AIMC Topic: Cholinesterase Inhibitors

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Enhanced in silico QSAR-based screening of butyrylcholinesterase inhibitors using multi-feature selection and machine learning.

SAR and QSAR in environmental research Feb 21, 2025
Butyrylcholinesterase inhibition offers one of the formulated solutions to tackle the aggravating symptoms of dementia that downgrades to cholinergic neuronal loss in Alzheimer's disease. We developed a QSAR model to facilitate the identification of ...
Butyrylcholinesterase Humans Machine Learning Drug Discovery Algorithms Cholinesterase Inhibitors Computer Simulation Quantitative Structure-Activity Relationship
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Dual inhibition of AChE and MAO-B in Alzheimer's disease: machine learning approaches and model interpretations.

Molecular diversity Jan 21, 2025
Alzheimer's disease (AD) is one of the most prevalent neurodegenerative diseases. Given the multifactorial pathophysiology of AD, monotargeted agents can only alleviate symptoms but not cure AD. Acetylcholinesterase (AChE) and Monoamine oxidase B (MA...
Humans Machine Learning Cholinesterase Inhibitors Monoamine Oxidase Monoamine Oxidase Inhibitors Algorithms Alzheimer Disease Acetylcholinesterase
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A hybrid artificial neural network and multi-objective genetic algorithm approach to optimize extraction conditions of Mentha longifolia and biological activities.

Scientific reports Dec 28, 2024
In this work, artificial neural network coupled with multi-objective genetic algorithm (ANN-NSGA-II) has been used to develop a model and optimize the conditions for the extracting of the Mentha longifolia (L.) L. plant. Input parameters were extract...
Algorithms Antioxidants Plant Extracts Neural Networks, Computer Cholinesterase Inhibitors Flavonoids Phenols Mentha
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Identifying Organic Chemicals with Acetylcholinesterase Inhibition in Nationwide Estuarine Waters by Machine Learning-Assisted Mass Spectrometric Screening.

Environmental science & technology Dec 4, 2024
Neurotoxicity is frequently observed in the global aquatic environment, threatening aquatic ecosystems and human health. However, a very limited proportion of neurotoxic effects (∼1%) has been explained by known chemicals of concern. Here, we integra...
Machine Learning China Cholinesterase Inhibitors Mass Spectrometry Organic Chemicals Water Pollutants, Chemical Estuaries Environmental Monitoring Acetylcholinesterase
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Estimating AChE inhibitors from MCE database by machine learning and atomistic calculations.

Journal of molecular graphics & modelling Nov 14, 2024
Acetylcholinesterase (AChE) is one of the most successful targets for the treatment of Alzheimer's disease (AD). Inhibition of AChE can result in preventing AD. In this context, the machine-learning (ML) model, molecular docking, and molecular dynami...
Molecular Docking Simulation Humans Protein Binding Ligands Molecular Dynamics Simulation Machine Learning Acetylcholinesterase Databases, Chemical Cholinesterase Inhibitors Binding Sites
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Machine learning-assisted melamine-Cu nanozyme and cholinesterase integrated array for multi-category pesticide intelligent recognition.

Biosensors & bioelectronics Sep 4, 2024
Expanding target pesticide species and intelligent pesticide recognition were formidable challenges for existing cholinesterase inhibition methods. To improve this status, multi-active Mel-Cu nanozyme with mimetic Cu-N sites was prepared for the firs...
Butyrylcholinesterase Pesticides Triazines Machine Learning Copper Biosensing Techniques Acetylcholinesterase Limit of Detection Cholinesterase Inhibitors
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Sequential Contrastive and Deep Learning Models to Identify Selective Butyrylcholinesterase Inhibitors.

Journal of chemical information and modeling Mar 26, 2024
Butyrylcholinesterase (BChE) is a target of interest in late-stage Alzheimer's Disease (AD) where selective BChE inhibitors (BIs) may offer symptomatic treatment without the harsh side effects of acetylcholinesterase (AChE) inhibitors. In this study,...
Humans Acetylcholinesterase Cholinesterase Inhibitors Butyrylcholinesterase Deep Learning Models, Molecular Alzheimer Disease
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Cheminformatics and Machine Learning Approaches to Assess Aquatic Toxicity Profiles of Fullerene Derivatives.

International journal of molecular sciences Sep 15, 2023
Fullerene derivatives (FDs) are widely used in nanomaterials production, the pharmaceutical industry and biomedicine. In the present study, we focused on the potential toxic effects of FDs on the aquatic environment. First, we analyzed the binding af...
Daphnia Quantitative Structure-Activity Relationship Cyprinidae Cheminformatics Humans Fullerenes Water Pollutants, Chemical Acetylcholinesterase Cholinesterase Inhibitors Machine Learning Animals
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A pendant droplet-based sensor for the detection of acetylcholinesterase and its inhibitors.

Chemical communications (Cambridge, England) Sep 6, 2021
In this work, a pendant droplet-based sensor is developed for the rapid and label-free detection of acetylcholinesterase (AChE) and its inhibitors. The detection limit of AChE reaches 0.17 mU mL. The pIC values of AChE inhibitors such as neostigmine,...
Rivastigmine Cholinesterase Inhibitors Limit of Detection Galantamine Acetylcholinesterase Neostigmine
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Machine learning models to select potential inhibitors of acetylcholinesterase activity from SistematX: a natural products database.

Molecular diversity Jun 16, 2021
Alzheimer's disease is the most common form of dementia, representing 60-70% of dementia cases. The enzyme acetylcholinesterase (AChE) cleaves the ester bonds in acetylcholine and plays an important role in the termination of acetylcholine activity a...
Area Under Curve Models, Molecular Humans Workflow Machine Learning Algorithms ROC Curve Molecular Dynamics Simulation Molecular Docking Simulation Biological Products Cheminformatics Acetylcholinesterase Drug Discovery Structure-Activity Relationship Databases, Pharmaceutical Cholinesterase Inhibitors
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