High resolution ensemble description of metamorphic and intrinsically disordered proteins using an efficient hybrid...

Area of Science:

• Computational Biology
• Biophysics
• Molecular Dynamics

Background:

• Mapping protein free energy landscapes is crucial but challenging for complex multi-funneled metamorphic and intrinsically disordered proteins (IDPs).
• Existing rare-event sampling molecular dynamics simulations often require restraints or data reweighing to align with experimental results.

Purpose of the Study:

• To develop an efficient and accurate method for conformational sampling of diverse protein types.
• To overcome limitations of traditional molecular dynamics simulations in studying complex protein landscapes.

Main Methods:

• A novel parallel-tempering molecular dynamics method incorporating accelerated water dynamics.
• Benchmarking against standard model systems (alanine di-peptide, TRP-cage, β-hairpin) for sampling efficiency.
• Application to large metamorphic proteins (RFA-H) and intrinsically disordered proteins (Histatin-5).

Main Results:

• Demonstrated improved sampling efficiency compared to standard methods.
• Achieved accurate conformational sampling across a wide variety of proteins, including large and disordered ones.
• Calculated ensemble averages closely matched experimental data (NMR, SAXS) without reweighing.

Conclusions:

• The developed parallel-tempering method enables efficient and accurate sampling of protein free energy landscapes.
• This approach facilitates the study of complex, multi-funneled, and intrinsically disordered proteins.
• The method provides a powerful tool for exploring uncharted protein conformational spaces and validating against biophysical experiments.