Molecular Simulation Guided Optimization of Multi-Epitope Nanobody Affinity for Enhanced Förster Resonance Energy Transfer System Performance

Förster resonance energy transfer (FRET) based detection systems are indispensable for pathogen screening due to their rapid response, high molecular specificity, and operational simplicity. However, current probes suffer from low sensitivity, poor environmental adaptability, and epitope interference, which significantly limit detection performance. To overcome these challenges, we developed novel multiepitope probes (MEPs) with high sensitivity, robustness, and coordinated epitope recognition, layered onto a prevalidated nanobody panel to streamline compatibility assessment and affinity optimization. As proof of concept, rotavirus was selected as the detection model, and molecular docking was employed as an auxiliary tool to identify a high-performance tetra-epitope nanobody sandwich complex. The nanobodies were individually conjugated to high-quality luminescent microspheres to construct MEPs and integrated into a rapid, sensitive homogeneous FRET detection system. Importantly, site-directed saturation mutagenesis of key amino acids within the MEPs further enhanced FRET sensitivity by 10.18-fold. Within 50 min, the MEPs-based FRET signal exhibited a linear response to rotavirus VP6 protein concentrations ranging from 1.56 and 50 pg/mL, with a detection limit of 0.83 pg/mL─representing a 1566-fold reduction compared with conventional monoclonal antibody-based FRET detection systems (1.3 ng/mL). Systematic evaluations confirmed that the MEPs-based FRET system delivers outstanding sensitivity, specificity, stability, and accuracy, underscoring its strong potential for real-world applications. Overall, this work introduces a novel strategy for creating high-performance FRET systems for large-protein detection and offers an innovative tool for public safety monitoring and pathogen detection.