The investigation of a method to generate conformal lattice structures for additive manufacturing

Additive manufacturing (AM) allows a geometric complexity in products not seen in conventional manufacturing. This geometric freedom facilitates the design and fabrication of conformal hierarchical structures. Entire parts or regions of a part can be populated with lattice structure, designed to exhibit properties that differ from the solid material used in fabrication. Current computer aided design (CAD) software used to design products is not suitable for the generation of lattice structure models. Although conceptually simple, the memory requirements to store a virtual CAD model of a lattice structure are prohibitively high. Conventional CAD software defines geometry through boundary representation (B-rep); shapes are described by the connectivity of faces, edges and vertices. While useful for representing accurate models of complex shape, the sheer quantity of individual surfaces required to represent each of the relatively simple individual struts that comprise a lattice structure ensure that memory limitations are soon reached. Additionally, the conventional data flow from CAD to manufactured part is arduous, involving several conversions between file formats. As well as a lengthy process, each conversion risks the generation of geometric errors that must be fixed before manufacture. A method was developed to specifically generate large arrays of lattice structures, based on a general voxel modelling method identified in the literature review. The method is much less sensitive to geometric complexity than conventional methods and thus facilitates the design of considerably more complex structures. The ability to grade structure designs across regions of a part (termed functional grading ) was also investigated, as well as a method to retain connectivity between boundary struts of a conformal structure. In addition, the method streamlines the data flow from design to manufacture: earlier steps of the data conversion process are bypassed entirely. The effect of the modelling method on surface roughness of parts produced was investigated, as voxel models define boundaries with discrete, stepped blocks. It was concluded that the effect of this stepping on surface roughness was minimal. This thesis concludes with suggestions for further work to improve the efficiency, capability and usability of the conformal structure method developed in this work

Molecular dynamics simulations of the structure and phase behaviour of model lipid membranes and the effect of hydrostatic pressure

Lipid membranes have a rich and complex phase behaviour, involving topological changes to the three-dimensional shape of the membrane, changes to the molecular packing within the membrane and changes to molecular conformations. Studying this phase behaviour can reveal a lot about the fundamental chemistry and physics which govern these systems and the roles that this phase behaviour might play in biological processes. In this work, molecular dynamics simulations are used to investigate the structure, properties and phase behaviour of a range of different lipid membrane systems. The widely used MARTINI model is shown to be able to reproduce the gel/fluid phase transition in single component membranes and Lo/Ld phase separation in ternary mixtures with qualitative agreement with experiment. The compositions of the Lo and Ld phases are calculated and the ternary phase diagram is plotted revealing a wide Lo/Ld coexistence region. The p-T solid/liquid phase diagram for the MARTINI water model is also calculated as a useful resource for future simulations. Non-equilibrium molecular dynamics simulations are used to show that a thermal gradient across a membrane can induce asymmetry in the cholesterol composition and flip-flop process. The effect of the thermal gradient and cholesterol asymmetry on the structure of the membrane is also investigated at steady-state. Cholesterol is found to be thermophobic, with a higher affinity for the colder membrane leaflet due to the more ordered lipid tails. The gel phases formed by different MARTINI POPC topologies are compared revealing very different structures. A new backmapping definition for the current MARTINI POPC topology is defined and used to generate an atomistic gel phase. Simulations using the slipids forcefield show that the final gel phase structure is strongly dependent on the initial configuration. Finally, methods to generate a primitive bicontinuous cubic phase and to calculate the optimum water per lipid ratio in a cubic phase are presented. The effectiveness of both methods is demonstrated by simulations using a new MARTINI topology for monoelaidin.Open Acces

Biophysical studies of lipid membranes by solid state NMR and molecular dynamics simulations

Biological membranes separate the cell interior from the outside and have diverse functions from signal transduction, apoptosis to transportations of ions and small molecules in and out of the cell. Most of these functions are fulfilled by proteins incorporated in the membrane. However, lipids as the main component of membrane not only serve as structural element for bilayer formation but they are also directly involved e.g. signalling processes and bilayer properties are important to mediate protein interactions. To fully understand the role of lipids, it is necessary to develop a molecular understanding of how certain membrane components modify bulk bilayer structure and dynamics. Membranes are known to have many different motions in different conditions and time scales. Temperature, pH, water content and many other conditions change membrane dynamics in a high degree. In addition to this, time scales of motions in membranes vary from ns to ms range corresponding to fast motion and slow motion, respectively. Therefore, membranes are needed to be studied systematically by varying the conditions and using methods to investigate motions in various time scales separately. The aim of this study was therefore perform a combined solid-state NMR / molecular dynamics study on model membranes. Different substrates, such as potential drugs, polarizing agents and signaling lipids were incorporated into bilayers and their location within the membrane and their effect onto the membrane was probed. NSAIDs (non-steroidal anti-inflammatory drugs), pirinixic acid derivatives, ceramides and polarizing agents were the substrates for membranes in this study. There were several experimental methods that were applied in order to investigate effects of these substrates on membrane dynamics. Different kind of phospholipids including POPC, DMPC and DPPC were used. In addition to experimental work, with the information gathered from solid state NMR experiments molecular dynamics simulations were performed to obtain more information about the membranes at the molecular level. As a result, combination of solid-state NMR with molecular dynamics simulations provides very systematic way of investigating membrane dynamics in a large range of time scales. Pirinixic acid derivatives were special interest of this study because of their activity on peroxisome proliferator-activated receptor (PPAR) as an agonist as well as on enzymes of microsomal prostaglandin E2 synthase-1 (PGE2s) -1 and 5-lipoxygenase (5-LO) as dual inhibitor. Two potent pirinixic acid derivatives, 2-(4-chloro-6-(quinolin-6-ylamino)pyrimidin-2-ylthio)octanoic acid (compound 2) and 2-(4-chloro-6-(quinolin-6-ylamino)pyrimidin-2-ylthio)octanoate (compound 3), have been worked and their insertion depts were investigated by combining of solid state NMR and molecular dynamics simulations. Both experimental and theoretical results pointed out that compound 3 was inserted the phospholipid bilayer more deeply than 2. NSAIDs – lipid mixtures have been also studied here. It is known that consumption of NSAIDs as in mixture with lipids results much fewer side effects than consumption of the drugs alone. Thus, it is crucial to understand interactions of NSAIDs with lipids and investigate the possible complex formation of drugs with lipids. In this study, interactions of three widely used NSAIDs, ibuprofen, diclofenac and piroxicam, with DPPC were investigated by solid-state NMR. 1H and 31P NMR results depicted that ibuprofen and diclofenac had interactions with lipids, which is an indication of drug-lipid complex formation whereas piroxicam didn’t show any interactions with lipids suggesting that no complex formation occurred in the case of piroxicam. Ceramides are known to play key roles in many cell processes and many studies showed that the functions of ceramides are related with the ceramide effects on biological membranes. Therefore, in this study, influences of ceramides on biophysics of lipid bilayers were investigated by using various solid state NMR techniques and molecular dynamics simulations. Results from molecular dynamics simulations clearly showed that ceramide and lipids have strong interactions. More evidences about ceramide-lipid interactions were provided from 1H and 14N NMR results. In addition, it was indicated by both simulation and experimental methods that ceramide increased the rigidity of DMPC by increasing chain order parameters. BTbk is a biradical, which is used as polarizing agent for dynamic nuclear polarization (DNP) experiments and found to be more efficient than other widely used polarizing agents such as TOTAPOL. Since it is a hydrophobic compound, which prefers to stay inside lipid bilayer it is important to investigate the location and orientation of bTbk along the bilayer in order to understand its enhancement profile in DNP measurements. In this study, both NMR relaxation time measurements and molecular dynamics simulations revealed that bTbk tends to stay more close to hydrophobic chain of lipids than the interfacial part of lipids at bilayer surface. In the first part of this work, a brief introduction on lipid membranes as well as a theoretical summary on both methods of solid-state NMR and molecular dynamics simulations is given. Then, in the second part methodology is introduced for both solid-state NMR spectrometer and theoretical calculations. Afterwards, results of different membrane systems are discussed in the following parts for both solid state NMR and MD. Finally, in the last part, a summary and the conclusion of the overall results together with some future plans are explained.Biologische Membranen stellen eine Permeabilitätsbarriere zwischen dem Inneren und dem Äußeren von Zellen dar, die im Wesentlichen über die eingebetteten Membranproteine gesteuert wird. Für die mit der Membran assoziierten funktionalen Prozesse spielen aber auch Lipidbestandteile eine wichtige Rolle, was deren genaue Charakterisierung erforderlich macht. Beispiele hierfür sind u.a. laterale Phasentrennung/Rafts, Auflösung von Doppelschichtphasen bei der Zellfusion, die Rolle bestimmter Lipidbestandteile als sekundäre Botenstoffe, Modulierung der Aktivität von Membranproteinen über spezifische Lipidinteraktionen oder veränderte physikalische Membranparameter oder auch die Interaktion lipophiler Pharmaka mit Lipiden. Festkörper-NMR bietet einen idealen Zugang zu diesen Fragestellungen, da diese Technik direkte Experimente an verschiedensten Lipidphasen zulässt sowie über eine sehr große dynamische Bandbreite verfügt, über die mit geeigneten Experimenten viele dynamische Prozesse in der Membran detektiert werden können. Komplementär zu Festkörper-NMR können MD-Simulationen an vollständigen Lipiddoppelschichten zum Einsatz gebracht werden, um entweder Vorhersagen machen zu können, die mittels NMR überprüft werden können, oder um im Falle von unvollständigen NMR Datensätzen zu einem vollständigeren molekularen Bild des betrachteten Systems zu gelangen. Ziel dieser Dissertation war es daher, einen kombinierten FK-NMR/MD-Simulationsansatz für die Untersuchung kleiner Moleküle in der Lipidmembran zu etablieren und an mehreren Beispielen zu demonstrieren...

Quantification of Order in Point Patterns

Pattern attributes are important in many disciplines, e.g. developmental biology, but there are few objective measures of them. Here we concentrate on the attribute of order in point patterns and its objective measurement. We examine perception of order and develop analysis algorithms that quantify the attribute in accordance with perception of it. Based on pairwise ranking of point patterns by degree of order, we show that judgements are highly consistent across individuals and that the perceptual dimension has an interval scale structure, spanning roughly 10 just-noticeable differences (jnds) between disorder and order. We designed a geometric algorithm that estimates order to an accuracy of half a jnd by quantifying the variability of the spaces between points. By anchoring the output of the algorithm so that Poisson point processes score on average 0, and perfect lattices score 10, we constructed an absolute interval scale of order. We demonstrated its utility in biology by quantifying the order of the Drosophila dorsal thorax epithelium during development. The psychophysical scaling method used relies on the comparison of stimuli with similar levels of order yielding a discrimination-based scale. As with other perceptual dimensions, an interesting question is whether supra-threshold perceptual differences are consistent with this scale. To test that we collected discrimination data, and data based on comparison of perceptual differences. Although the judgements of perceptual differences were found to be consistent with an interval scale, like the discrimination judgements, no common interval scale that could predict both sets of data was possible. Point patterns are commonly displayed as arrangements of dots. To examine how presentation parameters (dot size, dot numbers, and pattern area) affect discrimination, we collected discrimination data for ten presentation conditions. We found that discrimination performance depends on the ratio ‘dot diameter / average dot spacing’

Alternative Splicing and Protein Structure Evolution

In den letzten Jahren gab es in verschiedensten Bereichen der Biologie einen dramatischen Anstieg verfügbarer, experimenteller Daten. Diese erlauben zum ersten Mal eine detailierte Analyse der Funktionsweisen von zellulären Komponenten wie Genen und Proteinen, die Analyse ihrer Verknüpfung in zellulären Netzwerken sowie der Geschichte ihrer Evolution. Insbesondere der Bioinformatik kommt hier eine wichtige Rolle in der Datenaufbereitung und ihrer biologischen Interpretation zu. In der vorliegenden Doktorarbeit werden zwei wichtige Bereiche der aktuellen bioinformatischen Forschung untersucht, nämlich die Analyse von Proteinstrukturevolution und Ähnlichkeiten zwischen Proteinstrukturen, sowie die Analyse von alternativem Splicing, einem integralen Prozess in eukaryotischen Zellen, der zur funktionellen Diversität beiträgt. Insbesondere führen wir mit dieser Arbeit die Idee einer kombinierten Analyse der beiden Mechanismen (Strukturevolution und Splicing) ein. Wir zeigen, dass sich durch eine kombinierte Betrachtung neue Einsichten gewinnen lassen, wie Strukturevolution und alternatives Splicing sowie eine Kopplung beider Mechanismen zu funktioneller und struktureller Komplexität in höheren Organismen beitragen. Die in der Arbeit vorgestellten Methoden, Hypothesen und Ergebnisse können dabei einen Beitrag zu unserem Verständnis der Funktionsweise von Strukturevolution und alternativem Splicing bei der Entstehung komplexer Organismen leisten wodurch beide, traditionell getrennte Bereiche der Bioinformatik in Zukunft voneinander profitieren können

Protein-water interactions studied by molecular dynamics simulations

Most proteins have evolved to function optimally in aqueous environments, and the interactions between protein and water therefore play a fundamental role in the stability, dynamics, and function of proteins. Although we understand many details of water, we understand much less about the protein-water interface. In this thesis we use molecular dynamics (MD) simulations to cast light on many structural and dynamical properties of protein hydration for which a detailed picture is lacking.We show that the 1 ms MD simulation of the bovine pancreatic trypsin inhibitor (BPTI) by Shaw \textsl{et al.} (Science 2010, 330, 341) reproduces the mean survival times from magnetic relaxation dispersion (MRD) experiments by computing the relevant survival correlation function that is probed by these experiments. The simulation validates several assumptions in the model used to interpret MRD data, and reveals a possible mechanism for the water-exchange; water molecules gain access to the internal sites by a transient aqueduct mechanism, migrating as single-file water chains through transient tunnels or pores. The same simulation was also used to reveal a possible mechanism for hydrogen exchange of backbone amides, involving short-lived locally distorted conformations of the protein whereby the amide is presolvated by two water molecules before the catalyst can approach the amide through a water wire.We perform MD simulations of several small globular proteins in dilute aqueous solution to spatially resolve protein hydration. Defining mono-molecular thick hydration shells as a metric from the protein surface, we compute structural and dynamical properties of water in these shells and show that the protein-induced water perturbation is short ranged, essentially only affecting water molecules in the first hydration shell, thus validating the model used to interpret MRD data. Compared to the bulk, the first shell is 6 \% more dense and 25-30 \% less compressible. The shell-averaged rotation of water molecules in the first hydration shell is retarded by a factor 4-5 compared to bulk, and the contributions to this retardation can be resolved based on a universal confinement index. The dynamical heterogeneity in the first shell is a result of water molecules rotating by different mechanisms on a spectrum between two extremes: a collective bulk-like mechanism and a protein-coupled mechanism where water molecules in confined sites are orientationally restricted and require an exchange event

Graph based pattern discovery in protein structures

The rapidly growing body of 3D protein structure data provides new opportunities to study the relation between protein structure and protein function. Local structure pattern of proteins has been the focus of recent efforts to link structural features found in proteins to protein function. In addition, structure patterns have demonstrated values in applications such as predicting protein-protein interaction, engineering proteins, and designing novel medicines. My thesis introduces graph-based representations of protein structure and new subgraph mining algorithms to identify recurring structure patterns common to a set of proteins. These techniques enable families of proteins exhibiting similar function to be analyzed for structural similarity. Previous approaches to protein local structure pattern discovery operate in a pairwise fashion and have prohibitive computational cost when scaled to families of proteins. The graph mining strategy is robust in the face of errors in the structure, and errors in the set of proteins thought to share a function. Two collaborations with domain experts at the UNC School of Pharmacy and the UNC Medical School demonstrate the utility of these techniques. The first is to predict the function of several newly characterized protein structures. The second is to identify conserved structural features in evolutionarily related proteins