Computational insights into C–O–C-type Biflavonoids as multi-target inhibitors of ER α, PR, EGFR, and mTOR in breast cancer therapy

Abstract

Breast cancer (BC) remains a leading cause of cancer-related mortality worldwide. Its molecular complexity and pathway cross-talk often reduce the effectiveness of single-target therapies, highlighting the need for multi-targeted approaches. Secondary metabolites have emerged as valuable scaffolds for anticancer drug discovery owing to their structural diversity and broad bioactivity. In this study, we investigated six C–O–C-type biflavonoids – Delicaflavone ( c 1 ), Lophirone L ( c 2 ), Hinokiflavone ( c 3 ), Ochnaflavone ( c 4 ), Lanaroflavone ( c 5 ), and Loniflavone ( c 6 ) – for their potential to inhibit four key BC-related targets: ER α (estrogen receptor), PR (progesterone receptor), EGFR (epidermal growth factor receptor), and mTOR (mechanistic target of rapamycin), using an integrated computational approach. Molecular docking revealed strong binding affinities for all compounds, outperforming reference drugs such as Tamoxifen . Quantum chemical descriptors derived from density functional theory (DFT) confirmed their favorable electronic properties, suggesting high reactivity and stability. ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) predictions indicated acceptable drug-likeness, low toxicity, and promising pharmacokinetic profiles. Molecular dynamics (MD) simulations validated the stability of the complexes, as reflected by consistent RMSD (root mean square deviation), RMSF (root mean square fluctuation), Rg (radius of gyration), and hydrogen-bond profiles over 100 ns simulations. Furthermore, binding free energy (BFE) calculations using MM-PBSA and MM-GBSA approaches supported the high affinity and stable binding of the compounds, with per-residue decomposition highlighting key interactions within the active sites. Overall, this study provides compelling evidence for the multitarget inhibitory potential and favorable pharmacological profiles of these biflavonoids. The findings suggest that these compounds represent promising lead scaffolds for further experimental evaluation as anti-breast cancer agents. This comprehensive in silico workflow – integrating molecular docking, DFT, ADMET, MD, and BFE analyses – offers a rational strategy for drug discovery targeting multifactorial cancers such as BC. • Six C–O–C-type biflavonoids (Delicaflavone, Lophirone L, Hinokiflavone, Ochnaflavone, Lanaroflavone, and Loniflavone) were identified as potent multitarget inhibitors of ER α , PR, EGFR, and mTOR through comprehensive in silico screening. • Molecular docking and MM-PBSA/GBSA calculations confirmed strong and stable binding of selected biflavonoids, outperforming Tamoxifen in several cases. • DFT-based quantum chemical analysis revealed favorable electronic properties such as low HOMO–LUMO gaps, indicating high reactivity and antioxidant potential. • ADMET and toxicity profiling predicted excellent drug-likeness, low toxicity, and acceptable pharmacokinetic behavior across all compounds. • Molecular dynamics simulations (100 ns) showed stable protein–ligand complexes with consistent RMSD, RMSF, Rg, and hydrogen bonding, supporting their potential as lead compounds in breast cancer therapy.