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

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Abstract

In this work we have developed a hybrid QM and MM approach to predict pKa of small drug-like molecules in explicit solvent. The gas phase free energy of deprotonation is calculated using the M06-2X density functional theory level with Pople basis sets. The solvation free energy difference of the acid and its conjugate base is calculated at MD level using thermodynamic integration. We applied this method to the 24 drug-like molecules in the SAMPL6 blind pKa prediction challenge. We achieved an overall RMSE of 2.4 pKa units in our prediction. Our results show that further optimization of the protocol needs to be done before this method can be used as an alternative approach to the well established approaches of a full quantum level or empirical pKa prediction methods.

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Acknowledgements

The work is supported by the Intramural Research Program of the National Heart, Lung and Blood Institute Z01 HL001051. The authors would like to acknowledge Xiongwu Wu, Kyungreem Han, Philip Hudson, Michael Jones, Ana Damjanovic, Gerhard Konig, Frank Pickard, Florentina Tofoleanu, Reuben Meanapa for helpful discussion. This work utilized the computational resources of the NIH HPC Biowulf cluster. http://hpc.nih.gov and the Laboratory of Computational Biology cluster. SP would like to acknowledge Biochemistry, Cellular and Molecular Biology (BCMB) graduate program at JHMI.

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  1. Laboratory of Computational Biology, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, 20814, USA

    Samarjeet Prasad, Qiao Zeng & Bernard R. Brooks

  2. Biophysics and Biophysical Chemistry, The Johns Hopkins University, School of Medicine, Baltimore, MD, 21205, USA

    Samarjeet Prasad

  3. School of Life Sciences, Westlake University, 18 Shilongshan Street, Xihu District, Hangzhou, Zhejiang, China

    Jing Huang

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Prasad, S., Huang, J., Zeng, Q. et al. An explicit-solvent hybrid QM and MM approach for predicting pKa of small molecules in SAMPL6 challenge. J Comput Aided Mol Des 32, 1191–1201 (2018). https://doi.org/10.1007/s10822-018-0167-1

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