A continuum membrane model can predict curvature sensing by helix insertion.

Area of Science:

• Biophysics
• Cell Biology
• Structural Biology

Background:

• Protein domains like ENTH and BAR utilize amphipathic helices for membrane curvature sensing.
• Predicting how physical parameters of these domains control curvature sensing is complex due to local membrane deformations.

Purpose of the Study:

• To develop and validate a deformable continuum model for predicting protein domain-induced membrane curvature sensing.
• To establish an empirical expression relating membrane energy to physical properties and helix insertion parameters.

Main Methods:

• Utilized a deformable continuum model incorporating membrane physical properties and helix insertion.
• Validated the model against experimental data for ENTH and ArfGAP helices binding to vesicles and cylinders.
• Numerically calculated membrane energies as a function of bending modulus, radius, spontaneous curvature, and inserted area.

Main Results:

• Modeled helix insertion as a local change in spontaneous curvature (cins0), achieving excellent agreement with experimental energetics.
• Demonstrated that helix insertion lowers energy on small, high-curvature vesicles but increases energy on larger vesicles by introducing strain.
• Formulated an empirical expression accurately capturing membrane energies based on physical and insertion parameters.

Conclusions:

• The developed model accurately predicts curvature sensing behavior of protein domains.
• Physical parameters of protein domains and membrane properties dictate the energetics of helix binding to curved membranes.
• This work provides a framework for understanding protein localization dynamics in membrane remodeling.