Identification of sulfonamide-based butyrylcholinesterase inhibitors using machine learning.
Future Med Chem
; 14(14): 1049-1070, 2022 07.
Article
in En
| MEDLINE
| ID: mdl-35707942
ABSTRACT
Aim:
This study reports the designing of BChE inhibitors through machine learning (ML), followed by in silico and in vitro evaluations.Methodology:
ML technique was used to predict the virtual hit, and its derivatives were synthesized and characterized. The compounds were evaluated by using various in vitro tests and in silico methods.Results:
The gradient boosting classifier predicted N-phenyl-4-(phenylsulfonamido) benzamide as an active BChE inhibitor. The derivatives of the inhibitor, i.e., compounds 34, 37 and 54 were potent BChE inhibitors and displayed blood-brain barrier permeability with no significant AChE inhibition.Conclusion:
The ML prediction was effective, and the synthesized compounds showed the BChE inhibitory activity, which was also supported by the in silico studies.Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Butyrylcholinesterase
/
Cholinesterase Inhibitors
Type of study:
Diagnostic_studies
Language:
En
Journal:
Future Med Chem
Year:
2022
Document type:
Article
Affiliation country: