Computational estimation of the acidities of purines and indoles

Purines and related compounds are central ingredients in the genetic code and form the structural framework for many drugs and other bioactive compounds. A key feature of these compounds is their acidity, as expressed by their pK_a values. For a proper understanding of the behaviors of these compounds, it is important to have a theoretical means for estimating their acidities. Here we present a quantum-chemical quantitative structure-activity relationship (QSAR) study of these compounds aimed at estimating the aqueous pK_a values of purines and related compounds based on the energy differences in solution ΔE(H₂O) between the parent compounds and their dissociation products. This method was applied to both the cation → neutral (pK_a1) and neutral → anion (pK_a2) dissociations of the compounds. Computations were performed using density functional theory at the B3LYP/6-31 + G** level with the SM8 aqueous solvent model. Good-quality QSAR regression equations were obtained for both dissociations using the ΔE(H₂O) descriptor. These equations were applied to estimate missing pK_a values for compounds in this category, and should also be applicable to the acidities of other related heterocyclic compounds.