Active ingredients and molecular targets of Tripterygium wilfordii against colorectal cancer: network pharmacology, molecular docking, molecular dynamics simulations and in vitro evaluation

Integrated GC-MS Profiling and Multi-Scale Computational Analyses Identify Promising Phytochemicals Leads Targeting MAPK14 in Colorectal Cancer

Network pharmacology, molecular docking, and dynamics simulation reveal multi-target mechanisms of Mesua ferrea linn phytochemicals against cervical cancer.

Cervical cancer represents the second most prevalent malignancy among women in India and is etiologically linked to persistent infection with high-risk human papillomavirus (HPV) strains. Mesua ferrea Linn, a medicinal tree species distributed across the Eastern Himalayan region, Eastern Indian states, and the Western Ghats, has demonstrated anticancer potential in several preclinical investigations; however, its mechanistic basis in cervical cancer remains insufficiently elucidated. In this study, a network pharmacology-based workflow was employed to identify the phytochemicals of Mesua ferrea, predict key targets, analyse protein-protein interactions and construct a compound-target pathway network along with network enrichment analysis. ADMET analysis, molecular docking, and molecular dynamics simulation were used to assess the stability of key compounds relative to potential targets. 16 phytochemicals, based on drug-likeness criteria, were identified, yielding 60 common targets, including AKT1, KDR, PIK3CA, MTOR, and EGFR, which are involved in Ras, PI3K-Akt, Jak-Stat, and HPV-associated pathways. Molecular docking and molecular dynamics simulations verified the stable binding of key phytochemicals to core cervical cancer-associated proteins. Collectively, these findings indicate that Mesua ferrea Linn exerts multi-target, multi-pathway regulatory effects in cervical cancer, supporting its potential as a source of phytotherapeutic agents. The study provides a mechanistic foundation for future in vitro and in vivo validation, contributing to the rational development of plant-derived interventions for cervical cancer management.

Anticancer activity of lichen-derived compounds against triple-negative breast cancer: integrated in vitro evaluation, network pharmacology, molecular docking, and KEGG pathway analysis.

Lichen-derived compounds atranorin, barbatic acid, and usnic acid demonstrated anticancer activity in vitro, while integrated computational analyses suggested potential multitarget interactions that warrant further experimental validation.

Exploring the Mechanism of Curcumin in the Treatment of Gastric Cancer based on Network Pharmacology, Molecular Dynamics Simulation, and In Vitro Experimental Verification.

INTRODUCTION Gastric Cancer (GC) is still one of the leading causes of cancer-related deaths worldwide. Curcumin, a natural polyphenol found in turmeric, has been reported to have anti-tumor properties. However, the mechanism by which curcumin acts against GC remains unclear. In this study, we combined approaches such as network pharmacology, GEO microarray analysis, molecular docking and molecular dynamics, bioinformatics, and in vitro experiments to explore the various ways in which curcumin may act on GC. METHODS Curcumin targets were predicted using TCMSP, SwissTargetPrediction, TargetNet, and PharmMapper, and standardized using UniProt. GC differential genes were derived from GEO GSE54129. Overlapping targets were analyzed using STRING protein-protein interaction networks, with hubs identified using cytoHubba and MCODE. GO and KEGG enrichment analyses were performed to determine significantly enriched biological functions and pathways. Docking and 100-ns Molecular Dynamics (MD) were used to assess binding stability. GEPIA and TCGA validated target expression and immune-correlated gene expression. in vitro, SGC-7901 cells underwent CCK-8, colony formation, wound-healing, and Western blot analysis to evaluate CYP1A2, CYP3A4, and CYP2D6 expression. RESULTS We identified 439 curcumin targets, 1,619 GC differential genes, and 83 overlaps. Hubs were MMP9, SERPINE1, PLAU, and MMP3. GO terms highlighted responses to chemicals and oxygen-containing compounds, extracellular vesicle processes, and related processes. KEGG pathways included cytochrome P450 metabolism, arachidonic acid metabolism, apoptosis, etc. Docking (Vina) predicted favorable binding poses, with binding energies (kcal/mol) of -7.3 for SERPINE1, -6.8 for MMP3, -6.7 for MMP9, and -5.9 for PLAU. MD supported structural plausibility across all four hubs. GEPIA and TCGA showed higher mRNA levels of these targets in GC and significant associations with neutrophils, macrophages, and dendritic cells. Curcumin reduced SGC-7901 viability in a concentration-dependent manner (IC50 24.4 μM), suppressed colony formation and migration, and increased CYP1A2, CYP3A4, and CYP2D6 expression (P < 0.01). DISCUSSION Data indicate curcumin targets ECM remodeling and proteolysis via MMP9, MMP3, SERPINE1, and PLAU, and modulates metabolic and inflammatory signaling, including cytochrome P450. Concordance across in silico, bioinformatics, and cell assays supports a multi-target mechanism. Limitations include reliance on a single dataset and cell line, lack of in vivo validation, and curcumin's low bioavailability. CONCLUSION Curcumin engages MMP9, SERPINE1, PLAU, and MMP3 and regulates cytochrome P450 and inflammation-related pathways, thereby inhibiting GC cell proliferation, clonogenicity, and migration. These findings provide a mechanistic basis for further in vivo and translational studies of curcumin-based strategies in GC.

Integrating in silico modeling and experimental validation to determine the anti-breast cancer mechanisms of mulberry leaf bioactive compounds.

Breast cancer (BRCA) is the most prevalent malignancy and leading cause of cancer-related death in women. To elucidate the anti-BRCA mechanisms of mulberry leaves (ML), the present study used an integrated strategy combining network pharmacology, molecular docking and in vitro validation. The active components of ML, their putative targets and BRCA-related proteins were screened from public databases (Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform, and Encyclopedia of Traditional Chinese Medicine). A protein-protein interaction network was constructed using Cytoscape, followed by Gene Ontology (GO) biological function and Kyoto Encyclopedia of Genes and Genes (KEGG) pathway analyses through the Database for Annotation, Visualization and Integrated Discovery. Molecular docking was then conducted to assess the binding affinities of key compounds to prioritized targets. In vitro assays (MTT, wound healing and flow cytometry) were performed to evaluate the effects of ML on MDA-MB-231 cell proliferation, migration, apoptosis and cell cycle progression. Western blotting was conducted to validate core target proteins. In total, nine bioactive ML compounds (such as quercetin and stigmasterol) were identified, targeting six core proteins [tumor protein p53, estrogen receptor 1 (ESR1), catenin β1, AKT serine/threonine kinase 1, MYC proto-oncogene/BHLH transcription factor and telomerase reverse transcriptase]. GO analysis revealed enrichment in 'nucleoplasm', 'enzyme binding' and 'cellular response to hypoxia' terms, whilst KEGG pathway analysis results highlighted 'cancer-related pathways' (such as PI3K/AKT). Stigmasterol exhibited the strongest binding affinity to ESR1 (in silico). In vitro, ML extract significantly suppressed MDA-MB-231 proliferation and migration, induced apoptosis and triggered G2/M arrest. Western blotting confirmed the downregulation of oncoproteins (TP53, AKT1, ESR1 and JUN). The results of the present study suggest that ML can inhibit the proliferation and migration of BRCA cells whilst inducing their apoptosis by regulating the expression of key proteins. This provides a scientific basis for the in-depth exploration of the anti-BRCA mechanism of ML.

Network pharmacology-guided identification of Rabdosia rubescent as a suppressor of laryngeal cancer via MMP9-mediated extracellular matrix remodeling: integrated in silico and experimental validation

Background Laryngeal cancer, particularly laryngeal squamous cell carcinoma (LSCC), poses a significant threat to global health, especially within Asian populations. While Rabdosia Rubescens is known for its antitumor properties, the specific bioactive compounds and mechanisms underlying its activity against laryngeal carcinoma remain to be fully elucidated. Methods This study employed an integrated approach combining network pharmacology, molecular docking, and 500 ns molecular dynamics simulations to screen bioactive compounds from Rabdosia Rubescens. Key therapeutic targets were identified and validated using transcriptomic data from The Cancer Genome Atlas (TCGA). The most promising candidate was subsequently validated in vitro using cytotoxicity assays (TU177 and RK33 cell lines) and wound healing migration assays, alongside MMP9 knockdown models to confirm mechanistic specificity. Results Network pharmacology identified MMP9 as a critical therapeutic target, which was found to be significantly overexpressed in LSCC tissues. Virtual screening and MD simulations identified Cirsiliol as the most potent inhibitor among the tested phytochemicals, exhibiting a highly favorable binding free energy (ΔGbinding = −179.793 kJ/mol) and stable interactions with key residues (ALA189, HIS266, and LEU243). Experimental validation demonstrated that Cirsiliol induced dose-dependent growth inhibition with IC50 values of 31.59 μM in TU177 cells and 17.73 μM in RK33 cells. Furthermore, the compound significantly suppressed cell migration, mirroring the effects observed in MMP9-knockdown TU177 cells. Conclusion This study establishes Cirsiliol as a potent, specific inhibitor of MMP9 derived from Rabdosia Rubescens. By effectively targeting the MMP9 pathway, Cirsiliol suppresses tumor invasiveness and migration, highlighting its potential as a promising lead compound for the treatment of laryngeal cancer.