Lipid fingerprints are similar between SLC6 transporters in the neuronal membrane
Wilson, K. A.; Wang, L.; Lin, Y.; O'Mara, M. L.
Show abstract
We use molecular dynamics simulations to characterise the local lipid annulus, or "fingerprint", of three SLC6 transporters (dDAT, hSERT, and GlyT2) embedded into a complex neuronal membrane. New membrane analysis tools were created to improve leaflet detection and leaflet-dependent properties. Overall, lipid fingerprints are comprised of similar lipids when grouped by headgroup or tail saturation. The enrichment and depletion of specific lipids, including sites of cholesterol contacts, varies between transporters. The subtle differences in lipid fingerprints results in varying membrane biophysical properties near the transporter. Through comparisons to previous literature, we highlight that the lipid-fingerprint in complex membranes is highly dependent on membrane composition. Furthermore, through embedding these transporters in a simplified model membrane, we show that the simplified membrane is not able to capture the biophysical properties of the complex membrane. Our results further characterise how the presence and identity of membrane proteins affects the complex interplay of lipid-protein interactions, including the local lipid environment and membrane biophysical properties. HIGHLIGHTSO_LILipid fingerprints are comprised of similar lipid classes C_LIO_LISites of specific lipid contacts, including CHOL, varies between transporters C_LIO_LIChanges in lipid annulus result in variable local membrane biophysical properties C_LIO_LIMembrane composition, including that of complex membranes, affects lipid annulus C_LI GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=91 SRC="FIGDIR/small/427530v1_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@ae6ee9org.highwire.dtl.DTLVardef@1f39af0org.highwire.dtl.DTLVardef@412256org.highwire.dtl.DTLVardef@355f1c_HPS_FORMAT_FIGEXP M_FIG C_FIG
Matching journals
The top 6 journals account for 50% of the predicted probability mass.