scholarly journals Exploration of the mechanism of Ziyin Tongluo Formula on preventing and treating postmenopausal osteoporosis based on the network pharmacology and molecular docking

2020 ◽  
Author(s):  
Rong-Bin Chen ◽  
Ying-Dong Yang ◽  
Kai Sun ◽  
Shan Liu ◽  
Wei Guo ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Postmenopausal Osteoporosis ◽  
Signaling Pathway ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Active Ingredients ◽  
Active Compounds ◽  
Core Proteins ◽  
Key Genes

Abstract Background: Postmenopausal osteoporosis (PMOP) is a global chronic and metabolic bone disease, which poses huge challenges to individuals and society. Ziyin Tongluo Formula (ZYTLF) has been proved effective in the treatment of PMOP. However, the material basis and mechanism of ZYLTF against PMOP have not been thoroughly elucidated.Methods: Online databases were used to identify the active ingredients of ZYTLF and corresponding putative targets. Genes associated with PMOP were mined, and then mapped with the putative targets to obtain overlapping genes. Multiple networks were constructed and analyzed, from which the key genes were selected. The key genes were imported to the DAVID database to performs GO and KEGG pathway enrichment analysis. Finally, AutoDock Tools and other software were used for molecular docking of core compounds and key proteins. Results: Ninety-two active compounds of ZYTLF corresponded to 243 targets, with 129 target genes interacting with PMOP, and 50 key genes were selected. Network analysis showed the top 5 active ingredients including quercetin, kaempferol, luteolin, scutellarein, and formononetin., and the top 50 key genes such as VEGFA, MAPK8, AKT1, TNF, ESR1. Enrichment analysis uncovered two significant types of KEGG pathways in PMOP, hormone-related signaling pathways (estrogen , prolactin, and thyroid hormone signaling pathway) and inflammation-related pathways (TNF, PI3K-Akt, and MAPK signaling pathway). Moreover, molecular docking analysis verified that the main active compounds were tightly bound to the core proteins, further confirming the anti-PMOP effects. Conclusions: Based on network pharmacology and molecular docking technology, this study initially revealed the mechanisms of ZYTLF on PMOP, which involves multiple targets and multiple pathways.

scholarly journals Potential mechanism of Ziyin Tongluo Formula in the treatment of postmenopausal osteoporosis: based on network pharmacology and ovariectomized rat model

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Rong-Bin Chen ◽  
Ying-Dong Yang ◽  
Kai Sun ◽  
Shan Liu ◽  
Wei Guo ◽  
...  
Keyword(s):  
Postmenopausal Osteoporosis ◽  
Signaling Pathway ◽  
Rat Model ◽  
Experimental Studies ◽  
Enrichment Analysis ◽  
Ovariectomized Rat ◽  
Active Ingredients ◽  
Active Compounds ◽  
Osteoclast Activity ◽  
Key Genes

Abstract Background Amending from ancient classic, Ziyin Tongluo Formula (ZYTLF) has been prescribed to treat postmenopausal osteoporosis (PMOP) for decades with good curative effect. However, the possible mechanisms of it are still unknown. Methods Ovariectomized rat model was established to validate the therapeutic effect of ZYTLF on PMOP by Micro-CT bone analysis and pathological observation. Subsequently, active ingredients of ZYTLF and corresponding putative targets were identified by online databases. Overlapping genes were first obtained from mining genes associated with PMOP and then overlapped them with the putative targets. Key genes were selected from the multiple constructed and analyzed networks. GO and KEGG pathway enrichment analysis were performed by importing the key genes to the DAVID database. Moreover, validation of the binding association between key targets and their corresponding active compounds were accomplished by AutoDock Tools and other software. Lastly, Enzyme linked immunosorbent assay (Elisa) detection and Western blot analysis were utilized to further explore the possible mechanism of ZYTLF on PMOP. Results With 129 target genes interacting with PMOP, 92 active compounds of ZYTLF corresponded to 243 targets, and 50 key genes were chosen. Network analysis revealed the top 10 active ingredients, such as quercetin and kaempferol and the top 50 key genes, such as ERα, p38 MAPK, p-AKT and TGF-β1. Enrichment analysis uncovered multiple signaling pathways, including estrogen signaling pathway, TNF signaling pathway, PI3K-Akt signaling pathway and MAPK signaling pathway. Furthermore, our finding of the foremost active compounds was tightly bound to the core proteins, which were verified by molecular docking analysis. Through experimental studies, we confirmed that the prescription of ZYTLF could ameliorate the OVX-induced bone loss, suppress the osteoclast activity and boost osteoblast ability through experimental studies. Conclusion The potential mechanisms and therapeutic effects of ZYTLF against PMOP may be ascribed to inhibition of osteoclast activity, boost of osteoblast activity and enhancement of the expression of ERα.

scholarly journals Exploring the Pharmacological Mechanism of Duhuo Jisheng Decoction in Treating Osteoporosis Based on Network Pharmacology

2021 ◽  
Vol 2021 ◽  
pp. 1-21
Author(s):  
Zhencheng Xiong ◽  
Can Zheng ◽  
Yanan Chang ◽  
Kuankuan Liu ◽  
Li Shu ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Enrichment Analysis ◽  
Mapk Signaling ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Hub Genes ◽  
Active Compounds ◽  
Treatment Of Osteoporosis ◽  
Target Proteins

Objective. The purpose of this work is to study the mechanism of action of Duhuo Jisheng Decoction (DHJSD) in the treatment of osteoporosis based on the methods of bioinformatics and network pharmacology. Methods. In this study, the active compounds of each medicinal ingredient of DHJSD and their corresponding targets were obtained from TCMSP database. Osteoporosis was treated as search query in GeneCards, MalaCards, DisGeNET, Therapeutic Target Database (TTD), Comparative Toxicogenomics Database (CTD), and OMIM databases to obtain disease-related genes. The overlapping targets of DHJSD and osteoporosis were identified, and then GO and KEGG enrichment analysis were performed. Cytoscape was employed to construct DHJSD-compounds-target genes-osteoporosis network and protein-protein interaction (PPI) network. CytoHubba was utilized to select the hub genes. The activities of binding of hub genes and key components were confirmed by molecular docking. Results. 174 active compounds and their 205 related potential targets were identified in DHJSD for the treatment of osteoporosis, including 10 hub genes (AKT1, ALB, IL6, MAPK3, VEGFA, JUN, CASP3, EGFR, MYC, and EGF). Pathway enrichment analysis of target proteins indicated that osteoclast differentiation, AGE-RAGE signaling pathway in diabetic complications, Wnt signaling pathway, MAPK signaling pathway, PI3K-Akt signaling pathway, JAK-STAT signaling pathway, calcium signaling pathway, and TNF signaling pathway were the specifically major pathways regulated by DHJSD against osteoporosis. Further verification based on molecular docking results showed that the small molecule compounds (Quercetin, Kaempferol, Beta-sitosterol, Beta-carotene, and Formononetin) contained in DHJSD generally have excellent binding affinity to the macromolecular target proteins encoded by the top 10 genes. Conclusion. This study reveals the characteristics of multi-component, multi-target, and multi-pathway of DHJSD against osteoporosis and provides novel insights for verifying the mechanism of DHJSD in the treatment of osteoporosis.

Systematic evaluation of the mechanisms of Mulberry leaf (Morus alba Linne) acting on diabetes based on network pharmacology and molecular docking

2020 ◽  
Vol 23 ◽  
Author(s):  
Qiguo Wu ◽  
Yeqing Hu
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Active Compounds ◽  
Pathway Network ◽  
Pathway Enrichment ◽  
Mulberry Leaves ◽  
Mulberry Leaf

Background: Diabetes mellitus is one of the most common endocrine metabolic disorder diseases. The application of herbal medicine to control glucose levels and improve insulin action might be a useful approach in the treatment of diabetes. Mulberry leaves (ML) has been reported to exert important activities of anti-diabetic. Objective: In this work, we aimed to explore the multi-targets and multi-pathways regulatory molecular mechanism of Mulberry leaves (ML, Morus alba Linne) acting on diabetes. Methods: Identification of active compounds of Mulberry leaves using Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. Bioactive components were screened by FAF-Drugs4 website (Free ADME-Tox Filtering Tool). The targets of bioactive components were predicted from SwissTargetPrediction website, and the diabetes related targets were screened from GeneCards database. The common targets of ML and diabetes are used for Gene Ontology (GO) and pathway enrichment analysis. The visualization networks were constructed by Cytoscape 3.7.1 software. The construction of biological networks were performed to analyze the mechanisms as follows: (1) Compound-Target network; (2) Common target-Compound network; (3) Common targets protein interaction network; (4) Compound-Diabetes protein-protein interactions (PPI) network; (5) Target-Pathway network; (6) Compound-Target-Pathway network. At last, the prediction results of network pharmacology were verified by molecular docking method. Results: 17 active components were obtained by TCMSP database and FAF-Drugs4 website. 51 potential targets (11 common targets and 40 associated indirect targets) were obtained and used to build the PPI network by String database. Furthermore, the potential targets were used to GO and pathway enrichment analysis. 8 key active compounds (quercetin, Iristectorigenin A, 4-Prenylresveratrol, Moracin H, Moracin C, Isoramanone, Moracin E and Moracin D) and 8 key targets (AKT1, IGF1R, EIF2AK3, PPARG, AGTR1, PPARA, PTPN1 and PIK3R1) were obtained to play major roles in Mulberry leaf acting on diabetes. And the signal pathways involved in the mechanisms mainly include AMPK signaling pathway, PI3K-Akt signaling pathway, mTOR signaling pathway, insulin signaling pathway and insulin resistance. The molecular docking results show that the 8 key active compounds have good affinity with the key target of AKT1, and the 5 key targets (IGF1R, EIF2AK3, PPARG, PPARA and PTPN1) have better affinity than AKT1 with the key compound of quercetin. Conclusion: Based on network pharmacology and molecular docking of this work provided an important systematic and visualized basis for further understanding the synergy mechanism of ML acting on diabetes.

scholarly journals Network Pharmacology Study and Molecular Docking on the Mechanism of Treatment of Colorectal Cancer by Xiao-Chai-Hu-Tang

2021 ◽  
Author(s):  
Jingyun Jin ◽  
Bin Chen ◽  
Xiangyang Zhan ◽  
Zhiyi Zhou ◽  
Hui Liu ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Gene Ontology ◽  
Molecular Docking ◽  
Signaling Pathway ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Signal Pathways ◽  
Active Ingredients ◽  
Pathway Gene

Abstract Background and objective: To predict the targets and signal pathways of Xiao-Chai-Hu-Tang (XCHT) in the treatment of colorectal cancer (CRC) based on network pharmacology, to further analyze its anti-CRC material basis and mechanism of action.Methods: TCMSP and TCMID databases were adopted to screen the active ingredients and potential targets of XCHT. CRC-related targets were retrieved by analyzing published microarray data (accession number GSE110224) from the Gene Expression Omnibus (GEO) database. The above common targets were used to construct the “herb-active ingredients-target” network by Cytoscape 3.8.0 software. And then, the protein-to-protein interaction（PPI）was constructed and analyzed with BisoGenet and CytoNCA plug-in in Cytoscape. Gene Ontology (GO) functional and the Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment analysis for target genes were then performed using the R package of cluster Profiler. Further, AutoDock Vina software was used to conduct molecular docking studies on the active ingredients and key targets to verify the network pharmacological analysis results.Results: A total of 71 active ingredients of XCHT and 20 potential targets for anti-CRC were identified. The network analysis revealed that quercetin, stigmasterol, kaempferol, baicalein, acacetin may be the key compounds. And PTGS2, NR3C2, CA2, MMP1 may be the key targets. The active ingredients of XCHT interacted with most disease targets of CRC. It fully showed that XCHT exerted its therapeutic effect through the synergistic action of the multi-compound, multi-target, and multi-pathway. Gene ontology enrichment analysis showed 46 GO entries, including 20 biological processes, 6 cellular components, and 20 molecular functions. 11 KEGG signaling pathways had been identified, including IL-17 signaling pathway, TNF signaling pathway, Toll-like receptor signaling pathway, and NF-kappa B signaling pathway. It showed that XCHT played a role in the treatment of CRC by regulating different signal pathways. Molecular docking confirmed the correlation between five core compounds (including quercetin, stigmasterol, kaempferol, baicalein, and acacetin) and PTGS2.Conclusion: The potential active ingredients, possible targets, and key biological pathways for the efficacy of XCHT in the treatment of CRC were preliminarily described, which provided a theoretical basis for further experimental verification research.

scholarly journals Potential Mechanism of Ziyin Tongluo Formula in the Treatment of Postmenopausal Osteoporosis：based on Network Pharmacology and Ovariectomized Rat Model

2021 ◽  
Author(s):  
Chen Rongbin ◽  
Yang Yingdong ◽  
Sun Kai ◽  
Liu Shan ◽  
Guo Wei ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Rat Model ◽  
Enrichment Analysis ◽  
Enzyme Linked Immunosorbent Assay ◽  
Therapeutic Effects ◽  
Active Ingredients ◽  
Active Compounds ◽  
Osteoclast Activity ◽  
Core Proteins ◽  
Key Genes

Abstract BackgroundAmending from ancient classic, Ziyin Tongluo Formula (ZYTLF) has been prescribed to treat Postmenopausal osteoporosis (PMOP) for decades and obtained beneficial effect. However, the possible mechanisms of it are still unknown. MethodsOvariectomized rat model were established to validate the therapeutic effect of ZYTLF on PMOP by Micro-CT bone analysis and pathological observation. Subsequently, active ingredients of ZYTLF and corresponding putative targets were identified by online databases. Overlapping genes were obtained by mining genes associated with PMOP and then overlapping them with the putative targets. Key genes were selected from the multiple constructed and analyzed networks. GO and KEGG pathway enrichment analysis were performed by importing the key genes to the DAVID database. Moreover, validation of the binding association between key targets and their corresponding active compounds were accomplished by AutoDock Tools and other softwares. Lastly, Enzyme linked immunosorbent assay (Elisa) detection and Western blot analysis were utilized to further explore the possible mechanism of ZYTLF on PMOP. ResultsWith 129 target genes interacting with PMOP, 92 active compounds of ZYTLF corresponded to 243 targets, and 50 key genes were chosen. Network analysis revealed the top 10 active ingredients, such as quercetin, kaempferol and the top 50 key genes, such as ERα, p38 MAPK , p-AKT, TGF-β1. Enrichment analysis uncovered multiple signaling pathways, including estrogen signaling pathway, TNF signaling pathway, PI3K-Akt signaling pathway, MAPK signaling pathway. Furthermore, our finding of the foremost active compounds were tightly bound to the core proteins was verified by molecular docking analysis. We confirmed that the prescription of ZYTLF could ameliorate the OVX-induced bone loss, suppress the osteoclast activity and boost osteoblastg ability through experimental studies. ConclusionThe potential mechanisms and therapeutic effects of ZYTLF against PMOP may be ascribed to inhabit osteoclast activity, boost osteoblast activity and enhance the expression of ERα .

scholarly journals Predicting the Molecular Mechanism of Sini Jia Renshen Decoction in Treating Severe COVID-19 Patients Based on Network Pharmacology and Molecular Docking

2021 ◽  
Vol 16 (12) ◽  
pp. 1934578X2110592
Author(s):  
Yi Wen Liu ◽  
Ai Xia Yang ◽  
Li Lu ◽  
Tie Hua Huang
Keyword(s):  
Molecular Docking ◽  
Protein Interactions ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Protein Protein Interactions ◽  
Active Ingredients ◽  
Active Compounds ◽  
Pathway Network ◽  
Function Enrichment Analysis

Objective: To explore the potential mechanism of Sini jia Renshen Decoction (SJRD) in the treatment of COVID-19 based on network pharmacology and molecular docking. Methods: The active compounds and potential therapeutic targets of SJRD were collected through the Traditional Chinese Medicine Systems Pharmacology Database (TCMSP). Then a string database was used to build a protein–protein interactions (PPI) network between proteins, and use the David database to perform gene ontology (GO) function enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis on core targets. Then we used Cytoscape software to construct an active ingredients-core target-signaling pathway network, and finally the active ingredients of SJRD were molecularly docked with the core targets to predict the mechanism of SJRD in the treatment of COVID-19. Results: A total of 136 active compounds, 51 core targets and 93 signaling pathways were selected. Molecular docking results revealed that quercetin, 3,22-dihydroxy-11-oxo-delta(12)-oleanene-27-alpha-methoxycarbonyl-29-oic acid, 18α-hydroxyglycyrrhetic acid, gomisin B and ignavine had considerable binding ability with ADRB2, PRKACA, DPP4, PIK3CG and IL6. Conclusions: This study preliminarily explored the mechanism of multiple components，multiple targets，and multiple pathways of SJRD in the treatment of COVID-19 by network pharmacology．

scholarly journals Molecular mechanism underlying the hypolipidemic effect of Shanmei Capsule based on network pharmacology and molecular docking

2021 ◽  
Vol 29 ◽  
pp. 239-256
Author(s):  
Qian Wang ◽  
Lijing Du ◽  
Jiana Hong ◽  
Zhenlin Chen ◽  
Huijian Liu ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Molecular Mechanism ◽  
Kegg Pathway ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Signal Pathways ◽  
Hypolipidemic Effect ◽  
Active Ingredients ◽  
Pathway Enrichment

BACKGROUND: Shanmei Capsule is a famous preparation in China. However, the related mechanism of Shanmei Capsule against hyperlipidemia has yet to be revealed. OBJECTIVE: To elucidate underlying mechanism of Shanmei Capsule against hyperlipidemia through network pharmacology approach and molecular docking. METHODS: Active ingredients, targets of Shanmei Capsule as well as targets for hyperlipidemia were screened based on database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were performed via Database for Annotation, Visualization, and Integrated Discovery (DAVID) 6.8 database. Ingredient-target-disease-pathway network was visualized utilizing Cytoscape software and molecular docking was performed by Autodock Vina. RESULTS: Seventeen active ingredients in Shanmei Capsule were screened out with a closely connection with 34 hyperlipidemia-related targets. GO analysis revealed 40 biological processes, 5 cellular components and 29 molecular functions. A total of 15 signal pathways were enriched by KEGG pathway enrichment analysis. The docking results indicated that the binding activities of key ingredients for PPAR-α are equivalent to that of the positive drug lifibrate. CONCLUSIONS: The possible molecular mechanism mainly involved PPAR signaling pathway, Bile secretion and TNF signaling pathway via acting on MAPK8, PPARγ, MMP9, PPARα, FABP4 and NOS2 targets.

scholarly journals Potential mechanisms of Guizhi decoction against hypertension based on network pharmacology and Dahl salt-sensitive rat model

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Jiye Chen ◽  
Yongjian Zhang ◽  
Yongcheng Wang ◽  
Ping Jiang ◽  
Guofeng Zhou ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Rat Model ◽  
Experimental Studies ◽  
Matrix Metalloproteinase 2 ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Therapeutic Effects ◽  
Active Ingredients ◽  
Active Compounds ◽  
Guizhi Decoction

Abstract Background Guizhi decoction (GZD), a classical Chinese herbal formula, has been widely used to treat hypertension, but its underlying mechanisms remain elusive. The present study aimed to explore the potential mechanisms and therapeutic effects of GZD on hypertension by integrating network pharmacology and experimental validation. Methods The active ingredients and corresponding targets were collected from the Traditional Chinese Medicine Systems Pharmacology database and Analysis Platform (TCMSP). The targets related to hypertension were identified from the CTD, GeneCards, OMIM and Drugbank databases. Multiple networks were constructed to identify the key compounds, hub targets, and main biological processes and pathways of GZD against hypertension. The Surflex-Dock software was used to validate the binding affinity between key targets and their corresponding active compounds. The Dahl salt-sensitive rat model was used to evaluate the therapeutic effects of GZD against hypertension. Results A total of 112 active ingredients, 222 targets of GZD and 341 hypertension-related targets were obtained. Furthermore, 56 overlapping targets were identified, five of which were determined as the hub targets for experimental verification, including interleukin 6 (IL-6), C–C motif chemokine 2 (CCL2), IL-1β, matrix metalloproteinase 2 (MMP-2), and MMP-9. Pathway enrichment analysis results indicated that 56 overlapping targets were mainly enriched in several inflammation pathways such as the tumor necrosis factor (TNF) signaling pathway, Toll-like receptor (TLR) signaling pathway and nuclear factor kappa-B (NF-κB) signaling pathway. Molecular docking confirmed that most active compounds of GZD could bind tightly to the key targets. Experimental studies revealed that the administration of GZD improved blood pressure, reduced the area of cardiac fibrosis, and inhibited the expression of IL-6, CCL2, IL-1β, MMP-2 and MMP-9 in rats. Conclusion The potential mechanisms and therapeutic effects of GZD on hypertension may be attributed to the regulation of cardiac inflammation and fibrosis.

scholarly journals Integrating Network Pharmacology with Molecular Docking to Unravel the Active Compounds and Potential Mechanism of Simiao Pill Treating Rheumatoid Arthritis

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Mengshi Tang ◽  
Xi Xie ◽  
Pengji Yi ◽  
Jin Kang ◽  
Jiafen Liao ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Molecular Docking ◽  
Signaling Pathway ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Binding Activity ◽  
New Combination ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Potential Mechanism

Objective. To explore the main components and unravel the potential mechanism of simiao pill (SM) on rheumatoid arthritis (RA) based on network pharmacological analysis and molecular docking. Methods. Related compounds were obtained from TCMSP and BATMAN-TCM database. Oral bioavailability and drug-likeness were then screened by using absorption, distribution, metabolism, and excretion (ADME) criteria. Additionally, target genes related to RA were acquired from GeneCards and OMIM database. Correlations about SM-RA, compounds-targets, and pathways-targets-compounds were visualized through Cytoscape 3.7.1. The protein-protein interaction (PPI) network was constructed by STRING. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed via R packages. Molecular docking analysis was constructed by the Molecular Operating Environment (MOE). Results. A total of 72 potential compounds and 77 associated targets of SM were identified. The compounds-targets network analysis indicated that the 6 compounds, including quercetin, kaempferol, baicalein, wogonin, beta-sitosterol, and eugenol, were linked to ≥10 target genes, and the 10 target genes (PTGS1, ESR1, AR, PGR, CHRM3, PPARG, CHRM2, BCL2, CASP3, and RELA) were core target genes in the network. Enrichment analysis indicated that PI3K-Akt, TNF, and IL-17 signaling pathway may be a critical signaling pathway in the network pharmacology. Molecular docking showed that quercetin, kaempferol, baicalein, and wogonin have good binding activity with IL6, VEGFA, EGFR, and NFKBIA targets. Conclusion. The integrative investigation based on bioinformatics/network topology strategy may elaborate on the multicomponent synergy mechanisms of SM against RA and provide the way out to develop new combination medicines for RA.

scholarly journals Study on the Multitarget Mechanism of Sanmiao Pill on Gouty Arthritis Based on Network Pharmacology

2020 ◽  
Vol 2020 ◽  
pp. 1-11 ◽  
Author(s):  
Huiqin Qian ◽  
Qianqian Jin ◽  
Yichen Liu ◽  
Ning Wang ◽  
Yuru Chu ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Gouty Arthritis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Regulation Of Transcription ◽  
Receptor Signaling ◽  
Active Compounds ◽  
Receptor Signaling Pathway ◽  
Compound Target

Sanmiao pill (SMP), a Chinese traditional formula, had been used to treat gouty arthritis (GA). However, the active compounds and underlying mechanism remained unclear. Hence, network pharmacology and molecular docking were utilized to explore bioactive compounds and potential mechanism of action of SMP in treating GA. In the study, the compounds of SMP, corresponding targets, and GA-related targets were mined from various pharmacological databases. Then, herb-compound-target, compound-target, PPI, and target-pathway networks were constructed. Ultimately, molecular docking was carried out to verify the predicted results. The results indicated that 47 active compounds, 338 targets, and 144 disease targets were collected. Network analysis implied that Phellodendron chinense Schneid. played a vital role in the whole formula. Moreover, 7 compounds (quercetin, kaempferol, wogonin, rutaecarpine, baicalein, beta-sitosterol, and stigmasterol) and 4 targets (NFKB1, RELA, MAPK1, and TNF) might be the kernel compounds and targets of SMP against GA. According to GOBP and KEGG pathway enrichment analysis and target-pathway network, SMP might exert a therapeutic role in GA by regulating numerous biological processes and pathways, including lipopolysaccharide-mediated signaling pathway, positive regulation of transcription, Toll-like receptor signaling pathway, JAK-STAT signaling pathway, NOD-like receptor signaling pathway, and MAPK signaling pathway. The results of molecular docking showcased that 11 pairs of compound with targets had tight binding strength. Thereinto, 4 compounds of MAPK1 and 5 compounds of NFKB1 possessed a better combination, suggesting that MAPK1 and NFKB1 might be considered as therapeutic targets in treatment of GA. This study verified that SMP had synergistic effect on GA by multicomponents, multitargets, and multipathways.

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