Prediction of pKa values using the PM6 semiempirical method.

Jimmy C Kromann,Hadeel Moustafa,Jan H Jensen,Frej Larsen

doi:10.7717/peerj.2335

Abstract

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.

Highlights

A large proportion of organic molecules relevant to medicine and biotechnology contain one or more ionizable groups, which means that fundamental physical and chemical properties, such as the charge of the molecule, depend on the pH of the solution via the corresponding pKa values of the molecules
The data shows that all three ab initio methods perform roughly well, with all three methods giving a mean absolute differences (MADs) below 1 pH unit, with the exception of alcohols where the MAD ranges from 1.0–1.3 pH units
The pKa values of the 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 MADs for these four functional groups are 0.7–0.8 and 0.6–0.7 pH units, for the ab initio and PM6-based predictions

Summary

Introduction

A large proportion of organic molecules relevant to medicine and biotechnology contain one or more ionizable groups, which means that fundamental physical and chemical properties, such as the charge of the molecule, depend on the pH of the solution via the corresponding pKa values of the molecules. There are several empirical pKa prediction tools, such as ACD pKa DB (ACDLabs, Toronto, Canada), Chemaxon (Chemaxon, Budapest, Hungary), and Epik (Schordinger, New York, USA), that offer predictions in less than a second and can be used by nonexperts. These methods are generally quite accurate but can fail for classes of molecules that are not found in the underlying databases. Settimo, Bellman & Knegtel (2013) have recently shown that the empirical methods are prone to failure for amines, How to cite this article Kromann et al (2016), Prediction of pKa values using the PM6 semiempirical method. The user is generally not able to augment the databases for cases where the empirical methods are found to fail

Methods

Results

Conclusion