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Bulletin of Mathematical Biology

, Volume 42, Issue 5, pp 601–625 | Cite as

Theory of cation-phospholipid-induced shape changes in a lipid bilayer couple

  • Gregory S. B. Lin
Article

Abstract

A quantitative model of ion binding and molecular interactions in the lipid bilayer membrane is proposed and found to be useful in examining the factors underlying such membrane characteristics as shape, sidedness, stability and vesicle size at various cation concentrations. The lipid membrane behaves as a bilayer couple whose preferential radius of curvature depends on the expansion or contraction of one monolayer relative to the other. It is proposed that molecular packing may be altered by electrostatic repulsion of adjacent like-charged phospholipid headgroups, or by bringing two headgroups closer together by divalent cation crossbridging. The surface concentrations of each type of cation-phospholipid complex can be described by simple binding equilibria and the Gouy-Chapman-Stern formulation for the surface potential in a diffuse double layer. The asymmetric distribution of acidic phospholipids in most biological membranes can account for the differential effects of identical ionic environments on either side of the bilayer. The fraction of vesicle material which tends to have a right-side-out orientation may be approximated by a normal distribution about the mean curvature. The theory generates vesicle sidedness distributions that, when fitted to experimental results from human erythrocyte membranes, provide an alternative method of estimating intrinsic cationphospholipid dissociation constants and other molecular parameters of the bilayer. The results also corroborate earlier suggestions that the Gouy-Chapman theory tends to overestimate free counter-ion concentrations at the surface under large surface potentials.

Keywords

Divalent Cation Phosphatidic Acid Acidic Phospholipid Human Erythrocyte Membrane Phospholipid Headgroups 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Society for Mathematical Biology 1980

Authors and Affiliations

  • Gregory S. B. Lin
    • 1
  1. 1.Department of Physiology-Anatomy, and Group in Biophysics and Medical PhysicsUniversity of CaliforniaBerkeleyUSA

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