Abstract
A Quantitative Structure Activity Relationship (QSAR) study has been an attempted on a series of 88 N-aryl derivatives which display varied inhibitory activity towards both acetylcholinesterase (AChE) and butyrylcholinesterase (BChE), targets in Alzheimer’s drug discovery. QSAR models were derived for 53 and 61 compounds for each target, respectively, with the aid of genetic function approximation (GFA) technique using topological, molecular shape, electronic and structural descriptors. The predictive ability of the QSAR model was evaluated using a test set of 26 compounds for AChE (r2 pred = 0.857), (q2 = 0.803) and 20 compounds for BChE (r2 pred = 0.882), (q2 = 0.857). The QSAR models point out that AlogP98, Wiener, Kappa-1-AM, Dipole-Mag, and CHI-1 are the important descriptors effectively describing the bioactivity of the compounds.
Highlights
Alzheimer’s disease (AD), the most common form of dementia among the aged, is a fatal neurodegenerative disease characterized by loss of mental ability, cognition deterioration, progressive impairment of daily activities and a variety of neuropsychiatric symptoms and behavioral disturbances [1,2]
An interesting application of Genetic Function Approximation (GFA) is in the Quantitative Structure Activity Relationship (QSAR) studies on acetylcholinesterase inhibitors which has already resulted in discovery of a new molecule, E2020, for the treatment of Alzheimer’s disease [20]
Out of 88 N-aryl derivatives, the QSAR models were generated using 53 and 59 compounds as training set for acetylcholinesterase and butyrylcholinesterase, respectively
Summary
Alzheimer’s disease (AD), the most common form of dementia among the aged, is a fatal neurodegenerative disease characterized by loss of mental ability, cognition deterioration, progressive impairment of daily activities and a variety of neuropsychiatric symptoms and behavioral disturbances [1,2] Both acetylcholinesterase and butyrylcholinesterase are enzymes whose vital function is the hydrolytic breakdown and degradation of acetylcholine (ACh), a neurotransmitter which plays a role in Molecules 2009, 14 the modulation of memory function in normal and neurodegenerative conditions [3]. Galantamine, rivastigmine, donopezil and huperzine are some cholinesterase inhibitors, currently used promising drugs for the treatment of Alzheimer’s disease [5] Their clinical use is strictly limited because of several adverse effects such as hepatotoxicity and some pharmacokinetic disadvantages, so the study of new compounds as cholinesterase inhibitors is required to discover more effective and targeted drugs. An interesting application of GFA is in the QSAR studies on acetylcholinesterase inhibitors which has already resulted in discovery of a new molecule, E2020, for the treatment of Alzheimer’s disease [20]
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