Statistical coil model of the unfolded state: resolving the reconciliation problem

Area of Science:

• Biophysics
• Computational Biology
• Structural Biology

Background:

• Understanding protein folding requires characterizing the unfolded state.
• Chemically denatured proteins exhibit complex behaviors, including random coil scaling and local structure.

Purpose of the Study:

• To develop a statistical coil model for generating accurate unfolded protein ensembles.
• To reconcile seemingly contradictory experimental observations of the denatured state.

Main Methods:

• Utilized a self-avoiding statistical coil model based on backbone conformational frequencies from a coil library.
• Incorporated neighboring residue correlations to refine conformational preferences.

Main Results:

• The model successfully reproduced random coil scaling of the radius of gyration and NMR residual dipolar couplings.
• The model identified stretched conformations and specific local structures (polyproline II, beta conformers) as key contributors.
• Achieved improved agreement with NMR data by including residue-specific correlations.

Conclusions:

• The statistical coil model provides an accurate representation of the protein unfolded state.
• This model can improve thermodynamic and kinetic modeling of protein folding processes.
• The generated ensembles do not exhibit native-like topology, distinguishing them from folded states.