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PeerJ (San Francisco, CA), 2016-08, Vol.4, p.e2335-e2335, Article e2335
2016
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Autor(en) / Beteiligte
Titel
Prediction of pKa values using the PM6 semiempirical method
Ist Teil von
  • PeerJ (San Francisco, CA), 2016-08, Vol.4, p.e2335-e2335, Article e2335
Ort / Verlag
United States: PeerJ, Inc
Erscheinungsjahr
2016
Quelle
EZB Electronic Journals Library
Beschreibungen/Notizen
  • 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.
Sprache
Englisch
Identifikatoren
ISSN: 2167-8359
eISSN: 2167-8359
DOI: 10.7717/peerj.2335
Titel-ID: cdi_doaj_primary_oai_doaj_org_article_12434cc5c1db43a8a8430d5df4621c12

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