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Sample records for active site prediction

  1. Prediction of P53 mutants (multiple sites transcriptional activity based on structural (2D&3D properties.

    R Geetha Ramani

    Full Text Available Prediction of secondary site mutations that reinstate mutated p53 to normalcy has been the focus of intense research in the recent past owing to the fact that p53 mutants have been implicated in more than half of all human cancers and restoration of p53 causes tumor regression. However laboratory investigations are more often laborious and resource intensive but computational techniques could well surmount these drawbacks. In view of this, we formulated a novel approach utilizing computational techniques to predict the transcriptional activity of multiple site (one-site to five-site p53 mutants. The optimal MCC obtained by the proposed approach on prediction of one-site, two-site, three-site, four-site and five-site mutants were 0.775,0.341,0.784,0.916 and 0.655 respectively, the highest reported thus far in literature. We have also demonstrated that 2D and 3D features generate higher prediction accuracy of p53 activity and our findings revealed the optimal results for prediction of p53 status, reported till date. We believe detection of the secondary site mutations that suppress tumor growth may facilitate better understanding of the relationship between p53 structure and function and further knowledge on the molecular mechanisms and biological activity of p53, a targeted source for cancer therapy. We expect that our prediction methods and reported results may provide useful insights on p53 functional mechanisms and generate more avenues for utilizing computational techniques in biological data analysis.

  2. In Silico Structure Prediction of Human Fatty Acid Synthase-Dehydratase: A Plausible Model for Understanding Active Site Interactions.

    John, Arun; Umashankar, Vetrivel; Samdani, A; Sangeetha, Manoharan; Krishnakumar, Subramanian; Deepa, Perinkulam Ravi

    2016-01-01

    Fatty acid synthase (FASN, UniProt ID: P49327) is a multienzyme dimer complex that plays a critical role in lipogenesis. Consequently, this lipogenic enzyme has gained tremendous biomedical importance. The role of FASN and its inhibition is being extensively researched in several clinical conditions, such as cancers, obesity, and diabetes. X-ray crystallographic structures of some of its domains, such as β-ketoacyl synthase, acetyl transacylase, malonyl transacylase, enoyl reductase, β-ketoacyl reductase, and thioesterase, (TE) are already reported. Here, we have attempted an in silico elucidation of the uncrystallized dehydratase (DH) catalytic domain of human FASN. This theoretical model for DH domain was predicted using comparative modeling methods. Different stand-alone tools and servers were used to validate and check the reliability of the predicted models, which suggested it to be a highly plausible model. The stereochemical analysis showed 92.0% residues in favorable region of Ramachandran plot. The initial physiological substrate β-hydroxybutyryl group was docked into active site of DH domain using Glide. The molecular dynamics simulations carried out for 20 ns in apo and holo states indicated the stability and accuracy of the predicted structure in solvated condition. The predicted model provided useful biochemical insights into the substrate-active site binding mechanisms. This model was then used for identifying potential FASN inhibitors using high-throughput virtual screening of the National Cancer Institute database of chemical ligands. The inhibitory efficacy of the top hit ligands was validated by performing molecular dynamics simulation for 20 ns, where in the ligand NSC71039 exhibited good enzyme inhibition characteristics and exhibited dose-dependent anticancer cytotoxicity in retinoblastoma cancer cells in vitro. PMID:27559295

  3. SitesIdentify: a protein functional site prediction tool

    Doig Andrew J

    2009-11-01

    Full Text Available Abstract Background The rate of protein structures being deposited in the Protein Data Bank surpasses the capacity to experimentally characterise them and therefore computational methods to analyse these structures have become increasingly important. Identifying the region of the protein most likely to be involved in function is useful in order to gain information about its potential role. There are many available approaches to predict functional site, but many are not made available via a publicly-accessible application. Results Here we present a functional site prediction tool (SitesIdentify, based on combining sequence conservation information with geometry-based cleft identification, that is freely available via a web-server. We have shown that SitesIdentify compares favourably to other functional site prediction tools in a comparison of seven methods on a non-redundant set of 237 enzymes with annotated active sites. Conclusion SitesIdentify is able to produce comparable accuracy in predicting functional sites to its closest available counterpart, but in addition achieves improved accuracy for proteins with few characterised homologues. SitesIdentify is available via a webserver at http://www.manchester.ac.uk/bioinformatics/sitesidentify/

  4. LRRK2 Kinase Activity and Biology are Not Uniformly Predicted by its Autophosphorylation and Cellular Phosphorylation Site Status

    April Reynolds

    2014-06-01

    Full Text Available Missense mutations in the Leucine Rich Repeat protein Kinase 2 (LRRK2 gene are the most common genetic predisposition to develop Parkinson’s disease (PD LRRK2 is a large multi-domain phosphoprotein with a GTPase domain and a serine/threonine protein kinase domain whose activity is implicated in neuronal toxicity; however the precise mechanism is unknown. LRRK2 autophosphorylates on several serine/threonine residues across the enzyme and is found constitutively phosphorylated on Ser910, Ser935, Ser955 and Ser973, which are proposed to be regulated by upstream kinases. Here we investigate the phosphoregulation at these sites by analyzing the effects of disease-associated mutations Arg1441Cys, Arg1441Gly, Ala1442Pro, Tyr1699Cys, Ile2012Thr, Gly2019Ser, and Ile2020Thr. We also studied alanine substitutions of phosphosite serines 910, 935, 955 and 973 and specific LRRK2 inhibition on autophosphorylation of LRRK2 Ser1292, Thr1491, Thr2483 and phosphorylation at the cellular sites. We found that mutants in the Roc-COR domains, including Arg1441Cys, Arg1441His, Ala1442Pro and Tyr1699Cys, can positively enhance LRRK2 kinase activity while concomitantly inducing the dephosphorylation of the cellular sites. Mutation of the cellular sites individually did not affect LRRK2 intrinsic kinase activity; however, Ser910/935/955/973Ala mutations trended toward increased kinase activity of LRRK2. Increased cAMP levels did not lead to increased LRRK2 cellular site phosphorylation, 14-3-3 binding or kinase activity. In cells, inhibition of LRRK2 kinase activity leads to dephosphorylation of Ser1292 by Calyculin A and okadaic acid sensitive phosphatases, while the cellular sites are dephosphorylated by Calyculin A sensitive phosphatases. These findings indicate that comparative analysis of both Ser1292 and Ser910/935/955/973 phosphorylation sites will provide important and distinct measures of LRRK2 kinase and biological activity in vitro and in vivo.

  5. Predicting geomagnetic activity indices

    Complete text of publication follows. Magnetically active times, e.g., Kp > 5, are notoriously difficult to predict, precisely the times when such predictions are crucial to the space weather users. Taking advantage of the routinely available solar wind measurements at Lagrangian point (L1) and nowcast Kps, Kp and Dst forecast models based on neural networks were developed with the focus on improving the forecast for active times. To satisfy different needs and operational constraints, three models were developed: (1) a model that inputs nowcast Kp and solar wind parameters and predicts Kp 1 hr ahead; (2) a model with the same input as model 1 and predicts Kp 4 hr ahead; and (3) a model that inputs only solar wind parameters and predicts Kp 1 hr ahead (the exact prediction lead time depends on the solar wind speed and the location of the solar wind monitor.) Extensive evaluations of these models and other major operational Kp forecast models show that, while the new models can predict Kps more accurately for all activities, the most dramatic improvements occur for moderate and active times. Similar Dst models were developed. Information dynamics analysis of Kp, suggests that geospace is more dominated by internal dynamics near solar minimum than near solar maximum, when it is more directly driven by external inputs, namely solar wind and interplanetary magnetic field (IMF).

  6. Predictions of Cleavability of Calpain Proteolysis by Quantitative Structure-Activity Relationship Analysis Using Newly Determined Cleavage Sites and Catalytic Efficiencies of an Oligopeptide Array.

    Shinkai-Ouchi, Fumiko; Koyama, Suguru; Ono, Yasuko; Hata, Shoji; Ojima, Koichi; Shindo, Mayumi; duVerle, David; Ueno, Mika; Kitamura, Fujiko; Doi, Naoko; Takigawa, Ichigaku; Mamitsuka, Hiroshi; Sorimachi, Hiroyuki

    2016-04-01

    Calpains are intracellular Ca(2+)-regulated cysteine proteases that are essential for various cellular functions. Mammalian conventional calpains (calpain-1 and calpain-2) modulate the structure and function of their substrates by limited proteolysis. Thus, it is critically important to determine the site(s) in proteins at which calpains cleave. However, the calpains' substrate specificity remains unclear, because the amino acid (aa) sequences around their cleavage sites are very diverse. To clarify calpains' substrate specificities, 84 20-mer oligopeptides, corresponding to P10-P10' of reported cleavage site sequences, were proteolyzed by calpains, and the catalytic efficiencies (kcat/Km) were globally determined by LC/MS. This analysis revealed 483 cleavage site sequences, including 360 novel ones. Thekcat/Kms for 119 sites ranged from 12.5-1,710 M(-1)s(-1) Although most sites were cleaved by both calpain-1 and -2 with a similarkcat/Km, sequence comparisons revealed distinct aa preferences at P9-P7/P2/P5'. The aa compositions of the novel sites were not statistically different from those of previously reported sites as a whole, suggesting calpains have a strict implicit rule for sequence specificity, and that the limited proteolysis of intact substrates is because of substrates' higher-order structures. Cleavage position frequencies indicated that longer sequences N-terminal to the cleavage site (P-sites) were preferred for proteolysis over C-terminal (P'-sites). Quantitative structure-activity relationship (QSAR) analyses using partial least-squares regression and >1,300 aa descriptors achievedkcat/Kmprediction withr= 0.834, and binary-QSAR modeling attained an 87.5% positive prediction value for 132 reported calpain cleavage sites independent of our model construction. These results outperformed previous calpain cleavage predictors, and revealed the importance of the P2, P3', and P4' sites, and P1-P2 cooperativity. Furthermore, using our binary-QSAR model

  7. Habitat composition and connectivity predicts bat presence and activity at foraging sites in a large UK conurbation.

    James D Hale

    Full Text Available BACKGROUND: Urbanization is characterized by high levels of sealed land-cover, and small, geometrically complex, fragmented land-use patches. The extent and density of urbanized land-use is increasing, with implications for habitat quality, connectivity and city ecology. Little is known about densification thresholds for urban ecosystem function, and the response of mammals, nocturnal and cryptic taxa are poorly studied in this respect. Bats (Chiroptera are sensitive to changing urban form at a species, guild and community level, so are ideal model organisms for analyses of this nature. METHODOLOGY/PRINCIPAL FINDINGS: We surveyed bats around urban ponds in the West Midlands conurbation, United Kingdom (UK. Sites were stratified between five urban land classes, representing a gradient of built land-cover at the 1 km(2 scale. Models for bat presence and activity were developed using land-cover and land-use data from multiple radii around each pond. Structural connectivity of tree networks was used as an indicator of the functional connectivity between habitats. All species were sensitive to measures of urban density. Some were also sensitive to landscape composition and structural connectivity at different spatial scales. These results represent new findings for an urban area. The activity of Pipistrellus pipistrellus (Schreber 1774 exhibited a non-linear relationship with the area of built land-cover, being much reduced beyond the threshold of ∼60% built surface. The presence of tree networks appears to mitigate the negative effects of urbanization for this species. CONCLUSIONS/SIGNIFICANCE: Our results suggest that increasing urban density negatively impacts the study species. This has implications for infill development policy, built density targets and the compact city debate. Bats were also sensitive to the composition and structure of the urban form at a range of spatial scales, with implications for land-use planning and management

  8. Prediction of proprotein convertase cleavage sites

    Duckert, Peter; Brunak, Søren; Blom, Nikolaj

    2004-01-01

    has created additional focus on proprotein processing. We have developed a method for prediction of cleavage sites for PCs based on artificial neural networks. Two different types of neural networks have been constructed: a furin-specific network based on experimental results derived from the...

  9. Computational prediction of structure, substrate binding mode, mechanism, and rate for a malaria protease with a novel type of active site.

    Bjelic, Sinisa; Aqvist, Johan

    2004-11-23

    The histo-aspartic protease (HAP) from the malaria parasite P. falciparum is one of several new promising targets for drug intervention. The enzyme possesses a novel type of active site, but its 3D structure and mechanism of action are still unknown. Here we use a combination of homology modeling, automated docking searches, and molecular dynamics/reaction free energy profile simulations to predict the enzyme structure, conformation of bound substrate, catalytic mechanism, and rate of the peptide cleavage reaction. We find that the computational tools are sufficiently reliable both for identifying substrate binding modes and for distinguishing between different possible reaction mechanisms. It is found that the favored pathway only involves direct participation by the catalytic aspartate, with the neighboring histidine providing critical stabilization (by a factor of approximately 10000) along the reaction. The calculated catalytic rate constant of about 0.1 s(-1) for a hexapeptide substrate derived from the alpha chain of human hemoglobin is in excellent agreement with experimental kinetic data for a similar peptide fragment. PMID:15544322

  10. DOE site performance assessment activities

    Information on performance assessment capabilities and activities was collected from eight DOE sites. All eight sites either currently dispose of low-level radioactive waste (LLW) or plan to dispose of LLW in the near future. A survey questionnaire was developed and sent to key individuals involved in DOE Order 5820.2A performance assessment activities at each site. The sites surveyed included: Hanford Site (Hanford), Idaho National Engineering Laboratory (INEL), Los Alamos National Laboratory (LANL), Nevada Test Site (NTS), Oak Ridge National Laboratory (ORNL), Paducah Gaseous Diffusion Plant (Paducah), Portsmouth Gaseous Diffusion Plant (Portsmouth), and Savannah River Site (SRS). The questionnaire addressed all aspects of the performance assessment process; from waste source term to dose conversion factors. This report presents the information developed from the site questionnaire and provides a comparison of site-specific performance assessment approaches, data needs, and ongoing and planned activities. All sites are engaged in completing the radioactive waste disposal facility performance assessment required by DOE Order 5820.2A. Each site has achieved various degrees of progress and have identified a set of critical needs. Within several areas, however, the sites identified common needs and questions

  11. Exploiting protein flexibility to predict the location of allosteric sites

    Panjkovich Alejandro

    2012-10-01

    Full Text Available Abstract Background Allostery is one of the most powerful and common ways of regulation of protein activity. However, for most allosteric proteins identified to date the mechanistic details of allosteric modulation are not yet well understood. Uncovering common mechanistic patterns underlying allostery would allow not only a better academic understanding of the phenomena, but it would also streamline the design of novel therapeutic solutions. This relatively unexplored therapeutic potential and the putative advantages of allosteric drugs over classical active-site inhibitors fuel the attention allosteric-drug research is receiving at present. A first step to harness the regulatory potential and versatility of allosteric sites, in the context of drug-discovery and design, would be to detect or predict their presence and location. In this article, we describe a simple computational approach, based on the effect allosteric ligands exert on protein flexibility upon binding, to predict the existence and position of allosteric sites on a given protein structure. Results By querying the literature and a recently available database of allosteric sites, we gathered 213 allosteric proteins with structural information that we further filtered into a non-redundant set of 91 proteins. We performed normal-mode analysis and observed significant changes in protein flexibility upon allosteric-ligand binding in 70% of the cases. These results agree with the current view that allosteric mechanisms are in many cases governed by changes in protein dynamics caused by ligand binding. Furthermore, we implemented an approach that achieves 65% positive predictive value in identifying allosteric sites within the set of predicted cavities of a protein (stricter parameters set, 0.22 sensitivity, by combining the current analysis on dynamics with previous results on structural conservation of allosteric sites. We also analyzed four biological examples in detail, revealing

  12. Text mining improves prediction of protein functional sites.

    Karin M Verspoor

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

  13. Combining specificity determining and conserved residues improves functional site prediction

    Gelfand Mikhail S

    2009-06-01

    Full Text Available Abstract Background Predicting the location of functionally important sites from protein sequence and/or structure is a long-standing problem in computational biology. Most current approaches make use of sequence conservation, assuming that amino acid residues conserved within a protein family are most likely to be functionally important. Most often these approaches do not consider many residues that act to define specific sub-functions within a family, or they make no distinction between residues important for function and those more relevant for maintaining structure (e.g. in the hydrophobic core. Many protein families bind and/or act on a variety of ligands, meaning that conserved residues often only bind a common ligand sub-structure or perform general catalytic activities. Results Here we present a novel method for functional site prediction based on identification of conserved positions, as well as those responsible for determining ligand specificity. We define Specificity-Determining Positions (SDPs, as those occupied by conserved residues within sub-groups of proteins in a family having a common specificity, but differ between groups, and are thus likely to account for specific recognition events. We benchmark the approach on enzyme families of known 3D structure with bound substrates, and find that in nearly all families residues predicted by SDPsite are in contact with the bound substrate, and that the addition of SDPs significantly improves functional site prediction accuracy. We apply SDPsite to various families of proteins containing known three-dimensional structures, but lacking clear functional annotations, and discusse several illustrative examples. Conclusion The results suggest a better means to predict functional details for the thousands of protein structures determined prior to a clear understanding of molecular function.

  14. Active Site Engineering in Electrocatalysis

    Verdaguer Casadevall, Arnau; Stephens, Ifan; Chorkendorff, Ib

    The overall goal of this thesis has been to design better catalysts for electrochemical reactions through a fundamental understanding of the materials at atomic scale. This has been achieved by combining electrochemical measurements with a variety of characterization techniques, often in ultra high...... under reaction conditions, which is ultimately controlled by the crystal structure of the underlying alloy.• Oxygen reduction to hydrogen peroxide has been investigated on single site catalysts, mainly alloys of noble metals with Hg. This resulted in a very special structure with isolated atoms of Pt or......, inexistent in other forms of Cu. The presence of strong CO binding sites correlates well with electrochemical activity, which paves the way for the rational development of even better electrocatalysts....

  15. High precision prediction of functional sites in protein structures.

    Ljubomir Buturovic

    Full Text Available We address the problem of assigning biological function to solved protein structures. Computational tools play a critical role in identifying potential active sites and informing screening decisions for further lab analysis. A critical parameter in the practical application of computational methods is the precision, or positive predictive value. Precision measures the level of confidence the user should have in a particular computed functional assignment. Low precision annotations lead to futile laboratory investigations and waste scarce research resources. In this paper we describe an advanced version of the protein function annotation system FEATURE, which achieved 99% precision and average recall of 95% across 20 representative functional sites. The system uses a Support Vector Machine classifier operating on the microenvironment of physicochemical features around an amino acid. We also compared performance of our method with state-of-the-art sequence-level annotator Pfam in terms of precision, recall and localization. To our knowledge, no other functional site annotator has been rigorously evaluated against these key criteria. The software and predictive models are incorporated into the WebFEATURE service at http://feature.stanford.edu/wf4.0-beta.

  16. Predicting on-site environmental impacts of municipal engineering works

    Gangolells, Marta, E-mail: marta.gangolells@upc.edu; Casals, Miquel, E-mail: miquel.casals@upc.edu; Forcada, Núria, E-mail: nuria.forcada@upc.edu; Macarulla, Marcel, E-mail: marcel.macarulla@upc.edu

    2014-01-15

    The research findings fill a gap in the body of knowledge by presenting an effective way to evaluate the significance of on-site environmental impacts of municipal engineering works prior to the construction stage. First, 42 on-site environmental impacts of municipal engineering works were identified by means of a process-oriented approach. Then, 46 indicators and their corresponding significance limits were determined on the basis of a statistical analysis of 25 new-build and remodelling municipal engineering projects. In order to ensure the objectivity of the assessment process, direct and indirect indicators were always based on quantitative data from the municipal engineering project documents. Finally, two case studies were analysed and found to illustrate the practical use of the proposed model. The model highlights the significant environmental impacts of a particular municipal engineering project prior to the construction stage. Consequently, preventive actions can be planned and implemented during on-site activities. The results of the model also allow a comparison of proposed municipal engineering projects and alternatives with respect to the overall on-site environmental impact and the absolute importance of a particular environmental aspect. These findings are useful within the framework of the environmental impact assessment process, as they help to improve the identification and evaluation of on-site environmental aspects of municipal engineering works. The findings may also be of use to construction companies that are willing to implement an environmental management system or simply wish to improve on-site environmental performance in municipal engineering projects. -- Highlights: • We present a model to predict the environmental impacts of municipal engineering works. • It highlights significant on-site environmental impacts prior to the construction stage. • Findings are useful within the environmental impact assessment process. • They also

  17. SVM-based prediction of caspase substrate cleavage sites

    Wee, Lawrence JK; Tan, Tin Wee; Ranganathan, Shoba

    2006-01-01

    Background Caspases belong to a class of cysteine proteases which function as critical effectors in apoptosis and inflammation by cleaving substrates immediately after unique sites. Prediction of such cleavage sites will complement structural and functional studies on substrates cleavage as well as discovery of new substrates. Recently, different computational methods have been developed to predict the cleavage sites of caspase substrates with varying degrees of success. As the support vector...

  18. Prediction of allosteric sites and mediating interactions through bond-to-bond propensities

    Amor, Benjamin R C; Yaliraki, Sophia N; Barahona, Mauricio

    2016-01-01

    Allosteric regulation is central to many biochemical processes. Allosteric sites provide a target to fine-tune protein activity, yet we lack computational methods to predict them. Here, we present an efficient graph-theoretical approach for identifying allosteric sites and the mediating interactions that connect them to the active site. Using an atomistic graph with edges weighted by covalent and non-covalent bond energies, we obtain a bond-to-bond propensity that quantifies the effect of instantaneous bond fluctuations propagating through the protein. We use this propensity to detect the sites and communication pathways most strongly linked to the active site, assessing their significance through quantile regression and comparison against a reference set of 100 generic proteins. We exemplify our method in detail with three well-studied allosteric proteins: caspase-1, CheY, and h-Ras, correctly predicting the location of the allosteric site and identifying key allosteric interactions. Consistent prediction of...

  19. Flood Predictions Combining Regional and Single Site Hydrometric Information

    Campos–Aranda

    2010-07-01

    Full Text Available Initially, the statistic benefit of flood predictions obtained by combining reliable regional and scarce site hydrometric data is pointed out. Then the mathematical equations for combining mean and standard deviation logarithms of regional and site data are exposed, as well as the necessary expressions for desired predictions, based on Student's t distribution. Later two numerical applications are described, the first one based in Carrizal hydrometric station located in Santiago River in Nayarit and the second one which makes use of five water gauging stations in Tempoal River in Veracruz. Finally, a conclusion is formulated pointing out the simplicity of that method and the accuracy of its predictions.

  20. The Binding Mode Prediction and Similar Ligand Potency in the Active Site of Vitamin D Receptor with QM/MM Interaction, MESP, and MD Simulation.

    Selvaraman, Nagamani; Selvam, Saravana Kumar; Muthusamy, Karthikeyan

    2016-08-01

    Non-secosteroidal ligands are well-known vitamin D receptor (VDR) agonists. In this study, we described a combined QM/MM to define the protein-ligand interaction energy a strong positive correlation in both QM-MM interaction energy and binding free energy against the biological activity. The molecular dynamics simulation study was performed, and specific interactions were extensively studied. The molecular docking results and surface analysis shed light on steric and electrostatic complementarities of these non-secosteroidal ligands to VDR. Finally, the drug likeness properties were also calculated and found within the acceptable range. The results show that bulky group substitutions in side chain decrease the VDR activity, whereas a small substitution increased it. Functional analyses of H393A and H301A mutations substantiate their roles in the VDR agonistic and antagonistic activities. Apart from the His393 and His301, two other amino acids in the hinge region viz. Ser233 and Arg270 acted as an electron donor/acceptor specific to the agonist in the distinct ligand potency. The results from this study disclose the binding mechanism of VDR agonists and structural modifications required to improve the selectivity. PMID:26945790

  1. Pripper: prediction of caspase cleavage sites from whole proteomes

    Salmi Jussi

    2010-06-01

    Full Text Available Abstract Background Caspases are a family of proteases that have central functions in programmed cell death (apoptosis and inflammation. Caspases mediate their effects through aspartate-specific cleavage of their target proteins, and at present almost 400 caspase substrates are known. There are several methods developed to predict caspase cleavage sites from individual proteins, but currently none of them can be used to predict caspase cleavage sites from multiple proteins or entire proteomes, or to use several classifiers in combination. The possibility to create a database from predicted caspase cleavage products for the whole genome could significantly aid in identifying novel caspase targets from tandem mass spectrometry based proteomic experiments. Results Three different pattern recognition classifiers were developed for predicting caspase cleavage sites from protein sequences. Evaluation of the classifiers with quality measures indicated that all of the three classifiers performed well in predicting caspase cleavage sites, and when combining different classifiers the accuracy increased further. A new tool, Pripper, was developed to utilize the classifiers and predict the caspase cut sites from an arbitrary number of input sequences. A database was constructed with the developed tool, and it was used to identify caspase target proteins from tandem mass spectrometry data from two different proteomic experiments. Both known caspase cleavage products as well as novel cleavage products were identified using the database demonstrating the usefulness of the tool. Pripper is not restricted to predicting only caspase cut sites, but it gives the possibility to scan protein sequences for any given motif(s and predict cut sites once a suitable cut site prediction model for any other protease has been developed. Pripper is freely available and can be downloaded from http://users.utu.fi/mijopi/Pripper. Conclusions We have developed Pripper, a tool for

  2. A systems biology approach to transcription factor binding site prediction.

    Xiang Zhou

    Full Text Available BACKGROUND: The elucidation of mammalian transcriptional regulatory networks holds great promise for both basic and translational research and remains one the greatest challenges to systems biology. Recent reverse engineering methods deduce regulatory interactions from large-scale mRNA expression profiles and cross-species conserved regulatory regions in DNA. Technical challenges faced by these methods include distinguishing between direct and indirect interactions, associating transcription regulators with predicted transcription factor binding sites (TFBSs, identifying non-linearly conserved binding sites across species, and providing realistic accuracy estimates. METHODOLOGY/PRINCIPAL FINDINGS: We address these challenges by closely integrating proven methods for regulatory network reverse engineering from mRNA expression data, linearly and non-linearly conserved regulatory region discovery, and TFBS evaluation and discovery. Using an extensive test set of high-likelihood interactions, which we collected in order to provide realistic prediction-accuracy estimates, we show that a careful integration of these methods leads to significant improvements in prediction accuracy. To verify our methods, we biochemically validated TFBS predictions made for both transcription factors (TFs and co-factors; we validated binding site predictions made using a known E2F1 DNA-binding motif on E2F1 predicted promoter targets, known E2F1 and JUND motifs on JUND predicted promoter targets, and a de novo discovered motif for BCL6 on BCL6 predicted promoter targets. Finally, to demonstrate accuracy of prediction using an external dataset, we showed that sites matching predicted motifs for ZNF263 are significantly enriched in recent ZNF263 ChIP-seq data. CONCLUSIONS/SIGNIFICANCE: Using an integrative framework, we were able to address technical challenges faced by state of the art network reverse engineering methods, leading to significant improvement in direct

  3. Glycosylation site prediction using ensembles of Support Vector Machine classifiers

    Silvescu Adrian

    2007-11-01

    Full Text Available Abstract Background Glycosylation is one of the most complex post-translational modifications (PTMs of proteins in eukaryotic cells. Glycosylation plays an important role in biological processes ranging from protein folding and subcellular localization, to ligand recognition and cell-cell interactions. Experimental identification of glycosylation sites is expensive and laborious. Hence, there is significant interest in the development of computational methods for reliable prediction of glycosylation sites from amino acid sequences. Results We explore machine learning methods for training classifiers to predict the amino acid residues that are likely to be glycosylated using information derived from the target amino acid residue and its sequence neighbors. We compare the performance of Support Vector Machine classifiers and ensembles of Support Vector Machine classifiers trained on a dataset of experimentally determined N-linked, O-linked, and C-linked glycosylation sites extracted from O-GlycBase version 6.00, a database of 242 proteins from several different species. The results of our experiments show that the ensembles of Support Vector Machine classifiers outperform single Support Vector Machine classifiers on the problem of predicting glycosylation sites in terms of a range of standard measures for comparing the performance of classifiers. The resulting methods have been implemented in EnsembleGly, a web server for glycosylation site prediction. Conclusion Ensembles of Support Vector Machine classifiers offer an accurate and reliable approach to automated identification of putative glycosylation sites in glycoprotein sequences.

  4. Prediction of PK-specific phosphorylation site based on information entropy

    2008-01-01

    Phosphorylation is a crucial way to control the activity of proteins in many eukaryotic organisms in vivo. Experimental methods to determine phosphorylation sites in substrates are usually restricted by the in vitro condition of enzymes and very intensive in time and labor. Although some in silico methods and web servers have been introduced for automatic detection of phosphorylation sites, sophisticated methods are still in urgent demand to further improve prediction performances. Protein primary se-quences can help predict phosphorylation sites catalyzed by different protein kinase and most com-putational approaches use a short local peptide to make prediction. However, the useful information may be lost if only the conservative residues that are not close to the phosphorylation site are consid-ered in prediction, which would hamper the prediction results. A novel prediction method named IEPP (Information-Entropy based Phosphorylation Prediction) is presented in this paper for automatic de-tection of potential phosphorylation sites. In prediction, the sites around the phosphorylation sites are selected or excluded by their entropy values. The algorithm was compared with other methods such as GSP and PPSP on the ABL, MAPK and PKA PK families. The superior prediction accuracies were ob-tained in various measurements such as sensitivity (Sn) and specificity (Sp). Furthermore, compared with some online prediction web servers on the new discovered phosphorylation sites, IEPP also yielded the best performance. IEPP is another useful computational resource for identification of PK-specific phosphorylation sites and it also has the advantages of simpleness, efficiency and con-venience.

  5. Reliable prediction of transcription factor binding sites by phylogenetic verification

    Li, Xiaoman; Zhong, Sheng; Wong, Wing H.

    2005-01-01

    We present a statistical methodology that largely improves the accuracy in computational predictions of transcription factor (TF) binding sites in eukaryote genomes. This method models the cross-species conservation of binding sites without relying on accurate sequence alignment. It can be coupled with any motif-finding algorithm that searches for overrepresented sequence motifs in individual species and can increase the accuracy of the coupled motif-finding algorithm. Because this method is ...

  6. Predicting web site audience demographics for web advertising targeting using multi-web site clickstream data

    Bock, K W; D. VAN DEN POEL; S. MANIGART

    2009-01-01

    Several recent studies have explored the virtues of behavioral targeting and personalization for online advertising. In this paper, we add to this literature by proposing a cost-effective methodology for the prediction of demographic web site visitor profiles that can be used for web advertising targeting purposes. The methodology involves the transformation of web site visitors’ clickstream patterns to a set of features and the training of Random Forest classifiers that generate predictions ...

  7. Fast dynamics perturbation analysis for prediction of protein functional sites

    Cohn Judith D

    2008-01-01

    Full Text Available Abstract Background We present a fast version of the dynamics perturbation analysis (DPA algorithm to predict functional sites in protein structures. The original DPA algorithm finds regions in proteins where interactions cause a large change in the protein conformational distribution, as measured using the relative entropy Dx. Such regions are associated with functional sites. Results The Fast DPA algorithm, which accelerates DPA calculations, is motivated by an empirical observation that Dx in a normal-modes model is highly correlated with an entropic term that only depends on the eigenvalues of the normal modes. The eigenvalues are accurately estimated using first-order perturbation theory, resulting in a N-fold reduction in the overall computational requirements of the algorithm, where N is the number of residues in the protein. The performance of the original and Fast DPA algorithms was compared using protein structures from a standard small-molecule docking test set. For nominal implementations of each algorithm, top-ranked Fast DPA predictions overlapped the true binding site 94% of the time, compared to 87% of the time for original DPA. In addition, per-protein recall statistics (fraction of binding-site residues that are among predicted residues were slightly better for Fast DPA. On the other hand, per-protein precision statistics (fraction of predicted residues that are among binding-site residues were slightly better using original DPA. Overall, the performance of Fast DPA in predicting ligand-binding-site residues was comparable to that of the original DPA algorithm. Conclusion Compared to the original DPA algorithm, the decreased run time with comparable performance makes Fast DPA well-suited for implementation on a web server and for high-throughput analysis.

  8. An Overview of the Prediction of Protein DNA-Binding Sites

    Jingna Si

    2015-03-01

    Full Text Available Interactions between proteins and DNA play an important role in many essential biological processes such as DNA replication, transcription, splicing, and repair. The identification of amino acid residues involved in DNA-binding sites is critical for understanding the mechanism of these biological activities. In the last decade, numerous computational approaches have been developed to predict protein DNA-binding sites based on protein sequence and/or structural information, which play an important role in complementing experimental strategies. At this time, approaches can be divided into three categories: sequence-based DNA-binding site prediction, structure-based DNA-binding site prediction, and homology modeling and threading. In this article, we review existing research on computational methods to predict protein DNA-binding sites, which includes data sets, various residue sequence/structural features, machine learning methods for comparison and selection, evaluation methods, performance comparison of different tools, and future directions in protein DNA-binding site prediction. In particular, we detail the meta-analysis of protein DNA-binding sites. We also propose specific implications that are likely to result in novel prediction methods, increased performance, or practical applications.

  9. Human activity recognition and prediction

    2016-01-01

    This book provides a unique view of human activity recognition, especially fine-grained human activity structure learning, human-interaction recognition, RGB-D data based action recognition, temporal decomposition, and causality learning in unconstrained human activity videos. The techniques discussed give readers tools that provide a significant improvement over existing methodologies of video content understanding by taking advantage of activity recognition. It links multiple popular research fields in computer vision, machine learning, human-centered computing, human-computer interaction, image classification, and pattern recognition. In addition, the book includes several key chapters covering multiple emerging topics in the field. Contributed by top experts and practitioners, the chapters present key topics from different angles and blend both methodology and application, composing a solid overview of the human activity recognition techniques. .

  10. Reliable prediction of transcription factor binding sites by phylogenetic verification.

    Li, Xiaoman; Zhong, Sheng; Wong, Wing H

    2005-11-22

    We present a statistical methodology that largely improves the accuracy in computational predictions of transcription factor (TF) binding sites in eukaryote genomes. This method models the cross-species conservation of binding sites without relying on accurate sequence alignment. It can be coupled with any motif-finding algorithm that searches for overrepresented sequence motifs in individual species and can increase the accuracy of the coupled motif-finding algorithm. Because this method is capable of accurately detecting TF binding sites, it also enhances our ability to predict the cis-regulatory modules. We applied this method on the published chromatin immunoprecipitation (ChIP)-chip data in Saccharomyces cerevisiae and found that its sensitivity and specificity are 9% and 14% higher than those of two recent methods. We also recovered almost all of the previously verified TF binding sites and made predictions on the cis-regulatory elements that govern the tight regulation of ribosomal protein genes in 13 eukaryote species (2 plants, 4 yeasts, 2 worms, 2 insects, and 3 mammals). These results give insights to the transcriptional regulation in eukaryotic organisms. PMID:16286651

  11. Computational Prediction of RNA-Binding Proteins and Binding Sites

    Jingna Si

    2015-11-01

    Full Text Available Proteins and RNA interaction have vital roles in many cellular processes such as protein synthesis, sequence encoding, RNA transfer, and gene regulation at the transcriptional and post-transcriptional levels. Approximately 6%–8% of all proteins are RNA-binding proteins (RBPs. Distinguishing these RBPs or their binding residues is a major aim of structural biology. Previously, a number of experimental methods were developed for the determination of protein–RNA interactions. However, these experimental methods are expensive, time-consuming, and labor-intensive. Alternatively, researchers have developed many computational approaches to predict RBPs and protein–RNA binding sites, by combining various machine learning methods and abundant sequence and/or structural features. There are three kinds of computational approaches, which are prediction from protein sequence, prediction from protein structure, and protein-RNA docking. In this paper, we review all existing studies of predictions of RNA-binding sites and RBPs and complexes, including data sets used in different approaches, sequence and structural features used in several predictors, prediction method classifications, performance comparisons, evaluation methods, and future directions.

  12. Characterization of Reuse Activities at Contaminated Sites

    Angela Vitulli; Charlotte Dougherty; Kimberly Bosworth

    2004-01-01

    Given the increased focus on reuse activity within EPA and state site cleanup programs, policy makers would benefit from looking across programs to better understand the extent and nature of reuse; examine site characteristics that influence reuse; leverage lessons learned; and coordinate reuse activities, data collection, and information management. This research paper begins to examine these issues. It reports the results of a preliminary review and analysis of available EPA and state progr...

  13. Fingerprinting differential active site constraints of ATPases

    Hacker, Stephan M.; Hardt, Norman; Buntru, Alexander; Pagliarini, Dana; Möckel, Martin; Mayer, Thomas U; Scheffner, Martin; Hauck, Christof R.; Marx, Andreas

    2013-01-01

    The free energy provided by adenosine triphosphate (ATP) hydrolysis is central to many cellular processes and, therefore, the number of enzymes utilizing ATP as a substrate is almost innumerable. Modified analogues of ATP are a valuable means to understand the biological function of ATPases. Although these enzymes have evolved towards binding to ATP, large differences in active site architectures were found. In order to systematically access the specific active site constraints of different A...

  14. SITE-DIRECTED MUTAGENESIS OF PROPOSED ACTIVE-SITE RESIDUES OF PENICILLIN-BINDING PROTEIN-5 FROM ESCHERICHIA-COLI

    VANDERLINDEN, MPG; DEHAAN, L; DIDEBERG, O; KECK, W

    1994-01-01

    Alignment of the amino acid sequence of penicillin-binding protein 5 (PBP5) with the sequences of other members of the family of active-site-serine penicillin-interacting enzymes predicted the residues playing a role in the catalytic mechanism of PBP5. Apart from the active-site (Ser(44)), Lys(47),

  15. Glycosylation site prediction using ensembles of Support Vector Machine classifiers

    Silvescu Adrian; Sinapov Jivko; Caragea Cornelia; Dobbs Drena; Honavar Vasant

    2007-01-01

    Abstract Background Glycosylation is one of the most complex post-translational modifications (PTMs) of proteins in eukaryotic cells. Glycosylation plays an important role in biological processes ranging from protein folding and subcellular localization, to ligand recognition and cell-cell interactions. Experimental identification of glycosylation sites is expensive and laborious. Hence, there is significant interest in the development of computational methods for reliable prediction of glyco...

  16. Activity Prediction: A Twitter-based Exploration

    Weerkamp, W.; Rijke, de, M.

    2012-01-01

    Social media platforms allow users to share their messages with everyone else. In microblogs, e.g., Twitter, people mostly report on what they did, they talk about current activities, and mention things they plan to do in the near future. In this paper, we propose the task of activity prediction, that is, trying to establish a set of activities that are likely to become popular at a later time. We perform a small-scale initial experiment, in which we try to predict popular activities for the ...

  17. Seismic Hazard Assessment in Site Evaluation for Nuclear Installations: Ground Motion Prediction Equations and Site Response

    The objective of this publication is to provide the state-of-the-art practice and detailed technical elements related to ground motion evaluation by ground motion prediction equations (GMPEs) and site response in the context of seismic hazard assessments as recommended in IAEA Safety Standards Series No. SSG-9, Seismic Hazards in Site Evaluation for Nuclear Installations. The publication includes the basics of GMPEs, ground motion simulation, selection and adjustment of GMPEs, site characterization, and modelling of site response in order to improve seismic hazard assessment. The text aims at delineating the most important aspects of these topics (including current practices, criticalities and open problems) within a coherent framework. In particular, attention has been devoted to filling conceptual gaps. It is written as a reference text for trained users who are responsible for planning preparatory seismic hazard analyses for siting of all nuclear installations and/or providing constraints for anti-seismic design and retrofitting of existing structures

  18. MetWAMer: eukaryotic translation initiation site prediction

    Brendel Volker

    2008-09-01

    Full Text Available Abstract Background Translation initiation site (TIS identification is an important aspect of the gene annotation process, requisite for the accurate delineation of protein sequences from transcript data. We have developed the MetWAMer package for TIS prediction in eukaryotic open reading frames of non-viral origin. MetWAMer can be used as a stand-alone, third-party tool for post-processing gene structure annotations generated by external computational programs and/or pipelines, or directly integrated into gene structure prediction software implementations. Results MetWAMer currently implements five distinct methods for TIS prediction, the most accurate of which is a routine that combines weighted, signal-based translation initiation site scores and the contrast in coding potential of sequences flanking TISs using a perceptron. Also, our program implements clustering capabilities through use of the k-medoids algorithm, thereby enabling cluster-specific TIS parameter utilization. In practice, our static weight array matrix-based indexing method for parameter set lookup can be used with good results in data sets exhibiting moderate levels of 5'-complete coverage. Conclusion We demonstrate that improvements in statistically-based models for TIS prediction can be achieved by taking the class of each potential start-methionine into account pending certain testing conditions, and that our perceptron-based model is suitable for the TIS identification task. MetWAMer represents a well-documented, extensible, and freely available software system that can be readily re-trained for differing target applications and/or extended with existing and novel TIS prediction methods, to support further research efforts in this area.

  19. Managing Siting Activities for Nuclear Power Plants

    One of the IAEA's statutory objectives is to ''seek to accelerate and enlarge the contribution of atomic energy to peace, health and prosperity throughout the world''. One way this objective is achieved is through the publication of a range of technical series. Two of these are the IAEA Nuclear Energy Series and the IAEA Safety Standards Series. According to Article III.A.6 of the IAEA Statute, the safety standards establish 'standards of safety for protection of health and minimization of danger to life and property.' The safety standards include the Safety Fundamentals, Safety Requirements and Safety Guides. These standards are written primarily in a regulatory style, and are binding on the IAEA for its own programmes. The principal users are the regulatory bodies in Member States and other national authorities. The IAEA Nuclear Energy Series comprises reports designed to encourage and assist R and D on, and application of, nuclear energy for peaceful uses. This includes practical examples to be used by owners and operators of utilities in Member States, implementing organizations, academia, and government officials, among others. This information is presented in guides, reports on technology status and advances, and best practices for peaceful uses of nuclear energy based on inputs from international experts. The IAEA Nuclear Energy Series complements the IAEA Safety Standards Series. The introduction of nuclear power brings new challenges to States - one of them being the selection of appropriates sites. It is a project that needs to begin early, be well managed, and deploy good communications with all stakeholders; including regulators. This is important, not just for those States introducing nuclear power for the first time, but for any State looking to build a new nuclear power plant. The purpose of the siting activities goes beyond choosing a suitable site and acquiring a licence. A large part of the project is about producing and maintaining a validated

  20. Efficient oxygen electrocatalysis on special active sites

    Halck, Niels Bendtsen

    cobalt incorporated in ruthenium dioxide at high overpotentials during the oxygen reduction reaction (ORR). Density functional theory calculations were used to explain this phenomenon. The special active sites concepts are used to propose a general unified approach to increase the efficiency for oxygen...

  1. Resolving the Structure of Active Sites on Platinum Catalytic Nanoparticles

    Chang, Lan Yun; Barnard, Amanda S.; Gontard, Lionel Cervera; Dunin-Borkowski, Rafal E.

    2010-01-01

    Accurate understanding of the structure of active sites is fundamentally important in predicting catalytic properties of heterogeneous nanocatalysts. We present an accurate determination of both experimental and theoretical atomic structures of surface monatomic steps on industrial platinum...... nanoparticles. This comparison reveals that the edges of nanoparticles can significantly alter the atomic positions of monatomic steps in their proximity, which can lead to substantial deviations in the catalytic properties compared with the extended surfaces....

  2. Site characterization and validation. Stage 2 - Preliminary predictions

    The Site Characterization and Validation (SCV) project is designed to assess how well we can characterize a volume of rock prior to using it as a repository. The programme of work focuses on the validation of the techniques used in site characterization. The SCV project contains 5 stages of work arranged in two 'cycles' of data-gathering, prediction, and validation. The first stage of work has included drilling of 6 boreholes (N2, N3, N4, W1, W2 and V3) and measurements of geology, fracture characteristics, stess, single borehole geophysical logging, radar, seismics and hydrogeology. The rock at the SCV site is granite with small lithological variations. Based essentially on radar and seismic results 5 'fracture zones' have been identified, named GA, GB, GC, GH and GI. They all extend acroos the entire SCV site. They aer basically in in two groups (GA, GB, GC and GH, GI). The first group are aligned N40 degree E with a dip of 35 degree to the south. The second group are aligned approximately N10 degree W dipping 60 degree E. From the stochastic analysis of the joint data it was possible to identify three main fracture orientation clusters. The orientation of two of these clusters agree roughly with orientation of the main features. Cluster B has roughly the same orientation as GH and GI, while features GA, GB and GC have an orientation similar to the more loosely defined cluster C. The orientation of the third cluster (A) is northwest with a dip to northeast. It is found that 94% of all measured hydraulic transmissivity is accounted for by 4% of the tested rock, not all of this 'concentrated' transmissivity is with the major features defined by geophysics. When the hydraulic connections across the site are examied they show that there are several welldefined zones which permit rapid transmission of hydraulic signals. These are essentially from the northeast to the southwest. (66 figs., 21 tabs., 33 refs.)

  3. Method of predicting Splice Sites based on signal interactions

    Deogun Jitender S

    2006-04-01

    Full Text Available Abstract Background Predicting and proper ranking of canonical splice sites (SSs is a challenging problem in bioinformatics and machine learning communities. Any progress in SSs recognition will lead to better understanding of splicing mechanism. We introduce several new approaches of combining a priori knowledge for improved SS detection. First, we design our new Bayesian SS sensor based on oligonucleotide counting. To further enhance prediction quality, we applied our new de novo motif detection tool MHMMotif to intronic ends and exons. We combine elements found with sensor information using Naive Bayesian Network, as implemented in our new tool SpliceScan. Results According to our tests, the Bayesian sensor outperforms the contemporary Maximum Entropy sensor for 5' SS detection. We report a number of putative Exonic (ESE and Intronic (ISE Splicing Enhancers found by MHMMotif tool. T-test statistics on mouse/rat intronic alignments indicates, that detected elements are on average more conserved as compared to other oligos, which supports our assumption of their functional importance. The tool has been shown to outperform the SpliceView, GeneSplicer, NNSplice, Genio and NetUTR tools for the test set of human genes. SpliceScan outperforms all contemporary ab initio gene structural prediction tools on the set of 5' UTR gene fragments. Conclusion Designed methods have many attractive properties, compared to existing approaches. Bayesian sensor, MHMMotif program and SpliceScan tools are freely available on our web site. Reviewers This article was reviewed by Manyuan Long, Arcady Mushegian and Mikhail Gelfand.

  4. Better estimation of protein-DNA interaction parameters improve prediction of functional sites

    O'Flanagan Ruadhan A

    2008-12-01

    Full Text Available Abstract Background Characterizing transcription factor binding motifs is a common bioinformatics task. For transcription factors with variable binding sites, we need to get many suboptimal binding sites in our training dataset to get accurate estimates of free energy penalties for deviating from the consensus DNA sequence. One procedure to do that involves a modified SELEX (Systematic Evolution of Ligands by Exponential Enrichment method designed to produce many such sequences. Results We analyzed low stringency SELEX data for E. coli Catabolic Activator Protein (CAP, and we show here that appropriate quantitative analysis improves our ability to predict in vitro affinity. To obtain large number of sequences required for this analysis we used a SELEX SAGE protocol developed by Roulet et al. The sequences obtained from here were subjected to bioinformatic analysis. The resulting bioinformatic model characterizes the sequence specificity of the protein more accurately than those sequence specificities predicted from previous analysis just by using a few known binding sites available in the literature. The consequences of this increase in accuracy for prediction of in vivo binding sites (and especially functional ones in the E. coli genome are also discussed. We measured the dissociation constants of several putative CAP binding sites by EMSA (Electrophoretic Mobility Shift Assay and compared the affinities to the bioinformatics scores provided by methods like the weight matrix method and QPMEME (Quadratic Programming Method of Energy Matrix Estimation trained on known binding sites as well as on the new sites from SELEX SAGE data. We also checked predicted genome sites for conservation in the related species S. typhimurium. We found that bioinformatics scores based on SELEX SAGE data does better in terms of prediction of physical binding energies as well as in detecting functional sites. Conclusion We think that training binding site detection

  5. Efficient oxygen electrocatalysis on special active sites

    Halck, Niels Bendtsen

    Oxygen electrocatalysis will be pivotal in future independent of fossil fuels. Renewable energy production will rely heavily on oxygen electrocatalysis as a method for storing energy from intermittent energy sources such as the wind and sun in the form of chemical bonds and to release the energy ...... electrocatalysis (ORR and OER) using organic functional groups on another class of catalysts. These consist of graphene sheets modified to have a local porphyrine site with different transition metals ions as model systems....... stored in these bonds in an eco-friendly fashion in fuel cells. This thesis explores catalysts for oxygen electrocatalysis and how carefully designed local structures on catalysts surfaces termed special active sites can influence the activity. Density functional theory has been used as a method...... throughout this thesis to understand these local structure effects and their influence on surface reactions. The concept of these special active sites is used to explain how oxygen evolution reaction (OER) catalysts can have activities beyond the limits of what was previously thought possible. The concept is...

  6. Prediction of fine-tuned promoter activity from DNA sequence

    Siwo, Geoffrey; Rider, Andrew; Tan, Asako; Pinapati, Richard; Emrich, Scott; Chawla, Nitesh; Ferdig, Michael

    2016-01-01

    The quantitative prediction of transcriptional activity of genes using promoter sequence is fundamental to the engineering of biological systems for industrial purposes and understanding the natural variation in gene expression. To catalyze the development of new algorithms for this purpose, the Dialogue on Reverse Engineering Assessment and Methods (DREAM) organized a community challenge seeking predictive models of promoter activity given normalized promoter activity data for 90 ribosomal protein promoters driving expression of a fluorescent reporter gene. By developing an unbiased modeling approach that performs an iterative search for predictive DNA sequence features using the frequencies of various k-mers, inferred DNA mechanical properties and spatial positions of promoter sequences, we achieved the best performer status in this challenge. The specific predictive features used in the model included the frequency of the nucleotide G, the length of polymeric tracts of T and TA, the frequencies of 6 distinct trinucleotides and 12 tetranucleotides, and the predicted protein deformability of the DNA sequence. Our method accurately predicted the activity of 20 natural variants of ribosomal protein promoters (Spearman correlation r = 0.73) as compared to 33 laboratory-mutated variants of the promoters (r = 0.57) in a test set that was hidden from participants. Notably, our model differed substantially from the rest in 2 main ways: i) it did not explicitly utilize transcription factor binding information implying that subtle DNA sequence features are highly associated with gene expression, and ii) it was entirely based on features extracted exclusively from the 100 bp region upstream from the translational start site demonstrating that this region encodes much of the overall promoter activity. The findings from this study have important implications for the engineering of predictable gene expression systems and the evolution of gene expression in naturally occurring

  7. Can one predict DNA Transcription Start Sites by studying bubbles?

    Van Erp, T S; Hagmann, J G; Peyrard, M

    2005-01-01

    It has been speculated that bubble formation of several base-pairs due to thermal fluctuations is indicatory for biological active sites. Recent evidence, based on experiments and molecular dynamics (MD) simulations using the Peyrard-Bishop-Dauxois model, seems to point in this direction. However, sufficiently large bubbles appear only seldom which makes an accurate calculation difficult even for minimal models. In this letter, we introduce a new method that is orders of magnitude faster than MD. Using this method we are able to show that the present evidence is unsubstantiated.

  8. Prediction of allosteric sites and mediating interactions through bond-to-bond propensities

    Amor, B. R. C.; Schaub, M. T.; Yaliraki, S. N.; Barahona, M.

    2016-01-01

    Allostery is a fundamental mechanism of biological regulation, in which binding of a molecule at a distant location affects the active site of a protein. Allosteric sites provide targets to fine-tune protein activity, yet we lack computational methodologies to predict them. Here we present an efficient graph-theoretical framework to reveal allosteric interactions (atoms and communication pathways strongly coupled to the active site) without a priori information of their location. Using an atomistic graph with energy-weighted covalent and weak bonds, we define a bond-to-bond propensity quantifying the non-local effect of instantaneous bond fluctuations propagating through the protein. Significant interactions are then identified using quantile regression. We exemplify our method with three biologically important proteins: caspase-1, CheY, and h-Ras, correctly predicting key allosteric interactions, whose significance is additionally confirmed against a reference set of 100 proteins. The almost-linear scaling of our method renders it suitable for high-throughput searches for candidate allosteric sites. PMID:27561351

  9. BET is active on Sellafield site

    Several companies, all part of BET Plant Services are carrying out work at the British Nuclear Fuels (BNFL) site at Sellafield, Cumbria, on one of the largest construction projects in Europe. The main development scheme is the THORP (Thermal Oxide Reprocessing Plant) buildings. One of the BET companies has the contract to paint the inside of the fuel storage ponds. It will also coat the surfaces of the MASWEP (Medium Active Solid Waste Encapsulation Plant) complex. Other work includes insulation and fire prevention installation. Scaffolding at the EARP (Enhanced Actinide Removal Plant) site is being provided on a common user basis so all the contractors can use the scaffolding and share the cost. Temporary office and living accommodation blocks have been provide by another BET company. (author)

  10. The next generation of transcription factor binding site prediction.

    Anthony Mathelier

    Full Text Available Finding where transcription factors (TFs bind to the DNA is of key importance to decipher gene regulation at a transcriptional level. Classically, computational prediction of TF binding sites (TFBSs is based on basic position weight matrices (PWMs which quantitatively score binding motifs based on the observed nucleotide patterns in a set of TFBSs for the corresponding TF. Such models make the strong assumption that each nucleotide participates independently in the corresponding DNA-protein interaction and do not account for flexible length motifs. We introduce transcription factor flexible models (TFFMs to represent TF binding properties. Based on hidden Markov models, TFFMs are flexible, and can model both position interdependence within TFBSs and variable length motifs within a single dedicated framework. The availability of thousands of experimentally validated DNA-TF interaction sequences from ChIP-seq allows for the generation of models that perform as well as PWMs for stereotypical TFs and can improve performance for TFs with flexible binding characteristics. We present a new graphical representation of the motifs that convey properties of position interdependence. TFFMs have been assessed on ChIP-seq data sets coming from the ENCODE project, revealing that they can perform better than both PWMs and the dinucleotide weight matrix extension in discriminating ChIP-seq from background sequences. Under the assumption that ChIP-seq signal values are correlated with the affinity of the TF-DNA binding, we find that TFFM scores correlate with ChIP-seq peak signals. Moreover, using available TF-DNA affinity measurements for the Max TF, we demonstrate that TFFMs constructed from ChIP-seq data correlate with published experimentally measured DNA-binding affinities. Finally, TFFMs allow for the straightforward computation of an integrated TF occupancy score across a sequence. These results demonstrate the capacity of TFFMs to accurately model DNA

  11. Prediction control of active power filters

    王莉娜; 罗安

    2003-01-01

    A prediction method to obtain harmonic reference for active power filter is presented. It is a new use ofthe adaptive predictive filter based on FIR. The delay inherent in digital controller is successfully compensated by u-sing the proposed method, and the computing load is not very large compared with the conventional method. Moreo-ver, no additional hardware is needed. Its DSP-based realization is also presented, which is characterized by time-va-riant rate sampling, quasi synchronous sampling, and synchronous operation among the line frequency, PWM gener-ating and sampling in A/D unit. Synchronous operation releases the limitation on PWM modulation ratio and guar-antees that the electrical noises resulting from the switching operation of IGBTs do not interfere with the sampledcurrent. The simulation and experimental results verify the satisfactory performance of the proposed method.

  12. Prediction of flow and drawdown for the site characterization and validation site in the Stripa Mine

    Geophysical and hydrologic data from a location in the Stripa Mine in Sweden, called the Site Characterization and Validation (SCV) block, has been used to create a series of models for flow through the fracture network. The models can be characterized as ''equivalent discontinuum'' models. Equivalent discontinuum models are derived starting from a specified lattice or 6 ''template''. An inverse analysis called ''Simulated Annealing'' is used to make a random search through the elements of the lattice to find a configuration that can reproduce the measured responses. Evidence at Stripa points to hydrology which is dominated by fracture zones. These have been identified and located through extensive characterization efforts. Lattice templates were arranged to lie on the fracture zones identified by Black and Olsson. The fundamental goal of this project was to build a fracture flow model based an initial data set, and use this model to make predictions of the flow behavior during a new test. Then given data from the new test, predict a second test, etc. The first data set was an interference test called C1-2. Both a two-dimensional and a three-dimensional model were annealed to the C1-2 data and use this model to predict the behavior of the Simulated Drift Experiment (SDE). The SDE measured the flow into, and drawdown due to reducing the pressure in a group of 6 parallel boreholes. Then both the C1-2 and SDE data were used to predict the flow into and drawdown due to an excavation, the Validation Drift (VD), made through the boreholes. Finally, all the data was used to predict the hydrologic response to opening another hole, T1

  13. Prediction of flow and drawdown for the site characterization and validation site in the Stripa mine

    Geophysical and hydrologic data from a location in the Stripa mine in Sweden, called the Site Characterization and Validation (SCV) block, has been used to create a series of models for flow through the fracture network. The models can be characterized as 'equivalent discontinuum' models. Equivalent discontinuum models are derived starting from a specified lattice or 'template'. An inverse analysis called 'simulated annealing' is used to make a random search through the elements of the lattice to find a configuration that can reproduce the measured responses. Evidence at Stripa points to hydrology which is dominated by fracture zones. These have been identified and located through extensive characterization efforts. Lattice templates were arranged to lie on the fracture zones identified by Black and Olsson. The fundamental goal of this project was to build a fracture flow model based on an initial data set, and use this model to make predictions of the flow behavior during a new test. Then given data from the new test, predict a second test, etc. The first data set was an interference test called C1-2. Both a two-dimensional and a three-dimensional model were annealed to the C1-2 data and use this model to predict the behavior of the Simulated Drift Experiment (SDE). The SDE measured the flow into, and drawdown due to reducing the pressure in a group of 6 parallel boreholes. Then both the C1-2 and SDE data were used to predict the flow into a drawdown due to an excavation, the Validation Drift (VD), made through the boreholes. Finally, all the data was used to predict the hydrologic response to opening another hole, T1. Annealing to the C1-2 test gave an excellent prediction of the SDE. The VD effects were dominated by near-field physics that were not predictable. However, the calculations and measurements could be used to postulate that a dramatic decrease in hydraulic conductivity near the drift was due to degassing of nitrogen as the inflowing water was

  14. CERAPP: Collaborative estrogen receptor activity prediction project

    Mansouri, Kamel; Abdelaziz, Ahmed; Rybacka, Aleksandra;

    2016-01-01

    Background: Humans are exposed to thousands of man-made chemicals in the environment. Some chemicals mimic natural endocrine hormones and, thus, have the potential to be endocrine disruptors. Most of these chemicals have never been tested for their ability to interact with the estrogen receptor (ER......). Risk assessors need tools to prioritize chemicals for evaluation in costly in vivo tests, for instance, within the U.S. EPA Endocrine Disruptor Screening Program. oBjectives: We describe a large-scale modeling project called CERAPP (Collaborative Estrogen Receptor Activity Prediction Project) and...

  15. Establishing a predictive maintenance program at the Hanford Site

    This document contains information about a new Predictive Maintenance Program being developed and implemented at the Hanford Reservation. Details of the document include: background on persons developing the program, history of predictive maintenance, implementation of new program, engineering task analysis, network development and new software, issues to be resolved, benefits expected, and appendix gives information about the symposium from which this paper is based

  16. Computational prediction of cAMP receptor protein (CRP) binding sites in cyanobacterial genomes

    Xu, Minli; Su, Zhengchang

    2009-01-01

    Background Cyclic AMP receptor protein (CRP), also known as catabolite gene activator protein (CAP), is an important transcriptional regulator widely distributed in many bacteria. The biological processes under the regulation of CRP are highly diverse among different groups of bacterial species. Elucidation of CRP regulons in cyanobacteria will further our understanding of the physiology and ecology of this important group of microorganisms. Previously, CRP has been experimentally studied in only two cyanobacterial strains: Synechocystis sp. PCC 6803 and Anabaena sp. PCC 7120; therefore, a systematic genome-scale study of the potential CRP target genes and binding sites in cyanobacterial genomes is urgently needed. Results We have predicted and analyzed the CRP binding sites and regulons in 12 sequenced cyanobacterial genomes using a highly effective cis-regulatory binding site scanning algorithm. Our results show that cyanobacterial CRP binding sites are very similar to those in E. coli; however, the regulons are very different from that of E. coli. Furthermore, CRP regulons in different cyanobacterial species/ecotypes are also highly diversified, ranging from photosynthesis, carbon fixation and nitrogen assimilation, to chemotaxis and signal transduction. In addition, our prediction indicates that crp genes in modern cyanobacteria are likely inherited from a common ancestral gene in their last common ancestor, and have adapted various cellular functions in different environments, while some cyanobacteria lost their crp genes as well as CRP binding sites during the course of evolution. Conclusion The CRP regulons in cyanobacteria are highly diversified, probably as a result of divergent evolution to adapt to various ecological niches. Cyanobacterial CRPs may function as lineage-specific regulators participating in various cellular processes, and are important in some lineages. However, they are dispensable in some other lineages. The loss of CRPs in these species

  17. Computational prediction of cAMP receptor protein (CRP binding sites in cyanobacterial genomes

    Su Zhengchang

    2009-01-01

    Full Text Available Abstract Background Cyclic AMP receptor protein (CRP, also known as catabolite gene activator protein (CAP, is an important transcriptional regulator widely distributed in many bacteria. The biological processes under the regulation of CRP are highly diverse among different groups of bacterial species. Elucidation of CRP regulons in cyanobacteria will further our understanding of the physiology and ecology of this important group of microorganisms. Previously, CRP has been experimentally studied in only two cyanobacterial strains: Synechocystis sp. PCC 6803 and Anabaena sp. PCC 7120; therefore, a systematic genome-scale study of the potential CRP target genes and binding sites in cyanobacterial genomes is urgently needed. Results We have predicted and analyzed the CRP binding sites and regulons in 12 sequenced cyanobacterial genomes using a highly effective cis-regulatory binding site scanning algorithm. Our results show that cyanobacterial CRP binding sites are very similar to those in E. coli; however, the regulons are very different from that of E. coli. Furthermore, CRP regulons in different cyanobacterial species/ecotypes are also highly diversified, ranging from photosynthesis, carbon fixation and nitrogen assimilation, to chemotaxis and signal transduction. In addition, our prediction indicates that crp genes in modern cyanobacteria are likely inherited from a common ancestral gene in their last common ancestor, and have adapted various cellular functions in different environments, while some cyanobacteria lost their crp genes as well as CRP binding sites during the course of evolution. Conclusion The CRP regulons in cyanobacteria are highly diversified, probably as a result of divergent evolution to adapt to various ecological niches. Cyanobacterial CRPs may function as lineage-specific regulators participating in various cellular processes, and are important in some lineages. However, they are dispensable in some other lineages. The

  18. Study the active site of flavonoid applying radiation chemistry

    Flavonoid are a large and important class of naturally occurring, low molecular weight benzo-γ-pyrone derivatives which are reported to have a myriad of biological activities, but the study on the active sites of flavonoids is still ambiguous. In this paper, rutin, quercetin and baicalin have been selected as model compounds. It is well known that rutin is used in inhibiting arteriosclerosis and baicalin is antibacterial and antiviral. They have similar basic structure, but their medicinal properties are so different, why? As most flavonoids contain carbonyl group, which can capture electron effectively, we predict that flavonoids can capture electron to form radical anion. The formation of anion radical may have influence on the mitochondrial electron transport chain. The difference in the ability of forming anion radical may cause the difference in their medicinal effects. (author)

  19. Predicting on-site environmental impacts of municipal engineering works

    Gangolells Solanellas, Marta; Casals Casanova, Miquel; Forcada Matheu, Núria; Macarulla Martí, Marcel

    2014-01-01

    The research findings fill a gap in the body of knowledge by presenting an effective way to evaluate the significance of on-site environmental impacts of municipal engineering works prior to the construction stage. First, 42 on-site environmental impacts of municipal engineering works were identified by means of a process-oriented approach. Then, 46 indicators and their corresponding significance limits were determined on the basis of a statistical analysis of 25 new-build and remodelling mun...

  20. SSFinder: High Throughput CRISPR-Cas Target Sites Prediction Tool

    Santosh Kumar Upadhyay; Shailesh Sharma

    2014-01-01

    Clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated protein (Cas) system facilitates targeted genome editing in organisms. Despite high demand of this system, finding a reliable tool for the determination of specific target sites in large genomic data remained challenging. Here, we report SSFinder, a python script to perform high throughput detection of specific target sites in large nucleotide datasets. The SSFinder is a user-friendly tool, compatible wit...

  1. Predicting functional sites with an automated algorithm suitable for heterogeneous datasets

    Livesay Dennis R

    2005-05-01

    Full Text Available Abstract Background In a previous report (La et al., Proteins, 2005, we have demonstrated that the identification of phylogenetic motifs, protein sequence fragments conserving the overall familial phylogeny, represent a promising approach for sequence/function annotation. Across a structurally and functionally heterogeneous dataset, phylogenetic motifs have been demonstrated to correspond to a wide variety of functional site archetypes, including those defined by surface loops, active site clefts, and less exposed regions. However, in our original demonstration of the technique, phylogenetic motif identification is dependent upon a manually determined similarity threshold, prohibiting large-scale application of the technique. Results In this report, we present an algorithmic approach that determines thresholds without human subjectivity. The approach relies on significant raw data preprocessing to improve signal detection. Subsequently, Partition Around Medoids Clustering (PAMC of the similarity scores assesses sequence fragments where functional annotation remains in question. The accuracy of the approach is confirmed through comparisons to our previous (manual results and structural analyses. Triosephosphate isomerase and arginyl-tRNA synthetase are discussed as exemplar cases. A quantitative functional site prediction assessment algorithm indicates that the phylogenetic motif predictions, which require sequence information only, are nearly as good as those from evolutionary trace methods that do incorporate structure. Conclusion The automated threshold detection algorithm has been incorporated into MINER, our web-based phylogenetic motif identification server. MINER is freely available on the web at http://www.pmap.csupomona.edu/MINER/. Pre-calculated functional site predictions of the COG database and an implementation of the threshold detection algorithm, in the R statistical language, can also be accessed at the website.

  2. A Mechanism-Based Model for the Prediction of the Metabolic Sites of Steroids Mediated by Cytochrome P450 3A4

    Zi-Ru Dai

    2015-06-01

    Full Text Available Early prediction of xenobiotic metabolism is essential for drug discovery and development. As the most important human drug-metabolizing enzyme, cytochrome P450 3A4 has a large active cavity and metabolizes a broad spectrum of substrates. The poor substrate specificity of CYP3A4 makes it a huge challenge to predict the metabolic site(s on its substrates. This study aimed to develop a mechanism-based prediction model based on two key parameters, including the binding conformation and the reaction activity of ligands, which could reveal the process of real metabolic reaction(s and the site(s of modification. The newly established model was applied to predict the metabolic site(s of steroids; a class of CYP3A4-preferred substrates. 38 steroids and 12 non-steroids were randomly divided into training and test sets. Two major metabolic reactions, including aliphatic hydroxylation and N-dealkylation, were involved in this study. At least one of the top three predicted metabolic sites was validated by the experimental data. The overall accuracy for the training and test were 82.14% and 86.36%, respectively. In summary, a mechanism-based prediction model was established for the first time, which could be used to predict the metabolic site(s of CYP3A4 on steroids with high predictive accuracy.

  3. Promoter proximal polyadenylation sites reduce transcription activity

    Andersen, Pia Kjølhede; Lykke-Andersen, Søren; Jensen, Torben Heick

    2012-01-01

    transcription requires promoter proximity, as demonstrated using artificial constructs and supported by a genome-wide data set. Importantly, transcription down-regulation can be recapitulated in a gene context devoid of splice sites by placing a functional bona fide pA site/transcription terminator within ∼500...

  4. SSFinder: High Throughput CRISPR-Cas Target Sites Prediction Tool

    Santosh Kumar Upadhyay

    2014-01-01

    Full Text Available Clustered regularly interspaced short palindromic repeats (CRISPR and CRISPR-associated protein (Cas system facilitates targeted genome editing in organisms. Despite high demand of this system, finding a reliable tool for the determination of specific target sites in large genomic data remained challenging. Here, we report SSFinder, a python script to perform high throughput detection of specific target sites in large nucleotide datasets. The SSFinder is a user-friendly tool, compatible with Windows, Mac OS, and Linux operating systems, and freely available online.

  5. Prediction for human transcription start site using diversity measure with quadratic discriminant

    Lu, Jun; Luo, LiaoFu

    2008-01-01

    The accurate identification of promoter regions and transcription start sites is a challenge to the construction of human transcription regulation networks. Thus, an efficient prediction method based on theoretical formulation is necessary for this purpose. We used the method of increment diversity with quadratic discriminant analysis (IDQD) to predict transcription start sites (TSS). The method produced sensitivity and positive predictive value of more than 65% with positives to negatives ra...

  6. Activities on the site during construction phase

    A survey is given of the work done on the site from site-opening till turn over of the plant to the client. After a short introduction to time schedules, manpower on site, site facilities and civil work and constructions, the commissioning and trial operation phase is discussed in detail. This phase begins with finishing the assembly of individual systems and components and ends with the trial operation and the acceptance measurement. During this period the subsystems are started-up in a useful sequence, first from cold, then from hot conditions and are finally operated as a total with nuclear energy. The single steps are: a) commissioning of indivudal systems; b) hot functional test 1 (without fuels) c) baseline inspection at the reactor pressure vessel; d) hot functional test 2 (with fuels); e) preparation for first criticality; f) postcriticality test program; g) trial operation: h) acceptance measurement. (HP)

  7. Virtual Screening and Prediction of Site of Metabolism for Cytochrome P450 1A2 Ligands

    Vasanthanathan, P.; Hritz, Jozef; Taboureau, Olivier; Olsen, Lars; Jørgensen, F.S.; Vermeulen, N.P.E.; Oostenbrink, C.

    2009-01-01

    questions have been addressed: 1. Binding orientations and conformations were successfully predicted for various substrates. 2. A virtual screen was performed with satisfying enrichment rates. 3. A classification of individual compounds into active and inactive was performed. It was found that while docking...... can be used successfully to address the first two questions, it seems to be more difficult to perform the classification. Different scoring functions were included, and the well-characterized water molecule in the active site was included in various ways. Results are compared to experimental data and...... earlier classification data using machine learning methods. The possibilities and limitations of using structure-based drug design tools for cytochrome P450 1A2 come to light and are discussed....

  8. Crystallographic B factor of critical residues at enzyme active site

    张海龙; 宋时英; 林政炯

    1999-01-01

    Thirty-seven sets of crystallographic enzyme data were selected from Protein Data Bank (PDB, 1995). The average temperature factors (B) of the critical residues at the active site and the whole molecule of those enzymes were calculated respectively. The statistical results showed that the critical residues at the active site of most of the enzymes had lower B factors than did the whole molecules, indicating that in the crystalline state the critical residues at the active site of the natural enzymes possess more stable conformation than do the whole molecules. The flexibility of the active site during the unfolding by denaturing was also discussed.

  9. DAPPLE 2: a Tool for the Homology-Based Prediction of Post-Translational Modification Sites.

    Trost, Brett; Maleki, Farhad; Kusalik, Anthony; Napper, Scott

    2016-08-01

    The post-translational modification of proteins is critical for regulating their function. Although many post-translational modification sites have been experimentally determined, particularly in certain model organisms, experimental knowledge of these sites is severely lacking for many species. Thus, it is important to be able to predict sites of post-translational modification in such species. Previously, we described DAPPLE, a tool that facilitates the homology-based prediction of one particular post-translational modification, phosphorylation, in an organism of interest using known phosphorylation sites from other organisms. Here, we describe DAPPLE 2, which expands and improves upon DAPPLE in three major ways. First, it predicts sites for many post-translational modifications (20 different types) using data from several sources (15 online databases). Second, it has the ability to make predictions approximately 2-7 times faster than DAPPLE depending on the database size and the organism of interest. Third, it simplifies and accelerates the process of selecting predicted sites of interest by categorizing them based on gene ontology terms, keywords, and signaling pathways. We show that DAPPLE 2 can successfully predict known human post-translational modification sites using, as input, known sites from species that are either closely (e.g., mouse) or distantly (e.g., yeast) related to humans. DAPPLE 2 can be accessed at http://saphire.usask.ca/saphire/dapple2 . PMID:27367363

  10. A computational approach for prediction of donor splice sites with improved accuracy.

    Meher, Prabina Kumar; Sahu, Tanmaya Kumar; Rao, A R; Wahi, S D

    2016-09-01

    Identification of splice sites is important due to their key role in predicting the exon-intron structure of protein coding genes. Though several approaches have been developed for the prediction of splice sites, further improvement in the prediction accuracy will help predict gene structure more accurately. This paper presents a computational approach for prediction of donor splice sites with higher accuracy. In this approach, true and false splice sites were first encoded into numeric vectors and then used as input in artificial neural network (ANN), support vector machine (SVM) and random forest (RF) for prediction. ANN and SVM were found to perform equally and better than RF, while tested on HS3D and NN269 datasets. Further, the performance of ANN, SVM and RF were analyzed by using an independent test set of 50 genes and found that the prediction accuracy of ANN was higher than that of SVM and RF. All the predictors achieved higher accuracy while compared with the existing methods like NNsplice, MEM, MDD, WMM, MM1, FSPLICE, GeneID and ASSP, using the independent test set. We have also developed an online prediction server (PreDOSS) available at http://cabgrid.res.in:8080/predoss, for prediction of donor splice sites using the proposed approach. PMID:27302911

  11. Prediction of protein hydration sites from sequence by modular neural networks

    Ehrlich, L.; Reczko, M.; Bohr, Henrik; Wade, R.C.

    1998-01-01

    separate neural networks. These predictions are used as input together with protein sequences for networks predicting hydration of residues, backbone atoms and sidechains. These networks are teined with protein crystal structures. The prediction of hydration is improved by adding information on secondary......The hydration properties of a protein are important determinants of its structure and function. Here, modular neural networks are employed to predict ordered hydration sites using protein sequence information. First, secondary structure and solvent accessibility are predicted from sequence with two...... using the actual values. The inclusion of property information allows a smaller squence window to be used in the networks to predict hydration. It has a greater impact on the accuracy of hydration site prediction for backbone atoms than for sidechains and for non-polar than polar residues. The networks...

  12. Conserved Functional Motifs and Homology Modeling to Predict Hidden Moonlighting Functional Sites

    Wong, Aloysius Tze

    2015-06-09

    Moonlighting functional centers within proteins can provide them with hitherto unrecognized functions. Here, we review how hidden moonlighting functional centers, which we define as binding sites that have catalytic activity or regulate protein function in a novel manner, can be identified using targeted bioinformatic searches. Functional motifs used in such searches include amino acid residues that are conserved across species and many of which have been assigned functional roles based on experimental evidence. Molecules that were identified in this manner seeking cyclic mononucleotide cyclases in plants are used as examples. The strength of this computational approach is enhanced when good homology models can be developed to test the functionality of the predicted centers in silico, which, in turn, increases confidence in the ability of the identified candidates to perform the predicted functions. Computational characterization of moonlighting functional centers is not diagnostic for catalysis but serves as a rapid screening method, and highlights testable targets from a potentially large pool of candidates for subsequent in vitro and in vivo experiments required to confirm the functionality of the predicted moonlighting centers.

  13. Conserved functional motifs and homology modelling to predict hidden moonlighting functional sites

    Helen R Irving

    2015-06-01

    Full Text Available Moonlighting functional centers within proteins can provide them with hitherto unrecognized functions. Here we review how hidden moonlighting functional centers which we define as binding sites that have catalytic activity or regulate protein function in a novel manner, can be identified using targeted bioinformatic searches. Functional motifs used in such searches include amino acid residues that are conserved across species and many of which have been assigned functional roles based on experimental evidence. Molecules that were identified in this manner seeking cyclic mononucleotide cyclases in plants are used as examples. The strength of this computational approach is enhanced when good homology models can be developed to test the functionality of the predicted centers in silico which in turn, increases confidence in the ability of the identified candidates to perform the predicted functions. Computational characterization of moonlighting functional centers is not diagnostic for catalysis but serves as a rapid screening method, and highlights testable targets from a potentially large pool of candidates for subsequent in vitro and in vivo experiments required to confirm the functionality of the predicted moonlighting centers.

  14. Safety Oversight of Decommissioning Activities at DOE Nuclear Sites

    The Defense Nuclear Facilities Safety Board (Board) is an independent federal agency established by Congress in 1988 to provide nuclear safety oversight of activities at U.S. Department of Energy (DOE) defense nuclear facilities. The activities under the Board's jurisdiction include the design, construction, startup, operation, and decommissioning of defense nuclear facilities at DOE sites. This paper reviews the Board's safety oversight of decommissioning activities at DOE sites, identifies the safety problems observed, and discusses Board initiatives to improve the safety of decommissioning activities at DOE sites. The decommissioning of former defense nuclear facilities has reduced the risk of radioactive material contamination and exposure to the public and site workers. In general, efforts to perform decommissioning work at DOE defense nuclear sites have been successful, and contractors performing decommissioning work have a good safety record. Decommissioning activities have recently been completed at sites identified for closure, including the Rocky Flats Environmental Technology Site, the Fernald Closure Project, and the Miamisburg Closure Project (the Mound site). The Rocky Flats and Fernald sites, which produced plutonium parts and uranium materials for defense needs (respectively), have been turned into wildlife refuges. The Mound site, which performed R and D activities on nuclear materials, has been converted into an industrial and technology park called the Mound Advanced Technology Center. The DOE Office of Legacy Management is responsible for the long term stewardship of these former EM sites. The Board has reviewed many decommissioning activities, and noted that there are valuable lessons learned that can benefit both DOE and the contractor. As part of its ongoing safety oversight responsibilities, the Board and its staff will continue to review the safety of DOE and contractor decommissioning activities at DOE defense nuclear sites

  15. The balance of flexibility and rigidity in the active site residues of hen egg white lysozyme

    Qi Jian-Xun; Jiang Fan

    2011-01-01

    The crystallographic temperature factors (B factor) of individual atoms contain important information about the thermal motion of the atoms in a macromolecule. Previously the theory of flexibility of active site has been established based on the observation that the enzyme activity is sensitive to low concentration denaturing agents. It has been found that the loss of enzyme activity occurs well before the disruption of the three-dimensional structural scaffold of the enzyme. To test the theory of conformational flexibility of enzyme active site, crystal structures were perturbed by soaking in low concentration guanidine hydrochloride solutions. It was found that many lysozyme crystals tested could still diffract until the concentration of guanidine hydrochloride reached 3 M. It was also found that the B factors averaged over individually collected data sets were more accurate. Thus it suggested that accurate measurement of crystal temperature factors could be achieved for medium-high or even medium resolution crystals by averaging over multiple data sets. Furthermore, we found that the correctly predicted active sites included not only the more flexible residues, but also some more rigid residues. Both the flexible and the rigid residues in the active site played an important role in forming the active site residue network, covering the majority of the substrate binding residues. Therefore, this experimental prediction method may be useful for characterizing the binding site and the function of a protein, such as drug targeting.

  16. Savannah River Site prioritization of transition activities

    Effective management of SRS conversion from primarily a production facility to other missions (or Decontamination and Decommissioning (D ampersand D)) requires a systematic and consistent method of prioritizing the transition activities. This report discusses the design of a prioritizing method developed to achieve systematic and consistent methods of prioritizing these activities

  17. Savannah River Site prioritization of transition activities

    Finley, R.H.

    1993-11-01

    Effective management of SRS conversion from primarily a production facility to other missions (or Decontamination and Decommissioning (D&D)) requires a systematic and consistent method of prioritizing the transition activities. This report discusses the design of a prioritizing method developed to achieve systematic and consistent methods of prioritizing these activities.

  18. Prediction, conservation analysis, and structural characterization of mammalian mucin-type O-glycosylation sites

    Julenius, Karin; Mølgaard, Anne; Gupta, Ramneek;

    2005-01-01

    experimentally investigated with regard to glycosylation status. From O-GLYCBASE a total of 86 mammalian proteins experimentally investigated for in vivo O-GalNAc sites were extracted. Mammalian protein homolog comparisons showed that a glycosylated serine or threonine is less likely to be precisely conserved...... than a nonglycosylated one. The Protein Data Bank was analyzed for structural information, and 12 glycosylated structures were obtained. All positive sites were found in coil or turn regions. A method for predicting the location for mucin-type glycosylation sites was trained using a neural network...... approach. The best overall network used as input amino acid composition, averaged surface accessibility predictions together with substitution matrix profile encoding of the sequence. To improve prediction on isolated (single) sites, networks were trained on isolated sites only. The final method combines...

  19. Prediction, conservation analysis, and structural characterization of mammalian mucin-type O-glycosylation sites

    Julenius, Karin; Mølgaard, Anne; Gupta, Ramneek;

    2004-01-01

    experimentally investigated with regard to glycosylation status. From O-GLYCBASE a total of 86 mammalian proteins experimentally investigated for in vivo O-GalNAc sites were extracted. Mammalian protein homolog comparisons showed that a glycosylated serine or threonine is less likely to be precisely conserved...... than a nonglycosylated one. The Protein Data Bank was analyzed for structural information, and 12 glycosylated structures were obtained. All positive sites were found in coil or turn regions. A method for predicting the location for mucin-type glycosylation sites was trained using a neural network...... approach. The best overall network used as input amino acid composition, averaged surface accessibility predictions together with substitution matrix profile encoding of the sequence. To improve prediction on isolated (single) sites, networks were trained on isolated sites only. The final method combines...

  20. The Built Environment Predicts Observed Physical Activity

    Kelly, Cheryl; Wilson, Jeffrey S.; Schootman, Mario; Clennin, Morgan; Baker, Elizabeth A.; Miller, Douglas K.

    2014-01-01

    Background: In order to improve our understanding of the relationship between the built environment and physical activity, it is important to identify associations between specific geographic characteristics and physical activity behaviors. Purpose: Examine relationships between observed physical activity behavior and measures of the built environment collected on 291 street segments in Indianapolis and St. Louis. Methods: Street segments were selected using a stratified geographic samp...

  1. PROSPER: an integrated feature-based tool for predicting protease substrate cleavage sites.

    Jiangning Song

    Full Text Available The ability to catalytically cleave protein substrates after synthesis is fundamental for all forms of life. Accordingly, site-specific proteolysis is one of the most important post-translational modifications. The key to understanding the physiological role of a protease is to identify its natural substrate(s. Knowledge of the substrate specificity of a protease can dramatically improve our ability to predict its target protein substrates, but this information must be utilized in an effective manner in order to efficiently identify protein substrates by in silico approaches. To address this problem, we present PROSPER, an integrated feature-based server for in silico identification of protease substrates and their cleavage sites for twenty-four different proteases. PROSPER utilizes established specificity information for these proteases (derived from the MEROPS database with a machine learning approach to predict protease cleavage sites by using different, but complementary sequence and structure characteristics. Features used by PROSPER include local amino acid sequence profile, predicted secondary structure, solvent accessibility and predicted native disorder. Thus, for proteases with known amino acid specificity, PROSPER provides a convenient, pre-prepared tool for use in identifying protein substrates for the enzymes. Systematic prediction analysis for the twenty-four proteases thus far included in the database revealed that the features we have included in the tool strongly improve performance in terms of cleavage site prediction, as evidenced by their contribution to performance improvement in terms of identifying known cleavage sites in substrates for these enzymes. In comparison with two state-of-the-art prediction tools, PoPS and SitePrediction, PROSPER achieves greater accuracy and coverage. To our knowledge, PROSPER is the first comprehensive server capable of predicting cleavage sites of multiple proteases within a single substrate

  2. A Data Mining Approach for the Prediction of Hepatitis C Virus protease Cleavage Sites

    Ahmed mohamed samir ali gamal eldin

    2011-12-01

    Full Text Available Summary: Several papers have been published about the prediction of hepatitis C virus (HCV polyprotein cleavage sites, using symbolic and non-symbolic machine learning techniques. The published papers achieved different Levels of prediction accuracy. the achieved results depends on the used technique and the availability of adequate and accurate HCV polyprotein sequences with known cleavage sites. We tried here to achieve more accurate prediction results, and more Informative knowledge about the HCV protein cleavage sites using Decision tree algorithm. There are several factors that can affect the overall prediction accuracy. One of the most important factors is the availably of acceptable and accurate HCV polyproteins sequences with known cleavage sites. We collected latest accurate data sets to build the prediction model. Also we collected another dataset for the model testing. Motivation: Hepatitis C virus is a global health problem affecting a significant portion of the world’s population. The World Health Organization estimated that in1999; 170 million hepatitis C virus (HCV carriers were present worldwide, with 3 to 4 million new cases per year. Several approaches have been performed to analyze HCV life cycle to find out the important factors of the viral replication process. HCV polyprotein processing by the viral protease has a vital role in the virus replication. The prediction of HCV protease cleavage sites can help the biologists in the design of suitable viral inhibitors. Results: The ease to use and to understand of the decision tree enabled us to create simple prediction model. We used here the latest accurate viral datasets. Decision tree achieved here acceptable prediction accuracy results. Also it generated informative knowledge about the cleavage process itself. These results can help the researchers in the development of effective viral inhibitors. Using decision tree to predict HCV protein cleavage sites achieved high

  3. Stock Price Change Rate Prediction by Utilizing Social Network Activities

    Shangkun Deng; Takashi Mitsubuchi; Akito Sakurai

    2014-01-01

    Predicting stock price change rates for providing valuable information to investors is a challenging task. Individual participants may express their opinions in social network service (SNS) before or after their transactions in the market; we hypothesize that stock price change rate is better predicted by a function of social network service activities and technical indicators than by a function of just stock market activities. The hypothesis is tested by accuracy of predictions as well as pe...

  4. NetPhosYeast: prediction of protein phosphorylation sites in yeast

    Ingrell, C.R.; Miller, Martin Lee; Jensen, O.N.; Blom, Nikolaj

    2007-01-01

    We here present a neural network-based method for the prediction of protein phosphorylation sites in yeast-an important model organism for basic research. Existing protein phosphorylation site predictors are primarily based on mammalian data and show reduced sensitivity on yeast phosphorylation...... sites compared to those in humans, suggesting the need for an yeast-specific phosphorylation site predictor. NetPhosYeast achieves a correlation coefficient close to 0.75 with a sensitivity of 0.84 and specificity of 0.90 and outperforms existing predictors in the identification of phosphorylation sites...... in yeast....

  5. Ensemble approach combining multiple methods improves human transcription start site prediction.

    Dineen, David G

    2010-01-01

    The computational prediction of transcription start sites is an important unsolved problem. Some recent progress has been made, but many promoters, particularly those not associated with CpG islands, are still difficult to locate using current methods. These methods use different features and training sets, along with a variety of machine learning techniques and result in different prediction sets.

  6. Activity, exposure rate and spectrum prediction with Java programming

    In order to envision the radiation exposure during Neutron Activation Analysis (NAA) experiments, a software called Activity Predictor is developed using JavaTM programming language. The Activity Predictor calculates activities, exposure rates and gamma spectra of activated samples for NAA experiments performed at Radiation Science and Engineering Center (RSEC), Penn State Breazeale Reactor (PSBR). The calculation procedure for predictions involves both analytical and Monte Carlo methods. The Activity Predictor software is validated with a series of activation experiments. It has been found that Activity Predictor software calculates the activities and exposure rates precisely. The software also predicts gamma spectrum for each measurement. The predicted spectra agreed partially with measured spectra. The error in net photo peak areas varied from 4.8 to 51.29%, which is considered to be due to simplistic modeling, statistical fluctuations and unknown contaminants in the samples. (author)

  7. Active Power Filter Using Predicted Current Control

    Xiaojie, Y.; Pivoňka, P.; Valouch, Viktor

    2001-01-01

    Roč. 46, č. 1 (2001), s. 41-50. ISSN 0001-7043 Institutional research plan: CEZ:AV0Z2057903 Keywords : active power filter * control strategy Subject RIV: JA - Electronics ; Optoelectronics, Electrical Engineering

  8. Analysis and prediction of gene splice sites in four Aspergillus genomes

    Wang, Kai; Ussery, David; Brunak, Søren

    2009-01-01

    , splice site prediction program called NetAspGene, for the genus Aspergillus. Gene sequences from Aspergillus fumigatus, the most common mould pathogen, were used to build and test our model. Compared to many animals and plants, Aspergillus contains smaller introns; thus we have applied a larger window...... better splice site prediction than other available tools. NetAspGene will be very helpful for the study in Aspergillus splice sites and especially in alternative splicing. A webpage for NetAspGene is publicly available at http://www.cbs.dtu.dk/services/NetAspGene....

  9. Using site-specific soil samples as a substitution for improved hydrological and nonpoint source predictions.

    Chen, Lei; Wang, Guobo; Zhong, Yucen; Zhao, Xin; Shen, Zhenyao

    2016-08-01

    Soil databases are one of the most important inputs for watershed models, and the quality of soil properties affects how well a model performs. The objectives of this study were to (1) quantify the sensitivity of model outputs to soil properties and to (2) use site-specific soil properties as a substitution for more accurate hydrological and nonpoint source (H/NPS) predictions. Soil samples were collected from a typical mountainous watershed in China, and the impacts of soil sample parameters on H/NPS predictions were quantified using the Soil and Water Assessment Tool (SWAT). The most sensitive parameters related to predicting flow, sediment, and total phosphorus (TP) mainly were the soil hydrological, the channel erosion processes, and the initial soil chemical environment, respectively. When the site-specific soil properties were used, the uncertainties (coefficient of variation) related to predicting the hydrology, sediment and TP decreased by 75∼80 %, 75∼84 %, and 46∼61 %, respectively. Based on changes in the Nash-Sutcliff coefficient, the model performance improved by 4.9 and 19.45 % for the hydrological and sediment model, accordingly. However, site-specific soil properties did not contribute to better TP predictions because of the high spatial variability of the soil P concentrations across the large watershed. Thus, although site-specific soil samples can be used to obtain more accurate H/NPS predictions, more sampling sites are required to apply this method in large watersheds. PMID:27146539

  10. Discrete fracture modelling for the Stripa site characterization and validation drift inflow predictions

    Groundwater flow through three-dimensional networks of discrete fractures was modeled to predict the flux into a fifty meter long drift, as part of the site characterization and validation project conducted during phase 3 of the Stripa project. Predictions were made on the basis of a site scale discrete fracture conceptual model developed by synthesis of geological, geophysical, and hydrological site characterization data. Individual fractures were treated as stochastic features, described by probability distributions of geometric and hydrologic properties. Fractures were divided into three populations: Fractures within fracture zones near the drift, non-fracture zone fractures near the drift, and fractures in fracture zones over 20 meters from the drift. Fractures outside fracture zones are not modelled beyond 20 meters from the drift. Both data analysis and flow predictions were produced using the FracMan discrete fracture modelling package. Probabilistic flow predictions were produced in seven formats specified by the Stripa task force on fracture flow modelling. (au)

  11. RNA:(guanine-N2 methyltransferases RsmC/RsmD and their homologs revisited – bioinformatic analysis and prediction of the active site based on the uncharacterized Mj0882 protein structure

    Rychlewski Leszek

    2002-04-01

    Full Text Available Abstract Background Escherichia coli guanine-N2 (m2G methyltransferases (MTases RsmC and RsmD modify nucleosides G1207 and G966 of 16S rRNA. They possess a common MTase domain in the C-terminus and a variable region in the N-terminus. Their C-terminal domain is related to the YbiN family of hypothetical MTases, but nothing is known about the structure or function of the N-terminal domain. Results Using a combination of sequence database searches and fold recognition methods it has been demonstrated that the N-termini of RsmC and RsmD are related to each other and that they represent a "degenerated" version of the C-terminal MTase domain. Novel members of the YbiN family from Archaea and Eukaryota were also indentified. It is inferred that YbiN and both domains of RsmC and RsmD are closely related to a family of putative MTases from Gram-positive bacteria and Archaea, typified by the Mj0882 protein from M. jannaschii (1dus in PDB. Based on the results of sequence analysis and structure prediction, the residues involved in cofactor binding, target recognition and catalysis were identified, and the mechanism of the guanine-N2 methyltransfer reaction was proposed. Conclusions Using the known Mj0882 structure, a comprehensive analysis of sequence-structure-function relationships in the family of genuine and putative m2G MTases was performed. The results provide novel insight into the mechanism of m2G methylation and will serve as a platform for experimental analysis of numerous uncharacterized N-MTases.

  12. Predicting mining activity with parallel genetic algorithms

    Talaie, S.; Leigh, R.; Louis, S.J.; Raines, G.L.

    2005-01-01

    We explore several different techniques in our quest to improve the overall model performance of a genetic algorithm calibrated probabilistic cellular automata. We use the Kappa statistic to measure correlation between ground truth data and data predicted by the model. Within the genetic algorithm, we introduce a new evaluation function sensitive to spatial correctness and we explore the idea of evolving different rule parameters for different subregions of the land. We reduce the time required to run a simulation from 6 hours to 10 minutes by parallelizing the code and employing a 10-node cluster. Our empirical results suggest that using the spatially sensitive evaluation function does indeed improve the performance of the model and our preliminary results also show that evolving different rule parameters for different regions tends to improve overall model performance. Copyright 2005 ACM.

  13. The Surface Groups and Active Site of Fibrous Mineral Materials

    DONG Fa-qin; WAN Pu; FENG Qi-ming; SONG Gong-bao; PENG Tong-jiang; LI Ping; LI Guo-wu

    2004-01-01

    The exposed and transformed groups of fibrous brucite,wollastonite,chrysotile asbestos,sepiolite,palygorskite,clinoptilolite,crocidolite and diatomaceous earth mineral materials are analyzed by IR spectra after acid and alikali etching,strong mechanical and polarity molecular interaction.The results show the active sites concentrate on the ends in stick mineral materials and on the defect or hole edge in pipe mineral materials.The inside active site of mineral materials plays a main role in small molecular substance.The shape of minerals influence their distribution and density of active site.The strong mechanical impulsion and weak chemical force change the active site feature of minerals,the powder process enables minerals exposed more surface group and more combined types.The surface processing with the small polarity molecular or the brand of middle molecular may produce ionation and new coordinate bond,and change the active properties and level of original mineral materials.

  14. FunFOLDQA: a quality assessment tool for protein-ligand binding site residue predictions.

    Daniel B Roche

    Full Text Available The estimation of prediction quality is important because without quality measures, it is difficult to determine the usefulness of a prediction. Currently, methods for ligand binding site residue predictions are assessed in the function prediction category of the biennial Critical Assessment of Techniques for Protein Structure Prediction (CASP experiment, utilizing the Matthews Correlation Coefficient (MCC and Binding-site Distance Test (BDT metrics. However, the assessment of ligand binding site predictions using such metrics requires the availability of solved structures with bound ligands. Thus, we have developed a ligand binding site quality assessment tool, FunFOLDQA, which utilizes protein feature analysis to predict ligand binding site quality prior to the experimental solution of the protein structures and their ligand interactions. The FunFOLDQA feature scores were combined using: simple linear combinations, multiple linear regression and a neural network. The neural network produced significantly better results for correlations to both the MCC and BDT scores, according to Kendall's τ, Spearman's ρ and Pearson's r correlation coefficients, when tested on both the CASP8 and CASP9 datasets. The neural network also produced the largest Area Under the Curve score (AUC when Receiver Operator Characteristic (ROC analysis was undertaken for the CASP8 dataset. Furthermore, the FunFOLDQA algorithm incorporating the neural network, is shown to add value to FunFOLD, when both methods are employed in combination. This results in a statistically significant improvement over all of the best server methods, the FunFOLD method (6.43%, and one of the top manual groups (FN293 tested on the CASP8 dataset. The FunFOLDQA method was also found to be competitive with the top server methods when tested on the CASP9 dataset. To the best of our knowledge, FunFOLDQA is the first attempt to develop a method that can be used to assess ligand binding site

  15. TarPmiR: a new approach for microRNA target site prediction

    Ding, Jun; Li, Xiaoman; Hu, Haiyan

    2016-01-01

    Motivation: The identification of microRNA (miRNA) target sites is fundamentally important for studying gene regulation. There are dozens of computational methods available for miRNA target site prediction. Despite their existence, we still cannot reliably identify miRNA target sites, partially due to our limited understanding of the characteristics of miRNA target sites. The recently published CLASH (crosslinking ligation and sequencing of hybrids) data provide an unprecedented opportunity to study the characteristics of miRNA target sites and improve miRNA target site prediction methods. Results: Applying four different machine learning approaches to the CLASH data, we identified seven new features of miRNA target sites. Combining these new features with those commonly used by existing miRNA target prediction algorithms, we developed an approach called TarPmiR for miRNA target site prediction. Testing on two human and one mouse non-CLASH datasets, we showed that TarPmiR predicted more than 74.2% of true miRNA target sites in each dataset. Compared with three existing approaches, we demonstrated that TarPmiR is superior to these existing approaches in terms of better recall and better precision. Availability and Implementation: The TarPmiR software is freely available at http://hulab.ucf.edu/research/projects/miRNA/TarPmiR/. Contacts: haihu@cs.ucf.edu or xiaoman@mail.ucf.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27207945

  16. The active site behaviour of electrochemically synthesised gold nanomaterials.

    Plowman, Blake J; O'Mullane, Anthony P; Bhargava, Suresh K

    2011-01-01

    Even though gold is the noblest of metals, a weak chemisorber and is regarded as being quite inert, it demonstrates significant electrocatalytic activity in its nanostructured form. It is demonstrated here that nanostructured and even evaporated thin films of gold are covered with active sites which are responsible for such activity. The identification of these sites is demonstrated with conventional electrochemical techniques such as cyclic voltammetry as well as a large amplitude Fourier transformed alternating current (FT-ac) method under acidic and alkaline conditions. The latter technique is beneficial in determining if an electrode process is either Faradaic or capacitive in nature. The observed behaviour is analogous to that observed for activated gold electrodes whose surfaces have been severely disrupted by cathodic polarisation in the hydrogen evolution region. It is shown that significant electrochemical oxidation responses occur at discrete potential values well below that for the formation of the compact monolayer oxide of bulk gold and are attributed to the facile oxidation of surface active sites. Several electrocatalytic reactions are explored in which the onset potential is determined by the presence of such sites on the surface. Significantly, the facile oxidation of active sites is used to drive the electroless deposition of metals such as platinum, palladium and silver from their aqueous salts on the surface of gold nanostructures. The resultant surface decoration of gold with secondary metal nanoparticles not only indicates regions on the surface which are rich in active sites but also provides a method to form interesting bimetallic surfaces. PMID:22455038

  17. Nicotinamide Cofactors Suppress Active-Site Labeling of Aldehyde Dehydrogenases.

    Stiti, Naim; Chandrasekar, Balakumaran; Strubl, Laura; Mohammed, Shabaz; Bartels, Dorothea; van der Hoorn, Renier A L

    2016-06-17

    Active site labeling by (re)activity-based probes is a powerful chemical proteomic tool to globally map active sites in native proteomes without using substrates. Active site labeling is usually taken as a readout for the active state of the enzyme because labeling reflects the availability and reactivity of active sites, which are hallmarks for enzyme activities. Here, we show that this relationship holds tightly, but we also reveal an important exception to this rule. Labeling of Arabidopsis ALDH3H1 with a chloroacetamide probe occurs at the catalytic Cys, and labeling is suppressed upon nitrosylation and oxidation, and upon treatment with other Cys modifiers. These experiments display a consistent and strong correlation between active site labeling and enzymatic activity. Surprisingly, however, labeling is suppressed by the cofactor NAD(+), and this property is shared with other members of the ALDH superfamily and also detected for unrelated GAPDH enzymes with an unrelated hydantoin-based probe in crude extracts of plant cell cultures. Suppression requires cofactor binding to its binding pocket. Labeling is also suppressed by ALDH modulators that bind at the substrate entrance tunnel, confirming that labeling occurs through the substrate-binding cavity. Our data indicate that cofactor binding adjusts the catalytic Cys into a conformation that reduces the reactivity toward chloroacetamide probes. PMID:26990764

  18. Comparison of Different Ranking Methods in Protein-Ligand Binding Site Prediction

    Gao, Jun; Liu, Qi; Kang, Hong; Cao, Zhiwei; Zhu, Ruixin

    2012-01-01

    In recent years, although many ligand-binding site prediction methods have been developed, there has still been a great demand to improve the prediction accuracy and compare different prediction algorithms to evaluate their performances. In this work, in order to improve the performance of the protein-ligand binding site prediction method presented in our former study, a comparison of different binding site ranking lists was studied. Four kinds of properties, i.e., pocket size, distance from the protein centroid, sequence conservation and the number of hydrophobic residues, have been chosen as the corresponding ranking criterion respectively. Our studies show that the sequence conservation information helps to rank the real pockets with the most successful accuracy compared to others. At the same time, the pocket size and the distance of binding site from the protein centroid are also found to be helpful. In addition, a multi-view ranking aggregation method, which combines the information among those four properties, was further applied in our study. The results show that a better performance can be achieved by the aggregation of the complementary properties in the prediction of ligand-binding sites. PMID:22942732

  19. Using Proximity to Predict Activity in Social Networks

    Lerman, Kristina; Intagorn, Suradej; Kang, Jeon-Hyung; Ghosh, Rumi

    2011-01-01

    The structure of a social network contains information useful for predicting its evolution. Nodes that are "close" in some sense are more likely to become linked in the future than more distant nodes. We show that structural information can also help predict node activity. We use proximity to capture the degree to which two nodes are "close" to each other in the network. In addition to standard proximity metrics used in the link prediction task, such as neighborhood overlap, we introduce new ...

  20. Regression applied to protein binding site prediction and comparison with classification

    Gala Jean-Luc

    2009-09-01

    Full Text Available Abstract Background The structural genomics centers provide hundreds of protein structures of unknown function. Therefore, developing methods enabling the determination of a protein function automatically is imperative. The determination of a protein function can be achieved by studying the network of its physical interactions. In this context, identifying a potential binding site between proteins is of primary interest. In the literature, methods for predicting a potential binding site location generally are based on classification tools. The aim of this paper is to show that regression tools are more efficient than classification tools for patches based binding site predictors. For this purpose, we developed a patches based binding site localization method usable with either regression or classification tools. Results We compared predictive performances of regression tools with performances of machine learning classifiers. Using leave-one-out cross-validation, we showed that regression tools provide better predictions than classification ones. Among regression tools, Multilayer Perceptron ranked highest in the quality of predictions. We compared also the predictive performance of our patches based method using Multilayer Perceptron with the performance of three other methods usable through a web server. Our method performed similarly to the other methods. Conclusion Regression is more efficient than classification when applied to our binding site localization method. When it is possible, using regression instead of classification for other existing binding site predictors will probably improve results. Furthermore, the method presented in this work is flexible because the size of the predicted binding site is adjustable. This adaptability is useful when either false positive or negative rates have to be limited.

  1. Fluorescence energy transfer studies on the active site of papain

    Henes, Jill B.; Briggs, Martha S.; Sligar, Stephen G.; Fruton, Joseph S.

    1980-01-01

    Measurements have been performed of the excited-state lifetimes and fluorescence yields of papain tryptophan units when acyl derivatives of Phe-glycinal are bound at the active site of the enzyme. The enhancement of tryptophan fluorescence in complexes of papain with the acetyl or benzyloxycarbonyl derivatives is not stereospecific with respect to the configuration of the phenylalanyl residue, and the L and D isomers are equally effective as active-site-directed inhibitors of papain action. E...

  2. Key messages from active CO2 storage sites

    Wildenborg, T.; Wollenweber, J. [TNO, Princetonlaan 6, 3584 CB Utrecht (Netherlands); Chadwick, A. [BGS, Environmental Science Centre, Keyworth, Nottingham, NG12 5GG (United Kingdom); Deflandre, J.P. [IFP Energies nouvelles, 1-4 avenue de Bois Preau, 92852 Rueil-Malmaison (France); Eiken, O. [Statoil Research Centre, Rotvoll, Arkitekt Ebbells vei 10, 7005 Trondheim (Norway); Mathieson, A. [BP, Alternative Energy, Chertsey Road, Sunbury on Thames (United Kingdom); Metcalfe, R. [QUINTESSA, The Hub, 14 Station Road, Henley-on-Thames, Oxfordshire (United Kingdom); Schmidt Hattenberger, C. [GFZ German Research Centre for Geosciences, Centre for CO2Storage, Potsdam (Germany)

    2013-07-01

    An extensive programme of modelling, monitoring and verification activities was deployed at a set of active storage sites worldwide including Sleipner, In Salah, Ketzin, Weyburn, K12-B and Snoehvit (EU CO2ReMoVe project). All investigated storage sites were well managed and did not have a negative impact on humans or the environment. Time-lapse seismic and pressure monitoring are key in verifying the deep subsurface performance of the storage sites. Evidence gathered during the site characterisation and operational phases is key to handover responsibility of the storage site to governmental authorities after injection has definitely ceased, which is the focus of the follow-up EU project CO2CARE.

  3. Klipperaas study site. Scope of activities and main results

    During the period from 1977 - 1986 SKB (Swedish Nuclear Fuel and Waste Management Co.) performed surface and borehole investigations of 14 study sites for the purpose of assessing their suitability for a repository of spent nuclear fuel. The next phase in the SKB site selection rpogramme will be to perform detailed characterisation, including characterization from shafts and/or tunnels, of two or three sites. The detailed investigations will continue over several years to provide all the data needed for a licensing application to build a repository. Such an application is foreseen to be given to the authorities around the year 2003. It is presently not clear if any of the study sites will be selected as a site for detailed characterization. Other sites with geological and/or socio-economical characteristics judged more favorable may very well be the ones selected. However, as a part of the background documentation needed for the site selection studies to come, summary reports will be prepared for most study sites. These reports will include scope of activities, main results, uncertainties and need of complementary investigations. This report concern the Klipperaas study site. The main topics are the scope of activities, geologic model, geohydrological model, groundwater chemistry, assessment of solute transport, and rock mechanics

  4. Ensemble Prediction and Uncertainty Quantification of the Propagation of Weak Seismic Pulses with Minimal Site Characterization

    Vecherin, S.; Ketcham, S.; Parker, M.; Picucci, J.

    2015-12-01

    To make a prediction for the propagation of seismic pulses, one needs to specify physical properties and subsurface ground structure of the site. This information is frequently unknown or estimated with significant uncertainty. We developed a methodology for the ensemble prediction of the propagation of weak seismic pulses for short ranges. The ranges of interest are 10-100 of meters, and the pulse bandwidth is up to 200 Hz. Instead of specifying specific values for viscoelastic site properties, the methodology operates with probability distribution functions of the inputs. This yields ensemble realizations of the pulse at specified locations, where mean, median, and maximum likelihood predictions can be made, and confidence intervals are estimated. Starting with the site's Vs30, the methodology creates an ensemble of plausible vertically stratified Vs profiles for the site. The number and thickness of the layers are modeled using inhomogeneous Poisson process, and the Vs values in the layers are modeled by Gaussian correlated process. The Poisson expectation rate and Vs correlation between adjacent layers take into account layers depth and thickness, and are specific for a site class, as defined by the Federal Emergency Management Agency (FEMA). High-fidelity three-dimension thin layer method (TLM) is used to yield an ensemble of frequency response functions. Comparison with experiments revealed that measured signals are not always within the predicted ensemble. Variance-based global sensitivity analysis has shown that the most significant parameter in the TLM for the prediction of the pulse energy is the shear quality factor, Qs. Some strategies how to account for significant uncertainty in this parameter and to improve accuracy of the ensemble predictions for a specific site are investigated and discussed.

  5. Predicting evolutionary site variability from structure in viral proteins: buriedness, flexibility, and design

    Shahmoradi, Amir; Spielman, Stephanie J; Jackson, Eleisha L; Dawson, Eric T; Meyer, Austin G; Wilke, Claus O

    2014-01-01

    Several recent works have shown that protein structure can predict site-specific evolutionary sequence variation. In particular, sites that are buried and/or have many contacts with other sites in a structure have been shown to evolve more slowly, on average, than surface sites with few contacts. Here, we present a comprehensive study of the extent to which numerous structural properties can predict sequence variation. The structural properties we considered include buriedness (relative solvent accessibility and contact number), structural flexibility (B factors, root-mean-square fluctuations, and variation in dihedral angles), and variability in designed structures. We obtained structural flexibility measures both from molecular dynamics simulations performed on 9 non-homologous viral protein structures and from variation in homologous variants of those proteins, where available. We obtained measures of variability in designed structures from flexible-backbone design in the Rosetta software. We found that mo...

  6. [Spatial distribution prediction of surface soil Pb in a battery contaminated site].

    Liu, Geng; Niu, Jun-Jie; Zhang, Chao; Zhao, Xin; Guo, Guan-Lin

    2014-12-01

    In order to enhance the reliability of risk estimation and to improve the accuracy of pollution scope determination in a battery contaminated site with the soil characteristic pollutant Pb, four spatial interpolation models, including Combination Prediction Model (OK(LG) + TIN), kriging model (OK(BC)), Inverse Distance Weighting model (IDW), and Spline model were employed to compare their effects on the spatial distribution and pollution assessment of soil Pb. The results showed that Pb concentration varied significantly and the data was severely skewed. The variation coefficient of the site was higher in the local region. OK(LG) + TIN was found to be more accurate than the other three models in predicting the actual pollution situations of the contaminated site. The prediction accuracy of other models was lower, due to the effect of the principle of different models and datum feature. The interpolation results of OK(BC), IDW and Spline could not reflect the detailed characteristics of seriously contaminated areas, and were not suitable for mapping and spatial distribution prediction of soil Pb in this site. This study gives great contributions and provides useful references for defining the remediation boundary and making remediation decision of contaminated sites. PMID:25826945

  7. GPS-SNO: computational prediction of protein S-nitrosylation sites with a modified GPS algorithm.

    Yu Xue

    Full Text Available As one of the most important and ubiquitous post-translational modifications (PTMs of proteins, S-nitrosylation plays important roles in a variety of biological processes, including the regulation of cellular dynamics and plasticity. Identification of S-nitrosylated substrates with their exact sites is crucial for understanding the molecular mechanisms of S-nitrosylation. In contrast with labor-intensive and time-consuming experimental approaches, prediction of S-nitrosylation sites using computational methods could provide convenience and increased speed. In this work, we developed a novel software of GPS-SNO 1.0 for the prediction of S-nitrosylation sites. We greatly improved our previously developed algorithm and released the GPS 3.0 algorithm for GPS-SNO. By comparison, the prediction performance of GPS 3.0 algorithm was better than other methods, with an accuracy of 75.80%, a sensitivity of 53.57% and a specificity of 80.14%. As an application of GPS-SNO 1.0, we predicted putative S-nitrosylation sites for hundreds of potentially S-nitrosylated substrates for which the exact S-nitrosylation sites had not been experimentally determined. In this regard, GPS-SNO 1.0 should prove to be a useful tool for experimentalists. The online service and local packages of GPS-SNO were implemented in JAVA and are freely available at: http://sno.biocuckoo.org/.

  8. Prediction of transcription regulatory sites in Archaea by a comparative genomic approach.

    Gelfand, M S; Koonin, E V; Mironov, A A

    2000-02-01

    Intragenomic and intergenomic comparisons of upstream nucleotide sequences of archaeal genes were performed with the goal of predicting transcription regulatory sites (operators) and identifying likely regulons. Learning sets for the detection of regulatory sites were constructed using the available experimental data on archaeal transcription regulation or by analogy with known bacterial regulons, and further analysis was performed using iterative profile searches. The information content of the candidate signals detected by this method is insufficient for reliable predictions to be made. Therefore, this approach has to be complemented by examination of evolutionary conservation in different archaeal genomes. This combined strategy resulted in the prediction of a conserved heat shock regulon in all euryarchaea, a nitrogen fixation regulon in the methanogens Methanococcus jannaschii and Methanobacterium thermoautotrophicum and an aromatic amino acid regulon in M.thermoautotrophicum. Unexpectedly, the heat shock regulatory site was detected not only for genes that encode known chaperone proteins but also for archaeal histone genes. This suggests a possible function for archaeal histones in stress-related changes in DNA condensation. In addition, comparative analysis of the genomes of three Pyrococcus species resulted in the prediction of their purine metabolism and transport regulon. The results demonstrate the feasibility of prediction of at least some transcription regulatory sites by comparing poorly characterized prokaryotic genomes, particularly when several closely related genome sequences are available. PMID:10637320

  9. Prediction of transcription regulatory sites in Archaea by a comparative genomic approach

    Gelfand, M S; Koonin, E.V.; Mironov, A. A.

    2000-01-01

    Intragenomic and intergenomic comparisons of upstream nucleotide sequences of archaeal genes were performed with the goal of predicting transcription regulatory sites (operators) and identifying likely regulons. Learning sets for the detection of regulatory sites were constructed using the available experimental data on archaeal transcription regulation or by analogy with known bacterial regulons, and further analysis was performed using iterative profile searches. The information content of ...

  10. Predicting the Mutating Distribution at Antigenic Sites of the Influenza Virus

    Hongyang Xu; Yiyan Yang; Shuning Wang; Ruixin Zhu; Tianyi Qiu; Jingxuan Qiu; Qingchen Zhang; Li Jin; Yungang He; Kailin Tang; Zhiwei Cao

    2016-01-01

    Mutations of the influenza virus lead to antigenic changes that cause recurrent epidemics and vaccine resistance. Preventive measures would benefit greatly from the ability to predict the potential distribution of new antigenic sites in future strains. By leveraging the extensive historical records of HA sequences for 90 years, we designed a computational model to simulate the dynamic evolution of antigenic sites in A/H1N1. With templates of antigenic sequences, the model can effectively pred...

  11. Establishing a predictive maintenance (PdM) program at the Hanford Site

    The production reactors have been shut down for some time. But for the rest of the site, there is currently about 16,000 people engaged in a multi-billion dollar effort to safely process wastes which have been stored at the site since the 1940's. This effort also includes demolition of some older facilities and environmental restoration of much of the site. This is expected to take approximately 30 to 40 years. The concept of a site-wide predictive maintenance (PdM) program began to form in early 1993. Several informal studies showed that the stand alone predictive maintenance groups which had prevailed on site to date were less than 15% effective at trending equipment conditions and predicting failures. To improve the effectiveness of PdM within the company, an engineering analysis by Rick Winslow confirmed that utilization of software networking technology which was now available would significantly overcome many of these built in handicaps. A site-wide predictive maintenance network would make PdM technology accessible to all of the areas and facilities at the site regardless of geographical distances and company division lines. Site resident vibration experts can easily be located and provide consultations on the network. However, it was recognized that strong leadership and management skills would be required within each of the two organizations for effective implementation. To start this process, a letter of understanding and agreement between the facilities and Tank Farm divisions was drafted and endorsed by company management. The agreement assigned the primary responsibility of acquiring the network software and licensee to the Tank Farms division. The acquisition and installation of the network server would be the responsibility of the facilities division. This paper describes the rest of the network development and implementation process

  12. PREDICTION OF ANTIGENIC AND BINDING SITES OF NEUROTOXIN 23 OF SCORPION (LYCHASMUCRONACTUS SP.)

    Bharati K Thosare; Ingale, Arun G

    2015-01-01

    Identification of antigenic and binding site of protein is highly desirable for the design of vaccines and immunodiagnostics. The present exercise deals with a prediction of antigenic as well as binding sites of neurotoxin 23 of Lychasmucronactus. This species of scorpion having diverse molecules of toxic peptide, the peptide neurotoxin 23 is 96 amino acids long of which 23 to 96 specifically code for neurotoxin. The total of 27 such different ligand binding residue were identifie...

  13. Dashboard applications to monitor experiment activities at sites

    Andreeva, Julia; Belforte, Stefano; Boehm, Max; Casajus, Adrian; Flix, Josep; Gaidioz, Benjamin; Grigoras, Costin; Kokoszkiewicz, Lukasz; Lanciotti, Elisa; Rocha, Ricardo; Saiz, Pablo; Santinelli, Roberto; Sidorova, Irina; Sciabà, Andrea; Tsaregorodtsev, Andrei

    2010-04-01

    In the framework of a distributed computing environment, such as WLCG, monitoring has a key role in order to keep under control activities going on in sites located in different countries and involving people based in many different sites. To be able to cope with such a large scale heterogeneous infrastructure, it is necessary to have monitoring tools providing a complete and reliable view of the overall performance of the sites. Moreover, the structure of a monitoring system critically depends on the object to monitor and on the users it is addressed to. In this article we will describe two different monitoring systems both aimed to monitor activities and services provided in the WLCG framework, but designed in order to meet the requirements of different users: Site Status Board has an overall view of the services available in all the sites supporting an experiment, whereas Siteview provides a complete view of all the activities going on at a site, for all the experiments supported by the site.

  14. Dashboard applications to monitor experiment activities at sites

    Andreeva, J; Boehm, M; Casajus, A; Flix, J; Gaidioz, B; Grigoras, C; Kokoszkiewicz, L; Lanciotti, E; Rocha, R; Saiz, P; Santinelli, R; Sidorova, I; Sciabà, A; Tsaregorodtsev, A

    2010-01-01

    In the framework of a distributed computing environment, such as WLCG, monitoring has a key role in order to keep under control activities going on in sites located in different countries and involving people based in many different sites. To be able to cope with such a large scale heterogeneous infrastructure, it is necessary to have monitoring tools providing a complete and reliable view of the overall performance of the sites. Moreover, the structure of a monitoring system critically depends on the object to monitor and on the users it is addressed to. In this article we will describe two different monitoring systems both aimed to monitor activities and services provided in the WLCG framework, but designed in order to meet the requirements of different users: Site Status Board has an overall view of the services available in all the sites supporting an experiment, whereas Siteview provides a complete view of all the activities going on at a site, for all the experiments supported by the site.

  15. Dashboard applications to monitor experiment activities at sites

    In the framework of a distributed computing environment, such as WLCG, monitoring has a key role in order to keep under control activities going on in sites located in different countries and involving people based in many different sites. To be able to cope with such a large scale heterogeneous infrastructure, it is necessary to have monitoring tools providing a complete and reliable view of the overall performance of the sites. Moreover, the structure of a monitoring system critically depends on the object to monitor and on the users it is addressed to. In this article we will describe two different monitoring systems both aimed to monitor activities and services provided in the WLCG framework, but designed in order to meet the requirements of different users: Site Status Board has an overall view of the services available in all the sites supporting an experiment, whereas Siteview provides a complete view of all the activities going on at a site, for all the experiments supported by the site.

  16. SITE-94. Discrete-feature modelling of the Aespoe Site: 3. Predictions of hydrogeological parameters for performance assessment

    Geier, J.E. [Golder Associates AB, Uppsala (Sweden)

    1996-12-01

    A 3-dimensional, discrete-feature hydrological model is developed. The model integrates structural and hydrologic data for the Aespoe site, on scales ranging from semi regional fracture zones to individual fractures in the vicinity of the nuclear waste canisters. Predicted parameters for the near field include fracture spacing, fracture aperture, and Darcy velocity at each of forty canister deposition holes. Parameters for the far field include discharge location, Darcy velocity, effective longitudinal dispersion coefficient and head gradient, flow porosity, and flow wetted surface, for each canister source that discharges to the biosphere. Results are presented in the form of statistical summaries for a total of 42 calculation cases, which treat a set of 25 model variants in various combinations. The variants for the SITE-94 Reference Case model address conceptual and parametric uncertainty related to the site-scale hydrogeologic model and its properties, the fracture network within the repository, effective semi regional boundary conditions for the model, and the disturbed-rock zone around the repository tunnels and shafts. Two calculation cases simulate hydrologic conditions that are predicted to occur during future glacial episodes. 30 refs.

  17. SITE-94. Discrete-feature modelling of the Aespoe Site: 3. Predictions of hydrogeological parameters for performance assessment

    A 3-dimensional, discrete-feature hydrological model is developed. The model integrates structural and hydrologic data for the Aespoe site, on scales ranging from semi regional fracture zones to individual fractures in the vicinity of the nuclear waste canisters. Predicted parameters for the near field include fracture spacing, fracture aperture, and Darcy velocity at each of forty canister deposition holes. Parameters for the far field include discharge location, Darcy velocity, effective longitudinal dispersion coefficient and head gradient, flow porosity, and flow wetted surface, for each canister source that discharges to the biosphere. Results are presented in the form of statistical summaries for a total of 42 calculation cases, which treat a set of 25 model variants in various combinations. The variants for the SITE-94 Reference Case model address conceptual and parametric uncertainty related to the site-scale hydrogeologic model and its properties, the fracture network within the repository, effective semi regional boundary conditions for the model, and the disturbed-rock zone around the repository tunnels and shafts. Two calculation cases simulate hydrologic conditions that are predicted to occur during future glacial episodes. 30 refs

  18. Comparison of reactive transport model predictions for natural attenuation processes occurring at chlorinated solvent contaminated site

    Chiu, H. M.; Tsai, C. H.; Lai, K. H.; Chen, J. S.

    2014-12-01

    Prediction of an analytical model and numerical model, namely BIOCLOR and HYDRODEOCHEM, for a test scenario involving the natural attenuations of dissolved solvent at chlorinated contaminated site are compared. Two models make same predictions for PCE, TCE and DCE and considerable different predictions for VC and ETH for the case of all species having identical retardation factors. Significant discrepancies between two models are observed for all species when retardation coefficients are considered to be different for all species. These differences can be attributed to the basic assumption that all the species have the same retardation factors embedded in BIOCHLOR.

  19. Predicting Physical Activity in Arab American School Children

    Martin, Jeffrey J.; McCaughtry, Nate; Shen, Bo

    2008-01-01

    Theoretically grounded research on the determinants of Arab American children's physical activity is virtually nonexistent. Thus, the purpose of our investigation was to evaluate the ability of the theory of planned behavior (TPB) and social cognitive theory (SCT) to predict Arab American children's moderate-to-vigorous physical activity (MVPA).…

  20. Fjaellveden study site. Scope of activities and main results

    During the period from 1977-1986 SKB (Swedish Nuclear Fuel and Waste Management CO) performed surface and borehole investigations of 14 study sites for the purpose of assessing their suitability for a repository of spent nuclear fuel. The next phase in the SKB site selection programme will be to perform detailed characterization, including characterization from shafts and/or tunnels, of two or three sites. The detailed investigations will continue over several years to provide all the data needed for a licensing application to build repository. Such an application is foreseen to be given to the authorities around the year 2003. It is presently not clear if anyone of the study sites will be selected as a site for detailed characterization. Other sites with geological and/or socio-economical characteristics judged more favourable may very well be the ones selected. However, as a part of the background documentation needed for the site selection studies to come, summary reports will be prepared for most study sites. These reports will include scope of activities, main results, uncertainties and need for complementary investigations. This report concerns the Fjaellveden study site. (au)

  1. Gideaa study site. Scope of activities and main results

    During the period from 1977-1986 SKB (Swedish Nuclear Fuel and Waste Management Co) performed surface and borehole investigations of 14 study sites for the purpose of assessing their suitability for a repository of spent nuclear fuel. The next phase in the SKB site selection programme will be to perform detailed characterization, including characterization from shafts and/or tunnels, of two or three sites. The detailed investigations will continue over several years to provide all the data needed for a licensing application to build a repository. Such an application is foreseen to be given to the authorities around the year 2003. It is presently not clear if anyone of the study sites will be selected as a site for detailed characterization. Other site with geological and/or socio-economical characteristics judged more favourable may very well be the ones selected. However, as a part of the background documentation needed for the site selection studies to come, summary reports will be prepared for most study sites. These reports will include scope of activities, main results, uncertainties and need of complementary investigations. This report concerns the Gideaa study site. (au)

  2. Kamlunge study site. Scope of activities and main results

    During the period from 1977-1986 SKB (Swedish nuclear Fuel and Waste Management Co.) performed surface and borehole investigations of 14 study sites for the purpose of assessing their suitability for a repository of spent nuclear fuel. The next phase in the SKB site selection programme will be to perform detailed characterization, including characterization from shafts and/or tunnels, of two or three sites. The detailed investigations will continue over several years to provide all the data needed for a licensing application to build a repository. Such an application is foreseen to be given to the authorities around the year 2003. It is presently not clear if anyone of the study sites will be selected as a site for detailed characterization. Other sites with geological and/or socio-economical characteristics judged more favourable may very well be selected. However, as a part of the background documentation needed for the site selection studies to come, summary reports will be prepared for most study sites. These reports will include scope of activities, main results, uncertainties and need of complementary investigations. This report concerns the Kamlunge study site. (79 refs.) (au)

  3. PASS-GP: Predictive active set selection for Gaussian processes

    Henao, Ricardo; Winther, Ole

    We propose a new approximation method for Gaussian process (GP) learning for large data sets that combines inline active set selection with hyperparameter optimization. The predictive probability of the label is used for ranking the data points. We use the leave-one-out predictive probability...... the active set selection strategy and marginal likelihood optimization on the active set. We make extensive tests on the USPS and MNIST digit classification databases with and without incorporating invariances, demonstrating that we can get state-of-the-art results (e.g.0.86% error on MNIST) with...

  4. Reduction of urease activity by interaction with the flap covering the active site.

    Macomber, Lee; Minkara, Mona S; Hausinger, Robert P; Merz, Kenneth M

    2015-02-23

    With the increasing appreciation for the human microbiome coupled with the global rise of antibiotic resistant organisms, it is imperative that new methods be developed to specifically target pathogens. To that end, a novel computational approach was devised to identify compounds that reduce the activity of urease, a medically important enzyme of Helicobacter pylori, Proteus mirabilis, and many other microorganisms. Urease contains a flexible loop that covers its active site; Glide was used to identify small molecules predicted to lock this loop in an open conformation. These compounds were screened against the model urease from Klebsiella aerogenes, and the natural products epigallocatechin and quercetin were shown to inhibit at low and high micromolar concentrations, respectively. These molecules exhibit a strong time-dependent inactivation of urease that was not due to their oxygen sensitivity. Rather, these compounds appear to inactivate urease by reacting with a specific Cys residue located on the flexible loop. Substitution of this cysteine by alanine in the C319A variant increased the urease resistance to both epigallocatechin and quercetin, as predicted by the computational studies. Protein dynamics are integral to the function of many enzymes; thus, identification of compounds that lock an enzyme into a single conformation presents a useful approach to define potential inhibitors. PMID:25594724

  5. Genome-wide de novo prediction of cis-regulatory binding sites in prokaryotes

    Zhang, Shaoqiang; Xu, Minli; Su, Zhengchang

    2009-01-01

    Although cis-regulatory binding sites (CRBSs) are at least as important as the coding sequences in a genome, our general understanding of them in most sequenced genomes is very limited due to the lack of efficient and accurate experimental and computational methods for their characterization, which has largely hindered our understanding of many important biological processes. In this article, we describe a novel algorithm for genome-wide de novo prediction of CRBSs with high accuracy. We designed our algorithm to circumvent three identified difficulties for CRBS prediction using comparative genomics principles based on a new method for the selection of reference genomes, a new metric for measuring the similarity of CRBSs, and a new graph clustering procedure. When operon structures are correctly predicted, our algorithm can predict 81% of known individual binding sites belonging to 94% of known cis-regulatory motifs in the Escherichia coli K12 genome, while achieving high prediction specificity. Our algorithm has also achieved similar prediction accuracy in the Bacillus subtilis genome, suggesting that it is very robust, and thus can be applied to any other sequenced prokaryotic genome. When compared with the prior state-of-the-art algorithms, our algorithm outperforms them in both prediction sensitivity and specificity. PMID:19383880

  6. Ensemble approach combining multiple methods improves human transcription start site prediction

    Dineen, David G

    2010-11-30

    Abstract Background The computational prediction of transcription start sites is an important unsolved problem. Some recent progress has been made, but many promoters, particularly those not associated with CpG islands, are still difficult to locate using current methods. These methods use different features and training sets, along with a variety of machine learning techniques and result in different prediction sets. Results We demonstrate the heterogeneity of current prediction sets, and take advantage of this heterogeneity to construct a two-level classifier (\\'Profisi Ensemble\\') using predictions from 7 programs, along with 2 other data sources. Support vector machines using \\'full\\' and \\'reduced\\' data sets are combined in an either\\/or approach. We achieve a 14% increase in performance over the current state-of-the-art, as benchmarked by a third-party tool. Conclusions Supervised learning methods are a useful way to combine predictions from diverse sources.

  7. Application of GIS in prediction and assessment system of off-site accident consequence for NPP

    The assessment and prediction software system of off-site accident consequence for Guangdong Nuclear Power Plant (GNARD2.0) is a GIS-based software system. The spatial analysis of radioactive materials and doses with geographic information is available in this system. The structure and functions of the GNARD system and the method of applying ArcView GIS are presented

  8. Survey on Nucleotide Encoding Techniques and SVM Kernel Design for Human Splice Site Prediction

    A.T.M. Golam Bari

    2012-12-01

    Full Text Available Splice site prediction in DNA sequence is a basic search problem for finding exon/intron and intron/exon boundaries. Removing introns and then joining the exons together forms the mRNA sequence. These sequences are the input of the translation process. It is a necessary step in the central dogma of molecular biology. The main task of splice site prediction is to find out the exact GT and AG ended sequences. Then it identifies the true and false GT and AG ended sequences among those candidate sequences. In this paper, we survey research works on splice site prediction based on support vector machine (SVM. The basic difference between these research works is nucleotide encoding technique and SVM kernel selection. Some methods encode the DNA sequence in a sparse way whereas others encode in a probabilistic manner. The encoded sequences serve as input of SVM. The task of SVM is to classify them using its learning model. The accuracy of classification largely depends on the proper kernel selection for sequence data as well as a selection of kernel parameter. We observe each encoding technique and classify them according to their similarity. Then we discuss about kernel and their parameter selection. Our survey paper provides a basic understanding of encoding approaches and proper kernel selection of SVM for splice site prediction.

  9. Long-term predictions of water table from precipitation analysis for a waste disposal site

    Long-term predictions of water table fluctuations at a waste disposal site have been made from precipitation analysis. Two methods have been applied: a statistical/empirical correlative approach, and a hydrogeologic modelling approach using the finite difference code SWIFT (Simulator for Waste Injection Flow and Transport). This paper discusses the methodology and the results of these assessments

  10. Predicting changes in protein thermostability brought about by single- or multi-site mutations

    Chu Xiaoyu

    2010-07-01

    Full Text Available Abstract Background An important aspect of protein design is the ability to predict changes in protein thermostability arising from single- or multi-site mutations. Protein thermostability is reflected in the change in free energy (ΔΔG of thermal denaturation. Results We have developed predictive software, Prethermut, based on machine learning methods, to predict the effect of single- or multi-site mutations on protein thermostability. The input vector of Prethermut is based on known structural changes and empirical measurements of changes in potential energy due to protein mutations. Using a 10-fold cross validation test on the M-dataset, consisting of 3366 mutants proteins from ProTherm, the classification accuracy of random forests and the regression accuracy of random forest regression were slightly better than support vector machines and support vector regression, whereas the overall accuracy of classification and the Pearson correlation coefficient of regression were 79.2% and 0.72, respectively. Prethermut performs better on proteins containing multi-site mutations than those with single mutations. Conclusions The performance of Prethermut indicates that it is a useful tool for predicting changes in protein thermostability brought about by single- or multi-site mutations and will be valuable in the rational design of proteins.

  11. Improving the prediction of protein binding sites by combining heterogeneous data and Voronoi diagrams

    Fernandez-Fuentes Narcis

    2011-08-01

    Full Text Available Abstract Background Protein binding site prediction by computational means can yield valuable information that complements and guides experimental approaches to determine the structure of protein complexes. Predictions become even more relevant and timely given the current resolution of protein interaction maps, where there is a very large and still expanding gap between the available information on: (i which proteins interact and (ii how proteins interact. Proteins interact through exposed residues that present differential physicochemical properties, and these can be exploited to identify protein interfaces. Results Here we present VORFFIP, a novel method for protein binding site prediction. The method makes use of broad set of heterogeneous data and defined of residue environment, by means of Voronoi Diagrams that are integrated by a two-steps Random Forest ensemble classifier. Four sets of residue features (structural, energy terms, sequence conservation, and crystallographic B-factors used in different combinations together with three definitions of residue environment (Voronoi Diagrams, sequence sliding window, and Euclidian distance have been analyzed in order to maximize the performance of the method. Conclusions The integration of different forms information such as structural features, energy term, evolutionary conservation and crystallographic B-factors, improves the performance of binding site prediction. Including the information of neighbouring residues also improves the prediction of protein interfaces. Among the different approaches that can be used to define the environment of exposed residues, Voronoi Diagrams provide the most accurate description. Finally, VORFFIP compares favourably to other methods reported in the recent literature.

  12. Proteins and Their Interacting Partners: An Introduction to Protein–Ligand Binding Site Prediction Methods

    Daniel Barry Roche

    2015-12-01

    Full Text Available Elucidating the biological and biochemical roles of proteins, and subsequently determining their interacting partners, can be difficult and time consuming using in vitro and/or in vivo methods, and consequently the majority of newly sequenced proteins will have unknown structures and functions. However, in silico methods for predicting protein–ligand binding sites and protein biochemical functions offer an alternative practical solution. The characterisation of protein–ligand binding sites is essential for investigating new functional roles, which can impact the major biological research spheres of health, food, and energy security. In this review we discuss the role in silico methods play in 3D modelling of protein–ligand binding sites, along with their role in predicting biochemical functionality. In addition, we describe in detail some of the key alternative in silico prediction approaches that are available, as well as discussing the Critical Assessment of Techniques for Protein Structure Prediction (CASP and the Continuous Automated Model EvaluatiOn (CAMEO projects, and their impact on developments in the field. Furthermore, we discuss the importance of protein function prediction methods for tackling 21st century problems.

  13. Active Sites Environmental Monitoring Program: Mid-FY 1991 report

    Ashwood, T.L.; Wickliff, D.S.; Morrissey, C.M.

    1991-10-01

    This report summarizes the activities of the Active Sites Environmental Monitoring Program (ASEMP) from October 1990 through March 1991. The ASEMP was established in 1989 by Solid Waste Operations and the Environmental Sciences Division to provide early detection and performance monitoring at active low-level radioactive waste (LLW) disposal sites in Solid Waste Storage Area (SWSA) 6 and transuranic (TRU) waste storage sites in SWSA 5 as required by chapters II and III of US Department of Energy Order 5820.2A. Monitoring results continue to demonstrate the no LLW is being leached from the storage vaults on the tumulus pads. Loading of vaults on Tumulus II began during this reporting period and 115 vaults had been loaded by the end of March 1991.

  14. PREDICTION OF ANTIGENIC AND BINDING SITES OF NEUROTOXIN 23 OF SCORPION (LYCHASMUCRONACTUS SP.

    Bharati K Thosare

    2015-07-01

    Full Text Available Identification of antigenic and binding site of protein is highly desirable for the design of vaccines and immunodiagnostics. The present exercise deals with a prediction of antigenic as well as binding sites of neurotoxin 23 of Lychasmucronactus. This species of scorpion having diverse molecules of toxic peptide, the peptide neurotoxin 23 is 96 amino acids long of which 23 to 96 specifically code for neurotoxin. The total of 27 such different ligand binding residue were identified by ConSurf and Raptor X server. The web tool Ellipro which implements Modeller and Jmol viewer, predicted and visualized the linear and discontinuous antibody epitopes ofneurotoxin 23 protein sequence.Thus the information discussed here provides a clue for understanding antigenic site and molecular function of neurotoxin 23.

  15. Nonlinear Predictive Control of Semi-Active Landing Gear System

    Wu, Dongsu; Gu, Hongbin; Liu, Hui

    2010-01-01

    The application of model predictive control and constructive nonlinear control methodology to semi-active landing gear system is studied in this paper. A unified shock absorber mathematical model incorporates solenoid valve’s electromechanical and magnetic dynamics is built to facilitate simulation and controller design. Then we propose a hierarchical control structure to deal with the high nonlinearity. A dual mode model predictive controller as an outer loop controller is developed to gen...

  16. Active chemisorption sites in functionalized ionic liquids for carbon capture.

    Cui, Guokai; Wang, Jianji; Zhang, Suojiang

    2016-07-25

    Development of novel technologies for the efficient and reversible capture of CO2 is highly desired. In the last decade, CO2 capture using ionic liquids has attracted intensive attention from both academia and industry, and has been recognized as a very promising technology. Recently, a new approach has been developed for highly efficient capture of CO2 by site-containing ionic liquids through chemical interaction. This perspective review focuses on the recent advances in the chemical absorption of CO2 using site-containing ionic liquids, such as amino-based ionic liquids, azolate ionic liquids, phenolate ionic liquids, dual-functionalized ionic liquids, pyridine-containing ionic liquids and so on. Other site-containing liquid absorbents such as amine-based solutions, switchable solvents, and functionalized ionic liquid-amine blends are also investigated. Strategies have been discussed for how to activate the existent reactive sites and develop novel reactive sites by physical and chemical methods to enhance CO2 absorption capacity and reduce absorption enthalpy. The carbon capture mechanisms of these site-containing liquid absorbents are also presented. Particular attention has been paid to the latest progress in CO2 capture in multiple-site interactions by amino-free anion-functionalized ionic liquids. In the last section, future directions and prospects for carbon capture by site-containing ionic liquids are outlined. PMID:27243042

  17. A kinetic description for sodium and potassium effects on (Na+ plus K+)-adenosine triphosphatase: a model for a two-nonequivalent site potassium activation and an analysis of multiequivalent site models for sodium activation.

    Lindenmayer, G E; Schwartz, A; Thompson, H K

    1974-01-01

    1. Dissociation constants for sodium and potassium of a site that modulates the rate of ouabain-(Na(+)+K(+))-ATPase interaction were applied to models for potassium activation of (Na(+)+K(+))-ATPase. The constants for potassium (0.213 mM) and for sodium (13.7 mM) were defined, respectively, as activation constant, K(a) and inhibitory constant, K(i).2. Tests of the one- and the two-equivalent site models, that describe sodium and potassium competition, revealed that neither model adequately predicts the activation effects of potassium in the presence of 100 or 200 mM sodium.3. The potassium-activation data, obtained at low potassium and high sodium, were explained by a two-nonequivalent site model where the dissociation constants of the first site are 0.213 mM for potassium and 13.7 mM for sodium. The second site was characterized by dissociation constants of 0.091 mM for potassium and 74.1 mM for sodium.4. The two-nonequivalent site model adequately predicted the responses to concentrations of potassium between 0.25 and 5 mM in the presence of 100-500 mM sodium. At lower sodium concentrations the predicted responses formed an upper limit for the function of observed activities. This limit was reached at lower concentrations of potassium and higher concentrations of sodium, which inferred saturation of the sodium-activation sites with sodium.5. Sodium-activation data were corrected for sodium interaction with potassium-activation sites by use of the two-nonequivalent site model for potassium activation. Tests of equivalent site models suggested that the corrected data for sodium activation may be most consistent with a model that has three-equivalent sites. Other multiequivalent site models (n = 2, 4, 5 or 6), however, cannot be statistically eliminated as possibilities. The three-equivalent site activation model was characterized by dissociation constants of 1.39 mM for sodium and 11.7 mM for potassium. The system theoretically would be half-maximally activated by

  18. Prediction of functional sites based on the fuzzy oil drop model.

    Michał Bryliński

    2007-05-01

    Full Text Available A description of many biological processes requires knowledge of the 3-D structure of proteins and, in particular, the defined active site responsible for biological function. Many proteins, the genes of which have been identified as the result of human genome sequencing, and which were synthesized experimentally, await identification of their biological activity. Currently used methods do not always yield satisfactory results, and new algorithms need to be developed to recognize the localization of active sites in proteins. This paper describes a computational model that can be used to identify potential areas that are able to interact with other molecules (ligands, substrates, inhibitors, etc.. The model for active site recognition is based on the analysis of hydrophobicity distribution in protein molecules. It is shown, based on the analyses of proteins with known biological activity and of proteins of unknown function, that the region of significantly irregular hydrophobicity distribution in proteins appears to be function related.

  19. Structure based activity prediction of HIV-1 reverse transcriptase inhibitors.

    de Jonge, Marc R; Koymans, Lucien M H; Vinkers, H Maarten; Daeyaert, Frits F D; Heeres, Jan; Lewi, Paul J; Janssen, Paul A J

    2005-03-24

    We have developed a fast and robust computational method for prediction of antiviral activity in automated de novo design of HIV-1 reverse transcriptase inhibitors. This is a structure-based approach that uses a linear relation between activity and interaction energy with discrete orientation sampling and with localized interaction energy terms. The localization allows for the analysis of mutations of the protein target and for the separation of inhibition and a specific binding to the enzyme. We apply the method to the prediction of pIC(50) of HIV-1 reverse transcriptase inhibitors. The model predicts the activity of an arbitrary compound with a q(2) of 0.681 and an average absolute error of 0.66 log value, and it is fast enough to be used in high-throughput computational applications. PMID:15771460

  20. Genetic algorithm learning as a robust approach to RNA editing site prediction

    Gopal Shuba

    2006-03-01

    Full Text Available Abstract Background RNA editing is one of several post-transcriptional modifications that may contribute to organismal complexity in the face of limited gene complement in a genome. One form, known as C → U editing, appears to exist in a wide range of organisms, but most instances of this form of RNA editing have been discovered serendipitously. With the large amount of genomic and transcriptomic data now available, a computational analysis could provide a more rapid means of identifying novel sites of C → U RNA editing. Previous efforts have had some success but also some limitations. We present a computational method for identifying C → U RNA editing sites in genomic sequences that is both robust and generalizable. We evaluate its potential use on the best data set available for these purposes: C → U editing sites in plant mitochondrial genomes. Results Our method is derived from a machine learning approach known as a genetic algorithm. REGAL (RNA Editing site prediction by Genetic Algorithm Learning is 87% accurate when tested on three mitochondrial genomes, with an overall sensitivity of 82% and an overall specificity of 91%. REGAL's performance significantly improves on other ab initio approaches to predicting RNA editing sites in this data set. REGAL has a comparable sensitivity and higher specificity than approaches which rely on sequence homology, and it has the advantage that strong sequence conservation is not required for reliable prediction of edit sites. Conclusion Our results suggest that ab initio methods can generate robust classifiers of putative edit sites, and we highlight the value of combinatorial approaches as embodied by genetic algorithms. We present REGAL as one approach with the potential to be generalized to other organisms exhibiting C → U RNA editing.

  1. SPE-5 Ground-Motion Prediction at Far-Field Geophone and Accelerometer Array Sites and SPE-5 Moment and Corner-Frequency Prediction

    Yang, Xiaoning [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Patton, Howard John [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Chen, Ting [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-03-25

    This report offers predictions for the SPE-5 ground-motion and accelerometer array sites. These predictions pertain to the waveform and spectral amplitude at certain geophone sites using Denny&Johnson source model and a source model derived from SPE data; waveform, peak velocity and peak acceleration at accelerometer sites using the SPE source model and the finite-difference simulation with LLNL 3D velocity model; and the SPE-5 moment and corner frequency.

  2. Influence Of Site Classification On Computing Empirical Ground-Motion Prediction Equations In Italy

    di Alessandro, C.; Bonilla, L.; Rovelli, A.; Scotti, O.

    2008-12-01

    In this study, we investigate a site classification method for stations of the Italian Accelerometric Network based on the predominant period of ground motion at the site. The site predominant period is identified from the average horizontal-to-vertical (H/V) spectral ratios of the 5%-damped response spectra of Italian earthquake records. We selected a data-set of 610 three-component analogue and digital recordings from 120 earthquakes recorded at 214 seismic stations within an hypocentral distance of 200 km. Selected events are in the moment-magnitude Mw range of 4.0 to 6.8 and the focal depth ranges from 5 to 40 km. Whenever possible, we classified each site by assigning them to one of six predominant period classes (in the range 0.05 to 2 seconds) that we propose as a modification of the Zhao et al. (2006) procedure. We then investigated the impact of this classification scheme on empirical ground-motion prediction equations. We adopted the same functional form of Fukushima et al. (2007) and we computed a nonlinear period- dependent regression that allowed us to derive site coefficients using the proposed six predominant period classes. We also derived site coefficients for a simplified classification based on the general soil conditions at each site. This classification uses two classes (which we call A-B and C-D, with Vs ≥ 360 m/s and Vs < 360 m/s, respectively) based on the four basic ground categories in the current European (CEN 2004) and Italian seismic codes. Our empirical site classification scheme based on strong-motion data provides the opportunity to explore whether we can decrease the misfit by improving the site characterization of the Italian data set. Comparison of our results with other empirical ground-motion prediction equations (GMPEs) based on conventional site classifications do not display a significant reduction of overall standard deviation. However, our site classification schemes shows promise in reducing the uncertainty in ground

  3. Resonant active sites in catalytic ammonia synthesis: A structural model

    Cholach, Alexander R.; Bryliakova, Anna A.; Matveev, Andrey V.; Bulgakov, Nikolai N.

    2016-03-01

    Adsorption sites Mn consisted of n adjacent atoms M, each bound to the adsorbed species, are considered within a realistic model. The sum of bonds Σ lost by atoms in a site in comparison with the bulk atoms was used for evaluation of the local surface imperfection, while the reaction enthalpy at that site was used as a measure of activity. The comparative study of Mn sites (n = 1-5) at basal planes of Pt, Rh, Ir, Fe, Re and Ru with respect to heat of N2 dissociative adsorption QN and heat of Nad + Had → NHad reaction QNH was performed using semi-empirical calculations. Linear QN(Σ) increase and QNH(Σ) decrease allowed to specify the resonant Σ for each surface in catalytic ammonia synthesis at equilibrium Nad coverage. Optimal Σ are realizable for Ru2, Re2 and Ir4 only, whereas other centers meet steric inhibition or unreal crystal structure. Relative activity of the most active sites in proportion 5.0 × 10- 5: 4.5 × 10- 3: 1: 2.5: 3.0: 1080: 2270 for a sequence of Pt4, Rh4, Fe4(fcc), Ir4, Fe2-5(bcc), Ru2, Re2, respectively, is in agreement with relevant experimental data. Similar approach can be applied to other adsorption or catalytic processes exhibiting structure sensitivity.

  4. Improved Species-Specific Lysine Acetylation Site Prediction Based on a Large Variety of Features Set.

    Wuyun, Qiqige; Zheng, Wei; Zhang, Yanping; Ruan, Jishou; Hu, Gang

    2016-01-01

    Lysine acetylation is a major post-translational modification. It plays a vital role in numerous essential biological processes, such as gene expression and metabolism, and is related to some human diseases. To fully understand the regulatory mechanism of acetylation, identification of acetylation sites is first and most important. However, experimental identification of protein acetylation sites is often time consuming and expensive. Therefore, the alternative computational methods are necessary. Here, we developed a novel tool, KA-predictor, to predict species-specific lysine acetylation sites based on support vector machine (SVM) classifier. We incorporated different types of features and employed an efficient feature selection on each type to form the final optimal feature set for model learning. And our predictor was highly competitive for the majority of species when compared with other methods. Feature contribution analysis indicated that HSE features, which were firstly introduced for lysine acetylation prediction, significantly improved the predictive performance. Particularly, we constructed a high-accurate structure dataset of H.sapiens from PDB to analyze the structural properties around lysine acetylation sites. Our datasets and a user-friendly local tool of KA-predictor can be freely available at http://sourceforge.net/p/ka-predictor. PMID:27183223

  5. Stock price change rate prediction by utilizing social network activities.

    Deng, Shangkun; Mitsubuchi, Takashi; Sakurai, Akito

    2014-01-01

    Predicting stock price change rates for providing valuable information to investors is a challenging task. Individual participants may express their opinions in social network service (SNS) before or after their transactions in the market; we hypothesize that stock price change rate is better predicted by a function of social network service activities and technical indicators than by a function of just stock market activities. The hypothesis is tested by accuracy of predictions as well as performance of simulated trading because success or failure of prediction is better measured by profits or losses the investors gain or suffer. In this paper, we propose a hybrid model that combines multiple kernel learning (MKL) and genetic algorithm (GA). MKL is adopted to optimize the stock price change rate prediction models that are expressed in a multiple kernel linear function of different types of features extracted from different sources. GA is used to optimize the trading rules used in the simulated trading by fusing the return predictions and values of three well-known overbought and oversold technical indicators. Accumulated return and Sharpe ratio were used to test the goodness of performance of the simulated trading. Experimental results show that our proposed model performed better than other models including ones using state of the art techniques. PMID:24790586

  6. The nature of the active site in heterogeneous metal catalysis

    Nørskov, Jens Kehlet; Bligaard, Thomas; Larsen, Britt Hvolbæk;

    2008-01-01

    This tutorial review, of relevance for the surface science and heterogeneous catalysis communities, provides a molecular-level discussion of the nature of the active sites in metal catalysis. Fundamental concepts such as "Bronsted-Evans-Polanyi relations'' and "volcano curves'' are introduced, and...

  7. Probing the active sites for CO dissociation on ruthenium nanoparticles

    Strebel, Christian Ejersbo; Murphy, Shane; Nielsen, Rasmus Munksgård;

    2012-01-01

    The active sites for CO dissociation were probed on mass-selected Ru nanoparticles on a HOPG support by temperature programmed desorption spectroscopy using isotopically labelled CO. Combined with transmission electron microscopy we gain insight on how the size and morphology of the nanoparticles...

  8. Chemical Modification of Papain and Subtilisin: An Active Site Comparison

    St-Vincent, Mireille; Dickman, Michael

    2004-01-01

    An experiment using methyle methanethiosulfonate (MMTS) and phenylmethylsulfonyl flouride (PMSF) to specifically modify the cysteine and serine residues in the active sites of papain and subtilism respectively is demonstrated. The covalent modification of these enzymes and subsequent rescue of papain shows the beginning biochemist that proteins…

  9. Active site modeling in copper azurin molecular dynamics simulations

    Rizzuti, B; Swart, M; Sportelli, L; Guzzi, R

    2004-01-01

    Active site modeling in molecular dynamics simulations is investigated for the reduced state of copper azurin. Five simulation runs (5 ns each) were performed at room temperature to study the consequences of a mixed electrostatic/constrained modeling for the coordination between the metal and the po

  10. Active Sites Environmental Monitoring Program: FY 1990 annual report

    Wickliff, D.S.; Morrissey, C.M.; Ashwood, T.L.

    1991-10-01

    Chapter 3 of US Department of Energy (DOE) Order 5820.2A (DOE 1988) sets forth requirements for environmental monitoring of active low-level waste (LLW) disposal sites. Active sites are defined as those LLW facilities that were in use on or after the date of the order (September 1988). The transuranic (TRU) waste storage areas in Solid Waste Storage Area (SWSA) 5 North are covered by Chap. 2 of the order. In both chapters, monitoring is required to provide for early warning of leaks before those leaks pose a threat to human health or the environment. Chapter 3 also requires that monitoring be conducted to evaluate the short- and long-term performance of LLW disposal facilities. In accordance with this order, the Solid Waste Operations Department at Oak Ridge National Laboratory (ORNL) has established an Active Sites Environmental Monitoring Program (ASEMP) that is implemented by staff of the Environmental Sciences Division (ESD) at ORNL. This report summarizes data from ASEMP monitoring activities for the final 6 months of FY 1990. A brief summary of the monitoring methodology for each site is presented also.

  11. Active Sites Environmental Monitoring Program: FY 1990 annual report

    Chapter 3 of US Department of Energy (DOE) Order 5820.2A (DOE 1988) sets forth requirements for environmental monitoring of active low-level waste (LLW) disposal sites. Active sites are defined as those LLW facilities that were in use on or after the date of the order (September 1988). The transuranic (TRU) waste storage areas in Solid Waste Storage Area (SWSA) 5 North are covered by Chap. 2 of the order. In both chapters, monitoring is required to provide for early warning of leaks before those leaks pose a threat to human health or the environment. Chapter 3 also requires that monitoring be conducted to evaluate the short- and long-term performance of LLW disposal facilities. In accordance with this order, the Solid Waste Operations Department at Oak Ridge National Laboratory (ORNL) has established an Active Sites Environmental Monitoring Program (ASEMP) that is implemented by staff of the Environmental Sciences Division (ESD) at ORNL. This report summarizes data from ASEMP monitoring activities for the final 6 months of FY 1990. A brief summary of the monitoring methodology for each site is presented also

  12. Improving N(6)-methyladenosine site prediction with heuristic selection of nucleotide physical-chemical properties.

    Zhang, Ming; Sun, Jia-Wei; Liu, Zi; Ren, Ming-Wu; Shen, Hong-Bin; Yu, Dong-Jun

    2016-09-01

    N(6)-methyladenosine (m(6)A) is one of the most common and abundant post-transcriptional RNA modifications found in viruses and most eukaryotes. m(6)A plays an essential role in many vital biological processes to regulate gene expression. Because of its widespread distribution across the genomes, the identification of m(6)A sites from RNA sequences is of significant importance for better understanding the regulatory mechanism of m(6)A. Although progress has been achieved in m(6)A site prediction, challenges remain. This article aims to further improve the performance of m(6)A site prediction by introducing a new heuristic nucleotide physical-chemical property selection (HPCS) algorithm. The proposed HPCS algorithm can effectively extract an optimized subset of nucleotide physical-chemical properties under the prescribed feature representation for encoding an RNA sequence into a feature vector. We demonstrate the efficacy of the proposed HPCS algorithm under different feature representations, including pseudo dinucleotide composition (PseDNC), auto-covariance (AC), and cross-covariance (CC). Based on the proposed HPCS algorithm, we implemented an m(6)A site predictor, called M6A-HPCS, which is freely available at http://csbio.njust.edu.cn/bioinf/M6A-HPCS. Experimental results over rigorous jackknife tests on benchmark datasets demonstrated that the proposed M6A-HPCS achieves higher success rates and outperforms existing state-of-the-art sequence-based m(6)A site predictors. PMID:27293216

  13. A Python analytical pipeline to identify prohormone precursors and predict prohormone cleavage sites

    Bruce Southey

    2008-12-01

    Full Text Available Neuropeptides and hormones are signaling molecules that support cell-cell communication in the central nervous system. Experimentally characterizing neuropeptides requires significant efforts because of the complex and variable processing of prohormone precursor proteins into neuropeptides and hormones. We demonstrate the power and flexibility of the Python language to develop components of an bioinformatic analytical pipeline to identify precursors from genomic data and to predict cleavage as these precursors are en route to the final bioactive peptides. We identified 75 precursors in the rhesus genome, predicted cleavage sites using support vector machines and compared the rhesus predictions to putative assignments based on homology to human sequences. The correct classification rate of cleavage using the support vector machines was over 97% for both human and rhesus data sets. The functionality of Python has been important to develop and maintain NeuroPred (http://neuroproteomics.scs.uiuc.edu/neuropred.html, a user-centered web application for the neuroscience community that provides cleavage site prediction from a wide range of models, precision and accuracy statistics, post-translational modifications, and the molecular mass of potential peptides. The combined results illustrate the suitability of the Python language to implement an all-inclusive bioinformatics approach to predict neuropeptides that encompasses a large number of interdependent steps, from scanning genomes for precursor genes to identification of potential bioactive neuropeptides.

  14. Splice site prediction in Arabidopsis thaliana pre-mRNA by combining local and global sequence information

    Hebsgaard, Stefan M.; Korning, Peter G.; Tolstrup, Niels;

    1996-01-01

    experimentally observed in A.thaliana transformants. Predictions for alternatively spliced genes are also presented, together with examples of genes from other dicots, monocots and algae. The method has been made available through electronic mail (NetPlantGene@cbs.dtu.dk), or the WWW at http://www.cbs.dtu.dk/NetPlantGene.html......Artificial neural networks have been combined with a rule based system to predict intron splice sites in the dicot plant Arabidopsis thaliana. A two step prediction scheme, where a global prediction of the coding potential regulates a cutoff level for a local predicition of splice sites, is refined...... by rules based on splice site confidence values, prediction scores, coding context and distances between potential splice sites. In this approach, the prediction of splice sites mutually affect each other in a non-local manner. The combined approach drastically reduces the large amount of false...

  15. Predicting Active Users' Personality Based on Micro-Blogging Behaviors

    Lin LI; Li, Ang; Hao, Bibo; Guan, Zengda; Zhu, Tingshao

    2014-01-01

    Because of its richness and availability, micro-blogging has become an ideal platform for conducting psychological research. In this paper, we proposed to predict active users' personality traits through micro-blogging behaviors. 547 Chinese active users of micro-blogging participated in this study. Their personality traits were measured by the Big Five Inventory, and digital records of micro-blogging behaviors were collected via web crawlers. After extracting 845 micro-blogging behavioral fe...

  16. Teenagers and social network sites: Do off-line inequalities predict their online social networks?

    Ahn, June

    2011-01-01

    This study analyzes a data set of 701 U.S. teenagers (ages 12-18) that merges an online survey of social network site (SNS) preferences with administrative records from their public school districts. Using a multinomial logistic model, I examine whether offline divides across gender, ethnicity, socioeconomic status, self-esteem, and social capital predict teenagers’ membership into the popular SNSs, Facebook and Myspace. The results show that the characteristics of teens that use Facebook, ...

  17. LRR Conservation Mapping to Predict Functional Sites within Protein Leucine-Rich Repeat Domains

    Helft, Laura; Reddy, Vignyan; Chen, Xiyang; Koller, Teresa; Federici, Luca; Fernández-Recio, Juan; Gupta, Rishabh; Bent, Andrew

    2011-01-01

    Computational prediction of protein functional sites can be a critical first step for analysis of large or complex proteins. Contemporary methods often require several homologous sequences and/or a known protein structure, but these resources are not available for many proteins. Leucine-rich repeats (LRRs) are ligand interaction domains found in numerous proteins across all taxonomic kingdoms, including immune system receptors in plants and animals. We devised Repeat Conservation Mapping (RCM...

  18. Suction Drain Tip Culture after Spine Surgery: Can It Predict a Surgical Site Infection?

    Ahn, Jae-Sung; Lee, Ho-Jin; Park, Eugene; Park, Il-Young; Lee, Jae Won

    2015-01-01

    Study Design Retrospective clinical study. Purpose To assess the diagnostic value of suction drain tip culture in patients undergoing primary posterior spine surgery. Overview of Literature To date, the diagnostic value of suction drain tip culture for predicting surgical site infection (SSI) has not been firmly established in orthopedic or spinal surgery. Methods In total, 133 patients who underwent primary posterior spine surgery from January 2013 to April 2015 were included in this retrosp...

  19. Genome-wide de novo prediction of cis-regulatory binding sites in prokaryotes

    Zhang, Shaoqiang; Xu, Minli; Li, Shan; Su, Zhengchang

    2009-01-01

    Although cis-regulatory binding sites (CRBSs) are at least as important as the coding sequences in a genome, our general understanding of them in most sequenced genomes is very limited due to the lack of efficient and accurate experimental and computational methods for their characterization, which has largely hindered our understanding of many important biological processes. In this article, we describe a novel algorithm for genome-wide de novo prediction of CRBSs with high accuracy. We desi...

  20. Neural Network Prediction of Translation Initiation Sites in Eukaryotes: Perspectives for EST and Genome analysis

    Pedersen, Anders Gorm; Nielsen, Henrik

    Translation in eukaryotes does not always start at the first AUG in an mRNA, implying that context information also plays a role.This makes prediction of translation initiation sites a non-trivial task, especially when analysing EST and genome data where the entire mature mRNA sequence is not known...... and database annotations are analysed in detail, leading to identification of possible database errors....

  1. Resting alpha activity predicts learning ability in alpha neurofeedback

    Wenya eNan

    2014-07-01

    Full Text Available Individuals differ in their ability to learn how to regulate the alpha activity by neurofeedback. This study aimed to investigate whether the resting alpha activity is related to the learning ability of alpha enhancement in neurofeedback and could be used as a predictor. A total of 25 subjects performed 20 sessions of individualized alpha neurofeedback in order to learn how to enhance activity in the alpha frequency band. The learning ability was assessed by three indices respectively: the training parameter changes between two periods, within a short period and across the whole training time. It was found that the resting alpha amplitude measured before training had significant positive correlations with all learning indices and could be used as a predictor for the learning ability prediction. This finding would help the researchers in not only predicting the training efficacy in individuals but also gaining further insight into the mechanisms of alpha neurofeedback.

  2. Predicting active users' personality based on micro-blogging behaviors.

    Lin Li

    Full Text Available Because of its richness and availability, micro-blogging has become an ideal platform for conducting psychological research. In this paper, we proposed to predict active users' personality traits through micro-blogging behaviors. 547 Chinese active users of micro-blogging participated in this study. Their personality traits were measured by the Big Five Inventory, and digital records of micro-blogging behaviors were collected via web crawlers. After extracting 839 micro-blogging behavioral features, we first trained classification models utilizing Support Vector Machine (SVM, differentiating participants with high and low scores on each dimension of the Big Five Inventory [corrected]. The classification accuracy ranged from 84% to 92%. We also built regression models utilizing PaceRegression methods, predicting participants' scores on each dimension of the Big Five Inventory. The Pearson correlation coefficients between predicted scores and actual scores ranged from 0.48 to 0.54. Results indicated that active users' personality traits could be predicted by micro-blogging behaviors.

  3. On splice site prediction using weight array models: a comparison of smoothing techniques

    In most eukaryotic genes, protein-coding exons are separated by non-coding introns which are removed from the primary transcript by a process called 'splicing'. The positions where introns are cut and exons are spliced together are called 'splice sites'. Thus, computational prediction of splice sites is crucial for gene finding in eukaryotes. Weight array models are a powerful probabilistic approach to splice site detection. Parameters for these models are usually derived from m-tuple frequencies in trusted training data and subsequently smoothed to avoid zero probabilities. In this study we compare three different ways of parameter estimation for m-tuple frequencies, namely (a) non-smoothed probability estimation, (b) standard pseudo counts and (c) a Gaussian smoothing procedure that we recently developed

  4. On splice site prediction using weight array models: a comparison of smoothing techniques

    Taher, Leila; Meinicke, Peter; Morgenstern, Burkhard

    2007-11-01

    In most eukaryotic genes, protein-coding exons are separated by non-coding introns which are removed from the primary transcript by a process called "splicing". The positions where introns are cut and exons are spliced together are called "splice sites". Thus, computational prediction of splice sites is crucial for gene finding in eukaryotes. Weight array models are a powerful probabilistic approach to splice site detection. Parameters for these models are usually derived from m-tuple frequencies in trusted training data and subsequently smoothed to avoid zero probabilities. In this study we compare three different ways of parameter estimation for m-tuple frequencies, namely (a) non-smoothed probability estimation, (b) standard pseudo counts and (c) a Gaussian smoothing procedure that we recently developed.

  5. Prediction of posttranslational modification sites from amino acid sequences with kernel methods.

    Xu, Yan; Wang, Xiaobo; Wang, Yongcui; Tian, Yingjie; Shao, Xiaojian; Wu, Ling-Yun; Deng, Naiyang

    2014-03-01

    Post-translational modification (PTM) is the chemical modification of a protein after its translation and one of the later steps in protein biosynthesis for many proteins. It plays an important role which modifies the end product of gene expression and contributes to biological processes and diseased conditions. However, the experimental methods for identifying PTM sites are both costly and time-consuming. Hence computational methods are highly desired. In this work, a novel encoding method PSPM (position-specific propensity matrices) is developed. Then a support vector machine (SVM) with the kernel matrix computed by PSPM is applied to predict the PTM sites. The experimental results indicate that the performance of new method is better or comparable with the existing methods. Therefore, the new method is a useful computational resource for the identification of PTM sites. A unified standalone software PTMPred is developed. It can be used to predict all types of PTM sites if the user provides the training datasets. The software can be freely downloaded from http://www.aporc.org/doc/wiki/PTMPred. PMID:24291233

  6. Prediction and assignment of site occupation and energy levels for Pb2+ ions in crystal hosts

    The environmental factor he of the host was calculated quantitatively in Pb2+-doped 23 compounds based on the dielectric theory of chemical bond for complex crystals. The relationship between the A band energy EA of Pb2+ and the environmental factor he was intensively studied. The results indicate that EA of Pb2+ decreases linearly with increasing of he. A linear model was proposed which allows us to correctly predict and assign the site occupations and the position of A band for Pb2+-doped compounds if the crystal structure and the refraction index were known. Applied to SrGa2O4:Pb2+, CaAl2B2O7:Pb2+ and SrAl2B2O7:Pb2+, the theoretical predictions are in very good agreement with the experimental data. In SrGa2O4:Pb2+, the excitation spectrum of Pb2+ from two different cation sites was identified: the higher energy band of A (265 nm) from the site of Sr2, and the lower ones (280 nm) from the site of Sr1. - Graphical abstract: The A band energy EA of Pb2+ has linear relationship with environmental factor he.

  7. High DNA melting temperature predicts transcription start site location in human and mouse.

    Dineen, David G

    2009-12-01

    The accurate computational prediction of transcription start sites (TSS) in vertebrate genomes is a difficult problem. The physicochemical properties of DNA can be computed in various ways and a many combinations of DNA features have been tested in the past for use as predictors of transcription. We looked in detail at melting temperature, which measures the temperature, at which two strands of DNA separate, considering the cooperative nature of this process. We find that peaks in melting temperature correspond closely to experimentally determined transcription start sites in human and mouse chromosomes. Using melting temperature alone, and with simple thresholding, we can predict TSS with accuracy that is competitive with the most accurate state-of-the-art TSS prediction methods. Accuracy is measured using both experimentally and manually determined TSS. The method works especially well with CpG island containing promoters, but also works when CpG islands are absent. This result is clear evidence of the important role of the physical properties of DNA in the process of transcription. It also points to the importance for TSS prediction methods to include melting temperature as prior information.

  8. NBA-Palm: prediction of palmitoylation site implemented in Naïve Bayes algorithm

    Jin Changjiang

    2006-10-01

    Full Text Available Abstract Background Protein palmitoylation, an essential and reversible post-translational modification (PTM, has been implicated in cellular dynamics and plasticity. Although numerous experimental studies have been performed to explore the molecular mechanisms underlying palmitoylation processes, the intrinsic feature of substrate specificity has remained elusive. Thus, computational approaches for palmitoylation prediction are much desirable for further experimental design. Results In this work, we present NBA-Palm, a novel computational method based on Naïve Bayes algorithm for prediction of palmitoylation site. The training data is curated from scientific literature (PubMed and includes 245 palmitoylated sites from 105 distinct proteins after redundancy elimination. The proper window length for a potential palmitoylated peptide is optimized as six. To evaluate the prediction performance of NBA-Palm, 3-fold cross-validation, 8-fold cross-validation and Jack-Knife validation have been carried out. Prediction accuracies reach 85.79% for 3-fold cross-validation, 86.72% for 8-fold cross-validation and 86.74% for Jack-Knife validation. Two more algorithms, RBF network and support vector machine (SVM, also have been employed and compared with NBA-Palm. Conclusion Taken together, our analyses demonstrate that NBA-Palm is a useful computational program that provides insights for further experimentation. The accuracy of NBA-Palm is comparable with our previously described tool CSS-Palm. The NBA-Palm is freely accessible from: http://www.bioinfo.tsinghua.edu.cn/NBA-Palm.

  9. Mapping the active site of vaccinia virus RNA triphosphatase

    The RNA triphosphatase component of vaccinia virus mRNA capping enzyme (the product of the viral D1 gene) belongs to a family of metal-dependent phosphohydrolases that includes the RNA triphosphatases of fungi, protozoa, Chlorella virus, and baculoviruses. The family is defined by two glutamate-containing motifs (A and C) that form the metal-binding site. Most of the family members resemble the fungal and Chlorella virus enzymes, which have a complex active site located within the hydrophilic interior of a topologically closed eight-stranded β barrel (the so-called ''triphosphate tunnel''). Here we queried whether vaccinia virus capping enzyme is a member of the tunnel subfamily, via mutational mapping of amino acids required for vaccinia triphosphatase activity. We identified four new essential side chains in vaccinia D1 via alanine scanning and illuminated structure-activity relationships by conservative substitutions. Our results, together with previous mutational data, highlight a constellation of six acidic and three basic amino acids that likely compose the vaccinia triphosphatase active site (Glu37, Glu39, Arg77, Lys107, Glu126, Asp159, Lys161, Glu192, and Glu194). These nine essential residues are conserved in all vertebrate and invertebrate poxvirus RNA capping enzymes. We discerned no pattern of clustering of the catalytic residues of the poxvirus triphosphatase that would suggest structural similarity to the tunnel proteins (exclusive of motifs A and C). We infer that the poxvirus triphosphatases are a distinct lineage within the metal-dependent RNA triphosphatase family. Their unique active site, which is completely different from that of the host cell's capping enzyme, recommends the poxvirus RNA triphosphatase as a molecular target for antipoxviral drug discovery

  10. Predicting the macroseismic intensity from early radiated P wave energy for on-site earthquake early warning in Italy

    Brondi, P.; Picozzi, M.; Emolo, A.; Zollo, A.; Mucciarelli, M.

    2015-10-01

    Earthquake Early Warning Systems (EEWS) are potentially effective tools for risk mitigation in active seismic regions. The present study explores the possibility of predicting the macroseismic intensity within EEW timeframes using the squared velocity integral (IV2) measured on the early P wave signals, a proxy for the P wave radiated energy of earthquakes. This study shows that IV2 correlates better than the peak displacement measured on P waves with both the peak ground velocity and the Housner Intensity, with the latter being recognized by engineers as a reliable proxy for damage assessment. Therefore, using the strong motion recordings of the Italian Accelerometric Archive, a novel relationship between the parameter IV2 and the macroseismic intensity (IM) has been derived. The validity of this relationship has been assessed using the strong motion recordings of the Istituto Nazionale di Geofisica e Vulcanologia Strong Motion Data and Osservatorio Sismico delle Strutture databases, as well as, in the case of the MW 6, 29 May 2012 Emilia earthquake (Italy), comparing the predicted intensities with the ones observed after a macroseismic survey. Our results indicate that P wave IV2 can become a key parameter for the design of on-site EEWS, capable of proving real-time predictions of the IM at target sites.

  11. Decommissioning and decontamination activity, Gnome Site, Eddy County, New Mexico

    The purpose of this assessment is to present a brief description of the proposed activity and its potential impacts on the environment. This assessment will constitute an evaluation as to whether or not a formal Environmental Statement need be prepared. As background to the proposed activity, Project Gnome was an underground nuclear test conducted in December 1961 as part of the PLOWSHARE Program. The project site is located about 25 miles southeast of Carlsbad, New Mexico. By means of an excavated shaft and tunnel, a 3-kiloton nuclear explosive was emplaced and detonated in a salt bed about 1200 feet below the surface. The uncontaminated rock and salt muck from the original excavation and subsequent contaminated muck and minor construction debris from reentry activities into the nuclear cavity is commingled and stored in a pile near the Gnome/Coach Shaft. Other areas on the site are known to have been contaminated. In 1969, a program was conducted to cleanup and dispose of all surface contamination to whatever depth it occurred in excess of 0.1 mR/hr. Contaminated materials and soil were collected and disposed into the Gnome shaft, which was filled and sealed. Since then, NV has proposed to DOE/HQ much lower criteria for residual radioactive contamination for the Gnome Site. These proposed criteria were to collect and dispose of surficial materials which contain more than 2 x 10-5 microcuries per gram of soil for beta/gamma emitters and 3 x 10-2 microcuries per milliliter of tritium in soil moisture. According to the latest reconnaissance in 1972, low concentrations of Cs-137, Sr-90 and tritium were present at various locations on the site in excess of these proposed guidelines. Other operational areas within the site are suspected of containing radioactive contamination in much lesser volume, which are to be determined by careful probing and monitoring, as described in the next section

  12. Platelet serotonin transporter function predicts default-mode network activity.

    Christian Scharinger

    Full Text Available The serotonin transporter (5-HTT is abundantly expressed in humans by the serotonin transporter gene SLC6A4 and removes serotonin (5-HT from extracellular space. A blood-brain relationship between platelet and synaptosomal 5-HT reuptake has been suggested, but it is unknown today, if platelet 5-HT uptake can predict neural activation of human brain networks that are known to be under serotonergic influence.A functional magnetic resonance study was performed in 48 healthy subjects and maximal 5-HT uptake velocity (Vmax was assessed in blood platelets. We used a mixed-effects multilevel analysis technique (MEMA to test for linear relationships between whole-brain, blood-oxygen-level dependent (BOLD activity and platelet Vmax.The present study demonstrates that increases in platelet Vmax significantly predict default-mode network (DMN suppression in healthy subjects independent of genetic variation within SLC6A4. Furthermore, functional connectivity analyses indicate that platelet Vmax is related to global DMN activation and not intrinsic DMN connectivity.This study provides evidence that platelet Vmax predicts global DMN activation changes in healthy subjects. Given previous reports on platelet-synaptosomal Vmax coupling, results further suggest an important role of neuronal 5-HT reuptake in DMN regulation.

  13. Predicting activity approach based on new atoms similarity kernel function.

    Abu El-Atta, Ahmed H; Moussa, M I; Hassanien, Aboul Ella

    2015-07-01

    Drug design is a high cost and long term process. To reduce time and costs for drugs discoveries, new techniques are needed. Chemoinformatics field implements the informational techniques and computer science like machine learning and graph theory to discover the chemical compounds properties, such as toxicity or biological activity. This is done through analyzing their molecular structure (molecular graph). To overcome this problem there is an increasing need for algorithms to analyze and classify graph data to predict the activity of molecules. Kernels methods provide a powerful framework which combines machine learning with graph theory techniques. These kernels methods have led to impressive performance results in many several chemoinformatics problems like biological activity prediction. This paper presents a new approach based on kernel functions to solve activity prediction problem for chemical compounds. First we encode all atoms depending on their neighbors then we use these codes to find a relationship between those atoms each other. Then we use relation between different atoms to find similarity between chemical compounds. The proposed approach was compared with many other classification methods and the results show competitive accuracy with these methods. PMID:26117822

  14. Predictive Active Set Selection Methods for Gaussian Processes

    Henao, Ricardo; Winther, Ole

    2012-01-01

    We propose an active set selection framework for Gaussian process classification for cases when the dataset is large enough to render its inference prohibitive. Our scheme consists of a two step alternating procedure of active set update rules and hyperparameter optimization based upon marginal...... active set parameters that directly control its complexity. We also provide both theoretical and empirical support for our active set selection strategy being a good approximation of a full Gaussian process classifier. Our extensive experiments show that our approach can compete with state...... likelihood maximization. The active set update rules rely on the ability of the predictive distributions of a Gaussian process classifier to estimate the relative contribution of a datapoint when being either included or removed from the model. This means that we can use it to include points with potentially...

  15. Methodology for contaminated sites of military activity territories restoration

    Major part of Eastern Europe countries meet environmental problems related to sites of military activity. Major part of these sites is characterised with degradation of natural landscapes and contamination of geological environment with toxic and hazardous waste representing actual and potential danger for population and environment. Actual danger is caused with localisation of toxic waste, hazardous materials and waste which are preventing normal land use. Potential danger is related to successive dispersion of contamination in biosphere as well as origin of new derivatives and products having toxic and hazardous properties. The list of such sites and objects comprises bases of land, air and naval forces. These objects include a network of infrastructures: storages of fuels and lubricants (surface, underground), filling stations, pipe lines, reparation stations, garages, decontamination stations, underground storages of different purposes, depots (for ammunition, chemical products), hospitals, constructions, firing grounds (tank, artillery, aircraft bombing etc.) and waste disposal sites. Special programs aimed at military industries and bases contaminated sites remediation have been carrying out in developed countries (USA, United Kingdom, Germany etc.). This experience was used in the frames of joint programs having been founded in several countries of Central and Eastern Europe (Chesh Republic, Slovakia, Lithuania etc.). (author)

  16. Active sites in char gasification: Final technical report

    Wojtowicz, M.; Lilly, W.D.; Perkins, M.T.; Hradil, G.; Calo, J.M.; Suuberg, E.M.

    1987-09-01

    Among the key variables in the design of gasifiers and combustors is the reactivity of the chars which must be gasified or combusted. Significant loss of unburned char is unacceptable in virtually any process; the provision of sufficient residence time for complete conversion is essential. A very wide range of reactivities are observed, depending upon the nature of the char in a process. The current work focuses on furthering the understanding of gasification reactivities of chars. It has been well established that the reactivity of char to gasification generally depends upon three principal factors: (1) the concentration of ''active sites'' in the char; (2) mass transfer within the char; and (3) the type and concentration of catalytic impurities in the char. The present study primarily addresses the first factor. The subject of this research is the origin, nature, and fate of active sites in chars derived from parent hydrocarbons with coal-like structure. The nature and number of the active sites and their reactivity towards oxygen are examined in ''model'' chars derived from phenol-formaldehyde type resins. How the active sites are lost by the process of thermal annealing during heat treatment of chars are studied, and actual rate for the annealing process is derived. Since intrinsic char reactivities are of primary interest in the present study, a fair amount of attention was given to the model char synthesis and handling so that the effect of catalytic impurities and oxygen-containing functional groups in the chemical structure of the material were minimized, if not completely eliminated. The project would not be considered complete without comparing characteristic features of synthetic chars with kinetic behavior exhibited by natural chars, including coal chars.

  17. Exploiting Innocuous Activity for Correlating Users Across Sites

    Goga, Oana; Lei, Howard; Parthasarathi, Sree Hari Krishnan; Friedland, Gerald; Sommer, Robin; Teixeira, Renata

    2013-01-01

    International audience We study how potential attackers can identify accounts on different social network sites that all belong to the same user, exploiting only innocuous activity that inherently comes with posted content. We examine three specific features on Yelp, Flickr, and Twitter: the geo-location attached to a user's posts, the timestamp of posts, and the user's writing style as captured by language models. We show that among these three features the location of posts is the most po...

  18. The purification of affinity-labelled active-site peptides

    The isolation of the labelled peptide from the protein digest, following the affinity labelling of the active sites of enzymes or antibodies, is described. Single-step affinity chromatography utilises the affinity of the native enzymes or antibody for the ligand used to label the same protein. The labelled peptide is the only one in the digest that displays affinity for the immobilised protein and can be released with eluants that dissociate the protein-ligand complex. (Auth.)

  19. Brownian aggregation rate of colloid particles with several active sites

    We theoretically analyze the aggregation kinetics of colloid particles with several active sites. Such particles (so-called “patchy particles”) are well known as chemically anisotropic reactants, but the corresponding rate constant of their aggregation has not yet been established in a convenient analytical form. Using kinematic approximation for the diffusion problem, we derived an analytical formula for the diffusion-controlled reaction rate constant between two colloid particles (or clusters) with several small active sites under the following assumptions: the relative translational motion is Brownian diffusion, and the isotropic stochastic reorientation of each particle is Markovian and arbitrarily correlated. This formula was shown to produce accurate results in comparison with more sophisticated approaches. Also, to account for the case of a low number of active sites per particle we used Monte Carlo stochastic algorithm based on Gillespie method. Simulations showed that such discrete model is required when this number is less than 10. Finally, we applied the developed approach to the simulation of immunoagglutination, assuming that the formed clusters have fractal structure

  20. Prediction of functional sites based on the fuzzy oil drop model.

    Michał Bryliński; Katarzyna Prymula; Wiktor Jurkowski; Marek Kochańczyk; Ewa Stawowczyk; Leszek Konieczny; Irena Roterman

    2007-01-01

    A description of many biological processes requires knowledge of the 3-D structure of proteins and, in particular, the defined active site responsible for biological function. Many proteins, the genes of which have been identified as the result of human genome sequencing, and which were synthesized experimentally, await identification of their biological activity. Currently used methods do not always yield satisfactory results, and new algorithms need to be developed to recognize the localiza...

  1. Prediction of Functional Sites Based on the Fuzzy Oil Drop Model

    Bryliński, Michał; Prymula, Katarzyna; Jurkowski, Wiktor; Kochańczyk, Marek; Stawowczyk, Ewa; Konieczny, Leszek; Roterman, Irena

    2007-01-01

    A description of many biological processes requires knowledge of the 3-D structure of proteins and, in particular, the defined active site responsible for biological function. Many proteins, the genes of which have been identified as the result of human genome sequencing, and which were synthesized experimentally, await identification of their biological activity. Currently used methods do not always yield satisfactory results, and new algorithms need to be developed to recognize the localiza...

  2. Site characterization techniques used in environmental remediation activities

    As a result of decades of nuclear energy research, weapons production, as well as ongoing operations, a significant amount of radioactive contamination has occurred throughout the United States Department of Energy (DOE) complex. DOE facility are in the process of assessing and potentially remediating various sites according to the regulations imposed by a Federal Facility Agreement and Consent order (FFA/CO) between DOE, the state in which the facility is located, and the U.S. Environmental Protection Agency (EPA). In support of these active site remediation efforts, the DOE has devoted considerable resources towards the development of innovative site characterization techniques that support environmental restoration activities. These resources and efforts have focused on various aspects of this complex problem. Research and technology development conducted at the Idaho National Engineering and Environmental Laboratory (INEEL) has resulted in the ability and state-of-the-art equipment required to obtain real-time, densely spaced, in situ characterization data (i.e. detection, speciation, and location) of various radionuclides and contaminants. The Remedial Action Monitoring System (RAMS), developed by the INEEL, consists of enhanced sensor technology, measurement modeling and interpretation techniques, and a suite of deployment platforms which can be interchanged to directly support remedial cleanup and site verification operations. In situ characterization techniques have advanced to the point where they are being actively deployed in support of remedial operations. The INEEL has deployed its system at various DOE and international sites. The deployment of in situ characterization systems during environmental restoration operations has shown that this approach results in several significant benefits versus conventional sampling techniques. A flexible characterization system permits rapid modification to satisfy physical site conditions, available site resources

  3. Rapid and accurate prediction and scoring of water molecules in protein binding sites.

    Gregory A Ross

    Full Text Available Water plays a critical role in ligand-protein interactions. However, it is still challenging to predict accurately not only where water molecules prefer to bind, but also which of those water molecules might be displaceable. The latter is often seen as a route to optimizing affinity of potential drug candidates. Using a protocol we call WaterDock, we show that the freely available AutoDock Vina tool can be used to predict accurately the binding sites of water molecules. WaterDock was validated using data from X-ray crystallography, neutron diffraction and molecular dynamics simulations and correctly predicted 97% of the water molecules in the test set. In addition, we combined data-mining, heuristic and machine learning techniques to develop probabilistic water molecule classifiers. When applied to WaterDock predictions in the Astex Diverse Set of protein ligand complexes, we could identify whether a water molecule was conserved or displaced to an accuracy of 75%. A second model predicted whether water molecules were displaced by polar groups or by non-polar groups to an accuracy of 80%. These results should prove useful for anyone wishing to undertake rational design of new compounds where the displacement of water molecules is being considered as a route to improved affinity.

  4. Platelet Serotonin Transporter Function Predicts Default-Mode Network Activity

    Christian Scharinger; Ulrich Rabl; Christian H. Kasess; Meyer, Bernhard M.; Tina Hofmaier; Kersten Diers; Lucie Bartova; Gerald Pail; Wolfgang Huf; Zeljko Uzelac; Beate Hartinger; Klaudius Kalcher; Thomas Perkmann; Helmuth Haslacher; Andreas Meyer-Lindenberg

    2014-01-01

    Background The serotonin transporter (5-HTT) is abundantly expressed in humans by the serotonin transporter gene SLC6A4 and removes serotonin (5-HT) from extracellular space. A blood-brain relationship between platelet and synaptosomal 5-HT reuptake has been suggested, but it is unknown today, if platelet 5-HT uptake can predict neural activation of human brain networks that are known to be under serotonergic influence. Methods A functional magnetic resonance study was performed in 48 healthy...

  5. Neural activity during encoding predicts false memories created by misinformation

    Okado, Yoko; Stark, Craig E.L.

    2005-01-01

    False memories are often demonstrated using the misinformation paradigm, in which a person's recollection of a witnessed event is altered after exposure to misinformation about the event. The neural basis of this phenomenon, however, remains unknown. We used fMRI to investigate encoding processes during the viewing of an event and misinformation to see whether neural activity during either encoding phase could predict what would be remembered. fMRI data were collected as participants studied ...

  6. Mathematical models for predicting indoor air quality from smoking activity.

    Ott, W R

    1999-01-01

    Much progress has been made over four decades in developing, testing, and evaluating the performance of mathematical models for predicting pollutant concentrations from smoking in indoor settings. Although largely overlooked by the regulatory community, these models provide regulators and risk assessors with practical tools for quantitatively estimating the exposure level that people receive indoors for a given level of smoking activity. This article reviews the development of the mass balanc...

  7. Resource assurance predicts specialist and generalist bee activity in drought

    Minckley, Robert L.; Roulston, T'ai H.; Williams, Neal M.

    2013-01-01

    Many short-lived desert organisms remain in diapause during drought. Theoretically, the cues desert species use to continue diapause through drought should differ depending on the availability of critical resources, but the unpredictability and infrequent occurrence of climate extremes and reduced insect activity during such events make empirical tests of this prediction difficult. An intensive study of a diverse bee–plant community through a drought event found that bee specialists of a drou...

  8. Seismic activity parameters of the Finnish potential repository sites

    Posiva Oy has started a project for estimating the possible earthquake induced rock movements on the deposition holes containing canisters of spent nuclear fuel. These estimates will be made for the four investigation sites, Romuvaara, Kivetty, Olkiluoto and Haestholmen. This study deals with the current and future seismicity associated with the above mentioned sites. Seismic belts that participate the seismic behaviour of the studied sites have been identified and the magnitude-frequency distributions of these belts have been estimated. The seismic activity parameters of the sites have been deduced from the characteristics of the seismic belts in order to forecast the seismicity during the next 100,000 years. The report discusses the possible earthquakes induced by future glaciation. The seismic interpretation seems to indicate that the previous postglacial faults in Finnish Lapland have been generated in compressional environment. The orientation of the rather uniform compression has been NW-SE, which coincide with the current stress field. It seems that, although the impact of postglacial crustal rebound must have been significant, the impact of plate tectonics has been dominant. A major assumption of this study has been that future seismicity will generally resemble the current seismicity. However, when the postglacial seismicity is concerned, the magnitude-frequency distribution is likely different and the expected maximum magnitude will be higher. Maximum magnitudes of future postglacial earthquakes have been approximated by strain release examinations. Seismicity has been examined within the framework of the lineament maps, in order to associate the future significant earthquakes with active fault zones in the vicinity of the potential repository sites. (orig.)

  9. Seismic activity parameters of the Finnish potential repository sites

    Saari, J. [Fortum Engineering Oy, Vantaa (Finland)

    2000-10-01

    Posiva Oy has started a project for estimating the possible earthquake induced rock movements on the deposition holes containing canisters of spent nuclear fuel. These estimates will be made for the four investigation sites, Romuvaara, Kivetty, Olkiluoto and Haestholmen. This study deals with the current and future seismicity associated with the above mentioned sites. Seismic belts that participate the seismic behaviour of the studied sites have been identified and the magnitude-frequency distributions of these belts have been estimated. The seismic activity parameters of the sites have been deduced from the characteristics of the seismic belts in order to forecast the seismicity during the next 100,000 years. The report discusses the possible earthquakes induced by future glaciation. The seismic interpretation seems to indicate that the previous postglacial faults in Finnish Lapland have been generated in compressional environment. The orientation of the rather uniform compression has been NW-SE, which coincide with the current stress field. It seems that, although the impact of postglacial crustal rebound must have been significant, the impact of plate tectonics has been dominant. A major assumption of this study has been that future seismicity will generally resemble the current seismicity. However, when the postglacial seismicity is concerned, the magnitude-frequency distribution is likely different and the expected maximum magnitude will be higher. Maximum magnitudes of future postglacial earthquakes have been approximated by strain release examinations. Seismicity has been examined within the framework of the lineament maps, in order to associate the future significant earthquakes with active fault zones in the vicinity of the potential repository sites. (orig.)

  10. A homology-based pipeline for global prediction of post-translational modification sites

    Chen, Xiang; Shi, Shao-Ping; Xu, Hao-Dong; Suo, Sheng-Bao; Qiu, Jian-Ding

    2016-05-01

    The pathways of protein post-translational modifications (PTMs) have been shown to play particularly important roles for almost any biological process. Identification of PTM substrates along with information on the exact sites is fundamental for fully understanding or controlling biological processes. Alternative computational strategies would help to annotate PTMs in a high-throughput manner. Traditional algorithms are suited for identifying the common organisms and tissues that have a complete PTM atlas or extensive experimental data. While annotation of rare PTMs in most organisms is a clear challenge. In this work, to this end we have developed a novel homology-based pipeline named PTMProber that allows identification of potential modification sites for most of the proteomes lacking PTMs data. Cross-promotion E-value (CPE) as stringent benchmark has been used in our pipeline to evaluate homology to known modification sites. Independent-validation tests show that PTMProber achieves over 58.8% recall with high precision by CPE benchmark. Comparisons with other machine-learning tools show that PTMProber pipeline performs better on general predictions. In addition, we developed a web-based tool to integrate this pipeline at http://bioinfo.ncu.edu.cn/PTMProber/index.aspx. In addition to pre-constructed prediction models of PTM, the website provides an extensional functionality to allow users to customize models.

  11. The Prediction of Calpain Cleavage Sites with the mRMR and IFS Approaches

    Wenyi Zhang

    2013-01-01

    Full Text Available Calpains are an important family of the Ca2+-dependent cysteine proteases which catalyze the limited proteolysis of many specific substrates. Calpains play crucial roles in basic physiological and pathological processes, and identification of the calpain cleavage sites may facilitate the understanding of the molecular mechanisms and biological function. But traditional experiment approaches to predict the sites are accurate, and are always labor-intensive and time-consuming. Thus, it is common to see that computational methods receive increasing attention due to their convenience and fast speed in recent years. In this study, we develop a new predictor based on the support vector machine (SVM with the maximum relevance minimum redundancy (mRMR method followed by incremental feature selection (IFS. And we concern the feature of physicochemical/biochemical properties, sequence conservation, residual disorder, secondary structure, and solvent accessibility to represent the calpain cleavage sites. Experimental results show that the performance of our predictor is better than several other state-of- the-art predictors, whose average prediction accuracy is 79.49%, sensitivity is 62.31%, and specificity is 88.12%. Since user-friendly and publicly accessible web servers represent the future direction for developing practically more useful predictors, here we have provided a web-server for the method presented in this paper.

  12. Prediction of TF target sites based on atomistic models of protein-DNA complexes

    Collado-Vides Julio

    2008-10-01

    Full Text Available Abstract Background The specific recognition of genomic cis-regulatory elements by transcription factors (TFs plays an essential role in the regulation of coordinated gene expression. Studying the mechanisms determining binding specificity in protein-DNA interactions is thus an important goal. Most current approaches for modeling TF specific recognition rely on the knowledge of large sets of cognate target sites and consider only the information contained in their primary sequence. Results Here we describe a structure-based methodology for predicting sequence motifs starting from the coordinates of a TF-DNA complex. Our algorithm combines information regarding the direct and indirect readout of DNA into an atomistic statistical model, which is used to estimate the interaction potential. We first measure the ability of our method to correctly estimate the binding specificities of eight prokaryotic and eukaryotic TFs that belong to different structural superfamilies. Secondly, the method is applied to two homology models, finding that sampling of interface side-chain rotamers remarkably improves the results. Thirdly, the algorithm is compared with a reference structural method based on contact counts, obtaining comparable predictions for the experimental complexes and more accurate sequence motifs for the homology models. Conclusion Our results demonstrate that atomic-detail structural information can be feasibly used to predict TF binding sites. The computational method presented here is universal and might be applied to other systems involving protein-DNA recognition.

  13. LIGSITEcsc: predicting ligand binding sites using the Connolly surface and degree of conservation

    Schroeder Michael

    2006-09-01

    Full Text Available Abstract Background Identifying pockets on protein surfaces is of great importance for many structure-based drug design applications and protein-ligand docking algorithms. Over the last ten years, many geometric methods for the prediction of ligand-binding sites have been developed. Results We present LIGSITEcsc, an extension and implementation of the LIGSITE algorithm. LIGSITEcsc is based on the notion of surface-solvent-surface events and the degree of conservation of the involved surface residues. We compare our algorithm to four other approaches, LIGSITE, CAST, PASS, and SURFNET, and evaluate all on a dataset of 48 unbound/bound structures and 210 bound-structures. LIGSITEcsc performs slightly better than the other tools and achieves a success rate of 71% and 75%, respectively. Conclusion The use of the Connolly surface leads to slight improvements, the prediction re-ranking by conservation to significant improvements of the binding site predictions. A web server for LIGSITEcsc and its source code is available at scoppi.biotec.tu-dresden.de/pocket.

  14. Sequence-based prediction of protein-peptide binding sites using support vector machine.

    Taherzadeh, Ghazaleh; Yang, Yuedong; Zhang, Tuo; Liew, Alan Wee-Chung; Zhou, Yaoqi

    2016-05-15

    Protein-peptide interactions are essential for all cellular processes including DNA repair, replication, gene-expression, and metabolism. As most protein-peptide interactions are uncharacterized, it is cost effective to investigate them computationally as the first step. All existing approaches for predicting protein-peptide binding sites, however, are based on protein structures despite the fact that the structures for most proteins are not yet solved. This article proposes the first machine-learning method called SPRINT to make Sequence-based prediction of Protein-peptide Residue-level Interactions. SPRINT yields a robust and consistent performance for 10-fold cross validations and independent test. The most important feature is evolution-generated sequence profiles. For the test set (1056 binding and non-binding residues), it yields a Matthews' Correlation Coefficient of 0.326 with a sensitivity of 64% and a specificity of 68%. This sequence-based technique shows comparable or more accurate than structure-based methods for peptide-binding site prediction. SPRINT is available as an online server at: http://sparks-lab.org/. © 2016 Wiley Periodicals, Inc. PMID:26833816

  15. Prefrontal activity predicts monkeys' decisions during an auditory category task

    Jung Hoon Lee

    2009-06-01

    Full Text Available The neural correlates that relate auditory categorization to aspects of goal-directed behavior, such as decision-making, are not well understood. Since the prefrontal cortex plays an important role in executive function and the categorization of auditory objects, we hypothesized that neural activity in the prefrontal cortex (PFC should predict an animal's behavioral reports (decisions during a category task. To test this hypothesis, we tested PFC activity that was recorded while monkeys categorized human spoken words (Russ et al., 2008b. We found that activity in the ventrolateral PFC, on average, correlated best with the monkeys' choices than with the auditory stimuli. This finding demonstrates a direct link between PFC activity and behavioral choices during a non-spatial auditory task.

  16. Oxygen reduction and evolution at single-metal active sites

    Calle-Vallejo, F.; Martínez, J.I.; García Lastra, Juan Maria;

    2013-01-01

    A worldwide spread of clean technologies such as low-temperature fuel cells and electrolyzers depends strictly on their technical reliability and economic affordability. Currently, both conditions are hardly fulfilled mainly due to the same reason: the oxygen electrode, which has large overpotent......A worldwide spread of clean technologies such as low-temperature fuel cells and electrolyzers depends strictly on their technical reliability and economic affordability. Currently, both conditions are hardly fulfilled mainly due to the same reason: the oxygen electrode, which has large...... overpotentials and is made of precious materials. A possible solution is the use of non-noble electrocatalysts with single-metal active sites. Here, on the basis of DFT calculations of adsorbed intermediates and a thermodynamic analysis, we compare the oxygen reduction (ORR) and evolution (OER) activities of...... functionalized graphitic materials and gas-phase porphyrins with late transition metals. We find that both kinds of materials follow approximately the same activity trends, and active sites with transition metals from groups 7 to 9 may be good ORR and OER electrocatalysts. However, spin analyses show more...

  17. HDAC Inhibitors without an Active Site Zn2+-Binding Group

    Vickers, Chris J.; Olsen, Christian Adam; Leman, Luke J.;

    2012-01-01

    Natural and synthetic histone deacetylase (HDAC) inhibitors generally derive their strong binding affinity and high potency from a key functional group that binds to the Zn2+ ion within the enzyme active site. However, this feature is also thought to carry the potential liability of undesirable off......-target interactions with other metalloenzymes. As a step toward mitigating this issue, here, we describe the design, synthesis, and structure−activity characterizations of cyclic α3β-tetrapeptide HDAC inhibitors that lack the presumed indispensable Zn2+-binding group. The lead compounds (e.g., 15 and 26) display good...... potency against class 1 HDACs and are active in tissue culture against various human cancer cell lines. Importantly, enzymological analysis of 26 indicates that the cyclic α3β-tetrapeptide is a fast-on/ off competitive inhibitor of HDACs 1−3 with Ki values of 49, 33, and 37 nM, respectively. Our proof...

  18. Big-Five Personality Prediction Based on User Behaviors at Social Network Sites

    Bai, Shuotian; Cheng, Li

    2012-01-01

    Many customer services are already available at Social Network Sites (SNSs), including user recommendation and media interaction, to name a few. There are strong desires to provide online users more dedicated and personalized services that fit into individual's need, usually strongly depending on the inner personalities of the user. However, little has been done to conduct proper psychological analysis, crucial for explaining the user's outer behaviors from their inner personality. In this paper, we propose an approach that intends to facilitate this line of research by directly predicting the so called Big-Five Personality from user's SNS behaviors. Comparing to the conventional inventory-based psychological analysis, we demonstrate via experimental studies that users' personalities can be predicted with reasonable precision based on their online behaviors. Except for proving some former behavior-personality correlation results, our experiments show that extraversion is positively related to one's status rep...

  19. Sequence-based prediction of protein-protein interaction sites with L1-logreg classifier.

    Dhole, Kaustubh; Singh, Gurdeep; Pai, Priyadarshini P; Mondal, Sukanta

    2014-05-01

    Protein-protein interactions are of central importance for virtually every process in a living cell. Information about the interaction sites in proteins improves our understanding of disease mechanisms and can provide the basis for new therapeutic approaches. Since a multitude of unique residue-residue contacts facilitate the interactions, protein-protein interaction sites prediction has become one of the most important and challenging problems of computational biology. Although much progress in this field has been reported, this problem is yet to be satisfactorily solved. Here, a novel method (LORIS: L1-regularized LOgistic Regression based protein-protein Interaction Sites predictor) is proposed, that identifies interaction residues, using sequence features and is implemented via the L1-logreg classifier. Results show that LORIS is not only quite effective, but also, performs better than existing state-of-the art methods. LORIS, available as standalone package, can be useful for facilitating drug-design and targeted mutation related studies, which require a deeper knowledge of protein interactions sites. PMID:24486250

  20. Prediction of pollution into ore bearing aquifer from ISL-site

    Outcomes of present mineralogical investigations explain some phenomena observed in previous sorption experiences. First of all they elucidate cutback of filtration coefficients of sediments exposed under pollution process as granulometric fractions of these permeable sediments decreased in its weight ratio in according to impermeable ones. Then sorption graphics are explained by chemical and mineralogical changes in experienced substance. Explores made diagnoses and estimation about 45 authigenous and technogenous minerals playing the essential role in the process of mass transfer of uranium and polluted components in ISL-sites. They are considered in all basic fractions of studied sediments. Bright peculiarities are noticed for gravel and coarse sands, which went to pieces as a result of dilution or decomposition of its cement. Mineral composition of clayey fraction also significantly changed after pollution process. Steep lost of weight of fraction 0.005-0.001mm consisted with partial decomposition of clayey minerals basically of montmorillonite. These investigations show also that ones of the main minerals playing such the essential role are sorptive such as silica, silica gel, common opal, opal-CT, noble opal, allophane, montmorillonite and zeolite minerals. In conclusion the given work shows some filtration properties of aquifer in an ISL-site and predicts the spread of a possible pollution for ISL-site to environment. The extension of pollution could be more one-two dimension of affected by ISL-process. The prediction would be exact if the previous investigation included the desorptive characteristics and sorptive data depending on temperature and pressure. Current investigations continued pervious ones after which some inexplicable matters of migration of contaminated halo from an ISL-polygon are as follows: Identification and specification of all minerals outside ISL-polygon; Calculation of mineral balance for contaminated sites; Specification of flow

  1. Caspase cleavage sites in the human proteome: CaspDB, a database of predicted substrates.

    Sonu Kumar

    Full Text Available Caspases are enzymes belonging to a conserved family of cysteine-dependent aspartic-specific proteases that are involved in vital cellular processes and play a prominent role in apoptosis and inflammation. Determining all relevant protein substrates of caspases remains a challenging task. Over 1500 caspase substrates have been discovered in the human proteome according to published data and new substrates are discovered on a daily basis. To aid the discovery process we developed a caspase cleavage prediction method using the recently published curated MerCASBA database of experimentally determined caspase substrates and a Random Forest classification method. On both internal and external test sets, the ranking of predicted cleavage positions is superior to all previously developed prediction methods. The in silico predicted caspase cleavage positions in human proteins are available from a relational database: CaspDB. Our database provides information about potential cleavage sites in a verified set of all human proteins collected in Uniprot and their orthologs, allowing for tracing of cleavage motif conservation. It also provides information about the positions of disease-annotated single nucleotide polymorphisms, and posttranslational modifications that may modulate the caspase cleaving efficiency.

  2. IRESPred: Web Server for Prediction of Cellular and Viral Internal Ribosome Entry Site (IRES).

    Kolekar, Pandurang; Pataskar, Abhijeet; Kulkarni-Kale, Urmila; Pal, Jayanta; Kulkarni, Abhijeet

    2016-01-01

    Cellular mRNAs are predominantly translated in a cap-dependent manner. However, some viral and a subset of cellular mRNAs initiate their translation in a cap-independent manner. This requires presence of a structured RNA element, known as, Internal Ribosome Entry Site (IRES) in their 5' untranslated regions (UTRs). Experimental demonstration of IRES in UTR remains a challenging task. Computational prediction of IRES merely based on sequence and structure conservation is also difficult, particularly for cellular IRES. A web server, IRESPred is developed for prediction of both viral and cellular IRES using Support Vector Machine (SVM). The predictive model was built using 35 features that are based on sequence and structural properties of UTRs and the probabilities of interactions between UTR and small subunit ribosomal proteins (SSRPs). The model was found to have 75.51% accuracy, 75.75% sensitivity, 75.25% specificity, 75.75% precision and Matthews Correlation Coefficient (MCC) of 0.51 in blind testing. IRESPred was found to perform better than the only available viral IRES prediction server, VIPS. The IRESPred server is freely available at http://bioinfo.net.in/IRESPred/. PMID:27264539

  3. Caspase cleavage sites in the human proteome: CaspDB, a database of predicted substrates.

    Kumar, Sonu; van Raam, Bram J; Salvesen, Guy S; Cieplak, Piotr

    2014-01-01

    Caspases are enzymes belonging to a conserved family of cysteine-dependent aspartic-specific proteases that are involved in vital cellular processes and play a prominent role in apoptosis and inflammation. Determining all relevant protein substrates of caspases remains a challenging task. Over 1500 caspase substrates have been discovered in the human proteome according to published data and new substrates are discovered on a daily basis. To aid the discovery process we developed a caspase cleavage prediction method using the recently published curated MerCASBA database of experimentally determined caspase substrates and a Random Forest classification method. On both internal and external test sets, the ranking of predicted cleavage positions is superior to all previously developed prediction methods. The in silico predicted caspase cleavage positions in human proteins are available from a relational database: CaspDB. Our database provides information about potential cleavage sites in a verified set of all human proteins collected in Uniprot and their orthologs, allowing for tracing of cleavage motif conservation. It also provides information about the positions of disease-annotated single nucleotide polymorphisms, and posttranslational modifications that may modulate the caspase cleaving efficiency. PMID:25330111

  4. Current activities handbook: formerly utilized sites remedial action program

    This volume is one of a series produced under contract with the DOE, by Politech Corporation to develop a legislative and regulatory data base to assist the FUSRAP management in addressing the institutional and socioeconomic issues involved in carrying out the Formerly Utilized Sites Remedial Action Program. This Information Handbook series contains information about all relevant government agencies at the Federal and state levels, the pertinent programs they administer, each affected state legislature, and current Federal and state legislative and regulatory initiatives. This volume is a compilation of information about the activities each of the thirteen state legislatures potentially affected by the Formerly Utilized Sites Remedial Action Program. It contains a description of the state legislative procedural rules and a schedule of each legislative session; a summary of pending relevant legislation; the name and telephone number of legislative and state agency contacts; and the full text of all bills identified

  5. Current activities handbook: formerly utilized sites remedial action program

    None

    1981-02-27

    This volume is one of a series produced under contract with the DOE, by Politech Corporation to develop a legislative and regulatory data base to assist the FUSRAP management in addressing the institutional and socioeconomic issues involved in carrying out the Formerly Utilized Sites Remedial Action Program. This Information Handbook series contains information about all relevant government agencies at the Federal and state levels, the pertinent programs they administer, each affected state legislature, and current Federal and state legislative and regulatory initiatives. This volume is a compilation of information about the activities each of the thirteen state legislatures potentially affected by the Formerly Utilized Sites Remedial Action Program. It contains a description of the state legislative procedural rules and a schedule of each legislative session; a summary of pending relevant legislation; the name and telephone number of legislative and state agency contacts; and the full text of all bills identified.

  6. Overview of the activities carried out at the FEBEX site

    Missana, T.; Buil, B.; Garralon, A.; Gomez, P. [CIEMAT, Dept. de Medioambien te, 28040 Madrid (Spain); Perez-Estaun, A.; Carbonell, R. [Inst. Jaume Almera, CSIC (Spain); Suso, J.; Carretero, G.; Bueno, J.; Martinez, L. [AITEMIN (Spain) ; Hernan, P. [ENRESA (Spain)

    2007-06-15

    One of the main aim of WP 4.1 and 4.2 is to study solute migration mechanisms in crystalline host-rock in realistic conditions. Many organisations are participating in a joint study that is being performed in the FEBEX gallery (NAGRA's Grimsel Test Site, GTS, Switzerland). The FEBEX experiment reproduces at a real scale a high-level waste repository in granite and was installed more than 9 years ago. At moment, it represents the most realistic environment where the processes affecting radionuclide migration from the bentonite to granite can be studied. This paper summarises the main activities carried out at the FEBEX site during the second year of the project.

  7. Predictive Models for Halogen-bond Basicity of Binding Sites of Polyfunctional Molecules.

    Glavatskikh, Marta; Madzhidov, Timur; Solov'ev, Vitaly; Marcou, Gilles; Horvath, Dragos; Graton, Jérôme; Le Questel, Jean-Yves; Varnek, Alexandre

    2016-02-01

    Halogen bonding (XB) strength assesses the ability of an electron-enriched group to be involved in complexes with polarizable electrophilic halogenated or diatomic halogen molecules. Here, we report QSPR models of XB of particular relevance for an efficient screening of large sets of compounds. The basicity is described by pKBI2 , the decimal logarithm of the experimental 1 : 1 (B : I2 ) complexation constant K of organic compounds (B) with diiodine (I2 ) as a reference halogen-bond donor in alkanes at 298 K. Modeling involved ISIDA fragment descriptors, using SVM and MLR methods on a set of 598 organic compounds. Developed models were then challenged to make predictions for an external test set of 11 polyfunctional compounds for which unambiguous assignment of the measured effective complexation constant to specific groups out of the putative acceptor sites is not granted. At this stage, developed models were used to predict pKBI2 of all putative acceptor sites, followed by an estimation of the predicted effective complexation constant using the ChemEqui program. The best consensus models perform well both in cross-validation (root mean squared error RMSE=0.39-0.47 logKBI2 units) and external predictions (RMSE=0.49). The SVM models are implemented on our website (http://infochim.u-strasbg.fr/webserv/VSEngine.html) together with the estimation of their applicability domain and an automatic detection of potential halogen-bond acceptor atoms. PMID:27491792

  8. A Cascade Random Forests Algorithm for Predicting Protein-Protein Interaction Sites.

    Wei, Zhi-Sen; Yang, Jing-Yu; Shen, Hong-Bin; Yu, Dong-Jun

    2015-10-01

    Protein-protein interactions exist ubiquitously and play important roles in the life cycles of living cells. The interaction sites (residues) are essential to understanding the underlying mechanisms of protein-protein interactions. Previous research has demonstrated that the accurate identification of protein-protein interaction sites (PPIs) is helpful for developing new therapeutic drugs because many drugs will interact directly with those residues. Because of its significant potential in biological research and drug development, the prediction of PPIs has become an important topic in computational biology. However, a severe data imbalance exists in the PPIs prediction problem, where the number of the majority class samples (non-interacting residues) is far larger than that of the minority class samples (interacting residues). Thus, we developed a novel cascade random forests algorithm (CRF) to address the serious data imbalance that exists in the PPIs prediction problem. The proposed CRF resolves the negative effect of data imbalance by connecting multiple random forests in a cascade-like manner, each of which is trained with a balanced training subset that includes all minority samples and a subset of majority samples using an effective ensemble protocol. Based on the proposed CRF, we implemented a new sequence-based PPIs predictor, called CRF-PPI, which takes the combined features of position-specific scoring matrices, averaged cumulative hydropathy, and predicted relative solvent accessibility as model inputs. Benchmark experiments on both the cross validation and independent validation datasets demonstrated that the proposed CRF-PPI outperformed the state-of-the-art sequence-based PPIs predictors. The source code for CRF-PPI and the benchmark datasets are available online at http://csbio.njust.edu.cn/bioinf/CRF-PPI for free academic use. PMID:26441427

  9. 10 CFR 63.16 - Review of site characterization activities. 2

    2010-01-01

    ... 10 Energy 2 2010-01-01 2010-01-01 false Review of site characterization activities. 2 63.16... site characterization activities. 2 2 In addition to the review of site characterization activities... investigation and site characterization, to allow early identification of potential licensing issues for...

  10. SuccinSite: a computational tool for the prediction of protein succinylation sites by exploiting the amino acid patterns and properties.

    Hasan, Md Mehedi; Yang, Shiping; Zhou, Yuan; Mollah, Md Nurul Haque

    2016-03-23

    Lysine succinylation is an emerging protein post-translational modification, which plays an important role in regulating the cellular processes in both eukaryotic and prokaryotic cells. However, the succinylation modification site is particularly difficult to detect because the experimental technologies used are often time-consuming and costly. Thus, an accurate computational method for predicting succinylation sites may help researchers towards designing their experiments and to understand the molecular mechanism of succinylation. In this study, a novel computational tool termed SuccinSite has been developed to predict protein succinylation sites by incorporating three sequence encodings, i.e., k-spaced amino acid pairs, binary and amino acid index properties. Then, the random forest classifier was trained with these encodings to build the predictor. The SuccinSite predictor achieves an AUC score of 0.802 in the 5-fold cross-validation set and performs significantly better than existing predictors on a comprehensive independent test set. Furthermore, informative features and predominant rules (i.e. feature combinations) were extracted from the trained random forest model for an improved interpretation of the predictor. Finally, we also compiled a database covering 4411 experimentally verified succinylation proteins with 12 456 lysine succinylation sites. Taken together, these results suggest that SuccinSite would be a helpful computational resource for succinylation sites prediction. The web-server, datasets, source code and database are freely available at . PMID:26739209

  11. Predicting flow at work: investigating the activities and job characteristics that predict flow states at work.

    Nielsen, Karina; Cleal, Bryan

    2010-04-01

    Flow (a state of consciousness where people become totally immersed in an activity and enjoy it intensely) has been identified as a desirable state with positive effects for employee well-being and innovation at work. Flow has been studied using both questionnaires and Experience Sampling Method (ESM). In this study, we used a newly developed 9-item flow scale in an ESM study combined with a questionnaire to examine the predictors of flow at two levels: the activities (brainstorming, planning, problem solving and evaluation) associated with transient flow states and the more stable job characteristics (role clarity, influence and cognitive demands). Participants were 58 line managers from two companies in Denmark; a private accountancy firm and a public elder care organization. We found that line managers in elder care experienced flow more often than accountancy line managers, and activities such as planning, problem solving, and evaluation predicted transient flow states. The more stable job characteristics included in this study were not, however, found to predict flow at work. PMID:20364915

  12. Identification of covalent active site inhibitors of dengue virus protease.

    Koh-Stenta, Xiaoying; Joy, Joma; Wang, Si Fang; Kwek, Perlyn Zekui; Wee, John Liang Kuan; Wan, Kah Fei; Gayen, Shovanlal; Chen, Angela Shuyi; Kang, CongBao; Lee, May Ann; Poulsen, Anders; Vasudevan, Subhash G; Hill, Jeffrey; Nacro, Kassoum

    2015-01-01

    Dengue virus (DENV) protease is an attractive target for drug development; however, no compounds have reached clinical development to date. In this study, we utilized a potent West Nile virus protease inhibitor of the pyrazole ester derivative class as a chemical starting point for DENV protease drug development. Compound potency and selectivity for DENV protease were improved through structure-guided small molecule optimization, and protease-inhibitor binding interactions were validated biophysically using nuclear magnetic resonance. Our work strongly suggests that this class of compounds inhibits flavivirus protease through targeted covalent modification of active site serine, contrary to an allosteric binding mechanism as previously described. PMID:26677315

  13. Identification of covalent active site inhibitors of dengue virus protease

    Koh-Stenta, Xiaoying; Joy, Joma; Wang, Si Fang; Kwek, Perlyn Zekui; Wee, John Liang Kuan; Wan, Kah Fei; Gayen, Shovanlal; Chen, Angela Shuyi; Kang, CongBao; Lee, May Ann; Poulsen, Anders; Vasudevan, Subhash G; Hill, Jeffrey; Nacro, Kassoum

    2015-01-01

    Dengue virus (DENV) protease is an attractive target for drug development; however, no compounds have reached clinical development to date. In this study, we utilized a potent West Nile virus protease inhibitor of the pyrazole ester derivative class as a chemical starting point for DENV protease drug development. Compound potency and selectivity for DENV protease were improved through structure-guided small molecule optimization, and protease-inhibitor binding interactions were validated biophysically using nuclear magnetic resonance. Our work strongly suggests that this class of compounds inhibits flavivirus protease through targeted covalent modification of active site serine, contrary to an allosteric binding mechanism as previously described. PMID:26677315

  14. Quantitative perturbation-based analysis of gene expression predicts enhancer activity in early Drosophila embryo.

    Sayal, Rupinder; Dresch, Jacqueline M; Pushel, Irina; Taylor, Benjamin R; Arnosti, David N

    2016-01-01

    Enhancers constitute one of the major components of regulatory machinery of metazoans. Although several genome-wide studies have focused on finding and locating enhancers in the genomes, the fundamental principles governing their internal architecture and cis-regulatory grammar remain elusive. Here, we describe an extensive, quantitative perturbation analysis targeting the dorsal-ventral patterning gene regulatory network (GRN) controlled by Drosophila NF-κB homolog Dorsal. To understand transcription factor interactions on enhancers, we employed an ensemble of mathematical models, testing effects of cooperativity, repression, and factor potency. Models trained on the dataset correctly predict activity of evolutionarily divergent regulatory regions, providing insights into spatial relationships between repressor and activator binding sites. Importantly, the collective predictions of sets of models were effective at novel enhancer identification and characterization. Our study demonstrates how experimental dataset and modeling can be effectively combined to provide quantitative insights into cis-regulatory information on a genome-wide scale. PMID:27152947

  15. Prediction of Antifungal Activity of Gemini Imidazolium Compounds

    Łukasz Pałkowski

    2015-01-01

    Full Text Available The progress of antimicrobial therapy contributes to the development of strains of fungi resistant to antimicrobial drugs. Since cationic surfactants have been described as good antifungals, we present a SAR study of a novel homologous series of 140 bis-quaternary imidazolium chlorides and analyze them with respect to their biological activity against Candida albicans as one of the major opportunistic pathogens causing a wide spectrum of diseases in human beings. We characterize a set of features of these compounds, concerning their structure, molecular descriptors, and surface active properties. SAR study was conducted with the help of the Dominance-Based Rough Set Approach (DRSA, which involves identification of relevant features and relevant combinations of features being in strong relationship with a high antifungal activity of the compounds. The SAR study shows, moreover, that the antifungal activity is dependent on the type of substituents and their position at the chloride moiety, as well as on the surface active properties of the compounds. We also show that molecular descriptors MlogP, HOMO-LUMO gap, total structure connectivity index, and Wiener index may be useful in prediction of antifungal activity of new chemical compounds.

  16. Polarizability of the active site of cytochrome c reduces the activation barrier for electron transfer

    Dinpajooh, Mohammadhasan; Martin, Daniel R.; Matyushov, Dmitry V.

    2016-06-01

    Enzymes in biology’s energy chains operate with low energy input distributed through multiple electron transfer steps between protein active sites. The general challenge of biological design is how to lower the activation barrier without sacrificing a large negative reaction free energy. We show that this goal is achieved through a large polarizability of the active site. It is polarized by allowing a large number of excited states, which are populated quantum mechanically by electrostatic fluctuations of the protein and hydration water shells. This perspective is achieved by extensive mixed quantum mechanical/molecular dynamics simulations of the half reaction of reduction of cytochrome c. The barrier for electron transfer is consistently lowered by increasing the number of excited states included in the Hamiltonian of the active site diagonalized along the classical trajectory. We suggest that molecular polarizability, in addition to much studied electrostatics of permanent charges, is a key parameter to consider in order to understand how enzymes work.

  17. Polarizability of the active site of cytochrome c reduces the activation barrier for electron transfer

    Dinpajooh, Mohammadhasan; Martin, Daniel R.; Matyushov, Dmitry V.

    2016-01-01

    Enzymes in biology’s energy chains operate with low energy input distributed through multiple electron transfer steps between protein active sites. The general challenge of biological design is how to lower the activation barrier without sacrificing a large negative reaction free energy. We show that this goal is achieved through a large polarizability of the active site. It is polarized by allowing a large number of excited states, which are populated quantum mechanically by electrostatic fluctuations of the protein and hydration water shells. This perspective is achieved by extensive mixed quantum mechanical/molecular dynamics simulations of the half reaction of reduction of cytochrome c. The barrier for electron transfer is consistently lowered by increasing the number of excited states included in the Hamiltonian of the active site diagonalized along the classical trajectory. We suggest that molecular polarizability, in addition to much studied electrostatics of permanent charges, is a key parameter to consider in order to understand how enzymes work. PMID:27306204

  18. Feature selection for splice site prediction: A new method using EDA-based feature ranking

    Rouzé Pierre

    2004-05-01

    Full Text Available Abstract Background The identification of relevant biological features in large and complex datasets is an important step towards gaining insight in the processes underlying the data. Other advantages of feature selection include the ability of the classification system to attain good or even better solutions using a restricted subset of features, and a faster classification. Thus, robust methods for fast feature selection are of key importance in extracting knowledge from complex biological data. Results In this paper we present a novel method for feature subset selection applied to splice site prediction, based on estimation of distribution algorithms, a more general framework of genetic algorithms. From the estimated distribution of the algorithm, a feature ranking is derived. Afterwards this ranking is used to iteratively discard features. We apply this technique to the problem of splice site prediction, and show how it can be used to gain insight into the underlying biological process of splicing. Conclusion We show that this technique proves to be more robust than the traditional use of estimation of distribution algorithms for feature selection: instead of returning a single best subset of features (as they normally do this method provides a dynamical view of the feature selection process, like the traditional sequential wrapper methods. However, the method is faster than the traditional techniques, and scales better to datasets described by a large number of features.

  19. Predicting success of oligomerized pool engineering (OPEN for zinc finger target site sequences

    Goodwin Mathew J

    2010-11-01

    Full Text Available Abstract Background Precise and efficient methods for gene targeting are critical for detailed functional analysis of genomes and regulatory networks and for potentially improving the efficacy and safety of gene therapies. Oligomerized Pool ENgineering (OPEN is a recently developed method for engineering C2H2 zinc finger proteins (ZFPs designed to bind specific DNA sequences with high affinity and specificity in vivo. Because generation of ZFPs using OPEN requires considerable effort, a computational method for identifying the sites in any given gene that are most likely to be successfully targeted by this method is desirable. Results Analysis of the base composition of experimentally validated ZFP target sites identified important constraints on the DNA sequence space that can be effectively targeted using OPEN. Using alternate encodings to represent ZFP target sites, we implemented Naïve Bayes and Support Vector Machine classifiers capable of distinguishing "active" targets, i.e., ZFP binding sites that can be targeted with a high rate of success, from those that are "inactive" or poor targets for ZFPs generated using current OPEN technologies. When evaluated using leave-one-out cross-validation on a dataset of 135 experimentally validated ZFP target sites, the best Naïve Bayes classifier, designated ZiFOpT, achieved overall accuracy of 87% and specificity+ of 90%, with an ROC AUC of 0.89. When challenged with a completely independent test set of 140 newly validated ZFP target sites, ZiFOpT performance was comparable in terms of overall accuracy (88% and specificity+ (92%, but with reduced ROC AUC (0.77. Users can rank potentially active ZFP target sites using a confidence score derived from the posterior probability returned by ZiFOpT. Conclusion ZiFOpT, a machine learning classifier trained to identify DNA sequences amenable for targeting by OPEN-generated zinc finger arrays, can guide users to target sites that are most likely to function

  20. Metal active site elasticity linked to activation of homocysteine in methionine synthases

    Koutmos, Markos; Pejchal, Robert; Bomer, Theresa M.; Matthews, Rowena G.; Smith, Janet L.; Ludwig, Martha L. (Michigan)

    2008-04-02

    Enzymes possessing catalytic zinc centers perform a variety of fundamental processes in nature, including methyl transfer to thiols. Cobalamin-independent (MetE) and cobalamin-dependent (MetH) methionine synthases are two such enzyme families. Although they perform the same net reaction, transfer of a methyl group from methyltetrahydrofolate to homocysteine (Hcy) to form methionine, they display markedly different catalytic strategies, modular organization, and active site zinc centers. Here we report crystal structures of zinc-replete MetE and MetH, both in the presence and absence of Hcy. Structural investigation of the catalytic zinc sites of these two methyltransferases reveals an unexpected inversion of zinc geometry upon binding of Hcy and displacement of an endogenous ligand in both enzymes. In both cases a significant movement of the zinc relative to the protein scaffold accompanies inversion. These structures provide new information on the activation of thiols by zinc-containing enzymes and have led us to propose a paradigm for the mechanism of action of the catalytic zinc sites in these and related methyltransferases. Specifically, zinc is mobile in the active sites of MetE and MetH, and its dynamic nature helps facilitate the active site conformational changes necessary for thiol activation and methyl transfer.

  1. Perchlorate Reductase Is Distinguished by Active Site Aromatic Gate Residues.

    Youngblut, Matthew D; Tsai, Chi-Lin; Clark, Iain C; Carlson, Hans K; Maglaqui, Adrian P; Gau-Pan, Phonchien S; Redford, Steven A; Wong, Alan; Tainer, John A; Coates, John D

    2016-04-22

    Perchlorate is an important ion on both Earth and Mars. Perchlorate reductase (PcrAB), a specialized member of the dimethylsulfoxide reductase superfamily, catalyzes the first step of microbial perchlorate respiration, but little is known about the biochemistry, specificity, structure, and mechanism of PcrAB. Here we characterize the biophysics and phylogeny of this enzyme and report the 1.86-Å resolution PcrAB complex crystal structure. Biochemical analysis revealed a relatively high perchlorate affinity (Km = 6 μm) and a characteristic substrate inhibition compared with the highly similar respiratory nitrate reductase NarGHI, which has a relatively much lower affinity for perchlorate (Km = 1.1 mm) and no substrate inhibition. Structural analysis of oxidized and reduced PcrAB with and without the substrate analog SeO3 (2-) bound to the active site identified key residues in the positively charged and funnel-shaped substrate access tunnel that gated substrate entrance and product release while trapping transiently produced chlorate. The structures suggest gating was associated with shifts of a Phe residue between open and closed conformations plus an Asp residue carboxylate shift between monodentate and bidentate coordination to the active site molybdenum atom. Taken together, structural and mutational analyses of gate residues suggest key roles of these gate residues for substrate entrance and product release. Our combined results provide the first detailed structural insight into the mechanism of biological perchlorate reduction, a critical component of the chlorine redox cycle on Earth. PMID:26940877

  2. Maxey Flats low-level waste disposal site closure activities

    The Maxey Flats Radioactive Waste Disposal Facility in Fleming County, Kentucky is in the process of being closed. The facility opened for commercial business in the spring of 1963 and received approximately 4.75 million cubic feet of radioactive waste by the time it was closed in December of 1977. During fourteen years of operation approximately 2.5 million curies of by-product material, 240,000 kilograms of source material, and 430 kilograms of special nuclear material were disposed. The Commonwealth purchased the lease hold estate and rights in May 1978 from the operating company. This action was taken to stabilize the facility and prepare it for closure consisting of passive care and monitoring. To prepare the site for closure, a number of remedial activities had to be performed. The remediation activities implemented have included erosion control, surface drainage modifications, installation of a temporary plastic surface cover, leachate removal, analysis, treatment and evaporation, US DOE funded evaporator concentrates solidification project and their on-site disposal in an improved disposal trench with enhanced cover for use in a humid environment situated in a fractured geology, performance evaluation of a grout injection demonstration, USGS subsurface geologic investigation, development of conceptual closure designs, and finally being added to the US EPA National Priority List for remediation and closure under Superfund. 13 references, 3 figures

  3. Identification of covalent active site inhibitors of dengue virus protease

    Koh-Stenta X

    2015-12-01

    Full Text Available Xiaoying Koh-Stenta,1 Joma Joy,1 Si Fang Wang,1 Perlyn Zekui Kwek,1 John Liang Kuan Wee,1 Kah Fei Wan,2 Shovanlal Gayen,1 Angela Shuyi Chen,1 CongBao Kang,1 May Ann Lee,1 Anders Poulsen,1 Subhash G Vasudevan,3 Jeffrey Hill,1 Kassoum Nacro11Experimental Therapeutics Centre, Agency for Science, Technology and Research (A*STAR, Singapore; 2Novartis Institute for Tropical Diseases, Singapore; 3Program in Emerging Infectious Diseases, Duke-NUS Graduate Medical School, SingaporeAbstract: Dengue virus (DENV protease is an attractive target for drug development; however, no compounds have reached clinical development to date. In this study, we utilized a potent West Nile virus protease inhibitor of the pyrazole ester derivative class as a chemical starting point for DENV protease drug development. Compound potency and selectivity for DENV protease were improved through structure-guided small molecule optimization, and protease-inhibitor binding interactions were validated biophysically using nuclear magnetic resonance. Our work strongly suggests that this class of compounds inhibits flavivirus protease through targeted covalent modification of active site serine, contrary to an allosteric binding mechanism as previously described.Keywords: flavivirus protease, small molecule optimization, covalent inhibitor, active site binding, pyrazole ester derivatives

  4. Human glutaminyl cyclase and bacterial zinc aminopeptidase share a common fold and active site

    Misquitta Stephanie A

    2004-02-01

    Full Text Available Abstract Background Glutaminyl cyclase (QC forms the pyroglutamyl residue at the amino terminus of numerous secretory peptides and proteins. We previously proposed the mammalian QC has some features in common with zinc aminopeptidases. We now have generated a structural model for human QC based on the aminopeptidase fold (pdb code 1AMP and mutated the apparent active site residues to assess their role in QC catalysis. Results The structural model proposed here for human QC, deposited in the protein databank as 1MOI, is supported by a variety of fold prediction programs, by the circular dichroism spectrum, and by the presence of the disulfide. Mutagenesis of the six active site residues present in both 1AMP and QC reveal essential roles for the two histidines (140 and 330, QC numbering and the two glutamates (201 and 202, while the two aspartates (159 and 248 appear to play no catalytic role. ICP-MS analysis shows less than stoichiometric zinc (0.3:1 in the purified enzyme. Conclusions We conclude that human pituitary glutaminyl cyclase and bacterial zinc aminopeptidase share a common fold and active site residues. In contrast to the aminopeptidase, however, QC does not appear to require zinc for enzymatic activity.

  5. Integrated Model of DNA Sequence Numerical Representation and Artificial Neural Network for Human Donor and Acceptor Sites Prediction

    Mohammed Abo-Zahhad

    2014-07-01

    Full Text Available Human Genome Project has led to a huge inflow of genomic data. After the completion of human genome sequencing, more and more effort is being put into identification of splicing sites of exons and introns (donor and acceptor sites. These invite bioinformatics to analysis the genome sequences and identify the location of exon and intron boundaries or in other words prediction of splicing sites. Prediction of splice sites in genic regions of DNA sequence is one of the most challenging aspects of gene structure recognition. Over the last two decades, artificial neural networks gradually became one of the essential tools in bioinformatics. In this paper artificial neural networks with different numerical mapping techniques have been employed for building integrated model for splice site prediction in genes. An artificial neural network is trained and then used to find splice sites in human genes. A comparison between different mapping methods using trained neural network in terms of their precision in prediction of donor and acceptor sites will be presented in this paper. Training and measuring performance of neural network are carried out using sequences of the human genome (GRch37/hg19- chr21. Simulation results indicate that using Electron-Ion Interaction Potential numerical mapping method with neural network yields to the best performance in prediction.

  6. Insight into the mechanism of phosphoenolpyruvate mutase catalysis derived from site-directed mutagenesis studies of active site residues.

    Jia, Y; Lu, Z; Huang, K; Herzberg, O; Dunaway-Mariano, D

    1999-10-26

    PEP mutase catalyzes the conversion of phosphoenolpyruvate (PEP) to phosphonopyruvate in biosynthetic pathways leading to phosphonate secondary metabolites. A recent X-ray structure [Huang, K., Li, Z., Jia, Y., Dunaway-Mariano, D., and Herzberg, O. (1999) Structure (in press)] of the Mytilus edulis enzyme complexed with the Mg(II) cofactor and oxalate inhibitor reveals an alpha/beta-barrel backbone-fold housing an active site in which Mg(II) is bound by the two carboxylate groups of the oxalate ligand and the side chain of D85 and, via bridging water molecules, by the side chains of D58, D85, D87, and E114. The oxalate ligand, in turn, interacts with the side chains of R159, W44, and S46 and the backbone amide NHs of G47 and L48. Modeling studies identified two feasible PEP binding modes: model A in which PEP replaces oxalate with its carboxylate group interacting with R159 and its phosphoryl group positioned close to D58 and Mg(II) shifting slightly from its original position in the crystal structure, and model B in which PEP replaces oxalate with its phosphoryl group interacting with R159 and Mg(II) retaining its original position. Site-directed mutagenesis studies of the key mutase active site residues (R159, D58, D85, D87, and E114) were carried out in order to evaluate the catalytic roles predicted by the two models. The observed retention of low catalytic activity in the mutants R159A, D85A, D87A, and E114A, coupled with the absence of detectable catalytic activity in D58A, was interpreted as evidence for model A in which D58 functions in nucleophilic catalysis (phosphoryl transfer), R159 functions in PEP carboxylate group binding, and the carboxylates of D85, D87 and E114 function in Mg(II) binding. These results also provide evidence against model B in which R159 serves to mediate the phosphoryl transfer. A catalytic motif, which could serve both the phosphoryl transfer and the C-C cleavage enzymes of the PEP mutase superfamily, is proposed. PMID:10571990

  7. Active site loop conformation regulates promiscuous activity in a lactonase from Geobacillus kaustophilus HTA426.

    Yu Zhang

    Full Text Available Enzyme promiscuity is a prerequisite for fast divergent evolution of biocatalysts. A phosphotriesterase-like lactonase (PLL from Geobacillus kaustophilus HTA426 (GkaP exhibits main lactonase and promiscuous phosphotriesterase activities. To understand its catalytic and evolutionary mechanisms, we investigated a "hot spot" in the active site by saturation mutagenesis as well as X-ray crystallographic analyses. We found that position 99 in the active site was involved in substrate discrimination. One mutant, Y99L, exhibited 11-fold improvement over wild-type in reactivity (kcat/Km toward the phosphotriesterase substrate ethyl-paraoxon, but showed 15-fold decrease toward the lactonase substrate δ-decanolactone, resulting in a 157-fold inversion of the substrate specificity. Structural analysis of Y99L revealed that the mutation causes a ∼6.6 Å outward shift of adjacent loop 7, which may cause increased flexibility of the active site and facilitate accommodation and/or catalysis of organophosphate substrate. This study provides for the PLL family an example of how the evolutionary route from promiscuity to specificity can derive from very few mutations, which promotes alteration in the conformational adjustment of the active site loops, in turn draws the capacity of substrate binding and activity.

  8. Active site and laminarin binding in glycoside hydrolase family 55.

    Bianchetti, Christopher M; Takasuka, Taichi E; Deutsch, Sam; Udell, Hannah S; Yik, Eric J; Bergeman, Lai F; Fox, Brian G

    2015-05-01

    The Carbohydrate Active Enzyme (CAZy) database indicates that glycoside hydrolase family 55 (GH55) contains both endo- and exo-β-1,3-glucanases. The founding structure in the GH55 is PcLam55A from the white rot fungus Phanerochaete chrysosporium (Ishida, T., Fushinobu, S., Kawai, R., Kitaoka, M., Igarashi, K., and Samejima, M. (2009) Crystal structure of glycoside hydrolase family 55 β-1,3-glucanase from the basidiomycete Phanerochaete chrysosporium. J. Biol. Chem. 284, 10100-10109). Here, we present high resolution crystal structures of bacterial SacteLam55A from the highly cellulolytic Streptomyces sp. SirexAA-E with bound substrates and product. These structures, along with mutagenesis and kinetic studies, implicate Glu-502 as the catalytic acid (as proposed earlier for Glu-663 in PcLam55A) and a proton relay network of four residues in activating water as the nucleophile. Further, a set of conserved aromatic residues that define the active site apparently enforce an exo-glucanase reactivity as demonstrated by exhaustive hydrolysis reactions with purified laminarioligosaccharides. Two additional aromatic residues that line the substrate-binding channel show substrate-dependent conformational flexibility that may promote processive reactivity of the bound oligosaccharide in the bacterial enzymes. Gene synthesis carried out on ∼30% of the GH55 family gave 34 active enzymes (19% functional coverage of the nonredundant members of GH55). These active enzymes reacted with only laminarin from a panel of 10 different soluble and insoluble polysaccharides and displayed a broad range of specific activities and optima for pH and temperature. Application of this experimental method provides a new, systematic way to annotate glycoside hydrolase phylogenetic space for functional properties. PMID:25752603

  9. Ngram time series model to predict activity type and energy cost from wrist, hip and ankle accelerometers: implications of age

    Strath, Scott J; Kate, Rohit J; Keenan, Kevin G; Welch, Whitney A; Swartz, Ann M

    2016-01-01

    To develop and test time series single site and multi-site placement models, we used wrist, hip and ankle processed accelerometer data to estimate energy cost and type of physical activity in adults. Ninety-nine subjects in three age groups (18–39, 40–64, 65 + years) performed 11 activities while wearing three triaxial accelereometers: one each on the non-dominant wrist, hip, and ankle. During each activity net oxygen cost (METs) was assessed. The time series of accelerometer signals were represented in terms of uniformly discretized values called bins. Support Vector Machine was used for activity classification with bins and every pair of bins used as features. Bagged decision tree regression was used for net metabolic cost prediction. To evaluate model performance we employed the jackknife leave-one-out cross validation method. Single accelerometer and multi-accelerometer site model estimates across and within age group revealed similar accuracy, with a bias range of −0.03 to 0.01 METs, bias percent of −0.8 to 0.3%, and a rMSE range of 0.81–1.04 METs. Multi-site accelerometer location models improved activity type classification over single site location models from a low of 69.3% to a maximum of 92.8% accuracy. For each accelerometer site location model, or combined site location model, percent accuracy classification decreased as a function of age group, or when young age groups models were generalized to older age groups. Specific age group models on average performed better than when all age groups were combined. A time series computation show promising results for predicting energy cost and activity type. Differences in prediction across age group, a lack of generalizability across age groups, and that age group specific models perform better than when all ages are combined needs to be considered as analytic calibration procedures to detect energy cost and type are further developed. PMID:26449155

  10. Ngram time series model to predict activity type and energy cost from wrist, hip and ankle accelerometers: implications of age.

    Strath, Scott J; Kate, Rohit J; Keenan, Kevin G; Welch, Whitney A; Swartz, Ann M

    2015-11-01

    To develop and test time series single site and multi-site placement models, we used wrist, hip and ankle processed accelerometer data to estimate energy cost and type of physical activity in adults. Ninety-nine subjects in three age groups (18-39, 40-64, 65 +  years) performed 11 activities while wearing three triaxial accelereometers: one each on the non-dominant wrist, hip, and ankle. During each activity net oxygen cost (METs) was assessed. The time series of accelerometer signals were represented in terms of uniformly discretized values called bins. Support Vector Machine was used for activity classification with bins and every pair of bins used as features. Bagged decision tree regression was used for net metabolic cost prediction. To evaluate model performance we employed the jackknife leave-one-out cross validation method. Single accelerometer and multi-accelerometer site model estimates across and within age group revealed similar accuracy, with a bias range of -0.03 to 0.01 METs, bias percent of -0.8 to 0.3%, and a rMSE range of 0.81-1.04 METs. Multi-site accelerometer location models improved activity type classification over single site location models from a low of 69.3% to a maximum of 92.8% accuracy. For each accelerometer site location model, or combined site location model, percent accuracy classification decreased as a function of age group, or when young age groups models were generalized to older age groups. Specific age group models on average performed better than when all age groups were combined. A time series computation show promising results for predicting energy cost and activity type. Differences in prediction across age group, a lack of generalizability across age groups, and that age group specific models perform better than when all ages are combined needs to be considered as analytic calibration procedures to detect energy cost and type are further developed. PMID:26449155

  11. Active serine involved in the stabilization of the active site loop in the Humicola lanuginosa lipase

    Peters, Günther H.j.; Svendsen, A.; Langberg, H.; Vind, J.; Patkar, S.A.; Toxvaerd, S.; Kinnunen, P.K.J.

    1998-01-01

    reveal that the hinges of the active site lid are more flexible in the wild-type Hll than in S146A. In contrast, larger fluctuations are observed in the middle region of the active site loop in S 146A than in Hll. These findings reveal that the single mutation (S146A) of the active site serine leads to...

  12. Meteorological predictions for Mars 2020 Exploration Rover high-priority landing sites throug MRAMS Mesoscale Modeling

    Pla-García, Jorge; Rafkin, Scot C. R.

    2015-04-01

    The Mars Regional Atmospheric Modeling System (MRAMS) is used to predict meteorological conditions that are likely to be encountered by the Mars 2020 Exploration Rover at several proposed landing sites during entry, descent, and landing (EDL). The meteorology during the EDL window at most of the sites is dynamic. The intense heating of the lower atmosphere drives intense thermals and mesoscale thermal circulations. Moderate mean winds, wind shear, turbulence, and vertical air currents associated with convection are present and potentially hazardous to EDL [1]. Nine areas with specific high-priority landing ellipses of the 2020 Rover, are investigated: NE Syrtis, Nili Fossae, Nili Fossae Carbonates, Jezero Crater Delta, Holden Crater, McLaughlin Crater, Southwest Melas Basin, Mawrth Vallis and East Margaritifer Chloride. MRAMS was applied to the landing site regions using nested grids with a spacing of 330 meters on the innermost grid that is centered over each landing site. MRAMS is ideally suited for this investigation; the model is explicitly designed to simulate Mars' atmospheric thermal circulations at the mesoscale and smaller with realistic, high-resolution surface properties [2, 3]. Horizontal wind speeds, both vertical profiles and vertical cross-sections wind speeds, are studied. For some landing sites simulations, two example configurations -including and not including Hellas basin in the mother domain- were generated, in order to study how the basin affects the innermost grids circulations. Afternoon circulations at all sites pose some risk entry, descent, and landing. Most of the atmospheric hazards are not evident in current observational data and general circulation model simulations and can only be ascertained through mesoscale modeling of the region. Decide where to go first and then design a system that can tolerate the environment would greatly minimize risk. References: [1] Rafkin, S. C. R., and T. I. Michaels (2003), J. Geophys. Res., 108(E12

  13. The sequential structure of brain activation predicts skill.

    Anderson, John R; Bothell, Daniel; Fincham, Jon M; Moon, Jungaa

    2016-01-29

    In an fMRI study, participants were trained to play a complex video game. They were scanned early and then again after substantial practice. While better players showed greater activation in one region (right dorsal striatum) their relative skill was better diagnosed by considering the sequential structure of whole brain activation. Using a cognitive model that played this game, we extracted a characterization of the mental states that are involved in playing a game and the statistical structure of the transitions among these states. There was a strong correspondence between this measure of sequential structure and the skill of different players. Using multi-voxel pattern analysis, it was possible to recognize, with relatively high accuracy, the cognitive states participants were in during particular scans. We used the sequential structure of these activation-recognized states to predict the skill of individual players. These findings indicate that important features about information-processing strategies can be identified from a model-based analysis of the sequential structure of brain activation. PMID:26707716

  14. Prediction of the flooding process at the Ronneburg site - results of an integrated approach

    The flooding process of the Ronneburg uranium mine (WISMUT) was initiated at the turn of the year 1997 to 1998. In order to prepare the flooding process and to derive and optimize technological measures an integrated modelling approach was chosen which includes several coupled modules. The most important issues to be answered are: (1) prediction of the flooding time (2) prediction of the groundwater level at the post-flooding stage, assessment of amount, location and quality of flooding waters entering the receiving streams at the final stage (3) water quality prediction within the mine during the flooding process (4) definition of technological measures and assessment of their efficiency A box model which includes the three-dimensional distribution of the cavity volume in the mine represents the model core. The model considers the various types of dewatered cavity volumes for each mine level / mining field and the degree of vertical and horizontal connection between the mining fields. Different types of open mine space as well as the dewatered geological pore and joint volume are considered taking into account the contour of the depression cone prior to flooding and the characteristics of the different rock types. Based on the mine water balance and the flooding technology the model predicts the rise of the water table over time during the flooding process for each mine field separately. In order to predict the mine water quality and the efficiency of in-situ water treatment the box model was linked to a geochemical model (PHREEQC). A three-dimensional flow model is used to evaluate the post-flooding situation at the Ronneburg site. This model is coupled to the box model. The modelling results of various flooding scenarios show that a prediction of the post-flooding geohydraulic situation is possible despite of uncertainties concerning the input parameters which still exist. The post-flooding water table in the central part of the Ronneburg mine will be 270 m

  15. Prediction and Analysis of Post-Translational Pyruvoyl Residue Modification Sites from Internal Serines in Proteins.

    Yang Jiang

    Full Text Available Most of pyruvoyl-dependent proteins observed in prokaryotes and eukaryotes are critical regulatory enzymes, which are primary targets of inhibitors for anti-cancer and anti-parasitic therapy. These proteins undergo an autocatalytic, intramolecular self-cleavage reaction in which a covalently bound pyruvoyl group is generated on a conserved serine residue. Traditional detections of the modified serine sites are performed by experimental approaches, which are often labor-intensive and time-consuming. In this study, we initiated in an attempt for the computational predictions of such serine sites with Feature Selection based on a Random Forest. Since only a small number of experimentally verified pyruvoyl-modified proteins are collected in the protein database at its current version, we only used a small dataset in this study. After removing proteins with sequence identities >60%, a non-redundant dataset was generated and was used, which contained only 46 proteins, with one pyruvoyl serine site for each protein. Several types of features were considered in our method including PSSM conservation scores, disorders, secondary structures, solvent accessibilities, amino acid factors and amino acid occurrence frequencies. As a result, a pretty good performance was achieved in our dataset. The best 100.00% accuracy and 1.0000 MCC value were obtained from the training dataset, and 93.75% accuracy and 0.8441 MCC value from the testing dataset. The optimal feature set contained 9 features. Analysis of the optimal feature set indicated the important roles of some specific features in determining the pyruvoyl-group-serine sites, which were consistent with several results of earlier experimental studies. These selected features may shed some light on the in-depth understanding of the mechanism of the post-translational self-maturation process, providing guidelines for experimental validation. Future work should be made as more pyruvoyl-modified proteins are

  16. Prediction of DtxR regulon: Identification of binding sites and operons controlled by Diphtheria toxin repressor in Corynebacterium diphtheriae

    Hasnain Seyed

    2004-09-01

    Full Text Available Abstract Background The diphtheria toxin repressor, DtxR, of Corynebacterium diphtheriae has been shown to be an iron-activated transcription regulator that controls not only the expression of diphtheria toxin but also of iron uptake genes. This study aims to identify putative binding sites and operons controlled by DtxR to understand the role of DtxR in patho-physiology of Corynebacterium diphtheriae. Result Positional Shannon relative entropy method was used to build the DtxR-binding site recognition profile and the later was used to identify putative regulatory sites of DtxR within C. diphtheriae genome. In addition, DtxR-regulated operons were also identified taking into account the predicted DtxR regulatory sites and genome annotation. Few of the predicted motifs were experimentally validated by electrophoretic mobility shift assay. The analysis identifies motifs upstream to the novel iron-regulated genes that code for Formamidopyrimidine-DNA glycosylase (FpG, an enzyme involved in DNA-repair and starvation inducible DNA-binding protein (Dps which is involved in iron storage and oxidative stress defense. In addition, we have found the DtxR motifs upstream to the genes that code for sortase which catalyzes anchoring of host-interacting proteins to the cell wall of pathogenic bacteria and the proteins of secretory system which could be involved in translocation of various iron-regulated virulence factors including diphtheria toxin. Conclusions We have used an in silico approach to identify the putative binding sites and genes controlled by DtxR in Corynebacterium diphtheriae. Our analysis shows that DtxR could provide a molecular link between Fe+2-induced Fenton's reaction and protection of DNA from oxidative damage. DtxR-regulated Dps prevents lethal combination of Fe+2 and H2O2 and also protects DNA by nonspecific DNA-binding. In addition DtxR could play an important role in host interaction and virulence by regulating the levels of sortase

  17. PhosphoScan: A Probability-Based Method for Phosphorylation Site Prediction Using MS2/MS3 Pair Information

    Wan, Yunhu; Cripps, Diane; Thomas, Stefani; Campbell, Patricia; Ambulos, Nicholas; CHEN Ting; Yang, Austin

    2008-01-01

    Phosphopeptide identification and phosphorylation site localization are crucial aspects of many biological studies. Furthermore, multiple phosphorylations of peptides make site localization even more difficult. We developed a probability-based method to unambiguously determine phosphorylation sites within phosphopeptides using MS2/3 pair information. A comparison test was performed with SEQUEST and MASCOT predictions using a spectral data set from a synthetic doubly phosphorylated peptide, an...

  18. Structure prediction and activity analysis of human heme oxygenase-1 and its mutant

    Zhen-Wei Xia; Wen-Pu Zhou; Wen-Jun Cui; Xue-Hong Zhang; Qing-Xiang Shen; Yun-Zhu Li; Shan-Chang Yu

    2004-01-01

    AIM: To predict wild human heme oxygenase-1 (whHO-1)and hHO-1 His25Ala mutant (△hHO-1) structures, to clone and express them and analyze their activities.METHODS: Swiss-PdbViewer and Antheprot 5.0 were used for the prediction of structure diversity and physicalchemical changes between wild and mutant hHO-1. hHO1 His25Ala mutant cDNA was constructed by site-directed mutagenesis in two plasmids of E. coli DH5α. Expression products were purified by ammonium sulphate precipitation and Q-Sepharose Fast Flow column chromatography, and their activities were measured.RESULTS: rHO-1 had the structure of a helical fold with the heme sandwiched between heme-heme oxygenase1 helices. Bond angle, dihedral angle and chemical bond in the active pocket changed after Ala25 was replaced by His25, but Ala25 was still contacting the surface and the electrostatic potential of the active pocket was negative. The mutated enzyme kept binding activity to heme. Two vectors pBHO-1 and pBHO-1(M) were constructed and expressed. Ammonium sulphate precipitation and column chromatography yielded 3.6-fold and 30-fold higher purities of whHO-1, respectively. The activity of △hHO-1 was reduced 91.21% after mutation compared with whHO-1.CONCLUSION: Proximal His25 ligand is crucial for normal hHO-1 catalytic activity. △hHO-1 is deactivated by mutation but keeps the same binding site as whHO-1. △hHO-1 might be a potential inhibitor of whHO-1 for preventing neonatal hyperbilirubinemia.

  19. Recent and Past Musical Activity Predicts Cognitive Aging Variability: Direct Comparison with Leisure Activities

    Brenda eHanna-Pladdy

    2012-07-01

    Full Text Available Studies evaluating the impact of modifiable lifestyle factors on cognition offer potential insights into sources of cognitive aging variability. Recently, we reported an association between extent of musical instrumental practice throughout the life span (greater than 10 years on preserved cognitive functioning in advanced age . These findings raise the question of whether there are training-induced brain changes in musicians that can transfer to nonmusical cognitive abilities to allow for compensation of age-related cognitive declines. However, because of the relationship between engagement in lifestyle activities and preserved cognition, it remains unclear whether these findings are specifically driven by musical training or the types of individuals likely to engage in greater activities in general. The current study examined the type of leisure activity (musical versus other as well as the timing of engagement (age of acquisition, past versus recent in predictive models of successful cognitive aging. Seventy age and education matched older musicians (> 10 years and nonmusicians (ages 59-80 were evaluated on neuropsychological tests and life-style activities (AAP. Partition analyses were conducted on significant cognitive measures to explain performance variance in musicians. Musicians scored higher on tests of phonemic fluency, verbal immediate recall, judgment of line orientation (JLO, and Letter Number Sequencing (LNS, but not the AAP. The first partition analysis revealed education best predicted JLO in musicians, followed by recent musical engagement which offset low education. In the second partition analysis, early age of musical acquisition (< 9 years predicted enhanced LNS in musicians, while analyses for AAP, verbal recall and fluency were not predictive. Recent and past musical activity, but not leisure activity, predicted variability across verbal and visuospatial domains in aging. Early musical acquisition predicted auditory

  20. Real-time prediction of earthquake ground motion: time evolutional prediction using data assimilation and real-time correction of site amplification factors

    Hoshiba, M.

    2012-12-01

    In this presentation, I propose a new approach for real-time prediction of seismic ground motion which is applicable to Earthquake Early Waning (EEW). Many methods of EEW are based on a network method in which hypocenter and magnitude (source parameters) are quickly determined (that is, interpretation of current wavefield), and then the ground motions are predicted, and warnings are issued depending on the strength of the predicted ground motion. In this method, though we can predict ground motions using a few parameters (location of hypocenter, magnitude, site factors) at any points, it is necessary to determine the hypocenter and magnitude at first, and error of the source parameters leads directly to the error of the prediction. It is not easy to take the effects of rupture directivity and source extent into account, and it is impossible to fully reproduce the current wavefield from the interpreted source parameters. In general, wave motion is predictable when boundary condition and initial condition are given. Time evolutional prediction is a method based on this approach using the current wavefield as an initial condition, that is u(x, t+Δt)=H(u(x, t)), where u is the wave motion at location x at lapse time t, and H is the prediction operator. Future wave motion, u(x, t+Δt), is predicted from the distribution of the current wave motion u(x, t) using H. For H, finite difference technique or boundary integral equation method, such as Kirchhoff integral, is used. In the time evolutional prediction, determination of detailed distribution of current wave motion is a key, so that dense seismic observation network is required. Data assimilation is a technique to produce artificially denser network, which is widely used for numerical weather prediction and oceanography. Distribution of current wave motion is estimated from not only the current real observation of u(x, t), but also the prediction of one step before, H(u(x, t-Δt)). Combination of them produces denser

  1. Metavanadate at the active site of the phosphatase VHZ.

    Kuznetsov, Vyacheslav I; Alexandrova, Anastassia N; Hengge, Alvan C

    2012-09-01

    Vanadate is a potent modulator of a number of biological processes and has been shown by crystal structures and NMR spectroscopy to interact with numerous enzymes. Although these effects often occur under conditions where oligomeric forms dominate, the crystal structures and NMR data suggest that the inhibitory form is usually monomeric orthovanadate, a particularly good inhibitor of phosphatases because of its ability to form stable trigonal-bipyramidal complexes. We performed a computational analysis of a 1.14 Å structure of the phosphatase VHZ in complex with an unusual metavanadate species and compared it with two classical trigonal-bipyramidal vanadate-phosphatase complexes. The results support extensive delocalized bonding to the apical ligands in the classical structures. In contrast, in the VHZ metavanadate complex, the central, planar VO(3)(-) moiety has only one apical ligand, the nucleophilic Cys95, and a gap in electron density between V and S. A computational analysis showed that the V-S interaction is primarily ionic. A mechanism is proposed to explain the formation of metavanadate in the active site from a dimeric vanadate species that previous crystallographic evidence has shown to be able to bind to the active sites of phosphatases related to VHZ. Together, the results show that the interaction of vanadate with biological systems is not solely reliant upon the prior formation of a particular inhibitory form in solution. The catalytic properties of an enzyme may act upon the oligomeric forms primarily present in solution to generate species such as the metavanadate ion observed in the VHZ structure. PMID:22876963

  2. Design and prediction of new acetylcholinesterase inhibitor via quantitative structure activity relationship of huprines derivatives.

    Zhang, Shuqun; Hou, Bo; Yang, Huaiyu; Zuo, Zhili

    2016-05-01

    Acetylcholinesterase (AChE) is an important enzyme in the pathogenesis of Alzheimer's disease (AD). Comparative quantitative structure-activity relationship (QSAR) analyses on some huprines inhibitors against AChE were carried out using comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), and hologram QSAR (HQSAR) methods. Three highly predictive QSAR models were constructed successfully based on the training set. The CoMFA, CoMSIA, and HQSAR models have values of r (2) = 0.988, q (2) = 0.757, ONC = 6; r (2) = 0.966, q (2) = 0.645, ONC = 5; and r (2) = 0.957, q (2) = 0.736, ONC = 6. The predictabilities were validated using an external test sets, and the predictive r (2) values obtained by the three models were 0.984, 0.973, and 0.783, respectively. The analysis was performed by combining the CoMFA and CoMSIA field distributions with the active sites of the AChE to further understand the vital interactions between huprines and the protease. On the basis of the QSAR study, 14 new potent molecules have been designed and six of them are predicted to be more active than the best active compound 24 described in the literature. The final QSAR models could be helpful in design and development of novel active AChE inhibitors. PMID:26832327

  3. Statistical estimations for predicting the detection limit of low activities

    When extremely low activities are measured, the statistics of the observed decay events may be insufficient for a justified application of statistical assessments based on the Gaussian distribution. Student's t-distribution and the theory of the interval estimation are used as the basis for a statistical model for predicting the detection limit and the signal-to-noise ratio which could be reached under the conditions of the measurement. The derived statistical estimations are applicable in cases when a small number of decay events is expected to be recorded. The minimum detectable activity characterizing the detection limit under the conditions of the measurement, is determined at the given confidence limits and assumed permissible relative statistical errors during the measurement of the sample and the background (within the available time limits). The derived statistical estimations can be used for comparing the possibilities offered by the different measuring methods applied for determination of extremely low activities. These evaluations can also be used as a criterion for discussing the reliability of the measurement results. (author). 6 refs

  4. Solubility Prediction of Active Pharmaceutical Compounds with the UNIFAC Model

    Nouar, Abderrahim; Benmessaoud, Ibtissem; Koutchoukali, Ouahiba; Koutchoukali, Mohamed Salah

    2016-03-01

    The crystallization from solution of an active pharmaceutical ingredient requires the knowledge of the solubility in the entire temperature range investigated during the process. However, during the development of a new active ingredient, these data are missing. Its experimental determination is possible, but tedious. UNIFAC Group contribution method Fredenslund et al. (Vapor-liquid equilibria using UNIFAC: a group contribution method, 1977; AIChE J 21:1086, 1975) can be used to predict this physical property. Several modifications on this model have been proposed since its development in 1977, modified UNIFAC of Dortmund Weidlich et al. (Ind Eng Chem Res 26:1372, 1987), Gmehling et al. (Ind Eng Chem Res 32:178, 1993), Pharma-modified UNIFAC Diedrichs et al. (Evaluation und Erweiterung thermodynamischer Modelle zur Vorhersage von Wirkstofflöslichkeiten, PhD Thesis, 2010), KT-UNIFAC Kang et al. (Ind Eng Chem Res 41:3260, 2002), ldots In this study, we used UNIFAC model by considering the linear temperature dependence of interaction parameters as in Pharma-modified UNIFAC and structural groups as defined by KT-UNIFAC first-order model. More than 100 binary datasets were involved in the estimation of interaction parameters. These new parameters were then used to calculate activity coefficient and solubility of some molecules in various solvents at different temperatures. The model gives better results than those from the original UNIFAC and shows good agreement between the experimental solubility and the calculated one.

  5. Decreased dopamine activity predicts relapse in methamphetamine abusers

    Studies in methamphetamine (METH) abusers showed that the decreases in brain dopamine (DA) function might recover with protracted detoxification. However, the extent to which striatal DA function in METH predicts recovery has not been evaluated. Here we assessed whether striatal DA activity in METH abusers is associated with clinical outcomes. Brain DA D2 receptor (D2R) availability was measured with positron emission tomography and (11C)raclopride in 16 METH abusers, both after placebo and after challenge with 60 mg oral methylphenidate (MPH) (to measure DA release) to assess whether it predicted clinical outcomes. For this purpose, METH abusers were tested within 6 months of last METH use and then followed up for 9 months of abstinence. In parallel, 15 healthy controls were tested. METH abusers had lower D2R availability in caudate than in controls. Both METH abusers and controls showed decreased striatal D2R availability after MPH and these decreases were smaller in METH than in controls in left putamen. The six METH abusers who relapsed during the follow-up period had lower D2R availability in dorsal striatum than in controls, and had no D2R changes after MPH challenge. The 10 METH abusers who completed detoxification did not differ from controls neither in striatal D2R availability nor in MPH-induced striatal DA changes. These results provide preliminary evidence that low striatal DA function in METH abusers is associated with a greater likelihood of relapse during treatment. Detection of the extent of DA dysfunction may be helpful in predicting therapeutic outcomes.

  6. Decreased dopamine activity predicts relapse in methamphetamine abusers

    Wang G. J.; Wang, G.-J.; Smith, L.; Volkow, N.D.; Telang, F.; Logan, J.; Tomasi, D.; Wong, C.T.; Hoffman, W.; Jayne, M.; Alia-Klein, N.; Thanos, P.; Fowler, J.S.

    2011-01-20

    Studies in methamphetamine (METH) abusers showed that the decreases in brain dopamine (DA) function might recover with protracted detoxification. However, the extent to which striatal DA function in METH predicts recovery has not been evaluated. Here we assessed whether striatal DA activity in METH abusers is associated with clinical outcomes. Brain DA D2 receptor (D2R) availability was measured with positron emission tomography and [{sup 11}C]raclopride in 16 METH abusers, both after placebo and after challenge with 60 mg oral methylphenidate (MPH) (to measure DA release) to assess whether it predicted clinical outcomes. For this purpose, METH abusers were tested within 6 months of last METH use and then followed up for 9 months of abstinence. In parallel, 15 healthy controls were tested. METH abusers had lower D2R availability in caudate than in controls. Both METH abusers and controls showed decreased striatal D2R availability after MPH and these decreases were smaller in METH than in controls in left putamen. The six METH abusers who relapsed during the follow-up period had lower D2R availability in dorsal striatum than in controls, and had no D2R changes after MPH challenge. The 10 METH abusers who completed detoxification did not differ from controls neither in striatal D2R availability nor in MPH-induced striatal DA changes. These results provide preliminary evidence that low striatal DA function in METH abusers is associated with a greater likelihood of relapse during treatment. Detection of the extent of DA dysfunction may be helpful in predicting therapeutic outcomes.

  7. MicroRNA transcription start site prediction with multi-objective feature selection.

    Bhattacharyya, Malay; Feuerbach, Lars; Bhadra, Tapas; Lengauer, Thomas; Bandyopadhyay, Sanghamitra

    2012-01-01

    MicroRNAs (miRNAs) are non-coding, short (21-23nt) regulators of protein-coding genes that are generally transcribed first into primary miRNA (pri-miR), followed by the generation of precursor miRNA (pre-miR). This finally leads to the production of the mature miRNA. A large amount of information is available on the pre- and mature miRNAs. However, very little is known about the pri-miRs, due to a lack of knowledge about their transcription start sites (TSSs). Based on the genomic loci, miRNAs can be categorized into two types --intragenic (intra-miR) and intergenic (inter-miR). While it is already an established fact that intra-miRs are commonly transcribed in conjunction with their host genes, the transcription machinery of inter-miRs is poorly understood. Although it is assumed that miRNA promoters are similar in structure to gene promoters, since both are transcribed by RNA polymerase II (Pol II), computational validations exhibit poor performance of gene promoter prediction methods on miRNAs. In this paper, we concentrate on the problem of TSS prediction for miRNAs. The present study begins with the identification of positive and negative promoter samples from recently published data stemming from RNA-sequencing studies. From these samples of experimentally validated miRNA TSSs, a number of standard sequence features are extracted. Furthermore, to account for potential footprints related to promoter regulation by CpG dinucleotide targeted DNA methylation, a number of novel features are defined. We develop a support vector machine (SVM) with RBF kernel for the prediction of miRNA TSSs trained on human miRNA promoters. A novel feature reduction technique based on archived multi-objective simulated annealing (AMOSA) identifies the final set of features. The resulting model trained on miRNA promoters shows improved performance over the one trained on protein-coding gene promoters in terms of classification accuracy, sensitivity and specificity. Results are also

  8. Screening breeding sites of the common toad (Bufo bufo) in England and Wales for evidence of endocrine disrupting activity.

    Pickford, Daniel B; Jones, Alexandra; Velez-Pelez, Alejandra; Orton, Frances; Iguchi, Taisen; Mitsui, Naoko; Tooi, Osamu

    2015-07-01

    Anuran amphibians are often present in agricultural landscapes and may therefore be exposed to chemicals in surface waters used for breeding. We used passive accumulation devices (SPMD and POCIS) to sample contaminants from nine breeding sites of the Common toad (Bufo bufo) across England and Wales, measuring endocrine activity of the extracts in a recombinant yeast androgen screen (YAS) and yeast estrogen screen (YES) and an in vitro vitellogenin induction screen in primary culture of Xenopus laevis hepatocytes. We also assessed hatching, growth, survival, and development in caged larvae in situ, and sampled metamorphs for gonadal histopathology. None of the SPMD extracts exhibited estrogen receptor or androgen receptor agonist activity, while POCIS extracts from two sites in west-central England exhibited concentration-dependent androgenic activity in the YAS. Three sites exhibited significant estrogenic activity in both the YES and the Xenopus hepatocyte. Hatching rates varied widely among sites, but there was no consistent correlation between hatching rate and intensity of agricultural activity, predicted concentrations of agrochemicals, or endocrine activity measured in YES/YAS assays. While a small number of intersex individuals were observed, their incidence could not be associated with predicted pesticide exposure or endocrine activitity measured in the in vitro screens. There were no significant differences in sex ratio, as determined by gonadal histomorphology among the study sites, and no significant correlation was observed between proportion of males and predicted exposure to agrochemicals. However, a negative correlation did become apparent in later sampling periods between proportion of males and estrogenic activity of the POCIS sample, as measured in the YES. Our results suggest that larval and adult amphibians may be exposed to endocrine disrupting chemicals in breeding ponds, albeit at low concentrations, and that chemical contaminants other than

  9. Prediction of Water Binding to Protein Hydration Sites with a Discrete, Semiexplicit Solvent Model.

    Setny, Piotr

    2015-12-01

    Buried water molecules are ubiquitous in protein structures and are found at the interface of most protein-ligand complexes. Determining their distribution and thermodynamic effect is a challenging yet important task, of great of practical value for the modeling of biomolecular structures and their interactions. In this study, we present a novel method aimed at the prediction of buried water molecules in protein structures and estimation of their binding free energies. It is based on a semiexplicit, discrete solvation model, which we previously introduced in the context of small molecule hydration. The method is applicable to all macromolecular structures described by a standard all-atom force field, and predicts complete solvent distribution within a single run with modest computational cost. We demonstrate that it indicates positions of buried hydration sites, including those filled by more than one water molecule, and accurately differentiates them from sterically accessible to water but void regions. The obtained estimates of water binding free energies are in fair agreement with reference results determined with the double decoupling method. PMID:26642995

  10. 10 CFR 60.18 - Review of site characterization activities. 2

    2010-01-01

    ... 10 Energy 2 2010-01-01 2010-01-01 false Review of site characterization activities. 2 60.18... IN GEOLOGIC REPOSITORIES Licenses Preapplication Review § 60.18 Review of site characterization activities. 2 2 In addition to the review of site characterization activities specified in this section,...