Capturing Biologically Complex Tissue-Specific Membranes at Different Levels of Compositional Complexity

Plasma membranes
(PMs) contain hundreds of different lipid species
that contribute differently to overall bilayer properties. By modulation
of these properties, membrane protein function can be affected. Furthermore,
inhomogeneous lipid mixing and domains of lipid enrichment/depletion
can sort proteins and provide optimal local environments. Recent coarse-grained
(CG) Martini molecular dynamics efforts have provided glimpses into
lipid organization of different PMs: an “Average” and
a “Brain” PM. Their high complexity and large size require
long simulations (∼80 μs) for proper sampling. Thus,
these simulations are computationally taxing. This level of complexity
is beyond the possibilities of all-atom simulations, raising the questionwhat
complexity is needed for “realistic” bilayer properties?
We constructed CG Martini PM models of varying complexity (63 down
to 8 different lipids). Lipid tail saturations and headgroup combinations
were kept as consistent as possible for the “tissues’”
(Average/Brain) at three levels of compositional complexity. For each
system, we analyzed membrane properties to evaluate which features
can be retained at lower complexity and validate eight-component bilayers
that can act as reliable mimetics for Average or Brain PMs. Systems
of reduced complexity deliver a more robust and malleable tool for
computational membrane studies and allow for equivalent all-atom simulations
and experiments.