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Lipid packing drives the segregation of transmembrane helices into disordered lipid domains in model membranes.

ABSTRACT: Cell membranes are comprised of multicomponent lipid and protein mixtures that exhibit a complex partitioning behavior. Regions of structural and compositional heterogeneity play a major role in the sorting and self-assembly of proteins, and their clustering into higher-order oligomers. Here, we use computer simulations and optical microscopy to study the sorting of transmembrane helices into the liquid-disordered domains of phase-separated model membranes, irrespective of peptide-lipid hydrophobic mismatch. Free energy calculations show that the enthalpic contribution due to the packing of the lipids drives the lateral sorting of the helices. Hydrophobic mismatch regulates the clustering into either small dynamic or large static aggregates. These results reveal important molecular driving forces for the lateral organization and self-assembly of transmembrane helices in heterogeneous model membranes, with implications for the formation of functional protein complexes in real cells.

SUBMITTER: Schafer LV

PROVIDER: S-EPMC3029762 | biostudies-literature | 2011 Jan

REPOSITORIES: biostudies-literature

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Lipid packing drives the segregation of transmembrane helices into disordered lipid domains in model membranes.

Schäfer Lars V LV de Jong Djurre H DH Holt Andrea A Rzepiela Andrzej J AJ de Vries Alex H AH Poolman Bert B Killian J Antoinette JA Marrink Siewert J SJ

Proceedings of the National Academy of Sciences of the United States of America 20110104 4

Cell membranes are comprised of multicomponent lipid and protein mixtures that exhibit a complex partitioning behavior. Regions of structural and compositional heterogeneity play a major role in the sorting and self-assembly of proteins, and their clustering into higher-order oligomers. Here, we use computer simulations and optical microscopy to study the sorting of transmembrane helices into the liquid-disordered domains of phase-separated model membranes, irrespective of peptide-lipid hydropho ...[more]

PMID: 21205902

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Project description:Studying membrane active peptides or protein fragments within the lipid bilayer environment is particularly challenging in the case of synthetically modified, labeled, artificial, or recently discovered native structures. For such samples the localization and orientation of the molecular species or probe within the lipid bilayer environment is the focus of research prior to an evaluation of their dynamic or mechanistic behavior. X-ray scattering is a powerful method to study peptide/lipid interactions in the fluid, fully hydrated state of a lipid bilayer. For one, the lipid response can be revealed by observing membrane thickening and thinning as well as packing in the membrane plane; at the same time, the distinct positions of peptide moieties within lipid membranes can be elucidated at resolutions of up to several angstroms by applying heavy-atom labeling techniques. In this study, we describe a generally applicable X-ray scattering approach that provides robust and quantitative information about peptide insertion and localization as well as peptide/lipid interaction within highly oriented, hydrated multilamellar membrane stacks. To this end, we have studied an artificial, designed β-helical peptide motif in its homodimeric and hairpin variants adopting different states of oligomerization. These peptide lipid complexes were analyzed by grazing incidence diffraction (GID) to monitor changes in the lateral lipid packing and ordering. In addition, we have applied anomalous reflectivity using synchrotron radiation as well as in-house X-ray reflectivity in combination with iodine-labeling in order to determine the electron density distribution ρ(z) along the membrane normal (z axis), and thereby reveal the hydrophobic mismatch situation as well as the position of certain amino acid side chains within the lipid bilayer. In the case of multiple labeling, the latter technique is not only applicable to demonstrate the peptide's reconstitution but also to generate evidence about the relative peptide orientation with respect to the lipid bilayer.

Project description:BackgroundSince membrane protein structures are challenging to crystallize, computational approaches are essential for elucidating the sequence-to-structure relationships. Structural modeling of membrane proteins requires a multidimensional approach, and one critical geometric parameter is the rotational angle of transmembrane helices. Rotational angles of transmembrane helices are characterized by their folded structures and could be inferred by the hydrophobic moment; however, the folding mechanism of membrane proteins is not yet fully understood. The rotational angle of a transmembrane helix is related to the exposed surface of a transmembrane helix, since lipid exposure gives the degree of accessibility of each residue in lipid environment. To the best of our knowledge, there have been few advances in investigating whether an environment descriptor of lipid exposure could infer a geometric parameter of rotational angle.ResultsHere, we present an analysis of the relationship between rotational angles and lipid exposure and a support-vector-machine method, called TMexpo, for predicting both structural features from sequences. First, we observed from the development set of 89 protein chains that the lipid exposure, i.e., the relative accessible surface area (rASA) of residues in the lipid environment, generated from high-resolution protein structures could infer the rotational angles with a mean absolute angular error (MAAE) of 46.32˚. More importantly, the predicted rASA from TMexpo achieved an MAAE of 51.05˚, which is better than 71.47˚ obtained by the best of the compared hydrophobicity scales. Lastly, TMexpo outperformed the compared methods in rASA prediction on the independent test set of 21 protein chains and achieved an overall Matthew's correlation coefficient, accuracy, sensitivity, specificity, and precision of 0.51, 75.26%, 81.30%, 69.15%, and 72.73%, respectively. TMexpo is publicly available at http://bio-cluster.iis.sinica.edu.tw/TMexpo.ConclusionsTMexpo can better predict rASA and rotational angles than the compared methods. When rotational angles can be accurately predicted, free modeling of transmembrane protein structures in turn may benefit from a reduced complexity in ensembles with a significantly less number of packing arrangements. Furthermore, sequence-based prediction of both rotational angle and lipid exposure can provide essential information when high-resolution structures are unavailable and contribute to experimental design to elucidate transmembrane protein functions.

Dataset Information

Lipid packing drives the segregation of transmembrane helices into disordered lipid domains in model membranes.

Publications

Lipid packing drives the segregation of transmembrane helices into disordered lipid domains in model membranes.

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