scholarly journals Based on Network Pharmacology to Explore the Molecular Mechanism of Buzhong Yiqi Decoction for the Treatment of Gastric Cancer

2021 ◽  
Author(s):  
Ruiping Yang ◽  
Xiaojing Lin ◽  
Chunhui Tao ◽  
Ruixue Jiang
Keyword(s):  
Gastric Cancer ◽  
Molecular Dynamics ◽  
Molecular Docking ◽  
Signaling Pathway ◽  
Molecular Mechanism ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Dynamics Simulation ◽  
Network Pharmacology ◽  
Active Ingredients

Abstract BackgroundBuzhong Yiqi Decoction (BZYQD) has been widely accepted as an alternative treatment for gastric cancer (GC) in China. The present study set out to determine the potential molecular mechanism of BZYQD in the treatment of GC by means of network pharmacology, molecular docking, and molecular dynamics simulation.MethodsThe potential active ingredients and targets of BZYQD were screened out through the Traditional Chinese Medicine Systems Pharmacology (TCMSP). GC-related targets were screened out through the GeneCards database, and the intersection targets of BZYQD and GC were obtained by using the Venn diagram online tool. Then, the TCM-Active Ingredient-Target network was constructed by using the Cytoscape, and the protein-protein interaction (PPI) network was constructed by using the STRING database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of the effective targets of BZYQD in GC were performed through the Metascape platform. Finally, the molecular docking between the compounds and the target proteins was performed by using the AutoDock Vina software. The simulation of molecular dynamics was conducted for the optimal protein-ligand complex obtained by molecular docking using the Amber18 software.ResultsA total of 150 active ingredients of BZYQD were retrieved, corresponding to 136 targets of GC. The key active ingredients were quercetin, kaempferol, nobiletin, naringenin, and formononetin. The core targets were AKT1, STAT3, TP53, MAPK1, and MAPK3. GO functional enrichment analysis showed that BZYQD treated GC by affecting various biological processes such as oxidative stress, chemical stress, lipopolysaccharide reaction, and apoptosis. KEGG pathway enrichment analysis indicated that the apoptosis signaling pathway, PI3K/Akt signaling pathway, proteoglycan in cancer, IL-17 signaling pathway, TNF signaling pathway, and HIF-1 signaling pathway were involved. Molecular docking results revealed the highest binding energy for MAPK3 and naringenin. The stable binding of MAPK3 and naringenin was also demonstrated in the molecular dynamics simulation test, with the binding free energy of -25kcal/mol.ConclusionThis study preliminarily revealed the multi-component, multi-target, and multi-pathway characteristics of BZYQD against GC, laying a scientific basis for further research on the molecular mechanism of BZYQD.

scholarly journals Molecular Mechanism of Gelsemium elegans (Gardner and Champ.) Benth. Against Neuropathic Pain Based on Network Pharmacology and Experimental Evidence

2022 ◽  
Vol 12 ◽  
Author(s):  
Wancai Que ◽  
Zhaoyang Wu ◽  
Maohua Chen ◽  
Binqing Zhang ◽  
Chuihuai You ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Neuropathic Pain ◽  
Molecular Dynamics Simulation ◽  
Experimental Evidence ◽  
Signaling Pathway ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Dynamics Simulation ◽  
Network Pharmacology ◽  
Holistic View

Gelsemium elegans (Gardner and Champ.) Benth. (Gelsemiaceae) (GEB) is a toxic plant indigenous to Southeast Asia especially China, and has long been used as Chinese folk medicine for the treatment of various types of pain, including neuropathic pain (NPP). Nevertheless, limited data are available on the understanding of the interactions between ingredients-targets-pathways. The present study integrated network pharmacology and experimental evidence to decipher molecular mechanisms of GEB against NPP. The candidate ingredients of GEB were collected from the published literature and online databases. Potentially active targets of GEB were predicted using the SwissTargetPrediction database. NPP-associated targets were retrieved from GeneCards, Therapeutic Target database, and DrugBank. Then the protein-protein interaction network was constructed. The DAVID database was applied to Gene Ontology and Kyoto Encyclopedia of Genes and Genome pathway enrichment analysis. Molecular docking was employed to validate the interaction between ingredients and targets. Subsequently, a 50 ns molecular dynamics simulation was performed to analyze the conformational stability of the protein-ligand complex. Furthermore, the potential anti-NPP mechanisms of GEB were evaluated in the rat chronic constriction injury model. A total of 47 alkaloids and 52 core targets were successfully identified for GEB in the treatment of NPP. Functional enrichment analysis showed that GEB was mainly involved in phosphorylation reactions and nitric oxide synthesis processes. It also participated in 73 pathways in the pathogenesis of NPP, including the neuroactive ligand-receptor interaction signaling pathway, calcium signaling pathway, and MAPK signaling pathway. Interestingly, 11-Hydroxyrankinidin well matched the active pockets of crucial targets, such as EGFR, JAK1, and AKT1. The 11-hydroxyrankinidin-EGFR complex was stable throughout the entire molecular dynamics simulation. Besides, the expression of EGFR and JAK1 could be regulated by koumine to achieve the anti-NPP action. These findings revealed the complex network relationship of GEB in the “multi-ingredient, multi-target, multi-pathway” mode, and explained the synergistic regulatory effect of each complex ingredient of GEB based on the holistic view of traditional Chinese medicine. The present study would provide a scientific approach and strategy for further studies of GEB in the treatment of NPP in the future.

scholarly journals A network pharmacology-based investigation on the bioactive ingredients and molecular mechanisms of Gelsemium elegans Benth against colorectal cancer

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Wancai Que ◽  
Maohua Chen ◽  
Ling Yang ◽  
Bingqing Zhang ◽  
Zhichang Zhao ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Molecular Dynamics ◽  
Molecular Docking ◽  
Molecular Dynamics Simulation ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Molecular Mechanism ◽  
Enrichment Analysis ◽  
Dynamics Simulation ◽  
Network Pharmacology

Abstract Background Colorectal cancer (CRC) remains one of the leading causes of cancer-related death worldwide. Gelsemium elegans Benth (GEB) is a traditional Chinese medicine commonly used for treatment for gastrointestinal cancer, including CRC. However, the underlying active ingredients and mechanism remain unknown. This study aims to explore the active components and the functional mechanisms of GEB in treating CRC by network pharmacology-based approaches. Methods Candidate compounds of GEB were collected from the Traditional Chinese Medicine@Taiwan, Traditional Chinese Medicines Integrated Database, Bioinformatics Analysis Tool for Molecular mechanism of Traditional Chinese Medicine, and published literature. Potentially active targets of compounds in GEB were retrieved from SwissTargetPrediction databases. Keywords “colorectal cancer”, “rectal cancer” and “colon cancer” were used as keywords to search for related targets of CRC from the GeneCards database, then the overlapped targets of compounds and CRC were further intersected with CRC related genes from the TCGA database. The Cytoscape was applied to construct a graph of visualized compound-target and pathway networks. Protein-protein interaction networks were constructed by using STRING database. The DAVID tool was applied to carry out Gene Ontology and Kyoto Encyclopedia of Genes and Genome pathway enrichment analysis of final targets. Molecular docking was employed to validate the interaction between compounds and targets. AutoDockTools was used to construct docking grid box for each target. Docking and molecular dynamics simulation were performed by Autodock Vina and Gromacs software, respectively. Results Fifty-three bioactive compounds were successfully identified, corresponding to 136 targets that were screened out for the treatment of CRC. Functional enrichment analysis suggested that GEB exerted its pharmacological effects against CRC via modulating multiple pathways, such as pathways in cancer, cell cycle, and colorectal cancer. Molecular docking analysis showed that the representative compounds had good affinity with the key targets. Molecular dynamics simulation indicated that the best hit molecules formed a stable protein-ligand complex. Conclusion This network pharmacology study revealed the multiple ingredients, targets, and pathways synergistically involved in the anti-CRC effect of GEB, which will enhance our understanding of the potential molecular mechanism of GEB in treatment for CRC and lay a foundation for further experimental research.

scholarly journals Exploring the Molecular Mechanism of Action of Yinchen Wuling Powder for the Treatment of Hyperlipidemia, Using Network Pharmacology, Molecular Docking, and Molecular Dynamics Simulation

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Jiahao Ye ◽  
Lin Li ◽  
Zhixi Hu
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Mechanism Of Action ◽  
Core Protein ◽  
Enrichment Analysis ◽  
Dynamics Simulation ◽  
Network Pharmacology ◽  
Advanced Glycation ◽  
Active Ingredients ◽  
Glycation End Products

Background. Yinchen Wuling powder is often used to treat clinical hyperlipidemia, although its mechanism of action remains unclear. In this study, we aimed to investigate the active ingredients found in Yinchen Wuling powder and find its mechanism of action when treating hyperlipidemia, using a combination of network pharmacology, molecular docking, and molecular dynamics simulation approaches. Methods. The TCMSP database was used to obtain the principle active ingredients found in Yinchen Wuling powder and the NCBI and DisGeNet databases were used to obtain the main target genes involved in hyperlipidemia, and the intersectional targets were obtained by EXCEL. We also used Cytoscape 3.7.2 software to construct a “Traditional Chinese Medicine-Active Ingredient-Target” network and use STRING platform to conduct “protein-protein interactional” (PPI) analyses on the intersection targets. Bioconductor software and RX 64 4.0.0 software were then used to perform GO functional enrichment analysis and KEGG pathway enrichment analysis on the targets. Molecular docking of core protein-ligand interactions was modeled using AutoDock Vina software. A simulation of molecular dynamics was conducted for the optimal core protein-ligand obtained by molecular docking using Amber18 software. Results. A total of 63 active ingredients were found in Yinchen Wuling powder, corresponding to 175 targets, 508 hyperlipidemia targets, and 55 intersection targets in total. Cytoscape 3.7.2 showed that the key active ingredients were quercetin, isorhamnetin, taxifolin, demethoxycapillarisin, and artepillin A. The PPI network showed that the key proteins involved were AKT1, IL6, VEGFA, and PTGS2. GO enrichment analysis found that genes were enriched primarily in response to oxygen levels and nutrient levels of the vesicular lumen and were associated with membrane rafts. These were mainly enriched in AGE-RAGE (advanced glycation end products-receptor for advanced glycation end products) signaling pathway in diabetic complications, fluid shear stress, and atherosclerosis, as well as other pathways. The molecular docking results indicated key binding activity between PTGS2-quercetin, PTGS2-isorhamnetin, and PTGS2-taxifolin. Results from molecular dynamics simulations showed that PTGS2-quercetin, PTGS2-isorhamnetin, and PTGS2-taxifolin bound more stably, and their binding free energies were PTGS2-quercetin -29.5 kcal/mol, PTGS2-isorhamnetin -32 kcal/mol, and PTGS2-taxifolin -32.9 kcal/mol. Conclusion. This study is based on network pharmacology and reveals the potential molecular mechanisms involved in the treatment of hyperlipidemia by Yinchen Wuling powder.

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 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 Network Pharmacology-Based Approach to Investigate the Mechanisms ofHedyotis diffusaWilld. in the Treatment of Gastric Cancer

2018 ◽  
Vol 2018 ◽  
pp. 1-17 ◽  
Author(s):  
Xinkui Liu ◽  
Jiarui Wu ◽  
Dan Zhang ◽  
Kaihuan Wang ◽  
Xiaojiao Duan ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Cell Cycle ◽  
Signaling Pathway ◽  
Excision Repair ◽  
Enrichment Analysis ◽  
Cyclin B1 ◽  
Functional Enrichment ◽  
Network Pharmacology ◽  
Ras Signaling ◽  
Therapeutic Effects

Background.Hedyotis diffusaWilld. (HDW) is one of the renowned herbs often used in the treatment of gastric cancer (GC). However, its curative mechanism has not been fully elucidated.Objective. To systematically investigate the mechanisms of HDW in GC.Methods. A network pharmacology approach mainly comprising target prediction, network construction, and module analysis was adopted in this study.Results. A total of 353 targets of the 32 bioactive compounds in HDW were obtained. The network analysis showed that CA isoenzymes, p53, PIK3CA, CDK2,P27Kip1, cyclin D1, cyclin B1, cyclin A2, AKT1, BCL2, MAPK1, and VEGFA were identified as key targets of HDW in the treatment of GC. The functional enrichment analysis indicated that HDW probably produced the therapeutic effects against GC by synergistically regulating many biological pathways, such as nucleotide excision repair, apoptosis, cell cycle, PI3K/AKT/mTOR signaling pathway, VEGF signaling pathway, and Ras signaling pathway.Conclusions. This study holistically illuminates the fact that the pharmacological mechanisms of HDW in GC might be strongly associated with its synergic modulation of apoptosis, cell cycle, differentiation, proliferation, migration, invasion, and angiogenesis.

scholarly journals Molecular Targets and Mechanisms of Scutellariae radix-Coptidis rhizoma Drug Pair for the Treatment of Ulcerative Colitis Based on Network Pharmacology and Molecular Docking

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Kai Niu ◽  
Qifang Li ◽  
Yuan Liu ◽  
Yi Qiao ◽  
Bingbing Li ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Active Ingredient ◽  
Enrichment Analysis ◽  
Akt Signaling ◽  
Network Pharmacology ◽  
Akt Signaling Pathway ◽  
Active Ingredients ◽  
Scutellariae Radix ◽  
Drug Ingredient

This study aims to analyze the targets of the effective active ingredients of Scutellariae radix-Coptidis rhizoma drug pair (SCDP) in ulcerative colitis (UC) by network pharmacology and molecular docking and to explore the associated therapeutic mechanism. The effective active ingredients and targets of SCDP were determined from the TCMSP database, and the drug ingredient-target network was constructed using the Cytoscape software. The disease targets related to UC were searched in GeneCards, DisGeNET, OMIM, and DrugBank databases. Then, the drug ingredient and disease targets were intersected to construct a protein-protein interaction network through the STRING database. The Metascape database was used for the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses of the predicted targets of SCDP for UC. The Autodock software was used for molecular docking between the main active ingredient and the core target to evaluate the binding ability. SCDP has 43 effective active ingredients and 134 intersection targets. Core targets included AKT1, TP53, IL-6, VEGFA, CASP3, JUN, TNF, MYC, EGFR, and PTGS2. GO functional enrichment analysis showed that biological process was mainly associated with a cytokine-mediated signaling pathway, response to an inorganic substance, response to a toxic substance, response to lipopolysaccharide, reactive oxygen species metabolic process, positive regulation of cell death, apoptotic signaling pathway, and response to wounding. KEGG enrichment analysis showed main pathway concentrations were related to pathways in cancer, AGE-RAGE signaling pathway in diabetic complications, bladder cancer, IL-17 signaling pathway, apoptosis, p53 signaling pathway, and PI3K-Akt signaling pathway. The drug active ingredient-core target-key pathway network contains 41 nodes and 108 edges, of which quercetin, wogonin, baicalein, acacetin, oroxylin A, and beta-sitosterol are important active ingredients; PTGS2, CASP3, TP53, IL-6, TNF, and AKT1 are important targets; and the pathways involved in UC treatment include pathways in cancer, PI3K-Akt signaling pathway, AGE-RAGE signaling pathway in diabetic, apoptosis, IL-17 signaling pathway and herpes simplex infection. The active ingredient has a good binding capacity to the core target. SCDP key active ingredients are mainly quercetin, wogonin, baicalein, acacetin, oroxylin A, and beta-sitosterol, which function mainly by regulating targets, such as PTGS2, CASP3, TP53, IL-6, TNF, and AKT1, and are associated with multiple signaling pathways as pathways in cancer, PI3K-Akt signaling pathway, apoptosis, IL-17 signaling pathways.

scholarly journals Molecular Mechanism of Danxiong Tongmai Granules in Treatment of Coronary Heart Disease

2021 ◽  
Author(s):  
Jiahao Ye ◽  
Ruiping Yang ◽  
Zhixi Hu ◽  
Lin Li ◽  
Senjie Zhong ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Coronary Heart Disease ◽  
Heart Disease ◽  
Molecular Docking ◽  
Enrichment Analysis ◽  
Dynamics Simulation ◽  
Venn Diagram ◽  
Network Pharmacology ◽  
Ppi Network ◽  
Ligand Interaction

Abstract Background: Network pharmacology has been widely adopted for mechanistic studies of Traditional Chinese Medicines (TCM). The present study uses network pharmacology to investigate the main ingredients, targets and pathways of Danxiong Tongmai Granules (DXTMG) in the treatment of coronary heart disease (CHD). We aim to validate our findings using molecular docking and molecular dynamics simulations.Methods: TCM compounds and targets were identified via searches in the BATMAN-TCM database, and the GeneCards database were used to obtain the main target genes involved in CHD, We combined disease targets with the drug targets to identify common targets, and draw a Venn diagram to visualize the results. The "TCM-compound-target" network was plotted using Cytoscape 3.7.2 software and a protein-protein interaction (PPI) network was constructed using the STRING database from which core targets were obtained. Gene ontology (GO) function analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed for common drug-disease targets using R Version 4.0.4 (64 bit) software. Molecular docking of core protein-small molecule ligand interaction was modeled using AutoDock Vina software. A simulation of molecular dynamics was conducted for the optimal protein-ligand complex obtained by molecular docking using Amber18 software.Results: 162 potential targets of DXTMG involved in CHD were identified. These included INS, ALB, IL-6 and TNF according to PPI network studies. GO enrichment analysis identified a total of 3365 GO pathways, including 3049 biological process pathways (BP) concerned with the heart and circulatory system;109 cellular component (CC) pathways, including cation channels and membrane rafts and 207 molecular function (MF) pathways related to receptor ligands and activators. KEGG analysis revealed a total of 137 pathways (p<0.05), including those related to AGE-RAGE signaling associated with diabetic complications, fluid shear stress and atherosclerosis. Molecular docking revealed the highest binding energy for Neocryptotanshinone Ii (the key compound of DXTMG) and TNF. Molecular dynamics simulation indicated stable binding for TNF-Neocryptotanshinone Ii with strong hydrophobic interactions mediated predominantly by the hydrophobic residues, Leu279, Val280 and Phe278 plus hydrogen-bonding with Leu279.Conclusion: The present study reveals novel insights into the mechanism of DXTMG in treating CHD. DXTMG can influence oxidative stress、inflammation response and regulating cardiomyocytes, thereby reducing the occurrence and development of CHD.

scholarly journals Identifying Synergistic Mechanisms of Multiple Ingredients in Shuangbai Tablets against Proteinuria by Virtual Screening and a Network Pharmacology Approach

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Xiaoqin Ma ◽  
Meixiang Yu ◽  
Chenxia Hao ◽  
Wanhua Yang
Keyword(s):  
Molecular Docking ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Active Ingredients ◽  
Human Phenotype ◽  
Herbal Mixture ◽  
Relationship Of

Shuangbai Tablets (SBT), a traditional herbal mixture, has shown substantial clinical efficacy. However, a systematic mechanism of its active ingredients and pharmacological mechanisms of action against proteinuria continues being lacking. A network pharmacology approach was effectual in discovering the relationship of multiple ingredients and targets of the herbal mixture. This study aimed to identify key targets, major active ingredients, and pathways of SBT against proteinuria by network pharmacology approach combined with thin layer chromatography (TLC). Human phenotype (HP) disease analysis, gene ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and molecular docking were used in this study. To this end, a total of 48 candidate targets of 118 active ingredients of SBT were identified. Network analysis showed PTGS2, ESR1, and NOS2 to be the three key targets, and beta-sitosterol, quercetin, and berberine were the three major active ingredients; among them one of the major active ingredients, quercetin, was discriminated by TLC. These results of the functional enrichment analysis indicated that the most relevant disease including these 48 candidate proteins is proteinuria, SBT treated proteinuria by sympathetically regulating multiple biological pathways, such as the HIF-1, RAS, AGE-RAGE, and VEGF signaling pathways. Additionally, molecular docking validation suggested that major active ingredients of SBT were capable of binding to HIF-1A and VEGFA of the main pathways. Consequently, key targets, major active ingredients, and pathways based on data analysis of SBT against proteinuria were systematically identified confirming its utility and providing a new drug against proteinuria.

scholarly journals Siteng Fang Reverses Multidrug Resistance in Gastric Cancer: A Network Pharmacology and Molecular Docking Study

2021 ◽  
Vol 11 ◽  
Author(s):  
Lingjian Guo ◽  
Haixia Shi ◽  
Limin Zhu
Keyword(s):  
Gastric Cancer ◽  
Molecular Docking ◽  
Multidrug Resistance ◽  
Signaling Pathway ◽  
Akt Signaling ◽  
Proteoglycan Synthesis ◽  
Network Pharmacology ◽  
Signal Pathways ◽  
Akt Signaling Pathway ◽  
Active Ingredients

Siteng Fang (STF) has been shown to inhibit migration, invasion, and adhesion as well as promote apoptosis in gastric cancer (GC) cells. However, whether it can reverse the multidrug resistance (MDR) of GC to chemotherapy drugs is unknown. Thus, we aimed to elucidate the mechanism of STF in reversing the MDR of GC. The chemical composition of STF and genes related to GC were obtained from the TCMNPAS(TCM Network Pharmacology Analysis System, TCMNPAS) Database, and the targets of the active ingredients were predicted using the Swiss Target Prediction Database. The obtained data were mapped to obtain the key active ingredients and core targets of STF in treating GC. The active component-target network and protein interaction network were constructed by Cytoscape and String database, and the key genes and core active ingredients were obtained. The biological functions and related signal pathways corresponding to the key targets were analyzed and then verified via molecular docking. A total of 14 core active ingredients of STF were screened, as well as 20 corresponding targets, which were mainly enriched in cancer pathway, proteoglycan synthesis, PI3K-AKT signaling pathway, and focal adhesion. Molecular docking showed that the core active ingredients related to MDR, namely quercetin and diosgenin, could bind well to the target. In summary, STF may reverse the MDR of GC and exert synergistic effect with chemotherapeutic drugs. It mediates MDR mainly through the action of quercetin and diosgenin on the PI3K/AKT signaling pathway. These findings are the first to demonstrate the molecular mechanism of STF in reversing MDR in GC, thus providing a direction for follow-up basic research.

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