Prediction of cyclohexane-water distribution coefficients with COSMO-RS on the SAMPL5 data set

The Conductor-Like-Screening-Model for Real Solvents (COSMO-RS) method has been used for the blind prediction of cyclohexane-water distribution coefficients logD within the SAMPL challenge. The partition coefficient logP of the neutral species was calculated first and then corrected for dissociation...

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Bibliographic Details
Published in:Journal of computer-aided molecular design 2016-11, Vol.30 (11), p.959-967
Main Authors: Klamt, Andreas, Eckert, Frank, Reinisch, Jens, Wichmann, Karin
Format: Article
Language:English
Subjects:
Animal Anatomy
CAD
Chemistry
Chemistry and Materials Science
Computer aided design
Computer Applications in Chemistry
Computer Simulation
Cyclohexanes - chemistry
Datasets
Drug Discovery
Histology
Models, Chemical
Molecular Conformation
Molecular physics
Morphology
Pharmaceutical Preparations - chemistry
Physical Chemistry
Solubility
Solutes
Solvents
Solvents - chemistry
Thermodynamics
Water - chemistry
Water distribution
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Summary:The Conductor-Like-Screening-Model for Real Solvents (COSMO-RS) method has been used for the blind prediction of cyclohexane-water distribution coefficients logD within the SAMPL challenge. The partition coefficient logP of the neutral species was calculated first and then corrected for dissociation or protonation, as appropriate for acidic or basic solutes, to obtain the cyclohexane-water logD. Using the latest version of the COSMO therm implementation, this approach in combination with a rigorous conformational sampling yielded a predictive accuracy of 2.11 log units (RMSD) for the 53 compounds of the blind prediction dataset. By that it was the most accurate of all contest submissions and it also achieved the best rank order. The RMSD mainly arises from a group of outliers in the negative logD range, which at least partly may arise from dimerization or other experimental problems coming up for very polar molecules in very non-polar solvents.
ISSN:0920-654X
1573-4951
DOI:10.1007/s10822-016-9927-y