Statistical Model To Decipher Protein Folding/Unfolding at a Local Scale.

Area of Science:

• Computational Biology and Biophysics
• Protein Dynamics and Thermodynamics

Background:

• Experimental analysis of protein folding/unfolding often relies on local probes and temperature-dependent physical properties.
• Understanding local unfolding mechanisms is crucial for deciphering complex protein dynamics beyond simple two-state models.

Purpose of the Study:

• To adapt the Lifson-Roig helix-coil transition model for analyzing local thermal unfolding.
• To investigate the local unfolding behavior of the bacteriophage lambda W protein (gpW) using molecular dynamics simulations.

Main Methods:

• Employed all-atom molecular dynamics (MD) simulations of gpW in explicit solvent across 15 temperatures.
• Utilized coarse-grained dihedral and bond angles as local probes of protein structure.
• Defined local native/non-native states based on free-energy landscapes and extracted local equilibrium constants.

Main Results:

• Modified Lifson-Roig model predictions closely matched MD simulation data for local denaturation curves.
• gpW exhibited gradual unfolding between 320-340 K, with local structure stability decreasing significantly.
• Enthalpy calculations indicated a dynamic equilibrium of diverse structures in the unfolded state.

Conclusions:

• The adapted Lifson-Roig model effectively analyzes local thermal unfolding without parameter adjustment.
• Results support a downhill unfolding mechanism for gpW, deviating from a two-state global model.
• Provides insights into interpreting local denaturation curves and the nature of unfolded protein ensembles.