ArticleACS omega2023
Modeling and Insights into the Structural Characteristics of Chemical Mitochondrial Toxicity.
Article in ACS omega, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Natural Products as Promising Pharmacological Agents Against Cancer: A Holistic Overview of Their Anti-Cancer Mechanisms of Action of the Last Five Years.Pharmaceuticals (Basel, Switzerland) · 2026Review
- In silico prediction of drug-induced cardiotoxicity with ensemble machine learning and structural pattern recognition.Molecular diversity · 2026Article
- ChronicDPipredictor: an interpretable deep learning framework for chemical chronic and subchronic toxicity assessment.Molecular diversity · 2026Article
- Hybrid non-animal modeling: A mechanistic approach to predict chemical hepatotoxicity.Journal of hazardous materials · 2024Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Mitochondria are the energy metabolism center of cells and are involved in a number of other processes, such as cell differentiation and apoptosis, signal transduction, and regulation of cell cycle and cell proliferation. It is of great significance to evaluate the mitochondrial toxicity of drugs and other chemicals. In the present study, we aimed to propose easily available artificial intelligence (AI) models for the prediction of chemical mitochondrial toxicity and investigate the structural characteristics with the analysis of molecular properties and structural alerts. The consensus model achieved good predictive results with high total accuracy at 87.21% for validation sets. The models can be accessed freely via https://ochem.eu/article/158582. Besides, several commonly used chemical properties were significantly different between chemicals with and without mitochondrial toxicity. We also detected the structural alerts (SAs) responsible for mitochondrial toxicity and integrated them into the web-server SApredictor (www.sapredictor.cn). The study may provide useful tools for in silico estimation of mitochondrial toxicity and be helpful to understand the mechanisms of mitochondrial toxicity.
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Registered trials
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