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High accuracy quantum-chemistry-based calculation and blind prediction of macroscopic pKa values in the context of the SAMPL6 challenge

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Abstract

Recent advances in the development of low-cost quantum chemical methods have made the prediction of conformational preferences and physicochemical properties of medium-sized drug-like molecules routinely feasible, with significant potential to advance drug discovery. In the context of the SAMPL6 challenge, macroscopic pKa values were blindly predicted for a set of 24 of such molecules. In this paper we present two similar quantum chemical based approaches based on the high accuracy calculation of standard reaction free energies and the subsequent determination of those pKa values via a linear free energy relationship. Both approaches use extensive conformational sampling and apply hybrid and double-hybrid density functional theory with continuum solvation to calculate free energies. The blindly calculated macroscopic pKa values were in excellent agreement with the experiment.

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Acknowledgements

We thank Wolfgang Zipfel and the NIBR NX Scientific Computing team for generous allocation of and help with HPC resources. We thank Jens Reinisch, Uwe Huniar, Michael Diedenhofen and the whole COSMOlogic team for helpful discussions. This work was supported by the German Research Foundation (DFG) through a Leibniz prize to S.G.

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Authors and Affiliations

  1. Mulliken Center for Theoretical Chemistry, Institute of Physical and Theoretical Chemistry, University of Bonn, Beringstr. 4, 53115, Bonn, Germany

    Philipp Pracht & Stefan Grimme

  2. Novartis Institutes for Biomedical Research, 4002, Basel, Switzerland

    Rainer Wilcken & Stephane Rodde

  3. Novartis Pharma AG, Technical Research and Development, 4002, Basel, Switzerland

    Anikó Udvarhelyi

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  1. Philipp Pracht
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  2. Rainer Wilcken
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  3. Anikó Udvarhelyi
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  4. Stephane Rodde
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  5. Stefan Grimme
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Correspondence to Rainer Wilcken or Stefan Grimme.

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Pracht, P., Wilcken, R., Udvarhelyi, A. et al. High accuracy quantum-chemistry-based calculation and blind prediction of macroscopic pKa values in the context of the SAMPL6 challenge. J Comput Aided Mol Des 32, 1139–1149 (2018). https://doi.org/10.1007/s10822-018-0145-7

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