Lateral organization of complex lipid mixtures from multiscale modeling

Area of Science:

• Biophysics
• Computational Biology
• Materials Science

Background:

• Complex lipid mixtures organize into functional structures within cell membranes.
• Ternary lipid-cholesterol (CHOL) mixtures serve as model systems for studying membrane "rafts".

Purpose of the Study:

• To develop and validate a self-consistent mean-field model for investigating the lateral organization of multi-component lipid mixtures.
• To incorporate molecular dynamics simulations for parameter extraction and to study domain formation in model membranes.

Main Methods:

• A self-consistent mean-field model was developed, integrating data from molecular dynamics simulations.
• The model was applied to ternary mixtures of dioleoylphosphatidylcholine:18:0 sphingomyelin:CHOL.
• Interaction parameters and chain configuration order parameter libraries were extracted using molecular dynamics.

Main Results:

• Model predictions showed regions of bimodal order on ternary plots, consistent with experimental findings.
• The model successfully captured the lateral organization of the studied lipid mixtures.
• Specific intermolecular interactions driving localized domain formation were identified.

Conclusions:

• The developed model provides a robust framework for understanding lipid organization in complex mixtures.
• The findings offer valuable insights into the molecular mechanisms underlying lipid raft formation.
• This approach enhances the predictive power of computational models for membrane biophysics.