Exploring the molecular mechanism of Xuebifang in the treatment of diabetic peripheral neuropathy based on bioinformatics and network pharmacology
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SUBMITTER: Hu F
PROVIDER: S-EPMC10881818 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature
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Project description:BackgroundDiabetic peripheral neuropathy (DPN) is one of the most common chronic complications of diabetes, which seriously affects the physical and mental health of patients. Sappan Lignum (SL) is effective in treating DPN. Previous reports have shown that SL has a clear hypoglycemic and anti-inflammatory effect. However, the study of SL in the treatment of DPN is still limited and rare.ObjectiveTo investigate the mechanism of SL in the treatment of DPN based on network pharmacology.MethodsThe active ingredients of SL were screened by related databases. The compound targets were collected by the target prediction platforms. The DPN-related targets were gathered through disease databases. The intersection targets were obtained by uploading the compound targets and disease targets to Venny 2.1.0, and a compound-target network was constructed by Cytoscape3.7.2. The protein-protein interaction (PPI) relationships were obtained by the STRING11.0 database. Genome Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed using the DAVID6.8 database. Molecular docking of key compounds and core targets was performed by DockThor.ResultsA total of 29 compounds and 51 intersection targets with potential therapeutic effects on DPN were obtained. The compound-target network construction resulted in four key compounds: protostemonine, 3-deoxysappanchalcone, 7,3',4'-trihydroxy-3-benzyl-2H-chromene, and o-12'-methylergocornine. PPI network analysis yielded 10 core targets: AKT1, MAPK3, CXCL8, TNF, OPRM1, MTOR, STAT3, MAPK8, SIRT1, and HSP90AA1. KEGG analysis resulted in 82 signaling pathways (P < 0.05), including insulin resistance, HIF-1 signaling pathway, and type II diabetes. The docking results indicated that the main active compounds could stably bind to core targets.ConclusionSL had the mechanism of multiple ingredients, multiple targets, and multiple pathways in the treatment of DPN. This study provided a scientific basis for further research on the treatment of DPN with SL and its extracts.
| S-EPMC8263209 | 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:BackgroundSalvianolic acid B (Sal B) is a bioactive component of Radix Salviae, which has antiinflammation and antiapoptotic activity in diabetic complications. However, the molecular mechanism of action of Sal B on diabetic peripheral neuropathy (DPN) is unknown. This study was designed to identify a mechanism for Sal B in the treatment of DPN by using a pharmacology network, molecular docking, and in vitro experiments.MethodsSal B and DPN-related targets from Gene Cards and OMIM platforms were retrieved and screened. Then, an analysis of possible targets with STRING and Cytoscape software was conducted. KEGG signaling pathways were determined using the R software. Subsequently, the binding capacity of Sal B to target proteins was analyzed by molecular docking and in vitro experiments.ResultsA total of 501 targets related to Sal B and 4662 targets related to DPN were identified. Among these targets, 108 intersection targets were shared by Sal B and DPN. After topological and cluster analysis, 11 critical targets were identified, including p38MAPK. KEGG analysis revealed that the AGE-RAGE signaling pathway likely plays an important role in Sal B action on DPN. The p38MAPK protein is a key target in the AGE-RAGE signaling pathway. Molecular docking results suggested that Sal B and p38MAPK have excellent binding affinity (<-5 kcal/mol). The in vitro experiments revealed that Sal B downregulates the expressions of p-P38MAPK, inflammatory cytokines, and apoptosis targets, which are upregulated by hyperglycemia.ConclusionSal B may alter DPN by inhibiting inflammation and apoptosis activated by p38MAPK.
| S-EPMC9440779 | biostudies-literature
Project description:ObjectiveBased on bioinformatics and network pharmacology, the treatment of Saussurea involucrata (SAIN) on novel coronavirus (COVID-19) was evaluated by the GEO clinical sample gene difference analysis, compound-target molecular docking, and molecular dynamics simulation. role in the discovery of new targets for the prevention or treatment of COVID-19, to better serve the discovery and clinical application of new drugs.Materials and methodsTaking the Traditional Chinese Medicine System Pharmacology Database (TCMSP) as the starting point for the preliminary selection of compounds and targets, we used tools such as Cytoscape 3.8.0, TBtools 1.098, AutoDock vina, R 4.0.2, PyMol, and GROMACS to analyze the compounds of SAIN and targets were initially screened. To further screen the active ingredients and targets, we carried out genetic difference analysis (n = 72) through clinical samples of COVID-19 derived from GEO and carried out biological process (BP) analysis on these screened targets (P ≤ 0.05)., gene = 9), KEGG pathway analysis (FDR≤0.05, gene = 9), protein interaction network (PPI) analysis (gene = 9), and compounds-target-pathway network analysis (gene = 9), to obtain the target Point-regulated biological processes, disease pathways, and compounds-target-pathway relationships. Through the precise molecular docking between the compounds and the targets, we further screened SAIN's active ingredients (Affinity ≤ -7.2 kcal/mol) targets and visualized the data. After that, we performed molecular dynamics simulations and consulted a large number of related Validation of the results in the literature.ResultsThrough the screening, analysis, and verification of the data, it was finally confirmed that there are five main active ingredients in SAIN, which are Quercitrin, Rutin, Caffeic acid, Jaceosidin, and Beta-sitosterol, and mainly act on five targets. These targets mainly regulate Tuberculosis, TNF signaling pathway, Alzheimer's disease, Pertussis, Toll-like receptor signaling pathway, Influenza A, Non-alcoholic fatty liver disease (NAFLD), Neuroactive ligand-receptor interaction, Complement and coagulation cascades, Fructose and mannose metabolism, and Metabolic pathways, play a role in preventing or treating COVID-19. Molecular dynamics simulation results show that the four active ingredients of SAIN, Quercitrin, Rutin, Caffeic acid, and Jaceosidin, act on the four target proteins of COVID-19, AKR1B1, C5AR1, GSK3B, and IL1B to form complexes that can be very stable in the human environment. Tertiary structure exists.ConclusionOur study successfully explained the effective mechanism of SAIN in improving COVID-19, and at the same time predicted the potential targets of SAIN in the treatment of COVID-19, AKR1B1, IL1B, and GSK3B. It provides a new basis and provides great support for subsequent research on COVID-19.
| S-EPMC9035664 | biostudies-literature
Project description:ObjectiveTo explore the mechanism of hirudin in the treatment of diabetic kidney disease (DKD).MethodCytoscape software was used to analyze the network between hirudin targets and active components in the treatment of DKD. The biological function and mechanism of effective targets of hirudin for DKD treatment were analyzed by the Database for Annotation, Visualization and Integrated Discovery (DAVID) database. Molecular docking technology was used to simulate the docking of key targets, and the DKD rat model was used to verify the first 4 key targets with high "Hydrogen number" among the top 10 targets verified by molecular docking.ResultsTotal of 12334 DKD targets were screened in GeneCards, OMIM and other databases, Hirudin and DKD had 247 common target genes, and the protein interaction network got 2115 edges. The DAVID database was used for the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis, confirming that hirudin in treatment of DKD involves multiple signaling pathways such as the forkhead box O signaling pathway, the phosphatidylinositol 3-kinase-protein kinase B signaling pathway, the vascular endothelial-derived growth factor signaling pathway and other signaling pathways. The top ten key targets of hirudin in treatment of DKD were verified by molecular docking. Animal experiments showed that hirudin could decrease the expression of caspase-3 in renal tissue of DKD rats, and increase the expression of RAC-alpha serine/threonine-protein kinase, Catalase, and Heat shock protein HSP 90-alpha in renal tissue of DKD rats.ConclusionThis study preliminarily reveals that hirudin treats DKD through multiple targets and pathways, and molecular docking and animal experiments indicates the feasibility of this study. Hirudin may be directly or indirectly involved in the regulation of cell metabolism, oxidative stress and other mechanisms in the treatment of DKD, which will lay the foundation for future molecular biological experiments of hirudin in the treatment of DKD.
| S-EPMC9924777 | biostudies-literature
Project description: Not available
| S-EPMC11319946 | 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:Chemotherapy-induced peripheral neuropathy (CIPN) is a common side effect of anticancer treatment, which may influence its successful completion. The Huang-Qi-Gui-Zhi-Wu-Wu decoction (HQGZWWD) has been widely used to treat CIPN in China although the pharmacological mechanisms involved have not been clarified. Using the network pharmacology approach, this study investigated the potential pathogenesis of CIPN and the therapeutic mechanisms exerted by the HQGZWWD herbal formula in CIPN. The targets of HQGZWWD were identified using traditional Chinese medicine (TCM) databases (TCMSP and ETCM) and prediction platforms (PharmMapper and TargetNet), and the genes of CIPN were collected by DisGeNET, GeneCards, and literature search. The common target interaction network between herbal formula and diseases was constructed by using Cytoscape. Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were used to reveal the mechanism and efficacy of HQGZWWD in the treatment of CIPN. A total of 153 CIPN-related genes were screened, and a protein-protein interaction (PPI) network with 96 nodes and 424 edges was constructed. Sixty-three active components were retrieved from HQGZWWD, with a herb-composite compound-target network including 748 nodes and 5448 edges. Forty-one targets belong to the above two networks. The analysis of network results and literature review shows that the main pathological processes of CIPN may be the inflammatory response and nerve injury, and HQGZWWD plays a therapeutic role in CIPN by regulating inflammatory response and repairing nerve injury, thus verifying the reliable efficacy of this herbal formula. In addition, we found two new potential therapeutic targets (CDK7 and GSTM2) warranting further investigation. This study fully illustrates that TCM has the characteristics of a multicompound, multitarget, and multipathway treatment, which is of great significance to study the curative effect of herbal formulations.
| S-EPMC7704154 | biostudies-literature
Project description:Background: Invasion is an important characteristic of the malignancy of glioblastoma (GBM) and a significant prognostic factor. Sempervirine (SPV), a yohimbine-type alkaloid, has been proven to inhibit GBM cells proliferation in previous research and found to have a potential effect in anti-invasion, but its mechanism of anti-invasion is still unknown. Methods: To explore its pharmacodynamics in inhibiting GBM cell invasion in this study, we combined network pharmacology and bioinformatics to comprehensive exploratory analysis of SPV and verified the mechanism in vitro. Results: Firstly, targets of SPV and invasion-related genes were collected from public databases. Moreover, GBM samples were obtained to analyze differentially expressed genes (DEGs) from The Cancer Genome Atlas (TCGA). Then, the relevant targets of SPV inhibiting GBM invasion (SIGI) were obtained through the intersection of the three gene sets. Further, GO and KEGG analysis showed that the targets of SIGI were heavily enriched in the AKT signaling pathway. Subsequently, based on the method of machine learning, a clinical prognostic model of the relevant targets of SIGI was constructed using GBM samples from TCGA and the Gene Expression Omnibus (GEO). A four-genes model (DUSP6, BMP2, MMP2, and MMP13) was successfully constructed, and Vina Scores of MMP2 and MMP13 in molecular docking were higher, which may be the main targets of SIGI. Then, the effect of SIGI was confirmed via functional experiments on invasion, migration, and adhesion assay, and the effect involved changes in the expressions of p-AKT, MMP2 and MMP13. Finally, combined with AKT activator (SC79) and inhibitor (MK2206), we further confirmed that SPV inhibits GBM invasion through AKT phosphorylation. Conclusions: This study provides valuable and an expected point of view into the regulation of AKT phosphorylation and inhibition of GBM invasion by SPV.
| S-EPMC11510114 | biostudies-literature
Project description:Gegensan (GGS) has been reported for the treatment of alcoholic liver disease (ALD), but its therapeutic mechanism is still unclear. This paper aims to determine the therapeutic mechanism and targets of action of GGS on alcoholic liver disease utilizing network pharmacology and bioinformatics. The active ingredients in GGS were screened in the literature and databases, and common targets of ALD were then obtained from public databases to construct the network diagram of traditional Chinese medicine-active ingredient targets. Based on the common targets, Gene Ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed to find target enrichment pathways, and the core targets were screened out by combining differential analysis and protein-protein interaction network analysis. Molecular docking was performed to verify the binding effect between the core targets and the corresponding active ingredients. ALD and GGS have 84 common targets, corresponding to 91 active ingredients. After subsequent differential analysis and protein-protein interaction network analysis, 10 core targets were identified. Gene Ontology and KEGG enrichment analyses showed that the main BPs corresponding to the common targets included the response to lipopolysaccharide, inflammatory response, etc. The KEGG pathways involved in the regulation of the common targets included the lipid-atherosclerosis pathway and the alcoholic liver disease pathway, etc. Further molecular docking showed that the core targets CYP1A1, CYP1A2, CXCL8, ADH1C, MMP1, SERPINE1, COL1A1, APOB, MMP1, and their corresponding 4 active ingredients, Naringenin, Kaempferol, Quercetin, and Stigmasterol, have a greater docking potential. The above results suggest that GGS can regulate lipid metabolism and inflammatory response in the ALD process, and alleviate the lipid accumulation and oxidative stress caused by ethanol. This study analyzed the core targets and mechanisms of action of GGS on ALD, which provides certain theoretical support for the further development of GGS in the treatment of ALD, and provides a reference for the subsequent research on the treatment of ALD.
| S-EPMC11191986 | biostudies-literature