Aromatic Functionality of Target Proteins Influences Monomer Selection for Creating Artificial Antibodies on Plasmonic Biosensors

Natural antibodies used as biorecognition elements suffer from numerous shortcomings, such as limited chemical and environmental stability and cost. Artificial antibodies based on molecular imprinting are an attractive alternative to natural antibodies. We investigated the role of aromatic interactions in target recognition capabilities of artificial antibodies. Three proteins with different aromatic amino acid content were employed as model targets. Artificial antibodies were formed on nanostructures using combinations of silane monomers of varying aromatic functionality. We employed refractive index sensitivity of plasmonic nanostructures as a transduction platform for monitoring various steps in the imprinting process and to quantify the target recognition capabilities of the artificial antibodies. The sensitivity of the artificial antibodies with aromatic interactions exhibited a protein-dependent enhancement. Selectivity and sensitivity enhancement due to the presence of aromatic groups in imprinted polymer matrix was found to be higher for target proteins with higher aromatic amino acid content. Our results indicate that tailoring the monomer composition based on the amino acid content of the target protein can improve the sensitivity of plasmonic biosensors based on artificial antibodies without affecting the selectivity.