Yantiao Formula Intervention in Rats with Sepsis: Network Pharmacology and Experimental Analysis.

<bold>Objective</bold> To further explore the mechanism of Babao Dan (BBD) combined with oxaliplatin (L-OHP) in treating colorectal cancer (CRC) through a network pharmacology analysis. <bold>Methods</bold> The analysis involved the following steps: screen the chemical components of BBD through literature review of Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), Chemistry Database, PubChem, and other databases; obtain L-OHP-related targets through GeneCards database; and search CRC-related targets through OMIM, GeneMap, TTD, DisGeNET, CTD, GeneCards, and other databases. After the intersection and mapping of drugs and disease, the protein-protein interaction (PPI) network and core targets were obtained using STRING database and CytoScape software. MetaScape database was used to analyze the core targets to obtain GO biological processes and KEGG pathways. <bold>Results</bold> BBD contained 495 chemical components with 204 active components screened out through the Swiss ADME database and 770 targets were obtained through the Swiss Target Prediction database. After the intersection of BBD and 775 targets of L-OHP with the CRC targets, it resulted in 74 potential targets. Twenty-four core targets were determined from the 74 intersection targets, which were related to the positive regulation of kinase activity, the positive regulation of cell migration, and peptidyl-serine modification in GO biological process. The KEGG pathway analysis showed that the core targets were related to pathway in cancer, proteoglycan in cancer, endocrine resistance, and microRNA in cancer, TNF signaling pathway, platinum resistance, and other pathways. Molecular docking showed that the core targets could bind to the most examined compounds. <bold>Conclusion</bold> Quercetin-7-olate, cyclo (L-tyrosyl-L-phenylalanyl), panaxadiol, and other compounds in BBD may play an anti-colorectal cancer effect in multiple pathways, including EGFR, AKT1, mTOR, and other targets in synergy with L-OHP.

To explore the mechanism of Shouhui Tongbian Capsules in treating constipation by means of network pharmacology and molecular docking approach. Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP) and Bioinfoematics Analysis Tool for Molecular Mechanism of Traditional Chinese Medicine(BATMAN) were applied to obtain chemical components and potential targets of eight herbs in Shouhui Tongbian Capsules according to the screening principles of oral availability(OB)≥30% and drug-like property(DL)≥0.18. Disease targets relating to constipation were screened out through GeneCards, PharmGkb and other databases, drug targets were integrated with disease targets, and intersection targets were exactly the potential action targets of Shouhui Tongbian Capsules for treating constipation; PPI network of potential targets was constructed using STRING platform, and GO(gene ontology) analysis and KEGG(Kyoto encyclopedia of genes and genomes) pathway data were obtained to conduct enrichment analysis and predict its mechanism of action. Cytoscape 3.6.1 was used to construct a network of &quot;medicinal materials-chemical components-drug targets&quot;, and the network topology analysis was carried out on the PPI network to obtain its main components and key targets. Molecular docking between components and key targets of Shouhui Tongbian Capsules verified the accuracy of network pharmacological analysis results. The PPI network analysis showed 92 chemical components, including quercetin, stigmaste-rol, aloe-emodin, rhein, and key targets for instance AKT1, MAPK1, IL6, JUN, TNF and TP53. The enrichment analysis of KEGG screened out 157 signal pathways(P&lt;0.01), mainly involving interleukin 17 signaling pathway, AGE-RAGE signaling pathway in diabetic complications, thyroid hormone signaling pathway. Quercetin, resveratrol and lysine with top degree value had a rational conformation in docking site of protein crystal complexes. This study preliminarily showed that various active ingredients in Shouhui Tongbian Capsules could regulate multiple signaling pathways, increase intestinal smoothness and peristalsis function, ensure smooth intestinal lumen, and play a role in treating constipation by acting on key targets, such as AKT1, MAPK1, IL6 and JUN.

Purpose Traditional Chinese medicine (TCM) sometimes plays a crucial role in advanced cancer treatment. Despite the significant therapeutic efficacy in hepatocellular carcinoma (HCC) that Actinidia chinensis Planch root extract (acRoots) has proven, its complex composition and underlying mechanism have not been fully elucidated. Therefore, this study analyzed the multiple chemical compounds in acRoots and their targets via network pharmacology and bioinformatics analysis, with the overarching goal of revealing the potential mechanisms of the anti-HCC effect. Methods The main ingredients contained in acRoots were initially screened from the traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), and the candidate bioactive ingredient targets were identified using DrugBank and the UniProt public databases. Second, the biological processes of the targets of active molecules filtered from the ingredients of acRoots were evaluated using gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Third, weighted gene coexpression network analysis (WGCNA) was performed to identify gene coexpression modules associated with HCC. The hub genes of acRoots in HCC were defined via contrasting the above module eigengenes with candidate target genes of acRoots. Furthermore, the target-pathway network was analyzed to explore the mechanism for anti-HCC effect of hub genes. Kaplan–Meier plotter database analysis was performed to validate the hub genes of acRoots correlation with prognostic values in HCC. In order to verify the results of the network pharmacological analysis, we performed a molecular docking approach on the active ingredients and key targets using the Discovery Studio software. The viability of SMMC-7721 and HL-7702 cells was determined by Cell counting kit-8 (CCK-8) after being treated with different concentrations of (+)-catechin (0, 50, 100, 150, 200, and 250 g/ml) for 24, 48, and 72 hours, respectively. Finally, qRT-PCR and Western blot involving human hepatocarcinoma cells were utilized to verify the impact of (+)-catechin on the hub genes associated with prognosis. Results 6 out of 26 active ingredients extracted from TCMSP were deemed as the core ingredients of acRoots. 175 bioactive-ingredient targets of acRoots were obtained and a bioactive-ingredient targets network was established correspondingly. The biological processes (BP) of target genes mainly involved processes, such as toxic substance and wounding. The results of KEGG pathways indicated that the target genes were mainly enriched in pathways in cancer, AGE-RAGE signaling pathway in diabetic complications, IL-17 signaling pathway, and other pathways. Also, the two hub genes (i.e., ESR1 and CAT) were closely associated with the prognosis of HCC patients. As a consequence, we predicated a series of signaling pathways, including estrogen signaling pathway and longevity regulation pathway, through which acRoots could facilitate the treatment for HCC. The molecular docking experiment ascertained that ESR1 and CAT had an effective binding force with (+)-catechin, one of the core ingredients of acRoots. Furthermore, (+)-catechin inhibited SMMC-7721 cell growth in a dose-dependent manner and a time-dependent manner. Finally, we suggest that the expression level of ESR1 and CAT is positively related to the (+)-catechin concentrations in in-vitro experiments. Conclusion The bioactive ingredients of acRoots, including quercetin, (+)-catechin, beta-sitosterol, and aloe-emodin, have synergistic interactions in reinforcing the anticancer effect in HCC. Evidently, acRoots took effect by regulating multitargets and multipathways through its active ingredients. Further, (+)-catechin, the possible paramount anti-HCC active ingredient in acRoots, helped improve the prognosis of HCC patients by increasing the expression of ESR1 and CAT. Additionally, the findings yielded provide a conceptual guidance for the clinical treatment of HCC and the methods adopted are potentially applicable in the future comprehensive analysis of the underlying mechanisms of TCMs.

Astragali Radix (AR) has been widely used in traditional Chinese medicine prescriptions for acute and chronic liver injury. However, little is known about the effects of AR on acetaminophen (APAP)-induced liver injury (ALI). In the current study, a network pharmacology–based approach was applied to characterize the action mechanism of AR on ALI. All compounds of AR were obtained from the corresponding databases, and active compounds were selected according to its oral bioavailability and drug-likeness index. The potential genes of AR were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), and the Bioinformatics Analysis Tool for Molecular Mechanism of Traditional Chinese Medicine (BATMAN-TCM) and PubChem, whereas the potential genes related to ALI were obtained from Online databases (GeneCards and Online Mendelian Inheritance in Man) and Gene Expression Omnibus profiles. The enriched processes, pathways, and target genes of the diseases were analyzed by referring to the Search Tool for the Retrieval of Interacting Genes/Proteins database. A network constructed through Cytoscape software was used to identify the target proteins that connected the compounds in AR with the differential genes of ALI. Subsequently, the potential underlying action mechanisms of AR on ALI predicted by the network pharmacology analyses were experimentally validated in APAP-induced liver injury in mice and HL7702 cells incubated with APAP. The compound-target network included 181 targets, whereas the potential genes related to ALI were 4,621. A total of 49 AR–ALI crossover proteins, corresponding to 49 genes, were filtered into a protein–protein interaction network complex and designated as the potential targets of AR on ALI. Among the genes, the three highest-scoring genes, MYC, MAPK8, and CXCL8 were highly associated with apoptosis in ALI. Then in vitro and in vivo experiments confirmed that AR exhibited its prominent therapeutic effects on ALI mainly via regulating hepatocyte apoptosis related to inhibiting the expressions of MYC (c-Myc), MAPK8 (JNK1), and CXCL8 (IL-8). In conclusion, our study suggested that the combination of network pharmacology prediction with experimental validation might offer a useful tool to characterize the molecular mechanism of AR on ALI.

Introduction: Angong Niuhuang pills (ANPs) exhibit a curative effect in patients with stroke, but its main effective components remain unexplored. Here, we aims to elucidate the molecular mechanisms and active ingredients of ANPs against stroke through network pharmacology, molecular docking, and cellular experiments. Methods: The compounds and targets of each herb in the ANP were retrieved from Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and Bioinformatics Analysis Tool for Molecular Mechanism of Traditional Chinese Medicine (BATMAN-TCM) databases. The genes corresponding to the targets were retrieved from the GeneCards database. A traditional Chinese medicine (TCM) formulae-compound-disease-target network was constructed using Cytoscape. A protein-protein interaction network was constructed using the STRING database. The core targets of ANP were analyzed using gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses using the ClueGO plug-in of Cytoscape. The active ingredients of ANP were docked to the top three core targets. Finally, we explored the effects of coptisine on the oxygen-glucose deprivation/reperfusion (OGD/R) models of PC12 cells. Results: The TCM formulae-compound-disease-target network contained 81 active ingredients and 759 core targets. We identified 47 GO entries of ANP types for stroke, and 55 pathways were screened based on GO and KEGG pathway analyses. Core targets were mainly involved in biological processes (GO enrichment analysis, p &lt; 0.05), including the regulation of heart contraction, muscle contraction, and steroid metabolic processes. In the KEGG pathway, the core targets were mainly involved in AGE-RAGE signaling pathway in diabetic complications, neurotrophin signaling pathway, and cGMP-PKG signaling pathway. Molecular docking results showed that norwogonin, coptisine, and musennin had a high affinity for ubiquitin C (UBC), E1A binding protein P300 (EP300), and cellular tumor antigen p53 (TP53), respectively. Coptisine alleviates OGD/R injury by regulating EP300 and LC3B expression. Conclusion: This study, using network pharmacology, molecular docking analysis, and cellular experiments, provides insights into the potential mechanisms and active ingredients of ANPs in stroke protection. The identification of core target genes and signaling pathways suggests that coptisine could be a promising candidate for treating cerebral ischemia-reperfusion injury.

XiaoLuoWan (XLW) is a classical formula in traditional Chinese medicine (TCM) that has satisfactory therapeutic effects for uterine fibroids (UFs). However, its underlying mechanisms remain unclear. To elucidate the pharmacological actions of XLW in treating UFs, an ingredient–target–disease framework was proposed based on network pharmacology strategies. The active ingredients in XLW and their putative targets were obtained from the TCM systems pharmacology database and analysis platform (TCMSP) and Bioinformatics Analysis Tool for Molecular mechANism of Traditional Chinese Medicine (BATMAN-TCM) platforms. The known therapeutic targets of UFs were acquired from the DigSee and DrugBank databases. Then, the links between putative XLW targets and therapeutic UF targets were identified to establish interaction networks by Cytoscape. Finally, Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses of overlapping gene targets were performed in the STRING database and visualized in R software. In total, 9 active compounds were obtained from 74 ingredients, with 71 curative targets predicted in XLW. Moreover, 321 known therapeutic targets were closely related to UFs, with 29 targets overlapping with XLW and considered interacting genes. Pathway enrichment revealed that the calcium signaling pathway was significantly enriched and the mitogen-activated protein kinase (MAPK) signaling pathway, cAMP signaling pathway, cancer and vascular smooth muscle contraction pathways, cGMP-PKG signaling pathway, and AGE-RAGE signaling pathway were closely associated with XLW intervention for UFs. In conclusion, the network pharmacology detection identified 9 available chemicals as the active ingredients in XLW that may relieve UFs by regulating 29 target genes involved in the calcium signaling pathway, MAPK pathway and cAMP pathway. Network pharmacology analyses may provide more convincing evidence for the investigation of classical TCM prescriptions, such as XLW.

Epimedii herba (EH) showed numerous activities and has the potential to treat periodontitis. However, the pharmacological mechanism has not been exhaustively elucidated. This study predicted the specific targets and mechanisms of EH to prevent and treat periodontitis. A traditional Chinese medicine system pharmacology database and analysis platform was used to screen key compounds of EH and their corresponding targets. Therapeutic Target Database and Comparative Toxicogenomics Database were used to identify targets related to periodontitis. Intersection targets were observed using a Venn diagram. The key components and corresponding protein targets of EH were searched. The intersection targets were obtained and then they were imported into the STRING database to construct a PPI network. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed. Molecular docking between the screened chemical components of EH and key targets was performed using Discovery Studio 2019. The binding stability between components and target proteins was confirmed using molecular dynamics simulations. The binding stability between components and target proteins was confirmed using molecular dynamics simulations. Through network pharmacological analysis, 23 active compounds of EH were identified, including kaempferol and icariin. Based on GeneCards, GEO, and other databases, 3291 periodontitis-related genes were obtained. Venn diagram analysis revealed 137 intersection targets of EH and periodontitis, and Protein kinase B (AKT1) and Tumor necrosis factor (TNF) were identified as the key targets of EH for periodontitis treatment. GO and KEGG analyses revealed that the primary pathways mediating the therapeutic effects of EH were related to cancer, lipid, and atherosclerosis. Molecular docking showed that 8-isopentenyl-kaempferol had the best binding ability to ESR1, which was confirmed by dynamics simulations. This study demonstrated that EH can be used for periodontitis treatment, and the corresponding targets and potential mechanisms were investigated based on network pharmacology, molecular docking, and dynamics simulation analysis. Notably, 8-isopentenyl-kaempferol exhibited good binding affinity and stability to ESR1, which may partially explain the molecular mechanisms of EH for treating periodontitis. Hence, EH can be a novel choice for the clinical treatment of periodontitis in the future.

Network pharmacology and molecular docking analysis on molecular targets and mechanism prediction of Huanglian Jiedu Decoction in the treatment of COVID-19

Aims of this studyThis study aims to investigate the potential of Huangqin Tang (HQT), a traditional Chinese medicine formulation, in the treatment of breast cancer (BC) through a comprehensive approach integrating network pharmacology, molecular docking, and experimental validation.MethodsChemical composition and target information of HQT were collected using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). Disease-related target genes were obtained from the GeneCards database. Network pharmacological analysis, including construction of compound-disease-target networks and protein-protein interaction networks, was performed. Molecular docking simulations were conducted to evaluate the binding affinity between HQT components and key targets. Experimental validation was carried out using cell viability assays, clone formation assays, flow cytometry, Western blotting, and pathway analysis.ResultsA total of 210 candidate targets were identified. Network analysis revealed STAT3, AKT1, MAPK3 etc. as central targets. Enrichment analysis suggested HQT may exert anti-tumor effects through regulating lipid metabolism and inflammation related pathways. Molecular docking showed that the key compounds baicalein, wogonin, kaempferol and quercetin all bound effectively to MAPK1. The binding of baicalein to IL6 and naringenin to TNF-α was also relatively stable. The experimental results demonstrated that HQT effectively inhibited the proliferation of breast cancer cells, with IC50 values of 2.334 mg/mL and 1.749 mg/mL in MCF-7 cells at 24 h and 48 h, and IC50 values of 1.286 mg/mL and 1.496 mg/mL in MDA-MB-231 cells at 24 h and 48 h, respectively. Furthermore, HQT induced cell cycle arrest at the G2/M phase in breast cancer cells and downregulated the expression of related proteins including CDK1, Cyclin B1, CDK2, and Cyclin E. Additionally, HQT promoted apoptosis in breast cancer cells by upregulating the expression of Bak and CC-3, while downregulating the expression of Bcl-2. Notably, HQT also exhibited regulatory effects on the HIF-1 signaling pathway.ConclusionsThis study provides insights into the potential multi-component and multi-target mechanisms of HQT against BC, suggesting it may achieve therapeutic effects through regulating inflammatory response and cancer-related pathways via the identified active compounds and targets. The findings highlight the importance of integrating traditional medicine with modern approaches for the development of novel cancer therapies.

Bushao Tiaozhi Capsule (BSTZC) is a novel drug in China that is used in clinical practice and has significant therapeutic effects on hyperlipidemia (HLP). In our previous study, BSTZC has a good regulatory effect on lipid metabolism of HLP rats. However, its bioactive compounds, potential targets, and underlying mechanism remain largely unclear. We extracted the active ingredients and targets in BSTZC from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and literature mining. Subsequently, core ingredients, potential targets, and signaling pathways were determined through bioinformatics analysis, including constructed Drug-Ingredient-Gene symbols-Disease (D-I-G-D), protein–protein interaction (PPI), the Gene Ontology (GO), and the Kyoto Encyclopedia of Genes and Genomes (KEGG). Finally, the reliability of the core targets was evaluated using in vivo studies. A total of 36 bioactive ingredients and 209 gene targets were identified in BSTZC. The network analysis revealed that quercetin, kaempferol, wogonin, isorhamnetin, baicalein and luteolin may be the core ingredients. The 26 core targets of BSTZC, including IL-6, TNF, VEGFA, and CASP3, were considered potential therapeutic targets. Furthermore, GO and KEGG analyses indicated that the treatment of HLP by BSTZC might be related to lipopolysaccharide, oxidative stress, inflammatory response and cell proliferation, differentiation and apoptosis. The pathway analysis showed enrichment for different pathways like MAPK signaling pathway, AGE-RAGE signaling pathway in diabetic, IL-17 signaling pathway and TNF signaling pathway. In this study, network pharmacology analysis, and experiment verification were combined, and revealed that BSTZC may regulate key inflammatory markers and apoptosis for ameliorating HLP.

Objective: The objective is to study the network pharmacology of Qixiong formula (QXF) and explore the mechanism of QXF in the treatment of oligoasthenospermia. Materials and Methods: Using Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), a Bioinformatics Analysis Tool for Molecular mechANism of Traditional Chinese Medicine (BATMAN-traditional Chinese medicine), and an encyclopaedia of traditional Chinese medicine (ETCM) databases as well as data from relevant studies, the effective components and targets of QXF were obtained. Genes associated with oligospermia were screened using GeneCards, OMIM, DisGeNet, DrugBank, and GAD databases. The intersection target was obtained by mapping the target to the gene, and the protein interaction network was created using the STRING database to screen the core target of QXF in the treatment of oligospermia. The intersection target was enriched using gene ontology (GO) and the Kyoto Encyclopedia of genes and genomes (KEGG) pathway analysis with the DAVID database. The network of the disease drug target pathway was drawn using Cytoscape software. Results: Overall, 536 active components of QXF and 40 core targets for the treatment of oligoasthenozoospermia were obtained. The analysis of GO and KEGG showed that QXF is mainly involved in oxidative stress, cell motility, nutritional response, and other biological processes. Through the regulation of FOXO, p53, PI3K/Akt, MAPK, mammalian target of rapamycin, Foxo, Wnt, and other signaling pathways, QXF played a role in the treatment of oligoasthenospermia. Conclusion: QXF has multi-component, multi-target, and multi-channel characteristics, providing a new way to study the mechanism of QXF in the treatment of oligoasthenospermia.

Mechanism of action of Bu Zhong Yi Qi Decoction in the treatment of chronic fatigue syndrome based on network pharmacology and molecular docking

Background:To explore the mechanism of compound Hongginshen decoction in improving pulmonary fibrosis based on network pharmacology.Methods:The active components and targets of ginseng and Salvia miltiorrhiza were screened from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) database. The chemical components of Rhodiola, Ophiopogon japonicus, and Dendrobium were screened using the Traditional Chinese Medicine Integrated Database (TCMID), and the target compounds were predicted by the Swisstargets method. The related target genes of pulmonary fiber (PF) were screened by the Genecards database and the National Center of Biotechnology Information (NCBI) database. The protein–protein interaction network was drawn using the string database and Cytoscape software, and the network topology was analyzed. Then, using R3.6.3 software, biological processes, molecular function, cell component enrichment, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were carried out on the common targets of drugs and diseases. The network diagram of the “traditional Chinese medicine composition disease target” of Compound Hongginshen Decoction was constructed and analyzed with the software of Cytoscape 3.6.1.Results:We identified 159 active components and 2820 targets in Compound Hongginshen Decoction, and 2680 targets in pulmonary fibrosis. A total of 343 common targets were obtained by the intersection of drug targets and disease targets. protein–protein interaction protein interaction network analysis showed that PIK3CA, PIK3R1, MAPK1, SRC, AKT1, and so on may be the core targets of the compound Hongjingshen recipe in the treatment of pulmonary fibrosis. Gene Ontology (GO) enrichment analysis identified 3463 items, and KEGG pathway enrichment analysis identified 181 related signaling pathways, including the PI3K-Akt signaling pathway, HCMV pathway, Hb pathway, PGs pathway, and KSHV signaling pathway.Conclusion:Compound Hongginshen Decoction has the characteristics of a multichannel and multitargeted effect in the treatment of pulmonary fibrosis. Radix Ophiopogonis and Dendrobium officinale play a key role in the treatment of pulmonary fibrosis. The whole compound prescription may play a therapeutic role by affecting cell metabolism, being anti-inflammatory, regulating the immune system, promoting angiogenesis, and improving anaerobic metabolism.

Baihe Zhimu decoction (BZD) has significant antidepressant properties and is widely used to treat mental diseases. However, the multitarget mechanism of BZD in postpartum depression (PPD) remains to be elucidated. Therefore, the aim of this study was to explore the molecular mechanisms of BDZ in treating PPD using network pharmacology and molecular docking. Active components and their target proteins were screened from the traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). The PPD-related targets were obtained from the OMIM, CTD, and GeneCards databases. After overlap, the targets of BZD against PPD were collected. Protein-protein interaction (PPI) network and core target analyses were conducted using the STRING network platform and Cytoscape software. Moreover, molecular docking methods were used to confirm the high affinity between BZD and targets. Finally, the DAVID online tool was used to perform gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of overlapping targets. The TCMSP database showed that BZD contained 23 active ingredients in PPD. KEGG analysis showed that overlapping genes were mainly enriched in HIF-1, dopaminergic synapses, estrogen, and serotonergic synaptic signalling pathways. Combining the PPI network and KEGG enrichment analysis, we found that ESR1, MAOA, NR3C1, VEGFA, and mTOR were the key targets of PPD. In addition, molecular docking confirmed the high affinity between BZD and the PPD target. Verified by a network pharmacology approach based on data mining and molecular docking methods, the multi-target drug BZD may serve as a promising therapeutic candidate for PPD, but further in vivo/in vitro experiments are needed.

Yindan Xinnaotong soft capsule (YDXNT), a traditional Chinese medicine preparation, has shown a promising effect in the treatment of acute ischemic stroke (AIS). The goal of this study was to investigate the therapeutic effects and pharmacological mechanisms of YDXNT on AIS. Randomized controlled trials were searched and screened. Review Manager 5.4 was used for a meta-analysis. Active ingredients and targets of YDXNT were extracted from the Traditional Chinese Medicine Systems Pharmacology Database, Bioinformatics Analysis Tool for Molecular mechANism of Traditional Chinese Medicine, and Encyclopaedia of Traditional Chinese Medicine. AIS-related targets were retrieved from GeneCards, OMIM, and DrugBank databases. We constructed PPI and ingredient-target networks, performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, and conducted molecular docking. The YDXNT group had a higher total effective rate and a higher Barthel Index score. YDXNT reduced the low-density lipoprotein cholesterol and the whole blood viscosity at high and shear rates. Our study identified 313 ingredients and 1196 common targets. The key ingredients were mainly quercetin, neocryptotanshinone II, miltionone I, neotanshinone C, and tanshiquinone B, and the key targets were mainly SRC, MAPK3, AKT1, MAPK1, and JUN. GO analysis showed that the core targets mainly involved in atherosclerosis and neural apoptosis. The core pathways were lipid and atherosclerosis, PI3K-Akt, MAPK, and other pathways. Key ingredients exhibited robust binding interactions with core targets. YDXNT could effectively improve the total effective rate, ability of daily life, blood lipids, and blood viscosity. Antiatherosclerotic and neuroprotective effects are the main pharmacological mechanisms.Registration number: CRD42023400127.