In silico identification of CDK1 as a candidate target in breast cancer via integrative transcriptomic and docking analysis of Moringa Oleifera compounds

We combined transcriptomic profiling, network biology, and structure-based computational modeling to explore potential therapeutic targets in breast cancer. Analysis of GEO dataset GSE134359 identified 4,140 genes significantly upregulated in tumor samples (FDR < 0.05; |log₂FC| >1). Network clustering (MCODE) revealed nine functional modules, with the top module (49 nodes, 1,114 edges) enriched for mitotic control. Hub analysis (MCC) highlighted CDK1 as a key regulator of the G₂/M transition, supported by GO enrichment in chromosome segregation, spindle assembly, and immune modulation. A curated library of 137 Moringa oleifera–derived phytochemicals was docked against CDK1 using a GLIDE XP–Induced-Fit–MM-GBSA pipeline. Among these, gossypetin, quercetagetin, and luteolin demonstrated favorable docking scores (≤ − 11.578 kcal/mol), binding energies (up to − 44.83 kcal/mol), and predicted pIC₅₀ values. ADME profiling and QSAR modeling further suggested their drug-likeness and potential bioactivity. While this study is entirely computational, it provides predictive insights that support the prioritization of CDK1 and selected phytochemicals for future in vitro validation and preclinical exploration in breast cancer research.