Holographic quantitative structure-activity relationship for prediction of the toxicity of polybromi

来源 :Science in China(Series B:Chemistry) | 被引量 : 0次 | 上传用户:zxllxp
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Polybrominated diphenyl ether congeners (PBDEs) might activate the AhR (aromatic hydrocarbon receptor) signal transduction,and thus might have an adverse effect on the health of humans and wildlife. Because of the limited experimental data,it is important and necessary to develop structure-based models for prediction of the toxicity of the compounds. In this study,a new molecular structure representation,molecular hologram,was employed to investigate the quantitative relationship between toxicity and molecular structures for 18 PBDEs. The model with the significant correlation and robustness (r2 = 0.991,q2LOO = 0.917) was developed. To verify the robustness and prediction capacity of the derived model,14 PBDEs were randomly selected from the database as the training set,while the rest were used as the test set. The results generated under the same modeling conditions as the optimal model are as follows:r2 = 0.988,q2LOO = 0.598,r2pred = 0.955,and RMSE (root-mean-square of errors) = 0.155,suggesting the excellent ability of the derived model to predict the toxicity of PBDEs. Furthermore,the structural features and molecular mechanism related to the toxicity of PBDEs were explored using HQSAR color coding. Because of the limited experimental data, it is important and necessary to develop structure- based models for prediction of the toxicity of the compounds. In this study, a new molecular structure representation, molecular hologram, was employed to investigate the quantitative relationship between toxicity and molecular structures for 18 PBDEs. The model with the significant correlation and robustness (r2 = 0.991, q2LOO = 0.917) was developed. To verify the robustness and prediction capacity of the derived model, 14 PBDEs were randomly selected from the database as the training set, while the rest were used as the test set. The results generated under the same modeling conditions as the optimal model are as follows: r2 = 0.988, q2LOO = 0.598, r2pred = 0.955, and RMSE (root-mean-square of errors) = 0.15 Suggests the excellent ability of the derived model to predict the toxicity of PBDEs. Furthermore, the structural features and molecular mechanism related to the toxicity of PBDEs were explored using HQSAR color coding.
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