Comparison of prediction methods for octanol-air partition coefficients of diverse organic compounds

The octanol-air partition coefficient (K-OA) is needed for assessing multimedia transport and bio-accumulability of organic chemicals in the environment. As experimental determination of K-OA for various chemicals is costly and laborious, development of K-OA estimation methods is necessary. We investigated three methods for K-OA prediction, conventional quantitative structure activity relationship (QSAR) models based on molecular structural descriptors, group contribution models based on atom centered fragments, and a novel model that predicts K-OA via solvation free energy from air to octanol phase (Delta G(O)(0)), with a collection of 939 experimental K-OA values for 379 compounds at different temperatures (263.15-323.15 K) as validation or training sets. The developed models were evaluated with the OECD guidelines on QSAR models validation and applicability domain (AD) description. Results showed that although the Delta G(O)(0) model is theoretically sound and has a broad AD, the prediction accuracy of the model is the poorest. The QSAR models perform better than the group contribution models, and have similar predictability and accuracy with the conventional method that estimates Km from the octanol water partition coefficient and Henry's law constant. One QSAR model, which can predict K-OA at different temperatures, was recommended for application as to assess the long-range transport potential of chemicals. (C) 2016 Elsevier Ltd. All rights reserved.