Ganglioside-Lipid and Ganglioside-Protein Interactions Revealed by Coarse-Grained and Atomistic Molecular Dynamics Simulations

Abstract

Gangliosides are glycolipids in which an oligosaccharide headgroup containing one or more sialic acids is connected to a ceramide. Gangliosides reside in the outer leaflet of the plasma membrane and play a crucial role in various physiological processes such as cell signal transduction and neuronal differentiation by modulating structures and functions of membrane proteins. Because the detailed behavior of gangliosides and protein-ganglioside interactions are poorly known, we investigated the interactions between the gangliosides GM1 and GM3 and the proteins aquaporin (AQP1) and WALP23 using equilibrium molecular dynamics simulations and potential of mean force calculations at both coarse-grained (CG) and atomistic levels. In atomistic simulations, on the basis of the GROMOS force field, ganglioside aggregation appears to be a result of the balance between hydrogen bond interactions and steric hindrance of the headgroups. GM3 clusters are slightly larger and more ordered than GM1 clusters due to the smaller headgroup of GM3. The different structures of GM1 and GM3 clusters from atomistic simulations are not observed at the CG level based on the Martini model, implying a difference in driving forces for ganglioside interactions in atomistic and CG simulations. For protein-ganglioside interactions, in the atomistic simulations, GM1 lipids bind to specific sites on the AQP1 surface, whereas they are depleted from WALP23. In the CG simulations, the ganglioside binding sites on the AQP1 surface are similar, but ganglioside aggregation and protein-ganglioside interactions are more prevalent than in the atomistic simulations. Using the polarizable Martini water model, results were closer to the atomistic simulations. Although experimental data for validation is lacking, we proposed modified Martini parameters for gangliosides to more closely mimic the sizes and structures of ganglioside clusters observed at the atomistic level.

CHARMM‐GUI Martini Maker for modeling and simulation of complex bacterial membranes with lipopolysaccharides

“…To this end, web‐based user‐friendly Martini‐Maker is developed to construct flat bilayers, vesicles, micelles, and nanodiscs with minimal user inputs. We have shown that the resulting structures are robust and similar compared to their atomistic counterparts, although there is room for improvement (i) by optimizing the Martini parameters for Ca 2+ and by reducing the overall stickiness of sugar‐based molecules as was recently performed for gangliosides and (ii) the Martini‐Maker system building parameters to better estimate the number of lipid molecules in Vesicle Builder . Martini‐Maker is expected to replace the laborious process of manual system setup of these complex LPS‐containing systems with an easy to use, freely available, online procedure that requires minimal manual intervention.…”

Spatial Relationship and Functional Relevance of Three Lipid Domain Populations at the Erythrocyte Surface

“…Considering the wide range of domain features that lipid-lipid interactions can generate in molecular simulations of simple and complex bilayers, it is not so surprising to unveil such a diversity of lipid domains in living cell membranes. As a matter of fact, lipid clusters in simulated membranes show various (i) composition, as they are not only enriched in SM and chol, but also in gangliosides (GM1 and GM3) and in PC analogs [44,45]; (ii) lipid order; and (iii) topography, as some GM3 nano-clusters have been shown to preferentially associate with concave (when viewed from the extracellular medium) membranes [46]. Such lipid domain diversity is also supported by several experimental data on simple lipid mixtures [47][48][49].…”

“…head group, acyl chain length and saturation [50]). Moreover, lipid domain biogenesis and/or maintenance also depend on the chol content, as chol is a key regulator of membrane fluidity (and thus space between phospholipids for optimal head group interactions) and is able to directly interact with SM or GM1 [45,51].…”

Cholesterol interaction sites on the transmembrane domain of the hedgehog signal transducer and Class F G protein-coupled receptor Smoothened

“…A comparable analysis of our equilibrium CG simulations yielded a free energy of interaction of -6 kJ/mol. Given the detailed differences between the various studies, a conservative interpretation would be that cholesterol interactions with GPCRs are of the order of -5 to -10 kJ/mol, in contrast with estimated free energies of -10 to -40 kJ/mol for the interactions of a range of different membrane proteins with anionic phospholipids calculated by the same approach (see (Arnarez et al, 2016;Domański et al, 2017;Domicevica et al, 2018;Gu et al, 2017;Hedger et al, 2016a;Hedger et al, 2016b) and Table S1).…”