Identification of kinetic order parameters for non-equilibrium dynamics

Area of Science:

• Computational Chemistry and Molecular Dynamics
• Statistical Mechanics and Complex Systems

Background:

• Analyzing high-dimensional many-body systems often involves projecting trajectories onto collective variables.
• Existing methods like time-lagged independent component analysis (TICA) have limitations, requiring detailed balance and long equilibrated trajectories.

Purpose of the Study:

• To develop a dimension reduction method applicable to non-equilibrium dynamics.
• To provide a more general alternative to TICA for analyzing complex system dynamics.

Main Methods:

• Developed a novel dimension reduction technique based on the Variational Approach for Markov Processes (VAMP).
• Applied VAMP to a single-file ion diffusion model and molecular dynamics simulations of the KcsA channel protein.

Main Results:

• VAMP successfully obtained a low-dimensional description of the ion diffusion model.
• Identified long-lived states in KcsA channel simulations under electrochemical potential.
• Revealed insights into the coupling between conformational dynamics, selectivity filter configuration, and channel conductance.

Conclusions:

• The Variational Approach for Markov Processes (VAMP) is effective for dimension reduction in non-equilibrium dynamics.
• VAMP offers a more general and powerful approach compared to TICA for analyzing molecular dynamics.
• This method provides valuable insights into the functional mechanisms of biological channels.