8 resultados para Superfamily

em Aston University Research Archive


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Epitope identification is the basis of modern vaccine design. The present paper studied the supermotif of the HLA-A3 superfamily, using comparative molecular similarity indices analysis (CoMSIA). Four alleles with high phenotype frequencies were used: A*1101, A*0301, A*3101 and A*6801. Five physicochemical properties—steric bulk, electrostatic potential, local hydro-phobicity, hydrogen-bond donor and acceptor abilities—were considered and ‘all fields’ models were produced for each of the alleles. The models have a moderate level of predictivity and there is a good correlation between the data. A revised HLA-A3 supermotif was defined based on the comparison of favoured and disfavoured properties for each position of the MHC bound peptide. The present study demonstrated that CoMSIA is an effective tool for studying peptide–MHC interactions.

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Tetraspanins are thought to exert their biological function(s) by co-ordinating the lateral movement and trafficking of associated molecules into tetraspanin-enriched microdomains. A second four-TM (transmembrane) domain protein family, the Claudin superfamily, is the major structural component of cellular TJs (tight junctions). Although the Claudin family displays low sequence homology and appears to be evolutionarily distinct from the tetraspanins, CD81 and Claudin-1 are critical molecules defining HCV (hepatitis C virus) entry; we recently demonstrated that CD81-Claudin-1 complexes have an essential role in this process. To understand the molecular basis of CD81-Claudin-1 complex formation, we produced and purified milligram quantities of full-length CD81 and Claudin-1, alone and in complex, in both detergent and lipid contexts. Structural characterization of these purified proteins will allow us to define the mechanism(s) underlying virus-cell interactions and aid the design of therapeutic agents targeting early steps in the viral life cycle.

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G-protein coupled receptors (GPCRs) are a superfamily of membrane integral proteins responsible for a large number of physiological functions. Approximately 50% of marketed drugs are targeted toward a GPCR. Despite showing a high degree of structural homology, there is a large variance in sequence within the GPCR superfamily which has lead to difficulties in identifying and classifying potential new GPCR proteins. Here the various computational techniques that can be used to characterize a novel GPCR protein are discussed, including both alignment-based and alignment-free approaches. In addition, the application of homology modeling to building the three-dimensional structures of GPCRs is described.

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The transmembrane domain proteins of the claudin superfamily are the major structural components of cellular tight junctions. One family member, claudin-1, also associates with tetraspanin CD81 as part of a receptor complex that is essential for hepatitis C virus (HCV) infection of the liver. To understand the molecular basis of claudin-1/CD81 association we previously produced and purified milligram quantities of functional, full-length CD81, which binds a soluble form of HCV E2 glycoprotein (sE2). Here we report the production, purification and characterization of claudin-1. Both yeast membrane-bound and detergent-extracted, purified claudin-1 were antigenic and recognized by specific antibodies. Analytical ultracentrifugation demonstrated that extraction with n-octyl-ß-d-glucopyranoside yielded monodispersed, dimeric pools of claudin-1 while extraction with profoldin-8 or n-decylphosphocholine yielded a dynamic mixture of claudin-1 oligomers. Neither form bound sE2 in line with literature expectations, while further functional analysis was hampered by the finding that incorporation of claudin-1 into proteoliposomes rendered them intractable to study. Dynamic light scattering demonstrated that claudin-1 oligomers associate with CD81 in vitro in a defined molar ratio of 1:2 and that complex formation was enhanced by the presence of cholesteryl hemisuccinate. Attempts to assay the complex biologically were limited by our finding that claudin-1 affects the properties of proteoliposomes. We conclude that recombinant, correctly-folded, full-length claudin-1 can be produced in yeast membranes, that it can be extracted in different oligomeric forms that do not bind sE2 and that a dynamic preparation can form a specific complex with CD81 in vitro in the absence of any other cellular components. These findings pave the way for the structural characterization of claudin-1 alone and in complex with CD81.

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The G-protein coupled receptor (GPCR) superfamily fulfils various metabolic functions and interacts with a diverse range of ligands. There is a lack of sequence similarity between the six classes that comprise the GPCR superfamily. Moreover, most novel GPCRs found have low sequence similarity to other family members which makes it difficult to infer properties from related receptors. Many different approaches have been taken towards developing efficient and accurate methods for GPCR classification, ranging from motif-based systems to machine learning as well as a variety of alignment-free techniques based on the physiochemical properties of their amino acid sequences. This review describes the inherent difficulties in developing a GPCR classification algorithm and includes techniques previously employed in this area.

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The bronchial epithelium is a source of both α and β chemokines and, uniquely, of secretory component (SC), the extracellular ligand-binding domain of the polymeric IgA receptor. Ig superfamily relatives of SC, such as IgG and α2-macroglobulin, bind IL-8. Therefore, we tested the hypothesis that SC binds IL-8, modifying its activity as a neutrophil chemoattractant. Primary bronchial epithelial cells were cultured under conditions to optimize SC synthesis. The chemokines IL-8, epithelial neutrophil-activating peptide-78, growth-related oncogene α, and RANTES were released constitutively by epithelial cells from both normal and asthmatic donors and detected in high m.w. complexes with SC. There were no qualitative differences in the production of SC-chemokine complexes by epithelial cells from normal or asthmatic donors, and in all cases this was the only form of chemokine detected. SC contains 15% N-linked carbohydrate, and complete deglycosylation with peptide N-glycosidase F abolished IL-8 binding. In micro-Boyden chamber assays, no IL-8-dependent neutrophil chemotactic responses to epithelial culture supernatants could be demonstrated. SC dose-dependently (IC50 ∼0.3 nM) inhibited the neutrophil chemotactic response to rIL-8 (10 nM) in micro-Boyden chamber assays and also inhibited IL-8-mediated neutrophil transendothelial migration. SC inhibited the binding of IL-8 to nonspecific binding sites on polycarbonate filters and endothelial cell monolayers, and therefore the formation of haptotactic gradients, without effects on IL-8 binding to specific receptors on neutrophils. The data indicate that in the airways IL-8 may be solubilized and inactivated by binding to SC

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The underlying assumption in quantitative structure–activity relationship (QSAR) methodology is that related chemical structures exhibit related biological activities. We review here two QSAR methods in terms of their applicability for human MHC supermotif definition. Supermotifs are motifs that characterise binding to more than one allele. Supermotif definition is the initial in silico step of epitope-based vaccine design. The first QSAR method we review here—the additive method—is based on the assumption that the binding affinity of a peptide depends on contributions from both amino acids and the interactions between them. The second method is a 3D-QSAR method: comparative molecular similarity indices analysis (CoMSIA). Both methods were applied to 771 peptides binding to 9 HLA alleles. Five of the alleles (A*0201, A* 0202, A*0203, A*0206 and A*6802) belong to the HLA-A2 superfamily and the other four (A*0301, A*1101, A*3101 and A*6801) to the HLA-A3 superfamily. For each superfamily, supermotifs defined by the two QSAR methods agree closely and are supported by many experimental data.

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Since the first discovery of S100 members in 1965, their expressions have been affiliated with numerous biological functions in all cells of the body. However, in the recent years, S100A4, a member of this superfamily has emerged as the central target in generating new avenue for cancer therapy as its overexpression has been correlated with cancer patients’ mortality as well as established roles as motility and metastasis promoter. As it has no catalytic activity, S100A4 has to interact with its target proteins to regulate such effects. Up to date, more than 10 S100A4 target proteins have been identified but the mechanical process regulated by S100A4 to induce motility remains vague. In this work, we demonstrated that S100A4 overexpression resulted in actin filaments disorganisation, reduction in focal adhesions, instability of filopodia as well as exhibiting polarised morphology. However, such effects were not observed in truncated versions of S100A4 possibly highlighting the importance of C terminus of S100A4 target recognition. In order to assess some of the intracellular mechanisms that may be involved in promoting migrations, different strategies were used, including active pharmaceutical agents, inhibitors and knockdown experiments. Treatment of S100A4 overexpressing cells with blebbistatin and Y-27632, non muscle myosin IIA (NMMIIA) inhibitors, as well as knockdown of NMMIIA, resulted in motility enhancement and focal adhesions reduction proposing that NMMIIA assisted S100A4 in regulating cell motility but its presence is not essential. Further work done using Cos 7 cell lines, naturally lacking NMMIIA, further demonstrated that S100A4 is capable of regulating cell motility independent of NMMIIA, possibly through poor maturation of focal adhesion. Given that all these experiments highlighted the independency of NMMIIA towards migration, a protein that has been put at the forefront of S100A4-induced motility, we aimed to gather further understanding regarding the other molecular mechanisms that may be at play for motility. Using high throughput imaging (HCI), 3 compounds were identified to be capable of inhibiting S100A4-mediated migration. Although we have yet to investigate the underlying mechanism for their effects, these compounds have been shown to target membrane proteins and the externalisation of S100 proteins, for at least one of the compounds, leading us to speculate that preventing externalisation of S100A4 could potentially regulate cell motility.