29 resultados para Protein Structure, Multifractal Analysis, 6 Letter Model

em Aston University Research Archive


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The role of receptor activity modifying protein 1 (RAMP1) in forming receptors with the calcitonin receptor-like receptor (CLR) and the calcitonin receptor (CTR) was examined by producing chimeras between RAMP1 and RAMP3. RAMPs have three extracellular helices. Exchange of helix 1 of the RAMPs or residues 62-69 in helix 2 greatly reduced CLR trafficking (a marker for CLR association). Modeling suggests that these exchanges alter the CLR recognition site on RAMP1, which is more exposed than on RAMP3. Exchange of residues 86-89 of RAMP1 had no effect on the trafficking of CLR but reduced the potency of human (h) alphaCGRP and adrenomedullin. However, these alterations to RAMP1 had no effect on the potency of hbetaCGRP. These residues of RAMP1 lie at the junction of helix 3 and its connecting loop with helix 2. Modeling suggests that the loop is more exposed in RAMP1 than RAMP3; it may play an important role in peptide binding, either directly or indirectly. Exchange of residues 90-94 of RAMP1 caused a modest reduction in CLR expression and a 15-fold decrease in CGRP potency. It is unlikely that the decrease in expression is enough to explain the reduction in potency, and so these may have dual roles in recognizing CLR and CGRP. For CTR, only 6 out of 26 chimeras covering the extracellular part of RAMP1 did not reduce agonist potency. Thus the association of CTR with RAMP1 seems more sensitive to changes in RAMP1 structure induced by the chimeras than is CLR.

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Objective In this study, we have used a chemometrics-based method to correlate key liposomal adjuvant attributes with in-vivo immune responses based on multivariate analysis. Methods The liposomal adjuvant composed of the cationic lipid dimethyldioctadecylammonium bromide (DDA) and trehalose 6,6-dibehenate (TDB) was modified with 1,2-distearoyl-sn-glycero-3-phosphocholine at a range of mol% ratios, and the main liposomal characteristics (liposome size and zeta potential) was measured along with their immunological performance as an adjuvant for the novel, postexposure fusion tuberculosis vaccine, Ag85B-ESAT-6-Rv2660c (H56 vaccine). Partial least square regression analysis was applied to correlate and cluster liposomal adjuvants particle characteristics with in-vivo derived immunological performances (IgG, IgG1, IgG2b, spleen proliferation, IL-2, IL-5, IL-6, IL-10, IFN-γ). Key findings While a range of factors varied in the formulations, decreasing the 1,2-distearoyl-sn-glycero-3-phosphocholine content (and subsequent zeta potential) together built the strongest variables in the model. Enhanced DDA and TDB content (and subsequent zeta potential) stimulated a response skewed towards a cell mediated immunity, with the model identifying correlations with IFN-γ, IL-2 and IL-6. Conclusion This study demonstrates the application of chemometrics-based correlations and clustering, which can inform liposomal adjuvant design.

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Receptor activity modifying protein 1 (RAMP1) is an integral component of several receptors including the calcitonin gene-related peptide (CGRP) receptor. It forms a complex with the calcitonin receptor-like receptor (CLR) and is required for receptor trafficking and ligand binding. The N-terminus of RAMP1 comprises three helices. The current study investigated regions of RAMP1 important for CGRP or CLR interactions by alanine mutagenesis. Modeling suggested the second and third helices were important in protein-protein interactions. Most of the conserved residues in the N-terminus (M48, W56, Y66, P85, N66, H97, F101, D113, P114, P115), together with a further 13 residues spread throughout three helices of RAMP1, were mutated to alanine and coexpressed with CLR in Cos 7 cells. None of the mutations significantly reduced RAMP expression. Of the nine mutants from helix 1, only M48A had any effect, producing a modest reduction in trafficking of CLR to the cell surface. In helix 2 Y66A almost completely abolished CLR trafficking; L69A and T73A reduced the potency of CGRP to produce cAMP. In helix 3, H97A abolished CLR trafficking; P85A, N86A, and F101A had caused modest reductions in CLR trafficking and also reduced the potency of CGRP on cAMP production. F93A caused a modest reduction in CLR trafficking alone and L94A increased cAMP production. The data are consistent with a CLR recognition site particularly involving Y66 and H97, with lesser roles for adjacent residues in helix 3. L69 and T73 may contribute to a CGRP recognition site in helix 2 also involving nearby residues.

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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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After decades of slow progress, the pace of research on membrane protein structures is beginning to quicken thanks to various improvements in technology, including protein engineering and microfocus X-ray diffraction. Here we review these developments and, where possible, highlight generic new approaches to solving membrane protein structures based on recent technological advances. Rational approaches to overcoming the bottlenecks in the field are urgently required as membrane proteins, which typically comprise ~30% of the proteomes of organisms, are dramatically under-represented in the structural database of the Protein Data Bank.

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This thesis provides a set of tools for managing uncertainty in Web-based models and workflows.To support the use of these tools, this thesis firstly provides a framework for exposing models through Web services. An introduction to uncertainty management, Web service interfaces,and workflow standards and technologies is given, with a particular focus on the geospatial domain.An existing specification for exposing geospatial models and processes, theWeb Processing Service (WPS), is critically reviewed. A processing service framework is presented as a solutionto usability issues with the WPS standard. The framework implements support for Simple ObjectAccess Protocol (SOAP), Web Service Description Language (WSDL) and JavaScript Object Notation (JSON), allowing models to be consumed by a variety of tools and software. Strategies for communicating with models from Web service interfaces are discussed, demonstrating the difficultly of exposing existing models on the Web. This thesis then reviews existing mechanisms for uncertainty management, with an emphasis on emulator methods for building efficient statistical surrogate models. A tool is developed to solve accessibility issues with such methods, by providing a Web-based user interface and backend to ease the process of building and integrating emulators. These tools, plus the processing service framework, are applied to a real case study as part of the UncertWeb project. The usability of the framework is proved with the implementation of aWeb-based workflow for predicting future crop yields in the UK, also demonstrating the abilities of the tools for emulator building and integration. Future directions for the development of the tools are discussed.

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Modelling class B G-protein-coupled receptors (GPCRs) using class A GPCR structural templates is difficult due to lack of homology. The plant GPCR, GCR1, has homology to both class A and class B GPCRs. We have used this to generate a class A-class B alignment, and by incorporating maximum lagged correlation of entropy and hydrophobicity into a consensus score, we have been able to align receptor transmembrane regions. We have applied this analysis to generate active and inactive homology models of the class B calcitonin gene-related peptide (CGRP) receptor, and have supported it with site-directed mutagenesis data using 122 CGRP receptor residues and 144 published mutagenesis results on other class B GPCRs. The variation of sequence variability with structure, the analysis of polarity violations, the alignment of group-conserved residues and the mutagenesis results at 27 key positions were particularly informative in distinguishing between the proposed and plausible alternative alignments. Furthermore, we have been able to associate the key molecular features of the class B GPCR signalling machinery with their class A counterparts for the first time. These include the [K/R]KLH motif in intracellular loop 1, [I/L]xxxL and KxxK at the intracellular end of TM5 and TM6, the NPXXY/VAVLY motif on TM7 and small group-conserved residues in TM1, TM2, TM3 and TM7. The equivalent of the class A DRY motif is proposed to involve Arg(2.39), His(2.43) and Glu(3.46), which makes a polar lock with T(6.37). These alignments and models provide useful tools for understanding class B GPCR function.

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A simple protein-DNA interaction analysis has been developed using a high-affinity/high-specificity zinc finger protein. In essence, purified protein samples are immobilized directly onto the surface of microplate wells, and fluorescently labeled DNA is added in solution. After incubation and washing, bound DNA is detected in a standard microplate reader. The minimum sensitivity of the assay is approximately 0.2 nM DNA. Since the detection of bound DNA is noninvasive and the protein-DNA interaction is not disrupted during detection, iterative readings may be taken from the same well, after successive alterations in interaction conditions, if required. In this respect, the assay may therefore be considered real time and permits appropriate interaction conditions to be determined quantitatively. The assay format is ideally suited to investigate the interactions of purified unlabeled DNA binding proteins in a high-throughput format.

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A simple protein-DNA interaction analysis has been developed using both a high-affinity/high-specificity zinc finger protein and a low-specificity zinc finger protein with nonspecific DNA binding capability. The latter protein is designed to mimic background binding by proteins generated in randomized or shuffled gene libraries. In essence, DNA is immobilized onto the surface of microplate wells via streptavidin capture, and green fluorescent protein (GFP)-labeled protein is added in solution as part of a crude cell lysate or protein mixture. After incubation and washing, bound protein is detected in a standard microplate reader. The minimum sensitivity of the assay is approximately 0.4 nM protein. The assay format is ideally suited to investigate the interactions of DNA binding proteins from within crude cell extracts and/or mixtures of proteins that may be encountered in protein libraries generated by codon randomization or gene shuffling.

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Accurate protein structure prediction remains an active objective of research in bioinformatics. Membrane proteins comprise approximately 20% of most genomes. They are, however, poorly tractable targets of experimental structure determination. Their analysis using bioinformatics thus makes an important contribution to their on-going study. Using a method based on Bayesian Networks, which provides a flexible and powerful framework for statistical inference, we have addressed the alignment-free discrimination of membrane from non-membrane proteins. The method successfully identifies prokaryotic and eukaryotic α-helical membrane proteins at 94.4% accuracy, β-barrel proteins at 72.4% accuracy, and distinguishes assorted non-membranous proteins with 85.9% accuracy. The method here is an important potential advance in the computational analysis of membrane protein structure. It represents a useful tool for the characterisation of membrane proteins with a wide variety of potential applications.

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Motivation: Within bioinformatics, the textual alignment of amino acid sequences has long dominated the determination of similarity between proteins, with all that implies for shared structure, function, and evolutionary descent. Despite the relative success of modern-day sequence alignment algorithms, so-called alignment-free approaches offer a complementary means of determining and expressing similarity, with potential benefits in certain key applications, such as regression analysis of protein structure-function studies, where alignment-base similarity has performed poorly. Results: Here, we offer a fresh, statistical physics-based perspective focusing on the question of alignment-free comparison, in the process adapting results from “first passage probability distribution” to summarize statistics of ensemble averaged amino acid propensity values. In this paper, we introduce and elaborate this approach.

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Full text: The idea of producing proteins from recombinant DNA hatched almost half a century ago. In his PhD thesis, Peter Lobban foresaw the prospect of inserting foreign DNA (from any source, including mammalian cells) into the genome of a λ phage in order to detect and recover protein products from Escherichia coli [ 1 and 2]. Only a few years later, in 1977, Herbert Boyer and his colleagues succeeded in the first ever expression of a peptide-coding gene in E. coli — they produced recombinant somatostatin [ 3] followed shortly after by human insulin. The field has advanced enormously since those early days and today recombinant proteins have become indispensable in advancing research and development in all fields of the life sciences. Structural biology, in particular, has benefitted tremendously from recombinant protein biotechnology, and an overwhelming proportion of the entries in the Protein Data Bank (PDB) are based on heterologously expressed proteins. Nonetheless, synthesizing, purifying and stabilizing recombinant proteins can still be thoroughly challenging. For example, the soluble proteome is organized to a large part into multicomponent complexes (in humans often comprising ten or more subunits), posing critical challenges for recombinant production. A third of all proteins in cells are located in the membrane, and pose special challenges that require a more bespoke approach. Recent advances may now mean that even these most recalcitrant of proteins could become tenable structural biology targets on a more routine basis. In this special issue, we examine progress in key areas that suggests this is indeed the case. Our first contribution examines the importance of understanding quality control in the host cell during recombinant protein production, and pays particular attention to the synthesis of recombinant membrane proteins. A major challenge faced by any host cell factory is the balance it must strike between its own requirements for growth and the fact that its cellular machinery has essentially been hijacked by an expression construct. In this context, Bill and von der Haar examine emerging insights into the role of the dependent pathways of translation and protein folding in defining high-yielding recombinant membrane protein production experiments for the common prokaryotic and eukaryotic expression hosts. Rather than acting as isolated entities, many membrane proteins form complexes to carry out their functions. To understand their biological mechanisms, it is essential to study the molecular structure of the intact membrane protein assemblies. Recombinant production of membrane protein complexes is still a formidable, at times insurmountable, challenge. In these cases, extraction from natural sources is the only option to prepare samples for structural and functional studies. Zorman and co-workers, in our second contribution, provide an overview of recent advances in the production of multi-subunit membrane protein complexes and highlight recent achievements in membrane protein structural research brought about by state-of-the-art near-atomic resolution cryo-electron microscopy techniques. E. coli has been the dominant host cell for recombinant protein production. Nonetheless, eukaryotic expression systems, including yeasts, insect cells and mammalian cells, are increasingly gaining prominence in the field. The yeast species Pichia pastoris, is a well-established recombinant expression system for a number of applications, including the production of a range of different membrane proteins. Byrne reviews high-resolution structures that have been determined using this methylotroph as an expression host. Although it is not yet clear why P. pastoris is suited to producing such a wide range of membrane proteins, its ease of use and the availability of diverse tools that can be readily implemented in standard bioscience laboratories mean that it is likely to become an increasingly popular option in structural biology pipelines. The contribution by Columbus concludes the membrane protein section of this volume. In her overview of post-expression strategies, Columbus surveys the four most common biochemical approaches for the structural investigation of membrane proteins. Limited proteolysis has successfully aided structure determination of membrane proteins in many cases. Deglycosylation of membrane proteins following production and purification analysis has also facilitated membrane protein structure analysis. Moreover, chemical modifications, such as lysine methylation and cysteine alkylation, have proven their worth to facilitate crystallization of membrane proteins, as well as NMR investigations of membrane protein conformational sampling. Together these approaches have greatly facilitated the structure determination of more than 40 membrane proteins to date. It may be an advantage to produce a target protein in mammalian cells, especially if authentic post-translational modifications such as glycosylation are required for proper activity. Chinese Hamster Ovary (CHO) cells and Human Embryonic Kidney (HEK) 293 cell lines have emerged as excellent hosts for heterologous production. The generation of stable cell-lines is often an aspiration for synthesizing proteins expressed in mammalian cells, in particular if high volumetric yields are to be achieved. In his report, Buessow surveys recent structures of proteins produced using stable mammalian cells and summarizes both well-established and novel approaches to facilitate stable cell-line generation for structural biology applications. The ambition of many biologists is to observe a protein's structure in the native environment of the cell itself. Until recently, this seemed to be more of a dream than a reality. Advances in nuclear magnetic resonance (NMR) spectroscopy techniques, however, have now made possible the observation of mechanistic events at the molecular level of protein structure. Smith and colleagues, in an exciting contribution, review emerging ‘in-cell NMR’ techniques that demonstrate the potential to monitor biological activities by NMR in real time in native physiological environments. A current drawback of NMR as a structure determination tool derives from size limitations of the molecule under investigation and the structures of large proteins and their complexes are therefore typically intractable by NMR. A solution to this challenge is the use of selective isotope labeling of the target protein, which results in a marked reduction of the complexity of NMR spectra and allows dynamic processes even in very large proteins and even ribosomes to be investigated. Kerfah and co-workers introduce methyl-specific isotopic labeling as a molecular tool-box, and review its applications to the solution NMR analysis of large proteins. Tyagi and Lemke next examine single-molecule FRET and crosslinking following the co-translational incorporation of non-canonical amino acids (ncAAs); the goal here is to move beyond static snap-shots of proteins and their complexes and to observe them as dynamic entities. The encoding of ncAAs through codon-suppression technology allows biomolecules to be investigated with diverse structural biology methods. In their article, Tyagi and Lemke discuss these approaches and speculate on the design of improved host organisms for ‘integrative structural biology research’. Our volume concludes with two contributions that resolve particular bottlenecks in the protein structure determination pipeline. The contribution by Crepin and co-workers introduces the concept of polyproteins in contemporary structural biology. Polyproteins are widespread in nature. They represent long polypeptide chains in which individual smaller proteins with different biological function are covalently linked together. Highly specific proteases then tailor the polyprotein into its constituent proteins. Many viruses use polyproteins as a means of organizing their proteome. The concept of polyproteins has now been exploited successfully to produce hitherto inaccessible recombinant protein complexes. For instance, by means of a self-processing synthetic polyprotein, the influenza polymerase, a high-value drug target that had remained elusive for decades, has been produced, and its high-resolution structure determined. In the contribution by Desmyter and co-workers, a further, often imposing, bottleneck in high-resolution protein structure determination is addressed: The requirement to form stable three-dimensional crystal lattices that diffract incident X-ray radiation to high resolution. Nanobodies have proven to be uniquely useful as crystallization chaperones, to coax challenging targets into suitable crystal lattices. Desmyter and co-workers review the generation of nanobodies by immunization, and highlight the application of this powerful technology to the crystallography of important protein specimens including G protein-coupled receptors (GPCRs). Recombinant protein production has come a long way since Peter Lobban's hypothesis in the late 1960s, with recombinant proteins now a dominant force in structural biology. The contributions in this volume showcase an impressive array of inventive approaches that are being developed and implemented, ever increasing the scope of recombinant technology to facilitate the determination of elusive protein structures. Powerful new methods from synthetic biology are further accelerating progress. Structure determination is now reaching into the living cell with the ultimate goal of observing functional molecular architectures in action in their native physiological environment. We anticipate that even the most challenging protein assemblies will be tackled by recombinant technology in the near future.

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Human CD81 (hCD81) protein has been recombinantly produced in the methylotrophic yeast Pichia pastoris. The purified protein, produced at a yield of 1.75 mg/L of culture, was shown to interact with Hepatitis C virus E2 glycoprotein. Immunofluorescent and flow cytometric staining of P. pastoris protoplasts with monoclonal antibodies specific for the second extracellular loop (EC2) of hCD81 confirmed the antigenicity of the recombinant molecule. Full-length hCD81 was solubilized with an array of detergents and subsequently characterized using circular dichroism (CD) and analytical ultracentrifugation. These biophysical techniques confirmed that the protein solution comprises a homogenous species possessing a highly-defined alpha-helical secondary structure. The predicted alpha-helical content of the protein from CD analysis (77.1%) fits remarkably well with what would be expected (75.2%) from knowledge of the protein sequence together with the data from the crystal structure of the second extracellular loop. This study represents the first biophysical characterization of a full-length recombinant tetraspanin, and opens the way for structure-activity analyses of this ubiquitous family of transmembrane proteins.

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This work introduces a new variational Bayes data assimilation method for the stochastic estimation of precipitation dynamics using radar observations for short term probabilistic forecasting (nowcasting). A previously developed spatial rainfall model based on the decomposition of the observed precipitation field using a basis function expansion captures the precipitation intensity from radar images as a set of ‘rain cells’. The prior distributions for the basis function parameters are carefully chosen to have a conjugate structure for the precipitation field model to allow a novel variational Bayes method to be applied to estimate the posterior distributions in closed form, based on solving an optimisation problem, in a spirit similar to 3D VAR analysis, but seeking approximations to the posterior distribution rather than simply the most probable state. A hierarchical Kalman filter is used to estimate the advection field based on the assimilated precipitation fields at two times. The model is applied to tracking precipitation dynamics in a realistic setting, using UK Met Office radar data from both a summer convective event and a winter frontal event. The performance of the model is assessed both traditionally and using probabilistic measures of fit based on ROC curves. The model is shown to provide very good assimilation characteristics, and promising forecast skill. Improvements to the forecasting scheme are discussed