Size distribution of gel and fluid clusters in DMPC/DSPC lipid bilayers. AMonte Carlo simulation study

Citation
Ei. Michonova-alexova et Ip. Sugar, Size distribution of gel and fluid clusters in DMPC/DSPC lipid bilayers. AMonte Carlo simulation study, J PHYS CH B, 105(41), 2001, pp. 10076-10083
Citations number
40
Categorie Soggetti
Physical Chemistry/Chemical Physics
Journal title
JOURNAL OF PHYSICAL CHEMISTRY B
ISSN journal
15206106 → ACNP
Volume
105
Issue
41
Year of publication
2001
Pages
10076 - 10083
Database
ISI
SICI code
1520-6106(20011018)105:41<10076:SDOGAF>2.0.ZU;2-#
Abstract
Proteins and lipid components are organized into domains in many biological membranes. With different experimental techniques vastly different cluster sizes have been measured in an equimolar mixture of a DMPC/DSPC two-compon ent lipid bilayer: very small ones in the nanometer range and very large on es of size comparable with the size of the bilayer. In this paper the later al distribution of gel and fluid lipid molecules in a DMPC/DSPC bilayer is simulated by using a two-state, Ising type model with the application of Mo nte Carlo methods. The same model has been able to predict the excess heat capacity curves, FRAP threshold temperatures, average coherence length betw een DSPC clusters, and the fractal dimension of gel clusters, in agreement with the respective experimental data. In this work, similarly to the exper imental results, the calculated equilibrium distributions of cluster size s how that, between the onset temperature of the gel-to-fluid transition and the percolation threshold temperature of the gel clusters, nanometer size g el clusters coexist with a gel cluster of size comparable to the bilayer's size itself. The calculated upper bound for the size of the small clusters, 8 +/- 1.5 nm is very close to the experimental estimate of 10 nm. More tha n one large gel clusters might be present in the case of nonequilibrium lat eral distributions. By means of the calculated temperature dependence of th ree different cluster size averages we can get insight into the process of cluster growth.