Investigation of the Binding Fraction of PFAS in Human Plasma and Underlying Mechanisms Based on Machine Learning and Molecular Dynamics Simulation
文献类型：期刊论文
| 作者 | Cao, Huiming; Peng, Jianhua; Zhou, Zhen; Yang, Zeguo; Wang, Ling; Sun, Yuzhen; Wang, Yawei; Liang, Yong |
| 刊名 | ENVIRONMENTAL SCIENCE & TECHNOLOGY
 |
| 出版日期 | 2022 |
| 页码 | 1-12 |
| 关键词 | PFAS Bioaccumulation Plasma binding protein Machine learning Molecular dynamics simulations |
| ISSN号 | 0013-936X |
| 英文摘要 | More than 7000 per-and polyfluorinated alkyl substances (PFAS) have been documented in the U.S. Environmental Protection Agency's CompTox Chemicals database. These PFAS can be used in a broad range of industrial and consumer applications but may pose potential environmental issues and health risks. However, little is known about emerging PFAS bioaccumulation to assess their chemical safety. This study focuses specifically on the large and high-quality data set of fluorochemicals from the related environmental and pharmaceutical chemicals databases, and machine learning (ML) models were developed for the classification prediction of the unbound fraction of compounds in plasma. A comprehensive evaluation of the ML models shows that the best blending model yields an accuracy of 0.901 for the test set. The predictions suggest that most PFAS (similar to 92%) have a high binding fraction in plasma. Introduction of alkaline amino groups is likely to reduce the binding affinities of PFAS with plasma proteins. Molecular dynamics simulations indicate a clear distinction between the high and low binding fractions of PFAS. These computational workflows can be used to predict the bioaccumulation of emerging PFAS and are also helpful for the molecular design of PFAS to prevent the release of high-bioaccumulation compounds into the environment. |
| 源URL | [https://ir.rcees.ac.cn/handle/311016/48497]  |
| 专题 | 生态环境研究中心_环境化学与生态毒理学国家重点实验室 |
| 作者单位 | 1.Chinese Academy of Sciences 2.Jianghan University 3.Research Center for Eco-Environmental Sciences (RCEES) |
| 推荐引用方式 GB/T 7714 | Cao, Huiming,Peng, Jianhua,Zhou, Zhen,et al. Investigation of the Binding Fraction of PFAS in Human Plasma and Underlying Mechanisms Based on Machine Learning and Molecular Dynamics Simulation[J]. ENVIRONMENTAL SCIENCE & TECHNOLOGY,2022:1-12. |
| APA | Cao, Huiming.,Peng, Jianhua.,Zhou, Zhen.,Yang, Zeguo.,Wang, Ling.,...&Liang, Yong.(2022).Investigation of the Binding Fraction of PFAS in Human Plasma and Underlying Mechanisms Based on Machine Learning and Molecular Dynamics Simulation.ENVIRONMENTAL SCIENCE & TECHNOLOGY,1-12. |
| MLA | Cao, Huiming,et al."Investigation of the Binding Fraction of PFAS in Human Plasma and Underlying Mechanisms Based on Machine Learning and Molecular Dynamics Simulation".ENVIRONMENTAL SCIENCE & TECHNOLOGY (2022):1-12. |
入库方式： OAI收割
来源：生态环境研究中心
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