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Background. Gleditsiae Spina, widely used in traditional Chinese medicine, has a good curative effect on malignant tumors such as ovarian cancer, but the mechanism is not clear. So, we aimed to analyze the pharmacological mechanism of Gleditsiae Spina in the treatment of high-grade serous ovarian cancer (HGSC) based on network pharmacology and biological experiments. Methods. The main active ingredients of Gleditsiae Spina were identified by high performance liquid chromatography (HPLC) and mass spectrometry (MS), and the active ingredients were performed by ADME screening. The component targets of Gleditsiae Spina were screened using the PharmMapper platform, and differentially expressed genes in normal and HGSC tissues were identified through the GEO database. Thereafter, the network of “active ingredient-targets” was constructed by cytoscape 3.7.2 software. The protein-protein interaction network was established by the BioGenet database to mine the potential protein function. Biological processes and pathways were analyzed through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis. The binding ability of the core components of the Gleditsiae Spina and the core target of HGSC was verified by molecular docking and molecular dynamics simulation, and the therapeutic effect of Gleditsiae Spina was proved in vitro through cytotoxicity experiments. The effect of Gleditsiae Spina on the core pathway is obtained by western blotting. Results. Gleditsiae Spina had cytotoxicity on HGSC based on network pharmacology and biological experiments. Luteolin, genistein, D-(+)-tryptophan, ursolic acid, and berberine are the identified core active ingredients of Gleditsiae Spina for regulating HGSC, with HPSE, PI3KCA, AKT1, and CTNNB1as the ideal targets. The prediction results were verified by molecular docking, molecular dynamic simulation, cell viability, and western blot analysis. Conclusion. Gleditsiae Spina mainly downregulates the expression of heparanase and β-catenin to affect the composition of tumor cytoplasmic matrix and can regulate the PI3K-AKT pathway, integrating multiple targets and multiple pathways to play a therapeutic role. It also provides a theoretical basis for the prevention of ovarian cancer and its treatment using traditional Chinese medicine in the future.

Objective. To explore the mechanism and principles of traditional Chinese medicine (TCM) in the management of radiation pneumonia. Methods. The targets of radiation pneumonia were obtained by screening the GeneCards, OMIM, TTD, DrugBank, and HERB databases, analyzing ADME parameters. In addition, compounds and Chinese herbs that can act on the targets were screened from the TCMSP database. The core target compounds for TCM were used to construct the target-compound, compound-traditional Chinese medicine, and target-compound-traditional Chinese medicine networks. These networks were further used to select the core targets, compounds, and TCM. The binding strength between the core targets and compounds was determined using AutoDock Vina. The trajectory for the molecular dynamics simulation was completed by Desmond version 2020. Results. A total of 55 active targets in radiation pneumonia were identified. Subsequently, 137 candidate compounds and 469 Chinese herbs were matched. Frequency statistics showed that the Chinese herbs that could interfere with radiation pneumonia were mainly bitter, spicy, and sweet, with both cold and warm properties. Moreover, they mainly belonged to liver and lung channels. The core targets included TNF, IL-6, TGF-β1, and TP53. The most important components were quercetin, resveratrol, and (-)-epigallocatechin-3-gallate. Moreover, the most significant traditional Chinese herbs were Perilla pueraria, ephedra, Lonicerae japonicae, and sea buckthorn. Furthermore, analysis of 222 sets of receptor-ligand docking results suggested that the compounds had good docking activity to their core targets. By combining the docking binding energy, we determined that the chemical compounds had strong binding energy to the targets. Conclusion. Using network pharmacology, we explored the potential mechanism of TCM in the treatment of radiation pneumonia. The general rules for application of TCM in the treatment of radiation pneumonia were summarized. This study provides baseline information for future research on the development of TCM for the management of radiation pneumonia.

Background. Kanglaite injection (KLTi) has shown good clinical efficacy in the treatment of pancreatic ductal adenocarcinoma (PDAC). While previous studies have demonstrated the antitumor effects of the oil compounds in KLTi, it is unclear whether the unsaponifiable matter (USM) also has antitumor effects. This study used network pharmacology, molecular docking, and database verification methods to investigate the molecular biological mechanisms of USM. Methods. Compounds of USM were obtained from GC-MS, and targets from DrugBank. Next, the GEO database was searched for differentially expressed genes in cancerous tissues and healthy tissues of PDAC to identify targets. Subsequently, the protein-protein interaction of USM and PDAC targets was constructed by BisoGenet to extract candidate genes. The candidate genes were enriched using GO and KEGG by Metascape, and the gene-pathway network was constructed to screen the key genes. Molecular docking and molecular dynamic simulations of core compound targets were finally performed and to explore the diagnostic, survival, and prognosis value of targets. Results. A total of 10 active compounds and 36 drug targets were screened for USM, 919 genes associated with PDAC, and 139 USM candidate genes against PDAC were excavated. The enrichment predicted USM by acting on RELA, NFKB1, IKBKG, JUN, MAPK1, TP53, and AKT1. Molecular docking and dynamic simulations confirmed the screened core targets had good affinity and stability with the corresponding compounds. In diagnostic ROC validation, the above targets have certain accuracy for diagnosing PDAC, and the combined diagnosis is more advantageous. As the most diagnostic value of RELA, it is equally significant in predicting disease-specific survival and progression-free interval. Conclusions. USM in KLTi plays an anti-PDAC role by intervening in the cell cycle, inducing apoptosis, and downregulating the NF-κB, MAPK, and PI3K-Akt pathways. It might participate in the pancreatic cancer pathway, and core target groups have diagnostic, survival, and prognosis value biomarker significance.

Background and Aim. Antineoplastic drug-induced cardiotoxicity (ADIC) becomes the second leading cause of death for tumor survivors after tumor recurrence and metastasis, and there may be great room for development in the future of traditional Chinese medicine (TCM). However, the theory of anticardiotoxicity of TCM has not yet formed a system. This study aimed to explore the material basis and the rule of TCM against ADIC based on network pharmacology and data mining. Methods. The targets of antineoplastic drugs with cardiotoxicity were obtained from the National Center for Biotechnology Information (NCBI) database, China national knowledge infrastructure (CNKI) database, and Swiss Target Prediction platform. Then, the cardiotoxicity-related targets were derived from the Gene Cards, Disgenet, OMIM, and DrugBank databases, as well as the drug of current clinical guidelines. The targets both in these two sets were regarded as potential targets to alleviate ADIC. Then, candidate compounds and herbs were matched via Traditional Chinese Medicine Systems Pharmacology (TCMSP) platform. Cytoscape3.7.1 was used to set up the target-compound-herb network. Molecular docking between core targets and compounds was performed with AutodockVina1.1.2. The rules of herbs were summarized by analyzing their property, flavor, and channel tropism. Results. Twenty-one potential targets, 332 candidate compounds, and 400 kinds of herbs were obtained. Five core targets including potassium voltage-gated channel subfamily H member 2 (KCNH2), cyclin-dependent kinase 1 (CDK1), matrix metalloproteinase 2 (MMP2), mitogen-activated protein kinase1 (MAPK1), and tumor protein p53 (TP53) and 29 core compounds (beta-sitosterol, quercetin, kaempferol, etc.) were collected. Five core herbs (Yanhusuo, Gouteng, Huangbai, Lianqiao, and Gancao) were identified. Also, the TCM against ADIC were mainly bitter and acrid in taste, warm in property, and distributed to the liver and lung meridians. Conclusion. TCM against ADIC has great potential. Our study provides a new method and ideas for clinical applications of integrated Chinese and western medicine in treating ADIC.

Aim. The incidence of ulcerative colitis (UC) is increasing steadily in developed countries, it is plaguing nearly 1 million people in the United States and European countries, while developing countries have had a rapidly increased incidence over the past decades. Curcuma is widely used in treating malaria, UC, Crohn’s disease, and colon cancer, which lead to diarrhea and bloody stool. However, the systemic mechanism of curcuma in treating UC is still unclear. Our work was supposed to expound how does curcuma alleviate UC in a comprehensive and systematic way by network pharmacology, molecular docking, and experiment verification. Methods. Traditional Chinese Medicine System Pharmacology Database (TCMSP), Shanghai Chemistry & Chemical Industry Data Platform (SGST), and papers published in Chinese Network Knowledge Infrastructure (CNKI) and PubMed were used to collect the chemical constituents of curcuma based on ADME (absorption, distribution, metabolism, and excretion). And effective targets were predicted by Swiss Target Prediction to establish the curcuma-related database. The disease targets of UC were screened by GeneCards and DrugBank databases, and Wayne (Venn) analysis was carried out with curcuma targets to determine the intersection targets. AutoDock software and TCMNPAS system were used to dock the core chemical components of curcuma with key UC targets. Protein interaction (PPI) network was constructed based on the STRING database and Cytoscape software. Gene function GO analysis and KEGG pathway enrichment analysis were carried out by using Metascape database. Finally, HE staining was performed to identify the inflammatory infiltration and expression difference in TNF-α and STAT3 before and after the treatment of curcuma which was verified by immunoblotting. Results. Twelve active components containing 148 target genes were selected from curcuma. Potential therapeutic targets of curcuma in the treatment of UC were acquired from 54 overlapped targets from UC and curcuma. Molecular docking was used to filter the exact 24 core proteins interacting with compounds whose docking energy is lower than −5.5 and stronger than that of 5-aminosalicylic acid (5-ASA). GO and KEGG analyses showed that these targets were highly correlated with EGFR tyrosine kinase inhibitor resistance, PI3K-Akt signaling pathway, JAK-STAT signaling pathway, MAPK signaling pathway, and inflammatory bowel disease (IBD). Experiments verified curcuma relieved pathological manifestation and decreased the expression of TNF-α and STAT3. Conclusion. Curcuma relieved the colon inflammation of ulcerative colitis via inactivating TNF pathway, inflammatory bowel disease pathway, and epithelial cell signaling in Helicobacter pylori infection pathway, probably by binding to STAT3 and TNF-α.

Although traditional Chinese medicine is effective and safe for the treatment of angiogenesis, the in vivo intervention mechanism is diverse, complex, and largely unknown. Therefore, we aimed to explore the active ingredients of traditional Chinese medicine and their mechanisms of action against angiogenesis. Data on angiogenesis-related targets were collected from GeneCards, Therapeutic Target Database, Online Mendelian Inheritance in Man, DrugBank, and DisGeNET. These were matched to related molecular compounds and ingredients in the traditional Chinese medicine system pharmacology platform. The data were integrated and based on the condition of degree > 1, and relevant literature, target-compound, compound-medicine, and target-compound-medicine networks were constructed using Cytoscape. Molecular docking was used to predict the predominant binding combination of core targets and components. We obtained 79 targets for angiogenesis; 41 targets were matched to 3839 compounds, of which 110 compounds were selected owing to their high correlation with angiogenesis. Fifty-five combinations in the network were obtained by molecular docking, among which PTGS2-astragalin (−9.18 kcal/mol), KDR-astragalin (−7.94 kcal/mol), PTGS2-quercetin (−7.41 kcal/mol), and PTGS2-myricetin (−7.21 kcal/mol) were top. These results indicated that the selected potential core compounds have good binding activity with the core targets. Eighty new combinations were obtained from the network, and the top combinations based on affinity were KDR-beta-carotene (−10.13 kcal/mol), MMP9-beta-sitosterol (−8.04 kcal/mol), MMP9-astragalin (−7.82 kcal/mol), and MMP9-diosgenin (−7.51 kcal/mol). The core targets included PTGS2, KDR, VEGFA, and MMP9. The essential components identified were astragalin, kaempferol, myricetin, quercetin, and β-sitosterol. The crucial Chinese medicines identified included Polygoni Cuspidati Rhizoma et Radix, Morus alba Root Bark, and Forsythiae Fructus. By systematically analysing the ingredients of traditional Chinese medicine and their targets, it is possible to determine their potential mechanisms of action against pathological angiogenesis. Our study provides a basis for further research and the development of new therapeutics for angiogenesis.

This study addresses limitations of mainstream approaches in traditional Chinese medicine (TCM) data mining by developing the SinoMedminer R package and its Shiny web application. The R package's core functionalities include data cleaning, transformation, TCM attribute statistics, association rule exploration and analysis, clustering analysis, co-occurrence network analysis, formula similarity analysis, formula identification, and dosage analysis. This package enables efficient project analyses without requiring complex coding. The accompanying Shiny web application provides an interactive, menu-driven interface for users without programming knowledge. SinoMedminer combines the computational power of a programming language with user-friendly accessibility, significantly enhancing the efficiency and standardization of TCM data mining research. A deployed server platform further simplifies access and usability by allowing direct utilization of the Shiny application. By optimizing data processing and analysis workflows, SinoMedminer enhances big data handling capabilities, accelerates research progress and product development, and promotes the integration of digital technologies into TCM research and clinical practice.

In this study, the role of traditional Chinese medicine (TCM) in relieving epidermal growth factor receptor-tyrosine kinase inhibitor- (EGFR-TKI-) associated diarrhea was discussed by network pharmacology and data mining. Prediction of drug targets by introducing the EGFR-TKI molecular structures into the SwissTargetPrediction platform and diarrhea-related targets in the DrugBank, GeneCards, DisGeNET, and OMIM databases were obtained. Compounds in the drug-disease target intersection were screened by absorption, distribution, metabolism, and excretion parameters and Lipinski’s rule in Traditional Chinese Medicine Systems Pharmacology. TCM-containing compounds were selected, and information on the property, taste, and meridian tropism of these TCMs was summarized and analyzed. A target-compound-TCM network diagram was constructed, and core targets, compounds, and TCMs were selected. The core targets and components were docked by AutoDock Vina (Version 1.1.2) to explore the target combinations of related compounds and evaluate the docking activity of related targets and compounds. Twenty-three potential therapeutic TCM targets for the treatment of EGFR-TKI-related diarrhea were obtained. There were 339 compounds acting on potential therapeutic targets, involving a total of 402 TCMs. The results of molecular docking showed good binding between the core targets and compounds, and the binding between the core targets and compounds was similar to that of the core target and the recommended drug loperamide. TCMs have multitarget characteristics and are present in a variety of compounds used for relieving EGFR-TKI-associated diarrhea. Antitumor activity and the efficacy of alleviating diarrhea are the pharmacological basis of combining TCMs with EGFR-TKI in the treatment of non-small-cell lung cancer. The core targets, compounds, and TCMs can provide data to support experimental and clinical studies on the relief of EGFR-TKI-associated diarrhea in the future.

A peptic ulcer (PU) is a digestive disorder most commonly found in clinical practice. An oriental herbal formula, Xiao Chai Hu Tang (XCHT), has been used to treat PU for an extended period in China. The effectiveness and safety of XCHT in treating peptic ulcers was evaluated using a systematic review of randomized controlled trials (RCTs). Studies were systematically retrieved from CNKI, Embase, Medline, PubMed, SinoMed, VIP, Wanfang, and Web of Science. The following information was extracted from the relevant RCTs: the clinical efficacy rate, recurrence rate, clinical efficacy of traditional Chinese medicine, and the adverse effects. 13 RCTs, including 1334 patients, were included in this review. The meta-analysis showed that treatment with XCHT was superior to conventional pharmacotherapy (CPT) in improving the clinical efficacy rate (RR: 1.20, 95% confidence intervals (CIs): 1.08–1.34, P=0.0007), poor appetite (RR: 0.30, 95% CI: 0.15–0.61, P=0.0009), abdominal distension (RR: 0.61, 95% CI: 0.39–0.96, P=0.03), vomiting (RR: 0.33, 95% CI: 0.19–0.55, P<0.0001), and stomach pain (RR: 0.36, 95% CI: 0.19–0.68, P=0.002) and reducing adverse events (RR: 0.23, 95% CI: 0.07–0.69, P=0.009). XCHT considerably increased the total clinical efficacy rate (RR: 1.22, 95% CI: 1.15–1.30, P<0.00001) as both monotherapy and adjunctive therapy. The recurrence rate (RR = 0.29; 95% CI: 0.16–0.52, P<0.0001) was remarkably decreased in the XCHT plus CPT group. The meta-analysis did not show a significant beneficial effect of XCHT compared with CPT in reducing the recurrence rate (RR = 0.45; 95% CI: 0.07–3.10, P=0.42) and acid reflux (RR: 0.76, 95% CI: 0.47–1.23, P=0.26). Our findings show that XCHT can treat peptic ulcers as part of an alternative medicine approach.

Drugs for the treatment of tumors could result in cardiotoxicity and cardiovascular diseases. We aimed to explore the anticancer properties of Huang yam as well as its cardioprotective properties using network pharmacology and molecular docking technology. The cardiovascular targets of the major chemical components of Huang yam were obtained from the following databases: TCMSP, ETCM, and BATMAN-TCM. The active ingredients of Huang yam were obtained from SwissADME. The cardiovascular targets of antitumor drugs were obtained using GeneCards, OMIM, DrugBank, DisGeNET, and SwissTargetPrediction databases. The drug-disease intersection genes were used to construct a drug-compound-target network using Cytoscape 3.7.1. A protein-protein interaction network was constructed using Cytoscape’s BisoGenet, and the core targets of Huang yam were screened to determine their antitumor properties and identify the cardiovascular targets based on topological parameters. Potential targets were imported into the Metascape platform for GO and KEGG analysis. The results were saved and visualized using R software. The components with higher median values in the network were molecularly docked with the core targets. The network contained 10 compounds, including daucosterol, delusive, dioxin, panthogenin-B, and 124 targets, such as TP53, RPS27A, and UBC. The GO function enrichment analysis showed that there were 478 items in total. KEGG enrichment analysis showed a total of 140 main pathways associated with abnormal transcription of cancer, PI3K-Akt signaling pathway, cell cycle, cancer pathway, ubiquitination-mediated proteolysis, and other pathways. Molecular docking results showed that daucosterol, delusive, dioxin, and panthogenin-B had the highest affinity for TP53, RPS27A, and UBC. The treatment of diseases using traditional Chinese medicine encompasses multiple active ingredients, targets, and pathways. Huang yam has the potential to treat cardiotoxicity caused by antitumor drugs.