DOI: 10.1021/jacs.6c15448 ISSN: 0002-7863

Molecular Programming of Steric Tags for Controlled Nanopore Translocation toward Precision Clinical Diagnostic Assistance

Yiheng Liu, Shijun Lin, Minglun Li, Hao Fang, Zhicheng Zhang, Ruwei Wei, Yan Zhang, Jun Dai, Tao Liu, Fan Xia, Xiaoding Lou

Abstract

The precise resolution of single-molecule events is often limited by the stochastic thermal motion of analytes, which traverse nanoscale sensing zones too rapidly for conventional detection bandwidths. This remains a fundamental challenge in nanopore chemistry, particularly for small and flexible peptides. Here, we report a chemically intuitive molecular programming strategy─steric blockage-enabled slow translocation (SLOW-Trans)─that overcomes this physical limitation through the rational design of sterically demanding probe molecules. By site-specifically conjugating rigid aromatic steric tags with precisely defined dimensions to peptide substrates, we actively reshape the translocation energy landscape within the ∼1.2 nm constriction of the M2MspA nanopore. Systematic variation of tag size and rigidity enables deterministic control over peptide residence time, transforming transient stochastic events into stable and highly discriminable current signatures. Using this strategy, we achieve a six-order-of-magnitude dynamic range (0.001–1000 ng/mL) for matrix metalloproteinases (MMP-1, -2, and -9). In a cohort of 231 clinical urine samples, the nanopore-derived MMP activity profiles showed excellent agreement with ELISA-derived measurements and, when integrated with a machine-learning classifier, enabled classification of urothelial carcinoma with 96.2% accuracy. As a proof-of-concept extension, the modular probe design was further adapted for PSA/KLK3 activity analysis in clinical serum samples, supporting the feasibility of extending the approach to an additional protease target. This work establishes a general chemical framework for programming molecular behavior in confined nanoscale environments, bridging molecular design principles with functional nanopore sensing.