Development, Validation and Inspection of the Applicability Domain of QSPR Models for Physicochemical Properties of Polybrominated Diphenyl Ethers

Abstract

Polybrominated diphenyl ethers (PBDEs) are a group of brominated flame retardants (BFRs), which were widely used in a variety of consumer products. Because of evidences of toxicity effects on different organisms and humans, as well as the ubiquitary profile of these compounds, PBDEs are considered an emerging group of toxic and persistent organic pollutants. However, due to the small amount of experimental data available, still little is known about the properties of most of these chemicals. In this study several physicochemical properties, experimentally available for few PBDE congeners and hexabromobenzene (HBB), were investigated through a modelling approach based on quantitative structure-property relationships (QSPR). The OLS regression models, based on theoretical molecular descriptors, are calculated for Henry's law constant, melting point, subcooled liquid vapor pressure, water solubility, octanol-air partition coefficient, and octanol-water partition coefficient. These models can be useful to predict the big amount of missing data and to plan safer alternatives to dangerous BFRs. The innovative aspect of the proposed models, compared to those already published in the literature, is their development according to the OECD principles for regulatory acceptability of QSARs. This includes the validation for predictivity (both by internal and external statistical validation) and the inspection of the applicability domain

QSAR model reproducibility and applicability: A case study of rate constants of hydroxyl radical reaction models applied to polybrominated diphenyl ethers and (benzo‐)triazoles

“…We used quantum chemical descriptors previously 10,22 calculated in our group, but the same descriptors can also be freely calculated on the web. 13 Respectively, input sets of 344 descriptors and 1026 descriptors underwent the subsequent selection for the best modeling variables.…”

Development of a QSPR model for predicting thermal stabilities of nitroaromatic compounds taking into account their decomposition mechanisms

“…They require a defined endpoint, an unambiguous algorithm, a defined domain of applicability, appropriate measures of goodness-of-fit, robustness and predictivity and a mechanistic interpretation, if possible. Until now, only few QSPR models were investigated under these principles [34].…”

On the Use of Local and Global QSPRs for the Prediction of Physico‐chemical Properties of Polybrominated Diphenyl Ethers

“…[10] Logarithmic values for the endpoints Koa and Kow, and MP values expressed in centigrade scale, were used to perform all the calculations reported in this paper, in agreement with the originally modeled values and predictions reported in literature. [10-14, 26, 27] If more than one experimental value was available for a single compound and a single endpoint, the averaged values were used to develop the here analyzed QSPR models.…”

“…In this study several QSPR models specifically developed for the prediction of logKoa, logKow and melting point of PBDEs [10][11][12][13][14] were compared with predictions performed by KoaWIN, KowWIN and MPBPWIN from EPI Suite package, [26] and by DRAGON software (AlogP and MlogP). [27] Aim of this work was to identify ranges of reliable application of the analyzed QSPRs and to highlight unsuitability of some of the studied models for the prediction of the examined physico-chemical properties of PBDEs.…”

“…[9][10][11][12][13][14] These models are typically characterized by structural applicability domains (AD) which are strictly associated to the structural space of the related experimental training set.…”