Mechanism of tangshen formula in treating diabetic nephropathy revealed by network pharmacology approach.
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SUBMITTER: Quan N
PROVIDER: S-EPMC8425243 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ObjectiveInflammation and fibrosis are essential promoters in the pathogenesis of diabetic nephropathy (DN) in type 2 diabetes. The present study examined the anti-inflammation and anti-fibrosis effect of Tangshen Formula (TSF), a traditional Chinese medicine, on DN.Research design and methodsProtective role of TSF in DN was examined in a rat model of type 2 DN that was established by high-fat diet-fed and low-dose-streptozotocin injection. TSF was suspended in 0.5% CMC-Na solution and delivered by oral gavage at a dosage of 1.67g/Kg body weight/day. The therapeutic effects and mechanisms of TSF on diabetic kidney injury were examined.ResultsWe found that TSF treatment for 20 weeks attenuated DN by significantly inhibiting urinary excretion of albumin and renal histological injuries. These beneficial effects were associated with an inactivation of NF-?B signaling, thereby blocking the upregulation of pro-inflammatory cytokines (IL-1?, TNF?), chemokine (MCP-1), and macrophage infiltration in the TSF-treated rats with type 2 DN. In addition, TSF treatment also inactivated TGF-?/Smad3 signaling and therefore suppressed renal fibrosis including expressions of fibronectin, collagen I, and collagen IV. Further studies revealed that the inhibitory effect of TSF on TGF-?/Smad3 and NF-?B signaling in DN was associated with inhibition of Smurf2-dependent ubiquitin degradation of Smad7.ConclusionsThe present study reveals that TSF has therapeutic potential for type 2 DN in rats. Blockade of NF-?B-driven renal inflammation and TGF-?/Smad3-mediated renal fibrosis by preventing the Smurf2-mediated Smad7 degradation pathway may be mechanisms through which TSF inhibits type 2 DN.
| S-EPMC4726711 | biostudies-literature
Project description:Background: Chuanxiong Rhizoma is one of the traditional Chinese medicines which have been used for years in the treatment of diabetic nephropathy (DN). However, the mechanism of Chuanxiong Rhizoma in DN has not yet been fully understood. Methods: We performed network pharmacology to construct target proteins interaction network of Chuanxiong Rhizoma. Active ingredients were acquired from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform. DRUGBANK database was used to predict target proteins of Chuanxiong Rhizoma. Gene ontology (GO) biological process analyses and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were also performed for functional prediction of the target proteins. Molecular docking was applied for evaluating the drug interactions between hub targets and active ingredients. Results: Twenty-eight target genes fished by 6 active ingredients of Chuanxiong Rhizoma were obtained in the study. The top 10 significant GO analyses and 6 KEGG pathways were enriched for genomic analysis. We also acquired 1366 differentially expressed genes associated with DN from GSE30528 dataset, including five target genes: KCNH2, NCOA1, KDR, NR3C2 and ADRB2. Molecular docking analysis successfully combined KCNH2, NCOA1, KDR and ADRB2 to Myricanone with docking scores from 4.61 to 6.28. NR3C2 also displayed good docking scores with Wallichilide and Sitosterol (8.13 and 8.34, respectively), revealing good binding forces to active compounds of Chuanxiong Rhizoma. Conclusions: Chuanxiong Rhizoma might take part in the treatment of DN through pathways associated with steroid hormone, estrogen, thyroid hormone and IL-17. KCNH2, NCOA1, KDR, ADRB2 and NR3C2 were proved to be the hub targets, which were closely related to corresponding active ingredients of Chuanxiong Rhizoma.
| S-EPMC7484651 | biostudies-literature
Project description:ObjectiveTo systematically study the mechanism of cordyceps cicadae in the treatment of diabetic nephropathy (DN) with the method of network pharmacology and molecular docking analysis, so as to provide theoretical basis for the development of new drugs for the treatment of DN.MethodsTCMSP, Symmap, PubChem, PubMed, and CTD database were used to predict and screen the active components and therapeutic targets for DN. The network of active components and targets was drawn by Cytoscape 3.6.0, the protein-protein interaction (PPI) was analyzed by the STRING database, and the DAVID database was used for the enrichment analysis of intersection targets. Molecular docking studies were finished by Discovery Studio 3.5.ResultsA total of 36 active compounds, including myriocin, guanosine, and inosine, and 378 potential targets of cordyceps cicadae were obtained. PPI network analysis showed that AKT1, MAPK8, and TP53 and other targets were related to both cordyceps cicadae and DN. GO and KEGG pathway analysis showed that these targets were mostly involved in R-HSA-450341, 157.14-3-3 cell cycle, and PDGF pathways. Docking studies suggested that myriocin can fit in the binding pocket of two target proteins (AKT1 and MAPK8).ConclusionActive ingredients of cordyceps cicadae such as myriocin may act on DN through different targets such as AKT1, MAPK8, and TP53 and other targets, which can help to develop innovative drugs for effective treatment of DN.
| S-EPMC8492289 | biostudies-literature
Project description:BackgroundDiabetic nephropathy (DN) is a common and serious complication of diabetes, but without a satisfactory treatment strategy till now. Liuwei Dihuang pills (LDP), an effective Chinese medicinal formula, has been used to treat DN for more than 1000 years. However, its underlying mechanism of action is still vague.MethodsActive compounds and corresponding targets of LDP were predicted from the TCMSP database. DN disease targets were extracted from the OMIM, GeneCards, TTD, DisGeNET, and DrugBank databases. Subsequently, the "herbal-compound-target" network and protein-protein interaction (PPI) network were constructed and analyzed via the STRING web platform and Cytoscape software. GO functional and KEGG pathway enrichment analyses were carried out on the Metascape web platform. Molecular docking utilized AutoDock Vina and PyMOL software.Results41 active components and 186 corresponding targets of LDP were screened out. 131 common targets of LDP and DN were acquired. Quercetin, kaempferol, beta-sitosterol, diosgenin, and stigmasterol could be defined as five crucial compounds. JUN, MAPK8, AKT1, EGF, TP53, VEGFA, MMP9, MAPK1, and TNF might be the nine key targets. The enrichment analysis showed that common targets were mainly associated with inflammation reaction, oxidative stress, immune regulation, and cell apoptosis. AGE-RAGE and IL-17 were the suggested two significant signal pathways. Molecular docking revealed that the nine key targets could closely bind to their corresponding active compounds.ConclusionThe present study fully reveals the multicompound's and multitarget's characteristics of LDP in DN treatment. Furthermore, this study provides valuable evidence for further scientific research of the pharmacological mechanisms and broader clinical application.
| S-EPMC8452392 | biostudies-literature
Project description:The commonly prescribed Tangshen Formula (TSF) is a traditional Chinese formulation that has been shown to reduce plasma lipid metabolism and proteinuria and improve the estimated glomerular filtration rate (eGFR) in patients with diabetic kidney disease. This study investigated the underlying mechanism whereby TSF regulates renal lipid accumulation and ameliorates diabetic renal injuries in spontaneous diabetic db/db mice and in vitro in sodium palmitate (PA)-stimulated and Abca1-SiRNA-transfected mouse tubular epithelial cells (mTECs). The results revealed that TSF treatment significantly ameliorated the renal injuries by lowering urinary albumin excretion and improving renal tissue injuries in diabetic (db/db) mice. Interestingly, the treatment with TSF also resulted in decreased cholesterol levels in the renal tissues of db/db mice, which was associated with increased expression of the peroxisome proliferator-activated receptor ? coactivator 1-? (PGC-1?), the Liver X receptors (LXR), and ATP-binding cassette subfamily A member 1 (ABCA1), suggesting that TSF might attenuate diabetic kidney injury via a mechanism associated with improving cholesterol efflux in the diabetic kidney. This was investigated in vitro in mTECs, and the results showed that TSF reduced the PA-stimulated cholesterol accumulation in mTECs. Mechanistically, the addition of TSF was capable of reversing PA-induced downregulation of PGC-1?, LXR, and ABCA1 expression and cholesterol accumulation in mTECs, suggesting that TSF might act the protection via the PGC-1?-LXR-ABCA1 pathway to improve the cholesterol efflux in the renal tissues of db/db mice. This was further confirmed by silencing ABCA1 to block the promotive effect of TSF on cholesterol efflux in vitro. In conclusion, TSF might ameliorate diabetic kidney injuries by promoting ABCA1-mediated renal cholesterol efflux.
| S-EPMC5897509 | biostudies-literature
Project description:ObjectiveTo elucidate the pharmacological mechanisms of Qubi Formula (QBF), a traditional Chinese medicine (TCM) formula which has been demonstrated as an effective therapy for psoriasis in China.MethodsThe Traditional Chinese Medicine Systems Pharmacology (TCMSP) database, BATMAN-TCM database, and literature search were used to excavate the pharmacologically active ingredients of QBF and to predict the potential targets. Psoriasis-related targets were obtained from Therapeutic Target Database (TTD), DrugBank database (DBD), MalaCards database, and DisGeNET database. Then, we established the network concerning the interactions of potential targets of QBF with well-known psoriasis-related targets by using protein-protein interaction (PPI) data in String database. Afterwards, topological parameters (including DNMC, Degree, Closeness, and Betweenness) were calculated to excavate the core targets of Qubi Formula in treating psoriasis (main targets in the PPI network). Cytoscape was used to construct the ingredients-targets core network for Qubi Formula in treating psoriasis, and ClueGO was used to perform GO-BP and KEGG pathway enrichment analysis on these core targets.ResultsThe ingredient-target-disease core network of QBF in treating psoriasis was screened to contain 175 active ingredients, which corresponded to 27 core targets. Additionally, enrichment analysis suggested that targets of QBF in treating psoriasis were mainly clustered into multiple biological processes (associated with nuclear translocation of proteins, cellular response to multiple stimuli (immunoinflammatory factors, oxidative stress, and nutrient substance), lymphocyte activation, regulation of cyclase activity, cell-cell adhesion, and cell death) and related pathways (VEGF, JAK-STAT, TLRs, NF-κB, and lymphocyte differentiation-related pathways), indicating the underlying mechanisms of QBF on psoriasis.ConclusionIn this work, we have successfully illuminated that Qubi Formula could relieve a wide variety of pathological factors (such as inflammatory infiltration and abnormal angiogenesis) of psoriasis in a "multicompound, multitarget, and multipathway" manner by using network pharmacology. Moreover, our present outcomes might shed light on the further clinical application of QBF on psoriasis treatment.
| S-EPMC7327573 | biostudies-literature
Project description:BackgroundHuangqi Gegen decoction (HGD), a Chinese herb formula, has been widely used to treat diabetic nephropathy in China, while the pharmacological mechanisms are still unclear. Therefore, the present study aims to explore the underlying mechanism of HGD for treating diabetic nephropathy (DN).Materials and methodsTraditional Chinese Medicine Systems Pharmacology Database (TCMSP), UniProt, and SwissTargetPrediction databases were used to search the active ingredients and potential targets of HGD. In addition, multiple disease-related databases were used to collect DN-related targets. Common targets of the protein-protein interaction (PPI) network were established using the STRING database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the DAVID database. At last, AutoDockVina was used to conduct molecular docking verification for the core components and targets.ResultsA total of 27 active ingredients and 354 putative identified target genes were screened from HGD, of which 99 overlapped with the targets of DN and were considered potential therapeutic targets. Further analysis showed that the HGD activity of quercetin, formononetin, kaempferol, isorhamnetin, and beta-sitosterol ingredients is possible through VEGFA, IL6, TNF, AKT1, and TP53 targets involved in TNF, toll-like receptors, and MAPK-related pathways, which have anti-inflammatory, antiapoptosis, antioxidation, and autophagy effects, relieve renal fibrosis and renal cortex injury, and improve renal function, thus delaying the development of DN. The molecular docking results showed that quercetin, formononetin, kaempferol, isorhamnetin, beta-sitosterol had a good binding activity with VEGFA, IL6, TNF, AKT1, and TP53.ConclusionThis study demonstrated that HGD might take part in the treatment of DN through multicomponent, multitarget, and multichannel combined action.
| S-EPMC8121566 | biostudies-literature
Project description:BackgroundGandi capsule is a traditional Chinese herbal formula used to promote blood circulation and removing blood stasis in clinical. Our previous study has shown that it reduces proteinuria with routine treatment in diabetic nephrophy (DN), but its pharmacological action mechanism is still unknown.MethodsTo facilitate the identification of components, a component database of Gandi capsule and target database of DN were established by ourselves. The components absorbed in blood circle were identified in rat plasma after oral administration of Gandi capsule by UHPLC-QQQ-MS/MS. The potential targets were screened by using Libdock tolls in Discovery studio 3.0. Then Pathway and Network analyses were used to enrich the screened targets. The possible targets were verified by using a surface plasmon resonance (SPR) test and the molecular mechanism focusing these targets for treating DN was clarified by western blot.ResultsSix components in Gandi capsule were identified detected in rat plasma after oral administration by UHPLC-QQQ-MS/MS. After molecular docking analyses in KEGG and Discovery studio, four protein targets including HNF4A, HMGCR, JAK3, and SIRT1, were screened out, and proved as effective binding with baicalin, wogonoside by SPR. And the molecular mechanism was clarified that baicalin and wogonoside inhibit the effect of high glucose (HG)-induced decreased cell viability and podocin expression, and strengthen the activation p-AKT, p-PI3K, and p-AMPK.ConclusionBaicalin and wogonoside were screened out to be the active compounds in Gandi capsule and can ameliorate HG-induced podocyte damage by influencing the AMPK and PI3K-AKT signaling pathways by binding with HNF4A, HMGCR, JAK3, and SIRT1.
| S-EPMC7685593 | biostudies-literature
Project description:ObjectiveTo investigate the potential mechanism of action of Yi-Qi-Huo-Xue-Tong-Luo formula (YQHXTLF) in the treatment of diabetic peripheral neuropathy (DPN).MethodsNetwork pharmacology and molecular docking techniques were used in this study. Firstly, the active ingredients and the corresponding targets of YQHXTLF were retrieved using the Traditional Chinese Medicine Systems Pharmacology (TCMSP) platform; subsequently, the targets related to DPN were retrieved using GeneCards, Online Mendelian Inheritance in Man (OMIM), Pharmgkb, Therapeutic Target Database (TTD) and Drugbank databases; the common targets of YQHXTLF and DPN were obtained by Venn diagram; afterwards, the "YQHXTLF Pharmacodynamic Component-DPN Target" regulatory network was visualized using Cytoscape 3.6.1 software, and Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed on the potential targets using R 3.6.3 software. Finally, molecular docking of the main chemical components in the PPI network with the core targets was verified by Autodock Vina software.ResultsA total of 86 active ingredients and 229 targets in YQHXTLF were screened, and 81 active ingredients and 110 targets were identified to be closely related to diabetic peripheral neuropathy disease. PPI network mapping identified TP53, MAPK1, JUN, and STAT3 as possible core targets. KEGG pathway analysis showed that these targets are mostly involved in AGE-RAGE signaling pathway in diabetic complications, TNF signaling pathway, and MAPK signaling pathway. The molecular docking results showed that the main chemical components of YQHXTLF have a stable binding activity to the core pivotal targets.ConclusionYQHXTLF may act on TP53, MAPK1, JUN, and STAT3 to regulate inflammatory response, apoptosis, or proliferation as a molecular mechanism for the treatment of diabetic peripheral neuropathy, reflecting its multitarget and multipathway action, and providing new ideas to further uncover its pharmacological basis and mechanism of action.
| S-EPMC8188603 | biostudies-literature
Project description:Dapagliflozin, an inhibitor of sodium-glucose cotransporter 2 (SGLT2), is a new type of oral hypoglycemic drugs which can promote glucose excretion in the kidney. Studies have shown that dapagliflozin has renoprotective effect in the treatment of type 2 diabetes. However, the underlying mechanism remains unclear. Here, we combined integrated RNA sequencing and network pharmacology approach to investigate the molecular mechanism of dapagliflozin for diabetic nephropathy (DN). Dapagliflozin significantly relieved glucose intolerance, urinary albumin/creatinine ratio (UACR) and renal pathological injuries of db/db mice. The LncRNA and mRNA expression in kidney tissues from control group (CR), db/db group (DN) and dapagliflozin group (DG) were assessed by RNA sequencing. We identified 7 LncRNAs and 64 mRNAs common differentially expressed in CR vs DN and DN vs DG, which were used to construct co-expression network to reveal significantly correlated expression patterns in DN. In addition, network pharmacology was used to predict the therapeutic targets of dapagliflozin and we constructed component-target-pathway network according to the results of RNA sequencing and network pharmacology. We found that SMAD9, PPARG, CD36, CYP4A12A, CYP4A12B, CASP3, H2-DMB2, MAPK1, MAPK3, C3 and IL-10 might be the pivotal targets of dapagliflozin for treating DN and these genes were mainly enriched in pathways including TGF-β signaling pathway, PPAR signaling pathway, Chemokine signaling pathway, etc. Our results have important implication and provide novel insights into the protective mechanism of dapagliflozin for treating DN.
| S-EPMC9533015 | biostudies-literature