Folding simulations of small proteins.

Area of Science:

• Computational Biology
• Biophysics
• Protein Science

Background:

• Protein folding is a fundamental yet complex process in molecular biology.
• Understanding protein folding pathways is crucial for deciphering protein function and dysfunction.
• Current models face challenges in accurately simulating the dynamics of protein folding.

Purpose of the Study:

• To simulate and analyze the folding pathways of small proteins using an optimized atomistic model.
• To investigate the relationship between early folding events and equilibrium thermodynamic properties.
• To determine the convergence of non-equilibrium folding trajectories.

Main Methods:

• Utilized an optimized united-residue force field for atomistic simulations.
• Performed extensive Monte Carlo folding simulations with high step counts (10^9 and 10^6 steps).
• Conducted multiple independent simulation runs (ten and 200) for each protein to ensure robustness.

Main Results:

• Simulated proteins (HP-36, protein A, 1fsd, betanova) successfully folded into native-like conformations.
• Observed glassy transitions at low temperatures, indicating complex dynamics.
• Identified diverse, non-equilibrium early folding pathways that uniquely converge for each protein.

Conclusions:

• Direct folding simulations are essential for identifying the convergence points of early folding pathways.
• The free energy surface, an equilibrium property, dictates the slower, later stages of protein folding.
• The study provides insights into the multi-stage nature of protein folding, from rapid initial events to slower thermodynamic control.