Reconstructing the Most Probable Folding Transition Path from Replica Exchange Molecular Dynamics Simulations

Area of Science:

• Computational chemistry
• Biophysics
• Molecular dynamics

Background:

• Studying rare events like protein folding requires characterizing transition pathways and states.
• Molecular dynamics simulations are powerful tools for observing molecular behavior.

Purpose of the Study:

• To demonstrate a method for recovering the most probable transition pathways between metastable states from molecular dynamics data.
• To apply this method to a beta hairpin peptide to elucidate its folding mechanism and transition state.

Main Methods:

• Utilized replica exchange molecular dynamics simulations.
• Employed the dynamic string method to identify the most probable transition path.
• Calculated local drift vectors in collective variables between replica exchanges.
• Updated string points based on drift vectors to generate reaction pathways.

Main Results:

• Successfully recovered folding pathways for a designed beta hairpin peptide.
• Identified two distinct folding pathways with different event orders.
• Estimated relative free energy differences for each pathway.
• Characterized structures near the transition state.

Conclusions:

• The dynamic string method effectively recovers most probable transition pathways from molecular dynamics data.
• The study provides insights into the folding mechanism and transition state of a beta hairpin peptide.
• This approach is valuable for studying rare events in molecular systems.