Long-range correlation in protein dynamics: Confirmation by structural data and normal mode analysis

Area of Science:

• Structural Biology
• Computational Biology
• Biophysics

Background:

• Proteins exhibit long-range correlations in their dynamics, where local changes affect distant residues.
• These correlations are crucial for biological processes like allostery, catalysis, and molecular transport.
• Understanding the structural basis of these correlations is key to deciphering protein design principles.

Purpose of the Study:

• To investigate the structural origin of long-range correlations in protein dynamics.
• To explore how native protein topology influences protein structure and dynamics.
• To identify universal principles governing protein evolution across different sizes.

Main Methods:

• Analysis of a large dataset of globular proteins obtained via X-ray crystallography.
• Application of normal mode analysis using elastic network models.
• Scaling analysis of the slowest vibration mode, average path length, and modularity concerning protein size.

Main Results:

• Demonstrated that native protein topology encodes long-range correlations in protein dynamics.
• Quantitatively described the balance between order and disorder in native proteins, characterized by dense packing and fractal topology.
• Showed that the interplay between stability and flexibility acts as an evolutionary constraint for proteins of varying sizes.

Conclusions:

• Native protein topology is fundamental to its dynamic behavior and functional capabilities.
• Proteins exhibit a balance of order and disorder, with fractal properties, reflecting evolutionary optimization.
• A universal principle linking protein size, stability-flexibility balance, and evolutionary trajectory was revealed.