Girsanov reweighting for metadynamics simulations.

Area of Science:

• Computational chemistry
• Molecular dynamics
• Statistical mechanics

Background:

• Metadynamics enhances molecular system exploration by adding Gaussian functions to escape potential energy minima.
• Metadynamics simulations generate unphysical dynamics, limiting direct use for dynamical property estimation.
• Girsanov reweighting constructs Markov State Models (MSMs) for systems under external perturbation.

Purpose of the Study:

• To combine metadynamics and Girsanov reweighting to obtain unbiased MSMs from biased simulations.
• To validate the combined technique on simple systems and challenging peptides.
• To enable phase space exploration for systems with slow dynamics.

Main Methods:

• Metadynamics simulations with on-the-fly Gaussian function addition.
• Girsanov reweighting to correct for the applied bias.
• Markov State Model (MSM) construction from reweighted trajectories.

Main Results:

• The metadynamics/Girsanov-reweighting method successfully generated unbiased MSMs.
• Results showed excellent agreement with MSMs from direct unbiased simulations.
• The technique was applied to a beta-hairpin peptide with slow dynamics.

Conclusions:

• Metadynamics/Girsanov-reweighting is an effective method for constructing unbiased MSMs.
• This approach overcomes limitations of direct simulation for systems with slow dynamics.
• It provides a powerful tool for exploring complex molecular system phase spaces.