PackMem: A Versatile Tool to Compute and Visualize Interfacial Packing Defects in Lipid Bilayers

Abstract

The analysis of the structural organization of lipid bilayers is generally performed across the direction normal to the bilayer/water interface, whereas the surface properties of the bilayer at the interface with water are often neglected. Here, we present PackMem, a bioinformatic tool that performs a topographic analysis of the bilayer surface from various molecular dynamics simulations. PackMem unifies and rationalizes previous analyses based on a Cartesian grid. The grid allows identification of surface regions defined as lipid-packing defects where lipids are loosely packed, leading to cavities in which aliphatic carbons are exposed to the solvent, either deep inside or close to the membrane surface. Examples are provided to show that the abundance of lipid-packing defects varies according to the temperature and to the bilayer composition. Because lipid-packing defects control the adsorption of peripheral proteins with hydrophobic insertions, PackMem is instrumental for us to understand and quantify the adhesive properties of biological membranes as well as their response to mechanical perturbations such as membrane deformation.

Membrane Thinning Induces Sorting of Lipids and the Amphipathic Lipid Packing Sensor (ALPS) Protein Motif

“…(D) Top view of the 55 × 10 nm 2 POPC membrane. Cyan patches depict lipid packing defects (visualized by PackMem (Gautier et al, 2018). (E) Quantification of lipid packing defects in the thin (cyan) and normal zones (black).…”

“…The block-averaged defect size constants in the bar plot (right) equate to the inverse of the slope of the linear fit to the probability distribution (left). The vertical and horizontal dotted lines indicate the minimal values for curve fitting (area A = 15 Å 2 and probability p(A) = 10 -4 , as recommended by the PackMem authors (Gautier et al, 2018).…”

Breakage of Hydrophobic Contacts Limits the Rate of Passive Lipid Exchange Between Membranes

“…The density of hydrophobic molecular fragments below the tagged lipid gradually increases while the number of hydrophilic ones decreases ( Figure S3). Defects in the polar head group region of the bilayer that expose hydrophobic membrane patches 54,55 are also observed in the transition state ensemble ( Figures S5 and S6). Based on these results, we hypothesized that the reaction coordinate for passive lipid exchange monitors the formation and breakage of hydrophobic contacts between the tagged lipid and membrane ( Figure 1B).…”

3D Packing Defects in Lipid Membrane as a Function of Membrane Order

“…S3 in the SI). Though the defect analysis tool from Antonny and co-workers [27], PackMem, can identify defects to be shallow or deep, it cannot provide the exact measure of their depths.…”

“…Based on the nature of the atom encountered, they classified the defect to be either geometric or chemical. Very recently, Antonny and co-workers optimized their algorithm and presented it in the form of a bioinformatic tool, named PackMem [27], where they also characterize packing defects to be shallow or deep. However, these elegant schemes still analyze the lipid packing defects in 2-dimensions (2D) and report them as area though such defects are actually 3-dimensional voids on the lipid membrane surface [28].…”