Submitted by Danielle Karla Martins Silva (danielle.martins@ufpe.br) on 2015-03-13T15:19:57Z No. of bitstreams: 2 TESE Victor Holanda Rusu.pdf: 9721565 bytes, checksum: 063e96f770d05cfa859b3846c87a33f5 (MD5) license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) / Made available in DSpace on 2015-03-13T15:19:57Z (GMT). No. of bitstreams: 2 TESE Victor Holanda Rusu.pdf: 9721565 bytes, checksum: 063e96f770d05cfa859b3846c87a33f5 (MD5) license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Previous issue date: 2014 / CAPES / Desenvolvimento de um campo de força “coarse-grain” para carboidratos. Doutorado em Química, orientador prof. Dr. Roberto Dias Lins Neto, Departamento de Química Fundamental, Universidade Federal de Pernambuco, Recife, Pernambuco, Brasil, 2014. Na natureza, os carboidratos são geralmente encontrados na forma polimérica e/ou complexados com outras biomoléculas, tais como proteínas, lipídeos, etc. A descrição teórica do comportamento destes sistemas biomoleculares requer simulações relativamente longas e consequentemente, computacionalmente custosas. Uma maneira de diminuir os requerimentos computacionais é através do uso de campos de força “coarse-grain” (CG). Nesta abordagem, grupos de átomos são mapeados em esferas diminuindo o número total de partículas no sistema, mas com o custo da perda de detalhes químicos. Neste trabalho desenvolvemos uma nova maneira de expressar carboidratos de forma mais aproximada e combinando com o modelo de água SPC CG GROMOS. O novo campo de força, denominado PITOMBA, corretamente mapeia as conformações barco e cadeira, bem como, os anômeros alfa e beta. A validação dos parâmetros são mostrados para as amilose V e A e α-, β- and γ-ciclodextrinas (CD). Nosso trabalho abre a possibilidade de simular sistemas contendo carboidratos e a termodinâmica de formação de complexos com CDs com um ganho de tempo computacional de 1-2 ordens de grandeza em comparação aos campo de força atomísticos.

An antibody microarray consists of antibody bound to a surface. Antibody microarrays have great potential in many fields, particularly as a tool to detect antigens. Unfortunately, antibodies suffer from poor performance. A greater understanding of how antibodies interact with surfaces would improve microarray design and performance, but experimental methods fall short of being able to observe these interactions. Therefore molecular simulation has emerged as the primary method to study protein/surface interactions.The simulations here were coarse grain simulations performed using the model of Karanicolas and Brooks. Additionally, an advanced surface model was used that allows for different surface chemistries. PyMBAR analysis was used to find heat capacities and determine relative stabilities of different linkers and tethering sites for the antibody/surface system.The actual work looked at how 24 different tethering sites affect antibody stability on two different surfaces and examined nine linkers varying in length and rigidity. Ultimately the findings were that antibody stability is a function of tethering position when tethered to a hydrophobic surface, but not when tethered to a hydrophilic surface. Furthermore, the length and rigidity of the linkers do not have a significant impact on stability.

Configurable devices have become more and more popularnowadays. This is because they can improve the system performance inmany ways. In this thesis work it is studied how introduction of coarse grain configurability can improve the ePUMA, the low power highspeed DSP platform, in terms ofperformance and power consumption. This study takes two DSP algorithms, Fast Fourier Transform (FFT) and FIR filtering asbenchmarks to study the effect of this new feature. Architectures are presented for calculation of FFT and FIR filters and it is shown how they can contribute to the system performance. Finally it is suggestedto consider coarse grain configurability as an option for improvement of the system.

A coarse-grain parallel multi-block algorithm was designed for CHEQNS - a multi-block solver for solving chemically reacting flows in local chemical equilibrium and has been implemented using the Message Passing Interface (MPI). The parallel implementation confirms to the Single Program Multiple Data (SPMD) model. The parallel implementation uses synchronous update of fluxes across the block-block boundaries. The solution algorithm consists of block-decoupled Gauss-Seidel iterations. The coupling between the sub-domains on different processors occurs at the Newton iteration level. The parallel implementation is general and can accept an arbitrary arrangement of blocks in multi-block configuration with multiple blocks per processor. The parallel implementation has been verified against the results from the sequential multi-block solver for different types of flows. The parallel performance has been studied in terms of speed-up and efficiency. The influence of parallelization on the convergence was also studied.

The use of computational simulation to study the dynamics and interactions of macromolecules has become an important tool in the field of biochemistry. A common method to perform these simulations is to use all-atom explicit-solvent molecular dynamics (MD). However, due to the limitations in computational power currently available, this method is not practical for simulating large-scale biomolecular systems on long timescales. An alternative is to perform implicit-solvent Brownian dynamics (BD) simulations using a coarse grained (CG) model that allows for increased computational efficiency. However, if simulations using the CG model are not realistic, then the gain in computational efficiency from using a CG model is not worthwhile. This thesis describes the derivation of a set of bonded and nonbonded CG potential functions for use in implicit-solvent BD simulations of proteins derived from all-atom explicit-solvent MD simulations of amino acids. To determine which force field and water model to use in the MD simulations, Chapter II describes 1 Μs all-atom explicit-solvent MD simulations of glycine, asparagine, phenylalanine, and valine solutions at 50, 100, 200 and 300 mg/ml concentrations performed using eight different force field and water model combinations. To evaluate the accuracy of the force fields at high solute concentrations, the density, viscosity, and dielectric increments of the four amino acids were calculated from the simulations and compared to experimental results. Additionally, the change in the strength of hydrophobic and electrostatic interactions with increasing solute concentration was calculated for each force field and water model combination. As a result of this study, the Amber ff99SB-ILDN force field and TIP4P-Ew explicit-solvent water model were chosen for all subsequent MD simulations. Chapter III describes the derivation of CG bonded potential functions from 1 Μs all-atom explicit-solvent MD simulations of each of the twenty amino acids, including a separate simulation for protonated histidine. The angle and dihedral probability distributions sampled during the MD simulations were used to optimize the bonded potential functions using the iterative Boltzmann inversion (IBI) method. Chapter IV describes the derivation of CG nonbonded potential functions from 1 Μs all-atom explicit-solvent MD simulations of every possible pairing of the amino acids (231 different systems). The radial distribution functions calculated from these MD simulations were used to optimize a set of nonbonded CG potential functions using the IBI method. The optimized set of bonded and nonbonded potential functions, which is termed COFFDROP (COarse-grained Force Field for Dynamic Representation Of Proteins), quantitatively reproduced all of the calculated MD distributions. To determine if COFFDROP would be useful for simulations of bimolecular systems, Chapter V describes the testing of the transferability of the force field. First, COFFDROP was used to simulate concentrated amino acid solutions. The clustering of the solutes in these simulations was directly compared with results from corresponding all-atom explicit-solvent MD simulations and found to be in excellent agreement. Next, BD simulations of 9.2 mM solutions of the small protein villin headpiece were performed. The proteins aggregated during these simulations, which is in agreement with results from MD simulation but in disagreement with experiment. After scaling the strength of COFFDROP's nonbonded potential functions by a factor of 0.8 and rerunning the BD simulations, the amount of aggregation was comparable to experimental observations. Based on these results, COFFDROP is likely to be applicable in CG BD simulations of large, highly concentrated, biomolecular systems.

Membrane active peptides with the ability to cross the plasma membrane represent a promising class of therapeutic compounds. However, translocation efficacy and membrane toxicity of these peptides appear correlated and a better understanding of their mechanisms of action is needed to achieve the desired effect. Here, a range of coarse grain molecular dynamics simulations have been performed to systematically investigate the interactions of such cell-penetrating peptides (CPPs) with biologically relevant membranes. Challenges associated to the development of a suitable asymmetric mammalian membrane model demonstrated the importance of lipid species distribution on the bilayer mechanical properties, as well as the effect of coarse graining on its electrostatic properties. However, simulations successfully discriminated between two CPPs, penetratin and transportan, and were consistent with the experimental data available for these. The results obtained suggest that the ability of transportan peptides to aggregate into flexible, dynamic, transmembrane bundles is responsible for their relative membrane toxicity. The stability and structure of these aggregates, as well as the extent of the bilayer perturbations they induced, were shown to depend on the membrane composition and asymmetry, thus providing a molecular basis to explain how the toxicity of CPPs is modulated by membranes. In particular, bilayer destabilisation was enhanced by the presence of anionic lipids and hampered by that of cholesterol. Transportan aggregates were also observed to trigger lipid flip-flops above a certain size and a new pathway for such events, not relying on the formation of water defects, was characterised.

Water plays a critical role in the function and structure of biological systems. Current techniques to study biologically relevant events that span many length and time scales are limited by the prohibitive computational cost of including accurate effects from the aqueous environment. The aim of this work is to expand the reach of current molecular dynamics techniques by reducing the computational cost for achieving an accurate description of water and its effects on biomolecular systems. This work builds from the assumption that the “local” effect of water (e.g. the local orientational preferences and hydrogen bonding) can be effectively modelled considering only the atomistic detail in a very limited region. A recent adaptive resolution simulation technique (AdResS) has been developed to practically apply this idea; in this work it will be extended to systems of simple hydrophobic solutes to determine a characteristic length for which thermodynamic, structural, and dynamic properties are preserved near the solute. This characteristic length can then be used for simulation of biomolecular systems, specifically those involving protein dynamics in water. Before this can be done, current coarse grain models must be adapted to couple with a coarse grain model of water. This thesis is organized in to five chapters. The first will give an overview of water, and the current methodologies used to simulate water in biological systems. The second chapter will describe the AdResS technique and its application to simple test systems. The third chapter will show that this method can be used to accurately describe hydrophobic solutes in water. The fourth chapter describes the use of coarse grain models as a starting point for targeted search with all-atom models. The final chapter will describe attempts to couple a coarse grain model of a protein with a single-site model for water, and it’s implications for future multi-resolution studies.

Polymer nanocomposites refer to a broad range of composite materials with polymer acting as the matrix and any material which has at least one dimension in the order of 1 ~ 100 nanometer acting as the filler. Due to unprecedented improvement observed in properties of the nanocomposites, research interest in this area has grown exponentially in recent years. In designing better nano-composites for advanced technological applications some of the major challenges are: understanding the structure-property relationships, interaction and integrity of the two components at the interface, the role of nanofillers in enhancing the properties of the resulting material. In our work, we have utilized first principle calculations, atomistic simulations, coarse-grained modeling and constitutive equations to develop structureproperty relationships for an amorphous aromatic piezoelectric polyimide substituted with nitrile dipole, carbon nanotubes and resulting nanocomposites. We have studied in detail structure-property relationships for carbon nanotubes and (? ?CN)APB/ODPA polyimide. We have developed chemically sound coarse-grained model based on atomic level simulations of the piezoelectric polyimide to address the larger length and time scale phenomena. The challenge of coarse grain model for these polymers is to reproduce electrical properties in addition to the structure and energetics; our model is the first to successfully achieve this goal. We have compared and analyzed atomistic scale simulation results on the nanocomposite with those predicted from micromechanics analysis. Notably, we have investigated the time dependent response of these highly complex polymers, to our best knowledge this is the first of its kind. In particular we have studied the thermal, mechanical and dielectric properties of the polyimide, nanotube and their nanocomposites through multi-scale modeling technique. We expect the results obtained and understanding gained through modeling and simulations may be used in guiding development of new nanocomposites for various advanced future applications. In conclusion we have developed a computational paradigm to rationally develop next generation nano-materials.

As the number of processors in multiprocessor system-on-chip devices continues to increase, the complexity required for full cache coherence support is often unwarranted for application-specific designs. Bus-based interconnects are no longer suitable for larger-scale systems, and the logic and storage overhead associated with the use of a complex packet-switched network and directory-based cache coherence may be undesirable in single-chip systems. Unidirectional rings are a suitable alternative because they offer many properties favorable to both on-chip implementation and to supporting cache coherence. Reducing the overhead of cache coherence traffic is, however, a concern for these systems. This thesis adapts two filter structures that are based on principles of coarse-grained coherence tracking, and applies them to a ring-based multiprocessor. The first structure tracks the total number of blocks of remote data cached by all processors in a node for a set of regions, where a region is a large area of memory referenced by the upper bits of an address. The second structure records regions of local data whose contents are not cached by any remote node. When used together to filter incoming or outgoing requests, these structures reduce the extent of coherence traffic and limit the transmission of coherent requests to the necessary parts of the system. A complete single-chip multiprocessor system that includes the proposed filters is designed and implemented in programmable logic for this thesis. The system is composed of nodes of bus-based multiprocessors, and each node includes a common memory, two or more pipelined 32-bit processors with coherent data caches, a split-transaction bus with separate lines for requests and responses, and an interface for the system-level ring interconnect. Two coarse-grained filters are attached to each node to reduce the impact of coherence traffic on the system. Cache coherence within the node is enforced through bus snooping, while coherence across the interconnect is supported by a reduced-complexity ring snooping protocol. Main memory is globally shared and is physically distributed among the nodes. Results are presented to highlight the system's key implementation points. Synthesis results are presented in order to evaluate hardware overhead, and operational results are shown to demonstrate the functionality of the multiprocessor system and of the filter structures. / Thesis (Master, Electrical & Computer Engineering) -- Queen's University, 2007-10-24 10:16:47.81 / Financial support for this work was provided by the National Sciences and Engineering Research Council of Canada, Communications and Information Technology Ontario, and Queen's University.

Molecular dynamics simulations are a theoretical method enabling to trace the movement of atoms within a system. The system studied is usually treated on the atomistic level, however its overall properties can be also described satisfactory if several atoms are handled as one particle (coarse-grained molecular dynamics). This thesis presents molecular modeling and (coarse-grained) molecular dynamics as tools for the description of different biologically relevant systems. The coarse-grained force field parameters had to be developed prior to characterization of the thylakoid membrane from cyanobacterium Synechocystis PCC6803. Two different compositions of the membrane were studied in order to reveal differences in their behavior. The PsbI subunit of photosystem II was embedded into the thylakoid membrane and its behavior, both as an isolated protein and as a cluster of several units, was described. The last system examined was the C-type lectin-like domain of NKR-P1, a surface receptor of natural killer cells. Attention was payed to its structural characterization.