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PubMed2026

Exploring the mechanism of Acanthopanax in treating vertigo: A network pharmacology and molecular docking study.

Acanthopanax has therapeutic efficacy against vertigo; however, the underlying mechanism remains unclear. This study aimed to elucidate the mechanism by which Acanthopanax treats vertigo through integrated network pharmacology and molecular docking techniques, and retrieved all target genes of Acanthopanax for vertigo treatment from July to October 2025. Vertigo-related target genes were subsequently identified from public databases, including GeneCards and Online Mendelian Inheritance in Man. The intersection between Acanthopanax-derived targets and vertigo-related targets was analyzed to identify candidate target genes. Using the STRING platform, we constructed protein-protein interaction networks for the identified candidate targets and mined the core functional modules within these networks. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed on candidate targets via the clusterProfiler package. A carp bile poisoning-liver injury target-pathway network was constructed via Cytoscape 3.8.2 software, network topology analysis was conducted, and the core components and targets were screened. The results found that A total of 295 candidate targets for the treatment of vertigo caused by Eleutherococcus senticosus were identified. Pathway enrichment analysis revealed that Eleutherococcus senticosus treatment for vertigo may be closely associated with pathways related to IL-17, TNF, phosphoinositide 3-kinase (PI3K)-Akt, p53, HIF-1, and Forkhead box O signaling. The core targets for the treatment of A. senticosus vertigo include TP53, AKT1, STAT3, TNF, and JUN. Network pharmacology and molecular docking studies suggest that A. senticosus may treat vertigo by regulating targets such as JUN, TNF, AKT1, STAT3, and STAT3 through pathways such as the IL-17, TNF, phosphoinositide 3-kinase-Akt, p53, HIF-1, and Forkhead box O signaling pathways. These mechanisms warrant further investigation in future o and in vitro studies.

Molecular Docking Simulation↗

PubMed2026

A Network Pharmacology and Molecular Docking Study of TongBi Formula for Osteoarthritis.

This study applied network pharmacology combined with molecular docking to predict the potential therapeutic targets and molecular mechanisms of TongBi Formula (TBF) in osteoarthritis (OA). Active components and corresponding targets of TBF were retrieved from the traditional Chinese medicine Systems Pharmacology Database and Analysis Platform, while OA-related targets were collected from Online Mendelian Inheritance in Man, GeneCards, DrugBank, and Therapeutic Target Database. A network visualization and analysis software was used to construct compound-target and protein-protein interaction (PPI) networks. Gene Ontology functional annotation and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed using the Database for Annotation, Visualization and Integrated Discovery platform. Molecular docking analysis was conducted using a molecular docking software to evaluate the predicted binding affinity between key active compounds and core target proteins. A total of 47 overlapping targets between TBF and OA were identified. PPI network analysis highlighted JUN, RELA, IL6, MAPK1, and IL10 as potential hub targets. Enrichment analysis suggested that TBF may regulate inflammation, lipid metabolism, and multiple intracellular signaling pathways associated with OA progression. Molecular docking results demonstrated favorable predicted binding affinities between core active compounds and key OA-related protein targets. These findings provide a computational framework for understanding the potential mechanisms of TBF against OA and support further experimental validation.

Molecular Docking Simulation↗

PubMed2026

Gut microbiota-derived metabolites target C5AR1/KDM2A/HCAR3 axis in inflammatory bowel disease: a multi-machine learning algorithms and molecular docking study.

BACKGROUND: Inflammatory bowel disease (IBD) is a chronic recurrent disorder. Gut microbiota-derived metabolites regulate intestinal homeostasis, but their molecular mechanisms in IBD remain unclear. Current studies lack systematic "microbiota-metabolite-target" network mining with multi-method validation. This study integrates network pharmacology, three machine learning algorithms, and molecular docking to construct this regulatory network in IBD. METHODS: Transcriptome data were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified using limma (p < 0.05, |log2FC| > 0.5). Weighted gene co-expression network analysis (WGCNA) with an optimal soft threshold of β = 7 was performed to identify key module genes. Candidate genes were obtained by intersecting DEGs, gut microbiota-associated genes from the gutMGene database, and WGCNA module genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted to explore the functional roles of candidate genes. Core genes were identified using three machine learning algorithms (LASSO, Boruta, and SVM-RFE), followed by protein-protein interaction (PPI) network analysis. Molecular docking was performed to assess the binding affinities between hub proteins and gut microbiota-derived metabolites. RESULTS: A total of 885 DEGs were identified between the IBD and control groups, including 463 upregulated and 422 downregulated genes. WGCNA identified 280 key module genes from the purple and yellow modules. The intersection of DEGs, gut microbiota-associated genes, and WGCNA module genes yielded 19 core candidate genes. PPI network analysis combined with three machine learning algorithms jointly identified C5AR1, KDM2A, and HCAR3 as core hub genes. ROC curve analysis demonstrated that all three hub genes achieved AUC values greater than 0.7 in both the training and validation sets, indicating excellent diagnostic performance for IBD. Enrichment analysis revealed significant associations with the TNF, NF-κB, and IL-17 signaling pathways. Molecular docking confirmed stable binding of C5AR1 with 1,3-Diphenylpropan-2-Ol (-7.87 ± 0.83 kcal·mol-¹) and HCAR3 with 3-Indolepropionic Acid (-6.35 ± 0.70 kcal·mol-¹), both below -5.0 kcal·mol-¹. CONCLUSION: This study first constructs a "gut microbiota-metabolite-hub gene" axis in IBD, providing a computational framework for microbiota-targeted precision therapy, and identifying C5AR1/KDM2A/HCAR3 as computationally predicted diagnostic biomarkers and 1,3-Diphenylpropan-2-Ol/3-Indolepropionic Acid as candidate intervention molecules that warrant further experimental validation.

Molecular Docking Simulation↗

PubMed2026

Elucidating the mechanism of Buyang Huanwu Decoction in the treatment of ischemic stroke: A network pharmacology and molecular docking study.

A large number of functional disorders and uncomfortable symptoms often remain following ischemic stroke (IS). Existing drug therapy is not ideal for the direct improvement of symptoms, which often leads to poor patient compliance with physical rehabilitation therapy. Buyang Huanwu Decoction (BYHWD) is a famous prescription that is effective in treating IS, especially during the sequela stage of IS. We analyzed the therapeutic mechanism of BYHWD through network pharmacology. This study aims to investigate the potential active ingredients, targets, and signaling pathways of BYHWD for the treatment of IS, utilizing network pharmacology and molecular docking technology. The active ingredients of 7 Chinese herbs in BYHWD were obtained from the Traditional Chinese Medicine Systems Pharmacology and HERB databases, and IS-related disease targets were searched in the DisGeNET, GeneCards, and OMIM databases. The protein-protein interaction network was constructed using the STRING database and analyzed by Cytoscape 3.10.2 software. Additionally, the target genes were uploaded to the Database for Annotation, Visualization, and Integrated Discovery website for Gene Ontology alongside Kyoto Encyclopedia of Genes and Genomes analyses. With the assistance of AutoDockTools and PyMOL software (Schrödinger, Inc.), a validation of molecular docking results and a visualization of the results were performed. The results showed that there were 190 intersection targets between the active drug components and IS, corresponding to 61 active components, among which the top 5 target genes were tumor suppressor protein 53, Jun proto-oncogene, AKT serine/threonine kinase 1, mitogen-activated protein kinase 1, and estrogen receptor alpha. The PI3K-Akt signaling pathway is one of the top 10 pathways. The molecular docking results indicated that most of the top 5 targets had good affinities for the 8 core compounds. This computational analysis suggests that BYHWD may treat IS through multiple targets and pathways. It may play a neuroprotective role by regulating the inflammatory response, oxidative stress, apoptosis, autophagy, and vascular endothelial homeostasis. The identification of core effective components provides a theoretical foundation and candidate compounds for further investigation into new drugs for the treatment of sequelae after IS.

Drugs, Chinese Herbal↗

PubMed2025

Inflammatory pathways and immune dysregulation in pediatric postoperative septic shock: A study integrating transcriptomics, machine learning and molecular docking.

This study elucidates the molecular and immune regulatory mechanisms of pediatric postoperative septic shock. Transcriptomic data were obtained from the Gene Expression Omnibus database. Differentially expressed genes were identified using the limma package, and gene co-expression modules were constructed using Weighted Gene Co-expression Network Analysis. Functional enrichment was performed via gene set enrichment analysis, Gene Ontology, and Kyoto Encyclopedia of Genes and Genomes analyses. Immune cell infiltration was assessed using ESTIMATE and CIBERSORT. Mendelian randomization was applied to explore causal relationships between gene expression and septic shock. Feature genes were selected using machine learning algorithms, and a diagnostic nomogram model was constructed. Finally, molecular docking analysis was performed to screen and evaluate the binding affinity of traditional Chinese medicine monomers to core target proteins. A total of 1331 differentially expressed genes were identified, and the turquoise module was strongly correlated with septic shock. Enrichment analysis revealed significant activation of IL-6/JAK/STAT3, TNF-α/NF-κB, and PI3K/Akt/mTOR pathways. Immune infiltration analysis indicated suppressed immune scores and imbalances in neutrophils, macrophages, T cells, and B cells. Mendelian randomization confirmed causal associations for 6 genes, including PIM3. The predictive model based on feature genes demonstrated high diagnostic performance. Molecular docking suggested that quercetin and astramembrannin I could stably bind PIM3. This study systematically identified core genes, dysregulated immune pathways, and candidate small-molecule interventions in pediatric septic shock, providing novel insights for early diagnosis and targeted therapy.

Humans↗

PubMed2026

Elucidating the Mechanism of Xiaoqinglong Decoction in Chronic Urticaria Treatment: An Integrated Approach of Network Pharmacology, Bioinformatics Analysis, Molecular Docking, and Molecular Dynamics Simulations.

INTRODUCTION: Xiaoqinglong Decoction (XQLD) is a traditional Chinese medicinal formula commonly used to treat chronic urticaria (CU). However, its underlying therapeutic mechanisms remain incompletely characterized. This study employed an integrated approach combining network pharmacology, bioinformatics, molecular docking, and molecular dynamics simulations to identify the active components, potential targets, and related signaling pathways involved in XQLD's therapeutic action against CU, thereby providing a mechanistic foundation for its clinical application. METHODS: The active components of XQLD and their corresponding targets were identified using the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. CU-related targets were retrieved from the OMIM and GeneCards databases. Subsequently, core components and targets were determined via protein-protein interaction (PPI) network analysis and component-target-pathway network construction. Topological analyses were performed using Cytoscape software to prioritize core nodes within these networks. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted via the DAVID database to identify enriched biological processes and signaling pathways. Molecular docking was performed to evaluate binding interactions between key components and core targets, while molecular dynamics (MD) simulations were employed to assess the stability of the component-target complexes with the lowest binding energy. Finally, CU-related targets of XQLD were validated using datasets from the Gene Expression Omnibus (GEO) database. RESULTS: A total of 135 active components and 249 potential targets of XQLD were identified, alongside 1,711 CU-related targets. Core components, such as quercetin, kaempferol, beta-sitosterol, naringenin, stigmasterol, and luteolin, exhibited high degree values in the constructed networks. The core targets identified included AKT1, TNF, IL6, TP53, PTGS2, CASP3, BCL2, ESR1, PPARG, and MAPK3. GO and KEGG pathway enrichment analyses revealed the PI3K-Akt signaling pathway as a central regulatory mechanism. Molecular docking studies demonstrated strong binding affinities between active components and core targets, with the stigmasterol-AKT1 complex exhibiting the lowest binding energy (-11.4 kcal/mol) and high stability in MD simulations. Validation using GEO datasets identified 12 core genes shared between CU-related targets and XQLD-associated targets, including PTGS2 and IL6, which were also prioritized as core targets in the network pharmacology analyses. DISCUSSION: This study comprehensively integrates multidisciplinary approaches to clarify the potential molecular mechanisms of XQLD in treating CU, highlighting its multitarget and multipathway synergistic effects. Molecular docking and dynamics simulations confirm the stable interaction between stigmasterol and the core target AKT1. Additionally, GEO dataset analysis verifies the pathogenic relevance of targets such as PTGS2 and IL6, significantly enhancing the credibility of our findings. These results provide a modern scientific basis for the traditional therapeutic effects of XQLD on CU and have important implications for developing multitarget treatments for this condition. However, this study mainly relies on database mining and computational simulations. Further in vitro and in vivo experimental validations are needed to confirm the predicted component-target-pathway interactions. CONCLUSION: This study identifies the active components, potential targets, and pathways through which XQLD exerts therapeutic effects on CU. These findings provide a theoretical foundation for further mechanistic studies and support their clinical application in the treatment of CU.

Molecular Docking Simulation↗

PubMed2025

Donepezil and Memantine Derivatives for Dual-Function and Prodrug Applications in Alzheimer's Disease.

The treatment of Alzheimer's disease by acetylcholinesterase (AChE) and N-methyl-d-aspartate receptor (NMDAR) inhibitors is limited by the narrow therapeutic window and adverse side effects of the drugs. This study aims to increase the efficacy and limit the side effects of donepezil, an AChE inhibitor, and memantine, an NMDAR inhibitor, through the addition of amyloid-β (Aβ)-targeting fragments to create dual-function compounds. The incorporation of the amyloid-targeting fragments successfully produced compounds with affinity for Aβ fibrils, and that can stain amyloid plaques in the brains of 5xFAD mice. The donepezil-based compounds showed significant changes in AChE inhibition compared to donepezil due to the incorporation of the Aβ-targeting fragment and as confirmed by molecular docking studies. The memantine-derived compound showed good brain uptake in 5xFAD mice but lacked compatibility with NMDAR inhibition based on in vitro assays and molecular docking. Importantly, the memantine-derived compound acts as a prodrug in vivo, releasing memantine within a pharmacologically relevant time frame. Overall, these findings suggest that dual-function compounds may be useful as drug delivery agents that can be metabolized to release an active drug in areas of the brain rich in amyloid plaques and thus could lead to improved treatments for Alzheimer's disease.

Animals↗

PubMed2026

Development of metal-free one-pot sequential synthesis of carbazolyl-thiazolidinones as anti-leukemic agents with potential β-catenin/c-MYC pathway modulation: from synthesis to in vitro and in silico profiling.

Cancer remains a leading cause of mortality worldwide, necessitating the development of new, selective, and potent therapeutic agents. In this study, a novel, metal-free, one-pot sequential synthetic approach was developed for the synthesis of carbazolyl-thiazolidinone (CTZD) derivatives via the reaction of N-octylcarbazole-3-carbaldehyde with variety of aromatic and aliphatic primary and secondary amines and thioglycolic acid. This strategy efficiently yielded a diverse range of CTZD derivatives (4a-p) in moderate to high yields (20-95%). The synthesized compounds were characterized by FTIR, NMR (1H, 13C, DEPT, APT), and HRMS. Their in vitro cytotoxicity was tested on human leukemia cell lines NB4, K562 and U937 using MTT assays, where four derivatives (4e, 4i, 4j, and 4o) exhibited potent, concentration-dependent antiproliferative activity over the tested concentration range (1.25-10 μM). As c-MYC is a key regulator of cell proliferation, qRT-PCR analysis demonstrated that these four derivatives significantly downregulated c-MYC mRNA expression, with compound 4j producing the greatest reduction, suggesting a potential association with modulation of the Wnt/β-catenin pathway. DNA fragmentation analysis showed no detectable late-stage apoptosis, indicating that the observed c-MYC downregulation and antiproliferative effects were not associated with late-stage apoptotic cell death. The ADME/T analysis of all compounds showed favorable pharmacokinetic profiles with prediction of good oral absorption (HIA >92%) and no hERG I liability. Molecular docking studies demonstrated strong binding affinities of these compounds to β-catenin protein (PDB ID: 7ZRB) with compound 4i showing strongest affinity with ΔG = -8.10 kcal/mol via H-bonds with Ser473, Asn430, Arg469 and His470 amino acid residues. The developed metal-free synthesis provided a sustainable route to bioactive carbazolyl-thiazolidinones, and derivatives 4e, 4i, 4j, 4o could be promising leads for targeting Wnt/β-catenin/c-MYC signaling in leukemia.

Humans↗

PubMed2026

Targeting pancreatic cancer progression: The formononetin and salvianolic acid B combination suppresses JAK/STAT signaling via MBOAT2 downregulation.

OBJECTIVE: Formononetin and salvianolic acid B (FcS) are the primary bioactive components of the Astragalus mongholicus-Salvia miltiorrhiza herbal pair, a classic combination for treating pancreatic cancer associated with qi deficiency and blood stasis. This study elucidates the therapeutic potential and mechanisms of FcS in the treatment of pancreatic cancer. METHODS: A zebrafish xenograft model was used to screen bioactive combinations derived from A. mongholicus and S. miltiorrhiza, identifying FcS as a candidate with antitumor activity. Its efficacy was evaluated in vivo using the zebrafish model, orthotopic LSL-KrasG12D/+, LSL-Trp53R172H/+ and Pdx-1-Cre (KPC) mice, and subcutaneous xenograft models. Cell viability and proliferation were assessed using cell counting kit-8, 5-ethynyl-2'-deoxyuridine and colony formation assays, and migration and invasion were evaluated by wound healing and transwell assays. Membrane-bound O-acyltransferase 2 (MBOAT2) was identified as a potential target through a molecular docking study and the Cancer Genome Atlas (TCGA) analysis. MBOAT2 knockdown cells were used to explore its roles and the Janus kinase/signal transducer and activator of transcription (JAK/STAT) signaling pathway in FcS-mediated inhibition. RESULTS: In the zebrafish model, FcS strongly inhibited pancreatic tumor growth. FcS reduced tumor volume, the expression of proliferation marker Ki-67, and proliferating cell nuclear antigen in KPC mice. In vitro, FcS inhibited pancreatic cancer cell viability, proliferation, migration and invasion, which was accompanied by downregulation of MBOAT2 expression. TCGA analysis linked high MBOAT2 expression to aggressive phenotypes. MBOAT2 knockdown reduced the survival, proliferation and invasion of BxPC-3 cells. Rescue experiments revealed that MBOAT2 knockdown attenuated the antitumor effects of FcS, possibly through modulation of the JAK/STAT signaling pathway. FcS also inhibited tumor proliferation in xenograft models, and MBOAT2 expression was elevated in tumor tissues from pancreatic cancer patients. CONCLUSION: FcS suppresses pancreatic cancer progression via MBOAT2 downregulation and JAK/STAT pathway inhibition, which highlights MBOAT2 as a potential therapeutic target. Please cite this article as: Xu Y, Xu CS, Jin HB, Gu WG, Shen HZ, Lu L, Chen Y, Xu DC, Zhang XF, Yang JF, Wang Y. Targeting pancreatic cancer progression: The formononetin and salvianolic acid B combination suppresses JAK/STAT signaling via MBOAT2 downregulation. J Integr Med. 2026; 24(5):725-741.

Animals↗

PubMed2025

Click synthesis of some novel benzo[d]thiazole-1,2,3-triazole hybrid compounds with benzamide and/or benzoate tethers as EGFR-dependent signaling inhibitors against breast cancer.

The elaboration of anti-breast cancer agents targeting EGFR represents a promising strategy in medicinal chemistry. Consequently, under optimized Cu(i)-catalyzed click synthesis, a new library of 1,4-disubstituted 1,2,3-triazole-based benzo[d]thiazole scaffold carrying benzamide and/or benzoate tethers 5a-t was designed, synthesized, and characterized by appropriate spectral techniques. They were also screened for their in vitro anti-cancer activity against a panel of cancer cell lines, breast (T47D), prostate (PC3), lung (A549), and colon (HCT116) human cancer, along with normal fibroblast cells. Notably, the hybrid triazoles, 5p, 5s, and 5t emerged as the most potent candidates, especially against T47D, with IC50 values of 15, 26, and 28 μM, respectively. Compound 5p significantly induced apoptosis in T47D by 27.3-fold, causing total apoptosis of 19.39% compared to 0.71%, arresting cell proliferation at the G2/M phase. Regarding EGFR as the molecular target, among the tested compounds, 5p significantly inhibited EGFR by 96.8%, with an IC50 value of 65.6 nM, compared to erlotinib, having an IC50 value of 84.1 nM. Compound 5p showed promising PI3K/AKT/mTOR inhibition as the EGFR-dependent signaling pathway with IC50 values of 4.98 μM, 0.21 μM, and 0.49 nM, respectively, compared to their reference inhibitors. Finally, a molecular docking study highlighted the binding mode disposition and binding interactions with key amino acids as a promising EGFR inhibitor.

Journal Article↗

PubMed2026

Analysis of the molecular mechanism underlying di(2-ethylhexyl) phthalate-induced bladder carcinogenesis via network toxicology and molecular docking approaches: An observational study.

This study aims to investigate the toxicity of di(2-ethylhexyl) phthalate (DEHP) and the potential molecular mechanisms of DEHP-induced bladder cancer (BLCA) using network toxicology and molecular docking strategies. The toxicity of DEHP was assessed using Prox-II software, and potential targets for DEHP-induced BLCA were identified by integrating data from ChEMBL database, Search Tool for Interactions of Chemicals, SwissTargetPrediction, GeneCards, Therapeutic Target Database, Online Mendelian Inheritance in Man, and The Cancer Genome Atlas. STRING database and Cytoscape were employed to construct target networks and determine core targets. The expression levels of core targets were analyzed using R. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed on potential and core targets. Molecular docking was carried out using CB-Dock 2 to verify the interactions between DEHP and core targets. A total of 105 potential targets related to DEHP-induced BLCA were identified, from which 7 core targets were selected: cyclin-dependent kinase 1, interleukin 6, cyclin-dependent kinase 2, cyclin B1, Erb-B2 receptor tyrosine kinase 2, cyclin B2, and B-cell lymphoma 2. IL-6 and B-cell lymphoma 2 showed downregulated expression in tumor tissues, while cyclin-dependent kinase 1, cyclin-dependent kinase 2, cyclin B1, Erb-B2 receptor tyrosine kinase 2, and cyclin B2 were upregulated. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses indicated that these targets were enriched in cell signaling and cancer-related pathways. Molecular docking confirmed that DEHP interacts with these core targets. DEHP may promote the development of BLCA by interacting with key proteins and signaling pathways. This study provides a theoretical basis for understanding the molecular mechanisms of DEHP-induced BLCA and offers references for future prevention and treatment strategies.

Diethylhexyl Phthalate↗

PubMed2025

Network pharmacology-based study on the mechanism of Tangfukang formula against type 2 diabetes mellitus.

OBJECTIVE: To explore the mechanism of Tangfukang formula (, TFK) in treating type 2 diabetes mellitus (T2DM). METHODS: We employed network pharmacology combined with experimental validation to explore the potential mechanism of TFK against T2DM. Initially, we filtered bioactive compounds with the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and Symptom Mapping (SymMap), and gathered targets of TFK and T2DM. Subsequently, we constructed a protein-protein interaction (PPI) network, enriched core targets through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), and adopted molecular docking to study the binding mode of compounds and the signaling pathway. Finally, we employed a KKAy mice model to investigate the effect and mechanism of TFK against T2DM. Biochemical assay, histology assay, and Western blot (WB) were used to assess the mechanism. RESULTS: There were 492 bioactive compounds of TFK screened, and 1226 overlapping targets of TFK against T2DM identified. A compound-T2DM-related target network with 997 nodes and 4439 edges was constructed. KEGG enrichment analysis identified some core pathways related to T2DM, including adenosine 5-monophosphate-activated protein kinase (AMPK) signaling pathway. Molecular docking study revealed that compounds of TFK, including citric acid, could bind to the active pocket of AMPK crystal structure with free binding energy of －4.8, －8 and －7.9, respectively. Animal experiments indicated that TFK decreased body weight, fasting blood glucose, fasting serum insulin, homeostasis model of insulin resistance, glycosylated serum protein, total cholesterol, triglyceride, and low-density lipoprotein cholesterol, and improve oral glucose tolerance test results. TFK reduced steatosis in liver tissue, and infiltration of inflammatory cells, and protected liver cells to a certain extent. WB analysis revealed that, TFK upregulated the phosphorylation of AMPK and branched-chain α-ketoacid dehydrogenase proteins. CONCLUSION: TFK has the potential to effectively manage T2DM, possibly by regulating the AMPK signaling pathway. The present study lays a new foundation for the therapeutic application of TFK in the treatment of T2DM.

Diabetes Mellitus, Type 2↗

PubMed2026

Exploring the mechanism of the Lianshi Jianpi formula in treating impaired glucose tolerance: a network pharmacology, molecular docking, and experimental validation study.

OBJECTIVE: To explore the bioactive constituents, key targets, signalling pathways, and molecular mechanisms of Lianshi Jianpi formula (, LSJPF) in the treatment of impaired glucose tolerance (IGT) through network pharmacology, molecular docking, and in vivo experiments. METHODS: The active ingredients and targets of LSJPF were identified using the Traditional Chinese Medicine Systems Pharmacology and HERB databases, whereas the IGT-related targets were sourced from GeneCards, DisGeNET, and PubMed. The overlap analysis identified potential targets of LSJPF. Protein-protein interaction networks and core targets were evaluated using the Search Tool for the Retrieval of Interacting Genes/Proteins and Cytoscape, and molecular docking confirmed the binding affinities. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed using Metascape. The therapeutic mechanisms were validated in an animal IGT model. RESULTS: LSJPF contained 229 compounds, with 15 active compounds and 77 potential target proteins. The phosphatidylinositol-3-kinase (PI3K)-protein kinase B (AKT) signalling pathway emerged as a key IGT pathway. The KEGG enrichment analysis revealed the pivotal genes RAC-alpha serine/threonine-protein kinase (AKT1), heat shock protein 90 kDa alpha B1, and B-cell lymphoma 2 family protein, which predominantly interact with beta-sitosterol and beta-carotene, the major constituents of Semen Euryales, Semen lablab Album, Semen sojae Atricolor in LSJPF. Molecular docking revealed strong binding affinities between LSJPF and IGT-related targets. In an animal IGT model, LSJPF treatment prevented weight loss; reduced food and water intake; decreased blood glucose levels; improved insulin resistance; decreased serum triglyceride, cholesterol, and low-density lipoprotein cholesterol levels; alleviated liver pathology; and significantly increased the levels of phosphorylated adenosine 5'-monophosphate-activated protein kinase (AMPK), PI3K, and AKT, suggesting its potential role in regulating glucose and lipid metabolism. CONCLUSIONS: These findings reveal the potential of LSJPF as an IGT intervention that targets the AMPK/PI3K/AKT cascade, validating network pharmacology predictions and highlighting the role of multipathway mechanisms in metabolic diseases.

Molecular Docking Simulation↗

PubMed2026

Multitarget interactions of bisphenol A in polycystic ovary syndrome: evidence from integrated network toxicology, mendelian randomization, and molecular docking.

OBJECTIVE: To study the potential pathogenic mechanisms of bisphenol A (BPA) in polycystic ovary syndrome (PCOS) using an integrative computational strategy. DESIGN: Integrative computational study combining network toxicology, Mendelian randomization (MR), and molecular docking. SUBJECTS: For MR analysis, genetic data were sourced from large European-ancestry cohorts, including plasma protein quantitative trait loci data and genome-wide association study summary statistics for PCOS (3,045 cases and 267,780 controls). EXPOSURE: In silico exposure to BPA for target prediction; genetically predicted plasma protein levels for causal inference. MAIN OUTCOME MEASURES: Identification of overlapping targets between BPA and PCOS; functional enrichment pathways; causal effects of prioritized proteins on PCOS risk (odds ratios with 95% confidence intervals); binding affinities between BPA and core targets (kcal/mol). RESULTS: Network toxicology identified 310 overlapping targets between BPA and PCOS. Enrichment analyses revealed significant involvement in endocrine signaling, inflammatory pathways (eg, IL-17), and cellular processes. MR demonstrated that genetically elevated levels of RET, CXCL8, HTR6, MMP1, MMP9, NTRK1, and TNNI2 were significantly associated with increased PCOS risk, whereas higher PSAP and SHBG levels were protective. Molecular docking confirmed stable binding between BPA and all nine key targets, with strongest affinity for SHBG (-8.4 kcal/mol), followed by NTRK1, TNNI2, and RET. CONCLUSION: This integrative investigation suggests that BPA may contribute to PCOS pathogenesis through multitarget interactions involving inflammatory mediators, endocrine regulators, and tissue remodeling proteins. The findings provide prioritized targets and mechanistic insights for future experimental validation and environmental risk assessment.

Female↗

PubMed2023

Structural and functional insights into a novel homozygous missense pathogenic variant in CUL7 identified in consanguineous Pakistani family.

3M syndrome is a rare genetic familial disorder characterized by short stature, growth retardation, facial dysmorphism, skeletal abnormalities, fleshy protruding heels, and normal intelligence, caused by mutations in the CUL7, OBSL1 and CCDC8 genes. In the present study, a novel homozygous missense variant of CUL7 (NP_001161842.1, c.4493T > C, p.L1498P) has been identified in a consanguineous Pakistani family by whole exome sequencing. In silico structural evaluation, molecular docking and simulation studies of mutant CUL7 provides substantial evidence about its crucial role in the progression of discussed ailment. The newly discovered variant significantly altered the protein's three dimensional structure, leading to abnormal interaction with binding proteins. This computational and experimental investigation provides useful information to drug developers for the synthesis of novel therapeutics against the discussed ailment.Communicated by Ramaswamy H. Sarma.

Humans↗

PubMed2026

Computational discovery of emodin-based anthraquinones as PARP-1 inhibitors with relevance to ovarian and prostate cancer.

Cancer is a disease characterized by genomic instability and aberrant DNA repair. Poly (ADP-ribose) polymerase-1 (PARP-1) represents a well-established therapeutic target, particularly in ovarian and prostate cancer. However, the currently approved PARP inhibitors face challenges such as resistance, toxicity, and reduced efficacy. The search for alternative scaffolds has therefore become increasingly urgent. In this study, we used an integrated approach combining computer-aided methods to search for potential lead compounds among emodin-based anthraquinone derivatives as PARP-1 inhibitors. Using a PASS-based QSAR approach, drug-likeness prediction, and in silico ADMET assessment, we pre-screened a large set of anthraquinones and identified several potential hits for interaction with PARP-1. These hits were studied using molecular docking with the PARP-1 catalytic domain (PDB ID: 7KK4). The most stable and compact complexes were further explored by 500 ns molecular dynamics (MD) simulations and various dynamic properties (RMSD, RMSF, Rg, SASA, MolSA, hydrogen bonds, PCA, DCCM). The key finding of this study is that several emodin-derived anthraquinones exhibited binding behavior and ADMET profiles comparable to, or better than, the reference PARP-1 inhibitor. Among them, CID-10425624 emerged as the most promising candidate, exhibiting stable binding, reduced conformational fluctuation, compact complex formation, persistent hydrogen-bond interactions, and enhanced dynamic residue correlations within the PARP-1 catalytic domain. These findings suggest that the anthraquinone scaffold can provide a valuable starting point for developing structurally distinct PARP-1 inhibitors. In summary, this study identified several emodin-derived anthraquinones, particularly CID-10425624, as computationally prioritized lead candidates for PARP-1 inhibition, providing a novel anthraquinone-based scaffold for further experimental validation and optimization.

Anthraquinones↗

PubMed2026

Molecular docking, molecular dynamics simulation, and enzyme inhibitory studies of vitamin K family members on aldose reductase.

Aldose reductase (AR) is a key enzyme in the polyol pathway and plays a major role in the progression of secondary complications of diabetes. Despite extensive efforts to develop natural and synthetic aldose reductase inhibitors (ARIs), most candidates have shown limited clinical efficacy, highlighting the need for more potent and selective inhibitors. In this study, we have systematically evaluated the inhibitory potential of vitamin K family members (vitamin K1, vitamin K2, and vitamin K3) using molecular docking, protein-ligand interaction analysis, molecular dynamics simulations, and enzyme kinetics. Docking analysis predicted that vitamin K2 has the highest binding affinity for AR. Subsequent molecular dynamics simulations revealed that both vitamin K1 and vitamin K2 formed stable complexes with the protein, exhibiting comparable RMSD (∼0.5 Å difference), similar RMSF profiles, and reduced radius of gyration, indicating compact and stable binding. Interaction analysis demonstrated that ligand binding is predominantly driven by hydrophobic interactions, with vitamin K2 forming a higher number of hydrophobic contacts, while vitamin K1 exhibited slightly more hydrogen bonding. Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) results further supports stronger binding of vitamin K2 (-56 kcal/mol) compared to vitaminK1 (-51 kcal/mol). Consistent with these findings, enzyme kinetics showed a slightly lower Ki value for vitamin K2 than vitamin K1. In contrast, vitamin K3 failed to maintain stable binding and moved out of the active site during simulation. Overall, the study highlights that hydrophobic interaction-driven stabilization plays a key role in ligand binding, and identifies vitamin K1 and vitamin K2 as promising inhibitors against AR, with vitamin K2 exhibiting more favourable hydrophobic interactions and binding stability.

Aldose Reductase↗

PubMed2026

The Mechanism of Celosiae Semen in the Treatment of Diabetic Cataract: Based on Network Pharmacology.

INTRODUCTION: Diabetes mellitus can be complicated by a variety of ocular diseases, among which the postoperative complications of diabetic cataract (DC) are significantly higher than those of non-DC patients. Therefore, finding drugs with natural active ingredients is an urgent challenge in the prevention and treatment of DC. Discovering the potential molecular mechanism of celosiae semen (CS) for the treatment of DC and providing new ideas and programs for the treatment and prevention of DC. METHODS: In this study, network pharmacology, molecular docking, and molecular dynamics simulations were utilized to predict the binding and functional enrichment of the main active ingredients of CS with DC-related targets, and to explore the potential pathways and mechanisms of CS for the treatment of DC. RESULTS: Through database searching and screening, a total of 45 potential targets of CS for the treatment of DC were identified, functionally enriched, and a protein-protein interaction network was constructed, and the key target, SRC, was finally found. The results of molecular docking and molecular dynamics simulation showed that the main active ingredient of CS, stigmasterol, could bind stably to the key target SRC protein. DISCUSSION: This study not only elucidates the phyto-pharmacological basis of CS in DC management but also provides a framework for developing natural product-derived targeted therapies against diabetic ocular complications. The integration of modern genomics and computational chemistry to deconstruct the therapeutic effects of traditional Chinese herbal medicines has great clinical significance in expanding the scope of traditional Chinese medicines for the treatment of DC and promoting precision targeting. However, this requires verification through basic experiments. CONCLUSION: These computational findings suggest that CS may exert its anti-cataract effects through the multi-target modulation of diabetic metabolic pathways and SRC-mediated signaling cascades.

Humans↗