AIMC Topic: Mutagenicity Tests

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Safety Evaluation of Serendipity Berry Sweet Protein From Komagataella phaffii.

Journal of applied toxicology : JAT Mar 31, 2025
Serendipity Berry Sweet Protein (sweelin) is a novel hyper-sweet thermophilic protein designed using Artificial Intelligence Computational Protein Design (AI-CPD) to improve the stability and sensory profile of the protein found in serendipity berry ...
Animals Male Female Rats Rats, Sprague-Dawley No-Observed-Adverse-Effect Level Mutagenicity Tests Fruit
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Explainable no-code OECD-compliant machine learning models to predict the mutagenic activity of polycyclic aromatic hydrocarbons and their radical cation metabolites.

The Science of the total environment Mar 18, 2025
Polycyclic aromatic hydrocarbons (PAHs) are persistent pollutants with well-known genotoxic and mutagenic effects, posing risks to ecosystems and human health. Their hydrophobic nature promotes accumulation in soils and aquatic environments, increasi...
Machine Learning Organisation for Economic Co-Operation and Development Polycyclic Aromatic Hydrocarbons Mutagens Mutagenicity Tests Cations Models, Chemical Environmental Pollutants Risk Assessment Environmental Monitoring
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Predicting the Mutagenic Activity of Nitroaromatics Using Conceptual Density Functional Theory Descriptors and Explainable No-Code Machine Learning Approaches.

Journal of chemical information and modeling Feb 27, 2025
Nitroaromatic compounds (NAs) are widely used in industrial applications but pose significant genotoxic risks, necessitating accurate mutagenicity prediction for chemical safety assessments. This study integrates conceptual density functional theory ...
Machine Learning Density Functional Theory Nitro Compounds Mutagenicity Tests Mutagens Quantitative Structure-Activity Relationship
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Machine learning enhances genotoxicity assessment using MultiFlow® DNA damage assay.

Environmental and molecular mutagenesis Dec 30, 2024
Genotoxicity is a critical determinant for assessing the safety of pharmaceutical drugs, their metabolites, and impurities. Among genotoxicity tests, mechanistic assays such as the MultiFlow® DNA damage assay (MFA) allows the investigations on mode o...
Mutagens Mutagenicity Tests Machine Learning Algorithms Computer Simulation DNA Damage Humans
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Deep active learning with high structural discriminability for molecular mutagenicity prediction.

Communications biology Aug 31, 2024
The assessment of mutagenicity is essential in drug discovery, as it may lead to cancer and germ cells damage. Although in silico methods have been proposed for mutagenicity prediction, their performance is hindered by the scarcity of labeled molecul...
Mutagenicity Tests Deep Learning Mutagens Humans Computer Simulation Drug Discovery Algorithms
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DeepRA: A novel deep learning-read-across framework and its application in non-sugar sweeteners mutagenicity prediction.

Computers in biology and medicine Jun 12, 2024
Non-sugar sweeteners (NSSs) or artificial sweeteners have long been used as food chemicals since World War II. NSSs, however, also raise a concern about their mutagenicity. Evaluating the mutagenic ability of NSSs is crucial for food safety; this ste...
Neural Networks, Computer Sweetening Agents Mutagens Algorithms Mutagenicity Tests Deep Learning
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Visualization strategies to aid interpretation of high-dimensional genotoxicity data.

Environmental and molecular mutagenesis May 17, 2024
This article describes a range of high-dimensional data visualization strategies that we have explored for their ability to complement machine learning algorithm predictions derived from MultiFlow® assay results. For this exercise, we focused on seve...
Mutagenicity Tests Humans Data Visualization Machine Learning Principal Component Analysis Mutagens Cluster Analysis Cell Line Algorithms Biomarkers
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AMPred-CNN: Ames mutagenicity prediction model based on convolutional neural networks.

Computers in biology and medicine May 8, 2024
Mutagenicity assessment plays a pivotal role in the safety evaluation of chemicals, pharmaceuticals, and environmental compounds. In recent years, the development of robust computational models for predicting chemical mutagenicity has gained signific...
Neural Networks, Computer Mutagens Mutagenicity Tests
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DeepAmes: A deep learning-powered Ames test predictive model with potential for regulatory application.

Regulatory toxicology and pharmacology : RTP Aug 25, 2023
The Ames assay is required by the regulatory agencies worldwide to assess the mutagenic potential risk of consumer products. As well as this in vitro assay, in silico approaches have been widely used to predict Ames test results as outlined in the In...
Mutagenesis Mutagenicity Tests Deep Learning Mutagens
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Mechanistic Task Groupings Enhance Multitask Deep Learning of Strain-Specific Ames Mutagenicity.

Chemical research in toxicology Jul 21, 2023
The Ames test is a gold standard mutagenicity assay that utilizes various strains with and without S9 fraction to provide insights into the mechanisms by which a chemical can mutate DNA. Multitask deep learning is an ideal framework for developing Q...
Mutagenesis DNA Neural Networks, Computer Mutagenicity Tests Mutagens Deep Learning
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