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PubMed2025

Based on network pharmacology, molecular docking, and validation experiments to investigate the active components and mechanisms of action of Tibetan Medog County Citrus medica L.: In antioxidant activity.

BACKGROUND: The antioxidant potential of citrus plants is closely related to their geographical origin, making it crucial to evaluate the natural antioxidant properties of Citrus medica L. (C. medica) from Medog County, Tibet. METHODS: This study systematically investigates the antioxidant mechanisms of C. medica using network pharmacology, molecular docking, and experimental assays. RESULTS: The antioxidant activity experiments showed that C. medica exhibits good bioactivity, and the fruit has better antioxidant activity than the leaves. Network pharmacology revealed 11 active components of C. medica with 1547 antioxidant-related targets. Key targets include TP53, IL6, AKT1, STAT3, and TNF. Gene ontology (GO) analysis identified 1419 biological process entries, 147 cellular component entries, and 306 molecular function entries. Kyoto Encyclopedia of Genes and Genomes analysis identified 212 antioxidant-related signaling pathways. The GO and Kyoto Encyclopedia of Genes and Genomes enrichment analyses showed that the targets are involved in cancer pathways, protein binding, enzyme binding, lipid metabolism, and atherosclerosis. Molecular docking demonstrated that the 11 active components of Medog C. medica exhibit binding energies with core targets TP53, IL6, AKT1, STAT3, and TNF generally less than -5 kcal·mol-1, indicating good affinity. CONCLUSION: This study identifies the excellent antioxidant activity of C. medica from multiple aspects and elucidates its potential antioxidant mechanisms, providing a theoretical basis for the development and application of C. medica as an antioxidant functional additive.

Molecular Docking Simulation↗

PubMed2026

Integrated network pharmacology, molecular docking, and experimental validation to reveal the potential mechanism of Ginsenoside Rg1 on chronic obstructive pulmonary disease.

Ginsenoside Rg1 (GS Rg1), a natural flavonoid exhibiting anti-inflammatory and antioxidant properties, holds significant potential for treatment chronic obstructive pulmonary disease (COPD). Nevertheless, the precise mechanisms underlying its therapeutic effects remain to be fully elucidated. This study aimed to explore the role and potential mechanism of GS Rg1 in the treatment of COPD using network pharmacology, molecular docking, and experimental validation.Targets related to GS Rg1 and COPD were screened from public databases, and the potential common targets were then imported into the STRING database to construct a protein-protein interaction (PPI) network. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis were performed to identify key signaling pathways. Molecular docking was employed to predict the binding interactions between GS Rg1 and core targets. A BEAS-2B cell model induced by lipopolysaccharide(LPS) and cigarette smoke extract(CSE) was used to explore the protective mechanisms of GS Rg1. Western blot analysis was conducted to validate the critical targets and pathways involved in the anti-COPD effects of GS Rg1. Network pharmacology analysis revealed 105 common targets between GS Rg1 and COPD. The EGFR/PI3K/AKT and EGFR/STAT3 signaling pathways were selected for further validation. GS Rg1 was demonstrated to effectively inhibit inflammation and mucus hypersecretion in vitro models of COPD. Western blot results showed that GS Rg1 treatment significantly downregulated the expression of proteins involved in the EGFR/PI3K/AKT and EGFR/STAT3 signaling pathway, consistent with the network pharmacology findings. CSE/LPS exposure induces inflammation and oxidative stress in COPD by disrupting the EGFR/PI3K/AKT and EGFR/STAT3 signaling pathways, and GS Rg1 significantly alleviates these effects, which may be partially through regulating the EGFR/PI3K/AKT and EGFR/STAT3 signaling pathway.

Ginsenosides↗

PubMed2026

Mechanism exploration of divergent partial denitrification performance under tetracycline stress: Insights from functional gene, electron transport and molecular docking.

Nitrates and antibiotics like tetracycline (TC) coexist in wastewater and inhibit nitrite (NO₂--N) accumulation during partial denitrification (PD), restricting anammox coupling. A moving bed biofilm reactor (PD-MBBR) and a sequencing batch reactor (PD-SBR) were compared under TC stress (0-8 mg/L). The PD-MBBR proved more robust, sustaining a high nitrate transformation ratio (NTR) of 95.11% and ∼53% TC removal. Metagenomic sequencing, quantitative polymerase chain reaction (qPCR), and molecular docking revealed this tolerance stemmed from physical shielding and metabolic compensation. Carrier-attached growth promoted extracellular polymeric substances (EPS) overproduction, forming a dense barrier preventing TC from binding to key denitrifying enzymes. The biofilm maintained stable nitrate reductase (NAR) activity via high narG and napA gene abundances, while nitrite reductase (NIR) was inhibited, ensuring efficient NO₂--N accumulation. This was supported by hyperactivated electron transport chain components, with complex III relative abundance increasing 15.08% and peak enzymatic activity reaching 149.02%. While IntI1-mediated horizontal gene transfer fortified community defense, concentrated antibiotic resistance genes (ARGs) within the biofilm pose a secondary dissemination risk. Thus, PD-MBBR provides an efficient pretreatment strategy for anammox, though downstream ARGs management is warranted.

Denitrification↗

PubMed2026

Domesticated Argania spinosa in Eastern Morocco: HPLC-DAD/GC-MS Chemical Profiling, Antioxidant and Antidiabetic Activities, and Network Pharmacology-Guided Molecular Docking.

The argan tree (Argania spinosa) is an endemic Moroccan species known for its primary product, argan oil, which possesses exceptional nutritional and medicinal properties. The current study aimed to evaluate and compare the antidiabetic and antioxidant activities of argan oil obtained from the introduced and native argan tree in eastern Morocco, to analyze its chemical composition using HPLC-DAD and GC-MS, and to investigate the molecular mechanisms behind the obtained pharmacological activities through an in silico pharmacological networking and molecular docking study. The results revealed that argan oil from all three regions of Morocco (Oujda, Agadir, and Chouihya) is rich in oleic and linoleic acids as major constituents, along with the presence of significant tocopherols. Regarding the antioxidant assays, including DPPH radical scavenging and iron-reducing power tests, argan oil from Oujda exhibited the highest activity, with the lowest IC50 values of 15.25 ± 0.022 mg/mL and 28.5 ± 1.7 mg/mL, respectively. Concerning the antidiabetic activity, we found that oil from Chaouihya showed the strongest α-amylase inhibition, while Oujda oil had the highest antiglycation activity, indicating that even introduced argan trees retain potent bioactivity. The results of the in silico investigation suggested that tocopherols may contribute to the antioxidant and antidiabetic potential of argan oil, showing predicted antioxidant activity (Pa = 0.843-0.967) and favorable binding affinities toward iNOS (ΔG = -9.3 kcal mol-1) and α-glucosidase (ΔG = -8.2 kcal mol-1). The identified fatty acids also showed predicted insulin-promoting activity (Pa = 0.59-0.75) and moderate enzyme-binding potential. Pharmacological network analysis identified 51 shared genes associated with antioxidant, antidiabetic, and argan-related targets, with enrichment of the AGE-RAGE signaling pathway. These computational findings provide possible molecular associations that may help explain the observed biological activities, although they remain predictive and require experimental validation. Overall, the in silico analysis suggests that tocopherols could be among the contributors to the multi-target profile of Argania spinosa oil, while fatty acids may provide complementary effects related to glycemic regulation.

Sapotaceae↗

PubMed2026

Precision UV-B irradiation for flavonoid biofortification in indoor-cultivated Morus nigra: Integrated multi-omics and molecular docking insights.

Precision application of UV irradiation represents an effective strategy for improving the quality of functional food crops under controlled environmental conditions. Morus nigra serves as a significant functional food resource in Xinjiang, with its leaves being rich in diverse bioactive compounds with nutritional and health-promoting properties. In this study, a low-dose UV-B treatment regimen was developed to enhance flavonoids in indoor-cultivated M. nigra without growth penalty. Multi-omics revealed a hormone shift (suppressed auxin vs. activated JA signaling). This triggered transcriptional reprogramming of PAL/4CL and CHS/CYP75B1, redirecting carbon flux towards flavonoid biosynthesis. Transient overexpression of MYB, NAC, and TIFY variants validated this regulatory network. The UV-B-induced NAC upregulated key genes and flavonoids, while different TIFY members showed diverse regulatory effects. Molecular docking predicted that the induced flavonoids had hypoglycemic, antioxidant, and anti-browning potential. This study indicates targeted UV-B as a green biofortification strategy for high-value crops in controlled environments.

Flavonoid biosynthesis↗

PubMed2026

Olive leaf protein hydrolysates yield gastro-resistant peptides with antioxidant and anti-inflammatory potential: peptidomics, in vitro validation and molecular docking analyses.

Olive (Olea europaea L.) leaves are an abundant olive-oil by-product and a promising feedstock for sustainable valorisation. An olive leaf protein isolate (OLPI) from olive-leaf powder (OLP) was enzymatically hydrolysed to yield seven hydrolysates (OLPHs). All showed notable antioxidant activity as whole hydrolysate matrices (EC₅₀ = 0.11-0.28 mg mL-1); likely reflecting the combined contribution of released peptides and co-extracted phenolic compounds; the 15-min Alcalase product (OLPH15A) showed high activity with the shortest processing time. Its INFOGEST digest (dOLPH15A) attenuated LPS-induced inflammation in Caco-2 cells, down-regulating pro-inflammatory and up-regulating anti-inflammatory genes. Peptidomics identified 7037 peptides in OLPH15A and 534 in dOLPH15A, from which twenty gastro-resistant sequences were prioritised for in silico analysis. Multi-tool prediction and docking highlighted four peptides, GAAGGIGQPL, QSAYPGTGPL, GGGAGGGDGGIL and LDAQFPGVN, with favourable predicted affinity for the TLR4/MD2 complex, suggesting that they may contribute to the observed immunomodulatory response. These findings position olive leaves as a viable source of protein hydrolysate-based ingredients with antioxidant and anti-inflammatory potential, advancing the valorisation of olive-oil by-products.

Olea↗

PubMed2026

Inhibitory mechanism of anthocyanin B-ring substituents on advanced glycation end-product formation through bovine serum albumin binding: Insights from multispectral, molecular docking and proteomics approaches.

This study demonstrated that the inhibitory effect of anthocyanins on AGEs formation is highly dependent on the substitution pattern of the B-ring. Among the four anthocyanins, delphinidin-3-O-glucoside (D3G) exhibited the most potent antiglycation activity across BSA-fructose, MGO, and GO models with half-maximal inhibitory concentration (IC50) of 30.77, 200.29 and 269.97 μM. This superior performance was attributed to the presence of three hydroxyl groups on the B-ring, which facilitates a high-affinity, spontaneous binding interaction with BSA primarily through hydrophobic forces and hydrogen bonding. Spectroscopic and computational analyses revealed that D3G effectively stabilizes the protein scaffold, specifically recovering α-helix content and shielding critical subdomains (IB, IIA, and IIIA). Proteomics data are consistent with a protective binding mechanism, suggesting that D3G reduces the accessibility of key lysine and arginine residues to glycation-induced modifications. These findings provide a structural basis for developing D3G-rich extracts as targeted, structure-based functional ingredients to mitigate glycation-associated food quality degradation and related health issues.

Anthocyanins↗

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↗

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↗

PubMed2026

Bioactive peptides for meat quality and preservation: Integrating peptidomics and computational screening.

Bioactive peptides generated from meat proteins, fermented meat products, and slaughter by-products have attracted increasing attention as functional molecules for improving meat quality and preservation. In meat systems, peptides can be produced through endogenous postmortem proteolysis, microbial fermentation, gastrointestinal digestion, or controlled enzymatic hydrolysis of underutilized animal by-products. These peptides are closely associated with key meat science endpoints, including postmortem tenderization, oxidative stability, color retention, flavor development, microbial inhibition, and the valorization of processing by-products. However, although high-resolution peptidomics has greatly expanded the identification of meat-derived peptide sequences, their translation into practical meat applications remains limited by matrix interactions, processing stability, sensory constraints, safety concerns, and insufficient validation in real meat systems. This review synthesizes recent advances in meat-related peptidomics and computational screening, including sequence-based prediction, machine learning, molecular docking, molecular dynamics, stability assessment, and safety-oriented filtering. Particular attention is given to how these approaches can prioritize peptides with antioxidant, antimicrobial, flavor-modulating, and preservation-related functions under meat-specific technological constraints. By integrating peptide generation pathways, mass spectrometry-based identification, in silico prioritization, and meat quality endpoints, this review proposes a stage-gated framework for translating meat-derived bioactive peptides from discovery to application. Future research should strengthen matrix-specific validation, standardized peptidomic reporting, and safety assessment to support the use of bioactive peptides in meat quality improvement, clean-label preservation, and circular utilization of meat industry by-products.

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

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↗

PubMed2026

Machine Learning in Hyperlipidaemia Research: Screening and Experimental Insights into Lipid Metabolism Modulators.

Hyperlipidemia, characterized by elevated blood lipid levels, represents a major global health concern due to its strong association with cardiovascular disease, diabetes, and metabolic syndrome. While current therapies - such as statins, fibrates, bile acid sequestrants, and PCSK9 inhibitors - are effective in controlling hyperlipidemia, they are often associated with adverse effects, potential drug resistance, and suboptimal efficacy in certain patient populations. All of the above underscore the urgent need for safer and more effective therapeutic alternatives. Among the major molecular targets involved in the regulation of lipid metabolism are HMG-CoA reductase, PCSK9, peroxisome proliferator-activated receptors (PPARs), cholesteryl ester transfer protein (CETP), and nuclear receptors, including the liver X receptor (LXR) and farnesoid X receptor (FXR), which are also targets for future antihyperlipidemic drug development. Recent advancements in artificial intelligence (AI) and machine learning (ML) have significantly transformed and accelerated drug discovery by enabling the processing of vast amounts of genomic, proteomic, and chemical data. Furthermore, ML tools such as quantitative structure-activity relationship (QSAR) modelling, deep learning, random forest, and support vector machines (SVM) have proven predictive and effective in identifying novel lipid metabolism modulators, thereby enhancing the efficacy and accuracy of virtual screening. Meanwhile, molecular docking has become an integral part of structure-based drug design (SBDD), and software such as AutoDock, Glide, and GOLD have proven effective in generating accurate ligand-target docking models. Molecular docking, together with ML-based approaches, enables the identification of potent and selective drug candidates. Overall, the combination of ML and molecular docking offers an efficient and accurate platform for antihyperlipidemic drug discovery, helping to overcome the limitations of currently available therapeutic strategies.

HMG-CoA reductase↗

PubMed2026

Exploring the Potential Molecular Targets of Cyanidin-3-O-glucoside for Type 2 Diabetes Mellitus Treatment.

INTRODUCTION: This study aims to elucidate the multi-target molecular mechanism of cyanidin-3-O-glucoside (C3G) in treating Type 2 Diabetes (T2DM) through network pharmacology methods. METHODS: The study was designed to predict the targets of C3G through public databases and to screen for T2DM-related targets. Protein-protein interaction (PPI) network analysis, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed on the common targets. Core targets were further validated through molecular docking and molecular dynamics (MD) simulations. RESULTS: This research identified a total of 57 potential targets of C3G in the treatment of T2DM. Subsequent PPI analysis identified ALB (Degree=43), AKT1 (Degree=41), and TNF (Degree=41) as the top three hub proteins. Pathway analysis indicated significant involvement in the insulin signaling pathway (P = 4.205×10-9), AMPK signaling pathway (P = 9.582×10-7), and FoxO signaling pathway (P = 1.315×10-6). Molecular docking revealed strong binding affinities between C3G and NOS3 (-9.5 kcal/mol), PPARG (-9.0 kcal/mol), TNF (-8.5 kcal/mol), and INSR (-8.4 kcal/mol). MD simulations further confirmed that the C3G-target complex has excellent binding stability. DISCUSSION: C3G may intervene in the pathological progression of T2DM by regulating key pathways such as insulin sensitivity, inflammatory responses, and oxidative stress. Further studies suggest that INSR and NOS3 may be new targets through which C3G exerts its effects, but their specific mechanisms and in vivo biological functions still need to be elucidated by subsequent experiments. CONCLUSION: C3G may intervene in the progression of T2DM in a multi-pathway synergistic manner by targeting key molecules such as INSR and NOS3.

Anthocyanins↗

PubMed2026

Integrative computational analysis combining network pharmacology, regulatory network modeling, and molecular dynamics reveals the mechanisms of Quanshen compound in ITP.

UNLABELLED: Immune thrombocytopenia (ITP) is a hemorrhagic disorder caused by immune dysfunction. Quanshen Compound (QSC) is an in-house preparation developed by the Uyghur Hospital in Hotan Prefecture. This study primarily investigates and validates the potential pharmacological basis and mechanism of action of QSC in modulating immune thrombopoiesis. Based on the multi-database screening of the QSC and the related targets of ITP, the intersection was obtained to construct a protein-protein interaction (PPI) network and screen the core targets; the intersection targets were analyzed for gene ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis using R packages; a component-target-pathway network was constructed to screen the key active components and their mechanisms of action. At the same time, the TF-mRNA-miRNA regulatory network of the core targets was constructed, and chromosome localization and subcellular localization analysis were performed; further, the binding stability of key components and core targets was verified through molecular docking and molecular dynamics simulation. A total of 227 potential target sites were screened out, among which TNF, IL6, AKT1, TP53 and IL1B were the core targets. The enrichment results indicated that these intersecting target sites mainly participated in inflammatory responses, immune regulation and hemostasis-related biological processes, and were significantly enriched in the PI3K-Akt signaling pathway, Toll-like receptor signaling pathway, Th17 cell differentiation and PD-1/PD-L1 signaling pathway. The core target TF-mRNA-miRNA regulatory network contained 184 nodes and 200 edges, suggesting that the core targets were subject to multi-level regulation. Molecular docking results showed that the main active components had good binding activity with the core targets, and molecular dynamics simulation further verified the stability of the complex. QSC may improve ITP through a multi-component, multi-target, and multi-pathway synergistic mechanism involving key targets such as TNF, IL6, AKT1, TP53, and IL1B, as well as the PI3K-Akt signaling pathway. These findings provide new insights into the potential therapeutic mechanisms of QSC against ITP and warrant further experimental validation. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at https://doi.org/10.1007/s40203-026-00718-0.

Immune thrombocytopenia↗

PubMed2026

Integrated dual transcriptome sequencing and experimental validation reveal potential mechanisms of baicalin against pneumocystis pneumonia in immunosuppressed rats.

BACKGROUND: Pneumocystis pneumonia (PCP) remains a major cause of morbidity and mortality in immunocompromised individuals. Although baicalin (Ba), a natural bioactive flavonoid, has demonstrated protective and therapeutic effects against PCP, its molecular mechanisms remain undefined. We employed dual RNA sequencing (dual RNA-seq) to characterize host and pathogen transcriptional responses to Ba treatment in an immunosuppressed rat model of PCP. METHODS: Comparative transcriptomic analyses identified differentially expressed genes in both the host and Pneumocystis, followed by Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and gene set enrichment analyses. Candidate targets were further investigated using network pharmacology, protein-protein interaction analysis, molecular docking, and molecular dynamics simulations. Key findings were validated by immunohistochemistry, enzyme-linked immunosorbent assay, and quantitative PCR. RESULTS: Ba markedly remodeled host and pathogen transcriptomes. Host transcriptomic analyses showed that Ba attenuated inflammatory and oxidative stress responses by modulating immune-related pathways, including Toll-like receptor, NF-κB, cytokine-cytokine receptor interaction, chemokine signaling, Th17 cell differentiation, and antigen processing and presentation. Experimental validation demonstrated that Ba reduced pulmonary expression of indoleamine 2,3-dioxygenase 1 (IDO1), Toll-like receptor 2 (TLR2), and TLR4 while increasing nuclear factor erythroid 2-related factor 2 (Nrf2) and its downstream antioxidant enzyme heme oxygenase-1 (HO-1). Pathogen transcriptomic analysis identified Pneumocystis Rtt109 (PcRtt109), a fungal histone acetyltransferase, as a potential pathogen-specific target that was significantly downregulated after Ba treatment. Molecular docking and molecular dynamics simulations supported stable interactions between Ba and IDO1, Nrf2, TLR2, TLR4, and PcRtt109, with the strongest predicted binding observed for PcRtt109. CONCLUSION: Dual RNA-seq revealed that Ba exerts anti-PCP activity through coordinated modulation of host and pathogen molecular networks. Its therapeutic effects are associated with suppression of inflammatory signaling, enhancement of antioxidant defenses, and inhibition of a fungal virulence-associated target. These findings provide mechanistic insights into host-pathogen interactions during PCP and support Ba as a potential therapeutic candidate for PCP.

Nrf2↗

PubMed2026

Exploring the mechanism of Shengmai San in treating lung adenocarcinoma based on bioinformatics and molecular dynamics simulation.

To investigate the mechanism of Shengmai San (SMS) in the treatment of lung adenocarcinoma (LUAD) based on an integrated strategy combining "network pharmacology, bioinformatics, molecular docking, and molecular dynamics simulation," aiming to provide a precise combination therapy strategy and identify potential bioactive compounds. Differentially expressed genes in LUAD were identified from the Gene Expression Omnibus database using R (originally developed at Bell Laboratories and currently managed by Lucent Technologies). SMS components (ginseng, Ophiopogon japonicus, and Schisandra chinensis) were retrieved from encyclopaedia of traditional Chinese medicine, with Lipinski-compliant compounds selected. Compound targets were predicted via SwissTargetPrediction and Similarity Ensemble Approach. Intersecting targets between differentially expressed genes and compound targets were identified for "herbs-compounds-targets-disease" network construction. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed. Hub targets were identified by analyzing the protein-protein interaction network. High-prognostic relevance targets were screened from The Cancer Genome Atlas. Compounds targeting these were identified through the herbs-compounds-targets-disease network, and absorption, distribution, metabolism, excretion, and toxicity-compliant compounds were selected using SwissADME (a web-based tool provided by the Molecular Modeling Group of the Swiss Institute of Bioinformatics). Core regulatory targets were identified through molecular docking, with complex stability assessed by molecular dynamics simulations. The key bioactive compounds of SMS for treating LUAD were identified as 7-hydroxy-2,5-dimethyl-4H-1-benzopyran-4-one, N-trans-feruloyltyramine, paprazine, and (E)-N-[(2S)-2-hydroxy-2-(4-hydroxyphenyl)ethyl]-3-(4-hydroxyphenyl)prop-2-enamide. Hub targets included AURKA, CCNA2, CCNB1, CDK1, CHEK1, KIF11, NEK2, PLK1, TTK, and TYMS. Among these, CDK1, CHEK1, and PLK1 demonstrated both high-prognostic relevance and strong binding affinity with SMS, emerging as core regulatory targets for SMS in LUAD treatment. Mechanistically, SMS exerts its anticancer effects primarily by modulating the tumor necrosis factor, interleukin-17, cell cycle, and Lipid and atherosclerosis signaling pathways. The active components of SMS, such as paprazine, may exert antitumor effects partly through downregulating CDK1, CHEK1, and PLK1 expression. Although the present study did not examine drug-resistance models or combination regimens, our findings raise the possibility that, in patients with high expression of these genes, combining SMS with standard chemotherapy or targeted therapy could potentially enhance chemosensitivity and mitigate the development of resistance. This hypothesis, however, requires formal testing in appropriate preclinical models and functional validation studies.

Molecular Dynamics Simulation↗

PubMed2026

LARS promotes hepatocellular carcinoma progression via the PI3K/AKT/mTOR pathway and interaction with RPS5, and serves as a prognostic biomarker.

BACKGROUND: Hepatocellular carcinoma (HCC) caused many cancer deaths around the world. Its progression involves complex mechanisms, creating an urgent need to identify new therapeutic targets. Leucine-tRNA synthetase (LARS) is a key enzyme for protein synthesis, but its specific role and mechanism in HCC are not well understood. PURPOSE: This research aims to investigate the biological function, molecular mechanism, and clinical relevance of the LARS gene in HCC progression, to assess its potential as a treatment target. METHODS: LARS expression was assessed in HCC cell lines (PLC-PRF-5, HCC-LM3) and in mouse subcutaneous tumor models using siRNA and adeno-associated virus (AAV). Techniques including Cell Counting Kit-8(CCK-8), colony formation, EdU, Transwell, wound healing, and flow cytometry were used to measure cell proliferation, migration, invasion, and apoptosis. RNA-seq, proteomics (TMT), western blot, co-immunoprecipitation (Co-IP) with mass spectrometry, molecular docking, and molecular dynamics simulation were employed to study the affected signaling pathway (PI3K/AKT/mTOR) and interacting protein (RPS5). The TCGA (The Cancer Genome Atlas) database and UALCAN platform were used to analyze links between LARS expression and clinicopathological features or prognosis in HCC patients. RESULTS: Reducing LARS expression significantly inhibited the proliferation, colony formation, migration, and invasion of HCC cells, while promoting apoptosis. In mice, LARS knockdown markedly slowed tumor growth. Mechanistic studies showed that reducing LARS expression levels affected the PI3K/AKT/mTOR signaling pathway and led to decreased levels of the key interacting protein RPS5. Overexpressing RPS5 partly reversed the proliferation inhibition caused by LARS depletion. Molecular docking and dynamics simulations suggested that the environmental contaminant triphenyl phosphate (TPP) might bind to the LARS protein. Clinical data analysis revealed that LARS expression is higher in HCC tissues. High LARS expression was significantly associated with shorter overall survival (OS) in patients and correlated positively with various clinical features like tumor stage, grade, and TP53 mutation status. CONCLUSION: LARS helped HCC become worse by affecting the PI3K/AKT/mTOR pathway and working with RPS5. High LARS meant a worse outcome for patients. This suggested LARS could be used to predict disease or as a treatment target in HCC.

Carcinoma, Hepatocellular↗