Lipid-Protein Interactions Are Unique Fingerprints for Membrane Proteins

Abstract

Cell membranes contain hundreds of different proteins and lipids in an asymmetric arrangement. Our current understanding of the detailed organization of cell membranes remains rather elusive, because of the challenge to study fluctuating nanoscale assemblies of lipids and proteins with the required spatiotemporal resolution. Here, we use molecular dynamics simulations to characterize the lipid environment of 10 different membrane proteins. To provide a realistic lipid environment, the proteins are embedded in a model plasma membrane, where more than 60 lipid species are represented, asymmetrically distributed between the leaflets. The simulations detail how each protein modulates its local lipid environment in a unique way, through enrichment or depletion of specific lipid components, resulting in thickness and curvature gradients. Our results provide a molecular glimpse of the complexity of lipid-protein interactions, with potentially far-reaching implications for our understanding of the overall organization of real cell membranes.

Figure 1

Unique lipid environments for different membrane proteins. (A) Simulation setup, consisting of a plasma membrane model containing 63 different lipid types with four membrane proteins embedded. (B) View of the local lipid environment around AQP1, displaying lipids within a distance cutoff of 0.7 nm from the protein surface. (C) Lipid depletion–enrichment (D–E) index in the case of AQP1, obtained from the last 5 μs of a 30 μs long simulation, and averaged over the four AQP1 molecules (error bars indicate standard deviation). The D–E index is computed by dividing the lipid composition of the first 0.7 nm shell by the bulk membrane composition. Values larger than 1 indicate enrichment of a given lipid group, while values smaller than 1 indicate depletion. (D) D–E index matrix, with average depletion (blue)/enrichment (red) for 10 different membrane proteins (the calculation for additional distance cutoffs and corresponding standard deviations are shown in Table S1). The COX-1 D–E index values for the negatively charged lipids of the lower leaflet have been omitted because they are difficult to interpret given the partial insertion of the protein only in the upper leaflet (see the note in Table S1). Lipid classes considered are phosphatidylcholine (PC), phosphatidylethanolamine (PE), phosphatidylserine (PS), phosphatidic acid (PA), diacyl-glycerol (DG), lyso-PC (LPC), sphingomyelin (SM), ceramide (CER), phosphatidylinositol (PI), phosphatidylinositol-(bi, tri)phosphate (PIPs), ganglioside (GM), cholesterol (CHOL), polyunsaturated (PU), fully saturated (FS), and others.

Figure 2

Membrane protein fingerprints. (A) Two-dimensional lateral density maps, showing local density fluctuations around AQP1 in upper (top row) and lower (bottom row) leaflets, grouped according to lipid classes: polyunsaturated (PU) lipids, fully saturated (FS) lipids, and cholesterol. Major observations are indicated by arrows, see text for details: I, nonspecific binding; II, nonuniform distribution; III, leaflet asymmetry; IV, specific binding; V, membrane fluctuations. (B) Nonuniform variations in local membrane properties around AQP1: thickness, mean curvature, and Gaussian curvature for upper (top row) and lower (bottom row) leaflets.