Protein dynamics using frequency-dependent order parameters from analysis of NMR relaxation data

Area of Science:

• Biophysics
• Structural Biology
• Nuclear Magnetic Resonance (NMR) Spectroscopy

Background:

• Protein dynamics are crucial for function, but characterizing motions across various timescales remains challenging.
• Nuclear Magnetic Resonance (NMR) relaxation measurements provide insights into molecular motions.
• Generalized order parameters (S(2)) offer a simplified view of protein dynamics.

Purpose of the Study:

• To develop a novel method for analyzing NMR relaxation data to better understand protein dynamics.
• To introduce and define the frequency-dependent order parameter, S(2)(omega).
• To enable the estimation of contributions from different motional frequencies (picosecond to nanosecond) to the overall S(2).

Main Methods:

• Analysis of 15N NMR relaxation data from protein GB1 at multiple magnetic field strengths (500, 600, and 800 MHz).
• Introduction of the frequency-dependent order parameter, S(2)(omega), derived from the Lorentzian expansion of the spectral density function.
• Quantification of motional contributions across specific frequency ranges.

Main Results:

• The frequency-dependent order parameter, S(2)(omega), successfully estimates contributions to S(2) from distinct motional frequencies.
• The method provides detailed information on motional restrictions within specific time scales (picoseconds to nanoseconds).
• Demonstrated normalized comparison of motional restrictions for proteins with varying overall tumbling correlation times.

Conclusions:

• The novel S(2)(omega) approach offers a more refined analysis of protein dynamics from NMR relaxation data.
• This method enhances the understanding of motional restrictions at specific frequencies.
• It facilitates robust comparisons of protein dynamics, even for molecules with different rotational correlation times.