Small-angle X-ray Solution Scattering Study of the Multi-aminoacyl-tRNA Synthetase Complex Reveals an Elongated and Multi-armed particle*

Science.gov (United States)

Dias, José; Renault, Louis; Pérez, Javier; Mirande, Marc

2013-01-01

In animal cells, nine aminoacyl-tRNA synthetases are associated with the three auxiliary proteins p18, p38, and p43 to form a stable and conserved large multi-aminoacyl-tRNA synthetase complex (MARS), whose molecular mass has been proposed to be between 1.0 and 1.5 MDa. The complex acts as a molecular hub for coordinating protein synthesis and diverse regulatory signal pathways. Electron microscopy studies defined its low resolution molecular envelope as an overall rather compact, asymmetric triangular shape. Here, we have analyzed the composition and homogeneity of the native mammalian MARS isolated from rabbit liver and characterized its overall internal structure, size, and shape at low resolution by hydrodynamic methods and small-angle x-ray scattering in solution. Our data reveal that the MARS exhibits a much more elongated and multi-armed shape than expected from previous reports. The hydrodynamic and structural features of the MARS are large compared with other supramolecular assemblies involved in translation, including ribosome. The large dimensions and non-compact structural organization of MARS favor a large protein surface accessibility for all its components. This may be essential to allow structural rearrangements between the catalytic and cis-acting tRNA binding domains of the synthetases required for binding the bulky tRNA substrates. This non-compact architecture may also contribute to the spatiotemporal controlled release of some of its components, which participate in non-canonical functions after dissociation from the complex. PMID:23836901

A Bacillus megaterium System for the Production of Recombinant Proteins and Protein Complexes.

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Biedendieck, Rebekka

2016-01-01

For many years the Gram-positive bacterium Bacillus megaterium has been used for the production and secretion of recombinant proteins. For this purpose it was systematically optimized. Plasmids with different inducible promoter systems, with different compatible origins, with small tags for protein purification and with various specific signals for protein secretion were combined with genetically improved host strains. Finally, the development of appropriate cultivation conditions for the production strains established this organism as a bacterial cell factory even for large proteins. Along with the overproduction of individual proteins the organism is now also used for the simultaneous coproduction of up to 14 recombinant proteins, multiple subsequently interacting or forming protein complexes. Some of these recombinant strains are successfully used for bioconversion or the biosynthesis of valuable components including vitamins. The titers in the g per liter scale for the intra- and extracellular recombinant protein production prove the high potential of B. megaterium for industrial applications. It is currently further enhanced for the production of recombinant proteins and multi-subunit protein complexes using directed genetic engineering approaches based on transcriptome, proteome, metabolome and fluxome data.

DNA-Directed Assembly of Capture Tools for Constitutional Studies of Large Protein Complexes.

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Meyer, Rebecca; Faesen, Alex; Vogel, Katrin; Jeganathan, Sadasivam; Musacchio, Andrea; Niemeyer, Christof M

2015-06-10

Large supramolecular protein complexes, such as the molecular machinery involved in gene regulation, cell signaling, or cell division, are key in all fundamental processes of life. Detailed elucidation of structure and dynamics of such complexes can be achieved by reverse-engineering parts of the complexes in order to probe their interactions with distinctive binding partners in vitro. The exploitation of DNA nanostructures to mimic partially assembled supramolecular protein complexes in which the presence and state of two or more proteins are decisive for binding of additional building blocks is reported here. To this end, four-way DNA Holliday junction motifs bearing a fluorescein and a biotin tag, for tracking and affinity capture, respectively, are site-specifically functionalized with centromeric protein (CENP) C and CENP-T. The latter serves as baits for binding of the so-called KMN component, thereby mimicking early stages of the assembly of kinetochores, structures that mediate and control the attachment of microtubules to chromosomes in the spindle apparatus. Results from pull-down experiments are consistent with the hypothesis that CENP-C and CENP-T may bind cooperatively to the KMN network. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Improved Peak Detection and Deconvolution of Native Electrospray Mass Spectra from Large Protein Complexes.

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Lu, Jonathan; Trnka, Michael J; Roh, Soung-Hun; Robinson, Philip J J; Shiau, Carrie; Fujimori, Danica Galonic; Chiu, Wah; Burlingame, Alma L; Guan, Shenheng

2015-12-01

Native electrospray-ionization mass spectrometry (native MS) measures biomolecules under conditions that preserve most aspects of protein tertiary and quaternary structure, enabling direct characterization of large intact protein assemblies. However, native spectra derived from these assemblies are often partially obscured by low signal-to-noise as well as broad peak shapes because of residual solvation and adduction after the electrospray process. The wide peak widths together with the fact that sequential charge state series from highly charged ions are closely spaced means that native spectra containing multiple species often suffer from high degrees of peak overlap or else contain highly interleaved charge envelopes. This situation presents a challenge for peak detection, correct charge state and charge envelope assignment, and ultimately extraction of the relevant underlying mass values of the noncovalent assemblages being investigated. In this report, we describe a comprehensive algorithm developed for addressing peak detection, peak overlap, and charge state assignment in native mass spectra, called PeakSeeker. Overlapped peaks are detected by examination of the second derivative of the raw mass spectrum. Charge state distributions of the molecular species are determined by fitting linear combinations of charge envelopes to the overall experimental mass spectrum. This software is capable of deconvoluting heterogeneous, complex, and noisy native mass spectra of large protein assemblies as demonstrated by analysis of (1) synthetic mononucleosomes containing severely overlapping peaks, (2) an RNA polymerase II/α-amanitin complex with many closely interleaved ion signals, and (3) human TriC complex containing high levels of background noise. Graphical Abstract ᅟ.

A constraint logic programming approach to associate 1D and 3D structural components for large protein complexes.

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Dal Palù, Alessandro; Pontelli, Enrico; He, Jing; Lu, Yonggang

2007-01-01

The paper describes a novel framework, constructed using Constraint Logic Programming (CLP) and parallelism, to determine the association between parts of the primary sequence of a protein and alpha-helices extracted from 3D low-resolution descriptions of large protein complexes. The association is determined by extracting constraints from the 3D information, regarding length, relative position and connectivity of helices, and solving these constraints with the guidance of a secondary structure prediction algorithm. Parallelism is employed to enhance performance on large proteins. The framework provides a fast, inexpensive alternative to determine the exact tertiary structure of unknown proteins.

HKC: An Algorithm to Predict Protein Complexes in Protein-Protein Interaction Networks

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Xiaomin Wang

2011-01-01

Full Text Available With the availability of more and more genome-scale protein-protein interaction (PPI networks, research interests gradually shift to Systematic Analysis on these large data sets. A key topic is to predict protein complexes in PPI networks by identifying clusters that are densely connected within themselves but sparsely connected with the rest of the network. In this paper, we present a new topology-based algorithm, HKC, to detect protein complexes in genome-scale PPI networks. HKC mainly uses the concepts of highest k-core and cohesion to predict protein complexes by identifying overlapping clusters. The experiments on two data sets and two benchmarks show that our algorithm has relatively high F-measure and exhibits better performance compared with some other methods.

3D complex: a structural classification of protein complexes.

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Emmanuel D Levy

2006-11-01

Full Text Available Most of the proteins in a cell assemble into complexes to carry out their function. It is therefore crucial to understand the physicochemical properties as well as the evolution of interactions between proteins. The Protein Data Bank represents an important source of information for such studies, because more than half of the structures are homo- or heteromeric protein complexes. Here we propose the first hierarchical classification of whole protein complexes of known 3-D structure, based on representing their fundamental structural features as a graph. This classification provides the first overview of all the complexes in the Protein Data Bank and allows nonredundant sets to be derived at different levels of detail. This reveals that between one-half and two-thirds of known structures are multimeric, depending on the level of redundancy accepted. We also analyse the structures in terms of the topological arrangement of their subunits and find that they form a small number of arrangements compared with all theoretically possible ones. This is because most complexes contain four subunits or less, and the large majority are homomeric. In addition, there is a strong tendency for symmetry in complexes, even for heteromeric complexes. Finally, through comparison of Biological Units in the Protein Data Bank with the Protein Quaternary Structure database, we identified many possible errors in quaternary structure assignments. Our classification, available as a database and Web server at http://www.3Dcomplex.org, will be a starting point for future work aimed at understanding the structure and evolution of protein complexes.

Identifying Hierarchical and Overlapping Protein Complexes Based on Essential Protein-Protein Interactions and “Seed-Expanding” Method

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Jun Ren

2014-01-01

Full Text Available Many evidences have demonstrated that protein complexes are overlapping and hierarchically organized in PPI networks. Meanwhile, the large size of PPI network wants complex detection methods have low time complexity. Up to now, few methods can identify overlapping and hierarchical protein complexes in a PPI network quickly. In this paper, a novel method, called MCSE, is proposed based on λ-module and “seed-expanding.” First, it chooses seeds as essential PPIs or edges with high edge clustering values. Then, it identifies protein complexes by expanding each seed to a λ-module. MCSE is suitable for large PPI networks because of its low time complexity. MCSE can identify overlapping protein complexes naturally because a protein can be visited by different seeds. MCSE uses the parameter λ_th to control the range of seed expanding and can detect a hierarchical organization of protein complexes by tuning the value of λ_th. Experimental results of S. cerevisiae show that this hierarchical organization is similar to that of known complexes in MIPS database. The experimental results also show that MCSE outperforms other previous competing algorithms, such as CPM, CMC, Core-Attachment, Dpclus, HC-PIN, MCL, and NFC, in terms of the functional enrichment and matching with known protein complexes.

Dynameomics: a multi-dimensional analysis-optimized database for dynamic protein data.

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Kehl, Catherine; Simms, Andrew M; Toofanny, Rudesh D; Daggett, Valerie

2008-06-01

The Dynameomics project is our effort to characterize the native-state dynamics and folding/unfolding pathways of representatives of all known protein folds by way of molecular dynamics simulations, as described by Beck et al. (in Protein Eng. Des. Select., the first paper in this series). The data produced by these simulations are highly multidimensional in structure and multi-terabytes in size. Both of these features present significant challenges for storage, retrieval and analysis. For optimal data modeling and flexibility, we needed a platform that supported both multidimensional indices and hierarchical relationships between related types of data and that could be integrated within our data warehouse, as described in the accompanying paper directly preceding this one. For these reasons, we have chosen On-line Analytical Processing (OLAP), a multi-dimensional analysis optimized database, as an analytical platform for these data. OLAP is a mature technology in the financial sector, but it has not been used extensively for scientific analysis. Our project is further more unusual for its focus on the multidimensional and analytical capabilities of OLAP rather than its aggregation capacities. The dimensional data model and hierarchies are very flexible. The query language is concise for complex analysis and rapid data retrieval. OLAP shows great promise for the dynamic protein analysis for bioengineering and biomedical applications. In addition, OLAP may have similar potential for other scientific and engineering applications involving large and complex datasets.

Using lanthanoid complexes to phase large macromolecular assemblies

International Nuclear Information System (INIS)

Talon, Romain; Kahn, Richard; Durá, M. Asunción; Maury, Olivier; Vellieux, Frédéric M. D.; Franzetti, Bruno; Girard, Eric

2011-01-01

A lanthanoid complex, [Eu(DPA) 3 ] 3− , was used to obtain experimental phases at 4.0 Å resolution of PhTET1-12s, a large self-compartmentalized homo-dodecameric protease complex of 444 kDa. Lanthanoid ions exhibit extremely large anomalous X-ray scattering at their L III absorption edge. They are thus well suited for anomalous diffraction experiments. A novel class of lanthanoid complexes has been developed that combines the physical properties of lanthanoid atoms with functional chemical groups that allow non-covalent binding to proteins. Two structures of large multimeric proteins have already been determined by using such complexes. Here the use of the luminescent europium tris-dipicolinate complex [Eu(DPA) 3 ] 3− to solve the low-resolution structure of a 444 kDa homododecameric aminopeptidase, called PhTET1-12s from the archaea Pyrococcus horikoshii, is reported. Surprisingly, considering the low resolution of the data, the experimental electron density map is very well defined. Experimental phases obtained by using the lanthanoid complex lead to maps displaying particular structural features usually observed in higher-resolution maps. Such complexes open a new way for solving the structure of large molecular assemblies, even with low-resolution data

Decomposition of overlapping protein complexes: A graph theoretical method for analyzing static and dynamic protein associations

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Guimarães Katia S

2006-04-01

Full Text Available Abstract Background Most cellular processes are carried out by multi-protein complexes, groups of proteins that bind together to perform a specific task. Some proteins form stable complexes, while other proteins form transient associations and are part of several complexes at different stages of a cellular process. A better understanding of this higher-order organization of proteins into overlapping complexes is an important step towards unveiling functional and evolutionary mechanisms behind biological networks. Results We propose a new method for identifying and representing overlapping protein complexes (or larger units called functional groups within a protein interaction network. We develop a graph-theoretical framework that enables automatic construction of such representation. We illustrate the effectiveness of our method by applying it to TNFα/NF-κB and pheromone signaling pathways. Conclusion The proposed representation helps in understanding the transitions between functional groups and allows for tracking a protein's path through a cascade of functional groups. Therefore, depending on the nature of the network, our representation is capable of elucidating temporal relations between functional groups. Our results show that the proposed method opens a new avenue for the analysis of protein interaction networks.

Prediction of heterodimeric protein complexes from weighted protein-protein interaction networks using novel features and kernel functions.

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Peiying Ruan

Full Text Available Since many proteins express their functional activity by interacting with other proteins and forming protein complexes, it is very useful to identify sets of proteins that form complexes. For that purpose, many prediction methods for protein complexes from protein-protein interactions have been developed such as MCL, MCODE, RNSC, PCP, RRW, and NWE. These methods have dealt with only complexes with size of more than three because the methods often are based on some density of subgraphs. However, heterodimeric protein complexes that consist of two distinct proteins occupy a large part according to several comprehensive databases of known complexes. In this paper, we propose several feature space mappings from protein-protein interaction data, in which each interaction is weighted based on reliability. Furthermore, we make use of prior knowledge on protein domains to develop feature space mappings, domain composition kernel and its combination kernel with our proposed features. We perform ten-fold cross-validation computational experiments. These results suggest that our proposed kernel considerably outperforms the naive Bayes-based method, which is the best existing method for predicting heterodimeric protein complexes.

Detecting protein complexes based on a combination of topological and biological properties in protein-protein interaction network

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Pooja Sharma

2018-06-01

Full Text Available Protein complexes are known to play a major role in controlling cellular activity in a living being. Identifying complexes from raw protein protein interactions (PPIs is an important area of research. Earlier work has been limited mostly to yeast. Such protein complex identification methods, when applied to large human PPIs often give poor performance. We introduce a novel method called CSC to detect protein complexes. The method is evaluated in terms of positive predictive value, sensitivity and accuracy using the datasets of the model organism, yeast and humans. CSC outperforms several other competing algorithms for both organisms. Further, we present a framework to establish the usefulness of CSC in analyzing the influence of a given disease gene in a complex topologically as well as biologically considering eight major association factors. Keywords: Protein complex, Connectivity, Semantic similarity, Contribution

Surfactant-free purification of membrane protein complexes from bacteria: application to the staphylococcal penicillin-binding protein complex PBP2/PBP2a

International Nuclear Information System (INIS)

Paulin, Sarah; Rosado, Helena; Taylor, Peter W; Jamshad, Mohammed; Dafforn, Timothy R; Garcia-Lara, Jorge; Foster, Simon J; Galley, Nicola F; Roper, David I

2014-01-01

Surfactant-mediated removal of proteins from biomembranes invariably results in partial or complete loss of function and disassembly of multi-protein complexes. We determined the capacity of styrene-co-maleic acid (SMA) co-polymer to remove components of the cell division machinery from the membrane of drug-resistant staphylococcal cells. SMA-lipid nanoparticles solubilized FtsZ-PBP2-PBP2a complexes from intact cells, demonstrating the close physical proximity of these proteins within the lipid bilayer. Exposure of bacteria to (-)-epicatechin gallate, a polyphenolic agent that abolishes β-lactam resistance in staphylococci, disrupted the association between PBP2 and PBP2a. Thus, SMA purification provides a means to remove native integral membrane protein assemblages with minimal physical disruption and shows promise as a tool for the interrogation of molecular aspects of bacterial membrane protein structure and function. (paper)

Surfactant-free purification of membrane protein complexes from bacteria: application to the staphylococcal penicillin-binding protein complex PBP2/PBP2a

Science.gov (United States)

Paulin, Sarah; Jamshad, Mohammed; Dafforn, Timothy R.; Garcia-Lara, Jorge; Foster, Simon J.; Galley, Nicola F.; Roper, David I.; Rosado, Helena; Taylor, Peter W.

2014-07-01

Surfactant-mediated removal of proteins from biomembranes invariably results in partial or complete loss of function and disassembly of multi-protein complexes. We determined the capacity of styrene-co-maleic acid (SMA) co-polymer to remove components of the cell division machinery from the membrane of drug-resistant staphylococcal cells. SMA-lipid nanoparticles solubilized FtsZ-PBP2-PBP2a complexes from intact cells, demonstrating the close physical proximity of these proteins within the lipid bilayer. Exposure of bacteria to (-)-epicatechin gallate, a polyphenolic agent that abolishes β-lactam resistance in staphylococci, disrupted the association between PBP2 and PBP2a. Thus, SMA purification provides a means to remove native integral membrane protein assemblages with minimal physical disruption and shows promise as a tool for the interrogation of molecular aspects of bacterial membrane protein structure and function.

'Multi-epitope-targeted' immune-specific therapy for a multiple sclerosis-like disease via engineered multi-epitope protein is superior to peptides.

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Nathali Kaushansky

Full Text Available Antigen-induced peripheral tolerance is potentially one of the most efficient and specific therapeutic approaches for autoimmune diseases. Although highly effective in animal models, antigen-based strategies have not yet been translated into practicable human therapy, and several clinical trials using a single antigen or peptidic-epitope in multiple sclerosis (MS yielded disappointing results. In these clinical trials, however, the apparent complexity and dynamics of the pathogenic autoimmunity associated with MS, which result from the multiplicity of potential target antigens and "epitope spread", have not been sufficiently considered. Thus, targeting pathogenic T-cells reactive against a single antigen/epitope is unlikely to be sufficient; to be effective, immunospecific therapy to MS should logically neutralize concomitantly T-cells reactive against as many major target antigens/epitopes as possible. We investigated such "multi-epitope-targeting" approach in murine experimental autoimmune encephalomyelitis (EAE associated with a single ("classical" or multiple ("complex" anti-myelin autoreactivities, using cocktail of different encephalitogenic peptides vis-a-vis artificial multi-epitope-protein (designated Y-MSPc encompassing rationally selected MS-relevant epitopes of five major myelin antigens, as "multi-epitope-targeting" agents. Y-MSPc was superior to peptide(s in concomitantly downregulating pathogenic T-cells reactive against multiple myelin antigens/epitopes, via inducing more effective, longer lasting peripheral regulatory mechanisms (cytokine shift, anergy, and Foxp3+ CTLA4+ regulatory T-cells. Y-MSPc was also consistently more effective than the disease-inducing single peptide or peptide cocktail, not only in suppressing the development of "classical" or "complex EAE" or ameliorating ongoing disease, but most importantly, in reversing chronic EAE. Overall, our data emphasize that a "multi-epitope-targeting" strategy is required for

NMR approaches in structure-based lead discovery: recent developments and new frontiers for targeting multi-protein complexes.

Science.gov (United States)

Dias, David M; Ciulli, Alessio

2014-01-01

Nuclear magnetic resonance (NMR) spectroscopy is a pivotal method for structure-based and fragment-based lead discovery because it is one of the most robust techniques to provide information on protein structure, dynamics and interaction at an atomic level in solution. Nowadays, in most ligand screening cascades, NMR-based methods are applied to identify and structurally validate small molecule binding. These can be high-throughput and are often used synergistically with other biophysical assays. Here, we describe current state-of-the-art in the portfolio of available NMR-based experiments that are used to aid early-stage lead discovery. We then focus on multi-protein complexes as targets and how NMR spectroscopy allows studying of interactions within the high molecular weight assemblies that make up a vast fraction of the yet untargeted proteome. Finally, we give our perspective on how currently available methods could build an improved strategy for drug discovery against such challenging targets. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Drosophila protein interaction map (DPiM): a paradigm for metazoan protein complex interactions.

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Guruharsha, K G; Obar, Robert A; Mintseris, Julian; Aishwarya, K; Krishnan, R T; Vijayraghavan, K; Artavanis-Tsakonas, Spyros

2012-01-01

Proteins perform essential cellular functions as part of protein complexes, often in conjunction with RNA, DNA, metabolites and other small molecules. The genome encodes thousands of proteins but not all of them are expressed in every cell type; and expressed proteins are not active at all times. Such diversity of protein expression and function accounts for the level of biological intricacy seen in nature. Defining protein-protein interactions in protein complexes, and establishing the when, what and where of potential interactions, is therefore crucial to understanding the cellular function of any protein-especially those that have not been well studied by traditional molecular genetic approaches. We generated a large-scale resource of affinity-tagged expression-ready clones and used co-affinity purification combined with tandem mass-spectrometry to identify protein partners of nearly 5,000 Drosophila melanogaster proteins. The resulting protein complex "map" provided a blueprint of metazoan protein complex organization. Here we describe how the map has provided valuable insights into protein function in addition to generating hundreds of testable hypotheses. We also discuss recent technological advancements that will be critical in addressing the next generation of questions arising from the map.

Multi-signal sedimentation velocity analysis with mass conservation for determining the stoichiometry of protein complexes.

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Chad A Brautigam

Full Text Available Multi-signal sedimentation velocity analytical ultracentrifugation (MSSV is a powerful tool for the determination of the number, stoichiometry, and hydrodynamic shape of reversible protein complexes in two- and three-component systems. In this method, the evolution of sedimentation profiles of macromolecular mixtures is recorded simultaneously using multiple absorbance and refractive index signals and globally transformed into both spectrally and diffusion-deconvoluted component sedimentation coefficient distributions. For reactions with complex lifetimes comparable to the time-scale of sedimentation, MSSV reveals the number and stoichiometry of co-existing complexes. For systems with short complex lifetimes, MSSV reveals the composition of the reaction boundary of the coupled reaction/migration process, which we show here may be used to directly determine an association constant. A prerequisite for MSSV is that the interacting components are spectrally distinguishable, which may be a result, for example, of extrinsic chromophores or of different abundances of aromatic amino acids contributing to the UV absorbance. For interacting components that are spectrally poorly resolved, here we introduce a method for additional regularization of the spectral deconvolution by exploiting approximate knowledge of the total loading concentrations. While this novel mass conservation principle does not discriminate contributions to different species, it can be effectively combined with constraints in the sedimentation coefficient range of uncomplexed species. We show in theory, computer simulations, and experiment, how mass conservation MSSV as implemented in SEDPHAT can enhance or even substitute for the spectral discrimination of components. This should broaden the applicability of MSSV to the analysis of the composition of reversible macromolecular complexes.

Modeling complexes of modeled proteins.

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Anishchenko, Ivan; Kundrotas, Petras J; Vakser, Ilya A

2017-03-01

Structural characterization of proteins is essential for understanding life processes at the molecular level. However, only a fraction of known proteins have experimentally determined structures. This fraction is even smaller for protein-protein complexes. Thus, structural modeling of protein-protein interactions (docking) primarily has to rely on modeled structures of the individual proteins, which typically are less accurate than the experimentally determined ones. Such "double" modeling is the Grand Challenge of structural reconstruction of the interactome. Yet it remains so far largely untested in a systematic way. We present a comprehensive validation of template-based and free docking on a set of 165 complexes, where each protein model has six levels of structural accuracy, from 1 to 6 Å C α RMSD. Many template-based docking predictions fall into acceptable quality category, according to the CAPRI criteria, even for highly inaccurate proteins (5-6 Å RMSD), although the number of such models (and, consequently, the docking success rate) drops significantly for models with RMSD > 4 Å. The results show that the existing docking methodologies can be successfully applied to protein models with a broad range of structural accuracy, and the template-based docking is much less sensitive to inaccuracies of protein models than the free docking. Proteins 2017; 85:470-478. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Recovering protein-protein and domain-domain interactions from aggregation of IP-MS proteomics of coregulator complexes.

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Amin R Mazloom

2011-12-01

Full Text Available Coregulator proteins (CoRegs are part of multi-protein complexes that transiently assemble with transcription factors and chromatin modifiers to regulate gene expression. In this study we analyzed data from 3,290 immuno-precipitations (IP followed by mass spectrometry (MS applied to human cell lines aimed at identifying CoRegs complexes. Using the semi-quantitative spectral counts, we scored binary protein-protein and domain-domain associations with several equations. Unlike previous applications, our methods scored prey-prey protein-protein interactions regardless of the baits used. We also predicted domain-domain interactions underlying predicted protein-protein interactions. The quality of predicted protein-protein and domain-domain interactions was evaluated using known binary interactions from the literature, whereas one protein-protein interaction, between STRN and CTTNBP2NL, was validated experimentally; and one domain-domain interaction, between the HEAT domain of PPP2R1A and the Pkinase domain of STK25, was validated using molecular docking simulations. The scoring schemes presented here recovered known, and predicted many new, complexes, protein-protein, and domain-domain interactions. The networks that resulted from the predictions are provided as a web-based interactive application at http://maayanlab.net/HT-IP-MS-2-PPI-DDI/.

Simulating evolution of protein complexes through gene duplication and co-option.

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Haarsma, Loren; Nelesen, Serita; VanAndel, Ethan; Lamine, James; VandeHaar, Peter

2016-06-21

We present a model of the evolution of protein complexes with novel functions through gene duplication, mutation, and co-option. Under a wide variety of input parameters, digital organisms evolve complexes of 2-5 bound proteins which have novel functions but whose component proteins are not independently functional. Evolution of complexes with novel functions happens more quickly as gene duplication rates increase, point mutation rates increase, protein complex functional probability increases, protein complex functional strength increases, and protein family size decreases. Evolution of complexity is inhibited when the metabolic costs of making proteins exceeds the fitness gain of having functional proteins, or when point mutation rates get so large the functional proteins undergo deleterious mutations faster than new functional complexes can evolve. Copyright © 2016 Elsevier Ltd. All rights reserved.

MicroProtein-mediated recruitment of CONSTANS into a TOPLESS trimeric complex represses flowering in Arabidopsis

DEFF Research Database (Denmark)

Graeff, Moritz; Straub, Daniel; Eguen, Tenai E.

2016-01-01

MicroProteins are short, single domain proteins that act by sequestering larger, multi-domain proteins into non-functional complexes. MicroProteins have been identified in plants and animals, where they are mostly involved in the regulation of developmental processes. Here we show that two...

Nanoscale Dewetting Transition in Protein Complex Folding

Science.gov (United States)

Hua, Lan; Huang, Xuhui; Liu, Pu; Zhou, Ruhong; Berne, Bruce J.

2011-01-01

In a previous study, a surprising drying transition was observed to take place inside the nanoscale hydrophobic channel in the tetramer of the protein melittin. The goal of this paper is to determine if there are other protein complexes capable of displaying a dewetting transition during their final stage of folding. We searched the entire protein data bank (PDB) for all possible candidates, including protein tetramers, dimers, and two-domain proteins, and then performed the molecular dynamics (MD) simulations on the top candidates identified by a simple hydrophobic scoring function based on aligned hydrophobic surface areas. Our large scale MD simulations found several more proteins, including three tetramers, six dimers, and two two-domain proteins, which display a nanoscale dewetting transition in their final stage of folding. Even though the scoring function alone is not sufficient (i.e., a high score is necessary but not sufficient) in identifying the dewetting candidates, it does provide useful insights into the features of complex interfaces needed for dewetting. All top candidates have two features in common: (1) large aligned (matched) hydrophobic areas between two corresponding surfaces, and (2) large connected hydrophobic areas on the same surface. We have also studied the effect on dewetting of different water models and different treatments of the long-range electrostatic interactions (cutoff vs PME), and found the dewetting phenomena is fairly robust. This work presents a few proteins other than melittin tetramer for further experimental studies of the role of dewetting in the end stages of protein folding. PMID:17608515

Systematic identification of protein complexes in Saccharomyces cerevisiae by mass spectrometry

DEFF Research Database (Denmark)

Ho, Yuen; Gruhler, Albrecht; Heilbut, Adrian

2002-01-01

The recent abundance of genome sequence data has brought an urgent need for systematic proteomics to decipher the encoded protein networks that dictate cellular function. To date, generation of large-scale protein-protein interaction maps has relied on the yeast two-hybrid system, which detects...... as a test case, an example of this approach, which we term high-throughput mass spectrometric protein complex identification (HMS-PCI). Beginning with 10% of predicted yeast proteins as baits, we detected 3,617 associated proteins covering 25% of the yeast proteome. Numerous protein complexes were...... identified, including many new interactions in various signalling pathways and in the DNA damage response. Comparison of the HMS-PCI data set with interactions reported in the literature revealed an average threefold higher success rate in detection of known complexes compared with large-scale two...

Construction of ontology augmented networks for protein complex prediction.

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Zhang, Yijia; Lin, Hongfei; Yang, Zhihao; Wang, Jian

2013-01-01

Protein complexes are of great importance in understanding the principles of cellular organization and function. The increase in available protein-protein interaction data, gene ontology and other resources make it possible to develop computational methods for protein complex prediction. Most existing methods focus mainly on the topological structure of protein-protein interaction networks, and largely ignore the gene ontology annotation information. In this article, we constructed ontology augmented networks with protein-protein interaction data and gene ontology, which effectively unified the topological structure of protein-protein interaction networks and the similarity of gene ontology annotations into unified distance measures. After constructing ontology augmented networks, a novel method (clustering based on ontology augmented networks) was proposed to predict protein complexes, which was capable of taking into account the topological structure of the protein-protein interaction network, as well as the similarity of gene ontology annotations. Our method was applied to two different yeast protein-protein interaction datasets and predicted many well-known complexes. The experimental results showed that (i) ontology augmented networks and the unified distance measure can effectively combine the structure closeness and gene ontology annotation similarity; (ii) our method is valuable in predicting protein complexes and has higher F1 and accuracy compared to other competing methods.

Searching for the Pareto frontier in multi-objective protein design.

Science.gov (United States)

Nanda, Vikas; Belure, Sandeep V; Shir, Ofer M

2017-08-01

The goal of protein engineering and design is to identify sequences that adopt three-dimensional structures of desired function. Often, this is treated as a single-objective optimization problem, identifying the sequence-structure solution with the lowest computed free energy of folding. However, many design problems are multi-state, multi-specificity, or otherwise require concurrent optimization of multiple objectives. There may be tradeoffs among objectives, where improving one feature requires compromising another. The challenge lies in determining solutions that are part of the Pareto optimal set-designs where no further improvement can be achieved in any of the objectives without degrading one of the others. Pareto optimality problems are found in all areas of study, from economics to engineering to biology, and computational methods have been developed specifically to identify the Pareto frontier. We review progress in multi-objective protein design, the development of Pareto optimization methods, and present a specific case study using multi-objective optimization methods to model the tradeoff between three parameters, stability, specificity, and complexity, of a set of interacting synthetic collagen peptides.

LC-MS/MS as an alternative for SDS-PAGE in blue native analysis of protein complexes.

NARCIS (Netherlands)

Wessels, H.C.T.; Vogel, R.O.; Heuvel, L.P.W.J. van den; Smeitink, J.A.M.; Rodenburg, R.J.T.; Nijtmans, L.G.J.; Farhoud, M.H.

2009-01-01

Two-dimensional blue native/SDS-PAGE is widely applied to investigate native protein-protein interactions, particularly those within membrane multi-protein complexes. MS has enabled the application of this approach at the proteome scale, typically by analysis of picked protein spots. Here, we

A multi-protein receptor-ligand complex underlies combinatorial dendrite guidance choices in C. elegans

Science.gov (United States)

Zou, Wei; Shen, Ao; Dong, Xintong; Tugizova, Madina; Xiang, Yang K; Shen, Kang

2016-01-01

Ligand receptor interactions instruct axon guidance during development. How dendrites are guided to specific targets is less understood. The C. elegans PVD sensory neuron innervates muscle-skin interface with its elaborate dendritic branches. Here, we found that LECT-2, the ortholog of leukocyte cell-derived chemotaxin-2 (LECT2), is secreted from the muscles and required for muscle innervation by PVD. Mosaic analyses showed that LECT-2 acted locally to guide the growth of terminal branches. Ectopic expression of LECT-2 from seam cells is sufficient to redirect the PVD dendrites onto seam cells. LECT-2 functions in a multi-protein receptor-ligand complex that also contains two transmembrane ligands on the skin, SAX-7/L1CAM and MNR-1, and the neuronal transmembrane receptor DMA-1. LECT-2 greatly enhances the binding between SAX-7, MNR-1 and DMA-1. The activation of DMA-1 strictly requires all three ligands, which establishes a combinatorial code to precisely target and pattern dendritic arbors. DOI: http://dx.doi.org/10.7554/eLife.18345.001 PMID:27705746

The coat protein complex II, COPII, protein Sec13 directly interacts with presenilin-1

International Nuclear Information System (INIS)

Nielsen, Anders Lade

2009-01-01

Mutations in the human gene encoding presenilin-1, PS1, account for most cases of early-onset familial Alzheimer's disease. PS1 has nine transmembrane domains and a large loop orientated towards the cytoplasm. PS1 locates to cellular compartments as endoplasmic reticulum (ER), Golgi apparatus, vesicular structures, and plasma membrane, and is an integral member of γ-secretase, a protein protease complex with specificity for intra-membranous cleavage of substrates such as β-amyloid precursor protein. Here, an interaction between PS1 and the Sec13 protein is described. Sec13 takes part in coat protein complex II, COPII, vesicular trafficking, nuclear pore function, and ER directed protein sequestering and degradation control. The interaction maps to the N-terminal part of the large hydrophilic PS1 loop and the first of the six WD40-repeats present in Sec13. The identified Sec13 interaction to PS1 is a new candidate interaction for linking PS1 to secretory and protein degrading vesicular circuits.

The coat protein complex II, COPII, protein Sec13 directly interacts with presenilin-1

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Nielsen, Anders Lade, E-mail: aln@humgen.au.dk [Department of Human Genetics, The Bartholin Building, University of Aarhus, DK-8000 Aarhus C (Denmark)

2009-10-23

Mutations in the human gene encoding presenilin-1, PS1, account for most cases of early-onset familial Alzheimer's disease. PS1 has nine transmembrane domains and a large loop orientated towards the cytoplasm. PS1 locates to cellular compartments as endoplasmic reticulum (ER), Golgi apparatus, vesicular structures, and plasma membrane, and is an integral member of {gamma}-secretase, a protein protease complex with specificity for intra-membranous cleavage of substrates such as {beta}-amyloid precursor protein. Here, an interaction between PS1 and the Sec13 protein is described. Sec13 takes part in coat protein complex II, COPII, vesicular trafficking, nuclear pore function, and ER directed protein sequestering and degradation control. The interaction maps to the N-terminal part of the large hydrophilic PS1 loop and the first of the six WD40-repeats present in Sec13. The identified Sec13 interaction to PS1 is a new candidate interaction for linking PS1 to secretory and protein degrading vesicular circuits.

Structuring and assessing large and complex decision problems using MCDA

DEFF Research Database (Denmark)

Barfod, Michael Bruhn

This paper presents an approach for the structuring and assessing of large and complex decision problems using multi-criteria decision analysis (MCDA). The MCDA problem is structured in a decision tree and assessed using the REMBRANDT technique featuring a procedure for limiting the number of pair...

Complex mixture analysis of peptides using LC/LC-MS/MS and data-dependent protein identification

International Nuclear Information System (INIS)

Wasinger, V.; Corthals, G.

2001-01-01

The comprehensive identification of proteins within complex solutions by mass-spectrometry largely depends on the sensitivity, resolving power and sampling efficiency of the technology. An integrated orthogonal approach using Strong Cation Exchange-Reverse Phase-MS/MS (SCX-RP-MS/MS) was used to evaluate the data-dependent Collision Induced Dissociation (CID) of yeast peptides. Reverse phase gradient times of 4, 10. 30, 90, and 180 minutes allowed the identification of hundreds of proteins in a nearly automated fashion from nuclear, membrane, and cytosolic distributions. Many proteins from typically difficult to resolve regions of two-dimensional gels, such as >100kDa, > pI 9.0 and Codon Adaptation Index < 0.2, were also identified using this multi-dimensional separation technology. Few low mass proteins (<10kDa) were identified. The impact of scan-range and duty-cycle on CID of peptides will be discussed

Analysis of protein-protein docking decoys using interaction fingerprints: application to the reconstruction of CaM-ligand complexes

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Uchikoga Nobuyuki

2010-05-01

Full Text Available Abstract Background Protein-protein docking for proteins with large conformational changes was analyzed by using interaction fingerprints, one of the scales for measuring similarities among complex structures, utilized especially for searching near-native protein-ligand or protein-protein complex structures. Here, we have proposed a combined method for analyzing protein-protein docking by taking large conformational changes into consideration. This combined method consists of ensemble soft docking with multiple protein structures, refinement of complexes, and cluster analysis using interaction fingerprints and energy profiles. Results To test for the applicability of this combined method, various CaM-ligand complexes were reconstructed from the NMR structures of unbound CaM. For the purpose of reconstruction, we used three known CaM-ligands, namely, the CaM-binding peptides of cyclic nucleotide gateway (CNG, CaM kinase kinase (CaMKK and the plasma membrane Ca2+ ATPase pump (PMCA, and thirty-one structurally diverse CaM conformations. For each ligand, 62000 CaM-ligand complexes were generated in the docking step and the relationship between their energy profiles and structural similarities to the native complex were analyzed using interaction fingerprint and RMSD. Near-native clusters were obtained in the case of CNG and CaMKK. Conclusions The interaction fingerprint method discriminated near-native structures better than the RMSD method in cluster analysis. We showed that a combined method that includes the interaction fingerprint is very useful for protein-protein docking analysis of certain cases.

Design of multi-specificity in protein interfaces.

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Elisabeth L Humphris

2007-08-01

Full Text Available Interactions in protein networks may place constraints on protein interface sequences to maintain correct and avoid unwanted interactions. Here we describe a "multi-constraint" protein design protocol to predict sequences optimized for multiple criteria, such as maintaining sets of interactions, and apply it to characterize the mechanism and extent to which 20 multi-specific proteins are constrained by binding to multiple partners. We find that multi-specific binding is accommodated by at least two distinct patterns. In the simplest case, all partners share key interactions, and sequences optimized for binding to either single or multiple partners recover only a subset of native amino acid residues as optimal. More interestingly, for signaling interfaces functioning as network "hubs," we identify a different, "multi-faceted" mode, where each binding partner prefers its own subset of wild-type residues within the promiscuous binding site. Here, integration of preferences across all partners results in sequences much more "native-like" than seen in optimization for any single binding partner alone, suggesting these interfaces are substantially optimized for multi-specificity. The two strategies make distinct predictions for interface evolution and design. Shared interfaces may be better small molecule targets, whereas multi-faceted interactions may be more "designable" for altered specificity patterns. The computational methodology presented here is generalizable for examining how naturally occurring protein sequences have been selected to satisfy a variety of positive and negative constraints, as well as for rationally designing proteins to have desired patterns of altered specificity.

Combining biophysical methods for the analysis of protein complex stoichiometry and affinity in SEDPHAT

International Nuclear Information System (INIS)

Zhao, Huaying; Schuck, Peter

2015-01-01

Global multi-method analysis for protein interactions (GMMA) can increase the precision and complexity of binding studies for the determination of the stoichiometry, affinity and cooperativity of multi-site interactions. The principles and recent developments of biophysical solution methods implemented for GMMA in the software SEDPHAT are reviewed, their complementarity in GMMA is described and a new GMMA simulation tool set in SEDPHAT is presented. Reversible macromolecular interactions are ubiquitous in signal transduction pathways, often forming dynamic multi-protein complexes with three or more components. Multivalent binding and cooperativity in these complexes are often key motifs of their biological mechanisms. Traditional solution biophysical techniques for characterizing the binding and cooperativity are very limited in the number of states that can be resolved. A global multi-method analysis (GMMA) approach has recently been introduced that can leverage the strengths and the different observables of different techniques to improve the accuracy of the resulting binding parameters and to facilitate the study of multi-component systems and multi-site interactions. Here, GMMA is described in the software SEDPHAT for the analysis of data from isothermal titration calorimetry, surface plasmon resonance or other biosensing, analytical ultracentrifugation, fluorescence anisotropy and various other spectroscopic and thermodynamic techniques. The basic principles of these techniques are reviewed and recent advances in view of their particular strengths in the context of GMMA are described. Furthermore, a new feature in SEDPHAT is introduced for the simulation of multi-method data. In combination with specific statistical tools for GMMA in SEDPHAT, simulations can be a valuable step in the experimental design

Principles of assembly reveal a periodic table of protein complexes.

Science.gov (United States)

Ahnert, Sebastian E; Marsh, Joseph A; Hernández, Helena; Robinson, Carol V; Teichmann, Sarah A

2015-12-11

Structural insights into protein complexes have had a broad impact on our understanding of biological function and evolution. In this work, we sought a comprehensive understanding of the general principles underlying quaternary structure organization in protein complexes. We first examined the fundamental steps by which protein complexes can assemble, using experimental and structure-based characterization of assembly pathways. Most assembly transitions can be classified into three basic types, which can then be used to exhaustively enumerate a large set of possible quaternary structure topologies. These topologies, which include the vast majority of observed protein complex structures, enable a natural organization of protein complexes into a periodic table. On the basis of this table, we can accurately predict the expected frequencies of quaternary structure topologies, including those not yet observed. These results have important implications for quaternary structure prediction, modeling, and engineering. Copyright © 2015, American Association for the Advancement of Science.

Fanconi anemia group A and C double-mutant mice: functional evidence for a multi-protein Fanconi anemia complex.

Science.gov (United States)

Noll, Meenakshi; Battaile, Kevin P; Bateman, Raynard; Lax, Timothy P; Rathbun, Keany; Reifsteck, Carol; Bagby, Grover; Finegold, Milton; Olson, Susan; Grompe, Markus

2002-07-01

Fanconi anemia (FA) is a genetically heterogeneous disorder associated with defects in at least eight genes. The biochemical function(s) of the FA proteins are unknown, but together they define the FA pathway, which is involved in cellular responses to DNA damage and in other cellular processes. It is currently unknown whether all FA proteins are involved in controlling a single function or whether some of the FA proteins have additional roles. The aim of this study was 1) to determine whether the FA group A and group C genes have identical or partially distinct functions, and 2) to have a better model for human FA. We generated mice with a targeted mutation in fanca and crossed them with fancc disrupted animals. Several phenotypes including sensitivity to DNA cross linkers and ionizing radiation, hematopoietic colony growth, and germ cell loss were analyzed in fanca-/-, fancc-/-, fanca/fancc double -/-, and controls. Fibroblast cells and hematopoietic precursors from fanca/fancc double-mutant mice were not more sensitive to MMC than those of either single mutant. fanca/fancc double mutants had no evidence for an additive phenotype at the cellular or organismal level. These results support a model where both FANCA and FANCC are part of a multi-protein nuclear FA complex with identical function in cellular responses to DNA damage and germ cell survival.

Investigating the Role of Large-Scale Domain Dynamics in Protein-Protein Interactions.

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Delaforge, Elise; Milles, Sigrid; Huang, Jie-Rong; Bouvier, Denis; Jensen, Malene Ringkjøbing; Sattler, Michael; Hart, Darren J; Blackledge, Martin

2016-01-01

Intrinsically disordered linkers provide multi-domain proteins with degrees of conformational freedom that are often essential for function. These highly dynamic assemblies represent a significant fraction of all proteomes, and deciphering the physical basis of their interactions represents a considerable challenge. Here we describe the difficulties associated with mapping the large-scale domain dynamics and describe two recent examples where solution state methods, in particular NMR spectroscopy, are used to investigate conformational exchange on very different timescales.

Prediction of Protein-Protein Interactions Related to Protein Complexes Based on Protein Interaction Networks

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Peng Liu

2015-01-01

Full Text Available A method for predicting protein-protein interactions based on detected protein complexes is proposed to repair deficient interactions derived from high-throughput biological experiments. Protein complexes are pruned and decomposed into small parts based on the adaptive k-cores method to predict protein-protein interactions associated with the complexes. The proposed method is adaptive to protein complexes with different structure, number, and size of nodes in a protein-protein interaction network. Based on different complex sets detected by various algorithms, we can obtain different prediction sets of protein-protein interactions. The reliability of the predicted interaction sets is proved by using estimations with statistical tests and direct confirmation of the biological data. In comparison with the approaches which predict the interactions based on the cliques, the overlap of the predictions is small. Similarly, the overlaps among the predicted sets of interactions derived from various complex sets are also small. Thus, every predicted set of interactions may complement and improve the quality of the original network data. Meanwhile, the predictions from the proposed method replenish protein-protein interactions associated with protein complexes using only the network topology.

Membrane-localized extra-large G proteins and Gbg of the heterotrimeric G proteins form functional complexes engaged in plant immunity in Arabidopsis.

Science.gov (United States)

Maruta, Natsumi; Trusov, Yuri; Brenya, Eric; Parekh, Urvi; Botella, José Ramón

2015-03-01

In animals, heterotrimeric G proteins, comprising Ga, Gb, and Gg subunits, are molecular switches whose function tightly depends on Ga and Gbg interaction. Intriguingly, in Arabidopsis (Arabidopsis thaliana), multiple defense responses involve Gbg, but not Ga. We report here that the Gbg dimer directly partners with extra-large G proteins (XLGs) to mediate plant immunity. Arabidopsis mutants deficient in XLGs, Gb, and Gg are similarly compromised in several pathogen defense responses, including disease development and production of reactive oxygen species. Genetic analysis of double, triple, and quadruple mutants confirmed that XLGs and Gbg functionally interact in the same defense signaling pathways. In addition, mutations in XLG2 suppressed the seedling lethal and cell death phenotypes of BRASSINOSTEROID INSENSITIVE1-associated receptor kinase1-interacting receptor-like kinase1 mutants in an identical way as reported for Arabidopsis Gb-deficient mutants. Yeast (Saccharomyces cerevisiae) three-hybrid and bimolecular fluorescent complementation assays revealed that XLG2 physically interacts with all three possible Gbg dimers at the plasma membrane. Phylogenetic analysis indicated a close relationship between XLGs and plant Ga subunits, placing the divergence point at the dawn of land plant evolution. Based on these findings, we conclude that XLGs form functional complexes with Gbg dimers, although the mechanism of action of these complexes, including activation/deactivation, must be radically different form the one used by the canonical Ga subunit and are not likely to share the same receptors. Accordingly, XLGs expand the repertoire of heterotrimeric G proteins in plants and reveal a higher level of diversity in heterotrimeric G protein signaling.

Assembly of the novel five-component apicomplexan multi-aminoacyl-tRNA synthetase complex is driven by the hybrid scaffold protein Tg-p43.

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Jason M van Rooyen

Full Text Available In Toxoplasma gondii, as in other eukaryotes, a subset of the amino-acyl-tRNA synthetases are arranged into an abundant cytoplasmic multi-aminoacyl-tRNA synthetase (MARS complex. Through a series of genetic pull-down assays, we have identified the enzymes of this complex as: methionyl-, glutaminyl-, glutamyl-, and tyrosyl-tRNA synthetases, and we show that the N-terminal GST-like domain of a partially disordered hybrid scaffold protein, Tg-p43, is sufficient for assembly of the intact complex. Our gel filtration studies revealed significant heterogeneity in the size and composition of isolated MARS complexes. By targeting the tyrosyl-tRNA synthetases subunit, which was found exclusively in the complete 1 MDa complex, we were able to directly visualize MARS particles in the electron microscope. Image analyses of the negative stain data revealed the observed heterogeneity and instability of these complexes to be driven by the intrinsic flexibility of the domain arrangements within the MARS complex. These studies provide unique insights into the assembly of these ubiquitous but poorly understood eukaryotic complexes.

Detection of protein complex from protein-protein interaction network using Markov clustering

International Nuclear Information System (INIS)

Ochieng, P J; Kusuma, W A; Haryanto, T

2017-01-01

Detection of complexes, or groups of functionally related proteins, is an important challenge while analysing biological networks. However, existing algorithms to identify protein complexes are insufficient when applied to dense networks of experimentally derived interaction data. Therefore, we introduced a graph clustering method based on Markov clustering algorithm to identify protein complex within highly interconnected protein-protein interaction networks. Protein-protein interaction network was first constructed to develop geometrical network, the network was then partitioned using Markov clustering to detect protein complexes. The interest of the proposed method was illustrated by its application to Human Proteins associated to type II diabetes mellitus. Flow simulation of MCL algorithm was initially performed and topological properties of the resultant network were analysed for detection of the protein complex. The results indicated the proposed method successfully detect an overall of 34 complexes with 11 complexes consisting of overlapping modules and 20 non-overlapping modules. The major complex consisted of 102 proteins and 521 interactions with cluster modularity and density of 0.745 and 0.101 respectively. The comparison analysis revealed MCL out perform AP, MCODE and SCPS algorithms with high clustering coefficient (0.751) network density and modularity index (0.630). This demonstrated MCL was the most reliable and efficient graph clustering algorithm for detection of protein complexes from PPI networks. (paper)

Large branched self-assembled DNA complexes

International Nuclear Information System (INIS)

Tosch, Paul; Waelti, Christoph; Middelberg, Anton P J; Davies, A Giles

2007-01-01

Many biological molecules have been demonstrated to self-assemble into complex structures and networks by using their very efficient and selective molecular recognition processes. The use of biological molecules as scaffolds for the construction of functional devices by self-assembling nanoscale complexes onto the scaffolds has recently attracted significant attention and many different applications in this field have emerged. In particular DNA, owing to its inherent sophisticated self-organization and molecular recognition properties, has served widely as a scaffold for various nanotechnological self-assembly applications, with metallic and semiconducting nanoparticles, proteins, macromolecular complexes, inter alia, being assembled onto designed DNA scaffolds. Such scaffolds may typically contain multiple branch-points and comprise a number of DNA molecules selfassembled into the desired configuration. Previously, several studies have used synthetic methods to produce the constituent DNA of the scaffolds, but this typically constrains the size of the complexes. For applications that require larger self-assembling DNA complexes, several tens of nanometers or more, other techniques need to be employed. In this article, we discuss a generic technique to generate large branched DNA macromolecular complexes

Development of a Multi-Point Quantitation Method to Simultaneously Measure Enzymatic and Structural Components of the Clostridium thermocellum Cellulosome Protein Complex

Energy Technology Data Exchange (ETDEWEB)

Dykstra, Andrew B [ORNL; St. Brice, Lois [Dartmouth College; Rodriguez, Jr., Miguel [ORNL; Raman, Babu [ORNL; Izquierdo, Javier [ORNL; Cook, Kelsey [ORNL; Lynd, Lee R [ORNL; Hettich, Robert {Bob} L [ORNL

2014-01-01

Clostridium thermocellum has emerged as a leading bioenergy-relevant microbe due to its ability to solubilize cellulose into carbohydrates, mediated by multi-component membrane-attached complexes termed cellulosomes. To probe microbial cellulose utilization rates, it is desirable to be able to measure the concentrations of saccharolytic enzymes and estimate the total amount of cellulosome present on a mass basis. Current cellulase determination methodologies involve labor-intensive purification procedures and only allow for indirect determination of abundance. We have developed a method using multiple reaction monitoring (MRM-MS) to simultaneously quantitate both enzymatic and structural components of the cellulosome protein complex in samples ranging in complexity from purified cellulosomes to whole cell lysates, as an alternative to a previously-developed enzyme-linked immunosorbent assay (ELISA) method of cellulosome quantitation. The precision of the cellulosome mass concentration in technical replicates is better than 5% relative standard deviation for all samples, indicating high precision for determination of the mass concentration of cellulosome components.

Comprehensive inventory of protein complexes in the Protein Data Bank from consistent classification of interfaces

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Gorin Andrey A

2008-05-01

Full Text Available Abstract Background Protein-protein interactions are ubiquitous and essential for all cellular processes. High-resolution X-ray crystallographic structures of protein complexes can reveal the details of their function and provide a basis for many computational and experimental approaches. Differentiation between biological and non-biological contacts and reconstruction of the intact complex is a challenging computational problem. A successful solution can provide additional insights into the fundamental principles of biological recognition and reduce errors in many algorithms and databases utilizing interaction information extracted from the Protein Data Bank (PDB. Results We have developed a method for identifying protein complexes in the PDB X-ray structures by a four step procedure: (1 comprehensively collecting all protein-protein interfaces; (2 clustering similar protein-protein interfaces together; (3 estimating the probability that each cluster is relevant based on a diverse set of properties; and (4 combining these scores for each PDB entry in order to predict the complex structure. The resulting clusters of biologically relevant interfaces provide a reliable catalog of evolutionary conserved protein-protein interactions. These interfaces, as well as the predicted protein complexes, are available from the Protein Interface Server (PInS website (see Availability and requirements section. Conclusion Our method demonstrates an almost two-fold reduction of the annotation error rate as evaluated on a large benchmark set of complexes validated from the literature. We also estimate relative contributions of each interface property to the accurate discrimination of biologically relevant interfaces and discuss possible directions for further improving the prediction method.

Investigating the Role of Large-Scale Domain Dynamics in Protein-Protein Interactions

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Elise Delaforge

2016-09-01

Full Text Available Intrinsically disordered linkers provide multi-domain proteins with degrees of conformational freedom that are often essential for function. These highly dynamic assemblies represent a significant fraction of all proteomes, and deciphering the physical basis of their interactions represents a considerable challenge. Here we describe the difficulties associated with mapping the large-scale domain dynamics and describe two recent examples where solution state methods, in particular NMR spectroscopy, are used to investigate conformational exchange on very different timescales.

CPdock: the complementarity plot for docking of proteins: implementing multi-dielectric continuum electrostatics.

Science.gov (United States)

Basu, Sankar

2017-12-07

The complementarity plot (CP) is an established validation tool for protein structures, applicable to both globular proteins (folding) as well as protein-protein complexes (binding). It computes the shape and electrostatic complementarities (S m , E m ) for amino acid side-chains buried within the protein interior or interface and plots them in a two-dimensional plot having knowledge-based probabilistic quality estimates for the residues as well as for the whole structure. The current report essentially presents an upgraded version of the plot with the implementation of the advanced multi-dielectric functionality (as in Delphi version 6.2 or higher) in the computation of electrostatic complementarity to make the validation tool physico-chemically more realistic. The two methods (single- and multi-dielectric) agree decently in their resultant E m values, and hence, provisions for both methods have been kept in the software suite. So to speak, the global electrostatic balance within a well-folded protein and/or a well-packed interface seems only marginally perturbed by the choice of different internal dielectric values. However, both from theoretical as well as practical grounds, the more advanced multi-dielectric version of the plot is certainly recommended for potentially producing more reliable results. The report also presents a new methodology and a variant plot, namely CP dock , based on the same principles of complementarity specifically designed to be used in the docking of proteins. The efficacy of the method to discriminate between good and bad docked protein complexes has been tested on a recent state-of-the-art docking benchmark. The results unambiguously indicate that CP dock can indeed be effective in the initial screening phase of a docking scoring pipeline before going into more sophisticated and computationally expensive scoring functions. CP dock has been made available at https://github.com/nemo8130/CPdock . Graphical Abstract An example showing

'Fractional recovery' analysis of a presynaptic synaptotagmin 1-anchored endocytic protein complex.

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Rajesh Khanna

Full Text Available BACKGROUND: The integral synaptic vesicle protein and putative calcium sensor, synaptotagmin 1 (STG, has also been implicated in synaptic vesicle (SV recovery. However, proteins with which STG interacts during SV endocytosis remain poorly understood. We have isolated an STG-associated endocytic complex (SAE from presynaptic nerve terminals and have used a novel fractional recovery (FR assay based on electrostatic dissociation to identify SAE components and map the complex structure. The location of SAE in the presynaptic terminal was determined by high-resolution quantitative immunocytochemistry at the chick ciliary ganglion giant calyx-type synapse. METHODOLOGY/PRINCIPLE FINDINGS: The first step in FR analysis was to immunoprecipitate (IP the complex with an antibody against one protein component (the IP-protein. The immobilized complex was then exposed to a high salt (1150 mM stress-test that caused shedding of co-immunoprecipitated proteins (co-IP-proteins. A Fractional Recovery ratio (FR: recovery after high salt/recovery with control salt as assayed by Western blot was calculated for each co-IP-protein. These FR values reflect complex structure since an easily dissociated protein, with a low FR value, cannot be intermediary between the IP-protein and a salt-resistant protein. The structure of the complex was mapped and a blueprint generated with a pair of FR analyses generated using two different IP-proteins. The blueprint of SAE contains an AP180/X/STG/stonin 2/intersectin/epsin core (X is unknown and epsin is hypothesized, and an AP2 adaptor, H-/L-clathrin coat and dynamin scission protein perimeter. Quantitative immunocytochemistry (ICA/ICQ method at an isolated calyx-type presynaptic terminal indicates that this complex is associated with STG at the presynaptic transmitter release face but not with STG on intracellular synaptic vesicles. CONCLUSIONS/SIGNIFICANCE: We hypothesize that the SAE serves as a recognition site and also as a

Protein complex detection in PPI networks based on data integration and supervised learning method.

Science.gov (United States)

Yu, Feng; Yang, Zhi; Hu, Xiao; Sun, Yuan; Lin, Hong; Wang, Jian

2015-01-01

Revealing protein complexes are important for understanding principles of cellular organization and function. High-throughput experimental techniques have produced a large amount of protein interactions, which makes it possible to predict protein complexes from protein-protein interaction (PPI) networks. However, the small amount of known physical interactions may limit protein complex detection. The new PPI networks are constructed by integrating PPI datasets with the large and readily available PPI data from biomedical literature, and then the less reliable PPI between two proteins are filtered out based on semantic similarity and topological similarity of the two proteins. Finally, the supervised learning protein complex detection (SLPC), which can make full use of the information of available known complexes, is applied to detect protein complex on the new PPI networks. The experimental results of SLPC on two different categories yeast PPI networks demonstrate effectiveness of the approach: compared with the original PPI networks, the best average improvements of 4.76, 6.81 and 15.75 percentage units in the F-score, accuracy and maximum matching ratio (MMR) are achieved respectively; compared with the denoising PPI networks, the best average improvements of 3.91, 4.61 and 12.10 percentage units in the F-score, accuracy and MMR are achieved respectively; compared with ClusterONE, the start-of the-art complex detection method, on the denoising extended PPI networks, the average improvements of 26.02 and 22.40 percentage units in the F-score and MMR are achieved respectively. The experimental results show that the performances of SLPC have a large improvement through integration of new receivable PPI data from biomedical literature into original PPI networks and denoising PPI networks. In addition, our protein complexes detection method can achieve better performance than ClusterONE.

Protein complex prediction via dense subgraphs and false positive analysis.

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Cecilia Hernandez

Full Text Available Many proteins work together with others in groups called complexes in order to achieve a specific function. Discovering protein complexes is important for understanding biological processes and predict protein functions in living organisms. Large-scale and throughput techniques have made possible to compile protein-protein interaction networks (PPI networks, which have been used in several computational approaches for detecting protein complexes. Those predictions might guide future biologic experimental research. Some approaches are topology-based, where highly connected proteins are predicted to be complexes; some propose different clustering algorithms using partitioning, overlaps among clusters for networks modeled with unweighted or weighted graphs; and others use density of clusters and information based on protein functionality. However, some schemes still require much processing time or the quality of their results can be improved. Furthermore, most of the results obtained with computational tools are not accompanied by an analysis of false positives. We propose an effective and efficient mining algorithm for discovering highly connected subgraphs, which is our base for defining protein complexes. Our representation is based on transforming the PPI network into a directed acyclic graph that reduces the number of represented edges and the search space for discovering subgraphs. Our approach considers weighted and unweighted PPI networks. We compare our best alternative using PPI networks from Saccharomyces cerevisiae (yeast and Homo sapiens (human with state-of-the-art approaches in terms of clustering, biological metrics and execution times, as well as three gold standards for yeast and two for human. Furthermore, we analyze false positive predicted complexes searching the PDBe (Protein Data Bank in Europe database in order to identify matching protein complexes that have been purified and structurally characterized. Our analysis shows

Multi-Label Learning via Random Label Selection for Protein Subcellular Multi-Locations Prediction.

Science.gov (United States)

Wang, Xiao; Li, Guo-Zheng

2013-03-12

Prediction of protein subcellular localization is an important but challenging problem, particularly when proteins may simultaneously exist at, or move between, two or more different subcellular location sites. Most of the existing protein subcellular localization methods are only used to deal with the single-location proteins. In the past few years, only a few methods have been proposed to tackle proteins with multiple locations. However, they only adopt a simple strategy, that is, transforming the multi-location proteins to multiple proteins with single location, which doesn't take correlations among different subcellular locations into account. In this paper, a novel method named RALS (multi-label learning via RAndom Label Selection), is proposed to learn from multi-location proteins in an effective and efficient way. Through five-fold cross validation test on a benchmark dataset, we demonstrate our proposed method with consideration of label correlations obviously outperforms the baseline BR method without consideration of label correlations, indicating correlations among different subcellular locations really exist and contribute to improvement of prediction performance. Experimental results on two benchmark datasets also show that our proposed methods achieve significantly higher performance than some other state-of-the-art methods in predicting subcellular multi-locations of proteins. The prediction web server is available at http://levis.tongji.edu.cn:8080/bioinfo/MLPred-Euk/ for the public usage.

Predicting protein complexes from weighted protein-protein interaction graphs with a novel unsupervised methodology: Evolutionary enhanced Markov clustering.

Science.gov (United States)

Theofilatos, Konstantinos; Pavlopoulou, Niki; Papasavvas, Christoforos; Likothanassis, Spiros; Dimitrakopoulos, Christos; Georgopoulos, Efstratios; Moschopoulos, Charalampos; Mavroudi, Seferina

2015-03-01

Proteins are considered to be the most important individual components of biological systems and they combine to form physical protein complexes which are responsible for certain molecular functions. Despite the large availability of protein-protein interaction (PPI) information, not much information is available about protein complexes. Experimental methods are limited in terms of time, efficiency, cost and performance constraints. Existing computational methods have provided encouraging preliminary results, but they phase certain disadvantages as they require parameter tuning, some of them cannot handle weighted PPI data and others do not allow a protein to participate in more than one protein complex. In the present paper, we propose a new fully unsupervised methodology for predicting protein complexes from weighted PPI graphs. The proposed methodology is called evolutionary enhanced Markov clustering (EE-MC) and it is a hybrid combination of an adaptive evolutionary algorithm and a state-of-the-art clustering algorithm named enhanced Markov clustering. EE-MC was compared with state-of-the-art methodologies when applied to datasets from the human and the yeast Saccharomyces cerevisiae organisms. Using public available datasets, EE-MC outperformed existing methodologies (in some datasets the separation metric was increased by 10-20%). Moreover, when applied to new human datasets its performance was encouraging in the prediction of protein complexes which consist of proteins with high functional similarity. In specific, 5737 protein complexes were predicted and 72.58% of them are enriched for at least one gene ontology (GO) function term. EE-MC is by design able to overcome intrinsic limitations of existing methodologies such as their inability to handle weighted PPI networks, their constraint to assign every protein in exactly one cluster and the difficulties they face concerning the parameter tuning. This fact was experimentally validated and moreover, new

On the importance of polar interactions for complexes containing intrinsically disordered proteins.

Directory of Open Access Journals (Sweden)

Eric T C Wong

Full Text Available There is a growing recognition for the importance of proteins with large intrinsically disordered (ID segments in cell signaling and regulation. ID segments in these proteins often harbor regions that mediate molecular recognition. Coupled folding and binding of the recognition regions has been proposed to confer high specificity to interactions involving ID segments. However, researchers recently questioned the origin of the interaction specificity of ID proteins because of the overrepresentation of hydrophobic residues in their interaction interfaces. Here, we focused on the role of polar and charged residues in interactions mediated by ID segments. Making use of the extended nature of most ID segments when in complex with globular proteins, we first identified large numbers of complexes between globular proteins and ID segments by using radius-of-gyration-based selection criteria. Consistent with previous studies, we found the interfaces of these complexes to be enriched in hydrophobic residues, and that these residues contribute significantly to the stability of the interaction interface. However, our analyses also show that polar interactions play a larger role in these complexes than in structured protein complexes. Computational alanine scanning and salt-bridge analysis indicate that interfaces in ID complexes are highly complementary with respect to electrostatics, more so than interfaces of globular proteins. Follow-up calculations of the electrostatic contributions to the free energy of binding uncovered significantly stronger Coulombic interactions in complexes harbouring ID segments than in structured protein complexes. However, they are counter-balanced by even higher polar-desolvation penalties. We propose that polar interactions are a key contributing factor to the observed high specificity of ID segment-mediated interactions.

Extreme disorder in an ultrahigh-affinity protein complex

DEFF Research Database (Denmark)

Borgia, Alessandro; Borgia, Madeleine B; Bugge, Katrine

2018-01-01

Molecular communication in biology is mediated by protein interactions. According to the current paradigm, the specificity and affinity required for these interactions are encoded in the precise complementarity of binding interfaces. Even proteins that are disordered under physiological conditions...... with picomolar affinity, but fully retain their structural disorder, long-range flexibility and highly dynamic character. On the basis of closely integrated experiments and molecular simulations, we show that the interaction can be explained by the large opposite net charge of the two proteins, without requiring...... or that contain large unstructured regions commonly interact with well-structured binding sites on other biomolecules. Here we demonstrate the existence of an unexpected interaction mechanism: the two intrinsically disordered human proteins histone H1 and its nuclear chaperone prothymosin-α associate in a complex...

Determining protein complex connectivity using a probabilistic deletion network derived from quantitative proteomics.

Science.gov (United States)

Sardiu, Mihaela E; Gilmore, Joshua M; Carrozza, Michael J; Li, Bing; Workman, Jerry L; Florens, Laurence; Washburn, Michael P

2009-10-06

Protein complexes are key molecular machines executing a variety of essential cellular processes. Despite the availability of genome-wide protein-protein interaction studies, determining the connectivity between proteins within a complex remains a major challenge. Here we demonstrate a method that is able to predict the relationship of proteins within a stable protein complex. We employed a combination of computational approaches and a systematic collection of quantitative proteomics data from wild-type and deletion strain purifications to build a quantitative deletion-interaction network map and subsequently convert the resulting data into an interdependency-interaction model of a complex. We applied this approach to a data set generated from components of the Saccharomyces cerevisiae Rpd3 histone deacetylase complexes, which consists of two distinct small and large complexes that are held together by a module consisting of Rpd3, Sin3 and Ume1. The resulting representation reveals new protein-protein interactions and new submodule relationships, providing novel information for mapping the functional organization of a complex.

Evidence for the robustness of protein complexes to inter-species hybridization.

Directory of Open Access Journals (Sweden)

Jean-Baptiste Leducq

Full Text Available Despite the tremendous efforts devoted to the identification of genetic incompatibilities underlying hybrid sterility and inviability, little is known about the effect of inter-species hybridization at the protein interactome level. Here, we develop a screening platform for the comparison of protein-protein interactions (PPIs among closely related species and their hybrids. We examine in vivo the architecture of protein complexes in two yeast species (Saccharomyces cerevisiae and Saccharomyces kudriavzevii that diverged 5-20 million years ago and in their F1 hybrids. We focus on 24 proteins of two large complexes: the RNA polymerase II and the nuclear pore complex (NPC, which show contrasting patterns of molecular evolution. We found that, with the exception of one PPI in the NPC sub-complex, PPIs were highly conserved between species, regardless of protein divergence. Unexpectedly, we found that the architecture of the complexes in F1 hybrids could not be distinguished from that of the parental species. Our results suggest that the conservation of PPIs in hybrids likely results from the slow evolution taking place on the very few protein residues involved in the interaction or that protein complexes are inherently robust and may accommodate protein divergence up to the level that is observed among closely related species.

Tenant Placement Strategies within Multi-Level Large-Scale Shopping Centers

OpenAIRE

Tony Shun-Te Yuo; Colin Lizieri

2013-01-01

This paper argues that tenant placement strategies for large-scale multi-unit shopping centers differ depending on the number of floor levels. Two core strategies are identified: dispersion and departmentalization. There exists a trade-off between three income effects: basic footfall effects, spillover effects, and an effective floor area effect, which varies by the number of floor levels. Departmentalization is favored for centers with more than four floors. Greater spatial complexity also p...

ProteinSplit: splitting of multi-domain proteins using prediction of ordered and disordered regions in protein sequences for virtual structural genomics

International Nuclear Information System (INIS)

Wyrwicz, Lucjan S; Koczyk, Grzegorz; Rychlewski, Leszek; Plewczynski, Dariusz

2007-01-01

The annotation of protein folds within newly sequenced genomes is the main target for semi-automated protein structure prediction (virtual structural genomics). A large number of automated methods have been developed recently with very good results in the case of single-domain proteins. Unfortunately, most of these automated methods often fail to properly predict the distant homology between a given multi-domain protein query and structural templates. Therefore a multi-domain protein should be split into domains in order to overcome this limitation. ProteinSplit is designed to identify protein domain boundaries using a novel algorithm that predicts disordered regions in protein sequences. The software utilizes various sequence characteristics to assess the local propensity of a protein to be disordered or ordered in terms of local structure stability. These disordered parts of a protein are likely to create interdomain spacers. Because of its speed and portability, the method was successfully applied to several genome-wide fold annotation experiments. The user can run an automated analysis of sets of proteins or perform semi-automated multiple user projects (saving the results on the server). Additionally the sequences of predicted domains can be sent to the Bioinfo.PL Protein Structure Prediction Meta-Server for further protein three-dimensional structure and function prediction. The program is freely accessible as a web service at http://lucjan.bioinfo.pl/proteinsplit together with detailed benchmark results on the critical assessment of a fully automated structure prediction (CAFASP) set of sequences. The source code of the local version of protein domain boundary prediction is available upon request from the authors

Determining protein complex connectivity using a probabilistic deletion network derived from quantitative proteomics.

Directory of Open Access Journals (Sweden)

Mihaela E Sardiu

2009-10-01

Full Text Available Protein complexes are key molecular machines executing a variety of essential cellular processes. Despite the availability of genome-wide protein-protein interaction studies, determining the connectivity between proteins within a complex remains a major challenge. Here we demonstrate a method that is able to predict the relationship of proteins within a stable protein complex. We employed a combination of computational approaches and a systematic collection of quantitative proteomics data from wild-type and deletion strain purifications to build a quantitative deletion-interaction network map and subsequently convert the resulting data into an interdependency-interaction model of a complex. We applied this approach to a data set generated from components of the Saccharomyces cerevisiae Rpd3 histone deacetylase complexes, which consists of two distinct small and large complexes that are held together by a module consisting of Rpd3, Sin3 and Ume1. The resulting representation reveals new protein-protein interactions and new submodule relationships, providing novel information for mapping the functional organization of a complex.

Integrated analysis of RNA-binding protein complexes using in vitro selection and high-throughput sequencing and sequence specificity landscapes (SEQRS).

Science.gov (United States)

Lou, Tzu-Fang; Weidmann, Chase A; Killingsworth, Jordan; Tanaka Hall, Traci M; Goldstrohm, Aaron C; Campbell, Zachary T

2017-04-15

RNA-binding proteins (RBPs) collaborate to control virtually every aspect of RNA function. Tremendous progress has been made in the area of global assessment of RBP specificity using next-generation sequencing approaches both in vivo and in vitro. Understanding how protein-protein interactions enable precise combinatorial regulation of RNA remains a significant problem. Addressing this challenge requires tools that can quantitatively determine the specificities of both individual proteins and multimeric complexes in an unbiased and comprehensive way. One approach utilizes in vitro selection, high-throughput sequencing, and sequence-specificity landscapes (SEQRS). We outline a SEQRS experiment focused on obtaining the specificity of a multi-protein complex between Drosophila RBPs Pumilio (Pum) and Nanos (Nos). We discuss the necessary controls in this type of experiment and examine how the resulting data can be complemented with structural and cell-based reporter assays. Additionally, SEQRS data can be integrated with functional genomics data to uncover biological function. Finally, we propose extensions of the technique that will enhance our understanding of multi-protein regulatory complexes assembled onto RNA. Copyright © 2016 Elsevier Inc. All rights reserved.

Light-fuelled transport of large dendrimers and proteins.

Science.gov (United States)

Koskela, Jenni E; Liljeström, Ville; Lim, Jongdoo; Simanek, Eric E; Ras, Robin H A; Priimagi, Arri; Kostiainen, Mauri A

2014-05-14

This work presents a facile water-based supramolecular approach for light-induced surface patterning. The method is based upon azobenzene-functionalized high-molecular weight triazine dendrimers up to generation 9, demonstrating that even very large globular supramolecular complexes can be made to move in response to light. We also demonstrate light-fuelled macroscopic movements in native biomolecules, showing that complexes of apoferritin protein and azobenzene can effectively form light-induced surface patterns. Fundamentally, the results establish that thin films comprising both flexible and rigid globular particles of large diameter can be moved with light, whereas the presented material concepts offer new possibilities for the yet marginally explored biological applications of azobenzene surface patterning.

Multi-level discriminative dictionary learning with application to large scale image classification.

Science.gov (United States)

Shen, Li; Sun, Gang; Huang, Qingming; Wang, Shuhui; Lin, Zhouchen; Wu, Enhua

2015-10-01

The sparse coding technique has shown flexibility and capability in image representation and analysis. It is a powerful tool in many visual applications. Some recent work has shown that incorporating the properties of task (such as discrimination for classification task) into dictionary learning is effective for improving the accuracy. However, the traditional supervised dictionary learning methods suffer from high computation complexity when dealing with large number of categories, making them less satisfactory in large scale applications. In this paper, we propose a novel multi-level discriminative dictionary learning method and apply it to large scale image classification. Our method takes advantage of hierarchical category correlation to encode multi-level discriminative information. Each internal node of the category hierarchy is associated with a discriminative dictionary and a classification model. The dictionaries at different layers are learnt to capture the information of different scales. Moreover, each node at lower layers also inherits the dictionary of its parent, so that the categories at lower layers can be described with multi-scale information. The learning of dictionaries and associated classification models is jointly conducted by minimizing an overall tree loss. The experimental results on challenging data sets demonstrate that our approach achieves excellent accuracy and competitive computation cost compared with other sparse coding methods for large scale image classification.

ComplexContact: a web server for inter-protein contact prediction using deep learning

KAUST Repository

Zeng, Hong; Wang, Sheng; Zhou, Tianming; Zhao, Feifeng; Li, Xiufeng; Wu, Qing; Xu, Jinbo

2018-01-01

ComplexContact (http://raptorx2.uchicago.edu/ComplexContact/) is a web server for sequence-based interfacial residue-residue contact prediction of a putative protein complex. Interfacial residue-residue contacts are critical for understanding how proteins form complex and interact at residue level. When receiving a pair of protein sequences, ComplexContact first searches for their sequence homologs and builds two paired multiple sequence alignments (MSA), then it applies co-evolution analysis and a CASP-winning deep learning (DL) method to predict interfacial contacts from paired MSAs and visualizes the prediction as an image. The DL method was originally developed for intra-protein contact prediction and performed the best in CASP12. Our large-scale experimental test further shows that ComplexContact greatly outperforms pure co-evolution methods for inter-protein contact prediction, regardless of the species.

ComplexContact: a web server for inter-protein contact prediction using deep learning

KAUST Repository

Zeng, Hong

2018-05-20

ComplexContact (http://raptorx2.uchicago.edu/ComplexContact/) is a web server for sequence-based interfacial residue-residue contact prediction of a putative protein complex. Interfacial residue-residue contacts are critical for understanding how proteins form complex and interact at residue level. When receiving a pair of protein sequences, ComplexContact first searches for their sequence homologs and builds two paired multiple sequence alignments (MSA), then it applies co-evolution analysis and a CASP-winning deep learning (DL) method to predict interfacial contacts from paired MSAs and visualizes the prediction as an image. The DL method was originally developed for intra-protein contact prediction and performed the best in CASP12. Our large-scale experimental test further shows that ComplexContact greatly outperforms pure co-evolution methods for inter-protein contact prediction, regardless of the species.

ComplexContact: a web server for inter-protein contact prediction using deep learning.

Science.gov (United States)

Zeng, Hong; Wang, Sheng; Zhou, Tianming; Zhao, Feifeng; Li, Xiufeng; Wu, Qing; Xu, Jinbo

2018-05-22

ComplexContact (http://raptorx2.uchicago.edu/ComplexContact/) is a web server for sequence-based interfacial residue-residue contact prediction of a putative protein complex. Interfacial residue-residue contacts are critical for understanding how proteins form complex and interact at residue level. When receiving a pair of protein sequences, ComplexContact first searches for their sequence homologs and builds two paired multiple sequence alignments (MSA), then it applies co-evolution analysis and a CASP-winning deep learning (DL) method to predict interfacial contacts from paired MSAs and visualizes the prediction as an image. The DL method was originally developed for intra-protein contact prediction and performed the best in CASP12. Our large-scale experimental test further shows that ComplexContact greatly outperforms pure co-evolution methods for inter-protein contact prediction, regardless of the species.

Protein complex prediction based on k-connected subgraphs in protein interaction network

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Habibi Mahnaz

2010-09-01

Full Text Available Abstract Background Protein complexes play an important role in cellular mechanisms. Recently, several methods have been presented to predict protein complexes in a protein interaction network. In these methods, a protein complex is predicted as a dense subgraph of protein interactions. However, interactions data are incomplete and a protein complex does not have to be a complete or dense subgraph. Results We propose a more appropriate protein complex prediction method, CFA, that is based on connectivity number on subgraphs. We evaluate CFA using several protein interaction networks on reference protein complexes in two benchmark data sets (MIPS and Aloy, containing 1142 and 61 known complexes respectively. We compare CFA to some existing protein complex prediction methods (CMC, MCL, PCP and RNSC in terms of recall and precision. We show that CFA predicts more complexes correctly at a competitive level of precision. Conclusions Many real complexes with different connectivity level in protein interaction network can be predicted based on connectivity number. Our CFA program and results are freely available from http://www.bioinf.cs.ipm.ir/softwares/cfa/CFA.rar.

Identification of a multi-protein reductive dehalogenase complex in Dehalococcoides mccartyi strain CBDB1 suggests a protein-dependent respiratory electron transport chain obviating quinone involvement

DEFF Research Database (Denmark)

Kublik, Anja; Deobald, Darja; Hartwig, Stefanie

2016-01-01

electrophoresis (BN-PAGE), gel filtration and ultrafiltration an active dehalogenating protein complex with a molecular mass of 250–270 kDa was identified. The active subunit of reductive dehalogenase (RdhA) colocalised with a complex iron-sulfur molybdoenzyme (CISM) subunit (CbdbA195) and an iron-sulfur cluster...... of the dehalogenating complex prior to membrane solubilisation. Taken together, the identification of the respiratory dehalogenase protein complex and the absence of indications for quinone participation in the respiration suggest a quinone-independent protein-based respiratory electron transfer chain in D. mccartyi....

Protein complex prediction based on k-connected subgraphs in protein interaction network

OpenAIRE

Habibi, Mahnaz; Eslahchi, Changiz; Wong, Limsoon

2010-01-01

Abstract Background Protein complexes play an important role in cellular mechanisms. Recently, several methods have been presented to predict protein complexes in a protein interaction network. In these methods, a protein complex is predicted as a dense subgraph of protein interactions. However, interactions data are incomplete and a protein complex does not have to be a complete or dense subgraph. Results We propose a more appropriate protein complex prediction method, CFA, that is based on ...

Multi-location gram-positive and gram-negative bacterial protein subcellular localization using gene ontology and multi-label classifier ensemble.

Science.gov (United States)

Wang, Xiao; Zhang, Jun; Li, Guo-Zheng

2015-01-01

It has become a very important and full of challenge task to predict bacterial protein subcellular locations using computational methods. Although there exist a lot of prediction methods for bacterial proteins, the majority of these methods can only deal with single-location proteins. But unfortunately many multi-location proteins are located in the bacterial cells. Moreover, multi-location proteins have special biological functions capable of helping the development of new drugs. So it is necessary to develop new computational methods for accurately predicting subcellular locations of multi-location bacterial proteins. In this article, two efficient multi-label predictors, Gpos-ECC-mPLoc and Gneg-ECC-mPLoc, are developed to predict the subcellular locations of multi-label gram-positive and gram-negative bacterial proteins respectively. The two multi-label predictors construct the GO vectors by using the GO terms of homologous proteins of query proteins and then adopt a powerful multi-label ensemble classifier to make the final multi-label prediction. The two multi-label predictors have the following advantages: (1) they improve the prediction performance of multi-label proteins by taking the correlations among different labels into account; (2) they ensemble multiple CC classifiers and further generate better prediction results by ensemble learning; and (3) they construct the GO vectors by using the frequency of occurrences of GO terms in the typical homologous set instead of using 0/1 values. Experimental results show that Gpos-ECC-mPLoc and Gneg-ECC-mPLoc can efficiently predict the subcellular locations of multi-label gram-positive and gram-negative bacterial proteins respectively. Gpos-ECC-mPLoc and Gneg-ECC-mPLoc can efficiently improve prediction accuracy of subcellular localization of multi-location gram-positive and gram-negative bacterial proteins respectively. The online web servers for Gpos-ECC-mPLoc and Gneg-ECC-mPLoc predictors are freely accessible

Suitability of magnetic single- and multi-core nanoparticles to detect protein binding with dynamic magnetic measurement techniques

International Nuclear Information System (INIS)

Remmer, Hilke; Dieckhoff, Jan; Schilling, Meinhard; Ludwig, Frank

2015-01-01

We investigated the binding of biotinylated proteins to various streptavidin functionalized magnetic nanoparticles with different dynamic magnetic measurement techniques to examine their potential for homogeneous bioassays. As particle systems, single-core nanoparticles with a nominal core diameter of 30 nm as well as multi-core nanoparticles with hydrodynamic sizes varying between nominally 60 nm and 100 nm were chosen. As experimental techniques, fluxgate magnetorelaxometry (MRX), complex ac susceptibility (ACS) and measurements of the phase lag between rotating field and sample magnetization are applied. MRX measurements are only suited for the detection of small analytes if the multivalency of functionalized nanoparticles and analytes causes cross-linking, thus forming larger aggregates. ACS measurements showed for all nanoparticle systems a shift of the imaginary part's maximum towards small frequencies. In rotating field measurements only the single-core nanoparticle systems with dominating Brownian mechanism exhibit an increase of the phase lag upon binding in the investigated frequency range. The coexistence of Brownian and Néel relaxation processes can cause a more complex phase lag change behavior, as demonstrated for multi-core nanoparticle systems. - Highlights: • Cealization of homogeneous magnetic bioassays using different magnetic techniques. • Comparison of single- and multi-core nanoparticle systems. • ac Susceptibility favorable for detection of small analytes. • Magnetorelaxometry favorable for detection of large analytes or cross-linking assays

Extreme disorder in an ultrahigh-affinity protein complex

Science.gov (United States)

Borgia, Alessandro; Borgia, Madeleine B.; Bugge, Katrine; Kissling, Vera M.; Heidarsson, Pétur O.; Fernandes, Catarina B.; Sottini, Andrea; Soranno, Andrea; Buholzer, Karin J.; Nettels, Daniel; Kragelund, Birthe B.; Best, Robert B.; Schuler, Benjamin

2018-03-01

Molecular communication in biology is mediated by protein interactions. According to the current paradigm, the specificity and affinity required for these interactions are encoded in the precise complementarity of binding interfaces. Even proteins that are disordered under physiological conditions or that contain large unstructured regions commonly interact with well-structured binding sites on other biomolecules. Here we demonstrate the existence of an unexpected interaction mechanism: the two intrinsically disordered human proteins histone H1 and its nuclear chaperone prothymosin-α associate in a complex with picomolar affinity, but fully retain their structural disorder, long-range flexibility and highly dynamic character. On the basis of closely integrated experiments and molecular simulations, we show that the interaction can be explained by the large opposite net charge of the two proteins, without requiring defined binding sites or interactions between specific individual residues. Proteome-wide sequence analysis suggests that this interaction mechanism may be abundant in eukaryotes.

Structure solution of DNA-binding proteins and complexes with ARCIMBOLDO libraries

Energy Technology Data Exchange (ETDEWEB)

Pröpper, Kevin [University of Göttingen, (Germany); Instituto de Biologia Molecular de Barcelona (IBMB-CSIC), (Spain); Meindl, Kathrin; Sammito, Massimo [Instituto de Biologia Molecular de Barcelona (IBMB-CSIC), (Spain); Dittrich, Birger; Sheldrick, George M. [University of Göttingen, (Germany); Pohl, Ehmke, E-mail: ehmke.pohl@durham.ac.uk [Durham University, (United Kingdom); Usón, Isabel, E-mail: ehmke.pohl@durham.ac.uk [Instituto de Biologia Molecular de Barcelona (IBMB-CSIC), (Spain); Institucio Catalana de Recerca i Estudis Avancats (ICREA), (Spain); University of Göttingen, (Germany)

2014-06-01

The structure solution of DNA-binding protein structures and complexes based on the combination of location of DNA-binding protein motif fragments with density modification in a multi-solution frame is described. Protein–DNA interactions play a major role in all aspects of genetic activity within an organism, such as transcription, packaging, rearrangement, replication and repair. The molecular detail of protein–DNA interactions can be best visualized through crystallography, and structures emphasizing insight into the principles of binding and base-sequence recognition are essential to understanding the subtleties of the underlying mechanisms. An increasing number of high-quality DNA-binding protein structure determinations have been witnessed despite the fact that the crystallographic particularities of nucleic acids tend to pose specific challenges to methods primarily developed for proteins. Crystallographic structure solution of protein–DNA complexes therefore remains a challenging area that is in need of optimized experimental and computational methods. The potential of the structure-solution program ARCIMBOLDO for the solution of protein–DNA complexes has therefore been assessed. The method is based on the combination of locating small, very accurate fragments using the program Phaser and density modification with the program SHELXE. Whereas for typical proteins main-chain α-helices provide the ideal, almost ubiquitous, small fragments to start searches, in the case of DNA complexes the binding motifs and DNA double helix constitute suitable search fragments. The aim of this work is to provide an effective library of search fragments as well as to determine the optimal ARCIMBOLDO strategy for the solution of this class of structures.

Supervised maximum-likelihood weighting of composite protein networks for complex prediction

Directory of Open Access Journals (Sweden)

Yong Chern Han

2012-12-01

Full Text Available Abstract Background Protein complexes participate in many important cellular functions, so finding the set of existent complexes is essential for understanding the organization and regulation of processes in the cell. With the availability of large amounts of high-throughput protein-protein interaction (PPI data, many algorithms have been proposed to discover protein complexes from PPI networks. However, such approaches are hindered by the high rate of noise in high-throughput PPI data, including spurious and missing interactions. Furthermore, many transient interactions are detected between proteins that are not from the same complex, while not all proteins from the same complex may actually interact. As a result, predicted complexes often do not match true complexes well, and many true complexes go undetected. Results We address these challenges by integrating PPI data with other heterogeneous data sources to construct a composite protein network, and using a supervised maximum-likelihood approach to weight each edge based on its posterior probability of belonging to a complex. We then use six different clustering algorithms, and an aggregative clustering strategy, to discover complexes in the weighted network. We test our method on Saccharomyces cerevisiae and Homo sapiens, and show that complex discovery is improved: compared to previously proposed supervised and unsupervised weighting approaches, our method recalls more known complexes, achieves higher precision at all recall levels, and generates novel complexes of greater functional similarity. Furthermore, our maximum-likelihood approach allows learned parameters to be used to visualize and evaluate the evidence of novel predictions, aiding human judgment of their credibility. Conclusions Our approach integrates multiple data sources with supervised learning to create a weighted composite protein network, and uses six clustering algorithms with an aggregative clustering strategy to

Large-Eddy Simulations of Flows in Complex Terrain

Science.gov (United States)

Kosovic, B.; Lundquist, K. A.

2011-12-01

Large-eddy simulation as a methodology for numerical simulation of turbulent flows was first developed to study turbulent flows in atmospheric by Lilly (1967). The first LES were carried by Deardorff (1970) who used these simulations to study atmospheric boundary layers. Ever since, LES has been extensively used to study canonical atmospheric boundary layers, in most cases flat plate boundary layers under the assumption of horizontal homogeneity. Carefully designed LES of canonical convective and neutrally stratified and more recently stably stratified atmospheric boundary layers have contributed significantly to development of better understanding of these flows and their parameterizations in large scale models. These simulations were often carried out using codes specifically designed and developed for large-eddy simulations of horizontally homogeneous flows with periodic lateral boundary conditions. Recent developments in multi-scale numerical simulations of atmospheric flows enable numerical weather prediction (NWP) codes such as ARPS (Chow and Street, 2009), COAMPS (Golaz et al., 2009) and Weather Research and Forecasting model, to be used nearly seamlessly across a wide range of atmospheric scales from synoptic down to turbulent scales in atmospheric boundary layers. Before we can with confidence carry out multi-scale simulations of atmospheric flows, NWP codes must be validated for accurate performance in simulating flows over complex or inhomogeneous terrain. We therefore carry out validation of WRF-LES for simulations of flows over complex terrain using data from Askervein Hill (Taylor and Teunissen, 1985, 1987) and METCRAX (Whiteman et al., 2008) field experiments. WRF's nesting capability is employed with a one-way nested inner domain that includes complex terrain representation while the coarser outer nest is used to spin up fully developed atmospheric boundary layer turbulence and thus represent accurately inflow to the inner domain. LES of a

Monte Carlo simulations of flexible polyanions complexing with whey proteins at their isoelectric point.

Science.gov (United States)

de Vries, R

2004-02-15

Electrostatic complexation of flexible polyanions with the whey proteins alpha-lactalbumin and beta-lactoglobulin is studied using Monte Carlo simulations. The proteins are considered at their respective isoelectric points. Discrete charges on the model polyelectrolytes and proteins interact through Debye-Huckel potentials. Protein excluded volume is taken into account through a coarse-grained model of the protein shape. Consistent with experimental results, it is found that alpha-lactalbumin complexes much more strongly than beta-lactoglobulin. For alpha-lactalbumin, strong complexation is due to localized binding to a single large positive "charge patch," whereas for beta-lactoglobulin, weak complexation is due to diffuse binding to multiple smaller charge patches. Copyright 2004 American Institute of Physics

Isothermal chemical denaturation of large proteins: Path-dependence and irreversibility.

Science.gov (United States)

Wafer, Lucas; Kloczewiak, Marek; Polleck, Sharon M; Luo, Yin

2017-12-15

State functions (e.g., ΔG) are path independent and quantitatively describe the equilibrium states of a thermodynamic system. Isothermal chemical denaturation (ICD) is often used to extrapolate state function parameters for protein unfolding in native buffer conditions. The approach is prudent when the unfolding/refolding processes are path independent and reversible, but may lead to erroneous results if the processes are not reversible. The reversibility was demonstrated in several early studies for smaller proteins, but was assumed in some reports for large proteins with complex structures. In this work, the unfolding/refolding of several proteins were systematically studied using an automated ICD instrument. It is shown that: (i) the apparent unfolding mechanism and conformational stability of large proteins can be denaturant-dependent, (ii) equilibration times for large proteins are non-trivial and may introduce significant error into calculations of ΔG, (iii) fluorescence emission spectroscopy may not correspond to other methods, such as circular dichroism, when used to measure protein unfolding, and (iv) irreversible unfolding and hysteresis can occur in the absence of aggregation. These results suggest that thorough confirmation of the state functions by, for example, performing refolding experiments or using additional denaturants, is needed when quantitatively studying the thermodynamics of protein unfolding using ICD. Copyright © 2017 Elsevier Inc. All rights reserved.

Characterization of Mediator Complex and its Associated Proteins from Rice.

Science.gov (United States)

Samanta, Subhasis; Thakur, Jitendra Kumar

2017-01-01

The Mediator complex is a multi-protein complex that acts as a molecular bridge conveying transcriptional messages from the cis element-bound transcription factor to the RNA Polymerase II machinery. It is found in all eukaryotes including members of the plant kingdom. Increasing number of reports from plants regarding different Mediator subunits involved in a multitude of processes spanning from plant development to environmental interactions have firmly established it as a central hub of plant regulatory networks. Routine isolation of Mediator complex in a particular species is a necessity because of many reasons. First, composition of the Mediator complex varies from species to species. Second, the composition of the Mediator complex in a particular species is not static under all developmental and environmental conditions. Besides this, at times, Mediator complex is used in in vitro transcription systems. Rice, a staple food crop of the world, is used as a model monocot crop. Realizing the need of a reliable protocol for the isolation of Mediator complex from plants, we describe here the isolation of Mediator complex from rice.

Looping and clustering model for the organization of protein-DNA complexes on the bacterial genome

Science.gov (United States)

Walter, Jean-Charles; Walliser, Nils-Ole; David, Gabriel; Dorignac, Jérôme; Geniet, Frédéric; Palmeri, John; Parmeggiani, Andrea; Wingreen, Ned S.; Broedersz, Chase P.

2018-03-01

The bacterial genome is organized by a variety of associated proteins inside a structure called the nucleoid. These proteins can form complexes on DNA that play a central role in various biological processes, including chromosome segregation. A prominent example is the large ParB-DNA complex, which forms an essential component of the segregation machinery in many bacteria. ChIP-Seq experiments show that ParB proteins localize around centromere-like parS sites on the DNA to which ParB binds specifically, and spreads from there over large sections of the chromosome. Recent theoretical and experimental studies suggest that DNA-bound ParB proteins can interact with each other to condense into a coherent 3D complex on the DNA. However, the structural organization of this protein-DNA complex remains unclear, and a predictive quantitative theory for the distribution of ParB proteins on DNA is lacking. Here, we propose the looping and clustering model, which employs a statistical physics approach to describe protein-DNA complexes. The looping and clustering model accounts for the extrusion of DNA loops from a cluster of interacting DNA-bound proteins that is organized around a single high-affinity binding site. Conceptually, the structure of the protein-DNA complex is determined by a competition between attractive protein interactions and loop closure entropy of this protein-DNA cluster on the one hand, and the positional entropy for placing loops within the cluster on the other. Indeed, we show that the protein interaction strength determines the ‘tightness’ of the loopy protein-DNA complex. Thus, our model provides a theoretical framework for quantitatively computing the binding profiles of ParB-like proteins around a cognate (parS) binding site.

Hierarchical modeling and robust synthesis for the preliminary design of large scale complex systems

Science.gov (United States)

Koch, Patrick Nathan

Large-scale complex systems are characterized by multiple interacting subsystems and the analysis of multiple disciplines. The design and development of such systems inevitably requires the resolution of multiple conflicting objectives. The size of complex systems, however, prohibits the development of comprehensive system models, and thus these systems must be partitioned into their constituent parts. Because simultaneous solution of individual subsystem models is often not manageable iteration is inevitable and often excessive. In this dissertation these issues are addressed through the development of a method for hierarchical robust preliminary design exploration to facilitate concurrent system and subsystem design exploration, for the concurrent generation of robust system and subsystem specifications for the preliminary design of multi-level, multi-objective, large-scale complex systems. This method is developed through the integration and expansion of current design techniques: (1) Hierarchical partitioning and modeling techniques for partitioning large-scale complex systems into more tractable parts, and allowing integration of subproblems for system synthesis, (2) Statistical experimentation and approximation techniques for increasing both the efficiency and the comprehensiveness of preliminary design exploration, and (3) Noise modeling techniques for implementing robust preliminary design when approximate models are employed. The method developed and associated approaches are illustrated through their application to the preliminary design of a commercial turbofan turbine propulsion system; the turbofan system-level problem is partitioned into engine cycle and configuration design and a compressor module is integrated for more detailed subsystem-level design exploration, improving system evaluation.

A Large-Scale Multi-Hop Localization Algorithm Based on Regularized Extreme Learning for Wireless Networks.

Science.gov (United States)

Zheng, Wei; Yan, Xiaoyong; Zhao, Wei; Qian, Chengshan

2017-12-20

A novel large-scale multi-hop localization algorithm based on regularized extreme learning is proposed in this paper. The large-scale multi-hop localization problem is formulated as a learning problem. Unlike other similar localization algorithms, the proposed algorithm overcomes the shortcoming of the traditional algorithms which are only applicable to an isotropic network, therefore has a strong adaptability to the complex deployment environment. The proposed algorithm is composed of three stages: data acquisition, modeling and location estimation. In data acquisition stage, the training information between nodes of the given network is collected. In modeling stage, the model among the hop-counts and the physical distances between nodes is constructed using regularized extreme learning. In location estimation stage, each node finds its specific location in a distributed manner. Theoretical analysis and several experiments show that the proposed algorithm can adapt to the different topological environments with low computational cost. Furthermore, high accuracy can be achieved by this method without setting complex parameters.

Polycomb group protein-mediated repression of transcription

DEFF Research Database (Denmark)

Morey, Lluís; Helin, Kristian

2010-01-01

The polycomb group (PcG) proteins are essential for the normal development of multicellular organisms. They form multi-protein complexes that work as transcriptional repressors of several thousand genes controlling differentiation pathways during development. How the PcG proteins work as transcri......The polycomb group (PcG) proteins are essential for the normal development of multicellular organisms. They form multi-protein complexes that work as transcriptional repressors of several thousand genes controlling differentiation pathways during development. How the PcG proteins work...... as transcriptional repressors is incompletely understood, but involves post-translational modifications of histones by two major PcG protein complexes: polycomb repressive complex 1 and polycomb repressive complex 2....

Reliability of large and complex systems

CERN Document Server

Kolowrocki, Krzysztof

2014-01-01

Reliability of Large and Complex Systems, previously titled Reliability of Large Systems, is an innovative guide to the current state and reliability of large and complex systems. In addition to revised and updated content on the complexity and safety of large and complex mechanisms, this new edition looks at the reliability of nanosystems, a key research topic in nanotechnology science. The author discusses the importance of safety investigation of critical infrastructures that have aged or have been exposed to varying operational conditions. This reference provides an asympt

Finding low-conductance sets with dense interactions (FLCD) for better protein complex prediction.

Science.gov (United States)

Wang, Yijie; Qian, Xiaoning

2017-03-14

Intuitively, proteins in the same protein complexes should highly interact with each other but rarely interact with the other proteins in protein-protein interaction (PPI) networks. Surprisingly, many existing computational algorithms do not directly detect protein complexes based on both of these topological properties. Most of them, depending on mathematical definitions of either "modularity" or "conductance", have their own limitations: Modularity has the inherent resolution problem ignoring small protein complexes; and conductance characterizes the separability of complexes but fails to capture the interaction density within complexes. In this paper, we propose a two-step algorithm FLCD (Finding Low-Conductance sets with Dense interactions) to predict overlapping protein complexes with the desired topological structure, which is densely connected inside and well separated from the rest of the networks. First, FLCD detects well-separated subnetworks based on approximating a potential low-conductance set through a personalized PageRank vector from a protein and then solving a mixed integer programming (MIP) problem to find the minimum-conductance set within the identified low-conductance set. At the second step, the densely connected parts in those subnetworks are discovered as the protein complexes by solving another MIP problem that aims to find the dense subnetwork in the minimum-conductance set. Experiments on four large-scale yeast PPI networks from different public databases demonstrate that the complexes predicted by FLCD have better correspondence with the yeast protein complex gold standards than other three state-of-the-art algorithms (ClusterONE, LinkComm, and SR-MCL). Additionally, results of FLCD show higher biological relevance with respect to Gene Ontology (GO) terms by GO enrichment analysis.

X-ray structure of the mammalian GIRK2-βγ G-protein complex

Energy Technology Data Exchange (ETDEWEB)

Whorton, Matthew R.; MacKinnon, Roderick [Rockefeller

2013-07-30

G-protein-gated inward rectifier K⁺ (GIRK) channels allow neurotransmitters, through G-protein-coupled receptor stimulation, to control cellular electrical excitability. In cardiac and neuronal cells this control regulates heart rate and neural circuit activity, respectively. Here we present the 3.5Å resolution crystal structure of the mammalian GIRK2 channel in complex with βγ G-protein subunits, the central signalling complex that links G-protein-coupled receptor stimulation to K⁺ channel activity. Short-range atomic and long-range electrostatic interactions stabilize four βγ G-protein subunits at the interfaces between four K⁺ channel subunits, inducing a pre-open state of the channel. The pre-open state exhibits a conformation that is intermediate between the closed conformation and the open conformation of the constitutively active mutant. The resultant structural picture is compatible with ‘membrane delimited’ activation of GIRK channels by G proteins and the characteristic burst kinetics of channel gating. The structures also permit a conceptual understanding of how the signalling lipid phosphatidylinositol-4,5-bisphosphate (PIP₂) and intracellular Na⁺ ions participate in multi-ligand regulation of GIRK channels.

SVM-Fold: a tool for discriminative multi-class protein fold and superfamily recognition.

Science.gov (United States)

Melvin, Iain; Ie, Eugene; Kuang, Rui; Weston, Jason; Stafford, William Noble; Leslie, Christina

2007-05-22

Predicting a protein's structural class from its amino acid sequence is a fundamental problem in computational biology. Much recent work has focused on developing new representations for protein sequences, called string kernels, for use with support vector machine (SVM) classifiers. However, while some of these approaches exhibit state-of-the-art performance at the binary protein classification problem, i.e. discriminating between a particular protein class and all other classes, few of these studies have addressed the real problem of multi-class superfamily or fold recognition. Moreover, there are only limited software tools and systems for SVM-based protein classification available to the bioinformatics community. We present a new multi-class SVM-based protein fold and superfamily recognition system and web server called SVM-Fold, which can be found at http://svm-fold.c2b2.columbia.edu. Our system uses an efficient implementation of a state-of-the-art string kernel for sequence profiles, called the profile kernel, where the underlying feature representation is a histogram of inexact matching k-mer frequencies. We also employ a novel machine learning approach to solve the difficult multi-class problem of classifying a sequence of amino acids into one of many known protein structural classes. Binary one-vs-the-rest SVM classifiers that are trained to recognize individual structural classes yield prediction scores that are not comparable, so that standard "one-vs-all" classification fails to perform well. Moreover, SVMs for classes at different levels of the protein structural hierarchy may make useful predictions, but one-vs-all does not try to combine these multiple predictions. To deal with these problems, our method learns relative weights between one-vs-the-rest classifiers and encodes information about the protein structural hierarchy for multi-class prediction. In large-scale benchmark results based on the SCOP database, our code weighting approach

HD-MTL: Hierarchical Deep Multi-Task Learning for Large-Scale Visual Recognition.

Science.gov (United States)

Fan, Jianping; Zhao, Tianyi; Kuang, Zhenzhong; Zheng, Yu; Zhang, Ji; Yu, Jun; Peng, Jinye

2017-02-09

In this paper, a hierarchical deep multi-task learning (HD-MTL) algorithm is developed to support large-scale visual recognition (e.g., recognizing thousands or even tens of thousands of atomic object classes automatically). First, multiple sets of multi-level deep features are extracted from different layers of deep convolutional neural networks (deep CNNs), and they are used to achieve more effective accomplishment of the coarseto- fine tasks for hierarchical visual recognition. A visual tree is then learned by assigning the visually-similar atomic object classes with similar learning complexities into the same group, which can provide a good environment for determining the interrelated learning tasks automatically. By leveraging the inter-task relatedness (inter-class similarities) to learn more discriminative group-specific deep representations, our deep multi-task learning algorithm can train more discriminative node classifiers for distinguishing the visually-similar atomic object classes effectively. Our hierarchical deep multi-task learning (HD-MTL) algorithm can integrate two discriminative regularization terms to control the inter-level error propagation effectively, and it can provide an end-to-end approach for jointly learning more representative deep CNNs (for image representation) and more discriminative tree classifier (for large-scale visual recognition) and updating them simultaneously. Our incremental deep learning algorithms can effectively adapt both the deep CNNs and the tree classifier to the new training images and the new object classes. Our experimental results have demonstrated that our HD-MTL algorithm can achieve very competitive results on improving the accuracy rates for large-scale visual recognition.

Functional Assembly of Soluble and Membrane Recombinant Proteins of Mammalian NADPH Oxidase Complex.

Science.gov (United States)

Souabni, Hajer; Ezzine, Aymen; Bizouarn, Tania; Baciou, Laura

2017-01-01

Activation of phagocyte cells from an innate immune system is associated with a massive consumption of molecular oxygen to generate highly reactive oxygen species (ROS) as microbial weapons. This is achieved by a multiprotein complex, the so-called NADPH oxidase. The activity of phagocyte NADPH oxidase relies on an assembly of more than five proteins, among them the membrane heterodimer named flavocytochrome b 558 (Cytb 558 ), constituted by the tight association of the gp91 phox (also named Nox2) and p22 phox proteins. The Cytb 558 is the membrane catalytic core of the NADPH oxidase complex, through which the reducing equivalent provided by NADPH is transferred via the associated prosthetic groups (one flavin and two hemes) to reduce dioxygen into superoxide anion. The other major proteins (p47 phox , p67 phox , p40 phox , Rac) requisite for the complex activity are cytosolic proteins. Thus, the NADPH oxidase functioning relies on a synergic multi-partner assembly that in vivo can be hardly studied at the molecular level due to the cell complexity. Thus, a cell-free assay method has been developed to study the NADPH oxidase activity that allows measuring and eventually quantifying the ROS generation based on optical techniques following reduction of cytochrome c. This setup is a valuable tool for the identification of protein interactions, of crucial components and additives for a functional enzyme. Recently, this method was improved by the engineering and the production of a complete recombinant NADPH oxidase complex using the combination of purified proteins expressed in bacterial and yeast host cells. The reconstitution into artificial membrane leads to a fully controllable system that permits fine functional studies.

Large-scale protein-protein interaction analysis in Arabidopsis mesophyll protoplasts by split firefly luciferase complementation.

Science.gov (United States)

Li, Jian-Feng; Bush, Jenifer; Xiong, Yan; Li, Lei; McCormack, Matthew

2011-01-01

Protein-protein interactions (PPIs) constitute the regulatory network that coordinates diverse cellular functions. There are growing needs in plant research for creating protein interaction maps behind complex cellular processes and at a systems biology level. However, only a few approaches have been successfully used for large-scale surveys of PPIs in plants, each having advantages and disadvantages. Here we present split firefly luciferase complementation (SFLC) as a highly sensitive and noninvasive technique for in planta PPI investigation. In this assay, the separate halves of a firefly luciferase can come into close proximity and transiently restore its catalytic activity only when their fusion partners, namely the two proteins of interest, interact with each other. This assay was conferred with quantitativeness and high throughput potential when the Arabidopsis mesophyll protoplast system and a microplate luminometer were employed for protein expression and luciferase measurement, respectively. Using the SFLC assay, we could monitor the dynamics of rapamycin-induced and ascomycin-disrupted interaction between Arabidopsis FRB and human FKBP proteins in a near real-time manner. As a proof of concept for large-scale PPI survey, we further applied the SFLC assay to testing 132 binary PPIs among 8 auxin response factors (ARFs) and 12 Aux/IAA proteins from Arabidopsis. Our results demonstrated that the SFLC assay is ideal for in vivo quantitative PPI analysis in plant cells and is particularly powerful for large-scale binary PPI screens.

Large-scale protein-protein interaction analysis in Arabidopsis mesophyll protoplasts by split firefly luciferase complementation.

Directory of Open Access Journals (Sweden)

Jian-Feng Li

Full Text Available Protein-protein interactions (PPIs constitute the regulatory network that coordinates diverse cellular functions. There are growing needs in plant research for creating protein interaction maps behind complex cellular processes and at a systems biology level. However, only a few approaches have been successfully used for large-scale surveys of PPIs in plants, each having advantages and disadvantages. Here we present split firefly luciferase complementation (SFLC as a highly sensitive and noninvasive technique for in planta PPI investigation. In this assay, the separate halves of a firefly luciferase can come into close proximity and transiently restore its catalytic activity only when their fusion partners, namely the two proteins of interest, interact with each other. This assay was conferred with quantitativeness and high throughput potential when the Arabidopsis mesophyll protoplast system and a microplate luminometer were employed for protein expression and luciferase measurement, respectively. Using the SFLC assay, we could monitor the dynamics of rapamycin-induced and ascomycin-disrupted interaction between Arabidopsis FRB and human FKBP proteins in a near real-time manner. As a proof of concept for large-scale PPI survey, we further applied the SFLC assay to testing 132 binary PPIs among 8 auxin response factors (ARFs and 12 Aux/IAA proteins from Arabidopsis. Our results demonstrated that the SFLC assay is ideal for in vivo quantitative PPI analysis in plant cells and is particularly powerful for large-scale binary PPI screens.

Which clustering algorithm is better for predicting protein complexes?

Directory of Open Access Journals (Sweden)

Moschopoulos Charalampos N

2011-12-01

Full Text Available Abstract Background Protein-Protein interactions (PPI play a key role in determining the outcome of most cellular processes. The correct identification and characterization of protein interactions and the networks, which they comprise, is critical for understanding the molecular mechanisms within the cell. Large-scale techniques such as pull down assays and tandem affinity purification are used in order to detect protein interactions in an organism. Today, relatively new high-throughput methods like yeast two hybrid, mass spectrometry, microarrays, and phage display are also used to reveal protein interaction networks. Results In this paper we evaluated four different clustering algorithms using six different interaction datasets. We parameterized the MCL, Spectral, RNSC and Affinity Propagation algorithms and applied them to six PPI datasets produced experimentally by Yeast 2 Hybrid (Y2H and Tandem Affinity Purification (TAP methods. The predicted clusters, so called protein complexes, were then compared and benchmarked with already known complexes stored in published databases. Conclusions While results may differ upon parameterization, the MCL and RNSC algorithms seem to be more promising and more accurate at predicting PPI complexes. Moreover, they predict more complexes than other reviewed algorithms in absolute numbers. On the other hand the spectral clustering algorithm achieves the highest valid prediction rate in our experiments. However, it is nearly always outperformed by both RNSC and MCL in terms of the geometrical accuracy while it generates the fewest valid clusters than any other reviewed algorithm. This article demonstrates various metrics to evaluate the accuracy of such predictions as they are presented in the text below. Supplementary material can be found at: http://www.bioacademy.gr/bioinformatics/projects/ppireview.htm

Coordinated Multi-layer Multi-domain Optical Network (COMMON) for Large-Scale Science Applications (COMMON)

Energy Technology Data Exchange (ETDEWEB)

Vokkarane, Vinod [University of Massachusetts

2013-09-01

We intend to implement a Coordinated Multi-layer Multi-domain Optical Network (COMMON) Framework for Large-scale Science Applications. In the COMMON project, specific problems to be addressed include 1) anycast/multicast/manycast request provisioning, 2) deployable OSCARS enhancements, 3) multi-layer, multi-domain quality of service (QoS), and 4) multi-layer, multidomain path survivability. In what follows, we outline the progress in the above categories (Year 1, 2, and 3 deliverables).

Conformational co-dependence between Plasmodium berghei LCCL proteins promotes complex formation and stability.

Science.gov (United States)

Saeed, Sadia; Tremp, Annie Z; Dessens, Johannes T

2012-10-01

Malaria parasites express a conserved family of LCCL-lectin adhesive-like domain proteins (LAPs) that have essential functions in sporozoite transmission. In Plasmodium falciparum all six family members are expressed in gametocytes and form a multi-protein complex. Intriguingly, knockout of P. falciparum LCCL proteins adversely affects expression of other family members at protein, but not at mRNA level, a phenomenon termed co-dependent expression. Here, we investigate this in Plasmodium berghei by crossing a PbLAP1 null mutant parasite with a parasite line expressing GFP-tagged PbLAP3 that displays strong fluorescence in gametocytes. Selected and validated double mutants show normal synthesis and subcellular localization of PbLAP3::GFP. However, GFP-based fluorescence is dramatically reduced without PbLAP1 present, indicating that PbLAP1 and PbLAP3 interact. Moreover, absence of PbLAP1 markedly reduces the half-life of PbLAP3, consistent with a scenario of misfolding. These findings unveil a potential mechanism of conformational interdependence that facilitates assembly and stability of the functional LCCL protein complex. Copyright © 2012 Elsevier B.V. All rights reserved.

Study of multi-functional precision optical measuring system for large scale equipment

Science.gov (United States)

Jiang, Wei; Lao, Dabao; Zhou, Weihu; Zhang, Wenying; Jiang, Xingjian; Wang, Yongxi

2017-10-01

The effective application of high performance measurement technology can greatly improve the large-scale equipment manufacturing ability. Therefore, the geometric parameters measurement, such as size, attitude and position, requires the measurement system with high precision, multi-function, portability and other characteristics. However, the existing measuring instruments, such as laser tracker, total station, photogrammetry system, mostly has single function, station moving and other shortcomings. Laser tracker needs to work with cooperative target, but it can hardly meet the requirement of measurement in extreme environment. Total station is mainly used for outdoor surveying and mapping, it is hard to achieve the demand of accuracy in industrial measurement. Photogrammetry system can achieve a wide range of multi-point measurement, but the measuring range is limited and need to repeatedly move station. The paper presents a non-contact opto-electronic measuring instrument, not only it can work by scanning the measurement path but also measuring the cooperative target by tracking measurement. The system is based on some key technologies, such as absolute distance measurement, two-dimensional angle measurement, automatically target recognition and accurate aiming, precision control, assembly of complex mechanical system and multi-functional 3D visualization software. Among them, the absolute distance measurement module ensures measurement with high accuracy, and the twodimensional angle measuring module provides precision angle measurement. The system is suitable for the case of noncontact measurement of large-scale equipment, it can ensure the quality and performance of large-scale equipment throughout the process of manufacturing and improve the manufacturing ability of large-scale and high-end equipment.

Exploring the dynamics of formal and informal networks in complex multi-team development projects

DEFF Research Database (Denmark)

Kratzer, J.; Gemuenden, H. G.; Lettl, Christopher

2007-01-01

The increasing number of complex multi-team projects and the scarcity of knowledge about how to run them successfully, create a need for systematic empirical studies. We attempt to lessen this empirical gap by examining the overlap and structure of formally ascribed design interfaces and informal...... communication networks between participating teams in two complex multi-team projects in the space industry. We study the two projects longitudinally throughout the design and integration phases of product development. There are three major findings. First, formally ascribed design interfaces and informal...... communication networks overlap only marginally. Second, the structure of informal communication remains largely stable in the transition from the design to the integration phase. The third and most intriguing finding is that the weak overlap between formally ascribed design interfaces and the informal...

A 3D model of the membrane protein complex formed by the white spot syndrome virus structural proteins.

Directory of Open Access Journals (Sweden)

Yun-Shiang Chang

Full Text Available BACKGROUND: Outbreaks of white spot disease have had a large negative economic impact on cultured shrimp worldwide. However, the pathogenesis of the causative virus, WSSV (whit spot syndrome virus, is not yet well understood. WSSV is a large enveloped virus. The WSSV virion has three structural layers surrounding its core DNA: an outer envelope, a tegument and a nucleocapsid. In this study, we investigated the protein-protein interactions of the major WSSV structural proteins, including several envelope and tegument proteins that are known to be involved in the infection process. PRINCIPAL FINDINGS: In the present report, we used coimmunoprecipitation and yeast two-hybrid assays to elucidate and/or confirm all the interactions that occur among the WSSV structural (envelope and tegument proteins VP51A, VP19, VP24, VP26 and VP28. We found that VP51A interacted directly not only with VP26 but also with VP19 and VP24. VP51A, VP19 and VP24 were also shown to have an affinity for self-interaction. Chemical cross-linking assays showed that these three self-interacting proteins could occur as dimers. CONCLUSIONS: From our present results in conjunction with other previously established interactions we construct a 3D model in which VP24 acts as a core protein that directly associates with VP26, VP28, VP38A, VP51A and WSV010 to form a membrane-associated protein complex. VP19 and VP37 are attached to this complex via association with VP51A and VP28, respectively. Through the VP26-VP51C interaction this envelope complex is anchored to the nucleocapsid, which is made of layers of rings formed by VP664. A 3D model of the nucleocapsid and the surrounding outer membrane is presented.

Visualizing the complex functions and mechanisms of the anaphase promoting complex/cyclosome (APC/C)

Science.gov (United States)

Alfieri, Claudio; Zhang, Suyang

2017-01-01

The anaphase promoting complex or cyclosome (APC/C) is a large multi-subunit E3 ubiquitin ligase that orchestrates cell cycle progression by mediating the degradation of important cell cycle regulators. During the two decades since its discovery, much has been learnt concerning its role in recognizing and ubiquitinating specific proteins in a cell-cycle-dependent manner, the mechanisms governing substrate specificity, the catalytic process of assembling polyubiquitin chains on its target proteins, and its regulation by phosphorylation and the spindle assembly checkpoint. The past few years have witnessed significant progress in understanding the quantitative mechanisms underlying these varied APC/C functions. This review integrates the overall functions and properties of the APC/C with mechanistic insights gained from recent cryo-electron microscopy (cryo-EM) studies of reconstituted human APC/C complexes. PMID:29167309

The Fanconi anemia protein FANCF forms a nuclear complex with FANCA, FANCC and FANCG.

Science.gov (United States)

de Winter, J P; van der Weel, L; de Groot, J; Stone, S; Waisfisz, Q; Arwert, F; Scheper, R J; Kruyt, F A; Hoatlin, M E; Joenje, H

2000-11-01

Fanconi anemia (FA) is a chromosomal instability syndrome associated with a strong predisposition to cancer, particularly acute myeloid leukemia and squamous cell carcinoma. At the cellular level, FA is characterized by spontaneous chromosomal breakage and a unique hypersensitivity to DNA cross-linking agents. Complementation analysis has indicated that at least seven distinct genes are involved in the pathogenesis of FA. Despite the identification of four of these genes (FANCA, FANCC, FANCF and FANCG), the nature of the 'FA pathway' has remained enigmatic, as the FA proteins lack sequence homologies or motifs that could point to a molecular function. To further define this pathway, we studied the subcellular localizations and mutual interactions of the FA proteins, including the recently identified FANCF protein, in human lymphoblasts. FANCF was found predominantly in the nucleus, where it complexes with FANCA, FANCC and FANCG. These interactions were detected in wild-type and FA-D lymphoblasts, but not in lymphoblasts of other FA complementation groups. This implies that each of the FA proteins, except FANCD, is required for these complexes to form. Similarly, we show that the interaction between FANCA and FANCC is restricted to wild-type and FA-D cells. Furthermore, we document the subcellular localization of FANCA and the FANCA/FANCG complex in all FA complementation groups. Our results, along with published data, culminate in a model in which a multi-protein FA complex serves a nuclear function to maintain genomic integrity.

FamPlex: a resource for entity recognition and relationship resolution of human protein families and complexes in biomedical text mining.

Science.gov (United States)

Bachman, John A; Gyori, Benjamin M; Sorger, Peter K

2018-06-28

For automated reading of scientific publications to extract useful information about molecular mechanisms it is critical that genes, proteins and other entities be correctly associated with uniform identifiers, a process known as named entity linking or "grounding." Correct grounding is essential for resolving relationships among mined information, curated interaction databases, and biological datasets. The accuracy of this process is largely dependent on the availability of machine-readable resources associating synonyms and abbreviations commonly found in biomedical literature with uniform identifiers. In a task involving automated reading of ∼215,000 articles using the REACH event extraction software we found that grounding was disproportionately inaccurate for multi-protein families (e.g., "AKT") and complexes with multiple subunits (e.g."NF- κB"). To address this problem we constructed FamPlex, a manually curated resource defining protein families and complexes as they are commonly encountered in biomedical text. In FamPlex the gene-level constituents of families and complexes are defined in a flexible format allowing for multi-level, hierarchical membership. To create FamPlex, text strings corresponding to entities were identified empirically from literature and linked manually to uniform identifiers; these identifiers were also mapped to equivalent entries in multiple related databases. FamPlex also includes curated prefix and suffix patterns that improve named entity recognition and event extraction. Evaluation of REACH extractions on a test corpus of ∼54,000 articles showed that FamPlex significantly increased grounding accuracy for families and complexes (from 15 to 71%). The hierarchical organization of entities in FamPlex also made it possible to integrate otherwise unconnected mechanistic information across families, subfamilies, and individual proteins. Applications of FamPlex to the TRIPS/DRUM reading system and the Biocreative VI Bioentity

Advances in Multi-Sensor Scanning and Visualization of Complex Plants: the Utmost Case of a Reactor Building

Science.gov (United States)

Hullo, J.-F.; Thibault, G.; Boucheny, C.

2015-02-01

In a context of increased maintenance operations and workers generational renewal, a nuclear owner and operator like Electricité de France (EDF) is interested in the scaling up of tools and methods of "as-built virtual reality" for larger buildings and wider audiences. However, acquisition and sharing of as-built data on a large scale (large and complex multi-floored buildings) challenge current scientific and technical capacities. In this paper, we first present a state of the art of scanning tools and methods for industrial plants with very complex architecture. Then, we introduce the inner characteristics of the multi-sensor scanning and visualization of the interior of the most complex building of a power plant: a nuclear reactor building. We introduce several developments that made possible a first complete survey of such a large building, from acquisition, processing and fusion of multiple data sources (3D laser scans, total-station survey, RGB panoramic, 2D floor plans, 3D CAD as-built models). In addition, we present the concepts of a smart application developed for the painless exploration of the whole dataset. The goal of this application is to help professionals, unfamiliar with the manipulation of such datasets, to take into account spatial constraints induced by the building complexity while preparing maintenance operations. Finally, we discuss the main feedbacks of this large experiment, the remaining issues for the generalization of such large scale surveys and the future technical and scientific challenges in the field of industrial "virtual reality".

NHL and RCGA Based Multi-Relational Fuzzy Cognitive Map Modeling for Complex Systems

Directory of Open Access Journals (Sweden)

Zhen Peng

2015-11-01

Full Text Available In order to model multi-dimensions and multi-granularities oriented complex systems, this paper firstly proposes a kind of multi-relational Fuzzy Cognitive Map (FCM to simulate the multi-relational system and its auto construct algorithm integrating Nonlinear Hebbian Learning (NHL and Real Code Genetic Algorithm (RCGA. The multi-relational FCM fits to model the complex system with multi-dimensions and multi-granularities. The auto construct algorithm can learn the multi-relational FCM from multi-relational data resources to eliminate human intervention. The Multi-Relational Data Mining (MRDM algorithm integrates multi-instance oriented NHL and RCGA of FCM. NHL is extended to mine the causal relationships between coarse-granularity concept and its fined-granularity concepts driven by multi-instances in the multi-relational system. RCGA is used to establish high-quality high-level FCM driven by data. The multi-relational FCM and the integrating algorithm have been applied in complex system of Mutagenesis. The experiment demonstrates not only that they get better classification accuracy, but it also shows the causal relationships among the concepts of the system.

A multi-directional rapidly exploring random graph (mRRG) for protein folding

KAUST Repository

Nath, Shuvra Kanti; Thomas, Shawna; Ekenna, Chinwe; Amato, Nancy M.

2012-01-01

Modeling large-scale protein motions, such as those involved in folding and binding interactions, is crucial to better understanding not only how proteins move and interact with other molecules but also how proteins misfold, thus causing many devastating diseases. Robotic motion planning algorithms, such as Rapidly Exploring Random Trees (RRTs), have been successful in simulating protein folding pathways. Here, we propose a new multi-directional Rapidly Exploring Random Graph (mRRG) specifically tailored for proteins. Unlike traditional RRGs which only expand a parent conformation in a single direction, our strategy expands the parent conformation in multiple directions to generate new samples. Resulting samples are connected to the parent conformation and its nearest neighbors. By leveraging multiple directions, mRRG can model the protein motion landscape with reduced computational time compared to several other robotics-based methods for small to moderate-sized proteins. Our results on several proteins agree with experimental hydrogen out-exchange, pulse-labeling, and F-value analysis. We also show that mRRG covers the conformation space better as compared to the other computation methods. Copyright © 2012 ACM.

Olfactory receptor signaling is regulated by the post-synaptic density 95, Drosophila discs large, zona-occludens 1 (PDZ) scaffold multi-PDZ domain protein 1.

LENUS (Irish Health Repository)

Dooley, Ruth

2009-12-01

The unique ability of mammals to detect and discriminate between thousands of different odorant molecules is governed by the diverse array of olfactory receptors expressed by olfactory sensory neurons in the nasal epithelium. Olfactory receptors consist of seven transmembrane domain G protein-coupled receptors and comprise the largest gene superfamily in the mammalian genome. We found that approximately 30% of olfactory receptors possess a classical post-synaptic density 95, Drosophila discs large, zona-occludens 1 (PDZ) domain binding motif in their C-termini. PDZ domains have been established as sites for protein-protein interaction and play a central role in organizing diverse cell signaling assemblies. In the present study, we show that multi-PDZ domain protein 1 (MUPP1) is expressed in the apical compartment of olfactory sensory neurons. Furthermore, on heterologous co-expression with olfactory sensory neurons, MUPP1 was shown to translocate to the plasma membrane. We found direct interaction of PDZ domains 1 + 2 of MUPP1 with the C-terminus of olfactory receptors in vitro. Moreover, the odorant-elicited calcium response of OR2AG1 showed a prolonged decay in MUPP1 small interfering RNA-treated cells. We have therefore elucidated the first building blocks of the putative \\'olfactosome\\

Dynamics in electron transfer protein complexes

OpenAIRE

Bashir, Qamar

2010-01-01

Recent studies have provided experimental evidence for the existence of an encounter complex, a transient intermediate in the formation of protein complexes. We have used paramagnetic relaxation enhancement NMR spectroscopy in combination with Monte Carlo simulations to characterize and visualize the ensemble of encounter orientations in the short-lived electron transfer complex of yeast Cc and CcP. The complete conformational space sampled by the protein molecules during the dynamic part of ...

Fast and Accurate Identification of Cross-Linked Peptides for the Structural Analysis of Large Protein Complexes and Elucidation of Interaction Networks. / Tahir, Salman; Bukowski-Wills, Jimi-Carlo; Rasmussen, Morten; Rappsilber, Juri

DEFF Research Database (Denmark)

Rasmussen, Morten

to investigate protein structure and protein-protein interactions. When applied to single proteins or small purified protein complexes, this methodology works well. However certain challenges arise when applied to more complex samples. One of the main problems is the combinatorial increase in the search space...... simplify a spectrum because we remove all peaks that are accounted for by the fragmentation of peptide one. This approach is highly sensitive and scales well as revealed by searching our data of synthetic cross-links against a large sequence database. Currently, against a protein database of >1300 proteins...... a spectrum is searched in 0.35 seconds - a vast improvement when compared to the exhaustive search method of combining every potential cross-link for each spectrum(60 hours). In fact the search time is comparable, if not better, than existing linear search engines. Furthermore, we auto-validate the results...

Ubiquitin fusion constructs allow the expression and purification of multi-KOW domain complexes of the Saccharomyces cerevisiae transcription elongation factor Spt4/5.

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Blythe, Amanda; Gunasekara, Sanjika; Walshe, James; Mackay, Joel P; Hartzog, Grant A; Vrielink, Alice

2014-08-01

Spt4/5 is a hetero-dimeric transcription elongation factor that can both inhibit and promote transcription elongation by RNA polymerase II (RNAPII). However, Spt4/5's mechanism of action remains elusive. Spt5 is an essential protein and the only universally-conserved RNAP-associated transcription elongation factor. The protein contains multiple Kyrpides, Ouzounis and Woese (KOW) domains. These domains, in other proteins, are thought to bind RNA although there is little direct evidence in the literature to support such a function in Spt5. This could be due, at least in part, to difficulties in expressing and purifying recombinant Spt5. When expressed in Escherichia coli (E. coli), Spt5 is innately insoluble. Here we report a new approach for the successful expression and purification of milligram quantities of three different multi-KOW domain complexes of Saccharomyces cerevisiae Spt4/5 for use in future functional studies. Using the E. coli strain Rosetta2 (DE3) we have developed strategies for co-expression of Spt4 and multi-KOW domain Spt5 complexes from the bi-cistronic pET-Duet vector. In a second strategy, Spt4/5 was expressed via co-transformation of Spt4 in the vector pET-M11 with Spt5 ubiquitin fusion constructs in the vector pHUE. We characterized the multi-KOW domain Spt4/5 complexes by Western blot, limited proteolysis, circular dichroism, SDS-PAGE and size exclusion chromatography-multiangle light scattering and found that the proteins are folded with a Spt4:Spt5 hetero-dimeric stoichiometry of 1:1. These expression constructs encompass a larger region of Spt5 than has previously been reported, and will provide the opportunity to elucidate the biological function of the multi-KOW containing Spt5. Copyright © 2014 Elsevier Inc. All rights reserved.

Consistent two-dimensional visualization of protein-ligand complex series

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Stierand Katrin

2011-06-01

Full Text Available Abstract Background The comparative two-dimensional graphical representation of protein-ligand complex series featuring different ligands bound to the same active site offers a quick insight in their binding mode differences. In comparison to arbitrary orientations of the residue molecules in the individual complex depictions a consistent placement improves the legibility and comparability within the series. The automatic generation of such consistent layouts offers the possibility to apply it to large data sets originating from computer-aided drug design methods. Results We developed a new approach, which automatically generates a consistent layout of interacting residues for a given series of complexes. Based on the structural three-dimensional input information, a global two-dimensional layout for all residues of the complex ensemble is computed. The algorithm incorporates the three-dimensional adjacencies of the active site residues in order to find an universally valid circular arrangement of the residues around the ligand. Subsequent to a two-dimensional ligand superimposition step, a global placement for each residue is derived from the set of already placed ligands. The method generates high-quality layouts, showing mostly overlap-free solutions with molecules which are displayed as structure diagrams providing interaction information in atomic detail. Application examples document an improved legibility compared to series of diagrams whose layouts are calculated independently from each other. Conclusions The presented method extends the field of complex series visualizations. A series of molecules binding to the same protein active site is drawn in a graphically consistent way. Compared to existing approaches these drawings substantially simplify the visual analysis of large compound series.

Multi-level machine learning prediction of protein–protein interactions in Saccharomyces cerevisiae

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Julian Zubek

2015-07-01

Full Text Available Accurate identification of protein–protein interactions (PPI is the key step in understanding proteins’ biological functions, which are typically context-dependent. Many existing PPI predictors rely on aggregated features from protein sequences, however only a few methods exploit local information about specific residue contacts. In this work we present a two-stage machine learning approach for prediction of protein–protein interactions. We start with the carefully filtered data on protein complexes available for Saccharomyces cerevisiae in the Protein Data Bank (PDB database. First, we build linear descriptions of interacting and non-interacting sequence segment pairs based on their inter-residue distances. Secondly, we train machine learning classifiers to predict binary segment interactions for any two short sequence fragments. The final prediction of the protein–protein interaction is done using the 2D matrix representation of all-against-all possible interacting sequence segments of both analysed proteins. The level-I predictor achieves 0.88 AUC for micro-scale, i.e., residue-level prediction. The level-II predictor improves the results further by a more complex learning paradigm. We perform 30-fold macro-scale, i.e., protein-level cross-validation experiment. The level-II predictor using PSIPRED-predicted secondary structure reaches 0.70 precision, 0.68 recall, and 0.70 AUC, whereas other popular methods provide results below 0.6 threshold (recall, precision, AUC. Our results demonstrate that multi-scale sequence features aggregation procedure is able to improve the machine learning results by more than 10% as compared to other sequence representations. Prepared datasets and source code for our experimental pipeline are freely available for download from: http://zubekj.github.io/mlppi/ (open source Python implementation, OS independent.

Brownian dynamics of a protein-polymer chain complex in a solid-state nanopore

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Wells, Craig C.; Melnikov, Dmitriy V.; Gracheva, Maria E.

2017-08-01

We study the movement of a polymer attached to a large protein inside a nanopore in a thin silicon dioxide membrane submerged in an electrolyte solution. We use Brownian dynamics to describe the motion of a negatively charged polymer chain of varying lengths attached to a neutral protein modeled as a spherical bead with a radius larger than that of the nanopore, allowing the chain to thread the nanopore but preventing it from translocating. The motion of the protein-polymer complex within the pore is also compared to that of a freely translocating polymer. Our results show that the free polymer's standard deviations in the direction normal to the pore axis is greater than that of the protein-polymer complex. We find that restrictions imposed by the protein, bias, and neighboring chain segments aid in controlling the position of the chain in the pore. Understanding the behavior of the protein-polymer chain complex may lead to methods that improve molecule identification by increasing the resolution of ionic current measurements.

Evaluation of multiple protein docking structures using correctly predicted pairwise subunits

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Esquivel-Rodríguez Juan

2012-03-01

Full Text Available Abstract Background Many functionally important proteins in a cell form complexes with multiple chains. Therefore, computational prediction of multiple protein complexes is an important task in bioinformatics. In the development of multiple protein docking methods, it is important to establish a metric for evaluating prediction results in a reasonable and practical fashion. However, since there are only few works done in developing methods for multiple protein docking, there is no study that investigates how accurate structural models of multiple protein complexes should be to allow scientists to gain biological insights. Methods We generated a series of predicted models (decoys of various accuracies by our multiple protein docking pipeline, Multi-LZerD, for three multi-chain complexes with 3, 4, and 6 chains. We analyzed the decoys in terms of the number of correctly predicted pair conformations in the decoys. Results and conclusion We found that pairs of chains with the correct mutual orientation exist even in the decoys with a large overall root mean square deviation (RMSD to the native. Therefore, in addition to a global structure similarity measure, such as the global RMSD, the quality of models for multiple chain complexes can be better evaluated by using the local measurement, the number of chain pairs with correct mutual orientation. We termed the fraction of correctly predicted pairs (RMSD at the interface of less than 4.0Å as fpair and propose to use it for evaluation of the accuracy of multiple protein docking.

Protein (multi-)location prediction: utilizing interdependencies via a generative model.

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Simha, Ramanuja; Briesemeister, Sebastian; Kohlbacher, Oliver; Shatkay, Hagit

2015-06-15

Proteins are responsible for a multitude of vital tasks in all living organisms. Given that a protein's function and role are strongly related to its subcellular location, protein location prediction is an important research area. While proteins move from one location to another and can localize to multiple locations, most existing location prediction systems assign only a single location per protein. A few recent systems attempt to predict multiple locations for proteins, however, their performance leaves much room for improvement. Moreover, such systems do not capture dependencies among locations and usually consider locations as independent. We hypothesize that a multi-location predictor that captures location inter-dependencies can improve location predictions for proteins. We introduce a probabilistic generative model for protein localization, and develop a system based on it-which we call MDLoc-that utilizes inter-dependencies among locations to predict multiple locations for proteins. The model captures location inter-dependencies using Bayesian networks and represents dependency between features and locations using a mixture model. We use iterative processes for learning model parameters and for estimating protein locations. We evaluate our classifier MDLoc, on a dataset of single- and multi-localized proteins derived from the DBMLoc dataset, which is the most comprehensive protein multi-localization dataset currently available. Our results, obtained by using MDLoc, significantly improve upon results obtained by an initial simpler classifier, as well as on results reported by other top systems. MDLoc is available at: http://www.eecis.udel.edu/∼compbio/mdloc. © The Author 2015. Published by Oxford University Press.

AMMOS2: a web server for protein-ligand-water complexes refinement via molecular mechanics.

Science.gov (United States)

Labbé, Céline M; Pencheva, Tania; Jereva, Dessislava; Desvillechabrol, Dimitri; Becot, Jérôme; Villoutreix, Bruno O; Pajeva, Ilza; Miteva, Maria A

2017-07-03

AMMOS2 is an interactive web server for efficient computational refinement of protein-small organic molecule complexes. The AMMOS2 protocol employs atomic-level energy minimization of a large number of experimental or modeled protein-ligand complexes. The web server is based on the previously developed standalone software AMMOS (Automatic Molecular Mechanics Optimization for in silico Screening). AMMOS utilizes the physics-based force field AMMP sp4 and performs optimization of protein-ligand interactions at five levels of flexibility of the protein receptor. The new version 2 of AMMOS implemented in the AMMOS2 web server allows the users to include explicit water molecules and individual metal ions in the protein-ligand complexes during minimization. The web server provides comprehensive analysis of computed energies and interactive visualization of refined protein-ligand complexes. The ligands are ranked by the minimized binding energies allowing the users to perform additional analysis for drug discovery or chemical biology projects. The web server has been extensively tested on 21 diverse protein-ligand complexes. AMMOS2 minimization shows consistent improvement over the initial complex structures in terms of minimized protein-ligand binding energies and water positions optimization. The AMMOS2 web server is freely available without any registration requirement at the URL: http://drugmod.rpbs.univ-paris-diderot.fr/ammosHome.php. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Mapping multivalency and differential affinities within large intrinsically disordered protein complexes with segmental motion analysis.

Science.gov (United States)

Milles, Sigrid; Lemke, Edward A

2014-07-07

Intrinsically disordered proteins (IDPs) can bind to multiple interaction partners. Numerous binding regions in the IDP that act in concert through complex cooperative effects facilitate such interactions, but complicate studying IDP complexes. To address this challenge we developed a combined fluorescence correlation and time-resolved polarization spectroscopy approach to study the binding properties of the IDP nucleoporin153 (Nup153) to nuclear transport receptors (NTRs). The detection of segmental backbone mobility of Nup153 within the unperturbed complex provided a readout of local, region-specific binding properties that are usually masked in measurements of the whole IDP. The binding affinities of functionally and structurally diverse NTRs to distinct regions of Nup153 can differ by orders of magnitudes-a result with implications for the diversity of transport routes in nucleocytoplasmic transport. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Complexity optimization and high-throughput low-latency hardware implementation of a multi-electrode spike-sorting algorithm.

Science.gov (United States)

Dragas, Jelena; Jackel, David; Hierlemann, Andreas; Franke, Felix

2015-03-01

Reliable real-time low-latency spike sorting with large data throughput is essential for studies of neural network dynamics and for brain-machine interfaces (BMIs), in which the stimulation of neural networks is based on the networks' most recent activity. However, the majority of existing multi-electrode spike-sorting algorithms are unsuited for processing high quantities of simultaneously recorded data. Recording from large neuronal networks using large high-density electrode sets (thousands of electrodes) imposes high demands on the data-processing hardware regarding computational complexity and data transmission bandwidth; this, in turn, entails demanding requirements in terms of chip area, memory resources and processing latency. This paper presents computational complexity optimization techniques, which facilitate the use of spike-sorting algorithms in large multi-electrode-based recording systems. The techniques are then applied to a previously published algorithm, on its own, unsuited for large electrode set recordings. Further, a real-time low-latency high-performance VLSI hardware architecture of the modified algorithm is presented, featuring a folded structure capable of processing the activity of hundreds of neurons simultaneously. The hardware is reconfigurable “on-the-fly” and adaptable to the nonstationarities of neuronal recordings. By transmitting exclusively spike time stamps and/or spike waveforms, its real-time processing offers the possibility of data bandwidth and data storage reduction.

Protein (multi-)location prediction: utilizing interdependencies via a generative model

Science.gov (United States)

Shatkay, Hagit

2015-01-01

Motivation: Proteins are responsible for a multitude of vital tasks in all living organisms. Given that a protein’s function and role are strongly related to its subcellular location, protein location prediction is an important research area. While proteins move from one location to another and can localize to multiple locations, most existing location prediction systems assign only a single location per protein. A few recent systems attempt to predict multiple locations for proteins, however, their performance leaves much room for improvement. Moreover, such systems do not capture dependencies among locations and usually consider locations as independent. We hypothesize that a multi-location predictor that captures location inter-dependencies can improve location predictions for proteins. Results: We introduce a probabilistic generative model for protein localization, and develop a system based on it—which we call MDLoc—that utilizes inter-dependencies among locations to predict multiple locations for proteins. The model captures location inter-dependencies using Bayesian networks and represents dependency between features and locations using a mixture model. We use iterative processes for learning model parameters and for estimating protein locations. We evaluate our classifier MDLoc, on a dataset of single- and multi-localized proteins derived from the DBMLoc dataset, which is the most comprehensive protein multi-localization dataset currently available. Our results, obtained by using MDLoc, significantly improve upon results obtained by an initial simpler classifier, as well as on results reported by other top systems. Availability and implementation: MDLoc is available at: http://www.eecis.udel.edu/∼compbio/mdloc. Contact: shatkay@udel.edu. PMID:26072505

Universal correlators for multi-arc complex matrix models

International Nuclear Information System (INIS)

Akemann, G.

1997-01-01

The correlation functions of the multi-arc complex matrix model are shown to be universal for any finite number of arcs. The universality classes are characterized by the support of the eigenvalue density and are conjectured to fall into the same classes as the ones recently found for the Hermitian model. This is explicitly shown to be true for the case of two arcs, apart from the known result for one arc. The basic tool is the iterative solution of the loop equation for the complex matrix model with multiple arcs, which provides all multi-loop correlators up to an arbitrary genus. Explicit results for genus one are given for any number of arcs. The two-arc solution is investigated in detail, including the double-scaling limit. In addition universal expressions for the string susceptibility are given for both the complex and Hermitian model. (orig.)

Integral and peripheral association of proteins and protein complexes with Yersinia pestis inner and outer membranes

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Bunai Christine L

2009-02-01

Full Text Available Abstract Yersinia pestis proteins were sequentially extracted from crude membranes with a high salt buffer (2.5 M NaBr, an alkaline solution (180 mM Na2CO3, pH 11.3 and membrane denaturants (8 M urea, 2 M thiourea and 1% amidosulfobetaine-14. Separation of proteins by 2D gel electrophoresis was followed by identification of more than 600 gene products by MS. Data from differential 2D gel display experiments, comparing protein abundances in cytoplasmic, periplasmic and all three membrane fractions, were used to assign proteins found in the membrane fractions to three protein categories: (i integral membrane proteins and peripheral membrane proteins with low solubility in aqueous solutions (220 entries; (ii peripheral membrane proteins with moderate to high solubility in aqueous solutions (127 entries; (iii cytoplasmic or ribosomal membrane-contaminating proteins (80 entries. Thirty-one proteins were experimentally associated with the outer membrane (OM. Circa 50 proteins thought to be part of membrane-localized, multi-subunit complexes were identified in high Mr fractions of membrane extracts via size exclusion chromatography. This data supported biologically meaningful assignments of many proteins to the membrane periphery. Since only 32 inner membrane (IM proteins with two or more predicted transmembrane domains (TMDs were profiled in 2D gels, we resorted to a proteomic analysis by 2D-LC-MS/MS. Ninety-four additional IM proteins with two or more TMDs were identified. The total number of proteins associated with Y. pestis membranes increased to 456 and included representatives of all six β-barrel OM protein families and 25 distinct IM transporter families.

Intermolecular detergent-membrane protein noes for the characterization of the dynamics of membrane protein-detergent complexes.

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Eichmann, Cédric; Orts, Julien; Tzitzilonis, Christos; Vögeli, Beat; Smrt, Sean; Lorieau, Justin; Riek, Roland

2014-12-11

The interaction between membrane proteins and lipids or lipid mimetics such as detergents is key for the three-dimensional structure and dynamics of membrane proteins. In NMR-based structural studies of membrane proteins, qualitative analysis of intermolecular nuclear Overhauser enhancements (NOEs) or paramagnetic resonance enhancement are used in general to identify the transmembrane segments of a membrane protein. Here, we employed a quantitative characterization of intermolecular NOEs between (1)H of the detergent and (1)H(N) of (2)H-perdeuterated, (15)N-labeled α-helical membrane protein-detergent complexes following the exact NOE (eNOE) approach. Structural considerations suggest that these intermolecular NOEs should show a helical-wheel-type behavior along a transmembrane helix or a membrane-attached helix within a membrane protein as experimentally demonstrated for the complete influenza hemagglutinin fusion domain HAfp23. The partial absence of such a NOE pattern along the amino acid sequence as shown for a truncated variant of HAfp23 and for the Escherichia coli inner membrane protein YidH indicates the presence of large tertiary structure fluctuations such as an opening between helices or the presence of large rotational dynamics of the helices. Detergent-protein NOEs thus appear to be a straightforward probe for a qualitative characterization of structural and dynamical properties of membrane proteins embedded in detergent micelles.

A Variable Stiffness Analysis Model for Large Complex Thin-Walled Guide Rail

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Wang Xiaolong

2016-01-01

Full Text Available Large complex thin-walled guide rail has complicated structure and no uniform low rigidity. The traditional cutting simulations are time consuming due to huge computation especially in large workpiece. To solve these problems, a more efficient variable stiffness analysis model has been propose, which can obtain quantitative stiffness value of the machining surface. Applying simulate cutting force in sampling points using finite element analysis software ABAQUS, the single direction variable stiffness rule can be obtained. The variable stiffness matrix has been propose by analyzing multi-directions coupling variable stiffness rule. Combining with the three direction cutting force value, the reasonability of existing processing parameters can be verified and the optimized cutting parameters can be designed.

Exploration of the dynamic properties of protein complexes predicted from spatially constrained protein-protein interaction networks.

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Eric A Yen

2014-05-01

Full Text Available Protein complexes are not static, but rather highly dynamic with subunits that undergo 1-dimensional diffusion with respect to each other. Interactions within protein complexes are modulated through regulatory inputs that alter interactions and introduce new components and deplete existing components through exchange. While it is clear that the structure and function of any given protein complex is coupled to its dynamical properties, it remains a challenge to predict the possible conformations that complexes can adopt. Protein-fragment Complementation Assays detect physical interactions between protein pairs constrained to ≤8 nm from each other in living cells. This method has been used to build networks composed of 1000s of pair-wise interactions. Significantly, these networks contain a wealth of dynamic information, as the assay is fully reversible and the proteins are expressed in their natural context. In this study, we describe a method that extracts this valuable information in the form of predicted conformations, allowing the user to explore the conformational landscape, to search for structures that correlate with an activity state, and estimate the abundance of conformations in the living cell. The generator is based on a Markov Chain Monte Carlo simulation that uses the interaction dataset as input and is constrained by the physical resolution of the assay. We applied this method to an 18-member protein complex composed of the seven core proteins of the budding yeast Arp2/3 complex and 11 associated regulators and effector proteins. We generated 20,480 output structures and identified conformational states using principle component analysis. We interrogated the conformation landscape and found evidence of symmetry breaking, a mixture of likely active and inactive conformational states and dynamic exchange of the core protein Arc15 between core and regulatory components. Our method provides a novel tool for prediction and

Structural entanglements in protein complexes

Science.gov (United States)

Zhao, Yani; Chwastyk, Mateusz; Cieplak, Marek

2017-06-01

We consider multi-chain protein native structures and propose a criterion that determines whether two chains in the system are entangled or not. The criterion is based on the behavior observed by pulling at both termini of each chain simultaneously in the two chains. We have identified about 900 entangled systems in the Protein Data Bank and provided a more detailed analysis for several of them. We argue that entanglement enhances the thermodynamic stability of the system but it may have other functions: burying the hydrophobic residues at the interface and increasing the DNA or RNA binding area. We also study the folding and stretching properties of the knotted dimeric proteins MJ0366, YibK, and bacteriophytochrome. These proteins have been studied theoretically in their monomeric versions so far. The dimers are seen to separate on stretching through the tensile mechanism and the characteristic unraveling force depends on the pulling direction.

High-resolution diffraction from crystals of a membrane-protein complex: bacterial outer membrane protein OmpC complexed with the antibacterial eukaryotic protein lactoferrin

International Nuclear Information System (INIS)

Sundara Baalaji, N.; Acharya, K. Ravi; Singh, T. P.; Krishnaswamy, S.

2005-01-01

Crystals of the complex formed between the bacterial membrane protein OmpC and the antibacterial protein lactoferrin suitable for high-resolution structure determination have been obtained. The crystals belong to the hexagonal space group P6, with unit-cell parameters a = b = 116.3, c = 152.4 Å. Crystals of the complex formed between the outer membrane protein OmpC from Escherichia coli and the eukaryotic antibacterial protein lactoferrin from Camelus dromedarius (camel) have been obtained using a detergent environment. Initial data processing suggests that the crystals belong to the hexagonal space group P6, with unit-cell parameters a = b = 116.3, c = 152.4 Å, α = β = 90, γ = 120°. This indicated a Matthews coefficient (V M ) of 3.3 Å 3 Da −1 , corresponding to a possible molecular complex involving four molecules of lactoferrin and two porin trimers in the unit cell (4832 amino acids; 533.8 kDa) with 63% solvent content. A complete set of diffraction data was collected to 3 Å resolution at 100 K. Structure determination by molecular replacement is in progress. Structural study of this first surface-exposed membrane-protein complex with an antibacterial protein will provide insights into the mechanism of action of OmpC as well as lactoferrin

Phylogenetic and structural analysis of centromeric DNA and kinetochore proteins

OpenAIRE

Meraldi, Patrick; McAinsh, Andrew D; Rheinbay, Esther; Sorger, Peter K

2006-01-01

Background: Kinetochores are large multi-protein structures that assemble on centromeric DNA (CEN DNA) and mediate the binding of chromosomes to microtubules. Comprising 125 base-pairs of CEN DNA and 70 or more protein components, Saccharomyces cerevisiae kinetochores are among the best understood. In contrast, most fungal, plant and animal cells assemble kinetochores on CENs that are longer and more complex, raising the question of whether kinetochore architecture has been conserved through ...

A new look on protein-polyphenol complexation during honey storage: is this a random or organized event with the help of dirigent-like proteins?

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Katrina Brudzynski

Full Text Available Honey storage initiates melanoidin formation that involves a cascade of seemingly unguided redox reactions between amino acids/proteins, reducing sugars and polyphenols. In the process, high molecular weight protein-polyphenol complexes are formed, but the mechanism involved remains unknown. The objective of this study was twofold: to determine quantitative and qualitative changes in proteins in honeys stored for prolonged times and in different temperatures and to relate these changes to the formation of protein-polyphenol complexes. Six -month storage decreased the protein content by 46.7% in all tested honeys (t-test, p<0.002 with the rapid reduction occurring during the first three month. The changes in protein levels coincided with alterations in molecular size and net charge of proteins on SDS -PAGE. Electro-blotted proteins reacted with a quinone-specific nitro blue tetrazolium (NBT on nitrocellulose membranes indicating that quinones derived from oxidized polyphenols formed covalent bonds with proteins. Protein-polyphenol complexes isolated by size-exclusion chromatography differed in size and stoichiometry and fall into two categories: (a high molecular weight complexes (230-180 kDa enriched in proteins but possessing a limited reducing activity toward the NBT and (b lower molecular size complexes (110-85 kDa enriched in polyphenols but strongly reducing the dye. The variable stoichiometry suggest that the large, "protein-type" complexes were formed by protein cross-linking, while in the smaller, "polyphenol-type" complexes polyphenols were first polymerized prior to protein binding. Quinones preferentially bound a 31 kDa protein which, by the electrospray quadrupole time of flight mass spectrometry (ESI-Qtof-MS analysis, showed homology to dirigent-like proteins known for assisting in radical coupling and polymerization of phenolic compounds. These findings provide a new look on protein-polyphenol interaction in honey where the

DNA-protein complexes induced by chromate and other carcinogens

International Nuclear Information System (INIS)

Costa, M.

1991-01-01

DNA-protein complexes induced in intact Chinese hamster ovary cells by chromate have been isolated, analyzed, and compared with those induced by cis-platinum, ultraviolet light, and formaldehyde. Actin has been identified as one of the major proteins complexed to DNA by chromate based upon its molecular weight, isoelectric point, positive reaction with an actin polyclonal antibody, and proteolytic mapping. Chromate and cis-platinum both complex proteins of similar molecular weight and isoelectric point, positive reaction with an actin polyclonal antibody, and proteolytic mapping. Chromate and cis-platinum both complex proteins of similar molecular weight and isoelectric points, and these complexes can be disrupted by chelating agents and sulfhydryl reducing agents, suggesting that the metal itself is participating in binding rather than having a catalytic or indirect role (i.e., oxygen radicals). In contrast, formaldehyde complexed histones to the DNA, and these complexes were not disrupted by chelating or reducing agents. An antiserum raised to chromate-induced DNA-protein complexes reacted primarily with 97,000 kDa protein that did not silver stain. Slot blots, as well as Western blots, were used to detect formation of p97 DNA crosslinks. This protein was complexed to the DNA by all four agents studied

Cooperation of TOM and TIM23 complexes during translocation of proteins into mitochondria.

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Waegemann, Karin; Popov-Čeleketić, Dušan; Neupert, Walter; Azem, Abdussalam; Mokranjac, Dejana

2015-03-13

Translocation of the majority of mitochondrial proteins from the cytosol into mitochondria requires the cooperation of TOM and TIM23 complexes in the outer and inner mitochondrial membranes. The molecular mechanisms underlying this cooperation remain largely unknown. Here, we present biochemical and genetic evidence that at least two contacts from the side of the TIM23 complex play an important role in TOM-TIM23 cooperation in vivo. Tim50, likely through its very C-terminal segment, interacts with Tom22. This interaction is stimulated by translocating proteins and is independent of any other TOM-TIM23 contact known so far. Furthermore, the exposure of Tim23 on the mitochondrial surface depends not only on its interaction with Tim50 but also on the dynamics of the TOM complex. Destabilization of the individual contacts reduces the efficiency of import of proteins into mitochondria and destabilization of both contacts simultaneously is not tolerated by yeast cells. We conclude that an intricate and coordinated network of protein-protein interactions involving primarily Tim50 and also Tim23 is required for efficient translocation of proteins across both mitochondrial membranes. Copyright © 2014 Elsevier Ltd. All rights reserved.

Multi-Morbidity in Hospitalised Older Patients: Who Are the Complex Elderly?

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Ruiz, Milagros; Bottle, Alex; Long, Susannah; Aylin, Paul

2015-01-01

No formal definition for the "complex elderly" exists; moreover, these older patients with high levels of multi-morbidity are not readily identified as such at point of hospitalisation, thus missing a valuable opportunity to manage the older patient appropriately within the hospital setting. To empirically identify the complex elderly patient based on degree of multi-morbidity. Retrospective observational study using administrative data. English hospitals during the financial year 2012-13. All admitted patients aged 65 years and over. By using exploratory analysis (correspondence analysis) we identify multi-morbidity groups based on 20 target conditions whose hospital prevalence was ≥ 1%. We examined a total of 2788900 hospital admissions. Multi-morbidity was highly prevalent, 62.8% had 2 or more of the targeted conditions while 4.7% had six or more. Multi-morbidity increased with age from 56% (65-69yr age-groups) up to 67% (80-84yr age-group). The average multi-morbidity was 3.2±1.2 (SD). Correspondence analysis revealed 3 distinct groups of older patients. Group 1 (multi-morbidity ≤2), associated with cancer and/or metastasis; Group 2 (multi-morbidity of 3, 4 or 5), associated with chronic pulmonary disease, lung disease, rheumatism and osteoporosis; finally Group 3 with the highest level of multi-morbidity (≥6) and associated with heart failure, cerebrovascular accident, diabetes, hypertension and myocardial infarction. By using widely available hospital administrative data, we propose patients in Groups 2 and 3 to be identified as the complex elderly. Identification of multi-morbidity patterns can help to predict the needs of the older patient and improve resource provision.

Multi-Morbidity in Hospitalised Older Patients: Who Are the Complex Elderly?

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Milagros Ruiz

Full Text Available No formal definition for the "complex elderly" exists; moreover, these older patients with high levels of multi-morbidity are not readily identified as such at point of hospitalisation, thus missing a valuable opportunity to manage the older patient appropriately within the hospital setting.To empirically identify the complex elderly patient based on degree of multi-morbidity.Retrospective observational study using administrative data.English hospitals during the financial year 2012-13.All admitted patients aged 65 years and over.By using exploratory analysis (correspondence analysis we identify multi-morbidity groups based on 20 target conditions whose hospital prevalence was ≥ 1%.We examined a total of 2788900 hospital admissions. Multi-morbidity was highly prevalent, 62.8% had 2 or more of the targeted conditions while 4.7% had six or more. Multi-morbidity increased with age from 56% (65-69yr age-groups up to 67% (80-84yr age-group. The average multi-morbidity was 3.2±1.2 (SD. Correspondence analysis revealed 3 distinct groups of older patients. Group 1 (multi-morbidity ≤2, associated with cancer and/or metastasis; Group 2 (multi-morbidity of 3, 4 or 5, associated with chronic pulmonary disease, lung disease, rheumatism and osteoporosis; finally Group 3 with the highest level of multi-morbidity (≥6 and associated with heart failure, cerebrovascular accident, diabetes, hypertension and myocardial infarction.By using widely available hospital administrative data, we propose patients in Groups 2 and 3 to be identified as the complex elderly. Identification of multi-morbidity patterns can help to predict the needs of the older patient and improve resource provision.

Expression of endogenous proteins in maize hybrids in a multi-location field trial in India.

Science.gov (United States)

Gutha, Linga R; Purushottam, Divakar; Veeramachaneni, Aruna; Tigulla, Sarita; Kodappully, Vikas; Enjala, Chandana; Rajput, Hitendrasinh; Anderson, Jennifer; Hong, Bonnie; Schmidt, Jean; Bagga, Shveta

2018-05-17

Genetically modified (GM) crops undergo large scale multi-location field trials to characterize agronomics, composition, and the concentration of newly expressed protein(s) [herein referred to as transgenic protein(s)]. The concentration of transgenic proteins in different plant tissues and across the developmental stages of the plant is considered in the safety assessment of GM crops. Reference or housekeeping proteins are expected to maintain a relatively stable expression pattern in healthy plants given their role in cellular functions. Understanding the effects of genotype, growth stage and location on the concentration of endogenous housekeeping proteins may provide insight into the contribution these factors could have on transgenic protein concentrations in GM crops. The concentrations of three endogenous proteins (actin, elongation factor 1-alpha, and glyceraldehyde 3-phosphate dehydrogenase) were measured in several different maize hybrids grown across multiple field locations over 2 years. Leaf samples were collected from healthy plants at three developmental stages across the growing seasons, and protein concentrations were quantified by indirect enzyme-linked immunosorbent assay (ELISA) for each protein. In general, the concentrations of these three endogenous proteins were relatively consistent across hybrid backgrounds, when compared within one growth stage and location (2-26%CV), whereas the concentrations of proteins in the same hybrid and growth stage across different locations were more variable (12-64%CV). In general, the protein concentrations in 2013 and 2014 show similar trends in variability. Some degree of variability in protein concentrations should be expected for both transgenic and endogenous plant-expressed proteins. In the case of GM crops, the potential variation in protein concentrations due to location effects is captured in the current model of multi-location field testing.

Design of Protein Multi-specificity Using an Independent Sequence Search Reduces the Barrier to Low Energy Sequences.

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Alexander M Sevy

2015-07-01

Full Text Available Computational protein design has found great success in engineering proteins for thermodynamic stability, binding specificity, or enzymatic activity in a 'single state' design (SSD paradigm. Multi-specificity design (MSD, on the other hand, involves considering the stability of multiple protein states simultaneously. We have developed a novel MSD algorithm, which we refer to as REstrained CONvergence in multi-specificity design (RECON. The algorithm allows each state to adopt its own sequence throughout the design process rather than enforcing a single sequence on all states. Convergence to a single sequence is encouraged through an incrementally increasing convergence restraint for corresponding positions. Compared to MSD algorithms that enforce (constrain an identical sequence on all states the energy landscape is simplified, which accelerates the search drastically. As a result, RECON can readily be used in simulations with a flexible protein backbone. We have benchmarked RECON on two design tasks. First, we designed antibodies derived from a common germline gene against their diverse targets to assess recovery of the germline, polyspecific sequence. Second, we design "promiscuous", polyspecific proteins against all binding partners and measure recovery of the native sequence. We show that RECON is able to efficiently recover native-like, biologically relevant sequences in this diverse set of protein complexes.

Complex Susceptibility Measurement Using Multi-frequency Slingram EMI Instrument

OpenAIRE

Simon , François Xavier; Tabbagh , Alain; Thiesson , Julien; Donati , J.C.; Sarris , A.

2014-01-01

International audience; Complex magnetic susceptibility is a well-known property both theoretically and experimentally. To achieve this measurement, different ways have been tested, like TDEM or multi-frequential measurement on soil sample. In this study we carry out the measurements by the use of a multi-frequential EMI Slingram instrument to collect data quickly and in-situ. The use of multi-frequency data is also a way to correct effects of the conductivity on the in-phase component and ef...

Ablation of whirlin long isoform disrupts the USH2 protein complex and causes vision and hearing loss.

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Jun Yang

2010-05-01

Full Text Available Mutations in whirlin cause either Usher syndrome type II (USH2, a deafness-blindness disorder, or nonsyndromic deafness. The molecular basis for the variable disease expression is unknown. We show here that only the whirlin long isoform, distinct from a short isoform by virtue of having two N-terminal PDZ domains, is expressed in the retina. Both long and short isoforms are expressed in the inner ear. The N-terminal PDZ domains of the long whirlin isoform mediates the formation of a multi-protein complex that includes usherin and VLGR1, both of which are also implicated in USH2. We localized this USH2 protein complex to the periciliary membrane complex (PMC in mouse photoreceptors that appears analogous to the frog periciliary ridge complex. The latter is proposed to play a role in photoreceptor protein trafficking through the connecting cilium. Mice carrying a targeted disruption near the N-terminus of whirlin manifest retinal and inner ear defects, reproducing the clinical features of human USH2 disease. This is in contrast to mice with mutations affecting the C-terminal portion of whirlin in which the phenotype is restricted to the inner ear. In mice lacking any one of the USH2 proteins, the normal localization of all USH2 proteins is disrupted, and there is evidence of protein destabilization. Taken together, our findings provide new insights into the pathogenic mechanism of Usher syndrome. First, the three USH2 proteins exist as an obligatory functional complex in vivo, and loss of one USH2 protein is functionally close to loss of all three. Second, defects in the three USH2 proteins share a common pathogenic process, i.e., disruption of the PMC. Third, whirlin mutations that ablate the N-terminal PDZ domains lead to Usher syndrome, but non-syndromic hearing loss will result if they are spared.

Biochemical characterization of native Usher protein complexes from a vesicular subfraction of tracheal epithelial cells.

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Zallocchi, Marisa; Sisson, Joseph H; Cosgrove, Dominic

2010-02-16

Usher syndrome is the major cause of deaf/blindness in the world. It is a genetic heterogeneous disorder, with nine genes already identified as causative for the disease. We noted expression of all known Usher proteins in bovine tracheal epithelial cells and exploited this system for large-scale biochemical analysis of Usher protein complexes. The dissected epithelia were homogenized in nondetergent buffer and sedimented on sucrose gradients. At least two complexes were evident after the first gradient: one formed by specific isoforms of CDH23, PCDH15, and VLGR-1 and a different one at the top of the gradient that included all of the Usher proteins and rab5, a transport vesicle marker. TEM analysis of these top fractions found them enriched in 100-200 nm vesicles, confirming a vesicular association of the Usher complex(es). Immunoisolation of these vesicles confirmed some of the associations already predicted and identified novel interactions. When the vesicles are lysed in the presence of phenylbutyrate, most of the Usher proteins cosediment into the gradient at a sedimentation coefficient of approximately 50 S, correlating with a predicted molecular mass of 2 x 10(6) Da. Although it is still unclear whether there is only one complex or several independent complexes that are trafficked within distinct vesicular pools, this work shows for the first time that native Usher protein complexes occur in vivo. This complex(es) is present primarily in transport vesicles at the apical pole of tracheal epithelial cells, predicting that Usher proteins may be directionally transported as complexes in hair cells and photoreceptors.

BIOCHEMICAL CHARACTERIZATION OF NATIVE USHER PROTEIN COMPLEXES FROM A VESICULAR SUBFRACTION OF TRACHEAL EPITHELIAL CELLS†

Science.gov (United States)

Zallocchi, Marisa; Sisson, Joseph H.; Cosgrove, Dominic

2010-01-01

Usher syndrome is the major cause of deaf/blindness in the world. It is a genetic heterogeneous disorder, with nine genes already identified as causative for the disease. We noted expression of all known Usher proteins in bovine tracheal epithelial cells, and exploited this system for large-scale biochemical analysis of Usher protein complexes. The dissected epithelia were homogenized in non-detergent buffer, and sedimented on sucrose gradients. At least two complexes were evident after the first gradient: one formed by specific isoforms of CDH23, PCDH15 and VLGR-1, and a different one at the top of the gradient that included all the Usher proteins and rab5, a transport vesicle marker. TEM analysis of these top fractions found them enriched in 100–200 nm vesicles, confirming a vesicular association of the Usher complex(es). Immunoisolation of these vesicles confirmed some of the associations already predicted and identified novel interactions. When the vesicles are lysed in the presence of phenylbutyrate, most of the Usher proteins co-sediment into the gradient at a sedimentation coefficient of approximately 50S, correlating with a predicted molecular mass of 2 × 106 Daltons. Although it is still unclear whether there is only one complex or several independent complexes that are trafficked within distinct vesicular pools, this work shows for the first time that native Usher proteins complexes occur in vivo. This complex(es) is present primarily in transport vesicles at the apical pole of tracheal epithelial cells, predicting that Usher proteins may be directionally transported as complexes in hair cells and photoreceptors. PMID:20058854

Contribution of Human Oral Cells to Astringency by Binding Salivary Protein/Tannin Complexes.

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Soares, Susana; Ferrer-Galego, Raúl; Brandão, Elsa; Silva, Mafalda; Mateus, Nuno; Freitas, Victor de

2016-10-10

The most widely accepted mechanism to explain astringency is the interaction and precipitation of salivary proteins by food tannins, in particular proline-rich proteins. However, other mechanisms have been arising to explain astringency, such as binding of tannins to oral cells. In this work, an experimental method was adapted to study the possible contribution of both salivary proteins and oral cells to astringency induced by grape seed procyanidin fractions. Overall, in the absence of salivary proteins, the extent of procyanidin complexation with oral cells increased with increasing procyanidin degree of polymerization (mDP). Procyanidin fractions rich in monomers were the ones with the lowest ability to bind to oral cells. In the presence of salivary proteins and for procyanidins with mDP 2 the highest concentrations (1.5 and 2.0 mM) resulted in an increased binding of procyanidins to oral cells. This was even more evident for fractions III and IV at 1.0 mM and upper concentrations. Regarding the salivary proteins affected, it was possible to observe a decrease of P-B peptide and aPRP proteins for fractions II and III. This decrease is greater as the procyanidins' mDP increases. In fact, for fraction IV an almost total depletion of all salivary proteins was observed. This decrease is due to the formation of insoluble salivary protein/procyanidin complexes. Altogether, these data suggest that some procyanidins are able to bind to oral cells and that the salivary proteins interact with procyanidins forming salivary protein/procyanidin complexes that are also able to link to oral cells. The procyanidins that remain unbound to oral cells are able to bind to salivary proteins forming a large network of salivary protein/procyanidin complexes. Overall, the results presented herein provide one more step to understand food oral astringency onset.

A novel microfluidic chip electrophoresis strategy for simultaneous, label-free, multi-protein detection based on a graphene energy transfer biosensor.

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Lin, Fengming; Zhao, Xiaochao; Wang, Jianshe; Yu, Shiyong; Deng, Yulin; Geng, Lina; Li, HuanJun

2014-06-07

A new type of high-throughput and parallel optical sensing platform with a single-color probe based on microfluidic chip electrophoresis combined with aptamer-carboxyfluorescein/graphene oxide energy transfer is reported here. Label-free protein multi-targets were detected, even in challenging complex samples without any pre-treatment.

Multi-PAS domain-mediated protein oligomerization of PpsR from Rhodobacter sphaeroides

International Nuclear Information System (INIS)

Heintz, Udo; Meinhart, Anton; Winkler, Andreas

2014-01-01

Crystal structures of two truncated variants of the transcription factor PpsR from R. sphaeroides are presented that enabled the phasing of a triple PAS domain construct. Together, these structures reveal the importance of α-helical PAS extensions for multi-PAS domain-mediated protein oligomerization and function. Per–ARNT–Sim (PAS) domains are essential modules of many multi-domain signalling proteins that mediate protein interaction and/or sense environmental stimuli. Frequently, multiple PAS domains are present within single polypeptide chains, where their interplay is required for protein function. Although many isolated PAS domain structures have been reported over the last decades, only a few structures of multi-PAS proteins are known. Therefore, the molecular mechanism of multi-PAS domain-mediated protein oligomerization and function is poorly understood. The transcription factor PpsR from Rhodobacter sphaeroides is such a multi-PAS domain protein that, in addition to its three PAS domains, contains a glutamine-rich linker and a C-terminal helix–turn–helix DNA-binding motif. Here, crystal structures of two N-terminally and C-terminally truncated PpsR variants that comprise a single (PpsR Q-PAS1 ) and two (PpsR N-Q-PAS1 ) PAS domains, respectively, are presented and the multi-step strategy required for the phasing of a triple PAS domain construct (PpsR ΔHTH ) is illustrated. While parts of the biologically relevant dimerization interface can already be observed in the two shorter constructs, the PpsR ΔHTH structure reveals how three PAS domains enable the formation of multiple oligomeric states (dimer, tetramer and octamer), highlighting that not only the PAS cores but also their α-helical extensions are essential for protein oligomerization. The results demonstrate that the long helical glutamine-rich linker of PpsR results from a direct fusion of the N-cap of the PAS1 domain with the C-terminal extension of the N-domain that plays an important

Effects of ionizing radiations on DNA-protein complexes; Effets des radiations ionisantes sur des complexes ADN-proteine

Energy Technology Data Exchange (ETDEWEB)

Gillard, N

2005-11-15

The radio-induced destruction of DNA-protein complexes may have serious consequences for systems implicated in important cellular functions. The first system which has been studied is the lactose operon system, that regulates gene expression in Escherichia coli. First of all, the repressor-operator complex is destroyed after irradiation of the complex or of the protein alone. The damaging of the domain of repressor binding to DNA (headpiece) has been demonstrated and studied from the point of view of peptide chain integrity, conformation and amino acids damages. Secondly, dysfunctions of the in vitro induction of an irradiated repressor-unirradiated DNA complex have been observed. These perturbations, due to a decrease of the number of inducer binding sites, are correlated to the damaging of tryptophan residues. Moreover, the inducer protects the repressor when they are irradiated together, both by acting as a scavenger in the bulk, and by the masking of its binding site on the protein. The second studied system is formed by Fpg (for Formamido pyrimidine glycosylase), a DNA repair protein and a DNA with an oxidative lesion. The results show that irradiation disturbs the repair both by decreasing its efficiency of DNA lesion recognition and binding, and by altering its enzymatic activity. (author)

Accelerating large-scale protein structure alignments with graphics processing units

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Pang Bin

2012-02-01

Full Text Available Abstract Background Large-scale protein structure alignment, an indispensable tool to structural bioinformatics, poses a tremendous challenge on computational resources. To ensure structure alignment accuracy and efficiency, efforts have been made to parallelize traditional alignment algorithms in grid environments. However, these solutions are costly and of limited accessibility. Others trade alignment quality for speedup by using high-level characteristics of structure fragments for structure comparisons. Findings We present ppsAlign, a parallel protein structure Alignment framework designed and optimized to exploit the parallelism of Graphics Processing Units (GPUs. As a general-purpose GPU platform, ppsAlign could take many concurrent methods, such as TM-align and Fr-TM-align, into the parallelized algorithm design. We evaluated ppsAlign on an NVIDIA Tesla C2050 GPU card, and compared it with existing software solutions running on an AMD dual-core CPU. We observed a 36-fold speedup over TM-align, a 65-fold speedup over Fr-TM-align, and a 40-fold speedup over MAMMOTH. Conclusions ppsAlign is a high-performance protein structure alignment tool designed to tackle the computational complexity issues from protein structural data. The solution presented in this paper allows large-scale structure comparisons to be performed using massive parallel computing power of GPU.

SV40 large T-p53 complex: evidence for the presence of two immunologically distinct forms of p53

International Nuclear Information System (INIS)

Milner, J.; Gamble, J.

1985-01-01

The transforming protein of SV40 is the large T antigen. Large T binds a cellular protein, p53, which is potentially oncogenic by virtue of its functional involvement in the control of cell proliferation. This raises the possibility that p53 may mediate, in part, the transforming function of SV40 large T. Two immunologically distinct forms of p53 have been identified in normal cells: the forms are cell-cycle dependent, one being restricted to nondividing cells (p53-Go) and the second to dividing cells (p53-G divided by). The authors have now dissociated and probed the multimeric complex of SV40 large T-p53 for the presence of immunologically distinct forms of p53. Here they present evidence for the presence of p53-Go and p53-G divided by complexed with SV40 large T

Combining NMR and small angle X-ray and neutron scattering in the structural analysis of a ternary protein-RNA complex

International Nuclear Information System (INIS)

Hennig, Janosch; Wang, Iren; Sonntag, Miriam; Gabel, Frank; Sattler, Michael

2013-01-01

Many processes in the regulation of gene expression and signaling involve the formation of protein complexes involving multi-domain proteins. Individual domains that mediate protein-protein and protein-nucleic acid interactions are typically connected by flexible linkers, which contribute to conformational dynamics and enable the formation of complexes with distinct binding partners. Solution techniques are therefore required for structural analysis and to characterize potential conformational dynamics. Nuclear magnetic resonance spectroscopy (NMR) provides such information but often only sparse data are obtained with increasing molecular weight of the complexes. It is therefore beneficial to combine NMR data with additional structural restraints from complementary solution techniques. Small angle X-ray/neutron scattering (SAXS/SANS) data can be efficiently combined with NMR-derived information, either for validation or by providing additional restraints for structural analysis. Here, we show that the combination of SAXS and SANS data can help to refine structural models obtained from data-driven docking using HADDOCK based on sparse NMR data. The approach is demonstrated with the ternary protein-protein-RNA complex involving two RNA recognition motif (RRM) domains of Sex-lethal, the N-terminal cold shock domain of Upstream-to-N-Ras, and msl-2 mRNA. Based on chemical shift perturbations we have mapped protein-protein and protein-RNA interfaces and complemented this NMR-derived information with SAXS data, as well as SANS measurements on subunit-selectively deuterated samples of the ternary complex. Our results show that, while the use of SAXS data is beneficial, the additional combination with contrast variation in SANS data resolves remaining ambiguities and improves the docking based on chemical shift perturbations of the ternary protein-RNA complex.

Combining NMR and small angle X-ray and neutron scattering in the structural analysis of a ternary protein-RNA complex

Energy Technology Data Exchange (ETDEWEB)

Hennig, Janosch; Wang, Iren; Sonntag, Miriam [Institute of Structural Biology, Helmholtz Zentrum Muenchen (Germany); Gabel, Frank [Extremophiles and Large Molecular Assemblies Group (ELMA), Institut de Biologie Structurale (IBS) CEA-CNRS-UJF (France); Sattler, Michael, E-mail: sattler@helmholtz-muenchen.de [Institute of Structural Biology, Helmholtz Zentrum Muenchen (Germany)

2013-05-15

Many processes in the regulation of gene expression and signaling involve the formation of protein complexes involving multi-domain proteins. Individual domains that mediate protein-protein and protein-nucleic acid interactions are typically connected by flexible linkers, which contribute to conformational dynamics and enable the formation of complexes with distinct binding partners. Solution techniques are therefore required for structural analysis and to characterize potential conformational dynamics. Nuclear magnetic resonance spectroscopy (NMR) provides such information but often only sparse data are obtained with increasing molecular weight of the complexes. It is therefore beneficial to combine NMR data with additional structural restraints from complementary solution techniques. Small angle X-ray/neutron scattering (SAXS/SANS) data can be efficiently combined with NMR-derived information, either for validation or by providing additional restraints for structural analysis. Here, we show that the combination of SAXS and SANS data can help to refine structural models obtained from data-driven docking using HADDOCK based on sparse NMR data. The approach is demonstrated with the ternary protein-protein-RNA complex involving two RNA recognition motif (RRM) domains of Sex-lethal, the N-terminal cold shock domain of Upstream-to-N-Ras, and msl-2 mRNA. Based on chemical shift perturbations we have mapped protein-protein and protein-RNA interfaces and complemented this NMR-derived information with SAXS data, as well as SANS measurements on subunit-selectively deuterated samples of the ternary complex. Our results show that, while the use of SAXS data is beneficial, the additional combination with contrast variation in SANS data resolves remaining ambiguities and improves the docking based on chemical shift perturbations of the ternary protein-RNA complex.

Discovering functional interdependence relationship in PPI networks for protein complex identification.

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Lam, Winnie W M; Chan, Keith C C

2012-04-01

Protein molecules interact with each other in protein complexes to perform many vital functions, and different computational techniques have been developed to identify protein complexes in protein-protein interaction (PPI) networks. These techniques are developed to search for subgraphs of high connectivity in PPI networks under the assumption that the proteins in a protein complex are highly interconnected. While these techniques have been shown to be quite effective, it is also possible that the matching rate between the protein complexes they discover and those that are previously determined experimentally be relatively low and the "false-alarm" rate can be relatively high. This is especially the case when the assumption of proteins in protein complexes being more highly interconnected be relatively invalid. To increase the matching rate and reduce the false-alarm rate, we have developed a technique that can work effectively without having to make this assumption. The name of the technique called protein complex identification by discovering functional interdependence (PCIFI) searches for protein complexes in PPI networks by taking into consideration both the functional interdependence relationship between protein molecules and the network topology of the network. The PCIFI works in several steps. The first step is to construct a multiple-function protein network graph by labeling each vertex with one or more of the molecular functions it performs. The second step is to filter out protein interactions between protein pairs that are not functionally interdependent of each other in the statistical sense. The third step is to make use of an information-theoretic measure to determine the strength of the functional interdependence between all remaining interacting protein pairs. Finally, the last step is to try to form protein complexes based on the measure of the strength of functional interdependence and the connectivity between proteins. For performance evaluation

Two alternative binding mechanisms connect the protein translocation Sec71-Sec72 complex with heat shock proteins

Energy Technology Data Exchange (ETDEWEB)

Tripathi, Arati; Mandon, Elisabet C.; Gilmore, Reid; Rapoport, Tom A. (UMASS, MED); (Harvard-Med)

2017-03-12

The biosynthesis of many eukaryotic proteins requires accurate targeting to and translocation across the endoplasmic reticulum membrane. Post-translational protein translocation in yeast requires both the Sec61 translocation channel, and a complex of four additional proteins: Sec63, Sec62, Sec71, and Sec72. The structure and function of these proteins are largely unknown. This pathway also requires the cytosolic Hsp70 protein Ssa1, but whether Ssa1 associates with the translocation machinery to target protein substrates to the membrane is unclear. Here, we use a combined structural and biochemical approach to explore the role of Sec71-Sec72 subcomplex in post-translational protein translocation. To this end, we report a crystal structure of the Sec71-Sec72 complex, which revealed that Sec72 contains a tetratricopeptide repeat (TPR) domain that is anchored to the endoplasmic reticulum membrane by Sec71. We also determined the crystal structure of this TPR domain with a C-terminal peptide derived from Ssa1, which suggests how Sec72 interacts with full-length Ssa1. Surprisingly, Ssb1, a cytoplasmic Hsp70 that binds ribosome-associated nascent polypeptide chains, also binds to the TPR domain of Sec72, even though it lacks the TPR-binding C-terminal residues of Ssa1. We demonstrate that Ssb1 binds through its ATPase domain to the TPR domain, an interaction that leads to inhibition of nucleotide exchange. Taken together, our results suggest that translocation substrates can be recruited to the Sec71-Sec72 complex either post-translationally through Ssa1 or co-translationally through Ssb1.

Multi-dimensional discovery of biomarker and phenotype complexes

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Huang Kun

2010-10-01

Full Text Available Abstract Background Given the rapid growth of translational research and personalized healthcare paradigms, the ability to relate and reason upon networks of bio-molecular and phenotypic variables at various levels of granularity in order to diagnose, stage and plan treatments for disease states is highly desirable. Numerous techniques exist that can be used to develop networks of co-expressed or otherwise related genes and clinical features. Such techniques can also be used to create formalized knowledge collections based upon the information incumbent to ontologies and domain literature. However, reports of integrative approaches that bridge such networks to create systems-level models of disease or wellness are notably lacking in the contemporary literature. Results In response to the preceding gap in knowledge and practice, we report upon a prototypical series of experiments that utilize multi-modal approaches to network induction. These experiments are intended to elicit meaningful and significant biomarker-phenotype complexes spanning multiple levels of granularity. This work has been performed in the experimental context of a large-scale clinical and basic science data repository maintained by the National Cancer Institute (NCI funded Chronic Lymphocytic Leukemia Research Consortium. Conclusions Our results indicate that it is computationally tractable to link orthogonal networks of genes, clinical features, and conceptual knowledge to create multi-dimensional models of interrelated biomarkers and phenotypes. Further, our results indicate that such systems-level models contain interrelated bio-molecular and clinical markers capable of supporting hypothesis discovery and testing. Based on such findings, we propose a conceptual model intended to inform the cross-linkage of the results of such methods. This model has as its aim the identification of novel and knowledge-anchored biomarker-phenotype complexes.

Systematic methods for defining coarse-grained maps in large biomolecules.

Science.gov (United States)

Zhang, Zhiyong

2015-01-01

Large biomolecules are involved in many important biological processes. It would be difficult to use large-scale atomistic molecular dynamics (MD) simulations to study the functional motions of these systems because of the computational expense. Therefore various coarse-grained (CG) approaches have attracted rapidly growing interest, which enable simulations of large biomolecules over longer effective timescales than all-atom MD simulations. The first issue in CG modeling is to construct CG maps from atomic structures. In this chapter, we review the recent development of a novel and systematic method for constructing CG representations of arbitrarily complex biomolecules, in order to preserve large-scale and functionally relevant essential dynamics (ED) at the CG level. In this ED-CG scheme, the essential dynamics can be characterized by principal component analysis (PCA) on a structural ensemble, or elastic network model (ENM) of a single atomic structure. Validation and applications of the method cover various biological systems, such as multi-domain proteins, protein complexes, and even biomolecular machines. The results demonstrate that the ED-CG method may serve as a very useful tool for identifying functional dynamics of large biomolecules at the CG level.

Stabilization of Proteins and Noncovalent Protein Complexes during Electrospray Ionization by Amino Acid Additives.

Science.gov (United States)

Zhang, Hua; Lu, Haiyan; Chingin, Konstantin; Chen, Huanwen

2015-07-21

Ionization of proteins and noncovalent protein complexes with minimal disturbance to their native structure presents a great challenge for biological mass spectrometry (MS). In living organisms, the native structure of intracellular proteins is commonly stabilized by solute amino acids (AAs) accumulated in cells at very high concentrations. Inspired by nature, we hypothesized that AAs could also pose a stabilizing effect on the native structure of proteins and noncovalent protein complexes during ionization. To test this hypothesis, here we explored MS response for various protein complexes upon the addition of free AAs at mM concentrations into the electrospray ionization (ESI) solution. Thermal activation of ESI droplets in the MS inlet capillary was employed as a model destabilizing factor during ionization. Our results indicate that certain AAs, in particular proline (Pro), pose considerable positive effect on the stability of noncovalent protein complexes in ESI-MS without affecting the signal intensity of protein ions and original protein-ligand equilibrium, even when added at the 20 mM concentration. The data suggest that the degree of protein stabilization is primarily determined by the osmolytic and ampholytic characteristics of AA solutes. The highest stability and visibility of noncovalent protein complexes in ESI-MS are achieved using AA additives with neutral isoelectric point, moderate proton affinity, and unfavorable interaction with the native protein state. Overall, our results indicate that the simple addition of free amino acids into the working solution can notably improve the stability and accuracy of protein analysis by native ESI-MS.

Characterization of known protein complexes using k-connectivity and other topological measures

Science.gov (United States)

Gallagher, Suzanne R; Goldberg, Debra S

2015-01-01

Many protein complexes are densely packed, so proteins within complexes often interact with several other proteins in the complex. Steric constraints prevent most proteins from simultaneously binding more than a handful of other proteins, regardless of the number of proteins in the complex. Because of this, as complex size increases, several measures of the complex decrease within protein-protein interaction networks. However, k-connectivity, the number of vertices or edges that need to be removed in order to disconnect a graph, may be consistently high for protein complexes. The property of k-connectivity has been little used previously in the investigation of protein-protein interactions. To understand the discriminative power of k-connectivity and other topological measures for identifying unknown protein complexes, we characterized these properties in known Saccharomyces cerevisiae protein complexes in networks generated both from highly accurate X-ray crystallography experiments which give an accurate model of each complex, and also as the complexes appear in high-throughput yeast 2-hybrid studies in which new complexes may be discovered. We also computed these properties for appropriate random subgraphs.We found that clustering coefficient, mutual clustering coefficient, and k-connectivity are better indicators of known protein complexes than edge density, degree, or betweenness. This suggests new directions for future protein complex-finding algorithms. PMID:26913183

Interactions of the human MCM-BP protein with MCM complex components and Dbf4.

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Tin Nguyen

Full Text Available MCM-BP was discovered as a protein that co-purified from human cells with MCM proteins 3 through 7; results which were recapitulated in frogs, yeast and plants. Evidence in all of these organisms supports an important role for MCM-BP in DNA replication, including contributions to MCM complex unloading. However the mechanisms by which MCM-BP functions and associates with MCM complexes are not well understood. Here we show that human MCM-BP is capable of interacting with individual MCM proteins 2 through 7 when co-expressed in insect cells and can greatly increase the recovery of some recombinant MCM proteins. Glycerol gradient sedimentation analysis indicated that MCM-BP interacts most strongly with MCM4 and MCM7. Similar gradient analyses of human cell lysates showed that only a small amount of MCM-BP overlapped with the migration of MCM complexes and that MCM complexes were disrupted by exogenous MCM-BP. In addition, large complexes containing MCM-BP and MCM proteins were detected at mid to late S phase, suggesting that the formation of specific MCM-BP complexes is cell cycle regulated. We also identified an interaction between MCM-BP and the Dbf4 regulatory component of the DDK kinase in both yeast 2-hybrid and insect cell co-expression assays, and this interaction was verified by co-immunoprecipitation of endogenous proteins from human cells. In vitro kinase assays showed that MCM-BP was not a substrate for DDK but could inhibit DDK phosphorylation of MCM4,6,7 within MCM4,6,7 or MCM2-7 complexes, with little effect on DDK phosphorylation of MCM2. Since DDK is known to activate DNA replication through phosphorylation of these MCM proteins, our results suggest that MCM-BP may affect DNA replication in part by regulating MCM phosphorylation by DDK.

Interactions of the human MCM-BP protein with MCM complex components and Dbf4.

Science.gov (United States)

Nguyen, Tin; Jagannathan, Madhav; Shire, Kathy; Frappier, Lori

2012-01-01

MCM-BP was discovered as a protein that co-purified from human cells with MCM proteins 3 through 7; results which were recapitulated in frogs, yeast and plants. Evidence in all of these organisms supports an important role for MCM-BP in DNA replication, including contributions to MCM complex unloading. However the mechanisms by which MCM-BP functions and associates with MCM complexes are not well understood. Here we show that human MCM-BP is capable of interacting with individual MCM proteins 2 through 7 when co-expressed in insect cells and can greatly increase the recovery of some recombinant MCM proteins. Glycerol gradient sedimentation analysis indicated that MCM-BP interacts most strongly with MCM4 and MCM7. Similar gradient analyses of human cell lysates showed that only a small amount of MCM-BP overlapped with the migration of MCM complexes and that MCM complexes were disrupted by exogenous MCM-BP. In addition, large complexes containing MCM-BP and MCM proteins were detected at mid to late S phase, suggesting that the formation of specific MCM-BP complexes is cell cycle regulated. We also identified an interaction between MCM-BP and the Dbf4 regulatory component of the DDK kinase in both yeast 2-hybrid and insect cell co-expression assays, and this interaction was verified by co-immunoprecipitation of endogenous proteins from human cells. In vitro kinase assays showed that MCM-BP was not a substrate for DDK but could inhibit DDK phosphorylation of MCM4,6,7 within MCM4,6,7 or MCM2-7 complexes, with little effect on DDK phosphorylation of MCM2. Since DDK is known to activate DNA replication through phosphorylation of these MCM proteins, our results suggest that MCM-BP may affect DNA replication in part by regulating MCM phosphorylation by DDK.

Heuristic Relative Entropy Principles with Complex Measures: Large-Degree Asymptotics of a Family of Multi-variate Normal Random Polynomials

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Kiessling, Michael Karl-Heinz

2017-10-01

Let z\\in C, let σ ^2>0 be a variance, and for N\\in N define the integrals E_N^{}(z;σ ) := {1/σ } \\int _R\\ (x^2+z^2) e^{-{1/2σ^2 x^2}}{√{2π }}/dx \\quad if N=1, {1/σ } \\int _{R^N} \\prod \\prod \\limits _{1≤ k1. These are expected values of the polynomials P_N^{}(z)=\\prod _{1≤ n≤ N}(X_n^2+z^2) whose 2 N zeros ± i X_k^{}_{k=1,\\ldots ,N} are generated by N identically distributed multi-variate mean-zero normal random variables {X_k}N_{k=1} with co-variance {Cov}_N^{}(X_k,X_l)=(1+σ ^2-1/N)δ _{k,l}+σ ^2-1/N(1-δ _{k,l}). The E_N^{}(z;σ ) are polynomials in z^2, explicitly computable for arbitrary N, yet a list of the first three E_N^{}(z;σ ) shows that the expressions become unwieldy already for moderate N—unless σ = 1, in which case E_N^{}(z;1) = (1+z^2)^N for all z\\in C and N\\in N. (Incidentally, commonly available computer algebra evaluates the integrals E_N^{}(z;σ ) only for N up to a dozen, due to memory constraints). Asymptotic evaluations are needed for the large- N regime. For general complex z these have traditionally been limited to analytic expansion techniques; several rigorous results are proved for complex z near 0. Yet if z\\in R one can also compute this "infinite-degree" limit with the help of the familiar relative entropy principle for probability measures; a rigorous proof of this fact is supplied. Computer algebra-generated evidence is presented in support of a conjecture that a generalization of the relative entropy principle to signed or complex measures governs the N→ ∞ asymptotics of the regime iz\\in R. Potential generalizations, in particular to point vortex ensembles and the prescribed Gauss curvature problem, and to random matrix ensembles, are emphasized.

Characterization of anti-P monoclonal antibodies directed against the ribosomal protein-RNA complex antigen and produced using Murphy Roths large autoimmune-prone mice.

Science.gov (United States)

Sato, H; Onozuka, M; Hagiya, A; Hoshino, S; Narita, I; Uchiumi, T

2015-02-01

Autoantibodies, including anti-ribosomal P proteins (anti-P), are thought to be produced by an antigen-driven immune response in systemic lupus erythematosus (SLE). To test this hypothesis, we reconstituted the ribosomal antigenic complex in vitro using human P0, phosphorylated P1 and P2 and a 28S rRNA fragment covering the P0 binding site, and immunized Murphy Roths large (MRL)/lrp lupus mice with this complex without any added adjuvant to generate anti-P antibodies. Using hybridoma technology, we subsequently obtained 34 clones, each producing an anti-P monoclonal antibody (mAb) that recognized the conserved C-terminal tail sequence common to all three P proteins. We also obtained two P0-specific monoclonal antibodies, but no antibody specific to P1, P2 or rRNA fragment. Two types of mAbs were found among these anti-P antibodies: one type (e.g. 9D5) reacted more strongly with the phosphorylated P1 and P2 than that with their non-phosphorylated forms, whereas the other type (e.g. 4H11) reacted equally with both phosphorylated and non-phosphorylated forms of P1/P2. Both 9D5 and 4H11 inhibited the ribosome/eukaryotic elongation factor-2 (eEF-2)-coupled guanosine triphosphate (GTP)ase activity. However, preincubation with a synthetic peptide corresponding to the C-terminal sequence common to all three P proteins, but not the peptide that lacked the last three C-terminal amino acids, mostly prevented the mAb-induced inhibition of GTPase activity. Thus, at least two types of anti-P were produced preferentially following the immunization of MRL mice with the reconstituted antigenic complex. Presence of multiple copies of the C-termini, particularly that of the last three C-terminal amino acid residues, in the antigenic complex appears to contribute to the immunogenic stimulus. © 2014 British Society for Immunology.

Nicotine affects protein complex rearrangement in Caenorhabditis elegans cells.

Science.gov (United States)

Sobkowiak, Robert; Zielezinski, Andrzej; Karlowski, Wojciech M; Lesicki, Andrzej

2017-10-01

Nicotine may affect cell function by rearranging protein complexes. We aimed to determine nicotine-induced alterations of protein complexes in Caenorhabditis elegans (C. elegans) cells, thereby revealing links between nicotine exposure and protein complex modulation. We compared the proteomic alterations induced by low and high nicotine concentrations (0.01 mM and 1 mM) with the control (no nicotine) in vivo by using mass spectrometry (MS)-based techniques, specifically the cetyltrimethylammonium bromide (CTAB) discontinuous gel electrophoresis coupled with liquid chromatography (LC)-MS/MS and spectral counting. As a result, we identified dozens of C. elegans proteins that are present exclusively or in higher abundance in either nicotine-treated or untreated worms. Based on these results, we report a possible network that captures the key protein components of nicotine-induced protein complexes and speculate how the different protein modules relate to their distinct physiological roles. Using functional annotation of detected proteins, we hypothesize that the identified complexes can modulate the energy metabolism and level of oxidative stress. These proteins can also be involved in modulation of gene expression and may be crucial in Alzheimer's disease. The findings reported in our study reveal putative intracellular interactions of many proteins with the cytoskeleton and may contribute to the understanding of the mechanisms of nicotinic acetylcholine receptor (nAChR) signaling and trafficking in cells.

Multi-view L2-SVM and its multi-view core vector machine.

Science.gov (United States)

Huang, Chengquan; Chung, Fu-lai; Wang, Shitong

2016-03-01

In this paper, a novel L2-SVM based classifier Multi-view L2-SVM is proposed to address multi-view classification tasks. The proposed Multi-view L2-SVM classifier does not have any bias in its objective function and hence has the flexibility like μ-SVC in the sense that the number of the yielded support vectors can be controlled by a pre-specified parameter. The proposed Multi-view L2-SVM classifier can make full use of the coherence and the difference of different views through imposing the consensus among multiple views to improve the overall classification performance. Besides, based on the generalized core vector machine GCVM, the proposed Multi-view L2-SVM classifier is extended into its GCVM version MvCVM which can realize its fast training on large scale multi-view datasets, with its asymptotic linear time complexity with the sample size and its space complexity independent of the sample size. Our experimental results demonstrated the effectiveness of the proposed Multi-view L2-SVM classifier for small scale multi-view datasets and the proposed MvCVM classifier for large scale multi-view datasets. Copyright © 2015 Elsevier Ltd. All rights reserved.

Role for a Novel Usher Protein Complex in Hair Cell Synaptic Maturation

Science.gov (United States)

Zallocchi, Marisa; Meehan, Daniel T.; Delimont, Duane; Rutledge, Joseph; Gratton, Michael Anne; Flannery, John; Cosgrove, Dominic

2012-01-01

The molecular mechanisms underlying hair cell synaptic maturation are not well understood. Cadherin-23 (CDH23), protocadherin-15 (PCDH15) and the very large G-protein coupled receptor 1 (VLGR1) have been implicated in the development of cochlear hair cell stereocilia, while clarin-1 has been suggested to also play a role in synaptogenesis. Mutations in CDH23, PCDH15, VLGR1 and clarin-1 cause Usher syndrome, characterized by congenital deafness, vestibular dysfunction and retinitis pigmentosa. Here we show developmental expression of these Usher proteins in afferent spiral ganglion neurons and hair cell synapses. We identify a novel synaptic Usher complex comprised of clarin-1 and specific isoforms of CDH23, PCDH15 and VLGR1. To establish the in vivo relevance of this complex, we performed morphological and quantitative analysis of the neuronal fibers and their synapses in the Clrn1−/− mouse, which was generated by incomplete deletion of the gene. These mice showed a delay in neuronal/synaptic maturation by both immunostaining and electron microscopy. Analysis of the ribbon synapses in Ames waltzerav3J mice also suggests a delay in hair cell synaptogenesis. Collectively, these results show that, in addition to the well documented role for Usher proteins in stereocilia development, Usher protein complexes comprised of specific protein isoforms likely function in synaptic maturation as well. PMID:22363448

Role for a novel Usher protein complex in hair cell synaptic maturation.

Directory of Open Access Journals (Sweden)

Marisa Zallocchi

Full Text Available The molecular mechanisms underlying hair cell synaptic maturation are not well understood. Cadherin-23 (CDH23, protocadherin-15 (PCDH15 and the very large G-protein coupled receptor 1 (VLGR1 have been implicated in the development of cochlear hair cell stereocilia, while clarin-1 has been suggested to also play a role in synaptogenesis. Mutations in CDH23, PCDH15, VLGR1 and clarin-1 cause Usher syndrome, characterized by congenital deafness, vestibular dysfunction and retinitis pigmentosa. Here we show developmental expression of these Usher proteins in afferent spiral ganglion neurons and hair cell synapses. We identify a novel synaptic Usher complex comprised of clarin-1 and specific isoforms of CDH23, PCDH15 and VLGR1. To establish the in vivo relevance of this complex, we performed morphological and quantitative analysis of the neuronal fibers and their synapses in the Clrn1-/- mouse, which was generated by incomplete deletion of the gene. These mice showed a delay in neuronal/synaptic maturation by both immunostaining and electron microscopy. Analysis of the ribbon synapses in Ames waltzer(av3J mice also suggests a delay in hair cell synaptogenesis. Collectively, these results show that, in addition to the well documented role for Usher proteins in stereocilia development, Usher protein complexes comprised of specific protein isoforms likely function in synaptic maturation as well.

Natural ventilation of large multi-span greenhouses

NARCIS (Netherlands)

Jong, de T.

1990-01-01

In this thesis the ventilation of large multi-span greenhouses caused by wind and temperature effects is studied. Quantification of the ventilation is important to improve the control of the greenhouse climate.

Knowledge of the flow characteristics of the one-side-mounted windows of

RNF4 interacts with multiSUMOylated ETV4.

Science.gov (United States)

Aguilar-Martinez, Elisa; Guo, Baoqiang; Sharrocks, Andrew D

2016-01-01

Protein SUMOylation represents an important regulatory event that changes the activities of numerous proteins. Recent evidence demonstrates that polySUMO chains can act as a trigger to direct the ubiquitin ligase RNF4 to substrates to cause their turnover through the ubiquitin pathway. RNF4 uses multiple SUMO interaction motifs (SIMs) to bind to these chains. However, in addition to polySUMO chains, a multimeric binding surface created by the simultaneous SUMOylation of multiple residues on a protein or complex could also provide a platform for the recruitment of multi-SIM proteins like RNF4. Here we demonstrate that multiSUMOylated ETV4 can bind to RNF4 and that a unique combination of SIMs is required for RNF4 to interact with this multiSUMOylated platform. Thus RNF4 can bind to proteins that are either polySUMOylated through a single site or multiSUMOylated on several sites and raises the possibility that such multiSIM-multiSUMO interactions might be more widespread.

Complex engineering objects construction using Multi-D innovative technology

International Nuclear Information System (INIS)

Agafonov, Alexey

2013-01-01

Multi-D technology is an integrated innovative project management system for a construction of complex engineering objects based on a construction process simulation using an intellectual 3D model. Multi-D technology includes: • The unified schedule of E+P+C; • The schedule of loading of human resources, machines & mechanisms; • The budget of expenses and the income integrated with the schedule; • 3D model; • Multi-D model; • Weekly-daily tasks (with 4th level schedules); • Control system of interaction of Customer-EPC(m) company - Contractors; • Change and configuration management system

Improved understanding of protein complex offers insight into DNA

Science.gov (United States)

Summer Science Writing Internship Improved understanding of protein complex offers insight into DNA clearer understanding of the origin recognition complex (ORC) - a protein complex that directs DNA replication - through its crystal structure offers new insight into fundamental mechanisms of DNA replication

Dynamics in electron transfer protein complexes

NARCIS (Netherlands)

Bashir, Qamar

2010-01-01

Recent studies have provided experimental evidence for the existence of an encounter complex, a transient intermediate in the formation of protein complexes. We have used paramagnetic relaxation enhancement NMR spectroscopy in combination with Monte Carlo simulations to characterize and visualize

Multi-Purpose Storage Complex description

International Nuclear Information System (INIS)

Nyman, D.H.

1993-01-01

The Multi-Purpose Storage Complex will provide interim storage of radioactive material (irradiated fuel, cesium/strontium capsules, plutonium residuals, canisters of vitrified high-level waste glass, and other radioactive material) at the Hanford Site near Richland, Washington. A Storage Preparation and Shipping Facility is included that will have the capability to stabilize failed metal fuel, segregate high-level solid waste, and package/repackage any of the materials for interim storage/final disposal or subsequent processing. Current technology, both domestic and foreign, will be adapted with the expectation that no new technology will be required. This cost-effective approach will use fuel casks, transport systems, and/or modular vaults that have been licensed in the United States. The complex will have a central control room, and appropriate safeguards and security measures will be incorporated. A specific design objective will be to minimize the amount of secondary waste

Optimal number of coarse-grained sites in different components of large biomolecular complexes.

Science.gov (United States)

Sinitskiy, Anton V; Saunders, Marissa G; Voth, Gregory A

2012-07-26

The computational study of large biomolecular complexes (molecular machines, cytoskeletal filaments, etc.) is a formidable challenge facing computational biophysics and biology. To achieve biologically relevant length and time scales, coarse-grained (CG) models of such complexes usually must be built and employed. One of the important early stages in this approach is to determine an optimal number of CG sites in different constituents of a complex. This work presents a systematic approach to this problem. First, a universal scaling law is derived and numerically corroborated for the intensity of the intrasite (intradomain) thermal fluctuations as a function of the number of CG sites. Second, this result is used for derivation of the criterion for the optimal number of CG sites in different parts of a large multibiomolecule complex. In the zeroth-order approximation, this approach validates the empirical rule of taking one CG site per fixed number of atoms or residues in each biomolecule, previously widely used for smaller systems (e.g., individual biomolecules). The first-order corrections to this rule are derived and numerically checked by the case studies of the Escherichia coli ribosome and Arp2/3 actin filament junction. In different ribosomal proteins, the optimal number of amino acids per CG site is shown to differ by a factor of 3.5, and an even wider spread may exist in other large biomolecular complexes. Therefore, the method proposed in this paper is valuable for the optimal construction of CG models of such complexes.

Meredys, a multi-compartment reaction-diffusion simulator using multistate realistic molecular complexes

Directory of Open Access Journals (Sweden)

Le Novère Nicolas

2010-03-01

Full Text Available Abstract Background Most cellular signal transduction mechanisms depend on a few molecular partners whose roles depend on their position and movement in relation to the input signal. This movement can follow various rules and take place in different compartments. Additionally, the molecules can form transient complexes. Complexation and signal transduction depend on the specific states partners and complexes adopt. Several spatial simulator have been developed to date, but none are able to model reaction-diffusion of realistic multi-state transient complexes. Results Meredys allows for the simulation of multi-component, multi-feature state molecular species in two and three dimensions. Several compartments can be defined with different diffusion and boundary properties. The software employs a Brownian dynamics engine to simulate reaction-diffusion systems at the reactive particle level, based on compartment properties, complex structure, and hydro-dynamic radii. Zeroth-, first-, and second order reactions are supported. The molecular complexes have realistic geometries. Reactive species can contain user-defined feature states which can modify reaction rates and outcome. Models are defined in a versatile NeuroML input file. The simulation volume can be split in subvolumes to speed up run-time. Conclusions Meredys provides a powerful and versatile way to run accurate simulations of molecular and sub-cellular systems, that complement existing multi-agent simulation systems. Meredys is a Free Software and the source code is available at http://meredys.sourceforge.net/.

MultiLoc2: integrating phylogeny and Gene Ontology terms improves subcellular protein localization prediction

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Kohlbacher Oliver

2009-09-01

Full Text Available Abstract Background Knowledge of subcellular localization of proteins is crucial to proteomics, drug target discovery and systems biology since localization and biological function are highly correlated. In recent years, numerous computational prediction methods have been developed. Nevertheless, there is still a need for prediction methods that show more robustness and higher accuracy. Results We extended our previous MultiLoc predictor by incorporating phylogenetic profiles and Gene Ontology terms. Two different datasets were used for training the system, resulting in two versions of this high-accuracy prediction method. One version is specialized for globular proteins and predicts up to five localizations, whereas a second version covers all eleven main eukaryotic subcellular localizations. In a benchmark study with five localizations, MultiLoc2 performs considerably better than other methods for animal and plant proteins and comparably for fungal proteins. Furthermore, MultiLoc2 performs clearly better when using a second dataset that extends the benchmark study to all eleven main eukaryotic subcellular localizations. Conclusion MultiLoc2 is an extensive high-performance subcellular protein localization prediction system. By incorporating phylogenetic profiles and Gene Ontology terms MultiLoc2 yields higher accuracies compared to its previous version. Moreover, it outperforms other prediction systems in two benchmarks studies. MultiLoc2 is available as user-friendly and free web-service, available at: http://www-bs.informatik.uni-tuebingen.de/Services/MultiLoc2.

Supercharging Protein Complexes from Aqueous Solution Disrupts their Native Conformations

Science.gov (United States)

Sterling, Harry J.; Kintzer, Alexander F.; Feld, Geoffrey K.; Cassou, Catherine A.; Krantz, Bryan A.; Williams, Evan R.

2012-02-01

The effects of aqueous solution supercharging on the solution- and gas-phase structures of two protein complexes were investigated using traveling-wave ion mobility-mass spectrometry (TWIMS-MS). Low initial concentrations of m-nitrobenzyl alcohol ( m-NBA) in the electrospray ionization (ESI) solution can effectively increase the charge of concanavalin A dimers and tetramers, but at higher m-NBA concentrations, the increases in charge are accompanied by solution-phase dissociation of the dimers and up to a ~22% increase in the collision cross section (CCS) of the tetramers. With just 0.8% m-NBA added to the ESI solution of a ~630 kDa anthrax toxin octamer complex, the average charge is increased by only ~4% compared with the "native" complex, but it is sufficiently destabilized so that extensive gas-phase fragmentation occurs in the relatively high pressure regions of the TWIMS device. Anthrax toxin complexes exist in either a prechannel or a transmembrane channel state. With m-NBA, the prechannel state of the complex has the same CCS/charge ratio in the gas phase as the transmembrane channel state of the same complex formed without m-NBA, yet undergoes extensive dissociation, indicating that destabilization from supercharging occurs in the ESI droplet prior to ion formation and is not a result of Coulombic destabilization in the gas phase as a result of higher charging. These results demonstrate that the supercharging of large protein complexes is the result of conformational changes induced by the reagents in the ESI droplets, where enrichment of the supercharging reagent during droplet evaporation occurs.

Automated multi-dimensional purification of tagged proteins.

Science.gov (United States)

Sigrell, Jill A; Eklund, Pär; Galin, Markus; Hedkvist, Lotta; Liljedahl, Pia; Johansson, Christine Markeland; Pless, Thomas; Torstenson, Karin

2003-01-01

The capacity for high throughput purification (HTP) is essential in fields such as structural genomics where large numbers of protein samples are routinely characterized in, for example, studies of structural determination, functionality and drug development. Proteins required for such analysis must be pure and homogenous and available in relatively large amounts. AKTA 3D system is a powerful automated protein purification system, which minimizes preparation, run-time and repetitive manual tasks. It has the capacity to purify up to 6 different His6- or GST-tagged proteins per day and can produce 1-50 mg protein per run at >90% purity. The success of automated protein purification increases with careful experimental planning. Protocol, columns and buffers need to be chosen with the final application area for the purified protein in mind.

A novel protein-protein interaction in the RES (REtention and Splicing) complex.

Science.gov (United States)

Tripsianes, Konstantinos; Friberg, Anders; Barrandon, Charlotte; Brooks, Mark; van Tilbeurgh, Herman; Seraphin, Bertrand; Sattler, Michael

2014-10-10

The retention and splicing (RES) complex is a conserved spliceosome-associated module that was shown to enhance splicing of a subset of transcripts and promote the nuclear retention of unspliced pre-mRNAs in yeast. The heterotrimeric RES complex is organized around the Snu17p protein that binds to both the Bud13p and Pml1p subunits. Snu17p exhibits an RRM domain that resembles a U2AF homology motif (UHM) and Bud13p harbors a Trp residue reminiscent of an UHM-ligand motif (ULM). It has therefore been proposed that the interaction between Snu17p and Bud13p resembles canonical UHM-ULM complexes. Here, we have used biochemical and NMR structural analysis to characterize the structure of the yeast Snu17p-Bud13p complex. Unlike known UHMs that sequester the Trp residue of the ULM ligand in a hydrophobic pocket, Snu17p and Bud13p utilize a large interaction surface formed around the two helices of the Snu17p domain. In total 18 residues of the Bud13p ligand wrap around the Snu17p helical surface in an U-turn-like arrangement. The invariant Trp(232) in Bud13p is located in the center of the turn, and contacts surface residues of Snu17p. The structural data are supported by mutational analysis and indicate that Snu17p provides an extended binding surface with Bud13p that is notably distinct from canonical UHM-ULM interactions. Our data highlight structural diversity in RRM-protein interactions, analogous to the one seen for nucleic acid interactions. © 2014 by The American Society for Biochemistry and Molecular Biology, Inc.

A fluorescence anisotropy method for measuring protein concentration in complex cell culture media.

Science.gov (United States)

Groza, Radu Constantin; Calvet, Amandine; Ryder, Alan G

2014-04-22

The rapid, quantitative analysis of the complex cell culture media used in biopharmaceutical manufacturing is of critical importance. Requirements for cell culture media composition profiling, or changes in specific analyte concentrations (e.g. amino acids in the media or product protein in the bioprocess broth) often necessitate the use of complicated analytical methods and extensive sample handling. Rapid spectroscopic methods like multi-dimensional fluorescence (MDF) spectroscopy have been successfully applied for the routine determination of compositional changes in cell culture media and bioprocess broths. Quantifying macromolecules in cell culture media is a specific challenge as there is a need to implement measurements rapidly on the prepared media. However, the use of standard fluorescence spectroscopy is complicated by the emission overlap from many media components. Here, we demonstrate how combining anisotropy measurements with standard total synchronous fluorescence spectroscopy (TSFS) provides a rapid, accurate quantitation method for cell culture media. Anisotropy provides emission resolution between large and small fluorophores while TSFS provides a robust measurement space. Model cell culture media was prepared using yeastolate (2.5 mg mL(-1)) spiked with bovine serum albumin (0 to 5 mg mL(-1)). Using this method, protein emission is clearly discriminated from background yeastolate emission, allowing for accurate bovine serum albumin (BSA) quantification over a 0.1 to 4.0 mg mL(-1) range with a limit of detection (LOD) of 13.8 μg mL(-1). Copyright © 2014. Published by Elsevier B.V.

Protein complex finding and ranking: An application to Alzheimer's

Indian Academy of Sciences (India)

Protein complexes are known to play a major role in controlling cellular activity in a living being. Identifying complexesfrom raw protein–protein interactions (PPIs) is an important area of research. Earlier work has been limited mostly to yeastand a few other model organisms. Such protein complex identification methods, ...

Linking structural features of protein complexes and biological function.

Science.gov (United States)

Sowmya, Gopichandran; Breen, Edmond J; Ranganathan, Shoba

2015-09-01

Protein-protein interaction (PPI) establishes the central basis for complex cellular networks in a biological cell. Association of proteins with other proteins occurs at varying affinities, yet with a high degree of specificity. PPIs lead to diverse functionality such as catalysis, regulation, signaling, immunity, and inhibition, playing a crucial role in functional genomics. The molecular principle of such interactions is often elusive in nature. Therefore, a comprehensive analysis of known protein complexes from the Protein Data Bank (PDB) is essential for the characterization of structural interface features to determine structure-function relationship. Thus, we analyzed a nonredundant dataset of 278 heterodimer protein complexes, categorized into major functional classes, for distinguishing features. Interestingly, our analysis has identified five key features (interface area, interface polar residue abundance, hydrogen bonds, solvation free energy gain from interface formation, and binding energy) that are discriminatory among the functional classes using Kruskal-Wallis rank sum test. Significant correlations between these PPI interface features amongst functional categories are also documented. Salt bridges correlate with interface area in regulator-inhibitors (r = 0.75). These representative features have implications for the prediction of potential function of novel protein complexes. The results provide molecular insights for better understanding of PPIs and their relation to biological functions. © 2015 The Protein Society.

Structure of the JmjC domain-containing protein NO66 complexed with ribosomal protein Rpl8

Energy Technology Data Exchange (ETDEWEB)

Wang, Chengliang [University of Science and Technology of China, 96 Jinzhai Road, Hefei, Anhui 230026, People’s Republic of (China); Chinese Academy of Sciences, Hefei, Anhui 230026, People’s Republic of (China); Zhang, Qiongdi [University of Science and Technology of China, 96 Jinzhai Road, Hefei, Anhui 230026, People’s Republic of (China); Hang, Tianrong [University of Science and Technology of China, 96 Jinzhai Road, Hefei, Anhui 230026, People’s Republic of (China); Chinese Academy of Sciences, Hefei, Anhui 230026, People’s Republic of (China); Tao, Yue [Shanghai Children’s Medical Center, 1678 Dongfang Road, Pudong, Shanghai 200120, People’s Republic of (China); Ma, Xukai [University of Science and Technology of China, 96 Jinzhai Road, Hefei, Anhui 230026, People’s Republic of (China); Wu, Minhao; Zhang, Xuan, E-mail: xuanzbin@ustc.edu.cn; Zang, Jianye, E-mail: xuanzbin@ustc.edu.cn [University of Science and Technology of China, 96 Jinzhai Road, Hefei, Anhui 230026, People’s Republic of (China); Chinese Academy of Sciences, Hefei, Anhui 230026, People’s Republic of (China)

2015-08-28

The structure of the complex of NO66 and Rpl8 was solved in the native state and NO66 recognizes the consensus motif NHXH . Tetramerization is required for efficient substrate binding and catalysis by NO66. The JmjC domain-containing proteins belong to a large family of oxygenases possessing distinct substrate specificities which are involved in the regulation of different biological processes, such as gene transcription, RNA processing and translation. Nucleolar protein 66 (NO66) is a JmjC domain-containing protein which has been reported to be a histone demethylase and a ribosome protein 8 (Rpl8) hydroxylase. The present biochemical study confirmed the hydroxylase activity of NO66 and showed that oligomerization is required for NO66 to efficiently catalyze the hydroxylation of Rpl8. The structures of NO66{sup 176–C} complexed with Rpl8{sup 204–224} in a tetrameric form and of the mutant protein M2 in a dimeric form were solved. Based on the results of structural and biochemical analyses, the consensus sequence motif NHXH recognized by NO66 was confirmed. Several potential substrates of NO66 were found by a BLAST search according to the consensus sequence motif. When binding to substrate, the relative positions of each subunit in the NO66 tetramer shift. Oligomerization may facilitate the motion of each subunit in the NO66 tetramer and affect the catalytic activity.

Multi-label learning with fuzzy hypergraph regularization for protein subcellular location prediction.

Science.gov (United States)

Chen, Jing; Tang, Yuan Yan; Chen, C L Philip; Fang, Bin; Lin, Yuewei; Shang, Zhaowei

2014-12-01

Protein subcellular location prediction aims to predict the location where a protein resides within a cell using computational methods. Considering the main limitations of the existing methods, we propose a hierarchical multi-label learning model FHML for both single-location proteins and multi-location proteins. The latent concepts are extracted through feature space decomposition and label space decomposition under the nonnegative data factorization framework. The extracted latent concepts are used as the codebook to indirectly connect the protein features to their annotations. We construct dual fuzzy hypergraphs to capture the intrinsic high-order relations embedded in not only feature space, but also label space. Finally, the subcellular location annotation information is propagated from the labeled proteins to the unlabeled proteins by performing dual fuzzy hypergraph Laplacian regularization. The experimental results on the six protein benchmark datasets demonstrate the superiority of our proposed method by comparing it with the state-of-the-art methods, and illustrate the benefit of exploiting both feature correlations and label correlations.

Multi-Agent System Supporting Automated Large-Scale Photometric Computations

Directory of Open Access Journals (Sweden)

Adam Sȩdziwy

2016-02-01

Full Text Available The technologies related to green energy, smart cities and similar areas being dynamically developed in recent years, face frequently problems of a computational nature rather than a technological one. The example is the ability of accurately predicting the weather conditions for PV farms or wind turbines. Another group of issues is related to the complexity of the computations required to obtain an optimal setup of a solution being designed. In this article, we present the case representing the latter group of problems, namely designing large-scale power-saving lighting installations. The term “large-scale” refers to an entire city area, containing tens of thousands of luminaires. Although a simple power reduction for a single street, giving limited savings, is relatively easy, it becomes infeasible for tasks covering thousands of luminaires described by precise coordinates (instead of simplified layouts. To overcome this critical issue, we propose introducing a formal representation of a computing problem and applying a multi-agent system to perform design-related computations in parallel. The important measure introduced in the article indicating optimization progress is entropy. It also allows for terminating optimization when the solution is satisfying. The article contains the results of real-life calculations being made with the help of the presented approach.

Proteins with complex architecture as potential targets for drug design: a case study of Mycobacterium tuberculosis.

Directory of Open Access Journals (Sweden)

Bálint Mészáros

2011-07-01

Full Text Available Lengthy co-evolution of Homo sapiens and Mycobacterium tuberculosis, the main causative agent of tuberculosis, resulted in a dramatically successful pathogen species that presents considerable challenge for modern medicine. The continuous and ever increasing appearance of multi-drug resistant mycobacteria necessitates the identification of novel drug targets and drugs with new mechanisms of action. However, further insights are needed to establish automated protocols for target selection based on the available complete genome sequences. In the present study, we perform complete proteome level comparisons between M. tuberculosis, mycobacteria, other prokaryotes and available eukaryotes based on protein domains, local sequence similarities and protein disorder. We show that the enrichment of certain domains in the genome can indicate an important function specific to M. tuberculosis. We identified two families, termed pkn and PE/PPE that stand out in this respect. The common property of these two protein families is a complex domain organization that combines species-specific regions, commonly occurring domains and disordered segments. Besides highlighting promising novel drug target candidates in M. tuberculosis, the presented analysis can also be viewed as a general protocol to identify proteins involved in species-specific functions in a given organism. We conclude that target selection protocols should be extended to include proteins with complex domain architectures instead of focusing on sequentially unique and essential proteins only.

Stoichiometric balance of protein copy numbers is measurable and functionally significant in a protein-protein interaction network for yeast endocytosis.

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Holland, David O; Johnson, Margaret E

2018-03-01

Stoichiometric balance, or dosage balance, implies that proteins that are subunits of obligate complexes (e.g. the ribosome) should have copy numbers expressed to match their stoichiometry in that complex. Establishing balance (or imbalance) is an important tool for inferring subunit function and assembly bottlenecks. We show here that these correlations in protein copy numbers can extend beyond complex subunits to larger protein-protein interactions networks (PPIN) involving a range of reversible binding interactions. We develop a simple method for quantifying balance in any interface-resolved PPINs based on network structure and experimentally observed protein copy numbers. By analyzing such a network for the clathrin-mediated endocytosis (CME) system in yeast, we found that the real protein copy numbers were significantly more balanced in relation to their binding partners compared to randomly sampled sets of yeast copy numbers. The observed balance is not perfect, highlighting both under and overexpressed proteins. We evaluate the potential cost and benefits of imbalance using two criteria. First, a potential cost to imbalance is that 'leftover' proteins without remaining functional partners are free to misinteract. We systematically quantify how this misinteraction cost is most dangerous for strong-binding protein interactions and for network topologies observed in biological PPINs. Second, a more direct consequence of imbalance is that the formation of specific functional complexes depends on relative copy numbers. We therefore construct simple kinetic models of two sub-networks in the CME network to assess multi-protein assembly of the ARP2/3 complex and a minimal, nine-protein clathrin-coated vesicle forming module. We find that the observed, imperfectly balanced copy numbers are less effective than balanced copy numbers in producing fast and complete multi-protein assemblies. However, we speculate that strategic imbalance in the vesicle forming module

Characterising antimicrobial protein-membrane complexes

International Nuclear Information System (INIS)

Xun, Gloria; Dingley, Andrew; Tremouilhac, Pierre

2009-01-01

Full text: Antimicrobial proteins (AMPs) are host defence molecules that protect organisms from microbial infection. A number of hypotheses for AMP activity have been proposed which involve protein membrane interactions. However, there is a paucity of information describing AMP-membrane complexes in detail. The aim of this project is to characterise the interactions of amoebapore-A (APA-1) with membrane models using primarily solution-state NMR spectroscopy. APA-1 is an AMP which is regulated by a pH-dependent dimerisation event. Based on the atomic resolution solution structure of monomeric APA-1, it is proposed that this dimerisation is a prerequisite for ring-like hexameric pore formation. Due to the cytotoxicity of APA-1, we have developed a cell-free system to produce this protein. To facilitate our studies, we have adapted the cell-free system to isotope label APA-1. 13 C /15 N -enriched APA-1 sample was achieved and we have begun characterising APA-1 dimerisation and membrane interactions using NMR spectroscopy and other biochemical/biophysical methods. Neutron reflectometry is a surface-sensitive technique and therefore represents an ideal technique to probe how APA-1 interacts with membranes at the molecular level under different physiological conditions. Using Platypus, the pH-induced APA-1-membrane interactions should be detectable as an increase of the amount of protein adsorbed at the membrane surface and changes in the membrane properties. Specifically, detailed information of the structure and dimensions of the protein-membrane complex, the position and amount of the protein in the membrane, and the perturbation of the membrane phospholipids on protein incorporation can be extracted from the neutron reflectometry measurement. Such information will enable critical assessment of current proposed mechanisms of AMP activity in bacterial membranes and complement our NMR studies

Conformational dynamics and ligand binding in the multi-domain protein PDC109.

Directory of Open Access Journals (Sweden)

Hyun Jin Kim

2010-02-01

Full Text Available PDC109 is a modular multi-domain protein with two fibronectin type II (Fn2 repeats joined by a linker. It plays a major role in bull sperm binding to the oviductal epithelium through its interactions with phosphorylcholines (PhCs, a head group of sperm cell membrane lipids. The crystal structure of the PDC109-PhC complex shows that each PhC binds to the corresponding Fn2 domain, while the two domains are on the same face of the protein. Long timescale explicit solvent molecular dynamics (MD simulations of PDC109, in the presence and absence of PhC, suggest that PhC binding strongly correlates with the relative orientation of choline-phospholipid binding sites of the two Fn2 domains; unless the two domains tightly bind PhCs, they tend to change their relative orientation by deforming the flexible linker. The effective PDC109-PhC association constant of 28 M(-1, estimated from their potential of mean force is consistent with the experimental result. Principal component analysis of the long timescale MD simulations was compared to the significantly less expensive normal mode analysis of minimized structures. The comparison indicates that difference between relative domain motions of PDC109 with bound and unbound PhC is captured by the first principal component in the principal component analysis as well as the three lowest normal modes in the normal mode analysis. The present study illustrates the use of detailed MD simulations to clarify the energetics of specific ligand-domain interactions revealed by a static crystallographic model, as well as their influence on relative domain motions in a multi-domain protein.

Minimum Information Loss Based Multi-kernel Learning for Flagellar Protein Recognition in Trypanosoma Brucei

KAUST Repository

Wang, Jim Jing-Yan

2014-12-01

Trypanosma brucei (T. Brucei) is an important pathogen agent of African trypanosomiasis. The flagellum is an essential and multifunctional organelle of T. Brucei, thus it is very important to recognize the flagellar proteins from T. Brucei proteins for the purposes of both biological research and drug design. In this paper, we investigate computationally recognizing flagellar proteins in T. Brucei by pattern recognition methods. It is argued that an optimal decision function can be obtained as the difference of probability functions of flagella protein and the non-flagellar protein for the purpose of flagella protein recognition. We propose to learn a multi-kernel classification function to approximate this optimal decision function, by minimizing the information loss of such approximation which is measured by the Kull back-Leibler (KL) divergence. An iterative multi-kernel classifier learning algorithm is developed to minimize the KL divergence for the problem of T. Brucei flagella protein recognition, experiments show its advantage over other T. Brucei flagellar protein recognition and multi-kernel learning methods. © 2014 IEEE.

Recording information on protein complexes in an information management system.

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Savitsky, Marc; Diprose, Jonathan M; Morris, Chris; Griffiths, Susanne L; Daniel, Edward; Lin, Bill; Daenke, Susan; Bishop, Benjamin; Siebold, Christian; Wilson, Keith S; Blake, Richard; Stuart, David I; Esnouf, Robert M

2011-08-01

The Protein Information Management System (PiMS) is a laboratory information management system (LIMS) designed for use with the production of proteins in a research environment. The software is distributed under the CCP4 licence, and so is available free of charge to academic laboratories. Like most LIMS, the underlying PiMS data model originally had no support for protein-protein complexes. To support the SPINE2-Complexes project the developers have extended PiMS to meet these requirements. The modifications to PiMS, described here, include data model changes, additional protocols, some user interface changes and functionality to detect when an experiment may have formed a complex. Example data are shown for the production of a crystal of a protein complex. Integration with SPINE2-Complexes Target Tracker application is also described. Copyright © 2011 Elsevier Inc. All rights reserved.

Proteomics-Based Analysis of Protein Complexes in Pluripotent Stem Cells and Cancer Biology.

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Sudhir, Putty-Reddy; Chen, Chung-Hsuan

2016-03-22

A protein complex consists of two or more proteins that are linked together through protein-protein interactions. The proteins show stable/transient and direct/indirect interactions within the protein complex or between the protein complexes. Protein complexes are involved in regulation of most of the cellular processes and molecular functions. The delineation of protein complexes is important to expand our knowledge on proteins functional roles in physiological and pathological conditions. The genetic yeast-2-hybrid method has been extensively used to characterize protein-protein interactions. Alternatively, a biochemical-based affinity purification coupled with mass spectrometry (AP-MS) approach has been widely used to characterize the protein complexes. In the AP-MS method, a protein complex of a target protein of interest is purified using a specific antibody or an affinity tag (e.g., DYKDDDDK peptide (FLAG) and polyhistidine (His)) and is subsequently analyzed by means of MS. Tandem affinity purification, a two-step purification system, coupled with MS has been widely used mainly to reduce the contaminants. We review here a general principle for AP-MS-based characterization of protein complexes and we explore several protein complexes identified in pluripotent stem cell biology and cancer biology as examples.

Multi-iPPseEvo: A Multi-label Classifier for Identifying Human Phosphorylated Proteins by Incorporating Evolutionary Information into Chou's General PseAAC via Grey System Theory.

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Qiu, Wang-Ren; Zheng, Quan-Shu; Sun, Bi-Qian; Xiao, Xuan

2017-03-01

Predicting phosphorylation protein is a challenging problem, particularly when query proteins have multi-label features meaning that they may be phosphorylated at two or more different type amino acids. In fact, human protein usually be phosphorylated at serine, threonine and tyrosine. By introducing the "multi-label learning" approach, a novel predictor has been developed that can be used to deal with the systems containing both single- and multi-label phosphorylation protein. Here we proposed a predictor called Multi-iPPseEvo by (1) incorporating the protein sequence evolutionary information into the general pseudo amino acid composition (PseAAC) via the grey system theory, (2) balancing out the skewed training datasets by the asymmetric bootstrap approach, and (3) constructing an ensemble predictor by fusing an array of individual random forest classifiers thru a voting system. Rigorous cross-validations via a set of multi-label metrics indicate that the multi-label phosphorylation predictor is very promising and encouraging. The current approach represents a new strategy to deal with the multi-label biological problems, and the software is freely available for academic use at http://www.jci-bioinfo.cn/Multi-iPPseEvo. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Polerovirus protein P0 prevents the assembly of small RNA-containing RISC complexes and leads to degradation of ARGONAUTE1.

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Csorba, Tibor; Lózsa, Rita; Hutvágner, György; Burgyán, József

2010-05-01

RNA silencing plays an important role in plants in defence against viruses. To overcome this defence, plant viruses encode suppressors of RNA silencing. The most common mode of silencing suppression is sequestration of double-stranded RNAs involved in the antiviral silencing pathways. Viral suppressors can also overcome silencing responses through protein-protein interaction. The poleroviral P0 silencing suppressor protein targets ARGONAUTE (AGO) proteins for degradation. AGO proteins are the core component of the RNA-induced silencing complex (RISC). We found that P0 does not interfere with the slicer activity of pre-programmed siRNA/miRNA containing AGO1, but prevents de novo formation of siRNA/miRNA containing AGO1. We show that the AGO1 protein is part of a high-molecular-weight complex, suggesting the existence of a multi-protein RISC in plants. We propose that P0 prevents RISC assembly by interacting with one of its protein components, thus inhibiting formation of siRNA/miRNA-RISC, and ultimately leading to AGO1 degradation. Our findings also suggest that siRNAs enhance the stability of co-expressed AGO1 in both the presence and absence of P0.

Large-scale Complex IT Systems

OpenAIRE

Sommerville, Ian; Cliff, Dave; Calinescu, Radu; Keen, Justin; Kelly, Tim; Kwiatkowska, Marta; McDermid, John; Paige, Richard

2011-01-01

This paper explores the issues around the construction of large-scale complex systems which are built as 'systems of systems' and suggests that there are fundamental reasons, derived from the inherent complexity in these systems, why our current software engineering methods and techniques cannot be scaled up to cope with the engineering challenges of constructing such systems. It then goes on to propose a research and education agenda for software engineering that identifies the major challen...

Large-scale complex IT systems

OpenAIRE

Sommerville, Ian; Cliff, Dave; Calinescu, Radu; Keen, Justin; Kelly, Tim; Kwiatkowska, Marta; McDermid, John; Paige, Richard

2012-01-01

12 pages, 2 figures This paper explores the issues around the construction of large-scale complex systems which are built as 'systems of systems' and suggests that there are fundamental reasons, derived from the inherent complexity in these systems, why our current software engineering methods and techniques cannot be scaled up to cope with the engineering challenges of constructing such systems. It then goes on to propose a research and education agenda for software engineering that ident...

iLoc-Animal: a multi-label learning classifier for predicting subcellular localization of animal proteins.

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Lin, Wei-Zhong; Fang, Jian-An; Xiao, Xuan; Chou, Kuo-Chen

2013-04-05

Predicting protein subcellular localization is a challenging problem, particularly when query proteins have multi-label features meaning that they may simultaneously exist at, or move between, two or more different subcellular location sites. Most of the existing methods can only be used to deal with the single-label proteins. Actually, multi-label proteins should not be ignored because they usually bear some special function worthy of in-depth studies. By introducing the "multi-label learning" approach, a new predictor, called iLoc-Animal, has been developed that can be used to deal with the systems containing both single- and multi-label animal (metazoan except human) proteins. Meanwhile, to measure the prediction quality of a multi-label system in a rigorous way, five indices were introduced; they are "Absolute-True", "Absolute-False" (or Hamming-Loss"), "Accuracy", "Precision", and "Recall". As a demonstration, the jackknife cross-validation was performed with iLoc-Animal on a benchmark dataset of animal proteins classified into the following 20 location sites: (1) acrosome, (2) cell membrane, (3) centriole, (4) centrosome, (5) cell cortex, (6) cytoplasm, (7) cytoskeleton, (8) endoplasmic reticulum, (9) endosome, (10) extracellular, (11) Golgi apparatus, (12) lysosome, (13) mitochondrion, (14) melanosome, (15) microsome, (16) nucleus, (17) peroxisome, (18) plasma membrane, (19) spindle, and (20) synapse, where many proteins belong to two or more locations. For such a complicated system, the outcomes achieved by iLoc-Animal for all the aforementioned five indices were quite encouraging, indicating that the predictor may become a useful tool in this area. It has not escaped our notice that the multi-label approach and the rigorous measurement metrics can also be used to investigate many other multi-label problems in molecular biology. As a user-friendly web-server, iLoc-Animal is freely accessible to the public at the web-site .

A new theoretical approach to analyze complex processes in cytoskeleton proteins.

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Li, Xin; Kolomeisky, Anatoly B

2014-03-20

Cytoskeleton proteins are filament structures that support a large number of important biological processes. These dynamic biopolymers exist in nonequilibrium conditions stimulated by hydrolysis chemical reactions in their monomers. Current theoretical methods provide a comprehensive picture of biochemical and biophysical processes in cytoskeleton proteins. However, the description is only qualitative under biologically relevant conditions because utilized theoretical mean-field models neglect correlations. We develop a new theoretical method to describe dynamic processes in cytoskeleton proteins that takes into account spatial correlations in the chemical composition of these biopolymers. Our approach is based on analysis of probabilities of different clusters of subunits. It allows us to obtain exact analytical expressions for a variety of dynamic properties of cytoskeleton filaments. By comparing theoretical predictions with Monte Carlo computer simulations, it is shown that our method provides a fully quantitative description of complex dynamic phenomena in cytoskeleton proteins under all conditions.

Formation of protein-birnessite complex: XRD, FTIR, and AFM analysis.

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Naidja, A; Liu, C; Huang, P M

2002-07-01

Limited information is available on formation chemistry of enzyme-Mn oxide complexes. Adsorption isotherm of protein molecules (tyrosinase) on birnessite (delta-MnO(2)) at pH 6.0 and room temperature (23 degrees C) was of H type, indicating a very high affinity of the enzyme protein molecules to the birnessite mineral surfaces. After thorough washing of the protein-mineral complex with deionized-distilled water, up to 89% of adsorbed protein molecules remained bound to the mineral surfaces. When a high amount of the protein was immobilized, the X-ray diffractogram shows a significant decrease in the intensity of characteristic d-spacings of birnessite. No shift to higher values of the d-spacings of protein-birnessite complex was observed, indicating that the enzyme molecules were not intercalated in the mineral structure but immobilized at the external surfaces and the edges of the mineral oxide. By comparison to the free enzyme, infrared absorption spectra of the protein-birnessite complexes show a shift by up to 11 cm(-1) to lower frequencies in the absorption bands characteristic of amide I and II modes of the polypeptides chains. The mineral surfaces exerted some strain on the protein structure, resulting in an alteration of the protein molecular conformation after binding to the mineral colloid surfaces. In the free state, the globular protein molecules had a spheroid shape with an average cross-sectional diameter of 70+/-6 nm. The unfolding and flattening of the protein molecules after immobilization is clearly shown in atomic force micrographs. Compared to the tyrosinase-birnessite complex, similar FTIR spectra and atomic force micrographs were observed for the pure protein, bovine serum albumin (BSA), after immobilization on birnessite. The information obtained in this study is of fundamental significance for understanding birnessite as an adsorbent of biopolymers and the catalytic role of the enzyme-birnessite complex.

Mechanisms of Host-Pathogen Protein Complex Formation and Bacterial Immune Evasion of Streptococcus suis Protein Fhb.

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Li, Xueqin; Liu, Peng; Gan, Shuzhen; Zhang, Chunmao; Zheng, Yuling; Jiang, Yongqiang; Yuan, Yuan

2016-08-12

Streptococcus suis serotype 2 (S. suis 2)-induced sepsis and meningitis are often accompanied by bacteremia. The evasion of polymorphonuclear leukocyte-mediated phagocytic clearance is central to the establishment of bacteremia caused by S. suis 2 and is facilitated by the ability of factor H (FH)-binding protein (Fhb) to bind FH on the bacterial surface, thereby impeding alternative pathway complement activation and phagocytic clearance. Here, C3b/C3d was found to bind to Fhb, along with FH, forming a large immune complex. The formation of this immune complex was mediated by domain II of Fhb via electrostatic and hydrophobic interactions, which, to our knowledge, is a new type of interaction. Interestingly, Fhb was found to be associated with the cell envelope and also present in the culture supernatant, where secreted Fhb inhibited complement activation via interactions with domain II, thereby enhancing antiphagocytic clearance by polymorphonuclear leukocytes. Thus, Fhb is a multifunctional bacterial protein, which binds host complement component C3 as well as FH and interferes with innate immune recognition in a secret protein manner. S. suis 2 therefore appears to have developed a new strategy to combat host innate immunity and enhance survival in host blood. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Mechanisms of Host-Pathogen Protein Complex Formation and Bacterial Immune Evasion of Streptococcus suis Protein Fhb*

Science.gov (United States)

Li, Xueqin; Liu, Peng; Gan, Shuzhen; Zhang, Chunmao; Zheng, Yuling; Jiang, Yongqiang; Yuan, Yuan

2016-01-01

Streptococcus suis serotype 2 (S. suis 2)-induced sepsis and meningitis are often accompanied by bacteremia. The evasion of polymorphonuclear leukocyte-mediated phagocytic clearance is central to the establishment of bacteremia caused by S. suis 2 and is facilitated by the ability of factor H (FH)-binding protein (Fhb) to bind FH on the bacterial surface, thereby impeding alternative pathway complement activation and phagocytic clearance. Here, C3b/C3d was found to bind to Fhb, along with FH, forming a large immune complex. The formation of this immune complex was mediated by domain II of Fhb via electrostatic and hydrophobic interactions, which, to our knowledge, is a new type of interaction. Interestingly, Fhb was found to be associated with the cell envelope and also present in the culture supernatant, where secreted Fhb inhibited complement activation via interactions with domain II, thereby enhancing antiphagocytic clearance by polymorphonuclear leukocytes. Thus, Fhb is a multifunctional bacterial protein, which binds host complement component C3 as well as FH and interferes with innate immune recognition in a secret protein manner. S. suis 2 therefore appears to have developed a new strategy to combat host innate immunity and enhance survival in host blood. PMID:27342778

Automation of multi-agent control for complex dynamic systems in heterogeneous computational network

Science.gov (United States)

Oparin, Gennady; Feoktistov, Alexander; Bogdanova, Vera; Sidorov, Ivan

2017-01-01

The rapid progress of high-performance computing entails new challenges related to solving large scientific problems for various subject domains in a heterogeneous distributed computing environment (e.g., a network, Grid system, or Cloud infrastructure). The specialists in the field of parallel and distributed computing give the special attention to a scalability of applications for problem solving. An effective management of the scalable application in the heterogeneous distributed computing environment is still a non-trivial issue. Control systems that operate in networks, especially relate to this issue. We propose a new approach to the multi-agent management for the scalable applications in the heterogeneous computational network. The fundamentals of our approach are the integrated use of conceptual programming, simulation modeling, network monitoring, multi-agent management, and service-oriented programming. We developed a special framework for an automation of the problem solving. Advantages of the proposed approach are demonstrated on the parametric synthesis example of the static linear regulator for complex dynamic systems. Benefits of the scalable application for solving this problem include automation of the multi-agent control for the systems in a parallel mode with various degrees of its detailed elaboration.

A multi-element cosmological model with a complex space-time topology

Science.gov (United States)

Kardashev, N. S.; Lipatova, L. N.; Novikov, I. D.; Shatskiy, A. A.

2015-02-01

Wormhole models with a complex topology having one entrance and two exits into the same space-time of another universe are considered, as well as models with two entrances from the same space-time and one exit to another universe. These models are used to build a model of a multi-sheeted universe (a multi-element model of the "Multiverse") with a complex topology. Spherical symmetry is assumed in all the models. A Reissner-Norström black-hole model having no singularity beyond the horizon is constructed. The strength of the central singularity of the black hole is analyzed.

Ensemble Linear Neighborhood Propagation for Predicting Subchloroplast Localization of Multi-Location Proteins.

Science.gov (United States)

Wan, Shibiao; Mak, Man-Wai; Kung, Sun-Yuan

2016-12-02

In the postgenomic era, the number of unreviewed protein sequences is remarkably larger and grows tremendously faster than that of reviewed ones. However, existing methods for protein subchloroplast localization often ignore the information from these unlabeled proteins. This paper proposes a multi-label predictor based on ensemble linear neighborhood propagation (LNP), namely, LNP-Chlo, which leverages hybrid sequence-based feature information from both labeled and unlabeled proteins for predicting localization of both single- and multi-label chloroplast proteins. Experimental results on a stringent benchmark dataset and a novel independent dataset suggest that LNP-Chlo performs at least 6% (absolute) better than state-of-the-art predictors. This paper also demonstrates that ensemble LNP significantly outperforms LNP based on individual features. For readers' convenience, the online Web server LNP-Chlo is freely available at http://bioinfo.eie.polyu.edu.hk/LNPChloServer/ .

A multi-target caffeine derived rhodium(i) N-heterocyclic carbene complex: evaluation of the mechanism of action.

Science.gov (United States)

Zhang, Jing-Jing; Muenzner, Julienne K; Abu El Maaty, Mohamed A; Karge, Bianka; Schobert, Rainer; Wölfl, Stefan; Ott, Ingo

2016-08-16

A rhodium(i) and a ruthenium(ii) complex with a caffeine derived N-heterocyclic carbene (NHC) ligand were biologically investigated as organometallic conjugates consisting of a metal center and a naturally occurring moiety. While the ruthenium(ii) complex was largely inactive, the rhodium(i) NHC complex displayed selective cytotoxicity and significant anti-metastatic and in vivo anti-vascular activities and acted as both a mammalian and an E. coli thioredoxin reductase inhibitor. In HCT-116 cells it increased the reactive oxygen species level, leading to DNA damage, and it induced cell cycle arrest, decreased the mitochondrial membrane potential, and triggered apoptosis. This rhodium(i) NHC derivative thus represents a multi-target compound with promising anti-cancer potential.

Analysis of Proteins, Protein Complexes, and Organellar Proteomes Using Sheathless Capillary Zone Electrophoresis - Native Mass Spectrometry

Science.gov (United States)

Belov, Arseniy M.; Viner, Rosa; Santos, Marcia R.; Horn, David M.; Bern, Marshall; Karger, Barry L.; Ivanov, Alexander R.

2017-12-01

Native mass spectrometry (MS) is a rapidly advancing field in the analysis of proteins, protein complexes, and macromolecular species of various types. The majority of native MS experiments reported to-date has been conducted using direct infusion of purified analytes into a mass spectrometer. In this study, capillary zone electrophoresis (CZE) was coupled online to Orbitrap mass spectrometers using a commercial sheathless interface to enable high-performance separation, identification, and structural characterization of limited amounts of purified proteins and protein complexes, the latter with preserved non-covalent associations under native conditions. The performance of both bare-fused silica and polyacrylamide-coated capillaries was assessed using mixtures of protein standards known to form non-covalent protein-protein and protein-ligand complexes. High-efficiency separation of native complexes is demonstrated using both capillary types, while the polyacrylamide neutral-coated capillary showed better reproducibility and higher efficiency for more complex samples. The platform was then evaluated for the determination of monoclonal antibody aggregation and for analysis of proteomes of limited complexity using a ribosomal isolate from E. coli. Native CZE-MS, using accurate single stage and tandem-MS measurements, enabled identification of proteoforms and non-covalent complexes at femtomole levels. This study demonstrates that native CZE-MS can serve as an orthogonal and complementary technique to conventional native MS methodologies with the advantages of low sample consumption, minimal sample processing and losses, and high throughput and sensitivity. This study presents a novel platform for analysis of ribosomes and other macromolecular complexes and organelles, with the potential for discovery of novel structural features defining cellular phenotypes (e.g., specialized ribosomes). [Figure not available: see fulltext.

Multi-scale carbon micro/nanofibers-based adsorbents for protein immobilization

Energy Technology Data Exchange (ETDEWEB)

Singh, Shiv; Singh, Abhinav [Department of Chemical Engineering, Indian Institute of Technology Kanpur, Kanpur 208016 (India); Bais, Vaibhav Sushil Singh; Prakash, Balaji [Department of Biological Science and Bioengineering, Indian Institute of Technology Kanpur, Kanpur 208016 (India); Verma, Nishith, E-mail: nishith@iitk.ac.in [Department of Chemical Engineering, Indian Institute of Technology Kanpur, Kanpur 208016 (India); Center for Environmental Science and Engineering, Indian Institute of Technology Kanpur, Kanpur 208016 (India)

2014-05-01

In the present study, different proteins, namely, bovine serum albumin (BSA), glucose oxidase (GOx) and the laboratory purified YqeH were immobilized in the phenolic resin precursor-based multi-scale web of activated carbon microfibers (ACFs) and carbon nanofibers (CNFs). These biomolecules are characteristically different from each other, having different structure, number of parent amino acid molecules and isoelectric point. CNF was grown on ACF substrate by chemical vapor deposition, using Ni nanoparticles (Nps) as the catalyst. The ultra-sonication of the CNFs was carried out in acidic medium to remove Ni Nps from the tip of the CNFs to provide additional active sites for adsorption. The prepared material was directly used as an adsorbent for proteins, without requiring any additional treatment. Several analytical techniques were used to characterize the prepared materials, including scanning electron microscopy, Fourier transform infrared spectroscopy, BET surface area, pore-size distribution, and UV–vis spectroscopy. The adsorption capacities of prepared ACFs/CNFs in this study were determined to be approximately 191, 39 and 70 mg/g for BSA, GOx and YqeH, respectively, revealing that the carbon micro-nanofibers forming synthesized multi-scale web are efficient materials for the immobilization of protein molecules. - Highlights: • Ni metal Np-dispersed carbon micro-nanofibers (ACFs/CNFs) are prepared. • ACFs/CNFs are mesoporous. • Significant adsorption of BSA, GOx and YqeH is observed on ACFs/CNFs. • Multi-scale web of ACFs/CNFs is effective for protein immobilization.

Preparation of a large-scale and multi-layer molybdenum crystal and its characteristics

International Nuclear Information System (INIS)

Fujii, Tadayuki

1989-01-01

In the present work, the secondary recrystallization method was applied to obtain a large-scale and multi-layer crystal from a hot-rolled multi-laminated molybdenum sheet doped and stacked alternately with different amounts of dopant. It was found that the time and/or temperature at which secondary recrystallization commence from the multi- layer sheet is strongly dependent on the amounts of dopants. Therefore the potential nucleus of the secondary grain from layers with different amounts of dopant occurred first at the layer with a small amount of dopant and then grew into the layer with a large amount of dopant after an anneal at 1800 0 C-2000 0 C. Consequently a large -scale and multi-layer molybdenum crystal can easily be obtained. 12 refs., 9 figs., 2 tabs. (Author)

Bombyx mori and Aedes aegypti form multi-functional immune complexes that integrate pattern recognition, melanization, coagulants, and hemocyte recruitment.

Science.gov (United States)

Phillips, Dennis R; Clark, Kevin D

2017-01-01

The innate immune system of insects responds to wounding and pathogens by mobilizing multiple pathways that provide both systemic and localized protection. Key localized responses in hemolymph include melanization, coagulation, and hemocyte encapsulation, which synergistically seal wounds and envelop and destroy pathogens. To be effective, these pathways require a targeted deposition of their components to provide protection without compromising the host. Extensive research has identified a large number of the effectors that comprise these responses, but questions remain regarding their post-translational processing, function, and targeting. Here, we used mass spectrometry to demonstrate the integration of pathogen recognition proteins, coagulants, and melanization components into stable, high-mass, multi-functional Immune Complexes (ICs) in Bombyx mori and Aedes aegypti. Essential proteins common to both include phenoloxidases, apolipophorins, serine protease homologs, and a serine protease that promotes hemocyte recruitment through cytokine activation. Pattern recognition proteins included C-type Lectins in B. mori, while A. aegypti contained a protein homologous to Plasmodium-resistant LRIM1 from Anopheles gambiae. We also found that the B. mori IC is stabilized by extensive transglutaminase-catalyzed cross-linking of multiple components. The melanization inhibitor Egf1.0, from the parasitoid wasp Microplitis demolitor, blocked inclusion of specific components into the IC and also inhibited transglutaminase activity. Our results show how coagulants, melanization components, and hemocytes can be recruited to a wound surface or pathogen, provide insight into the mechanism by which a parasitoid evades this immune response, and suggest that insects as diverse as Lepidoptera and Diptera utilize similar defensive mechanisms.

HPSLPred: An Ensemble Multi-Label Classifier for Human Protein Subcellular Location Prediction with Imbalanced Source.

Science.gov (United States)

Wan, Shixiang; Duan, Yucong; Zou, Quan

2017-09-01

Predicting the subcellular localization of proteins is an important and challenging problem. Traditional experimental approaches are often expensive and time-consuming. Consequently, a growing number of research efforts employ a series of machine learning approaches to predict the subcellular location of proteins. There are two main challenges among the state-of-the-art prediction methods. First, most of the existing techniques are designed to deal with multi-class rather than multi-label classification, which ignores connections between multiple labels. In reality, multiple locations of particular proteins imply that there are vital and unique biological significances that deserve special focus and cannot be ignored. Second, techniques for handling imbalanced data in multi-label classification problems are necessary, but never employed. For solving these two issues, we have developed an ensemble multi-label classifier called HPSLPred, which can be applied for multi-label classification with an imbalanced protein source. For convenience, a user-friendly webserver has been established at http://server.malab.cn/HPSLPred. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Multi-segmental movement patterns reflect juggling complexity and skill level.

Science.gov (United States)

Zago, Matteo; Pacifici, Ilaria; Lovecchio, Nicola; Galli, Manuela; Federolf, Peter Andreas; Sforza, Chiarella

2017-08-01

The juggling action of six experts and six intermediates jugglers was recorded with a motion capture system and decomposed into its fundamental components through Principal Component Analysis. The aim was to quantify trends in movement dimensionality, multi-segmental patterns and rhythmicity as a function of proficiency level and task complexity. Dimensionality was quantified in terms of Residual Variance, while the Relative Amplitude was introduced to account for individual differences in movement components. We observed that: experience-related modifications in multi-segmental actions exist, such as the progressive reduction of error-correction movements, especially in complex task condition. The systematic identification of motor patterns sensitive to the acquisition of specific experience could accelerate the learning process. Copyright © 2017 Elsevier B.V. All rights reserved.

Sequence-specific capture of protein-DNA complexes for mass spectrometric protein identification.

Directory of Open Access Journals (Sweden)

Cheng-Hsien Wu

Full Text Available The regulation of gene transcription is fundamental to the existence of complex multicellular organisms such as humans. Although it is widely recognized that much of gene regulation is controlled by gene-specific protein-DNA interactions, there presently exists little in the way of tools to identify proteins that interact with the genome at locations of interest. We have developed a novel strategy to address this problem, which we refer to as GENECAPP, for Global ExoNuclease-based Enrichment of Chromatin-Associated Proteins for Proteomics. In this approach, formaldehyde cross-linking is employed to covalently link DNA to its associated proteins; subsequent fragmentation of the DNA, followed by exonuclease digestion, produces a single-stranded region of the DNA that enables sequence-specific hybridization capture of the protein-DNA complex on a solid support. Mass spectrometric (MS analysis of the captured proteins is then used for their identification and/or quantification. We show here the development and optimization of GENECAPP for an in vitro model system, comprised of the murine insulin-like growth factor-binding protein 1 (IGFBP1 promoter region and FoxO1, a member of the forkhead rhabdomyosarcoma (FoxO subfamily of transcription factors, which binds specifically to the IGFBP1 promoter. This novel strategy provides a powerful tool for studies of protein-DNA and protein-protein interactions.

Wongabel Rhabdovirus Accessory Protein U3 Targets the SWI/SNF Chromatin Remodeling Complex

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Joubert, D. Albert; Rodriguez-Andres, Julio; Monaghan, Paul; Cummins, Michelle; McKinstry, William J.; Paradkar, Prasad N.; Moseley, Gregory W.

2014-01-01

ABSTRACT Wongabel virus (WONV) is an arthropod-borne rhabdovirus that infects birds. It is one of the growing array of rhabdoviruses with complex genomes that encode multiple accessory proteins of unknown function. In addition to the five canonical rhabdovirus structural protein genes (N, P, M, G, and L), the 13.2-kb negative-sense single-stranded RNA (ssRNA) WONV genome contains five uncharacterized accessory genes, one overlapping the N gene (Nx or U4), three located between the P and M genes (U1 to U3), and a fifth one overlapping the G gene (Gx or U5). Here we show that WONV U3 is expressed during infection in insect and mammalian cells and is required for efficient viral replication. A yeast two-hybrid screen against a mosquito cell cDNA library identified that WONV U3 interacts with the 83-amino-acid (aa) C-terminal domain of SNF5, a component of the SWI/SNF chromatin remodeling complex. The interaction was confirmed by affinity chromatography, and nuclear colocalization was established by confocal microscopy. Gene expression studies showed that SNF5 transcripts are upregulated during infection of mosquito cells with WONV, as well as West Nile virus (Flaviviridae) and bovine ephemeral fever virus (Rhabdoviridae), and that SNF5 knockdown results in increased WONV replication. WONV U3 also inhibits SNF5-regulated expression of the cytokine gene CSF1. The data suggest that WONV U3 targets the SWI/SNF complex to block the host response to infection. IMPORTANCE The rhabdoviruses comprise a large family of RNA viruses infecting plants, vertebrates, and invertebrates. In addition to the major structural proteins (N, P, M, G, and L), many rhabdoviruses encode a diverse array of accessory proteins of largely unknown function. Understanding the role of these proteins may reveal much about host-pathogen interactions in infected cells. Here we examine accessory protein U3 of Wongabel virus, an arthropod-borne rhabdovirus that infects birds. We show that U3 enters the

Benchmarking multi-dimensional large strain consolidation analyses

International Nuclear Information System (INIS)

Priestley, D.; Fredlund, M.D.; Van Zyl, D.

2010-01-01

Analyzing the consolidation of tailings slurries and dredged fills requires a more extensive formulation than is used for common (small strain) consolidation problems. Large strain consolidation theories have traditionally been limited to 1-D formulations. SoilVision Systems has developed the capacity to analyze large strain consolidation problems in 2 and 3-D. The benchmarking of such formulations is not a trivial task. This paper presents several examples of modeling large strain consolidation in the beta versions of the new software. These examples were taken from the literature and were used to benchmark the large strain formulation used by the new software. The benchmarks reported here are: a comparison to the consolidation software application CONDES0, Townsend's Scenario B and a multi-dimensional analysis of long-term column tests performed on oil sands tailings. All three of these benchmarks were attained using the SVOffice suite. (author)

The method of measurement and synchronization control for large-scale complex loading system

International Nuclear Information System (INIS)

Liao Min; Li Pengyuan; Hou Binglin; Chi Chengfang; Zhang Bo

2012-01-01

With the development of modern industrial technology, measurement and control system was widely used in high precision, complex industrial control equipment and large-tonnage loading device. The measurement and control system is often used to analyze the distribution of stress and displacement in the complex bearing load or the complex nature of the mechanical structure itself. In ITER GS mock-up with 5 flexible plates, for each load combination, detect and measure potential slippage between the central flexible plate and the neighboring spacers is necessary as well as the potential slippage between each pre-stressing bar and its neighboring plate. The measurement and control system consists of seven sets of EDC controller and board, computer system, 16-channel quasi-dynamic strain gauge, 25 sets of displacement sensors, 7 sets of load and displacement sensors in the cylinders. This paper demonstrates the principles and methods of EDC220 digital controller to achieve synchronization control, and R and D process of multi-channel loading control software and measurement software. (authors)

Multi-Level Formation of Complex Software Systems

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Hui Li

2016-05-01

Full Text Available We present a multi-level formation model for complex software systems. The previous works extract the software systems to software networks for further studies, but usually investigate the software networks at the class level. In contrast to these works, our treatment of software systems as multi-level networks is more realistic. In particular, the software networks are organized by three levels of granularity, which represents the modularity and hierarchy in the formation process of real-world software systems. More importantly, simulations based on this model have generated more realistic structural properties of software networks, such as power-law, clustering and modularization. On the basis of this model, how the structure of software systems effects software design principles is then explored, and it could be helpful for understanding software evolution and software engineering practices.

Protein Complex Production from the Drug Discovery Standpoint.

Science.gov (United States)

Moarefi, Ismail

2016-01-01

Small molecule drug discovery critically depends on the availability of meaningful in vitro assays to guide medicinal chemistry programs that are aimed at optimizing drug potency and selectivity. As it becomes increasingly evident, most disease relevant drug targets do not act as a single protein. In the body, they are instead generally found in complex with protein cofactors that are highly relevant for their correct function and regulation. This review highlights selected examples of the increasing trend to use biologically relevant protein complexes for rational drug discovery to reduce costly late phase attritions due to lack of efficacy or toxicity.

Operon Gene Order Is Optimized for Ordered Protein Complex Assembly

Science.gov (United States)

Wells, Jonathan N.; Bergendahl, L. Therese; Marsh, Joseph A.

2016-01-01

Summary The assembly of heteromeric protein complexes is an inherently stochastic process in which multiple genes are expressed separately into proteins, which must then somehow find each other within the cell. Here, we considered one of the ways by which prokaryotic organisms have attempted to maximize the efficiency of protein complex assembly: the organization of subunit-encoding genes into operons. Using structure-based assembly predictions, we show that operon gene order has been optimized to match the order in which protein subunits assemble. Exceptions to this are almost entirely highly expressed proteins for which assembly is less stochastic and for which precisely ordered translation offers less benefit. Overall, these results show that ordered protein complex assembly pathways are of significant biological importance and represent a major evolutionary constraint on operon gene organization. PMID:26804901

UO{sub 2}{sup 2+}/protein complexation sites screening

Energy Technology Data Exchange (ETDEWEB)

Guilbaud, P.; Pible, O

2004-07-01

Uranium(VI) is likely to make strong coordination with some proteins in the plasma and in targeted cells. In the frame of a nuclear toxicology program, a biochemical strategy has been developed to identify these targets in complex biological media. The present work focuses on an approach based on the screening of 3D protein structures in order to identify proteins able to bind UO{sub 2}{sup 2+} and the corresponding complexation sites in these proteins. Our preliminary results show that indeed a few proteins display a high affinity to uranyl salt. The site of interaction may be mapped using molecular modeling, providing coherent results with the biochemical data. (authors)

Multi-stage decoding of multi-level modulation codes

Science.gov (United States)

Lin, Shu; Kasami, Tadao; Costello, Daniel J., Jr.

1991-01-01

Various types of multi-stage decoding for multi-level modulation codes are investigated. It is shown that if the component codes of a multi-level modulation code and types of decoding at various stages are chosen properly, high spectral efficiency and large coding gain can be achieved with reduced decoding complexity. Particularly, it is shown that the difference in performance between the suboptimum multi-stage soft-decision maximum likelihood decoding of a modulation code and the single-stage optimum soft-decision decoding of the code is very small, only a fraction of dB loss in signal to noise ratio at a bit error rate (BER) of 10(exp -6).

Assembly and structural organization of pigment-protein complexes in membranes of Rhodopseudomonas sphaeroides

International Nuclear Information System (INIS)

Hunter, C.N.; Pennoyer, J.D.; Niederman, R.A.

1982-01-01

The B875 and B800-850 light-harvesting pigment-protein complexes of Rhodopseudomonas sphaeroides are characterized further by lithium dodecyl sulfate/polyacrylamide gel electrophoresis at 4 degrees C. Bacteriochlorophyll a was shown in reconstruction studies to remain complexed with its respective binding proteins during this procedure. From distributions in these gels, a quantitative description for the arrangement of the complexes is proposed. Assembly of the complexes was examined in delta-aminolevulinate-requiring mutant H-5 after a shift from high- to low-light intensity. After 10 h of delta-[ 3 H]aminolevulinate labeling, the specific radioactivity of bacteriochlorophyll in a fraction containing putative membrane invaginations reached the maximal level, while that of the mature photosynthetic membrane was at only one-third this level. This suggests that membrane invaginations are sites of preferential bacteriochlorophyll synthesis in which completed pigment-proteins exist transiently. Analysis of the 3 H distribution after electrophoretic separation further suggests that photosynthetic membranes grow mainly by addition of B800-850 to preformed membrane consisting largely of B875 and photochemical reaction centers. These results corroborate the above model for the structural organization of the light-harvesting system and indicate that the structurally and functionally discrete B800-850 pool is not completely assembled until all B875 sites for B800-850 interactions are occupied

Effects of ionizing radiations on DNA-protein complexes

International Nuclear Information System (INIS)

Gillard, N.

2005-11-01

The radio-induced destruction of DNA-protein complexes may have serious consequences for systems implicated in important cellular functions. The first system which has been studied is the lactose operon system, that regulates gene expression in Escherichia coli. First of all, the repressor-operator complex is destroyed after irradiation of the complex or of the protein alone. The damaging of the domain of repressor binding to DNA (headpiece) has been demonstrated and studied from the point of view of peptide chain integrity, conformation and amino acids damages. Secondly, dysfunctions of the in vitro induction of an irradiated repressor-unirradiated DNA complex have been observed. These perturbations, due to a decrease of the number of inducer binding sites, are correlated to the damaging of tryptophan residues. Moreover, the inducer protects the repressor when they are irradiated together, both by acting as a scavenger in the bulk, and by the masking of its binding site on the protein. The second studied system is formed by Fpg (for Formamido pyrimidine glycosylase), a DNA repair protein and a DNA with an oxidative lesion. The results show that irradiation disturbs the repair both by decreasing its efficiency of DNA lesion recognition and binding, and by altering its enzymatic activity. (author)

Carotenoid-protein complexes and their stability towards oxygen and radiation

International Nuclear Information System (INIS)

Ramakrishnan, T.V.; Francis, F.J.

1980-01-01

Carotenoid-protein complexes isolated from fresh mangoes were found to be more stable to oxygen and radiation when dissolved in water as compared with β-carotene in petroleum ether. Part of the pigment could be released from the complex by gamma irradiation. Observations on the stability of the carotenoid (98% β-carotene) in the complex indicated that the pigment is either associated with the lipid prosthetic group of the protein or loosely attached to the protein by weak hydrophobic bonds. (author)

Rapamycin-binding FKBP25 associates with diverse proteins that form large intracellular entities

International Nuclear Information System (INIS)

Galat, Andrzej; Thai, Robert

2014-01-01

Highlights: • The hFKBP25 interacts with diverse components of macromolecular entities. • We show that the endogenous human FKBP25 is bound to polyribosomes. • The endogenous hFKBP25 co-immunoprecipitated with nucleosomal proteins. • FKBP25 could induce conformational switch in macromolecular complexes. - Abstract: In this paper, we show some evidence that a member of the FK506-binding proteins, FKBP25 is associated to diverse components that are part of several different intracellular large-molecular mass entities. The FKBP25 is a high-affinity rapamycin-binding immunophilin, which has nuclear translocation signals present in its PPIase domain but it was detected both in the cytoplasm compartment and in the nuclear proteome. Analyses of antiFKBP25-immunoprecipitated proteins have revealed that the endogenous FKBP25 is associated to the core histones of the nucleosome, and with several proteins forming spliceosomal complexes and ribosomal subunits. Using polyclonal antiFKBP25 we have detected FKBP25 associated with polyribosomes. Added RNAs or 0.5 M NaCl release FKBP25 that was associated with the polyribosomes indicating that the immunophilin has an intrinsic capacity to form complexes with polyribonucleotides via its charged surface patches. Rapamycin or FK506 treatments of the polyribosomes isolated from porcine brain, HeLa and K568 cells caused a residual release of the endogenous FKBP25, which suggests that the immunophilin also binds to some proteins via its PPIase cavity. Our proteomics study indicates that the nuclear pool of the FKBP25 targets various nuclear proteins that are crucial for packaging of DNA, chromatin remodeling and pre-mRNA splicing whereas the cytosolic pool of this immunophilin is bound to some components of the ribosome

Rapamycin-binding FKBP25 associates with diverse proteins that form large intracellular entities

Energy Technology Data Exchange (ETDEWEB)

Galat, Andrzej, E-mail: galat@dsvidf.cea.fr; Thai, Robert

2014-08-08

Highlights: • The hFKBP25 interacts with diverse components of macromolecular entities. • We show that the endogenous human FKBP25 is bound to polyribosomes. • The endogenous hFKBP25 co-immunoprecipitated with nucleosomal proteins. • FKBP25 could induce conformational switch in macromolecular complexes. - Abstract: In this paper, we show some evidence that a member of the FK506-binding proteins, FKBP25 is associated to diverse components that are part of several different intracellular large-molecular mass entities. The FKBP25 is a high-affinity rapamycin-binding immunophilin, which has nuclear translocation signals present in its PPIase domain but it was detected both in the cytoplasm compartment and in the nuclear proteome. Analyses of antiFKBP25-immunoprecipitated proteins have revealed that the endogenous FKBP25 is associated to the core histones of the nucleosome, and with several proteins forming spliceosomal complexes and ribosomal subunits. Using polyclonal antiFKBP25 we have detected FKBP25 associated with polyribosomes. Added RNAs or 0.5 M NaCl release FKBP25 that was associated with the polyribosomes indicating that the immunophilin has an intrinsic capacity to form complexes with polyribonucleotides via its charged surface patches. Rapamycin or FK506 treatments of the polyribosomes isolated from porcine brain, HeLa and K568 cells caused a residual release of the endogenous FKBP25, which suggests that the immunophilin also binds to some proteins via its PPIase cavity. Our proteomics study indicates that the nuclear pool of the FKBP25 targets various nuclear proteins that are crucial for packaging of DNA, chromatin remodeling and pre-mRNA splicing whereas the cytosolic pool of this immunophilin is bound to some components of the ribosome.

Feasibility of using sodium chloride as a tracer for the characterization of the distribution of matter in complex multi-compartment 3D bioreactors for stem cell culture.

Science.gov (United States)

Gerlach, Jörg C; Witaschek, Tom; Strobel, Catrin; Brayfield, Candace A; Bornemann, Reinhard; Catapano, Gerardo; Zeilinger, Katrin

2010-06-01

The experimental characterization of the distribution of matter in complex multi-compartment three-dimensional membrane bioreactors for human cell culture is complicated by tracer interactions with the membranes and other bioreactor constituents. This is due to the fact that membranes with a high specific surface area often feature a hydrophobic chemical backbone that may adsorb tracers often used to this purpose, such as proteins and dyes. Membrane selectivity, and its worsening caused by protein adsorption, may also hinder tracer transfer across neighboring compartments, thus preventing effective characterization of the distribution of matter in the whole bioreactor. Tracer experiments with sodium chloride (NaCl) may overcome some of these limitations and be effectively used to characterize the distribution of matter in complex 3D multi-compartments membrane bioreactors for stem cell culture. NaCl freely permeates most used membranes, it does not adsorb on uncharged membranes, and its concentration may be accurately measured in terms of solution conductivity. In this preliminary study, the feasibility of complex multi-compartment membrane bioreactors was investigated with a NaCl concentration pulse challenge to characterize how their distribution of matter changes when they are operated under different conditions. In particular, bioreactors consisting of three different membrane types stacked on top of one another to form a 3D network were characterized under different feed conditions.

Protein (multi-)location prediction: using location inter-dependencies in a probabilistic framework

Science.gov (United States)

2014-01-01

Motivation Knowing the location of a protein within the cell is important for understanding its function, role in biological processes, and potential use as a drug target. Much progress has been made in developing computational methods that predict single locations for proteins. Most such methods are based on the over-simplifying assumption that proteins localize to a single location. However, it has been shown that proteins localize to multiple locations. While a few recent systems attempt to predict multiple locations of proteins, their performance leaves much room for improvement. Moreover, they typically treat locations as independent and do not attempt to utilize possible inter-dependencies among locations. Our hypothesis is that directly incorporating inter-dependencies among locations into both the classifier-learning and the prediction process can improve location prediction performance. Results We present a new method and a preliminary system we have developed that directly incorporates inter-dependencies among locations into the location-prediction process of multiply-localized proteins. Our method is based on a collection of Bayesian network classifiers, where each classifier is used to predict a single location. Learning the structure of each Bayesian network classifier takes into account inter-dependencies among locations, and the prediction process uses estimates involving multiple locations. We evaluate our system on a dataset of single- and multi-localized proteins (the most comprehensive protein multi-localization dataset currently available, derived from the DBMLoc dataset). Our results, obtained by incorporating inter-dependencies, are significantly higher than those obtained by classifiers that do not use inter-dependencies. The performance of our system on multi-localized proteins is comparable to a top performing system (YLoc+), without being restricted only to location-combinations present in the training set. PMID:24646119

Protein (multi-)location prediction: using location inter-dependencies in a probabilistic framework.

Science.gov (United States)

Simha, Ramanuja; Shatkay, Hagit

2014-03-19

Knowing the location of a protein within the cell is important for understanding its function, role in biological processes, and potential use as a drug target. Much progress has been made in developing computational methods that predict single locations for proteins. Most such methods are based on the over-simplifying assumption that proteins localize to a single location. However, it has been shown that proteins localize to multiple locations. While a few recent systems attempt to predict multiple locations of proteins, their performance leaves much room for improvement. Moreover, they typically treat locations as independent and do not attempt to utilize possible inter-dependencies among locations. Our hypothesis is that directly incorporating inter-dependencies among locations into both the classifier-learning and the prediction process can improve location prediction performance. We present a new method and a preliminary system we have developed that directly incorporates inter-dependencies among locations into the location-prediction process of multiply-localized proteins. Our method is based on a collection of Bayesian network classifiers, where each classifier is used to predict a single location. Learning the structure of each Bayesian network classifier takes into account inter-dependencies among locations, and the prediction process uses estimates involving multiple locations. We evaluate our system on a dataset of single- and multi-localized proteins (the most comprehensive protein multi-localization dataset currently available, derived from the DBMLoc dataset). Our results, obtained by incorporating inter-dependencies, are significantly higher than those obtained by classifiers that do not use inter-dependencies. The performance of our system on multi-localized proteins is comparable to a top performing system (YLoc+), without being restricted only to location-combinations present in the training set.

A Complex Systems Approach to More Resilient Multi-Layered Security Systems

Energy Technology Data Exchange (ETDEWEB)

Brown, Nathanael J. K. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Jones, Katherine A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Bandlow, Alisa [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Nozick, Linda Karen [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Waddell, Lucas [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Levin, Drew [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Whetzel, Jonathan [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2016-09-01

In July 2012, protestors cut through security fences and gained access to the Y-12 National Security Complex. This was believed to be a highly reliable, multi-layered security system. This report documents the results of a Laboratory Directed Research and Development (LDRD) project that created a consistent, robust mathematical framework using complex systems analysis algorithms and techniques to better understand the emergent behavior, vulnerabilities and resiliency of multi-layered security systems subject to budget constraints and competing security priorities. Because there are several dimensions to security system performance and a range of attacks that might occur, the framework is multi-objective for a performance frontier to be estimated. This research explicitly uses probability of intruder interruption given detection (P_I) as the primary resilience metric. We demonstrate the utility of this framework with both notional as well as real-world examples of Physical Protection Systems (PPSs) and validate using a well-established force-on-force simulation tool, Umbra.

Immersion freezing of ice nucleation active protein complexes

Directory of Open Access Journals (Sweden)

S. Hartmann

2013-06-01

Full Text Available Utilising the Leipzig Aerosol Cloud Interaction Simulator (LACIS, the immersion freezing behaviour of droplet ensembles containing monodisperse particles, generated from a Snomax™ solution/suspension, was investigated. Thereto ice fractions were measured in the temperature range between −5 °C to −38 °C. Snomax™ is an industrial product applied for artificial snow production and contains Pseudomonas syringae} bacteria which have long been used as model organism for atmospheric relevant ice nucleation active (INA bacteria. The ice nucleation activity of such bacteria is controlled by INA protein complexes in their outer membrane. In our experiments, ice fractions increased steeply in the temperature range from about −6 °C to about −10 °C and then levelled off at ice fractions smaller than one. The plateau implies that not all examined droplets contained an INA protein complex. Assuming the INA protein complexes to be Poisson distributed over the investigated droplet populations, we developed the CHESS model (stoCHastic modEl of similar and poiSSon distributed ice nuclei which allows for the calculation of ice fractions as function of temperature and time for a given nucleation rate. Matching calculated and measured ice fractions, we determined and parameterised the nucleation rate of INA protein complexes exhibiting class III ice nucleation behaviour. Utilising the CHESS model, together with the determined nucleation rate, we compared predictions from the model to experimental data from the literature and found good agreement. We found that (a the heterogeneous ice nucleation rate expression quantifying the ice nucleation behaviour of the INA protein complex is capable of describing the ice nucleation behaviour observed in various experiments for both, Snomax™ and P. syringae bacteria, (b the ice nucleation rate, and its temperature dependence, seem to be very similar regardless of whether the INA protein complexes inducing ice

Identification of Essential Proteins Based on a New Combination of Local Interaction Density and Protein Complexes.

Directory of Open Access Journals (Sweden)

Jiawei Luo

Full Text Available Computational approaches aided by computer science have been used to predict essential proteins and are faster than expensive, time-consuming, laborious experimental approaches. However, the performance of such approaches is still poor, making practical applications of computational approaches difficult in some fields. Hence, the development of more suitable and efficient computing methods is necessary for identification of essential proteins.In this paper, we propose a new method for predicting essential proteins in a protein interaction network, local interaction density combined with protein complexes (LIDC, based on statistical analyses of essential proteins and protein complexes. First, we introduce a new local topological centrality, local interaction density (LID, of the yeast PPI network; second, we discuss a new integration strategy for multiple bioinformatics. The LIDC method was then developed through a combination of LID and protein complex information based on our new integration strategy. The purpose of LIDC is discovery of important features of essential proteins with their neighbors in real protein complexes, thereby improving the efficiency of identification.Experimental results based on three different PPI(protein-protein interaction networks of Saccharomyces cerevisiae and Escherichia coli showed that LIDC outperformed classical topological centrality measures and some recent combinational methods. Moreover, when predicting MIPS datasets, the better improvement of performance obtained by LIDC is over all nine reference methods (i.e., DC, BC, NC, LID, PeC, CoEWC, WDC, ION, and UC.LIDC is more effective for the prediction of essential proteins than other recently developed methods.

Proteins interacting with the 26S proteasome

DEFF Research Database (Denmark)

Hartmann-Petersen, R; Gordon, C

2004-01-01

The 26S proteasome is the multi-protein protease that recognizes and degrades ubiquitinylated substrates targeted for destruction by the ubiquitin pathway. In addition to the well-documented subunit organization of the 26S holoenzyme, it is clear that a number of other proteins transiently...... associate with the 26S complex. These transiently associated proteins confer a number of different roles such as substrate presentation, cleavage of the multi-ubiquitin chain from the protein substrate and turnover of misfolded proteins. Such activities are essential for the 26S proteasome to efficiently...... fulfill its intracellular function in protein degradation....

Quantitative Interpretation of Multifrequency Multimode EPR Spectra of Metal Containing Proteins, Enzymes, and Biomimetic Complexes.

Science.gov (United States)

Petasis, Doros T; Hendrich, Michael P

2015-01-01

Electron paramagnetic resonance (EPR) spectroscopy has long been a primary method for characterization of paramagnetic centers in materials and biological complexes. Transition metals in biological complexes have valence d-orbitals that largely define the chemistry of the metal centers. EPR spectra are distinctive for metal type, oxidation state, protein environment, substrates, and inhibitors. The study of many metal centers in proteins, enzymes, and biomimetic complexes has led to the development of a systematic methodology for quantitative interpretation of EPR spectra from a wide array of metal containing complexes. The methodology is now contained in the computer program SpinCount. SpinCount allows simulation of EPR spectra from any sample containing multiple species composed of one or two metals in any spin state. The simulations are quantitative, thus allowing determination of all species concentrations in a sample directly from spectra. This chapter will focus on applications to transition metals in biological systems using EPR spectra from multiple microwave frequencies and modes. © 2015 Elsevier Inc. All rights reserved.

Improving prediction of heterodimeric protein complexes using combination with pairwise kernel.

Science.gov (United States)

Ruan, Peiying; Hayashida, Morihiro; Akutsu, Tatsuya; Vert, Jean-Philippe

2018-02-19

Since many proteins become functional only after they interact with their partner proteins and form protein complexes, it is essential to identify the sets of proteins that form complexes. Therefore, several computational methods have been proposed to predict complexes from the topology and structure of experimental protein-protein interaction (PPI) network. These methods work well to predict complexes involving at least three proteins, but generally fail at identifying complexes involving only two different proteins, called heterodimeric complexes or heterodimers. There is however an urgent need for efficient methods to predict heterodimers, since the majority of known protein complexes are precisely heterodimers. In this paper, we use three promising kernel functions, Min kernel and two pairwise kernels, which are Metric Learning Pairwise Kernel (MLPK) and Tensor Product Pairwise Kernel (TPPK). We also consider the normalization forms of Min kernel. Then, we combine Min kernel or its normalization form and one of the pairwise kernels by plugging. We applied kernels based on PPI, domain, phylogenetic profile, and subcellular localization properties to predicting heterodimers. Then, we evaluate our method by employing C-Support Vector Classification (C-SVC), carrying out 10-fold cross-validation, and calculating the average F-measures. The results suggest that the combination of normalized-Min-kernel and MLPK leads to the best F-measure and improved the performance of our previous work, which had been the best existing method so far. We propose new methods to predict heterodimers, using a machine learning-based approach. We train a support vector machine (SVM) to discriminate interacting vs non-interacting protein pairs, based on informations extracted from PPI, domain, phylogenetic profiles and subcellular localization. We evaluate in detail new kernel functions to encode these data, and report prediction performance that outperforms the state-of-the-art.

Losses, Expansions, and Novel Subunit Discovery of Adaptor Protein Complexes in Haptophyte Algae.

Science.gov (United States)

Lee, Laura J Y; Klute, Mary J; Herman, Emily K; Read, Betsy; Dacks, Joel B

2015-11-01

The phylum Haptophyta (Diaphoratickes) contains marine algae that perform biomineralization, extruding large, distinctive calcium carbonate scales (coccoliths) that completely cover the cell. Coccolith production is an important part of global carbon cycling; however, the membrane trafficking pathway by which they are secreted has not yet been elucidated. In most eukaryotes, post-Golgi membrane trafficking involves five heterotetrameric adaptor protein (AP) complexes, which impart cargo selection specificity. To better understand coccolith secretion, we performed comparative genomic, phylogenetic, and transcriptomic analyses of the AP complexes in Emiliania huxleyi strains 92A, Van556, EH2, and CCMP1516, and related haptophytes Gephyrocapsa oceanica and Isochrysis galbana; the latter has lost the ability to biomineralize. We show that haptophytes have a modified membrane trafficking system (MTS), as we found both AP subunit losses and duplications. Additionally, we identified a single conserved subunit of the AP-related TSET complex, whose expression suggests a functional role in membrane trafficking. Finally, we detected novel alpha adaptin ear and gamma adaptin ear proteins, the first of their kind to be described outside of opisthokonts. These novel ear proteins and the sculpting of the MTS may support the capacity for biomineralization in haptophytes, enhancing their ability to perform this highly specialized form of secretion. Copyright © 2015 Elsevier GmbH. All rights reserved.

Ternary WD40 repeat-containing protein complexes: evolution, composition and roles in plant immunity

Directory of Open Access Journals (Sweden)

Jimi C. Miller

2016-01-01

Full Text Available Plants, like mammals, rely on their innate immune system to perceive and discriminate among the majority of their microbial pathogens. Unlike mammals, plants respond to this molecular dialogue by unleashing a complex chemical arsenal of defense metabolites to resist or evade pathogen infection. In basal or non-host resistance, plants utilize signal transduction pathways to detect non-self, damaged-self and altered-self-associated molecular patterns and translate these danger signals into largely inducible chemical defenses. The WD40 repeat (WDR-containing proteins Gβ and TTG1 are constituents of two independent ternary protein complexes functioning at opposite ends of a plant immune signaling pathway. Gβ and TTG1 are also encoded by single-copy genes that are ubiquitous in higher plants, implying the limited diversity and functional conservation of their respective complexes. In this review, we summarize what is currently known about the evolutionary history of these WDR-containing ternary complexes, their repertoire and combinatorial interactions, and their downstream effectors and pathways in plant defense.

On the interconnection of stable protein complexes: inter-complex hubs and their conservation in Saccharomyces cerevisiae and Homo sapiens networks.

Science.gov (United States)

Guerra, Concettina

2015-01-01

Protein complexes are key molecular entities that perform a variety of essential cellular functions. The connectivity of proteins within a complex has been widely investigated with both experimental and computational techniques. We developed a computational approach to identify and characterise proteins that play a role in interconnecting complexes. We computed a measure of inter-complex centrality, the crossroad index, based on disjoint paths connecting proteins in distinct complexes and identified inter-complex hubs as proteins with a high value of the crossroad index. We applied the approach to a set of stable complexes in Saccharomyces cerevisiae and in Homo sapiens. Just as done for hubs, we evaluated the topological and biological properties of inter-complex hubs addressing the following questions. Do inter-complex hubs tend to be evolutionary conserved? What is the relation between crossroad index and essentiality? We found a good correlation between inter-complex hubs and both evolutionary conservation and essentiality.

Comparative evolutionary analysis of protein complexes in E. coli and yeast

Directory of Open Access Journals (Sweden)

Ranea Juan AG

2010-02-01

Full Text Available Abstract Background Proteins do not act in isolation; they frequently act together in protein complexes to carry out concerted cellular functions. The evolution of complexes is poorly understood, especially in organisms other than yeast, where little experimental data has been available. Results We generated accurate, high coverage datasets of protein complexes for E. coli and yeast in order to study differences in the evolution of complexes between these two species. We show that substantial differences exist in how complexes have evolved between these organisms. A previously proposed model of complex evolution identified complexes with cores of interacting homologues. We support findings of the relative importance of this mode of evolution in yeast, but find that it is much less common in E. coli. Additionally it is shown that those homologues which do cluster in complexes are involved in eukaryote-specific functions. Furthermore we identify correlated pairs of non-homologous domains which occur in multiple protein complexes. These were identified in both yeast and E. coli and we present evidence that these too may represent complex cores in yeast but not those of E. coli. Conclusions Our results suggest that there are differences in the way protein complexes have evolved in E. coli and yeast. Whereas some yeast complexes have evolved by recruiting paralogues, this is not apparent in E. coli. Furthermore, such complexes are involved in eukaryotic-specific functions. This implies that the increase in gene family sizes seen in eukaryotes in part reflects multiple family members being used within complexes. However, in general, in both E. coli and yeast, homologous domains are used in different complexes.

A novel Multi-Agent Ada-Boost algorithm for predicting protein structural class with the information of protein secondary structure.

Science.gov (United States)

Fan, Ming; Zheng, Bin; Li, Lihua

2015-10-01

Knowledge of the structural class of a given protein is important for understanding its folding patterns. Although a lot of efforts have been made, it still remains a challenging problem for prediction of protein structural class solely from protein sequences. The feature extraction and classification of proteins are the main problems in prediction. In this research, we extended our earlier work regarding these two aspects. In protein feature extraction, we proposed a scheme by calculating the word frequency and word position from sequences of amino acid, reduced amino acid, and secondary structure. For an accurate classification of the structural class of protein, we developed a novel Multi-Agent Ada-Boost (MA-Ada) method by integrating the features of Multi-Agent system into Ada-Boost algorithm. Extensive experiments were taken to test and compare the proposed method using four benchmark datasets in low homology. The results showed classification accuracies of 88.5%, 96.0%, 88.4%, and 85.5%, respectively, which are much better compared with the existing methods. The source code and dataset are available on request.

Large-Scale Multi-Resolution Representations for Accurate Interactive Image and Volume Operations

KAUST Repository

Sicat, Ronell B.

2015-11-25

The resolutions of acquired image and volume data are ever increasing. However, the resolutions of commodity display devices remain limited. This leads to an increasing gap between data and display resolutions. To bridge this gap, the standard approach is to employ output-sensitive operations on multi-resolution data representations. Output-sensitive operations facilitate interactive applications since their required computations are proportional only to the size of the data that is visible, i.e., the output, and not the full size of the input. Multi-resolution representations, such as image mipmaps, and volume octrees, are crucial in providing these operations direct access to any subset of the data at any resolution corresponding to the output. Despite its widespread use, this standard approach has some shortcomings in three important application areas, namely non-linear image operations, multi-resolution volume rendering, and large-scale image exploration. This dissertation presents new multi-resolution representations for large-scale images and volumes that address these shortcomings. Standard multi-resolution representations require low-pass pre-filtering for anti- aliasing. However, linear pre-filters do not commute with non-linear operations. This becomes problematic when applying non-linear operations directly to any coarse resolution levels in standard representations. Particularly, this leads to inaccurate output when applying non-linear image operations, e.g., color mapping and detail-aware filters, to multi-resolution images. Similarly, in multi-resolution volume rendering, this leads to inconsistency artifacts which manifest as erroneous differences in rendering outputs across resolution levels. To address these issues, we introduce the sparse pdf maps and sparse pdf volumes representations for large-scale images and volumes, respectively. These representations sparsely encode continuous probability density functions (pdfs) of multi-resolution pixel

MacroBac: New Technologies for Robust and Efficient Large-Scale Production of Recombinant Multiprotein Complexes.

Science.gov (United States)

Gradia, Scott D; Ishida, Justin P; Tsai, Miaw-Sheue; Jeans, Chris; Tainer, John A; Fuss, Jill O

2017-01-01

Recombinant expression of large, multiprotein complexes is essential and often rate limiting for determining structural, biophysical, and biochemical properties of DNA repair, replication, transcription, and other key cellular processes. Baculovirus-infected insect cell expression systems are especially well suited for producing large, human proteins recombinantly, and multigene baculovirus systems have facilitated studies of multiprotein complexes. In this chapter, we describe a multigene baculovirus system called MacroBac that uses a Biobricks-type assembly method based on restriction and ligation (Series 11) or ligation-independent cloning (Series 438). MacroBac cloning and assembly is efficient and equally well suited for either single subcloning reactions or high-throughput cloning using 96-well plates and liquid handling robotics. MacroBac vectors are polypromoter with each gene flanked by a strong polyhedrin promoter and an SV40 poly(A) termination signal that minimize gene order expression level effects seen in many polycistronic assemblies. Large assemblies are robustly achievable, and we have successfully assembled as many as 10 genes into a single MacroBac vector. Importantly, we have observed significant increases in expression levels and quality of large, multiprotein complexes using a single, multigene, polypromoter virus rather than coinfection with multiple, single-gene viruses. Given the importance of characterizing functional complexes, we believe that MacroBac provides a critical enabling technology that may change the way that structural, biophysical, and biochemical research is done. © 2017 Elsevier Inc. All rights reserved.

Protein scaffolds and higher-order complexes in synthetic biology

NARCIS (Netherlands)

den Hamer, A.; Rosier, B.J.H.M.; Brunsveld, L.; de Greef, T.F.A.; Ryadnov, M.; Brunsveld, L.; Suga, H.

2017-01-01

Interactions between proteins control molecular functions such as signalling or metabolic activity. Assembly of proteins via scaffold proteins or in higher-order complexes is a key regulatory mechanism. Understanding and functionally applying this concept requires the construction, study, and

Unusually large erupted complex odontoma: A rare case report

Energy Technology Data Exchange (ETDEWEB)

Bagewadi, Shivanand B.; Kukreja, Rahul; Suma, Gundareddy N.; Yadav, Bhawn; Sharma, Havi [Dept. of Oral Medicine and Radiology, ITS Centre for Dental Studies and Research, Murad Nagar (India)

2015-03-15

Odontomas are nonaggressive, hamartomatous developmental malformations composed of mature tooth substances and may be compound or complex depending on the extent of morphodifferentiation or on their resemblance to normal teeth. Among them, complex odontomas are relatively rare tumors. They are usually asymptomatic in nature. Occasionally, these tumors become large, causing bone expansion followed by facial asymmetry. Odontoma eruptions are uncommon, and thus far, very few cases of erupted complex odontomas have been reported in the literature. Here, we report the case of an unusually large, painless, complex odontoma located in the right posterior mandible.

Thermal proximity coaggregation for system-wide profiling of protein complex dynamics in cells.

Science.gov (United States)

Tan, Chris Soon Heng; Go, Ka Diam; Bisteau, Xavier; Dai, Lingyun; Yong, Chern Han; Prabhu, Nayana; Ozturk, Mert Burak; Lim, Yan Ting; Sreekumar, Lekshmy; Lengqvist, Johan; Tergaonkar, Vinay; Kaldis, Philipp; Sobota, Radoslaw M; Nordlund, Pär

2018-03-09

Proteins differentially interact with each other across cellular states and conditions, but an efficient proteome-wide strategy to monitor them is lacking. We report the application of thermal proximity coaggregation (TPCA) for high-throughput intracellular monitoring of protein complex dynamics. Significant TPCA signatures observed among well-validated protein-protein interactions correlate positively with interaction stoichiometry and are statistically observable in more than 350 annotated human protein complexes. Using TPCA, we identified many complexes without detectable differential protein expression, including chromatin-associated complexes, modulated in S phase of the cell cycle. Comparison of six cell lines by TPCA revealed cell-specific interactions even in fundamental cellular processes. TPCA constitutes an approach for system-wide studies of protein complexes in nonengineered cells and tissues and might be used to identify protein complexes that are modulated in diseases. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Nonlinear dynamics of the complex multi-scale network

Science.gov (United States)

Makarov, Vladimir V.; Kirsanov, Daniil; Goremyko, Mikhail; Andreev, Andrey; Hramov, Alexander E.

2018-04-01

In this paper, we study the complex multi-scale network of nonlocally coupled oscillators for the appearance of chimera states. Chimera is a special state in which, in addition to the asynchronous cluster, there are also completely synchronous parts in the system. We show that the increase of nodes in subgroups leads to the destruction of the synchronous interaction within the common ring and to the narrowing of the chimera region.

mPLR-Loc: an adaptive decision multi-label classifier based on penalized logistic regression for protein subcellular localization prediction.

Science.gov (United States)

Wan, Shibiao; Mak, Man-Wai; Kung, Sun-Yuan

2015-03-15

Proteins located in appropriate cellular compartments are of paramount importance to exert their biological functions. Prediction of protein subcellular localization by computational methods is required in the post-genomic era. Recent studies have been focusing on predicting not only single-location proteins but also multi-location proteins. However, most of the existing predictors are far from effective for tackling the challenges of multi-label proteins. This article proposes an efficient multi-label predictor, namely mPLR-Loc, based on penalized logistic regression and adaptive decisions for predicting both single- and multi-location proteins. Specifically, for each query protein, mPLR-Loc exploits the information from the Gene Ontology (GO) database by using its accession number (AC) or the ACs of its homologs obtained via BLAST. The frequencies of GO occurrences are used to construct feature vectors, which are then classified by an adaptive decision-based multi-label penalized logistic regression classifier. Experimental results based on two recent stringent benchmark datasets (virus and plant) show that mPLR-Loc remarkably outperforms existing state-of-the-art multi-label predictors. In addition to being able to rapidly and accurately predict subcellular localization of single- and multi-label proteins, mPLR-Loc can also provide probabilistic confidence scores for the prediction decisions. For readers' convenience, the mPLR-Loc server is available online (http://bioinfo.eie.polyu.edu.hk/mPLRLocServer). Copyright © 2014 Elsevier Inc. All rights reserved.

Research and assessment of competitiveness of large engineering complexes

Directory of Open Access Journals (Sweden)

Krivorotov V.V.

2017-01-01

Full Text Available The urgency of the problem of ensuring the competitiveness of manufacturing and high-tech sectors is shown. Substantiated the decisive role of the large industrial complexes in the formation of the results of the national economy; the author’s interpretation of the concept of “industrial complex” with regard to current economic systems. Current approaches to assessing the competitiveness of enterprises and industrial complexes are analyzed; showing their main advantages and disadvantages. Provides scientific-methodological approach to the study and management of competitiveness of a large industrial complex; the description of its main units is provided. As a Central element of the scientific methodology approach proposed the methodology for assessing the competitiveness of a large industrial complex based on the Pattern-method; a modular system of indicators of competitiveness is developed and its adaptation to a large engineering complexes is made. Using the developed methodology the competitiveness of one of the largest engineering complexes of the group of companies Uralelectrotyazhmash, which is the leading enterprises in electrotechnical industry of Russia is assessed. The evaluation identified the main problems and bottlenecks in the development of these enterprises, and their comparison with leading competitors is provided. According to the results of the study the main conclusions and recommendations are formed.

Multi-fidelity uncertainty quantification in large-scale predictive simulations of turbulent flow

Science.gov (United States)

Geraci, Gianluca; Jofre-Cruanyes, Lluis; Iaccarino, Gianluca

2017-11-01

The performance characterization of complex engineering systems often relies on accurate, but computationally intensive numerical simulations. It is also well recognized that in order to obtain a reliable numerical prediction the propagation of uncertainties needs to be included. Therefore, Uncertainty Quantification (UQ) plays a fundamental role in building confidence in predictive science. Despite the great improvement in recent years, even the more advanced UQ algorithms are still limited to fairly simplified applications and only moderate parameter dimensionality. Moreover, in the case of extremely large dimensionality, sampling methods, i.e. Monte Carlo (MC) based approaches, appear to be the only viable alternative. In this talk we describe and compare a family of approaches which aim to accelerate the convergence of standard MC simulations. These methods are based on hierarchies of generalized numerical resolutions (multi-level) or model fidelities (multi-fidelity), and attempt to leverage the correlation between Low- and High-Fidelity (HF) models to obtain a more accurate statistical estimator without introducing additional HF realizations. The performance of these methods are assessed on an irradiated particle laden turbulent flow (PSAAP II solar energy receiver). This investigation was funded by the United States Department of Energy's (DoE) National Nuclear Security Administration (NNSA) under the Predicitive Science Academic Alliance Program (PSAAP) II at Stanford University.

Complex Event Detection via Multi Source Video Attributes (Open Access)

Science.gov (United States)

2013-10-03

Complex Event Detection via Multi-Source Video Attributes Zhigang Ma† Yi Yang‡ Zhongwen Xu‡§ Shuicheng Yan Nicu Sebe† Alexander G. Hauptmann...under its International Research Centre @ Singapore Fund- ing Initiative and administered by the IDM Programme Of- fice, and the Intelligence Advanced

Peroxisome protein import: a complex journey.

Science.gov (United States)

Baker, Alison; Lanyon-Hogg, Thomas; Warriner, Stuart L

2016-06-15

The import of proteins into peroxisomes possesses many unusual features such as the ability to import folded proteins, and a surprising diversity of targeting signals with differing affinities that can be recognized by the same receptor. As understanding of the structure and function of many components of the protein import machinery has grown, an increasingly complex network of factors affecting each step of the import pathway has emerged. Structural studies have revealed the presence of additional interactions between cargo proteins and the PEX5 receptor that affect import potential, with a subtle network of cargo-induced conformational changes in PEX5 being involved in the import process. Biochemical studies have also indicated an interdependence of receptor-cargo import with release of unloaded receptor from the peroxisome. Here, we provide an update on recent literature concerning mechanisms of protein import into peroxisomes. © 2016 The Author(s).

Interaction of the anaphase-promoting complex/cyclosome and proteasome protein complexes with multiubiquitin chain-binding proteins

DEFF Research Database (Denmark)

Seeger, Michael; Hartmann-Petersen, Rasmus; Wilkinson, Caroline R M

2003-01-01

Fission yeast Rhp23 and Pus1 represent two families of multiubiquitin chain-binding proteins that associate with the proteasome. We show that both proteins bind to different regions of the proteasome subunit Mts4. The binding site for Pus1 was mapped to a cluster of repetitive sequences also found...... in the proteasome subunit SpRpn2 and the anaphase-promoting complex/cyclosome (APC/C) subunit Cut4. The putative role of Pus1 as a factor involved in allocation of ubiquitinylated substrates for the proteasome is discussed....

The Meckel syndrome- associated protein MKS1 functionally interacts with components of the BBSome and IFT complexes to mediate ciliary trafficking and hedgehog signaling

Science.gov (United States)

Barrington, Chloe L.; Katsanis, Nicholas

2017-01-01

The importance of primary cilia in human health is underscored by the link between ciliary dysfunction and a group of primarily recessive genetic disorders with overlapping clinical features, now known as ciliopathies. Many of the proteins encoded by ciliopathy-associated genes are components of a handful of multi-protein complexes important for the transport of cargo to the basal body and/or into the cilium. A key question is whether different complexes cooperate in cilia formation, and whether they participate in cilium assembly in conjunction with intraflagellar transport (IFT) proteins. To examine how ciliopathy protein complexes might function together, we have analyzed double mutants of an allele of the Meckel syndrome (MKS) complex protein MKS1 and the BBSome protein BBS4. We find that Mks1; Bbs4 double mutant mouse embryos exhibit exacerbated defects in Hedgehog (Hh) dependent patterning compared to either single mutant, and die by E14.5. Cells from double mutant embryos exhibit a defect in the trafficking of ARL13B, a ciliary membrane protein, resulting in disrupted ciliary structure and signaling. We also examined the relationship between the MKS complex and IFT proteins by analyzing double mutant between Mks1 and a hypomorphic allele of the IFTB component Ift172. Despite each single mutant surviving until around birth, Mks1; Ift172avc1 double mutants die at mid-gestation, and exhibit a dramatic failure of cilia formation. We also find that Mks1 interacts genetically with an allele of Dync2h1, the IFT retrograde motor. Thus, we have demonstrated that the MKS transition zone complex cooperates with the BBSome to mediate trafficking of specific trans-membrane receptors to the cilium. Moreover, the genetic interaction of Mks1 with components of IFT machinery suggests that the transition zone complex facilitates IFT to promote cilium assembly and structure. PMID:28291807

The Meckel syndrome- associated protein MKS1 functionally interacts with components of the BBSome and IFT complexes to mediate ciliary trafficking and hedgehog signaling.

Directory of Open Access Journals (Sweden)

Sarah C Goetz

Full Text Available The importance of primary cilia in human health is underscored by the link between ciliary dysfunction and a group of primarily recessive genetic disorders with overlapping clinical features, now known as ciliopathies. Many of the proteins encoded by ciliopathy-associated genes are components of a handful of multi-protein complexes important for the transport of cargo to the basal body and/or into the cilium. A key question is whether different complexes cooperate in cilia formation, and whether they participate in cilium assembly in conjunction with intraflagellar transport (IFT proteins. To examine how ciliopathy protein complexes might function together, we have analyzed double mutants of an allele of the Meckel syndrome (MKS complex protein MKS1 and the BBSome protein BBS4. We find that Mks1; Bbs4 double mutant mouse embryos exhibit exacerbated defects in Hedgehog (Hh dependent patterning compared to either single mutant, and die by E14.5. Cells from double mutant embryos exhibit a defect in the trafficking of ARL13B, a ciliary membrane protein, resulting in disrupted ciliary structure and signaling. We also examined the relationship between the MKS complex and IFT proteins by analyzing double mutant between Mks1 and a hypomorphic allele of the IFTB component Ift172. Despite each single mutant surviving until around birth, Mks1; Ift172avc1 double mutants die at mid-gestation, and exhibit a dramatic failure of cilia formation. We also find that Mks1 interacts genetically with an allele of Dync2h1, the IFT retrograde motor. Thus, we have demonstrated that the MKS transition zone complex cooperates with the BBSome to mediate trafficking of specific trans-membrane receptors to the cilium. Moreover, the genetic interaction of Mks1 with components of IFT machinery suggests that the transition zone complex facilitates IFT to promote cilium assembly and structure.

Predicting co-complexed protein pairs using genomic and proteomic data integration

Directory of Open Access Journals (Sweden)

King Oliver D

2004-04-01

Full Text Available Abstract Background Identifying all protein-protein interactions in an organism is a major objective of proteomics. A related goal is to know which protein pairs are present in the same protein complex. High-throughput methods such as yeast two-hybrid (Y2H and affinity purification coupled with mass spectrometry (APMS have been used to detect interacting proteins on a genomic scale. However, both Y2H and APMS methods have substantial false-positive rates. Aside from high-throughput interaction screens, other gene- or protein-pair characteristics may also be informative of physical interaction. Therefore it is desirable to integrate multiple datasets and utilize their different predictive value for more accurate prediction of co-complexed relationship. Results Using a supervised machine learning approach – probabilistic decision tree, we integrated high-throughput protein interaction datasets and other gene- and protein-pair characteristics to predict co-complexed pairs (CCP of proteins. Our predictions proved more sensitive and specific than predictions based on Y2H or APMS methods alone or in combination. Among the top predictions not annotated as CCPs in our reference set (obtained from the MIPS complex catalogue, a significant fraction was found to physically interact according to a separate database (YPD, Yeast Proteome Database, and the remaining predictions may potentially represent unknown CCPs. Conclusions We demonstrated that the probabilistic decision tree approach can be successfully used to predict co-complexed protein (CCP pairs from other characteristics. Our top-scoring CCP predictions provide testable hypotheses for experimental validation.

Automated NMR fragment based screening identified a novel interface blocker to the LARG/RhoA complex.

Directory of Open Access Journals (Sweden)

Jia Gao

Full Text Available The small GTPase cycles between the inactive GDP form and the activated GTP form, catalyzed by the upstream guanine exchange factors. The modulation of such process by small molecules has been proven to be a fruitful route for therapeutic intervention to prevent the over-activation of the small GTPase. The fragment based approach emerging in the past decade has demonstrated its paramount potential in the discovery of inhibitors targeting such novel and challenging protein-protein interactions. The details regarding the procedure of NMR fragment screening from scratch have been rarely disclosed comprehensively, thus restricts its wider applications. To achieve a consistent screening applicable to a number of targets, we developed a highly automated protocol to cover every aspect of NMR fragment screening as possible, including the construction of small but diverse libray, determination of the aqueous solubility by NMR, grouping compounds with mutual dispersity to a cocktail, and the automated processing and visualization of the ligand based screening spectra. We exemplified our streamlined screening in RhoA alone and the complex of the small GTPase RhoA and its upstream guanine exchange factor LARG. Two hits were confirmed from the primary screening in cocktail and secondary screening over individual hits for LARG/RhoA complex, while one of them was also identified from the screening for RhoA alone. HSQC titration of the two hits over RhoA and LARG alone, respectively, identified one compound binding to RhoA.GDP at a 0.11 mM affinity, and perturbed the residues at the switch II region of RhoA. This hit blocked the formation of the LARG/RhoA complex, validated by the native gel electrophoresis, and the titration of RhoA to ¹⁵N labeled LARG in the absence and presence the compound, respectively. It therefore provides us a starting point toward a more potent inhibitor to RhoA activation catalyzed by LARG.

Assembling large, complex environmental metagenomes

Energy Technology Data Exchange (ETDEWEB)

Howe, A. C. [Michigan State Univ., East Lansing, MI (United States). Microbiology and Molecular Genetics, Plant Soil and Microbial Sciences; Jansson, J. [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Earth Sciences Division; Malfatti, S. A. [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States); Tringe, S. G. [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States); Tiedje, J. M. [Michigan State Univ., East Lansing, MI (United States). Microbiology and Molecular Genetics, Plant Soil and Microbial Sciences; Brown, C. T. [Michigan State Univ., East Lansing, MI (United States). Microbiology and Molecular Genetics, Computer Science and Engineering

2012-12-28

The large volumes of sequencing data required to sample complex environments deeply pose new challenges to sequence analysis approaches. De novo metagenomic assembly effectively reduces the total amount of data to be analyzed but requires significant computational resources. We apply two pre-assembly filtering approaches, digital normalization and partitioning, to make large metagenome assemblies more computationaly tractable. Using a human gut mock community dataset, we demonstrate that these methods result in assemblies nearly identical to assemblies from unprocessed data. We then assemble two large soil metagenomes from matched Iowa corn and native prairie soils. The predicted functional content and phylogenetic origin of the assembled contigs indicate significant taxonomic differences despite similar function. The assembly strategies presented are generic and can be extended to any metagenome; full source code is freely available under a BSD license.

Short length transmembrane domains having voluminous exoplasmic halves determine retention of Type II membrane proteins in the Golgi complex

OpenAIRE

Quiroga, Rodrigo; Trenchi, Alejandra; Gonzalez Montoro, Ayelén; Valdez, Javier Esteban; Maccioni, Hugo Jose Fernando

2017-01-01

It is still unclear why some proteins that travel along the secretory pathway are retained in the Golgi complex whereas others make their way to the plasma membrane. Recent bioinformatic analyses on a large number of single-spanning membrane proteins support the hypothesis that specific features of the transmembrane domain (TMD) are relevant to the sorting of these proteins to particular organelles. Here we experimentally test this hypothesis for Golgi and plasma membrane proteins. Using the ...

From nonspecific DNA-protein encounter complexes to the prediction of DNA-protein interactions.

Directory of Open Access Journals (Sweden)

Mu Gao

2009-03-01

Full Text Available DNA-protein interactions are involved in many essential biological activities. Because there is no simple mapping code between DNA base pairs and protein amino acids, the prediction of DNA-protein interactions is a challenging problem. Here, we present a novel computational approach for predicting DNA-binding protein residues and DNA-protein interaction modes without knowing its specific DNA target sequence. Given the structure of a DNA-binding protein, the method first generates an ensemble of complex structures obtained by rigid-body docking with a nonspecific canonical B-DNA. Representative models are subsequently selected through clustering and ranking by their DNA-protein interfacial energy. Analysis of these encounter complex models suggests that the recognition sites for specific DNA binding are usually favorable interaction sites for the nonspecific DNA probe and that nonspecific DNA-protein interaction modes exhibit some similarity to specific DNA-protein binding modes. Although the method requires as input the knowledge that the protein binds DNA, in benchmark tests, it achieves better performance in identifying DNA-binding sites than three previously established methods, which are based on sophisticated machine-learning techniques. We further apply our method to protein structures predicted through modeling and demonstrate that our method performs satisfactorily on protein models whose root-mean-square Calpha deviation from native is up to 5 A from their native structures. This study provides valuable structural insights into how a specific DNA-binding protein interacts with a nonspecific DNA sequence. The similarity between the specific DNA-protein interaction mode and nonspecific interaction modes may reflect an important sampling step in search of its specific DNA targets by a DNA-binding protein.

Insights into Hox protein function from a large scale combinatorial analysis of protein domains.

Directory of Open Access Journals (Sweden)

Samir Merabet

2011-10-01

Full Text Available Protein function is encoded within protein sequence and protein domains. However, how protein domains cooperate within a protein to modulate overall activity and how this impacts functional diversification at the molecular and organism levels remains largely unaddressed. Focusing on three domains of the central class Drosophila Hox transcription factor AbdominalA (AbdA, we used combinatorial domain mutations and most known AbdA developmental functions as biological readouts to investigate how protein domains collectively shape protein activity. The results uncover redundancy, interactivity, and multifunctionality of protein domains as salient features underlying overall AbdA protein activity, providing means to apprehend functional diversity and accounting for the robustness of Hox-controlled developmental programs. Importantly, the results highlight context-dependency in protein domain usage and interaction, allowing major modifications in domains to be tolerated without general functional loss. The non-pleoitropic effect of domain mutation suggests that protein modification may contribute more broadly to molecular changes underlying morphological diversification during evolution, so far thought to rely largely on modification in gene cis-regulatory sequences.

Multi-stage decoding for multi-level block modulation codes

Science.gov (United States)

Lin, Shu

1991-01-01

In this paper, we investigate various types of multi-stage decoding for multi-level block modulation codes, in which the decoding of a component code at each stage can be either soft-decision or hard-decision, maximum likelihood or bounded-distance. Error performance of codes is analyzed for a memoryless additive channel based on various types of multi-stage decoding, and upper bounds on the probability of an incorrect decoding are derived. Based on our study and computation results, we find that, if component codes of a multi-level modulation code and types of decoding at various stages are chosen properly, high spectral efficiency and large coding gain can be achieved with reduced decoding complexity. In particular, we find that the difference in performance between the suboptimum multi-stage soft-decision maximum likelihood decoding of a modulation code and the single-stage optimum decoding of the overall code is very small: only a fraction of dB loss in SNR at the probability of an incorrect decoding for a block of 10(exp -6). Multi-stage decoding of multi-level modulation codes really offers a way to achieve the best of three worlds, bandwidth efficiency, coding gain, and decoding complexity.

Multi-person tracking with overlapping cameras in complex, dynamic environments

NARCIS (Netherlands)

Liem, M.; Gavrila, D.M.

2009-01-01

This paper presents a multi-camera system to track multiple persons in complex, dynamic environments. Position measurements are obtained by carving out the space defined by foreground regions in the overlapping camera views and projecting these onto blobs on the ground plane. Person appearance is

Predicting protein complexes using a supervised learning method combined with local structural information.

Science.gov (United States)

Dong, Yadong; Sun, Yongqi; Qin, Chao

2018-01-01

The existing protein complex detection methods can be broadly divided into two categories: unsupervised and supervised learning methods. Most of the unsupervised learning methods assume that protein complexes are in dense regions of protein-protein interaction (PPI) networks even though many true complexes are not dense subgraphs. Supervised learning methods utilize the informative properties of known complexes; they often extract features from existing complexes and then use the features to train a classification model. The trained model is used to guide the search process for new complexes. However, insufficient extracted features, noise in the PPI data and the incompleteness of complex data make the classification model imprecise. Consequently, the classification model is not sufficient for guiding the detection of complexes. Therefore, we propose a new robust score function that combines the classification model with local structural information. Based on the score function, we provide a search method that works both forwards and backwards. The results from experiments on six benchmark PPI datasets and three protein complex datasets show that our approach can achieve better performance compared with the state-of-the-art supervised, semi-supervised and unsupervised methods for protein complex detection, occasionally significantly outperforming such methods.

Multi-frequency complex network from time series for uncovering oil-water flow structure.

Science.gov (United States)

Gao, Zhong-Ke; Yang, Yu-Xuan; Fang, Peng-Cheng; Jin, Ning-De; Xia, Cheng-Yi; Hu, Li-Dan

2015-02-04

Uncovering complex oil-water flow structure represents a challenge in diverse scientific disciplines. This challenge stimulates us to develop a new distributed conductance sensor for measuring local flow signals at different positions and then propose a novel approach based on multi-frequency complex network to uncover the flow structures from experimental multivariate measurements. In particular, based on the Fast Fourier transform, we demonstrate how to derive multi-frequency complex network from multivariate time series. We construct complex networks at different frequencies and then detect community structures. Our results indicate that the community structures faithfully represent the structural features of oil-water flow patterns. Furthermore, we investigate the network statistic at different frequencies for each derived network and find that the frequency clustering coefficient enables to uncover the evolution of flow patterns and yield deep insights into the formation of flow structures. Current results present a first step towards a network visualization of complex flow patterns from a community structure perspective.

Quantifying the energetics of cooperativity in a ternary protein complex

DEFF Research Database (Denmark)

Andersen, Peter S; Schuck, Peter; Sundberg, Eric J

2002-01-01

and mathematical modeling to describe the energetics of cooperativity in a trimolecular protein complex. As a model system for quantifying cooperativity, we studied the ternary complex formed by the simultaneous interaction of a superantigen with major histocompatibility complex and T cell receptor, for which...... a structural model is available. This system exhibits positive and negative cooperativity, as well as augmentation of the temperature dependence of binding kinetics upon the cooperative interaction of individual protein components in the complex. Our experimental and theoretical analysis may be applicable...... to other systems involving cooperativity....

Evaluation of recombinant multi-epitope proteins for diagnosis of goat schistosomiasis by enzyme-linked immunosorbent assay.

Science.gov (United States)

Lv, Chao; Hong, Yang; Fu, Zhiqiang; Lu, Ke; Cao, Xiaodan; Wang, Tao; Zhu, Chuangang; Li, Hao; Xu, Rui; Jia, Bingguang; Han, Qian; Dou, Xuefeng; Shen, Yuanxi; Zhang, Zuhang; Zai, Jinli; Feng, Jintao; Lin, Jiaojiao

2016-03-09

Schistosomiasis is a huge threat to human and animal health. Apart from bovines, goats play an important role in the transmission of schistosomiasis in some endemic areas of China. An accessible, quality-assured goat schistosomiasis diagnostic technique is needed. Recently, our laboratory identified two recombinant diagnostic antigens, SjPGM and SjRAD23 via an immuno-proteomic method. The application of these two recombinant antigens to develop a higher sensitivity and specificity technique for the sheep schistosomiasis diagnosis is urgently needed. Epitopes of SjPGM and SjRAD23 were predicted and three polypeptides, two from SjRAD23 and one from SjPGM, were selected. Recombinant plasmids containing two to three DNA sequences encoding predicted polypeptides or large hydrophilic region of Sj23 (LHD-Sj23) were constructed and expressed. Eight recombinant schistosome antigens including four multi-epitope proteins and four recombinant single-molecule antigens as well as SEA, were assessed by ELISA in 91 sera from schistosome-infected goats, 44 sera from non-infected goats, 37 sera from Orientobilharzia-infected goats, and 12 from Haemonchus contortus-infected goats. ELISA tests showed that three multi-epitope proteins had higher sensitivity than the four single-molecule antigens (rSjRAD23, rSjPGM, rBSjRAD23-1, rBSj23) and the multi-epitope protein rBSjPGM-BSjRAD23-1-BSj23 had the highest sensitivity (97.8 %, 89/91) and maintained good specificity (100 %, 44/44) as well as low cross-reactivity with haemonchosis (8.33 %, 3/12) and orientobilharziasis (13.51 %, 5/37) in the diagnosis of goat schistosomiasis. In contrast, when SEA was applied as a diagnosis antigen, it had 100 % (91/91) sensitivity, 75 % (33/44) specificity, 25 and 83.78 % cross-reactivity with haemonchosis (3/12) and orientobilharziasis (31/37), respectively. The application of recombinant multi-epitope proteins may increase the sensitivity of diagnosis technique and retain high specificity of single

RRW: repeated random walks on genome-scale protein networks for local cluster discovery

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Can Tolga

2009-09-01

Full Text Available Abstract Background We propose an efficient and biologically sensitive algorithm based on repeated random walks (RRW for discovering functional modules, e.g., complexes and pathways, within large-scale protein networks. Compared to existing cluster identification techniques, RRW implicitly makes use of network topology, edge weights, and long range interactions between proteins. Results We apply the proposed technique on a functional network of yeast genes and accurately identify statistically significant clusters of proteins. We validate the biological significance of the results using known complexes in the MIPS complex catalogue database and well-characterized biological processes. We find that 90% of the created clusters have the majority of their catalogued proteins belonging to the same MIPS complex, and about 80% have the majority of their proteins involved in the same biological process. We compare our method to various other clustering techniques, such as the Markov Clustering Algorithm (MCL, and find a significant improvement in the RRW clusters' precision and accuracy values. Conclusion RRW, which is a technique that exploits the topology of the network, is more precise and robust in finding local clusters. In addition, it has the added flexibility of being able to find multi-functional proteins by allowing overlapping clusters.

Biomimetic Membranes for Multi-Redox Center Proteins

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Renate L. C. Naumann

2016-03-01

Full Text Available His-tag technology was applied for biosensing purposes involving multi-redox center proteins (MRPs. An overview is presented on various surfaces ranging from flat to spherical and modified with linker molecules with nitrile-tri-acetic acid (NTA terminal groups to bind his-tagged proteins in a strict orientation. The bound proteins are submitted to in situ dialysis in the presence of lipid micelles to form a so-called protein-tethered bilayer lipid membrane (ptBLM. MRPs, such as the cytochrome c oxidase (CcO from R. sphaeroides and P. denitrificans, as well as photosynthetic reactions centers (RCs from R. sphaeroides, were thus investigated. Electrochemical and surface-sensitive optical techniques, such as surface plasmon resonance, surface plasmon-enhanced fluorescence, surface-enhanced infrared absorption spectroscopy (SEIRAS and surface-enhanced resonance Raman spectroscopy (SERRS, were employed in the case of the ptBLM structure on flat surfaces. Spherical particles ranging from µm size agarose gel beads to nm size nanoparticles modified in a similar fashion were called proteo-lipobeads (PLBs. The particles were investigated by laser-scanning confocal fluorescence microscopy (LSM and UV/Vis spectroscopy. Electron and proton transfer through the proteins were demonstrated to take place, which was strongly affected by the membrane potential. MRPs can thus be used for biosensing purposes under quasi-physiological conditions.

Protein-induced geometric constraints and charge transfer in bacteriochlorophyll-histidine complexes in LH2.

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Wawrzyniak, Piotr K; Alia, A; Schaap, Roland G; Heemskerk, Mattijs M; de Groot, Huub J M; Buda, Francesco

2008-12-14

Bacteriochlorophyll-histidine complexes are ubiquitous in nature and are essential structural motifs supporting the conversion of solar energy into chemically useful compounds in a wide range of photosynthesis processes. A systematic density functional theory study of the NMR chemical shifts for histidine and for bacteriochlorophyll-a-histidine complexes in the light-harvesting complex II (LH2) is performed using the BLYP functional in combination with the 6-311++G(d,p) basis set. The computed chemical shift patterns are consistent with available experimental data for positive and neutral(tau) (N(tau) protonated) crystalline histidines. The results for the bacteriochlorophyll-a-histidine complexes in LH2 provide evidence that the protein environment is stabilizing the histidine close to the Mg ion, thereby inducing a large charge transfer of approximately 0.5 electronic equivalent. Due to this protein-induced geometric constraint, the Mg-coordinated histidine in LH2 appears to be in a frustrated state very different from the formal neutral(pi) (N(pi) protonated) form. This finding could be important for the understanding of basic functional mechanisms involved in tuning the electronic properties and exciton coupling in LH2.

The fifth adaptor protein complex.

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Jennifer Hirst

2011-10-01

Full Text Available Adaptor protein (AP complexes sort cargo into vesicles for transport from one membrane compartment of the cell to another. Four distinct AP complexes have been identified, which are present in most eukaryotes. We report the existence of a fifth AP complex, AP-5. Tagged AP-5 localises to a late endosomal compartment in HeLa cells. AP-5 does not associate with clathrin and is insensitive to brefeldin A. Knocking down AP-5 subunits interferes with the trafficking of the cation-independent mannose 6-phosphate receptor and causes the cell to form swollen endosomal structures with emanating tubules. AP-5 subunits can be found in all five eukaryotic supergroups, but they have been co-ordinately lost in many organisms. Concatenated phylogenetic analysis provides robust resolution, for the first time, into the evolutionary order of emergence of the adaptor subunit families, showing AP-3 as the basal complex, followed by AP-5, AP-4, and AP-1 and AP-2. Thus, AP-5 is an evolutionarily ancient complex, which is involved in endosomal sorting, and which has links with hereditary spastic paraplegia.

Gene ontology based transfer learning for protein subcellular localization

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Zhou Shuigeng

2011-02-01

Full Text Available Abstract Background Prediction of protein subcellular localization generally involves many complex factors, and using only one or two aspects of data information may not tell the true story. For this reason, some recent predictive models are deliberately designed to integrate multiple heterogeneous data sources for exploiting multi-aspect protein feature information. Gene ontology, hereinafter referred to as GO, uses a controlled vocabulary to depict biological molecules or gene products in terms of biological process, molecular function and cellular component. With the rapid expansion of annotated protein sequences, gene ontology has become a general protein feature that can be used to construct predictive models in computational biology. Existing models generally either concatenated the GO terms into a flat binary vector or applied majority-vote based ensemble learning for protein subcellular localization, both of which can not estimate the individual discriminative abilities of the three aspects of gene ontology. Results In this paper, we propose a Gene Ontology Based Transfer Learning Model (GO-TLM for large-scale protein subcellular localization. The model transfers the signature-based homologous GO terms to the target proteins, and further constructs a reliable learning system to reduce the adverse affect of the potential false GO terms that are resulted from evolutionary divergence. We derive three GO kernels from the three aspects of gene ontology to measure the GO similarity of two proteins, and derive two other spectrum kernels to measure the similarity of two protein sequences. We use simple non-parametric cross validation to explicitly weigh the discriminative abilities of the five kernels, such that the time & space computational complexities are greatly reduced when compared to the complicated semi-definite programming and semi-indefinite linear programming. The five kernels are then linearly merged into one single kernel for

Energy landscape of all-atom protein-protein interactions revealed by multiscale enhanced sampling.

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Kei Moritsugu

2014-10-01

Full Text Available Protein-protein interactions are regulated by a subtle balance of complicated atomic interactions and solvation at the interface. To understand such an elusive phenomenon, it is necessary to thoroughly survey the large configurational space from the stable complex structure to the dissociated states using the all-atom model in explicit solvent and to delineate the energy landscape of protein-protein interactions. In this study, we carried out a multiscale enhanced sampling (MSES simulation of the formation of a barnase-barstar complex, which is a protein complex characterized by an extraordinary tight and fast binding, to determine the energy landscape of atomistic protein-protein interactions. The MSES adopts a multicopy and multiscale scheme to enable for the enhanced sampling of the all-atom model of large proteins including explicit solvent. During the 100-ns MSES simulation of the barnase-barstar system, we observed the association-dissociation processes of the atomistic protein complex in solution several times, which contained not only the native complex structure but also fully non-native configurations. The sampled distributions suggest that a large variety of non-native states went downhill to the stable complex structure, like a fast folding on a funnel-like potential. This funnel landscape is attributed to dominant configurations in the early stage of the association process characterized by near-native orientations, which will accelerate the native inter-molecular interactions. These configurations are guided mostly by the shape complementarity between barnase and barstar, and lead to the fast formation of the final complex structure along the downhill energy landscape.

Generalist solutions to complex problems: generating practice-based evidence--the example of managing multi-morbidity.

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Reeve, Joanne; Blakeman, Tom; Freeman, George K; Green, Larry A; James, Paul A; Lucassen, Peter; Martin, Carmel M; Sturmberg, Joachim P; van Weel, Chris

2013-08-07

A growing proportion of people are living with long term conditions. The majority have more than one. Dealing with multi-morbidity is a complex problem for health systems: for those designing and implementing healthcare as well as for those providing the evidence informing practice. Yet the concept of multi-morbidity (the presence of >2 diseases) is a product of the design of health care systems which define health care need on the basis of disease status. So does the solution lie in an alternative model of healthcare? Strengthening generalist practice has been proposed as part of the solution to tackling multi-morbidity. Generalism is a professional philosophy of practice, deeply known to many practitioners, and described as expertise in whole person medicine. But generalism lacks the evidence base needed by policy makers and planners to support service redesign. The challenge is to fill this practice-research gap in order to critically explore if and when generalist care offers a robust alternative to management of this complex problem. We need practice-based evidence to fill this gap. By recognising generalist practice as a 'complex intervention' (intervening in a complex system), we outline an approach to evaluate impact using action-research principles. We highlight the implications for those who both commission and undertake research in order to tackle this problem. Answers to the complex problem of multi-morbidity won't come from doing more of the same. We need to change systems of care, and so the systems for generating evidence to support that care. This paper contributes to that work through outlining a process for generating practice-based evidence of generalist solutions to the complex problem of person-centred care for people with multi-morbidity.

Directed self-assembly of large scaffold-free multi-cellular honeycomb structures

International Nuclear Information System (INIS)

Tejavibulya, Nalin; Youssef, Jacquelyn; Bao, Brian; Ferruccio, Toni-Marie; Morgan, Jeffrey R

2011-01-01

A significant challenge to the field of biofabrication is the rapid construction of large three-dimensional (3D) living tissues and organs. Multi-cellular spheroids have been used as building blocks. In this paper, we create large multi-cellular honeycomb building blocks using directed self-assembly, whereby cell-to-cell adhesion, in the context of the shape and obstacles of a micro-mold, drives the formation of a 3D structure. Computer-aided design, rapid prototyping and replica molding were used to fabricate honeycomb-shaped micro-molds. Nonadhesive hydrogels cast from these micro-molds were equilibrated in the cell culture medium and seeded with two types of mammalian cells. The cells settled into the honeycomb recess were unable to attach to the nonadhesive hydrogel and so cell-to-cell adhesion drove the self-assembly of a large multi-cellular honeycomb within 24 h. Distinct morphological changes occurred to the honeycomb and its cells indicating the presence of significant cell-mediated tension. Unlike the spheroid, whose size is constrained by a critical diffusion distance needed to maintain cell viability, the overall size of the honeycomb is not limited. The rapid production of the honeycomb building unit, with its multiple rings of high-density cells and open lumen spaces, offers interesting new possibilities for biofabrication strategies.

Examining Food Risk in the Large using a Complex, Networked System-of-sytems Approach

Energy Technology Data Exchange (ETDEWEB)

Ambrosiano, John [Los Alamos National Laboratory; Newkirk, Ryan [U OF MINNESOTA; Mc Donald, Mark P [VANDERBILT U

2010-12-03

The food production infrastructure is a highly complex system of systems. Characterizing the risks of intentional contamination in multi-ingredient manufactured foods is extremely challenging because the risks depend on the vulnerabilities of food processing facilities and on the intricacies of the supply-distribution networks that link them. A pure engineering approach to modeling the system is impractical because of the overall system complexity and paucity of data. A methodology is needed to assess food contamination risk 'in the large', based on current, high-level information about manufacturing facilities, corrunodities and markets, that will indicate which food categories are most at risk of intentional contamination and warrant deeper analysis. The approach begins by decomposing the system for producing a multi-ingredient food into instances of two subsystem archetypes: (1) the relevant manufacturing and processing facilities, and (2) the networked corrunodity flows that link them to each other and consumers. Ingredient manufacturing subsystems are modeled as generic systems dynamics models with distributions of key parameters that span the configurations of real facilities. Networks representing the distribution systems are synthesized from general information about food corrunodities. This is done in a series of steps. First, probability networks representing the aggregated flows of food from manufacturers to wholesalers, retailers, other manufacturers, and direct consumers are inferred from high-level approximate information. This is followed by disaggregation of the general flows into flows connecting 'large' and 'small' categories of manufacturers, wholesalers, retailers, and consumers. Optimization methods are then used to determine the most likely network flows consistent with given data. Vulnerability can be assessed for a potential contamination point using a modified CARVER + Shock model. Once the facility and

TargetCrys: protein crystallization prediction by fusing multi-view features with two-layered SVM.

Science.gov (United States)

Hu, Jun; Han, Ke; Li, Yang; Yang, Jing-Yu; Shen, Hong-Bin; Yu, Dong-Jun

2016-11-01

The accurate prediction of whether a protein will crystallize plays a crucial role in improving the success rate of protein crystallization projects. A common critical problem in the development of machine-learning-based protein crystallization predictors is how to effectively utilize protein features extracted from different views. In this study, we aimed to improve the efficiency of fusing multi-view protein features by proposing a new two-layered SVM (2L-SVM) which switches the feature-level fusion problem to a decision-level fusion problem: the SVMs in the 1st layer of the 2L-SVM are trained on each of the multi-view feature sets; then, the outputs of the 1st layer SVMs, which are the "intermediate" decisions made based on the respective feature sets, are further ensembled by a 2nd layer SVM. Based on the proposed 2L-SVM, we implemented a sequence-based protein crystallization predictor called TargetCrys. Experimental results on several benchmark datasets demonstrated the efficacy of the proposed 2L-SVM for fusing multi-view features. We also compared TargetCrys with existing sequence-based protein crystallization predictors and demonstrated that the proposed TargetCrys outperformed most of the existing predictors and is competitive with the state-of-the-art predictors. The TargetCrys webserver and datasets used in this study are freely available for academic use at: http://csbio.njust.edu.cn/bioinf/TargetCrys .

DisoMCS: Accurately Predicting Protein Intrinsically Disordered Regions Using a Multi-Class Conservative Score Approach.

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Zhiheng Wang

Full Text Available The precise prediction of protein intrinsically disordered regions, which play a crucial role in biological procedures, is a necessary prerequisite to further the understanding of the principles and mechanisms of protein function. Here, we propose a novel predictor, DisoMCS, which is a more accurate predictor of protein intrinsically disordered regions. The DisoMCS bases on an original multi-class conservative score (MCS obtained by sequence-order/disorder alignment. Initially, near-disorder regions are defined on fragments located at both the terminus of an ordered region connecting a disordered region. Then the multi-class conservative score is generated by sequence alignment against a known structure database and represented as order, near-disorder and disorder conservative scores. The MCS of each amino acid has three elements: order, near-disorder and disorder profiles. Finally, the MCS is exploited as features to identify disordered regions in sequences. DisoMCS utilizes a non-redundant data set as the training set, MCS and predicted secondary structure as features, and a conditional random field as the classification algorithm. In predicted near-disorder regions a residue is determined as an order or a disorder according to the optimized decision threshold. DisoMCS was evaluated by cross-validation, large-scale prediction, independent tests and CASP (Critical Assessment of Techniques for Protein Structure Prediction tests. All results confirmed that DisoMCS was very competitive in terms of accuracy of prediction when compared with well-established publicly available disordered region predictors. It also indicated our approach was more accurate when a query has higher homologous with the knowledge database.The DisoMCS is available at http://cal.tongji.edu.cn/disorder/.

Same but not alike: Structure, flexibility and energetics of domains in multi-domain proteins are influenced by the presence of other domains.

Science.gov (United States)

Vishwanath, Sneha; de Brevern, Alexandre G; Srinivasan, Narayanaswamy

2018-02-01

The majority of the proteins encoded in the genomes of eukaryotes contain more than one domain. Reasons for high prevalence of multi-domain proteins in various organisms have been attributed to higher stability and functional and folding advantages over single-domain proteins. Despite these advantages, many proteins are composed of only one domain while their homologous domains are part of multi-domain proteins. In the study presented here, differences in the properties of protein domains in single-domain and multi-domain systems and their influence on functions are discussed. We studied 20 pairs of identical protein domains, which were crystallized in two forms (a) tethered to other proteins domains and (b) tethered to fewer protein domains than (a) or not tethered to any protein domain. Results suggest that tethering of domains in multi-domain proteins influences the structural, dynamic and energetic properties of the constituent protein domains. 50% of the protein domain pairs show significant structural deviations while 90% of the protein domain pairs show differences in dynamics and 12% of the residues show differences in the energetics. To gain further insights on the influence of tethering on the function of the domains, 4 pairs of homologous protein domains, where one of them is a full-length single-domain protein and the other protein domain is a part of a multi-domain protein, were studied. Analyses showed that identical and structurally equivalent functional residues show differential dynamics in homologous protein domains; though comparable dynamics between in-silico generated chimera protein and multi-domain proteins were observed. From these observations, the differences observed in the functions of homologous proteins could be attributed to the presence of tethered domain. Overall, we conclude that tethered domains in multi-domain proteins not only provide stability or folding advantages but also influence pathways resulting in differences in

Patterning protein complexes on DNA nanostructures using a GFP nanobody.

Science.gov (United States)

Sommese, R F; Hariadi, R F; Kim, K; Liu, M; Tyska, M J; Sivaramakrishnan, S

2016-11-01

DNA nanostructures have become an important and powerful tool for studying protein function over the last 5 years. One of the challenges, though, has been the development of universal methods for patterning protein complexes on DNA nanostructures. Herein, we present a new approach for labeling DNA nanostructures by functionalizing them with a GFP nanobody. We demonstrate the ability to precisely control protein attachment via our nanobody linker using two enzymatic model systems, namely adenylyl cyclase activity and myosin motility. Finally, we test the power of this attachment method by patterning unpurified, endogenously expressed Arp2/3 protein complex from cell lysate. By bridging DNA nanostructures with a fluorescent protein ubiquitous throughout cell and developmental biology and protein biochemistry, this approach significantly streamlines the application of DNA nanostructures as a programmable scaffold in biological studies. © 2016 The Protein Society.

Characterization of the ternary Usher syndrome SANS/ush2a/whirlin protein complex.

Science.gov (United States)

Sorusch, Nasrin; Bauß, Katharina; Plutniok, Janet; Samanta, Ananya; Knapp, Barbara; Nagel-Wolfrum, Kerstin; Wolfrum, Uwe

2017-03-15

The Usher syndrome (USH) is the most common form of inherited deaf-blindness, accompanied by vestibular dysfunction. Due to the heterogeneous manifestation of the clinical symptoms, three USH types (USH1-3) and additional atypical forms are distinguished. USH1 and USH2 proteins have been shown to function together in multiprotein networks in photoreceptor cells and hair cells. Mutations in USH proteins are considered to disrupt distinct USH protein networks and finally lead to the development of USH.To get novel insights into the molecular pathomechanisms underlying USH, we further characterize the periciliary USH protein network in photoreceptor cells. We show the direct interaction between the scaffold protein SANS (USH1G) and the transmembrane adhesion protein ush2a and that both assemble into a ternary USH1/USH2 complex together with the PDZ-domain protein whirlin (USH2D) via mutual interactions. Immunohistochemistry and proximity ligation assays demonstrate co-localization of complex partners and complex formation, respectively, in the periciliary region, the inner segment and at the synapses of rodent and human photoreceptor cells. Protein-protein interaction assays and co-expression of complex partners reveal that pathogenic mutations in USH1G severely affect formation of the SANS/ush2a/whirlin complex. Translational read-through drug treatment, targeting the c.728C > A (p.S243X) nonsense mutation, restored SANS scaffold function. We conclude that USH1 and USH2 proteins function together in higher order protein complexes. The maintenance of USH1/USH2 protein complexes depends on multiple USH1/USH2 protein interactions, which are disrupted by pathogenic mutations in USH1G protein SANS. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Translation initiation mediated by nuclear cap-binding protein complex.

Science.gov (United States)

Ryu, Incheol; Kim, Yoon Ki

2017-04-01

In mammals, cap-dependent translation of mRNAs is initiated by two distinct mechanisms: cap-binding complex (CBC; a heterodimer of CBP80 and 20)-dependent translation (CT) and eIF4E-dependent translation (ET). Both translation initiation mechanisms share common features in driving cap- dependent translation; nevertheless, they can be distinguished from each other based on their molecular features and biological roles. CT is largely associated with mRNA surveillance such as nonsense-mediated mRNA decay (NMD), whereas ET is predominantly involved in the bulk of protein synthesis. However, several recent studies have demonstrated that CT and ET have similar roles in protein synthesis and mRNA surveillance. In a subset of mRNAs, CT preferentially drives the cap-dependent translation, as ET does, and ET is responsible for mRNA surveillance, as CT does. In this review, we summarize and compare the molecular features of CT and ET with a focus on the emerging roles of CT in translation. [BMB Reports 2017; 50(4): 186-193].

Adenosine deaminase complexing protein (ADCP): a transformation sensitive protein with potentials of a cancer marker.

Science.gov (United States)

Herbschleb-Voogt, E; Ten Kate, J; Meera Khan, P

1983-01-01

Several observations by independent investigators in the past have indicated that adenosine deaminase complexing protein (ADCP), present in considerable quantities in certain human tissues, was absent or decreased in the cancers originated from them. During the present study, electrophoretic analysis of adenosine deaminase (ADA) isozymes and radioimmunoassay for ADCP in the primary fibroblasts and the transformed as well as certain tumor derived cell lines have demonstrated that ADCP present in large quantities in the primary cells was absent or nearly absent in the transformed or tumor-derived cell lines. Though the mechanisms involved are not yet clear, the above observations indicate that ADCP has the potentials of a useful marker in the studies on transformed cells and cancer tissues.

Recombinant protein expression for structural biology in HEK 293F suspension cells: a novel and accessible approach.

Science.gov (United States)

Portolano, Nicola; Watson, Peter J; Fairall, Louise; Millard, Christopher J; Milano, Charles P; Song, Yun; Cowley, Shaun M; Schwabe, John W R

2014-10-16

The expression and purification of large amounts of recombinant protein complexes is an essential requirement for structural biology studies. For over two decades, prokaryotic expression systems such as E. coli have dominated the scientific literature over costly and less efficient eukaryotic cell lines. Despite the clear advantage in terms of yields and costs of expressing recombinant proteins in bacteria, the absence of specific co-factors, chaperones and post-translational modifications may cause loss of function, mis-folding and can disrupt protein-protein interactions of certain eukaryotic multi-subunit complexes, surface receptors and secreted proteins. The use of mammalian cell expression systems can address these drawbacks since they provide a eukaryotic expression environment. However, low protein yields and high costs of such methods have until recently limited their use for structural biology. Here we describe a simple and accessible method for expressing and purifying milligram quantities of protein by performing transient transfections of suspension grown HEK (Human Embryonic Kidney) 293 F cells.

Predictive Big Data Analytics: A Study of Parkinson's Disease Using Large, Complex, Heterogeneous, Incongruent, Multi-Source and Incomplete Observations.

Science.gov (United States)

Dinov, Ivo D; Heavner, Ben; Tang, Ming; Glusman, Gustavo; Chard, Kyle; Darcy, Mike; Madduri, Ravi; Pa, Judy; Spino, Cathie; Kesselman, Carl; Foster, Ian; Deutsch, Eric W; Price, Nathan D; Van Horn, John D; Ames, Joseph; Clark, Kristi; Hood, Leroy; Hampstead, Benjamin M; Dauer, William; Toga, Arthur W

2016-01-01

A unique archive of Big Data on Parkinson's Disease is collected, managed and disseminated by the Parkinson's Progression Markers Initiative (PPMI). The integration of such complex and heterogeneous Big Data from multiple sources offers unparalleled opportunities to study the early stages of prevalent neurodegenerative processes, track their progression and quickly identify the efficacies of alternative treatments. Many previous human and animal studies have examined the relationship of Parkinson's disease (PD) risk to trauma, genetics, environment, co-morbidities, or life style. The defining characteristics of Big Data-large size, incongruency, incompleteness, complexity, multiplicity of scales, and heterogeneity of information-generating sources-all pose challenges to the classical techniques for data management, processing, visualization and interpretation. We propose, implement, test and validate complementary model-based and model-free approaches for PD classification and prediction. To explore PD risk using Big Data methodology, we jointly processed complex PPMI imaging, genetics, clinical and demographic data. Collective representation of the multi-source data facilitates the aggregation and harmonization of complex data elements. This enables joint modeling of the complete data, leading to the development of Big Data analytics, predictive synthesis, and statistical validation. Using heterogeneous PPMI data, we developed a comprehensive protocol for end-to-end data characterization, manipulation, processing, cleaning, analysis and validation. Specifically, we (i) introduce methods for rebalancing imbalanced cohorts, (ii) utilize a wide spectrum of classification methods to generate consistent and powerful phenotypic predictions, and (iii) generate reproducible machine-learning based classification that enables the reporting of model parameters and diagnostic forecasting based on new data. We evaluated several complementary model-based predictive approaches

Predictive Big Data Analytics: A Study of Parkinson's Disease Using Large, Complex, Heterogeneous, Incongruent, Multi-Source and Incomplete Observations.

Directory of Open Access Journals (Sweden)

Ivo D Dinov

Full Text Available A unique archive of Big Data on Parkinson's Disease is collected, managed and disseminated by the Parkinson's Progression Markers Initiative (PPMI. The integration of such complex and heterogeneous Big Data from multiple sources offers unparalleled opportunities to study the early stages of prevalent neurodegenerative processes, track their progression and quickly identify the efficacies of alternative treatments. Many previous human and animal studies have examined the relationship of Parkinson's disease (PD risk to trauma, genetics, environment, co-morbidities, or life style. The defining characteristics of Big Data-large size, incongruency, incompleteness, complexity, multiplicity of scales, and heterogeneity of information-generating sources-all pose challenges to the classical techniques for data management, processing, visualization and interpretation. We propose, implement, test and validate complementary model-based and model-free approaches for PD classification and prediction. To explore PD risk using Big Data methodology, we jointly processed complex PPMI imaging, genetics, clinical and demographic data.Collective representation of the multi-source data facilitates the aggregation and harmonization of complex data elements. This enables joint modeling of the complete data, leading to the development of Big Data analytics, predictive synthesis, and statistical validation. Using heterogeneous PPMI data, we developed a comprehensive protocol for end-to-end data characterization, manipulation, processing, cleaning, analysis and validation. Specifically, we (i introduce methods for rebalancing imbalanced cohorts, (ii utilize a wide spectrum of classification methods to generate consistent and powerful phenotypic predictions, and (iii generate reproducible machine-learning based classification that enables the reporting of model parameters and diagnostic forecasting based on new data. We evaluated several complementary model

Multi-scale modeling with cellular automata: The complex automata approach

NARCIS (Netherlands)

Hoekstra, A.G.; Falcone, J.-L.; Caiazzo, A.; Chopard, B.

2008-01-01

Cellular Automata are commonly used to describe complex natural phenomena. In many cases it is required to capture the multi-scale nature of these phenomena. A single Cellular Automata model may not be able to efficiently simulate a wide range of spatial and temporal scales. It is our goal to

Anthropic prediction for a large multi-jump landscape

International Nuclear Information System (INIS)

Schwartz-Perlov, Delia

2008-01-01

The assumption of a flat prior distribution plays a critical role in the anthropic prediction of the cosmological constant. In a previous paper we analytically calculated the distribution for the cosmological constant, including the prior and anthropic selection effects, in a large toy 'single-jump' landscape model. We showed that it is possible for the fractal prior distribution that we found to behave as an effectively flat distribution in a wide class of landscapes, but only if the single-jump size is large enough. We extend this work here by investigating a large (N∼10 500 ) toy 'multi-jump' landscape model. The jump sizes range over three orders of magnitude and an overall free parameter c determines the absolute size of the jumps. We will show that for 'large' c the distribution of probabilities of vacua in the anthropic range is effectively flat, and thus the successful anthropic prediction is validated. However, we argue that for small c, the distribution may not be smooth

Multi-scaled normal mode analysis method for dynamics simulation of protein-membrane complexes: A case study of potassium channel gating motion correlations

Energy Technology Data Exchange (ETDEWEB)

Wu, Xiaokun; Han, Min; Ming, Dengming, E-mail: dming@fudan.edu.cn [Department of Physiology and Biophysics, School of Life Sciences, Fudan University, Shanghai (China)

2015-10-07

Membrane proteins play critically important roles in many cellular activities such as ions and small molecule transportation, signal recognition, and transduction. In order to fulfill their functions, these proteins must be placed in different membrane environments and a variety of protein-lipid interactions may affect the behavior of these proteins. One of the key effects of protein-lipid interactions is their ability to change the dynamics status of membrane proteins, thus adjusting their functions. Here, we present a multi-scaled normal mode analysis (mNMA) method to study the dynamics perturbation to the membrane proteins imposed by lipid bi-layer membrane fluctuations. In mNMA, channel proteins are simulated at all-atom level while the membrane is described with a coarse-grained model. mNMA calculations clearly show that channel gating motion can tightly couple with a variety of membrane deformations, including bending and twisting. We then examined bi-channel systems where two channels were separated with different distances. From mNMA calculations, we observed both positive and negative gating correlations between two neighboring channels, and the correlation has a maximum as the channel center-to-center distance is close to 2.5 times of their diameter. This distance is larger than recently found maximum attraction distance between two proteins embedded in membrane which is 1.5 times of the protein size, indicating that membrane fluctuation might impose collective motions among proteins within a larger area. The hybrid resolution feature in mNMA provides atomic dynamics information for key components in the system without costing much computer resource. We expect it to be a conventional simulation tool for ordinary laboratories to study the dynamics of very complicated biological assemblies. The source code is available upon request to the authors.

Identifying protein complex by integrating characteristic of core-attachment into dynamic PPI network.

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Xianjun Shen

Full Text Available How to identify protein complex is an important and challenging task in proteomics. It would make great contribution to our knowledge of molecular mechanism in cell life activities. However, the inherent organization and dynamic characteristic of cell system have rarely been incorporated into the existing algorithms for detecting protein complexes because of the limitation of protein-protein interaction (PPI data produced by high throughput techniques. The availability of time course gene expression profile enables us to uncover the dynamics of molecular networks and improve the detection of protein complexes. In order to achieve this goal, this paper proposes a novel algorithm DCA (Dynamic Core-Attachment. It detects protein-complex core comprising of continually expressed and highly connected proteins in dynamic PPI network, and then the protein complex is formed by including the attachments with high adhesion into the core. The integration of core-attachment feature into the dynamic PPI network is responsible for the superiority of our algorithm. DCA has been applied on two different yeast dynamic PPI networks and the experimental results show that it performs significantly better than the state-of-the-art techniques in terms of prediction accuracy, hF-measure and statistical significance in biology. In addition, the identified complexes with strong biological significance provide potential candidate complexes for biologists to validate.

Intensity limits for stationary and interacting multi-soliton complexes

International Nuclear Information System (INIS)

Sukhorukov, Andrey A.; Akhmediev, Nail N.

2002-01-01

We obtain an accurate estimate for the peak intensities of multi-soliton complexes for a Kerr-type nonlinearity in the (1+1) dimension problem. Using exact analytical solutions of the integrable set of nonlinear Schroedinger equations, we establish a rigorous relationship between the eigenvalues of incoherently-coupled fundamental solitons and the range of admissible intensities. A clear geometrical interpretation of this effect is given

Using the multi-objective optimization replica exchange Monte Carlo enhanced sampling method for protein-small molecule docking.

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Wang, Hongrui; Liu, Hongwei; Cai, Leixin; Wang, Caixia; Lv, Qiang

2017-07-10

In this study, we extended the replica exchange Monte Carlo (REMC) sampling method to protein-small molecule docking conformational prediction using RosettaLigand. In contrast to the traditional Monte Carlo (MC) and REMC sampling methods, these methods use multi-objective optimization Pareto front information to facilitate the selection of replicas for exchange. The Pareto front information generated to select lower energy conformations as representative conformation structure replicas can facilitate the convergence of the available conformational space, including available near-native structures. Furthermore, our approach directly provides min-min scenario Pareto optimal solutions, as well as a hybrid of the min-min and max-min scenario Pareto optimal solutions with lower energy conformations for use as structure templates in the REMC sampling method. These methods were validated based on a thorough analysis of a benchmark data set containing 16 benchmark test cases. An in-depth comparison between MC, REMC, multi-objective optimization-REMC (MO-REMC), and hybrid MO-REMC (HMO-REMC) sampling methods was performed to illustrate the differences between the four conformational search strategies. Our findings demonstrate that the MO-REMC and HMO-REMC conformational sampling methods are powerful approaches for obtaining protein-small molecule docking conformational predictions based on the binding energy of complexes in RosettaLigand.

Dynamic organization of genetic recombination proteins and chromosomes

International Nuclear Information System (INIS)

Essers, J.; Van Cappellen, G.; Van Drunen, E.; Theil, A.; Jaspers, N.N.G.J.; Houtsmuller, A.B.; Vermeulen, W.; Kanaar, R.

2003-01-01

Homologous recombination requires the co-ordinated action of the RAD52 group proteins, including Rad51, Rad52 and Rad54. Upon treatment of mammalian cells with ionizing radiation, these proteins accumulate into foci at sites of DSB induction. We probed the nature of the DNA damage-induced foci in living cells with the use of photobleaching techniques. These foci are not static assemblies of DNA repair proteins. Instead, they are dynamic structures of which Rad51 is a stable core component, while Rad52 and Rad54 reversibly interact with the structure. Furthermore, even though the RAD52 group proteins colocalize in the DNA damage-induced foci, the majority of the proteins are not part of the same multi-protein complex in the absence of DNA damage. Executing DNA transactions through dynamic multi-protein complexes, rather than stable holo-complexes, allows greater flexibility during the transaction. In case of DNA repair, for example, it allows cross talk between different DNA repair pathways and coupling to other DNA transactions, such as replication. In addition to the behavior of proteins in living cells, we have tracked chromosomes during cell division. Our results suggest that the relative position of chromosomes in the mother cell is conserved in its daughter cells

Precursor binding to an 880-kDa Toc complex as an early step during active import of protein into chloroplasts.

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Chen, Kuan-Yu; Li, Hsou-min

2007-01-01

The import of protein into chloroplasts is mediated by translocon components located in the chloroplast outer (the Toc proteins) and inner (the Tic proteins) envelope membranes. To identify intermediate steps during active import, we used sucrose density gradient centrifugation and blue-native polyacrylamide gel electrophoresis (BN-PAGE) to identify complexes of translocon components associated with precursor proteins under active import conditions instead of arrested binding conditions. Importing precursor proteins in solubilized chloroplast membranes formed a two-peak distribution in the sucrose density gradient. The heavier peak was in a similar position as the previously reported Tic/Toc supercomplex and was too large to be analyzed by BN-PAGE. The BN-PAGE analyses of the lighter peak revealed that precursors accumulated in at least two complexes. The first complex migrated at a position close to the ferritin dimer (approximately 880 kDa) and contained only the Toc components. Kinetic analyses suggested that this Toc complex represented an earlier step in the import process than the Tic/Toc supercomplex. The second complex in the lighter peak migrated at the position of the ferritin trimer (approximately 1320 kDa). It contained, in addition to the Toc components, Tic110, Hsp93, and an hsp70 homolog, but not Tic40. Two different precursor proteins were shown to associate with the same complexes. Processed mature proteins first appeared in the membranes at the same fractions as the Tic/Toc supercomplex, suggesting that processing of transit peptides occurs while precursors are still associated with the supercomplex.

A plant virus movement protein forms ringlike complexes with the major nucleolar protein, fibrillarin, in vitro.

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Canetta, Elisabetta; Kim, Sang Hyon; Kalinina, Natalia O; Shaw, Jane; Adya, Ashok K; Gillespie, Trudi; Brown, John W S; Taliansky, Michael

2008-02-29

Fibrillarin, one of the major proteins of the nucleolus, has methyltransferase activity directing 2'-O-ribose methylation of rRNA and snRNAs and is required for rRNA processing. The ability of the plant umbravirus, groundnut rosette virus, to move long distances through the phloem, the specialized plant vascular system, has been shown to strictly depend on the interaction of one of its proteins, the ORF3 protein (protein encoded by open reading frame 3), with fibrillarin. This interaction is essential for several stages in the groundnut rosette virus life cycle such as nucleolar import of the ORF3 protein via Cajal bodies, relocalization of some fibrillarin from the nucleolus to cytoplasm, and assembly of cytoplasmic umbraviral ribonucleoprotein particles that are themselves required for the long-distance spread of the virus and systemic infection. Here, using atomic force microscopy, we determine the architecture of these complexes as single-layered ringlike structures with a diameter of 18-22 nm and a height of 2.0+/-0.4 nm, which consist of several (n=6-8) distinct protein granules. We also estimate the molar ratio of fibrillarin to ORF3 protein in the complexes as approximately 1:1. Based on these data, we propose a model of the structural organization of fibrillarin-ORF3 protein complexes and discuss potential mechanistic and functional implications that may also apply to other viruses.

Multivariate Multi-Scale Permutation Entropy for Complexity Analysis of Alzheimer’s Disease EEG

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Isabella Palamara

2012-07-01

Full Text Available An original multivariate multi-scale methodology for assessing the complexity of physiological signals is proposed. The technique is able to incorporate the simultaneous analysis of multi-channel data as a unique block within a multi-scale framework. The basic complexity measure is done by using Permutation Entropy, a methodology for time series processing based on ordinal analysis. Permutation Entropy is conceptually simple, structurally robust to noise and artifacts, computationally very fast, which is relevant for designing portable diagnostics. Since time series derived from biological systems show structures on multiple spatial-temporal scales, the proposed technique can be useful for other types of biomedical signal analysis. In this work, the possibility of distinguish among the brain states related to Alzheimer’s disease patients and Mild Cognitive Impaired subjects from normal healthy elderly is checked on a real, although quite limited, experimental database.

PredPPCrys: accurate prediction of sequence cloning, protein production, purification and crystallization propensity from protein sequences using multi-step heterogeneous feature fusion and selection.

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Huilin Wang

Full Text Available X-ray crystallography is the primary approach to solve the three-dimensional structure of a protein. However, a major bottleneck of this method is the failure of multi-step experimental procedures to yield diffraction-quality crystals, including sequence cloning, protein material production, purification, crystallization and ultimately, structural determination. Accordingly, prediction of the propensity of a protein to successfully undergo these experimental procedures based on the protein sequence may help narrow down laborious experimental efforts and facilitate target selection. A number of bioinformatics methods based on protein sequence information have been developed for this purpose. However, our knowledge on the important determinants of propensity for a protein sequence to produce high diffraction-quality crystals remains largely incomplete. In practice, most of the existing methods display poorer performance when evaluated on larger and updated datasets. To address this problem, we constructed an up-to-date dataset as the benchmark, and subsequently developed a new approach termed 'PredPPCrys' using the support vector machine (SVM. Using a comprehensive set of multifaceted sequence-derived features in combination with a novel multi-step feature selection strategy, we identified and characterized the relative importance and contribution of each feature type to the prediction performance of five individual experimental steps required for successful crystallization. The resulting optimal candidate features were used as inputs to build the first-level SVM predictor (PredPPCrys I. Next, prediction outputs of PredPPCrys I were used as the input to build second-level SVM classifiers (PredPPCrys II, which led to significantly enhanced prediction performance. Benchmarking experiments indicated that our PredPPCrys method outperforms most existing procedures on both up-to-date and previous datasets. In addition, the predicted crystallization

Isotope coded protein labeling coupled immunoprecipitation (ICPL-IP): a novel approach for quantitative protein complex analysis from native tissue.

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Vogt, Andreas; Fuerholzner, Bettina; Kinkl, Norbert; Boldt, Karsten; Ueffing, Marius

2013-05-01

High confidence definition of protein interactions is an important objective toward the understanding of biological systems. Isotope labeling in combination with affinity-based isolation of protein complexes has increased in accuracy and reproducibility, yet, larger organisms--including humans--are hardly accessible to metabolic labeling and thus, a major limitation has been its restriction to small animals, cell lines, and yeast. As composition as well as the stoichiometry of protein complexes can significantly differ in primary tissues, there is a great demand for methods capable to combine the selectivity of affinity-based isolation as well as the accuracy and reproducibility of isotope-based labeling with its application toward analysis of protein interactions from intact tissue. Toward this goal, we combined isotope coded protein labeling (ICPL)(1) with immunoprecipitation (IP) and quantitative mass spectrometry (MS). ICPL-IP allows sensitive and accurate analysis of protein interactions from primary tissue. We applied ICPL-IP to immuno-isolate protein complexes from bovine retinal tissue. Protein complexes of immunoprecipitated β-tubulin, a highly abundant protein with known interactors as well as the lowly expressed small GTPase RhoA were analyzed. The results of both analyses demonstrate sensitive and selective identification of known as well as new protein interactions by our method.

Isotope Coded Protein Labeling Coupled Immunoprecipitation (ICPL-IP): A Novel Approach for Quantitative Protein Complex Analysis From Native Tissue*

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Vogt, Andreas; Fuerholzner, Bettina; Kinkl, Norbert; Boldt, Karsten; Ueffing, Marius

2013-01-01

High confidence definition of protein interactions is an important objective toward the understanding of biological systems. Isotope labeling in combination with affinity-based isolation of protein complexes has increased in accuracy and reproducibility, yet, larger organisms—including humans—are hardly accessible to metabolic labeling and thus, a major limitation has been its restriction to small animals, cell lines, and yeast. As composition as well as the stoichiometry of protein complexes can significantly differ in primary tissues, there is a great demand for methods capable to combine the selectivity of affinity-based isolation as well as the accuracy and reproducibility of isotope-based labeling with its application toward analysis of protein interactions from intact tissue. Toward this goal, we combined isotope coded protein labeling (ICPL)1 with immunoprecipitation (IP) and quantitative mass spectrometry (MS). ICPL-IP allows sensitive and accurate analysis of protein interactions from primary tissue. We applied ICPL-IP to immuno-isolate protein complexes from bovine retinal tissue. Protein complexes of immunoprecipitated β-tubulin, a highly abundant protein with known interactors as well as the lowly expressed small GTPase RhoA were analyzed. The results of both analyses demonstrate sensitive and selective identification of known as well as new protein interactions by our method. PMID:23268931

Impacts of large dams on the complexity of suspended sediment dynamics in the Yangtze River

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Wang, Yuankun; Rhoads, Bruce L.; Wang, Dong; Wu, Jichun; Zhang, Xiao

2018-03-01

The Yangtze River is one of the largest and most important rivers in the world. Over the past several decades, the natural sediment regime of the Yangtze River has been altered by the construction of dams. This paper uses multi-scale entropy analysis to ascertain the impacts of large dams on the complexity of high-frequency suspended sediment dynamics in the Yangtze River system, especially after impoundment of the Three Gorges Dam (TGD). In this study, the complexity of sediment dynamics is quantified by framing it within the context of entropy analysis of time series. Data on daily sediment loads for four stations located in the mainstem are analyzed for the past 60 years. The results indicate that dam construction has reduced the complexity of short-term (1-30 days) variation in sediment dynamics near the structures, but that complexity has actually increased farther downstream. This spatial pattern seems to reflect a filtering effect of the dams on the on the temporal pattern of sediment loads as well as decreased longitudinal connectivity of sediment transfer through the river system, resulting in downstream enhancement of the influence of local sediment inputs by tributaries on sediment dynamics. The TGD has had a substantial impact on the complexity of sediment series in the mainstem of the Yangtze River, especially after it became fully operational. This enhanced impact is attributed to the high trapping efficiency of this dam and its associated large reservoir. The sediment dynamics "signal" becomes more spatially variable after dam construction. This study demonstrates the spatial influence of dams on the high-frequency temporal complexity of sediment regimes and provides valuable information that can be used to guide environmental conservation of the Yangtze River.

RNF4 interacts with multiSUMOylated ETV4 [version 2; referees: 2 approved

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Elisa Aguilar-Martinez

2017-02-01

Full Text Available Protein SUMOylation represents an important regulatory event that changes the activities of numerous proteins. Recent evidence demonstrates that polySUMO chains can act as a trigger to direct the ubiquitin ligase RNF4 to substrates to cause their turnover through the ubiquitin pathway. RNF4 uses multiple SUMO interaction motifs (SIMs to bind to these chains. However, in addition to polySUMO chains, a multimeric binding surface created by the simultaneous SUMOylation of multiple residues on a protein or complex could also provide a platform for the recruitment of multi-SIM proteins like RNF4. Here we demonstrate that multiSUMOylated ETV4 can bind to RNF4 and that a unique combination of SIMs is required for RNF4 to interact with this multiSUMOylated platform. Thus RNF4 can bind to proteins that are either polySUMOylated through a single site or multiSUMOylated on several sites and raises the possibility that such multiSIM-multiSUMO interactions might be more widespread.

R7-binding protein targets the G protein β5/R7-regulator of G protein signaling complex to lipid rafts in neuronal cells and brain

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Zhang Jian-Hua

2007-09-01

Full Text Available Abstract Background Heterotrimeric guanine nucleotide-binding regulatory proteins (G proteins, composed of Gα, Gβ, and Gγ subunits, are positioned at the inner face of the plasma membrane and relay signals from activated G protein-coupled cell surface receptors to various signaling pathways. Gβ5 is the most structurally divergent Gβ isoform and forms tight heterodimers with regulator of G protein signalling (RGS proteins of the R7 subfamily (R7-RGS. The subcellular localization of Gβ 5/R7-RGS protein complexes is regulated by the palmitoylation status of the associated R7-binding protein (R7BP, a recently discovered SNARE-like protein. We investigate here whether R7BP controls the targeting of Gβ5/R7-RGS complexes to lipid rafts, cholesterol-rich membrane microdomains where conventional heterotrimeric G proteins and some effector proteins are concentrated in neurons and brain. Results We show that endogenous Gβ5/R7-RGS/R7BP protein complexes are present in native neuron-like PC12 cells and that a fraction is targeted to low-density, detergent-resistant membrane lipid rafts. The buoyant density of endogenous raft-associated Gβ5/R7-RGS protein complexes in PC12 cells was similar to that of lipid rafts containing the palmitoylated marker proteins PSD-95 and LAT, but distinct from that of the membrane microdomain where flotillin was localized. Overexpression of wild-type R7BP, but not its palmitoylation-deficient mutant, greatly enriched the fraction of endogenous Gβ5/R7-RGS protein complexes in the lipid rafts. In HEK-293 cells the palmitoylation status of R7BP also regulated the lipid raft targeting of co-expressed Gβ5/R7-RGS/R7BP proteins. A fraction of endogenous Gβ5/R7-RGS/R7BP complexes was also present in lipid rafts in mouse brain. Conclusion A fraction of Gβ5/R7-RGS/R7BP protein complexes is targeted to low-density, detergent-resistant membrane lipid rafts in PC12 cells and brain. In cultured cells, the palmitoylation status of

Multi-protein assemblies underlie the mesoscale organization of the plasma membrane

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Saka, Sinem K.; Honigmann, Alf; Eggeling, Christian; Hell, Stefan W.; Lang, Thorsten; Rizzoli, Silvio O.

2014-01-01

Most proteins have uneven distributions in the plasma membrane. Broadly speaking, this may be caused by mechanisms specific to each protein, or may be a consequence of a general pattern that affects the distribution of all membrane proteins. The latter hypothesis has been difficult to test in the past. Here, we introduce several approaches based on click chemistry, through which we study the distribution of membrane proteins in living cells, as well as in membrane sheets. We found that the plasma membrane proteins form multi-protein assemblies that are long lived (minutes), and in which protein diffusion is restricted. The formation of the assemblies is dependent on cholesterol. They are separated and anchored by the actin cytoskeleton. Specific proteins are preferentially located in different regions of the assemblies, from their cores to their edges. We conclude that the assemblies constitute a basic mesoscale feature of the membrane, which affects the patterning of most membrane proteins, and possibly also their activity. PMID:25060237

Hydrophobic Interaction Chromatography for Bottom-Up Proteomics Analysis of Single Proteins and Protein Complexes.

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Rackiewicz, Michal; Große-Hovest, Ludger; Alpert, Andrew J; Zarei, Mostafa; Dengjel, Jörn

2017-06-02

Hydrophobic interaction chromatography (HIC) is a robust standard analytical method to purify proteins while preserving their biological activity. It is widely used to study post-translational modifications of proteins and drug-protein interactions. In the current manuscript we employed HIC to separate proteins, followed by bottom-up LC-MS/MS experiments. We used this approach to fractionate antibody species followed by comprehensive peptide mapping as well as to study protein complexes in human cells. HIC-reversed-phase chromatography (RPC)-mass spectrometry (MS) is a powerful alternative to fractionate proteins for bottom-up proteomics experiments making use of their distinct hydrophobic properties.

Cas5d Protein Processes Pre-crRNA and Assembles into a Cascade-like Interference Complex in Subtype I-C/Dvulg CRISPR-Cas System

Energy Technology Data Exchange (ETDEWEB)

Nam, Ki Hyun; Haitjema, Charles; Liu, Xueqi; Ding, Fran; Wang, Hongwei; DeLisa, Matthew P.; Ke, Ailong (Yale); (Cornell); (Tsinghua)

2012-10-10

Clustered regularly interspaced short palindromic repeats (CRISPRs), together with an operon of CRISPR-associated (Cas) proteins, form an RNA-based prokaryotic immune system against exogenous genetic elements. Cas5 family proteins are found in several type I CRISPR-Cas systems. Here, we report the molecular function of subtype I-C/Dvulg Cas5d from Bacillus halodurans. We show that Cas5d cleaves pre-crRNA into unit length by recognizing both the hairpin structure and the 3 single stranded sequence in the CRISPR repeat region. Cas5d structure reveals a ferredoxin domain-based architecture and a catalytic triad formed by Y46, K116, and H117 residues. We further show that after pre-crRNA processing, Cas5d assembles with crRNA, Csd1, and Csd2 proteins to form a multi-sub-unit interference complex similar to Escherichia coli Cascade (CRISPR-associated complex for antiviral defense) in architecture. Our results suggest that formation of a crRNA-presenting Cascade-like complex is likely a common theme among type I CRISPR subtypes.

Radiolysis of DNA-protein complexes

Energy Technology Data Exchange (ETDEWEB)

Begusova, Marie [Department of Radiation Dosimetry, Nuclear Physics Institute, Na Truhlarce 39/64, CZ-18086, Prague 8 (Czech Republic)]. E-mail: begusova@ujf.cas.cz; Gillard, Nathalie [Centre de Biophysique Moleculaire, CNRS, rue Charles-Sadron, F-45071 Orleans Cedex 2 (France); Sy, Denise [Centre de Biophysique Moleculaire, CNRS, rue Charles-Sadron, F-45071 Orleans Cedex 2 (France); Castaing, Bertrand [Centre de Biophysique Moleculaire, CNRS, rue Charles-Sadron, F-45071 Orleans Cedex 2 (France); Charlier, Michel [Centre de Biophysique Moleculaire, CNRS, rue Charles-Sadron, F-45071 Orleans Cedex 2 (France); Spotheim-Maurizot, Melanie [Centre de Biophysique Moleculaire, CNRS, rue Charles-Sadron, F-45071 Orleans Cedex 2 (France)

2005-02-01

We discuss here modifications of DNA and protein radiolysis due to the interaction of these two partners in specific complexes. Experimental patterns of frank strand breaks (FSB) and alkali revealed breaks (ARB) obtained for DNA lac operator bound to the lac repressor and for a DNA containing an abasic site analog bound to the formamidopyrimidine-DNA glycosylase are reported. Experimental data are compared to predicted damage distribution obtained using the theoretical model RADACK.

Radiolysis of DNA-protein complexes

International Nuclear Information System (INIS)

Begusova, Marie; Gillard, Nathalie; Sy, Denise; Castaing, Bertrand; Charlier, Michel; Spotheim-Maurizot, Melanie

2005-01-01

We discuss here modifications of DNA and protein radiolysis due to the interaction of these two partners in specific complexes. Experimental patterns of frank strand breaks (FSB) and alkali revealed breaks (ARB) obtained for DNA lac operator bound to the lac repressor and for a DNA containing an abasic site analog bound to the formamidopyrimidine-DNA glycosylase are reported. Experimental data are compared to predicted damage distribution obtained using the theoretical model RADACK

Co-operative intra-protein structural response due to protein-protein complexation revealed through thermodynamic quantification: study of MDM2-p53 binding.

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Samanta, Sudipta; Mukherjee, Sanchita

2017-10-01

The p53 protein activation protects the organism from propagation of cells with damaged DNA having oncogenic mutations. In normal cells, activity of p53 is controlled by interaction with MDM2. The well understood p53-MDM2 interaction facilitates design of ligands that could potentially disrupt or prevent the complexation owing to its emergence as an important objective for cancer therapy. However, thermodynamic quantification of the p53-peptide induced structural changes of the MDM2-protein remains an area to be explored. This study attempts to understand the conformational free energy and entropy costs due to this complex formation from the histograms of dihedral angles generated from molecular dynamics simulations. Residue-specific quantification illustrates that, hydrophobic residues of the protein contribute maximum to the conformational thermodynamic changes. Thermodynamic quantification of structural changes of the protein unfold the fact that, p53 binding provides a source of inter-element cooperativity among the protein secondary structural elements, where the highest affected structural elements (α2 and α4) found at the binding site of the protein affects faraway structural elements (β1 and Loop1) of the protein. The communication perhaps involves water mediated hydrogen bonded network formation. Further, we infer that in inhibitory F19A mutation of P53, though Phe19 is important in the recognition process, it has less prominent contribution in the stability of the complex. Collectively, this study provides vivid microscopic understanding of the interaction within the protein complex along with exploring mutation sites, which will contribute further to engineer the protein function and binding affinity.

Co-operative intra-protein structural response due to protein-protein complexation revealed through thermodynamic quantification: study of MDM2-p53 binding

Science.gov (United States)

Samanta, Sudipta; Mukherjee, Sanchita

2017-10-01

The p53 protein activation protects the organism from propagation of cells with damaged DNA having oncogenic mutations. In normal cells, activity of p53 is controlled by interaction with MDM2. The well understood p53-MDM2 interaction facilitates design of ligands that could potentially disrupt or prevent the complexation owing to its emergence as an important objective for cancer therapy. However, thermodynamic quantification of the p53-peptide induced structural changes of the MDM2-protein remains an area to be explored. This study attempts to understand the conformational free energy and entropy costs due to this complex formation from the histograms of dihedral angles generated from molecular dynamics simulations. Residue-specific quantification illustrates that, hydrophobic residues of the protein contribute maximum to the conformational thermodynamic changes. Thermodynamic quantification of structural changes of the protein unfold the fact that, p53 binding provides a source of inter-element cooperativity among the protein secondary structural elements, where the highest affected structural elements (α2 and α4) found at the binding site of the protein affects faraway structural elements (β1 and Loop1) of the protein. The communication perhaps involves water mediated hydrogen bonded network formation. Further, we infer that in inhibitory F19A mutation of P53, though Phe19 is important in the recognition process, it has less prominent contribution in the stability of the complex. Collectively, this study provides vivid microscopic understanding of the interaction within the protein complex along with exploring mutation sites, which will contribute further to engineer the protein function and binding affinity.

Encapsulation of Protein-Polysaccharide HIP Complex in Polymeric Nanoparticles

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Ripal Gaudana

2011-01-01

Full Text Available The objective of the present study is to formulate and characterize a nanoparticulate-based formulation of a macromolecule in a hydrophobic ion pairing (HIP complex form. So far, HIP complexation approach has been studied only for proteins with molecular weight of 10–20 kDa. Hence, we have selected bovine serum albumin (BSA having higher molecular weight (66.3 kDa as a model protein and dextran sulphate (DS as a complexing polymer to generate HIP complex. We have prepared and optimized the HIP complex formation process of BSA with DS. Ionic interactions between basic amino acids of BSA with sulphate groups of DS were confirmed by FTIR analysis. Further, nanoparticles were prepared and characterized with respect to size and surface morphology. We observed significant entrapment of BSA in nanoparticles prepared with minimal amounts of PLGA polymer. Finally, results of circular dichroism and intrinsic fluorescence assay have clearly indicated that HIP complexation and method of nanoparticle preparation did not alter the secondary and tertiary structures of BSA.

Radioprotection by polyethylene glycol-protein complexes in mice

International Nuclear Information System (INIS)

Gray, B.H.; Stull, R.W.

1983-01-01

Polyethylene glycol of about 5000 D was activated with cyanuric chloride, and the activated compound was complexed to each of three proteins. Polyethylene glycol-superoxide dismutase and polyethylene glycol-catalase were each radioprotectants when administered prophylactically to female B6CBF1 mice before irradiation. The dose reduction factor for these mice was 1.2 when 5000 units of polyethylene glycol-catalase was administered before 60 Co irradiation. Female B6CBF1 mice administered prophylactic intravenous injections of catalase, polyethylene glycol-albumin, or heat-denatured polyethylene glycol-catalase had survival rates similar to phosphate-buffered saline-injected control mice following 60 Co irradiation. Polyethylene glycol-superoxide dismutase and polyethylene glycol-catalase have radioprotective activity in B6CBF1 mice, which appears to depend in part on enzymatic activities of the complex. However, no radioprotective effect was observed in male C57BL/6 mice injected with each polyethylene glycol-protein complex at either 3 or 24 hr before irradiation. The mechanism for radioprotection by these complexes may depend in part on other factors

Crystallization of bi-functional ligand protein complexes.

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Antoni, Claudia; Vera, Laura; Devel, Laurent; Catalani, Maria Pia; Czarny, Bertrand; Cassar-Lajeunesse, Evelyn; Nuti, Elisa; Rossello, Armando; Dive, Vincent; Stura, Enrico Adriano

2013-06-01

Homodimerization is important in signal transduction and can play a crucial role in many other biological systems. To obtaining structural information for the design of molecules able to control the signalization pathways, the proteins involved will have to be crystallized in complex with ligands that induce dimerization. Bi-functional drugs have been generated by linking two ligands together chemically and the relative crystallizability of complexes with mono-functional and bi-functional ligands has been evaluated. There are problems associated with crystallization with such ligands, but overall, the advantages appear to be greater than the drawbacks. The study involves two matrix metalloproteinases, MMP-12 and MMP-9. Using flexible and rigid linkers we show that it is possible to control the crystal packing and that by changing the ligand-enzyme stoichiometric ratio, one can toggle between having one bi-functional ligand binding to two enzymes and having the same ligand bound to each enzyme. The nature of linker and its point of attachment on the ligand can be varied to aid crystallization, and such variations can also provide valuable structural information about the interactions made by the linker with the protein. We report here the crystallization and structure determination of seven ligand-dimerized complexes. These results suggest that the use of bi-functional drugs can be extended beyond the realm of protein dimerization to include all drug design projects. Copyright © 2013 Elsevier Inc. All rights reserved.

Minmax defense strategy for complex multi-state systems

International Nuclear Information System (INIS)

Hausken, Kjell; Levitin, Gregory

2009-01-01

This paper presents a general optimization methodology that merges game theory and multi-state system survivability theory. The defender has multiple alternatives of defense strategy that presumes separation and protection of system elements. The attacker also has multiple alternatives of its attack strategy based on a combination of different possible attack actions against different groups of system elements. The defender minimizes, and the attacker maximizes, the expected damage caused by the attack (taking into account the unreliability of system elements and the multi-state nature of complex series-parallel systems). The problem is defined as a two-period minmax non-cooperative game between the defender who moves first and the attacker who moves second. An exhaustive minmax optimization algorithm is presented based on a double-loop genetic algorithm for determining the solution. A universal generating function technique is applied for evaluating the losses caused by system performance reduction. Illustrative examples with solutions are presented

Three-Dimentional Structures of Autophosphorylation Complexes in Crystals of Protein Kinases

KAUST Repository

Dumbrack, Roland

2016-01-26

Protein kinase autophosphorylation is a common regulatory mechanism in cell signaling pathways. Several autophosphorylation complexes have been identified in crystals of protein kinases, with a known serine, threonine, or tyrosine autophosphorylation site of one kinase monomer sitting in the active site of another monomer of the same protein in the crystal. We utilized a structural bioinformatics method to identify all such autophosphorylation complexes in X-ray crystallographic structures in the Protein Data Bank (PDB) by generating all unique kinase/kinase interfaces within and between asymmetric units of each crystal and measuring the distance between the hydroxyl oxygen of potential autophosphorylation sites and the oxygen atoms of the active site aspartic acid residue side chain. We have identified 15 unique autophosphorylation complexes in the PDB, of which 5 complexes have not previously been described in the relevant publications on the crystal structures (N-terminal juxtamembrane regions of CSF1R and EPHA2, activation loop tyrosines of LCK and IGF1R, and a serine in a nuclear localization signal region of CLK2. Mutation of residues in the autophosphorylation complex interface of LCK either severely impaired autophosphorylation or increased it. Taking the autophosphorylation complexes as a whole and comparing them with peptide-substrate/kinase complexes, we observe a number of important features among them. The novel and previously observed autophosphorylation sites are conserved in many kinases, indicating that by homology we can extend the relevance of these complexes to many other clinically relevant drug targets.

Displacement affinity chromatography of protein phosphatase one (PP1 complexes

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Gourlay Robert

2008-11-01

Full Text Available Abstract Background Protein phosphatase one (PP1 is a ubiquitously expressed, highly conserved protein phosphatase that dephosphorylates target protein serine and threonine residues. PP1 is localized to its site of action by interacting with targeting or regulatory proteins, a majority of which contains a primary docking site referred to as the RVXF/W motif. Results We demonstrate that a peptide based on the RVXF/W motif can effectively displace PP1 bound proteins from PP1 retained on the phosphatase affinity matrix microcystin-Sepharose. Subsequent co-immunoprecipitation experiments confirmed that each identified binding protein was either a direct PP1 interactor or was in a complex that contains PP1. Our results have linked PP1 to numerous new nuclear functions and proteins, including Ki-67, Rif-1, topoisomerase IIα, several nuclear helicases, NUP153 and the TRRAP complex. Conclusion This modification of the microcystin-Sepharose technique offers an effective means of purifying novel PP1 regulatory subunits and associated proteins and provides a simple method to uncover a link between PP1 and additional cellular processes.

Affinity capture of biotinylated proteins at acidic conditions to facilitate hydrogen/deuterium exchange mass spectrometry analysis of multimeric protein complexes

DEFF Research Database (Denmark)

Jensen, Pernille Foged; Jørgensen, Thomas J. D.; Koefoed, Klaus

2013-01-01

Characterization of conformational and dynamic changes associated with protein interactions can be done by hydrogen/deuterium exchange mass spectrometry (HDX-MS) by comparing the deuterium uptake in the bound and unbound state of the proteins. Investigation of local hydrogen/deuterium exchange...... in heteromultimeric protein complexes poses a challenge for the method due to the increased complexity of the mixture of peptides originating from all interaction partners in the complex. Previously, interference of peptides from one interaction partner has been removed by immobilizing the intact protein on beads...... complexes without interference of peptides originating from other interaction partners in the complex. The biotin-streptavidin strategy has been successfully implemented in a model system with two recombinant monoclonal antibodies that target nonoverlapping epitopes on the human epidermal growth factor...

Human cancer protein-protein interaction network: a structural perspective.

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Gozde Kar

2009-12-01

Full Text Available Protein-protein interaction networks provide a global picture of cellular function and biological processes. Some proteins act as hub proteins, highly connected to others, whereas some others have few interactions. The dysfunction of some interactions causes many diseases, including cancer. Proteins interact through their interfaces. Therefore, studying the interface properties of cancer-related proteins will help explain their role in the interaction networks. Similar or overlapping binding sites should be used repeatedly in single interface hub proteins, making them promiscuous. Alternatively, multi-interface hub proteins make use of several distinct binding sites to bind to different partners. We propose a methodology to integrate protein interfaces into cancer interaction networks (ciSPIN, cancer structural protein interface network. The interactions in the human protein interaction network are replaced by interfaces, coming from either known or predicted complexes. We provide a detailed analysis of cancer related human protein-protein interfaces and the topological properties of the cancer network. The results reveal that cancer-related proteins have smaller, more planar, more charged and less hydrophobic binding sites than non-cancer proteins, which may indicate low affinity and high specificity of the cancer-related interactions. We also classified the genes in ciSPIN according to phenotypes. Within phenotypes, for breast cancer, colorectal cancer and leukemia, interface properties were found to be discriminating from non-cancer interfaces with an accuracy of 71%, 67%, 61%, respectively. In addition, cancer-related proteins tend to interact with their partners through distinct interfaces, corresponding mostly to multi-interface hubs, which comprise 56% of cancer-related proteins, and constituting the nodes with higher essentiality in the network (76%. We illustrate the interface related affinity properties of two cancer-related hub

A multi-disciplinary approach to study coastal complex landslides: the case of Torino di Sangro (Central Italy)

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Sciarra, Marco; Carabba, Luigi; Urbano, Tullio; Calista, Monia

2016-04-01

This work illustrates the studies carried out on a complex landslide phenomenon between the Sangro and Osento River's mouths, near Torino di Sangro village in Southern Abruzzo Region (Italy). Historical activity of this landslide is well-documented since 1916; the activation/reactivation of the movements caused several interruptions of a national railway and the damage of few houses. The Torino di Sangro case study can be regarded as representative of many large landslides distributed along the central Adriatic coast (e.g., Ancona, Ortona, Vasto and Petacciato Landslides) that affect densely populated urban areas with a large amount of man-made infrastructure. The main controlling factors of these large and deep-seated landslides are still debated. From the geological and geomorphological viewpoint, the central Adriatic coast is characterized by a low-relief landscape (mesa) carved on clay-sandstone-conglomerate bedrock belonging to the Upper Pliocene - Lower Pleistocene marine deposits and locally to the Middle Pleistocene marine to continental transitional deposits. This high coast is widely affected by slope instability (rock falls, rotational, complex and shallow landslides) on both active and inactive sea cliffs, the first being mainly affected by wave-cut erosion and the latter influenced by heavy rainfall and changes of pore pressure. The main landslide has the typical characteristics of a deep-seated gravitation deformation. The landslide study was based on a multidisciplinary approach including: 1) definition and GIS mapping of geology and geomorphology factors (slope, aspect, topographic curvature, bedrock lithology, near-surface deposits, deposit thickness and land use), by means of DTM processing, multi-temporal analysis, and large-scale geomorphological field survey; 2) monitoring system in the landslide; 3) application of empiric models for the analysis of unstable sandstone-conglomerate escarpments; 4) slope stability analysis performed using a

BioPlex Display: An Interactive Suite for Large-Scale AP-MS Protein-Protein Interaction Data.

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Schweppe, Devin K; Huttlin, Edward L; Harper, J Wade; Gygi, Steven P

2018-01-05

The development of large-scale data sets requires a new means to display and disseminate research studies to large audiences. Knowledge of protein-protein interaction (PPI) networks has become a principle interest of many groups within the field of proteomics. At the confluence of technologies, such as cross-linking mass spectrometry, yeast two-hybrid, protein cofractionation, and affinity purification mass spectrometry (AP-MS), detection of PPIs can uncover novel biological inferences at a high-throughput. Thus new platforms to provide community access to large data sets are necessary. To this end, we have developed a web application that enables exploration and dissemination of the growing BioPlex interaction network. BioPlex is a large-scale interactome data set based on AP-MS of baits from the human ORFeome. The latest BioPlex data set release (BioPlex 2.0) contains 56 553 interactions from 5891 AP-MS experiments. To improve community access to this vast compendium of interactions, we developed BioPlex Display, which integrates individual protein querying, access to empirical data, and on-the-fly annotation of networks within an easy-to-use and mobile web application. BioPlex Display enables rapid acquisition of data from BioPlex and development of hypotheses based on protein interactions.

Sub-grouping and sub-functionalization of the RIFIN multi-copy protein family

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Sonnhammer Erik L

2008-01-01

Full Text Available Abstract Background Parasitic protozoans possess many multicopy gene families which have central roles in parasite survival and virulence. The number and variability of members of these gene families often make it difficult to predict possible functions of the encoded proteins. The families of extra-cellular proteins that are exposed to a host immune response have been driven via immune selection to become antigenically variant, and thereby avoid immune recognition while maintaining protein function to establish a chronic infection. Results We have combined phylogenetic and function shift analyses to study the evolution of the RIFIN proteins, which are antigenically variant and are encoded by the largest multicopy gene family in Plasmodium falciparum. We show that this family can be subdivided into two major groups that we named A- and B-RIFIN proteins. This suggested sub-grouping is supported by a recently published study that showed that, despite the presence of the Plasmodium export (PEXEL motif in all RIFIN variants, proteins from each group have different cellular localizations during the intraerythrocytic life cycle of the parasite. In the present study we show that function shift analysis, a novel technique to predict functional divergence between sub-groups of a protein family, indicates that RIFINs have undergone neo- or sub-functionalization. Conclusion These results question the general trend of clustering large antigenically variant protein groups into homogenous families. Assigning functions to protein families requires their subdivision into meaningful groups such as we have shown for the RIFIN protein family. Using phylogenetic and function shift analysis methods, we identify new directions for the investigation of this broad and complex group of proteins.

Megacities and Large Urban Complexes - WMO Role in Addressing Challenges and Opportunities

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Terblanche, Deon; Jalkanen, Liisa

2013-04-01

Megacities and Large Urban Complexes - WMO Role in Addressing Challenges and Opportunities Deon E. Terblanche and Liisa Jalkanen dterblanche@wmo.int ljalkanen@wmo.int World Meteorological Organization, Geneva, Switzerland The 21st Century could amongst others, become known as the century in which our species has evolved from Homo sapiens to Homo urbanus. By now the urban population has surpassed the rural population and the rate of urbanization will continue at such a pace that by 2050 urban dwellers could outnumber their rural counterpart by more than two to one. Most of this growth in urban population will occur in developing countries and along coastal areas. Urbanization is to a large extent the outcome of humans seeking a better life through improved opportunities presented by high-density communities. Megacities and large urban complexes provide more job opportunities and social structures, better transport and communication links and a relative abundance of physical goods and services when compared to most rural areas. Unfortunately these urban complexes also present numerous social and environmental challenges. Urban areas differ from their surroundings by morphology, population density, and with high concentration of industrial activities, energy consumption and transport. They also pose unique challenges to atmospheric modelling and monitoring and create a multi-disciplinary spectrum of potential threats, including air pollution, which need to be addressed in an integrated way. These areas are also vulnerable to the changing climate and its implications to sea-level and extreme events, air quality and related health impacts. Many urban activities are significantly impacted by weather events that would not be considered to be of high impact in less densely populated areas. For instance, moderate precipitation events can cause flooding and landslides as modified urban catchments generally have higher run-off to rainfall ratios than their more pristine rural

PROXiMATE: a database of mutant protein-protein complex thermodynamics and kinetics.

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Jemimah, Sherlyn; Yugandhar, K; Michael Gromiha, M

2017-09-01

We have developed PROXiMATE, a database of thermodynamic data for more than 6000 missense mutations in 174 heterodimeric protein-protein complexes, supplemented with interaction network data from STRING database, solvent accessibility, sequence, structural and functional information, experimental conditions and literature information. Additional features include complex structure visualization, search and display options, download options and a provision for users to upload their data. The database is freely available at http://www.iitm.ac.in/bioinfo/PROXiMATE/ . The website is implemented in Python, and supports recent versions of major browsers such as IE10, Firefox, Chrome and Opera. gromiha@iitm.ac.in. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Multi-functionalized naphthalene complexes for hydrogen storage

International Nuclear Information System (INIS)

Kalamse, Vijayanand; Wadnerkar, Nitin; Chaudhari, Ajay

2013-01-01

A density functional study of hydrogen uptake capacity of multi-functionalized naphthalene with Ti and Li metal atom has been carried out. It is observed that, the naphthalene functionalized with two Ti atoms can interact with total eight hydrogen molecules in which each Ti metal atom interacts with four hydrogen molecules. Naphthalene decorated with two Li atoms can interact with total three H 2 molecules only. First ( 19 Li) and second ( 20 Li) Li atom can interact with only one and two hydrogen molecule respectively. It is observed that, hydrogen molecules bind strongly to the C 10 H 8 Ti 2 complex than C 10 H 8 Li 2 complex. The gravimetric hydrogen uptake capacity of C 10 H 8 Ti 2 and C 10 H 8 Li 2 complex is found to be 6.72 and 3.73 wt% respectively. Moreover, after functionalizing naphthalene with four Li atoms, the uptake capacity is increased to 7.20 wt %. However, the thermochemistry result favors to Ti functionalized naphthalene complex (C 10 H 8 Ti 2 ) for hydrogen storage over Li functionalized naphthalene (both C 10 H 8 Li 2 and C 10 H 8 Li 4 ) complexes. Atom-centered density matrix propagation (ADMP) molecular dynamics simulations have been performed which showed that C 10 H 8 Li 2 and C 10 H 8 Li 4 complex cannot bind single hydrogen molecule at room temperature whereas C 10 H 8 Ti 2 can bind five hydrogen molecules. -- Highlights: ► The gravimetric H 2 uptake capacity of C 10 H 8 Ti 2 complex is 6.72 wt%. ► Uptake capacity of C 10 H 8 Li 2 and C 10 H 8 Li 4 complex is 3.73 and 7.20 wt% respectively. ► C 10 H 8 Ti is more promising material for hydrogen adsorption. ► C 10 H 8 Ti 2 can bind five hydrogen molecules as shown by ADMP-MD results.

Comparative Study of Elastic Network Model and Protein Contact Network for Protein Complexes: The Hemoglobin Case

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Guang Hu

2017-01-01

Full Text Available The overall topology and interfacial interactions play key roles in understanding structural and functional principles of protein complexes. Elastic Network Model (ENM and Protein Contact Network (PCN are two widely used methods for high throughput investigation of structures and interactions within protein complexes. In this work, the comparative analysis of ENM and PCN relative to hemoglobin (Hb was taken as case study. We examine four types of structural and dynamical paradigms, namely, conformational change between different states of Hbs, modular analysis, allosteric mechanisms studies, and interface characterization of an Hb. The comparative study shows that ENM has an advantage in studying dynamical properties and protein-protein interfaces, while PCN is better for describing protein structures quantitatively both from local and from global levels. We suggest that the integration of ENM and PCN would give a potential but powerful tool in structural systems biology.

Alpha complexes in protein structure prediction

DEFF Research Database (Denmark)

Winter, Pawel; Fonseca, Rasmus

2015-01-01

Reducing the computational effort and increasing the accuracy of potential energy functions is of utmost importance in modeling biological systems, for instance in protein structure prediction, docking or design. Evaluating interactions between nonbonded atoms is the bottleneck of such computations......-complexes from scratch for every configuration encountered during the search for the native structure would make this approach hopelessly slow. However, it is argued that kinetic a-complexes can be used to reduce the computational effort of determining the potential energy when "moving" from one configuration...... to a neighboring one. As a consequence, relatively expensive (initial) construction of an a-complex is expected to be compensated by subsequent fast kinetic updates during the search process. Computational results presented in this paper are limited. However, they suggest that the applicability of a...

Nuclear pore complex protein mediated nuclear localization of dicer protein in human cells.

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Yoshinari Ando

Full Text Available Human DICER1 protein cleaves double-stranded RNA into small sizes, a crucial step in production of single-stranded RNAs which are mediating factors of cytoplasmic RNA interference. Here, we clearly demonstrate that human DICER1 protein localizes not only to the cytoplasm but also to the nucleoplasm. We also find that human DICER1 protein associates with the NUP153 protein, one component of the nuclear pore complex. This association is detected predominantly in the cytoplasm but is also clearly distinguishable at the nuclear periphery. Additional characterization of the NUP153-DICER1 association suggests NUP153 plays a crucial role in the nuclear localization of the DICER1 protein.

[Complex automatic data processing in multi-profile hospitals].

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Dovzhenko, Iu M; Panov, G D

1990-01-01

The computerization of data processing in multi-disciplinary hospitals is the key factor in raising the quality of medical care provided to the population, intensifying the work of the personnel, improving the curative and diagnostic process and the use of resources. Even a small experience in complex computerization at the Botkin Hospital indicates that due to the use of the automated system the quality of data processing in being improved, a high level of patients' examination is being provided, a speedy training of young specialists is being achieved, conditions are being created for continuing education of physicians through the analysis of their own activity. At big hospitals a complex solution of administrative and curative diagnostic tasks on the basis of general hospital network of display connection and general hospital data bank is the most prospective form of computerization.

Identification of Protein Complexes Using Weighted PageRank-Nibble Algorithm and Core-Attachment Structure.

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Peng, Wei; Wang, Jianxin; Zhao, Bihai; Wang, Lusheng

2015-01-01

Protein complexes play a significant role in understanding the underlying mechanism of most cellular functions. Recently, many researchers have explored computational methods to identify protein complexes from protein-protein interaction (PPI) networks. One group of researchers focus on detecting local dense subgraphs which correspond to protein complexes by considering local neighbors. The drawback of this kind of approach is that the global information of the networks is ignored. Some methods such as Markov Clustering algorithm (MCL), PageRank-Nibble are proposed to find protein complexes based on random walk technique which can exploit the global structure of networks. However, these methods ignore the inherent core-attachment structure of protein complexes and treat adjacent node equally. In this paper, we design a weighted PageRank-Nibble algorithm which assigns each adjacent node with different probability, and propose a novel method named WPNCA to detect protein complex from PPI networks by using weighted PageRank-Nibble algorithm and core-attachment structure. Firstly, WPNCA partitions the PPI networks into multiple dense clusters by using weighted PageRank-Nibble algorithm. Then the cores of these clusters are detected and the rest of proteins in the clusters will be selected as attachments to form the final predicted protein complexes. The experiments on yeast data show that WPNCA outperforms the existing methods in terms of both accuracy and p-value. The software for WPNCA is available at "http://netlab.csu.edu.cn/bioinfomatics/weipeng/WPNCA/download.html".

Design principles for cancer therapy guided by changes in complexity of protein-protein interaction networks.

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Benzekry, Sebastian; Tuszynski, Jack A; Rietman, Edward A; Lakka Klement, Giannoula

2015-05-28

The ever-increasing expanse of online bioinformatics data is enabling new ways to, not only explore the visualization of these data, but also to apply novel mathematical methods to extract meaningful information for clinically relevant analysis of pathways and treatment decisions. One of the methods used for computing topological characteristics of a space at different spatial resolutions is persistent homology. This concept can also be applied to network theory, and more specifically to protein-protein interaction networks, where the number of rings in an individual cancer network represents a measure of complexity. We observed a linear correlation of R = -0.55 between persistent homology and 5-year survival of patients with a variety of cancers. This relationship was used to predict the proteins within a protein-protein interaction network with the most impact on cancer progression. By re-computing the persistent homology after computationally removing an individual node (protein) from the protein-protein interaction network, we were able to evaluate whether such an inhibition would lead to improvement in patient survival. The power of this approach lied in its ability to identify the effects of inhibition of multiple proteins and in the ability to expose whether the effect of a single inhibition may be amplified by inhibition of other proteins. More importantly, we illustrate specific examples of persistent homology calculations, which correctly predict the survival benefit observed effects in clinical trials using inhibitors of the identified molecular target. We propose that computational approaches such as persistent homology may be used in the future for selection of molecular therapies in clinic. The technique uses a mathematical algorithm to evaluate the node (protein) whose inhibition has the highest potential to reduce network complexity. The greater the drop in persistent homology, the greater reduction in network complexity, and thus a larger

Mannan-binding protein forms complexes with alpha-2-macroglobulin. A protein model for the interaction

DEFF Research Database (Denmark)

Storgaard, P; Holm Nielsen, E; Skriver, E

1995-01-01

We report that alpha-2-macroglobulin (alpha 2M) can form complexes with a high molecular weight porcine mannan-binding protein (pMBP-28). The alpha 2M/pMBP-28 complexes was isolated by PEG-precipitation and affinity chromatography on mannan-Sepharose, protein A-Sepharose and anti-IgM Sepharose......-PAGE, which reacted with antibodies against alpha 2M and pMBP-28, respectively, in Western blotting. Furthermore, alpha 2M/pMBP-28 complexes were demonstrated by electron microscopy. Fractionation of pMBP-containing D-mannose eluate from mannan-Sepharose on Superose 6 showed two protein peaks which reacted...... with anti-C1 s antibodies in ELISA, one of about 650-800 kDa, which in addition contained pMBP-28 and anti-alpha 2M reactive material, the other with an M(r) of 100-150 kDa. The latter peak revealed rhomboid molecules (7 x 15 nm) in the electron microscope and a 67 kDa band in SDS-PAGE under reducing...

Probing the Binding Interfaces of Protein Complexes Using Gas-Phase H/D Exchange Mass Spectrometry

DEFF Research Database (Denmark)

Mistarz, Ulrik H; Brown, Jeffery M; Haselmann, Kim F

2016-01-01

Fast gas-phase hydrogen/deuterium exchange mediated by ND3 gas and measured by mass spectrometry (gas-phase HDX-MS) is a largely unharnessed, fast, and sensitive method for probing primary- and higher-order polypeptide structure. Labeling of heteroatom-bound non-amide hydrogens in a sub-milliseco......Fast gas-phase hydrogen/deuterium exchange mediated by ND3 gas and measured by mass spectrometry (gas-phase HDX-MS) is a largely unharnessed, fast, and sensitive method for probing primary- and higher-order polypeptide structure. Labeling of heteroatom-bound non-amide hydrogens in a sub......-millisecond time span after electrospray ionization by ND3 gas can provide structural insights into protein conformers present in solution. Here, we have explored the use of gas-phase HDX-MS for probing the higher-order structure and binding interfaces of protein complexes originating from native solution...

Pancreatic Islet Protein Complexes and Their Dysregulation in Type 2 Diabetes

DEFF Research Database (Denmark)

Pedersen, Helle Krogh; Gudmundsdottir, Valborg; Brunak, Søren

2017-01-01

Type 2 diabetes (T2D) is a complex disease that involves multiple genes. Numerous risk loci have already been associated with T2D, although many susceptibility genes remain to be identified given heritability estimates. Systems biology approaches hold potential for discovering novel T2D genes...... by considering their biological context, such as tissue-specific protein interaction partners. Pancreatic islets are a key T2D tissue and many of the known genetic risk variants lead to impaired islet function, hence a better understanding of the islet-specific dysregulation in the disease-state is essential...... to unveil the full potential of person-specific profiles. Here we identify 3,692 overlapping pancreatic islet protein complexes (containing 10,805 genes) by integrating islet gene and protein expression data with protein interactions. We found 24 of these complexes to be significantly enriched for genes...

Proteins containing the UBA domain are able to bind to multi-ubiquitin chains

DEFF Research Database (Denmark)

Wilkinson, C R; Seeger, M; Hartmann-Petersen, R

2001-01-01

The UBA domain is a motif found in a variety of proteins, some of which are associated with the ubiquitin-proteasome system. We describe the isolation of a fission-yeast gene, mud1+, which encodes a UBA domain containing protein that is able to bind multi-ubiquitin chains. We show that the UBA do...

Large-scale analysis of phosphorylation site occupancy in eukaryotic proteins

DEFF Research Database (Denmark)

Rao, R Shyama Prasad; Møller, Ian Max

2012-01-01

in proteins is currently lacking. We have therefore analyzed the occurrence and occupancy of phosphorylated sites (~ 100,281) in a large set of eukaryotic proteins (~ 22,995). Phosphorylation probability was found to be much higher in both the  termini of protein sequences and this is much pronounced...... maximum randomness. An analysis of phosphorylation motifs indicated that just 40 motifs and a much lower number of associated kinases might account for nearly 50% of the known phosphorylations in eukaryotic proteins. Our results provide a broad picture of the phosphorylation sites in eukaryotic proteins.......Many recent high throughput technologies have enabled large-scale discoveries of new phosphorylation sites and phosphoproteins. Although they have provided a number of insights into protein phosphorylation and the related processes, an inclusive analysis on the nature of phosphorylated sites...

Architecture of the RNA polymerase II-TFIIF complex revealed by cross-linking and mass spectrometry

DEFF Research Database (Denmark)

Chen, Zhuo Angel; Jawhari, Anass; Fischer, Lutz

2010-01-01

Higher-order multi-protein complexes such as RNA polymerase II (Pol II) complexes with transcription initiation factors are often not amenable to X-ray structure determination. Here, we show that protein cross-linking coupled to mass spectrometry (MS) has now sufficiently advanced as a tool to ex...

A Type-2 fuzzy data fusion approach for building reliable weighted protein interaction networks with application in protein complex detection.

Science.gov (United States)

Mehranfar, Adele; Ghadiri, Nasser; Kouhsar, Morteza; Golshani, Ashkan

2017-09-01

Detecting the protein complexes is an important task in analyzing the protein interaction networks. Although many algorithms predict protein complexes in different ways, surveys on the interaction networks indicate that about 50% of detected interactions are false positives. Consequently, the accuracy of existing methods needs to be improved. In this paper we propose a novel algorithm to detect the protein complexes in 'noisy' protein interaction data. First, we integrate several biological data sources to determine the reliability of each interaction and determine more accurate weights for the interactions. A data fusion component is used for this step, based on the interval type-2 fuzzy voter that provides an efficient combination of the information sources. This fusion component detects the errors and diminishes their effect on the detection protein complexes. So in the first step, the reliability scores have been assigned for every interaction in the network. In the second step, we have proposed a general protein complex detection algorithm by exploiting and adopting the strong points of other algorithms and existing hypotheses regarding real complexes. Finally, the proposed method has been applied for the yeast interaction datasets for predicting the interactions. The results show that our framework has a better performance regarding precision and F-measure than the existing approaches. Copyright © 2017 Elsevier Ltd. All rights reserved.

Traveling-wave ion mobility mass spectrometry of protein complexes

DEFF Research Database (Denmark)

Salbo, Rune; Bush, Matthew F; Naver, Helle

2012-01-01

The collision cross-section (Ω) of a protein or protein complex ion can be measured using traveling-wave (T-wave) ion mobility (IM) mass spectrometry (MS) via calibration with compounds of known Ω. The T-wave Ω-values depend strongly on instrument parameters and calibrant selection. Optimization ...

Radiation-induced dissociation of stable DNA-protein complexes in Erlich ascites carcinoma cells

International Nuclear Information System (INIS)

Juhasz, P.P.; Sirota, N.P.; Gaziev, A.I.

1982-01-01

DNA of Ehrlich ascites carcinoma cells prepared under conditions that were highly denaturing for proteins but not for DNA, contained a group of nonhistone residual proteins. The amount of these proteins increased during DNA replication. The DNA-protein complex observed was sensitive to proteolytic enzymes and/or SH-reagents. γ-irradiation cells with moderate doses leads to a decrease in the amount of DNA-protein complexes. High-dose gamma-irradiation produces enhanced linking of chromosomal proteins with DNA. (author)

Nonlinear analysis of sequence repeats of multi-domain proteins

Energy Technology Data Exchange (ETDEWEB)

Huang Yanzhao [Biomolecular Physics and Modeling Group, Department of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei (China); Li Mingfeng [Biomolecular Physics and Modeling Group, Department of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei (China); Xiao Yi [Biomolecular Physics and Modeling Group, Department of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei (China)]. E-mail: lmf_bill@sina.com

2007-11-15

Many multi-domain proteins have repetitive three-dimensional structures but nearly-random amino acid sequences. In the present paper, by using a modified recurrence plot proposed by us previously, we show that these amino acid sequences have hidden repetitions in fact. These results indicate that the repetitive domain structures are encoded by the repetitive sequences. This also gives a method to detect the repetitive domain structures directly from amino acid sequences.

Large-scale biophysical evaluation of protein PEGylation effects