AIMC Topic: Cholinesterase Inhibitors
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Optimization of biological activities of Agaricus species: an artificial intelligence-assisted approach.
Scientific reports
Jul 2, 2025
This study aims to determine the optimum extraction conditions that maximize the biological activities of Agaricus campestris and Agaricus bisporus species. In the study, a total of 64 extraction experiments were carried out at different temperatures...
Discovery of Novel Anti-Acetylcholinesterase Peptides Using a Machine Learning and Molecular Docking Approach.
Drug design, development and therapy
Jun 14, 2025
OBJECTIVE: Alzheimer's disease poses a significant threat to human health. Currenttherapeutic medicines, while alleviate symptoms, fail to reverse the disease progression or reduce its harmful effects, and exhibit toxicity and side effects such as ga...
Extract optimization and biological activities of Otidea onotica using Artificial Neural Network-Genetic Algorithm and response surface methodology techniques.
BMC biotechnology
Mar 28, 2025
In this study, the biological activities of Otidea onotica were investigated using two optimization methods, Response Surface Methodology (RSM) and Artificial Neural Network-Genetic Algorithm (ANN-GA). The extracts were tested for phenolic content, a...
Bioactivity of Juglans regia kernel extracts optimized using response surface method and artificial neural Network-Genetic algorithm integration.
Scientific reports
Mar 15, 2025
In this study, the biological activities of the extracts obtained under optimum extraction conditions of the kernel part of Juglans regia L. were determined. Two different methods, Response Surface Method (RSM) and Artificial Neural Network-Genetic A...
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 ...
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...
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...
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...
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...
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,...
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