Exploring the mechanism of Epimedium in diabetes mellitus treatment based on network pharmacology and molecular dynamics simulation

Curculigo spp. is a herb that is commonly used in Indonesia to treat diabetes mellitus (DM) . The main active components of Curculigo spp. were identified through our previous metabolomic study and online database platform. However, the biological mechanisms underlying Curculigo spp. activity in treating DM remain unclear. Therefore, in this study, a network pharmacology was used to explore the active compounds of Curculigo spp. and their potential molecular mechanisms for treating DM. Oral bioavailability and drug-likeness from the compounds of Curculigo spp. were screened using Lipinski’s rule of five, BBB, HIA + and Caco-2 permeability criteria. A network of compound–target–disease–pathway was then constructed using Cytoscape. The highest degree compounds and targets were then confirmed by molecular docking and molecular dynamics (MD) simulations. The human body can absorb 33 compounds derived from Curculigo spp. In addition, 58 nodes and 62 edges generated a network analysis with the DM target. The highest degree of the compound–target–disease pathway was for orcinol glucoside, AKR1B1, autoimmune diabetes, bile acid and bile salt metabolism. Furthermore, the computational docking method on Curculigo spp. compounds with the highest degree revealed that orcinol glucoside interacted with PTPN1 through a hydrogen bond and resulted in a binding energy of −7.2 kcal mol−1. Through hydrogen bonds, orcinol glucoside in PTPN1 regulates multiple signaling pathways via the adherens junction pathway, which may play a therapeutic role in DM (type 2 diabetes: obesity). In addition, MD simulation confirmed that orcinol glucoside, is suitable for DM treatment by interacting with PTPN1. Communicated by Ramaswamy H. Sarma

Simple SummaryCOPD is a lung disease characterized by limited respiratory airflow aggravated with time. JPYF II granules are a traditional Chinese medicine used in the treatment of COPD. However, the main components and potential mechanisms of JPYF II granules are still unclear. The purpose of this study was to elucidate the potential mechanism underlying its ability to treat COPD through network pharmacology, molecular docking, and molecular dynamics simulation techniques. Kaempferol, quercetin, and stigmasterol are the main active compounds in the JPYF II Formula in the treatment of COPD, and AKT1, IL-6, and TNF are potential target proteins for the JPYF II Formula in the treatment of COPD. The potential effective compounds, targets, and related potential molecular mechanisms obtained here provide a reference for follow-up studies on COPD.Background: JianPiYiFei (JPYF) II granules are a Chinese medicine for the treatment of chronic obstructive pulmonary disease (COPD). However, the main components and underlying mechanisms of JPYF II granules are not well understood. This study aimed to elucidate the potential mechanism of JPYF II granules in the treatment of COPD using network pharmacology, molecular docking, and molecular dynamics simulation techniques. Methods: The active compounds and corresponding protein targets of the JPYF II granules were found using the TCMSP, ETCM, and Uniport databases, and a compound–target network was constructed using Cytoscape3.9.1. The COPD targets were searched for in GEO datasets and the OMIM and GeneCards databases. The intersection between the effective compound-related targets and disease-related targets was obtained, PPI networks were constructed, and GO and KEGG enrichment analyses were performed. Then, molecular docking analysis verified the results obtained using network pharmacology. Finally, the protein–compound complexes obtained from the molecular docking analysis were simulated using molecular dynamics (MD) simulations. Results: The network pharmacological results showed that quercetin, kaempferol, and stigmasterol are the main active compounds in JPYF II granules, and AKT1, IL-6, and TNF are key target proteins. The PI3K/AKT signaling pathway is a potential pathway through which the JPYF II granules affect COPD. The results of the molecular docking analysis suggested that quercetin, kaempferol, and stigmasterol have a good binding affinity with AKT1, IL-6, and TNF. The MD simulation results showed that TNF has a good binding affinity with the compounds. Conclusions: This study identified the effective compounds, targets, and related underlying molecular mechanisms of JPYF II granules in the treatment of COPD through network pharmacology, molecular docking, and MD simulation techniques, which provides a reference for subsequent research on the treatment of COPD.

Background:Alpinia officinarum, a member of the Zingiberaceae family, is native to East Asia. It possesses various properties, including antineoplastic effects, but the molecular mechanism underlying its inhibition of acute myeloid leukemia (AML) remains unclear. This study explored the biological mechanisms and pharmacological effects of Alpinia officinarum in AML through network pharmacology, molecular docking and molecular dynamics (MD) simulation. Methods: Active compounds were identified through a literature review and Dr. Duke’s database. Compounds were screened based on solubility, oral bioavailability (OB) and drug-likeness (DL) using SwissADME and Molsoft tools. Targets related to the identified compounds were acquired using SwissTargetPrediction, and AML targets were extracted from DisGeNET, OMIM and GeneCards. Common targets of the active compounds and AML were further analyzed via gene ontology (GO) and pathway enrichment using ShinyGO, followed by the protein–protein interaction (PPI) through STRING and Cytoscape to elucidate key targets. Molecular docking and dynamics simulation were employed to find a lead compound. Results: Eleven potential active compounds and six key targets were identified. The targets were enriched in pathways such as central carbon metabolism in cancer and the PI3K-Akt signaling pathway. Molecular docking revealed that Alpinin A had a high affinity for the six key targets (BCL2, AKT1, PIK3CA, ABL1, TERT and FLT3). Furthermore, MD simulation demonstrated the stability of the AKT1-Alpinin A complex which showed the best docking score among other active compounds. Conclusion: Our study indicates that Alpinin A may serve as a promising agent against AML, highlighting its potential for further pharmacological investigation.

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. 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. 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. 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. 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.

Nonalcoholic fatty liver disease (NAFLD) is a metabolic disease, the incidence of which increases annually. Shugan Xiaozhi (SGXZ) decoction, a composite traditional Chinese medicinal prescription, has been demonstrated to exert a therapeutic effect on NAFLD. In this study, the potential bioactive ingredients and mechanism of SGXZ decoction against NAFLD were explored via network pharmacology, molecular docking, and molecular dynamics simulation. Compounds in SGXZ decoction were identified and collected from the literature, and the corresponding targets were predicted through the Similarity Ensemble Approach database. Potential targets related to NAFLD were searched on DisGeNET and GeneCards databases. The compound-target-disease and protein-protein interaction (PPI) networks were constructed to recognize key compounds and targets. Functional enrichment analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) was performed on the targets. Molecular docking was used to further screen the potent active compounds in SGXZ. Finally, molecular dynamics (MD) simulation was applied to verify and validate the binding between the most potent compound and targets. A total of 31 active compounds and 220 corresponding targets in SGXZ decoction were collected. Moreover, 1,544 targets of NAFLD were obtained, of which 78 targets intersected with the targets of SGXZ decoction. Key compounds and targets were recognized through the compound-target-disease and PPI network. Multiple biological pathways were annotated, including PI3K-Akt, MAPK, insulin resistance, HIF-1, and tryptophan metabolism. Molecular docking showed that gallic acid, chlorogenic acid and isochlorogenic acid A could combine with the key targets. Molecular dynamics simulations suggested that isochlorogenic acid A might potentially bind directly with RELA, IL-6, VEGFA, and MMP9 in the regulation of PI3K-Akt signaling pathway. This study investigated the active substances and key targets of SGXZ decoction in the regulation of multiple-pathways based on network pharmacology and computational approaches, providing a theoretical basis for further pharmacological research into the potential mechanism of SGXZ in NAFLD.

Background: Osteoporosis is a prevalent bone metabolism disease characterized by a reduction in bone density, leading to several complications that significantly affect patients’ quality of life. The Achyranthes bidentata–Dipsacus asper (AB–DA) herb pair is commonly used in Traditional Chinese Medicine (TCM) to treat osteoporosis. This study aimed to investigate the therapeutic compounds and potential mechanisms of AB–DA using network pharmacology, molecular docking, molecular dynamics simulation, and experimental verification.Methods: Identified compounds of AB–DA were collected from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), Traditional Chinese Medicine Information Database (TCM-ID), TCM@Taiwan Database, BATMAN-TCM, and relevant literature. The main bioactive ingredients were screened based on the criteria of “OB (oral bioavailability) ≥ 30, DL (drug-likeness) ≥ 0.18.” Potential targets were predicted using the PharmMapper and SwissTargetPrediction websites, while disease (osteoporosis)-related targets were obtained from the GeneCards, DisGeNET, and OMIM databases. The PPI network and KEGG/GO enrichment analysis were utilized for core targets and pathway screening in the STRING and Metascape databases, respectively. A drug–compound–target–pathway–disease network was constructed using Cytoscape software to display core regulatory mechanisms. Molecular docking and dynamics simulation techniques explored the binding reliability and stability between core compounds and targets. In vitro and in vivo validation experiments were utilized to explore the anti-osteoporosis efficiency and mechanism of sitogluside.Results: A total of 31 compounds with 83 potential targets for AB–DA against osteoporosis were obtained. The PPI analysis revealed several hub targets, including AKT1, CASP3, EGFR, IGF1, MAPK1, MAPK8, and MAPK14. GO/KEGG analysis indicated that the MAPK cascade (ERK/JNK/p38) is the main pathway involved in treating osteoporosis. The D–C–T–P–T network demonstrated therapeutic compounds that mainly consisted of iridoids, steroids, and flavonoids, such as sitogluside, loganic acid, and β-ecdysterone. Molecular docking and dynamics simulation analyses confirmed strong binding affinity and stability between core compounds and targets. Additionally, the validation experiments showed preliminary evidence of antiosteoporosis effects.Conclusion: This study identified iridoids, steroids, and flavonoids as the main therapeutic compounds of AB–DA in treating osteoporosis. The underlying mechanisms may involve targeting core MAPK cascade (ERK/JNK/p38) targets, such as MAPK1, MAPK8, and MAPK14. In vivo experiments preliminarily validated the anti-osteoporosis effect of sitogluside. Further in-depth experimental studies are required to validate the therapeutic value of AB–DA for treating osteoporosis in clinical practice.

Xiangqin Jiere granules (XQJRG) is a proprietary Chinese medicine treating children’s colds and fevers, but its mechanism of action is unclear. The aim of this study was to explore the antipyretic mechanisms of XQJRG based on pharmacodynamics, non-targeted metabolomics, network pharmacology, molecular biology experiments, molecular docking, and molecular dynamics (MD) simulation. Firstly, the yeast-induced fever model was constructed in young rats to study antipyretic effect of XQJRG. Metabolomics and network pharmacology studies were performed to identify the key compounds, targets and pathways involved in the antipyretic of XQJRG. Subsequently, MetScape was used to jointly analyze targets from network pharmacology and metabolites from metabolomics. Finally, the key targets were validated by enzyme-linked immunosorbent assay (ELISA), and the affinity and stability of key ingredient and targets were evaluated by molecular docking and MD simulation. The animal experimental results showed that after XQJRG treatment, body temperature of febrile rats was significantly reduced, 13 metabolites were significantly modulated, and pathways of differential metabolite enrichment were mainly related to amino acid and lipid metabolism. Network pharmacology results indicated that quercetin and kaempferol were the key active components of XQJRG, TNF, AKT1, IL6, IL1B and PTGS2 were core targets. ELISA confirmed that XQJRG significantly reduced the plasma concentrations of IL-1β, IL-6, and TNF-α, and the hypothalamic concentrations of COX-2 and PGE2. Molecular docking demonstrated that the binding energies of kaempferol to the core targets were all below −5.0 kcal/mol. MD simulation results showed that the binding free energies of TNF-kaempferol, IL6-kaempferol, IL1B-kaempferol and PTGS2-kaempferol were −87.86 kcal/mol, −70.41 kcal/mol, −69.95 kcal/mol and −106.67 kcal/mol, respectively. In conclusion, XQJRG has antipyretic effects on yeast-induced fever in young rats, and its antipyretic mechanisms may be related to the inhibition of peripheral pyrogenic cytokines release by constituents such as kaempferol, the reduction of hypothalamic fever mediator production, and the amelioration of disturbances in amino acid and lipid metabolism.

The incidence rate of adolescent depression and anxiety has been increasing since the outbreak of COVID-19, which there are no effective therapeutic drugs available. Si-ni San is commonly used in traditional Chinese medicine for the treatment of depression-like as well as anxiety-like behavior, but its mechanism for treating depression combined with anxiety during adolescence is not yet clear. Network pharmacology was used to explore potential drug molecules and related targets, molecular docking and molecular dynamics (MD) simulation were used to evaluate the interaction between the potential drug molecules and related targets, and a model of anxiety combined with depression in adolescent rats as well as the following behavioral tests and molecular biology tests were used to verify the results from network pharmacology and molecular docking. As a result, 256 active ingredients of Si-ni San and 1128 potential targets were screened out. Among them, quercetin, Luteolin, kaempferol, 7-Methoxy-2-methyl isoflavone, formononetin showed to be the most potential ingredients; while STAT3, IL6, TNF, AKT1, AKT1, TP53, IL1B, MAPK3, VEGFA, CASP3, MMP9 showed to be the most potential targets. AGE-RAGE signaling pathway in diabetic complications, IL-17 signaling pathway, HIF-1 signaling pathway, PI3K-Akt signaling pathway and TNF signaling pathway, which are involved in anti-inflammation processes, showed to be the most probable pathways regulated by Si-ni San. Molecular docking and MD simulation between the compounds to inflammation-associated targets revealed good binding abilities of quercetin, Luteolin, kaempferol, nobiletin and formononetin to PTGS2 and PPARγ. In the experiment with adolescent rats, Si-ni San markedly suppressed early maternal separation (MS) combined with adolescent chronic unpredictable mild stress (CUMS)-induced depression combined with anxiety. The qPCR results further indicated that Si-ni San regulated the oxidative stress and inflammatory response. This study demonstrates that adolescent anxiety- and depression-like behavior induced by MS combined CUMS can be ameliorated by Si-ni San by improved inflammation in hippocampus via targeting TNF pathway and Nrf2 pathway, helping to reveal the mechanism of Si-ni San in treating adolescent depression combined with anxiety.

Periodontitis (PD) and type 2 diabetes mellitus (T2DM) represent interlinked global health burdens, commonly causing significant clinical complications when coincident. Therefore, managing both conditions (T2DM with periodontitis, DP) simultaneously poses considerable challenges, necessitating novel therapeutic strategies. KQJF has been clinically proven to treat DP with good efficacy, but its pharmacological substances and targets are not clear and urgently need to be clarified. To define the potential active components and targets of KQJF for the treatment of DP. The investigation commenced with the application of UPLC-Q-TOF/MS analysis to delineate the active constituents of KQJF and their associated targets in addressing DP. Additionally, the research incorporated subsequent methodologies such as machine learning, network pharmacology, molecular docking, molecular dynamics simulations, and a DP rat model was established and validated by in vivo experiments using H&E staining, immunohistochemistry, quantitative real-time PCR, and Western blot. KQJF was found to contain 49 prototype compounds and 121 metabolites with potential activity against PD and T2DM. Network pharmacology revealed 66 overlapping genes between the pharmacological targets of KQJF and known targets of PD and T2DM. Further exploration through PPI network and enrichment analyses illuminated the involvement of multi-target and multi-pathway mechanisms. Molecular docking and dynamics simulations confirmed the robust interactions between key compounds within KQJF and proteins associated with the diseases. In vivo validation demonstrated that KQJF treatment ameliorated DP-associated histopathological changes and modulated the expression of crucial proteins (including ABCG2, CCND1, CDKN1B, HIF1A, and PIK3R1) in a DP rat model. In summary, KQJF exhibits potential therapeutic benefits for DP through a multi-component and multi-target approach, potentially offering a novel integrative treatment strategy. This study underscores the importance of integrating traditional medicine with modern molecular techniques to explore novel therapeutic avenues for complex comorbid conditions, providing a blueprint for future pharmacological explorations.

Usnic acid, a compound from Usneae Filum, has shown notable antitumor effects. Nevertheless, the mechanism of its anti-NSCLC action remains incompletely elucidated. This study used metabolomics, network pharmacology, molecular docking, and dynamics simulation to investigate usnic acid's potential mechanism on NSCLC utilizing A549 cell samples. The integration of metabolomics and network pharmacology was confirmed through molecular docking and molecular dynamics simulation. Combining data-dependent acquisition (DDA) and data-independent acquisition (DIA) enables maximal MS/MS coverage of endogenous substances in complex biological matrices. Metabolomics based on DDA and DIA revealed 47 potential metabolites linked to usnic acid's therapeutic effects on NSCLC. Network pharmacology identified 24 targets, with key pathways including cancer, human cytomegalovirus infection, and p53 signaling. A network analysis highlighted myeloperoxidase (MPO) as a shared target, with molecular docking and dynamics simulations confirming strong binding and stability between usnic acid and MPO. This study uncovered usnic acid's molecular mechanisms in NSCLC, primarily through MPO targeting and modulation of purine metabolism. MPO inhibition attenuates oxidative stress-driven purine catabolism, reduces uric acid-induced inflammation, and restores metabolic homeostasis. These findings illuminate novel mechanisms of usnic acid's anticancer potential and advance mechanistic insights into traditional Chinese medicine (TCM) for clinical oncology applications.

BackgroundInflammation is a critical immune response that protects the body from infections and injuries. However, chronic inflammation can lead to diseases such as cancer. Curcumin, a bioactive compound extracted from Curcuma longa, has been widely studied for its anti-inflammatory properties. Despite extensive research, the comprehensive molecular mechanisms underlying curcumin’s anti-inflammatory effects, particularly its multi-target regulatory network, remain incompletely understood. This study aims to elucidate these mechanisms using an integrated approach combining network pharmacology, molecular docking, molecular dynamics simulation, and in vitro experimental validation.MethodsWe utilized network pharmacology to identify potential targets and pathways involved in curcumin’s anti-inflammatory effects. Molecular docking and dynamics simulation were conducted to evaluate the binding affinity and stability of curcumin with key inflammatory targets. The anti-inflammatory effects of curcumin were further validated in vitro using LPS-induced RAW 264.7 cells. Cell viability, NO content, and mRNA expression levels of pro-inflammatory cytokines (IL-1β, IL-6, and TNF) were assessed.ResultsNetwork pharmacology identified 135 potential targets for curcumin’s anti-inflammatory effects, with key pathways including TNF, HIF-1, PI3K-Akt, JAK-STAT, and MAPK signaling pathways. Molecular docking revealed strong binding affinities of curcumin with core targets such as IL-6, TNF, IL-1β, AKT1, and STAT3, with binding energies ranging from −6.2 to −7.5 kcal/mol. Molecular dynamics simulations demonstrated the stability of these complexes over a 100-nanosecond period. In vitro experiments showed that curcumin significantly reduced NO production and mRNA expression of IL-1β, IL-6, and TNF in LPS-induced RAW 264.7 cells, with optimal effects observed at a concentration of 125 μg/mL.ConclusionOur study provides a comprehensive understanding of curcumin’s anti-inflammatory mechanisms through an integrated approach. The findings highlight curcumin’s potential as a therapeutic agent for inflammatory diseases. However, further in vivo studies are necessary to fully elucidate its therapeutic efficacy and mechanisms of action.

Ovarian cystadenoma (OC) is a common benign tumor in women. Wang's formula for gynecological masses (WGM), a patented traditional Chinese medicine, was reported to have therapeutic potential for OC. Here, we explored the pharmacological effects of WGM on treating OC via network pharmacology, molecular docking, and molecular dynamics simulations. The active ingredients in WGM and their putative targets were acquired from the TCMSP and BATMAN-TCM platforms. The known therapeutic targets of OC were obtained from the DrugBank, OMIM, and GeneCards databases. GO and KEGG analyses of the overlapping targets were performed via the DAVID database. Molecular docking and molecular dynamics (MD) simulations were conducted to evaluate the binding efficacy of the chemical ingredients to the core targets. In total, 287 chemicals in WGM may relieve OC by targeting 134 genes involved in malignant tumors, endocrine resistance, and oxidative stress, of which ERBB2, ESR1, and AKT1 play vital roles. Molecular docking revealed stable binding energies of the receptors to the ligands, which bond via electrostatic interactions and van der Waals interactions in MD simulations. The in silico bioinformatics analysis revealed the mechanisms of WGM treatment for OC. More pharmacological evidence of WGM treatment for OC, such as in vivo and clinical studies, is needed before WGM can benefit more patients.

Si-Miao-Yong-An (SMYA) Decoction, a traditional Chinese herbal mixture, shows promise for managing diabetic complications. Up to this point, no reports have explored the effects of SMYA on diabetic wounds or the underlying mechanisms. This study aimed to investigate the therapeutic potential of SMYA in promoting diabetic wound healing and to elucidate the underlying molecular mechanisms. The wound healing effects of SMYA were evaluated in db/db diabetic mice by measuring wound closure rates and histological characteristics, including epidermal thickness and collagen deposition. Network pharmacology was utilized to identify active ingredients and corresponding therapeutic targets of SMYA, followed by validation through molecular docking and molecular dynamics simulations. KEGG and GO enrichment analyses were conducted to elucidate the relevant biological processes and pathways. In vitro studies involving high-glucose-treated HUVECs assessed the effects of SMYA-containing serum on cellular migration and angiogenesis. Finally, the expression of inflammatory factors and RAGE in the wound tissue was detected by qRT-PCR. SMYA significantly accelerated wound closure in db/db mice, as evidenced by improved epidermal thickness, tissue morphology, and collagen deposition. Network pharmacology identified 140 overlapping genes involved in angiogenesis and inflammation, with the AGE-RAGE signaling pathway playing a central role. Molecular docking and dynamics simulations revealed strong binding stability of quercetin and kaempferol to inflammation-related hub targets, including IL-6, TNF, and IL-1β. In vitro, SMYA-containing serum alleviated high-glucose-induced impairments in HUVEC migration and angiogenesis. Furthermore, qRT-PCR analysis showed that SMYA significantly downregulated Tnf, Il1b, Il6, and Rage expression in wound tissues, supporting its anti-inflammatory effect. SMYA promotes diabetic wound healing by modulating the inflammatory microenvironment and inhibiting the AGE-RAGE signaling pathway. These findings provide robust evidence for SMYA's therapeutic potential and lay a foundation for its future clinical application in treating diabetic wounds.

Luteolin inhibits the JAK/STAT pathway to alleviate auditory cell apoptosis of acquired sensorineural hearing loss based on network pharmacology, molecular docking, molecular dynamics simulation, and experiments in vitro

Licorice flavonoids (LCFs) are natural flavonoids isolated from Glycyrrhiza which are known to have anti-melanoma activities in vitro. However, the molecular mechanism of LCF anti-melanoma has not been fully understood. In this study, network pharmacology, 3D/2D-QSAR, molecular docking, and molecular dynamics (MD) simulation were used to explore the molecular mechanism of LCF anti-melanoma. First of all, we screened the key active components and targets of LCF anti-melanoma by network pharmacology. Then, the logIC50 values of the top 20 compounds were predicted by the 2D-QSAR pharmacophore model, and seven highly active compounds were screened successfully. An optimal 3D-QSAR pharmacophore model for predicting the activity of LCF compounds was established by the HipHop method. The effectiveness of the 3D-QSAR pharmacophore was verified by a training set of compounds with known activity, and the possible decisive therapeutic effect of the potency group was inferred. Finally, molecular docking and MD simulation were used to verify the effective pharmacophore. In conclusion, this study established the structure–activity relationship of LCF and provided theoretical guidance for the research of LCF anti-melanoma.