Accurately Predicting Protein pK_a Values Using Nonequilibrium Alchemy.

Area of Science:

• Computational chemistry
• Biophysics
• Protein science

Background:

• Protein stability, solubility, and function are influenced by residue net charge and protonation states.
• pKa values quantify residue protonation tendency at specific pH, crucial for protein behavior.
• Experimental pKa determination is possible, but theoretical and computational methods offer alternatives.

Purpose of the Study:

• To evaluate a nonequilibrium (NEQ) alchemical free energy method for predicting protein residue pKa values.
• To assess the accuracy and applicability of this computational approach across diverse protein systems.

Main Methods:

• Utilized a nonequilibrium (NEQ) alchemical free energy method for pKa prediction.
• Applied the method to a dataset of 144 residues across 13 different proteins.
• Employed an open-source, pmx-based computational framework.

Main Results:

• Achieved average unsigned errors of 0.77 ± 0.09, 0.69 ± 0.09, and 0.52 ± 0.04 pK for aspartate, glutamate, and lysine, respectively.
• Demonstrated accuracy comparable to state-of-the-art predictors and free energy perturbation methods.
• Successfully resolved pKa values for coupled residues and identified charge model performance issues.

Conclusions:

• The NEQ alchemical free energy method provides an accurate and reliable computational approach for pKa prediction.
• This open-source tool can aid in understanding protein properties and potentially guide protein design.
• Identified specific areas for improvement in existing protein force fields, particularly for lysine residues.