Exploring the mechanism of Glycyrrhiza glabra and Curcuma domestica against skin photoaging based on network pharmacology

PurposeTo study the efficacy of Ba Zhen Tang in delaying skin photoaging and its potential mechanism based on network pharmacology and molecular docking.MethodsFirst, we screened the active components and targets of Ba Zhen Tang by Traditional Chinese Medicine Database and Analysis Platform (TCMSP) and The Universal Protein Resource (UniProt). The target genes of skin photoaging were obtained from GeneCards and GeneMap database. Then, we analyzed the protein–protein interaction (PPI) by STRING database. The network map was constructed by Cytoscape. Finally, we performed Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis by Metascape database. The molecular docking via Autodock Vina and Pymol. Furthermore, skin photoaging cellular models were established, and the effects of Ba Zhen Tang on ameliorating skin photoaging were investigated.ResultsA total of 160 active ingredients in Ba Zhen Tang and 60 targets of Ba Zhen Tang for delaying skin photoaging were identified. By GO enrichment analysis, 1153 biological process entries, 45 cellular component entries and 89 molecular functional entries were obtained. A total of 155 signal pathways were obtained by KEGG analysis. Ba Zhen Tang is related to MAPK signaling pathway, TNF signaling pathway and AGE-RAGE signaling pathway in diabetic complications, etc., which directly affect the key nodes of photoaging. The molecular docking results showed that there was a certain affinity between the main compounds (kaempferol, quercetin, β-sitosterol, naringenin) and core target genes (PTGS2, CASP3, MAPK1, MAPK3, TP53). Ba Zhen Tang-treated mouse serum inhibited the senescence and p16INK4a expression of human immortalized keratinocyte (HaCaT) cells irradiated by ultraviolet-B (UVB).ConclusionOur study elucidated the potential pharmacological mechanism of Ba Zhen Tang in the treatment of photoaging through multiple targets and pathways. The therapeutic effects of Ba Zhen Tang on skin photoaging were validated in cellular models.

Infertility is a condition characterized by a low fertility rate, which significantly affects the physical and mental health of women of reproductive age. Typically, the treatment duration is prolonged, and the therapeutic outcomes are often unsatisfactory. Professor Cheng-yao He, a renowned expert in traditional Chinese medicine, commonly uses the herb Cnidii Fructus (SCZ) for the treatment of infertility. However, the exact mechanism remains unclear, and there is limited research available on this topic. The active ingredients of SCZ were obtained from the traditional chinese medicine system pharmacology (TCMSP) database and screened for pharmacokinetics (PK), involving absorption, distribution, metabolism, and excretion (ADME). Target prediction was performed by SwissTargetPrediction database, and infertility-related disease targets were searched in GeneCards, TTD, DrugBank, and OMIM database. The protein-protein interaction (PPI) network was constructed using the STRING database (Version 11.5) and analyzed by Cytoscape software (Version 3.9.1). Additionally, the target genes were subjected to biological enrichment analysis in the Metascape database, including gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis, and the "Disease-Ingredient-pathway-target" network was constructed using Cytoscape software. With the assistance of AutoDockVina, Ligplot, and PyMOL software, a validation of Molecular docking results and a visualization of the results were performed. This study identified 11 retained active ingredients of SCZ, 447 drug targets, 233 of which were related to infertility, and 5393 disease targets. GO enrichment analysis mainly involved 221 biological processes such as cellular response to chemical stress and gland development. KEGG enrichment analysis mainly involved 68 pathways such as thyroid hormone signaling pathway, estrogen signaling pathway, FOXO signaling pathway, and PI3K/Akt signaling pathway. Molecular docking showed that the core active ingredients of SCZ, including Ammidin, Diosmetin, Xanthoxylin N, and Prangenidin, had strong binding abilities with core targets such as MDM2, MTOR, CCND1, EGFR, and AKT1. This study preliminarily demonstrated that SCZ may act on the PI3K/Akt signaling pathway, exerting its therapeutic effects on infertility by improving energy metabolism disorders and endometrial receptivity, inducing primordial follicle activation, regulating oocyte proliferation, differentiation, and apoptosis, and promoting the release of dominant follicles.

Background Ankylosing spondylitis (AS) is a rheumatism that mainly affects the axial bones and joints. Xinfeng capsule (XFC) is a preparation with a remarkable clinical effect that is used in our hospital. And it has definite curative effect and less side effects in the treatment of AS. Objective Data mining and network pharmacology were used to analyze the efficacy of Chinese medicine Xinfeng capsule on treating the hypercoagulable state of ankylosing spondylitis and the underlying mechanism behind it. Methods Clinical data were collected and compiled from the Department of Rheumatology and Immunology of the First Affiliated Hospital of Anhui University of Chinese Medicine. Cluster analysis was used to investigate herbs that frequently used to treat AS, Apriori module was used to analyze the association rules between herbs and laboratory indexes, and the random walk model was used to reveal the therapeutic efficacy of XFC against AS. The TCMSP database was used to acquire the active components and targets of XFC, and the GeneCards and OMIM database were used to obtain the targets of AS. Afterward, an active ingredient-target network was established and core targets were screened for; overlapping targets were screened for the protein-protein interaction (PPI) network analysis, the Gene Ontology (GO) enrichment analysis, and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Molecular docking was adopted to investigate the interactions between main active components and core targets. Results Frequently used herbs could be divided into three groups, and according to the analysis of Apriori module, there is a strong correlation between XFC and the improvement of ESR and hs-CRP, and the results of the random walk model demonstrated that the effect of XFC on improving PLT, ESR, and hs-CRP was superior to the use of traditional Chinese medicine alone. In total, 103 active compounds of XFC and 59 overlapping targets were obtained. The PPI relationships were obtained through the STRING database, and 13 core targets were identified. 1786 GO enrichment results and 205 KEGG enrichment results were obtained, including NF-kappa B signaling pathway, TNF signaling pathway, and IL17 signaling pathway. The outcomes of molecular docking revealed a close relationship between the active compounds of XFC and core targets. Conclusion This study demonstrated that XFC can effectively improve the hypercoagulable state and the inflammatory indices of AS patients through data mining, and it has a strong correlation with the clinical improvement of inflammation. The active compounds of formononetin, triptolide, quercetin, and kaempferol may be the key active components of XFC in regulating AS, possibly through inhibiting the activation of NF-kappa B signaling pathway to improve hypercoagulable state.

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Exploring the pharmacological components and effective mechanism of Mori Folium against periodontitis using network pharmacology and molecular docking

Background Hyssopus cuspidatus Boriss. (Shen Xiang Cao (SXC)), a traditional medicine herb in Xinjiang, has a long history of being used by minorities to treat asthma. However, its active antiasthmatic compounds and underlying mechanism of action are still unknown. The aim of this study was to investigate the bioactive compounds and explore the molecular mechanism of SCX in the treatment of asthma using network pharmacology. Methods The compounds of SCX were collected by a literature search, and Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and SwissTargetPrediction were used to predict targets and screen active compounds. Moreover, asthma-related targets were obtained based on DisGeNET, Herb, and GeneCards databases, and a protein-protein interaction (PPI) network was built by the STRING database. Furthermore, the topological analysis of the PPI and SXC-compound-target networks were analyzed and established by Cytoscape software. Finally, the RStudio software package was used for carrying out Gene Ontology (GO) function enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. AutoDock tools and AutoDock Vina were used to molecularly dock the active compounds and key targets. Results A total of 8 active compounds and 258 potential targets related to SXC were predicted, and PPI network screened out key targets, including IL-6, JUN, TNF, IL10, and CXCL8. GO enrichment analysis involved cell responses to reactive oxygen species, oxidative stress, chemical stress, etc. In addition, KEGG pathway analysis showed that SXC effectively treated asthma through regulation of mitogen-activated protein kinases (MAPK) signaling pathways, interleukin 17 (IL-17) signaling pathways, toll-like receptor (TLR) signaling pathways, and tumor necrosis factor (TNF) signaling pathways. Conclusion The preliminary study that was based on multiple compounds, multiple targets, and multiple pathways provides a scientific basis for further elucidating the molecules involved and the underlying antiasthma-related mechanisms of SXC.

Previous studies have shown that asthma is a risk factor for lung cancer, while the mechanisms involved remain unclear. We attempted to further explore the association between asthma and non-small cell lung cancer (NSCLC) via bioinformatics analysis. We obtained GSE143303 and GSE18842 from the GEO database. Lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) groups were downloaded from the TCGA database. Based on the results of differentially expressed genes (DEGs) between asthma and NSCLC, we determined common DEGs by constructing a Venn diagram. Enrichment analysis was used to explore the common pathways of asthma and NSCLC. A protein-protein interaction (PPI) network was constructed to screen hub genes. KM survival analysis was performed to screen prognostic genes in the LUAD and LUSC groups. A Cox model was constructed based on hub genes and validated internally and externally. Tumor Immune Estimation Resource (TIMER) was used to evaluate the association of prognostic gene models with the tumor microenvironment (TME) and immune cell infiltration. Nomogram model was constructed by combining prognostic genes and clinical features. 114 common DEGs were obtained based on asthma and NSCLC data, and enrichment analysis showed that significant enrichment pathways mainly focused on inflammatory pathways. Screening of 5 hub genes as a key prognostic gene model for asthma progression to LUAD, and internal and external validation led to consistent conclusions. In addition, the risk score of the 5 hub genes could be used as a tool to assess the TME and immune cell infiltration. The nomogram model constructed by combining the 5 hub genes with clinical features was accurate for LUAD. Five-hub genes enrich our understanding of the potential mechanisms by which asthma contributes to the increased risk of lung cancer.

Objective Nephrotic syndrome (NS) is a common glomerular disease caused by a variety of causes and is the second most common kidney disease. Guizhi is the key drug of Wulingsan in the treatment of NS. However, the action mechanism remains unclear. In this study, network pharmacology and molecular docking were used to explore the underlying molecular mechanism of Guizhi in treating NS. Methods The active components and targets of Guizhi were screened by the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), Hitpick, SEA, and Swiss Target Prediction database. The targets related to NS were obtained from the DisGeNET, GeneCards, and OMIM database, and the intersected targets were obtained by Venny2.1.0. Then, active component-target network was constructed using Cytoscape software. And the protein-protein interaction (PPI) network was drawn through the String database and Cytoscape software. Next, Gene Ontology (GO) and pathway enrichment analyses of Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed by DAVID database. And overall network was constructed through Cytoscape. Finally, molecular docking was conducted using Autodock Vina. Results According to the screening criteria, a total of 8 active compounds and 317 potential targets of Guizhi were chosen. Through the online database, 2125 NS-related targets were identified, and 93 overlapping targets were obtained. In active component-target network, beta-sitosterol, sitosterol, cinnamaldehyde, and peroxyergosterol were the important active components. In PPI network, VEGFA, MAPK3, SRC, PTGS2, and MAPK8 were the core targets. GO and KEGG analyses showed that the main pathways of Guizhi in treating NS involved VEGF, Toll-like receptor, and MAPK signaling pathway. In molecular docking, the active compounds of Guizhi had good affinity with the core targets. Conclusions In this study, we preliminarily predicted the main active components, targets, and signaling pathways of Guizhi to treat NS, which could provide new ideas for further research on the protective mechanism and clinical application of Guizhi against NS.

Exploring the molecular mechanism of Lycium barbarum L. against breast cancer based on network pharmacology

Integrating network pharmacology and pharmacological evaluation to reveal the therapeutic effects and potential mechanism of S-allylmercapto-N-acetylcysteine on acute respiratory distress syndrome.

To analyze the effects and mechanisms of berberine in the treatment of aging-related cognitive dysfunction based on network pharmacology methods, molecular docking techniques, and animal experiments. A mouse model of cognitive dysfunction was constructed by subcutaneous injection of D-galactose (D-gal) for 10 weeks, and the neuroprotective effects of berberine on aging-related cognitive dysfunction mice were evaluated by the Morris water maze (MWM) and immunofluorescence staining. The targets of berberine were obtained by SwissTargetPrediction, GeneCards, and PharmMapper. Putative targets of cognitive dysfunction were obtained by GeneCards, TTD, and DrugBank database. The STRING database and Cytoscape software were applied for protein-protein interaction (PPI) analysis and further screening of core targets. The DAVID database was used for Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene ontology (GO) enrichment analysis to clarify the biological processes and pathways involved in the intersection targets, and AutoDockTools was adopted for molecular docking verification of core targets. Finally, the core genes were validated using real-time quantitative PCR. The MWM results showed that treatment with berberine significantly improved spatial learning and memory in mice with cognitive decline induced by D-gal. Immunofluorescence staining indicated that berberine modified the levels of aging-related markers in the brain. A total of 386 berberine putative targets associated with cognitive dysfunction were identified based on the public database. The core targets of berberine for improving cognitive function, include Mapk1, Src, Ctnnb1, Akt1, Pik3ca, Tp53, Jun, and Hsp90aa1. GO enrichment and KEGG pathway enrichment analyses indicated that the mechanism of berberine in the treatment of aging-related cognitive dysfunction is attributed to pathways such as PI3K-AKT and MAPK pathways. In vivo experiments further confirmed that Akt1, Ctnnb1, Tp53, and Jun were involved in the neuroprotective actions of berberine. This study reveals the multi-target and multi-pathway effects of berberine on regulating aging-related cognitive dysfunction, which provides preclinical evidence and may promote new drug development in mitigating cognitive dysfunction.

Integrating network pharmacology and pharmacological evaluation to explore the protective mechanism of Ershiwuwei Zhenzhu pill in ischemic stroke

This study aimed to explore the mechanism of Fuzi Lizhong Tang (FZLZT) in treating gastric cancer using network pharmacology and molecular docking, and to validate the results through in vitro experiments. Active ingredients and target genes of FZLZT were obtained from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database, while disease targets of gastric cancer were collected from GeneCards, OMIM, and DrugBank databases. The "herb-active ingredient-target gene" network was constructed using Cytoscape software, and core active ingredients were obtained through topological analysis. Protein-protein interaction analysis was performed using the STRING database, and core targets were obtained through topological analysis. Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway enrichment analysis were performed using the DAVID database. Molecular docking was conducted using AutoDock Vina software to verify the interaction between core ingredients and core targets. Cholecystokinin octapeptide (CCK-8) assay was used to determine the proliferation inhibition effect of FZLZT on AGS, BGC823, HGC-27, MGC-803, and SGC-7901 gastric cancer cell lines, and ANNEXIN V-FITC/PI double staining combined with flow cytometry was used to measure the cell apoptosis rate. Network pharmacology analysis revealed 117 active ingredients and 261 target genes of FZLZT, and 211 overlapping targets with gastric cancer. Ten core active ingredients were identified through topological analysis, including quercetin, 7-methoxy-2-methyl isoflavone, kaempferol, luteolin, naringenin, isorhamnetin, quercetagetin, glycyrrhizic acid A, β-sitosterol, and medioresinol. GO and KEGG enrichment analysis showed that the mechanism of FZLZT in treating gastric cancer mainly involves cancer, inflammation, metabolism, and blood rheology-related pathways, and may act through 7 core targets (CDKN1A, MYC, MAPK1, MAPK14, RB1, RELA, and STAT3). Molecular docking results further confirmed the prediction of network pharmacology. In vitro experiments showed that FZLZT inhibited the proliferation of all five gastric cancer cell lines, with the strongest effect on SGC-7901 cells, and induced apoptosis in SGC-7901 cells. FZLZT has a multi-component, multi-target, and multi-pathway characteristic in treating gastric cancer. Its active ingredients may regulate the expression of proteins such as CDKN1A, MYC, MAPK1, MAPK14, RB1, RELA, and STAT3 to activate cancer-related signaling pathways to achieve its therapeutic effect.

JiaWeiSiWu granule (JWSWG) has been applied clinically for more than a decade, and the preliminary results show that blood pressure can be reduced while protecting the target organ at the same time. The purpose of this research is to study the pharmacological mechanism of JWSWG in treating hypertension using network pharmacology. The chief active components, relevant targets, and the target genes of JWSWG were retrieved by the databases TCMSP and UniProt. The GeneCards database was used to obtain target genes of hypertension. Then, the target genes of hypertension and active components were intersected to discover the potential targets by which JWSWG acts on hypertension. Cytoscape software was employed to construct the "medicine-compound-target-disease" network. The STRING database was used to construct the protein-protein interaction network in order to screen the key target genes. Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were analyzed by RGUI and org.Hs.eg.db. By intersecting 102 compound target genes with 6,732 target genes of hypertension, 88 action target genes were obtained, thereby screening out the key compounds and key targets. The results of GO enrichment showed the main molecular functions, biological processes, and cellular components. The main pathways of JWSWG in treating hypertension were revealed by KEGG pathway enrichment. This research clarified the mechanism of JWSWG in the treatment of hypertension systematically, providing new potential ideas and a theoretical foundation for further experimental and clinical research.

Poria cocos (PC) is a traditional Chinese herbal medicine that plays an important role in the treatment of allergic rhinitis (AR); however, its specific mechanism of action has rarely been reported. This study was based on network pharmacology and molecular docking to explore the molecular mechanisms of PC in the treatment of AR. TCMSP, GeneCards, DrugBank, TTD, and OMIM databases were used to screen potential targets of Poria cocos for AR treatment. The STRING platform and Cytoscape 3.7.0 software (Cytoscape Consortium, San Diego) were used to construct a protein–protein interaction (PPI) network and screen core targets. Gene ontology (GO) functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted on potential target genes. Finally, molecular docking was conducted between the key active components and the core targets to validate their relevance. Fifteen active components of PC were identified and 94 common targets related to both PC and AR were screened. The top ten hub genes identified were TNF, IL1B, AKT1, prostaglandin G/H synthase 2 (PTGS2), epidermal growth factor receptor (EGFR), MMP9, PPARG, BCL2, NR3C1, and PTGS1. GO and KEGG enrichment analyses indicated that these core targets were involved in various biological processes, including the regulation of inflammatory responses, responses to exogenous stimuli, and modulation of defense responses. These targets influence AR through pathways such as the neuroactive ligand-receptor interaction pathway and PI3K-Akt signaling pathway. Molecular docking results indicated that pachymic acid-PTGS2, polyporenic acid C-EGFR, and PTGS2 exhibited strong binding activity, while pachymic acid, polyporenic acid C-TNF and cerevisterol-AKT1 demonstrated good binding activity. Our study found that the key active components of PC for treating AR are pachymic acid, polyporenic acid C, and cerevisterol. PTGS2, EGFR, TNF, and AKT1 are the key targets, while the neuroactive ligand-receptor interaction pathway and PI3K-Akt signaling pathway are the key pathways. These results indicate that PC may intervene in the intrinsic molecular mechanism of AR through multiple targets and pathways. Although further experimental verification is required, our study provides a theoretical basis for the clinical application of PC in AR treatment and subsequent related research.