1 / 96

Markus Deserno

Coarse-grained simulation studies of mesoscopic membrane phenomena. Markus Deserno. Department of Physics. Carnegie Mellon University. with:. Ira R. Cooke, Gregoria Illya, Benedict J. Reynwar, Vagelis A. Harmandaris, Kurt Kremer @ MPI-P.

ralderson
Download Presentation

Markus Deserno

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Coarse-grained simulation studies of mesoscopic membrane phenomena Markus Deserno Department of Physics Carnegie Mellon University with: Ira R. Cooke, Gregoria Illya, Benedict J. Reynwar, Vagelis A. Harmandaris, Kurt Kremer @ MPI-P IMA Workshop on the Development and Analysis of Multiscale Methods November 5, 2008

  2. Quick motivation Membranes Typical illustration of an animal cell http://www.animalport.com/img/Animal-Cell.jpg

  3. Quick motivation Membranes Typical illustration of an animal cell Almost everything you see here are membranes! http://www.animalport.com/img/Animal-Cell.jpg

  4. Quick motivation Membranes Notice the many changes in morphology! Almost everything you see here are membranes! http://www.animalport.com/img/Animal-Cell.jpg

  5. Quick motivation Membranes need to be constantly reshaped in order to do their task. The available energy is (bio)chemical; typically coming from ATP hydrolysis. Eavailable ~ 20 kBT (physiol. cond.)

  6. Quick motivation Membranes need to be constantly reshaped in order to do their task. The available energy is (bio)chemical; typically coming from ATP hydrolysis. Eavailable ~ 20 kBT (physiol. cond.) The elasticity of membranes needs to match the available deformation energies!

  7. Membrane bending modulus

  8. Membrane bending modulus

  9. Young’s modulus thickness Membrane bending modulus

  10. Young’s modulus Energy match thickness

  11. Young’s modulus Energy match thickness

  12. Young’s modulus Energy match thickness

  13. Young’s modulus Energy match thickness

  14. Young’s modulus Energy match thickness Let’s hypothesize…

  15. Young’s modulus Energy match thickness …and insist on metal!

  16. Young’s modulus Energy match thickness …and insist on metal!

  17. Å Young’s modulus Energy match thickness …and insist on metal!

  18. Å Young’s modulus Energy match thickness Fail! …and insist on metal!

  19. Moral: Membranes must be made from soft materials! We will invariably encounter long time scales!

  20. Quick motivation (II) Long time scales – How bad is it?

  21. Quick motivation (II) Long time scales – How bad is it? Lindahl, E. & Edholm, O. Mesoscopic undulations and thickness fluctuations in lipid bilayers from molecular dynamics simulations. Biophys. J. 79, 426-433 (2000). All-atom lipid bilayer 20nm20nm, 1024 lipids, 10ns

  22. Quick motivation (II) Long time scales – How bad is it? Lindahl, E. & Edholm, O. Mesoscopic undulations and thickness fluctuations in lipid bilayers from molecular dynamics simulations. Biophys. J. 79, 426-433 (2000). All-atom lipid bilayer 20nm20nm, 1024 lipids, 10ns What if we want a boxlength of L=200nm? How does computing effort scale with L?

  23. Amount of material Quick motivation (II) Long time scales – How bad is it? Lindahl, E. & Edholm, O. Mesoscopic undulations and thickness fluctuations in lipid bilayers from molecular dynamics simulations. Biophys. J. 79, 426-433 (2000). All-atom lipid bilayer 20nm20nm, 1024 lipids, 10ns What if we want a boxlength of L=200nm? How does computing effort scale with L? effort ~ L2

  24. Amount of material Equilibration time Quick motivation (II) Long time scales – How bad is it? Lindahl, E. & Edholm, O. Mesoscopic undulations and thickness fluctuations in lipid bilayers from molecular dynamics simulations. Biophys. J. 79, 426-433 (2000). All-atom lipid bilayer 20nm20nm, 1024 lipids, 10ns What if we want a boxlength of L=200nm? How does computing effort scale with L? effort ~ L2 L4

  25. Amount of material Equilibration time Quick motivation (II) Long time scales – How bad is it? Lindahl, E. & Edholm, O. Mesoscopic undulations and thickness fluctuations in lipid bilayers from molecular dynamics simulations. Biophys. J. 79, 426-433 (2000). All-atom lipid bilayer 20nm20nm, 1024 lipids, 10ns What if we want a boxlength of L=200nm? How does computing effort scale with L? effort ~ L2 L4~ L6

  26. 20nm 200nm Quick motivation (II) Long time scales – How bad is it? Million times more computationally expensive!

  27. 20nm 200nm Quick motivation (II) Long time scales – How bad is it? Million times more computationally expensive!

  28. 20nm 200nm Quick motivation (II) Long time scales – How bad is it? Million times more computationally expensive! 20 doublings of computer power!

  29. 20nm 200nm Quick motivation (II) Long time scales – How bad is it? Million times more computationally expensive! 20 doublings of computer power! 20 x 2 years (Moore’s law)

  30. 20nm 200nm Quick motivation (II) Long time scales – How bad is it? Million times more computationally expensive! 20 doublings of computer power! 20 x 2 years (Moore’s law) 40 years

  31. 20nm 200nm Quick motivation (II) Long time scales – How bad is it? Million times more computationally expensive! 20 doublings of computer power! 20 x 2 years (Moore’s law) 40 years I’ll be retired by then! (best case scenario)

  32. This is why we all love coarse graining

  33. Today: I’ll illustrate a way to efficiently treat the ~100nm regime. • Generic top-down bead-spring • solvent free • only pair forces • robust & physically meaningful I.R. Cooke, K. Kremer, M. Deserno, Phys. Rev. E 72, 011506 (2005); I.R. Cooke and M. Deserno, J. Chem. Phys. 123, 224710 (2005).

  34. unstable fluid phase temperature gel-phase(s) attraction range Today: I.R. Cooke, K. Kremer, M. Deserno, Phys. Rev. E 72, 011506 (2005); I.R. Cooke and M. Deserno, J. Chem. Phys. 123, 224710 (2005).

  35. unstable fluid phase temperature gel-phase(s) attraction range Today: Long-ranged attractions “save” the system some entropy! I.R. Cooke, K. Kremer, M. Deserno, Phys. Rev. E 72, 011506 (2005); I.R. Cooke and M. Deserno, J. Chem. Phys. 123, 224710 (2005).

  36. unstable fluid phase temperature gel-phase(s) attraction range Today: A.P. Gast, C.K. Hall, and W.B. Russel, J. Coll. Interface Sci. 96, 251 (1983); M.H.J. Hagen, D. Frenkel, J. Chem. Phys. 101, 4093 (1994); A.A. Louis, Phil. Trans. R. Soc. Lond. A 359, 939 (2001). Long-ranged attractions “save” the system some entropy! I.R. Cooke, K. Kremer, M. Deserno, Phys. Rev. E 72, 011506 (2005); I.R. Cooke and M. Deserno, J. Chem. Phys. 123, 224710 (2005).

  37. unstable fluid phase temperature gel-phase(s) attraction range Today: A.P. Gast, C.K. Hall, and W.B. Russel, J. Coll. Interface Sci. 96, 251 (1983); M.H.J. Hagen, D. Frenkel, J. Chem. Phys. 101, 4093 (1994); A.A. Louis, Phil. Trans. R. Soc. Lond. A 359, 939 (2001). Long-ranged attractions “save” the system some entropy! Shape of CG potential is qualitatively important! I.R. Cooke, K. Kremer, M. Deserno, Phys. Rev. E 72, 011506 (2005); I.R. Cooke and M. Deserno, J. Chem. Phys. 123, 224710 (2005).

  38. Illustrations: • Material properties • Adsorption to a substrate • Lipid curvature effects • Peptide-induced pore formation • Lipid mixtures • Protein-induced budding

  39. Illustrations: • Material properties • Adsorption to a substrate • Lipid curvature effects • Peptide-induced pore formation • Lipid mixtures • Protein-induced budding

  40. Material properties

  41. Material properties Probably most important: bending modulus

  42. Material properties Probably most important: bending modulus From fluctuations From deformations Can be determined in two very different ways

  43. Material properties Probably most important: bending modulus From fluctuations From deformations

  44. Material properties Probably most important: bending modulus From fluctuations From deformations energy of cylinder force to hold it V. Harmandaris and M. Deserno, J. Chem. Phys. 125, 204905 (2006)

  45. Both ways give the same answer Shows that Helfrich theory works up to extremely large curvature Material properties Probably most important: bending modulus From fluctuations From deformations energy of cylinder force to hold it V. Harmandaris and M. Deserno, J. Chem. Phys. 125, 204905 (2006)

  46. Both ways give the same answer Shows that Helfrich theory works up to extremely large curvature Material properties Probably most important: bending modulus From fluctuations From deformations energy of cylinder  force to hold it ~ 3…30kBT V. Harmandaris and M. Deserno, J. Chem. Phys. 125, 204905 (2006)

  47. Other Material properties Expansion modulus ~ 100 dyn/cm Line tension ~ 10 pN I.R. Cooke and M. Deserno, J. Chem. Phys. 123, 224710 (2005).

  48. Other Material properties Expansion modulus ~ 100 dyn/cm Line tension ~ 10 pN thermal expansivity ~ 2×10-3 K-1 I.R. Cooke and M. Deserno, J. Chem. Phys. 123, 224710 (2005).

  49. Illustrations: • Material properties • Adsorption to a substrate • Lipid curvature effects • Peptide-induced pore formation • Lipid mixtures • Protein-induced budding

  50. Adsorption to a substrate picture: M.I. Hoopes bilayer substrate M.I. Hoopes, M. Deserno, M.L. Longo, and R. Faller, J. Chem. Phys. (in press)

More Related