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 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 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.

Exploring the Potential of Capsaicin Against Cancer Metastasis Based on TGF-β Signaling Modulation Through Module-based Network Pharmacology Approach

2020 ◽  
Vol 17 (5) ◽  
pp. 647-660 ◽  
Author(s):  
Shivananda Kandagalla ◽  
Sharath Belenahalli Shekarappa ◽  
Gollapalli Pavan ◽  
Umme Hani ◽  
Manjunatha Hanumanthappa
Keyword(s):  
Amino Acid ◽  
Amino Acid Composition ◽  
Signaling Pathway ◽  
Acid Composition ◽  
Protein Interaction ◽  
Cancer Metastasis ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Mode Analysis ◽  
Network Pharmacology

Background: Capsaicin is an active alkaloid /principal component of red pepper responsible for the pungency of chili pepper. Capsaicin by changing the intracellular redox homeostasis regulate a variety of signaling pathways ultimately producing a divergent cellular outcome. Several reports showed the potential of capsaicin against cancer metastasis, however unexplored molecular mechanism is still an active part of the research. Several growth factors have a critical role during cancer metastasis among them TGF- β signaling play a vital role. Methods: The present study aimed at analyzing capsaicin modulation of TGF-β signaling using network pharmacology approach. The chemical and protein interaction data of capsaicin was curated and abstracted using STITCH4.0, PubChem and ChEMBL database. Further, the compiled data set was subjected to the pathway and functional enrichment analysis using Protein Analysis THrough Evolutionary Relationship (PANTHER) and, Database for Annotation, Visualization, and Integrated Discovery (DAVID) database. Meanwhile, the pattern of amino acid composition across the capsaicin targets was analyzed using the EMBOSS Pepstat tool. Capsaicin targets involved in TGF- β were identified and their Protein-Protein Interaction (PPI) network constructed using STRING v10 and Cytoscape (v 3.2.1). From the above-constructed network, the clusters were mined using the MCODE clustering algorithm and finally binding affinity of capsaicin with its targets involved in TGF-β signaling pathway was analyzed using Autodock Vina. Results: The analysis explored capsaicin targets and, their associated functional and pathway annotations. Besides, the analysis also provides a detailed distinct pattern of amino acid composition across the capsaicin targets. The capsaicin targets described as MAPK14, JUN, SMAD3, MAPK3, MAPK1 and MYC involved in TGF-β signaling pathway through pathway enrichment analysis. The binding mode analysis of capsaicin with its targets has shown high affinity with MAPK3, MAPK1, JUN and MYC. Conclusion: The study explores the potential of capsaicin as a potent modulator of TGF-β signaling pathway during cancer metastasis and proposes new methodology and mechanism of action of capsaicin against TGF- β signaling pathway.

scholarly journals The Mechanism Study of Xiao-Xian-Xiong Decoction in the Treatment of Atherosclerosis with Network Pharmacology

2020 ◽  
Author(s):  
Liucheng Xiao ◽  
Zonghuan Li ◽  
Chongyuan Fan ◽  
Chenggong Zhu ◽  
Xingyu Ma ◽  
...  
Keyword(s):  
Cell Proliferation ◽  
Signaling Pathway ◽  
Mapk Pathway ◽  
Enrichment Analysis ◽  
Foam Cells ◽  
Functional Enrichment ◽  
Network Pharmacology ◽  
Mechanism Study ◽  
Ppi Networks

Abstract Background: Xiao-Xian-Xiong decoction is a useful formula in the treatment of atherosclerosis in traditional Chinese medicine. In this study, we aimed to investigate the function of Xiao-Xian-Xiong decoction in the treatment of atherosclerosis. Methods: In this study, we conducted the method of network pharmacology and molecular docking to discover the mechanism of Xiao-Xian-Xiong decoction against atherosclerosis. Then, we validated the function of Xiao-Xian-Xiong decoction in atherosclerosis in vitro. We investigated the function and mechanism of Xiao-Xian-Xiong decoction in RAW264.7 macrophage-derived foam cells.Results: We identified 213 targets of Xiao-Xian-Xiong decoction and 331 targets of atherosclerosis. The PPI networks of Xiao-Xian-Xiong decoction and atherosclerosis were constructed. Furthermore, the two PPI networks were merged and the core PPI network was obtained. Then, functional enrichment analysis was conducted with GO and KEGG signaling pathway analysis. KEGG analysis indicated Xiao-Xian-Xiong decoction was correlated with ubiquitin mediated proteolysis pathway, PI3K-AKT pathway, MAPK pathway, Notch signaling pathway, and TGF-β signaling pathway. At last, we validated the function of Xiao-Xian-Xiong decoction with atherosclerosis in vitro. Xiao-Xian-Xiong decoction reduced lipid accumulation and promoted the outflow of cholesterol in RAW264.7-derived foam cells. Xiao-Xian-Xiong decoction increased the expression of ABCA1 and ABCG1 protein in foam cells. ABCA1 and ABCG1 were related with regulation of the inflammatory pathway and cell proliferation in atherosclerosis.Conclusions: Combined the mechanism of available treatments of atherosclerosis, we inferred Xiao-Xian-Xiong decoction could alleviate atherosclerosis by inhibiting inflammatory response and cell proliferation.

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 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 Research on Saponin Active Ingredient of Stir-Fried Dolichos Lablab L. Kernel for Treatment of Type-2 Diabetes Based on UHPLC-Q-Exactive Orbitrap MS and Network Pharmacology

2020 ◽  
Author(s):  
Han Jun ◽  
Liangzi Fang ◽  
Qinfang Zheng
Keyword(s):  
Type 2 Diabetes ◽  
Molecular Dynamics ◽  
Molecular Docking ◽  
Molecular Dynamics Simulation ◽  
Dynamics Simulation ◽  
Network Pharmacology ◽  
Dolichos Lablab ◽  
Q Exactive ◽  
Orbitrap Ms

Abstract BackgroundAlthough the clinical effect of stir-fried Dolichos lablab L. kernel has been approved in modern traditional Chinese medicine, existing associated studies mainly focus on its clinical studies and chemical ingredients. However, there are few studies on pharmacodynamics material basis and molecular mechanism of stirfried Dolichos lablab L. kernel in treatment of type-2 diabetes(T2DM), thus restricting the further development and utilization of stir-fried Dolichos lablab L. kernel.MethodsA qualitative analysis on saponin chemical ingredients of stir-fried Dolichos lablab L. kernel was performed using UHPLC-Q-Exactive Orbitrap MS. A total of 10 saponin ingredients were selected. Moreover, target screening, biological process and metabolism pathway analysis were accomplished by network pharmacology. Four key proteins(EGFR, IGF1, MAPK1 and PIK3R1) of type-2 diabetes were selected for molecular docking verification with saponin ingredients. Specifically, molecular dynamics simulation of ingredients which have strong bindings with proteins was conducted. ResultsIn this study, 16 saponin ingredients were identified from stir-fried Dolichos lablab L. kernel. There were 91 intersection targets and the KEGG pathway enrichment involved 20 relevant pathways. According to the molecular docking verification, saponin ingredients of stir-fried Dolichos lablab L. kernel can form stable binding with key protein targets. The molecular dynamics simulation further verifies stability and reasonability of the docking results. ConclusionsThis study provides references to identification of efficient ingredients of stir-fried Dolichos lablab L. kernel, screening of quality markers and explanation of relevant action mechanism by combining UHPLC-Q-Exactive Orbitrap MS and network pharmacology.

scholarly journals Study on The Effect Mechanism of “Common Treatment for Different Diseases” of Dachaihu Decoction on Prediabetes and Acute Hemorrhagic Stroke Based on Network Pharmacology

2020 ◽  
Author(s):  
Xiaolin Zhang ◽  
Di Cao ◽  
Qi Zhang ◽  
Dehui Ma ◽  
Mingjun Liu
Keyword(s):  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Signaling Pathway ◽  
Hemorrhagic Stroke ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Network Pharmacology ◽  
Active Components ◽  
The Common ◽  
Acute Hemorrhagic Stroke

Abstract Background: In this study, network pharmacology method was used to systematically predict and analyze the mechanism of "Common treatment for different diseases" effect of Dachaihu Decoction(DCHD) in the treatment of Prediabetes(PD) and Acute hemorrhagic stroke(AHS).Methods: TCMsp (Traditional Chinese Medicine systems pharmacology database and analysis platform) database was used to collect all the candidate active components related to 8 kinds of traditional Chinese medicine of DCHD, and UniProt database was used to obtain the drug action target and construct the "traditional Chinese medicine -Compound -target" action network; Genecards, OMIM(Online Mendelian Inheritance in Man), DisGeNET, CTD(Comparative Toxicogenomics Database) and TTD（Therapeutic Target Database）databases were used to obtain the related genes of PD and AHS respectively, and the interaction analysis of Venn with potential active components was carried out to obtain the common target of DCHD in the treatment of the two diseases.Using STRING 11.0 and Cytoscape3.72 to analyze protein-protein interaction of common targets and screen key common targets. BioGPS was used to obtain the distribution information in organs and tissues, and the relationship between the molecules and the key functional molecules were described. Bioconductor (R) was used to analyze the gene ontology (go) enrichment and the pathway analysis of the Kyoto Encyclopedia of genes and genomes (KEGG), so as to systematically predict the mechanism of "Common treatment for different diseases" of DCHD for PD and AHS.Results: with OB ≥ 30% and DL ≥ 0.18 as the screening criteria, 133 active compounds were screened out and 1034 drug targets were obtained; There are 3878 PD gene targets, 2674 AHS gene targets, 129 drug disease common targets, and 10 key targets whose median value is greater than 18;The key common targets displayed by biogps are mainly distributed in CD33+_ Myeloid.2(degree = 4)，Prostate.2(degree = 3)，CD56+_ NKCells.1(degree = 3)，Lung.2(degree = 3)，CD56+_ Nkcells. 2 (degree = 2);2281 biological processes, 65 cell components and 142 molecular functions were obtained by GO functional enrichment analysis;161 signal pathways were obtained by KEGG enrichment analysis, and the ones with higher proportion were AGE-RAGE signaling pathway in diabetic complications,PI3K-Akt signaling pathway,TNF signaling pathway,IL-17 signaling pathway,MAPK signaling pathway,HIF-1 signaling pathway,Relaxin signaling pathwa,C-type lectin receptor signaling pathway,which is mainly related to oxidative stress, glycolipid metabolism, immune inflammatory response, and neuroendocrine.Conclusion: DCHD can achieve the effect of "Common treatment for different diseases" by acting on the common receptor of PD and AHS through multi-component, multi-target and multi-channel, providing reference for further experimental verification, potential pharmacological mechanism and clinical application.

scholarly journals Molecular mechanism of Epicedium treatment for depression based on network pharmacology and molecular docking technology

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yankai Dong ◽  
Bo Tao ◽  
Xing Xue ◽  
Caixia Feng ◽  
Yating Ren ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Signaling Pathways ◽  
Signaling Pathway ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Testable Hypothesis ◽  
Network Pharmacology ◽  
Active Components ◽  
Active Compounds

Abstract Background Increasing attention has been paid to the effect of Epimedium on the nervous system, particularly anti-depression function. In the present study, we applied network pharmacology to introduce a testable hypothesis on the multi-target mechanisms of Epicedium against depression. Methods By reconstructing the network of protein–protein interaction and drug–component–target, we predicted the key protein targets of Epicedium for the treatment of depression. Then, through molecular docking, the interaction of the main active components of Epicedium and predicted candidate targets were verified. Results Nineteen active compounds were selected from Epicedium. There were 200 targets associated with Epicedium and 537 targets related to depression. The key targets of Epicedium for treating depression were IL6, VEGFA, AKT1, and EGF. According to gene ontology functional enrichment analysis, 22 items of biological process (BP), 13 items of cell composition (CC) and 9 items of molecular function (MF) were obtained. A total of 56 signaling pathways (P < 0.05) were identified by Kyoto Encyclopedia of Genes and Genomes analysis, mainly involving depression-related pathways such as dopaminergic synapse, TNF signaling pathway, and prolactin signaling pathway. The results of molecular docking showed that the most important activity components, including luteoklin, quercetin and kaempferol, were well combined with the key targets. Conclusions Luteoklin, quercetin, kaempferol and other active compounds in Epicedium can regulate multiple signaling pathways and targets such as IL6, AKT1, and EGF, therefore playing therapeutic roles in depression.

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