Network pharmacology and experimental verification to explore the effect of Hedyotis diffusa on Alzheimer's disease.

This study aimed to explore the active components and the effect of Hedyotis diffusa (HD) against Alzheimer's disease (AD) via network pharmacology, molecular docking, and experimental evaluations. We conducted a comprehensive screening process using the TCMSP, Swiss Target Prediction, and PharmMapper databases to identify the active components and their related targets in HD. In addition, we collected potential therapeutic targets of AD from the Gene Cards, Drugbank, and OMIM databases. Afterward, we utilized Cytoscape to establish both protein-protein interaction (PPI) networks and compound-target (C-T) networks. To gain further insights into the functional aspect, we performed GO and KEGG pathway analyses using the David database. Next, we employed Autodock vina to estimate the binding force between the components and the hub genes. To validate our network pharmacology findings, we conducted relevant experiments on Caenorhabditis elegans, further confirming the reliability of our results. Then a total of six active compounds and 149 therapeutic targets were detected. Through the analysis of the association between active compounds, therapeutic targets, and signaling pathways, it was observed that the therapeutic effect of HD primarily encompassed the inhibition of Aß, suppression of AChE activity, and mitigating oxidative stress. Additionally, our investigation revealed that the key active compounds in HD primarily consisted of iridoids, which exhibited resistance against AD by acting on the Alzheimer's disease pathway and the AGE-RAGE signaling pathway in diabetic complications.

On the mechanism of wogonin against acute monocytic leukemia using network pharmacology and experimental validation.

Wogonin is a natural flavone compound from the plant Scutellaria baicalensis, which has a variety of pharmacological activities such as anti-cancer, anti-virus, anti-inflammatory, and immune regulation. However, the potential mechanism of wogonin remains unknown. This study was to confirm the molecular mechanism of wogonin for acute monocytic leukemia treatment, known as AML-M5. The potential action targets between wogonin and acute monocytic leukemia were predicted from databases. The compound-target-pathway network and protein-protein interaction network (PPI) were constructed. The enrichment analysis of related targets and molecular docking were performed. The network pharmacological results of wogonin for AML-M5 treatment were verified using the THP-1 cell line. 71 target genes of wogonin associated with AML-M5 were found. The key genes TP53, SRC, AKT1, RELA, HSP90AA1, JUN, PIK3R1, and CCND1 were preliminarily found to be the potential central targets of wogonin for AML-M5 treatment. The PPI network analysis, GO analysis and KEGG pathway enrichment analysis demonstrated that the PI3K/AKT signaling pathway was the significant pathway in the wogonin for AML-M5 treatment. The antiproliferative effects of wogonin on THP-1 cells of AML-M5 presented a dose-dependent and time-dependent manner, inducing apoptosis, blocking the cell cycle at the G2/M phase, decreasing the expressions of CCND1, CDK2, and CyclinA2 mRNA, as well as AKT and p-AKT proteins. The mechanisms of wogonin on AML-M5 treatment may be associated with inhibiting cell proliferation and regulating the cell cycle via the PI3K/AKT signaling pathway.

Exploring the mechanism of Jinlida granules against type 2 diabetes mellitus by an integrative pharmacology strategy.

Jinlida granule (JLD) is a Traditional Chinese Medicine (TCM) formula used for the treatment of type 2 diabetes mellitus (T2DM). However, the mechanism of JLD treatment for T2DM is not fully revealed. In this study, we explored the mechanism of JLD against T2DM by an integrative pharmacology strategy. Active components and corresponding targets were retrieved from Traditional Chinese Medicine System Pharmacology (TCMSP), SwissADME and Bioinformatics Analysis Tool for Molecular Mechanisms of Traditional Chinese Medicine Database (BATMAN-TCM) database. T2DM-related targets were obtained from Drugbank and Genecards databases. The protein-protein interaction (PPI) network was constructed and analyzed with STRING (Search Toll for the Retrieval of Interacting Genes/proteins) and Cytoscape to get the key targets. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Gene and Genomes (KEGG) enrichment analyses were performed with the Database for Annotation, Visualization and Integrated Discovery (DAVID). Lastly, the binding capacities and reliability between potential active components and the targets were verified with molecular docking and molecular dynamics simulation. In total, 185 active components and 337 targets of JLD were obtained. 317 targets overlapped with T2DM-related targets. RAC-alpha serine/threonine-protein kinase (AKT1), tumor necrosis factor (TNF), interleukin-6 (IL-6), cellular tumor antigen p53 (TP53), prostaglandin G/H synthase 2 (PTGS2), Caspase-3 (CASP3) and signal transducer and activator of transcription 3 (STAT3) were identified as seven key targets by the topological analysis of the PPI network. GO and KEGG enrichment analyses showed that the effects were primarily associated with gene expression, signal transduction, apoptosis and inflammation. The pathways were mainly enriched in PI3K-AKT signaling pathway and AGE-RAGE signaling pathway in diabetic complications. Molecular docking and molecular dynamics simulation verified the good binding affinity between the key components and targets. The predicted results may provide a theoretical basis for drug screening of JLD and a new insight for the therapeutic effect of JLD on T2DM.

Ultrahigh-performance liquid chromatography Q-Exactive-Orbitrap mass spectrometry and molecular network analysis alongside network pharmacology to elucidate the active constituents and mechanism of action of Huahong tablet in treating pelvic inflammatory disease.

RATIONALE: Huahong tablet, a commonly used clinical Chinese patent medicine, shows good efficacy in treating pelvic inflammation and other gynaecological infectious diseases. However, the specific composition of Huahong tablets, which are complex herbal formulations, remains unclear. Therefore, this study aims to identify the active compounds and targets of Huahong tablets and investigate their mechanism of action in pelvic inflammatory diseases. METHODS: We utilised ultrahigh-performance liquid chromatography Q-Exactive-Orbitrap mass spectrometry and the relevant literature to identify the chemical components of Huahong tablets. The GNPS database was employed to further analyse and speculate on the components. Potential molecular targets of the active ingredients were predicted using the SwissTargetPrediction website. Protein-protein interaction analysis was conducted using the STRING database, with visualisation in Cytoscape 3.9.1. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the DAVID database. Additionally, a traditional Chinese medicine-ingredient-target-pathway network was constructed using Cytoscape 3.10.1. Molecular docking validation was carried out to investigate the interaction between core target and specific active ingredient. RESULTS: A total of 66 chemical components were identified, and 41 compounds were selected as potential active components based on the literature and the TCMSP database. Moreover, 38 core targets were identified as key targets in the treatment of pelvic inflammatory diseases with Huahong tablets. GO and KEGG enrichment analysis revealed 986 different biological functions and 167 signalling pathways. CONCLUSION: The active ingredients in Huahong tablets exert therapeutic effects on pelvic inflammatory diseases by acting on multiple targets and utilising different pathways. Molecular docking confirmed the high affinity between the specific active ingredients and disease targets.

Network-based approach for drug repurposing against mpox.

The current outbreak of mpox presents a significant threat to the global community. However, the lack of mpox-specific drugs necessitates the identification of additional candidates for clinical trials. In this study, a network medicine framework was used to investigate poxviruses-human interactions to identify potential drugs effective against the mpox virus (MPXV). The results indicated that poxviruses preferentially target hubs on the human interactome, and that these virally-targeted proteins (VTPs) tend to aggregate together within specific modules. Comorbidity analysis revealed that mpox is closely related to immune system diseases. Based on predicted drug-target interactions, 268 drugs were identified using the network proximity approach, among which 23 drugs displaying the least side-effects and significant proximity to MPXV were selected as the final candidates. Lastly, specific drugs were explored based on VTPs, differentially expressed proteins, and intermediate nodes, corresponding to different categories. These findings provide novel insights that can contribute to a deeper understanding of the pathogenesis of MPXV and development of ready-to-use treatment strategies based on drug repurposing.

Identification of Genes Hub Associated with Triple-Negative Breast Cancer and Cannabidiol Analogs Potential Inhibitory Agents: An In-silico Study.

OBJECTIVE: Triple-negative breast cancer presents a significant challenge in oncology due to its complex treatment and aggressive nature. This subtype lacks common cancer cell receptors like estrogen, progesterone, and human epidermal growth factor receptor 2 receptors. This study aimed to identify, through bioinformatic analysis, the key genes associated with triple-negative breast cancer. In addition, CBD analogs with potential inhibitory effects on these genes were evaluated through docking and molecular dynamics. METHODS: Gene expression profiles from the GSE178748 dataset were analyzed, focusing on MDA-MB-231 breast cancer cell lines. Differentially expressed genes were determined through protein-protein interaction networks and subsequently validated. Additionally, the inhibitory effects of cannabidiol analogs on these hub genes were assessed using molecular docking and dynamics. RESULTS:  Analysis of the hub highlighted RPL7A, NHP2L1, and PSMD11 as significant players in TNBC regulation. Ligand 44409296 showed the best affinity energy with RPL7A, while 166505341 exhibited the highest affinity with NHP2L1 and PSMD11, surpassing CBD. Analyses of RMSD, RMSF, SASA, and Gyration Radius indicated structural stability and interactions of the proteins with ligands over time. MMGBSA calculations showed favorable binding energies for the ligands with the target proteins. CONCLUSION: In conclusion, this study identified key genes, namely RPL7A, NHP2L1, and PSMD11, associated with triple-negative breast cancer and demonstrated promising interactions with cannabidiol analogs, particularly 44409296 and 166505341. These findings suggest potential therapeutic targets and highlight the relevance of further clinical investigations. Additionally, the ligands exhibited favorable ADME properties and low toxicity, underscoring their potential in future drug development for TNBC treatment.

Elucidating the molecular mechanisms of pterostilbene against cervical cancer through an integrated bioinformatics and network pharmacology approach.

Pterostilbene (PTE), a natural phenolic compound, has exhibited promising anticancer properties in the preclinical treatment of cervical cancer (CC). This study aims to comprehensively investigate the potential targets and mechanisms underlying PTE's anticancer effects in CC, thereby providing a theoretical foundation for its future clinical application and development. To accomplish this, we employed a range of methodologies, including network pharmacology, bioinformatics, and computer simulation, with specific techniques such as WGCNA, PPI network construction, ROC curve analysis, KM survival analysis, GO functional enrichment, KEGG pathway enrichment, molecular docking, MDS, and single-gene GSEA. Utilizing eight drug target prediction databases, we have identified a total of 532 potential targets for PTE. By combining CC-related genes from the GeneCards disease database with significant genes derived from WGCNA analysis of the GSE63514 dataset, we obtained 7915 unique CC-related genes. By analyzing the intersection of the 7915 CC-related genes and the 2810 genes that impact overall survival time in CC, we identified 690 genes as crucial for CC. Through the use of a Venn diagram, we discovered 36 overlapping targets shared by PTE and CC. We have constructed a PPI network and identified 9 core candidate targets. ROC and KM curve analyses subsequently revealed IL1B, EGFR, IL1A, JUN, MYC, MMP1, MMP3, and ANXA5 as the key targets modulated by PTE in CC. GO and KEGG pathway enrichment analyses indicated significant enrichment of these key targets, primarily in the MAPK and IL-17 signaling pathways. Molecular docking analysis verified the effective binding of PTE to all nine key targets. MDS results showed that the protein-ligand complex between MMP1 and PTE was the most stable among the nine targets. Additionally, GSEA enrichment analysis suggested a potential link between elevated MMP1 expression and the activation of the IL-17 signaling pathway. In conclusion, our study has identified key targets and uncovered the molecular mechanism behind PTE's anticancer activity in CC, establishing a firm theoretical basis for further exploration of PTE's pharmacological effects in CC therapy.

Efficacy of Glycyrrhetinic Acid in the Treatment of Acne Vulgaris Based on Network Pharmacology and Experimental Validation.

Glycyrrhetinic acid (GA) is a saponin compound, isolated from licorice (Glycyrrhiza glabra), which has been wildly explored for its intriguing pharmacological and medicinal effects. GA is a triterpenoid glycoside displaying an array of pharmacological and biological activities, including anti-inflammatory, anti-bacterial, antiviral and antioxidative properties. In this study, we investigated the underlying mechanisms of GA on acne vulgaris through network pharmacology and proteomics. After the intersection of the 154 drug targets and 581 disease targets, 37 therapeutic targets for GA against acne were obtained. A protein-protein interaction (PPI) network analysis highlighted TNF, IL1B, IL6, ESR1, PPARG, NFKB1, STAT3 and TLR4 as key targets of GA against acne, which is further verified by molecular docking. The experimental results showed that GA inhibited lipid synthesis in vitro and in vivo, improved the histopathological damage of skin, prevented mast cell infiltration and decreased the level of pro-inflammatory cytokines, including TNF-α, IL-1ß and IL-6. This study indicates that GA may regulate multiple pathways to improve acne symptoms, and the beneficial effects of GA against acne vulgaris might be through the regulation of sebogenesis and inflammatory responses.

Exploring the pathways of drug repurposing and Panax ginseng treatment mechanisms in chronic heart failure: a disease module analysis perspective.

Chronic Heart Failure (CHF) is a significant global public health issue, with high mortality and morbidity rates and associated costs. Disease modules, which are collections of disease-related genes, offer an effective approach to understanding diseases from a biological network perspective. We employed the multi-Steiner tree algorithm within the NeDRex platform to extract CHF disease modules, and subsequently utilized the Trustrank algorithm to rank potential drugs for repurposing. The constructed disease module was then used to investigate the mechanism by which Panax ginseng ameliorates CHF. The active constituents of Panax ginseng were identified through a comprehensive review of the TCMSP database and relevant literature. The Swiss target prediction database was utilized to determine the action targets of these components. These targets were then cross-referenced with the CHF disease module in the STRING database to establish protein-protein interaction (PPI) relationships. Potential action pathways were uncovered through Gene Ontology (GO) and KEGG pathway enrichment analyses on the DAVID platform. Molecular docking, the determination of the interaction of biological macromolecules with their ligands, and visualization were conducted using Autodock Vina, PLIP, and PyMOL, respectively. The findings suggest that drugs such as dasatinib and mitoxantrone, which have low docking scores with key disease proteins and are reported in the literature as effective against CHF, could be promising. Key components of Panax ginseng, including ginsenoside rh4 and ginsenoside rg5, may exert their effects by targeting key proteins such as AKT1, TNF, NFKB1, among others, thereby influencing the PI3K-Akt and calcium signaling pathways. In conclusion, drugs like dasatinib and midostaurin may be suitable for CHF treatment, and Panax ginseng could potentially mitigate the progression of CHF through a multi-component-multi-target-multi-pathway approach. Disease module analysis emerges as an effective strategy for exploring drug repurposing and the mechanisms of traditional Chinese medicine in disease treatment.

Network pharmacology and transcriptomics analysis reveal the mechanism of BushenHuoxue formula attenuates premature ovarian failure via modulation PI3K/AKT pathway.

This study aims to analyze the active components and mechanism of Bushen Huoxue (BSHX) formula on the autoimmune premature ovarian insufficiency (POI) by combining network pharmacology and Transcriptomics. The active components and targets of BSHXF were screened through Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). POI-related targets were identified through Therapeutic Targets Database (TTD), DisGeNET and drugbank database. The Veen diagram was performed to obtain the action targets. The active compound-target network and Protein-Protein Interaction (PPI) network were built by using STRING database and Cytoscape software. Key targets and active compounds were further identified by topological analysis. Molecular docking shows that Kaempferol, Isorhamnetin and Anhydroicaritin have strong binding to AKT. Finally, a zp3-induced autoimmune ovarian function deficiency mouse model was used to explore the potential mechanism of POI. The potential pathways of BSHXF for the treatment of POI were identified by Transcriptomic analysis. PI3K-AKT and NF-kb pathways were the common pathways between network pharmacology and transcriptomics. Our results revealed that BSHXF could reduce the FSH expression levels and raise the E2, and AMH levels in the serum. Western bloting demonstrates that BSHXF could upregulate the expression of p-PI3K and p-AKT.

Study on the mechanism of Huangqi Guizhi Wuwu Decoction in treating diabetes peripheral neuropathy based on network pharmacology and molecular docking.

This study aimed to explore the effective substances and mechanism network of Huangqi Guizhi Wuwu Decoction in treating diabetes peripheral neuropathy. Based on the TCM systemic pharmacological analysis platform (TCMP) and UniProt database, the database of active Huqarqu Decoction was constructed, and the related targets of diabetic peripheral neuropathy were collected through the OMIM, CTD, DisGeNET, TTD and GeneCards databases. The intersection targets were obtained to construct the network diagram of Huangqi dis Guizhi Wuwu Decoction-Active Through the String database, the interaction between target proteins was analyzed, and molecular docking between active components and potential targets was carried out. Combined with the DAVID v6.8 database, GO function analysis and KEGG pathway analysis were performed on the targets. Guizhi Wuwu Decoction mainly acts on core targets such as IL6, MAPK3, VE GFA, JUN and ESR1 through quercetin, kaempferol and naringin and regulates the TNF signaling pathway, estrogen signaling pathway and MAPK signaling pathway, thus achieving the effect of treating diabetes peripheral neuropathy. Huangqi Guizhi Wu has multiple targets and regulates multiple signaling pathways in neuropathy, which lays a foundation for future pharmacological research.

Network pharmacology and molecular docking technology for exploring the effect and mechanism of high-dose vitamin c on ferroptosis of tumor cells: A review.

To investigate the mechanism by which high-dose vitamin C (HVC) promotes ferroptosis in tumor cells via network pharmacology, vitamin C-related and ferroptosis-related targets were obtained from the PharmMapper and GeneCards databases, respectively, and their common targets were compared using the Venn diagram. Common targets were imported into the STRING database for protein-protein interaction analysis, and core targets were defined. Core targets were enriched for Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways using the R language packages. A map of the core target-based interaction network and a map of the mechanism by which HVC regulates ferroptosis were constructed. A total of 238 vitamin C-related and 721 ferroptosis-related targets were identified, of which 21 targets were common to both. Furthermore, ALDOA, AHCY, LDHB, HSPA8, LGALS3, and GSTP1 were identified as core targets. GO enrichment analysis suggested that the main biological processes included the extrinsic apoptotic signaling pathway and pyruvate metabolic process. KEGG enrichment analysis suggested that HVC regulates ferroptosis mainly through the amino acid and carbohydrate metabolic pathways. The targets were validated by molecular docking. In conclusion, HVC may promote ferroptosis in tumor cells by regulating metabolic pathways, and there is a synergistic effect between HVC and type I ferroptosis inducers. Glycolysis-dependent tumors may be beneficial for HVC therapy. Our study provides a reference for further clinical studies on HVC antitumor therapy.

Identification of potential anti-tumor targets and mechanisms of HuaChanSu injection using network pharmacology and cytological experiments in Breast cancer.

HuaChanSu (HCS) or Cinobufacini injection is an aqueous extract of the dried skin of Bufo bufo gargarigans, and has anti-tumor effects. The aim of this study was to evaluate the possible therapeutic effect of HCS against breast cancer (BRCA) using cytology, network pharmacology, and molecular biology approaches. The half-inhibitory concentration (IC50) of HCS in the BRCA cells was determined by cytotoxicity assay, and were accordingly treated with high and low doses HCS in the TUNEL and scratch assays. The potential targets of HCS in the BRCA cells were identified through functional enrichment analysis and protein-protein interaction (PPI) networks, and verified by molecular docking. The expression levels of key signaling pathways-related proteins in HCS-treated BRCA cells by western blotting. HCS inhibited the proliferation and migration of MCF-7 and MDA-MB-231 cells, and induced apoptosis in a dose-dependent manner. Furthermore, we screened 289 core HCS targets against BRCA, which were primarily enriched in the PI3K-AKT, MAPK chemokines, and other. signaling pathways. In addition, PIK3CA, PIK3CD, and MTOR were confirmed as HCS targets by molecular docking. Consistent with this, we observed a reduction in the expression levels of phosphorylated PI3K, AKT, and MTOR in the HCS-treated BRCA cells. Taken together, our findings suggest that HCS inhibits the growth of BRCA cells by targeting the PI3K-AKT pathway, and warrants further investigation as a therapeutic agent for treating patients with BRCA.

Mechanistic insights into targeting caspase-3 activation and alveolar macrophage pyroptosis by Ephedra and bitter almond compounds for treating pediatric pneumonia via network pharmacology and bioinformatics.

This study investigates the molecular mechanism of Ma Huang-Ku Xing Ren, a traditional Chinese medicine formula, in treating pediatric pneumonia. The focus is on the regulation of caspase-3 activation and reduction of alveolar macrophage necrosis through network pharmacology and bioinformatics analyses of Ephedra and bitter almond components. Active compounds and targets from ephedrine and bitter almond were obtained using TCMSP, TCMID, and GeneCards databases, identifying pediatric pneumonia-related genes. A protein-protein interaction (PPI) network was constructed, and core targets were screened. GO and KEGG pathway enrichment analyses identified relevant genes and pathways. An acute pneumonia mouse model was created using the lipopolysaccharide (LPS) inhalation method, with caspase-3 overexpression induced by a lentivirus. The mice were treated with Ephedra and bitter almond through gastric lavage. Lung tissue damage, inflammatory markers (IL-18 and IL-1ß), and cell death-related gene activation were assessed through H&E staining, ELISA, western blot, flow cytometry, and immunofluorescence. The study identified 128 active compounds and 121 gene targets from Ephedra and bitter almond. The PPI network revealed 13 core proteins, and pathway analysis indicated involvement in inflammation, apoptosis, and cell necrosis, particularly the caspase-3 pathway. In vivo results showed that Ephedra and bitter almond treatment significantly mitigated LPS-induced lung injury in mice, reducing lung injury scores and inflammatory marker levels. It also decreased caspase-3 activity and cell death in alveolar macrophages. In conclusion, the active ingredients of Ma Huang-Ku Xing Ren, particularly targeting caspase-3, may effectively treat pediatric pneumonia by reducing apoptosis in alveolar macrophages, as demonstrated by both network pharmacology, bioinformatics analyses, and experimental data.

Multi-level bioinformatics resources support drug target discovery of protein-protein interactions.

Drug discovery often begins with a new target. Protein-protein interactions (PPIs) are crucial to multitudinous cellular processes and offer a promising avenue for drug-target discovery. PPIs are characterized by multi-level complexity: at the protein level, interaction networks can be used to identify potential targets, whereas at the residue level, the details of the interactions of individual PPIs can be used to examine a target's druggability. Much great progress has been made in target discovery through multi-level PPI-related computational approaches, but these resources have not been fully discussed. Here, we systematically survey bioinformatics tools for identifying and assessing potential drug targets, examining their characteristics, limitations and applications. This work will aid the integration of the broader protein-to-network context with the analysis of detailed binding mechanisms to support the discovery of drug targets.

Exploring the mechanism of Corbrin capsules in the intervention of AKI-COVID-19 based on network pharmacology combined with GEO dataset.

AIM: of the study: This study used network pharmacology and the Gene Expression Omnibus (GEO) database to investigate the therapeutic effects of Corbrin capsules on acute kidney injury (AKI)-COVID-19 (coronavirus disease 2019). MATERIALS AND METHODS: The active constituents and specific molecular targets of Corbrin capsules were obtained from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) and Swiss Target Prediction databases. The targets related to AKI and COVID-19 disease were obtained from the Online Mendelian Inheritance in Man (OMIM), GeneCards, and GEO databases. A protein-protein interaction (PPI) network was constructed by utilizing Cytoscape. To enhance the analysis of pathways associated with the pathogenesis of AKI-COVID-19, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed. Furthermore, immune infiltration analysis was performed by using single-sample gene set enrichment analysis (ssGSEA) and CIBERSORT. Molecular docking was used to assess interactions between differentially expressed genes and active ingredients. Verification was performed by utilizing GEO databases and in vivo assays. RESULTS: This study revealed an overlap of 18 significantly differentially expressed genes between the Corbrin capsules group and the AKI-COVID-19 target group. Analysis of the PPI network identified TP53, JAK2, PIK3CA, PTGS2, KEAP1, and MCL1 as the top six core protein targets with the highest degrees. The results obtained from GO and KEGG analyses demonstrated that the target genes were primarily enriched in the apoptosis and JAK-STAT signaling pathways. Moreover, the analysis of immune infiltration revealed a notable disparity in the percentage of quiescent memory CD4 + T cells. Western blot analyses provided compelling evidence suggesting that the dysregulation of 6 core protein targets could be effectively reversed by Corbrin capsules. CONCLUSION: This study revealed the key components, targets, and pathways involved in treating AKI-related COVID-19 using Corbrin capsules. This study also provided a new understanding of the molecular mechanisms underlying this treatment.

In silico and network pharmacology analysis of fucosterol: a potent anticancer bioactive compound against HCC.

The Fucaceae family of marine brown algae includes Ascophyllum nodosum. Fucosterol (FSL) is a unique bioactive component that was identified through GC-MS analysis of the hydroalcoholic extract of A. nodosum. Fucosterol's mechanism of action towards hepatocellular cancer was clarified using network pharmacology and docking study techniques. The probable target gene of FSL has been predicted using the TargetNet and SwissTargetPred databases. GeneCards and the DisGNet database were used to check the targeted genes of FSL. By using the web programme Venny 2.1, the overlaps of FSL and HCC disease demonstrated that 18 genes (1.3%) were obtained as targeted genes Via the STRING database, a protein-protein interaction (PPI) network with 18 common target genes was constructed. With the aid of CytoNCA, hub genes were screened using the Cytoscape software, and the targets' hub genes were exported into the ShinyGo online tool for study of KEGG and gene ontology enrichment. Using the software AutoDock, a hub gene molecular docking study was performed. Ten genes, including AR, CYP19A1, ESR1, ESR2, TNF, PPARA, PPARG, HMGCR, SRC, and IGF1R, were obtained. The 10 targeted hubs docked with FSL successfully. The active components FSL of ASD, the FSL, are engaged in fatty liver disease, cancer pathways, and other signalling pathways, which could prove beneficial for the management of HCC.

Network Pharmacology Prediction and Molecular Docking-Based Strategy to Explore the Potential Mechanism of Gualou Xiebai Banxia Decoction against Myocardial Infarction.

The aim of this study was to investigate targets through which Gualou Xiebai Banxia decoction aids in treating myocardial infarction (MI) using network pharmacology in combination with molecular docking. The principal active ingredients of Gualou Xiebai Banxia decoction were identified from the TCMSP database using the criteria of drug-likeness ≥30% and oral bioavailability ≥0.18. Interactions and pathway enrichment were investigated using protein-protein interaction (PPI) networks and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, respectively. Active component structures were docked with those of potential protein targets using AutoDock molecular docking relative softwares. HIF1A was of particular interest as it was identified by the PPI network, GO and KEGG pathway enrichment analyses. In conclusion, the use of network pharmacology prediction and molecular docking assessments provides further information on the active components and mechanisms of action Gualou Xiebai Banxia decoction.

Elucidating the mechanism of action of Isobavachalcone induced autophagy and apoptosis in non-small cell lung cancer by network pharmacology and experimental validation methods.

BACKGROUND: Lung cancer is the leading cause of cancer deaths, and non-small cell lung cancer (NSCLC) accounts for the majority of lung cancer-related mortality. In recent years, there have been numerous treatments for non-small cell lung cancer, but the cure and survival rates are still extremely low. Isobavachalcone (IBC) belongs to the chalcone component of the traditional Chinese medicine Psoralea corylifolia L., and is a unique Protein kinase B (AKT) pathway inhibitor with significant anticancer effects. Previous studies have shown that IBC possess a variety of biological properties, including anti-cancer, anti-inflammatory, and antioxidant properties. This study focused on the use of network pharmacology analysis, molecular docking technology and experimental validation to elucidate the potential mechanisms of IBC for the treatment of NSCLC. METHODS: Screening key genes and pathways of IBC action in NSCLC using network pharmacology. The IBC target genes were from The Encyclopedia of Traditional Chinese Medicine (ETCM) and BATMAN-TCM databases, the NSCLC target genes were from GeneCards, Online Mendelian Inheritance in Man (OMIM) and The Therapeutic Target database (TTD) databases, both of which were taken as intersecting genes for protein-protein interaction network analysis and enrichment analysis, and the binding energies of the compounds to the core targets were further verified by molecular docking. Cell lines in vitro experiments were then performed to further unravel the mechanism of IBC for NSCLC. RESULTS: A total of 279 potential targets were retrieved by searching the intersection of IBC and NSCLC targets. Protein-protein interaction (PPI) network analysis indicated that 6 targets, including AKT1, RXRA, NCOA1, RXRB, RARA, PPARG were hub genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis suggested that IBC treatment of NSCLC mainly involves steroid binding, transcription factor activity, Pathways in cancer, cAMP signaling pathway, Adenosine 5'-monophosphate (AMP)-activated protein kinase (AMPK) signaling pathway. Among them, the AMPK signaling pathway, which contained the largest number of enriched genes, may play a greater role in the treatment of NSCLC. Then, the results of in vitro experiment indicated that IBC could inhibit proliferation of NSCLC cells and induce cell autophagy and apoptosis. The results also showed that IBC could increase the protein expression of AMPK and decrease the protein expression of AKT and mammalian target of rapamycin (mTOR), suggesting that IBC can treat NSCLC by inducing cellular autophagy and apoptosis as well as modulating AMPK and AKT signaling pathways. CONCLUSIONS: In summary, this study provided a new insight into the protective mechanism of IBC against NSCLC through network pharmacology and experimental validation.

Proximity interactome analysis of Lassa polymerase reveals eRF3a/GSPT1 as a druggable target for host-directed antivirals.

Completion of the Lassa virus (LASV) life cycle critically depends on the activities of the virally encoded, RNA-dependent RNA polymerase in replication and transcription of the viral RNA genome in the cytoplasm of infected cells. The contribution of cellular proteins to these processes remains unclear. Here, we applied proximity proteomics to define the interactome of LASV polymerase in cells under conditions that recreate LASV RNA synthesis. We engineered a LASV polymerase-biotin ligase (TurboID) fusion protein that retained polymerase activity and successfully biotinylated the proximal proteome, which allowed the identification of 42 high-confidence LASV polymerase interactors. We subsequently performed a small interfering RNA (siRNA) screen to identify those interactors that have functional roles in authentic LASV infection. As proof of principle, we characterized eukaryotic peptide chain release factor subunit 3a (eRF3a/GSPT1), which we found to be a proviral factor that physically associates with LASV polymerase. Targeted degradation of GSPT1 by a small-molecule drug candidate, CC-90009, resulted in strong inhibition of LASV infection in cultured cells. Our work demonstrates the feasibility of using proximity proteomics to illuminate and characterize yet-to-be-defined host-pathogen interactome, which can reveal new biology and uncover novel targets for the development of antivirals against highly pathogenic RNA viruses.