scholarly journals Elucidation of the mechanism of action of the anticholecystitis effect of the Tibetan medicine “Dida” using network pharmacology

2020 ◽  
Vol 19 (7) ◽  
pp. 1449-1457
Author(s):  
Chuan Liu ◽  
Fang-Fang Fan ◽  
Xuan-Hao Li ◽  
Wen-Xiang Wang ◽  
Ya Tu ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Bioactive Compounds ◽  
Kegg Pathway ◽  
Docking Simulation ◽  
Cell Receptor ◽  
Mapk Signaling ◽  
Tibetan Medicine ◽  
Network Pharmacology ◽  
Molecular Docking Simulation ◽  
Pathway Network

Purpose: To study the mechanism involved in the anti-cholecystitis effect the Tibetan medicine “Dida”, using network pharmacology-integrated molecular docking simulationsMethods: In this investigation, the bioactive compounds of Dida were collected, network pharmacology methods to predict their targets, and networks were constructed through GO and KEGG pathway analyses. The potential binding between the bioactive compounds and the targets were demonstrated using molecular docking simulations.Results: A total of 12 bioactive compounds and 50 key targets of Dida were identified. Two networks, namely, protein–protein interaction (PPI) network of cholecystitis targets, and compound–target– pathway network, were established. Network analysis showed that 10 targets (GAPDH, AKT1, CASP3, EGFR, TNF, MAPK3, MAPK1, HSP90AA1, STAT3, and BCL2L1) may be the therapeutic targets of Dida in cholecystitis. Analysis of the KEGG pathway indicated that the anti-cholecystitis effect of Dida may its regulation of a few crucial pathways, such as apoptosis, as well as toll-like  receptor, T cell receptor, NOD-like receptor, and MAPK signaling pathways. Furthermore, molecular docking simulation revealed that CASP3, CAPDH, HSP90AA1, MAPK3, MAPK1, and STAT3 had well-characterized interactions with the corresponding compounds.Conclusion: The mechanism underlying the anti-cholecystitis effect of Dida has been successfully predicted and verified using a combination of network pharmacology and molecular docking simulation. This provides a firm basis for the experimental verification of the use of Dida in the treatment of cholecystitis, and enhances its rational application in clinical practice. Keywords: Tibetan medicine, Dida, Cholecystitis, Mechanism, Network pharmacology, Molecular docking simulation

scholarly journals Elucidation of the mechanisms underlying the anticholecystitis effect of the Tibetan medicine “Dida” using Network pharmacology

2020 ◽  
Vol 19 (9) ◽  
pp. 1953-1961
Author(s):  
Chuan Liu ◽  
Fang-Fang Fan ◽  
Xuan-Hao Li ◽  
Wen-Xiang Wang ◽  
Ya Tu ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Bioactive Compounds ◽  
Kegg Pathway ◽  
Docking Simulation ◽  
Cell Receptor ◽  
Mapk Signaling ◽  
Tibetan Medicine ◽  
Network Pharmacology ◽  
Molecular Docking Simulation ◽  
Pathway Network

Purpose: To study the mechanism involved in the anti-cholecystitis effect the Tibetan medicine “Dida”, using network pharmacology-integrated molecular docking simulationsMethods: In this investigation, the bioactive compounds of Dida were collected, network pharmacology methods to predict their targets, and networks were constructed through GO and KEGG pathway analyses. The potential binding between the bioactive compounds and the targets were demonstrated using molecular docking simulations.Results: A total of 12 bioactive compounds and 50 key targets of Dida were identified. Two networks, namely, protein-protein interaction (PPI) network of cholecystitis targets, and compound-target-pathway network, were established. Network analysis showed that 10 targets (GAPDH, AKT1, CASP3, EGFR, TNF, MAPK3, MAPK1, HSP90AA1, STAT3, and BCL2L1) may be the therapeutic targets of Dida in cholecystitis. Analysis of the KEGG pathway indicated that the anti-cholecystitis effect of Dida may its regulation of a few crucial pathways, such as apoptosis, as well as toll-like  receptor, T cell receptor, NOD-like receptor, and MAPK signaling pathways. Furthermore, molecular docking simulation revealed that CASP3, CAPDH, HSP90AA1, MAPK3, MAPK1, and STAT3 had well-characterized interactions with the corresponding compounds.Conclusion: The mechanism underlying the anti-cholecystitis effect of Dida was successfully predicted and verified using a combination of network pharmacology and molecular docking simulation. This provides a firm basis for the experimental verification of the use of Dida in the treatment of cholecystitis, and enhances its rational application in clinical medication. Keywords: Tibetan medicine, Dida, Cholecystitis, Mechanism of effect, Network pharmacology, Molecular docking simulation

scholarly journals Insights into the mechanism of Arnebia euchroma on leukemia via network pharmacology approach

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Biting Wang ◽  
Zengrui Wu ◽  
Jiye Wang ◽  
Weihua Li ◽  
Guixia Liu ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Binding Free Energy ◽  
Leukemia Cell ◽  
Docking Simulation ◽  
Mapk Signaling ◽  
Network Pharmacology ◽  
Bipartite Network ◽  
Molecular Docking Simulation ◽  
Arnebia Euchroma ◽  
Compound Target

Abstract Background Arnebia euchroma (A. euchroma) is a traditional Chinese medicine (TCM) used for the treatment of blood diseases including leukemia. In recent years, many studies have been conducted on the anti-tumor effect of shikonin and its derivatives, the major active components of A. euchroma. However, the underlying mechanism of action (MoA) for all the components of A. euchroma on leukemia has not been explored systematically. Methods In this study, we analyzed the MoA of A. euchroma on leukemia via network pharmacology approach. Firstly, the chemical components and their concentrations in A. euchroma as well as leukemia-related targets were collected. Next, we predicted compound-target interactions (CTIs) with our balanced substructure-drug-target network-based inference (bSDTNBI) method. The known and predicted targets of A. euchroma and leukemia-related targets were merged together to construct A. euchroma-leukemia protein-protein interactions (PPIs) network. Then, weighted compound-target bipartite network was constructed according to combination of eight central attributes with concentration information through Cytoscape. Additionally, molecular docking simulation was performed to calculate whether the components and predicted targets have interactions or not. Results A total of 65 components of A. euchroma were obtained and 27 of them with concentration information, which were involved in 157 targets and 779 compound-target interactions (CTIs). Following the calculation of eight central attributes of targets in A. euchroma-leukemia PPI network, 37 targets with all central attributes greater than the median values were selected to construct the weighted compound-target bipartite network and do the KEGG pathway analysis. We found that A. euchroma candidate targets were significantly associated with several apoptosis and inflammation-related biological pathways, such as MAPK signaling, PI3K-Akt signaling, IL-17 signaling, and T cell receptor signaling pathways. Moreover, molecular docking simulation demonstrated that there were eight pairs of predicted CTIs had the strong binding free energy. Conclusions This study deciphered that the efficacy of A. euchroma in the treatment of leukemia might be attributed to 10 targets and 14 components, which were associated with inhibiting leukemia cell survival and inducing apoptosis, relieving inflammatory environment and inhibiting angiogenesis.

scholarly journals DMAG, a Novel Countermeasure for the Treatment of Thrombocytopenia

2021 ◽  
Author(s):  
Jing Lin ◽  
Jing Zeng ◽  
Sha Liu ◽  
Xin Shen ◽  
Nan Jiang ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Kegg Pathway ◽  
Docking Simulation ◽  
Dynamics Simulation ◽  
Network Pharmacology ◽  
Molecular Docking Simulation ◽  
The Core ◽  
Hel Cells ◽  
Megakaryocyte Differentiation

Abstract Background: Thrombocytopenia is one of the most common hematological disease that can be life-threatening caused by bleeding complications. However, the treatment options for thrombocytopenia remain limited. Methods: In this study, giemsa staining, phalloidin staining and flow cytometry were firstly used to identify the effects of 3,3'-Di-O-methylellagic acid 4'-glucoside (DMAG), a natural ellagic acid derived from Sanguisorba officinalis L. (SOL) on megakaryocyte differentiation in HEL cells. Then, thrombocytopenia mice model was constructed by X-ray irradiation to evaluate the therapeutic action of DMAG on thrombocytopenia. Next, network pharmacology approachs were carried out to identify the targets of DMAG. Moreover, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrich-ment analyses were performed to elucidate the underling mechanism of DMAG against thrombocytopenia. Finally, Molecular docking simulation, molecular dynamics simulation and western blot analysis were used to explore the relationship between DAMG with its targets.Results: DMAG significantly promoted megakaryocyte differentiation and maturation of HEL cells. DMAG administration accelerated platelet recovery and megakaryopoiesis in thrombocytopenia mice. Network pharmacology revealed that ITGA2B, ITGB3, VWF, PLEK, TLR2, BCL2, BCL2L1 and TNF were the core targets of DMAG. GO and KEGG pathway enrichment analyses suggested that the core targets of DMAG were enriched in PI3K-Akt signaling pathway, hematopoietic cell lineage, ECM-receptor interaction and platelet activation. Molecular docking simulation and molecular dynamics simulation further indicated that ITGA2B, ITGB3, PLEK and TLR2 displayed strong binding ability with DMAG. Finally, western blot analysis evidenced that DMAG up-regulated the expression of ITGA2B, ITGB3, VWF and PLEK. Conclusion: DMAG plays a critical role in promoting megakaryocytes differentiation and platelets production and might be a promising medicine for the treatment of thrombocytopenia.

scholarly journals Insights into the mechanism of Arnebia euchroma on leukemia via network pharmacology approach

2020 ◽  
Author(s):  
Biting Wang ◽  
Zengrui Wu ◽  
Jiye Wang ◽  
Weihua Li ◽  
Guixia Liu ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Binding Free Energy ◽  
Docking Simulation ◽  
Mapk Signaling ◽  
Network Pharmacology ◽  
Bipartite Network ◽  
Molecular Docking Simulation ◽  
Arnebia Euchroma ◽  
Compound Target

Abstract Background: Arnebia euchroma (A. euchroma), a traditional Chinese medicine (TCM) for the treatment of blood diseases. In recent years, more and more researches have been conducted on the anti-tumor effect of shikonin and its derivatives, the major active components of A. euchroma. However, the underlying mechanism of action (MoA) for all the ingredients of A. euchroma on leukemia has not been explored systematically.Methods: In this study, we tried to analyze the MoA of A. euchroma on leukemia via network pharmacology approach. Firstly, the chemical components and their concentrations in A. euchroma as well as leukemia-related targets were collected. Next, we predicted compound-target interactions (CTIs) via our balanced substructure-drug-target network-based inference (bSDTNBI) method. The known and predicted targets of A. euchroma and leukemia-related targets were merged together to construct A. euchroma-leukemia protein-protein interactions (PPIs) network. Then, weighted compound-target bipartite network was constructed according to combination of eight central attributes with concentrations information via Cytoscape. Additionally, molecular docking simulation was performed to determine the binding efficiency of compounds with targets.Results: A total of 65 components of A. euchroma were obtained and 27 of them with concentration information, which involved in 157 targets, 779 compound- target interactions (CTIs), including 129 known CTIs (KCTIs) and 650 predicted CTIs (PCTIs). Following the analysis of A. euchroma-leukemia PPI network, 37 targets were used to construct the weighted compound-target bipartite network and further KEGG pathway analysis. We found that A. euchroma candidate targets were significantly associated with several apoptosis and inflammation-related biological pathways, such as MAPK signaling pathway, PI3K-Akt signaling pathway, IL-17 signaling pathway, T cell receptor signaling pathway. Moreover, molecular docking simulation demonstrated that there were 8 pairs of PCTIs had the strong binding free energy.Conclusions: This network pharmacology-based study considered the information of component concentration, in combination with molecular docking, deciphered that the efficacy of A. euchroma in the treatment of leukemia may be mainly attributed to 10 targets and 14 components, which were associated with inhibiting leukemia cell survival and inducing apoptosis, relieving inflammatory environment and inhibiting angiogenesis.

scholarly journals Mechanisms of Compound Kushen Injection for the Treatment of Lung Cancer Based on Network Pharmacology

2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Ziqi Meng ◽  
Xinkui Liu ◽  
Jiarui Wu ◽  
Wei Zhou ◽  
Kaihuan Wang ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Molecular Docking ◽  
Small Cell Lung Cancer ◽  
Docking Simulation ◽  
Small Cell ◽  
Network Pharmacology ◽  
Small Cell Lung ◽  
Molecular Docking Simulation ◽  
Target Network ◽  
Compound Kushen Injection

Background. Compound Kushen Injection (CKI) is a Chinese patent drug that shows good efficacy in treating lung cancer (LC). However, its underlying mechanisms need to be further clarified.Methods. In this study, we adopted a network pharmacology method to gather compounds, predict targets, construct networks, and analyze biological functions and pathways. Moreover, molecular docking simulation was employed to assess the binding potential of selected target-compound pairs.Results. Four networks were established, including the compound-putative target network, protein-protein interaction (PPI) network of LC targets, compound-LC target network, and herb-compound-target-pathway network. Network analysis showed that 8 targets (CHRNA3, DRD2, PRKCA, CDK1, CDK2, CHRNA5, MMP1, and MMP9) may be the therapeutic targets of CKI in LC. In addition, molecular docking simulation indicated that CHRNA3, DRD2, PRKCA, CDK1, CDK2, MMP1, and MMP9 had good binding activity with the corresponding compounds. Furthermore, enrichment analysis indicated that CKI might exert a therapeutic role in LC by regulating some important pathways, namely, pathways in cancer, proteoglycans in cancer, PI3K-Akt signaling pathway, non-small-cell lung cancer, and small cell lung cancer.Conclusions. This study validated and predicted the mechanism of CKI in treating LC. Additionally, this study provides a good foundation for further experimental studies and promotes the reasonable application of CKI in the clinical treatment of LC.

scholarly journals Network pharmacology and molecular docking analysis on mechanisms of Tibetan Hongjingtian (Rhodiola crenulata) in the treatment of COVID-19

2021 ◽  
Vol 70 (7) ◽  
Author(s):  
Li Wang ◽  
Yuhe Wang ◽  
Wei Yang ◽  
Xue He ◽  
Shilin Xu ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Kegg Pathway ◽  
Signalling Pathway ◽  
Network Pharmacology ◽  
Cytokine Storm ◽  
Ppi Network ◽  
Pathway Network ◽  
Pathway Enrichment ◽  
Tnf Α ◽  
Rhodiola Crenulata

Introduction. Coronavirus disease 2019 (COVID-19) is a highly contagious disease and ravages the world. Hypothesis/Gap Statement. We proposed that R. crenulata might have potential value in the treatment of COVID-19 patients by regulating the immune response and inhibiting cytokine storm. Aim. We aimed to explore the potential molecular mechanism for Rhodiola crenulata (R. crenulata), against the immune regulation of COVID-19, and to provide a referenced candidate Tibetan herb (R. crenulata) to overcome COVID-19. Methodology. Components and targets of R. crenulata were retrieved from the TCMSP database. GO analysis and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment were built by R bioconductor package to explore the potential biological effects for targets of R. crenulata. The R. crenulata-compound-target network, target pathway network and protein–protein interaction (PPI) network were constructed using Cytoscape 3.3.0. Autodock 4.2 and Discovery Studio software were applied for molecular docking. Result. Four bioactive components (quercetin, kaempferol, kaempferol-3-O-α-l-rhamnoside and tamarixetin) and 159 potential targets of R. crenulata were identified from the TCMSP database. The result of GO annotation and KEGG-pathway-enrichment analyses showed that target genes of R. crenulata were associated with inflammatory response and immune-related signalling pathways, especially IL-17 signalling pathway, and TNF signalling pathway. Targets-pathway network and PPI network showed that IL-6, IL-1B and TNF-α were considered to be hub genes. Molecular docking showed that core compound (quercetin) had a certain affinity with IL-1β, IL-6 and TNF-α. Conclusion. R. crenulata might play an anti-inflammatory and immunoregulatory role in the cytokine storm of COVID-19.

scholarly journals Elucidating the mechanisms of Tibetan medicine Ershiwuwei Lvxue Pill in the treatment of rheumatoid arthritis via a system pharmacological approach

2020 ◽  
Author(s):  
Chuan Liu ◽  
Fangfang Fan ◽  
Lu Zhong ◽  
Ning Li ◽  
Yunsen Zhang ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Molecular Docking ◽  
Signaling Pathway ◽  
Bioactive Compounds ◽  
Mapk Signaling ◽  
Functional Enrichment ◽  
Tibetan Medicine ◽  
Chemical Compositions ◽  
Pharmacological Approach ◽  
Tof Ms

Abstract Background: Ershiwuwei Lvxue Pill (ELP, མགྲིན་མཚལ་ཉེར་ལྔ།), a traditional Tibetan medicine preparation, has been used hundreds of years for the clinical treatment of rheumatoid arthritis (RA) in Tibet, China. Nevertheless, its chemical compositions and therapeutic mechanism are unclear. Methods: In this work, a system pharmacological approach based on ultra-performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS), network pharmacology and molecular docking simulation was proposed for exploring the promising bioactive compounds and mechanisms for the treatment of RA.Results: For the first time, the compounds database of ELP was successfully established and 96 compounds were identified based on UPLC-Q-TOF/MS analysis. Among them, 22 bioactive compounds were screened according to ADME, oral bioavailability and drug likeness. Screening based on relevant databases and topological analysis revealed that 22 bioactive ingredients participated in 46 potential target proteins and 12 signaling pathways in RA. The functional enrichment analysis indicated that ELP exerted the anti-RA effects via synergistically regulating multiple biological nodes of the disease network. In that, 10 targets with high degree value including IL6, TNF, TP53, AKT1, JUN, VEGFA, MAPK3, STAT3, IL1β and PTGS2. The pathways with greater p-value contribution are PI3K-Akt signaling pathway, Cytokine-cytokine receptor interaction, JAK-STAT signaling pathway, MAPK signaling pathway, TNF signaling pathway and Toll-like receptor signaling pathway. In addition, good molecular docking scores were highlighted between five promising bioactive compounds (ellagic acid, quercetin, kaempferol, galangin, coptisine) and five core targets (PTGS2, STAT3, VEGFA, MAPK3, TNF). Conclusion: Overall, the present work revealed the material basis and potential mechanism of ELP treatment on RA and provides insight for further research. However, further studies are needed to validate the biological processes and effect pathways of ELP.

scholarly journals Uncovering the relationship and mechanisms of Tartary buckwheat (Fagopyrum tataricum) and Type II diabetes, hypertension, and hyperlipidemia using a network pharmacology approach

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e4042 ◽  
Author(s):  
Chao-Long Lu ◽  
Qi Zheng ◽  
Qi Shen ◽  
Chi Song ◽  
Zhi-Ming Zhang
Keyword(s):  
Molecular Docking ◽  
Type Ii Diabetes ◽  
Fluid Shear Stress ◽  
Docking Simulation ◽  
Tartary Buckwheat ◽  
Network Pharmacology ◽  
Chemical Components ◽  
Type Ii ◽  
Molecular Docking Simulation ◽  
The Relationship

Background Tartary buckwheat (TB), a crop rich in protein, dietary fiber, and flavonoids, has been reported to have an effect on Type II diabetes (T2D), hypertension (HT), and hyperlipidemia (HL). However, limited information is available about the relationship between Tartary buckwheat and these three diseases. The mechanisms of how TB impacts these diseases are still unclear. Methods In this study, network pharmacology was used to investigate the relationship between the herb as well as the diseases and the mechanisms of how TB might impact these diseases. Results A total of 97 putative targets of 20 compounds found in TB were obtained. Then, an interaction network of 97 putative targets for these compounds and known therapeutic targets for the treatment of the three diseases was constructed. Based on the constructed network, 28 major nodes were identified as the key targets of TB due to their importance in network topology. The targets of ATK2, IKBKB, RAF1, CHUK, TNF, JUN, and PRKCA were mainly involved in fluid shear stress and the atherosclerosis and PI3K-Akt signaling pathways. Finally, molecular docking simulation showed that 174 pairs of chemical components and the corresponding key targets had strong binding efficiencies. Conclusion For the first time, a comprehensive systemic approach integrating drug target prediction, network analysis, and molecular docking simulation was developed to reveal the relationships and mechanisms between the putative targets in TB and T2D, HT, and HL.

scholarly journals DMAG, a novel countermeasure for the treatment of thrombocytopenia

2021 ◽  
Vol 27 (1) ◽  
Author(s):  
Jing Lin ◽  
Jing Zeng ◽  
Sha Liu ◽  
Xin Shen ◽  
Nan Jiang ◽  
...  
Keyword(s):  
Bleeding Time ◽  
Kegg Pathway ◽  
Docking Simulation ◽  
Dynamics Simulation ◽  
Network Pharmacology ◽  
Molecular Docking Simulation ◽  
Pathway Enrichment ◽  
The Core ◽  
Hel Cells ◽  
Megakaryocyte Differentiation

Abstract Background Thrombocytopenia is one of the most common hematological disease that can be life-threatening caused by bleeding complications. However, the treatment options for thrombocytopenia remain limited. Methods In this study, giemsa staining, phalloidin staining, immunofluorescence and flow cytometry were used to identify the effects of 3,3ʹ-di-O-methylellagic acid 4ʹ-glucoside (DMAG), a natural ellagic acid derived from Sanguisorba officinalis L. (SOL) on megakaryocyte differentiation in HEL cells. Then, thrombocytopenia mice model was constructed by X-ray irradiation to evaluate the therapeutic action of DMAG on thrombocytopenia. Furthermore, the effects of DMAG on platelet function were evaluated by tail bleeding time, platelet aggregation and platelet adhesion assays. Next, network pharmacology approaches were carried out to identify the targets of DMAG. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to elucidate the underling mechanism of DMAG against thrombocytopenia. Finally, molecular docking simulation, molecular dynamics simulation and western blot analysis were used to explore the relationship between DAMG with its targets. Results DMAG significantly promoted megakaryocyte differentiation of HEL cells. DMAG administration accelerated platelet recovery and megakaryopoiesis, shortened tail bleeding time, strengthened platelet aggregation and adhesion in thrombocytopenia mice. Network pharmacology revealed that ITGA2B, ITGB3, VWF, PLEK, TLR2, BCL2, BCL2L1 and TNF were the core targets of DMAG. GO and KEGG pathway enrichment analyses suggested that the core targets of DMAG were enriched in PI3K–Akt signaling pathway, hematopoietic cell lineage, ECM-receptor interaction and platelet activation. Molecular docking simulation and molecular dynamics simulation further indicated that ITGA2B, ITGB3, PLEK and TLR2 displayed strong binding ability with DMAG. Finally, western blot analysis evidenced that DMAG up-regulated the expression of ITGA2B, ITGB3, VWF, p-Akt and PLEK. Conclusion DMAG plays a critical role in promoting megakaryocytes differentiation and platelets production and might be a promising medicine for the treatment of thrombocytopenia. Graphical Abstract

scholarly journals A Combined Network Pharmacology and Molecular Docking Approach to Investigate Candidate Active Components and Multitarget Mechanisms of Hemerocallis Flowers on Antidepressant Effect

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Tiancheng Ma ◽  
Yu Sun ◽  
Chang Jiang ◽  
Weilin Xiong ◽  
Tingxu Yan ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Protein Interactions ◽  
Kegg Pathway ◽  
Endocrine System ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Antidepressant Effect ◽  
Pathway Enrichment Analysis ◽  
Active Components ◽  
Pathway Network

Objective. The purpose of our research is to systematically explore the multiple mechanisms of Hemerocallis fulva Flowers (HF) on depressive disorder (DD). Methods. The components of HF were searched from the literature. The targets of components were obtained from PharmMapper. After that, Cytoscape software was used to build a component-target network. The targets of DD were collected from DisGeNET, PharmGKB, TTD, and OMIM. Protein-protein interactions (PPIs) among the DD targets were executed to screen the key targets. Afterward, the GO and KEGG pathway enrichment analysis were performed by the KOBAS database. A compound-target-KEGG pathway network was built to analyze the key compounds and targets. Finally, the potential active substances and targets were validated by molecular docking. Results. A total of 55 active compounds in HF, 646 compound-related targets, and 527 DD-related targets were identified from public databases. After treated with PPI, 219 key targets of DD were acquired. The gene enrichment analysis suggested that HF probably benefits DD patients by modulating pathways related to the nervous system, endocrine system, amino acid metabolism, and signal transduction. The network analysis showed the critical components and targets of HF on DD. Results of molecular docking increased the reliability of this study. Conclusions. It predicted and verified the pharmacological and molecular mechanism of HF against DD from a holistic perspective, which will also lay a foundation for further experimental research and rational clinical application of DD.

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