Improved Coarse-Grained Modeling of Cholesterol-Containing Lipid Bilayers

Cholesterol
trafficking, which is an essential function in mammalian cells, is
intimately connected to molecular-scale interactions through cholesterol
modulation of membrane structure and dynamics and interaction with
membrane receptors. Since these effects of cholesterol occur on micro-
to millisecond time scales, it is essential to develop accurate coarse-grained
simulation models that can reach these time scales. Cholesterol has
been shown experimentally to thicken the membrane and increase phospholipid
tail order between 0 and 40% cholesterol, above which these effects
plateau or slightly decrease. Here, we showed that the published MARTINI
coarse-grained force-field for phospholipid (POPC) and cholesterol
fails to capture these effects. Using reference atomistic simulations,
we systematically modified POPC and cholesterol bonded parameters
in MARTINI to improve its performance. We showed that the corrections
to pseudobond angles between glycerol and the lipid tails and around
the oleoyl double bond particle (the “angle-corrected model”)
slightly improves the agreement of MARTINI with experimentally measured
thermal, elastic, and dynamic properties of POPC membranes. The angle-corrected
model improves prediction of the thickening and ordering effects up
to 40% cholesterol but overestimates these effects at higher cholesterol
concentration. In accordance with prior work that showed the cholesterol
rough face methyl groups are important for limiting cholesterol self-association,
we revised the coarse-grained representation of these methyl groups
to better match cholesterol-cholesterol radial distribution functions
from atomistic simulations. In addition, by using a finer-grained
representation of the branched cholesterol tail than MARTINI, we improved
predictions of lipid tail order and bilayer thickness across a wide
range of concentrations. Finally, transferability testing shows that
a model incorporating our revised parameters into DOPC outperforms
other CG models in a DOPC/cholesterol simulation series, which further
argues for its efficacy and generalizability. These results argue
for the importance of systematic optimization for coarse-graining
biologically important molecules like cholesterol with complicated
molecular structure.