A Peptidoglycan-Mimetic Nanopore Receptor Resolves Glycopeptide Antibiotic Recognition and Resistance at the...

Glycopeptide antibiotics (GPAs) are a critical class of last-resort therapeutics for treating severe infections caused by multidrug-resistant Gram-positive bacteria. However, their highly similar molecular structures and binding mechanisms make accurate discrimination and mechanistic analysis challenging. Here, we report a peptidoglycan-mimetic nanopore receptor (PGP-αHL) for single-molecule fingerprinting of GPA-target interactions. The receptor incorporates a biomimetic peptide that can be stably immobilized within an αHL nanopore, thereby creating a well-defined single-molecule interface at which antibiotic binding events can be monitored in real time. Single-channel recordings reveal transient binding and unbinding events that follow a bimolecular association and unimolecular dissociation model, with kinetic parameters consistent with those obtained from isothermal titration calorimetry. Substitution of the terminal D-Ala residue with D-Ser in the peptide leads to reduced binding affinity, enabling direct observation of resistance-associated effects at the single-molecule level. In addition, the PGP-αHL platform enables reliable discrimination of structurally similar GPAs, including vancomycin, teicoplanin, and dalbavancin, achieving approximately 99% overall classification accuracy when combined with machine learning. The applicability of this approach is further demonstrated by the detection of GPA residues in spiked milk samples. This work establishes a target-mimetic nanopore receptor strategy that integrates single-molecule analysis of antibiotic-target recognition, resistance-associated binding alterations, and discrimination of structurally similar antibiotics within a unified sensing platform.