Realistic Membrane Modeling Using Complex Lipid Mixtures in Simulation Studies

Some in biophysics is rapidly growing. Common experimental approaches include fluorescence microscopy, neutron and x-ray scattering, mass spectroscopy, and atomic force microscopy. Computational approaches include phonological models and those based on statistical thermodynamics that help us understand atomistic or molecular level details of interactions occurring at the membrane interface and inside a hydrophobic core.

When using molecular dynamic simulations, challenges include sampling events of interest, setting a simulation's length, ensuring results converge and reproduce physical values, and accessing computational power. These challenges are particularly true for transient events at the membrane interface, such as the interaction of peripheral proteins with it or the aggregation of lipids and proteins that require large changes in confirmation. This protocol provides a beginner-friendly step-by-step guide to start running molecular dynamic simulations of complex lipid membranes.

There are many software alternatives to carry these simulations, and some packages have tutorials or manuals. We hope our protocol provides a concise foundation on realistic membrane modeling and tips on the considerations that influence the quality of results in these types of modeling studies. This protocol has allowed us to capture interactions between membrane lipids and other biomolecules that were not observed using pure or binary lipid mixtures.

Many interactions at the membrane surface depend on the diversity of lipids on the membrane itself. Our models demonstrate the importance of incorporating appropriate lipid species to accurately explore biomolecular function within membranes. To begin use a web browser to visit the CHARMM-GUI.

org website. Create and activate your free account before building your first set of files. Go to the top menu, navigate to the input generator, and select Membrane Builder from the available options on the left side of the screen.

Select the Bilayer Builder to construct a lipid bilayer then select the Membrane Only System and store the generated job ID for future access. Visualize the systems during every step of the building process by clicking View Structure located at the top of the page. Consistently inspect for missing components or errors in patch size.

Select the Heterogeneous Lipid option regardless of whether to build a single component bilayer, then choose a rectangular box type. For hydration select 45 water molecules per lipid, which is ample for a fully hydrated bilayer. Now set the length of XY based on the number of lipid components.

Determine the number of lipids needed for each lipid species based on the pre-planned model. To represent the endoplasmic reticulum in eukaryotic cells a combination of 336 DOPC, 132 DPPE, 60 cholesterol, and 72 POPI lipids was used in the PI model while 330 DOPC, 126 DPPE, 54 cholesterol, 66 POPI, and 24 DOPS lipids were used for the PIPS model. Input the desired number of molecules for the upper and lower leaflets in the two boxes next to the lipid name to create a symmetric membrane composition.

Then navigate to the top of the lipid species list and initiate the action by clicking on the Show the system info"button. Using CHARMM-GUI, validate the total count of lipids in each leaflet in the symmetric bilayer. Continue clicking the next screens to set the desired values for temperature and pressure for simulation and the syntax for the simulation files according to the molecular dynamics engine of choice.

For instance, GROMACS. Download the resulting files and transfer them to the computer cluster. Use selected software, for instance, Visual Molecular Dynamics or PyMOL, to visualize the final system.

After building the system coordinates for molecular dynamics simulations, create a submission script to minimize and relax the built coordinate system. Use the commands listed until Production comment in the README file provided in the output from CHARMM-GUI to the submission script. Submit the relaxation script and ensure all output files from its steps have been produced before progressing to the production run.

Upon completion, verify the presence of output files with different extensions generated from GROMACS during the six-step relaxation run. To perform benchmarking, generate short trajectories 1-2 nanoseconds long, and estimate the computational cost using varying numbers of computing nodes. Compare the performance in nanoseconds per day for different numbers of computing nodes to determine the optimal resources for the run.

Choose the number of nodes that result in a performance level between 75-80%of the maximum. Compressed raw trajectory files denoted as TRR files in GROMACS by changing the file format to XTC files or skipping frames to reduce file size to facilitate efficient transfer to the local station for visualization and analysis. Visualize the full trajectory before running any analysis to identify the molecules or atoms of interest and determine the trajectory portion intended for characterization.

Then determine the area per lipid time series for membrane only simulations and identify the equilibrated portion of the trajectory. Analysis of membrane structure revealed a significant difference in thickness between the two models for the endoplasmic reticulum, indicating an inverse relationship between the area per lipid and membrane thickness. Deuterium order parameters of each lipid species showed that there is little to no difference between the order of lipid tails between the models except for DPPE, which shows a slight increase for the SN1 tail in the PI model.

Lipid composition and membrane models modulates interactions with other molecules. For example, simulations using different ratios of PC and PS lipids showed that electrostatic interactions drive the initial binding of D112, a delocalized lipophilic cation to anionic lipids and hydrophobic interactions pull the molecule into the membrane core.