AIMC Topic: Acetylcholinesterase

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Design of Natural-Product-Inspired Multitarget Ligands by Machine Learning.

ChemMedChem
A virtual screening protocol based on machine learning models was used to identify mimetics of the natural product (-)-galantamine. This fully automated approach identified eight compounds with bioactivities on at least one of the macromolecular targ...

Peroxidase-like activity of acetylcholine-based colorimetric detection of acetylcholinesterase activity and an organophosphorus inhibitor.

Journal of materials chemistry. B
Colorimetric detection of acetylcholinesterase (AChE) and its inhibitor organophosphates (OPs) is attractive for its convenience, but the addition of exogenous catalyst to produce a chromogenic agent may result in complexity and interference. Herein,...

MOST: most-similar ligand based approach to target prediction.

BMC bioinformatics
BACKGROUND: Many computational approaches have been used for target prediction, including machine learning, reverse docking, bioactivity spectra analysis, and chemical similarity searching. Recent studies have suggested that chemical similarity searc...

Effects of mutations on the structure and function of silkworm type 1 acetylcholinesterase.

Pesticide biochemistry and physiology
AChE is the target of organophosphate (OP) and carbamate (CB) pesticides, and mutations in the gene can significantly reduce insects' sensitivity to these pesticides. Bombyx mori is highly sensitive to pesticides. To investigate the effects of mutati...

A modified binary particle swarm optimization with a machine learning algorithm and molecular docking for QSAR modelling of cholinesterase inhibitors.

SAR and QSAR in environmental research
The acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE) inhibitors play a key role in treating Alzheimer's disease. This study proposes an approach that integrates a modified binary particle swarm optimization (PSO) with a machine learning ...