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Measuring experimental cyclohexane-water distribution coefficients for the SAMPL5 challenge

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Abstract

Small molecule distribution coefficients between immiscible nonaqueuous and aqueous phases—such as cyclohexane and water—measure the degree to which small molecules prefer one phase over another at a given pH. As distribution coefficients capture both thermodynamic effects (the free energy of transfer between phases) and chemical effects (protonation state and tautomer effects in aqueous solution), they provide an exacting test of the thermodynamic and chemical accuracy of physical models without the long correlation times inherent to the prediction of more complex properties of relevance to drug discovery, such as protein-ligand binding affinities. For the SAMPL5 challenge, we carried out a blind prediction exercise in which participants were tasked with the prediction of distribution coefficients to assess its potential as a new route for the evaluation and systematic improvement of predictive physical models. These measurements are typically performed for octanol-water, but we opted to utilize cyclohexane for the nonpolar phase. Cyclohexane was suggested to avoid issues with the high water content and persistent heterogeneous structure of water-saturated octanol phases, since it has greatly reduced water content and a homogeneous liquid structure. Using a modified shake-flask LC-MS/MS protocol, we collected cyclohexane/water distribution coefficients for a set of 53 druglike compounds at pH 7.4. These measurements were used as the basis for the SAMPL5 Distribution Coefficient Challenge, where 18 research groups predicted these measurements before the experimental values reported here were released. In this work, we describe the experimental protocol we utilized for measurement of cyclohexane-water distribution coefficients, report the measured data, propose a new bootstrap-based data analysis procedure to incorporate multiple sources of experimental error, and provide insights to help guide future iterations of this valuable exercise in predictive modeling.

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Notes

  1. Shimadzu Cat. No. 228-45450-91.

  2. DMSO stocks from Genentech compound library.

  3. ACS grade \(\ge\)99 %, Sigma-Aldrich Cat. No 179191-2L, batch #00555ME.

  4. 136 mM NaCl, 2.6 mM KCl, 7.96 mM \(\hbox {Na}_2\hbox {HPO}_4\), 1.46 mM \(\hbox {KH}_2\hbox {PO}_4\), with pH adjusted to 7.4, prepared by the Genentech Media lab.

  5. Thermo Fisher Scientific, Titer Plate Shaker, model: 4625,Waltham, MA, USA.

  6. Agilent Technologies, Vial plate for holding 54 × 2 mL vials part no. G2255-68700.

  7. Eppendorf, Centrifuge 5804, Hamburg, Germany.

  8. 384-well glass coat plate:Thermo Scientific, Microplate, 384-Well; Webseal Plate; Glass-coated Polypropylene; Square well shape; U-Shape well bottom; 384 wells; 90 uL sample volume; Catalog Number: 3252187.

  9. ACROS Organics, 1-octanol 99 % pure, Catalog Number: AC150630010, Geel, Belgium.

  10. Waters Xbridge C18 2.130 mm with 2.5 m particles.

  11. Agilent Cat No 24214-001.

  12. All LC solvents were HPLC-grade and purchased from OmniSolv (Charlotte, NC, USA).

  13. This was done using a Shimadzu NexeraX2 consisting of an LC-30AD(pump), SIL-30AC (auto-injector), and SPD-20AC(UV/VIS detector) with Sciex API4000QTRP (MS).

  14. This was done using a Shimadzu NexeraX2 consisting of an LC-30AD(pump), SIL-30AC (auto-injector), and SPD-20AC(UV/VIS detector) with Sciex API4000 (MS).

  15. For the purpose of the D3R/SAMPL5 workshop, we originally erroneously reported the standard deviation \(\cdot \sqrt{3}\) instead of the standard error \(\cdot \sqrt{3}\). The factor of \(\sqrt{3}\) corrects the sample standard deviation across all MRM measurements for the correlation between the 3 replicate measurements belonging to a single independent experimental repeat.

Abbreviations

SAMPL:

Statistical assessment of the modeling of proteins and ligands

log P:

\(\log _{10}\) partition coefficient

log D:

\(\log _{10}\) distribution coefficient

LC-MS/MS:

Liquid chromatography - tandem mass spectrometry

HPLC:

High-pressure liquid chromatography

MRM:

Multiple reaction monitoring

PTFE:

Polytetrafluoroethylene

DMSO:

Dimethyl sulfoxide

PBS:

Phosphate buffered saline

RPM:

Revolutions per minute

CV:

Coefficient of variation

MAP:

Maximum a posteriori

MCMC:

Markov chain Monte Carlo

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Acknowledgments

The authors acknowledge Christopher Bayly (OpenEye Scientific) and Robert Abel (Schrödinger) for their contributions to discussions on compound selection; Joseph Pease (Genentech) for discussions of the experimental approach and aid in compound selection; Delia Li (Genentech) for her assistance in performing experimental work; Alberto Gobbi (Genentech), Man-Ling Lee (Genentech), and Ignacio Aliagas (Genentech) for helpful feedback on experimental issues; Andreas Klamt (Cosmologic) and Jens Reinisch (Cosmologic) for invigorating discussions regarding experimental data; Patrick Grinaway (MSKCC) for helpful discussions on analysis procedures; and Anthony Nicholls (OpenEye) for originating and supporting earlier iterations of SAMPL challenges.

Funding

This work was performed as part of an internship by ASR sponsored by Genentech, Inc., 1 DNA Way, South San Francisco, CA 94080, United States. JDC acknowledges support from the Sloan Kettering Institute and NIH grant P30 CA008748. DLM appreciates financial support from National Science Foundation (CHE 1352608).

Author information

Author notes

  1. Justin Dancer

    Present address: Theravance Biopharma, South San Francisco, CA, 94080, USA

Authors and Affiliations

  1. Graduate Program in Physiology, Biophysics, and Systems Biology, Weill Cornell Medical College, New York, NY, 10065, USA

    Ariën S. Rustenburg

  2. Computational Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA

    Ariën S. Rustenburg & John D. Chodera

  3. Genentech, Inc., 1 DNA Way, South San Francisco, CA, 94080, USA

    Justin Dancer, Baiwei Lin & Daniel F. Ortwine

  4. Denali Therapeutics, 151 Oyster Point Blvd, 2nd floor, South San Francisco, CA, 94080, USA

    Jianwen A. Feng

  5. Department of Pharmaceutical Sciences and Department of Chemistry, University of California, Irvine, Irvine, CA, 92697, USA

    David L. Mobley

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  1. Ariën S. Rustenburg
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Corresponding author

Correspondence to John D. Chodera.

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Conflict of interest statement

D. L. M. and J. D. C. are members of the Scientific Advisory Board for Schrödinger, LLC.

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Rustenburg, A.S., Dancer, J., Lin, B. et al. Measuring experimental cyclohexane-water distribution coefficients for the SAMPL5 challenge. J Comput Aided Mol Des 30, 945–958 (2016). https://doi.org/10.1007/s10822-016-9971-7

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