875 resultados para Molecular Dynamics, Simulation, Modeling, Protein, Coarse Graining


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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Time correlation functions of current fluctuations were calculated by molecular dynamics (MD) simulations in order to investigate sound waves of high wavevectors in the glass-forming liquid Ca(NO3)(2)center dot 4H(2)O. Dispersion curves, omega(k), were obtained for longitudinal (LA) and transverse acoustic (TA) modes, and also for longitudinal optic (LO) modes. Spectra of LA modes calculated by MD simulations were modeled by a viscoelastic model within the memory function framework. The viscoelastic model is used to rationalize the change of slope taking place at k similar to 0.3 angstrom(-1) in the omega(k) curve of acoustic modes. For still larger wavevectors, mixing of acoustic and optic modes is observed. Partial time correlation functions of longitudinal mass currents were calculated separately for the ions and the water molecules. The wavevector dependence of excitation energies of the corresponding partial LA modes indicates the coexistence of a relatively stiff subsystem made of cations and anions, and a softer subsystem made of water molecules. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4751548]

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The Dengue has become a global public health threat, with over 100 million infections annually; to date there is no specific vaccine or any antiviral drug. The structures of the envelope (E) proteins of the four known serotype of the dengue virus (DENV) are already known, but there are insufficient molecular details of their structural behavior in solution in the distinct environmental conditions in which the DENVs are submitted, from the digestive tract of the mosquito up to its replication inside the host cell. Such detailed knowledge becomes important because of the multifunctional character of the E protein: it mediates the early events in cell entry, via receptor endocytosis and, as a class II protein, participates determinately in the process of membrane fusion. The proposed infection mechanism asserts that once in the endosome, at low pH, the E homodimers dissociate and insert into the endosomal lipid membrane, after an extensive conformational change, mainly on the relative arrangement of its three domains. In this work we employ all-atom explicit solvent Molecular Dynamics simulations to specify the thermodynamic conditions in that the E proteins are induced to experience extensive structural changes, such as during the process of reducing pH. We study the structural behavior of the E protein monomer at acid pH solution of distinct ionic strength. Extensive simulations are carried out with all the histidine residues in its full protonated form at four distinct ionic strengths. The results are analyzed in detail from structural and energetic perspectives, and the virtual protein movements are described by means of the principal component analyses. As the main result, we found that at acid pH and physiological ionic strength, the E protein suffers a major structural change; for lower or higher ionic strengths, the crystal structure is essentially maintained along of all extensive simulations. On the other hand, at basic pH, when all histidine residues are in the unprotonated form, the protein structure is very stable for ionic strengths ranging from 0 to 225 mM. Therefore, our findings support the hypothesis that the histidines constitute the hot points that induce configurational changes of E protein in acid pH, and give extra motivation to the development of new ideas for antivirus compound design.

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Background: The ZNF706 gene encodes a protein that belongs to the zinc finger family of proteins and was found to be highly expressed in laryngeal cancer, making the structure and function of ZNF706 worthy of investigation. In this study, we expressed and purified recombinant human ZNF706 that was suitable for structural analysis in Escherichia coli BL21(DH3). Findings: ZNF706 mRNA was extracted from a larynx tissue sample, and cDNA was ligated into a cloning vector using the TOPO method. ZNF706 protein was expressed according to the E. coli expression system procedures and was purified using a nickel-affinity column. The structural qualities of recombinant ZNF706 and quantification alpha, beta sheet, and other structures were obtained by spectroscopy of circular dichroism. ZNF706's structural modeling showed that it is composed of α-helices (28.3%), β-strands (19.4%), and turns (20.9%), in agreement with the spectral data from the dichroism analysis. Conclusions: We used circular dichroism and molecular modeling to examine the structure of ZNF706. The results suggest that human recombinant ZNF706 keeps its secondary structures and is appropriate for functional and structural studies. The method of expressing ZNF706 protein used in this study can be used to direct various functional and structural studies that will contribute to the understanding of its function as well as its relationship with other biological molecules and its putative role in carcinogenesis.

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This thesis is based on five papers addressing variance reduction in different ways. The papers have in common that they all present new numerical methods. Paper I investigates quantitative structure-retention relationships from an image processing perspective, using an artificial neural network to preprocess three-dimensional structural descriptions of the studied steroid molecules. Paper II presents a new method for computing free energies. Free energy is the quantity that determines chemical equilibria and partition coefficients. The proposed method may be used for estimating, e.g., chromatographic retention without performing experiments. Two papers (III and IV) deal with correcting deviations from bilinearity by so-called peak alignment. Bilinearity is a theoretical assumption about the distribution of instrumental data that is often violated by measured data. Deviations from bilinearity lead to increased variance, both in the data and in inferences from the data, unless invariance to the deviations is built into the model, e.g., by the use of the method proposed in paper III and extended in paper IV. Paper V addresses a generic problem in classification; namely, how to measure the goodness of different data representations, so that the best classifier may be constructed. Variance reduction is one of the pillars on which analytical chemistry rests. This thesis considers two aspects on variance reduction: before and after experiments are performed. Before experimenting, theoretical predictions of experimental outcomes may be used to direct which experiments to perform, and how to perform them (papers I and II). After experiments are performed, the variance of inferences from the measured data are affected by the method of data analysis (papers III-V).

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Ion channels are protein molecules, embedded in the lipid bilayer of the cell membranes. They act as powerful sensing elements switching chemicalphysical stimuli into ion-fluxes. At a glance, ion channels are water-filled pores, which can open and close in response to different stimuli (gating), and one once open select the permeating ion species (selectivity). They play a crucial role in several physiological functions, like nerve transmission, muscular contraction, and secretion. Besides, ion channels can be used in technological applications for different purpose (sensing of organic molecules, DNA sequencing). As a result, there is remarkable interest in understanding the molecular determinants of the channel functioning. Nowadays, both the functional and the structural characteristics of ion channels can be experimentally solved. The purpose of this thesis was to investigate the structure-function relation in ion channels, by computational techniques. Most of the analyses focused on the mechanisms of ion conduction, and the numerical methodologies to compute the channel conductance. The standard techniques for atomistic simulation of complex molecular systems (Molecular Dynamics) cannot be routinely used to calculate ion fluxes in membrane channels, because of the high computational resources needed. The main step forward of the PhD research activity was the development of a computational algorithm for the calculation of ion fluxes in protein channels. The algorithm - based on the electrodiffusion theory - is computational inexpensive, and was used for an extensive analysis on the molecular determinants of the channel conductance. The first record of ion-fluxes through a single protein channel dates back to 1976, and since then measuring the single channel conductance has become a standard experimental procedure. Chapter 1 introduces ion channels, and the experimental techniques used to measure the channel currents. The abundance of functional data (channel currents) does not match with an equal abundance of structural data. The bacterial potassium channel KcsA was the first selective ion channels to be experimentally solved (1998), and after KcsA the structures of four different potassium channels were revealed. These experimental data inspired a new era in ion channel modeling. Once the atomic structures of channels are known, it is possible to define mathematical models based on physical descriptions of the molecular systems. These physically based models can provide an atomic description of ion channel functioning, and predict the effect of structural changes. Chapter 2 introduces the computation methods used throughout the thesis to model ion channels functioning at the atomic level. In Chapter 3 and Chapter 4 the ion conduction through potassium channels is analyzed, by an approach based on the Poisson-Nernst-Planck electrodiffusion theory. In the electrodiffusion theory ion conduction is modeled by the drift-diffusion equations, thus describing the ion distributions by continuum functions. The numerical solver of the Poisson- Nernst-Planck equations was tested in the KcsA potassium channel (Chapter 3), and then used to analyze how the atomic structure of the intracellular vestibule of potassium channels affects the conductance (Chapter 4). As a major result, a correlation between the channel conductance and the potassium concentration in the intracellular vestibule emerged. The atomic structure of the channel modulates the potassium concentration in the vestibule, thus its conductance. This mechanism explains the phenotype of the BK potassium channels, a sub-family of potassium channels with high single channel conductance. The functional role of the intracellular vestibule is also the subject of Chapter 5, where the affinity of the potassium channels hEag1 (involved in tumour-cell proliferation) and hErg (important in the cardiac cycle) for several pharmaceutical drugs was compared. Both experimental measurements and molecular modeling were used in order to identify differences in the blocking mechanism of the two channels, which could be exploited in the synthesis of selective blockers. The experimental data pointed out the different role of residue mutations in the blockage of hEag1 and hErg, and the molecular modeling provided a possible explanation based on different binding sites in the intracellular vestibule. Modeling ion channels at the molecular levels relates the functioning of a channel to its atomic structure (Chapters 3-5), and can also be useful to predict the structure of ion channels (Chapter 6-7). In Chapter 6 the structure of the KcsA potassium channel depleted from potassium ions is analyzed by molecular dynamics simulations. Recently, a surprisingly high osmotic permeability of the KcsA channel was experimentally measured. All the available crystallographic structure of KcsA refers to a channel occupied by potassium ions. To conduct water molecules potassium ions must be expelled from KcsA. The structure of the potassium-depleted KcsA channel and the mechanism of water permeation are still unknown, and have been investigated by numerical simulations. Molecular dynamics of KcsA identified a possible atomic structure of the potassium-depleted KcsA channel, and a mechanism for water permeation. The depletion from potassium ions is an extreme situation for potassium channels, unlikely in physiological conditions. However, the simulation of such an extreme condition could help to identify the structural conformations, so the functional states, accessible to potassium ion channels. The last chapter of the thesis deals with the atomic structure of the !- Hemolysin channel. !-Hemolysin is the major determinant of the Staphylococcus Aureus toxicity, and is also the prototype channel for a possible usage in technological applications. The atomic structure of !- Hemolysin was revealed by X-Ray crystallography, but several experimental evidences suggest the presence of an alternative atomic structure. This alternative structure was predicted, combining experimental measurements of single channel currents and numerical simulations. This thesis is organized in two parts, in the first part an overview on ion channels and on the numerical methods adopted throughout the thesis is provided, while the second part describes the research projects tackled in the course of the PhD programme. The aim of the research activity was to relate the functional characteristics of ion channels to their atomic structure. In presenting the different research projects, the role of numerical simulations to analyze the structure-function relation in ion channels is highlighted.

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The study of protein fold is a central problem in life science, leading in the last years to several attempts for improving our knowledge of the protein structures. In this thesis this challenging problem is tackled by means of molecular dynamics, chirality and NMR studies. In the last decades, many algorithms were designed for the protein secondary structure assignment, which reveals the local protein shape adopted by segments of amino acids. In this regard, the use of local chirality for the protein secondary structure assignment was demonstreted, trying to correlate as well the propensity of a given amino acid for a particular secondary structure. The protein fold can be studied also by Nuclear Magnetic Resonance (NMR) investigations, finding the average structure adopted from a protein. In this context, the effect of Residual Dipolar Couplings (RDCs) in the structure refinement was shown, revealing a strong improvement of structure resolution. A wide extent of this thesis is devoted to the study of avian prion protein. Prion protein is the main responsible of a vast class of neurodegenerative diseases, known as Bovine Spongiform Encephalopathy (BSE), present in mammals, but not in avian species and it is caused from the conversion of cellular prion protein to the pathogenic misfolded isoform, accumulating in the brain in form of amiloyd plaques. In particular, the N-terminal region, namely the initial part of the protein, is quite different between mammal and avian species but both of them contain multimeric sequences called Repeats, octameric in mammals and hexameric in avians. However, such repeat regions show differences in the contained amino acids, in particular only avian hexarepeats contain tyrosine residues. The chirality analysis of avian prion protein configurations obtained from molecular dynamics reveals a high stiffness of the avian protein, which tends to preserve its regular secondary structure. This is due to the presence of prolines, histidines and especially tyrosines, which form a hydrogen bond network in the hexarepeat region, only possible in the avian protein, and thus probably hampering the aggregation.

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From the perspective of a new-generation opto-electronic technology based on organic semiconductors, a major objective is to achieve a deep and detailed knowledge of the structure-property relationships, in order to optimize the electronic, optical, and charge transport properties by tuning the chemical-physical characteristics of the compounds. The purpose of this dissertation is to contribute to such understanding, through suitable theoretical and computational studies. Precisely, the structural, electronic, optical, and charge transport characteristics of several promising organic materials recently synthesized are investigated by means of an integrated approach encompassing quantum-chemical calculations, molecular dynamics and kinetic Monte Carlo simulations. Particular care is addressed to the rationalization of optical and charge transport properties in terms of both intra- and intermolecular features. Moreover, a considerable part of this project involves the development of a home-made set of procedures and parts of software code required to assist the modeling of charge transport properties in the framework of the non-adiabatic hopping mechanism applied to organic crystalline materials. As a first part of my investigations, I mainly discuss the optical, electronic, and structural properties of several core-extended rylene derivatives, which can be regarded to as model compounds for graphene nanoribbons. Two families have been studied, consisting in bay-linked perylene bisimide oligomers and N-annulated rylenes. Beside rylene derivatives, my studies also concerned electronic and spectroscopic properties of tetracene diimides, quinoidal oligothiophenes, and oxygen doped picene. As an example of device application, I studied the structural characteristics governing the efficiency of resistive molecular memories based on a derivative of benzoquinone. Finally, as a second part of my investigations, I concentrate on the charge transport properties of perylene bisimides derivatives. Precisely, a comprehensive study of the structural and thermal effects on the charge transport of several core-twisted chlorinated and fluoro-alkylated perylene bisimide n-type semiconductors is presented.

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We have modeled various soft-matter systems with molecular dynamics (MD) simulations. The first topic concerns liquid crystal (LC) biaxial nematic (Nb) phases, that can be possibly used in fast displays. We have investigated the phase organization of biaxial Gay-Berne (GB) mesogens, considering the effects of the orientation, strength and position of a molecular dipole. We have observed that for systems with a central dipole, nematic biaxial phases disappear when increasing dipole strength, while for systems characterized by an offset dipole, the Nb phase is stabilized at very low temperatures. In a second project, in view of their increasing importance as nanomaterials in LC phases, we are developing a DNA coarse-grained (CG) model, in which sugar and phosphate groups are represented with Lennard-Jones spheres, while bases with GB ellipsoids. We have obtained shape, position and orientation parameters for each bead, to best reproduce the atomistic structure of a B-DNA helix. Starting from atomistic simulations results, we have completed a first parametrization of the force field terms, accounting for bonded (bonds, angles and dihedrals) and non-bonded interactions (H-bond and stacking). We are currently validating the model, by investigating stability and melting temperature of various sequences. Finally, in a third project, we aim to explain the mechanism of enantiomeric discrimination due to the presence of a chiral helix of poly(gamma-benzyl L-glutamate) (PBLG), in solution of dimethylformamide (DMF), interacting with chiral or pro-chiral molecules (in our case heptyl butyrate, HEP), after tuning properly an atomistic force field (AMBER). We have observed that DMF and HEP molecules solvate uniformly the PBLG helix, but the pro-chiral solute is on average found closer to the helix with respect to the DMF. The solvent presents a faster isotropic diffusion, twice as HEP, also indicating a stronger interaction of the solute with the helix.

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The ability of block copolymers to spontaneously self-assemble into a variety of ordered nano-structures not only makes them a scientifically interesting system for the investigation of order-disorder phase transitions, but also offers a wide range of nano-technological applications. The architecture of a diblock is the most simple among the block copolymer systems, hence it is often used as a model system in both experiment and theory. We introduce a new soft-tetramer model for efficient computer simulations of diblock copolymer melts. The instantaneous non-spherical shape of polymer chains in molten state is incorporated by modeling each of the two blocks as two soft spheres. The interactions between the spheres are modeled in a way that the diblock melt tends to microphase separate with decreasing temperature. Using Monte Carlo simulations, we determine the equilibrium structures at variable values of the two relevant control parameters, the diblock composition and the incompatibility of unlike components. The simplicity of the model allows us to scan the control parameter space in a completeness that has not been reached in previous molecular simulations.The resulting phase diagram shows clear similarities with the phase diagram found in experiments. Moreover, we show that structural details of block copolymer chains can be reproduced by our simple model.We develop a novel method for the identification of the observed diblock copolymer mesophases that formalizes the usual approach of direct visual observation,using the characteristic geometry of the structures. A cluster analysis algorithm is used to determine clusters of each component of the diblock, and the number and shape of the clusters can be used to determine the mesophase.We also employ methods from integral geometry for the identification of mesophases and compare their usefulness to the cluster analysis approach.To probe the properties of our model in confinement, we perform molecular dynamics simulations of atomistic polyethylene melts confined between graphite surfaces. The results from these simulations are used as an input for an iterative coarse-graining procedure that yields a surface interaction potential for the soft-tetramer model. Using the interaction potential derived in that way, we perform an initial study on the behavior of the soft-tetramer model in confinement. Comparing with experimental studies, we find that our model can reflect basic features of confined diblock copolymer melts.

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Organic semiconductors with the unique combination of electronic and mechanical properties may offer cost-effective ways of realizing many electronic applications, e.g. large-area flexible displays, printed integrated circuits and plastic solar cells. In order to facilitate the rational compound design of organic semiconductors, it is essential to understand relevant physical properties e.g. charge transport. This, however, is not straightforward, since physical models operating on different time and length scales need to be combined. First, the material morphology has to be known at an atomistic scale. For this atomistic molecular dynamics simulations can be employed, provided that an atomistic force field is available. Otherwise it has to be developed based on the existing force fields and first principle calculations. However, atomistic simulations are typically limited to the nanometer length- and nanosecond time-scales. To overcome these limitations, systematic coarse-graining techniques can be used. In the first part of this thesis, it is demonstrated how a force field can be parameterized for a typical organic molecule. Then different coarse-graining approaches are introduced together with the analysis of their advantages and problems. When atomistic morphology is available, charge transport can be studied by combining the high-temperature Marcus theory with kinetic Monte Carlo simulations. The approach is applied to the hole transport in amorphous films of tris(8-hydroxyquinoline)aluminium (Alq3). First the influence of the force field parameters and the corresponding morphological changes on charge transport is studied. It is shown that the energetic disorder plays an important role for amorphous Alq3, defining charge carrier dynamics. Its spatial correlations govern the Poole-Frenkel behavior of the charge carrier mobility. It is found that hole transport is dispersive for system sizes accessible to simulations, meaning that calculated mobilities depend strongly on the system size. A method for extrapolating calculated mobilities to the infinite system size is proposed, allowing direct comparison of simulation results and time-of-flight experiments. The extracted value of the nondispersive hole mobility and its electric field dependence for amorphous Alq3 agree well with the experimental results.

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In dieser Arbeit wird ein vergröbertes (engl. coarse-grained, CG) Simulationsmodell für Peptide in wässriger Lösung entwickelt. In einem CG Verfahren reduziert man die Anzahl der Freiheitsgrade des Systems, so dass manrngrössere Systeme auf längeren Zeitskalen untersuchen kann. Die Wechselwirkungspotentiale des CG Modells sind so aufgebaut, dass die Peptid Konformationen eines höher aufgelösten (atomistischen) Modells reproduziert werden.rnIn dieser Arbeit wird der Einfluss unterschiedlicher bindender Wechsel-rnwirkungspotentiale in der CG Simulation untersucht, insbesondere daraufhin,rnin wie weit das Konformationsgleichgewicht der atomistischen Simulation reproduziert werden kann. Im CG Verfahren verliert man per Konstruktionrnmikroskopische strukturelle Details des Peptids, zum Beispiel, Korrelationen zwischen Freiheitsgraden entlang der Peptidkette. In der Dissertationrnwird gezeigt, dass diese “verlorenen” Eigenschaften in einem Rückabbildungsverfahren wiederhergestellt werden können, in dem die atomistischen Freiheitsgrade wieder in die CG-Strukturen eingefügt werden. Dies gelingt, solange die Konformationen des CG Modells grundsätzlich gut mit der atomistischen Ebene übereinstimmen. Die erwähnten Korrelationen spielen einerngrosse Rolle bei der Bildung von Sekundärstrukturen und sind somit vonrnentscheidender Bedeutung für ein realistisches Ensemble von Peptidkonformationen. Es wird gezeigt, dass für eine gute Übereinstimmung zwischen CG und atomistischen Kettenkonformationen spezielle bindende Wechselwirkungen wie zum Beispiel 1-5 Bindungs- und 1,3,5-Winkelpotentiale erforderlich sind. Die intramolekularen Parameter (d.h. Bindungen, Winkel, Torsionen), die für kurze Oligopeptide parametrisiert wurden, sind übertragbarrnauf längere Peptidsequenzen. Allerdings können diese gebundenen Wechselwirkungen nur in Kombination mit solchen nichtbindenden Wechselwirkungspotentialen kombiniert werden, die bei der Parametrisierung verwendet werden, sind also zum Beispiel nicht ohne weiteres mit einem andere Wasser-Modell kombinierbar. Da die Energielandschaft in CG-Simulationen glatter ist als im atomistischen Modell, gibt es eine Beschleunigung in der Dynamik. Diese Beschleunigung ist unterschiedlich für verschiedene dynamische Prozesse, zum Beispiel für verschiedene Arten von Bewegungen (Rotation und Translation). Dies ist ein wichtiger Aspekt bei der Untersuchung der Kinetik von Strukturbildungsprozessen, zum Beispiel Peptid Aggregation.rn

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Amphiphile Peptide, Pro-Glu-(Phe-Glu)n-Pro, Pro-Asp-(Phe-Asp)n-Pro, und Phe-Glu-(Phe-Glu)n-Phe, können so aus n alternierenden Sequenzen von hydrophoben und hydrophilen Aminosäuren konstruiert werden, dass sie sich in Monolagen an der Luft-Wasser Grenzfläche anordnen. In biologischen Systemen können Strukturen an der organisch-wässrigen Grenzfläche als Matrix für die Kristallisation von Hydroxyapatit dienen, ein Vorgang der für die Behandlung von Osteoporose verwendet werden kann. In der vorliegenden Arbeit wurden Computersimulationenrneingesetzt, um die Strukturen und die zugrunde liegenden Wechselwirkungen welche die Aggregation der Peptide auf mikroskopischer Ebene steuern, zu untersuchen. Atomistische Molekulardynamik-Simulationen von einzelnen Peptidsträngen zeigen, dass sie sich leicht an der Luft-Wasser Grenzfläche anordnen und die Fähigkeit haben, sich in β-Schleifen zu falten, selbst für relativ kurze Peptidlängen (n = 2). Seltene Ereignisse wie diese (i.e. Konformationsänderungen) erfordern den Einsatz fortgeschrittener Sampling-Techniken. Hier wurde “Replica Exchange” Molekulardynamik verwendet um den Einfluss der Peptidsequenzen zu untersuchen. Die Simulationsergebnisse zeigten, dass Peptide mit kürzeren azidischen Seitenketten (Asp vs. Glu) gestrecktere Konformationen aufwiesen als die mit längeren Seitenketten, die in der Lage waren die Prolin-Termini zu erreichen. Darüber hinaus zeigte sich, dass die Prolin-Termini (Pro vs. Phe) notwendig sind, um eine 2D-Ordnung innerhalb derrnAggregate zu erhalten. Das Peptid Pro-Asp-(Phe-Asp)n-Pro, das beide dieser Eigenschaften enthält, zeigt das geordnetste Verhalten, eine geringe Verdrehung der Hauptkette, und ist in der Lage die gebildeten Aggregate durch Wasserstoffbrücken zwischen den sauren Seitenketten zu stabilisieren. Somit ist dieses Peptid am besten zur Aggregation geeignet. Dies wurde auch durch die Beurteilung der Stabilität von experimentnah-aufgesetzten Peptidaggregaten, sowie der Neigung einzelner Peptide zur Selbstorganisation von anfänglich ungeordneten Konfigurationen unterstützt. Da atomistische Simulationen nur auf kleine Systemgrößen und relativ kurze Zeitskalen begrenzt sind, wird ein vergröbertes Modell entwickelt damit die Selbstorganisation auf einem größeren Maßstab studiert werden kann. Da die Selbstorganisation an der Grenzfläche vonrnInteresse ist, wurden existierenden Vergröberungsmethoden erweitert, um nicht-gebundene Potentiale für inhomogene Systeme zu bestimmen. Die entwickelte Methode ist analog zur iterativen Boltzmann Inversion, bildet aber das Update für das Interaktionspotential basierend auf der radialen Verteilungsfunktion in einer Slab-Geometrie und den Breiten des Slabs und der Grenzfläche. Somit kann ein Kompromiss zwischen der lokalen Flüssigketsstruktur und den thermodynamischen Eigenschaften der Grenzfläche erreicht werden. Die neue Methode wurde für einen Wasser- und einen Methanol-Slab im Vakuum demonstriert, sowie für ein einzelnes Benzolmolekül an der Vakuum-Wasser Grenzfläche, eine Anwendung die von besonderer Bedeutung in der Biologie ist, in der oft das thermodynamische/Grenzflächenpolymerisations-Verhalten zusätzlich der strukturellen Eigenschaften des Systems erhalten werden müssen. Daraufrnbasierend wurde ein vergröbertes Modell über einen Fragment-Ansatz parametrisiert und die Affinität des Peptids zur Vakuum-Wasser Grenzfläche getestet. Obwohl die einzelnen Fragmente sowohl die Struktur als auch die Wahrscheinlichkeitsverteilungen an der Grenzfläche reproduzierten, diffundierte das Peptid als Ganzes von der Grenzfläche weg. Jedoch führte eine Reparametrisierung der nicht-gebundenen Wechselwirkungen für eines der Fragmente der Hauptkette in einem Trimer dazu, dass das Peptid an der Grenzfläche blieb. Dies deutet darauf hin, dass die Kettenkonnektivität eine wichtige Rolle im Verhalten des Petpids an der Grenzfläche spielt.

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Sub-grid scale (SGS) models are required in order to model the influence of the unresolved small scales on the resolved scales in large-eddy simulations (LES), the flow at the smallest scales of turbulence. In the following work two SGS models are presented and deeply analyzed in terms of accuracy through several LESs with different spatial resolutions, i.e. grid spacings. The first part of this thesis focuses on the basic theory of turbulence, the governing equations of fluid dynamics and their adaptation to LES. Furthermore, two important SGS models are presented: one is the Dynamic eddy-viscosity model (DEVM), developed by \cite{germano1991dynamic}, while the other is the Explicit Algebraic SGS model (EASSM), by \cite{marstorp2009explicit}. In addition, some details about the implementation of the EASSM in a Pseudo-Spectral Navier-Stokes code \cite{chevalier2007simson} are presented. The performance of the two aforementioned models will be investigated in the following chapters, by means of LES of a channel flow, with friction Reynolds numbers $Re_\tau=590$ up to $Re_\tau=5200$, with relatively coarse resolutions. Data from each simulation will be compared to baseline DNS data. Results have shown that, in contrast to the DEVM, the EASSM has promising potentials for flow predictions at high friction Reynolds numbers: the higher the friction Reynolds number is the better the EASSM will behave and the worse the performances of the DEVM will be. The better performance of the EASSM is contributed to the ability to capture flow anisotropy at the small scales through a correct formulation for the SGS stresses. Moreover, a considerable reduction in the required computational resources can be achieved using the EASSM compared to DEVM. Therefore, the EASSM combines accuracy and computational efficiency, implying that it has a clear potential for industrial CFD usage.

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EPON 862 is an epoxy resin which is cured with the hardening agent DETDA to form a crosslinked epoxy polymer and is used as a component in modern aircraft structures. These crosslinked polymers are often exposed to prolonged periods of temperatures below glass transition range which cause physical aging to occur. Because physical aging can compromise the performance of epoxies and their composites and because experimental techniques cannot provide all of the necessary physical insight that is needed to fully understand physical aging, efficient computational approaches to predict the effects of physical aging on thermo-mechanical properties are needed. In this study, Molecular Dynamics and Molecular Minimization simulations are being used to establish well-equilibrated, validated molecular models of the EPON 862-DETDA epoxy system with a range of crosslink densities using a united-atom force field. These simulations are subsequently used to predict the glass transition temperature, thermal expansion coefficients, and elastic properties of each of the crosslinked systems for validation of the modeling techniques. The results indicate that glass transition temperature and elastic properties increase with increasing levels of crosslink density and the thermal expansion coefficient decreases with crosslink density, both above and below the glass transition temperature. The results also indicate that there may be an upper limit to crosslink density that can be realistically achieved in epoxy systems. After evaluation of the thermo-mechanical properties, a method is developed to efficiently establish molecular models of epoxy resins that represent the corresponding real molecular structure at specific aging times. Although this approach does not model the physical aging process, it is useful in establishing a molecular model that resembles the physically-aged state for further use in predicting thermo-mechanical properties as a function of aging time. An equation has been predicted based on the results which directly correlate aging time to aged volume of the molecular model. This equation can be helpful for modelers who want to study properties of epoxy resins at different levels of aging but have little information about volume shrinkage occurring during physical aging.