Search Results (760)

As a pivotal model organism in Lepidoptera research, the silkworm (Bombyx mori) holds significant importance in life science due to its economic value and biotechnological applications. Advancements in proteomics and bioinformatics have enabled substantial progress in characterizing the B. mori proteome. Systematic screening and identification of protein–protein interactions (PPIs) have progressively elucidated the molecular mechanisms governing key biological processes, including viral infection, immune regulation, and growth development. This review comprehensively summarizes traditional PPI detection techniques, such as yeast two-hybrid (Y2H) and immunoprecipitation (IP), alongside emerging methodologies such as mass spectrometry-based interactomics and artificial intelligence (AI)-driven PPI prediction. We critically analyze the strengths, limitations, and technological integration strategies for each approach, highlighting current field challenges. Furthermore, we elaborate on the molecular regulatory networks of Bombyx mori nucleopolyhedrovirus (BmNPV) from multiple perspectives: apoptosis and cell cycle regulation; viral protein invasion and trafficking; non-coding RNA-mediated modulation; metabolic reprogramming; and host immune evasion. These insights reveal the dynamic interplay between viral replication and host defense mechanisms. Collectively, this synthesis aims to provide a robust theoretical foundation and technical guidance for silkworm genetic improvement, infectious disease management, and the advancement of related biotechnological applications. 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

Background/Objectives: Cutaneous melanoma is one of the aggressive forms of skin cancer originating from melanocytes. The high incidence of melanoma metastasis continues to rise, partly due to the complex nature of the molecular mechanisms driving its progression. While melanomas generally arise from melanocytes, we investigated whether aberrant keratinocyte differentiation pathways—like cornified envelope formation—discriminate primary melanoma from metastatic melanoma, revealing novel biomarkers in progression. Methods: In the present study, we retrieved four datasets (GSE15605, GSE46517, GSE8401, and GSE7553) associated with primary and metastatic melanoma tissues and identified differentially expressed genes (DEGs). Thereafter, an integrated meta-analysis and functional enrichment analysis of the DEGs were performed to evaluate the molecular mechanisms involved in melanoma metastasis, such as immune cell deconvolution and protein-protein interaction (PPI) network construction. Hub genes were identified based on four topological methods, including ‘Betweenness’, ‘MCC’, ‘Degree’, and ‘Bottleneck’. We validated the findings using the TCGA-SKCM cohort. Drug-gene interactions were evaluated using the DGIdb, whereas structural druggability was assessed using the ProteinPlus and AlphaFold databases. Results: We identified a total of eleven hub genes associated with melanoma progression. These included members of the keratin gene family (e.g., KRT5, KRT6A, KRT6B, etc.). Except for the gene CDH1, all the hub genes were downregulated in metastatic melanoma tissues. From a prognostic perspective, these hub genes were associated with poor prognosis (i.e., unfavorable). Using the Human Protein Atlas (HPA), immunohistochemistry evaluation revealed mostly undetected levels in metastatic melanoma. Additionally, the cornified envelope formation was the most enriched pathway, with a gene ratio of 17/33. The tumor microenvironment (TME) of metastatic melanomas was predominantly enriched in NK cell–associated signatures. Finally, several hub genes demonstrated favorable druggable potential for immunotherapy. Conclusions: Through integrated meta-analysis, this study identifies transcriptional, immunological, and structural pathways to melanoma metastasis and highlights keratin family genes as promising biomarkers for therapeutic targeting. Full article

Lycopene exhibits a broad spectrum of biological activities with potential therapeutic applications. Despite its established antioxidant and anti-inflammatory properties, the molecular basis for its pharmacological actions remains incompletely defined. Here we investigated the molecular targets, pharmacodynamic feasibility, and tissue-specific expression of lycopene targets using a computational pharmacology approach combined with affinity and protein–protein interaction (PPI) analyses. Lycopene-associated human protein targets were predicted using a Swiss target screening platform. Molecular docking was used to estimate binding affinities, and concentration-affinity (CA) ratios were calculated based on physiologically relevant plasma concentrations (75–210 nM). PPI networks of lycopene targets were constructed to identify highly connected targets, and tissue expression analysis was assessed for high-affinity targets using protein-level data from the Human Protein Atlas database. Of the 94 predicted targets, 37% were nuclear receptors and 18% were Family A G Protein Coupled Receptors (GPCRs). Among the top 15 high-affinity targets, nuclear receptors and GPCRs comprised 40% and 26.7%, respectively. Twenty targets had affinities < 10 μM, with six key targets (MAP2K2, SCN2A, SLC6A5, SCN3A, TOP2A, and TRIM24) showing submicromolar binding. CA ratio analysis identified MAP2K2, SCN2A, and SLC6A5 as pharmacodynamically feasible targets (CA > 1). PPI analysis revealed 32 targets with high interaction and 9 with significant network connectivity. Seven targets (TRIM24, GRIN1, NTRK1, FGFR1, NTRK3, CHRNB4, and PIK3CD) showed both high affinity and centrality in the interaction network. The expression profiling of submicromolar targets revealed widespread tissue distribution for MAP2K2 and SCN3A, while SCN2A, TOP2A, and TRIM24 showed more restricted expression patterns. This integrative analysis identifies a subset of lycopene targets with both high affinity and pharmacological feasibility, particularly MAP2K2, SCN2A, and TRIM24. Lycopene appears to exert its biological effects through modulation of interconnected signalling networks involving nuclear receptors, GPCRs, and ion channels. These findings support the potential of lycopene as a multi-target therapeutic agent and provide a rationale for future experimental and clinical validation. Full article

Virulence factors (VFs), produced by pathogens, facilitate pathogenic microorganisms to invade, colonize, and damage the host cells. Accurate VF identification advances pathogenic mechanism understanding and provides novel anti-virulence targets. Existing models primarily utilize protein sequence features while overlooking the systematic protein–protein interaction (PPI) information, despite pathogenesis typically resulting from coordinated protein–protein actions. Moreover, a severe imbalance exists between virulence and non-virulence proteins, which causes existing models trained on balanced datasets by sampling to fail in incorporating proteins’ inherent distributional characteristics, thus restricting generalization to real-world imbalanced data. To address these challenges, we propose a novel Generative and Contrastive self-supervised learning framework for Virulence Factor identification (GC-VF) that transforms VF identification into an imbalanced node classification task on graphs generated from PPI networks. The framework encompasses two core modules: the generative attribute reconstruction module learns attribute space representations via feature reconstruction, capturing intrinsic data patterns and reducing noise; the local contrastive learning module employs node-level contrastive learning to precisely capture local features and contextual information, avoiding global aggregation losses while ensuring node representations truly reflect inherent characteristics. Comprehensive benchmark experiments demonstrate that GC-VF outperforms baseline methods on naturally imbalanced datasets, exhibiting higher accuracy and stability, as well as providing a potential solution for accurate VF identification. Full article

Background: Diabetic foot ulcers (DFUs) are a severe complication of diabetes and are characterized by impaired wound healing and a high amputation risk. Exosomes—which are nanovesicles carrying proteins, RNAs, and lipids—mediate intercellular communication in wound microenvironments, yet their biomarker potential in DFUs remains underexplored. Methods: We analyzed transcriptomic data from GSE134431 (13 DFU vs. 8 controls) as a training set and validated findings in GSE80178 (6 DFU vs. 3 controls). A sum of 7901 differentially expressed genes (DEGs) of DFUs were detected and intersected with 125 literature-curated exosome-related genes (ERGs) to yield 51 candidates. This was followed by GO/KEGG analyses and a PPI network construction. Support vector machine–recursive feature elimination (SVM-RFE) and the Boruta random forest algorithm distilled five biomarkers (DIS3L, EXOSC7, SDC1, STX11, SYT17). Expression trends were confirmed in both datasets. Analyses included nomogram construction, functional and correlation analyses, immune infiltration, GSEA, gene co-expression and regulatory network construction, drug prediction, molecular docking, and RT-qPCR validation in clinical samples. Results: A nomogram combining these markers achieved an acceptable calibration (Hosmer–Lemeshow p = 0.0718, MAE = 0.044). Immune cell infiltration (CIBERSORT) revealed associations between biomarker levels and NK cell and neutrophil subsets. Gene set enrichment analysis (GSEA) implicated IL-17 signaling, proteasome function, and microbial infection pathways. A GeneMANIA network highlighted RNA processing and vesicle trafficking. Transcription factor and miRNA predictions uncovered regulatory circuits, and DGIdb-driven drug repurposing followed by molecular docking identified Indatuximab ravtansine and heparin as high-affinity SDC1 binders. Finally, RT-qPCR validation in clinical DFU tissues (n = 5) recapitulated the bioinformatic expression patterns. Conclusions: We present five exosome-associated genes as novel DFU biomarkers with diagnostic potential and mechanistic links to immune modulation and vesicular transport. These findings lay the groundwork for exosome-based diagnostics and therapeutic targeting in DFU management. Full article

Acute lung injury is a severe disease with a high mortality rate, which can result in increased oxidative stress and further mitochondrial damage and cell apoptosis. L-Clausenamide is an amide from the fruit wampee. This study combined network pharmacology, molecular docking, and in vitro study to elucidate the effect of combating acute lung injury and the underlying mechanism of L-Clausenamide. Network pharmacology indicated that the 152 targets can treat acute lung injury through regulating oxidative stress. Based on PPI analysis and screening of the central target, AKT1 is the key target of the underlying mechanism. KEGG and GO enrichment analysis demonstrated that apoptosis is an important pathway for this curing effect. In the in vitro study, treatment with L-Clausenamide alleviates intracellular ROS accumulation, mitochondrial membrane potential loss, mitochondrial morphological distortion, ATP decrease, and the CASP3 activity. The SPR analysis was performed to validate the binding between AKT1 and L-Clausenamide. The Western blot result showed that L-Clausenamide increases the phosphorylation of Akt and decreases cleavage of CASP3. L-Clausenamide can alleviate lipopolysaccharide (LPS)-induced acute lung injury through targeting AKT1 and show an improvement in mitochondrial abnormality and inhibition against ROS-activated caspase-3-dependent apoptosis activation. Full article

Trachinotus ovatus is a euryhaline, warm-water pelagic fish species with strong adaptability, rapid growth, and a high survival rate, making it one of the most important marine aquaculture species in China. In recent years, extensive experience has been accumulated in the cage farming of T. ovatus, but whether it can adapt to deep-sea environments and grow normally remains a current research focus. This study used RNA-Seq sequencing technology to analyze the gene expression changes in the liver of T. ovatus under three conditions: rest (0 cm/s), medium flow velocity (54 cm/s), and high flow velocity (90 cm/s). Through differential expression analysis, Short Time-series Expression Miner (STEM) analysis and protein–protein interaction (PPI) network analysis, a total of 5107 differentially expressed genes (DEGs), three significantly expressed gene profiles (profile6, profile1, and profile5), and 15 hub genes were identified. The results showed that changes in flow speed significantly impacted key biological processes such as energy metabolism, protein homeostasis, and endoplasmic reticulum (ER) stress response. Under moderate and high flow conditions, glycolysis-related genes were upregulated to meet the energy demands of swimming, while the downregulation of the PPARγ-RXRG complex and its downstream genes in the lipid metabolism pathway suggested a limitation in its fatty acid β-oxidation capacity. At the same time, protein synthesis was enhanced, and the unfolded protein response (UPR) was activated to help cope with ER stress. Furthermore, when the flow speed reached 90 cm/s, the expression of UPR- related genes and the anti-apoptotic factor JNK significantly decreased, suggesting that the stress response was nearing its limit and could potentially trigger cell apoptosis. These findings provide new insights into the molecular adaptation mechanisms of T. ovatus to flow speed stress and offer theoretical support for its rational farming in deep-sea cages, suggesting that the water flow speed in farming should not exceed 90 cm/s. Full article

Background: Obesity is characterized by a chronic state of low-grade inflammation. Investigating immune-critical genes and their biological functions in the adipose tissue of postmenopausal obese women is crucial for elucidating the underlying mechanisms of immune dysregulation associated with obesity. Methods: In this study, microarray (GSE151839) and single-cell RNA-seq (GSE176171) datasets were obtained from the Gene Expression Omnibus (GEO). For microarray data analysis, weighted gene co-expression network analysis (WGCNA), protein–protein interaction network (PPI) analysis, and immune infiltration analysis (ssGSEA) were employed to identify obesity-related immune-critical genes. Subsequently, the candidate genes were validated using scRNA-seq data to explore their expression patterns at the single-cell level. Finally, the expression levels of these immune-critical genes were experimentally verified in adipose tissue from obese and control zebrafish models using RT-qPCR. Results: Analysis of microarray data through WGCNA, PPI and ssGSEA identified 16 obesity-related immune-critical genes, including IL7R, CD3E, CD2, CCR5, CD3D, MS4A1, TRAT1, SLAMF8, CCL3L1, SPP1, CCL5, IL2RG, CD3G, TLR8, ITK, and CCL3. Differential expression of SPP1, ITK and CCL5 was confirmed in scRNA-seq data, with ITK and CCL5 showing distinct expression patterns in natural killer (NK) cells. Furthermore, RT-qPCR analysis revealed upregulation of SPP1 and ITK in adipose tissue of obese zebrafish compared to lean controls. Conclusions: This study identifies SPP1, ITK and CCL5 as key immune hub genes in the adipose tissue of postmenopausal obese women, with NK cells playing a significant role in adipose tissue inflammation through the expression of these genes. These findings provide novel insights into potential therapeutic targets for the prevention and treatment of obesity in postmenopausal women. Full article

This study investigates the effect of tryptophan treatment on aged pig oocytes, focusing on its potential to reduce oxidative stress and improve oocyte quality. An oxidative stress model was induced using hydrogen peroxide (H₂O₂) to mimic aging effects on oocytes. Fresh ovaries from young sows were collected, and oocytes were aspirated and cultured for in vitro maturation. Oocytes in the H₂O₂ and the H₂O₂+Trp groups were exposed to 100 µM H₂O₂ for 30 min, with the H₂O₂+Trp group receiving an additional 50 µM tryptophan supplementation. RNA-sequencing was performed to study the underlying mechanism through which tryptophan mitigated the H₂O₂-induced oxidative stress in oocytes. The results demonstrated that tryptophan supplementation significantly reduced oxidative stress markers such as H₂O₂ and malonaldehyde (MDA) while restoring key antioxidant enzymes such as superoxide dismutase (SOD), and catalase (CAT) confirming its antioxidant role. Furthermore, tryptophan improved cumulus cell expansion, and oocyte quality, which were compromised by oxidative stress. Transcriptomics study revealed the enrichment of several KEGG pathways, such as P13K-Akt signaling pathways as a critical regulator of cell survival and function, emphasizing the protective effects of tryptophan on oocyte integrity. Moreover, the protein–protein interaction (PPI) network identified several hub genes in the tryptophan-treated group compared with H₂O₂, including TIMP1, CCN2, and MMP12 as key players in ECM remodeling and cellular adhesion, which are critical for restoring oocyte quality. These findings suggest that tryptophan supplementation not only mitigated oxidative stress but also modulated gene expression related to cellular functions and stress response. These results propose that tryptophan could be a valuable therapeutic strategy for improving reproductive outcomes in aging sows and other mammals facing age-related oocyte dysfunction. Full article

Background: Proton pump inhibitors (PPIs) are frequently used after endoscopic variceal ligation (EVL) to reduce post-procedural bleeding, though studies have shown mixed results regarding their efficacy. While some suggest benefits, others report no significant advantage and highlight potential risks, including infection, kidney injury, and hepatic complications in cirrhotic patients. This study utilizes the TriNetX global health research network to evaluate the outcomes of PPI use following elective EVL for primary prophylaxis. Methods: This retrospective cohort study was conducted using the TriNetX database to evaluate adult patients with cirrhosis and esophageal varices who underwent EVL for primary prophylaxis. Patients who received at least two weeks of PPI therapy following EVL were compared to those who did not receive PPI within one month post-procedure. Outcomes assessed included esophageal bleeding, adverse events such as acute kidney injury (AKI), pneumonia, spontaneous bacterial peritonitis (SBP), Clostridioides difficile infection, hepatic encephalopathy, and all-cause mortality at 4 weeks and 8 weeks. Results: Of 6196 patients with cirrhosis and esophageal varices who underwent EVL, 12% (n = 764) received adjuvant PPI post-procedure, while 88% (n = 5432) did not receive PPI. After 1:1 propensity score matching, two well-balanced cohorts of 618 patients each were analyzed. PPI use was not associated with a reduction in esophageal bleeding at either 4 weeks (1.8% vs. 1.7%, p = 0.89) or 8 weeks (2.3% vs. 1.9%, p = 0.60). However, the composite adverse event rate—including SBP, hepatic encephalopathy, pneumonia, C. difficile, and acute kidney injury (AKI)—was significantly higher in the PPI group at both 4 weeks (7.9% vs. 3.0%, p < 0.01) and 8 weeks (13.2% vs. 3.0%, p < 0.01). Subgroup analysis showed no significant differences in pneumonia, SBP, or C. difficile infection at either time point. Hepatic encephalopathy was significantly more frequent in the PPI group at 8 weeks (4.9% vs. 2.0%, p = 0.01), and AKI occurred more often at both 4 weeks (5.7% vs. 2.0%, p < 0.01) and 8 weeks (9.6% vs. 2.1%, p < 0.01). Mortality was similar at 4 weeks but significantly higher in the PPI group at 8 weeks (4.3% vs. 1.7%, p < 0.01). Conclusions: PPI use after prophylactic EVL did not reduce bleeding risk and was linked to higher rates of adverse events. These findings suggest routine use may not be beneficial and should be reconsidered in cirrhotic patients who undergo EVL for primary prophylaxis. Full article

Background: Rheumatoid arthritis-related interstitial lung disease (RA-ILD) is a significant complication of RA which lacks effective treatments with high mortality. This study aimed to investigate the role of matrix metalloproteinase-7 (MMP-7) in mediating RA-ILD. Methods: Based on the database of RA-ILD patients, a bioinformatics analysis was performed. A protein–protein interaction (PPI) network focusing on MMP-7 was simulated. Pleural mesothelial cells (PMCs) were treated with RA-ILD patients’ serum or RA-ILD-related inflammatory factors, and the protein expressions of collagen-I and MMP-7 were examined. An arthritis model was established using complete Freund’s adjuvant (CFA). Changes in the weight and joints of mice were recorded, and lung tissues were evaluated by Masson staining and Sirius red stain techniques. MMP-7 inhibitor, MMP-7 siRNA and MMP shRNA lentivirus were used to inhibit MMP-7 and investigate changes in collagen-I and fibrosis in vivo and in vitro. Results: MMP-7 was found to be significantly expressed in RA-ILD lung tissue by bioinformatics analysis, and MMP-7 to maybe interact with collagen-I. In vitro experiments indicated cytokines IL-1β, IL-6 and TNF-α promoted MMP-7 and collagen-I expression in PMCs. Serum obtained from patients with RA-ILD also upregulated MMP-7 and collagen-I expression in PMCs. Inhibition of MMP-7 with MMP-7 siRNA or MMP inhibitor prevented collagen-I synthesis in PMCs. In vivo, CFA induced arthritis and subpleural lung inflammation in rats, but the MMP-7 inhibitor and MMP-7 siRNA attenuated CFA-induced lung inflammation and subpleural lung fibrosis. Conclusions: MMP-7 mediated subpleural lung inflammation as well as fibrosis in RA-ILD. It provided theoretical and experimental support for MMP-7 being a therapeutic target in RA-ILD. Full article

Currently, there is no standard treatment for renal cell carcinoma (RCC) that is free of side effects and resistance. Additionally, limited information exists on how curcumin affects the gene expression profiles of patients with translocation renal cell carcinoma (tRCC) and papillary renal cell carcinoma (pRCC). The pathways responsible for metastasis in tRCC are still not well understood, and there is no established treatment or reliable biomarker to predict outcomes for metastatic tRCC. Primary clinical data from patients were retrieved from the TCGA database and analyzed using cBioPortal, stitch, string, R and Python. Various analyses were performed, including differential gene expression, protein-protein interaction (PPI) network analysis, drug-targeted gene analysis, gene ontology (GO), enrichment analyses, and systematic searches to assess the impact of curcumin on the transcriptomic profiles of tRCC, pRCC, and clear cell renal cell carcinoma (ccRCC). No significant impact of sensitive genes on survival in KIRC and KIRP was found, though a trend suggested they may delay disease progression. The combination of curcumin with sunitinib showed promise in overcoming drug resistance in ccRCC by inducing ferroptosis, reducing iron, and increasing ADAMTS18 expression. This study, leveraging data from the TCGA database and other databases explored the impact of curcumin on transcriptomic profiles in tRCC, pRCC, and clear cell RCC (ccRCC). Gene analysis revealed immune and metabolic differences, with KIRC showing a stronger immune response. This study is the first to propose that future research into the miR-148/ADAMTS18 genes and the ferroptosis pathway in tRCC and pRCC could lead to the development of new therapies and the identification of novel therapeutic targets, potentially overcoming drug resistance and metastasis. Full article

Background/Objectives: Studying protein–protein interaction (PPI) networks is crucial in understanding cancer phenotypes and molecular mechanisms. Here, we focus on PPIs involved in 12 different types of cancer (oncoPPIs), highlighting those protein pockets serving as outposts to modulate protein functioning. Methods: To explore these cavities linked to the cancer phenotype changes, we built a comprehensive pocketome of 314 crystallographically solved oncoPPIs. Based on this experimental data, we identified and investigated all ligandable protein pockets by employing 3D geometric and energetic descriptors. These pockets were classified as suitable for designing new oncoPPI modulators or PROTACs. The ligand-bound crystallographic pockets were analyzed to compare their properties across cancer types. Finally, 3D oncoPPI networks were built for each cancer type to identify highly connected proteins acting as hubs. Results: Combining interaction networks with structural pocket data helps identify cancer-relevant proteins and key interacting residues. Using this approach, we present clinical examples (e.g., S100A1, NRP1, CTNNB1, VCP) to show the therapeutic value of targeting ligandable 3D oncoPPIs. We also provide a publicly available reference dataset supporting future research. Conclusions: Notably, this study offers a flexible framework for evaluating and prioritizing novel disease targets. 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