Supplemental Material of Docking-Assisted Hybridization Chain Reaction Strategy Based on Bifunctional Hairpin Probes for Ultrasensitive Analysis of 17β-Estradiol

17β-Estradiol (E2), an endogenous estrogen, can be present in milk and may accumulate during processing, potentially contributing to long-term dietary exposure that raises concerns for consumer health. Regulatory agencies have established intake limits to minimize risk, highlighting the importance of reliable monitoring. In this study, we developed a docking-guided dual-mode aptasensor for sensitive, selective, and practical detection of E2 in complex dairy matrices. Molecular docking analyses revealed critical binding interactions within the aptamer, elucidating the spatial arrangement and chemical environment of the E2 recognition pocket. Van der Waals contacts dominated binding, with residues A41 and A7 serving as key anchoring points that stabilize E2 at the hairpin neck, forming a compact hydrophobic cavity that promotes selective recognition. These structural insights directly guided the rational design of bifunctional hairpin probes, enabling precise control of hairpin switching and hybridization chain reaction (HCR) amplification, while maintaining recognition fidelity under complex sample conditions such as milk, where matrix effects could perturb aptamer structure. Integrating these docking-informed designs with sequence optimization, the platform simultaneously employs 2-aminopurine (2-AP) fluorescence and gold nanobipyramids (AuNBPs)-based multicolor plasmonic readouts, achieving low detection limits of 7.71 pM and 88.9 pM with strong specificity and anti-interference capability.. The complementary dual-mode signals enhance detection reliability and reduce the risk of false positives by cross-validating fluorescence and colorimetric outputs. Coupled with a semi-quantitative visual color chart and a smartphone-assisted interface, this system enables intuitive, on-site, and user-friendly analysis. Application to real milk samples demonstrated reproducible performance, highlighting its potential for routine E2 surveillance, proactive food-safety management, quality assurance, and consumer health protection, while providing a generalizable framework for developing robust nucleic acid sensors targeting diverse small-molecule contaminants in the dairy industry.