The Journal of Membrane Biology

, Volume 248, Issue 3, pp 563–582 | Cite as

Efficient Exploration of Membrane-Associated Phenomena at Atomic Resolution

  • Josh V. Vermaas
  • Javier L. Baylon
  • Mark J. Arcario
  • Melanie P. Muller
  • Zhe Wu
  • Taras V. Pogorelov
  • Emad Tajkhorshid
Article

Abstract

Biological membranes constitute a critical component in all living cells. In addition to providing a conducive environment to a wide range of cellular processes, including transport and signaling, mounting evidence has established active participation of specific lipids in modulating membrane protein function through various mechanisms. Understanding lipid–protein interactions underlying these mechanisms at a sufficiently high resolution has proven extremely challenging, partly due to the semi-fluid nature of the membrane. In order to address this challenge computationally, multiple methods have been developed, including an alternative membrane representation termed highly mobile membrane mimetic (HMMM) in which lateral lipid diffusion has been significantly enhanced without compromising atomic details. The model allows for efficient sampling of lipid–protein interactions at atomic resolution, thereby significantly enhancing the effectiveness of molecular dynamics simulations in capturing membrane-associated phenomena. In this review, after providing an overview of HMMM model development, we will describe briefly successful application of the model to study a variety of membrane processes, including lipid-dependent binding and insertion of peripheral proteins, the mechanism of phospholipid insertion into lipid bilayers, and characterization of optimal tilt angle of transmembrane helices. We conclude with practical recommendations for proper usage of the model in simulation studies of membrane processes.

Keywords

Cellular membrane Lipid bilayer Membrane proteins Peripheral proteins Molecular dynamics simulation 

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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Josh V. Vermaas
    • 1
  • Javier L. Baylon
    • 1
  • Mark J. Arcario
    • 1
  • Melanie P. Muller
    • 1
  • Zhe Wu
    • 1
  • Taras V. Pogorelov
    • 1
  • Emad Tajkhorshid
    • 1
  1. 1.Department of Biochemistry, and Center for Biophysics and Computational Biology, Beckman InstituteUniversity of Illinois at Urbana-ChampaignUrbanaUSA

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