Exploiting Configurational Freezing in Nonequilibrium Monte Carlo Simulations.

Area of Science:

• Computational Chemistry
• Statistical Mechanics
• Biophysics

Background:

• Accurate free energy estimates using Jarzynski equality or Crooks fluctuation theorem require numerous trajectories due to dissipated work.
• Inefficient path-ensemble averages in nonequilibrium simulations increase computational cost.

Purpose of the Study:

• To propose a computational technique to improve free energy estimates by reducing dissipated work in Monte Carlo simulations.
• To introduce the 'configurational freezing' method inspired by dynamical freezing in molecular dynamics.

Main Methods:

• Configurational freezing limits sampling to the region of interest, freezing other particles.
• Assumes dissipation is a local phenomenon in single-molecule nonequilibrium processes.
• Reduces computational cost by focusing on the reaction site rather than the entire system.

Main Results:

• The method significantly lowers dissipated work, improving free energy estimation accuracy.
• Computational cost is decoupled from system size, depending only on the reaction site.
• Demonstrated effectiveness in calculating relative hydration free energy and potential of mean force for methane in water.

Conclusions:

• Configurational freezing offers a more efficient approach for free energy calculations in various nonequilibrium processes.
• The method is applicable to biopolymer folding, molecular docking, and alchemical transformations.
• Provides a computationally tractable alternative for complex molecular simulations.