The "Hot-Solvent/Cold-Solute" Problem Revisited.

Area of Science:

• Computational chemistry and biophysics
• Molecular dynamics simulations
• Macromolecular conformational dynamics

Background:

• Temperature significantly influences macromolecule equilibrium and nonequilibrium dynamics in solution.
• Accurate molecular dynamics (MD) simulations require effective temperature control strategies to sample experimental ensembles.
• Existing thermostats can interfere with natural molecular dynamics and create temperature gradients in inhomogeneous systems.

Purpose of the Study:

• To develop a temperature control strategy for MD simulations that minimizes perturbation to macromolecule dynamics.
• To ensure homogeneous temperature distribution and correct statistical ensemble sampling for solute molecules.
• To address the 'hot solvent/cold solute' problem caused by separate solute-solvent thermostatting.

Main Methods:

• Proposed a novel temperature control strategy leveraging the explicit solvent environment as a thermostat.
• The strategy aims to mimic the natural temperature fluctuations of the solute.
• Evaluated the impact on temperature homogeneity, statistical ensemble accuracy, and dynamics perturbation.

Main Results:

• The proposed method achieves a homogeneous temperature distribution across the solute-solvent system.
• It ensures the correct statistical ensemble for the solute molecule is sampled.
• The strategy minimally perturbs the inherent conformational dynamics of the macromolecule.

Conclusions:

• Explicit solvent can serve as an ideal thermostat, providing realistic temperature fluctuations.
• The novel temperature control strategy effectively balances accurate ensemble sampling with minimal dynamic perturbation.
• This approach offers a more reliable method for simulating macromolecule dynamics in solution.