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Ultrasensitive Detection of Biomarkers by Using a Molecular Imprinting Based Capacitive Biosensor

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Potentiometric sensor based on a computationally designed molecularly imprinted receptor.

Guohua Cui¹, Rongning Liang¹, Wei Qin²

¹CAS Key Laboratory of Coastal Environmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research (YIC), Chinese Academy of Sciences (CAS), Shandong Key Laboratory of Coastal Environmental Processes, YICCAS, Yantai, Shandong, 264003, PR China.

Analytica Chimica Acta

|January 11, 2023

Summary

This summary is machine-generated.

Computer-aided design accelerates the development of molecularly imprinted polymer (MIP) sensors. This study uses computational methods to select functional monomers, improving the efficiency of creating selective potentiometric sensors for organic species like sulfadiazine.

Keywords:

Computer-aided design Ion-selective electrode Molecularly imprinted polymer Potentiometry Sulfadiazine

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Area of Science:

Analytical Chemistry
Materials Science
Computational Chemistry

Background:

Molecularly imprinted polymer (MIP)-based sensors offer potential for detecting organic species.
Traditional MIP receptor preparation relies on empirical, time-consuming trial-and-error monomer selection.

Purpose of the Study:

To apply computer-aided design (CAD) for the selection of functional monomers in MIP receptor synthesis.
To develop a more efficient and facile method for fabricating MIP-based potentiometric sensors.

Main Methods:

Density Functional Theory (DFT) calculations using the B3LYP model and 6-31G(d) basis set were employed.
Binding energies between template molecules and functional monomers were calculated to guide monomer selection.
A potentiometric sensor was fabricated using the computationally designed MIP receptor.

Main Results:

The computer-aided approach successfully identified optimal functional monomers for MIP synthesis.
The resulting MIP-based sensor demonstrated high sensitivity (1-10 μM linear range) and good selectivity for the antibiotic sulfadiazine.
The study validates the efficacy of computational methods in MIP receptor design.

Conclusions:

Computer-aided synthesis provides a general and efficient alternative to traditional empirical methods for MIP receptor preparation.
This approach can be broadly applied to the fabrication of various MIP-based electrochemical and optical sensors.
The developed method streamlines the design process for selective molecular recognition materials.