Elucidating Protein Structures in the Gas Phase: Traversing Configuration Space with Biasing Methods

Area of Science:

• Computational chemistry
• Biophysics
• Structural biology

Background:

• Accurate characterization of gas-phase protein structures is crucial but challenging.
• Discrepancies exist between initial Molecular Dynamics (MD) simulations and experimental Collision Cross-Section (CCS) values obtained via Ion Mobility-Mass Spectrometry (IMS-MS).

Purpose of the Study:

• To improve the accuracy of gas-phase protein structure characterization.
• To reconcile discrepancies between simulated and experimental Collision Cross-Section (CCS) values.

Main Methods:

• Utilized Molecular Dynamics (MD) simulations combined with enhanced sampling techniques.
• Employed Harmonic Biasing Potential and Adaptive Biasing Force methods, using radius of gyration as a guiding parameter.
• Applied guiding forces to overcome energy barriers, allowing proteins to reach compact conformations.

Main Results:

• Enhanced sampling methods significantly improved the alignment between simulated and experimental CCS values.
• Achieved close agreement (within approximately 4%) between calculated and experimentally measured CCS.
• Validated the efficacy of Harmonic Biasing Potential and Adaptive Biasing Force in predicting gas-phase protein structures.

Conclusions:

• Enhanced sampling techniques are effective for accurate gas-phase protein structure prediction.
• This study provides a foundation for optimizing biasing methods for improved structural characterization.
• Future work will focus on expanding collective variables for more precise predictions.