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PubMed2026

Validating the potential mechanism and therapeutic effect of Qinlian Jiangxia decoction in the treatment of type 2 diabetes mellitus complicated with hyperlipidemia through network pharmacology, molecular docking, molecular dynamics simulation, andexperiments.

OBJECTIVE: To investigate the mechanism of action of Qinlian Jiangxia decoction (, QLJXD) in the treatment of type 2 diabetes mellitus (T2DM) complicated by hyperlipidemia using network pharmacology, molecular docking, molecular dynamics simulation and in vivo experiments. METHODS: Drug components, targets and disease targets were identified using databases such as TCM systems pharmacology database and analysis platform and GeneCards. The intersecting targets were subjected to protein-protein interaction analysis using the search tool for the retrieval of interacting genes/proteins database. Subsequently, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis of the intersecting targets were conducted using the Metascape platform to identify core components and targets. The results were validated using molecular docking, molecular dynamics simulations and in vivo experiments. RESULTS: QLJXD contains 76 active ingredients and 136 disease targets. The core ingredients are quercetin, β-sitosterol, wogonin and baicalein, while the core targets are fatty acid binding protein 4 (FABP4) and peroxisome proliferative activated receptor gamma (PPARG). Molecular docking and molecular dynamics simulations revealed that the core ingredients bound well to the core targets. Animal experiments demonstrated that QLJXD effectively inhibited the expression of FABP4 and increased the expression of PPARG, thereby enhancing disorders of glycolipid metabolism. CONCLUSION: The putative therapeutic efficacy of QLJXD in the management of T2DM complicated with hyperlipidemia may be ascribed to the synergistic actions of multiple components, such as quercetin, β-sitosterol, wogonin, and baicalein, which collectively modulate FABP4 and PPARG molecular targets.

Molecular Docking Simulation↗

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

A Computational Workflow for Prioritizing Microbial Metabolite-Associated Host Genes in Constipation-Predominant Irritable Bowel Syndrome.

No standardized computational pipeline exists for systematically prioritizing microbial metabolite-associated host genes and protein-ligand complexes from publicly available chemical, genomic, and structural databases. This article describes an eight-stage workflow that accepts a user-defined set of gut microbiota-derived metabolites and produces a ranked shortlist of candidate metabolite-associated host genes, enriched biological pathways, and structurally prioritized protein-ligand complexes for experimental follow-up. The pipeline integrates (i) chemoinformatic metabolite profiling; (ii) multi-database candidate target prediction using protein-chemical interaction and ligand-based target-prediction tool and a molecular docking program; (iii) differential gene expression analysis of publicly available transcriptomic data; (iv) target-differentially expressed gene overlap; (v) protein-protein interaction network construction and pathway enrichment; (vi) molecular docking with a molecular docking program; (vii) 200 ns molecular dynamics simulation using a molecular dynamics engine with a protein force field used for molecular dynamics simulations; and (viii) MM-PBSA binding free-energy estimation. As a worked example, nine gut microbiota-derived or microbiota-modified metabolites representing short-chain fatty acids, bile acids, tryptophan-derived metabolites, and urolithin A were processed using the public IBS-C rectal mucosal transcriptomic dataset GSE36701. The workflow ranked 17 unique predicted metabolite-associated genes that were differentially expressed in this dataset. Docking, molecular dynamics simulation, and MM-PBSA analyses structurally prioritized five metabolite-protein complexes: lithocholic acid-VDR, lithocholic acid-NR1H4/FXR, ursodeoxycholic acid-NR1H4/FXR, tryptamine-HTR2A (simulated in an explicit 1-Palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) lipid bilayer), and urolithin A-CASP3. The protocol is designed to be adaptable to other metabolite sets, disease transcriptomic datasets, and target classes; all outputs are hypothesis-generating computational predictions that require independent transcriptomic replication, protein-level validation, and functional ligand-response assays before causal or therapeutic conclusions can be drawn.

Irritable Bowel Syndrome↗

PubMed2026

Multiomics approaches reveal direct NF-κB p65 target genes in pancreatic islets during cytokine exposure and in type 1 diabetes.

Autoimmune diseases, including Type 1 diabetes (T1D), are often characterized by overactive inflammatory signaling pathways. The proinflammatory cytokine interleukin-1β (IL-1β) elicits global gene expression changes in islet β-cells which overlap with islets obtained from human donors with T1D. The direct transcriptional link between NF-κB subunit p65 and target genes involved with autoimmune events was investigated. We used a multiomics approach including bulk RNA-sequencing (RNA-Seq), single-cell RNA-sequencing (scRNA-Seq), and chromatin immunoprecipitation coupled to deep sequencing (ChIP-Seq), alongside molecular docking simulations, and transcriptional assays. Through the various experimental modalities, we identified early response genes driven by IL-1β that were differentially expressed in pancreatic islets from human T1D donors and also conserved across mouse, rat, and human tissues. ChIP-Seq revealed genes that are direct genomic targets of the NF-κB p65 transcription factor. Moreover, regions that gained RNA polymerase II binding following cellular exposure to IL-1β were identified, complementing the early response gene profile induced by β-cell exposure to IL-1β. Molecular docking simulations predicted that mutations reducing p65 transcriptional capacity do not alter DNA binding ability. These findings clearly show that IL-1β signaling in pancreatic β-cells directs p65 to specific genomic regions congruent with increased gene expression relevant to T1D in β-cell lines as well as mouse and human islets exposed to cytokines. Islets from human donors with T1D express genes identified as direct p65 targets using unbiased approaches, implicating heightened NF-κB activity as a critical component of autoimmune disease etiology.NEW & NOTEWORTHY Using multiple Seq-based approaches, this study identified genes expressed in human pancreatic tissue from donors with Type 1 diabetes that are regulated acutely by exposure to the cytokine interleukin-1beta. The NF-kB transcription factor p65 (RelA) was determined via ChIP-Seq to be a major control node regulating this immediate early response. These collective datasets are consistent with a paradigm of overactive NF-kB signaling as a critical component of autoimmunity in both rodents and humans.

Humans↗

PubMed2026

Screening of core targets for Di(2-ethylhexyl) Phthalate-related gastric cancer based on machine learning, molecular docking, and SHAP analysis.

PURPOSE: Given the existing uncertainties regarding the link between Di(2-ethylhexyl) phthalate (DEHP) exposure and gastric cancer (GC) progression, this study aimed to clarify their association, identify the toxic targets of DEHP, and elucidate the underlying molecular mechanisms. METHODS: Multiple integrated approaches were employed, including Gene Expression Omnibus (GEO) data analysis, network toxicology, molecular docking, and machine learning. STRING and Cytoscape tools were utilized to identify key targets, while Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to explore the functional enrichment of intersecting targets. Machine learning and SHAP analysis were applied to screen core targets in GC. Molecular docking was performed to evaluate the binding affinity of DEHP toward core targets, and 200 ns molecular dynamics simulations were further conducted for representative complexes to validate their dynamic stability. RESULTS: A total of 18 key targets were identified using STRING and Cytoscape. GO and KEGG enrichment analyses demonstrated that these intersecting targets were primarily enriched in the extracellular region, as well as the Calcium signaling pathway and cAMP signaling pathway. Through machine learning analyses, 7 key genes (ADRB2, ESRRG, GRIA4, IL13RA2, NR3C2, PLA2G1B, and SULT2A1) were identified as core targets in GC through machine learning analyses. Molecular docking simulations revealed strong binding specificity between DEHP and the target proteins. Among them, NR3C2 and ADRB2 exhibited relatively high predictive importance in the machine learning models. DEHP showed favorable binding affinity toward these core targets, and molecular dynamics simulations further confirmed that ADRB2-DEHP and NR3C2-DEHP complexes maintained stable conformations throughout the simulation. CONCLUSIONS: Our findings identified GC associated genes that were computationally predicted as potential targets of DEHP. These results indicated structural compatibility between DEHP and its target proteins but did not prove that DEHP exposure accounts for the gene expression changes in GC.

Molecular Docking Simulation↗

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↗

PubMed2026

Leveraging bioinformatics approaches for drug repositioning in space radiation protection.

The health effects of space radiation, primarily Galactic Cosmic Rays (GCRs), on humans remain largely unknown, with potential cardiovascular consequences posing a significant threat to astronauts on long-duration spaceflight missions. Currently, there are no established pharmacological countermeasures for GCR exposure. Drug repositioning offers a promising strategy to accelerate pharmaceutical research in space medicine. This study leverages existing bioinformatics techniques to identify and prioritize potential drug candidates associated with proteomic perturbations following simulated GCR exposure using previously published murine cardiac proteomic data. A protein-protein interaction (PPI) network was constructed using the top differentially expressed proteins (DEPs) from murine heart tissue following exposure to 5-ion GCRs as seed nodes, focusing on experimentally supported interactions. Network topology, Markov clustering, and functional enrichment analyses were used to characterize biologically relevant proteins and pathways. Drug-protein interactions were predicted using Drugst.One and mapped to PPI clusters of interest to identify candidate drugs. Selected drug-macromolecule interactions were further explored using CB-Dock2 molecular docking and short-duration molecular dynamics simulations as hypothesis-generating structural assessments. Analysis of a key PPI network cluster consisting of several ATP synthase proteins identified 23 unique drug candidates. These analyses demonstrate a systematic approach for leveraging bioinformatics techniques to identify candidate molecular targets and generate pharmacological hypotheses in the context of space radiation countermeasures. Ultimately, this strategy introduces a hypothesis-generating framework for the prioritization of potential drug candidates for future computational characterization and experimental investigation against spaceflight stressors.

Animals↗

PubMed2026

Integrated bioinformatics analysis reveals cross-talking hub genes and therapeutic agents between sepsis and acute myocardial infarction.

BACKGROUND: Sepsis and acute myocardial infarction (AMI) are two significant diseases that may share overlapping etiological mechanisms. This study aims to systematically identify core genes common to both conditions and to explore their potential as therapeutic targets and drug candidates through an integrative analysis of clinical data and bioinformatics. METHODS: The AMI dataset was obtained from the GEO database, and RNA sequencing data were collected from blood samples of patients with sepsis at our hospital. Common genes were identified using differential expression gene analysis (DEG) and weighted gene co-expression network analysis (WGCNA). Functional enrichment analyses, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, were performed. A protein-protein interaction (PPI) network was constructed, and hub genes were identified using the MCC/Degree algorithm. Diagnostic value was assessed via receiver operating characteristic curve analysis. Immune infiltration patterns, single-cell sequencing data, and molecular docking simulations were employed to evaluate immune relevance and identify potential therapeutic compounds. RESULTS: A total of 417 genes were identified between sepsis and AMI, with enrichment analysis revealing significant involvement in inflammatory responses. Three hub genes-JAK2, MYD88, and TIMP1-were selected for further investigation. ROC curves confirmed their strong diagnostic performance for both diseases. Immune infiltration analysis showed that these core genes were significantly correlated with the infiltration levels of various immune cell types. Molecular docking indicated that quercetin exhibited stable binding affinity with the proteins encoded by these genes. qPCR validation further confirmed the upregulation of these three genes, supporting the anti-inflammatory effects of quercetin as a potential targeted therapy. CONCLUSION: JAK2, MYD88, and TIMP1 were identified as shared core genes in sepsis and AMI. These genes not only serve as potential diagnostic biomarkers but also offer novel targets for developing common therapeutic strategies for both conditions. Furthermore, quercetin emerges as a promising candidate for targeted treatment.

Humans↗

PubMed2026

Matrine Alleviates Sepsis-Induced Acute Lung Injury by Reinforcing NQO1/SLC7A11/GPX4-Associated Anti-Ferroptotic Defenses and Attenuating NF-κB-Driven Inflammation.

BACKGROUND: Sepsis triggers dysregulated systemic inflammation and multiple-organ dysfunction, with the lungs being particularly susceptible to injury. Sepsis-induced acute respiratory distress syndrome (ARDS) is mainly driven by TLR4/NF-κB-mediated hyperinflammation and alveolar macrophage activation. Matrine, a bioactive alkaloid derived from Sophora flavescens, has been reported to modulate redox homeostasis and ferroptosis-associated lipid peroxidation. However, the target-specific mechanisms underlying its effects on ferroptosis and inflammatory signaling in sepsis-induced acute lung injury (SALI) remain incompletely understood. PURPOSE: This study aimed to evaluate the therapeutic effects of matrine in a cecal ligation and puncture (CLP)-induced SALI model and to determine whether its protective effects involve reinforcement of NQO1/SLC7A11/GPX4-associated anti-ferroptotic defenses and suppression of NF-κB-driven inflammation. METHODS: We analyzed the single-cell RNA-sequencing (scRNA-seq) dataset GSE273924 to characterize CD45-enriched pulmonary immune-cell subsets in sham mice and mice with intratracheal Escherichia coli-induced pneumonia. Network pharmacology and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to predict Kushen (KS)-related targets and pathways associated with SALI. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) of GSE245013 were used to identify candidate targets. Matrine-NQO1 binding and intracellular target engagement were evaluated using molecular docking, molecular dynamics simulations, surface plasmon resonance (SPR), and the cellular thermal shift assay (CETSA). The therapeutic effects of matrine were assessed in mice with CLP-induced SALI and in lipopolysaccharide (LPS)-stimulated MH-S cells. Lung histopathology, inflammatory cytokine production, target protein expression, ferroptosis-associated indicators, and NF-κB activation were evaluated using molecular, biochemical, and histological assays. The functional contribution of NQO1 was further examined using the NQO1 inhibitor ES936. RESULTS: scRNA-seq analysis of GSE273924 revealed substantial remodeling of the CD45-enriched pulmonary immune-cell landscape in mice with intratracheal E. coli-induced pneumonia, including macrophage transcriptional programs associated with ferroptosis and inflammatory signaling. Integrated network pharmacology and bioinformatics analyses prioritized NQO1 as a candidate target of matrine and identified NF-κB signaling as a potentially relevant pathway. Molecular docking, molecular dynamics simulations, SPR, and CETSA supported matrine-NQO1 binding and intracellular target engagement. Functionally, matrine improved survival, attenuated lung injury, reinforced NQO1/SLC7A11/GPX4-associated anti-ferroptotic defenses, and suppressed NF-κB activation in CLP mice. Similar protective effects were observed in LPS-stimulated MH-S cells. ES936 partially attenuated the matrine-mediated improvements in cell viability, redox homeostasis, ferroptosis-associated indicators, and NF-κB p65 phosphorylation, supporting a functional contribution of NQO1 to the protective effects of matrine. CONCLUSION: Matrine alleviates SALI by reinforcing NQO1/SLC7A11/GPX4-associated anti-ferroptotic defenses and attenuating NF-κB-driven inflammation.

Animals↗

PubMed2025

Caffeic acid phenethyl ester protects renal tubular epithelial cells against ferroptosis in diabetic kidney disease via restoring PINK1-mediated mitophagy.

Mounting evidence indicates that renal tubular ferroptosis plays a crucial role in the progression of diabetic kidney disease (DKD). Caffeic acid phenethyl ester (CAPE), derived from propolis, a precious resinous substance synthesized by various bee species, has garnered broad attention in biomedical research. This study aims to explore the mechanism by which CAPE protects renal tubular epithelial cells (TECs) against ferroptosis in DKD. DBA/2J mice were administered streptozotocin (STZ) by intraperitoneal injection, fed a high-fat diet (HFD) and treated with CAPE. The findings revealed significant changes in ferroptosis markers. In diabetic mice and TECs under high-glucose (HG) conditions, levels of glutathione peroxidase 4 (GPX4) and solute carrier family 7 member 11 (SLC7A11) decreased, while transferrin receptor 1 (TFR1) increased. These changes were accompanied by a reduction in antioxidant capability and the accumulation of malondialdehyde (MDA). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses showed that the intersection targets of CAPE and ferroptosis were mainly located in the mitochondria and exhibited high enrichment values in mitophagy. Further investigations revealed that HG induced a depolarization of mitochondrial membrane potential and an excessive level of mitochondrial reactive oxygen species (ROS), accompanied by defective mitophagy. The administration of CAPE inhibited exacerbated ferroptosis and rescued defective mitophagy induced by DKD. In addition, CAPE restored PTEN-induced putative kinase 1 (PINK1) levels, which were markedly diminished in the kidneys of DKD mice and TECs subjected to HG. Molecular docking simulation experiments suggested that CAPE is steadily bound to the PINK1 active pocket. Cellular Thermal Shift Assay (CETSA) and Drug Affinity Responsive Target Stability assay (DARTS) showed that CAPE enhances the thermal stability of the PINK1 protein within a specific temperature range and protects the PINK1 protein from degradation by proteolytic enzymes. These results confirm that CAPE interacts with PINK1 as its specific target. However, the positive outcomes of CAPE treatment on ferroptosis were nullified by the PINK1 siRNA. This research indicates that CAPE has potential therapeutic benefits for DKD by protecting renal TECs against ferroptosis via rescuing PINK1-mediated mitophagy. These findings suggest that CAPE shows potential as a therapeutic agent to prevent tubular injury in DKD.

Animals↗

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↗

PubMed2026

Zhiling Jiangya decoction treats hypertension in rats: An integrative study of network pharmacology, immune infiltration, molecular simulation, and 16S rDNA sequencing.

OBJECTIVE: This study integrated network pharmacology, immune infiltration analysis, molecular docking, molecular dynamics simulation, ADMET prediction, 16S rDNA sequencing, and rat experiments to elucidate the potential mechanisms underlying the antihypertensive effects of Zhiling Jiangya Decoction (ZLJYD). METHODS: Active compounds and their potential targets were screened from the PubChem, TCMSP, NovoPro, and SwissTargetPrediction databases. Hypertension-related targets were retrieved from the OMIM and GeneCards databases, and overlapping targets were identified. The STRING database and Cytoscape 3.10.1 software were used to construct a protein-protein interaction network and a herb-component-target-disease network. Gene Ontology functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis were performed to identify the key biological processes and signaling pathways involved. Using the CIBERSORT algorithm combined with correlation analysis, we investigated the association between key targets and immune cell infiltration. Molecular docking, molecular dynamics simulations, and ADMET predictions were performed to assess the binding stability and pharmacokinetic properties of the main compounds with their corresponding targets. Finally, the antihypertensive efficacy of ZLJYD was validated using a spontaneously hypertensive rat model, and alterations in gut microbiota were analyzed using 16S rDNA sequencing. RESULTS: A total of 123 active compounds and 267 hypertension-related targets of ZLJYD were identified. Enrichment analysis revealed that these targets were primarily associated with the PI3K-Akt signaling pathway and lipid and atherosclerosis pathways. Immune infiltration analysis suggested that the therapeutic effects of ZLJYD may involve the regulation of follicular helper T cells, naïve B cells, and naïve CD4⁺ T cells. Molecular docking and dynamics simulations supported the stable binding of key compounds to their target proteins, while ADMET predictions indicated favorable pharmacokinetic properties and safety profiles. Rat experiments demonstrated that ZLJYD significantly reduced blood pressure in spontaneously hypertensive rats, partially alleviated gut microbiota dysbiosis, and altered microbial community structure and phylogenetic diversity. CONCLUSION: This study systematically elucidates the potential mechanisms underlying the antihypertensive effects of ZLJYD through multiple components, targets, and pathways, particularly immune regulation and gut microbiota remodeling. These findings provide mechanistic insights into its potential therapeutic application.

16S rDNA sequencing↗

PubMed2023

Discussion on the mechanism of Lingguizhugan Decoction in treating hypertension based on network pharmacology and molecular simulation technology.

To explore the mechanism of Lingguizhugan Decoction in treating hypertension based on network pharmacology and molecular simulation. The active ingredients and potential targets were screened by the Systematic Pharmacological Analysis Platform of Traditional Chinese Medicine (TCMSP). Hypertension-related targets were obtained from OMIM and GeneCards databases. Common targets between drug and hypertension were screened in the Venny platform. A protein-protein interaction (PPI) network was constructed in the STRING database using intersection targets. Key targets in PPI network were analyzed by Cytoscape. R language program was used for Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Finally, the binding abilities of the main active ingredients to critical targets were verified by molecular simulation. Naringenin, quercetin, kaempferol, and β-sitosterol in Lingguizhugan Decoction, and potential targets such as STAT3, AKT1, TNF, IL6, JUN, PTGS2, MMP9, CASP3, TP53, and MAPK3, were screened out. KEGG Enrichment analysis revealed that the common targets of Lingguizhugan Decoction and hypertension are mainly involved in the lipid and atherosclerosis signaling pathway, AGE-RAGE signaling pathway in diabetic complications, fluid shear stress and atherosclerosis, and IL17 signaling pathway. The molecular simulation results showed that naringenin-MAPK3, quercetin-MMP9, quercetin-PTGS2, and quercetin-TP53 were the top four in the docking scores. Naringenin-MAPK3 and quercetin-MMP9 were stable, with binding free energies of -27.97 ± 1.41 kcal/mol and -21.15 ± 3.17 kcal/mol, respectively. The possible mechanism of Lingguizhugan Decoction in treating hypertension is characterized of multi-component, multi-target, and multi-pathway.Communicated by Ramaswamy H. Sarma.

Network Pharmacology↗

PubMed2025

Exploring effector protein dynamics and natural fungicidal potential in rice blast pathogen Magnaporthe oryzae.

Rice blast, caused by Magnaporthe oryzae, is one of the most destructive fungal diseases in rice, resulting in major economic losses worldwide. Genetic and genomic studies have identified key genes and proteins, such as AvrPik variants and MAX proteins, that are crucial for the pathogen's virulence. These effector proteins interact with specific alleles of the Pik gene family on rice chromosome 11, modulating the host's immune response. In this study, we investigated 35 plant-derived metabolites known for their antifungal properties as potential fungicides against M. oryzae. Using molecular docking, we identified Hecogenin and Cucurbitacin E as strong binders to MAX40 and APIKL2A proteins, which are essential for the fungus's immune evasion and pathogenicity. Molecular dynamics simulations further confirmed that these compounds form stable, strong interactions with the target proteins, validating their potential as therapeutic agents. Additionally, the compounds were evaluated based on Lipinski's rule of five and toxicity predictions, indicating their suitability for agricultural use. These results suggest that Hecogenin and Cucurbitacin E could serve as promising lead candidates in the development of novel fungicides for rice blast, offering new strategies for crop protection and sustainable agricultural practices.

Oryza↗

PubMed2025

Genetic targets related to aging for the treatment of coronary artery disease.

BACKGROUND: Coronary Artery Disease (CAD) is the most common cardiovascular disease worldwide, threatening human health, quality of life and longevity. Aging is a dominant risk factor for CAD. This study aims to investigate the potential mechanisms of aging-related genes and CAD, and to make molecular drug predictions that will contribute to the diagnosis and treatment. METHODS: We downloaded the gene expression profile of circulating leukocytes in CAD patients (GSE12288) from Gene Expression Omnibus database, obtained differentially expressed aging genes through "limma" package and GenaCards database, and tested their biological functions. Further screening of aging related characteristic genes (ARCGs) using least absolute shrinkage and selection operator and random forest, generating nomogram charts and ROC curves for evaluating diagnostic efficacy. Immune cells were estimated by ssGSEA, and then combine ARCGs with immune cells and clinical indicators based on Pearson correlation analysis. Unsupervised cluster analysis was used to construct molecular clusters based on ARCGs and to assess functional characteristics between clusters. The DSigDB database was employed to explore the potential targeted drugs of ARCGs, and the molecular docking was carried out through Autodock Vina. Finally, single-cell data (GSE159677) of arterial intima was used to further explore the expression of aging signature genes in different cell subpopulations. RESULTS: We identified 8 ARCGs associated with CAD, in which HIF1A and FGFR3 were up while NOX4, TCF7L2, HK3, CDK18, TFAP4, and ITPK1 were down in CAD patients. Based on this, CAD patients can be divided into two molecular clusters, among which cluster A mainly involves functional pathways such as ECM receptor interaction and focal adhesion; cluster B mainly involves functional pathways such as amimo sugar and nucleotide sugar metabolism and pyrimidine metabolism. In addition, the molecular docking results showed that retinoic acid and resveratrol had good binding affinity with targets genes. Further single-cell analysis results showed that NOX4, TCF7L2, ITPK1, and HIF1A were specifically expressed in different types of cells in atherosclerotic tissues. CONCLUSION: Our study identified several ARCGs that may be involved in the pathogenesis and progression of CAD. Further, retinoic acid and resveratrol were potential candidate molecule drugs for inhibiting these targets.

Humans↗

PubMed2026

Direct targeting of ORAI1 by ginsenoside Rg3 modulates calcium signaling and senescence-associated AMPK-NRF2 activation.

BACKGROUND: 20(S)-ginsenoside Rg3 (Rg3(S)), a major saponin derived from red ginseng, exhibits diverse biological activities, including antioxidant and anti-senescence effects. However, the direct molecular targets through which Rg3(S) regulates calcium signaling and its role at membrane contact sites during cellular senescence remain largely unknown. METHODS: Plasma membrane (PM)-endoplasmic reticulum (ER) contacts and related protein interactions were analyzed using proximity ligation assays and co-immunoprecipitation. Direct binding of Rg3(S) to ORAI1 was validated using cellular thermal shift assays and microscale thermophoresis. Molecular docking simulations followed by site-directed mutagenesis were used to define critical binding residues. Cytosolic calcium levels and cellular senescence were assessed using calcium imaging and senescence-associated β-galactosidase staining. RESULTS: Rg3(S) increased cytosolic calcium levels independently of ER calcium depletion and was accompanied by a reduction in PM-ER contacts. Rg3(S) directly bound to ORAI1 in a dose-dependent manner, identifying ORAI1 as a previously unrecognized molecular target of ginsenoside Rg3. Molecular docking revealed LYS204 and ILE229 within the extracellular loop of ORAI1 as key residues maintaining this interaction. Mutation of these residues abolished Rg3(S)-induced calcium influx, leading to impaired activation of the AMPK-NRF2 pathway and attenuation of the anti-senescence effect of Rg3(S). CONCLUSION: These findings identify ORAI1 as a key molecular mediator of ginsenoside Rg3(S)-induced calcium signaling linked to cellular senescence. By modulating PM-ER contact sites and cytosolic calcium dynamics, Rg3(S) attenuates senescence, providing new mechanistic insight into the anti-aging potential of ginseng-derived compounds beyond autophagy-centered pathways.

Calcium signaling↗

PubMed2026

Multimodal Analysis Reveals Aberrant Expression of SUMO2 and Its Significant Association With Key Mechanisms of Metabolic Pathways in Hepatocellular Carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related deaths worldwide. However, the role of small ubiquitin-like modifier 2 (SUMO2), a core member of the small ubiquitin-like modifier (SUMO) family, regarding its expression patterns and metabolism-related functions in HCC remains inadequately understood. METHODS: A multidimensional analytical framework was applied, integrating immunohistochemistry (153 HCC vs. 21 non-HCC samples), proteomics (159 paired samples), bulk transcriptomics (3240 HCC vs. 2267 non-HCC samples), single-cell RNA sequencing (RNA-seq) (10 HCC vs. 8 non-HCC samples), spatial transcriptomics, and external CRISPR/Cas9 functional genomics data. Systematic analyses included standardized mean difference (SMD), pathway enrichment, pseudotime trajectory inference, in silico knockout, cell-cell communication, metabolic flux scoring, immune infiltration, clinical correlation, drug sensitivity prediction, and molecular docking. RESULTS: At the protein level, immunohistochemistry (nuclear positivity) and external proteomic data collectively demonstrated consistent SUMO2 overexpression in HCC. Consistent upregulation was also observed at the mRNA level across large-scale cohorts. Single-cell RNA-seq and spatial transcriptomics localized SUMO2 enrichment to malignant hepatocytes and tumor-dominant regions. CRISPR-mediated SUMO2 knockout suppressed proliferation in multiple HCC cell lines. Mechanistically, high SUMO2 expression was significantly associated with metabolic reprogramming involving glycolysis/gluconeogenesis, pyruvate metabolism, and the tricarboxylic acid cycle. SUMO2-high malignant hepatocyte subpopulations exhibited enhanced activity of the macrophage migration inhibitory factor signaling axis and enhanced iron-sensor interactions. Further, the immune infiltration analysis revealed a negative correlation between SUMO2 expression and M1 macrophages and a positive correlation between follicular helper T cells and regulatory T cells. Clinically, elevated SUMO2 levels were found to be associated with adverse prognostic features. Furthermore, high SUMO2 expression was associated with increased sensitivity to dasatinib, and molecular docking simulations predicted potential binding between SUMO2 and dasatinib, with a Vina score of -8.5 kcal/mol. CONCLUSIONS: SUMO2 is aberrantly expressed at the protein, mRNA, single-cell, and spatial transcriptomic levels in HCC and is significantly associated with metabolic reprogramming and altered migration inhibitory factor (MIF)-mediated intercellular communication, suggesting its potential as a novel biomarker for diagnosis and treatment.

Humans↗

PubMed2026

In silico screening of anti-atherosclerotic compounds from Morus alba leaves by machine learning and network pharmacology.

OBJECTIVE: This study integrates machine learning with network pharmacology, molecular docking, and molecular dynamics simulations to screen bioactive compounds from Mulberry leaves and elucidate their potential mechanisms against atherosclerosis (AS). METHODS: A training dataset of anti-AS active compounds was compiled and encoded as Morgan fingerprints. Three machine learning classifiers, specifically Random Forest (RF), Support Vector Machine (SVM), and Extreme Gradient Boosting (XG-Boost), were constructed and evaluated using multiple performance metrics. Potential active components from Mulberry leaves and AS-related targets were retrieved, followed by protein-protein interaction network construction and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Molecular docking was then performed to evaluate binding affinities between core targets and candidate compounds, and the most stable complex was subjected to molecular dynamics simulations using GROMACS (2025). RESULTS: The RF model achieved superior performance (accuracy= 0.8354, F1 = 0.8408, AUC = 0.9119) with 100% external validation accuracy. Thirteen anti-AS candidates were prioritized from mulberry leaves, four of which have been previously documented. Network pharmacology revealed AKT1 and IL6 as core targets, enriched in pathways such as endocrine resistance. Molecular docking and dynamics simulations confirmed strong binding between oxysanguinarine and AKT1, with the complex exhibiting high stability. CONCLUSION: The RF model provides a reliable computational tool for prioritizing anti-AS compounds from Mulberry leaves. The integrated analysis reveals that Mulberry leaves exert anti-atherosclerotic effects through multi-target (e.g., AKT1, IL6) and multi-pathway (e.g., PI3K-Akt) mechanisms, offering a framework for further experimental validation.

Morus↗