Evolution of the folding ability of proteins through functional selection

Area of Science:

• Computational biology
• Protein folding dynamics
• Evolutionary algorithms

Background:

• Understanding the origin of protein folding ability is crucial for molecular biology.
• Protein sequences dictate their three-dimensional structures and functions.
• The relationship between sequence, structure, and folding dynamics remains a complex challenge.

Purpose of the Study:

• To investigate the origin of protein folding ability through evolutionary simulation.
• To explore how functional selection on local configurations influences global folding.
• To identify key features of sequences that enable fast protein folding.

Main Methods:

• Simulated protein evolution using a spin-glass-like model.
• Random mutation and folding process simulation at each generation.
• Selection based on the frequency of local configurations at active sites.

Main Results:

• Emergence of a globally folding sequence after several hundred generations.
• Identified distinct energy minimum and anisotropic funnel for the selected sequence.
• Demonstrated that functional selection accelerates global folding rates.

Conclusions:

• Evolutionary processes can lead to the emergence of efficient protein folding.
• Local configuration selection is a key driver for achieving global native conformations.
• The model provides insights into the biophysical basis of fast protein folding.