Measuring experimental cyclohexane-water distribution coefficients for the SAMPL5 challenge

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 drug like 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.

Blind prediction of cyclohexane–water distribution coefficients from the SAMPL5 challenge

“…The two phases for the distribution coefficients were cyclohexane and an aqueous buffer, however, DMSO and acetonitrile were used in the experiments [8] as well. While DMSO and acetonitrile were at very low concentrations, their presence in either solvent layer may affect how a solute distributes between phases.…”

“…Therefore, we investigated the how acetonitrile and DMSO would distribute in simulations. The experimental concentrations reported for each solvent are approximately 50%, 50%, 1%, and 0.4% by volume for cyclohexane, water, DMSO, and acetonitrile respectively [8]. To explore how the DMSO and acetonitrile distribute between cyclohexane and water we performed a single simulation with 130 cyclohexane, 780 water, four DMSO, and two acetonitrile molecules mirroring those concentrations.…”

“…But this type of data is extremely valuable — the past SAMPL challenges have driven real improvements in a variety of methods for calculating hydration free energies [1] — so we sought to include a similar physical property in SAMPL5. The organizers of SAMPL5 settled on cyclohexane-water distribution coefficients, and thanks to a partnership with Genentech, this led to a series of measurements on drug-like compounds, discussed in detail in this issue [8]. The experimental measurements are also straightforward enough that future distribution coefficient challenges can be deliberately designed to focus on issues that merit attention to move the field forward.…”

pKa measurements for the SAMPL6 prediction challenge for a set of kinase inhibitor-like fragments

“…As part of the SAMPL5 challenge series, a new cyclohexane-water distribution constant (log D) prediction challenge was introduced, where participants predicted the transfer free energy of small drug-like molecules between an aqueous buffer phase at pH 7.4 and a nonaqueous cyclohexane phase [16,17]. While octanol-water distribution coefficient measurements are more common, cyclohexane was selected for the simplicity of its liquid phase and relative dryness compared to wet octanol phases.…”

An explicit-solvent hybrid QM and MM approach for predicting pKa of small molecules in SAMPL6 challenge

“…Previous iterations of the SAMPL competitions have focussed on assessing methods for solvation free energy calculations [33], distribution coefficient and other challenges. [34, 35, 36, 37] We note that in the SAMPL5 distribution coefficient competition, Pickard and coworkers have calculated pKa values with QM methods, and used computed pKa to further correct their prediction of distribution coefficients [34]. …”