Integrating solvation shell structure in experimentally driven molecular dynamics using x-ray solution scattering...

Area of Science:

• Biophysics
• Computational Biology
• Structural Biology

Background:

• Molecular dynamics (MD) simulations are crucial for predicting protein structures.
• Current MD methods sometimes yield results that conflict with experimental data.
• Improved strategies are needed to align computational predictions with experimental observations.

Purpose of the Study:

• To develop a scalable and efficient MD simulation approach for exploring protein conformational landscapes.
• To integrate x-ray solution scattering data as a driving force for conformational searches.
• To improve the accuracy of MD simulations by incorporating hydration layer effects.

Main Methods:

• Developed an MD simulation protocol incorporating x-ray solution scattering signals.
• Included hydration layer effects in simulations for processes like protein unfolding.
• Utilized graphics processing units (GPUs) for efficient, on-the-fly calculation of scattering patterns.
• Applied the method to lysine-, arginine-, ornithine-binding protein and deca-alanine.

Main Results:

• Demonstrated a scalable and efficient MD approach driven by x-ray solution scattering.
• Showcased the importance of hydration effects for accurate simulation of unfolding.
• Achieved significant speed-up in calculations using GPU acceleration for all-atom simulations.
• Validated the methodology on two model protein systems.

Conclusions:

• The developed MD approach effectively guides conformational searches using experimental scattering data.
• Inclusion of hydration layers improves the description of protein dynamics and conformational changes.
• This method offers a powerful tool for interpreting scattering experiments in protein folding and association studies.