Abstract
Computer simulations constitute the basis of the design and discovery of new drugs. This approach is not only significant with regards to finding new structures, but also for selecting the molecules with the highest probability of being useful in the diagnostic process and treatment of numerous diseases. In our work, we used computational software to analyze 32 new acetylcholinesterase (AChE) inhibitors and formulate ADMET predictions. To understand the influence of the structure of our derivatives on binding mode, we docked all structures to the active site of AChE and assigned some pharmacophoric features. Finally, we undertook a chemometric analysis of all the compounds on the basis of FT-IR, which gave us the possibility of performing a fast categorization of the analyzed compounds and design compounds with similar structures.
Highlights
Alzheimer’s disease (AD) is a fatal neurodegenerative disease that affects elderly people
A model of the Ames test was used to compare our compounds with tacrine (THA)—a reference acetylcholinesterase inhibitor
We decided on the prediction of basic ADMET parameters for the structures obtained by modification of a well-known
Summary
Alzheimer’s disease (AD) is a fatal neurodegenerative disease that affects elderly people This disease is characterized by an irreversible degeneration of cholinergic neurons, which leads to an impairment of the cognitive functions. In the 1980s, it was confirmed that decreased level of choline acetyltransferase correlates with a decline in the mental status scores as described by Bartus [4]. This theory was the basis of one of the possible approaches to treating this disease. BuChE occurs in lungs, heart, kidneys, liver and serum In pathological states such as AD the level of BuChE builds up. Acetylcholinesterase inhibitors diminish the formation of amyloid fibrils and possess neuroprotective activity [5,6]
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