928 resultados para structure, analysis, modeling


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Receptor activity modifying proteins (RAMPs) are a family of single-pass transmembrane proteins that dimerize with G-protein-coupled receptors. They may alter the ligand recognition properties of the receptors (particularly for the calcitonin receptor-like receptor, CLR). Very little structural information is available about RAMPs. Here, an ab initio model has been generated for the extracellular domain of RAMP1. The disulfide bond arrangement (Cys 27-Cys82, Cys40-Cys72, and Cys 57-Cys104) was determined by site-directed mutagenesis. The secondary structure (a-helices from residues 29-51, 60-80, and 87-100) was established from a consensus of predictive routines. Using these constraints, an assemblage of 25,000 structures was constructed and these were ranked using an all-atom statistical potential. The best 1000 conformations were energy minimized. The lowest scoring model was refined by molecular dynamics simulation. To validate our strategy, the same methods were applied to three proteins of known structure; PDB:1HP8, PDB:1V54 chain H (residues 21-85), and PDB:1T0P. When compared to the crystal structures, the models had root mean-square deviations of 3.8 Å, 4.1 Å, and 4.0 Å, respectively. The model of RAMP1 suggested that Phe93, Tyr 100, and Phe101 form a binding interface for CLR, whereas Trp74 and Phe92 may interact with ligands that bind to the CLR/RAMP1 heterodimer. © 2006 by the Biophysical Society.

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This paper assesses the extent to which the equity markets of Hungary, Poland the Czech Republic and Russia have become less segmented. Using a variety of tests it is shown there has been a consistent increase in the co-movement of some Eastern European markets and developed markets. Using the variance decompositions from a vector autoregressive representation of returns it is shown that for Poland and Hungary global factors are having an increasing influence on equity returns, suggestive of increased equity market integration. In this paper we model a system of bivariate equity market correlations as a smooth transition logistic trend model in order to establish how rapidly the countries of Eastern Europe are moving away from market segmentation. We find that Hungary is the country which is becoming integrated the most quickly. © 2005 ELsevier Ltd. All rights reserved.

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Orthodox contingency theory links effective organisational performance to compatible relationships between the environment and organisation strategy and structure and assumes that organisations have the capacity to adapt as the environment changes. Recent contributions to the literature on organisation theory claim that the key to effective performance is effective adaptation which in turn requires the simultaneous reconciliation of efficiency and innovation which is afforded by an unique environment-organisation configuration. The literature on organisation theory recognises the continuing confusion caused by the fragmented and often conflicting results from cross-sectional studies. Although the case is made for longitudinal studies which comprehensively describe the evolving relationship between the environment and the organisation there is little to suggest how such studies should be executed in practice. Typically the choice is between the approaches of the historicised case study and statistical analysis of large populations which examine the relationship between environment and organisation strategy and/or structure and ignore the product-process relationship. This study combines the historicised case study and the multi-variable and ordinal scale approach of statistical analysis to construct an analytical framework which tracks and exposes the environment-organisation-performance relationship over time. The framework examines changes in the environment, strategy and structure and uniquely includes an assessment of the organisation's product-process relationship and its contribution to organisational efficiency and innovation. The analytical framework is applied to examine the evolving environment-organisation relationship of two organisations in the same industry over the same twenty-five year period to provide a sector perspective of organisational adaptation. The findings demonstrate the significance of the environment-organisation configuration to the scope and frequency of adaptation and suggest that the level of sector homogeneity may be linked to the level of product-process standardisation.

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The receptors for calcitonin gene-related peptide (CGRP) and adrenomedullin (AM) are complexes of the calcitonin receptor-like receptor (CLR) and receptor activity-modifying proteins (RAMP). The CGRP receptor is a CLR/RAMP1 pairing whereas CLR/RAMP2 and CLR/RAMP3 constitute two subtypes of AM receptor: AM(1) and AM(2), respectively. Previous studies identified Glu74 in RAMP3 to be important for AM binding and potency. To further understand the importance of this residue and its equivalent in RAMP1 (Trp74) we substituted the native amino acids with several others. In RAMP3, these were Trp, Phe, Tyr, Ala, Ser, Thr, Arg and Asn; in RAMP1, Glu, Phe, Tyr, Ala and Asn substitutions were made. The mutant RAMPs were co-expressed with CLR in Cos7 cells; receptor function in response to AM, AM(2)/intermedin and CGRP was measured in a cAMP assay and cell surface expression was determined by ELISA. Phe reduced AM potency in RAMP3 but had no effect in RAMP1. In contrast, Tyr had no effect in RAMP3 but enhanced AM potency in RAMP1. Most other substitutions had a small effect on AM potency in both receptors whereas there was little impact on CGRP or AM(2) potency. Overall, these data suggest that the geometry and charge of the residue at position 74 contribute to how AM interacts with the AM(2) and CGRP receptors and confirms the role of this position in dictating differential AM pharmacology at the AM(2) and CGRP receptors.

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By conducting point-by-point inscription in a continuously moving slab of a pure fused silica at the optimal depth (170 μm depth below the surface), we have fabricated a 250-nm-period nanostructure with 30 nJ, 300 fs, 1 kHz pulses from frequency-tripled Ti:sapphire laser. This is the smallest value for the inscribed period yet reported, and has been achieved with radical improvement in the quality of the inscribed nanostructures in comparison with previous reports. The performed numerical modeling confirms the obtained experimental results.

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DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

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Population measures for genetic programs are defined and analysed in an attempt to better understand the behaviour of genetic programming. Some measures are simple, but do not provide sufficient insight. The more meaningful ones are complex and take extra computation time. Here we present a unified view on the computation of population measures through an information hypertree (iTree). The iTree allows for a unified and efficient calculation of population measures via a basic tree traversal. © Springer-Verlag 2004.

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Quantitative structure-activity relationship (QSAR) analysis is a cornerstone of modern informatics. Predictive computational models of peptide-major histocompatibility complex (MHC)-binding affinity based on QSAR technology have now become important components of modern computational immunovaccinology. Historically, such approaches have been built around semiqualitative, classification methods, but these are now giving way to quantitative regression methods. We review three methods--a 2D-QSAR additive-partial least squares (PLS) and a 3D-QSAR comparative molecular similarity index analysis (CoMSIA) method--which can identify the sequence dependence of peptide-binding specificity for various class I MHC alleles from the reported binding affinities (IC50) of peptide sets. The third method is an iterative self-consistent (ISC) PLS-based additive method, which is a recently developed extension to the additive method for the affinity prediction of class II peptides. The QSAR methods presented here have established themselves as immunoinformatic techniques complementary to existing methodology, useful in the quantitative prediction of binding affinity: current methods for the in silico identification of T-cell epitopes (which form the basis of many vaccines, diagnostics, and reagents) rely on the accurate computational prediction of peptide-MHC affinity. We have reviewed various human and mouse class I and class II allele models. Studied alleles comprise HLA-A*0101, HLA-A*0201, HLA-A*0202, HLA-A*0203, HLA-A*0206, HLA-A*0301, HLA-A*1101, HLA-A*3101, HLA-A*6801, HLA-A*6802, HLA-B*3501, H2-K(k), H2-K(b), H2-D(b) HLA-DRB1*0101, HLA-DRB1*0401, HLA-DRB1*0701, I-A(b), I-A(d), I-A(k), I-A(S), I-E(d), and I-E(k). In this chapter we show a step-by-step guide into predicting the reliability and the resulting models to represent an advance on existing methods. The peptides used in this study are available from the AntiJen database (http://www.jenner.ac.uk/AntiJen). The PLS method is available commercially in the SYBYL molecular modeling software package. The resulting models, which can be used for accurate T-cell epitope prediction, will be made are freely available online at the URL http://www.jenner.ac.uk/MHCPred.

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The performances of L-band EDFA are modeled and analyzed, based on C-band EDFA, through variation of pump power, ion concentration and fiber length. The fiber length promises higher performance than others. © 2005 Optical Society of America.