scholarly journals Mechanisms of Core Chinese Herbs against Colorectal Cancer: A Study Based on Data Mining and Network Pharmacology

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Tong Lin ◽  
Caijun Liang ◽  
Wenya Peng ◽  
Yuqin Qiu ◽  
Lisheng Peng
Keyword(s):  
Colorectal Cancer ◽  
Data Mining ◽  
Bioactive Compounds ◽  
Target Genes ◽  
Prognostic Significance ◽  
Therapeutic Targets ◽  
Docking Simulation ◽  
Functional Enrichment ◽  
Chinese Herbs ◽  
Network Pharmacology

Colorectal cancer (CRC) is now the second most deadly cancer globally. Chinese herbal medicine (CHM) plays an indispensable role in CRC treatment in China. However, the core herbs (the CHs) in the treatment of CRC and their underlying therapeutic mechanisms remain unclear. This study aims to uncovering the CHs and their mechanisms of action of CRC treatment, applying data mining and network pharmacology approach. First, CHM prescriptions treating CRC were collected from clinical studies from the Chinese National Knowledge Infrastructure (CNKI) and MEDLINE databases, and the CHs were identified through data mining. Then, the bioactive compounds and the corresponding putative targets of the CHs were obtained from three traditional Chinese medicine (TCM) databases. CRC related targets were acquired from three disease databases; the overlapping targets between the CHs and CRC were identified as the therapeutic targets. Subsequently, functional enrichment analysis was performed to elucidate the mechanisms of the CHs on CRC. Moreover, networks were constructed to screen the major bioactive compounds and therapeutic targets. Finally, prognostic values of the major target genes were evaluated by survival analysis, and molecular docking simulation was performed to assess the binding affinity of key targets and major bioactive compounds. It came out that 10 the CHs from 113 prescriptions and 190 bioactive compounds with 118 therapeutic targets were identified. The therapeutic targets were mainly enriched in the biological progress of transcription, apoptosis, and response to cytokine. Various cancer-associated signaling pathways, including microRNAs, TNF, apoptosis, PI3K-Akt, and p53, were involved. Furthermore, 15 major bioactive compounds and five key target genes (VEGFA, CASP3, MYC, CYP1Y1, and NFKB1) with prognostic significance were identified. Additionally, most major bioactive compounds might bind firmly to the key target proteins. This study provided an overview of the anti-CRC mechanisms of the CHs, which might refer to the regulation of apoptosis, transcription, and inflammation.

scholarly journals Network pharmacology approach to reveals therapeutic mech-anism of traditional plants formulation used by Malaysia in-digenous ethnics in coronaviruses infection

2022 ◽  
Author(s):  
Fui Fui Lem ◽  
Dexter Jiunn Herng Lee ◽  
Fong Tyng Chee ◽  
Su Na Chin ◽  
Kai Min Lin ◽  
...  
Keyword(s):  
Bioactive Compounds ◽  
Target Genes ◽  
Interaction Network ◽  
Bioactive Compound ◽  
Functional Enrichment ◽  
Network Pharmacology ◽  
Pathway Network ◽  
Pharmacological Mechanism ◽  
Target Network ◽  
Compound Target

Network pharmacology analysis can act as a strategy to identify the pharmacological effect of plant-based bioactive compounds against coronavirus diseases. This study aimed to investigate the potential pharmacological mechanism of a local ethnomedicine (Costus speciosus, Hibiscus rosa-sinensis and Phyllanthus niruri) of Northern Borneo against coronaviruses known as CHP. Compounds in CHP were extracted from databases and screened for their oral bioavailability and drug-likeness before a compound-target network was built. Furthermore, the protein-protein interaction network and pathway enrichment were constructed and analyzed. A compound-target network consisting of 48 putative bioactive compounds targeting 587 candidate genes was identified. A total of 186 coronavirus-related genes were extracted and TP53, STAT3, HSP90AA1, STAT1, and EP300 were predicted to be the key targets. Notably, mapping of these target genes into the target-pathway network illustrated that functional enrichment was on viral infection and regulation of inflammation pathways. Urinatetralin is predicted, for the first time, as a bioactive compound that solely targets STAT3. The results from this study indicate that compounds present in CHP employ STAT3 and its connected pathways as the mechanism of action against coronaviruses. In conclusion, urinatetralin should be further investigated for its potential application against coronavirus infections.

scholarly journals Systematically Exploring the Antitumor Mechanisms of Core Chinese Herbs on Hepatocellular Carcinoma: A Computational Study

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Zhulin Wu ◽  
Li He ◽  
Lianan Wang ◽  
Lisheng Peng
Keyword(s):  
Hepatocellular Carcinoma ◽  
Data Mining ◽  
Survival Analysis ◽  
Molecular Docking ◽  
Bioactive Compounds ◽  
Target Genes ◽  
Chinese Herbs ◽  
Hub Genes ◽  
Combining Data ◽  
Common Target

Objective. Chinese herbs play a positive role in the management of hepatocellular carcinoma (HCC) in China. However, it is not clear which of Chinese herbs are critical for the treatment of HCC. Besides, mechanisms of CCHs in the treatment of HCC remain unclear. Hence, our goal is to identify the core Chinese herbs (CCHs) for treating HCC and explore their antitumor mechanism. Methods. Firstly, clinical traditional Chinese medicine (TCM) prescriptions for HCC were collected from Chinese National Knowledge Infrastructure (CNKI) database, and then, data mining software was used to identify CCHs. After that, bioactive compounds and corresponding target genes of CCHs were obtained using three TCM databases, and target genes of HCC were acquired from MalaCards and OMIM. Subsequently, common target genes of CCHs and HCC were screened. Moreover, biological functions and pathways were analyzed, and Cytoscape plugin cytoHubba was used to identify hub genes. Finally, prognostic values of hub genes were verified by survival analysis, and the molecular docking approach was utilized to validate the interactions between targets and bioactive compounds of CCHs. Results. Eight CCHs were determined from 630 prescriptions, and 100 bioactive compounds (e.g., quercetin and luteolin) and 126 common target genes were screened. Furthermore, common target genes of CCHs and HCC were mainly enriched in cancer-associated pathways, and six hub genes with statistical significance in survival analysis were selected as key target genes for molecular docking. Additionally, molecular docking showed that the bioactive compounds docked well with the protein receptors of key target genes. Conclusion. By combining data mining, network pharmacology, molecular docking, and survival analysis methods, we found that CCHs may play a therapeutic role in HCC through regulating the target genes and pathways related to cancer occurrence and development, angiogenesis, metastasis, and prognosis.

Network Pharmacology Analysis to Explore the Pharmacological Mechanism of Effective Chinese Medicines in Treating Metastatic Colorectal Cancer using Meta-Analysis Approach

2021 ◽  
pp. 1-32
Author(s):  
Ying Zhu ◽  
Jieru Yu ◽  
Kai Zhang ◽  
Yuqian Feng ◽  
Kaibo Guo ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Metastatic Colorectal Cancer ◽  
Meta Analysis ◽  
Chinese Herb ◽  
Functional Enrichment ◽  
Chinese Herbs ◽  
Network Pharmacology ◽  
Chemical Components ◽  
Active Components ◽  
Hub Genes

The role of traditional Chinese medicine (TCM) on treatment of metastatic colorectal cancer (mCRC) remains controversial, and its active components and potential targets are still unclear. This study mainly aimed to assess the efficacy and safety of TCM in mCRC treatment through meta-analysis and explore the effective components and potential targets based on the network pharmacology method. We systematically searched PubMed, EMBASE, Cochrane, CBM, WanFang, and CNKI database for randomized controlled trials (RCTs) comparing the treatment of mCRC patients with and without TCM. A meta-analysis using RevMan 5.4 was conducted. In total, 25 clinical trials were analyzed, and the result demonstrated that TCM was closely correlated with the improved OS (HR: 0.63; 95% CI: 0.52–0.76; [Formula: see text] < 0.00001) and PFS (HR: 0.73; 95% CI: 0.61–0.88; [Formula: see text] = 0.0010). Then, high-frequency Chinese herbs from the prescriptions extracted from the trails included in the OS meta-analysis were counted to construct a core-effective prescription. The TCMSP database was used to retrieve the active chemical components and predict herb targets. The Genecards, OMIM, Disgenet, DrugBank, and TTD database were searched for colorectal cancer targets. R-package was used to construct the Component-Target (C-T) network based on the intersection genes. Further, we extracted hub genes from C-T network and performed functional enrichment and pathway analysis. Finally, the C-T network showed 120 herb and disease co-target genes, and the most important top 10 active components were: Quercetin, Luteolin, Wogonin, Kaempferol, Nobiletin, Baicalein, Licochalcone A, Naringenin, Isorhamnetin, and Acacetin. The first 20 hub genes were extracted: CDKN1A, CDK1, CDK2, E2F1, CDK4, PCNA, RB1, CCNA2, MAPK3, CCND1, CCNB1, JUN, MAPK1, RELA, FOS, MAPK8, STAT3, MAPK14, NR3C1, and MYC. Thus, effective Chinese herb components may inhibit the mCRC by targeting multiple biological processes of the above hub genes.

scholarly journals Insights into the molecular mechanisms of Huangqi decoction on liver fibrosis via computational systems pharmacology approaches

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Biting Wang ◽  
Zengrui Wu ◽  
Weihua Li ◽  
Guixia Liu ◽  
Yun Tang
Keyword(s):  
Molecular Docking ◽  
Liver Fibrosis ◽  
Molecular Mechanisms ◽  
Docking Simulation ◽  
Chinese Herbs ◽  
Network Pharmacology ◽  
Bipartite Network ◽  
Metabolomics Data ◽  
Metabolic Products ◽  
Compound Target

Abstract Background The traditional Chinese medicine Huangqi decoction (HQD) consists of Radix Astragali and Radix Glycyrrhizae in a ratio of 6: 1, which has been used for the treatment of liver fibrosis. In this study, we tried to elucidate its action of mechanism (MoA) via a combination of metabolomics data, network pharmacology and molecular docking methods. Methods Firstly, we collected prototype components and metabolic products after administration of HQD from a publication. With known and predicted targets, compound-target interactions were obtained. Then, the global compound-liver fibrosis target bipartite network and the HQD-liver fibrosis protein–protein interaction network were constructed, separately. KEGG pathway analysis was applied to further understand the mechanisms related to the target proteins of HQD. Additionally, molecular docking simulation was performed to determine the binding efficiency of compounds with targets. Finally, considering the concentrations of prototype compounds and metabolites of HQD, the critical compound-liver fibrosis target bipartite network was constructed. Results 68 compounds including 17 prototype components and 51 metabolic products were collected. 540 compound-target interactions were obtained between the 68 compounds and 95 targets. Combining network analysis, molecular docking and concentration of compounds, our final results demonstrated that eight compounds (three prototype compounds and five metabolites) and eight targets (CDK1, MMP9, PPARD, PPARG, PTGS2, SERPINE1, TP53, and HIF1A) might contribute to the effects of HQD on liver fibrosis. These interactions would maintain the balance of ECM, reduce liver damage, inhibit hepatocyte apoptosis, and alleviate liver inflammation through five signaling pathways including p53, PPAR, HIF-1, IL-17, and TNF signaling pathway. Conclusions This study provides a new way to understand the MoA of HQD on liver fibrosis by considering the concentrations of components and metabolites, which might be a model for investigation of MoA of other Chinese herbs.

scholarly journals Elucidating the Mechanisms of Hugan Buzure Granule in the Treatment of Liver Fibrosis via Network Pharmacology

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Yi Zhu ◽  
Ming Qiao ◽  
Jianhua Yang ◽  
Junping Hu
Keyword(s):  
Liver Fibrosis ◽  
Rna Polymerase Ii ◽  
Molecular Mechanisms ◽  
Target Genes ◽  
Docking Simulation ◽  
Interaction Network ◽  
Network Pharmacology ◽  
Transcription Activator ◽  
Active Ingredients ◽  
Oxidoreductase Activity

Objective. To holistically explore the latent active ingredients, targets, and related mechanisms of Hugan buzure granule (HBG) in the treatment of liver fibrosis (LF) via network pharmacology. Methods. First, we collected the ingredients of HBG by referring the TCMSP server and literature and filtered the active ingredients though the criteria of oral bioavailability ≥30% and drug-likeness index ≥0.18. Second, herb-associated targets were predicted and screened based on the BATMAN-TCM and SwissTargetPrediction platforms. Candidate targets related to LF were collected from the GeneCards and OMIM databases. Furthermore, the overlapping target genes were used to construct the protein-protein interaction network and “drug-compound-target-disease” network. Third, GO and KEGG pathway analyses were carried out to illustrate the latent mechanisms of HBG in the treatment of LF. Finally, the combining activities of hub targets with active ingredients were further verified based on software AutoDock Vina. Results. A total of 25 active ingredients and 115 overlapping target genes of HBG and LF were collected. Besides, GO enrichment analysis exhibited that the overlapping target genes were involved in DNA-binding transcription activator activity, RNA polymerase II-specific, and oxidoreductase activity. Simultaneously, the key molecular mechanisms of HBG against LF were mainly involved in PI3K-AKT, MAPK, HIF-1, and NF-κB signaling pathways. Also, molecular docking simulation demonstrated that the key targets of HBG for antiliver fibrosis were IL6, CASP3, EGFR, VEGF, and MAPK. Conclusion. This work validated and predicted the underlying mechanisms of multicomponent and multitarget about HBG in treating LF and provided a scientific foundation for further research.

scholarly journals Network Pharmacology-Based Investigation into the Mechanisms of Quyushengxin Formula for the Treatment of Ulcerative Colitis

2019 ◽  
Vol 2019 ◽  
pp. 1-22
Author(s):  
Haojie Yang ◽  
Ying Li ◽  
Sichen Shen ◽  
Dan Gan ◽  
Changpeng Han ◽  
...  
Keyword(s):  
Ulcerative Colitis ◽  
Bioactive Compounds ◽  
Functional Enrichment ◽  
Network Pharmacology ◽  
Disease Network ◽  
Pathway Network ◽  
Similarity Algorithm ◽  
Target Network ◽  
Target Disease ◽  
Compound Target

Objective. Ulcerative colitis (UC) is a chronic idiopathic inflammatory bowel disease whose treatment strategies remain unsatisfactory. This study aims to investigate the mechanisms of Quyushengxin formula acting on UC based on network pharmacology. Methods. Ingredients of the main herbs in Quyushengxin formula were retrieved from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. Absorption, distribution, metabolism, and excretion properties of all ingredients were evaluated for screening out candidate bioactive compounds in Quyushengxin formula. Weighted ensemble similarity algorithm was applied for predicting direct targets of bioactive ingredients. Functional enrichment analyses were performed for the targets. In addition, compound-target network, target-disease network, and target-pathway network were established via Cytoscape 3.6.0 software. Results. A total of 41 bioactive compounds in Quyushengxin formula were selected out from the TCMSP database. These bioactive compounds were predicted to target 94 potential proteins by weighted ensemble similarity algorithm. Functional analysis suggested these targets were closely related with inflammatory- and immune-related biological progresses. Furthermore, the results of compound-target network, target-disease network, and target-pathway network indicated that the therapeutic effects of Quyushengxin on UC may be achieved through the synergistic and additive effects. Conclusion. Quyushengxin may act on immune and inflammation-related targets to suppress UC progression in a synergistic and additive manner.

scholarly journals Systematic Elucidation of the Potential Mechanisms of Core Chinese Materia Medicas in Treating Liver Cancer Based on Network Pharmacology

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Zhulin Wu ◽  
Lina Yang ◽  
Li He ◽  
Lianan Wang ◽  
Lisheng Peng
Keyword(s):  
Data Mining ◽  
Liver Cancer ◽  
Signaling Pathways ◽  
Target Genes ◽  
Primary Liver Cancer ◽  
Network Pharmacology ◽  
Data Mining Technique ◽  
Antitumor Effects ◽  
Bioactive Ingredients ◽  
Common Target

Objective. In this study, the data mining method was used to screen the core Chinese materia medicas (CCMMs) against primary liver cancer (PLC), and the potential mechanisms of CCMMs in treating PLC were analyzed based on network pharmacology. Methods. Traditional Chinese medicine (TCM) prescriptions for treating PLC were obtained from a famous TCM doctor in Shenzhen, China. According to the data mining technique, the TCM Inheritance Support System (TCMISS) was applied to excavate the CCMMs in the prescriptions. Then, bioactive ingredients and corresponding targets of CCMMs were collected using three different TCM online databases, and target genes of PLC were obtained from GeneCards and OMIM. Afterwards, common targets of CCMMs and PLC were screened. Furthermore, a network of CCMMs bioactive ingredients and common target gene was constructed by Cytoscape 3.7.1, and gene ontology (GO) and signaling pathways analyses were performed to explain the mechanism of CCMMs in treating PLC. Besides, protein-protein interaction (PPI) analysis was used to identify key target genes of CCMMs, and the prognostic value of key target genes was verified using survival analysis. Results. A total of 15 high-frequency Chinese materia medica combinations were found, and CCMMs (including Paeoniae Radix Alba, Radix Bupleuri, Macrocephalae Rhizoma, Coicis Semen, Poria, and Curcumae Radix) were identified by TCMISS. A total of 40 bioactive ingredients (e.g., quercetin, kaempferol, and naringenin) of CCMMs were obtained, and 202 common target genes of CCMMs and PLC were screened. GO analysis indicated that biological processes of CCMMs were mainly involved in response to drug, response to ethanol, etc. Pathway analysis demonstrated that CCMMs exerted its antitumor effects by acting on multiple signaling pathways, including PI3K-Akt, TNF, and MAPK pathways. Also, some key target genes of CCMMs were determined by PPI analysis, and four genes (MAPK3, VEGFA, EGF, and EGFR) were found to be correlated with survival in PLC patients. Conclusion. Based on data mining and network pharmacology methods, our results showed that the therapeutic effect of CCMMs on PLC may be realized by acting on multitargets and multipathways related to the occurrence and development of PLC.

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 Dissecting the Mechanism of Yuzhi Zhixue Granule on Ovulatory Dysfunctional Uterine Bleeding by Network Pharmacology and Molecular Docking

2020 ◽  
Author(s):  
Jialin Li ◽  
Hua Luo ◽  
Xinkui Liu ◽  
Jingyuan Zhang ◽  
Wei Zhou ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Therapeutic Target ◽  
Molecular Mechanisms ◽  
Therapeutic Targets ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Uterine Bleeding ◽  
Functional Enrichment ◽  
Network Pharmacology ◽  
Dysfunctional Uterine Bleeding

Abstract Background: Yuzhi Zhixue Granule (YZG)is a traditional Chinese patent medicine for treating excessive menstrual flow caused by ovulatory dysfunctional uterine bleeding (ODUB) accompanied by heat syndrome. However, the underlying molecular mechanisms, potential targets, and active ingredients of this prescription are still unknown. Therefore, it is imperative to explore the molecular mechanism of YZG.Methods: The active compounds in YZG were screened by the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). The putative targets of YZG were collected via TCMSP and Search Tool for Interacting Chemicals (STITCH) databases. The Therapeutic Target Database (TTD) and Pharmacogenomics Knowledgebase (PharmGKB) databases were used to identify the therapeutic targets of ODUB. A protein-protein interaction (PPI) network containing both the putative targets of YZG and known therapeutic targets of ODUB was built. Furthermore, bioinformatics resources from the database for annotation, visualization and integrated discovery (DAVID) were utilized for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Finally, molecular docking was performed to verify the binding effect between the YZG screened compounds and potential therapeutic target molecules.Results: The study employed a network pharmacology method, mainly containing target prediction, network construction, functional enrichment analysis, and molecular docking to systematically research the mechanisms of YZG in treating ODUB. The putative targets of YZG that treat ODUB mainly involved PTGS1, PTGS2, ALOX5, CASP3, LTA4H, F7 and F10. The functional enrichment analysis suggested that the produced therapeutic effect of YZG against ODUB is mediated by synergistical regulation of several biological pathways, including apoptosis arachidonic acid (AA) metabolism, serotonergic synapse, complement and coagulation cascades and C-type lectin receptor signaling pathways. Molecular docking simulation revealed good binding affinity of the seven putative targets with the corresponding compounds.Conclusion: This novel and scientific network pharmacology-based study holistically elucidated the basic pharmacological effects and the underlying mechanisms of YZG in the treatment of ODUB.

scholarly journals Exploration of Anti-Staphylococcus Aureus Activity and Molecular Mechanism of Wuweixiaoduyin using Network Pharmacology Anti-Staphylococcus Aureus Activity of Wuweixiaoduyin using Network Pharmacology

2021 ◽  
Author(s):  
Kai Huang ◽  
Bigyuan Lin ◽  
Haiyong Ren ◽  
Qifen Mao ◽  
Qiaofeng Guo ◽  
...  
Keyword(s):  
Staphylococcus Aureus ◽  
Growth Factor ◽  
Signaling Pathway ◽  
Target Genes ◽  
Therapeutic Targets ◽  
Mitogen Activated Protein Kinase ◽  
Network Pharmacology ◽  
Active Compounds ◽  
Pathway Enrichment ◽  
Aureus Infection

Abstract Background:S. aureus (Staphylococcus aureus) infection imposes a serious burden to global healthcare systems. WWXDY (Wuweixiaoduyin) is a traditional Chinese medicine, and it is usually used to treat infections in China. This study aimed to explore the active compounds, therapeutic targets, key pathways, and potential mechanisms of WWXDY in the treatment of S. aureus infection. Materials & Methods:Data related to active compounds and therapeutic targets of WWXDY for treating S. aureus were collected from DisGeNET, GeneCards, and DrugBank databases. To explore the roles of the active targets in gene function and signaling pathways, KEGG (Kyoto Gene and Genomics Encyclopedia) pathway enrichment and GO (Gene Ontology) analyses of the 122 target genes in the PPI (protein-protein interaction) network were performed. We further performed NP (network pharmacology) by using a network analyzer to screen 30 key targets. Results:A total 92 active compounds of WWXDY were screened. The 122 overlapped genes were found from 785 therapeutic targets and 684 S. aureus-related genes. Besides, 92 active compounds of WWXDY, such as mandenol, ethyllinolenate, eriodyctiol, secologanic dibutylacetal_qt, etc., were identified. The PPI network of the effective ingredients of WWXDY in treating S. aureus infection identified the top 30 genes, including IL-6 (interleukin-6), TNF-α (tumor necrosis factor-α), VEGFA (vascular endothelial growth factor A), AKT1, CXCL8, MAPK3 (mitogen-activated protein kinase 3), TLR (toll-like receptor 4), IL-1β, EGFR (epidermal growth factor receptor), and MMP9 (matrix metalloproteinase-9). Conclusion:The GO functional and KEGG pathway enrichment analyses indicated that 122 overlapped genes were mainly enriched in COVID-19, AGE-RAGE signaling pathway, C-type lectin receptor signaling pathway, Pertussis, and Chagas disease. Our findings indicated the active compounds and therapeutic targets of WWXDY in treating S. aureus infection, as well as its potential mechanisms.

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