scholarly journals Potential Molecular Mechanisms of Plantain in the Treatment of Gout and Hyperuricemia Based on Network Pharmacology

2020 ◽  
Vol 2020 ◽  
pp. 1-20
Author(s):  
Pei Liu ◽  
Huachong Xu ◽  
Yucong Shi ◽  
Li Deng ◽  
Xiaoyin Chen
Keyword(s):  
Signaling Pathway ◽  
Molecular Mechanisms ◽  
Interaction Network ◽  
Mendelian Inheritance ◽  
Venn Diagram ◽  
Network Pharmacology ◽  
Active Compounds ◽  
The Core ◽  
Pharmacological Analysis ◽  
Natural Medicine

Background. The incidence of gout and hyperuricemia is increasing year by year in the world. Plantain is a traditional natural medicine commonly used in the treatment of gout and hyperuricemia, but the molecular mechanism of its active compounds is still unclear. Based on network pharmacology, this article predicts the targets and pathways of effective components of plantain for gout and hyperuricemia and provides effective reference for clinical medication. Method. Traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP) and SymMap databases were used to screen out the active compounds and their targets in plantain. GeneCards, Therapeutic Target Database (TTD), and Online Mendelian Inheritance in Man (OMIM) databases were used to find the targets corresponding to gout and hyperuricemia. Venn diagram was used to obtain the intersection targets of plantain and diseases. The interaction network of the plantain active compounds-targets-pathways-diseases was constructed by using Cytoscape 3.7.2 software. Finally, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were carried out. Result. Seven active compounds were identified by network pharmacological analysis, including dinatin, baicalein, baicalin, sitosterol, 6-OH-luteolin, stigmasterol, and luteolin. Plantain plays a role in gout and hyperuricemia diseases by regulating various biological processes, cellular components, and molecular functions. The core targets of plantain for treating gout are MAPK1, RELA, TNF, NFKBIA, and IFNG, and the key pathways are pathways in cancer, hypoxia-inducible factor-1 (HIF-1) signaling pathway, interleukin (IL)-17 signaling pathway, Chagas disease (American trypanosomiasis), and relaxin signaling pathway. The core targets of plantain for hyperuricemia are RELA, MAPK1, NFKBIA, CASP3, CASP8, and TNF, and the main pathways are pathways in cancer, apoptosis, hepatitis B, IL-17 signaling pathway, and toxoplasmosis. Conclusion. This study explored the related targets and mechanisms of plantain for the treatment of gout and hyperuricemia from the perspective of network pharmacological analysis, reflecting the characteristics of multiple components, multiple targets, and multiple pathways, and it provides a good theoretical basis for the clinical application of plantain.

scholarly journals A Network Pharmacology-Based Study on the Anti-Lung Cancer Effect of Dipsaci Radix

2020 ◽  
Vol 2020 ◽  
pp. 1-9 ◽  
Author(s):  
Jiayan Wu ◽  
Shengkun Hong ◽  
Xiankuan Xie ◽  
Wangmi Liu
Keyword(s):  
Lung Cancer ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Molecular Mechanisms ◽  
Target Genes ◽  
Interaction Network ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Hub Genes ◽  
Active Compounds

Objective. Dipsaci Radix (DR) has been used to treat fracture and osteoporosis. Recent reports have shown that myeloid cells from bone marrow can promote the proliferation of lung cancer. However, the action and mechanism of DR has not been well defined in lung cancer. The aim of the present study was to define molecular mechanisms of DR as a potential therapeutic approach to treat lung cancer. Methods. Active compounds of DR with oral bioavailability ≥30% and drug-likeness index ≥0.18 were obtained from the traditional Chinese medicine systems pharmacology database and analysis platform. The potential target genes of the active compounds and bone were identified by PharmMapper and GeneCards, respectively. The compound-target network and protein-protein interaction network were built by Cytoscape software and Search Tool for the Retrieval of Interacting Genes webserver, respectively. GO analysis and pathway enrichment analysis were performed using R software. Results. Our study demonstrated that DR had 6 active compounds, including gentisin, sitosterol, Sylvestroside III, 3,5-Di-O-caffeoylquinic acid, cauloside A, and japonine. There were 254 target genes related to these active compounds as well as to bone. SRC, AKT1, and GRB2 were the top 3 hub genes. Metabolisms and signaling pathways associated with these hub genes were significantly enriched. Conclusions. This study indicated that DR could exhibit the anti-lung cancer effect by affecting multiple targets and multiple pathways. It reflects the traditional Chinese medicine characterized by multicomponents and multitargets. DR could be considered as a candidate for clinical anticancer therapy by regulating bone physiological functions.

scholarly journals A Network Pharmacology Approach to Uncover the Mechanisms of Shen-Qi-Di-Huang Decoction against Diabetic Nephropathy

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Sha Di ◽  
Lin Han ◽  
Qing Wang ◽  
Xinkui Liu ◽  
Yingying Yang ◽  
...  
Keyword(s):  
Diabetic Nephropathy ◽  
Signaling Pathway ◽  
Molecular Mechanisms ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Protein Protein Interaction ◽  
Regulation Of Blood Pressure ◽  
Protein Protein Interaction Network

Shen-Qi-Di-Huang decoction (SQDHD), a well-known herbal formula from China, has been widely used in the treatment of diabetic nephropathy (DN). However, the pharmacological mechanisms of SQDHD have not been entirely elucidated. At first, we conducted a comprehensive literature search to identify the active constituents of SQDHD, determined their corresponding targets, and obtained known DN targets from several databases. A protein-protein interaction network was then built to explore the complex relations between SQDHD targets and those known to treat DN. Following the topological feature screening of each node in the network, 400 major targets of SQDHD were obtained. The pathway enrichment analysis results acquired from DAVID showed that the significant bioprocesses and pathways include oxidative stress, response to glucose, regulation of blood pressure, regulation of cell proliferation, cytokine-mediated signaling pathway, and the apoptotic signaling pathway. More interestingly, five key targets of SQDHD, named AKT1, AR, CTNNB1, EGFR, and ESR1, were significant in the regulation of the above bioprocesses and pathways. This study partially verified and predicted the pharmacological and molecular mechanisms of SQDHD on DN from a holistic perspective. This has laid the foundation for further experimental research and has expanded the rational application of SQDHD in clinical practice.

scholarly journals A Network Pharmacology-Based Approach for Exploring Key Active Compounds and Pharmacological Mechanisms of Tangshen Formula for Treatment of Diabetic Nephropathy

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Weie Zhou ◽  
Xuefeng Zhou ◽  
Yuan Zhang ◽  
Yuyang Wang ◽  
Wenjie Wu ◽  
...  
Keyword(s):  
Diabetic Nephropathy ◽  
Signaling Pathway ◽  
Molecular Mechanisms ◽  
Synergistic Effects ◽  
Mapk Signaling ◽  
Network Pharmacology ◽  
Active Compounds ◽  
Promising Source ◽  
Tangshen Formula ◽  
Compound Target

Diabetic nephropathy (DN) is one of the common and severe microvascular complications of diabetes mellitus (DM). The occurrence and development of DN are related to multiple factors in the human body, which makes DN a complex disease, and the pathogeneses of DN have not yet been fully illustrated. Furthermore, DN lacks effective drugs for treatment nowadays. Chinese herbal medicine (CHM) often shows the feature of multicomponents, multitargets, multipathways, and synergistic effects and shows a promising source of new therapeutic drugs for DN. As a CHM, Tangshen Formula (TSF) was used to treat DN patients in China. However, its bioactive compounds and holistic pharmacological mechanisms on DN are both unclear. A network pharmacology approach was firstly applied to explore multiple active compounds and multiple key pharmacological mechanisms for TSF treating DN by drug-targeted interaction databases, herb-compound-target network, protein-protein interaction network, compound-target-pathway network, and analysis methods. And the results showed that TSF have the characteristic of multicomponents, multitargets, multipathways, and synergistic effects for treating DN. The quercetin, naringenin, kaempferol, and isorhamnetin as key active compounds and the PI3K-Akt signaling pathway, TNF signaling pathway, nonalcoholic fatty liver disease (NAFLD), focal adhesion, rap1 signaling pathway, T cell receptor signaling pathway, MAPK signaling pathway, and insulin resistance as the key molecular mechanisms play important roles in TSF treating DN. Moreover, quercetin, naringenin, kaempferol, and isorhamnetin were successfully detected in TSF by the UHPLC-MS/MS analysis method. And their concentrations were 0.224, 8.295, 0.0564, and 0.0879 mg·kg-1, respectively. The present findings not only provide new insights for a deeper understanding of the constituent basis and pharmacology of TSF but also provide guidance for further pharmacological studies on TSF.

scholarly journals Elucidation of the active compounds and molecular mechanisms of Smilacis Chinae Rhizoma for treatment of pelvic inflammatory disease based on network pharmacology and MMGBSA-docking

2020 ◽  
Author(s):  
Yunsen Zhang ◽  
Zikuang Zhao ◽  
Wenxiang Wang ◽  
Qi Li ◽  
Huimin Chen ◽  
...  
Keyword(s):  
Pelvic Inflammatory Disease ◽  
Signaling Pathway ◽  
Inflammatory Disease ◽  
Molecular Mechanisms ◽  
Binding Free Energy ◽  
Network Pharmacology ◽  
Therapeutic Effects ◽  
Active Ingredients ◽  
Active Compounds ◽  
Bidirectional Regulation

Abstract Background Smilacis Chinae Rhizoma (SCR) is widely used in the treatment of pelvic inflammatory disease (PID). However, its active ingredients and the mechanisms against PID remain elusive. This study aimed to clarify the active ingredients and explore their molecular mechanisms on PID. Method Network pharmacology and MMGBSA-docking exploited the active compounds and mechanisms against PID, as well as validating the binding mode of candidate targets.Results Network pharmacology revealed 32 active compounds and 718 compound-related targets mapped to 91 pathways which were clustered 7 genres (e.g., immunoregulation). C-T-P network and PPI analysis illustrated 17 PID-related targets, indicating that SCR may decrease inflammation, ameliorate fibrosis, and inhibit microorganisms via bidirectionally regulating IL-17 signaling pathway. Furthermore, active compounds were uncovered that bound to prostaglandin-endoperoxide synthase 2, matrix metalloprotein-9, lipocalin, signal transducer and activator of transcription 3, myeloperoxidase, and tumor necrosis factor. 19 active compounds (e.g., rutin (-66.43 kcal/mol), moracin M (-37.01 kcal/mol) and oxyresveratrol (-38.84 kcal/mol)) were found to show excellent binding free energy, demonstrating that H-bond, Pi electron cloud and electrostatic potential as the main binding ability to these targets. Conclusion Approach of network pharmacology and MMGBSA-docking revealed the active ingredients, such as rutin, moracin M, and oxyresveratrol, in SCR and dissected it exhibits the therapeutic effects (e.g., decrease inflammation, ameliorate fibrosis, and inhibit microorganisms) of PID by the bidirectional regulation of IL-17 signaling pathway.

scholarly journals A Network Pharmacology and Molecular Docking Approach to Investigate the Anticoronavirus-Induced Diseases Effect of Yinqiao Powder Combined With Modified Sangju Decoction

2021 ◽  
Vol 16 (9) ◽  
pp. 1934578X2110352
Author(s):  
Tian-Shun Wang ◽  
Xing-Pan Wu ◽  
Qiu-Yuan Jian ◽  
Yan-Fang Yang ◽  
Wu He-Zhen
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Treatment Strategies ◽  
Interaction Network ◽  
Mitogen Activated Protein Kinase ◽  
Network Pharmacology ◽  
Common Mechanism ◽  
Active Components ◽  
Discovery Studio ◽  
The Core

Severe acute respiratory syndrome (SARS) once caused great harm in China, but now it is the coronavirus disease 2019 (COVID-19) pandemic that has become a huge threat to global health, which raises urgent demand for developing effective treatment strategies to avoid the recurrence of tragedies. Yinqiao powder, combined with modified Sangju decoction (YPCMSD), has been clinically proven to have a good therapeutic effect on COVID-19 in China. This study aimed to analyze the common mechanism of YPCMSD in the treatment of SARS and COVID-19 through network pharmacology and molecular docking and further explore the potential application value of YPCMSD in the treatment of coronavirus infections. Firstly, the active components were collected from the literature and Traditional Chinese Medicine Systems Pharmacology database platform. The COVID-19 and SARS associated targets of the active components were forecasted by the SwissTargetPrediction database and GeneCards. A protein–protein-interaction network was drawn and the core targets were obtained by selecting the targets larger than the average degree. By importing the core targets into database for annotation, visualization, and integrated discovery, enrichment analysis of gene ontology, and construction of a Kyoto Encyclopedia of genes and genomes pathway was conducted. Cytoscape 3.6.1 software was used to construct a “components–targets–pathways” network. Active components were selected to dock with acute respiratory syndrome coronavirus type 2 (SARS-COV-2) 3CL and angiotensin-converting enzyme 2 (ACE2) through Discovery Studio 2016 software. A network of “components–targets–pathways” was successfully constructed, with key targets involving mitogen-activated protein kinase 1, caspase-3 (CASP3), tumor necrosis factor (TNF), and interleukin 6. Major metabolic pathways affected were those in cancer, the hypoxia-inducible factor 1 signaling pathway, the TNF signaling pathway, the Toll-like receptor signaling pathway, and the PI3K-Akt signaling pathway. The core components, such as arctiin, scopolin, linarin, and isovitexin, showed a strong binding ability with SARS-COV-2 3CL and ACE2. We predicted that the mechanism of action of this prescription in the treatment of COVID-19 and SARS might be associated with multicomponents that bind to SARS-COV-2 3CL and ACE2, thereby regulating targets that coexpressed with them and pathways related to inflammation and the immune system.

scholarly journals Network Pharmacology Identifies the Mechanisms of Sang-Xing-Zhi-Ke-Fang against Pharyngitis

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Yinhe Deng ◽  
Quanjiang Li ◽  
Menglin Li ◽  
Tiantian Han ◽  
Guixian Li ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Influenza A ◽  
Molecular Mechanisms ◽  
Mapk Signaling ◽  
Venn Diagram ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Ras Signaling ◽  
Clinical Effects ◽  
Overlapping Genes

Background. Sang-Xing-Zhi-Ke-Fang (SXZKF) demonstrates good therapeutic effect against pharyngitis. Nevertheless, the pharmacological mechanism underlying its effectiveness is still unclear. Objective. To investigate the underlying mechanisms of SXZKF against pharyngitis using network pharmacology method. Methods. Bioactive ingredients of SXZKF were collected and screened using published literature and two public databases. Using four public databases, the overlapping genes between these bioactive compound-related and pharyngitis-related genes were identified by Venn diagram. Protein-protein interaction (PPI) was obtained using “Search Tool for the Retrieval of Interacting Genes (STRING)” database. “Database for Annotation, Visualization, and Integrated Discovery ver. 6.8 (DAVID 6.8)” was used to perform Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis to explore the molecular mechanisms of SXZKF against pharyngitis. Finally, Cytoscape 3.7.2 software was used to construct and visualize the networks. Result. A total of 102 bioactive compounds were identified. Among them, 886 compounds-related and 6258 pharyngitis-related genes were identified, including 387 overlapping genes. Sixty-three core targets were obtained, including ALB, PPARγ, MAPK3, EGF, and PTGS2. Signaling pathways closely related to mechanisms of SXZKF for pharyngitis were identified, including serotonergic synapse, VEGF signaling pathway, Fc epsilon RI signaling pathway, Ras signaling pathway, MAPK signaling pathway, and influenza A. Conclusion. This is the first identification of in-depth study of SXZKF against pharyngitis using network pharmacology. This new evidence could be informative in providing new support on the clinical effects of SXZKF on pharyngitis and for the development of personalized medicine for pharyngitis.

scholarly journals A Network Pharmacology to Explore the Mechanism of Astragalus Membranaceus in the Treatment of Diabetic Retinopathy

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Qi Jin ◽  
Xiao-Feng Hao ◽  
Li-Ke Xie ◽  
Jing Xu ◽  
Mei Sun ◽  
...  
Keyword(s):  
Oxidative Stress ◽  
Diabetic Retinopathy ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Signaling Pathway ◽  
Astragalus Membranaceus ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Active Compounds ◽  
The Core

Background. Diabetic retinopathy (DR) includes a series of typical lesions affected by retinal microvascular damage caused by diabetes mellitus (DM), which not only seriously damages the vision, affecting the life’s quality of patients, but also brings a considerable burden to the family and society. Astragalus Membranaceus (AM) is a commonly used medicine in clinical therapy of eye disorders in traditional Chinese medicine (TCM). In recent years, it is also used for treating DR, but the specific mechanism is unclear. Therefore, this study explores the potential mechanism of AM in DR treatment by using network pharmacology. Methods. Based on the oral bioavailability (OB) and drug likeness (DL) of two ADME (absorption, distribution, metabolism, excretion) parameters, Traditional Chinese Medicine Systems Pharmacology Database (TCMSP), Swiss Target Prediction platform, GeneCards, and OMIM database were used to predict and screen the active compounds of AM, the core targets of AM in DR treatment. The Metascape data platform was used to perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis on the core targets. Results. 24 active compounds were obtained, such as quercetin, kaempferol, and astragaloside IV. There were 169 effective targets of AM in DR treatment, and the targets were further screened and finally, 38 core targets were obtained, such as VEGFA, AKT1, and IL-6. EGFR tyrosine kinase inhibitor resistance, AGE-RAGE signaling pathway in diabetic complications, PI3K-Akt signaling pathway, and other metabolic pathways participated in oxidative stress, cell apoptosis, angiogenesis signal transduction, inflammation, and other biological processes. Conclusion. AM treats DR through multiple compounds, multiple targets, and multiple pathways. AM may play a role in the treatment of DR by targeting VEGFA, AKT1, and IL-6 and participating in oxidative stress, angiogenesis, and inflammation.

scholarly journals Aberrant expression of BDNF might serve as a candidate target for cocaine-induced psychosis: insights from bioinformatics analysis and microarray validation

2021 ◽  
Vol 34 (5) ◽  
pp. e100587
Author(s):  
Youwei Zhu ◽  
Yan Zhao ◽  
Xiaomin Xu ◽  
Hang Su ◽  
Xiaotong Li ◽  
...  
Keyword(s):  
Molecular Mechanisms ◽  
Target Genes ◽  
Treatment Options ◽  
Interaction Network ◽  
Mendelian Inheritance ◽  
Network Pharmacology ◽  
Receptor Interaction ◽  
Aberrant Expression ◽  
Holistic View ◽  
Risk Genes

BackgroundCocaine use disorder (CUD) and associated psychosis are major public health issues worldwide, along with high relapse outcome and limited treatment options. Exploring the molecular mechanisms underlying cocaine-induced psychosis (CIP) could supply integrated insights for understanding the pathogenic mechanism and potential novel therapeutic targets.AimsThe aim of the study was to explore common alterations of CUD-schizophrenia-target genes and identify core risk genes contributing to CIP through data mining and network pharmacology approach.MethodsTarget genes of CUD were obtained from GeneCards, Comparative Toxicogenomics Database, Swiss Target Prediction platform and PubChem. Schizophrenia-related target genes were derived from DisGeNET, GeneCards, MalaCards and Online Mendelian Inheritance in Man databases. Then, the overlap genes of these two sets were regarded as risk genes contributing to CIP. Based on these CUD-schizophrenia-target genes, functional annotation and pathway analysis were performed using the clusterProfiler package in R. Protein–protein interaction network construction and module detection were performed based on the Search Tool for the Retrieval of Interacting Genes (STRING) database and Cytoscape software. Gene expression datasets GSE54839 and GSE93577 were applied for data validation and diagnostic capacity evaluation of interested hub genes.ResultsA total of 165 CUD-schizophrenia-target genes were obtained. These genes were mainly contributing to chemical synaptic transmission, neuropeptide hormone activity, postsynaptic membrane and neuroactive ligand–receptor interaction pathway. Network analysis and validation analysis indicated that BDNF might serve as an important risk gene in mediating CIP.ConclusionsThis study generates a holistic view of CIP and provides a basis for the identification of potential CUD-schizophrenia-target genes involved in the development of CIP. The abnormal expression of BDNF would be a candidate therapeutic target underlying the pathogenesis of CUD and associated CIP.

scholarly journals Exploring Molecular Mechanism of Traditional Chinese Medicine Euphorbiae Semen on Reversing of Multidrug Resistance in Leukemia Based on Network Pharmacology Strategy and Molecular Docking Technology

2020 ◽  
Author(s):  
Xiao Song ◽  
Fei Guo ◽  
Xiao-Chen Sun ◽  
Shu-Yue Wang ◽  
Yao-Hui Yuan ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Biological Functions ◽  
Active Compounds ◽  
The Core ◽  
The World ◽  
Target Network ◽  
Compound Target

Abstract Background: Leukemia was listed by the World Health Organization as one of the five most intractable diseases in the world. The multi-drug resistance (MDR) of leukemia cells limits the efficacy of anti-tumor drugs and is the major reason for the chemotherapy failure and recurrence of leukemia chemotherapy. Some studies have shown that Euphorbiae semen (ES) possesses the characteristics of new therapeutic drugs for MDR. However, the molecular mechanisms and active compounds have not yet been fully clarified. Therefore, there is a need for explore its active compounds and demonstrate its mechanisms through network pharmacology and molecular docking technology.Method: First, the TCMSP database was searched and screened the active compounds of the ES, supplemented with compounds verified by literature, so as to further identify the core compounds in the active ingredient. Simultaneously, the TCMSP and Swiss database were searched to the targets of active compounds, and the targets of reverses leukemia multidrug resistance (RL-MDR) were screened in the relevant databases, such as GeneCards and DrugBank. Then, the targets of active compounds were intersected with RL-MDR targets to obtain potential targets of ES acting on MDR. The compound–target network was constructed by Cytoscape. The target protein–protein interaction network was built using STRING and Cytoscape database. Second, the R language and DAVID database were used to analyse Gene Ontology (GO) biological functions analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) signal pathways enrichment. Finally, molecular docking method was utilized to investigate the binding activity between the core targets and the active compounds of ES.Results: Compound–target network mainly contained 22 compounds and 81 corresponding targets. Finally, seven components in ES were selected and 10 core targets were identified; Key targets contained JUN, CASP3, MAOA, AR, PPARG, DRD2, ADRA2A, CHRM2, PTGS2 and MAPK14. GO enrichment analysis indicated the main biological functions of potential genes of ES in the treatment of MDR. KEGG pathway enrichment analysis showed the main pathways, mainly including apoptosis, pathways in cancer, p53 signaling pathway, VEGF signaling pathway, TNF signaling pathway and PI3K–Akt signaling pathway. Finally, we chose the top 10 common targets for molecular docking with the 7 active compounds of ES. The results of molecular docking indicated that the compounds of ES, which had good affinity with targets. Conclusion: The molecular mechanism of ES in the treatment of MDR showed the synergistic reaction of multi-compound, multi-target, and multi-pathway of traditional Chinese medicine, which provided ideas for further clinical research.

scholarly journals A network pharmacology analysis on drug-like compounds from Ganoderma lucidum for alleviation of Atherosclerosis

2021 ◽  
Author(s):  
Ki Kwang Oh ◽  
Md. Adnan ◽  
Dong Ha Cho
Keyword(s):  
Signaling Pathways ◽  
Signaling Pathway ◽  
Ganoderma Lucidum ◽  
Mapk Signaling ◽  
Mendelian Inheritance ◽  
Chronic Inflammatory Disease ◽  
Mapk Signaling Pathway ◽  
Venn Diagram ◽  
Network Pharmacology ◽  
Overlapping Genes

Abstract Background: Ganoderma lucidum (GL) is known as a potent alleviator against chronic inflammatory disease like atherosclerosis (AS), but its critical bioactive compounds and their mechanisms against AS have not been unveiled. This research aimed to identify the key compounds(s) and mechanism(s) of GL against AS through network pharmacology.Methods: The compounds from GL were identified by gas chromatography-mass spectrum (GC-MS), and SwissADME screened their physicochemical properties. Then, the gene(s) associated with the screened compound(s) or AS related genes were identified by public databases, and we selected the overlapping genes using a Venn diagram. The networks between overlapping genes and compounds were visualized, constructed, and analyzed by RStudio. Finally, we performed molecular docking test (MDT) to identify key gene(s), compound(s) on AutoDockVina.Results: A total of 35 compounds in GL was detected via GC-MS, and 34 compounds (accepted by the Lipinski's rule) were selected as drug-like compounds (DLCs). A total of 34 compounds were connected to the number of 785 genes and 2,606 AS-related genes were identified by DisGeNET and Online Mendelian Inheritance in Man (OMIM). The final 98 overlapping genes were extracted between the compounds-genes network and AS-related genes. On Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, the number of 27 signaling pathways were sorted out, and a hub signaling pathway (MAPK signaling pathway), a core gene (PRKCA), and a key compound (Benzamide, 4-acetyl-N-(2,6-dimethylphenyl)) were selected among the 27 signaling pathways via MDT. Conclusion: Overall, we found that the identified 3 DLCs from GL have potent anti-inflammatory efficacy, improving AS by inactivating the MAPK signaling pathway.

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