Mechanistic insights into daidzin from Glycine max against breast cancer via network pharmacology and multi-level molecular modeling

Abstract

Breast cancer remains a major cause of morbidity and mortality in women, with around 2.3 million new cases and 670,000 deaths worldwide in 2022. Daidzin, a soy isoflavone glycoside from Glycine max, is a candidate bioactive scaffold, but its breast cancer-relevant mechanisms remain poorly defined. This study used an integrated in silico strategy combining network pharmacology and molecular modeling to prioritize daidzin targets and validate key interactions, with sirtinol as a reference compound. Target prediction identified 101 putative daidzin targets, and intersection with breast cancer-associated genes yielded 97 common targets. Protein-protein interaction analysis highlighted hub genes including ALB, TNF, MMP9, CASP3, SRC, ITGB1, MMP2, ESR1, IL2, and HSP90AA1. Enrichment analyses suggested convergence on extracellular/vesicle-related functions, metallopeptidase activity, and pathway modules spanning metabolism, inflammation, endocrine signaling, and cancer circuitry. Docking against ten hub proteins produced binding energies from −6.00 to −11.49 kcal/mol, with the strongest affinity for MMP9 (6ESM; −11.49 kcal/mol), exceeding B9Z (−10.54 kcal/mol) and sirtinol (−10.59 kcal/mol). Molecular dynamics simulations indicated stable complexes, and Molecular Mechanics Generalized Born Surface Area (MMGBSA) supported stronger binding for daidzin-MMP9 (−46.86 ± 3.83 kcal/mol) than sirtinol-MMP9 (−14.12 ± 8.99 kcal/mol). Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) prediction indicated favorable safety-related flags for daidzin, although lower predicted intestinal absorption and Caco2 permeability than sirtinol suggest potential exposure-related limitations. Density Functional Theory (DFT) analysis supported comparatively greater electronic stability. Collectively, the results prioritize a daidzin-MMP9 axis for experimental validation.