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

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Simulation of protein-imprinted polymers. 3. Imprinting selectivity.

Liora Levi¹, Simcha Srebnik

¹Department of Chemical Engineering, Technion-Israel Institute of Technology, Haifa, Israel.

The Journal of Physical Chemistry. B

|October 21, 2011

Summary

Molecular imprinting for proteins is challenging. This study uses a simulation model to show that protein surface charge distribution significantly impacts selectivity in imprinted polymers, guiding better template selection.

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Area of Science:

Polymer Science
Biophysical Chemistry
Materials Science

Background:

Molecular imprinting creates artificial recognition polymers for target molecules.
This technique is effective for small molecules but struggles with larger templates like proteins.
Previous work investigated protein-imprinted pore structures and imprinting factors.

Purpose of the Study:

To investigate imprinting conditions affecting the separation factor for protein imprinting.
To understand how protein size, charge density, and surface charge distribution influence selectivity.
To evaluate the impact of polymerization conditions on the separation factor.

Main Methods:

Development of a simple simulation model for protein imprinting.
Calculation of the separation factor based on template and competitor protein interaction energies.
Analysis of protein size, charge density, and surface charge distribution effects.
Evaluation of various polymerization conditions.

Main Results:

The model confirms that increased polymer surface functionality enhances the imprinting factor but reduces selectivity.
Protein surface charge distribution was identified as a critical factor for selectivity in protein-imprinted polymers.
The study suggests that certain proteins are more suitable for molecular imprinting than others.

Conclusions:

Protein imprinting selectivity is strongly influenced by the template protein's surface charge distribution.
Simulation models can effectively study protein imprinting parameters and predict outcomes.
Findings guide the selection of appropriate protein templates for developing selective molecularly imprinted polymers.