Antiviral drug resistance is a major problem in the treatment of viral infections, including influenza and hepatitis C virus (HCV). Influenza neuraminidase (NA) is a viral sialidase on the surface of the influenza virion and a primary antiviral target in influenza. Two subtypes of NA predominate in humans, N1 and N2, but different patterns of drug resistance have emerged in each subtype. To provide a framework for understanding the structural basis of subtype specific drug resistance mutations in NA, we used molecular dynamics simulations to define dynamic substrate envelopes for NA to determine how different patterns of drug resistance have emerged in N1 and N2 NA. Furthermore, we used the substrate envelope to analyze HCV NS3/4A protease inhibitors in clinical development. In addition, influenza hemagglutinin (HA) is a primary target of neutralizing antibodies against influenza. Novel broadly neutralizing antibodies (BnAbs) against the stem region of HA have been described and inhibit several influenza viral subtypes, but antibody neutralization escape mutations have emerged. We identified potential escape mutations in broadly neutralizing antibody F10 that may impact protein dynamics in HA that are critical for function. We also solved crystal structures of antibody fragments that are important for understanding the structural basis of antibody binding for influenza BnAbs. These studies can inform the design of improved therapeutic strategies against viruses by incorporating an understanding of structural elements that are critical for function, such as substrate processing and protein dynamics, into the development of novel therapeutics that are robust against resistance.

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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.

Formulamos um modelo simplificado para o estudo do processo de injeção de solvente em reservatórios de petróleo, onde o fluido injetado (um ácido) tem a capacidade de dissolver parcialmente a matriz sólida. Como hipóteses principais, consideramos que o solvente e o soluto (componente químico que constitui o meio poroso) são espécies totalmente miscíveis, a viscosidade da mistura solvente + soluto não varia com a concentração de soluto, há significativa transferência de massa entre as fases e a permeabilidade do meio poroso varia linearmente com a porosidade. O modelo é formado por duas Equações Diferenciais Parciais, uma do tipo Convecção-Difusão a outra é do tipo Convecção-Reação. Para resolução numérica, desenvolvemos uma metodologia que denominamos de EPEC (Explícita Porosidade e Explícita Concentração). Tal metodologia se baseia em um limitador de fluxo do tipo TVD e em diferenças finitas centradas de segunda ordem. Em adição, o EPEC emprega uma técnica de separação de operadores. Deste modo, em cada passo de tempo, realizamos inicialmente o cálculo explícito da porosidade seguido do cálculo explícito da concentração do solvente. Assim, obtemos um desacoplamento natural das equações que descrevem o problema. Resultados de simulações são apresentados para um meio poroso bidimensional, após sessenta dias de injeção de solvente. / We formulate a simplified Model to study the process of solvent injection in petroleum Reservoir, where the injected fluid (an acid) can partially dissolve a solid matrix. As prime hypotheses, we considered that solvent an soluble component are completely mixed, the viscosity of the fluid does not vary with the concentration of the soluble component, theres significant transfer of mass between the parts and, the permeability of media porous changes linearly with porosity. The model is formed by two Partial Differential Equation, one is convection-diffusion type and another is a convection-reaction type. The Numerical Resolution weve developed a method called EPEC (Explicit Porosity Explicit Concentration). Such methodology is based upon a Limiting of Flow of TVD type and, used Centered Finite Differences of second order. In addition, the EPEC use a operators separation technique. This way, every time, first we clearly calculate the porosity and then the concentration of solvent is calculated. Thus we obtain a natural decoupling of the equations that describe the problem. Simulation results are presented to a two dimensional media porous after sixty days of solvent injection.