QSAR e dinâmica molecular no estudo de sistemas biomoleculares: predição da atividade biológica de antagonistas do receptor sigma-1 e simulações de bicamadas lipídicas

Diferentes abordagens teóricas têm sido utilizadas em estudos de sistemas biomoleculares com o objetivo de contribuir com o tratamento de diversas doenças. Para a dor neuropática, por exemplo, o estudo de compostos que interagem com o receptor sigma-1 (Sig-1R) pode elucidar os principais fatores associados à atividade biológica dos mesmos. Nesse propósito, estudos de Relações Quantitativas Estrutura-Atividade (QSAR) utilizando os métodos de regressão por Mínimos Quadrados Parciais (PLS) e Rede Neural Artificial (ANN) foram aplicados a 64 antagonistas do Sig-1R pertencentes à classe de 1-arilpirazóis. Modelos PLS e ANN foram utilizados com o objetivo de descrever comportamentos lineares e não lineares, respectivamente, entre um conjunto de descritores e a atividade biológica dos compostos selecionados. O modelo PLS foi obtido com 51 compostos no conjunto treinamento e 13 compostos no conjunto teste (r² = 0,768, q² = 0,684 e r²teste = 0,785). Testes de leave-N-out, randomização da atividade biológica e detecção de outliers confirmaram a robustez e estabilidade dos modelos e mostraram que os mesmos não foram obtidos por correlações ao acaso. Modelos também foram gerados a partir da Rede Neural Artificial Perceptron de Multicamadas (MLP-ANN), sendo que a arquitetura 6-12-1, treinada com as funções de transferência tansig-tansig, apresentou a melhor resposta para a predição da atividade biológica dos compostos (r²treinamento = 0,891, r²validação = 0,852 e r²teste = 0,793). Outra abordagem foi utilizada para simular o ambiente de membranas sinápticas utilizando bicamadas lipídicas compostas por POPC, DOPE, POPS e colesterol. Os estudos de dinâmica molecular desenvolvidos mostraram que altas concentrações de colesterol induzem redução da área por lipídeo e difusão lateral e aumento na espessura da membrana e nos valores de parâmetro de ordem causados pelo ordenamento das cadeias acil dos fosfolipídeos. As bicamadas lipídicas obtidas podem ser usadas para simular interações entre lipídeos e pequenas moléculas ou proteínas contribuindo para as pesquisas associadas a doenças como Alzheimer e Parkinson. As abordagens usadas nessa tese são essenciais para o desenvolvimento de novas pesquisas em Química Medicinal Computacional.

Dinâmica molecular de sistemas iônicos poliatômicos: modelos polarizável e não-polarizável

Simulações de sais de carbonato fundidos pelo método de Dinâmica Molecular (MD) foram efetuadas com o modelo polarizável de cargas flutuantes (FC). O modelo de cargas flutuantes implementa os efeitos de polarização pelo método de Lagrangiano estendido, onde as variáveis extras são as próprias cargas parciais do íon poliatômico. O modelo FC foi parametrizado por meio de cálculos ab inito, aplicado ao ânion carbonato. Cálculos de Química Quântica ab initio foram utilizados para corroborar o modelo proposto para o ânion carbonato. Os sistemas investigados consistem em misturas de carbonatos alcalinos fundidos, Li2CO3/K2CO3, os quais são utilizados como eletrólitos em células a combustível. As simulações MD foram utilizadas para verificar o efeito da polarização dos ânions sobre a estrutura e dinâmica do líquido. Estudamos o efeito da inclusão de polarização sobre a condutividade do eletrólito.

A formal framework for modelling complex network management systems

Society today is completely dependent on computer networks, the Internet and distributed systems, which place at our disposal the necessary services to perform our daily tasks. Subconsciously, we rely increasingly on network management systems. These systems allow us to, in general, maintain, manage, configure, scale, adapt, modify, edit, protect, and enhance the main distributed systems. Their role is secondary and is unknown and transparent to the users. They provide the necessary support to maintain the distributed systems whose services we use every day. If we do not consider network management systems during the development stage of distributed systems, then there could be serious consequences or even total failures in the development of the distributed system. It is necessary, therefore, to consider the management of the systems within the design of the distributed systems and to systematise their design to minimise the impact of network management in distributed systems projects. In this paper, we present a framework that allows the design of network management systems systematically. To accomplish this goal, formal modelling tools are used for modelling different views sequentially proposed of the same problem. These views cover all the aspects that are involved in the system; based on process definitions for identifying responsible and defining the involved agents to propose the deployment in a distributed architecture that is both feasible and appropriate.

Conceptual Modelling of Complex Network Management Systems

Society, as we know it today, is completely dependent on computer networks, Internet and distributed systems, which place at our disposal the necessary services to perform our daily tasks. Moreover, and unconsciously, all services and distributed systems require network management systems. These systems allow us to, in general, maintain, manage, configure, scale, adapt, modify, edit, protect or improve the main distributed systems. Their role is secondary and is unknown and transparent to the users. They provide the necessary support to maintain the distributed systems whose services we use every day. If we don’t consider network management systems during the development stage of main distributed systems, then there could be serious consequences or even total failures in the development of the distributed systems. It is necessary, therefore, to consider the management of the systems within the design of distributed systems and systematize their conception to minimize the impact of the management of networks within the project of distributed systems. In this paper, we present a formalization method of the conceptual modelling for design of a network management system through the use of formal modelling tools, thus allowing from the definition of processes to identify those responsible for these. Finally we will propose a use case to design a conceptual model intrusion detection system in network.

The Multiple Signaling Systems Regulating Virulence in Pseudomonas aeruginosa

Cell-to-cell communication is a major process that allows bacteria to sense and coordinately react to the fluctuating conditions of the surrounding environment. In several pathogens, this process triggers the production of virulence factors and/or a switch in bacterial lifestyle that is a major determining factor in the outcome and severity of the infection. Understanding how bacteria control these signaling systems is crucial to the development of novel antimicrobial agents capable of reducing virulence while allowing the immune system of the host to clear bacterial infection, an approach likely to reduce the selective pressures for development of resistance. We provide here an up-to-date overview of the molecular basis and physiological implications of cell-to-cell signaling systems in Gram-negative bacteria, focusing on the well-studied bacterium Pseudomonas aeruginosa. All of the known cell-to-cell signaling systems in this bacterium are described, from the most-studied systems, i.e., N-acyl homoserine lactones (AHLs), the 4-quinolones, the global activator of antibiotic and cyanide synthesis (GAC), the cyclic di-GMP (c-di-GMP) and cyclic AMP (cAMP) systems, and the alarmones guanosine tetraphosphate (ppGpp) and guanosine pentaphosphate (pppGpp), to less-well-studied signaling molecules, including diketopiperazines, fatty acids (diffusible signal factor [DSF]-like factors), pyoverdine, and pyocyanin. This overview clearly illustrates that bacterial communication is far more complex than initially thought and delivers a clear distinction between signals that are quorum sensing dependent and those relying on alternative factors for their production.

Concentrations and isotopic compositions of low molecular weight hydrocarbons in hydrothermal fluids from ODP Field, Middle Valley, northern Juan de Fuca Ridge

The presence of sedimentary organic matter blanketing midocean ridge crests has a potentially strong impact on metal transport in hydrothermal vent fluids. To constrain the role of organic matter in metal mobility during hydrothermal sediment alteration, we reacted organic-rich diatomaceous ooze from Guaymas Basin, Gulf of California, and organic-poor hemipelagic mud from Middle Valley, northern Juan de Fuca Ridge, with seawater and a Na-Ca-K-Cl fluid of seawater chlorinity, at 275° to 400°C, 350 to 500 bars, and initial fluid: sediment mass ratios ranging from 1.6 to 9.8. Reaction of these fluids with both sediment types released CO2 and high concentrations of ore-forming metals (Fe, Mn, Zn, Pb) to solution. Relatively low concentrations of Cu were observed in solution and likely reflect the reducing conditions that resulted from the presence of sedimentary organic matter. Both the concentrations of CO2 and dissolved metals were lower in fluids reacted with Middle Valley sediment compared with aqueous concentrations in fluids reacted with Guaymas Basin sediment. During alteration of both sediment types, metal concentrations varied strongly as a function of temperature, increasing by up to an order of magnitude over the 75°C range of each experiment. Major element fluid chemistry and observed alteration assemblages suggest that during hydrothermal alteration of organic-lean sediment from Middle Valley a feldspar-quartz-illite mineral assemblage buffered in situ pH. In contrast, data from the experimental alteration of organic-rich Guaymas Basin sediment suggest that a calcite-plagioclase-quartz assemblage regulated in situ pH. Fluid speciation calculations suggest that in situ pH during Guaymas Basin sediment alteration was lower than during alteration of Middle Valley sediment and accounts for the substantially greater metal mobility at a given temperature and pressure during the former experiment. Comparison of our results with the results of basalt alteration experiments indicate that except for Cu, hydrothermal sediment alteration results in equal or greater concentrations of ore-forming metals at a given temperature and pressure. Accordingly, the presence of ore-forming metals in fluids currently venting from sediment-covered hydrothermal systems at concentrations substantially lower than in fluids from bare-rock systems may reflect chemical reequilibration during subsurface cooling within the sediment pile.

Facilitating Realistic and Efficient Applications of Ab Initio Electronic Dynamics for Polyatomic Systems

Thesis (Ph.D.)--University of Washington, 2016-06

Molecular dynamics simulation of organic-inorganic nanocomposites: Layering behavior and interlayer structure of organoclays

Isothermal-isobaric (NPT) molecular dynamics simulation has been performed to investigate the layering behavior and structure of nanoconfined quaternary alkylammoniums in organoclays. This work is focused on systems consisting of two clay layers and a number of alkylammoniums, and involves the use of modified Dreiding force field. The simulated basal spacings of organoclays agree satisfactorily with the experimental results in the literature. The atomic density profiles in the direction normal to the clay surface indicate that the alkyl chains within the interlayer space of montmorillonite exhibit an obvious layering behavior. The headgroups of long alkyl chains are distributed within two layers close to the clay surface, whereas the distributions of methyl and methylene groups are strongly dependent on the alkyl chain length and clay layer charge. Monolayer, bilayer, and pseudo-trilayer structures are found in organoclays modified with single long alkyl chains, which are identical to the structural models based on the measured basal spacings. A pseudo-quadrilayer structure, for the first time to our knowledge, is also identified in organoclays with double long alkyl chains. In the mixture structure of paraffin-type and multilayer, alkyl chains do not lie flat within a single layer but interlace, and also jump to the next layer in pseudo-trilayer as well as next nearest layer in pseudo-quadrilayer.

Estimating the specific heat capacity of starch-water-glycerol systems as a function of temperature and compositions

Increasing interests in the use of starch as biodegradable plastic materials demand, amongst others, accurate information on thermal properties of starch systems particularly in the processing of thermoplastic starch (TPS), where plasticisers (water and glycerol) are added. The specific heat capacity of starch-water-glycerol mixtures was determined within a temperature range of 40-120degreesC. A modulated temperature differential scanning calorimeter (MTDSC) was employed and regression equations were obtained to predict the specific heat capacity as a function of temperature, water and glycerol content for four maize starches of differing amylose content (0 - 85%). Generally, temperature and water content are directly proportional to the specific heat capacity of the systems, but the influence of glycerol content on the thermal property varied according to the starch type.

Lipid, sugar and liposaccharide based delivery systems 2

The vast majority of biologically active compounds will never be considered as potential drugs due to inherently poor bioavailability. This review discusses the progress in the development of chemical systems to improve the metabolic stability, absorption and physicochemical properties of potential drugs. Delivery systems that involve the conjugation of lipid and/or sugar moieties are highlighted, as well as novel methods of conjugation of these groups to drugs. The use of sugar molecules to target drugs to particular organs or cells is also discussed, as is the use of lipids in the growing area of gene delivery. This is an update of a previous review [1].

Three-dimensional solitons in coupled atomic-molecular Bose-Einstein condensates

We present a theoretical analysis of three-dimensional (3D) matter-wave solitons and their stability properties in coupled atomic and molecular Bose-Einstein condensates (BECs). The soliton solutions to the mean-field equations are obtained in an approximate analytical form by means of a variational approach. We investigate soliton stability within the parameter space described by the atom-molecule conversion coupling, the atom-atom s-wave scattering, and the bare formation energy of the molecular species. In terms of ordinary optics, this is analogous to the process of sub- or second-harmonic generation in a quadratic nonlinear medium modified by a cubic nonlinearity, together with a phase mismatch term between the fields. While the possibility of formation of multidimensional spatiotemporal solitons in pure quadratic media has been theoretically demonstrated previously, here we extend this prediction to matter-wave interactions in BEC systems where higher-order nonlinear processes due to interparticle collisions are unavoidable and may not be neglected. The stability of the solitons predicted for repulsive atom-atom interactions is investigated by direct numerical simulations of the equations of motion in a full 3D lattice. Our analysis also leads to a possible technique for demonstrating the ground state of the Schrodinger-Newton and related equations that describe Bose-Einstein condensates with nonlocal interparticle forces.

On systems thinking, systems biology and the in Silico Plant

The recent summary report of a Department of Energy Workshop on Plant Systems Biology (P.V. Minorsky [2003] Plant Physiol 132: 404-409) offered a welcomed advocacy for systems analysis as essential in understanding plant development, growth, and production. The goal of the Workshop was to consider methods for relating the results of molecular research to real-world challenges in plant production for increased food supplies, alternative energy sources, and environmental improvement. The rather surprising feature of this report, however, was that the Workshop largely overlooked the rich history of plant systems analysis extending over nearly 40 years (Sinclair and Seligman, 1996) that has considered exactly those challenges targeted by the Workshop. Past systems research has explored and incorporated biochemical and physiological knowledge into plant simulation models from a number of perspectives. The research has resulted in considerable understanding and insight about how to simulate plant systems and the relative contribution of various factors in influencing plant production. These past activities have contributed directly to research focused on solving the problems of increasing biomass production and crop yields. These modeling approaches are also now providing an avenue to enhance integration of molecular genetic technologies in plant improvement (Hammer et al., 2002).

Energy as an entanglement witness for quantum many-body systems

We investigate quantum many-body systems where all low-energy states are entangled. As a tool for quantifying such systems, we introduce the concept of the entanglement gap, which is the difference in energy between the ground-state energy and the minimum energy that a separable (unentangled) state may attain. If the energy of the system lies within the entanglement gap, the state of the system is guaranteed to be entangled. We find Hamiltonians that have the largest possible entanglement gap; for a system consisting of two interacting spin-1/2 subsystems, the Heisenberg antiferromagnet is one such example. We also introduce a related concept, the entanglement-gap temperature: the temperature below which the thermal state is certainly entangled, as witnessed by its energy. We give an example of a bipartite Hamiltonian with an arbitrarily high entanglement-gap temperature for fixed total energy range. For bipartite spin lattices we prove a theorem demonstrating that the entanglement gap necessarily decreases as the coordination number is increased. We investigate frustrated lattices and quantum phase transitions as physical phenomena that affect the entanglement gap.

A comparison of molecular markers for genetic analysis of macadamia

Various marker systems exist for genetic analysis of horticultural species. Isozymes were first applied to the woody perennial nut crop, macadamia, in the early 1990s. The advent of DNA markers saw the development, for macadamia, of STMS (sequence-tagged microsatellite site), RAPD (randomly amplified polymorphic DNA), and RAF (randomly amplified DNA fingerprinting). The RAF technique typically generates dominant markers, but within the dominant marker profiles, certain primers also amplify multi-allelic co-dominant markers that are suspected to be microsatellites. In this paper, we confirm this for one such marker, and describe how RAF primers can be chosen that amplify one or more putative microsatellites. This approach of genotyping anonymous microsatellite markers via RAF is designated RAMiFi (randomly amplified microsatellite fingerprinting). Several marker systems were compared for the type, amount, and cost-efficiency of the information generated, using data from published studies on macadamia. The markers were also compared for the way they clustered a common set of accessions. The RAMiFi approach was identified as the most efficient and economical. The availability of such a versatile tool offers many advantages for the genetic characterisation of horticultural species.

Trait physiology and crop modelling as a framework to link phenotypic complexity to underlying genetic systems

New tools derived from advances in molecular biology have not been widely adopted in plant breeding for complex traits because of the inability to connect information at gene level to the phenotype in a manner that is useful for selection. In this study, we explored whether physiological dissection and integrative modelling of complex traits could link phenotype complexity to underlying genetic systems in a way that enhanced the power of molecular breeding strategies. A crop and breeding system simulation study on sorghum, which involved variation in 4 key adaptive traits-phenology, osmotic adjustment, transpiration efficiency, stay-green-and a broad range of production environments in north-eastern Australia, was used. The full matrix of simulated phenotypes, which consisted of 547 location-season combinations and 4235 genotypic expression states, was analysed for genetic and environmental effects. The analysis was conducted in stages assuming gradually increased understanding of gene-to-phenotype relationships, which would arise from physiological dissection and modelling. It was found that environmental characterisation and physiological knowledge helped to explain and unravel gene and environment context dependencies in the data. Based on the analyses of gene effects, a range of marker-assisted selection breeding strategies was simulated. It was shown that the inclusion of knowledge resulting from trait physiology and modelling generated an enhanced rate of yield advance over cycles of selection. This occurred because the knowledge associated with component trait physiology and extrapolation to the target population of environments by modelling removed confounding effects associated with environment and gene context dependencies for the markers used. Developing and implementing this gene-to-phenotype capability in crop improvement requires enhanced attention to phenotyping, ecophysiological modelling, and validation studies to test the stability of candidate genetic regions.