Nanopore-Based Multiparametric Single-Molecule Protein Detection: From Structural Analysis to Clinical Translation

Single-molecule protein analysis is crucial for elucidating biological processes and enabling early disease diagnosis. Nanopore sensing technology, owing to its label-free operation, high throughput, and direct electrical readout, has emerged as a highly promising platform for protein analysis. This review summarizes recent advances in nanopore-based protein analysis, with an emphasis on the detection of both folded and unfolded proteins. We discuss protein size and shape analysis based on ionic-current blockade signals, the monitoring of conformational changes, the characterization of protein unfolding and unfolded proteins, the detection of posttranslational modifications (PTMs), and highly sensitive quantitative analysis. We further highlight the integration of machine learning to improve signal classification and analytical performance. In addition, we review recent applications in complex biological samples, including serum and urine, and discuss the challenges that currently limit practical implementation. Finally, we outline key future directions, including the integration of nanopore arrays, optical readout, and machine-learning-assisted analysis, which may synergistically enhance throughput, signal quality, and data-processing capabilities and thereby accelerate clinical translation.