scholarly journals Network Pharmacology Reveals the Molecular Mechanism of Cuyuxunxi Prescription in Promoting Wound Healing in Patients with Anal Fistula

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Yin Qu ◽  
Zhijun Zhang ◽  
Yafeng Lu ◽  
De Zheng ◽  
Yang Wei
Keyword(s):  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Target Genes ◽  
Herbal Medicines ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Network Pharmacology ◽  
Surgical Wound ◽  
Active Compounds

Background. The healing process of the surgical wound of anal fistulotomy is much slower because of the presence of stool within the wound. Cuyuxunxi (CYXX) prescription is a Chinese herbal fumigant that is being used to wash surgical wound after anal fistulotomy. This study aimed at investigating the molecular mechanism of CYXX prescription using a network pharmacology-based strategy. Materials and Methods. The active compounds in each herbal medicine were retrieved from the traditional Chinese medicine systems pharmacology (TCMSP) database and in Traditional Chinese Medicine Integrated Database (TCMID) analysis platform based on the criteria of oral bioavailability ≥40% and drug-likeness ≥0.2. The disease-related target genes were extracted from the Comparative Toxicogenomics Database. Protein-protein interaction network was built for the overlapped genes as well as functional enrichment analysis. Finally, an ingredient-target genes-pathway network was built by integrating all information. Results. A total of 375 chemical ingredients of the 5 main herbal medicines in CYXX prescription were retrieved from TCMSP database and TCMID. Among the 375 chemical ingredients, 59 were active compounds. Besides, 325 target genes for 16 active compounds in 3 herbal medicines were obtained. Functional enrichment analysis revealed that these overlapped genes were significantly related with immune response, biosynthesis of antibiotics, and complement and coagulation cascades. A comprehensive network which contains 133 nodes (8 disease nodes, 3 drug nodes, 8 ingredients, 103 target gene nodes, 7 GO nodes, and 4 pathway nodes) was built. Conclusion. The network built in this study might aid in understanding the action mechanism of CYXX prescription at molecular level to pathway level.

scholarly journals Network Pharmacology Integrated Molecular Docking Reveals the Anti-COVID-19 and SARS Mechanism of Fufang Banlangen Keli

2021 ◽  
Vol 16 (1) ◽  
pp. 1934578X2098842
Author(s):  
Li Cheng ◽  
Fei Wang ◽  
Shun Bo Zhang ◽  
Qiu Yun You
Keyword(s):  
Molecular Docking ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Docking Studies ◽  
Functional Enrichment ◽  
Network Pharmacology ◽  
Active Components

Purpose Fufang Banlangen Keli (FBK) has been recommended for its clinical treatment of Coronavirus disease 2019 (COVID-19) and severe acute respiratory syndrome (SARS), but the mechanism of action is unclear. So, using network pharmacology and molecular docking, we studied the active components and mechanism of FBK in the treatment of COVID-19 and SARS. Methods The Encyclopedia of Traditional Chinese Medicine and Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform were used to screen the active components by oral bioactivity and drug likeness. Then, PharmMapper and SwissTargetPrediction databases were used to screen potential target genes of active components; the related target genes of COVID-19 and SARS were obtained from the GeneCards database. The intersection of the active components and disease-related targets was performed by the Venny2.1.0 database. The DAVID6.8 database and KOBAS3.0 database were used to get gene ontology (GO) function enrichment and Kyoto Encyclopedia of Genes and Genomes pathway annotation of gene targets. The “components-targets-pathways (C-T-P)” network of FBK was conducted by Cytoscape3.6.1 software. The top active components, angiotensin-converting enzyme 2 (ACE2) and SARS-CoV-2 3 Cl, were imported into AutoDock and PyMOL for molecular docking. Results From the FBK, a total of 28 active components and 73 gene targets were screened through network pharmacology. Twenty pathways were analyzed, including pathways in cancer, nod-like receptor signaling pathway, and pancreatic cancer, etc. ( P < 0.05). A total of 337 items were obtained by GO functional enrichment analysis ( P < 0.05), including 257 items for biological process, 38 items for cell composition, and 42 items for molecular function. Furthermore, molecular docking studies were performed to study potential binding between the key gene targets and selected active components. Conclusion Based on network pharmacology and molecular docking technology, qingdainone, (2Z)-2-(2-oxoindolin-3-ylidene) indolin-3-one, sinensetin, and acacetin in FBK were verified to bind to ACE2 and SARS-COV-2 3 Cl, so as to treat COVID-19 and SARS.

scholarly journals A Network Pharmacology-Based Study on the Anti-Lung Cancer Effect of Dipsaci Radix

2020 ◽  
Vol 2020 ◽  
pp. 1-9 ◽  
Author(s):  
Jiayan Wu ◽  
Shengkun Hong ◽  
Xiankuan Xie ◽  
Wangmi Liu
Keyword(s):  
Lung Cancer ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Molecular Mechanisms ◽  
Target Genes ◽  
Interaction Network ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Hub Genes ◽  
Active Compounds

Objective. Dipsaci Radix (DR) has been used to treat fracture and osteoporosis. Recent reports have shown that myeloid cells from bone marrow can promote the proliferation of lung cancer. However, the action and mechanism of DR has not been well defined in lung cancer. The aim of the present study was to define molecular mechanisms of DR as a potential therapeutic approach to treat lung cancer. Methods. Active compounds of DR with oral bioavailability ≥30% and drug-likeness index ≥0.18 were obtained from the traditional Chinese medicine systems pharmacology database and analysis platform. The potential target genes of the active compounds and bone were identified by PharmMapper and GeneCards, respectively. The compound-target network and protein-protein interaction network were built by Cytoscape software and Search Tool for the Retrieval of Interacting Genes webserver, respectively. GO analysis and pathway enrichment analysis were performed using R software. Results. Our study demonstrated that DR had 6 active compounds, including gentisin, sitosterol, Sylvestroside III, 3,5-Di-O-caffeoylquinic acid, cauloside A, and japonine. There were 254 target genes related to these active compounds as well as to bone. SRC, AKT1, and GRB2 were the top 3 hub genes. Metabolisms and signaling pathways associated with these hub genes were significantly enriched. Conclusions. This study indicated that DR could exhibit the anti-lung cancer effect by affecting multiple targets and multiple pathways. It reflects the traditional Chinese medicine characterized by multicomponents and multitargets. DR could be considered as a candidate for clinical anticancer therapy by regulating bone physiological functions.

scholarly journals Exploring the Mechanisms of Lian Hua Qing Wen Capsule against COVID-19 by Network Pharmacology and Molecular Docking Approach

2020 ◽  
Author(s):  
Li Chen ◽  
Hua Qu ◽  
Yu Tan ◽  
Tao Han Wu ◽  
Zhuo Da Shi
Keyword(s):  
Molecular Docking ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Signaling Pathway ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Active Compounds ◽  
Related Target ◽  
Docking Approach ◽  
Omim Database

Abstract Background The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 or COVID-19) disease has led to a wide-spread global pandemic. There is no specific antiviral drug proven effective for the treatment of patients with COVID-19 at present. Combination of western and traditional Chinese medicine (TCM) is recommended, and Lian Hua Qing Wen (LHQW) capsule is a basic prescription and widely used to treat COVID-19 in China. However, the mechanisms of LHQW capsule treating COVID-19 are not clear. The aim of the study is to explore the mechanisms of LHQW capsule treating COVID-19 based on network pharmacy and molecular docking approach. Methods The active compounds and targets of LHQW capsule were obtained from traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP). COVID-19 related target genes were obtained from GeneCards database and OMIM database. Protein–protein interaction (PPI) networks of LHQW capsule targets and COVID-19-related genes were visualized and merged to identify the candidate targets for LHQW capsule treating COVID-19. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were also performed. The hub genes involved in the gene-related pathways were screened and their corresponding compounds were used for in vitro validation of molecular docking predictions.Results A total of 185 active compounds of LHQW capsule were screened out, and 263 targets were predicted. Third hundred and fifty-two COVID-19 related target genes were obtained from GeneCards database and OMIM database. GO functional enrichment analysis showed that the biological processes of LHQW capsule treating COVID-19 were closely linked with the regulation of inflammation, immunity, cytokines production, vascular permeability, oxidative stress and apoptosis. KEGG enrichment analysis revealed that the pathways of LHQW capsule treating COVID-19 were significantly enriched in AGE−RAGE signaling pathway in diabetic complications, Kaposi sarcoma−associated herpesvirus infection, TNF, IL−17, and Toll−like receptor (TLR) signaling pathway. The hub targets genes in the gene-related pathways analysis of LHQW capsule treating COVID-19 included MAPK1, MAPK3, RELA, IL-6 and CASP8, which closely associated with inflammation, cytokines storm and apoptosis. Finally, molecular docking showed that top 5 compounds of LHQW capsule also had good binding activities to the important targets in COVID-19.Conclusions The mechanisms of LHQW capsule treating COVID-19 may involve in inhibiting inflammatory response, cytokine storm and virus infection, and regulating immune reactions, apoptosis and endothelial barrier.

scholarly journals Network Pharmacology-Based Study on the Mechanism of Scutellariae Radix for Hepatocellular Carcinoma Treatment

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Qian Wang ◽  
Yan Liang ◽  
Can Peng ◽  
Peng Jiang
Keyword(s):  
Hepatocellular Carcinoma ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Mechanistic Study ◽  
Network Pharmacology ◽  
Therapeutic Drug ◽  
Active Components ◽  
Scutellariae Radix

Hepatocellular carcinoma (HCC) is a malignant tumor without effective therapeutic drugs for most patients in advanced stages. Scutellariae Radix (SR) is a well-known anti-inflammatory and anticarcinogenic herbal medicine. However, the mechanism of SR against HCC remains to be clarified. In the present study, network pharmacology was utilized to characterize the mechanism of SR on HCC. The active components of SR and their targets were collected from the traditional Chinese medicine systems pharmacology database and the traditional Chinese medicine integrated database. HCC-related targets were acquired from the liver cancer databases OncoDB.HCC and Liverome. The gene ontology and the Kyoto Encyclopedia of Genes and Genomes pathway were analyzed using the Database for Annotation, Visualization, and Integrated Discovery. Component-component target and protein-protein interaction networks were set up. A total of 143 components of SR were identified, and 37 of them were considered as candidate active components. Fifty targets corresponding to 29 components of SR were mapped with targets of HCC. Functional enrichment analysis indicated that SR exerted an antihepatocarcinoma effect by regulating pathways in cancer, hepatitis B, viral carcinogenesis, and PI3K-Akt signaling. The holistic approach of network pharmacology can provide novel insights into the mechanistic study and therapeutic drug development of SR for HCC treatment.

scholarly journals Network Pharmacology Prediction: The Possible Mechanisms of Cinobufotalin against Osteosarcoma

2022 ◽  
Vol 2022 ◽  
pp. 1-9
Author(s):  
Riyu Chen ◽  
Zeyi Guan ◽  
Xianxing Zhong ◽  
Wenzheng Zhang ◽  
Ya Zhang
Keyword(s):  
Survival Curve ◽  
Therapeutic Targets ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Network Pharmacology ◽  
Hub Genes ◽  
Survival Prognosis ◽  
Active Compounds ◽  
Protein Protein Interaction

Objective. To explore the active compounds and targets of cinobufotalin (huachansu) compared with the osteosarcoma genes to obtain the potential therapeutic targets and pharmacological mechanisms of action of cinobufotalin on osteosarcoma through network pharmacology. Methods. The composition of cinobufotalin was searched by literature retrieval, and the target was selected from the CTD and TCMSP databases. The osteosarcoma genes, found from the GeneCards, OMIM, and other databases, were compared with the cinobufotalin targets to obtain potential therapeutic targets. The protein-protein interaction (PPI) network of potential therapeutic targets, constructed through the STRING database, was inputted into Cytoscape software to calculate the hub genes, using the NetworkAnalyzer. The hub genes were inputted into the Kaplan-Meier Plotter online database for exploring the survival curve. Functional enrichment analysis was identified using the DAVID database. Results. 28 main active compounds of cinobufotalin were explored, including bufalin, adenosine, oleic acid, and cinobufagin. 128 potential therapeutic targets on osteosarcoma are confirmed among 184 therapeutic targets form cinobufotalin. The hub genes included TP53, ACTB, AKT1, MYC, CASP3, JUN, TNF, VEGFA, HSP90AA1, and STAT3. Among the hub genes, TP53, ACTB, MYC, TNF, VEGFA, and STAT3 affect the patient survival prognosis of sarcoma. Through function enrichment analysis, it is found that the main mechanisms of cinobufotalin on osteosarcoma include promoting sarcoma apoptosis, regulating the cell cycle, and inhibiting proliferation and differentiation. Conclusion. The possible mechanisms of cinobufotalin against osteosarcoma are preliminarily predicted through network pharmacology, and further experiments are needed to prove these predictions.

A Network Pharmacology Approach to Explore the Underlying Mechanism of Tufuling Qiwei Tangsan in Treating Psoriasis

2021 ◽  
Vol 16 ◽  
Author(s):  
Xiaolei Ma ◽  
Yinan Lu ◽  
Yang Lu ◽  
Zhili Pei
Keyword(s):  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Mechanism Of Action ◽  
Enrichment Analysis ◽  
Underlying Mechanism ◽  
Mapk Signaling ◽  
Binding Activity ◽  
Network Pharmacology ◽  
Active Components ◽  
Active Compounds

Background: Tufuling Qiwei Tangsan (TQTS) is a commonly used Mongolian medicine preparation against psoriasis in China. However, its mechanism of action and molecular targets for the treatment of psoriasis is still unclear. Network pharmacology can reveal the synergistic mechanism of drugs at the molecular, target and pathway levels, and is suitable for the complex study of traditional Chinese medicine formulations. However, it is rarely involved in the application of Mongolian medicine with the same holistic concept of traditional Chinese medicine. Method: In this paper, the active compounds of TQTS were collected and their targets were identified. Psoriasis-related targets were obtained by analyzing the differential expressed genes between psoriasis patients and healthy individuals. Then, the network concerning the interactions of potential targets of TQTS with well-known psoriasis-related targets was built. The core targets were selected according to topological parameters. And the enrichment analysis was carried out to explore the mechanism of action of TQTS. Moreover, molecular docking was performed to study the interaction between the selected ligands and receptors related to psoriasis. Result and Conclusion: Eighty-five active compounds of TQTS were screened, with corresponding 270 targets, and 313 differentially expressed genes were identified. Additionally, enrichment analysis showed that the targets of TQTS for treating psoriasis were mainly concentrated in multiple biological processes, including apoptosis, growth factor response,etc., and related pathways including PI3K-Akt and MAPK signaling pathway, and so on. Genes such as NFKB1, TP53 and MAPK1 are the key genes in the gene pathway network of TQTS against psoriasis. The 4 main active components of TQTS have certain binding activity with 13 potential targets, and the stability of interaction with AKT1 is the best, which indicate the potential mechanism of TQTS on psoriasis.

scholarly journals Research on Active Compounds of Huanglian Jiedu Decoction for the Treatment of Corona Virus Disease 2019 Based on Network Pharmacology and Molecular Docking

2020 ◽  
Author(s):  
Leping Liu ◽  
Xinyi Xu ◽  
Xueshuai Cao ◽  
Xi Long ◽  
Yanwei Luo ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Signaling Pathways ◽  
Target Genes ◽  
Virus Disease ◽  
Network Pharmacology ◽  
Signal Pathways ◽  
Active Compounds ◽  
Corona Virus

Abstract Background Huanglian Jiedu Decoction (HLJDD) is a traditional Chinese prescription for the treatment of influenza, inflammation and other ailments related to heat-syndrome, a typical pathological symptom in Traditional Chinese Medicine. It was recommended as one of the basic prescriptions among the Proposed Diagnoses and Treatment issued by China’s National Health Commission. In this work we investigated the molecular mechanism of action of Huanglian Jiedu Decoction in the treatment of Corona Virus Disease 2019 (COVID-19) through network pharmacology and molecular docking approaches. Methods The chemical constituents and action targets of Coptis chinensis, Scutellaria baicalensis, Phellodendron amurense, Gardenia jasminoides in HLJDD were retrieved on Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). The database of UniProt and GeneCards were used to query the target genes that corresponding to the active compounds, and then a compound-target network was constructed using Cytoscape 3.7.2. GO database was used to annotate GO functions. Reactome was used to analyze KEGG enrichment pathway, predicting the possible mechanisms of active compounds. DAVID database was used to analysis the tissue enrichment. The main active ingredient is molecularly docked with the SARS-CoV-2, ACE2 and TMPRSS2. Results We screened 84 compounds and obtained 341 corresponding target genes in the network. Gene annotation showed that the targets were involved mainly in 457 biological functions. 306 signaling pathways was enriched, involving chemokine and cytokine signaling pathways that mediate inflammation, interferon-γ signaling pathway, p53 pathway. And the targets mainly distributed in the lung liver and placenta, involving a variety of immune cells, such as T cells, B cells. The molecular docking results showed that core compounds such as beta-sitosterol, stigmasterol and quercetin had high affinity with SARS-CoV-2, ACE2 and TMPRSS2, which was comparable with drugs like abidol used to COVID-19 treatment by. Conclusions The active compounds in HLJDD may have a therapeutic effect on COVID-19 through regulating multiple signal pathways by targeting genes such as VEGF, NOS2, IL6, MMP9, IL10, and TGFB1.

scholarly journals Mechanisms and Molecular Targets of the Tao-Hong-Si-Wu-Tang Formula for Treatment of Osteonecrosis of Femoral Head: A Network Pharmacology Study

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Fanyu Fu ◽  
Zeqing Huang ◽  
Hengli Ye ◽  
Biao Tan ◽  
Rongtian Wang ◽  
...  
Keyword(s):  
Chinese Medicine ◽  
Femoral Head ◽  
Traditional Chinese Medicine ◽  
Drug Targets ◽  
Target Genes ◽  
Molecular Targets ◽  
Network Pharmacology ◽  
Active Compounds ◽  
Osteonecrosis Of Femoral Head ◽  
Intersection Analysis

The Tao-Hong-Si-Wu-Tang (THSWT) formula, a classic prescription of traditional Chinese medicine, has long been used for the treatment of osteonecrosis of femoral head (ONFH). However, its mechanisms of action and molecular targets are not comprehensively clear. In the present study, the Traditional Chinese Medicine System Pharmacology (TCMSP) database was employed to retrieve the active compounds of each herb included in the THSWT formula. After identifying the drug targets of active compounds and disease targets of ONFH, intersection analysis was conducted to screen out the shared targets. The protein-protein network of the shared targets was built for further topological analysis. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis were then carried out. A gene pathway network was constructed to screen the core target genes. We identified 61 active compounds, 155 drug targets, and 5443 disease targets. However, intersection analysis only screened out 37 shared targets. Kaempferol, luteolin, and baicalein regulated the greatest number of targets associated with ONFH. The THSWT formula may regulate osteocyte function through specific biological processes, including responses to toxic substances and oxidative stress. The regulated pathways included the relaxin, focal adhesion, nuclear factor-κB, toll-like receptor, and AGE/RAGE signaling pathways. RELA, VEGFA, and STAT1 were the important target genes in the gene network associated with the THSWT formula for the treatment of ONFH. Therefore, the present study suggested that the THSWT formula has an action mechanism involving multiple compounds and network targets for the treatment of ONFH.

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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