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Modeling and Insights into the Structural Characteristics of Chemical Mitochondrial Toxicity
[Image: see text] 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 to...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10483523/ https://www.ncbi.nlm.nih.gov/pubmed/37692239 http://dx.doi.org/10.1021/acsomega.3c01725 |
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author | Zhang, Ruiqiu Chen, Zhaoyang Wang, Baobao Li, Yan Mu, Yan Li, Xiao |
author_facet | Zhang, Ruiqiu Chen, Zhaoyang Wang, Baobao Li, Yan Mu, Yan Li, Xiao |
author_sort | Zhang, Ruiqiu |
collection | PubMed |
description | [Image: see text] 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. |
format | Online Article Text |
id | pubmed-10483523 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-104835232023-09-08 Modeling and Insights into the Structural Characteristics of Chemical Mitochondrial Toxicity Zhang, Ruiqiu Chen, Zhaoyang Wang, Baobao Li, Yan Mu, Yan Li, Xiao ACS Omega [Image: see text] 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. American Chemical Society 2023-08-23 /pmc/articles/PMC10483523/ /pubmed/37692239 http://dx.doi.org/10.1021/acsomega.3c01725 Text en © 2023 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by-nc-nd/4.0/Permits non-commercial access and re-use, provided that author attribution and integrity are maintained; but does not permit creation of adaptations or other derivative works (https://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Zhang, Ruiqiu Chen, Zhaoyang Wang, Baobao Li, Yan Mu, Yan Li, Xiao Modeling and Insights into the Structural Characteristics of Chemical Mitochondrial Toxicity |
title | Modeling and Insights
into the Structural Characteristics
of Chemical Mitochondrial Toxicity |
title_full | Modeling and Insights
into the Structural Characteristics
of Chemical Mitochondrial Toxicity |
title_fullStr | Modeling and Insights
into the Structural Characteristics
of Chemical Mitochondrial Toxicity |
title_full_unstemmed | Modeling and Insights
into the Structural Characteristics
of Chemical Mitochondrial Toxicity |
title_short | Modeling and Insights
into the Structural Characteristics
of Chemical Mitochondrial Toxicity |
title_sort | modeling and insights
into the structural characteristics
of chemical mitochondrial toxicity |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10483523/ https://www.ncbi.nlm.nih.gov/pubmed/37692239 http://dx.doi.org/10.1021/acsomega.3c01725 |
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