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On the Use of Local and Global QSPRs for the Prediction of Physico‐chemical Properties of Polybrominated Diphenyl Ethers by Ester Papa; Simona Kovarich; Paola Gramatica is a Computer Science article available to read on EtoBox.

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## Abstract Polybrominated diphenyl ethers (PBDEs) are persistent chemicals that have been among the most marketed flame retardants used all over the world in the last decades. PBDEs have been detected in all environmental compartments, as well as in humans and wildlife, where they are able to accumulate and exert their toxic effects. At present only a limited amount of experimental data is available to characterize the physico‐chemical and toxicological behavior of PBDEs and similar brominated flame retardants. QSA(P)R approaches are very useful tools to predict missing data starting from the chemical structure of compounds. In this study several local QSPR models, developed specifically for the prediction of log__Koa__, log__Kow__ and melting point of PBDEs, were compared with predictions by global QSPR models, such as KoaWIN, KowWIN and MPBPWIN from the EPI Suite package, and __A__log__P__ and __M__log__P__ from DRAGON software, which were trained on heterogeneous and large datasets. The analysis addressed in the paper supported the identification of points of strength and weaknesses of both local models, and global models. The results are relevant to support decisions made by g

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Author

Ester Papa; Simona Kovarich; Paola Gramatica

Publisher

Wiley (John Wiley & Sons); Wiley - VCH Verlag GmbH & CO. KGaA; Wiley (ISSN 1868-1743)

Published

2011

Language

EN

Field

Computer Science (Physical Sciences)