9,008 research outputs found

    Protein Expression, Characterization and Activity Comparisons of Wild Type and Mutant DUSP5 Proteins

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    Background The mitogen-activated protein kinases (MAPKs) pathway is critical for cellular signaling, and proteins such as phosphatases that regulate this pathway are important for normal tissue development. Based on our previous work on dual specificity phosphatase-5 (DUSP5), and its role in embryonic vascular development and disease, we hypothesized that mutations in DUSP5 will affect its function. Results In this study, we tested this hypothesis by generating full-length glutathione-S-transferase-tagged DUSP5 and serine 147 proline mutant (S147P) proteins from bacteria. Light scattering analysis, circular dichroism, enzymatic assays and molecular modeling approaches have been performed to extensively characterize the protein form and function. We demonstrate that both proteins are active and, interestingly, the S147P protein is hypoactive as compared to the DUSP5 WT protein in two distinct biochemical substrate assays. Furthermore, due to the novel positioning of the S147P mutation, we utilize computational modeling to reconstruct full-length DUSP5 and S147P to predict a possible mechanism for the reduced activity of S147P. Conclusion Taken together, this is the first evidence of the generation and characterization of an active, full-length, mutant DUSP5 protein which will facilitate future structure-function and drug development-based studies

    Functional Diversity and Structural Disorder in the Human Ubiquitination Pathway

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    The ubiquitin-proteasome system plays a central role in cellular regulation and protein quality control (PQC). The system is built as a pyramid of increasing complexity, with two E1 (ubiquitin activating), few dozen E2 (ubiquitin conjugating) and several hundred E3 (ubiquitin ligase) enzymes. By collecting and analyzing E3 sequences from the KEGG BRITE database and literature, we assembled a coherent dataset of 563 human E3s and analyzed their various physical features. We found an increase in structural disorder of the system with multiple disorder predictors (IUPred - E1: 5.97%, E2: 17.74%, E3: 20.03%). E3s that can bind E2 and substrate simultaneously (single subunit E3, ssE3) have significantly higher disorder (22.98%) than E3s in which E2 binding (multi RING-finger, mRF, 0.62%), scaffolding (6.01%) and substrate binding (adaptor/substrate recognition subunits, 17.33%) functions are separated. In ssE3s, the disorder was localized in the substrate/adaptor binding domains, whereas the E2-binding RING/HECT-domains were structured. To demonstrate the involvement of disorder in E3 function, we applied normal modes and molecular dynamics analyses to show how a disordered and highly flexible linker in human CBL (an E3 that acts as a regulator of several tyrosine kinase-mediated signalling pathways) facilitates long-range conformational changes bringing substrate and E2-binding domains towards each other and thus assisting in ubiquitin transfer. E3s with multiple interaction partners (as evidenced by data in STRING) also possess elevated levels of disorder (hubs, 22.90% vs. non-hubs, 18.36%). Furthermore, a search in PDB uncovered 21 distinct human E3 interactions, in 7 of which the disordered region of E3s undergoes induced folding (or mutual induced folding) in the presence of the partner. In conclusion, our data highlights the primary role of structural disorder in the functions of E3 ligases that manifests itself in the substrate/adaptor binding functions as well as the mechanism of ubiquitin transfer by long-range conformational transitions. © 2013 Bhowmick et al

    Structure and sequence analyses of Bacteroides proteins BVU_4064 and BF1687 reveal presence of two novel predominantly-beta domains, predicted to be involved in lipid and cell surface interactions.

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    BackgroundN-terminal domains of BVU_4064 and BF1687 proteins from Bacteroides vulgatus and Bacteroides fragilis respectively are members of the Pfam family PF12985 (DUF3869). Proteins containing a domain from this family can be found in most Bacteroides species and, in large numbers, in all human gut microbiome samples. Both BVU_4064 and BF1687 proteins have a consensus lipobox motif implying they are anchored to the membrane, but their functions are otherwise unknown. The C-terminal half of BVU_4064 is assigned to protein family PF12986 (DUF3870); the equivalent part of BF1687 was unclassified.ResultsCrystal structures of both BVU_4064 and BF1687 proteins, solved at the JCSG center, show strikingly similar three-dimensional structures. The main difference between the two is that the two domains in the BVU_4064 protein are connected by a short linker, as opposed to a longer insertion made of 4 helices placed linearly along with a strand that is added to the C-terminal domain in the BF1687 protein. The N-terminal domain in both proteins, corresponding to the PF12985 (DUF3869) domain is a β-sandwich with pre-albumin-like fold, found in many proteins belonging to the Transthyretin clan of Pfam. The structures of C-terminal domains of both proteins, corresponding to the PF12986 (DUF3870) domain in BVU_4064 protein and an unclassified domain in the BF1687 protein, show significant structural similarity to bacterial pore-forming toxins. A helix in this domain is in an analogous position to a loop connecting the second and third strands in the toxin structures, where this loop is implicated to play a role in the toxin insertion into the host cell membrane. The same helix also points to the groove between the N- and C-terminal domains that are loosely held together by hydrophobic and hydrogen bond interactions. The presence of several conserved residues in this region together with these structural determinants could make it a functionally important region in these proteins.ConclusionsStructural analysis of BVU_4064 and BF1687 points to possible roles in mediating multiple interactions on the cell-surface/extracellular matrix. In particular the N-terminal domain could be involved in adhesive interactions, the C-terminal domain and the inter-domain groove in lipid or carbohydrate interactions

    Intrinsic structural disorder in cytoskeletal proteins.

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    Cytoskeleton, the internal scaffold of the cell, displays an exceptional combination of stability and dynamics. It is composed of three major filamentous networks, microfilaments (actin filaments), intermediate filaments (neurofilaments), and microtubules. Together, they ensure the physical and structural stability of the cell, whereby also mediating its large-scale structural rearrangements, motility, stress response, division, and internal transport. All three cytoskeletal systems are built upon the same basic design: they have a central repetitive scaffold assembled from folded building elements, surrounded and regulated by accessory regions/proteins that regulate its formation and mediate its countless interactions with its environment, serving to send regulatory signals to and from the cytoskeleton. Here, we elaborate on the idea that the opposing features of stability and dynamics are also manifest in the dichotomy of the structural status of its components, the core being highly structured and the accessory proteins/regions being highly disordered, and are responsible for most of the regulatory (post-translational) input promoting adaptive responses and providing dynamics necessary for each of the cytoskeletal systems. This pattern entails special consequences, in which the manifold functional advantages of structural disorder, most pronounced in regulatory and signaling functions, are all exploited by nature. (c) 2013 Wiley Periodicals, Inc

    The Shigella flexneri OmpA amino acid residues 188EVQ190 are essential for the interaction with the virulence factor PhoN2

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    Shigella flexneri is an intracellular pathogen that deploys an arsenal of virulence factors promoting host cell invasion, intracellular multiplication and intra- and inter-cellular dissemination. We have previously reported that the interaction between apyrase (PhoN2), a periplasmic ATP-diphosphohydrolase, and the C-terminal domain of the outer membrane (OM) protein OmpA is likely required for proper IcsA exposition at the old bacterial pole and thus for full virulence expression of Shigella flexneri (Scribano et al., 2014). OmpA, that is the major OM protein of Gram-negative bacteria, is a multifaceted protein that plays many different roles both in the OM structural integrity and in the virulence of several pathogens. Here, by using yeast two-hybrid technology and by constructing an in silico 3D model of OmpA from S. flexneri 5a strain M90T, we observed that the OmpA residues 188EVQ190 are likely essential for PhoN2-OmpA interaction. The 188EVQ190 amino acids are located within a flexible region of the OmpA protein that could represent a scaffold for protein-protein interaction

    Structure- and context-based analysis of the GxGYxYP family reveals a new putative class of glycoside hydrolase.

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    BackgroundGut microbiome metagenomics has revealed many protein families and domains found largely or exclusively in that environment. Proteins containing the GxGYxYP domain are over-represented in the gut microbiota, and are found in Polysaccharide Utilization Loci in the gut symbiont Bacteroides thetaiotaomicron, suggesting their involvement in polysaccharide metabolism, but little else is known of the function of this domain.ResultsGenomic context and domain architecture analyses support a role for the GxGYxYP domain in carbohydrate metabolism. Sparse occurrences in eukaryotes are the result of lateral gene transfer. The structure of the GxGYxYP domain-containing protein encoded by the BT2193 locus reveals two structural domains, the first composed of three divergent repeats with no recognisable homology to previously solved structures, the second a more familiar seven-stranded β/α barrel. Structure-based analyses including conservation mapping localise a presumed functional site to a cleft between the two domains of BT2193. Matching to a catalytic site template from a GH9 cellulase and other analyses point to a putative catalytic triad composed of Glu272, Asp331 and Asp333.ConclusionsWe suggest that GxGYxYP-containing proteins constitute a novel glycoside hydrolase family of as yet unknown specificity

    Molecular Basis for poly(A) RNP Architecture and Recognition by the Pan2-Pan3 Deadenylase

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    The stability of eukaryotic mRNAs is dependent on a ribonucleoprotein (RNP) complex of poly(A)-binding proteins (PABPC1/Pab1) organized on the poly(A) tail. This poly(A) RNP not only protects mRNAs from premature degradation but also stimulates the Pan2-Pan3 deadenylase complex to catalyze the first step of poly(A) tail shortening. We reconstituted this process in vitro using recombinant proteins and show that Pan2-Pan3 associates with and degrades poly(A) RNPs containing two or more Pab1 molecules. The cryo-EM structure of Pan2-Pan3 in complex with a poly(A) RNP composed of 90 adenosines and three Pab1 protomers shows how the oligomerization interfaces of Pab1 are recognized by conserved features of the deadenylase and thread the poly(A) RNA substrate into the nuclease active site. The structure reveals the basis for the periodic repeating architecture at the 3' end of cytoplasmic mRNAs. This illustrates mechanistically how RNA-bound Pab1 oligomers act as rulers for poly(A) tail length over the mRNAs' lifetime.We would like to thank ... the MPIB cryo-EM, and core facilities ..

    Protein Domain Linker Prediction: A Direction for Detecting Protein – Protein Interactions

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    Protein chains are generally long and consist of multiple domains. Domains are the basic of elements of protein structures that can exist, evolve and function independently. The accurate and reliable identification of protein domains and their interactions has very important impacts in several protein research areas. The accurate prediction of protein domains is a fundamental stage in both experimental and computational proteomics. The knowledge is an initial stage of protein tertiary structure prediction which can give insight into the way in which protein works. The knowledge of domains is also useful in classifying the proteins, understanding their structures, functions and evolution, and predicting protein-protein interactions (PPI). However, predicting structural domains within proteins is a challenging task in computational biology. A promising direction of domain prediction is detecting inter-domain linkers and then predicting the reigns of the protein sequence in which the structural domains are located accordingly. Protein-protein interactions occur at almost every level of cell function. The identification of interaction among proteins and their associated domains provide a global picture of cellular functions and biological processes. It is also an essential step in the construction of PPI networks for human and other organisms. PPI prediction has been considered as a promising alternative to the traditional drug design techniques. The identification of possible viral-host protein interaction can lead to a better understanding of infection mechanisms and, in turn, to the development of several medication drugs and treatment optimization. In this work, a compact and accurate approach for inter-domain linker prediction is developed based solely on protein primary structure information. Then, inter-domain linker knowledge is used in predicting structural domains and detecting PPI. The research work in this dissertation can be summarized in three main contributions. The first contribution is predicting protein inter-domain linker regions by introducing the concept of amino acid compositional index and refining the prediction by using the Simulated Annealing optimization technique. The second contribution is identifying structural domains based on inter-domain linker knowledge. The inter-domain linker knowledge, represented by the compositional index, is enhanced by the in cooperation of biological knowledge, represented by amino acid physiochemical properties. To develop a well optimized Random Forest classifier for predicting novel domain and inter-domain linkers. In the third contribution, the domain information knowledge is utilized to predict protein-protein interactions. This is achieved by characterizing structural domains within protein sequences, analyzing their interactions, and predicting protein interaction based on their interacting domains. The experimental studies and the higher accuracy achieved is a valid argument in favor of the proposed framework

    Improved general regression network for protein domain boundary prediction

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    Background: Protein domains present some of the most useful information that can be used to understand protein structure and functions. Recent research on protein domain boundary prediction has been mainly based on widely known machine learning techniques, such as Artificial Neural Networks and Support Vector Machines. In this study, we propose a new machine learning model (IGRN) that can achieve accurate and reliable classification, with significantly reduced computations. The IGRN was trained using a PSSM (Position Specific Scoring Matrix), secondary structure, solvent accessibility information and inter-domain linker index to detect possible domain boundaries for a target sequence. Results: The proposed model achieved average prediction accuracy of 67% on the Benchmark_2 dataset for domain boundary identification in multi-domains proteins and showed superior predictive performance and generalisation ability among the most widely used neural network models. With the CASP7 benchmark dataset, it also demonstrated comparable performance to existing domain boundary predictors such as DOMpro, DomPred, DomSSEA, DomCut and DomainDiscovery with 70.10% prediction accuracy. Conclusion: The performance of proposed model has been compared favourably to the performance of other existing machine learning based methods as well as widely known domain boundary predictors on two benchmark datasets and excels in the identification of domain boundaries in terms of model bias, generalisation and computational requirements. © 2008 Yoo et al; licensee BioMed Central Ltd
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