Polarizable Atomic Multipole Solutes in a Generalized Kirkwood Continuum

Area of Science:

• Computational chemistry
• Molecular modeling
• Biophysics

Background:

• Continuum electrostatics models approximate solvation free energy for molecular systems.
• The generalized Born (GB) model is a common analytic approximation but is limited to monopole charge distributions.
• Accurate solvation energy prediction is crucial for understanding molecular interactions and dynamics.

Purpose of the Study:

• To introduce a novel generalized Kirkwood (GK) continuum electrostatics model.
• To extend electrostatic calculations beyond monopoles by incorporating arbitrary atomic multipole moments.
• To enable efficient and accurate solvation energy calculations for biomolecular systems using the AMOEBA force field.

Main Methods:

• Developed the generalized Kirkwood (GK) model based on Kirkwood's analytic solution for electrostatic solvation free energy.
• Applied the GK model with the Atomic Multipole Optimized Energetics for Biomolecular Applications (AMOEBA) force field, including permanent and induced atomic multipoles.
• Derived the GK gradient for energy minimization and molecular dynamics simulations.
• Compared GK solvation free energies and reaction fields against the Polarizable Multipole Poisson-Boltzmann (PMPB) model for 55 proteins.

Main Results:

• The GK model achieved a mean unsigned relative difference of 0.9% compared to the PMPB model for electrostatic solvation free energies.
• GK model's prediction of the total solvated dipole moment showed a mean unsigned relative difference of 2.7% compared to PMPB.
• GK calculations are approximately 3 times slower than vacuum AMOEBA, making them suitable for large-scale simulations.

Conclusions:

• The generalized Kirkwood (GK) model provides an accurate and computationally feasible method for continuum electrostatics in biomolecular simulations.
• GK effectively handles complex solute charge distributions using atomic multipole moments.
• This model represents a significant advancement for predicting solvation effects in molecular modeling and dynamics.