Systematic coarse-graining using structural information : applications to lipid membranes
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Doctoral thesis (article-based)
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Date
2009
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Language
en
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Verkkokirja (5313 KB, 68 s.)
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TKK dissertations,
159
Abstract
Within last 20 years, advances in computational power and methodology have made computer simulations an integral part of studies of biomolecular systems. Simulations on all-atom level are routinely used to study, e.g., microscopic details of lipid aggregates and proteins. However, many phenomena are still outside the reach of all-atom simulations, and coarser models are needed. Detailed information from all-atom models can provide input data for parameterizing coarse-grained (CG) models. Techniques for such parameterization are called systematic coarse-graining methods, and can be based, e.g., on matching forces or structural information between the two resolutions. The main part of this dissertation employs inverse Monte Carlo (IMC) for constructing CG models for a lipid membrane containing dipalmitoylphosphatidylcholine (DPPC) and cholesterol. Three 2D models are constructed at different levels of resolution, in each case matching the radial distribution functions (RDFs) of the CG model to those from atom-scale simulations. The main results are the presence of cholesterol-rich and cholesterol-poor domains at intermediate cholesterol concentrations and the presence of strong tail density fluctuations at low cholesterol concentrations. The former agrees with the experimental studies of the system, while the latter was confirmed through atom-scale simulations. Accurate quantitative studies were restricted by transferability problems in all the CG models; hence, focus is on comparing the different models and critical discussion of the RDF inversion as a basis for coarse-graining. The IMC method is also improved by increasing its tolerance to statistical noise, as well as through inclusion of a virial pressure constraint and generalization to models where particles have internal degrees of freedom. The dissertation also discusses the analysis of individual lipid conformations from atom-scale simulations using self-organizing maps (SOMs), as well as the use of SOMs in coarse-graining. Atomistic simulations provide a vast amount of data, and direct analysis may be difficult. SOM, an unsupervised machine learning method, is studied as an alternative to more traditional analysis. Focus is on determining good parameters for the method and on qualitative analysis based on the good visualization properties of SOM. The internal dynamics of the molecules are also analyzed using SOMs for visualization. A bilayer of palmitoyllinoleoyl-PC (PLPC) is used as a model system.Description
Keywords
coarse-graining, computer simulation, statistical physics, self-organizing maps, cholesterol
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Parts
- [Publication 1]: Teemu Murtola, Emma Falck, Michael Patra, Mikko Karttunen, and Ilpo Vattulainen. 2004. Coarse-grained model for phospholipid/cholesterol bilayer. The Journal of Chemical Physics, volume 121, number 18, pages 9156-9165. © 2004 American Institute of Physics. By permission.
- [Publication 2]: Teemu Murtola, Emma Falck, Mikko Karttunen, and Ilpo Vattulainen. 2007. Coarse-grained model for phospholipid/cholesterol bilayer employing inverse Monte Carlo with thermodynamic constraints. The Journal of Chemical Physics, volume 126, number 7, 075101. © 2007 American Institute of Physics. By permission.
- [Publication 3]: Teemu Murtola, Mikko Karttunen, and Ilpo Vattulainen. 2009. Systematic coarse-graining from structure using internal states: application to phospholipid / cholesterol bilayer. Helsinki Institute of Physics preprint HIP–2009–08/TH. © 2009 by authors and © 2009 American Institute of Physics. By permission.
- [Publication 4]: Teemu Murtola, Tomasz Róg, Emma Falck, Mikko Karttunen, and Ilpo Vattulainen. 2006. Transient ordered domains in single-component phospholipid bilayers. Physical Review Letters, volume 97, number 23, 238102. © 2006 American Physical Society. By permission.
- [Publication 5]: Teemu Murtola, Mikko Kupiainen, Emma Falck, and Ilpo Vattulainen. 2007. Conformational analysis of lipid molecules by self-organizing maps. The Journal of Chemical Physics, volume 126, number 5, 054707. © 2007 American Institute of Physics. By permission.