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Nontarget Screening of Per- and Polyfluoroalkyl Substances Binding to Human Liver Fatty Acid Binding Protein
Current studies on nontarget analysis and toxicities of PFASs are disconnected, due to the challenges posed by the large numbers (>1,000) and diverse structures of PFASs. The SECC method provides a high-throughput experimental way to tackle the challenge of prioritizing PFASs according to key proteins, especially when their authentic standards are not available. While this study is focused on hL-FABP due to its critical role in regulating the toxicokinetics of PFASs, the protein-centric method could also be adapted to screen PFASs binding to other key proteins, such as PPARs. Computational toxicology is the predominant strategy for high-throughput predictions of toxicities of chemical contaminants. This dataset is not publicly accessible because: Data generated and owned by external academic lab with chemicals provided by the EPA under an MTA. EPA's contribution was assisting in manuscript writing. It can be accessed through the following means: Contact the Corresponding author: Hui Peng, e-mail: hui.peng@utoronto.ca, Department of Chemistry, University of Toronto, Toronto, Ontario, M5S3H6, Canada. Format: Not available.
This dataset is associated with the following publication:
Yang, D., J. Han, D. Ross Hall, J. Sun, J. Fu, S. Kutarna, K. Houck, C. LaLone, J. Doering, C. Ng, and H. Peng. Nontarget Screening of Per- and Polyfluoroalkyl Substances Binding to Human Liver Fatty Acid Binding Protein. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 54(9): 5676-5686, (2020).
Complete Metadata
| accessLevel | public |
|---|---|
| bureauCode |
[
"020:00"
]
|
| contactPoint |
{
"fn": "Keith Houck",
"hasEmail": "mailto:houck.keith@epa.gov"
}
|
| description | Current studies on nontarget analysis and toxicities of PFASs are disconnected, due to the challenges posed by the large numbers (>1,000) and diverse structures of PFASs. The SECC method provides a high-throughput experimental way to tackle the challenge of prioritizing PFASs according to key proteins, especially when their authentic standards are not available. While this study is focused on hL-FABP due to its critical role in regulating the toxicokinetics of PFASs, the protein-centric method could also be adapted to screen PFASs binding to other key proteins, such as PPARs. Computational toxicology is the predominant strategy for high-throughput predictions of toxicities of chemical contaminants. This dataset is not publicly accessible because: Data generated and owned by external academic lab with chemicals provided by the EPA under an MTA. EPA's contribution was assisting in manuscript writing. It can be accessed through the following means: Contact the Corresponding author: Hui Peng, e-mail: hui.peng@utoronto.ca, Department of Chemistry, University of Toronto, Toronto, Ontario, M5S3H6, Canada. Format: Not available. This dataset is associated with the following publication: Yang, D., J. Han, D. Ross Hall, J. Sun, J. Fu, S. Kutarna, K. Houck, C. LaLone, J. Doering, C. Ng, and H. Peng. Nontarget Screening of Per- and Polyfluoroalkyl Substances Binding to Human Liver Fatty Acid Binding Protein. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 54(9): 5676-5686, (2020). |
| distribution |
[]
|
| identifier | https://doi.org/10.23719/1518709 |
| keyword |
[
"aqueous film-forming foams",
"hydrophobicity",
"nontargeted analysis",
"size exclusion chromatography"
]
|
| license | https://pasteur.epa.gov/license/sciencehub-license-non-epa-generated.html |
| modified | 2020-01-10 |
| programCode |
[
"020:095"
]
|
| publisher |
{
"name": "U.S. EPA Office of Research and Development (ORD)",
"subOrganizationOf": {
"name": "U.S. Environmental Protection Agency",
"subOrganizationOf": {
"name": "U.S. Government"
}
}
}
|
| references |
[
"https://doi.org/10.1021/acs.est.0c00049"
]
|
| rights |
null
|
| title | Nontarget Screening of Per- and Polyfluoroalkyl Substances Binding to Human Liver Fatty Acid Binding Protein |