Folding and stability of helical bundle proteins from coarse-grained models

Area of Science:

• Computational biology
• Biophysics
• Protein dynamics

Background:

• Understanding protein folding mechanisms is crucial for deciphering biological functions and disease pathologies.
• All-atom molecular dynamics simulations provide detailed insights but are computationally expensive.
• Coarse-grained models offer a balance between accuracy and computational efficiency.

Purpose of the Study:

• To develop and validate a novel coarse-grained model for protein folding simulations.
• To investigate the key physical interactions governing protein structure formation.
• To assess the model's ability to predict native states and alternative conformations.

Main Methods:

• Implicit solvent treatment and short-range electrostatics.
• Coarse-graining of side-chains to single beads.
• Parameterization using a training set of three proteins.
• Validation on a test set of nine proteins and their mutants.

Main Results:

• The model successfully folded proteins from random coil configurations into native states.
• An additional non-native state with altered helical bundle topology was observed for some proteins.
• Model dynamics showed good agreement with all-atom molecular dynamics simulations.
• Hydrophobic, electrostatic, and hydrogen bond strengths were identified as key folding parameters.

Conclusions:

• The developed coarse-grained model provides a computationally efficient approach to study protein folding.
• The model captures essential interactions governing protein structure and dynamics.
• It offers a valuable tool for exploring protein folding pathways and conformational heterogeneity.