Citation: LIU Yang-Hua, ZHOU Zhi-Xiang, ZHANG Xiao-Long, LI Han-Dong. Development of QSAR Model for Predicting the Mutagenicity of Aromatic Compounds[J]. Chinese Journal of Structural Chemistry, ;2015, 34(3): 324-334. doi: 10.14102/j.cnki.0254-5861.2011-0518 shu

Development of QSAR Model for Predicting the Mutagenicity of Aromatic Compounds

a.
a. College of Life Science and Bioengineering, Beijing University of Technology, Beijing 100124, China;
b.
b. Chinese Research Academy of Environmental Sciences, Beijing 100012, China

Received Date: 20 September 2014
Available Online: 16 December 2014
Fund Project: Supported by the Ministry of Environmental Protection of China (No. 2011467037) (No. 2011467037)

Quantitative structure-activity relationship (QSAR) model was developed for predicting the mutagenicity of aromatic compounds. The log revertants data of S. typhimurium TA98 strain from Ames test have been collected. 225 aromatic compounds were randomly divided into the training set with 186 molecules and test set with 39 molecules. Multiple linear regression (MLR) analysis was used to select six descriptors from thousands of descriptors calculated by semiempirical AM1 and E-dragon methods. The final QSAR model with six descriptors was internal and external validated. In addition, to validate the utility of our QSAR model for the chemical evaluation, three aromatic compounds were taken to test the predictive ability and reliability of the model experimentally. The compounds selected for testing were not based on the predictions, thus spanning the range of predicted probabilities. The subsequently generated results of the Ames test were in good correspondence with the predictions and confirmed this approach as a useful means of predicting likely mutagenic risk of aromatic compounds.
- aromatic compounds,
- quantitative structure-activity relationship (QSAR),
- multiple linear regression (MLR),
- mutagenicity,
- Ames test
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