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In This Article

  • Summary
  • Abstract
  • Introduction
  • Protocol
  • Representative Results
  • Discussion
  • Acknowledgements
  • Materials
  • References
  • Reprints and Permissions

Summary

Membrane lipid diversity in structure and composition is an important contributor to cellular processes and can be a marker of disease. Molecular dynamics simulations allow us to study membranes and their interactions with biomolecules at atomistic resolution. Here, we provide a protocol to build, run, and analyze complex membrane systems.

Abstract

Lipids are structural building blocks of cell membranes; lipid species vary across cell organelles and across organisms. This variety results in different mechanical and structural properties in the membrane that directly impact the molecules and processes that occur at this interface. Lipid composition is dynamic and can serve to modulate cell signaling processes. Computational approaches are increasingly used to predict interactions between biomolecules and provide molecular insights to experimental observables. Molecular dynamics (MD) is a technique based on statistical mechanics that predicts the movement of atoms based on the forces that act on them. MD simulations can be used to characterize the interaction of biomolecules. Here, we briefly introduce the technique, outline practical steps for beginners who are interested in simulating lipid bilayers, demonstrate the protocol with beginner-friendly software, and discuss alternatives, challenges, and important considerations of the process. Particularly, we emphasize the relevance of using complex lipid mixtures to model a cell membrane of interest to capture the appropriate hydrophobic and mechanical environments in simulation. We also discuss some examples where membrane composition and properties modulate the interactions of bilayers with other biomolecules.

Introduction

Lipids are major constituents of membranes, which provide boundaries for cells and enable intracellular compartmentalization1,2,3. Lipids are amphiphilic, with a polar head group and two hydrophobic fatty acid tails; these self-assemble into a bilayer to minimize contact of the hydrophobic chains with water3,4. Various combinations of hydrophilic head groups and hydrophobic tails result in different classes of lipids in biological membranes, such as glycerophospholipids, sphingolipids, and sterols (

Protocol

1. Building the system coordinates

  1. Navigate to CHARMM-GUI.org (C-GUI) using a web browser. On the top menu, navigate to Input Generator, then select Membrane Builder from the vertical options on the left side of the screen.
  2. To build a bilayer, select Bilayer Builder.
    NOTE: First time users must activate their free account before building their first set of coordinates.
  3. Select Membrane Only System. S.......

Representative Results

To illustrate the use of the protocol and the results that can be obtained, a comparison study for membrane models for the endoplasmic reticulum (ER) is discussed. The two models in this study were (i) the PI model, which contains the top four lipid species found in the ER, and (ii) the PI-PS model, which added the anionic phosphatidylserine (PS) lipid species. These models were later used in a study of a viral protein and how it interacts with the membrane, the interest on PS has been cited as important for the per.......

Discussion

Experimental techniques can visualize biomolecules at high resolution using cryo-electron microscopy (cryo-EM)58, fluorescence techniques, and atomic force microscopy (AFM)59. However, it is challenging to capture the interplay and dynamics of molecular interactions that underlie biological pathways, disease pathogenesis, and therapeutic delivery at the atomic or amino acid level. Here, capabilities of MD simulations to study lipid membranes and the main steps to design, bu.......

Acknowledgements

The authors thank Jinhui Li and Ricardo X. Ramirez for their simulation trajectories and discussions during the writing of this manuscript. O.C. was supported by the University at Buffalo Presidential Fellowship and National Institute of Health's Initiative for Maximizing Student Development Training Grant 1T32GM144920-01 awarded to Margarita L. Dubocovich (PI).

....

Materials

NameCompanyCatalog NumberComments
Anaconda3Anaconda Inc (Python & related libraries)N/A
CHARMM-GUI.orgIm lab, Lehigh UniversityN/A
GROMACSGROMACS development teamN/A
Linux HPC ClusterUB CCRN/A
MATLABMathWorksN/A
VMDTheoretical and Computational Biophysics GroupN/A

References

  1. Vanni, S., Riccardi, L., Palermo, G., De Vivo, M. Structure and Dynamics of the Acyl Chains in the Membrane Trafficking and Enzymatic Processing of Lipids. Accounts of Chemical Research. 52 (11), 3087-3096 (2019).
  2. Harayama, T., Riezman, H.

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Membrane ModelingComplex Lipid MixturesMolecular Dynamics SimulationsCell Membrane BiophysicsLipid CompositionBiomolecular InteractionsComputational ApproachesExperimental TechniquesLipid SpeciesMembrane InterfaceMembrane StructureCell Signaling

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