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

International Nuclear Information System (INIS)

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

2017-01-01

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

Do protein crystals nucleate within dense liquid clusters?

International Nuclear Information System (INIS)

Maes, Dominique; Vorontsova, Maria A.; Potenza, Marco A. C.; Sanvito, Tiziano; Sleutel, Mike; Giglio, Marzio; Vekilov, Peter G.

2015-01-01

The evolution of protein-rich clusters and nucleating crystals were characterized by dynamic light scattering (DLS), confocal depolarized dynamic light scattering (cDDLS) and depolarized oblique illumination dark-field microscopy. Newly nucleated crystals within protein-rich clusters were detected directly. These observations indicate that the protein-rich clusters are locations for crystal nucleation. Protein-dense liquid clusters are regions of high protein concentration that have been observed in solutions of several proteins. The typical cluster size varies from several tens to several hundreds of nanometres and their volume fraction remains below 10 −3 of the solution. According to the two-step mechanism of nucleation, the protein-rich clusters serve as locations for and precursors to the nucleation of protein crystals. While the two-step mechanism explained several unusual features of protein crystal nucleation kinetics, a direct observation of its validity for protein crystals has been lacking. Here, two independent observations of crystal nucleation with the proteins lysozyme and glucose isomerase are discussed. Firstly, the evolutions of the protein-rich clusters and nucleating crystals were characterized simultaneously by dynamic light scattering (DLS) and confocal depolarized dynamic light scattering (cDDLS), respectively. It is demonstrated that protein crystals appear following a significant delay after cluster formation. The cDDLS correlation functions follow a Gaussian decay, indicative of nondiffusive motion. A possible explanation is that the crystals are contained inside large clusters and are driven by the elasticity of the cluster surface. Secondly, depolarized oblique illumination dark-field microscopy reveals the evolution from liquid clusters without crystals to newly nucleated crystals contained in the clusters to grown crystals freely diffusing in the solution. Collectively, the observations indicate that the protein-rich clusters in

Structure based alignment and clustering of proteins (STRALCP)

Science.gov (United States)

Zemla, Adam T.; Zhou, Carol E.; Smith, Jason R.; Lam, Marisa W.

2013-06-18

Disclosed are computational methods of clustering a set of protein structures based on local and pair-wise global similarity values. Pair-wise local and global similarity values are generated based on pair-wise structural alignments for each protein in the set of protein structures. Initially, the protein structures are clustered based on pair-wise local similarity values. The protein structures are then clustered based on pair-wise global similarity values. For each given cluster both a representative structure and spans of conserved residues are identified. The representative protein structure is used to assign newly-solved protein structures to a group. The spans are used to characterize conservation and assign a "structural footprint" to the cluster.

K-nearest uphill clustering in the protein structure space

KAUST Repository

Cui, Xuefeng

2016-08-26

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 protein structure classifications (e.g., SCOP and CATH) are very successful, but recently suffer the slow updating problem because of the increased throughput of newly solved protein structures. Thus, fully automatic methods to cluster proteins in the protein structure space have been designed and developed. In this study, we observed that the SCOP superfamilies are highly consistent with clustering trees representing hierarchical clustering procedures, but the tree cutting is very challenging and becomes the bottleneck of clustering accuracy. To overcome this challenge, we proposed a novel density-based K-nearest uphill clustering method that effectively eliminates noisy pairwise protein structure similarities and identifies density peaks as cluster centers. Specifically, the density peaks are identified based on K-nearest uphills (i.e., proteins with higher densities) and K-nearest neighbors. To our knowledge, this is the first attempt to apply and develop density-based clustering methods in the protein structure space. Our results show that our density-based clustering method outperforms the state-of-the-art clustering methods previously applied to the problem. Moreover, we observed that computational methods and human experts could produce highly similar clusters at high precision values, while computational methods also suggest to split some large superfamilies into smaller clusters. © 2016 Elsevier B.V.

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.

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

Science.gov (United States)

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

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...

Turning Escherichia coli into a Frataxin-Dependent Organism.

Directory of Open Access Journals (Sweden)

Béatrice Roche

2015-05-01

Full Text Available Fe-S bound proteins are ubiquitous and contribute to most basic cellular processes. A defect in the ISC components catalyzing Fe-S cluster biogenesis leads to drastic phenotypes in both eukaryotes and prokaryotes. In this context, the Frataxin protein (FXN stands out as an exception. In eukaryotes, a defect in FXN results in severe defects in Fe-S cluster biogenesis, and in humans, this is associated with Friedreich's ataxia, a neurodegenerative disease. In contrast, prokaryotes deficient in the FXN homolog CyaY are fully viable, despite the clear involvement of CyaY in ISC-catalyzed Fe-S cluster formation. The molecular basis of the differing importance in the contribution of FXN remains enigmatic. Here, we have demonstrated that a single mutation in the scaffold protein IscU rendered E. coli viability strictly dependent upon a functional CyaY. Remarkably, this mutation changed an Ile residue, conserved in prokaryotes at position 108, into a Met residue, conserved in eukaryotes. We found that in the double mutant IscUIM ΔcyaY, the ISC pathway was completely abolished, becoming equivalent to the ΔiscU deletion strain and recapitulating the drastic phenotype caused by FXN deletion in eukaryotes. Biochemical analyses of the "eukaryotic-like" IscUIM scaffold revealed that it exhibited a reduced capacity to form Fe-S clusters. Finally, bioinformatic studies of prokaryotic IscU proteins allowed us to trace back the source of FXN-dependency as it occurs in present-day eukaryotes. We propose an evolutionary scenario in which the current mitochondrial Isu proteins originated from the IscUIM version present in the ancestor of the Rickettsiae. Subsequent acquisition of SUF, the second Fe-S cluster biogenesis system, in bacteria, was accompanied by diminished contribution of CyaY in prokaryotic Fe-S cluster biogenesis, and increased tolerance to change in the amino acid present at the 108th position of the scaffold.

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

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

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

Science.gov (United States)

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.

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

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

Directory of Open Access Journals (Sweden)

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.

A hybrid clustering approach to recognition of protein families in 114 microbial genomes

Directory of Open Access Journals (Sweden)

Gogarten J Peter

2004-04-01

Full Text Available Abstract Background Grouping proteins into sequence-based clusters is a fundamental step in many bioinformatic analyses (e.g., homology-based prediction of structure or function. Standard clustering methods such as single-linkage clustering capture a history of cluster topologies as a function of threshold, but in practice their usefulness is limited because unrelated sequences join clusters before biologically meaningful families are fully constituted, e.g. as the result of matches to so-called promiscuous domains. Use of the Markov Cluster algorithm avoids this non-specificity, but does not preserve topological or threshold information about protein families. Results We describe a hybrid approach to sequence-based clustering of proteins that combines the advantages of standard and Markov clustering. We have implemented this hybrid approach over a relational database environment, and describe its application to clustering a large subset of PDB, and to 328577 proteins from 114 fully sequenced microbial genomes. To demonstrate utility with difficult problems, we show that hybrid clustering allows us to constitute the paralogous family of ATP synthase F1 rotary motor subunits into a single, biologically interpretable hierarchical grouping that was not accessible using either single-linkage or Markov clustering alone. We describe validation of this method by hybrid clustering of PDB and mapping SCOP families and domains onto the resulting clusters. Conclusion Hybrid (Markov followed by single-linkage clustering combines the advantages of the Markov Cluster algorithm (avoidance of non-specific clusters resulting from matches to promiscuous domains and single-linkage clustering (preservation of topological information as a function of threshold. Within the individual Markov clusters, single-linkage clustering is a more-precise instrument, discerning sub-clusters of biological relevance. Our hybrid approach thus provides a computationally efficient

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

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

Science.gov (United States)

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

2015-03-01

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

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

Directory of Open Access Journals (Sweden)

Can Tolga

2009-09-01

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

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.

Which clustering algorithm is better for predicting protein complexes?

Directory of Open Access Journals (Sweden)

Moschopoulos Charalampos N

2011-12-01

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

Clustering and visualizing similarity networks of membrane proteins.

Science.gov (United States)

Hu, Geng-Ming; Mai, Te-Lun; Chen, Chi-Ming

2015-08-01

We proposed a fast and unsupervised clustering method, minimum span clustering (MSC), for analyzing the sequence-structure-function relationship of biological networks, and demonstrated its validity in clustering the sequence/structure similarity networks (SSN) of 682 membrane protein (MP) chains. The MSC clustering of MPs based on their sequence information was found to be consistent with their tertiary structures and functions. For the largest seven clusters predicted by MSC, the consistency in chain function within the same cluster is found to be 100%. From analyzing the edge distribution of SSN for MPs, we found a characteristic threshold distance for the boundary between clusters, over which SSN of MPs could be properly clustered by an unsupervised sparsification of the network distance matrix. The clustering results of MPs from both MSC and the unsupervised sparsification methods are consistent with each other, and have high intracluster similarity and low intercluster similarity in sequence, structure, and function. Our study showed a strong sequence-structure-function relationship of MPs. We discussed evidence of convergent evolution of MPs and suggested applications in finding structural similarities and predicting biological functions of MP chains based on their sequence information. © 2015 Wiley Periodicals, Inc.

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...

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...

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 ...

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

Science.gov (United States)

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.

Self Organizing Maps to efficiently cluster and functionally interpret protein conformational ensembles

Directory of Open Access Journals (Sweden)

Fabio Stella

2013-09-01

Full Text Available An approach that combines Self-Organizing maps, hierarchical clustering and network components is presented, aimed at comparing protein conformational ensembles obtained from multiple Molecular Dynamic simulations. As a first result the original ensembles can be summarized by using only the representative conformations of the clusters obtained. In addition the network components analysis allows to discover and interpret the dynamic behavior of the conformations won by each neuron. The results showed the ability of this approach to efficiently derive a functional interpretation of the protein dynamics described by the original conformational ensemble, highlighting its potential as a support for protein engineering.

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.

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.

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.

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.

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

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

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.

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.

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

Science.gov (United States)

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.

Automatic extraction of gene ontology annotation and its correlation with clusters in protein networks

Directory of Open Access Journals (Sweden)

Mazo Ilya

2007-07-01

Full Text Available Abstract Background Uncovering cellular roles of a protein is a task of tremendous importance and complexity that requires dedicated experimental work as well as often sophisticated data mining and processing tools. Protein functions, often referred to as its annotations, are believed to manifest themselves through topology of the networks of inter-proteins interactions. In particular, there is a growing body of evidence that proteins performing the same function are more likely to interact with each other than with proteins with other functions. However, since functional annotation and protein network topology are often studied separately, the direct relationship between them has not been comprehensively demonstrated. In addition to having the general biological significance, such demonstration would further validate the data extraction and processing methods used to compose protein annotation and protein-protein interactions datasets. Results We developed a method for automatic extraction of protein functional annotation from scientific text based on the Natural Language Processing (NLP technology. For the protein annotation extracted from the entire PubMed, we evaluated the precision and recall rates, and compared the performance of the automatic extraction technology to that of manual curation used in public Gene Ontology (GO annotation. In the second part of our presentation, we reported a large-scale investigation into the correspondence between communities in the literature-based protein networks and GO annotation groups of functionally related proteins. We found a comprehensive two-way match: proteins within biological annotation groups form significantly denser linked network clusters than expected by chance and, conversely, densely linked network communities exhibit a pronounced non-random overlap with GO groups. We also expanded the publicly available GO biological process annotation using the relations extracted by our NLP technology

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/).

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.

Structural fragment clustering reveals novel structural and functional motifs in α-helical transmembrane proteins

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Vassilev Boris

2010-04-01

Full Text Available Abstract Background A large proportion of an organism's genome encodes for membrane proteins. Membrane proteins are important for many cellular processes, and several diseases can be linked to mutations in them. With the tremendous growth of sequence data, there is an increasing need to reliably identify membrane proteins from sequence, to functionally annotate them, and to correctly predict their topology. Results We introduce a technique called structural fragment clustering, which learns sequential motifs from 3D structural fragments. From over 500,000 fragments, we obtain 213 statistically significant, non-redundant, and novel motifs that are highly specific to α-helical transmembrane proteins. From these 213 motifs, 58 of them were assigned to function and checked in the scientific literature for a biological assessment. Seventy percent of the motifs are found in co-factor, ligand, and ion binding sites, 30% at protein interaction interfaces, and 12% bind specific lipids such as glycerol or cardiolipins. The vast majority of motifs (94% appear across evolutionarily unrelated families, highlighting the modularity of functional design in membrane proteins. We describe three novel motifs in detail: (1 a dimer interface motif found in voltage-gated chloride channels, (2 a proton transfer motif found in heme-copper oxidases, and (3 a convergently evolved interface helix motif found in an aspartate symporter, a serine protease, and cytochrome b. Conclusions Our findings suggest that functional modules exist in membrane proteins, and that they occur in completely different evolutionary contexts and cover different binding sites. Structural fragment clustering allows us to link sequence motifs to function through clusters of structural fragments. The sequence motifs can be applied to identify and characterize membrane proteins in novel genomes.

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...

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

Science.gov (United States)

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

Directory of Open Access Journals (Sweden)

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/.

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

Directory of Open Access Journals (Sweden)

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.

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.

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

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.

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

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....

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

Science.gov (United States)

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.

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

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

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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.

Analysis of NFU-1 metallocofactor binding-site substitutions-impacts on iron-sulfur cluster coordination and protein structure and function.

Science.gov (United States)

Wesley, Nathaniel A; Wachnowsky, Christine; Fidai, Insiya; Cowan, J A

2017-11-01

Iron-sulfur (Fe/S) clusters are ancient prosthetic groups found in numerous metalloproteins and are conserved across all kingdoms of life due to their diverse, yet essential functional roles. Genetic mutations to a specific subset of mitochondrial Fe/S cluster delivery proteins are broadly categorized as disease-related under multiple mitochondrial dysfunction syndrome (MMDS), with symptoms indicative of a general failure of the metabolic system. Multiple mitochondrial dysfunction syndrome 1 (MMDS1) arises as a result of the missense mutation in NFU1, an Fe/S cluster scaffold protein, which substitutes a glycine near the Fe/S cluster-binding pocket to a cysteine (p.Gly208Cys). This substitution has been shown to promote protein dimerization such that cluster delivery to NFU1 is blocked, preventing downstream cluster trafficking. However, the possibility of this additional cysteine, located adjacent to the cluster-binding site, serving as an Fe/S cluster ligand has not yet been explored. To fully understand the consequences of this Gly208Cys replacement, complementary substitutions at the Fe/S cluster-binding pocket for native and Gly208Cys NFU1 were made, along with six other variants. Herein, we report the results of an investigation on the effect of these substitutions on both cluster coordination and NFU1 structure and function. The data suggest that the G208C substitution does not contribute to cluster binding. Rather, replacement of the glycine at position 208 changes the oligomerization state as a result of global structural alterations that result in the downstream effects manifest as MMDS1, but does not perturb the coordination chemistry of the Fe-S cluster. © 2017 Federation of European Biochemical Societies.

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

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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.

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

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.

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

Science.gov (United States)

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).

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...

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

Directory of Open Access Journals (Sweden)

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

Distinct functional domains within the acidic cluster of tegument protein pp28 required for trafficking and cytoplasmic envelopment of human cytomegalovirus.

Science.gov (United States)

Seo, Jun-Young; Jeon, Hyejin; Hong, Sookyung; Britt, William J

2016-10-01

Human cytomegalovirus UL99-encoded tegument protein pp28 contains a 16 aa acidic cluster that is required for pp28 trafficking to the assembly compartment (AC) and the virus assembly. However, functional signals within the acidic cluster of pp28 remain undefined. Here, we demonstrated that an acidic cluster rather than specific sorting signals was required for trafficking to the AC. Recombinant viruses with chimeric pp28 proteins expressing non-native acidic clusters exhibited delayed viral growth kinetics and decreased production of infectious virus, indicating that the native acidic cluster of pp28 was essential for wild-type virus assembly. These results suggested that the acidic cluster of pp28 has distinct functional domains required for trafficking and for efficient virus assembly. The first half (aa 44-50) of the acidic cluster was sufficient for pp28 trafficking, whereas the native acidic cluster consisting of aa 51-59 was required for the assembly of wild-type levels of infectious virus.

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

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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.

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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 unique fold and lability of the [2Fe-2S] clusters of NEET proteins mediate their key functions in health and disease.

Science.gov (United States)

Karmi, Ola; Marjault, Henri-Baptiste; Pesce, Luca; Carloni, Paolo; Onuchic, Jose' N; Jennings, Patricia A; Mittler, Ron; Nechushtai, Rachel

2018-02-12

NEET proteins comprise a new class of [2Fe-2S] cluster proteins. In human, three genes encode for NEET proteins: cisd1 encodes mitoNEET (mNT), cisd2 encodes the Nutrient-deprivation autophagy factor-1 (NAF-1) and cisd3 encodes MiNT (Miner2). These recently discovered proteins play key roles in many processes related to normal metabolism and disease. Indeed, NEET proteins are involved in iron, Fe-S, and reactive oxygen homeostasis in cells and play an important role in regulating apoptosis and autophagy. mNT and NAF-1 are homodimeric and reside on the outer mitochondrial membrane. NAF-1 also resides in the membranes of the ER associated mitochondrial membranes (MAM) and the ER. MiNT is a monomer with distinct asymmetry in the molecular surfaces surrounding the clusters. Unlike its paralogs mNT and NAF-1, it resides within the mitochondria. NAF-1 and mNT share similar backbone folds to the plant homodimeric NEET protein (At-NEET), while MiNT's backbone fold resembles a bacterial MiNT protein. Despite the variation of amino acid composition among these proteins, all NEET proteins retained their unique CDGSH domain harboring their unique 3Cys:1His [2Fe-2S] cluster coordination through evolution. The coordinating exposed His was shown to convey the lability to the NEET proteins' [2Fe-2S] clusters. In this minireview, we discuss the NEET fold and its structural elements. Special attention is given to the unique lability of the NEETs' [2Fe-2S] cluster and the implication of the latter to the NEET proteins' cellular and systemic function in health and disease.

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...

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

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

Science.gov (United States)

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.

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.

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

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

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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

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

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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

Association of papillomavirus E6 proteins with either MAML1 or E6AP clusters E6 proteins by structure, function, and evolutionary relatedness.

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Nicole Brimer

2017-12-01

Full Text Available Papillomavirus E6 proteins bind to LXXLL peptide motifs displayed on targeted cellular proteins. Alpha genus HPV E6 proteins associate with the cellular ubiquitin ligase E6AP (UBE3A, by binding to an LXXLL peptide (ELTLQELLGEE displayed by E6AP, thereby stimulating E6AP ubiquitin ligase activity. Beta, Gamma, and Delta genera E6 proteins bind a similar LXXLL peptide (WMSDLDDLLGS on the cellular transcriptional co-activator MAML1 and thereby repress Notch signaling. We expressed 45 different animal and human E6 proteins from diverse papillomavirus genera to ascertain the overall preference of E6 proteins for E6AP or MAML1. E6 proteins from all HPV genera except Alpha preferentially interacted with MAML1 over E6AP. Among animal papillomaviruses, E6 proteins from certain ungulate (SsPV1 from pigs and cetacean (porpoises and dolphins hosts functionally resembled Alpha genus HPV by binding and targeting the degradation of E6AP. Beta genus HPV E6 proteins functionally clustered with Delta, Pi, Tau, Gamma, Chi, Mu, Lambda, Iota, Dyokappa, Rho, and Dyolambda E6 proteins to bind and repress MAML1. None of the tested E6 proteins physically and functionally interacted with both MAML1 and E6AP, indicating an evolutionary split. Further, interaction of an E6 protein was insufficient to activate degradation of E6AP, indicating that E6 proteins that target E6AP co-evolved to separately acquire both binding and triggering of ubiquitin ligase activation. E6 proteins with similar biological function clustered together in phylogenetic trees and shared structural features. This suggests that the divergence of E6 proteins from either MAML1 or E6AP binding preference is a major event in papillomavirus evolution.

Fluorescence detection of a protein-bound 2Fe2S cluster.

Science.gov (United States)

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.

From Lipid Homeostasis to Differentiation: Old and New Functions of the Zinc Cluster Proteins Ecm22, Upc2, Sut1 and Sut2

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Ifeoluwapo Matthew Joshua

2017-04-01

Full Text Available Zinc cluster proteins are a large family of transcriptional regulators with a wide range of biological functions. The zinc cluster proteins Ecm22, Upc2, Sut1 and Sut2 have initially been identified as regulators of sterol import in the budding yeast Saccharomyces cerevisiae. These proteins also control adaptations to anaerobic growth, sterol biosynthesis as well as filamentation and mating. Orthologs of these zinc cluster proteins have been identified in several species of Candida. Upc2 plays a critical role in antifungal resistance in these important human fungal pathogens. Upc2 is therefore an interesting potential target for novel antifungals. In this review we discuss the functions, mode of actions and regulation of Ecm22, Upc2, Sut1 and Sut2 in budding yeast and Candida.

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.

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 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.

An Atlas of Peroxiredoxins Created Using an Active Site Profile-Based Approach to Functionally Relevant Clustering of Proteins.

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Angela F Harper

2017-02-01

Full Text Available Peroxiredoxins (Prxs or Prdxs are a large protein superfamily of antioxidant enzymes that rapidly detoxify damaging peroxides and/or affect signal transduction and, thus, have roles in proliferation, differentiation, and apoptosis. Prx superfamily members are widespread across phylogeny and multiple methods have been developed to classify them. Here we present an updated atlas of the Prx superfamily identified using a novel method called MISST (Multi-level Iterative Sequence Searching Technique. MISST is an iterative search process developed to be both agglomerative, to add sequences containing similar functional site features, and divisive, to split groups when functional site features suggest distinct functionally-relevant clusters. Superfamily members need not be identified initially-MISST begins with a minimal representative set of known structures and searches GenBank iteratively. Further, the method's novelty lies in the manner in which isofunctional groups are selected; rather than use a single or shifting threshold to identify clusters, the groups are deemed isofunctional when they pass a self-identification criterion, such that the group identifies itself and nothing else in a search of GenBank. The method was preliminarily validated on the Prxs, as the Prxs presented challenges of both agglomeration and division. For example, previous sequence analysis clustered the Prx functional families Prx1 and Prx6 into one group. Subsequent expert analysis clearly identified Prx6 as a distinct functionally relevant group. The MISST process distinguishes these two closely related, though functionally distinct, families. Through MISST search iterations, over 38,000 Prx sequences were identified, which the method divided into six isofunctional clusters, consistent with previous expert analysis. The results represent the most complete computational functional analysis of proteins comprising the Prx superfamily. The feasibility of this novel method is

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

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.

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.

UET: a database of evolutionarily-predicted functional determinants of protein sequences that cluster as functional sites in protein structures.

Science.gov (United States)

Lua, Rhonald C; Wilson, Stephen J; Konecki, Daniel M; Wilkins, Angela D; Venner, Eric; Morgan, Daniel H; Lichtarge, Olivier

2016-01-04

The structure and function of proteins underlie most aspects of biology and their mutational perturbations often cause disease. To identify the molecular determinants of function as well as targets for drugs, it is central to characterize the important residues and how they cluster to form functional sites. The Evolutionary Trace (ET) achieves this by ranking the functional and structural importance of the protein sequence positions. ET uses evolutionary distances to estimate functional distances and correlates genotype variations with those in the fitness phenotype. Thus, ET ranks are worse for sequence positions that vary among evolutionarily closer homologs but better for positions that vary mostly among distant homologs. This approach identifies functional determinants, predicts function, guides the mutational redesign of functional and allosteric specificity, and interprets the action of coding sequence variations in proteins, people and populations. Now, the UET database offers pre-computed ET analyses for the protein structure databank, and on-the-fly analysis of any protein sequence. A web interface retrieves ET rankings of sequence positions and maps results to a structure to identify functionally important regions. This UET database integrates several ways of viewing the results on the protein sequence or structure and can be found at http://mammoth.bcm.tmc.edu/uet/. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

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.

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...

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

Science.gov (United States)

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.

Functional Complementation Studies Reveal Different Interaction Partners of Escherichia coli IscS and Human NFS1.

Science.gov (United States)

Bühning, Martin; Friemel, Martin; Leimkühler, Silke

2017-08-29

The trafficking and delivery of sulfur to cofactors and nucleosides is a highly regulated and conserved process among all organisms. All sulfur transfer pathways generally have an l-cysteine desulfurase as an initial sulfur-mobilizing enzyme in common, which serves as a sulfur donor for the biosynthesis of sulfur-containing biomolecules like iron-sulfur (Fe-S) clusters, thiamine, biotin, lipoic acid, the molybdenum cofactor (Moco), and thiolated nucleosides in tRNA. The human l-cysteine desulfurase NFS1 and the Escherichia coli homologue IscS share a level of amino acid sequence identity of ∼60%. While E. coli IscS has a versatile role in the cell and was shown to have numerous interaction partners, NFS1 is mainly localized in mitochondria with a crucial role in the biosynthesis of Fe-S clusters. Additionally, NFS1 is also located in smaller amounts in the cytosol with a role in Moco biosynthesis and mcm 5 s 2 U34 thio modifications of nucleosides in tRNA. NFS1 and IscS were conclusively shown to have different interaction partners in their respective organisms. Here, we used functional complementation studies of an E. coli iscS deletion strain with human NFS1 to dissect their conserved roles in the transfer of sulfur to a specific target protein. Our results show that human NFS1 and E. coli IscS share conserved binding sites for proteins involved in Fe-S cluster assembly like IscU, but not with proteins for tRNA thio modifications or Moco biosynthesis. In addition, we show that human NFS1 was almost fully able to complement the role of IscS in Moco biosynthesis when its specific interaction partner protein MOCS3 from humans was also present.

Clustering of double strand break-containing chromosome domains is not inhibited by inactivation of major repair proteins

International Nuclear Information System (INIS)

Krawczyk, P. M.; Stap, C.; Van Oven, C.; Hoebe, R.; Aten, J. A.

2006-01-01

For efficient repair of DNA double strand breaks (DSBs) cells rely on a process that involves the Mre11/Rad50/Nbs1 complex, which may help to protect non-repaired DNA ends from separating until they can be rejoined by DNA repair proteins. It has been observed that as a secondary effect, this process can lead to unintended clustering of multiple, initially separate, DSB-containing chromosome domains. This work demonstrates that neither inactivation of the major repair proteins XRCC3 and the DNA-dependent protein kinase (DNA-PK) nor inhibition of DNA-PK by vanillin influences the aggregation of DSB-containing chromosome domains. (authors)

Cluster analysis of historical and modern hard red spring wheat cultivars based on parentage and HPLC analysis of gluten forming proteins

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In this study, 30 hard red spring (HRS) wheat cultivars released between 1910 and 2013 were analyzed to determine how they cluster in terms of parentage and protein data, analyzed by reverse-phase HPLC (RP-HPLC) of gliadins, and size-exclusion HPLC (SE-HPLC) of unreduced proteins. Dwarfing genes in...

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.

Cofactor-binding sites in proteins of deviating sequence: comparative analysis and clustering in torsion angle, cavity, and fold space.

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Stegemann, Björn; Klebe, Gerhard

2012-02-01

Small molecules are recognized in protein-binding pockets through surface-exposed physicochemical properties. To optimize binding, they have to adopt a conformation corresponding to a local energy minimum within the formed protein-ligand complex. However, their conformational flexibility makes them competent to bind not only to homologous proteins of the same family but also to proteins of remote similarity with respect to the shape of the binding pockets and folding pattern. Considering drug action, such observations can give rise to unexpected and undesired cross reactivity. In this study, datasets of six different cofactors (ADP, ATP, NAD(P)(H), FAD, and acetyl CoA, sharing an adenosine diphosphate moiety as common substructure), observed in multiple crystal structures of protein-cofactor complexes exhibiting sequence identity below 25%, have been analyzed for the conformational properties of the bound ligands, the distribution of physicochemical properties in the accommodating protein-binding pockets, and the local folding patterns next to the cofactor-binding site. State-of-the-art clustering techniques have been applied to group the different protein-cofactor complexes in the different spaces. Interestingly, clustering in cavity (Cavbase) and fold space (DALI) reveals virtually the same data structuring. Remarkable relationships can be found among the different spaces. They provide information on how conformations are conserved across the host proteins and which distinct local cavity and fold motifs recognize the different portions of the cofactors. In those cases, where different cofactors are found to be accommodated in a similar fashion to the same fold motifs, only a commonly shared substructure of the cofactors is used for the recognition process. Copyright © 2011 Wiley Periodicals, Inc.

Oligomeric protein structure networks: insights into protein-protein interactions

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Brinda KV

2005-12-01

Full Text Available Abstract Background Protein-protein association is essential for a variety of cellular processes and hence a large number of investigations are being carried out to understand the principles of protein-protein interactions. In this study, oligomeric protein structures are viewed from a network perspective to obtain new insights into protein association. Structure graphs of proteins have been constructed from a non-redundant set of protein oligomer crystal structures by considering amino acid residues as nodes and the edges are based on the strength of the non-covalent interactions between the residues. The analysis of such networks has been carried out in terms of amino acid clusters and hubs (highly connected residues with special emphasis to protein interfaces. Results A variety of interactions such as hydrogen bond, salt bridges, aromatic and hydrophobic interactions, which occur at the interfaces are identified in a consolidated manner as amino acid clusters at the interface, from this study. Moreover, the characterization of the highly connected hub-forming residues at the interfaces and their comparison with the hubs from the non-interface regions and the non-hubs in the interface regions show that there is a predominance of charged interactions at the interfaces. Further, strong and weak interfaces are identified on the basis of the interaction strength between amino acid residues and the sizes of the interface clusters, which also show that many protein interfaces are stronger than their monomeric protein cores. The interface strengths evaluated based on the interface clusters and hubs also correlate well with experimentally determined dissociation constants for known complexes. Finally, the interface hubs identified using the present method correlate very well with experimentally determined hotspots in the interfaces of protein complexes obtained from the Alanine Scanning Energetics database (ASEdb. A few predictions of interface hot

Fe-S Cluster Biogenesis in Isolated Mammalian Mitochondria

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Pandey, Alok; Pain, Jayashree; Ghosh, Arnab K.; Dancis, Andrew; Pain, Debkumar

2015-01-01

Iron-sulfur (Fe-S) clusters are essential cofactors, and mitochondria contain several Fe-S proteins, including the [4Fe-4S] protein aconitase and the [2Fe-2S] protein ferredoxin. Fe-S cluster assembly of these proteins occurs within mitochondria. Although considerable data exist for yeast mitochondria, this biosynthetic process has never been directly demonstrated in mammalian mitochondria. Using [35S]cysteine as the source of sulfur, here we show that mitochondria isolated from Cath.A-derived cells, a murine neuronal cell line, can synthesize and insert new Fe-35S clusters into aconitase and ferredoxins. The process requires GTP, NADH, ATP, and iron, and hydrolysis of both GTP and ATP is necessary. Importantly, we have identified the 35S-labeled persulfide on the NFS1 cysteine desulfurase as a genuine intermediate en route to Fe-S cluster synthesis. In physiological settings, the persulfide sulfur is released from NFS1 and transferred to a scaffold protein, where it combines with iron to form an Fe-S cluster intermediate. We found that the release of persulfide sulfur from NFS1 requires iron, showing that the use of iron and sulfur for the synthesis of Fe-S cluster intermediates is a highly coordinated process. The release of persulfide sulfur also requires GTP and NADH, probably mediated by a GTPase and a reductase, respectively. ATP, a cofactor for a multifunctional Hsp70 chaperone, is not required at this step. The experimental system described here may help to define the biochemical basis of diseases that are associated with impaired Fe-S cluster biogenesis in mitochondria, such as Friedreich ataxia. PMID:25398879

Integrative cluster analysis in bioinformatics

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Abu-Jamous, Basel; Nandi, Asoke K

2015-01-01

Clustering techniques are increasingly being put to use in the analysis of high-throughput biological datasets. Novel computational techniques to analyse high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. This book details the complete pathway of cluster analysis, from the basics of molecular biology to the generation of biological knowledge. The book also presents the latest clustering methods and clustering validation, thereby offering the reader a comprehensive review o

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

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Xiaomin Wang

2011-01-01

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

Validating clustering of molecular dynamics simulations using polymer models

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Phillips Joshua L

2011-11-01

Full Text Available Abstract Background Molecular dynamics (MD simulation is a powerful technique for sampling the meta-stable and transitional conformations of proteins and other biomolecules. Computational data clustering has emerged as a useful, automated technique for extracting conformational states from MD simulation data. Despite extensive application, relatively little work has been done to determine if the clustering algorithms are actually extracting useful information. A primary goal of this paper therefore is to provide such an understanding through a detailed analysis of data clustering applied to a series of increasingly complex biopolymer models. Results We develop a novel series of models using basic polymer theory that have intuitive, clearly-defined dynamics and exhibit the essential properties that we are seeking to identify in MD simulations of real biomolecules. We then apply spectral clustering, an algorithm particularly well-suited for clustering polymer structures, to our models and MD simulations of several intrinsically disordered proteins. Clustering results for the polymer models provide clear evidence that the meta-stable and transitional conformations are detected by the algorithm. The results for the polymer models also help guide the analysis of the disordered protein simulations by comparing and contrasting the statistical properties of the extracted clusters. Conclusions We have developed a framework for validating the performance and utility of clustering algorithms for studying molecular biopolymer simulations that utilizes several analytic and dynamic polymer models which exhibit well-behaved dynamics including: meta-stable states, transition states, helical structures, and stochastic dynamics. We show that spectral clustering is robust to anomalies introduced by structural alignment and that different structural classes of intrinsically disordered proteins can be reliably discriminated from the clustering results. To our

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.

Robust continuous clustering.

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Shah, Sohil Atul; Koltun, Vladlen

2017-09-12

Clustering is a fundamental procedure in the analysis of scientific data. It is used ubiquitously across the sciences. Despite decades of research, existing clustering algorithms have limited effectiveness in high dimensions and often require tuning parameters for different domains and datasets. We present a clustering algorithm that achieves high accuracy across multiple domains and scales efficiently to high dimensions and large datasets. The presented algorithm optimizes a smooth continuous objective, which is based on robust statistics and allows heavily mixed clusters to be untangled. The continuous nature of the objective also allows clustering to be integrated as a module in end-to-end feature learning pipelines. We demonstrate this by extending the algorithm to perform joint clustering and dimensionality reduction by efficiently optimizing a continuous global objective. The presented approach is evaluated on large datasets of faces, hand-written digits, objects, newswire articles, sensor readings from the Space Shuttle, and protein expression levels. Our method achieves high accuracy across all datasets, outperforming the best prior algorithm by a factor of 3 in average rank.

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.

Finding local communities in protein networks.

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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

[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.

Clustering structures of large proteins using multifractal analyses based on a 6-letter model and hydrophobicity scale of amino acids

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Yang Jianyi; Yu Zuguo; Anh, Vo

2009-01-01

The Schneider and Wrede hydrophobicity scale of amino acids and the 6-letter model of protein are proposed to study the relationship between the primary structure and the secondary structural classification of proteins. Two kinds of multifractal analyses are performed on the two measures obtained from these two kinds of data on large proteins. Nine parameters from the multifractal analyses are considered to construct the parameter spaces. Each protein is represented by one point in these spaces. A procedure is proposed to separate large proteins in the α, β, α + β and α/β structural classes in these parameter spaces. Fisher's linear discriminant algorithm is used to assess our clustering accuracy on the 49 selected large proteins. Numerical results indicate that the discriminant accuracies are satisfactory. In particular, they reach 100.00% and 84.21% in separating the α proteins from the {β, α + β, α/β} proteins in a parameter space; 92.86% and 86.96% in separating the β proteins from the {α + β, α/β} proteins in another parameter space; 91.67% and 83.33% in separating the α/β proteins from the α + β proteins in the last parameter space.

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.

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

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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.

A VTVH MCD and EPR Spectroscopic Study of the Maturation of the "Second" Nitrogenase P-Cluster.

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Rupnik, Kresimir; Lee, Chi Chung; Hu, Yilin; Ribbe, Markus W; Hales, Brian J

2018-04-16

The P-cluster of the nitrogenase MoFe protein is a [ Fe 8 S 7 ] cluster that mediates efficient transfer of electrons to the active site for substrate reduction. Arguably the most complex homometallic FeS cluster found in nature, the biosynthetic mechanism of the P-cluster is of considerable theoretical and synthetic interest to chemists and biochemists alike. Previous studies have revealed a biphasic assembly mechanism of the two P-clusters in the MoFe protein upon incubation with Fe protein and ATP, in which the first P-cluster is formed through fast fusion of a pair of [ Fe 4 S 4 ] + clusters within 5 min and the second P-cluster is formed through slow fusion of the second pair of [ Fe 4 S 4 ] + clusters in a period of 2 h. Here we report a VTVH MCD and EPR spectroscopic study of the biosynthesis of the slow-forming, second P-cluster within the MoFe protein. Our results show that the first major step in the formation of the second P-cluster is the conversion of one of the precursor [ Fe 4 S 4 ] + clusters into the integer spin cluster [ Fe 4 S 3-4 ] α , a process aided by the assembly protein NifZ, whereas the second major biosynthetic step appears to be the formation of a diamagnetic cluster with a possible structure of [ Fe 8 S 7-8 ] β , which is eventually converted into the P-cluster.

Site-Specific Biomolecule Labeling with Gold Clusters

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Ackerson, Christopher J.; Powell, Richard D.; Hainfeld, James F.

2013-01-01

Site-specific labeling of biomolecules in vitro with gold clusters can enhance the information content of electron cryomicroscopy experiments. This chapter provides a practical overview of well-established techniques for forming biomolecule/gold cluster conjugates. Three bioconjugation chemistries are covered: Linker-mediated bioconjugation, direct gold–biomolecule bonding, and coordination-mediated bonding of nickel(II) nitrilotriacetic acid (NTA)-derivatized gold clusters to polyhistidine (His)-tagged proteins. PMID:20887859

Noise reduction in protein-protein interaction graphs by the implementation of a novel weighting scheme

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Moschopoulos Charalampos

2011-06-01

Full Text Available Abstract Background Recent technological advances applied to biology such as yeast-two-hybrid, phage display and mass spectrometry have enabled us to create a detailed map of protein interaction networks. These interaction networks represent a rich, yet noisy, source of data that could be used to extract meaningful information, such as protein complexes. Several interaction network weighting schemes have been proposed so far in the literature in order to eliminate the noise inherent in interactome data. In this paper, we propose a novel weighting scheme and apply it to the S. cerevisiae interactome. Complex prediction rates are improved by up to 39%, depending on the clustering algorithm applied. Results We adopt a two step procedure. During the first step, by applying both novel and well established protein-protein interaction (PPI weighting methods, weights are introduced to the original interactome graph based on the confidence level that a given interaction is a true-positive one. The second step applies clustering using established algorithms in the field of graph theory, as well as two variations of Spectral clustering. The clustered interactome networks are also cross-validated against the confirmed protein complexes present in the MIPS database. Conclusions The results of our experimental work demonstrate that interactome graph weighting methods clearly improve the clustering results of several clustering algorithms. Moreover, our proposed weighting scheme outperforms other approaches of PPI graph weighting.

True Molecular Scale Visualization of Variable Clustering Properties of Ryanodine Receptors

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Isuru Jayasinghe

2018-01-01

Full Text Available Summary: Signaling nanodomains rely on spatial organization of proteins to allow controlled intracellular signaling. Examples include calcium release sites of cardiomyocytes where ryanodine receptors (RyRs are clustered with their molecular partners. Localization microscopy has been crucial to visualizing these nanodomains but has been limited by brightness of markers, restricting the resolution and quantification of individual proteins clustered within. Harnessing the remarkable localization precision of DNA-PAINT (<10 nm, we visualized punctate labeling within these nanodomains, confirmed as single RyRs. RyR positions within sub-plasmalemmal nanodomains revealed how they are organized randomly into irregular clustering patterns leaving significant gaps occupied by accessory or regulatory proteins. RyR-inhibiting protein junctophilin-2 appeared highly concentrated adjacent to RyR channels. Analyzing these molecular maps showed significant variations in the co-clustering stoichiometry between junctophilin-2 and RyR, even between nearby nanodomains. This constitutes an additional level of complexity in RyR arrangement and regulation of calcium signaling, intrinsically built into the nanodomains. : Jayasinghe et al. resolve the distribution of single ryanodine receptors (RyRs within intracellular signaling domains in cardiac myocytes with DNA-PAINT, a super-resolution microscopy approach. Individual RyRs are resolved within irregular cluster arrays. Quantitative imaging reveals significant variation in the co-clustering stoichiometry between RyRs and the regulatory protein junctophilin-2. Keywords: nanodomains, DNA-PAINT, single-molecule localization microscopy, ryanodine receptor, super-resolution imaging, junctophilin, heart

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

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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.

AutoSOME: a clustering method for identifying gene expression modules without prior knowledge of cluster number

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Cooper James B

2010-03-01

Full Text Available Abstract Background Clustering the information content of large high-dimensional gene expression datasets has widespread application in "omics" biology. Unfortunately, the underlying structure of these natural datasets is often fuzzy, and the computational identification of data clusters generally requires knowledge about cluster number and geometry. Results We integrated strategies from machine learning, cartography, and graph theory into a new informatics method for automatically clustering self-organizing map ensembles of high-dimensional data. Our new method, called AutoSOME, readily identifies discrete and fuzzy data clusters without prior knowledge of cluster number or structure in diverse datasets including whole genome microarray data. Visualization of AutoSOME output using network diagrams and differential heat maps reveals unexpected variation among well-characterized cancer cell lines. Co-expression analysis of data from human embryonic and induced pluripotent stem cells using AutoSOME identifies >3400 up-regulated genes associated with pluripotency, and indicates that a recently identified protein-protein interaction network characterizing pluripotency was underestimated by a factor of four. Conclusions By effectively extracting important information from high-dimensional microarray data without prior knowledge or the need for data filtration, AutoSOME can yield systems-level insights from whole genome microarray expression studies. Due to its generality, this new method should also have practical utility for a variety of data-intensive applications, including the results of deep sequencing experiments. AutoSOME is available for download at http://jimcooperlab.mcdb.ucsb.edu/autosome.

Analysis of hepatocellular carcinoma and metastatic hepatic carcinoma via functional modules in a protein-protein interaction network

Directory of Open Access Journals (Sweden)

Jun Pan

2014-01-01

Full Text Available Introduction: This study aims to identify protein clusters with potential functional relevance in the pathogenesis of hepatocellular carcinoma (HCC and metastatic hepatic carcinoma using network analysis. Materials and Methods: We used human protein interaction data to build a protein-protein interaction network with Cytoscape and then derived functional clusters using MCODE. Combining the gene expression profiles, we calculated the functional scores for the clusters and selected statistically significant clusters. Meanwhile, Gene Ontology was used to assess the functionality of these clusters. Finally, a support vector machine was trained on the gold standard data sets. Results: The differentially expressed genes of HCC were mainly involved in metabolic and signaling processes. We acquired 13 significant modules from the gene expression profiles. The area under the curve value based on the differentially expressed modules were 98.31%, which outweighed the classification with DEGs. Conclusions: Differentially expressed modules are valuable to screen biomarkers combined with functional modules.

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.

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

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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.

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.

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)

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

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 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

Proteomic properties reveal phyloecological clusters of Archaea.

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Nela Nikolic

Full Text Available In this study, we propose a novel way to describe the variety of environmental adaptations of Archaea. We have clustered 57 Archaea by using a non-redundant set of proteomic features, and verified that the clusters correspond to environmental adaptations to the archaeal habitats. The first cluster consists dominantly of hyperthermophiles and hyperthermoacidophilic aerobes. The second cluster joins together halophilic and extremely halophilic Archaea, while the third cluster contains mesophilic (mostly methanogenic Archaea together with thermoacidophiles. The non-redundant subset of proteomic features was found to consist of five features: the ratio of charged residues to uncharged, average protein size, normalized frequency of beta-sheet, normalized frequency of extended structure and number of hydrogen bond donors. We propose this clustering to be termed phyloecological clustering. This approach could give additional insights into relationships among archaeal species that may be hidden by sole phylogenetic analysis.

Chinese mitten crab (Eriocheir sinensis) iron-sulphur cluster assembly protein 2 (EsIscA2) is differentially regulated after immune and oxidative stress challenges.

Science.gov (United States)

Zhang, Peng; Liu, Yu; Wang, Min; Dong, Miren; Liu, Zhaoqun; Jia, Zhihao; Wang, Weilin; Zhang, Anguo; Wang, Lingling; Song, Linsheng

2018-07-01

Iron-sulphur clusters (ISCs), one of the oldest and most versatile cofactors of proteins, are involved in catalysis reactions, electron transport reactions, regulation processes as well as sensing of ambient conditions. Iron-sulphur cluster assembly protein (IscA) is a scaffold protein member of ISC formation system, which plays a significant role in the assembly and maturation process of ISC proteins. In the present study, the cDNA sequence of iron-sulphur cluster assembly protein 2 (designated as EsIscA2) was cloned from Eriocheir sinensis. The open reading frame (ORF) of EsIscA2 was of 507 bp, encoding a peptide of 168 amino acids with a typically conserved Fe-S domain. A tetrameric form was predicated by the SWISS-MODEL prediction algorithm, and three conserved cysteine residues (Cys-93, Cys-158, Cys-160) from each IscA monomer were predicted to form a 'cysteine pocket'. The deduced amino acid sequence of EsIscA2 shared over 50% similarity with that of other IscAs. EsIscA2 was clustered with IscA2 proteins from invertebrates and vertebrates, indicating that the protein was highly conservative in the evolution. rEsIscA2 exhibited a high iron binding affinity in the concentration ranging from 2 to 200 μM. EsIscA2 transcripts were detected in all the tested tissues including gonad, hemocytes, gill, muscle, heart, hepatopancreas and eyestalk, and EsIscA2 protein was detected in the mitochondria of hemocytes. The highest mRNA expression level of EsIscA2 was detected in muscle and hepatopancreas, which was about 34.66-fold (p < 0.05) and 27.07-fold (p < 0.05) of that in hemocytes, respectively. After Aeromonas hydrophila and lipopolysaccharide (LPS) stimulations, the mRNA expression of EsIscA2 in hemocytes was down-regulated and reached the lowest level at 24 h (0.31-fold, p < 0.05) and 48 h (0.29-fold, p < 0.05) compared to control group, respectively. And the expression of EsIscA2 mRNA in hepatopancreas was repressed from 6 h to 48 h post

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

Science.gov (United States)

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.

Network Analysis Tools: from biological networks to clusters and pathways.

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Brohée, Sylvain; Faust, Karoline; Lima-Mendez, Gipsi; Vanderstocken, Gilles; van Helden, Jacques

2008-01-01

Network Analysis Tools (NeAT) is a suite of computer tools that integrate various algorithms for the analysis of biological networks: comparison between graphs, between clusters, or between graphs and clusters; network randomization; analysis of degree distribution; network-based clustering and path finding. The tools are interconnected to enable a stepwise analysis of the network through a complete analytical workflow. In this protocol, we present a typical case of utilization, where the tasks above are combined to decipher a protein-protein interaction network retrieved from the STRING database. The results returned by NeAT are typically subnetworks, networks enriched with additional information (i.e., clusters or paths) or tables displaying statistics. Typical networks comprising several thousands of nodes and arcs can be analyzed within a few minutes. The complete protocol can be read and executed in approximately 1 h.

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.

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.

Statistical survey of the buried waters in the Protein Data Bank.

Science.gov (United States)

Carugo, Oliviero

2016-01-01

The structures of buried water molecules were studied in an ensemble of high-quality and non-redundant protein crystal structures. Buried water molecules were clustered and classified in lake-like clusters, which are completely isolated from the bulk solvent, and bay-like clusters, which are in contact with the bulk solvent through a surface water molecule. Buried water molecules are extremely common: lake-like clusters are found in 89 % of the protein crystal structures and bay-like clusters in 93 %. Clusters with only one water molecule are much more common than larger clusters. Both cluster types incline to be surrounded by loop residues, and to a minor extent by residues in extended secondary structure. Helical residues on the contrary do not tend to surround clusters of buried water molecules. One buried water molecule is found every 30-50 amino acid residues, depending on the secondary structures that are more abundant in the protein. Both main- and side-chain atoms are in contact with buried waters; they form four hydrogen bonds with the first water and 1-1.5 additional hydrogen bond for each additional water in the cluster. Consequently, buried water molecules appear to be firmly packed and rigid like the protein atoms. In this regard, it is remarkable to observe that prolines often surround water molecules buried in the protein interior. Interestingly, clusters of buried water molecules tend to be just beneath the protein surface. Moreover, water molecules tend to form a one-dimensional wire rather than more compact arrangements. This agrees with recent evidence of the mechanisms of solvent exchange between internal cavities and bulk solvent.

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

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

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.

Cluster (Viridiplantae) - PGDBj - Ortholog DB | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available 0”. This cluster ID is uniquely-assigned by the PGDBj Ortholog Database. Cluster size Number of proteins aff...r About This Database Database Description Download License Update History of This Database Site Policy | Contact Us Cluster (Viridiplantae) - PGDBj - Ortholog DB | LSDB Archive ... ...List Contact us PGDBj - Ortholog DB Cluster (Viridiplantae) Data detail Data name Cluster (Viridiplantae) DO...switchLanguage; BLAST Search Image Search Home About Archive Update History Data

Cluster (Cyanobacteria) - PGDBj - Ortholog DB | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available 3090”. This cluster ID is uniquely-assigned by the PGDBj Ortholog Database. Cluster size Number of proteins ...ster About This Database Database Description Download License Update History of This Database Site Policy | Contact Us Cluster (Cyanobacteria) - PGDBj - Ortholog DB | LSDB Archive ... ...List Contact us PGDBj - Ortholog DB Cluster (Cyanobacteria) Data detail Data name Cluster (Cyanobacteria) DO...switchLanguage; BLAST Search Image Search Home About Archive Update History Data

Localization and orientation of heavy-atom cluster compounds in protein crystals using molecular replacement.

Science.gov (United States)

Dahms, Sven O; Kuester, Miriam; Streb, Carsten; Roth, Christian; Sträter, Norbert; Than, Manuel E

2013-02-01

Heavy-atom clusters (HA clusters) containing a large number of specifically arranged electron-dense scatterers are especially useful for experimental phase determination of large complex structures, weakly diffracting crystals or structures with large unit cells. Often, the determination of the exact orientation of the HA cluster and hence of the individual heavy-atom positions proves to be the critical step in successful phasing and subsequent structure solution. Here, it is demonstrated that molecular replacement (MR) with either anomalous or isomorphous differences is a useful strategy for the correct placement of HA cluster compounds. The polyoxometallate cluster hexasodium α-metatungstate (HMT) was applied in phasing the structure of death receptor 6. Even though the HA cluster is bound in alternate partially occupied orientations and is located at a special position, its correct localization and orientation could be determined at resolutions as low as 4.9 Å. The broad applicability of this approach was demonstrated for five different derivative crystals that included the compounds tantalum tetradecabromide and trisodium phosphotungstate in addition to HMT. The correct placement of the HA cluster depends on the length of the intramolecular vectors chosen for MR, such that both a larger cluster size and the optimal choice of the wavelength used for anomalous data collection strongly affect the outcome.

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.

Localization and orientation of heavy-atom cluster compounds in protein crystals using molecular replacement

International Nuclear Information System (INIS)

Dahms, Sven O.; Kuester, Miriam; Streb, Carsten; Roth, Christian; Sträter, Norbert; Than, Manuel E.

2013-01-01

A new approach is presented that allows the efficient localization and orientation of heavy-atom cluster compounds used in experimental phasing by a molecular replacement procedure. This permits the calculation of meaningful phases up to the highest resolution of the diffraction data. Heavy-atom clusters (HA clusters) containing a large number of specifically arranged electron-dense scatterers are especially useful for experimental phase determination of large complex structures, weakly diffracting crystals or structures with large unit cells. Often, the determination of the exact orientation of the HA cluster and hence of the individual heavy-atom positions proves to be the critical step in successful phasing and subsequent structure solution. Here, it is demonstrated that molecular replacement (MR) with either anomalous or isomorphous differences is a useful strategy for the correct placement of HA cluster compounds. The polyoxometallate cluster hexasodium α-metatungstate (HMT) was applied in phasing the structure of death receptor 6. Even though the HA cluster is bound in alternate partially occupied orientations and is located at a special position, its correct localization and orientation could be determined at resolutions as low as 4.9 Å. The broad applicability of this approach was demonstrated for five different derivative crystals that included the compounds tantalum tetradecabromide and trisodium phosphotungstate in addition to HMT. The correct placement of the HA cluster depends on the length of the intramolecular vectors chosen for MR, such that both a larger cluster size and the optimal choice of the wavelength used for anomalous data collection strongly affect the outcome

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.

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

HotRegion: a database of predicted hot spot clusters.

Science.gov (United States)

Cukuroglu, Engin; Gursoy, Attila; Keskin, Ozlem

2012-01-01

Hot spots are energetically important residues at protein interfaces and they are not randomly distributed across the interface but rather clustered. These clustered hot spots form hot regions. Hot regions are important for the stability of protein complexes, as well as providing specificity to binding sites. We propose a database called HotRegion, which provides the hot region information of the interfaces by using predicted hot spot residues, and structural properties of these interface residues such as pair potentials of interface residues, accessible surface area (ASA) and relative ASA values of interface residues of both monomer and complex forms of proteins. Also, the 3D visualization of the interface and interactions among hot spot residues are provided. HotRegion is accessible at http://prism.ccbb.ku.edu.tr/hotregion.

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

Structure-sequence based analysis for identification of conserved regions in proteins

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Zemla, Adam T; Zhou, Carol E; Lam, Marisa W; Smith, Jason R; Pardes, Elizabeth

2013-05-28

Disclosed are computational methods, and associated hardware and software products for scoring conservation in a protein structure based on a computationally identified family or cluster of protein structures. A method of computationally identifying a family or cluster of protein structures in also disclosed herein.

Yeast Interacting Proteins Database: YOL069W, YIL144W [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available complex (Ndc80p-Nuf2p-Spc24p-Spc25p); involved in chromosome segregation, spindle checkpoint activity and kinetochore clustering...vity, kinetochore assembly and clustering Rows with this prey as prey (2) Rows with this prey as bait (0) 12...-Nuf2p-Spc24p-Spc25p); involved in chromosome segregation, spindle checkpoint activity and kinetochore clustering...d coiled-coil protein involved in chromosome segregation, spindle checkpoint activity, kinetochore assembly and clustering

Dynamics and molecular determinants of cytoplasmic lipid droplet clustering and dispersion.

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David J Orlicky

Full Text Available Perilipin-1 (Plin1, a prominent cytoplasmic lipid droplet (CLD binding phosphoprotein and key physiological regulator of triglyceride storage and lipolysis in adipocytes, is thought to regulate the fragmentation and dispersion of CLD that occurs in response to β-adrenergic activation of adenylate cyclase. Here we investigate the dynamics and molecular determinants of these processes using cell lines stably expressing recombinant forms of Plin1 and/or other members of the perilipin family. Plin1 and a C-terminal CLD-binding fragment of Plin1 (Plin1CT induced formation of single dense CLD clusters near the microtubule organizing center, whereas neither an N-terminal CLD-binding fragment of Plin1, nor Plin2 or Plin3 induced clustering. Clustered CLD coated by Plin1, or Plin1CT, dispersed in response to isoproterenol, or other agents that activate adenylate cyclase, in a process inhibited by the protein kinase A inhibitor, H89, and blocked by microtubule disruption. Isoproterenol-stimulated phosphorylation of CLD-associated Plin1 on serine 492 preceded their dispersion, and live cell imaging showed that cluster dispersion involved initial fragmentation of tight clusters into multiple smaller clusters, which then fragmented into well-dispersed individual CLD. siRNA knockdown of the cortical actin binding protein, moesin, induced disaggregation of tight clusters into multiple smaller clusters, and inhibited the reaggregation of dispersed CLD into tight clusters. Together these data suggest that the clustering and dispersion processes involve a complex orchestration of phosphorylation-dependent, microtubule-dependent and independent, and microfilament dependent steps.

Dynamics and molecular determinants of cytoplasmic lipid droplet clustering and dispersion.

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Orlicky, David J; Monks, Jenifer; Stefanski, Adrianne L; McManaman, James L

2013-01-01

Perilipin-1 (Plin1), a prominent cytoplasmic lipid droplet (CLD) binding phosphoprotein and key physiological regulator of triglyceride storage and lipolysis in adipocytes, is thought to regulate the fragmentation and dispersion of CLD that occurs in response to β-adrenergic activation of adenylate cyclase. Here we investigate the dynamics and molecular determinants of these processes using cell lines stably expressing recombinant forms of Plin1 and/or other members of the perilipin family. Plin1 and a C-terminal CLD-binding fragment of Plin1 (Plin1CT) induced formation of single dense CLD clusters near the microtubule organizing center, whereas neither an N-terminal CLD-binding fragment of Plin1, nor Plin2 or Plin3 induced clustering. Clustered CLD coated by Plin1, or Plin1CT, dispersed in response to isoproterenol, or other agents that activate adenylate cyclase, in a process inhibited by the protein kinase A inhibitor, H89, and blocked by microtubule disruption. Isoproterenol-stimulated phosphorylation of CLD-associated Plin1 on serine 492 preceded their dispersion, and live cell imaging showed that cluster dispersion involved initial fragmentation of tight clusters into multiple smaller clusters, which then fragmented into well-dispersed individual CLD. siRNA knockdown of the cortical actin binding protein, moesin, induced disaggregation of tight clusters into multiple smaller clusters, and inhibited the reaggregation of dispersed CLD into tight clusters. Together these data suggest that the clustering and dispersion processes involve a complex orchestration of phosphorylation-dependent, microtubule-dependent and independent, and microfilament dependent steps.

Distinct profile of vascular progenitor attachment to extracellular matrix proteins in cancer patients.

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Labonté, Laura; Li, Yuhua; Addison, Christina L; Brand, Marjorie; Javidnia, Hedyeh; Corsten, Martin; Burns, Kevin; Allan, David S

2012-04-01

Vascular progenitor cells (VPCs) facilitate angiogenesis and initiate vascular repair by homing in on sites of damage and adhering to extracellular matrix (ECM) proteins. VPCs also contribute to tumor angiogenesis and induce angiogenic switching in sites of metastatic cancer. In this study, the binding of attaching cells in VPC clusters that form in vitro on specific ECM proteins was investigated. VPC cluster assays were performed in vitro on ECM proteins enriched in cancer cells and in remodelling tissue. Profiles of VPC clusters from patients with cancer were compared to healthy controls. The role of VEGF and integrin-specific binding of angiogenic attaching cells was addressed. VPC clusters from cancer patients were markedly increased on fibronectin relative to other ECM proteins tested, in contrast to VPC clusters from control subjects, which formed preferentially on laminin. Specific integrin-mediated binding of attaching cells in VPC clusters was matrix protein-dependent. Furthermore, cancer patients had elevated plasma VEGF levels compared to healthy controls and VEGF facilitated preferential VPC cluster formation on fibronectin. Incubating cells from healthy controls with VEGF induced a switch from the 'healthy' VPC binding profile to the profile observed in cancer patients with a marked increase in VPC cluster formation on fibronectin. The ECM proteins laminin and fibronectin support VPC cluster formation via specific integrins on attaching cells and can facilitate patterns of VPC cluster formation that are distinct in cancer patients. Larger studies, however, are needed to gain insight on how tumor angiogenesis may differ from normal repair processes.

Correlation of mRNA and protein levels: Cell type-specific gene expression of cluster designation antigens in the prostate

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Deutsch Eric W

2008-05-01

Full Text Available Abstract Background: Expression levels of mRNA and protein by cell types exhibit a range of correlations for different genes. In this study, we compared levels of mRNA abundance for several cluster designation (CD genes determined by gene arrays using magnetic sorted and laser-capture microdissected human prostate cells with levels of expression of the respective CD proteins determined by immunohistochemical staining in the major cell types of the prostate – basal epithelial, luminal epithelial, stromal fibromuscular, and endothelial – and for prostate precursor/stem cells and prostate carcinoma cells. Immunohistochemical stains of prostate tissues from more than 50 patients were scored for informative CD antigen expression and compared with cell-type specific transcriptomes. Results: Concordance between gene and protein expression findings based on 'present' vs. 'absent' calls ranged from 46 to 68%. Correlation of expression levels was poor to moderate (Pearson correlations ranged from 0 to 0.63. Divergence between the two data types was most frequently seen for genes whose array signals exceeded background (> 50 but lacked immunoreactivity by immunostaining. This could be due to multiple factors, e.g. low levels of protein expression, technological sensitivities, sample processing, probe set definition or anatomical origin of tissue and actual biological differences between transcript and protein abundance. Conclusion: Agreement between these two very different methodologies has great implications for their respective use in both molecular studies and clinical trials employing molecular biomarkers.

VTVH-MCD study of the Delta nifB Delta nifZ MoFe protein from Azotobacter vinelandii.

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Cotton, Marcia S; Rupnik, Kresimir; Broach, Robyn B; Hu, Yilin; Fay, Aaron W; Ribbe, Markus W; Hales, Brian J

2009-04-08

NifZ is a member of a series of proteins associated with the maturation of the nitrogenase MoFe protein. An MCD spectroscopic study was undertaken on the Delta nifB Delta nifZ MoFe protein generated in the absence of both NifZ and NifB (deletion of NifB generates an apo-MoFe protein lacking the FeMo cofactor). Results presented here show that, in the absence of NifZ, only one of the two P-clusters of the MoFe protein is matured to the ultimate [8Fe-7S] structure. The other P-cluster site in the protein contains a [4Fe-4S] cluster pair, representing a P-cluster precursor that is electronically identical to the analogous clusters observed in the Delta nifH MoFe protein. These results suggest that the MoFe protein is synthesized in a stepwise fashion where NifZ is specifically required for the formation of the second P-cluster.

Architecture of the Yeast Mitochondrial Iron-Sulfur Cluster Assembly Machinery

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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

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

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Uchikoga Nobuyuki

2010-05-01

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

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

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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

Progeny Clustering: A Method to Identify Biological Phenotypes

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Hu, Chenyue W.; Kornblau, Steven M.; Slater, John H.; Qutub, Amina A.

2015-01-01

Estimating the optimal number of clusters is a major challenge in applying cluster analysis to any type of dataset, especially to biomedical datasets, which are high-dimensional and complex. Here, we introduce an improved method, Progeny Clustering, which is stability-based and exceptionally efficient in computing, to find the ideal number of clusters. The algorithm employs a novel Progeny Sampling method to reconstruct cluster identity, a co-occurrence probability matrix to assess the clustering stability, and a set of reference datasets to overcome inherent biases in the algorithm and data space. Our method was shown successful and robust when applied to two synthetic datasets (datasets of two-dimensions and ten-dimensions containing eight dimensions of pure noise), two standard biological datasets (the Iris dataset and Rat CNS dataset) and two biological datasets (a cell phenotype dataset and an acute myeloid leukemia (AML) reverse phase protein array (RPPA) dataset). Progeny Clustering outperformed some popular clustering evaluation methods in the ten-dimensional synthetic dataset as well as in the cell phenotype dataset, and it was the only method that successfully discovered clinically meaningful patient groupings in the AML RPPA dataset. PMID:26267476

Spatial cluster analysis of nanoscopically mapped serotonin receptors for classification of fixed brain tissue

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Sams, Michael; Silye, Rene; Göhring, Janett; Muresan, Leila; Schilcher, Kurt; Jacak, Jaroslaw

2014-01-01

We present a cluster spatial analysis method using nanoscopic dSTORM images to determine changes in protein cluster distributions within brain tissue. Such methods are suitable to investigate human brain tissue and will help to achieve a deeper understanding of brain disease along with aiding drug development. Human brain tissue samples are usually treated postmortem via standard fixation protocols, which are established in clinical laboratories. Therefore, our localization microscopy-based method was adapted to characterize protein density and protein cluster localization in samples fixed using different protocols followed by common fluorescent immunohistochemistry techniques. The localization microscopy allows nanoscopic mapping of serotonin 5-HT1A receptor groups within a two-dimensional image of a brain tissue slice. These nanoscopically mapped proteins can be confined to clusters by applying the proposed statistical spatial analysis. Selected features of such clusters were subsequently used to characterize and classify the tissue. Samples were obtained from different types of patients, fixed with different preparation methods, and finally stored in a human tissue bank. To verify the proposed method, samples of a cryopreserved healthy brain have been compared with epitope-retrieved and paraffin-fixed tissues. Furthermore, samples of healthy brain tissues were compared with data obtained from patients suffering from mental illnesses (e.g., major depressive disorder). Our work demonstrates the applicability of localization microscopy and image analysis methods for comparison and classification of human brain tissues at a nanoscopic level. Furthermore, the presented workflow marks a unique technological advance in the characterization of protein distributions in brain tissue sections.

Identification and phylogeny of the tomato receptor-like proteins family

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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

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.

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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.

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.

Analysis of protein profiles using fuzzy clustering methods

DEFF Research Database (Denmark)

Karemore, Gopal Raghunath; Ukendt, Sujatha; Rai, Lavanya

The tissue protein profiles of healthy volunteers and volunteers with cervical cancer were recorded using High Performance Liquid Chromatography combined with Laser Induced Fluorescence  technique  (HPLC-LIF)  developed  in  our  lab.      We analyzed      the protein profile data using different...

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.

Comparing the performance of biomedical clustering methods

DEFF Research Database (Denmark)

Wiwie, Christian; Baumbach, Jan; Röttger, Richard

2015-01-01

expression to protein domains. Performance was judged on the basis of 13 common cluster validity indices. We developed a clustering analysis platform, ClustEval (http://clusteval.mpi-inf.mpg.de), to promote streamlined evaluation, comparison and reproducibility of clustering results in the future......Identifying groups of similar objects is a popular first step in biomedical data analysis, but it is error-prone and impossible to perform manually. Many computational methods have been developed to tackle this problem. Here we assessed 13 well-known methods using 24 data sets ranging from gene....... This allowed us to objectively evaluate the performance of all tools on all data sets with up to 1,000 different parameter sets each, resulting in a total of more than 4 million calculated cluster validity indices. We observed that there was no universal best performer, but on the basis of this wide...

UQlust: combining profile hashing with linear-time ranking for efficient clustering and analysis of big macromolecular data.

Science.gov (United States)

Adamczak, Rafal; Meller, Jarek

2016-12-28

Advances in computing have enabled current protein and RNA structure prediction and molecular simulation methods to dramatically increase their sampling of conformational spaces. The quickly growing number of experimentally resolved structures, and databases such as the Protein Data Bank, also implies large scale structural similarity analyses to retrieve and classify macromolecular data. Consequently, the computational cost of structure comparison and clustering for large sets of macromolecular structures has become a bottleneck that necessitates further algorithmic improvements and development of efficient software solutions. uQlust is a versatile and easy-to-use tool for ultrafast ranking and clustering of macromolecular structures. uQlust makes use of structural profiles of proteins and nucleic acids, while combining a linear-time algorithm for implicit comparison of all pairs of models with profile hashing to enable efficient clustering of large data sets with a low memory footprint. In addition to ranking and clustering of large sets of models of the same protein or RNA molecule, uQlust can also be used in conjunction with fragment-based profiles in order to cluster structures of arbitrary length. For example, hierarchical clustering of the entire PDB using profile hashing can be performed on a typical laptop, thus opening an avenue for structural explorations previously limited to dedicated resources. The uQlust package is freely available under the GNU General Public License at https://github.com/uQlust . uQlust represents a drastic reduction in the computational complexity and memory requirements with respect to existing clustering and model quality assessment methods for macromolecular structure analysis, while yielding results on par with traditional approaches for both proteins and RNAs.

Lipid reorganization induced by Shiga toxin clustering on planar membranes.

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Barbara Windschiegl

Full Text Available The homopentameric B-subunit of bacterial protein Shiga toxin (STxB binds to the glycolipid Gb(3 in plasma membranes, which is the initial step for entering cells by a clathrin-independent mechanism. It has been suggested that protein clustering and lipid reorganization determine toxin uptake into cells. Here, we elucidated the molecular requirements for STxB induced Gb(3 clustering and for the proposed lipid reorganization in planar membranes. The influence of binding site III of the B-subunit as well as the Gb(3 lipid structure was investigated by means of high resolution methods such as fluorescence and scanning force microscopy. STxB was found to form protein clusters on homogenous 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC/cholesterol/Gb(3 (65:30:5 bilayers. In contrast, membranes composed of DOPC/cholesterol/sphingomyelin/Gb(3 (40:35:20:5 phase separate into a liquid ordered and liquid disordered phase. Dependent on the fatty acid composition of Gb(3, STxB-Gb(3 complexes organize within the liquid ordered phase upon protein binding. Our findings suggest that STxB is capable of forming a new membrane phase that is characterized by lipid compaction. The significance of this finding is discussed in the context of Shiga toxin-induced formation of endocytic membrane invaginations.

Comparative genomics of Cluster O mycobacteriophages.

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Cresawn, Steven G; Pope, Welkin H; Jacobs-Sera, Deborah; Bowman, Charles A; Russell, Daniel A; Dedrick, Rebekah M; Adair, Tamarah; Anders, Kirk R; Ball, Sarah; Bollivar, David; Breitenberger, Caroline; Burnett, Sandra H; Butela, Kristen; Byrnes, Deanna; Carzo, Sarah; Cornely, Kathleen A; Cross, Trevor; Daniels, Richard L; Dunbar, David; Findley, Ann M; Gissendanner, Chris R; Golebiewska, Urszula P; Hartzog, Grant A; Hatherill, J Robert; Hughes, Lee E; Jalloh, Chernoh S; De Los Santos, Carla; Ekanem, Kevin; Khambule, Sphindile L; King, Rodney A; King-Smith, Christina; Klyczek, Karen; Krukonis, Greg P; Laing, Christian; Lapin, Jonathan S; Lopez, A Javier; Mkhwanazi, Sipho M; Molloy, Sally D; Moran, Deborah; Munsamy, Vanisha; Pacey, Eddie; Plymale, Ruth; Poxleitner, Marianne; Reyna, Nathan; Schildbach, Joel F; Stukey, Joseph; Taylor, Sarah E; Ware, Vassie C; Wellmann, Amanda L; Westholm, Daniel; Wodarski, Donna; Zajko, Michelle; Zikalala, Thabiso S; Hendrix, Roger W; Hatfull, Graham F

2015-01-01

Mycobacteriophages--viruses of mycobacterial hosts--are genetically diverse but morphologically are all classified in the Caudovirales with double-stranded DNA and tails. We describe here a group of five closely related mycobacteriophages--Corndog, Catdawg, Dylan, Firecracker, and YungJamal--designated as Cluster O with long flexible tails but with unusual prolate capsids. Proteomic analysis of phage Corndog particles, Catdawg particles, and Corndog-infected cells confirms expression of half of the predicted gene products and indicates a non-canonical mechanism for translation of the Corndog tape measure protein. Bioinformatic analysis identifies 8-9 strongly predicted SigA promoters and all five Cluster O genomes contain more than 30 copies of a 17 bp repeat sequence with dyad symmetry located throughout the genomes. Comparison of the Cluster O phages provides insights into phage genome evolution including the processes of gene flux by horizontal genetic exchange.

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

Comparative analysis of clustering methods for gene expression time course data

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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.

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.

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.

Identification, characterization and metagenome analysis of oocyte-specific genes organized in clusters in the mouse genome

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Vaiman Daniel

2005-05-01

Full Text Available Abstract Background Genes specifically expressed in the oocyte play key roles in oogenesis, ovarian folliculogenesis, fertilization and/or early embryonic development. In an attempt to identify novel oocyte-specific genes in the mouse, we have used an in silico subtraction methodology, and we have focused our attention on genes that are organized in genomic clusters. Results In the present work, five clusters have been studied: a cluster of thirteen genes characterized by an F-box domain localized on chromosome 9, a cluster of six genes related to T-cell leukaemia/lymphoma protein 1 (Tcl1 on chromosome 12, a cluster composed of a SPErm-associated glutamate (E-Rich (Speer protein expressed in the oocyte in the vicinity of four unknown genes specifically expressed in the testis on chromosome 14, a cluster composed of the oocyte secreted protein-1 (Oosp-1 gene and two Oosp-related genes on chromosome 19, all three being characterized by a partial N-terminal zona pellucida-like domain, and another small cluster of two genes on chromosome 19 as well, composed of a TWIK-Related spinal cord K+ channel encoding-gene, and an unknown gene predicted in silico to be testis-specific. The specificity of expression was confirmed by RT-PCR and in situ hybridization for eight and five of them, respectively. Finally, we showed by comparing all of the isolated and clustered oocyte-specific genes identified so far in the mouse genome, that the oocyte-specific clusters are significantly closer to telomeres than isolated oocyte-specific genes are. Conclusion We have studied five clusters of genes specifically expressed in female, some of them being also expressed in male germ-cells. Moreover, contrarily to non-clustered oocyte-specific genes, those that are organized in clusters tend to map near chromosome ends, suggesting that this specific near-telomere position of oocyte-clusters in rodents could constitute an evolutionary advantage. Understanding the biological

Identifying technical aliases in SELDI mass spectra of complex mixtures of proteins

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2013-01-01

Background Biomarker discovery datasets created using mass spectrum protein profiling of complex mixtures of proteins contain many peaks that represent the same protein with different charge states. Correlated variables such as these can confound the statistical analyses of proteomic data. Previously we developed an algorithm that clustered mass spectrum peaks that were biologically or technically correlated. Here we demonstrate an algorithm that clusters correlated technical aliases only. Results In this paper, we propose a preprocessing algorithm that can be used for grouping technical aliases in mass spectrometry protein profiling data. The stringency of the variance allowed for clustering is customizable, thereby affecting the number of peaks that are clustered. Subsequent analysis of the clusters, instead of individual peaks, helps reduce difficulties associated with technically-correlated data, and can aid more efficient biomarker identification. Conclusions This software can be used to pre-process and thereby decrease the complexity of protein profiling proteomics data, thus simplifying the subsequent analysis of biomarkers by decreasing the number of tests. The software is also a practical tool for identifying which features to investigate further by purification, identification and confirmation. PMID:24010718

Comparative genomics of Cluster O mycobacteriophages.

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Steven G Cresawn

Full Text Available Mycobacteriophages--viruses of mycobacterial hosts--are genetically diverse but morphologically are all classified in the Caudovirales with double-stranded DNA and tails. We describe here a group of five closely related mycobacteriophages--Corndog, Catdawg, Dylan, Firecracker, and YungJamal--designated as Cluster O with long flexible tails but with unusual prolate capsids. Proteomic analysis of phage Corndog particles, Catdawg particles, and Corndog-infected cells confirms expression of half of the predicted gene products and indicates a non-canonical mechanism for translation of the Corndog tape measure protein. Bioinformatic analysis identifies 8-9 strongly predicted SigA promoters and all five Cluster O genomes contain more than 30 copies of a 17 bp repeat sequence with dyad symmetry located throughout the genomes. Comparison of the Cluster O phages provides insights into phage genome evolution including the processes of gene flux by horizontal genetic exchange.

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

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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.

Toxicological relationships between proteins obtained from protein target predictions of large toxicity databases

International Nuclear Information System (INIS)

Nigsch, Florian; Mitchell, John B.O.

2008-01-01

The combination of models for protein target prediction with large databases containing toxicological information for individual molecules allows the derivation of 'toxiclogical' profiles, i.e., to what extent are molecules of known toxicity predicted to interact with a set of protein targets. To predict protein targets of drug-like and toxic molecules, we built a computational multiclass model using the Winnow algorithm based on a dataset of protein targets derived from the MDL Drug Data Report. A 15-fold Monte Carlo cross-validation using 50% of each class for training, and the remaining 50% for testing, provided an assessment of the accuracy of that model. We retained the 3 top-ranking predictions and found that in 82% of all cases the correct target was predicted within these three predictions. The first prediction was the correct one in almost 70% of cases. A model built on the whole protein target dataset was then used to predict the protein targets for 150 000 molecules from the MDL Toxicity Database. We analysed the frequency of the predictions across the panel of protein targets for experimentally determined toxicity classes of all molecules. This allowed us to identify clusters of proteins related by their toxicological profiles, as well as toxicities that are related. Literature-based evidence is provided for some specific clusters to show the relevance of the relationships identified

Influence of dietary tender cluster beans (Cyamopsis tetragonoloba) on biliary proteins, bile acid synthesis and cholesterol crystal growth in rat bile.

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Raghavendra, Chikkanna K; Srinivasan, Krishnapura

2015-02-01

Tender cluster beans (CBs; Cyamopsis tetragonoloba) are observed to possess anti-lithogenic potential in experimental mice. Formation of cholesterol gallstones in gallbladder is controlled by procrystallizing and anticrystallizing factors present in bile in addition to supersaturation of cholesterol. This study aimed at evaluating the influence of CB on biliary glycoproteins, low molecular weight (LMW) and high molecular weight (HMW) proteins, cholesterol nucleation time, and cholesterol crystal growth in rat hepatic bile. Groups of rats were fed for 10 weeks with 0.5% cholesterol to render the bile lithogenic. Experimental dietary interventions were: 10% freeze-dried CB, 1% garlic powder or their combination. Incorporation of CB into HCD decreased the cholesterol saturation index in bile, increased bile flow and biliary glycoproteins. Dietary CB prolonged cholesterol nucleation time in bile. Electrophoresis of biliary proteins showed the presence of high concentration of 27 kDa protein which might be responsible for the prolongation of cholesterol nucleation time in the CB fed group. Proteins of 20 kDa and 18 kDa were higher in CB treated animals, while the same were less expressed in HCD group. Biliary proteins from CB fed animals reduced cholesterol crystal growth index which was elevated in the presence of proteins from HCD group. Cholesterol-7α-hydroxylase and cholesterol-27-hydroxylase mRNA expression was increased in CB treated animals contributing to the bile acid synthesis. Thus, the beneficial anti-lithogenic effect of dietary CB which primarily is due to reduced cholesterol saturation index was additionally affected through a modulation of the nucleating and anti-nucleating proteins that affect cholesterol crystallization. Copyright © 2014 Elsevier Inc. All rights reserved.

Double-stranded endonuclease activity in Bacillus halodurans clustered regularly interspaced short palindromic repeats (CRISPR)-associated Cas2 protein.

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Nam, Ki Hyun; Ding, Fran; Haitjema, Charles; Huang, Qingqiu; DeLisa, Matthew P; Ke, Ailong

2012-10-19

The CRISPR (clustered regularly interspaced short palindromic repeats) system is a prokaryotic RNA-based adaptive immune system against extrachromosomal genetic elements. Cas2 is a universally conserved core CRISPR-associated protein required for the acquisition of new spacers for CRISPR adaptation. It was previously characterized as an endoribonuclease with preference for single-stranded (ss)RNA. Here, we show using crystallography, mutagenesis, and isothermal titration calorimetry that the Bacillus halodurans Cas2 (Bha_Cas2) from the subtype I-C/Dvulg CRISPR instead possesses metal-dependent endonuclease activity against double-stranded (ds)DNA. This activity is consistent with its putative function in producing new spacers for insertion into the 5'-end of the CRISPR locus. Mutagenesis and isothermal titration calorimetry studies revealed that a single divalent metal ion (Mg(2+) or Mn(2+)), coordinated by a symmetric Asp pair in the Bha_Cas2 dimer, is involved in the catalysis. We envision that a pH-dependent conformational change switches Cas2 into a metal-binding competent conformation for catalysis. We further propose that the distinct substrate preferences among Cas2 proteins may be determined by the sequence and structure in the β1-α1 loop.

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.

Extracellular cyclophilin levels associate with parameters of asthma in phenotypic clusters.

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Stemmy, Erik J; Benton, Angela S; Lerner, Jennifer; Alcala, Sarah; Constant, Stephanie L; Freishtat, Robert J

2011-12-01

Leukocyte persistence during chronic (quiescent) phases of asthma is a major hallmark of the disease. The mechanisms regulating these persistent leukocyte populations are not clearly understood. An alternative family of chemoattracting proteins, cyclophilins (Cyps), has recently been shown to contribute to leukocyte recruitment in animal models of allergic asthma. The goals of this study were to determine whether Cyps are present in asthma patients during the chronic phase of the disease and to investigate whether levels of Cyps associate with clinical parameters of disease severity. Nasal wash samples from an urban cohort of 137 patients of age 6-20 years with physician-diagnosed asthma were examined for the presence of cyclophilin A (CypA), cyclophilin B (CypB), as well as several other classical chemokines. Linear, logistic, or ordinal regressions were performed to identify associations between Cyps, chemokines, and clinical parameters of asthma. The asthma cohort was further divided into previously established phenotypic clusters (cluster 1: n = 55; cluster 2: n = 31; and cluster 3: n = 51) and examined for associations. Levels of CypB in the asthma group were highly elevated compared to nonasthmatic controls, while a slight increase in Monocyte Chemotactic Protein-1 (MCP-1) was also observed. CypA and MCP-1 were associated with levels of eosinophil cationic protein (ECP; a marker of eosinophil activation). Cluster-specific associations were found for CypA and CypB and clinical asthma parameters [e.g. forced expiratory volume in 1 second (FEV(1)) and ECP]. Cyps are present in nasal wash samples of asthma patients and may be a novel biomarker for clinical parameters of asthma severity.

Investigation of glutathione-derived electrostatic and hydrogen-bonding interactions and their role in defining Grx5 [2Fe-2S] cluster optical spectra and transfer chemistry.

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Sen, Sambuddha; Bonfio, Claudia; Mansy, Sheref S; Cowan, J A

2018-03-01

Human glutaredoxin 5 (Grx5) is one of the core components of the Isc (iron-sulfur cluster) assembly and trafficking machinery, and serves as an intermediary cluster carrier, putatively delivering cluster from the Isu scaffold protein to target proteins. The tripeptide glutathione is intimately involved in this role, providing cysteinyl coordination to the iron center of the Grx5-bound [2Fe-2S] cluster. Grx5 has a well-defined glutathione-binding pocket with protein amino acid residues providing many ionic and hydrogen binding contacts to the bound glutathione. In this report, we investigated the importance of these interactions in cluster chirality and exchange reactivity by systematically perturbing the crucial contacts by use of natural and non-natural amino acid substitutions to disrupt the binding contacts from both the protein and glutathione. Native Grx5 could be reconstituted with all of the glutathione analogs used, as well as other thiol ligands, such as DTT or L-cysteine, by in vitro chemical reconstitution, and the holo proteins were found to transfer [2Fe-2S] cluster to apo ferredoxin 1 at comparable rates. However, the circular dichroism spectra of these derivatives displayed prominent differences that reflect perturbations in local cluster chirality. These studies provided a detailed molecular understanding of glutathione-protein interactions in holo Grx5 that define both cluster spectroscopy and exchange chemistry.

Statistical discovery of site inter-dependencies in sub-molecular hierarchical protein structuring.

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Durston, Kirk K; Chiu, David Ky; Wong, Andrew Kc; Li, Gary Cl

2012-07-13

Much progress has been made in understanding the 3D structure of proteins using methods such as NMR and X-ray crystallography. The resulting 3D structures are extremely informative, but do not always reveal which sites and residues within the structure are of special importance. Recently, there are indications that multiple-residue, sub-domain structural relationships within the larger 3D consensus structure of a protein can be inferred from the analysis of the multiple sequence alignment data of a protein family. These intra-dependent clusters of associated sites are used to indicate hierarchical inter-residue relationships within the 3D structure. To reveal the patterns of associations among individual amino acids or sub-domain components within the structure, we apply a k-modes attribute (aligned site) clustering algorithm to the ubiquitin and transthyretin families in order to discover associations among groups of sites within the multiple sequence alignment. We then observe what these associations imply within the 3D structure of these two protein families. The k-modes site clustering algorithm we developed maximizes the intra-group interdependencies based on a normalized mutual information measure. The clusters formed correspond to sub-structural components or binding and interface locations. Applying this data-directed method to the ubiquitin and transthyretin protein family multiple sequence alignments as a test bed, we located numerous interesting associations of interdependent sites. These clusters were then arranged into cluster tree diagrams which revealed four structural sub-domains within the single domain structure of ubiquitin and a single large sub-domain within transthyretin associated with the interface among transthyretin monomers. In addition, several clusters of mutually interdependent sites were discovered for each protein family, each of which appear to play an important role in the molecular structure and/or function. Our results

The Yeast Nbp35-Cfd1 Cytosolic Iron-Sulfur Cluster Scaffold Is an ATPase.

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Camire, Eric J; Grossman, John D; Thole, Grace J; Fleischman, Nicholas M; Perlstein, Deborah L

2015-09-25

Nbp35 and Cfd1 are prototypical members of the MRP/Nbp35 class of iron-sulfur (FeS) cluster scaffolds that function to assemble nascent FeS clusters for transfer to FeS-requiring enzymes. Both proteins contain a conserved NTPase domain that genetic studies have demonstrated is essential for their cluster assembly activity inside the cell. It was recently reported that these proteins possess no or very low nucleotide hydrolysis activity in vitro, and thus the role of the NTPase domain in cluster biogenesis has remained uncertain. We have reexamined the NTPase activity of Nbp35, Cfd1, and their complex. Using in vitro assays and site-directed mutagenesis, we demonstrate that the Nbp35 homodimer and the Nbp35-Cfd1 heterodimer are ATPases, whereas the Cfd1 homodimer exhibited no or very low ATPase activity. We ruled out the possibility that the observed ATP hydrolysis activity might result from a contaminating ATPase by showing that mutation of key active site residues reduced activity to background levels. Finally, we demonstrate that the fluorescent ATP analog 2'/3'-O-(N'-methylanthraniloyl)-ATP (mantATP) binds stoichiometrically to Nbp35 with a KD = 15.6 μM and that an Nbp35 mutant deficient in ATP hydrolysis activity also displays an increased KD for mantATP. Together, our results demonstrate that the cytosolic iron-sulfur cluster assembly scaffold is an ATPase and pave the way for interrogating the role of nucleotide hydrolysis in cluster biogenesis by this large family of cluster scaffolding proteins found across all domains of life. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

Formation of a homocitrate-free iron-molybdenum cluster on NifEN: implications for the role of homocitrate in nitrogenase assembly.

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Fay, Aaron Wolfe; Blank, Michael Aaron; Yoshizawa, Janice Mariko; Lee, Chi Chung; Wiig, Jared Andrew; Hu, Yilin; Hodgson, Keith Owen; Hedman, Britt; Ribbe, Markus Walter

2010-03-28

Molybdenum (Mo)-dependent nitrogenase is a complex metalloprotein that catalyzes the biological reduction of dinitrogen (N(2)) to ammonia (NH(3)) at the molybdenum-iron cofactor (FeMoco) site of its molybdenum-iron (MoFe) protein component. Here we report the formation of a homocitrate-free, iron-molybdenum ("FeMo") cluster on the biosynthetic scaffold of FeMoco, NifEN. Such a NifEN-associated "FeMo" cluster exhibits EPR features similar to those of the NifEN-associated, fully-complemented "FeMoco", which originate from the presence of Mo in both cluster species; however, "FeMo" cluster and "FeMoco" display different temperature-dependent changes in the line shape and the signal intensity of their respective EPR features, which reflect the impact of homocitrate on the redox properties of these clusters. XAS/EXAFS analysis reveals that the Mo centers in both "FeMo" cluster and "FeMoco" are present in a similar coordination environment, although Mo in "FeMo" cluster is more loosely coordinated as compared to that in "FeMoco" with respect to the Mo-O distances in the cluster, likely due to the absence of homocitrate that normally serves as an additional ligand for the Mo in the cluster. Subsequent biochemical investigation of the "FeMo" cluster not only facilitates the determination of the sequence of events in the mobilization of Mo and homocitrate during FeMoco maturation, but also permits the examination of the role of homocitrate in the transfer of FeMoco between NifEN and MoFe protein. Combined outcome of these studies establishes a platform for future structural analysis of the interactions between NifEN and MoFe protein, which will provide useful insights into the mechanism of cluster transfer between the two proteins.

Effects of clustering structure on volumetric properties of amino acids in (DMSO + water) mixtures

International Nuclear Information System (INIS)

Huang Aimin; Liu Chunli; Ma Lin; Tong Zhangfa; Lin Ruisen

2012-01-01

Graphical abstract: Together with static light scattering measurement, volumetric properties of glycine, L-alanine and L-serine were determined and utilized to reveal the microscopic solvent structure of (DMSO + water) mixtures and its influence on the interaction between DMSO and amino acids from a clustering point of view. The results demonstrated that the interaction between amino acids and DMSO was greatly related to the clustering structure of the mixed solvent and that amino acids interacted with already established solvent clusters. Hydrophobic aggregating of DMSO lead to a decrease in the hydrophobic effect of DMSO and the hydrophobic–hydrophilic and hydrophobic–hydrophobic interaction with amino acids, which was reflected by the solvation of proteins. Highlights: ► Determine volumetric properties of three amino acids in aqueous DMSO in details. ► Static light scattering measurement for clustering structure of aqueous DMSO. ► Volumetric behaviour of amino acids depends on clustering structure of aqueous DMSO. ► Clustering structure of aqueous DMSO influences solvation of protein and cellulose. - Abstract: For a better understanding on the functions of DMSO in biological systems at a relatively lower concentration, apparent molar volumes of three typical amino acids, glycine, L-alanine and L-serine in (DMSO + water) mixtures were determined and the transfer volumes from water to the mixtures were evaluated. Together with static light scattering measurement, the results were utilised to reveal the microscopic solvent structure of (DMSO + water) mixtures and its influence on the interaction between DMSO and amino acids from a clustering point of view. The results demonstrate that the interaction between amino acids and DMSO is greatly related to the clustering structure of the mixed solvent and that amino acids interacted with already established solvent clusters. The linear dependence of transfer volume of amino acids on DMSO concentration up to 2

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/.

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

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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

Brightest Cluster Galaxies in REXCESS Clusters

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Haarsma, Deborah B.; Leisman, L.; Bruch, S.; Donahue, M.

2009-01-01

Most galaxy clusters contain a Brightest Cluster Galaxy (BCG) which is larger than the other cluster ellipticals and has a more extended profile. In the hierarchical model, the BCG forms through many galaxy mergers in the crowded center of the cluster, and thus its properties give insight into the assembly of the cluster as a whole. In this project, we are working with the Representative XMM-Newton Cluster Structure Survey (REXCESS) team (Boehringer et al 2007) to study BCGs in 33 X-ray luminous galaxy clusters, 0.055 < z < 0.183. We are imaging the BCGs in R band at the Southern Observatory for Astrophysical Research (SOAR) in Chile. In this poster, we discuss our methods and give preliminary measurements of the BCG magnitudes, morphology, and stellar mass. We compare these BCG properties with the properties of their host clusters, particularly of the X-ray emitting gas.

Characterization of the largest effector gene cluster of Ustilago maydis.

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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.

The OGCleaner: filtering false-positive homology clusters.

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Fujimoto, M Stanley; Suvorov, Anton; Jensen, Nicholas O; Clement, Mark J; Snell, Quinn; Bybee, Seth M

2017-01-01

Detecting homologous sequences in organisms is an essential step in protein structure and function prediction, gene annotation and phylogenetic tree construction. Heuristic methods are often employed for quality control of putative homology clusters. These heuristics, however, usually only apply to pairwise sequence comparison and do not examine clusters as a whole. We present the Orthology Group Cleaner (the OGCleaner), a tool designed for filtering putative orthology groups as homology or non-homology clusters by considering all sequences in a cluster. The OGCleaner relies on high-quality orthologous groups identified in OrthoDB to train machine learning algorithms that are able to distinguish between true-positive and false-positive homology groups. This package aims to improve the quality of phylogenetic tree construction especially in instances of lower-quality transcriptome assemblies. https://github.com/byucsl/ogcleaner CONTACT: sfujimoto@gmail.comSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

SCPS: a fast implementation of a spectral method for detecting protein families on a genome-wide scale

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Paccanaro Alberto

2010-03-01

Full Text Available Abstract Background An important problem in genomics is the automatic inference of groups of homologous proteins from pairwise sequence similarities. Several approaches have been proposed for this task which are "local" in the sense that they assign a protein to a cluster based only on the distances between that protein and the other proteins in the set. It was shown recently that global methods such as spectral clustering have better performance on a wide variety of datasets. However, currently available implementations of spectral clustering methods mostly consist of a few loosely coupled Matlab scripts that assume a fair amount of familiarity with Matlab programming and hence they are inaccessible for large parts of the research community. Results SCPS (Spectral Clustering of Protein Sequences is an efficient and user-friendly implementation of a spectral method for inferring protein families. The method uses only pairwise sequence similarities, and is therefore practical when only sequence information is available. SCPS was tested on difficult sets of proteins whose relationships were extracted from the SCOP database, and its results were extensively compared with those obtained using other popular protein clustering algorithms such as TribeMCL, hierarchical clustering and connected component analysis. We show that SCPS is able to identify many of the family/superfamily relationships correctly and that the quality of the obtained clusters as indicated by their F-scores is consistently better than all the other methods we compared it with. We also demonstrate the scalability of SCPS by clustering the entire SCOP database (14,183 sequences and the complete genome of the yeast Saccharomyces cerevisiae (6,690 sequences. Conclusions Besides the spectral method, SCPS also implements connected component analysis and hierarchical clustering, it integrates TribeMCL, it provides different cluster quality tools, it can extract human-readable protein

SCPS: a fast implementation of a spectral method for detecting protein families on a genome-wide scale.

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Nepusz, Tamás; Sasidharan, Rajkumar; Paccanaro, Alberto

2010-03-09

An important problem in genomics is the automatic inference of groups of homologous proteins from pairwise sequence similarities. Several approaches have been proposed for this task which are "local" in the sense that they assign a protein to a cluster based only on the distances between that protein and the other proteins in the set. It was shown recently that global methods such as spectral clustering have better performance on a wide variety of datasets. However, currently available implementations of spectral clustering methods mostly consist of a few loosely coupled Matlab scripts that assume a fair amount of familiarity with Matlab programming and hence they are inaccessible for large parts of the research community. SCPS (Spectral Clustering of Protein Sequences) is an efficient and user-friendly implementation of a spectral method for inferring protein families. The method uses only pairwise sequence similarities, and is therefore practical when only sequence information is available. SCPS was tested on difficult sets of proteins whose relationships were extracted from the SCOP database, and its results were extensively compared with those obtained using other popular protein clustering algorithms such as TribeMCL, hierarchical clustering and connected component analysis. We show that SCPS is able to identify many of the family/superfamily relationships correctly and that the quality of the obtained clusters as indicated by their F-scores is consistently better than all the other methods we compared it with. We also demonstrate the scalability of SCPS by clustering the entire SCOP database (14,183 sequences) and the complete genome of the yeast Saccharomyces cerevisiae (6,690 sequences). Besides the spectral method, SCPS also implements connected component analysis and hierarchical clustering, it integrates TribeMCL, it provides different cluster quality tools, it can extract human-readable protein descriptions using GI numbers from NCBI, it interfaces with

Assembling Fe/S-clusters and modifying tRNAs: ancient co-factors meet ancient adaptors.

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Alfonzo, Juan D; Lukeš, Julius

2011-06-01

Trypanosoma brucei undergoes two clearly distinct develomental stages: in the insect vector (procyclic stage) the cells generate the bulk of their energy through respiration, whereas in the bloodstream of the mammalian host (bloodstream stage) they grow mostly glycolytically. Several mitochondrial respiratory proteins require iron-sulfur clusters for activity, and their activation coincides with developmental changes. Likewise some tRNA modification enzymes either require iron-sulfur clusters or use components of the iron-sulfur cluster assembly pathway for activity. These enzymes affect the anticodon loop of various tRNAs and can impact protein synthesis. Herein, the possibility of these pathways being integrated and exploited by T. brucei to carefully coordinate energy demands to translational rates in response to enviromental changes is examined.

Metal cluster compounds - chemistry and importance; clusters containing isolated main group element atoms, large metal cluster compounds, cluster fluxionality

International Nuclear Information System (INIS)

Walther, B.

1988-01-01

This part of the review on metal cluster compounds deals with clusters containing isolated main group element atoms, with high nuclearity clusters and metal cluster fluxionality. It will be obvious that main group element atoms strongly influence the geometry, stability and reactivity of the clusters. High nuclearity clusters are of interest in there own due to the diversity of the structures adopted, but their intermediate position between molecules and the metallic state makes them a fascinating research object too. These both sites of the metal cluster chemistry as well as the frequently observed ligand and core fluxionality are related to the cluster metal and surface analogy. (author)

PREFACE: Nuclear Cluster Conference; Cluster'07

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Freer, Martin

2008-05-01

The Cluster Conference is a long-running conference series dating back to the 1960's, the first being initiated by Wildermuth in Bochum, Germany, in 1969. The most recent meeting was held in Nara, Japan, in 2003, and in 2007 the 9th Cluster Conference was held in Stratford-upon-Avon, UK. As the name suggests the town of Stratford lies upon the River Avon, and shortly before the conference, due to unprecedented rainfall in the area (approximately 10 cm within half a day), lay in the River Avon! Stratford is the birthplace of the `Bard of Avon' William Shakespeare, and this formed an intriguing conference backdrop. The meeting was attended by some 90 delegates and the programme contained 65 70 oral presentations, and was opened by a historical perspective presented by Professor Brink (Oxford) and closed by Professor Horiuchi (RCNP) with an overview of the conference and future perspectives. In between, the conference covered aspects of clustering in exotic nuclei (both neutron and proton-rich), molecular structures in which valence neutrons are exchanged between cluster cores, condensates in nuclei, neutron-clusters, superheavy nuclei, clusters in nuclear astrophysical processes and exotic cluster decays such as 2p and ternary cluster decay. The field of nuclear clustering has become strongly influenced by the physics of radioactive beam facilities (reflected in the programme), and by the excitement that clustering may have an important impact on the structure of nuclei at the neutron drip-line. It was clear that since Nara the field had progressed substantially and that new themes had emerged and others had crystallized. Two particular topics resonated strongly condensates and nuclear molecules. These topics are thus likely to be central in the next cluster conference which will be held in 2011 in the Hungarian city of Debrechen. Martin Freer Participants and Cluster'07

Cross-over between discrete and continuous protein structure space: insights into automatic classification and networks of protein structures.

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Alberto Pascual-García

2009-03-01

Full Text Available Structural classifications of proteins assume the existence of the fold, which is an intrinsic equivalence class of protein domains. Here, we test in which conditions such an equivalence class is compatible with objective similarity measures. We base our analysis on the transitive property of the equivalence relationship, requiring that similarity of A with B and B with C implies that A and C are also similar. Divergent gene evolution leads us to expect that the transitive property should approximately hold. However, if protein domains are a combination of recurrent short polypeptide fragments, as proposed by several authors, then similarity of partial fragments may violate the transitive property, favouring the continuous view of the protein structure space. We propose a measure to quantify the violations of the transitive property when a clustering algorithm joins elements into clusters, and we find out that such violations present a well defined and detectable cross-over point, from an approximately transitive regime at high structure similarity to a regime with large transitivity violations and large differences in length at low similarity. We argue that protein structure space is discrete and hierarchic classification is justified up to this cross-over point, whereas at lower similarities the structure space is continuous and it should be represented as a network. We have tested the qualitative behaviour of this measure, varying all the choices involved in the automatic classification procedure, i.e., domain decomposition, alignment algorithm, similarity score, and clustering algorithm, and we have found out that this behaviour is quite robust. The final classification depends on the chosen algorithms. We used the values of the clustering coefficient and the transitivity violations to select the optimal choices among those that we tested. Interestingly, this criterion also favours the agreement between automatic and expert classifications

Identify High-Quality Protein Structural Models by Enhanced K-Means.

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Wu, Hongjie; Li, Haiou; Jiang, Min; Chen, Cheng; Lv, Qiang; Wu, Chuang

2017-01-01

Background. One critical issue in protein three-dimensional structure prediction using either ab initio or comparative modeling involves identification of high-quality protein structural models from generated decoys. Currently, clustering algorithms are widely used to identify near-native models; however, their performance is dependent upon different conformational decoys, and, for some algorithms, the accuracy declines when the decoy population increases. Results. Here, we proposed two enhanced K -means clustering algorithms capable of robustly identifying high-quality protein structural models. The first one employs the clustering algorithm SPICKER to determine the initial centroids for basic K -means clustering ( SK -means), whereas the other employs squared distance to optimize the initial centroids ( K -means++). Our results showed that SK -means and K -means++ were more robust as compared with SPICKER alone, detecting 33 (59%) and 42 (75%) of 56 targets, respectively, with template modeling scores better than or equal to those of SPICKER. Conclusions. We observed that the classic K -means algorithm showed a similar performance to that of SPICKER, which is a widely used algorithm for protein-structure identification. Both SK -means and K -means++ demonstrated substantial improvements relative to results from SPICKER and classical K -means.

Application of the AMPLE cluster-and-truncate approach to NMR structures for molecular replacement

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Bibby, Jaclyn [University of Liverpool, Liverpool L69 7ZB (United Kingdom); Keegan, Ronan M. [Research Complex at Harwell, STFC Rutherford Appleton Laboratory, Didcot OX11 0FA (United Kingdom); Mayans, Olga [University of Liverpool, Liverpool L69 7ZB (United Kingdom); Winn, Martyn D. [Science and Technology Facilities Council Daresbury Laboratory, Warrington WA4 4AD (United Kingdom); Rigden, Daniel J., E-mail: drigden@liv.ac.uk [University of Liverpool, Liverpool L69 7ZB (United Kingdom)

2013-11-01

Processing of NMR structures for molecular replacement by AMPLE works well. AMPLE is a program developed for clustering and truncating ab initio protein structure predictions into search models for molecular replacement. Here, it is shown that its core cluster-and-truncate methods also work well for processing NMR ensembles into search models. Rosetta remodelling helps to extend success to NMR structures bearing low sequence identity or high structural divergence from the target protein. Potential future routes to improved performance are considered and practical, general guidelines on using AMPLE are provided.

Improvement of activity and stability of Chondroitinase ABC I by introducing an aromatic cluster at the surface of protein.

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Shahaboddin, Mohammad Esmaeil; Khajeh, Khosro; Maleki, Monireh; Golestani, Abolfazl

2017-10-01

Chondroitinase ABC I (ChABC I) has been shown to depolymerize a variety of glycosaminoglycan substrates and promote regeneration of damaged spinal cord. However, to date, intrathecal delivery methods have been suboptimal largely due to enzyme instability which necessitates repeated administration to the injured loci. Among the aromatic amino acids, tyrosine has been shown to be more effective in creation of stable clusters and further stabilize of the proteins. Bioinformatics approaches have been used to examine the effect of an extra aromatic cluster at the surface of ChABC I. In this study two amino acids i.e., Asn 806 and Gln 810 were mutated to tyrosine and to alanine as negative control. In this way, four variants i.e., N806Y/Q810Y, N806A/Q810Y, N806Y/Q810A and N806A/Q810A were created. The results showed that N806Y/Q810Y mutation improved both activity and thermal stability of the enzyme while Ala substitution reduced the enzyme activity and destabilized it. Structural analysis of mutants showed an increase in intrinsic fluorescence intensity and secondary structure content of N806Y/Q810Y mutant when compared to the wild type enzyme indicating a more rigid structure of this variant. Moreover, the N806Y/Q810Y enzyme displayed a remarkable resistance against trypsin degradation with a half-life (t 1/2 ) of 45.0min versus 32.5min of wild-type. In conclusion, the data revealed that structural features and activity of ChABC I can be improved by introducing appropriate aromatic clusters at the surface of the enzyme. Copyright © 2017 Elsevier Inc. All rights reserved.

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.

Dynamics of water clusters confined in proteins: a molecular dynamics simulation study of interfacial waters in a dimeric hemoglobin.

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Gnanasekaran, Ramachandran; Xu, Yao; Leitner, David M

2010-12-23

Water confined in proteins exhibits dynamics distinct from the dynamics of water in the bulk or near the surface of a biomolecule. We examine the water dynamics at the interface of the two globules of the homodimeric hemoglobin from Scapharca inaequivalvis (HbI) by molecular dynamics (MD) simulations, with focus on water-protein hydrogen bond lifetimes and rotational anisotropy of the interfacial waters. We find that relaxation of the waters at the interface of both deoxy- and oxy-HbI, which contain a cluster of 17 and 11 interfacial waters, respectively, is well described by stretched exponentials with exponents from 0.1 to 0.6 and relaxation times of tens to thousands of picoseconds. The interfacial water molecules of oxy-HbI exhibit slower rotational relaxation and hydrogen bond rearrangement than those of deoxy-HbI, consistent with an allosteric transition from unliganded to liganded conformers involving the expulsion of several water molecules from the interface. Though the interfacial waters are translationally and rotationally static on the picosecond time scale, they contribute to fast communication between the globules via vibrations. We find that the interfacial waters enhance vibrational energy transport across the interface by ≈10%.

Identification of biofilm-associated cluster (bac in Pseudomonas aeruginosa involved in biofilm formation and virulence.

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Camille Macé

Full Text Available Biofilms are prevalent in diseases caused by Pseudomonas aeruginosa, an opportunistic and nosocomial pathogen. By a proteomic approach, we previously identified a hypothetical protein of P. aeruginosa (coded by the gene pA3731 that was accumulated by biofilm cells. We report here that a Delta pA3731 mutant is highly biofilm-defective as compared with the wild-type strain. Using a mouse model of lung infection, we show that the mutation also induces a defect in bacterial growth during the acute phase of infection and an attenuation of the virulence. The pA3731 gene is found to control positively the ability to swarm and to produce extracellular rhamnolipids, and belongs to a cluster of 4 genes (pA3729-pA3732 not previously described in P. aeruginosa. Though the protein PA3731 has a predicted secondary structure similar to that of the Phage Shock Protein, some obvious differences are observed compared to already described psp systems, e.g., this unknown cluster is monocistronic and no homology is found between the other proteins constituting this locus and psp proteins. As E. coli PspA, the amount of the protein PA3731 is enlarged by an osmotic shock, however, not affected by a heat shock. We consequently named this locus bac for biofilm-associated cluster.

Formation of stable products from cluster-cluster collisions

International Nuclear Information System (INIS)

Alamanova, Denitsa; Grigoryan, Valeri G; Springborg, Michael

2007-01-01

The formation of stable products from copper cluster-cluster collisions is investigated by using classical molecular-dynamics simulations in combination with an embedded-atom potential. The dependence of the product clusters on impact energy, relative orientation of the clusters, and size of the clusters is studied. The structures and total energies of the product clusters are analysed and compared with those of the colliding clusters before impact. These results, together with the internal temperature, are used in obtaining an increased understanding of cluster fusion processes

Statistical method on nonrandom clustering with application to somatic mutations in cancer

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Rejto Paul A

2010-01-01

Full Text Available Abstract Background Human cancer is caused by the accumulation of tumor-specific mutations in oncogenes and tumor suppressors that confer a selective growth advantage to cells. As a consequence of genomic instability and high levels of proliferation, many passenger mutations that do not contribute to the cancer phenotype arise alongside mutations that drive oncogenesis. While several approaches have been developed to separate driver mutations from passengers, few approaches can specifically identify activating driver mutations in oncogenes, which are more amenable for pharmacological intervention. Results We propose a new statistical method for detecting activating mutations in cancer by identifying nonrandom clusters of amino acid mutations in protein sequences. A probability model is derived using order statistics assuming that the location of amino acid mutations on a protein follows a uniform distribution. Our statistical measure is the differences between pair-wise order statistics, which is equivalent to the size of an amino acid mutation cluster, and the probabilities are derived from exact and approximate distributions of the statistical measure. Using data in the Catalog of Somatic Mutations in Cancer (COSMIC database, we have demonstrated that our method detects well-known clusters of activating mutations in KRAS, BRAF, PI3K, and β-catenin. The method can also identify new cancer targets as well as gain-of-function mutations in tumor suppressors. Conclusions Our proposed method is useful to discover activating driver mutations in cancer by identifying nonrandom clusters of somatic amino acid mutations in protein sequences.

Effects of punctal occlusion on global tear proteins in patients with dry eye.

Science.gov (United States)

Tong, Louis; Zhou, Lei; Beuerman, Roger; Simonyi, Susan; Hollander, David A; Stern, Michael E

2017-10-01

To investigate effects of punctal occlusion on global tear protein levels in patients with dry eye. In this prospective, longitudinal, single-center study, nonabsorbable punctal plugs were inserted bilaterally into the lower punctum of 30 patients with moderate dry eye. Dry eye symptoms, fluorescein corneal staining, Schirmer I test, tear film break-up time, and safety were assessed in the more severely affected eye. Tear proteins at weeks 1 and 3 were quantified by iTRAQ relative to baseline preocclusion levels. Of 29 patients who completed the study, 23 (mean age 49.8 years) had sufficient tear samples for analysis. After 3 weeks, punctal occlusion significantly upregulated tear proteins, including glutathione synthase (mean of 1.6-fold, P = 0.01) and interleukin-1 receptor antagonist (1.7-fold, P = 0.032) and downregulated cholinergic receptor (neuronal) alpha-7 (0.79-fold, P = 0.039) and lymphocyte cytosolic protein-1 (0.66-fold, P = 0.012). Clustering analysis of global tear proteins revealed two clear profile changes; the first group of patients (cluster 1, n = 10) had a reduction in the inflammatory proteins (e.g., S100A8) and rise in lacrimal proteins supporting the ocular surface (e.g., lysozyme), whereas the second group (cluster 2, n = 13) had an increase in inflammatory proteins and a decrease in lacrimal proteins. Logistic regression analysis revealed that cluster 1 patients had significantly (P = 0.006) lower Schirmer scores at baseline (mean [standard deviation]: 4.3 [4.3] mm) than cluster 2 (6.8 [2.6] mm). Punctal plugs produced a beneficial pattern of tear protein change in patients with relatively low Schirmer scores within 3 weeks of punctal occlusion. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Document clustering methods, document cluster label disambiguation methods, document clustering apparatuses, and articles of manufacture

Science.gov (United States)

Sanfilippo, Antonio [Richland, WA; Calapristi, Augustin J [West Richland, WA; Crow, Vernon L [Richland, WA; Hetzler, Elizabeth G [Kennewick, WA; Turner, Alan E [Kennewick, WA

2009-12-22

Document clustering methods, document cluster label disambiguation methods, document clustering apparatuses, and articles of manufacture are described. In one aspect, a document clustering method includes providing a document set comprising a plurality of documents, providing a cluster comprising a subset of the documents of the document set, using a plurality of terms of the documents, providing a cluster label indicative of subject matter content of the documents of the cluster, wherein the cluster label comprises a plurality of word senses, and selecting one of the word senses of the cluster label.

Fe-S Clusters Emerging as Targets of Therapeutic Drugs

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Laurence Vernis

2017-01-01

Full Text Available Fe-S centers exhibit strong electronic plasticity, which is of importance for insuring fine redox tuning of protein biological properties. In accordance, Fe-S clusters are also highly sensitive to oxidation and can be very easily altered in vivo by different drugs, either directly or indirectly due to catabolic by-products, such as nitric oxide species (NOS or reactive oxygen species (ROS. In case of metal ions, Fe-S cluster alteration might be the result of metal liganding to the coordinating sulfur atoms, as suggested for copper. Several drugs presented through this review are either capable of direct interaction with Fe-S clusters or of secondary Fe-S clusters alteration following ROS or NOS production. Reactions leading to Fe-S cluster disruption are also reported. Due to the recent interest and progress in Fe-S biology, it is very likely that an increasing number of drugs already used in clinics will emerge as molecules interfering with Fe-S centers in the near future. Targeting Fe-S centers could also become a promising strategy for drug development.

The [Mo₆Cl14]2- Cluster is Biologically Secure and Has Anti-Rotavirus Activity In Vitro.

Science.gov (United States)

Rojas-Mancilla, Edgardo; Oyarce, Alexis; Verdugo, Viviana; Morales-Verdejo, Cesar; Echeverria, Cesar; Velásquez, Felipe; Chnaiderman, Jonas; Valiente-Echeverría, Fernando; Ramirez-Tagle, Rodrigo

2017-07-05

The molybdenum cluster [Mo₆Cl 14 ] 2- is a fluorescent component with potential for use in cell labelling and pharmacology. Biological safety and antiviral properties of the cluster are as yet unknown. Here, we show the effect of acute exposition of human cells and red blood cells to the molybdenum cluster and its interaction with proteins and antiviral activity in vitro. We measured cell viability of HepG2 and EA.hy926 cell lines exposed to increasing concentrations of the cluster (0.1 to 250 µM), by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) colorimetric assay. Hemolysis and morphological alterations of red blood cells, obtained from healthy donors, exposed to the cluster (10 to 200 µM) at 37 °C were analyzed. Furthermore, quenching of tryptophan residues of albumin was performed. Finally, plaque formation by rotavirus SA11 in MA104 cells treated with the cluster (100 to 300 µM) were analyzed. We found that all doses of the cluster showed similar cell viability, hemolysis, and morphology values, compared to control. Quenching of tryptophan residues of albumin suggests a protein-cluster complex formation. Finally, the cluster showed antiviral activity at 300 µM. These results indicate that the cluster [Mo₆Cl 14 ] 2- could be intravenously administered in animals at therapeutic doses for further in vivo studies and might be studied as an antiviral agent.

Interspecific variation of total seed protein in wild rice germplasm using SDS-Page

International Nuclear Information System (INIS)

Shah, S.M.A.; Hidayat-ur-Rahman; Abbasi, F.M.; Ashiq, M.; Rabbani, A.M.; Khan, I.A.; Shinwari, Z.K.; Shah, Z.

2011-01-01

Variation in seed protein of 14 wild rice species (Oryza spp.) along with cultivated rice species (O. sativa) was studied using sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE) to assess genetic diversity in the rice germplasm. SDS bands were scored as present (1) or absent (0) for protein sample of each genotype. On the basis of cluster analysis, four clusters were identified at a similarity level of 0.85. O. nivara, O. rufipogon and O. sativa with AA genomes constituted the first cluster. The second cluster comprised O. punctata of BB genome and wild rice species of CC genome i.e., O. rhizomatis and O. officinalis. However, it also contained O. barthii and O. glumaepatula of AA genome. O. australiensis with EE genome, and O. latifolia, O. alta and O. grandiglumis having CCDD genomes comprised the third cluster. The fourth cluster consisted of wild rice species, O. brachyantha with EE genome along with two other wild rice species, O. longistaminata and O. meridionalis of AA genome. Overall, on the basis of total seed protein, the grouping pattern of rice genotypes was mostly compatible with their genome status. The results of the present work depicted considerable interspecific genetic variation in the investigated germplasm for total seed protein. Moreover, the results obtained in this study also suggest that analysis of seed protein can also provide a better understanding of genetic affinity of the germplasm. (author)

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

Science.gov (United States)

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

A complex of Cas proteins 5, 6, and 7 is required for the biogenesis and stability of clustered regularly interspaced short palindromic repeats (crispr)-derived rnas (crrnas) in Haloferax volcanii.

Science.gov (United States)

Brendel, Jutta; Stoll, Britta; Lange, Sita J; Sharma, Kundan; Lenz, Christof; Stachler, Aris-Edda; Maier, Lisa-Katharina; Richter, Hagen; Nickel, Lisa; Schmitz, Ruth A; Randau, Lennart; Allers, Thorsten; Urlaub, Henning; Backofen, Rolf; Marchfelder, Anita

2014-03-07

The clustered regularly interspaced short palindromic repeats/CRISPR-associated (CRISPR-Cas) system is a prokaryotic defense mechanism against foreign genetic elements. A plethora of CRISPR-Cas versions exist, with more than 40 different Cas protein families and several different molecular approaches to fight the invading DNA. One of the key players in the system is the CRISPR-derived RNA (crRNA), which directs the invader-degrading Cas protein complex to the invader. The CRISPR-Cas types I and III use the Cas6 protein to generate mature crRNAs. Here, we show that the Cas6 protein is necessary for crRNA production but that additional Cas proteins that form a CRISPR-associated complex for antiviral defense (Cascade)-like complex are needed for crRNA stability in the CRISPR-Cas type I-B system in Haloferax volcanii in vivo. Deletion of the cas6 gene results in the loss of mature crRNAs and interference. However, cells that have the complete cas gene cluster (cas1-8b) removed and are transformed with the cas6 gene are not able to produce and stably maintain mature crRNAs. crRNA production and stability is rescued only if cas5, -6, and -7 are present. Mutational analysis of the cas6 gene reveals three amino acids (His-41, Gly-256, and Gly-258) that are essential for pre-crRNA cleavage, whereas the mutation of two amino acids (Ser-115 and Ser-224) leads to an increase of crRNA amounts. This is the first systematic in vivo analysis of Cas6 protein variants. In addition, we show that the H. volcanii I-B system contains a Cascade-like complex with a Cas7, Cas5, and Cas6 core that protects the crRNA.

Nuclear clustering - a cluster core model study

International Nuclear Information System (INIS)

Paul Selvi, G.; Nandhini, N.; Balasubramaniam, M.

2015-01-01

Nuclear clustering, similar to other clustering phenomenon in nature is a much warranted study, since it would help us in understanding the nature of binding of the nucleons inside the nucleus, closed shell behaviour when the system is highly deformed, dynamics and structure at extremes. Several models account for the clustering phenomenon of nuclei. We present in this work, a cluster core model study of nuclear clustering in light mass nuclei

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

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

OpenAIRE

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

2008-01-01

Motivation: 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. Application: 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 ex...

Predicting and validating protein interactions using network structure.

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Pao-Yang Chen

2008-07-01

Full Text Available Protein interactions play a vital part in the function of a cell. As experimental techniques for detection and validation of protein interactions are time consuming, there is a need for computational methods for this task. Protein interactions appear to form a network with a relatively high degree of local clustering. In this paper we exploit this clustering by suggesting a score based on triplets of observed protein interactions. The score utilises both protein characteristics and network properties. Our score based on triplets is shown to complement existing techniques for predicting protein interactions, outperforming them on data sets which display a high degree of clustering. The predicted interactions score highly against test measures for accuracy. Compared to a similar score derived from pairwise interactions only, the triplet score displays higher sensitivity and specificity. By looking at specific examples, we show how an experimental set of interactions can be enriched and validated. As part of this work we also examine the effect of different prior databases upon the accuracy of prediction and find that the interactions from the same kingdom give better results than from across kingdoms, suggesting that there may be fundamental differences between the networks. These results all emphasize that network structure is important and helps in the accurate prediction of protein interactions. The protein interaction data set and the program used in our analysis, and a list of predictions and validations, are available at http://www.stats.ox.ac.uk/bioinfo/resources/PredictingInteractions.

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.

Phasing and structure of bestrophin-1: a case study in the use of heavy-atom cluster compounds with multi-subunit transmembrane proteins

Energy Technology Data Exchange (ETDEWEB)

Dickson, Veronica Kane (Cambridge)

2016-03-01

The purification and three-dimensional crystallization of membrane proteins are commonly affected by a cumulation of pathologies that are less prevalent in their soluble counterparts. This may include severe anisotropy, poor spot shape, poor to moderate-resolution diffraction, crystal twinning, translational pseudo-symmetry and poor uptake of heavy atoms for derivatization. Such challenges must be circumvented by adaptations in the approach to crystallization and/or phasing. Here, an example of a protein that exhibited all of the above-mentioned complications is presented. Bestrophin-1 is a eukaryotic calcium-activated chloride channel, the structure of which was recently determined in complex with monoclonal antibody fragments using SAD phasing with tantalum bromide clusters (Ta₆Br₁₂·Br₂). Some of the obstacles to obtaining improved diffraction and phasing for this particular channel are discussed, as well as the approach and adaptations that were key to determining the structure.

Cluster fusion algorithm: application to Lennard-Jones clusters

DEFF Research Database (Denmark)

Solov'yov, Ilia; Solov'yov, Andrey V.; Greiner, Walter

2006-01-01

paths up to the cluster size of 150 atoms. We demonstrate that in this way all known global minima structures of the Lennard-Jones clusters can be found. Our method provides an efficient tool for the calculation and analysis of atomic cluster structure. With its use we justify the magic number sequence......We present a new general theoretical framework for modelling the cluster structure and apply it to description of the Lennard-Jones clusters. Starting from the initial tetrahedral cluster configuration, adding new atoms to the system and absorbing its energy at each step, we find cluster growing...... for the clusters of noble gas atoms and compare it with experimental observations. We report the striking correspondence of the peaks in the dependence of the second derivative of the binding energy per atom on cluster size calculated for the chain of the Lennard-Jones clusters based on the icosahedral symmetry...

Cluster fusion algorithm: application to Lennard-Jones clusters

DEFF Research Database (Denmark)

Solov'yov, Ilia; Solov'yov, Andrey V.; Greiner, Walter

2008-01-01

paths up to the cluster size of 150 atoms. We demonstrate that in this way all known global minima structures of the Lennard-Jones clusters can be found. Our method provides an efficient tool for the calculation and analysis of atomic cluster structure. With its use we justify the magic number sequence......We present a new general theoretical framework for modelling the cluster structure and apply it to description of the Lennard-Jones clusters. Starting from the initial tetrahedral cluster configuration, adding new atoms to the system and absorbing its energy at each step, we find cluster growing...... for the clusters of noble gas atoms and compare it with experimental observations. We report the striking correspondence of the peaks in the dependence of the second derivative of the binding energy per atom on cluster size calculated for the chain of the Lennard-Jones clusters based on the icosahedral symmetry...

NMR of proteins (4Fe-4S): structural properties and intramolecular electron transfer; RMN de proteines (4Fe-4S): proprietes structurales et transfert electronique intramoleculaire

Energy Technology Data Exchange (ETDEWEB)

Huber, J G

1996-10-17

NMR started to be applied to Fe-S proteins in the seventies. Its use has recently been enlarged as the problems arising from the paramagnetic polymetallic clusters ware overcome. Applications to [4Fe-4S] are presented herein. The information derived thereof deepens the understanding of the redox properties of these proteins which play a central role in the metabolism of bacterial cells. The secondary structure elements and the overall folding of Chromatium vinosum ferredoxin (Cv Fd) in solution have been established by NMR. The unique features of this sequence have been shown to fold as an {alpha} helix at the C-terminus and as a loop between two cysteines ligand of one cluster: these two parts localize in close proximity from one another. The interaction between nuclear and electronic spins is a source of additional structural information for (4Fe-AS] proteins. The conformation of the cysteine-ligands, as revealed by the Fe-(S{sub {gamma}}-C{sub {beta}}-H{sub {beta}})Cys dihedral angles, is related to the chemical shifts of the signals associated with the protons of these residues. The longitudinal relaxation times of the protons depend on their distance to the cluster. A quantitative relationship has been established and used to show that the solution structure of the high-potential ferredoxin from Cv differs significantly from the crystal structure around Phe-48. Both parameters (chemical shifts and longitudinal relaxation times) give also insight into the electronic and magnetic properties of the [4Fe-4S] clusters. The rate of intramolecular electron transfer between the two [4FE-4S] clusters of ferredoxins has been measured by NMR. It is far slower in the case of Cv Fd than for shorter ferredoxins. The difference may be associated with changes in the magnetic and/or electronic properties of one cluster. The strong paramagnetism of the [4Fe-4S] clusters, which originally limited the applicability of NMR to proteins containing these cofactors, has been proven

Ligand-protected gold clusters: the structure, synthesis and applications

Science.gov (United States)

Pichugina, D. A.; Kuz'menko, N. E.; Shestakov, A. F.

2015-11-01

Modern concepts of the structure and properties of atomic gold clusters protected by thiolate, selenolate, phosphine and phenylacetylene ligands are analyzed. Within the framework of the superatom theory, the 'divide and protect' approach and the structure rule, the stability and composition of a cluster are determined by the structure of the cluster core, the type of ligands and the total number of valence electrons. Methods of selective synthesis of gold clusters in solution and on the surface of inorganic composites based, in particular, on the reaction of Aun with RS, RSe, PhC≡C, Hal ligands or functional groups of proteins, on stabilization of clusters in cavities of the α-, β and γ-cyclodextrin molecules (Au15 and Au25) and on anchorage to a support surface (Au25/SiO2, Au20/C, Au10/FeOx) are reviewed. Problems in this field are also discussed. Among the methods for cluster structure prediction, particular attention is given to the theoretical approaches based on the density functional theory (DFT). The structures of a number of synthesized clusters are described using the results obtained by X-ray diffraction analysis and DFT calculations. A possible mechanism of formation of the SR(AuSR)n 'staple' units in the cluster shell is proposed. The structure and properties of bimetallic clusters MxAunLm (M=Pd, Pt, Ag, Cu) are discussed. The Pd or Pt atom is located at the centre of the cluster, whereas Ag and Cu atoms form bimetallic compounds in which the heteroatom is located on the surface of the cluster core or in the 'staple' units. The optical properties, fluorescence and luminescence of ligand-protected gold clusters originate from the quantum effects of the Au atoms in the cluster core and in the oligomeric SR(AuSR)x units in the cluster shell. Homogeneous and heterogeneous reactions catalyzed by atomic gold clusters are discussed in the context of the reaction mechanism and the nature of the active sites. The bibliography includes 345 references.

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

Science.gov (United States)

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

2015-01-01

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

Cluster-cluster correlations and constraints on the correlation hierarchy

Science.gov (United States)

Hamilton, A. J. S.; Gott, J. R., III

1988-01-01

The hypothesis that galaxies cluster around clusters at least as strongly as they cluster around galaxies imposes constraints on the hierarchy of correlation amplitudes in hierachical clustering models. The distributions which saturate these constraints are the Rayleigh-Levy random walk fractals proposed by Mandelbrot; for these fractal distributions cluster-cluster correlations are all identically equal to galaxy-galaxy correlations. If correlation amplitudes exceed the constraints, as is observed, then cluster-cluster correlations must exceed galaxy-galaxy correlations, as is observed.

A framework for classification of prokaryotic protein kinases.

Directory of Open Access Journals (Sweden)

Nidhi Tyagi

Full Text Available BACKGROUND: Overwhelming majority of the Serine/Threonine protein kinases identified by gleaning archaeal and eubacterial genomes could not be classified into any of the well known Hanks and Hunter subfamilies of protein kinases. This is owing to the development of Hanks and Hunter classification scheme based on eukaryotic protein kinases which are highly divergent from their prokaryotic homologues. A large dataset of prokaryotic Serine/Threonine protein kinases recognized from genomes of prokaryotes have been used to develop a classification framework for prokaryotic Ser/Thr protein kinases. METHODOLOGY/PRINCIPAL FINDINGS: We have used traditional sequence alignment and phylogenetic approaches and clustered the prokaryotic kinases which represent 72 subfamilies with at least 4 members in each. Such a clustering enables classification of prokaryotic Ser/Thr kinases and it can be used as a framework to classify newly identified prokaryotic Ser/Thr kinases. After series of searches in a comprehensive sequence database we recognized that 38 subfamilies of prokaryotic protein kinases are associated to a specific taxonomic level. For example 4, 6 and 3 subfamilies have been identified that are currently specific to phylum proteobacteria, cyanobacteria and actinobacteria respectively. Similarly subfamilies which are specific to an order, sub-order, class, family and genus have also been identified. In addition to these, we also identify organism-diverse subfamilies. Members of these clusters are from organisms of different taxonomic levels, such as archaea, bacteria, eukaryotes and viruses. CONCLUSION/SIGNIFICANCE: Interestingly, occurrence of several taxonomic level specific subfamilies of prokaryotic kinases contrasts with classification of eukaryotic protein kinases in which most of the popular subfamilies of eukaryotic protein kinases occur diversely in several eukaryotes. Many prokaryotic Ser/Thr kinases exhibit a wide variety of modular

CONSTRAINING CLUSTER PHYSICS WITH THE SHAPE OF X-RAY CLUSTERS: COMPARISON OF LOCAL X-RAY CLUSTERS VERSUS ΛCDM CLUSTERS

International Nuclear Information System (INIS)

Lau, Erwin T.; Nagai, Daisuke; Kravtsov, Andrey V.; Vikhlinin, Alexey; Zentner, Andrew R.

2012-01-01

Recent simulations of cluster formation have demonstrated that condensation of baryons into central galaxies during cluster formation can drive the shape of the gas distribution in galaxy clusters significantly rounder out to their virial radius. These simulations generally predict stellar fractions within cluster virial radii that are ∼2-3 times larger than the stellar masses deduced from observations. In this paper, we compare ellipticity profiles of simulated clusters performed with varying input physics (radiative cooling, star formation, and supernova feedback) to the cluster ellipticity profiles derived from Chandra and ROSAT observations, in an effort to constrain the fraction of gas that cools and condenses into the central galaxies within clusters. We find that local relaxed clusters have an average ellipticity of ε = 0.18 ± 0.05 in the radial range of 0.04 ≤ r/r 500 ≤ 1. At larger radii r > 0.1r 500 , the observed ellipticity profiles agree well with the predictions of non-radiative simulations. In contrast, the ellipticity profiles of simulated clusters that include dissipative gas physics deviate significantly from the observed ellipticity profiles at all radii. The dissipative simulations overpredict (underpredict) ellipticity in the inner (outer) regions of galaxy clusters. By comparing simulations with and without dissipative gas physics, we show that gas cooling causes the gas distribution to be more oblate in the central regions, but makes the outer gas distribution more spherical. We find that late-time gas cooling and star formation are responsible for the significantly oblate gas distributions in cluster cores, but the gas shapes outside of cluster cores are set primarily by baryon dissipation at high redshift (z ≥ 2). Our results indicate that the shapes of X-ray emitting gas in galaxy clusters, especially at large radii, can be used to place constraints on cluster gas physics, making it potential probes of the history of baryonic

CHIPMUNK: A Virtual Synthesizable Small-Molecule Library for Medicinal Chemistry, Exploitable for Protein-Protein Interaction Modulators.

Science.gov (United States)

Humbeck, Lina; Weigang, Sebastian; Schäfer, Till; Mutzel, Petra; Koch, Oliver

2018-03-20

A common issue during drug design and development is the discovery of novel scaffolds for protein targets. On the one hand the chemical space of purchasable compounds is rather limited; on the other hand artificially generated molecules suffer from a grave lack of accessibility in practice. Therefore, we generated a novel virtual library of small molecules which are synthesizable from purchasable educts, called CHIPMUNK (CHemically feasible In silico Public Molecular UNiverse Knowledge base). Altogether, CHIPMUNK covers over 95 million compounds and encompasses regions of the chemical space that are not covered by existing databases. The coverage of CHIPMUNK exceeds the chemical space spanned by the Lipinski rule of five to foster the exploration of novel and difficult target classes. The analysis of the generated property space reveals that CHIPMUNK is well suited for the design of protein-protein interaction inhibitors (PPIIs). Furthermore, a recently developed structural clustering algorithm (StruClus) for big data was used to partition the sub-libraries into meaningful subsets and assist scientists to process the large amount of data. These clustered subsets also contain the target space based on ChEMBL data which was included during clustering. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Complex of Cas Proteins 5, 6, and 7 Is Required for the Biogenesis and Stability of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-derived RNAs (crRNAs) in Haloferax volcanii*

Science.gov (United States)

Brendel, Jutta; Stoll, Britta; Lange, Sita J.; Sharma, Kundan; Lenz, Christof; Stachler, Aris-Edda; Maier, Lisa-Katharina; Richter, Hagen; Nickel, Lisa; Schmitz, Ruth A.; Randau, Lennart; Allers, Thorsten; Urlaub, Henning; Backofen, Rolf; Marchfelder, Anita

2014-01-01

The clustered regularly interspaced short palindromic repeats/CRISPR-associated (CRISPR-Cas) system is a prokaryotic defense mechanism against foreign genetic elements. A plethora of CRISPR-Cas versions exist, with more than 40 different Cas protein families and several different molecular approaches to fight the invading DNA. One of the key players in the system is the CRISPR-derived RNA (crRNA), which directs the invader-degrading Cas protein complex to the invader. The CRISPR-Cas types I and III use the Cas6 protein to generate mature crRNAs. Here, we show that the Cas6 protein is necessary for crRNA production but that additional Cas proteins that form a CRISPR-associated complex for antiviral defense (Cascade)-like complex are needed for crRNA stability in the CRISPR-Cas type I-B system in Haloferax volcanii in vivo. Deletion of the cas6 gene results in the loss of mature crRNAs and interference. However, cells that have the complete cas gene cluster (cas1–8b) removed and are transformed with the cas6 gene are not able to produce and stably maintain mature crRNAs. crRNA production and stability is rescued only if cas5, -6, and -7 are present. Mutational analysis of the cas6 gene reveals three amino acids (His-41, Gly-256, and Gly-258) that are essential for pre-crRNA cleavage, whereas the mutation of two amino acids (Ser-115 and Ser-224) leads to an increase of crRNA amounts. This is the first systematic in vivo analysis of Cas6 protein variants. In addition, we show that the H. volcanii I-B system contains a Cascade-like complex with a Cas7, Cas5, and Cas6 core that protects the crRNA. PMID:24459147

Molecular basis of the γ-aminobutyric acid A receptor α3 subunit interaction with the clustering protein gephyrin

DEFF Research Database (Denmark)

Tretter, Verena; Kerschner, Bernd; Milenkovic, Ivan

2011-01-01

The multifunctional scaffolding protein gephyrin is a key player in the formation of the postsynaptic scaffold at inhibitory synapses, clustering both inhibitory glycine receptors (GlyRs) and selected GABA(A) receptor (GABA(A)R) subtypes. We report a direct interaction between the GABA(A)R α3...... subunit and gephyrin, mapping reciprocal binding sites using mutagenesis, overlay, and yeast two-hybrid assays. This analysis reveals that critical determinants of this interaction are located in the motif FNIVGTTYPI in the GABA(A)R α3 M3-M4 domain and the motif SMDKAFITVL at the N terminus...... of the gephyrin E domain. GABA(A)R α3 gephyrin binding-site mutants were unable to co-localize with endogenous gephyrin in transfected hippocampal neurons, despite being able to traffic to the cell membrane and form functional benzodiazepine-responsive GABA(A)Rs in recombinant systems. Interestingly, motifs...

Three Pseudomonas putida FNR Family Proteins with Different Sensitivities to O2.

Science.gov (United States)

Ibrahim, Susan A; Crack, Jason C; Rolfe, Matthew D; Borrero-de Acuña, José Manuel; Thomson, Andrew J; Le Brun, Nick E; Schobert, Max; Stapleton, Melanie R; Green, Jeffrey

2015-07-03

The Escherichia coli fumarate-nitrate reduction regulator (FNR) protein is the paradigm for bacterial O2-sensing transcription factors. However, unlike E. coli, some bacterial species possess multiple FNR proteins that presumably have evolved to fulfill distinct roles. Here, three FNR proteins (ANR, PP_3233, and PP_3287) from a single bacterial species, Pseudomonas putida KT2440, have been analyzed. Under anaerobic conditions, all three proteins had spectral properties resembling those of [4Fe-4S] proteins. The reactivity of the ANR [4Fe-4S] cluster with O2 was similar to that of E. coli FNR, and during conversion to the apo-protein, via a [2Fe-2S] intermediate, cluster sulfur was retained. Like ANR, reconstituted PP_3233 and PP_3287 were converted to [2Fe-2S] forms when exposed to O2, but their [4Fe-4S] clusters reacted more slowly. Transcription from an FNR-dependent promoter with a consensus FNR-binding site in P. putida and E. coli strains expressing only one FNR protein was consistent with the in vitro responses to O2. Taken together, the experimental results suggest that the local environments of the iron-sulfur clusters in the different P. putida FNR proteins influence their reactivity with O2, such that ANR resembles E. coli FNR and is highly responsive to low concentrations of O2, whereas PP_3233 and PP_3287 have evolved to be less sensitive to O2. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

Cluster analysis of obesity and asthma phenotypes.

Directory of Open Access Journals (Sweden)

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

Platelet apoptosis by cld-induced glycoportein Ibα clustering

DEFF Research Database (Denmark)

van der Wal, Dianne E; Du, V X; Lo, KS

2010-01-01

Summary Background:  Cold-storage of platelets followed by rewarming induces changes in Glycoprotein (GP) Ibα-distribution indicative of receptor clustering and initiates thromboxane A2-formation. GPIbα is associated with 14-3-3 proteins, which contribute to GPIbα-signaling and in nucleated cells...

Convex Clustering: An Attractive Alternative to Hierarchical Clustering

Science.gov (United States)

Chen, Gary K.; Chi, Eric C.; Ranola, John Michael O.; Lange, Kenneth

2015-01-01

The primary goal in cluster analysis is to discover natural groupings of objects. The field of cluster analysis is crowded with diverse methods that make special assumptions about data and address different scientific aims. Despite its shortcomings in accuracy, hierarchical clustering is the dominant clustering method in bioinformatics. Biologists find the trees constructed by hierarchical clustering visually appealing and in tune with their evolutionary perspective. Hierarchical clustering operates on multiple scales simultaneously. This is essential, for instance, in transcriptome data, where one may be interested in making qualitative inferences about how lower-order relationships like gene modules lead to higher-order relationships like pathways or biological processes. The recently developed method of convex clustering preserves the visual appeal of hierarchical clustering while ameliorating its propensity to make false inferences in the presence of outliers and noise. The solution paths generated by convex clustering reveal relationships between clusters that are hidden by static methods such as k-means clustering. The current paper derives and tests a novel proximal distance algorithm for minimizing the objective function of convex clustering. The algorithm separates parameters, accommodates missing data, and supports prior information on relationships. Our program CONVEXCLUSTER incorporating the algorithm is implemented on ATI and nVidia graphics processing units (GPUs) for maximal speed. Several biological examples illustrate the strengths of convex clustering and the ability of the proximal distance algorithm to handle high-dimensional problems. CONVEXCLUSTER can be freely downloaded from the UCLA Human Genetics web site at http://www.genetics.ucla.edu/software/ PMID:25965340

The role of mitochondria in cellular iron-sulfur protein biogenesis and iron metabolism.

Science.gov (United States)

Lill, Roland; Hoffmann, Bastian; Molik, Sabine; Pierik, Antonio J; Rietzschel, Nicole; Stehling, Oliver; Uzarska, Marta A; Webert, Holger; Wilbrecht, Claudia; Mühlenhoff, Ulrich

2012-09-01

Mitochondria play a key role in iron metabolism in that they synthesize heme, assemble iron-sulfur (Fe/S) proteins, and participate in cellular iron regulation. Here, we review the latter two topics and their intimate connection. The mitochondrial Fe/S cluster (ISC) assembly machinery consists of 17 proteins that operate in three major steps of the maturation process. First, the cysteine desulfurase complex Nfs1-Isd11 as the sulfur donor cooperates with ferredoxin-ferredoxin reductase acting as an electron transfer chain, and frataxin to synthesize an [2Fe-2S] cluster on the scaffold protein Isu1. Second, the cluster is released from Isu1 and transferred toward apoproteins with the help of a dedicated Hsp70 chaperone system and the glutaredoxin Grx5. Finally, various specialized ISC components assist in the generation of [4Fe-4S] clusters and cluster insertion into specific target apoproteins. Functional defects of the core ISC assembly machinery are signaled to cytosolic or nuclear iron regulatory systems resulting in increased cellular iron acquisition and mitochondrial iron accumulation. In fungi, regulation is achieved by iron-responsive transcription factors controlling the expression of genes involved in iron uptake and intracellular distribution. They are assisted by cytosolic multidomain glutaredoxins which use a bound Fe/S cluster as iron sensor and additionally perform an essential role in intracellular iron delivery to target metalloproteins. In mammalian cells, the iron regulatory proteins IRP1, an Fe/S protein, and IRP2 act in a post-transcriptional fashion to adjust the cellular needs for iron. Thus, Fe/S protein biogenesis and cellular iron metabolism are tightly linked to coordinate iron supply and utilization. This article is part of a Special Issue entitled: Cell Biology of Metals. Copyright © 2012 Elsevier B.V. All rights reserved.

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

NARCIS (Netherlands)

Bader, A.N.; Hoetzl, S.; Hofman, E.G.; Voortman, J.; van Bergen en Henegouwen, P.M.P.; van Meer, G.; Gerritsen, H.C.

2010-01-01

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

Cluster management.

Science.gov (United States)

Katz, R

1992-11-01

Cluster management is a management model that fosters decentralization of management, develops leadership potential of staff, and creates ownership of unit-based goals. Unlike shared governance models, there is no formal structure created by committees and it is less threatening for managers. There are two parts to the cluster management model. One is the formation of cluster groups, consisting of all staff and facilitated by a cluster leader. The cluster groups function for communication and problem-solving. The second part of the cluster management model is the creation of task forces. These task forces are designed to work on short-term goals, usually in response to solving one of the unit's goals. Sometimes the task forces are used for quality improvement or system problems. Clusters are groups of not more than five or six staff members, facilitated by a cluster leader. A cluster is made up of individuals who work the same shift. For example, people with job titles who work days would be in a cluster. There would be registered nurses, licensed practical nurses, nursing assistants, and unit clerks in the cluster. The cluster leader is chosen by the manager based on certain criteria and is trained for this specialized role. The concept of cluster management, criteria for choosing leaders, training for leaders, using cluster groups to solve quality improvement issues, and the learning process necessary for manager support are described.

Protein domain organisation: adding order.

Science.gov (United States)

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

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.

Lipid-protein interaction induced domains: Kinetics and conformational changes in multicomponent vesicles

Science.gov (United States)

Sreeja, K. K.; Sunil Kumar, P. B.

2018-04-01

The spatio-temporal organization of proteins and the associated morphological changes in membranes are of importance in cell signaling. Several mechanisms that promote the aggregation of proteins at low cell surface concentrations have been investigated in the past. We show, using Monte Carlo simulations, that the affinity of proteins for specific lipids can hasten their aggregation kinetics. The lipid membrane is modeled as a dynamically triangulated surface with the proteins defined as in-plane fields at the vertices. We show that, even at low protein concentrations, strong lipid-protein interactions can result in large protein clusters indicating a route to lipid mediated signal amplification. At high protein concentrations, the domains form buds similar to that seen in lipid-lipid interaction induced phase separation. Protein interaction induced domain budding is suppressed when proteins act as anisotropic inclusions and exhibit nematic orientational order. The kinetics of protein clustering and resulting conformational changes are shown to be significantly different for the isotropic and anisotropic curvature inducing proteins.

Nonclassical nucleation pathways in protein crystallization.

Science.gov (United States)

Zhang, Fajun

2017-11-08

Classical nucleation theory (CNT), which was established about 90 years ago, has been very successful in many research fields, and continues to be the most commonly used theory in describing the nucleation process. For a fluid-to-solid phase transition, CNT states that the solute molecules in a supersaturated solution reversibly form small clusters. Once the cluster size reaches a critical value, it becomes thermodynamically stable and favored for further growth. One of the most important assumptions of CNT is that the nucleation process is described by one reaction coordinate and all order parameters proceed simultaneously. Recent studies in experiments, computer simulations and theory have revealed nonclassical features in the early stage of nucleation. In particular, the decoupling of order parameters involved during a fluid-to-solid transition leads to the so-called two-step nucleation mechanism, in which a metastable intermediate phase (MIP) exists between the initial supersaturated solution and the final crystals. Depending on the exact free energy landscapes, the MIPs can be a high density liquid phase, mesoscopic clusters, or a pre-ordered state. In this review, we focus on the studies of nonclassical pathways in protein crystallization and discuss the applications of the various scenarios of two-step nucleation theory. In particular, we focus on protein solutions in the presence of multivalent salts, which serve as a model protein system to study the nucleation pathways. We wish to point out the unique features of proteins as model systems for further studies.

Nonclassical nucleation pathways in protein crystallization

Science.gov (United States)

Zhang, Fajun

2017-11-01

Classical nucleation theory (CNT), which was established about 90 years ago, has been very successful in many research fields, and continues to be the most commonly used theory in describing the nucleation process. For a fluid-to-solid phase transition, CNT states that the solute molecules in a supersaturated solution reversibly form small clusters. Once the cluster size reaches a critical value, it becomes thermodynamically stable and favored for further growth. One of the most important assumptions of CNT is that the nucleation process is described by one reaction coordinate and all order parameters proceed simultaneously. Recent studies in experiments, computer simulations and theory have revealed nonclassical features in the early stage of nucleation. In particular, the decoupling of order parameters involved during a fluid-to-solid transition leads to the so-called two-step nucleation mechanism, in which a metastable intermediate phase (MIP) exists between the initial supersaturated solution and the final crystals. Depending on the exact free energy landscapes, the MIPs can be a high density liquid phase, mesoscopic clusters, or a pre-ordered state. In this review, we focus on the studies of nonclassical pathways in protein crystallization and discuss the applications of the various scenarios of two-step nucleation theory. In particular, we focus on protein solutions in the presence of multivalent salts, which serve as a model protein system to study the nucleation pathways. We wish to point out the unique features of proteins as model systems for further studies.

Electrospray Ionization Mass Spectrometry: From Cluster Ions to Toxic metal Ions in Biology

Energy Technology Data Exchange (ETDEWEB)

Lentz, Nicholas B. [Iowa State Univ., Ames, IA (United States)

2007-01-01

This dissertation focused on using electrospray ionization mass spectrometry to study cluster ions and toxic metal ions in biology. In Chapter 2, it was shown that primary, secondary and quarternary amines exhibit different clustering characteristics under identical instrument conditions. Carbon chain length also played a role in cluster ion formation. In Chapters 3 and 4, the effects of solvent types/ratios and various instrumental parameters on cluster ion formation were examined. It was found that instrument interface design also plays a critical role in the cluster ion distribution seen in the mass spectrum. In Chapter 5, ESI-MS was used to investigate toxic metal binding to the [Gln¹¹]-amyloid β-protein fragment (1-16). Pb and Cd bound stronger than Zn, even in the presence of excess Zn. Hg bound weaker than Zn. There are endless options for future work on cluster ions. Any molecule that is poorly ionized in positive ion mode can potentially show an increase in ionization efficiency if an appropriate anion is used to produce a net negative charge. It is possible that drug protein or drug/DNA complexes can also be stabilized by adding counter-ions. This would preserve the solution characteristics of the complex in the gas phase. Once in the gas phase, CID could determine the drug binding location on the biomolecule. There are many research projects regarding toxic metals in biology that have yet to be investigated or even discovered. This is an area of research with an almost endless future because of the changing dynamics of biological systems. What is deemed safe today may show toxic effects in the future. Evolutionary changes in protein structures may render them more susceptible to toxic metal binding. As the understanding of toxicity evolves, so does the demand for new toxic metal research. New instrumentation designs and software make it possible to perform research that could not be done in the past. What was undetectable yesterday will

Lifting to cluster-tilting objects in higher cluster categories

OpenAIRE

Liu, Pin

2008-01-01

In this note, we consider the $d$-cluster-tilted algebras, the endomorphism algebras of $d$-cluster-tilting objects in $d$-cluster categories. We show that a tilting module over such an algebra lifts to a $d$-cluster-tilting object in this $d$-cluster category.

Domain organizations of modular extracellular matrix proteins and their evolution.

Science.gov (United States)

Engel, J

1996-11-01

Multidomain proteins which are composed of modular units are a rather recent invention of evolution. Domains are defined as autonomously folding regions of a protein, and many of them are similar in sequence and structure, indicating common ancestry. Their modular nature is emphasized by frequent repetitions in identical or in different proteins and by a large number of different combinations with other domains. The extracellular matrix is perhaps the largest biological system composed of modular mosaic proteins, and its astonishing complexity and diversity are based on them. A cluster of minireviews on modular proteins is being published in Matrix Biology. These deal with the evolution of modular proteins, the three-dimensional structure of domains and the ways in which these interact in a multidomain protein. They discuss structure-function relationships in calcium binding domains, collagen helices, alpha-helical coiled-coil domains and C-lectins. The present minireview is focused on some general aspects and serves as an introduction to the cluster.

Data Clustering

Science.gov (United States)

Wagstaff, Kiri L.

2012-03-01

On obtaining a new data set, the researcher is immediately faced with the challenge of obtaining a high-level understanding from the observations. What does a typical item look like? What are the dominant trends? How many distinct groups are included in the data set, and how is each one characterized? Which observable values are common, and which rarely occur? Which items stand out as anomalies or outliers from the rest of the data? This challenge is exacerbated by the steady growth in data set size [11] as new instruments push into new frontiers of parameter space, via improvements in temporal, spatial, and spectral resolution, or by the desire to "fuse" observations from different modalities and instruments into a larger-picture understanding of the same underlying phenomenon. Data clustering algorithms provide a variety of solutions for this task. They can generate summaries, locate outliers, compress data, identify dense or sparse regions of feature space, and build data models. It is useful to note up front that "clusters" in this context refer to groups of items within some descriptive feature space, not (necessarily) to "galaxy clusters" which are dense regions in physical space. The goal of this chapter is to survey a variety of data clustering methods, with an eye toward their applicability to astronomical data analysis. In addition to improving the individual researcher’s understanding of a given data set, clustering has led directly to scientific advances, such as the discovery of new subclasses of stars [14] and gamma-ray bursts (GRBs) [38]. All clustering algorithms seek to identify groups within a data set that reflect some observed, quantifiable structure. Clustering is traditionally an unsupervised approach to data analysis, in the sense that it operates without any direct guidance about which items should be assigned to which clusters. There has been a recent trend in the clustering literature toward supporting semisupervised or constrained

Bacillus sp.CDB3 isolated from cattle dip-sites possesses two ars gene clusters

Institute of Scientific and Technical Information of China (English)

Somanath Bhat; Xi Luo; Zhiqiang Xu; Lixia Liu; Ren Zhang

2011-01-01

Contamination of soil and water by arsenic is a global problem.In Australia, the dipping of cattle in arsenic-containing solution to control cattle ticks in last centenary has left many sites heavily contaminated with arsenic and other toxicants.We had previously isolated five soil bacterial strains (CDB1-5) highly resistant to arsenic.To understand the resistance mechanism, molecular studies have been carried out.Two chromosome-encoded arsenic resistance (ars) gene clusters have been cloned from CDB3 (Bacillus sp.).They both function in Escherichia coli and cluster 1 exerts a much higher resistance to the toxic metalloid.Cluster 2 is smaller possessing four open reading frames (ORFs) arsRorf2BC, similar to that identified in Bacillus subtilis Skin element.Among the eight ORFs in cluster 1 five are analogs of common ars genes found in other bacteria, however, organized in a unique order arsRBCDA instead of arsRDABC.Three other putative genes are located directly downstream and designated as arsTIP based on the homologies of their theoretical translation sequences respectively to thioredoxin reductases, iron-sulphur cluster proteins and protein phosphatases.The latter two are novel of any known ars operons.The arsD gene from Bacillus species was cloned for the first time and the predict protein differs from the well studied E.coli ArsD by lacking two pairs of C-terrninal cysteine residues.Its functional involvement in arsenic resistance has been confirmed by a deletion experiment.There exists also an inverted repeat in the intergenic region between arsC and arsD implying some unknown transcription regulation.

Cell-free H-cluster synthesis and [FeFe] hydrogenase activation: all five CO and CN⁻ ligands derive from tyrosine.

Directory of Open Access Journals (Sweden)

Jon M Kuchenreuther

Full Text Available [FeFe] hydrogenases are promising catalysts for producing hydrogen as a sustainable fuel and chemical feedstock, and they also serve as paradigms for biomimetic hydrogen-evolving compounds. Hydrogen formation is catalyzed by the H-cluster, a unique iron-based cofactor requiring three carbon monoxide (CO and two cyanide (CN⁻ ligands as well as a dithiolate bridge. Three accessory proteins (HydE, HydF, and HydG are presumably responsible for assembling and installing the H-cluster, yet their precise roles and the biosynthetic pathway have yet to be fully defined. In this report, we describe effective cell-free methods for investigating H-cluster synthesis and [FeFe] hydrogenase activation. Combining isotopic labeling with FTIR spectroscopy, we conclusively show that each of the CO and CN⁻ ligands derive respectively from the carboxylate and amino substituents of tyrosine. Such in vitro systems with reconstituted pathways comprise a versatile approach for studying biosynthetic mechanisms, and this work marks a significant step towards an understanding of both the protein-protein interactions and complex reactions required for H-cluster assembly and hydrogenase maturation.

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

Directory of Open Access Journals (Sweden)

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.

Cell surface clustering of Cadherin adhesion complex induced by antibody coated beads

Institute of Scientific and Technical Information of China (English)

无

2000-01-01

Cadherin receptors mediate cell-cell adhesion, signal transduction and assembly of cytoskeletons. How a single transmembrane molecule Cadherin can be involved in multiple functions through modulating its binding activities with many membrane adhesion molecules and cytoskeletal components is an unanswered question which can be elucidated by clues from bead experiments. Human lung cells expressing N-Cadherin were examined. After co-incubation with anti-N-Cadherin monoclonal antibody coated beads, cell surface clustering of N-Cadherin was induced. Immunofluorescent detection demonstrated that in addition to Cadherin, β-Catenin, α-Catenin, α-Actinin and Actin fluorescence also aggregated respectively at the membrane site of bead attachment. Myosin heavy chain (MHC), another major component of Actin cytoskeleton, did not aggregate at the membrane site of bead attachment. Adhesion unrelated protein Con A and polylysine conjugated beads did not induce the clustering of adhesion molecules. It is indicated that the Cadherin/Catenins/α-Actinin/Actin complex is formed at Cadherin mediated cell adherens junction; occupancy and cell surface clustering of Cadherin is crucial for the formation of Cadherin adhesion protein complexes.

Inhibition of protein aggregation: supramolecular assemblies of arginine hold the key.

Directory of Open Access Journals (Sweden)

Utpal Das

Full Text Available BACKGROUND: Aggregation of unfolded proteins occurs mainly through the exposed hydrophobic surfaces. Any mechanism of inhibition of this aggregation should explain the prevention of these hydrophobic interactions. Though arginine is prevalently used as an aggregation suppressor, its mechanism of action is not clearly understood. We propose a mechanism based on the hydrophobic interactions of arginine. METHODOLOGY: We have analyzed arginine solution for its hydrotropic effect by pyrene solubility and the presence of hydrophobic environment by 1-anilino-8-naphthalene sulfonic acid fluorescence. Mass spectroscopic analyses show that arginine forms molecular clusters in the gas phase and the cluster composition is dependent on the solution conditions. Light scattering studies indicate that arginine exists as clusters in solution. In the presence of arginine, the reverse phase chromatographic elution profile of Alzheimer's amyloid beta 1-42 (Abeta(1-42 peptide is modified. Changes in the hydrodynamic volume of Abeta(1-42 in the presence of arginine measured by size exclusion chromatography show that arginine binds to Abeta(1-42. Arginine increases the solubility of Abeta(1-42 peptide in aqueous medium. It decreases the aggregation of Abeta(1-42 as observed by atomic force microscopy. CONCLUSIONS: Based on our experimental results we propose that molecular clusters of arginine in aqueous solutions display a hydrophobic surface by the alignment of its three methylene groups. The hydrophobic surfaces present on the proteins interact with the hydrophobic surface presented by the arginine clusters. The masking of hydrophobic surface inhibits protein-protein aggregation. This mechanism is also responsible for the hydrotropic effect of arginine on various compounds. It is also explained why other amino acids fail to inhibit the protein aggregation.

Activation of protein kinase A and clustering of cell surface receptors by N-methyl-N'-nitro-N-nitrosoguanidine are independent of genomic DNA damage

Energy Technology Data Exchange (ETDEWEB)

Wang Zheng; Wang Guliang; Yang Jun; Guo Lei; Yu Yingnian

2003-07-25

Alkylating agent N-methyl-N'-nitro-N-nitrosoguanidine (MNNG) induces cellular stress leading to chromosomal aberrations, mutations and cell death. Previous reports from our laboratory have shown that low concentration of MNNG induces untargeted mutation (UTM), which occurs on intact DNA in mammalian cells through changes in gene expression profile. It also causes the activation of cAMP-protein kinase A (PKA) and up-regulation of POL-{beta}, which is demonstrated to play a role in DNA repair system. In order to find out the possible initial signal involved in UTM, we try to investigate whether the activation of PKA-CREB signal pathway is closely related to DNA damage. Our data shows that the treatment of low concentration MNNG (0.2 {mu}M) activates PKA-CREB pathway in a comparable level both in a nuclear and enucleated cell system. And similar to the cell response caused by UV, the clustering of cell surface receptors of epidermal growth factor (EGF) and tumor necrosis factor {alpha} (TNF{alpha}) was also observed in cells exposed to MNNG. It was further demonstrated that the clustering of the surface receptors is independent of the genomic DNA damage, as this phenomenon was also observed in enucleated cells. These observations indicate that the initiation of signal cascades induced by low concentration of MNNG might be associated with its interaction with cell surface receptors and/or direct activation of related signal proteins but not its DNA damaging property.

Dense Fe cluster-assembled films by energetic cluster deposition

International Nuclear Information System (INIS)

Peng, D.L.; Yamada, H.; Hihara, T.; Uchida, T.; Sumiyama, K.

2004-01-01

High-density Fe cluster-assembled films were produced at room temperature by an energetic cluster deposition. Though cluster-assemblies are usually sooty and porous, the present Fe cluster-assembled films are lustrous and dense, revealing a soft magnetic behavior. Size-monodispersed Fe clusters with the mean cluster size d=9 nm were synthesized using a plasma-gas-condensation technique. Ionized clusters are accelerated electrically and deposited onto the substrate together with neutral clusters from the same cluster source. Packing fraction and saturation magnetic flux density increase rapidly and magnetic coercivity decreases remarkably with increasing acceleration voltage. The Fe cluster-assembled film obtained at the acceleration voltage of -20 kV has a packing fraction of 0.86±0.03, saturation magnetic flux density of 1.78±0.05 Wb/m 2 , and coercivity value smaller than 80 A/m. The resistivity at room temperature is ten times larger than that of bulk Fe metal

Nutrient Shielding in Clusters of Cells

Science.gov (United States)

Lavrentovich, Maxim O.; Koschwanez, John H.; Nelson, David R.

2014-01-01

Cellular nutrient consumption is influenced by both the nutrient uptake kinetics of an individual cell and the cells’ spatial arrangement. Large cell clusters or colonies have inhibited growth at the cluster's center due to the shielding of nutrients by the cells closer to the surface. We develop an effective medium theory that predicts a thickness ℓ of the outer shell of cells in the cluster that receives enough nutrient to grow. The cells are treated as partially absorbing identical spherical nutrient sinks, and we identify a dimensionless parameter ν that characterizes the absorption strength of each cell. The parameter ν can vary over many orders of magnitude between different cell types, ranging from bacteria and yeast to human tissue. The thickness ℓ decreases with increasing ν, increasing cell volume fraction ϕ, and decreasing ambient nutrient concentration ψ∞. The theoretical results are compared with numerical simulations and experiments. In the latter studies, colonies of budding yeast, Saccharomyces cerevisiae, are grown on glucose media and imaged under a confocal microscope. We measure the growth inside the colonies via a fluorescent protein reporter and compare the experimental and theoretical results for the thickness ℓ. PMID:23848711

Cluster Physics with Merging Galaxy Clusters

Directory of Open Access Journals (Sweden)

Sandor M. Molnar

2016-02-01

Full Text Available Collisions between galaxy clusters provide a unique opportunity to study matter in a parameter space which cannot be explored in our laboratories on Earth. In the standard LCDM model, where the total density is dominated by the cosmological constant ($Lambda$ and the matter density by cold dark matter (CDM, structure formation is hierarchical, and clusters grow mostly by merging.Mergers of two massive clusters are the most energetic events in the universe after the Big Bang,hence they provide a unique laboratory to study cluster physics.The two main mass components in clusters behave differently during collisions:the dark matter is nearly collisionless, responding only to gravity, while the gas is subject to pressure forces and dissipation, and shocks and turbulenceare developed during collisions. In the present contribution we review the different methods used to derive the physical properties of merging clusters. Different physical processes leave their signatures on different wavelengths, thusour review is based on a multifrequency analysis. In principle, the best way to analyze multifrequency observations of merging clustersis to model them using N-body/HYDRO numerical simulations. We discuss the results of such detailed analyses.New high spatial and spectral resolution ground and space based telescopeswill come online in the near future. Motivated by these new opportunities,we briefly discuss methods which will be feasible in the near future in studying merging clusters.

Transcriptional analysis of ESAT-6 cluster 3 in Mycobacterium smegmatis

Directory of Open Access Journals (Sweden)

Riccardi Giovanna

2009-03-01

Full Text Available Abstract Background The ESAT-6 (early secreted antigenic target, 6 kDa family collects small mycobacterial proteins secreted by Mycobacterium tuberculosis, particularly in the early phase of growth. There are 23 ESAT-6 family members in M. tuberculosis H37Rv. In a previous work, we identified the Zur- dependent regulation of five proteins of the ESAT-6/CFP-10 family (esxG, esxH, esxQ, esxR, and esxS. esxG and esxH are part of ESAT-6 cluster 3, whose expression was already known to be induced by iron starvation. Results In this research, we performed EMSA experiments and transcriptional analysis of ESAT-6 cluster 3 in Mycobacterium smegmatis (msmeg0615-msmeg0625 and M. tuberculosis. In contrast to what we had observed in M. tuberculosis, we found that in M. smegmatis ESAT-6 cluster 3 responds only to iron and not to zinc. In both organisms we identified an internal promoter, a finding which suggests the presence of two transcriptional units and, by consequence, a differential expression of cluster 3 genes. We compared the expression of msmeg0615 and msmeg0620 in different growth and stress conditions by means of relative quantitative PCR. The expression of msmeg0615 and msmeg0620 genes was essentially similar; they appeared to be repressed in most of the tested conditions, with the exception of acid stress (pH 4.2 where msmeg0615 was about 4-fold induced, while msmeg0620 was repressed. Analysis revealed that in acid stress conditions M. tuberculosis rv0282 gene was 3-fold induced too, while rv0287 induction was almost insignificant. Conclusion In contrast with what has been reported for M. tuberculosis, our results suggest that in M. smegmatis only IdeR-dependent regulation is retained, while zinc has no effect on gene expression. The role of cluster 3 in M. tuberculosis virulence is still to be defined; however, iron- and zinc-dependent expression strongly suggests that cluster 3 is highly expressed in the infective process, and that the cluster

Ligand-protected gold clusters: the structure, synthesis and applications

International Nuclear Information System (INIS)

Pichugina, D A; Kuz'menko, N E; Shestakov, A F

2015-01-01

Modern concepts of the structure and properties of atomic gold clusters protected by thiolate, selenolate, phosphine and phenylacetylene ligands are analyzed. Within the framework of the superatom theory, the 'divide and protect' approach and the structure rule, the stability and composition of a cluster are determined by the structure of the cluster core, the type of ligands and the total number of valence electrons. Methods of selective synthesis of gold clusters in solution and on the surface of inorganic composites based, in particular, on the reaction of Au n with RS, RSe, PhC≡C, Hal ligands or functional groups of proteins, on stabilization of clusters in cavities of the α-, β and γ-cyclodextrin molecules (Au 15 and Au 25 ) and on anchorage to a support surface (Au 25 /SiO 2 , Au 20 /C, Au 10 /FeO x ) are reviewed. Problems in this field are also discussed. Among the methods for cluster structure prediction, particular attention is given to the theoretical approaches based on the density functional theory (DFT). The structures of a number of synthesized clusters are described using the results obtained by X-ray diffraction analysis and DFT calculations. A possible mechanism of formation of the SR(AuSR) n 'staple' units in the cluster shell is proposed. The structure and properties of bimetallic clusters M x Au n L m (M=Pd, Pt, Ag, Cu) are discussed. The Pd or Pt atom is located at the centre of the cluster, whereas Ag and Cu atoms form bimetallic compounds in which the heteroatom is located on the surface of the cluster core or in the 'staple' units. The optical properties, fluorescence and luminescence of ligand-protected gold clusters originate from the quantum effects of the Au atoms in the cluster core and in the oligomeric SR(AuSR) x units in the cluster shell. Homogeneous and heterogeneous reactions catalyzed by atomic gold clusters are discussed in the context of the reaction mechanism and the nature of the active

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

Science.gov (United States)

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...

Essential multimeric enzymes in kinetoplastid parasites: A host of potentially druggable protein-protein interactions.

Science.gov (United States)

Wachsmuth, Leah M; Johnson, Meredith G; Gavenonis, Jason

2017-06-01

Parasitic diseases caused by kinetoplastid parasites of the genera Trypanosoma and Leishmania are an urgent public health crisis in the developing world. These closely related species possess a number of multimeric enzymes in highly conserved pathways involved in vital functions, such as redox homeostasis and nucleotide synthesis. Computational alanine scanning of these protein-protein interfaces has revealed a host of potentially ligandable sites on several established and emerging anti-parasitic drug targets. Analysis of interfaces with multiple clustered hotspots has suggested several potentially inhibitable protein-protein interactions that may have been overlooked by previous large-scale analyses focusing solely on secondary structure. These protein-protein interactions provide a promising lead for the development of new peptide and macrocycle inhibitors of these enzymes.

Hemoglobin–Albumin Cluster Incorporating a Pt Nanoparticle: Artificial O2 Carrier with Antioxidant Activities

Science.gov (United States)

Hosaka, Hitomi; Haruki, Risa; Yamada, Kana; Böttcher, Christoph; Komatsu, Teruyuki

2014-01-01

A covalent core–shell structured protein cluster composed of hemoglobin (Hb) at the center and human serum albumins (HSA) at the periphery, Hb-HSAm, is an artificial O2 carrier that can function as a red blood cell substitute. Here we described the preparation of a novel Hb-HSA3 cluster with antioxidant activities and its O2 complex stable in aqueous H2O2 solution. We used an approach of incorporating a Pt nanoparticle (PtNP) into the exterior HSA unit of the cluster. A citrate reduced PtNP (1.8 nm diameter) was bound tightly within the cleft of free HSA with a binding constant (K) of 1.1×107 M−1, generating a stable HSA-PtNP complex. This platinated protein showed high catalytic activities for dismutations of superoxide radical anions (O2 •–) and hydrogen peroxide (H2O2), i.e., superoxide dismutase and catalase activities. Also, Hb-HSA3 captured PtNP into the external albumin unit (K = 1.1×107 M−1), yielding an Hb-HSA3(PtNP) cluster. The association of PtNP caused no alteration of the protein surface net charge and O2 binding affinity. The peripheral HSA-PtNP shell prevents oxidation of the core Hb, which enables the formation of an extremely stable O2 complex, even in H2O2 solution. PMID:25310133

Enhanced conformational sampling to visualize a free-energy landscape of protein complex formation.

Science.gov (United States)

Iida, Shinji; Nakamura, Haruki; Higo, Junichi

2016-06-15

We introduce various, recently developed, generalized ensemble methods, which are useful to sample various molecular configurations emerging in the process of protein-protein or protein-ligand binding. The methods introduced here are those that have been or will be applied to biomolecular binding, where the biomolecules are treated as flexible molecules expressed by an all-atom model in an explicit solvent. Sampling produces an ensemble of conformations (snapshots) that are thermodynamically probable at room temperature. Then, projection of those conformations to an abstract low-dimensional space generates a free-energy landscape. As an example, we show a landscape of homo-dimer formation of an endothelin-1-like molecule computed using a generalized ensemble method. The lowest free-energy cluster at room temperature coincided precisely with the experimentally determined complex structure. Two minor clusters were also found in the landscape, which were largely different from the native complex form. Although those clusters were isolated at room temperature, with rising temperature a pathway emerged linking the lowest and second-lowest free-energy clusters, and a further temperature increment connected all the clusters. This exemplifies that the generalized ensemble method is a powerful tool for computing the free-energy landscape, by which one can discuss the thermodynamic stability of clusters and the temperature dependence of the cluster networks. © 2016 The Author(s).

Crystal Structure of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-associated Csn2 Protein Revealed Ca[superscript 2+]-dependent Double-stranded DNA Binding Activity

Energy Technology Data Exchange (ETDEWEB)

Nam, Ki Hyun; Kurinov, Igor; Ke, Ailong (Cornell); (NWU)

2012-05-22

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 {angstrom} tetrameric ring structure. The inner circle of the Csn2 tetrameric ring is {approx}26 {angstrom} wide and populated with conserved lysine residues poised for nonspecific interactions with ds-DNA. Each Csn2 protomer contains an {alpha}/{beta} domain and an {alpha}-helical domain; significant hinge motion was observed between these two domains. Ca{sup 2+} was located at strategic positions in the oligomerization interface. We further showed that removal of Ca{sup 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{sup 2+} ions.

Are clusters of dietary patterns and cluster membership stable over time? Results of a longitudinal cluster analysis study.

Science.gov (United States)

Walthouwer, Michel Jean Louis; Oenema, Anke; Soetens, Katja; Lechner, Lilian; de Vries, Hein

2014-11-01

Developing nutrition education interventions based on clusters of dietary patterns can only be done adequately when it is clear if distinctive clusters of dietary patterns can be derived and reproduced over time, if cluster membership is stable, and if it is predictable which type of people belong to a certain cluster. Hence, this study aimed to: (1) identify clusters of dietary patterns among Dutch adults, (2) test the reproducibility of these clusters and stability of cluster membership over time, and (3) identify sociodemographic predictors of cluster membership and cluster transition. This study had a longitudinal design with online measurements at baseline (N=483) and 6 months follow-up (N=379). Dietary intake was assessed with a validated food frequency questionnaire. A hierarchical cluster analysis was performed, followed by a K-means cluster analysis. Multinomial logistic regression analyses were conducted to identify the sociodemographic predictors of cluster membership and cluster transition. At baseline and follow-up, a comparable three-cluster solution was derived, distinguishing a healthy, moderately healthy, and unhealthy dietary pattern. Male and lower educated participants were significantly more likely to have a less healthy dietary pattern. Further, 251 (66.2%) participants remained in the same cluster, 45 (11.9%) participants changed to an unhealthier cluster, and 83 (21.9%) participants shifted to a healthier cluster. Men and people living alone were significantly more likely to shift toward a less healthy dietary pattern. Distinctive clusters of dietary patterns can be derived. Yet, cluster membership is unstable and only few sociodemographic factors were associated with cluster membership and cluster transition. These findings imply that clusters based on dietary intake may not be suitable as a basis for nutrition education interventions. Copyright © 2014 Elsevier Ltd. All rights reserved.

Protein clustering and RNA phylogenetic reconstruction of the influenza A [corrected] virus NS1 protein allow an update in classification and identification of motif conservation.

Science.gov (United States)

Sevilla-Reyes, Edgar E; Chavaro-Pérez, David A; Piten-Isidro, Elvira; Gutiérrez-González, Luis H; Santos-Mendoza, Teresa

2013-01-01

The non-structural protein 1 (NS1) of influenza A virus (IAV), coded by its third most diverse gene, interacts with multiple molecules within infected cells. NS1 is involved in host immune response regulation and is a potential contributor to the virus host range. Early phylogenetic analyses using 50 sequences led to the classification of NS1 gene variants into groups (alleles) A and B. We reanalyzed NS1 diversity using 14,716 complete NS IAV sequences, downloaded from public databases, without host bias. Removal of sequence redundancy and further structured clustering at 96.8% amino acid similarity produced 415 clusters that enhanced our capability to detect distinct subgroups and lineages, which were assigned a numerical nomenclature. Maximum likelihood phylogenetic reconstruction using RNA sequences indicated the previously identified deep branching separating group A from group B, with five distinct subgroups within A as well as two and five lineages within the A4 and A5 subgroups, respectively. Our classification model proposes that sequence patterns in thirteen amino acid positions are sufficient to fit >99.9% of all currently available NS1 sequences into the A subgroups/lineages or the B group. This classification reduces host and virus bias through the prioritization of NS1 RNA phylogenetics over host or virus phenetics. We found significant sequence conservation within the subgroups and lineages with characteristic patterns of functional motifs, such as the differential binding of CPSF30 and crk/crkL or the availability of a C-terminal PDZ-binding motif. To understand selection pressures and evolution acting on NS1, it is necessary to organize the available data. This updated classification may help to clarify and organize the study of NS1 interactions and pathogenic differences and allow the drawing of further functional inferences on sequences in each group, subgroup and lineage rather than on a strain-by-strain basis.

Clusters and how to make it work : Cluster Strategy Toolkit

NARCIS (Netherlands)

Manickam, Anu; van Berkel, Karel

2014-01-01

Clusters are the magic answer to regional economic development. Firms in clusters are more innovative; cluster policy dominates EU policy; ‘top-sectors’ and excellence are the choice of national policy makers; clusters are ‘in’. But, clusters are complex, clusters are ‘messy’; there is no clear

Cluster dynamics at different cluster size and incident laser wavelengths

International Nuclear Information System (INIS)

Desai, Tara; Bernardinello, Andrea

2002-01-01

X-ray emission spectra from aluminum clusters of diameter -0.4 μm and gold clusters of dia. ∼1.25 μm are experimentally studied by irradiating the cluster foil targets with 1.06 μm laser, 10 ns (FWHM) at an intensity ∼10 12 W/cm 2 . Aluminum clusters show a different spectra compared to bulk material whereas gold cluster evolve towards bulk gold. Experimental data are analyzed on the basis of cluster dimension, laser wavelength and pulse duration. PIC simulations are performed to study the behavior of clusters at higher intensity I≥10 17 W/cm 2 for different size of the clusters irradiated at different laser wavelengths. Results indicate the dependence of cluster dynamics on cluster size and incident laser wavelength

Text Clustering Algorithm Based on Random Cluster Core

Directory of Open Access Journals (Sweden)

Huang Long-Jun

2016-01-01

Full Text Available Nowadays clustering has become a popular text mining algorithm, but the huge data can put forward higher requirements for the accuracy and performance of text mining. In view of the performance bottleneck of traditional text clustering algorithm, this paper proposes a text clustering algorithm with random features. This is a kind of clustering algorithm based on text density, at the same time using the neighboring heuristic rules, the concept of random cluster is introduced, which effectively reduces the complexity of the distance calculation.

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

Indian Academy of Sciences (India)

Pooja Sharma

2017-07-07

Jul 7, 2017 ... and a few other model organisms. .... form proteins) affect the protein formation process. Muta- ..... We implemented the ComFiR method in MATLAB run- ning on ..... Van Dongen SM 2001 Graph clustering by flow simulation.

Mutation of the His ligand in mitoNEET stabilizes the 2Fe–2S cluster despite conformational heterogeneity in the ligand environment

Energy Technology Data Exchange (ETDEWEB)

Conlan, Andrea R.; Paddock, Mark L.; Homer, Christina [University of California at San Diego, La Jolla, CA 92093 (United States); Axelrod, Herbert L.; Cohen, Aina E. [Stanford Synchrotron Radiation Laboratory, 2575 Sand Hill Road, Menlo Park, CA 94025 (United States); Abresch, Edward C.; Zuris, John A. [University of California at San Diego, La Jolla, CA 92093 (United States); Nechushtai, Rachel [Hebrew University of Jerusalem, Edmond J. Safra Campus, Givat Ram, Jerusalem 91904 (Israel); Jennings, Patricia A., E-mail: pajennin@ucsd.edu [University of California at San Diego, La Jolla, CA 92093 (United States)

2011-06-01

The spectroscopic and stability properties and X-ray crystal structure of the H87C mutant of the 2Fe–2S ligand mitoNEET are reported. Strikingly, the single point mutation leads to changes in its absorbance and CD spectra and an increase of around sixfold in the stability of the 2Fe–2S clusters over the pH range 5–7. However, the crystal structure of the H87C mutant displays heterogeneity in a few key residues, including the introduced cysteine ligand. Nonetheless, the cluster is highly stabilized from release. MitoNEET is the only identified Fe–S protein localized to the outer mitochondrial membrane and a 1.5 Å resolution X-ray analysis has revealed a unique structure [Paddock et al. (2007 ▶), Proc. Natl Acad. Sci. USA, 104, 14342–14347]. The 2Fe–2S cluster is bound with a 3Cys–1His coordination which defines a new class of 2Fe–2S proteins. The hallmark feature of this class is the single noncysteine ligand His87, which when replaced by Cys decreases the redox potential (E{sub m}) by ∼300 mV and increases the stability of the cluster by around sixfold. Unexpectedly, the pH dependence of the lifetime of the 2Fe–2S cluster remains the same as in the wild-type protein. Here, the crystal structure of H87C mitoNEET was determined to 1.7 Å resolution (R factor = 18%) to investigate the structural basis of the changes in the properties of the 2Fe–2S cluster. In comparison to the wild type, structural changes are localized to the immediate vicinity of the cluster-binding region. Despite the increased stability, Cys87 displays two distinct conformations, with distances of 2.3 and 3.2 Å between the S{sup γ} and the outer Fe of the 2Fe–2S cluster. In addition, Lys55 exhibits multiple conformations in the H87C mutant protein. The structure and distinct characteristics of the H87C mutant provide a framework for further studies investigating the effects of mutation on the properties of the 2Fe–2S cluster in this new class of proteins.

The CoxD protein, a novel AAA+ ATPase involved in metal cluster assembly: hydrolysis of nucleotide-triphosphates and oligomerization.

Directory of Open Access Journals (Sweden)

Tobias Maisel

Full Text Available CoxD of the α-proteobacterium Oligotropha carboxidovorans is a membrane protein which is involved in the posttranslational biosynthesis of the [CuSMoO₂] cluster in the active site of the enzyme CO dehydrogenase. The bacteria synthesize CoxD only in the presence of CO. Recombinant CoxD produced in E. coli K38 pGP1-2/pETMW2 appeared in inclusion bodies from where it was solubilized by urea and refolded by stepwise dilution. Circular dichroism spectroscopy revealed the presence of secondary structural elements in refolded CoxD. CoxD is a P-loop ATPase of the AAA-protein family. Refolded CoxD catalyzed the hydrolysis of MgATP yielding MgADP and inorganic phosphate at a 1∶1∶1 molar ratio. The reaction was inhibited by the slow hydrolysable MgATP-γ-S. GTPase activity of CoxD did not exceed 2% of the ATPase activity. Employing different methods (non linear regression, Hanes and Woolf, Lineweaver-Burk, preparations of CoxD revealed a mean K(M value of 0.69±0.14 mM ATP and an apparent V(max value of 19.3±2.3 nmol ATP hydrolyzed min⁻¹ mg⁻¹. Sucrose density gradient centrifugation and gel filtration showed that refolded CoxD can exist in various multimeric states (2-mer, 4-mer or 6-mer, preferentially as hexamer or dimer. Within weeks the hexamer dissociates into the dimer, a process which can be reversed by MgATP or MgATP-γ-S within hours. Only the hexamers and the dimers exhibited MgATPase activity. Transmission electron microscopy of negatively stained CoxD preparations revealed distinct particles within a size range of 10-16 nm, which further corroborates the oligomeric organization. The 3D structure of CoxD was modeled with the 3D structure of BchI from Rhodobacter capsulatus as template. It has the key elements of an AAA+ domain in the same arrangement and at same positions as in BchI and displays the characteristic inserts of the PS-II-insert clade. Possible functions of CoxD in [CuSMoO₂] cluster assembly are discussed.

Architectures and Functional Coverage of Protein-Protein Interfaces

Science.gov (United States)

Tuncbag, Nurcan; Gursoy, Attila; Guney, Emre; Nussinov, Ruth; Keskin, Ozlem

2008-01-01

The diverse range of cellular functions is performed by a limited number of protein folds existing in nature. One may similarly expect that cellular functional diversity would be covered by a limited number of protein-protein interface architectures. Here, we present 8205 interface clusters, each representing unique interface architecture. This dataset of protein-protein interfaces is analyzed and compared with older datasets. We observe that the number of both biological and crystal interfaces increase significantly compared to the number of PDB entries. Further, we find that the number of distinct interface architectures grows at a much faster rate than the number of folds and is yet to level off. We further analyze the growth trend of the functional coverage by constructing functional interaction networks from interfaces. The functional coverage is also found to steadily increase. Interestingly, we also observe that despite the diversity of interface architectures, some are more favorable and frequently used, and of particular interest, those are the ones which are also preferred in single chains. PMID:18620705

Insulin regulates Glut4 confinement in plasma membrane clusters in adipose cells.

Science.gov (United States)

Lizunov, Vladimir A; Stenkula, Karin; Troy, Aaron; Cushman, Samuel W; Zimmerberg, Joshua

2013-01-01

Insulin-stimulated delivery of glucose transporter-4 (GLUT4) to the plasma membrane (PM) is the hallmark of glucose metabolism. In this study we examined insulin's effects on GLUT4 organization in PM of adipose cells by direct microscopic observation of single monomers tagged with photoswitchable fluorescent protein. In the basal state, after exocytotic delivery only a fraction of GLUT4 is dispersed into the PM as monomers, while most of the GLUT4 stays at the site of fusion and forms elongated clusters (60-240 nm). GLUT4 monomers outside clusters diffuse freely and do not aggregate with other monomers. In contrast, GLUT4 molecule collision with an existing cluster can lead to immediate confinement and association with that cluster. Insulin has three effects: it shifts the fraction of dispersed GLUT4 upon delivery, it augments the dissociation of GLUT4 monomers from clusters ∼3-fold and it decreases the rate of endocytic uptake. All together these three effects of insulin shift most of the PM GLUT4 from clustered to dispersed states. GLUT4 confinement in clusters represents a novel kinetic mechanism for insulin regulation of glucose homeostasis.

Insulin regulates Glut4 confinement in plasma membrane clusters in adipose cells.

Directory of Open Access Journals (Sweden)

Vladimir A Lizunov

Full Text Available Insulin-stimulated delivery of glucose transporter-4 (GLUT4 to the plasma membrane (PM is the hallmark of glucose metabolism. In this study we examined insulin's effects on GLUT4 organization in PM of adipose cells by direct microscopic observation of single monomers tagged with photoswitchable fluorescent protein. In the basal state, after exocytotic delivery only a fraction of GLUT4 is dispersed into the PM as monomers, while most of the GLUT4 stays at the site of fusion and forms elongated clusters (60-240 nm. GLUT4 monomers outside clusters diffuse freely and do not aggregate with other monomers. In contrast, GLUT4 molecule collision with an existing cluster can lead to immediate confinement and association with that cluster. Insulin has three effects: it shifts the fraction of dispersed GLUT4 upon delivery, it augments the dissociation of GLUT4 monomers from clusters ∼3-fold and it decreases the rate of endocytic uptake. All together these three effects of insulin shift most of the PM GLUT4 from clustered to dispersed states. GLUT4 confinement in clusters represents a novel kinetic mechanism for insulin regulation of glucose homeostasis.

On clusters and clustering from atoms to fractals

CERN Document Server

Reynolds, PJ

1993-01-01

This book attempts to answer why there is so much interest in clusters. Clusters occur on all length scales, and as a result occur in a variety of fields. Clusters are interesting scientifically, but they also have important consequences technologically. The division of the book into three parts roughly separates the field into small, intermediate, and large-scale clusters. Small clusters are the regime of atomic and molecular physics and chemistry. The intermediate regime is the transitional regime, with its characteristics including the onset of bulk-like behavior, growth and aggregation, a

Protein Charge and Mass Contribute to the Spatio-temporal Dynamics of Protein-Protein Interactions in a Minimal Proteome

Science.gov (United States)

Xu, Yu; Wang, Hong; Nussinov, Ruth; Ma, Buyong

2013-01-01

We constructed and simulated a ‘minimal proteome’ model using Langevin dynamics. It contains 206 essential protein types which were compiled from the literature. For comparison, we generated six proteomes with randomized concentrations. We found that the net charges and molecular weights of the proteins in the minimal genome are not random. The net charge of a protein decreases linearly with molecular weight, with small proteins being mostly positively charged and large proteins negatively charged. The protein copy numbers in the minimal genome have the tendency to maximize the number of protein-protein interactions in the network. Negatively charged proteins which tend to have larger sizes can provide large collision cross-section allowing them to interact with other proteins; on the other hand, the smaller positively charged proteins could have higher diffusion speed and are more likely to collide with other proteins. Proteomes with random charge/mass populations form less stable clusters than those with experimental protein copy numbers. Our study suggests that ‘proper’ populations of negatively and positively charged proteins are important for maintaining a protein-protein interaction network in a proteome. It is interesting to note that the minimal genome model based on the charge and mass of E. Coli may have a larger protein-protein interaction network than that based on the lower organism M. pneumoniae. PMID:23420643

How Escherichia coli and Saccharomyces cerevisiae build Fe/S proteins.

Science.gov (United States)

Barras, Frédéric; Loiseau, Laurent; Py, Béatrice

2005-01-01

Owing to the versatile electronic properties of iron and sulfur, iron sulfur (Fe/S) clusters are perfectly suited for sensing changes in environmental conditions and regulating protein properties accordingly. Fe/S proteins have been recruited in a wide array of diverse biological processes, including electron transfer chains, metabolic pathways and gene regulatory circuits. Chemistry has revealed the great diversity of Fe/S clusters occurring in proteins. The question now is to understand how iron and sulfur come together to form Fe/S clusters and how these clusters are subsequently inserted into apoproteins. Iron, sulfide and reducing conditions were found to be sufficient for successful maturation of many apoproteins in vitro, opening the possibility that insertion might be a spontaneous event. However, as in many other biological pathways such as protein folding, genetic analyses revealed that Fe/S cluster biogenesis and insertion depend in vivo upon auxiliary proteins. This was brought to light by studies on Azotobacter vinelandii nitrogenase, which, in particular, led to the concept of scaffold proteins, the role of which would be to allow transient assembly of Fe/S cluster. These studies paved the way toward the identification of the ISC and SUF systems, subjects of the present review that allow Fe/S cluster assembly into apoproteins of most organisms. Despite the recent discovery of the SUF and ISC systems, remarkable progress has been made in our understanding of their molecular composition and biochemical mechanisms. Such a rapid increase in our knowledge arose from a convergent interest from researchers engaged in unrelated fields and whose complementary expertise covered most experimental approaches used in biology. Also, the high conservation of ISC and SUF systems throughout a wide array of organisms helped cross-feeding between studies. The ISC system is conserved in eubacteria and most eukaryotes, while the SUF system arises in eubacteria, archaea

The near-symmetry of proteins.

Science.gov (United States)

Bonjack-Shterengartz, Maayan; Avnir, David

2015-04-01

The majority of protein oligomers form clusters which are nearly symmetric. Understanding of that imperfection, its origins, and perhaps also its advantages requires the conversion of the currently used vague qualitative descriptive language of the near-symmetry into an accurate quantitative measure that will allow to answer questions such as: "What is the degree of symmetry deviation of the protein?," "how do these deviations compare within a family of proteins?," and so on. We developed quantitative methods to answer this type of questions, which are capable of analyzing the whole protein, its backbone or selected portions of it, down to comparison of symmetry-related specific amino-acids, and which are capable of visualizing the various levels of symmetry deviations in the form of symmetry maps. We have applied these methods on an extensive list of homomers and heteromers and found that apparently all proteins never reach perfect symmetry. Strikingly, even homomeric protein clusters are never ideally symmetric. We also found that the main burden of symmetry distortion is on the amino-acids near the symmetry axis; that it is mainly the more hydrophilic amino-acids that take place in symmetry-distortive interactions; and more. The remarkable ability of heteromers to preserve near-symmetry, despite the different sequences, was also shown and analyzed. The comprehensive literature on the suggested advantages symmetric oligomerizations raises a yet-unsolved key question: If symmetry is so advantageous, why do proteins stop shy of perfect symmetry? Some tentative answers to be tested in further studies are suggested in a concluding outlook. © 2014 Wiley Periodicals, Inc.

Fe-S cluster coordination of the chromokinesin KIF4A alters its sub-cellular localization during mitosis.

Science.gov (United States)

Ben-Shimon, Lilach; Paul, Viktoria D; David-Kadoch, Galit; Volpe, Marina; Stümpfig, Martin; Bill, Eckhard; Mühlenhoff, Ulrich; Lill, Roland; Ben-Aroya, Shay

2018-05-30

Fe-S clusters act as co-factors of proteins with diverse functions, e.g. in DNA repair. Down-regulation of the cytosolic iron-sulfur protein assembly (CIA) machinery promotes genomic instability by the inactivation of multiple DNA repair pathways. Furthermore, CIA deficiencies are associated with so far unexplained mitotic defects. Here, we show that CIA2B and MMS19, constituents of the CIA targeting complex involved in facilitating Fe-S cluster insertion into cytosolic and nuclear target proteins, co-localize with components of the mitotic machinery. Down-regulation of CIA2B and MMS19 impairs the mitotic cycle. We identify the chromokinesin KIF4A as a mitotic component involved in these effects. KIF4A binds a Fe-S cluster in vitro through its conserved cysteine-rich domain. We demonstrate in vivo that this domain is required for the mitosis-related KIF4A localization and for the mitotic defects associated with KIF4A knockout. KIF4A is the first identified mitotic component carrying such a post-translational modification. These findings suggest that the lack of Fe-S clusters in KIF4A upon down-regulation of the CIA targeting complex contributes to the mitotic defects. © 2018. Published by The Company of Biologists Ltd.

GibbsCluster: unsupervised clustering and alignment of peptide sequences

DEFF Research Database (Denmark)

Andreatta, Massimo; Alvarez, Bruno; Nielsen, Morten

2017-01-01

motif characterizing each cluster. Several parameters are available to customize cluster analysis, including adjustable penalties for small clusters and overlapping groups and a trash cluster to remove outliers. As an example application, we used the server to deconvolute multiple specificities in large......-scale peptidome data generated by mass spectrometry. The server is available at http://www.cbs.dtu.dk/services/GibbsCluster-2.0....

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

Directory of Open Access Journals (Sweden)

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.

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.

Partitional clustering algorithms

CERN Document Server

2015-01-01

This book summarizes the state-of-the-art in partitional clustering. Clustering, the unsupervised classification of patterns into groups, is one of the most important tasks in exploratory data analysis. Primary goals of clustering include gaining insight into, classifying, and compressing data. Clustering has a long and rich history that spans a variety of scientific disciplines including anthropology, biology, medicine, psychology, statistics, mathematics, engineering, and computer science. As a result, numerous clustering algorithms have been proposed since the early 1950s. Among these algorithms, partitional (nonhierarchical) ones have found many applications, especially in engineering and computer science. This book provides coverage of consensus clustering, constrained clustering, large scale and/or high dimensional clustering, cluster validity, cluster visualization, and applications of clustering. Examines clustering as it applies to large and/or high-dimensional data sets commonly encountered in reali...

NMR of proteins (4Fe-4S): structural properties and intramolecular electron transfer

International Nuclear Information System (INIS)

Huber, J.G.

1996-01-01

NMR started to be applied to Fe-S proteins in the seventies. Its use has recently been enlarged as the problems arising from the paramagnetic polymetallic clusters ware overcome. Applications to [4Fe-4S] are presented herein. The information derived thereof deepens the understanding of the redox properties of these proteins which play a central role in the metabolism of bacterial cells. The secondary structure elements and the overall folding of Chromatium vinosum ferredoxin (Cv Fd) in solution have been established by NMR. The unique features of this sequence have been shown to fold as an α helix at the C-terminus and as a loop between two cysteines ligand of one cluster: these two parts localize in close proximity from one another. The interaction between nuclear and electronic spins is a source of additional structural information for (4Fe-AS] proteins. The conformation of the cysteine-ligands, as revealed by the Fe-(S γ -C β -H β )Cys dihedral angles, is related to the chemical shifts of the signals associated with the protons of these residues. The longitudinal relaxation times of the protons depend on their distance to the cluster. A quantitative relationship has been established and used to show that the solution structure of the high-potential ferredoxin from Cv differs significantly from the crystal structure around Phe-48. Both parameters (chemical shifts and longitudinal relaxation times) give also insight into the electronic and magnetic properties of the [4Fe-4S] clusters. The rate of intramolecular electron transfer between the two [4FE-4S] clusters of ferredoxins has been measured by NMR. It is far slower in the case of Cv Fd than for shorter ferredoxins. The difference may be associated with changes in the magnetic and/or electronic properties of one cluster. The strong paramagnetism of the [4Fe-4S] clusters, which originally limited the applicability of NMR to proteins containing these cofactors, has been proven instrumental in affording new

SOS System Induction Inhibits the Assembly of Chemoreceptor Signaling Clusters in Salmonella enterica.

Science.gov (United States)

Irazoki, Oihane; Mayola, Albert; Campoy, Susana; Barbé, Jordi

2016-01-01

Swarming, a flagellar-driven multicellular form of motility, is associated with bacterial virulence and increased antibiotic resistance. In this work we demonstrate that activation of the SOS response reversibly inhibits swarming motility by preventing the assembly of chemoreceptor-signaling polar arrays. We also show that an increase in the concentration of the RecA protein, generated by SOS system activation, rather than another function of this genetic network impairs chemoreceptor polar cluster formation. Our data provide evidence that the molecular balance between RecA and CheW proteins is crucial to allow polar cluster formation in Salmonella enterica cells. Thus, activation of the SOS response by the presence of a DNA-injuring compound increases the RecA concentration, thereby disturbing the equilibrium between RecA and CheW and resulting in the cessation of swarming. Nevertheless, when the DNA-damage decreases and the SOS response is no longer activated, basal RecA levels and thus polar cluster assembly are reestablished. These results clearly show that bacterial populations moving over surfaces make use of specific mechanisms to avoid contact with DNA-damaging compounds.

Cluster Matters

DEFF Research Database (Denmark)

Gulati, Mukesh; Lund-Thomsen, Peter; Suresh, Sangeetha

2018-01-01

sell their products successfully in international markets, but there is also an increasingly large consumer base within India. Indeed, Indian industrial clusters have contributed to a substantial part of this growth process, and there are several hundred registered clusters within the country...... of this handbook, which focuses on the role of CSR in MSMEs. Hence we contribute to the literature on CSR in industrial clusters and specifically CSR in Indian industrial clusters by investigating the drivers of CSR in India’s industrial clusters....

Weighted Clustering

DEFF Research Database (Denmark)

Ackerman, Margareta; Ben-David, Shai; Branzei, Simina

2012-01-01

We investigate a natural generalization of the classical clustering problem, considering clustering tasks in which different instances may have different weights.We conduct the first extensive theoretical analysis on the influence of weighted data on standard clustering algorithms in both...... the partitional and hierarchical settings, characterizing the conditions under which algorithms react to weights. Extending a recent framework for clustering algorithm selection, we propose intuitive properties that would allow users to choose between clustering algorithms in the weighted setting and classify...

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

Science.gov (United States)

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...

Conditions for the Evolution of Gene Clusters in Bacterial Genomes

Science.gov (United States)

Ballouz, Sara; Francis, Andrew R.; Lan, Ruiting; Tanaka, Mark M.

2010-01-01

Genes encoding proteins in a common pathway are often found near each other along bacterial chromosomes. Several explanations have been proposed to account for the evolution of these structures. For instance, natural selection may directly favour gene clusters through a variety of mechanisms, such as increased efficiency of coregulation. An alternative and controversial hypothesis is the selfish operon model, which asserts that clustered arrangements of genes are more easily transferred to other species, thus improving the prospects for survival of the cluster. According to another hypothesis (the persistence model), genes that are in close proximity are less likely to be disrupted by deletions. Here we develop computational models to study the conditions under which gene clusters can evolve and persist. First, we examine the selfish operon model by re-implementing the simulation and running it under a wide range of conditions. Second, we introduce and study a Moran process in which there is natural selection for gene clustering and rearrangement occurs by genome inversion events. Finally, we develop and study a model that includes selection and inversion, which tracks the occurrence and fixation of rearrangements. Surprisingly, gene clusters fail to evolve under a wide range of conditions. Factors that promote the evolution of gene clusters include a low number of genes in the pathway, a high population size, and in the case of the selfish operon model, a high horizontal transfer rate. The computational analysis here has shown that the evolution of gene clusters can occur under both direct and indirect selection as long as certain conditions hold. Under these conditions the selfish operon model is still viable as an explanation for the evolution of gene clusters. PMID:20168992

Support Policies in Clusters: Prioritization of Support Needs by Cluster Members According to Cluster Life Cycle

Directory of Open Access Journals (Sweden)

Gulcin Salıngan

2012-07-01

Full Text Available Economic development has always been a moving target. Both the national and local governments have been facing the challenge of implementing the effective and efficient economic policy and program in order to best utilize their limited resources. One of the recent approaches in this area is called cluster-based economic analysis and strategy development. This study reviews key literature and some of the cluster based economic policies adopted by different governments. Based on this review, it proposes “the cluster life cycle” as a determining factor to identify the support requirements of clusters. A survey, designed based on literature review of International Cluster support programs, was conducted with 30 participants from 3 clusters with different maturity stage. This paper discusses the results of this study conducted among the cluster members in Eskişehir- Bilecik-Kütahya Region in Turkey on the requirement of the support to foster the development of related clusters.

Entry and exit of bacterial outer membrane proteins.

Science.gov (United States)

Misra, Rajeev

2015-08-01

The sites of new outer membrane protein (OMP) deposition and the fate of pre-existing OMPs are still enigmatic despite numerous concerted efforts. Rassam et al. identified mid-cell regions as the primary entry points for new OMP insertion in clusters, driving the pre-existing OMP clusters towards cell poles for long-term storage. Copyright © 2015 Elsevier Ltd. All rights reserved.

Clusters and how to make it work : toolkit for cluster strategy

NARCIS (Netherlands)

Manickam, Anu; van Berkel, Karel

2013-01-01

Clusters are the magic answer to regional economic development. Firms in clusters are more innovative; cluster policy dominates EU policy; ‘top-sectors’ and excellence are the choice of national policy makers; clusters are ‘in’. But, clusters are complex, clusters are ‘messy’; there is no clear

Arabidopsis thaliana mTERF proteins: evolution and functional classification

Directory of Open Access Journals (Sweden)

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

A PQL (protein quantity loci) analysis of mature pea seed proteins identifies loci determining seed protein composition.

Science.gov (United States)

Bourgeois, Michael; Jacquin, Françoise; Cassecuelle, Florence; Savois, Vincent; Belghazi, Maya; Aubert, Grégoire; Quillien, Laurence; Huart, Myriam; Marget, Pascal; Burstin, Judith

2011-05-01

Legume seeds are a major source of dietary proteins for humans and animals. Deciphering the genetic control of their accumulation is thus of primary significance towards their improvement. At first, we analysed the genetic variability of the pea seed proteome of three genotypes over 3 years of cultivation. This revealed that seed protein composition variability was under predominant genetic control, with as much as 60% of the spots varying quantitatively among the three genotypes. Then, by combining proteomic and quantitative trait loci (QTL) mapping approaches, we uncovered the genetic architecture of seed proteome variability. Protein quantity loci (PQL) were searched for 525 spots detected on 2-D gels obtained for 157 recombinant inbred lines. Most protein quantity loci mapped in clusters, suggesting that the accumulation of the major storage protein families was under the control of a limited number of loci. While convicilin accumulation was mainly under the control of cis-regulatory regions, vicilins and legumins were controlled by both cis- and trans-regulatory regions. Some loci controlled both seed protein composition and protein content and a locus on LGIIa appears to be a major regulator of protein composition and of protein in vitro digestibility. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Ensemble attribute profile clustering: discovering and characterizing groups of genes with similar patterns of biological features

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Bissell MJ

2006-03-01

Full Text Available Abstract Background Ensemble attribute profile clustering is a novel, text-based strategy for analyzing a user-defined list of genes and/or proteins. The strategy exploits annotation data present in gene-centered corpora and utilizes ideas from statistical information retrieval to discover and characterize properties shared by subsets of the list. The practical utility of this method is demonstrated by employing it in a retrospective study of two non-overlapping sets of genes defined by a published investigation as markers for normal human breast luminal epithelial cells and myoepithelial cells. Results Each genetic locus was characterized using a finite set of biological properties and represented as a vector of features indicating attributes associated with the locus (a gene attribute profile. In this study, the vector space models for a pre-defined list of genes were constructed from the Gene Ontology (GO terms and the Conserved Domain Database (CDD protein domain terms assigned to the loci by the gene-centered corpus LocusLink. This data set of GO- and CDD-based gene attribute profiles, vectors of binary random variables, was used to estimate multiple finite mixture models and each ensuing model utilized to partition the profiles into clusters. The resultant partitionings were combined using a unanimous voting scheme to produce consensus clusters, sets of profiles that co-occured consistently in the same cluster. Attributes that were important in defining the genes assigned to a consensus cluster were identified. The clusters and their attributes were inspected to ascertain the GO and CDD terms most associated with subsets of genes and in conjunction with external knowledge such as chromosomal location, used to gain functional insights into human breast biology. The 52 luminal epithelial cell markers and 89 myoepithelial cell markers are disjoint sets of genes. Ensemble attribute profile clustering-based analysis indicated that both lists

Rescuing the Rescuer: On the Protein Complex between the Human Mitochondrial Acyl Carrier Protein and ISD11.

Science.gov (United States)

Herrera, María Georgina; Pignataro, María Florencia; Noguera, Martín Ezequiel; Cruz, Karen Magalí; Santos, Javier

2018-05-16

Iron-sulfur clusters are essential cofactors in many biochemical processes. ISD11, one of the subunits of the protein complex that carries out the cluster assembly in mitochondria, is necessary for cysteine desulfurase NFS1 stability and function. Several authors have recently provided evidence showing that ISD11 interacts with the acyl carrier protein (ACP). We carried out the coexpression of human mitochondrial ACP and ISD11 in E. coli. This work shows that ACP and ISD11 form a soluble, structured, and stable complex able to bind to the human NFS1 subunit modulating its activity. Results suggest that ACP plays a key-role in ISD11 folding and stability in vitro. These findings offer the opportunity to study the mechanism of interaction between ISD11 and NFS1.

Determination of atomic cluster structure with cluster fusion algorithm

DEFF Research Database (Denmark)

Obolensky, Oleg I.; Solov'yov, Ilia; Solov'yov, Andrey V.

2005-01-01

We report an efficient scheme of global optimization, called cluster fusion algorithm, which has proved its reliability and high efficiency in determination of the structure of various atomic clusters.......We report an efficient scheme of global optimization, called cluster fusion algorithm, which has proved its reliability and high efficiency in determination of the structure of various atomic clusters....

Large-Scale Multi-Dimensional Document Clustering on GPU Clusters

Energy Technology Data Exchange (ETDEWEB)

Cui, Xiaohui [ORNL; Mueller, Frank [North Carolina State University; Zhang, Yongpeng [ORNL; Potok, Thomas E [ORNL

2010-01-01

Document clustering plays an important role in data mining systems. Recently, a flocking-based document clustering algorithm has been proposed to solve the problem through simulation resembling the flocking behavior of birds in nature. This method is superior to other clustering algorithms, including k-means, in the sense that the outcome is not sensitive to the initial state. One limitation of this approach is that the algorithmic complexity is inherently quadratic in the number of documents. As a result, execution time becomes a bottleneck with large number of documents. In this paper, we assess the benefits of exploiting the computational power of Beowulf-like clusters equipped with contemporary Graphics Processing Units (GPUs) as a means to significantly reduce the runtime of flocking-based document clustering. Our framework scales up to over one million documents processed simultaneously in a sixteennode GPU cluster. Results are also compared to a four-node cluster with higher-end GPUs. On these clusters, we observe 30X-50X speedups, which demonstrates the potential of GPU clusters to efficiently solve massive data mining problems. Such speedups combined with the scalability potential and accelerator-based parallelization are unique in the domain of document-based data mining, to the best of our knowledge.

Membership determination of open clusters based on a spectral clustering method

Science.gov (United States)

Gao, Xin-Hua

2018-06-01

We present a spectral clustering (SC) method aimed at segregating reliable members of open clusters in multi-dimensional space. The SC method is a non-parametric clustering technique that performs cluster division using eigenvectors of the similarity matrix; no prior knowledge of the clusters is required. This method is more flexible in dealing with multi-dimensional data compared to other methods of membership determination. We use this method to segregate the cluster members of five open clusters (Hyades, Coma Ber, Pleiades, Praesepe, and NGC 188) in five-dimensional space; fairly clean cluster members are obtained. We find that the SC method can capture a small number of cluster members (weak signal) from a large number of field stars (heavy noise). Based on these cluster members, we compute the mean proper motions and distances for the Hyades, Coma Ber, Pleiades, and Praesepe clusters, and our results are in general quite consistent with the results derived by other authors. The test results indicate that the SC method is highly suitable for segregating cluster members of open clusters based on high-precision multi-dimensional astrometric data such as Gaia data.

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

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Yong Chern Han

2012-12-01

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

Mitochondrial nucleoid clusters protect newly synthesized mtDNA during Doxorubicin- and Ethidium Bromide-induced mitochondrial stress

Energy Technology Data Exchange (ETDEWEB)

Alán, Lukáš, E-mail: lukas.alan@fgu.cas.cz; Špaček, Tomáš; Pajuelo Reguera, David; Jabůrek, Martin; Ježek, Petr

2016-07-01

Mitochondrial DNA (mtDNA) is compacted in ribonucleoprotein complexes called nucleoids, which can divide or move within the mitochondrial network. Mitochondrial nucleoids are able to aggregate into clusters upon reaction with intercalators such as the mtDNA depletion agent Ethidium Bromide (EB) or anticancer drug Doxorobicin (DXR). However, the exact mechanism of nucleoid clusters formation remains unknown. Resolving these processes may help to elucidate the mechanisms of DXR-induced cardiotoxicity. Therefore, we addressed the role of two key nucleoid proteins; mitochondrial transcription factor A (TFAM) and mitochondrial single-stranded binding protein (mtSSB); in the formation of mitochondrial nucleoid clusters during the action of intercalators. We found that both intercalators cause numerous aberrations due to perturbing their native status. By blocking mtDNA replication, both agents also prevented mtDNA association with TFAM, consequently causing nucleoid aggregation into large nucleoid clusters enriched with TFAM, co-existing with the normal nucleoid population. In the later stages of intercalation (> 48 h), TFAM levels were reduced to 25%. In contrast, mtSSB was released from mtDNA and freely distributed within the mitochondrial network. Nucleoid clusters mostly contained nucleoids with newly replicated mtDNA, however the nucleoid population which was not in replication mode remained outside the clusters. Moreover, the nucleoid clusters were enriched with p53, an anti-oncogenic gatekeeper. We suggest that mitochondrial nucleoid clustering is a mechanism for protecting nucleoids with newly replicated DNA against intercalators mediating genotoxic stress. These results provide new insight into the common mitochondrial response to mtDNA stress and can be implied also on DXR-induced mitochondrial cytotoxicity. - Highlights: • The mechanism for mitochondrial nucleoid clustering is proposed. • DNA intercalators (Doxorubicin or Ethidium Bromide) prevent TFAM

Dietary protein is associated with musculoskeletal health independently of dietary pattern: the Framingham Third Generation Study.

Science.gov (United States)

Mangano, Kelsey M; Sahni, Shivani; Kiel, Douglas P; Tucker, Katherine L; Dufour, Alyssa B; Hannan, Marian T

2017-03-01

Background: Above-average dietary protein, as a single nutrient, improves musculoskeletal health. Evaluating the link between dietary protein and musculoskeletal health from a whole-diet perspective is important, as dietary guidelines focus on dietary patterns. Objective: We examined the prospective association of novel dietary protein food clusters (derived from established dietary pattern techniques) with appendicular lean mass (ALM), quadriceps strength (QS), and bone mineral density (BMD) in 2986 men and women, aged 19-72 y, from the Framingham Third Generation Study. Design: Total protein intake was estimated by food-frequency questionnaire in 2002-2005. A cluster analysis was used to classify participants into mutually exclusive groups, which were determined by using the percentage of contribution of food intake to overall protein intake. General linear modeling was used to 1 ) estimate the association between protein intake (grams per day) and BMD, ALM, appendicular lean mass normalized for height (ALM/ht 2 ), and QS (2008-2011) and to 2 ) calculate adjusted least-squares mean outcomes across quartiles of protein (grams per day) and protein food clusters. Results: The mean ± SD age of subjects was 40 ± 9 y; 82% of participants met the Recommended Daily Allowance (0.8 g · kg body weight -1 · d -1 ). The following 6 dietary protein food clusters were identified: fast food and full-fat dairy, fish, red meat, chicken, low-fat milk, and legumes. BMD was not different across quartiles of protein intake ( P -trend range = 0.32-0.82); but significant positive trends were observed for ALM, ALM/ht 2 ( P dietary protein is associated with ALM and QS but not with BMD. In this study, dietary protein food patterns do not provide further insight into beneficial protein effects on muscle outcomes. © 2017 American Society for Nutrition.

Cluster headache

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Histamine headache; Headache - histamine; Migrainous neuralgia; Headache - cluster; Horton's headache; Vascular headache - cluster ... Doctors do not know exactly what causes cluster headaches. They ... (chemical in the body released during an allergic response) or ...

Phrase Mining of Textual Data to Analyze Extracellular Matrix Protein Patterns Across Cardiovascular Disease.

Science.gov (United States)

Liem, David Alexandre; Murali, Sanjana; Sigdel, Dibakar; Shi, Yu; Wang, Xuan; Shen, Jiaming; Choi, Howard; Caufield, J Harry; Wang, Wei; Ping, Peipei; Han, Jiawei

2018-05-18

Extracellular matrix (ECM) proteins have been shown to play important roles regulating multiple biological processes in an array of organ systems, including the cardiovascular system. By using a novel bioinformatics text-mining tool, we studied six categories of cardiovascular disease (CVD), namely ischemic heart disease (IHD), cardiomyopathies (CM), cerebrovascular accident (CVA), congenital heart disease (CHD), arrhythmias (ARR), and valve disease (VD), anticipating novel ECM protein-disease and protein-protein relationships hidden within vast quantities of textual data. We conducted a phrase-mining analysis, delineating the relationships of 709 ECM proteins with the six groups of CVDs reported in 1,099,254 abstracts. The technology pipeline known as Context-aware Semantic Online Analytical Processing (CaseOLAP) was applied to semantically rank the association of proteins to each and all six CVDs, performing analyses to quantify each protein-disease relationship. We performed principal component analysis and hierarchical clustering of the data, where each protein is visualized as a six dimensional vector. We found that ECM proteins display variable degrees of association with the six CVDs; certain CVDs share groups of associated proteins whereas others have divergent protein associations. We identified 82 ECM proteins sharing associations with all six CVDs. Our bioinformatics analysis ascribed distinct ECM pathways (via Reactome) from this subset of proteins, namely insulin-like growth factor regulation and interleukin-4 and interleukin-13 signaling, suggesting their contribution to the pathogenesis of all six CVDs. Finally, we performed hierarchical clustering analysis and identified protein clusters associated with a targeted CVD; analyses revealed unexpected insights underlying ECM-pathogenesis of CVDs.

Histone and ribosomal RNA repetitive gene clusters of the boll weevil are linked in a tandem array.

Science.gov (United States)

Roehrdanz, R; Heilmann, L; Senechal, P; Sears, S; Evenson, P

2010-08-01

Histones are the major protein component of chromatin structure. The histone family is made up of a quintet of proteins, four core histones (H2A, H2B, H3 & H4) and the linker histones (H1). Spacers are found between the coding regions. Among insects this quintet of genes is usually clustered and the clusters are tandemly repeated. Ribosomal DNA contains a cluster of the rRNA sequences 18S, 5.8S and 28S. The rRNA genes are separated by the spacers ITS1, ITS2 and IGS. This cluster is also tandemly repeated. We found that the ribosomal RNA repeat unit of at least two species of Anthonomine weevils, Anthonomus grandis and Anthonomus texanus (Coleoptera: Curculionidae), is interspersed with a block containing the histone gene quintet. The histone genes are situated between the rRNA 18S and 28S genes in what is known as the intergenic spacer region (IGS). The complete reiterated Anthonomus grandis histone-ribosomal sequence is 16,248 bp.

Maximum-likelihood model averaging to profile clustering of site types across discrete linear sequences.

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Zhang Zhang

2009-06-01

Full Text Available A major analytical challenge in computational biology is the detection and description of clusters of specified site types, such as polymorphic or substituted sites within DNA or protein sequences. Progress has been stymied by a lack of suitable methods to detect clusters and to estimate the extent of clustering in discrete linear sequences, particularly when there is no a priori specification of cluster size or cluster count. Here we derive and demonstrate a maximum likelihood method of hierarchical clustering. Our method incorporates a tripartite divide-and-conquer strategy that models sequence heterogeneity, delineates clusters, and yields a profile of the level of clustering associated with each site. The clustering model may be evaluated via model selection using the Akaike Information Criterion, the corrected Akaike Information Criterion, and the Bayesian Information Criterion. Furthermore, model averaging using weighted model likelihoods may be applied to incorporate model uncertainty into the profile of heterogeneity across sites. We evaluated our method by examining its performance on a number of simulated datasets as well as on empirical polymorphism data from diverse natural alleles of the Drosophila alcohol dehydrogenase gene. Our method yielded greater power for the detection of clustered sites across a breadth of parameter ranges, and achieved better accuracy and precision of estimation of clusters, than did the existing empirical cumulative distribution function statistics.

Single-cluster dynamics for the random-cluster model

NARCIS (Netherlands)

Deng, Y.; Qian, X.; Blöte, H.W.J.

2009-01-01

We formulate a single-cluster Monte Carlo algorithm for the simulation of the random-cluster model. This algorithm is a generalization of the Wolff single-cluster method for the q-state Potts model to noninteger values q>1. Its results for static quantities are in a satisfactory agreement with those

Epidemiology Analysis of Streptococcus pyogenes in a Hospital in Southern Taiwan by Use of the Updated emm Cluster Typing System.

Science.gov (United States)

Chiang-Ni, Chuan; Zheng, Po-Xing; Wang, Shu-Ying; Tsai, Pei-Jane; Chuang, Woei-Jer; Lin, Yee-Shin; Liu, Ching-Chuan; Wu, Jiunn-Jong

2016-01-01

emm typing is the most widely used molecular typing method for the human pathogen Streptococcus pyogenes (group A streptococcus [GAS]). emm typing is based on a small variable region of the emm gene; however, the emm cluster typing system defines GAS types according to the nearly complete sequence of the emm gene. Therefore, emm cluster typing is considered to provide more information regarding the functional and structural properties of M proteins in different emm types of GAS. In the present study, 677 isolates collected between 1994 and 2008 in a hospital in southern Taiwan were analyzed by the emm cluster typing system. emm clusters A-C4, E1, E6, and A-C3 were the most prevalent emm cluster types and accounted for 67.4% of total isolates. emm clusters A-C4 and E1 were associated with noninvasive diseases, whereas E6 was significantly associated with both invasive and noninvasive manifestations. In addition, emm clusters D4, E2, and E3 were significantly associated with invasive manifestations. Furthermore, we found that the functional properties of M protein, including low fibrinogen-binding and high IgG-binding activities, were correlated significantly with invasive manifestations. In summary, the present study provides updated epidemiological information on GAS emm cluster types in southern Taiwan. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Conditions for the evolution of gene clusters in bacterial genomes.

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Sara Ballouz

2010-02-01

Full Text Available Genes encoding proteins in a common pathway are often found near each other along bacterial chromosomes. Several explanations have been proposed to account for the evolution of these structures. For instance, natural selection may directly favour gene clusters through a variety of mechanisms, such as increased efficiency of coregulation. An alternative and controversial hypothesis is the selfish operon model, which asserts that clustered arrangements of genes are more easily transferred to other species, thus improving the prospects for survival of the cluster. According to another hypothesis (the persistence model, genes that are in close proximity are less likely to be disrupted by deletions. Here we develop computational models to study the conditions under which gene clusters can evolve and persist. First, we examine the selfish operon model by re-implementing the simulation and running it under a wide range of conditions. Second, we introduce and study a Moran process in which there is natural selection for gene clustering and rearrangement occurs by genome inversion events. Finally, we develop and study a model that includes selection and inversion, which tracks the occurrence and fixation of rearrangements. Surprisingly, gene clusters fail to evolve under a wide range of conditions. Factors that promote the evolution of gene clusters include a low number of genes in the pathway, a high population size, and in the case of the selfish operon model, a high horizontal transfer rate. The computational analysis here has shown that the evolution of gene clusters can occur under both direct and indirect selection as long as certain conditions hold. Under these conditions the selfish operon model is still viable as an explanation for the evolution of gene clusters.

Electrostatically induced recruitment of membrane peptides into clusters requires ligand binding at both interfaces.

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Yuri N Antonenko

Full Text Available Protein recruitment to specific membrane locations may be governed or facilitated by electrostatic attraction, which originates from a multivalent ligand. Here we explored the energetics of a model system in which this simple electrostatic recruitment mechanism failed. That is, basic poly-L-lysine binding to one leaflet of a planar lipid bilayer did not recruit the triply-charged peptide (O-Pyromellitylgramicidin. Clustering was only observed in cases where PLL was bound to both channel ends. Clustering was indicated (i by the decreased diffusional PLL mobility D(PLL and (ii by an increased lifetime τ(PLL of the clustered channels. In contrast, if PLL was bound to only one leaflet, neither D(PLL nor τ(P changed. Simple calculations suggest that electrostatic repulsion of the unbound ends prevented neighboring OPg dimers from approaching each other. We believe that a similar mechanism may also operate in cell signaling and that it may e.g. contribute to the controversial results obtained for the ligand driven dimerization of G protein-coupled receptors.

Anisotropy of the Coulomb Interaction between Folded Proteins: Consequences for Mesoscopic Aggregation of Lysozyme

Science.gov (United States)

Chan, Ho Yin; Lankevich, Vladimir; Vekilov, Peter G.; Lubchenko, Vassiliy

2012-01-01

Toward quantitative description of protein aggregation, we develop a computationally efficient method to evaluate the potential of mean force between two folded protein molecules that allows for complete sampling of their mutual orientation. Our model is valid at moderate ionic strengths and accounts for the actual charge distribution on the surface of the molecules, the dielectric discontinuity at the protein-solvent interface, and the possibility of protonation or deprotonation of surface residues induced by the electric field due to the other protein molecule. We apply the model to the protein lysozyme, whose solutions exhibit both mesoscopic clusters of protein-rich liquid and liquid-liquid separation; the former requires that protein form complexes with typical lifetimes of approximately milliseconds. We find the electrostatic repulsion is typically lower than the prediction of the Derjaguin-Landau-Verwey-Overbeek theory. The Coulomb interaction in the lowest-energy docking configuration is nonrepulsive, despite the high positive charge on the molecules. Typical docking configurations barely involve protonation or deprotonation of surface residues. The obtained potential of mean force between folded lysozyme molecules is consistent with the location of the liquid-liquid coexistence, but produces dimers that are too short-lived for clusters to exist, suggesting lysozyme undergoes conformational changes during cluster formation. PMID:22768950

Relevant Subspace Clustering

DEFF Research Database (Denmark)

Müller, Emmanuel; Assent, Ira; Günnemann, Stephan

2009-01-01

Subspace clustering aims at detecting clusters in any subspace projection of a high dimensional space. As the number of possible subspace projections is exponential in the number of dimensions, the result is often tremendously large. Recent approaches fail to reduce results to relevant subspace...... clusters. Their results are typically highly redundant, i.e. many clusters are detected multiple times in several projections. In this work, we propose a novel model for relevant subspace clustering (RESCU). We present a global optimization which detects the most interesting non-redundant subspace clusters...... achieves top clustering quality while competing approaches show greatly varying performance....

Is protein structure prediction still an enigma?

African Journals Online (AJOL)

STORAGESEVER

2008-12-29

Dec 29, 2008 ... Computer methods for protein analysis address this problem since they study the .... neighbor methods, molecular dynamic simulation, and approaches .... fuzzy clustering, neural net works, logistic regression, decision tree ...

Horticultural cluster

OpenAIRE

SHERSTIUK S.V.; POSYLAYEVA K.I.

2013-01-01

In the article there are the theoretical and methodological approaches to the nature and existence of the cluster. The cluster differences from other kinds of cooperative and integration associations. Was develop by scientific-practical recommendations for forming a competitive horticultur cluster.

Genetic clustering and polymorphism of the merozoite surface protein-3 of Plasmodium knowlesi clinical isolates from Peninsular Malaysia.

Science.gov (United States)

De Silva, Jeremy Ryan; Lau, Yee Ling; Fong, Mun Yik

2017-01-03

The simian malaria parasite Plasmodium knowlesi has been reported to cause significant numbers of human infection in South East Asia. Its merozoite surface protein-3 (MSP3) is a protein that belongs to a multi-gene family of proteins first found in Plasmodium falciparum. Several studies have evaluated the potential of P. falciparum MSP3 as a potential vaccine candidate. However, to date no detailed studies have been carried out on P. knowlesi MSP3 gene (pkmsp3). The present study investigates the genetic diversity, and haplotypes groups of pkmsp3 in P. knowlesi clinical samples from Peninsular Malaysia. Blood samples were collected from P. knowlesi malaria patients within a period of 4 years (2008-2012). The pkmsp3 gene of the isolates was amplified via PCR, and subsequently cloned and sequenced. The full length pkmsp3 sequence was divided into Domain A and Domain B. Natural selection, genetic diversity, and haplotypes of pkmsp3 were analysed using MEGA6 and DnaSP ver. 5.10.00 programmes. From 23 samples, 48 pkmsp3 sequences were successfully obtained. At the nucleotide level, 101 synonymous and 238 non-synonymous mutations were observed. Tests of neutrality were not significant for the full length, Domain A or Domain B sequences. However, the dN/dS ratio of Domain B indicates purifying selection for this domain. Analysis of the deduced amino acid sequences revealed 42 different haplotypes. Neighbour Joining phylogenetic tree and haplotype network analyses revealed that the haplotypes clustered into two distinct groups. A moderate level of genetic diversity was observed in the pkmsp3 and only the C-terminal region (Domain B) appeared to be under purifying selection. The separation of the pkmsp3 into two haplotype groups provides further evidence of the existence of two distinct P. knowlesi types or lineages. Future studies should investigate the diversity of pkmsp3 among P. knowlesi isolates in North Borneo, where large numbers of human knowlesi malaria infection

TreeCluster: Massively scalable transmission clustering using phylogenetic trees

OpenAIRE

Moshiri, Alexander

2018-01-01

Background: The ability to infer transmission clusters from molecular data is critical to designing and evaluating viral control strategies. Viral sequencing datasets are growing rapidly, but standard methods of transmission cluster inference do not scale well beyond thousands of sequences. Results: I present TreeCluster, a cross-platform tool that performs transmission cluster inference on a given phylogenetic tree orders of magnitude faster than existing inference methods and supports multi...

Voting-based consensus clustering for combining multiple clusterings of chemical structures

Directory of Open Access Journals (Sweden)

Saeed Faisal

2012-12-01

Full Text Available Abstract Background Although many consensus clustering methods have been successfully used for combining multiple classifiers in many areas such as machine learning, applied statistics, pattern recognition and bioinformatics, few consensus clustering methods have been applied for combining multiple clusterings of chemical structures. It is known that any individual clustering method will not always give the best results for all types of applications. So, in this paper, three voting and graph-based consensus clusterings were used for combining multiple clusterings of chemical structures to enhance the ability of separating biologically active molecules from inactive ones in each cluster. Results The cumulative voting-based aggregation algorithm (CVAA, cluster-based similarity partitioning algorithm (CSPA and hyper-graph partitioning algorithm (HGPA were examined. The F-measure and Quality Partition Index method (QPI were used to evaluate the clusterings and the results were compared to the Ward’s clustering method. The MDL Drug Data Report (MDDR dataset was used for experiments and was represented by two 2D fingerprints, ALOGP and ECFP_4. The performance of voting-based consensus clustering method outperformed the Ward’s method using F-measure and QPI method for both ALOGP and ECFP_4 fingerprints, while the graph-based consensus clustering methods outperformed the Ward’s method only for ALOGP using QPI. The Jaccard and Euclidean distance measures were the methods of choice to generate the ensembles, which give the highest values for both criteria. Conclusions The results of the experiments show that consensus clustering methods can improve the effectiveness of chemical structures clusterings. The cumulative voting-based aggregation algorithm (CVAA was the method of choice among consensus clustering methods.

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

OBSERVED SCALING RELATIONS FOR STRONG LENSING CLUSTERS: CONSEQUENCES FOR COSMOLOGY AND CLUSTER ASSEMBLY

International Nuclear Information System (INIS)

Comerford, Julia M.; Moustakas, Leonidas A.; Natarajan, Priyamvada

2010-01-01

Scaling relations of observed galaxy cluster properties are useful tools for constraining cosmological parameters as well as cluster formation histories. One of the key cosmological parameters, σ 8 , is constrained using observed clusters of galaxies, although current estimates of σ 8 from the scaling relations of dynamically relaxed galaxy clusters are limited by the large scatter in the observed cluster mass-temperature (M-T) relation. With a sample of eight strong lensing clusters at 0.3 8 , but combining the cluster concentration-mass relation with the M-T relation enables the inclusion of unrelaxed clusters as well. Thus, the resultant gains in the accuracy of σ 8 measurements from clusters are twofold: the errors on σ 8 are reduced and the cluster sample size is increased. Therefore, the statistics on σ 8 determination from clusters are greatly improved by the inclusion of unrelaxed clusters. Exploring cluster scaling relations further, we find that the correlation between brightest cluster galaxy (BCG) luminosity and cluster mass offers insight into the assembly histories of clusters. We find preliminary evidence for a steeper BCG luminosity-cluster mass relation for strong lensing clusters than the general cluster population, hinting that strong lensing clusters may have had more active merging histories.

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.

Cluster Headache

OpenAIRE

Pearce, Iris

1985-01-01

Cluster headache is the most severe primary headache with recurrent pain attacks described as worse than giving birth. The aim of this paper was to make an overview of current knowledge on cluster headache with a focus on pathophysiology and treatment. This paper presents hypotheses of cluster headache pathophysiology, current treatment options and possible future therapy approaches. For years, the hypothalamus was regarded as the key structure in cluster headache, but is now thought to be pa...

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.

Sizing protein-templated gold nanoclusters by time resolved fluorescence anisotropy decay measurements

Science.gov (United States)

Soleilhac, Antonin; Bertorelle, Franck; Antoine, Rodolphe

2018-03-01

Protein-templated gold nanoclusters (AuNCs) are very attractive due to their unique fluorescence properties. A major problem however may arise due to protein structure changes upon the nucleation of an AuNC within the protein for any future use as in vivo probes, for instance. In this work, we propose a simple and reliable fluorescence based technique measuring the hydrodynamic size of protein-templated gold nanoclusters. This technique uses the relation between the time resolved fluorescence anisotropy decay and the hydrodynamic volume, through the rotational correlation time. We determine the molecular size of protein-directed AuNCs, with protein templates of increasing sizes, e.g. insulin, lysozyme, and bovine serum albumin (BSA). The comparison of sizes obtained by other techniques (e.g. dynamic light scattering and small-angle X-ray scattering) between bare and gold clusters containing proteins allows us to address the volume changes induced either by conformational changes (for BSA) or the formation of protein dimers (for insulin and lysozyme) during cluster formation and incorporation.

Sizing protein-templated gold nanoclusters by time resolved fluorescence anisotropy decay measurements.

Science.gov (United States)

Soleilhac, Antonin; Bertorelle, Franck; Antoine, Rodolphe

2018-03-15

Protein-templated gold nanoclusters (AuNCs) are very attractive due to their unique fluorescence properties. A major problem however may arise due to protein structure changes upon the nucleation of an AuNC within the protein for any future use as in vivo probes, for instance. In this work, we propose a simple and reliable fluorescence based technique measuring the hydrodynamic size of protein-templated gold nanoclusters. This technique uses the relation between the time resolved fluorescence anisotropy decay and the hydrodynamic volume, through the rotational correlation time. We determine the molecular size of protein-directed AuNCs, with protein templates of increasing sizes, e.g. insulin, lysozyme, and bovine serum albumin (BSA). The comparison of sizes obtained by other techniques (e.g. dynamic light scattering and small-angle X-ray scattering) between bare and gold clusters containing proteins allows us to address the volume changes induced either by conformational changes (for BSA) or the formation of protein dimers (for insulin and lysozyme) during cluster formation and incorporation. Copyright © 2017 Elsevier B.V. All rights reserved.

Particle Simulation of Oxidation Induced Band 3 Clustering in Human Erythrocytes.

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Hanae Shimo

2015-06-01

Full Text Available Oxidative stress mediated clustering of membrane protein band 3 plays an essential role in the clearance of damaged and aged red blood cells (RBCs from the circulation. While a number of previous experimental studies have observed changes in band 3 distribution after oxidative treatment, the details of how these clusters are formed and how their properties change under different conditions have remained poorly understood. To address these issues, a framework that enables the simultaneous monitoring of the temporal and spatial changes following oxidation is needed. In this study, we established a novel simulation strategy that incorporates deterministic and stochastic reactions with particle reaction-diffusion processes, to model band 3 cluster formation at single molecule resolution. By integrating a kinetic model of RBC antioxidant metabolism with a model of band 3 diffusion, we developed a model that reproduces the time-dependent changes of glutathione and clustered band 3 levels, as well as band 3 distribution during oxidative treatment, observed in prior studies. We predicted that cluster formation is largely dependent on fast reverse reaction rates, strong affinity between clustering molecules, and irreversible hemichrome binding. We further predicted that under repeated oxidative perturbations, clusters tended to progressively grow and shift towards an irreversible state. Application of our model to simulate oxidation in RBCs with cytoskeletal deficiency also suggested that oxidation leads to more enhanced clustering compared to healthy RBCs. Taken together, our model enables the prediction of band 3 spatio-temporal profiles under various situations, thus providing valuable insights to potentially aid understanding mechanisms for removing senescent and premature RBCs.

Particle Simulation of Oxidation Induced Band 3 Clustering in Human Erythrocytes.

Science.gov (United States)

Shimo, Hanae; Arjunan, Satya Nanda Vel; Machiyama, Hiroaki; Nishino, Taiko; Suematsu, Makoto; Fujita, Hideaki; Tomita, Masaru; Takahashi, Koichi

2015-06-01

Oxidative stress mediated clustering of membrane protein band 3 plays an essential role in the clearance of damaged and aged red blood cells (RBCs) from the circulation. While a number of previous experimental studies have observed changes in band 3 distribution after oxidative treatment, the details of how these clusters are formed and how their properties change under different conditions have remained poorly understood. To address these issues, a framework that enables the simultaneous monitoring of the temporal and spatial changes following oxidation is needed. In this study, we established a novel simulation strategy that incorporates deterministic and stochastic reactions with particle reaction-diffusion processes, to model band 3 cluster formation at single molecule resolution. By integrating a kinetic model of RBC antioxidant metabolism with a model of band 3 diffusion, we developed a model that reproduces the time-dependent changes of glutathione and clustered band 3 levels, as well as band 3 distribution during oxidative treatment, observed in prior studies. We predicted that cluster formation is largely dependent on fast reverse reaction rates, strong affinity between clustering molecules, and irreversible hemichrome binding. We further predicted that under repeated oxidative perturbations, clusters tended to progressively grow and shift towards an irreversible state. Application of our model to simulate oxidation in RBCs with cytoskeletal deficiency also suggested that oxidation leads to more enhanced clustering compared to healthy RBCs. Taken together, our model enables the prediction of band 3 spatio-temporal profiles under various situations, thus providing valuable insights to potentially aid understanding mechanisms for removing senescent and premature RBCs.

Emerging critical roles of Fe-S clusters in DNA replication and repair

Science.gov (United States)

Fuss, Jill O.; Tsai, Chi-Lin; Ishida, Justin P.; Tainer, John A.

2015-01-01

Fe-S clusters are partners in the origin of life that predate cells, acetyl-CoA metabolism, DNA, and the RNA world. The double helix solved the mystery of DNA replication by base pairing for accurate copying. Yet, for genome stability necessary to life, the double helix has equally important implications for damage repair. Here we examine striking advances that uncover Fe-S cluster roles both in copying the genetic sequence by DNA polymerases and in crucial repair processes for genome maintenance, as mutational defects cause cancer and degenerative disease. Moreover, we examine an exciting, controversial role for Fe-S clusters in a third element required for life – the long-range coordination and regulation of replication and repair events. By their ability to delocalize electrons over both Fe and S centers, Fe-S clusters have unbeatable features for protein conformational control and charge transfer via double-stranded DNA that may fundamentally transform our understanding of life, replication, and repair. PMID:25655665

Properties of an ionised-cluster beam from a vaporised-cluster ion source

International Nuclear Information System (INIS)

Takagi, T.; Yamada, I.; Sasaki, A.

1978-01-01

A new type of ion source vaporised-metal cluster ion source, has been developed for deposition and epitaxy. A cluster consisting of 10 2 to 10 3 atoms coupled loosely together is formed by adiabatic expansion ejecting the vapour of materials into a high-vacuum region through the nozzle of a heated crucible. The clusters are ionised by electron bombardment and accelerated with neutral clusters toward a substrate. In this paper, mechanisms of cluster formation experimental results of the cluster size (atoms/cluster) and its distribution, and characteristics of the cluster ion beams are reported. The size is calculated from the kinetic equation E = (1/2)mNVsub(ej) 2 , where E is the cluster beam energy, Vsub(ej) is the ejection velocity, m is the mass of atom and N is the cluster size. The energy and the velocity of the cluster are measured by an electrostatic 127 0 energy analyser and a rotating disc system, respectively. The cluster size obtained for Ag is about 5 x 10 2 to 2 x 10 3 atoms. The retarding potential method is used to confirm the results for Ag. The same dependence on cluster size for metals such as Ag, Cu and Pb has been obtained in previous experiments. In the cluster state the cluster ion beam is easily produced by electron bombardment. About 50% of ionised clusters are obtained under typical operation conditions, because of the large ionisation cross sections of the clusters. To obtain a uniform spatial distribution, the ionising electrode system is also discussed. The new techniques are termed ionised-cluster beam deposition (ICBD) and epitaxy (ICBE). (author)

Feasibility Study of Parallel Finite Element Analysis on Cluster-of-Clusters

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Muraoka, Masae; Okuda, Hiroshi

With the rapid growth of WAN infrastructure and development of Grid middleware, it's become a realistic and attractive methodology to connect cluster machines on wide-area network for the execution of computation-demanding applications. Many existing parallel finite element (FE) applications have been, however, designed and developed with a single computing resource in mind, since such applications require frequent synchronization and communication among processes. There have been few FE applications that can exploit the distributed environment so far. In this study, we explore the feasibility of FE applications on the cluster-of-clusters. First, we classify FE applications into two types, tightly coupled applications (TCA) and loosely coupled applications (LCA) based on their communication pattern. A prototype of each application is implemented on the cluster-of-clusters. We perform numerical experiments executing TCA and LCA on both the cluster-of-clusters and a single cluster. Thorough these experiments, by comparing the performances and communication cost in each case, we evaluate the feasibility of FEA on the cluster-of-clusters.

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”

Characterization of the photolyase-like iron sulfur protein PhrB from Agrobacterium tumefaciens by Mössbauer spectroscopy

Science.gov (United States)

Bauer, T. O.; Graf, D.; Lamparter, T.; Schünemann, V.

2014-04-01

High field Mössbauer spectroscopy has been used to characterize the [4Fe-4S] 2 +cluster of the protein PhrB from Agrobacterium tumefaciens which belongs to the cryptochrome/photolyase family (CPF) and which biological function has previously been shown to be DNA repair. Mössbauer spectra taken of the as prepared protein reveal δ = 0. 42 mms - 1, and Δ E Q = 1. 26 mms - 1as well as an asymmetry parameter of η = 0. 8. These parameters are characteristic for a ferredoxin-type [4Fe-4S] 2 +cluster. In order to investigate whether this cluster is involved in DNA-repair the protein has also been studied in its photoactivated state during DNA binding. The so obtained data sets exhibit essentially the same Mössbauer parameters as those of the non-activated PhrB. This indicates that during DNA repair the [4Fe-4S] 2 +cluster of PhrB has no significant amounts of transition states which have conformational changes compared to the resting state of the protein and which have life times of several seconds or longer.

Categorias Cluster

OpenAIRE

Queiroz, Dayane Andrade

2015-01-01

Neste trabalho apresentamos as categorias cluster, que foram introduzidas por Aslak Bakke Buan, Robert Marsh, Markus Reineke, Idun Reiten e Gordana Todorov, com o objetivo de categoriíicar as algebras cluster criadas em 2002 por Sergey Fomin e Andrei Zelevinsky. Os autores acima, em [4], mostraram que existe uma estreita relação entre algebras cluster e categorias cluster para quivers cujo grafo subjacente é um diagrama de Dynkin. Para isto desenvolveram uma teoria tilting na estrutura triang...

BRIGHTEST CLUSTER GALAXIES AND CORE GAS DENSITY IN REXCESS CLUSTERS

International Nuclear Information System (INIS)

Haarsma, Deborah B.; Leisman, Luke; Donahue, Megan; Bruch, Seth; Voit, G. Mark; Boehringer, Hans; Pratt, Gabriel W.; Pierini, Daniele; Croston, Judith H.; Arnaud, Monique

2010-01-01

We investigate the relationship between brightest cluster galaxies (BCGs) and their host clusters using a sample of nearby galaxy clusters from the Representative XMM-Newton Cluster Structure Survey. The sample was imaged with the Southern Observatory for Astrophysical Research in R band to investigate the mass of the old stellar population. Using a metric radius of 12 h -1 kpc, we found that the BCG luminosity depends weakly on overall cluster mass as L BCG ∝ M 0.18±0.07 cl , consistent with previous work. We found that 90% of the BCGs are located within 0.035 r 500 of the peak of the X-ray emission, including all of the cool core (CC) clusters. We also found an unexpected correlation between the BCG metric luminosity and the core gas density for non-cool-core (non-CC) clusters, following a power law of n e ∝ L 2.7±0.4 BCG (where n e is measured at 0.008 r 500 ). The correlation is not easily explained by star formation (which is weak in non-CC clusters) or overall cluster mass (which is not correlated with core gas density). The trend persists even when the BCG is not located near the peak of the X-ray emission, so proximity is not necessary. We suggest that, for non-CC clusters, this correlation implies that the same process that sets the central entropy of the cluster gas also determines the central stellar density of the BCG, and that this underlying physical process is likely to be mergers.

Speed Controls in Translating Secretory Proteins in Eukaryotes - an Evolutionary Perspective

Science.gov (United States)

Mahlab, Shelly; Linial, Michal

2014-01-01

Protein translation is the most expensive operation in dividing cells from bacteria to humans. Therefore, managing the speed and allocation of resources is subject to tight control. From bacteria to humans, clusters of relatively rare tRNA codons at the N′-terminal of mRNAs have been implicated in attenuating the process of ribosome allocation, and consequently the translation rate in a broad range of organisms. The current interpretation of “slow” tRNA codons does not distinguish between protein translations mediated by free- or endoplasmic reticulum (ER)-bound ribosomes. We demonstrate that proteins translated by free- or ER-bound ribosomes exhibit different overall properties in terms of their translation efficiency and speed in yeast, fly, plant, worm, bovine and human. We note that only secreted or membranous proteins with a Signal peptide (SP) are specified by segments of “slow” tRNA at the N′-terminal, followed by abundant codons that are considered “fast.” Such profiles apply to 3100 proteins of the human proteome that are composed of secreted and signal peptide (SP)-assisted membranous proteins. Remarkably, the bulks of the proteins (12,000), or membranous proteins lacking SP (3400), do not have such a pattern. Alternation of “fast” and “slow” codons was found also in proteins that translocate to mitochondria through transit peptides (TP). The differential clusters of tRNA adapted codons is not restricted to the N′-terminal of transcripts. Specifically, Glycosylphosphatidylinositol (GPI)-anchored proteins are unified by clusters of low adapted tRNAs codons at the C′-termini. Furthermore, selection of amino acids types and specific codons was shown as the driving force which establishes the translation demands for the secretory proteome. We postulate that “hard-coded” signals within the secretory proteome assist the steps of protein maturation and folding. Specifically, “speed control” signals for delaying the translation

Scientific Cluster Deployment and Recovery - Using puppet to simplify cluster management

Science.gov (United States)

Hendrix, Val; Benjamin, Doug; Yao, Yushu

2012-12-01

Deployment, maintenance and recovery of a scientific cluster, which has complex, specialized services, can be a time consuming task requiring the assistance of Linux system administrators, network engineers as well as domain experts. Universities and small institutions that have a part-time FTE with limited time for and knowledge of the administration of such clusters can be strained by such maintenance tasks. This current work is the result of an effort to maintain a data analysis cluster (DAC) with minimal effort by a local system administrator. The realized benefit is the scientist, who is the local system administrator, is able to focus on the data analysis instead of the intricacies of managing a cluster. Our work provides a cluster deployment and recovery process (CDRP) based on the puppet configuration engine allowing a part-time FTE to easily deploy and recover entire clusters with minimal effort. Puppet is a configuration management system (CMS) used widely in computing centers for the automatic management of resources. Domain experts use Puppet's declarative language to define reusable modules for service configuration and deployment. Our CDRP has three actors: domain experts, a cluster designer and a cluster manager. The domain experts first write the puppet modules for the cluster services. A cluster designer would then define a cluster. This includes the creation of cluster roles, mapping the services to those roles and determining the relationships between the services. Finally, a cluster manager would acquire the resources (machines, networking), enter the cluster input parameters (hostnames, IP addresses) and automatically generate deployment scripts used by puppet to configure it to act as a designated role. In the event of a machine failure, the originally generated deployment scripts along with puppet can be used to easily reconfigure a new machine. The cluster definition produced in our CDRP is an integral part of automating cluster deployment

TLR-activated repression of Fe-S cluster biogenesis drives a metabolic shift and alters histone and tubulin acetylation.

Science.gov (United States)

Tong, Wing-Hang; Maio, Nunziata; Zhang, De-Liang; Palmieri, Erika M; Ollivierre, Hayden; Ghosh, Manik C; McVicar, Daniel W; Rouault, Tracey A

2018-05-22

Given the essential roles of iron-sulfur (Fe-S) cofactors in mediating electron transfer in the mitochondrial respiratory chain and supporting heme biosynthesis, mitochondrial dysfunction is a common feature in a growing list of human Fe-S cluster biogenesis disorders, including Friedreich ataxia and GLRX5-related sideroblastic anemia. Here, our studies showed that restriction of Fe-S cluster biogenesis not only compromised mitochondrial oxidative metabolism but also resulted in decreased overall histone acetylation and increased H3K9me3 levels in the nucleus and increased acetylation of α-tubulin in the cytosol by decreasing the lipoylation of the pyruvate dehydrogenase complex, decreasing levels of succinate dehydrogenase and the histone acetyltransferase ELP3, and increasing levels of the tubulin acetyltransferase MEC17. Previous studies have shown that the metabolic shift in Toll-like receptor (TLR)-activated myeloid cells involves rapid activation of glycolysis and subsequent mitochondrial respiratory failure due to nitric oxide (NO)-mediated damage to Fe-S proteins. Our studies indicated that TLR activation also actively suppresses many components of the Fe-S cluster biogenesis machinery, which exacerbates NO-mediated damage to Fe-S proteins by interfering with cluster recovery. These results reveal new regulatory pathways and novel roles of the Fe-S cluster biogenesis machinery in modifying the epigenome and acetylome and provide new insights into the etiology of Fe-S cluster biogenesis disorders.

Crystal structure of the FeS cluster-containing nucleotide excision repair helicase XPD.

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Stefanie C Wolski

2008-06-01

Full Text Available DNA damage recognition by the nucleotide excision repair pathway requires an initial step identifying helical distortions in the DNA and a proofreading step verifying the presence of a lesion. This proofreading step is accomplished in eukaryotes by the TFIIH complex. The critical damage recognition component of TFIIH is the XPD protein, a DNA helicase that unwinds DNA and identifies the damage. Here, we describe the crystal structure of an archaeal XPD protein with high sequence identity to the human XPD protein that reveals how the structural helicase framework is combined with additional elements for strand separation and DNA scanning. Two RecA-like helicase domains are complemented by a 4Fe4S cluster domain, which has been implicated in damage recognition, and an alpha-helical domain. The first helicase domain together with the helical and 4Fe4S-cluster-containing domains form a central hole with a diameter sufficient in size to allow passage of a single stranded DNA. Based on our results, we suggest a model of how DNA is bound to the XPD protein, and can rationalize several of the mutations in the human XPD gene that lead to one of three severe diseases, xeroderma pigmentosum, Cockayne syndrome, and trichothiodystrophy.

Cluster-cluster correlations in the two-dimensional stationary Ising-model

International Nuclear Information System (INIS)

Klassmann, A.

1997-01-01

In numerical integration of the Cahn-Hillard equation, which describes Oswald rising in a two-phase matrix, N. Masbaum showed that spatial correlations between clusters scale with respect to the mean cluster size (itself a function of time). T. B. Liverpool showed by Monte Carlo simulations for the Ising model that the analogous correlations have a similar form. Both demonstrated that immediately around each cluster there is some depletion area followed by something like a ring of clusters of the same size as the original one. More precisely, it has been shown that the distribution of clusters around a given cluster looks like a sinus-curve decaying exponentially with respect to the distance to a constant value

GraphCrunch 2: Software tool for network modeling, alignment and clustering.

Science.gov (United States)

Kuchaiev, Oleksii; Stevanović, Aleksandar; Hayes, Wayne; Pržulj, Nataša

2011-01-19

Recent advancements in experimental biotechnology have produced large amounts of protein-protein interaction (PPI) data. The topology of PPI networks is believed to have a strong link to their function. Hence, the abundance of PPI data for many organisms stimulates the development of computational techniques for the modeling, comparison, alignment, and clustering of networks. In addition, finding representative models for PPI networks will improve our understanding of the cell just as a model of gravity has helped us understand planetary motion. To decide if a model is representative, we need quantitative comparisons of model networks to real ones. However, exact network comparison is computationally intractable and therefore several heuristics have been used instead. Some of these heuristics are easily computable "network properties," such as the degree distribution, or the clustering coefficient. An important special case of network comparison is the network alignment problem. Analogous to sequence alignment, this problem asks to find the "best" mapping between regions in two networks. It is expected that network alignment might have as strong an impact on our understanding of biology as sequence alignment has had. Topology-based clustering of nodes in PPI networks is another example of an important network analysis problem that can uncover relationships between interaction patterns and phenotype. We introduce the GraphCrunch 2 software tool, which addresses these problems. It is a significant extension of GraphCrunch which implements the most popular random network models and compares them with the data networks with respect to many network properties. Also, GraphCrunch 2 implements the GRAph ALigner algorithm ("GRAAL") for purely topological network alignment. GRAAL can align any pair of networks and exposes large, dense, contiguous regions of topological and functional similarities far larger than any other existing tool. Finally, GraphCruch 2 implements an

GraphCrunch 2: Software tool for network modeling, alignment and clustering

Directory of Open Access Journals (Sweden)

Hayes Wayne

2011-01-01

Full Text Available Abstract Background Recent advancements in experimental biotechnology have produced large amounts of protein-protein interaction (PPI data. The topology of PPI networks is believed to have a strong link to their function. Hence, the abundance of PPI data for many organisms stimulates the development of computational techniques for the modeling, comparison, alignment, and clustering of networks. In addition, finding representative models for PPI networks will improve our understanding of the cell just as a model of gravity has helped us understand planetary motion. To decide if a model is representative, we need quantitative comparisons of model networks to real ones. However, exact network comparison is computationally intractable and therefore several heuristics have been used instead. Some of these heuristics are easily computable "network properties," such as the degree distribution, or the clustering coefficient. An important special case of network comparison is the network alignment problem. Analogous to sequence alignment, this problem asks to find the "best" mapping between regions in two networks. It is expected that network alignment might have as strong an impact on our understanding of biology as sequence alignment has had. Topology-based clustering of nodes in PPI networks is another example of an important network analysis problem that can uncover relationships between interaction patterns and phenotype. Results We introduce the GraphCrunch 2 software tool, which addresses these problems. It is a significant extension of GraphCrunch which implements the most popular random network models and compares them with the data networks with respect to many network properties. Also, GraphCrunch 2 implements the GRAph ALigner algorithm ("GRAAL" for purely topological network alignment. GRAAL can align any pair of networks and exposes large, dense, contiguous regions of topological and functional similarities far larger than any other

Structure and Sequence Analyses of Clustered Protocadherins Reveal Antiparallel Interactions that Mediate Homophilic Specificity.

Science.gov (United States)

Nicoludis, John M; Lau, Sze-Yi; Schärfe, Charlotta P I; Marks, Debora S; Weihofen, Wilhelm A; Gaudet, Rachelle

2015-11-03

Clustered protocadherin (Pcdh) proteins mediate dendritic self-avoidance in neurons via specific homophilic interactions in their extracellular cadherin (EC) domains. We determined crystal structures of EC1-EC3, containing the homophilic specificity-determining region, of two mouse clustered Pcdh isoforms (PcdhγA1 and PcdhγC3) to investigate the nature of the homophilic interaction. Within the crystal lattices, we observe antiparallel interfaces consistent with a role in trans cell-cell contact. Antiparallel dimerization is supported by evolutionary correlations. Two interfaces, located primarily on EC2-EC3, involve distinctive clustered Pcdh structure and sequence motifs, lack predicted glycosylation sites, and contain residues highly conserved in orthologs but not paralogs, pointing toward their biological significance as homophilic interaction interfaces. These two interfaces are similar yet distinct, reflecting a possible difference in interaction architecture between clustered Pcdh subfamilies. These structures initiate a molecular understanding of clustered Pcdh assemblies that are required to produce functional neuronal networks. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

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Jun Ren

2014-01-01

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

Meaningful Clusters

Energy Technology Data Exchange (ETDEWEB)

Sanfilippo, Antonio P.; Calapristi, Augustin J.; Crow, Vernon L.; Hetzler, Elizabeth G.; Turner, Alan E.

2004-05-26

We present an approach to the disambiguation of cluster labels that capitalizes on the notion of semantic similarity to assign WordNet senses to cluster labels. The approach provides interesting insights on how document clustering can provide the basis for developing a novel approach to word sense disambiguation.

Macroeconomic Dimensions in the Clusterization Processes: Lithuanian Biomass Cluster Case

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Navickas Valentinas

2017-03-01

Full Text Available The Future production systems’ increasing significance will impose work, which maintains not a competitive, but a collaboration basis, with concentrated resources and expertise, which can help to reach the general purpose. One form of collaboration among medium-size business organizations is work in clusters. Clusterization as a phenomenon has been known from quite a long time, but it offers simple benefits to researches at micro and medium levels. The clusterization process evaluation in macroeconomic dimensions has been comparatively little investigated. Thereby, in this article, the clusterization processes is analysed by concentrating our attention on macroeconomic factor researches. The authors analyse clusterization’s influence on country’s macroeconomic growth; they apply a structure research methodology for clusterization’s macroeconomic influence evaluation and propose that clusterization processes benefit macroeconomic analysis. The theoretical model of clusterization processes was validated by referring to a biomass cluster case. Because biomass cluster case is a new phenomenon, currently there are no other scientific approaches to them. The authors’ accomplished researches show that clusterization allows the achievement of a large positive slip in macroeconomics, which proves to lead to a high value added to creation, a faster country economic growth, and social situation amelioration.

Clustering Dycom

KAUST Repository

Minku, Leandro L.

2017-10-06

Background: Software Effort Estimation (SEE) can be formulated as an online learning problem, where new projects are completed over time and may become available for training. In this scenario, a Cross-Company (CC) SEE approach called Dycom can drastically reduce the number of Within-Company (WC) projects needed for training, saving the high cost of collecting such training projects. However, Dycom relies on splitting CC projects into different subsets in order to create its CC models. Such splitting can have a significant impact on Dycom\\'s predictive performance. Aims: This paper investigates whether clustering methods can be used to help finding good CC splits for Dycom. Method: Dycom is extended to use clustering methods for creating the CC subsets. Three different clustering methods are investigated, namely Hierarchical Clustering, K-Means, and Expectation-Maximisation. Clustering Dycom is compared against the original Dycom with CC subsets of different sizes, based on four SEE databases. A baseline WC model is also included in the analysis. Results: Clustering Dycom with K-Means can potentially help to split the CC projects, managing to achieve similar or better predictive performance than Dycom. However, K-Means still requires the number of CC subsets to be pre-defined, and a poor choice can negatively affect predictive performance. EM enables Dycom to automatically set the number of CC subsets while still maintaining or improving predictive performance with respect to the baseline WC model. Clustering Dycom with Hierarchical Clustering did not offer significant advantage in terms of predictive performance. Conclusion: Clustering methods can be an effective way to automatically generate Dycom\\'s CC subsets.

HIV protein sequence hotspots for crosstalk with host hub proteins.

Directory of Open Access Journals (Sweden)

Mahdi Sarmady

Full Text Available HIV proteins target host hub proteins for transient binding interactions. The presence of viral proteins in the infected cell results in out-competition of host proteins in their interaction with hub proteins, drastically affecting cell physiology. Functional genomics and interactome datasets can be used to quantify the sequence hotspots on the HIV proteome mediating interactions with host hub proteins. In this study, we used the HIV and human interactome databases to identify HIV targeted host hub proteins and their host binding partners (H2. We developed a high throughput computational procedure utilizing motif discovery algorithms on sets of protein sequences, including sequences of HIV and H2 proteins. We identified as HIV sequence hotspots those linear motifs that are highly conserved on HIV sequences and at the same time have a statistically enriched presence on the sequences of H2 proteins. The HIV protein motifs discovered in this study are expressed by subsets of H2 host proteins potentially outcompeted by HIV proteins. A large subset of these motifs is involved in cleavage, nuclear localization, phosphorylation, and transcription factor binding events. Many such motifs are clustered on an HIV sequence in the form of hotspots. The sequential positions of these hotspots are consistent with the curated literature on phenotype altering residue mutations, as well as with existing binding site data. The hotspot map produced in this study is the first global portrayal of HIV motifs involved in altering the host protein network at highly connected hub nodes.

LMC clusters: young

International Nuclear Information System (INIS)

Freeman, K.C.

1980-01-01

The young globular clusters of the LMC have ages of 10 7 -10 8 y. Their masses and structure are similar to those of the smaller galactic globular clusters. Their stellar mass functions (in the mass range 6 solar masses to 1.2 solar masses) vary greatly from cluster to cluster, although the clusters are similar in total mass, age, structure and chemical composition. It would be very interesting to know why these clusters are forming now in the LMC and not in the Galaxy. The author considers the 'young globular' or 'blue populous' clusters of the LMC. The ages of these objects are 10 7 to 10 8 y, and their masses are 10 4 to 10 5 solar masses, so they are populous enough to be really useful for studying the evolution of massive stars. The author concentrates on the structure and stellar content of these young clusters. (Auth.)

Major cluster mergers and the location of the brightest cluster galaxy

International Nuclear Information System (INIS)

Martel, Hugo; Robichaud, Fidèle; Barai, Paramita

2014-01-01

Using a large N-body cosmological simulation combined with a subgrid treatment of galaxy formation, merging, and tidal destruction, we study the formation and evolution of the galaxy and cluster population in a comoving volume (100 Mpc) 3 in a ΛCDM universe. At z = 0, our computational volume contains 1788 clusters with mass M cl > 1.1 × 10 12 M ☉ , including 18 massive clusters with M cl > 10 14 M ☉ . It also contains 1, 088, 797 galaxies with mass M gal ≥ 2 × 10 9 M ☉ and luminosity L > 9.5 × 10 5 L ☉ . For each cluster, we identified the brightest cluster galaxy (BCG). We then computed two separate statistics: the fraction f BNC of clusters in which the BCG is not the closest galaxy to the center of the cluster in projection, and the ratio Δv/σ, where Δv is the difference in radial velocity between the BCG and the whole cluster and σ is the radial velocity dispersion of the cluster. We found that f BNC increases from 0.05 for low-mass clusters (M cl ∼ 10 12 M ☉ ) to 0.5 for high-mass clusters (M cl > 10 14 M ☉ ) with very little dependence on cluster redshift. Most of this result turns out to be a projection effect and when we consider three-dimensional distances instead of projected distances, f BNC increases only to 0.2 at high-cluster mass. The values of Δv/σ vary from 0 to 1.8, with median values in the range 0.03-0.15 when considering all clusters, and 0.12-0.31 when considering only massive clusters. These results are consistent with previous observational studies and indicate that the central galaxy paradigm, which states that the BCG should be at rest at the center of the cluster, is usually valid, but exceptions are too common to be ignored. We built merger trees for the 18 most massive clusters in the simulation. Analysis of these trees reveal that 16 of these clusters have experienced 1 or several major or semi-major mergers in the past. These mergers leave each cluster in a non-equilibrium state, but eventually the cluster

The Sorcerer II Global Ocean Sampling Expedition: Expanding theUniverse of Protein Families