42 resultados para Lipid-protein interactions

em Aston University Research Archive


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Using microarrays to probe protein-protein interactions is becoming increasingly attractive due to their compatibility with highly sensitive detection techniques, selectivity of interaction, robustness and capacity for examining multiple proteins simultaneously. The major drawback to using this approach is the relatively large volumes and high concentrations necessary. Reducing the protein array spot size should allow for smaller volumes and lower concentrations to be used as well as opening the way for combination with more sensitive detection technologies. Dip-Pen Nanolithography (DPN) is a recently developed technique for structure creation on the nano to microscale with the capacity to create biological architectures. Here we describe the creation of miniaturised microarrays, 'mesoarrays', using DPN with protein spots 400× smaller by area compared to conventional microarrays. The mesoarrays were then used to probe the ERK2-KSR binding event of the Ras/Raf/MEK/ERK signalling pathway at a physical scale below that previously reported. Whilst the overall assay efficiency was determined to be low, the mesoarrays could detect KSR binding to ERK2 repeatedly and with low non-specific binding. This study serves as a first step towards an approach that can be used for analysis of proteins at a concentration level comparable to that found in the cellular environment.

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The influence of ionic strength and of the chemical nature of cations on the protein-protein interactions in ovalbumin solution was studied using small-angle X-ray and neutron scattering (SAXS/SANS). The globular protein ovalbumin is found in dimeric form in solutions as suggested by SANS/SAXS experiments. Due to the negative charge of the proteins at neutral pH, the protein-protein interactions without any salt addition are dominated by electrostatic repulsion. A structure factor related to screened Coulombic interactions together with an ellipsoid form factor was used to fit the scattering intensity. A monovalent salt (NaCl) and a trivalent salt (YCl3) were used to study the effect of the chemical nature of cations on the interaction in protein solutions. Upon addition of NaCl, with ionic strength below that of physiological conditions (150 mM), the effective interactions are still dominated by the surface charge of the proteins and the scattering data can be understood using the same model. When yttrium chloride was used, a reentrant condensation behavior, i.e., aggregation and subsequent redissolution of proteins with increasing salt concentration, was observed. SAXS measurements reveal a transition from effective repulsion to attraction with increasing salt concentration. The solutions in the reentrant regime become unstable after long times (several days). The results are discussed and compared with those from bovine serum albumin (BSA) in solutions.

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A major challenge in text mining for biomedicine is automatically extracting protein-protein interactions from the vast amount of biomedical literature. We have constructed an information extraction system based on the Hidden Vector State (HVS) model for protein-protein interactions. The HVS model can be trained using only lightly annotated data whilst simultaneously retaining sufficient ability to capture the hierarchical structure. When applied in extracting protein-protein interactions, we found that it performed better than other established statistical methods and achieved 61.5% in F-score with balanced recall and precision values. Moreover, the statistical nature of the pure data-driven HVS model makes it intrinsically robust and it can be easily adapted to other domains.

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This paper proposes a novel framework of incorporating protein-protein interactions (PPI) ontology knowledge into PPI extraction from biomedical literature in order to address the emerging challenges of deep natural language understanding. It is built upon the existing work on relation extraction using the Hidden Vector State (HVS) model. The HVS model belongs to the category of statistical learning methods. It can be trained directly from un-annotated data in a constrained way whilst at the same time being able to capture the underlying named entity relationships. However, it is difficult to incorporate background knowledge or non-local information into the HVS model. This paper proposes to represent the HVS model as a conditionally trained undirected graphical model in which non-local features derived from PPI ontology through inference would be easily incorporated. The seamless fusion of ontology inference with statistical learning produces a new paradigm to information extraction.

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To date, more than 16 million citations of published articles in biomedical domain are available in the MEDLINE database. These articles describe the new discoveries which accompany a tremendous development in biomedicine during the last decade. It is crucial for biomedical researchers to retrieve and mine some specific knowledge from the huge quantity of published articles with high efficiency. Researchers have been engaged in the development of text mining tools to find knowledge such as protein-protein interactions, which are most relevant and useful for specific analysis tasks. This chapter provides a road map to the various information extraction methods in biomedical domain, such as protein name recognition and discovery of protein-protein interactions. Disciplines involved in analyzing and processing unstructured-text are summarized. Current work in biomedical information extracting is categorized. Challenges in the field are also presented and possible solutions are discussed.

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Text classification is essential for narrowing down the number of documents relevant to a particular topic for further pursual, especially when searching through large biomedical databases. Protein-protein interactions are an example of such a topic with databases being devoted specifically to them. This paper proposed a semi-supervised learning algorithm via local learning with class priors (LL-CP) for biomedical text classification where unlabeled data points are classified in a vector space based on their proximity to labeled nodes. The algorithm has been evaluated on a corpus of biomedical documents to identify abstracts containing information about protein-protein interactions with promising results. Experimental results show that LL-CP outperforms the traditional semisupervised learning algorithms such as SVMand it also performs better than local learning without incorporating class priors.

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We have studied a series of samples of bovine serum albumin (BSA) solutions with protein concentration, c, ranging from 2 to 500 mg/mL and ionic strength, I, from 0 to 2 M by small-angle X-ray scattering (SAXS). The scattering intensity distribution was compared to simulations using an oblate ellipsoid form factor with radii of 17 x 42 x 42 A, combined with either a screened Coulomb, repulsive structure factor, S-SC(q), or an attractive square-well structure factor, S-SW(q). At pH = 7, BSA is negatively charged. At low ionic strength, I <0.3 M, the total interaction exhibits a decrease of the repulsive interaction when compared to the salt-free solution, as the net surface charge is screened, and the data can be fitted by assuming an ellipsoid form factor and screened Coulomb interaction. At moderate ionic strength (0.3-0.5 M), the interaction is rather weak, and a hard-sphere structure factor has been used to simulate the data with a higher volume fraction. Upon further increase of the ionic strength (I >= 1.0 M), the overall interaction potential was dominated by an additional attractive potential, and the data could be successfully fitted by an ellipsoid form factor and a square-well potential model. The fit parameters, well depth and well width, indicate that the attractive potential caused by a high salt concentration is weak and long-ranged. Although the long-range, attractive potential dominated the protein interaction, no gelation or precipitation was observed in any of the samples. This is explained by the increase of a short-range, repulsive interaction between protein molecules by forming a hydration layer with increasing salt concentration. The competition between long-range, attractive and short-range, repulsive interactions accounted for the stability of concentrated BSA solution at high ionic strength.

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The present study focuses on the synthesis of amphiphilic block copolymers containing poly(glycerol monomethacrylate) (PGMMA), showing the advantages of a protection/deprotection strategy based on silyl groups. PGMMA blocks were synthesized via ATRP started by a double functional poly(dimethyl siloxane) (PDMS) macroinitiator of molecular weight ≈7000 g mol-1. The resulting triblock copolymers were characterized by low polydispersity (generally ≤1.1) and their aggregation concentration in water was essentially dominated by the PDMS block length (critical aggregation concentration substantially invariant for GMMA degree of polymerization ≥30). For GMMA blocks with DP > 50, the self-assembly in water produced 35-50 nm spherical micelles, while shorter hydrophilic chains produced larger aggregates apparently displaying worm-like morphologies. Block copolymers with long GMMA chains (DP ≈ 200) produced particularly stable micellar aggregates, which were then selected for a preliminary assessment of the possibility of adsorption of plasma proteins (albumin and fibrinogen); using diffusion NMR as an analytical technique, no significant adsorption was recorded both on micelles and on soluble PGMMA employed as a control, indicating the possibility of a "stealth" behaviour. This journal is © 2013 The Royal Society of Chemistry.

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Life, and the biochemistry of which it is ultimately comprised, is built from the interactions of proteins, and the study of protein-protein interactions is fast becoming a central feature of molecular bioscience. This is as true of immunobiology as it is of other areas of the wider biological milieu. Protein-protein interactions within an immunological setting comprise both the kind familiar from other areas of biology and instantiations of protein-protein interactions special to the immune arena. Of the generic kind of protein-protein interaction, co-stimulatory receptors, such as CD28, and the interaction of accessory proteins, such as CD4 or CD8, are amongst the most prevalent and apposite of examples. The key examples of special immunological instantiations of protein-protein interactions are the binding of antigens by antibodies and the formation of peptide-MHC-TCR complexes; both prime examples of vital molecular recognition events mediated by protein-protein interactions. In this brief review, and within the context of this burgeoning field, we examine immunological protein-protein interactions, focussing on the problematic nature of defining such interactions. © 2011 by Nova Science Publishers, Inc. All rights reserved.

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The research described in this PhD thesis focuses on proteomics approaches to study the effect of oxidation on the modification status and protein-protein interactions of PTEN, a redox-sensitive phosphatase involved in a number of cellular processes including metabolism, apoptosis, cell proliferation, and survival. While direct evidence of a redox regulation of PTEN and its downstream signaling has been reported, the effect of cellular oxidative stress or direct PTEN oxidation on PTEN structure and interactome is still poorly defined. In a first study, GST-tagged PTEN was directly oxidized over a range of hypochlorous acid (HOCl) concentration, assayed for phosphatase activity, and oxidative post-translational modifications (oxPTMs) were quantified using LC-MS/MS-based label-free methods. In a second study, GSTtagged PTEN was prepared in a reduced and reversibly H2O2-oxidized form, immobilized on a resin support and incubated with HCT116 cell lysate to capture PTEN interacting proteins, which were analyzed by LC-MS/MS and comparatively quantified using label-free methods. In parallel experiments, HCT116 cells transfected with a GFP-tagged PTEN were treated with H2O2 and PTENinteracting proteins immunoprecipitated using standard methods. Several high abundance HOCl-induced oxPTMs were mapped, including those taking place at amino acids known to be important for PTEN phosphatase activity and protein-protein interactions, such as Met35, Tyr155, Tyr240 and Tyr315. A PTEN redox interactome was also characterized, which identified a number of PTEN-interacting proteins that vary with the reversible inactivation of PTEN caused by H2O2 oxidation. These included new PTEN interactors as well as the redox proteins peroxiredoxin-1 (Prdx1) and thioredoxin (Trx), which are known to be involved in the recycling of PTEN active site following H2O2-induced reversible inactivation. The results suggest that the oxidative modification of PTEN causes functional alterations in PTEN structure and interactome, with fundamental implications for the PTEN signaling role in many cellular processes, such as those involved in the pathophysiology of disease and ageing.

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The design and synthesis of biomaterials covers a growing number of biomedical applications. The use of biomaterials in biological environment is associated with a number of problems, the most important of which is biocompatabUity. If the implanted biomaterial is not compatible with the environment, it will be rejected by the biological site. This may be manifested in many ways depending on the environment in which it is used. Adsorption of proteins takes place almost instantaneously when a biomaterial comes into contact with most biological fluids. The eye is a unique body site for the study of protein interactions with biomaterials, because of its ease of access and deceptive complexity of the tears. The use of contact lenses for either vision correction and cosmetic reasons or as a route for the controlled drug delivery, has significantly increased in recent years. It is relatively easy to introduce a contact lens Into the tear fluid and remove after a few minutes without surgery or trauma to the patient. A range of analytical techniques were used and developed to measure the proteins absorbed to some existing commercial contact lens materials and also to novel hydrogels synthesised within the research group. Analysis of the identity and quantity of proteins absorbed to biomaterials revealed the importance of many factors on the absorption process. The effect of biomaterial structure, protein nature in terms of size. shape and charge and pH of the environment on the absorption process were examined in order to determine the relative up-take of tear proteins. This study showed that both lysozyme and lactoferrin penetrate the lens matrix of ionic materials. Measurement of the mobility and activity of the protein deposited into the surface and within the matrix of ionic lens materials demonstrated that the mobility is pH dependent and, within the experimental errors, the biological activity of lysozyme remained unchanged after adsorption and desorption. The study on the effect of different monomers copolymerised with hydroxyethyl methacrylate (HEMA) on the protein up-take showed that monomers producing a positive charge on the copolymer can reduce the spoilation with lysozyme. The studies were extended to real cases in order to compare the patient dependent factors. The in-vivo studies showed that the spoilation is patient dependent as well as other factors. Studies on the extrinsic factors such as dye used in colour lenses showed that the addition of colourant affects protein absorption and, in one case, its effect is beneficial to the wearer as it reduces the quantity of the protein absorbed.

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It has been recognised for some time that a full code of amino acid-based recognition of DNA sequences would be useful. Several approaches, which utilise small DNA binding motifs called zinc fingers, are presently employed. None of the current approaches successfully combine a combinatorial approach to the elucidation of a code with a single stage high throughput screening assay. The work outlined here describes the development of a model system for the study of DNA protein interactions and the development of a high throughput assay for detection of such interactions. A zinc finger protein was designed which will bind with high affinity and specificity to a known DNA sequence. For future work it is possible to mutate the region of the zinc finger responsible for the specificity of binding, in order to observe the effect on the DNA / protein interactions. The zinc finger protein was initially synthesised as a His tagged product. It was not possible however to develop a high throughput assay using the His tagged zinc finger protein. The gene encoding the zinc finger protein was altered and the protein synthesised as a Glutathione S-Transferase (GST) fusion product. A successful assay was developed using the GST protein and Scintillation Proximity Assay technology (Amersham Pharmacia Biotech). The scintillation proximity assay is a dynamic assay that allows the DNA protein interactions to be studied in "real time". This assay not only provides a high throughput method of screening zinc finger proteins for potential ligands but also allows the effect of addition of reagents or competitor ligands to be monitored.

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During the last decade, biomedicine has witnessed a tremendous development. Large amounts of experimental and computational biomedical data have been generated along with new discoveries, which are accompanied by an exponential increase in the number of biomedical publications describing these discoveries. In the meantime, there has been a great interest with scientific communities in text mining tools to find knowledge such as protein-protein interactions, which is most relevant and useful for specific analysis tasks. This paper provides a outline of the various information extraction methods in biomedical domain, especially for discovery of protein-protein interactions. It surveys methodologies involved in plain texts analyzing and processing, categorizes current work in biomedical information extraction, and provides examples of these methods. Challenges in the field are also presented and possible solutions are discussed.

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Protein modifications, including oxidative modifications, glycosylations, and oxidized lipid-protein adducts, are becoming increasingly important as biomarkers and in understanding disease etiology. There has been a great deal of interest in mapping these on Apo B100 from low density lipoprotein (LDL). We have used extracted ion chromatograms of product ions generated using a very narrow mass window from high-resolution tandem mass spectrometric data collected on a rapid scanning quadrupole time-of-flight (QTOF) instrument, to selectively and sensitively detect modified peptides and identify the site and nature of a number of protein modifications in parallel. We have demonstrated the utility of this method by characterizing for the first time oxidized phospholipid adducts to LDL and human serum albumin and for the detection of glycosylation and kynurenin formation from the oxidation of tryptophan residues in LDL. © 2013 American Chemical Society.

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The interactions between proteins and gold colloids functionalized with protein-resistant oligo(ethylene glycol) (OEG) thiol, HS(CH(2))(11) (OCH(2)CH(2))(6)OMe (EG(6)OMe), in aqueous solution have been studied by small-angle X-ray scattering (SAXS) and UV-vis spectroscopy. The mean size, 2R, and the size distribution of the decorated gold colloids have been characterized by SAXS. The monolayer-protected gold colloids have no correlations due to the low volume fraction in solution and are stable in a wide range of temperatures (5-70 degrees C, pH (1.3-12.4), and ionic strength (0-1.0 M). In contrast, protein (bovine serum albumin) solutions with concentrations in the range of 60-200 mg/mL (4.6-14.5 vol show a pronounced correlation peak in SAXS, which results from the repulsive electrostatic interaction between charged proteins. These protein interactions show significant dependence on ionic strength, as would be expected for an electrostatic interaction (Zhang et al. J. Phys. Chem. B 2007, 111, 251). For a mixture of proteins and gold colloids, the protein-protein interaction changes little upon mixing with OEG-decorated gold colloids. In contrast, the colloid-colloid interaction is found to be strongly dependent on the protein concentration and the size of the colloid itself. Adding protein to a colloidal solution results in an attractive depletion interaction between functionalized gold colloids, and above a critical protein concentration, c*, the colloids form aggregates and flocculate. Adding salt to such mixtures enhances the depletion effect and decreases the critical protein concentration. The aggregation is a reversible process (i.e., diluting the solution leads to dissolution of aggregates). The results also indicate that the charge of the OEG self-assembled monolayer at a curved interface has a rather limited effect on the colloidal stabilization and the repulsive interaction with proteins.