AIMC Topic: Acetylcholinesterase
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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...
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...
Natural compounds for Alzheimer's prevention and treatment: Integrating SELFormer-based computational screening with experimental validation.
Computers in biology and medicine
Dec 9, 2024
BACKGROUND: This study aimed to develop and apply a novel computational pipeline combining SELFormer, a transformer architecture-based chemical language model, with advanced deep learning techniques to predict natural compounds (NCs) with potential i...
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...
Diagnosis of Hirschsprung disease by analyzing acetylcholinesterase staining using artificial intelligence.
Journal of pediatric gastroenterology and nutrition
Aug 9, 2024
OBJECTIVES: Classical Hirschsprung disease (HD) is defined by the absence of ganglion cells in the rectosigmoid colon. The diagnosis is made from rectal biopsy, which reveals the aganglionosis and the presence of cholinergic hyperinnervation. However...
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,...
A practical guide to machine-learning scoring for structure-based virtual screening.
Nature protocols
Oct 16, 2023
Structure-based virtual screening (SBVS) via docking has been used to discover active molecules for a range of therapeutic targets. Chemical and protein data sets that contain integrated bioactivity information have increased both in number and in si...
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...
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