Unveiling the therapeutic mechanism of Epimedium Herba on prostate cancer through network pharmacology and experimental validation.

A network pharmacology study on the biological action of ginseng in the treatment of colorectal cancer (CRC) by regulating the tumor microenvironment (TME). To investigate the potential mechanism of action of ginseng in the treatment of CRC by regulating TME. This research employed network pharmacology, molecular docking techniques, and bioinformatics validation. Firstly, the active ingredients and the corresponding targets of ginseng were retrieved using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), the Traditional Chinese Medicine Integrated Database (TCMID), and the Traditional Chinese Medicine Database@Taiwan (TCM Database@Taiwan). Secondly, the targets related to CRC were retrieved using Genecards, Therapeutic Target Database (TTD), and Online Mendelian Inheritance in Man (OMIM). Tertiary, the targets related to TME were derived from screening the GeneCards and National Center for Biotechnology Information (NCBI)-Gene. Then the common targets of ginseng, CRC, and TME were obtained by Venn diagram. Afterward, the Protein-protein interaction (PPI) network was constructed in the STRING 11.5 database, intersecting targets identified by PPI analysis were introduced into Cytoscape 3.8.2 software cytoHubba plugin, and the final determination of core targets was based on degree value. The OmicShare Tools platform was used to analyze the Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of the core targets. Autodock and PyMOL were used for molecular docking verification and visual data analysis of docking results. Finally, we verified the core targets by Gene Expression Profiling Interactive Analysis (GEPIA) and Human Protein Atlas (HPA) databases in bioinformatics. A total of 22 active ingredients and 202 targets were identified to be closely related to the TME of CRC. PPI network mapping identified SRC, STAT3, PIK3R1, HSP90AA1, and AKT1 as possible core targets. Go enrichment analysis showed that it was mainly involved in T cell co-stimulation, lymphocyte co-stimulation, growth hormone response, protein input, and other biological processes; KEGG pathway analysis found 123 related signal pathways, including EGFR tyrosine kinase inhibitor resistance, chemokine signaling pathway, VEGF signaling pathway, ErbB signaling pathway, PD-L1 expression and PD-1 checkpoint pathway in cancer, etc. The molecular docking results showed that the main chemical components of ginseng have a stable binding activity to the core targets. The results of the GEPIA database showed that the mRNA levels of PIK3R1 were significantly lowly expressed and HSP90AA1 was significantly highly expressed in CRC tissues. Analysis of the relationship between core target mRNA levels and the pathological stage of CRC showed that the levels of SRC changed significantly with the pathological stage. The HPA database results showed that the expression levels of SRC were increased in CRC tissues, while the expression of STAT3, PIK3R1, HSP90AA1, and AKT1 were decreased in CRC tissues. Ginseng may act on SRC, STAT3, PIK3R1, HSP90AA1, and AKT1 to regulate T cell costimulation, lymphocyte costimulation, growth hormone response, protein input as a molecular mechanism regulating TME for CRC. It reflects the multi-target and multi-pathway role of ginseng in modulating TME for CRC, which provides new ideas to further reveal its pharmacological basis, mechanism of action and new drug design and development.

This study aimed to investigate the potential mechanism of Mahuang Xixin Fuzi Decoction in treating allergic rhinitis (AR) and predict its quality markers (Q-markers) using network pharmacology and molecular docking techniques.The chemical components of the herbal constituents in Mahuang Xixin Fuzi Decoction were retrieved from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). Active component-related targets were screened using the SwissTargetPrediction database, while AR-related targets were obtained from the GeneCards database. The intersection targets (potential therapeutic targets of the Mahuang Xixin Fuzi Decoction for AR) were identified via the Venn 2.1.0 platform, and a Venn diagram was constructed. A “herb–active component–potential target” network was established using Cytoscape 3.10.0, and core components were screened via topological analysis. Protein–protein interaction (PPI) network of the intersection targets was built using the String database, followed by topological analysis to identify core targets. Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed on the core targets using the DAVID database. Molecular docking of core components and targets was conducted using AutoDock Tools 1.5.7.Twenty-seven active components were identified from TCMSP, with 506 corresponding targets predicted by SwissTargetPrediction. A total of 2,447 AR-related targets were retrieved from GeneCards, yielding 165 intersection targets. Network analysis revealed naringenin, genkwanin, deoxyandrographolide, karakoline, and karanjin as core components. PPI network analysis identified 32 core targets. GO enrichment analysis screened 834 functional items, including 618 biological processes, 72 cellular components, and 144 molecular functions. KEGG analysis identified 165 signaling pathways. Molecular docking confirmed stable binding between core components and key targets.Multiple chemical components in Mahuang Xixin Fuzi Decoction may ameliorate AR by regulating diverse targets and biological processes. Naringenin, genkwanin, and deoxyandrographolide are proposed as potential Q-markers for this decoction in AR treatment.

Objective This study aimed to validate the potential targets of QLD for treating CRC and explore its possible therapeutic mechanism through network pharmacology, molecular docking, and experimental validation. Methods The Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), the Traditional Chinese Medicine Information Database (TCMID), a literature search, and the SwissTargetPrediction database were used to identify the active components and potential targets of QLD. The Online Mendelian Inheritance in Man (OMIM), GeneCards, and DrugBank databases were utilized for CRC target identification. Common targets in CRC and QLD were subsequently screened via a Venn diagram. Next, the Search Tool for the Retrieval of Interacting Genes/Genomes (STRING) database was used to perform protein-protein interaction (PPI) network analysis of the common targets. Gene Ontology (GO) functions and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were employed to identify signaling pathways. After that, “drug-component-target” networks were built via Cytoscape 3.9.1 [2024.3.2]. AutoDock Tools 1.5.7 [2024.4.6] and PyMoL 2.4.0 [2024.4.13] were utilized for molecular docking to analyze the relationships between the active ingredients and core targets. Later, in vitro experiments were performed to validate the anticancer effects of QLD on CRC. Results Network pharmacology analysis revealed 200 active components and 194 potential targets of QLD from the TCMSP database. Disease target databases predicted 1590 targets associated with CRC. The potential anti-colorectal cancer mechanism of QLD may involve lipid and atherosclerosis, chemical carcinogenesis-receptor activation, HIF-1 signaling pathway, TNF signaling pathway, cellular senescence, EGFR tyrosine kinase inhibitor resistance, platinum drug resistance, and the FoxO signaling pathway. Furthermore, QLD has a therapeutic effect through its effects on the 6 core targets TP53, AKT1, TNF, EGFR, IL6 and CASP3. Kaempferol is an active ingredient of QLD and is a flavonoid compound that is known for its antitumor, antioxidant and anti-inflammatory effects. It is unclear how kaempferol affects the onset of CRC. 1 In this study, when the concentration of kaempferol was 2 mg/mL, the proliferative capacity of colorectal cancer cells was inhibited, and kaempferol regulated the AKT/CyclinD1 pathway to inhibit the proliferation of Caco-2 cells. Conclusions Network pharmacology approaches in cancer therapy are highly beneficial. 2 This approach serves as an effective supplementary method for identifying multiple targets of QLD and the underlying mechanisms involved in the fight against CRC. This research reveals the potential role of QLD in the treatment of CRC from a network pharmacology perspective for the first time, enhances the knowledge regarding QLD and offers new insight into QLD research for CRC treatment.

Objective The aim of the study is to explore the molecular mechanism of Yadanzi (Brucea javanica) in the treatment of glioblastoma (GBM) by using the methods of bioinformatics and network pharmacology. Methods The Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and literature retrieval method were applied to obtain the active ingredients of Yadanzi (Brucea javanica), and to predict the relevant targets of the active ingredients. The GBM-related targets were retrieved and screened through the Gene Expression Profiling Interactive Analysis (GEPIA) database, and mapped to each other with the targets of the components of Yadanzi (Brucea javanica) to obtain the intersection targets. The GBM differentially expressed gene targets were imported into the String database to obtain the protein interaction relationship, the Cytoscape software was used to draw the protein interaction network, the Cytobba and MCODE plug-ins were used to screen the core genes and important protein interaction modules, and the GEPIA database was applied to make survival analysis of the core genes. The network map of “active ingredients-targets” was constructed through the Cytoscape 3.6.1 software. Gene Ontology (GO) biological function enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway enrichment analysis for GBM differentially expressed genes were performed through the DAVID database. Results Through TCMSP and literature retrieval, 23 potential active ingredients and 129 related targets were obtained from Yadanzi (Brucea javanica). In the GEPIA database, 247 GBM differentially expressed genes were screened, including 113 up-regulated genes and 134 downregulated genes. After mapping with the targets related to the active ingredients of Yadanzi (Brucea javanica), six intersection targets were obtained, that is, the potential action targets of Yadanzi (Brucea javanica) in treating GBM, including MMP2, HMOX1, BIRC5, EGFR, CCNB2, and TOP2A. Cytoscape software was applied to build an “active ingredient-action target” network. Two active ingredients and five action targets of β-sitosterol (BS) and luteolin were found, and the targets were mainly concentrated in BS. It was found by KEGG pathway enrichment analysis that GBM differentially expressed genes were mainly involved in signaling pathways related to Staphylococcus aureus infection, phagosome formation, tuberculosis and systemic lupus erythematosus and other infectious and autoimmune diseases. It was found by GO enrichment analysis that the GBM differentially expressed genes mainly involved such biological processes (BP) as the processing and presentation of exogenous antigenic peptides and polysaccharide antigens through MHC II molecules, γ-interferon-mediated signaling pathways, extracellular matrix composition, and chemical synapses transmission; it involved cellular components such as cell junctions, axon terminal buttons, extracellular space, vesicle membranes for endocytosis, and MHC II protein complexes; molecular functions such as calcium-mediated ionic protein binding, MHC II molecular receptor activity, immunoglobulin binding, and phospholipase inhibitor activity were also involved. Survival analysis was conducted by GEPIA on the top 37 core targets in degree value, and a total of five genes related to GBM prognosis were obtained. Among them, FN1 and MMP2 were highly expressed while GABRD (γ-aminobutyric acid A receptor delta subunit), RBFOX1, and SLC6A7 were expressed at a low level in cancer patients. Conclusion The pathogenesis of GBM is closely related to the human immune system, and BS and luteolin may be the main material basis of Yadanzi (Brucea javanica) for the treatment of GBM and the improvement of prognosis. The molecular mechanism may be related to the physical barrier formed by destroying the tumor cell stromal molecules and its involvement in tumor immune response.

To elucidate the mechanism of Fuzheng Gankang Pill in treating combined allergic rhinitis and asthma syndrome (CARAS) with lung–spleen qi deficiency and wind–cold invading the lung syndrome using network pharmacology and molecular docking.The active components and targets of the 13 herbs in Fuzheng Gankang Pill were retrieved from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and HERB. A “core herb-active component–target” network was constructed using Cytoscape to screen core components. CARAS disease targets were obtained from Genecards, National Center for Biotechnology Information (NCBI), and Online Mendelian Inheritance in Man (OMIM). Targets related to the clinical phenotypes of CARAS with lung–spleen qi deficiency and wind–cold invading the lung syndrome were retrieved from the Traditional Chinese Medicine Syndrome Ontology and Multidimensional Quantitative Association Calculation Platform. The intersection of CARAS disease targets and syndrome-related targets yielded CARAS disease–syndrome targets. The intersection of Fuzheng Gankang Pill component-related targets and CARAS disease–syndrome targets provided “disease–syndrome–formula” intersection targets. These targets were uploaded to the STRING database for protein–protein interaction (PPI) network analysis, with topological analysis identifying key targets. Metascape was used for Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Molecular docking validation was performed using AutoDock Vina 1.1.2.The 13 core herbs of Fuzheng Gankang Pill contain a total of 200 active ingredients and 289 related targets. There are 2,412 disease targets for CARAS and 735 corresponding disease targets for the main and secondary symptoms of lung–spleen qi deficiency and wind–cold invading the lung. Through the Venn diagram, a total of 35 intersecting targets were obtained for Fuzheng Gankang Pill, CARAS, and the combination of lung–spleen qi deficiency and wind–cold invading the lung syndrome. Quercetin, Polygonatum sibiricum flavonoids, β-sitosterol, baicalein, kaempferol, etc., are core components. PPI network analysis found that tumor necrosis factor (TNF), prostaglandin-endoperoxide synthase 2 (PTGS2), interleukin (IL)-1β, IL-6, transforming growth factor beta 1 (TGFβ1), BCL2, etc., are the core targets for the compound to exert therapeutic effects. GO enrichment analysis showed that the 13 core drugs of Fuzheng Gankang Pill mainly participate in key biological processes such as positive regulation of protein modification, response to hormones, and negative regulation of cell population proliferation through protein kinases in areas such as membrane rafts, membrane microregions, plasma membrane protein complexes, and receptor complexes. KEGG enriched a total of 30 signaling pathways. Molecular docking shows that active ingredients such as quercetin and kaempferol bind stably to TNF (binding energy ≤ −9.0 kcal·mol−1) and PTGS2 (≤ −8.5 kcal·mol−1).Fuzheng Gankang Pill may regulate biological processes such as cell apoptosis, tissue remodeling, inflammatory response, and immune response by acting on core targets such as TNF and PTGS2 through its core components quercetin, baicalein, β-sitosterol, baicalein, and kaempferol, thereby exerting therapeutic effects on CARAS with lung–spleen qi deficiency and wind–cold invading the lung syndrome.

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 < 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.

This study aimed to evaluate the pharmacological mechanism of Hedyotis diffusa Willd against CRC (colorectal cancer) using network pharmacological analysis combined with experimental validation. The active components and potential targets of Hedyotis diffusa Willd were screened from the tax compliance management program public database using network pharmacology. The core anti-CRC targets were screened using a protein-protein interaction (PPI) network. The mRNA and protein expression of core target genes in normal colon and CRC tissues and their relationship with overall CRC survival were evaluated using The Cancer Genome Atlas (TCGA), Human Protein Atlas (HPA), and Gene Expression Profiling Interactive Analysis (GEPIA) databases. Functional and pathway enrichment analyses of the potential targets were performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). The first six core targets with stable binding were molecular-docked with the active components quercetin and β-sitosterol. Finally, the results of network pharmacology were verified using in vitro experiments. In total, 149 potential targets were identified by searching for seven types of active components and the intersection of all potential and CRC targets. PPI network analysis showed that ten target genes, including tumor protein p53 (TP53) and recombinant cyclin D1 (CCND1), were pivotal genes. GO enrichment analysis involved 2043 biological processes, 52 cellular components, and 191 molecular functions. KEGG enrichment analysis indicated that the anticancer effects of H. alba were mediated by tumor necrosis factor, interleukin-17, and nuclear factor-κB (NF-κB) signaling pathways. Validation of key targets showed that the validation results for most core genes were consistent with those in this study. Molecular docking revealed that the ten core target proteins could be well combined with quercetin and β-sitosterol and the structure remained stable after binding. The results of the in vitro experiment showed that β-sitosterol inhibited proliferation and induced apoptosis in SW620 cells. This study identified a potential target plant for CRC through network pharmacology and in vitro validation.

The study aims to elucidate the pharmacological mechanisms of Sophorae Flavescentis Radix (SFR, Kushen) against ovarian cancer (OV) by employing an integrated approach that encompasses network pharmacology, molecular docking, and experimental validation. The effective components and potential targets of SFR were identified through screening the Traditional Chinese Medicine Systems Pharmacology (TSMSP) public database using network pharmacology. Core anti-OV targets were pinpointed using protein-protein interaction (PPI) networks. Datasets from The Cancer Genome Atlas (TCGA), the Human Protein Atlas (HPA), and Gene Expression Profiling Interactive Analysis (GEPIA) were used to investigate the mRNA and protein expressions of critical target genes in both normal and cancerous ovarian tissues, alongside their relationship to overall ovarian survival. Functional and pathway enrichment assessments of putative targets were carried out with Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). The assessment of stable binding effects was conducted through molecular docking with quercetin, luteolin, and formononetin, and validated by anti-OV cell activity. The investigation identified 22 active SFR components yielding 152 potential targets following the intersection with known OV targets. Analysis of PPI network highlighted 13 crucial target genes, including tumor necrosis factor (TNF) and interleukin-1A (IL-1A). GO enrichment analysis covered 703 biological activities, 72 cellular components, and 144 chemical functions. The KEGG enrichment analysis suggested that anti-cancer effects of SFR are mediated by the TNF, interleukin-17 (IL-17), and AGE-RAGE signaling pathways. Molecular docking demonstrated that TNF and IL-1A were stable and strong binding to quercetin, luteolin, and formononetin, indicating that these stable structures significantly inhibited A2780 OV cell viability. This study demonstrated the ability of TNF and IL-1A combined with quercetin, luteolin, and formononetin to decrease the activity of OV cells, suggesting potential therapeutic effect against OV.

The present study aimed to explore the underlying mechanism of Wuling Capsules in the treatment of hepatic fibrosis(HF) through network pharmacology, molecular docking, and animal experiments. Firstly, the chemical components and targets of Wuling Capsules against HF were searched from Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP), Traditional Chinese Medicines Integrated Database(TCMID), GeneCards, and literature retrieval. The protein-protein interaction(PPI) network analysis was carried out on the common targets by STRING database and Cytoscape 3.9.1 software, and the core targets were screened, followed by Gene Ontology(GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analyses. Enrichment analysis was conducted on the core targets and the "drug-core component-target-pathway-disease" network was further constructed. Subsequently, molecular docking between core components and core targets was conducted using AutoDock Vina software to predict the underlying mechanism of action against HF. Finally, an HF model induced by CCl_4 was constructed in rats, and the general signs and liver tissue morphology were observed. HE and Masson staining were used to analyze the liver tissue sections. The effects of Wuling Capsules on the levels of inflammatory factors, hydroxyproline(HYP) levels, and core targets were analyzed by ELISA, RT-PCR, etc. A total of 445 chemical components of Wuling Capsules were screened, corresponding to 3 882 potential targets, intersecting with 1 240 targets of HF, and 47 core targets such as TNF, IL6, INS, and PIK3CA were screened. GO and KEGG enrichment analysis showed that the core targets mainly affected the process of cell stimulation response and metabolic regulation, involving cancer, PI3K-Akt, MAPK, and other signaling pathways. Molecular docking showed that the core components of Wuling Capsules, such as lucidenic acid K, ganoderic acid B, lucidenic acid N, saikosaponin Q2, and neocryptotanshinone, had high affinities with the core targets, such as TNF, IL6 and PIK3CA. Animal experiments showed that Wuling Capsules could reduce fat vacuole, inflammatory infiltration, and collagen deposition in rat liver, decrease the levels of inflammatory cytokines TNF-α, IL-6, and HYP, and downregulated the expressions of PI3K and Akt mRNA. This study suggests that the anti-HF effect of Wuling Capsules may be achieved by regulating the PI3K-Akt signaling pathway, reducing the levels of TNF-α and IL-6 inflammatory factors, and inhibiting the excessive deposition of collagen.

Understanding apoptotic induction by Sargentodoxa cuneata-Patrinia villosa herb pair via PI3K/AKT/mTOR signalling in colorectal cancer cells using network pharmacology and cellular studies

This study aimed to decipher the pharmacodynamic material basis and mechanism of herbal pair Bupleurum scorzonerifolium-Paeonia lactiflora(BS-PL) against liver cancer based on UPLC-Q-TOF-MS and network pharmacology. MTT assay and human hepatocellular carcinoma HepG2 cells were used to screen the effective part of BS-PL, the active components of which were further analyzed and identified by UPLC-Q-TOF-MS. Next, we applied Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP) to screen the active ingredients with OB≥30%. Then TCMSP and SwissTargetPrediction were used to collect and predict component targets, followed by the search of liver cancer-related targets with GeneCards and DisGeNET. The intersection targets were obtained using Venny 2.1.0. Protein-protein interaction(PPI) network was constructed using STRING to uncover the core targets, which were subjected to Gene Ontology(GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) enrichment analysis based on DAVID. Finally, the effects of active ingredients on the expression of main proteins enriched in the key pathways of HepG2 cells were verified by Western blot. The results indicated that compared with 30%, 50%, and 70% ethanol extracts of BS-PL, the n-butanol extraction part(CSYZ) from 95% ethanol extract of BS-PL exhibited the best anti-tumor effect. UPLC-Q-TOF-MS revealed 31 ingredients, 14 of which showed OB≥30%. A total of 220 intersection targets were obtained, from which 35 were selected as the key targets under the condition of two times the median of degree. Among the 215 items with P<0.05 obtained through GO enrichment analysis, 154 were classified into biological processes, 22 into cell components and 39 into molecular functions. KEGG enrichment analysis revealed 95 significantly affected signaling pathways, and the ones(sorted in a descending order by P value) closely related to the anti-liver cancer effect of herbal pair were PI3 K-AKT signaling pathway, TNF signaling pathway, MAPK signaling pathway, HIF-1 signaling pathway, and ErbB signaling pathway. Finally, the PI3 K/AKT signaling pathway involving the largest number of targets was extrapolated, and it was found that this pathway contained 15 core targets and 8 active components. Experimental verification showed that the effective components of BS-PL significantly inhibited the expression of p-PI3 K and p-AKT, consistent with the prediction results of network pharmacology. In conclusion, the main pharmacodynamic substances of BS-PL against liver cancer are 14 components like saikosaponin a, saikosaponin d, and paeoniflorin, which exert the anti-liver cancer effect by regulating PI3 K/AKT pathway.

Naringenin (NR) is a kind of flavonoid which plays a great role in the treatment of autism spectrum disorder (ASD). However, the underlying mechanism of NR in treating ASD still remains unclear. This study used network pharmacology and molecular docking to examine the potential targets and pharmacological mechanism of NR on ASD. Targets related to NR were screened from Traditional Chinese Medicine System Pharmacology Database and Analysis Platform (TCMSP), Encyclopedia of Traditional Chinese Medicine Database (ETCM), Traditional Chinese Medicine Integrated Database (TCMID), PharmaMapper database, and targets related to ASD were screened from Online Mendelian Inheritance In Man (OMIM), Disgenet, GeneCards, Therapeutic Target Database (TTD), Drugbank, and ETCM. Screened of the intersected gene targets. Then, we used the protein-protein interaction (PPI) networks to construct a PPI network and used Network Analyzer plug-in to perform topological analysis to screen out the core target. We used Metascape platform to perform gene ontology (GO) functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and used Chem draw, Pymol, AutoDock 1.5.6 software for molecular docking verification with core targets. A total of 149 targets of NR and 1594 potential targets of ASD were screened, and 43 intersected targets and 8 key targets were obtained and screened. A total of 176 GO items were obtained by GO enrichment analysis (P < .05), 153 entries on biological process (BP), 12 entries on BP and 11entries on cell composition (CC) were included. A total of 100 signaling pathways were obtained by KEGG pathway enrichment screening (P < .05).The pathways that are closely related to the pathogenesis of ASD are estrogen signaling, thyroid hormone signaling pathway, prolactin signaling pathway, and endocrine resistance pathway. Molecular docking results showed that NR had the best docking activity with the core target CASP3, and had good binding ability with AKT1, ESR1, ACTB and MAPK3. Taken together, our findings support that NR exerts therapeutic effects on ASD with multi-target, and multi-pathway characteristics, which provides a preliminary theoretical basis for clinical trials. The mechanism of anti-oxidative stress response, anti-apoptosis, regulation of cell growth and metabolism, anti-inflammatory, balance hormone levels may be important for the therapeutic effect.

Allergic rhinitis(AR) is a chronic inflammatory disorder of nasal mucosa induced by allergen exposure triggering IgE-mediated inflammation. With frequent recurrence, it is difficult to be cured. Zixin Biqiu Granules is developed based on the 60-year clinical experience of CHAO En-xiang, a master of national medicine of China-Japan Friendship Hospital. At present, phase Ⅲ multicenter clinical trial is being prepared, but the mechanism is unclear. Therefore, this study explored the mechanism of Zixin Biqiu Granules against AR based on network pharmacology and molecular docking. First, the chemical components and targets of Zixin Biqiu Granules were retrieved from Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP), and the targets of AR from GeneCards and Online Mendelian Inheritance in Man(OMIM). Then the common targets of the two were screened out and the &quot;Chinese medicine-component-target&quot; network was constructed. Afterward, the common targets were imported into the STRING to obtain the interaction of them, and Cytoscape was employed to establish the protein-protein interaction(PPI) network. Through topological analysis, the core targets were obtained. DAVID was used for Gene Ontology(GO) term enrichment and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment. The &quot;key target-pathway-biological process&quot; network was constructed to explore the anti-AR mechanism of Zixin Biqiu Granules. Finally, the core targets were selected for molecular docking with the key components of Zixin Biqiu Granules to verify the mechanism. The results showed that there were 151 components and 97 targets in the &quot;Chinese medicine-component-target&quot; network. We obtained 20 core targets, 488 biological processes and 147 pathways in topological, GO, and KEGG enrichment analysis of the protein interaction network, and in the comprehensive analysis, it was found that Zixin Biqiu Granules mainly exerted the therapeutic effect through anti-inflammation and immunoregulation. Serine/threonine-protein kinase 1(AKT1) and tumor necrosis factor(TNF) were docked with the key components of Zixin Biqiu Granules, and the results showed that the key components of Zixin Biqiu Granules had high binding affinity to the core targets. This study preliminarily discussed the anti-AR mechanism of Zixin Biqiu Granules, which laid a scientific basis for its clinical application.

BackgroundOral squamous cell carcinoma (OSCC) is one of malignant tumors in oral and maxillofacial region with high fatality. Huanglianjiedu Decoction (HLJDD) is a well-known traditional Chinese medicinal prescription, which consists of Coptis chinensis Franch, Scutellaria baicalensis Georgi, Phellodendron amurense Rupr and Gardenia jasminoides J.Ellis. Some clinical studies showed HLJDD had good effectiveness on OSCC, but the mechanism is unclear.MethodsIn this study, potential components of HLJDD and putative targets were screened by Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). Combining with potential targets of OSCC searched from Therapeutic Target Database (TTD) and Online Mendelian Inheritance in Man (OMIM), we drew protein–protein interaction (PPI) network by Cytoscape v3.2.0 software. After topological analysis we got core targets and further did Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Then we did the in vitro experiments to verify the major biological processes (cell cycle, apoptosis and proliferation) and signaling pathways (mitogen-activated protein kinase (MAPK), nuclear factor-kappa B (NF-κB), protein kinase B (AKT)) on OSCC cell lines, SCC-25 and CAL-27.ResultsThe potential component targets number of Coptis chinensis Franch, Scutellaria baicalensis Georgi, Phellodendron amurense Rupr and Gardenia jasminoides J.Ellis were 39, 93, 81and 88, respectively. Then we got 52 core targets which enriched in cell cycle, apoptosis, proliferation, MAPK activation etc. and obtained TOP30 pathways. On SCC-25 and CAL-27, HLJDD suppressed cell proliferation, induced late apoptosis and inhibited cell invasion and migration which were consistent with the results from network pharmacology analysis. Additionally, in cell cycle, we confirmed HLJDD inhibited G1 phase and arrested in S phase to reduce cell proliferation on SCC-25. In signaling pathways, HLJDD inhibited the phosphorylation of extracellular regulatory protein kinase 1/2 (ERK1/2) and NF-κB p65 (S468) on SCC-25 and CAL-27.ConclusionsHLJDD played a potential therapeutic role on OSCC via inhibiting p-ERK1/2 and p-NF-κB p65 (S468).Graphical abstract

Background: The GCF, created by Professor Liu Shenlin, an esteemed expert in traditional Chinese medicine, is rooted in principles to improve blood flow, relieve blood congestion, clear heat, and detoxify the body. Developed as an empirical formula, it holds significance in CRC treatment. Objective: This study aimed to predict and confirm the active elements, possible targets, and molecular mechanisms against colorectal cancer (CRC) in the GCF enema formula. Methods: Using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), we screened active elements and drug targets. Colorectal cancer (CRC)-related targets were collected from the Online Mendelian Inheritance in Man (OMIM) database, Disease Gene Network (DisGeNET) database, and Therapeutic Target Database (TTD). The overlap between action targets of all active elements and CRC-related targets was determined to find common targets. A Protein-Protein Interaction (PPI) network of common targets was built using the String database, and Cytoscape software was used for visual analysis to identify core targets. Simultaneously, the common targets were analyzed using the Metascape database for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment. Additionally, core targets and active elements were tested using Discovery Studio 2019 for molecular docking. Furthermore, the expression differences and prognostic impacts of core targets were examined across various cancer databases. Results: Screening revealed 90 active elements and 251 drug targets in the GCF. There were 6113 disease targets, with 113 common targets between CRC and the GCF. Core targets identified through PPI analysis included AKT1, STAT3, MYC, SRC, EGFR, and IL6. KEGG enrichment analysis uncovered 101 relevant pathways related to these targets. Molecular docking experiments confirmed favorable interactions between core targets and multiple active elements in the GCF. Additionally, examination of the Human Protein Atlas (HPA) database highlighted differential expression of core targets MYC and EGFR in normal colorectal tissue compared to CRC tissue. Conclusion: The GCF, comprising a combination of three drugs, appears to counteract CRC by influencing core targets, such as AKT1, STAT3, MYC, SRC, EGFR, and IL6. This process involves regulating multiple cancer-related signaling pathways, notably the PI3K-AKT pathway.