scholarly journals Network Pharmacology Strategy to Investigate the Pharmacological Mechanism of Siwu Decoction on Primary Dysmenorrhea and Molecular Docking Verification

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Dandan Jiang ◽  
Xiaoyan Wang ◽  
Lijun Tian ◽  
Yufeng Zhang
Keyword(s):  
Molecular Docking ◽  
Target Genes ◽  
Network Pharmacology ◽  
Primary Dysmenorrhea ◽  
Ppi Network ◽  
Active Compounds ◽  
Docking Simulations ◽  
Active Target ◽  
Target Network ◽  
Compound Target

Objective. To study the pharmacological mechanisms of Siwu decoction (SWD) on primary dysmenorrhea (PDM) and verify with molecular docking. Methods. The  Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) was utilized to acquire the active compounds and their corresponding target genes. The GeneCards database was utilized in the search for target genes that were associated with PDM. The intersection genes from the active target genes of SWD and those associated with PDM represented the active target genes of SWD that act on PDM. The Gene Ontology (GO) function enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were both carried out by RGUI 3.6.1 and Cytoscape 3.6.0 software. Cytoscape was also utilized for creating a compound-target network, and a protein-protein interaction (PPI) network was created through the STRING database. Molecular docking simulations of the macromolecular protein target receptors and their corresponding compounds were performed using AutoDockTool 1.5.6 and AutoDock Vina software. Results. We identified 14 active compounds as well as 97 active target genes of SWD by using the TCMSP. We compared the 97 active target genes of SWD to the 299 target genes related to PDM, and 23 active target genes for SWD that act on PDM which correlated with 11 active compounds were detected. The compound-target network as well as the PPI network were created, in addition to selecting the most essential compounds and their targets in order to create a key compound-target network. The most essential compounds were kaempferol, beta-sitosterol, stigmasterol, and myricanone. The key targets were AKT1, PTGS2, ESR1, AHR, CASP3, and PGR. Lastly, molecular docking was used to confirm binding of the target with its corresponding compound. Conclusion. The pharmacological mechanisms of SWD that act on PDM were investigated, and the active compounds in the SWD for treating PDM were further verified.

scholarly journals Exploring Molecular Mechanism of Traditional Chinese Medicine Euphorbiae Semen on Reversing of Multidrug Resistance in Leukemia Based on Network Pharmacology Strategy and Molecular Docking Technology

2020 ◽  
Author(s):  
Xiao Song ◽  
Fei Guo ◽  
Xiao-Chen Sun ◽  
Shu-Yue Wang ◽  
Yao-Hui Yuan ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Biological Functions ◽  
Active Compounds ◽  
The Core ◽  
The World ◽  
Target Network ◽  
Compound Target

Abstract Background: Leukemia was listed by the World Health Organization as one of the five most intractable diseases in the world. The multi-drug resistance (MDR) of leukemia cells limits the efficacy of anti-tumor drugs and is the major reason for the chemotherapy failure and recurrence of leukemia chemotherapy. Some studies have shown that Euphorbiae semen (ES) possesses the characteristics of new therapeutic drugs for MDR. However, the molecular mechanisms and active compounds have not yet been fully clarified. Therefore, there is a need for explore its active compounds and demonstrate its mechanisms through network pharmacology and molecular docking technology.Method: First, the TCMSP database was searched and screened the active compounds of the ES, supplemented with compounds verified by literature, so as to further identify the core compounds in the active ingredient. Simultaneously, the TCMSP and Swiss database were searched to the targets of active compounds, and the targets of reverses leukemia multidrug resistance (RL-MDR) were screened in the relevant databases, such as GeneCards and DrugBank. Then, the targets of active compounds were intersected with RL-MDR targets to obtain potential targets of ES acting on MDR. The compound–target network was constructed by Cytoscape. The target protein–protein interaction network was built using STRING and Cytoscape database. Second, the R language and DAVID database were used to analyse Gene Ontology (GO) biological functions analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) signal pathways enrichment. Finally, molecular docking method was utilized to investigate the binding activity between the core targets and the active compounds of ES.Results: Compound–target network mainly contained 22 compounds and 81 corresponding targets. Finally, seven components in ES were selected and 10 core targets were identified; Key targets contained JUN, CASP3, MAOA, AR, PPARG, DRD2, ADRA2A, CHRM2, PTGS2 and MAPK14. GO enrichment analysis indicated the main biological functions of potential genes of ES in the treatment of MDR. KEGG pathway enrichment analysis showed the main pathways, mainly including apoptosis, pathways in cancer, p53 signaling pathway, VEGF signaling pathway, TNF signaling pathway and PI3K–Akt signaling pathway. Finally, we chose the top 10 common targets for molecular docking with the 7 active compounds of ES. The results of molecular docking indicated that the compounds of ES, which had good affinity with targets. Conclusion: The molecular mechanism of ES in the treatment of MDR showed the synergistic reaction of multi-compound, multi-target, and multi-pathway of traditional Chinese medicine, which provided ideas for further clinical research.

scholarly journals Deciphering the Molecular Targets and Mechanisms of HGWD in the Treatment of Rheumatoid Arthritis via Network Pharmacology and Molecular Docking

2020 ◽  
Vol 2020 ◽  
pp. 1-13 ◽  
Author(s):  
Wei Liu ◽  
Yihua Fan ◽  
Chunying Tian ◽  
Yue Jin ◽  
Shaopeng Du ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Molecular Docking ◽  
Signaling Pathway ◽  
Differentially Expressed Genes ◽  
Target Genes ◽  
Differentially Expressed ◽  
Network Pharmacology ◽  
Active Compounds ◽  
Target Proteins ◽  
Target Network

Background. Huangqi Guizhi Wuwu Decoction (HGWD) has been applied in the treatment of joint pain for more than 1000 years in China. Currently, most physicians use HGWD to treat rheumatoid arthritis (RA), and it has proved to have high efficacy. Therefore, it is necessary to explore the potential mechanism of action of HGWD in RA treatment based on network pharmacology and molecular docking methods. Methods. The active compounds of HGWD were collected, and their targets were identified from the Traditional Chinese Medicine Systems Pharmacology Database (TCMSP) and DrugBank database, respectively. The RA-related targets were retrieved by analyzing the differentially expressed genes between RA patients and healthy individuals. Subsequently, the compound-target network of HGWD was constructed and visualized through Cytoscape 3.8.0 software. Protein-protein interaction (PPI) network was constructed to explore the potential mechanisms of HGWD on RA using the plugin BisoGenet of Cytoscape 3.8.0 software. Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) were performed in R software (Bioconductor, clusterProfiler). Afterward, molecular docking was used to analyze the binding force of the top 10 active compounds with target proteins of VCAM1, CTNNB1, and JUN. Results. Cumulatively, 790 active compounds and 1006 targets of HGWD were identified. A total of 4570 differentially expressed genes of RA with a p value <0.05 and log 2fold change > 0.5 were collected. Moreover, 739 GO entries of HGWD on RA were identified, and 79 pathways were screened based on GO and KEGG analysis. The core target gene of HGWD in RA treatment was JUN. Other key target genes included FOS, CCND1, IL6, E2F2, and ICAM1. It was confirmed that the TNF signaling pathway and IL-17 signaling pathway are important pathways of HGWD in the treatment of RA. The molecular docking results revealed that the top 10 active compounds of HGWD had a strong binding to the target proteins of VCAM1, CTNNB1, and JUN. Conclusion. HGWD has important active compounds such as quercetin, kaempferol, and beta-sitosterol, which exert its therapeutic effect on multiple targets and multiple pathways.

scholarly journals Systematic Understanding of Mechanism of Danggui Shaoyao San against Ischemic Stroke Using a Network Pharmacology Approach

2022 ◽  
Vol 2022 ◽  
pp. 1-20
Author(s):  
Sijie Li ◽  
Yong Yang ◽  
Wei Zhang ◽  
Haiyan Li ◽  
Wantong Yu ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Molecular Docking ◽  
Western Blot ◽  
Signaling Pathway ◽  
Cellular Response ◽  
Network Pharmacology ◽  
Active Compounds ◽  
The Core ◽  
Target Network ◽  
Compound Target

Purpose. Danggui Shaoyao San (DSS) was developed to treat the ischemic stroke (IS) in patients and animal models. The purpose of this study was to explore its active compounds and demonstrate its mechanism against IS through network pharmacology, molecular docking, and animal experiment. Methods. All the components of DSS were retrieved from the pharmacology database of TCM system. The genes corresponding to the targets were retrieved using OMIM, CTD database, and TTD database. The herb-compound-target network was constructed by Cytoscape software. The target protein-protein interaction network was built using the STRING database. The core targets of DSS were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Then, we achieved molecular docking between the hub proteins and the key active compounds. Finally, animal experiments were performed to verify the core targets. Triphenyltetrazolium chloride (TTC) staining was used to calculate the infarct size in mice. The protein expression was determined using the Western blot. Results. Compound-target network mainly contained 51 compounds and 315 corresponding targets. Key targets contained MAPK1, SRC, PIK3R1, HRAS, AKT1, RHOA, RAC1, HSP90AA1, and RXRA FN1. There were 417 GO items in GO enrichment analysis ( p < 0.05 ) and 119 signaling pathways ( p < 0.05 ) in KEGG, mainly including negative regulation of apoptosis, steroid hormone-mediated signaling pathway, neutrophil activation, cellular response to oxidative stress, and VEGF signaling pathway. MAPK1, SRC, and PIK3R1 docked with small molecule compounds. According to the Western blot, the expression of p-MAPK 1, p-AKT, and p-SRC was regulated by DSS. Conclusions. This study showed that DSS can treat IS through multiple targets and routes and provided new insights to explore the mechanisms of DSS against IS.

scholarly journals Integrating Network Pharmacology and Molecular Docking to Analyse the Potential Mechanism of action of Macleaya cordata (Willd.) R. Br. in the Treatment of Bovine Hoof Disease

2021 ◽  
Vol 9 (1) ◽  
pp. 11
Author(s):  
Zhen Dong ◽  
Mengting Liu ◽  
Xianglin Zou ◽  
Wenqing Sun ◽  
Xiubin Liu ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Signaling Pathways ◽  
Mechanism Of Action ◽  
Target Genes ◽  
Network Pharmacology ◽  
Pharmacokinetic Parameters ◽  
Active Compounds ◽  
Ppi Networks ◽  
Bovine Hoof ◽  
Compound Target

Based on network pharmacological analysis and molecular docking techniques, the main components of M. cordata for the treatment of bovine relevant active compounds in M. cordata were searched for through previous research bases and literature databases, and then screened to identify candidate compounds based on physicochemical properties, pharmacokinetic parameters, bioavailability, and drug-like criteria. Target genes associated with hoof disease were obtained from the GeneCards database. Compound−target, compound−target−pathway−disease visualization networks, and protein−protein interaction (PPI) networks were constructed by Cytoscape. Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed in R language. Molecular docking analysis was done using AutoDockTools. The visual network analysis showed that four active compounds, sanguinarine, chelerythrine, allocryptopine and protopine, were associated with the 10 target genes/proteins (SRC, MAPK3, MTOR, ESR1, PIK3CA, BCL2L1, JAK2, GSK3B, MAPK1, and AR) obtained from the screen. The enrichment analysis indicated that the cAMP, PI3K-Akt, and ErbB signaling pathways may be key signaling pathways in network pharmacology. The molecular docking results showed that sanguinarine, chelerythrine, allocryptopine, and protopine bound well to MAPK3 and JAK2. A comprehensive bioinformatics-based network topology strategy and molecular docking study has elucidated the multi-component synergistic mechanism of action of M. cordata in the treatment of bovine hoof disease, offering the possibility of developing M. cordata as a new source of drugs for hoof disease treatment.

scholarly journals Research on the Mechanism of Guizhi to Treat Nephrotic Syndrome Based on Network Pharmacology and Molecular Docking Technology

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Dan He ◽  
Qiang Li ◽  
Guangli Du ◽  
Jijia Sun ◽  
Guofeng Meng ◽  
...  
Keyword(s):  
Nephrotic Syndrome ◽  
Molecular Docking ◽  
Active Component ◽  
Network Pharmacology ◽  
Protective Mechanism ◽  
Ppi Network ◽  
Active Components ◽  
Active Compounds ◽  
The Core ◽  
Target Network

Objective. Nephrotic syndrome (NS) is a common glomerular disease caused by a variety of causes and is the second most common kidney disease. Guizhi is the key drug of Wulingsan in the treatment of NS. However, the action mechanism remains unclear. In this study, network pharmacology and molecular docking were used to explore the underlying molecular mechanism of Guizhi in treating NS. Methods. The active components and targets of Guizhi were screened by the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), Hitpick, SEA, and Swiss Target Prediction database. The targets related to NS were obtained from the DisGeNET, GeneCards, and OMIM database, and the intersected targets were obtained by Venny2.1.0. Then, active component-target network was constructed using Cytoscape software. And the protein-protein interaction (PPI) network was drawn through the String database and Cytoscape software. Next, Gene Ontology (GO) and pathway enrichment analyses of Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed by DAVID database. And overall network was constructed through Cytoscape. Finally, molecular docking was conducted using Autodock Vina. Results. According to the screening criteria, a total of 8 active compounds and 317 potential targets of Guizhi were chosen. Through the online database, 2125 NS-related targets were identified, and 93 overlapping targets were obtained. In active component-target network, beta-sitosterol, sitosterol, cinnamaldehyde, and peroxyergosterol were the important active components. In PPI network, VEGFA, MAPK3, SRC, PTGS2, and MAPK8 were the core targets. GO and KEGG analyses showed that the main pathways of Guizhi in treating NS involved VEGF, Toll-like receptor, and MAPK signaling pathway. In molecular docking, the active compounds of Guizhi had good affinity with the core targets. Conclusions. In this study, we preliminarily predicted the main active components, targets, and signaling pathways of Guizhi to treat NS, which could provide new ideas for further research on the protective mechanism and clinical application of Guizhi against NS.

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.

scholarly journals Identifying Active Compounds and Targets of Fritillariae thunbergii against Influenza-Associated Inflammation by Network Pharmacology Analysis and Molecular Docking

Molecules ◽  
2020 ◽  
Vol 25 (17) ◽  
pp. 3853 ◽  
Author(s):  
Minjee Kim ◽  
Ki Hoon Park ◽  
Young Bong Kim
Keyword(s):  
Molecular Docking ◽  
Binding Affinity ◽  
Target Genes ◽  
Inflammatory Diseases ◽  
Network Pharmacology ◽  
Pharmacokinetic Parameters ◽  
Active Compounds ◽  
Biological Targets ◽  
Underlying Mechanisms ◽  
Cox 1

Complications due to influenza are often associated with inflammation with excessive release of cytokines. The bulbs of Fritillariae thunbergii (FT) have been traditionally used to control airway inflammatory diseases, such as bronchitis and pneumonia. To elucidate active compounds, the targets, and underlying mechanisms of FT for the treatment of influenza-induced inflammation, systems biology was employed. Active compounds of FT were identified through the TCMSP database according to oral bioavailability (OB) and drug-likeness (DL) criteria. Other pharmacokinetic parameters, Caco-2 permeability (Caco-2), and drug half-life (HL) were also identified. Biological targets of FT were retrieved from DrugBank and STITCH databases, and target genes associated with influenza, lung, and spleen inflammation were collected from DisGeNET and NCBI databases. Compound-disease-target (C-D-T) networks were constructed and merged using Cytoscape. Target genes retrieved from the C-D-T network were further analyzed with GO enrichment and KEGG pathway analysis. In our network, GO and KEGG results yielded two compounds (beta-sitosterol (BS) and pelargonidin (PG)), targets (PTGS1 (COX-1) and PTGS2 (COX-2)), and pathways (nitric oxide, TNF) were involved in the inhibitory effects of FT on influenza-associated inflammation. We retrieved the binding affinity of each ligand-target, and found that PG and COX-1 showed the strongest binding affinity among four binding results using a molecular docking method. We identified the potential compounds and targets of FT against influenza and suggest that FT is an immunomodulatory therapy for influenza-associated inflammation.

scholarly journals Network Pharmacology Identifies the Mechanisms of Action of Tongxie Anchang Decoction in the Treatment of Irritable Bowel Syndrome with Diarrhea Predominant

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Xiang Tan ◽  
Wenjing Pei ◽  
Chune Xie ◽  
Zhibin Wang ◽  
Tangyou Mao ◽  
...  
Keyword(s):  
Irritable Bowel Syndrome ◽  
Target Genes ◽  
Alternative Therapy ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Active Compounds ◽  
Complementary And Alternative Therapy ◽  
Pharmacological Mechanism ◽  
Target Network ◽  
Irritable Bowel

Aim. This study aims to uncover the pharmacological mechanism of Tongxie Anchang Decoction (TXACD), a new and effective traditional Chinese medicine (TCM) prescription, for treating irritable bowel syndrome with diarrhea predominant (IBS-D) using network pharmacology. Methods. The active compounds and putative targets of TXACD were retrieved from TCMSP database and published literature; related target genes of IBS-D were retrieved from GeneCards; PPI network of the common target hub gene was constructed by STRING. Furthermore, these hub genes were analyzed using gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Results. A total of 54 active compounds and 639 targets were identified through a database search. The compound-target network was constructed, and the key compounds were screened out according to the degree. By using the PPI and GO and KEGG enrichment analyses, the pharmacological mechanism network of TXACD in the treatment of IBS-D was constructed. Conclusions. This study revealed the possible mechanisms by which TXACD treatment alleviated IBS-D involvement in the modulation of multiple targets and multiple pathways, including the immune regulation, inflammatory response, and oxidative stress. These findings provide novel insights into the regulatory role of TXACD in the prevention and treatment of IBS-D and hold promise for herb-based complementary and alternative therapy.

scholarly journals Exploring the Pharmacological Mechanism of the modified Chinese medicine formulas “Shenfu-Linguizhugan decoction” treating Dilated cardiomyopathy Based on Network Pharmacology

2020 ◽  
Author(s):  
Wuxia Quan ◽  
Yandong Miao
Keyword(s):  
Gene Expression ◽  
Chinese Medicine ◽  
Dilated Cardiomyopathy ◽  
Target Genes ◽  
Muscle Disease ◽  
Network Pharmacology ◽  
Therapeutic Effects ◽  
Bioactive Components ◽  
Ppi Network ◽  
Compound Target

Abstract Background: Dilated cardiomyopathy (DCM) is a non-ischaemic cardiac muscle disease with structural and functional myocardial aberration can lead to extensive morbidity and mortality due to complications in particular heart failure and arrhythmia. Two classic Chinese medicine formulas, Shenfu decoction and Linguizhugan decoction, were both shown to exert therapeutic effects on heart disease. Thus, modified Shenfu and Linguizhugan decoction (SFLGZGD) is recommended for treatment DCM. However, its chemical and pharmacological characteristics remain to be elucidated. In the current study, a network pharmacology approach was applied to characterize the action mechanism and target genes of SFLGZGD on DCM.Methods: The gene expression of DCM was obtained from the Gene Expression Omnibus (GEO). All compounds were obtained from the correlative databases, and active mixture were selected according to their oral bioavailability (OB) and drug-likeness (DL) index. The potential targets of SFLGZGD were obtained from the traditional Chinese medicine systems pharmacology (TCMSP) database. The compound-target and target-pathway networks were constructed. The protein-protein interactive (PPI) network generated by R software was visualized by Cytoscape, and the topology scores, functional regions, and gene annotations were analyzed using plugins of Bisogenet and CytoNCA. The potential pathways related to target genes were determined by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses.Results: A total of 963 differentially expressed genes (DEGs), including 538 upregulated genes and 425 downregulated, were obtained from GSE19303. A total of 636 ingredients in SFLGZGD were obtained, among which, 93 were chosen as bioactive components. The compound-target network included 10 bioactive components and 18 potential targets and a total of 1939 genes obtained in the PPI network, among them, a total of 16 genes were screened out. Moreover,129 terms on the GO analysis and six pathways obtained. Among these potential targets, EGFR, CDKN1A, MMP1, COL1A1, COL3A1, MMP3, ICAM1, and HSPB1 were identified as relatively high-degree targets.Conclusions: The network pharmacology-based approach in the current study has shown promising potential in identifying major therapeutic targets from TCM formulations. Besides, our study suggested that network pharmacology prediction may provide a useful tool for describing the molecular mechanism of SFLGZGD on DCM.

scholarly journals Exploring the Mechanisms Underlying the Therapeutic Effect of Xixin Decoction on Alzheimer's Disease Based on Network Pharmacology and Molecular Docking

2021 ◽  
Author(s):  
Zhuo Zhang ◽  
Jiang-lin Xu ◽  
Ming-qing Wei ◽  
Ting Li ◽  
Jing Shi
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Molecular Docking ◽  
Signaling Pathway ◽  
Therapeutic Effect ◽  
Mapk Signaling ◽  
Network Pharmacology ◽  
Receptor Interaction ◽  
Ppi Network ◽  
Active Compounds

Abstract Background and objective: Alzheimer’s disease (AD) has been a worldwide problem, not only the treatment but also the prevention. As a commonly used Chinese Herbal Formula, Xixin Decoction (XXD) has significant therapeutic effect on AD but without clear mechanism. This study was aimed to predict the main active compounds and targets of XXD in the treatment of AD and to explore the potential mechanism by using network pharmacology and molecular docking. Methods: The compounds of XXD were searched in the TCMSP and the TCMID database, and the active compounds were screened based on the ADME model and SwissADME platform. SwissTargetPrediction platform was used to search for the primary candidate targets of XXD. The common targets related to AD obtained by two databases (GeneCards and DisGeNET) were determined as candidate proteins involved in AD. To acquire the related targets of XXD in the treatment of AD, the target proteins related to AD were intersected with the predicted targets of XXD. Then these overlapping targets were imported into the STRING database to build PPI network including hub targets; Cytoscape 3.7.2 software was used to construct the topology analysis for the herb-compound-target network diagram while one of it’s plug-in called CytoNCA was used to calculate degree value to screen the main active compounds of XXD. GO and KEGG pathway enrichment analyses were conducted to explore the core mechanism of action and biological pathways associated with the decoction via Metascape platform. We used AutoDock Vina and PyMOL 2.4.0 softwares for molecular docking of hub targets and main compounds.Results: We determined 114 active compounds which meet the conditions of ADME screening, 973 drug targets, and 973 disease targets. However, intersection analysis screened out 208 shared targets. PPI network identified 9 hub targets, including TP53, PIK3CA, MAPK1, MAPK3, STAT3, AKT1, etc. The 10 main active compounds play a major role in treatment of AD by XXD. Hub targets were found to be enriched in 10 KEGG pathways, involving the Pathways in cancer, AGE-RAGE signaling pathway in diabetic complications, Alzheimer's disease, Neuroactive ligand-receptor interaction, Dopaminergic synapse, Serotonergic synapse and MAPK signaling pathway. The docking results indicated that the 8 hub targets exhibit good binding activity with the 9 main active compounds of XXD.Conclusions: We found the advantages of multi-compounds-multi-targets-multi-pathways regulation to reveal the mechanism of XXD for treating AD based on network pharmacology and molecular docking. Our study provided a theorical basis for further clinical application and experimental research of XXD for anti-AD in the future.

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