Accelerated weight histogram method for exploring free energy landscapes.

Area of Science:

• Computational chemistry
• Molecular dynamics
• Biophysics

Background:

• Calculating free energies is crucial but difficult in molecular simulations.
• Complex systems require enhanced sampling methods to explore free energy landscapes.
• Existing methods face challenges in efficiency and applicability.

Purpose of the Study:

• Introduce and demonstrate the accelerated weight histogram (AWH) method for efficient free energy calculations.
• Showcase AWH's general applicability and potential for further extensions.
• Provide practical guidelines for setting up and running AWH simulations.

Main Methods:

• Utilized the accelerated weight histogram (AWH) method, an enhanced sampling technique.
• Employed adaptive biasing with a probability weight histogram for efficient free energy updates.
• Applied a non-uniform, free energy dependent target distribution in reaction coordinate space.

Main Results:

• Demonstrated AWH efficiency in calculating potential of mean force in one and multiple dimensions.
• Successfully applied AWH to molecular dynamics simulations of lithium acetate in solution.
• Showcased AWH's utility in studying the folding of chignolin, a 10-residue peptide.

Conclusions:

• The AWH method offers an efficient and general approach for free energy calculations in molecular simulations.
• AWH facilitates exploration of complex free energy landscapes, aiding in the study of systems like protein folding.
• The method's formulation supports further development and analysis within the field of enhanced sampling.