Coupling density functional theory to polarizable force fields for efficient and accurate Hamiltonian molecular...

Area of Science:

• Computational Chemistry
• Molecular Dynamics Simulations
• Quantum Chemistry

Background:

• Hybrid molecular dynamics (MD) simulations combining quantum mechanics (QM) and molecular mechanics (MM) are computationally demanding.
• Accurate treatment of the QM/MM interface and long-range electrostatics is crucial for reliable simulations.
• Existing methods face challenges in energy conservation and preventing artificial electron density distortions.

Purpose of the Study:

• To develop and implement a Hamiltonian density functional theory/(polarizable) molecular mechanics (DFT/(P)MM) approach for hybrid MD simulations.
• To ensure energy conservation, accurate electron density representation, and linear-scaling computational cost for long-range electrostatics.
• To validate the new implementation through simulations of small molecular systems.

Main Methods:

• A Hamiltonian DFT/(P)MM implementation is described, incorporating inducible atomic dipoles within a joint DFT/PMM self-consistency iteration.
• Long-range electrostatics are handled using hierarchically nested fast multipole expansions and a reaction field approach for linear scaling.
• Short-range over-polarization artifacts are mitigated using Gaussian inducible dipoles and Gaussian partial charges near the DFT region.

Main Results:

• The implementation demonstrates Hamiltonian character, stability, and efficiency in hybrid DFT/PMM-MD simulations.
• Simulations of a water dimer and bulk water treated with DFT and PMM show the method's capability.
• The approach successfully addresses energy conservation and electrostatic interaction challenges in hybrid simulations.

Conclusions:

• The developed Hamiltonian DFT/(P)MM method provides a robust and efficient framework for hybrid molecular dynamics simulations.
• This implementation accurately captures the interplay between QM and MM regions, crucial for studying complex molecular systems.
• The method offers a significant advancement in computational chemistry for simulating chemical processes in condensed phases.