scholarly journals Study on the Antianxiety Mechanism of Suanzaoren Decoction Based on Network Pharmacology and Molecular Docking

2021 ◽  
Vol 2021 ◽  
pp. 1-28
Author(s):  
Xiaocong Xu ◽  
Bingbing Gao ◽  
Xiongying Li ◽  
Shanshan Lei
Keyword(s):  
Molecular Docking ◽  
Binding Energy ◽  
Interaction Analysis ◽  
Modern Medicine ◽  
Network Pharmacology ◽  
Active Components ◽  
Material Basis ◽  
Go Enrichment ◽  
Antianxiety Drug ◽  
Analysis Platform

Objective. Suanzaoren Decoction (SZRT) is a classic decoction to calm the nerves in traditional Chinese medicine (TCM). It has been extensively treated as an antianxiety drug in modern times, but the material basis and pharmacological mechanisms are still unclear. To explore the material basis and corresponding potential targets, as well as to elucidate the mechanism of SZRT, network pharmacology and molecular docking methods were utilized. Methods. The main chemical compounds and potential targets of SZRT were collected from the pharmacological database analysis platform (TCMSP). Anxiety targets were obtained from the GeneCards database. Then, a target compound network was established using overlapping genes and the corresponding potential compounds. Protein interaction analysis, GO enrichment, and KEGG pathway enrichment were performed using the STRING database, DAVID database, and KOBAS database. Finally, molecular docking was conducted between MAOB and its corresponding active compound in SZRT to further verify the results. Results. A total of 137 active components in SZRT were screened from the TCMSP database, and 210 corresponding targets were predicted. A total of 5434 anxiety-related targets were obtained from the disease target database, and finally 22 potential targets of SZRT on antianxiety were obtained. The constructed C-T network showed that the average degree of active components was 5.4, and four of them interacted with six or more targets. PPI analysis shows that key genes such as MAOA, MAOB, IL1B, TNF, NR3CI, and HTR3A were identified as potential therapeutic targets. A pathway analysis showed that SZRT may participate in neurotransmitter regulation and immunoregulation in a synergistic way to treat anxiety. The binding energy between the active compounds and MAOB was low, indicating good binding. The results of molecular docking showed that all the 10 active ingredients were able to successfully dock with MAOB, and the binding energy of coumaroyltyramine with MAOB was the lowest, that is, −9.6 kcal/mol, and the binding method was hydrogen bonding. Conclusions. SZRT produces antianxiety effects mainly by affecting the neurotransmitter release, transmission, and immunoregulation. This study provides a new approach to elucidating the molecular mechanism and material basis of SZRT in the treatment of anxiety, and it will also benefit the application of TCM in modern medicine.

scholarly journals Analysis of the Active Components and Mechanism of Three Prescriptions in the Treatment of COVID-19 Via Network Pharmacology and Molecular Docking

2021 ◽  
Vol 16 (9) ◽  
pp. 1934578X2110477
Author(s):  
Fei Wang ◽  
Jia-Hui Chen ◽  
Bo Liu ◽  
Ting Zhang
Keyword(s):  
Molecular Docking ◽  
Binding Energies ◽  
Network Pharmacology ◽  
Active Components ◽  
Chinese Medicines ◽  
Protein Protein Interaction ◽  
Kegg Pathways ◽  
Ppi Networks ◽  
Infection And Inflammation ◽  
Analysis Platform

Purpose: Prescriptions of Han-Shi-Yu-Fei (HSYF), Han-Shi-Zu-Fei (HSZF), and Yi-Du-Bi-Fei (YDBF) were effective in treating COVID-19. Based on network pharmacology and molecular docking, overlapping Traditional Chinese medicines (TCMs), their active components, and core targets were explored in this study. Methods: First, the overlapping TCMs and their active components were collected from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) by evaluating Oral Bioactivity (OB) and Drug Likeness (DL). The overlapping targets of potential components and COVID-19 were collected by SwissTargetPrediction, Gene Cards, and Venn 2.1.0 databases. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment were analyzed via DAVID6.8.1 database. Through comprehensive analysis of the “prescriptions-TCMs-components” (P-T-C), “components-targets-pathways” (C-T-P) and “protein–protein interaction” (PPI) networks constructed by Cytoscape 3.7.1 software, the active components and core targets were obtained. Finally, the binding energies of these components with ACE2 and SARS-CoV-2 3CL were analyzed by AutDockTools-1.5.6 and PyMOL software. Results: In all, five overlapping TCMs, 40 potential active components, and 47 candidate targets were obtained and analyzed in these prescriptions. There were 288 GO entries ( P < 0.05), including 211 biological process (BP), 40 cell composition (CC), and 37 molecular function (MF) entries. Most of the 105 KEGG pathways ( P < 0.05) were involved with viral infection and inflammation. Through “PPI” and “C-T-P” networks, the core targets (EGFR, PTGS2, CDK2, GSK3B, PIK3R1, and MAPK3) and active components (Q27134551, acanthoside B, neohesperidin, and irisolidone) with high degrees were obtained. Molecular docking results showed that the above-mentioned four components could inhibit the binding of ACE2 and SARS-COV-2 3CL to protect against COVID-19. Conclusion: In this study, the active components and core targets of three prescriptions in the treatment of COVID-19 were elaborated by network pharmacology and molecular docking, providing a reference for their applications.

A Study on the Mechanism of Lavender in the Treatment of Insomnia Based on Network Pharmacology

2020 ◽  
Vol 23 (5) ◽  
pp. 419-432
Author(s):  
Yao Wang ◽  
Junbo Zou ◽  
Yanzhuo Jia ◽  
Yulin Liang ◽  
Xiaofei Zhang ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Target Protein ◽  
Ammonium Ion ◽  
Network Pharmacology ◽  
Common Disease ◽  
Active Components ◽  
Target Proteins ◽  
Analysis Platform

Aim and Objective: The common disease of insomnia has complex and diverse clinical manifestations. Lavender represents an effective treatment of insomnia, but the molecular mechanism underlying the effectiveness of this treatment is not clear. The purpose of this study is to investigate the active components, target proteins and molecular pathways of lavender in the treatment of insomnia, thus explaining its possible mechanism. Materials and Methods: Firstly, 54 active components of lavender were identified by gas chromatography-mass spectrometry (GC-MS). The target protein of lavender was predicted by the Traditional Chinese Medicine System Pharmacological Database and Analysis Platform and the SwissTargetPredicating tool, and the target protein of insomnia was predicted by the DisGeNET and DrugBank databases. Then, the "component-target-disease" network diagram was constructed using the Cytoscape 3.7.1 software. KEGG and GO enrichments were analyzed using the R statistical language. Finally, the key target proteins were verified by collecting and verifying the target protein GEO data using the Discovery Studio 3.5 molecular docking verification software. Results: 906 target proteins of lavender were predicted by the Traditional Chinese Medicine System Pharmacological Database and Analysis Platform and the SwissTargetPredicating tool, and 182 insomnia target proteins were predicted by the DisGeNET and DrugBank databases. The results of GO enrichment analysis showed that it included the reaction process of ammonium ion, the regulation of the membrane potential and the secretion of catecholamine, while the results of KEGG enrichment included the calcium signaling pathway, serotonin synapse, morphine addiction and many more. Finally, using the Discovery Studio3.5 molecular docking verification software, it was verified that the key target proteins are ADRB1 and HLA-DRB1. Conclusion: The components in the lavender essential oil include the Ethyl 2-(5-methyl-5-vinyltetrahydrofuran- 2-yl)propan-2-ylcarbonate (0.774); 5-Oxatricyclo[8.2.0.04,6]dodecane, 4,12,12-trimethyl- 9-methylene-, (1R,4R,6R,10S)-(0.147); P-Cymen-7-ol (0.063); .alpha-Humulenem (0.317); Acetic acid, hexyl ester (1.374); etc. The role lavender plays in the treatment of insomnia might be accomplished through the regulation of the key targets ADRB1 and HLA-DRB1.

scholarly journals Identification of Potential Bioactive Ingredients and Mechanisms of the Guanxin Suhe Pill on Angina Pectoris by Integrating Network Pharmacology and Molecular Docking

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Mingmin Wang ◽  
Shuangjie Yang ◽  
Mingyan Shao ◽  
Qian Zhang ◽  
Xiaoping Wang ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Angina Pectoris ◽  
Protein Interaction ◽  
Interaction Analysis ◽  
Network Pharmacology ◽  
Biological Processes ◽  
Protein Protein Interaction ◽  
Go Enrichment ◽  
Chemokine Ligand ◽  
Bioactive Ingredients

The Guanxin Suhe pill (GSP), a traditional Chinese medicine, has been widely used to treat angina pectoris (AP) in Chinese clinical practice. However, research on the bioactive ingredients and underlying mechanisms of GSP in AP remains scarce. In this study, a system pharmacology approach integrating gastrointestinal absorption (GA) evaluation, drug-likeness (DL) evaluation, target exploration, protein-protein-interaction analysis, Gene Ontology (GO) enrichment analysis, network construction, and molecular docking was adopted to explore its potential mechanisms. A total of 481 ingredients from five herbs were collected, and 242 were qualified based on GA and DL evaluation. Target exploration identified 107 shared targets between GSP and AP. Protein-protein interaction identified VEGFA (vascular endothelial growth factor A), TNF (tumor necrosis factor), CCL2 (C-C motif chemokine ligand 2), FN1 (fibronectin 1), MMP9 (matrix metallopeptidase 9), PTGS2 (prostaglandin-endoperoxide synthase 2), IL10 (interleukin 10), CXCL8 (C-X-C motif chemokine ligand 8), IL6 (interleukin 6), and INS (insulin) as hub targets for GSP, which were involved in the inflammatory process, ECM proteolysis, glucose metabolism, and lipid metabolism. GO enrichment identified top pathways in the biological processes, molecular functions, and cell components, explaining GSP’s potential AP treatment mechanism. Positive regulation of the nitric oxide biosynthetic process and the response to hypoxia ranked highest of the biological processes; core targets that GSP can regulate in these two pathways were PTGS2 and NOS2, respectively. Molecular docking verified the interactions between the core genes in the pathway and the active ingredients. The study lays a foundation for further experimental research and clinical application.

scholarly journals Network pharmacology and molecular docking analysis on molecular targets and mechanisms of Angelicae Pubescentis Radix in the treatment of rheumatoid arthritis

2021 ◽  
Author(s):  
yanni yang ◽  
yirixiati aihaiti ◽  
peng xu ◽  
haishi zheng
Keyword(s):  
Rheumatoid Arthritis ◽  
Molecular Docking ◽  
Signaling Pathway ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Receptor Interaction ◽  
Active Components ◽  
Target Proteins ◽  
Go Enrichment ◽  
Go Enrichment Analysis

Abstract Purpose:To explore the potential target proteins underlying the effect of Angelicae Pubescentis Radix(APR) on rheumatoid arthritis (RA) using a network pharmacology and molecular docking approach .Methods:First, the active components and target proteins of APR and RA related disease targets were obtained from the TCMSP, Gene Card,OMIM,DisGeNET and STRING databases. Then the active ingredient target in the RA network diagram was drawn using Cytoscape 3.7.1 software. Protein-protein interaction analysis, Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway analyses were carried out using the STRING and David databases. The crystal structures of RA related targets were retrieved from the RCSB PDB database. Finally, the potential active compounds and their related targets were validated using molecular docking technology.Results: Five active components of Angelicae Pubescentis Radix(APR) were screened out, including ammidin, isoimperatorin, beta-sitosterol, O-acetylcolumbianetin and angelicone and 80 key targets including MAPK8,EGFR,PTGS2,CASPASE3,MTOR,SRC,KDR,MAPK1,NOS3 and MAPK14, etc were obtained. GO enrichment analysis showed that 222 biological processes, 34 cell components and 72 molecular functions were identified; KEGG analysis showed that the targets of APR in the treatment of RA were significantly enriched in pathways in cancer, the PI3K−Akt signaling pathway, Proteoglycans in cancer, osteoclast differentiation, neuroactive ligand−receptor interaction, tuberculosis,TNF signaling pathway, serotonergic synapse, Rap1 signaling pathway,cAMP signaling pathway. The results of molecular docking showed that ammidin, isoimperatorin, beta-sitosterol, O-acetylcolumbianetin and angelicone had strong affinity for PTGS2, EGFR and MAPK8.Conclusion: APR treats RA through the characteristics of multi-component, multi-target and multi-pathway regulation.

scholarly journals Mechanism of Compound Houttuynia Mixture as an Anti-COVID-19 Drug Based on Network Pharmacology and Molecular Docking

2021 ◽  
Vol 16 (5) ◽  
pp. 1934578X2110167
Author(s):  
Xing-Pan Wu ◽  
Tian-Shun Wang ◽  
Zi-Xin Yuan ◽  
Yan-Fang Yang ◽  
He-Zhen Wu
Keyword(s):  
Molecular Docking ◽  
Target Prediction ◽  
Interaction Network ◽  
Scientific Basis ◽  
Network Pharmacology ◽  
Chemical Components ◽  
Active Components ◽  
Discovery Studio ◽  
The Core ◽  
Pathway Annotation

Objective To explore the anti-COVID-19 active components and mechanism of Compound Houttuynia mixture by using network pharmacology and molecular docking. Methods First, the main chemical components of Compound Houttuynia mixture were obtained by using the TCMSP database and referring to relevant chemical composition literature. The components were screened for OB ≥30% and DL ≥0.18 as the threshold values. Then Swiss Target Prediction database was used to predict the target of the active components and map the targets of COVID-19 obtained through GeneCards database to obtain the gene pool of the potential target of COVID-19 resistance of the active components of Compound Houttuynia mixture. Next, DAVID database was used for GO enrichment and KEGG pathway annotation of targets function. Cytoscape 3.8.0 software was used to construct a “components-targets-pathways” network. Then String database was used to construct a “protein-protein interaction” network. Finally, the core targets, SARS-COV-2 3 Cl, ACE2 and the core active components of Compound Houttuyna Mixture were imported into the Discovery Studio 2016 Client database for molecular docking verification. Results Eighty-two active compounds, including Xylostosidine, Arctiin, ZINC12153652 and ZINC338038, were screened from Compound Houttuyniae mixture. The key targets involved 128 targets, including MAPK1, MAPK3, MAPK8, MAPK14, TP53, TNF, and IL6. The HIF-1 signaling, VEGF signaling, TNF signaling and another 127 signaling pathways associated with COVID-19 were affected ( P < 0.05). From the results of molecular docking, the binding ability between the selected active components and the core targets was strong. Conclusion Through the combination of network pharmacology and molecular docking technology, this study revealed that the therapeutic effect of Compound Houttuynia mixture on COVID-19 was realized through multiple components, multiple targets and multiple pathways, which provided a certain scientific basis of the clinical application of Compound Houttuynia mixture.

Molecular Mechanism of The Effect of Huanglian Jiedu Decoction On Ulcerative Colitis Based On Network Pharmacology And Molecular Docking

2021 ◽  
Author(s):  
Jing Yang ◽  
Chao-Tao Tang ◽  
Ruiri Jin ◽  
Bixia Liu ◽  
Peng Wang ◽  
...  
Keyword(s):  
Ulcerative Colitis ◽  
Molecular Docking ◽  
Molecular Mechanism ◽  
Target Genes ◽  
Signal Pathway ◽  
Intestinal Barrier Function ◽  
Network Pharmacology ◽  
Bioactive Components ◽  
Ppi Network ◽  
Active Components

Abstract Huanglian jiedu decoction (HLJDD) is a heat-clearing and detoxifying agent composed of four kinds of Chinese herbal medicine. Previous studies have shown that HLJDD can improve the inflammatory response of ulcerative colitis (UC) and maintain intestinal barrier function. However, its molecular mechanism is not completely clear. In this study, we verified the bioactive components (BCI) and potential targets of HLJDD in the treatment of UC by means of network pharmacology and molecular docking, and constructed the pharmacological network and PPI network. Then the core genes were enriched by GO and KEGG. Finally, the bioactive components were docked with the key targets to verify the binding ability between them. A total of 54 active components related to UC were identified. Ten genes are considered to be very important to PPI network. Functional analysis showed that these target genes were mainly involved in the regulation of cell response to different stimuli, IL-17 signal pathway and TNF signal pathway. The results of molecular docking showed that the active components of HLJDD had good affinity with Hub gene. This study systematically elucidates the "multi-component, multi-target, multi-pathway" mechanism of anti-UC with HLJDD for the first time, suggesting that HLJDD or its active components may be candidate drugs for the treatment of ulcerative colitis.

The mechanism of radix paeoniae rubra in treatment of myocardial ischemia-reperfusion injury based on network pharmacology and molecular docking

2021 ◽  
Vol 11 (8) ◽  
pp. 1354-1365
Author(s):  
Meifang Yin ◽  
Lijuan Dai ◽  
Wenpei Ling ◽  
Chunyu Luo ◽  
Shuzhi Qin ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Myocardial Ischemia ◽  
Reperfusion Injury ◽  
Ischemia Reperfusion Injury ◽  
Ischemia Reperfusion ◽  
Network Pharmacology ◽  
Signal Pathways ◽  
Active Components ◽  
Myocardial Ischemia Reperfusion Injury ◽  
Myocardial Ischemia Reperfusion

Radix Paeoniae Rubra (RPR) is a widely used herb medicine. To better understand the mechanism of RPR in the treatment of myocardial ischemia-reperfusion injury (MIRI), in this study, the network of protein–protein interaction of the RPR-MIRI targets was constructed and analyzed through network pharmacology and molecular docking. The enrichment analysis was performed and the network map was established, and the componenttarget network was then verified by molecular docking. In the result, there were 14 components and 52 targets related to MIRI. The results of Gene Ontology (GO) analysis displayed 182 biological processes, 44 cellular components, 56 molecular functions. 45 signal pathways were collected from Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, which were mainly related to Rap1, PI3 K-Akt signal pathway and so on. Molecular docking verified that the active components had lower binding energy with key targets, indicating that it had better binding activity. In conclusion, the treatment of RPR on MIRI is implemented through multi-component, multi-target and multi-pathway, which makes a provision for exploring the therapeutic mechanism of RPR and expanding its clinical application.

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.

The Mechanism of Compound Danshen Dripping Pills in the Treatment of Diabetic Retinopathy Based on Network Pharmacology and Molecular Docking

2021 ◽  
Author(s):  
Xuedong An ◽  
LiYun Duan ◽  
YueHong Zhang ◽  
De Jin ◽  
Shenghui Zhao ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Cell Proliferation ◽  
Diabetic Retinopathy ◽  
Molecular Docking ◽  
Signaling Pathway ◽  
Active Ingredient ◽  
Network Pharmacology ◽  
Asiatic Acid ◽  
Active Components ◽  
The Core

Abstract BackgroundOur previous randomized, double-blind, placebo-controlled, multi-center clinical study showed that Compound Danshen Dripping Pills (CDDP) had a significant and safe effect in the treatment of diabetic retinopathy (DR), but its mechanism is still unclear, which we would explain based on network pharmacology and molecular docking.MethodThe active ingredients of CDDP (composed of Panax notoginseng, Salvia miltiorrhiza Bge., and Borneol) were searched in the TCMSP database. The validated target and Smiles number of the active ingredient are queried through the PubChem database, and the predicted target of the active ingredient is obtained through the Swisstarget Prediction database. The Drugbank, TTD, and DisGeNET databases were retrieved to obtain the related targets of DR. The core targets were obtained by the cluster analysis function of Cytoscape, and then the Protein-Protein Interaction was performed. The GO and KEGG signal pathways were enriched and clustered in David database. The potential active components and targets were docking with Autodock Vina, and the results were visualized by PyMOL.Result51 active components and 922 validation and prediction targets of CDDP, 715 targets of DR and 154 co-targets were obtained. Cluster analysis showed that there were two clusters, a total of 64 targets. Go and KEGG signal pathway enrichment analysis showed that the top 20 mainly included TNF and HIF-1 signaling pathway. In GO analysis, BP mainly includes positive regulation of smooth muscle cell proliferation and response to hypoxia, CC mainly includes extracellular space and extracellular domain, MF mainly includes protein binding and protein binding recognition. In KEGG database, the key genes in the TNF signaling pathway were TNF, NFkB and VEGF, in HIF-1 signaling pathway were the IL-6, STAT3, HIF1A and VEGF. Molecular docking results showed that all components of CDDP had a certain docking ability with TNF, NFkB, VEGF, IL-6, STAT3 and HIF1A, which of Asiatic acid and Salvianolic acid j was the strongest.Conclusion Based on the network pharmacology and molecular docking, the core active components of CDDP, mainly including Asiatic acid and Salvianolic acid j, which may play a role in regulating cell proliferation and response to inflammation and hypoxia by regulating the binding and recognition of intracellular and extracellular proteins, that is, mainly through TNF signaling pathway and HIF-1 signaling pathway.

Discussing the Mechanism of Dahuang Huanglian Xiexin Decoction in the Treatment of Type 2 Diabetes Mellitus via Network Pharmacology and Molecular Docking

2021 ◽  
Author(s):  
Xi Cen ◽  
Yan Wang ◽  
LeiLei Zhang ◽  
XiaoXiao Xue ◽  
Yan Wang ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Molecular Docking ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Overlapping Genes ◽  
Potential Mechanism ◽  
Active Components ◽  
The Core ◽  
Core Genes

Abstract BackgroundType 2 diabetes mellitus (T2DM) is regarded as Pi Dan disease in traditional Chinese medicine (TCM). Dahuang Huanglian Xiexin Decoction (DHXD), a classical TCM formula, has been used for treating Pi Dan disease in clinic, its pharmacological mechanism has not been elucidated. MethodsThis study used network pharmacological analysis and molecular docking approach to explore the mechanism of DHXD on T2DM. Firstly, the compounds in DHXD were obtained from TCMSP and TCMID databases, the potential targets were determined based on TCMSP and UniProt databases. Next, Genecards, Digenet and UniProt databases were used to identify the targets of T2DM. Then, the protein-protein interaction (PPI) network was established with overlapping genes of T2DM and compounds, and the core targets in the network were identified and analyzed. Then, the David database was used for GO and KEGG enrichment analysis. Finally, the target genes were selected and the molecular docking was completed by Autodock software to observe the binding level of active components with target genes.ResultsA total of 397 related components and 128 overlapping genes were identified. After enrichment analysis, it was found that HIF-1, TNF, IL-17 and other signaling pathways, as well as DNA transcription, gene expression, apoptosis and other cellular biological processes had the strongest correlation with the treatment of T2DM by DHXD, and most of them occurred in the extracellular space, plasma membrane and other places, which were related to enzyme binding and protein binding. In addition, 42 core genes of DHXD, such as VEGFA, TP53 and MAPK1, were considered as potential therapeutic targets, indicating the potential mechanism of DHXD on T2DM. Finally, the results of molecular docking showed that HIF-1 pathway had strong correlation with the target genes INSR and GLUT4, quercetin and berberine had the strongest binding power with them respectively.ConclusionThis study summarized the main components of DHXD in the treatment of T2DM, identified the core genes and pathways, and systematically analyzed the interaction of related targets, trying to lay the foundation for clarifying the potential mechanism of DHXD on T2DM, so as to carry out further research in the future.

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