Enantioselective Recognition and Detection of Cysteine Using a Three-Dimensional Mn1/3Zn2/3CO3-rGO/CNT Heterostructure-Based Molecularly Imprinted Sensor

Abstract

Enantioselective recognition of chiral molecules, particularly cysteine enantiomers (L/D-Cys), is crucial in life sciences, drug development, and clinical diagnostics due to their distinct physiological effects. However, conventional methods often lack sufficient selectivity and sensitivity. Herein, a molecularly imprinted electrochemical sensor based on a three-dimensional (3D) heterostructured Mn1/3Zn2/3CO3-rGO-CNTs was developed for highly selective detection of cysteine enantiomers. The Mn1/3Zn2/3CO3-rGO microspheres were successfully synthesized via a one-pot hydrothermal method, and combined with carbon nanotubes to construct a 3D carrier with high specific surface area and excellent conductivity. XPS, SEM, and TEM characterizations its suitability as an ideal platform for molecular imprinting. Using L-Cys or D-Cys as the template molecule, the chiral recognition sites were constructed on the modified electrode interface via electropolymerized polypyrrole, achieving efficient enantiomer differentiation. Combined with a pH/potential dynamic rapid-switching detection mode, the sensor exhibited significantly enhanced detection efficiency with the response time of 2 s. This proposed sensor demonstrated a wide linear range of 1×10-7 to 1×10-3 mol/L for L-Cys detection, and exhibited significant enantioselectivity at the same concentration (L/D = 4.248 ± 0.01, D/L = 5.033 ± 0.50). This method offers high sensitivity and stability, and applicability for complex biological sample analysis, providing a robust technical platform for chiral recognition and pharmaceutical research.

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Article information

Article type
Paper
Submitted
02 Dec 2025
Accepted
17 Feb 2026
First published
19 Feb 2026

Anal. Methods, 2026, Accepted Manuscript

Enantioselective Recognition and Detection of Cysteine Using a Three-Dimensional Mn1/3Zn2/3CO3-rGO/CNT Heterostructure-Based Molecularly Imprinted Sensor

Y. Rao, Q. Jian, C. Tan, X. Yu, X. Jiang, H. Dai, J. Zhang, L. Wu, D. Li and Z. Cao, Anal. Methods, 2026, Accepted Manuscript , DOI: 10.1039/D5AY01993A

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