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Strongly coarse-grained membrane simulations

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Markus DesernoCarnegie Mellon UniversityStrongly coarse-grained membrane simulationsDepartment of PhysicsOctober 19, 2011International Workshop on Coarse Grained Biomolecula Modeling, October 17–21, 2011, Lausanne, SwitzerlandIra Cooke, Benedict Reynwar, Gregoria Illya,Vagelis Harmandaris, Kurt Kremerwith many thanks toand our afternoon expertsMingyang Hu and Patrick DigginsIf you haven’t figured that out by now,you should ask for your money back.Why coarse-graining?No, seriously.Why coarse graining?EfficiencyWhy coarse-graining?InsightEfficiencyDoes that mean just “bigger systems”?No. Not just.Lindahl, E. & Edholm, O. Mesoscopic undulations and thickness fluctuations in lipid bilayersfrom molecular dynamics simulations.Biophys. J. 79, 426-433 (2000).All-atom lipid bilayer20nm×20nm, 1024 lipids, 10nsWhat if we want a boxlength of L=200nm? How does computing effort scale with L?effort ~ L2 × L4 ~ L6Equilibration timeAmount of materialEfficiency20nm200nmMillion times more computationally expensive!20 doublings of computer power!20 x 2 years40 years(Moore’s law)I’ll be retired by then!(best case scenario)EfficiencyEfficiencyStated differently:The amount of material scales with the membrane area A. Using a domain decomposition scheme, this can (in the best case) be compensated by increasing the number of processors proportional to A.But the simulation time towards equilibration scales like A3. This still leaves an uncompensated factor of A2 that you must do more work or have faster chips or better ideas.EfficiencyCoarse graining cannot just help you to look at much bigger systems. It can help you to get well equilibrated data for somewhat bigger systems.If someone offers you 1000 times more computational power, you should make your membrane length ~3 times bigger and simulate it for ~100 time longer!EfficiencyCoarse graining cannot just help you to look at much bigger systems. It can help you to get well equilibrated data for somewhat bigger systems.(Unfortunately, the latter doesn’t look as obviously sexy.)(Is it better to have non-equilibrated data of an impressively big or complex system, or to rather have equilibrated data of a system that is not accurate or big enough?)Insight“The purpose of computation is insight, not numbers.”Richard W. Hamming (1915-1998)InsightAssume that there’s some biophysical problem that can only be solved by sifting through many Terabytes of all-atom simulation trajectories.This of course might happen!But if it does, how much have we understood of the problem, after we have done the simulation?As scientists we ought to be curious about how many Terabytes of detail we can throw away before we begin to model the system.Because our brains are finite.(Engineering, on the other hand, might be a whole different issue. Numbers often matter!)InsightCoarse graining is the art of throwing such supposedly unnecessary detail away.(In fact, I believe that Physics is the art of throwing unnecessary detail away)It’s an art.There’s no sure-fire way of getting it right.You throw the wrong stuff away, you’re doomed!Well, not really: If you make sure that your simulation is correct, then you have a falsifiable result! So you’re scientific!Today:I’ll illustrate a way to treat the mesoscopic regime in an efficient and insightful way.(OK, that’s a tall order.)• Generic top-down bead-spring• solvent free• only pair forces• robust & physically meaningfulI.R. Cooke, K. Kremer, M. Deserno, Phys. Rev. E 72, 011506 (2005);I.R. Cooke and M. Deserno, J. Chem. Phys. 123, 224710 (2005).Today:I’ll illustrate a way to treat the mesoscopic regime in an efficient and insightful way.(OK, that’s a tall order.)• Generic top-down bead-spring• solvent free• only pair forces• robust & physically meaningfulI.R. Cooke, K. Kremer, M. Deserno, Phys. Rev. E 72, 011506 (2005);I.R. Cooke and M. Deserno, J. Chem. Phys. 123, 224710 (2005). J.-M. Drouffe, A. C. Maggs, and S. Leibler, Science 254, 1353 (1991) H. Noguchi and M. Takasu, Phys. Rev. E 64, 041913 (2001) Z.-J. Wang and D. Frenkel, J. Chem. Phys. 122, 234711 (2005) H. Noguchi and G. Gompper, Phys. Rev. E 72, 021903 (2006) G. Ayton and G.A. Voth, Biophys. J. 83, 3357 (2002) O. Farago, J. Chem. Phys. 119, 396 (2003) G. Brannigan and F.L.H. Brown, J. Chem. Phys. 120, 1059 (2004) G. Brannigan, P.F. Philips, and F.L.H. Brown, Phys. Rev. E 72, 011915, (2005)Today:Physics based?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).Definitely Yes!But is there room for physical reasoning or physics-based effects in biology?Definitely Yes!I think:Why is “solvent free” good?membrane surfacesolvent bulkUnless you’re careful, you might end up simulating a finite size effect!Examplemembrane surfacesolvent bulk16,000 DPD lipids 4 beads per lipid.M. Laradji & P.B. Sunil KumarPhys. Rev. Lett. 93, 198105 (2004).64,000 degrees of freedom for lipids.But in total 1,536,000 particles in box!96% of simulation time spent with solvent!(They had a good reason for doing this. But do you, too?)DifficultiesImplicit solvent models are incredibly common and useful in polymer physics.Why has it taken so long for them to appear in the field of membrane research?☞ Polymers don’t first have to self assemble!One needs additional cohesion to make the lipids come together.☞ Fluidity has proven to be the major challenge.DifficultiesImplicit solvent models are incredibly common and useful in polymer physics.Why has it taken so long for them to appear in the field of membrane research?☞ Polymers don’t first have to self assemble!One needs additional cohesion to make the lipids come together.☞ Fluidity has proven to be the major challenge.weak attraction ➠ gas phasestrong attraction ➠ solid (gel) phaseno fluid phase inbetween !?!?Link three beadsMake lipid stiffNonbondedOur modelattraction rangetemperatureunstablefluid phasegel-phase(s)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).Long-ranged attractions “save” the system some entropy!Overall phase behaviorLJattraction rangetemperatureunstablefluid phasegel-phase(s)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).Long-ranged attractions “save” the system some entropy!A.P. Gast, C.K. Hall, and W.B. Russel,J.


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