Comparison of different models predicting the phospholipid-membrane water partition coefficients of charged compounds. (February 2016)

• Record Type: Journal Article
• Authors: Bittermann, Kai; Spycher, Simon; Goss, Kai-Uwe
• Is Part Of: Chemosphere. Volume 144(2016)
• Page Start: 382
• Page End: 391
• Publication Date: 2016-02
• Subjects: Membrane -- Partitioning -- Liposome -- COSMOmic -- pp-LFER -- Ions; Pollution -- Periodicals; Pollution -- Physiological effect -- Periodicals; Environmental sciences -- Periodicals; Atmospheric chemistry -- Periodicals; 551.511
• DOI: 10.1016/j.chemosphere.2015.08.065
• Languages: English
• ISSNs: 0045-6535

Abstract

Abstract: A large fraction of commercially used chemicals is ionizable. This results in the need for mechanistic models to describe the physicochemical properties of ions, like the membrane-water partition coefficient ( K mw ), which is related to toxicity and bioaccumulation. In this work we compare 3 different and already existing modelling approaches to describe the liposome-water partition coefficient ( K lipw ) of organic ions, including 36 cations, 56 anions, 2 divalent cations and 2 zwitterions (plus 207 neutral compounds for ensuring model consistency). 1) The empirical correlation with the octanol-water partition coefficient of the corresponding neutral species yielded better results for the prediction of anions (RMSE = 0.79) than for cations (RMSE = 1.14). Though describing most anions reasonably well, the lack of mechanistic basis and the poor performance for cations constrain the usage of this model. 2) The polyparameter linear free energy relationship (pp-LFER) model performs worse (RMSE = 1.26/1.12 for anions/cations). The different physicochemical environments, due to different sorption depths into the membrane of the different species, cannot be described with a single pp-LFER model. 3) COSMO mic is based on quantum chemistry and fluid phase thermodynamics and has the widest applicability domain. It was the only model applicable for multiply charged ions and gave the best results for anions (RMSE = 0.66) and cations (RMSE = 0.71). We expect COSMO mic to contribute to a better estimation of the environmental risk of ionizable emerging pollutants. Graphical abstract: Highlights: Klipw of ionic and neutral organic compounds are modeled with 3 different models. COSMO mic has mechanistic basis and performs best for prediction of ionic compounds. PP-LFER and empirical Kow correlation perform equally well for neutral compounds. PP-LFER can't model cations + anions because they sorb to different membrane depths. Organic ions do not always sorb 1/10 as strong as neutral analogs.