Octanol/Air Partition Coefficient─A General-Purpose Fragment Model to Predict Log K_oa from Molecular Structure

The octanol/air partition coefficient K_oa is important for assessing the bioconcentration of airborne xenobiotics in foliage and in air-breathing organisms. Moreover, K_oa informs about compound partitioning to aerosols and indoor dust, and complements the octanol/water partition coefficient K_ow and the air/water partition coefficient K_aw for multimedia fate modeling. Experimental log K_oa at 25 °C has been collected from literature for 2161 compounds with molecular weights from 16 to 959 Da. The curated data set covers 18.2 log units (from -1.0 to 17.2). A newly developed fragment model for predicting log K_oa from molecular structure outperforms COSMOtherm, EPI-Suite KOAWIN, OPERA, and linear solvation energy relationships (LSERs) regarding the root-mean-squared error (rms) and the maximum negative and positive errors (mne and mpe) (rms: 0.57 vs 0.86 vs 1.09 vs 1.19 vs 1.05-1.53, mne: -2.55 vs -3.95 vs -7.51 vs -7.54 vs (-5.63) - (-7.34), mpe: 2.91 vs 5.97 vs 7.54 vs 4.24 vs 6.89-10.2 log units). The prediction capability, statistical robustness, and sound mechanistic basis are demonstrated through initial separation into a training and prediction set (80:20%), mutual leave-50%-out validation, and target value scrambling in terms of temporarily wrong compound-K_oa allocations. The new general-purpose model is implemented in a fully automatized form in the ChemProp software available to the public. Regarding K_oa indirectly determined through K_ow and K_aw, a new approach is developed to convert from wet to dry octanol, enabling higher consistency in experimental (and thus also predicted) K_oa.