Self-assembly of large, ordered lamellae from non-bilayer lipids and integral membrane proteins in vitro

In many biological membranes, the major lipids are “non-bilayer lipids,” which in purified form cannot be arranged in a lamellar structure. The structural and functional roles of these lipids are poorly understood. This work demonstrates that the in vitro association of the two main components of a membrane, the non-bilayer lipid monogalactosyldiacylglycerol (MGDG) and the chlorophyll-a/b light-harvesting antenna protein of photosystem II (LHCII) of pea thylakoids, leads to the formation of large, ordered lamellar structures: (i) thin-section electron microscopy and circular dichroism spectroscopy reveal that the addition of MGDG induces the transformation of isolated, disordered macroaggregates of LHCII into stacked lamellar aggregates with a long-range chiral order of the complexes; (ii) small-angle x-ray scattering discloses that LHCII perturbs the structure of the pure lipid and destroys the inverted hexagonal phase; and (iii) an analysis of electron micrographs of negatively stained 2D crystals indicates that in MGDG-LHCII the complexes are found in an ordered macroarray. It is proposed that, by limiting the space available for MGDG in the macroaggregate, LHCII inhibits formation of the inverted hexagonal phase of lipids; in thylakoids, a spatial limitation is likely to be imposed by the high concentration of membrane-associated proteins.

Enhanced conformational sampling in Monte Carlo simulations of proteins: application to a constrained peptide.

A Monte Carlo simulation method for globular proteins, called extended-scaled-collective-variable (ESCV) Monte Carlo, is proposed. This method combines two Monte Carlo algorithms known as entropy-sampling and scaled-collective-variable algorithms. Entropy-sampling Monte Carlo is able to sample a large configurational space even in a disordered system that has a large number of potential barriers. In contrast, scaled-collective-variable Monte Carlo provides an efficient sampling for a system whose dynamics is highly cooperative. Because a globular protein is a disordered system whose dynamics is characterized by collective motions, a combination of these two algorithms could provide an optimal Monte Carlo simulation for a globular protein. As a test case, we have carried out an ESCV Monte Carlo simulation for a cell adhesive Arg-Gly-Asp-containing peptide, Lys-Arg-Cys-Arg-Gly-Asp-Cys-Met-Asp, and determined the conformational distribution at 300 K. The peptide contains a disulfide bridge between the two cysteine residues. This bond mimics the strong geometrical constraints that result from a protein's globular nature and give rise to highly cooperative dynamics. Computation results show that the ESCV Monte Carlo was not trapped at any local minimum and that the canonical distribution was correctly determined.