WorldWideScience

Sample records for active site prediction

  1. Predicting active site residue annotations in the Pfam database

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    Finn Robert D

    2007-08-01

    Full Text Available Abstract Background Approximately 5% of Pfam families are enzymatic, but only a small fraction of the sequences within these families ( Description We have created a large database of predicted active site residues. On comparing our active site predictions to those found in UniProtKB, Catalytic Site Atlas, PROSITE and MEROPS we find that we make many novel predictions. On investigating the small subset of predictions made by these databases that are not predicted by us, we found these sequences did not meet our strict criteria for prediction. We assessed the sensitivity and specificity of our methodology and estimate that only 3% of our predicted sequences are false positives. Conclusion We have predicted 606110 active site residues, of which 94% are not found in UniProtKB, and have increased the active site annotations in Pfam by more than 200 fold. Although implemented for Pfam, the tool we have developed for transferring the data can be applied to any alignment with associated experimental active site data and is available for download. Our active site predictions are re-calculated at each Pfam release to ensure they are comprehensive and up to date. They provide one of the largest available databases of active site annotation.

  2. Functional and catalytic active sites prediction and docking analysis ...

    African Journals Online (AJOL)

    Bioinformatics

    2015-07-01

    Jul 1, 2015 ... industrially important azo dyes such as the molecular weight, molecular ... et al., 2010). The software possesses structure-based method to predict active sites in proteins based on a Difference of Gaussian (DoG) approach ...

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

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    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.

  4. Predicted effectiveness of in-situ activated carbon amendment for field sediment sites with variable site- and compound-specific characteristics

    Energy Technology Data Exchange (ETDEWEB)

    Choi, Yongju, E-mail: ychoi81@snu.ac.kr [Department of Civil and Environmental Engineering, Seoul National University, Seoul 151-744 (Korea, Republic of); Cho, Yeo-Myoung; Luthy, Richard G. [Department of Civil and Environmental Engineering, Stanford University, Stanford, CA 94305-4020 (United States); Werner, David [School of Civil Engineering and Geosciences, Newcastle University, Newcastle upon Tyne NE1 7RU (United Kingdom)

    2016-01-15

    Highlights: • The model accounts for the heterogeneity of AC distribution in field applications. • AC amendment effectiveness is predicted for ten sediment sites. • An HOC mass transfer model and calibrated parameters provide reliable predictions. • AC amendment is predicted to be effective for most sites. • K{sub ow}, K{sub d}, and equilibrium-based calculations are useful indicators. - Abstract: A growing body of evidence shows that the effectiveness of in-situ activated carbon (AC) amendment to treat hydrophobic organic contaminants (HOCs) in sediments can be reliably predicted using a mass transfer modeling approach. This study analyzes available field data for characterizing AC-sediment distribution after mechanical mixing of AC into sediment. Those distributions are used to develop an HOC mass transfer model that accounts for plausible heterogeneities resulting from mixing of AC into sediment. The model is applied to ten field sites in the U.S. and Europe with 2–3 representative HOCs from each site using site- and HOC-specific model parameters collected from the literature. The model predicts that the AC amendment reduces the pore-water HOC concentrations by more than 95% fifteen years after AC deployment for 18 of the 25 total simulated cases when the AC is applied at doses of 1.5 times sediment total organic carbon content with an upper limit of 5 dry wt%. The predicted effectiveness shows negative correlation with the HOC octanol–water partitioning coefficients and the sediment-water distribution coefficients, and positive correlation with the effectiveness calculated based on equilibrium coefficients of sediment and AC, suggesting the possibility for use of the values for screening-level assessments.

  5. Cloning and characterization of a novel nuclease from shrimp hepatopancreas, and prediction of its active site.

    Science.gov (United States)

    Wang, W Y; Liaw, S H; Liao, T H

    2000-03-15

    Approximately 95% of the amino acid sequence of a shrimp (Penaeus japonicus) nuclease was derived from protease-digested peptides. A 1461-base cDNA for the nuclease was amplified and sequenced with degenerate primers based on the amino acid sequence and then specific primers by 3' and 5' RACE (rapid amplification of cDNA ends). It contains an open reading frame encoding a putative 21-residue signal peptide and a 381-residue mature protein. The N-terminus of the enzyme is pyroglutamate, deduced from composition and matrix-assisted laser desorption ionization-time-of-flight MS analyses, and confirmed by a glutamine residue in the cDNA sequence. The enzyme has 11 Cys residues, forming five intramolecular disulphides. The eleventh Cys residue was linked to a thiol compound with an estimated molecular mass of between 500 and 700 Da. A sequence similarity search revealed no homologous proteins but residues 205-255 shared a conserved active-site motif within a distinct group of nucleases. His(211) in this conserved motif was shown to be very important in catalysis by site-specific modification with (14)C-labelled iodoacetate. The shrimp nuclease, previously designated DNase I, does indeed possess a low level of hydrolytic activity towards RNA in the presence of Mg(2+) and Ca(2+). The conservation of functionally important residues during distant evolution might imply that the catalytic mechanisms are similar in these nucleases, which should be classified in one subfamily. Finally, an active-site structure for shrimp nuclease was proposed on the basis of published structural data and the results of mutational and biochemical analyses of Serratia nuclease.

  6. Homology models of dipeptidyl peptidases 8 and 9 with a focus on loop predictions near the active site.

    Science.gov (United States)

    Rummey, Christian; Metz, Günther

    2007-01-01

    Dipeptidyl peptidase 4 (DP4) inhibitors are currently under intensive investigation in late-stage clinical trials as a treatment for type II diabetes. Lack of selectivity toward the related enzymes DP8 and DP9 has recently emerged as a possible source of drug-induced toxicity. Unlike DP4, X-ray structures of DP8 and DP9 are not yet available. As an aid to understanding the structural basis for selectivity, the authors have constructed homology models of DP8 and DP9 based on the X-ray coordinates of DP4. Accurate sequence alignment reveals common structural features indicative for a well-preserved overall fold comprising two domains, namely, a hydrolase domain and a so-called beta-propeller, which together form the active site deeply buried within the protein. The conformation of two loops inside this deep cavity is particularly relevant for the active sites. The authors used a published protocol for loop prediction based on conformational sampling and energy analysis to generate plausible solutions for these two loops. The predictive power of the approach was successfully evaluated for the template protein DP4 and two additional known structures from the same protein family, namely, FAP and DPX. The authors also show that inclusion of the covalent ligand NVP-728 greatly enhances the refinement. Based on the established evaluation protocol, the corresponding loops of DP8 and DP9 were predicted and the resulting active sites were compared with DP4. In particular, the authors conclude that differences in the P2-pocket are relevant for the design of selective DP4 inhibitors. The loss of key interactions in DP8 and DP9 as predicted from their models is consistent with the selectivity profile of the DP4 clinical candidate MK-431.

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

    Science.gov (United States)

    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.

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

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    April eReynolds

    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.

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

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    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

  10. Probabilistic prediction models for aggregate quarry siting

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    Robinson, G.R.; Larkins, P.M.

    2007-01-01

    Weights-of-evidence (WofE) and logistic regression techniques were used in a GIS framework to predict the spatial likelihood (prospectivity) of crushed-stone aggregate quarry development. The joint conditional probability models, based on geology, transportation network, and population density variables, were defined using quarry location and time of development data for the New England States, North Carolina, and South Carolina, USA. The Quarry Operation models describe the distribution of active aggregate quarries, independent of the date of opening. The New Quarry models describe the distribution of aggregate quarries when they open. Because of the small number of new quarries developed in the study areas during the last decade, independent New Quarry models have low parameter estimate reliability. The performance of parameter estimates derived for Quarry Operation models, defined by a larger number of active quarries in the study areas, were tested and evaluated to predict the spatial likelihood of new quarry development. Population density conditions at the time of new quarry development were used to modify the population density variable in the Quarry Operation models to apply to new quarry development sites. The Quarry Operation parameters derived for the New England study area, Carolina study area, and the combined New England and Carolina study areas were all similar in magnitude and relative strength. The Quarry Operation model parameters, using the modified population density variables, were found to be a good predictor of new quarry locations. Both the aggregate industry and the land management community can use the model approach to target areas for more detailed site evaluation for quarry location. The models can be revised easily to reflect actual or anticipated changes in transportation and population features. ?? International Association for Mathematical Geology 2007.

  11. Sequence- and structure-based prediction of eukaryotic proteinphosphorylation sites

    DEFF Research Database (Denmark)

    Blom, Nikolaj; Gammeltoft, Steen; Brunak, Søren

    1999-01-01

    in independent sequences with a sensitivity in the range from69 % to 96 %. As an example, we predict novel phosphorylation sites in the p300/CBP protein that may regulateinteraction with transcription factors and histone acetyltransferase activity. In addition, serine and threonine residues inp300/CBP that can...

  12. Cutoff lensing: predicting catalytic sites in enzymes

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    Aubailly, Simon; Piazza, Francesco

    2015-10-01

    Predicting function-related amino acids in proteins with unknown function or unknown allosteric binding sites in drug-targeted proteins is a task of paramount importance in molecular biomedicine. In this paper we introduce a simple, light and computationally inexpensive structure-based method to identify catalytic sites in enzymes. Our method, termed cutoff lensing, is a general procedure consisting in letting the cutoff used to build an elastic network model increase to large values. A validation of our method against a large database of annotated enzymes shows that optimal values of the cutoff exist such that three different structure-based indicators allow one to recover a maximum of the known catalytic sites. Interestingly, we find that the larger the structures the greater the predictive power afforded by our method. Possible ways to combine the three indicators into a single figure of merit and into a specific sequential analysis are suggested and discussed with reference to the classic case of HIV-protease. Our method could be used as a complement to other sequence- and/or structure-based methods to narrow the results of large-scale screenings.

  13. Selective prediction of interaction sites in protein structures with THEMATICS

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    Murga Leonel F

    2007-04-01

    Full Text Available Abstract Background Methods are now available for the prediction of interaction sites in protein 3D structures. While many of these methods report high success rates for site prediction, often these predictions are not very selective and have low precision. Precision in site prediction is addressed using Theoretical Microscopic Titration Curves (THEMATICS, a simple computational method for the identification of active sites in enzymes. Recall and precision are measured and compared with other methods for the prediction of catalytic sites. Results Using a test set of 169 enzymes from the original Catalytic Residue Dataset (CatRes it is shown that THEMATICS can deliver precise, localised site predictions. Furthermore, adjustment of the cut-off criteria can improve the recall rates for catalytic residues with only a small sacrifice in precision. Recall rates for CatRes/CSA annotated catalytic residues are 41.1%, 50.4%, and 54.2% for Z score cut-off values of 1.00, 0.99, and 0.98, respectively. The corresponding precision rates are 19.4%, 17.9%, and 16.4%. The success rate for catalytic sites is higher, with correct or partially correct predictions for 77.5%, 85.8%, and 88.2% of the enzymes in the test set, corresponding to the same respective Z score cut-offs, if only the CatRes annotations are used as the reference set. Incorporation of additional literature annotations into the reference set gives total success rates of 89.9%, 92.9%, and 94.1%, again for corresponding cut-off values of 1.00, 0.99, and 0.98. False positive rates for a 75-protein test set are 1.95%, 2.60%, and 3.12% for Z score cut-offs of 1.00, 0.99, and 0.98, respectively. Conclusion With a preferred cut-off value of 0.99, THEMATICS achieves a high success rate of interaction site prediction, about 86% correct or partially correct using CatRes/CSA annotations only and about 93% with an expanded reference set. Success rates for catalytic residue prediction are similar to those of

  14. Predicted metal binding sites for phytoremediation.

    Science.gov (United States)

    Sharma, Ashok; Roy, Sudeep; Tripathi, Kumar Parijat; Roy, Pratibha; Mishra, Manoj; Khan, Feroz; Meena, Abha

    2009-09-05

    Metal ion binding domains are found in proteins that mediate transport, buffering or detoxification of metal ions. The objective of the study is to design and analyze metal binding motifs against the genes involved in phytoremediation. This is being done on the basis of certain pre-requisite amino-acid residues known to bind metal ions/metal complexes in medicinal and aromatic plants (MAP's). Earlier work on MAP's have shown that heavy metals accumulated by aromatic and medicinal plants do not appear in the essential oil and that some of these species are able to grow in metal contaminated sites. A pattern search against the UniProtKB/Swiss-Prot and UniProtKB/TrEMBL databases yielded true positives in each case showing the high specificity of the motifs designed for the ions of nickel, lead, molybdenum, manganese, cadmium, zinc, iron, cobalt and xenobiotic compounds. Motifs were also studied against PDB structures. Results of the study suggested the presence of binding sites on the surface of protein molecules involved. PDB structures of proteins were finally predicted for the binding sites functionality in their respective phytoremediation usage. This was further validated through CASTp server to study its physico-chemical properties. Bioinformatics implications would help in designing strategy for developing transgenic plants with increased metal binding capacity. These metal binding factors can be used to restrict metal update by plants. This helps in reducing the possibility of metal movement into the food chain.

  15. A GIS approach for predicting prehistoric site locations.

    Energy Technology Data Exchange (ETDEWEB)

    Kuiper, J. A.; Wescott, K. L.

    1999-08-04

    Use of geographic information system (GIS)-based predictive mapping to locate areas of high potential for prehistoric archaeological sites is becoming increasingly popular among archaeologists. Knowledge of the environmental variables influencing activities of original inhabitants is used to produce GIS layers representing the spatial distribution of those variables. The GIS layers are then analyzed to identify locations where combinations of environmental variables match patterns observed at known prehistoric sites. Presented are the results of a study to locate high-potential areas for prehistoric sites in a largely unsurveyed area of 39,000 acres in the Upper Chesapeake Bay region, including details of the analysis process. The project used environmental data from over 500 known sites in other parts of the region and the results corresponded well with known sites in the study area.

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

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    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

  17. Text Mining Improves Prediction of Protein Functional Sites

    Science.gov (United States)

    Cohn, Judith D.; Ravikumar, Komandur E.

    2012-01-01

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

  18. Text mining improves prediction of protein functional sites.

    Science.gov (United States)

    Verspoor, Karin M; Cohn, Judith D; Ravikumar, Komandur E; Wall, Michael E

    2012-01-01

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

  19. Text mining improves prediction of protein functional sites.

    Directory of Open Access Journals (Sweden)

    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.

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

    DEFF Research Database (Denmark)

    Chang, Lan Yun; Barnard, Amanda S.; Gontard, Lionel Cervera

    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 nanop...

  1. SVM-based prediction of caspase substrate cleavage sites

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    Ranganathan Shoba

    2006-12-01

    Full Text Available Abstract 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 machines (SVM algorithm has been shown to be useful in several biological classification problems, we have implemented an SVM-based method to investigate its applicability to this domain. Results A set of unique caspase substrates cleavage sites were obtained from literature and used for evaluating the SVM method. Datasets containing (i the tetrapeptide cleavage sites, (ii the tetrapeptide cleavage sites, augmented by two adjacent residues, P1' and P2' amino acids and (iii the tetrapeptide cleavage sites with ten additional upstream and downstream flanking sequences (where available were tested. The SVM method achieved an accuracy ranging from 81.25% to 97.92% on independent test sets. The SVM method successfully predicted the cleavage of a novel caspase substrate and its mutants. Conclusion This study presents an SVM approach for predicting caspase substrate cleavage sites based on the cleavage sites and the downstream and upstream flanking sequences. The method shows an improvement over existing methods and may be useful for predicting hitherto undiscovered cleavage sites.

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

    CERN Document Server

    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...

  3. MONTE CARLO ANALYSIS FOR PREDICTION OF NOISE FROM A CONSTRUCTION SITE

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    Zaiton Haron

    2009-06-01

    Full Text Available The large number of operations involving noisy machinery associated with construction site activities result in considerable variation in the noise levels experienced at receiver locations. This paper suggests an approach to predict noise levels generated from a site by using a Monte Carlo approach. This approach enables the determination of details regarding the statistical uncertainties associated with noise level predictions or temporal distributions. This technique could provide the basis for a generalised prediction technique and a simple noise management tool.

  4. Positive-Unlabeled Learning for Pupylation Sites Prediction

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    Ming Jiang

    2016-01-01

    Full Text Available Pupylation plays a key role in regulating various protein functions as a crucial posttranslational modification of prokaryotes. In order to understand the molecular mechanism of pupylation, it is important to identify pupylation substrates and sites accurately. Several computational methods have been developed to identify pupylation sites because the traditional experimental methods are time-consuming and labor-sensitive. With the existing computational methods, the experimentally annotated pupylation sites are used as the positive training set and the remaining nonannotated lysine residues as the negative training set to build classifiers to predict new pupylation sites from the unknown proteins. However, the remaining nonannotated lysine residues may contain pupylation sites which have not been experimentally validated yet. Unlike previous methods, in this study, the experimentally annotated pupylation sites were used as the positive training set whereas the remaining nonannotated lysine residues were used as the unlabeled training set. A novel method named PUL-PUP was proposed to predict pupylation sites by using positive-unlabeled learning technique. Our experimental results indicated that PUL-PUP outperforms the other methods significantly for the prediction of pupylation sites. As an application, PUL-PUP was also used to predict the most likely pupylation sites in nonannotated lysine sites.

  5. A grammar inference approach for predicting kinase specific phosphorylation sites.

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    Datta, Sutapa; Mukhopadhyay, Subhasis

    2015-01-01

    Kinase mediated phosphorylation site detection is the key mechanism of post translational mechanism that plays an important role in regulating various cellular processes and phenotypes. Many diseases, like cancer are related with the signaling defects which are associated with protein phosphorylation. Characterizing the protein kinases and their substrates enhances our ability to understand the mechanism of protein phosphorylation and extends our knowledge of signaling network; thereby helping us to treat such diseases. Experimental methods for predicting phosphorylation sites are labour intensive and expensive. Also, manifold increase of protein sequences in the databanks over the years necessitates the improvement of high speed and accurate computational methods for predicting phosphorylation sites in protein sequences. Till date, a number of computational methods have been proposed by various researchers in predicting phosphorylation sites, but there remains much scope of improvement. In this communication, we present a simple and novel method based on Grammatical Inference (GI) approach to automate the prediction of kinase specific phosphorylation sites. In this regard, we have used a popular GI algorithm Alergia to infer Deterministic Stochastic Finite State Automata (DSFA) which equally represents the regular grammar corresponding to the phosphorylation sites. Extensive experiments on several datasets generated by us reveal that, our inferred grammar successfully predicts phosphorylation sites in a kinase specific manner. It performs significantly better when compared with the other existing phosphorylation site prediction methods. We have also compared our inferred DSFA with two other GI inference algorithms. The DSFA generated by our method performs superior which indicates that our method is robust and has a potential for predicting the phosphorylation sites in a kinase specific manner.

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

    Directory of Open Access Journals (Sweden)

    Steffen Kawelke

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

  7. Flood Predictions Combining Regional and Single Site Hydrometric Information

    Directory of Open Access Journals (Sweden)

    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.

  8. Prediction of dental caries activity

    OpenAIRE

    Crossner, Claes-Göran

    1980-01-01

    The aim of the present thesis was to find a test for prediction of caries activity which would be useful in routine clinical work.Correlations between oral health, general health, food habits and socioeconomic conditions were investigated in 4- and 8-year-old children. It was found that the salivary secretion rate and the prevalence of oral lactobacilli were factors which might be useful in caries prediction.In 5- and 8-year-old children negative correlations between caries frequency and secr...

  9. Variable context Markov chains for HIV protease cleavage site prediction.

    Science.gov (United States)

    Oğul, Hasan

    2009-06-01

    Deciphering the knowledge of HIV protease specificity and developing computational tools for detecting its cleavage sites in protein polypeptide chain are very desirable for designing efficient and specific chemical inhibitors to prevent acquired immunodeficiency syndrome. In this study, we developed a generative model based on a generalization of variable order Markov chains (VOMC) for peptide sequences and adapted the model for prediction of their cleavability by certain proteases. The new method, called variable context Markov chains (VCMC), attempts to identify the context equivalence based on the evolutionary similarities between individual amino acids. It was applied for HIV-1 protease cleavage site prediction problem and shown to outperform existing methods in terms of prediction accuracy on a common dataset. In general, the method is a promising tool for prediction of cleavage sites of all proteases and encouraged to be used for any kind of peptide classification problem as well.

  10. Structural descriptor database: a new tool for sequence-based functional site prediction

    Directory of Open Access Journals (Sweden)

    Vasconcelos Ana

    2008-11-01

    Full Text Available Abstract Background The Structural Descriptor Database (SDDB is a web-based tool that predicts the function of proteins and functional site positions based on the structural properties of related protein families. Structural alignments and functional residues of a known protein set (defined as the training set are used to build special Hidden Markov Models (HMM called HMM descriptors. SDDB uses previously calculated and stored HMM descriptors for predicting active sites, binding residues, and protein function. The database integrates biologically relevant data filtered from several databases such as PDB, PDBSUM, CSA and SCOP. It accepts queries in fasta format and predicts functional residue positions, protein-ligand interactions, and protein function, based on the SCOP database. Results To assess the SDDB performance, we used different data sets. The Trypsion-like Serine protease data set assessed how well SDDB predicts functional sites when curated data is available. The SCOP family data set was used to analyze SDDB performance by using training data extracted from PDBSUM (binding sites and from CSA (active sites. The ATP-binding experiment was used to compare our approach with the most current method. For all evaluations, significant improvements were obtained with SDDB. Conclusion SDDB performed better when trusty training data was available. SDDB worked better in predicting active sites rather than binding sites because the former are more conserved than the latter. Nevertheless, by using our prediction method we obtained results with precision above 70%.

  11. A predictive model of intein insertion site for use in the engineering of molecular switches.

    Directory of Open Access Journals (Sweden)

    James Apgar

    Full Text Available Inteins are intervening protein domains with self-splicing ability that can be used as molecular switches to control activity of their host protein. Successfully engineering an intein into a host protein requires identifying an insertion site that permits intein insertion and splicing while allowing for proper folding of the mature protein post-splicing. By analyzing sequence and structure based properties of native intein insertion sites we have identified four features that showed significant correlation with the location of the intein insertion sites, and therefore may be useful in predicting insertion sites in other proteins that provide native-like intein function. Three of these properties, the distance to the active site and dimer interface site, the SVM score of the splice site cassette, and the sequence conservation of the site showed statistically significant correlation and strong predictive power, with area under the curve (AUC values of 0.79, 0.76, and 0.73 respectively, while the distance to secondary structure/loop junction showed significance but with less predictive power (AUC of 0.54. In a case study of 20 insertion sites in the XynB xylanase, two features of native insertion sites showed correlation with the splice sites and demonstrated predictive value in selecting non-native splice sites. Structural modeling of intein insertions at two sites highlighted the role that the insertion site location could play on the ability of the intein to modulate activity of the host protein. These findings can be used to enrich the selection of insertion sites capable of supporting intein splicing and hosting an intein switch.

  12. Active Site Engineering in Electrocatalysis

    DEFF Research Database (Denmark)

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

    on nanostructured electrodes.• Oxygen reduction to water has been carried out on Pt-rare earth alloys, which outperformed the activity of Pt by as much as a factor of five while showing promising stability. The increase in activity can be attributed to compressive strain of the Pt overlayer formed under reaction...... vacuum, as well as theory calculations. The thesis falls in three different parts: firstly, study of model systems for oxygen reduction to water; secondly, oxygen reduction to hydrogen peroxide on both model systems and commercially relevant nanoparticles and thirdly CO2 and CO electroreduction studies...

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

    Directory of Open Access Journals (Sweden)

    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

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

    OpenAIRE

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

    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 ...

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

    Science.gov (United States)

    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.

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

    Institute of Scientific and Technical Information of China (English)

    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.

  17. Expert System for Minefield Site Prediction. Phase 1.

    Science.gov (United States)

    1988-02-01

    2.2111- .25 Jlill 1 MICROCOPY RESOLUTION TLST CHART % %R( % % % % % ko , %% % - Af-A -:A.ZA .A r. ETL-0492 Expert system for minefield site...1. TITLE (Include Security Gassfication) EXPERT SYSTEM FOR MINEFIELD SITE PREDICTION FIRST YEAR REPORT r.. Z. PERSONAL AUTHOR(S) Dillencourt, Michael...identify by block number)FIELD GROUP L SUB-GROUP I Expert System ’ LMinefield,8ite ,rediction - * Quadtree,CTeraiin--nalysis,.t 19, ABSTRACT (Continue on

  18. Prediction of calcium-binding sites by combining loop-modeling with machine learning

    Directory of Open Access Journals (Sweden)

    Altman Russ B

    2009-12-01

    Full Text Available Abstract Background Protein ligand-binding sites in the apo state exhibit structural flexibility. This flexibility often frustrates methods for structure-based recognition of these sites because it leads to the absence of electron density for these critical regions, particularly when they are in surface loops. Methods for recognizing functional sites in these missing loops would be useful for recovering additional functional information. Results We report a hybrid approach for recognizing calcium-binding sites in disordered regions. Our approach combines loop modeling with a machine learning method (FEATURE for structure-based site recognition. For validation, we compared the performance of our method on known calcium-binding sites for which there are both holo and apo structures. When loops in the apo structures are rebuilt using modeling methods, FEATURE identifies 14 out of 20 crystallographically proven calcium-binding sites. It only recognizes 7 out of 20 calcium-binding sites in the initial apo crystal structures. We applied our method to unstructured loops in proteins from SCOP families known to bind calcium in order to discover potential cryptic calcium binding sites. We built 2745 missing loops and evaluated them for potential calcium binding. We made 102 predictions of calcium-binding sites. Ten predictions are consistent with independent experimental verifications. We found indirect experimental evidence for 14 other predictions. The remaining 78 predictions are novel predictions, some with intriguing potential biological significance. In particular, we see an enrichment of beta-sheet folds with predicted calcium binding sites in the connecting loops on the surface that may be important for calcium-mediated function switches. Conclusion Protein crystal structures are a potentially rich source of functional information. When loops are missing in these structures, we may be losing important information about binding sites and active

  19. CERAPP: Collaborative Estrogen Receptor Activity Prediction Project

    Data.gov (United States)

    U.S. Environmental Protection Agency — Data from a large-scale modeling project called CERAPP (Collaborative Estrogen Receptor Activity Prediction Project) demonstrating using predictive computational...

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

  2. Comprehensive prediction of chromosome dimer resolution sites in bacterial genomes

    Directory of Open Access Journals (Sweden)

    Arakawa Kazuharu

    2011-01-01

    Full Text Available Abstract Background During the replication process of bacteria with circular chromosomes, an odd number of homologous recombination events results in concatenated dimer chromosomes that cannot be partitioned into daughter cells. However, many bacteria harbor a conserved dimer resolution machinery consisting of one or two tyrosine recombinases, XerC and XerD, and their 28-bp target site, dif. Results To study the evolution of the dif/XerCD system and its relationship with replication termination, we report the comprehensive prediction of dif sequences in silico using a phylogenetic prediction approach based on iterated hidden Markov modeling. Using this method, dif sites were identified in 641 organisms among 16 phyla, with a 97.64% identification rate for single-chromosome strains. The dif sequence positions were shown to be strongly correlated with the GC skew shift-point that is induced by replicational mutation/selection pressures, but the difference in the positions of the predicted dif sites and the GC skew shift-points did not correlate with the degree of replicational mutation/selection pressures. Conclusions The sequence of dif sites is widely conserved among many bacterial phyla, and they can be computationally identified using our method. The lack of correlation between dif position and the degree of GC skew suggests that replication termination does not occur strictly at dif sites.

  3. Improving prediction of surgical site infection risk with multilevel modeling.

    Directory of Open Access Journals (Sweden)

    Lauren Saunders

    Full Text Available BACKGROUND: Surgical site infection (SSI surveillance is a key factor in the elaboration of strategies to reduce SSI occurrence and in providing surgeons with appropriate data feedback (risk indicators, clinical prediction rule. AIM: To improve the predictive performance of an individual-based SSI risk model by considering a multilevel hierarchical structure. PATIENTS AND METHODS: Data were collected anonymously by the French SSI active surveillance system in 2011. An SSI diagnosis was made by the surgical teams and infection control practitioners following standardized criteria. A random 20% sample comprising 151 hospitals, 502 wards and 62280 patients was used. Three-level (patient, ward, hospital hierarchical logistic regression models were initially performed. Parameters were estimated using the simulation-based Markov Chain Monte Carlo procedure. RESULTS: A total of 623 SSI were diagnosed (1%. The hospital level was discarded from the analysis as it did not contribute to variability of SSI occurrence (p  = 0.32. Established individual risk factors (patient history, surgical procedure and hospitalization characteristics were identified. A significant heterogeneity in SSI occurrence between wards was found (median odds ratio [MOR] 3.59, 95% credibility interval [CI] 3.03 to 4.33 after adjusting for patient-level variables. The effects of the follow-up duration varied between wards (p<10-9, with an increased heterogeneity when follow-up was <15 days (MOR 6.92, 95% CI 5.31 to 9.07]. The final two-level model significantly improved the discriminative accuracy compared to the single level reference model (p<10-9, with an area under the ROC curve of 0.84. CONCLUSION: This study sheds new light on the respective contribution of patient-, ward- and hospital-levels to SSI occurrence and demonstrates the significant impact of the ward level over and above risk factors present at patient level (i.e., independently from patient case-mix.

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

    NARCIS (Netherlands)

    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),

  5. Efficient oxygen electrocatalysis on special active sites

    DEFF Research Database (Denmark)

    Halck, Niels Bendtsen

    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...

  6. Polyadenylation site prediction using PolyA-iEP method.

    Science.gov (United States)

    Kavakiotis, Ioannis; Tzanis, George; Vlahavas, Ioannis

    2014-01-01

    This chapter presents a method called PolyA-iEP that has been developed for the prediction of polyadenylation sites. More precisely, PolyA-iEP is a method that recognizes mRNA 3'ends which contain polyadenylation sites. It is a modular system which consists of two main components. The first exploits the advantages of emerging patterns and the second is a distance-based scoring method. The outputs of the two components are finally combined by a classifier. The final results reach very high scores of sensitivity and specificity.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    Si, Jingna; Cui, Jing; Cheng, Jin; Wu, Rongling

    2015-01-01

    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.

  9. HMMpTM: improving transmembrane protein topology prediction using phosphorylation and glycosylation site prediction.

    Science.gov (United States)

    Tsaousis, Georgios N; Bagos, Pantelis G; Hamodrakas, Stavros J

    2014-02-01

    During the last two decades a large number of computational methods have been developed for predicting transmembrane protein topology. Current predictors rely on topogenic signals in the protein sequence, such as the distribution of positively charged residues in extra-membrane loops and the existence of N-terminal signals. However, phosphorylation and glycosylation are post-translational modifications (PTMs) that occur in a compartment-specific manner and therefore the presence of a phosphorylation or glycosylation site in a transmembrane protein provides topological information. We examine the combination of phosphorylation and glycosylation site prediction with transmembrane protein topology prediction. We report the development of a Hidden Markov Model based method, capable of predicting the topology of transmembrane proteins and the existence of kinase specific phosphorylation and N/O-linked glycosylation sites along the protein sequence. Our method integrates a novel feature in transmembrane protein topology prediction, which results in improved performance for topology prediction and reliable prediction of phosphorylation and glycosylation sites. The method is freely available at http://bioinformatics.biol.uoa.gr/HMMpTM.

  10. Promoter proximal polyadenylation sites reduce transcription activity

    DEFF Research Database (Denmark)

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

    2012-01-01

    Gene expression relies on the functional communication between mRNA processing and transcription. We previously described the negative impact of a point-mutated splice donor (SD) site on transcription. Here we demonstrate that this mutation activates an upstream cryptic polyadenylation (CpA) site...... RNA polymerase II-transcribed genes use specialized termination mechanisms to maintain high transcription levels.......Gene expression relies on the functional communication between mRNA processing and transcription. We previously described the negative impact of a point-mutated splice donor (SD) site on transcription. Here we demonstrate that this mutation activates an upstream cryptic polyadenylation (CpA) site......, which in turn causes reduced transcription. Functional depletion of U1 snRNP in the context of the wild-type SD triggers the same CpA event accompanied by decreased RNA levels. Thus, in accordance with recent findings, U1 snRNP can shield premature pA sites. The negative impact of unshielded pA sites...

  11. Predicting sulfotyrosine sites using the random forest algorithm with significantly improved prediction accuracy

    Directory of Open Access Journals (Sweden)

    Yang Zheng

    2009-10-01

    Full Text Available Abstract Background Tyrosine sulfation is one of the most important posttranslational modifications. Due to its relevance to various disease developments, tyrosine sulfation has become the target for drug design. In order to facilitate efficient drug design, accurate prediction of sulfotyrosine sites is desirable. A predictor published seven years ago has been very successful with claimed prediction accuracy of 98%. However, it has a particularly low sensitivity when predicting sulfotyrosine sites in some newly sequenced proteins. Results A new approach has been developed for predicting sulfotyrosine sites using the random forest algorithm after a careful evaluation of seven machine learning algorithms. Peptides are formed by consecutive residues symmetrically flanking tyrosine sites. They are then encoded using an amino acid hydrophobicity scale. This new approach has increased the sensitivity by 22%, the specificity by 3%, and the total prediction accuracy by 10% compared with the previous predictor using the same blind data. Meanwhile, both negative and positive predictive powers have been increased by 9%. In addition, the random forest model has an excellent feature for ranking the residues flanking tyrosine sites, hence providing more information for further investigating the tyrosine sulfation mechanism. A web tool has been implemented at http://ecsb.ex.ac.uk/sulfotyrosine for public use. Conclusion The random forest algorithm is able to deliver a better model compared with the Hidden Markov Model, the support vector machine, artificial neural networks, and others for predicting sulfotyrosine sites. The success shows that the random forest algorithm together with an amino acid hydrophobicity scale encoding can be a good candidate for peptide classification.

  12. Computational predictions provide insights into the biology of TAL effector target sites.

    Science.gov (United States)

    Grau, Jan; Wolf, Annett; Reschke, Maik; Bonas, Ulla; Posch, Stefan; Boch, Jens

    2013-01-01

    Transcription activator-like (TAL) effectors are injected into host plant cells by Xanthomonas bacteria to function as transcriptional activators for the benefit of the pathogen. The DNA binding domain of TAL effectors is composed of conserved amino acid repeat structures containing repeat-variable diresidues (RVDs) that determine DNA binding specificity. In this paper, we present TALgetter, a new approach for predicting TAL effector target sites based on a statistical model. In contrast to previous approaches, the parameters of TALgetter are estimated from training data computationally. We demonstrate that TALgetter successfully predicts known TAL effector target sites and often yields a greater number of predictions that are consistent with up-regulation in gene expression microarrays than an existing approach, Target Finder of the TALE-NT suite. We study the binding specificities estimated by TALgetter and approve that different RVDs are differently important for transcriptional activation. In subsequent studies, the predictions of TALgetter indicate a previously unreported positional preference of TAL effector target sites relative to the transcription start site. In addition, several TAL effectors are predicted to bind to the TATA-box, which might constitute one general mode of transcriptional activation by TAL effectors. Scrutinizing the predicted target sites of TALgetter, we propose several novel TAL effector virulence targets in rice and sweet orange. TAL-mediated induction of the candidates is supported by gene expression microarrays. Validity of these targets is also supported by functional analogy to known TAL effector targets, by an over-representation of TAL effector targets with similar function, or by a biological function related to pathogen infection. Hence, these predicted TAL effector virulence targets are promising candidates for studying the virulence function of TAL effectors. TALgetter is implemented as part of the open-source Java library

  13. Computational predictions provide insights into the biology of TAL effector target sites.

    Directory of Open Access Journals (Sweden)

    Jan Grau

    Full Text Available Transcription activator-like (TAL effectors are injected into host plant cells by Xanthomonas bacteria to function as transcriptional activators for the benefit of the pathogen. The DNA binding domain of TAL effectors is composed of conserved amino acid repeat structures containing repeat-variable diresidues (RVDs that determine DNA binding specificity. In this paper, we present TALgetter, a new approach for predicting TAL effector target sites based on a statistical model. In contrast to previous approaches, the parameters of TALgetter are estimated from training data computationally. We demonstrate that TALgetter successfully predicts known TAL effector target sites and often yields a greater number of predictions that are consistent with up-regulation in gene expression microarrays than an existing approach, Target Finder of the TALE-NT suite. We study the binding specificities estimated by TALgetter and approve that different RVDs are differently important for transcriptional activation. In subsequent studies, the predictions of TALgetter indicate a previously unreported positional preference of TAL effector target sites relative to the transcription start site. In addition, several TAL effectors are predicted to bind to the TATA-box, which might constitute one general mode of transcriptional activation by TAL effectors. Scrutinizing the predicted target sites of TALgetter, we propose several novel TAL effector virulence targets in rice and sweet orange. TAL-mediated induction of the candidates is supported by gene expression microarrays. Validity of these targets is also supported by functional analogy to known TAL effector targets, by an over-representation of TAL effector targets with similar function, or by a biological function related to pathogen infection. Hence, these predicted TAL effector virulence targets are promising candidates for studying the virulence function of TAL effectors. TALgetter is implemented as part of the open

  14. Gene and translation initiation site prediction in metagenomic sequences

    Energy Technology Data Exchange (ETDEWEB)

    Hyatt, Philip Douglas [ORNL; LoCascio, Philip F [ORNL; Hauser, Loren John [ORNL; Uberbacher, Edward C [ORNL

    2012-01-01

    Gene prediction in metagenomic sequences remains a difficult problem. Current sequencing technologies do not achieve sufficient coverage to assemble the individual genomes in a typical sample; consequently, sequencing runs produce a large number of short sequences whose exact origin is unknown. Since these sequences are usually smaller than the average length of a gene, algorithms must make predictions based on very little data. We present MetaProdigal, a metagenomic version of the gene prediction program Prodigal, that can identify genes in short, anonymous coding sequences with a high degree of accuracy. The novel value of the method consists of enhanced translation initiation site identification, ability to identify sequences that use alternate genetic codes and confidence values for each gene call. We compare the results of MetaProdigal with other methods and conclude with a discussion of future improvements.

  15. Assessment of Mars Exploration Rover Landing Site Predictions

    Science.gov (United States)

    Golombek, M. P.

    2005-05-01

    Comprehensive analyses of remote sensing data during the 3-year effort to select the Mars Exploration Rover landing sites at Gusev crater and Meridiani Planum correctly predicted the safe and trafficable surfaces explored by the two rovers. Gusev crater was predicted to be a relatively low relief surface that was comparably dusty, but less rocky than the Viking landing sites. Available data for Meridiani Planum indicated a very flat plain composed of basaltic sand to granules and hematite that would look completely unlike any of the existing landing sites with a dark, low albedo surface, little dust and very few rocks. Orbital thermal inertia measurements of 315 J m-2 s-0.5 K-1 at Gusev suggested surfaces dominated by duricrust to cemented soil-like materials or cohesionless sand or granules, which is consistent with observed soil characteristics and measured thermal inertias from the surface. THEMIS thermal inertias along the traverse at Gusev vary from 285 at the landing site to 330 around Bonneville rim and show systematic variations that can be related to the observed increase in rock abundance (5-30%). Meridiani has an orbital bulk inertia of ~200, similar to measured surface inertias that correspond to observed surfaces dominated by 0.2 mm sand size particles. Rock abundance derived from orbital thermal differencing techniques suggested that Meridiani Planum would have very low rock abundance, consistent with the rock free plain traversed by Opportunity. Spirit landed in an 8% orbital rock abundance pixel, consistent with the measured 7% of the surface covered by rocks >0.04 m diameter at the landing site, which is representative of the plains away from craters. The orbital albedo of the Spirit traverse varies from 0.19 to 0.30, consistent with surface measurements in and out of dust devil tracks. Opportunity is the first landing in a low albedo portion of Mars as seen from orbit, which is consistent with the dark, dust-free surface and measured albedos. The

  16. Predicting N-terminal myristoylation sites in plant proteins

    Directory of Open Access Journals (Sweden)

    Podell Sheila

    2004-06-01

    Full Text Available Abstract Background N-terminal myristoylation plays a vital role in membrane targeting and signal transduction in plant responses to environmental stress. Although N-myristoyltransferase enzymatic function is conserved across plant, animal, and fungal kingdoms, exact substrate specificities vary, making it difficult to predict protein myristoylation accurately within specific taxonomic groups. Results A new method for predicting N-terminal myristoylation sites specifically in plants has been developed and statistically tested for sensitivity, specificity, and robustness. Compared to previously available methods, the new model is both more sensitive in detecting known positives, and more selective in avoiding false positives. Scores of myristoylated and non-myristoylated proteins are more widely separated than with other methods, greatly reducing ambiguity and the number of sequences giving intermediate, uninformative results. The prediction model is available at http://plantsp.sdsc.edu/myrist.html. Conclusion Superior performance of the new model is due to the selection of a plant-specific training set, covering 266 unique sequence examples from 40 different species, the use of a probability-based hidden Markov model to obtain predictive scores, and a threshold cutoff value chosen to provide maximum positive-negative discrimination. The new model has been used to predict 589 plant proteins likely to contain N-terminal myristoylation signals, and to analyze the functional families in which these proteins occur.

  17. MetWAMer: eukaryotic translation initiation site prediction

    Directory of Open Access Journals (Sweden)

    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.

  18. ESA-UbiSite: accurate prediction of human ubiquitination sites by identifying a set of effective negatives.

    Science.gov (United States)

    Wang, Jyun-Rong; Huang, Wen-Lin; Tsai, Ming-Ju; Hsu, Kai-Ti; Huang, Hui-Ling; Ho, Shinn-Ying

    2017-03-01

    Numerous ubiquitination sites remain undiscovered because of the limitations of mass spectrometry-based methods. Existing prediction methods use randomly selected non-validated sites as non-ubiquitination sites to train ubiquitination site prediction models. We propose an evolutionary screening algorithm (ESA) to select effective negatives among non-validated sites and an ESA-based prediction method, ESA-UbiSite, to identify human ubiquitination sites. The ESA selects non-validated sites least likely to be ubiquitination sites as training negatives. Moreover, the ESA and ESA-UbiSite use a set of well-selected physicochemical properties together with a support vector machine for accurate prediction. Experimental results show that ESA-UbiSite with effective negatives achieved 0.92 test accuracy and a Matthews's correlation coefficient of 0.48, better than existing prediction methods. The ESA increased ESA-UbiSite's test accuracy from 0.75 to 0.92 and can improve other post-translational modification site prediction methods. An ESA-UbiSite-based web server has been established at http://iclab.life.nctu.edu.tw/iclab_webtools/ESAUbiSite/ . syho@mail.nctu.edu.tw. Supplementary data are available at Bioinformatics online.

  19. Method of predicting Splice Sites based on signal interactions

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    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

  1. Human activity recognition and prediction

    CERN Document Server

    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. .

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

    CERN Document Server

    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.

  3. Protein-binding site prediction based on three-dimensional protein modeling.

    Science.gov (United States)

    Oh, Mina; Joo, Keehyoung; Lee, Jooyoung

    2009-01-01

    Structural information of a protein can guide one to understand the function of the protein, and ligand binding is one of the major biochemical functions of proteins. We have applied a two-stage template-based ligand binding site prediction method to CASP8 targets and achieved high quality results with accuracy/coverage = 70/80 (LEE). First, templates are used for protein structure modeling and then for binding site prediction by structural clustering of ligand-containing templates to the predicted protein model. Remarkably, the results are only a few percent worse than those one can obtain from native structures, which were available only after the prediction. Prediction was performed without knowing identity of ligands, and consequently, in many cases the ligand molecules used for prediction were different from the actual ligands, and yet we find that the prediction was quite successful. The current approach can be easily combined with experiments to investigate protein activities in a systematic way. Copyright 2009 Wiley-Liss, Inc.

  4. A machine-learning approach for predicting palmitoylation sites from integrated sequence-based features.

    Science.gov (United States)

    Li, Liqi; Luo, Qifa; Xiao, Weidong; Li, Jinhui; Zhou, Shiwen; Li, Yongsheng; Zheng, Xiaoqi; Yang, Hua

    2017-02-01

    Palmitoylation is the covalent attachment of lipids to amino acid residues in proteins. As an important form of protein posttranslational modification, it increases the hydrophobicity of proteins, which contributes to the protein transportation, organelle localization, and functions, therefore plays an important role in a variety of cell biological processes. Identification of palmitoylation sites is necessary for understanding protein-protein interaction, protein stability, and activity. Since conventional experimental techniques to determine palmitoylation sites in proteins are both labor intensive and costly, a fast and accurate computational approach to predict palmitoylation sites from protein sequences is in urgent need. In this study, a support vector machine (SVM)-based method was proposed through integrating PSI-BLAST profile, physicochemical properties, [Formula: see text]-mer amino acid compositions (AACs), and [Formula: see text]-mer pseudo AACs into the principal feature vector. A recursive feature selection scheme was subsequently implemented to single out the most discriminative features. Finally, an SVM method was implemented to predict palmitoylation sites in proteins based on the optimal features. The proposed method achieved an accuracy of 99.41% and Matthews Correlation Coefficient of 0.9773 for a benchmark dataset. The result indicates the efficiency and accuracy of our method in prediction of palmitoylation sites based on protein sequences.

  5. Probabilistic Assessment of Above Zone Pressure Predictions at a Geologic Carbon Storage Site

    Science.gov (United States)

    Namhata, Argha; Oladyshkin, Sergey; Dilmore, Robert M.; Zhang, Liwei; Nakles, David V.

    2016-12-01

    Carbon dioxide (CO2) storage into geological formations is regarded as an important mitigation strategy for anthropogenic CO2 emissions to the atmosphere. This study first simulates the leakage of CO2 and brine from a storage reservoir through the caprock. Then, we estimate the resulting pressure changes at the zone overlying the caprock also known as Above Zone Monitoring Interval (AZMI). A data-driven approach of arbitrary Polynomial Chaos (aPC) Expansion is then used to quantify the uncertainty in the above zone pressure prediction based on the uncertainties in different geologic parameters. Finally, a global sensitivity analysis is performed with Sobol indices based on the aPC technique to determine the relative importance of different parameters on pressure prediction. The results indicate that there can be uncertainty in pressure prediction locally around the leakage zones. The degree of such uncertainty in prediction depends on the quality of site specific information available for analysis. The scientific results from this study provide substantial insight that there is a need for site-specific data for efficient predictions of risks associated with storage activities. The presented approach can provide a basis of optimized pressure based monitoring network design at carbon storage sites.

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

    Science.gov (United States)

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

    2016-08-01

    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.

  7. Prediction of biological functions on glycosylation site migrations in human influenza H1N1 viruses.

    Science.gov (United States)

    Sun, Shisheng; Wang, Qinzhe; Zhao, Fei; Chen, Wentian; Li, Zheng

    2012-01-01

    Protein glycosylation alteration is typically employed by various viruses for escaping immune pressures from their hosts. Our previous work had shown that not only the increase of glycosylation sites (glycosites) numbers, but also glycosite migration might be involved in the evolution of human seasonal influenza H1N1 viruses. More importantly, glycosite migration was likely a more effectively alteration way for the host adaption of human influenza H1N1 viruses. In this study, we provided more bioinformatics and statistic evidences for further predicting the significant biological functions of glycosite migration in the host adaptation of human influenza H1N1 viruses, by employing homology modeling and in silico protein glycosylation of representative HA and NA proteins as well as amino acid variability analysis at antigenic sites of HA and NA. The results showed that glycosite migrations in human influenza viruses have at least five possible functions: to more effectively mask the antigenic sites, to more effectively protect the enzymatic cleavage sites of neuraminidase (NA), to stabilize the polymeric structures, to regulate the receptor binding and catalytic activities and to balance the binding activity of hemagglutinin (HA) with the release activity of NA. The information here can provide some constructive suggestions for the function research related to protein glycosylation of influenza viruses, although these predictions still need to be supported by experimental data.

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

    DEFF Research Database (Denmark)

    Julenius, Karin; Mølgaard, Anne; Gupta, Ramneek

    2005-01-01

    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...... predictions from the best overall network and the best isolated site network; this prediction method correctly predicted 76% of the glycosylated residues and 93% of the nonglycosylated residues. NetOGlyc 3.1 can predict sites for completely new proteins without losing its performance. The fact that the sites...

  9. Performance prediction for Grid workflow activities based on features-ranked RBF network

    Institute of Scientific and Technical Information of China (English)

    Wang Jie; Duan Rubing; Farrukh Nadeem

    2009-01-01

    Accurate performance prediction of Grid workflow activities can help Grid schedulers map activities to appropriate Grid sites. This paper describes an approach based on features-ranked RBF neural network to predict the performance of Grid workflow activities. Experimental results for two kinds of real world Grid workflow activities are presented to show effectiveness of our approach.

  10. Dynamo theory prediction of solar activity

    Science.gov (United States)

    Schatten, Kenneth H.

    1988-01-01

    The dynamo theory technique to predict decadal time scale solar activity variations is introduced. The technique was developed following puzzling correlations involved with geomagnetic precursors of solar activity. Based upon this, a dynamo theory method was developed to predict solar activity. The method was used successfully in solar cycle 21 by Schatten, Scherrer, Svalgaard, and Wilcox, after testing with 8 prior solar cycles. Schatten and Sofia used the technique to predict an exceptionally large cycle, peaking early (in 1990) with a sunspot value near 170, likely the second largest on record. Sunspot numbers are increasing, suggesting that: (1) a large cycle is developing, and (2) that the cycle may even surpass the largest cycle (19). A Sporer Butterfly method shows that the cycle can now be expected to peak in the latter half of 1989, consistent with an amplitude comparable to the value predicted near the last solar minimum.

  11. Activity Prediction: A Twitter-based Exploration

    NARCIS (Netherlands)

    Weerkamp, W.; de Rijke, 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, th

  12. Snow multivariable data assimilation for hydrological predictions in Alpine sites

    Science.gov (United States)

    Piazzi, Gaia; Thirel, Guillaume; Campo, Lorenzo; Gabellani, Simone; Stevenin, Hervè

    2017-04-01

    Snowpack dynamics (snow accumulation and ablation) strongly impacts on hydrological processes in Alpine areas. During the winter season the presence of snow cover (snow accumulation) reduces the drainage in the basin with a resulting lower watershed time of concentration in case of possible rainfall events. Moreover, the release of the significant water volume stored in winter (snowmelt) considerably contributes to the total discharge during the melting period. Therefore when modeling hydrological processes in snow-dominated catchments the quality of predictions deeply depends on how the model succeeds in catching snowpack dynamics. The integration of a hydrological model with a snow module allows improving predictions of river discharges. Besides the well-known modeling limitations (uncertainty in parameterizations; possible errors affecting both meteorological forcing data and initial conditions; approximations in boundary conditions), there are physical factors that make an exhaustive reconstruction of snow dynamics complicated: snow intermittence in space and time, stratification and slow phenomena like metamorphism processes, uncertainty in snowfall evaluation, wind transportation, etc. Data Assimilation (DA) techniques provide an objective methodology to combine several independent snow-related data sources (model simulations, ground-based measurements and remote sensed observations) in order to obtain the most likely estimate of snowpack state. This study presents SMASH (Snow Multidata Assimilation System for Hydrology), a multi-layer snow dynamic model strengthened by a multivariable DA framework for hydrological purposes. The model is physically based on mass and energy balances and can be used to reproduce the main physical processes occurring within the snowpack: accumulation, density dynamics, melting, sublimation, radiative balance, heat and mass exchanges. The model is driven by observed forcing meteorological data (air temperature, wind velocity

  13. Prediction of nucleosome positioning based on transcription factor binding sites.

    Directory of Open Access Journals (Sweden)

    Xianfu Yi

    Full Text Available BACKGROUND: The DNA of all eukaryotic organisms is packaged into nucleosomes, the basic repeating units of chromatin. The nucleosome consists of a histone octamer around which a DNA core is wrapped and the linker histone H1, which is associated with linker DNA. By altering the accessibility of DNA sequences, the nucleosome has profound effects on all DNA-dependent processes. Understanding the factors that influence nucleosome positioning is of great importance for the study of genomic control mechanisms. Transcription factors (TFs have been suggested to play a role in nucleosome positioning in vivo. PRINCIPAL FINDINGS: Here, the minimum redundancy maximum relevance (mRMR feature selection algorithm, the nearest neighbor algorithm (NNA, and the incremental feature selection (IFS method were used to identify the most important TFs that either favor or inhibit nucleosome positioning by analyzing the numbers of transcription factor binding sites (TFBSs in 53,021 nucleosomal DNA sequences and 50,299 linker DNA sequences. A total of nine important families of TFs were extracted from 35 families, and the overall prediction accuracy was 87.4% as evaluated by the jackknife cross-validation test. CONCLUSIONS: Our results are consistent with the notion that TFs are more likely to bind linker DNA sequences than the sequences in the nucleosomes. In addition, our results imply that there may be some TFs that are important for nucleosome positioning but that play an insignificant role in discriminating nucleosome-forming DNA sequences from nucleosome-inhibiting DNA sequences. The hypothesis that TFs play a role in nucleosome positioning is, thus, confirmed by the results of this study.

  14. Study the active site of flavonoid applying radiation chemistry

    Energy Technology Data Exchange (ETDEWEB)

    Wu Jilan; Sun Gang; Zhang Fugen; He Yongke; Li Jiuqiang [Department of Technical Physics, Peking Univ., Beijing (China)

    2000-03-01

    Flavonoid are a large and important class of naturally occurring, low molecular weight benzo-{gamma}-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)

  15. Factors predicting surgical site infection after posterior lumbar surgery

    Science.gov (United States)

    Wang, Tao; Wang, Hui; Yang, Da-Long; Jiang, Li-Qiang; Zhang, Li-Jun; Ding, Wen-Yuan

    2017-01-01

    Abstract This is a retrospective study. The purpose of this study is to explore incidence and risk factors for surgical site infection (SSI) after posterior lumbar surgery. SSI is a common complication after posterior lumbar surgery, bringing mental and physical pain and prolonging hospital stay. However, predisposing factors, as reported less, remain controversial. Patients who underwent posterior lumbar surgery at 3 centers between 2006 and 2016 were included. The possible factors include 3 aspects: demographic variables-age, sex, body mass index (BMI), waist-to-hip radio (WHR), hypertension, diabetes, heart disease, smoking, drinking, steroidal injection, surgical time between June and September, preoperative shower; blood test variables-white blood cell (WBC), neutrophil, red blood cell (RBC), hemoglobin (Hb), total protein (TP), albumin, albumin/globulin (A/G), C-reactive protein (CRP), procalcitonin (PCT), erythrocyte sedimentation rate (ESR) and surgical related variables-operation time, blood loss, operative level, instrumentation, incision length. Factors related with SSI were also performed by multivariate analysis. The prevalence of SSI was 3.00% (267 cases of 8879) had a postoperative wound infection. There were significant difference in WHR (0.92 vs 0.83), WBC (4.31 vs 6.69), TP (58.7 vs 65.2), albumin (36.9 vs 43.2), CRP (2.01 vs 0.57), PCT (0.097 vs 0.067), operation time (217.9 vs 195.7), blood loss (997.1 vs 915.3) and operative level (3.05 vs 2.45) and incision length (24.1 vs 20.0) between SSI group and non-SSI group. >60 years old, female, BMI 30.0, diabetes, male smoking, preoperative steroidal injection, surgical time between June and September, no preoperative shower, instrumentation surgery were risk factors for SSI after posterior lumbar surgery. Many factors, >60 years old, female, BMI, WHR, diabetes, male smoking, preoperative steroidal injection, surgical time between June and September, preoperative shower, WBC, TP, albumin, CRP, PCT

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

    Directory of Open Access Journals (Sweden)

    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

  17. Clostripain: Characterization of the active site

    National Research Council Canada - National Science Library

    Kembhavi, Ashu A; Buttle, David J; Rauber, Peter; Barrett, Alan J

    1991-01-01

    ... + for stability and activity. Mg 2+ and Sr 2+ were ineffective. Rapid inactivation by diethylpyrocarbonate, reversed by hydroxylamine, indicated that histidine is essential for catalytic activity...

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

    Institute of Scientific and Technical Information of China (English)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

  20. Homology modeling and functional sites prediction of azoreductase enzyme from the cyanobacterium Nostoc sp. PCC7120.

    Science.gov (United States)

    Devi, Philem Priyadarshini; Adhikari, Samrat

    2012-12-01

    Industrial dyes such as azodyes are potential environmental pollutants causing deleterious health hazards complications. These dyes are potentially degraded by azoreductase enzyme which is widely distributed in bacteria and also cyanobacteria. The azoreductase enzymes from cyanobacteria have not been explored in detail. Hence this enzyme from Nostoc sp. PCC 7120 has been addressed in detail in the present study considering to explore the physico-chemical properties, evolutionary relationships, functional sites and structural properties using various bioinformatics tools. Four conserved regions were obtained from the multiple sequence analysis. The multiple sequence alignment showed conserved regions at different stretches from 1-11, 40-57, 82-120 and 161-177 amino acid residues. These regions could be used for designing degenerate primers or probes for PCR-based amplification or hybridization-based detection of azoreductase sequences from different source organisms. Domain analysis and functional site prediction showed the presence of functional sites and domain such as flavodoxin like fold responsible for enzyme activity. 3D model was constructed and the best model was selected and validated. Superimposition of the final structure and the template showed variations in certain regions which might be involved in the accommodation of various dyes. Our results may be helpful for further investigations like docking studies as well as in vivo and in vitro conditions although these predictions still need to be studied.

  1. Predicting enzymatic function from global binding site descriptors.

    Science.gov (United States)

    Volkamer, Andrea; Kuhn, Daniel; Rippmann, Friedrich; Rarey, Matthias

    2013-03-01

    Due to the rising number of solved protein structures, computer-based techniques for automatic protein functional annotation and classification into families are of high scientific interest. DoGSiteScorer automatically calculates global descriptors for self-predicted pockets based on the 3D structure of a protein. Protein function predictors on three levels with increasing granularity are built by use of a support vector machine (SVM), based on descriptors of 26632 pockets from enzymes with known structure and enzyme classification. The SVM models represent a generalization of the available descriptor space for each enzyme class, subclass, and substrate-specific sub-subclass. Cross-validation studies show accuracies of 68.2% for predicting the correct main class and accuracies between 62.8% and 80.9% for the six subclasses. Substrate-specific recall rates for a kinase subset are 53.8%. Furthermore, application studies show the ability of the method for predicting the function of unknown proteins and gaining valuable information for the function prediction field. Copyright © 2012 Wiley Periodicals, Inc.

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

    Directory of Open Access Journals (Sweden)

    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. Savannah River Site prioritization of transition activities

    Energy Technology Data Exchange (ETDEWEB)

    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.

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

    DEFF Research Database (Denmark)

    Ehrlich, L.; Reczko, M.; Bohr, Henrik;

    1998-01-01

    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 t...... provide insight into the mutual interdependencies between the location of ordered water sites and the structural and chemical characteristics of the protein residues.......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...... structure and solvent accessibility and, using actual values of these properties, redidue hydration can be predicted to 77% accuracy with a Metthews coefficient of 0.43. However, predicted property data with an accuracy of 60-70% result in less than half the improvement in predictive performance observed...

  5. POLYAR, a new computer program for prediction of poly(A sites in human sequences

    Directory of Open Access Journals (Sweden)

    Qamar Raheel

    2010-11-01

    Full Text Available Abstract Background mRNA polyadenylation is an essential step of pre-mRNA processing in eukaryotes. Accurate prediction of the pre-mRNA 3'-end cleavage/polyadenylation sites is important for defining the gene boundaries and understanding gene expression mechanisms. Results 28761 human mapped poly(A sites have been classified into three classes containing different known forms of polyadenylation signal (PAS or none of them (PAS-strong, PAS-weak and PAS-less, respectively and a new computer program POLYAR for the prediction of poly(A sites of each class was developed. In comparison with polya_svm (till date the most accurate computer program for prediction of poly(A sites while searching for PAS-strong poly(A sites in human sequences, POLYAR had a significantly higher prediction sensitivity (80.8% versus 65.7% and specificity (66.4% versus 51.7% However, when a similar sort of search was conducted for PAS-weak and PAS-less poly(A sites, both programs had a very low prediction accuracy, which indicates that our knowledge about factors involved in the determination of the poly(A sites is not sufficient to identify such polyadenylation regions. Conclusions We present a new classification of polyadenylation sites into three classes and a novel computer program POLYAR for prediction of poly(A sites/regions of each of the class. In tests, POLYAR shows high accuracy of prediction of the PAS-strong poly(A sites, though this program's efficiency in searching for PAS-weak and PAS-less poly(A sites is not very high but is comparable to other available programs. These findings suggest that additional characteristics of such poly(A sites remain to be elucidated. POLYAR program with a stand-alone version for downloading is available at http://cub.comsats.edu.pk/polyapredict.htm.

  6. Predicting proteasomal cleavage sites: a comparison of available methods

    DEFF Research Database (Denmark)

    Saxova, P.; Buus, S.; Brunak, Søren

    2003-01-01

    The proteasome plays an essential role in the immune responses of vertebrates. By degrading intercellular proteins from self and non-self, the proteasome produces the majority of the peptides that are presented to cytotoxic T cells (CTL). There is accumulating evidence that the C......-terminal, in particular, of CTL epitopes is cleaved precisely by the proteasome, whereas the N-terminal is produced with an extension, and later trimmed by peptidases in the cytoplasm and in the endoplasmic reticulum. Recently, three publicly available methods have been developed for prediction of the specificity...... of the proteasome. Here, we compare the performance of these methods on a large set of CTL epitopes. The best method, NetChop at www.cbs.dtu.dk/Services/NetChop, can capture similar to70% of the C-termini correctly. This result suggests that the predictions can still be improved, particularly if more quantitative...

  7. Prediction control of active power filters

    Institute of Scientific and Technical Information of China (English)

    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.

  8. Utilizing Selected Di- and Trinucleotides of siRNA to Predict RNAi Activity

    Directory of Open Access Journals (Sweden)

    Ye Han

    2017-01-01

    Full Text Available Small interfering RNAs (siRNAs induce posttranscriptional gene silencing in various organisms. siRNAs targeted to different positions of the same gene show different effectiveness; hence, predicting siRNA activity is a crucial step. In this paper, we developed and evaluated a powerful tool named “siRNApred” with a new mixed feature set to predict siRNA activity. To improve the prediction accuracy, we proposed 2-3NTs as our new features. A Random Forest siRNA activity prediction model was constructed using the feature set selected by our proposed Binary Search Feature Selection (BSFS algorithm. Experimental data demonstrated that the binding site of the Argonaute protein correlates with siRNA activity. “siRNApred” is effective for selecting active siRNAs, and the prediction results demonstrate that our method can outperform other current siRNA activity prediction methods in terms of prediction accuracy.

  9. Kinase-specific prediction of protein phosphorylation sites

    DEFF Research Database (Denmark)

    Miller, Martin Lee; Blom, Nikolaj

    2009-01-01

    -substrate specificity. Here, we briefly describe the available resources for predicting kinase-specific phosphorylation from sequence properties. We address the strengths and weaknesses of these resources, which are based on methods ranging from simple consensus patterns to more advanced machine-learning algorithms....... Furthermore, a protocol for the use of the artificial neural network based predictors, NetPhos and NetPhosK, is provided. Finally, we point to possible developments with the intention of providing the community with improved and additional phosphorylation predictors for large-scale modeling of cellular...... signaling networks....

  10. RADIOLYTIC HYDROGEN GENERATION INSAVANNAH RIVER SITE (SRS) HIGH LEVEL WASTETANKS COMPARISON OF SRS AND HANFORDMODELING PREDICTIONS

    Energy Technology Data Exchange (ETDEWEB)

    Crawford, C; Ned Bibler, N

    2009-04-15

    In the high level waste tanks at the Savannah River Site (SRS), hydrogen is produced continuously by interaction of the radiation in the tank with water in the waste. Consequently, the vapor spaces of the tanks are purged to prevent the accumulation of H{sub 2} and possible formation of a flammable mixture in a tank. Personnel at SRS have developed an empirical model to predict the rate of H{sub 2} formation in a tank. The basis of this model is the prediction of the G value for H{sub 2} production. This G value is the number of H{sub 2} molecules produced per 100 eV of radiolytic energy absorbed by the waste. Based on experimental studies it was found that the G value for H{sub 2} production from beta radiation and from gamma radiation were essentially equal. The G value for H{sub 2} production from alpha radiation was somewhat higher. Thus, the model has two equations, one for beta/gamma radiation and one for alpha radiation. Experimental studies have also indicated that both G values are decreased by the presence of nitrate and nitrite ions in the waste. These are the main scavengers for the precursors of H{sub 2} in the waste; thus the equations that were developed predict G values for hydrogen production as a function of the concentrations of these two ions in waste. Knowing the beta/gamma and alpha heat loads in the waste allows one to predict the total generation rate for hydrogen in a tank. With this prediction a ventilation rate can be established for each tank to ensure that a flammable mixture is not formed in the vapor space in a tank. Recently personnel at Hanford have developed a slightly different model for predicting hydrogen G values. Their model includes the same precursor for H{sub 2} as the SRS model but also includes an additional precursor not in the SRS model. Including the second precursor for H{sub 2} leads to different empirical equations for predicting the G values for H{sub 2} as a function of the nitrate and nitrite concentrations in

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

    Institute of Scientific and Technical Information of China (English)

    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.

  12. Diffusional correlations among multiple active sites in a single enzyme.

    Science.gov (United States)

    Echeverria, Carlos; Kapral, Raymond

    2014-04-07

    Simulations of the enzymatic dynamics of a model enzyme containing multiple substrate binding sites indicate the existence of diffusional correlations in the chemical reactivity of the active sites. A coarse-grain, particle-based, mesoscopic description of the system, comprising the enzyme, the substrate, the product and solvent, is constructed to study these effects. The reactive and non-reactive dynamics is followed using a hybrid scheme that combines molecular dynamics for the enzyme, substrate and product molecules with multiparticle collision dynamics for the solvent. It is found that the reactivity of an individual active site in the multiple-active-site enzyme is reduced substantially, and this effect is analyzed and attributed to diffusive competition for the substrate among the different active sites in the enzyme.

  13. Perspective: On the active site model in computational catalyst screening

    Science.gov (United States)

    Reuter, Karsten; Plaisance, Craig P.; Oberhofer, Harald; Andersen, Mie

    2017-01-01

    First-principles screening approaches exploiting energy trends in surface adsorption represent an unparalleled success story in recent computational catalysis research. Here we argue that our still limited understanding of the structure of active sites is one of the major bottlenecks towards an ever extended and reliable use of such computational screening for catalyst discovery. For low-index transition metal surfaces, the prevalently chosen high-symmetry (terrace and step) sites offered by the nominal bulk-truncated crystal lattice might be justified. For more complex surfaces and composite catalyst materials, computational screening studies will need to actively embrace a considerable uncertainty with respect to what truly are the active sites. By systematically exploring the space of possible active site motifs, such studies might eventually contribute towards a targeted design of optimized sites in future catalysts.

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

    DEFF Research Database (Denmark)

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

    2004-01-01

    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...... could be predicted from averaged properties together with the fact that glycosylation sites are not precisely conserved indicates that mucin-type glycosylation in most cases is a bulk property and not a very site-specific one. NetOGlyc 3.1 is made available at www.cbs.dtu.dk/services/netoglyc....

  15. Recent Progress in Predicting Posttranslational Modification Sites in Proteins.

    Science.gov (United States)

    Xu, Yan; Chou, Kuo-Chen

    2016-01-01

    The posttranslational modification or PTM is a later but subtle step in protein biosynthesis via which to change the properties of a protein by adding a modified group to its one or more amino acid residues. PTMs are responsible for many significant biological processes, and meanwhile for many major diseases as well, such as cancer. Facing the avalanche of biological sequences generated in the post-genomic age, it is important for both basic research and drug development to timely identify the PTM sites in proteins. This Review is devoted to summarize the recent progresses in this area, with a focus on those predictors, which were developed based on the pseudo amino acid composition or PseAAC approach, and for which a publicly accessible web-server has been established. Meanwhile, the future challenge in this area has also been briefly addressed.

  16. CERAPP: Collaborative estrogen receptor activity prediction project

    DEFF Research Database (Denmark)

    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...

  17. Predicting DNA-binding sites of proteins based on sequential and 3D structural information.

    Science.gov (United States)

    Li, Bi-Qing; Feng, Kai-Yan; Ding, Juan; Cai, Yu-Dong

    2014-06-01

    Protein-DNA interactions play important roles in many biological processes. To understand the molecular mechanisms of protein-DNA interaction, it is necessary to identify the DNA-binding sites in DNA-binding proteins. In the last decade, computational approaches have been developed to predict protein-DNA-binding sites based solely on protein sequences. In this study, we developed a novel predictor based on support vector machine algorithm coupled with the maximum relevance minimum redundancy method followed by incremental feature selection. We incorporated not only features of physicochemical/biochemical properties, sequence conservation, residual disorder, secondary structure, solvent accessibility, but also five three-dimensional (3D) structural features calculated from PDB data to predict the protein-DNA interaction sites. Feature analysis showed that 3D structural features indeed contributed to the prediction of DNA-binding site and it was demonstrated that the prediction performance was better with 3D structural features than without them. It was also shown via analysis of features from each site that the features of DNA-binding site itself contribute the most to the prediction. Our prediction method may become a useful tool for identifying the DNA-binding sites and the feature analysis described in this paper may provide useful insights for in-depth investigations into the mechanisms of protein-DNA interaction.

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

    Institute of Scientific and Technical Information of China (English)

    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.

  19. A Large-Scale Assessment of Nucleic Acids Binding Site Prediction Programs

    OpenAIRE

    Miao, Zhichao; Westhof, Eric

    2015-01-01

    Computational prediction of nucleic acid binding sites in proteins are necessary to disentangle functional mechanisms in most biological processes and to explore the binding mechanisms. Several strategies have been proposed, but the state-of-the-art approaches display a great diversity in i) the definition of nucleic acid binding sites; ii) the training and test datasets; iii) the algorithmic methods for the prediction strategies; iv) the performance measures and v) the distribution and avail...

  20. A Large-Scale Assessment of Nucleic Acids Binding Site Prediction Programs.

    OpenAIRE

    Zhichao Miao; Eric Westhof

    2015-01-01

    Computational prediction of nucleic acid binding sites in proteins are necessary to disentangle functional mechanisms in most biological processes and to explore the binding mechanisms. Several strategies have been proposed, but the state-of-the-art approaches display a great diversity in i) the definition of nucleic acid binding sites; ii) the training and test datasets; iii) the algorithmic methods for the prediction strategies; iv) the performance measures and v) the distribution and avail...

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

    Directory of Open Access Journals (Sweden)

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

    KAUST Repository

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

  4. Using TESS to predict transcription factor binding sites in DNA sequence.

    Science.gov (United States)

    Schug, Jonathan

    2008-03-01

    This unit describes how to use the Transcription Element Search System (TESS). This Web site predicts transcription factor binding sites (TFBS) in DNA sequence using two different kinds of models of sites, strings and positional weight matrices. The binding of transcription factors to DNA is a major part of the control of gene expression. Transcription factors exhibit sequence-specific binding; they form stronger bonds to some DNA sequences than to others. Identification of a good binding site in the promoter for a gene suggests the possibility that the corresponding factor may play a role in the regulation of that gene. However, the sequences transcription factors recognize are typically short and allow for some amount of mismatch. Because of this, binding sites for a factor can typically be found at random every few hundred to a thousand base pairs. TESS has features to help sort through and evaluate the significance of predicted sites.

  5. Physical activity and cancer risk: dose-response and cancer, all sites and site-specific.

    Science.gov (United States)

    Thune, I; Furberg, A S

    2001-06-01

    The association between physical activity and overall and site-specific cancer risk is elaborated in relation to whether any observed dose-response association between physical activity and cancer can be interpreted in terms of how much physical activity (type, intensity, duration, frequency) is needed to influence site- and gender-specific cancer risk. Observational studies were reviewed that have examined the independent effect of the volume of occupational physical activity (OPA) and/or leisure time physical activity (LPA) on overall and site-specific cancer risk. The evidence of cohort and case-control studies suggests that both leisure time and occupational physical activity protect against overall cancer risk, with a graded dose-response association suggested in both sexes. Confounding effects such as diet, body weight, and parity are often included as a covariate in the analyses, with little influence on the observed associations. A crude graded inverse dose-response association was observed between physical activity and colon cancer in 48 studies including 40,674 colon/colorectal cancer cases for both sexes. A dose-response effect of physical activity on colon cancer risk was especially observed, when participation in activities of at least moderate activity (>4.5 MET) and demonstrated by activities expressed as MET-hours per week. An observed inverse association with a dose-response relationship between physical activity and breast cancer was also identified in the majority of the 41 studies including 108,031 breast cancer cases. The dose-response relationship was in particular observed in case-control studies and supported by observations in cohort studies when participation in activities of at least moderate activity (>4.5 MET) and demonstrated by activities expressed by MET-hours per week. This association between physical activity and breast cancer risk is possibly dependent on age at exposure, age at diagnosis, menopausal status and other effect

  6. NetPhosYeast: prediction of protein phosphorylation sites in yeast

    DEFF Research Database (Denmark)

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

    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 s...

  7. Genome-wide prediction, display and refinement of binding sites with information theory-based models

    Directory of Open Access Journals (Sweden)

    Leeder J Steven

    2003-09-01

    Full Text Available Abstract Background We present Delila-genome, a software system for identification, visualization and analysis of protein binding sites in complete genome sequences. Binding sites are predicted by scanning genomic sequences with information theory-based (or user-defined weight matrices. Matrices are refined by adding experimentally-defined binding sites to published binding sites. Delila-Genome was used to examine the accuracy of individual information contents of binding sites detected with refined matrices as a measure of the strengths of the corresponding protein-nucleic acid interactions. The software can then be used to predict novel sites by rescanning the genome with the refined matrices. Results Parameters for genome scans are entered using a Java-based GUI interface and backend scripts in Perl. Multi-processor CPU load-sharing minimized the average response time for scans of different chromosomes. Scans of human genome assemblies required 4–6 hours for transcription factor binding sites and 10–19 hours for splice sites, respectively, on 24- and 3-node Mosix and Beowulf clusters. Individual binding sites are displayed either as high-resolution sequence walkers or in low-resolution custom tracks in the UCSC genome browser. For large datasets, we applied a data reduction strategy that limited displays of binding sites exceeding a threshold information content to specific chromosomal regions within or adjacent to genes. An HTML document is produced listing binding sites ranked by binding site strength or chromosomal location hyperlinked to the UCSC custom track, other annotation databases and binding site sequences. Post-genome scan tools parse binding site annotations of selected chromosome intervals and compare the results of genome scans using different weight matrices. Comparisons of multiple genome scans can display binding sites that are unique to each scan and identify sites with significantly altered binding strengths

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

    DEFF Research Database (Denmark)

    Ehrlich, L.; Reczko, M.; Bohr, Henrik

    1998-01-01

    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 t...

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

    LENUS (Irish Health Repository)

    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.

  10. CaMELS: In silico prediction of calmodulin binding proteins and their binding sites.

    Science.gov (United States)

    Abbasi, Wajid Arshad; Asif, Amina; Andleeb, Saiqa; Minhas, Fayyaz Ul Amir Afsar

    2017-09-01

    Due to Ca(2+) -dependent binding and the sequence diversity of Calmodulin (CaM) binding proteins, identifying CaM interactions and binding sites in the wet-lab is tedious and costly. Therefore, computational methods for this purpose are crucial to the design of such wet-lab experiments. We present an algorithm suite called CaMELS (CalModulin intEraction Learning System) for predicting proteins that interact with CaM as well as their binding sites using sequence information alone. CaMELS offers state of the art accuracy for both CaM interaction and binding site prediction and can aid biologists in studying CaM binding proteins. For CaM interaction prediction, CaMELS uses protein sequence features coupled with a large-margin classifier. CaMELS models the binding site prediction problem using multiple instance machine learning with a custom optimization algorithm which allows more effective learning over imprecisely annotated CaM-binding sites during training. CaMELS has been extensively benchmarked using a variety of data sets, mutagenic studies, proteome-wide Gene Ontology enrichment analyses and protein structures. Our experiments indicate that CaMELS outperforms simple motif-based search and other existing methods for interaction and binding site prediction. We have also found that the whole sequence of a protein, rather than just its binding site, is important for predicting its interaction with CaM. Using the machine learning model in CaMELS, we have identified important features of protein sequences for CaM interaction prediction as well as characteristic amino acid sub-sequences and their relative position for identifying CaM binding sites. Python code for training and evaluating CaMELS together with a webserver implementation is available at the URL: http://faculty.pieas.edu.pk/fayyaz/software.html#camels. © 2017 Wiley Periodicals, Inc.

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

    Science.gov (United States)

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

    2011-07-01

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

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

    Science.gov (United States)

    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.

  13. Prediction of post-translational modification sites using multiple kernel support vector machine

    Directory of Open Access Journals (Sweden)

    BingHua Wang

    2017-04-01

    Full Text Available Protein post-translational modification (PTM is an important mechanism that is involved in the regulation of protein function. Considering the high-cost and labor-intensive of experimental identification, many computational prediction methods are currently available for the prediction of PTM sites by using protein local sequence information in the context of conserved motif. Here we proposed a novel computational method by using the combination of multiple kernel support vector machines (SVM for predicting PTM sites including phosphorylation, O-linked glycosylation, acetylation, sulfation and nitration. To largely make use of local sequence information and site-modification relationships, we developed a local sequence kernel and Gaussian interaction profile kernel, respectively. Multiple kernels were further combined to train SVM for efficiently leveraging kernel information to boost predictive performance. We compared the proposed method with existing PTM prediction methods. The experimental results revealed that the proposed method performed comparable or better performance than the existing prediction methods, suggesting the feasibility of the developed kernels and the usefulness of the proposed method in PTM sites prediction.

  14. Real-time seismic intensity prediction using frequency-dependent site amplification factors

    Science.gov (United States)

    Ogiso, Masashi; Aoki, Shigeki; Hoshiba, Mitsuyuki

    2016-05-01

    A promising approach for the next generation of earthquake early warning system is based on predicting ground motion directly from observed ground motion, without any information of hypocenter. In this study, we predicted seismic intensity at the target stations from the observed ground motion at adjacent stations, employing two different methods of correction for site amplification factors. The first method was frequency-dependent correction prediction, in which we used a digital causal filter to correct the site amplification for the observed waveform in the time domain. The second method was scalar correction, in which we used average differences in seismic intensity between two stations for the site amplification correction. Results from thousands of station pairs that covered almost all of Japan showed that seismic intensity prediction with frequency-dependent correction prediction was more accurate than prediction with scalar correction. Frequency-dependent correction for site amplification in the time domain may lead to more accurate prediction of ground motion in real time.

  15. Methanopyrus kandleri topoisomerase V contains three distinct AP lyase active sites in addition to the topoisomerase active site.

    Science.gov (United States)

    Rajan, Rakhi; Osterman, Amy; Mondragón, Alfonso

    2016-04-20

    Topoisomerase V (Topo-V) is the only topoisomerase with both topoisomerase and DNA repair activities. The topoisomerase activity is conferred by a small alpha-helical domain, whereas the AP lyase activity is found in a region formed by 12 tandem helix-hairpin-helix ((HhH)2) domains. Although it was known that Topo-V has multiple repair sites, only one had been mapped. Here, we show that Topo-V has three AP lyase sites. The atomic structure and Small Angle X-ray Scattering studies of a 97 kDa fragment spanning the topoisomerase and 10 (HhH)2 domains reveal that the (HhH)2 domains extend away from the topoisomerase domain. A combination of biochemical and structural observations allow the mapping of the second repair site to the junction of the 9th and 10th (HhH)2 domains. The second site is structurally similar to the first one and to the sites found in other AP lyases. The 3rd AP lyase site is located in the 12th (HhH)2 domain. The results show that Topo-V is an unusual protein: it is the only known protein with more than one (HhH)2 domain, the only known topoisomerase with dual activities and is also unique by having three AP lyase repair sites in the same polypeptide.

  16. Predicting Polymerase Ⅱ Core Promoters by Cooperating Transcription Factor Binding Sites in Eukaryotic Genes

    Institute of Scientific and Technical Information of China (English)

    Xiao-Tu MA; Min-Ping QIAN; Hai-Xu TANG

    2004-01-01

    Several discriminate functions for predicting core promoters that based on the potential cooperation between transcription factor binding sites (TFBSs) are discussed. It is demonstrated that the promoter predicting accuracy is improved when the cooperation among TFBSs is taken into consideration.The core promoter region of a newly discovered gene CKLFSF1 is predicted to locate more than 1.5 kb far away from the 5′ end of the transcript and in the last intron of its upstream gene, which is experimentally confirmed later. The core promoters of 3402 human RefSeq sequences, obtained by extending the mRNAs in human genome sequences, are predicted by our algorithm, and there are about 60% of the predicted core promoters locating within the ± 500 bp region relative to the annotated transcription start site.

  17. Cross-prediction of the groundwater chemistry at the SKB sites in Sweden. Pilot study

    Energy Technology Data Exchange (ETDEWEB)

    Skaarman, C.; Laaksoharju, M. [Intera KB (Sweden)

    1997-08-01

    The possibility to perform a large scale prediction throughout Sweden was tested. The aim of the work was: to collect data and create a groundwater database for current and future use; to see if there is any correlation between data at different sites; to perform a modelling where the groundwater composition at different regions in Sweden is predicted. The outcome of the predictions were compared with the measured data at different sites. The results show that it is possible but more work needs to be done to improve the prediction models. More measurements at depth are needed to enable the use of 3D models. It is also important to include hydrogeological parameters in the groundwater chemical prediction models that are used. 8 refs, 115 figs.

  18. MBSTAR: multiple instance learning for predicting specific functional binding sites in microRNA targets

    Science.gov (United States)

    Bandyopadhyay, Sanghamitra; Ghosh, Dip; Mitra, Ramkrishna; Zhao, Zhongming

    2015-01-01

    MicroRNA (miRNA) regulates gene expression by binding to specific sites in the 3'untranslated regions of its target genes. Machine learning based miRNA target prediction algorithms first extract a set of features from potential binding sites (PBSs) in the mRNA and then train a classifier to distinguish targets from non-targets. However, they do not consider whether the PBSs are functional or not, and consequently result in high false positive rates. This substantially affects the follow up functional validation by experiments. We present a novel machine learning based approach, MBSTAR (Multiple instance learning of Binding Sites of miRNA TARgets), for accurate prediction of true or functional miRNA binding sites. Multiple instance learning framework is adopted to handle the lack of information about the actual binding sites in the target mRNAs. Biologically validated 9531 interacting and 973 non-interacting miRNA-mRNA pairs are identified from Tarbase 6.0 and confirmed with PAR-CLIP dataset. It is found that MBSTAR achieves the highest number of binding sites overlapping with PAR-CLIP with maximum F-Score of 0.337. Compared to the other methods, MBSTAR also predicts target mRNAs with highest accuracy. The tool and genome wide predictions are available at http://www.isical.ac.in/~bioinfo_miu/MBStar30.htm.

  19. Cell-type specificity of ChIP-predicted transcription factor binding sites

    Directory of Open Access Journals (Sweden)

    Håndstad Tony

    2012-08-01

    Full Text Available Abstract Background Context-dependent transcription factor (TF binding is one reason for differences in gene expression patterns between different cellular states. Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq identifies genome-wide TF binding sites for one particular context—the cells used in the experiment. But can such ChIP-seq data predict TF binding in other cellular contexts and is it possible to distinguish context-dependent from ubiquitous TF binding? Results We compared ChIP-seq data on TF binding for multiple TFs in two different cell types and found that on average only a third of ChIP-seq peak regions are common to both cell types. Expectedly, common peaks occur more frequently in certain genomic contexts, such as CpG-rich promoters, whereas chromatin differences characterize cell-type specific TF binding. We also find, however, that genotype differences between the cell types can explain differences in binding. Moreover, ChIP-seq signal intensity and peak clustering are the strongest predictors of common peaks. Compared with strong peaks located in regions containing peaks for multiple transcription factors, weak and isolated peaks are less common between the cell types and are less associated with data that indicate regulatory activity. Conclusions Together, the results suggest that experimental noise is prevalent among weak peaks, whereas strong and clustered peaks represent high-confidence binding events that often occur in other cellular contexts. Nevertheless, 30-40% of the strongest and most clustered peaks show context-dependent regulation. We show that by combining signal intensity with additional data—ranging from context independent information such as binding site conservation and position weight matrix scores to context dependent chromatin structure—we can predict whether a ChIP-seq peak is likely to be present in other cellular contexts.

  20. Human Glycinamide Ribonucleotide Transformylase: Active Site Mutants as Mechanistic Probes†

    OpenAIRE

    Manieri, Wanda; Moore, Molly E.; Soellner, Matthew B.; Tsang, Pearl; Caperelli, Carol A.

    2007-01-01

    Human glycinamide ribonucleotide transformylase (GART) (EC2.1.2.2) is a validated target for cancer chemotherapy, but mechanistic studies of this therapeutically important enzyme are limited. Site-directed mutagenesis, initial velocity studies, pH-rate studies, and substrate binding studies have been employed to probe the role of the strictly conserved active site residues, N106, H108, D144, and the semi-conserved K170 in substrate binding and catalysis. Only two conservative substitutions, N...

  1. Spatial distribution of predicted transcription factor binding sites in Drosophila ChIP peaks.

    Science.gov (United States)

    Pettie, Kade P; Dresch, Jacqueline M; Drewell, Robert A

    2016-08-01

    In the development of the Drosophila embryo, gene expression is directed by the sequence-specific interactions of a large network of protein transcription factors (TFs) and DNA cis-regulatory binding sites. Once the identity of the typically 8-10bp binding sites for any given TF has been determined by one of several experimental procedures, the sequences can be represented in a position weight matrix (PWM) and used to predict the location of additional TF binding sites elsewhere in the genome. Often, alignments of large (>200bp) genomic fragments that have been experimentally determined to bind the TF of interest in Chromatin Immunoprecipitation (ChIP) studies are trimmed under the assumption that the majority of the binding sites are located near the center of all the aligned fragments. In this study, ChIP/chip datasets are analyzed using the corresponding PWMs for the well-studied TFs; CAUDAL, HUNCHBACK, KNIRPS and KRUPPEL, to determine the distribution of predicted binding sites. All four TFs are critical regulators of gene expression along the anterio-posterior axis in early Drosophila development. For all four TFs, the ChIP peaks contain multiple binding sites that are broadly distributed across the genomic region represented by the peak, regardless of the prediction stringency criteria used. This result suggests that ChIP peak trimming may exclude functional binding sites from subsequent analyses.

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

    Science.gov (United States)

    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.

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

    Energy Technology Data Exchange (ETDEWEB)

    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.

  4. De novo active sites for resurrected Precambrian enzymes

    Science.gov (United States)

    Risso, Valeria A.; Martinez-Rodriguez, Sergio; Candel, Adela M.; Krüger, Dennis M.; Pantoja-Uceda, David; Ortega-Muñoz, Mariano; Santoyo-Gonzalez, Francisco; Gaucher, Eric A.; Kamerlin, Shina C. L.; Bruix, Marta; Gavira, Jose A.; Sanchez-Ruiz, Jose M.

    2017-07-01

    Protein engineering studies often suggest the emergence of completely new enzyme functionalities to be highly improbable. However, enzymes likely catalysed many different reactions already in the last universal common ancestor. Mechanisms for the emergence of completely new active sites must therefore either plausibly exist or at least have existed at the primordial protein stage. Here, we use resurrected Precambrian proteins as scaffolds for protein engineering and demonstrate that a new active site can be generated through a single hydrophobic-to-ionizable amino acid replacement that generates a partially buried group with perturbed physico-chemical properties. We provide experimental and computational evidence that conformational flexibility can assist the emergence and subsequent evolution of new active sites by improving substrate and transition-state binding, through the sampling of many potentially productive conformations. Our results suggest a mechanism for the emergence of primordial enzymes and highlight the potential of ancestral reconstruction as a tool for protein engineering.

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

    CERN Document Server

    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. LRR conservation mapping to predict functional sites within protein leucine-rich repeat domains.

    Directory of Open Access Journals (Sweden)

    Laura Helft

    Full Text Available 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, a computational method that predicts functional sites of LRR domains. RCM utilizes two or more homologous sequences and a generic representation of the LRR structure to identify conserved or diversified patches of amino acids on the predicted surface of the LRR. RCM was validated using solved LRR+ligand structures from multiple taxa, identifying ligand interaction sites. RCM was then used for de novo dissection of two plant microbe-associated molecular pattern (MAMP receptors, EF-TU RECEPTOR (EFR and FLAGELLIN-SENSING 2 (FLS2. In vivo testing of Arabidopsis thaliana EFR and FLS2 receptors mutagenized at sites identified by RCM demonstrated previously unknown functional sites. The RCM predictions for EFR, FLS2 and a third plant LRR protein, PGIP, compared favorably to predictions from ODA (optimal docking area, Consurf, and PAML (positive selection analyses, but RCM also made valid functional site predictions not available from these other bioinformatic approaches. RCM analyses can be conducted with any LRR-containing proteins at www.plantpath.wisc.edu/RCM, and the approach should be modifiable for use with other types of repeat protein domains.

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

    DEFF Research Database (Denmark)

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

    2013-01-01

    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...... 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...... flexibility in the possible oxidation states of the metal atoms in solid electrocatalysts, while in porphyrins they must be +2. These observations reveal that the catalytic activity of these materials is mainly due to nearest-neighbor interactions. Based on this, we propose that this class of electrocatalysts...

  8. Cellular automaton rules conserving the number of active sites

    CERN Document Server

    Boccara, N; Boccara, Nino; Fuks, Henryk

    1997-01-01

    This paper shows how to determine all the unidimensional two-state cellular automaton rules of a given number of inputs which conserve the number of active sites. These rules have to satisfy a necessary and sufficient condition. If the active sites are viewed as cells occupied by identical particles, these cellular automaton rules represent evolution operators of systems of identical interacting particles whose total number is conserved. Some of these rules, which allow motion in both directions, mimic ensembles of one-dimensional pseudo-random walkers. The corresponding stochastic processes are, however, not Gaussian.

  9. Prediction of protein binding sites in protein structures using hidden Markov support vector machine

    Directory of Open Access Journals (Sweden)

    Lin Lei

    2009-11-01

    Full Text Available Abstract Background Predicting the binding sites between two interacting proteins provides important clues to the function of a protein. Recent research on protein binding site prediction has been mainly based on widely known machine learning techniques, such as artificial neural networks, support vector machines, conditional random field, etc. However, the prediction performance is still too low to be used in practice. It is necessary to explore new algorithms, theories and features to further improve the performance. Results In this study, we introduce a novel machine learning model hidden Markov support vector machine for protein binding site prediction. The model treats the protein binding site prediction as a sequential labelling task based on the maximum margin criterion. Common features derived from protein sequences and structures, including protein sequence profile and residue accessible surface area, are used to train hidden Markov support vector machine. When tested on six data sets, the method based on hidden Markov support vector machine shows better performance than some state-of-the-art methods, including artificial neural networks, support vector machines and conditional random field. Furthermore, its running time is several orders of magnitude shorter than that of the compared methods. Conclusion The improved prediction performance and computational efficiency of the method based on hidden Markov support vector machine can be attributed to the following three factors. Firstly, the relation between labels of neighbouring residues is useful for protein binding site prediction. Secondly, the kernel trick is very advantageous to this field. Thirdly, the complexity of the training step for hidden Markov support vector machine is linear with the number of training samples by using the cutting-plane algorithm.

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    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/.

  12. Prediction of Signal Peptide Cleavage Sites with Subsite-Coupled and Template Matching Fusion Algorithm.

    Science.gov (United States)

    Zhang, Shao-Wu; Zhang, Ting-He; Zhang, Jun-Nan; Huang, Yufei

    2014-03-01

    Fast and effective prediction of signal peptides (SP) and their cleavage sites is of great importance in computational biology. The approaches developed to predict signal peptide can be roughly divided into machine learning based, and sliding windows based. In order to further increase the prediction accuracy and coverage of organism for SP cleavage sites, we propose a novel method for predicting SP cleavage sites called Signal-CTF that utilizes machine learning and sliding windows, and is designed for N-termial secretory proteins in a large variety of organisms including human, animal, plant, virus, bacteria, fungi and archaea. Signal-CTF consists of three distinct elements: (1) a subsite-coupled and regularization function with a scaled window of fixed width that selects a set of candidates of possible secretion-cleavable segment for a query secretory protein; (2) a sum fusion system that integrates the outcomes from aligning the cleavage site template sequence with each of the aforementioned candidates in a scaled window of fixed width to determine the best candidate cleavage sites for the query secretory protein; (3) a voting system that identifies the ultimate signal peptide cleavage site among all possible results derived from using scaled windows of different width. When compared with Signal-3L and SignalP 4.0 predictors, the prediction accuracy of Signal-CTF is 4-12 %, 10-25 % higher than that of Signal-3L for human, animal and eukaryote, and SignalP 4.0 for eukaryota, Gram-positive bacteria and Gram-negative bacteria, respectively. Comparing with PRED-SIGNAL and SignalP 4.0 predictors on the 32 archaea secretory proteins of used in Bagos's paper, the prediction accuracy of Signal-CTF is 12.5 %, 25 % higher than that of PRED-SIGNAL and SignalP 4.0, respectively. The predicting results of several long signal peptides show that the Signal-CTF can better predict cleavage sites for long signal peptides than SignalP, Phobius, Philius, SPOCTOPUS, Signal

  13. Targeting Bax interaction sites reveals that only homo-oligomerization sites are essential for its activation

    Science.gov (United States)

    Peng, R; Tong, J-S; Li, H; Yue, B; Zou, F; Yu, J; Zhang, L

    2013-01-01

    Bax is a proapoptotic Bcl-2 family member that has a central role in the initiation of mitochondria-dependent apoptosis. However, the mechanism of Bax activation during apoptosis remains unsettled. It is believed that the activation of Bax is mediated by either dissociation from prosurvival Bcl-2 family members, or direct association with BH3-only members. Several interaction sites on Bax that mediate its interactions with other Bcl-2 family members, as well as its proapoptotic activity, have been identified in previous studies by other groups. To rigorously investigate the functional role of these interaction sites, we knocked in their respective mutants using HCT116 colon cancer cells, in which apoptosis induced by several stimuli is strictly Bax-dependent. Bax-mediated apoptosis was intact upon knock-in (KI) of K21E and D33A, which were shown to block the interaction of Bax with BH3-only activators. Apoptosis was partially reduced by KI of D68R, which impairs the interaction of Bax with prosurvival members, and S184V, a constitutively mitochondria-targeting mutant. In contrast, apoptosis was largely suppressed by KI of L70A/D71A, which blocks homo-oligomerization of Bax and its binding to prosurvival Bcl-2 family proteins. Collectively, our results suggest that the activation of endogenous Bax in HCT116 cells is dependent on its homo-oligomerization sites, but not those previously shown to interact with BH3-only activators or prosurvival proteins only. We therefore postulate that critical interaction sites yet to be identified, or mechanisms other than protein-protein interactions, need to be pursued to delineate the mechanism of Bax activation during apoptosis. PMID:23392123

  14. Predicting Ligand Binding Sites on Protein Surfaces by 3-Dimensional Probability Density Distributions of Interacting Atoms

    Science.gov (United States)

    Jian, Jhih-Wei; Elumalai, Pavadai; Pitti, Thejkiran; Wu, Chih Yuan; Tsai, Keng-Chang; Chang, Jeng-Yih; Peng, Hung-Pin; Yang, An-Suei

    2016-01-01

    Predicting ligand binding sites (LBSs) on protein structures, which are obtained either from experimental or computational methods, is a useful first step in functional annotation or structure-based drug design for the protein structures. In this work, the structure-based machine learning algorithm ISMBLab-LIG was developed to predict LBSs on protein surfaces with input attributes derived from the three-dimensional probability density maps of interacting atoms, which were reconstructed on the query protein surfaces and were relatively insensitive to local conformational variations of the tentative ligand binding sites. The prediction accuracy of the ISMBLab-LIG predictors is comparable to that of the best LBS predictors benchmarked on several well-established testing datasets. More importantly, the ISMBLab-LIG algorithm has substantial tolerance to the prediction uncertainties of computationally derived protein structure models. As such, the method is particularly useful for predicting LBSs not only on experimental protein structures without known LBS templates in the database but also on computationally predicted model protein structures with structural uncertainties in the tentative ligand binding sites. PMID:27513851

  15. Active site modeling in copper azurin molecular dynamics simulations

    NARCIS (Netherlands)

    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

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

    DEFF Research Database (Denmark)

    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...

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

    Science.gov (United States)

    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…

  18. Active site detection by spatial conformity and electrostatic analysis--unravelling a proteolytic function in shrimp alkaline phosphatase.

    Directory of Open Access Journals (Sweden)

    Sandeep Chakraborty

    Full Text Available Computational methods are increasingly gaining importance as an aid in identifying active sites. Mostly these methods tend to have structural information that supplement sequence conservation based analyses. Development of tools that compute electrostatic potentials has further improved our ability to better characterize the active site residues in proteins. We have described a computational methodology for detecting active sites based on structural and electrostatic conformity - CataLytic Active Site Prediction (CLASP. In our pipelined model, physical 3D signature of any particular enzymatic function as defined by its active sites is used to obtain spatially congruent matches. While previous work has revealed that catalytic residues have large pKa deviations from standard values, we show that for a given enzymatic activity, electrostatic potential difference (PD between analogous residue pairs in an active site taken from different proteins of the same family are similar. False positives in spatially congruent matches are further pruned by PD analysis where cognate pairs with large deviations are rejected. We first present the results of active site prediction by CLASP for two enzymatic activities - β-lactamases and serine proteases, two of the most extensively investigated enzymes. The results of CLASP analysis on motifs extracted from Catalytic Site Atlas (CSA are also presented in order to demonstrate its ability to accurately classify any protein, putative or otherwise, with known structure. The source code and database is made available at www.sanchak.com/clasp/. Subsequently, we probed alkaline phosphatases (AP, one of the well known promiscuous enzymes, for additional activities. Such a search has led us to predict a hitherto unknown function of shrimp alkaline phosphatase (SAP, where the protein acts as a protease. Finally, we present experimental evidence of the prediction by CLASP by showing that SAP indeed has protease activity in

  19. Active site detection by spatial conformity and electrostatic analysis--unravelling a proteolytic function in shrimp alkaline phosphatase.

    Science.gov (United States)

    Chakraborty, Sandeep; Minda, Renu; Salaye, Lipika; Bhattacharjee, Swapan K; Rao, Basuthkar J

    2011-01-01

    Computational methods are increasingly gaining importance as an aid in identifying active sites. Mostly these methods tend to have structural information that supplement sequence conservation based analyses. Development of tools that compute electrostatic potentials has further improved our ability to better characterize the active site residues in proteins. We have described a computational methodology for detecting active sites based on structural and electrostatic conformity - CataLytic Active Site Prediction (CLASP). In our pipelined model, physical 3D signature of any particular enzymatic function as defined by its active sites is used to obtain spatially congruent matches. While previous work has revealed that catalytic residues have large pKa deviations from standard values, we show that for a given enzymatic activity, electrostatic potential difference (PD) between analogous residue pairs in an active site taken from different proteins of the same family are similar. False positives in spatially congruent matches are further pruned by PD analysis where cognate pairs with large deviations are rejected. We first present the results of active site prediction by CLASP for two enzymatic activities - β-lactamases and serine proteases, two of the most extensively investigated enzymes. The results of CLASP analysis on motifs extracted from Catalytic Site Atlas (CSA) are also presented in order to demonstrate its ability to accurately classify any protein, putative or otherwise, with known structure. The source code and database is made available at www.sanchak.com/clasp/. Subsequently, we probed alkaline phosphatases (AP), one of the well known promiscuous enzymes, for additional activities. Such a search has led us to predict a hitherto unknown function of shrimp alkaline phosphatase (SAP), where the protein acts as a protease. Finally, we present experimental evidence of the prediction by CLASP by showing that SAP indeed has protease activity in vitro.

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

    DEFF Research Database (Denmark)

    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...

  1. Direct instrumental identification of catalytically active surface sites

    Science.gov (United States)

    Pfisterer, Jonas H. K.; Liang, Yunchang; Schneider, Oliver; Bandarenka, Aliaksandr S.

    2017-09-01

    The activity of heterogeneous catalysts—which are involved in some 80 per cent of processes in the chemical and energy industries—is determined by the electronic structure of specific surface sites that offer optimal binding of reaction intermediates. Directly identifying and monitoring these sites during a reaction should therefore provide insight that might aid the targeted development of heterogeneous catalysts and electrocatalysts (those that participate in electrochemical reactions) for practical applications. The invention of the scanning tunnelling microscope (STM) and the electrochemical STM promised to deliver such imaging capabilities, and both have indeed contributed greatly to our atomistic understanding of heterogeneous catalysis. But although the STM has been used to probe and initiate surface reactions, and has even enabled local measurements of reactivity in some systems, it is not generally thought to be suited to the direct identification of catalytically active surface sites under reaction conditions. Here we demonstrate, however, that common STMs can readily map the catalytic activity of surfaces with high spatial resolution: we show that by monitoring relative changes in the tunnelling current noise, active sites can be distinguished in an almost quantitative fashion according to their ability to catalyse the hydrogen-evolution reaction or the oxygen-reduction reaction. These data allow us to evaluate directly the importance and relative contribution to overall catalyst activity of different defects and sites at the boundaries between two materials. With its ability to deliver such information and its ready applicability to different systems, we anticipate that our method will aid the rational design of heterogeneous catalysts.

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

    LENUS (Irish Health Repository)

    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.

  3. Predicting protein ligand binding sites by combining evolutionary sequence conservation and 3D structure.

    Directory of Open Access Journals (Sweden)

    John A Capra

    2009-12-01

    Full Text Available Identifying a protein's functional sites is an important step towards characterizing its molecular function. Numerous structure- and sequence-based methods have been developed for this problem. Here we introduce ConCavity, a small molecule binding site prediction algorithm that integrates evolutionary sequence conservation estimates with structure-based methods for identifying protein surface cavities. In large-scale testing on a diverse set of single- and multi-chain protein structures, we show that ConCavity substantially outperforms existing methods for identifying both 3D ligand binding pockets and individual ligand binding residues. As part of our testing, we perform one of the first direct comparisons of conservation-based and structure-based methods. We find that the two approaches provide largely complementary information, which can be combined to improve upon either approach alone. We also demonstrate that ConCavity has state-of-the-art performance in predicting catalytic sites and drug binding pockets. Overall, the algorithms and analysis presented here significantly improve our ability to identify ligand binding sites and further advance our understanding of the relationship between evolutionary sequence conservation and structural and functional attributes of proteins. Data, source code, and prediction visualizations are available on the ConCavity web site (http://compbio.cs.princeton.edu/concavity/.

  4. Predicting protein ligand binding sites by combining evolutionary sequence conservation and 3D structure.

    Science.gov (United States)

    Capra, John A; Laskowski, Roman A; Thornton, Janet M; Singh, Mona; Funkhouser, Thomas A

    2009-12-01

    Identifying a protein's functional sites is an important step towards characterizing its molecular function. Numerous structure- and sequence-based methods have been developed for this problem. Here we introduce ConCavity, a small molecule binding site prediction algorithm that integrates evolutionary sequence conservation estimates with structure-based methods for identifying protein surface cavities. In large-scale testing on a diverse set of single- and multi-chain protein structures, we show that ConCavity substantially outperforms existing methods for identifying both 3D ligand binding pockets and individual ligand binding residues. As part of our testing, we perform one of the first direct comparisons of conservation-based and structure-based methods. We find that the two approaches provide largely complementary information, which can be combined to improve upon either approach alone. We also demonstrate that ConCavity has state-of-the-art performance in predicting catalytic sites and drug binding pockets. Overall, the algorithms and analysis presented here significantly improve our ability to identify ligand binding sites and further advance our understanding of the relationship between evolutionary sequence conservation and structural and functional attributes of proteins. Data, source code, and prediction visualizations are available on the ConCavity web site (http://compbio.cs.princeton.edu/concavity/).

  5. Modulation of RNase E activity by alternative RNA binding sites.

    Directory of Open Access Journals (Sweden)

    Daeyoung Kim

    Full Text Available Endoribonuclease E (RNase E affects the composition and balance of the RNA population in Escherichia coli via degradation and processing of RNAs. In this study, we investigated the regulatory effects of an RNA binding site between amino acid residues 25 and 36 (24LYDLDIESPGHEQK37 of RNase E. Tandem mass spectrometry analysis of the N-terminal catalytic domain of RNase E (N-Rne that was UV crosslinked with a 5'-32P-end-labeled, 13-nt oligoribonucleotide (p-BR13 containing the RNase E cleavage site of RNA I revealed that two amino acid residues, Y25 and Q36, were bound to the cytosine and adenine of BR13, respectively. Based on these results, the Y25A N-Rne mutant was constructed, and was found to be hypoactive in comparison to wild-type and hyperactive Q36R mutant proteins. Mass spectrometry analysis showed that Y25A and Q36R mutations abolished the RNA binding to the uncompetitive inhibition site of RNase E. The Y25A mutation increased the RNA binding to the multimer formation interface between amino acid residues 427 and 433 (427LIEEEALK433, whereas the Q36R mutation enhanced the RNA binding to the catalytic site of the enzyme (65HGFLPL*K71. Electrophoretic mobility shift assays showed that the stable RNA-protein complex formation was positively correlated with the extent of RNA binding to the catalytic site and ribonucleolytic activity of the N-Rne proteins. These mutations exerted similar effects on the ribonucleolytic activity of the full-length RNase E in vivo. Our findings indicate that RNase E has two alternative RNA binding sites for modulating RNA binding to the catalytic site and the formation of a functional catalytic unit.

  6. Role of active site rigidity in activity: MD simulation and fluorescence study on a lipase mutant.

    Directory of Open Access Journals (Sweden)

    Md Zahid Kamal

    Full Text Available Relationship between stability and activity of enzymes is maintained by underlying conformational flexibility. In thermophilic enzymes, a decrease in flexibility causes low enzyme activity while in less stable proteins such as mesophiles and psychrophiles, an increase in flexibility is associated with enhanced enzyme activity. Recently, we identified a mutant of a lipase whose stability and activity were enhanced simultaneously. In this work, we probed the conformational dynamics of the mutant and the wild type lipase, particularly flexibility of their active site using molecular dynamic simulations and time-resolved fluorescence techniques. In contrast to the earlier observations, our data show that active site of the mutant is more rigid than wild type enzyme. Further investigation suggests that this lipase needs minimal reorganization/flexibility of active site residues during its catalytic cycle. Molecular dynamic simulations suggest that catalytically competent active site geometry of the mutant is relatively more preserved than wild type lipase, which might have led to its higher enzyme activity. Our study implies that widely accepted positive correlation between conformation flexibility and enzyme activity need not be stringent and draws attention to the possibility that high enzyme activity can still be accomplished in a rigid active site and stable protein structures. This finding has a significant implication towards better understanding of involvement of dynamic motions in enzyme catalysis and enzyme engineering through mutations in active site.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    Roche, Daniel Barry; Brackenridge, Danielle Allison; McGuffin, Liam James

    2015-12-15

    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.

  9. Activation of phenylalanine hydroxylase by phenylalanine does not require binding in the active site.

    Science.gov (United States)

    Roberts, Kenneth M; Khan, Crystal A; Hinck, Cynthia S; Fitzpatrick, Paul F

    2014-12-16

    Phenylalanine hydroxylase (PheH), a liver enzyme that catalyzes the hydroxylation of excess phenylalanine in the diet to tyrosine, is activated by phenylalanine. The lack of activity at low levels of phenylalanine has been attributed to the N-terminus of the protein's regulatory domain acting as an inhibitory peptide by blocking substrate access to the active site. The location of the site at which phenylalanine binds to activate the enzyme is unknown, and both the active site in the catalytic domain and a separate site in the N-terminal regulatory domain have been proposed. Binding of catecholamines to the active-site iron was used to probe the accessibility of the active site. Removal of the regulatory domain increases the rate constants for association of several catecholamines with the wild-type enzyme by ∼2-fold. Binding of phenylalanine in the active site is effectively abolished by mutating the active-site residue Arg270 to lysine. The k(cat)/K(phe) value is down 10⁴ for the mutant enzyme, and the K(m) value for phenylalanine for the mutant enzyme is >0.5 M. Incubation of the R270K enzyme with phenylalanine also results in a 2-fold increase in the rate constants for catecholamine binding. The change in the tryptophan fluorescence emission spectrum seen in the wild-type enzyme upon activation by phenylalanine is also seen with the R270K mutant enzyme in the presence of phenylalanine. Both results establish that activation of PheH by phenylalanine does not require binding of the amino acid in the active site. This is consistent with a separate allosteric site, likely in the regulatory domain.

  10. Changes in active site histidine hydrogen bonding trigger cryptochrome activation.

    Science.gov (United States)

    Ganguly, Abir; Manahan, Craig C; Top, Deniz; Yee, Estella F; Lin, Changfan; Young, Michael W; Thiel, Walter; Crane, Brian R

    2016-09-06

    Cryptochrome (CRY) is the principal light sensor of the insect circadian clock. Photoreduction of the Drosophila CRY (dCRY) flavin cofactor to the anionic semiquinone (ASQ) restructures a C-terminal tail helix (CTT) that otherwise inhibits interactions with targets that include the clock protein Timeless (TIM). All-atom molecular dynamics (MD) simulations indicate that flavin reduction destabilizes the CTT, which undergoes large-scale conformational changes (the CTT release) on short (25 ns) timescales. The CTT release correlates with the conformation and protonation state of conserved His378, which resides between the CTT and the flavin cofactor. Poisson-Boltzmann calculations indicate that flavin reduction substantially increases the His378 pKa Consistent with coupling between ASQ formation and His378 protonation, dCRY displays reduced photoreduction rates with increasing pH; however, His378Asn/Arg variants show no such pH dependence. Replica-exchange MD simulations also support CTT release mediated by changes in His378 hydrogen bonding and verify other responsive regions of the protein previously identified by proteolytic sensitivity assays. His378 dCRY variants show varying abilities to light-activate TIM and undergo self-degradation in cellular assays. Surprisingly, His378Arg/Lys variants do not degrade in light despite maintaining reactivity toward TIM, thereby implicating different conformational responses in these two functions. Thus, the dCRY photosensory mechanism involves flavin photoreduction coupled to protonation of His378, whose perturbed hydrogen-bonding pattern alters the CTT and surrounding regions.

  11. Site of metabolism prediction based on ab initio derived atom representations.

    Science.gov (United States)

    Finkelmann, Arndt R; Göller, Andreas H; Schneider, Gisbert

    2017-03-21

    Machine learning models for site of metabolism (SoM) prediction offer the ability to identify metabolic soft spots in low molecular weight drug molecules at low computational cost and enable data-based reactivity prediction. SoM prediction is an atom classification problem. Successful construction of machine learning models requires atom representations that capture the reactivity-determining features of a potential reaction site. We have developed a descriptor scheme that characterizes an atom's steric and electronic environment and its relative location in the molecular structure. The partial charge distributions were obtained from fast quantum mechanical calculations. We successfully trained machine learning classifiers on curated cytochrome p450 metabolism data. The models based on the new atom descriptors showed sustained accuracy for retrospective analyses of metabolism optimization campaigns and lead optimization projects from Bayer Pharmaceuticals. The results obtained demonstrate the practicality of quantum-chemistry-supported machine learning models for hit-to-lead optimization.

  12. Prediction of Protein-Protein Interaction Sites Based on Naive Bayes Classifier

    Directory of Open Access Journals (Sweden)

    Haijiang Geng

    2015-01-01

    Full Text Available Protein functions through interactions with other proteins and biomolecules and these interactions occur on the so-called interface residues of the protein sequences. Identifying interface residues makes us better understand the biological mechanism of protein interaction. Meanwhile, information about the interface residues contributes to the understanding of metabolic, signal transduction networks and indicates directions in drug designing. In recent years, researchers have focused on developing new computational methods for predicting protein interface residues. Here we creatively used a 181-dimension protein sequence feature vector as input to the Naive Bayes Classifier- (NBC- based method to predict interaction sites in protein-protein complexes interaction. The prediction of interaction sites in protein interactions is regarded as an amino acid residue binary classification problem by applying NBC with protein sequence features. Independent test results suggested that Naive Bayes Classifier-based method with the protein sequence features as input vectors performed well.

  13. COMPARATIVE MODELLING AND LIGAND BINDING SITE PREDICTION OF A FAMILY 43 GLYCOSIDE HYDROLASE FROM Clostridium thermocellum

    Directory of Open Access Journals (Sweden)

    Shadab Ahmed

    2012-06-01

    Full Text Available The phylogenetic analysis of Clostridium thermocellum family 43 glycoside hydrolase (CtGH43 showed close evolutionary relation with carbohydrate binding family 6 proteins from C. cellulolyticum, C. papyrosolvens, C. cellulyticum, and A. cellulyticum. Comparative modeling of CtGH43 was performed based on crystal structures with PDB IDs 3C7F, 1YIF, 1YRZ, 2EXH and 1WL7. The structure having lowest MODELLER objective function was selected. The three-dimensional structure revealed typical 5-fold beta–propeller architecture. Energy minimization and validation of predicted model with VERIFY 3D indicated acceptability of the proposed atomic structure. The Ramachandran plot analysis by RAMPAGE confirmed that family 43 glycoside hydrolase (CtGH43 contains little or negligible segments of helices. It also showed that out of 301 residues, 267 (89.3% were in most favoured region, 23 (7.7% were in allowed region and 9 (3.0% were in outlier region. IUPred analysis of CtGH43 showed no disordered region. Active site analysis showed presence of two Asp and one Glu, assumed to form a catalytic triad. This study gives us information about three-dimensional structure and reaffirms the fact that it has the similar core 5-fold beta–propeller architecture and so probably has the same inverting mechanism of action with the formation of above mentioned catalytic triad for catalysis of polysaccharides.

  14. Studies on the biotin-binding site of avidin. Tryptophan residues involved in the active site.

    Science.gov (United States)

    Gitlin, G; Bayer, E A; Wilchek, M

    1988-01-01

    Egg-white avidin was modified with the tryptophan-specific reagent 2-hydroxy-5-nitrobenzyl bromide. The complete loss of biotin-binding activity was achieved upon modification of an average of one tryptophan residue per avidin subunit. The identity of the modified residues was determined by isolating the relevant tryptic and chymotryptic peptides from CNBr-cleaved avidin fragments. The results demonstrate that Trp-70 and Trp-110 are modified in approximately equivalent proportions. It is believed that these residues are located in the active site of avidin and take part in the binding of biotin. PMID:3355517

  15. Studies on the biotin-binding site of avidin. Tryptophan residues involved in the active site.

    Science.gov (United States)

    Gitlin, G; Bayer, E A; Wilchek, M

    1988-02-15

    Egg-white avidin was modified with the tryptophan-specific reagent 2-hydroxy-5-nitrobenzyl bromide. The complete loss of biotin-binding activity was achieved upon modification of an average of one tryptophan residue per avidin subunit. The identity of the modified residues was determined by isolating the relevant tryptic and chymotryptic peptides from CNBr-cleaved avidin fragments. The results demonstrate that Trp-70 and Trp-110 are modified in approximately equivalent proportions. It is believed that these residues are located in the active site of avidin and take part in the binding of biotin.

  16. A Random Forest Model for Predicting Allosteric and Functional Sites on Proteins.

    Science.gov (United States)

    Chen, Ava S-Y; Westwood, Nicholas J; Brear, Paul; Rogers, Graeme W; Mavridis, Lazaros; Mitchell, John B O

    2016-04-01

    We created a computational method to identify allosteric sites using a machine learning method trained and tested on protein structures containing bound ligand molecules. The Random Forest machine learning approach was adopted to build our three-way predictive model. Based on descriptors collated for each ligand and binding site, the classification model allows us to assign protein cavities as allosteric, regular or orthosteric, and hence to identify allosteric sites. 43 structural descriptors per complex were derived and were used to characterize individual protein-ligand binding sites belonging to the three classes, allosteric, regular and orthosteric. We carried out a separate validation on a further unseen set of protein structures containing the ligand 2-(N-cyclohexylamino) ethane sulfonic acid (CHES).

  17. Ten problems and solutions when predicting individual outcome from lesion site after stroke.

    Science.gov (United States)

    Price, Cathy J; Hope, Thomas M; Seghier, Mohamed L

    2017-01-15

    In this paper, we consider solutions to ten of the challenges faced when trying to predict an individual's functional outcome after stroke on the basis of lesion site. A primary goal is to find lesion-outcome associations that are consistently observed in large populations of stroke patients because consistent associations maximise confidence in future individualised predictions. To understand and control multiple sources of inter-patient variability, we need to systematically investigate each contributing factor and how each factor depends on other factors. This requires very large cohorts of patients, who differ from one another in typical and measurable ways, including lesion site, lesion size, functional outcome and time post stroke (weeks to decades). These multivariate investigations are complex, particularly when the contributions of different variables interact with one another. Machine learning algorithms can help to identify the most influential variables and indicate dependencies between different factors. Multivariate lesion analyses are needed to understand how the effect of damage to one brain region depends on damage or preservation in other brain regions. Such data-led investigations can reveal predictive relationships between lesion site and outcome. However, to understand and improve the predictions we need explanatory models of the neural networks and degenerate pathways that support functions of interest. This will entail integrating the results of lesion analyses with those from functional imaging (fMRI, MEG), transcranial magnetic stimulation (TMS) and diffusor tensor imaging (DTI) studies of healthy participants and patients. Copyright © 2016 Elsevier Inc. All rights reserved.

  18. STarMir Tools for Prediction of microRNA binding sites

    Science.gov (United States)

    Kanoria, Shaveta; Rennie, William; Liu, Chaochun; Carmack, C. Steven; Lu, Jun; Ding, Ye

    2017-01-01

    MicroRNAs (miRNAs) are a class of endogenous short non-coding RNAs that regulate gene expression by targeting messenger RNAs (mRNAs), which results in translational repression and/or mRNA degradation. As regulatory molecules, miRNAs are involved in many mammalian biological processes and also in the manifestation of certain human diseases. As miRNAs play central role in the regulation of gene expression, understanding miRNA-binding patterns is essential to gain an insight of miRNA mediated gene regulation and also holds promise for therapeutic applications. Computational prediction of miRNA binding sites on target mRNAs facilitates experimental investigation of miRNA functions. This chapter provides protocols for using the STarMir web server for improved predictions of miRNA binding sites on a target mRNA. As an application module of the Sfold RNA package, the current version of STarMir is an implementation of logistic prediction models developed with high throughput miRNA binding data from crosslinking immuno-precipitation (CLIP) studies. The models incorporated comprehensive thermodynamic, structural and sequence features, and were found to make improved predictions of both seed and seedless sites, in comparison to the established algorithms [1]. Their broad applicability was indicated by their good performance in cross-species validation. STarMir is freely available at http://sfold.wadsworth.org/starmir.html PMID:27665594

  19. Spatial characterization and prediction of Neanderthal sites based on environmental information and stochastic modelling

    Science.gov (United States)

    Maerker, Michael; Bolus, Michael

    2014-05-01

    We present a unique spatial dataset of Neanderthal sites in Europe that was used to train a set of stochastic models to reveal the correlations between the site locations and environmental indices. In order to assess the relations between the Neanderthal sites and environmental variables as described above we applied a boosted regression tree approach (TREENET) a statistical mechanics approach (MAXENT) and support vector machines. The stochastic models employ a learning algorithm to identify a model that best fits the relationship between the attribute set (predictor variables (environmental variables) and the classified response variable which is in this case the types of Neanderthal sites. A quantitative evaluation of model performance was done by determining the suitability of the model for the geo-archaeological applications and by helping to identify those aspects of the methodology that need improvements. The models' predictive performances were assessed by constructing the Receiver Operating Characteristics (ROC) curves for each Neanderthal class, both for training and test data. In a ROC curve the Sensitivity is plotted over the False Positive Rate (1-Specificity) for all possible cut-off points. The quality of a ROC curve is quantified by the measure of the parameter area under the ROC curve. The dependent variable or target variable in this study are the locations of Neanderthal sites described by latitude and longitude. The information on the site location was collected from literature and own research. All sites were checked for site accuracy using high resolution maps and google earth. The study illustrates that the models show a distinct ranking in model performance with TREENET outperforming the other approaches. Moreover Pre-Neanderthals, Early Neanderthals and Classic Neanderthals show a specific spatial distribution. However, all models show a wide correspondence in the selection of the most important predictor variables generally showing less

  20. A new global database to improve predictions of permeability distribution in crystalline rocks at site scale

    Science.gov (United States)

    Achtziger-Zupančič, P.; Loew, S.; Mariéthoz, G.

    2017-05-01

    A comprehensive worldwide permeability data set has been compiled consisting of 29,000 in situ permeabilities from 221 publications and reports and delineating the permeability distribution in crystalline rocks into depths of 2000 meters below ground surface (mbgs). We analyze the influence of technical factors (measurement method, scale effects, preferential sampling, and hydraulic anisotropy) and geological factors (lithology, current stress regime, current seismotectonic activity, and long-term tectonogeological history) on the permeability distribution with depth, by using regression analysis and k-means clustering. The influence of preferential sampling and hydraulic anisotropy are negligible. A scale dependency is observed based on calculated rock test volumes equaling 0.6 orders of magnitude of permeability change per order of magnitude of rock volume tested. Based on the entire data set, permeability decreases as log(k) = -1.5 × log(z) - 16.3 with permeability k (m2) and positively increasing depth z (km), and depth is the main factor driving the permeability distribution. The permeability variance is about 2 orders of magnitude at all depths, presumably representing permeability variations around brittle fault zones. Permeability and specific yield/storage exhibit similar depth trends. While in the upper 200 mbgs fracture flow varies between confined and unconfined, we observe confined fracture and matrix flow below about 600 mbgs depth. The most important geological factors are current seismotectonic activity (determined by peak ground acceleration) and long-term tectonogeological history (determined by geological province). The impact of lithology is less important. Based on the regression coefficients derived for all the geological key factors, permeability ranges of crystalline rocks at site scale can be predicted. First tests with independent data sets are promising.

  1. Ground Motion Prediction for the Vicinity by Using the Microtremor Site-effect Correction

    Science.gov (United States)

    Lin, C. M.; Wen, K. L.; Kuo, C. H.

    2015-12-01

    This study develops a method analyzing the seismograms of a strong-motion station and the microtremor site effects (H/V ratios) around it to predict the ground motion of its vicinity. The Hsinchu Science Park (HSP) in Taiwan was chosen as our study site. The horizontal S-wave seismograms of the TCU017 strong-motion station, which locates at the center of the HSP, were convoluted by the difference of the microtremor H/V ratio between various sites to synthesize the seismograms of several strong-motion stations around the HSP. The comparisons between synthetic and observed seismograms show that this method of ground motion prediction for the vicinity is feasible for far-field earthquakes. However, the seismic source and attenuation effects make this method ineffectual for near-field earthquakes. Because the microtremor H/V ratios at about 200 sites, which are densely distributed in the HSP, were conducted, the seismic ground motion distributions of some historical earthquakes were synthesized by this study. The synthetic ground motion distributions ignore the seismic source and attenuation effects but still show notable variations in the HSP because of the seismic site effects.

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

    Science.gov (United States)

    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.

  3. Protein function annotation with Structurally Aligned Local Sites of Activity (SALSAs

    Directory of Open Access Journals (Sweden)

    Wang Zhouxi

    2013-02-01

    Full Text Available Abstract Background The prediction of biochemical function from the 3D structure of a protein has proved to be much more difficult than was originally foreseen. A reliable method to test the likelihood of putative annotations and to predict function from structure would add tremendous value to structural genomics data. We report on a new method, Structurally Aligned Local Sites of Activity (SALSA, for the prediction of biochemical function based on a local structural match at the predicted catalytic or binding site. Results Implementation of the SALSA method is described. For the structural genomics protein PY01515 (PDB ID 2aqw from Plasmodium yoelii, it is shown that the putative annotation, Orotidine 5'-monophosphate decarboxylase (OMPDC, is most likely correct. SALSA analysis of YP_001304206.1 (PDB ID 3h3l, a putative sugar hydrolase from Parabacteroides distasonis, shows that its active site does not bear close resemblance to any previously characterized member of its superfamily, the Concanavalin A-like lectins/glucanases. It is noted that three residues in the active site of the thermophilic beta-1,4-xylanase from Nonomuraea flexuosa (PDB ID 1m4w, Y78, E87, and E176, overlap with POOL-predicted residues of similar type, Y168, D153, and E232, in YP_001304206.1. The substrate recognition regions of the two proteins are rather different, suggesting that YP_001304206.1 is a new functional type within the superfamily. A structural genomics protein from Mycobacterium avium (PDB ID 3q1t has been reported to be an enoyl-CoA hydratase (ECH, but SALSA analysis shows a poor match between the predicted residues for the SG protein and those of known ECHs. A better local structural match is obtained with Anabaena beta-diketone hydrolase (ABDH, a known β-diketone hydrolase from Cyanobacterium anabaena (PDB ID 2j5s. This suggests that the reported ECH function of the SG protein is incorrect and that it is more likely a β-diketone hydrolase. Conclusions

  4. Active sites in char gasification: Final technical report

    Energy Technology Data Exchange (ETDEWEB)

    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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Nekrasov, Vyacheslav M.; Yurkin, Maxim A.; Chernyshev, Andrei V., E-mail: chern@ns.kinetics.nsc.ru [Institute of Chemical Kinetics and Combustion, Institutskaya 3, 630090 Novosibirsk (Russian Federation); Physics Department, Novosibirsk State University, Pirogova 2, 630090 Novosibirsk (Russian Federation); Polshchitsin, Alexey A. [Institute of Chemical Kinetics and Combustion, Institutskaya 3, 630090 Novosibirsk (Russian Federation); JSC “VECTOR-BEST”, PO BOX 492, Novosibirsk 630117 (Russian Federation); Yakovleva, Galina E. [JSC “VECTOR-BEST”, PO BOX 492, Novosibirsk 630117 (Russian Federation); Maltsev, Valeri P. [Institute of Chemical Kinetics and Combustion, Institutskaya 3, 630090 Novosibirsk (Russian Federation); Physics Department, Novosibirsk State University, Pirogova 2, 630090 Novosibirsk (Russian Federation); Department of Preventive Medicine, Novosibirsk State Medical University, Krasny Prospect 52, 630091 Novosibirsk (Russian Federation)

    2014-08-14

    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.

  6. [Mechanism of arginine deiminase activity by site-directed mutagenesis].

    Science.gov (United States)

    Li, Lifeng; Ni, Ye; Sun, Zhihao

    2012-04-01

    Arginine deiminase (ADI) has been studied as a potential anti-cancer agent for inhibiting arginine-auxotrophic tumors (such as melanomas and hepatocellular carcinomas) in phase III clinical trials. In this work, we studied the molecular mechanism of arginine deiminase activity by site-directed mutagenesis. Three mutation sites, A128, H404 and 1410, were introduced into wild-type ADI gene by QuikChange site-directed mutagenesis method, and four ADI mutants M1 (A128T), M2 (H404R), M3 (I410L), and M4 (A128T, H404R) were obtained. The ADI mutants were individually expressed in Escherichia coli BL21 (DE3), and the enzymatic properties of the purified mutant proteins were determined. The results show that both A128T and H404R had enhanced optimum pH, higher activity and stability of ADI under physiological condition (pH 7.4), as well as reduced K(m) value. This study provides an insight into the molecular mechanism of the ADI activity, and also the experimental evidence for the rational protein evolution in the future.

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

    Energy Technology Data Exchange (ETDEWEB)

    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.

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

    Energy Technology Data Exchange (ETDEWEB)

    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.

  9. Development of a protein-ligand-binding site prediction method based on interaction energy and sequence conservation.

    Science.gov (United States)

    Tsujikawa, Hiroto; Sato, Kenta; Wei, Cao; Saad, Gul; Sumikoshi, Kazuya; Nakamura, Shugo; Terada, Tohru; Shimizu, Kentaro

    2016-09-01

    We present a new method for predicting protein-ligand-binding sites based on protein three-dimensional structure and amino acid conservation. This method involves calculation of the van der Waals interaction energy between a protein and many probes placed on the protein surface and subsequent clustering of the probes with low interaction energies to identify the most energetically favorable locus. In addition, it uses amino acid conservation among homologous proteins. Ligand-binding sites were predicted by combining the interaction energy and the amino acid conservation score. The performance of our prediction method was evaluated using a non-redundant dataset of 348 ligand-bound and ligand-unbound protein structure pairs, constructed by filtering entries in a ligand-binding site structure database, LigASite. Ligand-bound structure prediction (bound prediction) indicated that 74.0 % of predicted ligand-binding sites overlapped with real ligand-binding sites by over 25 % of their volume. Ligand-unbound structure prediction (unbound prediction) indicated that 73.9 % of predicted ligand-binding residues overlapped with real ligand-binding residues. The amino acid conservation score improved the average prediction accuracy by 17.0 and 17.6 points for the bound and unbound predictions, respectively. These results demonstrate the effectiveness of the combined use of the interaction energy and amino acid conservation in the ligand-binding site prediction.

  10. The Built Environment Predicts Observed Physical Activity

    Directory of Open Access Journals (Sweden)

    Cheryl eKelly

    2014-05-01

    Full Text Available 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 stratifıed geographic sampling design to ensure representation of neighborhoods with different land use and socioeconomic characteristics. Characteristics of the built environment on street segments were audited using two methods: in-person field audits and audits based on interpretation of Google Street View imagery with each method blinded to results from the other. Segments were dichotomized as having a particular characteristic (e.g., sidewalk present or not based on the two auditing methods separately. Counts of individuals engaged in different forms of physical activity on each segment were assessed using direct observation. Non-parametric statistics were used to compare counts of physically active individuals on each segment with built environment characteristic. Results. Counts of individuals engaged in physical activity were significantly higher on segments with mixed land use or all non-residential land use, and on segments with pedestrian infrastructure (e.g., crosswalks, sidewalks and public transit. Conclusions. Several micro-level built environment characteristics are associated with physical activity. These data provide support for theories that suggest changing the built environment and related policies may encourage more physical activity.

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

    Directory of Open Access Journals (Sweden)

    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.

  12. A python analytical pipeline to identify prohormone precursors and predict prohormone cleavage sites.

    Science.gov (United States)

    Southey, Bruce R; Sweedler, Jonathan V; Rodriguez-Zas, Sandra L

    2008-01-01

    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.

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

    DEFF Research Database (Denmark)

    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...

  14. Seismic activity parameters of the Finnish potential repository sites

    Energy Technology Data Exchange (ETDEWEB)

    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.)

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

    DEFF Research Database (Denmark)

    Peters, Günther H.j.; Svendsen, A.; Langberg, H.;

    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......We have investigated the binding properties of and dynamics in Humicola lanuginosa lipase (HII) and the inactive mutant S146A (active Ser146 substituted with Ala) using fluorescence spectroscopy and molecular dynamics simulations, respectively. Hll and S146A show significantly different binding......, whereas only small changes are observed for I-Ill suggesting that the active site Lid in the latter opens more easily and hence more lipase molecules are bound to the liposomes. These observations are in agreement with molecular dynamics simulations and subsequent essential dynamics analyses. The results...

  16. Identification of off-target cleavage sites of zinc finger nucleases and TAL effector nucleases using predictive models.

    Science.gov (United States)

    Fine, Eli J; Cradick, Thomas J; Bao, Gang

    2014-01-01

    Using engineered nucleases, such as Zinc Finger Nucleases (ZFNs) or Transcription Activator-Like Effector Nucleases (TALENs), to make targeted genomic modifications has become a common technique to create new model organisms and custom cell lines, and has shown great promise for disease treatment. However, these nucleases have the potential for off-target cleavage that could confound interpretation of experimental results and be detrimental for therapeutic use. Here, we describe a method to test for nuclease cleavage at potential off-target sites predicted by bioinformatics models.

  17. Prediction limits of mobile phone activity modelling

    Science.gov (United States)

    Kondor, Dániel; Grauwin, Sebastian; Kallus, Zsófia; Gódor, István; Sobolevsky, Stanislav; Ratti, Carlo

    2017-02-01

    Thanks to their widespread usage, mobile devices have become one of the main sensors of human behaviour and digital traces left behind can be used as a proxy to study urban environments. Exploring the nature of the spatio-temporal patterns of mobile phone activity could thus be a crucial step towards understanding the full spectrum of human activities. Using 10 months of mobile phone records from Greater London resolved in both space and time, we investigate the regularity of human telecommunication activity on urban scales. We evaluate several options for decomposing activity timelines into typical and residual patterns, accounting for the strong periodic and seasonal components. We carry out our analysis on various spatial scales, showing that regularity increases as we look at aggregated activity in larger spatial units with more activity in them. We examine the statistical properties of the residuals and show that it can be explained by noise and specific outliers. Also, we look at sources of deviations from the general trends, which we find to be explainable based on knowledge of the city structure and places of attractions. We show examples how some of the outliers can be related to external factors such as specific social events.

  18. SABER: a computational method for identifying active sites for new reactions.

    Science.gov (United States)

    Nosrati, Geoffrey R; Houk, K N

    2012-05-01

    A software suite, SABER (Selection of Active/Binding sites for Enzyme Redesign), has been developed for the analysis of atomic geometries in protein structures, using a geometric hashing algorithm (Barker and Thornton, Bioinformatics 2003;19:1644-1649). SABER is used to explore the Protein Data Bank (PDB) to locate proteins with a specific 3D arrangement of catalytic groups to identify active sites that might be redesigned to catalyze new reactions. As a proof-of-principle test, SABER was used to identify enzymes that have the same catalytic group arrangement present in o-succinyl benzoate synthase (OSBS). Among the highest-scoring scaffolds identified by the SABER search for enzymes with the same catalytic group arrangement as OSBS were L-Ala D/L-Glu epimerase (AEE) and muconate lactonizing enzyme II (MLE), both of which have been redesigned to become effective OSBS catalysts, demonstrated by experiments. Next, we used SABER to search for naturally existing active sites in the PDB with catalytic groups similar to those present in the designed Kemp elimination enzyme KE07. From over 2000 geometric matches to the KE07 active site, SABER identified 23 matches that corresponded to residues from known active sites. The best of these matches, with a 0.28 Å catalytic atom RMSD to KE07, was then redesigned to be compatible with the Kemp elimination using RosettaDesign. We also used SABER to search for potential Kemp eliminases using a theozyme predicted to provide a greater rate acceleration than the active site of KE07, and used Rosetta to create a design based on the proteins identified.

  19. Predicting interaction sites from the energetics of isolated proteins: a new approach to epitope mapping.

    Science.gov (United States)

    Scarabelli, Guido; Morra, Giulia; Colombo, Giorgio

    2010-05-19

    An increasing number of functional studies of proteins have shown that sequence and structural similarities alone may not be sufficient for reliable prediction of their interaction properties. This is particularly true for proteins recognizing specific antibodies, where the prediction of antibody-binding sites, called epitopes, has proven challenging. The antibody-binding properties of an antigen depend on its structure and related dynamics. Aiming to predict the antibody-binding regions of a protein, we investigate a new approach based on the integrated analysis of the dynamical and energetic properties of antigens, to identify nonoptimized, low-intensity energetic interaction networks in the protein structure isolated in solution. The method is based on the idea that recognition sites may correspond to localized regions with low-intensity energetic couplings with the rest of the protein, which allows them to undergo conformational changes, to be recognized by a binding partner, and to tolerate mutations with minimal energetic expense. Upon analyzing the results on isolated proteins and benchmarking against antibody complexes, it is found that the method successfully identifies binding sites located on the protein surface that are accessible to putative binding partners. The combination of dynamics and energetics can thus discriminate between epitopes and other substructures based only on physical properties. We discuss implications for vaccine design.

  20. Predicting carbon dioxide and energy fluxes across global FLUXNET sites with regression algorithms

    Science.gov (United States)

    Tramontana, Gianluca; Jung, Martin; Schwalm, Christopher R.; Ichii, Kazuhito; Camps-Valls, Gustau; Ráduly, Botond; Reichstein, Markus; Altaf Arain, M.; Cescatti, Alessandro; Kiely, Gerard; Merbold, Lutz; Serrano-Ortiz, Penelope; Sickert, Sven; Wolf, Sebastian; Papale, Dario

    2016-07-01

    Spatio-temporal fields of land-atmosphere fluxes derived from data-driven models can complement simulations by process-based land surface models. While a number of strategies for empirical models with eddy-covariance flux data have been applied, a systematic intercomparison of these methods has been missing so far. In this study, we performed a cross-validation experiment for predicting carbon dioxide, latent heat, sensible heat and net radiation fluxes across different ecosystem types with 11 machine learning (ML) methods from four different classes (kernel methods, neural networks, tree methods, and regression splines). We applied two complementary setups: (1) 8-day average fluxes based on remotely sensed data and (2) daily mean fluxes based on meteorological data and a mean seasonal cycle of remotely sensed variables. The patterns of predictions from different ML and experimental setups were highly consistent. There were systematic differences in performance among the fluxes, with the following ascending order: net ecosystem exchange (R2 0.6), gross primary production (R2> 0.7), latent heat (R2 > 0.7), sensible heat (R2 > 0.7), and net radiation (R2 > 0.8). The ML methods predicted the across-site variability and the mean seasonal cycle of the observed fluxes very well (R2 > 0.7), while the 8-day deviations from the mean seasonal cycle were not well predicted (R2 Fluxes were better predicted at forested and temperate climate sites than at sites in extreme climates or less represented by training data (e.g., the tropics). The evaluated large ensemble of ML-based models will be the basis of new global flux products.

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

    Science.gov (United States)

    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.

  2. SPEER-SERVER: a web server for prediction of protein specificity determining sites

    Science.gov (United States)

    Chakraborty, Abhijit; Mandloi, Sapan; Lanczycki, Christopher J.; Panchenko, Anna R.; Chakrabarti, Saikat

    2012-01-01

    Sites that show specific conservation patterns within subsets of proteins in a protein family are likely to be involved in the development of functional specificity. These sites, generally termed specificity determining sites (SDS), might play a crucial role in binding to a specific substrate or proteins. Identification of SDS through experimental techniques is a slow, difficult and tedious job. Hence, it is very important to develop efficient computational methods that can more expediently identify SDS. Herein, we present Specificity prediction using amino acids’ Properties, Entropy and Evolution Rate (SPEER)-SERVER, a web server that predicts SDS by analyzing quantitative measures of the conservation patterns of protein sites based on their physico-chemical properties and the heterogeneity of evolutionary changes between and within the protein subfamilies. This web server provides an improved representation of results, adds useful input and output options and integrates a wide range of analysis and data visualization tools when compared with the original standalone version of the SPEER algorithm. Extensive benchmarking finds that SPEER-SERVER exhibits sensitivity and precision performance that, on average, meets or exceeds that of other currently available methods. SPEER-SERVER is available at http://www.hpppi.iicb.res.in/ss/. PMID:22689646

  3. Snoring Sounds Predict Obstruction Sites and Surgical Response in Patients with Obstructive Sleep Apnea Hypopnea Syndrome

    Science.gov (United States)

    Lee, Li-Ang; Lo, Yu-Lun; Yu, Jen-Fang; Lee, Gui-She; Ni, Yung-Lun; Chen, Ning-Hung; Fang, Tuan-Jen; Huang, Chung-Guei; Cheng, Wen-Nuan; Li, Hsueh-Yu

    2016-01-01

    Snoring sounds generated by different vibrators of the upper airway may be useful indicators of obstruction sites in patients with obstructive sleep apnea hypopnea syndrome (OSAHS). This study aimed to investigate associations between snoring sounds, obstruction sites, and surgical responses (≥50% reduction in the apnea-hypopnea index [AHI] and DISE), and relocation pharyngoplasty. All patients received follow-up polysomnography after 6 months. Fifteen (42%) patients with at least two complete obstruction sites defined by DISE were significantly, positively associated with maximal snoring sound intensity (40–300 Hz; odds ratio [OR], 1.25, 95% confidence interval [CI] 1.05–1.49) and body mass index (OR, 1.48, 95% CI 1.02–2.15) after logistic regression analysis. Tonsil obstruction was significantly, inversely correlated with mean snoring sound intensity (301–850 Hz; OR, 0.84, 95% CI 0.74–0.96). Moreover, baseline tonsil obstruction detected by either DISE or mean snoring sound intensity (301–850 Hz), and AHI could significantly predict the surgical response. Our findings suggest that snoring sound detection may be helpful in determining obstruction sites and predict surgical responses. PMID:27471038

  4. Position-specific prediction of methylation sites from sequence conservation based on information theory.

    Science.gov (United States)

    Shi, Yinan; Guo, Yanzhi; Hu, Yayun; Li, Menglong

    2015-07-23

    Protein methylation plays vital roles in many biological processes and has been implicated in various human diseases. To fully understand the mechanisms underlying methylation for use in drug design and work in methylation-related diseases, an initial but crucial step is to identify methylation sites. The use of high-throughput bioinformatics methods has become imperative to predict methylation sites. In this study, we developed a novel method that is based only on sequence conservation to predict protein methylation sites. Conservation difference profiles between methylated and non-methylated peptides were constructed by the information entropy (IE) in a wider neighbor interval around the methylation sites that fully incorporated all of the environmental information. Then, the distinctive neighbor residues were identified by the importance scores of information gain (IG). The most representative model was constructed by support vector machine (SVM) for Arginine and Lysine methylation, respectively. This model yielded a promising result on both the benchmark dataset and independent test set. The model was used to screen the entire human proteome, and many unknown substrates were identified. These results indicate that our method can serve as a useful supplement to elucidate the mechanism of protein methylation and facilitate hypothesis-driven experimental design and validation.

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

    Science.gov (United States)

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

    2014-03-07

    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.

  6. Predicting mining activity with parallel genetic algorithms

    Science.gov (United States)

    Talaie, S.; Leigh, R.; Louis, S.J.; Raines, G.L.; Beyer, H.G.; O'Reilly, U.M.; Banzhaf, Arnold D.; Blum, W.; Bonabeau, C.; Cantu-Paz, E.W.; ,; ,

    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.

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

    Energy Technology Data Exchange (ETDEWEB)

    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.

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

    Energy Technology Data Exchange (ETDEWEB)

    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.

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

    LENUS (Irish Health Repository)

    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.

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

    Science.gov (United States)

    Xue, Yu; Chen, Hu; Jin, Changjiang; Sun, Zhirong; Yao, Xuebiao

    2006-10-17

    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. 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. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  12. Measuring Active Learning to Predict Course Quality

    Science.gov (United States)

    Taylor, John E.; Ku, Heng-Yu

    2011-01-01

    This study investigated whether active learning within computer-based training courses can be measured and whether it serves as a predictor of learner-perceived course quality. A major corporation participated in this research, providing access to internal employee training courses, training representatives, and historical course evaluation data.…

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

    DEFF Research Database (Denmark)

    Pedersen, Anders Gorm; Nielsen, Henrik

    1997-01-01

    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 global sequence information. Furthermore, analysis of false predictions shows that AUGs in frame with the actual start codon are more frequently selected than out-of-frame AUGs, suggesting that our nteworks use reading frame detection. A number of conflicts between neural network predictions and database...... annotations are analysed in detail, leading to identification of possible database errors....

  14. Social Networking Site Use Predicts Changes in Young Adults’ Psychological Adjustment

    Science.gov (United States)

    Szwedo, David E.; Mikami, Amori Yee; Allen, Joseph P.

    2012-01-01

    This study examined youths’ friendships and posted pictures on social networking sites as predictors of changes in their adjustment over time. Observational, self-report, and peer report data were obtained from a community sample of 89 young adults interviewed at age 21 and again at age 22. Findings were consistent with a leveling effect for online friendships, predicting decreases in internalizing symptoms for youth with lower initial levels of social acceptance, but increases in symptoms for youth with higher initial levels over the following year. Across the entire sample, deviant behavior in posted photos predicted increases in young adults’ problematic alcohol use over time. The importance of considering the interplay between online and offline social factors for predicting adjustment is discussed. PMID:23109797

  15. Selection and Assessment of Predictions of the Mars Pathfinder Landing Site

    Science.gov (United States)

    Golombek, M. P.; Moore, H. J.; Haldemann, A. F. C.; Cook, R. A.; Parker, T. J.; Schofield, J. T.

    1998-01-01

    The successful landing of the Mars Pathfinder spacecraft on Mars allows the review of the process of selecting the landing site and assessing predictions made for the site based on Viking and Earth-based data. Selection of the landing site for Mars Pathfinder was a two-phase process. The first phase took place from October 1993 to June 1994 and involved: initial identification of engineering constraints, definition of environmental conditions at the site for spacecraft design, and evaluation of the scientific potential of different landing sites. This phase culminated with the first "Mars Pathfinder Landing Site Workshop", held at the Lunar and Planetary Institute in Houston, Texas on April 18-19, 1994, in which suggested approaches and landing sites were solicited from the entire scientific community. A preliminary site was selected by the project for design purposes in June 1994. The second phase took place from July 1994 to March 1996 and involved: developing criteria for evaluating site safety using images and remote sensing data, testing of the spacecraft and landing subsystems (with design improvements) to establish quantitative engineering constraints on landing site characteristics, evaluating all potential landing sites on Mars, and certification of the site by the project. This phase included a second open workshop, "Mars Pathfinder Landing Site Workshop II: Characteristics of the Ares Vallis Region and Field Trips in the Channeled Scabland, Washington" held in Spokane and Moses Lake September 24-30, 1995 and formal acceptance of the site by NASA Headquarters. Engineering constraints on Pathfinder landing sites were developed from the initial design of the spacecraft and the entry, descent and landing scenario. The site must be within 5 degrees of the subsolar latitude at the time of landing (15N for maximum solar power and flexible communications with Earth. It also must be below 0 km elevation to enable enough time for the parachute to bring the lander

  16. Using Tree-Ring Width Data From 1000 Sites to Predict how American Forests Will Respond to Climate Change

    Science.gov (United States)

    Williams, P.; Still, C. J.; Leavitt, S. W.; Fischer, D. T.

    2007-12-01

    Beginning in the early 1900s, tree-ring scientists began analyzing the relative widths of annual growth rings preserved in the cross-sections of trees. Over the years, many ring-width index chronologies, each representing a specific site and species, have been developed and analyzed to infer details regarding past climate, growth response to environmental fluctuation, fire activity, logging practices by past societies, and more. Of the many ring-width chronologies constructed, 1035 represent sites within the continental United States and have been published online within The International Tree-Ring Data Bank as of September 2007 (ITRDB, http://www.ncdc.noaa.gov/paleo/treering.html). Approximately 85% of these sites are located west of the Mississippi River. Here we present results from a three-step study, using this large reserve of tree-growth data to determine how various tree species in various regions have responded to climate fluctuations in the past and how they can be expected to respond to future change. In the first step, we used linear regression to compare each time series of ring-width index values to a suite of local monthly climate variables that may influence tree growth, such as rainfall, temperature, and drought severity (PDSI). We identified the range of months (of a 24- month period) during which each climate parameter most strongly affects growth by comparing Pearson correlation coefficients. In the second step, we identified all sites where at least one climate parameter, during some rage of months, correlates significantly (95% confidence) with ring-width index values. For each of these sites, we constructed a growth model that uses each significantly correlating climate parameter as a growth predictor. In the third step, we applied the growth model to predict the next 100 years of growth response to a monthly climate forecast created by the Hadley Centre for Climate Prediction and Research. This forecast (HadCM3 IS92a) assumes a business as

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

    Science.gov (United States)

    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.

  18. Prediction of carbamylated lysine sites based on the one-class k-nearest neighbor method.

    Science.gov (United States)

    Huang, Guohua; Zhou, You; Zhang, Yuchao; Li, Bi-Qing; Zhang, Ning; Cai, Yu-Dong

    2013-11-01

    Protein carbamylation is one of the important post-translational modifications, which plays a pivotal role in a number of biological conditions, such as diseases, chronic renal failure and atherosclerosis. Therefore, recognition and identification of protein carbamylated sites are essential for disease treatment and prevention. Yet the mechanism of action of carbamylated lysine sites is still not realized. Thus it remains a largely unsolved challenge to uncover it, whether experimentally or theoretically. To address this problem, we have presented a computational framework for theoretically predicting and analyzing carbamylated lysine sites based on both the one-class k-nearest neighbor method and two-stage feature selection. The one-class k-nearest neighbor method requires no negative samples in training. Experimental results showed that by using 280 optimal features the presented method achieved promising performances of SN=82.50% for the jackknife test on the training set, and SN=66.67%, SP=100.00% and MCC=0.8097 for the independent test on the testing set, respectively. Further analysis of the optimal features provided insights into the mechanism of action of carbamylated lysine sites. It is anticipated that our method could be a potentially useful and essential tool for biologists to theoretically investigate carbamylated lysine sites.

  19. E1DS: catalytic site prediction based on 1D signatures of concurrent conservation.

    Science.gov (United States)

    Chien, Ting-Ying; Chang, Darby Tien-Hao; Chen, Chien-Yu; Weng, Yi-Zhong; Hsu, Chen-Ming

    2008-07-01

    Large-scale automatic annotation of protein sequences remains challenging in postgenomics era. E1DS is designed for annotating enzyme sequences based on a repository of 1D signatures. The employed sequence signatures are derived using a novel pattern mining approach that discovers long motifs consisted of several sequential blocks (conserved segments). Each of the sequential blocks is considerably conserved among the protein members of an EC group. Moreover, a signature includes at least three sequential blocks that are concurrently conserved, i.e. frequently observed together in sequences. In other words, a sequence signature is consisted of residues from multiple regions of the protein sequence, which echoes the observation that an enzyme catalytic site is usually constituted of residues that are largely separated in the sequence. E1DS currently contains 5421 sequence signatures that in total cover 932 4-digital EC numbers. E1DS is evaluated based on a collection of enzymes with catalytic sites annotated in Catalytic Site Atlas. When compared to the famous pattern database PROSITE, predictions based on E1DS signatures are considered more sensitive in identifying catalytic sites and the involved residues. E1DS is available at http://e1ds.ee.ncku.edu.tw/ and a mirror site can be found at http://e1ds.csbb.ntu.edu.tw/.

  20. Combining features in a graphical model to predict protein binding sites.

    Science.gov (United States)

    Wierschin, Torsten; Wang, Keyu; Welter, Marlon; Waack, Stephan; Stanke, Mario

    2015-05-01

    Large efforts have been made in classifying residues as binding sites in proteins using machine learning methods. The prediction task can be translated into the computational challenge of assigning each residue the label binding site or non-binding site. Observational data comes from various possibly highly correlated sources. It includes the structure of the protein but not the structure of the complex. The model class of conditional random fields (CRFs) has previously successfully been used for protein binding site prediction. Here, a new CRF-approach is presented that models the dependencies of residues using a general graphical structure defined as a neighborhood graph and thus our model makes fewer independence assumptions on the labels than sequential labeling approaches. A novel node feature "change in free energy" is introduced into the model, which is then denoted by ΔF-CRF. Parameters are trained with an online large-margin algorithm. Using the standard feature class relative accessible surface area alone, the general graph-structure CRF already achieves higher prediction accuracy than the linear chain CRF of Li et al. ΔF-CRF performs significantly better on a large range of false positive rates than the support-vector-machine-based program PresCont of Zellner et al. on a homodimer set containing 128 chains. ΔF-CRF has a broader scope than PresCont since it is not constrained to protein subgroups and requires no multiple sequence alignment. The improvement is attributed to the advantageous combination of the novel node feature with the standard feature and to the adopted parameter training method.

  1. AMP-activated protein kinase phosphorylates EMCV, TMEV and SafV leader proteins at different sites.

    Science.gov (United States)

    Basta, Holly A; Palmenberg, Ann C

    2014-08-01

    Cardioviruses of the Encephalomyocarditis virus (EMCV) and Theilovirus species encode small, amino-terminal proteins called Leaders (L). Phosphorylation of the EMCV L (LE) at two distinct sites by CK2 and Syk kinases is important for virus-induced Nup phosphorylation and nucleocytoplasmic trafficking inhibition. Despite similar biological activities, the LE phosphorylation sites are not conserved in the Theiloviruses, Saffold virus (LS, SafV) or Theiler׳s murine encephalitis virus (LT, TMEV) sequences even though these proteins also become phosphorylated in cells and cell-free extracts. Site prediction algorithms, combined with panels of site-specific protein mutations now identify analogous, but not homologous phosphorylation sites in the Ser/Thr and Theilo protein domains of LT and LS, respectively. In both cases, recombinant AMP-activated kinase (AMPK) was reactive with the proteins at these sites, and also with LE, modifying the same residue recognized by CK2. Copyright © 2014 Elsevier Inc. All rights reserved.

  2. Active diagnosis of hybrid systems - A model predictive approach

    OpenAIRE

    2009-01-01

    A method for active diagnosis of hybrid systems is proposed. The main idea is to predict the future output of both normal and faulty model of the system; then at each time step an optimization problem is solved with the objective of maximizing the difference between the predicted normal and faulty outputs constrained by tolerable performance requirements. As in standard model predictive control, the first element of the optimal input is applied to the system and the whole procedure is repeate...

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

    DEFF Research Database (Denmark)

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

    1996-01-01

    splice sites normally haunting splice site prediction. An analysis of the errors made by the networks in the first step of the method revealed a previously unknown feature, a frequent T-tract prolongation containing cryptic acceptor sites in the 5'end of exons. The method presented here has been compared...

  4. Short communication: genetic variability in the predicted microRNA target sites of caprine casein genes.

    Science.gov (United States)

    Zidi, A; Amills, M; Tomás, A; Vidal, O; Ramírez, O; Carrizosa, J; Urrutia, B; Serradilla, J M; Clop, A

    2010-04-01

    The main goal of the current work was to identify single nucleotide polymorphisms (SNP) that might create or disrupt microRNA (miRNA) target sites in the caprine casein genes. The 3' untranslated regions of the goat alpha(S1)-, alpha(S2)-, beta-, and kappa-casein genes (CSN1S1, CSN1S2, CSN2, and CSN3, respectively) were resequenced in 25 individuals of the Murciano-Granadina, Cashmere, Canarian, Saanen, and Sahelian breeds. Five SNP were identified through this strategy: c.175C>T at CSN1S1; c.109T>C, c.139G>C, and c.160T>C at CSN1S2; and c.216C>T at CSN2. Analysis with the Patrocles Finder tool predicted that all of these SNP are located within regions complementary to the seed of diverse miRNA sequences. These in silico results suggest that polymorphism at miRNA target sites might have some effect on casein expression. We explored this issue by genotyping the c.175C>T SNP (CSN1S1) in 85 Murciano-Granadina goats with records for milk CSN1S1 concentrations. This substitution destroys a putative target site for miR-101, a miRNA known to be expressed in the bovine mammary gland. Although TT goats had higher levels (6.25 g/L) of CSN1S1 than their CT (6.05 g/L) and CC (6.04 g/L) counterparts, these differences were not significant. Experimental confirmation of the miRNA target sites predicted in the current work and performance of additional association analyses in other goat populations will be an essential step to find out if polymorphic miRNA target sites constitute an important source of variation in casein expression.

  5. Predicting sites of new hemorrhage with amyloid imaging in cerebral amyloid angiopathy

    Science.gov (United States)

    Dierksen, Gregory; Betensky, Rebecca; Gidicsin, Christopher; Halpin, Amy; Becker, Alex; Carmasin, Jeremy; Ayres, Alison; Schwab, Kristin; Viswanathan, Anand; Salat, David; Rosand, Jonathan; Johnson, Keith A.; Greenberg, Steven M.

    2012-01-01

    Objective: We aimed to determine whether amyloid imaging can help predict the location and number of future hemorrhages in cerebral amyloid angiopathy (CAA). Methods: We performed a longitudinal cohort study of 11 patients with CAA without dementia who underwent serial brain MRIs after baseline amyloid imaging with Pittsburgh compound B (PiB). Mean distribution volume ratio (DVR) of PiB was determined at the sites of new micro/macrobleeds identified on follow-up MRI and compared with PiB retention at “simulated” hemorrhages, randomly placed in the same subjects using a probability distribution map of CAA-hemorrhage location. Mean PiB retention at the sites of observed new bleeds was also compared to that in shells concentrically surrounding the bleeds. Finally the association between number of incident bleeds and 3 regional amyloid measures were obtained. Results: Nine of 11 subjects had at least one new microbleed on follow-up MRI (median 4, interquartile range [IQR] 1–9) and 2 had 5 new intracerebral hemorrhages. Mean DVR was greater at the sites of incident bleeds (1.34, 95% confidence interval [CI] 1.23–1.46) than simulated lesions (1.14, 95% CI 1.07–1.22, p < 0.0001) in multivariable models. PiB retention decreased with increasing distance from sites of observed bleeds (p < 0.0001). Mean DVR in a superior frontal/parasagittal region of interest correlated independently with number of future hemorrhages after adjustment for relevant covariates (p = 0.003). Conclusions: Our results provide direct evidence that new CAA-related hemorrhages occur preferentially at sites of increased amyloid deposition and suggest that PiB-PET imaging may be a useful tool in prediction of incident hemorrhages in patients with CAA. PMID:22786597

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

    Directory of Open Access Journals (Sweden)

    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.

  7. 77 FR 39508 - Commercial Wind Lease Issuance and Site Assessment Activities on the Atlantic Outer Continental...

    Science.gov (United States)

    2012-07-03

    ... characterization activities (geophysical, geotechnical, archaeological, and biological surveys needed to develop..., site characterization, and site assessment in and around the Call Area (76 FR 51391). The Call Area...

  8. Probing the putative active site of YjdL

    DEFF Research Database (Denmark)

    Jensen, Johanne Mørch; Ismat, Fouzia; Szakonyi, Gerda;

    2012-01-01

    YjdL from E. coli is an unusual proton-coupled oligopeptide transporter (POT). Unlike prototypical POTs, dipeptides are preferred over tripeptides, in particular dipeptides with a positively charged C-terminal residue. To further understand this difference in peptide specificity, the sequences...... of YjdL and YdgR, a prototypical E. coli POT, were compared in light of the crystal structure of a POT from Shewanella oneidensis. Several residues found in the putative active site were mutated and the activities of the mutated variants were assessed in terms of substrate uptake assays, and changes...... pocket that opens towards the extracellular space. The C-terminal side chain faces in the opposite direction into a sub pocket that faces the cytoplasm. These data indicated a stabilizing effect on a bulky N-terminal residue by an Ala281Phe variant and on the dipeptide backbone by Trp278...

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

  11. Impediments to predicting site response: Seismic property estimation and modeling simplifications

    Science.gov (United States)

    Thompson, E.M.; Baise, L.G.; Kayen, R.E.; Guzina, B.B.

    2009-01-01

    We compare estimates of the empirical transfer function (ETF) to the plane SH-wave theoretical transfer function (TTF) within a laterally constant medium for invasive and noninvasive estimates of the seismic shear-wave slownesses at 13 Kiban-Kyoshin network stations throughout Japan. The difference between the ETF and either of the TTFs is substantially larger than the difference between the two TTFs computed from different estimates of the seismic properties. We show that the plane SH-wave TTF through a laterally homogeneous medium at vertical incidence inadequately models observed amplifications at most sites for both slowness estimates, obtained via downhole measurements and the spectral analysis of surface waves. Strategies to improve the predictions can be separated into two broad categories: improving the measurement of soil properties and improving the theory that maps the 1D soil profile onto spectral amplification. Using an example site where the 1D plane SH-wave formulation poorly predicts the ETF, we find a more satisfactory fit to the ETF by modeling the full wavefield and incorporating spatially correlated variability of the seismic properties. We conclude that our ability to model the observed site response transfer function is limited largely by the assumptions of the theoretical formulation rather than the uncertainty of the soil property estimates.

  12. Prediction of mutant activity and its application in molecular design of tumor necrosis factor-a

    Institute of Scientific and Technical Information of China (English)

    唐卫东; 奚涛; 王波; 郭冬林; 徐贤秀; 朱德煦

    1997-01-01

    Two models for prediction of the activity and stability of site-directed mutagenesis on tumor necrosis factor-α are established. The models are based on straightforward structural considerations, which do not require the elaboration of site-directed mutagenesis on the protein core and the hydrophobic surface area by analyzing the properties of the mutated amino acid residues. The reliabilities of the models have been tested by analyzing the mutants of tumor necrosis factor-α (TNF-α) whose two leucine residues (L29, L157) were mutated. Based on these models, a TNF-α mutant with high activity was created by molecular design.

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

    Directory of Open Access Journals (Sweden)

    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. A Large-Scale Assessment of Nucleic Acids Binding Site Prediction Programs.

    Directory of Open Access Journals (Sweden)

    Zhichao Miao

    2015-12-01

    Full Text Available Computational prediction of nucleic acid binding sites in proteins are necessary to disentangle functional mechanisms in most biological processes and to explore the binding mechanisms. Several strategies have been proposed, but the state-of-the-art approaches display a great diversity in i the definition of nucleic acid binding sites; ii the training and test datasets; iii the algorithmic methods for the prediction strategies; iv the performance measures and v the distribution and availability of the prediction programs. Here we report a large-scale assessment of 19 web servers and 3 stand-alone programs on 41 datasets including more than 5000 proteins derived from 3D structures of protein-nucleic acid complexes. Well-defined binary assessment criteria (specificity, sensitivity, precision, accuracy… are applied. We found that i the tools have been greatly improved over the years; ii some of the approaches suffer from theoretical defects and there is still room for sorting out the essential mechanisms of binding; iii RNA binding and DNA binding appear to follow similar driving forces and iv dataset bias may exist in some methods.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    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.

  17. Eel calcitonin binding site distribution and antinociceptive activity in rats

    Energy Technology Data Exchange (ETDEWEB)

    Guidobono, F.; Netti, C.; Sibilia, V.; Villa, I.; Zamboni, A.; Pecile, A.

    1986-03-01

    The distribution of binding site for (/sup 125/I)-eel-calcitonin (ECT) to rat central nervous system, studied by an autoradiographic technique, showed concentrations of binding in the diencephalon, the brain stem and the spinal cord. Large accumulations of grains were seen in the hypothalamus, the amygdala, in the fasciculus medialis prosencephali, in the fasciculus longitudinalis medialis, in the ventrolateral part of the periventricular gray matter, in the lemniscus medialis and in the raphe nuclei. The density of grains in the reticular formation and in the nucleus tractus spinalis nervi trigemini was more moderate. In the spinal cord, grains were scattered throughout the dorsal horns. Binding of the ligand was displaced equally by cold ECT and by salmon CT(sCT), indicating that both peptides bind to the same receptors. Human CT was much weaker than sCT in displacing (/sup 125/I)-ECT binding. The administration of ECT into the brain ventricles of rats dose-dependently induced a significant and long-lasting enhancement of hot-plate latencies comparable with that obtained with sCT. The antinociceptive activity induced by ECT is compatible with the topographical distribution of binding sites for the peptide and is a further indication that fish CTs are active in the mammalian brain.

  18. Selection and Assessment of Predictions of the Mars Pathfinder Landing Site

    Science.gov (United States)

    Golombek, M. P.; Moore, H. J.; Haldemann, A. F. C.; Cook, R. A.; Parker, T. J.; Schofield, J. T.

    1998-01-01

    The successful landing of the Mars Pathfinder spacecraft on Mars allows the review of the process of selecting the landing site and assessing predictions made for the site based on Viking and Earth-based data. Selection of the landing site for Mars Pathfinder was a two-phase process. The first phase took place from October 1993 to June 1994 and involved: initial identification of engineering constraints, definition of environmental conditions at the site for spacecraft design, and evaluation of the scientific potential of different landing sites. This phase culminated with the first "Mars Pathfinder Landing Site Workshop", held at the Lunar and Planetary Institute in Houston, Texas on April 18-19, 1994, in which suggested approaches and landing sites were solicited from the entire scientific community. A preliminary site was selected by the project for design purposes in June 1994. The second phase took place from July 1994 to March 1996 and involved: developing criteria for evaluating site safety using images and remote sensing data, testing of the spacecraft and landing subsystems (with design improvements) to establish quantitative engineering constraints on landing site characteristics, evaluating all potential landing sites on Mars, and certification of the site by the project. This phase included a second open workshop, "Mars Pathfinder Landing Site Workshop II: Characteristics of the Ares Vallis Region and Field Trips in the Channeled Scabland, Washington" held in Spokane and Moses Lake September 24-30, 1995 and formal acceptance of the site by NASA Headquarters. Engineering constraints on Pathfinder landing sites were developed from the initial design of the spacecraft and the entry, descent and landing scenario. The site must be within 5 degrees of the subsolar latitude at the time of landing (15N for maximum solar power and flexible communications with Earth. It also must be below 0 km elevation to enable enough time for the parachute to bring the lander

  19. Site characterization and related activities at the potential high-level radioactive waste repository site at Yucca Mountain, Nevada

    Energy Technology Data Exchange (ETDEWEB)

    Gertz, C.P.; Nelson, R.M. Jr.; Blanchard, M.B. [Department of Energy, Las Vegas, NV (United States); Cloke, P.L. [Science Applications International Corp., Las Vegas, NV (United States)

    1994-12-31

    The Yucca Mountain Site Characterization Project (YMP) involves a complex set of activities and issues. These include the Exploratory Studies Facility (ESF), site characterization surface-based testing, performance assessment, public outreach and information services, conceptual design of a potential repository, compliance with regulations, environmental issues, transportation of nuclear wastes, and systems engineering. Integration among the scientific and technical activities requires constant attention to keep work focused on determining the suitability of the site and on avoiding irretrievable loss of data. All activities must be conducted with due regard to quality assurance and safety and health. This paper provides a brief summary of the status of these activities as of December, 1993.

  20. Evaluation of WEPP for runoff and sediment yield prediction on natural gas well sites

    Science.gov (United States)

    Natural gas exploration and production, with nearly 30,000 new wells drilled each year in the US, requires land disturbing activities that can accelerate soil loss. Erosion modeling has been successfully used for decades to predict soil loss and conservation effects on agricultural fields, rangelan...

  1. Archaeology Through Computational Linguistics: Inscription Statistics Predict Excavation Sites of Indus Valley Artifacts.

    Science.gov (United States)

    Recchia, Gabriel L; Louwerse, Max M

    2016-11-01

    Computational techniques comparing co-occurrences of city names in texts allow the relative longitudes and latitudes of cities to be estimated algorithmically. However, these techniques have not been applied to estimate the provenance of artifacts with unknown origins. Here, we estimate the geographic origin of artifacts from the Indus Valley Civilization, applying methods commonly used in cognitive science to the Indus script. We show that these methods can accurately predict the relative locations of archeological sites on the basis of artifacts of known provenance, and we further apply these techniques to determine the most probable excavation sites of four sealings of unknown provenance. These findings suggest that inscription statistics reflect historical interactions among locations in the Indus Valley region, and they illustrate how computational methods can help localize inscribed archeological artifacts of unknown origin. The success of this method offers opportunities for the cognitive sciences in general and for computational anthropology specifically.

  2. Human glucocerebrosidase: heterologous expression of active site mutants in murine null cells.

    Science.gov (United States)

    Fabrega, S; Durand, P; Codogno, P; Bauvy, C; Delomenie, C; Henrissat, B; Martin, B M; McKinney, C; Ginns, E I; Mornon, J P; Lehn, P

    2000-11-01

    Using bioinformatics methods, we have previously identified Glu235 and Glu340 as the putative acid/base catalyst and nucleophile, respectively, in the active site of human glucocerebrosidase. Thus, we undertook site-directed mutagenesis studies to obtain experimental evidence supporting these predictions. Recombinant retroviruses were used to express wild-type and E235A and E340A mutant proteins in glucocerebrosidase-deficient murine cells. In contrast to wild-type enzyme, the mutants were found to be catalytically inactive. We also report the results of various studies (Western blotting, glycosylation analysis, subcellular fractionation, and confocal microscopy) indicating that the wild-type and mutant enzymes are identically processed and sorted to the lysosomes. Thus, enzymatic inactivity of the mutant proteins is not the result of incorrect folding/processing. These findings indicate that Glu235 plays a key role in the catalytic machinery of human glucocerebrosidase and may indeed be the acid/base catalyst. As concerns Glu340, the results both support our computer-based predictions and confirm, at the biological level, previous identification of Glu340 as the nucleophile by use of active site labeling techniques. Finally, our findings may help to better understand the molecular basis of Gaucher disease, the human lysosomal disease resulting from deficiency in glucocerebrosidase.

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

    CERN Document Server

    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...

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

    DEFF Research Database (Denmark)

    Julenius, Karin; Mølgaard, Anne; Gupta, Ramneek

    2005-01-01

    O-GalNAc-glycosylation is one of the main types of glycosylation in mammalian cells. No consensus recognition sequence for the O-glycosyltransferases is known, making prediction methods necessary to bridge the gap between the large number of known protein sequences and the small number of proteins...... 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...

  5. Evaluation of the DayCent model to predict carbon fluxes in French crop sites

    Science.gov (United States)

    Fujisaki, Kenji; Martin, Manuel P.; Zhang, Yao; Bernoux, Martial; Chapuis-Lardy, Lydie

    2017-04-01

    Croplands in temperate regions are an important component of the carbon balance and can act as a sink or a source of carbon, depending on pedoclimatic conditions and management practices. Therefore the evaluation of carbon fluxes in croplands by modelling approach is relevant in the context of global change. This study was part of the Comete-Global project funded by the multi-Partner call FACCE JPI. Carbon fluxes, net ecosystem exchange (NEE), leaf area index (LAI), biomass, and grain production were simulated at the site level in three French crop experiments from the CarboEurope project. Several crops were studied, like winter wheat, rapeseed, barley, maize, and sunflower. Daily NEE was measured with eddy covariance and could be partitioned between gross primary production (GPP) and total ecosystem respiration (TER). Measurements were compared to DayCent simulations, a process-based model predicting plant production and soil organic matter turnover at daily time step. We compared two versions of the model: the original one with a simplified plant module and a newer version that simulates LAI. Input data for modelling were soil properties, climate, and management practices. Simulations of grain yields and biomass production were acceptable when using optimized crop parameters. Simulation of NEE was also acceptable. GPP predictions were improved with the newer version of the model, eliminating temporal shifts that could be observed with the original model. TER was underestimated by the model. Predicted NEE was more sensitive to soil tillage and nitrogen applications than measured NEE. DayCent was therefore a relevant tool to predict carbon fluxes in French crops at the site level. The introduction of LAI in the model improved its performance.

  6. Predicting Protein-Protein Interaction Sites with a Novel Membership Based Fuzzy SVM Classifier.

    Science.gov (United States)

    Sriwastava, Brijesh K; Basu, Subhadip; Maulik, Ujjwal

    2015-01-01

    Predicting residues that participate in protein-protein interactions (PPI) helps to identify, which amino acids are located at the interface. In this paper, we show that the performance of the classical support vector machine (SVM) algorithm can further be improved with the use of a custom-designed fuzzy membership function, for the partner-specific PPI interface prediction problem. We evaluated the performances of both classical SVM and fuzzy SVM (F-SVM) on the PPI databases of three different model proteomes of Homo sapiens, Escherichia coli and Saccharomyces Cerevisiae and calculated the statistical significance of the developed F-SVM over classical SVM algorithm. We also compared our performance with the available state-of-the-art fuzzy methods in this domain and observed significant performance improvements. To predict interaction sites in protein complexes, local composition of amino acids together with their physico-chemical characteristics are used, where the F-SVM based prediction method exploits the membership function for each pair of sequence fragments. The average F-SVM performance (area under ROC curve) on the test samples in 10-fold cross validation experiment are measured as 77.07, 78.39, and 74.91 percent for the aforementioned organisms respectively. Performances on independent test sets are obtained as 72.09, 73.24 and 82.74 percent respectively. The software is available for free download from http://code.google.com/p/cmater-bioinfo.

  7. The effects of reading comprehension and launch site on frequency-predictability interactions during paragraph reading.

    Science.gov (United States)

    Whitford, Veronica; Titone, Debra

    2014-01-01

    We used eye movement measures of paragraph reading to examine whether word frequency and predictability interact during the earliest stages of lexical processing, with a specific focus on whether these effects are modulated by individual differences in reading comprehension or launch site (i.e., saccade length between the prior and currently fixated word--a proxy for the amount of parafoveal word processing). The joint impact of frequency and predictability on reading will elucidate whether these variables additively or multiplicatively affect the earliest stages of lexical access, which, in turn, has implications for computational models of eye movements during reading. Linear mixed effects models revealed additive effects during both early- and late-stage reading, where predictability effects were comparable for low- and high-frequency words. Moreover, less cautious readers (e.g., readers who engaged in skimming, scanning, mindless reading) demonstrated smaller frequency effects than more cautious readers. Taken together, our findings suggest that during extended reading, frequency and predictability exert additive influences on lexical and postlexical processing, and that individual differences in reading comprehension modulate sensitivity to the effects of word frequency.

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

    Directory of Open Access Journals (Sweden)

    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.

  9. Differential active site loop conformations mediate promiscuous activities in the lactonase SsoPox.

    Directory of Open Access Journals (Sweden)

    Julien Hiblot

    Full Text Available Enzymes are proficient catalysts that enable fast rates of Michaelis-complex formation, the chemical step and products release. These different steps may require different conformational states of the active site that have distinct binding properties. Moreover, the conformational flexibility of the active site mediates alternative, promiscuous functions. Here we focused on the lactonase SsoPox from Sulfolobus solfataricus. SsoPox is a native lactonase endowed with promiscuous phosphotriesterase activity. We identified a position in the active site loop (W263 that governs its flexibility, and thereby affects the substrate specificity of the enzyme. We isolated two different sets of substitutions at position 263 that induce two distinct conformational sampling of the active loop and characterized the structural and kinetic effects of these substitutions. These sets of mutations selectively and distinctly mediate the improvement of the promiscuous phosphotriesterase and oxo-lactonase activities of SsoPox by increasing active-site loop flexibility. These observations corroborate the idea that conformational diversity governs enzymatic promiscuity and is a key feature of protein evolvability.

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

    Directory of Open Access Journals (Sweden)

    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.

  11. An Active Site Water Network in the Plasminogen Activator Pla from Yersinia pestis

    Energy Technology Data Exchange (ETDEWEB)

    Eren, Elif; Murphy, Megan; Goguen, Jon; van den Berg, Bert (UMASS, MED)

    2010-08-13

    The plasminogen activator Pla from Yersinia pestis is an outer membrane protease (omptin) that is important for the virulence of plague. Here, we present the high-resolution crystal structure of wild-type, enzymatically active Pla at 1.9 {angstrom}. The structure shows a water molecule located between active site residues D84 and H208, which likely corresponds to the nucleophilic water. A number of other water molecules are present in the active site, linking residues important for enzymatic activity. The R211 sidechain in loop L4 is close to the nucleophilic water and possibly involved in the stabilization of the oxyanion intermediate. Subtle conformational changes of H208 result from the binding of lipopolysaccharide to the outside of the barrel, explaining the unusual dependence of omptins on lipopolysaccharide for activity. The Pla structure suggests a model for the interaction with plasminogen substrate and provides a more detailed understanding of the catalytic mechanism of omptin proteases.

  12. Predicting Physical Activity in Arab American School Children

    Science.gov (United States)

    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).…

  13. Predicting Physical Activity in Arab American School Children

    Science.gov (United States)

    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).…

  14. Prediction of S-Nitrosylation Modification Sites Based on Kernel Sparse Representation Classification and mRMR Algorithm

    Directory of Open Access Journals (Sweden)

    Guohua Huang

    2014-01-01

    Full Text Available Protein S-nitrosylation plays a very important role in a wide variety of cellular biological activities. Hitherto, accurate prediction of S-nitrosylation sites is still of great challenge. In this paper, we presented a framework to computationally predict S-nitrosylation sites based on kernel sparse representation classification and minimum Redundancy Maximum Relevance algorithm. As much as 666 features derived from five categories of amino acid properties and one protein structure feature are used for numerical representation of proteins. A total of 529 protein sequences collected from the open-access databases and published literatures are used to train and test our predictor. Computational results show that our predictor achieves Matthews’ correlation coefficients of 0.1634 and 0.2919 for the training set and the testing set, respectively, which are better than those of k-nearest neighbor algorithm, random forest algorithm, and sparse representation classification algorithm. The experimental results also indicate that 134 optimal features can better represent the peptides of protein S-nitrosylation than the original 666 redundant features. Furthermore, we constructed an independent testing set of 113 protein sequences to evaluate the robustness of our predictor. Experimental result showed that our predictor also yielded good performance on the independent testing set with Matthews’ correlation coefficients of 0.2239.

  15. Predictability of bone density at posterior mandibular implant sites using cone-beam computed tomography intensity values.

    Science.gov (United States)

    Alkhader, Mustafa; Hudieb, Malik; Khader, Yousef

    2017-01-01

    The aim of this study was to investigate the predictability of bone density at posterior mandibular implant sites using cone-beam computed tomography (CBCT) intensity values. CBCT cross-sectional images for 436 posterior mandibular implant sites were selected for the study. Using Invivo software (Anatomage, San Jose, California, USA), two observers classified the bone density into three categories: low, intermediate, and high, and CBCT intensity values were generated. Based on the consensus of the two observers, 15.6% of sites were of low bone density, 47.9% were of intermediate density, and 36.5% were of high density. Receiver-operating characteristic analysis showed that CBCT intensity values had a high predictive power for predicting high density sites (area under the curve [AUC] =0.94, P density sites (AUC = 0.81, P density sites was 218 (sensitivity = 0.77 and specificity = 0.76) and the best cut-off value for intensity to predict high density sites was 403 (sensitivity = 0.93 and specificity = 0.77). CBCT intensity values are considered useful for predicting bone density at posterior mandibular implant sites.

  16. Prediction of extreme wind velocity at the site of the Runyang Suspension Bridge

    Institute of Scientific and Technical Information of China (English)

    Yang DENG; You-liang DING; Ai-qun LI; Guang-dong ZHOU

    2011-01-01

    This paper presents a distribution free method for predicting the extreme wind velocity from wind monitoring data at the site of the Runyang Suspension Bridge (RSB),China using the maximum entropy theory.The maximum entropy theory is a rational approach for choosing the most unbiased probability distribution from a small sample,which is consistent with available data and contains a minimum of spurious information.In this paper,the theory is used for estimating a joint probability density function considering the combined action of wind speed and direction based on statistical analysis of wind monitoring data at the site of the RSB.The joint probability distribution model is further used to estimate the extreme wind velocity at the deck level of the RSB.The results of the analysis reveal that the probability density function of the maximum entropy method achieves a result that fits well with the monitoring data.Hypothesis testing shows that the distributions of the wind velocity data collected during the past three years do not obey the Gumbel distribution.Finally,our comparison shows that the wind predictions of the maximum entropy method are higher than that of the Gumbel distribution,but much lower than the design wind speed.

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

    Science.gov (United States)

    Zhang, Yu; An, Jiao; Yang, Guang-Yu; Bai, Aixi; Zheng, Baisong; Lou, Zhiyong; Wu, Geng; Ye, Wei; Chen, Hai-Feng; Feng, Yan; Manco, Giuseppe

    2015-01-01

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    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. Features and prospects of juridical predicting of entrepreneurial activity

    Directory of Open Access Journals (Sweden)

    Natalya V. Rubtsova

    2017-03-01

    Full Text Available Objective to identify characteristics and prospects of predicting the business activity. Methods historical sociological logical systematicstructural formallegal comparativelegal legal modeling method. Results in article suggests the legal definition of prediction of business activity as a scientific and practical study aimed at the determination of the future state and prospects of development of business activity consisting of the evaluation of legal regulation and analysis of the prospectsof further socioeconomic development which aims to select the optimal solution for the further development of entrepreneurship through legal regulators. The work proves the necessity of achieving a balanced legal regulation of social relations by changing the legislation in the field of business agreements investment and innovation. Scientific novelty the article for the first time formulates the concept characteristics and features of legal prediction of business activity substantiates the impact of predicting on the development of legal regulation of social relations. Practical significance the main provisions and conclusions of the article can be used in research and teaching while considering the issues of predicting both the socioeconomic processes in general and business activity in particular.

  1. Computational Prediction of O-linked Glycosylation Sites that Preferentially Map on Intrinsically Disordered Regions of Extracellular Proteins

    Directory of Open Access Journals (Sweden)

    Satoshi Fukuchi

    2010-12-01

    Full Text Available O-glycosylation of mammalian proteins is one of the important posttranslational modifications. We applied a support vector machine (SVM to predict whether Ser or Thr is glycosylated, in order to elucidate the O-glycosylation mechanism. O-glycosylated sites were often found clustered along the sequence, whereas other sites were located sporadically. Therefore, we developed two types of SVMs for predicting clustered and isolated sites separately. We found that the amino acid composition was effective for predicting the clustered type, whereas the site-specific algorithm was effective for the isolated type. The highest prediction accuracy for the clustered type was 74%, while that for the isolated type was 79%. The existence frequency of amino acids around the O-glycosylation sites was different in the two types: namely, Pro, Val and Ala had high existence probabilities at each specific position relative to a glycosylation site, especially for the isolated type. Independent component analyses for the amino acid sequences around O-glycosylation sites showed the position-specific existences of the identified amino acids as independent components. The O-glycosylation sites were preferentially located within intrinsically disordered regions of extracellular proteins: particularly, more than 90% of the clustered O-GalNAc glycosylation sites were observed in intrinsically disordered regions. This feature could be the key for understanding the non-conservation property of O-glycosylation, and its role in functional diversity and structural stability.

  2. Prediction of PKCθ Inhibitory Activity Using the Random Forest Algorithm

    Directory of Open Access Journals (Sweden)

    Shuwei Zhang

    2010-09-01

    Full Text Available This work is devoted to the prediction of a series of 208 structurally diverse PKCθ inhibitors using the Random Forest (RF based on the Mold2 molecular descriptors. The RF model was established and identified as a robust predictor of the experimental pIC50 values, producing good external R2pred of 0.72, a standard error of prediction (SEP of 0.45, for an external prediction set of 51 inhibitors which were not used in the development of QSAR models. By using the RF built-in measure of the relative importance of the descriptors, an important predictor—the number of group donor atoms for H-bonds (with N and O―has been identified to play a crucial role in PKCθ inhibitory activity. We hope that the developed RF model will be helpful in the screening and prediction of novel unknown PKCθ inhibitory activity.

  3. Identification of co-regulated genes through Bayesian clustering of predicted regulatory binding sites.

    Science.gov (United States)

    Qin, Zhaohui S; McCue, Lee Ann; Thompson, William; Mayerhofer, Linda; Lawrence, Charles E; Liu, Jun S

    2003-04-01

    The identification of co-regulated genes and their transcription-factor binding sites (TFBS) are key steps toward understanding transcription regulation. In addition to effective laboratory assays, various computational approaches for the detection of TFBS in promoter regions of coexpressed genes have been developed. The availability of complete genome sequences combined with the likelihood that transcription factors and their cognate sites are often conserved during evolution has led to the development of phylogenetic footprinting. The modus operandi of this technique is to search for conserved motifs upstream of orthologous genes from closely related species. The method can identify hundreds of TFBS without prior knowledge of co-regulation or coexpression. Because many of these predicted sites are likely to be bound by the same transcription factor, motifs with similar patterns can be put into clusters so as to infer the sets of co-regulated genes, that is, the regulons. This strategy utilizes only genome sequence information and is complementary to and confirmative of gene expression data generated by microarray experiments. However, the limited data available to characterize individual binding patterns, the variation in motif alignment, motif width, and base conservation, and the lack of knowledge of the number and sizes of regulons make this inference problem difficult. We have developed a Gibbs sampling-based Bayesian motif clustering (BMC) algorithm to address these challenges. Tests on simulated data sets show that BMC produces many fewer errors than hierarchical and K-means clustering methods. The application of BMC to hundreds of predicted gamma-proteobacterial motifs correctly identified many experimentally reported regulons, inferred the existence of previously unreported members of these regulons, and suggested novel regulons.

  4. Prediction of O-glycosylation Sites Using Random Forest and GA-Tuned PSO Technique.

    Science.gov (United States)

    Hassan, Hebatallah; Badr, Amr; Abdelhalim, M B

    2015-01-01

    O-glycosylation is one of the main types of the mammalian protein glycosylation; it occurs on the particular site of serine (S) or threonine (T). Several O-glycosylation site predictors have been developed. However, a need to get even better prediction tools remains. One challenge in training the classifiers is that the available datasets are highly imbalanced, which makes the classification accuracy for the minority class to become unsatisfactory. In our previous work, we have proposed a new classification approach, which is based on particle swarm optimization (PSO) and random forest (RF); this approach has considered the imbalanced dataset problem. The PSO parameters setting in the training process impacts the classification accuracy. Thus, in this paper, we perform parameters optimization for the PSO algorithm, based on genetic algorithm, in order to increase the classification accuracy. Our proposed genetic algorithm-based approach has shown better performance in terms of area under the receiver operating characteristic curve against existing predictors. In addition, we implemented a glycosylation predictor tool based on that approach, and we demonstrated that this tool could successfully identify candidate glycosylation sites in case study protein.

  5. External validation and prediction employing the predictive squared correlation coefficient test set activity mean vs training set activity mean.

    Science.gov (United States)

    Schüürmann, Gerrit; Ebert, Ralf-Uwe; Chen, Jingwen; Wang, Bin; Kühne, Ralph

    2008-11-01

    The external prediction capability of quantitative structure-activity relationship (QSAR) models is often quantified using the predictive squared correlation coefficient, q (2). This index relates the predictive residual sum of squares, PRESS, to the activity sum of squares, SS, without postprocessing of the model output, the latter of which is automatically done when calculating the conventional squared correlation coefficient, r (2). According to the current OECD guidelines, q (2) for external validation should be calculated with SS referring to the training set activity mean. Our present findings including a mathematical proof demonstrate that this approach yields a systematic overestimation of the prediction capability that is triggered by the difference between the training and test set activity means. Example calculations with three regression models and data sets taken from literature show further that for external test sets, q (2) based on the training set activity mean may become even larger than r (2). As a consequence, we suggest to always use the test set activity mean when quantifying the external prediction capability through q (2) and to revise the respective OECD guidance document accordingly. The discussion includes a comparison between r (2) and q (2) value ranges and the q (2) statistics for cross-validation.

  6. Active diagnosis of hybrid systems - A model predictive approach

    DEFF Research Database (Denmark)

    Tabatabaeipour, Seyed Mojtaba; Ravn, Anders P.; Izadi-Zamanabadi, Roozbeh;

    2009-01-01

    A method for active diagnosis of hybrid systems is proposed. The main idea is to predict the future output of both normal and faulty model of the system; then at each time step an optimization problem is solved with the objective of maximizing the difference between the predicted normal and faulty...... outputs constrained by tolerable performance requirements. As in standard model predictive control, the first element of the optimal input is applied to the system and the whole procedure is repeated until the fault is detected by a passive diagnoser. It is demonstrated how the generated excitation signal...

  7. Feature Selection Combined with Neural Network Structure Optimization for HIV-1 Protease Cleavage Site Prediction

    Directory of Open Access Journals (Sweden)

    Hui Liu

    2015-01-01

    Full Text Available It is crucial to understand the specificity of HIV-1 protease for designing HIV-1 protease inhibitors. In this paper, a new feature selection method combined with neural network structure optimization is proposed to analyze the specificity of HIV-1 protease and find the important positions in an octapeptide that determined its cleavability. Two kinds of newly proposed features based on Amino Acid Index database plus traditional orthogonal encoding features are used in this paper, taking both physiochemical and sequence information into consideration. Results of feature selection prove that p2, p1, p1′, and p2′ are the most important positions. Two feature fusion methods are used in this paper: combination fusion and decision fusion aiming to get comprehensive feature representation and improve prediction performance. Decision fusion of subsets that getting after feature selection obtains excellent prediction performance, which proves feature selection combined with decision fusion is an effective and useful method for the task of HIV-1 protease cleavage site prediction. The results and analysis in this paper can provide useful instruction and help designing HIV-1 protease inhibitor in the future.

  8. Predicting and mapping potential Whooping Crane stopover habitat to guide site selection for wind energy projects.

    Science.gov (United States)

    Belaire, J Amy; Kreakie, Betty J; Keitt, Timothy; Minor, Emily

    2014-04-01

    Migratory stopover habitats are often not part of planning for conservation or new development projects. We identified potential stopover habitats within an avian migratory flyway and demonstrated how this information can guide the site-selection process for new development. We used the random forests modeling approach to map the distribution of predicted stopover habitat for the Whooping Crane (Grus americana), an endangered species whose migratory flyway overlaps with an area where wind energy development is expected to become increasingly important. We then used this information to identify areas for potential wind power development in a U.S. state within the flyway (Nebraska) that minimize conflicts between Whooping Crane stopover habitat and the development of clean, renewable energy sources. Up to 54% of our study area was predicted to be unsuitable as Whooping Crane stopover habitat and could be considered relatively low risk for conflicts between Whooping Cranes and wind energy development. We suggest that this type of analysis be incorporated into the habitat conservation planning process in areas where incidental take permits are being considered for Whooping Cranes or other species of concern. Field surveys should always be conducted prior to construction to verify model predictions and understand baseline conditions.

  9. A Model for Predicting Late Prehistoric Architectural Sites at the Pinon Canyon Maneuver Site in Southeastern Colorado

    Science.gov (United States)

    2007-01-01

    Archaic. This suggests that vegetal materials, possibly including maize, and other cultigens probably constituted larger portions of the human diet ...placement of rock art has been demonstrated in Upper Paleolithic sites of Europe, as well as in North America (Waller 1993). Open-air sites near canyons

  10. Allosteric site-mediated active site inhibition of PBP2a using Quercetin 3-O-rutinoside and its combination.

    Science.gov (United States)

    Rani, Nidhi; Vijayakumar, Saravanan; P T V, Lakshmi; Arunachalam, Annamalai

    2016-08-01

    Recent crystallographic study revealed the involvement of allosteric site in active site inhibition of penicillin binding protein (PBP2a), where one molecule of Ceftaroline (Cef) binds to the allosteric site of PBP2a and paved way for the other molecule (Cef) to bind at the active site. Though Cef has the potency to inhibit the PBP2a, its adverse side effects are of major concern. Previous studies have reported the antibacterial property of Quercetin derivatives, a group of natural compounds. Hence, the present study aims to evaluate the effect of Quercetin 3-o-rutinoside (Rut) in allosteric site-mediated active site inhibition of PBP2a. The molecular docking studies between allosteric site and ligands (Rut, Que, and Cef) revealed a better binding efficiency (G-score) of Rut (-7.790318) and Cef (-6.194946) with respect to Que (-5.079284). Molecular dynamic (MD) simulation studies showed significant changes at the active site in the presence of ligands (Rut and Cef) at allosteric site. Four different combinations of Rut and Cef were docked and their G-scores ranged between -6.320 and -8.623. MD studies revealed the stability of the key residue (Ser403) with Rut being at both sites, compared to other complexes. Morphological analysis through electron microscopy confirmed that combination of Rut and Cefixime was able to disturb the bacterial cell membrane in a similar fashion to that of Rut and Cefixime alone. The results of this study indicate that the affinity of Rut at both sites were equally good, with further validations Rut could be considered as an alternative for inhibiting MRSA growth.

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

    DEFF Research Database (Denmark)

    Henao, Ricardo; Winther, Ole

    2010-01-01

    to 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 reasonable......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...... available in GPs to make a common ranking for both active and inactive points, allowing points to be removed again from the active set. This is important for keeping the complexity down and at the same time focusing on points close to the decision boundary. We lend both theoretical and empirical support...

  12. How well do cognitive and environmental variables predict active commuting?

    Directory of Open Access Journals (Sweden)

    Godin Gaston

    2009-03-01

    Full Text Available Abstract Background In recent years, there has been growing interest in theoretical studies integrating cognitions and environmental variables in the prediction of behaviour related to the obesity epidemic. This is the approach adopted in the present study in reference to the theory of planned behaviour. More precisely, the aim of this study was to determine the contribution of cognitive and environmental variables in the prediction of active commuting to get to and from work or school. Methods A prospective study was carried out with 130 undergraduate and graduate students (93 females; 37 males. Environmental, cognitive and socio-demographic variables were evaluated at baseline by questionnaire. Two weeks later, active commuting (walking/bicycling to get to and from work or school was self-reported by questionnaire. Hierarchical multiple regression analyses were performed to predict intention and behaviour. Results The model predicting behaviour based on cognitive variables explained more variance than the model based on environmental variables (37.4% versus 26.8%; Z = 3.86, p p p Conclusion The results showed that cognitive variables play a more important role than environmental variables in predicting and explaining active commuting. When environmental variables were significant, they were mediated by cognitive variables. Therefore, individual cognitions should remain one of the main focuses of interventions promoting active commuting among undergraduate and graduate students.

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

    Directory of Open Access Journals (Sweden)

    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.

  14. Residents’ Environmental Conservation Behaviors at Tourist Sites: Broadening the Norm Activation Framework by Adopting Environment Attachment

    Directory of Open Access Journals (Sweden)

    Yuling Zhang

    2016-06-01

    Full Text Available Understanding the factors that affect residents’ environmental conservation behaviors help in managing the environment of tourist sites. This research provides an integrative understanding of how residents near tourist sites form their environmental conservation behaviors by merging the norm-activation model and cognitive-affective model into one theoretical framework. Results of the structural analysis from a sample of 642 residents showed that this study’s proposed composite model includes a satisfactory level of predictive power for environmental conservation behaviors. The findings identify the following two dimensions of awareness of environmental consequences as having a key role in predicting environmental conservation behaviors: (1 awareness of positive consequences of environmental protection; and (2 awareness of disaster consequences. Results also show that environment attachment and personal norms about environmentalism played a mediating role between awareness of environmental consequences and environmental conservation behaviors, and that personal norms about environmentalism were the most powerful factor in predicting behaviors. Several practical implications were derived from the research findings that can contribute to environment management policy both within and outside the field of tourism, mostly notably: (1 how the effective promotion of these factors can encourage environmental conservation behaviors for residents; and (2 how governments can develop and implement environmental management measures to improve locals’ awareness of positive consequences of environmental protection.

  15. Active site conformational dynamics in human uridine phosphorylase 1.

    Directory of Open Access Journals (Sweden)

    Tarmo P Roosild

    Full Text Available Uridine phosphorylase (UPP is a central enzyme in the pyrimidine salvage pathway, catalyzing the reversible phosphorolysis of uridine to uracil and ribose-1-phosphate. Human UPP activity has been a focus of cancer research due to its role in activating fluoropyrimidine nucleoside chemotherapeutic agents such as 5-fluorouracil (5-FU and capecitabine. Additionally, specific molecular inhibitors of this enzyme have been found to raise endogenous uridine concentrations, which can produce a cytoprotective effect on normal tissues exposed to these drugs. Here we report the structure of hUPP1 bound to 5-FU at 2.3 A resolution. Analysis of this structure reveals new insights as to the conformational motions the enzyme undergoes in the course of substrate binding and catalysis. The dimeric enzyme is capable of a large hinge motion between its two domains, facilitating ligand exchange and explaining observed cooperativity between the two active sites in binding phosphate-bearing substrates. Further, a loop toward the back end of the uracil binding pocket is shown to flexibly adjust to the varying chemistry of different compounds through an "induced-fit" association mechanism that was not observed in earlier hUPP1 structures. The details surrounding these dynamic aspects of hUPP1 structure and function provide unexplored avenues to develop novel inhibitors of this protein with improved specificity and increased affinity. Given the recent emergence of new roles for uridine as a neuron protective compound in ischemia and degenerative diseases, such as Alzheimer's and Parkinson's, inhibitors of hUPP1 with greater efficacy, which are able to boost cellular uridine levels without adverse side-effects, may have a wide range of therapeutic applications.

  16. Evaluation of different approaches for identifying optimal sites to predict mean hillslope soil moisture content

    Science.gov (United States)

    Liao, Kaihua; Zhou, Zhiwen; Lai, Xiaoming; Zhu, Qing; Feng, Huihui

    2017-04-01

    The identification of representative soil moisture sampling sites is important for the validation of remotely sensed mean soil moisture in a certain area and ground-based soil moisture measurements in catchment or hillslope hydrological studies. Numerous approaches have been developed to identify optimal sites for predicting mean soil moisture. Each method has certain advantages and disadvantages, but they have rarely been evaluated and compared. In our study, surface (0-20 cm) soil moisture data from January 2013 to March 2016 (a total of 43 sampling days) were collected at 77 sampling sites on a mixed land-use (tea and bamboo) hillslope in the hilly area of Taihu Lake Basin, China. A total of 10 methods (temporal stability (TS) analyses based on 2 indices, K-means clustering based on 6 kinds of inputs and 2 random sampling strategies) were evaluated for determining optimal sampling sites for mean soil moisture estimation. They were TS analyses based on the smallest index of temporal stability (ITS, a combination of the mean relative difference and standard deviation of relative difference (SDRD)) and based on the smallest SDRD, K-means clustering based on soil properties and terrain indices (EFs), repeated soil moisture measurements (Theta), EFs plus one-time soil moisture data (EFsTheta), and the principal components derived from EFs (EFs-PCA), Theta (Theta-PCA), and EFsTheta (EFsTheta-PCA), and global and stratified random sampling strategies. Results showed that the TS based on the smallest ITS was better (RMSE = 0.023 m3 m-3) than that based on the smallest SDRD (RMSE = 0.034 m3 m-3). The K-means clustering based on EFsTheta (-PCA) was better (RMSE sampling design stratified by the land use was more efficient than the global random method. Forty and 60 sampling sites are needed for stratified sampling and global sampling respectively to make their performances comparable to the best K-means method (EFsTheta-PCA). Overall, TS required only one site, but its

  17. Hazardous Material Storage Facilities and Sites - WASTE_SOLID_ACTIVE_PERMITTED_IDEM_IN: Active Permitted Solid Waste Sites in Indiana (Indiana Department of Environmental Management, Point Shapefile)

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — WASTE_SOLID_ACTIVE_PERMITTED_IDEM_IN is a point shapefile that contains active permitted solid waste site locations in Indiana, provided by personnel of Indiana...

  18. A neural network model for olfactory glomerular activity prediction

    Science.gov (United States)

    Soh, Zu; Tsuji, Toshio; Takiguchi, Noboru; Ohtake, Hisao

    2012-12-01

    Recently, the importance of odors and methods for their evaluation have seen increased emphasis, especially in the fragrance and food industries. Although odors can be characterized by their odorant components, their chemical information cannot be directly related to the flavors we perceive. Biological research has revealed that neuronal activity related to glomeruli (which form part of the olfactory system) is closely connected to odor qualities. Here we report on a neural network model of the olfactory system that can predict glomerular activity from odorant molecule structures. We also report on the learning and prediction ability of the proposed model.

  19. Active site - a site of binding of affinity inhibitors in baker's yeast inorganic pyrophosphatase

    Energy Technology Data Exchange (ETDEWEB)

    Svyato, I.E.; Sklyankina, V.A.; Avaeva, S.M.

    1986-03-20

    The interaction of the enzyme-substrate complex with methyl phosphate, O-phosphoethanolamine, O-phosphopropanolamine, N-acetylphosphoserine, and phosphoglyolic acid, as well as pyrophosphatase, modified by monoesters of phosphoric acid, with pyrophosphate and tripolyphosphate, was investigated. It was shown that the enzyme containing the substrate in the active site does not react with monophosphates, but modified pyrophosphatase entirely retains the ability to bind polyanions to the regulatory site. It is concluded that the inactivation of baker's yeast inorganic pyrophosphatase by monoesters of phosphoric acid, which are affinity inhibitors of it, is the result of modification of the active site of the enzyme.

  20. Physical Activity Predicts Performance in an Unpracticed Bimanual Coordination Task

    Science.gov (United States)

    Boisgontier, Matthieu P.; Serbruyns, Leen; Swinnen, Stephan P.

    2017-01-01

    Practice of a given physical activity is known to improve the motor skills related to this activity. However, whether unrelated skills are also improved is still unclear. To test the impact of physical activity on an unpracticed motor task, 26 young adults completed the international physical activity questionnaire and performed a bimanual coordination task they had never practiced before. Results showed that higher total physical activity predicted higher performance in the bimanual task, controlling for multiple factors such as age, physical inactivity, music practice, and computer games practice. Linear mixed models allowed this effect of physical activity to be generalized to a large population of bimanual coordination conditions. This finding runs counter to the notion that generalized motor abilities do not exist and supports the existence of a “learning to learn” skill that could be improved through physical activity and that impacts performance in tasks that are not necessarily related to the practiced activity. PMID:28265253

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

    Science.gov (United States)

    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

  2. Site-directed mutagenesis of the Anabaena sp. strain PCC 7120 nitrogenase active site to increase photobiological hydrogen production.

    Science.gov (United States)

    Masukawa, Hajime; Inoue, Kazuhito; Sakurai, Hidehiro; Wolk, C Peter; Hausinger, Robert P

    2010-10-01

    Cyanobacteria use sunlight and water to produce hydrogen gas (H₂), which is potentially useful as a clean and renewable biofuel. Photobiological H₂ arises primarily as an inevitable by-product of N₂ fixation by nitrogenase, an oxygen-labile enzyme typically containing an iron-molybdenum cofactor (FeMo-co) active site. In Anabaena sp. strain 7120, the enzyme is localized to the microaerobic environment of heterocysts, a highly differentiated subset of the filamentous cells. In an effort to increase H₂ production by this strain, six nitrogenase amino acid residues predicted to reside within 5 Å of the FeMo-co were mutated in an attempt to direct electron flow selectively toward proton reduction in the presence of N₂. Most of the 49 variants examined were deficient in N₂-fixing growth and exhibited decreases in their in vivo rates of acetylene reduction. Of greater interest, several variants examined under an N₂ atmosphere significantly increased their in vivo rates of H₂ production, approximating rates equivalent to those under an Ar atmosphere, and accumulated high levels of H₂ compared to the reference strains. These results demonstrate the feasibility of engineering cyanobacterial strains for enhanced photobiological production of H₂ in an aerobic, nitrogen-containing environment.

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

    Directory of Open Access Journals (Sweden)

    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

  4. Effect of particle surface area on ice active site densities retrieved from droplet freezing spectra

    Science.gov (United States)

    Beydoun, Hassan; Polen, Michael; Sullivan, Ryan C.

    2016-10-01

    active site density functions, such as the popular ns parameterization, cannot be reliably extrapolated below this critical surface area threshold to describe freezing curves for lower particle surface area concentrations. Freezing curves obtained below this threshold translate to higher ns values, while the ns values are essentially the same from curves obtained above the critical area threshold; ns should remain the same for a system as concentration is varied. However, we can successfully predict the lower concentration freezing curves, which are more atmospherically relevant, through a process of random sampling from g distributions obtained from high particle concentration data. Our analysis is applied to cold plate freezing measurements of droplets containing variable concentrations of particles from NX illite minerals, MCC cellulose, and commercial Snomax bacterial particles. Parameterizations that can predict the temporal evolution of the frozen fraction of cloud droplets in larger atmospheric models are also derived from this new framework.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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

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

    Directory of Open Access Journals (Sweden)

    Shangkun Deng

    2014-01-01

    Full Text Available 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.

  8. Impulse propagation over a complex site: a comparison of experimental results and numerical predictions.

    Science.gov (United States)

    Dragna, Didier; Blanc-Benon, Philippe; Poisson, Franck

    2014-03-01

    Results from outdoor acoustic measurements performed in a railway site near Reims in France in May 2010 are compared to those obtained from a finite-difference time-domain solver of the linearized Euler equations. During the experiments, the ground profile and the different ground surface impedances were determined. Meteorological measurements were also performed to deduce mean vertical profiles of wind and temperature. An alarm pistol was used as a source of impulse signals and three microphones were located along a propagation path. The various measured parameters are introduced as input data into the numerical solver. In the frequency domain, the numerical results are in good accordance with the measurements up to a frequency of 2 kHz. In the time domain, except a time shift, the predicted waveforms match the measured waveforms with a close agreement.

  9. Prediction of primate splice site using inhomogeneous Markov chain and neural network.

    Science.gov (United States)

    Liu, Libin; Ho, Yee-Kin; Yau, Stephen

    2007-07-01

    The inhomogeneous Markov chain model is used to discriminate acceptor and donor sites in genomic DNA sequences. It outperforms statistical methods such as homogeneous Markov chain model, higher order Markov chain and interpolated Markov chain models, and machine-learning methods such as k-nearest neighbor and support vector machine as well. Besides its high accuracy, another advantage of inhomogeneous Markov chain model is its simplicity in computation. In the three states system (acceptor, donor, and neither), the inhomogeneous Markov chain model is combined with a three-layer feed forward neural network. Using this combined system 3175 primate splice-junction gene sequences have been tested, with a prediction accuracy of greater than 98%.

  10. Gene Expression-Based Survival Prediction in Lung Adenocarcinoma: A Multi-Site, Blinded Validation Study

    Science.gov (United States)

    Shedden, Kerby; Taylor, Jeremy M.G.; Enkemann, Steve A.; Tsao, Ming S.; Yeatman, Timothy J.; Gerald, William L.; Eschrich, Steve; Jurisica, Igor; Venkatraman, Seshan E.; Meyerson, Matthew; Kuick, Rork; Dobbin, Kevin K.; Lively, Tracy; Jacobson, James W.; Beer, David G.; Giordano, Thomas J.; Misek, David E.; Chang, Andrew C.; Zhu, Chang Qi; Strumpf, Dan; Hanash, Samir; Shepherd, Francis A.; Ding, Kuyue; Seymour, Lesley; Naoki, Katsuhiko; Pennell, Nathan; Weir, Barbara; Verhaak, Roel; Ladd-Acosta, Christine; Golub, Todd; Gruidl, Mike; Szoke, Janos; Zakowski, Maureen; Rusch, Valerie; Kris, Mark; Viale, Agnes; Motoi, Noriko; Travis, William; Sharma, Anupama

    2009-01-01

    Although prognostic gene expression signatures for survival in early stage lung cancer have been proposed, for clinical application it is critical to establish their performance across different subject populations and in different laboratories. Here we report a large, training-testing, multi-site blinded validation study to characterize the performance of several prognostic models based on gene expression for 442 lung adenocarcinomas. The hypotheses proposed examined whether microarray measurements of gene expression either alone or combined with basic clinical covariates (stage, age, sex) can be used to predict overall survival in lung cancer subjects. Several models examined produced risk scores that substantially correlated with actual subject outcome. Most methods performed better with clinical data, supporting the combined use of clinical and molecular information when building prognostic models for early stage lung cancer. This study also provides the largest available set of microarray data with extensive pathological and clinical annotation for lung adenocarcinomas. PMID:18641660

  11. ChloroP, a neural network-based method for predicting chloroplast transitpeptides and their cleavage sites

    DEFF Research Database (Denmark)

    Emanuelsson, O.; Nielsen, Henrik; von Heijne, Gunnar

    1999-01-01

    We present a neural network based method (ChloroP) for identifying chloroplast transit peptides and their cleavage sites. Using cross-validation, 88% of the sequences in our homology reduced training set were correctly classified as transit peptides or nontransit peptides. This performance level...... is well above that of the publicly available chloroplast localization predictor PSORT. Cleavage sites are predicted using a scoring matrix derived by an automatic motif-finding algorithm. Approximately 60% of the known cleavage sites in our sequence collection were predicted to within +/-2 residues from...

  12. SNP2TFBS – a database of regulatory SNPs affecting predicted transcription factor binding site affinity

    Science.gov (United States)

    Kumar, Sunil; Ambrosini, Giovanna; Bucher, Philipp

    2017-01-01

    SNP2TFBS is a computational resource intended to support researchers investigating the molecular mechanisms underlying regulatory variation in the human genome. The database essentially consists of a collection of text files providing specific annotations for human single nucleotide polymorphisms (SNPs), namely whether they are predicted to abolish, create or change the affinity of one or several transcription factor (TF) binding sites. A SNP's effect on TF binding is estimated based on a position weight matrix (PWM) model for the binding specificity of the corresponding factor. These data files are regenerated at regular intervals by an automatic procedure that takes as input a reference genome, a comprehensive SNP catalogue and a collection of PWMs. SNP2TFBS is also accessible over a web interface, enabling users to view the information provided for an individual SNP, to extract SNPs based on various search criteria, to annotate uploaded sets of SNPs or to display statistics about the frequencies of binding sites affected by selected SNPs. Homepage: http://ccg.vital-it.ch/snp2tfbs/. PMID:27899579

  13. Prediction of evacuation time for emergency planning zone of Uljin nuclear site

    Energy Technology Data Exchange (ETDEWEB)

    Jeon, In Young; Lee, Jai Ki [Hanyang Univ., Seoul (Korea, Republic of)

    2002-09-15

    The time for evacuation of residents in Emergency Planning Zone (EPZ) of Uljin nuclear site in case of a radiological emergency was estimated with traffic analysis. Evacuees were classified into 4 groups by considering population density, local jurisdictions, and whether they are residents or transients. The survey to investigate the behavioral characteristics of the residents was made for 200 households and included a hypothetical scenario explaining the accident situation and questions such as dwelling place, time demand for evacuation preparation, transportation means for evacuation, sheltering place, and evacuation direction. The microscopic traffic simulation model, CORSIM, was used to simulate the behavior of evacuating vehicles on networks. The results showed that the evacuation time required for total vehicles to move out from EPZ took longer in the daytime than at night in spite that the delay times at intersections were longer at night than in the daytime. This was analyzed due to the differences of the trip generation time distribution. To validate whether the CORSIM model can appropriately simulate the congested traffic phenomena assumable in case of emergency, a benchmark study was conducted at an intersection without an actuated traffic signal near Uljin site during the traffic peak-time in the morning. This study indicated that the predicted output by the CORSIM model was in good agreement with the observed data, satisfying the purpose of this study.

  14. Active versus passive radon monitoring at the Yucca Mountain site

    Energy Technology Data Exchange (ETDEWEB)

    Griffin, M.D. [Science Applications International Corp., Las Vegas, NV (United States)

    1994-12-31

    Federal Regulations have mandated that a baseline assessment for the Yucca Mountain Site be performed. This includes the detection and monitoring of specific radionuclides present at the site. These radionuclides include radon 222, a decay progeny of naturally occurring uranium. Two radon monitoring systems are utilized at the Yucca Mountain site to detect ambient levels of radon. The first is a passive time integrated system, and the second is a continuous radon monitoring (CRM) system.

  15. Predicting activities after stroke : what is clinically relevant?

    NARCIS (Netherlands)

    Kwakkel, G.; Kollen, B. J.

    Knowledge about factors that determine the final outcome after stroke is important for early stroke management, rehabilitation goals, and discharge planning. This narrative review provides an overview of current knowledge about the prediction of activities after stroke. We reviewed the pattern of

  16. GPS-SUMO: a tool for the prediction of sumoylation sites and SUMO-interaction motifs.

    Science.gov (United States)

    Zhao, Qi; Xie, Yubin; Zheng, Yueyuan; Jiang, Shuai; Liu, Wenzhong; Mu, Weiping; Liu, Zexian; Zhao, Yong; Xue, Yu; Ren, Jian

    2014-07-01

    Small ubiquitin-like modifiers (SUMOs) regulate a variety of cellular processes through two distinct mechanisms, including covalent sumoylation and non-covalent SUMO interaction. The complexity of SUMO regulations has greatly hampered the large-scale identification of SUMO substrates or interaction partners on a proteome-wide level. In this work, we developed a new tool called GPS-SUMO for the prediction of both sumoylation sites and SUMO-interaction motifs (SIMs) in proteins. To obtain an accurate performance, a new generation group-based prediction system (GPS) algorithm integrated with Particle Swarm Optimization approach was applied. By critical evaluation and comparison, GPS-SUMO was demonstrated to be substantially superior against other existing tools and methods. With the help of GPS-SUMO, it is now possible to further investigate the relationship between sumoylation and SUMO interaction processes. A web service of GPS-SUMO was implemented in PHP+JavaScript and freely available at http://sumosp.biocuckoo.org.

  17. PreTIS: A Tool to Predict Non-canonical 5’ UTR Translational Initiation Sites in Human and Mouse

    Science.gov (United States)

    Reuter, Kerstin; Helms, Volkhard

    2016-01-01

    Translation of mRNA sequences into proteins typically starts at an AUG triplet. In rare cases, translation may also start at alternative non–AUG codons located in the annotated 5’ UTR which leads to an increased regulatory complexity. Since ribosome profiling detects translational start sites at the nucleotide level, the properties of these start sites can then be used for the statistical evaluation of functional open reading frames. We developed a linear regression approach to predict in–frame and out–of–frame translational start sites within the 5’ UTR from mRNA sequence information together with their translation initiation confidence. Predicted start codons comprise AUG as well as near–cognate codons. The underlying datasets are based on published translational start sites for human HEK293 and mouse embryonic stem cells that were derived by the original authors from ribosome profiling data. The average prediction accuracy of true vs. false start sites for HEK293 cells was 80%. When applied to mouse mRNA sequences, the same model predicted translation initiation sites observed in mouse ES cells with an accuracy of 76%. Moreover, we illustrate the effect of in silico mutations in the flanking sequence context of a start site on the predicted initiation confidence. Our new webservice PreTIS visualizes alternative start sites and their respective ORFs and predicts their ability to initiate translation. Solely, the mRNA sequence is required as input. PreTIS is accessible at http://service.bioinformatik.uni-saarland.de/pretis. PMID:27768687

  18. Predicting enhancer activity and variant impact using gkm-SVM.

    Science.gov (United States)

    Beer, Michael A

    2017-01-25

    We participated in the Critical Assessment of Genome Interpretation eQTL challenge to further test computational models of regulatory variant impact and their association with human disease. Our prediction model is based on a discriminative gapped-kmer SVM (gkm-SVM) trained on genome-wide chromatin accessibility data in the cell type of interest. The comparisons with massively parallel reporter assays (MPRA) in lymphoblasts show that gkm-SVM is among the most accurate prediction models even though all other models used the MPRA data for model training, and gkm-SVM did not. In addition, we compare gkm-SVM with other MPRA datasets and show that gkm-SVM is a reliable predictor of expression and that deltaSVM is a reliable predictor of variant impact in K562 cells and mouse retina. We further show that DHS (DNase-I hypersensitive sites) and ATAC-seq (assay for transposase-accessible chromatin using sequencing) data are equally predictive substrates for training gkm-SVM, and that DHS regions flanked by H3K27Ac and H3K4me1 marks are more predictive than DHS regions alone.

  19. Predicting human brain activity associated with the meanings of nouns.

    Science.gov (United States)

    Mitchell, Tom M; Shinkareva, Svetlana V; Carlson, Andrew; Chang, Kai-Min; Malave, Vicente L; Mason, Robert A; Just, Marcel Adam

    2008-05-30

    The question of how the human brain represents conceptual knowledge has been debated in many scientific fields. Brain imaging studies have shown that different spatial patterns of neural activation are associated with thinking about different semantic categories of pictures and words (for example, tools, buildings, and animals). We present a computational model that predicts the functional magnetic resonance imaging (fMRI) neural activation associated with words for which fMRI data are not yet available. This model is trained with a combination of data from a trillion-word text corpus and observed fMRI data associated with viewing several dozen concrete nouns. Once trained, the model predicts fMRI activation for thousands of other concrete nouns in the text corpus, with highly significant accuracies over the 60 nouns for which we currently have fMRI data.

  20. Prediction of the Human EP1 Receptor Binding Site by Homology Modeling and Molecular Dynamics Simulation.

    Science.gov (United States)

    Zare, Behnoush; Madadkar-Sobhani, Armin; Dastmalchi, Siavoush; Mahmoudian, Masoud

    2011-01-01

    The prostanoid receptor EP1 is a G-protein-coupled receptor (GPCR) known to be involved in a variety of pathological disorders such as pain, fever and inflammation. These receptors are important drug targets, but design of subtype specific agonists and antagonists has been partially hampered by the absence of three-dimensional structures for these receptors. To understand the molecular interactions of the PGE2, an endogen ligand, with the EP1 receptor, a homology model of the human EP1 receptor (hEP1R) with all connecting loops was constructed from the 2.6 Å resolution crystal structure (PDB code: 1L9H) of bovine rhodopsin. The initial model generated by MODELLER was subjected to molecular dynamics simulation to assess quality of the model. Also, a step by step ligand-supported model refinement was performed, including initial docking of PGE2 and iloprost in the putative binding site, followed by several rounds of energy minimizations and molecular dynamics simulations. Docking studies were performed for PGE2 and some other related compounds in the active site of the final hEP1 receptor model. The docking enabled us to identify key molecular interactions supported by the mutagenesis data. Also, the correlation of r(2)=0.81 was observed between the Ki values and the docking scores of 15 prostanoid compounds. The results obtained in this study may provide new insights toward understanding the active site conformation of the hEP1 receptor and can be used for the structure-based design of novel specific ligands.

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

    Science.gov (United States)

    Ott, W R

    1999-05-01

    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 balance model and its application to predicting indoor pollutant concentrations from cigarette smoke and derives the time-averaged version of the model from the basic laws of conservation of mass. A simple table is provided of computed respirable particulate concentrations for any indoor location for which the active smoking count, volume, and concentration decay rate (deposition rate combined with air exchange rate) are known. Using the indoor ventilatory air exchange rate causes slightly higher indoor concentrations and therefore errs on the side of protecting health, since it excludes particle deposition effects, whereas using the observed particle decay rate gives a more accurate prediction of indoor concentrations. This table permits easy comparisons of indoor concentrations with air quality guidelines and indoor standards for different combinations of active smoking counts and air exchange rates. The published literature on mathematical models of environmental tobacco smoke also is reviewed and indicates that these models generally give good agreement between predicted concentrations and actual indoor measurements.

  2. Prediction of protein modification sites of pyrrolidone carboxylic acid using mRMR feature selection and analysis.

    Directory of Open Access Journals (Sweden)

    Lu-Lu Zheng

    Full Text Available Pyrrolidone carboxylic acid (PCA is formed during a common post-translational modification (PTM of extracellular and multi-pass membrane proteins. In this study, we developed a new predictor to predict the modification sites of PCA based on maximum relevance minimum redundancy (mRMR and incremental feature selection (IFS. We incorporated 727 features that belonged to 7 kinds of protein properties to predict the modification sites, including sequence conservation, residual disorder, amino acid factor, secondary structure and solvent accessibility, gain/loss of amino acid during evolution, propensity of amino acid to be conserved at protein-protein interface and protein surface, and deviation of side chain carbon atom number. Among these 727 features, 244 features were selected by mRMR and IFS as the optimized features for the prediction, with which the prediction model achieved a maximum of MCC of 0.7812. Feature analysis showed that all feature types contributed to the modification process. Further site-specific feature analysis showed that the features derived from PCA's surrounding sites contributed more to the determination of PCA sites than other sites. The detailed feature analysis in this paper might provide important clues for understanding the mechanism of the PCA formation and guide relevant experimental validations.

  3. Interactome-wide prediction of protein-protein binding sites reveals effects of protein sequence variation in Arabidopsis thaliana.

    Directory of Open Access Journals (Sweden)

    Felipe Leal Valentim

    Full Text Available The specificity of protein-protein interactions is encoded in those parts of the sequence that compose the binding interface. Therefore, understanding how changes in protein sequence influence interaction specificity, and possibly the phenotype, requires knowing the location of binding sites in those sequences. However, large-scale detection of protein interfaces remains a challenge. Here, we present a sequence- and interactome-based approach to mine interaction motifs from the recently published Arabidopsis thaliana interactome. The resultant proteome-wide predictions are available via www.ab.wur.nl/sliderbio and set the stage for further investigations of protein-protein binding sites. To assess our method, we first show that, by using a priori information calculated from protein sequences, such as evolutionary conservation and residue surface accessibility, we improve the performance of interface prediction compared to using only interactome data. Next, we present evidence for the functional importance of the predicted sites, which are under stronger selective pressure than the rest of protein sequence. We also observe a tendency for compensatory mutations in the binding sites of interacting proteins. Subsequently, we interrogated the interactome data to formulate testable hypotheses for the molecular mechanisms underlying effects of protein sequence mutations. Examples include proteins relevant for various developmental processes. Finally, we observed, by analysing pairs of paralogs, a correlation between functional divergence and sequence divergence in interaction sites. This analysis suggests that large-scale prediction of binding sites can cast light on evolutionary processes that shape protein-protein interaction networks.

  4. Immediate restoration of NobelActive implants placed into fresh extraction sites in the anterior maxilla.

    Science.gov (United States)

    Bell, Christopher; Bell, Robert E

    2014-08-01

    The aim of this study is to compare the success rates of immediately placed and loaded NobelActive implants with the success rate of immediately placed implants that were allowed to osseointigrate prior to loading. The charts of all patients in a private oral surgery office receiving single-unit dental implants in the maxillary anterior region in fresh extraction sites from 2008-2011 were evaluated. All patients receiving NobelActive implants and immediate restorations were included in the study group, while those receiving implants with delayed restorations were included in the control group. Patient records were evaluated for variables such as age, gender, torque values at time of implant placement, smoking habits, use of bisphosphonates, and other significant diseases such as diabetes. The success rate of the study group was 92.9%, whereas the success rate of the control group was 97.6%. This was not statistically significant. Torque values of the failed implants of the study group were similar to those of successful implants in the study group. All implants placed in patients scheduled for immediate loading achieved high torque values and were able to be restored immediately. NobelActive implants were able to obtain high torque values for predictable immediate restoration in fresh extraction sites. Acceptable success rates with excellent soft tissue healing were achieved.

  5. No site unseen: predicting the failure to control problematic Internet use among young adults.

    Science.gov (United States)

    Yamada, Tetsuhiro; Moshier, Samantha J; Otto, Michael W

    2016-11-01

    Problematic Internet use has been associated with the neglect of valued activities such as work, exercise, social activities, and relationships. In the present study, we expanded the understanding of problematic Internet use by identifying an important predictor of the inability to curb Internet use despite the desire to do so. Specifically, in a college student sample reporting a mean of 27.8 h of recreational Internet use in the past week, we investigated the role of distress intolerance (DI)-an individual difference variable that refers to the inability of an individual to tolerate emotional discomfort and to engage in goal-directed behavior when distressed-to predict the failure to meet personal restrictions on Internet use. Consistent with hypotheses, DI emerged as a significant predictor of the failure to meet self-control goals in both bivariate and multivariate models, indicating that DI offers unique prediction of self-control failure with problematic Internet use. Given that DI is a modifiable trait, these results encourage consideration of DI-focused early intervention strategies.

  6. Protein-Protein Interaction Site Predictions with Three-Dimensional Probability Distributions of Interacting Atoms on Protein Surfaces

    Science.gov (United States)

    Chen, Ching-Tai; Peng, Hung-Pin; Jian, Jhih-Wei; Tsai, Keng-Chang; Chang, Jeng-Yih; Yang, Ei-Wen; Chen, Jun-Bo; Ho, Shinn-Ying; Hsu, Wen-Lian; Yang, An-Suei

    2012-01-01

    Protein-protein interactions are key to many biological processes. Computational methodologies devised to predict protein-protein interaction (PPI) sites on protein surfaces are important tools in providing insights into the biological functions of proteins and in developing therapeutics targeting the protein-protein interaction sites. One of the general features of PPI sites is that the core regions from the two interacting protein surfaces are complementary to each other, similar to the interior of proteins in packing density and in the physicochemical nature of the amino acid composition. In this work, we simulated the physicochemical complementarities by constructing three-dimensional probability density maps of non-covalent interacting atoms on the protein surfaces. The interacting probabilities were derived from the interior of known structures. Machine learning algorithms were applied to learn the characteristic patterns of the probability density maps specific to the PPI sites. The trained predictors for PPI sites were cross-validated with the training cases (consisting of 432 proteins) and were tested on an independent dataset (consisting of 142 proteins). The residue-based Matthews correlation coefficient for the independent test set was 0.423; the accuracy, precision, sensitivity, specificity were 0.753, 0.519, 0.677, and 0.779 respectively. The benchmark results indicate that the optimized machine learning models are among the best predictors in identifying PPI sites on protein surfaces. In particular, the PPI site prediction accuracy increases with increasing size of the PPI site and with increasing hydrophobicity in amino acid composition of the PPI interface; the core interface regions are more likely to be recognized with high prediction confidence. The results indicate that the physicochemical complementarity patterns on protein surfaces are important determinants in PPIs, and a substantial portion of the PPI sites can be predicted correctly with

  7. Predictive Active Set Selection Methods for Gaussian Processes

    DEFF Research Database (Denmark)

    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...... 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...... high impact to the classifier decision process while removing those that are less relevant. We introduce two active set rules based on different criteria, the first one prefers a model with interpretable active set parameters whereas the second puts computational complexity first, thus a model...

  8. Monoclonal antibody against the active site of caeruloplasmin and the ELISA system detecting active caeruloplasmin.

    Science.gov (United States)

    Hiyamuta, S; Ito, K

    1994-04-01

    Serum caeruloplasmin deficiency is a characteristic biochemical abnormality found in patients with Wilson's disease, but the mechanism of this disease is unknown. Although the phenylenediamine oxidase activity of serum caeruloplasmin is markedly low in patients with Wilson's disease, mRNA of caeruloplasmin exists to some extent. To investigate the deficiency of caeruloplasmin oxidase activity in Wilson's disease, we generated 14 monoclonal antibodies (MAbs) and selected ID1, which had the strongest reactivity, and ID2, which had neutralizing ability. We also established a system to measure active caeruloplasmin specifically using these MAbs. These MAbs and the system will be useful tools in analyzing the active site of caeruloplasmin in patients with Wilson's disease.

  9. Sequence-specific flexibility organization of splicing flanking sequence and prediction of splice sites in the human genome.

    Science.gov (United States)

    Zuo, Yongchun; Zhang, Pengfei; Liu, Li; Li, Tao; Peng, Yong; Li, Guangpeng; Li, Qianzhong

    2014-09-01

    More and more reported results of nucleosome positioning and histone modifications showed that DNA structure play a well-established role in splicing. In this study, a set of DNA geometric flexibility parameters originated from molecular dynamics (MD) simulations were introduced to discuss the structure organization around splice sites at the DNA level. The obtained profiles of specific flexibility/stiffness around splice sites indicated that the DNA physical-geometry deformation could be used as an alternative way to describe the splicing junction region. In combination with structural flexibility as discriminatory parameter, we developed a hybrid computational model for predicting potential splicing sites. And the better prediction performance was achieved when the benchmark dataset evaluated. Our results showed that the mechanical deformability character of a splice junction is closely correlated with both the splice site strength and structural information in its flanking sequences.

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

    OpenAIRE

    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...

  11. Human population and activities in Forsmark. Site description

    Energy Technology Data Exchange (ETDEWEB)

    Miliander, Sofia; Punakivi, Mari; Kylaekorpi, Lasse; Rydgren, Bernt [SwedPower AB, Stockholm (Sweden)

    2004-12-01

    The Swedish Nuclear Fuel and Waste Management Co (SKB) is in the process of selecting a safe and environmentally acceptable location for a deep repository of radioactive waste. Two alternative locations are under investigation. These are Forsmark, Oesthammars kommun (kommun = municipality) and Simpevarp/Laxemar, Oskarshamns kommun. SKB has expressed the importance of describing the humans and their activities in these areas and therefore has this synthesis concerning the human population in Forsmark been produced.The description is a statistical synthesis, mainly based upon statistical data from SCB (Statistics Sweden) that has been collected, processed and analysed. The statistical data has not been verified through site inspections and interviews. When using statistical data, it is advisable to note that the data becomes more unreliable if the areas are small, with small populations.The data in this description is essential for future evaluations of the impact on the environment and its human population (Environmental Impact Assessments). The data is also important when modelling the potential flows of radio nuclides and calculating the risk of exposure in future safety assessments.The actual area for the study is in this report called 'the Forsmark area', an area of 19.5 km{sup 2} near Forsmark nuclear power plant. The land use in the Forsmark area differs notably from the land use in Uppsala laen (laen = county). Only 0.04% of the total area is developed (built-up) compared to 4.9% in Uppsala laen and only 4% is agricultural land compared to 25% in the county. Furthermore, there are far more forest, wetlands and water areas in the Forsmark area. The forest area represents as much as 72.5% of the total area.The Forsmark area is uninhabited, and its surroundings are very sparsely populated. In 2002, the population density in Forsmark was 1.8 inhabitants per square kilometre, which was 24 times lower than in Uppsala laen. The population density in the

  12. Improving active space telescope wavefront control using predictive thermal modeling

    Science.gov (United States)

    Gersh-Range, Jessica; Perrin, Marshall D.

    2015-01-01

    Active control algorithms for space telescopes are less mature than those for large ground telescopes due to differences in the wavefront control problems. Active wavefront control for space telescopes at L2, such as the James Webb Space Telescope (JWST), requires weighing control costs against the benefits of correcting wavefront perturbations that are a predictable byproduct of the observing schedule, which is known and determined in advance. To improve the control algorithms for these telescopes, we have developed a model that calculates the temperature and wavefront evolution during a hypothetical mission, assuming the dominant wavefront perturbations are due to changes in the spacecraft attitude with respect to the sun. Using this model, we show that the wavefront can be controlled passively by introducing scheduling constraints that limit the allowable attitudes for an observation based on the observation duration and the mean telescope temperature. We also describe the implementation of a predictive controller designed to prevent the wavefront error (WFE) from exceeding a desired threshold. This controller outperforms simpler algorithms even with substantial model error, achieving a lower WFE without requiring significantly more corrections. Consequently, predictive wavefront control based on known spacecraft attitude plans is a promising approach for JWST and other future active space observatories.

  13. Predicting transcription factor binding sites using local over-representation and comparative genomics

    Directory of Open Access Journals (Sweden)

    Touzet Hélène

    2006-08-01

    Full Text Available Abstract Background Identifying cis-regulatory elements is crucial to understanding gene expression, which highlights the importance of the computational detection of overrepresented transcription factor binding sites (TFBSs in coexpressed or coregulated genes. However, this is a challenging problem, especially when considering higher eukaryotic organisms. Results We have developed a method, named TFM-Explorer, that searches for locally overrepresented TFBSs in a set of coregulated genes, which are modeled by profiles provided by a database of position weight matrices. The novelty of the method is that it takes advantage of spatial conservation in the sequence and supports multiple species. The efficiency of the underlying algorithm and its robustness to noise allow weak regulatory signals to be detected in large heterogeneous data sets. Conclusion TFM-Explorer provides an efficient way to predict TFBS overrepresentation in related sequences. Promising results were obtained in a variety of examples in human, mouse, and rat genomes. The software is publicly available at http://bioinfo.lifl.fr/TFM-Explorer.

  14. Multiple repeats of Helicobacter pylori CagA EPIYA-C phosphorylation sites predict risk of gastric ulcer in Iran.

    Science.gov (United States)

    Honarmand-Jahromy, Sahar; Siavoshi, Farideh; Malekzadeh, Reza; Sattari, Taher Nejad; Latifi-Navid, Saeid

    2015-12-01

    Biological activity of Helicobacter pylori oncoprotein CagA is determined by a diversity in the tyrosine phosphorylation motif sites. In the present study, the diversity and the type of the H. pylori CagA EPIYA motifs and their association with gastric ulcer (GU) and duodenal ulcer (DU) in Iranian dyspeptic patients were assessed. PCR amplification, sequencing, and bioinformatic analysis were performed to determine the pattern of CagA EPIYA motifs. Of 168 H. pylori cagA(+) strains, the frequency of ABC was 93.50%, ABCCC 5.40%, ABC + ABCCC 0.6% and ABCC 0.6%. There was no EPIYA-D segment. The ABCCC pattern of EPIYA motif was more frequent in the H. pylori isolates from GU (8/50, 16%) than in those from chronic gastritis (CG) (0/81, 0%) (P = 0). In contrast, The ABC pattern of EPIYA motif was less frequent in the H. pylori isolates from GU (41/50, 82%) than in those from CG (80/81, 98.80%) (Age-sex-adjusted odds ratio (OR) = 0.020, 95% CI = 0.002-0.259; P = 0.003). The distribution of the ABC motif was almost the same in H. pylori isolates from CG (98.80%) and DU diseases (97.30%). There was no significant association between the number of CagA EPIYA-C segment and DU (P > 0.05). We have proposed that CagA from Iranian H. pylori strains were Western type and all strains had active phosphorylation sites. The three EPIYA-C motifs of CagA were more frequently observed in the H. pylori strains from GU; thus it might be an important biomarker for predicting the GU risk in Iran.

  15. Genome wide prediction of HNF4alpha functional binding sites by the use of local and global sequence context.

    Science.gov (United States)

    Kel, Alexander E; Niehof, Monika; Matys, Volker; Zemlin, Rüdiger; Borlak, Jürgen

    2008-01-01

    We report an application of machine learning algorithms that enables prediction of the functional context of transcription factor binding sites in the human genome. We demonstrate that our method allowed de novo identification of hepatic nuclear factor (HNF)4alpha binding sites and significantly improved an overall recognition of faithful HNF4alpha targets. When applied to published findings, an unprecedented high number of false positives were identified. The technique can be applied to any transcription factor.

  16. A new method for splice site prediction based on the sequence patterns of splicing signals and regulatory elements

    Institute of Scientific and Technical Information of China (English)

    SUN ZongXiao; SANG LingJie; JU LiNing; ZHU HuaiQiu

    2008-01-01

    It is of significance for splice site prediction to develop novel algorithms that combine the sequence patterns of regulatory elements such as enhancers and silencers with the patterns of splicing signals. In this paper, a statistical model of splicing signals was built based on the entropy density profile (EDP) method, weight array method (WAM) and κ test; moreover, the model of splicing regulatory elements was developed by an unsupervised self-learning method to detect motifs associated with regulatory elements. With two models incorporated, a multi-level support vector machine (SVM) system was de-vised to perform ab initio prediction for splice sites originating from DNA sequence in eukaryotic ge-home. Results of large scale tests on human genomic splice sites show that the new method achieves a comparative high performance in splice site prediction. The method is demonstrated to be with at least the same level of performance and usually better performance than the existing SpliceScan method based on modeling regulatory elements, and shown to have higher accuracies than the traditional methods with modeling splicing signals such as the GeneSplicer. In particular, the method has evident advantage over splice site prediction for the genes with lower GC content.

  17. Synthesis and characterization of 18F-labeled active site inhibited factor VII (ASIS)

    DEFF Research Database (Denmark)

    Erlandsson, Maria; Nielsen, Carsten Haagen; Jeppesen, Troels Elmer

    2015-01-01

    Activated factor VII blocked in the active site with Phe-Phe-Arg-chloromethyl ketone (active site inhibited factor VII (ASIS)) is a 50-kDa protein that binds with high affinity to its receptor, tissue factor (TF). TF is a transmembrane glycoprotein that plays an important role in, for example, th...

  18. Photoaffinity ligands in the study of cytochrome p450 active site structure.

    Science.gov (United States)

    Gartner, Carlos Augusto

    2003-04-01

    While photoaffinity ligands have been widely used to probe the structures of many receptors and nucleic acid binding proteins, their effective use in the study of cytochrome p450 structure is less established. Nevertheless, significant advances in this field have been made since the technique was first applied to p450cam in 1979. In several cases, especially studies involving p450s of the 1A and 2B families, peptides covalently modified with photoaffinity ligands have been isolated and characterized. Some of these peptides were predicted by molecular modeling to line substrate binding regions of the enzymes. Other data obtained from such studies were more difficult to reconcile with theory. This review addresses the status of photoaffinity labeling as a tool for studying cytochrome p450 structure. In addition, potential future directions in this field are discussed, including the development of heme-directed agents and validation of their effectiveness as photoaffinity ligands using sperm whale myoglobin as a test protein. The potential for hydroxyaromatic compounds to serve as photoactivated probes of active site nucleophiles is also discussed. This class of compounds and its derivatives has long been known in the fields of photochemistry and photophysics to be precursors of reactive radicals and quinone methides that are likely to serve as effective active site probes of the p450s.

  19. Oxygen Activation at the Active Site of a Fungal Lytic Polysaccharide Monooxygenase.

    Science.gov (United States)

    O'Dell, William B; Agarwal, Pratul K; Meilleur, Flora

    2017-01-16

    Lytic polysaccharide monooxygenases have attracted vast attention owing to their abilities to disrupt glycosidic bonds via oxidation instead of hydrolysis and to enhance enzymatic digestion of recalcitrant substrates including chitin and cellulose. We have determined high-resolution X-ray crystal structures of an enzyme from Neurospora crassa in the resting state and of a copper(II) dioxo intermediate complex formed in the absence of substrate. X-ray crystal structures also revealed "pre-bound" molecular oxygen adjacent to the active site. An examination of protonation states enabled by neutron crystallography and density functional theory calculations identified a role for a conserved histidine in promoting oxygen activation. These results provide a new structural description of oxygen activation by substrate free lytic polysaccharide monooxygenases and provide insights that can be extended to reactivity in the enzyme-substrate complex. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  20. Planning for subacute care: predicting demand using acute activity data.

    Science.gov (United States)

    Green, Janette P; McNamee, Jennifer P; Kobel, Conrad; Seraji, Md Habibur R; Lawrence, Suanne J

    2016-04-07

    Objective The aim of the present study was to develop a robust model that uses the concept of 'rehabilitation-sensitive' Diagnosis Related Groups (DRGs) in predicting demand for rehabilitation and geriatric evaluation and management (GEM) care following acute in-patient episodes provided in Australian hospitals.Methods The model was developed using statistical analyses of national datasets, informed by a panel of expert clinicians and jurisdictional advice. Logistic regression analysis was undertaken using acute in-patient data, published national hospital statistics and data from the Australasian Rehabilitation Outcomes Centre.Results The predictive model comprises tables of probabilities that patients will require rehabilitation or GEM care after an acute episode, with columns defined by age group and rows defined by grouped Australian Refined (AR)-DRGs.Conclusions The existing concept of rehabilitation-sensitive DRGs was revised and extended. When applied to national data, the model provided a conservative estimate of 83% of the activity actually provided. An example demonstrates the application of the model for service planning.What is known about the topic? Health service planning is core business for jurisdictions and local areas. With populations ageing and an acknowledgement of the underservicing of subacute care, it is timely to find improved methods of estimating demand for this type of care. Traditionally, age-sex standardised utilisation rates for individual DRGs have been applied to Australian Bureau of Statistics (ABS) population projections to predict the future need for subacute services. Improved predictions became possible when some AR-DRGs were designated 'rehabilitation-sensitive'. This improved methodology has been used in several Australian jurisdictions.What does this paper add? This paper presents a new tool, or model, to predict demand for rehabilitation and GEM services based on in-patient acute activity. In this model, the methodology

  1. Studies on the biotin-binding site of avidin. Lysine residues involved in the active site.

    Science.gov (United States)

    Gitlin, G; Bayer, E A; Wilchek, M

    1987-01-01

    Egg-white avidin was treated with 1-fluoro-2,4-dinitrobenzene. Modification of an average of one lysine residue per avidin subunit caused the complete loss of biotin binding. Tryptic peptides obtained from the 2,4-dinitrophenylated avidin were fractionated by reversed-phase h.p.l.c. Three peptides contained the 2,4-dinitrophenyl group. Amino acid analysis revealed that lysine residues 45, 94 and 111 are modified and probably comprise part of the biotin-binding site. PMID:3109401

  2. Studies on the biotin-binding site of avidin. Lysine residues involved in the active site.

    OpenAIRE

    Gitlin, G; Bayer, E A; Wilchek, M

    1987-01-01

    Egg-white avidin was treated with 1-fluoro-2,4-dinitrobenzene. Modification of an average of one lysine residue per avidin subunit caused the complete loss of biotin binding. Tryptic peptides obtained from the 2,4-dinitrophenylated avidin were fractionated by reversed-phase h.p.l.c. Three peptides contained the 2,4-dinitrophenyl group. Amino acid analysis revealed that lysine residues 45, 94 and 111 are modified and probably comprise part of the biotin-binding site.

  3. Preliminary siting activities for new waste handling facilities at the Idaho National Engineering Laboratory

    Energy Technology Data Exchange (ETDEWEB)

    Taylor, D.D.; Hoskinson, R.L.; Kingsford, C.O.; Ball, L.W.

    1994-09-01

    The Idaho Waste Processing Facility, the Mixed and Low-Level Waste Treatment Facility, and the Mixed and Low-Level Waste Disposal Facility are new waste treatment, storage, and disposal facilities that have been proposed at the Idaho National Engineering Laboratory (INEL). A prime consideration in planning for such facilities is the selection of a site. Since spring of 1992, waste management personnel at the INEL have been involved in activities directed to this end. These activities have resulted in the (a) identification of generic siting criteria, considered applicable to either treatment or disposal facilities for the purpose of preliminary site evaluations and comparisons, (b) selection of six candidate locations for siting,and (c) site-specific characterization of candidate sites relative to selected siting criteria. This report describes the information gathered in the above three categories for the six candidate sites. However, a single, preferred site has not yet been identified. Such a determination requires an overall, composite ranking of the candidate sites, which accounts for the fact that the sites under consideration have different advantages and disadvantages, that no single site is superior to all the others in all the siting criteria, and that the criteria should be assigned different weighing factors depending on whether a site is to host a treatment or a disposal facility. Stakeholder input should now be solicited to help guide the final selection. This input will include (a) siting issues not already identified in the siting, work to date, and (b) relative importances of the individual siting criteria. Final site selection will not be completed until stakeholder input (from the State of Idaho, regulatory agencies, the public, etc.) in the above areas has been obtained and a strategy has been developed to make a composite ranking of all candidate sites that accounts for all the siting criteria.

  4. Spontaneous brain activity predicts learning ability of foreign sounds.

    Science.gov (United States)

    Ventura-Campos, Noelia; Sanjuán, Ana; González, Julio; Palomar-García, María-Ángeles; Rodríguez-Pujadas, Aina; Sebastián-Gallés, Núria; Deco, Gustavo; Ávila, César

    2013-05-29

    Can learning capacity of the human brain be predicted from initial spontaneous functional connectivity (FC) between brain areas involved in a task? We combined task-related functional magnetic resonance imaging (fMRI) and resting-state fMRI (rs-fMRI) before and after training with a Hindi dental-retroflex nonnative contrast. Previous fMRI results were replicated, demonstrating that this learning recruited the left insula/frontal operculum and the left superior parietal lobe, among other areas of the brain. Crucially, resting-state FC (rs-FC) between these two areas at pretraining predicted individual differences in learning outcomes after distributed (Experiment 1) and intensive training (Experiment 2). Furthermore, this rs-FC was reduced at posttraining, a change that may also account for learning. Finally, resting-state network analyses showed that the mechanism underlying this reduction of rs-FC was mainly a transfer in intrinsic activity of the left frontal operculum/anterior insula from the left frontoparietal network to the salience network. Thus, rs-FC may contribute to predict learning ability and to understand how learning modifies the functioning of the brain. The discovery of this correspondence between initial spontaneous brain activity in task-related areas and posttraining performance opens new avenues to find predictors of learning capacities in the brain using task-related fMRI and rs-fMRI combined.

  5. 78 FR 33908 - Commercial Wind Lease Issuance and Site Assessment Activities on the Atlantic Outer Continental...

    Science.gov (United States)

    2013-06-05

    ... renewable energy leases and subsequent site characterization activities (geophysical, geotechnical, archaeological, and biological surveys needed to develop specific project proposals on those leases) in an... from leasing, site characterization, and site assessment in and around the Call Area (76 FR 51391)....

  6. Single-molecule catalysis mapping quantifies site-specific activity and uncovers radial activity gradient on single 2D nanocrystals.

    Science.gov (United States)

    Andoy, Nesha May; Zhou, Xiaochun; Choudhary, Eric; Shen, Hao; Liu, Guokun; Chen, Peng

    2013-02-06

    Shape-controlled metal nanocrystals are a new generation of nanoscale catalysts. Depending on their shapes, these nanocrystals exhibit various surface facets, and the assignments of their surface facets have routinely been used to rationalize or predict their catalytic activity in a variety of chemical transformations. Recently we discovered that for 1-dimensional (1D) nanocrystals (Au nanorods), the catalytic activity is not constant along the same side facets of single nanorods but rather differs significantly and further shows a gradient along its length, which we attributed to an underlying gradient of surface defect density resulting from their linear decay in growth rate during synthesis (Nat. Nanotechnol.2012, 7, 237-241). Here we report that this behavior also extends to 2D nanocrystals, even for a different catalytic reaction. By using super-resolution fluorescence microscopy to map out the locations of catalytic events within individual triangular and hexagonal Au nanoplates in correlation with scanning electron microscopy, we find that the catalytic activity within the flat {111} surface facet of a Au nanoplate exhibits a 2D radial gradient from the center toward the edges. We propose that this activity gradient results from a growth-dependent surface defect distribution. We also quantify the site-specific activity at different regions within a nanoplate: The corner regions have the highest activity, followed by the edge regions and then the flat surface facets. These discoveries highlight the spatial complexity of catalytic activity at the nanoscale as well as the interplay amid nanocrystal growth, morphology, and surface defects in determining nanocatalyst properties.

  7. Exploring the role of water in molecular recognition: predicting protein ligandability using a combinatorial search of surface hydration sites

    Science.gov (United States)

    Vukovic, Sinisa; Brennan, Paul E.; Huggins, David J.

    2016-09-01

    The interaction between any two biological molecules must compete with their interaction with water molecules. This makes water the most important molecule in medicine, as it controls the interactions of every therapeutic with its target. A small molecule binding to a protein is able to recognize a unique binding site on a protein by displacing bound water molecules from specific hydration sites. Quantifying the interactions of these water molecules allows us to estimate the potential of the protein to bind a small molecule. This is referred to as ligandability. In the study, we describe a method to predict ligandability by performing a search of all possible combinations of hydration sites on protein surfaces. We predict ligandability as the summed binding free energy for each of the constituent hydration sites, computed using inhomogeneous fluid solvation theory. We compared the predicted ligandability with the maximum observed binding affinity for 20 proteins in the human bromodomain family. Based on this comparison, it was determined that effective inhibitors have been developed for the majority of bromodomains, in the range from 10 to 100 nM. However, we predict that more potent inhibitors can be developed for the bromodomains BPTF and BRD7 with relative ease, but that further efforts to develop inhibitors for ATAD2 will be extremely challenging. We have also made predictions for the 14 bromodomains with no reported small molecule K d values by isothermal titration calorimetry. The calculations predict that PBRM1(1) will be a challenging target, while others such as TAF1L(2), PBRM1(4) and TAF1(2), should be highly ligandable. As an outcome of this work, we assembled a database of experimental maximal K d that can serve as a community resource assisting medicinal chemistry efforts focused on BRDs. Effective prediction of ligandability would be a very useful tool in the drug discovery process.

  8. Are nest sites actively chosen? Testing a common assumption for three non-resource limited birds

    Science.gov (United States)

    Goodenough, A. E.; Elliot, S. L.; Hart, A. G.

    2009-09-01

    Many widely-accepted ecological concepts are simplified assumptions about complex situations that remain largely untested. One example is the assumption that nest-building species choose nest sites actively when they are not resource limited. This assumption has seen little direct empirical testing: most studies on nest-site selection simply assume that sites are chosen actively (and seek explanations for such behaviour) without considering that sites may be selected randomly. We used 15 years of data from a nestbox scheme in the UK to test the assumption of active nest-site choice in three cavity-nesting bird species that differ in breeding and migratory strategy: blue tit ( Cyanistes caeruleus), great tit ( Parus major) and pied flycatcher ( Ficedula hypoleuca). Nest-site selection was non-random (implying active nest-site choice) for blue and great tits, but not for pied flycatchers. We also considered the relative importance of year-specific and site-specific factors in determining occupation of nest sites. Site-specific factors were more important than year-specific factors for the tit species, while the reverse was true for pied flycatchers. Our results show that nest-site selection, in birds at least, is not always the result of active choice, such that choice should not be assumed automatically in studies of nesting behaviour. We use this example to highlight the need to test key ecological assumptions empirically, and the importance of doing so across taxa rather than for single "model" species.

  9. Early Site Permit Demonstration Program: Recommendations for communication activities and public participation in the Early Site Permit Demonstration Program

    Energy Technology Data Exchange (ETDEWEB)

    1993-01-27

    On October 24, 1992, President Bush signed into law the National Energy Policy Act of 1992. The bill is a sweeping, comprehensive overhaul of the Nation`s energy laws, the first in more than a decade. Among other provisions, the National Energy Policy Act reforms the licensing process for new nuclear power plants by adopting a new approach developed by the US Nuclear Regulatory Commission (NRC) in 1989, and upheld in court in 1992. The NRC 10 CFR Part 52 rule is a three-step process that guarantees public participation at each step. The steps are: early site permit approval; standard design certifications; and, combined construction/operating licenses for nuclear power reactors. Licensing reform increases an organization`s ability to respond to future baseload electricity generation needs with less financial risk for ratepayers and the organization. Costly delays can be avoided because design, safety and siting issues will be resolved before a company starts to build a plant. Specifically, early site permit approval allows for site suitability and acceptability issues to be addressed prior to an organization`s commitment to build a plant. Responsibility for site-specific activities, including communications and public participation, rests with those organizations selected to try out early site approval. This plan has been prepared to assist those companies (referred to as sponsoring organizations) in planning their communications and public involvement programs. It provides research findings, information and recommendations to be used by organizations as a resource and starting point in developing their own plans.

  10. Human population and activities at Simpevarp. Site description

    Energy Technology Data Exchange (ETDEWEB)

    Miliander, Sofia; Punakivi, Mari; Kylaekorpi, Lasse; Rydgren, Bernt [SwedPower AB, Stockholm (Sweden)

    2004-12-01

    The Swedish Nuclear Fuel and Waste Management Co (SKB) is in the process of selecting a safe and environmentally acceptable location for a deep repository of radioactive waste. Two alternative locations are under investigation. These are Forsmark, Oesthammars kommun (kommun = municipality) and Simpevarp/Laxemar, Oskarshamns kommun. SKB has expressed the importance of describing the humans and their activities in these areas and therefore has this synthesis concerning the human population in Forsmark been produced. The description is a statistical synthesis, mainly based upon statistical data from SCB (Statistics Sweden) that has been collected, processed and analysed. The statistical data has not been verified through site inspections and interviews. When using statistical data, it is advisable to note that the data becomes more unreliable if the areas are small, with small populations. The data in this description is essential for future evaluations of the impact on the environment and its human population (environmental impacts assessments). The data is also important when modelling the potential flows of radio nuclides and calculating the risk of exposure in future safety assessments. The actual area for the study is in this report called 'the Simpevarp area', an area of 127.0 km{sup 2} near Oskarshamn nuclear power plant. The land use in Simpevarp area differs notably from the land use in Kalmar laen. The forest area is far more dominating in Simpevarp area than in Kalmar laen and it represents as much as 89% compared to 63% of the total area. Only 4.4% of the area is arable land compared to 11.6% in Kalmar laen and only 0.3% is of other type (wetlands, bare rock, quarries, pites etc) compared to 15.6% in the county. The main observation is that Simpevarp area is a sparsely populated area located in a relatively lightly populated county. In 2002, the population density was 7.4 inhabitants/km{sup 2}, three times lower than in Kalmar laen. The

  11. Human population and activities at Simpevarp. Site description

    Energy Technology Data Exchange (ETDEWEB)

    Miliander, Sofia; Punakivi, Mari; Kylaekorpi, Lasse; Rydgren, Bernt [SwedPower AB, Stockholm (Sweden)

    2004-12-01

    The Swedish Nuclear Fuel and Waste Management Co (SKB) is in the process of selecting a safe and environmentally acceptable location for a deep repository of radioactive waste. Two alternative locations are under investigation. These are Forsmark, Oesthammars kommun (kommun = municipality) and Simpevarp/Laxemar, Oskarshamns kommun. SKB has expressed the importance of describing the humans and their activities in these areas and therefore has this synthesis concerning the human population in Forsmark been produced. The description is a statistical synthesis, mainly based upon statistical data from SCB (Statistics Sweden) that has been collected, processed and analysed. The statistical data has not been verified through site inspections and interviews. When using statistical data, it is advisable to note that the data becomes more unreliable if the areas are small, with small populations. The data in this description is essential for future evaluations of the impact on the environment and its human population (environmental impacts assessments). The data is also important when modelling the potential flows of radio nuclides and calculating the risk of exposure in future safety assessments. The actual area for the study is in this report called 'the Simpevarp area', an area of 127.0 km{sup 2} near Oskarshamn nuclear power plant. The land use in Simpevarp area differs notably from the land use in Kalmar laen. The forest area is far more dominating in Simpevarp area than in Kalmar laen and it represents as much as 89% compared to 63% of the total area. Only 4.4% of the area is arable land compared to 11.6% in Kalmar laen and only 0.3% is of other type (wetlands, bare rock, quarries, pites etc) compared to 15.6% in the county. The main observation is that Simpevarp area is a sparsely populated area located in a relatively lightly populated county. In 2002, the population density was 7.4 inhabitants/km{sup 2}, three times lower than in Kalmar laen. The

  12. Neural network model for the prediction of PM10 daily concentrations in two sites in the Western Mediterranean.

    Science.gov (United States)

    de Gennaro, Gianluigi; Trizio, Livia; Di Gilio, Alessia; Pey, Jorge; Pérez, Noemi; Cusack, Michael; Alastuey, Andrés; Querol, Xavier

    2013-10-01

    An artificial neural network (ANN) was developed and tested to forecast PM10 daily concentration in two contrasted environments in NE Spain, a regional background site (Montseny), and an urban background site (Barcelona-CSIC), which was highly influenced by vehicular emissions. In order to predict 24-h average PM10 concentrations, the artificial neural network previously developed by Caselli et al. (2009) was improved by using hourly PM concentrations and deterministic factors such as a Saharan dust alert. In particular, the model input data for prediction were the hourly PM10 concentrations 1-day in advance, local meteorological data and information about air masses origin. The forecasted performance indexes for both sites were calculated and they showed better results for the regional background site in Montseny (R(2)=0.86, SI=0.75) than for urban site in Barcelona (R(2)=0.73, SI=0.58), influenced by local and sometimes unexpected sources. Moreover, a sensitivity analysis conducted to understand the importance of the different variables included among the input data, showed that local meteorology and air masses origin are key factors in the model forecasts. This result explains the reason for the improvement of ANN's forecasting performance at the Montseny site with respect to the Barcelona site. Moreover, the artificial neural network developed in this work could prove useful to predict PM10 concentrations, especially, at regional background sites such as those on the Mediterranean Basin which are primarily affected by long-range transports. Hence, the artificial neural network presented here could be a powerful tool for obtaining real time information on air quality status and could aid stakeholders in their development of cost-effective control strategies.

  13. Neural activity predicts attitude change in cognitive dissonance.

    Science.gov (United States)

    van Veen, Vincent; Krug, Marie K; Schooler, Jonathan W; Carter, Cameron S

    2009-11-01

    When our actions conflict with our prior attitudes, we often change our attitudes to be more consistent with our actions. This phenomenon, known as cognitive dissonance, is considered to be one of the most influential theories in psychology. However, the neural basis of this phenomenon is unknown. Using a Solomon four-group design, we scanned participants with functional MRI while they argued that the uncomfortable scanner environment was nevertheless a pleasant experience. We found that cognitive dissonance engaged the dorsal anterior cingulate cortex and anterior insula; furthermore, we found that the activation of these regions tightly predicted participants' subsequent attitude change. These effects were not observed in a control group. Our findings elucidate the neural representation of cognitive dissonance, and support the role of the anterior cingulate cortex in detecting cognitive conflict and the neural prediction of attitude change.

  14. MetalDetector v2.0: predicting the geometry of metal binding sites from protein sequence

    OpenAIRE

    Passerini, A; Lippi, M.; P. Frasconi

    2011-01-01

    MetalDetector identifies CYS and HIS involved in transition metal protein binding sites, starting from sequence alone. A major new feature of release 2.0 is the ability to predict which residues are jointly involved in the coordination of the same metal ion. The server is available at http://metaldetector.dsi.unifi.it/v2.0/.

  15. Improving model predictions for RNA interference activities that use support vector machine regression by combining and filtering features

    Directory of Open Access Journals (Sweden)

    Peek Andrew S

    2007-06-01

    Full Text Available Abstract Background RNA interference (RNAi is a naturally occurring phenomenon that results in the suppression of a target RNA sequence utilizing a variety of possible methods and pathways. To dissect the factors that result in effective siRNA sequences a regression kernel Support Vector Machine (SVM approach was used to quantitatively model RNA interference activities. Results Eight overall feature mapping methods were compared in their abilities to build SVM regression models that predict published siRNA activities. The primary factors in predictive SVM models are position specific nucleotide compositions. The secondary factors are position independent sequence motifs (N-grams and guide strand to passenger strand sequence thermodynamics. Finally, the factors that are least contributory but are still predictive of efficacy are measures of intramolecular guide strand secondary structure and target strand secondary structure. Of these, the site of the 5' most base of the guide strand is the most informative. Conclusion The capacity of specific feature mapping methods and their ability to build predictive models of RNAi activity suggests a relative biological importance of these features. Some feature mapping methods are more informative in building predictive models and overall t-test filtering provides a method to remove some noisy features or make comparisons among datasets. Together, these features can yield predictive SVM regression models with increased predictive accuracy between predicted and observed activities both within datasets by cross validation, and between independently collected RNAi activity datasets. Feature filtering to remove features should be approached carefully in that it is possible to reduce feature set size without substantially reducing predictive models, but the features retained in the candidate models become increasingly distinct. Software to perform feature prediction and SVM training and testing on nucleic acid

  16. The ACTIVE cognitive training trial and predicted medical expenditures

    Directory of Open Access Journals (Sweden)

    Smith David M

    2009-06-01

    Full Text Available Abstract Background Health care expenditures for older adults are disproportionately high and increasing at both the individual and population levels. We evaluated the effects of the three cognitive training interventions (memory, reasoning, or speed of processing in the ACTIVE study on changes in predicted medical care expenditures. Methods ACTIVE was a multisite randomized controlled trial of older adults (≥ 65. Five-year follow-up data were available for 1,804 of the 2,802 participants. Propensity score weighting was used to adjust for potential attrition bias. Changes in predicted annualmedical expenditures were calculated at the first and fifth annual follow-up assessments using a new method for translating functional status scores. Multiple linear regression methods were used in this cost-offset analysis. Results At one and five years post-training, annual predicted expenditures declinedby $223 (p = .024 and $128 (p = .309, respectively, in the speed of processing treatment group, but there were no statistically significant changes in the memory or reasoning treatment groups compared to the no-contact control group at either period. Statistical adjustment for age, race, education, MMSE scores, ADL and IADL performance scores, EPT scores, chronic condition counts, and the SF-36 PCS and MCS scores at baseline did not alter the one-year ($244; p = .012 or five-year ($143; p = .250 expenditure declines in the speed of processing treatment group. Conclusion The speed of processing intervention significantly reduced subsequent annual predicted medical care expenditures at the one-year post-baseline comparison, but annual savings were no longer statistically significant at the five-year post-baseline comparison.

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

    Science.gov (United States)

    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.

  18. V S30, slope, H 800 and f 0: performance of various site-condition proxies in reducing ground-motion aleatory variability and predicting nonlinear site response

    Science.gov (United States)

    Derras, Boumédiène; Bard, Pierre-Yves; Cotton, Fabrice

    2017-09-01

    The aim of this paper is to investigate the ability of various site-condition proxies (SCPs) to reduce ground-motion aleatory variability and evaluate how SCPs capture nonlinearity site effects. The SCPs used here are time-averaged shear-wave velocity in the top 30 m ( V S30), the topographical slope (slope), the fundamental resonance frequency ( f 0) and the depth beyond which V s exceeds 800 m/s ( H 800). We considered first the performance of each SCP taken alone and then the combined performance of the 6 SCP pairs [ V S30- f 0], [ V S30- H 800], [ f 0-slope], [ H 800-slope], [ V S30-slope] and [ f 0- H 800]. This analysis is performed using a neural network approach including a random effect applied on a KiK-net subset for derivation of ground-motion prediction equations setting the relationship between various ground-motion parameters such as peak ground acceleration, peak ground velocity and pseudo-spectral acceleration PSA ( T), and M w, R JB, focal depth and SCPs. While the choice of SCP is found to have almost no impact on the median ground-motion prediction, it does impact the level of aleatory uncertainty. V S30 is found to perform the best of single proxies at short periods ( T < 0.6 s), while f 0 and H 800 perform better at longer periods; considering SCP pairs leads to significant improvements, with particular emphasis on [ V S30- H 800] and [ f 0-slope] pairs. The results also indicate significant nonlinearity on the site terms for soft sites and that the most relevant loading parameter for characterising nonlinear site response is the "stiff" spectral ordinate at the considered period.[Figure not available: see fulltext.

  19. Baseline brain activity predicts response to neuromodulatory pain treatment.

    Science.gov (United States)

    Jensen, Mark P; Sherlin, Leslie H; Fregni, Felipe; Gianas, Ann; Howe, Jon D; Hakimian, Shahin

    2014-12-01

    The objective of this study was to examine the associations between baseline electroencephalogram (EEG)-assessed brain oscillations and subsequent response to four neuromodulatory treatments. Based on available research, we hypothesized that baseline theta oscillations would prospectively predict response to hypnotic analgesia. Analyses involving other oscillations and the other treatments (meditation, neurofeedback, and both active and sham transcranial direct current stimulation) were viewed as exploratory, given the lack of previous research examining brain oscillations as predictors of response to these other treatments. Randomized controlled study of single sessions of four neuromodulatory pain treatments and a control procedure. Thirty individuals with spinal cord injury and chronic pain had their EEG recorded before each session of four active treatments (hypnosis, meditation, EEG biofeedback, transcranial direct current stimulation) and a control procedure (sham transcranial direct stimulation). As hypothesized, more presession theta power was associated with greater response to hypnotic analgesia. In exploratory analyses, we found that less baseline alpha power predicted pain reduction with meditation. The findings support the idea that different patients respond to different pain treatments and that between-person treatment response differences are related to brain states as measured by EEG. The results have implications for the possibility of enhancing pain treatment response by either 1) better patient/treatment matching or 2) influencing brain activity before treatment is initiated in order to prepare patients to respond. Research is needed to replicate and confirm the findings in additional samples of individuals with chronic pain. Wiley Periodicals, Inc.

  20. Building gene expression signatures indicative of transcription factor activation to predict AOP modulation

    Science.gov (United States)

    Building gene expression signatures indicative of transcription factor activation to predict AOP modulation Adverse outcome pathways (AOPs) are a framework for predicting quantitative relationships between molecular initiatin...

  1. Protein-lipid interactions: correlation of a predictive algorithm for lipid-binding sites with three-dimensional structural data

    Directory of Open Access Journals (Sweden)

    Goldmann Wolfgang H

    2006-03-01

    Full Text Available Abstract Background Over the past decade our laboratory has focused on understanding how soluble cytoskeleton-associated proteins interact with membranes and other lipid aggregates. Many protein domains mediating specific cell membrane interactions appear by fluorescence microscopy and other precision techniques to be partially inserted into the lipid bilayer. It is unclear whether these protein-lipid-interactions are dependent on shared protein motifs or unique regional physiochemistry, or are due to more global characteristics of the protein. Results We have developed a novel computational program that predicts a protein's lipid-binding site(s from primary sequence data. Hydrophobic labeling, Fourier transform infrared spectroscopy (FTIR, film balance, T-jump, CD spectroscopy and calorimetry experiments confirm that the interfaces predicted for several key cytoskeletal proteins (alpha-actinin, Arp2, CapZ, talin and vinculin partially insert into lipid aggregates. The validity of these predictions is supported by an analysis of the available three-dimensional structural data. The lipid interfaces predicted by our algorithm generally contain energetically favorable secondary structures (e.g., an amphipathic alpha-helix flanked by a flexible hinge or loop region, are solvent-exposed in the intact protein, and possess favorable local or global electrostatic properties. Conclusion At present, there are few reliable methods to determine the region of a protein that mediates biologically important interactions with lipids or lipid aggregates. Our matrix-based algorithm predicts lipid interaction sites that are consistent with the available biochemical and structural data. To determine whether these sites are indeed correctly identified, and whether use of the algorithm can be safely extended to other classes of proteins, will require further mapping of these sites, including genetic manipulation and/or targeted crystallography.

  2. Dynamic neural networks for real-time water level predictions of sewerage systems-covering gauged and ungauged sites

    Directory of Open Access Journals (Sweden)

    Yen-Ming Chiang

    2010-07-01

    Full Text Available In this research, we propose recurrent neural networks (RNNs to build a relationship between rainfalls and water level patterns of an urban sewerage system based on historical torrential rain/storm events. The RNN allows signals to propagate in both forward and backward directions, which offers the network dynamic memories. Besides, the information at the current time-step with a feedback operation can yield a time-delay unit that provides internal input information at the next time-step to effectively deal with time-varying systems. The RNN is implemented at both gauged and ungauged sites for 5-, 10-, 15-, and 20-min-ahead water level predictions. The results show that the RNN is capable of learning the nonlinear sewerage system and producing satisfactory predictions at the gauged sites. Concerning the ungauged sites, there are no historical data of water level to support prediction. In order to overcome such problem, a set of synthetic data, generated from a storm water management model (SWMM under cautious verification process of applicability based on the data from nearby gauging stations, are introduced as the learning target to the training procedure of the RNN and moreover evaluating the performance of the RNN at the ungauged sites. The results demonstrate that the potential role of the SWMM coupled with nearby rainfall and water level information can be of great use in enhancing the capability of the RNN at the ungauged sites. Hence we can conclude that the RNN is an effective and suitable model for successfully predicting the water levels at both gauged and ungauged sites in urban sewerage systems.

  3. Conserved residues in RF-NH₂ receptor models identify predicted contact sites in ligand-receptor binding.

    Science.gov (United States)

    Bass, C; Katanski, C; Maynard, B; Zurro, I; Mariane, E; Matta, M; Loi, M; Melis, V; Capponi, V; Muroni, P; Setzu, M; Nichols, R

    2014-03-01

    Peptides in the RF-NH2 family are grouped together based on an amidated dipeptide C terminus and signal through G-protein coupled receptors (GPCRs) to influence diverse physiological functions. By determining the mechanisms underlying RF-NH2 signaling targets can be identified to modulate physiological activity; yet, how RF-NH2 peptides interact with GPCRs is relatively unexplored. We predicted conserved residues played a role in Drosophila melanogaster RF-NH2 ligand-receptor interactions. In this study D. melanogaster rhodopsin-like family A peptide GPCRs alignments identified eight conserved residues unique to RF-NH2 receptors. Three of these residues were in extra-cellular loops of modeled RF-NH2 receptors and four in transmembrane helices oriented into a ligand binding pocket to allow contact with a peptide. The eighth residue was unavailable for interaction; yet its conservation suggested it played another role. A novel hydrophobic region representative of RF-NH2 receptors was also discovered. The presence of rhodopsin-like family A GPCR structural motifs including a toggle switch indicated RF-NH2s signal classically; however, some features of the DMS receptors were distinct from other RF-NH2 GPCRs. Additionally, differences in RF-NH2 receptor structures which bind the same peptide explained ligand specificity. Our novel results predicted conserved residues as RF-NH2 ligand-receptor contact sites and identified unique and classic structural features. These discoveries will aid antagonist design to modulate RF-NH2 signaling. Copyright © 2013. Published by Elsevier Inc.

  4. 76 FR 24871 - Reimbursement for Costs of Remedial Action at Active Uranium and Thorium Processing Sites

    Science.gov (United States)

    2011-05-03

    ... Reimbursement for Costs of Remedial Action at Active Uranium and Thorium Processing Sites AGENCY: Department of... from eligible active uranium and thorium processing site licensees for reimbursement under Title X of...). Title X requires DOE to reimburse eligible uranium and thorium licensees for certain costs...

  5. 76 FR 30696 - Reimbursement for Costs of Remedial Action at Active Uranium and Thorium Processing Sites

    Science.gov (United States)

    2011-05-26

    ... Reimbursement for Costs of Remedial Action at Active Uranium and Thorium Processing Sites AGENCY: Department of... eligible active uranium and thorium processing site licensees for reimbursement under Title X of the Energy... requires DOE to reimburse eligible uranium and thorium licensees for certain costs of...

  6. Identification of Active Edge Sites for Electrochemical H2 Evolution from MoS2 Nanocatalysts

    DEFF Research Database (Denmark)

    Jaramillo, Thomas; Jørgensen, Kristina Pilt; Bonde, Jacob;

    2007-01-01

    The identification of the active sites in heterogeneous catalysis requires a combination of surface sensitive methods and reactivity studies. We determined the active site for hydrogen evolution, a reaction catalyzed by precious metals, on nanoparticulate molybdenum disulfide (MoS2) by atomically...

  7. Symmetrical 1-pyrrolidineacetamide showing anti-HIV activity through a new binding site on HIV-1 integrase

    Institute of Scientific and Technical Information of China (English)

    Li DU; Ya-xue ZHAO; Liu-meng YANG; Yong-tang ZHENG; Yun TANG; Xu SHEN; Hua-liang JIANG

    2008-01-01

    Aim:To characterize the functional and pharmacological features of a symmetrical 1-pyrrolidineacetamide,N,N'-(methylene-di-4,1-phenylene) bis-1-pyrrolidineacetamide,as a new anti-HIV compound which could competitively inhibit HIV-1 integrase (IN) binding to viral DNA.Methods:A surface plasma resonance (SPR)-based competitive assay was employed to determine the compound's inhibitory activity,and the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide cell assay was used to qualify the antiviral activity.The potential binding sites were predicted by molecular modeling and determined by site-directed mutagenesis and a SPR binding assay.Results:l-pyrrolidineacetamide,N,N'-(methylene-di-4,1-phenylene) bis-1-pyrrolidineacetamide could competitively inhibit IN binding to viral DNA with a 50% inhibitory concentration (IC50) value of 7.29±0.68 μmol/L as investigated by SPR-based investigation.Another antiretroviral activity assay showed that this compound exhibited inhibition against HⅣ-Ⅰ(ⅢB) replication with a 50% effective concentration (EC50) value of 40.54 μmol/L in C8166 cells,and cytotoxicity with a cytotoxic concentration value of 173.84 μmol/L in mock-infected C8166 cells.Molecular docking predicted 3 potential residues as 1-pyrrolidineacetamide,N,N'-(methylene-di-4,1-phenylene)bis-1-pyrrolidineacetamide binding sites.The importance of 3 key amino acid residues (Lys103,Lys173,and Thr174) involved in the binding was further identified by site-directed mutagenesis and a SPR binding assay.Conclusion:This present work identified a new anti-HIV compound through a new IN-binding site which is expected to supply new potential drug-binding site information for HIV-1 integrase inhibitor discovery and development.

  8. Active Tectonic Research for Seismic Safety Evaluation of Long-Line Engineering Sites in China

    Institute of Scientific and Technical Information of China (English)

    Ran Yongkang; Chen Lichun

    2005-01-01

    Long-line engineering sites usually have to pass through active tectonics, so the research of active tectonics is of great importance to seismic safety evaluation of this sort of site. In the paper, basing on the summarization and analysis of the requirements for seismic safety evaluation of long-line engineering site and the status quo of active tectonics research, we propose the focal points of active tectonics research for seismic safety evaluation of long-line engineering sites, including the research contents, technical targets and routes, and the submission of the achievements, etc. Finally, we make a preliminary analysis and discussion about the problems existing in the present-day active tectonics research for seismic safety evaluation of long-line engineering sites.

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

    Institute of Scientific and Technical Information of China (English)

    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.

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

    Science.gov (United States)

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

    2004-08-15

    To predict wild human heme oxygenase-1 (whHO-1) and hHO-1 His25Ala mutant (delta hHO-1) structures, to clone and express them and analyze their activities. Swiss-PdbViewer and Antheprot 5.0 were used for the prediction of structure diversity and physical-chemical changes between wild and mutant hHO-1. hHO-1 His25Ala mutant cDNA was constructed by site-directed mutagenesis in two plasmids of E. coli DH5alpha. Expression products were purified by ammonium sulphate precipitation and Q-Sepharose Fast Flow column chromatography, and their activities were measured. rHO-1 had the structure of a helical fold with the heme sandwiched between heme-heme oxygenase-1 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 delta hHO-1 was reduced 91.21% after mutation compared with whHO-1. Proximal His25 ligand is crucial for normal hHO-1 catalytic activity. delta hHO-1 is deactivated by mutation but keeps the same binding site as whHO-1. delta hHO-1 might be a potential inhibitor of whHO-1 for preventing neonatal hyperbilirubinemia.

  11. In Situ Probing of the Active Site Geometry of Ultrathin Nanowires for the Oxygen Reduction Reaction.

    Science.gov (United States)

    Liu, Haiqing; An, Wei; Li, Yuanyuan; Frenkel, Anatoly I; Sasaki, Kotaro; Koenigsmann, Christopher; Su, Dong; Anderson, Rachel M; Crooks, Richard M; Adzic, Radoslav R; Liu, Ping; Wong, Stanislaus S

    2015-10-07

    To create truly effective electrocatalysts for the cathodic reaction governing proton exchange membrane fuel cells (PEMFC), namely the oxygen reduction reaction (ORR), necessitates an accurate and detailed structural understanding of these electrocatalysts, especially at the nanoscale, and to precisely correlate that structure with demonstrable performance enhancement. To address this key issue, we have combined and interwoven theoretical calculations with experimental, spectroscopic observations in order to acquire useful structural insights into the active site geometry with implications for designing optimized nanoscale electrocatalysts with rationally predicted properties. Specifically, we have probed ultrathin (∼2 nm) core-shell Pt∼Pd9Au nanowires, which have been previously shown to be excellent candidates for ORR in terms of both activity and long-term stability, from the complementary perspectives of both DFT calculations and X-ray absorption spectroscopy (XAS). The combination and correlation of data from both experimental and theoretical studies has revealed for the first time that the catalytically active structure of our ternary nanowires can actually be ascribed to a PtAu∼Pd configuration, comprising a PtAu binary shell and a pure inner Pd core. Moreover, we have plausibly attributed the resulting structure to a specific synthesis step, namely the Cu underpotential deposition (UPD) followed by galvanic replacement with Pt. Hence, the fundamental insights gained into the performance of our ultrathin nanowires from our demonstrated approach will likely guide future directed efforts aimed at broadly improving upon the durability and stability of nanoscale electrocatalysts in general.

  12. Studies on the biotin-binding site of avidin. Tryptophan residues involved in the active site.

    OpenAIRE

    Gitlin, G; Bayer, E A; Wilchek, M

    1988-01-01

    Egg-white avidin was modified with the tryptophan-specific reagent 2-hydroxy-5-nitrobenzyl bromide. The complete loss of biotin-binding activity was achieved upon modification of an average of one tryptophan residue per avidin subunit. The identity of the modified residues was determined by isolating the relevant tryptic and chymotryptic peptides from CNBr-cleaved avidin fragments. The results demonstrate that Trp-70 and Trp-110 are modified in approximately equivalent proportions. It is beli...

  13. Blogs and Social Network Sites as Activity Systems: Exploring Adult Informal Learning Process through Activity Theory Framework

    Science.gov (United States)

    Heo, Gyeong Mi; Lee, Romee

    2013-01-01

    This paper uses an Activity Theory framework to explore adult user activities and informal learning processes as reflected in their blogs and social network sites (SNS). Using the assumption that a web-based space is an activity system in which learning occurs, typical features of the components were investigated and each activity system then…

  14. Prediction of suspended-sediment concentrations at selected sites in the Fountain Creek watershed, Colorado, 2008-09

    Science.gov (United States)

    Stogner, Robert W.; Nelson, Jonathan M.; McDonald, Richard R.; Kinzel, Paul J.; Mau, David P.

    2013-01-01

    In 2008, the U.S. Geological Survey (USGS), in cooperation with Pikes Peak Area Council of Governments, Colorado Water Conservation Board, Colorado Springs City Engineering, and the Lower Arkansas Valley Water Conservancy District, began a small-scale pilot study to evaluate the effectiveness of the use of a computational model of streamflow and suspended-sediment transport for predicting suspended-sediment concentrations and loads in the Fountain Creek watershed in Colorado. Increased erosion and sedimentation damage have been identified by the Fountain Creek Watershed Plan as key problems within the watershed. A recommendation in the Fountain Creek Watershed plan for management of the basin is to establish measurable criteria to determine if progress in reducing erosion and sedimentation damage is being made. The major objective of this study was to test a computational method to predict local suspended-sediment loads at two sites with different geomorphic characteristics in order to evaluate the feasibility of using such an approach to predict local suspended-sediment loads throughout the entire watershed. Detailed topographic surveys, particle-size data, and suspended-sediment samples were collected at two gaged sites: Monument Creek above Woodmen Road at Colorado Springs, Colorado (USGS gage 07103970), and Sand Creek above mouth at Colorado Springs, Colorado (USGS gage 07105600). These data were used to construct three-dimensional computational models of relatively short channel reaches at each site. The streamflow component of these models predicted a spatially distributed field of water-surface elevation, water velocity, and bed shear stress for a range of stream discharges. Using the model predictions, along with measured particle sizes, the sediment-transport component of the model predicted the suspended-sediment concentration throughout the reach of interest. These computed concentrations were used with predicted flow patterns and channel morphology to

  15. An epigenetic signature in peripheral blood predicts active ovarian cancer.

    Directory of Open Access Journals (Sweden)

    Andrew E Teschendorff

    Full Text Available BACKGROUND: Recent studies have shown that DNA methylation (DNAm markers in peripheral blood may hold promise as diagnostic or early detection/risk markers for epithelial cancers. However, to date no study has evaluated the diagnostic and predictive potential of such markers in a large case control cohort and on a genome-wide basis. PRINCIPAL FINDINGS: By performing genome-wide DNAm profiling of a large ovarian cancer case control cohort, we here demonstrate that active ovarian cancer has a significant impact on the DNAm pattern in peripheral blood. Specifically, by measuring the methylation levels of over 27,000 CpGs in blood cells from 148 healthy individuals and 113 age-matched pre-treatment ovarian cancer cases, we derive a DNAm signature that can predict the presence of active ovarian cancer in blind test sets with an AUC of 0.8 (95% CI (0.74-0.87. We further validate our findings in another independent set of 122 post-treatment cases (AUC = 0.76 (0.72-0.81. In addition, we provide evidence for a significant number of candidate risk or early detection markers for ovarian cancer. Furthermore, by comparing the pattern of methylation with gene expression data from major blood cell types, we here demonstrate that age and cancer elicit common changes in the composition of peripheral blood, with a myeloid skewing that increases with age and which is further aggravated in the presence of ovarian cancer. Finally, we show that most cancer and age associated methylation variability is found at CpGs located outside of CpG islands. SIGNIFICANCE: Our results underscore the potential of DNAm profiling in peripheral blood as a tool for detection or risk-prediction of epithelial cancers, and warrants further in-depth and higher CpG coverage studies to further elucidate this role.

  16. Solar Activity Predictions Based on Solar Dynamo Theories

    Science.gov (United States)

    Schatten, Kenneth H.

    2009-05-01

    We review solar activity prediction methods, statistical, precursor, and recently the Dikpati and the Choudhury groups’ use of numerical flux-dynamo methods. Outlining various methods, we compare precursor techniques with weather forecasting. Precursors involve events prior to a solar cycle. First started by the Russian geomagnetician Ohl, and then Brown and Williams; the Earth's field variations near solar minimum was used to predict the next solar cycle, with a correlation of 0.95. From the standpoint of causality, as well as energetically, these relationships were somewhat bizarre. One index used was the "number of anomalous quiet days,” an antiquated, subjective index. Scientific progress cannot be made without some suspension of disbelief; otherwise old paradigms become tautologies. So, with youthful naïveté, Svalgaard, Scherrer, Wilcox and I viewed the results through rose-colored glasses and pressed ahead searching for understanding. We eventually fumbled our way to explaining how the Sun could broadcast the state of its internal dynamo to Earth. We noted one key aspect of the Babcock-Leighton Flux Dynamo theory: the polar field at the end of a cycle serves as a seed for the next cycle's growth. Near solar minimum this field usually bathes the Earth, and thereby affects geomagnetic indices then. We found support by examining 8 previous solar cycles. Using our solar precursor technique we successfully predicted cycles 21, 22 and 23 using WSO and MWSO data. Pesnell and I improved the method using a SODA (SOlar Dynamo Amplitude) Index. In 2005, nearing cycle 23's minimum, Svalgaard and I noted an unusually weak polar field, and forecasted a small cycle 24. We discuss future advances: the flux-dynamo methods. As far as future solar activity, I shall let the Sun decide; it will do so anyhow.

  17. Predictive Analysis of Landslide Activity Using Remote Sensing Data

    Science.gov (United States)

    Markuzon, N.; Regan, J.; Slesnick, C.

    2012-12-01

    Landslides are historically one of the most damaging geohazard phenomena in terms of death tolls and socio-economic losses. Therefore, understanding the underlying causes of landslides and how environmental phenomena affect their frequency and severity is of critical importance. Of specific importance for mitigating future damage is increasing our understanding of how climate change will affect landslide severity, occurrence rates, and damage. We are developing data driven models aimed at predicting landslide activity. The models learn multi-dimensional weather and geophysical patterns associated with historical landslides and estimate location-dependent probabilities for landslides under current or future weather and geophysical conditions. Our approach uses machine learning algorithms capable of determining non-linear associations between dependent variables and landslide occurrence without requiring detailed knowledge of geomorphology. Our primary goal in year one of the project is to evaluate the predictive capabilities of data mining models in application to landslide activity, and to analyze if the approach will discover previously unknown variables and/or relationships important to landslide occurrence, frequency or severity. The models include remote sensing and ground-based data, including weather, landcover, slope, elevation and drainage information as well as urbanization data. The historical landslide dataset we used to build our preliminary models was compiled from City of Seattle landslide files, United States Geological Survey reports, newspaper articles, and a verified subset of the Seattle Landslide Database that consists of all reported landslides within Seattle, WA, between 1948 and 1999. Most of the landslides analyzed to-date are shallow. Using statistical analysis and unsupervised clustering methods we have thus far identified subsets of weather conditions that lead to a significantly higher landslide probability, and have developed

  18. Factors predicting surgical site infection after posterior lumbar surgery: A multicenter retrospective study.

    Science.gov (United States)

    Wang, Tao; Wang, Hui; Yang, Da-Long; Jiang, Li-Qiang; Zhang, Li-Jun; Ding, Wen-Yuan

    2017-02-01

    This is a retrospective study.The purpose of this study is to explore incidence and risk factors for surgical site infection (SSI) after posterior lumbar surgery.SSI is a common complication after posterior lumbar surgery, bringing mental and physical pain and prolonging hospital stay. However, predisposing factors, as reported less, remain controversial.Patients who underwent posterior lumbar surgery at 3 centers between 2006 and 2016 were included. The possible factors include 3 aspects: demographic variables-age, sex, body mass index (BMI), waist-to-hip radio (WHR), hypertension, diabetes, heart disease, smoking, drinking, steroidal injection, surgical time between June and September, preoperative shower; blood test variables-white blood cell (WBC), neutrophil, red blood cell (RBC), hemoglobin (Hb), total protein (TP), albumin, albumin/globulin (A/G), C-reactive protein (CRP), procalcitonin (PCT), erythrocyte sedimentation rate (ESR) and surgical related variables-operation time, blood loss, operative level, instrumentation, incision length. Factors related with SSI were also performed by multivariate analysis.The prevalence of SSI was 3.00% (267 cases of 8879) had a postoperative wound infection. There were significant difference in WHR (0.92 vs 0.83), WBC (4.31 vs 6.69), TP (58.7 vs 65.2), albumin (36.9 vs 43.2), CRP (2.01 vs 0.57), PCT (0.097 vs 0.067), operation time (217.9 vs 195.7), blood loss (997.1 vs 915.3) and operative level (3.05 vs 2.45) and incision length (24.1 vs 20.0) between SSI group and non-SSI group. >60 years old, female, BMI 30.0, diabetes, male smoking, preoperative steroidal injection, surgical time between June and September, no preoperative shower, instrumentation surgery were risk factors for SSI after posterior lumbar surgery.Many factors, >60 years old, female, BMI, WHR, diabetes, male smoking, preoperative steroidal injection, surgical time between June and September, preoperative shower, WBC, TP, albumin, CRP, PCT, operation time

  19. Role of active site conformational changes in photocycle activation of the AppA BLUF photoreceptor.

    Science.gov (United States)

    Goyal, Puja; Hammes-Schiffer, Sharon

    2017-02-14

    Blue light using flavin adenine dinucleotide (BLUF) proteins are essential for the light regulation of a variety of physiologically important processes and serve as a prototype for photoinduced proton-coupled electron transfer (PCET). Free-energy simulations elucidate the active site conformations in the AppA (activation of photopigment and puc expression) BLUF domain before and following photoexcitation. The free-energy profile for interconversion between conformations with either Trp104 or Met106 closer to the flavin, denoted Trpin/Metout and Trpout/Metin, reveals that both conformations are sampled on the ground state, with the former thermodynamically favorable by ∼3 kcal/mol. These results are consistent with the experimental observation of both conformations. To analyze the proton relay from Tyr21 to the flavin via Gln63, the free-energy profiles for Gln63 rotation were calculated on the ground state, the locally excited state of the flavin, and the charge-transfer state associated with electron transfer from Tyr21 to the flavin. For the Trpin/Metout conformation, the hydrogen-bonding pattern conducive to the proton relay is not thermodynamically favorable on the ground state but becomes more favorable, corresponding to approximately half of the configurations sampled, on the locally excited state. The calculated energy gaps between the locally excited and charge-transfer states suggest that electron transfer from Tyr21 to the flavin is more facile for configurations conducive to proton transfer. When the active site conformation is not conducive to PCET from Tyr21, Trp104 can directly compete with Tyr21 for electron transfer to the flavin through a nonproductive pathway, impeding the signaling efficiency.

  20. Assessment of activation products in the Savannah River Site environment

    Energy Technology Data Exchange (ETDEWEB)

    Carlton, W.H.; Denham, M.

    1996-07-01

    This document assesses the impact of radioactive activation products released from SRS facilities since the first reactor became operational late in 1953. The isotopes reported here are those whose release resulted in the highest dose to people living near SRS: {sup 32}P, {sup 51}Cr, {sup 60}C, and {sup 65}Zn. Release pathways, emission control features, and annual releases to the aqueous and atmospheric environments are discussed. No single incident has resulted in a major acute release of activation products to the environment. The releases were the result of normal operations of the reactors and separations facilities. Releases declined over the years as better controls were established and production was reduced. The overall radiological impact of SRS activation product atmospheric releases from 1954 through 1994 on the offsite maximally exposed individual can be characterized by a total dose of 0.76 mrem. During the same period, such an individual received a total dose of 14,400 mrem from non-SRS sources of ionizing radiation present in the environment. SRS activation product aqueous releases between 1954 and 1994 resulted in a total dose of 54 mrem to the offsite maximally exposed individual. The impact of SRS activation product releases on offsite populations also has been evaluated.

  1. Characterization of an Active Thermal Erosion Site, Caribou Creek, Alaska

    Science.gov (United States)

    Busey, R.; Bolton, W. R.; Cherry, J. E.; Hinzman, L. D.

    2013-12-01

    The goal of this project is to estimate volume loss of soil over time from this site, provide parameterizations on erodibility of ice rich permafrost and serve as a baseline for future landscape evolution simulations. Located in the zone of discontinuous permafrost, the interior region of Alaska (USA) is home to a large quantity of warm, unstable permafrost that is both high in ice content and has soil temperatures near the freezing point. Much of this permafrost maintains a frozen state despite the general warming air temperature trend in the region due to the presence of a thick insulating organic mat and a dense root network in the upper sub-surface of the soil column. At a rapidly evolving thermo-erosion site, located within the Caribou-Poker Creeks Research Watershed (part of the Bonanza Creek LTER) near Chatanika, Alaska (N65.140, W147.570), the protective organic layer and associated plants were disturbed by an adjacent traditional use trail and the shifting of a groundwater spring. These triggers have led to rapid geomorphological change on the landscape as the soil thaws and sediment is transported into the creek at the valley bottom. Since 2006 (approximately the time of initiation), the thermal erosion has grown to 170 meters length, 3 meters max depth, and 15 meters maximum width. This research combines several data sets: DGPS survey, imagery from an extremely low altitude pole-based remote sensing (3 to 5 meters above ground level), and imagery from an Unmanned Aerial System (UAS) at about 60m altitude.

  2. Using Geoarchaeology to Predict the Presence of Offshore Sites in Southern California (Invited)

    Science.gov (United States)

    Hildebrand, J.; York, A.

    2013-12-01

    During the late Pleistocene and early Holocene, the continental shelves off southern California were exposed and available for occupation by prehistoric peoples. Subsequent sealevel rise and marine transgression of the continental shelf resulted in both submergence and potentially reworking of site materials. A model has been developed and tested for continental shelf site locations, using geoarchaeological methods including seismic reflection imaging, coring, and invertebrate fossil identification. In this model, such factors as topography, rate of sea level rise, sediment thickness and context of deposition are all applied to the assessment of potential for site presence and preservation. The most desirable locations for site preservation are found in offshore valley floors and flanks, whereas adjacent uplands are prone to site erosion. Cultural materials from the La Jollan Complex were recovered from two separate offshore sites by large-scale dredging operations. Transgression at these sites occurred prior to about 8000 B.P.. The relation of these cultural materials to the offshore site location model will be discussed.

  3. Site directed mutagenesis of amino acid residues at the active site of mouse aldehyde oxidase AOX1.

    Directory of Open Access Journals (Sweden)

    Silvia Schumann

    Full Text Available Mouse aldehyde oxidase (mAOX1 forms a homodimer and belongs to the xanthine oxidase family of molybdoenzymes which are characterized by an essential equatorial sulfur ligand coordinated to the molybdenum atom. In general, mammalian AOs are characterized by broad substrate specificity and an yet obscure physiological function. To define the physiological substrates and the enzymatic characteristics of mAOX1, we established a system for the heterologous expression of the enzyme in Escherichia coli. The recombinant protein showed spectral features and a range of substrate specificity similar to the native protein purified from mouse liver. The EPR data of recombinant mAOX1 were similar to those of AO from rabbit liver, but differed from the homologous xanthine oxidoreductase enzymes. Site-directed mutagenesis of amino acids Val806, Met884 and Glu1265 at the active site resulted in a drastic decrease in the oxidation of aldehydes with no increase in the oxidation of purine substrates. The double mutant V806E/M884R and the single mutant E1265Q were catalytically inactive enzymes regardless of the aldehyde or purine substrates tested. Our results show that only Glu1265 is essential for the catalytic activity by initiating the base-catalyzed mechanism of substrate oxidation. In addition, it is concluded that the substrate specificity of molybdo-flavoenzymes is more complex and not only defined by the three characterized amino acids in the active site.

  4. Prediction of antibacterial activity from physicochemical properties of antimicrobial peptides.

    Directory of Open Access Journals (Sweden)

    Manuel N Melo

    Full Text Available Consensus is gathering that antimicrobial peptides that exert their antibacterial action at the membrane level must reach a local concentration threshold to become active. Studies of peptide interaction with model membranes do identify such disruptive thresholds but demonstrations of the possible correlation of these with the in vivo onset of activity have only recently been proposed. In addition, such thresholds observed in model membranes occur at local peptide concentrations close to full membrane coverage. In this work we fully develop an interaction model of antimicrobial peptides with biological membranes; by exploring the consequences of the underlying partition formalism we arrive at a relationship that provides antibacterial activity prediction from two biophysical parameters: the affinity of the peptide to the membrane and the critical bound peptide to lipid ratio. A straightforward and robust method to implement this relationship, with potential application to high-throughput screening approaches, is presented and tested. In addition, disruptive thresholds in model membranes and the onset of antibacterial peptide activity are shown to occur over the same range of locally bound peptide concentrations (10 to 100 mM, which conciliates the two types of observations.

  5. [Model for predicting childhood obesity from diet and physical activity].

    Science.gov (United States)

    Larrosa-Haro, Alfredo; González-Pérez, Guillermo Julián; Vásquez-Garibay, Edgar Manuel; Romero-Velarde, Enrique; Chávez-Palencia, Clío; Salazar-Preciado, Laura Leticia; Lizárraga-Corona, Elizabeth

    2014-01-01

    If obesity results from the interaction of variables that involve the subject and his environment, the alternatives to face the problem could be very diverse. The objective of this study was to seek for the best predictive model of childhood obesity from energy ingestion, dietary habits and physical activity. Case control study of 99 obese and 100 healthy weight children (Center for Diseases Control criteria). Energy ingestion was estimated by means of a 24-hour recall, dietary and physical activity habits by validated questionnaires. A logistic regression analysis was made. Variables independently associated to obesity were higher energy ingestion; lower frequency in mealtimes; having the afternoon lunch outside home; higher frequency of consumption of fat, junk food and sweetened beverages; lower time of moderate physical activity at school and at home; and increased time for homework and watching TV. The variables included in the regression model were energy intake; frequency of ingestion of fat, junk foods and sweetened beverages; and physical activity at home and at school. The diversity of associated variables underlines the complexity and multi-causal condition of obesity.

  6. Active site densities, oxygen activation and adsorbed reactive oxygen in alcohol activation on npAu catalysts

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Lu-Cun [Department of Chemistry and Chemical Biology; Harvard University; Cambridge, USA; Friend, C. M. [Department of Chemistry and Chemical Biology; Harvard University; Cambridge, USA; School of Engineering and Applied Sciences; Harvard University; Fushimi, Rebecca [Parks College of Engineering, Aviation and Technology; Saint Louis University; Saint Louis, USA; The Langmuir Research Institute; Saint Louis; Madix, Robert J. [School of Engineering and Applied Sciences; Harvard University; Cambridge, USA

    2016-01-01

    The activation of molecular O2as well as the reactivity of adsorbed oxygen species is of central importance in aerobic selective oxidation chemistry on Au-based catalysts. Herein, we address the issue of O2activation on unsupported nanoporous gold (npAu) catalysts by applying a transient pressure technique, a temporal analysis of products (TAP) reactor, to measure the saturation coverage of atomic oxygen, its collisional dissociation probability, the activation barrier for O2dissociation, and the facility with which adsorbed O species activate methanol, the initial step in the catalytic cycle of esterification. The results from these experiments indicate that molecular O2dissociation is associated with surface silver, that the density of reactive sites is quite low, that adsorbed oxygen atoms do not spill over from the sites of activation onto the surrounding surface, and that methanol reacts quite facilely with the adsorbed oxygen atoms. In addition, the O species from O2dissociation exhibits reactivity for the selective oxidation of methanol but not for CO. The TAP experiments also revealed that the surface of the npAu catalyst is saturated with adsorbed O under steady state reaction conditions, at least for the pulse reaction.

  7. In Vitro Analysis of Predicted DNA-Binding Sites for the Stl Repressor of the Staphylococcus aureus SaPIBov1 Pathogenicity Island.

    Directory of Open Access Journals (Sweden)

    Veronika Papp-Kádár

    Full Text Available The regulation model of the Staphylococcus aureus pathogenicity island SaPIbov1 transfer was recently reported. The repressor protein Stl obstructs the expression of SaPI proteins Str and Xis, latter which is responsible for mobilization initiation. Upon Φ11 phage infection of S. aureus. phage dUTPase activates the SaPI transfer via Stl-dUTPase complex formation. Our aim was to predict the binding sites for the Stl repressor within the S. aureus pathogenicity island DNA sequence. We found that Stl was capable to bind to three 23-mer oligonucleotides, two of those constituting sequence segments in the stl-str, while the other corresponding to sequence segment within the str-xis intergenic region. Within these oligonucleotides, mutational analysis revealed that the predicted binding site for the Stl protein exists as a palindromic segment in both intergenic locations. The palindromes are built as 6-mer repeat sequences involved in Stl binding. The 6-mer repeats are separated by a 5 oligonucleotides long, nonspecific sequence. Future examination of the interaction between Stl and its binding sites in vivo will provide a molecular explanation for the mechanisms of gene repression and gene activation exerted simultaneously by the Stl protein in regulating transfer of the SaPIbov1 pathogenicity island in S. aureus.

  8. Monte carlo simulation of base and nucleotide excision repair of clustered DNA damage sites. II. Comparisons of model predictions to measured data.

    Science.gov (United States)

    Semenenko, V A; Stewart, R D

    2005-08-01

    Clustered damage sites other than double-strand breaks (DSBs) have the potential to contribute to deleterious effects of ionizing radiation, such as cell killing and mutagenesis. In the companion article (Semenenko et al., Radiat. Res. 164, 180-193, 2005), a general Monte Carlo framework to simulate key steps in the base and nucleotide excision repair of DNA damage other than DSBs is proposed. In this article, model predictions are compared to measured data for selected low-and high-LET radiations. The Monte Carlo model reproduces experimental observations for the formation of enzymatic DSBs in Escherichia coli and cells of two Chinese hamster cell lines (V79 and xrs5). Comparisons of model predictions with experimental values for low-LET radiation suggest that an inhibition of DNA backbone incision at the sites of base damage by opposing strand breaks is active over longer distances between the damaged base and the strand break in hamster cells (8 bp) compared to E. coli (3 bp). Model estimates for the induction of point mutations in the human hypoxanthine guanine phosphoribosyl transferase (HPRT) gene by ionizing radiation are of the same order of magnitude as the measured mutation frequencies. Trends in the mutation frequency for low- and high-LET radiation are predicted correctly by the model. The agreement between selected experimental data sets and simulation results provides some confidence in postulated mechanisms for excision repair of DNA damage other than DSBs and suggests that the proposed Monte Carlo scheme is useful for predicting repair outcomes.

  9. Unusual adsorption site behavior in PCN-14 metal-organic framework predicted from Monte Carlo simulation.

    Science.gov (United States)

    Lucena, Sebastião M P; Mileo, Paulo G M; Silvino, Pedro F G; Cavalcante, Célio L

    2011-12-01

    The adsorption equilibrium of methane in PCN-14 was simulated by the Monte Carlo technique in the grand canonical ensemble. A new force field was proposed for the methane/PCN-14 system, and the temperature dependence of the molecular siting was investigated. A detailed study of the statistics of the center of mass and potential energy showed a surprising site behavior with no energy barriers between weak and strong sites, allowing open metal sites to guide methane molecules to other neighboring sites. Moreover, this study showed that a model assuming weakly adsorbing open metal clusters in PCN-14, densely populated only at low temperatures (below 150 K), can explain published experimental data. These results also explain previously observed discrepancies between neutron diffraction experiments and Monte Carlo simulations.

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

    Directory of Open Access Journals (Sweden)

    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

  11. The landscape degradation in the mining sites with suspended activity

    Directory of Open Access Journals (Sweden)

    Anca IONCE

    2009-08-01

    Full Text Available The extracting industry, through its extraction activities, of shipping the ores, of breaking the ores, of preparing the practical substances, of stowing the useless rock, of transporting the practical substances, etc. might modify the area’s relief and the quality of ground, of thesurface waters and of the air. Suceava County has an old tradition of mining, where the results of this activity are visible, especially the visual point of view, and where not taking certain measures of ecological remediation will emphasize the disappointing image of the landscape within the areas of mining activity performing.The predominant mountainous landscape, in which mining activities have been held, is being affected also by the abandoned industrial and administrative buildings, in an advanced degradation state.The hydrographic system, very rich in mining areas, has its water quality affected by the acid rock drainage- phenomenon which appeared in many mining waste deposits.

  12. Location and activity specific site-management for military locations

    NARCIS (Netherlands)

    Maring, L.; Hulst, M. van; Meuken, D.

    2009-01-01

    pace is limited in the Netherlands and military activities, that may cause nuisance or environmental hazards, should therefore be considered and evaluated during the use of military locations. The last few years TNO and Deltares have worked on a research program on environmental effects due to milit

  13. Encroachment of Human Activity on Sea Turtle Nesting Sites

    Science.gov (United States)

    Ziskin, D.; Aubrecht, C.; Elvidge, C.; Tuttle, B.; Baugh, K.; Ghosh, T.

    2008-12-01

    The encroachment of anthropogenic lighting on sea turtle nesting sites poses a serious threat to the survival of these animals [Nicholas, 2001]. This danger is quantified by combining two established data sets. The first is the Nighttime Lights data produced by the NOAA National Geophysical Data Center [Elvidge et al., 1997]. The second is the Marine Turtle Database produced by the World Conservation Monitoring Centre (WCMC). The technique used to quantify the threat of encroachment is an adaptation of the method described in Aubrecht et al. [2008], which analyzes the stress on coral reef systems by proximity to nighttime lights near the shore. Nighttime lights near beaches have both a direct impact on turtle reproductive success since they disorient hatchlings when they mistake land-based lights for the sky-lit surf [Lorne and Salmon, 2007] and the lights are also a proxy for other anthropogenic threats. The identification of turtle nesting sites with high rates of encroachment will hopefully steer conservation efforts to mitigate their effects [Witherington, 1999]. Aubrecht, C, CD Elvidge, T Longcore, C Rich, J Safran, A Strong, M Eakin, KE Baugh, BT Tuttle, AT Howard, EH Erwin, 2008, A global inventory of coral reef stressors based on satellite observed nighttime lights, Geocarto International, London, England: Taylor and Francis. In press. Elvidge, CD, KE Baugh, EA Kihn, HW Kroehl, ER Davis, 1997, Mapping City Lights with Nighttime Data from the DMSP Operational Linescan System, Photogrammatic Engineering and Remote Sensing, 63:6, pp. 727-734. Lorne, JK, M Salmon, 2007, Effects of exposure to artificial lighting on orientation of hatchling sea turtles on the beach and in the ocean, Endangered Species Research, Vol. 3: 23-30. Nicholas, M, 2001, Light Pollution and Marine Turtle Hatchlings: The Straw that Breaks the Camel's Back?, George Wright Forum, 18:4, p77-82. Witherington, BE, 1999, Reducing Threats To Nesting Habitat, Research and Management Techniques for

  14. ProBiS-CHARMMing: Web Interface for Prediction and Optimization of Ligands in Protein Binding Sites.

    Science.gov (United States)

    Konc, Janez; Miller, Benjamin T; Štular, Tanja; Lešnik, Samo; Woodcock, H Lee; Brooks, Bernard R; Janežič, Dušanka

    2015-11-23

    Proteins often exist only as apo structures (unligated) in the Protein Data Bank, with their corresponding holo structures (with ligands) unavailable. However, apoproteins may not represent the amino-acid residue arrangement upon ligand binding well, which is especially problematic for molecular docking. We developed the ProBiS-CHARMMing web interface by connecting the ProBiS ( http://probis.cmm.ki.si ) and CHARMMing ( http://www.charmming.org ) web servers into one functional unit that enables prediction of protein-ligand complexes and allows for their geometry optimization and interaction energy calculation. The ProBiS web server predicts ligands (small compounds, proteins, nucleic acids, and single-atom ligands) that may bind to a query protein. This is achieved by comparing its surface structure against a nonredundant database of protein structures and finding those that have binding sites similar to that of the query protein. Existing ligands found in the similar binding sites are then transposed to the query according to predictions from ProBiS. The CHARMMing web server enables, among other things, minimization and potential energy calculation for a wide variety of biomolecular systems, and it is used here to optimize the geometry of the predicted protein-ligand complex structures using the CHARMM force field and to calculate their interaction energies with the corresponding query proteins. We show how ProBiS-CHARMMing can be used to predict ligands and their poses for a particular binding site, and minimize the predicted protein-ligand complexes to obtain representations of holoproteins. The ProBiS-CHARMMing web interface is freely available for academic users at http://probis.nih.gov.

  15. Predictability during active break phases of Indian summer monsoon in an ensemble prediction system using climate forecast system

    Science.gov (United States)

    Abhilash, S.; Sahai, A. K.; Pattnaik, S.; De, S.

    2013-08-01

    This study examines the phase dependant temporal and spatial error evolution and prediction of active break spells of Indian summer monsoon rainfall in an ensemble prediction system (EPS) on a pentad time scale using climate forecast system (CFS). The EPS system shows systematic wet bias (overestimation) over west coast over the Arabian Sea and Myanmar coast and dry bias (underestimation) over Indian land mass even at pentad 1 lead and these biases consistently increase up to 4 pentad lead and saturate thereafter. Irrespective of the phases of the monsoon, the lower bound of predictability is 2 pentads, while upper bound of predictability for initial conditions starting from active phase saturates at 3 pentads and for break and transition phases predictability error saturates at a later stage at about 5 pentad. Initial conditions started from transition phase shows higher potential predictability followed by break phase and then active phase.

  16. Recent and past musical activity predicts cognitive aging variability: direct comparison with general lifestyle activities.

    Science.gov (United States)

    Hanna-Pladdy, Brenda; Gajewski, Byron

    2012-01-01

    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 non-musical cognitive abilities to allow for compensation of age-related cognitive declines. However, because of the relationship between engagement in general 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 controlled for general activity level in evaluating cognition between musicians and nomusicians. Also, the timing of engagement (age of acquisition, past versus recent) was assessed in predictive models of successful cognitive aging. Seventy age and education matched older musicians (>10 years) and non-musicians (ages 59-80) were evaluated on neuropsychological tests and general lifestyle activities. Musicians scored higher on tests of phonemic fluency, verbal working memory, verbal immediate recall, visuospatial judgment, and motor dexterity, but did not differ in other general leisure activities. Partition analyses were conducted on significant cognitive measures to determine aspects of musical training predictive of enhanced cognition. The first partition analysis revealed education best predicted visuospatial functions in musicians, followed by recent musical engagement which offset low education. In the second partition analysis, early age of musical acquisition (memory in musicians, while analyses for other measures were not predictive. Recent and past musical activity, but not general lifestyle activities, predicted variability

  17. Lipolytic activity from bacteria prospected in polluted portuary sites

    Directory of Open Access Journals (Sweden)

    Kaori Levy Fonseca

    2014-06-01

    This study demonstrates that these TBT resistant isolates have, at the same time, the capacity to produce enzymes with a large biotechnological potential but, nevertheless, their relationship is not well understood, representing a novel approach. It is expected for these organisms to produce highly biotechnological relevant biocatalysts, due to their severe adaptations (Suehiro et al., 2007. The fully characterization of these lipases, mostly for F3 with elevated lipolytic activity exhibited, presents also a future challenge.

  18. Molecular Basis for Enzymatic Sulfite Oxidation -- HOW THREE CONSERVED ACTIVE SITE RESIDUES SHAPE ENZYME ACTIVITY

    Energy Technology Data Exchange (ETDEWEB)

    Bailey, Susan; Rapson, Trevor; Johnson-Winters, Kayunta; Astashkin, Andrei; Enemark, John; Kappler, Ulrike

    2008-11-10

    Sulfite dehydrogenases (SDHs) catalyze the oxidation and detoxification of sulfite to sulfate, a reaction critical to all forms of life. Sulfite-oxidizing enzymes contain three conserved active site amino acids (Arg-55, His-57, and Tyr-236) that are crucial for catalytic competency. Here we have studied the kinetic and structural effects of two novel and one previously reported substitution (R55M, H57A, Y236F) in these residues on SDH catalysis. Both Arg-55 and His-57 were found to have key roles in substrate binding. An R55M substitution increased Km(sulfite)(app) by 2-3 orders of magnitude, whereas His-57 was required for maintaining a high substrate affinity at low pH when the imidazole ring is fully protonated. This effect may be mediated by interactions of His-57 with Arg-55 that stabilize the position of the Arg-55 side chain or, alternatively, may reflect changes in the protonation state of sulfite. Unlike what is seen for SDHWT and SDHY236F, the catalytic turnover rates of SDHR55M and SDHH57A are relatively insensitive to pH (~;;60 and 200 s-1, respectively). On the structural level, striking kinetic effects appeared to correlate with disorder (in SDHH57A and SDHY236F) or absence of Arg-55 (SDHR55M), suggesting that Arg-55 and the hydrogen bonding interactions it engages in are crucial for substrate binding and catalysis. The structure of SDHR55M has sulfate bound at the active site, a fact that coincides with a significant increase in the inhibitory effect of sulfate in SDHR55M. Thus, Arg-55 also appears to be involved in enabling discrimination between the substrate and product in SDH.

  19. Identification of inhibitors against the potential ligandable sites in the active cholera toxin.

    Science.gov (United States)

    Gangopadhyay, Aditi; Datta, Abhijit

    2015-04-01

    The active cholera toxin responsible for the massive loss of water and ions in cholera patients via its ADP ribosylation activity is a heterodimer of the A1 subunit of the bacterial holotoxin and the human cytosolic ARF6 (ADP Ribosylation Factor 6). The active toxin is a potential target for the design of inhibitors against cholera. In this study we identified the potential ligandable sites of the active cholera toxin which can serve as binding sites for drug-like molecules. By employing an energy-based approach to identify ligand binding sites, and comparison with the results of computational solvent mapping, we identified two potential ligandable sites in the active toxin which can be targeted during structure-based drug design against cholera. Based on the probe affinities of the identified ligandable regions, docking-based virtual screening was employed to identify probable inhibitors against these sites. Several indole-based alkaloids and phosphates showed strong interactions to the important residues of the ligandable region at the A1 active site. On the other hand, 26 top scoring hits were identified against the ligandable region at the A1 ARF6 interface which showed strong hydrogen bonding interactions, including guanidines, phosphates, Leucopterin and Aristolochic acid VIa. This study has important implications in the application of hybrid structure-based and ligand-based methods against the identified ligandable sites using the identified inhibitors as reference ligands, for drug design against the active cholera toxin.

  20. Revealing divergent evolution, identifying circular permutations and detecting active-sites by protein structure comparison

    Directory of Open Access Journals (Sweden)

    Wang Yong

    2006-09-01

    Full Text Available Abstract Background Protein structure comparison is one of the most important problems in computational biology and plays a key role in protein structure prediction, fold family classification, motif finding, phylogenetic tree reconstruction and protein docking. Results We propose a novel method to compare the protein structures in an accurate and efficient manner. Such a method can be used to not only reveal divergent evolution, but also identify circular permutations and further detect active-sites. Specifically, we define the structure alignment as a multi-objective optimization problem, i.e., maximizing the number of aligned atoms and minimizing their root mean square distance. By controlling a single distance-related parameter, theoretically we can obtain a variety of optimal alignments corresponding to different optimal matching patterns, i.e., from a large matching portion to a small matching portion. The number of variables in our algorithm increases with the number of atoms of protein pairs in almost a linear manner. In addition to solid theoretical background, numerical experiments demonstrated significant improvement of our approach over the existing methods in terms of quality and efficiency. In particular, we show that divergent evolution, circular permutations and active-sites (or structural motifs can be identified by our method. The software SAMO is available upon request from the authors, or from http://zhangroup.aporc.org/bioinfo/samo/ and http://intelligent.eic.osaka-sandai.ac.jp/chenen/samo.htm. Conclusion A novel formulation is proposed to accurately align protein structures in the framework of multi-objective optimization, based on a sequence order-independent strategy. A fast and accurate algorithm based on the bipartite matching algorithm is developed by exploiting the special features. Convergence of computation is shown in experiments and is also theoretically proven.

  1. Cooperative activation of cardiac transcription through myocardin bridging of paired MEF2 sites

    Energy Technology Data Exchange (ETDEWEB)

    Anderson, Courtney M. [Univ. of California, San Francisco, CA (United States). Cardiovascular Research Inst.; Hu, Jianxin [Univ. of California, San Francisco, CA (United States). Cardiovascular Research Inst.; Thomas, Reuben [Univ. of California, San Francisco, CA (United States). Gladstone Inst.; Gainous, T. Blair [Univ. of California, San Francisco, CA (United States). Cardiovascular Research Inst.; Celona, Barbara [Univ. of California, San Francisco, CA (United States). Cardiovascular Research Inst.; Sinha, Tanvi [Univ. of California, San Francisco, CA (United States). Cardiovascular Research Inst.; Dickel, Diane E. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Genomics Division; Heidt, Analeah B. [Univ. of California, San Francisco, CA (United States). Cardiovascular Research Inst.; Xu, Shan-Mei [Univ. of California, San Francisco, CA (United States). Cardiovascular Research Inst.; Bruneau, Benoit G. [Univ. of California, San Francisco, CA (United States). Cardiovascular Research Inst.; Univ. of California, San Francisco, CA (United States). Gladstone Inst.; Pollard, Katherine S. [Univ. of California, San Francisco, CA (United States). Gladstone Inst.; Pennacchio, Len A. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Genomics Division; Black, Brian L. [Univ. of California, San Francisco, CA (United States). Cardiovascular Research Inst.; Univ. of California, San Francisco, CA (United States). Dept. of

    2017-03-28

    Enhancers frequently contain multiple binding sites for the same transcription factor. These homotypic binding sites often exhibit synergy, whereby the transcriptional output from two or more binding sites is greater than the sum of the contributions of the individual binding sites alone. Although this phenomenon is frequently observed, the mechanistic basis for homotypic binding site synergy is poorly understood. Here in this paper, we identify a bona fide cardiac-specific Prkaa2 enhancer that is synergistically activated by homotypic MEF2 binding sites. We show that two MEF2 sites in the enhancer function cooperatively due to bridging of the MEF2C-bound sites by the SAP domain-containing co-activator protein myocardin, and we show that paired sites buffer the enhancer from integration site-dependent effects on transcription in vivo. Paired MEF2 sites are prevalent in cardiac enhancers, suggesting that this might be a common mechanism underlying synergy in the control of cardiac gene expression in vivo.

  2. Active Site Metal Occupancy and Cyclic Di-GMP Phosphodiesterase Activity of Thermotoga maritima HD-GYP.

    Science.gov (United States)

    Miner, Kyle D; Kurtz, Donald M

    2016-02-16

    HD-GYPs make up a subclass of the metal-dependent HD phosphohydrolase superfamily and catalyze conversion of cyclic di(3',5')-guanosine monophosphate (c-di-GMP) to 5'-phosphoguanylyl-(3'→5')-guanosine (pGpG) and GMP. Until now, the only reported crystal structure of an HD-GYP that also exhibits c-di-GMP phosphodiesterase activity contains a His/carboxylate ligated triiron active site. However, other structural and phylogenetic correlations indicate that some HD-GYPs contain dimetal active sites. Here we provide evidence that an HD-GYP c-di-GMP phosphodiesterase, TM0186, from Thermotoga maritima can accommodate both di- and trimetal active sites. We show that an as-isolated iron-containing TM0186 has an oxo/carboxylato-bridged diferric site, and that the reduced (diferrous) form is necessary and sufficient to catalyze conversion of c-di-GMP to pGpG, but that conversion of pGpG to GMP requires more than two metals per active site. Similar c-di-GMP phosphodiesterase activities were obtained with divalent iron or manganese. On the basis of activity correlations with several putative metal ligand residue variants and molecular dynamics simulations, we propose that TM0186 can accommodate both di- and trimetal active sites. Our results also suggest that a Glu residue conserved in a subset of HD-GYPs is required for formation of the trimetal site and can also serve as a labile ligand to the dimetal site. Given the anaerobic growth requirement of T. maritima, we suggest that this HD-GYP can function in vivo with either divalent iron or manganese occupying di- and trimetal sites.

  3. Decreased dopamine activity predicts relapse in methamphetamine abusers

    Energy Technology Data Exchange (ETDEWEB)

    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.

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

    Science.gov (United States)

    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. Effects of the cofactor binding sites on the activities of secondary alcohol dehydrogenase (SADH).

    Science.gov (United States)

    Wang, Tao; Chen, Xiangjun; Han, Jun; Ma, Sichun; Wang, Jianmei; Li, Xufeng; Zhang, Hui; Liu, Zhibin; Yang, Yi

    2016-07-01

    SADHs from Thermoanaerobacter ethanolicus are enzymes that, together with various cofactors, catalyze the reversible reduction of carbonyl compounds to their corresponding alcohols. To explore how cofactors bind to SADH, TeSADH was cloned in this study, and Ser(199) and Arg(200) were replaced by Tyr and Asp, respectively. Both sites were expected to be inside or adjacent to the cofactor-binding domain according to computational a prediction. Analysis of TeSADH activities revealed that the enzymatic efficiency (kcat/Km) of the S199Y mutant was noticeably enhanced using by NADH, NADPH as cofactors, and similar with that of wild-type using by NADP(+), NAD(+). Conversely, the activity of the R200D mutant significantly decreased with all cofactors. Furthermore, in yeast, the S199Y mutant substantially elevated the ethanol concentration compared with the wild type. Molecular dynamics simulation results indicated the H-bonding network between TeSADH and the cofactors was stronger for the S199Y mutant and the binding energy was simultaneously increased. Moreover, the fluorescence results indicated the S199Y mutant exhibited an increased preference for NAD(P)H, binding with NAD(P)H more compactly compared with wild type. Copyright © 2016 Elsevier B.V. All rights reserved.

  6. Structure analysis reveals the flexibility of the ADAMTS-5 active site

    Energy Technology Data Exchange (ETDEWEB)

    Shieh, Huey-Sheng; Tomasselli, Alfredo G.; Mathis, Karl J.; Schnute, Mark E.; Woodard, Scott S.; Caspers, Nicole; Williams, Jennifer M.; Kiefer, James R.; Munie, Grace; Wittwer, Arthur; Malfait, Anne-Marie; Tortorella, Micky D. (Pfizer)

    2012-03-02

    A ((1S,2R)-2-hydroxy-2,3-dihydro-1H-inden-1-yl) succinamide derivative (here referred to as Compound 12) shows significant activity toward many matrix metalloproteinases (MMPs), including MMP-2, MMP-8, MMP-9, and MMP-13. Modeling studies had predicted that this compound would not bind to ADAMTS-5 (a disintegrin and metalloproteinase with thrombospondin motifs-5) due to its shallow S1' pocket. However, inhibition analysis revealed it to be a nanomolar inhibitor of both ADAMTS-4 and -5. The observed inconsistency was explained by analysis of crystallographic structures, which showed that Compound 12 in complex with the catalytic domain of ADAMTS-5 (cataTS5) exhibits an unusual conformation in the S1' pocket of the protein. This first demonstration that cataTS5 can undergo an induced conformational change in its active site pocket by a molecule like Compound 12 should enable the design of new aggrecanase inhibitors with better potency and selectivity profiles.

  7. Predicting functional divergence in protein evolution by site-specific rate shifts

    Science.gov (United States)

    Gaucher, Eric A.; Gu, Xun; Miyamoto, Michael M.; Benner, Steven A.

    2002-01-01

    Most modern tools that analyze protein evolution allow individual sites to mutate at constant rates over the history of the protein family. However, Walter Fitch observed in the 1970s that, if a protein changes its function, the mutability of individual sites might also change. This observation is captured in the "non-homogeneous gamma model", which extracts functional information from gene families by examining the different rates at which individual sites evolve. This model has recently been coupled with structural and molecular biology to identify sites that are likely to be involved in changing function within the gene family. Applying this to multiple gene families highlights the widespread divergence of functional behavior among proteins to generate paralogs and orthologs.

  8. Active site proton delivery and the lyase activity of human CYP17A1

    Energy Technology Data Exchange (ETDEWEB)

    Khatri, Yogan; Gregory, Michael C.; Grinkova, Yelena V.; Denisov, Ilia G.; Sligar, Stephen G., E-mail: s-sligar@illinois.edu

    2014-01-03

    equivalents and protons are funneled into non-productive pathways. This is similar to previous work with other P450 catalyzed hydroxylation. However, catalysis of carbon–carbon bond scission by the T306A mutant was largely unimpeded by disruption of the CYP17A1 acid-alcohol pair. The unique response of CYP17A1 lyase activity to mutation of Thr306 is consistent with a reactive intermediate formed independently of proton delivery in the active site, and supports involvement of a nucleophilic peroxo-anion rather than the traditional Compound I in catalysis.

  9. Predicting ambient aerosol thermal-optical reflectance (TOR) measurements from infrared spectra: extending the predictions to different years and different sites

    Science.gov (United States)

    Reggente, Matteo; Dillner, Ann M.; Takahama, Satoshi

    2016-02-01

    Organic carbon (OC) and elemental carbon (EC) are major components of atmospheric particulate matter (PM), which has been associated with increased morbidity and mortality, climate change, and reduced visibility. Typically OC and EC concentrations are measured using thermal-optical methods such as thermal-optical reflectance (TOR) from samples collected on quartz filters. In this work, we estimate TOR OC and EC using Fourier transform infrared (FT-IR) absorbance spectra from polytetrafluoroethylene (PTFE Teflon) filters using partial least square regression (PLSR) calibrated to TOR OC and EC measurements for a wide range of samples. The proposed method can be integrated with analysis of routinely collected PTFE filter samples that, in addition to OC and EC concentrations, can concurrently provide information regarding the functional group composition of the organic aerosol. We have used the FT-IR absorbance spectra and TOR OC and EC concentrations collected in the Interagency Monitoring of PROtected Visual Environments (IMPROVE) network (USA). We used 526 samples collected in 2011 at seven sites to calibrate the models, and more than 2000 samples collected in 2013 at 17 sites to test the models. Samples from six sites are present both in the calibration and test sets. The calibrations produce accurate predictions both for samples collected at the same six sites present in the calibration set (R2 = 0.97 and R2 = 0.95 for OC and EC respectively), and for samples from 9 of the 11 sites not included in the calibration set (R2 = 0.96 and R2 = 0.91 for OC and EC respectively). Samples collected at the other two sites require a different calibration model to achieve accurate predictions. We also propose a method to anticipate the prediction error; we calculate the squared Mahalanobis distance in the feature space (scores determined by PLSR) between new spectra and spectra in the calibration set. The squared Mahalanobis distance provides a crude method for assessing the

  10. Predicting the unpredictable: Critical analysis and practical implications of predictive anticipatory activity

    Directory of Open Access Journals (Sweden)

    Julia eMossbridge

    2014-03-01

    Full Text Available A recent meta-analysis of experiments from seven independent laboratories (n=26 published since 1978 indicates that the human body can apparently detect randomly delivered stimuli occurring 1-10 seconds in the future (Mossbridge, Tressoldi, & Utts, 2012. The key observation in these studies is that human physiology appears to be able to distinguish between unpredictable dichotomous future stimuli, such as emotional vs. neutral images or sound vs. silence. This phenomenon has been called presentiment (as in feeling the future. In this paper we call it predictive anticipatory activity or PAA. The phenomenon is predictive because it can distinguish between upcoming stimuli; it is anticipatory because the physiological changes occur before a future event; and it is an activity because it involves changes in the cardiopulmonary, skin, and/or nervous systems. PAA is an unconscious phenomenon that seems to be a time-reversed reflection of the usual physiological response to a stimulus. It appears to resemble precognition (consciously knowing something is going to happen before it does, but PAA specifically refers to unconscious physiological reactions as opposed to conscious premonitions. Though it is possible that PAA underlies the conscious experience of precognition, experiments testing this idea have not produced clear results. The first part of this paper reviews the evidence for PAA and examines the two most difficult challenges for obtaining valid evidence for it: expectation bias and multiple analyses. The second part speculates on possible mechanisms and the theoretical implications of PAA for understanding physiology and consciousness. The third part examines potential practical applications.

  11. WAsP prediction errors due to site orography[Wind Atlas Analysis and Application Program

    Energy Technology Data Exchange (ETDEWEB)

    Bowen, A.J.; Mortensen, N.G.

    2004-12-01

    The influence of rugged terrain on the prediction accuracy of the Wind Atlas Analysis and Application Program (WAsP) is investigated using a case study of field measurements taken in rugged terrain. The parameters that could cause substantial errors in a prediction are identified and discussed. In particular, the effects from extreme orography are investigated. A suitable performance indicator is developed which predicts the sign and approximate magnitude of such errors due to orography. This procedure allows the user to assess the consequences of using WAsP outside its operating envelope and could provide a means of correction for rugged terrain effects. (au)

  12. NetOglyc: prediction of mucin type O-glycosylation sites based on sequence context and surface accessibility

    DEFF Research Database (Denmark)

    Hansen, Jan Erik; Lund, Ole; Tolstrup, Niels

    1998-01-01

    -glycosylation signals in these evolutionary-related glycoproteins were found in their first hypervariable loop, V1. However, the strain variation for HIV-1 gp120 was significant. A computer server, available through WWW or E-mail, has been developed for prediction of mucin type O-glycosylation sites in proteins based...... on the amino acid sequence. The server addresses are http://www.cbs.dtu.dk/services/NetOGlyc/ and netOglyc@cbs.dtu.dk...

  13. A neural network method for identification of prokaryotic and eukaryotic signal peptides and prediction of their cleavage sites

    DEFF Research Database (Denmark)

    Nielsen, Henrik; Engelbrecht, Jacob; Brunak, Søren;

    1997-01-01

    We have developed a new method for the identication of signal peptides and their cleavage sites based on neural networks trained on separate sets of prokaryotic and eukaryotic sequences. The method performs signicantly better than previous prediction schemes, and can easily be applied to genome-w......-wide data sets. Discrimination between cleaved signal peptides and uncleaved N-terminal signal-anchor sequences is also possible, though with lower precision....

  14. pkaPS: prediction of protein kinase A phosphorylation sites with the simplified kinase-substrate binding model

    Directory of Open Access Journals (Sweden)

    Schneider Georg

    2007-01-01

    Full Text Available Abstract Background Protein kinase A (cAMP-dependent kinase, PKA is a serine/threonine kinase, for which ca. 150 substrate proteins are known. Based on a refinement of the recognition motif using the available experimental data, we wished to apply the simplified substrate protein binding model for accurate prediction of PKA phosphorylation sites, an approach that was previously successful for the prediction of lipid posttranslational modifications and of the PTS1 peroxisomal translocation signal. Results Approximately 20 sequence positions flanking the phosphorylated residue on both sides have been found to be restricted in their sequence variability (region -18...+23 with the site at position 0. The conserved physical pattern can be rationalized in terms of a qualitative binding model with the catalytic cleft of the protein kinase A. Positions -6...+4 surrounding the phosphorylation site are influenced by direct interaction with the kinase in a varying degree. This sequence stretch is embedded in an intrinsically disordered region composed preferentially of hydrophilic residues with flexible backbone and small side chain. This knowledge has been incorporated into a simplified analytical model of productive binding of substrate proteins with PKA. Conclusion The scoring function of the pkaPS predictor can confidently discriminate PKA phosphorylation sites from serines/threonines with non-permissive sequence environments (sensitivity of ~96% at a specificity of ~94%. The tool "pkaPS" has been applied on the whole human proteome. Among new predicted PKA targets, there are entirely uncharacterized protein groups as well as apparently well-known families such as those of the ribosomal proteins L21e, L22 and L6. Availability The supplementary data as well as the prediction tool as WWW server are available at http://mendel.imp.univie.ac.at/sat/pkaPS. Reviewers Erik van Nimwegen (Biozentrum, University of Basel, Switzerland, Sandor Pongor (International

  15. Tumor characteristics and metastatic sites may predict bevacizumab efficacy in the first-line treatment of metastatic colorectal cancer

    OpenAIRE

    Varol, Umut; Oktay, Esin; YILDIRIM, Mustafa; SURMELI, ZEKI GOKHAN; Dirican, Ahmet; Meydan, Nezih; KARACA, BURCAK; Karabulut, Bulent; Uslu, Ruchan

    2013-01-01

    Colorectal cancer (CRC) is among the most frequently diagnosed cancers and a major cause of cancer-related mortality worldwide. The aim of the present study was to determine whether there was an improvement in the time to disease progression (TTP) in patients with metastatic colorectal cancer (mCRC) treated with first-line bevacizumab plus chemotherapy, according to tumor characteristics and metastatic sites. Tumor characteristics and tumor burden were considered to be predictive markers of t...

  16. Structure-based comparative analysis and prediction of N-linked glycosylation sites in evolutionarily distant eukaryotes.

    Science.gov (United States)

    Lam, Phuc Vinh Nguyen; Goldman, Radoslav; Karagiannis, Konstantinos; Narsule, Tejas; Simonyan, Vahan; Soika, Valerii; Mazumder, Raja

    2013-04-01

    The asparagine-X-serine/threonine (NXS/T) motif, where X is any amino acid except proline, is the consensus motif for N-linked glycosylation. Significant numbers of high-resolution crystal structures of glycosylated proteins allow us to carry out structural analysis of the N-linked glycosylation sites (NGS). Our analysis shows that there is enough structural information from diverse glycoproteins to allow the development of rules which can be used to predict NGS. A Python-based tool was developed to investigate asparagines implicated in N-glycosylation in five species: Homo sapiens, Mus musculus, Drosophila melanogaster, Arabidopsis thaliana and Saccharomyces cerevisiae. Our analysis shows that 78% of all asparagines of NXS/T motif involved in N-glycosylation are localized in the loop/turn conformation in the human proteome. Similar distribution was revealed for all the other species examined. Comparative analysis of the occurrence of NXS/T motifs not known to be glycosylated and their reverse sequence (S/TXN) shows a similar distribution across the secondary structural elements, indicating that the NXS/T motif in itself is not biologically relevant. Based on our analysis, we have defined rules to determine NGS. Using machine learning methods based on these rules we can predict with 93% accuracy if a particular site will be glycosylated. If structural information is not available the tool uses structural prediction results resulting in 74% accuracy. The tool was used to identify glycosylation sites in 108 human proteins with structures and 2247 proteins without structures that have acquired NXS/T site/s due to non-synonymous variation. The tool, Structure Feature Analysis Tool (SFAT), is freely available to the public at http://hive.biochemistry.gwu.edu/tools/sfat. Copyright © 2013. Production and hosting by Elsevier Ltd.

  17. JET2 Viewer: a database of predicted multiple, possibly overlapping, protein–protein interaction sites for PDB structures

    Science.gov (United States)

    Ripoche, Hugues; Laine, Elodie; Ceres, Nicoletta; Carbone, Alessandra

    2017-01-01

    The database JET2 Viewer, openly accessible at http://www.jet2viewer.upmc.fr/, reports putative protein binding sites for all three-dimensional (3D) structures available in the Protein Data Bank (PDB). This knowledge base was generated by applying the computational method JET2 at large-scale on more than 20 000 chains. JET2 strategy yields very precise predictions of interacting surfaces and unravels their evolutionary process and complexity. JET2 Viewer provides an online intelligent display, including interactive 3D visualization of the binding sites mapped onto PDB structures and suitable files recording JET2 analyses. Predictions were evaluated on more than 15 000 experimentally characterized protein interfaces. This is, to our knowledge, the largest evaluation of a protein binding site prediction method. The overall performance of JET2 on all interfaces are: Sen = 52.52, PPV = 51.24, Spe = 80.05, Acc = 75.89. The data can be used to foster new strategies for protein–protein interactions modulation and interaction surface redesign. PMID:27899675

  18. Using Carbohydrate Interaction Assays to Reveal Novel Binding Sites in Carbohydrate Active Enzymes

    DEFF Research Database (Denmark)

    Cockburn, Darrell; Wilkens, Casper; Dilokpimol, Adiphol

    2016-01-01

    Carbohydrate active enzymes often contain auxiliary binding sites located either on independent domains termed carbohydrate binding modules (CBMs) or as so-called surface binding sites (SBSs) on the catalytic module at a certain distance from the active site. The SBSs are usually critical...... for the activity of their cognate enzyme, though they are not readily detected in the sequence of a protein, but normally require a crystal structure of a complex for their identification. A variety of methods, including affinity electrophoresis (AE), insoluble polysaccharide pulldown (IPP) and surface plasmon...... sites, but also for identifying new ones, even without structural data available. We further verify the chosen assays discriminate between known SBS/CBM containing enzymes and negative controls. Altogether 35 enzymes are screened for the presence of SBSs or CBMs and several novel binding sites...

  19. Performance predictions for mechanical excavators in Yucca Mountain tuffs; Yucca Mountain Site Characterization Project

    Energy Technology Data Exchange (ETDEWEB)

    Ozdemir, L.; Gertsch, L.; Neil, D.; Friant, J. [Colorado School of Mines, Golden, CO (United States). Earth Mechanics Inst.

    1992-09-01

    The performances of several mechanical excavators are predicted for use in the tuffs at Yucca Mountain: Tunnel boring machines, the Mobile Miner, a roadheader, a blind shaft borer, a vertical wheel shaft boring machine, raise drills, and V-Moles. Work summarized is comprised of three parts: Initial prediction using existing rock physical property information; Measurement of additional rock physical properties; and Revision of the initial predictions using the enhanced database. The performance predictions are based on theoretical and empirical relationships between rock properties and the forces-experienced by rock cutters and bits during excavation. Machine backup systems and excavation design aspects, such as curves and grades, are considered in determining excavator utilization factors. Instanteous penetration rate, advance rate, and cutter costs are the fundamental performance indicators.

  20. Exploiting structural and topological information to improve prediction of RNA-protein binding sites

    Directory of Open Access Journals (Sweden)

    Yuan Zheng

    2009-10-01

    Full Text Available Abstract Background RNA-protein interactions are important for a wide range of biological processes. Current computational methods to predict interacting residues in RNA-protein interfaces predominately rely on sequence data. It is, however, known that interface residue propensity is closely correlated with structural properties. In this paper we systematically study information obtained from sequences and structures and compare their contributions in this prediction problem. Particularly, different geometrical and network topological properties of protein structures are evaluated to improve interface residue prediction accuracy. Results We have quantified the impact of structural information on the prediction accuracy in comparison to the purely sequence based approach using two machine learning techniques: Naïve Bayes classifiers and Support Vector Machines. The highest AUC of 0.83 was achieved by a Support Vector Machine, exploiting PSI-BLAST profile, accessible surface area, betweenness-centrality and retention coefficient as input features. Taking into account that our results are based on a larger non-redundant data set, the prediction accuracy is considerably higher than reported in previous, comparable studies. A protein-RNA interface predictor (PRIP and the data set have been made available at http://www.qfab.org/PRIP. Conclusion Graph-theoretic properties of residue contact maps derived from protein structures such as betweenness-centrality can supplement sequence or structure features to improve the prediction accuracy for binding residues in RNA-protein interactions. While Support Vector Machines perform better on this task, Naïve Bayes classifiers also have been found to achieve good prediction accuracies but require much less training time and are an attractive choice for large scale predictions.

  1. Medial Temporal Lobe Activity Predicts Successful Relational Memory Binding

    Science.gov (United States)

    Hannula, Deborah E.; Ranganath, Charan

    2009-01-01

    Previous neuropsychological findings have implicated medial temporal lobe (MTL) structures in retaining object-location relations over the course of short delays, but MTL effects have not always been reported in neuroimaging investigations with similar short-term memory requirements. Here, we used event-related functional magnetic resonance imaging to test the hypothesis that the hippocampus and related MTL structures support accurate retention of relational memory representations, even across short delays. On every trial, four objects were presented, each in one of nine possible locations of a three-dimensional grid. Participants were to mentally rotate the grid and then maintain the rotated representation in anticipation of a test stimulus: a rendering of the grid, rotated 90° from the original viewpoint. The test stimulus was either a “match” display, in which object-location relations were intact, or a “mismatch” display, in which one object occupied a new, previously unfilled location (mismatch position), or two objects had swapped locations (mismatch swap). Encoding phase activation in anterior and posterior regions of the left hippocampus, and in bilateral perirhinal cortex, predicted subsequent accuracy on the short-term memory decision, as did bilateral posterior hippocampal activity after the test stimulus. Notably, activation in these posterior hippocampal regions was also sensitive to the degree to which object-location bindings were preserved in the test stimulus; activation was greatest for match displays, followed by mismatch-position displays, and finally mismatch-swap displays. These results indicate that the hippocampus and related MTL structures contribute to successful encoding and retrieval of relational information in visual short-term memory. PMID:18171929

  2. Structure and nuclearity of active sites in Fe-zeolites: comparison with iron sites in enzymes and homogeneous catalysts.

    Science.gov (United States)

    Zecchina, Adriano; Rivallan, Mickaël; Berlier, Gloria; Lamberti, Carlo; Ricchiardi, Gabriele

    2007-07-21

    Fe-ZSM-5 and Fe-silicalite zeolites efficiently catalyse several oxidation reactions which find close analogues in the oxidation reactions catalyzed by homogeneous and enzymatic compounds. The iron centres are highly dispersed in the crystalline matrix and on highly diluted samples, mononuclear and dinuclear structures are expected to become predominant. The crystalline and robust character of the MFI framework has allowed to hypothesize that the catalytic sites are located in well defined crystallographic positions. For this reason these catalysts have been considered as the closest and best defined heterogeneous counterparts of heme and non heme iron complexes and of Fenton type Fe(2+) homogeneous counterparts. On this basis, an analogy with the methane monooxygenase has been advanced several times. In this review we have examined the abundant literature on the subject and summarized the most widely accepted views on the structure, nuclearity and catalytic activity of the iron species. By comparing the results obtained with the various characterization techniques, we conclude that Fe-ZSM-5 and Fe-silicalite are not the ideal samples conceived before and that many types of species are present, some active and some other silent from adsorptive and catalytic point of view. The relative concentration of these species changes with thermal treatments, preparation procedures and loading. Only at lowest loadings the catalytically active species become the dominant fraction of the iron species. On the basis of the spectroscopic titration of the active sites by using NO as a probe, we conclude that the active species on very diluted samples are isolated and highly coordinatively unsaturated Fe(2+) grafted to the crystalline matrix. Indication of the constant presence of a smaller fraction of Fe(2+) presumably located on small clusters is also obtained. The nitrosyl species formed upon dosing NO from the gas phase on activated Fe-ZSM-5 and Fe-silicalite, have been analyzed

  3. 77 FR 3460 - Reimbursement for Costs of Remedial Action at Active Uranium and Thorium Processing Sites

    Science.gov (United States)

    2012-01-24

    ... Uranium and Thorium Processing Sites AGENCY: Department of Energy. ACTION: Notice of the acceptance of... (DOE) acceptance of claims in FY 2012 from eligible active uranium and thorium processing site... uranium and thorium licensees for certain costs of decontamination, decommissioning, reclamation,...

  4. 75 FR 71677 - Reimbursement for Costs of Remedial Action at Active Uranium and Thorium Processing Sites

    Science.gov (United States)

    2010-11-24

    ... Reimbursement for Costs of Remedial Action at Active Uranium and Thorium Processing Sites AGENCY: Department of... uranium and thorium processing site licensees for reimbursement under Title X of the Energy Policy Act of... requires DOE to reimburse eligible uranium and thorium licensees for certain costs of...

  5. Bi-directional SIFT predicts a subset of activating mutations.

    Science.gov (United States)

    Lee, William; Zhang, Yan; Mukhyala, Kiran; Lazarus, Robert A; Zhang, Zemin

    2009-12-14

    Advancements in sequencing technologies have empowered recent efforts to identify polymorphisms and mutations on a global scale. The large number of variations and mutations found in these projects requires high-throughput tools to identify those that are most likely to have an impact on function. Numerous computational tools exist for predicting which mutations are likely to be functional, but none that specifically attempt to identify mutations that result in hyperactivation or gain-of-function. Here we present a modified version of the SIFT (Sorting Intolerant from Tolerant) algorithm that utilizes protein sequence alignments with homologous sequences to identify functional mutations based on evolutionary fitness. We show that this bi-directional SIFT (B-SIFT) is capable of identifying experimentally verified activating mutants from multiple datasets. B-SIFT analysis of large-scale cancer genotyping data identified potential activating mutations, some of which we have provided detailed structural evidence to support. B-SIFT could prove to be a valuable tool for efforts in protein engineering as well as in identification of functional mutations in cancer.

  6. Brain Monoamine Oxidase-A Activity Predicts Trait Aggression

    Science.gov (United States)

    Alia-Klein, Nelly; Goldstein, Rita Z.; Kriplani, Aarti; Logan, Jean; Tomasi, Dardo; Williams, Benjamin; Telang, Frank; Shumay, Elena; Biegon, Anat; Craig, Ian W.; Henn, Fritz; Wang, Gene-Jack; Volkow, Nora D.; Fowler, Joanna S.

    2008-01-01

    The genetic deletion of monoamine oxidase A (MAO A, an enzyme which breaks down the monoamine neurotransmitters norepinephrine, serotonin and dopamine) produces aggressive phenotypes across species. Therefore, a common polymorphism in the MAO A gene (MAOA, MIM 309850, referred to as high or low based on transcription in non-neuronal cells) has been investigated in a number of externalizing behavioral and clinical phenotypes. These studies provide evidence linking the low MAOA genotype and violent behavior but only through interaction with severe environmental stressors during childhood. Here, we hypothesized that in healthy adult males the gene product of MAO A in the brain, rather than the gene per se, would be associated with regulating the concentration of brain amines involved in trait aggression. Brain MAO A activity was measured in-vivo in healthy non-smoking men with positron emission tomography using a radioligand specific for MAO A (clorgyline labeled with carbon 11). Trait aggression was measured with the Multidimensional Personality Questionnaire (MPQ). Here we report for the first time that brain MAO A correlates inversely with the MPQ trait measure of aggression (but not with other personality traits) such that the lower the MAO A activity in cortical and subcortical brain regions the higher the self-reported aggression (in both MAOA genotype groups) contributing to more than a third of the variability. Since trait aggression is a measure used to predict antisocial behavior, these results underscore the relevance of MAO A as a neurochemical substrate of aberrant aggression. PMID:18463263

  7. Active site dynamics of toluene hydroxylation by cytochrome P-450

    Energy Technology Data Exchange (ETDEWEB)

    Hanzlik, R.P.; Kahhiing John Ling (Univ. of Kansas, Lawrence (United States))

    1990-06-22

    Rat liver cytochrome P-450 hydroxylates toluene to benzyl alcohol plus o-, m-, and p-cresol. Deuterated toluenes were incubated under saturating conditions with liver microsomes from phenobarbital-pretreated rats, and product yields and ratios were measured. Stepwise deuteration of the methyl leads to stepwise decreases in the alcohol/cresol ratio without changing the cresol isomer ratios. Extensive deuterium retention in the benzyl alcohols from PhCH{sub 2}D and PhCHD{sub 2} suggests there is a large intrinsic isotope effect for benzylic hydroxylation. After replacement of the third benzylic H by D, the drop in the alcohol/cresol ratio was particularly acute, suggsting that metabolic switching from D to H within the methyl group was easier than switching from the methyl to the ring. Comparison of the alcohol/cresol ratio for PhCH{sub 3} vs PhCD{sub 3} indicated a net isotope effect of 6.9 for benzylic hydroxylation. From product yield data for PhCH{sub 3} and PhCD{sub 3}, {sup D}V for benzyl alcohol formation is only 1.92, whereas {sup D}V for total product formation is 0.67 (i.e., inverse). From competitive incubations of PhCH{sub 3}/PhCD{sub 3} mixtures {sup D}(V/K) isotope effects on benzyl alcohol formation and total product formation (3.6 and 1.23, respectively) are greatly reduced, implying strong commitment to catalysis. In contrast, {sup D}(V/K) for the alcohol/cresol ratio is 6.3, indicating that the majority of the intrinsic isotope effect is expressed through metabolic switching. Overall, these data are consistent with reversible formation of a complex between toluene and the active oxygen form of cytochrome P-450, which rearranges internally and reacts to form products faster than it dissociates back to release substrate.

  8. Verification of geomechanical integrity and prediction of long-term mineral trapping for the Ketzin CO2 storage pilot site

    Science.gov (United States)

    Kempka, Thomas; De Lucia, Marco; Kühn, Michael

    2014-05-01

    Static and dynamic numerical modelling generally accompany the entire CO2 storage site life cycle. Thereto, it is required to match the employed models with field observations on a regular basis in order to predict future site behaviour. We investigated the coupled processes at the Ketzin CO2 storage pilot site [1] using a model coupling concept focusing on the temporal relevance of processes involved (hydraulic, chemical and mechanical) at given time-scales (site operation, abandonment and long-term stabilization). For that purpose, long-term dynamic multi-phase flow simulations [2], [3] established the basis for all simulations discussed in the following. Hereby, pressure changes resulting in geomechanical effects are largest during site operation, whereas geochemical reactions are governed by slow kinetics resulting in a long-term stabilization. To account for mechanical integrity, which may be mainly affected during site operation, we incorporated a regional-scale coupled hydro-mechanical model. Our simulation results show maximum ground surface displacements of about 4 mm, whereas shear and tensile failure are not observed. Consequently, the CO2 storage operation at the Ketzin pilot site does not compromise reservoir, caprock and fault integrity. Chemical processes responsible for mineral trapping are expected to mainly occur during long-term stabilization at the Ketzin pilot site [4]. Hence, our previous assessment [3] was extended by integrating two long-term mineral trapping scenarios. Thereby, mineral trapping contributes to the trapping mechanisms with 11.7 % after 16,000 years of simulation in our conservative and with 30.9 % in our maximum reactivity scenarios. Dynamic flow simulations indicate that only 0.2 % of the CO2 injected (about 67,270 t CO2 in total) is in gaseous state, but structurally trapped after 16,000 years. Depending on the studied long-term scenario, CO2 dissolution is the dominating trapping mechanism with 68.9 % and 88

  9. 1993 annual report of hazardous waste activities for the Oak Ridge K-25 site

    Energy Technology Data Exchange (ETDEWEB)

    1994-02-01

    This report is a detailed listing of all of the Hazardous Waste activities occurring at Martin Marietta`s K-25 site. Contained herein are hazardous waste notification forms, waste stream reports, generator fee forms and various TSDR reports.

  10. 1993 annual report of hazardous waste activities for the Oak Ridge K-25 site

    Energy Technology Data Exchange (ETDEWEB)

    1994-02-01

    This report is a detailed listing of all of the Hazardous Waste activities occurring at Martin Marietta`s K-25 site. Contained herein are hazardous waste notification forms, waste stream reports, generator fee forms and various TSDR reports.

  11. The thermal stability of the framework, hydroxyl groups, and active sites of faujasites

    Energy Technology Data Exchange (ETDEWEB)

    Mishin, I.V.; Kalinin, V.P.; Nissenbaum, V.D. [Zelinskii Institute of Organic Chemistry, Moscow (Russian Federation); Beyer, H.K. [Hungarian Academy of Sciences, Budapest (Hungary); Karge, H.G. [Fritz Haber Institute of the Max Planck Soceity, Berlin (Germany)

    1994-07-01

    The effect of the framework composition on the crystallinity and {open_quotes}density{close_quotes} of hydroxyl groups and the concentration of active sites is reported for hydrogen forms of Y zeolites preheated at 400 - 1000{degrees}C. The increase in the Si/Al ratios results in improved resistance of the framework atoms and hydroxyl groups to high temperatures and in enhanced thermal stability of the sites that are active in the cracking of isooctane and disproportionation of ethylbenzene.

  12. The prediction of induced activity levels in and around NIMROD

    CERN Document Server

    Hack, R C

    1973-01-01

    Comparisons are reported between measured and predicted levels of induced radioactivity for a number of irradiation conditions. Good agreement was found between experimental measurements and fairly simple methods of prediction developed at CERN.

  13. Evolution of neural networks for the prediction of hydraulic conductivity as a function of borehole geophysical logs: Shobasama site, Japan.

    Energy Technology Data Exchange (ETDEWEB)

    Reeves, Paul C.; McKenna, Sean Andrew

    2004-06-01

    This report describes the methodology and results of a project to develop a neural network for the prediction of the measured hydraulic conductivity or transmissivity in a series of boreholes at the Tono, Japan study site. Geophysical measurements were used as the input to EL feed-forward neural network. A simple genetic algorithm was used to evolve the architecture and parameters of the neural network in conjunction with an optimal subset of geophysical measurements for the prediction of hydraulic conductivity. The first attempt was focused on the estimation of the class of the hydraulic conductivity, high, medium or low, from the geophysical logs. This estimation was done while using the genetic algorithm to simultaneously determine which geophysical logs were the most important and optimizing the architecture of the neural network. Initial results showed that certain geophysical logs provided more information than others- most notably the 'short-normal', micro-resistivity, porosity and sonic logs provided the most information on hydraulic conductivity. The neural network produced excellent training results with accuracy of 90 percent or greater, but was unable to produce accurate predictions of the hydraulic conductivity class. The second attempt at prediction was done using a new methodology and a modified data set. The new methodology builds on the results of the first attempts at prediction by limiting the choices of geophysical logs to only those that provide significant information. Additionally, this second attempt uses a modified data set and predicts transmissivity instead of hydraulic conductivity. Results of these simulations indicate that the most informative geophysical measurements for the prediction of transmissivity are depth and sonic log. The long normal resistivity and self potential borehole logs are moderately informative. In addition, it was found that porosity and crack counts (clear, open, or hairline) do not inform predictions

  14. XAFS Study of the Photo-Active Site of Mo/MCM-41

    Science.gov (United States)

    Miyamoto, Daisuke; Ichikuni, Nobuyuki; Shimazu, Shogo

    2007-02-01

    An Mo/MCM-41 catalyst was prepared and used for study of propene and 1-butene photo-metathesis reactions. XAFS analysis revealed that hydrogen reduction leads to a decreased role for the Mo=O site. The Mo-O site plays an important role for the olefin photo-metathesis reaction on the H2 reduced Mo/MCM-41. From EXAFS analysis, the active site of photo-metathesis reaction is the Mo=O part for oxidized Mo/MCM-41, whereas it is the Mo-O site for reduced Mo/MCM-41.

  15. A sequence-based dynamic ensemble learning system for protein ligand-binding site prediction

    KAUST Repository

    Chen, Peng

    2015-12-03

    Background: Proteins have the fundamental ability to selectively bind to other molecules and perform specific functions through such interactions, such as protein-ligand binding. Accurate prediction of protein residues that physically bind to ligands is important for drug design and protein docking studies. Most of the successful protein-ligand binding predictions were based on known structures. However, structural information is not largely available in practice due to the huge gap between the number of known protein sequences and that of experimentally solved structures

  16. Sequence-based prediction of protein-binding sites in DNA: comparative study of two SVM models.

    Science.gov (United States)

    Park, Byungkyu; Im, Jinyong; Tuvshinjargal, Narankhuu; Lee, Wook; Han, Kyungsook

    2014-11-01

    As many structures of protein-DNA complexes have been known in the past years, several computational methods have been developed to predict DNA-binding sites in proteins. However, its inverse problem (i.e., predicting protein-binding sites in DNA) has received much less attention. One of the reasons is that the differences between the interaction propensities of nucleotides are much smaller than those between amino acids. Another reason is that DNA exhibits less diverse sequence patterns than protein. Therefore, predicting protein-binding DNA nucleotides is much harder than predicting DNA-binding amino acids. We computed the interaction propensity (IP) of nucleotide triplets with amino acids using an extensive dataset of protein-DNA complexes, and developed two support vector machine (SVM) models that predict protein-binding nucleotides from sequence data alone. One SVM model predicts protein-binding nucleotides using DNA sequence data alone, and the other SVM model predicts protein-binding nucleotides using both DNA and protein sequences. In a 10-fold cross-validation with 1519 DNA sequences, the SVM model that uses DNA sequence data only predicted protein-binding nucleotides with an accuracy of 67.0%, an F-measure of 67.1%, and a Matthews correlation coefficient (MCC) of 0.340. With an independent dataset of 181 DNAs that were not used in training, it achieved an accuracy of 66.2%, an F-measure 66.3% and a MCC of 0.324. Another SVM model that uses both DNA and protein sequences achieved an accuracy of 69.6%, an F-measure of 69.6%, and a MCC of 0.383 in a 10-fold cross-validation with 1519 DNA sequences and 859 protein sequences. With an independent dataset of 181 DNAs and 143 proteins, it showed an accuracy of 67.3%, an F-measure of 66.5% and a MCC of 0.329. Both in cross-validation and independent testing, the second SVM model that used both DNA and protein sequence data showed better performance than the first model that used DNA sequence data. To the best of

  17. 'Unconventional' coordination chemistry by metal chelating fragments in a metalloprotein active site.

    Science.gov (United States)

    Martin, David P; Blachly, Patrick G; Marts, Amy R; Woodruff, Tessa M; de Oliveira, César A F; McCammon, J Andrew; Tierney, David L; Cohen, Seth M

    2014-04-01

    The binding of three closely related chelators: 5-hydroxy-2-methyl-4H-pyran-4-thione (allothiomaltol, ATM), 3-hydroxy-2-methyl-4H-pyran-4-thione (thiomaltol, TM), and 3-hydroxy-4H-pyran-4-thione (thiopyromeconic acid, TPMA) to the active site of human carbonic anhydrase II (hCAII) has been investigated. Two of these ligands display a monodentate mode of coordination to the active site Zn(2+) ion in hCAII that is not recapitulated in model complexes of the enzyme active site. This unprecedented binding mode in the hCAII-thiomaltol complex has been characterized by both X-ray crystallography and X-ray spectroscopy. In addition, the steric restrictions of the active site force the ligands into a 'flattened' mode of coordination compared with inorganic model complexes. This change in geometry has been shown by density functional computations to significantly decrease the strength of the metal-ligand binding. Collectively, these data demonstrate that the mode of binding by small metal-binding groups can be significantly influenced by the protein active site. Diminishing the strength of the metal-ligand bond results in unconventional modes of metal coordination not found in typical coordination compounds or even carefully engineered active site models, and understanding these effects is critical to the rational design of inhibitors that target clinically relevant metalloproteins.

  18. Individual tree crown approach for predicting site index in boreal forests using airborne laser scanning and hyperspectral data

    Science.gov (United States)

    Kandare, Kaja; Ørka, Hans Ole; Dalponte, Michele; Næsset, Erik; Gobakken, Terje

    2017-08-01

    Site productivity is essential information for sustainable forest management and site index (SI) is the most common quantitative measure of it. The SI is usually determined for individual tree species based on tree height and the age of the 100 largest trees per hectare according to stem diameter. The present study aimed to demonstrate and validate a methodology for the determination of SI using remotely sensed data, in particular fused airborne laser scanning (ALS) and airborne hyperspectral data in a forest site in Norway. The applied approach was based on individual tree crown (ITC) delineation: tree species, tree height, diameter at breast height (DBH), and age were modelled and predicted at ITC level using 10-fold cross validation. Four dominant ITCs per 400 m2 plot were selected as input to predict SI at plot level for Norway spruce (Picea abies (L.) Karst.) and Scots pine (Pinus sylvestris L.). We applied an experimental setup with different subsets of dominant ITCs with different combinations of attributes (predicted or field-derived) for SI predictions. The results revealed that the selection of the dominant ITCs based on the largest DBH independent of tree species, predicted the SI with similar accuracy as ITCs matched with field-derived dominant trees (RMSE: 27.6% vs 23.3%). The SI accuracies were at the same level when dominant species were determined from the remotely sensed or field data (RMSE: 27.6% vs 27.8%). However, when the predicted tree age was used the SI accuracy decreased compared to field-derived age (RMSE: 27.6% vs 7.6%). In general, SI was overpredicted for both tree species in the mature forest, while there was an underprediction in the young forest. In conclusion, the proposed approach for SI determination based on ITC delineation and a combination of ALS and hyperspectral data is an efficient and stable procedure, which has the potential to predict SI in forest areas at various spatial scales and additionally to improve existing SI

  19. Poisoning Experiments Aimed at Discriminating Active and Less-Active Sites of Silica-Supported Tantalum Hydride for Alkane Metathesis

    KAUST Repository

    Saggio, Guillaume

    2010-10-04

    Only 50% of the silica-supported tantalum hydride sites are active in the metathesis of propane. Indeed, more than 45% of the tantalum hydride can be eliminated by a selective oxygen poisoning of inactive sites with no significant decrease in the global turnover. Conversely, cyclopentane induces no such selective poisoning. Hence, the active tantalum hydride sites that show greater resistance to oxygen poisoning correspond to the νTa-H bands of higher wavenumbers, particularly that at 1860cm-1. These active tantalum hydride sites should correspond to tris- or monohydride species relatively far from silica surface oxygen atoms. © 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  20. Computational Prediction of CRISPR/Cas9 Target Sites Reveals Potential Off-Target Risks in Human and Mouse.

    Science.gov (United States)

    Wang, Qingbo; Ui-Tei, Kumiko

    2017-01-01

    The clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated (Cas) system is a prominent genome engineering technology. In the CRISPR/Cas system, the RNA-guided endonuclease Cas protein introduces a DNA double-stranded break at the genome position recognized by a guide RNA (gRNA) based on complementary base-pairing of about 20-nucleotides in length. The 8- or 12-mer gRNA sequence in the proximal region is especially important for target recognition, and the genes with sequence complementarity to such regions are often disrupted. To carry out target site-specific genome editing, we released the CRISPRdirect ( http://crispr.dbcls.jp /) website. This website allows us to select target site-specific gRNA sequences by performing exhaustive searches against entire genomic sequences. In this study, target site-specific gRNA sequences were designed for human, mouse, Drosophila melanogaster, and Caenorhabditis elegans. The calculation results revealed that at least five gRNA sequences, each of them having only one perfectly complementary site in the whole genome, could be designed for more than 95% of genes, regardless of the organism. Next, among those gRNAs, we selected gRNAs that did not have any other complementary site to the unique 12-mer proximal sequences to avoid possible off-target effects. This computational prediction revealed that target site-specific gRNAs are selectable for the majority of genes in D. melanogaster and C. elegans. However, for >50% of genes in humans and mice, there are no target sites without possible off-target effects.

  1. Concept for calculating dose rates from activated groundwater at accelerator sites

    CERN Document Server

    Prolingheuer, N; Vanderborght, J; Schlögl, B; Nabbi, R; Moormann, R

    Licensing of particle accelerators requires the proof that the groundwater outside of the site will not be significantly contaminated by activation products formed below accelerator and target. In order to reduce the effort for this proof, a site independent simplified but conservative method is under development. The conventional approach for calculation of activation of soil and groundwater is shortly described on example of a site close to Forschungszentrum Juelich, Germany. Additionally an updated overview of a data library for partition coefficients for relevant nuclides transported in the aquifer at the site is presented. The approximate model for transport of nuclides with ground water including exemplary results on nuclide concentrations outside of the site boundary and of resulting effective doses is described. Further applications and developments are finally outlined.

  2. Paper Highlight: Biomarker Identified for Predicting Early Prostate Cancer Aggressiveness — Site

    Science.gov (United States)

    A team led by Cory Abate-Shen, Michael Shen, and Andrea Califano at Columbia University found that measuring the expression levels of three genes associated with aging can be used to predict the aggressiveness of seemingly low-risk prostate cancer.

  3. Mixing active-site components: a recipe for the unique enzymatic activity of a telomere resolvase.

    Science.gov (United States)

    Bankhead, Troy; Chaconas, George

    2004-09-21

    The ResT protein, a telomere resolvase from Borrelia burgdorferi, processes replication intermediates into linear replicons with hairpin ends by using a catalytic mechanism similar to that for tyrosine recombinases and type IB topoisomerases. We have identified in ResT a hairpin binding region typically found in cut-and-paste transposases. We show that substitution of residues within this region results in a decreased ability of these mutants to catalyze telomere resolution. However, the mutants are capable of resolving heteroduplex DNA substrates designed to allow spontaneous destabilization and prehairpin formation. These findings support the existence of a hairpin binding region in ResT, the only known occurrence outside a transposase. The combination of transposase-like and tyrosine-recombinase-like domains found in ResT indicates the use of a composite active site and helps explain the unique breakage-and-reunion reaction observed with this protein. Comparison of the ResT sequence with other known telomere resolvases suggests that a hairpin binding motif is a common feature in this class of enzyme; the sequence motif also appears in the RAG recombinases. Finally, our data support a mechanism of action whereby ResT induces prehairpin formation before the DNA cleavage step.

  4. ChIP-seq Accurately Predicts Tissue-Specific Activity of Enhancers

    Energy Technology Data Exchange (ETDEWEB)

    Visel, Axel; Blow, Matthew J.; Li, Zirong; Zhang, Tao; Akiyama, Jennifer A.; Holt, Amy; Plajzer-Frick, Ingrid; Shoukry, Malak; Wright, Crystal; Chen, Feng; Afzal, Veena; Ren, Bing; Rubin, Edward M.; Pennacchio, Len A.

    2009-02-01

    A major yet unresolved quest in decoding the human genome is the identification of the regulatory sequences that control the spatial and temporal expression of genes. Distant-acting transcriptional enhancers are particularly challenging to uncover since they are scattered amongst the vast non-coding portion of the genome. Evolutionary sequence constraint can facilitate the discovery of enhancers, but fails to predict when and where they are active in vivo. Here, we performed chromatin immunoprecipitation with the enhancer-associated protein p300, followed by massively-parallel sequencing, to map several thousand in vivo binding sites of p300 in mouse embryonic forebrain, midbrain, and limb tissue. We tested 86 of these sequences in a transgenic mouse assay, which in nearly all cases revealed reproducible enhancer activity in those tissues predicted by p300 binding. Our results indicate that in vivo mapping of p300 binding is a highly accurate means for identifying enhancers and their associated activities and suggest that such datasets will be useful to study the role of tissue-specific enhancers in human biology and disease on a genome-wide scale.

  5. The complexities of measuring access to parks and physical activity sites in New York City: a quantitative and qualitative approach

    Directory of Open Access Journals (Sweden)

    Sohler Nancy L

    2009-06-01

    Full Text Available Abstract Background Proximity to parks and physical activity sites has been linked to an increase in active behaviors, and positive impacts on health outcomes such as lower rates of cardiovascular disease, diabetes, and obesity. Since populations with a low socio-economic status as well as racial and ethnic minorities tend to experience worse health outcomes in the USA, access to parks and physical activity sites may be an environmental justice issue. Geographic Information systems were used to conduct quantitative and qualitative analyses of park accessibility in New York City, which included kernel density estimation, ordinary least squares (global regression, geographically weighted (local regression, and longitudinal case studies, consisting of field work and archival research. Accessibility was measured by both density of park acreage and density of physical activity sites. Independent variables included percent non-Hispanic black, percent Hispanic, percent below poverty, percent of adults without high school diploma, percent with limited English-speaking ability, and population density. Results The ordinary least squares linear regression found weak relationships in both the park acreage density and the physical activity site density models (Ra2 = .11 and .23, respectively; AIC = 7162 and 3529, respectively. Geographically weighted regression, however, suggested spatial non-stationarity in both models, indicating disparities in accessibility that vary over space with respect to magnitude and directionality of the relationships (AIC = 2014 and -1241, respectively. The qualitative analysis supported the findings of the local regression, confirming that although there is a geographically inequitable distribution of park space and physical activity sites, it is not globally predicted by race, ethnicity, or socio-economic status. Conclusion The combination of quantitative and qualitative analyses demonstrated the complexity of the issues around

  6. Correlated structural kinetics and retarded solvent dynamics at the metalloprotease active site

    Energy Technology Data Exchange (ETDEWEB)

    Grossman, Moran; Born, Benjamin; Heyden, Matthias; Tworowski, Dmitry; Fields, Gregg B.; Sagi, Irit; Havenith, Martina

    2011-09-18

    Solvent dynamics can play a major role in enzyme activity, but obtaining an accurate, quantitative picture of solvent activity during catalysis is quite challenging. Here, we combine terahertz spectroscopy and X-ray absorption analyses to measure changes in the coupled water-protein motions during peptide hydrolysis by a zinc-dependent human metalloprotease. These changes were tightly correlated with rearrangements at the active site during the formation of productive enzyme-substrate intermediates and were different from those in an enzyme–inhibitor complex. Molecular dynamics simulations showed a steep gradient of fast-to-slow coupled protein-water motions around the protein, active site and substrate. Our results show that water retardation occurs before formation of the functional Michaelis complex. We propose that the observed gradient of coupled protein-water motions may assist enzyme-substrate interactions through water-polarizing mechanisms that are remotely mediated by the catalytic metal ion and the enzyme active site.

  7. SVM-based prediction of propeptide cleavage sites in spider toxins identifies toxin innovation in an Australian tarantula.

    Directory of Open Access Journals (Sweden)

    Emily S W Wong

    Full Text Available Spider neurotoxins are commonly used as pharmacological tools and are a popular source of novel compounds with therapeutic and agrochemical potential. Since venom peptides are inherently toxic, the host spider must employ strategies to avoid adverse effects prior to venom use. It is partly for this reason that most spider toxins encode a protective proregion that upon enzymatic cleavage is excised from the mature peptide. In order to identify the mature toxin sequence directly from toxin transcripts, without resorting to protein sequencing, the propeptide cleavage site in the toxin precursor must be predicted bioinformatically. We evaluated different machine learning strategies (support vector machines, hidden Markov model and decision tree and developed an algorithm (SpiderP for prediction of propeptide cleavage sites in spider toxins. Our strategy uses a support vector machine (SVM framework that combines both local and global sequence information. Our method is superior or comparable to current tools for prediction of propeptide sequences in spider toxins. Evaluation of the SVM method on an independent test set of known toxin sequences yielded 96% sensitivity and 100% specificity. Furthermore, we sequenced five novel peptides (not used to train the final predictor from the venom of the Australian tarantula Selenotypus plumipes to test the accuracy of the predictor and found 80% sensitivity and 99.6% 8-mer specificity. Finally, we used the predictor together with homology information to predict and characterize seven groups of novel toxins from the deeply sequenced venom gland transcriptome of S. plumipes, which revealed structural complexity and innovations in the evolution of the toxins. The precursor prediction tool (SpiderP is freely available on ArachnoServer (http://www.arachnoserver.org/spiderP.html, a web portal to a comprehensive relational database of spider toxins. All training data, test data, and scripts used are available from

  8. In silico prediction of the site of oxidation by cytochrome P450 3A4 that leads to the formation of the toxic metabolites of pyrrolizidine alkaloids.

    Science.gov (United States)

    Fashe, Muluneh M; Juvonen, Risto O; Petsalo, Aleksanteri; Vepsäläinen, Jouko; Pasanen, Markku; Rahnasto-Rilla, Minna

    2015-04-20

    In humans, the metabolic bioactivation of pyrrolizidine alkaloids (PAs) is mediated mainly by cytochrome P450 3A4 (CYP3A4) via the hydroxylation of their necine bases at C3 or C8 of heliotridine- and retronecine-type PAs or at the N atom of the methyl substituent of otonecine-type PAs. However, no attempts have been made to identify which C atom is the most favorable site for hydroxylation in silico. Here, in order to determine the site of hydroxylation that eventually leads to the formation of the toxic metabolites produced from lasiocarpine, retrorsine, and senkirkin, we utilized the ligand-based electrophilic Fukui function f(-)(r) and hydrogen-bond dissociation energies (BDEs) as well as structure-based molecular docking. The ligand-based computations revealed that the C3 and C8 atoms of lasiocarpine and retrorsine and the C26 atom of senkirkin were chemically the most susceptible locations for electrophilic oxidizing reactions. Similarly, according to the predicted binding orientation in the active site of the crystal structure of human CYP3A4 (PDB code: 4I4G ), the alkaloids were positioned in such a way that the C3 atom of lasiocarpine and retrorsine and the C26 of senkirkin were closest to the catalytic heme Fe. Thus, it is concluded that the C3 atom of lasiocarpine and retrorsine and C26 of senkirkin are the most favored sites of hydroxylation that lead to the production of their toxic metabolites.

  9. The Predicting Model of E-commerce Site Based on the Ideas of Curve Fitting

    Science.gov (United States)

    Tao, Zhang; Li, Zhang; Dingjun, Chen

    On the basis of the idea of the second multiplication curve fitting, the number and scale of Chinese E-commerce site is analyzed. A preventing increase model is introduced in this paper, and the model parameters are solved by the software of Matlab. The validity of the preventing increase model is confirmed though the numerical experiment. The experimental results show that the precision of preventing increase model is ideal.

  10. Determination of the strain generated in InAs/InP quantum wires: prediction of nucleation sites

    Energy Technology Data Exchange (ETDEWEB)

    Molina, S I [Departamento de Ciencia de los Materiales e I.M. y Q.I., Facultad de Ciencias, Universidad de Cadiz, Campus RIo San Pedro, s/n, 11510 Puerto Real, Cadiz (Spain); Ben, T [Departamento de Ciencia de los Materiales e I.M. y Q.I., Facultad de Ciencias, Universidad de Cadiz, Campus RIo San Pedro, s/n, 11510 Puerto Real, Cadiz (Spain); Sales, D L [Departamento de Ciencia de los Materiales e I.M. y Q.I., Facultad de Ciencias, Universidad de Cadiz, Campus RIo San Pedro, s/n, 11510 Puerto Real, Cadiz (Spain); Pizarro, J [Departamento de Lenguajes y Sistemas Informaticos, CASEM, Universidad de Cadiz, Campus RIo San Pedro, s/n, 11510 Puerto Real, Cadiz (Spain); Galindo, P L [Departamento de Lenguajes y Sistemas Informaticos, CASEM, Universidad de Cadiz, Campus RIo San Pedro, s/n, 11510 Puerto Real, Cadiz (Spain); Varela, M [Condensed Matter Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States); Pennycook, S J [Condensed Matter Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States); Fuster, D [Instituto de Microelectronica de Madrid (CNM, CSIC), Isaac Newton 8, 28760 Tres Cantos, Madrid (Spain); Gonzalez, Y [Instituto de Microelectronica de Madrid (CNM, CSIC), Isaac Newton 8, 28760 Tres Cantos, Madrid (Spain); Gonzalez, L [Instituto de Microelectronica de Madrid (CNM, CSIC), Isaac Newton 8, 28760 Tres Cantos, Madrid (Spain)

    2006-11-28

    The compositional distribution in a self-assembled InAs(P) quantum wire grown by molecular beam epitaxy on an InP(001) substrate has been determined by electron energy loss spectrum imaging. We have determined the strain and stress fields generated in and around this wire capped with a 5 nm InP layer by finite element calculations using as input the compositional map experimentally obtained. Preferential sites for nucleation of wires grown on the surface of this InP capping layer are predicted, based on chemical potential minimization, from the determined strain and stress fields on this surface. The determined preferential sites for wire nucleation agree with their experimentally measured locations. The method used in this paper, which combines electron energy loss spectroscopy, high-resolution Z contrast imaging, and elastic theory finite element calculations, is believed to be a valuable technique of wide applicability for predicting the preferential nucleation sites of epitaxial self-assembled nano-objects.

  11. Single-nucleotide mutation matrix: a new model for predicting the NF-κB DNA binding sites.

    Directory of Open Access Journals (Sweden)

    Wenxin Du

    Full Text Available In this study, we established a single nucleotide mutation matrix (SNMM model based on the relative binding affinities of NF-κB p50 homodimer to a wild-type binding site (GGGACTTTCC and its all single-nucleotide mutants detected with the double-stranded DNA microarray. We evaluated this model by scoring different groups of 10-bp DNA sequences with this model and analyzing the correlations between the scores and the relative binding affinities detected with three wet experiments, including the electrophoresis mobility shift assay (EMSA, the protein-binding microarray (PBM and the systematic evolution of ligands by exponential enrichment-sequencing (SELEX-Seq. The results revealed that the SNMM scores were strongly correlated with the detected binding affinities. We also scored the DNA sequences with other three models, including the principal coordinate (PC model, the position weight matrix scoring algorithm (PWMSA model and the Match model, and analyzed the correlations between the scores and the detected binding affinities. In comparison with these models, the SNMM model achieved reliable results. We finally determined 0.747 as the optimal threshold for predicting the NF-κB DNA-binding sites with the SNMM model. The SNMM model thus provides a new alternative model for scoring the relative binding affinities of NF-κB to the 10-bp DNA sequences and predicting the NF-κB DNA-binding sites.

  12. Single-nucleotide mutation matrix: a new model for predicting the NF-κB DNA binding sites.

    Science.gov (United States)

    Du, Wenxin; Gao, Jing; Wang, Tingting; Wang, Jinke

    2014-01-01

    In this study, we established a single nucleotide mutation matrix (SNMM) model based on the relative binding affinities of NF-κB p50 homodimer to a wild-type binding site (GGGACTTTCC) and its all single-nucleotide mutants detected with the double-stranded DNA microarray. We evaluated this model by scoring different groups of 10-bp DNA sequences with this model and analyzing the correlations between the scores and the relative binding affinities detected with three wet experiments, including the electrophoresis mobility shift assay (EMSA), the protein-binding microarray (PBM) and the systematic evolution of ligands by exponential enrichment-sequencing (SELEX-Seq). The results revealed that the SNMM scores were strongly correlated with the detected binding affinities. We also scored the DNA sequences with other three models, including the principal coordinate (PC) model, the position weight matrix scoring algorithm (PWMSA) model and the Match model, and analyzed the correlations between the scores and the detected binding affinities. In comparison with these models, the SNMM model achieved reliable results. We finally determined 0.747 as the optimal threshold for predicting the NF-κB DNA-binding sites with the SNMM model. The SNMM model thus provides a new alternative model for scoring the relative binding affinities of NF-κB to the 10-bp DNA sequences and predicting the NF-κB DNA-binding sites.

  13. Polymorphisms in MicroRNA Binding Sites Predict Colorectal Cancer Survival

    Science.gov (United States)

    Yang, Ying-Pi; Ting, Wen-Chien; Chen, Lu-Min; Lu, Te-Ling; Bao, Bo-Ying

    2017-01-01

    Background: MicroRNAs (miRNAs) mediate negative regulation of target genes through base pairing, and aberrant miRNA expression has been described in cancers. We hypothesized that single nucleotide polymorphisms (SNPs) within miRNA target sites might influence clinical outcomes in patients with colorectal cancer. Methods: Sixteen common SNPs within miRNA target sites were identified, and the association between these SNPs and overall survival was assessed in colorectal cancer patients using Kaplan-Meier analysis, Cox regression model, and survival tree analysis. Results: Survival tree analysis identified a higher-order genetic interaction profile consisting of the RPS6KB1 rs1051424 and ZNF839 rs11704 that was significantly associated with overall survival. The 5-year survival rates were 74.6%, 62.7%, and 57.1% for the low-, medium-, and high-risk genetic profiles, respectively (P = 0.006). The genetic interaction profile remained significant even after adjusting for potential risk factors. Additional in silico analysis provided evidence that rs1051424 and rs11704 affect RPS6KB1 and ZNF839 expressions, which in turn is significantly correlated with prognosis in colorectal cancer. Conclusion: Our results suggest that the genetic interaction profiles among SNPs within miRNA target sites might be prognostic markers for colorectal cancer survival. PMID:28138309

  14. Structural and Kinetic Analyses of Macrophage Migration Inhibitory Factor Active Site Interactions

    Energy Technology Data Exchange (ETDEWEB)

    Crichlow, G.; Lubetsky, J; Leng, L; Bucala, R; Lolis, E

    2009-01-01

    Macrophage migration inhibitory factor (MIF) is a secreted protein expressed in numerous cell types that counters the antiinflammatory effects of glucocorticoids and has been implicated in sepsis, cancer, and certain autoimmune diseases. Interestingly, the structure of MIF contains a catalytic site resembling the tautomerase/isomerase sites of microbial enzymes. While bona fide physiological substrates remain unknown, model substrates have been identified. Selected compounds that bind in the tautomerase active site also inhibit biological functions of MIF. It had previously been shown that the acetaminophen metabolite, N-acetyl-p-benzoquinone imine (NAPQI), covalently binds to the active site of MIF. In this study, kinetic data indicate that NAPQI inhibits MIF both covalently and noncovalently. The structure of MIF cocrystallized with NAPQI reveals that the NAPQI has undergone a chemical alteration forming an acetaminophen dimer (bi-APAP) and binds noncovalently to MIF at the mouth of the active site. We also find that the commonly used protease inhibitor, phenylmethylsulfonyl fluoride (PMSF), forms a covalent complex with MIF and inhibits the tautomerase activity. Crystallographic analysis reveals the formation of a stable, novel covalent bond for PMSF between the catalytic nitrogen of the N-terminal proline and the sulfur of PMSF with complete, well-defined electron density in all three active sites of the MIF homotrimer. Conclusions are drawn from the structures of these two MIF-inhibitor complexes regarding the design of novel compounds that may provide more potent reversible and irreversible inhibition of MIF.

  15. Skin sites to predict deep-body temperature while wearing firefighters' personal protective equipment during periodical changes in air temperature.

    Science.gov (United States)

    Kim, Siyeon; Lee, Joo-Young

    2016-04-01

    The aim of this study was to investigate stable and valid measurement sites of skin temperatures as a non-invasive variable to predict deep-body temperature while wearing firefighters' personal protective equipment (PPE) during air temperature changes. Eight male firefighters participated in an experiment which consisted of 60-min exercise and 10-min recovery while wearing PPE without self-contained breathing apparatus (7.75 kg in total PPE mass). Air temperature was periodically fluctuated from 29.5 to 35.5 °C with an amplitude of 6 °C. Rectal temperature was chosen as a deep-body temperature, and 12 skin temperatures were recorded. The results showed that the forehead and chest were identified as the most valid sites to predict rectal temperature (R(2) = 0.826 and 0.824, respectively) in an environment with periodically fluctuated air temperatures. This study suggests that particular skin temperatures are valid as a non-invasive variable when predicting rectal temperature of an individual wearing PPE in changing ambient temperatures. Practitioner Summary: This study should offer assistance for developing a more reliable indirect indicating system of individual heat strain for firefighters in real time, which can be used practically as a precaution of firefighters' heat-related illness and utilised along with physiological monitoring.

  16. Predictability of PV power grid performance on insular sites without weather stations: use of artificial neural networks

    CERN Document Server

    Voyant, Cyril; Paoli, Christophe; Nivet, Marie Laure; Poggi, Philippe; Haurant, P; 10.4229/24thEUPVSEC2009-5BV.2.35

    2010-01-01

    The official meteorological network is poor on the island of Corsica: only three sites being about 50 km apart are equipped with pyranometers which enable measurements by hourly and daily step. These sites are Ajaccio (41\\degree 55'N and 8\\degree 48'E, seaside), Bastia (42\\degree 33'N, 9\\degree 29'E, seaside) and Corte (42\\degree 30'N, 9\\degree 15'E average altitude of 486 meters). This lack of weather station makes difficult the predictability of PV power grid performance. This work intends to study a methodology which can predict global solar irradiation using data available from another location for daily and hourly horizon. In order to achieve this prediction, we have used Artificial Neural Network which is a popular artificial intelligence technique in the forecasting domain. A simulator has been obtained using data available for the station of Ajaccio that is the only station for which we have a lot of data: 16 years from 1972 to 1987. Then we have tested the efficiency of this simulator in two places w...

  17. Predictive active disturbance rejection control for processes with time delay.

    Science.gov (United States)

    Zheng, Qinling; Gao, Zhiqiang

    2014-07-01

    Active disturbance rejection control (ADRC) has been shown to be an effective tool in dealing with real world problems of dynamic uncertainties, disturbances, nonlinearities, etc. This paper addresses its existing limitations with plants that have a large transport delay. In particular, to overcome the delay, the extended state observer (ESO) in ADRC is modified to form a predictive ADRC, leading to significant improvements in the transient response and stability characteristics, as shown in extensive simulation studies and hardware-in-the-loop tests, as well as in the frequency response analysis. In this research, it is assumed that the amount of delay is approximately known, as is the approximated model of the plant. Even with such uncharacteristic assumptions for ADRC, the proposed method still exhibits significant improvements in both performance and robustness over the existing methods such as the dead-time compensator based on disturbance observer and the Filtered Smith Predictor, in the context of some well-known problems of chemical reactor and boiler control problems.

  18. Traction force dynamics predict gap formation in activated endothelium.

    Science.gov (United States)

    Valent, Erik T; van Nieuw Amerongen, Geerten P; van Hinsbergh, Victor W M; Hordijk, Peter L

    2016-09-10

    In many pathological conditions the endothelium becomes activated and dysfunctional, resulting in hyperpermeability and plasma leakage. No specific therapies are available yet to control endothelial barrier function, which is regulated by inter-endothelial junctions and the generation of acto-myosin-based contractile forces in the context of cell-cell and cell-matrix interactions. However, the spatiotemporal distribution and stimulus-induced reorganization of these integral forces remain largely unknown. Traction force microscopy of human endothelial monolayers was used to visualize contractile forces in resting cells and during thrombin-induced hyperpermeability. Simultaneously, information about endothelial monolayer integrity, adherens junctions and cytoskeletal proteins (F-actin) were captured. This revealed a heterogeneous distribution of traction forces, with nuclear areas showing lower and cell-cell junctions higher traction forces than the whole-monolayer average. Moreover, junctional forces were asymmetrically distributed among neighboring cells. Force vector orientation analysis showed a good correlation with the alignment of F-actin and revealed contractile forces in newly formed filopodia and lamellipodia-like protrusions within the monolayer. Finally, unstable areas, showing high force fluctuations within the monolayer were prone to form inter-endothelial gaps upon stimulation with thrombin. To conclude, contractile traction forces are heterogeneously distributed within endothelial monolayers and force instability, rather than force magnitude, predicts the stimulus-induced formation of intercellular gaps. Copyright © 2016 Elsevier Inc. All rights reserved.

  19. Electrophysiological correlates of competitor activation predict retrieval-induced forgetting.

    Science.gov (United States)

    Hellerstedt, Robin; Johansson, Mikael

    2014-06-01

    The very act of retrieval modifies the accessibility of memory for knowledge and past events and can also cause forgetting. A prominent theory of such retrieval-induced forgetting (RIF) holds that retrieval recruits inhibition to overcome interference from competing memories, rendering these memories inaccessible. The present study tested a fundamental tenet of the inhibitory-control account: The competition-dependence assumption. Event-related potentials (ERPs) were recorded while participants engaged in a competitive retrieval task. Competition levels were manipulated within the retrieval task by varying the cue-item associative strength of competing items. In order to temporally separate ERP correlates of competitor activation and target retrieval, memory was probed with the sequential presentation of 2 cues: A category cue, to reactivate competitors, and a target cue. As predicted by the inhibitory-control account, competitors with strong compared with weak cue-competitor association were more susceptible to forgetting. Furthermore, competition-sensitive ERP modulations, elicited by the category cue, were observed over anterior regions and reflected individual differences in ensuing forgetting. The present study demonstrates ERP correlates of the reactivation of tightly bound associated memories (the competitors) and provides support for the inhibitory-control account of RIF.

  20. Predicting species distributions from checklist data using site-occupancy models

    Science.gov (United States)

    Kery, M.; Gardner, B.; Monnerat, C.

    2010-01-01

    Aim: (1) To increase awareness of the challenges induced by imperfect detection, which is a fundamental issue in species distribution modelling; (2) to emphasize the value of replicate observations for species distribution modelling; and (3) to show how 'cheap' checklist data in faunal/floral databases may be used for the rigorous modelling of distributions by site-occupancy models. Location: Switzerland. Methods: We used checklist data collected by volunteers during 1999 and 2000 to analyse the distribution of the blue hawker, Aeshna cyanea (Odonata, Aeshnidae), a common dragonfly in Switzerland. We used data from repeated visits to 1-ha pixels to derive 'detection histories' and apply site-occupancy models to estimate the 'true' species distribution, i.e. corrected for imperfect detection. We modelled blue hawker distribution as a function of elevation and year and its detection probability of elevation, year and season. Results: The best model contained cubic polynomial elevation effects for distribution and quadratic effects of elevation and season for detectability. We compared the site-occupancy model with a conventional distribution model based on a generalized linear model, which assumes perfect detectability (p = 1). The conventional distribution map looked very different from the distribution map obtained using site-occupancy models that accounted for the imperfect detection. The conventional model underestimated the species distribution by 60%, and the slope parameters of the occurrence-elevation relationship were also underestimated when assuming p = 1. Elevation was not only an important predictor of blue hawker occurrence, but also of the detection probability, with a bell-shaped relationship. Furthermore, detectability increased over the season. The average detection probability was estimated at only 0.19 per survey. Main conclusions: Conventional species distribution models do not model species distributions per se but rather the apparent

  1. Site- and horizon-specific patterns of microbial community structure and enzyme activities in permafrost-affected soils of Greenland.

    Science.gov (United States)

    Gittel, Antje; Bárta, Jiří; Kohoutová, Iva; Schnecker, Jörg; Wild, Birgit; Capek, Petr; Kaiser, Christina; Torsvik, Vigdis L; Richter, Andreas; Schleper, Christa; Urich, Tim

    2014-01-01

    Permafrost-affected soils in the Northern latitudes store huge amounts of organic carbon (OC) that is prone to microbial degradation and subsequent release of greenhouse gasses to the atmosphere. In Greenland, the consequences of permafrost thaw have only recently been addressed, and predictions on its impact on the carbon budget are thus still highly uncertain. However, the fate of OC is not only determined by abiotic factors, but closely tied to microbial activity. We investigated eight soil profiles in northeast Greenland comprising two sites with typical tundra vegetation and one wet fen site. We assessed microbial community structure and diversity (SSU rRNA gene tag sequencing, quantification of bacteria, archaea and fungi), and measured hydrolytic and oxidative enzyme activities. Sampling site and thus abiotic factors had a significant impact on microbial community structure, diversity and activity, the wet fen site exhibiting higher potential enzyme activities and presumably being a hot spot for anaerobic degradation processes such as fermentation and methanogenesis. Lowest fungal to bacterial ratios were found in topsoils that had been relocated by cryoturbation ("buried topsoils"), resulting from a decrease in fungal abundance compared to recent ("unburied") topsoils. Actinobacteria (in particular Intrasporangiaceae) accounted for a major fraction of the microbial community in buried topsoils, but were only of minor abundance in all other soil horizons. It was indicated that the distribution pattern of Actinobacteria and a variety of other bacterial classes was related to the activity of phenol oxidases and peroxidases supporting the hypothesis that bacteria might resume the role of fungi in oxidative enzyme production and degradation of phenolic and other complex substrates in these soils. Our study sheds light on the highly diverse, but poorly-studied communities in permafrost-affected soils in Greenland and their role in OC degradation.

  2. Support vector machines for prediction of protein signal sequences and their cleavage sites.

    Science.gov (United States)

    Cai, Yu-Dong; Lin, Shuo-liang; Chou, Kuo-Chen

    2003-01-01

    Given a nascent protein sequence, how can one predict its signal peptide or "Zipcode" sequence? This is an important problem for scientists to use signal peptides as a vehicle to find new drugs or to reprogram cells for gene therapy (see, e.g. K.C. Chou, Current Protein and Peptide Science 2002;3:615-22). In this paper, support vector machines (SVMs), a new machine learning method, is applied to approach this problem. The overall rate of correct prediction for 1939 secretary proteins and 1440 nonsecretary proteins was over 91%. It has not escaped our attention that the new method may also serve as a useful tool for further investigating many unclear details regarding the molecular mechanism of the ZIP code protein-sorting system in cells. Copyright 2002 Elsevier Science Inc.

  3. Activity after Site-Directed Mutagenesis of CD59 on Complement-Mediated Cytolysis

    Institute of Scientific and Technical Information of China (English)

    Xinhong Zhu; Meihua Gao; Shurong Ren; Qiubo Wang; Cunzhi Lin

    2008-01-01

    CD59 may inhibit the cytolytic activity of complement by binding to C8/C9 and protect host cell membranes against homologous membrane attack complex (MAC). However, CD59 is widely overexpressed on tumor cells,which has been implicated in tumorigenesis. The active site of CD59 relative to MAC is still confused. As reported the MAC binding site is located in the vicinity of a hydrophobic groove on the membrane distal face of the protein centered around residue W40. Here two site-directed mutagenesis were performed by overlapping extension PCR to delete residue W40 site (Mutant 1, M1) or to change C39W40K41 to W39W40W41 (Mutant 2, M2). Then we constructed mutant CD59 eukaryotic expression system and investigated their biological function on CHO cells compared with wild-type CD59. Stable populations of CHO cells expressing recombinant proteins were screened by immunotechnique. After 30 passages culturing, proteins could be tested. Dye release assays suggest that M1CD59 loses the activity against complement, while M2CD59 increases the anti-complement activity slightly.Results indicate that W40 of human CD59 is important to its activity, and prohibition of this site may be a potential way to increase complement activity and to treat tumors.

  4. Use of Prediction Markets to Forecast Infectious Disease Activity

    National Research Council Canada - National Science Library

    Philip M. Polgreen; Forrest D. Nelson; George R. Neumann

    2007-01-01

    Prediction markets have accurately forecasted the outcomes of a wide range of future events, including sales of computer printers, elections, and the Federal Reserve's decisions about interest rates...

  5. iNitro-Tyr: prediction of nitrotyrosine sites in proteins with general pseudo amino acid composition.

    Directory of Open Access Journals (Sweden)

    Yan Xu

    Full Text Available Nitrotyrosine is one of the post-translational modifications (PTMs in proteins that occurs when their tyrosine residue is nitrated. Compared with healthy people, a remarkably increased level of nitrotyrosine is detected in those suffering from rheumatoid arthritis, septic shock, and coeliac disease. Given an uncharacterized protein sequence that contains many tyrosine residues, which one of them can be nitrated and which one cannot? This is a challenging problem, not only directly related to in-depth understanding the PTM's mechanism but also to the nitrotyrosine-based drug development. Particularly, with the avalanche of protein sequences generated in the postgenomic age, it is highly desired to develop a high throughput tool in this regard. Here, a new predictor called "iNitro-Tyr" was developed by incorporating the position-specific dipeptide propensity into the general pseudo amino acid composition for discriminating the nitrotyrosine sites from non-nitrotyrosine sites in proteins. It was demonstrated via the rigorous jackknife tests that the new predictor not only can yield higher success rate but also is much more stable and less noisy. A web-server for iNitro-Tyr is accessible to the public at http://app.aporc.org/iNitro-Tyr/. For the convenience of most experimental scientists, we have further provided a protocol of step-by-step guide, by which users can easily get their desired results without the need to follow the complicated mathematics that were presented in this paper just for the integrity of its development process. It has not escaped our notice that the approach presented here can be also used to deal with the other PTM sites in proteins.

  6. Surface properties of the Mars Science Laboratory candidate landing sites: characterization from orbit and predictions

    Science.gov (United States)

    Fergason, R.L.; Christensen, P.R.; Golombek, M.P.; Parker, T.J.

    2012-01-01

    This work describes the interpretation of THEMIS-derived thermal inertia data at the Eberswalde, Gale, Holden, and Mawrth Vallis Mars Science Laboratory (MSL) candidate landing sites and determines how thermophysical variations correspond to morphology and, when apparent, mineralogical diversity. At Eberswalde, the proportion of likely unconsolidated material relative to exposed bedrock or highly indurated surfaces controls the thermal inertia of a given region. At Gale, the majority of the landing site region has a moderate thermal inertia (250 to 410 J m-2 K-1 s-1/2), which is likely an indurated surface mixed with unconsolidated materials. The primary difference between higher and moderate thermal inertia surfaces may be due to the amount of mantling material present. Within the mound of stratified material in Gale, layers are distinguished in the thermal inertia data; the MSL rover could be traversing through materials that are both thermophysically and compositionally diverse. The majority of the Holden ellipse has a thermal inertia of 340 to 475 J m-2 K-1 s-1/2 and consists of bed forms with some consolidated material intermixed. Mawrth Vallis has a mean thermal inertia of 310 J m-2 K-1 s-1/2 and a wide variety of materials is present contributing to the moderate thermal inertia surfaces, including a mixture of bedrock, indurated surfaces, bed forms, and unconsolidated fines. Phyllosilicates have been identified at all four candidate landing sites, and these clay-bearing units typically have a similar thermal inertia value (400 to 500 J m-2 K-1 s-1/2), suggesting physical properties that are also similar.

  7. On the nature of Parr functions to predict the most reactive sites along organic polar reactions

    Science.gov (United States)

    Chamorro, Eduardo; Pérez, Patricia; Domingo, Luis R.

    2013-09-01

    Very recently, local electrophilic and nucleophilic “Parr functions” were empirically introduced (L.R. Domingo, P. Pérez, J.A. Saez RSC Adv. 3 (2013) 1486) in order to properly characterize the most reactive sites along polar chemical reactions. This Letter reports a theoretical advance to the new methodology by identifying these quantities with key Fukui descriptors of the spin-polarized density functional theory. Given such framework properly incorporates the treatment of both charge-transfer and spin-polarization, this finding provides a significant insight and substantial step forward within the field of a chemical reactivity theory based on the conceptual framework of density functional theory.

  8. Type 2 diabetes mellitus: phylogenetic motifs for predicting protein functional sites

    Indian Academy of Sciences (India)

    Ashok Sharma; Tanuja Rastogi; Meenakshi Bhartiya; A K Shasany; S P S Khanuja

    2007-08-01

    Diabetes mellitus, commonly referred to as diabetes, is a medical condition associated with abnormally high levels of glucose (or sugar) in the blood. Keeping this view, we demonstrate the phylogenetic motifs (PMs) identification in type 2 diabetes mellitus very likely corresponding to protein functional sites. In this article, we have identified PMs for all the candidate genes for type 2 diabetes mellitus. Glycine 310 remains conserved for glucokinase and potassium channel KCNJ11. Isoleucine 137 was conserved for insulin receptor and regulatory subunit of a phosphorylating enzyme. Whereas residues valine, leucine, methionine were highly conserved for insulin receptor. Occurrence of proline was very high for calpain 10 gene and glucose transporter

  9. Cyanide does more to inhibit heme enzymes, than merely serving as an active-site ligand

    Energy Technology Data Exchange (ETDEWEB)

    Parashar, Abhinav [Center for Biomedical Research, VIT University, Vellore, Tamil Nadu, 632014 India (India); Venkatachalam, Avanthika [REDOx Lab, PSG Institute of Advanced Studies, Avinashi Road, Peelamedu, Coimbatore, Tamil Nadu, 641004 (India); Gideon, Daniel Andrew [Center for Biomedical Research, VIT University, Vellore, Tamil Nadu, 632014 India (India); Manoj, Kelath Murali, E-mail: satyamjayatu@yahoo.com [REDOx Lab, PSG Institute of Advanced Studies, Avinashi Road, Peelamedu, Coimbatore, Tamil Nadu, 641004 (India)

    2014-12-12

    Highlights: • Cyanide (CN) is a well-studied toxic principle, known to inhibit heme-enzymes. • Inhibition is supposed to result from CN binding at the active site as a ligand. • Diverse heme enzymes’ CN inhibition profiles challenge prevailing mechanism. • Poor binding efficiency of CN at low enzyme concentrations and ligand pressures. • CN-based diffusible radicals cause ‘non-productive electron transfers’ (inhibition). - Abstract: The toxicity of cyanide is hitherto attributed to its ability to bind to heme proteins’ active site and thereby inhibit their activity. It is shown herein that the long-held interpretation is inadequate to explain several observations in heme-enzyme reaction systems. Generation of cyanide-based diffusible radicals in heme-enzyme reaction milieu could shunt electron transfers (by non-active site processes), and thus be detrimental to the efficiency of oxidative outcomes.

  10. [Prediction of 137Cs behaviour in the soil-plant system in the territory of Semipalatinsk test site].

    Science.gov (United States)

    Spiridonov, S I; Mukusheva, M K; Gontarenko, I A; Fesenko, S V; Baranov, S A

    2005-01-01

    A mathematical model of 137Cs behaviour in the soil-plant system is presented. The model has been parameterized for the area adjacent to the testing area Ground Zero of the Semipalatinsk Test Site. The model describes the main processes responsible for the changes in 137Cs content in the soil solution and, thereby, dynamics of the radionuclide uptake by vegetation. The results are taken from predictive and retrospective calculations that reflect the dynamics of 137Cs distribution by species in soil after nuclear explosions. The importance of factors governing 137Cs accumulation in plants within the STS area is assessed. The analysis of sensitivity of the output model variable to changes in its parameters revealed that the key soil properties significantly influence the results of prediction of 137Cs content in plants.

  11. Echocardiographic prediction of the site of coronary artery obstruction in acute myocardial infarction.

    Science.gov (United States)

    Pierard, L A; Sprynger, M; Carlier, J

    1987-02-01

    In 49 patients with acute myocardial infarction (AMI), the infarction topography was assessed by cross-sectional echocardiography and the location of coronary artery obstruction were correlated. A ventricular segmentation of 5 right and 16 left ventricular segments was used. The site of coronary obstruction was determined in 45 patients by coronary angiography and by necropsy in 4 patients. The exact location of the obstruction could not be found in 4 patients. The infarct related vessel was the left main artery in 1 patient, the left anterior descending artery (LAD) in 19, the left circumflex in 6 and the right coronary artery in 24. Specific segments were identified for each of the 3 coronary arteries: anteroseptal and anterior segments for LAD, right ventricular segments for the right coronary artery and basal anterolateral segment for the left circumflex. Specific segments (specificity 100%) were also identified for the principal coronary branches: basal anterior for the first anterior descending diagonal (sensitivity 71%), basal anteroseptal for the first septal perforator (83%), middle anterior for the second diagonal (100%), middle anteroseptal for the second septal (89%), basal posteroseptal for a dominant right coronary artery (89%), right ventricular anterolateral segment for the right ventricular marginal branch (83%). Echocardiographic identification of the topography of AMI can be useful in recognizing the infarct-related vessel and identifying the site of coronary artery obstruction.

  12. Conformational Change in the Active Site of Streptococcal Unsaturated Glucuronyl Hydrolase Through Site-Directed Mutagenesis at Asp-115.

    Science.gov (United States)

    Nakamichi, Yusuke; Oiki, Sayoko; Mikami, Bunzo; Murata, Kousaku; Hashimoto, Wataru

    2016-08-01

    Bacterial unsaturated glucuronyl hydrolase (UGL) degrades unsaturated disaccharides generated from mammalian extracellular matrices, glycosaminoglycans, by polysaccharide lyases. Two Asp residues, Asp-115 and Asp-175 of Streptococcus agalactiae UGL (SagUGL), are completely conserved in other bacterial UGLs, one of which (Asp-175 of SagUGL) acts as a general acid and base catalyst. The other Asp (Asp-115 of SagUGL) also affects the enzyme activity, although its role in the enzyme reaction has not been well understood. Here, we show substitution of Asp-115 in SagUGL with Asn caused a conformational change in the active site. Tertiary structures of SagUGL mutants D115N and D115N/K370S with negligible enzyme activity were determined at 2.00 and 1.79 Å resolution, respectively, by X-ray crystallography. The side chain of Asn-115 is drastically shifted in both mutants owing to the interaction with several residues, including Asp-175, by formation of hydrogen bonds. This interaction between Asn-115 and Asp-175 probably prevents the mutants from triggering the enzyme reaction using Asp-175 as an acid catalyst.

  13. Serine-202 is the putative precursor of the active site dehydroalanine of phenylalanine ammonia lyase. Site-directed mutagenesis studies on the enzyme from parsley (Petroselinum crispum L.).

    Science.gov (United States)

    Schuster, B; Rétey, J

    1994-08-01

    To investigate the possible role of serine as a precursor of dehydroalanine at the active site of phenylalanine ammonia lyase, two serines, conserved in all known PAL and histidase sequences, were changed to alanine by site-directed mutagenesis. The resulting mutant genes were subcloned into the expression vector pT7.7 and the gene products were assayed for PAL activity. Mutant PALMutS209A showed the same catalytic property as wild-type PAL, whereas mutant PALMutS202A was devoid of catalytic activity, indicating that serine-202 is the most likely precursor of the active site dehydroalanine.

  14. Sites of regulated phosphorylation that control K-Cl cotransporter activity.

    Science.gov (United States)

    Rinehart, Jesse; Maksimova, Yelena D; Tanis, Jessica E; Stone, Kathryn L; Hodson, Caleb A; Zhang, Junhui; Risinger, Mary; Pan, Weijun; Wu, Dianqing; Colangelo, Christopher M; Forbush, Biff; Joiner, Clinton H; Gulcicek, Erol E; Gallagher, Patrick G; Lifton, Richard P

    2009-08-07

    Modulation of intracellular chloride concentration ([Cl(-)](i)) plays a fundamental role in cell volume regulation and neuronal response to GABA. Cl(-) exit via K-Cl cotransporters (KCCs) is a major determinant of [Cl(-)](I); however, mechanisms governing KCC activities are poorly understood. We identified two sites in KCC3 that are rapidly dephosphorylated in hypotonic conditions in cultured cells and human red blood cells in parallel with increased transport activity. Alanine substitutions at these sites result in constitutively active cotransport. These sites are highly phosphorylated in plasma membrane KCC3 in isotonic conditions, suggesting that dephosphorylation increases KCC3's intrinsic transport activity. Reduction of WNK1 expression via RNA interference reduces phosphorylation at these sites. Homologous sites are phosphorylated in all human KCCs. KCC2 is partially phosphorylated in neonatal mouse brain and dephosphorylated in parallel with KCC2 activation. These findings provide insight into regulation of [Cl(-)](i) and have implications for control of cell volume and neuronal function.

  15. Crystal structure of an avian influenza polymerase PA[subscript N] reveals an endonuclease active site

    Energy Technology Data Exchange (ETDEWEB)

    Yuan, Puwei; Bartlam, Mark; Lou, Zhiyong; Chen, Shoudeng; Zhou, Jie; He, Xiaojing; Lv, Zongyang; Ge, Ruowen; Li, Xuemei; Deng, Tao; Fodor, Ervin; Rao, Zihe; Liu, Yingfang; (NU Sinapore); (Nankai); (Oxford); (Chinese Aca. Sci.); (Tsinghua)

    2009-11-10

    The heterotrimeric influenza virus polymerase, containing the PA, PB1 and PB2 proteins, catalyses viral RNA replication and transcription in the nucleus of infected cells. PB1 holds the polymerase active site and reportedly harbours endonuclease activity, whereas PB2 is responsible for cap binding. The PA amino terminus is understood to be the major functional part of the PA protein and has been implicated in several roles, including endonuclease and protease activities as well as viral RNA/complementary RNA promoter binding. Here we report the 2.2 angstrom (A) crystal structure of the N-terminal 197 residues of PA, termed PA(N), from an avian influenza H5N1 virus. The PA(N) structure has an alpha/beta architecture and reveals a bound magnesium ion coordinated by a motif similar to the (P)DX(N)(D/E)XK motif characteristic of many endonucleases. Structural comparisons and mutagenesis analysis of the motif identified in PA(N) provide further evidence that PA(N) holds an endonuclease active site. Furthermore, functional analysis with in vivo ribonucleoprotein reconstitution and direct in vitro endonuclease assays strongly suggest that PA(N) holds the endonuclease active site and has critical roles in endonuclease activity of the influenza virus polymerase, rather than PB1. The high conservation of this endonuclease active site among influenza strains indicates that PA(N) is an important target for the design of new anti-influenza therapeutics.

  16. Substrate Shuttling Between Active Sites of Uroporphyrinogen Decarboxylase in Not Required to Generate Coproporphyrinogen

    Energy Technology Data Exchange (ETDEWEB)

    Phillips, J.; Warby, C; Whitby, F; Kushner, J; Hill, C

    2009-01-01

    Uroporphyrinogen decarboxylase (URO-D; EC 4.1.1.37), the fifth enzyme of the heme biosynthetic pathway, is required for the production of heme, vitamin B12, siroheme, and chlorophyll precursors. URO-D catalyzes the sequential decarboxylation of four acetate side chains in the pyrrole groups of uroporphyrinogen to produce coproporphyrinogen. URO-D is a stable homodimer, with the active-site clefts of the two subunits adjacent to each other. It has been hypothesized that the two catalytic centers interact functionally, perhaps by shuttling of reaction intermediates between subunits. We tested this hypothesis by construction of a single-chain protein (single-chain URO-D) in which the two subunits were connected by a flexible linker. The crystal structure of this protein was shown to be superimposable with wild-type activity and to have comparable catalytic activity. Mutations that impaired one or the other of the two active sites of single-chain URO-D resulted in approximately half of wild-type activity. The distributions of reaction intermediates were the same for mutant and wild-type sequences and were unaltered in a competition experiment using I and III isomer substrates. These observations indicate that communication between active sites is not required for enzyme function and suggest that the dimeric structure of URO-D is required to achieve conformational stability and to create a large active-site cleft.

  17. Residents’ Environmental Conservation Behaviors at Tourist Sites: Broadening the Norm Activation Framework by Adopting Environment Attachment

    OpenAIRE

    Yuling Zhang; Jie Zhang; Yuyao Ye; Qitao Wu; Lixia Jin; Hongou Zhang

    2016-01-01

    Understanding the factors that affect residents’ environmental conservation behaviors help in managing the environment of tourist sites. This research provides an integrative understanding of how residents near tourist sites form their environmental conservation behaviors by merging the norm-activation model and cognitive-affective model into one theoretical framework. Results of the structural analysis from a sample of 642 residents showed that this study’s proposed composite model includes ...

  18. Geospatial evaluation of lead bioaccessibility and distribution for site specific prediction of threshold limits.

    Science.gov (United States)

    Bower, Jennifer A; Lister, Sydney; Hazebrouck, Garrett; Perdrial, Nicolas

    2017-10-01

    Recent work identified the need for site-specific Pb bioaccessibility evaluation and scaled contaminant modeling. Pb heterogeneity has made bioaccessibility characterization difficult, and complicated distribution models. Using field testing, bioaccessibility measurement, Integrated Exposure Uptake and Biokinetic (IEUBK) modeling, and geospatial techniques, we propose a framework for conducting applied risk-based, multiscale assessment. This framework was tested and implemented in Burlington, VT, an area of old housing stock and high Pb burden (up to 15 000 mg kg(-1)) derived primarily from paint. After analyzing local soil samples for total and bioaccessible Pb, it was determined that bioaccessible and total Pb were well correlated in this area, through which an average bioaccessibility parameter was derived approximating Pb bioaccessibility for this soil type and Pb impact. This parameter was used with the IEUBK to recommend the local limit for residential soil Pb be reduced from 400 to 360 mg kg(-1), taking into consideration the lowering of the blood lead level threshold for Pb poisoning from 10 to 5 μg dL(-1) by the Centers for Disease Control (CDC). Geospatial investigation incorporated samples collected during this investigation and samples from a high school summer science academy, and relied on three techniques, used at different scales: kriging of total and background Pb alone, kriging of total and background Pb with housing age as a well-sampled, well-correlated secondary variable (cokriging), and inverse distance weighting of total and bioaccessible Pb. Modeling at different scales allowed for characterization of Pb impact at single sites as well as citywide. Model maps show positive correlation between areas of older housing and areas of high Pb burden, as well as potential at different scales for reducing the effects of Pb heterogeneity. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. Understanding Land-Atmosphere Coupling and its Predictability at the ARM Southern Great Plains Site

    Science.gov (United States)

    Ferguson, C. R.; Song, H. J.; Roundy, J. K.

    2015-12-01

    Ten years ago, the Global Energy and Water EXchanges Global Land Atmosphere Coupling Experiment (GLACE) spotlighted the Southern Great Plains (SGP) for being one of three hotspots globally for land-derived precipitation predictability. Since then, the GLACE results have served as the underlying motivation for numerous subsequent land-atmosphere (L-A) coupling studies over the SGP domain. The range of these studies includes: local point scale studies leveraging surface meteorological and flux measurements at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement SGP (ARM-SGP) Central Facility, regional pentad to monthly scale atmospheric moisture budget analyses based on atmospheric reanalysis, and regional limited duration (2-7 day) coupled model sensitivity experiments. This study has the following three objectives: (1) to provide the common historical context necessary for bridging past and future interdisciplinary characterizations of L-A coupling, (2) to isolate the mechanism(s) for the region's L-A coupling signal, and (3) to evaluate the short range (12-18hr) predictability of soil moisture-precipitation feedbacks. We produce a convective triggering potential—low-level humidity index (CTP-HI)—based climatology of L-A coupling at ARM-SGP for the period 1979-2014 using North American Regional Reanalysis and North American Land Data Assimilation System Phase 2 data. We link the underlying coupling regime classification timeseries to corresponding synoptic-mesoscale weather patterns and bulk atmospheric moisture budget analyses. On the whole, the region's precipitation variability is largely dependent on large-scale moisture transport and the role of the land is nominal. However, we show that surface sensible heat flux can play an important role in modulating diurnal precipitation cycle phase and amplitude—either directly (enhancing CTP) in water-limited conditions or indirectly (increasing HI) in energy-limited conditions. In fact, both 0700

  20. Modified Active Site Coordination in a Clinical Mutant of Sulfite Oxidase

    Energy Technology Data Exchange (ETDEWEB)

    Doonan, C.J.; Wilson, H.L.; Rajagopalan, K.V.; Garrett, R.M.; Bennett, B.; Prince, R.C.; George, G.N.

    2009-06-02

    The molybdenum site of the Arginine 160 {yields} Glutamine clinical mutant of the physiologically vital enzyme sulfite oxidase has been investigated by a combination of X-ray absorption spectroscopy and density functional theory calculations. We conclude that the mutant enzyme has a six-coordinate pseudo-octahedral active site with coordination of Glutamine O{sup {epsilon}} to molybdenum. This contrasts with the wild-type enzyme which is five-coordinate with approximately square-based pyramidal geometry. This difference in the structure of the molybdenum site explains many of the properties of the mutant enzyme which have previously been reported.

  1. AthMethPre: a web server for the prediction and query of mRNA m(6)A sites in Arabidopsis thaliana.

    Science.gov (United States)

    Xiang, Shunian; Yan, Zhangming; Liu, Ke; Zhang, Yaou; Sun, Zhirong

    2016-10-18

    N(6)-Methyladenosine (m(6)A) is the most prevalent and abundant modification in mRNA that has been linked to many key biological processes. High-throughput experiments have generated m(6)A-peaks across the transcriptome of A. thaliana, but the specific methylated sites were not assigned, which impedes the understanding of m(6)A functions in plants. Therefore, computational prediction of mRNA m(6)A sites becomes emergently important. Here, we present a method to predict the m(6)A sites for A. thaliana mRNA sequence(s). To predict the m(6)A sites of an mRNA sequence, we employed the support vector machine to build a classifier using the features of the positional flanking nucleotide sequence and position-independent k-mer nucleotide spectrum. Our method achieved good performance and was applied to a web server to provide service for the prediction of A. thaliana m(6)A sites. The server also provides a comprehensive database of predicted transcriptome-wide m(6)A sites and curated m(6)A-seq peaks from the literature for query and visualization. The AthMethPre web server is the first web server that provides a user-friendly tool for the prediction and query of A. thaliana mRNA m(6)A sites, which is freely accessible for public use at .

  2. Impact Assessment of Mikania Micrantha on Land Cover and Maxent Modeling to Predict its Potential Invasion Sites

    Science.gov (United States)

    Baidar, T.; Shrestha, A. B.; Ranjit, R.; Adhikari, R.; Ghimire, S.; Shrestha, N.

    2017-05-01

    Mikania micrantha is one of the major invasive alien plant species in tropical moist forest regions of Asia including Nepal. Recently, this weed is spreading at an alarming rate in Chitwan National Park (CNP) and threatening biodiversity. This paper aims to assess the impacts of Mikania micrantha on different land cover and to predict potential invasion sites in CNP using Maxent model. Primary data for this were presence point coordinates and perceived Mikania micrantha cover collected through systematic random sampling technique. Rapideye image, Shuttle Radar Topographic Mission data and bioclimatic variables were acquired as secondary data. Mikania micrantha distribution maps were prepared by overlaying the presence points on image classified by object based image analysis. The overall accuracy of classification was 90 % with Kappa coefficient 0.848. A table depicting the number of sample points in each land cover with respective Mikania micrantha coverage was extracted from the distribution maps to show the impact. The riverine forest was found to be the most affected land cover with 85.98 % presence points and sal forest was found to be very less affected with only 17.02 % presence points. Maxent modeling predicted the areas near the river valley as the potential invasion sites with statistically significant Area Under the Receiver Operating Curve (AUC) value of 0.969. Maximum temperature of warmest month and annual precipitation were identified as the predictor variables that contribute the most to Mikania micrantha's potential distribution.

  3. Computational Characterization and Prediction of Estrogen Receptor Coactivator Binding Site Inhibitors

    Science.gov (United States)

    2005-09-01

    Wormke, andS. Safe. 1997. Inhibition of estrogen-induced activity by 2,3,7,8- tetrachlorodibenzo-p- dioxin (TCDD) in the MCF-7 human breast cancer and...proliferation bioassay (E-Screen). Biomarkers 7(4):322-336. Reel, J.R., J.C.V. Lamb, andB.H. Neal. 1996. Survey and assessment of mammalian estrogen

  4. Computational Characterization and Prediction of Estrogen Receptor Coactivator Binding Site Inhibitors

    Energy Technology Data Exchange (ETDEWEB)

    Bennion, B J; Kulp, K S; Cosman, M; Lightstone, F C

    2005-08-26

    Many carcinogens have been shown to cause tissue specific tumors in animal models. The mechanism for this specificity has not been fully elucidated and is usually attributed to differences in organ metabolism. For heterocyclic amines, potent carcinogens that are formed in well-done meat, the ability to either bind to the estrogen receptor and activate or inhibit an estrogenic response will have a major impact on carcinogenicity. Here we describe our work with the human estrogen receptor alpha (hERa) and the mutagenic/carcinogenic heterocyclic amines PhIP, MeIQx, IFP, and the hydroxylated metabolite of PhIP, N2-hydroxy-PhIP. We found that PhIP, in contrast to the other heterocyclic amines, increased cell-proliferation in MCF-7 human breast cancer cells and activated the hERa receptor. We show mechanistic data supporting this activation both computationally by homology modeling and docking, and by NMR confirmation that PhIP binds with the ligand binding domain (LBD). This binding competes with estradiol (E2) in the native E2 binding cavity of the receptor. We also find that other heterocyclic amines and N2-hydroxy-PhIP inhibit ER activation presumably by binding into another cavity on the LBD. Moreover, molecular dynamics simulations of inhibitory heterocyclic amines reveal a disruption of the surface of the receptor protein involved with protein-protein signaling. We therefore propose that the mechanism for the tissue specific carcinogenicity seen in the rat breast tumors and the presumptive human breast cancer associated with the consumption of well-done meat maybe mediated by this receptor activation.

  5. Solvent Tuning of Electrochemical Potentials in the Active Sites of HiPIP Versus Ferredoxin

    Energy Technology Data Exchange (ETDEWEB)

    Dey, A.; Francis, E.J.; Adams, M.W.W.; Babini, E.; Takahashi, Y.; Fukuyama, K.; Hodgson, K.O.; Hedman, B.; Solomon, E.I.; /Stanford U., Chem. Dept. /Georgia U. /Bologna U. /Osaka U. /SLAC, SSRL

    2009-04-29

    A persistent puzzle in the field of biological electron transfer is the conserved iron-sulfur cluster motif in both high potential iron-sulfur protein (HiPIP) and ferredoxin (Fd) active sites. Despite this structural similarity, HiPIPs react oxidatively at physiological potentials, whereas Fds are reduced. Sulfur K-edge x-ray absorption spectroscopy uncovers the substantial influence of hydration on this variation in reactivity. Fe-S covalency is much lower in natively hydrated Fd active sites than in HiPIPs but increases upon water removal; similarly, HiPIP covalency decreases when unfolding exposes an otherwise hydrophobically shielded active site to water. Studies on model compounds and accompanying density functional theory calculations support a correlation of Fe-S covalency with ease of oxidation and therefore suggest that hydration accounts for most of the difference between Fd and HiPIP reduction potentials.

  6. Evolution of anatase surface active sites probed by in situ sum-frequency phonon spectroscopy.

    Science.gov (United States)

    Cao, Yue; Chen, Shiyou; Li, Yadong; Gao, Yi; Yang, Deheng; Shen, Yuen Ron; Liu, Wei-Tao

    2016-09-01

    Surface active sites of crystals often govern their relevant surface chemistry, yet to monitor them in situ in real atmosphere remains a challenge. Using surface-specific sum-frequency spectroscopy, we identified the surface phonon mode associated with the active sites of undercoordinated titanium ions and conjoint oxygen vacancies, and used it to monitor them on anatase (TiO2) (101) under ambient conditions. In conjunction with theory, we determined related surface structure around the active sites and tracked the evolution of oxygen vacancies under ultraviolet irradiation. We further found that unlike in vacuum, the surface oxygen vacancies, which dominate the surface reactivity, are strongly regulated by ambient gas molecules, including methanol and water, as well as weakly associated species, such as nitrogen and hydrogen. The result revealed a rich interplay between prevailing ambient species and surface reactivity, which can be omnipresent in environmental and catalytic applications of titanium dioxides.

  7. Quantum delocalization of protons in the hydrogen bond network of an enzyme active site

    CERN Document Server

    Wang, Lu; Boxer, Steven G; Markland, Thomas E

    2015-01-01

    Enzymes utilize protein architectures to create highly specialized structural motifs that can greatly enhance the rates of complex chemical transformations. Here we use experiments, combined with ab initio simulations that exactly include nuclear quantum effects, to show that a triad of strongly hydrogen bonded tyrosine residues within the active site of the enzyme ketosteroid isomerase (KSI) facilitates quantum proton delocalization. This delocalization dramatically stabilizes the deprotonation of an active site tyrosine residue, resulting in a very large isotope effect on its acidity. When an intermediate analog is docked, it is incorporated into the hydrogen bond network, giving rise to extended quantum proton delocalization in the active site. These results shed light on the role of nuclear quantum effects in the hydrogen bond network that stabilizes the reactive intermediate of KSI, and the behavior of protons in biological systems containing strong hydrogen bonds.

  8. Improving the neutral phytase activity from Bacillus amyloliquefaciens DSM 1061 by site-directed mutagenesis.

    Science.gov (United States)

    Xu, Wei; Shao, Rong; Wang, Zupeng; Yan, Xiuhua

    2015-03-01

    Neutral phytase is used as a feed additive for degradation of anti-nutritional phytate in aquatic feed industry. Site-directed mutagenesis of Bacillus amyloliquefaciens DSM 1061 phytase was performed with an aim to increase its activity. Mutation residues were chosen based on multiple sequence alignments and structure analysis of neutral phytsaes from different microorganisms. The mutation sites on surface (D148E, S197E and N156E) and around the active site (D52E) of phytase were selected. Analysis of the phytase variants showed that the specific activities of mutants D148E and S197E remarkably increased by about 35 and 13% over a temperature range of 40-75 °C at pH 7.0, respectively. The k cat of mutants D148E and S197E were 1.50 and 1.25 times than that of the wild-type phytase, respectively. Both D148E and S197E showed much higher thermostability than that of the wild-type phytase. However, mutants N156E and D52E led to significant loss of specific activity of the enzyme. Structural analysis revealed that these mutations may affect conformation of the active site of phytase. The present mutant phytases D148E and S197E with increased activities and thermostabilities have application potential as additives in aquaculture feed.

  9. Stringency of the 2-His-1-Asp active-site motif in prolyl 4-hydroxylase.

    Directory of Open Access Journals (Sweden)

    Kelly L Gorres

    Full Text Available The non-heme iron(II dioxygenase family of enzymes contain a common 2-His-1-carboxylate iron-binding motif. These enzymes catalyze a wide variety of oxidative reactions, such as the hydroxylation of aliphatic C-H bonds. Prolyl 4-hydroxylase (P4H is an alpha-ketoglutarate-dependent iron(II dioxygenase that catalyzes the post-translational hydroxylation of proline residues in protocollagen strands, stabilizing the ensuing triple helix. Human P4H residues His412, Asp414, and His483 have been identified as an iron-coordinating 2-His-1-carboxylate motif. Enzymes that catalyze oxidative halogenation do so by a mechanism similar to that of P4H. These halogenases retain the active-site histidine residues, but the carboxylate ligand is replaced with a halide ion. We replaced Asp414 of P4H with alanine (to mimic the active site of a halogenase and with glycine. These substitutions do not, however, convert P4H into a halogenase. Moreover, the hydroxylase activity of D414A P4H cannot be rescued with small molecules. In addition, rearranging the two His and one Asp residues in the active site eliminates hydroxylase activity. Our results demonstrate a high stringency for the iron-binding residues in the P4H active site. We conclude that P4H, which catalyzes an especially demanding chemical transformation, is recalcitrant to change.

  10. Fragment-based identification of determinants of conformational and spectroscopic change at the ricin active site

    Directory of Open Access Journals (Sweden)

    Soares Alexei S

    2007-11-01

    Full Text Available Abstract Background Ricin is a potent toxin and known bioterrorism threat with no available antidote. The ricin A-chain (RTA acts enzymatically to cleave a specific adenine base from ribosomal RNA, thereby blocking translation. To understand better the relationship between ligand binding and RTA active site conformational change, we used a fragment-based approach to find a minimal set of bonding interactions able to induce rearrangements in critical side-chain positions. Results We found that the smallest ligand stabilizing an open conformer of the RTA active site pocket was an amide group, bound weakly by only a few hydrogen bonds to the protein. Complexes with small amide-containing molecules also revealed a switch in geometry from a parallel towards a splayed arrangement of an arginine-tryptophan cation-pi interaction that was associated with an increase and red-shift in tryptophan fluorescence upon ligand binding. Using the observed fluorescence signal, we determined the thermodynamic changes of adenine binding to the RTA active site, as well as the site-specific binding of urea. Urea binding had a favorable enthalpy change and unfavorable entropy change, with a ΔH of -13 ± 2 kJ/mol and a ΔS of -0.04 ± 0.01 kJ/(K*mol. The side-chain position of residue Tyr80 in a complex with adenine was found not to involve as large an overlap of rings with the purine as previously considered, suggesting a smaller role for aromatic stacking at the RTA active site. Conclusion We found that amide ligands can bind weakly but specifically to the ricin active site, producing significant shifts in positions of the critical active site residues Arg180 and Tyr80. These results indicate that fragment-based drug discovery methods are capable of identifying minimal bonding determinants of active-site side-chain rearrangements and the mechanistic origins of spectroscopic shifts. Our results suggest that tryptophan fluorescence provides a sensitive probe for the

  11. Threatened and endangered wildlife species of the Hanford Site related to CERCLA characterization activities

    Energy Technology Data Exchange (ETDEWEB)

    Fitzner, R.E. [Pacific Northwest Lab., Richland, WA (United States); Weiss, S.G.; Stegen, J.A. [Westinghouse Hanford Co., Richland, WA (United States)

    1994-06-01

    The US Department of Energy`s (DOE) Hanford Site has been placed on the National Priorities List, which requires that it be remediated under the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) or Superfund. Potentially contaminated areas of the Hanford Site were grouped into operable units, and detailed characterization and investigation plans were formulated. The DOE Richland Operations Office requested Westinghouse Hanford Company (WHC) to conduct a biological assessment of the potential impact of these characterization activities on the threatened, endangered, and sensitive wildlife species of the Hanford Site. Additional direction for WHC compliances with wildlife protection can be found in the Environmental Compliance Manual. This document is intended to meet these requirements, in part, for the CERCLA characterization activities, as well as for other work comparable in scope. This report documents the biological assessment and describes the pertinent components of the Hanford Site as well as the planned characterization activities. Also provided are accounts of endangered, threatened, and federal candidate wildlife species on the Hanford Site and information as to how human disturbances can affect these species. Potential effects of the characterization activities are described with recommendations for mitigation measures.

  12. Deletion of loop fragment adjacent to active site diminishes the stability and activity of exo-inulinase.

    Science.gov (United States)

    Arjomand, Maryam Rezaei; Habibi-Rezaei, Mehran; Ahmadian, Gholamreza; Hassanzadeh, Malihe; Karkhane, Ali Asghar; Asadifar, Mandana; Amanlou, Massoud

    2016-11-01

    Inulinases are classified as hydrolases and widely used in the food and medical industries. Here, we report the deletion of a six-membered adjacent active site loop fragment ((74)YGSDVT(79) sequence) from third Ω-loop of the exo-inulinase containing aspartate residue from Aspergillus niger to study its structural and functional importance. Site-directed mutagenesis was used to create the mutant of the exo-inulinase (Δ6SL). To investigate the stability of the region spanning this loop, MD simulations were performed 80ns for 20-85 residues. Molecular docking was performed to compare the interactions in the active sites of enzymes with fructose as a ligand. Accordingly, the functional thermostability of the exo-inulinase was significantly decreased upon loop fragment deletion. Evaluation of the kinetics parameters (Vmax, Km, kcat and, kcat/Km) and activation energy (Ea) of the catalysis of enzymes indicated the importance of the deleted sequence on the catalytic performance of the enzyme. In conclusion, six-membered adjacent active site loop fragment not only plays a crucial role in the stability of the enzyme, but also it involves in the enzyme catalysis through lowering the activation energy of the catalysis and effective improving the catalytic performance. Copyright © 2016. Published by Elsevier B.V.

  13. The active site of low-temperature methane hydroxylation in iron-containing zeolites

    Science.gov (United States)

    Snyder, Benjamin E. R.; Vanelderen, Pieter; Bols, Max L.; Hallaert, Simon D.; Böttger, Lars H.; Ungur, Liviu; Pierloot, Kristine; Schoonheydt, Robert A.; Sels, Bert F.; Solomon, Edward I.

    2016-08-01

    An efficient catalytic process for converting methane into methanol could have far-reaching economic implications. Iron-containing zeolites (microporous aluminosilicate minerals) are noteworthy in this regard, having an outstanding ability to hydroxylate methane rapidly at room temperature to form methanol. Reactivity occurs at an extra-lattice active site called α-Fe(II), which is activated by nitrous oxide to form the reactive intermediate α-O; however, despite nearly three decades of research, the nature of the active site and the factors determining its exceptional reactivity are unclear. The main difficulty is that the reactive species—α-Fe(II) and α-O—are challenging to probe spectroscopically: data from bulk techniques such as X-ray absorption spectroscopy and magnetic susceptibility are complicated by contributions from inactive ‘spectator’ iron. Here we show that a site-selective spectroscopic method regularly used in bioinorganic chemistry can overcome this problem. Magnetic circular dichroism reveals α-Fe(II) to be a mononuclear, high-spin, square planar Fe(II) site, while the reactive intermediate, α-O, is a mononuclear, high-spin Fe(IV)=O species, whose exceptional reactivity derives from a constrained coordination geometry enforced by the zeolite lattice. These findings illustrate the value of our approach to exploring active sites in heterogeneous systems. The results also suggest that using matrix constraints to activate metal sites for function—producing what is known in the context of metalloenzymes as an ‘entatic’ state—might be a useful way to tune the activity of heterogeneous catalysts.

  14. Parameter estimation method and updating of regional prediction equations for ungaged sites in the desert region of California

    Science.gov (United States)

    Barth, Nancy A.; Veilleux, Andrea G.

    2012-01-01

    The U.S. Geological Survey (USGS) is currently updating at-site flood frequency estimates for USGS streamflow-gaging stations in the desert region of California. The at-site flood-frequency analysis is complicated by short record lengths (less than 20 years is common) and numerous zero flows/low outliers at many sites. Estimates of the three parameters (mean, standard deviation, and skew) required for fitting the log Pearson Type 3 (LP3) distribution are likely to be highly unreliable based on the limited and heavily censored at-site data. In a generalization of the recommendations in Bulletin 17B, a regional analysis was used to develop regional estimates of all three parameters (mean, standard deviation, and skew) of the LP3 distribution. A regional skew value of zero from a previously published report was used with a new estimated mean squared error (MSE) of 0.20. A weighted least squares (WLS) regression method was used to develop both a regional standard deviation and a mean model based on annual peak-discharge data for 33 USGS stations throughout California’s desert region. At-site standard deviation and mean values were determined by using an expected moments algorithm (EMA) method for fitting the LP3 distribution to the logarithms of annual peak-discharge data. Additionally, a multiple Grubbs-Beck (MGB) test, a generalization of the test recommended in Bulletin 17B, was used for detecting multiple potentially influential low outliers in a flood series. The WLS regression found that no basin characteristics could explain the variability of standard deviation. Consequently, a constant regional standard deviation model was selected, resulting in a log-space value of 0.91 with a MSE of 0.03 log units. Yet drainage area was found to be statistically significant at explaining the site-to-site variability in mean. The linear WLS regional mean model based on drainage area had a Pseudo- 2 R of 51 percent and a MSE of 0.32 log units. The regional parameter

  15. Directed Hierarchical Patterning of Polycarbonate Bisphenol A Glass Surface along Predictable Sites

    Directory of Open Access Journals (Sweden)

    Mazen Khaled

    2015-01-01

    Full Text Available This paper reports a new approach in designing textured and hierarchical surfaces on polycarbonate bisphenol A type glass to improve hydrophobicity and dust repellent application for solar panels. Solvent- and vapor-induced crystallization of thermoplastic glass polycarbonate bisphenol A (PC is carried out to create hierarchically structured surfaces. In this approach dichloromethane (DCM and acetone are used in sequence. Samples are initially immersed in DCM liquid to generate nanopores, followed by exposing to acetone vapor resulting in the generation of hierarchical structure along the interporous sites. The effects of exposure time on the size, density, and distance of the generated spherules and gaps are studied and correlated with the optical transmittance and contact angle measurements at the surface. At optimized exposure time a contact angle of 98° was achieved with 80% optical transmittance. To further increase the hydrophobicity while maintaining optical properties, the hierarchical surfaces were coated with a transparent composite of tetraethyl orthosilicate as precursor and hexamethyldisilazane as silylation agent resulting in an average contact angle of 135.8° and transmittance of around 70%. FTIR and AFM characterization techniques are employed to study the composition and morphology of the generated surfaces.

  16. In vitro anti-Mycobacterium avium activities of quinolones: predicted active structures and mechanistic considerations.

    Science.gov (United States)

    Klopman, G; Li, J Y; Wang, S; Pearson, A J; Chang, K; Jacobs, M R; Bajaksouzian, S; Ellner, J J

    1994-08-01

    The relationship between the structures of quinolones and their anti-Mycobacterium avium activities has been previously derived by using the Multiple Computer-Automated Structure Evaluation program. A number of substructural constraints required to overcome the resistance of most of the strains have been identified. Nineteen new quinolones which qualify under these substructural requirements were identified by the program and subsequently tested. The results show that the substructural attributes identified by the program produced a successful a priori prediction of the anti-M. avium activities of the new quinolones. All 19 quinolones were found to be active, and 4 of them are as active or better than ciprofloxacin. With these new quinolones, the updated multiple computer-automated structure evaluation program structure-activity relationship analysis has helped to uncover additional information about the nature of the substituents at the C5 and C7 positions needed for optimal inhibitory activity. A possible explanation of drug resistance based on the observation of suicide inactivation of bacterial cytochrome P-450 by the cyclopropylamine moiety has also been proposed and is discussed in this report. Furthermore, we confirm the view that the amount of the uncharged form present in a neutral pH solution plays a crucial role in the drug's penetration ability.

  17. Dopamine transporter comparative molecular modeling and binding site prediction using the LeuT(Aa) leucine transporter as a template.

    Science.gov (United States)

    Indarte, Martín; Madura, Jeffry D; Surratt, Christopher K

    2008-02-15

    Pharmacological and behavioral studies indicate that binding of cocaine and the amphetamines by the dopamine transporter (DAT) protein is principally responsible for initiating the euphoria and addiction associated with these drugs. The lack of an X-ray crystal structure for the DAT or any other member of the neurotransmitter:sodium symporter (NSS) family has hindered understanding of psychostimulant recognition at the atomic level; structural information has been obtained largely from mutagenesis and biophysical studies. The recent publication of a crystal structure for the bacterial leucine transporter LeuT(Aa), a distantly related NSS family homolog, provides for the first time a template for three-dimensional comparative modeling of NSS proteins. A novel computational modeling approach using the capabilities of the Molecular Operating Environment program MOE 2005.06 in conjunction with other comparative modeling servers generated the LeuT(Aa)-directed DAT model. Probable dopamine and amphetamine binding sites were identified within the DAT model using multiple docking approaches. Binding sites for the substrate ligands (dopamine and amphetamine) overlapped substantially with the analogous region of the LeuT(Aa) crystal structure for the substrate leucine. The docking predictions implicated DAT side chains known to be critical for high affinity ligand binding and suggest novel mutagenesis targets in elucidating discrete substrate and inhibitor binding sites. The DAT model may guide DAT ligand QSAR studies, and rational design of novel DAT-binding therapeutics.

  18. Mixed valency and site-preference chemistry for cerium and its compounds: A predictive density-functional theory study

    Energy Technology Data Exchange (ETDEWEB)

    Alam, Aftab [Ames Laboratory; Johnson, Duane D. [Ames Laboratory

    2014-06-01

    Cerium and its technologically relevant compounds are examples of anomalous mixed valency, originating from two competing oxidation states—itinerant Ce4+ and localized Ce3+. Under applied stress, anomalous transitions are observed but not well understood. Here we treat mixed valency as an “alloy” problem involving two valences with competing and numerous site-occupancy configurations. We use density-functional theory with Hubbard U (i.e., DFT+U) to evaluate the effective valence and predict properties, including controlling the valence by pseudoternary alloying. For Ce and its compounds, such as (Ce,La)2(Fe,Co)14B permanent magnets, we find a stable mixed-valent α state near the spectroscopic value of νs=3.53. Ce valency in compounds depends on its steric volume and local chemistry. For La doping, Ce valency shifts towards γ-like Ce3+, as expected from steric volume; for Co doping, valency depends on local Ce-site chemistry and steric volume. Our approach captures the key origins of anomalous valency and site-preference chemistry in complex compounds.

  19. Timing of initial arrival at the breeding site predicts age at first reproduction in a long-lived migratory bird.

    Science.gov (United States)

    Becker, Peter H; Dittmann, Tobias; Ludwigs, Jan-Dieter; Limmer, Bente; Ludwig, Sonja C; Bauch, Christina; Braasch, Alexander; Wendeln, Helmut

    2008-08-26

    In long-lived vertebrates, individuals generally visit potential breeding areas or populations during one or more seasons before reproducing for the first time. During these years of prospecting, they select a future breeding site, colony, or mate and improve various skills and their physical condition to meet the requirements of reproduction. One precondition of successful reproduction is arrival in time on the breeding grounds. Here, we study the intricate links among the date of initial spring arrival, body mass, sex, and the age of first breeding in the common tern Sterna hirundo, a long-lived migratory colonial seabird. The study is based on a unique, individual-based, long-term dataset of sexed birds, marked with transponders, which allow recording their individual arrival, overall attendance, and clutch initiation remotely and automatically year by year over the entire lifetime at the natal colony site. We show that the seasonal date of initial arrival at the breeding grounds predicts the individual age at first reproduction, which mostly occurs years later. Late first-time arrivals remain delayed birds throughout subsequent years. Our findings reveal that timing of arrival at the site of reproduction and timing of reproduction itself are coherent parameters of individual quality, which are linked with the prospects of the breeding career and may have consequences for fitness.

  20. Agenda Trending: Reciprocity and the Predictive Capacity of Social Networking Sites in Intermedia Agenda Setting across Topics over Time

    Directory of Open Access Journals (Sweden)

    Jacob Groshek

    2013-08-01

    Full Text Available In the contemporary converged media environment, agenda setting is being transformed by the dramatic growth of audiences that are simultaneously media users and producers. The study reported here addresses related gaps in the literature by first comparing the topical agendas of two leading traditional media outlets (New York Times and CNN with the most frequently shared stories and trending topics on two widely popular Social Networking Sites (Facebook and Twitter. Time-series analyses of the most prominent topics identify the extent to which traditional media sets the agenda for social media as well as reciprocal agenda-setting effects of social media topics entering traditional media agendas. In addition, this study examines social intermedia agenda setting topically and across time within social networking sites, and in so doing, adds a vital understanding of where traditional media, online uses, and social media content intersect around instances of focusing events, particularly elections. Findings identify core differences between certain traditional and social media agendas, but also within social media agendas that extend from uses examined here. Additional results further suggest important topical and event-oriented limitations upon the predictive capacit of social networking sites to shape traditional media agendas over time.

  1. The Eyes Have It: Hippocampal Activity Predicts Expression of Memory in Eye Movements

    National Research Council Canada - National Science Library

    Hannula, Deborah E; Ranganath, Charan

    2009-01-01

    ...) with concurrent indirect, eye-movement-based memory measures, we obtained evidence that hippocampal activity predicted expressions of relational memory in subsequent patterns of viewing, even when...

  2. Structure prediction and binding sites analysis of curcin protein of Jatropha curcas using computational approaches.

    Science.gov (United States)

    Srivastava, Mugdha; Gupta, Shishir K; Abhilash, P C; Singh, Nandita

    2012-07-01

    Ribosome inactivating proteins (RIPs) are defense proteins in a number of higher-plant species that are directly targeted toward herbivores. Jatropha curcas is one of the biodiesel plants having RIPs. The Jatropha seed meal, after extraction of oil, is rich in curcin, a highly toxic RIP similar to ricin, which makes it unsuitable for animal feed. Although the toxicity of curcin is well documented in the literature, the detailed toxic properties and the 3D structure of curcin has not been determined by X-ray crystallography, NMR spectroscopy or any in silico techniques to date. In this pursuit, the structure of curcin was modeled by a composite approach of 3D structure prediction using threading and ab initio modeling. Assessment of model quality was assessed by methods which include Ramachandran plot analysis and Qmean score estimation. Further, we applied the protein-ligand docking approach to identify the r-RNA binding residue of curcin. The present work provides the first structural insight into the binding mode of r-RNA adenine to the curcin protein and forms the basis for designing future inhibitors of curcin. Cloning of a future peptide inhibitor within J. curcas can produce non-toxic varieties of J. curcas, which would make the seed-cake suitable as animal feed without curcin detoxification.

  3. New active site oriented glyoxyl-agarose derivatives of Escherichia coli penicillin G acylase

    Directory of Open Access Journals (Sweden)

    Terreni Marco

    2007-09-01

    Full Text Available Abstract Background Immobilized Penicillin G Acylase (PGA derivatives are biocatalysts that are industrially used for the hydrolysis of Penicillin G by fermentation and for the kinetically controlled synthesis of semi-synthetic β-lactam antibiotics. One of the most used supports for immobilization is glyoxyl-activated agarose, which binds the protein by reacting through its superficial Lys residues. Since in E. coli PGA Lys are also present near the active site, an immobilization that occurs through these residues may negatively affect the performance of the biocatalyst due to the difficult diffusion of the substrate into the active site. A preferential orientation of the enzyme with the active site far from the support surface would be desirable to avoid this problem. Results Here we report how it is possible to induce a preferential orientation of the protein during the binding process on aldehyde activated supports. A superficial region of PGA, which is located on the opposite side of the active site, is enriched in its Lys content. The binding of the enzyme onto the support is consequently forced through the Lys rich region, thus leaving the active site fully accessible to the substrate. Different mutants with an increasing number of Lys have been designed and, when active, immobilized onto glyoxyl agarose. The synthetic performances of these new catalysts were compared with those of the immobilized wild-type (wt PGA. Our results show that, while the synthetic performance of the wt PGA sensitively decreases after immobilization, the Lys enriched mutants have similar performances to the free enzyme even after immobilization. We also report the observations made with other mutants which were unable to undergo a successful maturation process for the production of active enzymes or which resulted toxic for the host cell. Conclusion The desired orientation of immobilized PGA with the active site freely accessible can be obtained by increasing

  4. Evidence for an Elevated Aspartate pKa in the Active Site of Human Aromatase*

    Science.gov (United States)

    Di Nardo, Giovanna; Breitner, Maximilian; Bandino, Andrea; Ghosh, Debashis; Jennings, Gareth K.; Hackett, John C.; Gilardi, Gianfranco

    2015-01-01

    Aromatase (CYP19A1), the enzyme that converts androgens to estrogens, is of significant mechanistic and therapeutic interest. Crystal structures and computational studies of this enzyme shed light on the critical role of Asp309 in substrate binding and catalysis. These studies predicted an elevated pKa for Asp309 and proposed that protonation of this residue was required for function. In this study, UV-visible absorption, circular dichroism, resonance Raman spectroscopy, and enzyme kinetics were used to study the impact of pH on aromatase structure and androstenedione binding. Spectroscopic studies demonstrate that androstenedione binding is pH-dependent, whereas, in contrast, the D309N mutant retains its ability to bind to androstenedione across the entire pH range studied. Neither pH nor mutation perturbed the secondary structure or heme environment. The origin of the observed pH dependence was further narrowed to the protonation equilibria of Asp309 with a parallel set of spectroscopic studies using exemestane and anastrozole. Because exemestane interacts with Asp309 based on its co-crystal structure with the enzyme, its binding is pH-dependent. Aromatase binding to anastrozole is pH-independent, consistent with the hypothesis that this ligand exploits a distinct set of interactions in the active site. In summary, we assign the apparent pKa of 8.2 observed for androstenedione binding to the side chain of Asp309. To our knowledge, this work represents the first experimental assignment of a pKa value to a residue in a cytochrome P450. This value is in agreement with theoretical calculations (7.7–8.1) despite the reliance of the computational methods on the conformational snapshots provided by crystal structures. PMID:25425647

  5. Stochastic modelling of corrosion damage propagation in active sites from field inspection data

    Energy Technology Data Exchange (ETDEWEB)

    Alamilla, J.L. [Mexican Institute of Petroleum, Eje Central Lazaro Cardenas No. 152, 07730, Mexico DF (Mexico)], E-mail: jalamill@imp.mx; Sosa, E. [Mexican Institute of Petroleum, Eje Central Lazaro Cardenas No. 152, 07730, Mexico DF (Mexico)

    2008-07-15

    A stochastic model for prediction of corrosion damage evolution in active sites, applicable under professional practice conditions is presented here. The damage of a material and its evolution are determined from the damage state at a given time instant and the rate of damage occurrence. To this end, probability density function of the corrosion damage depths of the system is estimated and four models to calculate corrosion damage velocities at localized defects are shown. Their application depends on the amount of inspection reports available. This work takes into account two settings: the first considers that the system has only one inspection report and the second assumes that there are two inspection reports; this latter setting has two variations, the first, when the same defects can be identified at both inspections, and the second, when they are not identifiable. Furthermore, the work introduces a Bayesian model that allows updating corrosion damage velocity on the basis of new measurements found in successive inspection reports. The stochastic model is exemplified by inspection data from a real pipeline system. Its analysis takes into account technical specifications of the system, measured depths of corrosion defects and the number of defects. Additionally, it considers measurement errors during inspection and the variability of corrosion phenomenon under field conditions. Model robustness lies in the fact that corrosion damage estimates are based on measurements reported during inspections. It implicitly considers multiple factors, such as aggressive chemical environment, microstructure composition, operating conditions (temperature, fluid velocity, etc) intervening in the corrosion process, as well as their correlations and variability.

  6. A class of edit kernels for SVMs to predict translation initiation sites in eukaryotic mRNAs.

    Science.gov (United States)

    Li, Haifeng; Jiang, Tao

    2005-01-01

    The prediction of translation initiation sites (TISs) in eukaryotic mRNAs has been a challenging problem in computational molecular biology. In this paper, we present a new algorithm to recognize TISs with a very high accuracy. Our algorithm includes two novel ideas. First, we introduce a class of new sequence-similarity kernels based on string editing, called edit kernels, for use with support vector machines (SVMs) in a discriminative approach to predict TISs. The edit kernels are simple and have significant biological and probabilistic interpretations. Although the edit kernels are not positive definite, it is easy to make the kernel matrix positive definite by adjusting the parameters. Second, we convert the region of an input mRNA sequence downstream to a putative TIS into an amino acid sequence before applying SVMs to avoid the high redundancy in the genetic code. The algorithm has been implemented and tested on previously published data. Our experimental results on real mRNA data show that both ideas improve the prediction accuracy greatly and that our method performs significantly better than those based on neural networks and SVMs with polynomial kernels or Salzberg kernels.

  7. Accurate microRNA target prediction using detailed binding site accessibility and machine learning on proteomics data

    Directory of Open Access Journals (Sweden)

    Martin eReczko

    2012-01-01

    Full Text Available MicroRNAs (miRNAs are a class of small regulatory genes regulating gene ex