Integrative multi-transcriptomics and network pharmacology reveal natural therapeutics as anti-cancer agents...

Ovarian cancer (OC) remains one of the most lethal gynecologic malignancies, largely because it is often diagnosed late, recurs frequently, and develops resistance to conventional chemotherapy. These challenges emphasize the urgent need for novel and less toxic therapeutic strategies. In this study, we applied an integrative in silico workflow combining transcriptomic analysis, network biology, pan-cancer exploration, and computational drug discovery to identify potential phytochemical inhibitors targeting Aurora kinase A (AURKA) in OC. Differential gene expression analysis of three GEO datasets (GSE14407, GSE18520, and GSE26712) identified common dysregulated genes associated with OC progression. Functional enrichment and regulatory network analyses revealed strong involvement of these genes in cell-cycle regulation, mitotic progression, and cancer-related signaling pathways. Protein-protein interaction analysis identified AURKA as a central hub gene with high network connectivity and strong overexpression across multiple cancer types. Further pan-cancer analyses demonstrated significant associations of AURKA with immune infiltration patterns and recurrent genetic alterations, supporting its therapeutic relevance. After removing duplicates from the 6834 collected phytochemicals, a total of 2046 unique compounds derived from medicinal plants of the Indian subcontinent were screened against the AURKA crystal structure using molecular docking to identify potential inhibitors. Several compounds demonstrated binding affinities comparable to the reference inhibitor Y3M. Subsequent drug-likeness, ADMET, toxicity prediction, molecular dynamics simulation, MM-GBSA binding energy analysis, and quantum mechanical evaluations identified CID-87014 (2-(Hydroxymethyl)anthraquinone) as the most promising candidate. This compound exhibited stable protein-ligand interactions, favorable binding free energy, acceptable predicted pharmacokinetic properties, and balanced electronic stability throughout the analyses. Although the findings are computational and require experimental validation, CID-87014 emerged as a promising lead compound targeting AURKA and may serve as a foundation for future ovarian cancer drug development.