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

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...

Full description

Saved in:
Bibliographic Details
Published in:SAR and QSAR in environmental research 2022, Vol.33 (1), p.49-61
Main Authors: Cañizares-Carmenate, Y., Nam, N.-H., Díaz-Amador, R., Thuan, N.T., Dung, P.T.P., Torrens, F., Pham-The, H., Perez-Gimenez, F., Castillo-Garit, J.A.
Format: Article
Language:English
Subjects:
1-dioxide
Acetylcholinesterase
Acetylcholinesterase - metabolism
Acetylcholinesterase inhibitor
Alzheimer Disease - drug therapy
Alzheimer's disease
benzothiadiazine 1
Chemical synthesis
Cholinesterase Inhibitors
Drug development
Health services
Humans
Ligands
Medical treatment
Molecular Docking Simulation
Neurodegenerative diseases
Numerical analysis
Quality of Life
Quantitative Structure-Activity Relationship
quinazolinones
Reproducibility of Results
Signs and symptoms
Structure-activity relationships
support vector machine
Support vector machines
Therapeutic targets
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:1062-936X
1029-046X
DOI:10.1080/1062936X.2022.2025615