Multiple pH regime molecular dynamics simulation for pK calculations.

Area of Science:

• Computational Biology
• Protein Biophysics
• Molecular Dynamics

Background:

• Protein ionization equilibria are crucial for function but challenging to model.
• Standard molecular dynamics (MD) simulations suffer from fixed protonation state bias.
• This bias leads to inaccurate conformational sampling and pK predictions, especially at extrapolated pH values.

Purpose of the Study:

• To develop a simple yet effective method to reduce bias in MD simulations of protein ionization.
• To improve the accuracy of predicting protein pK values across a wide pH range.
• To validate a novel multiple pH molecular dynamics approach using experimental data.

Main Methods:

• Generated three sets of MD structures, each with a different, pH-relevant protonation state for the protein.
• Calculated pK values from each structure set.
• Combined pK predictions from the multiple sets to cover the entire pH range of interest.

Main Results:

• The multiple pH MD approach was successfully tested on the GCN4 leucine zipper.
• Predicted pK values showed a mean deviation of 0.29 pH units from experimental data.
• Achieved a precision of 0.13 pH units for pK predictions at equivalent sites.

Conclusions:

• The multiple pH molecular dynamics method effectively mitigates fixed protonation state bias in simulations.
• This approach provides accurate and precise pK predictions for proteins over broad pH ranges.
• The findings offer a significant improvement for computational studies of protein ionization and function.