Based on Network Pharmacology and Molecular Docking to Explore the Underlying Mechanism of Huangqi Gegen Decoction for Treating Diabetic Nephropathy

Background. Huangqi Gegen decoction (HGD), a Chinese herb formula, has been widely used to treat diabetic nephropathy in China, while the pharmacological mechanisms are still unclear. Therefore, the present study aims to explore the underlying mechanism of HGD for treating diabetic nephropathy (DN). Materials and Methods. Traditional Chinese Medicine Systems Pharmacology Database (TCMSP), UniProt, and SwissTargetPrediction databases were used to search the active ingredients and potential targets of HGD. In addition, multiple disease-related databases were used to collect DN-related targets. Common targets of the protein-protein interaction (PPI) network were established using the STRING database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the DAVID database. At last, AutoDockVina was used to conduct molecular docking verification for the core components and targets. Results. A total of 27 active ingredients and 354 putative identified target genes were screened from HGD, of which 99 overlapped with the targets of DN and were considered potential therapeutic targets. Further analysis showed that the HGD activity of quercetin, formononetin, kaempferol, isorhamnetin, and beta-sitosterol ingredients is possible through VEGFA, IL6, TNF, AKT1, and TP53 targets involved in TNF, toll-like receptors, and MAPK-related pathways, which have anti-inflammatory, antiapoptosis, antioxidation, and autophagy effects, relieve renal fibrosis and renal cortex injury, and improve renal function, thus delaying the development of DN. The molecular docking results showed that quercetin, formononetin, kaempferol, isorhamnetin, beta-sitosterol had a good binding activity with VEGFA, IL6, TNF, AKT1, and TP53. Conclusion. This study demonstrated that HGD might take part in the treatment of DN through multicomponent, multitarget, and multichannel combined action.

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Potential Molecular Target Prediction and Docking Verification of Hua-Feng-Dan in Stroke Based on Network Pharmacology

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2020/8872593 ◽

2020 ◽

Vol 2020 ◽

pp. 1-12

Author(s):

Ping Yang ◽

Haifeng He ◽

Shangfu Xu ◽

Ping Liu ◽

Xinyu Bai

Keyword(s):

Molecular Docking ◽

Signaling Pathways ◽

Target Genes ◽

Target Prediction ◽

Interaction Network ◽

Network Pharmacology ◽

Core Network ◽

Active Ingredients ◽

Protein Protein Interaction ◽

Highly Correlated

Objective. Hua-Feng-Dan (HFD) is a Chinese medicine for stroke. This study is to predict and verify potential molecular targets and pathways of HFD against stroke using network pharmacology. Methods. The TCMSP database and TCMID were used to search for the active ingredients of HFD, and GeneCards and DrugBank databases were used to search for stroke-related target genes to construct the “component-target-disease” by Cytoscape 3.7.1, which was further filtered by MCODE to build a core network. The STRING database was used to obtain interrelationships by topology and to construct a protein-protein interaction network. GO and KEGG were carried out through DAVID Bioinformatics. Autodock 4.2 was used for molecular docking. BaseSpace was used to correlate target genes with the GEO database. Results. Based on OB ≥ 30% and DL ≥ 0.18, 42 active ingredients were extracted from HFD, and 107 associated targets were obtained. PPI network and Cytoscape analysis identified 22 key targets. GO analysis suggested 51 cellular biological processes, and KEGG suggested that 60 pathways were related to the antistroke mechanism of HFD, with p53, PI3K-Akt, and apoptosis signaling pathways being most important for HFD effects. Molecular docking verified interactions between the core target (CASP8, CASP9, MDM2, CYCS, RELA, and CCND1) and the active ingredients (beta-sitosterol, luteolin, baicalein, and wogonin). The identified gene targets were highly correlated with the GEO biosets, and the stroke-protection effects of Xuesaitong in the database were verified by identified targets. Conclusion. HFD could regulate the symptoms of stroke through signaling pathways with core targets. This work provided a bioinformatic method to clarify the antistroke mechanism of HFD, and the identified core targets could be valuable to evaluate the antistroke effects of traditional Chinese medicines.

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Based on Network Pharmacology to Explore the Molecular Targets and Mechanisms of Gegen Qinlian Decoction for the Treatment of Ulcerative Colitis

BioMed Research International ◽

10.1155/2020/5217405 ◽

2020 ◽

Vol 2020 ◽

pp. 1-18

Author(s):

Meiqi Wei ◽

He Li ◽

Qifang Li ◽

Yi Qiao ◽

Qun Ma ◽

...

Keyword(s):

Ulcerative Colitis ◽

Molecular Docking ◽

Signaling Pathway ◽

Target Genes ◽

Topological Analysis ◽

Molecular Targets ◽

Enrichment Analysis ◽

Binding Activity ◽

Network Pharmacology ◽

Active Ingredients

Background. Gegen Qinlian (GGQL) decoction is a common Chinese herbal compound for the treatment of ulcerative colitis (UC). In this study, we aimed to identify its molecular target and the mechanism involved in UC treatment by network pharmacology and molecular docking. Material and Methods. The active ingredients of Puerariae, Scutellariae, Coptis, and Glycyrrhiza were screened using the TCMSP platform with drug ‐ like properties DL ≥ 0.18 and oral availability OB ≥ 30 % . To find the intersection genes and construct the TCM compound-disease regulatory network, the molecular targets were determined in the UniProt database and then compared with the UC disease differential genes with P value < 0.005 and ∣ log 2 fold change ∣ > 1 obtained in the GEO database. The intersection genes were subjected to protein-protein interaction (PPI) construction and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. After screening the key active ingredients and target genes, the AutoDock software was used for molecular docking, and the best binding target was selected for molecular docking to verify the binding activity. Results. A total of 146 active compounds were screened, and quercetin, kaempferol, wogonin, and stigmasterol were identified as the active ingredients with the highest associated targets, and NOS2, PPARG, and MMP1 were the targets associated with the maximum number of active ingredients. Through topological analysis, 32 strongly associated proteins were found, of which EGFR, PPARG, ESR1, HSP90AA1, MYC, HSPA5, AR, AKT1, and RELA were predicted targets of the traditional Chinese medicine, and PPARG was also an intersection gene. It was speculated that these targets were the key to the use of GGQL in UC treatment. GO enrichment results showed significant enrichment of biological processes, such as oxygen levels, leukocyte migration, collagen metabolic processes, and nutritional coping. KEGG enrichment showed that genes were particularly enriched in the IL-17 signaling pathway, AGE-RAGE signaling pathway, toll-like receptor signaling pathway, tumor necrosis factor signaling pathway, transcriptional deregulation in cancer, and other pathways. Molecular docking results showed that key components in GGQL had good potential to bind to the target genes MMP3, IL1B, NOS2, HMOX1, PPARG, and PLAU. Conclusion. GGQL may play a role in the treatment of ulcerative colitis by anti-inflammation, antioxidation, and inhibition of cancer gene transcription.

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Integrating Network Pharmacology with Molecular Docking to Unravel the Active Compounds and Potential Mechanism of Simiao Pill Treating Rheumatoid Arthritis

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2020/5786053 ◽

2020 ◽

Vol 2020 ◽

pp. 1-16

Author(s):

Mengshi Tang ◽

Xi Xie ◽

Pengji Yi ◽

Jin Kang ◽

Jiafen Liao ◽

...

Keyword(s):

Rheumatoid Arthritis ◽

Molecular Docking ◽

Signaling Pathway ◽

Target Genes ◽

Enrichment Analysis ◽

Binding Activity ◽

New Combination ◽

Network Pharmacology ◽

Pathway Enrichment Analysis ◽

Potential Mechanism

Objective. To explore the main components and unravel the potential mechanism of simiao pill (SM) on rheumatoid arthritis (RA) based on network pharmacological analysis and molecular docking. Methods. Related compounds were obtained from TCMSP and BATMAN-TCM database. Oral bioavailability and drug-likeness were then screened by using absorption, distribution, metabolism, and excretion (ADME) criteria. Additionally, target genes related to RA were acquired from GeneCards and OMIM database. Correlations about SM-RA, compounds-targets, and pathways-targets-compounds were visualized through Cytoscape 3.7.1. The protein-protein interaction (PPI) network was constructed by STRING. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed via R packages. Molecular docking analysis was constructed by the Molecular Operating Environment (MOE). Results. A total of 72 potential compounds and 77 associated targets of SM were identified. The compounds-targets network analysis indicated that the 6 compounds, including quercetin, kaempferol, baicalein, wogonin, beta-sitosterol, and eugenol, were linked to ≥10 target genes, and the 10 target genes (PTGS1, ESR1, AR, PGR, CHRM3, PPARG, CHRM2, BCL2, CASP3, and RELA) were core target genes in the network. Enrichment analysis indicated that PI3K-Akt, TNF, and IL-17 signaling pathway may be a critical signaling pathway in the network pharmacology. Molecular docking showed that quercetin, kaempferol, baicalein, and wogonin have good binding activity with IL6, VEGFA, EGFR, and NFKBIA targets. Conclusion. The integrative investigation based on bioinformatics/network topology strategy may elaborate on the multicomponent synergy mechanisms of SM against RA and provide the way out to develop new combination medicines for RA.

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Network Pharmacology-Based Study on the Mechanism of Aloe Vera for Treating Cancer

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2021/6077698 ◽

2021 ◽

Vol 2021 ◽

pp. 1-8

Author(s):

Jing Xie ◽

Jun Wu ◽

Sihui Yang ◽

Huaijun Zhou

Keyword(s):

Molecular Docking ◽

Drug Targets ◽

Aloe Vera ◽

Beta Carotene ◽

Network Pharmacology ◽

Potential Mechanism ◽

Active Ingredients ◽

Protein Protein Interaction ◽

Target Network ◽

Molecule Docking

Background. Aloe vera has long been considered an anticancer herb in different parts of the world. Objective. To explore the potential mechanism of aloe vera in the treatment of cancer using network pharmacology and molecule docking approaches. Methods. The active ingredients and corresponding protein targets of aloe vera were identified from the TCMSP database. Targets related to cancer were obtained from GeneCards and OMIM databases. The anticancer targets of aloe vera were obtained by intersecting the drug targets with the disease targets, and the process was presented in the form of a Venn plot. These targets were uploaded to the String database for protein-protein interaction (PPI) analysis, and the result was visualized by Cytoscape software. Go and KEGG enrichment were used to analyze the biological process of the target proteins. Molecular docking was used to verify the relationship between the active ingredients of aloe vera and predicted targets. Results. By screening and analyzing, 8 active ingredients and 174 anticancer targets of aloe vera were obtained. The active ingredient-anticancer target network constructed by Cytoscape software indicated that quercetin, arachidonic acid, aloe-emodin, and beta-carotene, which have more than 4 gene targets, may play crucial roles. In the PPI network, AKT1, TP53, and VEGFA have the top 3 highest values. The anticancer targets of aloe vera were mainly involved in pathways in cancer, prostate cancer, bladder cancer, pancreatic cancer, and non-small-cell lung cancer and the TNF signaling pathway. The results of molecular docking suggested that the binding ability between TP53 and quercetin was the strongest. Conclusion. This study revealed the active ingredients of aloe vera and the potential mechanism underlying its anticancer effect based on network pharmacology and provided ideas for further research.

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Impact of Qi-Invigorating Traditional Chinese Medicines on Diffuse Large B Cell Lymphoma Based on Network Pharmacology and Experimental Validation

Frontiers in Pharmacology ◽

10.3389/fphar.2021.787816 ◽

2021 ◽

Vol 12 ◽

Author(s):

Qian Huang ◽

Jinkun Lin ◽

Surong Huang ◽

Jianzhen Shen

Keyword(s):

Molecular Docking ◽

Target Genes ◽

Cell Lymphoma ◽

B Cell Lymphoma ◽

Network Pharmacology ◽

Active Ingredients ◽

Hub Genes ◽

Large B Cell Lymphoma ◽

Large B Cell

Background: It has been verified that deficiency of Qi, a fundamental substance supporting daily activities according to the Traditional Chinese Medicine theory, is an important symptom of cancer. Qi-invigorating herbs can inhibit cancer development through promoting apoptosis and improving cancer microenvironment. In this study, we explored the potential mechanisms of Qi-invigorating herbs in diffuse large B cell lymphoma (DLBCL) through network pharmacology and in vitro experiment.Methods: Active ingredients of Qi-invigorating herbs were predicted from the Traditional Chinese Medicine Systems Pharmacology Database. Potential targets were obtained via the SwissTargetPrediction and STITCH databases. Target genes of DLBCL were obtained through the PubMed, the gene-disease associations and the Malacards databases. Overlapping genes between DLBCL and each Qi-invigorating herb were collected. Hub genes were subsequently screened via Cytoscape. The Gene Ontology and pathway enrichment analyses were performed using the DAVID database. Molecular docking was performed among active ingredients and hub genes. Hub genes linked with survival and tumor microenvironment were analyzed through the GEPIA 2.0 and TIMER 2.0 databases, respectively. Additionally, in vitro experiment was performed to verify the roles of common hub genes.Results: Through data mining, 14, 4, 22, 22, 35, 2, 36 genes were filtered as targets of Ginseng Radix et Rhizoma, Panacis Quinquefolii Radix, Codonopsis Radix, Pseudostellariae Radix, Astragali Radix, Dioscoreae Rhizoma, Glycyrrhizae Radix et Rhizoma for DLBCL treatment, respectively. Then besides Panacis Quinquefolii Radix and Dioscoreae Rhizoma, 1,14, 10, 14,13 hub genes were selected, respectively. Molecular docking studies indicated that active ingredients could stably bind to the pockets of hub proteins. CASP3, CDK1, AKT1 and MAPK3 were predicted as common hub genes. However, through experimental verification, only CASP3 was considered as the common target of Qi-invigorating herbs on DLBCL apoptosis. Furthermore, the TIMER2.0 database showed that Qi-invigorating herbs might act on DLBCL microenvironment through their target genes. Tumor-associated neutrophils may be main target cells of DLBCL treated by Qi-invigorating herbs.Conclusion: Our results support the effects of Qi-invigorating herbs on DLBCL. Hub genes and immune infiltrating cells provided the molecular basis for each Qi-invigorating herb acting on DLBCL.

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Based on Network Pharmacology Tools to Investigate the Molecular Mechanism of Cordyceps sinensis on the Treatment of Diabetic Nephropathy

Journal of Diabetes Research ◽

10.1155/2021/8891093 ◽

2021 ◽

Vol 2021 ◽

pp. 1-12

Author(s):

Yan Li ◽

Lei Wang ◽

Bojun Xu ◽

Liangbin Zhao ◽

Li Li ◽

...

Keyword(s):

Oxidative Stress ◽

Insulin Resistance ◽

Diabetic Nephropathy ◽

Inflammatory Response ◽

Signaling Pathway ◽

Molecular Mechanisms ◽

Target Genes ◽

Cordyceps Sinensis ◽

Network Pharmacology ◽

Active Ingredients

Background. Diabetic nephropathy (DN) is one of the most common complications of diabetes mellitus and is a major cause of end-stage kidney disease. Cordyceps sinensis (Cordyceps, Dong Chong Xia Cao) is a widely applied ingredient for treating patients with DN in China, while the molecular mechanisms remain unclear. This study is aimed at revealing the therapeutic mechanisms of Cordyceps in DN by undertaking a network pharmacology analysis. Materials and Methods. In this study, active ingredients and associated target proteins of Cordyceps sinensis were obtained via Traditional Chinese Medicine Systems Pharmacology Database (TCMSP) and Swiss Target Prediction platform, then reconfirmed by using PubChem databases. The collection of DN-related target genes was based on DisGeNET and GeneCards databases. A DN-Cordyceps common target interaction network was carried out via the STRING database, and the results were integrated and visualized by utilizing Cytoscape software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to determine the molecular mechanisms and therapeutic effects of Cordyceps on the treatment of DN. Results. Seven active ingredients were screened from Cordyceps, 293 putative target genes were identified, and 85 overlapping targets matched with DN were considered potential therapeutic targets, such as TNF, MAPK1, EGFR, ACE, and CASP3. The results of GO and KEGG analyses revealed that hub targets mainly participated in the AGE-RAGE signaling pathway in diabetic complications, TNF signaling pathway, PI3K-Akt signaling pathway, and IL-17 signaling pathway. These targets were correlated with inflammatory response, apoptosis, oxidative stress, insulin resistance, and other biological processes. Conclusions. Our study showed that Cordyceps is characterized as multicomponent, multitarget, and multichannel. Cordyceps may play a crucial role in the treatment of DN by targeting TNF, MAPK1, EGFR, ACE, and CASP3 signaling and involved in the inflammatory response, apoptosis, oxidative stress, and insulin resistance.

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Uncovering the mechanism of Ge-Gen-Qin-Lian decoction for treating ulcerative colitis based on network pharmacology and molecular docking verification

Bioscience Reports ◽

10.1042/bsr20203565 ◽

2021 ◽

Vol 41 (2) ◽

Author(s):

Lin Xu ◽

Jiaqi Zhang ◽

Yifan Wang ◽

Zedan Zhang ◽

Fengyun Wang ◽

...

Keyword(s):

Ulcerative Colitis ◽

Molecular Docking ◽

Interaction Network ◽

Network Pharmacology ◽

Potential Candidate ◽

Active Ingredients ◽

Protein Protein Interaction ◽

Pharmacological Mechanism ◽

Th17 Cell Differentiation ◽

The Relationship

Abstract Background: Ge-Gen-Qin-Lian Decoction (GGQLD), a traditional Chinese medicine (TCM) formula, has been widely used for ulcerative colitis (UC) in China, but the pharmacological mechanisms remain unclear. This research was designed to clarify the underlying pharmacological mechanism of GGQLD against UC. Method: In this research, a GGQLD-compound-target-UC network was constructed based on public databases to clarify the relationship between active compounds in GGQLD and potential targets. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analyses were performed to investigate biological functions associated with potential targets. A protein–protein interaction network was constructed to screen and evaluate hub genes and key active ingredients. Molecular docking was used to verify the activities of binding between hub targets and ingredients. Results: Finally, 83 potential therapeutic targets and 118 corresponding active ingredients were obtained by network pharmacology. Quercetin, kaempferol, wogonin, baicalein, and naringenin were identified as potential candidate ingredients. GO and KEGG enrichment analyses revealed that GGQLD had anti-inflammatory, antioxidative, and immunomodulatory effects. The effect of GGQLD on UC might be achieved by regulating the balance of cytokines (e.g., IL-6, TNF, IL-1β, CXCL8, CCL2) in the immune system and inflammation-related pathways, such as the IL-17 pathway and the Th17 cell differentiation pathway. In addition, molecular docking results demonstrated that the main active ingredient, quercetin, exhibited good affinity to hub targets. Conclusion: This research fully reflects the multicomponent and multitarget characteristics of GGQLD in the treatment of UC. Furthermore, the present study provided new insight into the mechanisms of GGQLD against UC.

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The Study on the Molecular Mechanism of Erchen Tang on Asthma Based on Network Pharmacology

10.21203/rs.3.rs-34639/v1 ◽

2020 ◽

Author(s):

Yuzhe Ren ◽

Haijing Zhang ◽

Zhou Yu ◽

Jun Wan ◽

Xuejin Peng ◽

...

Keyword(s):

Functional Analysis ◽

Target Genes ◽

Tissue Injury ◽

Underlying Mechanism ◽

Network Pharmacology ◽

Inflammatory Factor ◽

Active Ingredients ◽

Cationic Protein ◽

Stat3 Pathway ◽

Tnf Α

Abstract Objective: To explore the active ingredients of ECT and their targets of asthma and investigate the potential mechanism of ECT on asthma. Methods: Firstly, the active ingredients and target of ECT were screened for BATMAN and TCMSP, functional analysis was finished via DAVID. Then, animal model was induced by ovalbumin (OVA) and aluminum hydroxide. Eosinophil (EOS) counts, EOS active substance Eosinophilic cationic protein (ECP) and eotaxin levels were detected followed the instruction. Pathological changes of lungs tissue were examined by H&E staining and transmission electron microscopy. Interleukin (IL-4, IL-10, IL-13, TNF-α), TIgE and IgE level in bronchoalveolar lavage fluid (BALF) were measured by ELISA. Finally, the protein expression of TGF-β / STAT3 pathway to lung tissue was detected by Western Blot. Results: A total of 450 compounds and 526 target genes were retrieved in Erchen tang. Functional analysis indicated that its treatment of asthma was associated with inflammatory factor and fibrosis. In the animal experiment, the results showed that ECT significantly regulated inflammatory cytokine (IL-4, IL-10, IL-13, TNF-α) levels in (P<0.05, P<0.01) , reduced EOS number (P<0.05) and also ECP and Eotaxin levels in blood (P<0.05) in BALF and / or plasma. Bronchial tissue injury was obviously improved on ECT treatment. Associated protein in TGF-β / STAT3 pathway were significantly regulated by ECT (P<0.05). Conclusion: This study originally provided the evidence that the Erchen tang was effective against the treatment of asthma symptoms, and its underlying mechanism might be regulation of inflammatory factor secretion and TGF-β/STAT3 signaling pathway.

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Exploring the Mechanisms Underlying the Therapeutic Effect of Salvia Miltiorrhiza Against Diabetic Nephropathy Using Network Pharmacology and Molecular Docking

10.21203/rs.3.rs-85980/v1 ◽

2020 ◽

Author(s):

Li-Li Zhang ◽

Lin Han ◽

Xin-Miao Wang ◽

Yu Wei ◽

Jing-Hui Zheng ◽

...

Keyword(s):

Diabetic Nephropathy ◽

Molecular Docking ◽

Therapeutic Effect ◽

Molecular Mechanisms ◽

Function Analysis ◽

Salvia Miltiorrhiza ◽

Network Pharmacology ◽

Pathway Enrichment Analysis ◽

Ppi Network ◽

Active Ingredients

Abstract BackgroundThe mechanisms underlying the therapeutic effect of Salvia Miltiorrhiza (SM) against diabetic nephropathy (DN) using systematic network pharmacology and molecular docking methods were examined.MethodsTCMSP database was used to screen the active ingredients of SM. Gene targets were obtained using Swiss Target Prediction and TCMSP databases. Related targets of DN were retrieved from the Genecards and DisGeNET databases. Next, a PPI network was constructed using the common targets of SM-DN in the STRING database. The Metascape platform was used for GO function analysis and Cytoscape plug-in ClueGO was used for KEGG pathway enrichment analysis. Molecular docking was performed using iGEMDOCK and AutoDock Vina software. Pymol and LigPlos were used for mapping the network. ResultsSixty-six active ingredients and 189 targets were screened from SM. Among them, 64 targets overlapped with DN targets. The PPI network diagram revealed that AKT1, VEGFA, IL6, TNF, MAPK1, TP53, EGFR, STAT3, MAPK14, and JUN were the top 10 relevant targets. GO and KEGG analyses mainly focused on advanced glycation end products, oxidative stress, inflammatory response, and immune regulation. Molecular docking revealed that the potential target genes closely related to DN, including TNF, NOS2, and AKT1, were more stable in combination with salvianolic acid B, and their stability was better than that of tanshinone IIA.ConclusionThis study reveals the active components and potential molecular mechanisms involved in the therapeutic effect of SM against DN and provides a reference for the wide application of SM in clinically managing DN.

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Construction of Pharmacological Network and Molecular Docking Analysis of Key Molecular Components of Jianpi Yiqi Formula for Idiopathic Thrombocytopenic Purpura

10.21203/rs.3.rs-1067274/v1 ◽

2021 ◽

Author(s):

Qiming Li ◽

Gang Deng ◽

Yunlei He ◽

Jiafeng Yang

Keyword(s):

Molecular Docking ◽

Idiopathic Thrombocytopenic Purpura ◽

Target Genes ◽

Network Pharmacology ◽

Active Ingredients ◽

Critical Pathway ◽

Thrombocytopenic Purpura ◽

Active Compounds ◽

Docking Analysis ◽

Molecular Docking Analysis

Abstract Purpose: To perform network pharmacological analysis so as to identify and screen the active ingredients of Jianpi Yiqi Formula; find its core target and explore its mechanism in the treatment of idiopathic thrombocytopenic purpura (ITP). Materials and Methods: A network pharmacology approach was used to inquire and screen the active ingredients from the Traditional Chinese Medicine System Pharmacology (TCMSP) database for potential active compounds that are commonly contained in the Jianpi Yiqi formula. The Swiss Target Prediction database was used for the prediction of the active ingredient's target of the action; the genecard database was used to search for target genes associated with ITP and to screen for target genes, in which the drug target was intersected with the disease target. Protein interaction network was constructed using string database software for GO and KEGG analysis to construct the "component/target/pathway" pharmacology network of Jianpi Yiqi granules therapy for ITP. Cytoscape 3.7.2 software was harnessed to visualize and integrate this network. The Virtua Drug web-based pharmacology website ( https://www.dockingserver.com ) was used to validate the regulatory relationship between key active compounds and critical pathway molecular signals by molecular docking. Results: Two key active ingredients, quercetin, and kaempferol, were selected from hundreds of herbal ingredients referenced in online pharmacological studies. Molecular docking analysis revealed that quercetin and kaempferol could stably bind PI3K/AKT and exert inhibitory effects, respectively. It was also speculated that PI3K/AKT/mTOR pathway might be the critical pathway for the pharmacokinetic mechanism of Jianpi Yiqi Granules. Conclusion: The present study suggests the multi-component effect characteristic of the treatment of ITP with Jianpi Yiqi granules, thus providing a theoretical basis for the clinical use of Jianpi Yiqi formula.

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