Marci Smeltz, John F. Wambaugh, and Barbara A. Wetmore, Plasma Protein Binding Evaluations of Per- and Polyfluoroalkyl Substances for Category-Based Toxicokinetic Assessment, Chemical Research in Toxicology, 10.1021/acs.chemrestox.3c00003. This dataset is associated with the following publication: Smeltz, M., J. Wambaugh, and B. Wetmore. Plasma Protein Binding Evaluations of Per- and Polyfluoroalkyl Substances for Category-Based Toxicokinetic Assessment. CHEMICAL RESEARCH IN TOXICOLOGY. American Chemical Society, Washington, DC, USA, 36(6): 870-871, (2023).

Supplementary material for "Kreutz, A.; Clifton, M.S.; Henderson, W.M.; Smeltz, M.G.; Phillips, M.; Wambaugh, J.F.; Wetmore, B.A. Category-Based Toxicokinetic Evaluations of Data-Poor Per- and Polyfluoroalkyl Substances (PFAS) using Gas Chromatography Coupled with Mass Spectrometry. Toxics 2023, 11, 463. https://doi.org/10.3390/toxics11050463". This dataset is associated with the following publication: Kreutz, A., M. Clifton, W. Henderson, M. Smeltz, M. Phillips, J. Wambaugh, and B. Wetmore. Category-Based Toxicokinetic Evaluations of Data-Poor Per- and Polyfluoroalkyl Substances (PFAS) using Gas Chromatography Coupled with Mass Spectrometry. Toxics. MDPI, Basel, SWITZERLAND, 11(5): 463, (2023).

Supplementary material for "Kreutz, A.; Clifton, M.S.; Henderson, W.M.; Smeltz, M.G.; Phillips, M.; Wambaugh, J.F.; Wetmore, B.A. Category-Based Toxicokinetic Evaluations of Data-Poor Per- and Polyfluoroalkyl Substances (PFAS) using Gas Chromatography Coupled with Mass Spectrometry. Toxics 2023, 11, 463. https://doi.org/10.3390/toxics11050463". This dataset is associated with the following publication: Kreutz, A., M. Clifton, W. Henderson, M. Smeltz, M. Phillips, J. Wambaugh, and B. Wetmore. Category-Based Toxicokinetic Evaluations of Data-Poor Per- and Polyfluoroalkyl Substances (PFAS) using Gas Chromatography Coupled with Mass Spectrometry. Toxics. MDPI, Basel, SWITZERLAND, 11(5): 463, (2023).

Data for Ann M. "Richard, Ryan Lougee, Matthew Adams, Hannah Hidle, Chihae Yang, James Rathman, Tomasz Magdziarz, Bruno Bienfait, Antony J. Williams, and Grace Patlewicz, Chemical Research in Toxicology 2023 36 (3), 508-534, DOI: 10.1021/acs.chemrestox.2c00403" Table S1 FP ToxPrint fingerprint matrix exported from the ChemoTyper for PFASSTRUCTV5 containing 14,735 rows indexed by DTXSID substance identifier and 729 columns indexed by ToxPrint names (alphabetized); Table S2 TxP_PFAS_v1.0.4 fingerprint matrix exported from the ChemoTyper for PFASSTRUCTV5 containing 14,735 rows indexed by DTXSID substance identifier and 129 columns indexed by TxP_PFAS_v1.0.4 chemotype names (alphabetized) Table S3 Chemotype count totals for TxP_PFAS_v1.0.4 mapped to PFASSTRUCTV5 compared to counts for PFASSTRUCTV4, as well as corresponding ToxPrint names where a close correspondence exists Table S4 Chemotype count totals for ToxPrints mapped to PFASSTRUCTV5 compared to counts for PFASSTRUCTV4, as well as indications of which ToxPrints have a closely corresponding TxP_PFAS chemotype Table S5 DSSTox chemical identifiers (DTXSID, SMILES, name, CASRN, formula) for PFASSTRUCTV5 list, indicator column for overlapping content in PFASSTRUCTV4 (10,586) and PFASOECD (3662) lists, indicator columns for the 7 TxP_PFAS chemotypes used in the OECD Category analysis of Section 5, indicator columns for chemicals containing one or more of the 20 TxP_PFAS fluorotelomer (FT) chemotypes or designated as an OECD FT, and assigned OECD Structure-Category Name for the 3662 overlapping OECD vs PFASSTRUCTV5 chemicals, with the last separated column listing the 106 unique OECD Structure Categories; PFASSTRUCTV5_20221101.sdf containing 14,735 structures, also described and available for viewing and download at: https://comptox.epa.gov/dashboard/chemical-lists/PFASSTRUCTV5; TxP_PFAS_v1.0.4.xml CSRML file containing coding for 129 TxP_PFAS chemotypes and their hierarchy index. This dataset is associated with the following publication: Richard, A., R. Lougee, M. Adams, H. Hidle, C. Yang, J. Rathman, T. Magdziarz, A. Williams, G. Patlewicz, and B. Bienfait. A New CSRML Structure-Based Fingerprint Method for Profiling and Categorizing Per- and Polyfluoroalkyl Substances (PFAS). CHEMICAL RESEARCH IN TOXICOLOGY. American Chemical Society, Washington, DC, USA, 36(3): 508-534, (2023).

Data for Ann M. "Richard, Ryan Lougee, Matthew Adams, Hannah Hidle, Chihae Yang, James Rathman, Tomasz Magdziarz, Bruno Bienfait, Antony J. Williams, and Grace Patlewicz, Chemical Research in Toxicology 2023 36 (3), 508-534, DOI: 10.1021/acs.chemrestox.2c00403" Table S1 FP ToxPrint fingerprint matrix exported from the ChemoTyper for PFASSTRUCTV5 containing 14,735 rows indexed by DTXSID substance identifier and 729 columns indexed by ToxPrint names (alphabetized); Table S2 TxP_PFAS_v1.0.4 fingerprint matrix exported from the ChemoTyper for PFASSTRUCTV5 containing 14,735 rows indexed by DTXSID substance identifier and 129 columns indexed by TxP_PFAS_v1.0.4 chemotype names (alphabetized) Table S3 Chemotype count totals for TxP_PFAS_v1.0.4 mapped to PFASSTRUCTV5 compared to counts for PFASSTRUCTV4, as well as corresponding ToxPrint names where a close correspondence exists Table S4 Chemotype count totals for ToxPrints mapped to PFASSTRUCTV5 compared to counts for PFASSTRUCTV4, as well as indications of which ToxPrints have a closely corresponding TxP_PFAS chemotype Table S5 DSSTox chemical identifiers (DTXSID, SMILES, name, CASRN, formula) for PFASSTRUCTV5 list, indicator column for overlapping content in PFASSTRUCTV4 (10,586) and PFASOECD (3662) lists, indicator columns for the 7 TxP_PFAS chemotypes used in the OECD Category analysis of Section 5, indicator columns for chemicals containing one or more of the 20 TxP_PFAS fluorotelomer (FT) chemotypes or designated as an OECD FT, and assigned OECD Structure-Category Name for the 3662 overlapping OECD vs PFASSTRUCTV5 chemicals, with the last separated column listing the 106 unique OECD Structure Categories; PFASSTRUCTV5_20221101.sdf containing 14,735 structures, also described and available for viewing and download at: https://comptox.epa.gov/dashboard/chemical-lists/PFASSTRUCTV5; TxP_PFAS_v1.0.4.xml CSRML file containing coding for 129 TxP_PFAS chemotypes and their hierarchy index. This dataset is associated with the following publication: Richard, A., R. Lougee, M. Adams, H. Hidle, C. Yang, J. Rathman, T. Magdziarz, A. Williams, G. Patlewicz, and B. Bienfait. A New CSRML Structure-Based Fingerprint Method for Profiling and Categorizing Per- and Polyfluoroalkyl Substances (PFAS). CHEMICAL RESEARCH IN TOXICOLOGY. American Chemical Society, Washington, DC, USA, 36(3): 508-534, (2023).

The dataset has all of the information used to create and evaluate 3 independent QSAR models for the fraction of a chemical unbound by plasma protein (Fub) for environmentally relevant chemicals. In vitro plasma protein values for 1245 pharmaceuticals and 406 ToxCast chemicals were collected from the literature (Obach 2008, Zhu 2013, Wetmore 2012, Wetmore 2015). The 21 descriptors calculated by MOE that were used in the models are included, as is an acid/base/neutral/zwitterions classification based on ionization percentages calculated in ADMET Predictor. Finally, the dataset includes the in silico Fub predictions for each chemical from the constructed k-nearest neighbor, support vector machine, and random forest QSAR models, as well as a consensus (average) prediction. This dataset is associated with the following publication: Ingle, B., R. Tornero-Velez, J. Nichols, and B. Veber. Informing the Human Plasma Protein Binding of Environmental Chemicals by Machine Learning in the Pharmaceutical Space: Applicability Domain and Limits of Predictability. Journal of Chemical Information and Modeling. American Chemical Society, Washington, DC, USA, 56(11): 2243-2252, (2016).

The dataset has all of the information used to create and evaluate 3 independent QSAR models for the fraction of a chemical unbound by plasma protein (Fub) for environmentally relevant chemicals. In vitro plasma protein values for 1245 pharmaceuticals and 406 ToxCast chemicals were collected from the literature (Obach 2008, Zhu 2013, Wetmore 2012, Wetmore 2015). The 21 descriptors calculated by MOE that were used in the models are included, as is an acid/base/neutral/zwitterions classification based on ionization percentages calculated in ADMET Predictor. Finally, the dataset includes the in silico Fub predictions for each chemical from the constructed k-nearest neighbor, support vector machine, and random forest QSAR models, as well as a consensus (average) prediction. This dataset is associated with the following publication: Ingle, B., R. Tornero-Velez, J. Nichols, and B. Veber. Informing the Human Plasma Protein Binding of Environmental Chemicals by Machine Learning in the Pharmaceutical Space: Applicability Domain and Limits of Predictability. Journal of Chemical Information and Modeling. American Chemical Society, Washington, DC, USA, 56(11): 2243-2252, (2016).

R-language data files from "Carstens KE, Freudenrich T, Wallace K, Choo S, Carpenter A, Smeltz M, Clifton MS, Henderson WM, Richard AM, Patlewicz G, Wetmore BA, Paul Friedman K, Shafer T. Evaluation of Per- and Polyfluoroalkyl Substances (PFAS) In Vitro Toxicity Testing for Developmental Neurotoxicity. Chem Res Toxicol. 2023 Mar 20;36(3):402-419. doi: 10.1021/acs.chemrestox.2c00344. Epub 2023 Feb 23. PMID: 36821828.". This dataset is associated with the following publication: Carstens, K., T. Freudenrich, K. Wallace, S. Choo, A. Carpenter, M. Smeltz, M. Clifton, M. Henderson, A. Richard, G. Patlewicz, B. Wetmore, K. Friedman, and T. Shafer. Evaluation of Per- and Polyfluoroalkyl Substances (PFAS) In Vitro Toxicity Testing for Developmental Neurotoxicity. CHEMICAL RESEARCH IN TOXICOLOGY. American Chemical Society, Washington, DC, USA, 36(3): 402-419, (2023).

Data belongs to Detlef Knappe's research group at North Carolina State University, as this study was that of PhD students and postdoctoral researches from his laboratory. This dataset is not publicly accessible because: Non-EPA generated data. It can be accessed through the following means: Non-EPA generated data. Format: Non-EPA generated data. This dataset is associated with the following publication: Liberatore, H., A. McElroy, C. Zhang, N.L. Alexander, and D. Knappe. Stability of Per- and Polyfluoroalkyl Substances in Solvents Relevant to Environmental and Toxicological Analysis. JOURNAL OF THE AMERICAN CHEMICAL SOCIETY. American Chemical Society, Washington, DC, USA, na, (2021).

Study reports for "Subchronic Toxicities of Four Per- and Polyfluoroalkyl Substances (PFASs) by Oral Exposure in Sprague–Dawley Rats". This dataset is associated with the following publication: Kenyon, E., M. Devito, G. Patlewicz, L. Adams, R. Thomas, J. Ambroso, X. Yang, J. Blake, B. Upadhyay, J. Furr, and M. Hughes. Subchronic Toxicities of Four Per- and Polyfluoroalkyl Substances (PFASs) by Oral Exposure in Sprague–Dawley Rats. Toxics. MDPI, Basel, SWITZERLAND, 13(7): 524, (2025).