Improved Highly Mobile Membrane Mimetic Model for Investigating Protein-Cholesterol Interactions

Area of Science:

• Computational biophysics
• Membrane protein dynamics
• Molecular simulations

Background:

• Cholesterol (CHL) is crucial for mammalian membrane protein function.
• Conventional simulations of protein-CHL interactions are computationally intensive due to slow lipid dynamics.
• Existing models like the highly mobile membrane mimetic (HMMM) facilitate lipid interactions but require modifications for non-phospholipid components like CHL.

Purpose of the Study:

• To develop and validate an updated HMMM model (HMMM-CHL) capable of simulating cholesterol behavior and interactions.
• To optimize customized solvents within the HMMM framework for accurate CHL dynamics.
• To assess the model's performance in characterizing protein-CHL interactions in complex membrane systems.

Main Methods:

• Development of the HMMM-CHL model by optimizing solvents for CHL.
• Integration of enhanced CHL dynamics and accelerated lipid diffusion within the HMMM framework.
• Application of the HMMM-CHL model to simulate the human β2-adrenergic receptor (β2AR) and VDAC-1.

Main Results:

• The HMMM-CHL model successfully incorporates and simulates cholesterol dynamics.
• Optimized solvents demonstrated compatibility with force-based switching protocols.
• Simulations accurately identified CHL binding sites and interactions for β2AR and VDAC-1, consistent with experimental data.

Conclusions:

• The HMMM-CHL model provides an efficient approach for enhanced sampling of protein-CHL interactions.
• This updated model is valuable for studying cholesterol's role in membrane protein function.
• The method offers a significant advancement for computational investigations of membrane protein-cholesterol systems.