QSPR study on the octanol/air partition coefficient of polybrominated diphenyl ethers by using molecular distance-edge vector index.

BACKGROUND

The quantitative structure property relationship (QSPR) for octanol/air partition coefficient (K OA) of polybrominated diphenyl ethers (PBDEs) was investigated. Molecular distance-edge vector (MDEV) index was used as the structural descriptor of PBDEs. The quantitative relationship between the MDEV index and the lgK OA of PBDEs was modeled by multivariate linear regression (MLR) and artificial neural network (ANN) respectively. Leave one out cross validation and external validation was carried out to assess the predictive ability of the developed models. The investigated 22 PBDEs were randomly split into two groups: Group I, which comprises 16 PBDEs, and Group II, which comprises 6 PBDEs.

RESULTS

The MLR model and the ANN model for predicting the K OA of PBDEs were established. For the MLR model, the prediction root mean square relative error (RMSRE) of leave one out cross validation and external validation is 2.82 and 2.95, respectively. For the L-ANN model, the prediction RMSRE of leave one out cross validation and external validation is 2.55 and 2.69, respectively.

CONCLUSION

The developed MLR and ANN model are practicable and easy-to-use for predicting the K OA of PBDEs. The MDEV index of PBDEs is shown to be quantitatively related to the K OA of PBDEs. MLR and ANN are both practicable for modeling the quantitative relationship between the MDEV index and the K OA of PBDEs. The prediction accuracy of the ANN model is slightly higher than that of the MLR model. The obtained ANN model shoud be a more promising model for studying the octanol/air partition behavior of PBDEs.