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Partition coefficients for the SAMPL5 challenge using transfer free energies

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Abstract

SAMPL challenges (Mobley et al. in J Comput Aided Mol Des 28:135–150, 2014; Skillman in J Comput Aided Mol Des 26:473–474, 2012; Geballe in J Comput Aided Mol Des 24:259–279, 2010; Guthrie in J Phys Chem B 113:4501–4507, 2009) provide excellent opportunities to assess theoretical approaches on new data sets with a goal of gaining greater insight towards protein and ligand modeling. In the SAMPL5 experiment, cyclohexane–water partition coefficients were determined using a vertical solvation scheme in conjunction with the SMD continuum solvent model. Several DFT functionals partnered with correlation consistent basis sets were evaluated for the prediction of the partition coefficients. The approach chosen for the competition, a B3PW91 vertical solvation scheme, yields a mean absolute deviation of 1.9 logP units and performs well at estimating the correct hydrophilicity and hydrophobicity for the full SAMPL5 molecule set.

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Acknowledgments

This research was supported in part by the Intramural Research Program of the NIH, NHLBI. During the beginning of the SAMPL5 competition, AKW and MRJ were at the University of North Texas, where the calculations were done. Thus, the authors gratefully acknowledge Research Computing Services at the University of North Texas for computational resources. The authors thank Frank C. Pickard IV and Yihan Shao for their comments on the manuscript.

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Authors and Affiliations

  1. Department of Chemistry, Michigan State University, 578 S. Shaw Ln, East Lansing, MI, 48824, USA

    Michael R. Jones & Angela K. Wilson

  2. Laboratory of Computational Biology, National Heart, Lung and Blood Institute, 5635 Fishers Lane, T-900 Suite, Rockville, MD, 20852, USA

    Michael R. Jones & Bernard R. Brooks

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  1. Michael R. Jones
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  2. Bernard R. Brooks
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  3. Angela K. Wilson
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Correspondence to Angela K. Wilson.

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Jones, M.R., Brooks, B.R. & Wilson, A.K. Partition coefficients for the SAMPL5 challenge using transfer free energies. J Comput Aided Mol Des 30, 1129–1138 (2016). https://doi.org/10.1007/s10822-016-9964-6

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