4.7 Article

Peptide nanotubes/self-assembled polydopamine molecularly imprinted biochip for the impedimetric detection of human Interleukin-6

Journal

BIOELECTROCHEMISTRY
Volume 145, Issue -, Pages -

Publisher

ELSEVIER SCIENCE SA
DOI: 10.1016/j.bioelechem.2022.108053

Keywords

Interleukin-6; Molecularly imprinted; Polydopamine; Peptide nanotube; Impedimetric detection

Funding

  1. Research Council of Hacettepe University [FCP-2019-18214]

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An impedimetric biochip with molecularly imprinted polydopamine was developed for the detection of interleukin 6. The biochip showed excellent performance and selectivity, making it a promising tool for rapid and accurate IL-6 detection.
In the study, an impedimetric biochip was designed with molecularly imprinted polydopamine (MIP (pDa)) on peptide nanotube (PNT) functionalized screen printed electrodes (SPEs) and adopted first time as a support matrix to construct the electrochemical sensor for the determination of interleukin 6 (IL-6). IL-6, which is one of the important cytokines, was used as a template molecule during the self-assembly polymerization strategy of dopamine. Dopamine acted as a functional monomer and self-polymerization occurred without any initiator, enzyme, or crosslinker. Impedimetric, spectrometric, and morphological characterization data demonstrated that MIP(pDa)/PNT provided satisfactory performance for the impedimetric diagnosis of IL-6. Analyzed IL-6 biomolecules could be detected in the range of 1- 200 pg/mL due to the good correlation between the redox pair response and the logarithm of IL-6 con-centration. The MIP(pDa)/PNT electrode was capable of selective binding for IL-6 with high recovery val-ues in urine sample. The designed methodology allowed us to detect IL-6 with an effective, facile and inexpensive route that was easy to fabricate and scale-up. The coupling of MIP(pDa)/PNT with SPEs and the use of the impedimetric detection approach holds great potential to provide a new avenue for clinical diagnostics because in these systems small volumes of samples can be analyzed without the need for any pre-processing steps in short times.(c) 2022 Elsevier B.V. All rights reserved.

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