Search Results (77)

Background and Aim: The immunological interactions between soil-transmitted helminths (STHs) and herpes simplex virus type 2 (HSV-2), particularly in the context of co-infection, are poorly understood. Next-generation sequencing (NGS) offers a powerful approach to explore these complex immune responses and uncover potential therapeutic targets. This study leveraged NGS and bioinformatic tools to investigate transcriptional changes and immunological pathways in female genital tract (FGT) tissues of BALB/c mice acutely infected with Nippostrongylus brasiliensis (Nb), HSV-2, or co-infected. Methods: Total RNA was harvested from FGT tissues of BALB/c mice infected with Nb, HSV-2, co-infected with both pathogens, and uninfected controls. Differentially expressed genes (DEGs) were identified by comparing uninfected versus infected FGT tissues in R using edgeR and limma packages. Immune-related genes were identified by intersecting DEGs in each group-wise comparison with immune function gene sets derived from the Mouse Genome Informatics (MGI) database. Functional and pathway enrichment analyses were performed with g: Profiler and protein–protein interaction networks were built using the STRING database and visualized with Cytoscape. Key hub genes and significant gene modules were identified using the Cytoscape plugins CytoHubba and MCODE, followed by further functional analysis of these modules. Results: NGS analysis revealed distinct gene expression profiles in response to single infection with Nb or HSV-2, with both showing significant differences when uninfected controls were compared to infected FGT tissues at a 5% false discovery rate. Notably, there were no significant differences in gene expression profiles between uninfected and co-infected FGT tissues. In the comparison of uninfected versus Nb-infected FGT tissues, 368 DEGs were identified, with 356 genes upregulated and 12 downregulated. Several immune-related genes, such as Ptprc, Ccl11, Ccr2, and Cx3cr1, were significantly altered. Pathway analysis of DEGs, hub genes, and significant modules indicated modulation of immune and defense responses. Notably, Nb infection induced a robust Th2-dominant immune response in the FGT, with downregulation of pro-inflammatory genes. This likely reflects helminth-driven modulation that may impair protective Th1 responses and highlights the systemic impact of Nb on the FGT immunity. In the comparison of uninfected versus HSV-2-infected FGT tissues, 140 DEGs were identified, with 121 upregulated and 19 downregulated. Immune-related genes, including Ldlr, Camk1d, Lrp8 and Epg5, were notably altered. HSV-2 infection led to early and predominant downregulation of immune genes, consistent with viral immune evasion strategies. In addition, functional analysis revealed enrichment in cell cycle and sterol biosynthesis pathways, suggesting that HSV-2 modulates host metabolism to support viral replication while influencing immune responses. In co-infection, no significant transcriptional changes were observed, potentially reflecting immune antagonism where Nb-induced Th2 responses may suppress HSV-2-driven Th1 immune responses. Conclusions: This preliminary study offers insights into the gene expression responses in the FGT to acute single and co-infection with Nb and HSV-2. Together, these findings reveal distinct transcriptomic changes in the FGT following Nb and HSV-2 infection, with co-infection potentially leading to immune antagonism and transcriptional equilibrium. This highlights the complex interplay between helminth- and virus-induced immune modulation in shaping FGT immunity. By leveraging NGS, this study highlights important immune-related pathways and serves as a foundation for further investigations into the mechanistic roles of DEGs in immunity to these pathogens, with potential implications for developing novel therapeutic strategies. Full article

This study explores how aristolochic acid I (AAI) drives hepatocellular carcinoma (HCC). We first employ network toxicology and machine learning to map the key molecular target genes. Next, our research utilizes molecular docking to evaluate how AAI binds to these targets, and finally confirms the stability and dynamics of the resulting complexes through molecular dynamics simulations. We identified 193 overlapping target genes between AAI and HCC through databases such as PubChem, OMIM, and ChEMBL. Machine learning algorithms (SVM-RFE, random forest, and LASSO regression) were employed to screen 11 core genes. LASSO serves as a rapid dimension-reduction tool, SVM-RFE recursively eliminates the features with the smallest weights, and Random Forest achieves ensemble learning through decision trees. Protein–protein interaction networks were constructed using Cytoscape 3.9.1, and key genes were validated through GO and KEGG enrichment analyses, an immune infiltration analysis, a drug sensitivity analysis, and a survival analysis. Molecular-docking experiments showed that AAI binds to each of the core targets with a binding affinity stronger than −5 kcal mol⁻¹, and subsequent molecular dynamics simulations verified that these complexes remain stable over time. This study determined the potential molecular mechanisms underlying AAI-induced HCC and identified key genes (CYP1A2, ESR1, and AURKA) as potential therapeutic targets, providing valuable insights for developing targeted strategies to mitigate the health risks associated with AAI exposure. Full article

Background: Dendritic cells (DCs) play an important role as a bridge between innate and adaptive immunity, and changes in gene expression of DCs during the immune response to Mycobacterium tuberculosis (M.tb) may affect the development of tuberculosis. Methods: Using systems biology methods, mRNA and miRNA expression profile data of DCs infected with M.tb were obtained. A total of 1398 differentially expressed mRNAs and 79 differentially expressed miRNAs were identified, and a corresponding miRNA–mRNA regulatory network was constructed using Cytoscape 3.9.1 software. The functional annotations and pathway classifications of the miRNA–mRNA network were identified using the DAVID tool. Then, the key pathway modules in the miRNA–mRNA network were screened and subjected to PPI network analysis to identify hub nodes. Subsequently the miRNA/mRNA axis was determined, validated by qRT-PCR, and evaluated through ROC curve analysis. Results: The TNF signaling pathway and the Tuberculosis pathway were key pathway modules, with miR-34a-3p/TNF and miR-190a-3p/IL1B being the greatest correlations with the two pathway modules. qRT-PCR results showed that IL1B and miR-190a-3p exhibited significant differences in both the H37Ra and BCG infection groups. The AUC of two factors (IL1B and miR-190a-3p) was 0.9561 and 0.9625, respectively, showing high sensitivity and specificity. Conclusions: Consequently, miR-190a-3p/IL1B might be a good candidate marker to characterize the immune response of DCs to M.tb and a transition signal from innate to adaptive immunity. Full article

Objective: This study aims to elucidate the potential mechanisms by which Fespixon cream promotes diabetic foot ulcer (DFU) healing using network pharmacology, molecular docking, and RT-qPCR validation in clinical tissue samples. Methods: Active components of Fespixon cream were screened from the Traditional Chinese Medicine Systems Pharmacology Database (TCMSP) and relevant literature, and their corresponding targets were standardized using the Universal Protein Resource (UniProt) database. Diabetic foot ulcer (DFU)-related targets were retrieved and filtered from the GeneCards database and the Online Mendelian Inheritance in Man (OMIM) database. The intersection of drug and disease targets was identified, and a protein–protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. The interaction network was visualized using Cytoscape version 3.7.2 software. The potential mechanisms of the shared targets were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis using R software packages, and results were visualized through Bioinformatics online tools. Molecular docking was performed to validate the binding between key active compounds of Fespixon cream and core DFU targets using AutoDock Vina version 1.1.2 and PyMOL software. Furthermore, RT-qPCR analysis was performed on wound edge tissue samples from DFU patients treated with Fespixon cream to experimentally verify the mRNA expression levels of predicted hub genes. Results: Network pharmacology analysis identified eight active compounds in Fespixon cream, along with 153 potential therapeutic targets related to diabetic foot ulcer (DFU). Among these, 21 were determined as core targets, with the top five ranked by degree value being RAC-αserine/threonine-protein kinase (AKT1), Cellular tumor antigen p53 (TP53), Tumor necrosis factor (TNF), Interleukin-6 (IL6), and Mitogen-activated protein kinase 1 (MAPK1). GO enrichment analysis indicated that the targets of Fespixon cream were primarily involved in various biological processes related to cellular stress responses. KEGG pathway enrichment revealed that these targets were significantly enriched in pathways associated with diabetic complications, atherosclerosis, inflammation, and cancer. Molecular docking confirmed stable binding interactions between the five major active compounds—quercetin, apigenin, rosmarinic acid, salvigenin, and cirsimaritin—and the five core targets (AKT1, TP53, TNF, IL6, MAPK1). Among them, quercetin exhibited the strongest binding affinity with AKT1. RT-qPCR validation in clinical DFU tissue samples demonstrated consistent expression trends with computational predictions: AKT1 was significantly upregulated, while TP53, TNF, IL6, and MAPK1 were markedly downregulated in the Fespixon-treated group compared to controls (p < 0.001), supporting the proposed multi-target therapeutic mechanism. Conclusions: Our study reveals the potential mechanisms by which Fespixon cream exerts therapeutic effects on DFUs. The efficacy of Fespixon cream in treating DFUs is attributed to the synergistic actions of its bioactive components through multiple targets and multiple signaling pathways. Full article

P-phenylenediamines (PPDs) and their quinone derivatives (PPDQs), emerging pollutants widespread in urban environments, exhibit biotoxicological risks. Epidemiological studies suggest their adverse impacts on intestinal health, yet the underlying mechanisms remain unclear. This study aimed to investigate the potential mechanisms of enterotoxicity induced by 13 PPDs and PPDQs using network toxicology and molecular docking approaches. Through the SuperPred, STITCH, GeneCards, and OMIM databases, 182 potential targets associated with PPD- and PPDQ-induced enterotoxicity were identified. Thirty hub targets, including SRC, EGFR, CASP3, and others, were prioritized using STRING and Cytoscape tools. GO and KEGG enrichment analyses via the DAVID and FUMA databases revealed significant enrichment of core enterotoxicity-related targets in the MAPK signaling pathway and the calcium signaling pathway. Molecular docking with AutoDock confirmed strong binding affinities between PPDs/PPDQs and core targets. These results suggest that PPDs and PPDQs may promote the onset and progression of bowel cancer and intestinal inflammation by modulating cancer cell death, proliferation, and inflammatory signaling pathways. This research provides a theoretical framework for elucidating the molecular mechanisms of PPD- and PPDQ-induced enterotoxicity, offering insights for the prevention of associated diseases. Full article

(1) Backgroud Astragalus, a traditional Chinese medicine, demonstrates therapeutic effectiveness in acute pancreatitis (AP). Nevertheless, its precise pharmacological mechanism remains unclear, and clinical guidelines have not been established. This study aims to systematically elucidate the active compounds and molecular mechanisms underlying Astragalus’ therapeutic effects in AP, and provide clinical evidence supporting its efficacy. (2) Methods: TCMSP and Swiss Target Prediction identified drug targets; GeneCards, DrugBank, and OMIM provided disease targets. Venny determined the therapeutic targets, while STRING constructed a protein–protein interaction network. Cytoscape 3.10.3 validated core targets. DAVID was used to conduct GO and KEGG pathway analyses, visualized via Bioinformatic platform. Cytoscape 3.10.3 was used to build a “drug–ingredients–targets–pathways–disease” network. AutoDock Vina 1.1.2 and AutoDockTools 1.5.7 was used to performed molecular docking, with PyMOL 3.0 visualizing the results. PubMed, Embase, Cochrane, Web of Science, CNKI, Wanfang, VIP, and CBMdisc were searched. The literature was screened, extracted, and evaluated, followed by a meta-analysis, using RevMan 5.4.1 and Stata 18. (3) Results: We identified 539 targets for the active ingredients of astragalus. Among 1974 disease-related targets, 232 were found to be therapeutic targets. The GO analysis yielded 589 entries, while the KEGG pathway enrichment analysis identified 147 relevant pathways. The top five active ingredients were quercetin, kaempferol, isorhamnetin, formononetin, and calycosin. Molecular docking analysis revealed potential synergistic effects between these components and core targets. The meta-analysis, comprising six randomized controlled trials, demonstrated a significantly higher total effective rate of clinical efficacy in the astragalus group compared to the control group. (4) Conclusions: Astragalus treats AP through the synergistic action of its components, targets, and pathways. Key active compounds, such as quercetin, kaempferol, isorhamnetin, formononetin, and calycosin, engage with pivotal targets, including TP53, AKT1, TNF, IL6, EGFR, CASP3, MYC, and HIF1A, within primary pathways, such as pathways in cancer, PI3K-Akt signaling pathway, and lipid metabolism, and atherosclerosis. Astragalus effectively treats AP and alleviates clinical symptoms by reducing the time for gas or defecation passage, the disappearance time of abdominal pain or distension, and the recovery time of bowel sounds. Full article

Background: Spinal cord injury (SCI) remains a profound medical challenge, with limited therapeutic options available. Studies focusing on individual molecular markers have limitations in addressing the complex disease process. Methods: This study utilizes RNA-sequencing (RNA-seq) to investigate the differentially expressed genes (DEGs) in spinal cord tissue from a rat SCI model at 1 and 21 days post-injury (dpi). After data processing and analysis, a series of biological pathway enrichment analyses were performed using online tools DAVID and GSEA. Interactions among the enriched genes were studied using Cytoscape software to visualize protein–protein interaction networks. Results: Our analysis identified 595 DEGs, with 399 genes significantly upregulated and 196 significantly downregulated at both time points. CD68 was the most upregulated gene at 21 dpi, with a significant fold change at 1 dpi. Conversely, MPZ was the most downregulated gene. Key immune response processes, including tumor necrosis factor (TNF) production, phagocytosis, and complement cascades, as well as systemic lupus erythematosus (SLE)-associated pathways, were enriched in the upregulated group. The enriched pathways in the downregulated group were related to the myelin sheath and neuronal synapse. Genes of interest from the most significantly downregulated DEGs were SCD, DHCR24, PRX, HHIP, and ZDHHC22. Upregulation of Fc-γ receptor genes, including FCGR2B and FCGR2A, points to potential autoimmune mechanisms. Conclusions: Our findings highlight complex immune and autoimmune responses that contribute to ongoing inflammation and tissue damage post-SCI, underscoring new avenues for therapeutic interventions targeting these molecular processes. Full article

Background/Objectives: Ginseng has been a traditional remedy for centuries, known for its diverse benefits such as anti-inflammation, antioxidant, bactericidal, fungicidal antidiabetic, and anticancer effects. This study employs a network pharmacology approach with molecular dynamics simulation to investigate the potential mechanisms through which ginseng-derived compounds control hypertension. Methods: The total of 70 bioactive compounds were identified from the literature and classified as ginsenosides, which fall under Protopanaxadiol-type ginsenosides, Protopanaxatriol-type ginsenosides, and Ocotillol-type saponins. The target proteins related to hypertension were collected from the drug bank, and interactions between proteins network were examined using STRING 12.0 and Cytoscape 3.10.1. Bioinformatics tools were used to analyze the biological enrichment of genes. The core targets extracted through network pharmacology were subjected to molecular docking studies. Similarly, the docking score below −6.0 kcal/mol was further visualized by performing molecular dynamics simulation to see the binding affinity between the complexes. Finally, pharmacokinetics and toxicity of the compounds were evaluated using computational tools. Results: Molecular docking and simulation results revealed that Floralquinquenoside C, Ginsenoside Rg6, Notoginsenoside T1, and Floralquinquenoside B exhibited strong binding and stability with Angiotensin-converting enzyme (ACE) and Carbonic Anhydrase-I (CA-I), which alters the renin–angiotensin system, calcium signaling pathway, adrenergic signaling in cardiomyocytes, c-GMP-PKG signaling pathway, etc., to regulate high blood pressure. Conclusions: The results show that the phytochemicals from ginseng could act as potential candidates for the management of hypertension, which may help minimize the side effects caused by synthetic anti-hypertensive drugs available on the market. Full article

Background and Objectives: Bladder cancer (BLCA), intimately associated with the immune system, represents a substantial global health burden due to its high recurrence rates and limited therapeutic effectiveness. Although immunotherapy shows promise, challenges persist due to the lack of reliable therapeutic targets. This study aims to investigate potential immune-related biomarkers that could influence the tumor microenvironment in BLCA, using proteomic and in silico approaches. Materials and Methods: Tissue samples from BLCA patients (n = 27) and controls (n = 27) were collected from Şişli Hamidiye Etfal Training and Research Hospital. Proteomic analysis was performed by liquid chromatography/mass spectrometry (LC-MS)/MS to reveal the identities of differentially regulated proteins. Protein network analysis and hub protein detection were performed using Cytoscape (v.3.10.3), while functional annotation was carried out using EnrichR. The immunological analysis of hub proteins was performed in Sangerbox platform, and prognostic associations were evaluated through the Kaplan–Meier Plotter tool. Results: LC-MS/MS analysis identified 120 differentially regulated immune-related proteins. STRING analysis, using an immune response dataset (GO:0006955), highlighted the complement cascade as a significantly enriched pathway (p < 0.05). Proteins, namely C4A, CFB, C4B, C8B, CFH, CFI, C5, C4BPA, C3, and C2, that are known to play key roles in the complement system were identified. Immunological analysis with these proteins revealed the phenomena of immune infiltration and immune checkpoint gene associations (p < 0.05). Four hub genes—CFB, C4B, CFI, and C2—demonstrated a significant prognostic value for BLCA (p < 0.05). Conclusions: This study highlights the pivotal role of the complement system in the immune regulation of BLCA. CFI, C4A, and C4B emerged as potential target proteins for BLCA treatment, particularly in immunotherapy, for enhancing survival. Future research on these proteins and the complement system specifically focusing on BLCA may facilitate the development of targeted immunotherapies, ultimately improving treatment outcomes. Full article

Background: Breast cancer (BC) is the most common cancer among women worldwide, with incidence and mortality rates varying across ethnic groups due to sociodemographic, clinicopathological, and genomic differences. This study aimed to characterize the genomic landscape of BC in diverse ethnic groups using computational tools to explore these variations. Methodology: cBioPortal was used to analyze genomic, clinicopathological, and sociodemographic data from 1084 BC samples. Mutated genes were classified based on GeneCards platform data. Enrichment analysis was performed with CancerHallmarks, and genes not found were compared with MSigDB’s Hallmark Gene Sets. Genes absent from both were further analyzed using NDEx through Cytoscape.org to explore their role in cancer. Results: Significant differences (p < 0.05) were observed in sex, tumor subtypes, genetic ancestry, median of the fraction of the altered genome, mutation count, and mutation frequencies of genes across ethnic groups. We identified the most frequently mutated genes. Some of these genes were found to be associated with classic cancer hallmarks, such as replicative immortality, sustained proliferative signaling, and the evasion of growth suppressors. However, the exact role of some of these genes in cancer remains unclear, highlighting the need for further research to better understand their involvement in tumor biology. Conclusions: This study identified significant clinicopathological and genomic variations in BC across ethnic groups. While key genes associated with cancer hallmarks were found, the incomplete characterization of some highlights the need for further research, especially focusing on ethnic groups, to understand their role in tumor biology and improve personalized treatments. Full article

The impacts of air pollution on human health have become a major concern, especially with rising greenhouse gas emissions and urban development. This study investigates the molecular mechanisms using the STITCH 4.0 and STRING 9.0 databases to analyze the interaction networks (PCI and PPI) associated with two air pollutants: carbon monoxide and hydrogen sulfide. The functional and pathway analysis related to these pollutants were performed by OmicsBox v.3.0. Additionally, critical proteins and their essential pathways were also identified by the Cytoscape networking tool v.3.10.3. AutoDock vina was employed to hypothetically determine the direct interactions of CO and H₂S with the proteins that were found by STITCH. This study revealed that CO and H₂S interacted with the different biological processes related to human health, including erythropoiesis, oxidative stress, energy production, amino acids metabolism, and multiple signaling pathways associated with respiratory, cardiovascular, and neurological functions. Six essential proteins were identified based on their degree of centrality, namely, FECH, HMOX1, ALB, CTH, CBS, and CBSL, which regulate various Reactome and KEGG pathways. Molecular docking analysis revealed that CO exhibited a strong interaction with ADI1, demonstrating a binding affinity of −1.9 kcal/mL. Alternately, the binding energy associated with the H₂S interaction was notably weak (below −0.9 kcal/mL). This present research highlights the necessity for ongoing investigation into the molecular effects of air pollution to guide public health policies and interventions. Full article

Background/Objectives: Endometrial cancer (EC) is a heterogeneous gynecological malignancy characterized by varied clinical outcomes and complex molecular mechanisms. The dysregulation of cyclin K (CCNK), a key regulator of transcription and cell cycle progression, has been implicated in cancer development. This study aimed to investigate CCNK expression at the protein level in EC tissues and at the mRNA level using in silico analysis. Additionally, the prognostic significance of CCNK expression in EC was assessed. Methods: CCNK expression was evaluated using immunohistochemical analysis and mRNA expression profiling in EC tissues, adjacent non-tumorous tissues, and histologically normal endometrial tissues. Immunohistochemical staining was performed on tissue macroarrays, and protein expression was quantified using the Immunoreactivity Score (IRS). mRNA expression analysis was conducted in silico using TCGA data via UCSC Xena and UALCAN web tool. Pathway enrichment was analyzed using Reactome and DAVID tool, while PPI networks were constructed with STRING and Cytoscape. Statistical analyses, including Mann–Whitney U test, Fisher’s exact test, Chi-square test, Kaplan–Meier survival analysis, and Cox regression, were performed using GraphPad Prism. Results: Immunohistochemical analysis revealed significantly elevated CCNK protein expression in tumor tissues, particularly in advanced-stage cases, correlating with adverse pathological features such as higher tumor stage and FIGO grade. High CCNK protein expression was significantly associated with poorer OS in the overall EC cohort and non-endometrioid subtypes, whereas no significant association was observed in endometrioid subtypes. mRNA expression analysis demonstrated significantly higher CCNK levels in non-endometrioid tumors compared to adjacent non-tumorous tissues, but no significant correlation with OS was observed. Functional enrichment analysis highlighted the involvement of CCNK-associated genes in RNA metabolism and transcriptional regulation. Conclusions: These findings emphasize the prognostic value of CCNK expression in EC, particularly in aggressive subtypes. The results suggest that CCNK may serve as a potential therapeutic target, warranting further investigation into its role in EC progression and treatment strategies. Full article

In order to elucidate the active ingredients, potential targets, and mechanisms of action of peppermint in treating bovine mastitis, this study utilized network pharmacology analysis and molecular docking to conduct an exploratory, prospective investigation. Using the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database, all compounds and targets of peppermint were retrieved. After removing duplicates, a total of 133 compounds and 272 targets were obtained. Targets were then standardized to gene names using the UniProt database to construct a drug–component-target network. A total of 183 disease targets related to bovine mastitis were retrieved from the GeneCards database. We obtained 28 cross targets of peppermint targets and bovine mastitis targets, and constructed a protein–protein interaction (PPI) network using the STRING database. A visual network was built using Cytoscape 3.10.0 software, and seven core targets were analyzed and obtained. GO and KEGG pathway enrichment analysis was performed using the Metascape database. Molecular docking was conducted using AutoDockTools–1.5.6 software on some small–molecule compounds and the seven targets to evaluate the stability of binding between peppermint and core targets. Apigenin, luteolin, and ursolic acid are the three main components in peppermint. Core targets (TNF, IL–6, STAT–3, IL–1β, FGF–2, IFNG, and ESR–1) were selected based on the PPI network. The enrichment analysis suggested that the major signaling pathways in network pharmacology may include AGEs–RAGE, IL–17, NF–κB, TLRs, HIF–1, TGF–β, PI3K–Akt, and MAPK. The molecular docking results showed that one of the main components of mint, ursolic acid, exhibited good binding activity with all core targets of bovine mastitis. Other constituents also produced favorable binding with some core targets. This study elucidates the mechanisms of mint in treating bovine mastitis, providing data to support the potential development of new therapies for bovine mastitis using mint and its constituents. Full article

Background: Schizophrenia manifests through behavioral abnormalities, suicidal ideation, and neuropsychological deficits. Hence, this study focused on 5-hydroxytryptamine (5-HT 2C) which influenced the modulation of the series of events that lead to schizophrenia. Methodology: Based on the computational study, the potential 5-HT 2C inhibitors such as Ephemeranthoquinone from Arundina graminifolia and Actinodaphnine from Litsea polyantha were determined. The candidate ligands were optimized using the Gaussian 16 software package and the DFT 6-31g (d,p) basis set. The interaction between the ligands and proteins was examined with PyRx 0.8. Additionally, pharmacokinetics was assessed using SwissADME, and Protox II for toxicity prediction. The network pharmacology study was examined by using the STRING database and the Cytoscape 3.10.1 tool. Moreover, a 100-nanosecond molecular dynamics simulation analysis using Desmond to ensure the stability of these two compounds was carried out. Result: This computational research observed that ephemeranthoquinone and actinodaphnine are the most selective 5-HT 2C inhibitors due to their docking score, optimization, and molecular dynamics simulation results. Conclusions: These compounds are required to be studied further to develop a useful 5-HT 2C inhibitors for the treatment of schizophrenia. Full article

(1) Background: N-(1,3-Dimethylbutyl)-N′-phenyl-p-phenylenediamine-quinone (6PPDQ), as a newly discovered environmental toxin, has been found more frequently in our living conditions. The literature reports that damage to the reproductive and cardiovascular system is associated with exposure to 6PPDQ. However, the relationship between 6PPDQ and cancer still requires more investigation. This research aims to investigate the association between 6PPDQ and prostate cancer. (2) Methods and Results: Based on the data retrieved from the Pharmmapper, CTD, SEA, SwissTargetPrediction, GeneCard, and OMIM databases, we summarized 239 potential targets utilizing the Venn tool. Through the STRING network database and Cytoscape software, we constructed a PPI network and confirmed ten core targets, including IGF1R, PIK3R1, PTPN11, EGFR, SRC, GRB2, JAK2, SOS1, KDR, and IRS1. We identified the potential pathways through which 6PPDQ acts on these core targets using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Ultimately, through molecular docking methods, 6PPDQ binds closely with these ten core targets. These findings indicate that 6PPDQ may influence the proteins related to prostate cancer and may be linked to prostate cancer via several known signaling pathways. (3) Conclusions: This article employs innovative network toxicology to elucidate the prostate carcinogenic effects of 6PPDQ through its modulation of specific vital genes and signaling pathways, thereby establishing a foundational platform for future investigations into the impact of 6PPDQ on prostate cancer and potentially other tumors. Full article