Abstract
ABSTRACT 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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.