Computational Study of the pH-Dependent Ionic Environment around β-Lactoglobulin.

Area of Science:

• Biophysics
• Computational Chemistry
• Biochemistry

Background:

• Ions play crucial roles in biological processes, interacting with biomolecules like proteins.
• While ion-nucleic acid interactions are well-studied, ion-protein interactions, especially pH-dependent ones, are gaining research interest.

Purpose of the Study:

• To analyze ion binding and distribution around β-lactoglobulin.
• To compare constant-pH molecular dynamics (CpHMD) simulations with the Poisson-Boltzmann (PB) model and experimental data across a pH range of 3-8.

Main Methods:

• Utilized constant-pH molecular dynamics (CpHMD) simulations to model ion distribution around β-lactoglobulin.
• Compared simulation results with the nonlinear Poisson-Boltzmann (NLPB) model, linear PB (LPB) model, and experimental measurements.
• Analyzed ion concentration maps and protein total charge.

Main Results:

• CpHMD simulations demonstrated good agreement with experimental data and the NLPB model.
• The linear PB model showed theoretical inconsistencies and deviated from simulation results.
• CpHMD accurately predicted pH-dependent ion trends and validated protein charge estimations.

Conclusions:

• CpHMD is a reliable method for studying ion-protein interactions, particularly their pH dependence.
• The nonlinear PB model provides a reasonable approximation, but CpHMD offers more detailed insights.
• Discrepancies between CpHMD and NLPB highlight potential limitations of the PB model at short distances.