Modeling of Nanostructures : Bionanosystems, Polymers, and Surfaces

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1 2008 Alberta Nanotech Showcase November 20, 2008 Maria Stepanova Research Officer Principal Investigator NINT Modeling of Nanostructures : Bionanosystems, Polymers, and Surfaces

2 We develop numeric tools for nanotechnology What for?... So that we can understand, predict, and direct structural organization in natural and engineered nanosystems How?... Mesoscale kinetic modeling, Kinetic Monte-Carlo, Self-consistent field theory (SCFT), Generalized Langevin dynamics, Multivariate analysis of molecular dynamics trajectories. Whenever possible, we parameterize our models through a multiscale approach combining into an integrated hierarchical system various levels of modeling, starting from molecular and atomic properties. Examples : Synthesis Nanopatterns Mesophases Nanodomains Dynamic structure of Nanocrystals in Polymers of amphiphilic in lipid membranes of Proteins surfactants See our posters! 2

3 Mesophases of Amphiphilic Surfactants Dispersion aids and emulsifiers; Components in detergents, shampoos, soaps, and more... A surfactant molecule contains a hydrophilic head group and hydrophobic tail. In water surfactants form micelles, lamellae, and mesophases. DPPC Branched phospholipids are the major component of bio-membranes 3

4 Equilibrium Morphologies of Branched Lipids at Air-Water Interfaces Branched Initial distribution: lipid random mix of lipids, water, and air A self-consistent iterative procedure (SCFT) generates equilibrium distributions of the components ϕ Water Air 0.4 Lipid tail 0.2 Lipid head z Lipid membranes self-organize at air-water interfaces Innovations : Extension and application of the SCFT to handle monolayers of branched lipids at air/water interfaces Capacity : Analyse mesophases in surfactants ; identify function of their components [ Y. Lauw, A. Kovalenko, and M. Stepanova, J. Phys. Chem. B 112 (2008) 2119; K.P. Santo, A. Kovalenko and M. Stepanova (2008) to be submitted ] Concentration of Lipid Increases 4

5 Nano-Phase Domains in Lung Surfactants Surfactants cover the surface of lung alveoli. These surfactants maintain low surface tension during breathing. Dipalmitoylphosphatidylcholine (DPPC) is the most abundant component in lung surfactants B. Piknova et. al., Curr..Opinion in Struct. Biol. 12 (2002)487 When compressed, membranes of liquid DPPC form micro- and nanodomains of gel phase. This process may be basic for the lung' function. But quantitative understanding of the kinetics is not available. Phase separation in compressed DPPC film Adapted from [A. Cruz et. al. Langmuir, 21 (2005) 5349 ] 5

6 Kinetic Modeling of Nanodomains in Monolayers of DPPC A quantitative model imitates kinetics of a breath-like process when the surface area changes Diffusion of DPPC Drift by mean force Film continuity Excluded volume Long-range attraction EXAMPLES DPPC phase-separates spontaneously 100 nm Dark gel (condensed) Light liquid (expanded) The morphology change is reversible 0.05 ms 0.5 ms 5 ms Morphology is dramatically area-dependent Equilibration 2 ms Area reduction: 10% 15% 15% Total area of gel nanodomains equilibrates over a few ms, e.g. is highly efficient for maintaining low surface tension in lungs. The size of gel nanodomains tends to increase slowly, and is kinetically limited. Micron-scale domains may arise from fluctuations in area density of DPPC molecules. 6

7 Structure-Function Relation in Proteins Proteins are necessary for virtually every activity in cells They are also the most variable and complex molecules General rules behind proteins folding structure, which define their function (or dysfunction) remain largely unknown 7

8 Molecular Dynamics Modeling represents molecular motion in atomic detail All atoms in protein Analysis of structure Raw MD data are highly redundant and unsorted Need extracting a manageable number of representative characteristics

9 ...for protein conformations? We develop advanced numeric methods to characterize structural properties of proteins 9 Image adapted from

10 Framework : Modeling of Coarse-Grained Dynamics in Proteins 1. MD trajectory generated ~0.1 ns 2. Essential collective coordinates identified 3. Generalized Langevin equations (GLE) derived 4. Dynamic structural domains identified Background : Essential coordinates: A. Kitao, F. Hirata, and N. Go, Chem. Phys. 158 (1991) 447 Mori projection method: H. Mori, Prog. Theor. Phys. 33, 423 (1965); ibid, Prog. Theor. Phys. 34, 399 (1965). Innovations : Rigorous definition of the essential variables in GLE for proteins Definition of dynamic domains and chain flexibility from direction cosines of principal components Reference-free identification of structural subunits in proteins [ M. Stepanova, Phys. Rev. E 76 (2007) ; Condens. Matter Phys. 10 (2007) 441 ] 10

11 Example: Dynamic domains in protein G Protein G is often used to bind, detect, and/or characterize antibodies Well-studied protein with known structure Classic "benchmark" molecule for structural analysis 3 largest domains in protein G The domains identify compact groups of atoms although the spatial proximity is not required by the technique There is a close ( but not a 100% ) match with secondary structure The domains indicate regions of relative rigidity in the molecule Off-domain regions are relatively soft Colors indicate large domains Gromacs trajectory provided by Mark Berjanskii (2006) 11

12 The predicted domain system in protein G matches NMR experiments Large domains correspond to high levels of model-free order parameter S 2 Colors indicate large domains Adapted from [ M.J. Stone et. al., JACS., 123 (2001) 185 ] The dynamic domain analysis can be employed to interpret NMR data 12

13 Study of Structural Domains and Main-Chain Flexibility of Prion Proteins Unfolding and misfolding of prion proteins is the anticipated reason behind the prion diseases The mechanism of unfolding/misfolding is not understood clearly enough The dynamic domain analysis may be indicative of the route of unfolding Collaboration Dr. D. Wishart [ N. Blinov, M. Berjanskii, D. Wishart, and M. Stepanova (2008), submitted ] 13

14 Outlook Basic Studies Structure of biomembranes and function of their components Folding and dynamic structure of proteins Applications: Environment Exposure and toxic impact of nanoparticles Applications: Biotechnologies Detergents, foams, soaps, etc., Protein engineering, Drug discovery, Bioinformatics, and more... 14

15 Contact : Maria Stepanova, PhD, Dr.Sci. National Institute for Nanotechnology NRC Saskatchewan Drive, Edmonton (AB) T6G 2M9 Tel.: maria.stepanova@nrc-cnrc.gc.ca 15