Journal of Computer-Aided Molecular Design

, Volume 30, Issue 11, pp 989–1006 | Cite as

Calculating distribution coefficients based on multi-scale free energy simulations: an evaluation of MM and QM/MM explicit solvent simulations of water-cyclohexane transfer in the SAMPL5 challenge

  • Gerhard KönigEmail author
  • Frank C. Pickard IV
  • Jing Huang
  • Andrew C. Simmonett
  • Florentina Tofoleanu
  • Juyong Lee
  • Pavlo O. Dral
  • Samarjeet Prasad
  • Michael Jones
  • Yihan Shao
  • Walter Thiel
  • Bernard R. Brooks


One of the central aspects of biomolecular recognition is the hydrophobic effect, which is experimentally evaluated by measuring the distribution coefficients of compounds between polar and apolar phases. We use our predictions of the distribution coefficients between water and cyclohexane from the SAMPL5 challenge to estimate the hydrophobicity of different explicit solvent simulation techniques. Based on molecular dynamics trajectories with the CHARMM General Force Field, we compare pure molecular mechanics (MM) with quantum-mechanical (QM) calculations based on QM/MM schemes that treat the solvent at the MM level. We perform QM/MM with both density functional theory (BLYP) and semi-empirical methods (OM1, OM2, OM3, PM3). The calculations also serve to test the sensitivity of partition coefficients to solute polarizability as well as the interplay of the quantum-mechanical region with the fixed-charge molecular mechanics environment. Our results indicate that QM/MM with both BLYP and OM2 outperforms pure MM. However, this observation is limited to a subset of cases where convergence of the free energy can be achieved.


Distribution coefficient Partition coefficient Water Cyclohexane Multi-scale free energy simulations Explicit solvent 



The authors would like to thank Tim Miller, Richard Venable and John Legato for technical assistance. We would also like to thank Richard Pastor and Richard Venable for very helpful discussions concerning the nature of the apolar phase, especially in octanol. This work was partially supported by the intramural research program of the National Heart, Lung and Blood Institute of the National Institutes of Health and utilized the high-performance computational capabilities of the LoBoS and Biowulf Linux clusters at the National Institutes of Health. ( and The research leading to these results has also received funding from the European Research Council within an ERC Advanced Grant (OMSQC).


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Copyright information

© Springer International Publishing Switzerland (outside the USA) 2016

Authors and Affiliations

  • Gerhard König
    • 1
    • 2
    Email author
  • Frank C. Pickard IV
    • 1
  • Jing Huang
    • 1
  • Andrew C. Simmonett
    • 1
  • Florentina Tofoleanu
    • 1
  • Juyong Lee
    • 1
  • Pavlo O. Dral
    • 2
  • Samarjeet Prasad
    • 1
  • Michael Jones
    • 1
  • Yihan Shao
    • 1
  • Walter Thiel
    • 2
  • Bernard R. Brooks
    • 1
  1. 1.Laboratory of Computational BiologyNational Heart, Lung and Blood Institute, National Institutes of HealthBethesdaUSA
  2. 2.Max-Planck-Institut für KohlenforschungMülheim an der RuhrGermany

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