A reliable and efficient first principles-based method for predicting pK(a) values. 1. Methodology.

Area of Science:

• Computational Chemistry
• Physical Chemistry

Background:

• Accurate prediction of acid-base dissociation constants (pK(a)) is crucial in chemistry.
• Density Functional Theory (DFT) offers a computationally feasible approach for such calculations.
• Existing DFT protocols for pK(a) determination can be computationally intensive or lack broad applicability.

Purpose of the Study:

• To develop an efficient and reliable protocol for calculating pK(a) values in aqueous solution using DFT.
• To identify the optimal computational parameters balancing accuracy and efficiency.

Main Methods:

• Developed a linear regression model correlating calculated deprotonation energies with experimental pK(a) values.
• Systematically evaluated various DFT levels of theory, including basis sets, exchange-correlation functionals, and solvation models.
• Utilized the COSMO solvation model and tested different geometry optimization levels.

Main Results:

• A modest basis set (6-311+G**) is sufficient for energy difference calculations, while a smaller basis set (3-21G*) suffices for geometry optimization.
• Consistent use of a solvation model (COSMO) is essential for reliable pK(a) predictions.
• The choice of exchange-correlation functional has a minor impact; pure DFT functionals are adequate.

Conclusions:

• The established protocol provides an efficient and accurate method for calculating pK(a) values.
• The protocol simplifies complex factors by absorbing them into fitting constants.
• This method is suitable for application to large datasets of molecules.