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Bulletin of the Korean Chemical Society (BKCS)

ISSN 0253-2964(Print)
ISSN 1229-5949(Online)
Volume 35, Number 12
BKCSDE 35(12)
December 20, 2014 

Prediction of the Toxicity of Dimethylformamide, Methyl Ethyl Ketone, and Toluene Mixtures by QSAR Modeling
Ki-Woong Kim*, Yong Lim Won, Mun Ki Hong, Jihoon Jo, Sung Kwang Lee
QSAR, Chemical mixtures, Toxicity
In this study, we analyzed the toxicity of mixtures of dimethylformamide (DMF) and methyl ethyl ketone (MEK) or DMF and toluene (TOL) and predicted their toxicity using quantitative structure-activity relationships (QSAR). A QSAR model for single substances and mixtures was analyzed using multiple linear regression (MLR) by taking into account the statistical parameters between the observed and predicted EC50. After preprocessing, the best subsets of descriptors in the learning methods were determined using a 5-fold cross-validation method. Significant differences in physico-chemical properties such as boiling point (BP), specific gravity (SG), Reid vapor pressure (rVP), flash point (FP), low explosion limit (LEL), and octanol/ water partition coefficient (Pow) were observed between the single substances and the mixtures. The EC50 of the mixture of DMF and TOL was significantly lower than that of DMF. The mixture toxicity was directly related to the mixing ratio of TOL and MEK (MLR EC50 equation = 1.76997 − 1.12249 × TOL + 1.21045 × MEK), as well as to SG, VP, and LEL (MLR equation EC50 = 15.44388 − 19.84549 × SG + 0.05091 × VP + 1.85846 × LEL). These results show that QSAR-based models can be used to quantitatively predict the toxicity of mixtures used in manufacturing industries.
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