Dataset Information

Construction of an implicit membrane environment for the lattice Monte Carlo simulation of transmembrane protein.

ABSTRACT: Due to the complexity of biological membrane, computer simulation of transmembrane protein's folding is challenging. In this paper, an implicit biological membrane environment has been constructed in lattice space, in which the lipid chains and water molecules were represented by the unoccupied lattice sites. The biological membrane was characterized with three features: stronger hydrogen bonding interaction, membrane lateral pressure, and lipophobicity index for the amino acid residues. In addition to the hydrocarbon core spanning region and the water solution, the lipid interface has also been represented in this implicit membrane environment, which was proved to be effective for the transmembrane protein's folding. The associated Monte Carlo simulations have been performed for SARS-CoV E protein and M2 protein segment (residues 18-60) of influenza A virus. It was found that the coil-helix transition of the transmembrane segment occurred earlier than the coil-globule transition of the two terminal domains. The folding process and final orientation of the amphipathic helical block in water solution are obviously influenced by its corresponding hydrophobicity/lipophobicity. Therefore, this implicit membrane environment, though in lattice space, can make an elaborate balance between different driving forces for the membrane protein's folding, thus offering a potential means for the simulation of transmembrane protein oligomers in feasible time.

SUBMITTER: Chen Y

PROVIDER: S-EPMC7117040 | biostudies-literature | 2010 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Construction of an implicit membrane environment for the lattice Monte Carlo simulation of transmembrane protein.

Chen Yantao Y Wang Mingliang M Zhang Qianling Q Liu Jianhong J

Biophysical chemistry 20091228 1-2

Due to the complexity of biological membrane, computer simulation of transmembrane protein's folding is challenging. In this paper, an implicit biological membrane environment has been constructed in lattice space, in which the lipid chains and water molecules were represented by the unoccupied lattice sites. The biological membrane was characterized with three features: stronger hydrogen bonding interaction, membrane lateral pressure, and lipophobicity index for the amino acid residues. In addi ...[more]

PMID: 20079964

Similar Datasets

Project description:Ionic transport in solid electrolytes can often be approximated as ions performing a sequence of hops between distinct lattice sites. If these hops are uncorrelated, quantitative relationships can be derived that connect microscopic hopping rates to macroscopic transport coefficients; i.e. tracer diffusion coefficients and ionic conductivities. In real materials, hops are uncorrelated only in the dilute limit. At non-dilute concentrations, the relationships between hopping frequency, diffusion coefficient and ionic conductivity deviate from the random walk case, with this deviation quantified by single-particle and collective correlation factors, f and fI, respectively. These factors vary between materials, and depend on the concentration of mobile particles, the nature of the interactions, and the host lattice geometry. Here, we study these correlation effects for the garnet lattice using lattice-gas Monte Carlo simulations. We find that, for non-interacting particles (volume exclusion only), single-particle correlation effects are more significant than for any previously studied three-dimensional lattice. This is attributed to the presence of two-coordinate lattice sites, which causes correlation effects intermediate between typical three-dimensional and one-dimensional lattices. Including nearest-neighbour repulsion and on-site energies produces more complex single-particle correlations and introduces collective correlations. We predict particularly strong correlation effects at xLi=3 (from site energies) and xLi=6 (from nearest-neighbour repulsion), where xLi=9 corresponds to a fully occupied lithium sublattice. Both effects are consequences of ordering of the mobile particles. Using these simulation data, we consider tuning the mobile-ion stoichiometry to maximize the ionic conductivity, and show that the 'optimal' composition is highly sensitive to the precise nature and strength of the microscopic interactions. Finally, we discuss the practical implications of these results in the context of lithium garnets and other solid electrolytes.

Dataset Information

Construction of an implicit membrane environment for the lattice Monte Carlo simulation of transmembrane protein.

Publications

Construction of an implicit membrane environment for the lattice Monte Carlo simulation of transmembrane protein.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets