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Multiscale Modeling and Simulation Approaches to Lipid–Protein Interactions

Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 2003)

Abstract

Lipid membranes play a crucial role in living systems by compartmentalizing biological processes and forming a barrier between these processes and the environment. Naturally, a large apparatus of biomolecules is responsible for construction, maintenance, transport, and degradation of these lipid barriers. Additional classes of biomolecules are tasked with transport of specific substances or transduction of signals from the environment across lipid membranes. In this article, we intend to describe a set of techniques that enable one to build accurate models of lipid systems and their associated proteins, and to simulate their dynamics over a variety of time and length scales. We discuss the methods and challenges that allow us to derive structural, mechanistic, and thermodynamic information from these models. We also show how these models have recently been applied in research to study some of the most complex lipid–protein systems to date, including bacterial and viral envelopes, neuronal membranes, and mammalian signaling systems.

Key words

Molecular dynamics (MD) simulation Molecular modeling Protein–lipid interactions Lipid-binding protein Membrane proteins Membrane peptides Multiscale Coarse-grained (CG) models 

Notes

Acknowledgments

T.S.C. and H.I.I. acknowledge that this work has been supported in part by the Joint Design of Advanced Computing Solutions for Cancer (JDACS4C) program established by the U.S. Department of Energy (DOE) and the National Cancer Institute (NCI) of the National Institutes of Health. T.S.C. and H.I.I. note that this work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL-JRNL-752805. J.R.A. acknowledges the following sources of funding: Rutherford Discovery Fellowship (15-MAU-001); Marsden grant (15-UOA-105); New Zealand Ministry of Business, Innovation and Employment (MBIE) Endeavour Smart Ideas grant (UOCX1706); Maurice Wilkins Centre for Molecular Biodiscovery Flagship Project grant (MWC 3716850). W.A.I. was supported by the following sources of funding: Massey University Doctoral Scholarship; Massey University Doctoral Dissemination grant. N.D. thanks the Nehru trust for Cambridge University and Rajiv Gandhi (UK) foundation for funding. P.J.B. and J.K.M. acknowledge funding from the Ministry of Education in Singapore (MOE AcRF Tier 3 Grant Number MOE2012-T3-1-008).

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Authors and Affiliations

  1. 1.Bioinformatics Institute (BII)Agency for Science, Technology and Research (A*STAR)SingaporeSingapore
  2. 2.Biosciences and Biotechnology Division, Physical and Life Sciences DirectorateLawrence Livermore National LaboratoryLivermoreUSA
  3. 3.Department of ChemistryUniversity of CambridgeCambridgeUK
  4. 4.Centre for Theoretical Chemistry and Physics, Institute of Natural and Mathematical SciencesMassey UniversityAucklandNew Zealand
  5. 5.School of ChemistryUniversity of SouthamptonSouthamptonUK
  6. 6.School of Biological Sciences and Maurice Wilkins Centre for Molecular BiodiscoveryThe University of AucklandAucklandNew Zealand
  7. 7.Biomolecular Interaction CentreUniversity of CanterburyChristchurchNew Zealand
  8. 8.Department of Biological SciencesNational University of SingaporeSingaporeSingapore

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