Ensemble-Biased Metadynamics: A Molecular Simulation Method to Sample Experimental Distributions.

Area of Science:

• Computational chemistry
• Biophysics
• Molecular dynamics simulations

Background:

• Molecular dynamics (MD) simulations are crucial for understanding molecular behavior.
• Enhanced sampling methods are needed to overcome timescale limitations in MD.
• Integrating experimental data into simulations can improve accuracy and efficiency.

Discussion:

• Ensemble-biased metadynamics (EBMetaD) is a novel enhanced-sampling technique for MD.
• It biases simulations to match known probability distributions, such as experimental intramolecular distances.
• The method operates on the maximum-entropy principle, introducing minimal bias.

Key Insights:

• EBMetaD accurately reproduces experimental distance distributions from double electron-electron resonance (DEER) spectroscopy.
• The method was validated on a model system and spin-labeled T4 lysozyme.
• It achieves this accuracy within tens of nanoseconds, demonstrating significant efficiency.

Outlook:

• EBMetaD is integrated into the open-source PLUMED plugin, ensuring broad accessibility.
• The method offers a computationally efficient and straightforward approach for MD simulations.
• It has the potential to accelerate the integration of experimental data into computational studies.