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Accurately Predicting Protein pKa Values Using Nonequilibrium Alchemy

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de Groot,  Berend L.
Department of Theoretical and Computational Biophysics, Max Planck Institute for Multidisciplinary Sciences, Max Planck Society;
Research Group of Computational Biomolecular Dynamics, Max Planck Institute for Multidisciplinary Sciences, Max Planck Society;

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Gapsys,  Vytautas
Department of Theoretical and Computational Biophysics, Max Planck Institute for Multidisciplinary Sciences, Max Planck Society;
Research Group of Computational Biomolecular Dynamics, Max Planck Institute for Multidisciplinary Sciences, Max Planck Society;

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Citation

Wilson, C., Karttunen, M., de Groot, B. L., & Gapsys, V. (2023). Accurately Predicting Protein pKa Values Using Nonequilibrium Alchemy. Journal of Chemical Theory and Computation, 19(21), 7833-7845. doi:10.1021/acs.jctc.3c00721.


Cite as: https://hdl.handle.net/21.11116/0000-000E-2B5F-9
Abstract
The stability, solubility, and function of a protein depend on both its net charge and the protonation states of its individual residues. pKa is a measure of the tendency for a given residue to (de)protonate at a specific pH. Although pKa values can be resolved experimentally, theory and computation provide a compelling alternative. To this end, we assess the applicability of a nonequilibrium (NEQ) alchemical free energy method to the problem of pKa prediction. On a data set of 144 residues that span 13 proteins, we report an average unsigned error of 0.77 ± 0.09, 0.69 ± 0.09, and 0.52 ± 0.04 pK for aspartate, glutamate, and lysine, respectively. This is comparable to current state-of-the-art predictors and the accuracy recently reached using free energy perturbation methods (e.g., FEP+). Moreover, we demonstrate that our open-source, pmx-based approach can accurately resolve the pKa values of coupled residues and observe a substantial performance disparity associated with the lysine partial charges in Amber14SB/Amber99SB*-ILDN, for which an underused fix already exists.