Dataset Information

Network Pharmacology Analysis of the Therapeutic Mechanisms Underlying Beimu-Gualou Formula Activity against Bronchiectasis with In Silico Molecular Docking Validation.

ABSTRACT:

Background

The classical Chinese herbal prescription Beimu-Gualou formula (BMGLF) has been diffusely applied to the treatment of respiratory diseases, including bronchiectasis. Although concerning bronchiectasis the effects and mechanisms of action of the BMGLF constituents have been partially elucidated, it remains to be determined how the formula in its entirety exerts therapeutic effects.

Methods

In this study, the multitarget mechanisms of BMGLF against bronchiectasis were predicted with network pharmacology analysis. Using prepared data, a drug-target interaction network was established and subsequently the core therapeutic targets of BMGLF were identified. Furthermore, the biological function and pathway enrichment of potential targets were analyzed to evaluate the therapeutic effects and pivotal signaling pathways of BMGLF. Finally, virtual molecular docking was performed to assess the affinities of compounds for the candidate targets.

Results

The therapeutic action of BMGLF against bronchiectasis involves 18 core target proteins, including the aforementioned candidates (i.e., ALB, ICAM1, IL10, and MAPK1), which are assumed to be related to biological processes such as drug response, cellular response to lipopolysaccharide, immune response, and positive regulation of NF-?B activity in bronchiectasis. Among the top 20 signaling pathways identified, mechanisms of action appear to be primarily related to Chagas disease, allograft rejection, hepatitis B, and inflammatory bowel disease.

Conclusion

In summary, using a network pharmacology approach, we initially predicted the complex regulatory profile of BMGLF against bronchiectasis in which multilink suppression of immune/inflammatory responses plays an essential role. These results may provide a basis for novel pharmacotherapeutic approaches for bronchiectasis.

SUBMITTER: Shen X

PROVIDER: S-EPMC7803403 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Network Pharmacology Analysis of the Therapeutic Mechanisms Underlying Beimu-Gualou Formula Activity against Bronchiectasis with <i>In Silico</i> Molecular Docking Validation.

Shen Xin X Li Hong H Zou Wen-Jun WJ Wu Jian-Ming JM Wang Long L Wang Wei W Chen Hui H Zhou Ling-Li LL Hu Yuan-Hui YH Qin Xu-Hua XH Yang Jing J

Evidence-based complementary and alternative medicine : eCAM 20210105

<h4>Background</h4>The classical Chinese herbal prescription Beimu-Gualou formula (BMGLF) has been diffusely applied to the treatment of respiratory diseases, including bronchiectasis. Although concerning bronchiectasis the effects and mechanisms of action of the BMGLF constituents have been partially elucidated, it remains to be determined how the formula in its entirety exerts therapeutic effects.<h4>Methods</h4>In this study, the multitarget mechanisms of BMGLF against bronchiectasis were pre ...[more]

PMID: 33488758

Similar Datasets

Project description:BackgroundThe incidence of depression has been increasing globally, which has brought a serious burden to society. Sinisan Formula (SNSF), a well-known formula of traditional Chinese medicine (TCM), has been found to demonstrate an antidepressant effect. However, the therapeutic mechanism of this formula remains unclear. Thus, the present study aimed to explore the mechanism of SNSF in depression through network pharmacology combined with molecular docking methods.Materials and methodsBioactive compounds, potential targets of SNSF, and related genes of depression were obtained from public databases. Essential ingredients, potential targets, and signaling pathways were identified using bioinformatics analysis, including protein-protein interaction (PPI), the Gene Ontology (GO), and the Kyoto Encyclopedia of Genes and Genomes (KEGG). Subsequently, Autodock software was further performed for conducting molecular docking to verify the binding ability of active ingredients to targets.ResultsA total of 91 active compounds were successfully identified in SNSF with the use of the comprehensive network pharmacology approach, and they were found to be closely connected to 112 depression-related targets, among which CREB1, NOS3, CASP3, TP53, ESR1, and SLC6A4 might be the main potential targets for the treatment of depression. GO analysis revealed 801 biological processes, 123 molecular functions, and 67 cellular components. KEGG pathway enrichment analysis indicated that neuroactive ligand-receptor interaction, serotonergic synapse pathways, dopaminergic synapse pathways, and GABAergic synapse pathways might have played a role in treating depression. Molecular docking suggested that beta-sitosterol, nobiletin, and 7-methoxy-2-methyl isoflavone bound well to the main potential targets.ConclusionThis study comprehensively illuminated the active ingredients, potential targets, primary pharmacological effects, and relevant mechanism of the SNSF in the treatment of depression. SNSF might exert its antidepressant effects by regulating the signaling pathway of 5-hydroxytryptamine, dopamine, GABA, and neuroactive ligand receptor interactions. Still, more pharmacological experiments are needed for verification.

Project description:Le-Cao-Shi (LCS) has long been used as a folk traditional Chinese medicine formula against liver injuries, whereas its pharmacological mechanisms remain elusive. Our study aims to investigate the underlying mechanism of LCS in treating liver injuries via integrated network pharmacology, metabonomics, and experimental validation. By network pharmacology, 57 compounds were screened as candidate compounds based on ADME parameters from the LCS compound bank (213 compounds collected from the literature of three single herbs). According to online compound-target databases, the aforementioned candidate compounds were predicted to target 87 potential targets related to liver injuries. More than 15 pathways connected with these potential targets were considered vital pathways in collectively modulating liver injuries, which were found to be relevant to cancer, xenobiotic metabolism by cytochrome P450 enzymes, bile secretion, inflammation, and antioxidation. Metabonomics analysis by using the supernatant of the rat liver homogenate with UPLC-Q-TOF/MS demonstrated that 18 potential biomarkers could be regulated by LCS, which was closely related to linoleic acid metabolism, glutathione metabolism, cysteine and methionine metabolism, and glycerophospholipid metabolism pathways. Linoleic acid metabolism and glutathione metabolism pathways were two key common pathways in both network pharmacology and metabonomics analysis. In ELISA experiments with the CCl4-induced rat liver injury model, LCS was found to significantly reduce the levels of inflammatory parameters, decrease liver malondialdehyde (MDA) levels, and enhance the activities of hepatic antioxidant enzymes, which validated that LCS could inhibit liver injuries through anti-inflammatory property and by suppressing lipid peroxidation and improving the antioxidant defense system. Our work could provide new insights into the underlying pharmacological mechanisms of LCS against liver injuries, which is beneficial for its further investigation and modernization.

Project description:The mechanisms underlying the therapeutic effect of Salvia miltiorrhiza (SM) on diabetic nephropathy (DN) were examined using a systematic network pharmacology approach and molecular docking. The Traditional Chinese Medicine Systems Pharmacology (TCMSP) database was used to screen active ingredients of SM. Targets were obtained using the SwissTargetPrediction and TCMSP databases. Proteins related to DN were retrieved from the GeneCards and DisGeNET databases. A protein-protein interaction (PPI) network was constructed using common SM/DN targets in the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. The Metascape platform was used for Gene Ontology (GO) function analysis, and the Cytoscape plug-in ClueGO was used for Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Molecular docking was performed using iGEMDOCK and AutoDock Vina software. Pymol and LigPlos were used for network mapping. Sixty-six active ingredients and 189 targets of SM were found. Sixty-four targets overlapped with DN-related proteins. The PPI network revealed that AKT serine/threonine kinase 1 (AKT1), VEGFA, interleukin 6 (IL6), TNF, mitogen-activated protein kinase 1 (MAPK1), tumor protein p53 (TP53), epidermal growth factor receptor (EGFR), signal transducer and activator of transcription 3 (STAT3), mitogen-activated protein kinase 14 (MAPK14), and JUN were the ten most relevant targets. GO and KEGG analyses revealed that the common targets of DN and SM were mainly involved in advanced glycation end-products, oxidative stress, inflammatory response, and immune regulation. Molecular docking revealed that potential DN-related targets, including tumor necrosis factor (TNF), NOS2, and AKT1, more stably bound with salvianolic acid B than with tanshinone IIA. In conclusion, the present study revealed the active components and potential molecular therapeutic mechanisms of SM in DN and provides a reference for the wide application of SM in clinically managing DN.

Project description:ObjectiveHyperuricemia (HUA) is a common metabolic disease caused by disordered purine metabolism. We aim to reveal the mechanisms underlying the anti-HUA function of Simiao pill and provide therapeutic targets.MethodsSimiao pill-related targets were obtained using Herbal Ingredients' Targets (HIT), Traditional Chinese Medicine Systems Pharmacology (TCMSP), and Traditional Chinese Medicine Integrated Database (TCMID). HUA-associated targets were retrieved from GeneCards, DisGeNET, and Therapeutic Targets Database (TTD). Protein-protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database, ggraph and igraph R packages. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed using ClusterProfiler. The top 10 core targets were identified through cytoHubba. Molecular docking was conducted using PyMOL and AutoDock high-performance liquid chromatograph (HPLC) analysis was performed to identify effective compounds of Simiao pill.ResultsSimiao pill-HUA target network contained 80 targets. The key targets were mainly involved in inflammatory responses. Insulin (INS), tumor necrosis factor (TNF), interleukin-6 (IL6), interleukin 1 beta (IL1B), vascular endothelial growth factor A (VEGFA), leptin (LEP), signal transducer and activator of transcription 3 (STAT3), C-C motif chemokine ligand 2 (CCL2), interleukin-10 (IL10), and toll like receptor 4 (TLR4) were the top 10 targets in the PPI network. GO analysis demonstrated the main implication of the targets in molecular responses, production, and metabolism. KEGG analysis revealed that Simiao pill might mitigate HUA through advanced glycation end-product- (AGE-) receptor for AGE- (RAGE-) and hypoxia-inducible factor-1- (HIF-1-) associated pathways. IL1B, IL6, IL10, TLR4, and TNF were finally determined as the promising targets of Simiao pill treating HUA. Through molecular docking and HPLC analysis, luteolin, quercetin, rutaecarpine, baicalin, and atractylenolide I were the main active compounds.ConclusionsSimiao pill can mitigate HUA by restraining inflammation, mediating AGE-RAGE- and HIF-1-related pathways, and targeting IL1B, IL6, IL10, TLR4, and TNF.

Project description:Chronic kidney disease (CKD) is a leading public health problem with high morbidity and mortality, but the therapies remain limited. Bupi Yishen Formula (BYF) - a patent traditional Chinese medicine (TCM) formula - has been proved to be effective for CKD treatment in a high-quality clinical trial. However, BYF's underlying mechanism is unclear. Thus, we aimed to reveal BYF pharmacological mechanism against CKD by network pharmacology and experimental studies. Network pharmacology-based analysis of the drug-compound-target interaction was used to predict the potential pharmacological mechanism and biological basis of BYF. We performed a comprehensive study by detecting the expression levels of fibrotic and inflammatory markers and main molecules of candidate signal pathway in adenine-induced CKD rats and TGF-β1-induced HK-2 cells with the treatment of BYF by western blotting and RT-qPCR analyses. Using small interfering RNA, we assessed the effect of BYF on the TLR4-mediated NF-κB mechanism for CKD renal fibrosis and inflammation. Network pharmacology analysis results identified 369 common targets from BYF and CKD. Based on these common targets, the BYF intervention pathway was analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. We found that Toll-like receptor (TLR) and NF-κB signaling pathways were enriched. Then, we demonstrated that BYF significantly improved the adenine-induced CKD rat model condition by kidney dysfunction improvement and reversing renal fibrosis and inflammation. Subsequently, we investigated BYF's effect on the TLR4/NF-κB signaling pathway. We found that TLR4 and phospho-NF-κB (p-p65 and p-IKβα) expression was significantly upregulated in adenine-induced CKD rats, then partially downregulated by BYF. Furthermore, BYF inhibited fibrotic and inflammatory responses, as well as TLR4, p-p65, and p-IKβα in TGF-β1-induced HK-2 cells. Additionally, the BYF inhibitory effect on fibrosis and inflammation, and NF-κB pathway activation were significantly reduced in TGF-β1-induced HK-2 cells transfected with TLR4 siRNA. Altogether, these findings demonstrated that the suppression of TLR4-mediated NF-κB signaling was an important anti-fibrotic and anti-inflammatory mechanism for BYF against CKD. It also provided a molecular basis for new CKD treatment drug candidates.

Project description:Objective Explore the potential molecular mechanisms behind the therapeutic functions of Gualou Niubang decoction (GLNBD) in the treatment of plasma cell mastitis (PCM) by network pharmacology and molecular docking. Methods GLNBD is a formula of Chinese traditional medicine consisting of 12 herbs. The potential active ingredients of GLNBD and their target genes were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform database, and PCM-related target genes were obtained from GeneCards, OMIM, and NCBI databases, using R language to obtain intersection targets; then, the STRING database and Cytoscape software were used to establish protein-protein interaction networks and herb ingredient target networks. DAVID was used to perform GO and KEGG pathway enrichment analyses on the intersection target. PyMoL-2.5.0 and AutoDock Tools-1.5.6 were used to verify the molecular docking. Results 164 ingredients and 58 intersection targets were obtained in the treatment of PCM by GLNBD. Four key active compounds and four key proteins were identified. Then, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses showed that biological functions of potential target genes were associated with negative regulation of the apoptotic process, response to hypoxia, positive regulation of transcription, and DNA-templated, with related pathways involving the pathway in cancer, phosphatidylinositol 3-kinase (PI3K) Akt signaling pathway, and AGE-RAGE signaling pathway in diabetic complications. Moreover, the binding activities of key target genes and essential active compounds of Chinese herbal medicines in GLNBD were further validated by molecular docking. The results showed that the docking results were stable and had good binding ability. Conclusion This study suggested that four potential key active components, including quercetin, luteolin, fisetin, and kaempferol, were identified in GLNBD, which could interact with ALB, EGFR, IL-6, and VEGFA modulating the activation of the pathway in cancer, PI3K-Akt pathway, and AGE-RAGE signaling pathway in diabetic complications.