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 Integrating Network Pharmacology and Experimental Validation Deciphers the Mechanism of Guizhi Fuling Wan against Adenomyosis

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Haoxian Wang ◽  
Jihong Zhang ◽  
Qinqin Zhu ◽  
Xianyun Fu ◽  
Chenjie Li
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Kegg Pathway ◽  
Animal Experiments ◽  
Enrichment Analysis ◽  
Estrogen Signaling ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Pathway Enrichment ◽  
Verification Methods

Aim. This study aimed to predict the key targets and endocrine mechanisms of Guizhi Fuling Wan (GZFLW) in treating adenomyosis (AM) through network pharmacology, molecular docking, and animal experiment verification. Methods. The related ingredients and targets of GZFLW in treating AM were screened out using TCMSP, BATMAN-TCM, SwissTargetPrediction, and PubChem Database. Then, the protein-protein interaction (PPI) analysis and the network of compound-hub targets were constructed. At the same time, the key targets were uploaded to the Metascape Database for KEGG pathway enrichment analysis. After that, the molecular docking technology of the main active components and hub targets was performed. Furthermore, animal experiments were used to verify the results of network pharmacology analysis. Results. A total of 55 active ingredients of GZFLW and 44 overlapping targets of GZFLW in treating AM were obtained. After screening, 25 hub targets were collected, including ESR1, EGF, and EGFR. Then, the KEGG pathway enrichment analysis results indicated that the endocrine therapeutic mechanism of GZFLW against AM is mainly associated with the estrogen signaling pathway, endocrine resistance, and an EGFR tyrosine kinase signaling pathway. Then, molecular docking showed that the significant compounds of GZFLW had a strong binding ability with ERα and EGFR. More importantly, the animal experiments confirmed that the GZFLW could downregulate the abnormal infiltration of the endometrial epithelium into the myometrium and had no interference with the normal sexual cycle. This effect may be directly related to intervening the local estrogen signaling pathway of the endometrial myometrial interface (EMI). It may also be associated with the myometrium cells’ estrogen resistance via GPER/EGFR signaling pathway. Conclusion. The endocrine mechanism of GZFLW in treating AM was explored based on network pharmacology, molecular docking, and animal experiments, which provided a theoretical basis for the clinical application of GZFLW.

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.

Systematic Investigation of Quercetin for Treating Cardiovascular Disease Based on Network Pharmacology

2019 ◽  
Vol 22 (6) ◽  
pp. 411-420 ◽  
Author(s):  
Xian-Jun Wu ◽  
Xin-Bin Zhou ◽  
Chen Chen ◽  
Wei Mao
Keyword(s):  
Cardiovascular Disease ◽  
Cardiovascular Diseases ◽  
Signaling Pathway ◽  
Kegg Pathway ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Therapeutic Effects ◽  
Pathway Enrichment ◽  
Compound Target

Aim and Objective: Cardiovascular disease is a serious threat to human health because of its high mortality and morbidity rates. At present, there is no effective treatment. In Southeast Asia, traditional Chinese medicine is widely used in the treatment of cardiovascular diseases. Quercetin is a flavonoid extract of Ginkgo biloba leaves. Basic experiments and clinical studies have shown that quercetin has a significant effect on the treatment of cardiovascular diseases. However, its precise mechanism is still unclear. Therefore, it is necessary to exploit the network pharmacological potential effects of quercetin on cardiovascular disease. Materials and Methods: In the present study, a novel network pharmacology strategy based on pharmacokinetic filtering, target fishing, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, compound-target-pathway network structured was performed to explore the anti- cardiovascular disease mechanism of quercetin. Results:: The outcomes showed that quercetin possesses favorable pharmacokinetic profiles, which have interactions with 47 cardiovascular disease-related targets and 12 KEGG signaling pathways to provide potential synergistic therapeutic effects. Following the construction of Compound-Target-Pathway (C-T-P) network, and the network topological feature calculation, we obtained top 10 core genes in this network which were AKT1, IL1B, TNF, IL6, JUN, CCL2, FOS, VEGFA, CXCL8, and ICAM1. KEGG pathway enrichment analysis. These indicated that quercetin produced the therapeutic effects against cardiovascular disease by systemically and holistically regulating many signaling pathways, including Fluid shear stress and atherosclerosis, AGE-RAGE signaling pathway in diabetic complications, TNF signaling pathway, MAPK signaling pathway, IL-17 signaling pathway and PI3K-Akt signaling pathway.

scholarly journals The Underlying Mechanism of Chinese Herb of Regulating Marrow in the Treatment of  Osteonecrosis of the Femoral Head Based on Network Pharmacology and Molecular Docking

2021 ◽  
Author(s):  
Xiaojian Wang ◽  
Rui Wang ◽  
Ting Xu ◽  
Hongting Jin ◽  
Peijian Tong ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Chinese Medicine ◽  
Signaling Pathway ◽  
Kegg Pathway ◽  
Enrichment Analysis ◽  
Underlying Mechanism ◽  
Chinese Herbs ◽  
Network Pharmacology ◽  
Active Components ◽  
Pathway Enrichment

Abstract Background The lesion of marrow is a crucial factor in orthopedic diseases, which is recognized by orthopedics-traumatology expert from "Zhe-School of Chinese Medicine". The Chinese herbs of regulating marrow has been widely used to treat osteonecrosis of the femoral head (ONFH) in China, while the interaction mechanisms were still elucidated. Thus, we conducted this study to explore the underlying mechanism of the five highest-frequency Chinese herbs of regulating marrow(HF-CHRM) in the treatment of ONFH with the aid of network pharmacology(NP) and molecular docking(MD). Methods The active components and potential targets of HF-CHRM were obtained through several online databases, such as Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP), UniProt database. The gene targets related to ONFH were collected with the help of the OMIM and GeneCards disease-related databases. The "drug- component-target-disease" network and protein-protein interaction(PPI) network of the drug and disease intersecting targets were constructed by using Cytoscape software and the STRING database. R software was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. The MD of critical components and targets was carried out using Autodock Vina and Pymol to validate the binding affinity. Results A total of 54 active components, 1074 drug targets and 195 gene targets were obtained. There were 1219 ONFH related targets. 39 drug and disease intersection targets(representative genes: IL6, TP53, VEGFA, ESR1, IL1B) were obtained and considered potential therapeutic targets. 1619 items were obtained by the GO enrichment analysis, including 1517 biological processes, 10 cellular components and 92 molecular functions, which is mainly related to angiogenesis, bone and lipid metabolism and inflammatory reaction. The KEGG pathway enrichment analysis revealed 119 pathways, including AGE-RAGE signaling pathway, PI3K-Akt signaling pathway and IL-17 signaling pathway. MD results showed that quercetin, wogonin, and kaempferol active components had good affinity with IL6, TP53, and VEGFA core proteins. Conclusion The HF-CHRM can treat ONFH by multi-component, multi-target, and multi-pathway comprehensive action.

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 Effect and mechanism of Acoritataninowii Rhizoma and Curcumae Radix on chronic gastritis: a network pharmacology study

2020 ◽  
Author(s):  
Ling Zhang ◽  
Yunkai Dai ◽  
Yuping Li ◽  
Weijing Chen ◽  
Ruliu Li ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Chronic Gastritis ◽  
Protein Interaction ◽  
Target Genes ◽  
Kegg Pathway ◽  
Network Pharmacology ◽  
Signal Pathways ◽  
Ppi Network ◽  
Pathway Enrichment ◽  
Go Enrichment

Abstract Background Chronic gastritis (CG) is an inflammatory disease which is one of the common diseases of the digestive system. To investigate the mechanisms of herbal pair Acoritataninowii Rhizoma(Shichangpu, AR) and Curcumae Radix༈Yujin, CR༉ in treatment of CG based on the network pharmacology. Methods The possible active ingredients and targets of AR-CR were obtained by the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). The UniProt database was used to query the human gene corresponding to each target protein. The genes related to CG were collected from the GeneCards database, the OMIM database, the DisGeNET database and the PharmGKB database. Intersected the target genes of AR-CR and CG, then protein-protein interaction(PPI) network was constructed by STRING website. The overlapped genes were subjected to gene ontology༈GO༉enrichment and Kyoto encyclopedia of genes and genomes༈KEGG༉pathway enrichment analyses by David. Results 45 intersection genes were obtained, and there were 40 targets in the PPI network for protein interaction, the kernel targets with Degree ≥ 10 included AKT1, TNF, JUN, MAPK3, MAPK8 and MAPK1. The Go enrichment analysis was mainly related to protein binding, enzyme binding, protein homodimerization activity, etc. The KEGG pathway enrichment analyses mainly involved the Pathways in cancer, TNF signaling pathway, Apoptosis, and VEGF signaling pathway. Conclusion AR-CR might delayed, blocked or reversed the atrophy, intestinal metaplasia, dysplasia and canceration of gastric mucosa by targeting key proteins and signal pathways,achieved the effect of the treatment of CG.

scholarly journals Mechanism of Youguiyin in the Treatment of Osteoporosis Based on Network Pharmacology and Molecular Docking

2021 ◽  
Author(s):  
Yi Pan ◽  
Wanlu Zhao ◽  
Luping Qin ◽  
Lu Zhang
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Transcriptional Gene Silencing ◽  
Pathway Enrichment Analysis ◽  
Signal Pathways ◽  
Biological Processes ◽  
The Core ◽  
Material Basis

Abstract Background: Youguiyin (YGY) has been confirmed to treat osteoporosis (OP) in clinical trials, but its specific pharmacological mechanism remains unclear. This study aimed to explore the material basis and potential mechanism of YGY in the treatment of OP based on network pharmacology and molecular docking.Methods: Databases including TCMSP, SwissTargetPrediction database, OMIM, and TTD were used to predict the effective ingredients and relevant targets of YGY in the treatment of OP. The STRING database was used to reveal the relationship between each intersection target protein. Metascape database was used to perform GO enrichment analysis and KEGG pathway enrichment analysis on the intersection targets. Cytoscape 3.6.0 software was used to show the complex network relationship of YGY in the treatment of OP. According to the results of network characteristics analysis, the core effective ingredients and the core targets were screened out. Autodock 4.0 was used for molecular docking and Pymol was used to visualize the docking results.Results: 290 effective ingredients, 1127 targets of the effective ingredients, 273 relevant targets of OP and 17 intersection targets were screened out in total by searching literature and databases. Intersection targets could affect biological processes including regulation of inflammatory response, ossification, negative regulation of post-transcriptional gene silencing, positive regulation of cytokine biosynthetic process and regulation of hormone levels by regulating signal pathways including TNF signaling pathway, osteoclast differentiation, apoptosis, MAPK signaling pathway and PI3K/Akt signaling pathway. Through screening, 14 core effective ingredients and 6 core targets were confirmed. The results of molecular docking showed that most of the core effective ingredients including α-humulene, cinnamaldehyde, denudatine, benzoylhypaconine and quercetin had good binding activity with the core targets including TNF-α, IL-1β and IL-6.Conclusion: Based on network pharmacology and molecular docking, the critical effective ingredients, key targets, important signal pathways and main biological processes of YGY in the treatment of OP were successfully screened out. This study revealed the material basis and the mechanism of YGY in the treatment of OP and provided a theoretical basis for follow-up experimental research and clinical application of YGY.

scholarly journals Pharmacological Mechanisms of Tinglizi against Chronic Heart Failure Determined by Network Pharmacology and Molecular Docking

2022 ◽  
Vol 2022 ◽  
pp. 1-11
Author(s):  
Liangtao Luo ◽  
Haowen Wang ◽  
Guowei Huang ◽  
Lu Zhang ◽  
Xiuwei Li ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Kegg Pathway ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Advanced Glycation ◽  
Pathway Enrichment ◽  
Material Basis ◽  
Glycation End Products ◽  
End Products

Objective. Tinglizi has been extensively used to treat chronic heart failure (CHF) in modern times, but the material basis and pharmacological mechanisms are still unclear. To explore the material basis and corresponding potential targets and to elucidate the mechanism of Tinglizi, network pharmacology and molecular docking methods were utilized. Methods. The main chemical compounds and potential targets of Tinglizi were collected from the pharmacological database analysis platform (TCMSP). The corresponding genes of related action targets were queried through gene cards and UniProt database. The corresponding genes of CHF-related targets were searched through Disgenet database, and the intersection targets were obtained by drawing Venn map with the target genes related to pharmacodynamic components. Then, drug targets and disease targets were intersected and put into STRING database to establish a protein interaction network. The “active ingredient-CHF target” network was constructed with Cytoscape 3.8.2. Finally, Gene Ontology (GO) Enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment of intersection targets were analyzed using metascape. With the aid of SYBYL software, the key active ingredients and core targets were docked at molecular level, and the results were visualized by PyMOL software. Molecular docking was carried out to investigate interactions between active compounds and potential targets. Results. A total of 12 active components in Tinglizi were chosen from the TCMSP database, and 193 corresponding targets were predicted. Twenty-nine potential targets of Tinglizi on CHF were obtained, of which nine were the core targets of this study. Twenty GO items were obtained by GO function enrichment analysis ( P < 0.05 ), and 10 signal pathways were screened by KEGG pathway enrichment analysis ( P < 0.05 ), which is closely related to the treatment of CHF by Tinglizi. The constructed drug compound composition action target disease network shows that quercetin, kaempferol, and other active compounds play a key role in the whole network. The results of molecular docking showed that all the key active ingredients, such as quercetin and isorhamnetin, were able to successfully dock with ADRB2 and HMOX1 with a total score above 5.0, suggesting that these key components have a strong binding force with the targets. Conclusion. Through network pharmacology and molecular docking technology, we found that the main components of Tinglizi in the treatment of CHF are quercetin, kaempferol, β-sitosterol, isorhamnetin, and so on. The action targets are beta 2-adrenergic receptor (ADRB2), heme oxygenase 1 (HMOX1), and so on. The main pathways are advanced glycation end products/receptor for advanced glycation end products (AGE-RAGE) signaling pathway in diabetic complications, hypoxia-inducible factor (HIF-1) signaling pathway, estrogen signaling pathway, and so on. They play an integrated role in the treatment of CHF.

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 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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