Inherent structure analysis of protein folding

Area of Science:

• Computational chemistry
• Biophysics
• Protein dynamics

Background:

• Understanding protein folding is crucial for molecular biology and disease research.
• The protein folding landscape is complex, featuring multiple inherent structures (IS) or local minima.
• Previous models often simplified the energy landscape, limiting insights into folding pathways.

Purpose of the Study:

• To analyze the inherent structures (IS) of protein energy landscapes.
• To investigate the role of anharmonic vibrational free energy in protein folding.
• To identify novel indicators for determining protein folding transitions in multifunnel systems.

Main Methods:

• Applied potential energy landscape analysis to a 46-bead BLN protein model.
• Utilized enhanced sampling techniques to determine IS states and thermodynamic quantities.
• Calculated density of states and occupation probabilities (pi) for low-lying IS.

Main Results:

• Identified 239,199 inherent structure states, encompassing most compact, low-energy states.
• Observed distinct density of states lobes for compact and extended states.
• Demonstrated that anharmonic vibrational free energy is critical for protein folding, revealing entropic barriers and a multifunnel landscape structure.

Conclusions:

• Protein folding transitions are influenced by the multifunnel energy landscape and entropic barriers.
• Novel indicators, based on occupation probabilities of IS, can predict foldability.
• Poor foldability correlates with a large 'misfolding interval' where excited states occupy more than the native state.