Correlation between native-state hydrogen exchange and cooperative residue fluctuations from a simple model

Area of Science:

• Structural Biology
• Computational Biology
• Biophysics

Background:

• Understanding protein conformational fluctuations is crucial for deciphering protein function and dynamics.
• Existing simulation methods for protein dynamics are often computationally intensive.
• Hydrogen exchange (HX) experiments provide valuable data on protein conformational dynamics.

Purpose of the Study:

• To apply a novel, simplified analytical model, the Gaussian network model (GNM), to interpret protein hydrogen exchange (HX) data.
• To assess the GNM's ability to describe protein conformational fluctuations in the native state and under weak denaturing conditions.
• To investigate the contribution of local, cooperative fluctuations to overall protein dynamics.

Main Methods:

• Development of a simple analytical model (GNM) based on local residue packing densities and tertiary contact distributions.
• Application of the GNM to analyze experimental hydrogen exchange (HX) data for five diverse proteins.
• Comparison of GNM-calculated fluctuations with experimental HX measurements.

Main Results:

• The GNM demonstrated good agreement between calculated protein fluctuations and experimental HX data across five different proteins.
• GNM calculations were significantly faster (2-3 orders of magnitude) than previous complex simulation methods.
• The model's success highlights the importance of local, cooperative conformational fluctuations in native-state HX behavior.

Conclusions:

• The Gaussian network model (GNM) provides an efficient and accurate approach for analyzing protein conformational dynamics and HX data.
• Local, cooperative residue fluctuations play a significant role in protein conformational dynamics.
• GNM-derived local conformational susceptibilities may offer insights into global protein dynamics and unfolding pathways.