Enhanced Jarzynski free energy calculations using weighted ensemble.

Area of Science:

• Computational chemistry
• Thermodynamics
• Molecular dynamics

Background:

• Binding free energy calculations are crucial for drug design.
• Existing methods face challenges with convergence and sampling low-probability events.
• The Jarzynski equality offers a path to calculate free energies from nonequilibrium work measurements.

Purpose of the Study:

• To investigate the efficacy of combining weighted ensemble algorithms with the Jarzynski equality for binding free energy calculations.
• To evaluate novel weighted ensemble resampling techniques and diffusion Monte Carlo methods.
• To assess the accuracy and efficiency of these methods for model systems.

Main Methods:

• Utilizing weighted ensemble algorithms with cloning and merging operations to sample nonequilibrium trajectories.
• Implementing a novel weighted ensemble resampler for direct importance sampling.
• Applying diffusion Monte Carlo with applied work as a selection potential.

Main Results:

• Weighted ensemble methods combined with the Jarzynski equality efficiently determine accurate binding free energies.
• The approach is particularly effective for deeper Lennard-Jones well depths.
• The examined methods show improved efficiency in calculating unbinding free energies.

Conclusions:

• The combination of weighted ensemble algorithms and the Jarzynski equality presents a more efficient and accurate approach for binding free energy calculations.
• These enhanced sampling techniques are valuable for computational drug design and molecular simulations.
• Further application of these methods can advance the understanding of molecular interactions.