Virtual screening for alpha7 nicotinic acetylcholine receptor for treatment of Alzheimer's disease.

Alzheimer's disease (AD) is the most common form of dementia. Although its cause and mechanism of progression are not well understood, various in vitro and in vivo experiments have proved that the decreased activity of the cholinergic neuron is responsible for the memory damage that is observed in these patients. Therefore, the nicotinic acetylcholine receptor (nAChR) is one of the possible drug targets for this disease. At present, extensive nAChR ligands have been designed, and some of the α7 nAChR agonists (e.g., DMXB-A and JN403) have been found to improve the memories and spatial abilities of animal models. However, most of the α7 nAChR agonists cannot be used therapeutically for various reasons, such as poor selectivity for nAChR subtypes, poor pharmacokinetic properties, or toxicity. In the current study, we built homology models of α7 nAChR and virtually screened possible nAChR ligands by combining molecular docking, molecular feature searches, hydrogen bond analyses, and quantitative structure activity relationship (QSAR) study. Our docking simulations and QSAR modeling were reasonably accurate and predictive of nAChR ligand affinity, and we have provided novel and reasonable computational methods for the virtual screening of possible α7 nAChR agonists that may be effectively used for the treatment of various neural disorders, particularly Alzheimer's disease. The compounds that were found in this study may be assessed in future in vitro or in vivo experiments for their affinities to nAChRs in addition to their biological functions.