Literature DB >> 14672317

Estimation of cytotoxicity to HEP-G2 cells of 255 environmental pollutants and water using QSAR (Quantitative Structure-Activity Relationship).

Ryo Shoji1, Takanori Miyazaki, Tatsuaki Nishimiya.   

Abstract

Although bioassays are considered to be a rational method for environmental management, the procedure is generally too complicated to be applied to daily water quality management. In this study, the feasibility of using for application of a conventional QSAR (Quantitative Structure-Activity Relationship) method was examined to estimate the cytotoxicity of various pollutants found in environmental water. logP, pKa, and molecular weight were chosen as the physico/chemical properties of the pollutants, and defined equations for estimating cytotoxicity based on multiple linear regression analysis between these properties and in vitro cytotoxicity data from our previous results. As a result, a method for estimating cytotoxicity of environmental pollutants that had a certain probability (R>0.8) for the 255 chemicals was successfully developed. Considerably high reliability was shown in the leave-one-out prediction of multi-regression analysis. In addition, the cytotoxicity of environmental water samples was estimated based on multi-regression analysis, using as our samples leachates from 25 landfill sites in Japan. The method developed in this study estimated quantitatively the cytotoxicity of the environmental water from chemical analysis data without conducting a cytotoxicity test.

Entities:  

Mesh:

Substances:

Year:  2003        PMID: 14672317     DOI: 10.1081/ese-120025832

Source DB:  PubMed          Journal:  J Environ Sci Health A Tox Hazard Subst Environ Eng        ISSN: 1093-4529            Impact factor:   2.269


  1 in total

1.  Prediction of genotoxicity of various environmental pollutants by artificial neural network simulation.

Authors:  Ryo Shoji; Masato Kawakami
Journal:  Mol Divers       Date:  2006-06-27       Impact factor: 2.943

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.