Molecular simulation of the effect of cholesterol on lipid-mediated protein-protein interactions

GxxxG motifs, phenylalanine, and cholesterol guide the self-association of transmembrane domains of ErbB2 receptors

GxxxG motifs are common in transmembrane domains of membrane proteins and are often introduced to artificial peptides to inhibit or promote association to stable structures. The transmembrane domain of ErbB2 presents two separate such motifs that are proposed to be connected to stability and activity of the dimer. Using molecular simulations, we show that these sequences play a critical role during the recognition stage, forming transient complexes that lead to stable dimers. In pure phospholipid bilayers association occurs by contacts formed at the C-terminus promoted by the presence of phenylalanine residues. Helices subsequently rotate to eventually pack at short separations favored by lipid entropic contributions. In contrast, at intermediate cholesterol concentrations, a different pathway is followed that involves dimers with a weaker interface toward the N-terminus. However, at high cholesterol content, a switch toward the C-terminus is observed with an overall nonmonotonic change of the dimerization affinity. This conformational switch modulated by cholesterol has important implications on the thermodynamic, structural, and kinetic characteristics of helix-helix association in lipid membranes.

Aggregation of model membrane proteins, modulated by hydrophobic mismatch, membrane curvature, and protein class

Aggregation of transmembrane proteins is important for many biological processes, such as protein sorting and cell signaling, and also for in vitro processes such as two-dimensional crystallization. We have used large-scale simulations to study the lateral organization and dynamics of lipid bilayers containing multiple inserted proteins. Using coarse-grained molecular dynamics simulations, we have studied model membranes comprising ∼7000 lipids and 16 identical copies of model cylindrical proteins of either α-helical or β-barrel types. Through variation of the lipid tail length and hence the degree of hydrophobic mismatch, our simulations display levels of protein aggregation ranging from negligible to extensive. The nature and extent of aggregation are shown to be influenced by membrane curvature and the shape or orientation of the protein. Interestingly, a model β-barrel protein aggregates to form one-dimensional strings within the bilayer plane, whereas a model α-helical bundle forms two-dimensional clusters. Overall, it is clear that the nature and extent of membrane protein aggregation is dependent on several aspects of the proteins and lipids, including hydrophobic mismatch, protein class and shape, and membrane curvature.

Modeling the self-assembly of lipids and nanotubes in solution: forming vesicles and bicelles with transmembrane nanotube channels

Via dissipative particle dynamics (DPD), we simulate the self-assembly of end-functionalized, amphiphilic nanotubes and lipids in a hydrophilic solvent. Each nanotube encompasses a hydrophobic stalk and two hydrophilic ends, which are functionalized with end-tethered chains. With a relatively low number of the nanotubes in solution, the components self-assemble into stable lipid-nanotube vesicles. As the number of nanotubes is increased, the system exhibits a vesicle-to-bicelle transition, resulting in stable hybrid bicelle. Moreover, our results reveal that the nanotubes cluster into distinct tripod-like structures within the vesicles and aggregate into a ring-like assembly within the bicelles. For both the vesicles and bicelles, the nanotubes assume trans-membrane orientations, with the tethered hairs extending into the surrounding solution or the encapsulated fluid. Thus, the hairs provide a means of regulating the transport of species through the self-assembled structures. Our findings provide guidelines for creating nanotube clusters with distinctive morphologies that might be difficult to achieve through more conventional means. The results also yield design rules for creating synthetic cell-like objects or microreactors that can exhibit biomimetic functionality.

Clusters of proteins in biomembranes: insights into the roles of interaction potential shapes and of protein diversity

It has recently been proposed that proteins embedded in lipidic biomembranes can spontaneously self-organize into stable small clusters, or membrane nanodomains, due to the competition between short-range attractive and longer-range repulsive forces between proteins, specific to these systems. In this paper, we carry on our investigation, by Monte Carlo simulations, of different aspects of cluster phases of proteins in biomembranes. First, we compare different long-range potentials (including notably three-body terms) to demonstrate that the existence of cluster phases should be quite generic. Furthermore, a real membrane contains hundreds of different protein species that are far from being randomly distributed in these nanodomains. We take this protein diversity into account by modulating protein-protein interaction potentials both at short and longer range. We confirm theoretical predictions in terms of biological cluster specialization by deciphering how clusters recruit only a few protein species. In this respect, we highlight that cluster phases can turn out to be an advantage at the biological level, for example by enhancing the cell response to external stimuli.

From Coarse Grained to Atomistic: A Serial Multiscale Approach to Membrane Protein Simulations

Coarse-grained molecular dynamics provides a means for simulating the assembly and the interactions of membrane protein/lipid complexes at a reduced level of representation, allowing longer and larger simulations. We describe a fragment-based protocol for converting membrane simulation systems, comprising a membrane protein embedded in a phospholipid bilayer, from coarse-grained to atomistic resolution, for further refinement and analysis via atomistic simulations. Overall, this provides a method for generating an accurate and well equilibrated membrane protein/lipid complex. We exemplify the protocol using the acid-sensing/amiloride-sensitive ion channel protein (ASIC) channel protein, a trimeric integral membrane protein. The method is further evaluated using a test set of 10 different membrane proteins of differing size and complexity. Simulations are assessed in terms of protein conformational drift, lipid/protein interactions, and lipid dynamics.