Evaluation of Acidity Constants of Anthraquinone Derivatives in Methanol/Water Mixtures Using Real Quantum Descriptors

This work presents an evaluation of the acidity constants of 1-hydroxy-9,10-anthraquinone derivatives using electronic descriptors in four methanol/water mixtures with different volume percents and in isolation. An Onsager reaction field model was applied for charges, orbital energies, and dipole descriptors of solutes in the four different solvent mixtures with different volume percents. Each solute was placed in a cavity surrounded by a continuous dielectric constant medium, and the quantum chemical descriptors of the solute were calculated. Electrostatic potential energy descriptors of the isolated solutes were obtained using density functional theory. Relevant descriptors affecting the acidities of the anthraquinones were selected using a genetic algorithm (GA) method. Contributions of the selected variables to the prediction of the experimental acidity constant values were determined by applying a multi-layer perceptron-based feedforward artificial neural network (ANN). A proper model, reproducing experimental acidity constants within average absolute errors of less than 1.10% was achieved. The model proposed relatively higher contributions of dipoles (insolvent) and electrostatic potentials (in isolation) than the orbital energies, revealing the role of strong dipole–dipole interactions such as hydrogen bonds as well as halogen bonds in the proton dissociation process. The gaps between the HOMO and LUMO energies were found to contribute to the stabilization of anions leading to higher dissociation constants.