Evaluation of QSAR models for predicting the partition coefficient (log P) of chemicals under the REACH regulation.

Autor: Cappelli CI; Laboratory of Environmental Chemistry and Toxicology, Department of Environmental Health Sciences, IRCCS-Istituto di Ricerche Farmacologiche 'Mario Negri', Milan, Italy. Electronic address: claudia.cappelli@marionegri.it., Benfenati E; Laboratory of Environmental Chemistry and Toxicology, Department of Environmental Health Sciences, IRCCS-Istituto di Ricerche Farmacologiche 'Mario Negri', Milan, Italy. Electronic address: emilio.benfenati@marionegri.it., Cester J; Departament d'Enginyeria Quimica, Universitat Rovira i Virgili, Av. Països Catalans 26, Catalunya, Tarragona 43007, Spain. Electronic address: josep.cester@urv.cat.
Jazyk: angličtina
Zdroj: Environmental research [Environ Res] 2015 Nov; Vol. 143 (Pt A), pp. 26-32. Date of Electronic Publication: 2015 Sep 29.
DOI: 10.1016/j.envres.2015.09.025
Abstrakt: The partition coefficient (log P) is a physicochemical parameter widely used in environmental and health sciences and is important in REACH and CLP regulations. In this regulatory context, the number of existing experimental data on log P is negligible compared to the number of chemicals for which it is necessary. There are many models to predict log P and we have selected a number of free programs to examine how they predict the log P of chemicals registered for REACH and to evaluate wheter they can be used in place of experimental data. Some results are good, especially if the information on the applicability domain of the models is considered, with R(2) values from 0.7 to 0.8 and root mean square error (RMSE) from 0.8 to 1.5.
(Copyright © 2015 Elsevier Inc. All rights reserved.)
Databáze: MEDLINE
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