction network was searched using the random-walk-with-restart algorithm with these 446 genes as seed nodes to assess the linkages between other genes and allergic rhinitis. Then, this result was further examined by three screening tests, including permutation, interaction, and enrichment tests, which aimed to pick up genes that have strong and special associations with allergic rhinitis. 52 novel genes were finally obtained. The functional enrichment test confirmed their relationships to the biological processes and pathways related to allergic rhinitis. Furthermore, some genes were extensively analyzed to uncover their special or latent associations to allergic rhinitis, including IRAK2 and MAPK, which are involved in the pathogenesis of allergic rhinitis and the inhibition of allergic inflammation via the p38-MAPK pathway, respectively. The new found genes may help the following investigations for understanding the underlying molecular mechanisms of allergic rhinitis and developing effective treatments.

Deciphering the Systemic Impact of Herbal Medicines on Allergic Rhinitis: A Network Pharmacological Approach.

Allergic rhinitis (AR) is a systemic allergic disease that has a considerable impact on patients' quality of life. Current treatments include antihistamines and nasal steroids; however, their long-term use often causes undesirable side effects. In this context, traditional Asian medicine (TAM), with its multi-compound, multi-target herbal medicines (medicinal plants), offers a promising alternative. However, the complexity of these multi-compound traits poses challenges in understanding the overall mechanisms and efficacy of herbal medicines. Here, we demonstrate the efficacy and underlying mechanisms of these multi-compound herbal medicines specifically used for AR at a systemic level. We utilized a modified term frequency-inverse document frequency method to select AR-specific herbs and constructed an herb-compound-target network using reliable databases and computational methods, such as the Quantitative Estimate of Drug-likeness for compound filtering, STITCH database for compound-target interaction prediction (with a high confidence score threshold of 0.7), and DisGeNET and CTD databases for disease-gene association analysis. Through this network, we conducted AR-related targets and pathway analyses, as well as clustering analysis based on target-level information of the herbs. Gene ontology enrichment analysis was conducted using a protein-protein interaction network. Our research identified 14 AR-specific herbs and analyzed whether AR-specific herbs are highly related to previously known AR-related genes and pathways. AR-specific herbs were found to target several genes related to inflammation and AR pathogenesis, such as PTGS2, HRH1, and TBXA2R. Pathway analysis revealed that AR-specific herbs were associated with multiple AR-related pathways, including cytokine signaling, immune response, and allergic inflammation. Additionally, clustering analysis based on target similarity identified three distinct subgroups of AR-specific herbs, corroborated by a protein-protein interaction network. Group 1 herbs were associated with the regulation of inflammatory responses to antigenic stimuli, while Group 2 herbs were related to the detection of chemical stimuli involved in the sensory perception of bitter taste. Group 3 herbs were distinctly associated with antigen processing and presentation and NIK/NF-kappa B signaling. This study decodes the principles of TAM herbal configurations for AR using a network pharmacological approach, providing a holistic understanding of drug effects beyond specific pathways.