Literature DB >> 9717517

Phenol toxicity in leukemia cells: a radical process?

C D Selassie1, T V DeSoyza, M Rosario, H Gao, C Hansch.   

Abstract

The multiple functions of the phenol moiety that are widely present in disparate sources such as drugs, pesticides, teas, fuel additives and surfactants have not been clearly delineated. The differences in behavior of phenols, which run the gamut from aberrations in DNA/chromosomes to suppression of genotoxic activity of carcinogenic compounds, merit further attention. In this study, a through examination of the growth inhibition patterns of 37, simple 3- and 4-substituted phenols in mouse leukemia cells was carried out and the following quantitative structure-activity relationship (QSAR) was obtained for the 23 electron releasing substituents in X-phenols: log 1/IC50 = -1.58 sigma(+) +0.21 log P + 3.10. In this QSAR, IC50 is the concentration of phenol that induces 50% inhibition of growth. P is a measure of the hydrophobicity of each phenol and Brown's electronic parameter, sigma+, represents the electronic effect of the substituent. The negative dependence on sigma+ is strongly reminiscent of what is observed in the developmental toxicity of phenols on rat embryos as well as for the radical abstraction of a hydrogen atom from phenolic groups. The other 15 electron-attracting substituted X-phenols clearly show a linear dependence on hydrophobicity alone: Log 1/IC50 = 0.62 log P + 2.35. The bifurcation in mechanism of action of this large set of diverse phenols is novel and unusual. It suggests that two distinct processes are operative. In the case of electron releasing substituted phenols, the observations are not inconsistent with a radical mediated process while with electron attracting substituted phenols, non-specific toxicity as modulated by hydrophobicity, appears to predominate.

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Year:  1998        PMID: 9717517     DOI: 10.1016/s0009-2797(98)00027-1

Source DB:  PubMed          Journal:  Chem Biol Interact        ISSN: 0009-2797            Impact factor:   5.192


  3 in total

1.  Application of artificial neural networks for predicting the aqueous acidity of various phenols using QSAR.

Authors:  Aziz Habibi-Yangjeh; Mohammad Danandeh-Jenagharad; Mahdi Nooshyar
Journal:  J Mol Model       Date:  2005-12-13       Impact factor: 1.810

2.  3D-QSAR studies on caspase-mediated apoptosis activity of phenolic analogues.

Authors:  Yuanqiang Wang; Heng Zhang; Yong Lin; Qi Zhao; Hui Liu; Zhan Zhang; Qingyou Xia; Bo Zhu; Zhihua Lin
Journal:  J Mol Model       Date:  2010-03-21       Impact factor: 1.810

3.  Growth Inhibition and DNA Damage Induced by X-Phenols in Yeast: A Quantitative Structure-Activity Relationship Study.

Authors:  M Cristina Negritto; Clarissa Valdez; Jasmine Sharma; Christa Rosenberg; Cynthia R Selassie
Journal:  ACS Omega       Date:  2017-12-01
  3 in total

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