Journal of Computer-Aided Molecular Design

, Volume 32, Issue 6, pp 711–722 | Cite as

Prediction of partition and distribution coefficients in various solvent pairs with COSMO-RS

  • Sofja Tshepelevitsh
  • Kertu Hernits
  • Ivo Leito


Performance of COSMO-RS method as a tool for partition and distribution modeling in 20 solvent pairs—composed of neutral or acidic aqueous solution and organic solvents of different polarity, ranging from alcohols to toluene and hexane—was evaluated. Experimental partition/distribution data of lignin-related and drug-like compounds (neutral, acidic, moderately basic) were used as reference. Several aspects of partition modeling were addressed: accounting for mutual saturation of aqueous and organic phases, variability of systematic prediction errors across solvent pairs, taking solute ionization into account. COSMO-RS was found to predict extraction outcome for both ligneous and drug-like compounds in various solvent pairs fairly well without any additional empirical input. The solvent-specific systematic errors were found to be moderate, despite being statistically significant, and related to the solvent hydrophobicity. Accounting for mutual solubilities of the two liquids was proven crucial in cases where water was considerably soluble in the organic solvent. The root mean square error of a priori logP prediction varied, depending mainly on the solvent pair, from 0.2 to 0.7, overall value being 0.6 log units. The accuracy was higher in case of hydrophilic than hydrophobic solvents. The logD predictions were less accurate, due to pKa prediction being an additional source of error, and also because of the complexity of modeling the behaviour of ionic species in the two-phase system. A simple correction for partitioning of free ions was found to notably improve logD prediction accuracy in case of the most hydrophilic organic phase (butanol/water).


COSMO-RS Distribution coefficient Molecular modeling Liquid–liquid extraction Solvent effects 



This work was supported by the Institutional Funding IUT20-14 from the Estonian Research Council and by the EU through the European Regional Development Fund (TK141 “Advanced materials and high-technology devices for energy recuperation systems”). Authors thank Dr. Jens Reinisch for helpful discussions. Authors also thank Dr. Joel Hawkins and Pfizer Inc. for helpful discussions and help in obtaining chemicals.

Supplementary material

10822_2018_125_MOESM1_ESM.pdf (881 kb)
Supplementary material 1 (PDF 881 KB)


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Institute of ChemistryUniversity of TartuTartuEstonia

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