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首页> 外文期刊>Chemistry central journal >QSPR study on the octanol/air partition coefficient of polybrominated diphenyl ethers by using molecular distance-edge vector index
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QSPR study on the octanol/air partition coefficient of polybrominated diphenyl ethers by using molecular distance-edge vector index

机译:利用分子距离边缘向量指数对多溴联苯醚的辛醇/空气分配系数进行QSPR研究

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Background The quantitative structure property relationship (QSPR) for octanol/air partition coefficient (KOA) 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 lgKOA 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 KOA 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 KOA of PBDEs. The MDEV index of PBDEs is shown to be quantitatively related to the KOA of PBDEs. MLR and ANN are both practicable for modeling the quantitative relationship between the MDEV index and the KOA 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.
机译:背景研究了多溴联苯醚(PBDEs)的辛醇/空气分配系数(KOA)的定量结构性质关系(QSPR)。分子距离边缘向量(MDEV)索引用作多溴二苯醚的结构描述符。分别通过多元线性回归(MLR)和人工神经网络(ANN)对MDEV指数与PBDEs lgKOA之间的定量关系进行建模。遗漏了交叉验证,并进行了外部验证来评估开发模型的预测能力。被调查的22种多溴二苯醚被随机分为两组:第一类包括16种多溴二苯醚,第二类包括6种多溴二苯醚。结果建立了预测多溴二苯醚KOA的MLR模型和ANN模型。对于MLR模型,留一法交叉验证和外部验证的预测均方根相对误差(RMSRE)分别为2.82和2.95。对于L-ANN模型,留一法交叉验证和外部验证的预测RMSRE分别为2.55和2.69。结论所建立的MLR和ANN模型可用于预测多溴二苯醚的KOA,且实用且易于使用。 PBDEs的MDEV指数与PBDEs的KOA定量相关。 MLR和ANN都可用于建立MDEV指数与多溴二苯醚的KOA之间的定量关系。 ANN模型的预测精度略高于MLR模型。所获得的人工神经网络模型应该成为研究多溴二苯醚的辛醇/空气分配行为的更有前途的模型。

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