999 resultados para Backbone-cyclized Proteins Database


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Application of a computational membrane organization prediction pipeline, MemO, identified putative type II membrane proteins as proteins predicted to encode a single alpha-helical transmembrane domain (TMD) and no signal peptides. MemO was applied to RIKEN's mouse isoform protein set to identify 1436 non-overlapping genomic regions or transcriptional units (TUs), which encode exclusively type II membrane proteins. Proteins with overlapping predicted InterPro and TMDs were reviewed to discard false positive predictions resulting in a dataset comprised of 1831 transcripts in 1408 TUs. This dataset was used to develop a systematic protocol to document subcellular localization of type II membrane proteins. This approach combines mining of published literature to identify subcellular localization data and a high-throughput, polymerase chain reaction (PCR)-based approach to experimentally characterize subcellular localization. These approaches have provided localization data for 244 and 169 proteins. Type II membrane proteins are localized to all major organelle compartments; however, some biases were observed towards the early secretory pathway and punctate structures. Collectively, this study reports the subcellular localization of 26% of the defined dataset. All reported localization data are presented in the LOCATE database (http://www.locate.imb.uq.edu.au).

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Short proteins play key roles in cell signalling and other processes, but their abundance in the mammalian proteome is unknown. Current catalogues of mammalian proteins exhibit an artefactual discontinuity at a length of 100 aa, so that protein abundance peaks just above this length and falls off sharply below it. To clarify the abundance of short proteins, we identify proteins in the FANTOM collection of mouse cDNAs by analysing synonymous and nonsynonymous substitutions with the computer program CRITICA. This analysis confirms that there is no real discontinuity at length 100. Roughly 10% of mouse proteins are shorter than 100 aa, although the majority of these are variants of proteins longer than 100 aa. We identify many novel short proteins, including a dark matter'' subset containing ones that lack detectable homology to other known proteins. Translation assays confirm that some of these novel proteins can be translated and localised to the secretory pathway.

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Cyclotides are a fascinating family of plant-derived peptides characterized by their head-to-tail cyclized backbone and knotted arrangement of three disulfide bonds. This conserved structural architecture, termed the CCK (cyclic cystine knot), is responsible for their exceptional resistance to thermal, chemical and enzymatic degradation. Cyclotides have a variety of biological activities, but their insecticidal activities suggest that their primary function is in plant defence. In the present study, we determined the cyclotide content of the sweet violet Viola odorata, a member of the Violaceae family. We identified 30 cyclotides from the aerial parts and roots of this plant, 13 of which are novel sequences. The new sequences provide information about the natural diversity of cyclotides and the role of particular residues in defining structure and function. As many of the biological activities of cyclotides appear to be associated with membrane interactions, we used haemolytic activity as a marker of bioactivity for a selection of the new cyclotides. The new cyclotides were tested for their ability to resist proteolysis by a range of enzymes and, in common with other cyclotides, were completely resistant to trypsin, pepsin and thermolysin. The results show that while biological activity varies with the sequence, the proteolytic stability of the framework does not, and appears to be an inherent feature of the cyclotide framework. The structure of one of the new cyclotides, cycloviolacin O14, was determined and shown to contain the CCK motif. This study confirms that cyclotides may be regarded as a natural combinatorial template that displays a variety of peptide epitopes most likely targeted to a range of plant pests and pathogens.

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Three iromps (iron-regulated outer membrane proteins) of Aeromonas salmonicida were identified by the use of specific antibodies together with Southern hybridization analysis and limited nucleotide sequencing of their genes. The results of these experiments together with a search of the international database for homologous sequences led to their identification as follows: -86 kDa iromp (FstA) as a Vibrio anguillarum Fat A homologue -82 kDa iromp (FepA) as an Escherichia coli FepA homologue -74 kDa iromp (IrpA) as an Escherichia coli Cir homologue.

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Protein-DNA interactions are an essential feature in the genetic activities of life, and the ability to predict and manipulate such interactions has applications in a wide range of fields. This Thesis presents the methods of modelling the properties of protein-DNA interactions. In particular, it investigates the methods of visualising and predicting the specificity of DNA-binding Cys2His2 zinc finger interaction. The Cys2His2 zinc finger proteins interact via their individual fingers to base pair subsites on the target DNA. Four key residue positions on the a- helix of the zinc fingers make non-covalent interactions with the DNA with sequence specificity. Mutating these key residues generates combinatorial possibilities that could potentially bind to any DNA segment of interest. Many attempts have been made to predict the binding interaction using structural and chemical information, but with only limited success. The most important contribution of the thesis is that the developed model allows for the binding properties of a given protein-DNA binding to be visualised in relation to other protein-DNA combinations without having to explicitly physically model the specific protein molecule and specific DNA sequence. To prove this, various databases were generated, including a synthetic database which includes all possible combinations of the DNA-binding Cys2His2 zinc finger interactions. NeuroScale, a topographic visualisation technique, is exploited to represent the geometric structures of the protein-DNA interactions by measuring dissimilarity between the data points. In order to verify the effect of visualisation on understanding the binding properties of the DNA-binding Cys2His2 zinc finger interaction, various prediction models are constructed by using both the high dimensional original data and the represented data in low dimensional feature space. Finally, novel data sets are studied through the selected visualisation models based on the experimental DNA-zinc finger protein database. The result of the NeuroScale projection shows that different dissimilarity representations give distinctive structural groupings, but clustering in biologically-interesting ways. This method can be used to forecast the physiochemical properties of the novel proteins which may be beneficial for therapeutic purposes involving genome targeting in general.

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Background: HLA-DPs are class II MHC proteins mediating immune responses to many diseases. Peptides bind MHC class II proteins in the acidic environment within endosomes. Acidic pH markedly elevates association rate constants but dissociation rates are almost unchanged in the pH range 5.0 - 7.0. This pH-driven effect can be explained by the protonation/deprotonation states of Histidine, whose imidazole has a pKa of 6.0. At pH 5.0, imidazole ring is protonated, making Histidine positively charged and very hydrophilic, while at pH 7.0 imidazole is unprotonated, making Histidine less hydrophilic. We develop here a method to predict peptide binding to the four most frequent HLA-DP proteins: DP1, DP41, DP42 and DP5, using a molecular docking protocol. Dockings to virtual combinatorial peptide libraries were performed at pH 5.0 and pH 7.0. Results: The X-ray structure of the peptide - HLA-DP2 protein complex was used as a starting template to model by homology the structure of the four DP proteins. The resulting models were used to produce virtual combinatorial peptide libraries constructed using the single amino acid substitution (SAAS) principle. Peptides were docked into the DP binding site using AutoDock at pH 5.0 and pH 7.0. The resulting scores were normalized and used to generate Docking Score-based Quantitative Matrices (DS-QMs). The predictive ability of these QMs was tested using an external test set of 484 known DP binders. They were also compared to existing servers for DP binding prediction. The models derived at pH 5.0 predict better than those derived at pH 7.0 and showed significantly improved predictions for three of the four DP proteins, when compared to the existing servers. They are able to recognize 50% of the known binders in the top 5% of predicted peptides. Conclusions: The higher predictive ability of DS-QMs derived at pH 5.0 may be rationalised by the additional hydrogen bond formed between the backbone carbonyl oxygen belonging to the peptide position before p1 (p-1) and the protonated ε-nitrogen of His 79β. Additionally, protonated His residues are well accepted at most of the peptide binding core positions which is in a good agreement with the overall negatively charged peptide binding site of most MHC proteins. © 2012 Patronov et al.; licensee BioMed Central Ltd.

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Background: DNA-binding proteins play a pivotal role in various intra- and extra-cellular activities ranging from DNA replication to gene expression control. Identification of DNA-binding proteins is one of the major challenges in the field of genome annotation. There have been several computational methods proposed in the literature to deal with the DNA-binding protein identification. However, most of them can't provide an invaluable knowledge base for our understanding of DNA-protein interactions. Results: We firstly presented a new protein sequence encoding method called PSSM Distance Transformation, and then constructed a DNA-binding protein identification method (SVM-PSSM-DT) by combining PSSM Distance Transformation with support vector machine (SVM). First, the PSSM profiles are generated by using the PSI-BLAST program to search the non-redundant (NR) database. Next, the PSSM profiles are transformed into uniform numeric representations appropriately by distance transformation scheme. Lastly, the resulting uniform numeric representations are inputted into a SVM classifier for prediction. Thus whether a sequence can bind to DNA or not can be determined. In benchmark test on 525 DNA-binding and 550 non DNA-binding proteins using jackknife validation, the present model achieved an ACC of 79.96%, MCC of 0.622 and AUC of 86.50%. This performance is considerably better than most of the existing state-of-the-art predictive methods. When tested on a recently constructed independent dataset PDB186, SVM-PSSM-DT also achieved the best performance with ACC of 80.00%, MCC of 0.647 and AUC of 87.40%, and outperformed some existing state-of-the-art methods. Conclusions: The experiment results demonstrate that PSSM Distance Transformation is an available protein sequence encoding method and SVM-PSSM-DT is a useful tool for identifying the DNA-binding proteins. A user-friendly web-server of SVM-PSSM-DT was constructed, which is freely accessible to the public at the web-site on http://bioinformatics.hitsz.edu.cn/PSSM-DT/.

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In this study, we carried out a comparative analysis between two classical methodologies to prospect residue contacts in proteins: the traditional cutoff dependent (CD) approach and cutoff free Delaunay tessellation (DT). In addition, two alternative coarse-grained forms to represent residues were tested: using alpha carbon (CA) and side chain geometric center (GC). A database was built, comprising three top classes: all alpha, all beta, and alpha/beta. We found that the cutoff value? at about 7.0 A emerges as an important distance parameter.? Up to 7.0 A, CD and DT properties are unified, which implies that at this distance all contacts are complete and legitimate (not occluded). We also have shown that DT has an intrinsic missing edges problem when mapping the first layer of neighbors. In proteins, it may produce systematic errors affecting mainly the contact network in beta chains with CA. The almost-Delaunay (AD) approach has been proposed to solve this DT problem. We found that even AD may not be an advantageous solution. As a consequence, in the strict range up ? to 7.0 A, the CD approach revealed to be a simpler, more complete, and reliable technique than DT or AD. Finally, we have shown that coarse-grained residue representations may introduce bias in the analysis of neighbors in cutoffs up to ? 6.8 A, with CA favoring alpha proteins and GC favoring beta proteins. This provides an additional argument pointing to ? the value of 7.0 A as an important lower bound cutoff to be used in contact analysis of proteins.

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Xanthomonas citri subsp. citri (X. citri) is the causative agent of the citrus canker, a disease that affects several citrus plants in Brazil and across the world. Although many studies have demonstrated the importance of genes for infection and pathogenesis in this bacterium, there are no data related to phosphate uptake and assimilation pathways. To identify the proteins that are involved in the phosphate response, we performed a proteomic analysis of X. citri extracts after growth in three culture media with different phosphate concentrations. Using mass spectrometry and bioinformatics analysis, we showed that X. citri conserved orthologous genes from Pho regulon in Escherichia coli, including the two-component system PhoR/PhoB, ATP binding cassette (ABC transporter) Pst for phosphate uptake, and the alkaline phosphatase PhoA. Analysis performed under phosphate starvation provided evidence of the relevance of the Pst system for phosphate uptake, as well as both periplasmic binding proteins, PhoX and PstS, which were formed in high abundance. The results from this study are the first evidence of the Pho regulon activation in X. citri and bring new insights for studies related to the bacterial metabolism and physiology. Biological significance Using proteomics and bioinformatics analysis we showed for the first time that the phytopathogenic bacterium X. citri conserves a set of proteins that belong to the Pho regulon, which are induced during phosphate starvation. The most relevant in terms of conservation and up-regulation were the periplasmic-binding proteins PstS and PhoX from the ABC transporter PstSBAC for phosphate, the two-component system composed by PhoR/PhoB and the alkaline phosphatase PhoA.

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Understanding the molecular mechanisms of oral carcinogenesis will yield important advances in diagnostics, prognostics, effective treatment, and outcome of oral cancer. Hence, in this study we have investigated the proteomic and peptidomic profiles by combining an orthotopic murine model of oral squamous cell carcinoma (OSCC), mass spectrometry-based proteomics and biological network analysis. Our results indicated the up-regulation of proteins involved in actin cytoskeleton organization and cell-cell junction assembly events and their expression was validated in human OSCC tissues. In addition, the functional relevance of talin-1 in OSCC adhesion, migration and invasion was demonstrated. Taken together, this study identified specific processes deregulated in oral cancer and provided novel refined OSCC-targeting molecules.

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High-throughput screening of physical, genetic and chemical-genetic interactions brings important perspectives in the Systems Biology field, as the analysis of these interactions provides new insights into protein/gene function, cellular metabolic variations and the validation of therapeutic targets and drug design. However, such analysis depends on a pipeline connecting different tools that can automatically integrate data from diverse sources and result in a more comprehensive dataset that can be properly interpreted. We describe here the Integrated Interactome System (IIS), an integrative platform with a web-based interface for the annotation, analysis and visualization of the interaction profiles of proteins/genes, metabolites and drugs of interest. IIS works in four connected modules: (i) Submission module, which receives raw data derived from Sanger sequencing (e.g. two-hybrid system); (ii) Search module, which enables the user to search for the processed reads to be assembled into contigs/singlets, or for lists of proteins/genes, metabolites and drugs of interest, and add them to the project; (iii) Annotation module, which assigns annotations from several databases for the contigs/singlets or lists of proteins/genes, generating tables with automatic annotation that can be manually curated; and (iv) Interactome module, which maps the contigs/singlets or the uploaded lists to entries in our integrated database, building networks that gather novel identified interactions, protein and metabolite expression/concentration levels, subcellular localization and computed topological metrics, GO biological processes and KEGG pathways enrichment. This module generates a XGMML file that can be imported into Cytoscape or be visualized directly on the web. We have developed IIS by the integration of diverse databases following the need of appropriate tools for a systematic analysis of physical, genetic and chemical-genetic interactions. IIS was validated with yeast two-hybrid, proteomics and metabolomics datasets, but it is also extendable to other datasets. IIS is freely available online at: http://www.lge.ibi.unicamp.br/lnbio/IIS/.

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Congenital muscular dystrophy with laminin α2 chain deficiency (MDC1A) is one of the most severe forms of muscular disease and is characterized by severe muscle weakness and delayed motor milestones. The genetic basis of MDC1A is well known, yet the secondary mechanisms ultimately leading to muscle degeneration and subsequent connective tissue infiltration are not fully understood. In order to obtain new insights into the molecular mechanisms underlying MDC1A, we performed a comparative proteomic analysis of affected muscles (diaphragm and gastrocnemius) from laminin α2 chain-deficient dy(3K)/dy(3K) mice, using multidimensional protein identification technology combined with tandem mass tags. Out of the approximately 700 identified proteins, 113 and 101 proteins, respectively, were differentially expressed in the diseased gastrocnemius and diaphragm muscles compared with normal muscles. A large portion of these proteins are involved in different metabolic processes, bind calcium, or are expressed in the extracellular matrix. Our findings suggest that metabolic alterations and calcium dysregulation could be novel mechanisms that underlie MDC1A and might be targets that should be explored for therapy. Also, detailed knowledge of the composition of fibrotic tissue, rich in extracellular matrix proteins, in laminin α2 chain-deficient muscle might help in the design of future anti-fibrotic treatments. All MS data have been deposited in the ProteomeXchange with identifier PXD000978 (http://proteomecentral.proteomexchange.org/dataset/PXD000978).

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This work describes the evaluation of metals and (metallo)proteins in vitreous humor samples and their correlations with some biological aspects in different post-mortem intervals (1-7 days), taking into account both decomposing and non-decomposing bodies. After qualitative evaluation of the samples involving 26 elements, representative metal ions (Fe, Mg and Mo) are determined by inductively coupled plasma mass spectrometry after using mini-vial decomposition system for sample preparation. A significant trend for Fe is found with post-mortem time for decomposing bodies because of a significant increase of iron concentration when comparing samples from bodies presenting 3 and 7 days post-mortem interval. An important clue to elucidate the role of metals is the coupling of liquid chromatography with inductively coupled plasma mass spectrometry for identification of metals linked to proteins, as well as mass spectrometry for the identification of those proteins involved in the post-mortem interval.

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Different types of water bodies, including lakes, streams, and coastal marine waters, are often susceptible to fecal contamination from a range of point and nonpoint sources, and have been evaluated using fecal indicator microorganisms. The most commonly used fecal indicator is Escherichia coli, but traditional cultivation methods do not allow discrimination of the source of pollution. The use of triplex PCR offers an approach that is fast and inexpensive, and here enabled the identification of phylogroups. The phylogenetic distribution of E. coli subgroups isolated from water samples revealed higher frequencies of subgroups A1 and B23 in rivers impacted by human pollution sources, while subgroups D1 and D2 were associated with pristine sites, and subgroup B1 with domesticated animal sources, suggesting their use as a first screening for pollution source identification. A simple classification is also proposed based on phylogenetic subgroup distribution using the w-clique metric, enabling differentiation of polluted and unpolluted sites.