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Assessment of Methodology and Chemical Group Dependences in the Calculation of the pKa for Several Chemical Groups

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† Department of Chemistry, Graduate School of Pure and Applied Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8577, Japan
‡ Center for Computational Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8577, Japan
*E-mail: [email protected]. Fax: +81-29-853-7392.
Cite this: J. Chem. Theory Comput. 2017, 13, 10, 4791–4803
Publication Date (Web):September 1, 2017
https://doi.org/10.1021/acs.jctc.7b00587
Copyright © 2017 American Chemical Society
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Abstract

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We have investigated the dependencies of various computational methods in the calculation of acid dissociation constants (pKa values) of certain chemical groups found in protonatable amino acids based on our previous scheme [Matsui; Phys. Chem. Chem. Phys. 2012, 14, 4181−4187]. By changing the quantum chemical (QC) method (Hartree–Fock (HF) and perturbation theory, and composite methods, or exchange–correlation functionals in density functional theory (DFT)), basis sets, solvation models, and the cavities used in the solvent models, we have exhaustively tested about 2,200 combinations to find the best combination for pKa estimation among them. Of the tested parameters, the choice of the basis set and cavity is the most crucial to reproduce experimental values compared to other factors. Concerning the basis set, the inclusion of diffuse functions is quite important for carboxyl, thiol, and phenol groups judging from the mean absolute errors (MAEs) measured from the experimental values. Of the cavity models, between the Pauling, Klamt, and the universal force field (UFF) definitions, the UFF defined cavity is the best choice, resulting in the smallest MAEs. Concerning the QC methods, hybrid DFTs and range-separated DFTs always provide better results than pure DFTs and HF. As a result, we found that LC-ϖPBE/6-31+G(d) with PCM-SMD/UFF provides the best pKa estimation with a MAE within 0.15 pKa units.

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The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.jctc.7b00587.

  • Detailed data of the experimental data for pKa values and all calculated results (2,214 combinations of computational methods) (PDF)

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Cited By

This article is cited by 15 publications.

  1. Yuri B. Vysotsky, Elena S. Kartashynska, Dieter Vollhardt, Valentin B. Fainerman. Surface pKa of Saturated Carboxylic Acids at the Air/Water Interface: A Quantum Chemical Approach. The Journal of Physical Chemistry C 2020, 124 (25) , 13809-13818. https://doi.org/10.1021/acs.jpcc.0c03785
  2. Saber Mirzaei, Maxim V. Ivanov, Qadir K. Timerghazin. Improving Performance of the SMD Solvation Model: Bondi Radii Improve Predicted Aqueous Solvation Free Energies of Ions and pKa Values of Thiols. The Journal of Physical Chemistry A 2019, 123 (44) , 9498-9504. https://doi.org/10.1021/acs.jpca.9b02340
  3. Nicolae C. Iovanac, Brett M. Savoie. Improved Chemical Prediction from Scarce Data Sets via Latent Space Enrichment. The Journal of Physical Chemistry A 2019, 123 (19) , 4295-4302. https://doi.org/10.1021/acs.jpca.9b01398
  4. Toru Matsui, Kanako Yamamoto, Takehiro Fujita, Kenji Morihashi. Molecular Dynamics and Quantum Chemical Approach for the Estimation of an Intramolecular Hydrogen Bond Strength in Okadaic Acid. The Journal of Physical Chemistry B 2018, 122 (29) , 7233-7242. https://doi.org/10.1021/acs.jpcb.8b03272
  5. Peng Lian, Ryne C. Johnston, Jerry M. Parks, Jeremy C. Smith. Quantum Chemical Calculation of pKas of Environmentally Relevant Functional Groups: Carboxylic Acids, Amines, and Thiols in Aqueous Solution. The Journal of Physical Chemistry A 2018, 122 (17) , 4366-4374. https://doi.org/10.1021/acs.jpca.8b01751
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  8. Anita Bosak, Dejan M. Opsenica, Goran Šinko, Matija Zlatar, Zrinka Kovarik. Structural aspects of 4-aminoquinolines as reversible inhibitors of human acetylcholinesterase and butyrylcholinesterase. Chemico-Biological Interactions 2019, 308 , 101-109. https://doi.org/10.1016/j.cbi.2019.05.024
  9. Niraj Verma, Yunwen Tao, Bruna Luana Marcial, Elfi Kraka. Correlation between molecular acidity (pKa) and vibrational spectroscopy. Journal of Molecular Modeling 2019, 25 (2) https://doi.org/10.1007/s00894-019-3928-4
  10. Pirom Chenprakhon, Thanyaporn Wongnate, Pimchai Chaiyen. Monooxygenation of aromatic compounds by flavin-dependent monooxygenases. Protein Science 2019, 28 (1) , 8-29. https://doi.org/10.1002/pro.3525
  11. Miroslav M. Ristić, Milena Petković, Branislav Milovanović, Jelena Belić, Mihajlo Etinski. New hybrid cluster-continuum model for pKa values calculations: Case study of neurotransmitters’ amino group acidity. Chemical Physics 2019, 516 , 55-62. https://doi.org/10.1016/j.chemphys.2018.08.022
  12. Ryo Fujiki, Yukako Kasai, Yuki Seno, Toru Matsui, Yasuteru Shigeta, Norio Yoshida, Haruyuki Nakano. A computational scheme of p K a values based on the three-dimensional reference interaction site model self-consistent field theory coupled with the linear fitting correction scheme. Physical Chemistry Chemical Physics 2018, 20 (43) , 27272-27279. https://doi.org/10.1039/C8CP04354J
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