A network pharmacology perspective for deciphering potential mechanisms of action of Solanum nigrum L. in bladder cancer

Abstract Background Solanum nigrum L. decoction has been used as a folklore medicine in China to prevent the postoperative recurrence of bladder cancer (BC). However, there are no previous pharmacological studies on the protective mechanisms of this activity of the plant. Thus, this study aimed to perform a systematic analysis and to predict the potential action mechanisms underlying S. nigrum activity in BC based on network pharmacology. Methods Based on network pharmacology, the active ingredients of S. nigrum and the corresponding targets were identified using the Traditional Chinese Medicines for Systems Pharmacology Database and Analysis Platform database, and BC-related genes were screened using GeneCards and the Online Mendelian Inheritance in Man database. In addition, ingredient-target (I–T) and protein–protein interaction (PPI) networks were constructed using STRING and Cytoscape, Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted, and then the pathways directly related to BC were integrated manually to reveal the pharmacological mechanism underlying S. nigrum-medicated therapeutic effects in BC. Results Seven active herbal ingredients from 39 components of S. nigrum were identified, which shared 77 common target genes related to BC. I-T network analysis revealed that quercetin was associated with all targets and that NCOA2 was targeted by four ingredients. Besides, interleukin 6 had the highest degree value in the PPI network, indicating a hub role. A subsequent gene enrichment analysis yielded 86 significant GO terms and 89 significant pathways, implying that S. nigrum had therapeutic benefits in BC through multi-pathway effects, including the HIF-1, TNF, P53, MAPK, PI3K/Akt, apoptosis and bladder cancer pathway. Conclusions S. nigrum may mediate pharmacological effects in BC through multi-target and various signaling pathways. Further validation is required experimentally. Network pharmacology approach provides a predicative novel strategy to reveal the holistic mechanism of action of herbs.

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Mechanisms of Compound Kushen Injection for Treatment of Bladder Cancer Based on Bioinformatics and Network Pharmacology With Experimental Validation

10.21203/rs.3.rs-71493/v1 ◽

2020 ◽

Author(s):

Lihui Zhang ◽

Wanying Zhang ◽

Jiaming Xiong ◽

Xiumei Duan ◽

Lina Hai ◽

...

Keyword(s):

Bladder Cancer ◽

Target Genes ◽

Medicinal Preparation ◽

Malignant Neoplasm ◽

Enrichment Analysis ◽

Functional Enrichment ◽

Bladder Cancer Cell Line ◽

Network Pharmacology ◽

Therapeutic Effects ◽

Gene And Protein Expression

Abstract Background: Bladder cancer is the most common malignant neoplasm of the urinary system. CompoundKushen injection (CKI) is a Chinese medicinal preparation that has been used clinically to treat varioustypes of cancers for more than 20 years. However, the pharmacological effect of CKI on bladder cancerrequires further clarification.Methods: Network pharmacology combined with bioinformatics was used to elucidate the therapeuticmechanism and potential targets of CKI in bladder cancer. The mechanism by which CKI is effective againstbladder cancer was further verified in vitro using the human bladder cancer cell line T24.Results: Network pharmacology analysis identified 35 active compounds and 268 target genes of CKI.Bioinformatics data mining revealed 5500 differentially expressed genes associated with bladder cancer.Common genes of CKI and bladder cancer suggested that CKI exerts anti-bladder cancer effects byregulating genes such as MMP-9, JUN, EGFR, and ERK1. Functional enrichment analysis indicated thatCKI has a therapeutic effect on bladder cancer by synergistically regulating certain biological processes,including cell proliferation, cell migration, and cell apoptosis. In addition, Kyoto Encyclopedia of Genes andGenomes enrichment analysis implicated pathways related to cancer, bladder cancer, and the PI3K-Aktsignaling pathway. Consistently, cell experiments indicated that CKI could inhibit proliferation andmigration of T24 bladder cancer cells, and induce their apoptosis. Moreover, RT-qPCR and western blotresults indicated that CKI may treat bladder cancer by downregulating gene and protein expression levels,respectively of MMP-9, JUN, EGFR, and ERK1.Conclusions: CKI can inhibit proliferation and migration, and induce apoptosis of T24 bladder cancer cellsthrough multiple biological pathways and targets. CKI also has significant effects on regulation of key genesand proteins associated with bladder cancer. Overall, our findings provide solid evidence and deepen currentunderstanding of the therapeutic effects of CKI for bladder cancer, and further support its clinical use.

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Therapeutic Effects of Naringin in Rheumatoid Arthritis: Network Pharmacology and Experimental Validation

Frontiers in Pharmacology ◽

10.3389/fphar.2021.672054 ◽

2021 ◽

Vol 12 ◽

Author(s):

Yirixiati Aihaiti ◽

Yong Song Cai ◽

Xiadiye Tuerhong ◽

Yan Ni Yang ◽

Yao Ma ◽

...

Keyword(s):

Rheumatoid Arthritis ◽

Target Genes ◽

Topological Analysis ◽

Osteoclast Differentiation ◽

Critical Factor ◽

Network Pharmacology ◽

Therapeutic Effects ◽

Dependent Manner ◽

Ppi Networks

Rheumatoid arthritis is a chronic autoimmune disease characterized by persistent hyperplasia of the synovial membrane and progressive erosion of articular cartilage. Disequilibrium between the proliferation and death of RA fibroblast-like synoviocytes (RA-FLSs) is the critical factor in progression of RA. Naringin has been reported to exert anti-inflammatory and antioxidant effect in acute and chronic animal models of RA. However, the therapeutic effect and underlying mechanisms of naringin in human RA-FLS remain unclear. Based on network pharmacology, the corresponding targets of naringin were identified using SwissTargetPrediction database, STITCH database, and Comparative Toxicogenomics Database. Deferentially expressed genes (DEGs) in RA were obtained from the GEO database. The protein–protein interaction (PPI) networks of intersected targets were constructed using the STRING database and visualized using Cytoscape. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed, and the pathways directly related to pathogenesis of RA were integrated manually. Further, in vitro studies were carried out based on network pharmacology. 99 target genes were intersected between targets of naringin and DEGs. The PPI network and topological analysis indicated that IL-6, MAPK8, MMP-9, TNF, and MAPK1 shared the highest centrality among all. GO analysis and KEGG analysis indicated that target genes were mostly enriched in (hsa05200) pathways in cancer, (hsa05161) hepatitis B, (hsa04380) osteoclast differentiation, (hsa04151) PI3K-Akt signaling pathway, and (hsa05142) Chagas disease (American trypanosomiasis). In vitro studies revealed that naringin exposure was found to promote apoptosis of RA-FLS, increased the activation of caspase-3, and increased the ratio of Bax/Bcl-2 in a dose-dependent manner. Furthermore, treatment of naringin attenuated the production of inflammatory cytokines and matrix metalloproteinases (MMPs) in TNF-ɑ–induced RA-FLS. Moreover, treatment of naringin inhibited the phosphorylation of Akt and ERK in RA-FLS. Network pharmacology provides a predicative strategy to investigate the therapeutic effects and mechanisms of herbs and compounds. Naringin inhibits inflammation and MMPs production and promotes apoptosis in RA-FLS via PI3K/Akt and MAPK/ERK signaling pathways.

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Identification of the Active Constituents and Significant Pathways of Shen-qi-Yi-zhu Decoction on Antigastric Cancer: A Network Pharmacology Research and Experimental Validation

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2021/6642171 ◽

2021 ◽

Vol 2021 ◽

pp. 1-13

Author(s):

Shuhong Zeng ◽

Zhibao Yu ◽

Xintian Xu ◽

Yuanjie Liu ◽

Jiepin Li ◽

...

Keyword(s):

Experimental Validation ◽

Target Genes ◽

Cell Model ◽

Network Pharmacology ◽

Disease Network ◽

Systematic Method ◽

Protein Protein Interaction ◽

Ppi Networks ◽

Underlying Mechanisms

Shen-qi-Yi-zhu decoction (SQYZD) is an empirical prescription with antigastric cancer (GC) property created by Xu Jing-fan, a National Chinese Medical Master. However, its underlying mechanisms are still unclear. Based on network pharmacology and experimental verification, this study puts forward a systematic method to clarify the anti-GC mechanism of SQYZD. The active ingredients of SQYZD and their potential targets were acquired from the TCMSP database. The target genes related to GC gathered from GeneCards, DisGeNET, OMIM, TTD, and DrugBank databases were imported to establish protein-protein interaction (PPI) networks in GeneMANIA. Cytoscape was used to establish the drug-ingredients-targets-disease network. The hub target genes collected from the SQYZD and GC were parsed via GO and KEGG analysis. Our findings from network pharmacology were successfully validated using an in vitro HGC27 cell model experiment. In a word, this study proves that the combination of network pharmacology and in vitro experiments is effective in clarifying the potential molecular mechanism of traditional Chinese medicine (TCM).

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Elucidation of the Mechanisms and Molecular Targets of Lianhuaqingwen for Treatment of COVID-19 Based on Network Pharmacology

Asian Journal of Complementary and Alternative Medicine ◽

10.53043/2347-3894.acam90020 ◽

2021 ◽

Vol 9 (4) ◽

pp. 111-122

Author(s):

Yan Luo ◽

Si-ting Gao ◽

Jun-xiong Cheng ◽

Wei-jian Xiong ◽

Wen-Fu Cao

Keyword(s):

Target Genes ◽

Molecular Targets ◽

Core Gene ◽

Mechanisms Of Action ◽

Network Pharmacology ◽

Pathway Network ◽

Functional Annotations ◽

Gene Pathway ◽

Protein Protein Interaction ◽

Ppi Networks

Lianhuaqingwen (LH) is the widely used in the treatment of Coronavirus disease 2019 (COVID-19). However, its mechanisms of action and molecular targets for treatment of COVID-19 are not clear. The active compounds of LH were collected and their targets were identified through the network pharmacology. The mechanism of compound multi components and multi targets and its relationship with disease are analyzed. COVID-19 targets were obtained by analyzing with TCMSP. In total, 282 active ingredients and 510 targets of LH were identified. Twenty-one target genes associated with LH and COVID-19. Protein-protein interaction (PPI) data were then obtained and PPI networks of LH putative targets and COVID-19-related targets were visualized and merged to identify the candidate targets for LH against COVID-19. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis were carried out. The gene-pathway network was constructed to screen the crucial target genes. The functional annotations of target genes were found to be related to immune regulation, host defense, inflammatory reaction and autoimmune diseases and so on. Twenty pathways including immunology, cancer, and cell processing were significantly enriched. Quercetin and luteolin might be the crucial ingredients. IL6 was the core gene and other several genes including IL1B, STAT1, IFNGR1, and NCF1 were the key genes in the gene-pathway network of LH for treatment of COVID-19. The results indicated that LH’s effects against COVID-19 might relate to regulation of immunological function through the specific biological processes and the related pathways. This study demonstrates the application of network pharmacology in evaluating mechanisms of action and molecular targets of complex herbal formulations.

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

10.21203/rs.3.rs-19020/v1 ◽

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.

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Network Pharmacology-Based Systematic Analysis of Molecular Mechanisms of Geranium wilfordii Maxim for HSV-2 Infection

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2021/1009551 ◽

2021 ◽

Vol 2021 ◽

pp. 1-9

Author(s):

Hao Zhang ◽

Ming-Huang Gao ◽

Yang Chen ◽

Tao Liu

Keyword(s):

Molecular Docking ◽

Molecular Mechanisms ◽

Target Genes ◽

Pharmacological Study ◽

Network Pharmacology ◽

System Response ◽

Cytokine Signaling ◽

Bioactive Substances ◽

Systematic Analysis ◽

Specific Distribution

Background. Being a traditional Chinese medicine, Geranium wilfordii Maxim (GWM) is used for the treatment of various infectious diseases, and its main active ingredients are the polyphenolic substances such as polyphenols quercetin, corilagin, and geraniin. Previous studies have demonstrated the anti-HSV-1 viral activity of these three main ingredients. Through employing a network pharmacological method, the authors of the present research intend to probe the mechanism of GWM for the therapeutic treatment of HSV-2 infection. Methods. The bioactive substances and related targets of GWM were obtained from the TCMSP database. Gene expression discrepancy for HSV-2 infection was obtained from dataset GSE18527. Crossover genes between disease target genes and GWM target genes were gained via Circos package. Distinctively displayed genes (DDGs) during HSV-2 infection were uploaded to the Metascape database with GWM target genes for further analysis. The tissue-specific distribution of the genes was obtained by uploading the genes to the PaGenBase database. Ingredient-gene-pathway (IGP) networks were constructed using Cytoscape software. Molecular docking investigations were carried out utilizing AutoDock Vina software. Results. Nine actively involved components were retrieved from the TCMSP database. After taking the intersection among 153 drug target genes and 83 DDGs, 7 crossover genes were screened. Gene enrichment analysis showed that GWM treatment of HSV-2 infection mainly involves cytokine signaling in the immune system, response to virus, epithelial cell differentiation, and type II interferon signaling (IFNG). One hub, three core objectives, and two critical paths were filtered out from the built network. Geraniin showed strong binding activity with HSV-2 gD protein and STING protein in molecular docking. Conclusions. This network pharmacological study provides a fundamental molecular mechanistic exploration of GWM for the treatment of HSV-2 infection.

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Elucidating the Effects of Curcumin against Influenza Using In Silico and In Vitro Approaches

Pharmaceuticals ◽

10.3390/ph14090880 ◽

2021 ◽

Vol 14 (9) ◽

pp. 880

Author(s):

Minjee Kim ◽

Hanul Choi ◽

Sumin Kim ◽

Lin Woo Kang ◽

Young Bong Kim

Keyword(s):

Influenza Virus ◽

Molecular Docking ◽

Mdck Cells ◽

Influenza Infection ◽

Network Pharmacology ◽

Therapeutic Effects ◽

In Vitro Experiments ◽

Target Interaction ◽

Ppi Networks

The influenza virus is a constantly evolving pathogen that challenges medical and public health systems. Traditionally, curcumin has been used to treat airway inflammatory diseases, such as bronchitis and pneumonia. To elucidate common targets of curcumin and influenza infection and underlying mechanisms, we employed network pharmacology and molecular docking approaches and confirmed results using in vitro experiments. Biological targets of curcumin and influenza were collected, and potential targets were identified by constructing compound–disease target (C-D) and protein–protein interaction (PPI) networks. The ligand–target interaction was determined using the molecular docking method, and in vitro antiviral experiments and target confirmation were conducted to evaluate curcumin’s effects on influenza. Our network and pathway analyses implicated the four targets of AKT1, RELA, MAPK1, and TP53 that could be involved in the inhibitory effects of curcumin on influenza. The binding energy calculations of each ligand–target interaction in the molecular docking showed that curcumin bound to AKT1 with the highest affinity among the four targets. In vitro experiments, in which influenza virus-infected MDCK cells were pre-, co-, or post-treated with curcumin, confirmed curcumin’s prophylactic and therapeutic effects. Influenza virus induction increased the level of mRNA expression of AKT in MDCK cells, and the level was attenuated by curcumin treatment. Collectively, our findings identified potential targets of curcumin against influenza and suggest curcumin as a potential therapy for influenza infection.

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Network Pharmacology-Based Systematic Analysis of Molecular Mechanisms of Dingji Fumai Decoction for Ventricular Arrhythmia

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2021/5535480 ◽

2021 ◽

Vol 2021 ◽

pp. 1-12

Author(s):

Yi Liang ◽

Bo Liang ◽

Xin-Rui Wu ◽

Wen Chen ◽

Li-Zhi Zhao

Keyword(s):

Molecular Docking ◽

Ventricular Arrhythmia ◽

Molecular Mechanisms ◽

Mendelian Inheritance ◽

Network Pharmacology ◽

Ppi Network ◽

Systematic Analysis ◽

Chemical Structures ◽

Function Modules ◽

Underlying Mechanisms

Background. Dingji Fumai Decoction (DFD), a traditional herbal mixture, has been widely used to ventricular arrhythmia (VA) in clinical practice in China. However, research on the bioactive components and underlying mechanisms of DFD in VA is still scarce. Methods. Components of DFD were collected from TCMSP, ETCM, and literature. The chemical structures of each component were obtained from PubChem. Next, SwissADME and SwissTargetPrediction were applied for compounds screening and targets prediction of DFD; meanwhile, targets of VA were collected from DrugBank and Online Mendelian Inheritance in Man (OMIM). Then, the H-C-T-D network and the protein-protein interaction (PPI) network were constructed based on the data obtained above. CytoNCA was utilized to filter hub genes and VarElect was used to analyze the relationship between genes and diseases. At last, Metascape was employed for systematic analysis on the potential targets of herbals against VA, and AutoDock was applied for molecular docking to verify the results. Results. A total of 434 components were collected, 168 of which were qualified, and there were 28 shared targets between DFD and VA. Three function modules of DFD were found from the PPI network. Further systematic analysis of shared genes and function modules explained the potential mechanism of DFD in the treatment of VA; molecular docking has verified the interactions. Conclusions. DFD could be employed for VA through mechanisms, including complex interactions between related components and targets, as predicted by network pharmacology and molecular docking. This work confirmed that DFD could apply to the treatment of VA and promoted the explanation of DFD for VA in the molecular mechanisms.

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A Comprehensive Network Pharmacology-Based Strategy to Investigate Multiple Mechanisms of HeChan Tablet on Lung Cancer

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2020/7658342 ◽

2020 ◽

Vol 2020 ◽

pp. 1-17 ◽

Cited By ~ 2

Author(s):

Zhenjie Zhuang ◽

Qianying Chen ◽

Cihui Huang ◽

Junmao Wen ◽

Haifu Huang ◽

...

Keyword(s):

Lung Cancer ◽

Therapeutic Target ◽

Molecular Mechanisms ◽

Target Genes ◽

Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Network Pharmacology ◽

Hub Genes ◽

Lung Cancer Patients ◽

Ppi Networks

Background. HeChan tablet (HCT) is a traditional Chinese medicine preparation extensively prescribed to treat lung cancer in China. However, the pharmacological mechanisms of HCT on lung cancer remain to be elucidated. Methods. A comprehensive network pharmacology-based strategy was conducted to explore underlying mechanisms of HCT on lung cancer. Putative targets and compounds of HCT were retrieved from TCMSP and BATMAN-TCM databases; related genes of lung cancer were retrieved from OMIM and DisGeNET databases; known therapeutic target genes of lung cancer were retrieved from TTD and DrugBank databases; PPI networks among target genes were constructed to filter hub genes by STRING. Furthermore, the pathway and GO enrichment analysis of hub genes was performed by clusterProfiler, and the clinical significance of hub genes was identified by The Cancer Genome Atlas. Result. A total of 206 compounds and 2,433 target genes of HCT were obtained. 5,317 related genes of lung cancer and 77 known therapeutic target genes of lung cancer were identified. 507 unique target genes were identified among HCT-related genes of lung cancer and 34 unique target genes were identified among HCT-known therapeutic target genes of lung cancer. By PPI networks, 11 target genes AKT1, TP53, MAPK8, JUN, EGFR, TNF, INS, IL-6, MYC, VEGFA, and MAPK1 were identified as major hub genes. IL-6, JUN, EGFR, and MYC were shown to associate with the survival of lung cancer patients. Five compounds of HCT， quercetin, luteolin, kaempferol, beta-sitosterol, and baicalein were recognized as key compounds of HCT on lung cancer. The gene enrichment analysis implied that HCT probably benefitted patients with lung cancer by modulating the MAPK and PI3K-Akt pathways. Conclusion. This study predicted pharmacological and molecular mechanisms of HCT against lung cancer and could pave the way for further experimental research and clinical application of HCT.

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Network Pharmacology Analysis of Traditional Chinese Medicine Formula Xiao Ke Yin Shui Treating Type 2 Diabetes Mellitus

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2019/4202563 ◽

2019 ◽

Vol 2019 ◽

pp. 1-15 ◽

Cited By ~ 7

Author(s):

Jiewen Zhou ◽

Qiuyan Wang ◽

Zhinan Xiang ◽

Qilin Tong ◽

Jun Pan ◽

...

Keyword(s):

Diabetes Mellitus ◽

Type 2 Diabetes ◽

Chinese Medicine ◽

Traditional Chinese Medicine ◽

Target Genes ◽

Network Pharmacology ◽

Ppi Networks ◽

Chinese Medicine Formula ◽

Herb Extracts

Xiao Ke Yin Shui (XKYS) formula is a traditional Chinese medicine formula treating type 2 diabetes mellitus (T2DM). XKYS formula consists of four herbs, i.e., Coptidis rhizoma, Liriopes radix, bitter melon, and Cassiae semen. Herein, the chemical profiles of four herb extracts were investigated, and further analysis of the underlying mechanism of XKYS formula treating T2DM was performed using network pharmacology. The main components were selected for our network-based research. Targets of XKYS formula were mainly collected from two databases, SwissTargetPrediction and Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), and the text-mining method was also implemented. T2DM relating genes and therapeutic targets were collected from five databases. Subsequently, STRING and Cytoscape were employed for the analysis of protein-protein interaction (PPI) networks. Functional annotation and pathway analysis were conducted to investigate the functions and relating pathways of target genes. The content of 12 compounds in the herb extracts was determined. With the analysis of PPI networks, a total of 76 genes were found to be important nodes and could be defined as the main target genes regulated by XKYS formula in the treatment of T2DM and its complications. Components in XKYS formula mainly regulate proteins including protein kinase B (Akt), phosphatidylinositol 3-kinase (PI3K), insulin receptor substrate (IRS), and tumor necrosis factor (TNF). XKYS formula exerts therapeutic effects in a synergetic manner and exhibits antidiabetic effect mainly via reducing insulin resistance. These findings could be guidelines in the further investigation of this formula.

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