Ligand-based discovery of new potential acetylcholinesterase inhibitors for Alzheimer's disease treatment

被引:4
|
作者
Canizares-Carmenate, Y. [1 ]
Nam, N-H [2 ]
Diaz-Amador, R. [3 ]
Thuan, N. T. [2 ]
Dung, P. T. P. [2 ]
Torrens, F. [4 ]
Pham-The, H. [2 ]
Perez-Gimenez, F. [5 ]
Castillo-Garit, J. A. [5 ,6 ]
机构
[1] Univ Cent Marta Abreu Las Villas, Fac Quim Farm, Unit Comp Aided Mol Biosil Discovery & Bioinforma, Santa Clara, Cuba
[2] Hanoi Univ Pharm, Dept Pharmaceut Chem, Hanoi, Vietnam
[3] Univ Cent Marta Abreu Las Villas, Dept Comp Sci, Santa Clara, Cuba
[4] Univ Valencia, Inst Univ Ciencia Mol, Edifici Inst Paterna, Valencia, Spain
[5] Univ Valencia, Fac Farm, Dept Quim Fis, Unidad Invest Diseno Farmacos & Conectividad Mol, Valencia, Spain
[6] Univ Ciencias Med Villa Clara, Unidad Toxicol Expt, Santa Clara, Cuba
关键词
Acetylcholinesterase inhibitor; Alzheimer's disease; benzothiadiazine; 1; 1-dioxide; quinazolinones; support vector machine; DRUG DESIGN; CLASSIFICATION;
D O I
10.1080/1062936X.2022.2025615
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
The enzyme acetylcholinesterase (AChE) is currently a therapeutic target for the treatment of neurodegenerative diseases. These diseases have highly variable causes but irreversible evolutions. Although the treatments are palliative, they help relieve symptoms and allow a better quality of life, so the search for new therapeutic alternatives is the focus of many scientists worldwide. In this study, a QSAR-SVM classification model was developed by using the MATLAB numerical computation system and the molecular descriptors implemented in the Dragon software. The obtained parameters are adequate with accuracy of 88.63% for training set, 81.13% for cross-validation experiment and 81.15% for prediction set. In addition, its application domain was determined to guarantee the reliability of the predictions. Finally, the model was used to predict AChE inhibition by a group of quinazolinones and benzothiadiazine 1,1-dioxides obtained by chemical synthesis, resulting in 14 drug candidates with in silico activity comparable to acetylcholine.
引用
收藏
页码:49 / 61
页数:13
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