期刊
JOURNAL OF THE CHINESE CHEMICAL SOCIETY
卷 68, 期 8, 页码 1379-1399出版社
WILEY-V C H VERLAG GMBH
DOI: 10.1002/jccs.202000457
关键词
acetylcholinesterase; Alzheimer; molecular docking; QSAR‐ ANN; virtual screening
The study utilized cheminformatics tools and artificial neural networks to explore new therapeutic drug molecules for Alzheimer's disease. A quantitative structure-activity relationship model was established for AChE inhibitors, leading to the discovery of novel anti-AChE candidates with improved activity through virtual screening and docking simulation. These compounds exhibited strong binding affinity to the AChE enzyme active site with optimal conformations, showing promise for potential therapeutic use.
The deficit in cholinergic neurotransmission is the main incentives for the development of new therapeutic drugs for the treatment of Alzheimer's disease (AD). In this study, we employed cheminformatics tools to explore new molecules that can serve as effective therapeutic agents against AD. Artificial neural networks (ANNs) were applied in a quantitative structure anti-acetylcholinesterase (AChE)-activity relationship study on a series of AChE inhibitors (AChEIs). The best computational neural network had an [5-10-12-1] architecture, with a low value of mean squared error (MSE = 0.06) and a high value of R-2 (0.96). All validations showed that the ANN model can be used quite satisfactorily for the screening of a new series of molecules having anti-AChE activity. The virtual screening based on the molecular similarity method and applicability domain of ANN-quantitative structure-activity relationships allowed the discovery of novel anti-AChE candidates with improved activity. Docking simulation carried out on these novel AChEIs has identified eight best hits with a higher binding affinity toward their target (4EY7). These eight stable complexes were in good agreement with the biological activity and they have an inhibition profile at a similar rate as the reference drug donepezil. The results showed that these compounds were strongly bound up with the AChE enzyme active site with the optimal conformations.
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