An arginine chiral sensor based on walnut-like molecularly imprinted polymers
Enantioselective discrimination of chiral amino acids is critically important across biomedicine, pharmacology, and food science, given the distinct biological roles of D- and L-enantiomers. In this study, a novel chiral sensor based on walnut-shaped molecularly imprinted polymers (w-MIPs) was developed for the highly sensitive and selective recognition of D- and L-arginine (Arg). The unique core-shell w-MIPs architecture, containing targeted binding sites, was synthesized <i>via</i> tailored precipitation polymerization and characterized using transmission electron microscopy (TEM), atomic force microscopy (AFM), and Fourier transform infrared spectroscopy (FT-IR). The sensing mechanism for Arg detection involves two consecutive steps. First, Arg molecules which diffuse to specific w-MIPs recognition sites are preferentially captured by the specific w-MIPs recognition sites. Subsequently, the Arg molecules captured on the electrode surface underwent oxidation. Electrochemical characterization demonstrated the exceptional performance of the chiral sensor, exhibiting a broad linear range of 0.005-5000 nM and ultra-low detection limits (1.34 pM for L-Arg; 1.20 pM for D-Arg). Importantly, the sensor exhibits high binding affinity for L-Arg, enabling effective chiral discrimination. This capability was validated by accurately determining L-Arg levels in pig serum (recovery: 95.0-103.0%), with results showing excellent agreement with HPLC analysis. This work establishes w-MIPs as a powerful platform for chiral sensing, offering significant potential for applications in drug monitoring, clinical diagnostics, and biochemical analysis.
Authors
- Sha Luo (ORCID: https://orcid.org/0000-0001-8942-8350)
- Xuan Yuan (ORCID: https://orcid.org/0000-0002-7304-9927)
- Dan Li (ORCID: https://orcid.org/0000-0003-2691-0275)
- Zhong Cao (ORCID: https://orcid.org/0000-0001-8521-2552)
- Liming Huang
- Siying Chen (ORCID: https://orcid.org/0000-0003-1773-0475)
- Yiyun Liu (ORCID: https://orcid.org/0009-0001-6941-8611)
- Xin Yi
- R. Liu (ORCID: https://orcid.org/0000-0002-7774-8696)
- Ling Wu (ORCID: https://orcid.org/0009-0000-1303-1672)
Institutions
- Changsha University of Science and Technology (CN)
Publication Details
- Journal
- Analytical Methods
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1039/d5ay00605h
- Citations
- 2
- Primary Topic
- Mass Spectrometry Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 1.51