Dynamic zebrafish interactome reveals transcriptional mechanisms of dioxin toxicity.

Directory of Open Access Journals (Sweden)

Andrey Alexeyenko

2010-05-01

Full Text Available In order to generate hypotheses regarding the mechanisms by which 2,3,7,8-tetrachlorodibenzo-p-dioxin (dioxin causes toxicity, we analyzed global gene expression changes in developing zebrafish embryos exposed to this potent toxicant in the context of a dynamic gene network. For this purpose, we also computationally inferred a zebrafish (Danio rerio interactome based on orthologs and interaction data from other eukaryotes.Using novel computational tools to analyze this interactome, we distinguished between dioxin-dependent and dioxin-independent interactions between proteins, and tracked the temporal propagation of dioxin-dependent transcriptional changes from a few genes that were altered initially, to large groups of biologically coherent genes at later times. The most notable processes altered at later developmental stages were calcium and iron metabolism, embryonic morphogenesis including neuronal and retinal development, a variety of mitochondria-related functions, and generalized stress response (not including induction of antioxidant genes. Within the interactome, many of these responses were connected to cytochrome P4501A (cyp1a as well as other genes that were dioxin-regulated one day after exposure. This suggests that cyp1a may play a key role initiating the toxic dysregulation of those processes, rather than serving simply as a passive marker of dioxin exposure, as suggested by earlier research.Thus, a powerful microarray experiment coupled with a flexible interactome and multi-pronged interactome tools (which are now made publicly available for microarray analysis and related work suggest the hypothesis that dioxin, best known in fish as a potent cardioteratogen, has many other targets. Many of these types of toxicity have been observed in mammalian species and are potentially caused by alterations to cyp1a.

RNA-Binding Proteins Revisited – The Emerging Arabidopsis mRNA Interactome

KAUST Repository

Köster, Tino

2017-04-13

RNA–protein interaction is an important checkpoint to tune gene expression at the RNA level. Global identification of proteins binding in vivo to mRNA has been possible through interactome capture – where proteins are fixed to target RNAs by UV crosslinking and purified through affinity capture of polyadenylated RNA. In Arabidopsis over 500 RNA-binding proteins (RBPs) enriched in UV-crosslinked samples have been identified. As in mammals and yeast, the mRNA interactomes came with a few surprises. For example, a plethora of the proteins caught on RNA had not previously been linked to RNA-mediated processes, for example proteins of intermediary metabolism. Thus, the studies provide unprecedented insights into the composition of the mRNA interactome, highlighting the complexity of RNA-mediated processes.

RNA-Binding Proteins Revisited – The Emerging Arabidopsis mRNA Interactome

KAUST Repository

Kö ster, Tino; Marondedze, Claudius; Meyer, Katja; Staiger, Dorothee

2017-01-01

RNA–protein interaction is an important checkpoint to tune gene expression at the RNA level. Global identification of proteins binding in vivo to mRNA has been possible through interactome capture – where proteins are fixed to target RNAs by UV crosslinking and purified through affinity capture of polyadenylated RNA. In Arabidopsis over 500 RNA-binding proteins (RBPs) enriched in UV-crosslinked samples have been identified. As in mammals and yeast, the mRNA interactomes came with a few surprises. For example, a plethora of the proteins caught on RNA had not previously been linked to RNA-mediated processes, for example proteins of intermediary metabolism. Thus, the studies provide unprecedented insights into the composition of the mRNA interactome, highlighting the complexity of RNA-mediated processes.

Arabidopsis G-protein interactome reveals connections to cell wall carbohydrates and morphogenesis.

Science.gov (United States)

Klopffleisch, Karsten; Phan, Nguyen; Augustin, Kelsey; Bayne, Robert S; Booker, Katherine S; Botella, Jose R; Carpita, Nicholas C; Carr, Tyrell; Chen, Jin-Gui; Cooke, Thomas Ryan; Frick-Cheng, Arwen; Friedman, Erin J; Fulk, Brandon; Hahn, Michael G; Jiang, Kun; Jorda, Lucia; Kruppe, Lydia; Liu, Chenggang; Lorek, Justine; McCann, Maureen C; Molina, Antonio; Moriyama, Etsuko N; Mukhtar, M Shahid; Mudgil, Yashwanti; Pattathil, Sivakumar; Schwarz, John; Seta, Steven; Tan, Matthew; Temp, Ulrike; Trusov, Yuri; Urano, Daisuke; Welter, Bastian; Yang, Jing; Panstruga, Ralph; Uhrig, Joachim F; Jones, Alan M

2011-09-27

The heterotrimeric G-protein complex is minimally composed of Gα, Gβ, and Gγ subunits. In the classic scenario, the G-protein complex is the nexus in signaling from the plasma membrane, where the heterotrimeric G-protein associates with heptahelical G-protein-coupled receptors (GPCRs), to cytoplasmic target proteins called effectors. Although a number of effectors are known in metazoans and fungi, none of these are predicted to exist in their canonical forms in plants. To identify ab initio plant G-protein effectors and scaffold proteins, we screened a set of proteins from the G-protein complex using two-hybrid complementation in yeast. After deep and exhaustive interrogation, we detected 544 interactions between 434 proteins, of which 68 highly interconnected proteins form the core G-protein interactome. Within this core, over half of the interactions comprising two-thirds of the nodes were retested and validated as genuine in planta. Co-expression analysis in combination with phenotyping of loss-of-function mutations in a set of core interactome genes revealed a novel role for G-proteins in regulating cell wall modification.

Mapping the Small Molecule Interactome by Mass Spectrometry.

Science.gov (United States)

Flaxman, Hope A; Woo, Christina M

2018-01-16

Mapping small molecule interactions throughout the proteome provides the critical structural basis for functional analysis of their impact on biochemistry. However, translation of mass spectrometry-based proteomics methods to directly profile the interaction between a small molecule and the whole proteome is challenging because of the substoichiometric nature of many interactions, the diversity of covalent and noncovalent interactions involved, and the subsequent computational complexity associated with their spectral assignment. Recent advances in chemical proteomics have begun fill this gap to provide a structural basis for the breadth of small molecule-protein interactions in the whole proteome. Innovations enabling direct characterization of the small molecule interactome include faster, more sensitive instrumentation coupled to chemical conjugation, enrichment, and labeling methods that facilitate detection and assignment. These methods have started to measure molecular interaction hotspots due to inherent differences in local amino acid reactivity and binding affinity throughout the proteome. Measurement of the small molecule interactome is producing structural insights and methods for probing and engineering protein biochemistry. Direct structural characterization of the small molecule interactome is a rapidly emerging area pushing new frontiers in biochemistry at the interface of small molecules and the proteome.

Characterization and interactome study of white spot syndrome virus envelope protein VP11.

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Wang-Jing Liu

Full Text Available White spot syndrome virus (WSSV is a large enveloped virus. The WSSV viral particle consists of three structural layers that surround its core DNA: an outer envelope, a tegument and a nucleocapsid. Here we characterize the WSSV structural protein VP11 (WSSV394, GenBank accession number AF440570, and use an interactome approach to analyze the possible associations between this protein and an array of other WSSV and host proteins. Temporal transcription analysis showed that vp11 is an early gene. Western blot hybridization of the intact viral particles and fractionation of the viral components, and immunoelectron microscopy showed that VP11 is an envelope protein. Membrane topology software predicted VP11 to be a type of transmembrane protein with a highly hydrophobic transmembrane domain at its N-terminal. Based on an immunofluorescence assay performed on VP11-transfected Sf9 cells and a trypsin digestion analysis of the virion, we conclude that, contrary to topology software prediction, the C-terminal of this protein is in fact inside the virion. Yeast two-hybrid screening combined with co-immunoprecipitation assays found that VP11 directly interacted with at least 12 other WSSV structural proteins as well as itself. An oligomerization assay further showed that VP11 could form dimers. VP11 is also the first reported WSSV structural protein to interact with the major nucleocapsid protein VP664.

Prediction Reweighting for Domain Adaptation.

Science.gov (United States)

Shuang Li; Shiji Song; Gao Huang

2017-07-01

There are plenty of classification methods that perform well when training and testing data are drawn from the same distribution. However, in real applications, this condition may be violated, which causes degradation of classification accuracy. Domain adaptation is an effective approach to address this problem. In this paper, we propose a general domain adaptation framework from the perspective of prediction reweighting, from which a novel approach is derived. Different from the major domain adaptation methods, our idea is to reweight predictions of the training classifier on testing data according to their signed distance to the domain separator, which is a classifier that distinguishes training data (from source domain) and testing data (from target domain). We then propagate the labels of target instances with larger weights to ones with smaller weights by introducing a manifold regularization method. It can be proved that our reweighting scheme effectively brings the source and target domains closer to each other in an appropriate sense, such that classification in target domain becomes easier. The proposed method can be implemented efficiently by a simple two-stage algorithm, and the target classifier has a closed-form solution. The effectiveness of our approach is verified by the experiments on artificial datasets and two standard benchmarks, a visual object recognition task and a cross-domain sentiment analysis of text. Experimental results demonstrate that our method is competitive with the state-of-the-art domain adaptation algorithms.

Construction and application of a protein and genetic interaction network (yeast interactome).

Science.gov (United States)

Stuart, Gregory R; Copeland, William C; Strand, Micheline K

2009-04-01

Cytoscape is a bioinformatic data analysis and visualization platform that is well-suited to the analysis of gene expression data. To facilitate the analysis of yeast microarray data using Cytoscape, we constructed an interaction network (interactome) using the curated interaction data available from the Saccharomyces Genome Database (www.yeastgenome.org) and the database of yeast transcription factors at YEASTRACT (www.yeastract.com). These data were formatted and imported into Cytoscape using semi-automated methods, including Linux-based scripts, that simplified the process while minimizing the introduction of processing errors. The methods described for the construction of this yeast interactome are generally applicable to the construction of any interactome. Using Cytoscape, we illustrate the use of this interactome through the analysis of expression data from a recent yeast diauxic shift experiment. We also report and briefly describe the complex associations among transcription factors that result in the regulation of thousands of genes through coordinated changes in expression of dozens of transcription factors. These cells are thus able to sensitively regulate cellular metabolism in response to changes in genetic or environmental conditions through relatively small changes in the expression of large numbers of genes, affecting the entire yeast metabolome.

The role of domain analysis in prediction instrument development

NARCIS (Netherlands)

van der Spoel, Sjoerd; Amrit, Chintan Amrit; van Hillegersberg, Jos

2016-01-01

In order to develop prediction instruments that have sufficient predictive power, it is essential to understand the specific domain the prediction instrument is developed for. This domain analysis is especially important for domains where human behavior, politics, or other soft factors play a role.

A "candidate-interactome" aggregate analysis of genome-wide association data in multiple sclerosis

DEFF Research Database (Denmark)

Mechelli, Rosella; Umeton, Renato; Policano, Claudia

2013-01-01

of genes whose products are known to physically interact with environmental factors that may be relevant for disease pathogenesis) analysis of genome-wide association data in multiple sclerosis. We looked for statistical enrichment of associations among interactomes that, at the current state of knowledge......, may be representative of gene-environment interactions of potential, uncertain or unlikely relevance for multiple sclerosis pathogenesis: Epstein-Barr virus, human immunodeficiency virus, hepatitis B virus, hepatitis C virus, cytomegalovirus, HHV8-Kaposi sarcoma, H1N1-influenza, JC virus, human innate...... immunity interactome for type I interferon, autoimmune regulator, vitamin D receptor, aryl hydrocarbon receptor and a panel of proteins targeted by 70 innate immune-modulating viral open reading frames from 30 viral species. Interactomes were either obtained from the literature or were manually curated...

Improved microarray-based decision support with graph encoded interactome data.

Directory of Open Access Journals (Sweden)

Anneleen Daemen

Full Text Available In the past, microarray studies have been criticized due to noise and the limited overlap between gene signatures. Prior biological knowledge should therefore be incorporated as side information in models based on gene expression data to improve the accuracy of diagnosis and prognosis in cancer. As prior knowledge, we investigated interaction and pathway information from the human interactome on different aspects of biological systems. By exploiting the properties of kernel methods, relations between genes with similar functions but active in alternative pathways could be incorporated in a support vector machine classifier based on spectral graph theory. Using 10 microarray data sets, we first reduced the number of data sources relevant for multiple cancer types and outcomes. Three sources on metabolic pathway information (KEGG, protein-protein interactions (OPHID and miRNA-gene targeting (microRNA.org outperformed the other sources with regard to the considered class of models. Both fixed and adaptive approaches were subsequently considered to combine the three corresponding classifiers. Averaging the predictions of these classifiers performed best and was significantly better than the model based on microarray data only. These results were confirmed on 6 validation microarray sets, with a significantly improved performance in 4 of them. Integrating interactome data thus improves classification of cancer outcome for the investigated microarray technologies and cancer types. Moreover, this strategy can be incorporated in any kernel method or non-linear version of a non-kernel method.

A highly efficient approach to protein interactome mapping based on collaborative filtering framework.

Science.gov (United States)

Luo, Xin; You, Zhuhong; Zhou, Mengchu; Li, Shuai; Leung, Hareton; Xia, Yunni; Zhu, Qingsheng

2015-01-09

The comprehensive mapping of protein-protein interactions (PPIs) is highly desired for one to gain deep insights into both fundamental cell biology processes and the pathology of diseases. Finely-set small-scale experiments are not only very expensive but also inefficient to identify numerous interactomes despite their high accuracy. High-throughput screening techniques enable efficient identification of PPIs; yet the desire to further extract useful knowledge from these data leads to the problem of binary interactome mapping. Network topology-based approaches prove to be highly efficient in addressing this problem; however, their performance deteriorates significantly on sparse putative PPI networks. Motivated by the success of collaborative filtering (CF)-based approaches to the problem of personalized-recommendation on large, sparse rating matrices, this work aims at implementing a highly efficient CF-based approach to binary interactome mapping. To achieve this, we first propose a CF framework for it. Under this framework, we model the given data into an interactome weight matrix, where the feature-vectors of involved proteins are extracted. With them, we design the rescaled cosine coefficient to model the inter-neighborhood similarity among involved proteins, for taking the mapping process. Experimental results on three large, sparse datasets demonstrate that the proposed approach outperforms several sophisticated topology-based approaches significantly.

Interactome of the hepatitis C virus: Literature mining with ANDSystem.

Science.gov (United States)

Saik, Olga V; Ivanisenko, Timofey V; Demenkov, Pavel S; Ivanisenko, Vladimir A

2016-06-15

A study of the molecular genetics mechanisms of host-pathogen interactions is of paramount importance in developing drugs against viral diseases. Currently, the literature contains a huge amount of information that describes interactions between HCV and human proteins. In addition, there are many factual databases that contain experimentally verified data on HCV-host interactions. The sources of such data are the original data along with the data manually extracted from the literature. However, the manual analysis of scientific publications is time consuming and, because of this, databases created with such an approach often do not have complete information. One of the most promising methods to provide actualisation and completeness of information is text mining. Here, with the use of a previously developed method by the authors using ANDSystem, an automated extraction of information on the interactions between HCV and human proteins was conducted. As a data source for the text mining approach, PubMed abstracts and full text articles were used. Additionally, external factual databases were analyzed. On the basis of this analysis, a special version of ANDSystem, extended with the HCV interactome, was created. The HCV interactome contains information about the interactions between 969 human and 11 HCV proteins. Among the 969 proteins, 153 'new' proteins were found not previously referred to in any external databases of protein-protein interactions for HCV-host interactions. Thus, the extended ANDSystem possesses a more comprehensive detailing of HCV-host interactions versus other existing databases. It was interesting that HCV proteins more preferably interact with human proteins that were already involved in a large number of protein-protein interactions as well as those associated with many diseases. Among human proteins of the HCV interactome, there were a large number of proteins regulated by microRNAs. It turned out that the results obtained for protein

In vitro nuclear interactome of the HIV-1 Tat protein.

LENUS (Irish Health Repository)

Gautier, Virginie W

2009-01-01

BACKGROUND: One facet of the complexity underlying the biology of HIV-1 resides not only in its limited number of viral proteins, but in the extensive repertoire of cellular proteins they interact with and their higher-order assembly. HIV-1 encodes the regulatory protein Tat (86-101aa), which is essential for HIV-1 replication and primarily orchestrates HIV-1 provirus transcriptional regulation. Previous studies have demonstrated that Tat function is highly dependent on specific interactions with a range of cellular proteins. However they can only partially account for the intricate molecular mechanisms underlying the dynamics of proviral gene expression. To obtain a comprehensive nuclear interaction map of Tat in T-cells, we have designed a proteomic strategy based on affinity chromatography coupled with mass spectrometry. RESULTS: Our approach resulted in the identification of a total of 183 candidates as Tat nuclear partners, 90% of which have not been previously characterised. Subsequently we applied in silico analysis, to validate and characterise our dataset which revealed that the Tat nuclear interactome exhibits unique signature(s). First, motif composition analysis highlighted that our dataset is enriched for domains mediating protein, RNA and DNA interactions, and helicase and ATPase activities. Secondly, functional classification and network reconstruction clearly depicted Tat as a polyvalent protein adaptor and positioned Tat at the nexus of a densely interconnected interaction network involved in a range of biological processes which included gene expression regulation, RNA biogenesis, chromatin structure, chromosome organisation, DNA replication and nuclear architecture. CONCLUSION: We have completed the in vitro Tat nuclear interactome and have highlighted its modular network properties and particularly those involved in the coordination of gene expression by Tat. Ultimately, the highly specialised set of molecular interactions identified will

Evidence That a Psychopathology Interactome Has Diagnostic Value, Predicting Clinical Needs: An Experience Sampling Study

Science.gov (United States)

van Os, Jim; Lataster, Tineke; Delespaul, Philippe; Wichers, Marieke; Myin-Germeys, Inez

2014-01-01

Background For the purpose of diagnosis, psychopathology can be represented as categories of mental disorder, symptom dimensions or symptom networks. Also, psychopathology can be assessed at different levels of temporal resolution (monthly episodes, daily fluctuating symptoms, momentary fluctuating mental states). We tested the diagnostic value, in terms of prediction of treatment needs, of the combination of symptom networks and momentary assessment level. Method Fifty-seven patients with a psychotic disorder participated in an ESM study, capturing psychotic experiences, emotions and circumstances at 10 semi-random moments in the flow of daily life over a period of 6 days. Symptoms were assessed by interview with the Positive and Negative Syndrome Scale (PANSS); treatment needs were assessed using the Camberwell Assessment of Need (CAN). Results Psychotic symptoms assessed with the PANSS (Clinical Psychotic Symptoms) were strongly associated with psychotic experiences assessed with ESM (Momentary Psychotic Experiences). However, the degree to which Momentary Psychotic Experiences manifested as Clinical Psychotic Symptoms was determined by level of momentary negative affect (higher levels increasing probability of Momentary Psychotic Experiences manifesting as Clinical Psychotic Symptoms), momentary positive affect (higher levels decreasing probability of Clinical Psychotic Symptoms), greater persistence of Momentary Psychotic Experiences (persistence predicting increased probability of Clinical Psychotic Symptoms) and momentary environmental stress associated with events and activities (higher levels increasing probability of Clinical Psychotic Symptoms). Similarly, the degree to which momentary visual or auditory hallucinations manifested as Clinical Psychotic Symptoms was strongly contingent on the level of accompanying momentary paranoid delusional ideation. Momentary Psychotic Experiences were associated with CAN unmet treatment needs, over and above PANSS

A domain-based approach to predict protein-protein interactions

Directory of Open Access Journals (Sweden)

Resat Haluk

2007-06-01

Full Text Available Abstract Background Knowing which proteins exist in a certain organism or cell type and how these proteins interact with each other are necessary for the understanding of biological processes at the whole cell level. The determination of the protein-protein interaction (PPI networks has been the subject of extensive research. Despite the development of reasonably successful methods, serious technical difficulties still exist. In this paper we present DomainGA, a quantitative computational approach that uses the information about the domain-domain interactions to predict the interactions between proteins. Results DomainGA is a multi-parameter optimization method in which the available PPI information is used to derive a quantitative scoring scheme for the domain-domain pairs. Obtained domain interaction scores are then used to predict whether a pair of proteins interacts. Using the yeast PPI data and a series of tests, we show the robustness and insensitivity of the DomainGA method to the selection of the parameter sets, score ranges, and detection rules. Our DomainGA method achieves very high explanation ratios for the positive and negative PPIs in yeast. Based on our cross-verification tests on human PPIs, comparison of the optimized scores with the structurally observed domain interactions obtained from the iPFAM database, and sensitivity and specificity analysis; we conclude that our DomainGA method shows great promise to be applicable across multiple organisms. Conclusion We envision the DomainGA as a first step of a multiple tier approach to constructing organism specific PPIs. As it is based on fundamental structural information, the DomainGA approach can be used to create potential PPIs and the accuracy of the constructed interaction template can be further improved using complementary methods. Explanation ratios obtained in the reported test case studies clearly show that the false prediction rates of the template networks constructed

Sequence- and interactome-based prediction of viral protein hotspots targeting host proteins: a case study for HIV Nef.

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Mahdi Sarmady

Full Text Available Virus proteins alter protein pathways of the host toward the synthesis of viral particles by breaking and making edges via binding to host proteins. In this study, we developed a computational approach to predict viral sequence hotspots for binding to host proteins based on sequences of viral and host proteins and literature-curated virus-host protein interactome data. We use a motif discovery algorithm repeatedly on collections of sequences of viral proteins and immediate binding partners of their host targets and choose only those motifs that are conserved on viral sequences and highly statistically enriched among binding partners of virus protein targeted host proteins. Our results match experimental data on binding sites of Nef to host proteins such as MAPK1, VAV1, LCK, HCK, HLA-A, CD4, FYN, and GNB2L1 with high statistical significance but is a poor predictor of Nef binding sites on highly flexible, hoop-like regions. Predicted hotspots recapture CD8 cell epitopes of HIV Nef highlighting their importance in modulating virus-host interactions. Host proteins potentially targeted or outcompeted by Nef appear crowding the T cell receptor, natural killer cell mediated cytotoxicity, and neurotrophin signaling pathways. Scanning of HIV Nef motifs on multiple alignments of hepatitis C protein NS5A produces results consistent with literature, indicating the potential value of the hotspot discovery in advancing our understanding of virus-host crosstalk.

Next Generation Protein Interactomes for Plant Systems Biology and Biomass Feedstock Research

Energy Technology Data Exchange (ETDEWEB)

Ecker, Joseph Robert [The Salk Inst. for Biological Studies, La Jolla, CA (United States). Genome Analysis and Plant Biology Lab.; Trigg, Shelly [The Salk Inst. for Biological Studies, La Jolla, CA (United States). Genome Analysis and Plant Biology Lab.; Univ. of California, San Diego, CA (United States). Biological Sciences Dept.; Garza, Renee [The Salk Inst. for Biological Studies, La Jolla, CA (United States). Genome Analysis and Plant Biology Lab.; Song, Haili [The Salk Inst. for Biological Studies, La Jolla, CA (United States). Genome Analysis and Plant Biology Lab.; MacWilliams, Andrew [The Salk Inst. for Biological Studies, La Jolla, CA (United States). Genome Analysis and Plant Biology Lab.; Nery, Joseph [The Salk Inst. for Biological Studies, La Jolla, CA (United States). Genome Analysis and Plant Biology Lab.; Reina, Joaquin [The Salk Inst. for Biological Studies, La Jolla, CA (United States). Genome Analysis and Plant Biology Lab.; Bartlett, Anna [The Salk Inst. for Biological Studies, La Jolla, CA (United States). Genome Analysis and Plant Biology Lab.; Castanon, Rosa [The Salk Inst. for Biological Studies, La Jolla, CA (United States). Genome Analysis and Plant Biology Lab.; Goubil, Adeline [The Salk Inst. for Biological Studies, La Jolla, CA (United States). Genome Analysis and Plant Biology Lab.; Feeney, Joseph [The Salk Inst. for Biological Studies, La Jolla, CA (United States). Genome Analysis and Plant Biology Lab.; O' Malley, Ronan [The Salk Inst. for Biological Studies, La Jolla, CA (United States). Genome Analysis and Plant Biology Lab.; Huang, Shao-shan Carol [The Salk Inst. for Biological Studies, La Jolla, CA (United States). Genome Analysis and Plant Biology Lab.; Zhang, Zhuzhu [The Salk Inst. for Biological Studies, La Jolla, CA (United States). Genome Analysis and Plant Biology Lab.; Galli, Mary [The Salk Inst. for Biological Studies, La Jolla, CA (United States). Genome Analysis and Plant Biology Lab.

2016-11-30

Biofuel crop cultivation is a necessary step in heading towards a sustainable future, making their genomic studies a priority. While technology platforms that currently exist for studying non-model crop species, like switch-grass or sorghum, have yielded large quantities of genomic and expression data, still a large gap exists between molecular mechanism and phenotype. The aspect of molecular activity at the level of protein-protein interactions has recently begun to bridge this gap, providing a more global perspective. Interactome analysis has defined more specific functional roles of proteins based on their interaction partners, neighborhoods, and other network features, making it possible to distinguish unique modules of immune response to different plant pathogens(Jiang, Dong, and Zhang 2016). As we work towards cultivating heartier biofuel crops, interactome data will lead to uncovering crop-specific defense and development networks. However, the collection of protein interaction data has been limited to expensive, time-consuming, hard-to-scale assays that mostly require cloned ORF collections. For these reasons, we have successfully developed a highly scalable, economical, and sensitive yeast two-hybrid assay, ProCREate, that can be universally applied to generate proteome-wide primary interactome data. ProCREate enables en masse pooling and massively paralleled sequencing for the identification of interacting proteins by exploiting Cre-lox recombination. ProCREate can be used to screen ORF/cDNA libraries from feedstock plant tissues. The interactome data generated will yield deeper insight into many molecular processes and pathways that can be used to guide improvement of feedstock productivity and sustainability.

Protein function prediction involved on radio-resistant bacteria

International Nuclear Information System (INIS)

Mezhoud, Karim; Mankai, Houda; Sghaier, Haitham; Barkallah, Insaf

2009-01-01

Previously, we identified 58 proteins under positive selection in ionizing-radiation-resistant bacteria (IRRB) but absent in all ionizing-radiation-sensitive bacteria (IRSB). These are good reasons to believe these 58 proteins with their interactions with other proteins (interactomes) are a part of the answer to the question as to how IRRB resist to radiation, because our knowledge of interactomes of positively selected orphan proteins in IRRB might allow us to define cellular pathways important to ionizing-radiation resistance. Using the Database of Interacting Proteins and the PSIbase, we have predicted interactions of orthologs of the 58 proteins under positive selection in IRRB but absent in all IRSB. We used integrate experimental data sets with molecular interaction networks and protein structure prediction from databases. Among these, 18 proteins with their interactomes were identified in Deinococcus radiodurans R1. DNA checkpoint and repair, kinases pathways, energetic and nucleotide metabolisms were the important biological process that found. We predicted the interactomes of 58 proteins under positive selection in IRRB. It is hoped our data will provide new clues as to the cellular pathways that are important for ionizing-radiation resistance. We have identified news proteins involved on DNA management which were not previously mentioned. It is an important input in addition to protein that studied. It does still work to deepen our study on these new proteins

Crowd sourcing a new paradigm for interactome driven drug target identification in Mycobacterium tuberculosis.

Directory of Open Access Journals (Sweden)

Rohit Vashisht

Full Text Available A decade since the availability of Mycobacterium tuberculosis (Mtb genome sequence, no promising drug has seen the light of the day. This not only indicates the challenges in discovering new drugs but also suggests a gap in our current understanding of Mtb biology. We attempt to bridge this gap by carrying out extensive re-annotation and constructing a systems level protein interaction map of Mtb with an objective of finding novel drug target candidates. Towards this, we synergized crowd sourcing and social networking methods through an initiative 'Connect to Decode' (C2D to generate the first and largest manually curated interactome of Mtb termed 'interactome pathway' (IPW, encompassing a total of 1434 proteins connected through 2575 functional relationships. Interactions leading to gene regulation, signal transduction, metabolism, structural complex formation have been catalogued. In the process, we have functionally annotated 87% of the Mtb genome in context of gene products. We further combine IPW with STRING based network to report central proteins, which may be assessed as potential drug targets for development of drugs with least possible side effects. The fact that five of the 17 predicted drug targets are already experimentally validated either genetically or biochemically lends credence to our unique approach.

Crowd Sourcing a New Paradigm for Interactome Driven Drug Target Identification in Mycobacterium tuberculosis

Science.gov (United States)

Rohira, Harsha; Bhat, Ashwini G.; Passi, Anurag; Mukherjee, Keya; Choudhary, Kumari Sonal; Kumar, Vikas; Arora, Anshula; Munusamy, Prabhakaran; Subramanian, Ahalyaa; Venkatachalam, Aparna; S, Gayathri; Raj, Sweety; Chitra, Vijaya; Verma, Kaveri; Zaheer, Salman; J, Balaganesh; Gurusamy, Malarvizhi; Razeeth, Mohammed; Raja, Ilamathi; Thandapani, Madhumohan; Mevada, Vishal; Soni, Raviraj; Rana, Shruti; Ramanna, Girish Muthagadhalli; Raghavan, Swetha; Subramanya, Sunil N.; Kholia, Trupti; Patel, Rajesh; Bhavnani, Varsha; Chiranjeevi, Lakavath; Sengupta, Soumi; Singh, Pankaj Kumar; Atray, Naresh; Gandhi, Swati; Avasthi, Tiruvayipati Suma; Nisthar, Shefin; Anurag, Meenakshi; Sharma, Pratibha; Hasija, Yasha; Dash, Debasis; Sharma, Arun; Scaria, Vinod; Thomas, Zakir; Chandra, Nagasuma; Brahmachari, Samir K.; Bhardwaj, Anshu

2012-01-01

A decade since the availability of Mycobacterium tuberculosis (Mtb) genome sequence, no promising drug has seen the light of the day. This not only indicates the challenges in discovering new drugs but also suggests a gap in our current understanding of Mtb biology. We attempt to bridge this gap by carrying out extensive re-annotation and constructing a systems level protein interaction map of Mtb with an objective of finding novel drug target candidates. Towards this, we synergized crowd sourcing and social networking methods through an initiative ‘Connect to Decode’ (C2D) to generate the first and largest manually curated interactome of Mtb termed ‘interactome pathway’ (IPW), encompassing a total of 1434 proteins connected through 2575 functional relationships. Interactions leading to gene regulation, signal transduction, metabolism, structural complex formation have been catalogued. In the process, we have functionally annotated 87% of the Mtb genome in context of gene products. We further combine IPW with STRING based network to report central proteins, which may be assessed as potential drug targets for development of drugs with least possible side effects. The fact that five of the 17 predicted drug targets are already experimentally validated either genetically or biochemically lends credence to our unique approach. PMID:22808064

Functional interactome of Aquaporin 1 sub-family reveals new physiological functions in Arabidopsis Thaliana

Directory of Open Access Journals (Sweden)

Mohamed Ragab Abdel Gawwad

2013-09-01

Full Text Available Aquaporins are channel proteins found in plasma membranes and intercellular membranes of different cellular compartments, facilitate the water flux, solutes and gases across the cellular plasma membranes. The present study highlights the sub-family plasma membrane intrinsic protein (PIP predicting the 3-D structure and analyzing the functional interactome of it homologs. PIP1 homologs integrate with many proteins with different plant physiological roles in Arabidopsis thaliana including; PIP1A and PIP1B: facilitate the transport of water, diffusion of amino acids and/or peptides from the vacuolar compartment to the cytoplasm, play a role in the control of cell turgor and cell expansion and involved in root water uptake respectively. In addition we found that PIP1B plays a defensive role against Pseudomonas syringae infection through the interaction with the plasma membrane Rps2 protein. Another substantial function of PIP1C via the interaction with PIP2E is the response to nematode infection. Generally, PIP1 sub-family interactome controlling many physiological processes in plant cell like; osmoregulation in plants under high osmotic stress such as under a high salt, response to nematode, facilitate the transport of water across cell membrane and regulation of floral initiation in Arabidopsis thaliana.

Interactome of Obesity: Obesidome : Genetic Obesity, Stress Induced Obesity, Pathogenic Obesity Interaction.

Science.gov (United States)

Geronikolou, Styliani A; Pavlopoulou, Athanasia; Cokkinos, Dennis; Chrousos, George

2017-01-01

Obesity is a chronic disease of increasing prevalence reaching epidemic proportions. Genetic defects as well as epigenetic effects contribute to the obesity phenotype. Investigating gene (e.g. MC4R defects)-environment (behavior, infectious agents, stress) interactions is a relative new field of great research interest. In this study, we have made an effort to create an interactome (henceforth referred to as "obesidome"), where extrinsic stressors response, intrinsic predisposition, immunity response to inflammation and autonomous nervous system implications are integrated. These pathways are presented in one interactome network for the first time. In our study, obesity-related genes/gene products were found to form a complex interactions network.

Identification of human disease genes from interactome network using graphlet interaction.

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Xiao-Dong Wang

Full Text Available Identifying genes related to human diseases, such as cancer and cardiovascular disease, etc., is an important task in biomedical research because of its applications in disease diagnosis and treatment. Interactome networks, especially protein-protein interaction networks, had been used to disease genes identification based on the hypothesis that strong candidate genes tend to closely relate to each other in some kinds of measure on the network. We proposed a new measure to analyze the relationship between network nodes which was called graphlet interaction. The graphlet interaction contained 28 different isomers. The results showed that the numbers of the graphlet interaction isomers between disease genes in interactome networks were significantly larger than random picked genes, while graphlet signatures were not. Then, we designed a new type of score, based on the network properties, to identify disease genes using graphlet interaction. The genes with higher scores were more likely to be disease genes, and all candidate genes were ranked according to their scores. Then the approach was evaluated by leave-one-out cross-validation. The precision of the current approach achieved 90% at about 10% recall, which was apparently higher than the previous three predominant algorithms, random walk, Endeavour and neighborhood based method. Finally, the approach was applied to predict new disease genes related to 4 common diseases, most of which were identified by other independent experimental researches. In conclusion, we demonstrate that the graphlet interaction is an effective tool to analyze the network properties of disease genes, and the scores calculated by graphlet interaction is more precise in identifying disease genes.

Identification of Human Disease Genes from Interactome Network Using Graphlet Interaction

Science.gov (United States)

Yang, Lun; Wei, Dong-Qing; Qi, Ying-Xin; Jiang, Zong-Lai

2014-01-01

Identifying genes related to human diseases, such as cancer and cardiovascular disease, etc., is an important task in biomedical research because of its applications in disease diagnosis and treatment. Interactome networks, especially protein-protein interaction networks, had been used to disease genes identification based on the hypothesis that strong candidate genes tend to closely relate to each other in some kinds of measure on the network. We proposed a new measure to analyze the relationship between network nodes which was called graphlet interaction. The graphlet interaction contained 28 different isomers. The results showed that the numbers of the graphlet interaction isomers between disease genes in interactome networks were significantly larger than random picked genes, while graphlet signatures were not. Then, we designed a new type of score, based on the network properties, to identify disease genes using graphlet interaction. The genes with higher scores were more likely to be disease genes, and all candidate genes were ranked according to their scores. Then the approach was evaluated by leave-one-out cross-validation. The precision of the current approach achieved 90% at about 10% recall, which was apparently higher than the previous three predominant algorithms, random walk, Endeavour and neighborhood based method. Finally, the approach was applied to predict new disease genes related to 4 common diseases, most of which were identified by other independent experimental researches. In conclusion, we demonstrate that the graphlet interaction is an effective tool to analyze the network properties of disease genes, and the scores calculated by graphlet interaction is more precise in identifying disease genes. PMID:24465923

Generalized predictive control in the delta-domain

DEFF Research Database (Denmark)

Lauritsen, Morten Bach; Jensen, Morten Rostgaard; Poulsen, Niels Kjølstad

1995-01-01

This paper describes new approaches to generalized predictive control formulated in the delta (δ) domain. A new δ-domain version of the continuous-time emulator-based predictor is presented. It produces the optimal estimate in the deterministic case whenever the predictor order is chosen greater...... than or equal to the number of future predicted samples, however a “good” estimate is usually obtained in a much longer range of samples. This is particularly advantageous at fast sampling rates where a “conventional” predictor is bound to become very computationally demanding. Two controllers...

Proteomic-coupled-network analysis of T877A-androgen receptor interactomes can predict clinical prostate cancer outcomes between White (non-Hispanic and African-American groups.

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Naif Zaman

Full Text Available The androgen receptor (AR remains an important contributor to the neoplastic evolution of prostate cancer (CaP. CaP progression is linked to several somatic AR mutational changes that endow upon the AR dramatic gain-of-function properties. One of the most common somatic mutations identified is Thr877-to-Ala (T877A, located in the ligand-binding domain, that results in a receptor capable of promiscuous binding and activation by a variety of steroid hormones and ligands including estrogens, progestins, glucocorticoids, and several anti-androgens. In an attempt to further define somatic mutated AR gain-of-function properties, as a consequence of its promiscuous ligand binding, we undertook a proteomic/network analysis approach to characterize the protein interactome of the mutant T877A-AR in LNCaP cells under eight different ligand-specific treatments (dihydrotestosterone, mibolerone, R1881, testosterone, estradiol, progesterone, dexamethasone, and cyproterone acetate. In extending the analysis of our multi-ligand complexes of the mutant T877A-AR we observed significant enrichment of specific complexes between normal and primary prostatic tumors, which were furthermore correlated with known clinical outcomes. Further analysis of certain mutant T877A-AR complexes showed specific population preferences distinguishing primary prostatic disease between white (non-Hispanic vs. African-American males. Moreover, these cancer-related AR-protein complexes demonstrated predictive survival outcomes specific to CaP, and not for breast, lung, lymphoma or medulloblastoma cancers. Our study, by coupling data generated by our proteomics to network analysis of clinical samples, has helped to define real and novel biological pathways in complicated gain-of-function AR complex systems.

Expression of DISC1-interactome members correlates with cognitive phenotypes related to schizophrenia.

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Rampino, Antonio; Walker, Rosie May; Torrance, Helen Scott; Anderson, Susan Maguire; Fazio, Leonardo; Di Giorgio, Annabella; Taurisano, Paolo; Gelao, Barbara; Romano, Raffaella; Masellis, Rita; Ursini, Gianluca; Caforio, Grazia; Blasi, Giuseppe; Millar, J Kirsty; Porteous, David John; Thomson, Pippa Ann; Bertolino, Alessandro; Evans, Kathryn Louise

2014-01-01

Cognitive dysfunction is central to the schizophrenia phenotype. Genetic and functional studies have implicated Disrupted-in-Schizophrenia 1 (DISC1), a leading candidate gene for schizophrenia and related psychiatric conditions, in cognitive function. Altered expression of DISC1 and DISC1-interactors has been identified in schizophrenia. Dysregulated expression of DISC1-interactome genes might, therefore, contribute to schizophrenia susceptibility via disruption of molecular systems required for normal cognitive function. Here, the blood RNA expression levels of DISC1 and DISC1-interacting proteins were measured in 63 control subjects. Cognitive function was assessed using neuropsychiatric tests and functional magnetic resonance imaging was used to assess the activity of prefrontal cortical regions during the N-back working memory task, which is abnormal in schizophrenia. Pairwise correlations between gene expression levels and the relationship between gene expression levels and cognitive function and N-back-elicited brain activity were assessed. Finally, the expression levels of DISC1, AKAP9, FEZ1, NDEL1 and PCM1 were compared between 63 controls and 69 schizophrenic subjects. We found that DISC1-interactome genes showed correlated expression in the blood of healthy individuals. The expression levels of several interactome members were correlated with cognitive performance and N-back-elicited activity in the prefrontal cortex. In addition, DISC1 and NDEL1 showed decreased expression in schizophrenic subjects compared to healthy controls. Our findings highlight the importance of the coordinated expression of DISC1-interactome genes for normal cognitive function and suggest that dysregulated DISC1 and NDEL1 expression might, in part, contribute to susceptibility for schizophrenia via disruption of prefrontal cortex-dependent cognitive functions.

Expression of DISC1-interactome members correlates with cognitive phenotypes related to schizophrenia.

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Antonio Rampino

Full Text Available Cognitive dysfunction is central to the schizophrenia phenotype. Genetic and functional studies have implicated Disrupted-in-Schizophrenia 1 (DISC1, a leading candidate gene for schizophrenia and related psychiatric conditions, in cognitive function. Altered expression of DISC1 and DISC1-interactors has been identified in schizophrenia. Dysregulated expression of DISC1-interactome genes might, therefore, contribute to schizophrenia susceptibility via disruption of molecular systems required for normal cognitive function. Here, the blood RNA expression levels of DISC1 and DISC1-interacting proteins were measured in 63 control subjects. Cognitive function was assessed using neuropsychiatric tests and functional magnetic resonance imaging was used to assess the activity of prefrontal cortical regions during the N-back working memory task, which is abnormal in schizophrenia. Pairwise correlations between gene expression levels and the relationship between gene expression levels and cognitive function and N-back-elicited brain activity were assessed. Finally, the expression levels of DISC1, AKAP9, FEZ1, NDEL1 and PCM1 were compared between 63 controls and 69 schizophrenic subjects. We found that DISC1-interactome genes showed correlated expression in the blood of healthy individuals. The expression levels of several interactome members were correlated with cognitive performance and N-back-elicited activity in the prefrontal cortex. In addition, DISC1 and NDEL1 showed decreased expression in schizophrenic subjects compared to healthy controls. Our findings highlight the importance of the coordinated expression of DISC1-interactome genes for normal cognitive function and suggest that dysregulated DISC1 and NDEL1 expression might, in part, contribute to susceptibility for schizophrenia via disruption of prefrontal cortex-dependent cognitive functions.

DomPep--a general method for predicting modular domain-mediated protein-protein interactions.

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Lei Li

Full Text Available Protein-protein interactions (PPIs are frequently mediated by the binding of a modular domain in one protein to a short, linear peptide motif in its partner. The advent of proteomic methods such as peptide and protein arrays has led to the accumulation of a wealth of interaction data for modular interaction domains. Although several computational programs have been developed to predict modular domain-mediated PPI events, they are often restricted to a given domain type. We describe DomPep, a method that can potentially be used to predict PPIs mediated by any modular domains. DomPep combines proteomic data with sequence information to achieve high accuracy and high coverage in PPI prediction. Proteomic binding data were employed to determine a simple yet novel parameter Ligand-Binding Similarity which, in turn, is used to calibrate Domain Sequence Identity and Position-Weighted-Matrix distance, two parameters that are used in constructing prediction models. Moreover, DomPep can be used to predict PPIs for both domains with experimental binding data and those without. Using the PDZ and SH2 domain families as test cases, we show that DomPep can predict PPIs with accuracies superior to existing methods. To evaluate DomPep as a discovery tool, we deployed DomPep to identify interactions mediated by three human PDZ domains. Subsequent in-solution binding assays validated the high accuracy of DomPep in predicting authentic PPIs at the proteome scale. Because DomPep makes use of only interaction data and the primary sequence of a domain, it can be readily expanded to include other types of modular domains.

Intranuclear interactomic inhibition of NF-κB suppresses LPS-induced severe sepsis

International Nuclear Information System (INIS)

Park, Sung-Dong; Cheon, So Yeong; Park, Tae-Yoon; Shin, Bo-Young; Oh, Hyunju; Ghosh, Sankar; Koo, Bon-Nyeo; Lee, Sang-Kyou

2015-01-01

Suppression of nuclear factor-κB (NF-κB) activation, which is best known as a major regulator of innate and adaptive immune responses, is a potent strategy for the treatment of endotoxic sepsis. To inhibit NF-κB functions, we designed the intra-nuclear transducible form of transcription modulation domain (TMD) of RelA (p65), called nt-p65-TMD, which can be delivered effectively into the nucleus without influencing the cell viability, and work as interactomic inhibitors via disruption of the endogenous p65-mediated transcription complex. nt-p65-TMD effectively inhibited the secretion of pro-inflammatory cytokines, including TNF-α, IL-1β, or IL-6 from BV2 microglia cells stimulated by lipopolysaccharide (LPS). nt-p65-TMD did not inhibit tyrosine phosphorylation of signaling mediators such as ZAP-70, p38, JNK, or ERK involved in T cell activation, but was capable of suppressing the transcriptional activity of NF-κB without the functional effect on that of NFAT upon T-cell receptor (TCR) stimulation. The transduced nt-p65-TMD in T cell did not affect the expression of CD69, however significantly inhibited the secretion of T cell-specific cytokines such as IL-2, IFN-γ, IL-4, IL-17A, or IL-10. Systemic administration of nt-p65-TMD showed a significant therapeutic effect on LPS-induced sepsis model by inhibiting pro-inflammatory cytokines secretion. Therefore, nt-p65-TMD can be a novel therapeutics for the treatment of various inflammatory diseases, including sepsis, where a transcription factor has a key role in pathogenesis, and further allows us to discover new functions of p65 under normal physiological condition without genetic alteration. - Highlights: • The nt-p65-TMD is intra-nuclear interactomic inhibitor of endogenous p65. • The nt-p65-TMD effectively inhibited the secretion of pro-inflammatory cytokines. • The excellent therapeutic potential of nt-p65-TMD was confirmed in sepsis model

Intranuclear interactomic inhibition of NF-κB suppresses LPS-induced severe sepsis

Energy Technology Data Exchange (ETDEWEB)

Park, Sung-Dong [Translational Research Center for Protein Function Control, College of Life Science and Biotechnology, Yonsei University, Seoul 120-749 (Korea, Republic of); Department of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seoul 120-749 (Korea, Republic of); Cheon, So Yeong [Department of Anesthesiology and Pain Medicine, Anesthesia and Pain Research Institute, Yonsei University College of Medicine, Seoul 120-752 (Korea, Republic of); Park, Tae-Yoon; Shin, Bo-Young [Translational Research Center for Protein Function Control, College of Life Science and Biotechnology, Yonsei University, Seoul 120-749 (Korea, Republic of); Department of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seoul 120-749 (Korea, Republic of); Oh, Hyunju; Ghosh, Sankar [Department of Microbiology and Immunology, College of Physicians and Surgeons, Columbia University, New York, NY 10032 (United States); Koo, Bon-Nyeo, E-mail: koobn@yuhs.ac [Department of Anesthesiology and Pain Medicine, Anesthesia and Pain Research Institute, Yonsei University College of Medicine, Seoul 120-752 (Korea, Republic of); Lee, Sang-Kyou, E-mail: sjrlee@yonsei.ac.kr [Translational Research Center for Protein Function Control, College of Life Science and Biotechnology, Yonsei University, Seoul 120-749 (Korea, Republic of); Department of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seoul 120-749 (Korea, Republic of)

2015-08-28

Suppression of nuclear factor-κB (NF-κB) activation, which is best known as a major regulator of innate and adaptive immune responses, is a potent strategy for the treatment of endotoxic sepsis. To inhibit NF-κB functions, we designed the intra-nuclear transducible form of transcription modulation domain (TMD) of RelA (p65), called nt-p65-TMD, which can be delivered effectively into the nucleus without influencing the cell viability, and work as interactomic inhibitors via disruption of the endogenous p65-mediated transcription complex. nt-p65-TMD effectively inhibited the secretion of pro-inflammatory cytokines, including TNF-α, IL-1β, or IL-6 from BV2 microglia cells stimulated by lipopolysaccharide (LPS). nt-p65-TMD did not inhibit tyrosine phosphorylation of signaling mediators such as ZAP-70, p38, JNK, or ERK involved in T cell activation, but was capable of suppressing the transcriptional activity of NF-κB without the functional effect on that of NFAT upon T-cell receptor (TCR) stimulation. The transduced nt-p65-TMD in T cell did not affect the expression of CD69, however significantly inhibited the secretion of T cell-specific cytokines such as IL-2, IFN-γ, IL-4, IL-17A, or IL-10. Systemic administration of nt-p65-TMD showed a significant therapeutic effect on LPS-induced sepsis model by inhibiting pro-inflammatory cytokines secretion. Therefore, nt-p65-TMD can be a novel therapeutics for the treatment of various inflammatory diseases, including sepsis, where a transcription factor has a key role in pathogenesis, and further allows us to discover new functions of p65 under normal physiological condition without genetic alteration. - Highlights: • The nt-p65-TMD is intra-nuclear interactomic inhibitor of endogenous p65. • The nt-p65-TMD effectively inhibited the secretion of pro-inflammatory cytokines. • The excellent therapeutic potential of nt-p65-TMD was confirmed in sepsis model.

Building and analyzing protein interactome networks by cross-species comparisons

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Blackman Barron

2010-03-01

Full Text Available Abstract Background A genomic catalogue of protein-protein interactions is a rich source of information, particularly for exploring the relationships between proteins. Numerous systems-wide and small-scale experiments have been conducted to identify interactions; however, our knowledge of all interactions for any one species is incomplete, and alternative means to expand these network maps is needed. We therefore took a comparative biology approach to predict protein-protein interactions across five species (human, mouse, fly, worm, and yeast and developed InterologFinder for research biologists to easily navigate this data. We also developed a confidence score for interactions based on available experimental evidence and conservation across species. Results The connectivity of the resultant networks was determined to have scale-free distribution, small-world properties, and increased local modularity, indicating that the added interactions do not disrupt our current understanding of protein network structures. We show examples of how these improved interactomes can be used to analyze a genome-scale dataset (RNAi screen and to assign new function to proteins. Predicted interactions within this dataset were tested by co-immunoprecipitation, resulting in a high rate of validation, suggesting the high quality of networks produced. Conclusions Protein-protein interactions were predicted in five species, based on orthology. An InteroScore, a score accounting for homology, number of orthologues with evidence of interactions, and number of unique observations of interactions, is given to each known and predicted interaction. Our website http://www.interologfinder.org provides research biologists intuitive access to this data.

Concomitant prediction of function and fold at the domain level with GO-based profiles.

Science.gov (United States)

Lopez, Daniel; Pazos, Florencio

2013-01-01

Predicting the function of newly sequenced proteins is crucial due to the pace at which these raw sequences are being obtained. Almost all resources for predicting protein function assign functional terms to whole chains, and do not distinguish which particular domain is responsible for the allocated function. This is not a limitation of the methodologies themselves but it is due to the fact that in the databases of functional annotations these methods use for transferring functional terms to new proteins, these annotations are done on a whole-chain basis. Nevertheless, domains are the basic evolutionary and often functional units of proteins. In many cases, the domains of a protein chain have distinct molecular functions, independent from each other. For that reason resources with functional annotations at the domain level, as well as methodologies for predicting function for individual domains adapted to these resources are required.We present a methodology for predicting the molecular function of individual domains, based on a previously developed database of functional annotations at the domain level. The approach, which we show outperforms a standard method based on sequence searches in assigning function, concomitantly predicts the structural fold of the domains and can give hints on the functionally important residues associated to the predicted function.

Grouping annotations on the subcellular layered interactome demonstrates enhanced autophagy activity in a recurrent experimental autoimmune uveitis T cell line.

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Xiuzhi Jia

Full Text Available Human uveitis is a type of T cell-mediated autoimmune disease that often shows relapse-remitting courses affecting multiple biological processes. As a cytoplasmic process, autophagy has been seen as an adaptive response to cell death and survival, yet the link between autophagy and T cell-mediated autoimmunity is not certain. In this study, based on the differentially expressed genes (GSE19652 between the recurrent versus monophasic T cell lines, whose adoptive transfer to susceptible animals may result in respective recurrent or monophasic uveitis, we proposed grouping annotations on a subcellular layered interactome framework to analyze the specific bioprocesses that are linked to the recurrence of T cell autoimmunity. That is, the subcellular layered interactome was established by the Cytoscape and Cerebral plugin based on differential expression, global interactome, and subcellular localization information. Then, the layered interactomes were grouping annotated by the ClueGO plugin based on Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases. The analysis showed that significant bioprocesses with autophagy were orchestrated in the cytoplasmic layered interactome and that mTOR may have a regulatory role in it. Furthermore, by setting up recurrent and monophasic uveitis in Lewis rats, we confirmed by transmission electron microscopy that, in comparison to the monophasic disease, recurrent uveitis in vivo showed significantly increased autophagy activity and extended lymphocyte infiltration to the affected retina. In summary, our framework methodology is a useful tool to disclose specific bioprocesses and molecular targets that can be attributed to a certain disease. Our results indicated that targeted inhibition of autophagy pathways may perturb the recurrence of uveitis.

Interactome analysis of transcriptional coactivator multiprotein bridging factor 1 unveils a yeast AP-1-like transcription factor involved in oxidation tolerance of mycopathogen Beauveria bassiana.

Science.gov (United States)

Chu, Xin-Ling; Dong, Wei-Xia; Ding, Jin-Li; Feng, Ming-Guang; Ying, Sheng-Hua

2018-02-01

Oxidation tolerance is an important determinant to predict the virulence and biocontrol potential of Beauveria bassiana, a well-known entomopathogenic fungus. As a transcriptional coactivator, multiprotein bridging factor 1 mediates the activity of transcription factor in diverse physiological processes, and its homolog in B. bassiana (BbMBF1) contributes to fungal oxidation tolerance. In this study, the BbMBF1-interactomes under oxidative stress and normal growth condition were deciphered by mass spectrometry integrated with the immunoprecipitation. BbMBF1p factor has a broad interaction with proteins that are involved in various cellular processes, and this interaction is dynamically regulated by oxidative stress. Importantly, a B. bassiana homolog of yeast AP-1-like transcription factor (BbAP-1) was specifically associated with the BbMBF1-interactome under oxidation and significantly contributed to fungal oxidation tolerance. In addition, qPCR analysis revealed that several antioxidant genes are jointly controlled by BbAP-1 and BbMBF1. Conclusively, it is proposed that BbMBF1p protein mediates BbAP-1p factor to transcribe the downstream antioxidant genes in B. bassiana under oxidative stress. This study demonstrates for the first time a proteomic view of the MBF1-interactome in fungi, and presents an initial framework to probe the transcriptional mechanism involved in fungal response to oxidation, which will provide a new strategy to improve the biocontrol efficacy of B. bassiana.

Waggawagga-CLI: A command-line tool for predicting stable single α-helices (SAH-domains, and the SAH-domain distribution across eukaryotes.

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Dominic Simm

Full Text Available Stable single-alpha helices (SAH-domains function as rigid connectors and constant force springs between structural domains, and can provide contact surfaces for protein-protein and protein-RNA interactions. SAH-domains mainly consist of charged amino acids and are monomeric and stable in polar solutions, characteristics which distinguish them from coiled-coil domains and intrinsically disordered regions. Although the number of reported SAH-domains is steadily increasing, genome-wide analyses of SAH-domains in eukaryotic genomes are still missing. Here, we present Waggawagga-CLI, a command-line tool for predicting and analysing SAH-domains in protein sequence datasets. Using Waggawagga-CLI we predicted SAH-domains in 24 datasets from eukaryotes across the tree of life. SAH-domains were predicted in 0.5 to 3.5% of the protein-coding content per species. SAH-domains are particularly present in longer proteins supporting their function as structural building block in multi-domain proteins. In human, SAH-domains are mainly used as alternative building blocks not being present in all transcripts of a gene. Gene ontology analysis showed that yeast proteins with SAH-domains are particular enriched in macromolecular complex subunit organization, cellular component biogenesis and RNA metabolic processes, and that they have a strong nuclear and ribonucleoprotein complex localization and function in ribosome and nucleic acid binding. Human proteins with SAH-domains have roles in all types of RNA processing and cytoskeleton organization, and are predicted to function in RNA binding, protein binding involved in cell and cell-cell adhesion, and cytoskeletal protein binding. Waggawagga-CLI allows the user to adjust the stabilizing and destabilizing contribution of amino acid interactions in i,i+3 and i,i+4 spacings, and provides extensive flexibility for user-designed analyses.

Molecular characterization and interactome analysis of Trypanosoma cruzi tryparedoxin II.

Science.gov (United States)

Arias, Diego G; Piñeyro, María Dolores; Iglesias, Alberto A; Guerrero, Sergio A; Robello, Carlos

2015-04-29

Trypanosoma cruzi, the causative agent of Chagas disease, possesses two tryparedoxins (TcTXNI and TcTXNII), belonging to the thioredoxin superfamily. TXNs are oxidoreductases which mediate electron transfer between trypanothione and peroxiredoxins. This constitutes a difference with the host cells, in which these activities are mediated by thioredoxins. These differences make TXNs an attractive target for drug development. In a previous work we characterized TcTXNI, including the redox interactome. In this work we extend the study to TcTXNII. We demonstrate that TcTXNII is a transmembrane protein anchored to the surface of the mitochondria and endoplasmic reticulum, with a cytoplasmatic orientation of the redox domain. It would be expressed during the metacyclogenesis process. In order to continue with the characterization of the redox interactome of T. cruzi, we designed an active site mutant TcTXNII lacking the resolving cysteine, and through the expression of this mutant protein and incubation with T. cruzi proteins, heterodisulfide complexes were isolated by affinity chromatography and identified by mass spectrometry. This allowed us to identify sixteen TcTXNII interacting proteins, which are involved in a wide range of cellular processes, indicating the relevance of TcTXNII, and contributing to our understanding of the redox interactome of T. cruzi. T. cruzi, the causative agent of Chagas disease, constitutes a major sanitary problem in Latin America. The number of estimated infected persons is ca. 8 million, 28 million people are at risk of infection and ~20,000 deaths occur per year in endemic regions. No vaccines are available at present, and most drugs currently in use were developed decades ago and show variable efficacy with undesirable side effects. The parasite is able to live and prolipherate inside macrophage phagosomes, where it is exposed to cytotoxic reactive oxygen and nitrogen species, derived from macrophage activation. Therefore, T. cruzi

Domain Adaptation for Pedestrian Detection Based on Prediction Consistency

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Yu Li-ping

2014-01-01

Full Text Available Pedestrian detection is an active area of research in computer vision. It remains a quite challenging problem in many applications where many factors cause a mismatch between source dataset used to train the pedestrian detector and samples in the target scene. In this paper, we propose a novel domain adaptation model for merging plentiful source domain samples with scared target domain samples to create a scene-specific pedestrian detector that performs as well as rich target domain simples are present. Our approach combines the boosting-based learning algorithm with an entropy-based transferability, which is derived from the prediction consistency with the source classifications, to selectively choose the samples showing positive transferability in source domains to the target domain. Experimental results show that our approach can improve the detection rate, especially with the insufficient labeled data in target scene.

Protein Inference from the Integration of Tandem MS Data and Interactome Networks.

Science.gov (United States)

Zhong, Jiancheng; Wang, Jianxing; Ding, Xiaojun; Zhang, Zhen; Li, Min; Wu, Fang-Xiang; Pan, Yi

2017-01-01

Since proteins are digested into a mixture of peptides in the preprocessing step of tandem mass spectrometry (MS), it is difficult to determine which specific protein a shared peptide belongs to. In recent studies, besides tandem MS data and peptide identification information, some other information is exploited to infer proteins. Different from the methods which first use only tandem MS data to infer proteins and then use network information to refine them, this study proposes a protein inference method named TMSIN, which uses interactome networks directly. As two interacting proteins should co-exist, it is reasonable to assume that if one of the interacting proteins is confidently inferred in a sample, its interacting partners should have a high probability in the same sample, too. Therefore, we can use the neighborhood information of a protein in an interactome network to adjust the probability that the shared peptide belongs to the protein. In TMSIN, a multi-weighted graph is constructed by incorporating the bipartite graph with interactome network information, where the bipartite graph is built with the peptide identification information. Based on multi-weighted graphs, TMSIN adopts an iterative workflow to infer proteins. At each iterative step, the probability that a shared peptide belongs to a specific protein is calculated by using the Bayes' law based on the neighbor protein support scores of each protein which are mapped by the shared peptides. We carried out experiments on yeast data and human data to evaluate the performance of TMSIN in terms of ROC, q-value, and accuracy. The experimental results show that AUC scores yielded by TMSIN are 0.742 and 0.874 in yeast dataset and human dataset, respectively, and TMSIN yields the maximum number of true positives when q-value less than or equal to 0.05. The overlap analysis shows that TMSIN is an effective complementary approach for protein inference.

Serum Amyloid P Component (SAP) Interactome in Human Plasma Containing Physiological Calcium Levels.

Science.gov (United States)

Poulsen, Ebbe Toftgaard; Pedersen, Kata Wolff; Marzeda, Anna Maria; Enghild, Jan J

2017-02-14

The pentraxin serum amyloid P component (SAP) is secreted by the liver and found in plasma at a concentration of approximately 30 mg/L. SAP is a 25 kDa homopentamer known to bind both protein and nonprotein ligands, all in a calcium-dependent manner. The function of SAP is unclear but likely involves the humoral innate immune system spanning the complement system, inflammation, and coagulation. Also, SAP is known to bind to the generic structure of amyloid deposits and possibly to protect them against proteolysis. In this study, we have characterized the SAP interactome in human plasma containing the physiological Ca 2+ concentration using SAP affinity pull-down and co-immunoprecipitation experiments followed by mass spectrometry analyses. The analyses resulted in the identification of 33 proteins, of which 24 were direct or indirect interaction partners not previously reported. The SAP interactome can be divided into categories that include apolipoproteins, the complement system, coagulation, and proteolytic regulation.

The conservation pattern of short linear motifs is highly correlated with the function of interacting protein domains

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Wang Yiguo

2008-10-01

Full Text Available Abstract Background Many well-represented domains recognize primary sequences usually less than 10 amino acids in length, called Short Linear Motifs (SLiMs. Accurate prediction of SLiMs has been difficult because they are short (often Results Our combined approach revealed that SLiMs are highly conserved in proteins from functional classes that are known to interact with a specific domain, but that they are not conserved in most other protein groups. We found that SLiMs recognized by SH2 domains were highly conserved in receptor kinases/phosphatases, adaptor molecules, and tyrosine kinases/phosphatases, that SLiMs recognized by SH3 domains were highly conserved in cytoskeletal and cytoskeletal-associated proteins, that SLiMs recognized by PDZ domains were highly conserved in membrane proteins such as channels and receptors, and that SLiMs recognized by S/T kinase domains were highly conserved in adaptor molecules, S/T kinases/phosphatases, and proteins involved in transcription or cell cycle control. We studied Tyr-SLiMs recognized by SH2 domains in more detail, and found that SH2-recognized Tyr-SLiMs on the cytoplasmic side of membrane proteins are more highly conserved than those on the extra-cellular side. Also, we found that SH2-recognized Tyr-SLiMs that are associated with SH3 motifs and a tyrosine kinase phosphorylation motif are more highly conserved. Conclusion The interactome of protein domains is reflected by the evolutionary conservation of SLiMs recognized by these domains. Combining scoring matrixes derived from peptide libraries and conservation analysis, we would be able to find those protein groups that are more likely to interact with specific domains.

Comprehensive RNA Polymerase II Interactomes Reveal Distinct and Varied Roles for Each Phospho-CTD Residue

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Kevin M. Harlen

2016-06-01

Full Text Available Transcription controls splicing and other gene regulatory processes, yet mechanisms remain obscure due to our fragmented knowledge of the molecular connections between the dynamically phosphorylated RNA polymerase II (Pol II C-terminal domain (CTD and regulatory factors. By systematically isolating phosphorylation states of the CTD heptapeptide repeat (Y1S2P3T4S5P6S7, we identify hundreds of protein factors that are differentially enriched, revealing unappreciated connections between the Pol II CTD and co-transcriptional processes. These data uncover a role for threonine-4 in 3′ end processing through control of the transition between cleavage and termination. Furthermore, serine-5 phosphorylation seeds spliceosomal assembly immediately downstream of 3′ splice sites through a direct interaction with spliceosomal subcomplex U1. Strikingly, threonine-4 phosphorylation also impacts splicing by serving as a mark of co-transcriptional spliceosome release and ensuring efficient post-transcriptional splicing genome-wide. Thus, comprehensive Pol II interactomes identify the complex and functional connections between transcription machinery and other gene regulatory complexes.

Interactomes, manufacturomes and relational biology: analogies between systems biology and manufacturing systems

Science.gov (United States)

2011-01-01

Background We review and extend the work of Rosen and Casti who discuss category theory with regards to systems biology and manufacturing systems, respectively. Results We describe anticipatory systems, or long-range feed-forward chemical reaction chains, and compare them to open-loop manufacturing processes. We then close the loop by discussing metabolism-repair systems and describe the rationality of the self-referential equation f = f (f). This relationship is derived from some boundary conditions that, in molecular systems biology, can be stated as the cardinality of the following molecular sets must be about equal: metabolome, genome, proteome. We show that this conjecture is not likely correct so the problem of self-referential mappings for describing the boundary between living and nonliving systems remains an open question. We calculate a lower and upper bound for the number of edges in the molecular interaction network (the interactome) for two cellular organisms and for two manufacturomes for CMOS integrated circuit manufacturing. Conclusions We show that the relevant mapping relations may not be Abelian, and that these problems cannot yet be resolved because the interactomes and manufacturomes are incomplete. PMID:21689427

Interactomic approach for evaluating nucleophosmin-binding proteins as biomarkers for Ewing's sarcoma.

Science.gov (United States)

Haga, Ayako; Ogawara, Yoko; Kubota, Daisuke; Kitabayashi, Issay; Murakami, Yasufumi; Kondo, Tadashi

2013-06-01

Nucleophosmin (NPM) is a novel prognostic biomarker for Ewing's sarcoma. To evaluate the prognostic utility of NPM, we conducted an interactomic approach to characterize the NPM protein complex in Ewing's sarcoma cells. A gene suppression assay revealed that NPM promoted cell proliferation and the invasive properties of Ewing's sarcoma cells. FLAG-tag-based affinity purification coupled with liquid chromatography-tandem mass spectrometry identified 106 proteins in the NPM protein complex. The functional classification suggested that the NPM complex participates in critical biological events, including ribosome biogenesis, regulation of transcription and translation, and protein folding, that are mediated by these proteins. In addition to JAK1, a candidate prognostic biomarker for Ewing's sarcoma, the NPM complex, includes 11 proteins known as prognostic biomarkers for other malignancies. Meta-analysis of gene expression profiles of 32 patients with Ewing's sarcoma revealed that 6 of 106 were significantly and independently associated with survival period. These observations suggest a functional role as well as prognostic value of these NPM complex proteins in Ewing's sarcoma. Further, our study suggests the potential applications of interactomics in conjunction with meta-analysis for biomarker discovery. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

RNA/DNA Hybrid Interactome Identifies DXH9 as a Molecular Player in Transcriptional Termination and R-Loop-Associated DNA Damage.

Science.gov (United States)

Cristini, Agnese; Groh, Matthias; Kristiansen, Maiken S; Gromak, Natalia

2018-05-08

R-loops comprise an RNA/DNA hybrid and displaced single-stranded DNA. They play important biological roles and are implicated in pathology. Even so, proteins recognizing these structures are largely undefined. Using affinity purification with the S9.6 antibody coupled to mass spectrometry, we defined the RNA/DNA hybrid interactome in HeLa cells. This consists of known R-loop-associated factors SRSF1, FACT, and Top1, and yet uncharacterized interactors, including helicases, RNA processing, DNA repair, and chromatin factors. We validate specific examples of these interactors and characterize their involvement in R-loop biology. A top candidate DHX9 helicase promotes R-loop suppression and transcriptional termination. DHX9 interacts with PARP1, and both proteins prevent R-loop-associated DNA damage. DHX9 and other interactome helicases are overexpressed in cancer, linking R-loop-mediated DNA damage and disease. Our RNA/DNA hybrid interactome provides a powerful resource to study R-loop biology in health and disease. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

A graph kernel approach for alignment-free domain-peptide interaction prediction with an application to human SH3 domains.

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Kundu, Kousik; Costa, Fabrizio; Backofen, Rolf

2013-07-01

State-of-the-art experimental data for determining binding specificities of peptide recognition modules (PRMs) is obtained by high-throughput approaches like peptide arrays. Most prediction tools applicable to this kind of data are based on an initial multiple alignment of the peptide ligands. Building an initial alignment can be error-prone, especially in the case of the proline-rich peptides bound by the SH3 domains. Here, we present a machine-learning approach based on an efficient graph-kernel technique to predict the specificity of a large set of 70 human SH3 domains, which are an important class of PRMs. The graph-kernel strategy allows us to (i) integrate several types of physico-chemical information for each amino acid, (ii) consider high-order correlations between these features and (iii) eliminate the need for an initial peptide alignment. We build specialized models for each human SH3 domain and achieve competitive predictive performance of 0.73 area under precision-recall curve, compared with 0.27 area under precision-recall curve for state-of-the-art methods based on position weight matrices. We show that better models can be obtained when we use information on the noninteracting peptides (negative examples), which is currently not used by the state-of-the art approaches based on position weight matrices. To this end, we analyze two strategies to identify subsets of high confidence negative data. The techniques introduced here are more general and hence can also be used for any other protein domains, which interact with short peptides (i.e. other PRMs). The program with the predictive models can be found at http://www.bioinf.uni-freiburg.de/Software/SH3PepInt/SH3PepInt.tar.gz. We also provide a genome-wide prediction for all 70 human SH3 domains, which can be found under http://www.bioinf.uni-freiburg.de/Software/SH3PepInt/Genome-Wide-Predictions.tar.gz. Supplementary data are available at Bioinformatics online.

An Efficient Semi-supervised Learning Approach to Predict SH2 Domain Mediated Interactions.

Science.gov (United States)

Kundu, Kousik; Backofen, Rolf

2017-01-01

Src homology 2 (SH2) domain is an important subclass of modular protein domains that plays an indispensable role in several biological processes in eukaryotes. SH2 domains specifically bind to the phosphotyrosine residue of their binding peptides to facilitate various molecular functions. For determining the subtle binding specificities of SH2 domains, it is very important to understand the intriguing mechanisms by which these domains recognize their target peptides in a complex cellular environment. There are several attempts have been made to predict SH2-peptide interactions using high-throughput data. However, these high-throughput data are often affected by a low signal to noise ratio. Furthermore, the prediction methods have several additional shortcomings, such as linearity problem, high computational complexity, etc. Thus, computational identification of SH2-peptide interactions using high-throughput data remains challenging. Here, we propose a machine learning approach based on an efficient semi-supervised learning technique for the prediction of 51 SH2 domain mediated interactions in the human proteome. In our study, we have successfully employed several strategies to tackle the major problems in computational identification of SH2-peptide interactions.

Investigation of PARP-1, PARP-2, and PARG interactomes by affinity-purification mass spectrometry

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Isabelle Maxim

2010-04-01

Full Text Available Abstract Background Poly(ADP-ribose polymerases (PARPs catalyze the formation of poly(ADP-ribose (pADPr, a post-translational modification involved in several important biological processes, namely surveillance of genome integrity, cell cycle progression, initiation of the DNA damage response, apoptosis, and regulation of transcription. Poly(ADP-ribose glycohydrolase (PARG, on the other hand, catabolizes pADPr and thereby accounts for the transient nature of poly(ADP-ribosylation. Our investigation of the interactomes of PARP-1, PARP-2, and PARG by affinity-purification mass spectrometry (AP-MS aimed, on the one hand, to confirm current knowledge on these interactomes and, on the other hand, to discover new protein partners which could offer insights into PARPs and PARG functions. Results PARP-1, PARP-2, and PARG were immunoprecipitated from human cells, and pulled-down proteins were separated by gel electrophoresis prior to in-gel trypsin digestion. Peptides were identified by tandem mass spectrometry. Our AP-MS experiments resulted in the identifications of 179 interactions, 139 of which are novel interactions. Gene Ontology analysis of the identified protein interactors points to five biological processes in which PARP-1, PARP-2 and PARG may be involved: RNA metabolism for PARP-1, PARP-2 and PARG; DNA repair and apoptosis for PARP-1 and PARP-2; and glycolysis and cell cycle for PARP-1. Conclusions This study reveals several novel protein partners for PARP-1, PARP-2 and PARG. It provides a global view of the interactomes of these proteins as well as a roadmap to establish the systems biology of poly(ADP-ribose metabolism.

Deciphering peculiar protein-protein interacting modules in Deinococcus radiodurans

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Barkallah Insaf

2009-04-01

Full Text Available Abstract Interactomes of proteins under positive selection from ionizing-radiation-resistant bacteria (IRRB might be a part of the answer to the question as to how IRRB, particularly Deinococcus radiodurans R1 (Deira, resist ionizing radiation. Here, using the Database of Interacting Proteins (DIP and the Protein Structural Interactome (PSI-base server for PSI map, we have predicted novel interactions of orthologs of the 58 proteins under positive selection in Deira and other IRRB, but which are absent in IRSB. Among these, 18 domains and their interactomes have been identified in DNA checkpoint and repair; kinases pathways; energy and nucleotide metabolisms were the important biological processes that were found to be involved. This finding provides new clues to the cellular pathways that can to be important for ionizing-radiation resistance in Deira.

COPRED: prediction of fold, GO molecular function and functional residues at the domain level.

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López, Daniel; Pazos, Florencio

2013-07-15

Only recently the first resources devoted to the functional annotation of proteins at the domain level started to appear. The next step is to develop specific methodologies for predicting function at the domain level based on these resources, and to implement them in web servers to be used by the community. In this work, we present COPRED, a web server for the concomitant prediction of fold, molecular function and functional sites at the domain level, based on a methodology for domain molecular function prediction and a resource of domain functional annotations previously developed and benchmarked. COPRED can be freely accessed at http://csbg.cnb.csic.es/copred. The interface works in all standard web browsers. WebGL (natively supported by most browsers) is required for the in-line preview and manipulation of protein 3D structures. The website includes a detailed help section and usage examples. pazos@cnb.csic.es.

The development and application of a quantitative peptide microarray platform to SH2 domain specificity space

Science.gov (United States)

Engelmann, Brett Warren

The Src homology 2 (SH2) domains evolved alongside protein tyrosine kinases (PTKs) and phosphatases (PTPs) in metazoans to recognize the phosphotyrosine (pY) post-translational modification. The human genome encodes 121 SH2 domains within 111 SH2 domain containing proteins that represent the primary mechanism for cellular signal transduction immediately downstream of PTKs. Despite pY recognition contributing to roughly half of the binding energy, SH2 domains possess substantial binding specificity, or affinity discrimination between phosphopeptide ligands. This specificity is largely imparted by amino acids (AAs) adjacent to the pY, typically from positions +1 to +4 C-terminal to the pY. Much experimental effort has been undertaken to construct preferred binding motifs for many SH2 domains. However, due to limitations in previous experimental methodologies these motifs do not account for the interplay between AAs. It was therefore not known how AAs within the context of individual peptides function to impart SH2 domain specificity. In this work we identified the critical role context plays in defining SH2 domain specificity for physiological ligands. We also constructed a high quality interactome using 50 SH2 domains and 192 physiological ligands. We next developed a quantitative high-throughput (Q-HTP) peptide microarray platform to assess the affinities four SH2 domains have for 124 physiological ligands. We demonstrated the superior characteristics of our platform relative to preceding approaches and validated our results using established biophysical techniques, literature corroboration, and predictive algorithms. The quantitative information provided by the arrays was leveraged to investigate SH2 domain binding distributions and identify points of binding overlap. Our microarray derived affinity estimates were integrated to produce quantitative interaction motifs capable of predicting interactions. Furthermore, our microarrays proved capable of resolving

BIPS: BIANA Interolog Prediction Server. A tool for protein-protein interaction inference.

Science.gov (United States)

Garcia-Garcia, Javier; Schleker, Sylvia; Klein-Seetharaman, Judith; Oliva, Baldo

2012-07-01

Protein-protein interactions (PPIs) play a crucial role in biology, and high-throughput experiments have greatly increased the coverage of known interactions. Still, identification of complete inter- and intraspecies interactomes is far from being complete. Experimental data can be complemented by the prediction of PPIs within an organism or between two organisms based on the known interactions of the orthologous genes of other organisms (interologs). Here, we present the BIANA (Biologic Interactions and Network Analysis) Interolog Prediction Server (BIPS), which offers a web-based interface to facilitate PPI predictions based on interolog information. BIPS benefits from the capabilities of the framework BIANA to integrate the several PPI-related databases. Additional metadata can be used to improve the reliability of the predicted interactions. Sensitivity and specificity of the server have been calculated using known PPIs from different interactomes using a leave-one-out approach. The specificity is between 72 and 98%, whereas sensitivity varies between 1 and 59%, depending on the sequence identity cut-off used to calculate similarities between sequences. BIPS is freely accessible at http://sbi.imim.es/BIPS.php.

Sequential Elution Interactome Analysis of the Mind Bomb 1 Ubiquitin Ligase Reveals a Novel Role in Dendritic Spine Outgrowth*

Science.gov (United States)

Mertz, Joseph; Tan, Haiyan; Pagala, Vishwajeeth; Bai, Bing; Chen, Ping-Chung; Li, Yuxin; Cho, Ji-Hoon; Shaw, Timothy; Wang, Xusheng; Peng, Junmin

2015-01-01

The mind bomb 1 (Mib1) ubiquitin ligase is essential for controlling metazoan development by Notch signaling and possibly the Wnt pathway. It is also expressed in postmitotic neurons and regulates neuronal morphogenesis and synaptic activity by mechanisms that are largely unknown. We sought to comprehensively characterize the Mib1 interactome and study its potential function in neuron development utilizing a novel sequential elution strategy for affinity purification, in which Mib1 binding proteins were eluted under different stringency and then quantified by the isobaric labeling method. The strategy identified the Mib1 interactome with both deep coverage and the ability to distinguish high-affinity partners from low-affinity partners. A total of 817 proteins were identified during the Mib1 affinity purification, including 56 high-affinity partners and 335 low-affinity partners, whereas the remaining 426 proteins are likely copurified contaminants or extremely weak binding proteins. The analysis detected all previously known Mib1-interacting proteins and revealed a large number of novel components involved in Notch and Wnt pathways, endocytosis and vesicle transport, the ubiquitin-proteasome system, cellular morphogenesis, and synaptic activities. Immunofluorescence studies further showed colocalization of Mib1 with five selected proteins: the Usp9x (FAM) deubiquitinating enzyme, alpha-, beta-, and delta-catenins, and CDKL5. Mutations of CDKL5 are associated with early infantile epileptic encephalopathy-2 (EIEE2), a severe form of mental retardation. We found that the expression of Mib1 down-regulated the protein level of CDKL5 by ubiquitination, and antagonized CDKL5 function during the formation of dendritic spines. Thus, the sequential elution strategy enables biochemical characterization of protein interactomes; and Mib1 analysis provides a comprehensive interactome for investigating its role in signaling networks and neuronal development. PMID:25931508

The chicken B-cell line DT40 proteome, beadome and interactomes

Directory of Open Access Journals (Sweden)

Johanna S. Rees

2015-06-01

Full Text Available In developing a new quantitative AP-MS method for exploring interactomes in the chicken B-cell line DT40, we also surveyed the most abundant proteins in this organism and explored the likely contaminants that bind to a variety of affinity resins that would later be confirmed quantitatively [1]. We present the ‘Top 150 abundant DT40 proteins list’, the DT40 beadomes as well as protein interaction lists for the Phosphatidyl inositol 5-phosphate 4-kinase 2β and Fanconi anaemia protein complexes.

The L1TD1 Protein Interactome Reveals the Importance of Post-transcriptional Regulation in Human Pluripotency

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Maheswara Reddy Emani

2015-03-01

Full Text Available The RNA-binding protein L1TD1 is one of the most specific and abundant proteins in pluripotent stem cells and is essential for the maintenance of pluripotency in human cells. Here, we identify the protein interaction network of L1TD1 in human embryonic stem cells (hESCs and provide insights into the interactome network constructed in human pluripotent cells. Our data reveal that L1TD1 has an important role in RNA splicing, translation, protein traffic, and degradation. L1TD1 interacts with multiple stem-cell-specific proteins, many of which are still uncharacterized in the context of development. Further, we show that L1TD1 is a part of the pluripotency interactome network of OCT4, SOX2, and NANOG, bridging nuclear and cytoplasmic regulation and highlighting the importance of RNA biology in pluripotency.

Delayed Recall and Working Memory MMSE Domains Predict Delirium following Cardiac Surgery.

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Price, Catherine C; Garvan, Cynthia; Hizel, Loren P; Lopez, Marcos G; Billings, Frederic T

2017-01-01

Reduced preoperative cognition is a risk factor for postoperative delirium. The significance for type of preoperative cognitive deficit, however, has yet to be explored and could provide important insights into mechanisms and prediction of delirium. Our goal was to determine if certain cognitive domains from the general cognitive screener, the Mini-Mental State Exam (MMSE), predict delirium after cardiac surgery. Patients completed a preoperative MMSE prior to undergoing elective cardiac surgery. Following surgery, delirium was assessed throughout ICU stay using the Confusion Assessment Method for ICU delirium and the Richmond Agitation and Sedation Scale. Cardiac surgery patients who developed delirium (n = 137) had lower total MMSE scores than patients who did not develop delirium (n = 457). In particular, orientation to place, working memory, delayed recall, and language domain scores were lower. Of these, only the working memory and delayed recall domains predicted delirium in a regression model adjusting for history of chronic obstructive pulmonary disease, age, sex, and duration of cardiopulmonary bypass. For each word not recalled on the three-word delayed recall assessment, the odds of delirium increased by 50%. For each item missed on the working memory index, the odds of delirium increased by 36%. Of the patients who developed delirium, 47% had a primary impairment in memory, 21% in working memory, and 33% in both domains. The area under the receiver operating characteristics curve using only the working memory and delayed recall domains was 0.75, compared to 0.76 for total MMSE score. Delirium risk is greater for individuals with reduced MMSE scores on the delayed recall and working memory domains. Research should address why patients with memory and executive vulnerabilities are more prone to postoperative delirium than those with other cognitive limitations.

Triangle network motifs predict complexes by complementing high-error interactomes with structural information.

Science.gov (United States)

Andreopoulos, Bill; Winter, Christof; Labudde, Dirk; Schroeder, Michael

2009-06-27

A lot of high-throughput studies produce protein-protein interaction networks (PPINs) with many errors and missing information. Even for genome-wide approaches, there is often a low overlap between PPINs produced by different studies. Second-level neighbors separated by two protein-protein interactions (PPIs) were previously used for predicting protein function and finding complexes in high-error PPINs. We retrieve second level neighbors in PPINs, and complement these with structural domain-domain interactions (SDDIs) representing binding evidence on proteins, forming PPI-SDDI-PPI triangles. We find low overlap between PPINs, SDDIs and known complexes, all well below 10%. We evaluate the overlap of PPI-SDDI-PPI triangles with known complexes from Munich Information center for Protein Sequences (MIPS). PPI-SDDI-PPI triangles have ~20 times higher overlap with MIPS complexes than using second-level neighbors in PPINs without SDDIs. The biological interpretation for triangles is that a SDDI causes two proteins to be observed with common interaction partners in high-throughput experiments. The relatively few SDDIs overlapping with PPINs are part of highly connected SDDI components, and are more likely to be detected in experimental studies. We demonstrate the utility of PPI-SDDI-PPI triangles by reconstructing myosin-actin processes in the nucleus, cytoplasm, and cytoskeleton, which were not obvious in the original PPIN. Using other complementary datatypes in place of SDDIs to form triangles, such as PubMed co-occurrences or threading information, results in a similar ability to find protein complexes. Given high-error PPINs with missing information, triangles of mixed datatypes are a promising direction for finding protein complexes. Integrating PPINs with SDDIs improves finding complexes. Structural SDDIs partially explain the high functional similarity of second-level neighbors in PPINs. We estimate that relatively little structural information would be sufficient

Structures and short linear motif of disordered transcription factor regions provide clues to the interactome of the cellular hub radical-induced cell death1

DEFF Research Database (Denmark)

O'Shea, Charlotte; Staby, Lasse; Bendsen, Sidsel Krogh

2017-01-01

Intrinsically disordered protein regions (IDRs) lack a well-defined three-dimensional structure, but often facilitate key protein functions. Some interactions between IDRs and folded protein domains rely on short linear motifs (SLiMs). These motifs are challenging to identify, but once found can...... point to larger networks of interactions, such as with proteins that serve as hubs for essential cellular functions. The stress-associated plant protein Radical-Induced Cell Death1 (RCD1) is one such hub, interacting with many transcription factors via their flexible IDRs. To identify the SLiM bound......046 formed different structures or were fuzzy in the complexes. These findings allow us to present a model of the stress-associated RCD1-transcription factor interactome and to contribute to the emerging understanding of the interactions between folded hubs and their intrinsically disordered partners....

Genome-Wide Prediction and Analysis of 3D-Domain Swapped Proteins in the Human Genome from Sequence Information.

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Upadhyay, Atul Kumar; Sowdhamini, Ramanathan

2016-01-01

3D-domain swapping is one of the mechanisms of protein oligomerization and the proteins exhibiting this phenomenon have many biological functions. These proteins, which undergo domain swapping, have acquired much attention owing to their involvement in human diseases, such as conformational diseases, amyloidosis, serpinopathies, proteionopathies etc. Early realisation of proteins in the whole human genome that retain tendency to domain swap will enable many aspects of disease control management. Predictive models were developed by using machine learning approaches with an average accuracy of 78% (85.6% of sensitivity, 87.5% of specificity and an MCC value of 0.72) to predict putative domain swapping in protein sequences. These models were applied to many complete genomes with special emphasis on the human genome. Nearly 44% of the protein sequences in the human genome were predicted positive for domain swapping. Enrichment analysis was performed on the positively predicted sequences from human genome for their domain distribution, disease association and functional importance based on Gene Ontology (GO). Enrichment analysis was also performed to infer a better understanding of the functional importance of these sequences. Finally, we developed hinge region prediction, in the given putative domain swapped sequence, by using important physicochemical properties of amino acids.

Embryonic stem cell interactomics: the beginning of a long road to biological function.

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Yousefi, Maram; Hajihoseini, Vahid; Jung, Woojin; Hosseinpour, Batol; Rassouli, Hassan; Lee, Bonghee; Baharvand, Hossein; Lee, KiYoung; Salekdeh, Ghasem Hosseini

2012-12-01

Embryonic stem cells (ESCs) are capable of unlimited self-renewal while maintaining pluripotency. They are of great interest in regenerative medicine due to their ability to differentiate into all cell types of the three embryonic germ layers. Recently, induced pluripotent stem cells (iPSCs) have shown similarities to ESCs and thus promise great therapeutic potential in regenerative medicine. Despite progress in stem cell biology, our understanding of the exact mechanisms by which pluripotency and self-renewal are established and maintained is largely unknown. A better understanding of these processes may lead to discovery of alternative ways for reprogramming, differentiation and more reliable applications of stem cells in therapies. It has become evident that proteins generally function as members of large complexes that are part of a more complex network. Therefore, the identification of protein-protein interactions (PPI) is an efficient strategy for understanding protein function and regulation. Systematic genome-wide and pathway-specific PPI analysis of ESCs has generated a network of ESC proteins, including major transcription factors. These PPI networks of ESCs may contribute to a mechanistic understanding of self-renewal and pluripotency. In this review we describe different experimental approaches for the identification of PPIs along with various databases. We discuss biological findings and technical challenges encountered with interactome studies of pluripotent stem cells, and provide insight into how interactomics is likely to develop.

Prediction of small molecule binding property of protein domains with Bayesian classifiers based on Markov chains.

Science.gov (United States)

Bulashevska, Alla; Stein, Martin; Jackson, David; Eils, Roland

2009-12-01

Accurate computational methods that can help to predict biological function of a protein from its sequence are of great interest to research biologists and pharmaceutical companies. One approach to assume the function of proteins is to predict the interactions between proteins and other molecules. In this work, we propose a machine learning method that uses a primary sequence of a domain to predict its propensity for interaction with small molecules. By curating the Pfam database with respect to the small molecule binding ability of its component domains, we have constructed a dataset of small molecule binding and non-binding domains. This dataset was then used as training set to learn a Bayesian classifier, which should distinguish members of each class. The domain sequences of both classes are modelled with Markov chains. In a Jack-knife test, our classification procedure achieved the predictive accuracies of 77.2% and 66.7% for binding and non-binding classes respectively. We demonstrate the applicability of our classifier by using it to identify previously unknown small molecule binding domains. Our predictions are available as supplementary material and can provide very useful information to drug discovery specialists. Given the ubiquitous and essential role small molecules play in biological processes, our method is important for identifying pharmaceutically relevant components of complete proteomes. The software is available from the author upon request.

Human alpha2-macroglobulin is composed of multiple domains, as predicted by homology with complement component C3.

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Doan, Ninh; Gettins, Peter G W

2007-10-01

Human alpha2M (alpha2-macroglobulin) and the complement components C3 and C4 are thiol ester-containing proteins that evolved from the same ancestral gene. The recent structure determination of human C3 has allowed a detailed prediction of the location of domains within human alpha2M to be made. We describe here the expression and characterization of three alpha(2)M domains predicted to be involved in the stabilization of the thiol ester in native alpha2M and in its activation upon bait region proteolysis. The three newly expressed domains are MG2 (macroglobulin domain 2), TED (thiol ester-containing domain) and CUB (complement protein subcomponents C1r/C1s, urchin embryonic growth factor and bone morphogenetic protein 1) domain. Together with the previously characterized RBD (receptor-binding domain), they represent approx. 42% of the alpha2M polypeptide. Their expression as folded domains strongly supports the predicted domain organization of alpha2M. An X-ray crystal structure of MG2 shows it to have a fibronectin type-3 fold analogous to MG1-MG8 of C3. TED is, as predicted, an alpha-helical domain. CUB is a spliced domain composed of two stretches of polypeptide that flank TED in the primary structure. In intact C3 TED interacts with RBD, where it is in direct contact with the thiol ester, and with MG2 and CUB on opposite, flanking sides. In contrast, these alpha2M domains, as isolated species, show negligible interaction with one another, suggesting that the native conformation of alpha2M, and the consequent thiol ester-stabilizing domain-domain interactions, result from additional restraints imposed by the physical linkage of these domains or by additional domains in the protein.

Introducing the hypothome

DEFF Research Database (Denmark)

Madsen, Claus Desler; Zambach, Sine; Suravajhala, Prashanth

2014-01-01

of doing so is the risk of devaluing the definition of interactomes. By adding proteins that have only been predicted, an interactome can no longer be classified as experimentally verified and the integrity of the interactome will be endured. Therefore, we propose the term 'hypothome' (collection......An interactome is defined as a network of protein-protein interactions built from experimentally verified interactions. Basic science as well as application-based research of potential new drugs can be promoted by including proteins that are only predicted into interactomes. The disadvantage...

Human α2-macroglobulin is composed of multiple domains, as predicted by homology with complement component C3

Science.gov (United States)

Doan, Ninh; Gettins, Peter G. W.

2007-01-01

Human α2M (α2-macroglobulin) and the complement components C3 and C4 are thiol ester-containing proteins that evolved from the same ancestral gene. The recent structure determination of human C3 has allowed a detailed prediction of the location of domains within human α2M to be made. We describe here the expression and characterization of three α2M domains predicted to be involved in the stabilization of the thiol ester in native α2M and in its activation upon bait region proteolysis. The three newly expressed domains are MG2 (macroglobulin domain 2), TED (thiol ester-containing domain) and CUB (complement protein subcomponents C1r/C1s, urchin embryonic growth factor and bone morphogenetic protein 1) domain. Together with the previously characterized RBD (receptor-binding domain), they represent approx. 42% of the α2M polypeptide. Their expression as folded domains strongly supports the predicted domain organization of α2M. An X-ray crystal structure of MG2 shows it to have a fibronectin type-3 fold analogous to MG1–MG8 of C3. TED is, as predicted, an α-helical domain. CUB is a spliced domain composed of two stretches of polypeptide that flank TED in the primary structure. In intact C3 TED interacts with RBD, where it is in direct contact with the thiol ester, and with MG2 and CUB on opposite, flanking sides. In contrast, these α2M domains, as isolated species, show negligible interaction with one another, suggesting that the native conformation of α2M, and the consequent thiol ester-stabilizing domain–domain interactions, result from additional restraints imposed by the physical linkage of these domains or by additional domains in the protein. PMID:17608619

Triangle network motifs predict complexes by complementing high-error interactomes with structural information

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Labudde Dirk

2009-06-01

Full Text Available Abstract Background A lot of high-throughput studies produce protein-protein interaction networks (PPINs with many errors and missing information. Even for genome-wide approaches, there is often a low overlap between PPINs produced by different studies. Second-level neighbors separated by two protein-protein interactions (PPIs were previously used for predicting protein function and finding complexes in high-error PPINs. We retrieve second level neighbors in PPINs, and complement these with structural domain-domain interactions (SDDIs representing binding evidence on proteins, forming PPI-SDDI-PPI triangles. Results We find low overlap between PPINs, SDDIs and known complexes, all well below 10%. We evaluate the overlap of PPI-SDDI-PPI triangles with known complexes from Munich Information center for Protein Sequences (MIPS. PPI-SDDI-PPI triangles have ~20 times higher overlap with MIPS complexes than using second-level neighbors in PPINs without SDDIs. The biological interpretation for triangles is that a SDDI causes two proteins to be observed with common interaction partners in high-throughput experiments. The relatively few SDDIs overlapping with PPINs are part of highly connected SDDI components, and are more likely to be detected in experimental studies. We demonstrate the utility of PPI-SDDI-PPI triangles by reconstructing myosin-actin processes in the nucleus, cytoplasm, and cytoskeleton, which were not obvious in the original PPIN. Using other complementary datatypes in place of SDDIs to form triangles, such as PubMed co-occurrences or threading information, results in a similar ability to find protein complexes. Conclusion Given high-error PPINs with missing information, triangles of mixed datatypes are a promising direction for finding protein complexes. Integrating PPINs with SDDIs improves finding complexes. Structural SDDIs partially explain the high functional similarity of second-level neighbors in PPINs. We estimate that

The Role of Child Abuse and Neglect in Predicting the Early Maladaptive Schemas Domain

Directory of Open Access Journals (Sweden)

Mohammad Narimani

2012-10-01

Full Text Available Background: The purpose of this study was to investigate the role of child abuse and neglect in predicting the early maladaptive schemas domains.Materials and Methods: This is a causal-comparative research. Sampling was performed using multistage clustering and simple random sampling methods. 500 individuals constituted the preliminary sample. After identifying 140 abused individuals, they were compared to 140 ordinary persons. In order to collect the data, the 53-item version of Bernstein Childhood Trauma Questionnaire (CTQ, and Yang Schema Questionnaire: Short Form 2 (YSQ-SF2 were used. To analyze the data, multivariate regression coefficient enter method was deployed.Results: Results showed that about 24% of the variance of the disconnection and rejection maladaptive schema domain, as well as 12% of the variance of the impaired autonomy and performance maladaptive schema domain were explained by the emotional abuse, physical abuse, and physical neglect. 13% of the other-directedness maladaptive schema domain variance, 6% of the impaired limits maladaptive schema domain, and 5% of the overvigilance and inhibition maladaptive schema domain variance were explained by the emotional abuse.Conclusion: According to the findings, it can be concluded that one could predict schemas and their respective domains with regards to abused children. Abused children are likely to develop maladaptive schemas and cognitive distortions due to the dull and harsh atmosphere of the family and its unhealthy environment.

Predictive value of cognition for different domains of outcome in recent-onset schizophrenia.

Science.gov (United States)

Holthausen, Esther A E; Wiersma, Durk; Cahn, Wiepke; Kahn, René S; Dingemans, Peter M; Schene, Aart H; van den Bosch, Robert J

2007-01-15

The aim of this study was to see whether and how cognition predicts outcome in recent-onset schizophrenia in a large range of domains such as course of illness, self-care, interpersonal functioning, vocational functioning and need for care. At inclusion, 115 recent-onset patients were tested on a cognitive battery and 103 patients participated in the follow-up 2 years after inclusion. Differences in outcome between cognitively normal and cognitively impaired patients were also analysed. Cognitive measures at inclusion did not predict number of relapses, activities of daily living and interpersonal functioning. Time in psychosis or in full remission, as well as need for care, were partly predicted by specific cognitive measures. Although statistically significant, the predictive value of cognition with regard to clinical outcome was limited. There was a significant difference between patients with and without cognitive deficits in competitive employment status and vocational functioning. The predictive value of cognition for different social outcome domains varies. It seems that cognition most strongly predicts work performance, where having a cognitive deficit, regardless of the nature of the deficit, acts as a rate-limiting factor.

PrionScan: an online database of predicted prion domains in complete proteomes.

Science.gov (United States)

Espinosa Angarica, Vladimir; Angulo, Alfonso; Giner, Arturo; Losilla, Guillermo; Ventura, Salvador; Sancho, Javier

2014-02-05

Prions are a particular type of amyloids related to a large variety of important processes in cells, but also responsible for serious diseases in mammals and humans. The number of experimentally characterized prions is still low and corresponds to a handful of examples in microorganisms and mammals. Prion aggregation is mediated by specific protein domains with a remarkable compositional bias towards glutamine/asparagine and against charged residues and prolines. These compositional features have been used to predict new prion proteins in the genomes of different organisms. Despite these efforts, there are only a few available data sources containing prion predictions at a genomic scale. Here we present PrionScan, a new database of predicted prion-like domains in complete proteomes. We have previously developed a predictive methodology to identify and score prionogenic stretches in protein sequences. In the present work, we exploit this approach to scan all the protein sequences in public databases and compile a repository containing relevant information of proteins bearing prion-like domains. The database is updated regularly alongside UniprotKB and in its present version contains approximately 28000 predictions in proteins from different functional categories in more than 3200 organisms from all the taxonomic subdivisions. PrionScan can be used in two different ways: database query and analysis of protein sequences submitted by the users. In the first mode, simple queries allow to retrieve a detailed description of the properties of a defined protein. Queries can also be combined to generate more complex and specific searching patterns. In the second mode, users can submit and analyze their own sequences. It is expected that this database would provide relevant insights on prion functions and regulation from a genome-wide perspective, allowing researches performing cross-species prion biology studies. Our database might also be useful for guiding experimentalists

MADS interactomics : towards understanding the molecular mechanisms of plant MADS-domain transcription factor function

NARCIS (Netherlands)

Smaczniak, C.D.

2013-01-01

Protein-protein and protein-DNA interactions are essential for the molecular action of transcription factors. By combinatorial binding to target gene promoters, transcription factors are able to up- or down-regulate the expression of these genes. MADS-domain proteins comprise a large family of

Predicting detection performance with model observers: Fourier domain or spatial domain?

Science.gov (United States)

Chen, Baiyu; Yu, Lifeng; Leng, Shuai; Kofler, James; Favazza, Christopher; Vrieze, Thomas; McCollough, Cynthia

2016-02-27

The use of Fourier domain model observer is challenged by iterative reconstruction (IR), because IR algorithms are nonlinear and IR images have noise texture different from that of FBP. A modified Fourier domain model observer, which incorporates nonlinear noise and resolution properties, has been proposed for IR and needs to be validated with human detection performance. On the other hand, the spatial domain model observer is theoretically applicable to IR, but more computationally intensive than the Fourier domain method. The purpose of this study is to compare the modified Fourier domain model observer to the spatial domain model observer with both FBP and IR images, using human detection performance as the gold standard. A phantom with inserts of various low contrast levels and sizes was repeatedly scanned 100 times on a third-generation, dual-source CT scanner at 5 dose levels and reconstructed using FBP and IR algorithms. The human detection performance of the inserts was measured via a 2-alternative-forced-choice (2AFC) test. In addition, two model observer performances were calculated, including a Fourier domain non-prewhitening model observer and a spatial domain channelized Hotelling observer. The performance of these two mode observers was compared in terms of how well they correlated with human observer performance. Our results demonstrated that the spatial domain model observer correlated well with human observers across various dose levels, object contrast levels, and object sizes. The Fourier domain observer correlated well with human observers using FBP images, but overestimated the detection performance using IR images.

Interactome Screening Identifies the ER Luminal Chaperone Hsp47 as a Regulator of the Unfolded Protein Response Transducer IRE1α.

Science.gov (United States)

Sepulveda, Denisse; Rojas-Rivera, Diego; Rodríguez, Diego A; Groenendyk, Jody; Köhler, Andres; Lebeaupin, Cynthia; Ito, Shinya; Urra, Hery; Carreras-Sureda, Amado; Hazari, Younis; Vasseur-Cognet, Mireille; Ali, Maruf M U; Chevet, Eric; Campos, Gisela; Godoy, Patricio; Vaisar, Tomas; Bailly-Maitre, Béatrice; Nagata, Kazuhiro; Michalak, Marek; Sierralta, Jimena; Hetz, Claudio

2018-01-18

Maintenance of endoplasmic reticulum (ER) proteostasis is controlled by a dynamic signaling network known as the unfolded protein response (UPR). IRE1α is a major UPR transducer, determining cell fate under ER stress. We used an interactome screening to unveil several regulators of the UPR, highlighting the ER chaperone Hsp47 as the major hit. Cellular and biochemical analysis indicated that Hsp47 instigates IRE1α signaling through a physical interaction. Hsp47 directly binds to the ER luminal domain of IRE1α with high affinity, displacing the negative regulator BiP from the complex to facilitate IRE1α oligomerization. The regulation of IRE1α signaling by Hsp47 is evolutionarily conserved as validated using fly and mouse models of ER stress. Hsp47 deficiency sensitized cells and animals to experimental ER stress, revealing the significance of Hsp47 to global proteostasis maintenance. We conclude that Hsp47 adjusts IRE1α signaling by fine-tuning the threshold to engage an adaptive UPR. Copyright © 2018 Elsevier Inc. All rights reserved.

Striatal Transcriptome and Interactome Analysis of Shank3-overexpressing Mice Reveals the Connectivity between Shank3 and mTORC1 Signaling

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Yeunkum Lee

2017-06-01

Full Text Available Mania causes symptoms of hyperactivity, impulsivity, elevated mood, reduced anxiety and decreased need for sleep, which suggests that the dysfunction of the striatum, a critical component of the brain motor and reward system, can be causally associated with mania. However, detailed molecular pathophysiology underlying the striatal dysfunction in mania remains largely unknown. In this study, we aimed to identify the molecular pathways showing alterations in the striatum of SH3 and multiple ankyrin repeat domains 3 (Shank3-overexpressing transgenic (TG mice that display manic-like behaviors. The results of transcriptome analysis suggested that mammalian target of rapamycin complex 1 (mTORC1 signaling may be the primary molecular signature altered in the Shank3 TG striatum. Indeed, we found that striatal mTORC1 activity, as measured by mTOR S2448 phosphorylation, was significantly decreased in the Shank3 TG mice compared to wild-type (WT mice. To elucidate the potential underlying mechanism, we re-analyzed previously reported protein interactomes, and detected a high connectivity between Shank3 and several upstream regulators of mTORC1, such as tuberous sclerosis 1 (TSC1, TSC2 and Ras homolog enriched in striatum (Rhes, via 94 common interactors that we denominated “Shank3-mTORC1 interactome”. We noticed that, among the 94 common interactors, 11 proteins were related to actin filaments, the level of which was increased in the dorsal striatum of Shank3 TG mice. Furthermore, we could co-immunoprecipitate Shank3, Rhes and Wiskott-Aldrich syndrome protein family verprolin-homologous protein 1 (WAVE1 proteins from the striatal lysate of Shank3 TG mice. By comparing with the gene sets of psychiatric disorders, we also observed that the 94 proteins of Shank3-mTORC1 interactome were significantly associated with bipolar disorder (BD. Altogether, our results suggest a protein interaction-mediated connectivity between Shank3 and certain upstream

Accumulating Data to Optimally Predict Obesity Treatment (ADOPT) Core Measures: Psychosocial Domain.

Science.gov (United States)

Sutin, Angelina R; Boutelle, Kerri; Czajkowski, Susan M; Epel, Elissa S; Green, Paige A; Hunter, Christine M; Rice, Elise L; Williams, David M; Young-Hyman, Deborah; Rothman, Alexander J

2018-04-01

Within the Accumulating Data to Optimally Predict obesity Treatment (ADOPT) Core Measures Project, the psychosocial domain addresses how psychosocial processes underlie the influence of obesity treatment strategies on weight loss and weight maintenance. The subgroup for the psychosocial domain identified an initial list of high-priority constructs and measures that ranged from relatively stable characteristics about the person (cognitive function, personality) to dynamic characteristics that may change over time (motivation, affect). This paper describes (a) how the psychosocial domain fits into the broader model of weight loss and weight maintenance as conceptualized by ADOPT; (b) the guiding principles used to select constructs and measures for recommendation; (c) the high-priority constructs recommended for inclusion; (d) domain-specific issues for advancing the science; and (e) recommendations for future research. The inclusion of similar measures across trials will help to better identify how psychosocial factors mediate and moderate the weight loss and weight maintenance process, facilitate research into dynamic interactions with factors in the other ADOPT domains, and ultimately improve the design and delivery of effective interventions. © 2018 The Obesity Society.

Predicting binding within disordered protein regions to structurally characterised peptide-binding domains.

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Waqasuddin Khan

Full Text Available Disordered regions of proteins often bind to structured domains, mediating interactions within and between proteins. However, it is difficult to identify a priori the short disordered regions involved in binding. We set out to determine if docking such peptide regions to peptide binding domains would assist in these predictions.We assembled a redundancy reduced dataset of SLiM (Short Linear Motif containing proteins from the ELM database. We selected 84 sequences which had an associated PDB structures showing the SLiM bound to a protein receptor, where the SLiM was found within a 50 residue region of the protein sequence which was predicted to be disordered. First, we investigated the Vina docking scores of overlapping tripeptides from the 50 residue SLiM containing disordered regions of the protein sequence to the corresponding PDB domain. We found only weak discrimination of docking scores between peptides involved in binding and adjacent non-binding peptides in this context (AUC 0.58.Next, we trained a bidirectional recurrent neural network (BRNN using as input the protein sequence, predicted secondary structure, Vina docking score and predicted disorder score. The results were very promising (AUC 0.72 showing that multiple sources of information can be combined to produce results which are clearly superior to any single source.We conclude that the Vina docking score alone has only modest power to define the location of a peptide within a larger protein region known to contain it. However, combining this information with other knowledge (using machine learning methods clearly improves the identification of peptide binding regions within a protein sequence. This approach combining docking with machine learning is primarily a predictor of binding to peptide-binding sites, and is not intended as a predictor of specificity of binding to particular receptors.

System-level insights into the cellular interactome of a non-model organism: inferring, modelling and analysing functional gene network of soybean (Glycine max.

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Yungang Xu

Full Text Available Cellular interactome, in which genes and/or their products interact on several levels, forming transcriptional regulatory-, protein interaction-, metabolic-, signal transduction networks, etc., has attracted decades of research focuses. However, such a specific type of network alone can hardly explain the various interactive activities among genes. These networks characterize different interaction relationships, implying their unique intrinsic properties and defects, and covering different slices of biological information. Functional gene network (FGN, a consolidated interaction network that models fuzzy and more generalized notion of gene-gene relations, have been proposed to combine heterogeneous networks with the goal of identifying functional modules supported by multiple interaction types. There are yet no successful precedents of FGNs on sparsely studied non-model organisms, such as soybean (Glycine max, due to the absence of sufficient heterogeneous interaction data. We present an alternative solution for inferring the FGNs of soybean (SoyFGNs, in a pioneering study on the soybean interactome, which is also applicable to other organisms. SoyFGNs exhibit the typical characteristics of biological networks: scale-free, small-world architecture and modularization. Verified by co-expression and KEGG pathways, SoyFGNs are more extensive and accurate than an orthology network derived from Arabidopsis. As a case study, network-guided disease-resistance gene discovery indicates that SoyFGNs can provide system-level studies on gene functions and interactions. This work suggests that inferring and modelling the interactome of a non-model plant are feasible. It will speed up the discovery and definition of the functions and interactions of other genes that control important functions, such as nitrogen fixation and protein or lipid synthesis. The efforts of the study are the basis of our further comprehensive studies on the soybean functional

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

International Nuclear Information System (INIS)

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

2007-01-01

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

An affinity pull-down approach to identify the plant cyclic nucleotide interactome

KAUST Repository

Donaldson, Lara Elizabeth; Meier, Stuart Kurt

2013-01-01

Cyclic nucleotides (CNs) are intracellular second messengers that play an important role in mediating physiological responses to environmental and developmental signals, in species ranging from bacteria to humans. In response to these signals, CNs are synthesized by nucleotidyl cyclases and then act by binding to and altering the activity of downstream target proteins known as cyclic nucleotide-binding proteins (CNBPs). A number of CNBPs have been identified across kingdoms including transcription factors, protein kinases, phosphodiesterases, and channels, all of which harbor conserved CN-binding domains. In plants however, few CNBPs have been identified as homology searches fail to return plant sequences with significant matches to known CNBPs. Recently, affinity pull-down techniques have been successfully used to identify CNBPs in animals and have provided new insights into CN signaling. The application of these techniques to plants has not yet been extensively explored and offers an alternative approach toward the unbiased discovery of novel CNBP candidates in plants. Here, an affinity pull-down technique for the identification of the plant CN interactome is presented. In summary, the method involves an extraction of plant proteins which is incubated with a CN-bait, followed by a series of increasingly stringent elutions that eliminates proteins in a sequential manner according to their affinity to the bait. The eluted and bait-bound proteins are separated by one-dimensional gel electrophoresis, excised, and digested with trypsin after which the resultant peptides are identified by mass spectrometry - techniques that are commonplace in proteomics experiments. The discovery of plant CNBPs promises to provide valuable insight into the mechanism of CN signal transduction in plants. © Springer Science+Business Media New York 2013.

An affinity pull-down approach to identify the plant cyclic nucleotide interactome

KAUST Repository

Donaldson, Lara Elizabeth

2013-09-03

Cyclic nucleotides (CNs) are intracellular second messengers that play an important role in mediating physiological responses to environmental and developmental signals, in species ranging from bacteria to humans. In response to these signals, CNs are synthesized by nucleotidyl cyclases and then act by binding to and altering the activity of downstream target proteins known as cyclic nucleotide-binding proteins (CNBPs). A number of CNBPs have been identified across kingdoms including transcription factors, protein kinases, phosphodiesterases, and channels, all of which harbor conserved CN-binding domains. In plants however, few CNBPs have been identified as homology searches fail to return plant sequences with significant matches to known CNBPs. Recently, affinity pull-down techniques have been successfully used to identify CNBPs in animals and have provided new insights into CN signaling. The application of these techniques to plants has not yet been extensively explored and offers an alternative approach toward the unbiased discovery of novel CNBP candidates in plants. Here, an affinity pull-down technique for the identification of the plant CN interactome is presented. In summary, the method involves an extraction of plant proteins which is incubated with a CN-bait, followed by a series of increasingly stringent elutions that eliminates proteins in a sequential manner according to their affinity to the bait. The eluted and bait-bound proteins are separated by one-dimensional gel electrophoresis, excised, and digested with trypsin after which the resultant peptides are identified by mass spectrometry - techniques that are commonplace in proteomics experiments. The discovery of plant CNBPs promises to provide valuable insight into the mechanism of CN signal transduction in plants. © Springer Science+Business Media New York 2013.

Mapping the ER Interactome: The P Domains of Calnexin and Calreticulin as Plurivalent Adapters for Foldases and Chaperones.

Science.gov (United States)

Kozlov, Guennadi; Muñoz-Escobar, Juliana; Castro, Karla; Gehring, Kalle

2017-09-05

The lectin chaperones calreticulin (CRT) and calnexin (CNX) contribute to the folding of glycoproteins in the ER by recruiting foldases such as the protein disulfide isomerase ERp57 and the peptidyl prolyl cis-trans isomerase CypB. Recently, CRT was shown to interact with the chaperone ERp29. Here, we show that ERp29 directly binds to the P domain of CNX. Crystal structures of the D domain of ERp29 in complex with the P domains from CRT and calmegin, a tissue-specific CNX homolog, reveal a commonality in the mechanism of binding whereby the tip of the P domain functions as a plurivalent adapter to bind a variety of folding factors. We show that mutation of a single residue, D348 in CNX, abrogates binding to ERp29 as well as ERp57 and CypB. The structural diversity of the accessory factors suggests that these chaperones became specialized for glycoprotein folding through convergent evolution of their P-domain binding sites. Copyright © 2017 Elsevier Ltd. All rights reserved.

Predictive modeling of nanoscale domain morphology in solution-processed organic thin films

Science.gov (United States)

Schaaf, Cyrus; Jenkins, Michael; Morehouse, Robell; Stanfield, Dane; McDowall, Stephen; Johnson, Brad L.; Patrick, David L.

2017-09-01

The electronic and optoelectronic properties of molecular semiconductor thin films are directly linked to their extrinsic nanoscale structural characteristics such as domain size and spatial distributions. In films prepared by common solution-phase deposition techniques such as spin casting and solvent-based printing, morphology is governed by a complex interrelated set of thermodynamic and kinetic factors that classical models fail to adequately capture, leaving them unable to provide much insight, let alone predictive design guidance for tailoring films with specific nanostructural characteristics. Here we introduce a comprehensive treatment of solution-based film formation enabling quantitative prediction of domain formation rates, coverage, and spacing statistics based on a small number of experimentally measureable parameters. The model combines a mean-field rate equation treatment of monomer aggregation kinetics with classical nucleation theory and a supersaturation-dependent critical nucleus size to solve for the quasi-two-dimensional temporally and spatially varying monomer concentration, nucleation rate, and other properties. Excellent agreement is observed with measured nucleation densities and interdomain radial distribution functions in polycrystalline tetracene films. Numerical solutions lead to a set of general design rules enabling predictive morphological control in solution-processed molecular crystalline films.

Lukasiewicz-Topos Models of Neural Networks, Cell Genome and Interactome Nonlinear Dynamic Models

CERN Document Server

Baianu, I C

2004-01-01

A categorical and Lukasiewicz-Topos framework for Lukasiewicz Algebraic Logic models of nonlinear dynamics in complex functional systems such as neural networks, genomes and cell interactomes is proposed. Lukasiewicz Algebraic Logic models of genetic networks and signaling pathways in cells are formulated in terms of nonlinear dynamic systems with n-state components that allow for the generalization of previous logical models of both genetic activities and neural networks. An algebraic formulation of variable 'next-state functions' is extended to a Lukasiewicz Topos with an n-valued Lukasiewicz Algebraic Logic subobject classifier description that represents non-random and nonlinear network activities as well as their transformations in developmental processes and carcinogenesis.

Computationally Efficient Amplitude Modulated Sinusoidal Audio Coding using Frequency-Domain Linear Prediction

DEFF Research Database (Denmark)

Christensen, M. G.; Jensen, Søren Holdt

2006-01-01

A method for amplitude modulated sinusoidal audio coding is presented that has low complexity and low delay. This is based on a subband processing system, where, in each subband, the signal is modeled as an amplitude modulated sum of sinusoids. The envelopes are estimated using frequency......-domain linear prediction and the prediction coefficients are quantized. As a proof of concept, we evaluate different configurations in a subjective listening test, and this shows that the proposed method offers significant improvements in sinusoidal coding. Furthermore, the properties of the frequency...

Comparing human-Salmonella with plant-Salmonella protein-protein interaction predictions

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Sylvia eSchleker

2015-01-01

Full Text Available Salmonellosis is the most frequent food-borne disease world-wide and can be transmitted to humans by a variety of routes, especially via animal and plant products. Salmonella bacteria are believed to use not only animal and human but also plant hosts despite their evolutionary distance. This raises the question if Salmonella employs similar mechanisms in infection of these diverse hosts. Given that most of our understanding comes from its interaction with human hosts, we investigate here to what degree knowledge of Salmonella-human interactions can be transferred to the Salmonella-plant system. Reviewed are recent publications on analysis and prediction of Salmonella-host interactomes. Putative protein-protein interactions (PPIs between Salmonella and its human and Arabidopsis hosts were retrieved utilizing purely interolog-based approaches in which predictions were inferred based on available sequence and domain information of known PPIs, and machine learning approaches that integrate a larger set of useful information from different sources. Transfer learning is an especially suitable machine learning technique to predict plant host targets from the knowledge of human host targets. A comparison of the prediction results with transcriptomic data shows a clear overlap between the host proteins predicted to be targeted by PPIs and their gene ontology enrichment in both host species and regulation of gene expression. In particular, the cellular processes Salmonella interferes with in plants and humans are catabolic processes. The details of how these processes are targeted, however, are quite different between the two organisms, as expected based on their evolutionary and habitat differences. Possible implications of this observation on evolution of host-pathogen communication are discussed.

Toxoplasmosis and Polygenic Disease Susceptibility Genes: Extensive Toxoplasma gondii Host/Pathogen Interactome Enrichment in Nine Psychiatric or Neurological Disorders

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C. J. Carter

2013-01-01

Full Text Available Toxoplasma gondii is not only implicated in schizophrenia and related disorders, but also in Alzheimer's or Parkinson's disease, cancer, cardiac myopathies, and autoimmune disorders. During its life cycle, the pathogen interacts with ~3000 host genes or proteins. Susceptibility genes for multiple sclerosis, Alzheimer's disease, schizophrenia, bipolar disorder, depression, childhood obesity, Parkinson's disease, attention deficit hyperactivity disorder (multiple sclerosis, and autism (, but not anorexia or chronic fatigue are highly enriched in the human arm of this interactome and 18 (ADHD to 33% (MS of the susceptibility genes relate to it. The signalling pathways involved in the susceptibility gene/interactome overlaps are relatively specific and relevant to each disease suggesting a means whereby susceptibility genes could orient the attentions of a single pathogen towards disruption of the specific pathways that together contribute (positively or negatively to the endophenotypes of different diseases. Conditional protein knockdown, orchestrated by T. gondii proteins or antibodies binding to those of the host (pathogen derived autoimmunity and metabolite exchange, may contribute to this disruption. Susceptibility genes may thus be related to the causes and influencers of disease, rather than (and as well as to the disease itself.

DIMA 3.0: Domain Interaction Map.

Science.gov (United States)

Luo, Qibin; Pagel, Philipp; Vilne, Baiba; Frishman, Dmitrij

2011-01-01

Domain Interaction MAp (DIMA, available at http://webclu.bio.wzw.tum.de/dima) is a database of predicted and known interactions between protein domains. It integrates 5807 structurally known interactions imported from the iPfam and 3did databases and 46,900 domain interactions predicted by four computational methods: domain phylogenetic profiling, domain pair exclusion algorithm correlated mutations and domain interaction prediction in a discriminative way. Additionally predictions are filtered to exclude those domain pairs that are reported as non-interacting by the Negatome database. The DIMA Web site allows to calculate domain interaction networks either for a domain of interest or for entire organisms, and to explore them interactively using the Flash-based Cytoscape Web software.

Prediction of Cancer Proteins by Integrating Protein Interaction, Domain Frequency, and Domain Interaction Data Using Machine Learning Algorithms

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Chien-Hung Huang

2015-01-01

Full Text Available Many proteins are known to be associated with cancer diseases. It is quite often that their precise functional role in disease pathogenesis remains unclear. A strategy to gain a better understanding of the function of these proteins is to make use of a combination of different aspects of proteomics data types. In this study, we extended Aragues’s method by employing the protein-protein interaction (PPI data, domain-domain interaction (DDI data, weighted domain frequency score (DFS, and cancer linker degree (CLD data to predict cancer proteins. Performances were benchmarked based on three kinds of experiments as follows: (I using individual algorithm, (II combining algorithms, and (III combining the same classification types of algorithms. When compared with Aragues’s method, our proposed methods, that is, machine learning algorithm and voting with the majority, are significantly superior in all seven performance measures. We demonstrated the accuracy of the proposed method on two independent datasets. The best algorithm can achieve a hit ratio of 89.4% and 72.8% for lung cancer dataset and lung cancer microarray study, respectively. It is anticipated that the current research could help understand disease mechanisms and diagnosis.

Topology and weights in a protein domain interaction network--a novel way to predict protein interactions.

Science.gov (United States)

Wuchty, Stefan

2006-05-23

While the analysis of unweighted biological webs as diverse as genetic, protein and metabolic networks allowed spectacular insights in the inner workings of a cell, biological networks are not only determined by their static grid of links. In fact, we expect that the heterogeneity in the utilization of connections has a major impact on the organization of cellular activities as well. We consider a web of interactions between protein domains of the Protein Family database (PFAM), which are weighted by a probability score. We apply metrics that combine the static layout and the weights of the underlying interactions. We observe that unweighted measures as well as their weighted counterparts largely share the same trends in the underlying domain interaction network. However, we only find weak signals that weights and the static grid of interactions are connected entities. Therefore assuming that a protein interaction is governed by a single domain interaction, we observe strong and significant correlations of the highest scoring domain interaction and the confidence of protein interactions in the underlying interactions of yeast and fly. Modeling an interaction between proteins if we find a high scoring protein domain interaction we obtain 1, 428 protein interactions among 361 proteins in the human malaria parasite Plasmodium falciparum. Assessing their quality by a logistic regression method we observe that increasing confidence of predicted interactions is accompanied by high scoring domain interactions and elevated levels of functional similarity and evolutionary conservation. Our results indicate that probability scores are randomly distributed, allowing to treat static grid and weights of domain interactions as separate entities. In particular, these finding confirms earlier observations that a protein interaction is a matter of a single interaction event on domain level. As an immediate application, we show a simple way to predict potential protein interactions

Crystal complexes of a predicted S-adenosylmethionine-dependent methyltransferase reveal a typical AdoMet binding domain and a substrate recognition domain

Energy Technology Data Exchange (ETDEWEB)

Miller, D.J.; Ouellette, N.; Evodokimova, E.; Savchenko, A.; Edwards, A.; Anderson, W.F. (Toronto); (NWU)

2010-03-08

S-adenosyl-L-methionine-dependent methyltransferases (MTs) are abundant, and highly conserved across phylogeny. These enzymes use the cofactor AdoMet to methylate a wide variety of molecular targets, thereby modulating important cellular and metabolic activities. Thermotoga maritima protein 0872 (TM0872) belongs to a large sequence family of predicted MTs, ranging phylogenetically from relatively simple bacteria to humans. The genes for many of the bacterial homologs are located within operons involved in cell wall synthesis and cell division. Despite preliminary biochemical studies in E. coli and B. subtilis, the substrate specificity of this group of more than 150 proteins is unknown. As part of the Midwest Center for Structural Genomics initiative (www.mcsg.anl.gov), we have determined the structure of TM0872 in complexes with AdoMet and with S-adenosyl-L-homocysteine (AdoHcy). As predicted, TM0872 has a typical MT domain, and binds endogenous AdoMet, or co-crystallized AdoHcy, in a manner consistent with other known MT structures. In addition, TM0872 has a second domain that is novel among MTs in both its location in the sequence and its structure. The second domain likely acts in substrate recognition and binding, and there is a potential substrate-binding cleft spanning the two domains. This long and narrow cleft is lined with positively charged residues which are located opposite the S{sup +}-CH{sub 3} bond, suggesting that a negatively charged molecule might be targeted for catalysis. However, AdoMet and AdoHcy are both buried, and access to the methyl group would presumably require structural rearrangement. These TM0872 crystal structures offer the first structural glimpses at this phylogenetically conserved sequence family.

PRGPred: A platform for prediction of domains of resistance gene analogue (RGA in Arecaceae developed using machine learning algorithms

Directory of Open Access Journals (Sweden)

MATHODIYIL S. MANJULA

2015-12-01

Full Text Available Plant disease resistance genes (R-genes are responsible for initiation of defense mechanism against various phytopathogens. The majority of plant R-genes are members of very large multi-gene families, which encode structurally related proteins containing nucleotide binding site domains (NBS and C-terminal leucine rich repeats (LRR. Other classes possess' an extracellular LRR domain, a transmembrane domain and sometimes, an intracellular serine/threonine kinase domain. R-proteins work in pathogen perception and/or the activation of conserved defense signaling networks. In the present study, sequences representing resistance gene analogues (RGAs of coconut, arecanut, oil palm and date palm were collected from NCBI, sorted based on domains and assembled into a database. The sequences were analyzed in PRINTS database to find out the conserved domains and their motifs present in the RGAs. Based on these domains, we have also developed a tool to predict the domains of palm R-genes using various machine learning algorithms. The model files were selected based on the performance of the best classifier in training and testing. All these information is stored and made available in the online ‘PRGpred' database and prediction tool.

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

Directory of Open Access Journals (Sweden)

Amin R Mazloom

2011-12-01

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

Interactome analyses identify ties of PrP and its mammalian paralogs to oligomannosidic N-glycans and endoplasmic reticulum-derived chaperones.

Directory of Open Access Journals (Sweden)

Joel C Watts

2009-10-01

Full Text Available The physiological environment which hosts the conformational conversion of the cellular prion protein (PrP(C to disease-associated isoforms has remained enigmatic. A quantitative investigation of the PrP(C interactome was conducted in a cell culture model permissive to prion replication. To facilitate recognition of relevant interactors, the study was extended to Doppel (Prnd and Shadoo (Sprn, two mammalian PrP(C paralogs. Interestingly, this work not only established a similar physiological environment for the three prion protein family members in neuroblastoma cells, but also suggested direct interactions amongst them. Furthermore, multiple interactions between PrP(C and the neural cell adhesion molecule, the laminin receptor precursor, Na/K ATPases and protein disulfide isomerases (PDI were confirmed, thereby reconciling previously separate findings. Subsequent validation experiments established that interactions of PrP(C with PDIs may extend beyond the endoplasmic reticulum and may play a hitherto unrecognized role in the accumulation of PrP(Sc. A simple hypothesis is presented which accounts for the majority of interactions observed in uninfected cells and suggests that PrP(C organizes its molecular environment on account of its ability to bind to adhesion molecules harboring immunoglobulin-like domains, which in turn recognize oligomannose-bearing membrane proteins.

Interactome analyses identify ties of PrP and its mammalian paralogs to oligomannosidic N-glycans and endoplasmic reticulum-derived chaperones.

Science.gov (United States)

Watts, Joel C; Huo, Hairu; Bai, Yu; Ehsani, Sepehr; Jeon, Amy Hye Won; Won, Amy Hye; Shi, Tujin; Daude, Nathalie; Lau, Agnes; Young, Rebecca; Xu, Lei; Carlson, George A; Williams, David; Westaway, David; Schmitt-Ulms, Gerold

2009-10-01

The physiological environment which hosts the conformational conversion of the cellular prion protein (PrP(C)) to disease-associated isoforms has remained enigmatic. A quantitative investigation of the PrP(C) interactome was conducted in a cell culture model permissive to prion replication. To facilitate recognition of relevant interactors, the study was extended to Doppel (Prnd) and Shadoo (Sprn), two mammalian PrP(C) paralogs. Interestingly, this work not only established a similar physiological environment for the three prion protein family members in neuroblastoma cells, but also suggested direct interactions amongst them. Furthermore, multiple interactions between PrP(C) and the neural cell adhesion molecule, the laminin receptor precursor, Na/K ATPases and protein disulfide isomerases (PDI) were confirmed, thereby reconciling previously separate findings. Subsequent validation experiments established that interactions of PrP(C) with PDIs may extend beyond the endoplasmic reticulum and may play a hitherto unrecognized role in the accumulation of PrP(Sc). A simple hypothesis is presented which accounts for the majority of interactions observed in uninfected cells and suggests that PrP(C) organizes its molecular environment on account of its ability to bind to adhesion molecules harboring immunoglobulin-like domains, which in turn recognize oligomannose-bearing membrane proteins.

Theoretical predictions for pp and panti p elastic scattering in the TeV energy domain

International Nuclear Information System (INIS)

Bourrely, C.; Martin, A.

1984-01-01

We present theoretical predictions on total cross-sections and elastic scattering in the TeV energy domain obtained from the present experimental situation at the ISR and the panti p Collider. (orig.)

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

Science.gov (United States)

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

2018-02-22

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

Topology and weights in a protein domain interaction network – a novel way to predict protein interactions

Directory of Open Access Journals (Sweden)

Wuchty Stefan

2006-05-01

Full Text Available Abstract Background While the analysis of unweighted biological webs as diverse as genetic, protein and metabolic networks allowed spectacular insights in the inner workings of a cell, biological networks are not only determined by their static grid of links. In fact, we expect that the heterogeneity in the utilization of connections has a major impact on the organization of cellular activities as well. Results We consider a web of interactions between protein domains of the Protein Family database (PFAM, which are weighted by a probability score. We apply metrics that combine the static layout and the weights of the underlying interactions. We observe that unweighted measures as well as their weighted counterparts largely share the same trends in the underlying domain interaction network. However, we only find weak signals that weights and the static grid of interactions are connected entities. Therefore assuming that a protein interaction is governed by a single domain interaction, we observe strong and significant correlations of the highest scoring domain interaction and the confidence of protein interactions in the underlying interactions of yeast and fly. Modeling an interaction between proteins if we find a high scoring protein domain interaction we obtain 1, 428 protein interactions among 361 proteins in the human malaria parasite Plasmodium falciparum. Assessing their quality by a logistic regression method we observe that increasing confidence of predicted interactions is accompanied by high scoring domain interactions and elevated levels of functional similarity and evolutionary conservation. Conclusion Our results indicate that probability scores are randomly distributed, allowing to treat static grid and weights of domain interactions as separate entities. In particular, these finding confirms earlier observations that a protein interaction is a matter of a single interaction event on domain level. As an immediate application, we

A graph kernel approach for alignment-free domain–peptide interaction prediction with an application to human SH3 domains

Science.gov (United States)

Kundu, Kousik; Costa, Fabrizio; Backofen, Rolf

2013-01-01

Motivation: State-of-the-art experimental data for determining binding specificities of peptide recognition modules (PRMs) is obtained by high-throughput approaches like peptide arrays. Most prediction tools applicable to this kind of data are based on an initial multiple alignment of the peptide ligands. Building an initial alignment can be error-prone, especially in the case of the proline-rich peptides bound by the SH3 domains. Results: Here, we present a machine-learning approach based on an efficient graph-kernel technique to predict the specificity of a large set of 70 human SH3 domains, which are an important class of PRMs. The graph-kernel strategy allows us to (i) integrate several types of physico-chemical information for each amino acid, (ii) consider high-order correlations between these features and (iii) eliminate the need for an initial peptide alignment. We build specialized models for each human SH3 domain and achieve competitive predictive performance of 0.73 area under precision-recall curve, compared with 0.27 area under precision-recall curve for state-of-the-art methods based on position weight matrices. We show that better models can be obtained when we use information on the noninteracting peptides (negative examples), which is currently not used by the state-of-the art approaches based on position weight matrices. To this end, we analyze two strategies to identify subsets of high confidence negative data. The techniques introduced here are more general and hence can also be used for any other protein domains, which interact with short peptides (i.e. other PRMs). Availability: The program with the predictive models can be found at http://www.bioinf.uni-freiburg.de/Software/SH3PepInt/SH3PepInt.tar.gz. We also provide a genome-wide prediction for all 70 human SH3 domains, which can be found under http://www.bioinf.uni-freiburg.de/Software/SH3PepInt/Genome-Wide-Predictions.tar.gz. Contact: backofen@informatik.uni-freiburg.de Supplementary

Deep sequencing of cardiac microRNA-mRNA interactomes in clinical and experimental cardiomyopathy.

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Matkovich, Scot J; Dorn, Gerald W

2015-01-01

MicroRNAs are a family of short (~21 nucleotide) noncoding RNAs that serve key roles in cellular growth and differentiation and the response of the heart to stress stimuli. As the sequence-specific recognition element of RNA-induced silencing complexes (RISCs), microRNAs bind mRNAs and prevent their translation via mechanisms that may include transcript degradation and/or prevention of ribosome binding. Short microRNA sequences and the ability of microRNAs to bind to mRNA sites having only partial/imperfect sequence complementarity complicate purely computational analyses of microRNA-mRNA interactomes. Furthermore, computational microRNA target prediction programs typically ignore biological context, and therefore the principal determinants of microRNA-mRNA binding: the presence and quantity of each. To address these deficiencies we describe an empirical method, developed via studies of stressed and failing hearts, to determine disease-induced changes in microRNAs, mRNAs, and the mRNAs targeted to the RISC, without cross-linking mRNAs to RISC proteins. Deep sequencing methods are used to determine RNA abundances, delivering unbiased, quantitative RNA data limited only by their annotation in the genome of interest. We describe the laboratory bench steps required to perform these experiments, experimental design strategies to achieve an appropriate number of sequencing reads per biological replicate, and computer-based processing tools and procedures to convert large raw sequencing data files into gene expression measures useful for differential expression analyses.

Web-page Prediction for Domain Specific Web-search using Boolean Bit Mask

OpenAIRE

Sinha, Sukanta; Duttagupta, Rana; Mukhopadhyay, Debajyoti

2012-01-01

Search Engine is a Web-page retrieval tool. Nowadays Web searchers utilize their time using an efficient search engine. To improve the performance of the search engine, we are introducing a unique mechanism which will give Web searchers more prominent search results. In this paper, we are going to discuss a domain specific Web search prototype which will generate the predicted Web-page list for user given search string using Boolean bit mask.

Proteomic Analysis of the Mediator Complex Interactome in Saccharomyces cerevisiae.

Science.gov (United States)

Uthe, Henriette; Vanselow, Jens T; Schlosser, Andreas

2017-02-27

Here we present the most comprehensive analysis of the yeast Mediator complex interactome to date. Particularly gentle cell lysis and co-immunopurification conditions allowed us to preserve even transient protein-protein interactions and to comprehensively probe the molecular environment of the Mediator complex in the cell. Metabolic 15 N-labeling thereby enabled stringent discrimination between bona fide interaction partners and nonspecifically captured proteins. Our data indicates a functional role for Mediator beyond transcription initiation. We identified a large number of Mediator-interacting proteins and protein complexes, such as RNA polymerase II, general transcription factors, a large number of transcriptional activators, the SAGA complex, chromatin remodeling complexes, histone chaperones, highly acetylated histones, as well as proteins playing a role in co-transcriptional processes, such as splicing, mRNA decapping and mRNA decay. Moreover, our data provides clear evidence, that the Mediator complex interacts not only with RNA polymerase II, but also with RNA polymerases I and III, and indicates a functional role of the Mediator complex in rRNA processing and ribosome biogenesis.

Two Predicted Transmembrane Domains Exclude Very Long Chain Fatty acyl-CoAs from the Active Site of Mouse Wax Synthase.

Directory of Open Access Journals (Sweden)

Steffen Kawelke

Full Text Available Wax esters are used as coatings or storage lipids in all kingdoms of life. They are synthesized from a fatty alcohol and an acyl-CoA by wax synthases. In order to get insights into the structure-function relationships of a wax synthase from Mus musculus, a domain swap experiment between the mouse acyl-CoA:wax alcohol acyltransferase (AWAT2 and the homologous mouse acyl-CoA:diacylglycerol O-acyltransferase 2 (DGAT2 was performed. This showed that the substrate specificity of AWAT2 is partially determined by two predicted transmembrane domains near the amino terminus of AWAT2. Upon exchange of the two domains for the respective part of DGAT2, the resulting chimeric enzyme was capable of incorporating up to 20% of very long acyl chains in the wax esters upon expression in S. cerevisiae strain H1246. The amount of very long acyl chains in wax esters synthesized by wild type AWAT2 was negligible. The effect was narrowed down to a single amino acid position within one of the predicted membrane domains, the AWAT2 N36R variant. Taken together, we provide first evidence that two predicted transmembrane domains in AWAT2 are involved in determining its acyl chain length specificity.

An Experimental Evaluation of Competing Age-Predictions of Future Time Perspective between Workplace and Retirement Domains.

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Kerry, Matthew J; Embretson, Susan E

2017-01-01

Future time perspective (FTP) is defined as "perceptions of the future as being limited or open-ended" (Lang and Carstensen, 2002; p. 125). The construct figures prominently in both workplace and retirement domains, but the age-predictions are competing: Workplace research predicts decreasing FTP age-change, in contrast, retirement scholars predict increasing FTP age-change. For the first time, these competing predictions are pitted in an experimental manipulation of subjective life expectancy (SLE). A sample of N = 207 older adults (age 45-60) working full-time (>30-h/week) were randomly assigned to SLE questions framed as either 'Live-to' or 'Die-by' to evaluate competing predictions for FTP. Results indicate general support for decreasing age-change in FTP, indicated by independent-sample t -tests showing lower FTP in the 'Die-by' framing condition. Further general-linear model analyses were conducted to test for interaction effects of retirement planning with experimental framings on FTP and intended retirement; While retirement planning buffered FTP's decrease, simple-effects also revealed that retirement planning increased intentions for sooner retirement, but lack of planning increased intentions for later retirement. Discussion centers on practical implications of our findings and consequences validity evidence in future empirical research of FTP in both workplace and retirement domains.

Protein domain analysis of genomic sequence data reveals regulation of LRR related domains in plant transpiration in Ficus.

Science.gov (United States)

Lang, Tiange; Yin, Kangquan; Liu, Jinyu; Cao, Kunfang; Cannon, Charles H; Du, Fang K

2014-01-01

Predicting protein domains is essential for understanding a protein's function at the molecular level. However, up till now, there has been no direct and straightforward method for predicting protein domains in species without a reference genome sequence. In this study, we developed a functionality with a set of programs that can predict protein domains directly from genomic sequence data without a reference genome. Using whole genome sequence data, the programming functionality mainly comprised DNA assembly in combination with next-generation sequencing (NGS) assembly methods and traditional methods, peptide prediction and protein domain prediction. The proposed new functionality avoids problems associated with de novo assembly due to micro reads and small single repeats. Furthermore, we applied our functionality for the prediction of leucine rich repeat (LRR) domains in four species of Ficus with no reference genome, based on NGS genomic data. We found that the LRRNT_2 and LRR_8 domains are related to plant transpiration efficiency, as indicated by the stomata index, in the four species of Ficus. The programming functionality established in this study provides new insights for protein domain prediction, which is particularly timely in the current age of NGS data expansion.

Selective Targeting of SH2 Domain-Phosphotyrosine Interactions of Src Family Tyrosine Kinases with Monobodies.

Science.gov (United States)

Kükenshöner, Tim; Schmit, Nadine Eliane; Bouda, Emilie; Sha, Fern; Pojer, Florence; Koide, Akiko; Seeliger, Markus; Koide, Shohei; Hantschel, Oliver

2017-05-05

The binding of Src-homology 2 (SH2) domains to phosphotyrosine (pY) sites is critical for the autoinhibition and substrate recognition of the eight Src family kinases (SFKs). The high sequence conservation of the 120 human SH2 domains poses a significant challenge to selectively perturb the interactions of even the SFK SH2 family against the rest of the SH2 domains. We have developed synthetic binding proteins, termed monobodies, for six of the SFK SH2 domains with nanomolar affinity. Most of these monobodies competed with pY ligand binding and showed strong selectivity for either the SrcA (Yes, Src, Fyn, Fgr) or SrcB subgroup (Lck, Lyn, Blk, Hck). Interactome analysis of intracellularly expressed monobodies revealed that they bind SFKs but no other SH2-containing proteins. Three crystal structures of monobody-SH2 complexes unveiled different and only partly overlapping binding modes, which rationalized the observed selectivity and enabled structure-based mutagenesis to modulate inhibition mode and selectivity. In line with the critical roles of SFK SH2 domains in kinase autoinhibition and T-cell receptor signaling, monobodies binding the Src and Hck SH2 domains selectively activated respective recombinant kinases, whereas an Lck SH2-binding monobody inhibited proximal signaling events downstream of the T-cell receptor complex. Our results show that SFK SH2 domains can be targeted with unprecedented potency and selectivity using monobodies. They are excellent tools for dissecting SFK functions in normal development and signaling and to interfere with aberrant SFK signaling networks in cancer cells. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Comprehensively Characterizing the Thioredoxin Interactome In Vivo Highlights the Central Role Played by This Ubiquitous Oxidoreductase in Redox Control*

Science.gov (United States)

Arts, Isabelle S.; Vertommen, Didier; Baldin, Francesca; Laloux, Géraldine; Collet, Jean-François

2016-01-01

Thioredoxin (Trx) is a ubiquitous oxidoreductase maintaining protein-bound cysteine residues in the reduced thiol state. Here, we combined a well-established method to trap Trx substrates with the power of bacterial genetics to comprehensively characterize the in vivo Trx redox interactome in the model bacterium Escherichia coli. Using strains engineered to optimize trapping, we report the identification of a total 268 Trx substrates, including 201 that had never been reported to depend on Trx for reduction. The newly identified Trx substrates are involved in a variety of cellular processes, ranging from energy metabolism to amino acid synthesis and transcription. The interaction between Trx and two of its newly identified substrates, a protein required for the import of most carbohydrates, PtsI, and the bacterial actin homolog MreB was studied in detail. We provide direct evidence that PtsI and MreB contain cysteine residues that are susceptible to oxidation and that participate in the formation of an intermolecular disulfide with Trx. By considerably expanding the number of Trx targets, our work highlights the role played by this major oxidoreductase in a variety of cellular processes. Moreover, as the dependence on Trx for reduction is often conserved across species, it also provides insightful information on the interactome of Trx in organisms other than E. coli. PMID:27081212

Exploitation of complex network topology for link prediction in biological interactomes

KAUST Repository

Alanis Lobato, Gregorio

2014-01-01

In this work, we propose three novel and powerful approaches for the prediction of interactions in biological networks and conclude that it is possible to mine the topology of these complex system representations and produce reliable

Systematic differences in signal emitting and receiving revealed by PageRank analysis of a human protein interactome.

Directory of Open Access Journals (Sweden)

Donglei Du

Full Text Available Most protein PageRank studies do not use signal flow direction information in protein interactions because this information was not readily available in large protein databases until recently. Therefore, four questions have yet to be answered: A What is the general difference between signal emitting and receiving in a protein interactome? B Which proteins are among the top ranked in directional ranking? C Are high ranked proteins more evolutionarily conserved than low ranked ones? D Do proteins with similar ranking tend to have similar subcellular locations? In this study, we address these questions using the forward, reverse, and non-directional PageRank approaches to rank an information-directional network of human proteins and study their evolutionary conservation. The forward ranking gives credit to information receivers, reverse ranking to information emitters, and non-directional ranking mainly to the number of interactions. The protein lists generated by the forward and non-directional rankings are highly correlated, but those by the reverse and non-directional rankings are not. The results suggest that the signal emitting/receiving system is characterized by key-emittings and relatively even receivings in the human protein interactome. Signaling pathway proteins are frequent in top ranked ones. Eight proteins are both informational top emitters and top receivers. Top ranked proteins, except a few species-related novel-function ones, are evolutionarily well conserved. Protein-subunit ranking position reflects subunit function. These results demonstrate the usefulness of different PageRank approaches in characterizing protein networks and provide insights to protein interaction in the cell.

Systematic differences in signal emitting and receiving revealed by PageRank analysis of a human protein interactome.

Science.gov (United States)

Du, Donglei; Lee, Connie F; Li, Xiu-Qing

2012-01-01

Most protein PageRank studies do not use signal flow direction information in protein interactions because this information was not readily available in large protein databases until recently. Therefore, four questions have yet to be answered: A) What is the general difference between signal emitting and receiving in a protein interactome? B) Which proteins are among the top ranked in directional ranking? C) Are high ranked proteins more evolutionarily conserved than low ranked ones? D) Do proteins with similar ranking tend to have similar subcellular locations? In this study, we address these questions using the forward, reverse, and non-directional PageRank approaches to rank an information-directional network of human proteins and study their evolutionary conservation. The forward ranking gives credit to information receivers, reverse ranking to information emitters, and non-directional ranking mainly to the number of interactions. The protein lists generated by the forward and non-directional rankings are highly correlated, but those by the reverse and non-directional rankings are not. The results suggest that the signal emitting/receiving system is characterized by key-emittings and relatively even receivings in the human protein interactome. Signaling pathway proteins are frequent in top ranked ones. Eight proteins are both informational top emitters and top receivers. Top ranked proteins, except a few species-related novel-function ones, are evolutionarily well conserved. Protein-subunit ranking position reflects subunit function. These results demonstrate the usefulness of different PageRank approaches in characterizing protein networks and provide insights to protein interaction in the cell.

HER family kinase domain mutations promote tumor progression and can predict response to treatment in human breast cancer

KAUST Repository

Boulbes, Delphine R.; Arold, Stefan T.; Chauhan, Gaurav B.; Blachno, Korina V.; Deng, Nanfu; Chang, Wei-Chao; Jin, Quanri; Huang, Tzu-Hsuan; Hsu, Jung-Mao; Brady, Samuel W.; Bartholomeusz, Chandra; Ladbury, John E.; Stone, Steve; Yu, Dihua; Hung, Mien-Chie; Esteva, Francisco J.

2014-01-01

Resistance to HER2-targeted therapies remains a major obstacle in the treatment of HER2-overexpressing breast cancer. Understanding the molecular pathways that contribute to the development of drug resistance is needed to improve the clinical utility of novel agents, and to predict the success of targeted personalized therapy based on tumor-specific mutations. Little is known about the clinical significance of HER family mutations in breast cancer. Because mutations within HER1/EGFR are predictive of response to tyrosine kinase inhibitors (TKI) in lung cancer, we investigated whether mutations in HER family kinase domains are predictive of response to targeted therapy in HER2-overexpressing breast cancer. We sequenced the HER family kinase domains from 76 HER2-overexpressing invasive carcinomas and identified 12 missense variants. Patients whose tumors carried any of these mutations did not respond to HER2 directed therapy in the metastatic setting. We developed mutant cell lines and used structural analyses to determine whether changes in protein conformation could explain the lack of response to therapy. We also functionally studied all HER2 mutants and showed that they conferred an aggressive phenotype and altered effects of the TKI lapatinib. Our data demonstrate that mutations in the finely tuned HER kinase domains play a critical function in breast cancer progression and may serve as prognostic and predictive markers.

HER family kinase domain mutations promote tumor progression and can predict response to treatment in human breast cancer

KAUST Repository

Boulbes, Delphine R.

2014-11-11

Resistance to HER2-targeted therapies remains a major obstacle in the treatment of HER2-overexpressing breast cancer. Understanding the molecular pathways that contribute to the development of drug resistance is needed to improve the clinical utility of novel agents, and to predict the success of targeted personalized therapy based on tumor-specific mutations. Little is known about the clinical significance of HER family mutations in breast cancer. Because mutations within HER1/EGFR are predictive of response to tyrosine kinase inhibitors (TKI) in lung cancer, we investigated whether mutations in HER family kinase domains are predictive of response to targeted therapy in HER2-overexpressing breast cancer. We sequenced the HER family kinase domains from 76 HER2-overexpressing invasive carcinomas and identified 12 missense variants. Patients whose tumors carried any of these mutations did not respond to HER2 directed therapy in the metastatic setting. We developed mutant cell lines and used structural analyses to determine whether changes in protein conformation could explain the lack of response to therapy. We also functionally studied all HER2 mutants and showed that they conferred an aggressive phenotype and altered effects of the TKI lapatinib. Our data demonstrate that mutations in the finely tuned HER kinase domains play a critical function in breast cancer progression and may serve as prognostic and predictive markers.

Using context to improve protein domain identification

Directory of Open Access Journals (Sweden)

Llinás Manuel

2011-03-01

Full Text Available Abstract Background Identifying domains in protein sequences is an important step in protein structural and functional annotation. Existing domain recognition methods typically evaluate each domain prediction independently of the rest. However, the majority of proteins are multidomain, and pairwise domain co-occurrences are highly specific and non-transitive. Results Here, we demonstrate how to exploit domain co-occurrence to boost weak domain predictions that appear in previously observed combinations, while penalizing higher confidence domains if such combinations have never been observed. Our framework, Domain Prediction Using Context (dPUC, incorporates pairwise "context" scores between domains, along with traditional domain scores and thresholds, and improves domain prediction across a variety of organisms from bacteria to protozoa and metazoa. Among the genomes we tested, dPUC is most successful at improving predictions for the poorly-annotated malaria parasite Plasmodium falciparum, for which over 38% of the genome is currently unannotated. Our approach enables high-confidence annotations in this organism and the identification of orthologs to many core machinery proteins conserved in all eukaryotes, including those involved in ribosomal assembly and other RNA processing events, which surprisingly had not been previously known. Conclusions Overall, our results demonstrate that this new context-based approach will provide significant improvements in domain and function prediction, especially for poorly understood genomes for which the need for additional annotations is greatest. Source code for the algorithm is available under a GPL open source license at http://compbio.cs.princeton.edu/dpuc/. Pre-computed results for our test organisms and a web server are also available at that location.

Accumulating Data to Optimally Predict Obesity Treatment (ADOPT) Core Measures: Behavioral Domain.

Science.gov (United States)

Lytle, Leslie A; Nicastro, Holly L; Roberts, Susan B; Evans, Mary; Jakicic, John M; Laposky, Aaron D; Loria, Catherine M

2018-04-01

The ability to identify and measure behaviors that are related to weight loss and the prevention of weight regain is crucial to understanding the variability in response to obesity treatment and the development of tailored treatments. The overarching goal of the Accumulating Data to Optimally Predict obesity Treatment (ADOPT) Core Measures Project is to provide obesity researchers with guidance on a set of constructs and measures that are related to weight control and that span and integrate obesity-related behavioral, biological, environmental, and psychosocial domains. This article describes how the behavioral domain subgroup identified the initial list of high-priority constructs and measures to be included, and it describes practical considerations for assessing the following four behavioral areas: eating, activity, sleep, and self-monitoring of weight. Challenges and considerations for advancing the science related to weight loss and maintenance behaviors are also discussed. Assessing a set of core behavioral measures in combination with those from other ADOPT domains is critical to improve our understanding of individual variability in response to adult obesity treatment. The selection of behavioral measures is based on the current science, although there continues to be much work needed in this field. © 2018 The Obesity Society.

Predicting the multi-domain progression of Parkinson's disease: a Bayesian multivariate generalized linear mixed-effect model.

Science.gov (United States)

Wang, Ming; Li, Zheng; Lee, Eun Young; Lewis, Mechelle M; Zhang, Lijun; Sterling, Nicholas W; Wagner, Daymond; Eslinger, Paul; Du, Guangwei; Huang, Xuemei

2017-09-25

It is challenging for current statistical models to predict clinical progression of Parkinson's disease (PD) because of the involvement of multi-domains and longitudinal data. Past univariate longitudinal or multivariate analyses from cross-sectional trials have limited power to predict individual outcomes or a single moment. The multivariate generalized linear mixed-effect model (GLMM) under the Bayesian framework was proposed to study multi-domain longitudinal outcomes obtained at baseline, 18-, and 36-month. The outcomes included motor, non-motor, and postural instability scores from the MDS-UPDRS, and demographic and standardized clinical data were utilized as covariates. The dynamic prediction was performed for both internal and external subjects using the samples from the posterior distributions of the parameter estimates and random effects, and also the predictive accuracy was evaluated based on the root of mean square error (RMSE), absolute bias (AB) and the area under the receiver operating characteristic (ROC) curve. First, our prediction model identified clinical data that were differentially associated with motor, non-motor, and postural stability scores. Second, the predictive accuracy of our model for the training data was assessed, and improved prediction was gained in particularly for non-motor (RMSE and AB: 2.89 and 2.20) compared to univariate analysis (RMSE and AB: 3.04 and 2.35). Third, the individual-level predictions of longitudinal trajectories for the testing data were performed, with ~80% observed values falling within the 95% credible intervals. Multivariate general mixed models hold promise to predict clinical progression of individual outcomes in PD. The data was obtained from Dr. Xuemei Huang's NIH grant R01 NS060722 , part of NINDS PD Biomarker Program (PDBP). All data was entered within 24 h of collection to the Data Management Repository (DMR), which is publically available ( https://pdbp.ninds.nih.gov/data-management ).

Frontotemporal dysregulation of the SNARE protein interactome is associated with faster cognitive decline in old age.

Science.gov (United States)

Ramos-Miguel, Alfredo; Jones, Andrea A; Sawada, Ken; Barr, Alasdair M; Bayer, Thomas A; Falkai, Peter; Leurgans, Sue E; Schneider, Julie A; Bennett, David A; Honer, William G

2018-06-01

The molecular underpinnings associated with cognitive reserve remain poorly understood. Because animal models fail to fully recapitulate the complexity of human brain aging, postmortem studies from well-designed cohorts are crucial to unmask mechanisms conferring cognitive resistance against cumulative neuropathologies. We tested the hypothesis that functionality of the SNARE protein interactome might be an important resilience factor preserving cognitive abilities in old age. Cognition was assessed annually in participants from the Rush "Memory and Aging Project" (MAP), a community-dwelling cohort representative of the overall aging population. Associations between cognition and postmortem neurochemical data were evaluated in functional assays quantifying various species of the SNARE (soluble N-ethylmaleimide-sensitive factor attachment protein receptor) machinery in samples from the inferior temporal (IT, n = 154) and middle-frontal (MF, n = 174) gyri. Using blue-native gel electrophoresis, we isolated and quantified several types of complexes containing the three SNARE proteins (syntaxin-1, SNAP25, VAMP), as well as the GABAergic/glutamatergic selectively expressed complexins-I/II (CPLX1/2), in brain tissue homogenates and reconstitution assays with recombinant proteins. Multivariate analyses revealed significant associations between IT and MF neurochemical data (SNARE proteins and/or complexes), and multiple age-related neuropathologies, as well as with multiple cognitive domains of MAP participants. Controlling for demographic variables, neuropathologic indices and total synapse density, we found that temporal 150-kDa SNARE species (representative of pan-synaptic functionality) and frontal CPLX1/CPLX2 ratio of 500-kDa heteromeric species (representative of inhibitory/excitatory input functionality) were, among all the immunocharacterized complexes, the strongest predictors of cognitive function nearest death. Interestingly, these two neurochemical

Prediction model of potential hepatocarcinogenicity of rat hepatocarcinogens using a large-scale toxicogenomics database

International Nuclear Information System (INIS)

Uehara, Takeki; Minowa, Yohsuke; Morikawa, Yuji; Kondo, Chiaki; Maruyama, Toshiyuki; Kato, Ikuo; Nakatsu, Noriyuki; Igarashi, Yoshinobu; Ono, Atsushi; Hayashi, Hitomi; Mitsumori, Kunitoshi; Yamada, Hiroshi; Ohno, Yasuo; Urushidani, Tetsuro

2011-01-01

The present study was performed to develop a robust gene-based prediction model for early assessment of potential hepatocarcinogenicity of chemicals in rats by using our toxicogenomics database, TG-GATEs (Genomics-Assisted Toxicity Evaluation System developed by the Toxicogenomics Project in Japan). The positive training set consisted of high- or middle-dose groups that received 6 different non-genotoxic hepatocarcinogens during a 28-day period. The negative training set consisted of high- or middle-dose groups of 54 non-carcinogens. Support vector machine combined with wrapper-type gene selection algorithms was used for modeling. Consequently, our best classifier yielded prediction accuracies for hepatocarcinogenicity of 99% sensitivity and 97% specificity in the training data set, and false positive prediction was almost completely eliminated. Pathway analysis of feature genes revealed that the mitogen-activated protein kinase p38- and phosphatidylinositol-3-kinase-centered interactome and the v-myc myelocytomatosis viral oncogene homolog-centered interactome were the 2 most significant networks. The usefulness and robustness of our predictor were further confirmed in an independent validation data set obtained from the public database. Interestingly, similar positive predictions were obtained in several genotoxic hepatocarcinogens as well as non-genotoxic hepatocarcinogens. These results indicate that the expression profiles of our newly selected candidate biomarker genes might be common characteristics in the early stage of carcinogenesis for both genotoxic and non-genotoxic carcinogens in the rat liver. Our toxicogenomic model might be useful for the prospective screening of hepatocarcinogenicity of compounds and prioritization of compounds for carcinogenicity testing. - Highlights: →We developed a toxicogenomic model to predict hepatocarcinogenicity of chemicals. →The optimized model consisting of 9 probes had 99% sensitivity and 97% specificity. �

Protein Sub-Nuclear Localization Prediction Using SVM and Pfam Domain Information

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Kumar, Ravindra; Jain, Sohni; Kumari, Bandana; Kumar, Manish

2014-01-01

The nucleus is the largest and the highly organized organelle of eukaryotic cells. Within nucleus exist a number of pseudo-compartments, which are not separated by any membrane, yet each of them contains only a specific set of proteins. Understanding protein sub-nuclear localization can hence be an important step towards understanding biological functions of the nucleus. Here we have described a method, SubNucPred developed by us for predicting the sub-nuclear localization of proteins. This method predicts protein localization for 10 different sub-nuclear locations sequentially by combining presence or absence of unique Pfam domain and amino acid composition based SVM model. The prediction accuracy during leave-one-out cross-validation for centromeric proteins was 85.05%, for chromosomal proteins 76.85%, for nuclear speckle proteins 81.27%, for nucleolar proteins 81.79%, for nuclear envelope proteins 79.37%, for nuclear matrix proteins 77.78%, for nucleoplasm proteins 76.98%, for nuclear pore complex proteins 88.89%, for PML body proteins 75.40% and for telomeric proteins it was 83.33%. Comparison with other reported methods showed that SubNucPred performs better than existing methods. A web-server for predicting protein sub-nuclear localization named SubNucPred has been established at http://14.139.227.92/mkumar/subnucpred/. Standalone version of SubNucPred can also be downloaded from the web-server. PMID:24897370

Domain fusion analysis by applying relational algebra to protein sequence and domain databases.

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Truong, Kevin; Ikura, Mitsuhiko

2003-05-06

Domain fusion analysis is a useful method to predict functionally linked proteins that may be involved in direct protein-protein interactions or in the same metabolic or signaling pathway. As separate domain databases like BLOCKS, PROSITE, Pfam, SMART, PRINTS-S, ProDom, TIGRFAMs, and amalgamated domain databases like InterPro continue to grow in size and quality, a computational method to perform domain fusion analysis that leverages on these efforts will become increasingly powerful. This paper proposes a computational method employing relational algebra to find domain fusions in protein sequence databases. The feasibility of this method was illustrated on the SWISS-PROT+TrEMBL sequence database using domain predictions from the Pfam HMM (hidden Markov model) database. We identified 235 and 189 putative functionally linked protein partners in H. sapiens and S. cerevisiae, respectively. From scientific literature, we were able to confirm many of these functional linkages, while the remainder offer testable experimental hypothesis. Results can be viewed at http://calcium.uhnres.utoronto.ca/pi. As the analysis can be computed quickly on any relational database that supports standard SQL (structured query language), it can be dynamically updated along with the sequence and domain databases, thereby improving the quality of predictions over time.

The C-terminal domain of the bacterial SSB protein acts as a DNA maintenance hub at active chromosome replication forks.

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Audrey Costes

2010-12-01

Full Text Available We have investigated in vivo the role of the carboxy-terminal domain of the Bacillus subtilis Single-Stranded DNA Binding protein (SSB(Cter as a recruitment platform at active chromosomal forks for many proteins of the genome maintenance machineries. We probed this SSB(Cter interactome using GFP fusions and by Tap-tag and biochemical analysis. It includes at least 12 proteins. The interactome was previously shown to include PriA, RecG, and RecQ and extended in this study by addition of DnaE, SbcC, RarA, RecJ, RecO, XseA, Ung, YpbB, and YrrC. Targeting of YpbB to active forks appears to depend on RecS, a RecQ paralogue, with which it forms a stable complex. Most of these SSB partners are conserved in bacteria, while others, such as the essential DNA polymerase DnaE, YrrC, and the YpbB/RecS complex, appear to be specific to B. subtilis. SSB(Cter deletion has a moderate impact on B. subtilis cell growth. However, it markedly affects the efficiency of repair of damaged genomic DNA and arrested replication forks. ssbΔCter mutant cells appear deficient in RecA loading on ssDNA, explaining their inefficiency in triggering the SOS response upon exposure to genotoxic agents. Together, our findings show that the bacterial SSB(Cter acts as a DNA maintenance hub at active chromosomal forks that secures their propagation along the genome.

The IntFOLD server: an integrated web resource for protein fold recognition, 3D model quality assessment, intrinsic disorder prediction, domain prediction and ligand binding site prediction.

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Roche, Daniel B; Buenavista, Maria T; Tetchner, Stuart J; McGuffin, Liam J

2011-07-01

The IntFOLD server is a novel independent server that integrates several cutting edge methods for the prediction of structure and function from sequence. Our guiding principles behind the server development were as follows: (i) to provide a simple unified resource that makes our prediction software accessible to all and (ii) to produce integrated output for predictions that can be easily interpreted. The output for predictions is presented as a simple table that summarizes all results graphically via plots and annotated 3D models. The raw machine readable data files for each set of predictions are also provided for developers, which comply with the Critical Assessment of Methods for Protein Structure Prediction (CASP) data standards. The server comprises an integrated suite of five novel methods: nFOLD4, for tertiary structure prediction; ModFOLD 3.0, for model quality assessment; DISOclust 2.0, for disorder prediction; DomFOLD 2.0 for domain prediction; and FunFOLD 1.0, for ligand binding site prediction. Predictions from the IntFOLD server were found to be competitive in several categories in the recent CASP9 experiment. The IntFOLD server is available at the following web site: http://www.reading.ac.uk/bioinf/IntFOLD/.

Interactomes to Biological Phase Space: a call to begin thinking at a new level in computational biology.

Energy Technology Data Exchange (ETDEWEB)

Davidson, George S.; Brown, William Michael

2007-09-01

Techniques for high throughput determinations of interactomes, together with high resolution protein collocalizations maps within organelles and through membranes will soon create a vast resource. With these data, biological descriptions, akin to the high dimensional phase spaces familiar to physicists, will become possible. These descriptions will capture sufficient information to make possible realistic, system-level models of cells. The descriptions and the computational models they enable will require powerful computing techniques. This report is offered as a call to the computational biology community to begin thinking at this scale and as a challenge to develop the required algorithms and codes to make use of the new data.3

Fly-DPI: database of protein interactomes for D. melanogaster in the approach of systems biology

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Lin Chieh-Hua

2006-12-01

Full Text Available Abstract Background Proteins control and mediate many biological activities of cells by interacting with other protein partners. This work presents a statistical model to predict protein interaction networks of Drosophila melanogaster based on insight into domain interactions. Results Three high-throughput yeast two-hybrid experiments and the collection in FlyBase were used as our starting datasets. The co-occurrences of domains in these interactive events are converted into a probability score of domain-domain interaction. These scores are used to infer putative interaction among all available open reading frames (ORFs of fruit fly. Additionally, the likelihood function is used to estimate all potential protein-protein interactions. All parameters are successfully iterated and MLE is obtained for each pair of domains. Additionally, the maximized likelihood reaches its converged criteria and maintains the probability stable. The hybrid model achieves a high specificity with a loss of sensitivity, suggesting that the model may possess major features of protein-protein interactions. Several putative interactions predicted by the proposed hybrid model are supported by literatures, while experimental data with a low probability score indicate an uncertain reliability and require further proof of interaction. Fly-DPI is the online database used to present this work. It is an integrated proteomics tool with comprehensive protein annotation information from major databases as well as an effective means of predicting protein-protein interactions. As a novel search strategy, the ping-pong search is a naïve path map between two chosen proteins based on pre-computed shortest paths. Adopting effective filtering strategies will facilitate researchers in depicting the bird's eye view of the network of interest. Fly-DPI can be accessed at http://flydpi.nhri.org.tw. Conclusion This work provides two reference systems, statistical and biological, to evaluate

Attention deficits predict phenotypic outcomes in syndrome-specific and domain-specific ways

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Kim eCornish

2012-07-01

Full Text Available Attentional difficulties, both at home and in the classroom, are reported across a number of neurodevelopmental disorders. However, exactly how attention influences early socio-cognitive learning remains unclear. We addressed this question both concurrently and longitudinally in a cross-syndrome design, with respect to the communicative domain of vocabulary and to the cognitive domain of early literacy, and then extended the analysis to social behavior. Participants were young children (aged 4 to 9 years at Time 1 with either Williams syndrome (WS, N=26 or Down syndrome (DS, N=26 and typically developing controls (N=103. Children with WS displayed significantly greater attentional deficits (as indexed by teacher report of behavior typical of attention deficit hyperactivity disorder, ADHD than children with DS, but both groups had greater attentional problems than the controls. Despite their attention differences, children with DS and those with WS were equivalent in their cognitive abilities of reading single words, both at Time 1 and 12 months later, at Time 2, although they differed in their early communicative abilities in terms of vocabulary. Greater ADHD-like behaviors predicted poorer subsequent literacy for children with DS, but not for children with WS, pointing to syndrome-specific attentional constraints on specific aspects of early development. Overall, our findings highlight the need to investigate more precisely whether and, if so, how, syndrome-specific profiles of behavioral difficulties constrain learning and socio-cognitive outcomes across different domains.

Dissection of protein interactomics highlights microRNA synergy.

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Zhu, Wenliang; Zhao, Yilei; Xu, Yingqi; Sun, Yong; Wang, Zhe; Yuan, Wei; Du, Zhimin

2013-01-01

Despite a large amount of microRNAs (miRNAs) have been validated to play crucial roles in human biology and disease, there is little systematic insight into the nature and scale of the potential synergistic interactions executed by miRNAs themselves. Here we established an integrated parameter synergy score to determine miRNA synergy, by combining the two mechanisms for miRNA-miRNA interactions, miRNA-mediated gene co-regulation and functional association between target gene products, into one single parameter. Receiver operating characteristic (ROC) analysis indicated that synergy score accurately identified the gene ontology-defined miRNA synergy (AUC = 0.9415, psynergy, implying poor expectancy of widespread synergy. However, targeting more key genes made two miRNAs more likely to act synergistically. Compared to other miRNAs, miR-21 was a highly exceptional case due to frequent appearance in the top synergistic miRNA pairs. This result highlighted its essential role in coordinating or strengthening physiological and pathological functions of other miRNAs. The synergistic effect of miR-21 and miR-1 were functionally validated for their significant influences on myocardial apoptosis, cardiac hypertrophy and fibrosis. The novel approach established in this study enables easy and effective identification of condition-restricted potent miRNA synergy simply by concentrating the available protein interactomics and miRNA-target interaction data into a single parameter synergy score. Our results may be important for understanding synergistic gene regulation by miRNAs and may have significant implications for miRNA combination therapy of cardiovascular disease.

Characterization of hampin/MSL1 as a node in the nuclear interactome

International Nuclear Information System (INIS)

Dmitriev, Ruslan I.; Korneenko, Tatyana V.; Bessonov, Alexander A.; Shakhparonov, Mikhail I.; Modyanov, Nikolai N.; Pestov, Nikolay B.

2007-01-01

Hampin, homolog of Drosophila MSL1, is a partner of histone acetyltransferase MYST1/MOF. Functions of these proteins remain poorly understood beyond their participation in chromatin remodeling complex MSL. In order to identify new proteins interacting with hampin, we screened a mouse cDNA library in yeast two-hybrid system with mouse hampin as bait and found five high-confidence interactors: MYST1, TPR proteins TTC4 and KIAA0103, NOP17 (homolog of a yeast nucleolar protein), and transcription factor GC BP. Subsequently, all these proteins were used as baits in library screenings and more new interactions were found: tumor suppressor RASSF1C and spliceosome component PRP3 for KIAA0103, ring finger RNF10 for RASSF1C, and RNA polymerase II regulator NELF-C for MYST1. The majority of the observed interactions was confirmed in vitro by pull-down of bacterially expressed proteins. Reconstruction of a fragment of mammalian interactome suggests that hampin may be linked to diverse regulatory processes in the nucleus

Prediction of radiation ratio and sound transmission of complex extruded panel using wavenumber domain Unite element and boundary element methods

International Nuclear Information System (INIS)

Kim, H; Ryue, J; Thompson, D J; Müller, A D

2016-01-01

Recently, complex shaped aluminium panels have been adopted in many structures to make them lighter and stronger. The vibro-acoustic behaviour of these complex panels has been of interest for many years but conventional finite element and boundary element methods are not efficient to predict their performance at higher frequencies. Where the cross-sectional properties of the panels are constant in one direction, wavenumber domain numerical analysis can be applied and this becomes more suitable for panels with complex cross-sectional geometries. In this paper, a coupled wavenumber domain finite element and boundary element method is applied to predict the sound radiation from and sound transmission through a double-layered aluminium extruded panel, having a typical shape used in railway carriages. The predicted results are compared with measured ones carried out on a finite length panel and good agreement is found. (paper)

Epidermal Growth Factor-like Domain 7 Predicts Response to First-Line Chemotherapy and Bevacizumab in Patients with Metastatic Colorectal Cancer

DEFF Research Database (Denmark)

Hansen, Torben Frøstrup; Nielsen, Boye Schnack; Sørensen, Flemming Brandt

2014-01-01

The number of approved antiangiogenic drugs is constantly growing and emphasizes the need for predictive biomarkers. The aim of this study was to analyze the predictive value of epidermal growth factor-like domain 7 (EGFL7) and microRNA-126 (miR126) to first-line chemotherapy combined with bevaci...

Predicting first-grade mathematics achievement: The contributions of domain-general cognitive abilities, nonverbal number sense, and early number competence.

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Caroline eHornung

2014-04-01

Full Text Available Early number competence, grounded in number-specific and domain-general cognitive abilities, is theorized to lay the foundation for later math achievement. Few longitudinal studies have tested a comprehensive model for early math development. Using structural equation modeling and mediation analyses, the present work examined the influence of kindergarteners’ nonverbal number sense and domain-general abilities i.e., working memory, fluid intelligence, and receptive vocabulary and their early number competence (i.e., symbolic number skills on first grade math achievement (arithmetic, shape and space skills, and number line estimation assessed one year later. Latent regression models revealed that nonverbal number sense and working memory are central building blocks for developing early number competence in kindergarten and that early number competence is key for first grade math achievement. After controlling for early number competence, fluid intelligence significantly predicted arithmetic and number line estimation while receptive vocabulary significantly predicted shape and space skills. In sum we suggest that early math achievement draws on different constellations of number-specific and domain-general mechanisms.

Structure homology and interaction redundancy for discovering virus–host protein interactions

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de Chassey, Benoît; Meyniel-Schicklin, Laurène; Aublin-Gex, Anne; Navratil, Vincent; Chantier, Thibaut; André, Patrice; Lotteau, Vincent

2013-01-01

Virus–host interactomes are instrumental to understand global perturbations of cellular functions induced by infection and discover new therapies. The construction of such interactomes is, however, technically challenging and time consuming. Here we describe an original method for the prediction of high-confidence interactions between viral and human proteins through a combination of structure and high-quality interactome data. Validation was performed for the NS1 protein of the influenza virus, which led to the identification of new host factors that control viral replication. PMID:24008843

Structure homology and interaction redundancy for discovering virus-host protein interactions.

Science.gov (United States)

de Chassey, Benoît; Meyniel-Schicklin, Laurène; Aublin-Gex, Anne; Navratil, Vincent; Chantier, Thibaut; André, Patrice; Lotteau, Vincent

2013-10-01

Virus-host interactomes are instrumental to understand global perturbations of cellular functions induced by infection and discover new therapies. The construction of such interactomes is, however, technically challenging and time consuming. Here we describe an original method for the prediction of high-confidence interactions between viral and human proteins through a combination of structure and high-quality interactome data. Validation was performed for the NS1 protein of the influenza virus, which led to the identification of new host factors that control viral replication.

Gait Rather Than Cognition Predicts Decline in Specific Cognitive Domains in Early Parkinson's Disease.

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Morris, Rosie; Lord, Sue; Lawson, Rachael A; Coleman, Shirley; Galna, Brook; Duncan, Gordon W; Khoo, Tien K; Yarnall, Alison J; Burn, David J; Rochester, Lynn

2017-11-09

Dementia is significant in Parkinson's disease (PD) with personal and socioeconomic impact. Early identification of risk is of upmost importance to optimize management. Gait precedes and predicts cognitive decline and dementia in older adults. We aimed to evaluate gait characteristics as predictors of cognitive decline in newly diagnosed PD. One hundred and nineteen participants recruited at diagnosis were assessed at baseline, 18 and 36 months. Baseline gait was characterized by variables that mapped to five domains: pace, rhythm, variability, asymmetry, and postural control. Cognitive assessment included attention, fluctuating attention, executive function, visual memory, and visuospatial function. Mixed-effects models tested independent gait predictors of cognitive decline. Gait characteristics of pace, variability, and postural control predicted decline in fluctuating attention and visual memory, whereas baseline neuropsychological assessment performance did not predict decline. This provides novel evidence for gait as a clinical biomarker for PD cognitive decline in early disease. © The Author 2017. Published by Oxford University Press on behalf of The Gerontological Society of America.

Predicting and analyzing DNA-binding domains using a systematic approach to identifying a set of informative physicochemical and biochemical properties

Science.gov (United States)

2011-01-01

Background Existing methods of predicting DNA-binding proteins used valuable features of physicochemical properties to design support vector machine (SVM) based classifiers. Generally, selection of physicochemical properties and determination of their corresponding feature vectors rely mainly on known properties of binding mechanism and experience of designers. However, there exists a troublesome problem for designers that some different physicochemical properties have similar vectors of representing 20 amino acids and some closely related physicochemical properties have dissimilar vectors. Results This study proposes a systematic approach (named Auto-IDPCPs) to automatically identify a set of physicochemical and biochemical properties in the AAindex database to design SVM-based classifiers for predicting and analyzing DNA-binding domains/proteins. Auto-IDPCPs consists of 1) clustering 531 amino acid indices in AAindex into 20 clusters using a fuzzy c-means algorithm, 2) utilizing an efficient genetic algorithm based optimization method IBCGA to select an informative feature set of size m to represent sequences, and 3) analyzing the selected features to identify related physicochemical properties which may affect the binding mechanism of DNA-binding domains/proteins. The proposed Auto-IDPCPs identified m=22 features of properties belonging to five clusters for predicting DNA-binding domains with a five-fold cross-validation accuracy of 87.12%, which is promising compared with the accuracy of 86.62% of the existing method PSSM-400. For predicting DNA-binding sequences, the accuracy of 75.50% was obtained using m=28 features, where PSSM-400 has an accuracy of 74.22%. Auto-IDPCPs and PSSM-400 have accuracies of 80.73% and 82.81%, respectively, applied to an independent test data set of DNA-binding domains. Some typical physicochemical properties discovered are hydrophobicity, secondary structure, charge, solvent accessibility, polarity, flexibility, normalized Van Der

CTCF and CohesinSA-1 Mark Active Promoters and Boundaries of Repressive Chromatin Domains in Primary Human Erythroid Cells.

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Laurie A Steiner

Full Text Available CTCF and cohesinSA-1 are regulatory proteins involved in a number of critical cellular processes including transcription, maintenance of chromatin domain architecture, and insulator function. To assess changes in the CTCF and cohesinSA-1 interactomes during erythropoiesis, chromatin immunoprecipitation coupled with high throughput sequencing and mRNA transcriptome analyses via RNA-seq were performed in primary human hematopoietic stem and progenitor cells (HSPC and primary human erythroid cells from single donors.Sites of CTCF and cohesinSA-1 co-occupancy were enriched in gene promoters in HSPC and erythroid cells compared to single CTCF or cohesin sites. Cell type-specific CTCF sites in erythroid cells were linked to highly expressed genes, with the opposite pattern observed in HSPCs. Chromatin domains were identified by ChIP-seq with antibodies against trimethylated lysine 27 histone H3, a modification associated with repressive chromatin. Repressive chromatin domains increased in both number and size during hematopoiesis, with many more repressive domains in erythroid cells than HSPCs. CTCF and cohesinSA-1 marked the boundaries of these repressive chromatin domains in a cell-type specific manner.These genome wide data, changes in sites of protein occupancy, chromatin architecture, and related gene expression, support the hypothesis that CTCF and cohesinSA-1 have multiple roles in the regulation of gene expression during erythropoiesis including transcriptional regulation at gene promoters and maintenance of chromatin architecture. These data from primary human erythroid cells provide a resource for studies of normal and perturbed erythropoiesis.

Three-dimensional (3D) structure prediction and function analysis of the chitin-binding domain 3 protein HD73_3189 from Bacillus thuringiensis HD73.

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Zhan, Yiling; Guo, Shuyuan

2015-01-01

Bacillus thuringiensis (Bt) is capable of producing a chitin-binding protein believed to be functionally important to bacteria during the stationary phase of its growth cycle. In this paper, the chitin-binding domain 3 protein HD73_3189 from B. thuringiensis has been analyzed by computer technology. Primary and secondary structural analyses demonstrated that HD73_3189 is negatively charged and contains several α-helices, aperiodical coils and β-strands. Domain and motif analyses revealed that HD73_3189 contains a signal peptide, an N-terminal chitin binding 3 domains, two copies of a fibronectin-like domain 3 and a C-terminal carbohydrate binding domain classified as CBM_5_12. Moreover, analysis predicted the protein's associated localization site to be the cell wall. Ligand site prediction determined that amino acid residues GLU-312, TRP-334, ILE-341 and VAL-382 exposed on the surface of the target protein exhibit polar interactions with the substrate.

Hum-mPLoc 3.0: prediction enhancement of human protein subcellular localization through modeling the hidden correlations of gene ontology and functional domain features.

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Zhou, Hang; Yang, Yang; Shen, Hong-Bin

2017-03-15

Protein subcellular localization prediction has been an important research topic in computational biology over the last decade. Various automatic methods have been proposed to predict locations for large scale protein datasets, where statistical machine learning algorithms are widely used for model construction. A key step in these predictors is encoding the amino acid sequences into feature vectors. Many studies have shown that features extracted from biological domains, such as gene ontology and functional domains, can be very useful for improving the prediction accuracy. However, domain knowledge usually results in redundant features and high-dimensional feature spaces, which may degenerate the performance of machine learning models. In this paper, we propose a new amino acid sequence-based human protein subcellular location prediction approach Hum-mPLoc 3.0, which covers 12 human subcellular localizations. The sequences are represented by multi-view complementary features, i.e. context vocabulary annotation-based gene ontology (GO) terms, peptide-based functional domains, and residue-based statistical features. To systematically reflect the structural hierarchy of the domain knowledge bases, we propose a novel feature representation protocol denoted as HCM (Hidden Correlation Modeling), which will create more compact and discriminative feature vectors by modeling the hidden correlations between annotation terms. Experimental results on four benchmark datasets show that HCM improves prediction accuracy by 5-11% and F 1 by 8-19% compared with conventional GO-based methods. A large-scale application of Hum-mPLoc 3.0 on the whole human proteome reveals proteins co-localization preferences in the cell. www.csbio.sjtu.edu.cn/bioinf/Hum-mPLoc3/. hbshen@sjtu.edu.cn. 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

Accumulating Data to Optimally Predict Obesity Treatment (ADOPT) Core Measures: Environmental Domain.

Science.gov (United States)

Saelens, Brian E; Arteaga, S Sonia; Berrigan, David; Ballard, Rachel M; Gorin, Amy A; Powell-Wiley, Tiffany M; Pratt, Charlotte; Reedy, Jill; Zenk, Shannon N

2018-04-01

There is growing interest in how environment is related to adults' weight and activity and eating behaviors. However, little is known about whether environmental factors are related to the individual variability seen in adults' intentional weight loss or maintenance outcomes. The environmental domain subgroup of the Accumulating Data to Optimally Predict obesity Treatment (ADOPT) Core Measures Project sought to identify a parsimonious set of objective and perceived neighborhood and social environment constructs and corresponding measures to include in the assessment of response to adult weight-loss treatment. Starting with the home address, the environmental domain subgroup recommended for inclusion in future weight-loss or maintenance studies constructs and measures related to walkability, perceived land use mix, food outlet accessibility (perceived and objective), perceived food availability, socioeconomics, and crime-related safety (perceived and objective) to characterize the home neighborhood environment. The subgroup also recommended constructs and measures related to social norms (perceived and objective) and perceived support to characterize an individual's social environment. The 12 neighborhood and social environment constructs and corresponding measures provide a succinct and comprehensive set to allow for more systematic examination of the impact of environment on adults' weight loss and maintenance. © 2018 The Obesity Society.

A comprehensive protein-protein interactome for yeast PAS kinase 1 reveals direct inhibition of respiration through the phosphorylation of Cbf1.

Science.gov (United States)

DeMille, Desiree; Bikman, Benjamin T; Mathis, Andrew D; Prince, John T; Mackay, Jordan T; Sowa, Steven W; Hall, Tacie D; Grose, Julianne H

2014-07-15

Per-Arnt-Sim (PAS) kinase is a sensory protein kinase required for glucose homeostasis in yeast, mice, and humans, yet little is known about the molecular mechanisms of its function. Using both yeast two-hybrid and copurification approaches, we identified the protein-protein interactome for yeast PAS kinase 1 (Psk1), revealing 93 novel putative protein binding partners. Several of the Psk1 binding partners expand the role of PAS kinase in glucose homeostasis, including new pathways involved in mitochondrial metabolism. In addition, the interactome suggests novel roles for PAS kinase in cell growth (gene/protein expression, replication/cell division, and protein modification and degradation), vacuole function, and stress tolerance. In vitro kinase studies using a subset of 25 of these binding partners identified Mot3, Zds1, Utr1, and Cbf1 as substrates. Further evidence is provided for the in vivo phosphorylation of Cbf1 at T211/T212 and for the subsequent inhibition of respiration. This respiratory role of PAS kinase is consistent with the reported hypermetabolism of PAS kinase-deficient mice, identifying a possible molecular mechanism and solidifying the evolutionary importance of PAS kinase in the regulation of glucose homeostasis. © 2014 DeMille et al. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Inferring domain-domain interactions from protein-protein interactions with formal concept analysis.

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Susan Khor

Full Text Available Identifying reliable domain-domain interactions will increase our ability to predict novel protein-protein interactions, to unravel interactions in protein complexes, and thus gain more information about the function and behavior of genes. One of the challenges of identifying reliable domain-domain interactions is domain promiscuity. Promiscuous domains are domains that can occur in many domain architectures and are therefore found in many proteins. This becomes a problem for a method where the score of a domain-pair is the ratio between observed and expected frequencies because the protein-protein interaction network is sparse. As such, many protein-pairs will be non-interacting and domain-pairs with promiscuous domains will be penalized. This domain promiscuity challenge to the problem of inferring reliable domain-domain interactions from protein-protein interactions has been recognized, and a number of work-arounds have been proposed. This paper reports on an application of Formal Concept Analysis to this problem. It is found that the relationship between formal concepts provides a natural way for rare domains to elevate the rank of promiscuous domain-pairs and enrich highly ranked domain-pairs with reliable domain-domain interactions. This piggybacking of promiscuous domain-pairs onto less promiscuous domain-pairs is possible only with concept lattices whose attribute-labels are not reduced and is enhanced by the presence of proteins that comprise both promiscuous and rare domains.

Inferring Domain-Domain Interactions from Protein-Protein Interactions with Formal Concept Analysis

Science.gov (United States)

Khor, Susan

2014-01-01

Identifying reliable domain-domain interactions will increase our ability to predict novel protein-protein interactions, to unravel interactions in protein complexes, and thus gain more information about the function and behavior of genes. One of the challenges of identifying reliable domain-domain interactions is domain promiscuity. Promiscuous domains are domains that can occur in many domain architectures and are therefore found in many proteins. This becomes a problem for a method where the score of a domain-pair is the ratio between observed and expected frequencies because the protein-protein interaction network is sparse. As such, many protein-pairs will be non-interacting and domain-pairs with promiscuous domains will be penalized. This domain promiscuity challenge to the problem of inferring reliable domain-domain interactions from protein-protein interactions has been recognized, and a number of work-arounds have been proposed. This paper reports on an application of Formal Concept Analysis to this problem. It is found that the relationship between formal concepts provides a natural way for rare domains to elevate the rank of promiscuous domain-pairs and enrich highly ranked domain-pairs with reliable domain-domain interactions. This piggybacking of promiscuous domain-pairs onto less promiscuous domain-pairs is possible only with concept lattices whose attribute-labels are not reduced and is enhanced by the presence of proteins that comprise both promiscuous and rare domains. PMID:24586450

Synaptic Interactome Mining Reveals p140Cap as a New Hub for PSD Proteins Involved in Psychiatric and Neurological Disorders

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Annalisa Alfieri

2017-06-01

Full Text Available Altered synaptic function has been associated with neurological and psychiatric conditions including intellectual disability, schizophrenia and autism spectrum disorder (ASD. Amongst the recently discovered synaptic proteins is p140Cap, an adaptor that localizes at dendritic spines and regulates their maturation and physiology. We recently showed that p140Cap knockout mice have cognitive deficits, impaired long-term potentiation (LTP and long-term depression (LTD, and immature, filopodia-like dendritic spines. Only a few p140Cap interacting proteins have been identified in the brain and the molecular complexes and pathways underlying p140Cap synaptic function are largely unknown. Here, we isolated and characterized the p140Cap synaptic interactome by co-immunoprecipitation from crude mouse synaptosomes, followed by mass spectrometry-based proteomics. We identified 351 p140Cap interactors and found that they cluster to sub complexes mostly located in the postsynaptic density (PSD. p140Cap interactors converge on key synaptic processes, including transmission across chemical synapses, actin cytoskeleton remodeling and cell-cell junction organization. Gene co-expression data further support convergent functions: the p140Cap interactors are tightly co-expressed with each other and with p140Cap. Importantly, the p140Cap interactome and its co-expression network show strong enrichment in genes associated with schizophrenia, autism, bipolar disorder, intellectual disability and epilepsy, supporting synaptic dysfunction as a shared biological feature in brain diseases. Overall, our data provide novel insights into the molecular organization of the synapse and indicate that p140Cap acts as a hub for postsynaptic complexes relevant to psychiatric and neurological disorders.

Protein domain recurrence and order can enhance prediction of protein functions

KAUST Repository

Abdel Messih, Mario A.

2012-09-07

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

Seasonal dependence of the predictable low-level circulation patterns over the tropical Indo-Pacific domain

Science.gov (United States)

Zhang, Tuantuan; Huang, Bohua; Yang, Song; Laohalertchai, Charoon

2018-06-01

The seasonal dependence of the prediction skill of 850-hPa monthly zonal wind over the tropical Indo-Pacific domain is examined using the ensemble reforecasts for 1983-2010 from the National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis and Reforecast (CFSRR) project. According to a maximum signal-to-noise empirical orthogonal function analysis, the most predictable patterns of atmospheric low-level circulation are associated with the developing and maturing phases of El Niño-Southern Oscillation (ENSO). The CFSv2 is capable of predicting these ENSO-related patterns up to 9-months in advance for all months, except for May-June when the effect of the spring barrier is strong. The other predictable climate processes associated with the low-level atmospheric circulation are more seasonally dependent. For winter and spring, the second most predictable patterns are associated with the ENSO decaying phase. Within these seasons, the monthly evolution of the predictable patterns is characterized by a southward shift of westerly wind anomalies, generated by the interaction between the annual cycle and the ENSO signals (i.e., the combination-mode). In general, the CFSv2 hindcast well predicts these patterns at least 5 months in advance for spring, while shows much lower skills for winter months. In summer, the second predictable patterns are associated with the western North Pacific (WNP) monsoon (i.e., the WNP anticyclone/cyclone) in short leads while associated with ENSO in longer leads (after 4-month lead). The second predictable patterns in fall are mainly associated with tropical Indian Ocean Dipole, which can be predicted 3 months in advance.

Stereochemical determinants of C-terminal specificity in PDZ peptide-binding domains: a novel contribution of the carboxylate-binding loop.

Science.gov (United States)

Amacher, Jeanine F; Cushing, Patrick R; Bahl, Christopher D; Beck, Tobias; Madden, Dean R

2013-02-15

PDZ (PSD-95/Dlg/ZO-1) binding domains often serve as cellular traffic engineers, controlling the localization and activity of a wide variety of binding partners. As a result, they play important roles in both physiological and pathological processes. However, PDZ binding specificities overlap, allowing multiple PDZ proteins to mediate distinct effects on shared binding partners. For example, several PDZ domains bind the cystic fibrosis (CF) transmembrane conductance regulator (CFTR), an epithelial ion channel mutated in CF. Among these binding partners, the CFTR-associated ligand (CAL) facilitates post-maturational degradation of the channel and is thus a potential therapeutic target. Using iterative optimization, we previously developed a selective CAL inhibitor peptide (iCAL36). Here, we investigate the stereochemical basis of iCAL36 specificity. The crystal structure of iCAL36 in complex with the CAL PDZ domain reveals stereochemical interactions distributed along the peptide-binding cleft, despite the apparent degeneracy of the CAL binding motif. A critical selectivity determinant that distinguishes CAL from other CFTR-binding PDZ domains is the accommodation of an isoleucine residue at the C-terminal position (P(0)), a characteristic shared with the Tax-interacting protein-1. Comparison of the structures of these two PDZ domains in complex with ligands containing P(0) Leu or Ile residues reveals two distinct modes of accommodation for β-branched C-terminal side chains. Access to each mode is controlled by distinct residues in the carboxylate-binding loop. These studies provide new insights into the primary sequence determinants of binding motifs, which in turn control the scope and evolution of PDZ interactomes.

Domain-General Factors Influencing Numerical and Arithmetic Processing

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André Knops

2017-12-01

Full Text Available This special issue contains 18 articles that address the question how numerical processes interact with domain-general factors. We start the editorial with a discussion of how to define domain-general versus domain-specific factors and then discuss the contributions to this special issue grouped into two core numerical domains that are subject to domain-general influences (see Figure 1. The first group of contributions addresses the question how numbers interact with spatial factors. The second group of contributions is concerned with factors that determine and predict arithmetic understanding, performance and development. This special issue shows that domain-general (Table 1a as well as domain-specific (Table 1b abilities influence numerical and arithmetic performance virtually at all levels and make it clear that for the field of numerical cognition a sole focus on one or several domain-specific factors like the approximate number system or spatial-numerical associations is not sufficient. Vice versa, in most studies that included domain-general and domain-specific variables, domain-specific numerical variables predicted arithmetic performance above and beyond domain-general variables. Therefore, a sole focus on domain-general aspects such as, for example, working memory, to explain, predict and foster arithmetic learning is also not sufficient. Based on the articles in this special issue we conclude that both domain-general and domain-specific factors contribute to numerical cognition. But the how, why and when of their contribution still needs to be better understood. We hope that this special issue may be helpful to readers in constraining future theory and model building about the interplay of domain-specific and domain-general factors.

Dissection of the BCR-ABL signaling network using highly specific monobody inhibitors to the SHP2 SH2 domains.

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Sha, Fern; Gencer, Emel Basak; Georgeon, Sandrine; Koide, Akiko; Yasui, Norihisa; Koide, Shohei; Hantschel, Oliver

2013-09-10

The dysregulated tyrosine kinase BCR-ABL causes chronic myelogenous leukemia in humans and forms a large multiprotein complex that includes the Src-homology 2 (SH2) domain-containing phosphatase 2 (SHP2). The expression of SHP2 is necessary for BCR-ABL-dependent oncogenic transformation, but the precise signaling mechanisms of SHP2 are not well understood. We have developed binding proteins, termed monobodies, for the N- and C-terminal SH2 domains of SHP2. Intracellular expression followed by interactome analysis showed that the monobodies are essentially monospecific to SHP2. Two crystal structures revealed that the monobodies occupy the phosphopeptide-binding sites of the SH2 domains and thus can serve as competitors of SH2-phosphotyrosine interactions. Surprisingly, the segments of both monobodies that bind to the peptide-binding grooves run in the opposite direction to that of canonical phosphotyrosine peptides, which may contribute to their exquisite specificity. When expressed in cells, monobodies targeting the N-SH2 domain disrupted the interaction of SHP2 with its upstream activator, the Grb2-associated binder 2 adaptor protein, suggesting decoupling of SHP2 from the BCR-ABL protein complex. Inhibition of either N-SH2 or C-SH2 was sufficient to inhibit two tyrosine phosphorylation events that are critical for SHP2 catalytic activity and to block ERK activation. In contrast, targeting the N-SH2 or C-SH2 revealed distinct roles of the two SH2 domains in downstream signaling, such as the phosphorylation of paxillin and signal transducer and activator of transcription 5. Our results delineate a hierarchy of function for the SH2 domains of SHP2 and validate monobodies as potent and specific antagonists of protein-protein interactions in cancer cells.

Predictive, Construct, and Convergent Validity of General and Domain-Specific Measures of Hope for College Student Academic Achievement

Science.gov (United States)

Robinson, Cecil; Rose, Sage

2010-01-01

One leading version of hope theory posits hope to be a general disposition for goal-directed agency and pathways thinking. Domain-specific hope theory suggests that hope operates within context and measures of hope should reflect that context. This study examined three measures of hope to test the predictive, construct, and convergent validity…

Domains of cognitive function in early old age: which ones are predicted by pre-retirement psychosocial work characteristics?

Science.gov (United States)

Sabbath, Erika; Andel, Ross; Zins, Marie; Goldberg, Marcel; Berr, Claudine

2016-01-01

Background Psychosocial work characteristics may predict cognitive functioning after retirement. However, little research has explored specific cognitive domains associated with psychosocial work environments. Our study tested whether exposure to job demands, job control, and their combination during working life predicted post-retirement performance on eight cognitive tests. Methods We used data from French GAZEL cohort members who had undergone post-retirement cognitive testing (n=2,149). Psychosocial job characteristics were measured on average four years before retirement using Karasek’s Job Content Questionnaire (job demands, job control, demand-control combinations). We tested associations between these exposures and post-retirement performance on tests of executive function, visual-motor speed, psycho-motor speed, verbal memory, and verbal fluency using OLS regression. Results Low job control during working life was negatively associated with executive function, psychomotor speed, phonemic fluency, and semantic fluency after retirement (p’scognitive domains. In addition to work stress, associations between passive work and subsequent cognitive function may implicate lack of cognitive engagement at work as a risk factor for future cognitive difficulties. PMID:27188277

The PAS fold: A redefinition of the PAS domain based upon structural prediction. A large-scale homology modelling study

NARCIS (Netherlands)

Hefti, M.H.; Francoijs, C.J.J.; Vries, de S.C.; Dixon, R.; Vervoort, J.J.M.

2004-01-01

In the postgenomic era it is essential that protein sequences are annotated correctly in order to help in the assignment of their putative functions. Over 1300 proteins in current protein sequence databases are predicted to contain a PAS domain based upon amino acid sequence alignments. One of the

Making connections for life: an in vivo map of the yeast interactome.

Science.gov (United States)

Kast, Juergen

2008-10-01

Proteins are the true workhorses of any cell. To carry out specific tasks, they frequently bind other molecules in their surroundings. Due to their structural complexity and flexibility, the most diverse array of interactions is seen with other proteins. The different geometries and affinities available for such interactions typically bestow specific functions on proteins. Having available a map of protein-protein interactions is therefore of enormous importance for any researcher interested in gaining insight into biological systems at the level of cells and organisms. In a recent report, a novel approach has been employed that relies on the spontaneous folding of complementary enzyme fragments fused to two different proteins to test whether these interact in their actual cellular context [Tarassov et al., Science 320, 1465-1470 (2008)]. Genome-wide application of this protein-fragment complementation assay has resulted in the first map of the in vivo interactome of Saccharomyces cerevisiae. The current data show striking similarities but also significant differences to those obtained using other large-scale approaches for the same task. This warrants a general discussion of the current state of affairs of protein-protein interaction studies and foreseeable future trends, highlighting their significance for a variety of applications and their potential to revolutionize our understanding of the architecture and dynamics of biological systems.

Mapping the Interactome of a Major Mammalian Endoplasmic Reticulum Heat Shock Protein 90.

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Feng Hong

Full Text Available Up to 10% of cytosolic proteins are dependent on the mammalian heat shock protein 90 (HSP90 for folding. However, the interactors of its endoplasmic reticulum (ER paralogue (gp96, Grp94 and HSP90b1 has not been systematically identified. By combining genetic and biochemical approaches, we have comprehensively mapped the interactome of gp96 in macrophages and B cells. A total of 511 proteins were reduced in gp96 knockdown cells, compared to levels observed in wild type cells. By immunoprecipitation, we found that 201 proteins associated with gp96. Gene Ontology analysis indicated that these proteins are involved in metabolism, transport, translation, protein folding, development, localization, response to stress and cellular component biogenesis. While known gp96 clients such as integrins, Toll-like receptors (TLRs and Wnt co-receptor LRP6, were confirmed, cell surface HSP receptor CD91, TLR4 pathway protein CD180, WDR1, GANAB and CAPZB were identified as potentially novel substrates of gp96. Taken together, our study establishes gp96 as a critical chaperone to integrate innate immunity, Wnt signaling and organ development.

Computational analysis and prediction of the binding motif and protein interacting partners of the Abl SH3 domain.

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Tingjun Hou

2006-01-01

Full Text Available Protein-protein interactions, particularly weak and transient ones, are often mediated by peptide recognition domains, such as Src Homology 2 and 3 (SH2 and SH3 domains, which bind to specific sequence and structural motifs. It is important but challenging to determine the binding specificity of these domains accurately and to predict their physiological interacting partners. In this study, the interactions between 35 peptide ligands (15 binders and 20 non-binders and the Abl SH3 domain were analyzed using molecular dynamics simulation and the Molecular Mechanics/Poisson-Boltzmann Solvent Area method. The calculated binding free energies correlated well with the rank order of the binding peptides and clearly distinguished binders from non-binders. Free energy component analysis revealed that the van der Waals interactions dictate the binding strength of peptides, whereas the binding specificity is determined by the electrostatic interaction and the polar contribution of desolvation. The binding motif of the Abl SH3 domain was then determined by a virtual mutagenesis method, which mutates the residue at each position of the template peptide relative to all other 19 amino acids and calculates the binding free energy difference between the template and the mutated peptides using the Molecular Mechanics/Poisson-Boltzmann Solvent Area method. A single position mutation free energy profile was thus established and used as a scoring matrix to search peptides recognized by the Abl SH3 domain in the human genome. Our approach successfully picked ten out of 13 experimentally determined binding partners of the Abl SH3 domain among the top 600 candidates from the 218,540 decapeptides with the PXXP motif in the SWISS-PROT database. We expect that this physical-principle based method can be applied to other protein domains as well.

Fast kinase domain-containing protein 3 is a mitochondrial protein essential for cellular respiration

Energy Technology Data Exchange (ETDEWEB)

Simarro, Maria [Division of Rheumatology, Immunology and Allergy, Brigham and Women' s Hospital, and Department of Medicine, Harvard Medical School, Boston, MA 02115 (United States); Gimenez-Cassina, Alfredo [Department of Cancer Biology at Dana Farber Institute, Boston, MA 02115 (United States); Kedersha, Nancy [Division of Rheumatology, Immunology and Allergy, Brigham and Women' s Hospital, and Department of Medicine, Harvard Medical School, Boston, MA 02115 (United States); Lazaro, Jean-Bernard; Adelmant, Guillaume O.; Marto, Jarrod A. [Department of Cancer Biology at Dana Farber Institute, Boston, MA 02115 (United States); Rhee, Kirsten [Division of Rheumatology, Immunology and Allergy, Brigham and Women' s Hospital, and Department of Medicine, Harvard Medical School, Boston, MA 02115 (United States); Tisdale, Sarah; Danial, Nika [Department of Cancer Biology at Dana Farber Institute, Boston, MA 02115 (United States); Benarafa, Charaf [Theodor Kocher Institute, University of Bern, 3012 Bern (Switzerland); Orduna, Anonio [Unidad de Investigacion, Hospital Clinico Universitario de Valladolid, 47005 Valladolid (Spain); Anderson, Paul, E-mail: panderson@rics.bwh.harvard.edu [Division of Rheumatology, Immunology and Allergy, Brigham and Women' s Hospital, and Department of Medicine, Harvard Medical School, Boston, MA 02115 (United States)

2010-10-22

Research highlights: {yields} Five members of the FAST kinase domain-containing proteins are localized to mitochondria in mammalian cells. {yields} The FASTKD3 interactome includes proteins involved in various aspects of mitochondrial metabolism. {yields} Targeted knockdown of FASTKD3 significantly reduces basal and maximal mitochondrial oxygen consumption. -- Abstract: Fas-activated serine/threonine phosphoprotein (FAST) is the founding member of the FAST kinase domain-containing protein (FASTKD) family that includes FASTKD1-5. FAST is a sensor of mitochondrial stress that modulates protein translation to promote the survival of cells exposed to adverse conditions. Mutations in FASTKD2 have been linked to a mitochondrial encephalomyopathy that is associated with reduced cytochrome c oxidase activity, an essential component of the mitochondrial electron transport chain. We have confirmed the mitochondrial localization of FASTKD2 and shown that all FASTKD family members are found in mitochondria. Although human and mouse FASTKD1-5 genes are expressed ubiquitously, some of them are most abundantly expressed in mitochondria-enriched tissues. We have found that RNA interference-mediated knockdown of FASTKD3 severely blunts basal and stress-induced mitochondrial oxygen consumption without disrupting the assembly of respiratory chain complexes. Tandem affinity purification reveals that FASTKD3 interacts with components of mitochondrial respiratory and translation machineries. Our results introduce FASTKD3 as an essential component of mitochondrial respiration that may modulate energy balance in cells exposed to adverse conditions by functionally coupling mitochondrial protein synthesis to respiration.

Fast kinase domain-containing protein 3 is a mitochondrial protein essential for cellular respiration

International Nuclear Information System (INIS)

Simarro, Maria; Gimenez-Cassina, Alfredo; Kedersha, Nancy; Lazaro, Jean-Bernard; Adelmant, Guillaume O.; Marto, Jarrod A.; Rhee, Kirsten; Tisdale, Sarah; Danial, Nika; Benarafa, Charaf; Orduna, Anonio; Anderson, Paul

2010-01-01

Research highlights: → Five members of the FAST kinase domain-containing proteins are localized to mitochondria in mammalian cells. → The FASTKD3 interactome includes proteins involved in various aspects of mitochondrial metabolism. → Targeted knockdown of FASTKD3 significantly reduces basal and maximal mitochondrial oxygen consumption. -- Abstract: Fas-activated serine/threonine phosphoprotein (FAST) is the founding member of the FAST kinase domain-containing protein (FASTKD) family that includes FASTKD1-5. FAST is a sensor of mitochondrial stress that modulates protein translation to promote the survival of cells exposed to adverse conditions. Mutations in FASTKD2 have been linked to a mitochondrial encephalomyopathy that is associated with reduced cytochrome c oxidase activity, an essential component of the mitochondrial electron transport chain. We have confirmed the mitochondrial localization of FASTKD2 and shown that all FASTKD family members are found in mitochondria. Although human and mouse FASTKD1-5 genes are expressed ubiquitously, some of them are most abundantly expressed in mitochondria-enriched tissues. We have found that RNA interference-mediated knockdown of FASTKD3 severely blunts basal and stress-induced mitochondrial oxygen consumption without disrupting the assembly of respiratory chain complexes. Tandem affinity purification reveals that FASTKD3 interacts with components of mitochondrial respiratory and translation machineries. Our results introduce FASTKD3 as an essential component of mitochondrial respiration that may modulate energy balance in cells exposed to adverse conditions by functionally coupling mitochondrial protein synthesis to respiration.

MitProNet: A knowledgebase and analysis platform of proteome, interactome and diseases for mammalian mitochondria.

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Jiabin Wang

Full Text Available Mitochondrion plays a central role in diverse biological processes in most eukaryotes, and its dysfunctions are critically involved in a large number of diseases and the aging process. A systematic identification of mitochondrial proteomes and characterization of functional linkages among mitochondrial proteins are fundamental in understanding the mechanisms underlying biological functions and human diseases associated with mitochondria. Here we present a database MitProNet which provides a comprehensive knowledgebase for mitochondrial proteome, interactome and human diseases. First an inventory of mammalian mitochondrial proteins was compiled by widely collecting proteomic datasets, and the proteins were classified by machine learning to achieve a high-confidence list of mitochondrial proteins. The current version of MitProNet covers 1124 high-confidence proteins, and the remainders were further classified as middle- or low-confidence. An organelle-specific network of functional linkages among mitochondrial proteins was then generated by integrating genomic features encoded by a wide range of datasets including genomic context, gene expression profiles, protein-protein interactions, functional similarity and metabolic pathways. The functional-linkage network should be a valuable resource for the study of biological functions of mitochondrial proteins and human mitochondrial diseases. Furthermore, we utilized the network to predict candidate genes for mitochondrial diseases using prioritization algorithms. All proteins, functional linkages and disease candidate genes in MitProNet were annotated according to the information collected from their original sources including GO, GEO, OMIM, KEGG, MIPS, HPRD and so on. MitProNet features a user-friendly graphic visualization interface to present functional analysis of linkage networks. As an up-to-date database and analysis platform, MitProNet should be particularly helpful in comprehensive studies of

Multi-level learning: improving the prediction of protein, domain and residue interactions by allowing information flow between levels

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McDermott Drew

2009-08-01

Full Text Available Abstract Background Proteins interact through specific binding interfaces that contain many residues in domains. Protein interactions thus occur on three different levels of a concept hierarchy: whole-proteins, domains, and residues. Each level offers a distinct and complementary set of features for computationally predicting interactions, including functional genomic features of whole proteins, evolutionary features of domain families and physical-chemical features of individual residues. The predictions at each level could benefit from using the features at all three levels. However, it is not trivial as the features are provided at different granularity. Results To link up the predictions at the three levels, we propose a multi-level machine-learning framework that allows for explicit information flow between the levels. We demonstrate, using representative yeast interaction networks, that our algorithm is able to utilize complementary feature sets to make more accurate predictions at the three levels than when the three problems are approached independently. To facilitate application of our multi-level learning framework, we discuss three key aspects of multi-level learning and the corresponding design choices that we have made in the implementation of a concrete learning algorithm. 1 Architecture of information flow: we show the greater flexibility of bidirectional flow over independent levels and unidirectional flow; 2 Coupling mechanism of the different levels: We show how this can be accomplished via augmenting the training sets at each level, and discuss the prevention of error propagation between different levels by means of soft coupling; 3 Sparseness of data: We show that the multi-level framework compounds data sparsity issues, and discuss how this can be dealt with by building local models in information-rich parts of the data. Our proof-of-concept learning algorithm demonstrates the advantage of combining levels, and opens up

Specificity and commonality of the phosphoinositide-binding proteome analyzed by quantitative mass spectrometry

DEFF Research Database (Denmark)

Jungmichel, Stephanie; Sylvestersen, Kathrine B; Choudhary, Chuna Ram

2014-01-01

than the total number of phospho- or ubiquitin-binding domains. Translocation and inhibitor assays of identified PIP-binding proteins confirmed that our methodology targets direct interactors. The PIP interactome encompasses proteins from diverse cellular compartments, prominently including the nucleus...

Decision-Making Competence Predicts Domain-Specific Risk Attitudes

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Joshua eWeller

2015-05-01

Full Text Available Decision Making Competence (DMC reflects individual differences in rational responding across several classic behavioral decision-making tasks. Although it has been associated with real-world risk behavior, less is known about the degree to which DMC contributes to specific components of risk attitudes. Utilizing a psychological risk-return framework, we examined the associations between risk attitudes and DMC. Italian community residents (n = 804 completed an online DMC measure, using a subset of the original Adult-DMC battery (A-DMC; Bruine de Bruin, Parker, & Fischhoff, 2007. Participants also completed a self-reported risk attitude measure for three components of risk attitudes (risk-taking, risk perceptions, and expected benefits across six risk domains. Overall, greater performance on the DMC component scales were inversely, albeit modestly, associated with risk-taking tendencies. Structural equation modeling results revealed that DMC was associated with lower perceived expected benefits for all domains. In contrast, its association with perceived risks was more domain-specific. These analyses also revealed stronger indirect effects for the DMC  expected benefits  risk-taking than the DMC  perceived risk  risk-taking path, especially for risk behaviors that may be considered more antisocial in nature. These results suggest that DMC performance differentially impacts specific components of risk attitudes, and may be more strongly related to the evaluation of expected value of the given behavior.

The Private Legal Governance of Domain Names

DEFF Research Database (Denmark)

Schovsbo, Jens Hemmingsen

2015-01-01

. the UDRP (WIPO) and the Danish Complaints Board for Internet Domain Names (the Board) to discuss how and to what extent the domain name system balances interests between trademark owners and other users of domain names and secures the rule of law (legal certainty and predictability) with a special focus...

N-Terminal Domains in Two-Domain Proteins Are Biased to Be Shorter and Predicted to Fold Faster Than Their C-Terminal Counterparts

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Etai Jacob

2013-04-01

Full Text Available Computational analysis of proteomes in all kingdoms of life reveals a strong tendency for N-terminal domains in two-domain proteins to have shorter sequences than their neighboring C-terminal domains. Given that folding rates are affected by chain length, we asked whether the tendency for N-terminal domains to be shorter than their neighboring C-terminal domains reflects selection for faster-folding N-terminal domains. Calculations of absolute contact order, another predictor of folding rate, provide additional evidence that N-terminal domains tend to fold faster than their neighboring C-terminal domains. A possible explanation for this bias, which is more pronounced in prokaryotes than in eukaryotes, is that faster folding of N-terminal domains reduces the risk for protein aggregation during folding by preventing formation of nonnative interdomain interactions. This explanation is supported by our finding that two-domain proteins with a shorter N-terminal domain are much more abundant than those with a shorter C-terminal domain.

A critical analysis of the Mises stress criterion used in frequency domain fatigue life prediction

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Adam Niesłony

2016-10-01

Full Text Available Multiaxial fatigue failure criteria are formulated in time and frequency domain. The number of frequency domain criteria is rather small and the most popular one is the equivalent von Mises stress criterion. This criterion was elaborated by Preumont and Piefort on the basis of well-known von Mises stress concept, first proposed by Huber in 1907, and well accepted by the scientific community and engineers. It is important to know, that the criterion was developed to determine the yield stress and material effort under static load. Therefore the direct use of equivalent von Mises stress criterion for fatigue life prediction can lead to some incorrectness of theoretical and practical nature. In the present study four aspects were discussed: influence of the value of fatigue strength of tension and torsion, lack of parallelism of the SN curves, abnormal behaviour of the criterion under biaxial tensioncompression and influence of phase shift between particular stress state components. Information contained in this article will help to prevent improper use of this criterion and contributes to its better understanding

Predicting protein-protein interactions from multimodal biological data sources via nonnegative matrix tri-factorization.

Science.gov (United States)

Wang, Hua; Huang, Heng; Ding, Chris; Nie, Feiping

2013-04-01

Protein interactions are central to all the biological processes and structural scaffolds in living organisms, because they orchestrate a number of cellular processes such as metabolic pathways and immunological recognition. Several high-throughput methods, for example, yeast two-hybrid system and mass spectrometry method, can help determine protein interactions, which, however, suffer from high false-positive rates. Moreover, many protein interactions predicted by one method are not supported by another. Therefore, computational methods are necessary and crucial to complete the interactome expeditiously. In this work, we formulate the problem of predicting protein interactions from a new mathematical perspective--sparse matrix completion, and propose a novel nonnegative matrix factorization (NMF)-based matrix completion approach to predict new protein interactions from existing protein interaction networks. Through using manifold regularization, we further develop our method to integrate different biological data sources, such as protein sequences, gene expressions, protein structure information, etc. Extensive experimental results on four species, Saccharomyces cerevisiae, Drosophila melanogaster, Homo sapiens, and Caenorhabditis elegans, have shown that our new methods outperform related state-of-the-art protein interaction prediction methods.

Improvement in Protein Domain Identification Is Reached by Breaking Consensus, with the Agreement of Many Profiles and Domain Co-occurrence.

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Juliana Bernardes

2016-07-01

Full Text Available Traditional protein annotation methods describe known domains with probabilistic models representing consensus among homologous domain sequences. However, when relevant signals become too weak to be identified by a global consensus, attempts for annotation fail. Here we address the fundamental question of domain identification for highly divergent proteins. By using high performance computing, we demonstrate that the limits of state-of-the-art annotation methods can be bypassed. We design a new strategy based on the observation that many structural and functional protein constraints are not globally conserved through all species but might be locally conserved in separate clades. We propose a novel exploitation of the large amount of data available: 1. for each known protein domain, several probabilistic clade-centered models are constructed from a large and differentiated panel of homologous sequences, 2. a decision-making protocol combines outcomes obtained from multiple models, 3. a multi-criteria optimization algorithm finds the most likely protein architecture. The method is evaluated for domain and architecture prediction over several datasets and statistical testing hypotheses. Its performance is compared against HMMScan and HHblits, two widely used search methods based on sequence-profile and profile-profile comparison. Due to their closeness to actual protein sequences, clade-centered models are shown to be more specific and functionally predictive than the broadly used consensus models. Based on them, we improved annotation of Plasmodium falciparum protein sequences on a scale not previously possible. We successfully predict at least one domain for 72% of P. falciparum proteins against 63% achieved previously, corresponding to 30% of improvement over the total number of Pfam domain predictions on the whole genome. The method is applicable to any genome and opens new avenues to tackle evolutionary questions such as the reconstruction of

A Global Interactome Map of the Dengue Virus NS1 Identifies Virus Restriction and Dependency Host Factors

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Mohamed Lamine Hafirassou

2017-12-01

Full Text Available Dengue virus (DENV infections cause the most prevalent mosquito-borne viral disease worldwide, for which no therapies are available. DENV encodes seven non-structural (NS proteins that co-assemble and recruit poorly characterized host factors to form the DENV replication complex essential for viral infection. Here, we provide a global proteomic analysis of the human host factors that interact with the DENV NS1 protein. Combined with a functional RNAi screen, this study reveals a comprehensive network of host cellular processes involved in DENV infection and identifies DENV host restriction and dependency factors. We highlight an important role of RACK1 and the chaperonin TRiC (CCT and oligosaccharyltransferase (OST complexes during DENV replication. We further show that the OST complex mediates NS1 and NS4B glycosylation, and pharmacological inhibition of its N-glycosylation function strongly impairs DENV infection. In conclusion, our study provides a global interactome of the DENV NS1 and identifies host factors targetable for antiviral therapies.

Anisotropy of domain wall resistance

Science.gov (United States)

Viret; Samson; Warin; Marty; Ott; Sondergard; Klein; Fermon

2000-10-30

The resistive effect of domain walls in FePd films with perpendicular anisotropy was studied experimentally as a function of field and temperature. The films were grown directly on MgO substrates, which induces an unusual virgin magnetic configuration composed of 60 nm wide parallel stripe domains. This allowed us to carry out the first measurements of the anisotropy of domain wall resistivity in the two configurations of current perpendicular and parallel to the walls. At 18 K, we find 8.2% and 1.3% for the domain wall magnetoresistance normalized to the wall width (8 nm) in these two respective configurations. These values are consistent with the predictions of Levy and Zhang.

Predictive value of different conventional and non-conventional MRI-parameters for specific domains of cognitive function in multiple sclerosis

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Daniela Pinter

2015-01-01

Conclusions: The predictive value of distinct MRI-parameters differs for specific domains of cognitive function, with a greater impact of cortical volume, focal and diffuse white matter abnormalities on overall cognitive function, an additional role of basal ganglia iron deposition on cognitive efficiency, and thalamic and hippocampal volume on memory function. This suggests the usefulness of using multiparametric MRI to assess (microstructural correlates of different cognitive constructs.

Detecting atypical examples of known domain types by sequence similarity searching: the SBASE domain library approach.

Science.gov (United States)

Dhir, Somdutta; Pacurar, Mircea; Franklin, Dino; Gáspári, Zoltán; Kertész-Farkas, Attila; Kocsor, András; Eisenhaber, Frank; Pongor, Sándor

2010-11-01

SBASE is a project initiated to detect known domain types and predicting domain architectures using sequence similarity searching (Simon et al., Protein Seq Data Anal, 5: 39-42, 1992, Pongor et al, Nucl. Acids. Res. 21:3111-3115, 1992). The current approach uses a curated collection of domain sequences - the SBASE domain library - and standard similarity search algorithms, followed by postprocessing which is based on a simple statistics of the domain similarity network (http://hydra.icgeb.trieste.it/sbase/). It is especially useful in detecting rare, atypical examples of known domain types which are sometimes missed even by more sophisticated methodologies. This approach does not require multiple alignment or machine learning techniques, and can be a useful complement to other domain detection methodologies. This article gives an overview of the project history as well as of the concepts and principles developed within this the project.

Rating knowledge sharing in cross-domain collaborative filtering.

Science.gov (United States)

Li, Bin; Zhu, Xingquan; Li, Ruijiang; Zhang, Chengqi

2015-05-01

Cross-domain collaborative filtering (CF) aims to share common rating knowledge across multiple related CF domains to boost the CF performance. In this paper, we view CF domains as a 2-D site-time coordinate system, on which multiple related domains, such as similar recommender sites or successive time-slices, can share group-level rating patterns. We propose a unified framework for cross-domain CF over the site-time coordinate system by sharing group-level rating patterns and imposing user/item dependence across domains. A generative model, say ratings over site-time (ROST), which can generate and predict ratings for multiple related CF domains, is developed as the basic model for the framework. We further introduce cross-domain user/item dependence into ROST and extend it to two real-world cross-domain CF scenarios: 1) ROST (sites) for alleviating rating sparsity in the target domain, where multiple similar sites are viewed as related CF domains and some items in the target domain depend on their correspondences in the related ones; and 2) ROST (time) for modeling user-interest drift over time, where a series of time-slices are viewed as related CF domains and a user at current time-slice depends on herself in the previous time-slice. All these ROST models are instances of the proposed unified framework. The experimental results show that ROST (sites) can effectively alleviate the sparsity problem to improve rating prediction performance and ROST (time) can clearly track and visualize user-interest drift over time.

Searching for cellular partners of hantaviral nonstructural protein NSs: Y2H screening of mouse cDNA library and analysis of cellular interactome.

Science.gov (United States)

Rönnberg, Tuomas; Jääskeläinen, Kirsi; Blot, Guillaume; Parviainen, Ville; Vaheri, Antti; Renkonen, Risto; Bouloy, Michele; Plyusnin, Alexander

2012-01-01

Hantaviruses (Bunyaviridae) are negative-strand RNA viruses with a tripartite genome. The small (S) segment encodes the nucleocapsid protein and, in some hantaviruses, also the nonstructural protein (NSs). The aim of this study was to find potential cellular partners for the hantaviral NSs protein. Toward this aim, yeast two-hybrid (Y2H) screening of mouse cDNA library was performed followed by a search for potential NSs protein counterparts via analyzing a cellular interactome. The resulting interaction network was shown to form logical, clustered structures. Furthermore, several potential binding partners for the NSs protein, for instance ACBD3, were identified and, to prove the principle, interaction between NSs and ACBD3 proteins was demonstrated biochemically.

System Identification A Frequency Domain Approach

CERN Document Server

Pintelon, Rik

2012-01-01

System identification is a general term used to describe mathematical tools and algorithms that build dynamical models from measured data. Used for prediction, control, physical interpretation, and the designing of any electrical systems, they are vital in the fields of electrical, mechanical, civil, and chemical engineering. Focusing mainly on frequency domain techniques, System Identification: A Frequency Domain Approach, Second Edition also studies in detail the similarities and differences with the classical time domain approach. It high??lights many of the important steps in the identi

Bioinformatics and moonlighting proteins

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Sergio eHernández

2015-06-01

Full Text Available Multitasking or moonlighting is the capability of some proteins to execute two or more biochemical functions. Usually, moonlighting proteins are experimentally revealed by serendipity. For this reason, it would be helpful that Bioinformatics could predict this multifunctionality, especially because of the large amounts of sequences from genome projects. In the present work, we analyse and describe several approaches that use sequences, structures, interactomics and current bioinformatics algorithms and programs to try to overcome this problem. Among these approaches are: a remote homology searches using Psi-Blast, b detection of functional motifs and domains, c analysis of data from protein-protein interaction databases (PPIs, d match the query protein sequence to 3D databases (i.e., algorithms as PISITE, e mutation correlation analysis between amino acids by algorithms as MISTIC. Programs designed to identify functional motif/domains detect mainly the canonical function but usually fail in the detection of the moonlighting one, Pfam and ProDom being the best methods. Remote homology search by Psi-Blast combined with data from interactomics databases (PPIs have the best performance. Structural information and mutation correlation analysis can help us to map the functional sites. Mutation correlation analysis can only be used in very specific situations –it requires the existence of multialigned family protein sequences - but can suggest how the evolutionary process of second function acquisition took place. The multitasking protein database MultitaskProtDB (http://wallace.uab.es/multitask/, previously published by our group, has been used as a benchmark for the all of the analyses.

Delta-Domain Predictive Control and Identification for Control

DEFF Research Database (Denmark)

Lauritsen, Morten Bach

1997-01-01

The present thesis is concerned with different aspects of modelling, control and identification of linear systems. Traditionally, discrete-time sampled-data systems are represented using shift-operator parametrizations. Such parametrizations are not suitable at fast sampling rates. An alternative...... minimum-variance predictor as a special case and to have a well-defined continuous-time limit. By means of this new prediction method a unified framework for discrete-time and continuous-time predictive control algorithms is developed. This contains a continuous-time like discrete-time predictive...... controller which is insensitive to the choice of sampling period and has a well-defined limit in the continuous-time case. Also more conventional discrete-time predictive control methods may be described within the unified approach. The predictive control algorithms are extended to frequency weighted...

Predicting homophobic behavior among heterosexual youth: domain general and sexual orientation-specific factors at the individual and contextual level.

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Poteat, V Paul; DiGiovanni, Craig D; Scheer, Jillian R

2013-03-01

As a form of bias-based harassment, homophobic behavior remains prominent in schools. Yet, little attention has been given to factors that underlie it, aside from bullying and sexual prejudice. Thus, we examined multiple domain general (empathy, perspective-taking, classroom respect norms) and sexual orientation-specific factors (sexual orientation identity importance, number of sexual minority friends, parents' sexual minority attitudes, media messages). We documented support for a model in which these sets of factors converged to predict homophobic behavior, mediated through bullying and prejudice, among 581 students in grades 9-12 (55 % female). The structural equation model indicated that, with the exception of media messages, these additional factors predicted levels of prejudice and bullying, which in turn predicted the likelihood of students to engage in homophobic behavior. These findings highlight the importance of addressing multiple interrelated factors in efforts to reduce bullying, prejudice, and discrimination among youth.

Domain-Specific and Domain-General Training to Improve Kindergarten Children’s Mathematics

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Geetha B. Ramani

2017-12-01

Full Text Available Ensuring that kindergarten children have a solid foundation in early numerical knowledge is of critical importance for later mathematical achievement. In this study, we targeted improving the numerical knowledge of kindergarteners (n = 81 from primarily low-income backgrounds using two approaches: one targeting their conceptual knowledge, specifically, their understanding of numerical magnitudes; and the other targeting their underlying cognitive system, specifically, their working memory. Both interventions involved playing game-like activities on tablet computers over the course of several sessions. As predicted, both interventions improved children’s numerical magnitude knowledge as compared to a no-contact control group, suggesting that both domain-specific and domain-general interventions facilitate mathematical learning. Individual differences in effort during the working memory game, but not the number knowledge training game predicted children’s improvements in number line estimation. The results demonstrate the potential of using a rapidly growing technology in early childhood classrooms to promote young children’s numerical knowledge.

Domain-based small molecule binding site annotation

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Dumontier Michel

2006-03-01

Full Text Available Abstract Background Accurate small molecule binding site information for a protein can facilitate studies in drug docking, drug discovery and function prediction, but small molecule binding site protein sequence annotation is sparse. The Small Molecule Interaction Database (SMID, a database of protein domain-small molecule interactions, was created using structural data from the Protein Data Bank (PDB. More importantly it provides a means to predict small molecule binding sites on proteins with a known or unknown structure and unlike prior approaches, removes large numbers of false positive hits arising from transitive alignment errors, non-biologically significant small molecules and crystallographic conditions that overpredict ion binding sites. Description Using a set of co-crystallized protein-small molecule structures as a starting point, SMID interactions were generated by identifying protein domains that bind to small molecules, using NCBI's Reverse Position Specific BLAST (RPS-BLAST algorithm. SMID records are available for viewing at http://smid.blueprint.org. The SMID-BLAST tool provides accurate transitive annotation of small-molecule binding sites for proteins not found in the PDB. Given a protein sequence, SMID-BLAST identifies domains using RPS-BLAST and then lists potential small molecule ligands based on SMID records, as well as their aligned binding sites. A heuristic ligand score is calculated based on E-value, ligand residue identity and domain entropy to assign a level of confidence to hits found. SMID-BLAST predictions were validated against a set of 793 experimental small molecule interactions from the PDB, of which 472 (60% of predicted interactions identically matched the experimental small molecule and of these, 344 had greater than 80% of the binding site residues correctly identified. Further, we estimate that 45% of predictions which were not observed in the PDB validation set may be true positives. Conclusion By

Ferroelectric negative capacitance domain dynamics

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Hoffmann, Michael; Khan, Asif Islam; Serrao, Claudy; Lu, Zhongyuan; Salahuddin, Sayeef; Pešić, Milan; Slesazeck, Stefan; Schroeder, Uwe; Mikolajick, Thomas

2018-05-01

Transient negative capacitance effects in epitaxial ferroelectric Pb(Zr0.2Ti0.8)O3 capacitors are investigated with a focus on the dynamical switching behavior governed by domain nucleation and growth. Voltage pulses are applied to a series connection of the ferroelectric capacitor and a resistor to directly measure the ferroelectric negative capacitance during switching. A time-dependent Ginzburg-Landau approach is used to investigate the underlying domain dynamics. The transient negative capacitance is shown to originate from reverse domain nucleation and unrestricted domain growth. However, with the onset of domain coalescence, the capacitance becomes positive again. The persistence of the negative capacitance state is therefore limited by the speed of domain wall motion. By changing the applied electric field, capacitor area or external resistance, this domain wall velocity can be varied predictably over several orders of magnitude. Additionally, detailed insights into the intrinsic material properties of the ferroelectric are obtainable through these measurements. A new method for reliable extraction of the average negative capacitance of the ferroelectric is presented. Furthermore, a simple analytical model is developed, which accurately describes the negative capacitance transient time as a function of the material properties and the experimental boundary conditions.

Cross-Genome Comparisons of Newly Identified Domains in Mycoplasma gallisepticum and Domain Architectures with Other Mycoplasma species

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Chandra Sekhar Reddy Chilamakuri

2011-01-01

Full Text Available Accurate functional annotation of protein sequences is hampered by important factors such as the failure of sequence search methods to identify relationships and the inherent diversity in function of proteins related at low sequence similarities. Earlier, we had employed intermediate sequence search approach to establish new domain relationships in the unassigned regions of gene products at the whole genome level by taking Mycoplasma gallisepticum as a specific example and established new domain relationships. In this paper, we report a detailed comparison of the conservation status of the domain and domain architectures of the gene products that bear our newly predicted domains amongst 14 other Mycoplasma genomes and reported the probable implications for the organisms. Some of the domain associations, observed in Mycoplasma that afflict humans and other non-human primates, are involved in regulation of solute transport and DNA binding suggesting specific modes of host-pathogen interactions.

Generating Dynamic Persistence in the Time Domain

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Guerrero, A.; Smith, L. A.; Smith, L. A.; Kaplan, D. T.

2001-12-01

Many dynamical systems present long-range correlations. Physically, these systems vary from biological to economical, including geological or urban systems. Important geophysical candidates for this type of behaviour include weather (or climate) and earthquake sequences. Persistence is characterised by slowly decaying correlation function; that, in theory, never dies out. The Persistence exponent reflects the degree of memory in the system and much effort has been expended creating and analysing methods that successfully estimate this parameter and model data that exhibits persistence. The most widely used methods for generating long correlated time series are not dynamical systems in the time domain, but instead are derived from a given spectral density. Little attention has been drawn to modelling persistence in the time domain. The time domain approach has the advantage that an observation at certain time can be calculated using previous observations which is particularly suitable when investigating the predictability of a long memory process. We will describe two of these methods in the time domain. One is a traditional approach using fractional ARIMA (autoregressive and moving average) models; the second uses a novel approach to extending a given series using random Fourier basis functions. The statistical quality of the two methods is compared, and they are contrasted with weather data which shows, reportedly, persistence. The suitability of this approach both for estimating predictability and for making predictions is discussed.

CARF and WYL domains: ligand-binding regulators of prokaryotic defense systems

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Kira eMakarova

2014-04-01

Full Text Available CRISPR-Cas adaptive immunity systems of bacteria and archaea insert fragments of virus or plasmid DNA as spacer sequences into CRISPR repeat loci. Processed transcripts encompassing these spacers guide the cleavage of the cognate foreign DNA or RNA. Most CRISPR-Cas loci, in addition to recognized cas genes, also include genes that are not directly implicated in spacer acquisition, CRISPR transcript processing or interference. Here we comprehensively analyze sequences, structures and genomic neighborhoods of one of the most widespread groups of such genes that encode proteins containing a predicted nucleotide-binding domain with a Rossmann-like fold, which we denote CARF (CRISPR-associated Rossmann fold. Several CARF protein structures have been determined but functional characterization of these proteins is lacking. The CARF domain is most frequently combined with a C-terminal winged helix-turn-helix DNA-binding domain and effector domains most of which are predicted to possess DNase or RNase activity. Divergent CARF domains are also found in RtcR proteins, sigma-54 dependent regulators of the rtc RNA repair operon. CARF genes frequently co-occur with those coding for proteins containing the WYL domain with the Sm-like SH3 β-barrel fold, which is also predicted to bind ligands. CRISPR-Cas and possibly other defense systems are predicted to be transcriptionally regulated by multiple ligand-binding proteins containing WYL and CARF domains which sense modified nucleotides and nucleotide derivatives generated during virus infection. We hypothesize that CARF domains also transmit the signal from the bound ligand to the fused effector domains which attack either alien or self nucleic acids, resulting, respectively, in immunity complementing the CRISPR-Cas action or in dormancy/programmed cell death.

Self-Concept Predicts Academic Achievement Across Levels of the Achievement Distribution: Domain Specificity for Math and Reading.

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Susperreguy, Maria Ines; Davis-Kean, Pamela E; Duckworth, Kathryn; Chen, Meichu

2017-09-18

This study examines whether self-concept of ability in math and reading predicts later math and reading attainment across different levels of achievement. Data from three large-scale longitudinal data sets, the Avon Longitudinal Study of Parents and Children, National Institute of Child Health and Human Development-Study of Early Child Care and Youth Development, and Panel Study of Income Dynamics-Child Development Supplement, were used to answer this question by employing quantile regression analyses. After controlling for demographic variables, child characteristics, and early ability, the findings indicate that self-concept of ability in math and reading predicts later achievement in each respective domain across all quantile levels of achievement. These results were replicated across the three data sets representing different populations and provide robust evidence for the role of self-concept of ability in understanding achievement from early childhood to adolescence across the spectrum of performance (low to high). © 2017 The Authors. Child Development © 2017 Society for Research in Child Development, Inc.

Using the Positive and Negative Syndrome Scale (PANSS) to Define Different Domains of Negative Symptoms: Prediction of Everyday Functioning by Impairments in Emotional Expression and Emotional Experience

OpenAIRE

Harvey, Philip D.; Khan, Anzalee; Keefe, Richard S. E.

2017-01-01

Background: Reduced emotional experience and expression are two domains of negative symptoms. The authors assessed these two domains of negative symptoms using previously developed Positive and Negative Syndrome Scale (PANSS) factors. Using an existing dataset, the authors predicted three different elements of everyday functioning (social, vocational, and everyday activities) with these two factors, as well as with performance on measures of functional capacity. Methods: A large (n=630) sampl...

A TALE-inspired computational screen for proteins that contain approximate tandem repeats.

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Perycz, Malgorzata; Krwawicz, Joanna; Bochtler, Matthias

2017-01-01

TAL (transcription activator-like) effectors (TALEs) are bacterial proteins that are secreted from bacteria to plant cells to act as transcriptional activators. TALEs and related proteins (RipTALs, BurrH, MOrTL1 and MOrTL2) contain approximate tandem repeats that differ in conserved positions that define specificity. Using PERL, we screened ~47 million protein sequences for TALE-like architecture characterized by approximate tandem repeats (between 30 and 43 amino acids in length) and sequence variability in conserved positions, without requiring sequence similarity to TALEs. Candidate proteins were scored according to their propensity for nuclear localization, secondary structure, repeat sequence complexity, as well as covariation and predicted structural proximity of variable residues. Biological context was tentatively inferred from co-occurrence of other domains and interactome predictions. Approximate repeats with TALE-like features that merit experimental characterization were found in a protein of chestnut blight fungus, a eukaryotic plant pathogen.

Single-molecule folding mechanism of an EF-hand neuronal calcium sensor

DEFF Research Database (Denmark)

Heiðarsson, Pétur Orri; Otazo, Mariela R.; Bellucci, Luca

2013-01-01

EF-hand calcium sensors respond structurally to changes in intracellular Ca2+ concentration, triggering diverse cellular responses and resulting in broad interactomes. Despite impressive advances in decoding their structure-function relationships, the folding mechanism of neuronal calcium sensors...... of the N domain, showing striking interdomain dependence. Molecular dynamics results reveal the atomistic details of the unfolding process and rationalize the different domain stabilities during mechanical unfolding. Through constant-force experiments and hidden Markov model analysis, the free energy...

From link-prediction in brain connectomes and protein interactomes to the local-community-paradigm in complex networks.

KAUST Repository

Cannistraci, C.V.

2013-04-08

Growth and remodelling impact the network topology of complex systems, yet a general theory explaining how new links arise between existing nodes has been lacking, and little is known about the topological properties that facilitate link-prediction. Here we investigate the extent to which the connectivity evolution of a network might be predicted by mere topological features. We show how a link/community-based strategy triggers substantial prediction improvements because it accounts for the singular topology of several real networks organised in multiple local communities - a tendency here named local-community-paradigm (LCP). We observe that LCP networks are mainly formed by weak interactions and characterise heterogeneous and dynamic systems that use self-organisation as a major adaptation strategy. These systems seem designed for global delivery of information and processing via multiple local modules. Conversely, non-LCP networks have steady architectures formed by strong interactions, and seem designed for systems in which information/energy storage is crucial.

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.

Integration of multiple biological features yields high confidence human protein interactome.

Science.gov (United States)

Karagoz, Kubra; Sevimoglu, Tuba; Arga, Kazim Yalcin

2016-08-21

The biological function of a protein is usually determined by its physical interaction with other proteins. Protein-protein interactions (PPIs) are identified through various experimental methods and are stored in curated databases. The noisiness of the existing PPI data is evident, and it is essential that a more reliable data is generated. Furthermore, the selection of a set of PPIs at different confidence levels might be necessary for many studies. Although different methodologies were introduced to evaluate the confidence scores for binary interactions, a highly reliable, almost complete PPI network of Homo sapiens is not proposed yet. The quality and coverage of human protein interactome need to be improved to be used in various disciplines, especially in biomedicine. In the present work, we propose an unsupervised statistical approach to assign confidence scores to PPIs of H. sapiens. To achieve this goal PPI data from six different databases were collected and a total of 295,288 non-redundant interactions between 15,950 proteins were acquired. The present scoring system included the context information that was assigned to PPIs derived from eight biological attributes. A high confidence network, which included 147,923 binary interactions between 13,213 proteins, had scores greater than the cutoff value of 0.80, for which sensitivity, specificity, and coverage were 94.5%, 80.9%, and 82.8%, respectively. We compared the present scoring method with others for evaluation. Reducing the noise inherent in experimental PPIs via our scoring scheme increased the accuracy significantly. As it was demonstrated through the assessment of process and cancer subnetworks, this study allows researchers to construct and analyze context-specific networks via valid PPI sets and one can easily achieve subnetworks around proteins of interest at a specified confidence level. Copyright © 2016 Elsevier Ltd. All rights reserved.

Individual globular domains and domain unfolding visualized in overstretched titin molecules with atomic force microscopy.

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Zsolt Mártonfalvi

Full Text Available Titin is a giant elastomeric protein responsible for the generation of passive muscle force. Mechanical force unfolds titin's globular domains, but the exact structure of the overstretched titin molecule is not known. Here we analyzed, by using high-resolution atomic force microscopy, the structure of titin molecules overstretched with receding meniscus. The axial contour of the molecules was interrupted by topographical gaps with a mean width of 27.7 nm that corresponds well to the length of an unfolded globular (immunoglobulin and fibronectin domain. The wide gap-width distribution suggests, however, that additional mechanisms such as partial domain unfolding and the unfolding of neighboring domain multimers may also be present. In the folded regions we resolved globules with an average spacing of 5.9 nm, which is consistent with a titin chain composed globular domains with extended interdomain linker regions. Topographical analysis allowed us to allocate the most distal unfolded titin region to the kinase domain, suggesting that this domain systematically unfolds when the molecule is exposed to overstretching forces. The observations support the prediction that upon the action of stretching forces the N-terminal ß-sheet of the titin kinase unfolds, thus exposing the enzyme's ATP-binding site and hence contributing to the molecule's mechanosensory function.

Predictive value of different conventional and non-conventional MRI-parameters for specific domains of cognitive function in multiple sclerosis.

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Pinter, Daniela; Khalil, Michael; Pichler, Alexander; Langkammer, Christian; Ropele, Stefan; Marschik, Peter B; Fuchs, Siegrid; Fazekas, Franz; Enzinger, Christian

2015-01-01

While many studies correlated cognitive function with changes in brain morphology in multiple sclerosis (MS), few of them used a multi-parametric approach in a single dataset so far. We thus here assessed the predictive value of different conventional and quantitative MRI-parameters both for overall and domain-specific cognitive performance in MS patients from a single center. 69 patients (17 clinically isolated syndrome, 47 relapsing-remitting MS, 5 secondary-progressive MS) underwent the "Brief Repeatable Battery of Neuropsychological Tests" assessing overall cognition, cognitive efficiency and memory function as well as MRI at 3 Tesla to obtain T2-lesion load (T2-LL), normalized brain volume (global brain volume loss), normalized cortical volume (NCV), normalized thalamic volume (NTV), normalized hippocampal volume (NHV), normalized caudate nuclei volume (NCNV), basal ganglia R2* values (iron deposition) and magnetization transfer ratios (MTRs) for cortex and normal appearing brain tissue (NABT). Regression models including clinical, demographic variables and MRI-parameters explained 22-27% of variance of overall cognition, 17-26% of cognitive efficiency and 22-23% of memory. NCV, T2-LL and MTR of NABT were the strongest predictors of overall cognitive function. Cognitive efficiency was best predicted by NCV, T2-LL and iron deposition in the basal ganglia. NTV was the strongest predictor for memory function and NHV was particularly related to memory function. The predictive value of distinct MRI-parameters differs for specific domains of cognitive function, with a greater impact of cortical volume, focal and diffuse white matter abnormalities on overall cognitive function, an additional role of basal ganglia iron deposition on cognitive efficiency, and thalamic and hippocampal volume on memory function. This suggests the usefulness of using multiparametric MRI to assess (micro)structural correlates of different cognitive constructs.

The Relationship between Defense Patterns and DSM-5 Maladaptive Personality Domains

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Granieri, Antonella; La Marca, Luana; Mannino, Giuseppe; Giunta, Serena; Guglielmucci, Fanny; Schimmenti, Adriano

2017-01-01

Aim: Research has extensively examined the relationship between defense mechanisms (DM) and personality traits. However, no study to date has explored if specific defenses (alone or in combination) are able to predict dysfunctional variants of personality domains, as conceived in the alternative DSM-5 model for personality disorders. This study aimed to investigate the relationship between DMs and DSM-5 maladaptive personality domains among adults. Materials and Methods: Three hundred and twenty-eight adults aged between 18 and 64 years old completed measures on DMs and maladapive personality domains. Regression analyses were performed to determine which DMs predicted the maladaptive personality domains of negative affectivity, detachment, antagonism, disinhibition, and psychoticism. Results: According to psychoanalytic literature, results showed that immature defenses positively predicted maladaptive personality domain scores, whereas mature defenses were generally related with better personality functioning. Moreover, different defense patterns emerged as significant predictors of the maladaptive personality domains comprised in the alternative DSM-5 model for personality disorder. Discussion: Our findings support the view that defense patterns represent core components of personality and its disorders, and suggest that an increased use of immature defenses and a reduced use of mature defenses have a negative impact on the development of personality. PMID:29163301

Detection of dysregulated protein-association networks by high-throughput proteomics predicts cancer vulnerabilities.

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Lapek, John D; Greninger, Patricia; Morris, Robert; Amzallag, Arnaud; Pruteanu-Malinici, Iulian; Benes, Cyril H; Haas, Wilhelm

2017-10-01

The formation of protein complexes and the co-regulation of the cellular concentrations of proteins are essential mechanisms for cellular signaling and for maintaining homeostasis. Here we use isobaric-labeling multiplexed proteomics to analyze protein co-regulation and show that this allows the identification of protein-protein associations with high accuracy. We apply this 'interactome mapping by high-throughput quantitative proteome analysis' (IMAHP) method to a panel of 41 breast cancer cell lines and show that deviations of the observed protein co-regulations in specific cell lines from the consensus network affects cellular fitness. Furthermore, these aberrant interactions serve as biomarkers that predict the drug sensitivity of cell lines in screens across 195 drugs. We expect that IMAHP can be broadly used to gain insight into how changing landscapes of protein-protein associations affect the phenotype of biological systems.

A Simple PB/LIE Free Energy Function Accurately Predicts the Peptide Binding Specificity of the Tiam1 PDZ Domain.

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Panel, Nicolas; Sun, Young Joo; Fuentes, Ernesto J; Simonson, Thomas

2017-01-01

PDZ domains generally bind short amino acid sequences at the C-terminus of target proteins, and short peptides can be used as inhibitors or model ligands. Here, we used experimental binding assays and molecular dynamics simulations to characterize 51 complexes involving the Tiam1 PDZ domain and to test the performance of a semi-empirical free energy function. The free energy function combined a Poisson-Boltzmann (PB) continuum electrostatic term, a van der Waals interaction energy, and a surface area term. Each term was empirically weighted, giving a Linear Interaction Energy or "PB/LIE" free energy. The model yielded a mean unsigned deviation of 0.43 kcal/mol and a Pearson correlation of 0.64 between experimental and computed free energies, which was superior to a Null model that assumes all complexes have the same affinity. Analyses of the models support several experimental observations that indicate the orientation of the α 2 helix is a critical determinant for peptide specificity. The models were also used to predict binding free energies for nine new variants, corresponding to point mutants of the Syndecan1 and Caspr4 peptides. The predictions did not reveal improved binding; however, they suggest that an unnatural amino acid could be used to increase protease resistance and peptide lifetimes in vivo . The overall performance of the model should allow its use in the design of new PDZ ligands in the future.

A Simple PB/LIE Free Energy Function Accurately Predicts the Peptide Binding Specificity of the Tiam1 PDZ Domain

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Nicolas Panel

2017-09-01

Full Text Available PDZ domains generally bind short amino acid sequences at the C-terminus of target proteins, and short peptides can be used as inhibitors or model ligands. Here, we used experimental binding assays and molecular dynamics simulations to characterize 51 complexes involving the Tiam1 PDZ domain and to test the performance of a semi-empirical free energy function. The free energy function combined a Poisson-Boltzmann (PB continuum electrostatic term, a van der Waals interaction energy, and a surface area term. Each term was empirically weighted, giving a Linear Interaction Energy or “PB/LIE” free energy. The model yielded a mean unsigned deviation of 0.43 kcal/mol and a Pearson correlation of 0.64 between experimental and computed free energies, which was superior to a Null model that assumes all complexes have the same affinity. Analyses of the models support several experimental observations that indicate the orientation of the α2 helix is a critical determinant for peptide specificity. The models were also used to predict binding free energies for nine new variants, corresponding to point mutants of the Syndecan1 and Caspr4 peptides. The predictions did not reveal improved binding; however, they suggest that an unnatural amino acid could be used to increase protease resistance and peptide lifetimes in vivo. The overall performance of the model should allow its use in the design of new PDZ ligands in the future.

The SH2 Domain Interaction Landscape

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Michele Tinti

2013-04-01

Full Text Available Members of the SH2 domain family modulate signal transduction by binding to short peptides containing phosphorylated tyrosines. Each domain displays a distinct preference for the sequence context of the phosphorylated residue. We have developed a high-density peptide chip technology that allows for probing of the affinity of most SH2 domains for a large fraction of the entire complement of tyrosine phosphopeptides in the human proteome. Using this technique, we have experimentally identified thousands of putative SH2-peptide interactions for more than 70 different SH2 domains. By integrating this rich data set with orthogonal context-specific information, we have assembled an SH2-mediated probabilistic interaction network, which we make available as a community resource in the PepspotDB database. A predicted dynamic interaction between the SH2 domains of the tyrosine phosphatase SHP2 and the phosphorylated tyrosine in the extracellular signal-regulated kinase activation loop was validated by experiments in living cells.

Cytoprophet: a Cytoscape plug-in for protein and domain interaction networks inference.

Science.gov (United States)

Morcos, Faruck; Lamanna, Charles; Sikora, Marcin; Izaguirre, Jesús

2008-10-01

Cytoprophet is a software tool that allows prediction and visualization of protein and domain interaction networks. It is implemented as a plug-in of Cytoscape, an open source software framework for analysis and visualization of molecular networks. Cytoprophet implements three algorithms that predict new potential physical interactions using the domain composition of proteins and experimental assays. The algorithms for protein and domain interaction inference include maximum likelihood estimation (MLE) using expectation maximization (EM); the set cover approach maximum specificity set cover (MSSC) and the sum-product algorithm (SPA). After accepting an input set of proteins with Uniprot ID/Accession numbers and a selected prediction algorithm, Cytoprophet draws a network of potential interactions with probability scores and GO distances as edge attributes. A network of domain interactions between the domains of the initial protein list can also be generated. Cytoprophet was designed to take advantage of the visual capabilities of Cytoscape and be simple to use. An example of inference in a signaling network of myxobacterium Myxococcus xanthus is presented and available at Cytoprophet's website. http://cytoprophet.cse.nd.edu.

Entropy based classifier for cross-domain opinion mining

Directory of Open Access Journals (Sweden)

Jyoti S. Deshmukh

2018-01-01

Full Text Available In recent years, the growth of social network has increased the interest of people in analyzing reviews and opinions for products before they buy them. Consequently, this has given rise to the domain adaptation as a prominent area of research in sentiment analysis. A classifier trained from one domain often gives poor results on data from another domain. Expression of sentiment is different in every domain. The labeling cost of each domain separately is very high as well as time consuming. Therefore, this study has proposed an approach that extracts and classifies opinion words from one domain called source domain and predicts opinion words of another domain called target domain using a semi-supervised approach, which combines modified maximum entropy and bipartite graph clustering. A comparison of opinion classification on reviews on four different product domains is presented. The results demonstrate that the proposed method performs relatively well in comparison to the other methods. Comparison of SentiWordNet of domain-specific and domain-independent words reveals that on an average 72.6% and 88.4% words, respectively, are correctly classified.

Structure of the C-terminal heme-binding domain of THAP domain containing protein 4 from Homo sapiens

Energy Technology Data Exchange (ETDEWEB)

Bianchetti, Christopher M.; Bingman, Craig A.; Phillips, Jr., George N. (UW)

2012-03-15

The thanatos (the Greek god of death)-associated protein (THAP) domain is a sequence-specific DNA-binding domain that contains a C2-CH (Cys-Xaa{sub 2-4}-Cys-Xaa{sub 35-50}-Cys-Xaa{sub 2}-His) zinc finger that is similar to the DNA domain of the P element transposase from Drosophila. THAP-containing proteins have been observed in the proteome of humans, pigs, cows, chickens, zebrafish, Drosophila, C. elegans, and Xenopus. To date, there are no known THAP domain proteins in plants, yeast, or bacteria. There are 12 identified human THAP domain-containing proteins (THAP0-11). In all human THAP protein, the THAP domain is located at the N-terminus and is {approx}90 residues in length. Although all of the human THAP-containing proteins have a homologous N-terminus, there is extensive variation in both the predicted structure and length of the remaining protein. Even though the exact function of these THAP proteins is not well defined, there is evidence that they play a role in cell proliferation, apoptosis, cell cycle modulation, chromatin modification, and transcriptional regulation. THAP-containing proteins have also been implicated in a number of human disease states including heart disease, neurological defects, and several types of cancers. Human THAP4 is a 577-residue protein of unknown function that is proposed to bind DNA in a sequence-specific manner similar to THAP1 and has been found to be upregulated in response to heat shock. THAP4 is expressed in a relatively uniform manner in a broad range of tissues and appears to be upregulated in lymphoma cells and highly expressed in heart cells. The C-terminal domain of THAP4 (residues 415-577), designated here as cTHAP4, is evolutionarily conserved and is observed in all known THAP4 orthologs. Several single-domain proteins lacking a THAP domain are found in plants and bacteria and show significant levels of homology to cTHAP4. It appears that cTHAP4 belongs to a large class of proteins that have yet to be fully

Re-conceptualising prenatal life stressors in predicting post-partum depression: cumulative-, specific-, and domain-specific approaches to calculating risk.

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Liu, Cindy H; Tronick, Ed

2013-09-01

Prenatal life stress predicts post-partum depression (PPD); however, studies generally examine individual stressors (a specific approach) or the summation of such exposure (a cumulative approach) and their associations with PPD. Such approaches may oversimplify prenatal life stress as a risk factor for PPD. We evaluated approaches in assessing prenatal life stress as a predictor of PPD diagnosis, including a domain-specific approach that captures cumulative life stress while accounting for stress across different life stress domains: financial, relational, and physical health. The Pregnancy Risk Assessment Monitoring System, a population-based survey, was used to analyse the association of prenatal life stressors with PPD diagnoses among 3566 New York City post-partum women. Specific stressors were not associated with PPD diagnosis after controlling for sociodemographic variables. Exposure to a greater number of stressors was associated with PPD diagnosis, even after adjusting for both sociodemographic variables and specific stressors [odds ratio (OR) = 3.1, 95% confidence interval (CI) = 1.5, 6.7]. Individuals reporting a moderate-to-high number of financial problems along with a moderate-to-high number of physical problems were at greater odds of PPD (OR = 4.2, 95% CI = 1.2, 15.3); those with a moderate-to-high number of problems in all three domains were at over fivefold increased odds of PPD (OR = 5.5, CI = 1.1, 28.5). In assessing prenatal stress, clinicians should consider the extent to which stressors occur across different life domains; this association appears stronger with PPD diagnosis than simple assessments of individual stressors, which typically overestimate risk or cumulative exposures. © 2013 John Wiley & Sons Ltd.

SECOM: A novel hash seed and community detection based-approach for genome-scale protein domain identification

KAUST Repository

Fan, Ming

2012-06-28

With rapid advances in the development of DNA sequencing technologies, a plethora of high-throughput genome and proteome data from a diverse spectrum of organisms have been generated. The functional annotation and evolutionary history of proteins are usually inferred from domains predicted from the genome sequences. Traditional database-based domain prediction methods cannot identify novel domains, however, and alignment-based methods, which look for recurring segments in the proteome, are computationally demanding. Here, we propose a novel genome-wide domain prediction method, SECOM. Instead of conducting all-against-all sequence alignment, SECOM first indexes all the proteins in the genome by using a hash seed function. Local similarity can thus be detected and encoded into a graph structure, in which each node represents a protein sequence and each edge weight represents the shared hash seeds between the two nodes. SECOM then formulates the domain prediction problem as an overlapping community-finding problem in this graph. A backward graph percolation algorithm that efficiently identifies the domains is proposed. We tested SECOM on five recently sequenced genomes of aquatic animals. Our tests demonstrated that SECOM was able to identify most of the known domains identified by InterProScan. When compared with the alignment-based method, SECOM showed higher sensitivity in detecting putative novel domains, while it was also three orders of magnitude faster. For example, SECOM was able to predict a novel sponge-specific domain in nucleoside-triphosphatase (NTPases). Furthermore, SECOM discovered two novel domains, likely of bacterial origin, that are taxonomically restricted to sea anemone and hydra. SECOM is an open-source program and available at http://sfb.kaust.edu.sa/Pages/Software.aspx. © 2012 Fan et al.

SECOM: A novel hash seed and community detection based-approach for genome-scale protein domain identification

KAUST Repository

Fan, Ming; Wong, Ka-Chun; Ryu, Tae Woo; Ravasi, Timothy; Gao, Xin

2012-01-01

With rapid advances in the development of DNA sequencing technologies, a plethora of high-throughput genome and proteome data from a diverse spectrum of organisms have been generated. The functional annotation and evolutionary history of proteins are usually inferred from domains predicted from the genome sequences. Traditional database-based domain prediction methods cannot identify novel domains, however, and alignment-based methods, which look for recurring segments in the proteome, are computationally demanding. Here, we propose a novel genome-wide domain prediction method, SECOM. Instead of conducting all-against-all sequence alignment, SECOM first indexes all the proteins in the genome by using a hash seed function. Local similarity can thus be detected and encoded into a graph structure, in which each node represents a protein sequence and each edge weight represents the shared hash seeds between the two nodes. SECOM then formulates the domain prediction problem as an overlapping community-finding problem in this graph. A backward graph percolation algorithm that efficiently identifies the domains is proposed. We tested SECOM on five recently sequenced genomes of aquatic animals. Our tests demonstrated that SECOM was able to identify most of the known domains identified by InterProScan. When compared with the alignment-based method, SECOM showed higher sensitivity in detecting putative novel domains, while it was also three orders of magnitude faster. For example, SECOM was able to predict a novel sponge-specific domain in nucleoside-triphosphatase (NTPases). Furthermore, SECOM discovered two novel domains, likely of bacterial origin, that are taxonomically restricted to sea anemone and hydra. SECOM is an open-source program and available at http://sfb.kaust.edu.sa/Pages/Software.aspx. © 2012 Fan et al.

Small things matter: Implications of APP intracellular domain AICD nuclear signaling in the progression and pathogenesis of Alzheimer's disease.

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Bukhari, Hassan; Glotzbach, Annika; Kolbe, Katharina; Leonhardt, Gregor; Loosse, Christina; Müller, Thorsten

2017-09-01

Alzheimer's disease (AD) is the most common neurodegenerative disease with tens of millions of people affected worldwide. The pathogenesis is still poorly understood and various therapeutical approaches targeting the amyloid β (Aβ) peptide, a product of the amyloidogenic cleavage of the amyloid precursor protein (APP), failed. Moreover, a couple of studies critically questioned the relevance of Aβ in the pathogenesis of AD. Thus, new ideas need to be studied and one highly interesting hypothesis is the APP mediated signal transduction to the nucleus. As a consequence nuclear -potentially toxic- structures emerge, which were recently found to a high extent in human AD tissue and thus, may contribute to neurodegeneration. Relevant for the signaling machinery are modifications at the very C-terminal end of the precursor protein, the APP intracellular domain (AICD). In this review we update the knowledge on mechanisms on AICD referring to our 2008 article: The amyloid precursor protein intracellular domain (AICD) as modulator of gene expression, apoptosis, and cytoskeletal dynamics-Relevance for Alzheimer's disease (T. Muller, et al., 2008). We summarize how AICD is generated and degraded, we describe its intramolecular motifs, translational modifications, and how those as well as APP dimerization influence AICD generation and function. Moreover, we resume the AICD interactome and elucidate AICDs involvement in nuclear signaling, transcriptional regulation, cell death, DNA repair and cell cycle re-entry and we give insights in its physiological function. Results are summarized in the comprehensive poster "The world of AICD". Copyright © 2017 Elsevier Ltd. All rights reserved.

Structural mapping of the coiled-coil domain of a bacterial condensin and comparative analyses across all domains of life suggest conserved features of SMC proteins.

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Waldman, Vincent M; Stanage, Tyler H; Mims, Alexandra; Norden, Ian S; Oakley, Martha G

2015-06-01

The structural maintenance of chromosomes (SMC) proteins form the cores of multisubunit complexes that are required for the segregation and global organization of chromosomes in all domains of life. These proteins share a common domain structure in which N- and C- terminal regions pack against one another to form a globular ATPase domain. This "head" domain is connected to a central, globular, "hinge" or dimerization domain by a long, antiparallel coiled coil. To date, most efforts for structural characterization of SMC proteins have focused on the globular domains. Recently, however, we developed a method to map interstrand interactions in the 50-nm coiled-coil domain of MukB, the divergent SMC protein found in γ-proteobacteria. Here, we apply that technique to map the structure of the Bacillus subtilis SMC (BsSMC) coiled-coil domain. We find that, in contrast to the relatively complicated coiled-coil domain of MukB, the BsSMC domain is nearly continuous, with only two detectable coiled-coil interruptions. Near the middle of the domain is a break in coiled-coil structure in which there are three more residues on the C-terminal strand than on the N-terminal strand. Close to the head domain, there is a second break with a significantly longer insertion on the same strand. These results provide an experience base that allows an informed interpretation of the output of coiled-coil prediction algorithms for this family of proteins. A comparison of such predictions suggests that these coiled-coil deviations are highly conserved across SMC types in a wide variety of organisms, including humans. © 2015 Wiley Periodicals, Inc.

Java-Based Coupling for Parallel Predictive-Adaptive Domain Decomposition

Directory of Open Access Journals (Sweden)

Cécile Germain‐Renaud

1999-01-01

Full Text Available Adaptive domain decomposition exemplifies the problem of integrating heterogeneous software components with intermediate coupling granularity. This paper describes an experiment where a data‐parallel (HPF client interfaces with a sequential computation server through Java. We show that seamless integration of data‐parallelism is possible, but requires most of the tools from the Java palette: Java Native Interface (JNI, Remote Method Invocation (RMI, callbacks and threads.

TranscriptomeBrowser 3.0: introducing a new compendium of molecular interactions and a new visualization tool for the study of gene regulatory networks.

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Lepoivre, Cyrille; Bergon, Aurélie; Lopez, Fabrice; Perumal, Narayanan B; Nguyen, Catherine; Imbert, Jean; Puthier, Denis

2012-01-31

Deciphering gene regulatory networks by in silico approaches is a crucial step in the study of the molecular perturbations that occur in diseases. The development of regulatory maps is a tedious process requiring the comprehensive integration of various evidences scattered over biological databases. Thus, the research community would greatly benefit from having a unified database storing known and predicted molecular interactions. Furthermore, given the intrinsic complexity of the data, the development of new tools offering integrated and meaningful visualizations of molecular interactions is necessary to help users drawing new hypotheses without being overwhelmed by the density of the subsequent graph. We extend the previously developed TranscriptomeBrowser database with a set of tables containing 1,594,978 human and mouse molecular interactions. The database includes: (i) predicted regulatory interactions (computed by scanning vertebrate alignments with a set of 1,213 position weight matrices), (ii) potential regulatory interactions inferred from systematic analysis of ChIP-seq experiments, (iii) regulatory interactions curated from the literature, (iv) predicted post-transcriptional regulation by micro-RNA, (v) protein kinase-substrate interactions and (vi) physical protein-protein interactions. In order to easily retrieve and efficiently analyze these interactions, we developed In-teractomeBrowser, a graph-based knowledge browser that comes as a plug-in for Transcriptome-Browser. The first objective of InteractomeBrowser is to provide a user-friendly tool to get new insight into any gene list by providing a context-specific display of putative regulatory and physical interactions. To achieve this, InteractomeBrowser relies on a "cell compartments-based layout" that makes use of a subset of the Gene Ontology to map gene products onto relevant cell compartments. This layout is particularly powerful for visual integration of heterogeneous biological information

Polar Domain Discovery with Sparkler

Science.gov (United States)

Duerr, R.; Khalsa, S. J. S.; Mattmann, C. A.; Ottilingam, N. K.; Singh, K.; Lopez, L. A.

2017-12-01

The scientific web is vast and ever growing. It encompasses millions of textual, scientific and multimedia documents describing research in a multitude of scientific streams. Most of these documents are hidden behind forms which require user action to retrieve and thus can't be directly accessed by content crawlers. These documents are hosted on web servers across the world, most often on outdated hardware and network infrastructure. Hence it is difficult and time-consuming to aggregate documents from the scientific web, especially those relevant to a specific domain. Thus generating meaningful domain-specific insights is currently difficult. We present an automated discovery system (Figure 1) using Sparkler, an open-source, extensible, horizontally scalable crawler which facilitates high throughput and focused crawling of documents pertinent to a particular domain such as information about polar regions. With this set of highly domain relevant documents, we show that it is possible to answer analytical questions about that domain. Our domain discovery algorithm leverages prior domain knowledge to reach out to commercial/scientific search engines to generate seed URLs. Subject matter experts then annotate these seed URLs manually on a scale from highly relevant to irrelevant. We leverage this annotated dataset to train a machine learning model which predicts the `domain relevance' of a given document. We extend Sparkler with this model to focus crawling on documents relevant to that domain. Sparkler avoids disruption of service by 1) partitioning URLs by hostname such that every node gets a different host to crawl and by 2) inserting delays between subsequent requests. With an NSF-funded supercomputer Wrangler, we scaled our domain discovery pipeline to crawl about 200k polar specific documents from the scientific web, within a day.

Targeting EphA2-Sam and Its Interactome: Design and Evaluation of Helical Peptides Enriched in Charged Residues.

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Mercurio, Flavia A; Marasco, Daniela; Di Natale, Concetta; Pirone, Luciano; Costantini, Susan; Pedone, Emilia M; Leone, Marilisa

2016-11-17

The EphA2 receptor controls diverse physiological and pathological conditions and its levels are often upregulated in cancer. Targeting receptor overexpression, through modulation of endocytosis and consequent degradation, appears to be an appealing strategy for attacking tumor malignancy. In this scenario, the Sam domain of EphA2 plays a pivotal role because it is the site where protein regulators of endocytosis and stability are recruited by means of heterotypic Sam-Sam interactions. Because EphA2-Sam heterotypic complexes are largely based on electrostatic contacts, we have investigated the possibility of attacking these interactions with helical peptides enriched in charged residues. Several peptide sequences with high predicted helical propensities were designed, and detailed conformational analyses were conducted by diverse techniques including NMR, CD, and molecular dynamics (MD) simulations. Interaction studies were also performed by NMR, surface plasmon resonance (SPR), and microscale thermophoresis (MST) and led to the identification of two peptides capable of binding to the first Sam domain of Odin. These molecules represent early candidates for the generation of efficient Sam domain binders and antagonists of Sam-Sam interactions involving EphA2. © 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

The SH2 domain interaction landscape.

Science.gov (United States)

Tinti, Michele; Kiemer, Lars; Costa, Stefano; Miller, Martin L; Sacco, Francesca; Olsen, Jesper V; Carducci, Martina; Paoluzi, Serena; Langone, Francesca; Workman, Christopher T; Blom, Nikolaj; Machida, Kazuya; Thompson, Christopher M; Schutkowski, Mike; Brunak, Søren; Mann, Matthias; Mayer, Bruce J; Castagnoli, Luisa; Cesareni, Gianni

2013-04-25

Members of the SH2 domain family modulate signal transduction by binding to short peptides containing phosphorylated tyrosines. Each domain displays a distinct preference for the sequence context of the phosphorylated residue. We have developed a high-density peptide chip technology that allows for probing of the affinity of most SH2 domains for a large fraction of the entire complement of tyrosine phosphopeptides in the human proteome. Using this technique, we have experimentally identified thousands of putative SH2-peptide interactions for more than 70 different SH2 domains. By integrating this rich data set with orthogonal context-specific information, we have assembled an SH2-mediated probabilistic interaction network, which we make available as a community resource in the PepspotDB database. A predicted dynamic interaction between the SH2 domains of the tyrosine phosphatase SHP2 and the phosphorylated tyrosine in the extracellular signal-regulated kinase activation loop was validated by experiments in living cells. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

Using the Domain Identification Model to Study Major and Career Decision-Making Processes

Science.gov (United States)

Tendhar, Chosang; Singh, Kusum; Jones, Brett D.

2018-01-01

The purpose of this study was to examine the extent to which (1) a domain identification model could be used to predict students' engineering major and career intentions and (2) the MUSIC Model of Motivation components could be used to predict domain identification. The data for this study were collected from first-year engineering students. We…

Using the domain identification model to study major and career decision-making processes

Science.gov (United States)

Tendhar, Chosang; Singh, Kusum; Jones, Brett D.

2018-03-01

The purpose of this study was to examine the extent to which (1) a domain identification model could be used to predict students' engineering major and career intentions and (2) the MUSIC Model of Motivation components could be used to predict domain identification. The data for this study were collected from first-year engineering students. We used a structural equation model to test the hypothesised relationship between variables in the partial domain identification model. The findings suggested that engineering identification significantly predicted engineering major intentions and career intentions and had the highest effect on those two variables compared to other motivational constructs. Furthermore, results suggested that success, interest, and caring are plausible contributors to students' engineering identification. Overall, there is strong evidence that the domain identification model can be used as a lens to study career decision-making processes in engineering, and potentially, in other fields as well.

The DIMA web resource--exploring the protein domain network.

Science.gov (United States)

Pagel, Philipp; Oesterheld, Matthias; Stümpflen, Volker; Frishman, Dmitrij

2006-04-15

Conserved domains represent essential building blocks of most known proteins. Owing to their role as modular components carrying out specific functions they form a network based both on functional relations and direct physical interactions. We have previously shown that domain interaction networks provide substantially novel information with respect to networks built on full-length protein chains. In this work we present a comprehensive web resource for exploring the Domain Interaction MAp (DIMA), interactively. The tool aims at integration of multiple data sources and prediction techniques, two of which have been implemented so far: domain phylogenetic profiling and experimentally demonstrated domain contacts from known three-dimensional structures. A powerful yet simple user interface enables the user to compute, visualize, navigate and download domain networks based on specific search criteria. http://mips.gsf.de/genre/proj/dima

Exploring the knowledge behind predictions in everyday cognition: an iterated learning study.

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Stephens, Rachel G; Dunn, John C; Rao, Li-Lin; Li, Shu

2015-10-01

Making accurate predictions about events is an important but difficult task. Recent work suggests that people are adept at this task, making predictions that reflect surprisingly accurate knowledge of the distributions of real quantities. Across three experiments, we used an iterated learning procedure to explore the basis of this knowledge: to what extent is domain experience critical to accurate predictions and how accurate are people when faced with unfamiliar domains? In Experiment 1, two groups of participants, one resident in Australia, the other in China, predicted the values of quantities familiar to both (movie run-times), unfamiliar to both (the lengths of Pharaoh reigns), and familiar to one but unfamiliar to the other (cake baking durations and the lengths of Beijing bus routes). While predictions from both groups were reasonably accurate overall, predictions were inaccurate in the selectively unfamiliar domains and, surprisingly, predictions by the China-resident group were also inaccurate for a highly familiar domain: local bus route lengths. Focusing on bus routes, two follow-up experiments with Australia-resident groups clarified the knowledge and strategies that people draw upon, plus important determinants of accurate predictions. For unfamiliar domains, people appear to rely on extrapolating from (not simply directly applying) related knowledge. However, we show that people's predictions are subject to two sources of error: in the estimation of quantities in a familiar domain and extension to plausible values in an unfamiliar domain. We propose that the key to successful predictions is not simply domain experience itself, but explicit experience of relevant quantities.

Vortex Ring Dynamics in Radially Confined Domains

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Stewart, Kelley; Niebel, Casandra; Jung, Sunghwan; Vlachos, Pavlos

2010-11-01

Vortex ring dynamics have been studied extensively in semi-infinite quiescent volumes. However, very little is known about vortex-ring formation in wall-bounded domains where vortex wall interaction will affect both the vortex ring pinch-off and propagation velocity. This study addresses this limitation and studies vortex formation in radially confined domains to analyze the affect of vortex-ring wall interaction on the formation and propagation of the vortex ring. Vortex rings were produced using a pneumatically driven piston cylinder arrangement and were ejected into a long cylindrical tube which defined the confined downstream domain. A range of confinement domains were studied with varying confinement diameters Velocity field measurements were performed using planar Time Resolved Digital Particle Image Velocimetry (TRDPIV) and were processed using an in-house developed cross-correlation PIV algorithm. The experimental analysis was used to facilitate the development of a theoretical model to predict the variations in vortex ring circulation over time within confined domains.

Genome3D: a UK collaborative project to annotate genomic sequences with predicted 3D structures based on SCOP and CATH domains.

Science.gov (United States)

Lewis, Tony E; Sillitoe, Ian; Andreeva, Antonina; Blundell, Tom L; Buchan, Daniel W A; Chothia, Cyrus; Cuff, Alison; Dana, Jose M; Filippis, Ioannis; Gough, Julian; Hunter, Sarah; Jones, David T; Kelley, Lawrence A; Kleywegt, Gerard J; Minneci, Federico; Mitchell, Alex; Murzin, Alexey G; Ochoa-Montaño, Bernardo; Rackham, Owen J L; Smith, James; Sternberg, Michael J E; Velankar, Sameer; Yeats, Corin; Orengo, Christine

2013-01-01

Genome3D, available at http://www.genome3d.eu, is a new collaborative project that integrates UK-based structural resources to provide a unique perspective on sequence-structure-function relationships. Leading structure prediction resources (DomSerf, FUGUE, Gene3D, pDomTHREADER, Phyre and SUPERFAMILY) provide annotations for UniProt sequences to indicate the locations of structural domains (structural annotations) and their 3D structures (structural models). Structural annotations and 3D model predictions are currently available for three model genomes (Homo sapiens, E. coli and baker's yeast), and the project will extend to other genomes in the near future. As these resources exploit different strategies for predicting structures, the main aim of Genome3D is to enable comparisons between all the resources so that biologists can see where predictions agree and are therefore more trusted. Furthermore, as these methods differ in whether they build their predictions using CATH or SCOP, Genome3D also contains the first official mapping between these two databases. This has identified pairs of similar superfamilies from the two resources at various degrees of consensus (532 bronze pairs, 527 silver pairs and 370 gold pairs).

Quantifying information transfer by protein domains: Analysis of the Fyn SH2 domain structure

Directory of Open Access Journals (Sweden)

Serrano Luis

2008-10-01

Full Text Available Abstract Background Efficient communication between distant sites within a protein is essential for cooperative biological response. Although often associated with large allosteric movements, more subtle changes in protein dynamics can also induce long-range correlations. However, an appropriate formalism that directly relates protein structural dynamics to information exchange between functional sites is still lacking. Results Here we introduce a method to analyze protein dynamics within the framework of information theory and show that signal transduction within proteins can be considered as a particular instance of communication over a noisy channel. In particular, we analyze the conformational correlations between protein residues and apply the concept of mutual information to quantify information exchange. Mapping out changes of mutual information on the protein structure then allows visualizing how distal communication is achieved. We illustrate the approach by analyzing information transfer by the SH2 domain of Fyn tyrosine kinase, obtained from Monte Carlo dynamics simulations. Our analysis reveals that the Fyn SH2 domain forms a noisy communication channel that couples residues located in the phosphopeptide and specificity binding sites and a number of residues at the other side of the domain near the linkers that connect the SH2 domain to the SH3 and kinase domains. We find that for this particular domain, communication is affected by a series of contiguous residues that connect distal sites by crossing the core of the SH2 domain. Conclusion As a result, our method provides a means to directly map the exchange of biological information on the structure of protein domains, making it clear how binding triggers conformational changes in the protein structure. As such it provides a structural road, next to the existing attempts at sequence level, to predict long-range interactions within protein structures.

Systematic characterization of the specificity of the SH2 domains of cytoplasmic tyrosine kinases.

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Zhao, Bing; Tan, Pauline H; Li, Shawn S C; Pei, Dehua

2013-04-09

Cytoplasmic tyrosine kinases (CTK) generally contain a Src-homology 2 (SH2) domain, whose role in the CTK family is not fully understood. Here we report the determination of the specificity of 25 CTK SH2 domains by screening one-bead-one-compound (OBOC) peptide libraries. Based on the peptide sequences selected by the SH2 domains, we built Support Vector Machine (SVM) models for the prediction of binding ligands for the SH2 domains. These models yielded support for the progressive phosphorylation model for CTKs in which the overlapping specificity of the CTK SH2 and kinase domains has been proposed to facilitate targeting of the CTK substrates with at least two potential phosphotyrosine (pTyr) sites. We curated 93 CTK substrates with at least two pTyr sites catalyzed by the same CTK, and showed that 71% of these substrates had at least two pTyr sites predicted to bind a common CTK SH2 domain. More importantly, we found 34 instances where there was at least one pTyr site predicted to be recognized by the SH2 domain of the same CTK, suggesting that the SH2 and kinase domains of the CTKs may cooperate to achieve progressive phosphorylation of a protein substrate. This article is part of a Special Issue entitled: From protein structures to clinical applications. Copyright © 2012 Elsevier B.V. All rights reserved.

Rosette Assay: Highly Customizable Dot-Blot for SH2 Domain Screening.

Science.gov (United States)

Ng, Khong Y; Machida, Kazuya

2017-01-01

With a growing number of high-throughput studies, structural analyses, and availability of protein-protein interaction databases, it is now possible to apply web-based prediction tools to SH2 domain-interactions. However, in silico prediction is not always reliable and requires experimental validation. Rosette assay is a dot blot-based reverse-phase assay developed for the assessment of binding between SH2 domains and their ligands. It is conveniently customizable, allowing for low- to high-throughput analysis of interactions between various numbers of SH2 domains and their ligands, e.g., short peptides, purified proteins, and cell lysates. The binding assay is performed in a 96-well plate (MBA or MWA apparatus) in which a sample spotted membrane is incubated with up to 96 labeled SH2 domains. Bound domains are detected and quantified using a chemiluminescence or near-infrared fluorescence (IR) imaging system. In this chapter, we describe a practical protocol for rosette assay to assess interactions between synthesized tyrosine phosphorylated peptides and a library of GST-tagged SH2 domains. Since the methodology is not confined to assessment of SH2-pTyr interactions, rosette assay can be broadly utilized for ligand and drug screening using different protein interaction domains or antibodies.

Friction anisotropy-driven domain imaging on exfoliated monolayer graphene.

Science.gov (United States)

Choi, Jin Sik; Kim, Jin-Soo; Byun, Ik-Su; Lee, Duk Hyun; Lee, Mi Jung; Park, Bae Ho; Lee, Changgu; Yoon, Duhee; Cheong, Hyeonsik; Lee, Ki Ho; Son, Young-Woo; Park, Jeong Young; Salmeron, Miquel

2011-07-29

Graphene produced by exfoliation has not been able to provide an ideal graphene with performance comparable to that predicted by theory, and structural and/or electronic defects have been proposed as one cause of reduced performance. We report the observation of domains on exfoliated monolayer graphene that differ by their friction characteristics, as measured by friction force microscopy. Angle-dependent scanning revealed friction anisotropy with a periodicity of 180° on each friction domain. The friction anisotropy decreased as the applied load increased. We propose that the domains arise from ripple distortions that give rise to anisotropic friction in each domain as a result of the anisotropic puckering of the graphene.

A test of safety, violence prevention, and civility climate domain-specific relationships with relevant workplace hazards.

Science.gov (United States)

Gazica, Michele W; Spector, Paul E

2016-01-01

Safety climate, violence prevention climate, and civility climate were independently developed and linked to domain-specific workplace hazards, although all three were designed to promote the physical and psychological safety of workers. To test domain specificity between conceptually related workplace climates and relevant workplace hazards. Data were collected from 368 persons employed in various industries and descriptive statistics were calculated for all study variables. Correlational and relative weights analyses were used to test for domain specificity. The three climate domains were similarly predictive of most workplace hazards, regardless of domain specificity. This study suggests that the three climate domains share a common higher order construct that may predict relevant workplace hazards better than any of the scales alone.

Domain-wall dynamics in glass-coated magnetic microwires

International Nuclear Information System (INIS)

Varga, R.; Zhukov, A.; Usov, N.; Blanco, J.M.; Gonzalez, J.; Zhukova, V.; Vojtanik, P.

2007-01-01

Glass-coated magnetic microwires with positive magnetostriction show peculiar domain structure that consists mostly of one large domain with magnetization-oriented axially. It was shown that small closure domains appear at the end of the microwire in order to decrease the stray fields. As a result of such domain structure, the magnetization reversal in axial direction runs through the depinning of one of such closure domains and subsequent propagation of the corresponding domain wall. Quite unusual domain-wall (DW) dynamics of the DW propagation predicted previously from the theory has been found in such amorphous microwires. In this paper, we are dealing with the DW dynamics of glass-coated microwires with small positive magnetostriction. The DW damping coming from the structural relaxation dominates at low temperatures as a result of the decrease of the mobility of the structural atomic-level defects. Negative critical propagation field points to the possible DW propagation without applied magnetic field. Probable explanation could be in terms of the effective mass of the DW

Introduction: History of SH2 Domains and Their Applications.

Science.gov (United States)

Liu, Bernard A; Machida, Kazuya

2017-01-01

The Src Homology 2 (SH2) domain is the prototypical protein interaction module that lies at the heart of phosphotyrosine signaling. Since its serendipitous discovery, there has been a tremendous advancement in technologies and an array of techniques available for studying SH2 domains and phosphotyrosine signaling. In this chapter, we provide a glimpse of the history of SH2 domains and describe many of the tools and techniques that have been developed along the way and discuss future directions for SH2 domain studies. We highlight the gist of each chapter in this volume in the context of: the structural biology and phosphotyrosine binding; characterizing SH2 specificity and generating prediction models; systems biology and proteomics; SH2 domains in signal transduction; and SH2 domains in disease, diagnostics, and therapeutics. Many of the individual chapters provide an in-depth approach that will allow scientists to interrogate the function and role of SH2 domains.

The Genome Sequence of Leishmania (Leishmania) amazonensis: Functional Annotation and Extended Analysis of Gene Models

Science.gov (United States)

Real, Fernando; Vidal, Ramon Oliveira; Carazzolle, Marcelo Falsarella; Mondego, Jorge Maurício Costa; Costa, Gustavo Gilson Lacerda; Herai, Roberto Hirochi; Würtele, Martin; de Carvalho, Lucas Miguel; e Ferreira, Renata Carmona; Mortara, Renato Arruda; Barbiéri, Clara Lucia; Mieczkowski, Piotr; da Silveira, José Franco; Briones, Marcelo Ribeiro da Silva; Pereira, Gonçalo Amarante Guimarães; Bahia, Diana

2013-01-01

We present the sequencing and annotation of the Leishmania (Leishmania) amazonensis genome, an etiological agent of human cutaneous leishmaniasis in the Amazon region of Brazil. L. (L.) amazonensis shares features with Leishmania (L.) mexicana but also exhibits unique characteristics regarding geographical distribution and clinical manifestations of cutaneous lesions (e.g. borderline disseminated cutaneous leishmaniasis). Predicted genes were scored for orthologous gene families and conserved domains in comparison with other human pathogenic Leishmania spp. Carboxypeptidase, aminotransferase, and 3′-nucleotidase genes and ATPase, thioredoxin, and chaperone-related domains were represented more abundantly in L. (L.) amazonensis and L. (L.) mexicana species. Phylogenetic analysis revealed that these two species share groups of amastin surface proteins unique to the genus that could be related to specific features of disease outcomes and host cell interactions. Additionally, we describe a hypothetical hybrid interactome of potentially secreted L. (L.) amazonensis proteins and host proteins under the assumption that parasite factors mimic their mammalian counterparts. The model predicts an interaction between an L. (L.) amazonensis heat-shock protein and mammalian Toll-like receptor 9, which is implicated in important immune responses such as cytokine and nitric oxide production. The analysis presented here represents valuable information for future studies of leishmaniasis pathogenicity and treatment. PMID:23857904

Accumulating Data to Optimally Predict Obesity Treatment (ADOPT): Recommendations from the Biological Domain.

Science.gov (United States)

Rosenbaum, Michael; Agurs-Collins, Tanya; Bray, Molly S; Hall, Kevin D; Hopkins, Mark; Laughlin, Maren; MacLean, Paul S; Maruvada, Padma; Savage, Cary R; Small, Dana M; Stoeckel, Luke

2018-04-01

The responses to behavioral, pharmacological, or surgical obesity treatments are highly individualized. The Accumulating Data to Optimally Predict obesity Treatment (ADOPT) project provides a framework for how obesity researchers, working collectively, can generate the evidence base needed to guide the development of tailored, and potentially more effective, strategies for obesity treatment. The objective of the ADOPT biological domain subgroup is to create a list of high-priority biological measures for weight-loss studies that will advance the understanding of individual variability in response to adult obesity treatments. This list includes measures of body composition, energy homeostasis (energy intake and output), brain structure and function, and biomarkers, as well as biobanking procedures, which could feasibly be included in most, if not all, studies of obesity treatment. The recommended high-priority measures are selected to balance needs for sensitivity, specificity, and/or comprehensiveness with feasibility to achieve a commonality of usage and increase the breadth and impact of obesity research. The accumulation of data on key biological factors, along with behavioral, psychosocial, and environmental factors, can generate a more precise description of the interplay and synergy among them and their impact on treatment responses, which can ultimately inform the design and delivery of effective, tailored obesity treatments. © 2018 The Obesity Society.

CATHEDRAL: a fast and effective algorithm to predict folds and domain boundaries from multidomain protein structures.

Directory of Open Access Journals (Sweden)

Oliver C Redfern

2007-11-01

Full Text Available We present CATHEDRAL, an iterative protocol for determining the location of previously observed protein folds in novel multidomain protein structures. CATHEDRAL builds on the features of a fast secondary-structure-based method (using graph theory to locate known folds within a multidomain context and a residue-based, double-dynamic programming algorithm, which is used to align members of the target fold groups against the query protein structure to identify the closest relative and assign domain boundaries. To increase the fidelity of the assignments, a support vector machine is used to provide an optimal scoring scheme. Once a domain is verified, it is excised, and the search protocol is repeated in an iterative fashion until all recognisable domains have been identified. We have performed an initial benchmark of CATHEDRAL against other publicly available structure comparison methods using a consensus dataset of domains derived from the CATH and SCOP domain classifications. CATHEDRAL shows superior performance in fold recognition and alignment accuracy when compared with many equivalent methods. If a novel multidomain structure contains a known fold, CATHEDRAL will locate it in 90% of cases, with <1% false positives. For nearly 80% of assigned domains in a manually validated test set, the boundaries were correctly delineated within a tolerance of ten residues. For the remaining cases, previously classified domains were very remotely related to the query chain so that embellishments to the core of the fold caused significant differences in domain sizes and manual refinement of the boundaries was necessary. To put this performance in context, a well-established sequence method based on hidden Markov models was only able to detect 65% of domains, with 33% of the subsequent boundaries assigned within ten residues. Since, on average, 50% of newly determined protein structures contain more than one domain unit, and typically 90% or more of these

Chasing probabilities — Signaling negative and positive prediction errors across domains

DEFF Research Database (Denmark)

Meder, David; Madsen, Kristoffer H; Hulme, Oliver

2016-01-01

of the two. We acquired functional MRI data while volunteers performed four probabilistic reversal learning tasks which differed in terms of outcome valence (reward-seeking versus punishment-avoidance) and domain (abstract symbols versus facial expressions) of outcomes. We found that ventral striatum...

Atomic resolution imaging of ferroelectric domains

International Nuclear Information System (INIS)

Bursill, L.A.

1997-01-01

Electron optical principles involved in obtaining atomic resolution images of ferroelectric domains are reviewed, including the methods available to obtain meaningful interpretation and analysis of the image detail in terms of the atomic structures. Recent work is concerned with establishing the relationship between the essentially static chemical nanodomains and the spatial and temporal fluctuations of the nanoscale polar domains present in the relaxor class of materials, including lead scandium tantalate (PST) and lead magnesium niobate (PMN). Correct interpretation of the images required use of Next Nearest Neighbour Ising model simulations for the chemical domain textures upon which we must superimpose the polar domain textures; an introduction to this work is presented. A thorough analysis of the atomic scale chemical inhomogeneities, based upon the HRTEM results, has lead to an improved formulation of the theory of the dielectric response of PMN and PST, which is capable to predict the observed temperature and frequency dependence. HRTEM may be combined with solid state and statistical physics principles to provide a deeper understanding of structure/property relationships. 15 refs., 6 figs

Expanding the landscape of chromatin modification (CM-related functional domains and genes in human.

Directory of Open Access Journals (Sweden)

Shuye Pu

2010-11-01

Full Text Available Chromatin modification (CM plays a key role in regulating transcription, DNA replication, repair and recombination. However, our knowledge of these processes in humans remains very limited. Here we use computational approaches to study proteins and functional domains involved in CM in humans. We analyze the abundance and the pair-wise domain-domain co-occurrences of 25 well-documented CM domains in 5 model organisms: yeast, worm, fly, mouse and human. Results show that domains involved in histone methylation, DNA methylation, and histone variants are remarkably expanded in metazoan, reflecting the increased demand for cell type-specific gene regulation. We find that CM domains tend to co-occur with a limited number of partner domains and are hence not promiscuous. This property is exploited to identify 47 potentially novel CM domains, including 24 DNA-binding domains, whose role in CM has received little attention so far. Lastly, we use a consensus Machine Learning approach to predict 379 novel CM genes (coding for 329 proteins in humans based on domain compositions. Several of these predictions are supported by very recent experimental studies and others are slated for experimental verification. Identification of novel CM genes and domains in humans will aid our understanding of fundamental epigenetic processes that are important for stem cell differentiation and cancer biology. Information on all the candidate CM domains and genes reported here is publicly available.

Does expert perceptual anticipation transfer to a dissimilar domain?

Science.gov (United States)

Müller, Sean; McLaren, Michelle; Appleby, Brendyn; Rosalie, Simon M

2015-06-01

The purpose of this experiment was to extend theoretical understanding of transfer of learning by investigating whether expert perceptual anticipation skill transfers to a dissimilar domain. The capability of expert and near-expert rugby players as well as novices to anticipate skill type within rugby (learning sport) was first examined using a temporal occlusion paradigm. Participants watched video footage of an opponent performing rugby skill types that were temporally occluded at different points in the opponent's action and then made a written prediction. Thereafter, the capability of participants to transfer their anticipation skill to predict pitch type in baseball (transfer sport) was examined. Participants watched video footage of a pitcher throwing different pitch types that were temporally occluded and made a written prediction. Results indicated that expert and near-expert rugby players anticipated significantly better than novices across all occlusion conditions. However, none of the skill groups were able to transfer anticipation skill to predict pitch type in baseball. The findings of this paper, along with existing literature, support the theoretical prediction that transfer of perceptual anticipation is expertise dependent and restricted to similar domains. (c) 2015 APA, all rights reserved).

Domains of cognitive function in early old age: which ones are predicted by pre-retirement psychosocial work characteristics?

Science.gov (United States)

Sabbath, Erika L; Andel, Ross; Zins, Marie; Goldberg, Marcel; Berr, Claudine

2016-10-01

Psychosocial work characteristics may predict cognitive functioning after retirement. However, little research has explored specific cognitive domains associated with psychosocial work environments. Our study tested whether exposure to job demands, job control and their combination during working life predicted post-retirement performance on eight cognitive tests. We used data from French GAZEL cohort members who had undergone post-retirement cognitive testing (n=2149). Psychosocial job characteristics were measured on average for 4 years before retirement using Karasek's Job Content Questionnaire (job demands, job control and demand-control combinations). We tested associations between these exposures and post-retirement performance on tests for executive function, visual-motor speed, psychomotor speed, verbal memory, and verbal fluency using ordinary least squares regression. Low job control during working life was negatively associated with executive function, psychomotor speed, phonemic fluency and semantic fluency after retirement (p'swork stress, associations between passive work and subsequent cognitive function may implicate lack of cognitive engagement at work as a risk factor for future cognitive difficulties. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

TranscriptomeBrowser 3.0: introducing a new compendium of molecular interactions and a new visualization tool for the study of gene regulatory networks

Directory of Open Access Journals (Sweden)

Lepoivre Cyrille

2012-01-01

Full Text Available Abstract Background Deciphering gene regulatory networks by in silico approaches is a crucial step in the study of the molecular perturbations that occur in diseases. The development of regulatory maps is a tedious process requiring the comprehensive integration of various evidences scattered over biological databases. Thus, the research community would greatly benefit from having a unified database storing known and predicted molecular interactions. Furthermore, given the intrinsic complexity of the data, the development of new tools offering integrated and meaningful visualizations of molecular interactions is necessary to help users drawing new hypotheses without being overwhelmed by the density of the subsequent graph. Results We extend the previously developed TranscriptomeBrowser database with a set of tables containing 1,594,978 human and mouse molecular interactions. The database includes: (i predicted regulatory interactions (computed by scanning vertebrate alignments with a set of 1,213 position weight matrices, (ii potential regulatory interactions inferred from systematic analysis of ChIP-seq experiments, (iii regulatory interactions curated from the literature, (iv predicted post-transcriptional regulation by micro-RNA, (v protein kinase-substrate interactions and (vi physical protein-protein interactions. In order to easily retrieve and efficiently analyze these interactions, we developed In-teractomeBrowser, a graph-based knowledge browser that comes as a plug-in for Transcriptome-Browser. The first objective of InteractomeBrowser is to provide a user-friendly tool to get new insight into any gene list by providing a context-specific display of putative regulatory and physical interactions. To achieve this, InteractomeBrowser relies on a "cell compartments-based layout" that makes use of a subset of the Gene Ontology to map gene products onto relevant cell compartments. This layout is particularly powerful for visual integration

Individual and contextual parameters associated with adolescents' domain specific self-perceptions.

Science.gov (United States)

Kokkinos, Constantinos M; Hatzinikolaou, Stamatia

2011-04-01

The present study examined the role of adolescents' self-esteem and perceptions of family and classroom contexts on their domain specific self-perceptions. 345 Greek junior high school adolescents aged 14-16 completed measures of domain specific self-perceptions, self-esteem, parenting styles and classroom climate. Hierarchical regression analyses revealed that both family and classroom contexts predicted students' self-perceptions, after students' demographics, academic achievement and self-esteem were controlled for. However, different patterns emerged in the relationship between family, classroom climate and self-esteem depending on domain specific self-perceptions. Academic self-perceptions (scholastic, mathematics and language competences) were predicted by classroom climate dimensions (order and organization, student involvement, rule clarity), whereas self-perceptions regarding relations with parents, close friends and behaviour conduct, were predicted by parenting styles. Given the fact that adolescence is a period of fluctuation in self-understanding which renders self-perceptions particularly malleable, the results support the critical role of the social environments where adolescents operate. Copyright © 2010 The Association for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

Health numeracy: the importance of domain in assessing numeracy.

Science.gov (United States)

Levy, Helen; Ubel, Peter A; Dillard, Amanda J; Weir, David R; Fagerlin, Angela

2014-01-01

Existing research concludes that measures of general numeracy can be used to predict individuals' ability to assess health risks. We posit that the domain in which questions are posed affects the ability to perform mathematical tasks, raising the possibility of a separate construct of "health numeracy" that is distinct from general numeracy. The objective was to determine whether older adults' ability to perform simple math depends on domain. Community-based participants completed 4 math questions posed in 3 different domains: a health domain, a financial domain, and a pure math domain. Participants were 962 individuals aged 55 and older, representative of the community-dwelling US population over age 54. We found that respondents performed significantly worse when questions were posed in the health domain (54% correct) than in either the pure math domain (66% correct) or the financial domain (63% correct). Our experimental measure of numeracy consisted of only 4 questions, and it is possible that the apparent effect of domain is specific to the mathematical tasks that these questions require. These results suggest that health numeracy is strongly related to general numeracy but that the 2 constructs may not be the same. Further research is needed into how different aspects of general numeracy and health numeracy translate into actual medical decisions.

Multiple hypothesis tracking for the cyber domain

Science.gov (United States)

Schwoegler, Stefan; Blackman, Sam; Holsopple, Jared; Hirsch, Michael J.

2011-09-01

This paper discusses how methods used for conventional multiple hypothesis tracking (MHT) can be extended to domain-agnostic tracking of entities from non-kinematic constraints such as those imposed by cyber attacks in a potentially dense false alarm background. MHT is widely recognized as the premier method to avoid corrupting tracks with spurious data in the kinematic domain but it has not been extensively applied to other problem domains. The traditional approach is to tightly couple track maintenance (prediction, gating, filtering, probabilistic pruning, and target confirmation) with hypothesis management (clustering, incompatibility maintenance, hypothesis formation, and Nassociation pruning). However, by separating the domain specific track maintenance portion from the domain agnostic hypothesis management piece, we can begin to apply the wealth of knowledge gained from ground and air tracking solutions to the cyber (and other) domains. These realizations led to the creation of Raytheon's Multiple Hypothesis Extensible Tracking Architecture (MHETA). In this paper, we showcase MHETA for the cyber domain, plugging in a well established method, CUBRC's INFormation Engine for Real-time Decision making, (INFERD), for the association portion of the MHT. The result is a CyberMHT. We demonstrate the power of MHETA-INFERD using simulated data. Using metrics from both the tracking and cyber domains, we show that while no tracker is perfect, by applying MHETA-INFERD, advanced nonkinematic tracks can be captured in an automated way, perform better than non-MHT approaches, and decrease analyst response time to cyber threats.

HMMerThread: detecting remote, functional conserved domains in entire genomes by combining relaxed sequence-database searches with fold recognition.

Directory of Open Access Journals (Sweden)

Charles Richard Bradshaw

Full Text Available Conserved domains in proteins are one of the major sources of functional information for experimental design and genome-level annotation. Though search tools for conserved domain databases such as Hidden Markov Models (HMMs are sensitive in detecting conserved domains in proteins when they share sufficient sequence similarity, they tend to miss more divergent family members, as they lack a reliable statistical framework for the detection of low sequence similarity. We have developed a greatly improved HMMerThread algorithm that can detect remotely conserved domains in highly divergent sequences. HMMerThread combines relaxed conserved domain searches with fold recognition to eliminate false positive, sequence-based identifications. With an accuracy of 90%, our software is able to automatically predict highly divergent members of conserved domain families with an associated 3-dimensional structure. We give additional confidence to our predictions by validation across species. We have run HMMerThread searches on eight proteomes including human and present a rich resource of remotely conserved domains, which adds significantly to the functional annotation of entire proteomes. We find ∼4500 cross-species validated, remotely conserved domain predictions in the human proteome alone. As an example, we find a DNA-binding domain in the C-terminal part of the A-kinase anchor protein 10 (AKAP10, a PKA adaptor that has been implicated in cardiac arrhythmias and premature cardiac death, which upon stress likely translocates from mitochondria to the nucleus/nucleolus. Based on our prediction, we propose that with this HLH-domain, AKAP10 is involved in the transcriptional control of stress response. Further remotely conserved domains we discuss are examples from areas such as sporulation, chromosome segregation and signalling during immune response. The HMMerThread algorithm is able to automatically detect the presence of remotely conserved domains in

Framing Effects: Dynamics and Task Domains

Science.gov (United States)

Wang

1996-11-01

The author examines the mechanisms and dynamics of framing effects in risky choices across three distinct task domains (i.e., life-death, public property, and personal money). The choice outcomes of the problems presented in each of the three task domains had a binary structure of a sure thing vs a gamble of equal expected value; the outcomes differed in their framing conditions and the expected values, raging from 6000, 600, 60, to 6, numerically. It was hypothesized that subjects would become more risk seeking, if the sure outcome was below their aspiration level (the minimum requirement). As predicted, more subjects preferred the gamble when facing the life-death choice problems than facing the counterpart problems presented in the other two task domains. Subjects' risk preference varied categorically along the group size dimension in the life-death domain but changed more linearly over the expected value dimension in the monetary domain. Framing effects were observed in 7 of 13 pairs of problems, showing a positive frame-risk aversion and negative frame-risk seeking relationship. In addition, two types of framing effects were theoretically defined and empirically identified. A bidirectional framing effect involves a reversal in risk preference, and occurs when a decision maker's risk preference is ambiguous or weak. Four bidirectional effects were observed; in each case a majority of subjects preferred the sure outcome under a positive frame but the gamble under a negative frame. In contrast, a unidirectional framing effect refers to a preference shift due to the framing of choice outcomes: A majority of subjects preferred one choice outcome (either the sure thing or the gamble) under both framing conditions, with positive frame augmented the preference for the sure thing and negative frame augmented the preference for the gamble. These findings revealed some dynamic regularities of framing effects and posed implications for developing predictive and testable

An investigation of time-dependent domain wall pinning effects in Tb/Fe multilayer thin flms

NARCIS (Netherlands)

Phillips, G.N.; O'grady, K.; El-Hilo, M.

2002-01-01

Reverse domain nucleation time measurements have been performed on two Tb/Fe multilayer magneto-optic films exhibiting different degrees of domain wall pinning.A linear relationship between ln (reverse domain nucleation time) and the applied field has been predicted and observed for a sample

A Frequency-Domain Adaptive Filter (FDAF) Prediction Error Method (PEM) Framework for Double-Talk-Robust Acoustic Echo Cancellation

DEFF Research Database (Denmark)

Gil-Cacho, Jose M.; van Waterschoot, Toon; Moonen, Marc

2014-01-01

to the FDAF-PEM-AFROW algorithm. We show that FDAF-PEM-AFROW is by construction related to the best linear unbiased estimate (BLUE) of the echo path. We depart from this framework to show an improvement in performance with respect to other adaptive filters minimizing the BLUE criterion, namely the PEM......In this paper, we propose a new framework to tackle the double-talk (DT) problem in acoustic echo cancellation (AEC). It is based on a frequency-domain adaptive filter (FDAF) implementation of the so-called prediction error method adaptive filtering using row operations (PEM-AFROW) leading...... regularization (VR) algorithms. The FDAF-PEM-AFROW versions significantly outperform the original versions in every simulation. In terms of computational complexity, the FDAF-PEM-AFROW versions are themselves about two orders of magnitude cheaper than the original versions....

The Measurement and Role of Ecological Resilience Systems Theory Across Domain-Specific Outcomes: The Domain-Specific Resilient Systems Scales.

Science.gov (United States)

Maltby, John; Day, Liz; Hall, Sophie S; Chivers, Sally

2017-10-01

Research suggests that trait resilience may be best understood within an ecological resilient systems theory, comprising engineering, ecological, and adaptive capacity resilience. However, there is no evidence as to how this theory translates to specific life domains. Data from two samples (the United States, n = 1,278; the United Kingdom, n = 211) facilitated five studies that introduce the Domain-Specific Resilient Systems Scales for assessing ecological resilient systems theory within work, health, marriage, friendships, and education. The Domain-Specific Resilient Systems Scales are found to predict unique variance in job satisfaction, lower job burnout, quality-of-life following illness, marriage commitment, and educational engagement, while controlling for factors including sex, age, personality, cognitive ability, and trait resilience. The findings also suggest a distinction between the three resilience dimensions in terms of the types of systems to which they contribute. Engineering resilience may contribute most to life domains where an established system needs to be maintained, for example, one's health. Ecological resilience may contribute most to life domains where the system needs sustainability in terms of present and future goal orientation, for example, one's work. Adaptive Capacity may contribute most to life domains where the system needs to be retained, preventing it from reaching a crisis state, for example, work burnout.

A multi-domain Chebyshev collocation method for predicting ultrasonic field parameters in complex material geometries

DEFF Research Database (Denmark)

Nielsen, S.A.; Hesthaven, J.S.

2002-01-01

elastodynamic formulation, giving a direct solution of the time-domain elastodynamic equations. A typical calculation is performed by decomposing the global computational domain into a number of subdomains. Every subdomain is then mapped on a unit square using transfinite blending functions and spatial...

Predicting the effect of spectral subtraction on the speech recognition threshold based on the signal-to-noise ratio in the envelope domain

DEFF Research Database (Denmark)

Jørgensen, Søren; Dau, Torsten

2011-01-01

rarely been evaluated perceptually in terms of speech intelligibility. This study analyzed the effects of the spectral subtraction strategy proposed by Berouti at al. [ICASSP 4 (1979), 208-211] on the speech recognition threshold (SRT) obtained with sentences presented in stationary speech-shaped noise....... The SRT was measured in five normal-hearing listeners in six conditions of spectral subtraction. The results showed an increase of the SRT after processing, i.e. a decreased speech intelligibility, in contrast to what is predicted by the Speech Transmission Index (STI). Here, another approach is proposed......, denoted the speech-based envelope power spectrum model (sEPSM) which predicts the intelligibility based on the signal-to-noise ratio in the envelope domain. In contrast to the STI, the sEPSM is sensitive to the increased amount of the noise envelope power as a consequence of the spectral subtraction...

A frequency domain approach for MPC tuning

NARCIS (Netherlands)

Özkan, L.; Meijs, J.B.; Backx, A.C.P.M.; Karimi, I.A.; Srinivasan, R.

2012-01-01

This paper presents a frequency domain based approach to tune the penalty weights in the model predictive control (MPC) formulation. The two-step tuning method involves the design of a favourite controller taking into account the model-plant mismatch followed by the controller matching. We implement

Photoinduced Domain Pattern Transformation in Ferroelectric-Dielectric Superlattices

Energy Technology Data Exchange (ETDEWEB)

Ahn, Youngjun; Park, Joonkyu; Pateras, Anastasios; Rich, Matthew B.; Zhang, Qingteng; Chen, Pice; Yusuf, Mohammed H.; Wen, Haidan; Dawber, Matthew; Evans, Paul G.

2017-07-01

The nanodomain pattern in ferroelectric/dielectric superlattices transforms to a uniform polarization state under above-bandgap optical excitation. X-ray scattering reveals a disappearance of domain diffuse scattering and an expansion of the lattice. The reappearance of the domain pattern occurs over a period of seconds at room temperature, suggesting a transformation mechanism in which charge carriers in long-lived trap states screen the depolarization field. A Landau-Ginzburg-Devonshire model predicts changes in lattice parameter and a critical carrier concentration for the transformation.

Particle Communication and Domain Neighbor Coupling: Scalable Domain Decomposed Algorithms for Monte Carlo Particle Transport

Energy Technology Data Exchange (ETDEWEB)

O' Brien, M. J.; Brantley, P. S.

2015-01-20

In order to run Monte Carlo particle transport calculations on new supercomputers with hundreds of thousands or millions of processors, care must be taken to implement scalable algorithms. This means that the algorithms must continue to perform well as the processor count increases. In this paper, we examine the scalability of:(1) globally resolving the particle locations on the correct processor, (2) deciding that particle streaming communication has finished, and (3) efficiently coupling neighbor domains together with different replication levels. We have run domain decomposed Monte Carlo particle transport on up to 2²¹ = 2,097,152 MPI processes on the IBM BG/Q Sequoia supercomputer and observed scalable results that agree with our theoretical predictions. These calculations were carefully constructed to have the same amount of work on every processor, i.e. the calculation is already load balanced. We also examine load imbalanced calculations where each domain’s replication level is proportional to its particle workload. In this case we show how to efficiently couple together adjacent domains to maintain within workgroup load balance and minimize memory usage.

Beyond cross-domain learning: Multiple-domain nonnegative matrix factorization

KAUST Repository

Wang, Jim Jing-Yan; Gao, Xin

2014-01-01

Traditional cross-domain learning methods transfer learning from a source domain to a target domain. In this paper, we propose the multiple-domain learning problem for several equally treated domains. The multiple-domain learning problem assumes that samples from different domains have different distributions, but share the same feature and class label spaces. Each domain could be a target domain, while also be a source domain for other domains. A novel multiple-domain representation method is proposed for the multiple-domain learning problem. This method is based on nonnegative matrix factorization (NMF), and tries to learn a basis matrix and coding vectors for samples, so that the domain distribution mismatch among different domains will be reduced under an extended variation of the maximum mean discrepancy (MMD) criterion. The novel algorithm - multiple-domain NMF (MDNMF) - was evaluated on two challenging multiple-domain learning problems - multiple user spam email detection and multiple-domain glioma diagnosis. The effectiveness of the proposed algorithm is experimentally verified. © 2013 Elsevier Ltd. All rights reserved.

Beyond cross-domain learning: Multiple-domain nonnegative matrix factorization

KAUST Repository

Wang, Jim Jing-Yan

2014-02-01

Traditional cross-domain learning methods transfer learning from a source domain to a target domain. In this paper, we propose the multiple-domain learning problem for several equally treated domains. The multiple-domain learning problem assumes that samples from different domains have different distributions, but share the same feature and class label spaces. Each domain could be a target domain, while also be a source domain for other domains. A novel multiple-domain representation method is proposed for the multiple-domain learning problem. This method is based on nonnegative matrix factorization (NMF), and tries to learn a basis matrix and coding vectors for samples, so that the domain distribution mismatch among different domains will be reduced under an extended variation of the maximum mean discrepancy (MMD) criterion. The novel algorithm - multiple-domain NMF (MDNMF) - was evaluated on two challenging multiple-domain learning problems - multiple user spam email detection and multiple-domain glioma diagnosis. The effectiveness of the proposed algorithm is experimentally verified. © 2013 Elsevier Ltd. All rights reserved.

Image-domain full waveform inversion: Field data example

KAUST Repository

Zhang, Sanzong

2014-08-05

The main difficulty with the data-domain full waveform inversion (FWI) is that it tends to get stuck in the local minima associated with the waveform misfit function. This is the result of cycle skipping which degrades the low-wavenumber update in the absence of low-frequencies and long-offset data. An image-domain objective function is defined as the normed difference between the predicted and observed common image gathers (CIGs) in the subsurface offset domain. This new objective function is not constrained by cycle skipping at the far subsurface offsets. To test the effectiveness of this method, we apply it to marine data recorded in the Gulf of Mexico. Results show that image-domain FWI is less sensitive to the initial model and the absence of low-frequency data compared with conventional FWI. The liability, however, is that it is almost an order of magnitude more expensive than standard FWI.

Image-domain full waveform inversion: Field data example

KAUST Repository

Zhang, Sanzong; Schuster, Gerard T.

2014-01-01

The main difficulty with the data-domain full waveform inversion (FWI) is that it tends to get stuck in the local minima associated with the waveform misfit function. This is the result of cycle skipping which degrades the low-wavenumber update in the absence of low-frequencies and long-offset data. An image-domain objective function is defined as the normed difference between the predicted and observed common image gathers (CIGs) in the subsurface offset domain. This new objective function is not constrained by cycle skipping at the far subsurface offsets. To test the effectiveness of this method, we apply it to marine data recorded in the Gulf of Mexico. Results show that image-domain FWI is less sensitive to the initial model and the absence of low-frequency data compared with conventional FWI. The liability, however, is that it is almost an order of magnitude more expensive than standard FWI.

A role for chromatin topology in imprinted domain regulation.

Science.gov (United States)

MacDonald, William A; Sachani, Saqib S; White, Carlee R; Mann, Mellissa R W

2016-02-01

Recently, many advancements in genome-wide chromatin topology and nuclear architecture have unveiled the complex and hidden world of the nucleus, where chromatin is organized into discrete neighbourhoods with coordinated gene expression. This includes the active and inactive X chromosomes. Using X chromosome inactivation as a working model, we utilized publicly available datasets together with a literature review to gain insight into topologically associated domains, lamin-associated domains, nucleolar-associating domains, scaffold/matrix attachment regions, and nucleoporin-associated chromatin and their role in regulating monoallelic expression. Furthermore, we comprehensively review for the first time the role of chromatin topology and nuclear architecture in the regulation of genomic imprinting. We propose that chromatin topology and nuclear architecture are important regulatory mechanisms for directing gene expression within imprinted domains. Furthermore, we predict that dynamic changes in chromatin topology and nuclear architecture play roles in tissue-specific imprint domain regulation during early development and differentiation.

The effects of glutamine/asparagine content on aggregation and heterologous prion induction by yeast prion-like domains.

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Shattuck, Jenifer E; Waechter, Aubrey C; Ross, Eric D

2017-07-04

Prion-like domains are low complexity, intrinsically disordered domains that compositionally resemble yeast prion domains. Many prion-like domains are involved in the formation of either functional or pathogenic protein aggregates. These aggregates range from highly dynamic liquid droplets to highly ordered detergent-insoluble amyloid-like aggregates. To better understand the amino acid sequence features that promote conversion to stable, detergent-insoluble aggregates, we used the prediction algorithm PAPA to identify predicted aggregation-prone prion-like domains with a range of compositions. While almost all of the predicted aggregation-prone domains formed foci when expressed in cells, the ability to form the detergent-insoluble aggregates was highly correlated with glutamine/asparagine (Q/N) content, suggesting that high Q/N content may specifically promote conversion to the amyloid state in vivo. We then used this data set to examine cross-seeding between prion-like proteins. The prion protein Sup35 requires the presence of a second prion, [PIN + ], to efficiently form prions, but this requirement can be circumvented by the expression of various Q/N-rich protein fragments. Interestingly, almost all of the Q/N-rich domains that formed SDS-insoluble aggregates were able to promote prion formation by Sup35, highlighting the highly promiscuous nature of these interactions.

Individual domain wall resistance in submicron ferromagnetic structures.

Science.gov (United States)

Danneau, R; Warin, P; Attané, J P; Petej, I; Beigné, C; Fermon, C; Klein, O; Marty, A; Ott, F; Samson, Y; Viret, M

2002-04-15

The resistance generated by individual domain walls is measured in a FePd nanostructure. Combining transport and magnetic imaging measurements, the intrinsic domain wall resistance is quantified. It is found positive and of a magnitude consistent with that predicted by models based on spin scattering effects within the walls. This magnetoresistance at a nanometer scale allows a direct counting of the number of walls inside the nanostructure. The effect is then used to measure changes in the magnetic configuration of submicron stripes under application of a magnetic field.

Macroscopic domain formation in the platelet plasma membrane

DEFF Research Database (Denmark)

Bali, Rachna; Savino, Laura; Ramirez, Diego A.

2009-01-01

There has been ample debate on whether cell membranes can present macroscopic lipid domains as predicted by three-component phase diagrams obtained by fluorescence microscopy. Several groups have argued that membrane proteins and interactions with the cytoskeleton inhibit the formation of large d...

Classification and Lineage Tracing of SH2 Domains Throughout Eukaryotes.

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Liu, Bernard A

2017-01-01

Today there exists a rapidly expanding number of sequenced genomes. Cataloging protein interaction domains such as the Src Homology 2 (SH2) domain across these various genomes can be accomplished with ease due to existing algorithms and predictions models. An evolutionary analysis of SH2 domains provides a step towards understanding how SH2 proteins integrated with existing signaling networks to position phosphotyrosine signaling as a crucial driver of robust cellular communication networks in metazoans. However organizing and tracing SH2 domain across organisms and understanding their evolutionary trajectory remains a challenge. This chapter describes several methodologies towards analyzing the evolutionary trajectory of SH2 domains including a global SH2 domain classification system, which facilitates annotation of new SH2 sequences essential for tracing the lineage of SH2 domains throughout eukaryote evolution. This classification utilizes a combination of sequence homology, protein domain architecture and the boundary positions between introns and exons within the SH2 domain or genes encoding these domains. Discrete SH2 families can then be traced across various genomes to provide insight into its origins. Furthermore, additional methods for examining potential mechanisms for divergence of SH2 domains from structural changes to alterations in the protein domain content and genome duplication will be discussed. Therefore a better understanding of SH2 domain evolution may enhance our insight into the emergence of phosphotyrosine signaling and the expansion of protein interaction domains.

Contrasting two models of academic self-efficacy--domain-specific versus cross-domain--in children receiving and not receiving special instruction in mathematics.

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Jungert, Tomas; Hesser, Hugo; Träff, Ulf

2014-10-01

In social cognitive theory, self-efficacy is domain-specific. An alternative model, the cross-domain influence model, would predict that self-efficacy beliefs in one domain might influence performance in other domains. Research has also found that children who receive special instruction are not good at estimating their performance. The aim was to test two models of how self-efficacy beliefs influence achievement, and to contrast children receiving special instruction in mathematics with normally-achieving children. The participants were 73 fifth-grade children who receive special instruction and 70 children who do not receive any special instruction. In year four and five, the children's skills in mathematics and reading were assessed by national curriculum tests, and in their fifth year, self-efficacy in mathematics and reading were measured. Structural equation modeling showed that in domains where children do not receive special instruction in mathematics, self-efficacy is a mediating variable between earlier and later achievement in the same domain. Achievement in mathematics was not mediated by self-efficacy in mathematics for children who receive special instruction. For normal achieving children, earlier achievement in the language domain had an influence on later self-efficacy in the mathematics domain, and self-efficacy beliefs in different domains were correlated. Self-efficacy is mostly domain specific, but may play a different role in academic performance depending on whether children receive special instruction. The results of the present study provided some support of the Cross-Domain Influence Model for normal achieving children. © 2014 Scandinavian Psychological Associations and John Wiley & Sons Ltd.

Inhibition of the Hantavirus Fusion Process by Predicted Domain III and Stem Peptides from Glycoprotein Gc.

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Barriga, Gonzalo P; Villalón-Letelier, Fernando; Márquez, Chantal L; Bignon, Eduardo A; Acuña, Rodrigo; Ross, Breyan H; Monasterio, Octavio; Mardones, Gonzalo A; Vidal, Simon E; Tischler, Nicole D

2016-07-01

Hantaviruses can cause hantavirus pulmonary syndrome or hemorrhagic fever with renal syndrome in humans. To enter cells, hantaviruses fuse their envelope membrane with host cell membranes. Previously, we have shown that the Gc envelope glycoprotein is the viral fusion protein sharing characteristics with class II fusion proteins. The ectodomain of class II fusion proteins is composed of three domains connected by a stem region to a transmembrane anchor in the viral envelope. These fusion proteins can be inhibited through exogenous fusion protein fragments spanning domain III (DIII) and the stem region. Such fragments are thought to interact with the core of the fusion protein trimer during the transition from its pre-fusion to its post-fusion conformation. Based on our previous homology model structure for Gc from Andes hantavirus (ANDV), here we predicted and generated recombinant DIII and stem peptides to test whether these fragments inhibit hantavirus membrane fusion and cell entry. Recombinant ANDV DIII was soluble, presented disulfide bridges and beta-sheet secondary structure, supporting the in silico model. Using DIII and the C-terminal part of the stem region, the infection of cells by ANDV was blocked up to 60% when fusion of ANDV occurred within the endosomal route, and up to 95% when fusion occurred with the plasma membrane. Furthermore, the fragments impaired ANDV glycoprotein-mediated cell-cell fusion, and cross-inhibited the fusion mediated by the glycoproteins from Puumala virus (PUUV). The Gc fragments interfered in ANDV cell entry by preventing membrane hemifusion and pore formation, retaining Gc in a non-resistant homotrimer stage, as described for DIII and stem peptide inhibitors of class II fusion proteins. Collectively, our results demonstrate that hantavirus Gc shares not only structural, but also mechanistic similarity with class II viral fusion proteins, and will hopefully help in developing novel therapeutic strategies against hantaviruses.

Predictive Variable Gain Iterative Learning Control for PMSM

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Huimin Xu

2015-01-01

Full Text Available A predictive variable gain strategy in iterative learning control (ILC is introduced. Predictive variable gain iterative learning control is constructed to improve the performance of trajectory tracking. A scheme based on predictive variable gain iterative learning control for eliminating undesirable vibrations of PMSM system is proposed. The basic idea is that undesirable vibrations of PMSM system are eliminated from two aspects of iterative domain and time domain. The predictive method is utilized to determine the learning gain in the ILC algorithm. Compression mapping principle is used to prove the convergence of the algorithm. Simulation results demonstrate that the predictive variable gain is superior to constant gain and other variable gains.

The Interactomic Analysis Reveals Pathogenic Protein Networks in Phomopsis longicolla Underlying Seed Decay of Soybean

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Shuxian Li

2018-04-01

Full Text Available Phomopsis longicolla T. W. Hobbs (syn. Diaporthe longicolla is the primary cause of Phomopsis seed decay (PSD in soybean, Glycine max (L. Merrill. This disease results in poor seed quality and is one of the most economically important seed diseases in soybean. The objectives of this study were to infer protein–protein interactions (PPI and to identify conserved global networks and pathogenicity subnetworks in P. longicolla including orthologous pathways for cell signaling and pathogenesis. The interlog method used in the study identified 215,255 unique PPIs among 3,868 proteins. There were 1,414 pathogenicity related genes in P. longicolla identified using the pathogen host interaction (PHI database. Additionally, 149 plant cell wall degrading enzymes (PCWDE were detected. The network captured five different classes of carbohydrate degrading enzymes, including the auxiliary activities, carbohydrate esterases, glycoside hydrolases, glycosyl transferases, and carbohydrate binding molecules. From the PPI analysis, novel interacting partners were determined for each of the PCWDE classes. The most predominant class of PCWDE was a group of 60 glycoside hydrolases proteins. The glycoside hydrolase subnetwork was found to be interacting with 1,442 proteins within the network and was among the largest clusters. The orthologous proteins FUS3, HOG, CYP1, SGE1, and the g5566t.1 gene identified in this study could play an important role in pathogenicity. Therefore, the P. longicolla protein interactome (PiPhom generated in this study can lead to a better understanding of PPIs in soybean pathogens. Furthermore, the PPI may aid in targeting of genes and proteins for further studies of the pathogenicity mechanisms.

Domains and domain loss

DEFF Research Database (Denmark)

Haberland, Hartmut

2005-01-01

politicians and in the media, especially in the discussion whether some languages undergo ‘domain loss’ vis-à-vis powerful international languages like English. An objection that has been raised here is that domains, as originally conceived, are parameters of language choice and not properties of languages...

Improving the performance of DomainDiscovery of protein domain boundary assignment using inter-domain linker index

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Zomaya Albert Y

2006-12-01

Full Text Available Abstract Background Knowledge of protein domain boundaries is critical for the characterisation and understanding of protein function. The ability to identify domains without the knowledge of the structure – by using sequence information only – is an essential step in many types of protein analyses. In this present study, we demonstrate that the performance of DomainDiscovery is improved significantly by including the inter-domain linker index value for domain identification from sequence-based information. Improved DomainDiscovery uses a Support Vector Machine (SVM approach and a unique training dataset built on the principle of consensus among experts in defining domains in protein structure. The SVM was trained using a PSSM (Position Specific Scoring Matrix, secondary structure, solvent accessibility information and inter-domain linker index to detect possible domain boundaries for a target sequence. Results Improved DomainDiscovery is compared with other methods by benchmarking against a structurally non-redundant dataset and also CASP5 targets. Improved DomainDiscovery achieves 70% accuracy for domain boundary identification in multi-domains proteins. Conclusion Improved DomainDiscovery compares favourably to the performance of other methods and excels in the identification of domain boundaries for multi-domain proteins as a result of introducing support vector machine with benchmark_2 dataset.

The drug-minded protein interaction database (DrumPID) for efficient target analysis and drug development.

Science.gov (United States)

Kunz, Meik; Liang, Chunguang; Nilla, Santosh; Cecil, Alexander; Dandekar, Thomas

2016-01-01

The drug-minded protein interaction database (DrumPID) has been designed to provide fast, tailored information on drugs and their protein networks including indications, protein targets and side-targets. Starting queries include compound, target and protein interactions and organism-specific protein families. Furthermore, drug name, chemical structures and their SMILES notation, affected proteins (potential drug targets), organisms as well as diseases can be queried including various combinations and refinement of searches. Drugs and protein interactions are analyzed in detail with reference to protein structures and catalytic domains, related compound structures as well as potential targets in other organisms. DrumPID considers drug functionality, compound similarity, target structure, interactome analysis and organismic range for a compound, useful for drug development, predicting drug side-effects and structure-activity relationships.Database URL:http://drumpid.bioapps.biozentrum.uni-wuerzburg.de. © The Author(s) 2016. Published by Oxford University Press.

IIS--Integrated Interactome System: a web-based platform for the annotation, analysis and visualization of protein-metabolite-gene-drug interactions by integrating a variety of data sources and tools.

Science.gov (United States)

Carazzolle, Marcelo Falsarella; de Carvalho, Lucas Miguel; Slepicka, Hugo Henrique; Vidal, Ramon Oliveira; Pereira, Gonçalo Amarante Guimarães; Kobarg, Jörg; Meirelles, Gabriela Vaz

2014-01-01

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

The Reactive Species Interactome: Evolutionary Emergence, Biological Significance, and Opportunities for Redox Metabolomics and Personalized Medicine.

Science.gov (United States)

Cortese-Krott, Miriam M; Koning, Anne; Kuhnle, Gunter G C; Nagy, Peter; Bianco, Christopher L; Pasch, Andreas; Wink, David A; Fukuto, Jon M; Jackson, Alan A; van Goor, Harry; Olson, Kenneth R; Feelisch, Martin

2017-10-01

Oxidative stress is thought to account for aberrant redox homeostasis and contribute to aging and disease. However, more often than not, administration of antioxidants is ineffective, suggesting that our current understanding of the underlying regulatory processes is incomplete. Recent Advances: Similar to reactive oxygen species and reactive nitrogen species, reactive sulfur species are now emerging as important signaling molecules, targeting regulatory cysteine redox switches in proteins, affecting gene regulation, ion transport, intermediary metabolism, and mitochondrial function. To rationalize the complexity of chemical interactions of reactive species with themselves and their targets and help define their role in systemic metabolic control, we here introduce a novel integrative concept defined as the reactive species interactome (RSI). The RSI is a primeval multilevel redox regulatory system whose architecture, together with the physicochemical characteristics of its constituents, allows efficient sensing and rapid adaptation to environmental changes and various other stressors to enhance fitness and resilience at the local and whole-organism level. To better characterize the RSI-related processes that determine fluxes through specific pathways and enable integration, it is necessary to disentangle the chemical biology and activity of reactive species (including precursors and reaction products), their targets, communication systems, and effects on cellular, organ, and whole-organism bioenergetics using system-level/network analyses. Understanding the mechanisms through which the RSI operates will enable a better appreciation of the possibilities to modulate the entire biological system; moreover, unveiling molecular signatures that characterize specific environmental challenges or other forms of stress will provide new prevention/intervention opportunities for personalized medicine. Antioxid. Redox Signal. 00, 000-000.

Comparative proteomic analysis of normal and collagen IX null mouse cartilage reveals altered extracellular matrix composition and novel components of the collagen IX interactome.

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Brachvogel, Bent; Zaucke, Frank; Dave, Keyur; Norris, Emma L; Stermann, Jacek; Dayakli, Münire; Koch, Manuel; Gorman, Jeffrey J; Bateman, John F; Wilson, Richard

2013-05-10

Collagen IX is an integral cartilage extracellular matrix component important in skeletal development and joint function. Proteomic analysis and validation studies revealed novel alterations in collagen IX null cartilage. Matrilin-4, collagen XII, thrombospondin-4, fibronectin, βig-h3, and epiphycan are components of the in vivo collagen IX interactome. We applied a proteomics approach to advance our understanding of collagen IX ablation in cartilage. The cartilage extracellular matrix is essential for endochondral bone development and joint function. In addition to the major aggrecan/collagen II framework, the interacting complex of collagen IX, matrilin-3, and cartilage oligomeric matrix protein (COMP) is essential for cartilage matrix stability, as mutations in Col9a1, Col9a2, Col9a3, Comp, and Matn3 genes cause multiple epiphyseal dysplasia, in which patients develop early onset osteoarthritis. In mice, collagen IX ablation results in severely disturbed growth plate organization, hypocellular regions, and abnormal chondrocyte shape. This abnormal differentiation is likely to involve altered cell-matrix interactions but the mechanism is not known. To investigate the molecular basis of the collagen IX null phenotype we analyzed global differences in protein abundance between wild-type and knock-out femoral head cartilage by capillary HPLC tandem mass spectrometry. We identified 297 proteins in 3-day cartilage and 397 proteins in 21-day cartilage. Components that were differentially abundant between wild-type and collagen IX-deficient cartilage included 15 extracellular matrix proteins. Collagen IX ablation was associated with dramatically reduced COMP and matrilin-3, consistent with known interactions. Matrilin-1, matrilin-4, epiphycan, and thrombospondin-4 levels were reduced in collagen IX null cartilage, providing the first in vivo evidence for these proteins belonging to the collagen IX interactome. Thrombospondin-4 expression was reduced at the mRNA level

Evolution based on domain combinations: the case of glutaredoxins

Directory of Open Access Journals (Sweden)

Herrero Enrique

2009-03-01

Full Text Available Abstract Background Protein domains represent the basic units in the evolution of proteins. Domain duplication and shuffling by recombination and fusion, followed by divergence are the most common mechanisms in this process. Such domain fusion and recombination events are predicted to occur only once for a given multidomain architecture. However, other scenarios may be relevant in the evolution of specific proteins, such as convergent evolution of multidomain architectures. With this in mind, we study glutaredoxin (GRX domains, because these domains of approximately one hundred amino acids are widespread in archaea, bacteria and eukaryotes and participate in fusion proteins. GRXs are responsible for the reduction of protein disulfides or glutathione-protein mixed disulfides and are involved in cellular redox regulation, although their specific roles and targets are often unclear. Results In this work we analyze the distribution and evolution of GRX proteins in archaea, bacteria and eukaryotes. We study over one thousand GRX proteins, each containing at least one GRX domain, from hundreds of different organisms and trace the origin and evolution of the GRX domain within the tree of life. Conclusion Our results suggest that single domain GRX proteins of the CGFS and CPYC classes have, each, evolved through duplication and divergence from one initial gene that was present in the last common ancestor of all organisms. Remarkably, we identify a case of convergent evolution in domain architecture that involves the GRX domain. Two independent recombination events of a TRX domain to a GRX domain are likely to have occurred, which is an exception to the dominant mechanism of domain architecture evolution.

A dimensional approach to assessing personality functioning: examining personality trait domains utilizing DSM-IV personality disorder criteria.

Science.gov (United States)

Christopher Fowler, J; Sharp, Carla; Kalpakci, Allison; Madan, Alok; Clapp, Joshua; Allen, Jon G; Christopher Frueh, B; Oldham, John M

2015-01-01

This study compared a dimensional, trait domain approach to characterizing personality pathology with the traditional polythetic approach with respect to their associations with interpersonal functioning and personality traits from the five factor model. Psychiatric inpatients (N=1476) were administered the Structured Clinical Interview for DSM-IV Axis II personality disorders. Dimensional representations of trait domains were derived from reorganizing DSM-IV criteria into personality trait domains from DSM-5 Alternative Model. Dimensional scores and personality disorder (PD) total criterion scores served as independent variables in predicting interpersonal profile clusters, as well as extraversion, agreeableness conscientiousness, neuroticism and openness from the five factor model traits. Trait domain scores and PD criteria totals were significantly correlated with submissive interpersonal style yet none proved significant in regression analyses. Avoidant and borderline PD total criteria were negatively associated with a normative interpersonal style. Combined trait domain of detachment and avoidant PD total criteria predicted a hostile/withdrawn interpersonal style. The trait domain of detachment was negatively associated with five factor traits of extroversion, whereas borderline PD total criteria were negatively associated with conscientiousness. Avoidant and borderline PD total criteria were positively associated with neuroticism. The cross-cutting dimensional approach provided useful information in predicting a hostile/withdrawn interpersonal style as well as extroversion. Importantly, PD criterion scores and dimensional trait scores combined to predict this interpersonal style providing support to the alternative model of personality diagnosis in DSM-5. Clinicians are encouraged to assess dimensions of personality traits as these are related to interpersonal problems frequently encountered in psychiatric settings. While potentially useful, the dimensional

Membrane and Protein Interactions of the Pleckstrin Homology Domain Superfamily

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Marc Lenoir

2015-10-01

Full Text Available The human genome encodes about 285 proteins that contain at least one annotated pleckstrin homology (PH domain. As the first phosphoinositide binding module domain to be discovered, the PH domain recruits diverse protein architectures to cellular membranes. PH domains constitute one of the largest protein superfamilies, and have diverged to regulate many different signaling proteins and modules such as Dbl homology (DH and Tec homology (TH domains. The ligands of approximately 70 PH domains have been validated by binding assays and complexed structures, allowing meaningful extrapolation across the entire superfamily. Here the Membrane Optimal Docking Area (MODA program is used at a genome-wide level to identify all membrane docking PH structures and map their lipid-binding determinants. In addition to the linear sequence motifs which are employed for phosphoinositide recognition, the three dimensional structural features that allow peripheral membrane domains to approach and insert into the bilayer are pinpointed and can be predicted ab initio. The analysis shows that conserved structural surfaces distinguish which PH domains associate with membrane from those that do not. Moreover, the results indicate that lipid-binding PH domains can be classified into different functional subgroups based on the type of membrane insertion elements they project towards the bilayer.

Membrane and Protein Interactions of the Pleckstrin Homology Domain Superfamily.

Science.gov (United States)

Lenoir, Marc; Kufareva, Irina; Abagyan, Ruben; Overduin, Michael

2015-10-23

The human genome encodes about 285 proteins that contain at least one annotated pleckstrin homology (PH) domain. As the first phosphoinositide binding module domain to be discovered, the PH domain recruits diverse protein architectures to cellular membranes. PH domains constitute one of the largest protein superfamilies, and have diverged to regulate many different signaling proteins and modules such as Dbl homology (DH) and Tec homology (TH) domains. The ligands of approximately 70 PH domains have been validated by binding assays and complexed structures, allowing meaningful extrapolation across the entire superfamily. Here the Membrane Optimal Docking Area (MODA) program is used at a genome-wide level to identify all membrane docking PH structures and map their lipid-binding determinants. In addition to the linear sequence motifs which are employed for phosphoinositide recognition, the three dimensional structural features that allow peripheral membrane domains to approach and insert into the bilayer are pinpointed and can be predicted ab initio. The analysis shows that conserved structural surfaces distinguish which PH domains associate with membrane from those that do not. Moreover, the results indicate that lipid-binding PH domains can be classified into different functional subgroups based on the type of membrane insertion elements they project towards the bilayer.

Peak-summer East Asian rainfall predictability and prediction part II: extratropical East Asia

Science.gov (United States)

Yim, So-Young; Wang, Bin; Xing, Wen

2016-07-01

The part II of the present study focuses on northern East Asia (NEA: 26°N-50°N, 100°-140°E), exploring the source and limit of the predictability of the peak summer (July-August) rainfall. Prediction of NEA peak summer rainfall is extremely challenging because of the exposure of the NEA to midlatitude influence. By examining four coupled climate models' multi-model ensemble (MME) hindcast during 1979-2010, we found that the domain-averaged MME temporal correlation coefficient (TCC) skill is only 0.13. It is unclear whether the dynamical models' poor skills are due to limited predictability of the peak-summer NEA rainfall. In the present study we attempted to address this issue by applying predictable mode analysis method using 35-year observations (1979-2013). Four empirical orthogonal modes of variability and associated major potential sources of variability are identified: (a) an equatorial western Pacific (EWP)-NEA teleconnection driven by EWP sea surface temperature (SST) anomalies, (b) a western Pacific subtropical high and Indo-Pacific dipole SST feedback mode, (c) a central Pacific-El Nino-Southern Oscillation mode, and (d) a Eurasian wave train pattern. Physically meaningful predictors for each principal component (PC) were selected based on analysis of the lead-lag correlations with the persistent and tendency fields of SST and sea-level pressure from March to June. A suite of physical-empirical (P-E) models is established to predict the four leading PCs. The peak summer rainfall anomaly pattern is then objectively predicted by using the predicted PCs and the corresponding observed spatial patterns. A 35-year cross-validated hindcast over the NEA yields a domain-averaged TCC skill of 0.36, which is significantly higher than the MME dynamical hindcast (0.13). The estimated maximum potential attainable TCC skill averaged over the entire domain is around 0.61, suggesting that the current dynamical prediction models may have large rooms to improve

Characterizing implicit mental health associations across clinical domains.

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Werntz, Alexandra J; Steinman, Shari A; Glenn, Jeffrey J; Nock, Matthew K; Teachman, Bethany A

2016-09-01

Implicit associations are relatively uncontrollable associations between concepts in memory. The current investigation focuses on implicit associations in four mental health domains (alcohol use, anxiety, depression, and eating disorders) and how these implicit associations: a) relate to explicit associations and b) self-reported clinical symptoms within the same domains, and c) vary based on demographic characteristics (age, gender, race, ethnicity, and education). Participants (volunteers over age 18 to a research website) completed implicit association (Implicit Association Tests), explicit association (self + psychopathology or attitudes toward food, using semantic differential items), and symptom measures at the Project Implicit Mental Health website tied to: alcohol use (N = 12,387), anxiety (N = 21,304), depression (N = 24,126), or eating disorders (N = 10,115). Within each domain, implicit associations showed small to moderate associations with explicit associations and symptoms, and predicted self-reported symptoms beyond explicit associations. In general, implicit association strength varied little by race and ethnicity, but showed small ties to age, gender, and education. This research was conducted on a public research and education website, where participants could take more than one of the studies. Among a large and diverse sample, implicit associations in the four domains are congruent with explicit associations and self-reported symptoms, and also add to our prediction of self-reported symptoms over and above explicit associations, pointing to the potential future clinical utility and validity of using implicit association measures with diverse populations. Copyright © 2016 Elsevier Ltd. All rights reserved.

A time-domain binaural detection model and its predictions temporal-resolution data

NARCIS (Netherlands)

Breebaart, D.J.; Par, van de S.L.J.D.E.; Kohlrausch, A.G.

2002-01-01

This paper discusses the application of a time-domain binaural signal-detection model in the context of estimates of the temporal resolution of the binaural auditory system. It is demonstrated that the optimal detector which is present in the model is crucial to account for specific temporal

The Cardiomyocyte RNA-Binding Proteome: Links to Intermediary Metabolism and Heart Disease

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Yalin Liao

2016-08-01

Full Text Available RNA functions through the dynamic formation of complexes with RNA-binding proteins (RBPs in all clades of life. We determined the RBP repertoire of beating cardiomyocytic HL-1 cells by jointly employing two in vivo proteomic methods, mRNA interactome capture and RBDmap. Together, these yielded 1,148 RBPs, 391 of which are shared with all other available mammalian RBP repertoires, while 393 are thus far unique to cardiomyocytes. RBDmap further identified 568 regions of RNA contact within 368 RBPs. The cardiomyocyte mRNA interactome composition reflects their unique biology. Proteins with roles in cardiovascular physiology or disease, mitochondrial function, and intermediary metabolism are all highly represented. Notably, we identified 73 metabolic enzymes as RBPs. RNA-enzyme contacts frequently involve Rossmann fold domains with examples in evidence of both, mutual exclusivity of, or compatibility between RNA binding and enzymatic function. Our findings raise the prospect of previously hidden RNA-mediated regulatory interactions among cardiomyocyte gene expression, physiology, and metabolism.

Frequency-domain thermal modelling of power semiconductor devices

DEFF Research Database (Denmark)

Ma, Ke; Blaabjerg, Frede; Andresen, Markus

2015-01-01

to correctly predict the device temperatures, especially when considering the thermal grease and heat sink attached to the power semiconductor devices. In this paper, the frequency-domain approach is applied to the modelling of thermal dynamics for power devices. The limits of the existing RC lump...

Structural and Histone Binding Ability Characterizations of Human PWWP Domains

Energy Technology Data Exchange (ETDEWEB)

Wu, Hong; Zeng, Hong; Lam, Robert; Tempel, Wolfram; Amaya, Maria F.; Xu, Chao; Dombrovski, Ludmila; Qiu, Wei; Wang, Yanming; Min, Jinrong (Toronto); (Penn)

2013-09-25

The PWWP domain was first identified as a structural motif of 100-130 amino acids in the WHSC1 protein and predicted to be a protein-protein interaction domain. It belongs to the Tudor domain 'Royal Family', which consists of Tudor, chromodomain, MBT and PWWP domains. While Tudor, chromodomain and MBT domains have long been known to bind methylated histones, PWWP was shown to exhibit histone binding ability only until recently. The PWWP domain has been shown to be a DNA binding domain, but sequence analysis and previous structural studies show that the PWWP domain exhibits significant similarity to other 'Royal Family' members, implying that the PWWP domain has the potential to bind histones. In order to further explore the function of the PWWP domain, we used the protein family approach to determine the crystal structures of the PWWP domains from seven different human proteins. Our fluorescence polarization binding studies show that PWWP domains have weak histone binding ability, which is also confirmed by our NMR titration experiments. Furthermore, we determined the crystal structures of the BRPF1 PWWP domain in complex with H3K36me3, and HDGF2 PWWP domain in complex with H3K79me3 and H4K20me3. PWWP proteins constitute a new family of methyl lysine histone binders. The PWWP domain consists of three motifs: a canonical {beta}-barrel core, an insertion motif between the second and third {beta}-strands and a C-terminal {alpha}-helix bundle. Both the canonical {beta}-barrel core and the insertion motif are directly involved in histone binding. The PWWP domain has been previously shown to be a DNA binding domain. Therefore, the PWWP domain exhibits dual functions: binding both DNA and methyllysine histones.

Structure of the C-terminal domain of lettuce necrotic yellows virus phosphoprotein.

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Martinez, Nicolas; Ribeiro, Euripedes A; Leyrat, Cédric; Tarbouriech, Nicolas; Ruigrok, Rob W H; Jamin, Marc

2013-09-01

Lettuce necrotic yellows virus (LNYV) is a prototype of the plant-adapted cytorhabdoviruses. Through a meta-prediction of disorder, we localized a folded C-terminal domain in the amino acid sequence of its phosphoprotein. This domain consists of an autonomous folding unit that is monomeric in solution. Its structure, solved by X-ray crystallography, reveals a lollipop-shaped structure comprising five helices. The structure is different from that of the corresponding domains of other Rhabdoviridae, Filoviridae, and Paramyxovirinae; only the overall topology of the polypeptide chain seems to be conserved, suggesting that this domain evolved under weak selective pressure and varied in size by the acquisition or loss of functional modules.

Comparing Spatial Predictions

KAUST Repository

Hering, Amanda S.; Genton, Marc G.

2011-01-01

Under a general loss function, we develop a hypothesis test to determine whether a significant difference in the spatial predictions produced by two competing models exists on average across the entire spatial domain of interest. The null hypothesis

Exploring Cognitive Relations Between Prediction in Language and Music.

Science.gov (United States)

Patel, Aniruddh D; Morgan, Emily

2017-03-01

The online processing of both music and language involves making predictions about upcoming material, but the relationship between prediction in these two domains is not well understood. Electrophysiological methods for studying individual differences in prediction in language processing have opened the door to new questions. Specifically, we ask whether individuals with musical training predict upcoming linguistic material more strongly and/or more accurately than non-musicians. We propose two reasons why prediction in these two domains might be linked: (a) Musicians may have greater verbal short-term/working memory; (b) music may specifically reward predictions based on hierarchical structure. We provide suggestions as to how to expand upon recent work on individual differences in language processing to test these hypotheses. Copyright © 2016 Cognitive Science Society, Inc.

Domain-Specific Impulsivity in School-Age Children

Science.gov (United States)

Tsukayama, Eli; Duckworth, Angela Lee; Kim, Betty

2013-01-01

Impulsivity is a salient individual difference in children with well-established predictive validity for life outcomes. The current investigation proposes that impulsive behaviors vary systematically by domain. In a series of studies with ethnically and socioeconomically diverse samples of middle school students, we find that schoolwork-related and interpersonal-related impulsivity, as observed by teachers, parents, and the students themselves, are distinct, moderately correlated behavioral tendencies. Each demonstrates differentiated relationships with dimensions of childhood temperament, Big Five personality factors, and outcomes, such as sociometric popularity, report card grades, and classroom conduct. Implications for theoretical conceptions of impulsivity as well as for practical applications (e.g., domain-specific interventions) are discussed. PMID:24118714

Epitope mapping of the domains of human angiotensin converting enzyme.

Science.gov (United States)

Kugaevskaya, Elena V; Kolesanova, Ekaterina F; Kozin, Sergey A; Veselovsky, Alexander V; Dedinsky, Ilya R; Elisseeva, Yulia E

2006-06-01

Somatic angiotensin converting enzyme (sACE), contains in its single chain two homologous domains (called N- and C-domains), each bearing a functional zinc-dependent active site. The present study aims to define the differences between two sACE domains and to localize experimentally revealed antigenic determinants (B-epitopes) in the recently determined three-dimensional structure of testicular tACE. The predicted linear antigenic determinants of human sACE were determined by peptide scanning ("PEPSCAN") approach. Essential difference was demonstrated between locations of the epitopes in the N- and C-domains. Comparison of arrangement of epitopes in the human domains with the corresponding sequences of some mammalian sACEs enabled to classify the revealed antigenic determinants as variable or conserved areas. The location of antigenic determinants with respect to various structural elements and to functionally important sites of the human sACE C-domain was estimated. The majority of antigenic sites of the C-domain were located at the irregular elements and at the boundaries of secondary structure elements. The data show structural differences between the sACE domains. The experimentally revealed antigenic determinants were in agreement with the recently determined crystal tACE structure. New potential applications are open to successfully produce mono-specific and group-specific antipeptide antibodies.

Structure of the GH1 domain of guanylate kinase-associated protein from Rattus norvegicus

International Nuclear Information System (INIS)

Tong, Junsen; Yang, Huiseon; Eom, Soo Hyun; Chun, ChangJu; Im, Young Jun

2014-01-01

Graphical abstract: - Highlights: • The crystal structure of GKAP homology domain 1 (GH1) was determined. • GKAP GH1 is a three-helix bundle connected by short flexible loops. • The predicted helix α4 associates weakly with the helix α3, suggesting dynamic nature of the GH1 domain. - Abstract: Guanylate-kinase-associated protein (GKAP) is a scaffolding protein that links NMDA receptor-PSD-95 to Shank–Homer complexes by protein–protein interactions at the synaptic junction. GKAP family proteins are characterized by the presence of a C-terminal conserved GKAP homology domain 1 (GH1) of unknown structure and function. In this study, crystal structure of the GH1 domain of GKAP from Rattus norvegicus was determined in fusion with an N-terminal maltose-binding protein at 2.0 Å resolution. The structure of GKAP GH1 displays a three-helix bundle connected by short flexible loops. The predicted helix α4 which was not visible in the crystal structure associates weakly with the helix α3 suggesting dynamic nature of the GH1 domain. The strict conservation of GH1 domain across GKAP family members and the lack of a catalytic active site required for enzyme activity imply that the GH1 domain might serve as a protein–protein interaction module for the synaptic protein clustering

Structure of the GH1 domain of guanylate kinase-associated protein from Rattus norvegicus

Energy Technology Data Exchange (ETDEWEB)

Tong, Junsen; Yang, Huiseon [College of Pharmacy, Chonnam National University, Gwangju 500-757 (Korea, Republic of); Eom, Soo Hyun [School of Life Sciences, Steitz Center for Structural Biology, and Department of Chemistry, Gwangju Institute of Science and Technology, Gwangju 500-712 (Korea, Republic of); Chun, ChangJu, E-mail: cchun1130@jnu.ac.kr [College of Pharmacy, Chonnam National University, Gwangju 500-757 (Korea, Republic of); Im, Young Jun, E-mail: imyoungjun@jnu.ac.kr [College of Pharmacy, Chonnam National University, Gwangju 500-757 (Korea, Republic of)

2014-09-12

Graphical abstract: - Highlights: • The crystal structure of GKAP homology domain 1 (GH1) was determined. • GKAP GH1 is a three-helix bundle connected by short flexible loops. • The predicted helix α4 associates weakly with the helix α3, suggesting dynamic nature of the GH1 domain. - Abstract: Guanylate-kinase-associated protein (GKAP) is a scaffolding protein that links NMDA receptor-PSD-95 to Shank–Homer complexes by protein–protein interactions at the synaptic junction. GKAP family proteins are characterized by the presence of a C-terminal conserved GKAP homology domain 1 (GH1) of unknown structure and function. In this study, crystal structure of the GH1 domain of GKAP from Rattus norvegicus was determined in fusion with an N-terminal maltose-binding protein at 2.0 Å resolution. The structure of GKAP GH1 displays a three-helix bundle connected by short flexible loops. The predicted helix α4 which was not visible in the crystal structure associates weakly with the helix α3 suggesting dynamic nature of the GH1 domain. The strict conservation of GH1 domain across GKAP family members and the lack of a catalytic active site required for enzyme activity imply that the GH1 domain might serve as a protein–protein interaction module for the synaptic protein clustering.

Measuring time and risk preferences: Reliability, stability, domain specificity

NARCIS (Netherlands)

Wölbert, E.M.; Riedl, A.M.

2013-01-01

To accurately predict behavior economists need reliable measures of individual time preferences and attitudes toward risk and typically need to assume stability of these characteristics over time and across decision domains. We test the reliability of two choice tasks for eliciting discount rates,

Definition of the applicability domain of the Short Time Exposure (STE) test for predicting the eye irritation of chemicals.

Science.gov (United States)

Hayashi, Kazuhiko; Abo, Takayuki; Nukada, Yuko; Sakaguchi, Hitoshi

2013-05-01

The Short Time Exposure (STE) test is a simple and easy-to-perform in vitro eye irritation test, that uses the viability of SIRC cells (a rabbit corneal cell line) treated for five minutes as the endpoint. In this study, our goal was to define the applicability domain of the STE test, based on the results obtained with a set of 113 substances. To achieve this goal, chemicals were selected to represent both different chemical classes and different chemical properties, as well as to cover, in a balanced manner, the categories of eye irritation potential according to the Globally Harmonised System (GHS). Accuracy analysis indicated that the rates of false negatives for organic/inorganic salts (75.0%), hydrocarbons (33.3%) and alcohols (23.5%) were high. Many of the false negative results were for solid substances. It is noteworthy that no surfactant resulted in a false negative result in the STE test. Further examination of the physical property data and performance showed a significant improvement in the predictive accuracy, when substances with vapour pressures over 6kPa were excluded from the analyses. Our results indicate that several substances - i.e. certain solids such as salts, alcohols, hydrocarbons, and volatile substances with a vapour pressure over 6kPa - do not fall within the applicability domain of the STE test. Overall, we are encouraged by the performance and improved accuracy of the STE test. 2013 FRAME.

Hypothesis: NDL proteins function in stress responses by regulating microtubule organization.

Science.gov (United States)

Khatri, Nisha; Mudgil, Yashwanti

2015-01-01

N-MYC DOWNREGULATED-LIKE proteins (NDL), members of the alpha/beta hydrolase superfamily were recently rediscovered as interactors of G-protein signaling in Arabidopsis thaliana. Although the precise molecular function of NDL proteins is still elusive, in animals these proteins play protective role in hypoxia and expression is induced by hypoxia and nickel, indicating role in stress. Homology of NDL1 with animal counterpart N-MYC DOWNREGULATED GENE (NDRG) suggests similar functions in animals and plants. It is well established that stress responses leads to the microtubule depolymerization and reorganization which is crucial for stress tolerance. NDRG is a microtubule-associated protein which mediates the microtubule organization in animals by causing acetylation and increases the stability of α-tubulin. As NDL1 is highly homologous to NDRG, involvement of NDL1 in the microtubule organization during plant stress can also be expected. Discovery of interaction of NDL with protein kinesin light chain- related 1, enodomembrane family protein 70, syntaxin-23, tubulin alpha-2 chain, as a part of G protein interactome initiative encourages us to postulate microtubule stabilizing functions for NDL family in plants. Our search for NDL interactors in G protein interactome also predicts the role of NDL proteins in abiotic stress tolerance management. Based on published report in animals and predicted interacting partners for NDL in G protein interactome lead us to hypothesize involvement of NDL in the microtubule organization during abiotic stress management in plants.

A new scaling approach for the mesoscale simulation of magnetic domain structures using Monte Carlo simulations

Energy Technology Data Exchange (ETDEWEB)

Radhakrishnan, B., E-mail: radhakrishnb@ornl.gov; Eisenbach, M.; Burress, T.A.

2017-06-15

Highlights: • Developed new scaling technique for dipole–dipole interaction energy. • Developed new scaling technique for exchange interaction energy. • Used scaling laws to extend atomistic simulations to micrometer length scale. • Demonstrated transition from mono-domain to vortex magnetic structure. • Simulated domain wall width and transition length scale agree with experiments. - Abstract: A new scaling approach has been proposed for the spin exchange and the dipole–dipole interaction energy as a function of the system size. The computed scaling laws are used in atomistic Monte Carlo simulations of magnetic moment evolution to predict the transition from single domain to a vortex structure as the system size increases. The width of a 180° – domain wall extracted from the simulated structures is in close agreement with experimentally values for an F–Si alloy. The transition size from a single domain to a vortex structure is also in close agreement with theoretically predicted and experimentally measured values for Fe.

Figure 1. Prediction of ScHP1 transmembrane domains I to XIV. (http ...

Indian Academy of Sciences (India)

Figure 2. Comparison of the ScHP1 amino acid sequence with H. +. -PPase from other species. The conserved domains GGG,. DVGADLVGKVE, DNVGDNVGD, EYYT and GNTTAA were found in the sequence alignment (shown in red boxes).

Using the Positive and Negative Syndrome Scale (PANSS) to Define Different Domains of Negative Symptoms: Prediction of Everyday Functioning by Impairments in Emotional Expression and Emotional Experience.

Science.gov (United States)

Harvey, Philip D; Khan, Anzalee; Keefe, Richard S E

2017-12-01

Background: Reduced emotional experience and expression are two domains of negative symptoms. The authors assessed these two domains of negative symptoms using previously developed Positive and Negative Syndrome Scale (PANSS) factors. Using an existing dataset, the authors predicted three different elements of everyday functioning (social, vocational, and everyday activities) with these two factors, as well as with performance on measures of functional capacity. Methods: A large (n=630) sample of people with schizophrenia was used as the data source of this study. Using regression analyses, the authors predicted the three different aspects of everyday functioning, first with just the two Positive and Negative Syndrome Scale factors and then with a global negative symptom factor. Finally, we added neurocognitive performance and functional capacity as predictors. Results: The Positive and Negative Syndrome Scale reduced emotional experience factor accounted for 21 percent of the variance in everyday social functioning, while reduced emotional expression accounted for no variance. The total Positive and Negative Syndrome Scale negative symptom factor accounted for less variance (19%) than the reduced experience factor alone. The Positive and Negative Syndrome Scale expression factor accounted for, at most, one percent of the variance in any of the functional outcomes, with or without the addition of other predictors. Implications: Reduced emotional experience measured with the Positive and Negative Syndrome Scale, often referred to as "avolition and anhedonia," specifically predicted impairments in social outcomes. Further, reduced experience predicted social impairments better than emotional expression or the total Positive and Negative Syndrome Scale negative symptom factor. In this cross-sectional study, reduced emotional experience was specifically related with social outcomes, accounting for essentially no variance in work or everyday activities, and being the

Models for randomly distributed nanoscopic domains on spherical vesicles

Science.gov (United States)

Anghel, Vinicius N. P.; Bolmatov, Dima; Katsaras, John

2018-06-01

The existence of lipid domains in the plasma membrane of biological systems has proven controversial, primarily due to their nanoscopic size—a length scale difficult to interrogate with most commonly used experimental techniques. Scattering techniques have recently proven capable of studying nanoscopic lipid domains populating spherical vesicles. However, the development of analytical methods able of predicting and analyzing domain pair correlations from such experiments has not kept pace. Here, we developed models for the random distribution of monodisperse, circular nanoscopic domains averaged on the surface of a spherical vesicle. Specifically, the models take into account (i) intradomain correlations corresponding to form factors and interdomain correlations corresponding to pair distribution functions, and (ii) the analytical computation of interdomain correlations for cases of two and three domains on a spherical vesicle. In the case of more than three domains, these correlations are treated either by Monte Carlo simulations or by spherical analogs of the Ornstein-Zernike and Percus-Yevick (PY) equations. Importantly, the spherical analog of the PY equation works best in the case of nanoscopic size domains, a length scale that is mostly inaccessible by experimental approaches such as, for example, fluorescent techniques and optical microscopies. The analytical form factors and structure factors of nanoscopic domains populating a spherical vesicle provide a new and important framework for the quantitative analysis of experimental data from commonly studied phase-separated vesicles used in a wide range of biophysical studies.

Structures of the Gasdermin D C-Terminal Domains Reveal Mechanisms of Autoinhibition.

Science.gov (United States)

Liu, Zhonghua; Wang, Chuanping; Rathkey, Joseph K; Yang, Jie; Dubyak, George R; Abbott, Derek W; Xiao, Tsan Sam

2018-05-01

Pyroptosis is an inflammatory form of programmed cell death that plays important roles in immune protection against infections and in inflammatory disorders. Gasdermin D (GSDMD) is an executor of pyroptosis upon cleavage by caspases-1/4/5/11 following canonical and noncanonical inflammasome activation. GSDMD N-terminal domain assembles membrane pores to induce cytolysis, whereas its C-terminal domain inhibits cell death through intramolecular association with the N domain. The molecular mechanisms of autoinhibition for GSDMD are poorly characterized. Here we report the crystal structures of the human and murine GSDMD C-terminal domains, which differ from those of the full-length murine GSDMA3 and the human GSDMB C-terminal domain. Mutations of GSDMD C-domain residues predicted to locate at its interface with the N-domain enhanced pyroptosis. Our results suggest that GSDMDs may employ a distinct mode of intramolecular domain interaction and autoinhibition, which may be relevant to its unique role in pyroptosis downstream of inflammasome activation. Copyright © 2018 Elsevier Ltd. All rights reserved.

Structure of the C-Terminal Domain of Lettuce Necrotic Yellows Virus Phosphoprotein

Science.gov (United States)

Martinez, Nicolas; Ribeiro, Euripedes A.; Leyrat, Cédric; Tarbouriech, Nicolas; Ruigrok, Rob W. H.

2013-01-01

Lettuce necrotic yellows virus (LNYV) is a prototype of the plant-adapted cytorhabdoviruses. Through a meta-prediction of disorder, we localized a folded C-terminal domain in the amino acid sequence of its phosphoprotein. This domain consists of an autonomous folding unit that is monomeric in solution. Its structure, solved by X-ray crystallography, reveals a lollipop-shaped structure comprising five helices. The structure is different from that of the corresponding domains of other Rhabdoviridae, Filoviridae, and Paramyxovirinae; only the overall topology of the polypeptide chain seems to be conserved, suggesting that this domain evolved under weak selective pressure and varied in size by the acquisition or loss of functional modules. PMID:23785215

The arabidopsis cyclic nucleotide interactome

KAUST Repository

Donaldson, Lara Elizabeth

2016-05-11

Background Cyclic nucleotides have been shown to play important signaling roles in many physiological processes in plants including photosynthesis and defence. Despite this, little is known about cyclic nucleotide-dependent signaling mechanisms in plants since the downstream target proteins remain unknown. This is largely due to the fact that bioinformatics searches fail to identify plant homologs of protein kinases and phosphodiesterases that are the main targets of cyclic nucleotides in animals. Methods An affinity purification technique was used to identify cyclic nucleotide binding proteins in Arabidopsis thaliana. The identified proteins were subjected to a computational analysis that included a sequence, transcriptional co-expression and functional annotation analysis in order to assess their potential role in plant cyclic nucleotide signaling. Results A total of twelve cyclic nucleotide binding proteins were identified experimentally including key enzymes in the Calvin cycle and photorespiration pathway. Importantly, eight of the twelve proteins were shown to contain putative cyclic nucleotide binding domains. Moreover, the identified proteins are post-translationally modified by nitric oxide, transcriptionally co-expressed and annotated to function in hydrogen peroxide signaling and the defence response. The activity of one of these proteins, GLYGOLATE OXIDASE 1, a photorespiratory enzyme that produces hydrogen peroxide in response to Pseudomonas, was shown to be repressed by a combination of cGMP and nitric oxide treatment. Conclusions We propose that the identified proteins function together as points of cross-talk between cyclic nucleotide, nitric oxide and reactive oxygen species signaling during the defence response.

Work locus of control and its relationship to stress perception, related affections, attitudes and behaviours from a domain-specific perspective.

Science.gov (United States)

Tong, Jiajin; Wang, Lei

2012-08-01

This research aims to examine the value of applying the Work Locus of Control Scale in predicting work-related outcomes. Study 1 surveyed 323 employees from different companies in China and found that the domain-specific scale was more predictive than the general scale in predicting perceived stressors, rather than in predicting organizational affective commitment and altruistic behaviour. Study 2 applied a multi-wave and multi-source design and used commensurate Likert scales to measure work and general locus of control. Participants were 344 employees from one corporation. Work locus of control was found to be more useful in predicting supervisor-rated job performance, conscientious and altruistic behaviours. These findings help understand the theory-based and measurement-based reasons for the advantages of using domain-specific measures. They claim the importance for employing the domain-specific measure to predict work-related perceptions and behaviours. Implications for the theory and practice are discussed. Copyright © 2011 John Wiley & Sons, Ltd.

Mechanistic insights into phosphoprotein-binding FHA domains.

Science.gov (United States)

Liang, Xiangyang; Van Doren, Steven R

2008-08-01

[Structure: see text]. FHA domains are protein modules that switch signals in diverse biological pathways by monitoring the phosphorylation of threonine residues of target proteins. As part of the effort to gain insight into cellular avoidance of cancer, FHA domains involved in the cellular response to DNA damage have been especially well-characterized. The complete protein where the FHA domain resides and the interaction partners determine the nature of the signaling. Thus, a key biochemical question is how do FHA domains pick out their partners from among thousands of alternatives in the cell? This Account discusses the structure, affinity, and specificity of FHA domains and the formation of their functional structure. Although FHA domains share sequence identity at only five loop residues, they all fold into a beta-sandwich of two beta-sheets. The conserved arginine and serine of the recognition loops recognize the phosphorylation of the threonine targeted. Side chains emanating from loops that join beta-strand 4 with 5, 6 with 7, or 10 with 11 make specific contacts with amino acids of the ligand that tailor sequence preferences. Many FHA domains choose a partner in extended conformation, somewhat according to the residue three after the phosphothreonine in sequence (pT + 3 position). One group of FHA domains chooses a short carboxylate-containing side chain at pT + 3. Another group chooses a long, branched aliphatic side chain. A third group prefers other hydrophobic or uncharged polar side chains at pT + 3. However, another FHA domain instead chooses on the basis of pT - 2, pT - 3, and pT + 1 positions. An FHA domain from a marker of human cancer instead chooses a much longer protein fragment that adds a beta-strand to its beta-sheet and that presents hydrophobic residues from a novel helix to the usual recognition surface. This novel recognition site and more remote sites for the binding of other types of protein partners were predicted for the entire family

In silico target network analysis of de novo-discovered, tick saliva-specific microRNAs reveals important combinatorial effects in their interference with vertebrate host physiology

Czech Academy of Sciences Publication Activity Database

Hackenberg, M.; Langenberger, D.; Schwarz, Alexandra; Erhart, Jan; Kotsyfakis, Michalis

2017-01-01

Roč. 23, č. 8 (2017), s. 1259-1269 ISSN 1355-8382 Institutional support: RVO:60077344 Keywords : tick-vertebrate host interaction * deep-sequencing * microRNA * gene target prediction * interactomes/systems biology * disease biology Subject RIV: EB - Genetics ; Molecular Biology OBOR OECD: Biochemistry and molecular biology Impact factor: 4.605, year: 2016

Longitudinal analysis of domain-level breast cancer literacy among African-American women.

Science.gov (United States)

Mabiso, Athur; Williams, Karen Patricia; Todem, David; Templin, Thomas N

2010-02-01

Functional breast cancer literacy was assessed among African-American women and measured at the domain level over time. We used the Kin Keeper(SM) Cancer Prevention Intervention to educate 161 African-American women on three domains of breast cancer literacy: (i) cancer awareness, (ii) knowledge of breast cancer screening modalities and (iii) cancer prevention and control. A breast cancer literacy assessment was administered pre- and post-educational intervention at two time points followed by another assessment 12 months after the second intervention. Generalized estimating equations were specified to predict the probability of correctly answering questions in each domain over time. Domain-level literacy differentials exist; at baseline, women had higher test scores in the breast cancer prevention and control domain than the cancer awareness domain (odds ratio = 1.67, 95% confidence interval 1.19-2.34). After Kin Keeper(SM) Cancer Prevention Intervention, African-American women consistently improved their breast cancer literacy in all domains over the five time stages (P < 0.001) though at different rates for each domain. Differences in domain-level breast cancer literacy highlight the importance of assessing literacy at the domain level. Interventions to improve African-American women's breast cancer literacy should focus on knowledge of breast cancer screening modalities and cancer awareness domains.

Fine-tuning of protein domain boundary by minimizing potential coiled coil regions

International Nuclear Information System (INIS)

Iwaya, Naoko; Goda, Natsuko; Unzai, Satoru; Fujiwara, Kenichiro; Tanaka, Toshiki; Tomii, Kentaro; Tochio, Hidehito; Shirakawa, Masahiro; Hiroaki, Hidekazu

2007-01-01

Structural determination of individual protein domains isolated from multidomain proteins is a common approach in the post-genomic era. Novel and thus uncharacterized domains liberated from intact proteins often self-associate due to incorrectly defined domain boundaries. Self-association results in missing signals, poor signal dispersion and a low signal-to-noise ratio in 1 H- 15 N HSQC spectra. We have found that a putative, non-canonical coiled coil region close to a domain boundary can cause transient hydrophobic self-association and monomer-dimer equilibrium in solution. Here we propose a rational method to predict putative coiled coil regions adjacent to the globular core domain using the program COILS. Except for the amino acid sequence, no preexisting knowledge concerning the domain is required. A small number of mutant proteins with a minimized coiled coil region have been rationally designed and tested. The engineered domains exhibit decreased self-association as assessed by 1 H- 15 N HSQC spectra with improved peak dispersion and sharper cross peaks. Two successful examples of isolating novel N-terminal domains from AAA-ATPases are demonstrated. Our method is useful for the experimental determination of domain boundaries suited for structural genomics studies

Fine-tuning of protein domain boundary by minimizing potential coiled coil regions.

Science.gov (United States)

Iwaya, Naoko; Goda, Natsuko; Unzai, Satoru; Fujiwara, Kenichiro; Tanaka, Toshiki; Tomii, Kentaro; Tochio, Hidehito; Shirakawa, Masahiro; Hiroaki, Hidekazu

2007-01-01

Structural determination of individual protein domains isolated from multidomain proteins is a common approach in the post-genomic era. Novel and thus uncharacterized domains liberated from intact proteins often self-associate due to incorrectly defined domain boundaries. Self-association results in missing signals, poor signal dispersion and a low signal-to-noise ratio in (1)H-(15)N HSQC spectra. We have found that a putative, non-canonical coiled coil region close to a domain boundary can cause transient hydrophobic self-association and monomer-dimer equilibrium in solution. Here we propose a rational method to predict putative coiled coil regions adjacent to the globular core domain using the program COILS. Except for the amino acid sequence, no preexisting knowledge concerning the domain is required. A small number of mutant proteins with a minimized coiled coil region have been rationally designed and tested. The engineered domains exhibit decreased self-association as assessed by (1)H-(15)N HSQC spectra with improved peak dispersion and sharper cross peaks. Two successful examples of isolating novel N-terminal domains from AAA-ATPases are demonstrated. Our method is useful for the experimental determination of domain boundaries suited for structural genomics studies.

Unraveling the Plant-Soil Interactome

Science.gov (United States)

Lipton, M. S.; Hixson, K.; Ahkami, A. H.; HaHandkumbura, P. P.; Hess, N. J.; Fang, Y.; Fortin, D.; Stanfill, B.; Yabusaki, S.; Engbrecht, K. M.; Baker, E.; Renslow, R.; Jansson, C.

2017-12-01

Plant photosynthesis is the primary conduit of carbon fixation from the atmosphere to the terrestrial ecosystem. While more is known about plant physiology and biochemistry, the interplay between genetic and environmental factors that govern partitioning of carbon to above- and below ground plant biomass, to microbes, to the soil, and respired to the atmosphere is not well understood holistically. To address this knowledge gap there is a need to define, study, comprehend, and model the plant ecosystem as an integrated system of integrated biotic and abiotic processes and feedbacks. Local rhizosphere conditions are an important control on plant performance but are in turn affected by plant uptake and rhizodeposition processes. C3 and C4 plants have different CO2 fixation strategies and likely have differential metabolic profiles resulting in different carbon sources exuding to the rhizosphere. In this presentation, we report on an integrated capability to better understand plant-soil interactions, including modeling tools that address the spatiotemporal hydrobiogeochemistry in the rhizosphere. Comparing Brachypodium distachyon, (Brachypodium) as our C3 representative and Setaria viridis (Setaria) as our C4 representative, we designed, highly controlled single-plant experimental ecosystems based these model grasses to enable quantitative prediction of ecosystem traits and responses as a function of plant genotype and environmental variables. A metabolomics survey of 30 Brachypodium genotypes grown under control and drought conditions revealed specific metabolites that correlated with biomass production and drought tolerance. A comparison of Brachypodium and Setaria grown with control and a future predicted elevated CO2 level revealed changes in biomass accumulation and metabolite profiles between the C3 and C4 species in both leaves and roots. Finally, we are building an mechanistic modeling capability that will contribute to a better basis for modeling plant water

Predicting protein-protein interactions in Arabidopsis thaliana through integration of orthology, gene ontology and co-expression

Directory of Open Access Journals (Sweden)

Vandepoele Klaas

2009-06-01

Full Text Available Abstract Background Large-scale identification of the interrelationships between different components of the cell, such as the interactions between proteins, has recently gained great interest. However, unraveling large-scale protein-protein interaction maps is laborious and expensive. Moreover, assessing the reliability of the interactions can be cumbersome. Results In this study, we have developed a computational method that exploits the existing knowledge on protein-protein interactions in diverse species through orthologous relations on the one hand, and functional association data on the other hand to predict and filter protein-protein interactions in Arabidopsis thaliana. A highly reliable set of protein-protein interactions is predicted through this integrative approach making use of existing protein-protein interaction data from yeast, human, C. elegans and D. melanogaster. Localization, biological process, and co-expression data are used as powerful indicators for protein-protein interactions. The functional repertoire of the identified interactome reveals interactions between proteins functioning in well-conserved as well as plant-specific biological processes. We observe that although common mechanisms (e.g. actin polymerization and components (e.g. ARPs, actin-related proteins exist between different lineages, they are active in specific processes such as growth, cancer metastasis and trichome development in yeast, human and Arabidopsis, respectively. Conclusion We conclude that the integration of orthology with functional association data is adequate to predict protein-protein interactions. Through this approach, a high number of novel protein-protein interactions with diverse biological roles is discovered. Overall, we have predicted a reliable set of protein-protein interactions suitable for further computational as well as experimental analyses.

Is Time Predictability Quantifiable?

DEFF Research Database (Denmark)

Schoeberl, Martin

2012-01-01

Computer architects and researchers in the realtime domain start to investigate processors and architectures optimized for real-time systems. Optimized for real-time systems means time predictable, i.e., architectures where it is possible to statically derive a tight bound of the worst......-case execution time. To compare different approaches we would like to quantify time predictability. That means we need to measure time predictability. In this paper we discuss the different approaches for these measurements and conclude that time predictability is practically not quantifiable. We can only...... compare the worst-case execution time bounds of different architectures....

Blind prediction of interfacial water positions in CAPRI

NARCIS (Netherlands)

Lensink, Marc F; Moal, Iain H; Bates, Paul A; Kastritis, Panagiotis L; Melquiond, Adrien S J; Karaca, Ezgi; Schmitz, Christophe; van Dijk, Marc; Bonvin, Alexandre M J J; Eisenstein, Miriam; Jiménez-García, Brian; Grosdidier, Solène; Solernou, Albert; Pérez-Cano, Laura; Pallara, Chiara; Fernández-Recio, Juan; Xu, Jianqing; Muthu, Pravin; Praneeth Kilambi, Krishna; Gray, Jeffrey J; Grudinin, Sergei; Derevyanko, Georgy; Mitchell, Julie C; Wieting, John; Kanamori, Eiji; Tsuchiya, Yuko; Murakami, Yoichi; Sarmiento, Joy; Standley, Daron M; Shirota, Matsuyuki; Kinoshita, Kengo; Nakamura, Haruki; Chavent, Matthieu; Ritchie, David W; Park, Hahnbeom; Ko, Junsu; Lee, Hasup; Seok, Chaok; Shen, Yang; Kozakov, Dima; Vajda, Sandor; Kundrotas, Petras J; Vakser, Ilya A; Pierce, Brian G; Hwang, Howook; Vreven, Thom; Weng, Zhiping; Buch, Idit; Farkash, Efrat; Wolfson, Haim J; Zacharias, Martin; Qin, Sanbo; Zhou, Huan-Xiang; Huang, Shen-You; Zou, Xiaoqin; Wojdyla, Justyna A; Kleanthous, Colin; Wodak, Shoshana J

We report the first assessment of blind predictions of water positions at protein-protein interfaces, performed as part of the critical assessment of predicted interactions (CAPRI) community-wide experiment. Groups submitting docking predictions for the complex of the DNase domain of colicin E2 and

The BRCT domain is a phospho-protein binding domain.

Science.gov (United States)

Yu, Xiaochun; Chini, Claudia Christiano Silva; He, Miao; Mer, Georges; Chen, Junjie

2003-10-24

The carboxyl-terminal domain (BRCT) of the Breast Cancer Gene 1 (BRCA1) protein is an evolutionarily conserved module that exists in a large number of proteins from prokaryotes to eukaryotes. Although most BRCT domain-containing proteins participate in DNA-damage checkpoint or DNA-repair pathways, or both, the function of the BRCT domain is not fully understood. We show that the BRCA1 BRCT domain directly interacts with phosphorylated BRCA1-Associated Carboxyl-terminal Helicase (BACH1). This specific interaction between BRCA1 and phosphorylated BACH1 is cell cycle regulated and is required for DNA damage-induced checkpoint control during the transition from G2 to M phase of the cell cycle. Further, we show that two other BRCT domains interact with their respective physiological partners in a phosphorylation-dependent manner. Thirteen additional BRCT domains also preferentially bind phospho-peptides rather than nonphosphorylated control peptides. These data imply that the BRCT domain is a phospho-protein binding domain involved in cell cycle control.

Complex Systems Analysis of Cell Cycling Models in Carcinogenesis:II. Cell Genome and Interactome, Neoplastic Non-random Transformation Models in Topoi with Lukasiewicz-Logic and MV Algebras

CERN Document Server

Baianu, I C

2004-01-01

Quantitative Biology, abstract q-bio.OT/0406045 From: I.C. Baianu Dr. [view email] Date (v1): Thu, 24 Jun 2004 02:45:13 GMT (164kb) Date (revised v2): Fri, 2 Jul 2004 00:58:06 GMT (160kb) Complex Systems Analysis of Cell Cycling Models in Carcinogenesis: II. Authors: I.C. Baianu Comments: 23 pages, 1 Figure Report-no: CC04 Subj-class: Other Carcinogenesis is a complex process that involves dynamically inter-connected modular sub-networks that evolve under the influence of micro-environmentally induced perturbations, in non-random, pseudo-Markov chain processes. An appropriate n-stage model of carcinogenesis involves therefore n-valued Logic treatments of nonlinear dynamic transformations of complex functional genomes and cell interactomes. Lukasiewicz Algebraic Logic models of genetic networks and signaling pathways in cells are formulated in terms of nonlinear dynamic systems with n-state components that allow for the generalization of previous, Boolean or "fuzzy", logic models of genetic activities in vivo....

Stringent DDI-based prediction of H. sapiens-M. tuberculosis H37Rv protein-protein interactions.

Science.gov (United States)

Zhou, Hufeng; Rezaei, Javad; Hugo, Willy; Gao, Shangzhi; Jin, Jingjing; Fan, Mengyuan; Yong, Chern-Han; Wozniak, Michal; Wong, Limsoon

2013-01-01

H. sapiens-M. tuberculosis H37Rv protein-protein interaction (PPI) data are very important information to illuminate the infection mechanism of M. tuberculosis H37Rv. But current H. sapiens-M. tuberculosis H37Rv PPI data are very scarce. This seriously limits the study of the interaction between this important pathogen and its host H. sapiens. Computational prediction of H. sapiens-M. tuberculosis H37Rv PPIs is an important strategy to fill in the gap. Domain-domain interaction (DDI) based prediction is one of the frequently used computational approaches in predicting both intra-species and inter-species PPIs. However, the performance of DDI-based host-pathogen PPI prediction has been rather limited. We develop a stringent DDI-based prediction approach with emphasis on (i) differences between the specific domain sequences on annotated regions of proteins under the same domain ID and (ii) calculation of the interaction strength of predicted PPIs based on the interacting residues in their interaction interfaces. We compare our stringent DDI-based approach to a conventional DDI-based approach for predicting PPIs based on gold standard intra-species PPIs and coherent informative Gene Ontology terms assessment. The assessment results show that our stringent DDI-based approach achieves much better performance in predicting PPIs than the conventional approach. Using our stringent DDI-based approach, we have predicted a small set of reliable H. sapiens-M. tuberculosis H37Rv PPIs which could be very useful for a variety of related studies. We also analyze the H. sapiens-M. tuberculosis H37Rv PPIs predicted by our stringent DDI-based approach using cellular compartment distribution analysis, functional category enrichment analysis and pathway enrichment analysis. The analyses support the validity of our prediction result. Also, based on an analysis of the H. sapiens-M. tuberculosis H37Rv PPI network predicted by our stringent DDI-based approach, we have discovered some

A Wavelet Analysis-Based Dynamic Prediction Algorithm to Network Traffic

Directory of Open Access Journals (Sweden)

Meng Fan-Bo

2016-01-01

Full Text Available Network traffic is a significantly important parameter for network traffic engineering, while it holds highly dynamic nature in the network. Accordingly, it is difficult and impossible to directly predict traffic amount of end-to-end flows. This paper proposes a new prediction algorithm to network traffic using the wavelet analysis. Firstly, network traffic is converted into the time-frequency domain to capture time-frequency feature of network traffic. Secondly, in different frequency components, we model network traffic in the time-frequency domain. Finally, we build the prediction model about network traffic. At the same time, the corresponding prediction algorithm is presented to attain network traffic prediction. Simulation results indicates that our approach is promising.

Efficient multiscale magnetic-domain analysis of iron-core material under mechanical stress

Science.gov (United States)

Nishikubo, Atsushi; Ito, Shumpei; Mifune, Takeshi; Matsuo, Tetsuji; Kaido, Chikara; Takahashi, Yasuhito; Fujiwara, Koji

2018-05-01

For an efficient analysis of magnetization, a partial-implicit solution method is improved using an assembled domain structure model with six-domain mesoscopic particles exhibiting pinning-type hysteresis. The quantitative analysis of non-oriented silicon steel succeeds in predicting the stress dependence of hysteresis loss with computation times greatly reduced by using the improved partial-implicit method. The effect of cell division along the thickness direction is also evaluated.

NR4A nuclear receptors are orphans but not lonesome.

Science.gov (United States)

Kurakula, Kondababu; Koenis, Duco S; van Tiel, Claudia M; de Vries, Carlie J M

2014-11-01

The NR4A subfamily of nuclear receptors consists of three mammalian members: Nur77, Nurr1, and NOR-1. The NR4A receptors are involved in essential physiological processes such as adaptive and innate immune cell differentiation, metabolism and brain function. They act as transcription factors that directly modulate gene expression, but can also form trans-repressive complexes with other transcription factors. In contrast to steroid hormone nuclear receptors such as the estrogen receptor or the glucocorticoid receptor, no ligands have been described for the NR4A receptors. This lack of known ligands might be explained by the structure of the ligand-binding domain of NR4A receptors, which shows an active conformation and a ligand-binding pocket that is filled with bulky amino acid side-chains. Other mechanisms, such as transcriptional control, post-translational modifications and protein-protein interactions therefore seem to be more important in regulating the activity of the NR4A receptors. For Nur77, over 80 interacting proteins (the interactome) have been identified so far, and roughly half of these interactions has been studied in more detail. Although the NR4As show some overlap in interacting proteins, less information is available on the interactome of Nurr1 and NOR-1. Therefore, the present review will describe the current knowledge on the interactomes of all three NR4A nuclear receptors with emphasis on Nur77. Copyright © 2014 Elsevier B.V. All rights reserved.

Interaction of the superconducting domains induced by external electric field with electromagnetic waves

International Nuclear Information System (INIS)

Shapiro, B.Y.

1992-01-01

The behavior of a superconductor in time-independent electric field perpendicular to the surface and in the external electromagnetic wave is theoretically investigated. A new type of the resonance interaction between superconducting domains localized along the magnetic field (if the superconducting phase transition takes place in the external magnetic field perpendicular to the surface) and electromagnetic waves is predicted. The surface impedance of the superconductor with domains is calculated. It is shown that the real part of the impedance has a saturation if the skin length equals the domain size. (orig.)

Data Prediction for Public Events in Professional Domains Based on Improved RNN- LSTM

Science.gov (United States)

Song, Bonan; Fan, Chunxiao; Wu, Yuexin; Sun, Juanjuan

2018-02-01

The traditional data services of prediction for emergency or non-periodic events usually cannot generate satisfying result or fulfill the correct prediction purpose. However, these events are influenced by external causes, which mean certain a priori information of these events generally can be collected through the Internet. This paper studied the above problems and proposed an improved model—LSTM (Long Short-term Memory) dynamic prediction and a priori information sequence generation model by combining RNN-LSTM and public events a priori information. In prediction tasks, the model is qualified for determining trends, and its accuracy also is validated. This model generates a better performance and prediction results than the previous one. Using a priori information can increase the accuracy of prediction; LSTM can better adapt to the changes of time sequence; LSTM can be widely applied to the same type of prediction tasks, and other prediction tasks related to time sequence.

Domain analysis

DEFF Research Database (Denmark)

Hjørland, Birger

2017-01-01

The domain-analytic approach to knowledge organization (KO) (and to the broader field of library and information science, LIS) is outlined. The article reviews the discussions and proposals on the definition of domains, and provides an example of a domain-analytic study in the field of art studies....... Varieties of domain analysis as well as criticism and controversies are presented and discussed....

Measurement of electron paramagnetic resonance using terahertz time-domain spectroscopy.

Science.gov (United States)

Kozuki, Kohei; Nagashima, Takeshi; Hangyo, Masanori

2011-12-05

We present a frequency-domain electron spin resonance (ESR) measurement system using terahertz time-domain spectroscopy. A crossed polarizer technique is utilized to increase the sensitivity in detecting weak ESR signals of paramagnets caused by magnetic dipole transitions between magnetic sublevels. We demonstrate the measurements of ESR signal of paramagnetic copper(II) sulfate pentahydrate with uniaxial anisotropy of the g-factor under magnetic fields up to 10 T. The lineshape of the obtained ESR signals agrees well with the theoretical predictions for a powder sample with the uniaxial anisotropy.

Estimation of the applicability domain of kernel-based machine learning models for virtual screening

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Fechner Nikolas

2010-03-01

Full Text Available Abstract Background The virtual screening of large compound databases is an important application of structural-activity relationship models. Due to the high structural diversity of these data sets, it is impossible for machine learning based QSAR models, which rely on a specific training set, to give reliable results for all compounds. Thus, it is important to consider the subset of the chemical space in which the model is applicable. The approaches to this problem that have been published so far mostly use vectorial descriptor representations to define this domain of applicability of the model. Unfortunately, these cannot be extended easily to structured kernel-based machine learning models. For this reason, we propose three approaches to estimate the domain of applicability of a kernel-based QSAR model. Results We evaluated three kernel-based applicability domain estimations using three different structured kernels on three virtual screening tasks. Each experiment consisted of the training of a kernel-based QSAR model using support vector regression and the ranking of a disjoint screening data set according to the predicted activity. For each prediction, the applicability of the model for the respective compound is quantitatively described using a score obtained by an applicability domain formulation. The suitability of the applicability domain estimation is evaluated by comparing the model performance on the subsets of the screening data sets obtained by different thresholds for the applicability scores. This comparison indicates that it is possible to separate the part of the chemspace, in which the model gives reliable predictions, from the part consisting of structures too dissimilar to the training set to apply the model successfully. A closer inspection reveals that the virtual screening performance of the model is considerably improved if half of the molecules, those with the lowest applicability scores, are omitted from the screening

Estimation of the applicability domain of kernel-based machine learning models for virtual screening.

Science.gov (United States)

Fechner, Nikolas; Jahn, Andreas; Hinselmann, Georg; Zell, Andreas

2010-03-11

The virtual screening of large compound databases is an important application of structural-activity relationship models. Due to the high structural diversity of these data sets, it is impossible for machine learning based QSAR models, which rely on a specific training set, to give reliable results for all compounds. Thus, it is important to consider the subset of the chemical space in which the model is applicable. The approaches to this problem that have been published so far mostly use vectorial descriptor representations to define this domain of applicability of the model. Unfortunately, these cannot be extended easily to structured kernel-based machine learning models. For this reason, we propose three approaches to estimate the domain of applicability of a kernel-based QSAR model. We evaluated three kernel-based applicability domain estimations using three different structured kernels on three virtual screening tasks. Each experiment consisted of the training of a kernel-based QSAR model using support vector regression and the ranking of a disjoint screening data set according to the predicted activity. For each prediction, the applicability of the model for the respective compound is quantitatively described using a score obtained by an applicability domain formulation. The suitability of the applicability domain estimation is evaluated by comparing the model performance on the subsets of the screening data sets obtained by different thresholds for the applicability scores. This comparison indicates that it is possible to separate the part of the chemspace, in which the model gives reliable predictions, from the part consisting of structures too dissimilar to the training set to apply the model successfully. A closer inspection reveals that the virtual screening performance of the model is considerably improved if half of the molecules, those with the lowest applicability scores, are omitted from the screening. The proposed applicability domain formulations

Human surfactant protein D: SP-D contains a C-type lectin carbohydrate recognition domain.

Science.gov (United States)

Rust, K; Grosso, L; Zhang, V; Chang, D; Persson, A; Longmore, W; Cai, G Z; Crouch, E

1991-10-01

Lung surfactant protein D (SP-D) shows calcium-dependent binding to specific saccharides, and is similar in domain structure to certain members of the calcium-dependent (C-type) lectin family. Using a degenerate oligomeric probe corresponding to a conserved peptide sequence derived from the amino-terminus of the putative carbohydrate binding domain of rat and bovine SP-D, we screened a human lung cDNA library and isolated a 1.4-kb cDNA for the human protein. The relationship of the cDNA to SP-D was established by several techniques including amino-terminal microsequencing of SP-D-derived peptides, and immunoprecipitation of translation products of transcribed mRNA with monospecific antibodies to SP-D. In addition, antibodies to a synthetic peptide derived from a predicted unique epitope within the carbohydrate recognition domain of SP-D specifically reacted with SP-D. DNA sequencing demonstrated a noncollagenous carboxy-terminal domain that is highly homologous with the carboxy-terminal globular domain of previously described C-type lectins. This domain contains all of the so-called "invariant residues," including four conserved cysteine residues, and shows high homology with the mannose-binding subfamily of C-type lectins. Sequencing also demonstrated an amino-terminal collagenous domain that contains an uninterrupted sequence of 59 Gly-X-Y triplets and that also contains the only identified consensus for asparagine-linked oligosaccharides. The studies demonstrate that SP-D is a member of the C-type lectin family, and confirm predicted structural similarities to conglutinin, SP-D, and the serum mannose binding proteins.

Hepatitis C virus NS4B carboxy terminal domain is a membrane binding domain

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Spaan Willy JM

2009-05-01

Full Text Available Abstract Background Hepatitis C virus (HCV induces membrane rearrangements during replication. All HCV proteins are associated to membranes, pointing out the importance of membranes for HCV. Non structural protein 4B (NS4B has been reported to induce cellular membrane alterations like the membranous web. Four transmembrane segments in the middle of the protein anchor NS4B to membranes. An amphipatic helix at the amino-terminus attaches to membranes as well. The carboxy-terminal domain (CTD of NS4B is highly conserved in Hepaciviruses, though its function remains unknown. Results A cytosolic localization is predicted for the NS4B-CTD. However, using membrane floatation assays and immunofluorescence, we now show targeting of the NS4B-CTD to membranes. Furthermore, a profile-profile search, with an HCV NS4B-CTD multiple sequence alignment, indicates sequence similarity to the membrane binding domain of prokaryotic D-lactate dehydrogenase (d-LDH. The crystal structure of E. coli d-LDH suggests that the region similar to NS4B-CTD is located in the membrane binding domain (MBD of d-LDH, implying analogy in membrane association. Targeting of d-LDH to membranes occurs via electrostatic interactions of positive residues on the outside of the protein with negative head groups of lipids. To verify that anchorage of d-LDH MBD and NS4B-CTD is analogous, NS4B-CTD mutants were designed to disrupt these electrostatic interactions. Membrane association was confirmed by swopping the membrane contacting helix of d-LDH with the corresponding domain of the 4B-CTD. Furthermore, the functionality of these residues was tested in the HCV replicon system. Conclusion Together these data show that NS4B-CTD is associated to membranes, similar to the prokaryotic d-LDH MBD, and is important for replication.

Matter-antimatter domains in the universe

International Nuclear Information System (INIS)

Dolgov, A.

2001-01-01

A possible existence of cosmologically large domains of antimatter or astronomical 'anti-objects' is discussed. A brief review of different scenarios of baryogenesis predicting a noticeable amount of antimatter is given. Though both theory and observations indicate that the universe is most possibly uniformly charge asymmetric without any noticeable amount of antimatter, several natural scenarios are possible that allow for cosmologically (astronomically) interesting objects in close vicinity to us. The latter may be discovered by observation of cosmic ray antinuclei

Transcript structure and domain display: a customizable transcript visualization tool.

Science.gov (United States)

Watanabe, Kenneth A; Ma, Kaiwang; Homayouni, Arielle; Rushton, Paul J; Shen, Qingxi J

2016-07-01

Transcript Structure and Domain Display (TSDD) is a publicly available, web-based program that provides publication quality images of transcript structures and domains. TSDD is capable of producing transcript structures from GFF/GFF3 and BED files. Alternatively, the GFF files of several model organisms have been pre-loaded so that users only needs to enter the locus IDs of the transcripts to be displayed. Visualization of transcripts provides many benefits to researchers, ranging from evolutionary analysis of DNA-binding domains to predictive function modeling. TSDD is freely available for non-commercial users at http://shenlab.sols.unlv.edu/shenlab/software/TSD/transcript_display.html : jeffery.shen@unlv.nevada.edu. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

The YARHG domain: an extracellular domain in search of a function.

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Penny Coggill

Full Text Available We have identified a new bacterial protein domain that we hypothesise binds to peptidoglycan. This domain is called the YARHG domain after the most highly conserved sequence-segment. The domain is found in the extracellular space and is likely to be composed of four alpha-helices. The domain is found associated with protein kinase domains, suggesting it is associated with signalling in some bacteria. The domain is also found associated with three different families of peptidases. The large number of different domains that are found associated with YARHG suggests that it is a useful functional module that nature has recombined multiple times.

A residue-specific shift in stability and amyloidogenicity of antibody variable domains.

Science.gov (United States)

Nokwe, Cardine N; Zacharias, Martin; Yagi, Hisashi; Hora, Manuel; Reif, Bernd; Goto, Yuji; Buchner, Johannes

2014-09-26

Variable (V) domains of antibodies are essential for antigen recognition by our adaptive immune system. However, some variants of the light chain V domains (VL) form pathogenic amyloid fibrils in patients. It is so far unclear which residues play a key role in governing these processes. Here, we show that the conserved residue 2 of VL domains is crucial for controlling its thermodynamic stability and fibril formation. Hydrophobic side chains at position 2 stabilize the domain, whereas charged residues destabilize and lead to amyloid fibril formation. NMR experiments identified several segments within the core of the VL domain to be affected by changes in residue 2. Furthermore, molecular dynamic simulations showed that hydrophobic side chains at position 2 remain buried in a hydrophobic pocket, and charged side chains show a high flexibility. This results in a predicted difference in the dissociation free energy of ∼10 kJ mol(-1), which is in excellent agreement with our experimental values. Interestingly, this switch point is found only in VL domains of the κ family and not in VLλ or in VH domains, despite a highly similar domain architecture. Our results reveal novel insight into the architecture of variable domains and the prerequisites for formation of amyloid fibrils. This might also contribute to the rational design of stable variable antibody domains. © 2014 by The American Society for Biochemistry and Molecular Biology, Inc.

Prediction and characterization of protein-protein interaction networks in swine

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Wang Fen

2012-01-01

Full Text Available Abstract Background Studying the large-scale protein-protein interaction (PPI network is important in understanding biological processes. The current research presents the first PPI map of swine, which aims to give new insights into understanding their biological processes. Results We used three methods, Interolog-based prediction of porcine PPI network, domain-motif interactions from structural topology-based prediction of porcine PPI network and motif-motif interactions from structural topology-based prediction of porcine PPI network, to predict porcine protein interactions among 25,767 porcine proteins. We predicted 20,213, 331,484, and 218,705 porcine PPIs respectively, merged the three results into 567,441 PPIs, constructed four PPI networks, and analyzed the topological properties of the porcine PPI networks. Our predictions were validated with Pfam domain annotations and GO annotations. Averages of 70, 10,495, and 863 interactions were related to the Pfam domain-interacting pairs in iPfam database. For comparison, randomized networks were generated, and averages of only 4.24, 66.79, and 44.26 interactions were associated with Pfam domain-interacting pairs in iPfam database. In GO annotations, we found 52.68%, 75.54%, 27.20% of the predicted PPIs sharing GO terms respectively. However, the number of PPI pairs sharing GO terms in the 10,000 randomized networks reached 52.68%, 75.54%, 27.20% is 0. Finally, we determined the accuracy and precision of the methods. The methods yielded accuracies of 0.92, 0.53, and 0.50 at precisions of about 0.93, 0.74, and 0.75, respectively. Conclusion The results reveal that the predicted PPI networks are considerably reliable. The present research is an important pioneering work on protein function research. The porcine PPI data set, the confidence score of each interaction and a list of related data are available at (http://pppid.biositemap.com/.

Domain configuration and magnetization switching in arrays of permalloy nanostripes

International Nuclear Information System (INIS)

Iglesias-Freire, Ó.; Jaafar, M.; Pérez, L.; Abril, O. de; Vázquez, M.; Asenjo, A.

2014-01-01

The proximity effect in the collective behavior of arrays of magnetic nanostripes is currently a subject of intensive research. The imperative of reducing the size and distances between elements in order to achieve higher storage capacity, faster access to the information as well as low energy consumption, brings consequences about the isolated behavior of the elements and devices. Parallel to each other permalloy nanostripes with high aspect ratio have been prepared by the nanolithography technique. The evolution of the closure domains and the magnetization direction in individual nanostructures has been imaged under applied magnetic fields using Variable Field Magnetic Force Microscopy. Moreover, the magnetostatic interactions between neighboring elements and the proximity effects in arrays of such nanostructures have been quantitatively analyzed by Magnetic Force Microscopy and micromagnetic simulations. The agreement between simulations and the experimental results allows us to conclude the relevance of those interactions depending on the geometry characteristics. In particular, results suggest that the magnetostatic coupling between adjacent nanostripes vanishes for separation distances higher than 500 nm. - Highlights: • A shape anisotropy-induced single domain remanent state is present in the stripes. Closure domains are formed under external fields. • Separation distances between neighboring stripes (500 nm) are enough to overcome the magnetostatic coupling and avoid a multi-stripe character. • Micromagnetic simulations predict critical distances of around 500 nm for the onset of magnetostatic coupling between neighboring elements. • Simulations predict stripes with a small longitudinal separation to behave as single elements, with domain walls “jumping” between them

Domain configuration and magnetization switching in arrays of permalloy nanostripes

Energy Technology Data Exchange (ETDEWEB)

Iglesias-Freire, Ó., E-mail: aasenjo@icmm.csic.es [Instituto de Ciencia de Materiales de Madrid, CSIC, Sor Juana Inés de la Cruz 3, Madrid 28049 (Spain); Jaafar, M. [Instituto de Ciencia de Materiales de Madrid, CSIC, Sor Juana Inés de la Cruz 3, Madrid 28049 (Spain); Dpto. Física de la Materia Condensada, Universidad Autónoma de Madrid, Cantoblanco 28049 (Spain); Pérez, L. [Dpto. Física de Materiales, Universidad Complutense de Madrid, Madrid 28040 (Spain); Abril, O. de [Dpto. Física e Instalaciones Aplicadas a la Edificación, al Medio Ambiente y al Urbanismo, Universidad Politécnica de Madrid, Madrid 28040 (Spain); Vázquez, M.; Asenjo, A. [Instituto de Ciencia de Materiales de Madrid, CSIC, Sor Juana Inés de la Cruz 3, Madrid 28049 (Spain)

2014-04-15

The proximity effect in the collective behavior of arrays of magnetic nanostripes is currently a subject of intensive research. The imperative of reducing the size and distances between elements in order to achieve higher storage capacity, faster access to the information as well as low energy consumption, brings consequences about the isolated behavior of the elements and devices. Parallel to each other permalloy nanostripes with high aspect ratio have been prepared by the nanolithography technique. The evolution of the closure domains and the magnetization direction in individual nanostructures has been imaged under applied magnetic fields using Variable Field Magnetic Force Microscopy. Moreover, the magnetostatic interactions between neighboring elements and the proximity effects in arrays of such nanostructures have been quantitatively analyzed by Magnetic Force Microscopy and micromagnetic simulations. The agreement between simulations and the experimental results allows us to conclude the relevance of those interactions depending on the geometry characteristics. In particular, results suggest that the magnetostatic coupling between adjacent nanostripes vanishes for separation distances higher than 500 nm. - Highlights: • A shape anisotropy-induced single domain remanent state is present in the stripes. Closure domains are formed under external fields. • Separation distances between neighboring stripes (500 nm) are enough to overcome the magnetostatic coupling and avoid a multi-stripe character. • Micromagnetic simulations predict critical distances of around 500 nm for the onset of magnetostatic coupling between neighboring elements. • Simulations predict stripes with a small longitudinal separation to behave as single elements, with domain walls “jumping” between them.

.Gov Domains API

Data.gov (United States)

General Services Administration — This dataset offers the list of all .gov domains, including state, local, and tribal .gov domains. It does not include .mil domains, or other federal domains outside...

SH2 Ligand Prediction-Guidance for In-Silico Screening.

Science.gov (United States)

Li, Shawn S C; Li, Lei

2017-01-01

Systematic identification of binding partners for SH2 domains is important for understanding the biological function of the corresponding SH2 domain-containing proteins. Here, we describe two different web-accessible computer programs, SMALI and DomPep, for predicting binding ligands for SH2 domains. The former was developed using a Scoring Matrix method and the latter based on the Support Vector Machine model.

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

Science.gov (United States)

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

2018-02-01

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

Regulation of the Hsp104 middle domain activity is critical for yeast prion propagation.

Directory of Open Access Journals (Sweden)

Jennifer E Dulle

Full Text Available Molecular chaperones play a significant role in preventing protein misfolding and aggregation. Indeed, some protein conformational disorders have been linked to changes in the chaperone network. Curiously, in yeast, chaperones also play a role in promoting prion maintenance and propagation. While many amyloidogenic proteins are associated with disease in mammals, yeast prion proteins, and their ability to undergo conformational conversion into a prion state, are proposed to play a functional role in yeast biology. The chaperone Hsp104, a AAA+ ATPase, is essential for yeast prion propagation. Hsp104 fragments large prion aggregates to generate a population of smaller oligomers that can more readily convert soluble monomer and be transmitted to daughter cells. Here, we show that the middle (M domain of Hsp104, and its mobility, plays an integral part in prion propagation. We generated and characterized mutations in the M-domain of Hsp104 that are predicted to stabilize either a repressed or de-repressed conformation of the M-domain (by analogy to ClpB in bacteria. We show that the predicted stabilization of the repressed conformation inhibits general chaperone activity. Mutation to the de-repressed conformation, however, has differential effects on ATP hydrolysis and disaggregation, suggesting that the M-domain is involved in coupling these two activities. Interestingly, we show that changes in the M-domain differentially affect the propagation of different variants of the [PSI+] and [RNQ+] prions, which indicates that some prion variants are more sensitive to changes in the M-domain mobility than others. Thus, we provide evidence that regulation of the M-domain of Hsp104 is critical for efficient prion propagation. This shows the importance of elucidating the function of the M-domain in order to understand the role of Hsp104 in the propagation of different prions and prion variants.

Exploring off-targets and off-systems for adverse drug reactions via chemical-protein interactome--clozapine-induced agranulocytosis as a case study.

Directory of Open Access Journals (Sweden)

Lun Yang

2011-03-01

Full Text Available In the era of personalized medical practice, understanding the genetic basis of patient-specific adverse drug reaction (ADR is a major challenge. Clozapine provides effective treatments for schizophrenia but its usage is limited because of life-threatening agranulocytosis. A recent high impact study showed the necessity of moving clozapine to a first line drug, thus identifying the biomarkers for drug-induced agranulocytosis has become important. Here we report a methodology termed as antithesis chemical-protein interactome (CPI, which utilizes the docking method to mimic the differences in the drug-protein interactions across a panel of human proteins. Using this method, we identified HSPA1A, a known susceptibility gene for CIA, to be the off-target of clozapine. Furthermore, the mRNA expression of HSPA1A-related genes (off-target associated systems was also found to be differentially expressed in clozapine treated leukemia cell line. Apart from identifying the CIA causal genes we identified several novel candidate genes which could be responsible for agranulocytosis. Proteins related to reactive oxygen clearance system, such as oxidoreductases and glutathione metabolite enzymes, were significantly enriched in the antithesis CPI. This methodology conducted a multi-dimensional analysis of drugs' perturbation to the biological system, investigating both the off-targets and the associated off-systems to explore the molecular basis of an adverse event or the new uses for old drugs.

Using freelisting to identify, assess, and characterize age differences in shared cultural domains.

Science.gov (United States)

Schrauf, Robert W; Sanchez, Julia

2008-11-01

Freelisting is a brief, paper-and-pencil technique in which participants make lists of items that they believe belong in a particular domain. Where cultural domains are shared, as for young and old in the same society, subtle intracultural differences may be difficult to detect. This article presents a series of techniques for revealing and describing this intracultural variation in freelisted data among young versus old age groups. Older (N = 30) and younger (N = 31) Mexicans in Mexico City made freelists in four quotidian domains: animals, emotions, illnesses, and gendered occupations. We used minimum residual factor analysis (consensus analysis) to establish domain coherence and assess overall consensus concerning contents of the domains. We established subvariation within the overall consensus by comparing levels of observed versus predicted inter-informant agreement. Results showed divergent patterns of inter-informant agreement between young and old participants across domains. Qualitative examination of items with higher salience for young versus old revealed age differences consistent with prior findings in each domain. The concatenation of these techniques renders freelisting an accessible, easily administered tool for probing age and group differences in cultural domains.

Comprehensive Protein Interactome Analysis of a Key RNA Helicase: Detection of Novel Stress Granule Proteins

Directory of Open Access Journals (Sweden)

Rebecca Bish

2015-07-01

Full Text Available DDX6 (p54/RCK is a human RNA helicase with central roles in mRNA decay and translation repression. To help our understanding of how DDX6 performs these multiple functions, we conducted the first unbiased, large-scale study to map the DDX6-centric protein-protein interactome using immunoprecipitation and mass spectrometry. Using DDX6 as bait, we identify a high-confidence and high-quality set of protein interaction partners which are enriched for functions in RNA metabolism and ribosomal proteins. The screen is highly specific, maximizing the number of true positives, as demonstrated by the validation of 81% (47/58 of the RNA-independent interactors through known functions and interactions. Importantly, we minimize the number of indirect interaction partners through use of a nuclease-based digestion to eliminate RNA. We describe eleven new interactors, including proteins involved in splicing which is an as-yet unknown role for DDX6. We validated and characterized in more detail the interaction of DDX6 with Nuclear fragile X mental retardation-interacting protein 2 (NUFIP2 and with two previously uncharacterized proteins, FAM195A and FAM195B (here referred to as granulin-1 and granulin-2, or GRAN1 and GRAN2. We show that NUFIP2, GRAN1, and GRAN2 are not P-body components, but re-localize to stress granules upon exposure to stress, suggesting a function in translation repression in the cellular stress response. Using a complementary analysis that resolved DDX6’s multiple complex memberships, we further validated these interaction partners and the presence of splicing factors. As DDX6 also interacts with the E3 SUMO ligase TIF1β, we tested for and observed a significant enrichment of sumoylation amongst DDX6’s interaction partners. Our results represent the most comprehensive screen for direct interaction partners of a key regulator of RNA life cycle and localization, highlighting new stress granule components and possible DDX6 functions�

Exploring Cognitive Relations between Prediction in Language and Music

Science.gov (United States)

Patel, Aniruddh D.; Morgan, Emily

2017-01-01

The online processing of both music and language involves making predictions about upcoming material, but the relationship between prediction in these two domains is not well understood. Electrophysiological methods for studying individual differences in prediction in language processing have opened the door to new questions. Specifically, we ask…

Charged domain-wall dynamics in doped antiferromagnets and spin fluctuations in cuprate superconductors

International Nuclear Information System (INIS)

Zaanen, J.; Horbach, M.L.; van Saarloos, W.

1996-01-01

Evidence is accumulating that the electron liquid in the cuprate superconductors is characterized by many-hole correlations of the charged magnetic domain-wall type. Here we focus on the strong-coupling limit where all holes are bound to domain walls. We assert that at high temperatures a classical domain-wall fluid is realized and show that the dynamics of such a fluid is characterized by spatial and temporal crossover scales set by temperature itself. The fundamental parameters of this fluid are such that the domain-wall motions dominate the low-frequency spin fluctuations and we derive predictions for the behavior of the dynamical magnetic susceptibility. We argue that a crossover occurs from a high-temperature classical to a low-temperature quantum regime, in direct analogy with helium. We discuss some general characteristics of the domain-wall quantum liquid, realized at low temperatures. copyright 1996 The American Physical Society

Untangling spider silk evolution with spidroin terminal domains

Directory of Open Access Journals (Sweden)

Garb Jessica E

2010-08-01

Full Text Available Abstract Background Spidroins are a unique family of large, structural proteins that make up the bulk of spider silk fibers. Due to the highly variable nature of their repetitive sequences, spidroin evolutionary relationships have principally been determined from their non-repetitive carboxy (C-terminal domains, though they offer limited character data. The few known spidroin amino (N-terminal domains have been difficult to obtain, but potentially contain critical phylogenetic information for reconstructing the diversification of spider silks. Here we used silk gland expression data (ESTs from highly divergent species to evaluate the functional significance and phylogenetic utility of spidroin N-terminal domains. Results We report 11 additional spidroin N-termini found by sequencing ~1,900 silk gland cDNAs from nine spider species that shared a common ancestor > 240 million years ago. In contrast to their hyper-variable repetitive regions, spidroin N-terminal domains have retained striking similarities in sequence identity, predicted secondary structure, and hydrophobicity. Through separate and combined phylogenetic analyses of N-terminal domains and their corresponding C-termini, we find that combined analysis produces the most resolved trees and that N-termini contribute more support and less conflict than the C-termini. These analyses show that paralogs largely group by silk gland type, except for the major ampullate spidroins. Moreover, spidroin structural motifs associated with superior tensile strength arose early in the history of this gene family, whereas a motif conferring greater extensibility convergently evolved in two distantly related paralogs. Conclusions A non-repetitive N-terminal domain appears to be a universal attribute of spidroin proteins, likely retained from the origin of spider silk production. Since this time, spidroin N-termini have maintained several features, consistent with this domain playing a key role in silk

Protein interaction networks by proteome peptide scanning.

Directory of Open Access Journals (Sweden)

Christiane Landgraf

2004-01-01

Full Text Available A substantial proportion of protein interactions relies on small domains binding to short peptides in the partner proteins. Many of these interactions are relatively low affinity and transient, and they impact on signal transduction. However, neither the number of potential interactions mediated by each domain nor the degree of promiscuity at a whole proteome level has been investigated. We have used a combination of phage display and SPOT synthesis to discover all the peptides in the yeast proteome that have the potential to bind to eight SH3 domains. We first identified the peptides that match a relaxed consensus, as deduced from peptides selected by phage display experiments. Next, we synthesized all the matching peptides at high density on a cellulose membrane, and we probed them directly with the SH3 domains. The domains that we have studied were grouped by this approach into five classes with partially overlapping specificity. Within the classes, however, the domains display a high promiscuity and bind to a large number of common targets with comparable affinity. We estimate that the yeast proteome contains as few as six peptides that bind to the Abp1 SH3 domain with a dissociation constant lower than 100 microM, while it contains as many as 50-80 peptides with corresponding affinity for the SH3 domain of Yfr024c. All the targets of the Abp1 SH3 domain, identified by this approach, bind to the native protein in vivo, as shown by coimmunoprecipitation experiments. Finally, we demonstrate that this strategy can be extended to the analysis of the entire human proteome. We have developed an approach, named WISE (whole interactome scanning experiment, that permits rapid and reliable identification of the partners of any peptide recognition module by peptide scanning of a proteome. Since the SPOT synthesis approach is semiquantitative and provides an approximation of the dissociation constants of the several thousands of interactions that are

Parsimony in personality: predicting sexual prejudice.

Science.gov (United States)

Miller, Audrey K; Wagner, Maverick M; Hunt, Amy N

2012-01-01

Extant research has established numerous demographic, personal-history, attitudinal, and ideological correlates of sexual prejudice, also known as homophobia. The present study investigated whether Five-Factor Model (FFM) personality domains, particularly Openness, and FFM facets, particularly Openness to Values, contribute independent and incremental variance to the prediction of sexual prejudice beyond these established correlates. Participants were 117 college students who completed a comprehensive FFM measure, measures of sexual prejudice, and a demographics, personal-history, and attitudes-and-ideologies questionnaire. Results of stepwise multiple regression analyses demonstrated that, whereas Openness domain score predicted only marginal incremental variance in sexual prejudice, Openness facet scores (particularly Openness to Values) predicted independent and substantial incremental variance beyond numerous other zero-order correlates of sexual prejudice. The importance of integrating FFM personality variables, especially facet-level variables, into conceptualizations of sexual prejudice is highlighted. Study strengths and weaknesses are discussed as are potential implications for prejudice-reduction interventions.

Investigation into the efficacy of generating synthetic pathological oscillations for domain adaptation

Science.gov (United States)

Lewis, Rory; Ellenberger, James; Williams, Colton; White, Andrew M.

2013-11-01

In the ongoing investigation of integrating Knowledge Discovery in Databases (KDD) into neuroscience, we present a paper that facilitates overcoming the two challenges preventing this integration. Pathological oscillations found in the human brain are difficult to evaluate because 1) there is often no time to learn and train off of the same distribution in the fatally sick, and 2) sinusoidal signals found in the human brain are complex and transient in nature requiring large data sets to work with which are costly and often very expensive or impossible to acquire. Overcoming these challenges in today's neuro-intensive-care unit (ICU) requires insurmountable resources. For these reasons, optimizing KDD for pathological oscillations so machine learning systems can predict neuropathological states would be of immense value. Domain adaptation, which allows a way of predicting on a separate set of data than the training data, can theoretically overcome the first challenge. However, the challenge of acquiring large data sets that show whether domain adaptation is a good candidate to test in a live neuro ICU remains a challenge. To solve this conundrum, we present a methodology for generating synthesized neuropathological oscillations for domain adaptation.

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

Domain Engineering

Science.gov (United States)

Bjørner, Dines

Before software can be designed we must know its requirements. Before requirements can be expressed we must understand the domain. So it follows, from our dogma, that we must first establish precise descriptions of domains; then, from such descriptions, “derive” at least domain and interface requirements; and from those and machine requirements design the software, or, more generally, the computing systems.

Multimodal manifold-regularized transfer learning for MCI conversion prediction.

Science.gov (United States)

Cheng, Bo; Liu, Mingxia; Suk, Heung-Il; Shen, Dinggang; Zhang, Daoqiang

2015-12-01

As the early stage of Alzheimer's disease (AD), mild cognitive impairment (MCI) has high chance to convert to AD. Effective prediction of such conversion from MCI to AD is of great importance for early diagnosis of AD and also for evaluating AD risk pre-symptomatically. Unlike most previous methods that used only the samples from a target domain to train a classifier, in this paper, we propose a novel multimodal manifold-regularized transfer learning (M2TL) method that jointly utilizes samples from another domain (e.g., AD vs. normal controls (NC)) as well as unlabeled samples to boost the performance of the MCI conversion prediction. Specifically, the proposed M2TL method includes two key components. The first one is a kernel-based maximum mean discrepancy criterion, which helps eliminate the potential negative effect induced by the distributional difference between the auxiliary domain (i.e., AD and NC) and the target domain (i.e., MCI converters (MCI-C) and MCI non-converters (MCI-NC)). The second one is a semi-supervised multimodal manifold-regularized least squares classification method, where the target-domain samples, the auxiliary-domain samples, and the unlabeled samples can be jointly used for training our classifier. Furthermore, with the integration of a group sparsity constraint into our objective function, the proposed M2TL has a capability of selecting the informative samples to build a robust classifier. Experimental results on the Alzheimer's Disease Neuroimaging Initiative (ADNI) database validate the effectiveness of the proposed method by significantly improving the classification accuracy of 80.1 % for MCI conversion prediction, and also outperforming the state-of-the-art methods.

Structure of the first PDZ domain of human PSD-93

DEFF Research Database (Denmark)

Fiorentini, Monica; Nielsen, Ann Kallehauge; Kristensen, Ole

2009-01-01

The crystal structure of the PDZ1 domain of human PSD-93 has been determined to 2.0 A resolution. The PDZ1 domain forms a crystallographic trimer that is also predicted to be stable in solution. The main contributions to the stabilization of the trimer seem to arise from interactions involving...... the PDZ1-PDZ2 linker region at the extreme C-terminus of PDZ1, implying that the oligomerization that is observed is not of biological significance in full-length PSD-93. Comparison of the structures of the binding cleft of PSD-93 PDZ1 with the previously reported structures of PSD-93 PDZ2 and PDZ3...

Baryogenesis model predicting antimatter in the Universe

International Nuclear Information System (INIS)

Kirilova, D.

2003-01-01

Cosmic ray and gamma-ray data do not rule out antimatter domains in the Universe, separated at distances bigger than 10 Mpc from us. Hence, it is interesting to analyze the possible generation of vast antimatter structures during the early Universe evolution. We discuss a SUSY-condensate baryogenesis model, predicting large separated regions of matter and antimatter. The model provides generation of the small locally observed baryon asymmetry for a natural initial conditions, it predicts vast antimatter domains, separated from the matter ones by baryonically empty voids. The characteristic scale of antimatter regions and their distance from the matter ones is in accordance with observational constraints from cosmic ray, gamma-ray and cosmic microwave background anisotropy data

Characterizing SH2 Domain Specificity and Network Interactions Using SPOT Peptide Arrays.

Science.gov (United States)

Liu, Bernard A

2017-01-01

Src Homology 2 (SH2) domains are protein interaction modules that recognize and bind tyrosine phosphorylated ligands. Their ability to distinguish binding to over thousands of potential phosphotyrosine (pTyr) ligands within the cell is critical for the fidelity of receptor tyrosine kinase (RTK) signaling. Within humans there are over a hundred SH2 domains with more than several thousand potential ligands across many cell types and cell states. Therefore, defining the specificity of individual SH2 domains is critical for predicting and identifying their physiological ligands. Here, in this chapter, I describe the broad use of SPOT peptide arrays for examining SH2 domain specificity. An orientated peptide array library (OPAL) approach can uncover both favorable and non-favorable residues, thus providing an in-depth analysis to SH2 specificity. Moreover, I discuss the application of SPOT arrays for paneling SH2 ligand binding with physiological peptides.

Molecular Mechanics of the α-Actinin Rod Domain: Bending, Torsional, and Extensional Behavior

Science.gov (United States)

Golji, Javad; Collins, Robert; Mofrad, Mohammad R. K.

2009-01-01

α-Actinin is an actin crosslinking molecule that can serve as a scaffold and maintain dynamic actin filament networks. As a crosslinker in the stressed cytoskeleton, α-actinin can retain conformation, function, and strength. α-Actinin has an actin binding domain and a calmodulin homology domain separated by a long rod domain. Using molecular dynamics and normal mode analysis, we suggest that the α-actinin rod domain has flexible terminal regions which can twist and extend under mechanical stress, yet has a highly rigid interior region stabilized by aromatic packing within each spectrin repeat, by electrostatic interactions between the spectrin repeats, and by strong salt bridges between its two anti-parallel monomers. By exploring the natural vibrations of the α-actinin rod domain and by conducting bending molecular dynamics simulations we also predict that bending of the rod domain is possible with minimal force. We introduce computational methods for analyzing the torsional strain of molecules using rotating constraints. Molecular dynamics extension of the α-actinin rod is also performed, demonstrating transduction of the unfolding forces across salt bridges to the associated monomer of the α-actinin rod domain. PMID:19436721

Modulated Magnetic Nanowires for Controlling Domain Wall Motion: Toward 3D Magnetic Memories

KAUST Repository

Ivanov, Yurii P.; Chuvilin, Andrey; Lopatin, Sergei; Kosel, Jü rgen

2016-01-01

Cylindrical magnetic nanowires are attractive materials for next generation data storage devices owing to the theoretically achievable high domain wall velocity and their efficient fabrication in highly dense arrays. In order to obtain control over domain wall motion, reliable and well-defined pinning sites are required. Here, we show that modulated nanowires consisting of alternating nickel and cobalt sections facilitate efficient domain wall pinning at the interfaces of those sections. By combining electron holography with micromagnetic simulations, the pinning effect can be explained by the interaction of the stray fields generated at the interface and the domain wall. Utilizing a modified differential phase contrast imaging, we visualized the pinned domain wall with a high resolution, revealing its three-dimensional vortex structure with the previously predicted Bloch point at its center. These findings suggest the potential of modulated nanowires for the development of high-density, three-dimensional data storage devices. © 2016 American Chemical Society.

Modulated Magnetic Nanowires for Controlling Domain Wall Motion: Toward 3D Magnetic Memories

KAUST Repository

Ivanov, Yurii P.

2016-05-03

Cylindrical magnetic nanowires are attractive materials for next generation data storage devices owing to the theoretically achievable high domain wall velocity and their efficient fabrication in highly dense arrays. In order to obtain control over domain wall motion, reliable and well-defined pinning sites are required. Here, we show that modulated nanowires consisting of alternating nickel and cobalt sections facilitate efficient domain wall pinning at the interfaces of those sections. By combining electron holography with micromagnetic simulations, the pinning effect can be explained by the interaction of the stray fields generated at the interface and the domain wall. Utilizing a modified differential phase contrast imaging, we visualized the pinned domain wall with a high resolution, revealing its three-dimensional vortex structure with the previously predicted Bloch point at its center. These findings suggest the potential of modulated nanowires for the development of high-density, three-dimensional data storage devices. © 2016 American Chemical Society.

The Role of Domain Knowledge in Cognitive Modeling of Information Search

NARCIS (Netherlands)

Karanam, S.; Jorge-Botana, Guillermo; Olmos, Ricardo; van Oostendorp, H.

2017-01-01

Computational cognitive models developed so far do not incorporate individual differences in domain knowledge in predicting user clicks on search result pages. We address this problem using a cognitive model of information search which enables us to use two semantic spaces having a low (non-expert

Modeling Chronic Toxicity: A Comparison of Experimental Variability With (QSAR/Read-Across Predictions

Directory of Open Access Journals (Sweden)

Christoph Helma

2018-04-01

Full Text Available This study compares the accuracy of (QSAR/read-across predictions with the experimental variability of chronic lowest-observed-adverse-effect levels (LOAELs from in vivo experiments. We could demonstrate that predictions of the lazy structure-activity relationships (lazar algorithm within the applicability domain of the training data have the same variability as the experimental training data. Predictions with a lower similarity threshold (i.e., a larger distance from the applicability domain are also significantly better than random guessing, but the errors to be expected are higher and a manual inspection of prediction results is highly recommended.

Domain decomposition method for solving elliptic problems in unbounded domains

International Nuclear Information System (INIS)

Khoromskij, B.N.; Mazurkevich, G.E.; Zhidkov, E.P.

1991-01-01

Computational aspects of the box domain decomposition (DD) method for solving boundary value problems in an unbounded domain are discussed. A new variant of the DD-method for elliptic problems in unbounded domains is suggested. It is based on the partitioning of an unbounded domain adapted to the given asymptotic decay of an unknown function at infinity. The comparison of computational expenditures is given for boundary integral method and the suggested DD-algorithm. 29 refs.; 2 figs.; 2 tabs

Efficient learning mechanisms hold in the social domain and are implemented in the medial prefrontal cortex.

Science.gov (United States)

Seid-Fatemi, Azade; Tobler, Philippe N

2015-05-01

When we are learning to associate novel cues with outcomes, learning is more efficient if we take advantage of previously learned associations and thereby avoid redundant learning. The blocking effect represents this sort of efficiency mechanism and refers to the phenomenon in which a novel stimulus is blocked from learning when it is associated with a fully predicted outcome. Although there is sufficient evidence that this effect manifests itself when individuals learn about their own rewards, it remains unclear whether it also does when they learn about others' rewards. We employed behavioral and neuroimaging methods to address this question. We demonstrate that blocking does indeed occur in the social domain and it does so to a similar degree as observed in the individual domain. On the neural level, activations in the medial prefrontal cortex (mPFC) show a specific contribution to blocking and learning-related prediction errors in the social domain. These findings suggest that the efficiency principle that applies to reward learning in the individual domain also applies to that in the social domain, with the mPFC playing a central role in implementing it. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Structure of the C-terminal domain of nsp4 from feline coronavirus

International Nuclear Information System (INIS)

Manolaridis, Ioannis; Wojdyla, Justyna A.; Panjikar, Santosh; Snijder, Eric J.; Gorbalenya, Alexander E.; Berglind, Hanna; Nordlund, Pär; Coutard, Bruno; Tucker, Paul A.

2009-01-01

The structure of the cytosolic C-terminal domain of nonstructural protein 4 from feline coronavirus has been determined and analyzed. Coronaviruses are a family of positive-stranded RNA viruses that includes important pathogens of humans and other animals. The large coronavirus genome (26–31 kb) encodes 15–16 nonstructural proteins (nsps) that are derived from two replicase polyproteins by autoproteolytic processing. The nsps assemble into the viral replication–transcription complex and nsp3, nsp4 and nsp6 are believed to anchor this enzyme complex to modified intracellular membranes. The largest part of the coronavirus nsp4 subunit is hydrophobic and is predicted to be embedded in the membranes. In this report, a conserved C-terminal domain (∼100 amino-acid residues) has been delineated that is predicted to face the cytoplasm and has been isolated as a soluble domain using library-based construct screening. A prototypical crystal structure at 2.8 Å resolution was obtained using nsp4 from feline coronavirus. Unmodified and SeMet-substituted proteins were crystallized under similar conditions, resulting in tetragonal crystals that belonged to space group P4 3 . The phase problem was initially solved by single isomorphous replacement with anomalous scattering (SIRAS), followed by molecular replacement using a SIRAS-derived composite model. The structure consists of a single domain with a predominantly α-helical content displaying a unique fold that could be engaged in protein–protein interactions

Structure of the C-terminal domain of nsp4 from feline coronavirus

Energy Technology Data Exchange (ETDEWEB)

Manolaridis, Ioannis; Wojdyla, Justyna A.; Panjikar, Santosh [EMBL Hamburg Outstation, c/o DESY, Notkestrasse 85, D-22603 Hamburg (Germany); Snijder, Eric J.; Gorbalenya, Alexander E. [Molecular Virology Laboratory, Department of Medical Microbiology, Center of Infectious Diseases, Leiden University Medical Center, PO Box 9600, 2300 RC Leiden (Netherlands); Berglind, Hanna; Nordlund, Pär [Division of Biophysics, Department of Medical Biochemistry and Biophysics, Scheeles väg 2, Karolinska Institute, SE-171 77 Stockholm (Sweden); Coutard, Bruno [Laboratoire Architecture et Fonction des Macromolécules Biologiques, UMR 6098, AFMB-CNRS-ESIL, Case 925, 163 Avenue de Luminy, 13288 Marseille (France); Tucker, Paul A., E-mail: tucker@embl-hamburg.de [EMBL Hamburg Outstation, c/o DESY, Notkestrasse 85, D-22603 Hamburg (Germany)

2009-08-01

The structure of the cytosolic C-terminal domain of nonstructural protein 4 from feline coronavirus has been determined and analyzed. Coronaviruses are a family of positive-stranded RNA viruses that includes important pathogens of humans and other animals. The large coronavirus genome (26–31 kb) encodes 15–16 nonstructural proteins (nsps) that are derived from two replicase polyproteins by autoproteolytic processing. The nsps assemble into the viral replication–transcription complex and nsp3, nsp4 and nsp6 are believed to anchor this enzyme complex to modified intracellular membranes. The largest part of the coronavirus nsp4 subunit is hydrophobic and is predicted to be embedded in the membranes. In this report, a conserved C-terminal domain (∼100 amino-acid residues) has been delineated that is predicted to face the cytoplasm and has been isolated as a soluble domain using library-based construct screening. A prototypical crystal structure at 2.8 Å resolution was obtained using nsp4 from feline coronavirus. Unmodified and SeMet-substituted proteins were crystallized under similar conditions, resulting in tetragonal crystals that belonged to space group P4{sub 3}. The phase problem was initially solved by single isomorphous replacement with anomalous scattering (SIRAS), followed by molecular replacement using a SIRAS-derived composite model. The structure consists of a single domain with a predominantly α-helical content displaying a unique fold that could be engaged in protein–protein interactions.

Magnetic domain-wall tilting due to domain-wall speed asymmetry

Science.gov (United States)

Kim, Dae-Yun; Park, Min-Ho; Park, Yong-Keun; Kim, Joo-Sung; Nam, Yoon-Seok; Hwang, Hyun-Seok; Kim, Duck-Ho; Je, Soong-Geun; Min, Byoung-Chul; Choe, Sug-Bong

2018-04-01

Broken symmetries in diverse systems generate a number of intriguing phenomena and the analysis on such broken symmetries often provides decisive clues for exploring underlying physics in the systems. Recently, in magnetic thin-film systems, the Dzyaloshinskii-Moriya interaction (DMI)—induced by the broken symmetry of structural inversion—accounts for various chiral phenomena, which are of timely issues in spintronics. Here, we report an experimental observation on unexpected tilting of magnetic domain walls (DWs) due to the broken symmetry under the application of the magnetic field transverse to the magnetic wire systems. It has been predicted that the DMI possibly causes such DW tilting in the direction of the energy minimization. However, very interestingly, experimental observation reveals that the DW tilting does not follow the prediction based on the energy minimization, even for the tilting direction. Instead, the DW tilting is governed by the DW speed asymmetry that is initiated by the DW pinning at wire edges. A simple analytic model is proposed in consideration of the DW speed asymmetry at wire edges, which successfully explains the experimental observation of the DW tilting directions and angles, as confirmed by numerical simulation. The present study manifests the decisive role of the DW pinning with the DW speed asymmetry, which determines the DW configuration and consequently, the dynamics.

Comparison of S. cerevisiae F-BAR domain structures reveals a conserved inositol phosphate binding site

Science.gov (United States)

Moravcevic, Katarina; Alvarado, Diego; Schmitz, Karl R.; Kenniston, Jon A.; Mendrola, Jeannine M.; Ferguson, Kathryn M.; Lemmon, Mark A.

2015-01-01

SUMMARY F-BAR domains control membrane interactions in endocytosis, cytokinesis, and cell signaling. Although generally thought to bind curved membranes containing negatively charged phospholipids, numerous functional studies argue that differences in lipid-binding selectivities of F-BAR domains are functionally important. Here, we compare membrane-binding properties of the S. cerevisiae F-BAR domains in vitro and in vivo. Whereas some F-BAR domains (such as Bzz1p and Hof1p F-BARs) bind equally well to all phospholipids, the F-BAR domain from the RhoGAP Rgd1p preferentially binds phosphoinositides. We determined X-ray crystal structures of F-BAR domains from Hof1p and Rgd1p, the latter bound to an inositol phosphate. The structures explain phospholipid-binding selectivity differences, and reveal an F-BAR phosphoinositide binding site that is fully conserved in a mammalian RhoGAP called Gmip, and is partly retained in certain other F-BAR domains. Our findings reveal previously unappreciated determinants of F-BAR domain lipid-binding specificity, and provide a basis for its prediction from sequence. PMID:25620000

The SHOCT domain: a widespread domain under-represented in model organisms.

Directory of Open Access Journals (Sweden)

Ruth Y Eberhardt

Full Text Available We have identified a new protein domain, which we have named the SHOCT domain (Short C-terminal domain. This domain is widespread in bacteria with over a thousand examples. But we found it is missing from the most commonly studied model organisms, despite being present in closely related species. It's predominantly C-terminal location, co-occurrence with numerous other domains and short size is reminiscent of the Gram-positive anchor motif, however it is present in a much wider range of species. We suggest several hypotheses about the function of SHOCT, including oligomerisation and nucleic acid binding. Our initial experiments do not support its role as an oligomerisation domain.

Domain-to-domain coupling in voltage-sensing phosphatase.

Science.gov (United States)

Sakata, Souhei; Matsuda, Makoto; Kawanabe, Akira; Okamura, Yasushi

2017-01-01

Voltage-sensing phosphatase (VSP) consists of a transmembrane voltage sensor and a cytoplasmic enzyme region. The enzyme region contains the phosphatase and C2 domains, is structurally similar to the tumor suppressor phosphatase PTEN, and catalyzes the dephosphorylation of phosphoinositides. The transmembrane voltage sensor is connected to the phosphatase through a short linker region, and phosphatase activity is induced upon membrane depolarization. Although the detailed molecular characteristics of the voltage sensor domain and the enzyme region have been revealed, little is known how these two regions are coupled. In addition, it is important to know whether mechanism for coupling between the voltage sensor domain and downstream effector function is shared among other voltage sensor domain-containing proteins. Recent studies in which specific amino acid sites were genetically labeled using a fluorescent unnatural amino acid have enabled detection of the local structural changes in the cytoplasmic region of Ciona intestinalis VSP that occur with a change in membrane potential. The results of those studies provide novel insight into how the enzyme activity of the cytoplasmic region of VSP is regulated by the voltage sensor domain.

MIT domain of Vps4 is a Ca2+-dependent phosphoinositide-binding domain.

Science.gov (United States)

Iwaya, Naoko; Takasu, Hirotoshi; Goda, Natsuko; Shirakawa, Masahiro; Tanaka, Toshiki; Hamada, Daizo; Hiroaki, Hidekazu

2013-05-01

The microtubule interacting and trafficking (MIT) domain is a small protein module that is conserved in proteins of diverged function, such as Vps4, spastin and sorting nexin 15 (SNX15). The molecular function of the MIT domain is protein-protein interaction, in which the domain recognizes peptides containing MIT-interacting motifs. Recently, we identified an evolutionarily related domain, 'variant' MIT domain at the N-terminal region of the microtubule severing enzyme katanin p60. We found that the domain was responsible for binding to microtubules and Ca(2+). Here, we have examined whether the authentic MIT domains also bind Ca(2+). We found that the loop between the first and second α-helices of the MIT domain binds a Ca(2+) ion. Furthermore, the MIT domains derived from Vps4b and SNX15a showed phosphoinositide-binding activities in a Ca(2+)-dependent manner. We propose that the MIT domain is a novel membrane-associating domain involved in endosomal trafficking.

Comparative analysis of the apparent saturation hysteresis approach and the domain theory of hysteresis in respect of prediction of scanning curves and air entrapment

Science.gov (United States)

Beriozkin, A.; Mualem, Y.

2018-05-01

This study theoretically analyzes the concept of apparent saturation hysteresis, combined with the Scott et al. (1983) scaling approach, as suggested by Parker and Lenhard (1987), to account for the effect of air entrapment and release on the soil water hysteresis. We found that the theory of Parker and Lenhard (1987) is comprised of some mutually canceling mathematical operations, and when cleared of the superfluous intermediate calculations, their model reduces to the original Scott et al.'s (1983) scaling method, supplemented with the requirement of closure of scanning loops. Our analysis reveals that actually there is no effect of their technique of accounting for the entrapped air on the final prediction of the effective saturation (or water content) scanning curves. Our consideration indicates that the use of the Land (1968) formula for assessing the amount of entrapped air is in disaccord with the apparent saturation concept as introduced by Parker and Lenhard (1987). In this paper, a proper routine is suggested for predicting hysteretic scanning curves of any order, given the two measured main curves, in the complete hysteretic domain and some verification tests are carried out versus measured results. Accordingly, explicit closed-form formulae for direct prediction (with no need of intermediate calculation) of scanning curves up to the third order are derived to sustain our analysis.

Novel Technology for Protein-Protein Interaction-based Targeted Drug Discovery

Directory of Open Access Journals (Sweden)

Jung Me Hwang

2011-12-01

Full Text Available We have developed a simple but highly efficient in-cell protein-protein interaction (PPI discovery system based on the translocation properties of protein kinase C- and its C1a domain in live cells. This system allows the visual detection of trimeric and dimeric protein interactions including cytosolic, nuclear, and/or membrane proteins with their cognate ligands. In addition, this system can be used to identify pharmacological small compounds that inhibit specific PPIs. These properties make this PPI system an attractive tool for screening drug candidates and mapping the protein interactome.

Distinct mechanisms of a phosphotyrosyl peptide binding to two SH2 domains.

Science.gov (United States)

Pang, Xiaodong; Zhou, Huan-Xiang

2014-05-01

Protein phosphorylation is very common post-translational modification, catalyzed by kinases, for signaling and regulation. Phosphotyrosines frequently target SH2 domains. The spleen tyrosine kinase (Syk) is critical for tyrosine phosphorylation of multiple proteins and for regulation of important pathways. Phosphorylation of both Y342 and Y346 in Syk linker B is required for optimal signaling. The SH2 domains of Vav1 and PLC-γ both bind this doubly phosphorylated motif. Here we used a recently developed method to calculate the effects of Y342 and Y346 phosphorylation on the rate constants of a peptide from Syk linker B binding to the SH2 domains of Vav1 and PLC-γ. The predicted effects agree well with experimental observations. Moreover, we found that the same doubly phosphorylated peptide binds the two SH2 domains via distinct mechanisms, with apparent rigid docking for Vav1 SH2 and dock-and-coalesce for PLC-γ SH2.

Conversion of Dielectric Data from the Time Domain to the Frequency Domain

Directory of Open Access Journals (Sweden)

Vladimir Durman

2005-01-01

Full Text Available Polarisation and conduction processes in dielectric systems can be identified by the time domain or the frequency domain measurements. If the systems is a linear one, the results of the time domain measurements can be transformed into the frequency domain, and vice versa. Commonly, the time domain data of the absorption conductivity are transformed into the frequency domain data of the dielectric susceptibility. In practice, the relaxation are mainly evaluated by the frequency domain data. In the time domain, the absorption current measurement were prefered up to now. Recent methods are based on the recovery voltage measurements. In this paper a new method of the recovery data conversion from the time the frequency domain is proposed. The method is based on the analysis of the recovery voltage transient based on the Maxwell equation for the current density in a dielectric. Unlike the previous published solutions, the Laplace fransform was used to derive a formula suitable for practical purposes. the proposed procedure allows also calculating of the insulation resistance and separating the polarisation and conduction losses.

Disentangling the effects of predator hunting mode and habitat domain on the top-down control of insect herbivores.

Science.gov (United States)

Woodcock, Ben A; Heard, Matthew S

2011-03-01

1. Polyphagous predatory invertebrates play a key role in the top-down control of insect herbivores. However, predicting predation risk for herbivores is not a simple function of predator species richness. Predation risk may be reduced or enhanced depending on the functional characteristics predator species. We predict that where predator species spatially overlap this will reduce predation risk for herbivores by allowing negative inter-specific interaction between predators to occur. Where increased predation risk occurs, we also predict that this will have a cascading effect through the food chain reducing plant growth. 2. We used a substitutive replicated block design to identify the effect of similarity and dissimilarity in predator hunting mode (e.g. 'sit and wait', 'sit and pursue', and 'active') and habitat domain (e.g. canopy or ground) on the top-down control of planthoppers in grasslands. Predators included within the mesocosms were randomly selected from a pool of 17 local species. 3. Predation risk was reduced where predators shared the same habitat domain, independent of whether they shared hunting modes. Where predators shared the same habitat domains, there was some evidence that this had a cascading negative effect on the re-growth of grass biomass. Where predator habitat domains did not overlap, there were substitutable effects on predation risk to planthoppers. Predation risk for planthoppers was affected by taxonomic identity of predator species, i.e. whether they were beetles, spiders or true bugs. 4. Our results indicated that in multi-predator systems, the risk of predation is typically reduced. Consideration of functional characteristics of individual species, in particular aspects of habitat domain and hunting mode, are crucial in predicting the effects of multi-predator systems on the top-down control of herbivores. © 2010 The Authors. Journal of Animal Ecology © 2010 British Ecological Society.

The consequences of chronic stereotype threat: domain disidentification and abandonment.

Science.gov (United States)

Woodcock, Anna; Hernandez, Paul R; Estrada, Mica; Schultz, P Wesley

2012-10-01

Stereotype threat impairs performance across many domains. Despite a wealth of research, the long-term consequences of chronic stereotype threat have received little empirical attention. Beyond the immediate impact on performance, the experience of chronic stereotype threat is hypothesized to lead to domain disidentification and eventual domain abandonment. Stereotype threat is 1 explanation why African Americans and Hispanic/Latino(a)s "leak" from each juncture of the academic scientific pipeline in disproportionately greater numbers than their White and Asian counterparts. Using structural equation modeling, we tested the stereotype threat-disidentification hypothesis across 3 academic years with a national longitudinal panel of undergraduate minority science students. Experience of stereotype threat was associated with scientific disidentification, which in turn predicted a significant decline in the intention to pursue a scientific career. Race/ethnicity moderated this effect, whereby the effect was evident for Hispanic/Latino(a) students but not for all African American students. We discuss findings in terms of understanding chronic stereotype threat.

TMDIM: an improved algorithm for the structure prediction of transmembrane domains of bitopic dimers

Science.gov (United States)

Cao, Han; Ng, Marcus C. K.; Jusoh, Siti Azma; Tai, Hio Kuan; Siu, Shirley W. I.

2017-09-01

α-Helical transmembrane proteins are the most important drug targets in rational drug development. However, solving the experimental structures of these proteins remains difficult, therefore computational methods to accurately and efficiently predict the structures are in great demand. We present an improved structure prediction method TMDIM based on Park et al. (Proteins 57:577-585, 2004) for predicting bitopic transmembrane protein dimers. Three major algorithmic improvements are introduction of the packing type classification, the multiple-condition decoy filtering, and the cluster-based candidate selection. In a test of predicting nine known bitopic dimers, approximately 78% of our predictions achieved a successful fit (RMSD PHP, MySQL and Apache, with all major browsers supported.

Time and frequency domain analyses of the Hualien Large-Scale Seismic Test

International Nuclear Information System (INIS)

Kabanda, John; Kwon, Oh-Sung; Kwon, Gunup

2015-01-01

Highlights: • Time- and frequency-domain analysis methods are verified against each other. • The two analysis methods are validated against Hualien LSST. • The nonlinear time domain (NLTD) analysis resulted in more realistic response. • The frequency domain (FD) analysis shows amplification at resonant frequencies. • The NLTD analysis requires significant modeling and computing time. - Abstract: In the nuclear industry, the equivalent-linear frequency domain analysis method has been the de facto standard procedure primarily due to the method's computational efficiency. This study explores the feasibility of applying the nonlinear time domain analysis method for the soil–structure-interaction analysis of nuclear power facilities. As a first step, the equivalency of the time and frequency domain analysis methods is verified through a site response analysis of one-dimensional soil, a dynamic impedance analysis of soil–foundation system, and a seismic response analysis of the entire soil–structure system. For the verifications, an idealized elastic soil–structure system is used to minimize variables in the comparison of the two methods. Then, the verified analysis methods are used to develop time and frequency domain models of Hualien Large-Scale Seismic Test. The predicted structural responses are compared against field measurements. The models are also analyzed with an amplified ground motion to evaluate discrepancies of the time and frequency domain analysis methods when the soil–structure system behaves beyond the elastic range. The analysis results show that the equivalent-linear frequency domain analysis method amplifies certain frequency bands and tends to result in higher structural acceleration than the nonlinear time domain analysis method. A comparison with field measurements shows that the nonlinear time domain analysis method better captures the frequency distribution of recorded structural responses than the frequency domain

Concrete domains

OpenAIRE

Kahn, G.; Plotkin, G.D.

1993-01-01

This paper introduces the theory of a particular kind of computation domains called concrete domains. The purpose of this theory is to find a satisfactory framework for the notions of coroutine computation and sequentiality of evaluation.

Comparative metabolite fingerprinting of the rumen system during colonisation of three forage grass (Lolium perenne L. varieties.

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Alison H Kingston-Smith

Full Text Available The rumen microbiota enable ruminants to degrade complex ligno-cellulosic compounds to produce high quality protein for human consumption. However, enteric fermentation by domestic ruminants generates negative by-products: greenhouse gases (methane and environmental nitrogen pollution. The current lack of cultured isolates representative of the totality of rumen microbial species creates an information gap about the in vivo function of the rumen microbiota and limits our ability to apply predictive biology for improvement of feed for ruminants. In this work we took a whole ecosystem approach to understanding how the metabolism of the microbial population responds to introduction of its substrate. Fourier Transform Infra Red (FTIR spectroscopy-based metabolite fingerprinting was used to discriminate differences in the plant-microbial interactome of the rumen when using three forage grass varieties (Lolium perenne L. cv AberDart, AberMagic and Premium as substrates for microbial colonisation and fermentation. Specific examination of spectral regions associated with fatty acids, amides, sugars and alkanes indicated that although the three forages were apparently similar by traditional nutritional analysis, patterns of metabolite flux within the plant-microbial interactome were distinct and plant genotype dependent. Thus, the utilisation pattern of forage nutrients by the rumen microbiota can be influenced by subtleties determined by forage genotypes. These data suggest that our interactomic approach represents an important means to improve forages and ultimately the livestock environment.

A Logic for Inclusion of Administrative Domains and Administrators in Multi-domain Authorization

Science.gov (United States)

Iranmanesh, Zeinab; Amini, Morteza; Jalili, Rasool

Authorization policies for an administrative domain or a composition of multiple domains in multi-domain environments are determined by either one administrator or multiple administrators' cooperation. Several logic-based models for multi-domain environments' authorization have been proposed; however, they have not considered administrators and administrative domains in policies' representation. In this paper, we propose the syntax, proof theory, and semantics of a logic for multi-domain authorization policies including administrators and administrative domains. Considering administrators in policies provides the possibility of presenting composite administration having applicability in many collaborative applications. Indeed, administrators and administrative domains stated in policies can be used in authorization. The presented logic is based on modal logic and utilizes two calculi named the calculus of administrative domains and the calculus of administrators. It is also proved that the logic is sound. A case study is presented signifying the logic application in practical projects.

Disgust domains in the prediction of contamination fear : A comparison of Dutch and US samples

NARCIS (Netherlands)

Sawchuk, Craig N.; Olatunji, Bunmi O.; De Jong, Peter J.

2006-01-01

The present study examines the disgust-contamination fear relationship among Dutch (N =260) and US (N =292) participants. US participants reported higher levels of disgust sensitivity across the majority of disgust domains and also endorsed stronger contamination fear than their Dutch counterparts.

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

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Samuel Rout

2016-12-01

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

The Anabaena sensory rhodopsin transducer defines a novel superfamily of prokaryotic small-molecule binding domains

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De Souza Robson F

2009-08-01

Full Text Available Abstract The Anabaena sensory rhodopsin transducer (ASRT is a small protein that has been claimed to function as a signaling molecule downstream of the cyanobacterial sensory rhodopsin. However, orthologs of ASRT have been detected in several bacteria that lack rhodopsin, raising questions about the generality of this function. Using sequence profile searches we show that ASRT defines a novel superfamily of β-sandwich fold domains. Through contextual inference based on domain architectures and predicted operons and structural analysis we present strong evidence that these domains bind small molecules, most probably sugars. We propose that the intracellular versions like ASRT probably participate as sensors that regulate a diverse range of sugar metabolism operons or even the light sensory behavior in Anabaena by binding sugars or related metabolites. We also show that one of the extracellular versions define a predicted sugar-binding structure in a novel cell-surface lipoprotein found across actinobacteria, including several pathogens such as Tropheryma, Actinomyces and Thermobifida. The analysis of this superfamily also provides new data to investigate the evolution of carbohydrate binding modes in β-sandwich domains with very different topologies. Reviewers: This article was reviewed by M. Madan Babu and Mark A. Ragan.

Distribution and evolution of stable single α-helices (SAH domains in myosin motor proteins.

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Dominic Simm

Full Text Available Stable single-alpha helices (SAHs are versatile structural elements in many prokaryotic and eukaryotic proteins acting as semi-flexible linkers and constant force springs. This way SAH-domains function as part of the lever of many different myosins. Canonical myosin levers consist of one or several IQ-motifs to which light chains such as calmodulin bind. SAH-domains provide flexibility in length and stiffness to the myosin levers, and may be particularly suited for myosins working in crowded cellular environments. Although the function of the SAH-domains in human class-6 and class-10 myosins has well been characterised, the distribution of the SAH-domain in all myosin subfamilies and across the eukaryotic tree of life remained elusive. Here, we analysed the largest available myosin sequence dataset consisting of 7919 manually annotated myosin sequences from 938 species representing all major eukaryotic branches using the SAH-prediction algorithm of Waggawagga, a recently developed tool for the identification of SAH-domains. With this approach we identified SAH-domains in more than one third of the supposed 79 myosin subfamilies. Depending on the myosin class, the presence of SAH-domains can range from a few to almost all class members indicating complex patterns of independent and taxon-specific SAH-domain gain and loss.

Vigorous physical activity predicts higher heart rate variability among younger adults.

Science.gov (United States)

May, Richard; McBerty, Victoria; Zaky, Adam; Gianotti, Melino

2017-06-14

Baseline heart rate variability (HRV) is linked to prospective cardiovascular health. We tested intensity and duration of weekly physical activity as predictors of heart rate variability in young adults. Time and frequency domain indices of HRV were calculated based on 5-min resting electrocardiograms collected from 82 undergraduate students. Hours per week of both moderate and vigorous activity were estimated using the International Physical Activity Questionnaire. In regression analyses, hours of vigorous physical activity, but not moderate activity, significantly predicted greater time domain and frequency domain indices of heart rate variability. Adjusted for weekly frequency, greater daily duration of vigorous activity failed to predict HRV indices. Future studies should test direct measurements of vigorous activity patterns as predictors of autonomic function in young adulthood.

Feature-level domain adaptation

DEFF Research Database (Denmark)

Kouw, Wouter M.; Van Der Maaten, Laurens J P; Krijthe, Jesse H.

2016-01-01

-level domain adaptation (flda), that models the dependence between the two domains by means of a feature-level transfer model that is trained to describe the transfer from source to target domain. Subsequently, we train a domain-adapted classifier by minimizing the expected loss under the resulting transfer...... modeled via a dropout distribution, which allows the classiffier to adapt to differences in the marginal probability of features in the source and the target domain. Our experiments on several real-world problems show that flda performs on par with state-of-the-art domainadaptation techniques.......Domain adaptation is the supervised learning setting in which the training and test data are sampled from different distributions: training data is sampled from a source domain, whilst test data is sampled from a target domain. This paper proposes and studies an approach, called feature...

Evidence-based selection of theories for designing behaviour change interventions: using methods based on theoretical construct domains to understand clinicians' blood transfusion behaviour.

Science.gov (United States)

Francis, Jill J; Stockton, Charlotte; Eccles, Martin P; Johnston, Marie; Cuthbertson, Brian H; Grimshaw, Jeremy M; Hyde, Chris; Tinmouth, Alan; Stanworth, Simon J

2009-11-01

Many theories of behaviour are potentially relevant to predictive and intervention studies but most studies investigate a narrow range of theories. Michie et al. (2005) agreed 12 'theoretical domains' from 33 theories that explain behaviour change. They developed a 'Theoretical Domains Interview' (TDI) for identifying relevant domains for specific clinical behaviours, but the framework has not been used for selecting theories for predictive studies. It was used here to investigate clinicians' transfusion behaviour in intensive care units (ICU). Evidence suggests that red blood cells transfusion could be reduced for some patients without reducing quality of care. (1) To identify the domains relevant to transfusion practice in ICUs and neonatal intensive care units (NICUs), using the TDI. (2) To use the identified domains to select appropriate theories for a study predicting transfusion behaviour. An adapted TDI about managing a patient with borderline haemoglobin by watching and waiting instead of transfusing red blood cells was used to conduct semi-structured, one-to-one interviews with 18 intensive care consultants and neonatologists across the UK. Relevant theoretical domains were: knowledge, beliefs about capabilities, beliefs about consequences, social influences, behavioural regulation. Further analysis at the construct level resulted in selection of seven theoretical approaches relevant to this context: Knowledge-Attitude-Behaviour Model, Theory of Planned Behaviour, Social Cognitive Theory, Operant Learning Theory, Control Theory, Normative Model of Work Team Effectiveness and Action Planning Approaches. This study illustrated, the use of the TDI to identify relevant domains in a complex area of inpatient care. This approach is potentially valuable for selecting theories relevant to predictive studies and resulted in greater breadth of potential explanations than would be achieved if a single theoretical model had been adopted.

PREFACE: Domain wall dynamics in nanostructures Domain wall dynamics in nanostructures

Science.gov (United States)

Marrows, C. H.; Meier, G.

2012-01-01

Domain structures in magnetic materials are ubiquitous and have been studied for decades. The walls that separate them are topological defects in the magnetic order parameter and have a wide variety of complex forms. In general, their investigation is difficult in bulk materials since only the domain structure on the surface of a specimen is visible. Cutting the sample to reveal the interior causes a rearrangement of the domains into a new form. As with many other areas of magnetism, the study of domain wall physics has been revitalised by the advent of nanotechnology. The ability to fabricate nanoscale structures has permitted the formation of simplified and controlled domain patterns; the development of advanced microscopy methods has permitted them to be imaged and then modelled; subjecting them to ultrashort field and current pulses has permitted their dynamics to be explored. The latest results from all of these advances are described in this special issue. Not only has this led to results of great scientific beauty, but also to concepts of great applicability to future information technologies. In this issue the reader will find the latest results for these domain wall dynamics and the high-speed processes of topological structures such as domain walls and magnetic vortices. These dynamics can be driven by the application of magnetic fields, or by flowing currents through spintronic devices using the novel physics of spin-transfer torque. This complexity has been studied using a wide variety of experimental techniques at the edge of the spatial and temporal resolution currently available, and can be described using sophisticated analytical theory and computational modelling. As a result, the dynamics can be engineered to give rise to finely controlled memory and logic devices with new functionality. Moreover, the field is moving to study not only the conventional transition metal ferromagnets, but also complex heterostructures, novel magnets and even other

Novel prediction- and subblock-based algorithm for fractal image compression

International Nuclear Information System (INIS)

Chung, K.-L.; Hsu, C.-H.

2006-01-01

Fractal encoding is the most consuming part in fractal image compression. In this paper, a novel two-phase prediction- and subblock-based fractal encoding algorithm is presented. Initially the original gray image is partitioned into a set of variable-size blocks according to the S-tree- and interpolation-based decomposition principle. In the first phase, each current block of variable-size range block tries to find the best matched domain block based on the proposed prediction-based search strategy which utilizes the relevant neighboring variable-size domain blocks. The first phase leads to a significant computation-saving effect. If the domain block found within the predicted search space is unacceptable, in the second phase, a subblock strategy is employed to partition the current variable-size range block into smaller blocks to improve the image quality. Experimental results show that our proposed prediction- and subblock-based fractal encoding algorithm outperforms the conventional full search algorithm and the recently published spatial-correlation-based algorithm by Truong et al. in terms of encoding time and image quality. In addition, the performance comparison among our proposed algorithm and the other two algorithms, the no search-based algorithm and the quadtree-based algorithm, are also investigated

Time-domain modeling of electromagnetic diffusion with a frequency-domain code

NARCIS (Netherlands)

Mulder, W.A.; Wirianto, M.; Slob, E.C.

2007-01-01

We modeled time-domain EM measurements of induction currents for marine and land applications with a frequency-domain code. An analysis of the computational complexity of a number of numerical methods shows that frequency-domain modeling followed by a Fourier transform is an attractive choice if a

Domain analyses of Usher syndrome causing Clarin-1 and GPR98 protein models.

Science.gov (United States)

Khan, Sehrish Haider; Javed, Muhammad Rizwan; Qasim, Muhammad; Shahzadi, Samar; Jalil, Asma; Rehman, Shahid Ur

2014-01-01

Usher syndrome is an autosomal recessive disorder that causes hearing loss, Retinitis Pigmentosa (RP) and vestibular dysfunction. It is clinically and genetically heterogeneous disorder which is clinically divided into three types i.e. type I, type II and type III. To date, there are about twelve loci and ten identified genes which are associated with Usher syndrome. A mutation in any of these genes e.g. CDH23, CLRN1, GPR98, MYO7A, PCDH15, USH1C, USH1G, USH2A and DFNB31 can result in Usher syndrome or non-syndromic deafness. These genes provide instructions for making proteins that play important roles in normal hearing, balance and vision. Studies have shown that protein structures of only seven genes have been determined experimentally and there are still three genes whose structures are unavailable. These genes are Clarin-1, GPR98 and Usherin. In the absence of an experimentally determined structure, homology modeling and threading often provide a useful 3D model of a protein. Therefore in the current study Clarin-1 and GPR98 proteins have been analyzed for signal peptide, domains and motifs. Clarin-1 protein was found to be without any signal peptide and consists of prokar lipoprotein domain. Clarin-1 is classified within claudin 2 super family and consists of twelve motifs. Whereas, GPR98 has a 29 amino acids long signal peptide and classified within GPCR family 2 having Concanavalin A-like lectin/glucanase superfamily. It was found to be consists of GPS and G protein receptor F2 domains and twenty nine motifs. Their 3D structures have been predicted using I-TASSER server. The model of Clarin-1 showed only α-helix but no beta sheets while model of GPR98 showed both α-helix and β sheets. The predicted structures were then evaluated and validated by MolProbity and Ramachandran plot. The evaluation of the predicted structures showed 78.9% residues of Clarin-1 and 78.9% residues of GPR98 within favored regions. The findings of present study has resulted in the

Pathway evidence of how musical perception predicts word-level reading ability in children with reading difficulties.

Directory of Open Access Journals (Sweden)

Hugo Cogo-Moreira

Full Text Available To investigate whether specific domains of musical perception (temporal and melodic domains predict the word-level reading skills of eight- to ten-year-old children (n = 235 with reading difficulties, normal quotient of intelligence, and no previous exposure to music education classes.A general-specific solution of the Montreal Battery of Evaluation of Amusia (MBEA, which underlies a musical perception construct and is constituted by three latent factors (the general, temporal, and the melodic domain, was regressed on word-level reading skills (rate of correct isolated words/non-words read per minute.General and melodic latent domains predicted word-level reading skills.

Prediction of monomer isomery in Florine: a workflow dedicated to nonribosomal peptide discovery.

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Thibault Caradec

Full Text Available Nonribosomal peptides represent a large variety of natural active compounds produced by microorganisms. Due to their specific biosynthesis pathway through large assembly lines called NonRibosomal Peptide Synthetases (NRPSs, they often display complex structures with cycles and branches. Moreover they often contain non proteogenic or modified monomers, such as the D-monomers produced by epimerization. We investigate here some sequence specificities of the condensation (C and epimerization (E domains of NRPS that can be used to predict the possible isomeric state (D or L of each monomer in a putative peptide. We show that C- and E- domains can be divided into 2 sub-regions called Up-Seq and Down-Seq. The Up-Seq region corresponds to an InterPro domain (IPR001242 and is shared by C- and E-domains. The Down-Seq region is specific to the enzymatic activity of the domain. Amino-acid signatures (represented as sequence logos previously described for complete C-and E-domains have been restricted to the Down-Seq region and amplified thanks to additional sequences. Moreover a new Down-Seq signature has been found for Ct-domains found in fungi and responsible for terminal cyclization of the peptides. The identification of these signatures has been included in a workflow named Florine, aimed to predict nonribosomal peptides from NRPS sequence analyses. In some cases, the prediction of isomery is guided by genus-specific rules. Florine was used on a Pseudomonas genome to allow the determination of the type of pyoverdin produced, the update of syringafactin structure and the identification of novel putative products.

Full-length RNA structure prediction of the HIV-1 genome reveals a conserved core domain

DEFF Research Database (Denmark)

Sükösd, Zsuzsanna; Andersen, Ebbe Sloth; Seemann, Ernst Stefan

2015-01-01

of the HIV-1 genome is highly variable in most regions, with a limited number of stable and conserved RNA secondary structures. Most interesting, a set of long distance interactions form a core organizing structure (COS) that organize the genome into three major structural domains. Despite overlapping...

Separated matter and antimatter domains with vanishing domain walls

Energy Technology Data Exchange (ETDEWEB)

Dolgov, A.D.; Godunov, S.I.; Rudenko, A.S.; Tkachev, I.I., E-mail: dolgov@fe.infn.it, E-mail: sgodunov@itep.ru, E-mail: a.s.rudenko@inp.nsk.su, E-mail: tkachev@ms2.inr.ac.ru [Physics Department and Laboratory of Cosmology and Elementary Particle Physics, Novosibirsk State University, Pirogova st. 2, Novosibirsk, 630090 (Russian Federation)

2015-10-01

We present a model of spontaneous (or dynamical) C and CP violation where it is possible to generate domains of matter and antimatter separated by cosmologically large distances. Such C(CP) violation existed only in the early universe and later it disappeared with the only trace of generated baryonic and/or antibaryonic domains. So the problem of domain walls in this model does not exist. These features are achieved through a postulated form of interaction between inflaton and a new scalar field, realizing short time C(CP) violation.

Comprehensive in Vitro Analysis of Acyltransferase Domain Exchanges in Modular Polyketide Synthases and Its Application for Short-Chain Ketone Production

DEFF Research Database (Denmark)

Yuzawa, Satoshi; Deng, Kai; Wang, George

2017-01-01

AT domain replacements in most type I PKS modules. To further demonstrate the utility of the optimized AT domain boundary, we have constructed hybrid PKSs to produce industrially important short-chain ketones. Our in vitro and in vivo analysis demonstrated production of predicted ketones without significant...

Protein sorting by lipid phase-like domains supports emergent signaling function in B lymphocyte plasma membranes.

Science.gov (United States)

Stone, Matthew B; Shelby, Sarah A; Núñez, Marcos F; Wisser, Kathleen; Veatch, Sarah L

2017-02-01

Diverse cellular signaling events, including B cell receptor (BCR) activation, are hypothesized to be facilitated by domains enriched in specific plasma membrane lipids and proteins that resemble liquid-ordered phase-separated domains in model membranes. This concept remains controversial and lacks direct experimental support in intact cells. Here, we visualize ordered and disordered domains in mouse B lymphoma cell membranes using super-resolution fluorescence localization microscopy, demonstrate that clustered BCR resides within ordered phase-like domains capable of sorting key regulators of BCR activation, and present a minimal, predictive model where clustering receptors leads to their collective activation by stabilizing an extended ordered domain. These results provide evidence for the role of membrane domains in BCR signaling and a plausible mechanism of BCR activation via receptor clustering that could be generalized to other signaling pathways. Overall, these studies demonstrate that lipid mediated forces can bias biochemical networks in ways that broadly impact signal transduction.

Domain Walls and Matter-Antimatter Domains in the Early Universe

Directory of Open Access Journals (Sweden)

Dolgov A.D.

2017-01-01

Full Text Available We suggest a scenario of spontaneous (or dynamical C and CP violation according to which it is possible to generate domains of matter and antimatter separated by cosmologically large distances. Such C(CP violation existed only in the early universe and later it disappeared with the only trace of generated matter and antimatter domains. So this scenario does not suffer from the problem of domain walls. According to this scenario the width of the domain wall should grow exponentially to prevent annihilation at the domain boundaries. Though there is a classical result obtained by Basu and Vilenkin that the width of the wall tends to the one of the stationary solution (constant physical width. That is why we considered thick domain walls in a de Sitter universe following paper by Basu and Vilenkin. However, we were interested not only in stationary solutions found therein, but also investigated the general case of domain wall evolution with time. When the wall thickness parameter, δ0 , is smaller than H−1/2 where H is the Hubble parameter in de Sitter space-time, then the stationary solutions exist, and initial field configurations tend with time to the stationary ones. However, there are no stationary solutions for δ0>H−1/2 We have calculated numerically the rate of the wall expansion in this case and have found that the width of the wall grows exponentially fast for δ0≫H−1 An explanation for the critical value δ0c=H−1/2 is also proposed.

Does the Assessment of Recovery Capital scale reflect a single or multiple domains?

Science.gov (United States)

Arndt, Stephan; Sahker, Ethan; Hedden, Suzy

2017-01-01

The goal of this study was to determine whether the 50-item Assessment of Recovery Capital scale represents a single general measure or whether multiple domains might be psychometrically useful for research or clinical applications. Data are from a cross-sectional de-identified existing program evaluation information data set with 1,138 clients entering substance use disorder treatment. Principal components and iterated factor analysis were used on the domain scores. Multiple group factor analysis provided a quasi-confirmatory factor analysis. The solution accounted for 75.24% of the total variance, suggesting that 10 factors provide a reasonably good fit. However, Tucker's congruence coefficients between the factor structure and defining weights (0.41-0.52) suggested a poor fit to the hypothesized 10-domain structure. Principal components of the 10-domain scores yielded one factor whose eigenvalue was greater than one (5.93), accounting for 75.8% of the common variance. A few domains had perceptible but small unique variance components suggesting that a few of the domains may warrant enrichment. Our findings suggest that there is one general factor, with a caveat. Using the 10 measures inflates the chance for Type I errors. Using one general measure avoids this issue, is simple to interpret, and could reduce the number of items. However, those seeking to maximally predict later recovery success may need to use the full instrument and all 10 domains.

An Evaluation of the Performance Diagnostic Checklist-Human Services (PDC-HS) Across Domains.

Science.gov (United States)

Wilder, David A; Lipschultz, Joshua; Gehrman, Chana

2018-06-01

The Performance Diagnostic Checklist-Human Services (PDC-HS) is an informant-based tool designed to assess the environmental variables that contribute to poor employee performance in human service settings. Although the PDC-HS has been shown to effectively identify variables contributing to problematic performance, interventions based on only two of the four PDC-HS domains have been evaluated to date. In addition, the extent to which PDC-HS-indicated interventions are more effective than nonindicated interventions for two domains remains unclear. In the current study, we administered the PDC-HS to supervisors to assess the variables contributing to infrequent teaching of verbal operants and use of a timer by therapists at a center-based autism treatment program. Each of the four PDC-HS domains was identified as contributing to poor performance for at least one therapist. We then evaluated PDC-HS-indicated interventions for each domain. In addition, to assess the predictive validity of the tool, we evaluated various nonindicated interventions prior to implementing a PDC-HS-indicated intervention for two of the four domains. Results suggest that the PDC-HS-indicated interventions were effective across all four domains and were more effective than the nonindicated interventions for the two domains for which they were evaluated. Results are discussed in terms of the utility of the PDC-HS to identify appropriate interventions to manage therapist performance in human service settings.

Quantitative Structure-Use Relationship Model thresholds for Model Validation, Domain of Applicability, and Candidate Alternative Selection

Data.gov (United States)

U.S. Environmental Protection Agency — This file contains value of the model training set confusion matrix, domain of applicability evaluation based on training set to predicted chemicals structural...

The PH Domain of PDK1 Exhibits a Novel, Phospho-Regulated Monomer-Dimer Equilibrium With Important Implications for Kinase Domain Activation: Single Molecule and Ensemble Studies†

Science.gov (United States)

Ziemba, Brian P.; Pilling, Carissa; Calleja, Véronique; Larijani, Banafshé; Falke, Joseph J.

2013-01-01

the viscous bilayer, thereby increasing the diffusional friction. Ensemble measurements of PH domain affinity for PIP3 on plasma membrane-like bilayers reveals that dimeric WT PH domain possesses a one-order of magnitude higher target membrane affinity than the previously characterized monomeric PH domains, consistent with a dimerization-triggered, allosterically-enhanced affinity for one PIP3 molecule (a much larger affinity enhancement would be expected for dimerization-triggered binding to two PIP3 molecules). The monomeric T513E PDK1 PH domain, like other monomeric PH domains, exhibits a PIP3 affinity and bound state lifetime that are each a full order of magnitude lower than dimeric WT PH domain, which is predicted to facilitate release of activated, monomeric PDK1 to cytoplasm. Overall, the study yields the first molecular picture of PH domain regulation via electrostatic control of dimer-monomer conversion. PMID:23745598

Cloning and Expressing Recombinant Protective Antigen Domains of B. anthracis

Science.gov (United States)

2011-09-01

future predictive modeling toolkits. 1 1. Introduction The use of Bacillus anthracis as a bio - weapon in the United States in 2001 affirmed the need...for improved sensing and detection of biological weapons of mass destruction (WMD). Protective Antigen (PA) protein of Bacillus anthracis is the...Cloning and Expressing Recombinant Protective Antigen Domains of B. anthracis by Deborah A. Sarkes, Joshua M. Kogot, Irene Val-Addo

Characterization of the CLASP2 Protein Interaction Network Identifies SOGA1 as a Microtubule-Associated Protein

DEFF Research Database (Denmark)

Sørensen, Rikke Kruse; Krantz, James; Barker, Natalie

2017-01-01

. The GTPase-activating proteins AGAP1 and AGAP3 were also enriched in the CLASP2 interactome, although subsequent AGAP3 and CLIP2 interactome analysis suggests a preference of AGAP3 for CLIP2. Follow-up MARK2 interactome analysis confirmed reciprocal co-IP of CLASP2 and also revealed MARK2 can co-IP SOGA1......, glycogen synthase, and glycogenin. Investigating the SOGA1 interactome confirmed SOGA1 can reciprocal co-IP both CLASP2 and MARK2 as well as glycogen synthase and glycogenin. SOGA1 was confirmed to colocalize with CLASP2 and also with tubulin, which identifies SOGA1 as a new microtubule-associated protein....... These results introduce the metabolic function of these proposed novel protein networks and their relationship with microtubules as new fields of cytoskeleton-associated protein biology....

Theory and experimental evidence of phonon domains and their roles in pre-martensitic phenomena

Science.gov (United States)

Jin, Yongmei M.; Wang, Yu U.; Ren, Yang

2015-12-01

Pre-martensitic phenomena, also called martensite precursor effects, have been known for decades while yet remain outstanding issues. This paper addresses pre-martensitic phenomena from new theoretical and experimental perspectives. A statistical mechanics-based Grüneisen-type phonon theory is developed. On the basis of deformation-dependent incompletely softened low-energy phonons, the theory predicts a lattice instability and pre-martensitic transition into elastic-phonon domains via 'phonon spinodal decomposition.' The phase transition lifts phonon degeneracy in cubic crystal and has a nature of phonon pseudo-Jahn-Teller lattice instability. The theory and notion of phonon domains consistently explain the ubiquitous pre-martensitic anomalies as natural consequences of incomplete phonon softening. The phonon domains are characterised by broken dynamic symmetry of lattice vibrations and deform through internal phonon relaxation in response to stress (a particular case of Le Chatelier's principle), leading to previously unexplored new domain phenomenon. Experimental evidence of phonon domains is obtained by in situ three-dimensional phonon diffuse scattering and Bragg reflection using high-energy synchrotron X-ray single-crystal diffraction, which observes exotic domain phenomenon fundamentally different from usual ferroelastic domain switching phenomenon. In light of the theory and experimental evidence of phonon domains and their roles in pre-martensitic phenomena, currently existing alternative opinions on martensitic precursor phenomena are revisited.

Mechanisms for integration of information models across related domains

Science.gov (United States)

Atkinson, Rob

2010-05-01

It is well recognised that there are opportunities and challenges in cross-disciplinary data integration. A significant barrier, however, is creating a conceptual model of the combined domains and the area of integration. For example, a groundwater domain application may require information from several related domains: geology, hydrology, water policy, etc. Each domain may have its own data holdings and conceptual models, but these will share various common concepts (eg. The concept of an aquifer). These areas of semantic overlap present significant challenges, firstly to choose a single representation (model) of a concept that appears in multiple disparate models,, then to harmonise these other models with the single representation. In addition, models may exist at different levels of abstraction depending on how closely aligned they are with a particular implementation. This makes it hard for modellers in one domain to introduce elements from another domain without either introducing a specific style of implementation, or conversely dealing with a set of abstract patterns that are hard to integrate with existing implementations. Models are easier to integrate if they are broken down into small units, with common concepts implemented using common models from well-known, and predictably managed shared libraries. This vision however requires development of a set of mechanisms (tools and procedures) for implementing and exploiting libraries of model components. These mechanisms need to handle publication, discovery, subscription, versioning and implementation of models in different forms. In this presentation a coherent suite of such mechanisms is proposed, using a scenario based on re-use of geosciences models. This approach forms the basis of a comprehensive strategy to empower domain modellers to create more interoperable systems. The strategy address a range of concerns and practice, and includes methodologies, an accessible toolkit, improvements to available

The structure function of the death domain of human IRAK-M.

Science.gov (United States)

Du, Jiangfeng; Nicolaes, Gerry Af; Kruijswijk, Danielle; Versloot, Miranda; van der Poll, Tom; van 't Veer, Cornelis

2014-12-07

IRAK-M is an inhibitor of Toll-like receptor signaling that acts by re-directing IRAK-4 activity to TAK1 independent NF-κB activation and by inhibition of IRAK-1/IRAK-2 activity. IRAK-M is expressed in monocytes/macrophages and lung epithelial cells. Lack of IRAK-M in mice greatly improves the resistance to nosocomial pneumonia and lung tumors, which entices IRAK-M as a potential therapeutic target. IRAK-M consists of an N-terminal death domain (DD), a dysfunctional kinase domain and unstructured C-terminal domain. Little is known however on IRAK-M's structure-function relationships. Since death domains provide the important interactions of IRAK-1, IRAK-2 and IRAK-4 molecules, we generated a 3D structure model of the human IRAK-M-DD (residues C5-G119) to guide mutagenesis studies and predict protein-protein interaction points. First we identified the DD residues involved in the endogenous capacity of IRAK-M to activate NF-κB that is displayed upon overexpression in 293T cells. W74 and R97, at distinct interfaces of the IRAK-M-DD, were crucial for this endogenous NF-κB activating capacity, as well as the C-terminal domain (S445-E596) of IRAK-M. Resulting anti-inflammatory A20 and pro-inflammatory IL-8 transcription in 293T cells was W74 dependent, while IL-8 protein expression was dependent on R97 and the TRAF6 binding motif at P478. The IRAK-M-DD W74 and R97 binding interfaces are predicted to interact with opposite sides of IRAK-4-DD's. Secondly we identified DD residues important for the inhibitory action of IRAK-M by stable overexpression of mutants in THP-1 macrophages and H292 lung epithelial cells. IRAK-M inhibited TLR2/4-mediated cytokine production in macrophages in a manner that is largely dependent on W74. R97 was not involved in inhibition of TNF production but was engaged in IL-6 down-regulation by IRAK-M. Protein-interactive residues D19-A23, located in between W74 and R97, were also observed to be crucial for inhibition of TLR2/4 mediated cytokine

TOPDOM: database of conservatively located domains and motifs in proteins.

Science.gov (United States)

Varga, Julia; Dobson, László; Tusnády, Gábor E

2016-09-01

The TOPDOM database-originally created as a collection of domains and motifs located consistently on the same side of the membranes in α-helical transmembrane proteins-has been updated and extended by taking into consideration consistently localized domains and motifs in globular proteins, too. By taking advantage of the recently developed CCTOP algorithm to determine the type of a protein and predict topology in case of transmembrane proteins, and by applying a thorough search for domains and motifs as well as utilizing the most up-to-date version of all source databases, we managed to reach a 6-fold increase in the size of the whole database and a 2-fold increase in the number of transmembrane proteins. TOPDOM database is available at http://topdom.enzim.hu The webpage utilizes the common Apache, PHP5 and MySQL software to provide the user interface for accessing and searching the database. The database itself is generated on a high performance computer. tusnady.gabor@ttk.mta.hu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Frequency Domain Computer Programs for Prediction and Analysis of Rail Vehicle Dynamics : Volume 1. Technical Report

Science.gov (United States)

1975-12-01

Frequency domain computer programs developed or acquired by TSC for the analysis of rail vehicle dynamics are described in two volumes. Volume I defines the general analytical capabilities required for computer programs applicable to single rail vehi...

Investigation of the spatial structure and interactions of the genome at sub-kilobase-pair resolution using T2C.

Science.gov (United States)

Kolovos, Petros; Brouwer, Rutger W W; Kockx, Christel E M; Lesnussa, Michael; Kepper, Nick; Zuin, Jessica; Imam, A M Ali; van de Werken, Harmen J G; Wendt, Kerstin S; Knoch, Tobias A; van IJcken, Wilfred F J; Grosveld, Frank

2018-03-01

Chromosome conformation capture (3C) and its derivatives (e.g., 4C, 5C and Hi-C) are used to analyze the 3D organization of genomes. We recently developed targeted chromatin capture (T2C), an inexpensive method for studying the 3D organization of genomes, interactomes and structural changes associated with gene regulation, the cell cycle, and cell survival and development. Here, we present the protocol for T2C based on capture, describing all experimental steps and bio-informatic tools in full detail. T2C offers high resolution, a large dynamic interaction frequency range and a high signal-to-noise ratio. Its resolution is determined by the resulting fragment size of the chosen restriction enzyme, which can lead to sub-kilobase-pair resolution. T2C's high coverage allows the identification of the interactome of each individual DNA fragment, which makes binning of reads (often used in other methods) basically unnecessary. Notably, T2C requires low sequencing efforts. T2C also allows multiplexing of samples for the direct comparison of multiple samples. It can be used to study topologically associating domains (TADs), determining their position, shape, boundaries, and intra- and inter-domain interactions, as well as the composition of aggregated loops, interactions between nucleosomes, individual transcription factor binding sites, and promoters and enhancers. T2C can be performed by any investigator with basic skills in molecular biology techniques in ∼7-8 d. Data analysis requires basic expertise in bioinformatics and in Linux and Python environments.

Prediction and Experimental Evidence for Thermodynamically Stable Charged Orbital Domain Walls

Energy Technology Data Exchange (ETDEWEB)

Li, Qing’an; Gray, K. E.; Wilkins, S. B.; Garcia Fernandez, M.; Rosenkranz, S.; Zheng, H.; Mitchell, J. F.

2014-08-01

The quest for miniaturization is prevalent in many fields of modern science and technology. The ultimate limit for conduction would be a one-dimensional (1D) chain of atoms and, for example, carbon nanotubes are a notable approximation to this ideal. Here we present strong evidence for an unexpected phenomenon—a sliding charge-density wave along pseudo-1D, atomically homogeneous orbital domain walls (ODWs) in insulating bilayer manganite crystals. At a threshold electric field, crystals exhibit abrupt transformations to higher conductance, while x-ray diffraction confirms that these are not due to heating or melting of charge order. The conductance data resemble those of well-known pseudo-1D sliding-charge-density waves, in particular the presence of a depinning voltage. The vital link is our theoretical insight that ODWs must be partially charged due to competition between orbital-induced strain and Coulomb repulsion. The ideas found here embody a new principle for creating ultra-nano conductive paths in other materials and devices.

Medication Reconciliation: Work Domain Ontology, prototype development, and a predictive model.

Science.gov (United States)

Markowitz, Eliz; Bernstam, Elmer V; Herskovic, Jorge; Zhang, Jiajie; Shneiderman, Ben; Plaisant, Catherine; Johnson, Todd R

2011-01-01

Medication errors can result from administration inaccuracies at any point of care and are a major cause for concern. To develop a successful Medication Reconciliation (MR) tool, we believe it necessary to build a Work Domain Ontology (WDO) for the MR process. A WDO defines the explicit, abstract, implementation-independent description of the task by separating the task from work context, application technology, and cognitive architecture. We developed a prototype based upon the WDO and designed to adhere to standard principles of interface design. The prototype was compared to Legacy Health System's and Pre-Admission Medication List Builder MR tools via a Keystroke-Level Model analysis for three MR tasks. The analysis found the prototype requires the fewest mental operations, completes tasks in the fewest steps, and completes tasks in the least amount of time. Accordingly, we believe that developing a MR tool, based upon the WDO and user interface guidelines, improves user efficiency and reduces cognitive load.

Functional Domains of the Quechua Language in Peru: Issues of Status Planning.

Science.gov (United States)

Coronel-Molina, Serafin M.

1999-01-01

Examines the status of Quechua in Peru and how it has affected language maintenance efforts; discusses the functional domains served by Quechua, relating them to Peruvian language policies; notes the lack of grassroots efforts by indigenous people in Peru; and suggests possible measures to improve its status, noting predictions of the future of…

Scale-free crystallization of two-dimensional complex plasmas: Domain analysis using Minkowski tensors

Science.gov (United States)

Böbel, A.; Knapek, C. A.; Räth, C.

2018-05-01

Experiments of the recrystallization processes in two-dimensional complex plasmas are analyzed to rigorously test a recently developed scale-free phase transition theory. The "fractal-domain-structure" (FDS) theory is based on the kinetic theory of Frenkel. It assumes the formation of homogeneous domains, separated by defect lines, during crystallization and a fractal relationship between domain area and boundary length. For the defect number fraction and system energy a scale-free power-law relation is predicted. The long-range scaling behavior of the bond-order correlation function shows clearly that the complex plasma phase transitions are not of the Kosterlitz, Thouless, Halperin, Nelson, and Young type. Previous preliminary results obtained by counting the number of dislocations and applying a bond-order metric for structural analysis are reproduced. These findings are supplemented by extending the use of the bond-order metric to measure the defect number fraction and furthermore applying state-of-the-art analysis methods, allowing a systematic testing of the FDS theory with unprecedented scrutiny: A morphological analysis of lattice structure is performed via Minkowski tensor methods. Minkowski tensors form a complete family of additive, motion covariant and continuous morphological measures that are sensitive to nonlinear properties. The FDS theory is rigorously confirmed and predictions of the theory are reproduced extremely well. The predicted scale-free power-law relation between defect fraction number and system energy is verified for one more order of magnitude at high energies compared to the inherently discontinuous bond-order metric. It is found that the fractal relation between crystalline domain area and circumference is independent of the experiment, the particular Minkowski tensor method, and the particular choice of parameters. Thus, the fractal relationship seems to be inherent to two-dimensional phase transitions in complex plasmas. Minkowski

Extremes of random fields over arbitrary domains with application to concrete rupture stresses

DEFF Research Database (Denmark)

Ditlevsen, Ove Dalager

2004-01-01

function class is studied for Gaussian processes in earlier works by the author and it has been obtained explicitly for Gaussian fields on rectangular domains in the plane. Simulation studies show that rather good predictions are obtained for sufficiently smooth wide band Gaussian processes and fields...

Data management of protein interaction networks

CERN Document Server

Cannataro, Mario

2012-01-01

Interactomics: a complete survey from data generation to knowledge extraction With the increasing use of high-throughput experimental assays, more and more protein interaction databases are becoming available. As a result, computational analysis of protein-to-protein interaction (PPI) data and networks, now known as interactomics, has become an essential tool to determine functionally associated proteins. From wet lab technologies to data management to knowledge extraction, this timely book guides readers through the new science of interactomics, giving them the tools needed to: Generate

Crystal Structure of the Marburg Virus VP35 Oligomerization Domain

Energy Technology Data Exchange (ETDEWEB)

Bruhn, Jessica F.; Kirchdoerfer, Robert N.; Urata, Sarah M.; Li, Sheng; Tickle, Ian J.; Bricogne, Gérard; Saphire, Erica Ollmann (Scripps); (Globel Phasing); (UCSD)

2016-11-09

Marburg virus (MARV) is a highly pathogenic filovirus that is classified in a genus distinct from that of Ebola virus (EBOV) (generaMarburgvirusandEbolavirus, respectively). Both viruses produce a multifunctional protein termed VP35, which acts as a polymerase cofactor, a viral protein chaperone, and an antagonist of the innate immune response. VP35 contains a central oligomerization domain with a predicted coiled-coil motif. This domain has been shown to be essential for RNA polymerase function. Here we present crystal structures of the MARV VP35 oligomerization domain. These structures and accompanying biophysical characterization suggest that MARV VP35 is a trimer. In contrast, EBOV VP35 is likely a tetramer in solution. Differences in the oligomeric state of this protein may explain mechanistic differences in replication and immune evasion observed for MARV and EBOV.

IMPORTANCEMarburg virus can cause severe disease, with up to 90% human lethality. Its genome is concise, only producing seven proteins. One of the proteins, VP35, is essential for replication of the viral genome and for evasion of host immune responses. VP35 oligomerizes (self-assembles) in order to function, yet the structure by which it assembles has not been visualized. Here we present two crystal structures of this oligomerization domain. In both structures, three copies of VP35 twist about each other to form a coiled coil. This trimeric assembly is in contrast to tetrameric predictions for VP35 of Ebola virus and to known structures of homologous proteins in the measles, mumps, and Nipah viruses. Distinct oligomeric states of the Marburg and Ebola virus VP35 proteins may explain differences between them in polymerase function and immune evasion. These findings may provide a more accurate understanding of the

Structure characterization of the central repetitive domain of high molecular weight gluten proteins .1. Model studies using cyclic and linear peptides

NARCIS (Netherlands)

VanDijk, AA; VanWijk, LL; VanVliet, A; Haris, P; VanSwieten, E; Tesser, GI; Robillard, GT

The high molecular weight (HMW) proteins from wheat contain a repetitive domain that forms 60-80% of their sequence. The consensus peptides PGQGQQ and GYYPTSPQQ form more than 90% of the domain; both are predicted to adopt beta-turn structure. This paper describes the structural characterization of

Domain Decomposition Solvers for Frequency-Domain Finite Element Equations

KAUST Repository

Copeland, Dylan

2010-10-05

The paper is devoted to fast iterative solvers for frequency-domain finite element equations approximating linear and nonlinear parabolic initial boundary value problems with time-harmonic excitations. Switching from the time domain to the frequency domain allows us to replace the expensive time-integration procedure by the solution of a simple linear elliptic system for the amplitudes belonging to the sine- and to the cosine-excitation or a large nonlinear elliptic system for the Fourier coefficients in the linear and nonlinear case, respectively. The fast solution of the corresponding linear and nonlinear system of finite element equations is crucial for the competitiveness of this method. © 2011 Springer-Verlag Berlin Heidelberg.

Domain Decomposition Solvers for Frequency-Domain Finite Element Equations

KAUST Repository

Copeland, Dylan; Kolmbauer, Michael; Langer, Ulrich

2010-01-01

The paper is devoted to fast iterative solvers for frequency-domain finite element equations approximating linear and nonlinear parabolic initial boundary value problems with time-harmonic excitations. Switching from the time domain to the frequency domain allows us to replace the expensive time-integration procedure by the solution of a simple linear elliptic system for the amplitudes belonging to the sine- and to the cosine-excitation or a large nonlinear elliptic system for the Fourier coefficients in the linear and nonlinear case, respectively. The fast solution of the corresponding linear and nonlinear system of finite element equations is crucial for the competitiveness of this method. © 2011 Springer-Verlag Berlin Heidelberg.

Domain shape instabilities and dendrite domain growth in uniaxial ferroelectrics

Science.gov (United States)

Shur, Vladimir Ya.; Akhmatkhanov, Andrey R.

2018-01-01

The effects of domain wall shape instabilities and the formation of nanodomains in front of moving walls obtained in various uniaxial ferroelectrics are discussed. Special attention is paid to the formation of self-assembled nanoscale and dendrite domain structures under highly non-equilibrium switching conditions. All obtained results are considered in the framework of the unified kinetic approach to domain structure evolution based on the analogy with first-order phase transformation. This article is part of the theme issue `From atomistic interfaces to dendritic patterns'.

ING1 induces apoptosis through direct effects at the mitochondria

DEFF Research Database (Denmark)

Bose, P; Thakur, S; Thalappilly, S

2013-01-01

The ING family of tumor suppressors acts as readers and writers of the histone epigenetic code, affecting DNA repair, chromatin remodeling, cellular senescence, cell cycle regulation and apoptosis. The best characterized member of the ING family, ING1,interacts with the proliferating cell nuclear....... Bioinformatic analysis of the yeast interactome indicates that yeast ING proteins interact with 64 mitochondrial proteins. Also, sequence analysis of ING1 reveals the presence of a BH3-like domain. These data suggest a model in which stress-induced cytoplasmic relocalization of ING1 by14-3-3 induces ING1-BAX...

Jahn-teller domains and magnetic domains in Mn2FeO4

NARCIS (Netherlands)

Kub, J.; Brabers, V.A.M.; Novák, P.; Gemperle, R.; Simsova, J.

2000-01-01

Elastic (Jahn–Teller) domains and magnetic domains in the tetragonal spinel Mn2FeO4 were studied using X-ray double-crystal topography, X-ray diffractometry and the colloid-SEM method. The Jahn–Teller domains of the measured samples are tetragonal with the [0 0 1] c-axis alternating perpendicularly

The extended-domain-eigenfunction method for solving elliptic boundary value problems with annular domains

Energy Technology Data Exchange (ETDEWEB)

Aarao, J; Bradshaw-Hajek, B H; Miklavcic, S J; Ward, D A, E-mail: Stan.Miklavcic@unisa.edu.a [School of Mathematics and Statistics, University of South Australia, Mawson Lakes, SA 5095 (Australia)

2010-05-07

Standard analytical solutions to elliptic boundary value problems on asymmetric domains are rarely, if ever, obtainable. In this paper, we propose a solution technique wherein we embed the original domain into one with simple boundaries where the classical eigenfunction solution approach can be used. The solution in the larger domain, when restricted to the original domain, is then the solution of the original boundary value problem. We call this the extended-domain-eigenfunction method. To illustrate the method's strength and scope, we apply it to Laplace's equation on an annular-like domain.

Between-Domain Relations of Students’ Academic Emotions and Their Judgments of School Domain Similarity

Directory of Open Access Journals (Sweden)

Thomas eGoetz

2014-10-01

Full Text Available With the aim to deepen our understanding of the between-domain relations of academic emotions, a series of three studies was conducted. We theorized that between-domain relations of trait (i.e., habitual emotions reflected students’ judgments of domain similarities, whereas between-domain relations of state (i.e., momentary emotions did not. This supposition was based on the accessibility model of emotional self-report, according to which individuals’ beliefs tend to strongly impact trait, but not state emotions. The aim of Study 1 (interviews; N = 40; 8th and 11th graders was to gather salient characteristics of academic domains from students’ perspective. In Study 2 (N=1709; 8th and 11th graders the 13 characteristics identified in Study 1 were assessed along with academic emotions in four different domains (mathematics, physics, German, and English using a questionnaire-based trait assessment. With respect to the same domains, state emotions were assessed in Study 3 (N = 121; 8th and 11th graders by employing an experience sampling approach. In line with our initial assumptions, between-domain relations of trait but not state academic emotions reflected between-domain relations of domain characteristics. Implications for research and practice are discussed.

Between-domain relations of students' academic emotions and their judgments of school domain similarity

Science.gov (United States)

Goetz, Thomas; Haag, Ludwig; Lipnevich, Anastasiya A.; Keller, Melanie M.; Frenzel, Anne C.; Collier, Antonie P. M.

2014-01-01

With the aim to deepen our understanding of the between-domain relations of academic emotions, a series of three studies was conducted. We theorized that between-domain relations of trait (i.e., habitual) emotions reflected students' judgments of domain similarities, whereas between-domain relations of state (i.e., momentary) emotions did not. This supposition was based on the accessibility model of emotional self-report, according to which individuals' beliefs tend to strongly impact trait, but not state emotions. The aim of Study 1 (interviews; N = 40; 8th and 11th graders) was to gather salient characteristics of academic domains from students' perspective. In Study 2 (N = 1709; 8th and 11th graders) the 13 characteristics identified in Study 1 were assessed along with academic emotions in four different domains (mathematics, physics, German, and English) using a questionnaire-based trait assessment. With respect to the same domains, state emotions were assessed in Study 3 (N = 121; 8th and 11th graders) by employing an experience sampling approach. In line with our initial assumptions, between-domain relations of trait but not state academic emotions reflected between-domain relations of domain characteristics. Implications for research and practice are discussed. PMID:25374547

Expansion of protein domain repeats.

Directory of Open Access Journals (Sweden)

Asa K Björklund

2006-08-01

Full Text Available Many proteins, especially in eukaryotes, contain tandem repeats of several domains from the same family. These repeats have a variety of binding properties and are involved in protein-protein interactions as well as binding to other ligands such as DNA and RNA. The rapid expansion of protein domain repeats is assumed to have evolved through internal tandem duplications. However, the exact mechanisms behind these tandem duplications are not well-understood. Here, we have studied the evolution, function, protein structure, gene structure, and phylogenetic distribution of domain repeats. For this purpose we have assigned Pfam-A domain families to 24 proteomes with more sensitive domain assignments in the repeat regions. These assignments confirmed previous findings that eukaryotes, and in particular vertebrates, contain a much higher fraction of proteins with repeats compared with prokaryotes. The internal sequence similarity in each protein revealed that the domain repeats are often expanded through duplications of several domains at a time, while the duplication of one domain is less common. Many of the repeats appear to have been duplicated in the middle of the repeat region. This is in strong contrast to the evolution of other proteins that mainly works through additions of single domains at either terminus. Further, we found that some domain families show distinct duplication patterns, e.g., nebulin domains have mainly been expanded with a unit of seven domains at a time, while duplications of other domain families involve varying numbers of domains. Finally, no common mechanism for the expansion of all repeats could be detected. We found that the duplication patterns show no dependence on the size of the domains. Further, repeat expansion in some families can possibly be explained by shuffling of exons. However, exon shuffling could not have created all repeats.

Domain of composition and finite volume schemes on non-matching grids; Decomposition de domaine et schemas volumes finis sur maillages non-conformes

Energy Technology Data Exchange (ETDEWEB)

Saas, L.

2004-05-01

This Thesis deals with sedimentary basin modeling whose goal is the prediction through geological times of the localizations and appraisal of hydrocarbons quantities present in the ground. Due to the natural and evolutionary decomposition of the sedimentary basin in blocks and stratigraphic layers, domain decomposition methods are requested to simulate flows of waters and of hydrocarbons in the ground. Conservations laws are used to model the flows in the ground and form coupled partial differential equations which must be discretized by finite volume method. In this report we carry out a study on finite volume methods on non-matching grids solved by domain decomposition methods. We describe a family of finite volume schemes on non-matching grids and we prove that the associated global discretized problem is well posed. Then we give an error estimate. We give two examples of finite volume schemes on non matching grids and the corresponding theoretical results (Constant scheme and Linear scheme). Then we present the resolution of the global discretized problem by a domain decomposition method using arbitrary interface conditions (for example Robin conditions). Finally we give numerical results which validate the theoretical results and study the use of finite volume methods on non-matching grids for basin modeling. (author)

Applications of contact predictions to structural biology

Directory of Open Access Journals (Sweden)

Felix Simkovic

2017-05-01

Full Text Available Evolutionary pressure on residue interactions, intramolecular or intermolecular, that are important for protein structure or function can lead to covariance between the two positions. Recent methodological advances allow much more accurate contact predictions to be derived from this evolutionary covariance signal. The practical application of contact predictions has largely been confined to structural bioinformatics, yet, as this work seeks to demonstrate, the data can be of enormous value to the structural biologist working in X-ray crystallography, cryo-EM or NMR. Integrative structural bioinformatics packages such as Rosetta can already exploit contact predictions in a variety of ways. The contribution of contact predictions begins at construct design, where structural domains may need to be expressed separately and contact predictions can help to predict domain limits. Structure solution by molecular replacement (MR benefits from contact predictions in diverse ways: in difficult cases, more accurate search models can be constructed using ab initio modelling when predictions are available, while intermolecular contact predictions can allow the construction of larger, oligomeric search models. Furthermore, MR using supersecondary motifs or large-scale screens against the PDB can exploit information, such as the parallel or antiparallel nature of any β-strand pairing in the target, that can be inferred from contact predictions. Contact information will be particularly valuable in the determination of lower resolution structures by helping to assign sequence register. In large complexes, contact information may allow the identity of a protein responsible for a certain region of density to be determined and then assist in the orientation of an available model within that density. In NMR, predicted contacts can provide long-range information to extend the upper size limit of the technique in a manner analogous but complementary to experimental

A 2D Daubechies finite wavelet domain method for transient wave response analysis in shear deformable laminated composite plates

Science.gov (United States)

Nastos, C. V.; Theodosiou, T. C.; Rekatsinas, C. S.; Saravanos, D. A.

2018-03-01

An efficient numerical method is developed for the simulation of dynamic response and the prediction of the wave propagation in composite plate structures. The method is termed finite wavelet domain method and takes advantage of the outstanding properties of compactly supported 2D Daubechies wavelet scaling functions for the spatial interpolation of displacements in a finite domain of a plate structure. The development of the 2D wavelet element, based on the first order shear deformation laminated plate theory is described and equivalent stiffness, mass matrices and force vectors are calculated and synthesized in the wavelet domain. The transient response is predicted using the explicit central difference time integration scheme. Numerical results for the simulation of wave propagation in isotropic, quasi-isotropic and cross-ply laminated plates are presented and demonstrate the high spatial convergence and problem size reduction obtained by the present method.

Interoperable domain models : The ISO land administration domain model LADM and its external classes

NARCIS (Netherlands)

Lemmen, C.H.J.; Van Oosterom, P.J.M.; Uitermark, H.T.; Zevenbergen, J.A.; Cooper, A.K.

2011-01-01

This paper provides a brief overview of one of the first spatial domain standards: a standard for the domain of Land Administration (LA). This standard is in the draft stage of development now (May 2011). The development of domain standards is a logical follow up after domain-independent standards,

Using structural knowledge in the protein data bank to inform the search for potential host-microbe protein interactions in sequence space: application to Mycobacterium tuberculosis.

Science.gov (United States)

Mahajan, Gaurang; Mande, Shekhar C

2017-04-04

A comprehensive map of the human-M. tuberculosis (MTB) protein interactome would help fill the gaps in our understanding of the disease, and computational prediction can aid and complement experimental studies towards this end. Several sequence-based in silico approaches tap the existing data on experimentally validated protein-protein interactions (PPIs); these PPIs serve as templates from which novel interactions between pathogen and host are inferred. Such comparative approaches typically make use of local sequence alignment, which, in the absence of structural details about the interfaces mediating the template interactions, could lead to incorrect inferences, particularly when multi-domain proteins are involved. We propose leveraging the domain-domain interaction (DDI) information in PDB complexes to score and prioritize candidate PPIs between host and pathogen proteomes based on targeted sequence-level comparisons. Our method picks out a small set of human-MTB protein pairs as candidates for physical interactions, and the use of functional meta-data suggests that some of them could contribute to the in vivo molecular cross-talk between pathogen and host that regulates the course of the infection. Further, we present numerical data for Pfam domain families that highlights interaction specificity on the domain level. Not every instance of a pair of domains, for which interaction evidence has been found in a few instances (i.e. structures), is likely to functionally interact. Our sorting approach scores candidates according to how "distant" they are in sequence space from known examples of DDIs (templates). Thus, it provides a natural way to deal with the heterogeneity in domain-level interactions. Our method represents a more informed application of local alignment to the sequence-based search for potential human-microbial interactions that uses available PPI data as a prior. Our approach is somewhat limited in its sensitivity by the restricted size and

Domain architecture conservation in orthologs

Science.gov (United States)

2011-01-01

Background As orthologous proteins are expected to retain function more often than other homologs, they are often used for functional annotation transfer between species. However, ortholog identification methods do not take into account changes in domain architecture, which are likely to modify a protein's function. By domain architecture we refer to the sequential arrangement of domains along a protein sequence. To assess the level of domain architecture conservation among orthologs, we carried out a large-scale study of such events between human and 40 other species spanning the entire evolutionary range. We designed a score to measure domain architecture similarity and used it to analyze differences in domain architecture conservation between orthologs and paralogs relative to the conservation of primary sequence. We also statistically characterized the extents of different types of domain swapping events across pairs of orthologs and paralogs. Results The analysis shows that orthologs exhibit greater domain architecture conservation than paralogous homologs, even when differences in average sequence divergence are compensated for, for homologs that have diverged beyond a certain threshold. We interpret this as an indication of a stronger selective pressure on orthologs than paralogs to retain the domain architecture required for the proteins to perform a specific function. In general, orthologs as well as the closest paralogous homologs have very similar domain architectures, even at large evolutionary separation. The most common domain architecture changes observed in both ortholog and paralog pairs involved insertion/deletion of new domains, while domain shuffling and segment duplication/deletion were very infrequent. Conclusions On the whole, our results support the hypothesis that function conservation between orthologs demands higher domain architecture conservation than other types of homologs, relative to primary sequence conservation. This supports the

Effects of sub-domain structure on initial magnetization curve and domain size distribution of stacked media

International Nuclear Information System (INIS)

Sato, S.; Kumagai, S.; Sugita, R.

2015-01-01

In this paper, in order to confirm the sub-domain structure in stacked media demagnetized with in-plane field, initial magnetization curves and magnetic domain size distribution were investigated. Both experimental and simulation results showed that an initial magnetization curve for the medium demagnetized with in-plane field (MDI) initially rose faster than that for the medium demagnetized with perpendicular field (MDP). It is inferred that this is because the MDI has a larger number of domain walls than the MDP due to the existence of the sub-domains, resulting in an increase in the probability of domain wall motion. Dispersion of domain size for the MDI was larger than that for the MDP. This is because sub-domains are formed not only inside the domain but also at the domain boundary region, and they change the position of the domain boundary to affect the domain size. - Highlights: • An initial magnetization curve for MDI initially rose faster than that for MDP. • Dispersion of domain size for the MDI was larger than that for the MDP. • Experimental and simulation results can be explained by existence of sub-domains

The PH domain of phosphoinositide-dependent kinase-1 exhibits a novel, phospho-regulated monomer-dimer equilibrium with important implications for kinase domain activation: single-molecule and ensemble studies.

Science.gov (United States)

Ziemba, Brian P; Pilling, Carissa; Calleja, Véronique; Larijani, Banafshé; Falke, Joseph J

2013-07-16

deeper insertion of the protein into the viscous bilayer, thereby increasing the diffusional friction. Ensemble measurements of PH domain affinity for PIP3 on plasma membrane-like bilayers reveal that the dimeric WT PH domain possesses a one order of magnitude higher target membrane affinity than the previously characterized monomeric PH domains, consistent with a dimerization-triggered, allosterically enhanced affinity for one PIP3 molecule (a much larger affinity enhancement would be expected for dimerization-triggered binding to two PIP3 molecules). The monomeric T513E PDK1 PH domain, like other monomeric PH domains, exhibits a PIP3 affinity and bound state lifetime that are each 1 order of magnitude lower than those of the dimeric WT PH domain, which is predicted to facilitate release of activated, monomeric PDK1 to the cytoplasm. Overall, the study yields the first molecular picture of PH domain regulation via electrostatic control of dimer-monomer conversion.

Langevin equations with multiplicative noise: application to domain growth

International Nuclear Information System (INIS)

Sancho, J.M.; Hernandez-Machado, A.; Ramirez-Piscina, L.; Lacasta, A.M.

1993-01-01

Langevin equations of Ginzburg-Landau form with multiplicative noise, are proposed to study the effects of fluctuations in domain growth. These equations are derived from a coarse-grained methodology. The Cahn-Hilliard-Cook linear stability analysis predicts some effects in the transitory regime. We also derive numerical algorithms for the computer simulation of these equations. The numerical results corroborate the analytical productions of the linear analysis. We also present simulation results for spinodal decomposition at large times. (author). 28 refs, 2 figs

Isothermal and aniso-thermal creep in the {alpha} phase domain, {beta} phase domain and {alpha}+{beta} two phase domain in a Zr-1%NbO alloy; Fluage isotherme et anisotherme dans les domaines monophases ({alpha} et {beta}) et biphases ({alpha} et {beta}) d'un alliage Zr-1%NbO

Energy Technology Data Exchange (ETDEWEB)

Kaddour, D

2004-12-15

The coupling between phase transformation and mechanical behaviour of a Zr-1%NbO alloy was studied using an original experimental device already used in a previous study devoted to the Zy-4 alloy. The Zr-1%NbO alloy undergoes a phase transformation {alpha} (hc) {r_reversible} (cc) typically between 750 and 1000 C. The transformation temperatures were measured in situ by using the resistivity and dilatometry techniques. The isothermal creep behaviour of fuel cladding tubes was studied, first after heating, in the {alpha} phase domain between 650 and 760 C, in the {beta} phase domain between 960 and 1100 C, as well as in the ({alpha} + {beta}) two phase domain between 800 and 900 C. The results are summarized in Ashby deformation mechanism maps. It is confirmed that the {beta} phase is much more sensitive to creep flow than the {alpha} phase. The effect of microstructure on the isothermal creep flow behaviour was then investigated by first applying a thermal cycle involving either a full or a partial transformation from {alpha} to {beta}. It was investigated both in the {alpha} phase domain, and after direct cooling into the ({alpha} + {beta}) phase domain. The behaviour in aniso-thermal conditions was finally studied at heating and cooling rates of 10 and 200 C/min. In both cases, we showed that there is no significant transformation plasticity in the stress range under investigation ({<=} 5 MPa). A finite element model using Voronoi polyhedra and eventually meshing a film of intergranular {beta} phase was used to describe the behaviour of material in the ({alpha} + {beta}) domain in various microstructural states. The model predictions are in good agreement with the experimental results for the microstructure obtained after cooling, but the model underestimates creep deformation in the as-received state. This difference is probably related to the fact that interface sliding is not taken into account in the model. (author)