Literature DB >> 19268338

Classification of toxicity of phenols to Tetrahymena pyriformis and subsequent derivation of QSARs from hydrophobic, ionization and electronic parameters.

Yuan H Zhao1, Xing Yuan, Li M Su, Wei C Qin, Michael H Abraham.   

Abstract

Phenolic compounds were classified into different groups based on the structure and functional groups of the phenol. Quantitative structure-activity relationship (QSAR) analysis was performed between the toxicity and octanol/water partition coefficient (logP) for these groups. The results showed that the toxicity of non-ionisable phenols is dependent on their hydrophobicity. Poor relationships were found between the toxicity and logP for ionisable compounds, and the use of methods based on logP to predict the toxicity of ionisable compounds can result in considerable errors. Ionized and unionized forms have different contributions to toxicity; the unionized form plays a more important role than the ionized form because the toxicity of organic acids and phenols decreases as the pH increases. In order to investigate the effect of ionization, the fraction of ionized and unionized forms of phenols at different pH values were calculated from the pK(a) values, and a corrected distribution partition coefficient (D(T)) was derived from QSAR analysis for ionisable compounds. The prediction of toxicity of non-reactive ionisable compounds was improved remarkably by using the D(T) parameter. Ionization not only affects the bio-uptake of ionisable compounds, but interaction with the receptor micromolecule can also depend on the electronic situation, which is also related to the ionization. Stepwise regression showed that the reactivity of ionisable phenols was strongly correlated with the fraction of negatively charged form (F(-)). Interpretable QSAR equations with good statistical fits were developed from hydrophobic, ionization and electronic parameters for 207 phenols.

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Year:  2009        PMID: 19268338     DOI: 10.1016/j.chemosphere.2009.01.055

Source DB:  PubMed          Journal:  Chemosphere        ISSN: 0045-6535            Impact factor:   7.086


  3 in total

1.  Prediction of partition and distribution coefficients in various solvent pairs with COSMO-RS.

Authors:  Sofja Tshepelevitsh; Kertu Hernits; Ivo Leito
Journal:  J Comput Aided Mol Des       Date:  2018-05-30       Impact factor: 3.686

2.  MOA-based linear and nonlinear QSAR models for predicting the toxicity of organic chemicals to Vibrio fischeri.

Authors:  Shengnan Zhang; Ning Wang; Limin Su; Xiaoyan Xu; Chao Li; Weichao Qin; Yuanhui Zhao
Journal:  Environ Sci Pollut Res Int       Date:  2020-01-08       Impact factor: 4.223

3.  Inside of the Linear Relation between Dependent and Independent Variables.

Authors:  Lorentz Jäntschi; Lavinia L Pruteanu; Alina C Cozma; Sorana D Bolboacă
Journal:  Comput Math Methods Med       Date:  2015-05-25       Impact factor: 2.238

  3 in total

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