Linking well-tempered metadynamics simulations with experiments.

Area of Science:

• Biophysics
• Computational Biology
• Structural Biology

Background:

• Understanding protein-disordered states requires linking experimental data with atomistic simulations.
• Classical molecular dynamics (MD) simulations face sampling limitations for complex systems.
• Metadynamics offers a way to overcome these limitations by introducing history-dependent bias.

Purpose of the Study:

• To demonstrate a combined approach using enhanced molecular dynamics and experimental data for characterizing protein conformational ensembles.
• To validate the accuracy of metadynamics and reweighting algorithms in reconstructing equilibrium distributions.
• To compare simulated nuclear magnetic resonance (NMR) scalar couplings with experimental data for a helix-forming peptide.

Main Methods:

• Utilized well-tempered metadynamics combined with parallel tempering for enhanced sampling.
• Employed a recently developed reweighting algorithm to reconstruct the equilibrium Boltzmann distribution from biased simulations.
• Focused on a 13-residue helix-forming peptide system.

Main Results:

• Successfully characterized the conformational ensemble explored by the peptide.
• Reconstructed NMR scalar couplings showed quantitative agreement with experimental data.
• Demonstrated the potential of the combined simulation and reweighting approach.

Conclusions:

• The integration of enhanced molecular dynamics simulations (metadynamics) with experimental data provides powerful insights into protein-disordered states.
• The developed reweighting method enables accurate reconstruction of equilibrium properties, facilitating direct comparison with experimental measurements.
• This approach is valuable for studying the structure and dynamics of peptides and potentially larger disordered protein systems.