Disrupting tumour progression and immune evasion in ovarian cancer via STAT3/NFKB1/MTOR axis: network pharmacology and thermodynamic mechanistic analysis of Annona cherimola

Ovarian cancer remains a leading cause of gynecological cancer mortality, highlighting the urgent need for novel therapeutics. Annona cherimola (AC), long recognized for its medicinal uses, is underexplored for anticancer potential. This study employed an integrative computational strategy—combining network pharmacology, molecular docking, and molecular dynamics (MD) simulations—to elucidate the multi-target mechanisms of AC phytochemicals against ovarian cancer. Twenty bioactive compounds, mainly acetogenins, alkaloids, and phenolics, were identified, with 312 overlapping targets mapped to ovarian cancer genes. Protein–protein interaction analysis revealed hub genes including STAT3, NFKB1, and MTOR, while enrichment analyses linked them to key oncogenic and immune pathways. Docking and 200 ns MD simulations with MM/GBSA calculations demonstrated strong and stable interactions, with Anonaine and Liriodenine showing superior binding to reference inhibitors. These compounds appear to regulate signaling cascades associated with tumor progression, immune evasion, and therapy resistance. Overall, this work provides compelling in silico evidence for the multi-targeted anticancer potential of AC phytoconstituents, establishing a strong foundation for experimental validation and positioning AC as a promising source of candidate agents for ovarian cancer therapy.