Design and fabrication of a smart sensor using in silico epitope mapping and electro-responsive imprinted polymer nanoparticles for determination of insulin levels in human plasma
Abstract
A robust and highly specific sensor based on electroactive molecularly imprinted polymer nanoparticles (nanoMIP) was developed. The nanoMIP tagged with a redox probe, combines both recognition and reporting capabilities. The developed nanoMIP replaces enzyme-mediator pairs used in traditional biosensors thus, offering enhanced molecular recognition for insulin, improving performance in complex biological samples, and yielding high stability. Also, most of existing sensors show poor performance after storage. To improve costs of the logistics and avoid the need of cold storage in the chain supply, we developed an alternative to biorecognition system that relies on nanoMIP. NanoMIP were computationally designed using "in-silico" insulin epitope mapping and synthesized by solid phase polymerisation. The characterisation of the polymer nanoparticles was performed by transmission electron microscopy (TEM), dynamic light scattering (DLS), Fourier-transform Infrared (FT-IR) and surface plasmon resonance (SPR). The electrochemical sensor was developed by chemical immobilisation of the nanoMIP on screen printed platinum electrodes. The insulin sensor displayed satisfactory performances and reproducible results (RSD = 4.2%; n = 30) using differential pulse voltammetry (DPV) in the clinically relevant concentration range from 50 to 2000 pM. The developed nanoMIP offers the advantage of large number of specific recognition sites with tailored geometry, as the resultant, the sensor…
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Evidence Hub reads this as a experimental / empirical study, done in computer models (in silico), not in people. Its evidence level is 5 of 5 (Very low · case / narrative / animal / in vitro / in silico). Case reports, narrative reviews, and animal, cell or computer-model studies give the weakest evidence for human health. Reported size: 30 participants or records.
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