Communication: a minimal model for the diffusion-relaxation backbone dynamics of proteins

Area of Science:

• Biophysics
• Computational Biology
• Protein Dynamics

Background:

• Understanding protein dynamics is crucial for deciphering biological function.
• Existing models often struggle to capture both short-time diffusion and long-time relaxation behaviors.
• Accurate modeling of atomic movements aids in drug design and protein engineering.

Purpose of the Study:

• To present a novel model for local diffusion-relaxation dynamics of protein C(α)-atoms.
• To describe both short-time diffusive and long-time asymptotic relaxation dynamics.
• To analyze the relaxation rate spectra using shifted gamma distributions.

Main Methods:

• Developed a theoretical model for C(α)-atom dynamics.
• Utilized shifted gamma distributions to represent relaxation rate spectra.
• Applied the model to analyze data from molecular dynamics simulations of lysozyme.

Main Results:

• The model accurately describes short-time and long-time C(α)-atom dynamics.
• Shifted gamma distributions effectively capture relaxation behaviors in finite-sized macromolecules.
• A strong correlation was found between residue solvent-accessible surface and model parameters.

Conclusions:

• The proposed model provides an excellent fit for protein C(α)-atom dynamics.
• The model offers insights into the relationship between local protein structure and dynamics.
• This work advances the understanding of macromolecular dynamics and their relation to physical properties.