An Accurate Approach for Computational pKa Determination of Phenolic Compounds

Computational chemistry is a valuable tool, as it allows for in silico prediction of key parameters of novel compounds, such as pKa. In the framework of computational pKa determination, the literature offers several approaches based on different level of theories, functionals and continuum solvation...

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Bibliographic Details
Published in:	Molecules (Basel, Switzerland) Vol. 27; no. 23; p. 8590
Main Authors:	Pezzola, Silvia, Tarallo, Samuele, Iannini, Alessandro, Venanzi, Mariano, Galloni, Pierluca, Conte, Valeria, Sabuzi, Federica
Format:	Journal Article
Language:	English
Published:	Switzerland MDPI AG 01-12-2022 MDPI
Subjects:	Acids Computational chemistry computational pKa Computer applications Density Functional Theory DFT direct approach Drug resistance in microorganisms Energy Equilibrium Essences and essential oils industry Hydrogen bonds Mathematical models Nitrogen dioxide phenol Phenolic compounds Phenols Phenols - chemistry pKa Solvation Solvents Thermodynamics thymol Water - chemistry thymol DFT computational pKa pKa direct approach phenol solvation model based on density (SMD) CAM-B3LYP
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Summary:	Computational chemistry is a valuable tool, as it allows for in silico prediction of key parameters of novel compounds, such as pKa. In the framework of computational pKa determination, the literature offers several approaches based on different level of theories, functionals and continuum solvation models. However, correction factors are often used to provide reliable models that adequately predict pKa. In this work, an accurate protocol based on a direct approach is proposed for computing phenols pKa. Importantly, this methodology does not require the use of correction factors or mathematical fitting, making it highly practical, easy to use and fast. Above all, DFT calculations performed in the presence two explicit water molecules using CAM-B3LYP functional with 6-311G+dp basis set and a solvation model based on density (SMD) led to accurate pKa values. In particular, calculations performed on a series of 13 differently substituted phenols provided reliable results, with a mean absolute error of 0.3. Furthermore, the model achieves accurate results with -CN and -NO substituents, which are usually excluded from computational pKa studies, enabling easy and reliable pKa determination in a wide range of phenols.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ISSN:	1420-3049 1420-3049
DOI:	10.3390/molecules27238590