Literature DB >> 24491038

Predicting partition coefficients of Polyfluorinated and organosilicon compounds using polyparameter linear free energy relationships (PP-LFERs).

Satoshi Endo1, Kai-Uwe Goss.   

Abstract

The environmental behavior, fate, and effects of polyfluorinated compounds (PFCs) and organosilicon compounds (OSCs) have received increasing attention in recent years. In this study, polyparameter linear free energy relationships (PP-LFERs) were evaluated for predicting partition coefficients of neutral PFCs and OSCs, using experimental data for fluorotelomer alcohols (FTOHs) and cyclic volatile methylsiloxanes (cVMS) reported in the literature and measured newly for this work. It was found that the recently proposed PP-LFER model that uses the McGowan characteristic volume (V), the logarithmic hexadecane-air partition coefficient (L), and three polar interaction descriptors can accurately describe partition coefficients of PFCs and OSCs. The prediction errors were <1 log unit when literature descriptors were used, and the errors were reduced to <0.2 log units on average by further optimization of the descriptors. Surprisingly, the conventional forms of PP-LFERs that include the excess molar refraction (E) sometimes led to substantial errors (>1 log unit) even with optimized parameters. The system parameters for octanol-water, air-water, octanol-air, oil-water, liposome-water, and organic carbon-water partition coefficients as well as the solute descriptors for FTOHs and cVMS were recalibrated in this work, which should provide even more reliable predictions of partition coefficients. The results also confirm the consistency of the published experimental partition coefficients for FTOHs and cVMS.

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Year:  2014        PMID: 24491038     DOI: 10.1021/es405091h

Source DB:  PubMed          Journal:  Environ Sci Technol        ISSN: 0013-936X            Impact factor:   9.028


  5 in total

1.  Field-testing polyethylene passive samplers for the detection of neutral polyfluorinated alkyl substances in air and water.

Authors:  Erik Dixon-Anderson; Rainer Lohmann
Journal:  Environ Toxicol Chem       Date:  2018-11-05       Impact factor: 3.742

2.  Reliable Prediction of the Octanol-Air Partition Ratio.

Authors:  Sivani Baskaran; Ying Duan Lei; Frank Wania
Journal:  Environ Toxicol Chem       Date:  2021-10-01       Impact factor: 4.218

3.  Applications of Machine Learning to In Silico Quantification of Chemicals without Analytical Standards.

Authors:  Dimitri Panagopoulos Abrahamsson; June-Soo Park; Randolph R Singh; Marina Sirota; Tracey J Woodruff
Journal:  J Chem Inf Model       Date:  2020-05-20       Impact factor: 4.956

4.  Determination of soil-water sorption coefficients of volatile methylsiloxanes.

Authors:  Gary E Kozerski; Shihe Xu; Julie Miller; Jeremy Durham
Journal:  Environ Toxicol Chem       Date:  2014-08-04       Impact factor: 3.742

5.  Applicability Domain of Polyparameter Linear Free Energy Relationship Models Evaluated by Leverage and Prediction Interval Calculation.

Authors:  Satoshi Endo
Journal:  Environ Sci Technol       Date:  2022-04-14       Impact factor: 9.028

  5 in total

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