Using Atomic Charges to Describe the pKa of Carboxylic Acids.

In this study, we present an accurate protocol for the fast prediction of pKa's of carboxylic acids based on the linear relationship between computed atomic charges of the anionic form of the carboxylate fragment and their experimental pKa values. Five charge descriptors, three charge models, three solvent models, gas-phase calculations, several DFT methods (a combination of eight DFT functionals and fifteen basis sets), and four different semiempirical approaches were tested. Among those, the best combination to reproduce experimental pKa's is to compute the natural population analysis atomic charge using the solvation model based on density model at the M06L/6-311G(d,p) level of theory and selecting the maximum atomic charge on the carboxylic oxygen atoms (R2 = 0.955). The applicability of the suggested protocol and its stability along geometrical changes are verified by molecular dynamics simulations performed for a set of aspartate, glutamate, and alanine peptides. By reporting the calculated atomic charge of the carboxylate form into the linear relationship derived in this work, it should be possible to accurately estimate the amino acid's pKa's in a protein environment.