A computational approach to study functional monomer-protein molecular interactions to optimize protein molecular imprinting.

Molecular imprinting has become a promising approach for synthesis of polymeric materials having binding sites with a predetermined selectivity for a given analyte, the so-called molecularly imprinted polymers (MIPs), which can be used as artificial receptors in various application fields. Realization of binding sites in a MIP involves the formation of prepolymerization complexes between a template molecule and monomers, their subsequent polymerization, and the removal of the template. It is believed that the strength of the monomer-template interactions in the prepolymerization mixture influences directly on the quality of the binding sites in a MIP and consequently on its performance. In this study, a computational approach allowing the rational selection of an appropriate monomer for building a MIP capable of selectively rebinding macromolecular analytes has been developed. Molecular docking combined with quantum chemical calculations was used for modeling and comparing molecular interactions among a model macromolecular template, immunoglobulin G (IgG), and 1 of 3 electropolymerizable functional monomers: m-phenylenediamine (mPD), dopamine, and 3,4-ethylenedioxythiophene, as well as to predict the probable arrangement of multiple monomers around the protein. It was revealed that mPD was arranged more uniformly around IgG participating in multiple H-bond interactions with its polar residues and, therefore, could be considered as more advantageous for synthesis of a MIP for IgG recognition (IgG-MIP). These theoretical predictions were verified by the experimental results and found to be in good agreement showing higher binding affinity of the mPD-based IgG-MIP toward IgG as compared with the IgG-MIPs generated from the other 2 monomers.