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Within the scope of this thesis, a theoretical study of liquid flow in graphitic nanopores was performed. More precisely, a combination of numerical simulations and analytic approach was used to establish the special properties of carbon nanotubes for fluid transport: Molecular dynamics flow simulations of different liquids in carbon nanotubes exhibited flow velocities that are 1-3 orders of magnitude higher than predicted from the continuum hydrodynamics framework and the no-slip boundary condition. These results support previous experiments performed by several groups reporting exceptionally high flow rates for water in carbon nanotube membranes. The reason for this important flow enhancement with respect to the expectation was so far unclear. In this work, a careful investigation of the water/graphite friction coefficient which we identified as the crucial parameter for fast liquid transport in the considered systems, was carried out. In simulations, the friction coefficient was found to be very sensitive to wall curvature: friction is independent of confinement for water between flat graphene walls with zero curvature, while it increases with increasing negative curvature (water at the outside of the tube), and it decreases with increasing positive curvature (water inside the tube), eventually leading to quasi frictionless flow for water in a single file configuration in the smallest tubes. A similar behavior was moreover found with several other liquids, such as alcohol, alcane and OMCTS. Furthermore, a theoretical approximate expression for the friction coefficient is presented which predicts qualitatively and semi-quantitatively its curvature dependent behavior. Moreover, a deeper analysis of the simulations according to the proposed theoretical description shed light on the physical mechanisms at the origin of the ultra low liquid/solid friction in carbon nanotubes. In fine, it is due to their perfectly ordered molecular structure and their atomically smooth surface that carbon nanotubes are quasi-perfect liquid conductors compared to other membrane pores like, for example, nanochannels in amorphous silica. The newly gained understanding constitutes an important validation that carbon nanotubes operate as fast transporters of various liquids which makes them a promising option for different applications like energy conversion or filtration on the molecular level.

MT nucleation from γ-tubulin complexes, located at centrosome, is an essential step in the formation of MT cytoskeleton. In mammalian cells, -tubulin is encoded by two genes. We functionally characterized two γ-tubulin proteins and have found that both are functionally equivalent. γ-Tubulin 2 is able to substitute for γ-tubulin 1 in MT nucleation. However, we revealed that unlike TUBG1, TUBG2 expression is downregulated in mouse preimplantation development. Mast cells represent effectors of the allergy reaction. Their activation by antigen induces number of cellular processes such as degranulation, proliferation and cytoskeleton rearrangements. The regulatory mechanisms of MT reorganization during mast cell activation are unknown. We identified new signaling proteins, GIT1 and PIX that interact with - tubulin. Depletion of GIT1 or PIX leads to changes in MT nucleation. GIT1 is phosphorylated on tyrosine and associates with γ-tubulin in a Ca2+ -dependent manner. Our data suggested a novel signaling pathway for MT rearrangement in mast cells where tyrosine kinase-activated GIT1 and βPIX work in concert with Ca2+ signaling to regulate MT nucleation. We tested the capability of GIT1 and PIX to influence -tubulin function in more cell types. We found out that GIT1/βPIX signaling proteins together...

Aminoacyl-tRNA synthetases (aaRSs) are at the center of the question of the origin of life and are essential proteins found in all living organisms. AARSs arose early in evolution to interpret genetic code and are believed to be a group of ancient proteins. They constitute a family of enzymes integrating the two levels of cellular organization: nucleic acids and proteins. These enzymes ensure the fidelity of transfer of genetic information from the DNA to the protein. They are responsible for attaching amino acid residues to their cognate tRNA molecules by virtue of matching the nucleotide triplet, which is the first step in the protein synthesis. The translation of genetic code into protein sequence is mediated by tRNA, which accurately picks up the cognate amino acids. The attachment of the cognate amino acid to tRNA is catalyzed by aaRSs, which have binding sites for the anticodon region of tRNA and for the amino acid to be attached. The two binding sites are separated by ≈ 76 Å and experiments have shown that the communication does not go through tRNA (Gale et al., 1996). The problem addressed here is how the information of binding of tRNA anticodon near the anticodon binding site is communicated to the active site through the protein structure. These enzymes are modular with distinct domains on which extensive kinetic and mutational experiments and supported by structural data are available, highlighting the role of inter-domain communication (Alexander and Schimmel, 2001). Hence these proteins present themselves as excellent systems for in-silico studies. Various methods involved for the construction of protein structure networks are well established and analyzed in a variety of ways to gain insights into different aspects of protein structure, stability and function (Kannan and Vishveshwara, 1999; Brinda and Vishveshwara, 2005). In the present study, we have incorporated network parameters for the analysis of molecular dynamics (MD) simulation data, representing the global dynamic behavior of protein in a more elegant way. MD simulations have been performed on the available (and modeled) structures of aaRSs bound to a variety of ligands, and the protein structure networks (PSN) of non-covalent interactions have been characterized in dynamical equilibrium. The changes in the structure networks are used to understand the mode of communication, and the paths between the two sites of interest identified by the analysis of the shortest path. The allosteric concept has played a key role in understanding the biological functions of aaRSs. The rigidity/plasticity and the conformational population are the two important ideas invoked in explaining the allosteric effect. We have explored the conformational changes in the complexes of aaRSs through novel parameters such as cliques and communities (Palla et al., 2005), which identify the rigid regions in the protein structure networks (PSNs) constructed from the non-covalent interactions of amino acid side chains. The thesis consists of 7 chapters. The first chapter constitutes the survey of the literature and also provides suitable background for this study. The aims of the thesis are presented in this chapter. Chapter 2 describes various techniques employed and the new techniques developed for the analysis of PSNs. It includes a brief description of well -known methods of molecular dynamics simulations, essential dynamics, and cross correlation maps. The method used for the construction of graphs and networks is also described in detail. The incorporation of network parameters for the analysis of MD simulation data are done for the first time and has been applied on a well studied protein lysozyme, as described in chapter 3. Chapter 3 focuses on the dynamical behavior of protein structure networks, examined by considering the example of T4-lysozyme. The equilibrium dynamics and the process of unfolding are followed by simulating the protein with explicit water molecules at 300K and at higher temperatures (400K, 500K) respectively. Three simulations of 10ns duration have been performed at 500K to ensure the validity of the results. The snapshots of the protein structure from the simulations are represented as Protein Structure Networks (PSN) of non-covalent interactions. The strength of the non-covalent interaction is evaluated and used as an important criterion in the construction of edges. The profiles of the network parameters such as the degree distribution and the size of the largest cluster (giant component) have been examined as a function of interaction strength (Ghosh et al., 2007). We observe a critical strength of interaction (Icritical) at which there is a transition in the size of the largest cluster. Although the transition profiles at all temperatures show behavior similar to those found in the crystal structures, the 500K simulations show that the non-native structures have lower Icritical values. Based on the interactions evaluated at Icritical value, the folding/unfolding transition region has been identified from the 500K simulation trajectories. Furthermore, the residues in the largest cluster obtained at interaction strength higher than Icritical have been identified to be important for folding. Thus, the compositions of the top largest clusters in the 500K simulations have been monitored to understand the dynamical processes such as folding/unfolding and domain formation/disruption. The results correlate well with experimental findings. In addition, the highly connected residues in the network have been identified from the 300K and 400K simulations and have been correlated with the protein stability as determined from mutation experiments. Based on these analyses, certain residues, on which experimental data is not available, have been predicted to be important for the folding and the stability of the protein. The method can also be employed as a valuable tool in the analysis of MD simulation data, since it captures the details at a global level, which may elude conventional pair-wise interaction analysis. After standardizing the concept of dynamical network analysis using Lysozyme, it was applied to our system of interest, the aaRSs. The investigations carried out on Methionyl-tRNA synthetases (MetRS) are presented in chapter 4. This chapter is divided into three parts: Chapter 4A deals with the introduction to aminoacyl tRNA synthetases (aaRS). Classification and functional insights of aaRSs obtained through various studies are presented. Chapter 4B is again divided into parts: BI and BII. Chapter 4BI elucidates a new technique developed for finding communication pathways essential for proper functioning of aaRS. The enzymes of the family of tRNA synthetases perform their functions with high precision, by synchronously recognizing the anticodon region and the amino acylation region, which is separated by about 70Å in space. This precision in function is brought about by establishing good communication paths between the two regions. We have modelled the structure of E.coli Methionyl tRNA synthetase, which is complexed with tRNA and activated methionine. Molecular dynamics simulations have been performed on the modeled structure to obtain the equilibrated structure of the complex and the cross correlations between the residues in MetRS. Furthermore, the network analysis on these structures has been carried out to elucidate the paths of communication between the aminoacyl activation site and the anticodon recognition site (Ghosh and Vishveshwara, 2007). This study has provided the detailed paths of communication, which are consistent with experimental results. A similar study on the (MetRS + activated methionine) and (MetRS+tRNA) complexes along with ligand free-native enzyme has also been carried out. A comparison of the paths derived from the four simulations has clearly shown that the communication path is strongly correlated and unique to the enzyme complex, which is bound to both the tRNA and the activated methionine. The method developed here could also be utilized to investigate any protein system where the function takes place through long distance communication. The details of the method of our investigation and the biological implications of the results are presented in this chapter. In chapter 4BII, we have explored the conformational changes in the complexes of E.coli Methionyl tRNA synthetase (MetRS) through novel parameters such as cliques and communities, which identify the rigid regions in the protein structure networks (PSNs). The rigidity/plasticity and the conformational population are the two important ideas invoked in explaining the allosteric effect. MetRS belongs to the aminoacyl tRNA Synthetases (aaRSs) family that play a crucial role in initiating the protein synthesis process. The network parameters evaluated here on the conformational ensembles of MetRS complexes, generated from molecular dynamics simulations, have enabled us to understand the inter-domain communication in detail. Additionally, the characterization of conformational changes in terms of cliques/communities has also become possible, which had eluded conventional analyses. Furthermore, we find that most of the residues participating in clique/communities are strikingly different from those that take part in long-range communication. The cliques/communities evaluated here for the first time on PSNs have beautifully captured the local geometries in their detail within the framework of global topology. Here the allosteric effect is revealed at the residue level by identifying the important residues specific for structural rigidity and functional flexibility in MetRS. Chapter 4C focuses on MD simulations of Methionyl tRNA synthetase (AmetRS) from a thermophilic bacterium, Aquifex aeolicus. As describe in Chapter 4B, we have explored the communication pathways between the anticodon binding region and the aminoacylation site, and the conformational changes in the complexes through cliques and communities. The two MetRSs from E.coli and Aquifex aeolicus are structurally and sequentially very close to each other. But the communication pathways between anticodon binding region and the aminoacylation site from A. aeolicus have differed significantly with the communication paths obtained from E.coli. The residue composition and cliques/communities structure participating in communication are not similar in the MetRSs of both these organisms. Furthermore the formation of cliques/communities and hubs in the communication paths are more in A. aeolicus compared to E.coli. The participation of structurally homologous linker peptide, essential for orienting the two domains for efficient communication is same in both the organisms although, the residues composition near domain interface regions including the linker peptide is different. Thus, the diversity in the functioning of two different MetRS has been brought out, by comparing the E.coli and Aquifex aeolicus systems. Protein Structure network analysis of MD simulated trajectories of various ligand bound complexes of Escherichia coli Cysteinyl-tRNA synthetase (CysRS) have been discussed in Chapter 5. The modeling of the complex is done by docking the ligand CysAMP into the tRNA bound structure of E.coli Cysteinyl tRNA synthetase. Molecular dynamics simulations have been performed on the modeled structure and the paths of communications were evaluated using a similar method as used in finding communication paths for MetRS enzymes. Compared to MetRS the evaluation of communication paths in CysRS is complicated due to presence of both direct and indirect readouts. The direct and indirect readouts (DR/IR) involve interaction of protein residues with base-specific functional group and sugar-phosphate backbone of nucleic acids respectively. Two paths of communication between the anticodon region and the activation site has been identified by combining the cross correlation information with the protein structure network constructed on the basis of non-covalent interaction. The complete paths include DR/IR interactions with tRNA. Cliques/communities of non-covalently interacting residues imparting structural rigidity are present along the paths. The reduction of cooperative fluctuation due to the presence of community is compensated by IR/DR interaction and thus plays a crucial role in communication of CysRS. Chapter 6 focuses on free energy calculations of aminoacyl tRNA synthetases with various ligands. The free energy contributions to the binding of the substrates are calculated using a method called MM-PBSA (Massova and Kollman, 2000). The binding free energies were calculated as the difference between the free energy of the enzyme-ligand complex, and the free ligand and protein. The ligand unbinding energy values obtained from the umbrella sampling MD correlates well with the ligand binding energies obtained from MM-PBSA method. Furthermore the essential dynamics was captured from MD simulations trajectories performed on E.coli MetRS, A. aeolius MetRS and E.coli CysRS in terms of the eigenvalues. The top two modes account for more than 50% of the motion in essential space for systems E.coli MetRS, A. aeolius MetRS and E.coli CysRS. Population distribution of protein conformation states are looked at the essential plane defined by the two principal components with highest eigenvalues. This shows how aaRSs existed as a population of conformational states and the variation with the addition of ligands. The population of conformational states is converted into Free energy contour surface. From free energy surfaces, it is evident that the E.coli tRNAMet bound MetRS conformational fluctuations are more, which attributes to less rigidity in the complex. Whereas E.coli tRNACys bound CysRS conformational fluctuations are less and this is reflected in the increase in rigidity of the complex as confirmed by its entropic contribution. Future directions have been discussed in the final chapter (Chapter 7). Specifically, it deals with the ab-initio QM/MM study of the enzymatic reaction involved in the active site of E.coli Methionyl tRNA synthetase. To achieve this, two softwares are integrated: the Quantum Mechanics (QM) part includes small ligands and the Molecular Mechanics (MM) part as protein MetRS are handled using CPMD and Gromacs respectively. The inputs for two reactions pathways are prepared. First reaction involves cyclization reaction of homocysteine in the active site of MetRS and the second reaction deals with charging of methionine in the presence of ATP and magnesium ion. These simulations require very high power computing systems and also time of computation is also very large. With the available computational power we could simulate up to 10ps and it is insufficient for analysis. The future direction will involve the simulations of these systems for longer time, followed by the analysis for reaction pathways.

One of the main challenges to transform highly useful Direct Methanol Fuel Cells (DMFC) into a commercially viable technology has been to develop a low cost polymer electrolyte membrane (PEM) with high proton conductivity, high stability and low methanol crossover under operating conditions desirably including high temperatures. Nafion, the widely used PEM, fails to meet all of these criteria simultaneously. Recently developed acid-base polymer blend membranes constitute a promising class of PEMs alternative to Nafion on above criteria. Even though some of these membranes produce better performance than Nafion, they still present numerous opportunities for maximizing high temperature proton conductivity and dimensional stability with concomitant minimization of methanol crossover. Our contribution embarks on the fundamental study of one such novel class of blend membranes viz., sulfonated poly (ether ether ketone) (SPEEK)(95 % by weight) blended with polysulfone tethered with base (5 % by weight) such as 2-aminobenzimidazole (ABIm), 5-amino-benzotriazole (BTraz) and 1H-perimidine (PImd), developed by Manthiram group at The University of Texas at Austin. In this work, we report extensive all-atom classical as well as ab-initio molecular dynamics (MD) simulations of such water-methanol solvated blend membranes (as well as pure SPEEK and Nafion) the first time. Our approach consists of three steps: (1) Predict dynamical properties such as diffusivities of water, methanol and proton in such membranes (2) Validate against experiments (3) Develop understanding on the interplay between basic chemistry, structure and properties, the knowledge that can potentially be used to develop better candidate membranes. In particular, we elucidate the impact of simple, fundamental physiochemical features of the polymeric membranes such as hydrophilicity, hydrophobicity, structure or the size of the base on the structural manifestations on the bigger scale such as nanophase segregation, hydrogen bonding or pore sizes, which ultimately affect the permeant transport through such systems. / text

The Tumor Necrosis Factor derived-TIP peptide is a small 17 amino acids cyclic peptide with lectin-like activity, that possesses several therapeutically relevant biological activities, among which is activation of alveolar liquid clearance in both healthy and injured lungs in vivo. Accumulation of fluid in the lungs? alveoli and interstitial spaces is a life-threatening condition called pulmonary edema. The mortality rate due permeability pulmonary edema, accompanied by a dysfunction of the alveolar/capillary barrier, is high because no effective treatment lacking side effects exists nowadays. It is known that the TIP peptide is able to activate vectorial Na+ transport ? which mediates lung liquid clearance. However, the mechanism of action of remains elusive. The aim of this thesis was to investigate the initial steps of interaction between the TIP peptide and airway epithelial cells. Numerous novel methods and single-molecule techniques were used to unravel: (i) how the TIP peptide interacts with the molecules on the apical side of the lung epithelial cells; (ii) whether the TIP peptide need to be internalized inside of the cells to trigger its effects; (iii) the nature of the interaction between the TIP peptide and its putative receptor(s); (iv) the putative receptor(s) for the TIP peptide on the apical surface of the lung epithelial cells.

This thesis is an attempt to understand ways to improve thermo-mechanical and structural properties of nano-structured materials. A detailed study on computational design and analysis of metallic nanowires is carried out. Molecular dynamic simulation method is applied. In particular, FCC metallic nanowires, NiAl, and CuZr nanowires are studied. Various bottom-up approaches are suggested with improved structural and thermo¬mechanical properties. In the first part of the thesis, Cu nanowires are considered. Existence of a novel and stable pentagonal multi-shell nanobridge structure of Cu under high strain rate tensile loading is reported. Such a structure shows enhanced mechanical properties. A three-fold pseudo-elastic-plastic shape recovery mechanism in such nanowires is established. This study also shows that the length of the pentagonal nanobridge structures can be characterized by its inelastic strain. It is also reported that an initial FCC structure is transformed into a new HCP structure. The evidence of HCP structure is confirmed with the help of experimental data published in the literature. Subsequent to the above study, a novel mechanism involving coupled temperature-stress dependent reorientation in FCC nanowires is investigated. A detailed map is generated for size dependent stress-temperature induced solid-solid reorientation in Cu nanowires. In the second part of the thesis, deformation mechanisms in NiAl based intermetallic nanowires are studied. A novel mechanism of temperature and cross-section dependent pseudo-elastic/pseudo-plastic shape and strain recovery by an initial B2 phase of NiAl nanowire is reported. Such a recoverable strain, which is as high as ~ 30%, can potentially be utilized to realize various types of shape memory and strain sensing phenomena in nano-scale devices. An asymmetry in tensile and compressive yield strength behavior is also observed, which is due to the softening and hardening of the nanowires under tensile and compressive loadings, respectively. Two different deformation mechanisms dominated by twinning under tension and slip under compression are found. Most interestingly, a superplastic behavior with a failure strain of up to 700% in the intermetallic NiAl nanowires is found to exist at a temperature of 0.36Tm. Such superplastic behavior is attributed to the transformation of the nanowire from a crystalline phase to an amorphous phase after yielding of the nanowire. In the last part the work, another type of nanowires having Cu-Zr system is considered. A novel stress induced martensitic phase transformation from an initial B2 phase to BCT phase in a CuZr nanowire under tensile loading is reported. It is further shown that such a stress induced martenistic phase transformation can be achieved under both tensile as well as compressive loadings. Tensile-compressive asymmetry in the stress-strain behavior is observed due to two different phase transformation mechanisms having maximum transformation strains of ~ 5% under compressive loading and ~ 20% under tensile loading. A size and temperature dependent tensile phase transformation in the nanowire is also observed. Small nanowires show a single step tensile phase transformation whereas the nanowires with larger size show a two step deformation mechanism via an intermediate R-phase hardening followed by R-phase yielding. A study of energetic behavior of these nanowires reveals uniform distribution of stress over the nanowire cross-section and such stress distribution can lead to a significant improvement in its thermo-mechanical properties. Similar improvement is demonstrated by designing the nanowires via manipulating the surface configuration of B2-CuZr system. It is found that the CuZr nanowires with Zr atoms at the surface sites are energetically more stable and also give a uniform distribution of stresses across the cross-section. This leads to the improvement in yield strength as well as failure strain. An approach to design energetically stable nano-structured materials via manipulating the surface configurations with improved thermo-mechanical properties is demonstrated which can help in fundamental understanding and development of similar structures with more stability and enhanced structural properties. Further ab-initio and experimental studies on the confirmation of the stability of the nanowires via manipulating the surface site is an open area of research and related future scopes are highlighted in the closure.

<p>This study is concerned with the predictive modeling of the machining and the mechanical behaviors of additive manufactured (AMed) Ti6AlV/TiC composites and Ti6Al4V, respectively, using microstructure-based hierarchical multiscale modeling. The predicted results could constitute as a basis for optimizing the parameters of machining and AM of the current materials.</p> <p>Through hierarchical flow of material behaviors from the atomistic, to the microscopic and the macroscopic scales, multiscale heterogeneous models (MHMs) coupled to the finite element method (FEM) are employed to simulate the conventional and the laser assisted machining (LAM) of Ti6AlV/TiC composites. In the atomistic level, molecular dynamics (MD) simulations are used to determine the traction-separation relationship for the cohesive zone model (CZM) describing the Ti6AlV/TiC interface. Bridging the microstructures across the scales in MHMs is achieved by representing the workpiece by macroscopic model with the microscopic heterogeneous structure including the Ti6Al4V matrix, the TiC particles, and their interfaces represented by the parameterized CZM. As a result, MHMs are capable of revealing the possible reasons of the peculiar high thrust forces behavior during conventional machining of Ti6Al4V/TiC composites, and how laser assisted machining can improve this behavior, which has not been conducted before.</p> <p>Extending MHMs to predict the mechanical behaviors of AMed Ti6Al4V would require including the heterogeneous microstructure at the grain level, which could be computational expensive. To solve this issue, the extended mechanics of structure genome (XMSG) is introduced as a novel multiscale homogenization approach to predict the mechanical behavior of AMed Ti6Al4V in a computationally efficient manner. This is realized by embedding the effects of microstructure heterogeneity, porosity growth, and crack propagation in the multiscale calculations of the mechanical behavior of the AMed Ti6Al4V using FEM. In addition, the XMSG can predict the asymmetry in the Young’s modulus of the AMed Ti6Al4V under tensile and compression loading as well as the anisotropy in the mechanical behaviors. The applicability of XMSG to fatigue life prediction with valid results is conducted by including the energy dissipations associated with cyclic loading/unloading in the calculations of the cyclic response of the material.</p>

Vor dem Hintergrund zukünftiger Sensoren, basierend auf dem piezoresistiven Effekt von einwandigen Kohlenstoffnanoröhren (SWCNT), werden in dieser Arbeit umfangreiche Ergebnisse zum mechanischen Verhalten von Grenzflächen zwischen SWCNTs und edlen Metallen am Beispiel von Pd und Au präsentiert. Im Fokus steht dabei die Synergie von rechnerischen und experimentellen Methoden Molekulardynamik (MD), nanoskalige Tests und Analytik , um (1) mit guter Genauigkeit maximale Kräfte von gezogenen SWCNTs, welche in Metall eingebettet sind, vorauszuberechnen und (2) einen wertvollen Beitrag zum Verständnis der zu Grunde liegenden Fehlermechanismen zu liefern. Es wurde ein MDModell eines in eine einkristalline Matrix eingebetteten SWCNTs mit Randbedingen eines Auszugsversuchs entwickelt. Mit diesem Modell können Kraft-Weg-Beziehungen und Energieverläufe für einen quasistatischen verschiebungsgesteuerten Auszugsversuch errechnet werden. Das Modell liefert kritische Kräfte bei Versagen des Systems. Des Weiteren können mit diesem Modell der Einfluss des SWCNT-Typus, der Einbettungslänge, der Temperatur, von intrinsischen Defekten und Oberflächengruppen (SFGs) auf das Grenzflächenverhalten untersucht werden. Zum Vergleich wurden kritische Kräfte experimentell durch in situ Auszugsversuche in einem Rasterelektronenmikroskop bestimmt. Es wurde eine sehr gute Übereinstimmung von rechnerischen und experimentellen Daten festgestellt. Der vorherrschende Fehler im Experiment ist der SWCNT-Bruch, jedoch wurden auch einige SWCNT-Auszüge beobachtet. Mit Hilfe der MD-Simulationen wurde gefunden, dass die SFGs als kleine Anker in der umgebenden metallischen Matrix wirken und somit die maximalen Kräfte signifikant erhöhen. Diese Grenzflächenverstärkung kann Zugspannungen verursachen, die genügend hoch sind, so dass SWCNT-Bruch initiert wird. Im Gegensatz dazu zeigten Simulationen von Auszugstests mit idealen SWCNTs nur kleine Auszugskräfte, welche meistens unabhängig von der Einbettungslänge des SWCNTs sind. Dieses Verhalten wird mit einer inkommensurablen Konfiguration der Kristallstrukturen an der Grenzfläche von SWCNTs und der einbettenden Edelmetalle interpretiert. Zur Qualifizierung der Existenz von carboxylatischen Oberflächengruppen auf dem genutzten SWCNT-Material wurden analytische Untersuchungen mittels Fluoreszenzmarkierung von Oberflächengruppen durchgeführt. In Übereinstimmung mit Literaturstellen zum gesicherten Nachweis von SFGs, bedingt durch technologische Behandlungen, weisen diese Experimente stark auf das Vorhandensein von carboxylatischen Oberflächengruppen auf dem genutzten SWCNT-Material hin. Demnach kann der dominante SWCNT-Bruch Fehler durch die Grenzflächenverstärkung auf Grund von SFGs erklärt werden. / In the light of future sensors, that are based upon the piezoresistive effect of singlewalled carbon nanotubes (SWCNTs), this work presents comprehensive results of studies on the mechanical behavior of interfaces between SWCNTs and noble metals using the examples of Pd and Au. With this contribution, the focus is on a synergy between computational and experimental approaches involving molecular dynamics (MD) simulations, nanoscale testing, and analytics (1) to predict to a good degree of accuracy maximum forces of pulled SWCNTs embedded in a noble metal matrix and (2) to provide valuable input to understand the underlying mechanisms of failure. A MD model of a SWCNT embedded in a single crystalline matrix with pull-out test boundary conditions was developed. With this model, force-displacement relations and energy evolutions for a quasi-static displacement controlled test can be computed. The model provides critical forces for failure of the system. Furthermore, the influence of SWCNT type, embedding length, temperature, intrinsic defects and surface functional groups (SFGs) on the interface behavior can be studied using this model. For comparison, critical forces were experimentally determined by conducting pull-out tests in situ, inside a scanning electron microscope. A very good agreement of computational and experimental values was discovered. The dominant failure mode in the experiment was a SWCNT rupture, although several pull-out failures were also observed. From MD simulations, it was found that SFGs act as small anchors in the metal matrix and significantly enhance the maximum forces. This interface reinforcement can lead to tensile stresses sufficiently high to initiate SWCNT rupture. In contrast, pull-out test simulations of ideal SWCNTs show only small pull-out forces, which are mostly independent on SWCNT embedding length. This behavior is interpreted with an incommensurate configuration of crystal structures at the interface between SWCNTs and embedding noble metals. To qualify the existence of carboxylic SFGs on the used SWCNT material, an analytical investigation by means of fluorescence labeling of surface species was performed. In agreement with literature reports on the secured verification of SFGs due to necessary technological treatments, these experiments strongly indicate the presence of carboxylic SFGs on the used SWCNT material. Thus, the dominant SWCNT rupture failure is explained with an interface reinforcement by SFGs.

<p>Protein malfunction can cause human diseases, which makes the protein a target in the process of drug discovery. In-depth knowledge of how protein functions can widely contribute to the understanding of the mechanism of these diseases. Protein functions are determined by protein structures and their dynamic properties. Protein dynamics refers to the constant physical movement of atoms in a protein, which may result in the transition between different conformational states of the protein. These conformational transitions are critically important for the proteins to function. Understanding protein dynamics can help to understand and interfere with the conformational states and transitions, and thus with the function of the protein. If we can understand the mechanism of conformational transition of protein, we can design molecules to regulate this process and regulate the protein functions for new drug discovery. Protein Dynamics can be simulated by Molecular Dynamics (MD) Simulations.</p> <p>The MD simulation data generated are spatial-temporal and therefore very high dimensional. To analyze the data, distinguishing various atomic interactions within a protein by interpreting their 3D coordinate values plays a significant role. Since the data is humongous, the essential step is to find ways to interpret the data by generating more efficient algorithms to reduce the dimensionality and developing user-friendly visualization tools to find patterns and trends, which are not usually attainable by traditional methods of data process. The typical allosteric long-range nature of the interactions that lead to large conformational transition, pin-pointing the underlying forces and pathways responsible for the global conformational transition at atomic level is very challenging. To address the problems, Various analytical techniques are performed on the simulation data to better understand the mechanism of protein dynamics at atomic level by developing a new program called Probing Long-distance interactions by Tapping into Paired-Distances (PLITIP), which contains a set of new tools based on analysis of paired distances to remove the interference of the translation and rotation of the protein itself and therefore can capture the absolute changes within the protein.</p> <p>Firstly, we developed a tool called Decomposition of Paired Distances (DPD). This tool generates a distance matrix of all paired residues from our simulation data. This paired distance matrix therefore is not subjected to the interference of the translation or rotation of the protein and can capture the absolute changes within the protein. This matrix is then decomposed by DPD</p> <p>using Principal Component Analysis (PCA) to reduce dimensionality and to capture the largest structural variation. To showcase how DPD works, two protein systems, HIV-1 protease and 14-3-3 σ, that both have tremendous structural changes and conformational transitions as displayed by their MD simulation trajectories. The largest structural variation and conformational transition were captured by the first principal component in both cases. In addition, structural clustering and ranking of representative frames by their PC1 values revealed the long-distance nature of the conformational transition and locked the key candidate regions that might be responsible for the large conformational transitions.</p> <p>Secondly, to facilitate further analysis of identification of the long-distance path, a tool called Pearson Coefficient Spiral (PCP) that generates and visualizes Pearson Coefficient to measure the linear correlation between any two sets of residue pairs is developed. PCP allows users to fix one residue pair and examine the correlation of its change with other residue pairs.</p> <p>Thirdly, a set of visualization tools that generate paired atomic distances for the shortlisted candidate residue and captured significant interactions among them were developed. The first tool is the Residue Interaction Network Graph for Paired Atomic Distances (NG-PAD), which not only generates paired atomic distances for the shortlisted candidate residues, but also display significant interactions by a Network Graph for convenient visualization. Second, the Chord Diagram for Interaction Mapping (CD-IP) was developed to map the interactions to protein secondary structural elements and to further narrow down important interactions. Third, a Distance Plotting for Direct Comparison (DP-DC), which plots any two paired distances at user’s choice, either at residue or atomic level, to facilitate identification of similar or opposite pattern change of distances along the simulation time. All the above tools of PLITIP enabled us to identify critical residues contributing to the large conformational transitions in both HIV-1 protease and 14-3-3σ proteins.</p> <p>Beside the above major project, a side project of developing tools to study protein pseudo-symmetry is also reported. It has been proposed that symmetry provides protein stability, opportunities for allosteric regulation, and even functionality. This tool helps us to answer the questions of why there is a deviation from perfect symmetry in protein and how to quantify it.</p>