Quantitative structure-property relationships for octanol-air partition coefficients of polychlorinated naphthalenes, chlorobenzenes and p,p '-DDT

The octanol-air partition coefficient (K-OA) is a key descriptor of chemicals partitioning between the atmosphere and environmental organic phases. Quantitative structure-property relationships (QSPR) are necessary to model and predict KOA from molecular structures. Based on 12 quantum chemical descriptors computed by the PM3 Hamiltonian, using partial least squares (PLS) analysis, a QSPR model for logarithms of K-OA to base 10 (log K-OA) for polychlorinated naphthalenes (PCNs), chlorobenzenes and p,p'-DDT was obtained. The cross-validated Q(cum)(2) value of the model is 0.973, indicating a good predictive ability of the model. The main factors governing log K-OA of the PCNs, chlorobenzenes, and p,p'-DDT are, in order of decreasing importance, molecular size and molecular ability of donating/accepting electrons to participate in intermolecular interactions. The intermolecular dispersive interactions play a leading role in governing log K-OA. The more chlorines in PCN and chlorobenzene molecules, the greater the log K-OA values. Increasing E-LUMO (the energy of the lowest unoccupied molecular orbital) of the molecules leads to decreasing log K-OA values, implying possible intermolecular interactions between the molecules under study and octanol molecules. (C) 2002 Elsevier Science Ltd. All rights reserved.

Quantitative relationships between molecular structures, environmental temperatures and octanol-air partition coefficients of PCDD/Fs

A concise quantitative model that incorporates information on both environmental temperature M and molecular structures, for logarithm of octanol-air partition coefficient (K-OA) to base 10 (logK(OA)) of PCDDs, was developed. Partial least squares (PLS) analysis together with 14 quantum chemical descriptors were used to develop the quantitative relationships between structures, environmental temperatures and properties (QRSETP) model. It has been validated that the obtained QRSETP model can be used to predict logK(OA) of other PCDDs. Molecular size, environmental temperature (T), q(+) (the most positive net atomic charge on hydrogen or chlorine atoms in PCDD molecules) and E-LUMO (the energy of the lowest unoccupied molecular orbital) are main factors governing logK(OA) of PCDD/Fs under study. The intermolecular dispersive interactions and thus the size of the molecules play a leading role in governing logK(OA). The more chlorines in PCDD molecules, the greater the logK(OA) values. Increasing E-LUMO values of the molecules leads to decreasing logK(OA) values, implying possible intermolecular interactions between the molecules under study and octanol molecules. Greater q(+) values results in greater intermolecular electrostatic repulsive interactions between PCDD and octanol molecules and smaller logK(OA) values. (C) 2002 Elsevier Science B.V. All rights reserved.

Quantitative structure-property relationship studies on n-octanol/water partitioning coefficients of PCDD/Fs

Based on some fundamental quantum chemical descriptors computed by PM3 Hamiltonian, by the use of partial least-squares (PLS) analysis, a significant quantitative structure-property relationship (QSPR) model for logK(ow) of polychlorinated dibenzo-p-dioxins and dibenzo-p-furans (PCDD/Fs) was obtained. The QSPR can be used for prediction. The intermolecular dispersive interactions and thus the bulkness of the PCDD/Fs are the main factors affecting the logK(ow). The more chlorines in the PCDD/F molecule, the greater the logK(ow) values. (C) 2001 Elsevier Science Ltd. All rights reserved.