Abstract
Developing accurate quantum chemical approaches for calculating pKas is of broad interest. Useful accuracy can be obtained by using density functional theory (DFT) in combination with a polarizable continuum solvent model. However, some classes of molecules present problems for this approach, yielding errors greater than 5 pK units. Various methods have been developed to improve the accuracy of the combined strategy. These methods perform well but either do not generalize or introduce additional degrees of freedom, increasing the computational cost. The Solvation Model based on Density (SMD) has emerged as one of the most commonly used continuum solvent models. Nevertheless, for some classes of organic compounds, e.g., thiols, the pKas calculated with the original SMD model show errors of 6-10 pK units, and we traced these errors to inaccuracies in the solvation free energies of the anions. To improve the accuracy of pKas calculated with DFT and the SMD model, we developed a scaled solvent-accessible surface approach for constructing the solute-solvent boundary. By using a "direct" approach, in which all quantities are computed in the presence of the continuum solvent, the use of thermodynamic cycles is avoided. Furthermore, no explicit water molecules are required. Three benchmark data sets of experimentally measured pKa values, including 28 carboxylic acids, 10 aliphatic amines, and 45 thiols, were used to assess the optimized SMD model, which we call SMD with a scaled solvent-accessible surface (SMDsSAS). Of the methods tested, the M06-2X density functional approximation, 6-31+G(d,p) basis set, and SMDsSAS solvent model provided the most accurate pKas for each set, yielding mean unsigned errors of 0.9, 0.4, and 0.5 pK units, respectively, for carboxylic acids, aliphatic amines, and thiols. This approach is therefore useful for efficiently calculating the pKas of environmentally relevant functional groups.
Original language | English |
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Pages (from-to) | 4366-4374 |
Number of pages | 9 |
Journal | Journal of Physical Chemistry A |
Volume | 122 |
Issue number | 17 |
DOIs | |
State | Published - May 3 2018 |
Funding
This work was supported by the U.S. Department of Energy (DOE), Office of Science, Office of Biological and Environmental Research, Subsurface Biogeochemical Research Program through award DE-SC0016478 and through the Mercury Science Focus Area Program (SFA) at Oak Ridge National Laboratory (ORNL). ORNL is managed by UT-Battelle, LLC for the U.S. DOE under contract DE-AC05-00OR22725. This research used resources of the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the U.S. Department of Energy.