QSAR study of acetylcholinesterase inhibitors for Alzheimer’s disease

Alzheimer’s disease (AD) is an incapacitating neurodegenerative disease that slowly destroys brain cells. This disease progressively compromises both memory and cognition, culminating in a state of full dependence and dementia. Currently, AD is the main cause of dementia in the elderly and its prevalence in the developed world is increasing rapidly. Classic drugs, such as acetylcholinesterase inhibitors (AChEIs), fail to decline disease progression and display several side effects that reduce patient’s adhesion to pharmacotherapy. The past decade has witnessed an increasing focus on the search for novel AChEIs and new putative enzymatic targets for AD, like β –and γ -secretases, sirtuins, caspase proteins and glycogen syntheses kinase-3 (GSK-3). Genetic algorithm (GA), artificial neural network (ANN), multiple linear regression (MLR), were used to create QSAR models. According to the obtained results, GA-ANN model was the most favorable method toward the other statistical methods. For this purpose, ab initio geometry optimization was performed at B3LYP level with a known basis set at 6-33G(d). R and R2 values of the GA-stepwise MLR model were obtained as 98.0 and 98.9.

کلیدواژه ها:

Alzheimer’s disease ، Acetylcholinesterase and Genetic algorithm