An integrated multi-disciplinary approach to elucidate the molecular mechanism of liuwei dihuang pills in menopausal syndrome

Objective: Menopausal syndrome (MS) is a common condition affecting women during menopause. Liuwei Dihuang pills (LWDHP) exert therapeutic effects in alleviating MS symptoms; however, their underlying mechanisms remain incompletely understood. This study aimed to elucidate the therapeutic mechanisms of LWDHP for MS by combining network pharmacology, Mendelian randomization (MR), molecular docking, molecular dynamics (MD) simulation, and summary-data-based Mendelian randomization (SMR) analyses. Materials: Active constituents of LWDHP were extracted from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database and the Herb database, while targets associated with MS were gathered from GeneCards, OMIM, DrugBank, PharmGKB, Therapeutic Target Database (TTD), and MalaCards. SMR analysis precisely identified genes with potential pleiotropic associations with MS. A protein-protein interaction (PPI) network for key targets was constructed using the STRING database and analyzed with Cytoscape software. Topological analysis using the MCODE plugin identified the core network. Tissue/organ distribution of targets was analyzed using BioGPS. Disease Ontology (DO) analysis was performed with R software. DAVID was used to carry out Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, and molecular docking along with MD simulations served to confirm the interactions between active compounds and core targets. The TRRUST, MiRwalk, and STARbase databases were utilized to construct a ‘transcription factor (TF)-key target’ regulatory network and a competing endogenous RNA (ceRNA) network. Finally, MR analysis further assessed the causal relationship between key genes and menopausal symptoms. Results: Through network pharmacology, 69 bioactive components and their 1040 associated targets in LWDHP were identified. After screening, 3111 MS-related targets were obtained, with 513 overlapping targets between LWDHP and MS. SMR analysis revealed 133 genes with potential pleiotropic links to MS. PPI network construction and topological analysis further identified nine core genes: TP53, GAPDH, SRC, MAPK3, ESR1, NF-κB1, MMP9, SIRT1, and PTGS2. BioGPS analysis indicated high expression of these 133 genes in immune system cells, whole blood, and liver. DO enrichment revealed diseases sharing pathogenic mechanisms with MS, including breast cancer, thoracic cancer, and type 2 diabetes mellitus. GO enrichment indicated that LWDHP affects 51 biological processes (BP), 15 cellular components (CC), and 13 molecular functions (MF). KEGG analysis identified the PI3K-Akt signaling pathway as most significantly associated with MS, with TP53, NF-κB1, and MAPK3 enriched within this pathway. Molecular docking and 100-ns MD simulations demonstrated favorable binding affinity and structural stability between three active compounds (sitosterol, kadsurenone, and mudanpioside C) and four core targets (TP53, NF-κB1, MAPK3). Binding free energy calculations and residue decomposition analysis, supported by root-mean-square deviation (RMSD) and root-mean-square fluctuation (RMSF) data, further validated strong binding interactions and stability. MR analysis confirmed causal links between TP53, MAPK3, NF-κB1 and MS. Network analyses constructed a TF-key target network (1 TF for MAPK3, 49 for TP53, 38 for NF-κB1) and predicted 68 TFs and 165 miRNAs associated with NF-κB1. A ceRNA network comprising 17 miRNAs, 73 lncRNAs, and 3 mRNAs was also established. Conclusion: Our results demonstrated that LWDHP alleviates MS by modulating the PI3K-Akt pathway and targeting TP53, NF-κB1, and MAPK3, with sitosterol, kadsurenone, and mudanpioside as its key active components, providing a solid foundation for its clinical application.