Protein Folding Free Energy Landscape along the Committor - the Optimal Folding Coordinate

Area of Science:

• Computational Chemistry
• Biophysics
• Statistical Mechanics

Background:

• Analyzing large, complex simulation data requires automated tools.
• Describing molecular dynamics via diffusion on free energy landscapes is powerful.
• Optimal reaction coordinates (RCs) are crucial for accurate landscape approximations but difficult to determine.

Purpose of the Study:

• To develop a method for accurately determining the optimal RC (committor) for realistic systems.
• To enable quantitative analysis of molecular dynamics using free energy landscapes.
• To overcome limitations of existing parameter-heavy RC approximation methods.

Main Methods:

• An adaptive, nonparametric approach to determine the optimal RC (committor) from equilibrium trajectories.
• Optimization focuses adaptively on under-optimized regions to prevent overfitting.
• Application to an atomistic protein folding simulation (HP35).

Main Results:

• Successfully determined the optimal folding RC (committor) for HP35 protein.
• Generated the first quantitatively accurate protein folding free energy landscape.
• Validated that diffusion on this landscape accurately predicts kinetic properties and folding dynamics.

Conclusions:

• The adaptive nonparametric method accurately identifies optimal reaction coordinates.
• This enables precise free energy landscape calculations and quantitative analysis of molecular dynamics.
• The approach provides rigorous estimates for protein folding dynamics parameters.