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An Accurate Approach for Computational pKa Determination of Phenolic Compounds

Silvia Pezzola, Samuele Tarallo, Alessandro Iannini, Mariano Venanzi, Pierluca Galloni, Valeria Conte, Federica Sabuzi

2022Molecules33 citationsDOIOpen Access PDF

Abstract

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 -NO2 substituents, which are usually excluded from computational pKa studies, enabling easy and reliable pKa determination in a wide range of phenols.

Topics & Concepts

SolvationImplicit solvationQuantitative structure–activity relationshipPhenolsComputational chemistryComputer scienceChemistrySet (abstract data type)Density functional theoryIn silicoMean absolute errorRange (aeronautics)MoleculeBiological systemMachine learningMaterials scienceMathematicsMean squared errorOrganic chemistryStatisticsGeneComposite materialProgramming languageBiochemistryBiologyFree Radicals and AntioxidantsChemistry and Chemical EngineeringComputational Drug Discovery Methods