Using computational tools to design a molecularly imprinted polymer with selectivity and high affinity for acetylcholine

Nanomaterials are artificial materials that have been engineered to have special chemical properties. Molecularly imprinted polymers are a type of nanomaterial, which contain recognition sites with high selectivity and affinity for a template element. A neuroethological and computational approach was taken to rationally design a molecularly imprinted polymer for the neurotransmitter acetylcholine. The program AutoDock was used to study interactions of acetylcholine with the protein acetylcholinesterase. It was found acetylcholine interacts with the protein through hydrogen bonding, ionic interactions, and pi-cation interactions. The results of the docking study were used to select five functional monomers that could potentially engage in similar non-covalent interactions with acetylcholine. Density functional theory calculations were then performed with the General Atomic and Molecular Electronic Structure System to determine what functional monomer in complex with acetylcholine had the lowest stabilization energy. Results indicated that itaconic acid formed the most favorable complex with acetylcholine in silico. Therefore, itaconic acid is a promising candidate for future attempts to synthesize an acetylcholine molecularly imprinted polymer. Such a polymer could have applications in chromatography, biosensors, and biomedical devices. Of particular note, an acetylcholine molecularly imprinted polymer could be efficacious in developing a motor prosthesis with higher temporal and spatial resolution.