930 resultados para Protein Array Analysis -- methods


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Background: Protein tertiary structure can be partly characterized via each amino acid's contact number measuring how residues are spatially arranged. The contact number of a residue in a folded protein is a measure of its exposure to the local environment, and is defined as the number of C-beta atoms in other residues within a sphere around the C-beta atom of the residue of interest. Contact number is partly conserved between protein folds and thus is useful for protein fold and structure prediction. In turn, each residue's contact number can be partially predicted from primary amino acid sequence, assisting tertiary fold analysis from sequence data. In this study, we provide a more accurate contact number prediction method from protein primary sequence. Results: We predict contact number from protein sequence using a novel support vector regression algorithm. Using protein local sequences with multiple sequence alignments (PSI-BLAST profiles), we demonstrate a correlation coefficient between predicted and observed contact numbers of 0.70, which outperforms previously achieved accuracies. Including additional information about sequence weight and amino acid composition further improves prediction accuracies significantly with the correlation coefficient reaching 0.73. If residues are classified as being either contacted or non-contacted, the prediction accuracies are all greater than 77%, regardless of the choice of classification thresholds. Conclusion: The successful application of support vector regression to the prediction of protein contact number reported here, together with previous applications of this approach to the prediction of protein accessible surface area and B-factor profile, suggests that a support vector regression approach may be very useful for determining the structure-function relation between primary sequence and higher order consecutive protein structural and functional properties.

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Folates and its derivatives occur as polyglutamates in nature. The multiplicity of forms and the generally low levels in foods makes quantitative analysis of folate a difficult task. The assay of folates from foods generally involves three steps: liberation of folates from the cellular matrix; deconjugation from the polyglutamate to the mono and di-glutamate forms; and the detection of the biological activity or chemical concentration of the resulting folates. The detection methods used are the microbiological assay relying on the turbidimetric bacterial growth of Lactobacillus rhamnosus which is by far the most commonly used method; the HPLC and LC/MS techniques and bio-specific procedures. This review attempts to describe the methods along with the merits and demerits of using each of these methods.

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During the analytical method development for BAY 11-7082 ((E)-3-[4-methylphenylsulfonyl]-2-propenenitrile), using HPLC-MS-MS and HPLC-UV, we observed that the protein removal process (both ultrafiltration and precipitation method using organic solvents) prior to HPLC brought about a significant reduction in the concentration of this compound. The use of a structurally similar internal standard, BAY 11-7085 ((E)-3-[4-t-butylphenylsulfonyl]-2-propenenitrile), was not effective in compensating for the loss of analyte as the extent of reduction was different to that of the analyte. We present here a systematic investigation of this problem and a new validated method for the determination of BAY 11-7082. (c) 2006 Elsevier B.V. All rights reserved.

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We have developed a sensitive, non-radioactive method to assess the interaction of transcription factors/DNA-binding proteins with DNA. We have modified the traditional radiolabeled DNA gel mobility shift assay to incorporate a DNA probe end-labeled with a Texas-red fluorophore and a DNA-binding protein tagged with the green fluorescent protein to monitor precisely DNA-protein complexation by native gel electrophoresis. We have applied this method to the DNA-binding proteins telomere release factor-1 and the sex-determining region-Y, demonstrating that the method is sensitive (able to detect 100 fmol of fluorescently labeled DNA), permits direct visualization of both the DNA probe and the DNA-binding protein, and enables quantitative analysis of DNA and protein complexation, and thereby an estimation of the stoichiometry of protein-DNA binding.

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Background: Changes in brain gene expression are thought to be responsible for the tolerance, dependence, and neurotoxicity produced by chronic alcohol abuse, but there has been no large scale study of gene expression in human alcoholism. Methods: RNA was extracted from postmortem samples of superior frontal cortex of alcoholics and nonalcoholics. Relative levels of RNA were determined by array techniques. We used both cDNA and oligonucleotide microarrays to provide coverage of a large number of genes and to allow cross-validation for those genes represented on both types of arrays. Results: Expression levels were determined for over 4000 genes and 163 of these were found to differ by 40% or more between alcoholics and nonalcoholics. Analysis of these changes revealed a selective reprogramming of gene expression in this brain region, particularly for myelin-related genes which were downregulated in the alcoholic samples. In addition, cell cycle genes and several neuronal genes were changed in expression. Conclusions: These gene expression changes suggest a mechanism for the loss of cerebral white matter in alcoholics as well as alterations that may lead to the neurotoxic actions of ethanol.

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Visualization of high-dimensional data has always been a challenging task. Here we discuss and propose variants of non-linear data projection methods (Generative Topographic Mapping (GTM) and GTM with simultaneous feature saliency (GTM-FS)) that are adapted to be effective on very high-dimensional data. The adaptations use log space values at certain steps of the Expectation Maximization (EM) algorithm and during the visualization process. We have tested the proposed algorithms by visualizing electrostatic potential data for Major Histocompatibility Complex (MHC) class-I proteins. The experiments show that the variation in the original version of GTM and GTM-FS worked successfully with data of more than 2000 dimensions and we compare the results with other linear/nonlinear projection methods: Principal Component Analysis (PCA), Neuroscale (NSC) and Gaussian Process Latent Variable Model (GPLVM).

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The slow down in the drug discovery pipeline is, in part, owing to a lack of structural and functional information available for new drug targets. Membrane proteins, the targets of well over 50% of marketed pharmaceuticals, present a particular challenge. As they are not naturally abundant, they must be produced recombinantly for the structural biology that is a prerequisite to structure-based drug design. Unfortunately, however, obtaining high yields of functional, recombinant membrane proteins remains a major bottleneck in contemporary bioscience. While repeated rounds of trial-and-error optimization have not (and cannot) reveal mechanistic details of the biology of recombinant protein production, examination of the host response has provided new insights. To this end, we published an early transcriptome analysis that identified genes implicated in high-yielding yeast cell factories, which has enabled the engineering of improved production strains. These advances offer hope that the bottleneck of membrane protein production can be relieved rationally.

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Transmembrane proteins play crucial roles in many important physiological processes. The intracellular domain of membrane proteins is key for their function by interacting with a wide variety of cytosolic proteins. It is therefore important to examine this interaction. A recently developed method to study these interactions, based on the use of liposomes as a model membrane, involves the covalent coupling of the cytoplasmic domains of membrane proteins to the liposome membrane. This allows for the analysis of interaction partners requiring both protein and membrane lipid binding. This thesis further establishes the liposome recruitment system and utilises it to examine the intracellular interactome of the amyloid precursor protein (APP), most well-known for its proteolytic cleavage that results in the production and accumulation of amyloid beta fragments, the main constituent of amyloid plaques in Alzheimer’s disease pathology. Despite this, the physiological function of APP remains largely unclear. Through the use of the proteo-liposome recruitment system two novel interactions of APP’s intracellular domain (AICD) are examined with a view to gaining a greater insight into APP’s physiological function. One of these novel interactions is between AICD and the mTOR complex, a serine/threonine protein kinase that integrates signals from nutrients and growth factors. The kinase domain of mTOR directly binds to AICD and the N-terminal amino acids of AICD are crucial for this interaction. The second novel interaction is between AICD and the endosomal PIKfyve complex, a lipid kinase involved in the production of phosphatidylinositol-3,5-bisphosphate (PI(3,5)P2) from phosphatidylinositol-3-phosphate, which has a role in controlling ensdosome dynamics. The scaffold protein Vac14 of the PIKfyve complex binds directly to AICD and the C-terminus of AICD is important for its interaction with the PIKfyve complex. Using a recently developed intracellular PI(3,5)P2 probe it is shown that APP controls the formation of PI(3,5)P2 positive vesicular structures and that the PIKfyve complex is involved in the trafficking and degradation of APP. Both of these novel APP interactors have important implications of both APP function and Alzheimer’s disease. The proteo-liposome recruitment method is further validated through its use to examine the recruitment and assembly of the AP-2/clathrin coat from purified components to two membrane proteins containing different sorting motifs. Taken together this thesis highlights the proteo-liposome recruitment system as a valuable tool for the study of membrane proteins intracellular interactome. It allows for the mimicking of the protein in its native configuration therefore identifying weaker interactions that are not detected by more conventional methods and also detecting interactions that are mediated by membrane phospholipids.

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BACKGROUND: Enterotoxigenic Escherichia coli (ETEC) is a globally prevalent cause of diarrhea. Though usually self-limited, it can be severe and debilitating. Little is known about the host transcriptional response to infection. We report the first gene expression analysis of the human host response to experimental challenge with ETEC. METHODS: We challenged 30 healthy adults with an unattenuated ETEC strain, and collected serial blood samples shortly after inoculation and daily for 8 days. We performed gene expression analysis on whole peripheral blood RNA samples from subjects in whom severe symptoms developed (n = 6) and a subset of those who remained asymptomatic (n = 6) despite shedding. RESULTS: Compared with baseline, symptomatic subjects demonstrated significantly different expression of 406 genes highlighting increased immune response and decreased protein synthesis. Compared with asymptomatic subjects, symptomatic subjects differentially expressed 254 genes primarily associated with immune response. This comparison also revealed 29 genes differentially expressed between groups at baseline, suggesting innate resilience to infection. Drug repositioning analysis identified several drug classes with potential utility in augmenting immune response or mitigating symptoms. CONCLUSIONS: There are statistically significant and biologically plausible differences in host gene expression induced by ETEC infection. Differential baseline expression of some genes may indicate resilience to infection.

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The genomes of many strains of baker’s yeast, Saccharomyces cerevisiae, contain multiple repeats of the copper-binding protein Cup1. Cup1 is a member of the metallothionein family, and is found in a tandem array on chromosome VIII. In this thesis, I describe studies that characterized these tandem arrays and their mechanism of formation across diverse strains of yeast. I show that CUP1 arrays are an illuminating model system for observing recombination in eukaryotes, and describe insights derived from these observations.

In our first study, we analyzed 101 natural isolates of S. cerevisiae in order to examine the diversity of CUP1-containing repeats across different strains. We identified five distinct classes of repeats that contain CUP1. We also showed that some strains have only a single copy of CUP1. By comparing the sequences of all the strains, we were able to elucidate the mechanism of formation of the CUP1 tandem arrays, which involved unequal non-homologous recombination events starting from a strain that had only a single CUP1 gene. Our observation of CUP1 repeat formation allows more general insights about the formation of tandem repeats from single-copy genes in eukaryotes, which is one of the most important mechanisms by which organisms evolve.

In our second study, we delved deeper into our mechanistic investigations by measuring the relative rates of inter-homolog and intra-/inter-sister chromatid recombination in CUP1 tandem arrays. We used a diploid strain that is heterozygous both for insertion of a selectable marker (URA3) inside the tandem array, and also for markers at either end of the array. The intra-/inter-sister chromatid recombination rate turned out to be more than ten-fold greater than the inter-homolog rate. Moreover, we found that loss of the proteins Rad51 and Rad52, which are required for most inter-homolog recombination, did not greatly reduce recombination in the CUP1 tandem repeats. Additionally, we investigated the effects of elevated copper levels on the rate of each type of recombination at the CUP1 locus. Both types of recombination are increased at high concentrations of copper (as is known to be the case for CUP1 transcription). Furthermore, the inter-homolog recombination rate at the CUP1 locus is higher than the average over the genome during mitosis, but is lower than the average during meiosis.

The research described in Chapter 2 is published in 2014.

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Deletion of the TP53 gene on chromosome 17p13.1 is the prognostic factor associated with the shortest survival in CLL. We used array-based comparative genomic hybridisation (arrayCGH) to identify additional DNA copy number changes in peripheral blood samples from 74 LRF CLL4 trial patients, 37 with >or=5% and 37 without TP53-deleted cells. ArrayCGH reliably detected deletions on 17p, including the TP53 locus, in cases with >or=50%TP53-deleted cells detected by fluorescence in situ hybridisation, plus seven additional cases with deleted regions on 17p excluding TP53. Losses on chromosomal regions 18p and/or 20p were found exclusively in cases with >or=5%TP53-deleted cells (por=5%TP53-deleted cases (p=0.02). In particular, amplification of 2p and deletion of 6q were both more frequent. Cases with >20%TP53-deleted cells had the worst prognosis in the LRF CLL4 trial.

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Microsecond long Molecular Dynamics (MD) trajectories of biomolecular processes are now possible due to advances in computer technology. Soon, trajectories long enough to probe dynamics over many milliseconds will become available. Since these timescales match the physiological timescales over which many small proteins fold, all atom MD simulations of protein folding are now becoming popular. To distill features of such large folding trajectories, we must develop methods that can both compress trajectory data to enable visualization, and that can yield themselves to further analysis, such as the finding of collective coordinates and reduction of the dynamics. Conventionally, clustering has been the most popular MD trajectory analysis technique, followed by principal component analysis (PCA). Simple clustering used in MD trajectory analysis suffers from various serious drawbacks, namely, (i) it is not data driven, (ii) it is unstable to noise and change in cutoff parameters, and (iii) since it does not take into account interrelationships amongst data points, the separation of data into clusters can often be artificial. Usually, partitions generated by clustering techniques are validated visually, but such validation is not possible for MD trajectories of protein folding, as the underlying structural transitions are not well understood. Rigorous cluster validation techniques may be adapted, but it is more crucial to reduce the dimensions in which MD trajectories reside, while still preserving their salient features. PCA has often been used for dimension reduction and while it is computationally inexpensive, being a linear method, it does not achieve good data compression. In this thesis, I propose a different method, a nonmetric multidimensional scaling (nMDS) technique, which achieves superior data compression by virtue of being nonlinear, and also provides a clear insight into the structural processes underlying MD trajectories. I illustrate the capabilities of nMDS by analyzing three complete villin headpiece folding and six norleucine mutant (NLE) folding trajectories simulated by Freddolino and Schulten [1]. Using these trajectories, I make comparisons between nMDS, PCA and clustering to demonstrate the superiority of nMDS. The three villin headpiece trajectories showed great structural heterogeneity. Apart from a few trivial features like early formation of secondary structure, no commonalities between trajectories were found. There were no units of residues or atoms found moving in concert across the trajectories. A flipping transition, corresponding to the flipping of helix 1 relative to the plane formed by helices 2 and 3 was observed towards the end of the folding process in all trajectories, when nearly all native contacts had been formed. However, the transition occurred through a different series of steps in all trajectories, indicating that it may not be a common transition in villin folding. The trajectories showed competition between local structure formation/hydrophobic collapse and global structure formation in all trajectories. Our analysis on the NLE trajectories confirms the notion that a tight hydrophobic core inhibits correct 3-D rearrangement. Only one of the six NLE trajectories folded, and it showed no flipping transition. All the other trajectories get trapped in hydrophobically collapsed states. The NLE residues were found to be buried deeply into the core, compared to the corresponding lysines in the villin headpiece, thereby making the core tighter and harder to undo for 3-D rearrangement. Our results suggest that the NLE may not be a fast folder as experiments suggest. The tightness of the hydrophobic core may be a very important factor in the folding of larger proteins. It is likely that chaperones like GroEL act to undo the tight hydrophobic core of proteins, after most secondary structure elements have been formed, so that global rearrangement is easier. I conclude by presenting facts about chaperone-protein complexes and propose further directions for the study of protein folding.

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The protein lysate array is an emerging technology for quantifying the protein concentration ratios in multiple biological samples. It is gaining popularity, and has the potential to answer questions about post-translational modifications and protein pathway relationships. Statistical inference for a parametric quantification procedure has been inadequately addressed in the literature, mainly due to two challenges: the increasing dimension of the parameter space and the need to account for dependence in the data. Each chapter of this thesis addresses one of these issues. In Chapter 1, an introduction to the protein lysate array quantification is presented, followed by the motivations and goals for this thesis work. In Chapter 2, we develop a multi-step procedure for the Sigmoidal models, ensuring consistent estimation of the concentration level with full asymptotic efficiency. The results obtained in this chapter justify inferential procedures based on large-sample approximations. Simulation studies and real data analysis are used to illustrate the performance of the proposed method in finite-samples. The multi-step procedure is simpler in both theory and computation than the single-step least squares method that has been used in current practice. In Chapter 3, we introduce a new model to account for the dependence structure of the errors by a nonlinear mixed effects model. We consider a method to approximate the maximum likelihood estimator of all the parameters. Using the simulation studies on various error structures, we show that for data with non-i.i.d. errors the proposed method leads to more accurate estimates and better confidence intervals than the existing single-step least squares method.

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The folding and targeting of membrane proteins poses a major challenge to the cell, as they must remain insertion competent while their highly hydrophobic transmembrane (TM) domains are transferred from the ribosome, through the aqueous cytosol and into the lipid bilayer. The biogenesis of a mature membrane protein takes place through the insertion and integration into the lipid bilayer. A number of TM proteins have been shown to gain some degree of secondary structure within the ribosome tunnel and to retain this conformation throughout maturation. Although studies into the folding and targeting of a number of membrane proteins have been carried out to date, there is little information on one of the largest class of eukaryotic membrane proteins; the G-protein-coupled receptors (GPCRs). This project studies the early folding events of the human ortholog of GPR35. To analyse the structure of the 1st TM domain, intermediates were generated and assessed by the biochemical method of pegylation (PEG-MAL). A structurally-similar microbial opsin (Bacterioopsin) was also used to investigate the differences in the early protein folding within eukaryotic and prokaryotic translation systems. Results showed that neither the 1st TM domain of GPR35 nor Bacterioopsin were capable of compacting in the ribosome tunnel before their N-terminus reached the ribosome exit point. The results for this assay remained consistent whether the proteins were translated in a eukaryotic or prokaryotic translation system. To examine the communication mechanism between the ribosome, the nascent chain and the protein targeting pathway, crosslinking experiments were carried out using the homobifunctional lysine cross-linker BS3. Specifically, the data generated here show that the nascent chain of GPR35 reaches the ribosomal protein uL23 in an extended conformation and interacts with the SRP protein as it exits the ribosome tunnel. This confirms the role of SRP in the co-translational targeting of GPR35. Using these methods insights into the early folding of GPCRs has been obtained. Further experiments using site-directed mutagenesis to reduce hydrophobicity in the 1st TM domain of GPR35, highlighted the mechanisms by which GPCRs are targeted to the endoplasmic reticulum. Confirming that hydrophobicity within the signal anchor sequence is essential of SRP-dependent targeting. Following the successful interaction of the nascent GPR35 and SRP, GPR35 is successfully targeted to ER membranes, shown here as dog pancreas microsomes (DPMs). Glycosylation of the GPR35 N-terminus was used to determine nascent chain structure as it is inserted into the ER membrane. These glycosylation experiments confirm that TM1 has obtained its compacted state whilst residing in the translocon. Finally, a site-specific cross-linking approach using the homobifunctional cysteine cross-linker, BMH, was used to study the lateral integration of GPR35 into the ER. Cross-linking of GPR35 TM1 and TM2 could be detected adjacent to a protein of ~45kDa, believed to be Sec61α. The loss of this adduct, as the nascent chain extends, showed the lateral movement of GPR35 TM1 from the translocon was dependent on the subsequent synthesis of TM2.

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Suppressor of cytokine signalling 3 (SOCS3) is a potent inhibitor of the mitogenic, migratory and pro-inflammatory pathways responsible for the development of neointimal hyperplasia (NIH), a key contributor to the failure of vascular reconstructive procedures. However, the protein levels of SOCS3, and therefore its potential to reduce NIH, is limited by its ubiquitylation and high turnover by the proteasome. I hypothesised that stabilisation of endogenous SOCS3 by inhibiting its ubiquitylation has the potential to limit vascular inflammation and NIH. Consequently, the aim of this PhD was to identify the mechanisms promoting the rapid turnover of SOCS3. Initial experiments involved the identification of residues involved in regulating the turnover of SOCS3 at the proteasome. I assessed the ubiquitylation status of a panel of FLAG tagged SOCS3 truncation mutants and identified a C-terminal 44 amino acid region required for SOCS3 ubiquitylation. This region localised to the SOCS box which is involved in binding Elongin B/C and the formation of a functional E3 ubiquitin ligase complex. However, the single lysine residue at position 173, located within this 44 amino acid region, was not required for ubiquitylation. Moreover, Emetine chase assays revealed that loss of either Lys173 or Lys6 (as documented in the literature) had no significant effect on SOCS3 stability 8 hrs post emetine treatment. As mutagenesis studies failed to identify key sites of ubiquitylation responsible for targeting SOCS3 to the proteasome, LC-MS-MS analysis of a SOCS3 co-immunoprecipitate was employed. These data were searched for the presence of a Gly-Gly doublet (+114 Da mass shift) and revealed 8 distinct sites of ubiquitylation (Lys23, Lys28, Lys40, Lys85, Lys91, Lys173, Lys195, Lys206) on SOCS3 however Lys6 ubiquitylation was not detected. As multiple Lys residues were ubiquitylated, I hypothesised that only a Lys-less SOCS3, in which all 8 Lys residues were mutated to Arg, would be resistant to ubiquitylation. Compared to WT SOCS3, Lys-less SOCS3 was indeed found to be completely resistant to ubiquitylation, and significantly more stable than WT SOCS3. These changes occurred in the absence of any detrimental effect on the ability of Lys-less SOCS3 to interact with the Elongin B/C components required to generate a functional E3 ligase complex. In addition, both WT and Lys-less SOCS3 were equally capable of inhibiting cytokine-stimulated STAT3 phosphorylation upon co-expression with a chimeric EpoR-gp130 receptor. To assess whether SOCS3 auto-ubiquitylates I generated an L189A SOCS3 mutant that could no longer bind the Elongins and therefore form the E3 ligase complex required for ubiquitylation. A denaturing IP to assess the ubiquitylation status of this mutant was performed and revealed that, despite an inability to bind the Elongins, the L189A mutant was poly-ubiquitylated similar to WT SOCS3. Together these data suggested that SOCS3 does not auto-ubiquitylate and that a separate E3 ligase must regulate SOCS3 ubiquitylation. This study sought to identify the E3 ligase and deubiquitylating (DUB) enzymes controlling the ubiquitylation of SOCS3. Our initial strategy was to develop a tool to screen an E3 ligase/DUB library, using an siARRAY, to sequentially knockdown all known E3 ligases in the presence of a SOCS3-luciferase fusion protein or endogenous SOCS3 in a high content imaging screening platform. However, due to a poor assay window (<2) and non-specific immunoreactivity of SOCS3 antibodies available, these methods were deemed unsuitable for screening purposes. In the absence of a suitable tool to screen the si-ARRAY, LC-MS-MS analysis of a SOCS3 co-immunoprecipitate (co-IP) was investigated. I performed a SOCS3 under conditions which preserved protein-protein interactions, with the aim of identifying novel E3 ligase and/or DUBs that could potentially interact with SOCS3. These data were searched for E3 ligase or DUB enzymes that may interact with SOCS3 in HEK293 cells and identified two promising candidates i) an E3 ligase known as HectD1 and ii) a DUB known as USP15. This thesis has demonstrated that in the presence of HectD1 overexpression, a slight increase in K63-linked polyubiquitylation of SOCS3 was observed. Mutagenesis also revealed that an N-terminal region of SOCS3 may act as a repressor of this interaction with HectD1. Additionally, USP15 was shown to reduce SOCS3 polyubiquitylation in a HEK293 overexpression system suggesting this may act as a DUB for SOCS3. The C-terminal region of SOCS3 was also shown to play a major role in the interaction with USP15. The original hypothesis of this thesis was that stabilisation of endogenous SOCS3 by inhibiting its ubiquitylation has the potential to limit vascular inflammation and NIH. Consistent with this hypothesis, immunohistochemistry visualisation of SOCS3, in human saphenous vein tissue derived from CABG patients, revealed that while SOCS3 was present throughout the media of these vessels the levels of SOCS3 within the neointima was reduced. Finally, preliminary data supporting the hypothesis that SOCS3 overexpression may limit the proliferation, but not migration, of human saphenous vein smooth muscle cells (HSVSMCs) is presented. It is expected that multiple E3 ligases and DUBs will contribute to the regulation of SOCS3 turnover. However, the identification of candidate E3 ligases or DUBs that play a significant role in SOCS3 turnover may facilitate the development of peptide disruptors or gene therapy targets to attenuate pathological SMC proliferation. A targeted approach, inhibiting the interaction between SOCS3 and identified E3 ligase, that controls the levels of SOCS3, would be expected to reduce the undesirable effects associated with global inhibition of the E3 ligase involved.