19 resultados para Interpretive structural modelling (ISM)

em CentAUR: Central Archive University of Reading - UK


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The EfeUOB system of Escherichia coli is a tripartite, low pH, ferrous iron transporter. It resembles the high-affinity iron transporter (Ftr1p-Fet3p) of yeast in that EfeU is homologous to Ftr1p, an integral-membrane iron-permease. However, EfeUOB lacks an equivalent of the Fet3p component—the multicopper oxidase with three cupredoxin-like domains. EfeO and EfeB are periplasmic but their precise roles are unclear. EfeO consists primarily of a C-terminal peptidase-M75 domain with a conserved ‘HxxE’ motif potentially involved in metal binding. The smaller N-terminal domain (EfeO-N) is predicted to be cupredoxin (Cup) like, suggesting a previously unrecognised similarity between EfeO and Fet3p. Our structural modelling of the E. coli EfeO Cup domain identifies two potential metal-binding sites. Site I is predicted to bind Cu2+ using three conserved residues (C41 and 103, and E66) and M101. Of these, only one (C103) is conserved in classical cupredoxins where it also acts as a Cu ligand. Site II most probably binds Fe3+ and consists of four well conserved surface Glu residues. Phylogenetic analysis indicates that the EfeO-Cup domains form a novel Cup family, designated the ‘EfeO-Cup’ family. Structural modelling of two other representative EfeO-Cup domains indicates that different subfamilies employ distinct ligand sets at their proposed metal-binding sites. The ~100 efeO homologues in the bacterial sequence databases are all associated with various iron-transport related genes indicating a common role for EfeO-Cup proteins in iron transport, supporting a new copper-iron connection in biology.

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Hedgehog proteins are important cell-cell signalling proteins utilized during the development of multicellular animals. Members of the hedgehog gene family have not been detected outside the Metazoa, raising unanswered questions about their evolutionary origin. Here we report a highly unusual hedgehog-related gene from a choanoflagellate, a close unicellular relative of the animals. The deduced C-terminal domain, Hoglet-C, is homologous to the autocatalytic domain of Hedgehog proteins and is predicted to function in autocatalytic cleavage of the precursor peptide. In contrast, the N-terminal Hoglet-N peptide has no similarity to the signalling peptide of Hedgehog (Hh-N). Instead, Hoglet-N is deduced to be a secreted protein with an enormous threonine-rich domain of unprecedented size and purity (over 200 threonine residues) and two polysaccharide-binding domains. Structural modelling reveals that these domains have a novel combination of features found in cellulose-binding domains (CBD) of types IIa and IIb, and are expected to bind cellulose. We propose that the two CBD domains enable Hoglet-N to bind to plant matter, tethering an amorphous nucleophilic anchor, facilitating transient adhesion of the choanoflagellate cell. Since HhC and Hoglet-C are homologous, but Hh-N and Hoglet-N are not, we argue that metazoan hedgehog genes evolved by fusion of two distinct genes.

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This paper exploits a structural time series approach to model the time pattern of multiple and resurgent food scares and their direct and cross-product impacts on consumer response. A structural time series Almost Ideal Demand System (STS-AIDS) is embedded in a vector error correction framework to allow for dynamic effects (VEC-STS-AIDS). Italian aggregate household data on meat demand is used to assess the time-varying impact of a resurgent BSE crisis (1996 and 2000) and the 1999 Dioxin crisis. The VEC-STS-AIDS model monitors the short-run impacts and performs satisfactorily in terms of residuals diagnostics, overcoming the major problems encountered by the customary vector error correction approach.

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Two 28-membered octaazamacrocycles, [28]py(2)N(6) and Me-2[28]py(2)N(6), have been synthesized. The protonation constants of the N-methyl. derivative and the stability constants of its complexes with Ni2+, Cu2+, Zn2+, Cd2+, and Pb2+ were determined at 25degreesC in 0.10 mol dm(-3) KNO3. The high overall basicity of Me-2[28]py(2)N(6) is ascribed to the weaker repulsion between protonated contiguous charged ammonium sites separated by propyl chains. These studies together with NMR, UV-vis and EPR spectroscopies indicated the presence of mono- and di-nuclear species, The single crystal structure of the complex [Ni-2([28]py(2)N(6))(H2O)(4)]Cl-4.3H(2)O was determined, and showed each nickel centre in a distorted octahedral co-ordination environment. The nickel centres are held within the macrocycle at a large distance of 6.991(g) Angstrom from each other. The formation of mononuclear complexes was evaluated theoretically via molecular mechanics (MM) and molecular dynamics (MD) calculations and showed that these large macrocycles have sufficient flexibility to encapsulate metal ions with different stereo-electronic sizes. Structures for small and large metal ions are proposed.

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This paper describes the results and conclusions of the INCA (Integrated Nitrogen Model for European CAtchments) project and sets the findings in the context of the ELOISE (European Land-Ocean Interaction Studies) programme. The INCA project was concerned with the development of a generic model of the major factors and processes controlling nitrogen dynamics in European river systems, thereby providing a tool (a) to aid the scientific understanding of nitrogen transport and retention in catchments and (b) for river-basin management and policy-making. The findings of the study highlight the heterogeneity of the factors and processes controlling nitrogen dynamics in freshwater systems. Nonetheless, the INCA model was able to simulate the in-stream nitrogen concentrations and fluxes observed at annual and seasonal timescales in Arctic, Continental and Maritime-Temperate regimes. This result suggests that the data requirements and structural complexity of the INCA model are appropriate to simulate nitrogen fluxes across a wide range of European freshwater environments. This is a major requirement for the production of coupled fiver-estuary-coastal shelf models for the management of our aquatic environment. With regard to river-basin management, to achieve an efficient reduction in nutrient fluxes from the land to the estuarine and coastal zone, the model simulations suggest that management options must be adaptable to the prevailing environmental and socio-economic factors in individual catchments: 'Blanket approaches' to environmental policy appear too simple. (c) 2004 Elsevier B.V. All rights reserved.

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Uncertainties associated with the representation of various physical processes in global climate models (GCMs) mean that, when projections from GCMs are used in climate change impact studies, the uncertainty propagates through to the impact estimates. A complete treatment of this ‘climate model structural uncertainty’ is necessary so that decision-makers are presented with an uncertainty range around the impact estimates. This uncertainty is often underexplored owing to the human and computer processing time required to perform the numerous simulations. Here, we present a 189-member ensemble of global river runoff and water resource stress simulations that adequately address this uncertainty. Following several adaptations and modifications, the ensemble creation time has been reduced from 750 h on a typical single-processor personal computer to 9 h of high-throughput computing on the University of Reading Campus Grid. Here, we outline the changes that had to be made to the hydrological impacts model and to the Campus Grid, and present the main results. We show that, although there is considerable uncertainty in both the magnitude and the sign of regional runoff changes across different GCMs with climate change, there is much less uncertainty in runoff changes for regions that experience large runoff increases (e.g. the high northern latitudes and Central Asia) and large runoff decreases (e.g. the Mediterranean). Furthermore, there is consensus that the percentage of the global population at risk to water resource stress will increase with climate change.

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Purpose – While Freeman's stakeholder management approach has attracted much attention from both scholars and practitioners, little empirical work has considered the interconnectedness of organisational perspectives and stakeholder perspectives. The purpose of this paper is to respond to this gap by developing and empirically testing a bi-directional model of organisation/stakeholder relationships. Design/methodology/approach – A conceptual framework is developed that integrates how stakeholders are affected by organisations with how they affect organisations. Quantitative data relating to both sides of the relationship are obtained from 700 customers of a European service organisation and analysed using partial least squares structural equation modelling technique. Findings – The findings provide empirical support for the notion of mutual dependency between organisations and stakeholders as advocated by stakeholder theorists. The results suggest that the way stakeholders relate to organisations is dependent on how organisations relate to stakeholders. Originality/value – The study is original on two fronts: first, it provides a framework and process that can be used by researchers to model bi-directional research with other stakeholder groups and in different contexts. Second, the study presents an example application of bi-directional research by empirically linking organisational and stakeholder expectations in the case of customers of a UK service organisation.

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In this paper we examine the order of integration of EuroSterling interest rates by employing techniques that can allow for a structural break under the null and/or alternative hypothesis of the unit-root tests. In light of these results, we investigate the cointegrating relationship implied by the single, linear expectations hypothesis of the term structure of interest rates employing two techniques, one of which allows for the possibility of a break in the mean of the cointegrating relationship. The aim of the paper is to investigate whether or not the interest rate series can be viewed as I(1) processes and furthermore, to consider whether there has been a structural break in the series. We also determine whether, if we allow for a break in the cointegration analysis, the results are consistent with those obtained when a break is not allowed for. The main results reported in this paper support the conjecture that the ‘short’ Euro-currency rates are characterised as I(1) series that exhibit a structural break on or near Black Wednesday, 16 September 1992, whereas the ‘long’ rates are I(1) series that do not support the presence of a structural break. The evidence from the cointegration analysis suggests that tests of the expectations hypothesis based on data sets that include the ERM crisis period, or a period that includes a structural break, might be problematic if the structural break is not explicitly taken into account in the testing framework.

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The organization of non-crystalline polymeric materials at a local level, namely on a spatial scale between a few and 100 a, is still unclear in many respects. The determination of the local structure in terms of the configuration and conformation of the polymer chain and of the packing characteristics of the chain in the bulk material represents a challenging problem. Data from wide-angle diffraction experiments are very difficult to interpret due to the very large amount of information that they carry, that is the large number of correlations present in the diffraction patterns.We describe new approaches that permit a detailed analysis of the complex neutron diffraction patterns characterizing polymer melts and glasses. The coupling of different computer modelling strategies with neutron scattering data over a wide Q range allows the extraction of detailed quantitative information on the structural arrangements of the materials of interest. Proceeding from modelling routes as diverse as force field calculations, single-chain modelling and reverse Monte Carlo, we show the successes and pitfalls of each approach in describing model systems, which illustrate the need to attack the data analysis problem simultaneously from several fronts.

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Determination of the local structure of a polymer glass by scattering methods is complex due to the number of spatial and orientational correlations, both from within the polymer chain (intrachain) and between neighbouring chains (interchain), from which the scattering arises. Recently considerable advances have been made in the structural analysis of relatively simple polymers such as poly(ethylene) through the use of broad Q neutron scattering data tightly coupled to atomistic modelling procedures. This paper presents the results of an investigation into the use of these procedures for the analysis of the local structure of a-PMMA which is chemically more complex with a much greater number of intrachain structural parameters. We have utilised high quality neutron scattering data obtained using SANDALS at ISIS coupled with computer models representing both the single chain and bulk polymer system. Several different modelling approaches have been explored which encompass such techniques as Reverse Monte Carlo refinement and energy minimisation and their relative merits and successes are discussed. These different approaches highlight structural parameters which any realistic model of glassy atactic PMMA must replicate.

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Global wetlands are believed to be climate sensitive, and are the largest natural emitters of methane (CH4). Increased wetland CH4 emissions could act as a positive feedback to future warming. The Wetland and Wetland CH4 Inter-comparison of Models Project (WETCHIMP) investigated our present ability to simulate large-scale wetland characteristics and corresponding CH4 emissions. To ensure inter-comparability, we used a common experimental protocol driving all models with the same climate and carbon dioxide (CO2) forcing datasets. The WETCHIMP experiments were conducted for model equilibrium states as well as transient simulations covering the last century. Sensitivity experiments investigated model response to changes in selected forcing inputs (precipitation, temperature, and atmospheric CO2 concentration). Ten models participated, covering the spectrum from simple to relatively complex, including models tailored either for regional or global simulations. The models also varied in methods to calculate wetland size and location, with some models simulating wetland area prognostically, while other models relied on remotely sensed inundation datasets, or an approach intermediate between the two. Four major conclusions emerged from the project. First, the suite of models demonstrate extensive disagreement in their simulations of wetland areal extent and CH4 emissions, in both space and time. Simple metrics of wetland area, such as the latitudinal gradient, show large variability, principally between models that use inundation dataset information and those that independently determine wetland area. Agreement between the models improves for zonally summed CH4 emissions, but large variation between the models remains. For annual global CH4 emissions, the models vary by ±40% of the all-model mean (190 Tg CH4 yr−1). Second, all models show a strong positive response to increased atmospheric CO2 concentrations (857 ppm) in both CH4 emissions and wetland area. In response to increasing global temperatures (+3.4 °C globally spatially uniform), on average, the models decreased wetland area and CH4 fluxes, primarily in the tropics, but the magnitude and sign of the response varied greatly. Models were least sensitive to increased global precipitation (+3.9 % globally spatially uniform) with a consistent small positive response in CH4 fluxes and wetland area. Results from the 20th century transient simulation show that interactions between climate forcings could have strong non-linear effects. Third, we presently do not have sufficient wetland methane observation datasets adequate to evaluate model fluxes at a spatial scale comparable to model grid cells (commonly 0.5°). This limitation severely restricts our ability to model global wetland CH4 emissions with confidence. Our simulated wetland extents are also difficult to evaluate due to extensive disagreements between wetland mapping and remotely sensed inundation datasets. Fourth, the large range in predicted CH4 emission rates leads to the conclusion that there is both substantial parameter and structural uncertainty in large-scale CH4 emission models, even after uncertainties in wetland areas are accounted for.

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The global vegetation response to climate and atmospheric CO2 changes between the last glacial maximum and recent times is examined using an equilibrium vegetation model (BIOME4), driven by output from 17 climate simulations from the Palaeoclimate Modelling Intercomparison Project. Features common to all of the simulations include expansion of treeless vegetation in high northern latitudes; southward displacement and fragmentation of boreal and temperate forests; and expansion of drought-tolerant biomes in the tropics. These features are broadly consistent with pollen-based reconstructions of vegetation distribution at the last glacial maximum. Glacial vegetation in high latitudes reflects cold and dry conditions due to the low CO2 concentration and the presence of large continental ice sheets. The extent of drought-tolerant vegetation in tropical and subtropical latitudes reflects a generally drier low-latitude climate. Comparisons of the observations with BIOME4 simulations, with and without consideration of the direct physiological effect of CO2 concentration on C3 photosynthesis, suggest an important additional role of low CO2 concentration in restricting the extent of forests, especially in the tropics. Global forest cover was overestimated by all models when climate change alone was used to drive BIOME4, and estimated more accurately when physiological effects of CO2 concentration were included. This result suggests that both CO2 effects and climate effects were important in determining glacial-interglacial changes in vegetation. More realistic simulations of glacial vegetation and climate will need to take into account the feedback effects of these structural and physiological changes on the climate.