Rational Hapten Engineering Enables a Monoclonal Antibody for the Masked-Mycotoxin Zearalenone-14-Glucoside and...

Masked mycotoxins pose a persistent analytical challenge because their conjugated moieties are often weakly immunogenic and poorly captured by antibodies raised against parent toxins, leading to inadequate selectivity in rapid assays. Here, we introduce a computation-guided hapten engineering strategy for selectivity-by-design toward a masked toxin epitope, integrating conformational alignment, electrostatic potential mapping, and electronic structure descriptors to prioritize epitope presentation during immunization. Using zearalenone-14-glucoside (ZEN-14G) as a model analyte, this workflow enabled the generation of mAb-1C1, a monoclonal antibody elicited directly against a masked mycotoxin. The antibody exhibits sub-ng mL^-1 competitive performance (IC₅₀ = 0.093 ng mL^-1) and a cross-reactivity profile consistent with masked-epitope preference. Docking and alanine-scanning mutagenesis establish a dual-interaction architecture in which hydrophobic contacts stabilize the conserved toxin core, while polar hotspot residues interact with the glucoside moiety, providing a mechanistic basis for selectivity. We further translate the recognition element into an indirect competitive enzyme-linked immunosorbent assay (ELISA), a rapid competitive lateral flow assay, and a smartphone-based quantitative readout that normalizes strip variability by using a C/T metric. Accuracy in multiple cereal matrices is validated against liquid chromatography-mass spectrometry/MS (LC-MS/MS). Collectively, this work demonstrates a generalizable selectivity engineering framework that links in silico hapten design, mechanistic paratope mapping, and deployable measurement formats for analytically elusive conjugated small molecules.