Citation: Wan Jinyu, Liu Yifei. Toxicity Prediction of Organophosphorus Compounds based on QSAR Model[J]. Chemistry, ;2019, 82(10): 926-936. shu

Toxicity Prediction of Organophosphorus Compounds based on QSAR Model

Wan Jinyu ^1, ,
Liu Yifei ²

1.
Department of Pharmacy, QuanZhou Medical College, Quanzhou 362000
2.
The Second Affiliated Hospital, Fujian Medical University, Quanzhou 362000

Received Date: 10 May 2019
Accepted Date: 10 June 2019

Figures(3)

With the wide application of organophosphorus compounds (OPs), they have been detected in an increasing number of environmental media. Most OPs are poisonous, but people often lack fast and effective prediction methods to evaluate the toxicity. In this paper, the toxicity of 36 OPs was predicted by using different QSAR models combined with molecular descriptors by computer with E-Dragon software. Using the backward method as the screening result, root mean square error (RMSE) as evaluation standard, we found that the 14 molecular descriptors have a great influence on the linear kernel function of support vector machine (SVM) model. In the cross-validation results of SVM models, the correlation coefficient between the calculated value and the actual value was 0.913, the root mean square error is 0.388. In the results of external test verification, the average relative error was 9.10%. In addition, we also used multiple linear regression (MLR), artificial neural network (ANN) and partial least squares regression (PLS) models to predict the toxicity of OPs. The cross-validation results showed that the correlation coefficients between the calculated values and the actual values of the three models are 0.878, 0.686 and 0.620, respectively. Therefore, the linear kernel SVM model is an effective method for the toxicity prediction of OPs.
- Organophosphorous compounds,
- QSAR,
- Molecular descriptors,
- Support vector machine
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