Constant-pH Simulations with the Polarizable Atomic Multipole AMOEBA Force Field.

Area of Science:

• Biomolecular simulations
• Computational chemistry
• Structural biology

Background:

• Predicting protein behavior across pH is crucial but challenging for simulations.
• Existing constant-pH molecular dynamics (CpHMD) methods are restricted to fixed-charge force fields.
• This limits their application to systems with polarizable force fields like AMOEBA.

Purpose of the Study:

• To develop the first polarizable CpHMD algorithm using the AMOEBA force field.
• To implement this algorithm within the open-source Force Field X (FFX) software.
• To enable accurate titration state predictions for crystalline biomolecular systems.

Main Methods:

• Developed a novel polarizable CpHMD algorithm integrated with the AMOEBA force field.
• Implemented the algorithm in the Force Field X (FFX) software, supporting all 230 space groups.
• Evaluated the method on 11 crystalline peptide systems containing titratable amino acids (Asp, Glu, His, Lys, Cys).

Main Results:

• Successfully predicted titration states for 15 out of 16 amino acids across 11 systems.
• Accurately modeled cysteine coordination with Zn2+ ions.
• Observed a minor discrepancy for a histidine residue in a peptide system, where simulations predicted equally populated tautomers.

Conclusions:

• Polarizable CpHMD with AMOEBA shows significant promise for pKa prediction and studying biochemical mechanisms.
• The developed method enhances accuracy for protein-ligand binding affinity in pharmaceutical lead optimization.
• This work expands the capabilities of biomolecular simulations for complex biological systems.