Protein sequences clustering of herpes virus by using Tribe Markov clustering (Tribe-MCL)

Science.gov (United States)

Bustamam, A.; Siswantining, T.; Febriyani, N. L.; Novitasari, I. D.; Cahyaningrum, R. D.

2017-07-01

The herpes virus can be found anywhere and one of the important characteristics is its ability to cause acute and chronic infection at certain times so as a result of the infection allows severe complications occurred. The herpes virus is composed of DNA containing protein and wrapped by glycoproteins. In this work, the Herpes viruses family is classified and analyzed by clustering their protein-sequence using Tribe Markov Clustering (Tribe-MCL) algorithm. Tribe-MCL is an efficient clustering method based on the theory of Markov chains, to classify protein families from protein sequences using pre-computed sequence similarity information. We implement the Tribe-MCL algorithm using an open source program of R. We select 24 protein sequences of Herpes virus obtained from NCBI database. The dataset consists of three types of glycoprotein B, F, and H. Each type has eight herpes virus that infected humans. Based on our simulation using different inflation factor r=1.5, 2, 3 we find a various number of the clusters results. The greater the inflation factor the greater the number of their clusters. Each protein will grouped together in the same type of protein.

Spectromicroscopy of self-assembled protein clusters

Energy Technology Data Exchange (ETDEWEB)

Schonschek, O.; Hormes, J.; Herzog, V. [Univ. of Bonn (Germany)

1997-04-01

The aim of this project is to use synchrotron radiation as a tool to study biomedical questions concerned with the thyroid glands. The biological background is outlined in a recent paper. In short, Thyroglobulin (TG), the precursor protein of the hormone thyroxine, forms large (20 - 500 microns in diameter) clusters in the extracellular lumen of thyrocytes. The process of the cluster formation is still not well understood but is thought to be a main storage mechanism of TG and therefore thyroxine inside the thyroid glands. For human thyroids, the interconnections of the proteins inside the clusters are mainly disulfide bondings. Normally, sulfur bridges are catalyzed by an enzyme called Protein Disulfide Bridge Isomerase (PDI). While this enzyme is supposed to be not present in any extracellular space, the cluster formation of TG takes place in the lumen between the thyrocytes. A possible explanation is the autocatalysis of TG.

CytoCluster: A Cytoscape Plugin for Cluster Analysis and Visualization of Biological Networks.

Science.gov (United States)

Li, Min; Li, Dongyan; Tang, Yu; Wu, Fangxiang; Wang, Jianxin

2017-08-31

Nowadays, cluster analysis of biological networks has become one of the most important approaches to identifying functional modules as well as predicting protein complexes and network biomarkers. Furthermore, the visualization of clustering results is crucial to display the structure of biological networks. Here we present CytoCluster, a cytoscape plugin integrating six clustering algorithms, HC-PIN (Hierarchical Clustering algorithm in Protein Interaction Networks), OH-PIN (identifying Overlapping and Hierarchical modules in Protein Interaction Networks), IPCA (Identifying Protein Complex Algorithm), ClusterONE (Clustering with Overlapping Neighborhood Expansion), DCU (Detecting Complexes based on Uncertain graph model), IPC-MCE (Identifying Protein Complexes based on Maximal Complex Extension), and BinGO (the Biological networks Gene Ontology) function. Users can select different clustering algorithms according to their requirements. The main function of these six clustering algorithms is to detect protein complexes or functional modules. In addition, BinGO is used to determine which Gene Ontology (GO) categories are statistically overrepresented in a set of genes or a subgraph of a biological network. CytoCluster can be easily expanded, so that more clustering algorithms and functions can be added to this plugin. Since it was created in July 2013, CytoCluster has been downloaded more than 9700 times in the Cytoscape App store and has already been applied to the analysis of different biological networks. CytoCluster is available from http://apps.cytoscape.org/apps/cytocluster.

The Pacific Ocean virome (POV: a marine viral metagenomic dataset and associated protein clusters for quantitative viral ecology.

Directory of Open Access Journals (Sweden)

Bonnie L Hurwitz

Full Text Available Bacteria and their viruses (phage are fundamental drivers of many ecosystem processes including global biogeochemistry and horizontal gene transfer. While databases and resources for studying function in uncultured bacterial communities are relatively advanced, many fewer exist for their viral counterparts. The issue is largely technical in that the majority (often 90% of viral sequences are functionally 'unknown' making viruses a virtually untapped resource of functional and physiological information. Here, we provide a community resource that organizes this unknown sequence space into 27 K high confidence protein clusters using 32 viral metagenomes from four biogeographic regions in the Pacific Ocean that vary by season, depth, and proximity to land, and include some of the first deep pelagic ocean viral metagenomes. These protein clusters more than double currently available viral protein clusters, including those from environmental datasets. Further, a protein cluster guided analysis of functional diversity revealed that richness decreased (i from deep to surface waters, (ii from winter to summer, (iii and with distance from shore in surface waters only. These data provide a framework from which to draw on for future metadata-enabled functional inquiries of the vast viral unknown.

The Pacific Ocean virome (POV): a marine viral metagenomic dataset and associated protein clusters for quantitative viral ecology.

Science.gov (United States)

Hurwitz, Bonnie L; Sullivan, Matthew B

2013-01-01

Bacteria and their viruses (phage) are fundamental drivers of many ecosystem processes including global biogeochemistry and horizontal gene transfer. While databases and resources for studying function in uncultured bacterial communities are relatively advanced, many fewer exist for their viral counterparts. The issue is largely technical in that the majority (often 90%) of viral sequences are functionally 'unknown' making viruses a virtually untapped resource of functional and physiological information. Here, we provide a community resource that organizes this unknown sequence space into 27 K high confidence protein clusters using 32 viral metagenomes from four biogeographic regions in the Pacific Ocean that vary by season, depth, and proximity to land, and include some of the first deep pelagic ocean viral metagenomes. These protein clusters more than double currently available viral protein clusters, including those from environmental datasets. Further, a protein cluster guided analysis of functional diversity revealed that richness decreased (i) from deep to surface waters, (ii) from winter to summer, (iii) and with distance from shore in surface waters only. These data provide a framework from which to draw on for future metadata-enabled functional inquiries of the vast viral unknown.

Hierarchical partitioning of metazoan protein conservation profiles provides new functional insights.

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Jonathan Witztum

Full Text Available The availability of many complete, annotated proteomes enables the systematic study of the relationships between protein conservation and functionality. We explore this question based solely on the presence or absence of protein homologues (a.k.a. conservation profiles. We study 18 metazoans, from two distinct points of view: the human's and the fly's. Using the GOrilla gene ontology (GO analysis tool, we explore functional enrichment of the "universal proteins", those with homologues in all 17 other species, and of the "non-universal proteins". A large number of GO terms are strongly enriched in both human and fly universal proteins. Most of these functions are known to be essential. A smaller number of GO terms, exhibiting markedly different properties, are enriched in both human and fly non-universal proteins. We further explore the non-universal proteins, whose conservation profiles are consistent with the "tree of life" (TOL consistent, as well as the TOL inconsistent proteins. Finally, we applied Quantum Clustering to the conservation profiles of the TOL consistent proteins. Each cluster is strongly associated with one or a small number of specific monophyletic clades in the tree of life. The proteins in many of these clusters exhibit strong functional enrichment associated with the "life style" of the related clades. Most previous approaches for studying function and conservation are "bottom up", studying protein families one by one, and separately assessing the conservation of each. By way of contrast, our approach is "top down". We globally partition the set of all proteins hierarchically, as described above, and then identify protein families enriched within different subdivisions. While supporting previous findings, our approach also provides a tool for discovering novel relations between protein conservation profiles, functionality, and evolutionary history as represented by the tree of life.

Protein-protein association and cellular localization of four essential gene products encoded by tellurite resistance-conferring cluster "ter" from pathogenic Escherichia coli.

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Valkovicova, Lenka; Vavrova, Silvia Minarikova; Mravec, Jozef; Grones, Jozef; Turna, Jan

2013-12-01

Gene cluster "ter" conferring high tellurite resistance has been identified in various pathogenic bacteria including Escherichia coli O157:H7. However, the precise mechanism as well as the molecular function of the respective gene products is unclear. Here we describe protein-protein association and localization analyses of four essential Ter proteins encoded by minimal resistance-conferring fragment (terBCDE) by means of recombinant expression. By using a two-plasmid complementation system we show that the overproduced single Ter proteins are not able to mediate tellurite resistance, but all Ter members play an irreplaceable role within the cluster. We identified several types of homotypic and heterotypic protein-protein associations among the Ter proteins by in vitro and in vivo pull-down assays and determined their cellular localization by cytosol/membrane fractionation. Our results strongly suggest that Ter proteins function involves their mutual association, which probably happens at the interface of the inner plasma membrane and the cytosol.

The function of communities in protein interaction networks at multiple scales

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Jones Nick S

2010-07-01

Full Text Available Abstract Background If biology is modular then clusters, or communities, of proteins derived using only protein interaction network structure should define protein modules with similar biological roles. We investigate the link between biological modules and network communities in yeast and its relationship to the scale at which we probe the network. Results Our results demonstrate that the functional homogeneity of communities depends on the scale selected, and that almost all proteins lie in a functionally homogeneous community at some scale. We judge functional homogeneity using a novel test and three independent characterizations of protein function, and find a high degree of overlap between these measures. We show that a high mean clustering coefficient of a community can be used to identify those that are functionally homogeneous. By tracing the community membership of a protein through multiple scales we demonstrate how our approach could be useful to biologists focusing on a particular protein. Conclusions We show that there is no one scale of interest in the community structure of the yeast protein interaction network, but we can identify the range of resolution parameters that yield the most functionally coherent communities, and predict which communities are most likely to be functionally homogeneous.

Spectroscopic and functional characterization of iron-sulfur cluster-bound forms of Azotobacter vinelandii (Nif)IscA.

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Mapolelo, Daphne T; Zhang, Bo; Naik, Sunil G; Huynh, Boi Hanh; Johnson, Michael K

2012-10-16

The mechanism of [4Fe-4S] cluster assembly on A-type Fe-S cluster assembly proteins, in general, and the specific role of (Nif)IscA in the maturation of nitrogen fixation proteins are currently unknown. To address these questions, in vitro spectroscopic studies (UV-visible absorption/CD, resonance Raman and Mössbauer) have been used to investigate the mechanism of [4Fe-4S] cluster assembly on Azotobacter vinelandii(Nif)IscA, and the ability of (Nif)IscA to accept clusters from NifU and to donate clusters to the apo form of the nitrogenase Fe-protein. The results show that (Nif)IscA can rapidly and reversibly cycle between forms containing one [2Fe-2S](2+) and one [4Fe-4S](2+) cluster per homodimer via DTT-induced two-electron reductive coupling of two [2Fe-2S](2+) clusters and O(2)-induced [4Fe-4S](2+) oxidative cleavage. This unique type of cluster interconversion in response to cellular redox status and oxygen levels is likely to be important for the specific role of A-type proteins in the maturation of [4Fe-4S] cluster-containing proteins under aerobic growth or oxidative stress conditions. Only the [4Fe-4S](2+)-(Nif)IscA was competent for rapid activation of apo-nitrogenase Fe protein under anaerobic conditions. Apo-(Nif)IscA was shown to accept clusters from [4Fe-4S] cluster-bound NifU via rapid intact cluster transfer, indicating a potential role as a cluster carrier for delivery of clusters assembled on NifU. Overall the results support the proposal that A-type proteins can function as carrier proteins for clusters assembled on U-type proteins and suggest that they are likely to supply [2Fe-2S] clusters rather than [4Fe-4S] for the maturation of [4Fe-4S] cluster-containing proteins under aerobic or oxidative stress growth conditions.

Characterization of an M-Cluster-Substituted Nitrogenase VFe Protein.

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Rebelein, Johannes G; Lee, Chi Chung; Newcomb, Megan; Hu, Yilin; Ribbe, Markus W

2018-03-13

The Mo- and V-nitrogenases are two homologous members of the nitrogenase family that are distinguished mainly by the presence of different heterometals (Mo or V) at their respective cofactor sites (M- or V-cluster). However, the V-nitrogenase is ~600-fold more active than its Mo counterpart in reducing CO to hydrocarbons at ambient conditions. Here, we expressed an M-cluster-containing, hybrid V-nitrogenase in Azotobacter vinelandii and compared it to its native, V-cluster-containing counterpart in order to assess the impact of protein scaffold and cofactor species on the differential reactivities of Mo- and V-nitrogenases toward CO. Housed in the VFe protein component of V-nitrogenase, the M-cluster displayed electron paramagnetic resonance (EPR) features similar to those of the V-cluster and demonstrated an ~100-fold increase in hydrocarbon formation activity from CO reduction, suggesting a significant impact of protein environment on the overall CO-reducing activity of nitrogenase. On the other hand, the M-cluster was still ~6-fold less active than the V-cluster in the same protein scaffold, and it retained its inability to form detectable amounts of methane from CO reduction, illustrating a fine-tuning effect of the cofactor properties on this nitrogenase-catalyzed reaction. Together, these results provided important insights into the two major determinants for the enzymatic activity of CO reduction while establishing a useful framework for further elucidation of the essential catalytic elements for the CO reactivity of nitrogenase. IMPORTANCE This is the first report on the in vivo generation and in vitro characterization of an M-cluster-containing V-nitrogenase hybrid. The "normalization" of the protein scaffold to that of the V-nitrogenase permits a direct comparison between the cofactor species of the Mo- and V-nitrogenases (M- and V-clusters) in CO reduction, whereas the discrepancy between the protein scaffolds of the Mo- and V-nitrogenases (MoFe and VFe

Clustering on Membranes

DEFF Research Database (Denmark)

Johannes, Ludger; Pezeshkian, Weria; Ipsen, John H

2018-01-01

Clustering of extracellular ligands and proteins on the plasma membrane is required to perform specific cellular functions, such as signaling and endocytosis. Attractive forces that originate in perturbations of the membrane's physical properties contribute to this clustering, in addition to direct...... protein-protein interactions. However, these membrane-mediated forces have not all been equally considered, despite their importance. In this review, we describe how line tension, lipid depletion, and membrane curvature contribute to membrane-mediated clustering. Additional attractive forces that arise...... from protein-induced perturbation of a membrane's fluctuations are also described. This review aims to provide a survey of the current understanding of membrane-mediated clustering and how this supports precise biological functions....

Supported silver clusters as nanoplasmonic transducers for protein sensing

DEFF Research Database (Denmark)

Fojan, Peter; Hanif, Muhammad; Bartling, Stephen

2015-01-01

Transducers for optical sensing of proteins are prepared using cluster beam deposition on quartz substrates. Surface plasmon resonance phenomenon of the supported silver clusters is used for the detection. It is shown that surface immobilisation procedure providing adhesion of the silver clusters...... stages and protein immobilisation scheme the sensing of protein of interest can be assured using a relatively simple optical spectroscopy method....... an enhancement of the plasmon absorption band used for the detection. Atomic force microscopy study allows to suggest that immobilisation of antibodies on silver clusters has been achieved, thus giving a possibility to incubate and detect an antigen of interest. Hence, by applying the developed preparation...

Evaluation of clustering algorithms for protein-protein interaction networks

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van Helden Jacques

2006-11-01

Full Text Available Abstract Background Protein interactions are crucial components of all cellular processes. Recently, high-throughput methods have been developed to obtain a global description of the interactome (the whole network of protein interactions for a given organism. In 2002, the yeast interactome was estimated to contain up to 80,000 potential interactions. This estimate is based on the integration of data sets obtained by various methods (mass spectrometry, two-hybrid methods, genetic studies. High-throughput methods are known, however, to yield a non-negligible rate of false positives, and to miss a fraction of existing interactions. The interactome can be represented as a graph where nodes correspond with proteins and edges with pairwise interactions. In recent years clustering methods have been developed and applied in order to extract relevant modules from such graphs. These algorithms require the specification of parameters that may drastically affect the results. In this paper we present a comparative assessment of four algorithms: Markov Clustering (MCL, Restricted Neighborhood Search Clustering (RNSC, Super Paramagnetic Clustering (SPC, and Molecular Complex Detection (MCODE. Results A test graph was built on the basis of 220 complexes annotated in the MIPS database. To evaluate the robustness to false positives and false negatives, we derived 41 altered graphs by randomly removing edges from or adding edges to the test graph in various proportions. Each clustering algorithm was applied to these graphs with various parameter settings, and the clusters were compared with the annotated complexes. We analyzed the sensitivity of the algorithms to the parameters and determined their optimal parameter values. We also evaluated their robustness to alterations of the test graph. We then applied the four algorithms to six graphs obtained from high-throughput experiments and compared the resulting clusters with the annotated complexes. Conclusion This

Evidence for the additions of clustered interacting nodes during the evolution of protein interaction networks from network motifs

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Guo Hao

2011-05-01

Full Text Available Abstract Background High-throughput screens have revealed large-scale protein interaction networks defining most cellular functions. How the proteins were added to the protein interaction network during its growth is a basic and important issue. Network motifs represent the simplest building blocks of cellular machines and are of biological significance. Results Here we study the evolution of protein interaction networks from the perspective of network motifs. We find that in current protein interaction networks, proteins of the same age class tend to form motifs and such co-origins of motif constituents are affected by their topologies and biological functions. Further, we find that the proteins within motifs whose constituents are of the same age class tend to be densely interconnected, co-evolve and share the same biological functions, and these motifs tend to be within protein complexes. Conclusions Our findings provide novel evidence for the hypothesis of the additions of clustered interacting nodes and point out network motifs, especially the motifs with the dense topology and specific function may play important roles during this process. Our results suggest functional constraints may be the underlying driving force for such additions of clustered interacting nodes.

Arabidopsis thaliana mTERF proteins: evolution and functional classification

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Tatjana eKleine

2012-10-01

Full Text Available Organellar gene expression (OGE is crucial for plant development, photosynthesis and respiration, but our understanding of the mechanisms that control it is still relatively poor. Thus, OGE requires various nucleus-encoded proteins that promote transcription, splicing, trimming and editing of organellar RNAs, and regulate translation. In metazoans, proteins of the mitochondrial Transcription tERmination Factor (mTERF family interact with the mitochondrial chromosome and regulate transcriptional initiation and termination. Sequencing of the Arabidopsis thaliana genome led to the identification of a diversified MTERF gene family but, in contrast to mammalian mTERFs, knowledge about the function of these proteins in photosynthetic organisms is scarce. In this hypothesis article, I show that tandem duplications and one block duplication contributed to the large number of MTERF genes in A. thaliana, and propose that the expansion of the family is related to the evolution of land plants. The MTERF genes - especially the duplicated genes - display a number of distinct mRNA accumulation patterns, suggesting functional diversification of mTERF proteins to increase adaptability to environmental changes. Indeed, hypothetical functions for the different mTERF proteins can be predicted using co-expression analysis and gene ontology annotations. On this basis, mTERF proteins can be sorted into five groups. Members of the chloroplast and chloroplast-associated clusters are principally involved in chloroplast gene expression, embryogenesis and protein catabolism, while representatives of the mitochondrial cluster seem to participate in DNA and RNA metabolism in that organelle. Moreover, members of the mitochondrion-associated cluster and the low expression group may act in the nucleus and/or the cytosol. As proteins involved in OGE and presumably nuclear gene expression, mTERFs are ideal candidates for the coordination of the expression of organelle and nuclear

Analysis of substructural variation in families of enzymatic proteins with applications to protein function prediction

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Fofanov Viacheslav Y

2010-05-01

Full Text Available Abstract Background Structural variations caused by a wide range of physico-chemical and biological sources directly influence the function of a protein. For enzymatic proteins, the structure and chemistry of the catalytic binding site residues can be loosely defined as a substructure of the protein. Comparative analysis of drug-receptor substructures across and within species has been used for lead evaluation. Substructure-level similarity between the binding sites of functionally similar proteins has also been used to identify instances of convergent evolution among proteins. In functionally homologous protein families, shared chemistry and geometry at catalytic sites provide a common, local point of comparison among proteins that may differ significantly at the sequence, fold, or domain topology levels. Results This paper describes two key results that can be used separately or in combination for protein function analysis. The Family-wise Analysis of SubStructural Templates (FASST method uses all-against-all substructure comparison to determine Substructural Clusters (SCs. SCs characterize the binding site substructural variation within a protein family. In this paper we focus on examples of automatically determined SCs that can be linked to phylogenetic distance between family members, segregation by conformation, and organization by homology among convergent protein lineages. The Motif Ensemble Statistical Hypothesis (MESH framework constructs a representative motif for each protein cluster among the SCs determined by FASST to build motif ensembles that are shown through a series of function prediction experiments to improve the function prediction power of existing motifs. Conclusions FASST contributes a critical feedback and assessment step to existing binding site substructure identification methods and can be used for the thorough investigation of structure-function relationships. The application of MESH allows for an automated

The hybrid-cluster protein ('prismane protein') from Escherichia coli. Characterization of the hybrid-cluster protein, redox properties of the [2Fe-2S] and [4Fe-2S-2O] clusters and identification of an associated NADH oxidoreductase containing FAD and[2Fe-2S

NARCIS (Netherlands)

Berg, van den W.A.M.; Hagen, W.R.; Dongen, van W.M.A.M.

2000-01-01

Hybrid-cluster proteins ('prismane proteins') have previously been isolated and characterized from strictly anaerobic sulfate-reducing bacteria. These proteins contain two types of Fe/S clusters unique in biological systems: a [4Fe-4S] cubane cluster with spin-admixed S = 3/2 ground-state

The correlation functions for the clustering of galaxies and Abell clusters

International Nuclear Information System (INIS)

Jones, B.J.T.; Jones, J.E.; Copenhagen Univ.

1985-01-01

The difference in amplitudes between the galaxy-galaxy correlation function and the correlation function between Abell clusters is a consequence of two facts. Firstly, most Abell clusters with z<0.08 lie in a relatively small volume of the sampled space, and secondly, the fraction of galaxies lying in Abell clusters differs considerably inside and outside of this volume. (The Abell clusters are confined to a smaller volume of space than are the galaxies.) We discuss the implications of this interpretation of the clustering correlation functions and present a simple model showing how such a situation may arise quite naturally in standard theories for galaxy formation. (orig.)

Comprehensive cluster analysis with Transitivity Clustering.

Science.gov (United States)

Wittkop, Tobias; Emig, Dorothea; Truss, Anke; Albrecht, Mario; Böcker, Sebastian; Baumbach, Jan

2011-03-01

Transitivity Clustering is a method for the partitioning of biological data into groups of similar objects, such as genes, for instance. It provides integrated access to various functions addressing each step of a typical cluster analysis. To facilitate this, Transitivity Clustering is accessible online and offers three user-friendly interfaces: a powerful stand-alone version, a web interface, and a collection of Cytoscape plug-ins. In this paper, we describe three major workflows: (i) protein (super)family detection with Cytoscape, (ii) protein homology detection with incomplete gold standards and (iii) clustering of gene expression data. This protocol guides the user through the most important features of Transitivity Clustering and takes ∼1 h to complete.

Detection of secondary structure elements in proteins by hydrophobic cluster analysis.

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Woodcock, S; Mornon, J P; Henrissat, B

1992-10-01

Hydrophobic cluster analysis (HCA) is a protein sequence comparison method based on alpha-helical representations of the sequences where the size, shape and orientation of the clusters of hydrophobic residues are primarily compared. The effectiveness of HCA has been suggested to originate from its potential ability to focus on the residues forming the hydrophobic core of globular proteins. We have addressed the robustness of the bidimensional representation used for HCA in its ability to detect the regular secondary structure elements of proteins. Various parameters have been studied such as those governing cluster size and limits, the hydrophobic residues constituting the clusters as well as the potential shift of the cluster positions with respect to the position of the regular secondary structure elements. The following results have been found to support the alpha-helical bidimensional representation used in HCA: (i) there is a positive correlation (clearly above background noise) between the hydrophobic clusters and the regular secondary structure elements in proteins; (ii) the hydrophobic clusters are centred on the regular secondary structure elements; (iii) the pitch of the helical representation which gives the best correspondence is that of an alpha-helix. The correspondence between hydrophobic clusters and regular secondary structure elements suggests a way to implement variable gap penalties during the automatic alignment of protein sequences.

A Proteomic Approach to Investigating Gene Cluster Expression and Secondary Metabolite Functionality in Aspergillus fumigatus

Science.gov (United States)

Owens, Rebecca A.; Hammel, Stephen; Sheridan, Kevin J.; Jones, Gary W.; Doyle, Sean

2014-01-01

A combined proteomics and metabolomics approach was utilised to advance the identification and characterisation of secondary metabolites in Aspergillus fumigatus. Here, implementation of a shotgun proteomic strategy led to the identification of non-redundant mycelial proteins (n = 414) from A. fumigatus including proteins typically under-represented in 2-D proteome maps: proteins with multiple transmembrane regions, hydrophobic proteins and proteins with extremes of molecular mass and pI. Indirect identification of secondary metabolite cluster expression was also achieved, with proteins (n = 18) from LaeA-regulated clusters detected, including GliT encoded within the gliotoxin biosynthetic cluster. Biochemical analysis then revealed that gliotoxin significantly attenuates H2O2-induced oxidative stress in A. fumigatus (p>0.0001), confirming observations from proteomics data. A complementary 2-D/LC-MS/MS approach further elucidated significantly increased abundance (pproteome and experimental strategies, plus mechanistic data pertaining to gliotoxin functionality in the organism. PMID:25198175

Network based approaches reveal clustering in protein point patterns

Science.gov (United States)

Parker, Joshua; Barr, Valarie; Aldridge, Joshua; Samelson, Lawrence E.; Losert, Wolfgang

2014-03-01

Recent advances in super-resolution imaging have allowed for the sub-diffraction measurement of the spatial location of proteins on the surfaces of T-cells. The challenge is to connect these complex point patterns to the internal processes and interactions, both protein-protein and protein-membrane. We begin analyzing these patterns by forming a geometric network amongst the proteins and looking at network measures, such the degree distribution. This allows us to compare experimentally observed patterns to models. Specifically, we find that the experimental patterns differ from heterogeneous Poisson processes, highlighting an internal clustering structure. Further work will be to compare our results to simulated protein-protein interactions to determine clustering mechanisms.

Clustering evolving proteins into homologous families.

Science.gov (United States)

Chan, Cheong Xin; Mahbob, Maisarah; Ragan, Mark A

2013-04-08

Clustering sequences into groups of putative homologs (families) is a critical first step in many areas of comparative biology and bioinformatics. The performance of clustering approaches in delineating biologically meaningful families depends strongly on characteristics of the data, including content bias and degree of divergence. New, highly scalable methods have recently been introduced to cluster the very large datasets being generated by next-generation sequencing technologies. However, there has been little systematic investigation of how characteristics of the data impact the performance of these approaches. Using clusters from a manually curated dataset as reference, we examined the performance of a widely used graph-based Markov clustering algorithm (MCL) and a greedy heuristic approach (UCLUST) in delineating protein families coded by three sets of bacterial genomes of different G+C content. Both MCL and UCLUST generated clusters that are comparable to the reference sets at specific parameter settings, although UCLUST tends to under-cluster compositionally biased sequences (G+C content 33% and 66%). Using simulated data, we sought to assess the individual effects of sequence divergence, rate heterogeneity, and underlying G+C content. Performance decreased with increasing sequence divergence, decreasing among-site rate variation, and increasing G+C bias. Two MCL-based methods recovered the simulated families more accurately than did UCLUST. MCL using local alignment distances is more robust across the investigated range of sequence features than are greedy heuristics using distances based on global alignment. Our results demonstrate that sequence divergence, rate heterogeneity and content bias can individually and in combination affect the accuracy with which MCL and UCLUST can recover homologous protein families. For application to data that are more divergent, and exhibit higher among-site rate variation and/or content bias, MCL may often be the better

Effect of mitochondrial complex I inhibition on Fe-S cluster protein activity

Energy Technology Data Exchange (ETDEWEB)

Mena, Natalia P. [Department of Biology, Faculty of Sciences, Universidad de Chile, Las Palmeras 3425, Santiago (Chile); Millennium Institute of Cell Dynamics and Biotechnology, Santiago (Chile); Bulteau, Anne Laure [UPMC Univ Paris 06, UMRS 975 - UMR 7725, Centre de Recherche en Neurosciences, ICM, Therapeutique Experimentale de la Neurodegenerescence, Hopital de la Salpetriere, F-75005 Paris (France); Inserm, U 975, Centre de Recherche en Neurosciences, ICM, Therapeutique Experimentale de la Neurodegenerescence, Hopital de la Salpetriere, F-75005 Paris (France); CNRS, UMR 7225, Centre de Recherche en Neurosciences, ICM, Therapeutique Experimentale de la Neurodegenerescence, Hopital de la Salpetriere, F-75005 Paris (France); ICM, Therapeutique Experimentale de la Neurodegenerescence, Hopital de la Salpetriere, Paris 75013 (France); Salazar, Julio [Millennium Institute of Cell Dynamics and Biotechnology, Santiago (Chile); Hirsch, Etienne C. [UPMC Univ Paris 06, UMRS 975 - UMR 7725, Centre de Recherche en Neurosciences, ICM, Therapeutique Experimentale de la Neurodegenerescence, Hopital de la Salpetriere, F-75005 Paris (France); Inserm, U 975, Centre de Recherche en Neurosciences, ICM, Therapeutique Experimentale de la Neurodegenerescence, Hopital de la Salpetriere, F-75005 Paris (France); CNRS, UMR 7225, Centre de Recherche en Neurosciences, ICM, Therapeutique Experimentale de la Neurodegenerescence, Hopital de la Salpetriere, F-75005 Paris (France); ICM, Therapeutique Experimentale de la Neurodegenerescence, Hopital de la Salpetriere, Paris 75013 (France); Nunez, Marco T., E-mail: mnunez@uchile.cl [Department of Biology, Faculty of Sciences, Universidad de Chile, Las Palmeras 3425, Santiago (Chile); Millennium Institute of Cell Dynamics and Biotechnology, Santiago (Chile)

2011-06-03

Highlights: {yields} Mitochondrial complex I inhibition resulted in decreased activity of Fe-S containing enzymes mitochondrial aconitase and cytoplasmic aconitase and xanthine oxidase. {yields} Complex I inhibition resulted in the loss of Fe-S clusters in cytoplasmic aconitase and of glutamine phosphoribosyl pyrophosphate amidotransferase. {yields} Consistent with loss of cytoplasmic aconitase activity, an increase in iron regulatory protein 1 activity was found. {yields} Complex I inhibition resulted in an increase in the labile cytoplasmic iron pool. -- Abstract: Iron-sulfur (Fe-S) clusters are small inorganic cofactors formed by tetrahedral coordination of iron atoms with sulfur groups. Present in numerous proteins, these clusters are involved in key biological processes such as electron transfer, metabolic and regulatory processes, DNA synthesis and repair and protein structure stabilization. Fe-S clusters are synthesized mainly in the mitochondrion, where they are directly incorporated into mitochondrial Fe-S cluster-containing proteins or exported for cytoplasmic and nuclear cluster-protein assembly. In this study, we tested the hypothesis that inhibition of mitochondrial complex I by rotenone decreases Fe-S cluster synthesis and cluster content and activity of Fe-S cluster-containing enzymes. Inhibition of complex I resulted in decreased activity of three Fe-S cluster-containing enzymes: mitochondrial and cytosolic aconitases and xanthine oxidase. In addition, the Fe-S cluster content of glutamine phosphoribosyl pyrophosphate amidotransferase and mitochondrial aconitase was dramatically decreased. The reduction in cytosolic aconitase activity was associated with an increase in iron regulatory protein (IRP) mRNA binding activity and with an increase in the cytoplasmic labile iron pool. Since IRP activity post-transcriptionally regulates the expression of iron import proteins, Fe-S cluster inhibition may result in a false iron deficiency signal. Given that

Effect of mitochondrial complex I inhibition on Fe-S cluster protein activity

International Nuclear Information System (INIS)

Mena, Natalia P.; Bulteau, Anne Laure; Salazar, Julio; Hirsch, Etienne C.; Nunez, Marco T.

2011-01-01

Highlights: → Mitochondrial complex I inhibition resulted in decreased activity of Fe-S containing enzymes mitochondrial aconitase and cytoplasmic aconitase and xanthine oxidase. → Complex I inhibition resulted in the loss of Fe-S clusters in cytoplasmic aconitase and of glutamine phosphoribosyl pyrophosphate amidotransferase. → Consistent with loss of cytoplasmic aconitase activity, an increase in iron regulatory protein 1 activity was found. → Complex I inhibition resulted in an increase in the labile cytoplasmic iron pool. -- Abstract: Iron-sulfur (Fe-S) clusters are small inorganic cofactors formed by tetrahedral coordination of iron atoms with sulfur groups. Present in numerous proteins, these clusters are involved in key biological processes such as electron transfer, metabolic and regulatory processes, DNA synthesis and repair and protein structure stabilization. Fe-S clusters are synthesized mainly in the mitochondrion, where they are directly incorporated into mitochondrial Fe-S cluster-containing proteins or exported for cytoplasmic and nuclear cluster-protein assembly. In this study, we tested the hypothesis that inhibition of mitochondrial complex I by rotenone decreases Fe-S cluster synthesis and cluster content and activity of Fe-S cluster-containing enzymes. Inhibition of complex I resulted in decreased activity of three Fe-S cluster-containing enzymes: mitochondrial and cytosolic aconitases and xanthine oxidase. In addition, the Fe-S cluster content of glutamine phosphoribosyl pyrophosphate amidotransferase and mitochondrial aconitase was dramatically decreased. The reduction in cytosolic aconitase activity was associated with an increase in iron regulatory protein (IRP) mRNA binding activity and with an increase in the cytoplasmic labile iron pool. Since IRP activity post-transcriptionally regulates the expression of iron import proteins, Fe-S cluster inhibition may result in a false iron deficiency signal. Given that inhibition of complex

Clustering aspects in nuclear structure functions

International Nuclear Information System (INIS)

Hirai, M.; Saito, K.; Watanabe, T.; Kumano, S.

2011-01-01

For understanding an anomalous nuclear effect experimentally observed for the beryllium-9 nucleus at the Thomas Jefferson National Accelerator Facility, clustering aspects are studied in structure functions of deep inelastic lepton-nucleus scattering by using momentum distributions calculated in antisymmetrized (or fermionic) molecular dynamics (AMD) and also in a simple shell model for comparison. According to AMD, the 9 Be nucleus consists of two α-like clusters with a surrounding neutron. The clustering produces high-momentum components in nuclear wave functions, which affects nuclear modifications of the structure functions. We investigated whether clustering features could appear in the structure function F 2 of 9 Be along with studies for other light nuclei. We found that nuclear modifications of F 2 are similar in both AMD and shell models within our simple convolution description although there are slight differences in 9 Be. It indicates that the anomalous 9 Be result should be explained by a different mechanism from the nuclear binding and Fermi motion. If nuclear-modification slopes d(F 2 A /F 2 D )/dx are shown by the maximum local densities, the 9 Be anomaly can be explained by the AMD picture, namely by the clustering structure, whereas it certainly cannot be described in the simple shell model. This fact suggests that the large nuclear modification in 9 Be should be explained by large densities in the clusters. For example, internal nucleon structure could be modified in the high-density clusters. The clustering aspect of nuclear structure functions is an unexplored topic which is interesting for future investigations.

Zinc fingers, zinc clusters, and zinc twists in DNA-binding protein domains

International Nuclear Information System (INIS)

Vallee, B.L.; Auld, D.S.; Coleman, J.E.

1991-01-01

The authors recognize three distinct motifs of DNA-binding zinc proteins: (i) zinc fingers, (ii) zinc clusters, and (iii) zinc twists. Until very recently, x-ray crystallographic or NMR three-dimensional structure analyses of DNA-binding zinc proteins have not been available to serve as standards of reference for the zinc binding sites of these families of proteins. Those of the DNA-binding domains of the fungal transcription factor GAL4 and the rat glucocorticoid receptor are the first to have been determined. Both proteins contain two zinc binding sites, and in both, cysteine residues are the sole zinc ligands. In GAL4, two zinc atoms are bound to six cysteine residues which form a zinc cluster akin to that of metallothionein; the distance between the two zinc atoms of GAL4 is ∼3.5 angstrom. In the glucocorticoid receptor, each zinc atom is bound to four cysteine residues; the interatomic zinc-zinc distance is ∼13 angstrom, and in this instance, a zinc twist is represented by a helical DNA recognition site located between the two zinc atoms. Zinc clusters and zinc twists are here recognized as two distinctive motifs in DNA-binding proteins containing multiple zinc atoms. For native zinc fingers, structural data do not exist as yet; consequently, the interatomic distances between zinc atoms are not known. As further structural data become available, the structural and functional significance of these different motifs in their binding to DNA and other proteins participating in the transmission of the genetic message will become apparent

K-nearest uphill clustering in the protein structure space

KAUST Repository

Cui, Xuefeng; Gao, Xin

2016-01-01

The protein structure classification problem, which is to assign a protein structure to a cluster of similar proteins, is one of the most fundamental problems in the construction and application of the protein structure space. Early manually curated

Gene identification and protein classification in microbial metagenomic sequence data via incremental clustering

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Li Weizhong

2008-04-01

Full Text Available Abstract Background The identification and study of proteins from metagenomic datasets can shed light on the roles and interactions of the source organisms in their communities. However, metagenomic datasets are characterized by the presence of organisms with varying GC composition, codon usage biases etc., and consequently gene identification is challenging. The vast amount of sequence data also requires faster protein family classification tools. Results We present a computational improvement to a sequence clustering approach that we developed previously to identify and classify protein coding genes in large microbial metagenomic datasets. The clustering approach can be used to identify protein coding genes in prokaryotes, viruses, and intron-less eukaryotes. The computational improvement is based on an incremental clustering method that does not require the expensive all-against-all compute that was required by the original approach, while still preserving the remote homology detection capabilities. We present evaluations of the clustering approach in protein-coding gene identification and classification, and also present the results of updating the protein clusters from our previous work with recent genomic and metagenomic sequences. The clustering results are available via CAMERA, (http://camera.calit2.net. Conclusion The clustering paradigm is shown to be a very useful tool in the analysis of microbial metagenomic data. The incremental clustering method is shown to be much faster than the original approach in identifying genes, grouping sequences into existing protein families, and also identifying novel families that have multiple members in a metagenomic dataset. These clusters provide a basis for further studies of protein families.

Site-directed mutagenesis of Azotobacter vinelandii ferredoxin I: [Fe-S] cluster-driven protein rearrangement

International Nuclear Information System (INIS)

Martin, A.E.; Burgess, B.K.; Stout, C.D.; Cash, V.L.; Dean, D.R.; Jensen, G.M.; Stephens, P.J.

1990-01-01

Azotobacter vinelandii ferredoxin I is a small protein that contains one [4Fe-4S] cluster and one [3Fe-4S] cluster. Recently the x-ray crystal structure has been redetermined and the fdxA gene, which encodes the protein, has been cloned and sequenced. Here the authors report the site-directed mutation of Cys-20, which is a ligand of the [4Fe-4S] cluster in the native protein, to alanine and the characterization of the protein product by x-ray crystallographic and spectroscopic methods. The data show that the mutant protein again contains one [4Fe-4S] cluster and one [3Fe-4S] cluster. The new [4Fe-4S] cluster obtains its fourth ligand from Cys-24, a free cysteine in the native structure. The formation of this [4Fe-4S] cluster drives rearrangement of the protein structure

Lack of Dependence of the Sizes of the Mesoscopic Protein Clusters on Electrostatics.

Science.gov (United States)

Vorontsova, Maria A; Chan, Ho Yin; Lubchenko, Vassiliy; Vekilov, Peter G

2015-11-03

Protein-rich clusters of steady submicron size and narrow size distribution exist in protein solutions in apparent violation of the classical laws of phase equilibrium. Even though they contain a minor fraction of the total protein, evidence suggests that they may serve as essential precursors for the nucleation of ordered solids such as crystals, sickle-cell hemoglobin polymers, and amyloid fibrils. The cluster formation mechanism remains elusive. We use the highly basic protein lysozyme at nearly neutral and lower pH as a model and explore the response of the cluster population to the electrostatic forces, which govern numerous biophysical phenomena, including crystallization and fibrillization. We tune the strength of intermolecular electrostatic forces by varying the solution ionic strength I and pH and find that despite the weaker repulsion at higher I and pH, the cluster size remains constant. Cluster responses to the presence of urea and ethanol demonstrate that cluster formation is controlled by hydrophobic interactions between the peptide backbones, exposed to the solvent after partial protein unfolding that may lead to transient protein oligomers. These findings reveal that the mechanism of the mesoscopic clusters is fundamentally different from those underlying the two main classes of ordered protein solid phases, crystals and amyloid fibrils, and partial unfolding of the protein chain may play a significant role. Copyright © 2015 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Versatile microsphere attachment of GFP-labeled motors and other tagged proteins with preserved functionality

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Michael Bugiel

2015-11-01

Full Text Available Microspheres are often used as handles for protein purification or force spectroscopy. For example, optical tweezers apply forces on trapped particles to which motor proteins are attached. However, even though many attachment strategies exist, procedures are often limited to a particular biomolecule and prone to non-specific protein or surface attachment. Such interactions may lead to loss of protein functionality or microsphere clustering. Here, we describe a versatile coupling procedure for GFP-tagged proteins via a polyethylene glycol linker preserving the functionality of the coupled proteins. The procedure combines well-established protocols, is highly reproducible, reliable, and can be used for a large variety of proteins. The coupling is efficient and can be tuned to the desired microsphere-to-protein ratio. Moreover, microspheres hardly cluster or adhere to surfaces. Furthermore, the procedure can be adapted to different tags providing flexibility and a promising attachment strategy for any tagged protein.

Phenotype Clustering of Breast Epithelial Cells in Confocal Imagesbased on Nuclear Protein Distribution Analysis

Energy Technology Data Exchange (ETDEWEB)

Long, Fuhui; Peng, Hanchuan; Sudar, Damir; Levievre, Sophie A.; Knowles, David W.

2006-09-05

Background: The distribution of the chromatin-associatedproteins plays a key role in directing nuclear function. Previously, wedeveloped an image-based method to quantify the nuclear distributions ofproteins and showed that these distributions depended on the phenotype ofhuman mammary epithelial cells. Here we describe a method that creates ahierarchical tree of the given cell phenotypes and calculates thestatistical significance between them, based on the clustering analysisof nuclear protein distributions. Results: Nuclear distributions ofnuclear mitotic apparatus protein were previously obtained fornon-neoplastic S1 and malignant T4-2 human mammary epithelial cellscultured for up to 12 days. Cell phenotype was defined as S1 or T4-2 andthe number of days in cultured. A probabilistic ensemble approach wasused to define a set of consensus clusters from the results of multipletraditional cluster analysis techniques applied to the nucleardistribution data. Cluster histograms were constructed to show how cellsin any one phenotype were distributed across the consensus clusters.Grouping various phenotypes allowed us to build phenotype trees andcalculate the statistical difference between each group. The resultsshowed that non-neoplastic S1 cells could be distinguished from malignantT4-2 cells with 94.19 percent accuracy; that proliferating S1 cells couldbe distinguished from differentiated S1 cells with 92.86 percentaccuracy; and showed no significant difference between the variousphenotypes of T4-2 cells corresponding to increasing tumor sizes.Conclusion: This work presents a cluster analysis method that canidentify significant cell phenotypes, based on the nuclear distributionof specific proteins, with high accuracy.

Insulator function and topological domain border strength scale with architectural protein occupancy

Science.gov (United States)

2014-01-01

Background Chromosome conformation capture studies suggest that eukaryotic genomes are organized into structures called topologically associating domains. The borders of these domains are highly enriched for architectural proteins with characterized roles in insulator function. However, a majority of architectural protein binding sites localize within topological domains, suggesting sites associated with domain borders represent a functionally different subclass of these regulatory elements. How topologically associating domains are established and what differentiates border-associated from non-border architectural protein binding sites remain unanswered questions. Results By mapping the genome-wide target sites for several Drosophila architectural proteins, including previously uncharacterized profiles for TFIIIC and SMC-containing condensin complexes, we uncover an extensive pattern of colocalization in which architectural proteins establish dense clusters at the borders of topological domains. Reporter-based enhancer-blocking insulator activity as well as endogenous domain border strength scale with the occupancy level of architectural protein binding sites, suggesting co-binding by architectural proteins underlies the functional potential of these loci. Analyses in mouse and human stem cells suggest that clustering of architectural proteins is a general feature of genome organization, and conserved architectural protein binding sites may underlie the tissue-invariant nature of topologically associating domains observed in mammals. Conclusions We identify a spectrum of architectural protein occupancy that scales with the topological structure of chromosomes and the regulatory potential of these elements. Whereas high occupancy architectural protein binding sites associate with robust partitioning of topologically associating domains and robust insulator function, low occupancy sites appear reserved for gene-specific regulation within topological domains. PMID

Analysis and comparison of very large metagenomes with fast clustering and functional annotation

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Li Weizhong

2009-10-01

Full Text Available Abstract Background The remarkable advance of metagenomics presents significant new challenges in data analysis. Metagenomic datasets (metagenomes are large collections of sequencing reads from anonymous species within particular environments. Computational analyses for very large metagenomes are extremely time-consuming, and there are often many novel sequences in these metagenomes that are not fully utilized. The number of available metagenomes is rapidly increasing, so fast and efficient metagenome comparison methods are in great demand. Results The new metagenomic data analysis method Rapid Analysis of Multiple Metagenomes with a Clustering and Annotation Pipeline (RAMMCAP was developed using an ultra-fast sequence clustering algorithm, fast protein family annotation tools, and a novel statistical metagenome comparison method that employs a unique graphic interface. RAMMCAP processes extremely large datasets with only moderate computational effort. It identifies raw read clusters and protein clusters that may include novel gene families, and compares metagenomes using clusters or functional annotations calculated by RAMMCAP. In this study, RAMMCAP was applied to the two largest available metagenomic collections, the "Global Ocean Sampling" and the "Metagenomic Profiling of Nine Biomes". Conclusion RAMMCAP is a very fast method that can cluster and annotate one million metagenomic reads in only hundreds of CPU hours. It is available from http://tools.camera.calit2.net/camera/rammcap/.

clusterMaker: a multi-algorithm clustering plugin for Cytoscape

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Morris John H

2011-11-01

Full Text Available Abstract Background In the post-genomic era, the rapid increase in high-throughput data calls for computational tools capable of integrating data of diverse types and facilitating recognition of biologically meaningful patterns within them. For example, protein-protein interaction data sets have been clustered to identify stable complexes, but scientists lack easily accessible tools to facilitate combined analyses of multiple data sets from different types of experiments. Here we present clusterMaker, a Cytoscape plugin that implements several clustering algorithms and provides network, dendrogram, and heat map views of the results. The Cytoscape network is linked to all of the other views, so that a selection in one is immediately reflected in the others. clusterMaker is the first Cytoscape plugin to implement such a wide variety of clustering algorithms and visualizations, including the only implementations of hierarchical clustering, dendrogram plus heat map visualization (tree view, k-means, k-medoid, SCPS, AutoSOME, and native (Java MCL. Results Results are presented in the form of three scenarios of use: analysis of protein expression data using a recently published mouse interactome and a mouse microarray data set of nearly one hundred diverse cell/tissue types; the identification of protein complexes in the yeast Saccharomyces cerevisiae; and the cluster analysis of the vicinal oxygen chelate (VOC enzyme superfamily. For scenario one, we explore functionally enriched mouse interactomes specific to particular cellular phenotypes and apply fuzzy clustering. For scenario two, we explore the prefoldin complex in detail using both physical and genetic interaction clusters. For scenario three, we explore the possible annotation of a protein as a methylmalonyl-CoA epimerase within the VOC superfamily. Cytoscape session files for all three scenarios are provided in the Additional Files section. Conclusions The Cytoscape plugin cluster

A point mutation in the [2Fe–2S] cluster binding region of the NAF-1 protein (H114C) dramatically hinders the cluster donor properties

Energy Technology Data Exchange (ETDEWEB)

Tamir, Sagi; Eisenberg-Domovich, Yael [The Hebrew University of Jerusalem, Edmond J. Safra Campus at Givat Ram, Jerusalem 91904 (Israel); Conlan, Andrea R.; Stofleth, Jason T.; Lipper, Colin H.; Paddock, Mark L. [University of California at San Diego, La Jolla, CA 92093 (United States); Mittler, Ron [University of North Texas, Denton, TX 76203 (United States); Jennings, Patricia A. [University of California at San Diego, La Jolla, CA 92093 (United States); Livnah, Oded, E-mail: oded.livnah@huji.ac.il; Nechushtai, Rachel, E-mail: oded.livnah@huji.ac.il [The Hebrew University of Jerusalem, Edmond J. Safra Campus at Givat Ram, Jerusalem 91904 (Israel)

2014-06-01

NAF-1 has been shown to be related with human health and disease, is upregulated in epithelial breast cancer and suppression of its expression significantly suppresses tumor growth. It is shown that replacement of the single His ligand with Cys resulted in dramatic changes to the properties of its 2Fe-2S clusters without any global crystal structural changes. NAF-1 is an important [2Fe–2S] NEET protein associated with human health and disease. A mis-splicing mutation in NAF-1 results in Wolfram Syndrome type 2, a lethal childhood disease. Upregulation of NAF-1 is found in epithelial breast cancer cells, and suppression of NAF-1 expression by knockdown significantly suppresses tumor growth. Key to NAF-1 function is the NEET fold with its [2Fe–2S] cluster. In this work, the high-resolution structure of native NAF-1 was determined to 1.65 Å resolution (R factor = 13.5%) together with that of a mutant in which the single His ligand of its [2Fe–2S] cluster, His114, was replaced by Cys. The NAF-1 H114C mutant structure was determined to 1.58 Å resolution (R factor = 16.0%). All structural differences were localized to the cluster binding site. Compared with native NAF-1, the [2Fe–2S] clusters of the H114C mutant were found to (i) be 25-fold more stable, (ii) have a redox potential that is 300 mV more negative and (iii) have their cluster donation/transfer function abolished. Because no global structural differences were found between the mutant and the native (wild-type) NAF-1 proteins, yet significant functional differences exist between them, the NAF-1 H114C mutant is an excellent tool to decipher the underlying biological importance of the [2Fe–2S] cluster of NAF-1 in vivo.

A point mutation in the [2Fe–2S] cluster binding region of the NAF-1 protein (H114C) dramatically hinders the cluster donor properties

International Nuclear Information System (INIS)

Tamir, Sagi; Eisenberg-Domovich, Yael; Conlan, Andrea R.; Stofleth, Jason T.; Lipper, Colin H.; Paddock, Mark L.; Mittler, Ron; Jennings, Patricia A.; Livnah, Oded; Nechushtai, Rachel

2014-01-01

NAF-1 has been shown to be related with human health and disease, is upregulated in epithelial breast cancer and suppression of its expression significantly suppresses tumor growth. It is shown that replacement of the single His ligand with Cys resulted in dramatic changes to the properties of its 2Fe-2S clusters without any global crystal structural changes. NAF-1 is an important [2Fe–2S] NEET protein associated with human health and disease. A mis-splicing mutation in NAF-1 results in Wolfram Syndrome type 2, a lethal childhood disease. Upregulation of NAF-1 is found in epithelial breast cancer cells, and suppression of NAF-1 expression by knockdown significantly suppresses tumor growth. Key to NAF-1 function is the NEET fold with its [2Fe–2S] cluster. In this work, the high-resolution structure of native NAF-1 was determined to 1.65 Å resolution (R factor = 13.5%) together with that of a mutant in which the single His ligand of its [2Fe–2S] cluster, His114, was replaced by Cys. The NAF-1 H114C mutant structure was determined to 1.58 Å resolution (R factor = 16.0%). All structural differences were localized to the cluster binding site. Compared with native NAF-1, the [2Fe–2S] clusters of the H114C mutant were found to (i) be 25-fold more stable, (ii) have a redox potential that is 300 mV more negative and (iii) have their cluster donation/transfer function abolished. Because no global structural differences were found between the mutant and the native (wild-type) NAF-1 proteins, yet significant functional differences exist between them, the NAF-1 H114C mutant is an excellent tool to decipher the underlying biological importance of the [2Fe–2S] cluster of NAF-1 in vivo

Which clustering algorithm is better for predicting protein complexes?

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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

Comprehensive identification and clustering of CLV3/ESR-related (CLE) genes in plants finds groups with potentially shared function.

Science.gov (United States)

Goad, David M; Zhu, Chuanmei; Kellogg, Elizabeth A

2017-10-01

CLV3/ESR (CLE) proteins are important signaling peptides in plants. The short CLE peptide (12-13 amino acids) is cleaved from a larger pre-propeptide and functions as an extracellular ligand. The CLE family is large and has resisted attempts at classification because the CLE domain is too short for reliable phylogenetic analysis and the pre-propeptide is too variable. We used a model-based search for CLE domains from 57 plant genomes and used the entire pre-propeptide for comprehensive clustering analysis. In total, 1628 CLE genes were identified in land plants, with none recognizable from green algae. These CLEs form 12 groups within which CLE domains are largely conserved and pre-propeptides can be aligned. Most clusters contain sequences from monocots, eudicots and Amborella trichopoda, with sequences from Picea abies, Selaginella moellendorffii and Physcomitrella patens scattered in some clusters. We easily identified previously known clusters involved in vascular differentiation and nodulation. In addition, we found a number of discrete groups whose function remains poorly characterized. Available data indicate that CLE proteins within a cluster are likely to share function, whereas those from different clusters play at least partially different roles. Our analysis provides a foundation for future evolutionary and functional studies. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

A functional bikaverin biosynthesis gene cluster in rare strains of Botrytis cinerea is positively controlled by VELVET.

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Julia Schumacher

Full Text Available The gene cluster responsible for the biosynthesis of the red polyketidic pigment bikaverin has only been characterized in Fusarium ssp. so far. Recently, a highly homologous but incomplete and nonfunctional bikaverin cluster has been found in the genome of the unrelated phytopathogenic fungus Botrytis cinerea. In this study, we provided evidence that rare B. cinerea strains such as 1750 have a complete and functional cluster comprising the six genes orthologous to Fusarium fujikuroi ffbik1-ffbik6 and do produce bikaverin. Phylogenetic analysis confirmed that the whole cluster was acquired from Fusarium through a horizontal gene transfer (HGT. In the bikaverin-nonproducing strain B05.10, the genes encoding bikaverin biosynthesis enzymes are nonfunctional due to deleterious mutations (bcbik2-3 or missing (bcbik1 but interestingly, the genes encoding the regulatory proteins BcBIK4 and BcBIK5 do not harbor deleterious mutations which suggests that they may still be functional. Heterologous complementation of the F. fujikuroi Δffbik4 mutant confirmed that bcbik4 of strain B05.10 is indeed fully functional. Deletion of bcvel1 in the pink strain 1750 resulted in loss of bikaverin and overproduction of melanin indicating that the VELVET protein BcVEL1 regulates the biosynthesis of the two pigments in an opposite manner. Although strain 1750 itself expresses a truncated BcVEL1 protein (100 instead of 575 aa that is nonfunctional with regard to sclerotia formation, virulence and oxalic acid formation, it is sufficient to regulate pigment biosynthesis (bikaverin and melanin and fenhexamid HydR2 type of resistance. Finally, a genetic cross between strain 1750 and a bikaverin-nonproducing strain sensitive to fenhexamid revealed that the functional bikaverin cluster is genetically linked to the HydR2 locus.

Lactobacillus plantarum gene clusters encoding putative cell-surface protein complexes for carbohydrate utilization are conserved in specific gram-positive bacteria

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Muscariello Lidia

2006-05-01

Full Text Available Abstract Background Genomes of gram-positive bacteria encode many putative cell-surface proteins, of which the majority has no known function. From the rapidly increasing number of available genome sequences it has become apparent that many cell-surface proteins are conserved, and frequently encoded in gene clusters or operons, suggesting common functions, and interactions of multiple components. Results A novel gene cluster encoding exclusively cell-surface proteins was identified, which is conserved in a subgroup of gram-positive bacteria. Each gene cluster generally has one copy of four new gene families called cscA, cscB, cscC and cscD. Clusters encoding these cell-surface proteins were found only in complete genomes of Lactobacillus plantarum, Lactobacillus sakei, Enterococcus faecalis, Listeria innocua, Listeria monocytogenes, Lactococcus lactis ssp lactis and Bacillus cereus and in incomplete genomes of L. lactis ssp cremoris, Lactobacillus casei, Enterococcus faecium, Pediococcus pentosaceus, Lactobacillius brevis, Oenococcus oeni, Leuconostoc mesenteroides, and Bacillus thuringiensis. These genes are neither present in the genomes of streptococci, staphylococci and clostridia, nor in the Lactobacillus acidophilus group, suggesting a niche-specific distribution, possibly relating to association with plants. All encoded proteins have a signal peptide for secretion by the Sec-dependent pathway, while some have cell-surface anchors, novel WxL domains, and putative domains for sugar binding and degradation. Transcriptome analysis in L. plantarum shows that the cscA-D genes are co-expressed, supporting their operon organization. Many gene clusters are significantly up-regulated in a glucose-grown, ccpA-mutant derivative of L. plantarum, suggesting catabolite control. This is supported by the presence of predicted CRE-sites upstream or inside the up-regulated cscA-D gene clusters. Conclusion We propose that the CscA, CscB, CscC and Csc

Fast large-scale clustering of protein structures using Gauss integrals

DEFF Research Database (Denmark)

Harder, Tim; Borg, Mikael; Boomsma, Wouter

2011-01-01

trajectories. Results: We present Pleiades, a novel approach to clustering protein structures with a rigorous mathematical underpinning. The method approximates clustering based on the root mean square deviation by rst mapping structures to Gauss integral vectors – which were introduced by Røgen and co......-workers – and subsequently performing K-means clustering. Conclusions: Compared to current methods, Pleiades dramatically improves on the time needed to perform clustering, and can cluster a signicantly larger number of structures, while providing state-ofthe- art results. The number of low energy structures generated...

Growing functional modules from a seed protein via integration of protein interaction and gene expression data

Directory of Open Access Journals (Sweden)

Dimitrakopoulou Konstantina

2007-10-01

Full Text Available Abstract Background Nowadays modern biology aims at unravelling the strands of complex biological structures such as the protein-protein interaction (PPI networks. A key concept in the organization of PPI networks is the existence of dense subnetworks (functional modules in them. In recent approaches clustering algorithms were applied at these networks and the resulting subnetworks were evaluated by estimating the coverage of well-established protein complexes they contained. However, most of these algorithms elaborate on an unweighted graph structure which in turn fails to elevate those interactions that would contribute to the construction of biologically more valid and coherent functional modules. Results In the current study, we present a method that corroborates the integration of protein interaction and microarray data via the discovery of biologically valid functional modules. Initially the gene expression information is overlaid as weights onto the PPI network and the enriched PPI graph allows us to exploit its topological aspects, while simultaneously highlights enhanced functional association in specific pairs of proteins. Then we present an algorithm that unveils the functional modules of the weighted graph by expanding a kernel protein set, which originates from a given 'seed' protein used as starting-point. Conclusion The integrated data and the concept of our approach provide reliable functional modules. We give proofs based on yeast data that our method manages to give accurate results in terms both of structural coherency, as well as functional consistency.

Clusters of proteins in bio-membranes: insights into the roles of interaction potential shapes and of protein diversity

OpenAIRE

Meilhac, Nicolas; Destainville, Nicolas

2011-01-01

It has recently been proposed that proteins embedded in lipidic bio-membranes can spontaneously self-organize into stable small clusters, or membrane nano-domains, due to the competition between short-range attractive and longer-range repulsive forces between proteins, specific to these systems. In this paper, we carry on our investigation, by Monte Carlo simulations, of different aspects of cluster phases of proteins in bio-membranes. First, we compare different long-range potentials (includ...

Mass functions for eight galactic clusters in the solar neighborhood

International Nuclear Information System (INIS)

Francic, S.P.

1989-01-01

Mass functions for eight galactic clusters in the solar neighborhood have been obtained. The mass functions have been determined from proper motion membership probabilities and unlike similar investigations, corrected for outlying cluster stars. The membership probabilities have been determined from the joint proper motion and surface density distributions for the field and clusters stars. They have also been corrected for any magnitude dependences. Comparison of the mass functions with the Salpeter IMF shows that the older clusters tend to be deficient in the number of low mass stars, while the younger clusters tend to have more. Analysis of the relaxation times shows that the deficiency of faint stars in the older clusters is likely due to their evaporation from the cluster. The combined mass function for six of the cluster results in a power law with a power law index of -1.97 ± 0.17 for 1.1 < M/Mass of sun < 2.5. This agrees with a recent determination of the field star IMF where the power law index is -2.00 ± 0.18 for 0.8 < M/Mass of sun < 18. If the older clusters are not considered, then comparison of the combined mass function with the individual cluster mass functions shows that the universality hypothesis cannot be denied

Role of protein-glutathione contacts in defining glutaredoxin-3 [2Fe-2S] cluster chirality, ligand exchange and transfer chemistry.

Science.gov (United States)

Sen, Sambuddha; Cowan, J A

2017-10-01

Monothiol glutaredoxins (Grx) serve as intermediate cluster carriers in iron-sulfur cluster trafficking. The [2Fe-2S]-bound holo forms of Grx proteins display cysteinyl coordination from exogenous glutathione (GSH), in addition to contact from protein-derived Cys. Herein, we report mechanistic studies that investigate the role of exogenous glutathione in defining cluster chirality, ligand exchange, and the cluster transfer chemistry of Saccharomyces cerevisiae Grx3. Systematic perturbations were introduced to the glutathione-binding site by substitution of conserved charged amino acids that form crucial electrostatic contacts with the glutathione molecule. Native Grx3 could also be reconstituted in the absence of glutathione, with either DTT, BME or free L-cysteine as the source of the exogenous Fe-S ligand contact, while retaining full functional reactivity. The delivery of the [2Fe-2S] cluster to Grx3 from cluster donor proteins such as Isa, Nfu, and a [2Fe-2S](GS) 4 complex, revealed that electrostatic contacts are of key importance for positioning the exogenous glutathione that in turn influences the chiral environment of the cluster. All Grx3 derivatives were reconstituted by standard chemical reconstitution protocols and found to transfer cluster to apo ferredoxin 1 (Fdx1) at rates comparable to native protein, even when using DTT, BME or free L-cysteine as a thiol source in place of GSH during reconstitution. Kinetic analysis of cluster transfer from holo derivatives to apo Fdx1 has led to a mechanistic model for cluster transfer chemistry of native holo Grx3, and identification of the likely rate-limiting step for the reaction.

Genomic organization, tissue distribution and functional characterization of the rat Pate gene cluster.

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Angireddy Rajesh

Full Text Available The cysteine rich prostate and testis expressed (Pate proteins identified till date are thought to resemble the three fingered protein/urokinase-type plasminogen activator receptor proteins. In this study, for the first time, we report the identification, cloning and characterization of rat Pate gene cluster and also determine the expression pattern. The rat Pate genes are clustered on chromosome 8 and their predicted proteins retained the ten cysteine signature characteristic to TFP/Ly-6 protein family. PATE and PATE-F three dimensional protein structure was found to be similar to that of the toxin bucandin. Though Pate gene expression is thought to be prostate and testis specific, we observed that rat Pate genes are also expressed in seminal vesicle and epididymis and in tissues beyond the male reproductive tract. In the developing rats (20-60 day old, expression of Pate genes seem to be androgen dependent in the epididymis and testis. In the adult rat, androgen ablation resulted in down regulation of the majority of Pate genes in the epididymides. PATE and PATE-F proteins were found to be expressed abundantly in the male reproductive tract of rats and on the sperm. Recombinant PATE protein exhibited potent antibacterial activity, whereas PATE-F did not exhibit any antibacterial activity. Pate expression was induced in the epididymides when challenged with LPS. Based on our results, we conclude that rat PATE proteins may contribute to the reproductive and defense functions.

Identification of functional candidates amongst hypothetical proteins of Treponema pallidum ssp. pallidum.

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Naqvi, Ahmad Abu Turab; Shahbaaz, Mohd; Ahmad, Faizan; Hassan, Md Imtaiyaz

2015-01-01

Syphilis is a globally occurring venereal disease, and its infection is propagated through sexual contact. The causative agent of syphilis, Treponema pallidum ssp. pallidum, a Gram-negative sphirochaete, is an obligate human parasite. Genome of T. pallidum ssp. pallidum SS14 strain (RefSeq NC_010741.1) encodes 1,027 proteins, of which 444 proteins are known as hypothetical proteins (HPs), i.e., proteins of unknown functions. Here, we performed functional annotation of HPs of T. pallidum ssp. pallidum using various database, domain architecture predictors, protein function annotators and clustering tools. We have analyzed the sequences of 444 HPs of T. pallidum ssp. pallidum and subsequently predicted the function of 207 HPs with a high level of confidence. However, functions of 237 HPs are predicted with less accuracy. We found various enzymes, transporters, binding proteins in the annotated group of HPs that may be possible molecular targets, facilitating for the survival of pathogen. Our comprehensive analysis helps to understand the mechanism of pathogenesis to provide many novel potential therapeutic interventions.

GPI-anchored proteins are confined in subdiffraction clusters at the apical surface of polarized epithelial cells.

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Paladino, Simona; Lebreton, Stéphanie; Lelek, Mickaël; Riccio, Patrizia; De Nicola, Sergio; Zimmer, Christophe; Zurzolo, Chiara

2017-12-01

Spatio-temporal compartmentalization of membrane proteins is critical for the regulation of diverse vital functions in eukaryotic cells. It was previously shown that, at the apical surface of polarized MDCK cells, glycosylphosphatidylinositol (GPI)-anchored proteins (GPI-APs) are organized in small cholesterol-independent clusters of single GPI-AP species (homoclusters), which are required for the formation of larger cholesterol-dependent clusters formed by multiple GPI-AP species (heteroclusters). This clustered organization is crucial for the biological activities of GPI-APs; hence, understanding the spatio-temporal properties of their membrane organization is of fundamental importance. Here, by using direct stochastic optical reconstruction microscopy coupled to pair correlation analysis (pc-STORM), we were able to visualize and measure the size of these clusters. Specifically, we show that they are non-randomly distributed and have an average size of 67 nm. We also demonstrated that polarized MDCK and non-polarized CHO cells have similar cluster distribution and size, but different sensitivity to cholesterol depletion. Finally, we derived a model that allowed a quantitative characterization of the cluster organization of GPI-APs at the apical surface of polarized MDCK cells for the first time. Experimental FRET (fluorescence resonance energy transfer)/FLIM (fluorescence-lifetime imaging microscopy) data were correlated to the theoretical predictions of the model. © 2017 The Author(s).

Proteins in similarity relationship with the cluster - Gclust Server | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available List Contact us Gclust Server Proteins in similarity relationship with the cluster Data detail Data name Pro...teins in similarity relationship with the cluster DOI 10.18908/lsdba.nbdc00464-003 Description of data conte...s Proteins in similarity relationship with the cluster - Gclust Server | LSDB Archive ...

A proteomic approach to investigating gene cluster expression and secondary metabolite functionality in Aspergillus fumigatus.

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Rebecca A Owens

Full Text Available A combined proteomics and metabolomics approach was utilised to advance the identification and characterisation of secondary metabolites in Aspergillus fumigatus. Here, implementation of a shotgun proteomic strategy led to the identification of non-redundant mycelial proteins (n = 414 from A. fumigatus including proteins typically under-represented in 2-D proteome maps: proteins with multiple transmembrane regions, hydrophobic proteins and proteins with extremes of molecular mass and pI. Indirect identification of secondary metabolite cluster expression was also achieved, with proteins (n = 18 from LaeA-regulated clusters detected, including GliT encoded within the gliotoxin biosynthetic cluster. Biochemical analysis then revealed that gliotoxin significantly attenuates H2O2-induced oxidative stress in A. fumigatus (p>0.0001, confirming observations from proteomics data. A complementary 2-D/LC-MS/MS approach further elucidated significantly increased abundance (p<0.05 of proliferating cell nuclear antigen (PCNA, NADH-quinone oxidoreductase and the gliotoxin oxidoreductase GliT, along with significantly attenuated abundance (p<0.05 of a heat shock protein, an oxidative stress protein and an autolysis-associated chitinase, when gliotoxin and H2O2 were present, compared to H2O2 alone. Moreover, gliotoxin exposure significantly reduced the abundance of selected proteins (p<0.05 involved in de novo purine biosynthesis. Significantly elevated abundance (p<0.05 of a key enzyme, xanthine-guanine phosphoribosyl transferase Xpt1, utilised in purine salvage, was observed in the presence of H2O2 and gliotoxin. This work provides new insights into the A. fumigatus proteome and experimental strategies, plus mechanistic data pertaining to gliotoxin functionality in the organism.

Homo-FRET imaging as a tool to quantify protein and lipid clustering.

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Bader, Arjen N; Hoetzl, Sandra; Hofman, Erik G; Voortman, Jarno; van Bergen en Henegouwen, Paul M P; van Meer, Gerrit; Gerritsen, Hans C

2011-02-25

Homo-FRET, Förster resonance energy transfer between identical fluorophores, can be conveniently measured by observing its effect on the fluorescence anisotropy. This review aims to summarize the possibilities of fluorescence anisotropy imaging techniques to investigate clustering of identical proteins and lipids. Homo-FRET imaging has the ability to determine distances between fluorophores. In addition it can be employed to quantify cluster sizes as well as cluster size distributions. The interpretation of homo-FRET signals is complicated by the fact that both the mutual orientations of the fluorophores and the number of fluorophores per cluster affect the fluorescence anisotropy in a similar way. The properties of the fluorescence probes are very important. Taking these properties into account is critical for the correct interpretation of homo-FRET signals in protein- and lipid-clustering studies. This is be exemplified by studies on the clustering of the lipid raft markers GPI and K-ras, as well as for EGF receptor clustering in the plasma membrane. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Improved Density Functional Tight Binding Potentials for Metalloid Aluminum Clusters

Science.gov (United States)

2016-06-01

unlimited IMPROVED DENSITY-FUNCTIONAL TIGHT BINDING POTENTIALS FOR METALLOID ALUMINUM CLUSTERS by Joon H. Kim June 2016 Thesis Advisor...DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE IMPROVED DENSITY-FUNCTIONAL TIGHT BINDING POTENTIALS FOR METALLOID ALUMINUM CLUSTERS 5. FUNDING...repulsive potentials for use in density-functional tight binding (DFTB) simulations of low-valence aluminum metalloid clusters . These systems are under

[Clustered regularly interspaced short palindromic repeats: structure, function and application--a review].

Science.gov (United States)

Cui, Yujun; Li, Yanjun; Yan, Yanfeng; Yang, Ruifu

2008-11-01

CRISPRs (Clustered Regularly Interspaced Short Palindromic Repeats), the basis of spoligotyping technology, can provide prokaryotes with heritable adaptive immunity against phages' invasion. Studies on CRISPR loci and their associated elements, including various CAS (CRISPR-associated) proteins and leader sequences, are still in its infant period. We introduce the brief history', structure, function, bioinformatics research and application of this amazing immunity system in prokaryotic organism for inspiring more scientists to find their interest in this developing topic.

Global functional atlas of Escherichia coli encompassing previously uncharacterized proteins.

Science.gov (United States)

Hu, Pingzhao; Janga, Sarath Chandra; Babu, Mohan; Díaz-Mejía, J Javier; Butland, Gareth; Yang, Wenhong; Pogoutse, Oxana; Guo, Xinghua; Phanse, Sadhna; Wong, Peter; Chandran, Shamanta; Christopoulos, Constantine; Nazarians-Armavil, Anaies; Nasseri, Negin Karimi; Musso, Gabriel; Ali, Mehrab; Nazemof, Nazila; Eroukova, Veronika; Golshani, Ashkan; Paccanaro, Alberto; Greenblatt, Jack F; Moreno-Hagelsieb, Gabriel; Emili, Andrew

2009-04-28

One-third of the 4,225 protein-coding genes of Escherichia coli K-12 remain functionally unannotated (orphans). Many map to distant clades such as Archaea, suggesting involvement in basic prokaryotic traits, whereas others appear restricted to E. coli, including pathogenic strains. To elucidate the orphans' biological roles, we performed an extensive proteomic survey using affinity-tagged E. coli strains and generated comprehensive genomic context inferences to derive a high-confidence compendium for virtually the entire proteome consisting of 5,993 putative physical interactions and 74,776 putative functional associations, most of which are novel. Clustering of the respective probabilistic networks revealed putative orphan membership in discrete multiprotein complexes and functional modules together with annotated gene products, whereas a machine-learning strategy based on network integration implicated the orphans in specific biological processes. We provide additional experimental evidence supporting orphan participation in protein synthesis, amino acid metabolism, biofilm formation, motility, and assembly of the bacterial cell envelope. This resource provides a "systems-wide" functional blueprint of a model microbe, with insights into the biological and evolutionary significance of previously uncharacterized proteins.

Ligand cluster-based protein network and ePlatton, a multi-target ligand finder.

Science.gov (United States)

Du, Yu; Shi, Tieliu

2016-01-01

Small molecules are information carriers that make cells aware of external changes and couple internal metabolic and signalling pathway systems with each other. In some specific physiological status, natural or artificial molecules are used to interact with selective biological targets to activate or inhibit their functions to achieve expected biological and physiological output. Millions of years of evolution have optimized biological processes and pathways and now the endocrine and immune system cannot work properly without some key small molecules. In the past thousands of years, the human race has managed to find many medicines against diseases by trail-and-error experience. In the recent decades, with the deepening understanding of life and the progress of molecular biology, researchers spare no effort to design molecules targeting one or two key enzymes and receptors related to corresponding diseases. But recent studies in pharmacogenomics have shown that polypharmacology may be necessary for the effects of drugs, which challenge the paradigm, 'one drug, one target, one disease'. Nowadays, cheminformatics and structural biology can help us reasonably take advantage of the polypharmacology to design next-generation promiscuous drugs and drug combination therapies. 234,591 protein-ligand interactions were extracted from ChEMBL. By the 2D structure similarity, 13,769 ligand emerged from 156,151 distinct ligands which were recognized by 1477 proteins. Ligand cluster- and sequence-based protein networks (LCBN, SBN) were constructed, compared and analysed. For assisting compound designing, exploring polypharmacology and finding possible drug combination, we integrated the pathway, disease, drug adverse reaction and the relationship of targets and ligand clusters into the web platform, ePlatton, which is available at http://www.megabionet.org/eplatton. Although there were some disagreements between the LCBN and SBN, communities in both networks were largely the same

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.

Dynamic Change in p63 Protein Expression during Implantation of Urothelial Cancer Clusters

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Takahiro Yoshida

2015-07-01

Full Text Available Although the dissemination of urothelial cancer cells is supposed to be a major cause of the multicentricity of urothelial tumors, the mechanism of implantation has not been well investigated. Here, we found that cancer cell clusters from the urine of patients with urothelial cancer retain the ability to survive, grow, and adhere. By using cell lines and primary cells collected from multiple patients, we demonstrate that △Np63α protein in cancer cell clusters was rapidly decreased through proteasomal degradation when clusters were attached to the matrix, leading to downregulation of E-cadherin and upregulation of N-cadherin. Decreased △Np63α protein level in urothelial cancer cell clusters was involved in the clearance of the urothelium. Our data provide the first evidence that clusters of urothelial cancer cells exhibit dynamic changes in △Np63α expression during attachment to the matrix, and decreased △Np63α protein plays a critical role in the interaction between cancer cell clusters and the urothelium. Thus, because △Np63α might be involved in the process of intraluminal dissemination of urothelial cancer cells, blocking the degradation of △Np63α could be a target of therapy to prevent the dissemination of urothelial cancer.

Composite Structural Motifs of Binding Sites for Delineating Biological Functions of Proteins

Science.gov (United States)

Kinjo, Akira R.; Nakamura, Haruki

2012-01-01

Most biological processes are described as a series of interactions between proteins and other molecules, and interactions are in turn described in terms of atomic structures. To annotate protein functions as sets of interaction states at atomic resolution, and thereby to better understand the relation between protein interactions and biological functions, we conducted exhaustive all-against-all atomic structure comparisons of all known binding sites for ligands including small molecules, proteins and nucleic acids, and identified recurring elementary motifs. By integrating the elementary motifs associated with each subunit, we defined composite motifs that represent context-dependent combinations of elementary motifs. It is demonstrated that function similarity can be better inferred from composite motif similarity compared to the similarity of protein sequences or of individual binding sites. By integrating the composite motifs associated with each protein function, we define meta-composite motifs each of which is regarded as a time-independent diagrammatic representation of a biological process. It is shown that meta-composite motifs provide richer annotations of biological processes than sequence clusters. The present results serve as a basis for bridging atomic structures to higher-order biological phenomena by classification and integration of binding site structures. PMID:22347478

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.

Efficient algorithms for accurate hierarchical clustering of huge datasets: tackling the entire protein space.

Science.gov (United States)

Loewenstein, Yaniv; Portugaly, Elon; Fromer, Menachem; Linial, Michal

2008-07-01

UPGMA (average linking) is probably the most popular algorithm for hierarchical data clustering, especially in computational biology. However, UPGMA requires the entire dissimilarity matrix in memory. Due to this prohibitive requirement, UPGMA is not scalable to very large datasets. We present a novel class of memory-constrained UPGMA (MC-UPGMA) algorithms. Given any practical memory size constraint, this framework guarantees the correct clustering solution without explicitly requiring all dissimilarities in memory. The algorithms are general and are applicable to any dataset. We present a data-dependent characterization of hardness and clustering efficiency. The presented concepts are applicable to any agglomerative clustering formulation. We apply our algorithm to the entire collection of protein sequences, to automatically build a comprehensive evolutionary-driven hierarchy of proteins from sequence alone. The newly created tree captures protein families better than state-of-the-art large-scale methods such as CluSTr, ProtoNet4 or single-linkage clustering. We demonstrate that leveraging the entire mass embodied in all sequence similarities allows to significantly improve on current protein family clusterings which are unable to directly tackle the sheer mass of this data. Furthermore, we argue that non-metric constraints are an inherent complexity of the sequence space and should not be overlooked. The robustness of UPGMA allows significant improvement, especially for multidomain proteins, and for large or divergent families. A comprehensive tree built from all UniProt sequence similarities, together with navigation and classification tools will be made available as part of the ProtoNet service. A C++ implementation of the algorithm is available on request.

Finding local communities in protein networks.

Science.gov (United States)

Voevodski, Konstantin; Teng, Shang-Hua; Xia, Yu

2009-09-18

Protein-protein interactions (PPIs) play fundamental roles in nearly all biological processes, and provide major insights into the inner workings of cells. A vast amount of PPI data for various organisms is available from BioGRID and other sources. The identification of communities in PPI networks is of great interest because they often reveal previously unknown functional ties between proteins. A large number of global clustering algorithms have been applied to protein networks, where the entire network is partitioned into clusters. Here we take a different approach by looking for local communities in PPI networks. We develop a tool, named Local Protein Community Finder, which quickly finds a community close to a queried protein in any network available from BioGRID or specified by the user. Our tool uses two new local clustering algorithms Nibble and PageRank-Nibble, which look for a good cluster among the most popular destinations of a short random walk from the queried vertex. The quality of a cluster is determined by proportion of outgoing edges, known as conductance, which is a relative measure particularly useful in undersampled networks. We show that the two local clustering algorithms find communities that not only form excellent clusters, but are also likely to be biologically relevant functional components. We compare the performance of Nibble and PageRank-Nibble to other popular and effective graph partitioning algorithms, and show that they find better clusters in the graph. Moreover, Nibble and PageRank-Nibble find communities that are more functionally coherent. The Local Protein Community Finder, accessible at http://xialab.bu.edu/resources/lpcf, allows the user to quickly find a high-quality community close to a queried protein in any network available from BioGRID or specified by the user. We show that the communities found by our tool form good clusters and are functionally coherent, making our application useful for biologists who wish to

Finding local communities in protein networks

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Teng Shang-Hua

2009-09-01

Full Text Available Abstract Background Protein-protein interactions (PPIs play fundamental roles in nearly all biological processes, and provide major insights into the inner workings of cells. A vast amount of PPI data for various organisms is available from BioGRID and other sources. The identification of communities in PPI networks is of great interest because they often reveal previously unknown functional ties between proteins. A large number of global clustering algorithms have been applied to protein networks, where the entire network is partitioned into clusters. Here we take a different approach by looking for local communities in PPI networks. Results We develop a tool, named Local Protein Community Finder, which quickly finds a community close to a queried protein in any network available from BioGRID or specified by the user. Our tool uses two new local clustering algorithms Nibble and PageRank-Nibble, which look for a good cluster among the most popular destinations of a short random walk from the queried vertex. The quality of a cluster is determined by proportion of outgoing edges, known as conductance, which is a relative measure particularly useful in undersampled networks. We show that the two local clustering algorithms find communities that not only form excellent clusters, but are also likely to be biologically relevant functional components. We compare the performance of Nibble and PageRank-Nibble to other popular and effective graph partitioning algorithms, and show that they find better clusters in the graph. Moreover, Nibble and PageRank-Nibble find communities that are more functionally coherent. Conclusion The Local Protein Community Finder, accessible at http://xialab.bu.edu/resources/lpcf, allows the user to quickly find a high-quality community close to a queried protein in any network available from BioGRID or specified by the user. We show that the communities found by our tool form good clusters and are functionally coherent

Photometric studies of globular clusters in the Andromeda Nebula. Luminosity function for old globular clusters

International Nuclear Information System (INIS)

Sharov, A.S.; Lyutyj, V.M.

1989-01-01

The luminosity function for old globular clusters in M 31 is presented. The objects were selected according to their structural and photometric properties. At the usually accepted normal (Gaussian) distribution, the luminosity function is characterized by the following parameters: the mean magnitude, corrected for the extinction inside M 31, V-bar 0 =16 m ,38±0 m .08, and the absolute magnitude M-bar v =-8 m .29 assuming )m-M) v =23 m .67, standard deviation σ M v =1 m .16±0 m .08 and total object number N=300±17. Old globular clusters in M 31 are in the average about one magnitude more luminous then those in our Galaxy (M v ≅ -7 m .3). Intrinsic luminosity dispersions of globular clusters are nearly the same in both galaxies. Available data on globular clusters in the Local Group galaxies against the universality of globular luminosity function with identical parameters M v and σ M v

Differential dynamic microscopy of weakly scattering and polydisperse protein-rich clusters

Science.gov (United States)

Safari, Mohammad S.; Vorontsova, Maria A.; Poling-Skutvik, Ryan; Vekilov, Peter G.; Conrad, Jacinta C.

2015-10-01

Nanoparticle dynamics impact a wide range of biological transport processes and applications in nanomedicine and natural resource engineering. Differential dynamic microscopy (DDM) was recently developed to quantify the dynamics of submicron particles in solutions from fluctuations of intensity in optical micrographs. Differential dynamic microscopy is well established for monodisperse particle populations, but has not been applied to solutions containing weakly scattering polydisperse biological nanoparticles. Here we use bright-field DDM (BDDM) to measure the dynamics of protein-rich liquid clusters, whose size ranges from tens to hundreds of nanometers and whose total volume fraction is less than 10-5. With solutions of two proteins, hemoglobin A and lysozyme, we evaluate the cluster diffusion coefficients from the dependence of the diffusive relaxation time on the scattering wave vector. We establish that for weakly scattering populations, an optimal thickness of the sample chamber exists at which the BDDM signal is maximized at the smallest sample volume. The average cluster diffusion coefficient measured using BDDM is consistently lower than that obtained from dynamic light scattering at a scattering angle of 90∘. This apparent discrepancy is due to Mie scattering from the polydisperse cluster population, in which larger clusters preferentially scatter more light in the forward direction.

Simplified Swarm Optimization-Based Function Module Detection in Protein–Protein Interaction Networks

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Xianghan Zheng

2017-04-01

Full Text Available Proteomics research has become one of the most important topics in the field of life science and natural science. At present, research on protein–protein interaction networks (PPIN mainly focuses on detecting protein complexes or function modules. However, existing approaches are either ineffective or incomplete. In this paper, we investigate detection mechanisms of functional modules in PPIN, including open database, existing detection algorithms, and recent solutions. After that, we describe the proposed approach based on the simplified swarm optimization (SSO algorithm and the knowledge of Gene Ontology (GO. The proposed solution implements the SSO algorithm for clustering proteins with similar function, and imports biological gene ontology knowledge for further identifying function complexes and improving detection accuracy. Furthermore, we use four different categories of species datasets for experiment: fruitfly, mouse, scere, and human. The testing and analysis result show that the proposed solution is feasible, efficient, and could achieve a higher accuracy of prediction than existing approaches.

Clustering of near clusters versus cluster compactness

International Nuclear Information System (INIS)

Yu Gao; Yipeng Jing

1989-01-01

The clustering properties of near Zwicky clusters are studied by using the two-point angular correlation function. The angular correlation functions for compact and medium compact clusters, for open clusters, and for all near Zwicky clusters are estimated. The results show much stronger clustering for compact and medium compact clusters than for open clusters, and that open clusters have nearly the same clustering strength as galaxies. A detailed study of the compactness-dependence of correlation function strength is worth investigating. (author)

Global functional atlas of Escherichia coli encompassing previously uncharacterized proteins.

Directory of Open Access Journals (Sweden)

Pingzhao Hu

2009-04-01

Full Text Available One-third of the 4,225 protein-coding genes of Escherichia coli K-12 remain functionally unannotated (orphans. Many map to distant clades such as Archaea, suggesting involvement in basic prokaryotic traits, whereas others appear restricted to E. coli, including pathogenic strains. To elucidate the orphans' biological roles, we performed an extensive proteomic survey using affinity-tagged E. coli strains and generated comprehensive genomic context inferences to derive a high-confidence compendium for virtually the entire proteome consisting of 5,993 putative physical interactions and 74,776 putative functional associations, most of which are novel. Clustering of the respective probabilistic networks revealed putative orphan membership in discrete multiprotein complexes and functional modules together with annotated gene products, whereas a machine-learning strategy based on network integration implicated the orphans in specific biological processes. We provide additional experimental evidence supporting orphan participation in protein synthesis, amino acid metabolism, biofilm formation, motility, and assembly of the bacterial cell envelope. This resource provides a "systems-wide" functional blueprint of a model microbe, with insights into the biological and evolutionary significance of previously uncharacterized proteins.

BiP clustering facilitates protein folding in the endoplasmic reticulum.

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Marc Griesemer

2014-07-01

Full Text Available The chaperone BiP participates in several regulatory processes within the endoplasmic reticulum (ER: translocation, protein folding, and ER-associated degradation. To facilitate protein folding, a cooperative mechanism known as entropic pulling has been proposed to demonstrate the molecular-level understanding of how multiple BiP molecules bind to nascent and unfolded proteins. Recently, experimental evidence revealed the spatial heterogeneity of BiP within the nuclear and peripheral ER of S. cerevisiae (commonly referred to as 'clusters'. Here, we developed a model to evaluate the potential advantages of accounting for multiple BiP molecules binding to peptides, while proposing that BiP's spatial heterogeneity may enhance protein folding and maturation. Scenarios were simulated to gauge the effectiveness of binding multiple chaperone molecules to peptides. Using two metrics: folding efficiency and chaperone cost, we determined that the single binding site model achieves a higher efficiency than models characterized by multiple binding sites, in the absence of cooperativity. Due to entropic pulling, however, multiple chaperones perform in concert to facilitate the resolubilization and ultimate yield of folded proteins. As a result of cooperativity, multiple binding site models used fewer BiP molecules and maintained a higher folding efficiency than the single binding site model. These insilico investigations reveal that clusters of BiP molecules bound to unfolded proteins may enhance folding efficiency through cooperative action via entropic pulling.

25. Steenbock symposium -- Biosynthesis and function of metal clusters for enzymes: Proceedings

Energy Technology Data Exchange (ETDEWEB)

NONE

1997-12-31

This symposium was held June 10--14, 1997 in Madison, Wisconsin. The purpose of this conference was to provide a multidisciplinary forum for exchange of state-of-the-art information on biochemistry of enzymes that have an affinity for metal clusters. Attention is focused on the following: metal clusters involved in energy conservation and remediation; tungsten, molybdenum, and cobalt-containing enzymes; Fe proteins, and Mo-binding proteins; nickel enzymes; and nitrogenase.

Architecture of the Yeast Mitochondrial Iron-Sulfur Cluster Assembly Machinery: THE SUB-COMPLEX FORMED BY THE IRON DONOR, Yfh1 PROTEIN, AND THE SCAFFOLD, Isu1 PROTEIN.

Science.gov (United States)

Ranatunga, Wasantha; Gakh, Oleksandr; Galeano, Belinda K; Smith, Douglas Y; Söderberg, Christopher A G; Al-Karadaghi, Salam; Thompson, James R; Isaya, Grazia

2016-05-06

The biosynthesis of Fe-S clusters is a vital process involving the delivery of elemental iron and sulfur to scaffold proteins via molecular interactions that are still poorly defined. We reconstituted a stable, functional complex consisting of the iron donor, Yfh1 (yeast frataxin homologue 1), and the Fe-S cluster scaffold, Isu1, with 1:1 stoichiometry, [Yfh1]24·[Isu1]24 Using negative staining transmission EM and single particle analysis, we obtained a three-dimensional reconstruction of this complex at a resolution of ∼17 Å. In addition, via chemical cross-linking, limited proteolysis, and mass spectrometry, we identified protein-protein interaction surfaces within the complex. The data together reveal that [Yfh1]24·[Isu1]24 is a roughly cubic macromolecule consisting of one symmetric Isu1 trimer binding on top of one symmetric Yfh1 trimer at each of its eight vertices. Furthermore, molecular modeling suggests that two subunits of the cysteine desulfurase, Nfs1, may bind symmetrically on top of two adjacent Isu1 trimers in a manner that creates two putative [2Fe-2S] cluster assembly centers. In each center, conserved amino acids known to be involved in sulfur and iron donation by Nfs1 and Yfh1, respectively, are in close proximity to the Fe-S cluster-coordinating residues of Isu1. We suggest that this architecture is suitable to ensure concerted and protected transfer of potentially toxic iron and sulfur atoms to Isu1 during Fe-S cluster assembly. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Lithuanian medical tourism cluster: conditions and background for functioning

Directory of Open Access Journals (Sweden)

Korol A. N.

2017-10-01

Full Text Available as the global economy develops, more and more attention is paid to the creation of tourist clusters, which are extremely important for the economy and national competitiveness. This article analyzes the cluster of medical tourism in Lithuania, and explores the conditions for its successful functioning. The creation of the medical tourism cluster is highly influenced by a number of factors: the regulation of tourist and medical services, the level of entrepreneurial activity, human resources, the experience of partnership. In addition, the article analyzes the structure of the medical tourism cluster, determines the prerequisites for the functioning of the Lithuanian medical tourism cluster, including a wide range of services, European standards for the provision of medical services, high qualification of specialists, etc. When writing the article, the methods of systematic and logical analysis of scientific literature were used.

Cranked cluster wave function for molecular states

International Nuclear Information System (INIS)

Horiuchi, Hisashi; Yabana, Kazuhiro; Wada, Takahiro.

1986-01-01

Construction of the cranked cluster wave function is discussed by focussing on three problems; the self-consistency between the potential and the density distribution, the properties of the rotational angular frequency which is strongly influenced by the inter-cluster Pauli principle and by the parity projection, and the spin alignment along the rotation axis with the resulting structure-change of the molecular state. (author)

Protein function prediction using neighbor relativity in protein-protein interaction network.

Science.gov (United States)

Moosavi, Sobhan; Rahgozar, Masoud; Rahimi, Amir

2013-04-01

There is a large gap between the number of discovered proteins and the number of functionally annotated ones. Due to the high cost of determining protein function by wet-lab research, function prediction has become a major task for computational biology and bioinformatics. Some researches utilize the proteins interaction information to predict function for un-annotated proteins. In this paper, we propose a novel approach called "Neighbor Relativity Coefficient" (NRC) based on interaction network topology which estimates the functional similarity between two proteins. NRC is calculated for each pair of proteins based on their graph-based features including distance, common neighbors and the number of paths between them. In order to ascribe function to an un-annotated protein, NRC estimates a weight for each neighbor to transfer its annotation to the unknown protein. Finally, the unknown protein will be annotated by the top score transferred functions. We also investigate the effect of using different coefficients for various types of functions. The proposed method has been evaluated on Saccharomyces cerevisiae and Homo sapiens interaction networks. The performance analysis demonstrates that NRC yields better results in comparison with previous protein function prediction approaches that utilize interaction network. Copyright © 2012 Elsevier Ltd. All rights reserved.

Introducing a Clustering Step in a Consensus Approach for the Scoring of Protein-Protein Docking Models

KAUST Repository

Chermak, Edrisse; De Donato, Renato; Lensink, Marc F.; Petta, Andrea; Serra, Luigi; Scarano, Vittorio; Cavallo, Luigi; Oliva, Romina

2016-01-01

Correctly scoring protein-protein docking models to single out native-like ones is an open challenge. It is also an object of assessment in CAPRI (Critical Assessment of PRedicted Interactions), the community-wide blind docking experiment. We introduced in the field the first pure consensus method, CONSRANK, which ranks models based on their ability to match the most conserved contacts in the ensemble they belong to. In CAPRI, scorers are asked to evaluate a set of available models and select the top ten ones, based on their own scoring approach. Scorers' performance is ranked based on the number of targets/interfaces for which they could provide at least one correct solution. In such terms, blind testing in CAPRI Round 30 (a joint prediction round with CASP11) has shown that critical cases for CONSRANK are represented by targets showing multiple interfaces or for which only a very small number of correct solutions are available. To address these challenging cases, CONSRANK has now been modified to include a contact-based clustering of the models as a preliminary step of the scoring process. We used an agglomerative hierarchical clustering based on the number of common inter-residue contacts within the models. Two criteria, with different thresholds, were explored in the cluster generation, setting either the number of common contacts or of total clusters. For each clustering approach, after selecting the top (most populated) ten clusters, CONSRANK was run on these clusters and the top-ranked model for each cluster was selected, in the limit of 10 models per target. We have applied our modified scoring approach, Clust-CONSRANK, to SCORE_SET, a set of CAPRI scoring models made recently available by CAPRI assessors, and to the subset of homodimeric targets in CAPRI Round 30 for which CONSRANK failed to include a correct solution within the ten selected models. Results show that, for the challenging cases, the clustering step typically enriches the ten top ranked

Introducing a Clustering Step in a Consensus Approach for the Scoring of Protein-Protein Docking Models

KAUST Repository

Chermak, Edrisse

2016-11-15

Correctly scoring protein-protein docking models to single out native-like ones is an open challenge. It is also an object of assessment in CAPRI (Critical Assessment of PRedicted Interactions), the community-wide blind docking experiment. We introduced in the field the first pure consensus method, CONSRANK, which ranks models based on their ability to match the most conserved contacts in the ensemble they belong to. In CAPRI, scorers are asked to evaluate a set of available models and select the top ten ones, based on their own scoring approach. Scorers\\' performance is ranked based on the number of targets/interfaces for which they could provide at least one correct solution. In such terms, blind testing in CAPRI Round 30 (a joint prediction round with CASP11) has shown that critical cases for CONSRANK are represented by targets showing multiple interfaces or for which only a very small number of correct solutions are available. To address these challenging cases, CONSRANK has now been modified to include a contact-based clustering of the models as a preliminary step of the scoring process. We used an agglomerative hierarchical clustering based on the number of common inter-residue contacts within the models. Two criteria, with different thresholds, were explored in the cluster generation, setting either the number of common contacts or of total clusters. For each clustering approach, after selecting the top (most populated) ten clusters, CONSRANK was run on these clusters and the top-ranked model for each cluster was selected, in the limit of 10 models per target. We have applied our modified scoring approach, Clust-CONSRANK, to SCORE_SET, a set of CAPRI scoring models made recently available by CAPRI assessors, and to the subset of homodimeric targets in CAPRI Round 30 for which CONSRANK failed to include a correct solution within the ten selected models. Results show that, for the challenging cases, the clustering step typically enriches the ten top ranked

Transcriptional analysis of the jamaicamide gene cluster from the marine cyanobacterium Lyngbya majuscula and identification of possible regulatory proteins

Directory of Open Access Journals (Sweden)

Dorrestein Pieter C

2009-12-01

Full Text Available Abstract Background The marine cyanobacterium Lyngbya majuscula is a prolific producer of bioactive secondary metabolites. Although biosynthetic gene clusters encoding several of these compounds have been identified, little is known about how these clusters of genes are transcribed or regulated, and techniques targeting genetic manipulation in Lyngbya strains have not yet been developed. We conducted transcriptional analyses of the jamaicamide gene cluster from a Jamaican strain of Lyngbya majuscula, and isolated proteins that could be involved in jamaicamide regulation. Results An unusually long untranslated leader region of approximately 840 bp is located between the jamaicamide transcription start site (TSS and gene cluster start codon. All of the intergenic regions between the pathway ORFs were transcribed into RNA in RT-PCR experiments; however, a promoter prediction program indicated the possible presence of promoters in multiple intergenic regions. Because the functionality of these promoters could not be verified in vivo, we used a reporter gene assay in E. coli to show that several of these intergenic regions, as well as the primary promoter preceding the TSS, are capable of driving β-galactosidase production. A protein pulldown assay was also used to isolate proteins that may regulate the jamaicamide pathway. Pulldown experiments using the intergenic region upstream of jamA as a DNA probe isolated two proteins that were identified by LC-MS/MS. By BLAST analysis, one of these had close sequence identity to a regulatory protein in another cyanobacterial species. Protein comparisons suggest a possible correlation between secondary metabolism regulation and light dependent complementary chromatic adaptation. Electromobility shift assays were used to evaluate binding of the recombinant proteins to the jamaicamide promoter region. Conclusion Insights into natural product regulation in cyanobacteria are of significant value to drug discovery

Identification of tyrosine-phosphorylated proteins associated with metastasis and functional analysis of FER in human hepatocellular carcinoma cells

International Nuclear Information System (INIS)

Li, Haiyu; Ren, Zhenggang; Kang, Xiaonan; Zhang, Lan; Li, Xuefei; Wang, Yan; Xue, Tongchun; Shen, Yuefang; Liu, Yinkun

2009-01-01

Aberrant activity of tyrosine-phosphorylated proteins is commonly associated with HCC metastasis. Cell signaling events driven by these proteins are implicated in numerous processes that alter cancer cell behavior. Exploring the activities and signaling pathways of these proteins in HCC metastasis may help in identifying new candidate molecules for HCC-targeted therapy. Hep3B (a nonmetastatic HCC cell line) and MHCC97H (a highly metastatic HCC cell line) were used in this study, and the tyrosine-phosphorylated proteins expressed in these cell lines were profiled by a phosphoproteomics technique based on LC-MS/MS. Protein-protein interaction and functional clustering analyses were performed to determine the activities of the identified proteins and the signaling pathways closely related to HCC metastasis. In both cell lines, a total of 247 phosphotyrosine (pTyr) proteins containing 281 pTyr sites were identified without any stimulation. The involvement of almost 30% of these in liver or liver cancer has not been reported previously. Biological process clustering analysis indicated that pTyr proteins involved in cell motility, migration, protein autophosphorylation, cell-cell communication, and antiapoptosis functions were overexpressed during metastasis. Pathway clustering analysis revealed that signaling pathways such as those involved in EGFR signaling, cytokine- and chemokine-mediated signal transduction, and the PI3K and JAK-STAT cascades were significantly activated during HCC metastasis. Moreover, noncanonical regulation of the JNK cascade might also provide new targets for HCC metastasis. After comparing the pTyr proteins that were differentially expressed during HCC cell metastasis, we selected FER, a nonreceptor tyrosine kinase, and validated its role in terms of both expression and function. The data confirmed that FER might play a critical role in the invasion and metastasis of HCC. The identification of pTyr proteins and signaling pathways associated

Interaction between Nbp35 and Cfd1 proteins of cytosolic Fe-S cluster assembly reveals a stable complex formation in Entamoeba histolytica.

Directory of Open Access Journals (Sweden)

Shadab Anwar

Full Text Available Iron-Sulfur (Fe-S proteins are involved in many biological functions such as electron transport, photosynthesis, regulation of gene expression and enzymatic activities. Biosynthesis and transfer of Fe-S clusters depend on Fe-S clusters assembly processes such as ISC, SUF, NIF, and CIA systems. Unlike other eukaryotes which possess ISC and CIA systems, amitochondriate Entamoeba histolytica has retained NIF & CIA systems for Fe-S cluster assembly in the cytosol. In the present study, we have elucidated interaction between two proteins of E. histolytica CIA system, Cytosolic Fe-S cluster deficient 1 (Cfd1 protein and Nucleotide binding protein 35 (Nbp35. In-silico analysis showed that structural regions ranging from amino acid residues (P33-K35, G131-V135 and I147-E151 of Nbp35 and (G5-V6, M34-D39 and G46-A52 of Cfd1 are involved in the formation of protein-protein complex. Furthermore, Molecular dynamic (MD simulations study suggested that hydrophobic forces surpass over hydrophilic forces between Nbp35 and Cfd1 and Van-der-Waal interaction plays crucial role in the formation of stable complex. Both proteins were separately cloned, expressed as recombinant fusion proteins in E. coli and purified to homogeneity by affinity column chromatography. Physical interaction between Nbp35 and Cfd1 proteins was confirmed in vitro by co-purification of recombinant Nbp35 with thrombin digested Cfd1 and in vivo by pull down assay and immunoprecipitation. The insilico, in vitro as well as in vivo results prove a stable interaction between these two proteins, supporting the possibility of its involvement in Fe-S cluster transfer to target apo-proteins through CIA machinery in E. histolytica. Our study indicates that initial synthesis of a Fe-S precursor in mitochondria is not necessary for the formation of Cfd1-Nbp35 complex. Thus, Cfd1 and Nbp35 with the help of cytosolic NifS and NifU proteins can participate in the maturation of non-mitosomal Fe-S proteins

Topology-function conservation in protein-protein interaction networks.

Science.gov (United States)

Davis, Darren; Yaveroğlu, Ömer Nebil; Malod-Dognin, Noël; Stojmirovic, Aleksandar; Pržulj, Nataša

2015-05-15

Proteins underlay the functioning of a cell and the wiring of proteins in protein-protein interaction network (PIN) relates to their biological functions. Proteins with similar wiring in the PIN (topology around them) have been shown to have similar functions. This property has been successfully exploited for predicting protein functions. Topological similarity is also used to guide network alignment algorithms that find similarly wired proteins between PINs of different species; these similarities are used to transfer annotation across PINs, e.g. from model organisms to human. To refine these functional predictions and annotation transfers, we need to gain insight into the variability of the topology-function relationships. For example, a function may be significantly associated with specific topologies, while another function may be weakly associated with several different topologies. Also, the topology-function relationships may differ between different species. To improve our understanding of topology-function relationships and of their conservation among species, we develop a statistical framework that is built upon canonical correlation analysis. Using the graphlet degrees to represent the wiring around proteins in PINs and gene ontology (GO) annotations to describe their functions, our framework: (i) characterizes statistically significant topology-function relationships in a given species, and (ii) uncovers the functions that have conserved topology in PINs of different species, which we term topologically orthologous functions. We apply our framework to PINs of yeast and human, identifying seven biological process and two cellular component GO terms to be topologically orthologous for the two organisms. © The Author 2015. Published by Oxford University Press.

Functionality of system components: Conservation of protein function in protein feature space

DEFF Research Database (Denmark)

Jensen, Lars Juhl; Ussery, David; Brunak, Søren

2003-01-01

well on organisms other than the one on which it was trained. We evaluate the performance of such a method, ProtFun, which relies on protein features as its sole input, and show that the method gives similar performance for most eukaryotes and performs much better than anticipated on archaea......Many protein features useful for prediction of protein function can be predicted from sequence, including posttranslational modifications, subcellular localization, and physical/chemical properties. We show here that such protein features are more conserved among orthologs than paralogs, indicating...... they are crucial for protein function and thus subject to selective pressure. This means that a function prediction method based on sequence-derived features may be able to discriminate between proteins with different function even when they have highly similar structure. Also, such a method is likely to perform...

Inelastic electron scattering as an indicator of clustering in wave functions

International Nuclear Information System (INIS)

1998-01-01

While the shell model is the most fundamental of nuclear structure models, states in light nuclei also have been described successfully in terms of clusters. Indeed, Wildemuth and Tang have shown a correspondence between the cluster and shell models, the clusters arising naturally as correlations out of the shell model Hamiltonian. For light nuclei, the cluster model reduces the many-body problem to a few-body one, with interactions occurring between the clusters. These interactions involve particle exchanges, since the nucleons may still be considered somewhat freely moving, with their motion not strictly confined to the clusters themselves. Such is the relation of the cluster model to the shell model. For a realistic shell model then, one may expect some evidence of clustering in the wave functions for those systems in which the cluster model is valid. The results obtained using the multi-ℎωshell model wave functions are closer in agreement with experiment than the results obtained using the 0ℎωwave functions. Yet in all cases, that level of agreement is not good, with the calculations underpredicting the measured values by at least a factor of two. This indicates that the shell model wave functions do not exhibit clustering behavior, which is expected to manifest itself at small momentum transfer. The exception is the transition to the 7 - /2 state in 7 Li, for which the value obtained from the γ-decay width is in agreement with the value obtained from the MK3W and (0 + 2 + 4)ℎωshell model calculations

Evolution of the cluster X-ray luminosity function

DEFF Research Database (Denmark)

Mullis, C.R.; Vikhlinin, A.; Henry, J.P.

2004-01-01

We report measurements of the cluster X-ray luminosity function out to z = 0.8 based on the final sample of 201 galaxy systems from the 160 Square Degree ROSAT Cluster Survey. There is little evidence for any measurable change in cluster abundance out to z similar to 0.6 at luminosities of less...... than a few times 10(44) h(50)(-2) ergs s(-1) (0.5 - 2.0 keV). However, for 0.6 cluster deficit using integrated number counts...... independently confirm the presence of evolution. Whereas the bulk of the cluster population does not evolve, the most luminous and presumably most massive structures evolve appreciably between z = 0.8 and the present. Interpreted in the context of hierarchical structure formation, we are probing sufficiently...

Using the clustered circular layout as an informative method for visualizing protein-protein interaction networks.

Science.gov (United States)

Fung, David C Y; Wilkins, Marc R; Hart, David; Hong, Seok-Hee

2010-07-01

The force-directed layout is commonly used in computer-generated visualizations of protein-protein interaction networks. While it is good for providing a visual outline of the protein complexes and their interactions, it has two limitations when used as a visual analysis method. The first is poor reproducibility. Repeated running of the algorithm does not necessarily generate the same layout, therefore, demanding cognitive readaptation on the investigator's part. The second limitation is that it does not explicitly display complementary biological information, e.g. Gene Ontology, other than the protein names or gene symbols. Here, we present an alternative layout called the clustered circular layout. Using the human DNA replication protein-protein interaction network as a case study, we compared the two network layouts for their merits and limitations in supporting visual analysis.

Nitrosylation of Nitric-Oxide-Sensing Regulatory Proteins Containing [4Fe-4S] Clusters Gives Rise to Multiple Iron-Nitrosyl Complexes

Energy Technology Data Exchange (ETDEWEB)

Serrano, Pauline N. [Department of Chemistry, University of California, Davis CA 95616 USA; Wang, Hongxin [Department of Chemistry, University of California, Davis CA 95616 USA; Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley CA 94720 USA; Crack, Jason C. [Centre for Molecular and Structural Biochemistry, School of Chemistry, University of East Anglia, Norwich Research Park Norwich NR4 7TJ UK; Prior, Christopher [Centre for Molecular and Structural Biochemistry, School of Chemistry, University of East Anglia, Norwich Research Park Norwich NR4 7TJ UK; Hutchings, Matthew I. [School of Biological Sciences, University of East Anglia, Norwich NR4 7TJ UK; Thomson, Andrew J. [Centre for Molecular and Structural Biochemistry, School of Chemistry, University of East Anglia, Norwich Research Park Norwich NR4 7TJ UK; Kamali, Saeed [University of Tennessee Space Institute, Tullahome TN 37388-9700 USA; Yoda, Yoshitaka [Research and Utilization Division, SPring-8/JASRI, 1-1-1 Kouto, Sayo Hyogo 679-5198 Japan; Zhao, Jiyong [Advanced Photon Source, Argonne National Laboratory, Argonne IL 60439 USA; Hu, Michael Y. [Advanced Photon Source, Argonne National Laboratory, Argonne IL 60439 USA; Alp, Ercan E. [Advanced Photon Source, Argonne National Laboratory, Argonne IL 60439 USA; Oganesyan, Vasily S. [Centre for Molecular and Structural Biochemistry, School of Chemistry, University of East Anglia, Norwich Research Park Norwich NR4 7TJ UK; Le Brun, Nick E. [Centre for Molecular and Structural Biochemistry, School of Chemistry, University of East Anglia, Norwich Research Park Norwich NR4 7TJ UK; Cramer, Stephen P. [Department of Chemistry, University of California, Davis CA 95616 USA; Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley CA 94720 USA

2016-10-25

The reaction of protein-bound iron–sulfur (Fe-S) clusters with nitric oxide (NO) plays key roles in NO-mediated toxicity and signaling. Elucidation of the mechanism of the reaction of NO with DNA regulatory proteins that contain Fe-S clusters has been hampered by a lack of information about the nature of the iron-nitrosyl products formed. Herein, we report nuclear resonance vibrational spectroscopy (NRVS) and density functional theory (DFT) calculations that identify NO reaction products in WhiD and NsrR, regulatory proteins that use a [4Fe-4S] cluster to sense NO. This work reveals that nitrosylation yields multiple products structurally related to Roussin's Red Ester (RRE, [Fe₂(NO)₄(Cys)₂]) and Roussin's Black Salt (RBS, [Fe₄(NO)₇S₃]. In the latter case, the absence of ³²S/³⁴S shifts in the Fe-S region of the NRVS spectra suggest that a new species, Roussin's Black Ester (RBE), may be formed, in which one or more of the sulfide ligands is replaced by Cys thiolates.

Annotating Protein Functional Residues by Coupling High-Throughput Fitness Profile and Homologous-Structure Analysis

Directory of Open Access Journals (Sweden)

Yushen Du

2016-11-01

Full Text Available Identification and annotation of functional residues are fundamental questions in protein sequence analysis. Sequence and structure conservation provides valuable information to tackle these questions. It is, however, limited by the incomplete sampling of sequence space in natural evolution. Moreover, proteins often have multiple functions, with overlapping sequences that present challenges to accurate annotation of the exact functions of individual residues by conservation-based methods. Using the influenza A virus PB1 protein as an example, we developed a method to systematically identify and annotate functional residues. We used saturation mutagenesis and high-throughput sequencing to measure the replication capacity of single nucleotide mutations across the entire PB1 protein. After predicting protein stability upon mutations, we identified functional PB1 residues that are essential for viral replication. To further annotate the functional residues important to the canonical or noncanonical functions of viral RNA-dependent RNA polymerase (vRdRp, we performed a homologous-structure analysis with 16 different vRdRp structures. We achieved high sensitivity in annotating the known canonical polymerase functional residues. Moreover, we identified a cluster of noncanonical functional residues located in the loop region of the PB1 β-ribbon. We further demonstrated that these residues were important for PB1 protein nuclear import through the interaction with Ran-binding protein 5. In summary, we developed a systematic and sensitive method to identify and annotate functional residues that are not restrained by sequence conservation. Importantly, this method is generally applicable to other proteins about which homologous-structure information is available.

The non-random clustering of non-synonymous substitutions and its relationship to evolutionary rate

Directory of Open Access Journals (Sweden)

Stone Eric A

2011-08-01

Full Text Available Abstract Background Protein sequences are subject to a mosaic of constraint. Changes to functional domains and buried residues, for example, are more apt to disrupt protein structure and function than are changes to residues participating in loops or exposed to solvent. Regions of constraint on the tertiary structure of a protein often result in loose segmentation of its primary structure into stretches of slowly- and rapidly-evolving amino acids. This clustering can be exploited, and existing methods have done so by relying on local sequence conservation as a signature of selection to help identify functionally important regions within proteins. We invert this paradigm by leveraging the regional nature of protein structure and function to both illuminate and make use of genome-wide patterns of local sequence conservation. Results Our hypothesis is that the regional nature of structural and functional constraints will assert a positive autocorrelation on the evolutionary rates of neighboring sites, which, in a pairwise comparison of orthologous proteins, will manifest itself as the clustering of non-synonymous changes across the amino acid sequence. We introduce a dispersion ratio statistic to test this and related hypotheses. Using genome-wide interspecific comparisons of orthologous protein pairs, we reveal a strong log-linear relationship between the degree of clustering and the intensity of constraint. We further demonstrate how this relationship varies with the evolutionary distance between the species being compared. We provide some evidence that proteins with a history of positive selection deviate from genome-wide trends. Conclusions We find a significant association between the evolutionary rate of a protein and the degree to which non-synonymous changes cluster along its primary sequence. We show that clustering is a non-redundant predictor of evolutionary rate, and we speculate that conflicting signals of clustering and constraint may

Protein-protein interaction network-based detection of functionally similar proteins within species.

Science.gov (United States)

Song, Baoxing; Wang, Fen; Guo, Yang; Sang, Qing; Liu, Min; Li, Dengyun; Fang, Wei; Zhang, Deli

2012-07-01

Although functionally similar proteins across species have been widely studied, functionally similar proteins within species showing low sequence similarity have not been examined in detail. Identification of these proteins is of significant importance for understanding biological functions, evolution of protein families, progression of co-evolution, and convergent evolution and others which cannot be obtained by detection of functionally similar proteins across species. Here, we explored a method of detecting functionally similar proteins within species based on graph theory. After denoting protein-protein interaction networks using graphs, we split the graphs into subgraphs using the 1-hop method. Proteins with functional similarities in a species were detected using a method of modified shortest path to compare these subgraphs and to find the eligible optimal results. Using seven protein-protein interaction networks and this method, some functionally similar proteins with low sequence similarity that cannot detected by sequence alignment were identified. By analyzing the results, we found that, sometimes, it is difficult to separate homologous from convergent evolution. Evaluation of the performance of our method by gene ontology term overlap showed that the precision of our method was excellent. Copyright © 2012 Wiley Periodicals, Inc.

Inelastic electron scattering as an indicator of clustering in wave functions

Energy Technology Data Exchange (ETDEWEB)

NONE

1998-09-01

While the shell model is the most fundamental of nuclear structure models, states in light nuclei also have been described successfully in terms of clusters. Indeed, Wildemuth and Tang have shown a correspondence between the cluster and shell models, the clusters arising naturally as correlations out of the shell model Hamiltonian. For light nuclei, the cluster model reduces the many-body problem to a few-body one, with interactions occurring between the clusters. These interactions involve particle exchanges, since the nucleons may still be considered somewhat freely moving, with their motion not strictly confined to the clusters themselves. Such is the relation of the cluster model to the shell model. For a realistic shell model then, one may expect some evidence of clustering in the wave functions for those systems in which the cluster model is valid. The results obtained using the multi-{Dirac_h}{omega}shell model wave functions are closer in agreement with experiment than the results obtained using the 0{Dirac_h}{omega}wave functions. Yet in all cases, that level of agreement is not good, with the calculations underpredicting the measured values by at least a factor of two. This indicates that the shell model wave functions do not exhibit clustering behavior, which is expected to manifest itself at small momentum transfer. The exception is the transition to the 7{sup -}/2 state in {sup 7}Li, for which the value obtained from the {gamma}-decay width is in agreement with the value obtained from the MK3W and (0 + 2 + 4){Dirac_h}{omega}shell model calculations 17 refs., 1 tab., 2 figs.

Evolution of the cluster x-ray luminosity function slope

International Nuclear Information System (INIS)

Henry, J.P.; Soltan, A.; Briel, U.; Gunn, J.E.

1982-01-01

We report the results of an X-ray survey of 58 clusters of galaxies at moderate and high redshifts. Using a luminosity-limited subsample of 25 objects, we find that to a redshift of 0.5 the slope (i.e., power-law index) of the luminosity function of distant clusters is independent of redshift and consistent with that of nearby clusters. The time scale for change in the slope must be greater than 9 billion years. We cannot measure the normalization of the luminosity function because our sample is not complete. We discuss the implications of our data for theoretical models. In particular, Perrenod's models with high Ω are excluded by the present data

Sifting through genomes with iterative-sequence clustering produces a large, phylogenetically diverse protein-family resource.

Science.gov (United States)

Sharpton, Thomas J; Jospin, Guillaume; Wu, Dongying; Langille, Morgan G I; Pollard, Katherine S; Eisen, Jonathan A

2012-10-13

New computational resources are needed to manage the increasing volume of biological data from genome sequencing projects. One fundamental challenge is the ability to maintain a complete and current catalog of protein diversity. We developed a new approach for the identification of protein families that focuses on the rapid discovery of homologous protein sequences. We implemented fully automated and high-throughput procedures to de novo cluster proteins into families based upon global alignment similarity. Our approach employs an iterative clustering strategy in which homologs of known families are sifted out of the search for new families. The resulting reduction in computational complexity enables us to rapidly identify novel protein families found in new genomes and to perform efficient, automated updates that keep pace with genome sequencing. We refer to protein families identified through this approach as "Sifting Families," or SFams. Our analysis of ~10.5 million protein sequences from 2,928 genomes identified 436,360 SFams, many of which are not represented in other protein family databases. We validated the quality of SFam clustering through statistical as well as network topology-based analyses. We describe the rapid identification of SFams and demonstrate how they can be used to annotate genomes and metagenomes. The SFam database catalogs protein-family quality metrics, multiple sequence alignments, hidden Markov models, and phylogenetic trees. Our source code and database are publicly available and will be subject to frequent updates (http://edhar.genomecenter.ucdavis.edu/sifting_families/).

Functional aspects of protein flexibility

DEFF Research Database (Denmark)

Teilum, Kaare; Olsen, Johan G; Kragelund, Birthe B

2009-01-01

this into an intuitive perception of protein function is challenging. Flexibility is of overwhelming importance for protein function, and the changes in protein structure during interactions with binding partners can be dramatic. The present review addresses protein flexibility, focusing on protein-ligand interactions...

Disabled is a putative adaptor protein that functions during signaling by the sevenless receptor tyrosine kinase.

Science.gov (United States)

Le, N; Simon, M A

1998-08-01

DRK, the Drosophila homolog of the SH2-SH3 domain adaptor protein Grb2, is required during signaling by the sevenless receptor tyrosine kinase (SEV). One role of DRK is to provide a link between activated SEV and the Ras1 activator SOS. We have investigated the possibility that DRK performs other functions by identifying additional DRK-binding proteins. We show that the phosphotyrosine-binding (PTB) domain-containing protein Disabled (DAB) binds to the DRK SH3 domains. DAB is expressed in the ommatidial clusters, and loss of DAB function disrupts ommatidial development. Moreover, reduction of DAB function attenuates signaling by a constitutively activated SEV. Our biochemical analysis suggests that DAB binds SEV directly via its PTB domain, becomes tyrosine phosphorylated upon SEV activation, and then serves as an adaptor protein for SH2 domain-containing proteins. Taken together, these results indicate that DAB is a novel component of the SEV signaling pathway.

Estimation of cluster stability using the theory of electron density functional

International Nuclear Information System (INIS)

Borisov, Yu.A.

1985-01-01

Prospects of using simple versions of the electron density functional for studying the energy characteristics of cluster compounds Was discussed. These types of cluster compounds were considered: clusters of Cs, Be, B, Sr, Cd, Sc, In, V, Tl, I elements as intermediate form between molecule and solid body, metalloorganic Mo, W, Tc, Re, Rn clusters and elementoorganic compounds of nido-cluster type. The problem concerning changes in the binding energy of homoatomic clusters depending on their size and three-dimensional structure was analysed

Identification and phylogeny of the tomato receptor-like proteins family

Directory of Open Access Journals (Sweden)

Ermis Yanes-Paz

2017-03-01

Full Text Available The receptor-like proteins (RLPs play multiple roles in development and defense. In the current work 75 RLPs were identified in tomato (Solanum lycopersicum L. using iterative BLAST searches and domain prediction. A phylogenetic tree including all the identified RLPs from tomato and some functionally characterized RLPs from other species was built to identify their putative homologues in tomato. We first tested whether C3-F-based phylogeny was a good indicator of functional relation between related proteins of different species. Indeed, the functionally characterized CLAVATA2 (CLV2, the maize ortholog FASCIATED EAR2 (FEA2 and a putative tomato CLV2 described in Uniprot clustered together, which validates the approach. Using this approach Solyc12g042760.1.1 was identified as the putative tomato homologue of TOO MANY MOUTHS (TMM. It was shown that proteins in the same cluster of the phylogenetic tree share functional relations since several clusters of functionally related proteins i.e. the Ve cluster, the Cf cluster, and the Eix clade were formed.   Keywords: phylogeny, receptors, RLP, tomato

Photoluminescence quenching of chemically functionalized porous silicon by a ruthenium cluster

Energy Technology Data Exchange (ETDEWEB)

Boukherroub, R.; Wayner, D.D.M. [Steacie Institute for Molecular Sciences, National Research Council of Canada, Ottawa, Ontario (Canada); Lockwood, D.J. [Institute for Microstructural Sciences, National Research Council of Canada, Ottawa, Ontario (Canada); Zargarian, D. [Chemistry Department, University of Montreal, C.P. 6128, succursale, Centre-ville, Montreal QC (Canada)

2003-05-01

This paper describes photoluminescence (PL) quenching of hydrogen-terminated and chemically derivatized porous silicon (PSi) nanostructures by a green ruthenium cluster (I). Chemisorption of freshly prepared PSi surfaces in a hexane solution of the Ru cluster for several days at room temperature led to a complete quenching of the PSi PL. The only visible PL was due to the original PL of the cluster. When the PSi surface functionalized with undecylenic acid was immersed in the same hexane solution of (I), the PSi PL was completely quenched and accompanied with a shift to a lower energy of the cluster PL. This shift was assigned to the formation of an ester linkage resulting from the nucleophilic attack of the PO anion of the cluster on the terminal acid functional group. (Abstract Copyright [2003], Wiley Periodicals, Inc.)

Photoluminescence quenching of chemically functionalized porous silicon by a ruthenium cluster

Science.gov (United States)

Boukherroub, R.; Wayner, D. D. M.; Lockwood, D. J.; Zargarian, D.

2003-05-01

This paper describes photoluminescence (PL) quenching of hydrogen-terminated and chemically derivatized porous silicon (PSi) nanostructures by a green ruthenium cluster (I). Chemisorption of freshly prepared PSi surfaces in a hexane solution of the Ru cluster for several days at room temperature led to a complete quenching of the PSi PL. The only visible PL was due to the original PL of the cluster. When the PSi surface functionalized with undecylenic acid was immersed in the same hexane solution of (I), the PSi PL was completely quenched and accompanied with a shift to a lower energy of the cluster PL. This shift was assigned to the formation of an ester linkage resulting from the nucleophilic attack of the PO anion of the cluster on the terminal acid functional group.

A Clustering-Based Automatic Transfer Function Design for Volume Visualization

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Tianjin Zhang

2016-01-01

Full Text Available The two-dimensional transfer functions (TFs designed based on intensity-gradient magnitude (IGM histogram are effective tools for the visualization and exploration of 3D volume data. However, traditional design methods usually depend on multiple times of trial-and-error. We propose a novel method for the automatic generation of transfer functions by performing the affinity propagation (AP clustering algorithm on the IGM histogram. Compared with previous clustering algorithms that were employed in volume visualization, the AP clustering algorithm has much faster convergence speed and can achieve more accurate clustering results. In order to obtain meaningful clustering results, we introduce two similarity measurements: IGM similarity and spatial similarity. These two similarity measurements can effectively bring the voxels of the same tissue together and differentiate the voxels of different tissues so that the generated TFs can assign different optical properties to different tissues. Before performing the clustering algorithm on the IGM histogram, we propose to remove noisy voxels based on the spatial information of voxels. Our method does not require users to input the number of clusters, and the classification and visualization process is automatic and efficient. Experiments on various datasets demonstrate the effectiveness of the proposed method.

Genomic Enzymology: Web Tools for Leveraging Protein Family Sequence-Function Space and Genome Context to Discover Novel Functions.

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Gerlt, John A

2017-08-22

The exponentially increasing number of protein and nucleic acid sequences provides opportunities to discover novel enzymes, metabolic pathways, and metabolites/natural products, thereby adding to our knowledge of biochemistry and biology. The challenge has evolved from generating sequence information to mining the databases to integrating and leveraging the available information, i.e., the availability of "genomic enzymology" web tools. Web tools that allow identification of biosynthetic gene clusters are widely used by the natural products/synthetic biology community, thereby facilitating the discovery of novel natural products and the enzymes responsible for their biosynthesis. However, many novel enzymes with interesting mechanisms participate in uncharacterized small-molecule metabolic pathways; their discovery and functional characterization also can be accomplished by leveraging information in protein and nucleic acid databases. This Perspective focuses on two genomic enzymology web tools that assist the discovery novel metabolic pathways: (1) Enzyme Function Initiative-Enzyme Similarity Tool (EFI-EST) for generating sequence similarity networks to visualize and analyze sequence-function space in protein families and (2) Enzyme Function Initiative-Genome Neighborhood Tool (EFI-GNT) for generating genome neighborhood networks to visualize and analyze the genome context in microbial and fungal genomes. Both tools have been adapted to other applications to facilitate target selection for enzyme discovery and functional characterization. As the natural products community has demonstrated, the enzymology community needs to embrace the essential role of web tools that allow the protein and genome sequence databases to be leveraged for novel insights into enzymological problems.

Mathematical model for research and analyze relations and functions between enterprises, members of cluster

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Angelov, Kiril; Kaynakchieva, Vesela

2017-12-01

The aim of the current study is to research and analyze Mathematical model for research and analyze of relations and functions between enterprises, members of cluster, and its approbation in given cluster. Subject of the study are theoretical mechanisms for the definition of mathematical models for research and analyze of relations and functions between enterprises, members of cluster. Object of the study are production enterprises, members of cluster. Results of this study show that described theoretical mathematical model is applicable for research and analyze of functions and relations between enterprises, members of cluster from different industrial sectors. This circumstance creates alternatives for election of cluster, where is experimented this model for interaction improvement between enterprises, members of cluster.

On the Power and Limits of Sequence Similarity Based Clustering of Proteins Into Families

DEFF Research Database (Denmark)

Wiwie, Christian; Röttger, Richard

2017-01-01

Over the last decades, we have observed an ongoing tremendous growth of available sequencing data fueled by the advancements in wet-lab technology. The sequencing information is only the beginning of the actual understanding of how organisms survive and prosper. It is, for instance, equally...... important to also unravel the proteomic repertoire of an organism. A classical computational approach for detecting protein families is a sequence-based similarity calculation coupled with a subsequent cluster analysis. In this work we have intensively analyzed various clustering tools on a large scale. We...... used the data to investigate the behavior of the tools' parameters underlining the diversity of the protein families. Furthermore, we trained regression models for predicting the expected performance of a clustering tool for an unknown data set and aimed to also suggest optimal parameters...

Towards understanding the first genome sequence of a crenarchaeon by genome annotation using clusters of orthologous groups of proteins (COGs).

Science.gov (United States)

Natale, D A; Shankavaram, U T; Galperin, M Y; Wolf, Y I; Aravind, L; Koonin, E V

2000-01-01

Standard archival sequence databases have not been designed as tools for genome annotation and are far from being optimal for this purpose. We used the database of Clusters of Orthologous Groups of proteins (COGs) to reannotate the genomes of two archaea, Aeropyrum pernix, the first member of the Crenarchaea to be sequenced, and Pyrococcus abyssi. A. pernix and P. abyssi proteins were assigned to COGs using the COGNITOR program; the results were verified on a case-by-case basis and augmented by additional database searches using the PSI-BLAST and TBLASTN programs. Functions were predicted for over 300 proteins from A. pernix, which could not be assigned a function using conventional methods with a conservative sequence similarity threshold, an approximately 50% increase compared to the original annotation. A. pernix shares most of the conserved core of proteins that were previously identified in the Euryarchaeota. Cluster analysis or distance matrix tree construction based on the co-occurrence of genomes in COGs showed that A. pernix forms a distinct group within the archaea, although grouping with the two species of Pyrococci, indicative of similar repertoires of conserved genes, was observed. No indication of a specific relationship between Crenarchaeota and eukaryotes was obtained in these analyses. Several proteins that are conserved in Euryarchaeota and most bacteria are unexpectedly missing in A. pernix, including the entire set of de novo purine biosynthesis enzymes, the GTPase FtsZ (a key component of the bacterial and euryarchaeal cell-division machinery), and the tRNA-specific pseudouridine synthase, previously considered universal. A. pernix is represented in 48 COGs that do not contain any euryarchaeal members. Many of these proteins are TCA cycle and electron transport chain enzymes, reflecting the aerobic lifestyle of A. pernix. Special-purpose databases organized on the basis of phylogenetic analysis and carefully curated with respect to known and

Molecular comparison of the structural proteins encoding gene clusters of two related Lactobacillus delbrueckii bacteriophages.

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Vasala, A; Dupont, L; Baumann, M; Ritzenthaler, P; Alatossava, T

1993-01-01

Virulent phage LL-H and temperate phage mv4 are two related bacteriophages of Lactobacillus delbrueckii. The gene clusters encoding structural proteins of these two phages have been sequenced and further analyzed. Six open reading frames (ORF-1 to ORF-6) were detected. Protein sequencing and Western immunoblotting experiments confirmed that ORF-3 (g34) encoded the main capsid protein Gp34. The presence of a putative late promoter in front of the phage LL-H g34 gene was suggested by primer extension experiments. Comparative sequence analysis between phage LL-H and phage mv4 revealed striking similarities in the structure and organization of this gene cluster, suggesting that the genes encoding phage structural proteins belong to a highly conservative module. Images PMID:8497043

Sifting through genomes with iterative-sequence clustering produces a large, phylogenetically diverse protein-family resource

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Sharpton Thomas J

2012-10-01

Full Text Available Abstract Background New computational resources are needed to manage the increasing volume of biological data from genome sequencing projects. One fundamental challenge is the ability to maintain a complete and current catalog of protein diversity. We developed a new approach for the identification of protein families that focuses on the rapid discovery of homologous protein sequences. Results We implemented fully automated and high-throughput procedures to de novo cluster proteins into families based upon global alignment similarity. Our approach employs an iterative clustering strategy in which homologs of known families are sifted out of the search for new families. The resulting reduction in computational complexity enables us to rapidly identify novel protein families found in new genomes and to perform efficient, automated updates that keep pace with genome sequencing. We refer to protein families identified through this approach as “Sifting Families,” or SFams. Our analysis of ~10.5 million protein sequences from 2,928 genomes identified 436,360 SFams, many of which are not represented in other protein family databases. We validated the quality of SFam clustering through statistical as well as network topology–based analyses. Conclusions We describe the rapid identification of SFams and demonstrate how they can be used to annotate genomes and metagenomes. The SFam database catalogs protein-family quality metrics, multiple sequence alignments, hidden Markov models, and phylogenetic trees. Our source code and database are publicly available and will be subject to frequent updates (http://edhar.genomecenter.ucdavis.edu/sifting_families/.

Proteomic-based detection of a protein cluster dysregulated during cardiovascular development identifies biomarkers of congenital heart defects.

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Anjali K Nath

Full Text Available Cardiovascular development is vital for embryonic survival and growth. Early gestation embryo loss or malformation has been linked to yolk sac vasculopathy and congenital heart defects (CHDs. However, the molecular pathways that underlie these structural defects in humans remain largely unknown hindering the development of molecular-based diagnostic tools and novel therapies.Murine embryos were exposed to high glucose, a condition known to induce cardiovascular defects in both animal models and humans. We further employed a mass spectrometry-based proteomics approach to identify proteins differentially expressed in embryos with defects from those with normal cardiovascular development. The proteins detected by mass spectrometry (WNT16, ST14, Pcsk1, Jumonji, Morca2a, TRPC5, and others were validated by Western blotting and immunoflorescent staining of the yolk sac and heart. The proteins within the proteomic dataset clustered to adhesion/migration, differentiation, transport, and insulin signaling pathways. A functional role for several proteins (WNT16, ADAM15 and NOGO-A/B was demonstrated in an ex vivo model of heart development. Additionally, a successful application of a cluster of protein biomarkers (WNT16, ST14 and Pcsk1 as a prenatal screen for CHDs was confirmed in a study of human amniotic fluid (AF samples from women carrying normal fetuses and those with CHDs.The novel finding that WNT16, ST14 and Pcsk1 protein levels increase in fetuses with CHDs suggests that these proteins may play a role in the etiology of human CHDs. The information gained through this bed-side to bench translational approach contributes to a more complete understanding of the protein pathways dysregulated during cardiovascular development and provides novel avenues for diagnostic and therapeutic interventions, beneficial to fetuses at risk for CHDs.

The transcriptional repressor protein NsrR senses nitric oxide directly via a [2Fe-2S] cluster.

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Nicholas P Tucker

Full Text Available The regulatory protein NsrR, a member of the Rrf2 family of transcription repressors, is specifically dedicated to sensing nitric oxide (NO in a variety of pathogenic and non-pathogenic bacteria. It has been proposed that NO directly modulates NsrR activity by interacting with a predicted [Fe-S] cluster in the NsrR protein, but no experimental evidence has been published to support this hypothesis. Here we report the purification of NsrR from the obligate aerobe Streptomyces coelicolor. We demonstrate using UV-visible, near UV CD and EPR spectroscopy that the protein contains an NO-sensitive [2Fe-2S] cluster when purified from E. coli. Upon exposure of NsrR to NO, the cluster is nitrosylated, which results in the loss of DNA binding activity as detected by bandshift assays. Removal of the [2Fe-2S] cluster to generate apo-NsrR also resulted in loss of DNA binding activity. This is the first demonstration that NsrR contains an NO-sensitive [2Fe-2S] cluster that is required for DNA binding activity.

Metaproteomics of Colonic Microbiota Unveils Discrete Protein Functions among Colitic Mice and Control Groups.

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Moon, Clara; Stupp, Gregory S; Su, Andrew I; Wolan, Dennis W

2018-02-01

Metaproteomics can greatly assist established high-throughput sequencing methodologies to provide systems biological insights into the alterations of microbial protein functionalities correlated with disease-associated dysbiosis of the intestinal microbiota. Here, the authors utilize the well-characterized murine T cell transfer model of colitis to find specific changes within the intestinal luminal proteome associated with inflammation. MS proteomic analysis of colonic samples permitted the identification of ≈10 000-12 000 unique peptides that corresponded to 5610 protein clusters identified across three groups, including the colitic Rag1 -/- T cell recipients, isogenic Rag1 -/- controls, and wild-type mice. The authors demonstrate that the colitic mice exhibited a significant increase in Proteobacteria and Verrucomicrobia and show that such alterations in the microbial communities contributed to the enrichment of specific proteins with transcription and translation gene ontology terms. In combination with 16S sequencing, the authors' metaproteomics-based microbiome studies provide a foundation for assessing alterations in intestinal luminal protein functionalities in a robust and well-characterized mouse model of colitis, and set the stage for future studies to further explore the functional mechanisms of altered protein functionalities associated with dysbiosis and inflammation. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Structural and functional characterization of solute binding proteins for aromatic compounds derived from lignin: p-coumaric acid and related aromatic acids.

Science.gov (United States)

Tan, Kemin; Chang, Changsoo; Cuff, Marianne; Osipiuk, Jerzy; Landorf, Elizabeth; Mack, Jamey C; Zerbs, Sarah; Joachimiak, Andrzej; Collart, Frank R

2013-10-01

Lignin comprises 15-25% of plant biomass and represents a major environmental carbon source for utilization by soil microorganisms. Access to this energy resource requires the action of fungal and bacterial enzymes to break down the lignin polymer into a complex assortment of aromatic compounds that can be transported into the cells. To improve our understanding of the utilization of lignin by microorganisms, we characterized the molecular properties of solute binding proteins of ATP-binding cassette transporter proteins that interact with these compounds. A combination of functional screens and structural studies characterized the binding specificity of the solute binding proteins for aromatic compounds derived from lignin such as p-coumarate, 3-phenylpropionic acid and compounds with more complex ring substitutions. A ligand screen based on thermal stabilization identified several binding protein clusters that exhibit preferences based on the size or number of aromatic ring substituents. Multiple X-ray crystal structures of protein-ligand complexes for these clusters identified the molecular basis of the binding specificity for the lignin-derived aromatic compounds. The screens and structural data provide new functional assignments for these solute-binding proteins which can be used to infer their transport specificity. This knowledge of the functional roles and molecular binding specificity of these proteins will support the identification of the specific enzymes and regulatory proteins of peripheral pathways that funnel these compounds to central metabolic pathways and will improve the predictive power of sequence-based functional annotation methods for this family of proteins. Copyright © 2013 Wiley Periodicals, Inc.

Cluster protein structures using recurrence quantification analysis on coordinates of alpha-carbon atoms of proteins

International Nuclear Information System (INIS)

Zhou Yu; Yu Zuguo; Anh, Vo

2007-01-01

The 3-dimensional coordinates of alpha-carbon atoms of proteins are used to distinguish the protein structural classes based on recurrence quantification analysis (RQA). We consider two independent variables from RQA of coordinates of alpha-carbon atoms, %determ1 and %determ2, which were defined by Webber et al. [C.L. Webber Jr., A. Giuliani, J.P. Zbilut, A. Colosimo, Proteins Struct. Funct. Genet. 44 (2001) 292]. The variable %determ2 is used to define two new variables, %determ2 1 and %determ2 2 . Then three variables %determ1, %determ2 1 and %determ2 2 are used to construct a 3-dimensional variable space. Each protein is represented by a point in this variable space. The points corresponding to proteins from the α, β, α+β and α/β structural classes position into different areas in this variable space. In order to give a quantitative assessment of our clustering on the selected proteins, Fisher's discriminant algorithm is used. Numerical results indicate that the discriminant accuracies are very high and satisfactory

Phylogenetic continuum indicates "galaxies" in the protein universe: preliminary results on the natural group structures of proteins.

Science.gov (United States)

Ladunga, I

1992-04-01

The markedly nonuniform, even systematic distribution of sequences in the protein "universe" has been analyzed by methods of protein taxonomy. Mapping of the natural hierarchical system of proteins has revealed some dense cores, i.e., well-defined clusterings of proteins that seem to be natural structural groupings, possibly seeds for a future protein taxonomy. The aim was not to force proteins into more or less man-made categories by discriminant analysis, but to find structurally similar groups, possibly of common evolutionary origin. Single-valued distance measures between pairs of superfamilies from the Protein Identification Resource were defined by two chi 2-like methods on tripeptide frequencies and the variable-length subsequence identity method derived from dot-matrix comparisons. Distance matrices were processed by several methods of cluster analysis to detect phylogenetic continuum between highly divergent proteins. Only well-defined clusters characterized by relatively unique structural, intracellular environmental, organismal, and functional attribute states were selected as major protein groups, including subsets of viral and Escherichia coli proteins, hormones, inhibitors, plant, ribosomal, serum and structural proteins, amino acid synthases, and clusters dominated by certain oxidoreductases and apolar and DNA-associated enzymes. The limited repertoire of functional patterns due to small genome size, the high rate of recombination, specific features of the bacterial membranes, or of the virus cycle canalize certain proteins of viruses and Gram-negative bacteria, respectively, to organismal groups.

Functional clustering of time series gene expression data by Granger causality

Science.gov (United States)

2012-01-01

Background A common approach for time series gene expression data analysis includes the clustering of genes with similar expression patterns throughout time. Clustered gene expression profiles point to the joint contribution of groups of genes to a particular cellular process. However, since genes belong to intricate networks, other features, besides comparable expression patterns, should provide additional information for the identification of functionally similar genes. Results In this study we perform gene clustering through the identification of Granger causality between and within sets of time series gene expression data. Granger causality is based on the idea that the cause of an event cannot come after its consequence. Conclusions This kind of analysis can be used as a complementary approach for functional clustering, wherein genes would be clustered not solely based on their expression similarity but on their topological proximity built according to the intensity of Granger causality among them. PMID:23107425

Novel Functions of MicroRNA-17-92 Cluster in the Endocrine System.

Science.gov (United States)

Wan, Shan; Chen, Xiang; He, Yuedong; Yu, Xijie

2018-01-01

MiR-17-92 cluster is coded by MIR17HG in chromosome 13, which is highly conserved in vertebrates. Published literatures have proved that miR-17-92 cluster critically regulates tumorigenesis and metastasis. Recent researches showed that the miR-17-92 cluster also plays novel functions in the endocrine system. To summarize recent findings on the physiological and pathological roles of miR-17-92 cluster in bone, lipid and glucose metabolisms. MiR-17-92 cluster plays significant regulatory roles in bone development and metabolism through regulating the differentiation and function of osteoblasts and osteoclasts. In addition, miR-17- 92 cluster is nearly involved in every aspect of lipid metabolism. Last but not the least, the miR-17-92 cluster is closely bound up with pancreatic beta cell function, development of type 1 diabetes and insulin resistance. However, whether miR-17-92 cluster is involved in the communication among bone, fat and glucose metabolisms remains unknown. Growing evidence indicates that miR-17-92 cluster plays significant roles in bone, lipid and glucose metabolisms through a variety of signaling pathways. Fully understanding its modulating mechanisms may necessarily facilitate to comprehend the clinical and molecule features of some metabolic disorders such as osteoporosis, arthrosclerosis and diabetes mellitus. It may provide new drug targets to prevent and cure these disorders. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Annotating Protein Functional Residues by Coupling High-Throughput Fitness Profile and Homologous-Structure Analysis.

Science.gov (United States)

Du, Yushen; Wu, Nicholas C; Jiang, Lin; Zhang, Tianhao; Gong, Danyang; Shu, Sara; Wu, Ting-Ting; Sun, Ren

2016-11-01

Identification and annotation of functional residues are fundamental questions in protein sequence analysis. Sequence and structure conservation provides valuable information to tackle these questions. It is, however, limited by the incomplete sampling of sequence space in natural evolution. Moreover, proteins often have multiple functions, with overlapping sequences that present challenges to accurate annotation of the exact functions of individual residues by conservation-based methods. Using the influenza A virus PB1 protein as an example, we developed a method to systematically identify and annotate functional residues. We used saturation mutagenesis and high-throughput sequencing to measure the replication capacity of single nucleotide mutations across the entire PB1 protein. After predicting protein stability upon mutations, we identified functional PB1 residues that are essential for viral replication. To further annotate the functional residues important to the canonical or noncanonical functions of viral RNA-dependent RNA polymerase (vRdRp), we performed a homologous-structure analysis with 16 different vRdRp structures. We achieved high sensitivity in annotating the known canonical polymerase functional residues. Moreover, we identified a cluster of noncanonical functional residues located in the loop region of the PB1 β-ribbon. We further demonstrated that these residues were important for PB1 protein nuclear import through the interaction with Ran-binding protein 5. In summary, we developed a systematic and sensitive method to identify and annotate functional residues that are not restrained by sequence conservation. Importantly, this method is generally applicable to other proteins about which homologous-structure information is available. To fully comprehend the diverse functions of a protein, it is essential to understand the functionality of individual residues. Current methods are highly dependent on evolutionary sequence conservation, which is

Genome cluster database. A sequence family analysis platform for Arabidopsis and rice.

Science.gov (United States)

Horan, Kevin; Lauricha, Josh; Bailey-Serres, Julia; Raikhel, Natasha; Girke, Thomas

2005-05-01

The genome-wide protein sequences from Arabidopsis (Arabidopsis thaliana) and rice (Oryza sativa) spp. japonica were clustered into families using sequence similarity and domain-based clustering. The two fundamentally different methods resulted in separate cluster sets with complementary properties to compensate the limitations for accurate family analysis. Functional names for the identified families were assigned with an efficient computational approach that uses the description of the most common molecular function gene ontology node within each cluster. Subsequently, multiple alignments and phylogenetic trees were calculated for the assembled families. All clustering results and their underlying sequences were organized in the Web-accessible Genome Cluster Database (http://bioinfo.ucr.edu/projects/GCD) with rich interactive and user-friendly sequence family mining tools to facilitate the analysis of any given family of interest for the plant science community. An automated clustering pipeline ensures current information for future updates in the annotations of the two genomes and clustering improvements. The analysis allowed the first systematic identification of family and singlet proteins present in both organisms as well as those restricted to one of them. In addition, the established Web resources for mining these data provide a road map for future studies of the composition and structure of protein families between the two species.

Cluster-cluster clustering

International Nuclear Information System (INIS)

Barnes, J.; Dekel, A.; Efstathiou, G.; Frenk, C.S.; Yale Univ., New Haven, CT; California Univ., Santa Barbara; Cambridge Univ., England; Sussex Univ., Brighton, England)

1985-01-01

The cluster correlation function xi sub c(r) is compared with the particle correlation function, xi(r) in cosmological N-body simulations with a wide range of initial conditions. The experiments include scale-free initial conditions, pancake models with a coherence length in the initial density field, and hybrid models. Three N-body techniques and two cluster-finding algorithms are used. In scale-free models with white noise initial conditions, xi sub c and xi are essentially identical. In scale-free models with more power on large scales, it is found that the amplitude of xi sub c increases with cluster richness; in this case the clusters give a biased estimate of the particle correlations. In the pancake and hybrid models (with n = 0 or 1), xi sub c is steeper than xi, but the cluster correlation length exceeds that of the points by less than a factor of 2, independent of cluster richness. Thus the high amplitude of xi sub c found in studies of rich clusters of galaxies is inconsistent with white noise and pancake models and may indicate a primordial fluctuation spectrum with substantial power on large scales. 30 references

The Bologna Annotation Resource (BAR 3.0): improving protein functional annotation.

Science.gov (United States)

Profiti, Giuseppe; Martelli, Pier Luigi; Casadio, Rita

2017-07-03

BAR 3.0 updates our server BAR (Bologna Annotation Resource) for predicting protein structural and functional features from sequence. We increase data volume, query capabilities and information conveyed to the user. The core of BAR 3.0 is a graph-based clustering procedure of UniProtKB sequences, following strict pairwise similarity criteria (sequence identity ≥40% with alignment coverage ≥90%). Each cluster contains the available annotation downloaded from UniProtKB, GO, PFAM and PDB. After statistical validation, GO terms and PFAM domains are cluster-specific and annotate new sequences entering the cluster after satisfying similarity constraints. BAR 3.0 includes 28 869 663 sequences in 1 361 773 clusters, of which 22.2% (22 241 661 sequences) and 47.4% (24 555 055 sequences) have at least one validated GO term and one PFAM domain, respectively. 1.4% of the clusters (36% of all sequences) include PDB structures and the cluster is associated to a hidden Markov model that allows building template-target alignment suitable for structural modeling. Some other 3 399 026 sequences are singletons. BAR 3.0 offers an improved search interface, allowing queries by UniProtKB-accession, Fasta sequence, GO-term, PFAM-domain, organism, PDB and ligand/s. When evaluated on the CAFA2 targets, BAR 3.0 largely outperforms our previous version and scores among state-of-the-art methods. BAR 3.0 is publicly available and accessible at http://bar.biocomp.unibo.it/bar3. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Analysis of ligand-protein exchange by Clustering of Ligand Diffusion Coefficient Pairs (CoLD-CoP)

Science.gov (United States)

Snyder, David A.; Chantova, Mihaela; Chaudhry, Saadia

2015-06-01

NMR spectroscopy is a powerful tool in describing protein structures and protein activity for pharmaceutical and biochemical development. This study describes a method to determine weak binding ligands in biological systems by using hierarchic diffusion coefficient clustering of multidimensional data obtained with a 400 MHz Bruker NMR. Comparison of DOSY spectrums of ligands of the chemical library in the presence and absence of target proteins show translational diffusion rates for small molecules upon interaction with macromolecules. For weak binders such as compounds found in fragment libraries, changes in diffusion rates upon macromolecular binding are on the order of the precision of DOSY diffusion measurements, and identifying such subtle shifts in diffusion requires careful statistical analysis. The "CoLD-CoP" (Clustering of Ligand Diffusion Coefficient Pairs) method presented here uses SAHN clustering to identify protein-binders in a chemical library or even a not fully characterized metabolite mixture. We will show how DOSY NMR and the "CoLD-CoP" method complement each other in identifying the most suitable candidates for lysozyme and wheat germ acid phosphatase.

Protein kinase substrate identification on functional protein arrays

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Zhou Fang

2008-02-01

Full Text Available Abstract Background Over the last decade, kinases have emerged as attractive therapeutic targets for a number of different diseases, and numerous high throughput screening efforts in the pharmaceutical community are directed towards discovery of compounds that regulate kinase function. The emerging utility of systems biology approaches has necessitated the development of multiplex tools suitable for proteomic-scale experiments to replace lower throughput technologies such as mass spectroscopy for the study of protein phosphorylation. Recently, a new approach for identifying substrates of protein kinases has applied the miniaturized format of functional protein arrays to characterize phosphorylation for thousands of candidate protein substrates in a single experiment. This method involves the addition of protein kinases in solution to arrays of immobilized proteins to identify substrates using highly sensitive radioactive detection and hit identification algorithms. Results To date, the factors required for optimal performance of protein array-based kinase substrate identification have not been described. In the current study, we have carried out a detailed characterization of the protein array-based method for kinase substrate identification, including an examination of the effects of time, buffer compositions, and protein concentration on the results. The protein array approach was compared to standard solution-based assays for assessing substrate phosphorylation, and a correlation of greater than 80% was observed. The results presented here demonstrate how novel substrates for protein kinases can be quickly identified from arrays containing thousands of human proteins to provide new clues to protein kinase function. In addition, a pooling-deconvolution strategy was developed and applied that enhances characterization of specific kinase-substrate relationships and decreases reagent consumption. Conclusion Functional protein microarrays are an

Frataxin Is Localized to Both the Chloroplast and Mitochondrion and Is Involved in Chloroplast Fe-S Protein Function in Arabidopsis.

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Valeria R Turowski

Full Text Available Frataxin plays a key role in eukaryotic cellular iron metabolism, particularly in mitochondrial heme and iron-sulfur (Fe-S cluster biosynthesis. However, its precise role has yet to be elucidated. In this work, we studied the subcellular localization of Arabidopsis frataxin, AtFH, using confocal microscopy, and found a novel dual localization for this protein. We demonstrate that plant frataxin is targeted to both the mitochondria and the chloroplast, where it may play a role in Fe-S cluster metabolism as suggested by functional studies on nitrite reductase (NIR and ferredoxin (Fd, two Fe-S containing chloroplast proteins, in AtFH deficient plants. Our results indicate that frataxin deficiency alters the normal functioning of chloroplasts by affecting the levels of Fe, chlorophyll, and the photosynthetic electron transport chain in this organelle.

Cluster based on sequence comparison of homologous proteins of 95 organism species - Gclust Server | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available List Contact us Gclust Server Cluster based on sequence comparison of homologous proteins of 95 organism spe...cies Data detail Data name Cluster based on sequence comparison of homologous proteins of 95 organism specie...istory of This Database Site Policy | Contact Us Cluster based on sequence compariso

An interaction of the functionalized closo-borates with albumins: The protein fluorescence quenching and calorimetry study

International Nuclear Information System (INIS)

Losytskyy, Mykhaylo Yu.; Kovalska, Vladyslava B.; Varzatskii, Oleg A.; Kuperman, Marina V.; Potocki, Slawomir; Gumienna-Kontecka, Elzbieta; Zhdanov, Andrey P.; Yarmoluk, Sergiy M.; Voloshin, Yan Z.; Zhizhin, Konstantin Yu.; Kuznetsov, Nikolai T.; Elskaya, Anna V.

2016-01-01

An interaction of the boron clusters closo-borates K 2 [B 10 H 10 ], K 2 [B 12 H 12 ] and their functionalized derivatives with serum proteins human (HSA) and bovine (BSA) albumins and immonoglobulin IgG as well as globular proteins β-lactoglobulin and lysozyme was characterized. The steady state and time resolved protein fluorescence quenching studies point on the binding of the closo-borate arylamine derivatives to serum albumins and discrimination of other proteins. The mechanism of the albumin fluorescence quenching by the closo-borate arylamine derivatives was proposed. The complex formation between albumin and the closo-borate molecules has been confirmed by isothermal titration calorimetry (ITC). The compound (K 2 [B 10 H 10 ]) and its arylamine derivative both interact with HSA, have close values of K a (1.4 and 1.2×10 3 M −1 respectively) and Gibbs energy (−17.9 and −17.5 kJ/mol respectively). However, the arylamine derivative forms complex with the higher guest/host binding ratio (4:1) comparing to the parent closo-borate (2:1). - Highlights: • Complex formation between boron clusters closo-borates and albumins was confirmed. • Functional substituent of closo-borate strongly affects its complex with albumins. • Binding of arylamine closo-borates essentially quench the albumin fluorescence. • Mechanism of tryptophan emission quenching by arylamine closo-borates was proposed.

Interaction of the iron–sulfur cluster assembly protein IscU with the Hsc66/Hsc20 molecular chaperone system of Escherichia coli

Science.gov (United States)

Hoff, Kevin G.; Silberg, Jonathan J.; Vickery, Larry E.

2000-01-01

The iscU gene in bacteria is located in a gene cluster encoding proteins implicated in iron–sulfur cluster assembly and an hsc70-type (heat shock cognate) molecular chaperone system, iscSUA-hscBA. To investigate possible interactions between these systems, we have overproduced and purified the IscU protein from Escherichia coli and have studied its interactions with the hscA and hscB gene products Hsc66 and Hsc20. IscU and its iron–sulfur complex (IscU–Fe/S) stimulated the basal steady-state ATPase activity of Hsc66 weakly in the absence of Hsc20 but, in the presence of Hsc20, increased the ATPase activity up to 480-fold. Hsc20 also decreased the apparent Km for IscU stimulation of Hsc66 ATPase activity, and surface plasmon resonance studies revealed that Hsc20 enhances binding of IscU to Hsc66. Surface plasmon resonance and isothermal titration calorimetry further showed that IscU and Hsc20 form a complex, and Hsc20 may thereby aid in the targeting of IscU to Hsc66. These results establish a direct and specific role for the Hsc66/Hsc20 chaperone system in functioning with isc gene components for the assembly of iron–sulfur cluster proteins. PMID:10869428

Using hierarchical clustering of secreted protein families to classify and rank candidate effectors of rust fungi.

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Diane G O Saunders

Full Text Available Rust fungi are obligate biotrophic pathogens that cause considerable damage on crop plants. Puccinia graminis f. sp. tritici, the causal agent of wheat stem rust, and Melampsora larici-populina, the poplar leaf rust pathogen, have strong deleterious impacts on wheat and poplar wood production, respectively. Filamentous pathogens such as rust fungi secrete molecules called disease effectors that act as modulators of host cell physiology and can suppress or trigger host immunity. Current knowledge on effectors from other filamentous plant pathogens can be exploited for the characterisation of effectors in the genome of recently sequenced rust fungi. We designed a comprehensive in silico analysis pipeline to identify the putative effector repertoire from the genome of two plant pathogenic rust fungi. The pipeline is based on the observation that known effector proteins from filamentous pathogens have at least one of the following properties: (i contain a secretion signal, (ii are encoded by in planta induced genes, (iii have similarity to haustorial proteins, (iv are small and cysteine rich, (v contain a known effector motif or a nuclear localization signal, (vi are encoded by genes with long intergenic regions, (vii contain internal repeats, and (viii do not contain PFAM domains, except those associated with pathogenicity. We used Markov clustering and hierarchical clustering to classify protein families of rust pathogens and rank them according to their likelihood of being effectors. Using this approach, we identified eight families of candidate effectors that we consider of high value for functional characterization. This study revealed a diverse set of candidate effectors, including families of haustorial expressed secreted proteins and small cysteine-rich proteins. This comprehensive classification of candidate effectors from these devastating rust pathogens is an initial step towards probing plant germplasm for novel resistance components.

Comparing Residue Clusters from Thermophilic and Mesophilic Enzymes Reveals Adaptive Mechanisms.

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Sammond, Deanne W; Kastelowitz, Noah; Himmel, Michael E; Yin, Hang; Crowley, Michael F; Bomble, Yannick J

2016-01-01

Understanding how proteins adapt to function at high temperatures is important for deciphering the energetics that dictate protein stability and folding. While multiple principles important for thermostability have been identified, we lack a unified understanding of how internal protein structural and chemical environment determine qualitative or quantitative impact of evolutionary mutations. In this work we compare equivalent clusters of spatially neighboring residues between paired thermophilic and mesophilic homologues to evaluate adaptations under the selective pressure of high temperature. We find the residue clusters in thermophilic enzymes generally display improved atomic packing compared to mesophilic enzymes, in agreement with previous research. Unlike residue clusters from mesophilic enzymes, however, thermophilic residue clusters do not have significant cavities. In addition, anchor residues found in many clusters are highly conserved with respect to atomic packing between both thermophilic and mesophilic enzymes. Thus the improvements in atomic packing observed in thermophilic homologues are not derived from these anchor residues but from neighboring positions, which may serve to expand optimized protein core regions.

Canola/rapeseed protein-functionality and nutrition

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Wanasundara Janitha P.D.

2016-07-01

Full Text Available Protein rich meal is a valuable co-product of canola/rapeseed oil extraction. Seed storage proteins that include cruciferin (11S and napin (2S dominate the protein complement of canola while oleosins, lipid transfer proteins and other minor proteins of non-storage nature are also found. Although oil-free canola meal contains 36–40% protein on a dry weight basis, non-protein components including fibre, polymeric phenolics, phytates and sinapine, etc. of the seed coat and cellular components make protein less suitable for food use. Separation of canola protein from non-protein components is a technical challenge but necessary to obtain full nutritional and functional potential of protein. Process conditions of raw material and protein preparation are critical of nutritional and functional value of the final protein product. The storage proteins of canola can satisfy many nutritional and functional requirements for food applications. Protein macromolecules of canola also provide functionalities required in applications beyond edible uses; there exists substantial potential as a source of plant protein and a renewable biopolymer. Available information at present is mostly based on the protein products that can be obtained as mixtures of storage protein types and other chemical constituents of the seed; therefore, full potential of canola storage proteins is yet to be revealed.

The Mass Function of Young Star Clusters in the "Antennae" Galaxies.

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Zhang; Fall

1999-12-20

We determine the mass function of young star clusters in the merging galaxies known as the "Antennae" (NGC 4038/9) from deep images taken with the Wide Field Planetary Camera 2 on the refurbished Hubble Space Telescope. This is accomplished by means of reddening-free parameters and a comparison with stellar population synthesis tracks to estimate the intrinsic luminosity and age, and hence the mass, of each cluster. We find that the mass function of the young star clusters (with ages less, similar160 Myr) is well represented by a power law of the form psi&parl0;M&parr0;~M-2 over the range 104 less, similarM less, similar106 M middle dot in circle. This result may have important implications for our understanding of the origin of globular clusters during the early phases of galactic evolution.

Pulse laser-induced generation of cluster codes from metal nanoparticles for immunoassay applications

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Chia-Yin Chang

2017-05-01

Full Text Available In this work, we have developed an assay for the detection of proteins by functionalized nanomaterials coupled with laser-induced desorption/ionization mass spectrometry (LDI-MS by monitoring the generation of metal cluster ions. We achieved selective detection of three proteins [thrombin, vascular endothelial growth factor-A165 (VEGF-A165, and platelet-derived growth factor-BB (PDGF-BB] by modifying nanoparticles (NPs of three different metals (Au, Ag, and Pt with the corresponding aptamer or antibody in one assay. The Au, Ag, and Pt acted as metal bio-codes for the analysis of thrombin, VEGF-A165, and PDGF-BB, respectively, and a microporous cellulose acetate membrane (CAM served as a medium for an in situ separation of target protein-bound and -unbound NPs. The functionalized metal nanoparticles bound to their specific proteins were subjected to LDI-MS on the CAM. The functional nanoparticles/CAM system can function as a signal transducer and amplifier by transforming the protein concentration into an intense metal cluster ion signal during LDI-MS analysis. This system can selectively detect proteins at picomolar concentrations. Most importantly, the system has great potential for the detection of multiple proteins without any pre-concentration, separation, or purification process because LDI-MS coupled with CAM effectively removes all signals except for those from the metal cluster ions.

Diffusion Geometry Unravels the Emergence of Functional Clusters in Collective Phenomena

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De Domenico, Manlio

2017-04-01

Collective phenomena emerge from the interaction of natural or artificial units with a complex organization. The interplay between structural patterns and dynamics might induce functional clusters that, in general, are different from topological ones. In biological systems, like the human brain, the overall functionality is often favored by the interplay between connectivity and synchronization dynamics, with functional clusters that do not coincide with anatomical modules in most cases. In social, sociotechnical, and engineering systems, the quest for consensus favors the emergence of clusters. Despite the unquestionable evidence for mesoscale organization of many complex systems and the heterogeneity of their interconnectivity, a way to predict and identify the emergence of functional modules in collective phenomena continues to elude us. Here, we propose an approach based on random walk dynamics to define the diffusion distance between any pair of units in a networked system. Such a metric allows us to exploit the underlying diffusion geometry to provide a unifying framework for the intimate relationship between metastable synchronization, consensus, and random search dynamics in complex networks, pinpointing the functional mesoscale organization of synthetic and biological systems.

Origins of Protein Functions in Cells

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Seelig, Burchard; Pohorille, Andrzej

2011-01-01

In modern organisms proteins perform a majority of cellular functions, such as chemical catalysis, energy transduction and transport of material across cell walls. Although great strides have been made towards understanding protein evolution, a meaningful extrapolation from contemporary proteins to their earliest ancestors is virtually impossible. In an alternative approach, the origin of water-soluble proteins was probed through the synthesis and in vitro evolution of very large libraries of random amino acid sequences. In combination with computer modeling and simulations, these experiments allow us to address a number of fundamental questions about the origins of proteins. Can functionality emerge from random sequences of proteins? How did the initial repertoire of functional proteins diversify to facilitate new functions? Did this diversification proceed primarily through drawing novel functionalities from random sequences or through evolution of already existing proto-enzymes? Did protein evolution start from a pool of proteins defined by a frozen accident and other collections of proteins could start a different evolutionary pathway? Although we do not have definitive answers to these questions yet, important clues have been uncovered. In one example (Keefe and Szostak, 2001), novel ATP binding proteins were identified that appear to be unrelated in both sequence and structure to any known ATP binding proteins. One of these proteins was subsequently redesigned computationally to bind GTP through introducing several mutations that introduce targeted structural changes to the protein, improve its binding to guanine and prevent water from accessing the active center. This study facilitates further investigations of individual evolutionary steps that lead to a change of function in primordial proteins. In a second study (Seelig and Szostak, 2007), novel enzymes were generated that can join two pieces of RNA in a reaction for which no natural enzymes are known

Computer analysis of protein functional sites projection on exon structure of genes in Metazoa.

Science.gov (United States)

Medvedeva, Irina V; Demenkov, Pavel S; Ivanisenko, Vladimir A

2015-01-01

Study of the relationship between the structural and functional organization of proteins and their coding genes is necessary for an understanding of the evolution of molecular systems and can provide new knowledge for many applications for designing proteins with improved medical and biological properties. It is well known that the functional properties of proteins are determined by their functional sites. Functional sites are usually represented by a small number of amino acid residues that are distantly located from each other in the amino acid sequence. They are highly conserved within their functional group and vary significantly in structure between such groups. According to this facts analysis of the general properties of the structural organization of the functional sites at the protein level and, at the level of exon-intron structure of the coding gene is still an actual problem. One approach to this analysis is the projection of amino acid residue positions of the functional sites along with the exon boundaries to the gene structure. In this paper, we examined the discontinuity of the functional sites in the exon-intron structure of genes and the distribution of lengths and phases of the functional site encoding exons in vertebrate genes. We have shown that the DNA fragments coding the functional sites were in the same exons, or in close exons. The observed tendency to cluster the exons that code functional sites which could be considered as the unit of protein evolution. We studied the characteristics of the structure of the exon boundaries that code, and do not code, functional sites in 11 Metazoa species. This is accompanied by a reduced frequency of intercodon gaps (phase 0) in exons encoding the amino acid residue functional site, which may be evidence of the existence of evolutionary limitations to the exon shuffling. These results characterize the features of the coding exon-intron structure that affect the functionality of the encoded protein and

Application of clustering methods: Regularized Markov clustering (R-MCL) for analyzing dengue virus similarity

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Lestari, D.; Raharjo, D.; Bustamam, A.; Abdillah, B.; Widhianto, W.

2017-07-01

Dengue virus consists of 10 different constituent proteins and are classified into 4 major serotypes (DEN 1 - DEN 4). This study was designed to perform clustering against 30 protein sequences of dengue virus taken from Virus Pathogen Database and Analysis Resource (VIPR) using Regularized Markov Clustering (R-MCL) algorithm and then we analyze the result. By using Python program 3.4, R-MCL algorithm produces 8 clusters with more than one centroid in several clusters. The number of centroid shows the density level of interaction. Protein interactions that are connected in a tissue, form a complex protein that serves as a specific biological process unit. The analysis of result shows the R-MCL clustering produces clusters of dengue virus family based on the similarity role of their constituent protein, regardless of serotypes.

Function analysis of 5'-UTR of the cellulosomal xyl-doc cluster in Clostridium papyrosolvens.

Science.gov (United States)

Zou, Xia; Ren, Zhenxing; Wang, Na; Cheng, Yin; Jiang, Yuanyuan; Wang, Yan; Xu, Chenggang

2018-01-01

Anaerobic, mesophilic, and cellulolytic Clostridium papyrosolvens produces an efficient cellulolytic extracellular complex named cellulosome that hydrolyzes plant cell wall polysaccharides into simple sugars. Its genome harbors two long cellulosomal clusters: cip - cel operon encoding major cellulosome components (including scaffolding) and xyl - doc gene cluster encoding hemicellulases. Compared with works on cip - cel operon, there are much fewer studies on xyl - doc mainly due to its rare location in cellulolytic clostridia. Sequence analysis of xyl - doc revealed that it harbors a 5' untranslated region (5'-UTR) which potentially plays a role in the regulation of downstream gene expression. Here, we analyzed the function of 5'-UTR of xyl - doc cluster in C. papyrosolvens in vivo via transformation technology developed in this study. In this study, we firstly developed an electrotransformation method for C. papyrosolvens DSM 2782 before the analysis of 5'-UTR of xyl - doc cluster. In the optimized condition, a field with an intensity of 7.5-9.0 kV/cm was applied to a cuvette (0.2 cm gap) containing a mixture of plasmid and late cell suspended in exponential phase to form a 5 ms pulse in a sucrose-containing buffer. Afterwards, the putative promoter and the 5'-UTR of xyl - doc cluster were determined by sequence alignment. It is indicated that xyl - doc possesses a long conservative 5'-UTR with a complex secondary structure encompassing at least two perfect stem-loops which are potential candidates for controlling the transcriptional termination. In the last step, we employed an oxygen-independent flavin-based fluorescent protein (FbFP) as a quantitative reporter to analyze promoter activity and 5'-UTR function in vivo. It revealed that 5'-UTR significantly blocked transcription of downstream genes, but corn stover can relieve its suppression. In the present study, our results demonstrated that 5'-UTR of the cellulosomal xyl - doc cluster blocks the

Antisymmetrized four-body wave function and coexistence of single particle and cluster structures

International Nuclear Information System (INIS)

Sasakawa, T.

1979-01-01

It is shown that each Yakubovski component of the totally antisymmetric four-body wave function satisfies the same equation as the unantisymmetric wave function. In the antisymmetric total wave function, the wave functions belonging to the same kind of partition are totally antisymmetric among themselves. This leads to the coexistence of cluster models, including the single particle model as a special case of the cluster model, as a sum

Protein-protein interface detection using the energy centrality relationship (ECR characteristic of proteins.

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Sanjana Sudarshan

Full Text Available Specific protein interactions are responsible for most biological functions. Distinguishing Functionally Linked Interfaces of Proteins (FLIPs, from Functionally uncorrelated Contacts (FunCs, is therefore important to characterizing these interactions. To achieve this goal, we have created a database of protein structures called FLIPdb, containing proteins belonging to various functional sub-categories. Here, we use geometric features coupled with Kortemme and Baker's computational alanine scanning method to calculate the energetic sensitivity of each amino acid at the interface to substitution, identify hotspots, and identify other factors that may contribute towards an interface being FLIP or FunC. Using Principal Component Analysis and K-means clustering on a training set of 160 interfaces, we could distinguish FLIPs from FunCs with an accuracy of 76%. When these methods were applied to two test sets of 18 and 170 interfaces, we achieved similar accuracies of 78% and 80%. We have identified that FLIP interfaces have a stronger central organizing tendency than FunCs, due, we suggest, to greater specificity. We also observe that certain functional sub-categories, such as enzymes, antibody-heavy-light, antibody-antigen, and enzyme-inhibitors form distinct sub-clusters. The antibody-antigen and enzyme-inhibitors interfaces have patterns of physical characteristics similar to those of FunCs, which is in agreement with the fact that the selection pressures of these interfaces is differently evolutionarily driven. As such, our ECR model also successfully describes the impact of evolution and natural selection on protein-protein interfaces. Finally, we indicate how our ECR method may be of use in reducing the false positive rate of docking calculations.

Functional assignment to JEV proteins using SVM.

Science.gov (United States)

Sahoo, Ganesh Chandra; Dikhit, Manas Ranjan; Das, Pradeep

2008-01-01

Identification of different protein functions facilitates a mechanistic understanding of Japanese encephalitis virus (JEV) infection and opens novel means for drug development. Support vector machines (SVM), useful for predicting the functional class of distantly related proteins, is employed to ascribe a possible functional class to Japanese encephalitis virus protein. Our study from SVMProt and available JE virus sequences suggests that structural and nonstructural proteins of JEV genome possibly belong to diverse protein functions, are expected to occur in the life cycle of JE virus. Protein functions common to both structural and non-structural proteins are iron-binding, metal-binding, lipid-binding, copper-binding, transmembrane, outer membrane, channels/Pores - Pore-forming toxins (proteins and peptides) group of proteins. Non-structural proteins perform functions like actin binding, zinc-binding, calcium-binding, hydrolases, Carbon-Oxygen Lyases, P-type ATPase, proteins belonging to major facilitator family (MFS), secreting main terminal branch (MTB) family, phosphotransfer-driven group translocators and ATP-binding cassette (ABC) family group of proteins. Whereas structural proteins besides belonging to same structural group of proteins (capsid, structural, envelope), they also perform functions like nuclear receptor, antibiotic resistance, RNA-binding, DNA-binding, magnesium-binding, isomerase (intra-molecular), oxidoreductase and participate in type II (general) secretory pathway (IISP).

Protein domain recurrence and order can enhance prediction of protein functions

KAUST Repository

Abdel Messih, Mario A.

2012-09-07

Motivation: Burgeoning sequencing technologies have generated massive amounts of genomic and proteomic data. Annotating the functions of proteins identified in this data has become a big and crucial problem. Various computational methods have been developed to infer the protein functions based on either the sequences or domains of proteins. The existing methods, however, ignore the recurrence and the order of the protein domains in this function inference. Results: We developed two new methods to infer protein functions based on protein domain recurrence and domain order. Our first method, DRDO, calculates the posterior probability of the Gene Ontology terms based on domain recurrence and domain order information, whereas our second method, DRDO-NB, relies on the nave Bayes methodology using the same domain architecture information. Our large-scale benchmark comparisons show strong improvements in the accuracy of the protein function inference achieved by our new methods, demonstrating that domain recurrence and order can provide important information for inference of protein functions. The Author(s) 2012. Published by Oxford University Press.

Functional Interference Clusters in Cancer Patients With Bone Metastases: A Secondary Analysis of RTOG 9714

International Nuclear Information System (INIS)

Chow, Edward; James, Jennifer; Barsevick, Andrea; Hartsell, William; Ratcliffe, Sarah; Scarantino, Charles; Ivker, Robert; Roach, Mack; Suh, John; Petersen, Ivy; Konski, Andre; Demas, William; Bruner, Deborah

2010-01-01

Purpose: To explore the relationships (clusters) among the functional interference items in the Brief Pain Inventory (BPI) in patients with bone metastases. Methods: Patients enrolled in the Radiation Therapy Oncology Group (RTOG) 9714 bone metastases study were eligible. Patients were assessed at baseline and 4, 8, and 12 weeks after randomization for the palliative radiotherapy with the BPI, which consists of seven functional items: general activity, mood, walking ability, normal work, relations with others, sleep, and enjoyment of life. Principal component analysis with varimax rotation was used to determine the clusters between the functional items at baseline and the follow-up. Cronbach's alpha was used to determine the consistency and reliability of each cluster at baseline and follow-up. Results: There were 448 male and 461 female patients, with a median age of 67 years. There were two functional interference clusters at baseline, which accounted for 71% of the total variance. The first cluster (physical interference) included normal work and walking ability, which accounted for 58% of the total variance. The second cluster (psychosocial interference) included relations with others and sleep, which accounted for 13% of the total variance. The Cronbach's alpha statistics were 0.83 and 0.80, respectively. The functional clusters changed at week 12 in responders but persisted through week 12 in nonresponders. Conclusion: Palliative radiotherapy is effective in reducing bone pain. Functional interference component clusters exist in patients treated for bone metastases. These clusters changed over time in this study, possibly attributable to treatment. Further research is needed to examine these effects.

Regulation of human Nfu activity in Fe-S cluster delivery-characterization of the interaction between Nfu and the HSPA9/Hsc20 chaperone complex.

Science.gov (United States)

Wachnowsky, Christine; Liu, Yushi; Yoon, Taejin; Cowan, J A

2018-01-01

Iron-sulfur cluster biogenesis is a complex, but highly regulated process that involves de novo cluster formation from iron and sulfide ions on a scaffold protein, and subsequent delivery to final targets via a series of Fe-S cluster-binding carrier proteins. The process of cluster release from the scaffold/carrier for transfer to the target proteins may be mediated by a dedicated Fe-S cluster chaperone system. In human cells, the chaperones include heat shock protein HSPA9 and the J-type chaperone Hsc20. While the role of chaperones has been somewhat clarified in yeast and bacterial systems, many questions remain over their functional roles in cluster delivery and interactions with a variety of human Fe-S cluster proteins. One such protein, Nfu, has recently been recognized as a potential interaction partner of the chaperone complex. Herein, we examined the ability of human Nfu to function as a carrier by interacting with the human chaperone complex. Human Nfu is shown to bind to both chaperone proteins with binding affinities similar to those observed for IscU binding to the homologous HSPA9 and Hsc20, while Nfu can also stimulate the ATPase activity of HSPA9. Additionally, the chaperone complex was able to promote Nfu function by enhancing the second-order rate constants for Fe-S cluster transfer to target proteins and providing directionality in cluster transfer from Nfu by eliminating promiscuous transfer reactions. Together, these data support a hypothesis in which Nfu can serve as an alternative carrier protein for chaperone-mediated cluster release and delivery in Fe-S cluster biogenesis and trafficking. © 2017 Federation of European Biochemical Societies.

An interaction of the functionalized closo-borates with albumins: The protein fluorescence quenching and calorimetry study

Energy Technology Data Exchange (ETDEWEB)

Losytskyy, Mykhaylo Yu., E-mail: mlosytskyy@gmail.com [Institute of Molecular Biology and Genetics, NASU, 150 Zabolotnogo Street, 03143 Kyiv (Ukraine); Kovalska, Vladyslava B. [Institute of Molecular Biology and Genetics, NASU, 150 Zabolotnogo Street, 03143 Kyiv (Ukraine); Varzatskii, Oleg A. [V. I. Vernadsky Institute of General and Inorganic Chemistry, 32/34 Palladin Avenue, 03080 Kyiv (Ukraine); Kuperman, Marina V. [Institute of Molecular Biology and Genetics, NASU, 150 Zabolotnogo Street, 03143 Kyiv (Ukraine); Potocki, Slawomir; Gumienna-Kontecka, Elzbieta [Faculty of Chemistry, Wroclaw University, 14F. Joliot-Curie Street, 50-383 Wroclaw (Poland); Zhdanov, Andrey P. [Kurnakov Institute of General and Inorganic Chemistry, 31 Leninskii Avenue, 119991 Moscow (Russian Federation); Yarmoluk, Sergiy M. [Institute of Molecular Biology and Genetics, NASU, 150 Zabolotnogo Street, 03143 Kyiv (Ukraine); Voloshin, Yan Z. [Nesmeyanov Institute of Organoelement Compounds, 28 Vavilova Street, 119991 Moscow (Russian Federation); Zhizhin, Konstantin Yu.; Kuznetsov, Nikolai T. [Kurnakov Institute of General and Inorganic Chemistry, 31 Leninskii Avenue, 119991 Moscow (Russian Federation); Elskaya, Anna V. [Institute of Molecular Biology and Genetics, NASU, 150 Zabolotnogo Street, 03143 Kyiv (Ukraine)

2016-01-15

An interaction of the boron clusters closo-borates K{sub 2}[B{sub 10}H{sub 10}], K{sub 2}[B{sub 12}H{sub 12}] and their functionalized derivatives with serum proteins human (HSA) and bovine (BSA) albumins and immonoglobulin IgG as well as globular proteins β-lactoglobulin and lysozyme was characterized. The steady state and time resolved protein fluorescence quenching studies point on the binding of the closo-borate arylamine derivatives to serum albumins and discrimination of other proteins. The mechanism of the albumin fluorescence quenching by the closo-borate arylamine derivatives was proposed. The complex formation between albumin and the closo-borate molecules has been confirmed by isothermal titration calorimetry (ITC). The compound (K{sub 2}[B{sub 10}H{sub 10}]) and its arylamine derivative both interact with HSA, have close values of K{sub a} (1.4 and 1.2×10{sup 3} M{sup −1} respectively) and Gibbs energy (−17.9 and −17.5 kJ/mol respectively). However, the arylamine derivative forms complex with the higher guest/host binding ratio (4:1) comparing to the parent closo-borate (2:1). - Highlights: • Complex formation between boron clusters closo-borates and albumins was confirmed. • Functional substituent of closo-borate strongly affects its complex with albumins. • Binding of arylamine closo-borates essentially quench the albumin fluorescence. • Mechanism of tryptophan emission quenching by arylamine closo-borates was proposed.

Biases in the experimental annotations of protein function and their effect on our understanding of protein function space.

Directory of Open Access Journals (Sweden)

Alexandra M Schnoes

Full Text Available The ongoing functional annotation of proteins relies upon the work of curators to capture experimental findings from scientific literature and apply them to protein sequence and structure data. However, with the increasing use of high-throughput experimental assays, a small number of experimental studies dominate the functional protein annotations collected in databases. Here, we investigate just how prevalent is the "few articles - many proteins" phenomenon. We examine the experimentally validated annotation of proteins provided by several groups in the GO Consortium, and show that the distribution of proteins per published study is exponential, with 0.14% of articles providing the source of annotations for 25% of the proteins in the UniProt-GOA compilation. Since each of the dominant articles describes the use of an assay that can find only one function or a small group of functions, this leads to substantial biases in what we know about the function of many proteins. Mass-spectrometry, microscopy and RNAi experiments dominate high throughput experiments. Consequently, the functional information derived from these experiments is mostly of the subcellular location of proteins, and of the participation of proteins in embryonic developmental pathways. For some organisms, the information provided by different studies overlap by a large amount. We also show that the information provided by high throughput experiments is less specific than those provided by low throughput experiments. Given the experimental techniques available, certain biases in protein function annotation due to high-throughput experiments are unavoidable. Knowing that these biases exist and understanding their characteristics and extent is important for database curators, developers of function annotation programs, and anyone who uses protein function annotation data to plan experiments.

Spectroscopic constraints on the form of the stellar cluster mass function

Science.gov (United States)

Bastian, N.; Konstantopoulos, I. S.; Trancho, G.; Weisz, D. R.; Larsen, S. S.; Fouesneau, M.; Kaschinski, C. B.; Gieles, M.

2012-05-01

This contribution addresses the question of whether the initial cluster mass function (ICMF) has a fundamental limit (or truncation) at high masses. The shape of the ICMF at high masses can be studied using the most massive young (advantages are that more clusters can be used and that the ICMF leaves a distinct pattern on the global relation between the cluster luminosity and median age within a population. If a truncation is present, a generic prediction (nearly independent of the cluster disruption law adopted) is that the median age of bright clusters should be younger than that of fainter clusters. In the case of an non-truncated ICMF, the median age should be independent of cluster luminosity. Here, we present optical spectroscopy of twelve young stellar clusters in the face-on spiral galaxy NGC 2997. The spectra are used to estimate the age of each cluster, and the brightness of the clusters is taken from the literature. The observations are compared with the model expectations of Larsen (2009, A&A, 494, 539) for various ICMF forms and both mass dependent and mass independent cluster disruption. While there exists some degeneracy between the truncation mass and the amount of mass independent disruption, the observations favour a truncated ICMF. For low or modest amounts of mass independent disruption, a truncation mass of 5-6 × 105 M⊙ is estimated, consistent with previous determinations. Additionally, we investigate possible truncations in the ICMF in the spiral galaxy M 83, the interacting Antennae galaxies, and the collection of spiral and dwarf galaxies present in Larsen (2009, A&A, 494, 539) based on photometric catalogues taken from the literature, and find that all catalogues are consistent with having a truncation in the cluster mass functions. However for the case of the Antennae, we find a truncation mass of a few × 106M⊙ , suggesting a dependence on the environment, as has been previously suggested.

Ab Initio Calculations of the Electronic Structures and Biological Functions of Protein Molecules

Science.gov (United States)

Zheng, Haoping

2003-04-01

The self-consistent cluster-embedding (SCCE) calculation method reduces the computational effort from M3 to about M1 (M is the number of atoms in the system) with unchanged calculation precision. So the ab initio, all-electron calculation of the electronic structure and biological function of protein molecule becomes a reality, which will promote new proteomics considerably. The calculated results of two real protein molecules, the trypsin inhibitor from the seeds of squash Cucurbita maxima (CMTI-I, 436 atoms) and the Ascaris trypsin inhibitor (912 atoms, two three-dimensional structures), are presented. The reactive sites of the inhibitors are determined and explained. The precision of structure determination of inhibitors are tested theoretically.

Identification of a new genomic hot spot of evolutionary diversification of protein function.

Directory of Open Access Journals (Sweden)

Aline Winkelmann

Full Text Available Establishment of phylogenetic relationships remains a challenging task because it is based on computational analysis of genomic hot spots that display species-specific sequence variations. Here, we identify a species-specific thymine-to-guanine sequence variation in the Glrb gene which gives rise to species-specific splice donor sites in the Glrb genes of mouse and bushbaby. The resulting splice insert in the receptor for the inhibitory neurotransmitter glycine (GlyR conveys synaptic receptor clustering and specific association with a particular synaptic plasticity-related splice variant of the postsynaptic scaffold protein gephyrin. This study identifies a new genomic hot spot which contributes to phylogenetic diversification of protein function and advances our understanding of phylogenetic relationships.

Diblock-copolymer-mediated self-assembly of protein-stabilized iron oxide nanoparticle clusters for magnetic resonance imaging.

Science.gov (United States)

Tähkä, Sari; Laiho, Ari; Kostiainen, Mauri A

2014-03-03

Superparamagnetic iron oxide nanoparticles (SPIONs) can be used as efficient transverse relaxivity (T2 ) contrast agents in magnetic resonance imaging (MRI). Organizing small (Doxide) diblock copolymer (P2QVP-b-PEO) to mediate the self-assembly of protein-cage-encapsulated iron oxide (γ-Fe2 O3 ) nanoparticles (magnetoferritin) into stable PEO-coated clusters. This approach relies on electrostatic interactions between the cationic N-methyl-2-vinylpyridinium iodide block and magnetoferritin protein cage surface (pI≈4.5) to form a dense core, whereas the neutral ethylene oxide block provides a stabilizing biocompatible shell. Formation of the complexes was studied in aqueous solvent medium with dynamic light scattering (DLS) and cryogenic transmission electron microcopy (cryo-TEM). DLS results indicated that the hydrodynamic diameter (Dh ) of the clusters is approximately 200 nm, and cryo-TEM showed that the clusters have an anisotropic stringlike morphology. MRI studies showed that in the clusters the longitudinal relaxivity (r1 ) is decreased and the transverse relaxivity (r2 ) is increased relative to free magnetoferritin (MF), thus indicating that clusters can provide considerable contrast enhancement. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Comparing Residue Clusters from Thermophilic and Mesophilic Enzymes Reveals Adaptive Mechanisms.

Directory of Open Access Journals (Sweden)

Deanne W Sammond

Full Text Available Understanding how proteins adapt to function at high temperatures is important for deciphering the energetics that dictate protein stability and folding. While multiple principles important for thermostability have been identified, we lack a unified understanding of how internal protein structural and chemical environment determine qualitative or quantitative impact of evolutionary mutations. In this work we compare equivalent clusters of spatially neighboring residues between paired thermophilic and mesophilic homologues to evaluate adaptations under the selective pressure of high temperature. We find the residue clusters in thermophilic enzymes generally display improved atomic packing compared to mesophilic enzymes, in agreement with previous research. Unlike residue clusters from mesophilic enzymes, however, thermophilic residue clusters do not have significant cavities. In addition, anchor residues found in many clusters are highly conserved with respect to atomic packing between both thermophilic and mesophilic enzymes. Thus the improvements in atomic packing observed in thermophilic homologues are not derived from these anchor residues but from neighboring positions, which may serve to expand optimized protein core regions.

Comparison of two schemes for automatic keyword extraction from MEDLINE for functional gene clustering.

Science.gov (United States)

Liu, Ying; Ciliax, Brian J; Borges, Karin; Dasigi, Venu; Ram, Ashwin; Navathe, Shamkant B; Dingledine, Ray

2004-01-01

One of the key challenges of microarray studies is to derive biological insights from the unprecedented quatities of data on gene-expression patterns. Clustering genes by functional keyword association can provide direct information about the nature of the functional links among genes within the derived clusters. However, the quality of the keyword lists extracted from biomedical literature for each gene significantly affects the clustering results. We extracted keywords from MEDLINE that describes the most prominent functions of the genes, and used the resulting weights of the keywords as feature vectors for gene clustering. By analyzing the resulting cluster quality, we compared two keyword weighting schemes: normalized z-score and term frequency-inverse document frequency (TFIDF). The best combination of background comparison set, stop list and stemming algorithm was selected based on precision and recall metrics. In a test set of four known gene groups, a hierarchical algorithm correctly assigned 25 of 26 genes to the appropriate clusters based on keywords extracted by the TDFIDF weighting scheme, but only 23 og 26 with the z-score method. To evaluate the effectiveness of the weighting schemes for keyword extraction for gene clusters from microarray profiles, 44 yeast genes that are differentially expressed during the cell cycle were used as a second test set. Using established measures of cluster quality, the results produced from TFIDF-weighted keywords had higher purity, lower entropy, and higher mutual information than those produced from normalized z-score weighted keywords. The optimized algorithms should be useful for sorting genes from microarray lists into functionally discrete clusters.

Biases in the Experimental Annotations of Protein Function and Their Effect on Our Understanding of Protein Function Space

Science.gov (United States)

Schnoes, Alexandra M.; Ream, David C.; Thorman, Alexander W.; Babbitt, Patricia C.; Friedberg, Iddo

2013-01-01

The ongoing functional annotation of proteins relies upon the work of curators to capture experimental findings from scientific literature and apply them to protein sequence and structure data. However, with the increasing use of high-throughput experimental assays, a small number of experimental studies dominate the functional protein annotations collected in databases. Here, we investigate just how prevalent is the “few articles - many proteins” phenomenon. We examine the experimentally validated annotation of proteins provided by several groups in the GO Consortium, and show that the distribution of proteins per published study is exponential, with 0.14% of articles providing the source of annotations for 25% of the proteins in the UniProt-GOA compilation. Since each of the dominant articles describes the use of an assay that can find only one function or a small group of functions, this leads to substantial biases in what we know about the function of many proteins. Mass-spectrometry, microscopy and RNAi experiments dominate high throughput experiments. Consequently, the functional information derived from these experiments is mostly of the subcellular location of proteins, and of the participation of proteins in embryonic developmental pathways. For some organisms, the information provided by different studies overlap by a large amount. We also show that the information provided by high throughput experiments is less specific than those provided by low throughput experiments. Given the experimental techniques available, certain biases in protein function annotation due to high-throughput experiments are unavoidable. Knowing that these biases exist and understanding their characteristics and extent is important for database curators, developers of function annotation programs, and anyone who uses protein function annotation data to plan experiments. PMID:23737737

The luminosity function for globular clusters, 4: M3

International Nuclear Information System (INIS)

Simoda, Mahiro; Fukuoka, Takashi

1976-01-01

The subgiant-turnoff portion (V = 17.2 - 20.0 mag) of the luminosity function for the globular cluster M3 has been determined from photometry of the stars within the annuli 3'-8' and 6'-8' for V = 17.2 - 19.0 mag and 19.0 - 20.0 mag, respectively, by using plates taken with the Kitt Peak 2.1-m reflector. Our result shows that the luminosity function for M3 has a similar steep rise in the subgiant portion as other clusters so far studied (M5, M13, and M92), in direct conflict with the result by SANDAGE (1954, 1957). A probable cause of this discrepancy is given. Comparison with theoretical luminosity functions by SIMODA and IBEN (1970) suggests that theory and observation are not inconsistent if the initial helium abundance of M3 stars is taken to be about 20 percent. It is suggested that M13 has a larger helium abundance than M3 and M92 from the intercomparison of their luminosity functions and color-magnitude diagrams. (auth.)

Characterization of Glutaredoxin Fe-S Cluster-Binding Interactions Using Circular Dichroism Spectroscopy.

Science.gov (United States)

Albetel, Angela-Nadia; Outten, Caryn E

2018-01-01

Monothiol glutaredoxins (Grxs) with a conserved Cys-Gly-Phe-Ser (CGFS) active site are iron-sulfur (Fe-S) cluster-binding proteins that interact with a variety of partner proteins and perform crucial roles in iron metabolism including Fe-S cluster transfer, Fe-S cluster repair, and iron signaling. Various analytical and spectroscopic methods are currently being used to monitor and characterize glutaredoxin Fe-S cluster-dependent interactions at the molecular level. The electronic, magnetic, and vibrational properties of the protein-bound Fe-S cluster provide a convenient handle to probe the structure, function, and coordination chemistry of Grx complexes. However, some limitations arise from sample preparation requirements, complexity of individual techniques, or the necessity for combining multiple methods in order to achieve a complete investigation. In this chapter, we focus on the use of UV-visible circular dichroism spectroscopy as a fast and simple initial approach for investigating glutaredoxin Fe-S cluster-dependent interactions. © 2018 Elsevier Inc. All rights reserved.

Integration of Phenotypic Metadata and Protein Similarity in Archaea Using a Spectral Bipartitioning Approach

Energy Technology Data Exchange (ETDEWEB)

Hooper, Sean D.; Anderson, Iain J; Pati, Amrita; Dalevi, Daniel; Mavromatis, Konstantinos; Kyrpides, Nikos C

2009-01-01

In order to simplify and meaningfully categorize large sets of protein sequence data, it is commonplace to cluster proteins based on the similarity of those sequences. However, it quickly becomes clear that the sequence flexibility allowed a given protein varies significantly among different protein families. The degree to which sequences are conserved not only differs for each protein family, but also is affected by the phylogenetic divergence of the source organisms. Clustering techniques that use similarity thresholds for protein families do not always allow for these variations and thus cannot be confidently used for applications such as automated annotation and phylogenetic profiling. In this work, we applied a spectral bipartitioning technique to all proteins from 53 archaeal genomes. Comparisons between different taxonomic levels allowed us to study the effects of phylogenetic distances on cluster structure. Likewise, by associating functional annotations and phenotypic metadata with each protein, we could compare our protein similarity clusters with both protein function and associated phenotype. Our clusters can be analyzed graphically and interactively online.

The galaxy cluster mid-infrared luminosity function at 1.3 < z < 3.2

Energy Technology Data Exchange (ETDEWEB)

Wylezalek, Dominika; Vernet, Joël; De Breuck, Carlos [European Southern Observatory, Karl-Schwarzschildstr.2, D-85748 Garching bei München (Germany); Stern, Daniel [Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA 91109 (United States); Brodwin, Mark [Department of Physics and Astronomy, University of Missouri, 5110 Rockhill Road, Kansas City, MO 64110 (United States); Galametz, Audrey [INAF-Osservatorio di Roma, Via Frascati 33, I-00040, Monteporzio (Italy); Gonzalez, Anthony H. [Department of Astronomy, University of Florida, Gainesville, FL 32611 (United States); Jarvis, Matt [Astrophysics, Department of Physics, Keble Road, Oxford OX1 3RH (United Kingdom); Hatch, Nina [School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD (United Kingdom); Seymour, Nick [CASS, P.O. Box 76, Epping, NSW, 1710 (Australia); Stanford, Spencer A. [Physics Department, University of California, Davis, CA 95616 (United States)

2014-05-01

We present 4.5 μm luminosity functions for galaxies identified in 178 candidate galaxy clusters at 1.3 < z < 3.2. The clusters were identified as Spitzer/Infrared Array Camera (IRAC) color-selected overdensities in the Clusters Around Radio-Loud AGN project, which imaged 420 powerful radio-loud active galactic nuclei (RLAGNs) at z > 1.3. The luminosity functions are derived for different redshift and richness bins, and the IRAC imaging reaches depths of m* + 2, allowing us to measure the faint end slopes of the luminosity functions. We find that α = –1 describes the luminosity function very well in all redshift bins and does not evolve significantly. This provides evidence that the rate at which the low mass galaxy population grows through star formation gets quenched and is replenished by in-falling field galaxies does not have a major net effect on the shape of the luminosity function. Our measurements for m* are consistent with passive evolution models and high formation redshifts (z{sub f} ∼ 3). We find a slight trend toward fainter m* for the richest clusters, implying that the most massive clusters in our sample could contain older stellar populations, yet another example of cosmic downsizing. Modeling shows that a contribution of a star-forming population of up to 40% cannot be ruled out. This value, found from our targeted survey, is significantly lower than the values found for slightly lower redshift, z ∼ 1, clusters found in wide-field surveys. The results are consistent with cosmic downsizing, as the clusters studied here were all found in the vicinity of RLAGNs—which have proven to be preferentially located in massive dark matter halos in the richest environments at high redshift—and they may therefore be older and more evolved systems than the general protocluster population.

The galaxy cluster mid-infrared luminosity function at 1.3 < z < 3.2

International Nuclear Information System (INIS)

Wylezalek, Dominika; Vernet, Joël; De Breuck, Carlos; Stern, Daniel; Brodwin, Mark; Galametz, Audrey; Gonzalez, Anthony H.; Jarvis, Matt; Hatch, Nina; Seymour, Nick; Stanford, Spencer A.

2014-01-01

We present 4.5 μm luminosity functions for galaxies identified in 178 candidate galaxy clusters at 1.3 < z < 3.2. The clusters were identified as Spitzer/Infrared Array Camera (IRAC) color-selected overdensities in the Clusters Around Radio-Loud AGN project, which imaged 420 powerful radio-loud active galactic nuclei (RLAGNs) at z > 1.3. The luminosity functions are derived for different redshift and richness bins, and the IRAC imaging reaches depths of m* + 2, allowing us to measure the faint end slopes of the luminosity functions. We find that α = –1 describes the luminosity function very well in all redshift bins and does not evolve significantly. This provides evidence that the rate at which the low mass galaxy population grows through star formation gets quenched and is replenished by in-falling field galaxies does not have a major net effect on the shape of the luminosity function. Our measurements for m* are consistent with passive evolution models and high formation redshifts (z f ∼ 3). We find a slight trend toward fainter m* for the richest clusters, implying that the most massive clusters in our sample could contain older stellar populations, yet another example of cosmic downsizing. Modeling shows that a contribution of a star-forming population of up to 40% cannot be ruled out. This value, found from our targeted survey, is significantly lower than the values found for slightly lower redshift, z ∼ 1, clusters found in wide-field surveys. The results are consistent with cosmic downsizing, as the clusters studied here were all found in the vicinity of RLAGNs—which have proven to be preferentially located in massive dark matter halos in the richest environments at high redshift—and they may therefore be older and more evolved systems than the general protocluster population.

Structural studies of the Enterococcus faecalis SufU [Fe-S] cluster protein

Directory of Open Access Journals (Sweden)

Frazzon Jeverson

2009-02-01

Full Text Available Abstract Background Iron-sulfur clusters are ubiquitous and evolutionarily ancient inorganic prosthetic groups, the biosynthesis of which depends on complex protein machineries. Three distinct assembly systems involved in the maturation of cellular Fe-S proteins have been determined, designated the NIF, ISC and SUF systems. Although well described in several organisms, these machineries are poorly understood in Gram-positive bacteria. Within the Firmicutes phylum, the Enterococcus spp. genus have recently assumed importance in clinical microbiology being considered as emerging pathogens for humans, wherein Enterococcus faecalis represents the major species associated with nosocomial infections. The aim of this study was to carry out a phylogenetic analysis in Enterococcus faecalis V583 and a structural and conformational characterisation of it SufU protein. Results BLAST searches of the Enterococcus genome revealed a series of genes with sequence similarity to the Escherichia coli SUF machinery of [Fe-S] cluster biosynthesis, namely sufB, sufC, sufD and SufS. In addition, the E. coli IscU ortholog SufU was found to be the scaffold protein of Enterococcus spp., containing all features considered essential for its biological activity, including conserved amino acid residues involved in substrate and/or co-factor binding (Cys50,76,138 and Asp52 and, phylogenetic analyses showed a close relationship with orthologues from other Gram-positive bacteria. Molecular dynamics for structural determinations and molecular modeling using E. faecalis SufU primary sequence protein over the PDB:1su0 crystallographic model from Streptococcus pyogenes were carried out with a subsequent 50 ns molecular dynamic trajectory. This presented a stable model, showing secondary structure modifications near the active site and conserved cysteine residues. Molecular modeling using Haemophilus influenzae IscU primary sequence over the PDB:1su0 crystal followed by a MD

A-dependence of structure functions and multiquark clusters in nuclei

International Nuclear Information System (INIS)

Kondratyuk, L.; Shmatikov, M.

1984-01-01

Assuming existence of 12q-clusters (bags) in nuclei the structure functions of deep inelastic scattering of leptons on nuclei are discussed. Universal momentum distribution of quarks in a multiquark cluster is used with high-momentum component falling exponentially PHIsub(q)sup(2)(k) approximately esup(-k/ksub(0)) with k 0 approximately equal to 50-60 MeV/c. The admixture of 12q-cluster W required for the description of SLAG data increases from 10% for 4 He to 30% for Au. The A-dependence of W agrees well with the A-dependence of cumulative particle spectra

A spectral scheme for Kohn-Sham density functional theory of clusters

Science.gov (United States)

Banerjee, Amartya S.; Elliott, Ryan S.; James, Richard D.

2015-04-01

Starting from the observation that one of the most successful methods for solving the Kohn-Sham equations for periodic systems - the plane-wave method - is a spectral method based on eigenfunction expansion, we formulate a spectral method designed towards solving the Kohn-Sham equations for clusters. This allows for efficient calculation of the electronic structure of clusters (and molecules) with high accuracy and systematic convergence properties without the need for any artificial periodicity. The basis functions in this method form a complete orthonormal set and are expressible in terms of spherical harmonics and spherical Bessel functions. Computation of the occupied eigenstates of the discretized Kohn-Sham Hamiltonian is carried out using a combination of preconditioned block eigensolvers and Chebyshev polynomial filter accelerated subspace iterations. Several algorithmic and computational aspects of the method, including computation of the electrostatics terms and parallelization are discussed. We have implemented these methods and algorithms into an efficient and reliable package called ClusterES (Cluster Electronic Structure). A variety of benchmark calculations employing local and non-local pseudopotentials are carried out using our package and the results are compared to the literature. Convergence properties of the basis set are discussed through numerical examples. Computations involving large systems that contain thousands of electrons are demonstrated to highlight the efficacy of our methodology. The use of our method to study clusters with arbitrary point group symmetries is briefly discussed.

Topological defect clustering and plastic deformation mechanisms in functionalized graphene

Science.gov (United States)

Nunes, Ricardo; Araujo, Joice; Chacham, Helio

2011-03-01

We present ab initio results suggesting that strain plays a central role in the clustering of topological defects in strained and functionalized graphene models. We apply strain onto the topological-defect graphene networks from our previous work, and obtain topological-defect clustering patterns which are in excellent agreement with recent observations in samples of reduced graphene oxide. In our models, the graphene layer, containing an initial concentration of isolated topological defects, is covered by hydrogen or hydroxyl groups. Our results also suggest a rich variety of plastic deformation mechanism in functionalized graphene systems. We acknowledge support from the Brazilian agencies: CNPq, Fapemig, and INCT-Materiais de Carbono.

Density functional study of the bonding in small silicon clusters

International Nuclear Information System (INIS)

Fournier, R.; Sinnott, S.B.; DePristo, A.E.

1992-01-01

We report the ground electronic state, equilibrium geometry, vibrational frequencies, and binding energy for various isomers of Si n (n = 2--8) obtained with the linear combination of atomic orbitals-density functional method. We used both a local density approximation approach and one with gradient corrections. Our local density approximation results concerning the relative stability of electronic states and isomers are in agreement with Hartree--Fock and Moller--Plesset (MP2) calculations [K. Raghavachari and C. M. Rohlfing, J. Chem. Phys. 89, 2219 (1988)]. The binding energies calculated with the gradient corrected functional are in good agreement with experiment (Si 2 and Si 3 ) and with the best theoretical estimates. Our analysis of the bonding reveals two limiting modes of bonding and classes of silicon clusters. One class of clusters is characterized by relatively large s atomic populations and a large number of weak bonds, while the other class of clusters is characterized by relatively small s atomic populations and a small number of strong bonds

Density parameter estimation for finding clusters of homologous proteins-tracing actinobacterial pathogenicity lifestyles

DEFF Research Database (Denmark)

Röttger, Richard; Kalaghatgi, Prabhav; Sun, Peng

2013-01-01

Homology detection is a long-standing challenge in computational biology. To tackle this problem, typically all-versus-all BLAST results are coupled with data partitioning approaches resulting in clusters of putative homologous proteins. One of the main problems, however, has been widely neglecte...

PANDA: Protein function prediction using domain architecture and affinity propagation.

Science.gov (United States)

Wang, Zheng; Zhao, Chenguang; Wang, Yiheng; Sun, Zheng; Wang, Nan

2018-02-22

We developed PANDA (Propagation of Affinity and Domain Architecture) to predict protein functions in the format of Gene Ontology (GO) terms. PANDA at first executes profile-profile alignment algorithm to search against PfamA, KOG, COG, and SwissProt databases, and then launches PSI-BLAST against UniProt for homologue search. PANDA integrates a domain architecture inference algorithm based on the Bayesian statistics that calculates the probability of having a GO term. All the candidate GO terms are pooled and filtered based on Z-score. After that, the remaining GO terms are clustered using an affinity propagation algorithm based on the GO directed acyclic graph, followed by a second round of filtering on the clusters of GO terms. We benchmarked the performance of all the baseline predictors PANDA integrates and also for every pooling and filtering step of PANDA. It can be found that PANDA achieves better performances in terms of area under the curve for precision and recall compared to the baseline predictors. PANDA can be accessed from http://dna.cs.miami.edu/PANDA/ .

The Magellanic Bridge Cluster NGC 796: Deep Optical AO Imaging Reveals the Stellar Content and Initial Mass Function of a Massive Open Cluster

Science.gov (United States)

Kalari, Venu M.; Carraro, Giovanni; Evans, Christopher J.; Rubio, Monica

2018-04-01

NGC 796 is a massive young cluster located 59 kpc from us in the diffuse intergalactic medium of the 1/5–1/10 Z⊙ Magellanic Bridge, allowing us to probe variations in star formation and stellar evolution processes as a function of metallicity in a resolved fashion, and providing a link between resolved studies of nearby solar-metallicity and unresolved distant metal-poor clusters located in high-redshift galaxies. In this paper, we present adaptive optics griHα imaging of NGC 796 (at 0.″5, which is ∼0.14 pc at the cluster distance) along with optical spectroscopy of two bright members to quantify the cluster properties. Our aim is to explore whether star formation and stellar evolution vary as a function of metallicity by comparing the properties of NGC 796 to higher-metallicity clusters. We find an age of {20}-5+12 Myr from isochronal fitting of the cluster main sequence in the color–magnitude diagram. Based on the cluster luminosity function, we derive a top-heavy stellar initial mass function (IMF) with a slope α = 1.99 ± 0.2, hinting at a metallicity and/or environmental dependence of the IMF, which may lead to a top-heavy IMF in the early universe. Study of the Hα emission-line stars reveals that classical Be stars constitute a higher fraction of the total B-type stars when compared with similar clusters at greater metallicity, providing some support to the chemically homogeneous theory of stellar evolution. Overall, NGC 796 has a total estimated mass of 990 ± 200 M⊙, and a core radius of 1.4 ± 0.3 pc, which classifies it as a massive young open cluster, unique in the diffuse interstellar medium of the Magellanic Bridge.

WebGimm: An integrated web-based platform for cluster analysis, functional analysis, and interactive visualization of results.

Science.gov (United States)

Joshi, Vineet K; Freudenberg, Johannes M; Hu, Zhen; Medvedovic, Mario

2011-01-17

Cluster analysis methods have been extensively researched, but the adoption of new methods is often hindered by technical barriers in their implementation and use. WebGimm is a free cluster analysis web-service, and an open source general purpose clustering web-server infrastructure designed to facilitate easy deployment of integrated cluster analysis servers based on clustering and functional annotation algorithms implemented in R. Integrated functional analyses and interactive browsing of both, clustering structure and functional annotations provides a complete analytical environment for cluster analysis and interpretation of results. The Java Web Start client-based interface is modeled after the familiar cluster/treeview packages making its use intuitive to a wide array of biomedical researchers. For biomedical researchers, WebGimm provides an avenue to access state of the art clustering procedures. For Bioinformatics methods developers, WebGimm offers a convenient avenue to deploy their newly developed clustering methods. WebGimm server, software and manuals can be freely accessed at http://ClusterAnalysis.org/.

A spectral scheme for Kohn–Sham density functional theory of clusters

Energy Technology Data Exchange (ETDEWEB)

Banerjee, Amartya S., E-mail: baner041@umn.edu; Elliott, Ryan S., E-mail: relliott@umn.edu; James, Richard D., E-mail: james@umn.edu

2015-04-15

Starting from the observation that one of the most successful methods for solving the Kohn–Sham equations for periodic systems – the plane-wave method – is a spectral method based on eigenfunction expansion, we formulate a spectral method designed towards solving the Kohn–Sham equations for clusters. This allows for efficient calculation of the electronic structure of clusters (and molecules) with high accuracy and systematic convergence properties without the need for any artificial periodicity. The basis functions in this method form a complete orthonormal set and are expressible in terms of spherical harmonics and spherical Bessel functions. Computation of the occupied eigenstates of the discretized Kohn–Sham Hamiltonian is carried out using a combination of preconditioned block eigensolvers and Chebyshev polynomial filter accelerated subspace iterations. Several algorithmic and computational aspects of the method, including computation of the electrostatics terms and parallelization are discussed. We have implemented these methods and algorithms into an efficient and reliable package called ClusterES (Cluster Electronic Structure). A variety of benchmark calculations employing local and non-local pseudopotentials are carried out using our package and the results are compared to the literature. Convergence properties of the basis set are discussed through numerical examples. Computations involving large systems that contain thousands of electrons are demonstrated to highlight the efficacy of our methodology. The use of our method to study clusters with arbitrary point group symmetries is briefly discussed.

A spectral scheme for Kohn–Sham density functional theory of clusters

International Nuclear Information System (INIS)

Banerjee, Amartya S.; Elliott, Ryan S.; James, Richard D.

2015-01-01

Starting from the observation that one of the most successful methods for solving the Kohn–Sham equations for periodic systems – the plane-wave method – is a spectral method based on eigenfunction expansion, we formulate a spectral method designed towards solving the Kohn–Sham equations for clusters. This allows for efficient calculation of the electronic structure of clusters (and molecules) with high accuracy and systematic convergence properties without the need for any artificial periodicity. The basis functions in this method form a complete orthonormal set and are expressible in terms of spherical harmonics and spherical Bessel functions. Computation of the occupied eigenstates of the discretized Kohn–Sham Hamiltonian is carried out using a combination of preconditioned block eigensolvers and Chebyshev polynomial filter accelerated subspace iterations. Several algorithmic and computational aspects of the method, including computation of the electrostatics terms and parallelization are discussed. We have implemented these methods and algorithms into an efficient and reliable package called ClusterES (Cluster Electronic Structure). A variety of benchmark calculations employing local and non-local pseudopotentials are carried out using our package and the results are compared to the literature. Convergence properties of the basis set are discussed through numerical examples. Computations involving large systems that contain thousands of electrons are demonstrated to highlight the efficacy of our methodology. The use of our method to study clusters with arbitrary point group symmetries is briefly discussed

Formation of nucleoplasmic protein aggregates impairs nuclear function in response to SiO2 nanoparticles

International Nuclear Information System (INIS)

Chen Min; Mikecz, Anna von

2005-01-01

Despite of their exponentially growing use, little is known about cell biological effects of nanoparticles. Here, we report uptake of silica (SiO 2 ) nanoparticles to the cell nucleus where they induce aberrant clusters of topoisomerase I (topo I) in the nucleoplasm that additionally contain signature proteins of nuclear domains, and protein aggregation such as ubiquitin, proteasomes, cellular glutamine repeat (polyQ) proteins, and huntingtin. Formation of intranuclear protein aggregates (1) inhibits replication, transcription, and cell proliferation; (2) does not significantly alter proteasomal activity or cell viability; and (3) is reversible by Congo red and trehalose. Since SiO 2 nanoparticles trigger a subnuclear pathology resembling the one occurring in expanded polyglutamine neurodegenerative disorders, we suggest that integrity of the functional architecture of the cell nucleus should be used as a read out for cytotoxicity and considered in the development of safe nanotechnology

Theoretical stellar luminosity functions and globular cluster ages and compositions

International Nuclear Information System (INIS)

Ratcliff, S.J.

1985-01-01

The ages and chemical compositions of the stars in globular clusters are of great interest, particularly because age estimates from the well-known exercise of fitting observed color-magnitude diagrams to theoretical predictions tend to yield ages in excess of the Hubble time (an estimate to the age of the Universe) in standard cosmological models, for currently proposed high values of Hubble's constant (VandenBerg 1983). Relatively little use has been made of stellar luminosity functions of the globular clusters, for which reliable observations are now becoming available, to constrain the ages or compositions. The comparison of observed luminosity functions to theoretical ones allows one to take advantage of information not usually used, and has the advantage of being relatively insensitive to our lack of knowledge of the detailed structure of stellar envelopes and atmospheres. A computer program was developed to apply standard stellar evolutionary theory, using the most recently available input physics (opacities, nuclear reaction rates), to the calculation of the evolution of low-mass Population II stars. An algorithm for computing luminosity functions from the evolutionary tracks was applied to sets of tracks covering a broad range of chemical compositions and ages, such as may be expected for globular clusters

Transporter’s evolution and carbohydrate metabolic clusters

NARCIS (Netherlands)

Plantinga, Titia H.; Does, Chris van der; Driessen, Arnold J.M.

2004-01-01

The yiaQRS genes of Escherichia coli K-12 are involved in carbohydrate metabolism. Clustering of homologous genes was found throughout several unrelated bacteria. Strikingly, all four bacterial transport protein classes were found, conserving transport function but not mechanism. It appears that

Density functional study of structural and electronic properties of bimetallic silver-gold clusters: Comparison with pure gold and silver clusters

Science.gov (United States)

Bonacic-Koutecky, Vlasta; Burda, Jaroslav; Mitric, Roland; Ge, Maofa; Zampella, Giuseppe; Fantucci, Piercarlo

2002-08-01

Bimetallic silver-gold clusters offer an excellent opportunity to study changes in metallic versus "ionic" properties involving charge transfer as a function of the size and the composition, particularly when compared to pure silver and gold clusters. We have determined structures, ionization potentials, and vertical detachment energies for neutral and charged bimetallic AgmAun 3[less-than-or-equal](m+n)[less-than-or-equal]5 clusters. Calculated VDE values compare well with available experimental data. In the stable structures of these clusters Au atoms assume positions which favor the charge transfer from Ag atoms. Heteronuclear bonding is usually preferred to homonuclear bonding in clusters with equal numbers of hetero atoms. In fact, stable structures of neutral Ag2Au2, Ag3Au3, and Ag4Au4 clusters are characterized by the maximum number of hetero bonds and peripheral positions of Au atoms. Bimetallic tetramer as well as hexamer are planar and have common structural properties with corresponding one-component systems, while Ag4Au4 and Ag8 have 3D forms in contrast to Au8 which assumes planar structure. At the density functional level of theory we have shown that this is due to participation of d electrons in bonding of pure Aun clusters while s electrons dominate bonding in pure Agm as well as in bimetallic clusters. In fact, Aun clusters remain planar for larger sizes than Agm and AgnAun clusters. Segregation between two components in bimetallic systems is not favorable, as shown in the example of Ag5Au5 cluster. We have found that the structures of bimetallic clusters with 20 atoms Ag10Au10 and Ag12Au8 are characterized by negatively charged Au subunits embedded in Ag environment. In the latter case, the shape of Au8 is related to a pentagonal bipyramid capped by one atom and contains three exposed negatively charged Au atoms. They might be suitable for activating reactions relevant to catalysis. According to our findings the charge transfer in bimetallic

Searching remote homology with spectral clustering with symmetry in neighborhood cluster kernels.

Directory of Open Access Journals (Sweden)

Ujjwal Maulik

Full Text Available Remote homology detection among proteins utilizing only the unlabelled sequences is a central problem in comparative genomics. The existing cluster kernel methods based on neighborhoods and profiles and the Markov clustering algorithms are currently the most popular methods for protein family recognition. The deviation from random walks with inflation or dependency on hard threshold in similarity measure in those methods requires an enhancement for homology detection among multi-domain proteins. We propose to combine spectral clustering with neighborhood kernels in Markov similarity for enhancing sensitivity in detecting homology independent of "recent" paralogs. The spectral clustering approach with new combined local alignment kernels more effectively exploits the unsupervised protein sequences globally reducing inter-cluster walks. When combined with the corrections based on modified symmetry based proximity norm deemphasizing outliers, the technique proposed in this article outperforms other state-of-the-art cluster kernels among all twelve implemented kernels. The comparison with the state-of-the-art string and mismatch kernels also show the superior performance scores provided by the proposed kernels. Similar performance improvement also is found over an existing large dataset. Therefore the proposed spectral clustering framework over combined local alignment kernels with modified symmetry based correction achieves superior performance for unsupervised remote homolog detection even in multi-domain and promiscuous domain proteins from Genolevures database families with better biological relevance. Source code available upon request.sarkar@labri.fr.

Distinct cell clusters touching islet cells induce islet cell replication in association with over-expression of Regenerating Gene (REG protein in fulminant type 1 diabetes.

Directory of Open Access Journals (Sweden)

Kaoru Aida

Full Text Available BACKGROUND: Pancreatic islet endocrine cell-supporting architectures, including islet encapsulating basement membranes (BMs, extracellular matrix (ECM, and possible cell clusters, are unclear. PROCEDURES: The architectures around islet cell clusters, including BMs, ECM, and pancreatic acinar-like cell clusters, were studied in the non-diabetic state and in the inflamed milieu of fulminant type 1 diabetes in humans. RESULT: Immunohistochemical and electron microscopy analyses demonstrated that human islet cell clusters and acinar-like cell clusters adhere directly to each other with desmosomal structures and coated-pit-like structures between the two cell clusters. The two cell-clusters are encapsulated by a continuous capsule composed of common BMs/ECM. The acinar-like cell clusters have vesicles containing regenerating (REG Iα protein. The vesicles containing REG Iα protein are directly secreted to islet cells. In the inflamed milieu of fulminant type 1 diabetes, the acinar-like cell clusters over-expressed REG Iα protein. Islet endocrine cells, including beta-cells and non-beta cells, which were packed with the acinar-like cell clusters, show self-replication with a markedly increased number of Ki67-positive cells. CONCLUSION: The acinar-like cell clusters touching islet endocrine cells are distinct, because the cell clusters are packed with pancreatic islet clusters and surrounded by common BMs/ECM. Furthermore, the acinar-like cell clusters express REG Iα protein and secrete directly to neighboring islet endocrine cells in the non-diabetic state, and the cell clusters over-express REG Iα in the inflamed milieu of fulminant type 1 diabetes with marked self-replication of islet cells.

The food, GI tract functionality and human health cluster

NARCIS (Netherlands)

Mattila-Sandholm, T.; Blaut, M.; Daly, C.; Vuyst, de L.; Dore, J.; Gibson, G.; Goossens, H.; Knorr, D.; Lucas, J.; Lahteenmaki, L.; Mercenier, A.M.E.; Saarela, M.; Shanahan, F.; Vos, de W.M.

2002-01-01

The Food, GI-tract Functionality and Human Health (PROEUHEALTH) Cluster brings together eight complementary, multicentre interdisciplinary research projects. All have the common aim of improving the health and quality of life of European comsumers. The collaboration involves 64 different research

The E. coli monothiol glutaredoxin GrxD forms homodimeric and heterodimeric FeS cluster containing complexes.

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Yeung, N; Gold, B; Liu, N L; Prathapam, R; Sterling, H J; Willams, E R; Butland, G

2011-10-18

Monothiol glutaredoxins (mono-Grx) represent a highly evolutionarily conserved class of proteins present in organisms ranging from prokaryotes to humans. Mono-Grxs have been implicated in iron sulfur (FeS) cluster biosynthesis as potential scaffold proteins and in iron homeostasis via an FeS-containing complex with Fra2p (homologue of E. coli BolA) in yeast and are linked to signal transduction in mammalian systems. However, the function of the mono-Grx in prokaryotes and the nature of an interaction with BolA-like proteins have not been established. Recent genome-wide screens for E. coli genetic interactions reported the synthetic lethality (combination of mutations leading to cell death; mutation of only one of these genes does not) of a grxD mutation when combined with strains defective in FeS cluster biosynthesis (isc operon) functions [Butland, G., et al. (2008) Nature Methods 5, 789-795]. These data connected the only E. coli mono-Grx, GrxD to a potential role in FeS cluster biosynthesis. We investigated GrxD to uncover the molecular basis of this synthetic lethality and observed that GrxD can form FeS-bound homodimeric and BolA containing heterodimeric complexes. These complexes display substantially different spectroscopic and functional properties, including the ability to act as scaffold proteins for intact FeS cluster transfer to the model [2Fe-2S] acceptor protein E. coli apo-ferredoxin (Fdx), with the homodimer being significantly more efficient. In this work, we functionally dissect the potential cellular roles of GrxD as a component of both homodimeric and heterodimeric complexes to ultimately uncover if either of these complexes performs functions linked to FeS cluster biosynthesis. © 2011 American Chemical Society

Classification of protein profiles using fuzzy clustering techniques

DEFF Research Database (Denmark)

Karemore, Gopal; Mullick, Jhinuk B.; Sujatha, R.

2010-01-01

 Present  study  has  brought  out  a  comparison  of PCA  and  fuzzy  clustering  techniques  in  classifying  protein profiles  (chromatogram)  of  homogenates  of  different  tissue origins:  Ovarian,  Cervix,  Oral  cancers,  which  were  acquired using HPLC–LIF (High Performance Liquid...... Chromatography- Laser   Induced   Fluorescence)   method   developed   in   our laboratory. Study includes 11 chromatogram spectra each from oral,  cervical,  ovarian  cancers  as  well  as  healthy  volunteers. Generally  multivariate  analysis  like  PCA  demands  clear  data that   is   devoid   of   day......   PCA   mapping   in   classifying   various cancers from healthy spectra with classification rate up to 95 % from  60%.  Methods  are  validated  using  various  clustering indexes   and   shows   promising   improvement   in   developing optical pathology like HPLC-LIF for early detection of various...

Inferring the Functions of Proteins from the Interrelationships between Functional Categories.

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Taha, Kamal

2018-01-01

This study proposes a new method to determine the functions of an unannotated protein. The proteins and amino acid residues mentioned in biomedical texts associated with an unannotated protein can be considered as characteristics terms for , which are highly predictive of the potential functions of . Similarly, proteins and amino acid residues mentioned in biomedical texts associated with proteins annotated with a functional category can be considered as characteristics terms of . We introduce in this paper an information extraction system called IFP_IFC that predicts the functions of an unannotated protein by representing and each functional category by a vector of weights. Each weight reflects the degree of association between a characteristic term and (or a characteristic term and ). First, IFP_IFC constructs a network, whose nodes represent the different functional categories, and its edges the interrelationships between the nodes. Then, it determines the functions of by employing random walks with restarts on the mentioned network. The walker is the vector of . Finally, is assigned to the functional categories of the nodes in the network that are visited most by the walker. We evaluated the quality of IFP_IFC by comparing it experimentally with two other systems. Results showed marked improvement.

[Nitrogen oxide is involved in the regulation of the Fe-S cluster assembly in proteins and the formation of biofilms by Escherichia coli cells].

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Vasil'eva, S V; Streltsova, D A; Starostina, I A; Sanina, N A

2013-01-01

The functions of nitrogen oxide (NO) in the regulation of the reversible processes of Fe-S cluster assembly in proteins and the formation of Escherichia coli biofilms have been investigated. S-nitrosoglutathione (GSNO) and crystalline nitrosyl complexes of iron with sulfur-containing aliphatic ligands cisaconite (CisA) and penaconite have been used as NO donors for the first time. Wild-type E. coli cells of the strain MC4100, mutants deltaiscA and deltasufA, and the double paralog mutant deltaiscA/sufA with deletions in the alternative pathways of Fe2+ supply for cluster assembly (all derived from the above-named strain) were used in this study. Plankton growth of bacterial cultures, the mass of mature biofilms, and the expression of the SoxRS[2Fe-2S] regulon have been investigated and shown to depend on strain genotype, the process of Fe-S cluster assembly in iron-sulfur proteins, NO donor structure, and the presence of Fe2+ chelator ferene in the incubation medium. The antibiotic ciprofloxacine (CF) was used as an inhibitor of E. coli biofilm formation in the positive control. NO donors regulating Fe-S cluster assembly in E. coli have been shown to control plankton growth of the cultures and the process of mature biofilm formation; toxic doses of NO caused a dramatic (3- to 4-fold) stimulation of cell entry into biofilms as a response to nitrosative stress; NO donors CisA and GSNO in physiological concentrations suppressed the formation of mature biofilms, and the activity of these compounds was comparable to that of CE Regulation of both Fe-S cluster assembly in iron-sulfur proteins and biofilm formation by NO is indicative of the connection between these processes in E. coli.

Statistical indicators of collective behavior and functional clusters in gene networks of yeast

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Živković, J.; Tadić, B.; Wick, N.; Thurner, S.

2006-03-01

We analyze gene expression time-series data of yeast (S. cerevisiae) measured along two full cell-cycles. We quantify these data by using q-exponentials, gene expression ranking and a temporal mean-variance analysis. We construct gene interaction networks based on correlation coefficients and study the formation of the corresponding giant components and minimum spanning trees. By coloring genes according to their cell function we find functional clusters in the correlation networks and functional branches in the associated trees. Our results suggest that a percolation point of functional clusters can be identified on these gene expression correlation networks.

PSPP: a protein structure prediction pipeline for computing clusters.

Directory of Open Access Journals (Sweden)

Michael S Lee

2009-07-01

Full Text Available Protein structures are critical for understanding the mechanisms of biological systems and, subsequently, for drug and vaccine design. Unfortunately, protein sequence data exceed structural data by a factor of more than 200 to 1. This gap can be partially filled by using computational protein structure prediction. While structure prediction Web servers are a notable option, they often restrict the number of sequence queries and/or provide a limited set of prediction methodologies. Therefore, we present a standalone protein structure prediction software package suitable for high-throughput structural genomic applications that performs all three classes of prediction methodologies: comparative modeling, fold recognition, and ab initio. This software can be deployed on a user's own high-performance computing cluster.The pipeline consists of a Perl core that integrates more than 20 individual software packages and databases, most of which are freely available from other research laboratories. The query protein sequences are first divided into domains either by domain boundary recognition or Bayesian statistics. The structures of the individual domains are then predicted using template-based modeling or ab initio modeling. The predicted models are scored with a statistical potential and an all-atom force field. The top-scoring ab initio models are annotated by structural comparison against the Structural Classification of Proteins (SCOP fold database. Furthermore, secondary structure, solvent accessibility, transmembrane helices, and structural disorder are predicted. The results are generated in text, tab-delimited, and hypertext markup language (HTML formats. So far, the pipeline has been used to study viral and bacterial proteomes.The standalone pipeline that we introduce here, unlike protein structure prediction Web servers, allows users to devote their own computing assets to process a potentially unlimited number of queries as well as perform

Zinc and the iron donor frataxin regulate oligomerization of the scaffold protein to form new Fe-S cluster assembly centers.

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Galeano, B K; Ranatunga, W; Gakh, O; Smith, D Y; Thompson, J R; Isaya, G

2017-06-21

Early studies of the bacterial Fe-S cluster assembly system provided structural details for how the scaffold protein and the cysteine desulfurase interact. This work and additional work on the yeast and human systems elucidated a conserved mechanism for sulfur donation but did not provide any conclusive insights into the mechanism for iron delivery from the iron donor, frataxin, to the scaffold. We previously showed that oligomerization is a mechanism by which yeast frataxin (Yfh1) can promote assembly of the core machinery for Fe-S cluster synthesis both in vitro and in cells, in such a manner that the scaffold protein, Isu1, can bind to Yfh1 independent of the presence of the cysteine desulfurase, Nfs1. Here, in the absence of Yfh1, Isu1 was found to exist in two forms, one mostly monomeric with limited tendency to dimerize, and one with a strong propensity to oligomerize. Whereas the monomeric form is stabilized by zinc, the loss of zinc promotes formation of dimer and higher order oligomers. However, upon binding to oligomeric Yfh1, both forms take on a similar symmetrical trimeric configuration that places the Fe-S cluster coordinating residues of Isu1 in close proximity of iron-binding residues of Yfh1. This configuration is suitable for docking of Nfs1 in a manner that provides a structural context for coordinate iron and sulfur donation to the scaffold. Moreover, distinct structural features suggest that in physiological conditions the zinc-regulated abundance of monomeric vs. oligomeric Isu1 yields [Yfh1]·[Isu1] complexes with different Isu1 configurations that afford unique functional properties for Fe-S cluster assembly and delivery.

Protein domain organisation: adding order.

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Kummerfeld, Sarah K; Teichmann, Sarah A

2009-01-29

Domains are the building blocks of proteins. During evolution, they have been duplicated, fused and recombined, to produce proteins with novel structures and functions. Structural and genome-scale studies have shown that pairs or groups of domains observed together in a protein are almost always found in only one N to C terminal order and are the result of a single recombination event that has been propagated by duplication of the multi-domain unit. Previous studies of domain organisation have used graph theory to represent the co-occurrence of domains within proteins. We build on this approach by adding directionality to the graphs and connecting nodes based on their relative order in the protein. Most of the time, the linear order of domains is conserved. However, using the directed graph representation we have identified non-linear features of domain organization that are over-represented in genomes. Recognising these patterns and unravelling how they have arisen may allow us to understand the functional relationships between domains and understand how the protein repertoire has evolved. We identify groups of domains that are not linearly conserved, but instead have been shuffled during evolution so that they occur in multiple different orders. We consider 192 genomes across all three kingdoms of life and use domain and protein annotation to understand their functional significance. To identify these features and assess their statistical significance, we represent the linear order of domains in proteins as a directed graph and apply graph theoretical methods. We describe two higher-order patterns of domain organisation: clusters and bi-directionally associated domain pairs and explore their functional importance and phylogenetic conservation. Taking into account the order of domains, we have derived a novel picture of global protein organization. We found that all genomes have a higher than expected degree of clustering and more domain pairs in forward and

Protein domain organisation: adding order

Directory of Open Access Journals (Sweden)

Kummerfeld Sarah K

2009-01-01

Full Text Available Abstract Background Domains are the building blocks of proteins. During evolution, they have been duplicated, fused and recombined, to produce proteins with novel structures and functions. Structural and genome-scale studies have shown that pairs or groups of domains observed together in a protein are almost always found in only one N to C terminal order and are the result of a single recombination event that has been propagated by duplication of the multi-domain unit. Previous studies of domain organisation have used graph theory to represent the co-occurrence of domains within proteins. We build on this approach by adding directionality to the graphs and connecting nodes based on their relative order in the protein. Most of the time, the linear order of domains is conserved. However, using the directed graph representation we have identified non-linear features of domain organization that are over-represented in genomes. Recognising these patterns and unravelling how they have arisen may allow us to understand the functional relationships between domains and understand how the protein repertoire has evolved. Results We identify groups of domains that are not linearly conserved, but instead have been shuffled during evolution so that they occur in multiple different orders. We consider 192 genomes across all three kingdoms of life and use domain and protein annotation to understand their functional significance. To identify these features and assess their statistical significance, we represent the linear order of domains in proteins as a directed graph and apply graph theoretical methods. We describe two higher-order patterns of domain organisation: clusters and bi-directionally associated domain pairs and explore their functional importance and phylogenetic conservation. Conclusion Taking into account the order of domains, we have derived a novel picture of global protein organization. We found that all genomes have a higher than expected

Identification of multiply charged proteins and amino acid clusters by liquid nitrogen assisted spray ionization mass spectrometry.

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Kumar Kailasa, Suresh; Hasan, Nazim; Wu, Hui-Fen

2012-08-15

The development of liquid nitrogen assisted spray ionization mass spectrometry (LNASI MS) for the analysis of multiply charged proteins (insulin, ubiquitin, cytochrome c, α-lactalbumin, myoglobin and BSA), peptides (glutathione, HW6, angiotensin-II and valinomycin) and amino acid (arginine) clusters is described. The charged droplets are formed by liquid nitrogen assisted sample spray through a stainless steel nebulizer and transported into mass analyzer for the identification of multiply charged protein ions. The effects of acids and modifier volumes for the efficient ionization of the above analytes in LNASI MS were carefully investigated. Multiply charged proteins and amino acid clusters were effectively identified by LNASI MS. The present approach can effectively detect the multiply charged states of cytochrome c at 400 nM. A comparison between LNASI and ESI, CSI, SSI and V-EASI methods on instrumental conditions, applied temperature and observed charge states for the multiply charged proteins, shows that the LNASI method produces the good quality spectra of amino acid clusters at ambient conditions without applied any electric field and heat. To date, we believe that the LNASI method is the most simple, low cost and provided an alternative paradigm for production of multiply charged ions by LNASI MS, just as ESI-like ions yet no need for applying any electrical field and it could be operated at low temperature for generation of highly charged protein/peptide ions. Copyright © 2012 Elsevier B.V. All rights reserved.

Constraints on Ωm and σ8 from the potential-based cluster temperature function

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Angrick, Christian; Pace, Francesco; Bartelmann, Matthias; Roncarelli, Mauro

2015-12-01

The abundance of galaxy clusters is in principle a powerful tool to constrain cosmological parameters, especially Ωm and σ8, due to the exponential dependence in the high-mass regime. While the best observables are the X-ray temperature and luminosity, the abundance of galaxy clusters, however, is conventionally predicted as a function of mass. Hence, the intrinsic scatter and the uncertainties in the scaling relations between mass and either temperature or luminosity lower the reliability of galaxy clusters to constrain cosmological parameters. In this article, we further refine the X-ray temperature function for galaxy clusters by Angrick et al., which is based on the statistics of perturbations in the cosmic gravitational potential and proposed to replace the classical mass-based temperature function, by including a refined analytic merger model and compare the theoretical prediction to results from a cosmological hydrodynamical simulation. Although we find already a good agreement if we compare with a cluster temperature function based on the mass-weighted temperature, including a redshift-dependent scaling between mass-based and spectroscopic temperature yields even better agreement between theoretical model and numerical results. As a proof of concept, incorporating this additional scaling in our model, we constrain the cosmological parameters Ωm and σ8 from an X-ray sample of galaxy clusters and tentatively find agreement with the recent cosmic microwave background based results from the Planck mission at 1σ-level.

Conformational transitions and interactions underlying the function of membrane embedded receptor protein kinases.

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Bocharov, Eduard V; Sharonov, Georgy V; Bocharova, Olga V; Pavlov, Konstantin V

2017-09-01

Among membrane receptors, the single-span receptor protein kinases occupy a broad but specific functional niche determined by distinctive features of the underlying transmembrane signaling mechanisms that are briefly overviewed on the basis of some of the most representative examples, followed by a more detailed discussion of several hierarchical levels of organization and interactions involved. All these levels, including single-molecule interactions (e.g., dimerization, liganding, chemical modifications), local processes (e.g. lipid membrane perturbations, cytoskeletal interactions), and larger scale phenomena (e.g., effects of membrane surface shape or electrochemical potential gradients) appear to be closely integrated to achieve the observed diversity of the receptor functioning. Different species of receptor protein kinases meet their specific functional demands through different structural features defining their responses to stimulation, but certain common patterns exist. Signaling by receptor protein kinases is typically associated with the receptor dimerization and clustering, ligand-induced rearrangements of receptor domains through allosteric conformational transitions with involvement of lipids, release of the sequestered lipids, restriction of receptor diffusion, cytoskeleton and membrane shape remodeling. Understanding of complexity and continuity of the signaling processes can help identifying currently neglected opportunities for influencing the receptor signaling with potential therapeutic implications. This article is part of a Special Issue entitled: Interactions between membrane receptors in cellular membranes edited by Kalina Hristova. Copyright © 2017 Elsevier B.V. All rights reserved.

Density functional theory and surface reactivity study of bimetallic AgnYm (n+m = 10) clusters

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Hussain, Riaz; Hussain, Abdullah Ijaz; Chatha, Shahzad Ali Shahid; Hussain, Riaz; Hanif, Usman; Ayub, Khurshid

2018-06-01

Density functional theory calculations have been performed on pure silver (Agn), yttrium (Ym) and bimetallic silver yttrium clusters AgnYm (n + m = 2-10) for reactivity descriptors in order to realize sites for nucleophilic and electrophilic attack. The reactivity descriptors of the clusters, studied as a function of cluster size and shape, reveal the presence of different type of reactive sites in a cluster. The size and shape of the pure silver, yttrium and bimetallic silver yttrium cluster (n = 2-10) strongly influences the number and position of active sites for an electrophilic and/or nucleophilic attack. The trends of reactivities through reactivity descriptors are confirmed through comparison with experimental data for CO binding with silver clusters. Moreover, the adsorption of CO on bimetallic silver yttrium clusters is also evaluated. The trends of binding energies support the reactivity descriptors values. Doping of pure cluster with the other element also influence the hardness, softness and chemical reactivity of the clusters. The softness increases as we increase the number of silver atoms in the cluster, whereas the hardness decreases. The chemical reactivity increases with silver doping whereas it decreases by increasing yttrium concentration. Silver atoms are nucleophilic in small clusters but changed to electrophilic in large clusters.

Incorporating functional inter-relationships into protein function prediction algorithms

Directory of Open Access Journals (Sweden)

Kumar Vipin

2009-05-01

Full Text Available Abstract Background Functional classification schemes (e.g. the Gene Ontology that serve as the basis for annotation efforts in several organisms are often the source of gold standard information for computational efforts at supervised protein function prediction. While successful function prediction algorithms have been developed, few previous efforts have utilized more than the protein-to-functional class label information provided by such knowledge bases. For instance, the Gene Ontology not only captures protein annotations to a set of functional classes, but it also arranges these classes in a DAG-based hierarchy that captures rich inter-relationships between different classes. These inter-relationships present both opportunities, such as the potential for additional training examples for small classes from larger related classes, and challenges, such as a harder to learn distinction between similar GO terms, for standard classification-based approaches. Results We propose a method to enhance the performance of classification-based protein function prediction algorithms by addressing the issue of using these interrelationships between functional classes constituting functional classification schemes. Using a standard measure for evaluating the semantic similarity between nodes in an ontology, we quantify and incorporate these inter-relationships into the k-nearest neighbor classifier. We present experiments on several large genomic data sets, each of which is used for the modeling and prediction of over hundred classes from the GO Biological Process ontology. The results show that this incorporation produces more accurate predictions for a large number of the functional classes considered, and also that the classes benefitted most by this approach are those containing the fewest members. In addition, we show how our proposed framework can be used for integrating information from the entire GO hierarchy for improving the accuracy of

Conserved syntenic clusters of protein coding genes are missing in birds.

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Lovell, Peter V; Wirthlin, Morgan; Wilhelm, Larry; Minx, Patrick; Lazar, Nathan H; Carbone, Lucia; Warren, Wesley C; Mello, Claudio V

2014-01-01

Birds are one of the most highly successful and diverse groups of vertebrates, having evolved a number of distinct characteristics, including feathers and wings, a sturdy lightweight skeleton and unique respiratory and urinary/excretion systems. However, the genetic basis of these traits is poorly understood. Using comparative genomics based on extensive searches of 60 avian genomes, we have found that birds lack approximately 274 protein coding genes that are present in the genomes of most vertebrate lineages and are for the most part organized in conserved syntenic clusters in non-avian sauropsids and in humans. These genes are located in regions associated with chromosomal rearrangements, and are largely present in crocodiles, suggesting that their loss occurred subsequent to the split of dinosaurs/birds from crocodilians. Many of these genes are associated with lethality in rodents, human genetic disorders, or biological functions targeting various tissues. Functional enrichment analysis combined with orthogroup analysis and paralog searches revealed enrichments that were shared by non-avian species, present only in birds, or shared between all species. Together these results provide a clearer definition of the genetic background of extant birds, extend the findings of previous studies on missing avian genes, and provide clues about molecular events that shaped avian evolution. They also have implications for fields that largely benefit from avian studies, including development, immune system, oncogenesis, and brain function and cognition. With regards to the missing genes, birds can be considered ‘natural knockouts’ that may become invaluable model organisms for several human diseases.

Protein Functionalized Nanodiamond Arrays

Directory of Open Access Journals (Sweden)

Liu YL

2010-01-01

Full Text Available Abstract Various nanoscale elements are currently being explored for bio-applications, such as in bio-images, bio-detection, and bio-sensors. Among them, nanodiamonds possess remarkable features such as low bio-cytotoxicity, good optical property in fluorescent and Raman spectra, and good photostability for bio-applications. In this work, we devise techniques to position functionalized nanodiamonds on self-assembled monolayer (SAMs arrays adsorbed on silicon and ITO substrates surface using electron beam lithography techniques. The nanodiamond arrays were functionalized with lysozyme to target a certain biomolecule or protein specifically. The optical properties of the nanodiamond-protein complex arrays were characterized by a high throughput confocal microscope. The synthesized nanodiamond-lysozyme complex arrays were found to still retain their functionality in interacting with E. coli.

The systematic functional analysis of plasmodium protein kinases identifies essential regulators of mosquito transmission

KAUST Repository

Tewari, Rita; Straschil, Ursula; Bateman, Alex; Bö hme, Ulrike; Cherevach, Inna; Gong, Peng; Pain, Arnab; Billker, Oliver

2010-01-01

Although eukaryotic protein kinases (ePKs) contribute to many cellular processes, only three Plasmodium falciparum ePKs have thus far been identified as essential for parasite asexual blood stage development. To identify pathways essential for parasite transmission between their mammalian host and mosquito vector, we undertook a systematic functional analysis of ePKs in the genetically tractable rodent parasite Plasmodium berghei. Modeling domain signatures of conventional ePKs identified 66 putative Plasmodium ePKs. Kinomes are highly conserved between Plasmodium species. Using reverse genetics, we show that 23 ePKs are redundant for asexual erythrocytic parasite development in mice. Phenotyping mutants at four life cycle stages in Anopheles stephensi mosquitoes revealed functional clusters of kinases required for sexual development and sporogony. Roles for a putative SR protein kinase (SRPK) in microgamete formation, a conserved regulator of clathrin uncoating (GAK) in ookinete formation, and a likely regulator of energy metabolism (SNF1/KIN) in sporozoite development were identified. 2010 Elsevier Inc.

The systematic functional analysis of plasmodium protein kinases identifies essential regulators of mosquito transmission

KAUST Repository

Tewari, Rita

2010-10-21

Although eukaryotic protein kinases (ePKs) contribute to many cellular processes, only three Plasmodium falciparum ePKs have thus far been identified as essential for parasite asexual blood stage development. To identify pathways essential for parasite transmission between their mammalian host and mosquito vector, we undertook a systematic functional analysis of ePKs in the genetically tractable rodent parasite Plasmodium berghei. Modeling domain signatures of conventional ePKs identified 66 putative Plasmodium ePKs. Kinomes are highly conserved between Plasmodium species. Using reverse genetics, we show that 23 ePKs are redundant for asexual erythrocytic parasite development in mice. Phenotyping mutants at four life cycle stages in Anopheles stephensi mosquitoes revealed functional clusters of kinases required for sexual development and sporogony. Roles for a putative SR protein kinase (SRPK) in microgamete formation, a conserved regulator of clathrin uncoating (GAK) in ookinete formation, and a likely regulator of energy metabolism (SNF1/KIN) in sporozoite development were identified. 2010 Elsevier Inc.

Roles of Fe-S proteins: from cofactor synthesis to iron homeostasis to protein synthesis.

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Pain, Debkumar; Dancis, Andrew

2016-06-01

Fe-S cluster assembly is an essential process for all cells. Impairment of Fe-S cluster assembly creates diseases in diverse and surprising ways. In one scenario, the loss of function of lipoic acid synthase, an enzyme with Fe-S cluster cofactor in mitochondria, impairs activity of various lipoamide-dependent enzymes with drastic consequences for metabolism. In a second scenario, the heme biosynthetic pathway in red cell precursors is specifically targeted, and iron homeostasis is perturbed, but lipoic acid synthesis is unaffected. In a third scenario, tRNA modifications arising from action of the cysteine desulfurase and/or Fe-S cluster proteins are lost, which may lead to impaired protein synthesis. These defects can then result in cancer, neurologic dysfunction or type 2 diabetes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Defective functional connectivity between posterior hypothalamus and regions of the diencephalic-mesencephalic junction in chronic cluster headache.

Science.gov (United States)

Ferraro, Stefania; Nigri, Anna; Bruzzone, Maria Grazia; Brivio, Luca; Proietti Cecchini, Alberto; Verri, Mattia; Chiapparini, Luisa; Leone, Massimo

2018-01-01

Objective We tested the hypothesis of a defective functional connectivity between the posterior hypothalamus and diencephalic-mesencephalic regions in chronic cluster headache based on: a) clinical and neuro-endocrinological findings in cluster headache patients; b) neuroimaging findings during cluster headache attacks; c) neuroimaging findings in drug-refractory chronic cluster headache patients improved after successful deep brain stimulation. Methods Resting state functional magnetic resonance imaging, associated with a seed-based approach, was employed to investigate the functional connectivity of the posterior hypothalamus in chronic cluster headache patients (n = 17) compared to age and sex-matched healthy subjects (n = 16). Random-effect analyses were performed to study differences between patients and controls in ipsilateral and contralateral-to-the-pain posterior hypothalamus functional connectivity. Results Cluster headache patients showed an increased functional connectivity between the ipsilateral posterior hypothalamus and a number of diencephalic-mesencephalic structures, comprising ventral tegmental area, dorsal nuclei of raphe, and bilateral substantia nigra, sub-thalamic nucleus, and red nucleus ( p cluster headache patients mainly involves structures that are part of (i.e. ventral tegmental area, substantia nigra) or modulate (dorsal nuclei of raphe, sub-thalamic nucleus) the midbrain dopaminergic systems. The midbrain dopaminergic systems could play a role in cluster headache pathophysiology and in particular in the chronicization process. Future studies are needed to better clarify if this finding is specific to cluster headache or if it represents an unspecific response to chronic pain.

Modulated modularity clustering as an exploratory tool for functional genomic inference.

Directory of Open Access Journals (Sweden)

Eric A Stone

2009-05-01

Full Text Available In recent years, the advent of high-throughput assays, coupled with their diminishing cost, has facilitated a systems approach to biology. As a consequence, massive amounts of data are currently being generated, requiring efficient methodology aimed at the reduction of scale. Whole-genome transcriptional profiling is a standard component of systems-level analyses, and to reduce scale and improve inference clustering genes is common. Since clustering is often the first step toward generating hypotheses, cluster quality is critical. Conversely, because the validation of cluster-driven hypotheses is indirect, it is critical that quality clusters not be obtained by subjective means. In this paper, we present a new objective-based clustering method and demonstrate that it yields high-quality results. Our method, modulated modularity clustering (MMC, seeks community structure in graphical data. MMC modulates the connection strengths of edges in a weighted graph to maximize an objective function (called modularity that quantifies community structure. The result of this maximization is a clustering through which tightly-connected groups of vertices emerge. Our application is to systems genetics, and we quantitatively compare MMC both to the hierarchical clustering method most commonly employed and to three popular spectral clustering approaches. We further validate MMC through analyses of human and Drosophila melanogaster expression data, demonstrating that the clusters we obtain are biologically meaningful. We show MMC to be effective and suitable to applications of large scale. In light of these features, we advocate MMC as a standard tool for exploration and hypothesis generation.

Unveiling network-based functional features through integration of gene expression into protein networks.

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Jalili, Mahdi; Gebhardt, Tom; Wolkenhauer, Olaf; Salehzadeh-Yazdi, Ali

2018-06-01

Decoding health and disease phenotypes is one of the fundamental objectives in biomedicine. Whereas high-throughput omics approaches are available, it is evident that any single omics approach might not be adequate to capture the complexity of phenotypes. Therefore, integrated multi-omics approaches have been used to unravel genotype-phenotype relationships such as global regulatory mechanisms and complex metabolic networks in different eukaryotic organisms. Some of the progress and challenges associated with integrated omics studies have been reviewed previously in comprehensive studies. In this work, we highlight and review the progress, challenges and advantages associated with emerging approaches, integrating gene expression and protein-protein interaction networks to unravel network-based functional features. This includes identifying disease related genes, gene prioritization, clustering protein interactions, developing the modules, extract active subnetworks and static protein complexes or dynamic/temporal protein complexes. We also discuss how these approaches contribute to our understanding of the biology of complex traits and diseases. This article is part of a Special Issue entitled: Cardiac adaptations to obesity, diabetes and insulin resistance, edited by Professors Jan F.C. Glatz, Jason R.B. Dyck and Christine Des Rosiers. Copyright © 2018 Elsevier B.V. All rights reserved.

Effect of functionalization of boron nitride flakes by main group metal clusters on their optoelectronic properties

Science.gov (United States)

Chakraborty, Debdutta; Chattaraj, Pratim Kumar

2017-10-01

The possibility of functionalizing boron nitride flakes (BNFs) with some selected main group metal clusters, viz. OLi4, NLi5, CLi6, BLI7 and Al12Be, has been analyzed with the aid of density functional theory (DFT) based computations. Thermochemical as well as energetic considerations suggest that all the metal clusters interact with the BNF moiety in a favorable fashion. As a result of functionalization, the static (first) hyperpolarizability (β ) values of the metal cluster supported BNF moieties increase quite significantly as compared to that in the case of pristine BNF. Time dependent DFT analysis reveals that the metal clusters can lower the transition energies associated with the dominant electronic transitions quite significantly thereby enabling the metal cluster supported BNF moieties to exhibit significant non-linear optical activity. Moreover, the studied systems demonstrate broad band absorption capability spanning the UV-visible as well as infra-red domains. Energy decomposition analysis reveals that the electrostatic interactions principally stabilize the metal cluster supported BNF moieties.

Super Resolution Fluorescence Microscopy and Tracking of Bacterial Flotillin (Reggie Paralogs Provide Evidence for Defined-Sized Protein Microdomains within the Bacterial Membrane but Absence of Clusters Containing Detergent-Resistant Proteins.

Directory of Open Access Journals (Sweden)

Felix Dempwolff

2016-06-01

Full Text Available Biological membranes have been proposed to contain microdomains of a specific lipid composition, in which distinct groups of proteins are clustered. Flotillin-like proteins are conserved between pro-and eukaryotes, play an important function in several eukaryotic and bacterial cells, and define in vertebrates a type of so-called detergent-resistant microdomains. Using STED microscopy, we show that two bacterial flotillins, FloA and FloT, form defined assemblies with an average diameter of 85 to 110 nm in the model bacterium Bacillus subtilis. Interestingly, flotillin microdomains are of similar size in eukaryotic cells. The soluble domains of FloA form higher order oligomers of up to several hundred kDa in vitro, showing that like eukaryotic flotillins, bacterial assemblies are based in part on their ability to self-oligomerize. However, B. subtilis paralogs show significantly different diffusion rates, and consequently do not colocalize into a common microdomain. Dual colour time lapse experiments of flotillins together with other detergent-resistant proteins in bacteria show that proteins colocalize for no longer than a few hundred milliseconds, and do not move together. Our data reveal that the bacterial membrane contains defined-sized protein domains rather than functional microdomains dependent on flotillins. Based on their distinct dynamics, FloA and FloT confer spatially distinguishable activities, but do not serve as molecular scaffolds.

A Comparison between Standard and Functional Clustering Methodologies: Application to Agricultural Fields for Yield Pattern Assessment

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Simone Pascucci

2018-04-01

Full Text Available The recognition of spatial patterns within agricultural fields, presenting similar yield potential areas, stable through time, is very important for optimizing agricultural practices. This study proposes the evaluation of different clustering methodologies applied to multispectral satellite time series for retrieving temporally stable (constant patterns in agricultural fields, related to within-field yield spatial distribution. The ability of different clustering procedures for the recognition and mapping of constant patterns in fields of cereal crops was assessed. Crop vigor patterns, considered to be related to soils characteristics, and possibly indicative of yield potential, were derived by applying the different clustering algorithms to time series of Landsat images acquired on 94 agricultural fields near Rome (Italy. Two different approaches were applied and validated using Landsat 7 and 8 archived imagery. The first approach automatically extracts and calculates for each field of interest (FOI the Normalized Difference Vegetation Index (NDVI, then exploits the standard K-means clustering algorithm to derive constant patterns at the field level. The second approach applies novel clustering procedures directly to spectral reflectance time series, in particular: (1 standard K-means; (2 functional K-means; (3 multivariate functional principal components clustering analysis; (4 hierarchical clustering. The different approaches were validated through cluster accuracy estimates on a reference set of FOIs for which yield maps were available for some years. Results show that multivariate functional principal components clustering, with an a priori determination of the optimal number of classes for each FOI, provides a better accuracy than those of standard clustering algorithms. The proposed novel functional clustering methodologies are effective and efficient for constant pattern retrieval and can be used for a sustainable management of

Controlled expression of nif and isc iron-sulfur protein maturation components reveals target specificity and limited functional replacement between the two systems.

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Dos Santos, Patricia C; Johnson, Deborah C; Ragle, Brook E; Unciuleac, Mihaela-Carmen; Dean, Dennis R

2007-04-01

The nitrogen-fixing organism Azotobacter vinelandii contains at least two systems that catalyze formation of [Fe-S] clusters. One of these systems is encoded by nif genes, whose products supply [Fe-S] clusters required for maturation of nitrogenase. The other system is encoded by isc genes, whose products are required for maturation of [Fe-S] proteins that participate in general metabolic processes. The two systems are similar in that they include an enzyme for the mobilization of sulfur (NifS or IscS) and an assembly scaffold (NifU or IscU) upon which [Fe-S] clusters are formed. Normal cellular levels of the Nif system, which supplies [Fe-S] clusters for the maturation of nitrogenase, cannot also supply [Fe-S] clusters for the maturation of other cellular [Fe-S] proteins. Conversely, when produced at the normal physiological levels, the Isc system cannot supply [Fe-S] clusters for the maturation of nitrogenase. In the present work we found that such target specificity for IscU can be overcome by elevated production of NifU. We also found that NifU, when expressed at normal levels, is able to partially replace the function of IscU if cells are cultured under low-oxygen-availability conditions. In contrast to the situation with IscU, we could not establish conditions in which the function of IscS could be replaced by NifS. We also found that elevated expression of the Isc components, as a result of deletion of the regulatory iscR gene, improved the capacity for nitrogen-fixing growth of strains deficient in either NifU or NifS.

Structural symmetry and protein function.

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Goodsell, D S; Olson, A J

2000-01-01

The majority of soluble and membrane-bound proteins in modern cells are symmetrical oligomeric complexes with two or more subunits. The evolutionary selection of symmetrical oligomeric complexes is driven by functional, genetic, and physicochemical needs. Large proteins are selected for specific morphological functions, such as formation of rings, containers, and filaments, and for cooperative functions, such as allosteric regulation and multivalent binding. Large proteins are also more stable against denaturation and have a reduced surface area exposed to solvent when compared with many individual, smaller proteins. Large proteins are constructed as oligomers for reasons of error control in synthesis, coding efficiency, and regulation of assembly. Symmetrical oligomers are favored because of stability and finite control of assembly. Several functions limit symmetry, such as interaction with DNA or membranes, and directional motion. Symmetry is broken or modified in many forms: quasisymmetry, in which identical subunits adopt similar but different conformations; pleomorphism, in which identical subunits form different complexes; pseudosymmetry, in which different molecules form approximately symmetrical complexes; and symmetry mismatch, in which oligomers of different symmetries interact along their respective symmetry axes. Asymmetry is also observed at several levels. Nearly all complexes show local asymmetry at the level of side chain conformation. Several complexes have reciprocating mechanisms in which the complex is asymmetric, but, over time, all subunits cycle through the same set of conformations. Global asymmetry is only rarely observed. Evolution of oligomeric complexes may favor the formation of dimers over complexes with higher cyclic symmetry, through a mechanism of prepositioned pairs of interacting residues. However, examples have been found for all of the crystallographic point groups, demonstrating that functional need can drive the evolution of

Roles for text mining in protein function prediction.

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Verspoor, Karin M

2014-01-01

The Human Genome Project has provided science with a hugely valuable resource: the blueprints for life; the specification of all of the genes that make up a human. While the genes have all been identified and deciphered, it is proteins that are the workhorses of the human body: they are essential to virtually all cell functions and are the primary mechanism through which biological function is carried out. Hence in order to fully understand what happens at a molecular level in biological organisms, and eventually to enable development of treatments for diseases where some aspect of a biological system goes awry, we must understand the functions of proteins. However, experimental characterization of protein function cannot scale to the vast amount of DNA sequence data now available. Computational protein function prediction has therefore emerged as a problem at the forefront of modern biology (Radivojac et al., Nat Methods 10(13):221-227, 2013).Within the varied approaches to computational protein function prediction that have been explored, there are several that make use of biomedical literature mining. These methods take advantage of information in the published literature to associate specific proteins with specific protein functions. In this chapter, we introduce two main strategies for doing this: association of function terms, represented as Gene Ontology terms (Ashburner et al., Nat Genet 25(1):25-29, 2000), to proteins based on information in published articles, and a paradigm called LEAP-FS (Literature-Enhanced Automated Prediction of Functional Sites) in which literature mining is used to validate the predictions of an orthogonal computational protein function prediction method.

Isomers of Cu6 cluster: a density function theory study

International Nuclear Information System (INIS)

Jia Yanhui; Wang Shanshan; Li Gongping

2008-01-01

The possible structure of Cu 6 cluster has been given with the GaussView that is a graphical user interface software. The structure optimization was performed on the B3LYP functional and SDD basic set of the quantum computational software of Gaussian03. And eight isomers of Cu 6 cluster were calculated. The binding energy and the structure of eight isomers have been investigated in detail. The result showed that the value of the binding energy was in reasonable agreement with available experimental data, as well as with other theoretical results, and the most stable structure was the triangle of plane. Three new isomers of the Cu 6 cluster have been got in our work, which would be the valuable data for the further theoretical and experimental study. (authors)

Function and structure of GFP-like proteins in the protein data bank.

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Ong, Wayne J-H; Alvarez, Samuel; Leroux, Ivan E; Shahid, Ramza S; Samma, Alex A; Peshkepija, Paola; Morgan, Alicia L; Mulcahy, Shawn; Zimmer, Marc

2011-04-01

The RCSB protein databank contains 266 crystal structures of green fluorescent proteins (GFP) and GFP-like proteins. This is the first systematic analysis of all the GFP-like structures in the pdb. We have used the pdb to examine the function of fluorescent proteins (FP) in nature, aspects of excited state proton transfer (ESPT) in FPs, deformation from planarity of the chromophore and chromophore maturation. The conclusions reached in this review are that (1) The lid residues are highly conserved, particularly those on the "top" of the β-barrel. They are important to the function of GFP-like proteins, perhaps in protecting the chromophore or in β-barrel formation. (2) The primary/ancestral function of GFP-like proteins may well be to aid in light induced electron transfer. (3) The structural prerequisites for light activated proton pumps exist in many structures and it's possible that like bioluminescence, proton pumps are secondary functions of GFP-like proteins. (4) In most GFP-like proteins the protein matrix exerts a significant strain on planar chromophores forcing most GFP-like proteins to adopt non-planar chromophores. These chromophoric deviations from planarity play an important role in determining the fluorescence quantum yield. (5) The chemospatial characteristics of the chromophore cavity determine the isomerization state of the chromophore. The cavities of highlighter proteins that can undergo cis/trans isomerization have chemospatial properties that are common to both cis and trans GFP-like proteins.

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

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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.

Fluorescence detection of a protein-bound 2Fe2S cluster.

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Hoff, Kevin G; Goodlitt, Rochelle; Li, Rui; Smolke, Christina D; Silberg, Jonathan J

2009-03-02

A fluorescent biosensor is described for 2Fe2S clusters that is composed of green fluorescent protein (GFP) fused to glutaredoxin 2 (Grx2), as illustrated here. 2Fe2S detection is based on the reduction of GFP fluorescence upon the 2Fe2S-induced dimerization of GFP-Grx2. This assay is sufficiently sensitive to detect submicromolar changes in 2Fe2S levels, thus making it suitable for high-throughput measurements of metallocluster degradation and synthesis reactions.

Anaerobic Copper Toxicity and Iron-Sulfur Cluster Biogenesis in Escherichia coli.

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Tan, Guoqiang; Yang, Jing; Li, Tang; Zhao, Jin; Sun, Shujuan; Li, Xiaokang; Lin, Chuxian; Li, Jianghui; Zhou, Huaibin; Lyu, Jianxin; Ding, Huangen

2017-08-15

are under aerobic conditions. Under anaerobic conditions, E. coli cells accumulate excess intracellular copper, which specifically targets iron-sulfur proteins by blocking iron-sulfur cluster biogenesis. Since iron-sulfur proteins are involved in diverse and vital physiological processes, inhibition of iron-sulfur cluster biogenesis by copper disrupts multiple cellular functions and ultimately inhibits cell growth. The results from this study illustrate a new interplay between intracellular copper toxicity and iron-sulfur cluster biogenesis in bacterial cells under anaerobic conditions. Copyright © 2017 American Society for Microbiology.

Quantitative protein localization signatures reveal an association between spatial and functional divergences of proteins.

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Loo, Lit-Hsin; Laksameethanasan, Danai; Tung, Yi-Ling

2014-03-01

Protein subcellular localization is a major determinant of protein function. However, this important protein feature is often described in terms of discrete and qualitative categories of subcellular compartments, and therefore it has limited applications in quantitative protein function analyses. Here, we present Protein Localization Analysis and Search Tools (PLAST), an automated analysis framework for constructing and comparing quantitative signatures of protein subcellular localization patterns based on microscopy images. PLAST produces human-interpretable protein localization maps that quantitatively describe the similarities in the localization patterns of proteins and major subcellular compartments, without requiring manual assignment or supervised learning of these compartments. Using the budding yeast Saccharomyces cerevisiae as a model system, we show that PLAST is more accurate than existing, qualitative protein localization annotations in identifying known co-localized proteins. Furthermore, we demonstrate that PLAST can reveal protein localization-function relationships that are not obvious from these annotations. First, we identified proteins that have similar localization patterns and participate in closely-related biological processes, but do not necessarily form stable complexes with each other or localize at the same organelles. Second, we found an association between spatial and functional divergences of proteins during evolution. Surprisingly, as proteins with common ancestors evolve, they tend to develop more diverged subcellular localization patterns, but still occupy similar numbers of compartments. This suggests that divergence of protein localization might be more frequently due to the development of more specific localization patterns over ancestral compartments than the occupation of new compartments. PLAST enables systematic and quantitative analyses of protein localization-function relationships, and will be useful to elucidate protein

Scoring functions for protein-protein interactions.

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Moal, Iain H; Moretti, Rocco; Baker, David; Fernández-Recio, Juan

2013-12-01

The computational evaluation of protein-protein interactions will play an important role in organising the wealth of data being generated by high-throughput initiatives. Here we discuss future applications, report recent developments and identify areas requiring further investigation. Many functions have been developed to quantify the structural and energetic properties of interacting proteins, finding use in interrelated challenges revolving around the relationship between sequence, structure and binding free energy. These include loop modelling, side-chain refinement, docking, multimer assembly, affinity prediction, affinity change upon mutation, hotspots location and interface design. Information derived from models optimised for one of these challenges can be used to benefit the others, and can be unified within the theoretical frameworks of multi-task learning and Pareto-optimal multi-objective learning. Copyright © 2013 Elsevier Ltd. All rights reserved.

Structure and Stability of GeAun, n = 1-10 clusters: A Density Functional Study

International Nuclear Information System (INIS)

Priyanka,; Dharamvir, Keya; Sharma, Hitesh

2011-01-01

The structures of Germanium doped gold clusters GeAu n (n = 1-10) have been investigated using ab initio calculations based on density functional theory (DFT). We have obtained ground state geometries of GeAu n clusters and have it compared with Silicon doped gold clusters and pure gold clusters. The ground state geometries of the GeAu n clusters show patterns similar to silicon doped gold clusters except for n = 5, 6 and 9. The introduction of germanium atom increases the binding energy of gold clusters. The binding energy per atom of germanium doped cluster is smaller than the corresponding silicon doped gold cluster. The HUMO-LOMO gap for Au n Ge clusters have been found to vary between 0.46 eV-2.09 eV. The mullikan charge analysis indicates that charge of order of 0.1e always transfers from germanium atom to gold atom.

Interaction of proteins with ionic liquid, alcohol and DMSO and in situ generation of gold nano-clusters in a cell.

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Nandi, Somen; Parui, Sridip; Halder, Ritaban; Jana, Biman; Bhattacharyya, Kankan

2018-06-01

In this review, we give a brief overview on how the interaction of proteins with ionic liquids, alcohols and dimethyl sulfoxide (DMSO) influences the stability, conformational dynamics and function of proteins/enzymes. We present experimental results obtained from fluorescence correlation spectroscopy on the effect of ionic liquid or alcohol or DMSO on the size (more precisely, the diffusion constant) and conformational dynamics of lysozyme, cytochrome c and human serum albumin in aqueous solution. The interaction of ionic liquid with biomolecules (e.g. protein, DNA etc.) has emerged as a current frontier. We demonstrate that ionic liquids are excellent stabilizers of protein and DNA and, in some cases, cause refolding of a protein already denatured by chemical denaturing agents. We show that in ethanol-water binary mixture, proteins undergo non-monotonic changes in size and dynamics with increasing ethanol content. We also discuss the effect of water-DMSO mixture on the stability of proteins. We demonstrate how large-scale molecular dynamics simulations have revealed the molecular origin of this observed phenomenon and provide a microscopic picture of the immediate environment of the biomolecules. Finally, we describe how favorable interactions of ionic liquids may be utilized for in situ generation of fluorescent gold nano-clusters for imaging a live cell.

Recognition of functional sites in protein structures.

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Shulman-Peleg, Alexandra; Nussinov, Ruth; Wolfson, Haim J

2004-06-04

Recognition of regions on the surface of one protein, that are similar to a binding site of another is crucial for the prediction of molecular interactions and for functional classifications. We first describe a novel method, SiteEngine, that assumes no sequence or fold similarities and is able to recognize proteins that have similar binding sites and may perform similar functions. We achieve high efficiency and speed by introducing a low-resolution surface representation via chemically important surface points, by hashing triangles of physico-chemical properties and by application of hierarchical scoring schemes for a thorough exploration of global and local similarities. We proceed to rigorously apply this method to functional site recognition in three possible ways: first, we search a given functional site on a large set of complete protein structures. Second, a potential functional site on a protein of interest is compared with known binding sites, to recognize similar features. Third, a complete protein structure is searched for the presence of an a priori unknown functional site, similar to known sites. Our method is robust and efficient enough to allow computationally demanding applications such as the first and the third. From the biological standpoint, the first application may identify secondary binding sites of drugs that may lead to side-effects. The third application finds new potential sites on the protein that may provide targets for drug design. Each of the three applications may aid in assigning a function and in classification of binding patterns. We highlight the advantages and disadvantages of each type of search, provide examples of large-scale searches of the entire Protein Data Base and make functional predictions.

Crystal structure of Mycobacterium tuberculosis O6-methylguanine-DNA methyltransferase protein clusters assembled on to damaged DNA.

Science.gov (United States)

Miggiano, Riccardo; Perugino, Giuseppe; Ciaramella, Maria; Serpe, Mario; Rejman, Dominik; Páv, Ondřej; Pohl, Radek; Garavaglia, Silvia; Lahiri, Samarpita; Rizzi, Menico; Rossi, Franca

2016-01-15

Mycobacterium tuberculosis O(6)-methylguanine-DNA methyltransferase (MtOGT) contributes to protect the bacterial GC-rich genome against the pro-mutagenic potential of O(6)-methylated guanine in DNA. Several strains of M. tuberculosis found worldwide encode a point-mutated O(6)-methylguanine-DNA methyltransferase (OGT) variant (MtOGT-R37L), which displays an arginine-to-leucine substitution at position 37 of the poorly functionally characterized N-terminal domain of the protein. Although the impact of this mutation on the MtOGT activity has not yet been proved in vivo, we previously demonstrated that a recombinant MtOGT-R37L variant performs a suboptimal alkylated-DNA repair in vitro, suggesting a direct role for the Arg(37)-bearing region in catalysis. The crystal structure of MtOGT complexed with modified DNA solved in the present study reveals details of the protein-protein and protein-DNA interactions occurring during alkylated-DNA binding, and the protein capability also to host unmodified bases inside the active site, in a fully extrahelical conformation. Our data provide the first experimental picture at the atomic level of a possible mode of assembling three adjacent MtOGT monomers on the same monoalkylated dsDNA molecule, and disclose the conformational flexibility of discrete regions of MtOGT, including the Arg(37)-bearing random coil. This peculiar structural plasticity of MtOGT could be instrumental to proper protein clustering at damaged DNA sites, as well as to protein-DNA complexes disassembling on repair. © 2016 Authors; published by Portland Press Limited.

Low-mass stars in globular clusters. III. The mass function of 47 Tucanae.

Science.gov (United States)

de Marchi, G.; Paresce, F.

1995-12-01

We have used the WFPC2 on board HST to investigate the stellar population in a field located 4'6 E of the center of the globular cluster 47 Tuc (NGC 104), close to the half-mass radius, through wide band imaging at 606 and 812nm. A total of ~3000 stars are accurately classified by two-color photometry to form a color-magnitude diagram extending down to a limiting magnitude m_814_=~m_I_=~24. A rich cluster main sequence is detected spanning the range from m_814_=~18 through m_814_=~23, where it spreads considerably due to the increasing photometric uncertainty and galaxy contamination. A secondary sequence of objects is also detected, parallel to the main sequence, as expected for a population of binary stars. The measured binary fraction in the range 195%. The main sequence luminosity function obtained from the observed CMD increases with decreasing luminosity following a power-law trend with index α=~0.15 in the range 5crowding. On the basis of the available mass-luminosity relation for this metallicity, the resultant mass function shows a power-law increase in numbers for decreasing masses in the range 0.8-0.3Msun_ with a slope α=~1.5, but then flattens out in the 0.3-0.15Msun_ range. The comparison of the mass function of 47 Tuc with that of NGC 6397 (Paper I) and of M 15 (Paper II), previously investigated with the same instrumentation, suggests that the stellar population near the half-mass radius of these clusters should not be very sensitive to either internal or externally-driven dynamical processes. The difference between their mass functions could then be attributed to metallicity, reflecting an intrinsic difference in their initial mass functions, unless mass-segregation is stronger in 47 Tuc than in the other two clusters. This latter circumstance could be due, for instance, to the large number of binaries discovered in 47 Tuc. In all cases, however, the mass function is found to flatten below 0.3Msun_ and the flattening is most likely an intrinsic

Prediction of functional sites in proteins using conserved functional group analysis.

Science.gov (United States)

Innis, C Axel; Anand, A Prem; Sowdhamini, R

2004-04-02

A detailed knowledge of a protein's functional site is an absolute prerequisite for understanding its mode of action at the molecular level. However, the rapid pace at which sequence and structural information is being accumulated for proteins greatly exceeds our ability to determine their biochemical roles experimentally. As a result, computational methods are required which allow for the efficient processing of the evolutionary information contained in this wealth of data, in particular that related to the nature and location of functionally important sites and residues. The method presented here, referred to as conserved functional group (CFG) analysis, relies on a simplified representation of the chemical groups found in amino acid side-chains to identify functional sites from a single protein structure and a number of its sequence homologues. We show that CFG analysis can fully or partially predict the location of functional sites in approximately 96% of the 470 cases tested and that, unlike other methods available, it is able to tolerate wide variations in sequence identity. In addition, we discuss its potential in a structural genomics context, where automation, scalability and efficiency are critical, and an increasing number of protein structures are determined with no prior knowledge of function. This is exemplified by our analysis of the hypothetical protein Ydde_Ecoli, whose structure was recently solved by members of the North East Structural Genomics consortium. Although the proposed active site for this protein needs to be validated experimentally, this example illustrates the scope of CFG analysis as a general tool for the identification of residues likely to play an important role in a protein's biochemical function. Thus, our method offers a convenient solution to rapidly and automatically process the vast amounts of data that are beginning to emerge from structural genomics projects.

Differential Retention of Gene Functions in a Secondary Metabolite Cluster.

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Reynolds, Hannah T; Slot, Jason C; Divon, Hege H; Lysøe, Erik; Proctor, Robert H; Brown, Daren W

2017-08-01

In fungi, distribution of secondary metabolite (SM) gene clusters is often associated with host- or environment-specific benefits provided by SMs. In the plant pathogen Alternaria brassicicola (Dothideomycetes), the DEP cluster confers an ability to synthesize the SM depudecin, a histone deacetylase inhibitor that contributes weakly to virulence. The DEP cluster includes genes encoding enzymes, a transporter, and a transcription regulator. We investigated the distribution and evolution of the DEP cluster in 585 fungal genomes and found a wide but sporadic distribution among Dothideomycetes, Sordariomycetes, and Eurotiomycetes. We confirmed DEP gene expression and depudecin production in one fungus, Fusarium langsethiae. Phylogenetic analyses suggested 6-10 horizontal gene transfers (HGTs) of the cluster, including a transfer that led to the presence of closely related cluster homologs in Alternaria and Fusarium. The analyses also indicated that HGTs were frequently followed by loss/pseudogenization of one or more DEP genes. Independent cluster inactivation was inferred in at least four fungal classes. Analyses of transitions among functional, pseudogenized, and absent states of DEP genes among Fusarium species suggest enzyme-encoding genes are lost at higher rates than the transporter (DEP3) and regulatory (DEP6) genes. The phenotype of an experimentally-induced DEP3 mutant of Fusarium did not support the hypothesis that selective retention of DEP3 and DEP6 protects fungi from exogenous depudecin. Together, the results suggest that HGT and gene loss have contributed significantly to DEP cluster distribution, and that some DEP genes provide a greater fitness benefit possibly due to a differential tendency to form network connections. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution 2017. This work is written by US Government employees and is in the public domain in the US.

High-temperature protein G is essential for activity of the Escherichia coli clustered regularly interspaced short palindromic repeats (CRISPR)/Cas system.

Science.gov (United States)

Yosef, Ido; Goren, Moran G; Kiro, Ruth; Edgar, Rotem; Qimron, Udi

2011-12-13

Prokaryotic DNA arrays arranged as clustered regularly interspaced short palindromic repeats (CRISPR), along with their associated proteins, provide prokaryotes with adaptive immunity by RNA-mediated targeting of alien DNA or RNA matching the sequences between the repeats. Here, we present a thorough screening system for the identification of bacterial proteins participating in immunity conferred by the Escherichia coli CRISPR system. We describe the identification of one such protein, high-temperature protein G (HtpG), a homolog of the eukaryotic chaperone heat-shock protein 90. We demonstrate that in the absence of htpG, the E. coli CRISPR system loses its suicidal activity against λ prophage and its ability to provide immunity from lysogenization. Transcomplementation of htpG restores CRISPR activity. We further show that inactivity of the CRISPR system attributable to htpG deficiency can be suppressed by expression of Cas3, a protein that is essential for its activity. Accordingly, we also find that the steady-state level of overexpressed Cas3 is significantly enhanced following HtpG expression. We conclude that HtpG is a newly identified positive modulator of the CRISPR system that is essential for maintaining functional levels of Cas3.

The externally corrected coupled cluster approach with four- and five-body clusters from the CASSCF wave function.

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Xu, Enhua; Li, Shuhua

2015-03-07

An externally corrected CCSDt (coupled cluster with singles, doubles, and active triples) approach employing four- and five-body clusters from the complete active space self-consistent field (CASSCF) wave function (denoted as ecCCSDt-CASSCF) is presented. The quadruple and quintuple excitation amplitudes within the active space are extracted from the CASSCF wave function and then fed into the CCSDt-like equations, which can be solved in an iterative way as the standard CCSDt equations. With a size-extensive CASSCF reference function, the ecCCSDt-CASSCF method is size-extensive. When the CASSCF wave function is readily available, the computational cost of the ecCCSDt-CASSCF method scales as the popular CCSD method (if the number of active orbitals is small compared to the total number of orbitals). The ecCCSDt-CASSCF approach has been applied to investigate the potential energy surface for the simultaneous dissociation of two O-H bonds in H2O, the equilibrium distances and spectroscopic constants of 4 diatomic molecules (F2(+), O2(+), Be2, and NiC), and the reaction barriers for the automerization reaction of cyclobutadiene and the Cl + O3 → ClO + O2 reaction. In most cases, the ecCCSDt-CASSCF approach can provide better results than the CASPT2 (second order perturbation theory with a CASSCF reference function) and CCSDT methods.

Information processing architecture of functionally defined clusters in the macaque cortex.

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Shen, Kelly; Bezgin, Gleb; Hutchison, R Matthew; Gati, Joseph S; Menon, Ravi S; Everling, Stefan; McIntosh, Anthony R

2012-11-28

Computational and empirical neuroimaging studies have suggested that the anatomical connections between brain regions primarily constrain their functional interactions. Given that the large-scale organization of functional networks is determined by the temporal relationships between brain regions, the structural limitations may extend to the global characteristics of functional networks. Here, we explored the extent to which the functional network community structure is determined by the underlying anatomical architecture. We directly compared macaque (Macaca fascicularis) functional connectivity (FC) assessed using spontaneous blood oxygen level-dependent functional magnetic resonance imaging (BOLD-fMRI) to directed anatomical connectivity derived from macaque axonal tract tracing studies. Consistent with previous reports, FC increased with increasing strength of anatomical connection, and FC was also present between regions that had no direct anatomical connection. We observed moderate similarity between the FC of each region and its anatomical connectivity. Notably, anatomical connectivity patterns, as described by structural motifs, were different within and across functional modules: partitioning of the functional network was supported by dense bidirectional anatomical connections within clusters and unidirectional connections between clusters. Together, our data directly demonstrate that the FC patterns observed in resting-state BOLD-fMRI are dictated by the underlying neuroanatomical architecture. Importantly, we show how this architecture contributes to the global organizational principles of both functional specialization and integration.

The functional properties, modification and utilization of whey proteins

Directory of Open Access Journals (Sweden)

B. G. Venter

1986-03-01

Full Text Available Whey protein has an excellent nutritional value and exhibits a functional potential. In comparison with certain other food proteins, the whey protein content of essential amino acids is extremely favourable for human consumption. Depending on the heat-treatment history thereof, soluble whey proteins with utilizable functional properties, apart from high biological value, true digestibility, protein efficiency ratio and nett protein utilization, can be recovered. Various technological and chemical recovery processes have been designed. Chemically and enzymatically modified whey protein is manufactured to obtain technological and functional advantages. The important functional properties of whey proteins, namely hydration, gelation, emulsifying and foaming properties, are reviewed.

Density functional studies: First principles and semiempirical calculations of clusters and surfaces

International Nuclear Information System (INIS)

Sinnott, S.B.

1993-01-01

In the research presented here, various theoretical electronic structure techniques are utilized to analyze widely different systems from silicon clusters to transition metal solids and surfaces. For the silicon clusters, first principles density functional methods are used to investigate Si N for N = 2-8. The goal is to understand the different types of bonding that can occur in such small clusters where the coordination of the atoms differs substantially from that of the stable bulk tetrahedral bonding. Such uncoordinated structures can provide a good test of more approximate theories that can be used eventually to model silicon surfaces, of obvious technological importance. For the transition metal systems, non-self-consistent electronic structure methods are used to provide an understanding of the driving force for surface relaxations. An in-depth analysis of the results is presented and the physical basis of surface relaxation within the theory is discussed. In addition, the limitations inherent in calculations of metal surface relaxation are addressed. Finally, in an effort to increase understanding of approximate methods, a novel non-self-consistent density functional electronic structure method is developed that is ∼1000 times faster computationally than more sophisticated methods. This new method is tested for a variety of systems including diatomics, mixed clusters, surfaces and bulk lattices. The strengths and weaknesses of the new theory are discussed in detail, leading to greater understanding of non-self-consistent density functional theories as a whole

Hot-spot analysis to dissect the functional protein-protein interface of a tRNA-modifying enzyme.

Science.gov (United States)

Jakobi, Stephan; Nguyen, Tran Xuan Phong; Debaene, François; Metz, Alexander; Sanglier-Cianférani, Sarah; Reuter, Klaus; Klebe, Gerhard

2014-10-01

Interference with protein-protein interactions of interfaces larger than 1500 Ų by small drug-like molecules is notoriously difficult, particularly if targeting homodimers. The tRNA modifying enzyme Tgt is only functionally active as a homodimer. Thus, blocking Tgt dimerization is a promising strategy for drug therapy as this protein is key to the development of Shigellosis. Our goal was to identify hot-spot residues which, upon mutation, result in a predominantly monomeric state of Tgt. The detailed understanding of the spatial location and stability contribution of the individual interaction hot-spot residues and the plasticity of motifs involved in the interface formation is a crucial prerequisite for the rational identification of drug-like inhibitors addressing the respective dimerization interface. Using computational analyses, we identified hot-spot residues that contribute particularly to dimer stability: a cluster of hydrophobic and aromatic residues as well as several salt bridges. This in silico prediction led to the identification of a promising double mutant, which was validated experimentally. Native nano-ESI mass spectrometry showed that the dimerization of the suggested mutant is largely prevented resulting in a predominantly monomeric state. Crystal structure analysis and enzyme kinetics of the mutant variant further support the evidence for enhanced monomerization and provide first insights into the structural consequences of the dimer destabilization. © 2014 Wiley Periodicals, Inc.

Conformational Clusters of Phosphorylated Tyrosine.

Science.gov (United States)

Abdelrasoul, Maha; Ponniah, Komala; Mao, Alice; Warden, Meghan S; Elhefnawy, Wessam; Li, Yaohang; Pascal, Steven M

2017-12-06

Tyrosine phosphorylation plays an important role in many cellular and intercellular processes including signal transduction, subcellular localization, and regulation of enzymatic activity. In 1999, Blom et al., using the limited number of protein data bank (PDB) structures available at that time, reported that the side chain structures of phosphorylated tyrosine (pY) are partitioned into two conserved conformational clusters ( Blom, N.; Gammeltoft, S.; Brunak, S. J. Mol. Biol. 1999 , 294 , 1351 - 1362 ). We have used the spectral clustering algorithm to cluster the increasingly growing number of protein structures with pY sites, and have found that the pY residues cluster into three distinct side chain conformations. Two of these pY conformational clusters associate strongly with a narrow range of tyrosine backbone conformation. The novel cluster also highly correlates with the identity of the n + 1 residue, and is strongly associated with a sequential pYpY conformation which places two adjacent pY side chains in a specific relative orientation. Further analysis shows that the three pY clusters are associated with distinct distributions of cognate protein kinases.

The Luminosity Functions of Old and Intermediate-Age Globular Clusters in NGC 3610

OpenAIRE

Whitmore, B. C.; Schweizer, F.; Kundu, A.; Miller, B. W.

2002-01-01

The WFPC2 Camera on board HST has been used to obtain high-resolution images of NGC 3610, a dynamically young elliptical galaxy. These observations supersede shorter, undithered HST observations where an intermediate-age population of globular clusters was first discovered. The new observations show the bimodal color distribution of globular clusters more clearly, with peaks at (V-I)o = 0.95 and 1.17. The luminosity function (LF) of the blue, metal-poor population of clusters in NGC 3610 turn...

Symmetrized partial-wave method for density-functional cluster calculations

International Nuclear Information System (INIS)

Averill, F.W.; Painter, G.S.

1994-01-01

The computational advantage and accuracy of the Harris method is linked to the simplicity and adequacy of the reference-density model. In an earlier paper, we investigated one way the Harris functional could be extended to systems outside the limits of weakly interacting atoms by making the charge density of the interacting atoms self-consistent within the constraints of overlapping spherical atomic densities. In the present study, a method is presented for augmenting the interacting atom charge densities with symmetrized partial-wave expansions on each atomic site. The added variational freedom of the partial waves leads to a scheme capable of giving exact results within a given exchange-correlation approximation while maintaining many of the desirable convergence and stability properties of the original Harris method. Incorporation of the symmetry of the cluster in the partial-wave construction further reduces the level of computational effort. This partial-wave cluster method is illustrated by its application to the dimer C 2 , the hypothetical atomic cluster Fe 6 Al 8 , and the benzene molecule

Comparative analysis of clustering methods for gene expression time course data

Directory of Open Access Journals (Sweden)

Ivan G. Costa

2004-01-01

Full Text Available This work performs a data driven comparative study of clustering methods used in the analysis of gene expression time courses (or time series. Five clustering methods found in the literature of gene expression analysis are compared: agglomerative hierarchical clustering, CLICK, dynamical clustering, k-means and self-organizing maps. In order to evaluate the methods, a k-fold cross-validation procedure adapted to unsupervised methods is applied. The accuracy of the results is assessed by the comparison of the partitions obtained in these experiments with gene annotation, such as protein function and series classification.

The quantitative assessment of the role played by basic amino acid clusters in the nuclear uptake of human ribosomal protein L7

International Nuclear Information System (INIS)

Tai, Lin-Ru; Chou, Chang-Wei; Lee, I-Fang; Kirby, Ralph; Lin, Alan

2013-01-01

In this study, we used a multiple copy (EGFP) 3 reporter system to establish a numeric nuclear index system to assess the degree of nuclear import. The system was first validated by a FRAP assay, and then was applied to evaluate the essential and multifaceted nature of basic amino acid clusters during the nuclear import of ribosomal protein L7. The results indicate that the sequence context of the basic cluster determines the degree of nuclear import, and that the number of basic residues in the cluster is irrelevant; rather the position of the pertinent basic residues is crucial. Moreover, it also found that the type of carrier protein used by basic cluster has a great impact on the degree of nuclear import. In case of L7, importin β2 or importin β3 are preferentially used by clusters with a high import efficiency, notwithstanding that other importins are also used by clusters with a weaker level of nuclear import. Such a preferential usage of multiple basic clusters and importins to gain nuclear entry would seem to be a common practice among ribosomal proteins in order to ensure their full participation in high rate ribosome synthesis. - Highlights: ► We introduce a numeric index system that represents the degree of nuclear import. ► The rate of nuclear import is dictated by the sequence context of the basic cluster. ► Importin β2 and β3 were mainly responsible for the N4 mediated nuclear import

The quantitative assessment of the role played by basic amino acid clusters in the nuclear uptake of human ribosomal protein L7

Energy Technology Data Exchange (ETDEWEB)

Tai, Lin-Ru [Institute of Genome Sciences, National Yang-Ming University, Taipei, Taiwan, ROC (China); Chou, Chang-Wei [Institute of Clinical Dentistry Science, National Yang-Ming University, Taipei, Taiwan, ROC (China); Lee, I-Fang; Kirby, Ralph [Institute of Genome Sciences, National Yang-Ming University, Taipei, Taiwan, ROC (China); Lin, Alan, E-mail: alin@ym.edu.tw [Institute of Genome Sciences, National Yang-Ming University, Taipei, Taiwan, ROC (China); Institute of Clinical Dentistry Science, National Yang-Ming University, Taipei, Taiwan, ROC (China)

2013-02-15

In this study, we used a multiple copy (EGFP){sub 3} reporter system to establish a numeric nuclear index system to assess the degree of nuclear import. The system was first validated by a FRAP assay, and then was applied to evaluate the essential and multifaceted nature of basic amino acid clusters during the nuclear import of ribosomal protein L7. The results indicate that the sequence context of the basic cluster determines the degree of nuclear import, and that the number of basic residues in the cluster is irrelevant; rather the position of the pertinent basic residues is crucial. Moreover, it also found that the type of carrier protein used by basic cluster has a great impact on the degree of nuclear import. In case of L7, importin β2 or importin β3 are preferentially used by clusters with a high import efficiency, notwithstanding that other importins are also used by clusters with a weaker level of nuclear import. Such a preferential usage of multiple basic clusters and importins to gain nuclear entry would seem to be a common practice among ribosomal proteins in order to ensure their full participation in high rate ribosome synthesis. - Highlights: ► We introduce a numeric index system that represents the degree of nuclear import. ► The rate of nuclear import is dictated by the sequence context of the basic cluster. ► Importin β2 and β3 were mainly responsible for the N4 mediated nuclear import.

Investigating the Correspondence Between Transcriptomic and Proteomic Expression Profiles Using Coupled Cluster Models

International Nuclear Information System (INIS)

Rogers, Simon; Girolami, Mark; Kolch, Walter; Waters, Katrina M.; Liu, Tao; Thrall, Brian D.; Wiley, H. S.

2008-01-01

Modern transcriptomics and proteomics enable us to survey the expression of RNAs and proteins at large scales. While these data are usually generated and analyzed separately, there is an increasing interest in comparing and co-analyzing transcriptome and proteome expression data. A major open question is whether transcriptome and proteome expression is linked and how it is coordinated. Results: Here we have developed a probabilistic clustering model that permits analysis of the links between transcriptomic and proteomic profiles in a sensible and flexible manner. Our coupled mixture model defines a prior probability distribution over the component to which a protein profile should be assigned conditioned on which component the associated mRNA profile belongs to. By providing probabilistic assignments this approach sits between the two extremes of concatenating the data on the assumption that mRNA and protein clusters would have a one-to-one relationship, and independent clustering where the mRNA profile provides no information on the protein profile and vice-versa. We apply this approach to a large dataset of quantitative transcriptomic and proteomic expression data obtained from a human breast epithelial cell line (HMEC) stimulated by epidermal growth factor (EGF) over a series of timepoints corresponding to one cell cycle. The results reveal a complex relationship between transcriptome and proteome with most mRNA clusters linked to at least two protein clusters, and vice versa. A more detailed analysis incorporating information on gene function from the gene ontology database shows that a high correlation of mRNA and protein expression is limited to the components of some molecular machines, such as the ribosome, cell adhesion complexes and the TCP-1 chaperonin involved in protein folding. Conclusions: The dynamic regulation of the transcriptome and proteome in mammalian cells in response to an acute mitogenic stimulus appears largely independent with very little

Anchoring selenido-carbonyl ruthenium clusters to functionalized silica xerogels

International Nuclear Information System (INIS)

Cauzzi, Daniele; Graiff, Claudia; Pattacini, Roberto; Predieri, Giovanni; Tiripicchio, Antonio

2003-01-01

Silica Xerogels containing carbonyl Ru 3 Se 2 nido clusters were prepared in three different ways. The simple dispersion of [Ru 3 (μ 3 -Se) 2 (CO) 7 (PPh 3 ) 2 ] via sol gel process produces an inhomogeneous material; by contrast, homogeneous xerogels were obtained by reaction of [Ru 3 (μ 3 -Se) 2 (CO) 8 (PPh 3 )] with functionalized xerogels containing grafted diphenylphosphine moieties and by reaction of [Ru 3 (CO) 12 ] with a xerogel containing grafted phosphine-selenide groups. The reaction between [Ru 3 (CO) 12 ] and dodecyl diphenylphosphine selenide led to the formation of four selenido carbonyl clusters, which are soluble in hydrocarbon solvents and can be deposited as thin films from their solution by slow evaporation. (author)

Functional Principal Component Analysis and Randomized Sparse Clustering Algorithm for Medical Image Analysis

Science.gov (United States)

Lin, Nan; Jiang, Junhai; Guo, Shicheng; Xiong, Momiao

2015-01-01

Due to the advancement in sensor technology, the growing large medical image data have the ability to visualize the anatomical changes in biological tissues. As a consequence, the medical images have the potential to enhance the diagnosis of disease, the prediction of clinical outcomes and the characterization of disease progression. But in the meantime, the growing data dimensions pose great methodological and computational challenges for the representation and selection of features in image cluster analysis. To address these challenges, we first extend the functional principal component analysis (FPCA) from one dimension to two dimensions to fully capture the space variation of image the signals. The image signals contain a large number of redundant features which provide no additional information for clustering analysis. The widely used methods for removing the irrelevant features are sparse clustering algorithms using a lasso-type penalty to select the features. However, the accuracy of clustering using a lasso-type penalty depends on the selection of the penalty parameters and the threshold value. In practice, they are difficult to determine. Recently, randomized algorithms have received a great deal of attentions in big data analysis. This paper presents a randomized algorithm for accurate feature selection in image clustering analysis. The proposed method is applied to both the liver and kidney cancer histology image data from the TCGA database. The results demonstrate that the randomized feature selection method coupled with functional principal component analysis substantially outperforms the current sparse clustering algorithms in image cluster analysis. PMID:26196383

Accurate density-functional calculations on large systems: Fullerenes and magnetic clusters

International Nuclear Information System (INIS)

Dunlap, B.I.

1996-01-01

Efforts to accurately compute all-electron density-functional energies for large molecules and clusters using Gaussian basis sets will be reviewed. The foundation of this effort, variational fitting, will be described and followed by three applications of the method. The first application concerns fullerenes. When first discovered, C 60 is quite unstable relative to the higher fullerenes. In addition, to raising questions about the relative abundance of the various fullerenes, this work conflicted with the then state-of-the art density-funcitonal calculations on crystalline graphite. Now high accuracy molecular and band structure calculations are in fairly good agreement. Second, we have used these methods to design transition metal clusters having the highest magnetic moment by maximizing the symmetry-required degeneracy of the one-electron orbitals. Most recently, we have developed accurate, variational generalized-gradient approximation (GGA) forces for use in geometry optimization of clusters and in molecular-dynamics simulations of friction. The GGA optimized geometries of a number of large clusters will be given

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.

Exploring Protein Function Using the Saccharomyces Genome Database.

Science.gov (United States)

Wong, Edith D

2017-01-01

Elucidating the function of individual proteins will help to create a comprehensive picture of cell biology, as well as shed light on human disease mechanisms, possible treatments, and cures. Due to its compact genome, and extensive history of experimentation and annotation, the budding yeast Saccharomyces cerevisiae is an ideal model organism in which to determine protein function. This information can then be leveraged to infer functions of human homologs. Despite the large amount of research and biological data about S. cerevisiae, many proteins' functions remain unknown. Here, we explore ways to use the Saccharomyces Genome Database (SGD; http://www.yeastgenome.org ) to predict the function of proteins and gain insight into their roles in various cellular processes.

Determination of spectral, structural and energetic properties of small lithium clusters, within the density functional theory formalism

International Nuclear Information System (INIS)

Gardet, G.

1995-01-01

A systematic study of small lithium clusters (with size less than 19), within the Density Functional Theory (DFT) formalism is presented. We examine structural properties of the so called local level of approximation. For clusters with size smaller than 8, the conformations are well known from ab initio calculations and are found here at much lower computational cost, with only small differences. For bigger clusters, two growth pattern have been used, based upon the increase of the number of pentagonal subunits in the clusters by absorption of one or two Li atoms. Several new stable structures are proposed. Then DFT gradient-corrected functionals have been used for relative stability determination of these clusters. Ionisation potentials and binding energies are also investigated in regard to clusters size and geometry. Calculations of excited states of lithium clusters (with size less than 9) have been performed within two different approaches. Using a set of Kohn-Sham orbitals to construct wave functions, oscillator strengths calculation of the electric dipole transitions is performed. Transition energies, oscillator strengths and optical absorption presented here are generally in reasonable agreement with the experimental data and the Configuration Interaction calculations. (author)

Diametrical clustering for identifying anti-correlated gene clusters.

Science.gov (United States)

Dhillon, Inderjit S; Marcotte, Edward M; Roshan, Usman

2003-09-01

Clustering genes based upon their expression patterns allows us to predict gene function. Most existing clustering algorithms cluster genes together when their expression patterns show high positive correlation. However, it has been observed that genes whose expression patterns are strongly anti-correlated can also be functionally similar. Biologically, this is not unintuitive-genes responding to the same stimuli, regardless of the nature of the response, are more likely to operate in the same pathways. We present a new diametrical clustering algorithm that explicitly identifies anti-correlated clusters of genes. Our algorithm proceeds by iteratively (i). re-partitioning the genes and (ii). computing the dominant singular vector of each gene cluster; each singular vector serving as the prototype of a 'diametric' cluster. We empirically show the effectiveness of the algorithm in identifying diametrical or anti-correlated clusters. Testing the algorithm on yeast cell cycle data, fibroblast gene expression data, and DNA microarray data from yeast mutants reveals that opposed cellular pathways can be discovered with this method. We present systems whose mRNA expression patterns, and likely their functions, oppose the yeast ribosome and proteosome, along with evidence for the inverse transcriptional regulation of a number of cellular systems.

Defining functioning levels in patients with schizophrenia: A combination of a novel clustering method and brain SPECT analysis.

Science.gov (United States)

Catherine, Faget-Agius; Aurélie, Vincenti; Eric, Guedj; Pierre, Michel; Raphaëlle, Richieri; Marine, Alessandrini; Pascal, Auquier; Christophe, Lançon; Laurent, Boyer

2017-12-30

This study aims to define functioning levels of patients with schizophrenia by using a method of interpretable clustering based on a specific functioning scale, the Functional Remission Of General Schizophrenia (FROGS) scale, and to test their validity regarding clinical and neuroimaging characterization. In this observational study, patients with schizophrenia have been classified using a hierarchical top-down method called clustering using unsupervised binary trees (CUBT). Socio-demographic, clinical, and neuroimaging SPECT perfusion data were compared between the different clusters to ensure their clinical relevance. A total of 242 patients were analyzed. A four-group functioning level structure has been identified: 54 are classified as "minimal", 81 as "low", 64 as "moderate", and 43 as "high". The clustering shows satisfactory statistical properties, including reproducibility and discriminancy. The 4 clusters consistently differentiate patients. "High" functioning level patients reported significantly the lowest scores on the PANSS and the CDSS, and the highest scores on the GAF, the MARS and S-QoL 18. Functioning levels were significantly associated with cerebral perfusion of two relevant areas: the left inferior parietal cortex and the anterior cingulate. Our study provides relevant functioning levels in schizophrenia, and may enhance the use of functioning scale. Copyright © 2017 Elsevier B.V. All rights reserved.

Iron-sulfur cluster biogenesis in mammalian cells: new insights into the molecular mechanisms of cluster delivery

Science.gov (United States)

Maio, Nunziata; Rouault, Tracey. A.

2014-01-01

Iron-sulfur (Fe-S) clusters are ancient, ubiquitous cofactors composed of iron and inorganic sulfur. The combination of the chemical reactivity of iron and sulfur, together with many variations of cluster composition, oxidation states and protein environments, enables Fe-S clusters to participate in numerous biological processes. Fe-S clusters are essential to redox catalysis in nitrogen fixation, mitochondrial respiration and photosynthesis, to regulatory sensing in key metabolic pathways (i. e. cellular iron homeostasis and oxidative stress response), and to the replication and maintenance of the nuclear genome. Fe-S cluster biogenesis is a multistep process that involves a complex sequence of catalyzed protein- protein interactions and coupled conformational changes between the components of several dedicated multimeric complexes. Intensive studies of the assembly process have clarified key points in the biogenesis of Fe-S proteins. However several critical questions still remain, such as: what is the role of frataxin? Why do some defects of Fe-S cluster biogenesis cause mitochondrial iron overload? How are specific Fe-S recipient proteins recognized in the process of Fe-S transfer? This review focuses on the basic steps of Fe-S cluster biogenesis, drawing attention to recent advances achieved on the identification of molecular features that guide selection of specific subsets of nascent Fe-S recipients by the cochaperone HSC20. Additionally, it outlines the distinctive phenotypes of human diseases due to mutations in the components of the basic pathway. PMID:25245479

An Interactome-Centered Protein Discovery Approach Reveals Novel Components Involved in Mitosome Function and Homeostasis in Giardia lamblia.

Directory of Open Access Journals (Sweden)

Samuel Rout

2016-12-01

Full Text Available Protozoan parasites of the genus Giardia are highly prevalent globally, and infect a wide range of vertebrate hosts including humans, with proliferation and pathology restricted to the small intestine. This narrow ecological specialization entailed extensive structural and functional adaptations during host-parasite co-evolution. An example is the streamlined mitosomal proteome with iron-sulphur protein maturation as the only biochemical pathway clearly associated with this organelle. Here, we applied techniques in microscopy and protein biochemistry to investigate the mitosomal membrane proteome in association to mitosome homeostasis. Live cell imaging revealed a highly immobilized array of 30-40 physically distinct mitosome organelles in trophozoites. We provide direct evidence for the single giardial dynamin-related protein as a contributor to mitosomal morphogenesis and homeostasis. To overcome inherent limitations that have hitherto severely hampered the characterization of these unique organelles we applied a novel interaction-based proteome discovery strategy using forward and reverse protein co-immunoprecipitation. This allowed generation of organelle proteome data strictly in a protein-protein interaction context. We built an initial Tom40-centered outer membrane interactome by co-immunoprecipitation experiments, identifying small GTPases, factors with dual mitosome and endoplasmic reticulum (ER distribution, as well as novel matrix proteins. Through iterative expansion of this protein-protein interaction network, we were able to i significantly extend this interaction-based mitosomal proteome to include other membrane-associated proteins with possible roles in mitosome morphogenesis and connection to other subcellular compartments, and ii identify novel matrix proteins which may shed light on mitosome-associated metabolic functions other than Fe-S cluster biogenesis. Functional analysis also revealed conceptual conservation of protein

Protein Function Prediction Based on Sequence and Structure Information

KAUST Repository

Smaili, Fatima Z.

2016-05-25

The number of available protein sequences in public databases is increasing exponentially. However, a significant fraction of these sequences lack functional annotation which is essential to our understanding of how biological systems and processes operate. In this master thesis project, we worked on inferring protein functions based on the primary protein sequence. In the approach we follow, 3D models are first constructed using I-TASSER. Functions are then deduced by structurally matching these predicted models, using global and local similarities, through three independent enzyme commission (EC) and gene ontology (GO) function libraries. The method was tested on 250 “hard” proteins, which lack homologous templates in both structure and function libraries. The results show that this method outperforms the conventional prediction methods based on sequence similarity or threading. Additionally, our method could be improved even further by incorporating protein-protein interaction information. Overall, the method we use provides an efficient approach for automated functional annotation of non-homologous proteins, starting from their sequence.

The evolution of the global stellar mass function of star clusters: an analytic description

NARCIS (Netherlands)

Lamers, H.J.G.L.M.; Baumgardt, H.; Gieles, M.

2013-01-01

The evolution of the global stellar mass function of star clusters is studied based on a large set of N-body simulations of clusters with a range of initial masses, initial concentrations, in circular or elliptical orbits in different tidal environments. Models with and without initial mass

Dyadic Green's function of a cluster of spheres.

Science.gov (United States)

Moneda, Angela P; Chrissoulidis, Dimitrios P

2007-11-01

The electric dyadic Green's function (dGf) of a cluster of spheres is obtained by application of the superposition principle, dyadic algebra, and the indirect mode-matching method. The analysis results in a set of linear equations for the unknown, vector, wave amplitudes of the dGf; that set is solved by truncation and matrix inversion. The theory is exact in the sense that no simplifying assumptions are made in the analytical steps leading to the dGf, and it is general in the sense that any number, position, size and electrical properties can be considered for the spheres that cluster together. The point source can be anywhere, even within one of the spheres. Energy conservation, reciprocity, and other tests prove that this solution is correct. Numerical results are presented for an electric Hertz dipole radiating in the presence of an array of rexolite spheres, which manifests lensing and beam-forming capabilities.

Unveiling protein functions through the dynamics of the interaction network.

Directory of Open Access Journals (Sweden)

Irene Sendiña-Nadal

Full Text Available Protein interaction networks have become a tool to study biological processes, either for predicting molecular functions or for designing proper new drugs to regulate the main biological interactions. Furthermore, such networks are known to be organized in sub-networks of proteins contributing to the same cellular function. However, the protein function prediction is not accurate and each protein has traditionally been assigned to only one function by the network formalism. By considering the network of the physical interactions between proteins of the yeast together with a manual and single functional classification scheme, we introduce a method able to reveal important information on protein function, at both micro- and macro-scale. In particular, the inspection of the properties of oscillatory dynamics on top of the protein interaction network leads to the identification of misclassification problems in protein function assignments, as well as to unveil correct identification of protein functions. We also demonstrate that our approach can give a network representation of the meta-organization of biological processes by unraveling the interactions between different functional classes.

Identification of alterations associated with age in the clustering structure of functional brain networks.

Science.gov (United States)

Guzman, Grover E C; Sato, Joao R; Vidal, Maciel C; Fujita, Andre

2018-01-01

Initial studies using resting-state functional magnetic resonance imaging on the trajectories of the brain network from childhood to adulthood found evidence of functional integration and segregation over time. The comprehension of how healthy individuals' functional integration and segregation occur is crucial to enhance our understanding of possible deviations that may lead to brain disorders. Recent approaches have focused on the framework wherein the functional brain network is organized into spatially distributed modules that have been associated with specific cognitive functions. Here, we tested the hypothesis that the clustering structure of brain networks evolves during development. To address this hypothesis, we defined a measure of how well a brain region is clustered (network fitness index), and developed a method to evaluate its association with age. Then, we applied this method to a functional magnetic resonance imaging data set composed of 397 males under 31 years of age collected as part of the Autism Brain Imaging Data Exchange Consortium. As results, we identified two brain regions for which the clustering change over time, namely, the left middle temporal gyrus and the left putamen. Since the network fitness index is associated with both integration and segregation, our finding suggests that the identified brain region plays a role in the development of brain systems.

A theoretical study of lithium-doped gallium clusters by density functional theory

Energy Technology Data Exchange (ETDEWEB)

Sentuerk, Suekrue; Ekincioglu, Yavuz [Dumlupinar Univ., Kutahya (Turkey). Dept. of Physics

2012-05-15

The geometrical structures, stabilities, and electronic properties of Ga{sub n}Li (n = 1-13) clusters were investigated within the density functional theory (DFT). The impurity lithium atom enhances the stability of Ga{sub n}Li (n = 1-13) clusters, especially Ga{sub n}Li (n = 9-13) compared to Ga{sub n} (n = 9-14), that is at either apex position or side position. The dissociation energy, second-order energy differences, and the energy gaps between highest occupied and lowest unoccupied molecular orbital (HOMO-LUMO) indicate that the Ga{sub 7}Li, Ga{sub 9}Li, and Ga{sub 11}Li clusters are more stable within the studied cluster range. Moreover, the variation of the average bond length of Ga - Li is due to the surface effect, and the binding strength increases resulting from the increase of charge amount. (orig.)

bcl::Cluster : A method for clustering biological molecules coupled with visualization in the Pymol Molecular Graphics System.

Science.gov (United States)

Alexander, Nathan; Woetzel, Nils; Meiler, Jens

2011-02-01

Clustering algorithms are used as data analysis tools in a wide variety of applications in Biology. Clustering has become especially important in protein structure prediction and virtual high throughput screening methods. In protein structure prediction, clustering is used to structure the conformational space of thousands of protein models. In virtual high throughput screening, databases with millions of drug-like molecules are organized by structural similarity, e.g. common scaffolds. The tree-like dendrogram structure obtained from hierarchical clustering can provide a qualitative overview of the results, which is important for focusing detailed analysis. However, in practice it is difficult to relate specific components of the dendrogram directly back to the objects of which it is comprised and to display all desired information within the two dimensions of the dendrogram. The current work presents a hierarchical agglomerative clustering method termed bcl::Cluster. bcl::Cluster utilizes the Pymol Molecular Graphics System to graphically depict dendrograms in three dimensions. This allows simultaneous display of relevant biological molecules as well as additional information about the clusters and the members comprising them.

Filling- and interaction-driven Mott transition. Quantum cluster calculations within self-energy-functional theory

International Nuclear Information System (INIS)

Balzer, Matthias

2008-01-01

The central goal of this thesis is the examination of strongly correlated electron systems on the basis of the two-dimensional Hubbard model. We analyze how the properties of the Mott insulator change upon doping and with interaction strength. The numerical evaluation is done using quantum cluster approximations, which allow for a thermodynamically consistent description of the ground state properties. The framework of self-energy-functional theory offers great flexibility for the construction of cluster approximations. A detailed analysis sheds light on the quality and the convergence properties of different cluster approximations within the self-energy-functional theory. We use the one-dimensional Hubbard model for these examinations and compare our results with the exact solution. In two dimensions the ground state of the particle-hole symmetric model at half-filling is an antiferromagnetic insulator, independent of the interaction strength. The inclusion of short-range spatial correlations by our cluster approach leads to a considerable improvement of the antiferromagnetic order parameter as compared to dynamical mean-field theory. In the paramagnetic phase we furthermore observe a metal-insulator transition as a function of the interaction strength, which qualitatively differs from the pure mean-field scenario. Starting from the antiferromagnetic Mott insulator a filling-controlled metal-insulator transition in a paramagnetic metallic phase can be observed. Depending on the cluster approximation used an antiferromagnetic metallic phase may occur at first. In addition to long-range antiferromagnetic order, we also considered superconductivity in our calculations. The superconducting order parameter as a function of doping is in good agreement with other numerical methods, as well as with experimental results. (orig.)

Characterization of the largest effector gene cluster of Ustilago maydis.

Directory of Open Access Journals (Sweden)

Thomas Brefort

2014-07-01

Full Text Available In the genome of the biotrophic plant pathogen Ustilago maydis, many of the genes coding for secreted protein effectors modulating virulence are arranged in gene clusters. The vast majority of these genes encode novel proteins whose expression is coupled to plant colonization. The largest of these gene clusters, cluster 19A, encodes 24 secreted effectors. Deletion of the entire cluster results in severe attenuation of virulence. Here we present the functional analysis of this genomic region. We show that a 19A deletion mutant behaves like an endophyte, i.e. is still able to colonize plants and complete the infection cycle. However, tumors, the most conspicuous symptoms of maize smut disease, are only rarely formed and fungal biomass in infected tissue is significantly reduced. The generation and analysis of strains carrying sub-deletions identified several genes significantly contributing to tumor formation after seedling infection. Another of the effectors could be linked specifically to anthocyanin induction in the infected tissue. As the individual contributions of these genes to tumor formation were small, we studied the response of maize plants to the whole cluster mutant as well as to several individual mutants by array analysis. This revealed distinct plant responses, demonstrating that the respective effectors have discrete plant targets. We propose that the analysis of plant responses to effector mutant strains that lack a strong virulence phenotype may be a general way to visualize differences in effector function.

Biomimetic devices functionalized by membrane channel proteins

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Schmidt, Jacob

2004-03-01

We are developing a new family of active materials which derive their functional properties from membrane proteins. These materials have two primary components: the proteins and the membranes themselves. I will discuss our recent work directed toward development of a generic platform for a "plug-and-play" philosophy of membrane protein engineering. By creating a stable biomimetic polymer membrane a single molecular monolayer thick, we will enable the exploitation of the function of any membrane protein, from pores and pumps to sensors and energy transducers. Our initial work has centered on the creation, study, and characterization of the biomimetic membranes. We are attempting to make large areas of membrane monolayers using Langmuir-Blodgett film formation as well as through arrays of microfabricated black lipid membrane-type septa. A number of techniques allow the insertion of protein into the membranes. As a benchmark, we have been employing a model system of voltage-gated pore proteins, which have electrically controllable porosities. I will report on the progress of this work, the characterization of the membranes, protein insertion processes, and the yield and functionality of the composite.

Improving protein function prediction methods with integrated literature data

Directory of Open Access Journals (Sweden)

Gabow Aaron P

2008-04-01

Full Text Available Abstract Background Determining the function of uncharacterized proteins is a major challenge in the post-genomic era due to the problem's complexity and scale. Identifying a protein's function contributes to an understanding of its role in the involved pathways, its suitability as a drug target, and its potential for protein modifications. Several graph-theoretic approaches predict unidentified functions of proteins by using the functional annotations of better-characterized proteins in protein-protein interaction networks. We systematically consider the use of literature co-occurrence data, introduce a new method for quantifying the reliability of co-occurrence and test how performance differs across species. We also quantify changes in performance as the prediction algorithms annotate with increased specificity. Results We find that including information on the co-occurrence of proteins within an abstract greatly boosts performance in the Functional Flow graph-theoretic function prediction algorithm in yeast, fly and worm. This increase in performance is not simply due to the presence of additional edges since supplementing protein-protein interactions with co-occurrence data outperforms supplementing with a comparably-sized genetic interaction dataset. Through the combination of protein-protein interactions and co-occurrence data, the neighborhood around unknown proteins is quickly connected to well-characterized nodes which global prediction algorithms can exploit. Our method for quantifying co-occurrence reliability shows superior performance to the other methods, particularly at threshold values around 10% which yield the best trade off between coverage and accuracy. In contrast, the traditional way of asserting co-occurrence when at least one abstract mentions both proteins proves to be the worst method for generating co-occurrence data, introducing too many false positives. Annotating the functions with greater specificity is harder

Functions of intrinsic disorder in transmembrane proteins

DEFF Research Database (Denmark)

Kjaergaard, Magnus; Kragelund, Birthe B.

2017-01-01

Intrinsic disorder is common in integral membrane proteins, particularly in the intracellular domains. Despite this observation, these domains are not always recognized as being disordered. In this review, we will discuss the biological functions of intrinsically disordered regions of membrane...... receptors. The functions of the disordered regions are many and varied. We will discuss selected examples including: (1) Organization of receptors, kinases, phosphatases and second messenger sources into signaling complexes. (2) Modulation of the membrane-embedded domain function by ball-and-chain like...... mechanisms. (3) Trafficking of membrane proteins. (4) Transient membrane associations. (5) Post-translational modifications most notably phosphorylation and (6) disorder-linked isoform dependent function. We finish the review by discussing the future challenges facing the membrane protein community regarding...

Crystal structure of clustered regularly interspaced short palindromic repeats (CRISPR)-associated Csn2 protein revealed Ca2+-dependent double-stranded DNA binding activity.

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Nam, Ki Hyun; Kurinov, Igor; Ke, Ailong

2011-09-02

Clustered regularly interspaced short palindromic repeats (CRISPR) and their associated protein genes (cas genes) are widespread in bacteria and archaea. They form a line of RNA-based immunity to eradicate invading bacteriophages and malicious plasmids. A key molecular event during this process is the acquisition of new spacers into the CRISPR loci to guide the selective degradation of the matching foreign genetic elements. Csn2 is a Nmeni subtype-specific cas gene required for new spacer acquisition. Here we characterize the Enterococcus faecalis Csn2 protein as a double-stranded (ds-) DNA-binding protein and report its 2.7 Å tetrameric ring structure. The inner circle of the Csn2 tetrameric ring is ∼26 Å wide and populated with conserved lysine residues poised for nonspecific interactions with ds-DNA. Each Csn2 protomer contains an α/β domain and an α-helical domain; significant hinge motion was observed between these two domains. Ca(2+) was located at strategic positions in the oligomerization interface. We further showed that removal of Ca(2+) ions altered the oligomerization state of Csn2, which in turn severely decreased its affinity for ds-DNA. In summary, our results provided the first insight into the function of the Csn2 protein in CRISPR adaptation by revealing that it is a ds-DNA-binding protein functioning at the quaternary structure level and regulated by Ca(2+) ions.

Studying Membrane Protein Structure and Function Using Nanodiscs

DEFF Research Database (Denmark)

Huda, Pie

The structure and dynamic of membrane proteins can provide valuable information about general functions, diseases and effects of various drugs. Studying membrane proteins are a challenge as an amphiphilic environment is necessary to stabilise the protein in a functionally and structurally relevant...... form. This is most typically achieved through the use of detergent based reconstitution systems. However, time and again such systems fail to provide a suitable environment causing aggregation and inactivation. Nanodiscs are self-assembled lipoproteins containing two membrane scaffold proteins...... and a lipid bilayer in defined nanometer size, which can act as a stabiliser for membrane proteins. This enables both functional and structural investigation of membrane proteins in a detergent free environment which is closer to the native situation. Understanding the self-assembly of nanodiscs is important...

Functional Clustering of the Human Inferior Parietal Lobule by Whole-Brain Connectivity Mapping of Resting-State Functional Magnetic Resonance Imaging Signals

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Li, Chiang-Shan R.

2014-01-01

Abstract The human inferior parietal lobule (IPL) comprised the lateral bank of the intraparietal sulcus, angular gyrus, and supramarginal gyrus, defined on the basis of anatomical landmarks and cytoarchitectural organization of neurons. However, it is not clear as to whether the three areas represent functional subregions within the IPL. For instance, imaging studies frequently identified clusters of activities that cut across areal boundaries. Here, we used resting-state functional magnetic resonance imaging (fMRI) data to examine how individual voxels within the IPL are best clustered according to their connectivity to the whole brain. The results identified a best estimate of seven clusters that are hierarchically arranged as the anterior, middle, and posterior subregions. The anterior, middle, and posterior IPL are each significantly connected to the somatomotor areas, superior/middle/inferior frontal gyri, and regions of the default mode network. This functional segregation is supported by recent cytoarchitechtonics and tractography studies. IPL showed hemispheric differences in connectivity that accord with a predominantly left parietal role in tool use and language processing and a right parietal role in spatial attention and mathematical cognition. The functional clusters may also provide a more parsimonious and perhaps even accurate account of regional activations of the IPL during a variety of cognitive challenges, as reported in earlier fMRI studies. PMID:24308753

OrthoVenn: a web server for genome wide comparison and annotation of orthologous clusters across multiple species

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Genome wide analysis of orthologous clusters is an important component of comparative genomics studies. Identifying the overlap among orthologous clusters can enable us to elucidate the function and evolution of proteins across multiple species. Here, we report a web platform named OrthoVenn that i...

Density functional calculations on 13-atom Pd12M (M = Sc—Ni) bimetallic clusters

International Nuclear Information System (INIS)

Tang Chun-Mei; Chen Sheng-Wei; Zhu Wei-Hua; Tao Cheng-Jun; Zhang Ai-Mei; Gong Jiang-Feng; Zou Hua; Liu Ming-Yi; Zhu Feng

2012-01-01

The geometric structures, electronic and magnetic properties of the 3d transition metal doped clusters Pd 12 M (M = Sc—Ni) are studied using the semi-core pseudopots density functional theory. The groundstate geometric structure of the Pd 12 M cluster is probably of pseudoicosahedron. The I h -Pd 12 M cluster has the most thermodynamic stability in five different symmetric isomers. The energy gap shows that Pd 12 M cluster is partly metallic. Both the absolutely predominant metal bond and very weak covalent bond might exist in the Pd 12 M cluster. The magnetic moment of Pd 12 M varies from 0 to 5 μ B , implying that it has a potential application in new nanomaterials with tunable magnetic properties

Structure-based inference of molecular functions of proteins of unknown function from Berkeley Structural Genomics Center

Energy Technology Data Exchange (ETDEWEB)

Kim, Sung-Hou; Shin, Dong Hae; Hou, Jingtong; Chandonia, John-Marc; Das, Debanu; Choi, In-Geol; Kim, Rosalind; Kim, Sung-Hou

2007-09-02

Advances in sequence genomics have resulted in an accumulation of a huge number of protein sequences derived from genome sequences. However, the functions of a large portion of them cannot be inferred based on the current methods of sequence homology detection to proteins of known functions. Three-dimensional structure can have an important impact in providing inference of molecular function (physical and chemical function) of a protein of unknown function. Structural genomics centers worldwide have been determining many 3-D structures of the proteins of unknown functions, and possible molecular functions of them have been inferred based on their structures. Combined with bioinformatics and enzymatic assay tools, the successful acceleration of the process of protein structure determination through high throughput pipelines enables the rapid functional annotation of a large fraction of hypothetical proteins. We present a brief summary of the process we used at the Berkeley Structural Genomics Center to infer molecular functions of proteins of unknown function.

Protein complex prediction in large ontology attributed protein-protein interaction networks.

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Zhang, Yijia; Lin, Hongfei; Yang, Zhihao; Wang, Jian; Li, Yanpeng; Xu, Bo

2013-01-01

Protein complexes are important for unraveling the secrets of cellular organization and function. Many computational approaches have been developed to predict protein complexes in protein-protein interaction (PPI) networks. However, most existing approaches focus mainly on the topological structure of PPI networks, and largely ignore the gene ontology (GO) annotation information. In this paper, we constructed ontology attributed PPI networks with PPI data and GO resource. After constructing ontology attributed networks, we proposed a novel approach called CSO (clustering based on network structure and ontology attribute similarity). Structural information and GO attribute information are complementary in ontology attributed networks. CSO can effectively take advantage of the correlation between frequent GO annotation sets and the dense subgraph for protein complex prediction. Our proposed CSO approach was applied to four different yeast PPI data sets and predicted many well-known protein complexes. The experimental results showed that CSO was valuable in predicting protein complexes and achieved state-of-the-art performance.

Machine learning etudes in astrophysics: selection functions for mock cluster catalogs

Energy Technology Data Exchange (ETDEWEB)

Hajian, Amir; Alvarez, Marcelo A.; Bond, J. Richard, E-mail: ahajian@cita.utoronto.ca, E-mail: malvarez@cita.utoronto.ca, E-mail: bond@cita.utoronto.ca [Canadian Institute for Theoretical Astrophysics, University of Toronto, Toronto, ON M5S 3H8 (Canada)

2015-01-01

Making mock simulated catalogs is an important component of astrophysical data analysis. Selection criteria for observed astronomical objects are often too complicated to be derived from first principles. However the existence of an observed group of objects is a well-suited problem for machine learning classification. In this paper we use one-class classifiers to learn the properties of an observed catalog of clusters of galaxies from ROSAT and to pick clusters from mock simulations that resemble the observed ROSAT catalog. We show how this method can be used to study the cross-correlations of thermal Sunya'ev-Zeldovich signals with number density maps of X-ray selected cluster catalogs. The method reduces the bias due to hand-tuning the selection function and is readily scalable to large catalogs with a high-dimensional space of astrophysical features.

Machine learning etudes in astrophysics: selection functions for mock cluster catalogs

International Nuclear Information System (INIS)

Hajian, Amir; Alvarez, Marcelo A.; Bond, J. Richard

2015-01-01

Making mock simulated catalogs is an important component of astrophysical data analysis. Selection criteria for observed astronomical objects are often too complicated to be derived from first principles. However the existence of an observed group of objects is a well-suited problem for machine learning classification. In this paper we use one-class classifiers to learn the properties of an observed catalog of clusters of galaxies from ROSAT and to pick clusters from mock simulations that resemble the observed ROSAT catalog. We show how this method can be used to study the cross-correlations of thermal Sunya'ev-Zeldovich signals with number density maps of X-ray selected cluster catalogs. The method reduces the bias due to hand-tuning the selection function and is readily scalable to large catalogs with a high-dimensional space of astrophysical features

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

Gender differences in associations between DSM-5 posttraumatic stress disorder symptom clusters and functional impairment in war veterans.

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Meyer, Eric C; Konecky, Brian; Kimbrel, Nathan A; DeBeer, Bryann B; Marx, Brian P; Schumm, Jeremiah; Penk, Walter E; Gulliver, Suzy Bird; Morissette, Sandra B

2018-05-01

Understanding the links between posttraumatic stress disorder (PTSD) symptoms and functional impairment is essential for assisting veterans in transitioning to civilian life. Moreover, there may be differences between men and women in the relationships between PTSD symptoms and functional impairment. However, no prior studies have examined the links between functional impairment and the revised symptom clusters as defined in the Diagnostic and Statistical Manual of Mental Disorders, 5th ed. (DSM-5; American Psychiatric Association, 2013) or whether the associations between PTSD symptom clusters and functional impairment differ by gender. We examined the associations between the DSM-5 PTSD symptom clusters and functional impairment in 252 trauma-exposed Iraq and Afghanistan war veterans (79 females). Regression analyses included demographic factors and exposure to both combat and military sexual trauma as covariates. In the total sample, both the intrusions cluster (β = .18, p = .045) and the negative alterations in cognition and mood cluster (β = .45, p < .001) were associated with global functional impairment. Among male veterans, global functional impairment was associated only with negative alterations in cognition and mood (β = .52, p < .001). However, by contrast, among female veterans, only marked alterations in arousal and reactivity were associated with global functional impairment (β = .35, p = .027). These findings suggest that there may be important gender differences with respect to the relationship between PTSD symptoms and functional impairment. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Alignment and integration of complex networks by hypergraph-based spectral clustering

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Michoel, Tom; Nachtergaele, Bruno

2012-11-01

Complex networks possess a rich, multiscale structure reflecting the dynamical and functional organization of the systems they model. Often there is a need to analyze multiple networks simultaneously, to model a system by more than one type of interaction, or to go beyond simple pairwise interactions, but currently there is a lack of theoretical and computational methods to address these problems. Here we introduce a framework for clustering and community detection in such systems using hypergraph representations. Our main result is a generalization of the Perron-Frobenius theorem from which we derive spectral clustering algorithms for directed and undirected hypergraphs. We illustrate our approach with applications for local and global alignment of protein-protein interaction networks between multiple species, for tripartite community detection in folksonomies, and for detecting clusters of overlapping regulatory pathways in directed networks.

Text mining improves prediction of protein functional sites.

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Karin M Verspoor

Full Text Available We present an approach that integrates protein structure analysis and text mining for protein functional site prediction, called LEAP-FS (Literature Enhanced Automated Prediction of Functional Sites. The structure analysis was carried out using Dynamics Perturbation Analysis (DPA, which predicts functional sites at control points where interactions greatly perturb protein vibrations. The text mining extracts mentions of residues in the literature, and predicts that residues mentioned are functionally important. We assessed the significance of each of these methods by analyzing their performance in finding known functional sites (specifically, small-molecule binding sites and catalytic sites in about 100,000 publicly available protein structures. The DPA predictions recapitulated many of the functional site annotations and preferentially recovered binding sites annotated as biologically relevant vs. those annotated as potentially spurious. The text-based predictions were also substantially supported by the functional site annotations: compared to other residues, residues mentioned in text were roughly six times more likely to be found in a functional site. The overlap of predictions with annotations improved when the text-based and structure-based methods agreed. Our analysis also yielded new high-quality predictions of many functional site residues that were not catalogued in the curated data sources we inspected. We conclude that both DPA and text mining independently provide valuable high-throughput protein functional site predictions, and that integrating the two methods using LEAP-FS further improves the quality of these predictions.

Text Mining Improves Prediction of Protein Functional Sites

Science.gov (United States)

Cohn, Judith D.; Ravikumar, Komandur E.

2012-01-01

We present an approach that integrates protein structure analysis and text mining for protein functional site prediction, called LEAP-FS (Literature Enhanced Automated Prediction of Functional Sites). The structure analysis was carried out using Dynamics Perturbation Analysis (DPA), which predicts functional sites at control points where interactions greatly perturb protein vibrations. The text mining extracts mentions of residues in the literature, and predicts that residues mentioned are functionally important. We assessed the significance of each of these methods by analyzing their performance in finding known functional sites (specifically, small-molecule binding sites and catalytic sites) in about 100,000 publicly available protein structures. The DPA predictions recapitulated many of the functional site annotations and preferentially recovered binding sites annotated as biologically relevant vs. those annotated as potentially spurious. The text-based predictions were also substantially supported by the functional site annotations: compared to other residues, residues mentioned in text were roughly six times more likely to be found in a functional site. The overlap of predictions with annotations improved when the text-based and structure-based methods agreed. Our analysis also yielded new high-quality predictions of many functional site residues that were not catalogued in the curated data sources we inspected. We conclude that both DPA and text mining independently provide valuable high-throughput protein functional site predictions, and that integrating the two methods using LEAP-FS further improves the quality of these predictions. PMID:22393388

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.

Benchmark CCSD(T) and DFT study of binding energies in Be7 - 12: in search of reliable DFT functional for beryllium clusters

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Labanc, Daniel; Šulka, Martin; Pitoňák, Michal; Černušák, Ivan; Urban, Miroslav; Neogrády, Pavel

2018-05-01

We present a computational study of the stability of small homonuclear beryllium clusters Be7 - 12 in singlet electronic states. Our predictions are based on highly correlated CCSD(T) coupled cluster calculations. Basis set convergence towards the complete basis set limit as well as the role of the 1s core electron correlation are carefully examined. Our CCSD(T) data for binding energies of Be7 - 12 clusters serve as a benchmark for performance assessment of several density functional theory (DFT) methods frequently used in beryllium cluster chemistry. We observe that, from Be10 clusters on, the deviation from CCSD(T) benchmarks is stable with respect to size, and fluctuating within 0.02 eV error bar for most examined functionals. This opens up the possibility of scaling the DFT binding energies for large Be clusters using CCSD(T) benchmark values for smaller clusters. We also tried to find analogies between the performance of DFT functionals for Be clusters and for the valence-isoelectronic Mg clusters investigated recently in Truhlar's group. We conclude that it is difficult to find DFT functionals that perform reasonably well for both beryllium and magnesium clusters. Out of 12 functionals examined, only the M06-2X functional gives reasonably accurate and balanced binding energies for both Be and Mg clusters.

Cluster analysis of obesity and asthma phenotypes.

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E Rand Sutherland

Full Text Available Asthma is a heterogeneous disease with variability among patients in characteristics such as lung function, symptoms and control, body weight, markers of inflammation, and responsiveness to glucocorticoids (GC. Cluster analysis of well-characterized cohorts can advance understanding of disease subgroups in asthma and point to unsuspected disease mechanisms. We utilized an hypothesis-free cluster analytical approach to define the contribution of obesity and related variables to asthma phenotype.In a cohort of clinical trial participants (n = 250, minimum-variance hierarchical clustering was used to identify clinical and inflammatory biomarkers important in determining disease cluster membership in mild and moderate persistent asthmatics. In a subset of participants, GC sensitivity was assessed via expression of GC receptor alpha (GCRα and induction of MAP kinase phosphatase-1 (MKP-1 expression by dexamethasone. Four asthma clusters were identified, with body mass index (BMI, kg/m(2 and severity of asthma symptoms (AEQ score the most significant determinants of cluster membership (F = 57.1, p<0.0001 and F = 44.8, p<0.0001, respectively. Two clusters were composed of predominantly obese individuals; these two obese asthma clusters differed from one another with regard to age of asthma onset, measures of asthma symptoms (AEQ and control (ACQ, exhaled nitric oxide concentration (F(ENO and airway hyperresponsiveness (methacholine PC(20 but were similar with regard to measures of lung function (FEV(1 (% and FEV(1/FVC, airway eosinophilia, IgE, leptin, adiponectin and C-reactive protein (hsCRP. Members of obese clusters demonstrated evidence of reduced expression of GCRα, a finding which was correlated with a reduced induction of MKP-1 expression by dexamethasoneObesity is an important determinant of asthma phenotype in adults. There is heterogeneity in expression of clinical and inflammatory biomarkers of asthma across obese individuals

Interplay between experiments and calculations for organometallic clusters and caged clusters

International Nuclear Information System (INIS)

Nakajima, Atsushi

2015-01-01

Clusters consisting of 10-1000 atoms exhibit size-dependent electronic and geometric properties. In particular, composite clusters consisting of several elements and/or components provide a promising way for a bottom-up approach for designing functional advanced materials, because the functionality of the composite clusters can be optimized not only by the cluster size but also by their compositions. In the formation of composite clusters, their geometric symmetry and dimensionality are emphasized to control the physical and chemical properties, because selective and anisotropic enhancements for optical, chemical, and magnetic properties can be expected. Organometallic clusters and caged clusters are demonstrated as a representative example of designing the functionality of the composite clusters. Organometallic vanadium-benzene forms a one dimensional sandwich structure showing ferromagnetic behaviors and anomalously large HOMO-LUMO gap differences of two spin orbitals, which can be regarded as spin-filter components for cluster-based spintronic devices. Caged clusters of aluminum (Al) are well stabilized both geometrically and electronically at Al 12 X, behaving as a “superatom”

THE REST-FRAME OPTICAL LUMINOSITY FUNCTION OF CLUSTER GALAXIES AT z < 0.8 AND THE ASSEMBLY OF THE CLUSTER RED SEQUENCE

International Nuclear Information System (INIS)

Rudnick, Gregory; Von der Linden, Anja; De Lucia, Gabriella; White, Simon; Pello, Roser; Aragon-Salamanca, Alfonso; Marchesini, Danilo; Clowe, Douglas; Halliday, Claire; Jablonka, Pascale; Milvang-Jensen, Bo; Poggianti, Bianca; Saglia, Roberto; Simard, Luc; Zaritsky, Dennis

2009-01-01

We present the rest-frame optical luminosity function (LF) of red-sequence galaxies in 16 clusters at 0.4 < z < 0.8 drawn from the ESO Distant Cluster Survey (EDisCS). We compare our clusters to an analogous sample from the Sloan Digital Sky Survey (SDSS) and match the EDisCS clusters to their most likely descendants. We measure all LFs down to M ∼ M * + (2.5-3.5). At z < 0.8, the bright end of the LF is consistent with passive evolution but there is a significant buildup of the faint end of the red sequence toward lower redshift. There is a weak dependence of the LF on cluster velocity dispersion for EDisCS but no such dependence for the SDSS clusters. We find tentative evidence that red-sequence galaxies brighter than a threshold magnitude are already in place, and that this threshold evolves to fainter magnitudes toward lower redshifts. We compare the EDisCS LFs with the LF of coeval red-sequence galaxies in the field and find that the bright end of the LFs agree. However, relative to the number of bright red galaxies, the field has more faint red galaxies than clusters at 0.6 < z < 0.8 but fewer at 0.4 < z < 0.6, implying differential evolution. We compare the total light in the EDisCS cluster red sequences to the total red-sequence light in our SDSS cluster sample. Clusters at 0.4 < z < 0.8 must increase their luminosity on the red sequence (and therefore stellar mass in red galaxies) by a factor of 1-3 by z = 0. The necessary processes that add mass to the red sequence in clusters predict local clusters that are overluminous as compared to those observed in the SDSS. The predicted cluster luminosities can be reconciled with observed local cluster luminosities by combining multiple previously known effects.

Human Milk: Bioactive Proteins/Peptides and Functional Properties.

Science.gov (United States)

Lönnerdal, Bo

2016-06-23

Breastfeeding has been associated with many benefits, both in the short and in the long term. Infants being breastfed generally have less illness and have better cognitive development at 1 year of age than formula-fed infants. Later in life, they have a lower risk of obesity, diabetes and cardiovascular disease. Several components in breast milk may be responsible for these different outcomes, but bioactive proteins/peptides likely play a major role. Some proteins in breast milk are comparatively resistant towards digestion and may therefore exert their functions in the gastrointestinal tract in intact form or as larger fragments. Other milk proteins may be partially digested in the upper small intestine and the resulting peptides may exert functions in the lower small intestine. Lactoferrin, lysozyme and secretory IgA have been found intact in the stool of breastfed infants and are therefore examples of proteins that are resistant against proteolytic degradation in the gut. Together, these proteins serve protective roles against infection and support immune function in the immature infant. α-lactalbumin, β-casein, κ-casein and osteopontin are examples of proteins that are partially digested in the upper small intestine, and the resulting peptides influence functions in the gut. Such functions include stimulation of immune function, mineral and trace element absorption and defense against infection. © 2016 Nestec Ltd., Vevey/S. Karger AG, Basel.

Transcription Factor Functional Protein-Protein Interactions in Plant Defense Responses

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Murilo S. Alves

2014-03-01

Full Text Available Responses to biotic stress in plants lead to dramatic reprogramming of gene expression, favoring stress responses at the expense of normal cellular functions. Transcription factors are master regulators of gene expression at the transcriptional level, and controlling the activity of these factors alters the transcriptome of the plant, leading to metabolic and phenotypic changes in response to stress. The functional analysis of interactions between transcription factors and other proteins is very important for elucidating the role of these transcriptional regulators in different signaling cascades. In this review, we present an overview of protein-protein interactions for the six major families of transcription factors involved in plant defense: basic leucine zipper containing domain proteins (bZIP, amino-acid sequence WRKYGQK (WRKY, myelocytomatosis related proteins (MYC, myeloblastosis related proteins (MYB, APETALA2/ ETHYLENE-RESPONSIVE ELEMENT BINDING FACTORS (AP2/EREBP and no apical meristem (NAM, Arabidopsis transcription activation factor (ATAF, and cup-shaped cotyledon (CUC (NAC. We describe the interaction partners of these transcription factors as molecular responses during pathogen attack and the key components of signal transduction pathways that take place during plant defense responses. These interactions determine the activation or repression of response pathways and are crucial to understanding the regulatory networks that modulate plant defense responses.

Nutritional and functional properties of whey proteins concentrate and isolate

Directory of Open Access Journals (Sweden)

Zoran Herceg

2006-12-01

Full Text Available Whey protein fractions represent 18 - 20 % of total milk nitrogen content. Nutritional value in addition to diverse physico - chemical and functional properties make whey proteins highly suitable for application in foodstuffs. In the most cases, whey proteins are used because of their functional properties. Whey proteins possess favourable functional characteristics such as gelling, water binding, emulsification and foaming ability. Due to application of new process techniques (membrane fractionation techniques, it is possible to produce various whey - protein based products. The most important products based on the whey proteins are whey protein concentrates (WPC and whey protein isolates (WPI. The aim of this paper was to give comprehensive review of nutritional and functional properties of the most common used whey proteins (whey protein concentrate - WPC and whey protein isolate - WPI in the food industry.

MOCASSIN-prot: A multi-objective clustering approach for protein similarity networks

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Motivation: Proteins often include multiple conserved domains. Various evolutionary events including duplication and loss of domains, domain shuffling, as well as sequence divergence contribute to generating complexities in protein structures, and consequently, in their functions. The evolutionary h...

Random heteropolymers preserve protein function in foreign environments

Science.gov (United States)

Panganiban, Brian; Qiao, Baofu; Jiang, Tao; DelRe, Christopher; Obadia, Mona M.; Nguyen, Trung Dac; Smith, Anton A. A.; Hall, Aaron; Sit, Izaac; Crosby, Marquise G.; Dennis, Patrick B.; Drockenmuller, Eric; Olvera de la Cruz, Monica; Xu, Ting

2018-03-01

The successful incorporation of active proteins into synthetic polymers could lead to a new class of materials with functions found only in living systems. However, proteins rarely function under the conditions suitable for polymer processing. On the basis of an analysis of trends in protein sequences and characteristic chemical patterns on protein surfaces, we designed four-monomer random heteropolymers to mimic intrinsically disordered proteins for protein solubilization and stabilization in non-native environments. The heteropolymers, with optimized composition and statistical monomer distribution, enable cell-free synthesis of membrane proteins with proper protein folding for transport and enzyme-containing plastics for toxin bioremediation. Controlling the statistical monomer distribution in a heteropolymer, rather than the specific monomer sequence, affords a new strategy to interface with biological systems for protein-based biomaterials.

Cluster evolution

International Nuclear Information System (INIS)

Schaeffer, R.

1987-01-01

The galaxy and cluster luminosity functions are constructed from a model of the mass distribution based on hierarchical clustering at an epoch where the matter distribution is non-linear. These luminosity functions are seen to reproduce the present distribution of objects as can be inferred from the observations. They can be used to deduce the redshift dependence of the cluster distribution and to extrapolate the observations towards the past. The predicted evolution of the cluster distribution is quite strong, although somewhat less rapid than predicted by the linear theory

The Seven Sisters DANCe. I. Empirical isochrones, luminosity, and mass functions of the Pleiades cluster

Science.gov (United States)

Bouy, H.; Bertin, E.; Sarro, L. M.; Barrado, D.; Moraux, E.; Bouvier, J.; Cuillandre, J.-C.; Berihuete, A.; Olivares, J.; Beletsky, Y.

2015-05-01

Context. The DANCe survey provides photometric and astrometric (position and proper motion) measurements for approximately 2 million unique sources in a region encompassing ~80 deg2 centered on the Pleiades cluster. Aims: We aim at deriving a complete census of the Pleiades and measure the mass and luminosity functions of the cluster. Methods: Using the probabilistic selection method previously described, we identified high probability members in the DANCe (i ≥ 14 mag) and Tycho-2 (V ≲ 12 mag) catalogues and studied the properties of the cluster over the corresponding luminosity range. Results: We find a total of 2109 high-probability members, of which 812 are new, making it the most extensive and complete census of the cluster to date. The luminosity and mass functions of the cluster are computed from the most massive members down to ~0.025 M⊙. The size, sensitivity, and quality of the sample result in the most precise luminosity and mass functions observed to date for a cluster. Conclusions: Our census supersedes previous studies of the Pleiades cluster populations, in terms of both sensitivity and accuracy. Based on service observations made with the William Herschel Telescope operated on the island of La Palma by the Isaac Newton Group in the Spanish Observatorio del Roque de los Muchachos of the Instituto de Astrofísica de Canarias.Table 1 and Appendices are available in electronic form at http://www.aanda.orgDANCe catalogs (Tables 6 and 7) and full Tables 2-5 are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (ftp://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/577/A148

Nanomanufacturing of titania interfaces with controlled structural and functional properties by supersonic cluster beam deposition

International Nuclear Information System (INIS)

Podestà, Alessandro; Borghi, Francesca; Indrieri, Marco; Bovio, Simone; Piazzoni, Claudio; Milani, Paolo

2015-01-01

Great emphasis is placed on the development of integrated approaches for the synthesis and the characterization of ad hoc nanostructured platforms, to be used as templates with controlled morphology and chemical properties for the investigation of specific phenomena of great relevance in interdisciplinary fields such as biotechnology, medicine, and advanced materials. Here, we discuss the crucial role and the advantages of thin film deposition strategies based on cluster-assembling from supersonic cluster beams. We select cluster-assembled nanostructured titania (ns-TiO 2 ) as a case study to demonstrate that accurate control over morphological parameters can be routinely achieved, and consequently, over several relevant interfacial properties and phenomena, like surface charging in a liquid electrolyte, and proteins and nanoparticles adsorption. In particular, we show that the very good control of nanoscale morphology is obtained by taking advantage of simple scaling laws governing the ballistic deposition regime of low-energy, mass-dispersed clusters with reduced surface mobility

Nanomanufacturing of titania interfaces with controlled structural and functional properties by supersonic cluster beam deposition

Energy Technology Data Exchange (ETDEWEB)

Podestà, Alessandro, E-mail: alessandro.podesta@mi.infn.it, E-mail: pmilani@mi.infn.it; Borghi, Francesca; Indrieri, Marco; Bovio, Simone; Piazzoni, Claudio; Milani, Paolo, E-mail: alessandro.podesta@mi.infn.it, E-mail: pmilani@mi.infn.it [Centro Interdisciplinare Materiali e Interfacce Nanostrutturati (C.I.Ma.I.Na.), Dipartimento di Fisica, Università degli Studi di Milano, via Celoria 16, 20133 Milano (Italy)

2015-12-21

Great emphasis is placed on the development of integrated approaches for the synthesis and the characterization of ad hoc nanostructured platforms, to be used as templates with controlled morphology and chemical properties for the investigation of specific phenomena of great relevance in interdisciplinary fields such as biotechnology, medicine, and advanced materials. Here, we discuss the crucial role and the advantages of thin film deposition strategies based on cluster-assembling from supersonic cluster beams. We select cluster-assembled nanostructured titania (ns-TiO{sub 2}) as a case study to demonstrate that accurate control over morphological parameters can be routinely achieved, and consequently, over several relevant interfacial properties and phenomena, like surface charging in a liquid electrolyte, and proteins and nanoparticles adsorption. In particular, we show that the very good control of nanoscale morphology is obtained by taking advantage of simple scaling laws governing the ballistic deposition regime of low-energy, mass-dispersed clusters with reduced surface mobility.

Nanomanufacturing of titania interfaces with controlled structural and functional properties by supersonic cluster beam deposition

Science.gov (United States)

Podestà, Alessandro; Borghi, Francesca; Indrieri, Marco; Bovio, Simone; Piazzoni, Claudio; Milani, Paolo

2015-12-01

Great emphasis is placed on the development of integrated approaches for the synthesis and the characterization of ad hoc nanostructured platforms, to be used as templates with controlled morphology and chemical properties for the investigation of specific phenomena of great relevance in interdisciplinary fields such as biotechnology, medicine, and advanced materials. Here, we discuss the crucial role and the advantages of thin film deposition strategies based on cluster-assembling from supersonic cluster beams. We select cluster-assembled nanostructured titania (ns-TiO2) as a case study to demonstrate that accurate control over morphological parameters can be routinely achieved, and consequently, over several relevant interfacial properties and phenomena, like surface charging in a liquid electrolyte, and proteins and nanoparticles adsorption. In particular, we show that the very good control of nanoscale morphology is obtained by taking advantage of simple scaling laws governing the ballistic deposition regime of low-energy, mass-dispersed clusters with reduced surface mobility.

Dissociation of activated protein C functions by elimination of protein S cofactor enhancement.

LENUS (Irish Health Repository)

Harmon, Shona

2008-11-07

Activated protein C (APC) plays a critical anticoagulant role in vivo by inactivating procoagulant factor Va and factor VIIIa and thus down-regulating thrombin generation. In addition, APC bound to the endothelial cell protein C receptor can initiate protease-activated receptor-1 (PAR-1)-mediated cytoprotective signaling. Protein S constitutes a critical cofactor for the anticoagulant function of APC but is not known to be involved in regulating APC-mediated protective PAR-1 signaling. In this study we utilized a site-directed mutagenesis strategy to characterize a putative protein S binding region within the APC Gla domain. Three single amino acid substitutions within the APC Gla domain (D35T, D36A, and A39V) were found to mildly impair protein S-dependent anticoagulant activity (<2-fold) but retained entirely normal cytoprotective activity. However, a single amino acid substitution (L38D) ablated the ability of protein S to function as a cofactor for this APC variant. Consequently, in assays of protein S-dependent factor Va proteolysis using purified proteins or in the plasma milieu, APC-L38D variant exhibited minimal residual anticoagulant activity compared with wild type APC. Despite the location of Leu-38 in the Gla domain, APC-L38D interacted normally with endothelial cell protein C receptor and retained its ability to trigger PAR-1 mediated cytoprotective signaling in a manner indistinguishable from that of wild type APC. Consequently, elimination of protein S cofactor enhancement of APC anticoagulant function represents a novel and effective strategy by which to separate the anticoagulant and cytoprotective functions of APC for potential therapeutic gain.

A collaborative filtering approach for protein-protein docking scoring functions.

Science.gov (United States)

Bourquard, Thomas; Bernauer, Julie; Azé, Jérôme; Poupon, Anne

2011-04-22

A protein-protein docking procedure traditionally consists in two successive tasks: a search algorithm generates a large number of candidate conformations mimicking the complex existing in vivo between two proteins, and a scoring function is used to rank them in order to extract a native-like one. We have already shown that using Voronoi constructions and a well chosen set of parameters, an accurate scoring function could be designed and optimized. However to be able to perform large-scale in silico exploration of the interactome, a near-native solution has to be found in the ten best-ranked solutions. This cannot yet be guaranteed by any of the existing scoring functions. In this work, we introduce a new procedure for conformation ranking. We previously developed a set of scoring functions where learning was performed using a genetic algorithm. These functions were used to assign a rank to each possible conformation. We now have a refined rank using different classifiers (decision trees, rules and support vector machines) in a collaborative filtering scheme. The scoring function newly obtained is evaluated using 10 fold cross-validation, and compared to the functions obtained using either genetic algorithms or collaborative filtering taken separately. This new approach was successfully applied to the CAPRI scoring ensembles. We show that for 10 targets out of 12, we are able to find a near-native conformation in the 10 best ranked solutions. Moreover, for 6 of them, the near-native conformation selected is of high accuracy. Finally, we show that this function dramatically enriches the 100 best-ranking conformations in near-native structures.

Functionalization of whey proteins by reactive supercritical fluid extrusion

Directory of Open Access Journals (Sweden)

Khanitta Ruttarattanamongkol

2012-09-01

Full Text Available Whey protein, a by-product from cheese-making, is often used in a variety of food formulations due to its unsurpassednutritional quality and inherent functional properties. However, the possibilities for the improvement and upgrading of wheyprotein utilization still need to be explored. Reactive supercritical fluid extrusion (SCFX is a novel technique that has beenrecently reported to successfully functionalize commercially available whey proteins into a product with enhanced functionalproperties. The specific goal of this review is to provide fundamental understanding of the reinforcement mechanism andprocessing of protein functionalization by reactive SCFX process. The superimposed extrusion variables and their interactionmechanism affect the physico-chemical properties of whey proteins. By understanding the structure, functional properties andprocessing relationships of such materials, the rational design criteria for novel functionalized proteins could be developedand effectively utilized in food systems.

Covalent functionalization of octagraphene with magnetic octahedral B6- and non-planar C6- clusters

Science.gov (United States)

Chigo-Anota, E.; Cárdenas-Jirón, G.; Salazar Villanueva, M.; Bautista Hernández, A.; Castro, M.

2017-10-01

The interaction between the magnetic boron octahedral (B6-) and non-planar (C6-) carbon clusters with semimetal nano-sheet of octa-graphene (C64H24) in the gas phase is studied by means of DFT calculations. These results reveal that non-planar-1 (anion) carbon cluster exhibits structural stability, low chemical reactivity, magnetic (1.0 magneton bohr) and semiconductor behavior. On the other hand, there is chemisorption phenomena when the stable B6- and C6- clusters are absorbed on octa-graphene nanosheets. Such absorption generates high polarity and the low-reactivity remains as on the individual pristine cases. Electronic charge transference occurs from the clusters toward the nanosheets, producing a reduction of the work function for the complexes and also induces a magnetic behavior on the functionalized sheets. The quantum descriptors obtained for these systems reveal that they are feasible candidates for the design of molecular circuits, magnetic devices, and nano-vehicles for drug delivery.

Usher protein functions in hair cells and photoreceptors.

Science.gov (United States)

Cosgrove, Dominic; Zallocchi, Marisa

2014-01-01

The 10 different genes associated with the deaf/blind disorder, Usher syndrome, encode a number of structurally and functionally distinct proteins, most expressed as multiple isoforms/protein variants. Functional characterization of these proteins suggests a role in stereocilia development in cochlear hair cells, likely owing to adhesive interactions in hair bundles. In mature hair cells, homodimers of the Usher cadherins, cadherin 23 and protocadherin 15, interact to form a structural fiber, the tip link, and the linkages that anchor the taller stereocilia's actin cytoskeleton core to the shorter adjacent stereocilia and the elusive mechanotransduction channels, explaining the deafness phenotype when these molecular interactions are perturbed. The conundrum is that photoreceptors lack a synonymous mechanotransduction apparatus, and so a common theory for Usher protein function in the two neurosensory cell types affected in Usher syndrome is lacking. Recent evidence linking photoreceptor cell dysfunction in the shaker 1 mouse model for Usher syndrome to light-induced protein translocation defects, combined with localization of an Usher protein interactome at the periciliary region of the photoreceptors suggests Usher proteins might regulate protein trafficking between the inner and outer segments of photoreceptors. A distinct Usher protein complex is trafficked to the ribbon synapses of hair cells, and synaptic defects have been reported in Usher mutants in both hair cells and photoreceptors. This review aims to clarify what is known about Usher protein function at the synaptic and apical poles of hair cells and photoreceptors and the prospects for identifying a unifying pathobiological mechanism to explain deaf/blindness in Usher syndrome. Copyright © 2013 Elsevier Ltd. All rights reserved.

From Extraction of Local Structures of Protein Energy Landscapes to Improved Decoy Selection in Template-Free Protein Structure Prediction.

Science.gov (United States)

Akhter, Nasrin; Shehu, Amarda

2018-01-19

Due to the essential role that the three-dimensional conformation of a protein plays in regulating interactions with molecular partners, wet and dry laboratories seek biologically-active conformations of a protein to decode its function. Computational approaches are gaining prominence due to the labor and cost demands of wet laboratory investigations. Template-free methods can now compute thousands of conformations known as decoys, but selecting native conformations from the generated decoys remains challenging. Repeatedly, research has shown that the protein energy functions whose minima are sought in the generation of decoys are unreliable indicators of nativeness. The prevalent approach ignores energy altogether and clusters decoys by conformational similarity. Complementary recent efforts design protein-specific scoring functions or train machine learning models on labeled decoys. In this paper, we show that an informative consideration of energy can be carried out under the energy landscape view. Specifically, we leverage local structures known as basins in the energy landscape probed by a template-free method. We propose and compare various strategies of basin-based decoy selection that we demonstrate are superior to clustering-based strategies. The presented results point to further directions of research for improving decoy selection, including the ability to properly consider the multiplicity of native conformations of proteins.

From Extraction of Local Structures of Protein Energy Landscapes to Improved Decoy Selection in Template-Free Protein Structure Prediction

Directory of Open Access Journals (Sweden)

Nasrin Akhter

2018-01-01

Full Text Available Due to the essential role that the three-dimensional conformation of a protein plays in regulating interactions with molecular partners, wet and dry laboratories seek biologically-active conformations of a protein to decode its function. Computational approaches are gaining prominence due to the labor and cost demands of wet laboratory investigations. Template-free methods can now compute thousands of conformations known as decoys, but selecting native conformations from the generated decoys remains challenging. Repeatedly, research has shown that the protein energy functions whose minima are sought in the generation of decoys are unreliable indicators of nativeness. The prevalent approach ignores energy altogether and clusters decoys by conformational similarity. Complementary recent efforts design protein-specific scoring functions or train machine learning models on labeled decoys. In this paper, we show that an informative consideration of energy can be carried out under the energy landscape view. Specifically, we leverage local structures known as basins in the energy landscape probed by a template-free method. We propose and compare various strategies of basin-based decoy selection that we demonstrate are superior to clustering-based strategies. The presented results point to further directions of research for improving decoy selection, including the ability to properly consider the multiplicity of native conformations of proteins.

Automated quantitative assessment of proteins' biological function in protein knowledge bases.

Science.gov (United States)

Mayr, Gabriele; Lepperdinger, Günter; Lackner, Peter

2008-01-01

Primary protein sequence data are archived in databases together with information regarding corresponding biological functions. In this respect, UniProt/Swiss-Prot is currently the most comprehensive collection and it is routinely cross-examined when trying to unravel the biological role of hypothetical proteins. Bioscientists frequently extract single entries and further evaluate those on a subjective basis. In lieu of a standardized procedure for scoring the existing knowledge regarding individual proteins, we here report about a computer-assisted method, which we applied to score the present knowledge about any given Swiss-Prot entry. Applying this quantitative score allows the comparison of proteins with respect to their sequence yet highlights the comprehension of functional data. pfs analysis may be also applied for quality control of individual entries or for database management in order to rank entry listings.

Automated Quantitative Assessment of Proteins' Biological Function in Protein Knowledge Bases

Directory of Open Access Journals (Sweden)

Gabriele Mayr

2008-01-01

Full Text Available Primary protein sequence data are archived in databases together with information regarding corresponding biological functions. In this respect, UniProt/Swiss-Prot is currently the most comprehensive collection and it is routinely cross-examined when trying to unravel the biological role of hypothetical proteins. Bioscientists frequently extract single entries and further evaluate those on a subjective basis. In lieu of a standardized procedure for scoring the existing knowledge regarding individual proteins, we here report about a computer-assisted method, which we applied to score the present knowledge about any given Swiss-Prot entry. Applying this quantitative score allows the comparison of proteins with respect to their sequence yet highlights the comprehension of functional data. pfs analysis may be also applied for quality control of individual entries or for database management in order to rank entry listings.

Extending Ripley's K-Function to Quantify Aggregation in 2-D Grayscale Images.

Directory of Open Access Journals (Sweden)

Mohamed Amgad

Full Text Available In this work, we describe the extension of Ripley's K-function to allow for overlapping events at very high event densities. We show that problematic edge effects introduce significant bias to the function at very high densities and small radii, and propose a simple correction method that successfully restores the function's centralization. Using simulations of homogeneous Poisson distributions of events, as well as simulations of event clustering under different conditions, we investigate various aspects of the function, including its shape-dependence and correspondence between true cluster radius and radius at which the K-function is maximized. Furthermore, we validate the utility of the function in quantifying clustering in 2-D grayscale images using three modalities: (i Simulations of particle clustering; (ii Experimental co-expression of soluble and diffuse protein at varying ratios; (iii Quantifying chromatin clustering in the nuclei of wt and crwn1 crwn2 mutant Arabidopsis plant cells, using a previously-published image dataset. Overall, our work shows that Ripley's K-function is a valid abstract statistical measure whose utility extends beyond the quantification of clustering of non-overlapping events. Potential benefits of this work include the quantification of protein and chromatin aggregation in fluorescent microscopic images. Furthermore, this function has the potential to become one of various abstract texture descriptors that are utilized in computer-assisted diagnostics in anatomic pathology and diagnostic radiology.

Protein-gold clusters-capped mesoporous silica nanoparticles for high drug loading, autonomous gemcitabine/doxorubicin co-delivery, and in-vivo tumor imaging

KAUST Repository

Croissant, Jonas G.; Zhang, Dingyuan; Alsaiari, Shahad K.; Lu, Jie; Deng, Lin; Tamanoi, Fuyuhiko; Zink, Jeffrey I.; Khashab, Niveen M.

2016-01-01

Functional nanocarriers capable of transporting high drug contents without premature leakage and to controllably deliver several drugs are needed for better cancer treatments. To address this clinical need, gold cluster bovine serum albumin (AuNC@BSA) nanogates were engineered on mesoporous silica nanoparticles (MSN) for high drug loadings and co-delivery of two different anticancer drugs. The first drug, gemcitabine (GEM, 40 wt%), was loaded in positively-charged ammonium-functionalized MSN (MSN-NH3+). The second drug, doxorubicin (DOX, 32 wt%), was bound with negatively-charged AuNC@BSA electrostatically-attached onto MSN-NH3+, affording highly loaded pH-responsive MSN-AuNC@BSA nanocarriers. The co-delivery of DOX and GEM was achieved for the first time via an inorganic nanocarrier, possessing a zero-premature leakage behavior as well as drug loading capacities seven times higher than polymersome NPs. Besides, unlike the majority of strategies used to cap the pores of MSN, AuNC@BSA nanogates are biotools and were applied for targeted red nuclear staining and in-vivo tumor imaging. The straightforward non-covalent combination of MSN and gold-protein cluster bioconjugates thus leads to a simple, yet multifunctional nanotheranostic for the next generation of cancer treatments.

Protein-gold clusters-capped mesoporous silica nanoparticles for high drug loading, autonomous gemcitabine/doxorubicin co-delivery, and in-vivo tumor imaging

KAUST Repository

Croissant, Jonas G.

2016-03-23

Functional nanocarriers capable of transporting high drug contents without premature leakage and to controllably deliver several drugs are needed for better cancer treatments. To address this clinical need, gold cluster bovine serum albumin (AuNC@BSA) nanogates were engineered on mesoporous silica nanoparticles (MSN) for high drug loadings and co-delivery of two different anticancer drugs. The first drug, gemcitabine (GEM, 40 wt%), was loaded in positively-charged ammonium-functionalized MSN (MSN-NH3+). The second drug, doxorubicin (DOX, 32 wt%), was bound with negatively-charged AuNC@BSA electrostatically-attached onto MSN-NH3+, affording highly loaded pH-responsive MSN-AuNC@BSA nanocarriers. The co-delivery of DOX and GEM was achieved for the first time via an inorganic nanocarrier, possessing a zero-premature leakage behavior as well as drug loading capacities seven times higher than polymersome NPs. Besides, unlike the majority of strategies used to cap the pores of MSN, AuNC@BSA nanogates are biotools and were applied for targeted red nuclear staining and in-vivo tumor imaging. The straightforward non-covalent combination of MSN and gold-protein cluster bioconjugates thus leads to a simple, yet multifunctional nanotheranostic for the next generation of cancer treatments.

AVID: An integrative framework for discovering functional relationships among proteins

Directory of Open Access Journals (Sweden)

Keating Amy E

2005-06-01

Full Text Available Abstract Background Determining the functions of uncharacterized proteins is one of the most pressing problems in the post-genomic era. Large scale protein-protein interaction assays, global mRNA expression analyses and systematic protein localization studies provide experimental information that can be used for this purpose. The data from such experiments contain many false positives and false negatives, but can be processed using computational methods to provide reliable information about protein-protein relationships and protein function. An outstanding and important goal is to predict detailed functional annotation for all uncharacterized proteins that is reliable enough to effectively guide experiments. Results We present AVID, a computational method that uses a multi-stage learning framework to integrate experimental results with sequence information, generating networks reflecting functional similarities among proteins. We illustrate use of the networks by making predictions of detailed Gene Ontology (GO annotations in three categories: molecular function, biological process, and cellular component. Applied to the yeast Saccharomyces cerevisiae, AVID provides 37,451 pair-wise functional linkages between 4,191 proteins. These relationships are ~65–78% accurate, as assessed by cross-validation testing. Assignments of highly detailed functional descriptors to proteins, based on the networks, are estimated to be ~67% accurate for GO categories describing molecular function and cellular component and ~52% accurate for terms describing biological process. The predictions cover 1,490 proteins with no previous annotation in GO and also assign more detailed functions to many proteins annotated only with less descriptive terms. Predictions made by AVID are largely distinct from those made by other methods. Out of 37,451 predicted pair-wise relationships, the greatest number shared in common with another method is 3,413. Conclusion AVID provides

Scoring protein relationships in functional interaction networks predicted from sequence data.

Directory of Open Access Journals (Sweden)

Gaston K Mazandu

Full Text Available UNLABELLED: The abundance of diverse biological data from various sources constitutes a rich source of knowledge, which has the power to advance our understanding of organisms. This requires computational methods in order to integrate and exploit these data effectively and elucidate local and genome wide functional connections between protein pairs, thus enabling functional inferences for uncharacterized proteins. These biological data are primarily in the form of sequences, which determine functions, although functional properties of a protein can often be predicted from just the domains it contains. Thus, protein sequences and domains can be used to predict protein pair-wise functional relationships, and thus contribute to the function prediction process of uncharacterized proteins in order to ensure that knowledge is gained from sequencing efforts. In this work, we introduce information-theoretic based approaches to score protein-protein functional interaction pairs predicted from protein sequence similarity and conserved protein signature matches. The proposed schemes are effective for data-driven scoring of connections between protein pairs. We applied these schemes to the Mycobacterium tuberculosis proteome to produce a homology-based functional network of the organism with a high confidence and coverage. We use the network for predicting functions of uncharacterised proteins. AVAILABILITY: Protein pair-wise functional relationship scores for Mycobacterium tuberculosis strain CDC1551 sequence data and python scripts to compute these scores are available at http://web.cbio.uct.ac.za/~gmazandu/scoringschemes.

Mössbauer spectroscopy and DFT calculations on all protonation states of the 2Fe-2S cluster of the Rieske protein

Science.gov (United States)

Müller, C. S.; Auerbach, H.; Stegmaier, K.; Wolny, J. A.; Schünemann, V.; Pierik, A. J.

2017-11-01

The Thermus thermophilus Rieske protein ( TtRP) contains a 2Fe-2S cluster with one iron (Fe-Cys) coordinated by four sulfur atoms (2xS2- and 2xCys) and one iron (Fe-His) by two sulfur and two nitrogen atoms (2xS2-, His134 and His154). Here, the protein is investigated at three pH values (6.0, 8.5 and 10.5) in order to elucidate the protonation states of the His-ligands. Examination of the effect of protonation on the electronic structure of the cluster via Mössbauer spectroscopy gives a deeper understanding of the coupling of electron transfer to the protonation state of the His-ligands. Two components (1 referring to Fe-Cys and 2 to Fe-His) with parameters typical for a diamagnetic [2Fe-2S]2+ cluster are detected. The Mössbauer parameters and the protonation state clearly correlate: while δ remains almost pH-independent with δ 1 (pH6.0) = 0.23 (± 0.01) mms- 1 and δ 1 (pH10.5) = 0.24 (± 0.01) mms- 1 for Fe-Cys, it decreases for Fe-His from δ 2 (pH6.0) = 0.34 (± 0.01) mms- 1 to δ 2 (pH10.5) = 0.28 (± 0.01) mms- 1. Δ E Q changes from Δ E Q1 (pH6.0) = 0.57 (± 0.01) mms- 1 to Δ E Q1 (pH10.5) = 0.45 (± 0.01) mms- 1 and from Δ E Q2 (pH6.0) = 1.05 (± 0.01) mms- 1 to Δ E Q2 (pH10.5) = 0.71 (± 0.01) mms- 1. Density functional theory (DFT)-calculations based on the crystal structure (pdb 1NYK) (Hunsicker-Wang et al. Biochemistry 42, 7303, 2003) have been performed for the Rieske-cluster with different His-ligand protonation states, reproducing the experimentally observed trend.

Which Density Functional Should Be Used to Describe Protonated Water Clusters?

Science.gov (United States)

Shi, Ruili; Huang, Xiaoming; Su, Yan; Lu, Hai-Gang; Li, Si-Dian; Tang, Lingli; Zhao, Jijun

2017-04-27

Protonated water cluster is one of the most important hydrogen-bond network systems. Finding an appropriate DFT method to study the properties of protonated water clusters can substantially improve the economy in computational resources without sacrificing the accuracy compared to high-level methods. Using high-level MP2 and CCSD(T) methods as well as experimental results as benchmark, we systematically examined the effect of seven exchange-correlation GGA functionals (with BLYP, B3LYP, X3LYP, PBE0, PBE1W, M05-2X, and B97-D parametrizations) in describing the geometric parameters, interaction energies, dipole moments, and vibrational properties of protonated water clusters H + (H 2 O) 2-9,12 . The overall performance of all these functionals is acceptable, and each of them has its advantage in certain aspects. X3LYP is the best to describe the interaction energies, and PBE0 and M05-2X are also recommended to investigate interaction energies. PBE0 gives the best anharmonic frequencies, followed by PBE1W, B97-D and BLYP methods. PBE1W, B3LYP, B97-D, and X3LYP can yield better geometries. The capability of B97-D to distinguish the relative energies between isomers is the best among all the seven methods, followed by M05-2X and PBE0.

Clusters of Insomnia Disorder: An Exploratory Cluster Analysis of Objective Sleep Parameters Reveals Differences in Neurocognitive Functioning, Quantitative EEG, and Heart Rate Variability

Science.gov (United States)

Miller, Christopher B.; Bartlett, Delwyn J.; Mullins, Anna E.; Dodds, Kirsty L.; Gordon, Christopher J.; Kyle, Simon D.; Kim, Jong Won; D'Rozario, Angela L.; Lee, Rico S.C.; Comas, Maria; Marshall, Nathaniel S.; Yee, Brendon J.; Espie, Colin A.; Grunstein, Ronald R.

2016-01-01

Study Objectives: To empirically derive and evaluate potential clusters of Insomnia Disorder through cluster analysis from polysomnography (PSG). We hypothesized that clusters would differ on neurocognitive performance, sleep-onset measures of quantitative (q)-EEG and heart rate variability (HRV). Methods: Research volunteers with Insomnia Disorder (DSM-5) completed a neurocognitive assessment and overnight PSG measures of total sleep time (TST), wake time after sleep onset (WASO), and sleep onset latency (SOL) were used to determine clusters. Results: From 96 volunteers with Insomnia Disorder, cluster analysis derived at least two clusters from objective sleep parameters: Insomnia with normal objective sleep duration (I-NSD: n = 53) and Insomnia with short sleep duration (I-SSD: n = 43). At sleep onset, differences in HRV between I-NSD and I-SSD clusters suggest attenuated parasympathetic activity in I-SSD (P insomnia clusters derived from cluster analysis differ in sleep onset HRV. Preliminary data suggest evidence for three clusters in insomnia with differences for sustained attention and sleep-onset q-EEG. Clinical Trial Registration: Insomnia 100 sleep study: Australia New Zealand Clinical Trials Registry (ANZCTR) identification number 12612000049875. URL: https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=347742. Citation: Miller CB, Bartlett DJ, Mullins AE, Dodds KL, Gordon CJ, Kyle SD, Kim JW, D'Rozario AL, Lee RS, Comas M, Marshall NS, Yee BJ, Espie CA, Grunstein RR. Clusters of Insomnia Disorder: an exploratory cluster analysis of objective sleep parameters reveals differences in neurocognitive functioning, quantitative EEG, and heart rate variability. SLEEP 2016;39(11):1993–2004. PMID:27568796

The contact activation proteins: a structure/function overview

NARCIS (Netherlands)

Meijers, J. C.; McMullen, B. A.; Bouma, B. N.

1992-01-01

In recent years, extensive knowledge has been obtained on the structure/function relationships of blood coagulation proteins. In this overview, we present recent developments on the structure/function relationships of the contact activation proteins: factor XII, high molecular weight kininogen,

Cluster editing

DEFF Research Database (Denmark)

Böcker, S.; Baumbach, Jan

2013-01-01

. The problem has been the inspiration for numerous algorithms in bioinformatics, aiming at clustering entities such as genes, proteins, phenotypes, or patients. In this paper, we review exact and heuristic methods that have been proposed for the Cluster Editing problem, and also applications......The Cluster Editing problem asks to transform a graph into a disjoint union of cliques using a minimum number of edge modifications. Although the problem has been proven NP-complete several times, it has nevertheless attracted much research both from the theoretical and the applied side...

Alkylation damage by lipid electrophiles targets functional protein systems.

Science.gov (United States)

Codreanu, Simona G; Ullery, Jody C; Zhu, Jing; Tallman, Keri A; Beavers, William N; Porter, Ned A; Marnett, Lawrence J; Zhang, Bing; Liebler, Daniel C

2014-03-01

Protein alkylation by reactive electrophiles contributes to chemical toxicities and oxidative stress, but the functional impact of alkylation damage across proteomes is poorly understood. We used Click chemistry and shotgun proteomics to profile the accumulation of proteome damage in human cells treated with lipid electrophile probes. Protein target profiles revealed three damage susceptibility classes, as well as proteins that were highly resistant to alkylation. Damage occurred selectively across functional protein interaction networks, with the most highly alkylation-susceptible proteins mapping to networks involved in cytoskeletal regulation. Proteins with lower damage susceptibility mapped to networks involved in protein synthesis and turnover and were alkylated only at electrophile concentrations that caused significant toxicity. Hierarchical susceptibility of proteome systems to alkylation may allow cells to survive sublethal damage while protecting critical cell functions.

Alkylation Damage by Lipid Electrophiles Targets Functional Protein Systems*

Science.gov (United States)

Codreanu, Simona G.; Ullery, Jody C.; Zhu, Jing; Tallman, Keri A.; Beavers, William N.; Porter, Ned A.; Marnett, Lawrence J.; Zhang, Bing; Liebler, Daniel C.

2014-01-01

Protein alkylation by reactive electrophiles contributes to chemical toxicities and oxidative stress, but the functional impact of alkylation damage across proteomes is poorly understood. We used Click chemistry and shotgun proteomics to profile the accumulation of proteome damage in human cells treated with lipid electrophile probes. Protein target profiles revealed three damage susceptibility classes, as well as proteins that were highly resistant to alkylation. Damage occurred selectively across functional protein interaction networks, with the most highly alkylation-susceptible proteins mapping to networks involved in cytoskeletal regulation. Proteins with lower damage susceptibility mapped to networks involved in protein synthesis and turnover and were alkylated only at electrophile concentrations that caused significant toxicity. Hierarchical susceptibility of proteome systems to alkylation may allow cells to survive sublethal damage while protecting critical cell functions. PMID:24429493

Targeting protein-protein interaction between MLL1 and reciprocal proteins for leukemia therapy.

Science.gov (United States)

Wang, Zhi-Hui; Li, Dong-Dong; Chen, Wei-Lin; You, Qi-Dong; Guo, Xiao-Ke

2018-01-15

The mixed lineage leukemia protein-1 (MLL1), as a lysine methyltransferase, predominantly regulates the methylation of histone H3 lysine 4 (H3K4) and functions in hematopoietic stem cell (HSC) self-renewal. MLL1 gene fuses with partner genes that results in the generation of MLL1 fusion proteins (MLL1-FPs), which are frequently detected in acute leukemia. In the progress of leukemogenesis, a great deal of proteins cooperate with MLL1 to form multiprotein complexes serving for the dysregulation of H3K4 methylation, the overexpression of homeobox (HOX) cluster genes, and the consequent generation of leukemia. Hence, disrupting the interactions between MLL1 and the reciprocal proteins has been considered to be a new treatment strategy for leukemia. Here, we reviewed potential protein-protein interactions (PPIs) between MLL1 and its reciprocal proteins, and summarized the inhibitors to target MLL1 PPIs. The druggability of MLL1 PPIs for leukemia were also discussed. Copyright © 2017. Published by Elsevier Ltd.

One- and two-particle correlation functions in the dynamical quantum cluster approach

International Nuclear Information System (INIS)

Hochkeppel, Stephan

2008-01-01

This thesis is dedicated to a theoretical study of the 1-band Hubbard model in the strong coupling limit. The investigation is based on the Dynamical Cluster Approximation (DCA) which systematically restores non-local corrections to the Dynamical Mean Field approximation (DMFA). The DCA is formulated in momentum space and is characterised by a patching of the Brillouin zone where momentum conservation is only recovered between two patches. The approximation works well if k-space correlation functions show a weak momentum dependence. In order to study the temperature and doping dependence of the spin- and charge excitation spectra, we explicitly extend the Dynamical Cluster Approximation to two-particle response functions. The full irreducible two-particle vertex with three momenta and frequencies is approximated by an effective vertex dependent on the momentum and frequency of the spin and/or charge excitations. The effective vertex is calculated by using the Quantum Monte Carlo method on the finite cluster whereas the analytical continuation of dynamical quantities is performed by a stochastic version of the maximum entropy method. A comparison with high temperature auxiliary field quantum Monte Carlo data serves as a benchmark for our approach to two-particle correlation functions. Our method can reproduce basic characteristics of the spin- and charge excitation spectrum. Near and beyond optimal doping, our results provide a consistent overall picture of the interplay between charge, spin and single-particle excitations: a collective spin mode emerges at optimal doping and sufficiently low temperatures in the spin response spectrum and exhibits the energy scale of the magnetic exchange interaction J. Simultaneously, the low energy single-particle excitations are characterised by a coherent quasiparticle with bandwidth J. The origin of the quasiparticle can be quite well understood in a picture of a more or less antiferromagnetic ordered background in which holes

Live-cell FRET imaging reveals clustering of the prion protein at the cell surface induced by infectious prions.

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Tavares, Evandro; Macedo, Joana A; Paulo, Pedro M R; Tavares, Catarina; Lopes, Carlos; Melo, Eduardo P

2014-07-01

Prion diseases are associated to the conversion of the prion protein into a misfolded pathological isoform. The mechanism of propagation of protein misfolding by protein templating remains largely unknown. Neuroblastoma cells were transfected with constructs of the prion protein fused to both CFP-GPI-anchored and to YFP-GPI-anchored and directed to its cell membrane location. Live-cell FRET imaging between the prion protein fused to CFP or YFP was measured giving consistent values of 10±2%. This result was confirmed by fluorescence lifetime imaging microscopy and indicates intermolecular interactions between neighbor prion proteins. In particular, considering that a maximum FRET efficiency of 17±2% was determined from a positive control consisting of a fusion CFP-YFP-GPI-anchored. A stable cell clone expressing the two fusions containing the prion protein was also selected to minimize cell-to-cell variability. In both, stable and transiently transfected cells, the FRET efficiency consistently increased in the presence of infectious prions - from 4±1% to 7±1% in the stable clone and from 10±2% to 16±1% in transiently transfected cells. These results clearly reflect an increased clustering of the prion protein on the membrane in the presence of infectious prions, which was not observed in negative control using constructs without the prion protein and upon addition of non-infected brain. Our data corroborates the recent view that the primary site for prion conversion is the cell membrane. Since our fluorescent cell clone is not susceptible to propagate infectivity, we hypothesize that the initial event of prion infectivity might be the clustering of the GPI-anchored prion protein. Copyright © 2014 Elsevier B.V. All rights reserved.

Cluster size statistic and cluster mass statistic: two novel methods for identifying changes in functional connectivity between groups or conditions.

Science.gov (United States)

Ing, Alex; Schwarzbauer, Christian

2014-01-01

Functional connectivity has become an increasingly important area of research in recent years. At a typical spatial resolution, approximately 300 million connections link each voxel in the brain with every other. This pattern of connectivity is known as the functional connectome. Connectivity is often compared between experimental groups and conditions. Standard methods used to control the type 1 error rate are likely to be insensitive when comparisons are carried out across the whole connectome, due to the huge number of statistical tests involved. To address this problem, two new cluster based methods--the cluster size statistic (CSS) and cluster mass statistic (CMS)--are introduced to control the family wise error rate across all connectivity values. These methods operate within a statistical framework similar to the cluster based methods used in conventional task based fMRI. Both methods are data driven, permutation based and require minimal statistical assumptions. Here, the performance of each procedure is evaluated in a receiver operator characteristic (ROC) analysis, utilising a simulated dataset. The relative sensitivity of each method is also tested on real data: BOLD (blood oxygen level dependent) fMRI scans were carried out on twelve subjects under normal conditions and during the hypercapnic state (induced through the inhalation of 6% CO2 in 21% O2 and 73%N2). Both CSS and CMS detected significant changes in connectivity between normal and hypercapnic states. A family wise error correction carried out at the individual connection level exhibited no significant changes in connectivity.

Usher protein functions in hair cells and photoreceptors

OpenAIRE

Cosgrove, Dominic; Zallocchi, Marisa

2013-01-01

The 10 different genes associated with the deaf/blind disorder, Usher syndrome, encode a number of structurally and functionally distinct proteins, most expressed as multiple isoforms/protein variants. Functional characterization of these proteins suggests a role in stereocilia development in cochlear hair cells, likely owing to adhesive interactions in hair bundles. In mature hair cells, homodimers of the Usher cadherins, cadherin 23 and protocadherin 15, interact to form a structural fiber,...

Structure and function of nanoparticle-protein conjugates

International Nuclear Information System (INIS)

Aubin-Tam, M-E; Hamad-Schifferli, K

2008-01-01

Conjugation of proteins to nanoparticles has numerous applications in sensing, imaging, delivery, catalysis, therapy and control of protein structure and activity. Therefore, characterizing the nanoparticle-protein interface is of great importance. A variety of covalent and non-covalent linking chemistries have been reported for nanoparticle attachment. Site-specific labeling is desirable in order to control the protein orientation on the nanoparticle, which is crucial in many applications such as fluorescence resonance energy transfer. We evaluate methods for successful site-specific attachment. Typically, a specific protein residue is linked directly to the nanoparticle core or to the ligand. As conjugation often affects the protein structure and function, techniques to probe structure and activity are assessed. We also examine how molecular dynamics simulations of conjugates would complete those experimental techniques in order to provide atomistic details on the effect of nanoparticle attachment. Characterization studies of nanoparticle-protein complexes show that the structure and function are influenced by the chemistry of the nanoparticle ligand, the nanoparticle size, the nanoparticle material, the stoichiometry of the conjugates, the labeling site on the protein and the nature of the linkage (covalent versus non-covalent)

The function of Shp2 tyrosine phosphatase in the dispersal of acetylcholine receptor clusters

Directory of Open Access Journals (Sweden)

Madhavan Raghavan

2008-07-01

Full Text Available Abstract Background A crucial event in the development of the vertebrate neuromuscular junction (NMJ is the postsynaptic enrichment of muscle acetylcholine (ACh receptors (AChRs. This process involves two distinct steps: the local clustering of AChRs at synapses, which depends on the activation of the muscle-specific receptor tyrosine kinase MuSK by neural agrin, and the global dispersal of aneural or "pre-patterned" AChR aggregates, which is triggered by ACh or by synaptogenic stimuli. We and others have previously shown that tyrosine phosphatases, such as the SH2 domain-containing phosphatase Shp2, regulate AChR cluster formation in muscle cells, and that tyrosine phosphatases also mediate the dispersal of pre-patterned AChR clusters by synaptogenic stimuli, although the specific phosphatases involved in this latter step remain unknown. Results Using an assay system that allows AChR cluster assembly and disassembly to be studied separately and quantitatively, we describe a previously unrecognized role of the tyrosine phosphatase Shp2 in AChR cluster disassembly. Shp2 was robustly expressed in embryonic Xenopus muscle in vivo and in cultured myotomal muscle cells, and treatment of the muscle cultures with an inhibitor of Shp2 (NSC-87877 blocked the dispersal of pre-patterned AChR clusters by synaptogenic stimuli. In contrast, over-expression in muscle cells of either wild-type or constitutively active Shp2 accelerated cluster dispersal. Significantly, forced expression in muscle of the Shp2-activator SIRPα1 (signal regulatory protein α1 also enhanced the disassembly of AChR clusters, whereas the expression of a truncated SIRPα1 mutant that suppresses Shp2 signaling inhibited cluster disassembly. Conclusion Our results suggest that Shp2 activation by synaptogenic stimuli, through signaling intermediates such as SIRPα1, promotes the dispersal of pre-patterned AChR clusters to facilitate the selective accumulation of AChRs at developing NMJs.

Equilibrium Structures and Absorption Spectra for SixOy Molecular Clusters using Density Functional Theory

Science.gov (United States)

2017-05-05

Naval Research Laboratory Washington, DC 20375-5320 NRL/MR/6390--17-9724 Equilibrium Structures and Absorption Spectra for SixOy Molecular Clusters...TELEPHONE NUMBER (include area code) b. ABSTRACT c. THIS PAGE 18. NUMBER OF PAGES 17. LIMITATION OF ABSTRACT Equilibrium Structures and Absorption...and electronic excited-state absorption spectra for eqilibrium structures of SixOy molecular clusters using density function theory (DFT) and time

Identification of Flood Reactivity Regions via the Functional Clustering of Hydrographs

Science.gov (United States)

Brunner, Manuela I.; Viviroli, Daniel; Furrer, Reinhard; Seibert, Jan; Favre, Anne-Catherine

2018-03-01

Flood hydrograph shapes contain valuable information on the flood-generation mechanisms of a catchment. To make good use of this information, we express flood hydrograph shapes as continuous functions using a functional data approach. We propose a clustering approach based on functional data for flood hydrograph shapes to identify a set of representative hydrograph shapes on a catchment scale and use these catchment-specific sets of representative hydrographs to establish regions of catchments with similar flood reactivity on a regional scale. We applied this approach to flood samples of 163 medium-size Swiss catchments. The results indicate that three representative hydrograph shapes sufficiently describe the hydrograph shape variability within a catchment and therefore can be used as a proxy for the flood behavior of a catchment. These catchment-specific sets of three hydrographs were used to group the catchments into three reactivity regions of similar flood behavior. These regions were not only characterized by similar hydrograph shapes and reactivity but also by event magnitudes and triggering event conditions. We envision these regions to be useful in regionalization studies, regional flood frequency analyses, and to allow for the construction of synthetic design hydrographs in ungauged catchments. The clustering approach based on functional data which establish these regions is very flexible and has the potential to be extended to other geographical regions or toward the use in climate impact studies.

Phytochemicals perturb membranes and promiscuously alter protein function.

Science.gov (United States)

Ingólfsson, Helgi I; Thakur, Pratima; Herold, Karl F; Hobart, E Ashley; Ramsey, Nicole B; Periole, Xavier; de Jong, Djurre H; Zwama, Martijn; Yilmaz, Duygu; Hall, Katherine; Maretzky, Thorsten; Hemmings, Hugh C; Blobel, Carl; Marrink, Siewert J; Koçer, Armağan; Sack, Jon T; Andersen, Olaf S

2014-08-15

A wide variety of phytochemicals are consumed for their perceived health benefits. Many of these phytochemicals have been found to alter numerous cell functions, but the mechanisms underlying their biological activity tend to be poorly understood. Phenolic phytochemicals are particularly promiscuous modifiers of membrane protein function, suggesting that some of their actions may be due to a common, membrane bilayer-mediated mechanism. To test whether bilayer perturbation may underlie this diversity of actions, we examined five bioactive phenols reported to have medicinal value: capsaicin from chili peppers, curcumin from turmeric, EGCG from green tea, genistein from soybeans, and resveratrol from grapes. We find that each of these widely consumed phytochemicals alters lipid bilayer properties and the function of diverse membrane proteins. Molecular dynamics simulations show that these phytochemicals modify bilayer properties by localizing to the bilayer/solution interface. Bilayer-modifying propensity was verified using a gramicidin-based assay, and indiscriminate modulation of membrane protein function was demonstrated using four proteins: membrane-anchored metalloproteases, mechanosensitive ion channels, and voltage-dependent potassium and sodium channels. Each protein exhibited similar responses to multiple phytochemicals, consistent with a common, bilayer-mediated mechanism. Our results suggest that many effects of amphiphilic phytochemicals are due to cell membrane perturbations, rather than specific protein binding.

Guided basin-hopping search of small boron clusters with density functional theory

Energy Technology Data Exchange (ETDEWEB)

Ng, Wei Chun; Yoon, Tiem Leong [School of Physics, Universiti Sains Malaysia, 11800 USM, Penang (Malaysia); Lim, Thong Leng [Faculty of Engineering and Technology, Multimedia University, Melacca Campus, 75450 Melaka (Malaysia)

2015-04-24

The search for the ground state structures of Boron clusters has been a difficult computational task due to the unique metalloid nature of Boron atom. Previous research works had overcome the problem in the search of the Boron ground-state structures by adding symmetry constraints prior to the process of locating the local minima in the potential energy surface (PES) of the Boron clusters. In this work, we shown that, with the deployment of a novel computational approach that incorporates density functional theory (DFT) into a guided global optimization search algorithm based on basin-hopping, it is possible to directly locate the local minima of small Boron clusters in the PES at the DFT level. The ground-state structures search algorithm as proposed in this work is initiated randomly and needs not a priori symmetry constraint artificially imposed throughout the search process. Small sized Boron clusters so obtained compare well to the results obtained by similar calculations in the literature. The electronic properties of each structures obtained are calculated within the DFT framework.

Guided basin-hopping search of small boron clusters with density functional theory

International Nuclear Information System (INIS)

Ng, Wei Chun; Yoon, Tiem Leong; Lim, Thong Leng

2015-01-01

The search for the ground state structures of Boron clusters has been a difficult computational task due to the unique metalloid nature of Boron atom. Previous research works had overcome the problem in the search of the Boron ground-state structures by adding symmetry constraints prior to the process of locating the local minima in the potential energy surface (PES) of the Boron clusters. In this work, we shown that, with the deployment of a novel computational approach that incorporates density functional theory (DFT) into a guided global optimization search algorithm based on basin-hopping, it is possible to directly locate the local minima of small Boron clusters in the PES at the DFT level. The ground-state structures search algorithm as proposed in this work is initiated randomly and needs not a priori symmetry constraint artificially imposed throughout the search process. Small sized Boron clusters so obtained compare well to the results obtained by similar calculations in the literature. The electronic properties of each structures obtained are calculated within the DFT framework

Evolution of the stellar mass function in multiple-population globular clusters

Science.gov (United States)

Vesperini, Enrico; Hong, Jongsuk; Webb, Jeremy J.; D'Antona, Franca; D'Ercole, Annibale

2018-05-01

We present the results of a survey of N-body simulations aimed at studying the effects of the long-term dynamical evolution on the stellar mass function (MF) of multiple stellar populations in globular clusters. Our simulations show that if first-(1G) and second-generation (2G) stars have the same initial MF (IMF), the global MFs of the two populations are affected similarly by dynamical evolution and no significant differences between the 1G and 2G MFs arise during the cluster's evolution. If the two populations have different IMFs, dynamical effects do not completely erase memory of the initial differences. Should observations find differences between the global 1G and 2G MFs, these would reveal the fingerprints of differences in their IMFs. Irrespective of whether the 1G and 2G populations have the same global IMF or not, dynamical effects can produce differences between the local (measured at various distances from the cluster centre) 1G and 2G MFs; these differences are a manifestation of the process of mass segregation in populations with different initial structural properties. In dynamically old and spatially mixed clusters, however, differences between the local 1G and 2G MFs can reveal differences between the 1G and 2G global MFs. In general, for clusters with any dynamical age, large differences between the local 1G and 2G MFs are more likely to be associated with differences in the global MF. Our study also reveals a dependence of the spatial mixing rate on the stellar mass, another dynamical consequence of the multiscale nature of multiple-population clusters.

DNA mimic proteins: functions, structures, and bioinformatic analysis.

Science.gov (United States)

Wang, Hao-Ching; Ho, Chun-Han; Hsu, Kai-Cheng; Yang, Jinn-Moon; Wang, Andrew H-J

2014-05-13

DNA mimic proteins have DNA-like negative surface charge distributions, and they function by occupying the DNA binding sites of DNA binding proteins to prevent these sites from being accessed by DNA. DNA mimic proteins control the activities of a variety of DNA binding proteins and are involved in a wide range of cellular mechanisms such as chromatin assembly, DNA repair, transcription regulation, and gene recombination. However, the sequences and structures of DNA mimic proteins are diverse, making them difficult to predict by bioinformatic search. To date, only a few DNA mimic proteins have been reported. These DNA mimics were not found by searching for functional motifs in their sequences but were revealed only by structural analysis of their charge distribution. This review highlights the biological roles and structures of 16 reported DNA mimic proteins. We also discuss approaches that might be used to discover new DNA mimic proteins.

Iron-sulfur clusters as biological sensors: the chemistry of reactions with molecular oxygen and nitric oxide.

Science.gov (United States)

Crack, Jason C; Green, Jeffrey; Thomson, Andrew J; Le Brun, Nick E

2014-10-21

Iron-sulfur cluster proteins exhibit a range of physicochemical properties that underpin their functional diversity in biology, which includes roles in electron transfer, catalysis, and gene regulation. Transcriptional regulators that utilize iron-sulfur clusters are a growing group that exploit the redox and coordination properties of the clusters to act as sensors of environmental conditions including O2, oxidative and nitrosative stress, and metabolic nutritional status. To understand the mechanism by which a cluster detects such analytes and then generates modulation of DNA-binding affinity, we have undertaken a combined strategy of in vivo and in vitro studies of a range of regulators. In vitro studies of iron-sulfur cluster proteins are particularly challenging because of the inherent reactivity and fragility of the cluster, often necessitating strict anaerobic conditions for all manipulations. Nevertheless, and as discussed in this Account, significant progress has been made over the past decade in studies of O2-sensing by the fumarate and nitrate reduction (FNR) regulator and, more recently, nitric oxide (NO)-sensing by WhiB-like (Wbl) and FNR proteins. Escherichia coli FNR binds a [4Fe-4S] cluster under anaerobic conditions leading to a DNA-binding dimeric form. Exposure to O2 converts the cluster to a [2Fe-2S] form, leading to protein monomerization and hence loss of DNA binding ability. Spectroscopic and kinetic studies have shown that the conversion proceeds via at least two steps and involves a [3Fe-4S](1+) intermediate. The second step involves the release of two bridging sulfide ions from the cluster that, unusually, are not released into solution but rather undergo oxidation to sulfane (S(0)) subsequently forming cysteine persulfides that then coordinate the [2Fe-2S] cluster. Studies of other [4Fe-4S] cluster proteins that undergo oxidative cluster conversion indicate that persulfide formation and coordination may be more common than previously

Detection of Locally Over-Represented GO Terms in Protein-Protein Interaction Networks

Science.gov (United States)

LAVALLÉE-ADAM, MATHIEU; COULOMBE, BENOIT; BLANCHETTE, MATHIEU

2015-01-01

High-throughput methods for identifying protein-protein interactions produce increasingly complex and intricate interaction networks. These networks are extremely rich in information, but extracting biologically meaningful hypotheses from them and representing them in a human-readable manner is challenging. We propose a method to identify Gene Ontology terms that are locally over-represented in a subnetwork of a given biological network. Specifically, we propose several methods to evaluate the degree of clustering of proteins associated to a particular GO term in both weighted and unweighted PPI networks, and describe efficient methods to estimate the statistical significance of the observed clustering. We show, using Monte Carlo simulations, that our best approximation methods accurately estimate the true p-value, for random scale-free graphs as well as for actual yeast and human networks. When applied to these two biological networks, our approach recovers many known complexes and pathways, but also suggests potential functions for many subnetworks. Online Supplementary Material is available at www.liebertonline.com. PMID:20377456

A density functional study of structures and stability of SinCN clusters

International Nuclear Information System (INIS)

Gai Zhigang; Yang Li; Zhao Jie; Chu Shibo

2011-01-01

In this paper, density functional theory (DFT) B3LYP method with 6-311G * basis set has been used to investigate geometric configurations, vibrational frequencies and ground state energies of Si n CN (n = 2 ∼ 6) clusters. The energies and spin multiplicities of ground states and substable states have been discussed, respectively. Harmonic frequencies and infrared spectra intensity for these clusters are given in order to aid in the characterization of the stable structures. The results show that the zero point energy (ZPE), thermocapacity and entropies are nearly in proportion to increased n, whose average enhancement are 0.80 kcal/mol, 5.20 cal/mol · K and 12.72 cal/ mol · K, respectively. The stability of Si n CN (n = 2 ∼ 6) clusters with even n are greater than that with odd n. (authors)

PRIMUS: Galaxy clustering as a function of luminosity and color at 0.2 < z < 1

Energy Technology Data Exchange (ETDEWEB)

Skibba, Ramin A.; Smith, M. Stephen M.; Coil, Alison L.; Mendez, Alexander J. [Department of Physics, Center for Astrophysics and Space Sciences, University of California, 9500 Gilman Drive, La Jolla, San Diego, CA 92093 (United States); Moustakas, John [Department of Physics and Astronomy, Siena College, 515 Loudon Road, Loudonville, NY 12211 (United States); Aird, James [Department of Physics, Durham University, Durham DH1 3LE (United Kingdom); Blanton, Michael R. [Center for Cosmology and Particle Physics, Department of Physics, New York University, 4 Washington Place, New York, NY 10003 (United States); Bray, Aaron D.; Eisenstein, Daniel J. [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Cool, Richard J. [MMT Observatory, 1540 E Second Street, University of Arizona, Tucson, AZ 85721 (United States); Wong, Kenneth C. [Steward Observatory, The University of Arizona, 933 North Cherry Avenue, Tucson, AZ 85721 (United States); Zhu, Guangtun, E-mail: rskibba@ucsd.edu [Department of Physics and Astronomy, Johns Hopkins University, 3400 North Charles Street, Baltimore, MD 21218 (United States)

2014-04-01

We present measurements of the luminosity and color-dependence of galaxy clustering at 0.2 < z < 1.0 in the Prism Multi-object Survey. We quantify the clustering with the redshift-space and projected two-point correlation functions, ξ(r{sub p} , π) and w{sub p} (r{sub p} ), using volume-limited samples constructed from a parent sample of over ∼130, 000 galaxies with robust redshifts in seven independent fields covering 9 deg{sup 2} of sky. We quantify how the scale-dependent clustering amplitude increases with increasing luminosity and redder color, with relatively small errors over large volumes. We find that red galaxies have stronger small-scale (0.1 Mpc h {sup –1} < r{sub p} < 1 Mpc h {sup –1}) clustering and steeper correlation functions compared to blue galaxies, as well as a strong color dependent clustering within the red sequence alone. We interpret our measured clustering trends in terms of galaxy bias and obtain values of b {sub gal} ≈ 0.9-2.5, quantifying how galaxies are biased tracers of dark matter depending on their luminosity and color. We also interpret the color dependence with mock catalogs, and find that the clustering of blue galaxies is nearly constant with color, while redder galaxies have stronger clustering in the one-halo term due to a higher satellite galaxy fraction. In addition, we measure the evolution of the clustering strength and bias, and we do not detect statistically significant departures from passive evolution. We argue that the luminosity- and color-environment (or halo mass) relations of galaxies have not significantly evolved since z ∼ 1. Finally, using jackknife subsampling methods, we find that sampling fluctuations are important and that the COSMOS field is generally an outlier, due to having more overdense structures than other fields; we find that 'cosmic variance' can be a significant source of uncertainty for high-redshift clustering measurements.

Architecture of the Yeast Mitochondrial Iron-Sulfur Cluster Assembly Machinery

Science.gov (United States)

Ranatunga, Wasantha; Gakh, Oleksandr; Galeano, Belinda K.; Smith, Douglas Y.; Söderberg, Christopher A. G.; Al-Karadaghi, Salam; Thompson, James R.; Isaya, Grazia

2016-01-01

The biosynthesis of Fe-S clusters is a vital process involving the delivery of elemental iron and sulfur to scaffold proteins via molecular interactions that are still poorly defined. We reconstituted a stable, functional complex consisting of the iron donor, Yfh1 (yeast frataxin homologue 1), and the Fe-S cluster scaffold, Isu1, with 1:1 stoichiometry, [Yfh1]24·[Isu1]24. Using negative staining transmission EM and single particle analysis, we obtained a three-dimensional reconstruction of this complex at a resolution of ∼17 Å. In addition, via chemical cross-linking, limited proteolysis, and mass spectrometry, we identified protein-protein interaction surfaces within the complex. The data together reveal that [Yfh1]24·[Isu1]24 is a roughly cubic macromolecule consisting of one symmetric Isu1 trimer binding on top of one symmetric Yfh1 trimer at each of its eight vertices. Furthermore, molecular modeling suggests that two subunits of the cysteine desulfurase, Nfs1, may bind symmetrically on top of two adjacent Isu1 trimers in a manner that creates two putative [2Fe-2S] cluster assembly centers. In each center, conserved amino acids known to be involved in sulfur and iron donation by Nfs1 and Yfh1, respectively, are in close proximity to the Fe-S cluster-coordinating residues of Isu1. We suggest that this architecture is suitable to ensure concerted and protected transfer of potentially toxic iron and sulfur atoms to Isu1 during Fe-S cluster assembly. PMID:26941001