The foldability landscape of model proteins

Area of Science:

• Computational biology
• Protein evolution
• Molecular dynamics

Background:

• Molecular evolution is modeled as navigating a multidimensional fitness landscape.
• Protein fitness is linked to function, stability, and survivability.
• Understanding protein sequence evolution requires robust models.

Purpose of the Study:

• To present a simplified model for protein sequence evolution on a defined fitness landscape.
• To analyze the nature of the foldability landscape and evolutionary dynamics.
• To investigate the impact of selective pressure on evolutionary trajectories.

Main Methods:

• Utilizing simple lattice models to represent protein structures.
• Quantifying protein sequence fitness by its lowest energy foldability, based on the spin glass model.
• Incorporating selective pressure as a minimum foldability requirement.

Main Results:

• Native structures and their optimal foldabilities are clustered in interaction space.
• Evolving proteins minimally satisfy the imposed foldability selection criteria.
• Increased selective pressure restricts evolutionary paths to neutral networks, preserving structure.

Conclusions:

• The foldability landscape is not uniform, exhibiting clustering of similar structures.
• Protein evolution under selective pressure demonstrates adaptation within constraints.
• Neutral networks play a crucial role in maintaining protein structure during evolution.