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Peptide Aggregation and Pore Formation in a Lipid Bilayer; a Combined CG and AA MD Study Lea Thøgersen, University of Aarhus Pushing the Boundaries of.

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Presentation on theme: "Peptide Aggregation and Pore Formation in a Lipid Bilayer; a Combined CG and AA MD Study Lea Thøgersen, University of Aarhus Pushing the Boundaries of."— Presentation transcript:

1 Peptide Aggregation and Pore Formation in a Lipid Bilayer; a Combined CG and AA MD Study Lea Thøgersen, University of Aarhus Pushing the Boundaries of Biomolecular Simulation June 11, 2008

2 Outline Introduction Results Conclusions  Coarse-Grained Molecular Dynamics  Alamethicin  Modelling Setup  NAMD CG vs MARTINI CG  Microsecond Action  Structure  Reverse Coarse-Graining  Water Pore Formation  Structural Changes

3 Coarse Grained MD – Why? Reduction in degrees of freedom Fast frequenzy movements removed Smoother potential surface Longer time steps can be taken Microsecond simulations possible All-atom MD: time step of 1-2 fs, time frame sampled ~ 100 ns Coarse-grained MD: time step of 20-50 fs, time frame sampled ~ 1 μs Coarse-graining

4 Coarse Grained Molecular Dynamics Shelley, Shelley, Reeder, Bandyopadhyay, Klein; A Coarse Grain Model for Phospholipid Simulations J. Phys. Chem. B (2001) 105 4464 Shih, Arkhipov, Freddolino, Schulten; Coarse Grained Protein-Lipid Model with Application to Lipoprotein Particles J. Phys. Chem. B (2006) 110 3674 NAMD CG Marrink, de Vries, Mark; Coarse Grained Model for Semiquantitative Lipid Simulations J. Phys. Chem. B (2004) 108 750 MARTINI CG Marrink, Risselada, Yefimov, Tieleman, de Vries; The MARTINI Force Field: Coarse Grained Model for Biomolecular Simulations J. Phys. Chem. B (2007) 111 7812 Monticelli, Kandasamy, Periole, Larson, Tieleman, Marrink; The MARTINI Coarse-Grained Force Field: Extension to Proteins J. Chem. Theory and Comput. (2008) 4 819

5 20 amino acid antimicrobiel peptide. Part of the immune system (for fungi). Forms channels in membranes which allow water and ions to go through. Destroys membrane potential. Alamethicin Motivation: Potentially a good and simple membrane channel model Insight into this family of proteins could be valuable in the development of antibiotics Gln7 Glu18 Gln19

6 Widely Accepted Channel Model Tieleman, Hess, Sansom; Analysis and Evaluation of Channel Models: Simulations of Alamethicin. Biophys. J. (2002) 83 2392 Spaar, Münster, Salditt; Conformation of Peptides in Lipid Membranes Studied by X-Ray Grazing Incidence Scattering. Biophys. J. (2004) 87 396

7 Modelling Setup 25 peptides 330 DMPC lipids 26452 water ~117000 atoms ~ 11700 beads PBC 120 Å × 124 Å × 90 Å To study alamethicin interaction with membrane and each other

8 Apolar Polar Nonpolar Charged hydrogenbond donor acceptor both none hydrogenbond donor acceptor both none NAMD CG versus MARTINI CG NAMD CGMARTINI CG 1 4 4 1 2 1 2 4 2 degree of polarity 1-5 (MARTINI) (NAMD) AA GLYALAAIB NAMD MARTINI Nda N0 C5C4 CCCNda

9 32 ns 7 ns Alamethicin Behavior Alamethicin Hydrophilic sidechains Lipid Polar headgroup Non-polar tails C-term N-term 120 ns

10 Peptide Aggregation I 0-1 μs

11 Peptide Aggregation II 0 μs1 μs4 μs MARTINI NAMD

12 Structure of the Clusters 0 0.5 1 Gln7

13 Helix Tilt Alamethicin, DMPC lipid peptid:lipid - 1:15 15 N-Aib8 alamethicin Exp θ = 10˚ MD Vosegaard, Bertelsen, Pedersen, Thøgersen, Schiøtt, Tajkhorshid, Skrydstrup, Nielsen; Resolution Enhancement in Solid-State NMR of Oriented Membrane Proteins by Anisotropic Differential Linebroadening JACS (2008) 130 5028 θ Aib8

14 Reverse Coarse-Graining CG t = 0μs CG t = 1μs AA - rev CG t = 1μs AA after SA AA t = 0μs

15 CG water vs AA water 900-1000 ns δ-δ- δ+δ+ δ+δ+ Class: Polar 5.0Å2.8Å TIP3P model 35-40 ns

16 Structural Changes 18 of 25 peptides remain α-helical

17 Conclusions Alamethicin monomers readily aggregate and form clusters that grow in size over time. Large diversity in form of clusters and structure of peptides. Reverse CG required to  obtain detailed water interaction  validate results obtained on the long time scale

18 Acknowledgements Emad Tajkhorshid & the NAMD people Theoretical and Computational Biophysics Group University of Illinois at Urbana-Champaign, USA Birgit Schiøtt & the Biomodelling Group Department of Chemistry University of Aarhus, Denmark Niels Christian Nielsen & Thomas Vosegaard Laboratory for Biomolecular NMR spectroscopy Department of Chemistry University of Aarhus, Denmark Funding: &


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