title: Spontaneous adsorption of coiled-coil model peptides K and E to a mixed lipid bilayer.
abstract: A molecular description of the lipid-protein interactions underlying the adsorption of proteins to membranes is crucial for understanding, for example, the specificity of adsorption or the binding strength of a protein to a bilayer, or for characterizing protein-induced changes of membrane properties. In this paper, we extend an automated in silico assay (DAFT) for binding studies and apply it to characterize the adsorption of the model fusion peptides E and K to a mixed phospholipid/cholesterol membrane using coarse-grained molecular dynamics simulations. In addition, we couple the coarse-grained protocol to reverse transformation to atomistic resolution, thereby allowing to study molecular interactions with high detail. The experimentally observed differential binding of the peptides E and K to membranes, as well as the increased binding affinity of helical over unstructered peptides, could be well reproduced using the polarizable Martini coarse-grained (CG) force field. Binding to neutral membranes is shown to be dominated by initial binding of the positively charged N-terminus to the phospholipid headgroup region, followed by membrane surface-aligned insertion of the peptide at the interface between the hydrophobic core of the membrane and its polar headgroup region. Both coarse-grained and atomistic simulations confirm a before hypothesized snorkeling of lysine side chains for the membrane-bound state of the peptide K. Cholesterol was found to be enriched in peptide vicinity, which is probably of importance for the mechanism of membrane fusion. The applied sequential multiscale method, using coarse-grained simulations for the slow adsorption process of peptides to membranes followed by backward transformation to atomistic detail and subsequent atomistic simulations of the preformed peptide-lipid complexes, is shown to be a versatile approach to study the interactions of peptides or proteins with biomembranes.
authors.affiliation: Computational Biology, Department of Biology, University of Erlangen-Nürnberg, Staudtstr. 5, 91052 Erlangen, Germany.
authors.forename: Kristyna
authors.initials: K
authors.lastname: Pluhackova
authors.affiliation: Computational Biology, Department of Biology, University of Erlangen-Nürnberg, Staudtstr. 5, 91052 Erlangen, Germany.
authors.forename: Tsjerk A
authors.initials: TA
authors.lastname: Wassenaar
authors.affiliation: Computational Biology, Department of Biology, University of Erlangen-Nürnberg, Staudtstr. 5, 91052 Erlangen, Germany.
authors.forename: Sonja
authors.initials: S
authors.lastname: Kirsch
authors.affiliation: Computational Biology, Department of Biology, University of Erlangen-Nürnberg, Staudtstr. 5, 91052 Erlangen, Germany.
authors.forename: Rainer A
authors.initials: RA
authors.lastname: Böckmann
mesh_terms: D000327:Adsorption; D002784:Cholesterol / Q000737:chemistry; D004745:Enkephalins / Q000737:chemistry* / Q000235:genetics; D057927:Hydrophobic and Hydrophilic Interactions; D008051:Lipid Bilayers / Q000737:chemistry*; D056004:Molecular Dynamics Simulation; D010743:Phospholipids / Q000737:chemistry; D011485:Protein Binding; D017433:Protein Structure, Secondary; D014867:Water / Q000737:chemistry
chemical_list: D004745:Enkephalins; D008051:Lipid Bilayers; D010743:Phospholipids; D014867:Water; C039933:peptide E (adrenal medulla); D002784:Cholesterol