![]() $ gmx mdrun -deffnm dppc-min-init -v -c 128_o $ gmx grompp -f minimization.mdp -c 128_noW.gro -p dppc.top -o dppc-min-init.tpr You will also need a file with the particle definitions, in this case for version 2.1, which can be downloaded from the the Martini particle definition subsection of the Martini forcefield parameter section. Download it from the Martini lipidome page, see the Martini lipid topology section, place it in your current working directory, and check that the file name corresponds to the #include statement in the topology file dppc.top. The settings file minimization.mdp is provided for you, but you will need the topology for the DPPC lipid. Perform a short energy minimization of the system containing only the lipids the only reason for doing this, is getting rid of high forces between beads that may have been placed quite close to each other. The value of the flag -radius (default van der Waals radii) has to be increased from its default atomistic length (0.105 nm) to a value reflecting the size of Martini CG beads, and noW stands for no Water. $ cd spontaneous-assembly/initial_assembly For help on any gromacs tool, you can add the -h flag. The gromacs tool insert-molecules can take this single-molecule conformation and attempt to place it in a simulation box multiple times at a random position and random orientation, each time checking that there are no overlaps between the consecutively placed molecules. (Note that you can download coordinate files for all Martini lipids from the website, see the Martini lipid topology section.) A file with coordinates for a single DPPC molecule is available for you as o. This can be done by starting from a file containing a single DPPC molecule. The first step is to create a simulation box containing a random configuration of 128 DPPC lipids. Enter the spontaneous-assembly/initial_assembly subdirectory. We will begin with self-assembling a dipalmitoyl-phosphatidylcholine (DPPC) bilayer from a random configuration of lipids and water in the simulation box. $ tar -xzvf bilayer-lipidome-tutorial-GMX5_2017Aug04.tgz A smaller set that expects you to do more yourself is recommended and is named: bilayer-lipidome-tutorial-GMX5_2017Aug04.tgz Unpack one of the lipidome-tutorial.tgz archives (NOTE: both expand to a directory called bilayer-lipidome-tutorial), and enter the bilayer-lipidome-tutorial directory: You can download all the files, including worked examples of this tutorial (gromacs version 2016.3): bilayer-lipidome-tutorial-GMX5_2017Aug04-WORKED.tgz This is a rather large archive. Finally, we will move on to creating more complex multicomponent bilayers. Next, we will change the nature of the lipid head groups and tails, and study how that influences the properties. First, we will attempt to spontaneously self-assemble a DPPC bilayer and check various properties that characterize lipid bilayers, such as the area per lipid, bilayer thickness, order parameters, and diffusion. The aim of the tutorial is to create and study properties of CG Martini models of lipid bilayer membranes. An excellent gromacs tutorial is available at: /~mdcourse/. These tutorials assume a basic understanding of the Linux operating system and the gromacs molecular dynamics (MD) simulation package. You will also study a number of standard bilayer properties. In this tutorial, you will learn how to set up lipid-water system simulations with the lipidome, with a focus on bilayers. Their parameters are available in the Martini Lipidome, see the Martini lipid topology section. Due to the modularity of Martini, a large set of different lipid types has been parameterized. The CG beads have a fixed size and interact using an interaction map with 10 different interaction strengths. Martini uses an approximate 4:1 atomistic (heavy atoms) to CG bead mapping and in version 2.0 18 bead types were defined to represent chemical characteristics of the beads. The underlying philosophy of Martini is to build an extendable CG model based on simple modular building blocks and to use only few parameters and standard interaction potentials to maximise applicability and transferability. The Martini coarse-grained (CG) model was originally developed for lipids. Martini tutorials: lipids with the lipidome
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