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Prediction of pKa values using the PM6 semiempirical method

The PM6 semiempirical method and the dispersion and hydrogen bond-corrected PM6-D3H+ method are used together with the SMD and COSMO continuum solvation models to predict pKa values of pyridines, alcohols, phenols, benzoic acids, carboxylic acids, and phenols using isodesmic reactions and compared t...

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Detalles Bibliográficos
Autores principales: Kromann, Jimmy C., Larsen, Frej, Moustafa, Hadeel, Jensen, Jan H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4991863/
https://www.ncbi.nlm.nih.gov/pubmed/27602298
http://dx.doi.org/10.7717/peerj.2335
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author Kromann, Jimmy C.
Larsen, Frej
Moustafa, Hadeel
Jensen, Jan H.
author_facet Kromann, Jimmy C.
Larsen, Frej
Moustafa, Hadeel
Jensen, Jan H.
author_sort Kromann, Jimmy C.
collection PubMed
description The PM6 semiempirical method and the dispersion and hydrogen bond-corrected PM6-D3H+ method are used together with the SMD and COSMO continuum solvation models to predict pKa values of pyridines, alcohols, phenols, benzoic acids, carboxylic acids, and phenols using isodesmic reactions and compared to published ab initio results. The pKa values of pyridines, alcohols, phenols, and benzoic acids considered in this study can generally be predicted with PM6 and ab initio methods to within the same overall accuracy, with average mean absolute differences (MADs) of 0.6–0.7 pH units. For carboxylic acids, the accuracy (0.7–1.0 pH units) is also comparable to ab initio results if a single outlier is removed. For primary, secondary, and tertiary amines the accuracy is, respectively, similar (0.5–0.6), slightly worse (0.5–1.0), and worse (1.0–2.5), provided that di- and tri-ethylamine are used as reference molecules for secondary and tertiary amines. When applied to a drug-like molecule where an empirical pKa predictor exhibits a large (4.9 pH unit) error, we find that the errors for PM6-based predictions are roughly the same in magnitude but opposite in sign. As a result, most of the PM6-based methods predict the correct protonation state at physiological pH, while the empirical predictor does not. The computational cost is around 2–5 min per conformer per core processor, making PM6-based pKa prediction computationally efficient enough to be used for high-throughput screening using on the order of 100 core processors.
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spelling pubmed-49918632016-09-06 Prediction of pKa values using the PM6 semiempirical method Kromann, Jimmy C. Larsen, Frej Moustafa, Hadeel Jensen, Jan H. PeerJ Biophysics The PM6 semiempirical method and the dispersion and hydrogen bond-corrected PM6-D3H+ method are used together with the SMD and COSMO continuum solvation models to predict pKa values of pyridines, alcohols, phenols, benzoic acids, carboxylic acids, and phenols using isodesmic reactions and compared to published ab initio results. The pKa values of pyridines, alcohols, phenols, and benzoic acids considered in this study can generally be predicted with PM6 and ab initio methods to within the same overall accuracy, with average mean absolute differences (MADs) of 0.6–0.7 pH units. For carboxylic acids, the accuracy (0.7–1.0 pH units) is also comparable to ab initio results if a single outlier is removed. For primary, secondary, and tertiary amines the accuracy is, respectively, similar (0.5–0.6), slightly worse (0.5–1.0), and worse (1.0–2.5), provided that di- and tri-ethylamine are used as reference molecules for secondary and tertiary amines. When applied to a drug-like molecule where an empirical pKa predictor exhibits a large (4.9 pH unit) error, we find that the errors for PM6-based predictions are roughly the same in magnitude but opposite in sign. As a result, most of the PM6-based methods predict the correct protonation state at physiological pH, while the empirical predictor does not. The computational cost is around 2–5 min per conformer per core processor, making PM6-based pKa prediction computationally efficient enough to be used for high-throughput screening using on the order of 100 core processors. PeerJ Inc. 2016-08-11 /pmc/articles/PMC4991863/ /pubmed/27602298 http://dx.doi.org/10.7717/peerj.2335 Text en © 2016 Kromann et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Biophysics
Kromann, Jimmy C.
Larsen, Frej
Moustafa, Hadeel
Jensen, Jan H.
Prediction of pKa values using the PM6 semiempirical method
title Prediction of pKa values using the PM6 semiempirical method
title_full Prediction of pKa values using the PM6 semiempirical method
title_fullStr Prediction of pKa values using the PM6 semiempirical method
title_full_unstemmed Prediction of pKa values using the PM6 semiempirical method
title_short Prediction of pKa values using the PM6 semiempirical method
title_sort prediction of pka values using the pm6 semiempirical method
topic Biophysics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4991863/
https://www.ncbi.nlm.nih.gov/pubmed/27602298
http://dx.doi.org/10.7717/peerj.2335
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