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7: Computational Characterization of Membranes
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7.1: Mathematical Continuum Descriptions of Membranes
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Membranes have many roles in cellular function. To better understand membrane mechanics and how it affects cellular function, it is important to be able to mathematically describe the membrane morphology. Continuum descriptions are commonly used to do this, in which the membrane is treated as a two-dimensional sheet and the energy of a conformation is calculated. This energy can be minimized to determine equilibrium shapes of a biological system.
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7.2: Monte Carlo for Biomembranes
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The fluid mosaic model served as the starting point for our modern understanding of biological membranes. This model describes the biological membrane bilayer as an integration of proteins and lipids, which interact to control movement of material in and out of the cell through protein pores, form lipid rafts, and regulate vesicle formation. This Modules will focus on computational methods used to study biomembranes (specifically Monte Carlo).
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7.3: Molecular Dynamics for Biomembranes
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Molecular dynamics (MD) is a simulation method used in many fields to help understand the movement of atoms and molecules. This method is based on Newton's equations of motion. Each atom or molecule in the simulation is defined by a force field and mass, and is allowed to interact for a given time period. Biomembrane systems have various parameters that for MD simulations that can change the way the system evolves such as charged lipids, explicit vs implicit solvents, and membrane proteins.
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7.4: Designing Molecular Membranes Models with VMD
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This page describes how to use basic tools in Visual Molecular Dynamics (VMD) for visualization of membranes. The page also describes how to create homogeneous and heterogeneous membranes using VMD's MembraneBuilder and CHARMM-GUI's Membrane Builder tools, respectively.
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7.5: Coarse Grain Simulations of Membranes
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Capturing the time and length scale of biological processes using computational methods remains a challenge for molecular modeling as resolution is limited to the order of less than 100 ns and 10 nm in all-atom detail. Coarse graining reduces the degrees of freedom of the system to achieve greater size and time scales at the expense of molecular detail to simulate biological processes currently inaccessible to all atom models.