Enzyme-Mimics for Sensitive and Selective Steroid Metabolite Detection

• Published in: ACS applied materials & interfaces Vol. 15; no. 11; pp. 13971 - 13982
• Main Authors: Yeasmin, Sanjida, Ullah, Ahasan, Wu, Bo, Zhang, Xueqiao, Cheng, Li-Jing
• Format: Journal Article
• Language: English
• Published: United States American Chemical Society 12.03.2023
• Subjects: Biological and Medical Applications of Materials and Interfaces; cortisol; electrochemical; molecularly imprinted polymer; enzyme-mimics; steroids; electrocatalysis
• ISSN: 1944-8244; 1944-8252
• DOI: 10.1021/acsami.2c21980

We present an enzyme-like functional polymer that recognizes nonelectroactive targets and catalyzes their redox reactions for simple, selective steroid metabolite detection. Measuring steroid metabolites, such as cortisol, has been widely adopted to diagnose stress and chronic diseases. Conventional detection method based on competitive immunoassay requires time-consuming labeling processes for signal transduction and unstable biological receptors for biorecognition yet with limited selectivity. Inspired by natural enzymes’ target specificity and catalytic nature, we report an enzyme-mimic using electrocatalytic molecularly imprinted polymers (EC-MIP) to achieve label-free, external redox reagent-free, sensitive, and selective electrochemical detection of cortisol. The EC-MIP sensor contains molecularly imprinted cavities for specific cortisol binding and embedded copper phthalocyanine tetrasulfonate (CuPcTS) for electrocatalytic reduction of the ketones on the captured cortisol into alcohols. The direct sensing approach resolves the intrinsic limitations of conventional MIP-based sensors, most notably the use of external redox probes and weak sensing signals. The sensor exhibited a detection limit of 181 pM with significantly enhanced selectivity using a differential sensing mechanism. The new enzyme-like sensor can be modified to detect other targets, offering a simple, robust approach to future health monitoring technologies.