Blinded predictions of distribution coefficients in the SAMPL5 challenge

• Published in: Journal of computer-aided molecular design 2016-11, Vol.30 (11), p.1101-1114
• Main Authors: Bosisio, Stefano, Mey, Antonia S. J. S., Michel, Julien
• Format: Article
• Language: English
• Subjects: Animal Anatomy; Charging; Chemistry; Chemistry and Materials Science; Computer Applications in Chemistry; Computer Simulation; Confidence intervals; Cyclohexanes - chemistry; Databases, Chemical; Free energy; Histology; Mathematical models; Models, Chemical; Molecular physics; Molecular Structure; Morphology; Permissible error; Pharmaceutical Preparations - chemistry; Phases; Physical Chemistry; Quantum Theory; Simulation; Solubility; Solvents; Solvents - chemistry; Tautomers; Texts; Thermodynamics; Water - chemistry
• ISSN: 0920-654X; 1573-4951
• DOI: 10.1007/s10822-016-9969-1

In the context of the SAMPL5 challenge water-cyclohexane distribution coefficients for 53 drug-like molecules were predicted. Four different models based on molecular dynamics free energy calculations were tested. All models initially assumed only one chemical state present in aqueous or organic phases. Model A is based on results from an alchemical annihilation scheme; model B adds a long range correction for the Lennard Jones potentials to model A ; model C adds charging free energy corrections; model D applies the charging correction from model C to ionizable species only. Model A and B perform better in terms of mean-unsigned error ( MUE = 6.79 < 6.87 < 6.95 log D units − 95 % confidence interval) and determination coefficient ( R 2 = 0.26 < 0.27 < 0.28 ) , while charging corrections lead to poorer results with model D ( MUE = 12.8 < 12.63 < 12.98 and R 2 = 0.16 < 0.17 < 0.18 ). Because overall errors were large, a retrospective analysis that allowed co-existence of ionisable and neutral species of a molecule in aqueous phase was investigated. This considerably reduced systematic errors ( MUE = 1.87 < 1.97 < 2.07 and R 2 = 0.35 < 0.40 < 0.45 ). Overall accurate log D predictions for drug-like molecules that may adopt multiple tautomers and charge states proved difficult, indicating a need for methodological advances to enable satisfactory treatment by explicit-solvent molecular simulations.